From cfc71daf2a8e2c7c65f2b76214bd9f44583195cc Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 6 Mar 2026 08:37:21 -0500 Subject: [PATCH 01/18] initial pyproject.toml implementation --- MANIFEST.in | 5 - pyproject.toml | 105 ++ rdtools/__init__.py | 8 +- rdtools/_version.py | 683 ------------- setup.cfg | 28 - setup.py | 133 --- versioneer.py | 2277 ------------------------------------------- 7 files changed, 111 insertions(+), 3128 deletions(-) delete mode 100644 MANIFEST.in create mode 100644 pyproject.toml delete mode 100644 rdtools/_version.py delete mode 100644 setup.cfg delete mode 100755 setup.py delete mode 100644 versioneer.py diff --git a/MANIFEST.in b/MANIFEST.in deleted file mode 100644 index 4232463ea..000000000 --- a/MANIFEST.in +++ /dev/null @@ -1,5 +0,0 @@ -include versioneer.py -include rdtools/_version.py -include rdtools/data/* -include rdtools/models/* -include LICENSE \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 000000000..4f2817310 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,105 @@ +[build-system] +requires = ["setuptools>=64", "setuptools-scm>=8"] +build-backend = "setuptools.build_meta" + +[project] +name = "rdtools" +dynamic = ["version"] +description = "Functions for reproducible timeseries analysis of photovoltaic systems." +readme = "README.md" +license = {text = "MIT"} +requires-python = ">=3.10" +authors = [ + {name = "Rdtools Python Developers", email = "RdTools@nlr.gov"}, +] +maintainers = [ + {email = "RdTools@nlr.gov"}, +] +keywords = [ + "photovoltaic", + "solar", + "analytics", + "analysis", + "performance", + "degradation", + "PV", +] +classifiers = [ + "Development Status :: 5 - Production/Stable", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + "Intended Audience :: Science/Research", + "Programming Language :: Python", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Topic :: Scientific/Engineering", +] +dependencies = [ + "matplotlib >= 3.5.3", + "numpy >= 1.22.4", + "pandas >= 1.4.4", + "statsmodels >= 0.13.5", + "scipy >= 1.8.1", + "h5py >= 3.7.0", + "plotly >= 4.0.0", + "xgboost >= 1.6.0", + "pvlib >= 0.12.0", + "scikit-learn >= 1.1.3, != 1.6.0", + "arch >= 5.0", + "filterpy >= 1.4.2", +] + +[project.optional-dependencies] +doc = [ + "sphinx==7.4.7", + "nbsphinx==0.9.5", + "nbsphinx-link==1.3.1", + "sphinx_rtd_theme==3.0.1", + "ipython", + "sphinx-gallery==0.18.0", +] +test = [ + "pytest >= 3.10.1", + "pytest-cov", + "coverage", + "flake8", + "nbval >= 0.10.0", + "pytest-mock", +] +all = [ + "coverage", + "flake8", + "ipython", + "nbsphinx==0.9.5", + "nbsphinx-link==1.3.1", + "nbval >= 0.10.0", + "pytest >= 3.10.1", + "pytest-cov", + "pytest-mock", + "sphinx==7.4.7", + "sphinx-gallery==0.18.0", + "sphinx_rtd_theme==3.0.1", +] + +[project.urls] +Homepage = "https://github.com/NREL/rdtools" +"Bug Tracker" = "https://github.com/NREL/rdtools/issues" +Documentation = "https://rdtools.readthedocs.io/" +"Source Code" = "https://github.com/NREL/rdtools" + +[tool.setuptools_scm] + +[tool.setuptools.packages.find] +include = ["rdtools*"] + +[tool.setuptools.package-data] +rdtools = ["data/*", "models/*"] + +[tool.pytest.ini_options] +addopts = "--verbose" +filterwarnings = [ + "ignore:The .* module is currently experimental:UserWarning:rdtools", +] diff --git a/rdtools/__init__.py b/rdtools/__init__.py index 2cd286b00..cdf1d2e6c 100644 --- a/rdtools/__init__.py +++ b/rdtools/__init__.py @@ -40,5 +40,9 @@ from rdtools.utilities import robust_median from rdtools.utilities import robust_mean -from . import _version -__version__ = _version.get_versions()['version'] +from importlib.metadata import version, PackageNotFoundError + +try: + __version__ = version("rdtools") +except PackageNotFoundError: + __version__ = "0+unknown" diff --git a/rdtools/_version.py b/rdtools/_version.py deleted file mode 100644 index 2656d62e8..000000000 --- a/rdtools/_version.py +++ /dev/null @@ -1,683 +0,0 @@ - -# This file helps to compute a version number in source trees obtained from -# git-archive tarball (such as those provided by githubs download-from-tag -# feature). Distribution tarballs (built by setup.py sdist) and build -# directories (produced by setup.py build) will contain a much shorter file -# that just contains the computed version number. - -# This file is released into the public domain. -# Generated by versioneer-0.29 -# https://github.com/python-versioneer/python-versioneer - -"""Git implementation of _version.py.""" - -import errno -import os -import re -import subprocess -import sys -from typing import Any, Callable, Dict, List, Optional, Tuple -import functools - - -def get_keywords() -> Dict[str, str]: - """Get the keywords needed to look up the version information.""" - # these strings will be replaced by git during git-archive. - # setup.py/versioneer.py will grep for the variable names, so they must - # each be defined on a line of their own. _version.py will just call - # get_keywords(). - git_refnames = "$Format:%d$" - git_full = "$Format:%H$" - git_date = "$Format:%ci$" - keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} - return keywords - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - parentdir_prefix: str - versionfile_source: str - verbose: bool - - -def get_config() -> VersioneerConfig: - """Create, populate and return the VersioneerConfig() object.""" - # these strings are filled in when 'setup.py versioneer' creates - # _version.py - cfg = VersioneerConfig() - cfg.VCS = "git" - cfg.style = "pep440" - cfg.tag_prefix = "" - cfg.parentdir_prefix = "rdtools-" - cfg.versionfile_source = "rdtools/_version.py" - cfg.verbose = False - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - if vcs not in HANDLERS: - HANDLERS[vcs] = {} - HANDLERS[vcs][method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %s" % dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %s" % (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %s (error)" % dispcmd) - print("stdout was %s" % stdout) - return None, process.returncode - return stdout, process.returncode - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %s but none started with prefix %s" % - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%s', no digits" % ",".join(refs - tags)) - if verbose: - print("likely tags: %s" % ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %s" % r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %s not under git control" % root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%s'" - % describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%s' doesn't start with prefix '%s'" - print(fmt % (full_tag, tag_prefix)) - pieces["error"] = ("tag '%s' doesn't start with prefix '%s'" - % (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%d.dev%d" % (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%d" % (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%d" % pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%s'" % style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -def get_versions() -> Dict[str, Any]: - """Get version information or return default if unable to do so.""" - # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have - # __file__, we can work backwards from there to the root. Some - # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which - # case we can only use expanded keywords. - - cfg = get_config() - verbose = cfg.verbose - - try: - return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, - verbose) - except NotThisMethod: - pass - - try: - root = os.path.realpath(__file__) - # versionfile_source is the relative path from the top of the source - # tree (where the .git directory might live) to this file. Invert - # this to find the root from __file__. - for _ in cfg.versionfile_source.split('/'): - root = os.path.dirname(root) - except NameError: - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to find root of source tree", - "date": None} - - try: - pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) - return render(pieces, cfg.style) - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - except NotThisMethod: - pass - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to compute version", "date": None} diff --git a/setup.cfg b/setup.cfg deleted file mode 100644 index 36500c527..000000000 --- a/setup.cfg +++ /dev/null @@ -1,28 +0,0 @@ -# See the docstring in versioneer.py for instructions. Note that you must -# re-run 'versioneer.py setup' after changing this section, and commit the -# resulting files. - -[versioneer] -VCS = git -style = pep440 -versionfile_source = rdtools/_version.py -versionfile_build = rdtools/_version.py -tag_prefix = '' -parentdir_prefix = rdtools- - -[metadata] -description-file = README.md - - -[bdist_wheel] -universal = 1 - -[aliases] -test = pytest - -[tool:pytest] -addopts = --verbose -# suppress warnings. syntax is "action:message:category:module:lineno" -# https://docs.python.org/3/library/warnings.html#the-warnings-filter -filterwarnings = - ignore:The .* module is currently experimental:UserWarning:rdtools diff --git a/setup.py b/setup.py deleted file mode 100755 index a4c97a2f6..000000000 --- a/setup.py +++ /dev/null @@ -1,133 +0,0 @@ -#!/usr/bin/env python - -try: - from setuptools import setup -except ImportError: - raise RuntimeError('setuptools is required') - - -import versioneer - - -DESCRIPTION = 'Functions for reproducible timeseries analysis of photovoltaic systems.' - -LONG_DESCRIPTION = """ -RdTools is an open-source library to support reproducible technical analysis of -PV time series data. The library aims to provide best practice analysis -routines along with the building blocks for users to tailor their own analyses. - -Source code: https://github.com/NREL/rdtools -""" - -DISTNAME = 'rdtools' -LICENSE = 'MIT' -AUTHOR = 'Rdtools Python Developers' -AUTHOR_EMAIL = 'RdTools@nrel.gov' -MAINTAINER_EMAIL = 'RdTools@nrel.gov' - -URL = 'https://github.com/NREL/rdtools' - -SETUP_REQUIRES = [ - 'pytest-runner', -] - -TESTS_REQUIRE = [ - "pytest >= 3.10.1", - "pytest-cov", - "coverage", - "flake8", - "nbval>=0.10.0", - "pytest-mock", -] - -INSTALL_REQUIRES = [ - "matplotlib >= 3.5.3", - "numpy >= 1.22.4", - "pandas >= 1.4.4", - "statsmodels >= 0.13.5", - "scipy >= 1.8.1", - "h5py >= 3.7.0", - "plotly>=4.0.0", - "xgboost >= 1.6.0", - "pvlib >= 0.12.0", - "scikit-learn >= 1.1.3, != 1.6.0", - "arch >= 5.0", - "filterpy >= 1.4.2", -] - -EXTRAS_REQUIRE = { - "doc": [ - "sphinx==7.4.7", - "nbsphinx==0.9.5", - "nbsphinx-link==1.3.1", - "sphinx_rtd_theme==3.0.1", - "ipython", - # sphinx-gallery used indirectly for nbsphinx thumbnail galleries; see: - # https://nbsphinx.readthedocs.io/en/0.6.0/subdir/gallery.html#Creating-Thumbnail-Galleries - "sphinx-gallery==0.18.0", - ], - "test": TESTS_REQUIRE, -} -EXTRAS_REQUIRE['all'] = sorted(set(sum(EXTRAS_REQUIRE.values(), []))) - - -CLASSIFIERS = [ - "Development Status :: 5 - Production/Stable", - "License :: OSI Approved :: MIT License", - "Operating System :: OS Independent", - "Intended Audience :: Science/Research", - "Programming Language :: Python", - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", - "Programming Language :: Python :: 3.12", - "Programming Language :: Python :: 3.13", - "Topic :: Scientific/Engineering", -] - -KEYWORDS = [ - 'photovoltaic', - 'solar', - 'analytics', - 'analysis', - 'performance', - 'degradation', - 'PV' -] - -PROJECT_URLS = { - "Bug Tracker": "https://github.com/NREL/rdtools/issues", - "Documentation": "https://rdtools.readthedocs.io/", - "Source Code": "https://github.com/NREL/rdtools", -} - -setuptools_kwargs = { - 'zip_safe': False, - 'scripts': [], - 'include_package_data': True -} - -# set up packages to be installed and extensions to be compiled -PACKAGES = ['rdtools'] - - -setup(name=DISTNAME, - version=versioneer.get_version(), - cmdclass=versioneer.get_cmdclass(), - packages=PACKAGES, - keywords=KEYWORDS, - setup_requires=SETUP_REQUIRES, - tests_require=TESTS_REQUIRE, - install_requires=INSTALL_REQUIRES, - extras_require=EXTRAS_REQUIRE, - description=DESCRIPTION, - long_description=LONG_DESCRIPTION, - author=AUTHOR, - author_email=AUTHOR_EMAIL, - maintainer_email=MAINTAINER_EMAIL, - license=LICENSE, - url=URL, - project_urls=PROJECT_URLS, - classifiers=CLASSIFIERS, - python_requires='>=3.10', - **setuptools_kwargs) diff --git a/versioneer.py b/versioneer.py deleted file mode 100644 index 1e3753e63..000000000 --- a/versioneer.py +++ /dev/null @@ -1,2277 +0,0 @@ - -# Version: 0.29 - -"""The Versioneer - like a rocketeer, but for versions. - -The Versioneer -============== - -* like a rocketeer, but for versions! -* https://github.com/python-versioneer/python-versioneer -* Brian Warner -* License: Public Domain (Unlicense) -* Compatible with: Python 3.7, 3.8, 3.9, 3.10, 3.11 and pypy3 -* [![Latest Version][pypi-image]][pypi-url] -* [![Build Status][travis-image]][travis-url] - -This is a tool for managing a recorded version number in setuptools-based -python projects. The goal is to remove the tedious and error-prone "update -the embedded version string" step from your release process. Making a new -release should be as easy as recording a new tag in your version-control -system, and maybe making new tarballs. - - -## Quick Install - -Versioneer provides two installation modes. The "classic" vendored mode installs -a copy of versioneer into your repository. The experimental build-time dependency mode -is intended to allow you to skip this step and simplify the process of upgrading. - -### Vendored mode - -* `pip install versioneer` to somewhere in your $PATH - * A [conda-forge recipe](https://github.com/conda-forge/versioneer-feedstock) is - available, so you can also use `conda install -c conda-forge versioneer` -* add a `[tool.versioneer]` section to your `pyproject.toml` or a - `[versioneer]` section to your `setup.cfg` (see [Install](INSTALL.md)) - * Note that you will need to add `tomli; python_version < "3.11"` to your - build-time dependencies if you use `pyproject.toml` -* run `versioneer install --vendor` in your source tree, commit the results -* verify version information with `python setup.py version` - -### Build-time dependency mode - -* `pip install versioneer` to somewhere in your $PATH - * A [conda-forge recipe](https://github.com/conda-forge/versioneer-feedstock) is - available, so you can also use `conda install -c conda-forge versioneer` -* add a `[tool.versioneer]` section to your `pyproject.toml` or a - `[versioneer]` section to your `setup.cfg` (see [Install](INSTALL.md)) -* add `versioneer` (with `[toml]` extra, if configuring in `pyproject.toml`) - to the `requires` key of the `build-system` table in `pyproject.toml`: - ```toml - [build-system] - requires = ["setuptools", "versioneer[toml]"] - build-backend = "setuptools.build_meta" - ``` -* run `versioneer install --no-vendor` in your source tree, commit the results -* verify version information with `python setup.py version` - -## Version Identifiers - -Source trees come from a variety of places: - -* a version-control system checkout (mostly used by developers) -* a nightly tarball, produced by build automation -* a snapshot tarball, produced by a web-based VCS browser, like github's - "tarball from tag" feature -* a release tarball, produced by "setup.py sdist", distributed through PyPI - -Within each source tree, the version identifier (either a string or a number, -this tool is format-agnostic) can come from a variety of places: - -* ask the VCS tool itself, e.g. "git describe" (for checkouts), which knows - about recent "tags" and an absolute revision-id -* the name of the directory into which the tarball was unpacked -* an expanded VCS keyword ($Id$, etc) -* a `_version.py` created by some earlier build step - -For released software, the version identifier is closely related to a VCS -tag. Some projects use tag names that include more than just the version -string (e.g. "myproject-1.2" instead of just "1.2"), in which case the tool -needs to strip the tag prefix to extract the version identifier. For -unreleased software (between tags), the version identifier should provide -enough information to help developers recreate the same tree, while also -giving them an idea of roughly how old the tree is (after version 1.2, before -version 1.3). Many VCS systems can report a description that captures this, -for example `git describe --tags --dirty --always` reports things like -"0.7-1-g574ab98-dirty" to indicate that the checkout is one revision past the -0.7 tag, has a unique revision id of "574ab98", and is "dirty" (it has -uncommitted changes). - -The version identifier is used for multiple purposes: - -* to allow the module to self-identify its version: `myproject.__version__` -* to choose a name and prefix for a 'setup.py sdist' tarball - -## Theory of Operation - -Versioneer works by adding a special `_version.py` file into your source -tree, where your `__init__.py` can import it. This `_version.py` knows how to -dynamically ask the VCS tool for version information at import time. - -`_version.py` also contains `$Revision$` markers, and the installation -process marks `_version.py` to have this marker rewritten with a tag name -during the `git archive` command. As a result, generated tarballs will -contain enough information to get the proper version. - -To allow `setup.py` to compute a version too, a `versioneer.py` is added to -the top level of your source tree, next to `setup.py` and the `setup.cfg` -that configures it. This overrides several distutils/setuptools commands to -compute the version when invoked, and changes `setup.py build` and `setup.py -sdist` to replace `_version.py` with a small static file that contains just -the generated version data. - -## Installation - -See [INSTALL.md](./INSTALL.md) for detailed installation instructions. - -## Version-String Flavors - -Code which uses Versioneer can learn about its version string at runtime by -importing `_version` from your main `__init__.py` file and running the -`get_versions()` function. From the "outside" (e.g. in `setup.py`), you can -import the top-level `versioneer.py` and run `get_versions()`. - -Both functions return a dictionary with different flavors of version -information: - -* `['version']`: A condensed version string, rendered using the selected - style. This is the most commonly used value for the project's version - string. The default "pep440" style yields strings like `0.11`, - `0.11+2.g1076c97`, or `0.11+2.g1076c97.dirty`. See the "Styles" section - below for alternative styles. - -* `['full-revisionid']`: detailed revision identifier. For Git, this is the - full SHA1 commit id, e.g. "1076c978a8d3cfc70f408fe5974aa6c092c949ac". - -* `['date']`: Date and time of the latest `HEAD` commit. For Git, it is the - commit date in ISO 8601 format. This will be None if the date is not - available. - -* `['dirty']`: a boolean, True if the tree has uncommitted changes. Note that - this is only accurate if run in a VCS checkout, otherwise it is likely to - be False or None - -* `['error']`: if the version string could not be computed, this will be set - to a string describing the problem, otherwise it will be None. It may be - useful to throw an exception in setup.py if this is set, to avoid e.g. - creating tarballs with a version string of "unknown". - -Some variants are more useful than others. Including `full-revisionid` in a -bug report should allow developers to reconstruct the exact code being tested -(or indicate the presence of local changes that should be shared with the -developers). `version` is suitable for display in an "about" box or a CLI -`--version` output: it can be easily compared against release notes and lists -of bugs fixed in various releases. - -The installer adds the following text to your `__init__.py` to place a basic -version in `YOURPROJECT.__version__`: - - from ._version import get_versions - __version__ = get_versions()['version'] - del get_versions - -## Styles - -The setup.cfg `style=` configuration controls how the VCS information is -rendered into a version string. - -The default style, "pep440", produces a PEP440-compliant string, equal to the -un-prefixed tag name for actual releases, and containing an additional "local -version" section with more detail for in-between builds. For Git, this is -TAG[+DISTANCE.gHEX[.dirty]] , using information from `git describe --tags ---dirty --always`. For example "0.11+2.g1076c97.dirty" indicates that the -tree is like the "1076c97" commit but has uncommitted changes (".dirty"), and -that this commit is two revisions ("+2") beyond the "0.11" tag. For released -software (exactly equal to a known tag), the identifier will only contain the -stripped tag, e.g. "0.11". - -Other styles are available. See [details.md](details.md) in the Versioneer -source tree for descriptions. - -## Debugging - -Versioneer tries to avoid fatal errors: if something goes wrong, it will tend -to return a version of "0+unknown". To investigate the problem, run `setup.py -version`, which will run the version-lookup code in a verbose mode, and will -display the full contents of `get_versions()` (including the `error` string, -which may help identify what went wrong). - -## Known Limitations - -Some situations are known to cause problems for Versioneer. This details the -most significant ones. More can be found on Github -[issues page](https://github.com/python-versioneer/python-versioneer/issues). - -### Subprojects - -Versioneer has limited support for source trees in which `setup.py` is not in -the root directory (e.g. `setup.py` and `.git/` are *not* siblings). The are -two common reasons why `setup.py` might not be in the root: - -* Source trees which contain multiple subprojects, such as - [Buildbot](https://github.com/buildbot/buildbot), which contains both - "master" and "slave" subprojects, each with their own `setup.py`, - `setup.cfg`, and `tox.ini`. Projects like these produce multiple PyPI - distributions (and upload multiple independently-installable tarballs). -* Source trees whose main purpose is to contain a C library, but which also - provide bindings to Python (and perhaps other languages) in subdirectories. - -Versioneer will look for `.git` in parent directories, and most operations -should get the right version string. However `pip` and `setuptools` have bugs -and implementation details which frequently cause `pip install .` from a -subproject directory to fail to find a correct version string (so it usually -defaults to `0+unknown`). - -`pip install --editable .` should work correctly. `setup.py install` might -work too. - -Pip-8.1.1 is known to have this problem, but hopefully it will get fixed in -some later version. - -[Bug #38](https://github.com/python-versioneer/python-versioneer/issues/38) is tracking -this issue. The discussion in -[PR #61](https://github.com/python-versioneer/python-versioneer/pull/61) describes the -issue from the Versioneer side in more detail. -[pip PR#3176](https://github.com/pypa/pip/pull/3176) and -[pip PR#3615](https://github.com/pypa/pip/pull/3615) contain work to improve -pip to let Versioneer work correctly. - -Versioneer-0.16 and earlier only looked for a `.git` directory next to the -`setup.cfg`, so subprojects were completely unsupported with those releases. - -### Editable installs with setuptools <= 18.5 - -`setup.py develop` and `pip install --editable .` allow you to install a -project into a virtualenv once, then continue editing the source code (and -test) without re-installing after every change. - -"Entry-point scripts" (`setup(entry_points={"console_scripts": ..})`) are a -convenient way to specify executable scripts that should be installed along -with the python package. - -These both work as expected when using modern setuptools. When using -setuptools-18.5 or earlier, however, certain operations will cause -`pkg_resources.DistributionNotFound` errors when running the entrypoint -script, which must be resolved by re-installing the package. This happens -when the install happens with one version, then the egg_info data is -regenerated while a different version is checked out. Many setup.py commands -cause egg_info to be rebuilt (including `sdist`, `wheel`, and installing into -a different virtualenv), so this can be surprising. - -[Bug #83](https://github.com/python-versioneer/python-versioneer/issues/83) describes -this one, but upgrading to a newer version of setuptools should probably -resolve it. - - -## Updating Versioneer - -To upgrade your project to a new release of Versioneer, do the following: - -* install the new Versioneer (`pip install -U versioneer` or equivalent) -* edit `setup.cfg` and `pyproject.toml`, if necessary, - to include any new configuration settings indicated by the release notes. - See [UPGRADING](./UPGRADING.md) for details. -* re-run `versioneer install --[no-]vendor` in your source tree, to replace - `SRC/_version.py` -* commit any changed files - -## Future Directions - -This tool is designed to make it easily extended to other version-control -systems: all VCS-specific components are in separate directories like -src/git/ . The top-level `versioneer.py` script is assembled from these -components by running make-versioneer.py . In the future, make-versioneer.py -will take a VCS name as an argument, and will construct a version of -`versioneer.py` that is specific to the given VCS. It might also take the -configuration arguments that are currently provided manually during -installation by editing setup.py . Alternatively, it might go the other -direction and include code from all supported VCS systems, reducing the -number of intermediate scripts. - -## Similar projects - -* [setuptools_scm](https://github.com/pypa/setuptools_scm/) - a non-vendored build-time - dependency -* [minver](https://github.com/jbweston/miniver) - a lightweight reimplementation of - versioneer -* [versioningit](https://github.com/jwodder/versioningit) - a PEP 518-based setuptools - plugin - -## License - -To make Versioneer easier to embed, all its code is dedicated to the public -domain. The `_version.py` that it creates is also in the public domain. -Specifically, both are released under the "Unlicense", as described in -https://unlicense.org/. - -[pypi-image]: https://img.shields.io/pypi/v/versioneer.svg -[pypi-url]: https://pypi.python.org/pypi/versioneer/ -[travis-image]: -https://img.shields.io/travis/com/python-versioneer/python-versioneer.svg -[travis-url]: https://travis-ci.com/github/python-versioneer/python-versioneer - -""" -# pylint:disable=invalid-name,import-outside-toplevel,missing-function-docstring -# pylint:disable=missing-class-docstring,too-many-branches,too-many-statements -# pylint:disable=raise-missing-from,too-many-lines,too-many-locals,import-error -# pylint:disable=too-few-public-methods,redefined-outer-name,consider-using-with -# pylint:disable=attribute-defined-outside-init,too-many-arguments - -import configparser -import errno -import json -import os -import re -import subprocess -import sys -from pathlib import Path -from typing import Any, Callable, cast, Dict, List, Optional, Tuple, Union -from typing import NoReturn -import functools - -have_tomllib = True -if sys.version_info >= (3, 11): - import tomllib -else: - try: - import tomli as tomllib - except ImportError: - have_tomllib = False - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - versionfile_source: str - versionfile_build: Optional[str] - parentdir_prefix: Optional[str] - verbose: Optional[bool] - - -def get_root() -> str: - """Get the project root directory. - - We require that all commands are run from the project root, i.e. the - directory that contains setup.py, setup.cfg, and versioneer.py . - """ - root = os.path.realpath(os.path.abspath(os.getcwd())) - setup_py = os.path.join(root, "setup.py") - pyproject_toml = os.path.join(root, "pyproject.toml") - versioneer_py = os.path.join(root, "versioneer.py") - if not ( - os.path.exists(setup_py) - or os.path.exists(pyproject_toml) - or os.path.exists(versioneer_py) - ): - # allow 'python path/to/setup.py COMMAND' - root = os.path.dirname(os.path.realpath(os.path.abspath(sys.argv[0]))) - setup_py = os.path.join(root, "setup.py") - pyproject_toml = os.path.join(root, "pyproject.toml") - versioneer_py = os.path.join(root, "versioneer.py") - if not ( - os.path.exists(setup_py) - or os.path.exists(pyproject_toml) - or os.path.exists(versioneer_py) - ): - err = ("Versioneer was unable to run the project root directory. " - "Versioneer requires setup.py to be executed from " - "its immediate directory (like 'python setup.py COMMAND'), " - "or in a way that lets it use sys.argv[0] to find the root " - "(like 'python path/to/setup.py COMMAND').") - raise VersioneerBadRootError(err) - try: - # Certain runtime workflows (setup.py install/develop in a setuptools - # tree) execute all dependencies in a single python process, so - # "versioneer" may be imported multiple times, and python's shared - # module-import table will cache the first one. So we can't use - # os.path.dirname(__file__), as that will find whichever - # versioneer.py was first imported, even in later projects. - my_path = os.path.realpath(os.path.abspath(__file__)) - me_dir = os.path.normcase(os.path.splitext(my_path)[0]) - vsr_dir = os.path.normcase(os.path.splitext(versioneer_py)[0]) - if me_dir != vsr_dir and "VERSIONEER_PEP518" not in globals(): - print("Warning: build in %s is using versioneer.py from %s" - % (os.path.dirname(my_path), versioneer_py)) - except NameError: - pass - return root - - -def get_config_from_root(root: str) -> VersioneerConfig: - """Read the project setup.cfg file to determine Versioneer config.""" - # This might raise OSError (if setup.cfg is missing), or - # configparser.NoSectionError (if it lacks a [versioneer] section), or - # configparser.NoOptionError (if it lacks "VCS="). See the docstring at - # the top of versioneer.py for instructions on writing your setup.cfg . - root_pth = Path(root) - pyproject_toml = root_pth / "pyproject.toml" - setup_cfg = root_pth / "setup.cfg" - section: Union[Dict[str, Any], configparser.SectionProxy, None] = None - if pyproject_toml.exists() and have_tomllib: - try: - with open(pyproject_toml, 'rb') as fobj: - pp = tomllib.load(fobj) - section = pp['tool']['versioneer'] - except (tomllib.TOMLDecodeError, KeyError) as e: - print(f"Failed to load config from {pyproject_toml}: {e}") - print("Try to load it from setup.cfg") - if not section: - parser = configparser.ConfigParser() - with open(setup_cfg) as cfg_file: - parser.read_file(cfg_file) - parser.get("versioneer", "VCS") # raise error if missing - - section = parser["versioneer"] - - # `cast`` really shouldn't be used, but its simplest for the - # common VersioneerConfig users at the moment. We verify against - # `None` values elsewhere where it matters - - cfg = VersioneerConfig() - cfg.VCS = section['VCS'] - cfg.style = section.get("style", "") - cfg.versionfile_source = cast(str, section.get("versionfile_source")) - cfg.versionfile_build = section.get("versionfile_build") - cfg.tag_prefix = cast(str, section.get("tag_prefix")) - if cfg.tag_prefix in ("''", '""', None): - cfg.tag_prefix = "" - cfg.parentdir_prefix = section.get("parentdir_prefix") - if isinstance(section, configparser.SectionProxy): - # Make sure configparser translates to bool - cfg.verbose = section.getboolean("verbose") - else: - cfg.verbose = section.get("verbose") - - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -# these dictionaries contain VCS-specific tools -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - HANDLERS.setdefault(vcs, {})[method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %s" % dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %s" % (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %s (error)" % dispcmd) - print("stdout was %s" % stdout) - return None, process.returncode - return stdout, process.returncode - - -LONG_VERSION_PY['git'] = r''' -# This file helps to compute a version number in source trees obtained from -# git-archive tarball (such as those provided by githubs download-from-tag -# feature). Distribution tarballs (built by setup.py sdist) and build -# directories (produced by setup.py build) will contain a much shorter file -# that just contains the computed version number. - -# This file is released into the public domain. -# Generated by versioneer-0.29 -# https://github.com/python-versioneer/python-versioneer - -"""Git implementation of _version.py.""" - -import errno -import os -import re -import subprocess -import sys -from typing import Any, Callable, Dict, List, Optional, Tuple -import functools - - -def get_keywords() -> Dict[str, str]: - """Get the keywords needed to look up the version information.""" - # these strings will be replaced by git during git-archive. - # setup.py/versioneer.py will grep for the variable names, so they must - # each be defined on a line of their own. _version.py will just call - # get_keywords(). - git_refnames = "%(DOLLAR)sFormat:%%d%(DOLLAR)s" - git_full = "%(DOLLAR)sFormat:%%H%(DOLLAR)s" - git_date = "%(DOLLAR)sFormat:%%ci%(DOLLAR)s" - keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} - return keywords - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - parentdir_prefix: str - versionfile_source: str - verbose: bool - - -def get_config() -> VersioneerConfig: - """Create, populate and return the VersioneerConfig() object.""" - # these strings are filled in when 'setup.py versioneer' creates - # _version.py - cfg = VersioneerConfig() - cfg.VCS = "git" - cfg.style = "%(STYLE)s" - cfg.tag_prefix = "%(TAG_PREFIX)s" - cfg.parentdir_prefix = "%(PARENTDIR_PREFIX)s" - cfg.versionfile_source = "%(VERSIONFILE_SOURCE)s" - cfg.verbose = False - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - if vcs not in HANDLERS: - HANDLERS[vcs] = {} - HANDLERS[vcs][method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %%s" %% dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %%s" %% (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %%s (error)" %% dispcmd) - print("stdout was %%s" %% stdout) - return None, process.returncode - return stdout, process.returncode - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %%s but none started with prefix %%s" %% - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %%d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%%s', no digits" %% ",".join(refs - tags)) - if verbose: - print("likely tags: %%s" %% ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %%s" %% r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %%s not under git control" %% root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%%s'" - %% describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%%s' doesn't start with prefix '%%s'" - print(fmt %% (full_tag, tag_prefix)) - pieces["error"] = ("tag '%%s' doesn't start with prefix '%%s'" - %% (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%%d.g%%s" %% (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%%d.g%%s" %% (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%%d.dev%%d" %% (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%%d" %% (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%%d" %% pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%%s" %% pieces["short"] - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%%s" %% pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%%s" %% pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%%s" %% pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%%s'" %% style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -def get_versions() -> Dict[str, Any]: - """Get version information or return default if unable to do so.""" - # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have - # __file__, we can work backwards from there to the root. Some - # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which - # case we can only use expanded keywords. - - cfg = get_config() - verbose = cfg.verbose - - try: - return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, - verbose) - except NotThisMethod: - pass - - try: - root = os.path.realpath(__file__) - # versionfile_source is the relative path from the top of the source - # tree (where the .git directory might live) to this file. Invert - # this to find the root from __file__. - for _ in cfg.versionfile_source.split('/'): - root = os.path.dirname(root) - except NameError: - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to find root of source tree", - "date": None} - - try: - pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) - return render(pieces, cfg.style) - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - except NotThisMethod: - pass - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to compute version", "date": None} -''' - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%s', no digits" % ",".join(refs - tags)) - if verbose: - print("likely tags: %s" % ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %s" % r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %s not under git control" % root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%s'" - % describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%s' doesn't start with prefix '%s'" - print(fmt % (full_tag, tag_prefix)) - pieces["error"] = ("tag '%s' doesn't start with prefix '%s'" - % (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def do_vcs_install(versionfile_source: str, ipy: Optional[str]) -> None: - """Git-specific installation logic for Versioneer. - - For Git, this means creating/changing .gitattributes to mark _version.py - for export-subst keyword substitution. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - files = [versionfile_source] - if ipy: - files.append(ipy) - if "VERSIONEER_PEP518" not in globals(): - try: - my_path = __file__ - if my_path.endswith((".pyc", ".pyo")): - my_path = os.path.splitext(my_path)[0] + ".py" - versioneer_file = os.path.relpath(my_path) - except NameError: - versioneer_file = "versioneer.py" - files.append(versioneer_file) - present = False - try: - with open(".gitattributes", "r") as fobj: - for line in fobj: - if line.strip().startswith(versionfile_source): - if "export-subst" in line.strip().split()[1:]: - present = True - break - except OSError: - pass - if not present: - with open(".gitattributes", "a+") as fobj: - fobj.write(f"{versionfile_source} export-subst\n") - files.append(".gitattributes") - run_command(GITS, ["add", "--"] + files) - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %s but none started with prefix %s" % - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -SHORT_VERSION_PY = """ -# This file was generated by 'versioneer.py' (0.29) from -# revision-control system data, or from the parent directory name of an -# unpacked source archive. Distribution tarballs contain a pre-generated copy -# of this file. - -import json - -version_json = ''' -%s -''' # END VERSION_JSON - - -def get_versions(): - return json.loads(version_json) -""" - - -def versions_from_file(filename: str) -> Dict[str, Any]: - """Try to determine the version from _version.py if present.""" - try: - with open(filename) as f: - contents = f.read() - except OSError: - raise NotThisMethod("unable to read _version.py") - mo = re.search(r"version_json = '''\n(.*)''' # END VERSION_JSON", - contents, re.M | re.S) - if not mo: - mo = re.search(r"version_json = '''\r\n(.*)''' # END VERSION_JSON", - contents, re.M | re.S) - if not mo: - raise NotThisMethod("no version_json in _version.py") - return json.loads(mo.group(1)) - - -def write_to_version_file(filename: str, versions: Dict[str, Any]) -> None: - """Write the given version number to the given _version.py file.""" - contents = json.dumps(versions, sort_keys=True, - indent=1, separators=(",", ": ")) - with open(filename, "w") as f: - f.write(SHORT_VERSION_PY % contents) - - print("set %s to '%s'" % (filename, versions["version"])) - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%d.dev%d" % (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%d" % (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%d" % pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%s'" % style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -class VersioneerBadRootError(Exception): - """The project root directory is unknown or missing key files.""" - - -def get_versions(verbose: bool = False) -> Dict[str, Any]: - """Get the project version from whatever source is available. - - Returns dict with two keys: 'version' and 'full'. - """ - if "versioneer" in sys.modules: - # see the discussion in cmdclass.py:get_cmdclass() - del sys.modules["versioneer"] - - root = get_root() - cfg = get_config_from_root(root) - - assert cfg.VCS is not None, "please set [versioneer]VCS= in setup.cfg" - handlers = HANDLERS.get(cfg.VCS) - assert handlers, "unrecognized VCS '%s'" % cfg.VCS - verbose = verbose or bool(cfg.verbose) # `bool()` used to avoid `None` - assert cfg.versionfile_source is not None, \ - "please set versioneer.versionfile_source" - assert cfg.tag_prefix is not None, "please set versioneer.tag_prefix" - - versionfile_abs = os.path.join(root, cfg.versionfile_source) - - # extract version from first of: _version.py, VCS command (e.g. 'git - # describe'), parentdir. This is meant to work for developers using a - # source checkout, for users of a tarball created by 'setup.py sdist', - # and for users of a tarball/zipball created by 'git archive' or github's - # download-from-tag feature or the equivalent in other VCSes. - - get_keywords_f = handlers.get("get_keywords") - from_keywords_f = handlers.get("keywords") - if get_keywords_f and from_keywords_f: - try: - keywords = get_keywords_f(versionfile_abs) - ver = from_keywords_f(keywords, cfg.tag_prefix, verbose) - if verbose: - print("got version from expanded keyword %s" % ver) - return ver - except NotThisMethod: - pass - - try: - ver = versions_from_file(versionfile_abs) - if verbose: - print("got version from file %s %s" % (versionfile_abs, ver)) - return ver - except NotThisMethod: - pass - - from_vcs_f = handlers.get("pieces_from_vcs") - if from_vcs_f: - try: - pieces = from_vcs_f(cfg.tag_prefix, root, verbose) - ver = render(pieces, cfg.style) - if verbose: - print("got version from VCS %s" % ver) - return ver - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - ver = versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - if verbose: - print("got version from parentdir %s" % ver) - return ver - except NotThisMethod: - pass - - if verbose: - print("unable to compute version") - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, "error": "unable to compute version", - "date": None} - - -def get_version() -> str: - """Get the short version string for this project.""" - return get_versions()["version"] - - -def get_cmdclass(cmdclass: Optional[Dict[str, Any]] = None): - """Get the custom setuptools subclasses used by Versioneer. - - If the package uses a different cmdclass (e.g. one from numpy), it - should be provide as an argument. - """ - if "versioneer" in sys.modules: - del sys.modules["versioneer"] - # this fixes the "python setup.py develop" case (also 'install' and - # 'easy_install .'), in which subdependencies of the main project are - # built (using setup.py bdist_egg) in the same python process. Assume - # a main project A and a dependency B, which use different versions - # of Versioneer. A's setup.py imports A's Versioneer, leaving it in - # sys.modules by the time B's setup.py is executed, causing B to run - # with the wrong versioneer. Setuptools wraps the sub-dep builds in a - # sandbox that restores sys.modules to it's pre-build state, so the - # parent is protected against the child's "import versioneer". By - # removing ourselves from sys.modules here, before the child build - # happens, we protect the child from the parent's versioneer too. - # Also see https://github.com/python-versioneer/python-versioneer/issues/52 - - cmds = {} if cmdclass is None else cmdclass.copy() - - # we add "version" to setuptools - from setuptools import Command - - class cmd_version(Command): - description = "report generated version string" - user_options: List[Tuple[str, str, str]] = [] - boolean_options: List[str] = [] - - def initialize_options(self) -> None: - pass - - def finalize_options(self) -> None: - pass - - def run(self) -> None: - vers = get_versions(verbose=True) - print("Version: %s" % vers["version"]) - print(" full-revisionid: %s" % vers.get("full-revisionid")) - print(" dirty: %s" % vers.get("dirty")) - print(" date: %s" % vers.get("date")) - if vers["error"]: - print(" error: %s" % vers["error"]) - cmds["version"] = cmd_version - - # we override "build_py" in setuptools - # - # most invocation pathways end up running build_py: - # distutils/build -> build_py - # distutils/install -> distutils/build ->.. - # setuptools/bdist_wheel -> distutils/install ->.. - # setuptools/bdist_egg -> distutils/install_lib -> build_py - # setuptools/install -> bdist_egg ->.. - # setuptools/develop -> ? - # pip install: - # copies source tree to a tempdir before running egg_info/etc - # if .git isn't copied too, 'git describe' will fail - # then does setup.py bdist_wheel, or sometimes setup.py install - # setup.py egg_info -> ? - - # pip install -e . and setuptool/editable_wheel will invoke build_py - # but the build_py command is not expected to copy any files. - - # we override different "build_py" commands for both environments - if 'build_py' in cmds: - _build_py: Any = cmds['build_py'] - else: - from setuptools.command.build_py import build_py as _build_py - - class cmd_build_py(_build_py): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - _build_py.run(self) - if getattr(self, "editable_mode", False): - # During editable installs `.py` and data files are - # not copied to build_lib - return - # now locate _version.py in the new build/ directory and replace - # it with an updated value - if cfg.versionfile_build: - target_versionfile = os.path.join(self.build_lib, - cfg.versionfile_build) - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - cmds["build_py"] = cmd_build_py - - if 'build_ext' in cmds: - _build_ext: Any = cmds['build_ext'] - else: - from setuptools.command.build_ext import build_ext as _build_ext - - class cmd_build_ext(_build_ext): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - _build_ext.run(self) - if self.inplace: - # build_ext --inplace will only build extensions in - # build/lib<..> dir with no _version.py to write to. - # As in place builds will already have a _version.py - # in the module dir, we do not need to write one. - return - # now locate _version.py in the new build/ directory and replace - # it with an updated value - if not cfg.versionfile_build: - return - target_versionfile = os.path.join(self.build_lib, - cfg.versionfile_build) - if not os.path.exists(target_versionfile): - print(f"Warning: {target_versionfile} does not exist, skipping " - "version update. This can happen if you are running build_ext " - "without first running build_py.") - return - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - cmds["build_ext"] = cmd_build_ext - - if "cx_Freeze" in sys.modules: # cx_freeze enabled? - from cx_Freeze.dist import build_exe as _build_exe # type: ignore - # nczeczulin reports that py2exe won't like the pep440-style string - # as FILEVERSION, but it can be used for PRODUCTVERSION, e.g. - # setup(console=[{ - # "version": versioneer.get_version().split("+", 1)[0], # FILEVERSION - # "product_version": versioneer.get_version(), - # ... - - class cmd_build_exe(_build_exe): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - target_versionfile = cfg.versionfile_source - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - - _build_exe.run(self) - os.unlink(target_versionfile) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % - {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - cmds["build_exe"] = cmd_build_exe - del cmds["build_py"] - - if 'py2exe' in sys.modules: # py2exe enabled? - try: - from py2exe.setuptools_buildexe import py2exe as _py2exe # type: ignore - except ImportError: - from py2exe.distutils_buildexe import py2exe as _py2exe # type: ignore - - class cmd_py2exe(_py2exe): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - target_versionfile = cfg.versionfile_source - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - - _py2exe.run(self) - os.unlink(target_versionfile) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % - {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - cmds["py2exe"] = cmd_py2exe - - # sdist farms its file list building out to egg_info - if 'egg_info' in cmds: - _egg_info: Any = cmds['egg_info'] - else: - from setuptools.command.egg_info import egg_info as _egg_info - - class cmd_egg_info(_egg_info): - def find_sources(self) -> None: - # egg_info.find_sources builds the manifest list and writes it - # in one shot - super().find_sources() - - # Modify the filelist and normalize it - root = get_root() - cfg = get_config_from_root(root) - self.filelist.append('versioneer.py') - if cfg.versionfile_source: - # There are rare cases where versionfile_source might not be - # included by default, so we must be explicit - self.filelist.append(cfg.versionfile_source) - self.filelist.sort() - self.filelist.remove_duplicates() - - # The write method is hidden in the manifest_maker instance that - # generated the filelist and was thrown away - # We will instead replicate their final normalization (to unicode, - # and POSIX-style paths) - from setuptools import unicode_utils - normalized = [unicode_utils.filesys_decode(f).replace(os.sep, '/') - for f in self.filelist.files] - - manifest_filename = os.path.join(self.egg_info, 'SOURCES.txt') - with open(manifest_filename, 'w') as fobj: - fobj.write('\n'.join(normalized)) - - cmds['egg_info'] = cmd_egg_info - - # we override different "sdist" commands for both environments - if 'sdist' in cmds: - _sdist: Any = cmds['sdist'] - else: - from setuptools.command.sdist import sdist as _sdist - - class cmd_sdist(_sdist): - def run(self) -> None: - versions = get_versions() - self._versioneer_generated_versions = versions - # unless we update this, the command will keep using the old - # version - self.distribution.metadata.version = versions["version"] - return _sdist.run(self) - - def make_release_tree(self, base_dir: str, files: List[str]) -> None: - root = get_root() - cfg = get_config_from_root(root) - _sdist.make_release_tree(self, base_dir, files) - # now locate _version.py in the new base_dir directory - # (remembering that it may be a hardlink) and replace it with an - # updated value - target_versionfile = os.path.join(base_dir, cfg.versionfile_source) - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, - self._versioneer_generated_versions) - cmds["sdist"] = cmd_sdist - - return cmds - - -CONFIG_ERROR = """ -setup.cfg is missing the necessary Versioneer configuration. You need -a section like: - - [versioneer] - VCS = git - style = pep440 - versionfile_source = src/myproject/_version.py - versionfile_build = myproject/_version.py - tag_prefix = - parentdir_prefix = myproject- - -You will also need to edit your setup.py to use the results: - - import versioneer - setup(version=versioneer.get_version(), - cmdclass=versioneer.get_cmdclass(), ...) - -Please read the docstring in ./versioneer.py for configuration instructions, -edit setup.cfg, and re-run the installer or 'python versioneer.py setup'. -""" - -SAMPLE_CONFIG = """ -# See the docstring in versioneer.py for instructions. Note that you must -# re-run 'versioneer.py setup' after changing this section, and commit the -# resulting files. - -[versioneer] -#VCS = git -#style = pep440 -#versionfile_source = -#versionfile_build = -#tag_prefix = -#parentdir_prefix = - -""" - -OLD_SNIPPET = """ -from ._version import get_versions -__version__ = get_versions()['version'] -del get_versions -""" - -INIT_PY_SNIPPET = """ -from . import {0} -__version__ = {0}.get_versions()['version'] -""" - - -def do_setup() -> int: - """Do main VCS-independent setup function for installing Versioneer.""" - root = get_root() - try: - cfg = get_config_from_root(root) - except (OSError, configparser.NoSectionError, - configparser.NoOptionError) as e: - if isinstance(e, (OSError, configparser.NoSectionError)): - print("Adding sample versioneer config to setup.cfg", - file=sys.stderr) - with open(os.path.join(root, "setup.cfg"), "a") as f: - f.write(SAMPLE_CONFIG) - print(CONFIG_ERROR, file=sys.stderr) - return 1 - - print(" creating %s" % cfg.versionfile_source) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - - ipy = os.path.join(os.path.dirname(cfg.versionfile_source), - "__init__.py") - maybe_ipy: Optional[str] = ipy - if os.path.exists(ipy): - try: - with open(ipy, "r") as f: - old = f.read() - except OSError: - old = "" - module = os.path.splitext(os.path.basename(cfg.versionfile_source))[0] - snippet = INIT_PY_SNIPPET.format(module) - if OLD_SNIPPET in old: - print(" replacing boilerplate in %s" % ipy) - with open(ipy, "w") as f: - f.write(old.replace(OLD_SNIPPET, snippet)) - elif snippet not in old: - print(" appending to %s" % ipy) - with open(ipy, "a") as f: - f.write(snippet) - else: - print(" %s unmodified" % ipy) - else: - print(" %s doesn't exist, ok" % ipy) - maybe_ipy = None - - # Make VCS-specific changes. For git, this means creating/changing - # .gitattributes to mark _version.py for export-subst keyword - # substitution. - do_vcs_install(cfg.versionfile_source, maybe_ipy) - return 0 - - -def scan_setup_py() -> int: - """Validate the contents of setup.py against Versioneer's expectations.""" - found = set() - setters = False - errors = 0 - with open("setup.py", "r") as f: - for line in f.readlines(): - if "import versioneer" in line: - found.add("import") - if "versioneer.get_cmdclass()" in line: - found.add("cmdclass") - if "versioneer.get_version()" in line: - found.add("get_version") - if "versioneer.VCS" in line: - setters = True - if "versioneer.versionfile_source" in line: - setters = True - if len(found) != 3: - print("") - print("Your setup.py appears to be missing some important items") - print("(but I might be wrong). Please make sure it has something") - print("roughly like the following:") - print("") - print(" import versioneer") - print(" setup( version=versioneer.get_version(),") - print(" cmdclass=versioneer.get_cmdclass(), ...)") - print("") - errors += 1 - if setters: - print("You should remove lines like 'versioneer.VCS = ' and") - print("'versioneer.versionfile_source = ' . This configuration") - print("now lives in setup.cfg, and should be removed from setup.py") - print("") - errors += 1 - return errors - - -def setup_command() -> NoReturn: - """Set up Versioneer and exit with appropriate error code.""" - errors = do_setup() - errors += scan_setup_py() - sys.exit(1 if errors else 0) - - -if __name__ == "__main__": - cmd = sys.argv[1] - if cmd == "setup": - setup_command() From 77e8bd82bb456b1802053427afae3c2721cc1116 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 6 Mar 2026 08:41:24 -0500 Subject: [PATCH 02/18] changelog --- docs/sphinx/source/changelog/pending.rst | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index e69de29bb..2fdb3be22 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -0,0 +1,15 @@ +******* +Pending +******* + +Maintenance +----------- +* Migrated project configuration from ``setup.py``/``setup.cfg`` to + ``pyproject.toml`` using ``setuptools`` as the build backend. + (:pull:`488`) +* Replaced ``versioneer`` with ``setuptools-scm`` for automatic version + management from git tags. (:pull:`488`) +* Removed legacy build files: ``setup.py``, ``setup.cfg``, ``versioneer.py``, + ``MANIFEST.in``, and ``rdtools/_version.py``. (:pull:`488`) +* Updated ``rdtools/__init__.py`` to use ``importlib.metadata`` for version + retrieval instead of versioneer. (:pull:`488`) From 687f66d9e6e18e16efd98edbe5498c008ca29a07 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 6 Mar 2026 08:46:25 -0500 Subject: [PATCH 03/18] update URLs --- CITATION.cff | 2 +- README.md | 10 +++++----- docs/sphinx/source/conf.py | 6 +++--- docs/sphinx/source/developer_notes.rst | 2 +- docs/sphinx/source/index.rst | 6 +++--- pyproject.toml | 6 +++--- rdtools/soiling.py | 4 ++-- rdtools/test/soiling_test.py | 2 +- 8 files changed, 19 insertions(+), 19 deletions(-) diff --git a/CITATION.cff b/CITATION.cff index 2c050d4b1..299bd5994 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -43,4 +43,4 @@ authors: orcid: "https://orcid.org/0000-0002-9867-8930" title: "RdTools" doi: 10.5281/zenodo.1210316 -url: "https://github.com/NREL/rdtools" \ No newline at end of file +url: "https://github.com/NatLabRockies/rdtools" \ No newline at end of file diff --git a/README.md b/README.md index 189a4f610..39050dce8 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,13 @@ RdTools logo Master branch: -[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NREL/rdtools/actions?query=branch%3Amaster) +[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Amaster) Development branch: -[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NREL/rdtools/actions?query=branch%3Adevelopment) +[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Adevelopment) Code coverage: -[![codecov](https://codecov.io/gh/NREL/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NREL/rdtools) +[![codecov](https://codecov.io/gh/NatLabRockies/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NatLabRockies/rdtools) RdTools is an open-source library to support reproducible technical analysis of time series data from photovoltaic energy systems. The library aims to provide @@ -38,7 +38,7 @@ and the specific DOI coresponding to that version from [Zenodo](https://doi.org/ Martin Springer, Jiyang Yan, Kirsten Perry, Sandra Villamar, Will Vining, Gregory Kimball, Daniel Ruth, Noah Moyer, Quyen Nguyen, Dirk Jordan, Matthew Muller, and Chris Deline, RdTools, version {insert version}, Computer Software, - https://github.com/NREL/rdtools. DOI:{insert DOI} + https://github.com/NatLabRockies/rdtools. DOI:{insert DOI} The underlying workflow of RdTools has been published in several places. If you use RdTools in a published work, you may also wish to cite the following as @@ -76,5 +76,5 @@ Other useful references which may also be consulted for degradation rate methodo ## Further Instructions and Updates -Check out the [wiki](https://github.com/NREL/rdtools/wiki) for additional usage documentation, and for information on development goals and framework. +Check out the [wiki](https://github.com/NatLabRockies/rdtools/wiki) for additional usage documentation, and for information on development goals and framework. diff --git a/docs/sphinx/source/conf.py b/docs/sphinx/source/conf.py index c46717ae7..4bfd1da3d 100644 --- a/docs/sphinx/source/conf.py +++ b/docs/sphinx/source/conf.py @@ -62,8 +62,8 @@ # List of external link aliases. Allows use of :pull:`123` to autolink that PR extlinks = { - "issue": ("https://github.com/NREL/rdtools/issues/%s", "GH #%s"), - "pull": ("https://github.com/NREL/rdtools/pull/%s", "GH #%s"), + "issue": ("https://github.com/NatLabRockies/rdtools/issues/%s", "GH #%s"), + "pull": ("https://github.com/NatLabRockies/rdtools/pull/%s", "GH #%s"), "ghuser": ("https://github.com/%s", "@%s"), } @@ -195,7 +195,7 @@ def make_github_url(pagename): # either a branch name or a git tag will work for the URL branch = version_map.get(rtd_version, rtd_version) - URL_BASE = "https://github.com/nrel/rdtools/blob/{}/".format(branch) + URL_BASE = "https://github.com/NatLabRockies/rdtools/blob/{}/".format(branch) # is it an API autogen page? if pagename.startswith("generated/"): diff --git a/docs/sphinx/source/developer_notes.rst b/docs/sphinx/source/developer_notes.rst index d33272f24..f293d88d2 100644 --- a/docs/sphinx/source/developer_notes.rst +++ b/docs/sphinx/source/developer_notes.rst @@ -16,7 +16,7 @@ you'll need to clone the RdTools source repository from Github with e.g. :: - git clone https://github.com/NREL/rdtools.git + git clone https://github.com/NatLabRockies/rdtools.git from the command line, or using a GUI git client like Github Desktop. This will clone the entire git repository onto your computer. diff --git a/docs/sphinx/source/index.rst b/docs/sphinx/source/index.rst index cf6d0f0cc..e8b8b5990 100644 --- a/docs/sphinx/source/index.rst +++ b/docs/sphinx/source/index.rst @@ -187,7 +187,7 @@ and the specific DOI coresponding to that version from `Zenodo Date: Fri, 6 Mar 2026 08:49:37 -0500 Subject: [PATCH 04/18] change NREL to NLR --- CODE_OF_CONDUCT.md | 2 +- docs/sphinx/source/changelog/v2.0.0.rst | 2 +- docs/sphinx/source/developer_notes.rst | 20 ++++++++++---------- docs/sphinx/source/index.rst | 10 +++++----- rdtools/test/filtering_test.py | 2 +- 5 files changed, 18 insertions(+), 18 deletions(-) diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md index c18f3d799..e7799a422 100644 --- a/CODE_OF_CONDUCT.md +++ b/CODE_OF_CONDUCT.md @@ -55,7 +55,7 @@ further defined and clarified by project maintainers. ## Enforcement Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported by contacting the project team at RdTools@nrel.gov. All +reported by contacting the project team at RdTools@nlr.gov. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. diff --git a/docs/sphinx/source/changelog/v2.0.0.rst b/docs/sphinx/source/changelog/v2.0.0.rst index a9b981456..f05a8c5df 100644 --- a/docs/sphinx/source/changelog/v2.0.0.rst +++ b/docs/sphinx/source/changelog/v2.0.0.rst @@ -97,7 +97,7 @@ Example Updates variable names (:pull:`139`). * Add soiling section to the original example notebook. * Add a new example notebook that analyzes data from a PV system located at - NREL's South Table Mountain campus (PVDAQ system #4) (:pull:`171`). + NLR's South Table Mountain campus (PVDAQ system #4) (:pull:`171`). * Explicitly register pandas datetime converters which were `deprecated `_. * Add new ``system_availability_example.ipynb`` notebook (:pull:`131`) diff --git a/docs/sphinx/source/developer_notes.rst b/docs/sphinx/source/developer_notes.rst index f293d88d2..c4b502509 100644 --- a/docs/sphinx/source/developer_notes.rst +++ b/docs/sphinx/source/developer_notes.rst @@ -19,13 +19,13 @@ you'll need to clone the RdTools source repository from Github with e.g. git clone https://github.com/NatLabRockies/rdtools.git from the command line, or using a GUI git client like Github Desktop. This -will clone the entire git repository onto your computer. +will clone the entire git repository onto your computer. Installing RdTools dependencies ------------------------------- The packages necessary to run RdTools itself can be installed with ``pip``. -You can install the dependencies along with RdTools itself from +You can install the dependencies along with RdTools itself from `PyPI `_: :: @@ -66,14 +66,14 @@ Installing optional dependencies RdTools has extra dependencies for running its test suite and building its documentation. These packages aren't necessary for running RdTools itself and -are only needed if you want to contribute source code to RdTools. +are only needed if you want to contribute source code to RdTools. .. note:: These will install RdTools along with other packages necessary to build its documentation and run its test suite. We recommend doing this in a virtual environment to keep package installations between projects separate! -Optional dependencies can be installed with the special +Optional dependencies can be installed with the special `syntax `_: :: @@ -115,7 +115,7 @@ And even a single test function: pytest rdtools/test/soiling_test.py::test_soiling_srr -You can also evaluate code coverage when running the test suite using the +You can also evaluate code coverage when running the test suite using the `coverage `_ package: :: @@ -129,7 +129,7 @@ summary report showing how much much of each source file was executed in the test suite. If a percentage is below 100, that means a function isn't tested or a branch inside a function isn't tested. To get specific details, you can run ``coverage html`` to generate a detailed HTML -report at ``htmlcov/index.html`` to view in a browser. +report at ``htmlcov/index.html`` to view in a browser. Running the notebooks as tests @@ -214,7 +214,7 @@ docs should result in output like this: dumping search index in English (code: en) ... done dumping object inventory... done build succeeded. - + The HTML pages are in build\html. If you get an error like ``Pandoc wasn't found``, you can install it with conda: @@ -230,7 +230,7 @@ Contributing ------------ Community participation is welcome! New contributions should be based on the -``development`` branch as the ``master`` branch is used only for releases. +``development`` branch as the ``master`` branch is used only for releases. RdTools follows the `PEP 8 `_ style guide. We recommend setting up your text editor to automatically highlight style @@ -238,7 +238,7 @@ violations because it's easy to miss some issues (trailing whitespace, etc) othe Additionally, our documentation is built in part from docstrings in the source code. These docstrings must be in `NumpyDoc format `_ -to be rendered correctly in the documentation. +to be rendered correctly in the documentation. Finally, all code should be tested. Some older tests in RdTools use the unittest -module, but new tests should all use pytest. \ No newline at end of file +module, but new tests should all use pytest. \ No newline at end of file diff --git a/docs/sphinx/source/index.rst b/docs/sphinx/source/index.rst index e8b8b5990..4349fb5f1 100644 --- a/docs/sphinx/source/index.rst +++ b/docs/sphinx/source/index.rst @@ -53,7 +53,7 @@ The preferred method for degradation rate estimation is the year-on-year (YOY) approach (Jordan 2018), available in :py:func:`.degradation.degradation_year_on_year`. The YOY calculation yields a distribution of degradation rates, the central tendency of which is the most representative of the true -degradation. We note that the workflow described above and implemented in +degradation. We note that the workflow described above and implemented in :py:class:`.analysis_chains.TrendAnalysis` provides an estimate of degradation rate, not performance loss rate (PLR). PLR includes losses that are explicitly filtered out by the primary workflow (Deceglie 2023). @@ -102,14 +102,14 @@ The combined estimation of degradation and soiling (CODS) method (Skomedal 2020) in RdTools. CODS self-consistently extracts degradation, soiling, and seasonality of the daily-aggregated normalized performance signal. It is particularly useful when soiling trends are biasing degradation results. It's use is shown in both the TrendAnalysis -example notebook as well as the funtional API example notebook for degradation and soiling. +example notebook as well as the funtional API example notebook for degradation and soiling. TrendAnalysis ^^^^^^^^^^^^^ -An object-oriented API for complete soiling and degradation analysis including +An object-oriented API for complete soiling and degradation analysis including the normalize, filter, aggregate, analyze steps is available in :py:class:`.analysis_chains.TrendAnalysis`. See the -`TrendAnalysis example `_ for details. +`TrendAnalysis example `_ for details. Availability ------------ @@ -220,7 +220,7 @@ References :py:func:`.clearsky_temperature.get_clearsky_tamb()`, uses data from images created by Jesse Allen, NASA’s Earth Observatory using data courtesy of the MODIS Land Group. - + + https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MOD_LSTD_CLIM_M + https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MOD_LSTN_CLIM_M diff --git a/rdtools/test/filtering_test.py b/rdtools/test/filtering_test.py index 586b32165..8a993571a 100644 --- a/rdtools/test/filtering_test.py +++ b/rdtools/test/filtering_test.py @@ -509,7 +509,7 @@ def test_hour_angle_filter(): series = pd.Series([1, 2, 3, 4, 5], index=index) # Define latitude and longitude - lat, lon = 39.7413, -105.1684 # NREL, Golden, CO + lat, lon = 39.7413, -105.1684 # NLR, Golden, CO # Call the function with the test data result = hour_angle_filter(series, lat, lon) From 9c4dac5b5b66ccd353f387eb2b0837e714e88f4a Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 6 Mar 2026 08:49:48 -0500 Subject: [PATCH 05/18] linting --- docs/sphinx/source/changelog/v2.0.0.rst | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/sphinx/source/changelog/v2.0.0.rst b/docs/sphinx/source/changelog/v2.0.0.rst index f05a8c5df..e383f5757 100644 --- a/docs/sphinx/source/changelog/v2.0.0.rst +++ b/docs/sphinx/source/changelog/v2.0.0.rst @@ -11,12 +11,12 @@ API Changes right-labeled energy with :py:func:`~rdtools.normalization.energy_from_power` before being used with these normalization functions (:pull:`105`, :pull:`108`). * Remove ``low_power_cutoff`` parameter in :py:func:`~rdtools.filtering.clip_filter` (:issue:`84`). -* Many kwargs have changed name (but not input order) to bring nomenclature into +* Many kwargs have changed name (but not input order) to bring nomenclature into closer alignment with the `DuraMAT pv-terms project `_: (:pull:`185`) * :py:func:`~rdtools.aggregation.aggregation_insol` first kwarg is now ``energy_normalized``. - * :py:func:`~rdtools.degradation.degradation_year_on_year`, - :py:func:`~rdtools.degradation.degradation_ols` and + * :py:func:`~rdtools.degradation.degradation_year_on_year`, + :py:func:`~rdtools.degradation.degradation_ols` and :py:func:`~rdtools.degradation.degradation_classical_decomposition` first kwarg is now ``energy_normalized``. * :py:func:`~rdtools.filtering.normalized_filter` input kwargs are now ``energy_normalized``, ``energy_normalized_low`` and ``energy_normalized_high``. From cadebc6f7ef3ac4eaa848e62904d6a1879c9814f Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 6 Mar 2026 08:50:39 -0500 Subject: [PATCH 06/18] changelog --- docs/sphinx/source/changelog/pending.rst | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 2fdb3be22..29f438ae2 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -13,3 +13,6 @@ Maintenance ``MANIFEST.in``, and ``rdtools/_version.py``. (:pull:`488`) * Updated ``rdtools/__init__.py`` to use ``importlib.metadata`` for version retrieval instead of versioneer. (:pull:`488`) +* Updated GitHub URLs and references from ``NREL/rdtools`` to + ``NatLabRockies/rdtools`` and email addresses from ``@nrel.gov`` to + ``@nlr.gov``. (:pull:`492`) From b505b3f68d94ba51b56b43736c148502d4accd70 Mon Sep 17 00:00:00 2001 From: Martin Springer <97482055+martin-springer@users.noreply.github.com> Date: Fri, 20 Mar 2026 09:44:34 -0400 Subject: [PATCH 07/18] Migration from setup.py to pyproject.toml (#491) * initial pyproject.toml implementation * changelog --- MANIFEST.in | 5 - docs/sphinx/source/changelog/pending.rst | 15 + pyproject.toml | 105 + rdtools/__init__.py | 8 +- rdtools/_version.py | 683 ------- setup.cfg | 28 - setup.py | 133 -- versioneer.py | 2277 ---------------------- 8 files changed, 126 insertions(+), 3128 deletions(-) delete mode 100644 MANIFEST.in create mode 100644 pyproject.toml delete mode 100644 rdtools/_version.py delete mode 100644 setup.cfg delete mode 100755 setup.py delete mode 100644 versioneer.py diff --git a/MANIFEST.in b/MANIFEST.in deleted file mode 100644 index 4232463ea..000000000 --- a/MANIFEST.in +++ /dev/null @@ -1,5 +0,0 @@ -include versioneer.py -include rdtools/_version.py -include rdtools/data/* -include rdtools/models/* -include LICENSE \ No newline at end of file diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index e69de29bb..2fdb3be22 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -0,0 +1,15 @@ +******* +Pending +******* + +Maintenance +----------- +* Migrated project configuration from ``setup.py``/``setup.cfg`` to + ``pyproject.toml`` using ``setuptools`` as the build backend. + (:pull:`488`) +* Replaced ``versioneer`` with ``setuptools-scm`` for automatic version + management from git tags. (:pull:`488`) +* Removed legacy build files: ``setup.py``, ``setup.cfg``, ``versioneer.py``, + ``MANIFEST.in``, and ``rdtools/_version.py``. (:pull:`488`) +* Updated ``rdtools/__init__.py`` to use ``importlib.metadata`` for version + retrieval instead of versioneer. (:pull:`488`) diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 000000000..4f2817310 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,105 @@ +[build-system] +requires = ["setuptools>=64", "setuptools-scm>=8"] +build-backend = "setuptools.build_meta" + +[project] +name = "rdtools" +dynamic = ["version"] +description = "Functions for reproducible timeseries analysis of photovoltaic systems." +readme = "README.md" +license = {text = "MIT"} +requires-python = ">=3.10" +authors = [ + {name = "Rdtools Python Developers", email = "RdTools@nlr.gov"}, +] +maintainers = [ + {email = "RdTools@nlr.gov"}, +] +keywords = [ + "photovoltaic", + "solar", + "analytics", + "analysis", + "performance", + "degradation", + "PV", +] +classifiers = [ + "Development Status :: 5 - Production/Stable", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + "Intended Audience :: Science/Research", + "Programming Language :: Python", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Topic :: Scientific/Engineering", +] +dependencies = [ + "matplotlib >= 3.5.3", + "numpy >= 1.22.4", + "pandas >= 1.4.4", + "statsmodels >= 0.13.5", + "scipy >= 1.8.1", + "h5py >= 3.7.0", + "plotly >= 4.0.0", + "xgboost >= 1.6.0", + "pvlib >= 0.12.0", + "scikit-learn >= 1.1.3, != 1.6.0", + "arch >= 5.0", + "filterpy >= 1.4.2", +] + +[project.optional-dependencies] +doc = [ + "sphinx==7.4.7", + "nbsphinx==0.9.5", + "nbsphinx-link==1.3.1", + "sphinx_rtd_theme==3.0.1", + "ipython", + "sphinx-gallery==0.18.0", +] +test = [ + "pytest >= 3.10.1", + "pytest-cov", + "coverage", + "flake8", + "nbval >= 0.10.0", + "pytest-mock", +] +all = [ + "coverage", + "flake8", + "ipython", + "nbsphinx==0.9.5", + "nbsphinx-link==1.3.1", + "nbval >= 0.10.0", + "pytest >= 3.10.1", + "pytest-cov", + "pytest-mock", + "sphinx==7.4.7", + "sphinx-gallery==0.18.0", + "sphinx_rtd_theme==3.0.1", +] + +[project.urls] +Homepage = "https://github.com/NREL/rdtools" +"Bug Tracker" = "https://github.com/NREL/rdtools/issues" +Documentation = "https://rdtools.readthedocs.io/" +"Source Code" = "https://github.com/NREL/rdtools" + +[tool.setuptools_scm] + +[tool.setuptools.packages.find] +include = ["rdtools*"] + +[tool.setuptools.package-data] +rdtools = ["data/*", "models/*"] + +[tool.pytest.ini_options] +addopts = "--verbose" +filterwarnings = [ + "ignore:The .* module is currently experimental:UserWarning:rdtools", +] diff --git a/rdtools/__init__.py b/rdtools/__init__.py index 2cd286b00..cdf1d2e6c 100644 --- a/rdtools/__init__.py +++ b/rdtools/__init__.py @@ -40,5 +40,9 @@ from rdtools.utilities import robust_median from rdtools.utilities import robust_mean -from . import _version -__version__ = _version.get_versions()['version'] +from importlib.metadata import version, PackageNotFoundError + +try: + __version__ = version("rdtools") +except PackageNotFoundError: + __version__ = "0+unknown" diff --git a/rdtools/_version.py b/rdtools/_version.py deleted file mode 100644 index 2656d62e8..000000000 --- a/rdtools/_version.py +++ /dev/null @@ -1,683 +0,0 @@ - -# This file helps to compute a version number in source trees obtained from -# git-archive tarball (such as those provided by githubs download-from-tag -# feature). Distribution tarballs (built by setup.py sdist) and build -# directories (produced by setup.py build) will contain a much shorter file -# that just contains the computed version number. - -# This file is released into the public domain. -# Generated by versioneer-0.29 -# https://github.com/python-versioneer/python-versioneer - -"""Git implementation of _version.py.""" - -import errno -import os -import re -import subprocess -import sys -from typing import Any, Callable, Dict, List, Optional, Tuple -import functools - - -def get_keywords() -> Dict[str, str]: - """Get the keywords needed to look up the version information.""" - # these strings will be replaced by git during git-archive. - # setup.py/versioneer.py will grep for the variable names, so they must - # each be defined on a line of their own. _version.py will just call - # get_keywords(). - git_refnames = "$Format:%d$" - git_full = "$Format:%H$" - git_date = "$Format:%ci$" - keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} - return keywords - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - parentdir_prefix: str - versionfile_source: str - verbose: bool - - -def get_config() -> VersioneerConfig: - """Create, populate and return the VersioneerConfig() object.""" - # these strings are filled in when 'setup.py versioneer' creates - # _version.py - cfg = VersioneerConfig() - cfg.VCS = "git" - cfg.style = "pep440" - cfg.tag_prefix = "" - cfg.parentdir_prefix = "rdtools-" - cfg.versionfile_source = "rdtools/_version.py" - cfg.verbose = False - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - if vcs not in HANDLERS: - HANDLERS[vcs] = {} - HANDLERS[vcs][method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %s" % dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %s" % (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %s (error)" % dispcmd) - print("stdout was %s" % stdout) - return None, process.returncode - return stdout, process.returncode - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %s but none started with prefix %s" % - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%s', no digits" % ",".join(refs - tags)) - if verbose: - print("likely tags: %s" % ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %s" % r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %s not under git control" % root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%s'" - % describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%s' doesn't start with prefix '%s'" - print(fmt % (full_tag, tag_prefix)) - pieces["error"] = ("tag '%s' doesn't start with prefix '%s'" - % (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%d.dev%d" % (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%d" % (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%d" % pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%s'" % style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -def get_versions() -> Dict[str, Any]: - """Get version information or return default if unable to do so.""" - # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have - # __file__, we can work backwards from there to the root. Some - # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which - # case we can only use expanded keywords. - - cfg = get_config() - verbose = cfg.verbose - - try: - return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, - verbose) - except NotThisMethod: - pass - - try: - root = os.path.realpath(__file__) - # versionfile_source is the relative path from the top of the source - # tree (where the .git directory might live) to this file. Invert - # this to find the root from __file__. - for _ in cfg.versionfile_source.split('/'): - root = os.path.dirname(root) - except NameError: - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to find root of source tree", - "date": None} - - try: - pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) - return render(pieces, cfg.style) - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - except NotThisMethod: - pass - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to compute version", "date": None} diff --git a/setup.cfg b/setup.cfg deleted file mode 100644 index 36500c527..000000000 --- a/setup.cfg +++ /dev/null @@ -1,28 +0,0 @@ -# See the docstring in versioneer.py for instructions. Note that you must -# re-run 'versioneer.py setup' after changing this section, and commit the -# resulting files. - -[versioneer] -VCS = git -style = pep440 -versionfile_source = rdtools/_version.py -versionfile_build = rdtools/_version.py -tag_prefix = '' -parentdir_prefix = rdtools- - -[metadata] -description-file = README.md - - -[bdist_wheel] -universal = 1 - -[aliases] -test = pytest - -[tool:pytest] -addopts = --verbose -# suppress warnings. syntax is "action:message:category:module:lineno" -# https://docs.python.org/3/library/warnings.html#the-warnings-filter -filterwarnings = - ignore:The .* module is currently experimental:UserWarning:rdtools diff --git a/setup.py b/setup.py deleted file mode 100755 index eecd211ca..000000000 --- a/setup.py +++ /dev/null @@ -1,133 +0,0 @@ -#!/usr/bin/env python - -try: - from setuptools import setup -except ImportError: - raise RuntimeError('setuptools is required') - - -import versioneer - - -DESCRIPTION = 'Functions for reproducible timeseries analysis of photovoltaic systems.' - -LONG_DESCRIPTION = """ -RdTools is an open-source library to support reproducible technical analysis of -PV time series data. The library aims to provide best practice analysis -routines along with the building blocks for users to tailor their own analyses. - -Source code: https://github.com/NREL/rdtools -""" - -DISTNAME = 'rdtools' -LICENSE = 'MIT' -AUTHOR = 'Rdtools Python Developers' -AUTHOR_EMAIL = 'RdTools@nrel.gov' -MAINTAINER_EMAIL = 'RdTools@nrel.gov' - -URL = 'https://github.com/NREL/rdtools' - -SETUP_REQUIRES = [ - 'pytest-runner', -] - -TESTS_REQUIRE = [ - "pytest >= 3.10.1", - "pytest-cov", - "coverage", - "flake8", - "nbval>=0.10.0", - "pytest-mock", -] - -INSTALL_REQUIRES = [ - "matplotlib >= 3.5.3", - "numpy >= 1.22.4", - "pandas >= 1.4.4", - "statsmodels >= 0.13.5", - "scipy >= 1.8.1", - "h5py >= 3.7.0", - "plotly>=4.0.0", - "xgboost >= 1.7.0.post0", - "pvlib >= 0.13.1", - "scikit-learn >= 1.1.3, != 1.6.0", - "arch >= 5.6", - "filterpy >= 1.4.2", -] - -EXTRAS_REQUIRE = { - "doc": [ - "sphinx==7.4.7", - "nbsphinx==0.9.5", - "nbsphinx-link==1.3.1", - "sphinx_rtd_theme==3.0.1", - "ipython", - # sphinx-gallery used indirectly for nbsphinx thumbnail galleries; see: - # https://nbsphinx.readthedocs.io/en/0.6.0/subdir/gallery.html#Creating-Thumbnail-Galleries - "sphinx-gallery==0.18.0", - ], - "test": TESTS_REQUIRE, -} -EXTRAS_REQUIRE['all'] = sorted(set(sum(EXTRAS_REQUIRE.values(), []))) - - -CLASSIFIERS = [ - "Development Status :: 5 - Production/Stable", - "License :: OSI Approved :: MIT License", - "Operating System :: OS Independent", - "Intended Audience :: Science/Research", - "Programming Language :: Python", - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", - "Programming Language :: Python :: 3.12", - "Programming Language :: Python :: 3.13", - "Topic :: Scientific/Engineering", -] - -KEYWORDS = [ - 'photovoltaic', - 'solar', - 'analytics', - 'analysis', - 'performance', - 'degradation', - 'PV' -] - -PROJECT_URLS = { - "Bug Tracker": "https://github.com/NREL/rdtools/issues", - "Documentation": "https://rdtools.readthedocs.io/", - "Source Code": "https://github.com/NREL/rdtools", -} - -setuptools_kwargs = { - 'zip_safe': False, - 'scripts': [], - 'include_package_data': True -} - -# set up packages to be installed and extensions to be compiled -PACKAGES = ['rdtools'] - - -setup(name=DISTNAME, - version=versioneer.get_version(), - cmdclass=versioneer.get_cmdclass(), - packages=PACKAGES, - keywords=KEYWORDS, - setup_requires=SETUP_REQUIRES, - tests_require=TESTS_REQUIRE, - install_requires=INSTALL_REQUIRES, - extras_require=EXTRAS_REQUIRE, - description=DESCRIPTION, - long_description=LONG_DESCRIPTION, - author=AUTHOR, - author_email=AUTHOR_EMAIL, - maintainer_email=MAINTAINER_EMAIL, - license=LICENSE, - url=URL, - project_urls=PROJECT_URLS, - classifiers=CLASSIFIERS, - python_requires='>=3.10', - **setuptools_kwargs) diff --git a/versioneer.py b/versioneer.py deleted file mode 100644 index 1e3753e63..000000000 --- a/versioneer.py +++ /dev/null @@ -1,2277 +0,0 @@ - -# Version: 0.29 - -"""The Versioneer - like a rocketeer, but for versions. - -The Versioneer -============== - -* like a rocketeer, but for versions! -* https://github.com/python-versioneer/python-versioneer -* Brian Warner -* License: Public Domain (Unlicense) -* Compatible with: Python 3.7, 3.8, 3.9, 3.10, 3.11 and pypy3 -* [![Latest Version][pypi-image]][pypi-url] -* [![Build Status][travis-image]][travis-url] - -This is a tool for managing a recorded version number in setuptools-based -python projects. The goal is to remove the tedious and error-prone "update -the embedded version string" step from your release process. Making a new -release should be as easy as recording a new tag in your version-control -system, and maybe making new tarballs. - - -## Quick Install - -Versioneer provides two installation modes. The "classic" vendored mode installs -a copy of versioneer into your repository. The experimental build-time dependency mode -is intended to allow you to skip this step and simplify the process of upgrading. - -### Vendored mode - -* `pip install versioneer` to somewhere in your $PATH - * A [conda-forge recipe](https://github.com/conda-forge/versioneer-feedstock) is - available, so you can also use `conda install -c conda-forge versioneer` -* add a `[tool.versioneer]` section to your `pyproject.toml` or a - `[versioneer]` section to your `setup.cfg` (see [Install](INSTALL.md)) - * Note that you will need to add `tomli; python_version < "3.11"` to your - build-time dependencies if you use `pyproject.toml` -* run `versioneer install --vendor` in your source tree, commit the results -* verify version information with `python setup.py version` - -### Build-time dependency mode - -* `pip install versioneer` to somewhere in your $PATH - * A [conda-forge recipe](https://github.com/conda-forge/versioneer-feedstock) is - available, so you can also use `conda install -c conda-forge versioneer` -* add a `[tool.versioneer]` section to your `pyproject.toml` or a - `[versioneer]` section to your `setup.cfg` (see [Install](INSTALL.md)) -* add `versioneer` (with `[toml]` extra, if configuring in `pyproject.toml`) - to the `requires` key of the `build-system` table in `pyproject.toml`: - ```toml - [build-system] - requires = ["setuptools", "versioneer[toml]"] - build-backend = "setuptools.build_meta" - ``` -* run `versioneer install --no-vendor` in your source tree, commit the results -* verify version information with `python setup.py version` - -## Version Identifiers - -Source trees come from a variety of places: - -* a version-control system checkout (mostly used by developers) -* a nightly tarball, produced by build automation -* a snapshot tarball, produced by a web-based VCS browser, like github's - "tarball from tag" feature -* a release tarball, produced by "setup.py sdist", distributed through PyPI - -Within each source tree, the version identifier (either a string or a number, -this tool is format-agnostic) can come from a variety of places: - -* ask the VCS tool itself, e.g. "git describe" (for checkouts), which knows - about recent "tags" and an absolute revision-id -* the name of the directory into which the tarball was unpacked -* an expanded VCS keyword ($Id$, etc) -* a `_version.py` created by some earlier build step - -For released software, the version identifier is closely related to a VCS -tag. Some projects use tag names that include more than just the version -string (e.g. "myproject-1.2" instead of just "1.2"), in which case the tool -needs to strip the tag prefix to extract the version identifier. For -unreleased software (between tags), the version identifier should provide -enough information to help developers recreate the same tree, while also -giving them an idea of roughly how old the tree is (after version 1.2, before -version 1.3). Many VCS systems can report a description that captures this, -for example `git describe --tags --dirty --always` reports things like -"0.7-1-g574ab98-dirty" to indicate that the checkout is one revision past the -0.7 tag, has a unique revision id of "574ab98", and is "dirty" (it has -uncommitted changes). - -The version identifier is used for multiple purposes: - -* to allow the module to self-identify its version: `myproject.__version__` -* to choose a name and prefix for a 'setup.py sdist' tarball - -## Theory of Operation - -Versioneer works by adding a special `_version.py` file into your source -tree, where your `__init__.py` can import it. This `_version.py` knows how to -dynamically ask the VCS tool for version information at import time. - -`_version.py` also contains `$Revision$` markers, and the installation -process marks `_version.py` to have this marker rewritten with a tag name -during the `git archive` command. As a result, generated tarballs will -contain enough information to get the proper version. - -To allow `setup.py` to compute a version too, a `versioneer.py` is added to -the top level of your source tree, next to `setup.py` and the `setup.cfg` -that configures it. This overrides several distutils/setuptools commands to -compute the version when invoked, and changes `setup.py build` and `setup.py -sdist` to replace `_version.py` with a small static file that contains just -the generated version data. - -## Installation - -See [INSTALL.md](./INSTALL.md) for detailed installation instructions. - -## Version-String Flavors - -Code which uses Versioneer can learn about its version string at runtime by -importing `_version` from your main `__init__.py` file and running the -`get_versions()` function. From the "outside" (e.g. in `setup.py`), you can -import the top-level `versioneer.py` and run `get_versions()`. - -Both functions return a dictionary with different flavors of version -information: - -* `['version']`: A condensed version string, rendered using the selected - style. This is the most commonly used value for the project's version - string. The default "pep440" style yields strings like `0.11`, - `0.11+2.g1076c97`, or `0.11+2.g1076c97.dirty`. See the "Styles" section - below for alternative styles. - -* `['full-revisionid']`: detailed revision identifier. For Git, this is the - full SHA1 commit id, e.g. "1076c978a8d3cfc70f408fe5974aa6c092c949ac". - -* `['date']`: Date and time of the latest `HEAD` commit. For Git, it is the - commit date in ISO 8601 format. This will be None if the date is not - available. - -* `['dirty']`: a boolean, True if the tree has uncommitted changes. Note that - this is only accurate if run in a VCS checkout, otherwise it is likely to - be False or None - -* `['error']`: if the version string could not be computed, this will be set - to a string describing the problem, otherwise it will be None. It may be - useful to throw an exception in setup.py if this is set, to avoid e.g. - creating tarballs with a version string of "unknown". - -Some variants are more useful than others. Including `full-revisionid` in a -bug report should allow developers to reconstruct the exact code being tested -(or indicate the presence of local changes that should be shared with the -developers). `version` is suitable for display in an "about" box or a CLI -`--version` output: it can be easily compared against release notes and lists -of bugs fixed in various releases. - -The installer adds the following text to your `__init__.py` to place a basic -version in `YOURPROJECT.__version__`: - - from ._version import get_versions - __version__ = get_versions()['version'] - del get_versions - -## Styles - -The setup.cfg `style=` configuration controls how the VCS information is -rendered into a version string. - -The default style, "pep440", produces a PEP440-compliant string, equal to the -un-prefixed tag name for actual releases, and containing an additional "local -version" section with more detail for in-between builds. For Git, this is -TAG[+DISTANCE.gHEX[.dirty]] , using information from `git describe --tags ---dirty --always`. For example "0.11+2.g1076c97.dirty" indicates that the -tree is like the "1076c97" commit but has uncommitted changes (".dirty"), and -that this commit is two revisions ("+2") beyond the "0.11" tag. For released -software (exactly equal to a known tag), the identifier will only contain the -stripped tag, e.g. "0.11". - -Other styles are available. See [details.md](details.md) in the Versioneer -source tree for descriptions. - -## Debugging - -Versioneer tries to avoid fatal errors: if something goes wrong, it will tend -to return a version of "0+unknown". To investigate the problem, run `setup.py -version`, which will run the version-lookup code in a verbose mode, and will -display the full contents of `get_versions()` (including the `error` string, -which may help identify what went wrong). - -## Known Limitations - -Some situations are known to cause problems for Versioneer. This details the -most significant ones. More can be found on Github -[issues page](https://github.com/python-versioneer/python-versioneer/issues). - -### Subprojects - -Versioneer has limited support for source trees in which `setup.py` is not in -the root directory (e.g. `setup.py` and `.git/` are *not* siblings). The are -two common reasons why `setup.py` might not be in the root: - -* Source trees which contain multiple subprojects, such as - [Buildbot](https://github.com/buildbot/buildbot), which contains both - "master" and "slave" subprojects, each with their own `setup.py`, - `setup.cfg`, and `tox.ini`. Projects like these produce multiple PyPI - distributions (and upload multiple independently-installable tarballs). -* Source trees whose main purpose is to contain a C library, but which also - provide bindings to Python (and perhaps other languages) in subdirectories. - -Versioneer will look for `.git` in parent directories, and most operations -should get the right version string. However `pip` and `setuptools` have bugs -and implementation details which frequently cause `pip install .` from a -subproject directory to fail to find a correct version string (so it usually -defaults to `0+unknown`). - -`pip install --editable .` should work correctly. `setup.py install` might -work too. - -Pip-8.1.1 is known to have this problem, but hopefully it will get fixed in -some later version. - -[Bug #38](https://github.com/python-versioneer/python-versioneer/issues/38) is tracking -this issue. The discussion in -[PR #61](https://github.com/python-versioneer/python-versioneer/pull/61) describes the -issue from the Versioneer side in more detail. -[pip PR#3176](https://github.com/pypa/pip/pull/3176) and -[pip PR#3615](https://github.com/pypa/pip/pull/3615) contain work to improve -pip to let Versioneer work correctly. - -Versioneer-0.16 and earlier only looked for a `.git` directory next to the -`setup.cfg`, so subprojects were completely unsupported with those releases. - -### Editable installs with setuptools <= 18.5 - -`setup.py develop` and `pip install --editable .` allow you to install a -project into a virtualenv once, then continue editing the source code (and -test) without re-installing after every change. - -"Entry-point scripts" (`setup(entry_points={"console_scripts": ..})`) are a -convenient way to specify executable scripts that should be installed along -with the python package. - -These both work as expected when using modern setuptools. When using -setuptools-18.5 or earlier, however, certain operations will cause -`pkg_resources.DistributionNotFound` errors when running the entrypoint -script, which must be resolved by re-installing the package. This happens -when the install happens with one version, then the egg_info data is -regenerated while a different version is checked out. Many setup.py commands -cause egg_info to be rebuilt (including `sdist`, `wheel`, and installing into -a different virtualenv), so this can be surprising. - -[Bug #83](https://github.com/python-versioneer/python-versioneer/issues/83) describes -this one, but upgrading to a newer version of setuptools should probably -resolve it. - - -## Updating Versioneer - -To upgrade your project to a new release of Versioneer, do the following: - -* install the new Versioneer (`pip install -U versioneer` or equivalent) -* edit `setup.cfg` and `pyproject.toml`, if necessary, - to include any new configuration settings indicated by the release notes. - See [UPGRADING](./UPGRADING.md) for details. -* re-run `versioneer install --[no-]vendor` in your source tree, to replace - `SRC/_version.py` -* commit any changed files - -## Future Directions - -This tool is designed to make it easily extended to other version-control -systems: all VCS-specific components are in separate directories like -src/git/ . The top-level `versioneer.py` script is assembled from these -components by running make-versioneer.py . In the future, make-versioneer.py -will take a VCS name as an argument, and will construct a version of -`versioneer.py` that is specific to the given VCS. It might also take the -configuration arguments that are currently provided manually during -installation by editing setup.py . Alternatively, it might go the other -direction and include code from all supported VCS systems, reducing the -number of intermediate scripts. - -## Similar projects - -* [setuptools_scm](https://github.com/pypa/setuptools_scm/) - a non-vendored build-time - dependency -* [minver](https://github.com/jbweston/miniver) - a lightweight reimplementation of - versioneer -* [versioningit](https://github.com/jwodder/versioningit) - a PEP 518-based setuptools - plugin - -## License - -To make Versioneer easier to embed, all its code is dedicated to the public -domain. The `_version.py` that it creates is also in the public domain. -Specifically, both are released under the "Unlicense", as described in -https://unlicense.org/. - -[pypi-image]: https://img.shields.io/pypi/v/versioneer.svg -[pypi-url]: https://pypi.python.org/pypi/versioneer/ -[travis-image]: -https://img.shields.io/travis/com/python-versioneer/python-versioneer.svg -[travis-url]: https://travis-ci.com/github/python-versioneer/python-versioneer - -""" -# pylint:disable=invalid-name,import-outside-toplevel,missing-function-docstring -# pylint:disable=missing-class-docstring,too-many-branches,too-many-statements -# pylint:disable=raise-missing-from,too-many-lines,too-many-locals,import-error -# pylint:disable=too-few-public-methods,redefined-outer-name,consider-using-with -# pylint:disable=attribute-defined-outside-init,too-many-arguments - -import configparser -import errno -import json -import os -import re -import subprocess -import sys -from pathlib import Path -from typing import Any, Callable, cast, Dict, List, Optional, Tuple, Union -from typing import NoReturn -import functools - -have_tomllib = True -if sys.version_info >= (3, 11): - import tomllib -else: - try: - import tomli as tomllib - except ImportError: - have_tomllib = False - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - versionfile_source: str - versionfile_build: Optional[str] - parentdir_prefix: Optional[str] - verbose: Optional[bool] - - -def get_root() -> str: - """Get the project root directory. - - We require that all commands are run from the project root, i.e. the - directory that contains setup.py, setup.cfg, and versioneer.py . - """ - root = os.path.realpath(os.path.abspath(os.getcwd())) - setup_py = os.path.join(root, "setup.py") - pyproject_toml = os.path.join(root, "pyproject.toml") - versioneer_py = os.path.join(root, "versioneer.py") - if not ( - os.path.exists(setup_py) - or os.path.exists(pyproject_toml) - or os.path.exists(versioneer_py) - ): - # allow 'python path/to/setup.py COMMAND' - root = os.path.dirname(os.path.realpath(os.path.abspath(sys.argv[0]))) - setup_py = os.path.join(root, "setup.py") - pyproject_toml = os.path.join(root, "pyproject.toml") - versioneer_py = os.path.join(root, "versioneer.py") - if not ( - os.path.exists(setup_py) - or os.path.exists(pyproject_toml) - or os.path.exists(versioneer_py) - ): - err = ("Versioneer was unable to run the project root directory. " - "Versioneer requires setup.py to be executed from " - "its immediate directory (like 'python setup.py COMMAND'), " - "or in a way that lets it use sys.argv[0] to find the root " - "(like 'python path/to/setup.py COMMAND').") - raise VersioneerBadRootError(err) - try: - # Certain runtime workflows (setup.py install/develop in a setuptools - # tree) execute all dependencies in a single python process, so - # "versioneer" may be imported multiple times, and python's shared - # module-import table will cache the first one. So we can't use - # os.path.dirname(__file__), as that will find whichever - # versioneer.py was first imported, even in later projects. - my_path = os.path.realpath(os.path.abspath(__file__)) - me_dir = os.path.normcase(os.path.splitext(my_path)[0]) - vsr_dir = os.path.normcase(os.path.splitext(versioneer_py)[0]) - if me_dir != vsr_dir and "VERSIONEER_PEP518" not in globals(): - print("Warning: build in %s is using versioneer.py from %s" - % (os.path.dirname(my_path), versioneer_py)) - except NameError: - pass - return root - - -def get_config_from_root(root: str) -> VersioneerConfig: - """Read the project setup.cfg file to determine Versioneer config.""" - # This might raise OSError (if setup.cfg is missing), or - # configparser.NoSectionError (if it lacks a [versioneer] section), or - # configparser.NoOptionError (if it lacks "VCS="). See the docstring at - # the top of versioneer.py for instructions on writing your setup.cfg . - root_pth = Path(root) - pyproject_toml = root_pth / "pyproject.toml" - setup_cfg = root_pth / "setup.cfg" - section: Union[Dict[str, Any], configparser.SectionProxy, None] = None - if pyproject_toml.exists() and have_tomllib: - try: - with open(pyproject_toml, 'rb') as fobj: - pp = tomllib.load(fobj) - section = pp['tool']['versioneer'] - except (tomllib.TOMLDecodeError, KeyError) as e: - print(f"Failed to load config from {pyproject_toml}: {e}") - print("Try to load it from setup.cfg") - if not section: - parser = configparser.ConfigParser() - with open(setup_cfg) as cfg_file: - parser.read_file(cfg_file) - parser.get("versioneer", "VCS") # raise error if missing - - section = parser["versioneer"] - - # `cast`` really shouldn't be used, but its simplest for the - # common VersioneerConfig users at the moment. We verify against - # `None` values elsewhere where it matters - - cfg = VersioneerConfig() - cfg.VCS = section['VCS'] - cfg.style = section.get("style", "") - cfg.versionfile_source = cast(str, section.get("versionfile_source")) - cfg.versionfile_build = section.get("versionfile_build") - cfg.tag_prefix = cast(str, section.get("tag_prefix")) - if cfg.tag_prefix in ("''", '""', None): - cfg.tag_prefix = "" - cfg.parentdir_prefix = section.get("parentdir_prefix") - if isinstance(section, configparser.SectionProxy): - # Make sure configparser translates to bool - cfg.verbose = section.getboolean("verbose") - else: - cfg.verbose = section.get("verbose") - - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -# these dictionaries contain VCS-specific tools -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - HANDLERS.setdefault(vcs, {})[method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %s" % dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %s" % (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %s (error)" % dispcmd) - print("stdout was %s" % stdout) - return None, process.returncode - return stdout, process.returncode - - -LONG_VERSION_PY['git'] = r''' -# This file helps to compute a version number in source trees obtained from -# git-archive tarball (such as those provided by githubs download-from-tag -# feature). Distribution tarballs (built by setup.py sdist) and build -# directories (produced by setup.py build) will contain a much shorter file -# that just contains the computed version number. - -# This file is released into the public domain. -# Generated by versioneer-0.29 -# https://github.com/python-versioneer/python-versioneer - -"""Git implementation of _version.py.""" - -import errno -import os -import re -import subprocess -import sys -from typing import Any, Callable, Dict, List, Optional, Tuple -import functools - - -def get_keywords() -> Dict[str, str]: - """Get the keywords needed to look up the version information.""" - # these strings will be replaced by git during git-archive. - # setup.py/versioneer.py will grep for the variable names, so they must - # each be defined on a line of their own. _version.py will just call - # get_keywords(). - git_refnames = "%(DOLLAR)sFormat:%%d%(DOLLAR)s" - git_full = "%(DOLLAR)sFormat:%%H%(DOLLAR)s" - git_date = "%(DOLLAR)sFormat:%%ci%(DOLLAR)s" - keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} - return keywords - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - parentdir_prefix: str - versionfile_source: str - verbose: bool - - -def get_config() -> VersioneerConfig: - """Create, populate and return the VersioneerConfig() object.""" - # these strings are filled in when 'setup.py versioneer' creates - # _version.py - cfg = VersioneerConfig() - cfg.VCS = "git" - cfg.style = "%(STYLE)s" - cfg.tag_prefix = "%(TAG_PREFIX)s" - cfg.parentdir_prefix = "%(PARENTDIR_PREFIX)s" - cfg.versionfile_source = "%(VERSIONFILE_SOURCE)s" - cfg.verbose = False - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - if vcs not in HANDLERS: - HANDLERS[vcs] = {} - HANDLERS[vcs][method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %%s" %% dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %%s" %% (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %%s (error)" %% dispcmd) - print("stdout was %%s" %% stdout) - return None, process.returncode - return stdout, process.returncode - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %%s but none started with prefix %%s" %% - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %%d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%%s', no digits" %% ",".join(refs - tags)) - if verbose: - print("likely tags: %%s" %% ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %%s" %% r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %%s not under git control" %% root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%%s'" - %% describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%%s' doesn't start with prefix '%%s'" - print(fmt %% (full_tag, tag_prefix)) - pieces["error"] = ("tag '%%s' doesn't start with prefix '%%s'" - %% (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%%d.g%%s" %% (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%%d.g%%s" %% (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%%d.dev%%d" %% (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%%d" %% (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%%d" %% pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%%s" %% pieces["short"] - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%%s" %% pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%%s" %% pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%%s" %% pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%%s'" %% style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -def get_versions() -> Dict[str, Any]: - """Get version information or return default if unable to do so.""" - # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have - # __file__, we can work backwards from there to the root. Some - # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which - # case we can only use expanded keywords. - - cfg = get_config() - verbose = cfg.verbose - - try: - return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, - verbose) - except NotThisMethod: - pass - - try: - root = os.path.realpath(__file__) - # versionfile_source is the relative path from the top of the source - # tree (where the .git directory might live) to this file. Invert - # this to find the root from __file__. - for _ in cfg.versionfile_source.split('/'): - root = os.path.dirname(root) - except NameError: - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to find root of source tree", - "date": None} - - try: - pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) - return render(pieces, cfg.style) - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - except NotThisMethod: - pass - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to compute version", "date": None} -''' - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%s', no digits" % ",".join(refs - tags)) - if verbose: - print("likely tags: %s" % ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %s" % r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %s not under git control" % root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%s'" - % describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%s' doesn't start with prefix '%s'" - print(fmt % (full_tag, tag_prefix)) - pieces["error"] = ("tag '%s' doesn't start with prefix '%s'" - % (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def do_vcs_install(versionfile_source: str, ipy: Optional[str]) -> None: - """Git-specific installation logic for Versioneer. - - For Git, this means creating/changing .gitattributes to mark _version.py - for export-subst keyword substitution. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - files = [versionfile_source] - if ipy: - files.append(ipy) - if "VERSIONEER_PEP518" not in globals(): - try: - my_path = __file__ - if my_path.endswith((".pyc", ".pyo")): - my_path = os.path.splitext(my_path)[0] + ".py" - versioneer_file = os.path.relpath(my_path) - except NameError: - versioneer_file = "versioneer.py" - files.append(versioneer_file) - present = False - try: - with open(".gitattributes", "r") as fobj: - for line in fobj: - if line.strip().startswith(versionfile_source): - if "export-subst" in line.strip().split()[1:]: - present = True - break - except OSError: - pass - if not present: - with open(".gitattributes", "a+") as fobj: - fobj.write(f"{versionfile_source} export-subst\n") - files.append(".gitattributes") - run_command(GITS, ["add", "--"] + files) - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %s but none started with prefix %s" % - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -SHORT_VERSION_PY = """ -# This file was generated by 'versioneer.py' (0.29) from -# revision-control system data, or from the parent directory name of an -# unpacked source archive. Distribution tarballs contain a pre-generated copy -# of this file. - -import json - -version_json = ''' -%s -''' # END VERSION_JSON - - -def get_versions(): - return json.loads(version_json) -""" - - -def versions_from_file(filename: str) -> Dict[str, Any]: - """Try to determine the version from _version.py if present.""" - try: - with open(filename) as f: - contents = f.read() - except OSError: - raise NotThisMethod("unable to read _version.py") - mo = re.search(r"version_json = '''\n(.*)''' # END VERSION_JSON", - contents, re.M | re.S) - if not mo: - mo = re.search(r"version_json = '''\r\n(.*)''' # END VERSION_JSON", - contents, re.M | re.S) - if not mo: - raise NotThisMethod("no version_json in _version.py") - return json.loads(mo.group(1)) - - -def write_to_version_file(filename: str, versions: Dict[str, Any]) -> None: - """Write the given version number to the given _version.py file.""" - contents = json.dumps(versions, sort_keys=True, - indent=1, separators=(",", ": ")) - with open(filename, "w") as f: - f.write(SHORT_VERSION_PY % contents) - - print("set %s to '%s'" % (filename, versions["version"])) - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%d.dev%d" % (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%d" % (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%d" % pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%s'" % style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -class VersioneerBadRootError(Exception): - """The project root directory is unknown or missing key files.""" - - -def get_versions(verbose: bool = False) -> Dict[str, Any]: - """Get the project version from whatever source is available. - - Returns dict with two keys: 'version' and 'full'. - """ - if "versioneer" in sys.modules: - # see the discussion in cmdclass.py:get_cmdclass() - del sys.modules["versioneer"] - - root = get_root() - cfg = get_config_from_root(root) - - assert cfg.VCS is not None, "please set [versioneer]VCS= in setup.cfg" - handlers = HANDLERS.get(cfg.VCS) - assert handlers, "unrecognized VCS '%s'" % cfg.VCS - verbose = verbose or bool(cfg.verbose) # `bool()` used to avoid `None` - assert cfg.versionfile_source is not None, \ - "please set versioneer.versionfile_source" - assert cfg.tag_prefix is not None, "please set versioneer.tag_prefix" - - versionfile_abs = os.path.join(root, cfg.versionfile_source) - - # extract version from first of: _version.py, VCS command (e.g. 'git - # describe'), parentdir. This is meant to work for developers using a - # source checkout, for users of a tarball created by 'setup.py sdist', - # and for users of a tarball/zipball created by 'git archive' or github's - # download-from-tag feature or the equivalent in other VCSes. - - get_keywords_f = handlers.get("get_keywords") - from_keywords_f = handlers.get("keywords") - if get_keywords_f and from_keywords_f: - try: - keywords = get_keywords_f(versionfile_abs) - ver = from_keywords_f(keywords, cfg.tag_prefix, verbose) - if verbose: - print("got version from expanded keyword %s" % ver) - return ver - except NotThisMethod: - pass - - try: - ver = versions_from_file(versionfile_abs) - if verbose: - print("got version from file %s %s" % (versionfile_abs, ver)) - return ver - except NotThisMethod: - pass - - from_vcs_f = handlers.get("pieces_from_vcs") - if from_vcs_f: - try: - pieces = from_vcs_f(cfg.tag_prefix, root, verbose) - ver = render(pieces, cfg.style) - if verbose: - print("got version from VCS %s" % ver) - return ver - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - ver = versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - if verbose: - print("got version from parentdir %s" % ver) - return ver - except NotThisMethod: - pass - - if verbose: - print("unable to compute version") - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, "error": "unable to compute version", - "date": None} - - -def get_version() -> str: - """Get the short version string for this project.""" - return get_versions()["version"] - - -def get_cmdclass(cmdclass: Optional[Dict[str, Any]] = None): - """Get the custom setuptools subclasses used by Versioneer. - - If the package uses a different cmdclass (e.g. one from numpy), it - should be provide as an argument. - """ - if "versioneer" in sys.modules: - del sys.modules["versioneer"] - # this fixes the "python setup.py develop" case (also 'install' and - # 'easy_install .'), in which subdependencies of the main project are - # built (using setup.py bdist_egg) in the same python process. Assume - # a main project A and a dependency B, which use different versions - # of Versioneer. A's setup.py imports A's Versioneer, leaving it in - # sys.modules by the time B's setup.py is executed, causing B to run - # with the wrong versioneer. Setuptools wraps the sub-dep builds in a - # sandbox that restores sys.modules to it's pre-build state, so the - # parent is protected against the child's "import versioneer". By - # removing ourselves from sys.modules here, before the child build - # happens, we protect the child from the parent's versioneer too. - # Also see https://github.com/python-versioneer/python-versioneer/issues/52 - - cmds = {} if cmdclass is None else cmdclass.copy() - - # we add "version" to setuptools - from setuptools import Command - - class cmd_version(Command): - description = "report generated version string" - user_options: List[Tuple[str, str, str]] = [] - boolean_options: List[str] = [] - - def initialize_options(self) -> None: - pass - - def finalize_options(self) -> None: - pass - - def run(self) -> None: - vers = get_versions(verbose=True) - print("Version: %s" % vers["version"]) - print(" full-revisionid: %s" % vers.get("full-revisionid")) - print(" dirty: %s" % vers.get("dirty")) - print(" date: %s" % vers.get("date")) - if vers["error"]: - print(" error: %s" % vers["error"]) - cmds["version"] = cmd_version - - # we override "build_py" in setuptools - # - # most invocation pathways end up running build_py: - # distutils/build -> build_py - # distutils/install -> distutils/build ->.. - # setuptools/bdist_wheel -> distutils/install ->.. - # setuptools/bdist_egg -> distutils/install_lib -> build_py - # setuptools/install -> bdist_egg ->.. - # setuptools/develop -> ? - # pip install: - # copies source tree to a tempdir before running egg_info/etc - # if .git isn't copied too, 'git describe' will fail - # then does setup.py bdist_wheel, or sometimes setup.py install - # setup.py egg_info -> ? - - # pip install -e . and setuptool/editable_wheel will invoke build_py - # but the build_py command is not expected to copy any files. - - # we override different "build_py" commands for both environments - if 'build_py' in cmds: - _build_py: Any = cmds['build_py'] - else: - from setuptools.command.build_py import build_py as _build_py - - class cmd_build_py(_build_py): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - _build_py.run(self) - if getattr(self, "editable_mode", False): - # During editable installs `.py` and data files are - # not copied to build_lib - return - # now locate _version.py in the new build/ directory and replace - # it with an updated value - if cfg.versionfile_build: - target_versionfile = os.path.join(self.build_lib, - cfg.versionfile_build) - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - cmds["build_py"] = cmd_build_py - - if 'build_ext' in cmds: - _build_ext: Any = cmds['build_ext'] - else: - from setuptools.command.build_ext import build_ext as _build_ext - - class cmd_build_ext(_build_ext): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - _build_ext.run(self) - if self.inplace: - # build_ext --inplace will only build extensions in - # build/lib<..> dir with no _version.py to write to. - # As in place builds will already have a _version.py - # in the module dir, we do not need to write one. - return - # now locate _version.py in the new build/ directory and replace - # it with an updated value - if not cfg.versionfile_build: - return - target_versionfile = os.path.join(self.build_lib, - cfg.versionfile_build) - if not os.path.exists(target_versionfile): - print(f"Warning: {target_versionfile} does not exist, skipping " - "version update. This can happen if you are running build_ext " - "without first running build_py.") - return - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - cmds["build_ext"] = cmd_build_ext - - if "cx_Freeze" in sys.modules: # cx_freeze enabled? - from cx_Freeze.dist import build_exe as _build_exe # type: ignore - # nczeczulin reports that py2exe won't like the pep440-style string - # as FILEVERSION, but it can be used for PRODUCTVERSION, e.g. - # setup(console=[{ - # "version": versioneer.get_version().split("+", 1)[0], # FILEVERSION - # "product_version": versioneer.get_version(), - # ... - - class cmd_build_exe(_build_exe): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - target_versionfile = cfg.versionfile_source - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - - _build_exe.run(self) - os.unlink(target_versionfile) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % - {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - cmds["build_exe"] = cmd_build_exe - del cmds["build_py"] - - if 'py2exe' in sys.modules: # py2exe enabled? - try: - from py2exe.setuptools_buildexe import py2exe as _py2exe # type: ignore - except ImportError: - from py2exe.distutils_buildexe import py2exe as _py2exe # type: ignore - - class cmd_py2exe(_py2exe): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - target_versionfile = cfg.versionfile_source - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - - _py2exe.run(self) - os.unlink(target_versionfile) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % - {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - cmds["py2exe"] = cmd_py2exe - - # sdist farms its file list building out to egg_info - if 'egg_info' in cmds: - _egg_info: Any = cmds['egg_info'] - else: - from setuptools.command.egg_info import egg_info as _egg_info - - class cmd_egg_info(_egg_info): - def find_sources(self) -> None: - # egg_info.find_sources builds the manifest list and writes it - # in one shot - super().find_sources() - - # Modify the filelist and normalize it - root = get_root() - cfg = get_config_from_root(root) - self.filelist.append('versioneer.py') - if cfg.versionfile_source: - # There are rare cases where versionfile_source might not be - # included by default, so we must be explicit - self.filelist.append(cfg.versionfile_source) - self.filelist.sort() - self.filelist.remove_duplicates() - - # The write method is hidden in the manifest_maker instance that - # generated the filelist and was thrown away - # We will instead replicate their final normalization (to unicode, - # and POSIX-style paths) - from setuptools import unicode_utils - normalized = [unicode_utils.filesys_decode(f).replace(os.sep, '/') - for f in self.filelist.files] - - manifest_filename = os.path.join(self.egg_info, 'SOURCES.txt') - with open(manifest_filename, 'w') as fobj: - fobj.write('\n'.join(normalized)) - - cmds['egg_info'] = cmd_egg_info - - # we override different "sdist" commands for both environments - if 'sdist' in cmds: - _sdist: Any = cmds['sdist'] - else: - from setuptools.command.sdist import sdist as _sdist - - class cmd_sdist(_sdist): - def run(self) -> None: - versions = get_versions() - self._versioneer_generated_versions = versions - # unless we update this, the command will keep using the old - # version - self.distribution.metadata.version = versions["version"] - return _sdist.run(self) - - def make_release_tree(self, base_dir: str, files: List[str]) -> None: - root = get_root() - cfg = get_config_from_root(root) - _sdist.make_release_tree(self, base_dir, files) - # now locate _version.py in the new base_dir directory - # (remembering that it may be a hardlink) and replace it with an - # updated value - target_versionfile = os.path.join(base_dir, cfg.versionfile_source) - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, - self._versioneer_generated_versions) - cmds["sdist"] = cmd_sdist - - return cmds - - -CONFIG_ERROR = """ -setup.cfg is missing the necessary Versioneer configuration. You need -a section like: - - [versioneer] - VCS = git - style = pep440 - versionfile_source = src/myproject/_version.py - versionfile_build = myproject/_version.py - tag_prefix = - parentdir_prefix = myproject- - -You will also need to edit your setup.py to use the results: - - import versioneer - setup(version=versioneer.get_version(), - cmdclass=versioneer.get_cmdclass(), ...) - -Please read the docstring in ./versioneer.py for configuration instructions, -edit setup.cfg, and re-run the installer or 'python versioneer.py setup'. -""" - -SAMPLE_CONFIG = """ -# See the docstring in versioneer.py for instructions. Note that you must -# re-run 'versioneer.py setup' after changing this section, and commit the -# resulting files. - -[versioneer] -#VCS = git -#style = pep440 -#versionfile_source = -#versionfile_build = -#tag_prefix = -#parentdir_prefix = - -""" - -OLD_SNIPPET = """ -from ._version import get_versions -__version__ = get_versions()['version'] -del get_versions -""" - -INIT_PY_SNIPPET = """ -from . import {0} -__version__ = {0}.get_versions()['version'] -""" - - -def do_setup() -> int: - """Do main VCS-independent setup function for installing Versioneer.""" - root = get_root() - try: - cfg = get_config_from_root(root) - except (OSError, configparser.NoSectionError, - configparser.NoOptionError) as e: - if isinstance(e, (OSError, configparser.NoSectionError)): - print("Adding sample versioneer config to setup.cfg", - file=sys.stderr) - with open(os.path.join(root, "setup.cfg"), "a") as f: - f.write(SAMPLE_CONFIG) - print(CONFIG_ERROR, file=sys.stderr) - return 1 - - print(" creating %s" % cfg.versionfile_source) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - - ipy = os.path.join(os.path.dirname(cfg.versionfile_source), - "__init__.py") - maybe_ipy: Optional[str] = ipy - if os.path.exists(ipy): - try: - with open(ipy, "r") as f: - old = f.read() - except OSError: - old = "" - module = os.path.splitext(os.path.basename(cfg.versionfile_source))[0] - snippet = INIT_PY_SNIPPET.format(module) - if OLD_SNIPPET in old: - print(" replacing boilerplate in %s" % ipy) - with open(ipy, "w") as f: - f.write(old.replace(OLD_SNIPPET, snippet)) - elif snippet not in old: - print(" appending to %s" % ipy) - with open(ipy, "a") as f: - f.write(snippet) - else: - print(" %s unmodified" % ipy) - else: - print(" %s doesn't exist, ok" % ipy) - maybe_ipy = None - - # Make VCS-specific changes. For git, this means creating/changing - # .gitattributes to mark _version.py for export-subst keyword - # substitution. - do_vcs_install(cfg.versionfile_source, maybe_ipy) - return 0 - - -def scan_setup_py() -> int: - """Validate the contents of setup.py against Versioneer's expectations.""" - found = set() - setters = False - errors = 0 - with open("setup.py", "r") as f: - for line in f.readlines(): - if "import versioneer" in line: - found.add("import") - if "versioneer.get_cmdclass()" in line: - found.add("cmdclass") - if "versioneer.get_version()" in line: - found.add("get_version") - if "versioneer.VCS" in line: - setters = True - if "versioneer.versionfile_source" in line: - setters = True - if len(found) != 3: - print("") - print("Your setup.py appears to be missing some important items") - print("(but I might be wrong). Please make sure it has something") - print("roughly like the following:") - print("") - print(" import versioneer") - print(" setup( version=versioneer.get_version(),") - print(" cmdclass=versioneer.get_cmdclass(), ...)") - print("") - errors += 1 - if setters: - print("You should remove lines like 'versioneer.VCS = ' and") - print("'versioneer.versionfile_source = ' . This configuration") - print("now lives in setup.cfg, and should be removed from setup.py") - print("") - errors += 1 - return errors - - -def setup_command() -> NoReturn: - """Set up Versioneer and exit with appropriate error code.""" - errors = do_setup() - errors += scan_setup_py() - sys.exit(1 if errors else 0) - - -if __name__ == "__main__": - cmd = sys.argv[1] - if cmd == "setup": - setup_command() From 3d53bd1590d2f8143153f06edb8f1a9a29ada622 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 09:50:32 -0400 Subject: [PATCH 08/18] update PVDAQ citation in notebooks --- docs/Multi-year_on_year_example.ipynb | 6 +- docs/TrendAnalysis_example.ipynb | 46 +- docs/TrendAnalysis_example_NSRDB.ipynb | 6 +- docs/degradation_and_soiling_example.ipynb | 5824 ++++++++++---------- 4 files changed, 2945 insertions(+), 2937 deletions(-) diff --git a/docs/Multi-year_on_year_example.ipynb b/docs/Multi-year_on_year_example.ipynb index 6d77058bf..6bd460c4d 100644 --- a/docs/Multi-year_on_year_example.ipynb +++ b/docs/Multi-year_on_year_example.ipynb @@ -18,7 +18,9 @@ "\n", "For a consistent experience, we recommend installing the packages and versions documented in `docs/notebook_requirements.txt`. This can be achieved in your environment by running `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) This notebook was tested in python 3.12.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n" + "This notebook works with data from system 4 of the PVDAQ dataset [1]. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { @@ -247,7 +249,7 @@ ], "source": [ "# Provide additional timestamp information for the YoY slopes including the left and right timestamps that were used to calculate the slope.\n", - "# The index is set to equal dt_center because we passed label='center' in the yoy_kwargs. \n", + "# The index is set to equal dt_center because we passed label='center' in the yoy_kwargs.\n", "print(calc_info['YoY_times'].head().to_markdown())" ] }, diff --git a/docs/TrendAnalysis_example.ipynb b/docs/TrendAnalysis_example.ipynb index d9a396e16..dbea8a0de 100644 --- a/docs/TrendAnalysis_example.ipynb +++ b/docs/TrendAnalysis_example.ipynb @@ -14,9 +14,11 @@ "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.** \n", "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API to year on year (YOY) degradation and recovery (SRR) soiling calculations.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", "\n", - "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis." + "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis.\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { @@ -61547,7 +61549,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61583,7 +61585,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61607,7 +61609,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61643,7 +61645,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61658,7 +61660,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61694,7 +61696,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61721,7 +61723,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61757,7 +61759,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61772,7 +61774,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61808,7 +61810,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61953,7 +61955,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61989,7 +61991,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -62080,7 +62082,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62116,13 +62118,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62158,7 +62160,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -62290,8 +62292,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -62300,8 +62302,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "energy_Wh" diff --git a/docs/TrendAnalysis_example_NSRDB.ipynb b/docs/TrendAnalysis_example_NSRDB.ipynb index 0ffef29d6..038eb5826 100644 --- a/docs/TrendAnalysis_example_NSRDB.ipynb +++ b/docs/TrendAnalysis_example_NSRDB.ipynb @@ -14,9 +14,11 @@ "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.** \n", "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API for year on year (YOY) degradation calculations.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", "\n", - "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift." + "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift.\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { diff --git a/docs/degradation_and_soiling_example.ipynb b/docs/degradation_and_soiling_example.ipynb index d9c43099e..f5a9bcdaa 100644 --- a/docs/degradation_and_soiling_example.ipynb +++ b/docs/degradation_and_soiling_example.ipynb @@ -22,7 +22,9 @@ "\n", "Earlier versions of this notebook (RdTools<3.0) included a clear sky workflow in order to check the results for bias from sensor drift. With the wide availability of satellite data, we now recommend repeating the analysis with satellite data to double check the sensor-based result. This is illustrated using the object-oriented API in `TrendAnalysis_example_NSRDB.ipynb`\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal)." + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { @@ -6205,7 +6207,7 @@ 524.283, 204.75, 344.686, - 551.0, + 551, 668.64, 652.889, 485.25, @@ -7651,7 +7653,7 @@ 4.913, 4.513999999999999, 1.315, - 0.0, + 0, 3.033, 4.993, 3.363, @@ -7848,7 +7850,7 @@ 668.3480000000001, 705.922, 274.146, - 762.0, + 762, 599.007, 787.2589999999999, 504.854, @@ -10027,7 +10029,7 @@ 304.893, 515.656, 185.669, - 434.0, + 434, 413.856, 373.843, 528.55, @@ -21865,132 +21867,132 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.7539999999999, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -22784,17 +22786,17 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.073, 792.4169999999999, null, @@ -23623,62 +23625,62 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 799.1610000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.306, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.5880000000001, 795.5219999999999, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -24592,98 +24594,98 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.6010000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.164, - 800.0, - 800.0, + 800, + 800, 797.025, null, null, @@ -25469,117 +25471,117 @@ null, null, 793.325, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 795.054, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.227, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.342, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -26368,82 +26370,82 @@ null, null, 796.904, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.8910000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 794.52, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 797.196, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 796.238, null, null, @@ -27224,21 +27226,21 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 796.909, - 800.0, - 800.0, + 800, + 800, 793.27, - 800.0, + 800, 795.395, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, null, null, null, @@ -28033,37 +28035,37 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.8960000000001, null, null, @@ -28829,215 +28831,215 @@ null, 793.81, 794.3, - 800.0, + 800, 796.497, - 800.0, - 800.0, + 800, + 800, 798.418, - 800.0, + 800, 799.8660000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -29811,254 +29813,254 @@ 793.485, 797.053, 796.1, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.362, - 800.0, + 800, 795.175, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.132, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.5980000000001, 795.23, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 793.678, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.878, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.258, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 796.909, 794.8610000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -30540,7 +30542,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30576,7 +30578,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30600,7 +30602,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30636,7 +30638,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30651,7 +30653,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30687,7 +30689,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30714,7 +30716,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30750,7 +30752,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30765,7 +30767,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30801,7 +30803,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30946,7 +30948,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30982,7 +30984,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -31073,7 +31075,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -31109,13 +31111,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -31151,7 +31153,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -31283,8 +31285,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -31293,8 +31295,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "ac_power" @@ -46700,7 +46702,7 @@ 524.283, 204.75, 344.686, - 551.0, + 551, 668.64, 652.889, 485.25, @@ -48096,8 +48098,8 @@ 465.739, 608.818, 616.25, - 800.0, - 800.0, + 800, + 800, 543.535, 587.573, 746.965, @@ -48111,17 +48113,17 @@ 321.569, 530.658, 593.915, - 800.0, - 800.0, + 800, + 800, 596.365, - 800.0, + 800, 565.447, 560.453, - 800.0, + 800, 443.833, - 800.0, + 800, 661.554, - 800.0, + 800, 511.45, 748.9689999999999, 593.987, @@ -48132,10 +48134,10 @@ 666.7510000000001, 436.164, 474.635, - 800.0, - 800.0, + 800, + 800, 670.187, - 800.0, + 800, 252.036, 562.187, 354.684, @@ -49519,20 +49521,20 @@ 756.0369999999999, 756.1419999999999, 168.28799999999998, - 800.0, + 800, 626.887, - 800.0, + 800, 589.665, 739.5210000000001, 659.7919999999999, 518.381, - 800.0, + 800, 412.386, 631.996, 601.595, 677.068, 258.439, - 800.0, + 800, 781.687, 209.424, 732.37, @@ -49556,15 +49558,15 @@ 788.8330000000001, 734.456, 98.26, - 800.0, + 800, 784.115, 328.495, 471.029, - 800.0, - 800.0, + 800, + 800, 5.6370000000000005, 515.656, - 800.0, + 800, 310.97700000000003, 44.037, 74.565, @@ -49575,93 +49577,93 @@ 717.059, 377.55300000000005, 594.57, - 800.0, - 800.0, + 800, + 800, 652.944, 406.6, 464.7480000000001, - 800.0, - 800.0, + 800, + 800, 697.658, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 353.539, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 314.654, 705.949, - 800.0, - 800.0, + 800, + 800, 662.628, 445.253, 451.089, 698.9580000000001, 392.572, - 800.0, - 800.0, + 800, + 800, 720.17, 434.044, - 800.0, - 800.0, + 800, + 800, 782.331, 160.509, - 800.0, - 800.0, + 800, + 800, 797.306, 250.885, - 800.0, - 800.0, + 800, + 800, 777.057, 721.205, 517.726, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 740.4630000000001, 693.293, - 800.0, + 800, 187.552, 397.009, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 728.8739999999999, - 800.0, + 800, 651.727, 752.712, 79.883, 625.406, - 800.0, + 800, 676.765, - 800.0, + 800, 744.586, 353.082, - 800.0, - 800.0, + 800, + 800, 616.685, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 493.706, - 800.0, + 800, 756.643, 508.648, 795.5880000000001, 795.5219999999999, - 800.0, - 800.0, + 800, + 800, 563.244, 328.407, - 800.0, + 800, 403.049, - 800.0, + 800, 551.898, - 800.0, - 800.0, + 800, + 800, 419.747, 272.472, 437.705, @@ -49835,7 +49837,7 @@ 4.913, 4.513999999999999, 1.315, - 0.0, + 0, 3.033, 4.993, 3.363, @@ -50946,7 +50948,7 @@ 668.3480000000001, 705.922, 274.146, - 762.0, + 762, 599.007, 787.2589999999999, 504.854, @@ -55099,28 +55101,28 @@ 742.7810000000001, 715.0939999999999, 690.821, - 800.0, + 800, 748.77, 587.182, 554.2819999999999, 761.961, - 800.0, - 800.0, + 800, + 800, 776.688, 336.329, 535.855, - 800.0, + 800, 504.419, 764.813, 775.1080000000001, 620.7869999999999, - 800.0, + 800, 533.46, 620.0319999999999, 442.3130000000001, 796.909, 446.712, - 800.0, + 800, 626.3969999999999, 730.421, 626.094, @@ -55136,7 +55138,7 @@ 624.982, 709.2860000000001, 695.743, - 800.0, + 800, 793.27, 769.873, 506.897, @@ -55162,9 +55164,9 @@ 21.366, 347.582, 445.104, - 800.0, + 800, 795.395, - 800.0, + 800, 417.44, 342.886, 446.288, @@ -55176,10 +55178,10 @@ 582.871, 580.471, 426.199, - 800.0, + 800, 624.492, - 800.0, - 800.0, + 800, + 800, 181.953, 368.591, 610.145, @@ -56294,7 +56296,7 @@ 304.893, 515.656, 185.669, - 434.0, + 434, 413.856, 373.843, 528.55, @@ -56376,21 +56378,21 @@ 522.323, 777.525, 710.893, - 800.0, + 800, 701.8639999999999, - 800.0, + 800, 787.699, 772.801, 209.441, - 800.0, + 800, 441.564, 530.724, - 800.0, + 800, 719.74, 780.085, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 366.344, 173.46900000000002, 117.848, @@ -56420,7 +56422,7 @@ 754.166, 549.674, 462.309, - 800.0, + 800, 472.444, 365.133, 252.724, @@ -56562,47 +56564,47 @@ 379.249, 64.815, 40.932, - 800.0, - 800.0, + 800, + 800, 614.643, 382.271, 2.648, 72.318, - 800.0, + 800, 694.702, 693.948, - 800.0, - 800.0, + 800, + 800, 221.597, - 800.0, + 800, 637.259, - 800.0, + 800, 663.564, 705.6410000000001, 522.433, 706.819, 620.214, 754.815, - 800.0, + 800, 580.4209999999999, 735.2819999999999, - 800.0, - 800.0, + 800, + 800, 571.739, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 87.87700000000001, 411.318, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 659.908, - 800.0, - 800.0, + 800, + 800, 368.304, 375.351, - 800.0, + 800, 647.422, 673.181, 627.09, @@ -56652,13 +56654,13 @@ 644.482, 771.992, 508.372, - 800.0, + 800, 454.59, - 800.0, + 800, 613.387, - 800.0, + 800, 480.009, - 800.0, + 800, 601.556, 120.232, 45.21, @@ -60534,863 +60536,863 @@ ], "xaxis": "x", "y": [ - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.418, - 800.0, + 800, 799.8660000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 793.485, 797.053, 796.1, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.362, - 800.0, + 800, 795.175, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.132, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.5980000000001, 795.23, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 793.678, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.878, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 790.342, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.258, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 796.909, 791.784, 794.8610000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0 + 800, + 800, + 800, + 800, + 800 ], "yaxis": "y" } @@ -61481,7 +61483,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61517,7 +61519,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61541,7 +61543,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61577,7 +61579,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61592,7 +61594,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61628,7 +61630,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61655,7 +61657,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61691,7 +61693,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61706,7 +61708,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61742,7 +61744,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61887,7 +61889,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61923,7 +61925,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -62014,7 +62016,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62050,13 +62052,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62092,7 +62094,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -62224,8 +62226,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -62234,8 +62236,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "ac_power" @@ -77543,7 +77545,7 @@ 524.283, 204.75, 344.686, - 551.0, + 551, 668.64, 652.889, 485.25, @@ -80613,7 +80615,7 @@ 4.913, 4.513999999999999, 1.315, - 0.0, + 0, 3.033, 4.993, 3.363, @@ -81724,7 +81726,7 @@ 668.3480000000001, 705.922, 274.146, - 762.0, + 762, 599.007, 787.2589999999999, 504.854, @@ -87058,7 +87060,7 @@ 304.893, 515.656, 185.669, - 434.0, + 434, 413.856, 373.843, 528.55, @@ -91377,961 +91379,961 @@ ], "xaxis": "x", "y": [ - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.7539999999999, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 257.222, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 253.379, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 253.682, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 745.39, 746.596, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 745.17, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.132, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 746.095, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0 + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800 ], "yaxis": "y" } @@ -92422,7 +92424,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92458,7 +92460,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92482,7 +92484,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92518,7 +92520,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92533,7 +92535,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92569,7 +92571,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92596,7 +92598,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92632,7 +92634,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92647,7 +92649,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92683,7 +92685,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92828,7 +92830,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92864,7 +92866,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92955,7 +92957,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92991,13 +92993,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -93033,7 +93035,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -93165,8 +93167,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -93175,8 +93177,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "ac_power" From afb26a7dc0c214a922dc367477aa72ecf3e1ae93 Mon Sep 17 00:00:00 2001 From: Martin Springer <97482055+martin-springer@users.noreply.github.com> Date: Fri, 20 Mar 2026 10:36:33 -0400 Subject: [PATCH 09/18] Change NREL to NLR (#492) * initial pyproject.toml implementation * changelog * update URLs * change NREL to NLR * linting * changelog * update PVDAQ citation in notebooks --- CITATION.cff | 2 +- CODE_OF_CONDUCT.md | 2 +- README.md | 10 +- docs/Multi-year_on_year_example.ipynb | 6 +- docs/TrendAnalysis_example.ipynb | 46 +- docs/TrendAnalysis_example_NSRDB.ipynb | 6 +- docs/degradation_and_soiling_example.ipynb | 5824 ++++++++++---------- docs/sphinx/source/changelog/pending.rst | 3 + docs/sphinx/source/changelog/v2.0.0.rst | 8 +- docs/sphinx/source/conf.py | 6 +- docs/sphinx/source/developer_notes.rst | 22 +- docs/sphinx/source/index.rst | 16 +- pyproject.toml | 6 +- rdtools/soiling.py | 4 +- rdtools/test/filtering_test.py | 2 +- rdtools/test/soiling_test.py | 2 +- 16 files changed, 2988 insertions(+), 2977 deletions(-) diff --git a/CITATION.cff b/CITATION.cff index 2c050d4b1..299bd5994 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -43,4 +43,4 @@ authors: orcid: "https://orcid.org/0000-0002-9867-8930" title: "RdTools" doi: 10.5281/zenodo.1210316 -url: "https://github.com/NREL/rdtools" \ No newline at end of file +url: "https://github.com/NatLabRockies/rdtools" \ No newline at end of file diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md index c18f3d799..e7799a422 100644 --- a/CODE_OF_CONDUCT.md +++ b/CODE_OF_CONDUCT.md @@ -55,7 +55,7 @@ further defined and clarified by project maintainers. ## Enforcement Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported by contacting the project team at RdTools@nrel.gov. All +reported by contacting the project team at RdTools@nlr.gov. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. diff --git a/README.md b/README.md index 189a4f610..39050dce8 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,13 @@ RdTools logo Master branch: -[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NREL/rdtools/actions?query=branch%3Amaster) +[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Amaster) Development branch: -[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NREL/rdtools/actions?query=branch%3Adevelopment) +[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Adevelopment) Code coverage: -[![codecov](https://codecov.io/gh/NREL/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NREL/rdtools) +[![codecov](https://codecov.io/gh/NatLabRockies/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NatLabRockies/rdtools) RdTools is an open-source library to support reproducible technical analysis of time series data from photovoltaic energy systems. The library aims to provide @@ -38,7 +38,7 @@ and the specific DOI coresponding to that version from [Zenodo](https://doi.org/ Martin Springer, Jiyang Yan, Kirsten Perry, Sandra Villamar, Will Vining, Gregory Kimball, Daniel Ruth, Noah Moyer, Quyen Nguyen, Dirk Jordan, Matthew Muller, and Chris Deline, RdTools, version {insert version}, Computer Software, - https://github.com/NREL/rdtools. DOI:{insert DOI} + https://github.com/NatLabRockies/rdtools. DOI:{insert DOI} The underlying workflow of RdTools has been published in several places. If you use RdTools in a published work, you may also wish to cite the following as @@ -76,5 +76,5 @@ Other useful references which may also be consulted for degradation rate methodo ## Further Instructions and Updates -Check out the [wiki](https://github.com/NREL/rdtools/wiki) for additional usage documentation, and for information on development goals and framework. +Check out the [wiki](https://github.com/NatLabRockies/rdtools/wiki) for additional usage documentation, and for information on development goals and framework. diff --git a/docs/Multi-year_on_year_example.ipynb b/docs/Multi-year_on_year_example.ipynb index 6d77058bf..6bd460c4d 100644 --- a/docs/Multi-year_on_year_example.ipynb +++ b/docs/Multi-year_on_year_example.ipynb @@ -18,7 +18,9 @@ "\n", "For a consistent experience, we recommend installing the packages and versions documented in `docs/notebook_requirements.txt`. This can be achieved in your environment by running `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) This notebook was tested in python 3.12.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n" + "This notebook works with data from system 4 of the PVDAQ dataset [1]. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { @@ -247,7 +249,7 @@ ], "source": [ "# Provide additional timestamp information for the YoY slopes including the left and right timestamps that were used to calculate the slope.\n", - "# The index is set to equal dt_center because we passed label='center' in the yoy_kwargs. \n", + "# The index is set to equal dt_center because we passed label='center' in the yoy_kwargs.\n", "print(calc_info['YoY_times'].head().to_markdown())" ] }, diff --git a/docs/TrendAnalysis_example.ipynb b/docs/TrendAnalysis_example.ipynb index d9a396e16..dbea8a0de 100644 --- a/docs/TrendAnalysis_example.ipynb +++ b/docs/TrendAnalysis_example.ipynb @@ -14,9 +14,11 @@ "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.** \n", "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API to year on year (YOY) degradation and recovery (SRR) soiling calculations.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", "\n", - "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis." + "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis.\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { @@ -61547,7 +61549,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61583,7 +61585,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61607,7 +61609,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61643,7 +61645,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61658,7 +61660,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61694,7 +61696,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61721,7 +61723,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61757,7 +61759,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61772,7 +61774,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61808,7 +61810,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61953,7 +61955,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61989,7 +61991,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -62080,7 +62082,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62116,13 +62118,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62158,7 +62160,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -62290,8 +62292,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -62300,8 +62302,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "energy_Wh" diff --git a/docs/TrendAnalysis_example_NSRDB.ipynb b/docs/TrendAnalysis_example_NSRDB.ipynb index 0ffef29d6..038eb5826 100644 --- a/docs/TrendAnalysis_example_NSRDB.ipynb +++ b/docs/TrendAnalysis_example_NSRDB.ipynb @@ -14,9 +14,11 @@ "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.** \n", "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API for year on year (YOY) degradation calculations.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", "\n", - "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift." + "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift.\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { diff --git a/docs/degradation_and_soiling_example.ipynb b/docs/degradation_and_soiling_example.ipynb index d9c43099e..f5a9bcdaa 100644 --- a/docs/degradation_and_soiling_example.ipynb +++ b/docs/degradation_and_soiling_example.ipynb @@ -22,7 +22,9 @@ "\n", "Earlier versions of this notebook (RdTools<3.0) included a clear sky workflow in order to check the results for bias from sensor drift. With the wide availability of satellite data, we now recommend repeating the analysis with satellite data to double check the sensor-based result. This is illustrated using the object-oriented API in `TrendAnalysis_example_NSRDB.ipynb`\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal)." + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { @@ -6205,7 +6207,7 @@ 524.283, 204.75, 344.686, - 551.0, + 551, 668.64, 652.889, 485.25, @@ -7651,7 +7653,7 @@ 4.913, 4.513999999999999, 1.315, - 0.0, + 0, 3.033, 4.993, 3.363, @@ -7848,7 +7850,7 @@ 668.3480000000001, 705.922, 274.146, - 762.0, + 762, 599.007, 787.2589999999999, 504.854, @@ -10027,7 +10029,7 @@ 304.893, 515.656, 185.669, - 434.0, + 434, 413.856, 373.843, 528.55, @@ -21865,132 +21867,132 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.7539999999999, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -22784,17 +22786,17 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.073, 792.4169999999999, null, @@ -23623,62 +23625,62 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 799.1610000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.306, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.5880000000001, 795.5219999999999, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -24592,98 +24594,98 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.6010000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.164, - 800.0, - 800.0, + 800, + 800, 797.025, null, null, @@ -25469,117 +25471,117 @@ null, null, 793.325, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 795.054, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.227, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 796.342, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -26368,82 +26370,82 @@ null, null, 796.904, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.8910000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 794.52, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 797.196, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 796.238, null, null, @@ -27224,21 +27226,21 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 796.909, - 800.0, - 800.0, + 800, + 800, 793.27, - 800.0, + 800, 795.395, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, null, null, null, @@ -28033,37 +28035,37 @@ null, null, null, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.8960000000001, null, null, @@ -28829,215 +28831,215 @@ null, 793.81, 794.3, - 800.0, + 800, 796.497, - 800.0, - 800.0, + 800, + 800, 798.418, - 800.0, + 800, 799.8660000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -29811,254 +29813,254 @@ 793.485, 797.053, 796.1, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.362, - 800.0, + 800, 795.175, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.132, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.5980000000001, 795.23, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 793.678, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.878, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.258, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 796.909, 794.8610000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, null, null, null, @@ -30540,7 +30542,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30576,7 +30578,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30600,7 +30602,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30636,7 +30638,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30651,7 +30653,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30687,7 +30689,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30714,7 +30716,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30750,7 +30752,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30765,7 +30767,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30801,7 +30803,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -30946,7 +30948,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -30982,7 +30984,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -31073,7 +31075,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -31109,13 +31111,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -31151,7 +31153,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -31283,8 +31285,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -31293,8 +31295,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "ac_power" @@ -46700,7 +46702,7 @@ 524.283, 204.75, 344.686, - 551.0, + 551, 668.64, 652.889, 485.25, @@ -48096,8 +48098,8 @@ 465.739, 608.818, 616.25, - 800.0, - 800.0, + 800, + 800, 543.535, 587.573, 746.965, @@ -48111,17 +48113,17 @@ 321.569, 530.658, 593.915, - 800.0, - 800.0, + 800, + 800, 596.365, - 800.0, + 800, 565.447, 560.453, - 800.0, + 800, 443.833, - 800.0, + 800, 661.554, - 800.0, + 800, 511.45, 748.9689999999999, 593.987, @@ -48132,10 +48134,10 @@ 666.7510000000001, 436.164, 474.635, - 800.0, - 800.0, + 800, + 800, 670.187, - 800.0, + 800, 252.036, 562.187, 354.684, @@ -49519,20 +49521,20 @@ 756.0369999999999, 756.1419999999999, 168.28799999999998, - 800.0, + 800, 626.887, - 800.0, + 800, 589.665, 739.5210000000001, 659.7919999999999, 518.381, - 800.0, + 800, 412.386, 631.996, 601.595, 677.068, 258.439, - 800.0, + 800, 781.687, 209.424, 732.37, @@ -49556,15 +49558,15 @@ 788.8330000000001, 734.456, 98.26, - 800.0, + 800, 784.115, 328.495, 471.029, - 800.0, - 800.0, + 800, + 800, 5.6370000000000005, 515.656, - 800.0, + 800, 310.97700000000003, 44.037, 74.565, @@ -49575,93 +49577,93 @@ 717.059, 377.55300000000005, 594.57, - 800.0, - 800.0, + 800, + 800, 652.944, 406.6, 464.7480000000001, - 800.0, - 800.0, + 800, + 800, 697.658, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 353.539, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 314.654, 705.949, - 800.0, - 800.0, + 800, + 800, 662.628, 445.253, 451.089, 698.9580000000001, 392.572, - 800.0, - 800.0, + 800, + 800, 720.17, 434.044, - 800.0, - 800.0, + 800, + 800, 782.331, 160.509, - 800.0, - 800.0, + 800, + 800, 797.306, 250.885, - 800.0, - 800.0, + 800, + 800, 777.057, 721.205, 517.726, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 740.4630000000001, 693.293, - 800.0, + 800, 187.552, 397.009, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 728.8739999999999, - 800.0, + 800, 651.727, 752.712, 79.883, 625.406, - 800.0, + 800, 676.765, - 800.0, + 800, 744.586, 353.082, - 800.0, - 800.0, + 800, + 800, 616.685, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 493.706, - 800.0, + 800, 756.643, 508.648, 795.5880000000001, 795.5219999999999, - 800.0, - 800.0, + 800, + 800, 563.244, 328.407, - 800.0, + 800, 403.049, - 800.0, + 800, 551.898, - 800.0, - 800.0, + 800, + 800, 419.747, 272.472, 437.705, @@ -49835,7 +49837,7 @@ 4.913, 4.513999999999999, 1.315, - 0.0, + 0, 3.033, 4.993, 3.363, @@ -50946,7 +50948,7 @@ 668.3480000000001, 705.922, 274.146, - 762.0, + 762, 599.007, 787.2589999999999, 504.854, @@ -55099,28 +55101,28 @@ 742.7810000000001, 715.0939999999999, 690.821, - 800.0, + 800, 748.77, 587.182, 554.2819999999999, 761.961, - 800.0, - 800.0, + 800, + 800, 776.688, 336.329, 535.855, - 800.0, + 800, 504.419, 764.813, 775.1080000000001, 620.7869999999999, - 800.0, + 800, 533.46, 620.0319999999999, 442.3130000000001, 796.909, 446.712, - 800.0, + 800, 626.3969999999999, 730.421, 626.094, @@ -55136,7 +55138,7 @@ 624.982, 709.2860000000001, 695.743, - 800.0, + 800, 793.27, 769.873, 506.897, @@ -55162,9 +55164,9 @@ 21.366, 347.582, 445.104, - 800.0, + 800, 795.395, - 800.0, + 800, 417.44, 342.886, 446.288, @@ -55176,10 +55178,10 @@ 582.871, 580.471, 426.199, - 800.0, + 800, 624.492, - 800.0, - 800.0, + 800, + 800, 181.953, 368.591, 610.145, @@ -56294,7 +56296,7 @@ 304.893, 515.656, 185.669, - 434.0, + 434, 413.856, 373.843, 528.55, @@ -56376,21 +56378,21 @@ 522.323, 777.525, 710.893, - 800.0, + 800, 701.8639999999999, - 800.0, + 800, 787.699, 772.801, 209.441, - 800.0, + 800, 441.564, 530.724, - 800.0, + 800, 719.74, 780.085, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 366.344, 173.46900000000002, 117.848, @@ -56420,7 +56422,7 @@ 754.166, 549.674, 462.309, - 800.0, + 800, 472.444, 365.133, 252.724, @@ -56562,47 +56564,47 @@ 379.249, 64.815, 40.932, - 800.0, - 800.0, + 800, + 800, 614.643, 382.271, 2.648, 72.318, - 800.0, + 800, 694.702, 693.948, - 800.0, - 800.0, + 800, + 800, 221.597, - 800.0, + 800, 637.259, - 800.0, + 800, 663.564, 705.6410000000001, 522.433, 706.819, 620.214, 754.815, - 800.0, + 800, 580.4209999999999, 735.2819999999999, - 800.0, - 800.0, + 800, + 800, 571.739, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 87.87700000000001, 411.318, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 659.908, - 800.0, - 800.0, + 800, + 800, 368.304, 375.351, - 800.0, + 800, 647.422, 673.181, 627.09, @@ -56652,13 +56654,13 @@ 644.482, 771.992, 508.372, - 800.0, + 800, 454.59, - 800.0, + 800, 613.387, - 800.0, + 800, 480.009, - 800.0, + 800, 601.556, 120.232, 45.21, @@ -60534,863 +60536,863 @@ ], "xaxis": "x", "y": [ - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.418, - 800.0, + 800, 799.8660000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 793.485, 797.053, 796.1, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 792.362, - 800.0, + 800, 795.175, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.132, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.5980000000001, 795.23, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 793.678, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 797.878, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, 790.342, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 795.258, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, 796.909, 791.784, 794.8610000000001, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0 + 800, + 800, + 800, + 800, + 800 ], "yaxis": "y" } @@ -61481,7 +61483,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61517,7 +61519,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61541,7 +61543,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61577,7 +61579,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61592,7 +61594,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61628,7 +61630,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61655,7 +61657,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61691,7 +61693,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61706,7 +61708,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61742,7 +61744,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -61887,7 +61889,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -61923,7 +61925,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -62014,7 +62016,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62050,13 +62052,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -62092,7 +62094,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -62224,8 +62226,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -62234,8 +62236,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "ac_power" @@ -77543,7 +77545,7 @@ 524.283, 204.75, 344.686, - 551.0, + 551, 668.64, 652.889, 485.25, @@ -80613,7 +80615,7 @@ 4.913, 4.513999999999999, 1.315, - 0.0, + 0, 3.033, 4.993, 3.363, @@ -81724,7 +81726,7 @@ 668.3480000000001, 705.922, 274.146, - 762.0, + 762, 599.007, 787.2589999999999, 504.854, @@ -87058,7 +87060,7 @@ 304.893, 515.656, 185.669, - 434.0, + 434, 413.856, 373.843, 528.55, @@ -91377,961 +91379,961 @@ ], "xaxis": "x", "y": [ - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.7539999999999, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 257.222, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 253.379, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, 253.682, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 745.39, 746.596, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 745.17, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 798.132, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, 746.095, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0, - 800.0 + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800, + 800 ], "yaxis": "y" } @@ -92422,7 +92424,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92458,7 +92460,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92482,7 +92484,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92518,7 +92520,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92533,7 +92535,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92569,7 +92571,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92596,7 +92598,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92632,7 +92634,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92647,7 +92649,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92683,7 +92685,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92828,7 +92830,7 @@ }, "colorscale": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92864,7 +92866,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], @@ -92955,7 +92957,7 @@ ], "sequential": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -92991,13 +92993,13 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ], "sequentialminus": [ [ - 0.0, + 0, "#0d0887" ], [ @@ -93033,7 +93035,7 @@ "#fdca26" ], [ - 1.0, + 1, "#f0f921" ] ] @@ -93165,8 +93167,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "datetime" @@ -93175,8 +93177,8 @@ "yaxis": { "anchor": "x", "domain": [ - 0.0, - 1.0 + 0, + 1 ], "title": { "text": "ac_power" diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 2fdb3be22..29f438ae2 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -13,3 +13,6 @@ Maintenance ``MANIFEST.in``, and ``rdtools/_version.py``. (:pull:`488`) * Updated ``rdtools/__init__.py`` to use ``importlib.metadata`` for version retrieval instead of versioneer. (:pull:`488`) +* Updated GitHub URLs and references from ``NREL/rdtools`` to + ``NatLabRockies/rdtools`` and email addresses from ``@nrel.gov`` to + ``@nlr.gov``. (:pull:`492`) diff --git a/docs/sphinx/source/changelog/v2.0.0.rst b/docs/sphinx/source/changelog/v2.0.0.rst index a9b981456..e383f5757 100644 --- a/docs/sphinx/source/changelog/v2.0.0.rst +++ b/docs/sphinx/source/changelog/v2.0.0.rst @@ -11,12 +11,12 @@ API Changes right-labeled energy with :py:func:`~rdtools.normalization.energy_from_power` before being used with these normalization functions (:pull:`105`, :pull:`108`). * Remove ``low_power_cutoff`` parameter in :py:func:`~rdtools.filtering.clip_filter` (:issue:`84`). -* Many kwargs have changed name (but not input order) to bring nomenclature into +* Many kwargs have changed name (but not input order) to bring nomenclature into closer alignment with the `DuraMAT pv-terms project `_: (:pull:`185`) * :py:func:`~rdtools.aggregation.aggregation_insol` first kwarg is now ``energy_normalized``. - * :py:func:`~rdtools.degradation.degradation_year_on_year`, - :py:func:`~rdtools.degradation.degradation_ols` and + * :py:func:`~rdtools.degradation.degradation_year_on_year`, + :py:func:`~rdtools.degradation.degradation_ols` and :py:func:`~rdtools.degradation.degradation_classical_decomposition` first kwarg is now ``energy_normalized``. * :py:func:`~rdtools.filtering.normalized_filter` input kwargs are now ``energy_normalized``, ``energy_normalized_low`` and ``energy_normalized_high``. @@ -97,7 +97,7 @@ Example Updates variable names (:pull:`139`). * Add soiling section to the original example notebook. * Add a new example notebook that analyzes data from a PV system located at - NREL's South Table Mountain campus (PVDAQ system #4) (:pull:`171`). + NLR's South Table Mountain campus (PVDAQ system #4) (:pull:`171`). * Explicitly register pandas datetime converters which were `deprecated `_. * Add new ``system_availability_example.ipynb`` notebook (:pull:`131`) diff --git a/docs/sphinx/source/conf.py b/docs/sphinx/source/conf.py index c46717ae7..4bfd1da3d 100644 --- a/docs/sphinx/source/conf.py +++ b/docs/sphinx/source/conf.py @@ -62,8 +62,8 @@ # List of external link aliases. Allows use of :pull:`123` to autolink that PR extlinks = { - "issue": ("https://github.com/NREL/rdtools/issues/%s", "GH #%s"), - "pull": ("https://github.com/NREL/rdtools/pull/%s", "GH #%s"), + "issue": ("https://github.com/NatLabRockies/rdtools/issues/%s", "GH #%s"), + "pull": ("https://github.com/NatLabRockies/rdtools/pull/%s", "GH #%s"), "ghuser": ("https://github.com/%s", "@%s"), } @@ -195,7 +195,7 @@ def make_github_url(pagename): # either a branch name or a git tag will work for the URL branch = version_map.get(rtd_version, rtd_version) - URL_BASE = "https://github.com/nrel/rdtools/blob/{}/".format(branch) + URL_BASE = "https://github.com/NatLabRockies/rdtools/blob/{}/".format(branch) # is it an API autogen page? if pagename.startswith("generated/"): diff --git a/docs/sphinx/source/developer_notes.rst b/docs/sphinx/source/developer_notes.rst index d33272f24..c4b502509 100644 --- a/docs/sphinx/source/developer_notes.rst +++ b/docs/sphinx/source/developer_notes.rst @@ -16,16 +16,16 @@ you'll need to clone the RdTools source repository from Github with e.g. :: - git clone https://github.com/NREL/rdtools.git + git clone https://github.com/NatLabRockies/rdtools.git from the command line, or using a GUI git client like Github Desktop. This -will clone the entire git repository onto your computer. +will clone the entire git repository onto your computer. Installing RdTools dependencies ------------------------------- The packages necessary to run RdTools itself can be installed with ``pip``. -You can install the dependencies along with RdTools itself from +You can install the dependencies along with RdTools itself from `PyPI `_: :: @@ -66,14 +66,14 @@ Installing optional dependencies RdTools has extra dependencies for running its test suite and building its documentation. These packages aren't necessary for running RdTools itself and -are only needed if you want to contribute source code to RdTools. +are only needed if you want to contribute source code to RdTools. .. note:: These will install RdTools along with other packages necessary to build its documentation and run its test suite. We recommend doing this in a virtual environment to keep package installations between projects separate! -Optional dependencies can be installed with the special +Optional dependencies can be installed with the special `syntax `_: :: @@ -115,7 +115,7 @@ And even a single test function: pytest rdtools/test/soiling_test.py::test_soiling_srr -You can also evaluate code coverage when running the test suite using the +You can also evaluate code coverage when running the test suite using the `coverage `_ package: :: @@ -129,7 +129,7 @@ summary report showing how much much of each source file was executed in the test suite. If a percentage is below 100, that means a function isn't tested or a branch inside a function isn't tested. To get specific details, you can run ``coverage html`` to generate a detailed HTML -report at ``htmlcov/index.html`` to view in a browser. +report at ``htmlcov/index.html`` to view in a browser. Running the notebooks as tests @@ -214,7 +214,7 @@ docs should result in output like this: dumping search index in English (code: en) ... done dumping object inventory... done build succeeded. - + The HTML pages are in build\html. If you get an error like ``Pandoc wasn't found``, you can install it with conda: @@ -230,7 +230,7 @@ Contributing ------------ Community participation is welcome! New contributions should be based on the -``development`` branch as the ``master`` branch is used only for releases. +``development`` branch as the ``master`` branch is used only for releases. RdTools follows the `PEP 8 `_ style guide. We recommend setting up your text editor to automatically highlight style @@ -238,7 +238,7 @@ violations because it's easy to miss some issues (trailing whitespace, etc) othe Additionally, our documentation is built in part from docstrings in the source code. These docstrings must be in `NumpyDoc format `_ -to be rendered correctly in the documentation. +to be rendered correctly in the documentation. Finally, all code should be tested. Some older tests in RdTools use the unittest -module, but new tests should all use pytest. \ No newline at end of file +module, but new tests should all use pytest. \ No newline at end of file diff --git a/docs/sphinx/source/index.rst b/docs/sphinx/source/index.rst index cf6d0f0cc..4349fb5f1 100644 --- a/docs/sphinx/source/index.rst +++ b/docs/sphinx/source/index.rst @@ -53,7 +53,7 @@ The preferred method for degradation rate estimation is the year-on-year (YOY) approach (Jordan 2018), available in :py:func:`.degradation.degradation_year_on_year`. The YOY calculation yields a distribution of degradation rates, the central tendency of which is the most representative of the true -degradation. We note that the workflow described above and implemented in +degradation. We note that the workflow described above and implemented in :py:class:`.analysis_chains.TrendAnalysis` provides an estimate of degradation rate, not performance loss rate (PLR). PLR includes losses that are explicitly filtered out by the primary workflow (Deceglie 2023). @@ -102,14 +102,14 @@ The combined estimation of degradation and soiling (CODS) method (Skomedal 2020) in RdTools. CODS self-consistently extracts degradation, soiling, and seasonality of the daily-aggregated normalized performance signal. It is particularly useful when soiling trends are biasing degradation results. It's use is shown in both the TrendAnalysis -example notebook as well as the funtional API example notebook for degradation and soiling. +example notebook as well as the funtional API example notebook for degradation and soiling. TrendAnalysis ^^^^^^^^^^^^^ -An object-oriented API for complete soiling and degradation analysis including +An object-oriented API for complete soiling and degradation analysis including the normalize, filter, aggregate, analyze steps is available in :py:class:`.analysis_chains.TrendAnalysis`. See the -`TrendAnalysis example `_ for details. +`TrendAnalysis example `_ for details. Availability ------------ @@ -187,7 +187,7 @@ and the specific DOI coresponding to that version from `Zenodo Date: Fri, 20 Mar 2026 11:23:19 -0400 Subject: [PATCH 10/18] Adopt pixi for environment management and modernize CI (#493) * initial pixi implementation * add note on how to re-run notebooks with pixi * pixi version compatibility * update pixi lock file * pixi updates * add libomp as requirement for macOS users * use correct package name * convert notebooks to html without re-running * re-run notbooks to account for updated warning message formatting * Revert "re-run notbooks to account for updated warning message formatting" This reverts commit 7be24260983c5283fd02c0d1342ce450c42f579b. --- .github/workflows/nbval.yaml | 19 +- .github/workflows/pytest.yaml | 73 +- .github/workflows/requirements.yaml | 29 - .gitignore | 5 + .pixi.lnk | Bin 0 -> 707 bytes README.md | 32 +- docs/Multi-year_on_year_example.ipynb | 10 +- docs/TrendAnalysis_example.ipynb | 2 +- docs/TrendAnalysis_example_NSRDB.ipynb | 2 +- docs/degradation_and_soiling_example.ipynb | 6 +- docs/notebook_requirements.txt | 57 - docs/sphinx/source/changelog/pending.rst | 36 + docs/sphinx/source/developer_notes.rst | 207 +- docs/sphinx/source/index.rst | 17 +- docs/system_availability_example.ipynb | 2 +- pixi.lock | 18361 +++++++++++++++++++ pyproject.toml | 119 +- requirements-min.txt | 12 - requirements.txt | 35 - 19 files changed, 18798 insertions(+), 226 deletions(-) delete mode 100644 .github/workflows/requirements.yaml create mode 100644 .pixi.lnk delete mode 100644 docs/notebook_requirements.txt create mode 100644 pixi.lock delete mode 100644 requirements-min.txt delete mode 100644 requirements.txt diff --git a/.github/workflows/nbval.yaml b/.github/workflows/nbval.yaml index 53037e4bf..939edb00b 100644 --- a/.github/workflows/nbval.yaml +++ b/.github/workflows/nbval.yaml @@ -18,23 +18,16 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 + - uses: prefix-dev/setup-pixi@v0.8.3 with: - python-version: "3.12" - - name: Install notebook environment + environments: dev + - name: Validate notebook output run: | - python -m pip install --upgrade pip wheel - pip install --timeout=300 -r requirements.txt -r docs/notebook_requirements.txt .[test] - - name: Run notebook and check output + pixi run -e dev pytest --nbval --nbval-sanitize-with docs/nbval_sanitization_rules.cfg docs/${{ matrix.notebook-file }} + - name: Convert notebook to HTML run: | - # --nbval-sanitize-with: pre-process text to remove irrelevant differences (e.g. warning filepaths) - pytest --nbval --nbval-sanitize-with docs/nbval_sanitization_rules.cfg docs/${{ matrix.notebook-file }} - - name: Run notebooks again, save files - run: | - pip install nbconvert[webpdf] mkdir docs/artifacts - jupyter nbconvert --to html --execute --ExecutePreprocessor.timeout=600 --allow-errors --output artifacts/${{ matrix.notebook-file }}.html docs/${{ matrix.notebook-file }} + pixi run -e dev jupyter nbconvert --to html --output artifacts/${{ matrix.notebook-file }}.html docs/${{ matrix.notebook-file }} - name: Upload artifacts uses: actions/upload-artifact@v4 with: diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index 2b117ff16..4d94630dd 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -9,24 +9,60 @@ on: jobs: - build: + validate-envs: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: prefix-dev/setup-pixi@v0.8.3 + with: + environments: core default dev + frozen: true + - name: Validate core environment + run: pixi run -e core python -c "import rdtools; print(rdtools.__version__)" + - name: Validate default environment + run: pixi run python -c "import rdtools; import jupyter; print('default OK')" + - name: Validate dev environment + run: pixi run -e dev python -c "import rdtools; import pytest; import jupyter; print('dev OK')" + + test: + runs-on: ubuntu-latest + strategy: + matrix: + environment: [dev-py310, dev-py311, dev-py312, dev-py313, dev-py314] + fail-fast: false + + steps: + - uses: actions/checkout@v4 + - uses: prefix-dev/setup-pixi@v0.8.3 + with: + environments: ${{ matrix.environment }} + - name: Test with pytest (${{ matrix.environment }}) + run: pixi run -e ${{ matrix.environment }} test + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v4 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + + test-min: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + - uses: prefix-dev/setup-pixi@v0.8.3 + with: + environments: dev-min + - name: Test with pytest (minimum versions) + run: pixi run -e dev-min test + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v4 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + test-latest: runs-on: ubuntu-latest strategy: matrix: - python-version: ["3.10", "3.11", "3.12", "3.13"] - env: [ - '-r requirements.txt .[test]', - '-r requirements-min.txt .[test]', - '--upgrade --upgrade-strategy=eager .[test]' - ] - exclude: - - python-version: "3.11" - env: '-r requirements-min.txt .[test]' - - python-version: "3.12" - env: '-r requirements-min.txt .[test]' - - python-version: "3.13" - env: '-r requirements-min.txt .[test]' + python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"] fail-fast: false steps: @@ -35,13 +71,12 @@ jobs: uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} - - name: Install ${{ matrix.env }} + - name: Install latest versions run: | python -m pip install --upgrade pip wheel - pip install --timeout=300 ${{ matrix.env }} - - name: Test with pytest ${{ matrix.env }} - run: | - python -m pytest --cov=./ --cov-report=xml + pip install --timeout=300 --upgrade --upgrade-strategy=eager .[test] + - name: Test with pytest (latest) + run: python -m pytest --cov=rdtools --cov-report=xml - name: Upload coverage reports to Codecov uses: codecov/codecov-action@v4 env: diff --git a/.github/workflows/requirements.yaml b/.github/workflows/requirements.yaml deleted file mode 100644 index cb1d8b00a..000000000 --- a/.github/workflows/requirements.yaml +++ /dev/null @@ -1,29 +0,0 @@ -name: requirements - -on: - push: - branches: - - master - - development - pull_request: - - -jobs: - requirements: - - strategy: - matrix: - os: [ubuntu-latest, macos-latest, windows-latest] - - runs-on: ${{ matrix.os }} - - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: "3.12" - - name: Install notebook environment - run: | - python -m pip install --upgrade pip wheel - pip install --timeout=300 -r requirements.txt -r docs/notebook_requirements.txt diff --git a/.gitignore b/.gitignore index 72111dd48..6ab4ff4e7 100644 --- a/.gitignore +++ b/.gitignore @@ -11,6 +11,7 @@ .coveralls.yml .coverage .coverage.* +coverage.xml htmlcov/ # ignore test cache @@ -38,5 +39,9 @@ rdtools.egg-info* *.pickle +# pixi environments (local, not committed) +.pixi/* +!.pixi/config.toml + # ignore vscode settings .vscode/ diff --git a/.pixi.lnk b/.pixi.lnk new file mode 100644 index 0000000000000000000000000000000000000000..4852630c62d899beb55f76030c99962eae9ab586 GIT binary patch literal 707 zcmeZaU|?VrVFHp23ls8C zCW8$FCj$$^ z`+Xp>tQhU7dO#J;f*@t5z-kf1+a7iXJ%$2?Ooj>|W&m2vz+er;GC&M+7>I_L&%j^> zWQzhZGY}_a?bHEz&Ly!Vkpbv1h`kIT!(xyOOn@j~5CNn?Ah)=nC^IiTRoB?u)X=Dy z!Qo_x=~lKx867Rv)M3lO^ieE|!_9v~m2$>5{v_V?~m0!u$KCG^aD zy+#%&&IQC^O>96KIepi01+ND!BMLTWP(fw>)-*>Zot6IVMt|AU`S)g2eMLt z>>{8zNH-r4gLNY(1V^A4$SupVk~M6nUJ~4Tjp2a*O^FMtKyf*c29O7UK81P!*+n2( z1_nzY1{ttXEZ1diZ-K{h4+p&^wiP`f&t!lUcmQ#^)\n", @@ -94371,7 +94371,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "rdtools_313-nb", "language": "python", "name": "python3" }, @@ -94385,7 +94385,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.7" + "version": "3.13.11" } }, "nbformat": 4, diff --git a/docs/notebook_requirements.txt b/docs/notebook_requirements.txt deleted file mode 100644 index b44d257d4..000000000 --- a/docs/notebook_requirements.txt +++ /dev/null @@ -1,57 +0,0 @@ -appnope==0.1.4 -argon2-cffi==23.1.0 -argon2-cffi-bindings==21.2.0 -backcall==0.2.0 -beautifulsoup4==4.12.3 -bleach==6.1.0 -cffi==1.17.0 -colorama==0.4.6 -decorator==5.1.1 -defusedxml==0.7.1 -entrypoints==0.4 -html5lib==1.1 -ipykernel==6.29.5 -ipython==8.26.0 -ipython-genutils==0.2.0 -ipywidgets==8.1.3 -jedi==0.19.1 -Jinja2==3.1.6 -jsonschema==4.23.0 -jupyter==1.0.0 -jupyter-client==8.6.2 -jupyter-console==6.6.3 -jupyter-core==5.7.2 -jupyterlab-pygments==0.3.0 -lxml==5.3.0 -MarkupSafe==2.1.5 -mistune==3.0.2 -nbclient==0.10.0 -nbconvert==7.17.0 -nbformat==5.10.4 -nest-asyncio==1.6.0 -notebook==7.2.2 -numexpr==2.10.2 -pandocfilters==1.5.1 -parso==0.8.4 -pexpect==4.9.0 -pickleshare==0.7.5 -prometheus-client==0.20.0 -prompt-toolkit==3.0.47 -ptyprocess==0.7.0 -pycparser==2.22 -Pygments==2.18.0 -pyzmq==26.1.1 -qtconsole==5.5.2 -Send2Trash==1.8.3 -simplegeneric==0.8.1 -soupsieve==2.6 -tabulate==0.9.0 -terminado==0.18.1 -testpath==0.6.0 -tinycss2==1.2.1 -tornado==6.5.1 -traitlets==5.14.3 -wcwidth==0.2.13 -webencodings==0.5.1 -widgetsnbextension==4.0.11 - diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 29f438ae2..1ea5559a9 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -16,3 +16,39 @@ Maintenance * Updated GitHub URLs and references from ``NREL/rdtools`` to ``NatLabRockies/rdtools`` and email addresses from ``@nrel.gov`` to ``@nlr.gov``. (:pull:`492`) +* Adopted `pixi `_ for reproducible environment management. + Replaced ``requirements.txt``, ``requirements-min.txt``, and + ``docs/notebook_requirements.txt`` with pixi environments and a lockfile. + (:pull:`492`) +* Rewrote CI workflows (``pytest.yaml``, ``nbval.yaml``) to use pixi via + ``prefix-dev/setup-pixi`` and removed the ``requirements.yaml`` workflow. + (:pull:`492`) +* Bumped minimum ``arch`` version from 5.0 to 5.6. (:pull:`492`) +* Added Python 3.14 to the test matrix and package classifiers. + (:pull:`492`) +* Simplified pixi environments: ``core`` (bare), ``default`` (notebooks), + ``dev`` (notebooks + test, alias for ``dev-py313``), ``dev-py310`` through + ``dev-py314`` (full dev per Python version), and ``dev-min`` (minimum + dependency versions). All shared environments pin Python 3.13. + (:pull:`492`) +* Added composable pip extras: ``[notebooks]``, ``[test]``, ``[dev]``, + ``[doc]``, and ``[all]``. (:pull:`492`) +* Updated documentation (README, Sphinx index, developer notes, and example + notebook setup cells) for pixi and pip extras. (:pull:`492`) + +Bug Fixes +--------- +* Fixed broken link to TrendAnalysis example in Sphinx index page. + (:pull:`492`) + +Requirements +------------ +* Added ``llvm-openmp`` (the conda-forge name for libomp) as a platform-specific + conda dependency for macOS (osx-64 and osx-arm64) to fix XGBoost installation + issues. Users no longer need to install libomp via Homebrew. (:pull:`493`) +* Bumped minimum ``xgboost`` version from 1.6.0 to 1.7.0 to fix + ``pkg_resources`` import error in environments without ``setuptools``. + (:pull:`493`) +* Bumped minimum ``pvlib`` version from 0.12.0 to 0.13.1 to include the + ``detect_clearsky()`` bug fix (pvlib GH2550). (:pull:`493`) + diff --git a/docs/sphinx/source/developer_notes.rst b/docs/sphinx/source/developer_notes.rst index c4b502509..7d59b1f07 100644 --- a/docs/sphinx/source/developer_notes.rst +++ b/docs/sphinx/source/developer_notes.rst @@ -24,9 +24,109 @@ will clone the entire git repository onto your computer. Installing RdTools dependencies ------------------------------- -The packages necessary to run RdTools itself can be installed with ``pip``. -You can install the dependencies along with RdTools itself from -`PyPI `_: +RdTools uses `pixi `_ for reproducible environment management. +Pixi creates isolated environments from the lockfile (``pixi.lock``), ensuring +every contributor gets the exact same package versions. + +To install pixi, follow the instructions at https://pixi.sh. + +Once pixi is installed, navigate to the repository root and run: + +:: + + pixi install + +This creates the default environment with RdTools and its core dependencies. +Pixi environments are stored locally in ``.pixi/`` (gitignored) and do not +interfere with other Python environments on your system. + +To run a command inside a pixi environment, use ``pixi run``: + +:: + + pixi run python -c "import rdtools; print(rdtools.__version__)" + +.. _pixi-environments: + +Available pixi environments +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +RdTools defines several pixi environments in ``pyproject.toml``: + +- **core** — bare RdTools with core dependencies only (Python 3.13) +- **default** — RdTools + notebook extras for regular users (Python 3.13) +- **dev** — notebooks + test extras combined (Python 3.13); recommended for day-to-day development (alias for **dev-py313**) +- **dev-py310** through **dev-py314** — full dev environment pinned to a specific Python version +- **dev-min** — test-only environment with minimum supported dependency versions (Python 3.10) + +For most contributors, the **dev** environment is the best starting point +because it includes everything needed to run the test suite, launch Jupyter +notebooks, and check code style: + +:: + + pixi install -e dev + pixi run -e dev test # run the test suite + pixi run -e dev lab # launch Jupyter Lab + +To test against a specific Python version: + +:: + + pixi run -e dev-py310 test + +.. _updating-pixi-environments: + +Updating pixi environments +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +When ``pyproject.toml`` changes (e.g. a dependency is added, removed, or its +version constraint is updated), the pixi lockfile must be regenerated: + +1. **Re-solve dependencies** — run ``pixi update`` from the repository root. + This re-solves all environments against the current ``pyproject.toml`` + constraints and writes a new ``pixi.lock``: + + :: + + pixi update + +2. **Verify environments install correctly** — run ``pixi install`` to + re-create environments from the updated lockfile: + + :: + + pixi install + +3. **Run tests** to make sure nothing is broken: + + :: + + pixi run -e dev test + +4. **Commit both files** — always commit ``pyproject.toml`` and ``pixi.lock`` + together so that CI and other contributors stay in sync: + + :: + + git add pyproject.toml pixi.lock + git commit -m "Update dependencies" + +.. note:: + If you only want to update a single package, you can target it: + ``pixi update numpy``. To update packages only within a specific + environment, use ``pixi update -e dev numpy``. + +.. note:: + Contributors who pull changes that include an updated ``pixi.lock`` + just need to run ``pixi install`` to get the new environment. + +Installing without pixi +~~~~~~~~~~~~~~~~~~~~~~~~ + +If you prefer not to use pixi, you can still install RdTools and its +dependencies with pip. The packages necessary to run RdTools itself can be +installed from `PyPI `_: :: @@ -73,19 +173,28 @@ are only needed if you want to contribute source code to RdTools. documentation and run its test suite. We recommend doing this in a virtual environment to keep package installations between projects separate! -Optional dependencies can be installed with the special -`syntax `_: +With pixi (recommended): + +:: + + pixi install -e dev # all development dependencies (recommended) + pixi install -e dev-py310 # dev environment with Python 3.10 + pixi install -e dev-min # minimum supported dependency versions + +With pip: :: - pip install rdtools[test] # test suite dependencies + pip install rdtools[dev] # notebooks + test dependencies + pip install rdtools[test] # test suite dependencies only pip install rdtools[doc] # documentation dependencies Or, if your local repository has an updated dependencies list: :: - pip install .[test] # test suite dependencies + pip install .[dev] # notebooks + test dependencies + pip install .[test] # test suite dependencies only pip install .[doc] # documentation dependencies @@ -96,26 +205,43 @@ RdTools uses `pytest `_ to run its test suite. If you haven't already, install the testing dependencies (:ref:`installing-optional-dependencies`). -To run the entire test suite, navigate to the git repo folder and run +With pixi +~~~~~~~~~ + +Run the full test suite in the dev environment: :: - pytest + pixi run -e dev test -For convenience, pytest lets you run tests for a single module if you don't -want to wait around for the entire suite to finish: +Run a single test module: :: - pytest rdtools/test/soiling_test.py + pixi run -e dev pytest rdtools/test/soiling_test.py -And even a single test function: +Run a single test function: :: + pixi run -e dev pytest rdtools/test/soiling_test.py::test_soiling_srr + +Without pixi +~~~~~~~~~~~~~ + +If you installed RdTools and its test dependencies with pip, you can invoke +pytest directly: + +:: + + pytest rdtools/test/ + pytest rdtools/test/soiling_test.py pytest rdtools/test/soiling_test.py::test_soiling_srr -You can also evaluate code coverage when running the test suite using the +Measuring code coverage +~~~~~~~~~~~~~~~~~~~~~~~ + +You can evaluate code coverage when running the test suite using the `coverage `_ package: :: @@ -125,11 +251,19 @@ You can also evaluate code coverage when running the test suite using the The first line runs the test suite and keeps track of exactly what lines of code were run during test execution. The second line then prints out a -summary report showing how much much of each source file was -executed in the test suite. If a percentage is below 100, that means a -function isn't tested or a branch inside a function isn't tested. To get -specific details, you can run ``coverage html`` to generate a detailed HTML -report at ``htmlcov/index.html`` to view in a browser. +summary report showing how much of each source file was executed in the +test suite. If a percentage is below 100, that means a function isn't tested +or a branch inside a function isn't tested. To get specific details, you can +run ``coverage html`` to generate a detailed HTML report at +``htmlcov/index.html`` to view in a browser. + +Note that the pixi ``test`` task already includes ``--cov`` flags, so coverage +data is collected automatically when running ``pixi run -e dev test``. + +RdTools also uses `Codecov `_ to +track coverage over time. Coverage reports are uploaded automatically by CI +after each test run. Pull requests will show a Codecov status check indicating +whether the change increases or decreases overall coverage. Running the notebooks as tests @@ -142,7 +276,7 @@ and compare outputs for you: :: - pytest --nbval docs/system_availability_example.ipynb + pixi run -e dev pytest --nbval docs/system_availability_example.ipynb Some helpful options are ``--nbdime`` to display a visual before/after diff and ``--sanitize-with docs/nbval_sanitization_rules.cfg`` to ignore nuisance @@ -150,7 +284,34 @@ differences like the username shown in warning messages: :: - pytest --nbval --nbdime --sanitize-with docs/nbval_sanitization_rules.cfg docs/system_availability_example.ipynb + pixi run -e dev pytest --nbval --nbdime --sanitize-with docs/nbval_sanitization_rules.cfg docs/system_availability_example.ipynb + +Or to run all notebooks at once using the pixi task: + +:: + + pixi run -e dev nbval + + +Re-running and saving notebook outputs +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +If notebook outputs need to be refreshed (e.g. after a code change that +affects plots or printed results), you can re-execute all notebooks in place +using ``jupyter nbconvert``: + +:: + + pixi run -e dev jupyter nbconvert --to notebook --execute --inplace docs/*.ipynb + +Or a single notebook: + +:: + + pixi run -e dev jupyter nbconvert --to notebook --execute --inplace docs/TrendAnalysis_example.ipynb + +This overwrites each notebook file with freshly executed outputs. Review the +diffs before committing to make sure the changes look correct. Checking for code style @@ -163,13 +324,13 @@ folder and run :: - flake8 + pixi run -e dev flake8 Or, for a more detailed report: :: - flake8 --count --statistics --show-source + pixi run -e dev flake8 --count --statistics --show-source Building documentation locally diff --git a/docs/sphinx/source/index.rst b/docs/sphinx/source/index.rst index 4349fb5f1..b925f3388 100644 --- a/docs/sphinx/source/index.rst +++ b/docs/sphinx/source/index.rst @@ -109,7 +109,7 @@ TrendAnalysis An object-oriented API for complete soiling and degradation analysis including the normalize, filter, aggregate, analyze steps is available in :py:class:`.analysis_chains.TrendAnalysis`. See the -`TrendAnalysis example `_ for details. +`TrendAnalysis example `_ for details. Availability ------------ @@ -147,23 +147,22 @@ Alternatively it can be installed manually using the command line: On some systems, installation with ``pip`` can fail due to problems installing requirements. If this occurs, the requirements specified in -``setup.py`` may need to be separately installed (for example by using +``pyproject.toml`` may need to be separately installed (for example by using ``conda``) before installing ``rdtools``. For more detailed instructions, see the :ref:`developer_notes` page. -RdTools currently is tested on Python 3.9+. +RdTools currently is tested on Python 3.10+. Usage and examples ------------------ Full workflow examples are found in the notebooks in :ref:`examples`. -The examples are designed to work with python 3.12. For a consistent -experience, we recommend installing the packages and versions documented -in ``docs/notebook_requirements.txt``. This can be achieved in your -environment by first installing RdTools as described above, then running -``pip install -r docs/notebook_requirements.txt`` from the base -directory. +The examples are designed to work with python 3.13. For a consistent +experience, we recommend using `pixi `_ to set up the +notebook environment. From the base directory, run ``pixi run lab`` +to launch JupyterLab with all required packages. Alternatively, install +manually with ``pip install rdtools[notebooks]``. Documentation ------------- diff --git a/docs/system_availability_example.ipynb b/docs/system_availability_example.ipynb index 0b1af9f77..ac589f674 100644 --- a/docs/system_availability_example.ipynb +++ b/docs/system_availability_example.ipynb @@ -6,7 +6,7 @@ "source": [ "# System availability example\n", "\n", - "This notebook shows example usage of the inverter availability functions. As with the degradation and soiling example, we recommend installing the specific versions of packages used to develop this notebook. This can be achieved in your environment by running `pip install -r requirements.txt` followed by `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) These environments and examples are tested with Python 3.12.\n", + "This notebook shows example usage of the inverter availability functions. For a consistent experience, we recommend using [pixi](https://pixi.sh) to set up the notebook environment. From the base directory, run `pixi run -e notebooks lab` to launch JupyterLab with all required packages. Alternatively, install manually with `pip install rdtools[notebooks]`. These environments and examples are tested with Python 3.13.\n", "\n", "RdTools currently implements two methods of quantifying system availability. The first method compares power measurements from inverters and the system meter to distinguish subsystem communication interruptions from true outage events. The second method determines the uncertainty bounds around an energy estimate of a total system outage and compares with true production calculated from a meter's cumulative production measurements. The RdTools `AvailabilityAnalysis` class uses both methods to quantify downtime loss.\n", "\n", diff --git a/pixi.lock b/pixi.lock new file mode 100644 index 000000000..1d6c91ef4 --- /dev/null +++ b/pixi.lock @@ -0,0 +1,18361 @@ +version: 6 +environments: + core: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.12-hc97d973_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/d6/40/7b7ac152c35c32da2a00ba3523ea84c358478b12ee7b3b2b6892e5b9d81b/arch-8.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2b/0a/7b98e1e119878a27ba8618ca1e18b14f992ff1eda40f47bccccf4de44121/kiwisolver-1.5.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/75/97/a471f1c3eb1fd6f6c24a31a5858f443891d5127e63a7788678d14e249aea/matplotlib-3.10.8-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f2/85/ab6d04733a7d6ff32bfc8382bf1b07078228f5d6ebec5266b91bfc5c4ff7/pandas-3.0.1-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/24/538bff45bde96535d7d998c6fed1a751c75ac7c53c37c90dc2601b243893/pillow-12.1.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/cf/06896db3f71c75902a8e9943b444a56e727418f6b4b4a90c98c934f51ed4/scikit_learn-1.8.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/5f/f17563f28ff03c7b6799c50d01d5d856a1d55f2676f537ca8d28c7f627cd/scipy-1.17.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/b9/fd41f1f6af13a1a1212a06bb377b17762feaa6d656947bf666f76300fc05/statsmodels-0.14.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libmpdec-4.0.0-hf3981d6_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.13.12-h894a449_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/d6/51/78f84f9e486e173356931b2bfaf0c2a6d6923f1e8975045e3416ac388215/arch-8.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ce/48/adbb40df306f587054a348831220812b9b1d787aff714cfbc8556e38fccd/kiwisolver-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/3d/b9/15fd5541ef4f5b9a17eefd379356cf12175fe577424e7b1d80676516031a/matplotlib-3.10.8-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0b/48/aad6ec4f8d007534c091e9a7172b3ec1b1ee6d99a9cbb936b5eab6c6cf58/pandas-3.0.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/14/a1/16c4b823838ba4c9c52c0e6bbda903a3fe5a1bdbf1b8eb4fff7156f3e318/pillow-12.1.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/03/aa/e22e0768512ce9255eba34775be2e85c2048da73da1193e841707f8f039c/scikit_learn-1.8.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/76/27/07ee1b57b65e92645f219b37148a7e7928b82e2b5dbeccecb4dff7c64f0b/scipy-1.17.1-cp313-cp313-macosx_10_14_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/59/a5aad5b0cc266f5be013db8cde563ac5d2a025e7efc0c328d83b50c72992/statsmodels-0.14.6-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libmpdec-4.0.0-h84a0fba_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.13.12-h20e6be0_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/cb/b8/73910773efffc2d35d2739be1bdc70dfcc58a83cff35c4d62e14acceca2b/arch-8.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/3a/d0a972b34e1c63e2409413104216cd1caa02c5a37cb668d1687d466c1c45/kiwisolver-1.5.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/8d/a0/2ba3473c1b66b9c74dc7107c67e9008cb1782edbe896d4c899d39ae9cf78/matplotlib-3.10.8-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/14/5990826f779f79148ae9d3a2c39593dc04d61d5d90541e71b5749f35af95/pandas-3.0.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bb/ad/ad9dc98ff24f485008aa5cdedaf1a219876f6f6c42a4626c08bc4e80b120/pillow-12.1.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/58/37/31b83b2594105f61a381fc74ca19e8780ee923be2d496fcd8d2e1147bd99/scikit_learn-1.8.0-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ec/ae/db19f8ab842e9b724bf5dbb7db29302a91f1e55bc4d04b1025d6d605a2c5/scipy-1.17.1-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/dd/d8cfa7922fc6dc3c56fa6c59b348ea7de829a94cd73208c6f8202dd33f17/statsmodels-0.14.6-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.13.12-h09917c8_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/f1/e7/2d15374129c03b6f97321f837190cb19863204dbcff289e23cc37f035c96/arch-8.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/be/8a/be60e3bbcf513cc5a50f4a3e88e1dcecebb79c1ad607a7222877becaa101/kiwisolver-1.5.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/64/40/37612487cc8a437d4dd261b32ca21fe2d79510fe74af74e1f42becb1bdb8/matplotlib-3.10.8-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/7d/216a1588b65a7aa5f4535570418a599d943c85afb1d95b0876fc00aa1468/pandas-3.0.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/eb/b0834ad8b583d7d9d42b80becff092082a1c3c156bb582590fcc973f1c7c/pillow-12.1.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1c/f9/9b7563caf3ec8873e17a31401858efab6b39a882daf6c1bfa88879c0aa11/scikit_learn-1.8.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/35/e5/d6d0e51fc888f692a35134336866341c08655d92614f492c6860dc45bb2c/scipy-1.17.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/08/b79f0c614f38e566eebbdcff90c0bcacf3c6ba7a5bbb12183c09c29ca400/statsmodels-0.14.6-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ + default: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.12-hc97d973_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/40/7b7ac152c35c32da2a00ba3523ea84c358478b12ee7b3b2b6892e5b9d81b/arch-8.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2b/0a/7b98e1e119878a27ba8618ca1e18b14f992ff1eda40f47bccccf4de44121/kiwisolver-1.5.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d0/34/9e591954939276bb679b73773836c6684c22e56d05980e31d52a9a8deb18/lxml-6.0.2-cp313-cp313-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a9/21/9b05698b46f218fc0e118e1f8168395c65c8a2c750ae2bab54fc4bd4e0e8/markupsafe-3.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/75/97/a471f1c3eb1fd6f6c24a31a5858f443891d5127e63a7788678d14e249aea/matplotlib-3.10.8-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fc/f9/c9457652dfe28e2eb898372da2fe786c6db81af9540c0f853ee04a0699cc/numexpr-2.14.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f2/85/ab6d04733a7d6ff32bfc8382bf1b07078228f5d6ebec5266b91bfc5c4ff7/pandas-3.0.1-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/24/538bff45bde96535d7d998c6fed1a751c75ac7c53c37c90dc2601b243893/pillow-12.1.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f8/9b/c108cdb55560eaf253f0cbdb61b29971e9fb34d9c3499b0e96e4e60ed8a5/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/de/f7192e12b21b9e9a68a6d0f249b4af3fdcdff8418be0767a627564afa1f1/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/38/cf/06896db3f71c75902a8e9943b444a56e727418f6b4b4a90c98c934f51ed4/scikit_learn-1.8.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/5f/f17563f28ff03c7b6799c50d01d5d856a1d55f2676f537ca8d28c7f627cd/scipy-1.17.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/b9/fd41f1f6af13a1a1212a06bb377b17762feaa6d656947bf666f76300fc05/statsmodels-0.14.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libmpdec-4.0.0-hf3981d6_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.13.12-h894a449_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/51/78f84f9e486e173356931b2bfaf0c2a6d6923f1e8975045e3416ac388215/arch-8.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ce/48/adbb40df306f587054a348831220812b9b1d787aff714cfbc8556e38fccd/kiwisolver-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5d/f4/2a94a3d3dfd6c6b433501b8d470a1960a20ecce93245cf2db1706adf6c19/lxml-6.0.2-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/38/2f/907b9c7bbba283e68f20259574b13d005c121a0fa4c175f9bed27c4597ff/markupsafe-3.0.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/3d/b9/15fd5541ef4f5b9a17eefd379356cf12175fe577424e7b1d80676516031a/matplotlib-3.10.8-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/73/b4/9f6d637fd79df42be1be29ee7ba1f050fab63b7182cb922a0e08adc12320/numexpr-2.14.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0b/48/aad6ec4f8d007534c091e9a7172b3ec1b1ee6d99a9cbb936b5eab6c6cf58/pandas-3.0.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/14/a1/16c4b823838ba4c9c52c0e6bbda903a3fe5a1bdbf1b8eb4fff7156f3e318/pillow-12.1.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ed/dc/d61221eb88ff410de3c49143407f6f3147acf2538c86f2ab7ce65ae7d5f9/rpds_py-0.30.0-cp313-cp313-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/aa/e22e0768512ce9255eba34775be2e85c2048da73da1193e841707f8f039c/scikit_learn-1.8.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/76/27/07ee1b57b65e92645f219b37148a7e7928b82e2b5dbeccecb4dff7c64f0b/scipy-1.17.1-cp313-cp313-macosx_10_14_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/59/a5aad5b0cc266f5be013db8cde563ac5d2a025e7efc0c328d83b50c72992/statsmodels-0.14.6-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libmpdec-4.0.0-h84a0fba_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.13.12-h20e6be0_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b8/73910773efffc2d35d2739be1bdc70dfcc58a83cff35c4d62e14acceca2b/arch-8.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/3a/d0a972b34e1c63e2409413104216cd1caa02c5a37cb668d1687d466c1c45/kiwisolver-1.5.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/fd/4e8f0540608977aea078bf6d79f128e0e2c2bba8af1acf775c30baa70460/lxml-6.0.2-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/9c/d9/5f7756922cdd676869eca1c4e3c0cd0df60ed30199ffd775e319089cb3ed/markupsafe-3.0.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/8d/a0/2ba3473c1b66b9c74dc7107c67e9008cb1782edbe896d4c899d39ae9cf78/matplotlib-3.10.8-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/35/ae/d58558d8043de0c49f385ea2fa789e3cfe4d436c96be80200c5292f45f15/numexpr-2.14.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/14/5990826f779f79148ae9d3a2c39593dc04d61d5d90541e71b5749f35af95/pandas-3.0.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bb/ad/ad9dc98ff24f485008aa5cdedaf1a219876f6f6c42a4626c08bc4e80b120/pillow-12.1.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/32/55fb50ae104061dbc564ef15cc43c013dc4a9f4527a1f4d99baddf56fe5f/rpds_py-0.30.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/58/37/31b83b2594105f61a381fc74ca19e8780ee923be2d496fcd8d2e1147bd99/scikit_learn-1.8.0-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ec/ae/db19f8ab842e9b724bf5dbb7db29302a91f1e55bc4d04b1025d6d605a2c5/scipy-1.17.1-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/dd/d8cfa7922fc6dc3c56fa6c59b348ea7de829a94cd73208c6f8202dd33f17/statsmodels-0.14.6-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.13.12-h09917c8_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/e7/2d15374129c03b6f97321f837190cb19863204dbcff289e23cc37f035c96/arch-8.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/f7/a0b368ce54ffff9e9028c098bd2d28cfc5b54f9f6c186929083d4c60ba58/debugpy-1.8.20-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/be/8a/be60e3bbcf513cc5a50f4a3e88e1dcecebb79c1ad607a7222877becaa101/kiwisolver-1.5.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/0a/4643ccc6bb8b143e9f9640aa54e38255f9d3b45feb2cbe7ae2ca47e8782e/lxml-6.0.2-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/05/73/c4abe620b841b6b791f2edc248f556900667a5a1cf023a6646967ae98335/markupsafe-3.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/64/40/37612487cc8a437d4dd261b32ca21fe2d79510fe74af74e1f42becb1bdb8/matplotlib-3.10.8-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cc/23/9281bceaeb282cead95f0aa5f7f222ffc895670ea689cc1398355f6e3001/numexpr-2.14.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/7d/216a1588b65a7aa5f4535570418a599d943c85afb1d95b0876fc00aa1468/pandas-3.0.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/eb/b0834ad8b583d7d9d42b80becff092082a1c3c156bb582590fcc973f1c7c/pillow-12.1.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/cb/58d6ed3fd429c96a90ef01ac9a617af10a6d41469219c25e7dc162abbb71/pywinpty-3.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fc/7f/a21b20d577e4100c6a41795842028235998a643b1ad406a6d4163ea8f53e/pyzmq-27.1.0-cp312-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f2/e1/485132437d20aa4d3e1d8b3fb5a5e65aa8139f1e097080c2a8443201742c/rpds_py-0.30.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/f9/9b7563caf3ec8873e17a31401858efab6b39a882daf6c1bfa88879c0aa11/scikit_learn-1.8.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/35/e5/d6d0e51fc888f692a35134336866341c08655d92614f492c6860dc45bb2c/scipy-1.17.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/08/b79f0c614f38e566eebbdcff90c0bcacf3c6ba7a5bbb12183c09c29ca400/statsmodels-0.14.6-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ + dev: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.12-hc97d973_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/40/7b7ac152c35c32da2a00ba3523ea84c358478b12ee7b3b2b6892e5b9d81b/arch-8.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e4/dc/b2442d10020c2f52617828862d8b6ee337859cd8f3a1f13d607dddda9cf7/coverage-7.13.4-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2b/0a/7b98e1e119878a27ba8618ca1e18b14f992ff1eda40f47bccccf4de44121/kiwisolver-1.5.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d0/34/9e591954939276bb679b73773836c6684c22e56d05980e31d52a9a8deb18/lxml-6.0.2-cp313-cp313-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a9/21/9b05698b46f218fc0e118e1f8168395c65c8a2c750ae2bab54fc4bd4e0e8/markupsafe-3.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/75/97/a471f1c3eb1fd6f6c24a31a5858f443891d5127e63a7788678d14e249aea/matplotlib-3.10.8-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fc/f9/c9457652dfe28e2eb898372da2fe786c6db81af9540c0f853ee04a0699cc/numexpr-2.14.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f2/85/ab6d04733a7d6ff32bfc8382bf1b07078228f5d6ebec5266b91bfc5c4ff7/pandas-3.0.1-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/24/538bff45bde96535d7d998c6fed1a751c75ac7c53c37c90dc2601b243893/pillow-12.1.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f8/9b/c108cdb55560eaf253f0cbdb61b29971e9fb34d9c3499b0e96e4e60ed8a5/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/de/f7192e12b21b9e9a68a6d0f249b4af3fdcdff8418be0767a627564afa1f1/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/38/cf/06896db3f71c75902a8e9943b444a56e727418f6b4b4a90c98c934f51ed4/scikit_learn-1.8.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/5f/f17563f28ff03c7b6799c50d01d5d856a1d55f2676f537ca8d28c7f627cd/scipy-1.17.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/b9/fd41f1f6af13a1a1212a06bb377b17762feaa6d656947bf666f76300fc05/statsmodels-0.14.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libmpdec-4.0.0-hf3981d6_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.13.12-h894a449_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/51/78f84f9e486e173356931b2bfaf0c2a6d6923f1e8975045e3416ac388215/arch-8.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/db/23/aad45061a31677d68e47499197a131eea55da4875d16c1f42021ab963503/coverage-7.13.4-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ce/48/adbb40df306f587054a348831220812b9b1d787aff714cfbc8556e38fccd/kiwisolver-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5d/f4/2a94a3d3dfd6c6b433501b8d470a1960a20ecce93245cf2db1706adf6c19/lxml-6.0.2-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/38/2f/907b9c7bbba283e68f20259574b13d005c121a0fa4c175f9bed27c4597ff/markupsafe-3.0.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/3d/b9/15fd5541ef4f5b9a17eefd379356cf12175fe577424e7b1d80676516031a/matplotlib-3.10.8-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/73/b4/9f6d637fd79df42be1be29ee7ba1f050fab63b7182cb922a0e08adc12320/numexpr-2.14.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0b/48/aad6ec4f8d007534c091e9a7172b3ec1b1ee6d99a9cbb936b5eab6c6cf58/pandas-3.0.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/14/a1/16c4b823838ba4c9c52c0e6bbda903a3fe5a1bdbf1b8eb4fff7156f3e318/pillow-12.1.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ed/dc/d61221eb88ff410de3c49143407f6f3147acf2538c86f2ab7ce65ae7d5f9/rpds_py-0.30.0-cp313-cp313-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/aa/e22e0768512ce9255eba34775be2e85c2048da73da1193e841707f8f039c/scikit_learn-1.8.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/76/27/07ee1b57b65e92645f219b37148a7e7928b82e2b5dbeccecb4dff7c64f0b/scipy-1.17.1-cp313-cp313-macosx_10_14_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/59/a5aad5b0cc266f5be013db8cde563ac5d2a025e7efc0c328d83b50c72992/statsmodels-0.14.6-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libmpdec-4.0.0-h84a0fba_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.13.12-h20e6be0_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b8/73910773efffc2d35d2739be1bdc70dfcc58a83cff35c4d62e14acceca2b/arch-8.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/a5/70/9b8b67a0945f3dfec1fd896c5cefb7c19d5a3a6d74630b99a895170999ae/coverage-7.13.4-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/3a/d0a972b34e1c63e2409413104216cd1caa02c5a37cb668d1687d466c1c45/kiwisolver-1.5.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/fd/4e8f0540608977aea078bf6d79f128e0e2c2bba8af1acf775c30baa70460/lxml-6.0.2-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/9c/d9/5f7756922cdd676869eca1c4e3c0cd0df60ed30199ffd775e319089cb3ed/markupsafe-3.0.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/8d/a0/2ba3473c1b66b9c74dc7107c67e9008cb1782edbe896d4c899d39ae9cf78/matplotlib-3.10.8-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/35/ae/d58558d8043de0c49f385ea2fa789e3cfe4d436c96be80200c5292f45f15/numexpr-2.14.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/14/5990826f779f79148ae9d3a2c39593dc04d61d5d90541e71b5749f35af95/pandas-3.0.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bb/ad/ad9dc98ff24f485008aa5cdedaf1a219876f6f6c42a4626c08bc4e80b120/pillow-12.1.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/32/55fb50ae104061dbc564ef15cc43c013dc4a9f4527a1f4d99baddf56fe5f/rpds_py-0.30.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/58/37/31b83b2594105f61a381fc74ca19e8780ee923be2d496fcd8d2e1147bd99/scikit_learn-1.8.0-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ec/ae/db19f8ab842e9b724bf5dbb7db29302a91f1e55bc4d04b1025d6d605a2c5/scipy-1.17.1-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/dd/d8cfa7922fc6dc3c56fa6c59b348ea7de829a94cd73208c6f8202dd33f17/statsmodels-0.14.6-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.13.12-h09917c8_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/e7/2d15374129c03b6f97321f837190cb19863204dbcff289e23cc37f035c96/arch-8.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e2/0c/dbfafbe90a185943dcfbc766fe0e1909f658811492d79b741523a414a6cc/coverage-7.13.4-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/f7/a0b368ce54ffff9e9028c098bd2d28cfc5b54f9f6c186929083d4c60ba58/debugpy-1.8.20-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/be/8a/be60e3bbcf513cc5a50f4a3e88e1dcecebb79c1ad607a7222877becaa101/kiwisolver-1.5.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/0a/4643ccc6bb8b143e9f9640aa54e38255f9d3b45feb2cbe7ae2ca47e8782e/lxml-6.0.2-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/05/73/c4abe620b841b6b791f2edc248f556900667a5a1cf023a6646967ae98335/markupsafe-3.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/64/40/37612487cc8a437d4dd261b32ca21fe2d79510fe74af74e1f42becb1bdb8/matplotlib-3.10.8-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cc/23/9281bceaeb282cead95f0aa5f7f222ffc895670ea689cc1398355f6e3001/numexpr-2.14.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/7d/216a1588b65a7aa5f4535570418a599d943c85afb1d95b0876fc00aa1468/pandas-3.0.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/eb/b0834ad8b583d7d9d42b80becff092082a1c3c156bb582590fcc973f1c7c/pillow-12.1.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/cb/58d6ed3fd429c96a90ef01ac9a617af10a6d41469219c25e7dc162abbb71/pywinpty-3.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fc/7f/a21b20d577e4100c6a41795842028235998a643b1ad406a6d4163ea8f53e/pyzmq-27.1.0-cp312-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f2/e1/485132437d20aa4d3e1d8b3fb5a5e65aa8139f1e097080c2a8443201742c/rpds_py-0.30.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/f9/9b7563caf3ec8873e17a31401858efab6b39a882daf6c1bfa88879c0aa11/scikit_learn-1.8.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/35/e5/d6d0e51fc888f692a35134336866341c08655d92614f492c6860dc45bb2c/scipy-1.17.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/08/b79f0c614f38e566eebbdcff90c0bcacf3c6ba7a5bbb12183c09c29ca400/statsmodels-0.14.6-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ + dev-min: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcrypt-4.4.36-hd590300_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.10.20-h3c07f61_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/8c/b2/a4a3149e1dff8723f38a5698b03e606aebb53940765abed1deaf3da6ee8e/arch-5.6.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4b/2f/8a1d989bfadd120c90114ab33e0d2a0cbde05278c1fc15e83e62d570f50a/charset_normalizer-3.4.5-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/02/aa7ec01d1a5023c4b680ab7257f9bfde9defe8fdddfe40be096ac19e8177/coverage-7.13.4-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5c/57/a23a051fcff998fdfabdd33c6721b5bad499da08b586d3676993410071f0/fonttools-4.62.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/54/a4/974b666f64c339e5b0b44fc782edee92ab3341c17367a040e41f5132c15b/h5py-3.7.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/0e/ba4ae25d03722f64de8b2c13e80d82ab537a06b30fc7065183c6439357e3/kiwisolver-1.5.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e5/ca/3ed0e1de9df496392a4c9d75b0c78f82fe5758c66bb875903cf7a9402f0b/matplotlib-3.5.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b0/f4/d67c8c39efe3c45dfd32bb2a3fc49cbbe5496e575cc42b8bac60fe7b6701/numpy-1.22.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/48/0c/a1a3a8b3e3b70c5387dea1cafbc94f7ca7d0d6aa1895babcc2be738cfab9/pandas-1.4.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/7b/f9b09a7804ec7336effb96c26d37c29d27225783dc1501b7d62dcef6ae25/pillow-12.1.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/58/f3/a49d3281cc7275164ecf89ad3497556b11d9661faa119becdf7f9d3b2125/plotly-4.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5c/6c/94d8e520b20a2502e508e1c558f338061cf409cbee78fd6a3a5c6ae812bd/property_cached-1.6.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/04/9aea6b3ed8f1cba49c0f1cab70ff9e0cc5ff03555ffe8a41a2558047358b/pvlib-0.13.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/30/76/8f099f9d6482450428b17c4d6b241281af7ce6a9de8149ca8c1c649f6792/pyzmq-27.1.0-cp310-cp310-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/67/f3/6cd296376653270ac1b423bb30bd70942d9916b6978c6f40472d6ac038e7/retrying-1.4.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/61/b5/707f6cf0066a6412aacc11d17920ea2e19e5b2f04081c64526eb35b5c6e7/rpds_py-0.30.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/23/b6/5d339516e3fbb6cde8ad87e85d9f17a3270c9e508c860785f0b6239ea33a/scikit_learn-1.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/bc/fe/72b611ba221c3367b06163992af4807515d6e0e09b3b9beee8ec22162d6f/scipy-1.8.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/a5/3e573d7e0f79e8052628357ae75109b34293556fcd0709e75dee25eed0e4/statsmodels-0.13.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/19/10/96bb5b2985677cf6cd8f1f0a85e5e58710ad7946c5a6f202a57e9f13dc3b/xgboost-1.7.0.post0-py3-none-manylinux2014_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.10.20-hea035f4_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/45/b0e6e239d06b96dd2a2782610286449c58849ac0017361fe3a49a213314e/arch-5.6.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/44/d4/7827d9ffa34d5d4d752eec907022aa417120936282fc488306f5da08c292/coverage-7.13.4-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/dd/45/86eccfdc922cb9fafc63189a9793fa9f6dd60e68a07be42e454ef2c0deae/fonttools-4.62.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/6e/5e/f34fb9d87cec244d59604ef506d82727a1e35d03713dc5771bd95dcffa5d/h5py-3.7.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/eb/8476a0818850c563ff343ea7c9c05dcdcbd689a38e01aa31657df01f91fa/kiwisolver-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2d/4a/3262e792d1db92939f820c8fae5ac298b201769e12bb11c89de33ac7bae2/matplotlib-3.5.3-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/95/6a/319e9fafb828e4a651b03b9622b781dfd80b5f1f5f31cfa6c9b734ce7cda/numpy-1.22.4-cp310-cp310-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/14/8ff04ffc7b3839e388b974ede2b1e81919164d86ce20a6f0196213645bfe/pandas-1.4.4-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1d/30/5bd3d794762481f8c8ae9c80e7b76ecea73b916959eb587521358ef0b2f9/pillow-12.1.1-cp310-cp310-macosx_10_10_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/58/f3/a49d3281cc7275164ecf89ad3497556b11d9661faa119becdf7f9d3b2125/plotly-4.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5c/6c/94d8e520b20a2502e508e1c558f338061cf409cbee78fd6a3a5c6ae812bd/property_cached-1.6.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/04/9aea6b3ed8f1cba49c0f1cab70ff9e0cc5ff03555ffe8a41a2558047358b/pvlib-0.13.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/67/b9/52aa9ec2867528b54f1e60846728d8b4d84726630874fee3a91e66c7df81/pyzmq-27.1.0-cp310-cp310-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/67/f3/6cd296376653270ac1b423bb30bd70942d9916b6978c6f40472d6ac038e7/retrying-1.4.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/06/0c/0c411a0ec64ccb6d104dcabe0e713e05e153a9a2c3c2bd2b32ce412166fe/rpds_py-0.30.0-cp310-cp310-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/17/0b7adb6df00a30bc2c4a9e30e7f1c0c611035e2a5e22721b1bec0c2a5ffc/scikit_learn-1.1.3-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/32/1b/774c35c1246fbb2ce379272d6e8ffc61f85f2a1afeb13855f9cc2ad0b8b9/scipy-1.8.1-cp310-cp310-macosx_12_0_universal2.macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/43/f47848a73f8d0a57b54a00bc5a75ca3e4671e90d66d335de341066900960/statsmodels-0.13.5-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f3/75/f2b9d58d9bfa2dfa7e5fd287eb724d956c587e1facf3e133dab8c78544b7/xgboost-1.7.0.post0-py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.10.20-h1b19095_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/fa/4165805349e21ef83f42e29305a1c724ef68855ebbc5c11c115bec0ac510/arch-5.6.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/35/b0/d69df26607c64043292644dbb9dc54b0856fabaa2cbb1eeee3331cc9e280/coverage-7.13.4-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/e0/9db48ec7f6b95bae7b20667ded54f18dba8e759ef66232c8683822ae26fc/fonttools-4.62.0-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/af/60/0b59c97efe8450ed8fbcc9fffa367a31385e2f197eaf3bd55cfca74846ea/h5py-3.7.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f3/c4/f9c8a6b4c21aed4198566e45923512986d6cef530e7263b3a5f823546561/kiwisolver-1.5.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/61/1a/584f2e77e2f88239d66314dab14839a199424319df242c783b84ae23ae41/matplotlib-3.5.3-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/12/14529e4a0749c165c2f9df5cb09873f35ffe1bac7cfdf9a26fe90bfd587a/numpy-1.22.4-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0f/29/b1b0e546affca223467bde08f000c3163a17d80982c0271151ad0a7af3c8/pandas-1.4.4-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bd/c1/aab9e8f3eeb4490180e357955e15c2ef74b31f64790ff356c06fb6cf6d84/pillow-12.1.1-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/58/f3/a49d3281cc7275164ecf89ad3497556b11d9661faa119becdf7f9d3b2125/plotly-4.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5c/6c/94d8e520b20a2502e508e1c558f338061cf409cbee78fd6a3a5c6ae812bd/property_cached-1.6.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/04/9aea6b3ed8f1cba49c0f1cab70ff9e0cc5ff03555ffe8a41a2558047358b/pvlib-0.13.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/67/b9/52aa9ec2867528b54f1e60846728d8b4d84726630874fee3a91e66c7df81/pyzmq-27.1.0-cp310-cp310-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/67/f3/6cd296376653270ac1b423bb30bd70942d9916b6978c6f40472d6ac038e7/retrying-1.4.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/19/6a/4ba3d0fb7297ebae71171822554abe48d7cab29c28b8f9f2c04b79988c05/rpds_py-0.30.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/9a/3b/e7aca9745952d3abe278fcf68ed8106ea98b8e049f05a4047a3b5a6cb706/scikit_learn-1.1.3-cp310-cp310-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/2e/46/6d56589815f106f8851e4636d838740aaf8f26bb5ec857b2f6c0780a33de/scipy-1.8.1-cp310-cp310-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/9c/3f92cb98d9e632ad8e38b9bb45f332be57c6cc74852da936a18f97f76ab7/statsmodels-0.13.5-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/89/3faeac4661c2431422207c6694a84b6ab52ce85e1d87aac0420e9d83b82f/xgboost-1.7.0.post0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.10.20-hc20f281_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/2f/84/12132d3ee536b3147fd8c81cefbe6a2ced0105f6a0c9b8894a0bf3b6d839/arch-5.6.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a5/c3/84fb174e7770f2df2e1a2115090771bfbc2227fb39a765c6d00568d1aab4/charset_normalizer-3.4.5-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/78/13/331f94934cf6c092b8ea59ff868eb587bc8fe0893f02c55bc6c0183a192e/coverage-7.13.4-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/72/43/09d49106e770fe558ced5e80df2e3c2ebee10e576eda155dcc5670473663/debugpy-1.8.20-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e9/ee/08c0b7f8bac6e44638de6fe9a3e710a623932f60eccd58912c4d4743516d/fonttools-4.62.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/bd/18/f5eed64fc06b9d17ef11647d6c5016b8a97e3abf0afe6d080c070027a195/h5py-3.7.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/75/2b/3f641dfcbe72e222175d626bacf2f72c3b34312afec949dd1c50afa400f5/kiwisolver-1.5.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/90/81/b73cb7d615a70a01bd349b8e85a7648c51f3a6346695354c1ce569db6d8f/matplotlib-3.5.3-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/50/d7978137464251c393df28fe0592fbb968110f752d66f60c7a53f7158076/numpy-1.22.4-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4a/5b/d74c7faadceffce80a6fde9823bdfca69b1b6bdc307ce6df5b06e109f210/pandas-1.4.4-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/f9/9f6b01c0881d7036063aa6612ef04c0e2cad96be21325a1e92d0203f8e91/pillow-12.1.1-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/58/f3/a49d3281cc7275164ecf89ad3497556b11d9661faa119becdf7f9d3b2125/plotly-4.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5c/6c/94d8e520b20a2502e508e1c558f338061cf409cbee78fd6a3a5c6ae812bd/property_cached-1.6.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/04/9aea6b3ed8f1cba49c0f1cab70ff9e0cc5ff03555ffe8a41a2558047358b/pvlib-0.13.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/b2/f4ab56c8c595abcb26b2be5fd9fa9e6899c1e5ad54964e93ae8bb35482be/pyzmq-27.1.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/67/f3/6cd296376653270ac1b423bb30bd70942d9916b6978c6f40472d6ac038e7/retrying-1.4.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/96/cb/156d7a5cf4f78a7cc571465d8aec7a3c447c94f6749c5123f08438bcf7bc/rpds_py-0.30.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fe/28/2b78c8efceeb07e73cef24af458dd8241cc6c4b39abc7bf375ba38b07d28/scikit_learn-1.1.3-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/31/c2/0b8758ebaeb43e089eb56168390824a830f9f419ae07d755d99a46e5a937/scipy-1.8.1-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bf/0b/7f303511e59a4434dd0e9a8c4d550b7a5f32acb7c94821ccd3a465ef3137/statsmodels-0.13.5-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/85/ef/d8910ec6229a45b4d8d920858b91f7196eafabad254be9eb508b934d3c18/xgboost-1.7.0.post0-py3-none-win_amd64.whl + - pypi: ./ + dev-py310: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcrypt-4.4.36-hd590300_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.10.20-h3c07f61_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/44/c5/0e9a7a85eb0135d8d551660bb930561a49a506fe9d086cdefb530589f654/arch-8.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/29/9b366e70e243eb3d14a5cb488dfd3a0b6b2f1fb001a203f653b93ccfac88/cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4b/2f/8a1d989bfadd120c90114ab33e0d2a0cbde05278c1fc15e83e62d570f50a/charset_normalizer-3.4.5-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/5c/1ee32d1c7956923202f00cf8d2a14a62ed7517bdc0ee1e55301227fc273c/contourpy-1.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f8/02/aa7ec01d1a5023c4b680ab7257f9bfde9defe8fdddfe40be096ac19e8177/coverage-7.13.4-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5c/57/a23a051fcff998fdfabdd33c6721b5bad499da08b586d3676993410071f0/fonttools-4.62.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/92/a8851d936547efe30cc0ce5245feac01f3ec6171f7899bc3f775c72030b3/h5py-3.16.0-cp310-cp310-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/0e/ba4ae25d03722f64de8b2c13e80d82ab537a06b30fc7065183c6439357e3/kiwisolver-1.5.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/20/cf/cab09478699b003857ed6ebfe95e9fb9fa3d3c25f1353b905c9b73cfb624/lxml-6.0.2-cp310-cp310-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/cd/ce6e848bbf2c32314c9b237839119c5a564a59725b53157c856e90937b7a/markupsafe-3.0.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cb/aa/7ab67f2b729ae6a91bcf9dcac0affb95fb8c56f7fd2b2af894ae0b0cf6fa/matplotlib-3.10.8-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/d4/d1a410901c620f7a6a3c5c2b1fc9dab22170be05a89d2c02ae699e27bd3f/numexpr-2.14.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b4/63/3de6a34ad7ad6646ac7d2f55ebc6ad439dbbf9c4370017c50cf403fb19b5/numpy-2.2.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/40/a8/4dac1f8f8235e5d25b9955d02ff6f29396191d4e665d71122c3722ca83c5/pandas-2.3.3-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/7b/f9b09a7804ec7336effb96c26d37c29d27225783dc1501b7d62dcef6ae25/pillow-12.1.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7a/1e/7acc4f0e74c4b3d9531e24739e0ab832a5edf40e64fbae1a9c01941cabd7/pyyaml-6.0.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/30/76/8f099f9d6482450428b17c4d6b241281af7ce6a9de8149ca8c1c649f6792/pyzmq-27.1.0-cp310-cp310-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/61/b5/707f6cf0066a6412aacc11d17920ea2e19e5b2f04081c64526eb35b5c6e7/rpds_py-0.30.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/58/0e/8c2a03d518fb6bd0b6b0d4b114c63d5f1db01ff0f9925d8eb10960d01c01/scikit_learn-1.7.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/8e/6d/41991e503e51fc1134502694c5fa7a1671501a17ffa12716a4a9151af3df/scipy-1.15.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/94/55/b86c861c32186403fe121d9ab27bc16d05839b170d92a978beb33abb995e/statsmodels-0.14.6-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.10.20-hea035f4_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0f/f7/addc52355dd804416b086cb85287161bb8ee0e53eb9f527f45af93dff76c/arch-8.0.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/d7/516d984057745a6cd96575eea814fe1edd6646ee6efd552fb7b0921dec83/cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/12/a3/da4153ec8fe25d263aa48c1a4cbde7f49b59af86f0b6f7862788c60da737/contourpy-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/44/d4/7827d9ffa34d5d4d752eec907022aa417120936282fc488306f5da08c292/coverage-7.13.4-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/dd/45/86eccfdc922cb9fafc63189a9793fa9f6dd60e68a07be42e454ef2c0deae/fonttools-4.62.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/6b/231413e58a787a89b316bb0d1777da3c62257e4797e09afd8d17ad3549dc/h5py-3.16.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/eb/8476a0818850c563ff343ea7c9c05dcdcbd689a38e01aa31657df01f91fa/kiwisolver-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/12/64/27bcd07ae17ff5e5536e8d88f4c7d581b48963817a13de11f3ac3329bfa2/lxml-6.0.2-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e8/4b/3541d44f3937ba468b75da9eebcae497dcf67adb65caa16760b0a6807ebb/markupsafe-3.0.3-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/58/be/a30bd917018ad220c400169fba298f2bb7003c8ccbc0c3e24ae2aacad1e8/matplotlib-3.10.8-cp310-cp310-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/db/91/ccd504cbe5b88d06987c77f42ba37a13ef05065fdab4afe6dcfeb2961faf/numexpr-2.14.1-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/9a/3e/ed6db5be21ce87955c0cbd3009f2803f59fa08df21b5df06862e2d8e2bdd/numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3d/f7/f425a00df4fcc22b292c6895c6831c0c8ae1d9fac1e024d16f98a9ce8749/pandas-2.3.3-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1d/30/5bd3d794762481f8c8ae9c80e7b76ecea73b916959eb587521358ef0b2f9/pillow-12.1.1-cp310-cp310-macosx_10_10_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/a0/39350dd17dd6d6c6507025c0e53aef67a9293a6d37d3511f23ea510d5800/pyyaml-6.0.3-cp310-cp310-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/67/b9/52aa9ec2867528b54f1e60846728d8b4d84726630874fee3a91e66c7df81/pyzmq-27.1.0-cp310-cp310-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/06/0c/0c411a0ec64ccb6d104dcabe0e713e05e153a9a2c3c2bd2b32ce412166fe/rpds_py-0.30.0-cp310-cp310-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ba/3e/daed796fd69cce768b8788401cc464ea90b306fb196ae1ffed0b98182859/scikit_learn-1.7.2-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/78/2f/4966032c5f8cc7e6a60f1b2e0ad686293b9474b65246b0c642e3ef3badd0/scipy-1.15.3-cp310-cp310-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/6d/9ec309a175956f88eb8420ac564297f37cf9b1f73f89db74da861052dc29/statsmodels-0.14.6-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.10.20-h1b19095_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/a4/30ed8bac322681cf1ec86e644f6f531aeca6b1d20a26e029df537042988f/arch-8.0.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/84/ad6a0b408daa859246f57c03efd28e5dd1b33c21737c2db84cae8c237aa5/cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2f/6c/330de89ae1087eb622bfca0177d32a7ece50c3ef07b28002de4757d9d875/contourpy-1.3.2-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/35/b0/d69df26607c64043292644dbb9dc54b0856fabaa2cbb1eeee3331cc9e280/coverage-7.13.4-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/e0/9db48ec7f6b95bae7b20667ded54f18dba8e759ef66232c8683822ae26fc/fonttools-4.62.0-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/f9/557ce3aad0fe8471fb5279bab0fc56ea473858a022c4ce8a0b8f303d64e9/h5py-3.16.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f3/c4/f9c8a6b4c21aed4198566e45923512986d6cef530e7263b3a5f823546561/kiwisolver-1.5.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/db/8a/f8192a08237ef2fb1b19733f709db88a4c43bc8ab8357f01cb41a27e7f6a/lxml-6.0.2-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/98/1b/fbd8eed11021cabd9226c37342fa6ca4e8a98d8188a8d9b66740494960e4/markupsafe-3.0.3-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/58/27/ca01e043c4841078e82cf6e80a6993dfecd315c3d79f5f3153afbb8e1ec6/matplotlib-3.10.8-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f3/89/6b07977baf2af75fb6692f9e7a1fb612a15f600fc921f3f565366de01f4a/numexpr-2.14.1-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/c2/4b9221495b2a132cc9d2eb862e21d42a009f5a60e45fc44b00118c174bff/numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/4f/66d99628ff8ce7857aca52fed8f0066ce209f96be2fede6cef9f84e8d04f/pandas-2.3.3-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bd/c1/aab9e8f3eeb4490180e357955e15c2ef74b31f64790ff356c06fb6cf6d84/pillow-12.1.1-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/05/14/52d505b5c59ce73244f59c7a50ecf47093ce4765f116cdb98286a71eeca2/pyyaml-6.0.3-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/67/b9/52aa9ec2867528b54f1e60846728d8b4d84726630874fee3a91e66c7df81/pyzmq-27.1.0-cp310-cp310-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/19/6a/4ba3d0fb7297ebae71171822554abe48d7cab29c28b8f9f2c04b79988c05/rpds_py-0.30.0-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/ce/af9d99533b24c55ff4e18d9b7b4d9919bbc6cd8f22fe7a7be01519a347d5/scikit_learn-1.7.2-cp310-cp310-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/a0/6e/0c3bf90fae0e910c274db43304ebe25a6b391327f3f10b5dcc638c090795/scipy-1.15.3-cp310-cp310-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/86/8f/338c5568315ec5bf3ac7cd4b71e34b98cb3b0f834919c0c04a0762f878a1/statsmodels-0.14.6-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.10.20-hc20f281_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2e/41/d6aa187e4f6d1567b51ac8a1d12ec1a78a55310fad2a7f2300a251cfbb89/arch-8.0.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/fa/072dd15ae27fbb4e06b437eb6e944e75b068deb09e2a2826039e49ee2045/cffi-2.0.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a5/c3/84fb174e7770f2df2e1a2115090771bfbc2227fb39a765c6d00568d1aab4/charset_normalizer-3.4.5-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/ec/5162b8582f2c994721018d0c9ece9dc6ff769d298a8ac6b6a652c307e7df/contourpy-1.3.2-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/78/13/331f94934cf6c092b8ea59ff868eb587bc8fe0893f02c55bc6c0183a192e/coverage-7.13.4-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/72/43/09d49106e770fe558ced5e80df2e3c2ebee10e576eda155dcc5670473663/debugpy-1.8.20-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e9/ee/08c0b7f8bac6e44638de6fe9a3e710a623932f60eccd58912c4d4743516d/fonttools-4.62.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/66/35/d88fd6718832133c885004c61ceeeb24dbd6397ef877dbed6b3a64d6a286/h5py-3.16.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/75/2b/3f641dfcbe72e222175d626bacf2f72c3b34312afec949dd1c50afa400f5/kiwisolver-1.5.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/70/bd42491f0634aad41bdfc1e46f5cff98825fb6185688dc82baa35d509f1a/lxml-6.0.2-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d6/25/55dc3ab959917602c96985cb1253efaa4ff42f71194bddeb61eb7278b8be/markupsafe-3.0.3-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e2/e2/fd0bbadf837f81edb0d208ba8f8cb552874c3b16e27cb91a31977d90875d/matplotlib-3.10.8-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/af/26773a246716922794388786529e5640676399efabb0ee217ce034df9d27/numexpr-2.14.1-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a3/dd/4b822569d6b96c39d1215dbae0582fd99954dcbcf0c1a13c61783feaca3f/numpy-2.2.6-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/85/72/530900610650f54a35a19476eca5104f38555afccda1aa11a92ee14cb21d/pandas-2.3.3-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/f9/9f6b01c0881d7036063aa6612ef04c0e2cad96be21325a1e92d0203f8e91/pillow-12.1.1-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/28/a652709bd76ca7533cd1c443b03add9f5051fdf71bc6bdb8801dddd4e7a3/pywinpty-3.0.3-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2a/fa/926c003379b19fca39dd4634818b00dec6c62d87faf628d1394e137354d4/pyyaml-6.0.3-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/62/b2/f4ab56c8c595abcb26b2be5fd9fa9e6899c1e5ad54964e93ae8bb35482be/pyzmq-27.1.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/96/cb/156d7a5cf4f78a7cc571465d8aec7a3c447c94f6749c5123f08438bcf7bc/rpds_py-0.30.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7f/9b/87961813c34adbca21a6b3f6b2bea344c43b30217a6d24cc437c6147f3e8/scikit_learn-1.7.2-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/84/55bc4881973d3f79b479a5a2e2df61c8c9a04fcb986a213ac9c02cfb659b/scipy-1.15.3-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/1c/2e10b7c7cc44fa418272996bf0427b8016718fd62f995d9c1f7ab37adf35/statsmodels-0.14.6-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ + dev-py311: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcrypt-4.4.36-hd590300_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.11.15-hd63d673_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bc/00/7cc035e2a08b9186cfbd0b5d3dd3967481f64722c3af69416edc8a182fd7/arch-8.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/91/500d892b2bf36529a75b77958edfcd5ad8e2ce4064ce2ecfeab2125d72d1/cffi-2.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/f4/44d3b830a20e89ff82a3134912d9a1cf6084d64f3b95dcad40f74449a654/charset_normalizer-3.4.5-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5f/4b/6157f24ca425b89fe2eb7e7be642375711ab671135be21e6faa100f7448c/contourpy-1.3.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/76/53/c16972708cbb79f2942922571a687c52bd109a7bd51175aeb7558dff2236/coverage-7.13.4-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8a/d7/8e4845993ee233c2023d11babe9b3dae7d30333da1d792eeccebcb77baab/fonttools-4.62.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/a0/c1f604538ff6db22a0690be2dc44ab59178e115f63c917794e529356ab23/h5py-3.16.0-cp311-cp311-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3d/aa/898dec789a05731cd5a9f50605b7b44a72bd198fd0d4528e11fc610177cc/ipython-9.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/46/bddc13df6c2a40741e0cc7865bb1c9ed4796b6760bd04ce5fae3928ef917/kiwisolver-1.5.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b8/89/ea8f91594bc5dbb879734d35a6f2b0ad50605d7fb419de2b63d4211765cc/lxml-6.0.2-cp311-cp311-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/30/ac/0273f6fcb5f42e314c6d8cd99effae6a5354604d461b8d392b5ec9530a54/markupsafe-3.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/8f/a0/7024215e95d456de5883e6732e708d8187d9753a21d32f8ddb3befc0c445/matplotlib-3.10.8-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4c/1a/edbe839109518364ac0bd9e918cf874c755bb2c128040e920f198c494263/numexpr-2.14.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/78/51/9f5d7a41f0b51649ddf2f2320595e15e122a40610b233d51928dd6c92353/numpy-2.4.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2e/7c/870c7e7daec2a6c7ff2ac9e33b23317230d4e4e954b35112759ea4a924a7/pandas-3.0.1-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a2/c8/46dfeac5825e600579157eea177be43e2f7ff4a99da9d0d0a49533509ac5/pillow-12.1.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/60/917329f640924b18ff085ab889a11c763e0b573da888e8404ff486657602/pyyaml-6.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b1/c4/2a6fe5111a01005fc7af3878259ce17684fabb8852815eda6225620f3c59/pyzmq-27.1.0-cp311-cp311-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/1e/372195d326549bb51f0ba0f2ecb9874579906b97e08880e7a65c3bef1a99/rpds_py-0.30.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/36/4d/4a67f30778a45d542bbea5db2dbfa1e9e100bf9ba64aefe34215ba9f11f6/scikit_learn-1.8.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/09/7d/af933f0f6e0767995b4e2d705a0665e454d1c19402aa7e895de3951ebb04/scipy-1.17.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/40/c6/9ae8e9b0721e9b6eb5f340c3a0ce8cd7cce4f66e03dd81f80d60f111987f/statsmodels-0.14.6-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.11.15-ha9537fe_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/44/b5/8f04a871c2e0f94430c15d313f88fe7808d80c4752b0ebdeadfec21dec8e/arch-8.0.0-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/12/4a/3dfd5f7850cbf0d06dc84ba9aa00db766b52ca38d8b86e3a38314d52498c/cffi-2.0.0-cp311-cp311-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/8f/9e/bcec3b22c64ecec47d39bf5167c2613efd41898c019dccd4183f6aa5d6a7/charset_normalizer-3.4.5-cp311-cp311-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/91/2e/c4390a31919d8a78b90e8ecf87cd4b4c4f05a5b48d05ec17db8e5404c6f4/contourpy-1.3.3-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b4/ad/b59e5b451cf7172b8d1043dc0fa718f23aab379bc1521ee13d4bd9bfa960/coverage-7.13.4-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/7a/9aeec114bc9fc00d757a41f092f7107863d372e684a5b5724c043654477c/fonttools-4.62.0-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ba/95/a825894f3e45cbac7554c4e97314ce886b233a20033787eda755ca8fecc7/h5py-3.16.0-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3d/aa/898dec789a05731cd5a9f50605b7b44a72bd198fd0d4528e11fc610177cc/ipython-9.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/11/60/37b4047a2af0cf5ef6d8b4b26e91829ae6fc6a2d1f74524bcb0e7cd28a32/kiwisolver-1.5.0-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/28/66/1ced58f12e804644426b85d0bb8a4478ca77bc1761455da310505f1a3526/lxml-6.0.2-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/08/db/fefacb2136439fc8dd20e797950e749aa1f4997ed584c62cfb8ef7c2be0e/markupsafe-3.0.3-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f8/86/de7e3a1cdcfc941483af70609edc06b83e7c8a0e0dc9ac325200a3f4d220/matplotlib-3.10.8-cp311-cp311-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/a3/67999bdd1ed1f938d38f3fedd4969632f2f197b090e50505f7cc1fa82510/numexpr-2.14.1-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f9/51/5093a2df15c4dc19da3f79d1021e891f5dcf1d9d1db6ba38891d5590f3fe/numpy-2.4.3-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ff/07/c7087e003ceee9b9a82539b40414ec557aa795b584a1a346e89180853d79/pandas-3.0.1-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2b/46/5da1ec4a5171ee7bf1a0efa064aba70ba3d6e0788ce3f5acd1375d23c8c0/pillow-12.1.1-cp311-cp311-macosx_10_10_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6d/16/a95b6757765b7b031c9374925bb718d55e0a9ba8a1b6a12d25962ea44347/pyyaml-6.0.3-cp311-cp311-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/06/5d/305323ba86b284e6fcb0d842d6adaa2999035f70f8c38a9b6d21ad28c3d4/pyzmq-27.1.0-cp311-cp311-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4d/6e/f964e88b3d2abee2a82c1ac8366da848fce1c6d834dc2132c3fda3970290/rpds_py-0.30.0-cp311-cp311-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/c9/92/53ea2181da8ac6bf27170191028aee7251f8f841f8d3edbfdcaf2008fde9/scikit_learn-1.8.0-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/df/75/b4ce781849931fef6fd529afa6b63711d5a733065722d0c3e2724af9e40a/scipy-1.17.1-cp311-cp311-macosx_10_14_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/4d/df4dd089b406accfc3bb5ee53ba29bb3bdf5ae61643f86f8f604baa57656/statsmodels-0.14.6-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.11.15-h8561d8f_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/42/7f1b880857839ea0841304586715c7d2a477552d04bcde32d1d55d8ccaa0/arch-8.0.0-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4f/8b/f0e4c441227ba756aafbe78f117485b25bb26b1c059d01f137fa6d14896b/cffi-2.0.0-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/8f/9e/bcec3b22c64ecec47d39bf5167c2613efd41898c019dccd4183f6aa5d6a7/charset_normalizer-3.4.5-cp311-cp311-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/44/c4b0b6095fef4dc9c420e041799591e3b63e9619e3044f7f4f6c21c0ab24/contourpy-1.3.3-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/f1/17/0cb7ca3de72e5f4ef2ec2fa0089beafbcaaaead1844e8b8a63d35173d77d/coverage-7.13.4-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e4/33/63d79ca41020dd460b51f1e0f58ad1ff0a36b7bcbdf8f3971d52836581e9/fonttools-4.62.0-cp311-cp311-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bf/3b/38ff88b347c3e346cda1d3fc1b65a7aa75d40632228d8b8a5d7b58508c24/h5py-3.16.0-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3d/aa/898dec789a05731cd5a9f50605b7b44a72bd198fd0d4528e11fc610177cc/ipython-9.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/aa/510dc933d87767584abfe03efa445889996c70c2990f6f87c3ebaa0a18c5/kiwisolver-1.5.0-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/d5/becbe1e2569b474a23f0c672ead8a29ac50b2dc1d5b9de184831bda8d14c/lxml-6.0.2-cp311-cp311-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/e1/2e/5898933336b61975ce9dc04decbc0a7f2fee78c30353c5efba7f2d6ff27a/markupsafe-3.0.3-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/fd/14/baad3222f424b19ce6ad243c71de1ad9ec6b2e4eb1e458a48fdc6d120401/matplotlib-3.10.8-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/25/95/d64f680ea1fc56d165457287e0851d6708800f9fcea346fc1b9957942ee6/numexpr-2.14.1-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b5/7c/c061f3de0630941073d2598dc271ac2f6cbcf5c83c74a5870fea07488333/numpy-2.4.3-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/27/90683c7122febeefe84a56f2cde86a9f05f68d53885cebcc473298dfc33e/pandas-3.0.1-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/78/93/a29e9bc02d1cf557a834da780ceccd54e02421627200696fcf805ebdc3fb/pillow-12.1.1-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/16/19/13de8e4377ed53079ee996e1ab0a9c33ec2faf808a4647b7b4c0d46dd239/pyyaml-6.0.3-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/06/5d/305323ba86b284e6fcb0d842d6adaa2999035f70f8c38a9b6d21ad28c3d4/pyzmq-27.1.0-cp311-cp311-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/94/ba/24e5ebb7c1c82e74c4e4f33b2112a5573ddc703915b13a073737b59b86e0/rpds_py-0.30.0-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/01/18/d154dc1638803adf987910cdd07097d9c526663a55666a97c124d09fb96a/scikit_learn-1.8.0-cp311-cp311-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/f7/58/bccc2861b305abdd1b8663d6130c0b3d7cc22e8d86663edbc8401bfd40d4/scipy-1.17.1-cp311-cp311-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/af/ec48daa7f861f993b91a0dcc791d66e1cf56510a235c5cbd2ab991a31d5c/statsmodels-0.14.6-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.11.15-h0159041_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/4b/abfe066b00a5f1f0ab80dc5b7424f9fc1008116546fefcc1d17def0be9b6/arch-8.0.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ae/8f/dc5531155e7070361eb1b7e4c1a9d896d0cb21c49f807a6c03fd63fc877e/cffi-2.0.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fe/1f/a853b73d386521fd44b7f67ded6b17b7b2367067d9106a5c4b44f9a34274/charset_normalizer-3.4.5-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/4b/9bd370b004b5c9d8045c6c33cf65bae018b27aca550a3f657cdc99acdbd8/contourpy-1.3.3-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/61/08/3d9c8613079d2b11c185b865de9a4c1a68850cfda2b357fae365cf609f29/coverage-7.13.4-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d5/92/1cb532e88560cbee973396254b21bece8c5d7c2ece958a67afa08c9f10dc/debugpy-1.8.20-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/ce/f5a4c42c117f8113ce04048053c128d17426751a508f26398110c993a074/fonttools-4.62.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f7/20/e6c0ff62ca2ad1a396a34f4380bafccaaf8791ff8fccf3d995a1fc12d417/h5py-3.16.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3d/aa/898dec789a05731cd5a9f50605b7b44a72bd198fd0d4528e11fc610177cc/ipython-9.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/be/6c/28f17390b62b8f2f520e2915095b3c94d88681ecf0041e75389d9667f202/kiwisolver-1.5.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/7d/ca6fb13349b473d5732fb0ee3eec8f6c80fc0688e76b7d79c1008481bf1f/lxml-6.0.2-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/83/8a/4414c03d3f891739326e1783338e48fb49781cc915b2e0ee052aa490d586/markupsafe-3.0.3-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/6f/d3/a4bbc01c237ab710a1f22b4da72f4ff6d77eb4c7735ea9811a94ae239067/matplotlib-3.10.8-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/72/4ca9bd97b2eb6dce9f5e70a3b6acec1a93e1fb9b079cb4cba2cdfbbf295d/numexpr-2.14.1-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/76/1d/edccf27adedb754db7c4511d5eac8b83f004ae948fe2d3509e8b78097d4c/numpy-2.4.3-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/67/af63f83cd6ca603a00fe8530c10a60f0879265b8be00b5930e8e78c5b30b/pandas-3.0.1-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/31/03/bef822e4f2d8f9d7448c133d0a18185d3cce3e70472774fffefe8b0ed562/pillow-12.1.1-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/c3/3e75075c7f71735f22b66fab0481f2c98e3a4d58cba55cb50ba29114bcf6/pywinpty-3.0.3-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/da/e3/ea007450a105ae919a72393cb06f122f288ef60bba2dc64b26e2646fa315/pyyaml-6.0.3-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/23/6d/d8d92a0eb270a925c9b4dd039c0b4dc10abc2fcbc48331788824ef113935/pyzmq-27.1.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fa/5b/e7b7aa136f28462b344e652ee010d4de26ee9fd16f1bfd5811f5153ccf89/rpds_py-0.30.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/89/3c/45c352094cfa60050bcbb967b1faf246b22e93cb459f2f907b600f2ceda5/scikit_learn-1.8.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/95/da/0d1df507cf574b3f224ccc3d45244c9a1d732c81dcb26b1e8a766ae271a8/scipy-1.17.1-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bf/cc/018f14ecb58c6cb89de9d52695740b7d1f5a982aa9ea312483ea3c3d5f77/statsmodels-0.14.6-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ + dev-py312: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcrypt-4.4.36-hd590300_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.12.13-hd63d673_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a4/d3/da7d55f51bb31a10d1b4a01a22ec0180265a5afeed0d99bd4d0c7b3a61e1/arch-8.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/78/2d/7fa73dfa841b5ac06c7b8855cfc18622132e365f5b81d02230333ff26e9e/cffi-2.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/67/5c/ae30362a88b4da237d71ea214a8c7eb915db3eec941adda511729ac25fa2/charset_normalizer-3.4.5-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cc/8f/ec6289987824b29529d0dfda0d74a07cec60e54b9c92f3c9da4c0ac732de/contourpy-1.3.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/5d/a0/2ea570925524ef4e00bb6c82649f5682a77fac5ab910a65c9284de422600/coverage-7.13.4-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0b/a1/d16318232964d786907b9b3613b8409f74cf0be2da400854509d3a864e43/fonttools-4.62.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/e9/1a19e42cd43cc1365e127db6aae85e1c671da1d9a5d746f4d34a50edb577/h5py-3.16.0-cp312-cp312-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c4/13/680c54afe3e65767bed7ec1a15571e1a2f1257128733851ade24abcefbcc/kiwisolver-1.5.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c6/d1/232b3309a02d60f11e71857778bfcd4acbdb86c07db8260caf7d008b08f8/lxml-6.0.2-cp312-cp312-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/3c/2e/8d0c2ab90a8c1d9a24f0399058ab8519a3279d1bd4289511d74e909f060e/markupsafe-3.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/3e/f3/c5195b1ae57ef85339fd7285dfb603b22c8b4e79114bae5f4f0fcf688677/matplotlib-3.10.8-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/43/560e9ba23c02c904b5934496486d061bcb14cd3ebba2e3cf0e2dccb6c22b/numexpr-2.14.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/bd/79/cc665495e4d57d0aa6fbcc0aa57aa82671dfc78fbf95fe733ed86d98f52a/numpy-2.4.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3d/fe/89d77e424365280b79d99b3e1e7d606f5165af2f2ecfaf0c6d24c799d607/pandas-3.0.1-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ff/79/6df7b2ee763d619cda2fb4fea498e5f79d984dae304d45a8999b80d6cf5c/pillow-12.1.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8b/9d/b3589d3877982d4f2329302ef98a8026e7f4443c765c46cfecc8858c6b4b/pyyaml-6.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f8/9b/c108cdb55560eaf253f0cbdb61b29971e9fb34d9c3499b0e96e4e60ed8a5/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/1b/6f8f29f3f995c7ffdde46a626ddccd7c63aefc0efae881dc13b6e5d5bb16/rpds_py-0.30.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/97/74/b7a304feb2b49df9fafa9382d4d09061a96ee9a9449a7cbea7988dda0828/scikit_learn-1.8.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/01/8e/1e35281b8ab6d5d72ebe9911edcdffa3f36b04ed9d51dec6dd140396e220/scipy-1.17.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/68/dddd76117df2ef14c943c6bbb6618be5c9401280046f4ddfc9fb4596a1b8/statsmodels-0.14.6-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.12.13-ha9537fe_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/6e/b4379d1dee984f4a51afad9bfb49a3079ae196faf0bb834b7b5ad8e5ec6a/arch-8.0.0-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ea/47/4f61023ea636104d4f16ab488e268b93008c3d0bb76893b1b31db1f96802/cffi-2.0.0-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/9c/b6/9ee9c1a608916ca5feae81a344dffbaa53b26b90be58cc2159e3332d44ec/charset_normalizer-3.4.5-cp312-cp312-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/be/45/adfee365d9ea3d853550b2e735f9d66366701c65db7855cd07621732ccfc/contourpy-1.3.3-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/d1/81/4ce2fdd909c5a0ed1f6dedb88aa57ab79b6d1fbd9b588c1ac7ef45659566/coverage-7.13.4-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4d/8b/ba59069a490f61b737e064c3129453dbd28ee38e81d56af0d04d7e6b4de4/fonttools-4.62.0-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c8/c0/5d4119dba94093bbafede500d3defd2f5eab7897732998c04b54021e530b/h5py-3.16.0-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bf/d9/405320f8077e8e1c5c4bd6adc45e1e6edf6d727b6da7f2e2533cf58bff71/kiwisolver-1.5.0-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/37/6f/9aae1008083bb501ef63284220ce81638332f9ccbfa53765b2b7502203cf/lxml-6.0.2-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/5a/72/147da192e38635ada20e0a2e1a51cf8823d2119ce8883f7053879c2199b5/markupsafe-3.0.3-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/9e/67/f997cdcbb514012eb0d10cd2b4b332667997fb5ebe26b8d41d04962fa0e6/matplotlib-3.10.8-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/20/c473fc04a371f5e2f8c5749e04505c13e7a8ede27c09e9f099b2ad6f43d6/numexpr-2.14.1-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a9/ed/6388632536f9788cea23a3a1b629f25b43eaacd7d7377e5d6bc7b9deb69b/numpy-2.4.3-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/37/51/b467209c08dae2c624873d7491ea47d2b47336e5403309d433ea79c38571/pandas-3.0.1-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/d3/8df65da0d4df36b094351dce696f2989bec731d4f10e743b1c5f4da4d3bf/pillow-12.1.1-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/33/422b98d2195232ca1826284a76852ad5a86fe23e31b009c9886b2d0fb8b2/pyyaml-6.0.3-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/03/e7/98a2f4ac921d82f33e03f3835f5bf3a4a40aa1bfdc57975e74a97b2b4bdd/rpds_py-0.30.0-cp312-cp312-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/90/74/e6a7cc4b820e95cc38cf36cd74d5aa2b42e8ffc2d21fe5a9a9c45c1c7630/scikit_learn-1.8.0-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/35/48/b992b488d6f299dbe3f11a20b24d3dda3d46f1a635ede1c46b5b17a7b163/scipy-1.17.1-cp312-cp312-macosx_10_14_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/25/ce/308e5e5da57515dd7cab3ec37ea2d5b8ff50bef1fcc8e6d31456f9fae08e/statsmodels-0.14.6-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.12.13-h8561d8f_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8d/54/ab79d924327497fddb462ce51216d193e374ad2295b1003542802ed9a021/arch-8.0.0-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/df/a2/781b623f57358e360d62cdd7a8c681f074a71d445418a776eef0aadb4ab4/cffi-2.0.0-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/9c/b6/9ee9c1a608916ca5feae81a344dffbaa53b26b90be58cc2159e3332d44ec/charset_normalizer-3.4.5-cp312-cp312-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/3e/405b59cfa13021a56bba395a6b3aca8cec012b45bf177b0eaf7a202cde2c/contourpy-1.3.3-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/5d/96/5238b1efc5922ddbdc9b0db9243152c09777804fb7c02ad1741eb18a11c0/coverage-7.13.4-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/9d/7ad1ffc080619f67d0b1e0fa6a0578f0be077404f13fd8e448d1616a94a3/fonttools-4.62.0-cp312-cp312-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b0/42/c84efcc1d4caebafb1ecd8be4643f39c85c47a80fe254d92b8b43b1eadaf/h5py-3.16.0-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/99/9f/795fedf35634f746151ca8839d05681ceb6287fbed6cc1c9bf235f7887c2/kiwisolver-1.5.0-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f3/c8/8ff2bc6b920c84355146cd1ab7d181bc543b89241cfb1ebee824a7c81457/lxml-6.0.2-cp312-cp312-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/9a/81/7e4e08678a1f98521201c3079f77db69fb552acd56067661f8c2f534a718/markupsafe-3.0.3-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/65/07d5f5c7f7c994f12c768708bd2e17a4f01a2b0f44a1c9eccad872433e2e/matplotlib-3.10.8-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/45/93/b6760dd1904c2a498e5f43d1bb436f59383c3ddea3815f1461dfaa259373/numexpr-2.14.1-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/74/1b/ee2abfc68e1ce728b2958b6ba831d65c62e1b13ce3017c13943f8f9b5b2e/numpy-2.4.3-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7c/f1/e2567ffc8951ab371db2e40b2fe068e36b81d8cf3260f06ae508700e5504/pandas-3.0.1-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/71/5026395b290ff404b836e636f51d7297e6c83beceaa87c592718747e670f/pillow-12.1.1-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/89/a0/6cf41a19a1f2f3feab0e9c0b74134aa2ce6849093d5517a0c550fe37a648/pyyaml-6.0.3-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4d/a1/bca7fd3d452b272e13335db8d6b0b3ecde0f90ad6f16f3328c6fb150c889/rpds_py-0.30.0-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/49/d8/9be608c6024d021041c7f0b3928d4749a706f4e2c3832bbede4fb4f58c95/scikit_learn-1.8.0-cp312-cp312-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b2/02/cf107b01494c19dc100f1d0b7ac3cc08666e96ba2d64db7626066cee895e/scipy-1.17.1-cp312-cp312-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/05/30/affbabf3c27fb501ec7b5808230c619d4d1a4525c07301074eb4bda92fa9/statsmodels-0.14.6-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.12.13-h0159041_0_cpython.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ef/86/612d45473d0865d41934b0580fa05e6aa48167b502d0136e8bd9dd5aa581/arch-8.0.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/ed/13bd4418627013bec4ed6e54283b1959cf6db888048c7cf4b4c3b5b36002/cffi-2.0.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/70/53/e44a4c07e8904500aec95865dc3f6464dc3586a039ef0df606eb3ac38e35/charset_normalizer-3.4.5-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/19/e8/6026ed58a64563186a9ee3f29f41261fd1828f527dd93d33b60feca63352/contourpy-1.3.3-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/77/4e/c0a25a425fcf5557d9abd18419c95b63922e897bc86c1f327f155ef234a9/coverage-7.13.4-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a1/39/2bef246368bd42f9bd7cba99844542b74b84dacbdbea0833e610f384fee8/debugpy-1.8.20-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/06/cc96468781a4dc8ae2f14f16f32b32f69bde18cb9384aad27ccc7adf76f7/fonttools-4.62.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/03/c1/0976b235cf29ead553e22f2fb6385a8252b533715e00d0ae52ed7b900582/h5py-3.16.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ad/cf/0348374369ca588f8fe9c338fae49fa4e16eeb10ffb3d012f23a54578a9e/kiwisolver-1.5.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f7/d7/0cdfb6c3e30893463fb3d1e52bc5f5f99684a03c29a0b6b605cfae879cd5/lxml-6.0.2-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/aa/5b/bec5aa9bbbb2c946ca2733ef9c4ca91c91b6a24580193e891b5f7dbe8e1e/markupsafe-3.0.3-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/30/4e/c10f171b6e2f44d9e3a2b96efa38b1677439d79c99357600a62cc1e9594e/matplotlib-3.10.8-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/67/ffe750b5452eb66de788c34e7d21ec6d886abb4d7c43ad1dc88ceb3d998f/numexpr-2.14.1-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d7/7c/f5ee1bf6ed888494978046a809df2882aad35d414b622893322df7286879/numpy-2.4.3-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/75/08/67cc404b3a966b6df27b38370ddd96b3b023030b572283d035181854aac5/pandas-3.0.1-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3d/17/688626d192d7261bbbf98846fc98995726bddc2c945344b65bec3a29d731/pillow-12.1.1-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7c/d4/aeb5e1784d2c5bff6e189138a9ca91a090117459cea0c30378e1f2db3d54/pywinpty-3.0.3-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/86/bf/899e81e4cce32febab4fb42bb97dcdf66bc135272882d1987881a4b519e9/pyyaml-6.0.3-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fc/7f/a21b20d577e4100c6a41795842028235998a643b1ad406a6d4163ea8f53e/pyzmq-27.1.0-cp312-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/3b/f786af9957306fdc38a74cef405b7b93180f481fb48453a114bb6465744a/rpds_py-0.30.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/9f/c4/0ab22726a04ede56f689476b760f98f8f46607caecff993017ac1b64aa5d/scikit_learn-1.8.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a2/84/dc08d77fbf3d87d3ee27f6a0c6dcce1de5829a64f2eae85a0ecc1f0daa73/scipy-1.17.1-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/15/3daba2df40be8b8a9a027d7f54c8dedf24f0d81b96e54b52293f5f7e3418/statsmodels-0.14.6-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ + dev-py313: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.12-hc97d973_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/40/7b7ac152c35c32da2a00ba3523ea84c358478b12ee7b3b2b6892e5b9d81b/arch-8.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e4/dc/b2442d10020c2f52617828862d8b6ee337859cd8f3a1f13d607dddda9cf7/coverage-7.13.4-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2b/0a/7b98e1e119878a27ba8618ca1e18b14f992ff1eda40f47bccccf4de44121/kiwisolver-1.5.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d0/34/9e591954939276bb679b73773836c6684c22e56d05980e31d52a9a8deb18/lxml-6.0.2-cp313-cp313-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a9/21/9b05698b46f218fc0e118e1f8168395c65c8a2c750ae2bab54fc4bd4e0e8/markupsafe-3.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/75/97/a471f1c3eb1fd6f6c24a31a5858f443891d5127e63a7788678d14e249aea/matplotlib-3.10.8-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fc/f9/c9457652dfe28e2eb898372da2fe786c6db81af9540c0f853ee04a0699cc/numexpr-2.14.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f2/85/ab6d04733a7d6ff32bfc8382bf1b07078228f5d6ebec5266b91bfc5c4ff7/pandas-3.0.1-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/24/538bff45bde96535d7d998c6fed1a751c75ac7c53c37c90dc2601b243893/pillow-12.1.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f8/9b/c108cdb55560eaf253f0cbdb61b29971e9fb34d9c3499b0e96e4e60ed8a5/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/de/f7192e12b21b9e9a68a6d0f249b4af3fdcdff8418be0767a627564afa1f1/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/38/cf/06896db3f71c75902a8e9943b444a56e727418f6b4b4a90c98c934f51ed4/scikit_learn-1.8.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/5f/f17563f28ff03c7b6799c50d01d5d856a1d55f2676f537ca8d28c7f627cd/scipy-1.17.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/b9/fd41f1f6af13a1a1212a06bb377b17762feaa6d656947bf666f76300fc05/statsmodels-0.14.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libmpdec-4.0.0-hf3981d6_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.13.12-h894a449_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/51/78f84f9e486e173356931b2bfaf0c2a6d6923f1e8975045e3416ac388215/arch-8.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/db/23/aad45061a31677d68e47499197a131eea55da4875d16c1f42021ab963503/coverage-7.13.4-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ce/48/adbb40df306f587054a348831220812b9b1d787aff714cfbc8556e38fccd/kiwisolver-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5d/f4/2a94a3d3dfd6c6b433501b8d470a1960a20ecce93245cf2db1706adf6c19/lxml-6.0.2-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/38/2f/907b9c7bbba283e68f20259574b13d005c121a0fa4c175f9bed27c4597ff/markupsafe-3.0.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/3d/b9/15fd5541ef4f5b9a17eefd379356cf12175fe577424e7b1d80676516031a/matplotlib-3.10.8-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/73/b4/9f6d637fd79df42be1be29ee7ba1f050fab63b7182cb922a0e08adc12320/numexpr-2.14.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0b/48/aad6ec4f8d007534c091e9a7172b3ec1b1ee6d99a9cbb936b5eab6c6cf58/pandas-3.0.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/14/a1/16c4b823838ba4c9c52c0e6bbda903a3fe5a1bdbf1b8eb4fff7156f3e318/pillow-12.1.1-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ed/dc/d61221eb88ff410de3c49143407f6f3147acf2538c86f2ab7ce65ae7d5f9/rpds_py-0.30.0-cp313-cp313-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/aa/e22e0768512ce9255eba34775be2e85c2048da73da1193e841707f8f039c/scikit_learn-1.8.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/76/27/07ee1b57b65e92645f219b37148a7e7928b82e2b5dbeccecb4dff7c64f0b/scipy-1.17.1-cp313-cp313-macosx_10_14_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/59/a5aad5b0cc266f5be013db8cde563ac5d2a025e7efc0c328d83b50c72992/statsmodels-0.14.6-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libmpdec-4.0.0-h84a0fba_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.13.12-h20e6be0_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b8/73910773efffc2d35d2739be1bdc70dfcc58a83cff35c4d62e14acceca2b/arch-8.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/a5/70/9b8b67a0945f3dfec1fd896c5cefb7c19d5a3a6d74630b99a895170999ae/coverage-7.13.4-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/3a/d0a972b34e1c63e2409413104216cd1caa02c5a37cb668d1687d466c1c45/kiwisolver-1.5.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/fd/4e8f0540608977aea078bf6d79f128e0e2c2bba8af1acf775c30baa70460/lxml-6.0.2-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/9c/d9/5f7756922cdd676869eca1c4e3c0cd0df60ed30199ffd775e319089cb3ed/markupsafe-3.0.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/8d/a0/2ba3473c1b66b9c74dc7107c67e9008cb1782edbe896d4c899d39ae9cf78/matplotlib-3.10.8-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/35/ae/d58558d8043de0c49f385ea2fa789e3cfe4d436c96be80200c5292f45f15/numexpr-2.14.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a8/14/5990826f779f79148ae9d3a2c39593dc04d61d5d90541e71b5749f35af95/pandas-3.0.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bb/ad/ad9dc98ff24f485008aa5cdedaf1a219876f6f6c42a4626c08bc4e80b120/pillow-12.1.1-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/32/55fb50ae104061dbc564ef15cc43c013dc4a9f4527a1f4d99baddf56fe5f/rpds_py-0.30.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/58/37/31b83b2594105f61a381fc74ca19e8780ee923be2d496fcd8d2e1147bd99/scikit_learn-1.8.0-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ec/ae/db19f8ab842e9b724bf5dbb7db29302a91f1e55bc4d04b1025d6d605a2c5/scipy-1.17.1-cp313-cp313-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/53/dd/d8cfa7922fc6dc3c56fa6c59b348ea7de829a94cd73208c6f8202dd33f17/statsmodels-0.14.6-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.13.12-h09917c8_100_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/e7/2d15374129c03b6f97321f837190cb19863204dbcff289e23cc37f035c96/arch-8.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e2/0c/dbfafbe90a185943dcfbc766fe0e1909f658811492d79b741523a414a6cc/coverage-7.13.4-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/f7/a0b368ce54ffff9e9028c098bd2d28cfc5b54f9f6c186929083d4c60ba58/debugpy-1.8.20-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/be/8a/be60e3bbcf513cc5a50f4a3e88e1dcecebb79c1ad607a7222877becaa101/kiwisolver-1.5.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/0a/4643ccc6bb8b143e9f9640aa54e38255f9d3b45feb2cbe7ae2ca47e8782e/lxml-6.0.2-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/05/73/c4abe620b841b6b791f2edc248f556900667a5a1cf023a6646967ae98335/markupsafe-3.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/64/40/37612487cc8a437d4dd261b32ca21fe2d79510fe74af74e1f42becb1bdb8/matplotlib-3.10.8-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cc/23/9281bceaeb282cead95f0aa5f7f222ffc895670ea689cc1398355f6e3001/numexpr-2.14.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d6/7d/216a1588b65a7aa5f4535570418a599d943c85afb1d95b0876fc00aa1468/pandas-3.0.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/eb/b0834ad8b583d7d9d42b80becff092082a1c3c156bb582590fcc973f1c7c/pillow-12.1.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/cb/58d6ed3fd429c96a90ef01ac9a617af10a6d41469219c25e7dc162abbb71/pywinpty-3.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fc/7f/a21b20d577e4100c6a41795842028235998a643b1ad406a6d4163ea8f53e/pyzmq-27.1.0-cp312-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f2/e1/485132437d20aa4d3e1d8b3fb5a5e65aa8139f1e097080c2a8443201742c/rpds_py-0.30.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/f9/9b7563caf3ec8873e17a31401858efab6b39a882daf6c1bfa88879c0aa11/scikit_learn-1.8.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/35/e5/d6d0e51fc888f692a35134336866341c08655d92614f492c6860dc45bb2c/scipy-1.17.1-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/98/08/b79f0c614f38e566eebbdcff90c0bcacf3c6ba7a5bbb12183c09c29ca400/statsmodels-0.14.6-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ + dev-py314: + channels: + - url: https://conda.anaconda.org/conda-forge/ + indexes: + - https://pypi.org/simple + options: + pypi-prerelease-mode: if-necessary-or-explicit + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.3-h32b2ec7_101_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/22/11/8a3b956a532b26fe4f325d9829b09eba725eb25a3e89d568673e2015beca/arch-8.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/47/d9/d83e293854571c877a92da46fdec39158f8d7e68da75bf73581225d28e90/cffi-2.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/38/9c/71336bff6934418dc8d1e8a1644176ac9088068bc571da612767619c97b3/charset_normalizer-3.4.5-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/5f/9ff93450ba96b09c7c2b3f81c94de31c89f92292f1380261bd7195bea4ea/contourpy-1.3.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/06/90/2cdab0974b9b5bbc1623f7876b73603aecac11b8d95b85b5b86b32de5eab/coverage-7.13.4-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/86/c8/c6669e42d2f4efd60d38a3252cebbb28851f968890efb2b9b15f9d1092b0/fonttools-4.62.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/16/d905e7f53e661ce2c24686c38048d8e2b750ffc4350009d41c4e6c6c9826/h5py-3.16.0-cp314-cp314-manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/f9/b06c934a6aa8bc91f566bd2a214fd04c30506c2d9e2b6b171953216a65b6/kiwisolver-1.5.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/29/9c/47293c58cc91769130fbf85531280e8cc7868f7fbb6d92f4670071b9cb3e/lxml-6.0.2-cp314-cp314-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/41/3c/a36c2450754618e62008bf7435ccb0f88053e07592e6028a34776213d877/markupsafe-3.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f5/26/4221a741eb97967bc1fd5e4c52b9aa5a91b2f4ec05b59f6def4d820f9df9/matplotlib-3.10.8-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/88/e1/3db65117f02cdefb0e5e4c440daf1c30beb45051b7f47aded25b7f4f2f34/numexpr-2.14.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a9/7e/4f120ecc54ba26ddf3dc348eeb9eb063f421de65c05fc961941798feea18/numpy-2.4.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/55/77/6ea82043db22cb0f2bbfe7198da3544000ddaadb12d26be36e19b03a2dc5/pandas-3.0.1-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/ee/c85a38a9ab92037a75615aba572c85ea51e605265036e00c5b67dfafbfe2/pillow-12.1.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/88/f9/16491d7ed2a919954993e48aa941b200f38040928474c9e85ea9e64222c3/pyyaml-6.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/f8/9b/c108cdb55560eaf253f0cbdb61b29971e9fb34d9c3499b0e96e4e60ed8a5/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ce/81/9a91c0111ce1758c92516a3e44776920b579d9a7c09b2b06b642d4de3f0f/rpds_py-0.30.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b8/cb/861b41341d6f1245e6ca80b1c1a8c4dfce43255b03df034429089ca2a2c5/scikit_learn-1.8.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/0b/2e/7eea398450457ecb54e18e9d10110993fa65561c4f3add5e8eccd2b9cd41/scipy-1.17.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/0e/2408735aca9e764643196212f9069912100151414dd617d39ffc72d77eee/statsmodels-0.14.6-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + - pypi: ./ + osx-64: + - conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libmpdec-4.0.0-hf3981d6_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.14.3-h4f44bb5_101_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-64/zstd-1.5.7-h3eecb57_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/96/37/8d9ec002ec3e750f3ea2af42b67a1e3cf3a82523b556fd8d10d1f34a085a/arch-8.0.0-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/c4/3ce07396253a83250ee98564f8d7e9789fab8e58858f35d07a9a2c78de9f/cffi-2.0.0-cp314-cp314-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/43/be/0f0fd9bb4a7fa4fb5067fb7d9ac693d4e928d306f80a0d02bde43a7c4aee/charset_normalizer-3.4.5-cp314-cp314-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/72/8b/4546f3ab60f78c514ffb7d01a0bd743f90de36f0019d1be84d0a708a580a/contourpy-1.3.3-cp314-cp314-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/92/11/a9cf762bb83386467737d32187756a42094927150c3e107df4cb078e8590/coverage-7.13.4-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c6/57/6b08756fe4455336b1fe160ab3c11fccc90768ccb6ee03fb0b45851aace4/fonttools-4.62.0-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/48/3c/7fcd9b4c9eed82e91fb15568992561019ae7a829d1f696b2c844355d95dd/h5py-3.16.0-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/a7/78da680eadd06ff35edef6ef68a1ad273bad3e2a0936c9a885103230aece/kiwisolver-1.5.0-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c8/e8/c128e37589463668794d503afaeb003987373c5f94d667124ffd8078bbd9/lxml-6.0.2-cp314-cp314-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/33/8a/8e42d4838cd89b7dde187011e97fe6c3af66d8c044997d2183fbd6d31352/markupsafe-3.0.3-cp314-cp314-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/3c/43/9c0ff7a2f11615e516c3b058e1e6e8f9614ddeca53faca06da267c48345d/matplotlib-3.10.8-cp314-cp314-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ac/36/9db78dfbfdfa1f8bf0872993f1a334cdd8fca5a5b6567e47dcb128bcb7c2/numexpr-2.14.1-cp314-cp314-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/70/ae/3936f79adebf8caf81bd7a599b90a561334a658be4dcc7b6329ebf4ee8de/numpy-2.4.3-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bb/8b/4bb774a998b97e6c2fd62a9e6cfdaae133b636fd1c468f92afb4ae9a447a/pandas-3.0.1-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/04/dc5c3f297510ba9a6837cbb318b87dd2b8f73eb41a43cc63767f65cb599c/pillow-12.1.1-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/8c/f4bd7f6465179953d3ac9bc44ac1a8a3e6122cf8ada906b4f96c60172d43/pyyaml-6.0.3-cp314-cp314-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/86/81/dad16382ebbd3d0e0328776d8fd7ca94220e4fa0798d1dc5e7da48cb3201/rpds_py-0.30.0-cp314-cp314-macosx_10_12_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/24/05/1af2c186174cc92dcab2233f327336058c077d38f6fe2aceb08e6ab4d509/scikit_learn-1.8.0-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cf/83/333afb452af6f0fd70414dc04f898647ee1423979ce02efa75c3b0f2c28e/scipy-1.17.1-cp314-cp314-macosx_10_14_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/de/09540e870318e0c7b58316561d417be45eff731263b4234fdd2eee3511a8/statsmodels-0.14.6-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + - pypi: ./ + osx-arm64: + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libmpdec-4.0.0-h84a0fba_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.14.3-h4c637c5_101_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.7-hbf9d68e_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/70/c8/533ad2ef4277d2f6c95e8038088de2d80c6a41137c7d23e00b08425e2c39/arch-8.0.0-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/dd/27e9fa567a23931c838c6b02d0764611c62290062a6d4e8ff7863daf9730/cffi-2.0.0-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/43/be/0f0fd9bb4a7fa4fb5067fb7d9ac693d4e928d306f80a0d02bde43a7c4aee/charset_normalizer-3.4.5-cp314-cp314-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fd/e1/3542a9cb596cadd76fcef413f19c79216e002623158befe6daa03dbfa88c/contourpy-1.3.3-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/d3/28/56e6d892b7b052236d67c95f1936b6a7cf7c3e2634bf27610b8cbd7f9c60/coverage-7.13.4-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/64/61f69298aa6e7c363dcf00dd6371a654676900abe27d1effd1a74b43e5d0/fonttools-4.62.0-cp314-cp314-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/b7/9366ed44ced9b7ef357ab48c94205280276db9d7f064aa3012a97227e966/h5py-3.16.0-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/49/b2/97980f3ad4fae37dd7fe31626e2bf75fbf8bdf5d303950ec1fab39a12da8/kiwisolver-1.5.0-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/03/15/d4a377b385ab693ce97b472fe0c77c2b16ec79590e688b3ccc71fba19884/lxml-6.0.2-cp314-cp314-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/b5/64/7660f8a4a8e53c924d0fa05dc3a55c9cee10bbd82b11c5afb27d44b096ce/markupsafe-3.0.3-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/6f/ca/e8ae28649fcdf039fda5ef554b40a95f50592a3c47e6f7270c9561c12b07/matplotlib-3.10.8-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/c1/a5c78ae637402c5550e2e0ba175275d2515d432ec28af0cdc23c9b476e65/numexpr-2.14.1-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/9b/62/760f2b55866b496bb1fa7da2a6db076bef908110e568b02fcfc1422e2a3a/numpy-2.4.3-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/72/3a/5b39b51c64159f470f1ca3b1c2a87da290657ca022f7cd11442606f607d1/pandas-3.0.1-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/05/30/5db1236b0d6313f03ebf97f5e17cda9ca060f524b2fcc875149a8360b21c/pillow-12.1.1-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bd/9c/4d95bb87eb2063d20db7b60faa3840c1b18025517ae857371c4dd55a6b3a/pyyaml-6.0.3-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2b/60/19f7884db5d5603edf3c6bce35408f45ad3e97e10007df0e17dd57af18f8/rpds_py-0.30.0-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/a8/25/01c0af38fe969473fb292bba9dc2b8f9b451f3112ff242c647fee3d0dfe7/scikit_learn-1.8.0-cp314-cp314-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/ed/a6/d05a85fd51daeb2e4ea71d102f15b34fedca8e931af02594193ae4fd25f7/scipy-1.17.1-cp314-cp314-macosx_12_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/f0/63c1bfda75dc53cee858006e1f46bd6d6f883853bea1b97949d0087766ca/statsmodels-0.14.6-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + - pypi: ./ + win-64: + - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.3-h4b44e0e_101_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda + - pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0a/d1/14d3dab7283ea68a4e2d17be62d854af6df7e3d6f1b998a87d5be3ed8aed/arch-8.0.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/bb/92/882c2d30831744296ce713f0feb4c1cd30f346ef747b530b5318715cc367/cffi-2.0.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/40/65/e7c6c77d7aaa4c0d7974f2e403e17f0ed2cb0fc135f77d686b916bf1eead/charset_normalizer-3.4.5-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7d/c2/57f54b03d0f22d4044b8afb9ca0e184f8b1afd57b4f735c2fa70883dc601/contourpy-1.3.3-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a7/4d/1f8e723f6829977410efeb88f73673d794075091c8c7c18848d273dc9d73/coverage-7.13.4-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/d9/1f07395b54413432624d61524dfd98c1a7c7827d2abfdb8829ac92638205/debugpy-1.8.20-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2e/9f/91081ffe5881253177c175749cce5841f5ec6e931f5d52f4a817207b7429/fonttools-4.62.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3e/14/615a450205e1b56d16c6783f5ccd116cde05550faad70ae077c955654a75/h5py-3.16.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a3/36/4e551e8aa55c9188bca9abb5096805edbf7431072b76e2298e34fd3a3008/kiwisolver-1.5.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e3/e0/c96cf13eccd20c9421ba910304dae0f619724dcf1702864fd59dd386404d/lxml-6.0.2-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/28/52/182836104b33b444e400b14f797212f720cbc9ed6ba34c800639d154e821/markupsafe-3.0.3-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/93/a5/de89ac80f10b8dc615807ee1133cd99ac74082581196d4d9590bea10690d/matplotlib-3.10.8-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/4f/3e/d83e9401a1c3449a124f7d4b3fb44084798e0d30f7c11e60712d9b94cf11/numexpr-2.14.1-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/48/39/c56ef87af669364356bb011922ef0734fc49dad51964568634c72a009488/numpy-2.4.3-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/09/f8/8ce132104074f977f907442790eaae24e27bce3b3b454e82faa3237ff098/pandas-3.0.1-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/40/72/4c245f7d1044b67affc7f134a09ea619d4895333d35322b775b928180044/pillow-12.1.1-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/28/88/2ff917caff61e55f38bcdb27de06ee30597881b2cae44fbba7627be015c4/pywinpty-3.0.3-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/23/20/bb6982b26a40bb43951265ba29d4c246ef0ff59c9fdcdf0ed04e0687de4d/pyyaml-6.0.3-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/fc/7f/a21b20d577e4100c6a41795842028235998a643b1ad406a6d4163ea8f53e/pyzmq-27.1.0-cp312-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3e/d2/1aaac33287e8cfb07aab2e6b8ac1deca62f6f65411344f1433c55e6f3eb8/rpds_py-0.30.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/76/18/a8def8f91b18cd1ba6e05dbe02540168cb24d47e8dcf69e8d00b7da42a08/scikit_learn-1.8.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/4b/39/f0e8ea762a764a9dc52aa7dabcfad51a354819de1f0d4652b6a1122424d6/scipy-1.17.1-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/26/33/f1652d0c59fa51de18492ee2345b65372550501ad061daa38f950be390b6/statsmodels-0.14.6-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + - pypi: ./ +packages: +- conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda + build_number: 20 + sha256: 1dd3fffd892081df9726d7eb7e0dea6198962ba775bd88842135a4ddb4deb3c9 + md5: a9f577daf3de00bca7c3c76c0ecbd1de + depends: + - __glibc >=2.17,<3.0.a0 + - libgomp >=7.5.0 + constrains: + - openmp_impl <0.0a0 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 28948 + timestamp: 1770939786096 +- pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + name: anyio + version: 4.12.1 + sha256: d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c + requires_dist: + - exceptiongroup>=1.0.2 ; python_full_version < '3.11' + - idna>=2.8 + - typing-extensions>=4.5 ; python_full_version < '3.13' + - trio>=0.32.0 ; python_full_version >= '3.10' and extra == 'trio' + - trio>=0.31.0 ; python_full_version < '3.10' and extra == 'trio' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + name: appnope + version: 0.1.4 + sha256: 502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/2f/84/12132d3ee536b3147fd8c81cefbe6a2ced0105f6a0c9b8894a0bf3b6d839/arch-5.6.0-cp310-cp310-win_amd64.whl + name: arch + version: 5.6.0 + sha256: 7b1f78ad63b288014c3d453b29c9a1886e10a27eb53c5e58d55d8dd49b1a3d9a + requires_dist: + - numpy>=1.17 + - scipy>=1.3 + - pandas>=1.0 + - statsmodels>=0.11 + - property-cached>=1.6.4 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/77/45/b0e6e239d06b96dd2a2782610286449c58849ac0017361fe3a49a213314e/arch-5.6.0-cp310-cp310-macosx_10_9_x86_64.whl + name: arch + version: 5.6.0 + sha256: 478d049fb18e022670952792ebaa6b66acff77580c0f691497b706ce9192e941 + requires_dist: + - numpy>=1.17 + - scipy>=1.3 + - pandas>=1.0 + - statsmodels>=0.11 + - property-cached>=1.6.4 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/83/fa/4165805349e21ef83f42e29305a1c724ef68855ebbc5c11c115bec0ac510/arch-5.6.0-cp310-cp310-macosx_11_0_arm64.whl + name: arch + version: 5.6.0 + sha256: f0da8a70e56759b469eeef52153e0a6eaf2e384c4f48427189433ea12fc8886a + requires_dist: + - numpy>=1.17 + - scipy>=1.3 + - pandas>=1.0 + - statsmodels>=0.11 + - property-cached>=1.6.4 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/8c/b2/a4a3149e1dff8723f38a5698b03e606aebb53940765abed1deaf3da6ee8e/arch-5.6.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: arch + version: 5.6.0 + sha256: 3c838e92dd60367c0e5063bc98521aa341d20d97af7adf911526d1c819eef7ee + requires_dist: + - numpy>=1.17 + - scipy>=1.3 + - pandas>=1.0 + - statsmodels>=0.11 + - property-cached>=1.6.4 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/0a/d1/14d3dab7283ea68a4e2d17be62d854af6df7e3d6f1b998a87d5be3ed8aed/arch-8.0.0-cp314-cp314-win_amd64.whl + name: arch + version: 8.0.0 + sha256: 4849380bb831a1dc09891cd424f6623f163bde2403c66e376f9d0b5f8c1791c5 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/0f/f7/addc52355dd804416b086cb85287161bb8ee0e53eb9f527f45af93dff76c/arch-8.0.0-cp310-cp310-macosx_10_9_x86_64.whl + name: arch + version: 8.0.0 + sha256: fb60acaa9caa1353b75f19db910ac88e4238f4ca40282418e728174b1d3fe297 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/22/11/8a3b956a532b26fe4f325d9829b09eba725eb25a3e89d568673e2015beca/arch-8.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: arch + version: 8.0.0 + sha256: 563bea8e594f712a38ec2186f6dcd0d55a73f1c203bd228958cad495d9d471f1 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/2e/41/d6aa187e4f6d1567b51ac8a1d12ec1a78a55310fad2a7f2300a251cfbb89/arch-8.0.0-cp310-cp310-win_amd64.whl + name: arch + version: 8.0.0 + sha256: b56c3994069532c6621d211a333c62ae6b3cfeb3eef8089806bd4698062137ca + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/34/a4/30ed8bac322681cf1ec86e644f6f531aeca6b1d20a26e029df537042988f/arch-8.0.0-cp310-cp310-macosx_11_0_arm64.whl + name: arch + version: 8.0.0 + sha256: 51641954adb35f969b5c3333f6527fb090720fc0c973b6d2c4d927c8cc5dfe58 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/44/b5/8f04a871c2e0f94430c15d313f88fe7808d80c4752b0ebdeadfec21dec8e/arch-8.0.0-cp311-cp311-macosx_10_9_x86_64.whl + name: arch + version: 8.0.0 + sha256: 94262bef94dda3f72182a8dfc21cab1a8a79750cf168f3cf2aec02d7217bee55 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/44/c5/0e9a7a85eb0135d8d551660bb930561a49a506fe9d086cdefb530589f654/arch-8.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: arch + version: 8.0.0 + sha256: ec799301d904318d067d8d919069efc2825e8cea1654b1ffe623ea8c591fff5e + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/70/c8/533ad2ef4277d2f6c95e8038088de2d80c6a41137c7d23e00b08425e2c39/arch-8.0.0-cp314-cp314-macosx_11_0_arm64.whl + name: arch + version: 8.0.0 + sha256: a5a2ee20c5a0d88eda12894d8fbb8320b7bfe3436c2e40fa16da918db54eb5b4 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/84/6e/b4379d1dee984f4a51afad9bfb49a3079ae196faf0bb834b7b5ad8e5ec6a/arch-8.0.0-cp312-cp312-macosx_10_13_x86_64.whl + name: arch + version: 8.0.0 + sha256: 268dfe386f8c64a1973374bc0425bdf0c7c2250c2bfd7238d98bae701827ec2b + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/8d/54/ab79d924327497fddb462ce51216d193e374ad2295b1003542802ed9a021/arch-8.0.0-cp312-cp312-macosx_11_0_arm64.whl + name: arch + version: 8.0.0 + sha256: 1f4341b22279d82d0300ebd54d1d5f80324f31fc017c8138f47e810bdb81d753 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/96/37/8d9ec002ec3e750f3ea2af42b67a1e3cf3a82523b556fd8d10d1f34a085a/arch-8.0.0-cp314-cp314-macosx_10_15_x86_64.whl + name: arch + version: 8.0.0 + sha256: 8015f7bdcc14800dc2dc2acb01dffebddebf587df4aa27f62671e809ccfdefb1 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a4/d3/da7d55f51bb31a10d1b4a01a22ec0180265a5afeed0d99bd4d0c7b3a61e1/arch-8.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: arch + version: 8.0.0 + sha256: 13cbf04d45ecbee7578704a232f897cd02794d845f877158fb2838e6fb637887 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/b5/42/7f1b880857839ea0841304586715c7d2a477552d04bcde32d1d55d8ccaa0/arch-8.0.0-cp311-cp311-macosx_11_0_arm64.whl + name: arch + version: 8.0.0 + sha256: 1d9cb343f15e71e9cee2415bffa1e3458aeb674a538118de71f1124b6c5b755a + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/bc/00/7cc035e2a08b9186cfbd0b5d3dd3967481f64722c3af69416edc8a182fd7/arch-8.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: arch + version: 8.0.0 + sha256: 975ec3bdf7926335742ac362251fafe32b448b8f194dead062f22a00beef772d + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/cb/b8/73910773efffc2d35d2739be1bdc70dfcc58a83cff35c4d62e14acceca2b/arch-8.0.0-cp313-cp313-macosx_11_0_arm64.whl + name: arch + version: 8.0.0 + sha256: 6b75bc7f4af4da5aca6cbcc52284564fcce8c974cf7d89d8b9777d8c16a228b0 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d2/4b/abfe066b00a5f1f0ab80dc5b7424f9fc1008116546fefcc1d17def0be9b6/arch-8.0.0-cp311-cp311-win_amd64.whl + name: arch + version: 8.0.0 + sha256: 2aa5e631f91283733592b44e0c0640da5f690f5895738ad0d26a007325e3d0fc + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d6/40/7b7ac152c35c32da2a00ba3523ea84c358478b12ee7b3b2b6892e5b9d81b/arch-8.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: arch + version: 8.0.0 + sha256: 8c1f1d8abefab2f69f7fdbef08cc18c8377667d3b8d197a1f301d97f0e686cd2 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d6/51/78f84f9e486e173356931b2bfaf0c2a6d6923f1e8975045e3416ac388215/arch-8.0.0-cp313-cp313-macosx_10_13_x86_64.whl + name: arch + version: 8.0.0 + sha256: 4320a9b3707e819a97f0b0a10847e529e2f765158c617a455987a34305018617 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ef/86/612d45473d0865d41934b0580fa05e6aa48167b502d0136e8bd9dd5aa581/arch-8.0.0-cp312-cp312-win_amd64.whl + name: arch + version: 8.0.0 + sha256: 8b13d261e0a681b3a8a2f9c588ab37a35500bca9f3bbcc6ca1ce2d999322651d + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f1/e7/2d15374129c03b6f97321f837190cb19863204dbcff289e23cc37f035c96/arch-8.0.0-cp313-cp313-win_amd64.whl + name: arch + version: 8.0.0 + sha256: bd73bd2d811bcf0551443b6e0a10bc25af002e9eb146aff164897c70aac35e85 + requires_dist: + - numpy>=1.22.3,<3 + - pandas>=1.4.0 + - scipy>=1.8 + - statsmodels>=0.13.0 + - packaging + - pytest>=8.4.1,<9 ; extra == 'test' + - pytest-randomly ; extra == 'test' + - pytest-xdist ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage[toml] ; extra == 'test' + - meson ; extra == 'test' + - ninja ; extra == 'test' + - setuptools>=61 ; extra == 'doc' + - wheel ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'doc' + - cython>=3.0.13,<4 ; extra == 'doc' + - numpy>=2.3.4 ; extra == 'doc' + - scipy>=1.16.0 ; extra == 'doc' + - ipython>=8.0.1 ; extra == 'doc' + - matplotlib>=3.10 ; extra == 'doc' + - patsy>=0.5.3 ; extra == 'doc' + - statsmodels>=0.13.5 ; extra == 'doc' + - jinja2 ; extra == 'doc' + - sphinx>=7 ; extra == 'doc' + - seaborn ; extra == 'doc' + - numpydoc>=1.0.0 ; extra == 'doc' + - nbsphinx ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - jupyter ; extra == 'doc' + - notebook ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - fonttools>=4.43.0 ; extra == 'doc' + - jupyterlab>=4.4.8 ; extra == 'doc' + - ipython>=7 ; extra == 'doc' + - sphinx-immaterial ; extra == 'doc' + - nbconvert ; extra == 'doc' + - pickleshare ; extra == 'doc' + - pandas~=2.3.3 ; extra == 'doc' + - setuptools-scm[toml]>=9.2.0,<10 ; extra == 'dev' + - packaging ; extra == 'dev' + - cython>=3.0.10 ; extra == 'dev' + - numba>=0.55 ; extra == 'dev' + - matplotlib>=3 ; extra == 'dev' + - seaborn ; extra == 'dev' + - pytest>=8.4.1,<9 ; extra == 'dev' + - pytest-randomly ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - black[jupyter]~=25.9.0 ; extra == 'dev' + - isort~=6.0 ; extra == 'dev' + - colorama ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - mypy>=1.3 ; extra == 'dev' + - ruff>=0.8.6 ; extra == 'dev' + - pyupgrade>=3.4.0 ; extra == 'dev' + - jupyterlab-code-formatter ; extra == 'dev' + - jupyterlab>=4.4.8 ; extra == 'dev' + - zipp>=3.19.1 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl + name: argon2-cffi + version: 25.1.0 + sha256: fdc8b074db390fccb6eb4a3604ae7231f219aa669a2652e0f20e16ba513d5741 + requires_dist: + - argon2-cffi-bindings + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: argon2-cffi-bindings + version: 25.1.0 + sha256: d3e924cfc503018a714f94a49a149fdc0b644eaead5d1f089330399134fa028a + requires_dist: + - cffi>=1.0.1 ; python_full_version < '3.14' + - cffi>=2.0.0b1 ; python_full_version >= '3.14' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl + name: argon2-cffi-bindings + version: 25.1.0 + sha256: 2630b6240b495dfab90aebe159ff784d08ea999aa4b0d17efa734055a07d2f44 + requires_dist: + - cffi>=1.0.1 ; python_full_version < '3.14' + - cffi>=2.0.0b1 ; python_full_version >= '3.14' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl + name: argon2-cffi-bindings + version: 25.1.0 + sha256: 7aef0c91e2c0fbca6fc68e7555aa60ef7008a739cbe045541e438373bc54d2b0 + requires_dist: + - cffi>=1.0.1 ; python_full_version < '3.14' + - cffi>=2.0.0b1 ; python_full_version >= '3.14' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl + name: argon2-cffi-bindings + version: 25.1.0 + sha256: a98cd7d17e9f7ce244c0803cad3c23a7d379c301ba618a5fa76a67d116618b98 + requires_dist: + - cffi>=1.0.1 ; python_full_version < '3.14' + - cffi>=2.0.0b1 ; python_full_version >= '3.14' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl + name: arrow + version: 1.4.0 + sha256: 749f0769958ebdc79c173ff0b0670d59051a535fa26e8eba02953dc19eb43205 + requires_dist: + - python-dateutil>=2.7.0 + - backports-zoneinfo==0.2.1 ; python_full_version < '3.9' + - tzdata ; python_full_version >= '3.9' + - doc8 ; extra == 'doc' + - sphinx>=7.0.0 ; extra == 'doc' + - sphinx-autobuild ; extra == 'doc' + - sphinx-autodoc-typehints ; extra == 'doc' + - sphinx-rtd-theme>=1.3.0 ; extra == 'doc' + - dateparser==1.* ; extra == 'test' + - pre-commit ; extra == 'test' + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-mock ; extra == 'test' + - pytz==2025.2 ; extra == 'test' + - simplejson==3.* ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl + name: asttokens + version: 3.0.1 + sha256: 15a3ebc0f43c2d0a50eeafea25e19046c68398e487b9f1f5b517f7c0f40f976a + requires_dist: + - astroid>=2,<5 ; extra == 'astroid' + - astroid>=2,<5 ; extra == 'test' + - pytest<9.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-xdist ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl + name: async-lru + version: 2.2.0 + sha256: e2c1cf731eba202b59c5feedaef14ffd9d02ad0037fcda64938699f2c380eafe + requires_dist: + - typing-extensions>=4.0.0 ; python_full_version < '3.11' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + name: attrs + version: 25.4.0 + sha256: adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + name: babel + version: 2.18.0 + sha256: e2b422b277c2b9a9630c1d7903c2a00d0830c409c59ac8cae9081c92f1aeba35 + requires_dist: + - pytz>=2015.7 ; python_full_version < '3.9' + - tzdata ; sys_platform == 'win32' and extra == 'dev' + - backports-zoneinfo ; python_full_version < '3.9' and extra == 'dev' + - freezegun~=1.0 ; extra == 'dev' + - jinja2>=3.0 ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - pytest>=6.0 ; extra == 'dev' + - pytz ; extra == 'dev' + - setuptools ; extra == 'dev' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl + name: beautifulsoup4 + version: 4.14.3 + sha256: 0918bfe44902e6ad8d57732ba310582e98da931428d231a5ecb9e7c703a735bb + requires_dist: + - soupsieve>=1.6.1 + - typing-extensions>=4.0.0 + - cchardet ; extra == 'cchardet' + - chardet ; extra == 'chardet' + - charset-normalizer ; extra == 'charset-normalizer' + - html5lib ; extra == 'html5lib' + - lxml ; extra == 'lxml' + requires_python: '>=3.7.0' +- pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl + name: bleach + version: 6.3.0 + sha256: fe10ec77c93ddf3d13a73b035abaac7a9f5e436513864ccdad516693213c65d6 + requires_dist: + - webencodings + - tinycss2>=1.1.0,<1.5 ; extra == 'css' + requires_python: '>=3.10' +- conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda + sha256: 0b75d45f0bba3e95dc693336fa51f40ea28c980131fec438afb7ce6118ed05f6 + md5: d2ffd7602c02f2b316fd921d39876885 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + license: bzip2-1.0.6 + license_family: BSD + purls: [] + size: 260182 + timestamp: 1771350215188 +- conda: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h500dc9f_9.conda + sha256: 9f242f13537ef1ce195f93f0cc162965d6cc79da578568d6d8e50f70dd025c42 + md5: 4173ac3b19ec0a4f400b4f782910368b + depends: + - __osx >=10.13 + license: bzip2-1.0.6 + license_family: BSD + purls: [] + size: 133427 + timestamp: 1771350680709 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda + sha256: 540fe54be35fac0c17feefbdc3e29725cce05d7367ffedfaaa1bdda234b019df + md5: 620b85a3f45526a8bc4d23fd78fc22f0 + depends: + - __osx >=11.0 + license: bzip2-1.0.6 + license_family: BSD + purls: [] + size: 124834 + timestamp: 1771350416561 +- conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda + sha256: 76dfb71df5e8d1c4eded2dbb5ba15bb8fb2e2b0fe42d94145d5eed4c75c35902 + md5: 4cb8e6b48f67de0b018719cdf1136306 + depends: + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + license: bzip2-1.0.6 + license_family: BSD + purls: [] + size: 56115 + timestamp: 1771350256444 +- conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-h4c7d964_0.conda + sha256: 37950019c59b99585cee5d30dbc2cc9696ed4e11f5742606a4db1621ed8f94d6 + md5: f001e6e220355b7f87403a4d0e5bf1ca + depends: + - __win + license: ISC + purls: [] + size: 147734 + timestamp: 1772006322223 +- conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda + sha256: 67cc7101b36421c5913a1687ef1b99f85b5d6868da3abbf6ec1a4181e79782fc + md5: 4492fd26db29495f0ba23f146cd5638d + depends: + - __unix + license: ISC + purls: [] + size: 147413 + timestamp: 1772006283803 +- pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl + name: certifi + version: 2026.2.25 + sha256: 027692e4402ad994f1c42e52a4997a9763c646b73e4096e4d5d6db8af1d6f0fa + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/12/4a/3dfd5f7850cbf0d06dc84ba9aa00db766b52ca38d8b86e3a38314d52498c/cffi-2.0.0-cp311-cp311-macosx_10_13_x86_64.whl + name: cffi + version: 2.0.0 + sha256: b4c854ef3adc177950a8dfc81a86f5115d2abd545751a304c5bcf2c2c7283cfe + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/33/fa/072dd15ae27fbb4e06b437eb6e944e75b068deb09e2a2826039e49ee2045/cffi-2.0.0-cp310-cp310-win_amd64.whl + name: cffi + version: 2.0.0 + sha256: b18a3ed7d5b3bd8d9ef7a8cb226502c6bf8308df1525e1cc676c3680e7176739 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl + name: cffi + version: 2.0.0 + sha256: 19f705ada2530c1167abacb171925dd886168931e0a7b78f5bffcae5c6b5be75 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/47/d9/d83e293854571c877a92da46fdec39158f8d7e68da75bf73581225d28e90/cffi-2.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: cffi + version: 2.0.0 + sha256: afb8db5439b81cf9c9d0c80404b60c3cc9c3add93e114dcae767f1477cb53775 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl + name: cffi + version: 2.0.0 + sha256: 45d5e886156860dc35862657e1494b9bae8dfa63bf56796f2fb56e1679fc0bca + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl + name: cffi + version: 2.0.0 + sha256: 00bdf7acc5f795150faa6957054fbbca2439db2f775ce831222b66f192f03beb + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/4f/8b/f0e4c441227ba756aafbe78f117485b25bb26b1c059d01f137fa6d14896b/cffi-2.0.0-cp311-cp311-macosx_11_0_arm64.whl + name: cffi + version: 2.0.0 + sha256: 2de9a304e27f7596cd03d16f1b7c72219bd944e99cc52b84d0145aefb07cbd3c + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/59/dd/27e9fa567a23931c838c6b02d0764611c62290062a6d4e8ff7863daf9730/cffi-2.0.0-cp314-cp314-macosx_11_0_arm64.whl + name: cffi + version: 2.0.0 + sha256: c654de545946e0db659b3400168c9ad31b5d29593291482c43e3564effbcee13 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/78/2d/7fa73dfa841b5ac06c7b8855cfc18622132e365f5b81d02230333ff26e9e/cffi-2.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: cffi + version: 2.0.0 + sha256: 3e17ed538242334bf70832644a32a7aae3d83b57567f9fd60a26257e992b79ba + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/92/c4/3ce07396253a83250ee98564f8d7e9789fab8e58858f35d07a9a2c78de9f/cffi-2.0.0-cp314-cp314-macosx_10_13_x86_64.whl + name: cffi + version: 2.0.0 + sha256: fc33c5141b55ed366cfaad382df24fe7dcbc686de5be719b207bb248e3053dc5 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/93/d7/516d984057745a6cd96575eea814fe1edd6646ee6efd552fb7b0921dec83/cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl + name: cffi + version: 2.0.0 + sha256: 0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/98/29/9b366e70e243eb3d14a5cb488dfd3a0b6b2f1fb001a203f653b93ccfac88/cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: cffi + version: 2.0.0 + sha256: fc7de24befaeae77ba923797c7c87834c73648a05a4bde34b3b7e5588973a453 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: cffi + version: 2.0.0 + sha256: c8d3b5532fc71b7a77c09192b4a5a200ea992702734a2e9279a37f2478236f26 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/9e/84/ad6a0b408daa859246f57c03efd28e5dd1b33c21737c2db84cae8c237aa5/cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl + name: cffi + version: 2.0.0 + sha256: f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/ae/8f/dc5531155e7070361eb1b7e4c1a9d896d0cb21c49f807a6c03fd63fc877e/cffi-2.0.0-cp311-cp311-win_amd64.whl + name: cffi + version: 2.0.0 + sha256: 66f011380d0e49ed280c789fbd08ff0d40968ee7b665575489afa95c98196ab5 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/bb/92/882c2d30831744296ce713f0feb4c1cd30f346ef747b530b5318715cc367/cffi-2.0.0-cp314-cp314-win_amd64.whl + name: cffi + version: 2.0.0 + sha256: 203a48d1fb583fc7d78a4c6655692963b860a417c0528492a6bc21f1aaefab25 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/d7/91/500d892b2bf36529a75b77958edfcd5ad8e2ce4064ce2ecfeab2125d72d1/cffi-2.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: cffi + version: 2.0.0 + sha256: 8941aaadaf67246224cee8c3803777eed332a19d909b47e29c9842ef1e79ac26 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/df/a2/781b623f57358e360d62cdd7a8c681f074a71d445418a776eef0aadb4ab4/cffi-2.0.0-cp312-cp312-macosx_11_0_arm64.whl + name: cffi + version: 2.0.0 + sha256: 8eca2a813c1cb7ad4fb74d368c2ffbbb4789d377ee5bb8df98373c2cc0dee76c + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/ea/47/4f61023ea636104d4f16ab488e268b93008c3d0bb76893b1b31db1f96802/cffi-2.0.0-cp312-cp312-macosx_10_13_x86_64.whl + name: cffi + version: 2.0.0 + sha256: 6d02d6655b0e54f54c4ef0b94eb6be0607b70853c45ce98bd278dc7de718be5d + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/f8/ed/13bd4418627013bec4ed6e54283b1959cf6db888048c7cf4b4c3b5b36002/cffi-2.0.0-cp312-cp312-win_amd64.whl + name: cffi + version: 2.0.0 + sha256: da68248800ad6320861f129cd9c1bf96ca849a2771a59e0344e88681905916f5 + requires_dist: + - pycparser ; implementation_name != 'PyPy' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/03/f4/44d3b830a20e89ff82a3134912d9a1cf6084d64f3b95dcad40f74449a654/charset_normalizer-3.4.5-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 5bcb3227c3d9aaf73eaaab1db7ccd80a8995c509ee9941e2aae060ca6e4e5d81 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/38/9c/71336bff6934418dc8d1e8a1644176ac9088068bc571da612767619c97b3/charset_normalizer-3.4.5-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 01a1ed54b953303ca7e310fafe0fe347aab348bd81834a0bcd602eb538f89d66 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/40/65/e7c6c77d7aaa4c0d7974f2e403e17f0ed2cb0fc135f77d686b916bf1eead/charset_normalizer-3.4.5-cp314-cp314-win_amd64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 4481e6da1830c8a1cc0b746b47f603b653dadb690bcd851d039ffaefe70533aa + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/43/be/0f0fd9bb4a7fa4fb5067fb7d9ac693d4e928d306f80a0d02bde43a7c4aee/charset_normalizer-3.4.5-cp314-cp314-macosx_10_15_universal2.whl + name: charset-normalizer + version: 3.4.5 + sha256: 8197abe5ca1ffb7d91e78360f915eef5addff270f8a71c1fc5be24a56f3e4873 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/4b/2f/8a1d989bfadd120c90114ab33e0d2a0cbde05278c1fc15e83e62d570f50a/charset_normalizer-3.4.5-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 340810d34ef83af92148e96e3e44cb2d3f910d2bf95e5618a5c467d9f102231d + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/67/5c/ae30362a88b4da237d71ea214a8c7eb915db3eec941adda511729ac25fa2/charset_normalizer-3.4.5-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 7ad83b8f9379176c841f8865884f3514d905bcd2a9a3b210eaa446e7d2223e4d + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/70/53/e44a4c07e8904500aec95865dc3f6464dc3586a039ef0df606eb3ac38e35/charset_normalizer-3.4.5-cp312-cp312-win_amd64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 728c6a963dfab66ef865f49286e45239384249672cd598576765acc2a640a636 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/8f/9e/bcec3b22c64ecec47d39bf5167c2613efd41898c019dccd4183f6aa5d6a7/charset_normalizer-3.4.5-cp311-cp311-macosx_10_9_universal2.whl + name: charset-normalizer + version: 3.4.5 + sha256: 610f72c0ee565dfb8ae1241b666119582fdbfe7c0975c175be719f940e110694 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 0625665e4ebdddb553ab185de5db7054393af8879fb0c87bd5690d14379d6819 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/9c/b6/9ee9c1a608916ca5feae81a344dffbaa53b26b90be58cc2159e3332d44ec/charset_normalizer-3.4.5-cp312-cp312-macosx_10_13_universal2.whl + name: charset-normalizer + version: 3.4.5 + sha256: ed97c282ee4f994ef814042423a529df9497e3c666dca19be1d4cd1129dc7ade + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/a5/c3/84fb174e7770f2df2e1a2115090771bfbc2227fb39a765c6d00568d1aab4/charset_normalizer-3.4.5-cp310-cp310-win_amd64.whl + name: charset-normalizer + version: 3.4.5 + sha256: 02a9d1b01c1e12c27883b0c9349e0bcd9ae92e727ff1a277207e1a262b1cbf05 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + name: charset-normalizer + version: 3.4.5 + sha256: 4167a621a9a1a986c73777dbc15d4b5eac8ac5c10393374109a343d4013ec765 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + name: charset-normalizer + version: 3.4.5 + sha256: e37bd100d2c5d3ba35db9c7c5ba5a9228cbcffe5c4778dc824b164e5257813d7 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + name: charset-normalizer + version: 3.4.5 + sha256: ac59c15e3f1465f722607800c68713f9fbc2f672b9eb649fe831da4019ae9b23 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/fe/1f/a853b73d386521fd44b7f67ded6b17b7b2367067d9106a5c4b44f9a34274/charset_normalizer-3.4.5-cp311-cp311-win_amd64.whl + name: charset-normalizer + version: 3.4.5 + sha256: f8102ae93c0bc863b1d41ea0f4499c20a83229f52ed870850892df555187154a + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl + name: colorama + version: 0.4.6 + sha256: 4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6 + requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*' +- pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl + name: comm + version: 0.2.3 + sha256: c615d91d75f7f04f095b30d1c1711babd43bdc6419c1be9886a85f2f4e489417 + requires_dist: + - pytest ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/12/a3/da4153ec8fe25d263aa48c1a4cbde7f49b59af86f0b6f7862788c60da737/contourpy-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl + name: contourpy + version: 1.3.2 + sha256: ba38e3f9f330af820c4b27ceb4b9c7feee5fe0493ea53a8720f4792667465934 + requires_dist: + - numpy>=1.23 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.15.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/2f/6c/330de89ae1087eb622bfca0177d32a7ece50c3ef07b28002de4757d9d875/contourpy-1.3.2-cp310-cp310-macosx_11_0_arm64.whl + name: contourpy + version: 1.3.2 + sha256: dc41ba0714aa2968d1f8674ec97504a8f7e334f48eeacebcaa6256213acb0989 + requires_dist: + - numpy>=1.23 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.15.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/32/5c/1ee32d1c7956923202f00cf8d2a14a62ed7517bdc0ee1e55301227fc273c/contourpy-1.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: contourpy + version: 1.3.2 + sha256: ad687a04bc802cbe8b9c399c07162a3c35e227e2daccf1668eb1f278cb698631 + requires_dist: + - numpy>=1.23 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.15.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/54/ec/5162b8582f2c994721018d0c9ece9dc6ff769d298a8ac6b6a652c307e7df/contourpy-1.3.2-cp310-cp310-win_amd64.whl + name: contourpy + version: 1.3.2 + sha256: c440093bbc8fc21c637c03bafcbef95ccd963bc6e0514ad887932c18ca2a759a + requires_dist: + - numpy>=1.23 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.15.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/04/5f/9ff93450ba96b09c7c2b3f81c94de31c89f92292f1380261bd7195bea4ea/contourpy-1.3.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: f64836de09927cba6f79dcd00fdd7d5329f3fccc633468507079c829ca4db4e3 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/0d/44/c4b0b6095fef4dc9c420e041799591e3b63e9619e3044f7f4f6c21c0ab24/contourpy-1.3.3-cp311-cp311-macosx_11_0_arm64.whl + name: contourpy + version: 1.3.3 + sha256: 23416f38bfd74d5d28ab8429cc4d63fa67d5068bd711a85edb1c3fb0c3e2f381 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl + name: contourpy + version: 1.3.3 + sha256: 1cadd8b8969f060ba45ed7c1b714fe69185812ab43bd6b86a9123fe8f99c3263 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/19/e8/6026ed58a64563186a9ee3f29f41261fd1828f527dd93d33b60feca63352/contourpy-1.3.3-cp312-cp312-win_amd64.whl + name: contourpy + version: 1.3.3 + sha256: 8153b8bfc11e1e4d75bcb0bff1db232f9e10b274e0929de9d608027e0d34ff8b + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: 4debd64f124ca62069f313a9cb86656ff087786016d76927ae2cf37846b006c9 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/53/3e/405b59cfa13021a56bba395a6b3aca8cec012b45bf177b0eaf7a202cde2c/contourpy-1.3.3-cp312-cp312-macosx_11_0_arm64.whl + name: contourpy + version: 1.3.3 + sha256: 556dba8fb6f5d8742f2923fe9457dbdd51e1049c4a43fd3986a0b14a1d815fc6 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/5f/4b/6157f24ca425b89fe2eb7e7be642375711ab671135be21e6faa100f7448c/contourpy-1.3.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: 51e79c1f7470158e838808d4a996fa9bac72c498e93d8ebe5119bc1e6becb0db + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: 177fb367556747a686509d6fef71d221a4b198a3905fe824430e5ea0fda54eb5 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/72/8b/4546f3ab60f78c514ffb7d01a0bd743f90de36f0019d1be84d0a708a580a/contourpy-1.3.3-cp314-cp314-macosx_10_13_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: fde6c716d51c04b1c25d0b90364d0be954624a0ee9d60e23e850e8d48353d07a + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/7d/c2/57f54b03d0f22d4044b8afb9ca0e184f8b1afd57b4f735c2fa70883dc601/contourpy-1.3.3-cp314-cp314-win_amd64.whl + name: contourpy + version: 1.3.3 + sha256: cf9022ef053f2694e31d630feaacb21ea24224be1c3ad0520b13d844274614fd + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/91/2e/c4390a31919d8a78b90e8ecf87cd4b4c4f05a5b48d05ec17db8e5404c6f4/contourpy-1.3.3-cp311-cp311-macosx_10_9_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: 709a48ef9a690e1343202916450bc48b9e51c049b089c7f79a267b46cffcdaa1 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl + name: contourpy + version: 1.3.3 + sha256: d002b6f00d73d69333dac9d0b8d5e84d9724ff9ef044fd63c5986e62b7c9e1b1 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/98/4b/9bd370b004b5c9d8045c6c33cf65bae018b27aca550a3f657cdc99acdbd8/contourpy-1.3.3-cp311-cp311-win_amd64.whl + name: contourpy + version: 1.3.3 + sha256: 3519428f6be58431c56581f1694ba8e50626f2dd550af225f82fb5f5814d2a42 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/be/45/adfee365d9ea3d853550b2e735f9d66366701c65db7855cd07621732ccfc/contourpy-1.3.3-cp312-cp312-macosx_10_13_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: b08a32ea2f8e42cf1d4be3169a98dd4be32bafe4f22b6c4cb4ba810fa9e5d2cb + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/cc/8f/ec6289987824b29529d0dfda0d74a07cec60e54b9c92f3c9da4c0ac732de/contourpy-1.3.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: contourpy + version: 1.3.3 + sha256: 4d00e655fcef08aba35ec9610536bfe90267d7ab5ba944f7032549c55a146da1 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/fd/e1/3542a9cb596cadd76fcef413f19c79216e002623158befe6daa03dbfa88c/contourpy-1.3.3-cp314-cp314-macosx_11_0_arm64.whl + name: contourpy + version: 1.3.3 + sha256: cbedb772ed74ff5be440fa8eee9bd49f64f6e3fc09436d9c7d8f1c287b121d77 + requires_dist: + - numpy>=1.25 + - furo ; extra == 'docs' + - sphinx>=7.2 ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - bokeh ; extra == 'bokeh' + - selenium ; extra == 'bokeh' + - contourpy[bokeh,docs] ; extra == 'mypy' + - bokeh ; extra == 'mypy' + - docutils-stubs ; extra == 'mypy' + - mypy==1.17.0 ; extra == 'mypy' + - types-pillow ; extra == 'mypy' + - contourpy[test-no-images] ; extra == 'test' + - matplotlib ; extra == 'test' + - pillow ; extra == 'test' + - pytest ; extra == 'test-no-images' + - pytest-cov ; extra == 'test-no-images' + - pytest-rerunfailures ; extra == 'test-no-images' + - pytest-xdist ; extra == 'test-no-images' + - wurlitzer ; extra == 'test-no-images' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/06/90/2cdab0974b9b5bbc1623f7876b73603aecac11b8d95b85b5b86b32de5eab/coverage-7.13.4-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + name: coverage + version: 7.13.4 + sha256: 0dd7ab8278f0d58a0128ba2fca25824321f05d059c1441800e934ff2efa52129 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/35/b0/d69df26607c64043292644dbb9dc54b0856fabaa2cbb1eeee3331cc9e280/coverage-7.13.4-cp310-cp310-macosx_11_0_arm64.whl + name: coverage + version: 7.13.4 + sha256: a32ebc02a1805adf637fc8dec324b5cdacd2e493515424f70ee33799573d661b + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/44/d4/7827d9ffa34d5d4d752eec907022aa417120936282fc488306f5da08c292/coverage-7.13.4-cp310-cp310-macosx_10_9_x86_64.whl + name: coverage + version: 7.13.4 + sha256: 0fc31c787a84f8cd6027eba44010517020e0d18487064cd3d8968941856d1415 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/5d/96/5238b1efc5922ddbdc9b0db9243152c09777804fb7c02ad1741eb18a11c0/coverage-7.13.4-cp312-cp312-macosx_11_0_arm64.whl + name: coverage + version: 7.13.4 + sha256: 40aa8808140e55dc022b15d8aa7f651b6b3d68b365ea0398f1441e0b04d859c3 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/5d/a0/2ea570925524ef4e00bb6c82649f5682a77fac5ab910a65c9284de422600/coverage-7.13.4-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + name: coverage + version: 7.13.4 + sha256: 2c048ea43875fbf8b45d476ad79f179809c590ec7b79e2035c662e7afa3192e3 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/61/08/3d9c8613079d2b11c185b865de9a4c1a68850cfda2b357fae365cf609f29/coverage-7.13.4-cp311-cp311-win_amd64.whl + name: coverage + version: 7.13.4 + sha256: 2421d591f8ca05b308cf0092807308b2facbefe54af7c02ac22548b88b95c98f + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/76/53/c16972708cbb79f2942922571a687c52bd109a7bd51175aeb7558dff2236/coverage-7.13.4-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + name: coverage + version: 7.13.4 + sha256: 8e264226ec98e01a8e1054314af91ee6cde0eacac4f465cc93b03dbe0bce2fd7 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/77/4e/c0a25a425fcf5557d9abd18419c95b63922e897bc86c1f327f155ef234a9/coverage-7.13.4-cp312-cp312-win_amd64.whl + name: coverage + version: 7.13.4 + sha256: 9401ebc7ef522f01d01d45532c68c5ac40fb27113019b6b7d8b208f6e9baa126 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/78/13/331f94934cf6c092b8ea59ff868eb587bc8fe0893f02c55bc6c0183a192e/coverage-7.13.4-cp310-cp310-win_amd64.whl + name: coverage + version: 7.13.4 + sha256: 2cb0f1e000ebc419632bbe04366a8990b6e32c4e0b51543a6484ffe15eaeda95 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/92/11/a9cf762bb83386467737d32187756a42094927150c3e107df4cb078e8590/coverage-7.13.4-cp314-cp314-macosx_10_15_x86_64.whl + name: coverage + version: 7.13.4 + sha256: 300deaee342f90696ed186e3a00c71b5b3d27bffe9e827677954f4ee56969601 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a5/70/9b8b67a0945f3dfec1fd896c5cefb7c19d5a3a6d74630b99a895170999ae/coverage-7.13.4-cp313-cp313-macosx_11_0_arm64.whl + name: coverage + version: 7.13.4 + sha256: 3599eb3992d814d23b35c536c28df1a882caa950f8f507cef23d1cbf334995ac + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a7/4d/1f8e723f6829977410efeb88f73673d794075091c8c7c18848d273dc9d73/coverage-7.13.4-cp314-cp314-win_amd64.whl + name: coverage + version: 7.13.4 + sha256: 245e37f664d89861cf2329c9afa2c1fe9e6d4e1a09d872c947e70718aeeac505 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/b4/ad/b59e5b451cf7172b8d1043dc0fa718f23aab379bc1521ee13d4bd9bfa960/coverage-7.13.4-cp311-cp311-macosx_10_9_x86_64.whl + name: coverage + version: 7.13.4 + sha256: d490ba50c3f35dd7c17953c68f3270e7ccd1c6642e2d2afe2d8e720b98f5a053 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d1/81/4ce2fdd909c5a0ed1f6dedb88aa57ab79b6d1fbd9b588c1ac7ef45659566/coverage-7.13.4-cp312-cp312-macosx_10_13_x86_64.whl + name: coverage + version: 7.13.4 + sha256: 02231499b08dabbe2b96612993e5fc34217cdae907a51b906ac7fca8027a4459 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d3/28/56e6d892b7b052236d67c95f1936b6a7cf7c3e2634bf27610b8cbd7f9c60/coverage-7.13.4-cp314-cp314-macosx_11_0_arm64.whl + name: coverage + version: 7.13.4 + sha256: 29e3220258d682b6226a9b0925bc563ed9a1ebcff3cad30f043eceea7eaf2689 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/db/23/aad45061a31677d68e47499197a131eea55da4875d16c1f42021ab963503/coverage-7.13.4-cp313-cp313-macosx_10_13_x86_64.whl + name: coverage + version: 7.13.4 + sha256: b66a2da594b6068b48b2692f043f35d4d3693fb639d5ea8b39533c2ad9ac3ab9 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e2/0c/dbfafbe90a185943dcfbc766fe0e1909f658811492d79b741523a414a6cc/coverage-7.13.4-cp313-cp313-win_amd64.whl + name: coverage + version: 7.13.4 + sha256: e6f70dec1cc557e52df5306d051ef56003f74d56e9c4dd7ddb07e07ef32a84dd + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e4/dc/b2442d10020c2f52617828862d8b6ee337859cd8f3a1f13d607dddda9cf7/coverage-7.13.4-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + name: coverage + version: 7.13.4 + sha256: b720ce6a88a2755f7c697c23268ddc47a571b88052e6b155224347389fdf6a3b + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f1/17/0cb7ca3de72e5f4ef2ec2fa0089beafbcaaaead1844e8b8a63d35173d77d/coverage-7.13.4-cp311-cp311-macosx_11_0_arm64.whl + name: coverage + version: 7.13.4 + sha256: 19bc3c88078789f8ef36acb014d7241961dbf883fd2533d18cb1e7a5b4e28b11 + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f8/02/aa7ec01d1a5023c4b680ab7257f9bfde9defe8fdddfe40be096ac19e8177/coverage-7.13.4-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + name: coverage + version: 7.13.4 + sha256: 8041b6c5bfdc03257666e9881d33b1abc88daccaf73f7b6340fb7946655cd10f + requires_dist: + - tomli ; python_full_version <= '3.11' and extra == 'toml' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl + name: cycler + version: 0.12.1 + sha256: 85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30 + requires_dist: + - ipython ; extra == 'docs' + - matplotlib ; extra == 'docs' + - numpydoc ; extra == 'docs' + - sphinx ; extra == 'docs' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/13/f7/a0b368ce54ffff9e9028c098bd2d28cfc5b54f9f6c186929083d4c60ba58/debugpy-1.8.20-cp313-cp313-win_amd64.whl + name: debugpy + version: 1.8.20 + sha256: eb506e45943cab2efb7c6eafdd65b842f3ae779f020c82221f55aca9de135ed7 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/72/43/09d49106e770fe558ced5e80df2e3c2ebee10e576eda155dcc5670473663/debugpy-1.8.20-cp310-cp310-win_amd64.whl + name: debugpy + version: 1.8.20 + sha256: 3ca85463f63b5dd0aa7aaa933d97cbc47c174896dcae8431695872969f981893 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/a1/39/2bef246368bd42f9bd7cba99844542b74b84dacbdbea0833e610f384fee8/debugpy-1.8.20-cp312-cp312-win_amd64.whl + name: debugpy + version: 1.8.20 + sha256: a1a8f851e7cf171330679ef6997e9c579ef6dd33c9098458bd9986a0f4ca52e3 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/d5/92/1cb532e88560cbee973396254b21bece8c5d7c2ece958a67afa08c9f10dc/debugpy-1.8.20-cp311-cp311-win_amd64.whl + name: debugpy + version: 1.8.20 + sha256: 1f7650546e0eded1902d0f6af28f787fa1f1dbdbc97ddabaf1cd963a405930cb + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl + name: debugpy + version: 1.8.20 + sha256: 5be9bed9ae3be00665a06acaa48f8329d2b9632f15fd09f6a9a8c8d9907e54d7 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/e0/d9/1f07395b54413432624d61524dfd98c1a7c7827d2abfdb8829ac92638205/debugpy-1.8.20-cp314-cp314-win_amd64.whl + name: debugpy + version: 1.8.20 + sha256: a98eec61135465b062846112e5ecf2eebb855305acc1dfbae43b72903b8ab5be + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl + name: decorator + version: 5.2.1 + sha256: d316bb415a2d9e2d2b3abcc4084c6502fc09240e292cd76a76afc106a1c8e04a + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl + name: defusedxml + version: 0.7.1 + sha256: a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61 + requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*' +- pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl + name: exceptiongroup + version: 1.3.1 + sha256: a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598 + requires_dist: + - typing-extensions>=4.6.0 ; python_full_version < '3.13' + - pytest>=6 ; extra == 'test' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl + name: executing + version: 2.2.1 + sha256: 760643d3452b4d777d295bb167ccc74c64a81df23fb5e08eff250c425a4b2017 + requires_dist: + - asttokens>=2.1.0 ; extra == 'tests' + - ipython ; extra == 'tests' + - pytest ; extra == 'tests' + - coverage ; extra == 'tests' + - coverage-enable-subprocess ; extra == 'tests' + - littleutils ; extra == 'tests' + - rich ; python_full_version >= '3.11' and extra == 'tests' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl + name: fastjsonschema + version: 2.21.2 + sha256: 1c797122d0a86c5cace2e54bf4e819c36223b552017172f32c5c024a6b77e463 + requires_dist: + - colorama ; extra == 'devel' + - jsonschema ; extra == 'devel' + - json-spec ; extra == 'devel' + - pylint ; extra == 'devel' + - pytest ; extra == 'devel' + - pytest-benchmark ; extra == 'devel' + - pytest-cache ; extra == 'devel' + - validictory ; extra == 'devel' +- pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip + name: filterpy + version: 1.4.2 + sha256: 6e247b3c9de934dee5a8baa152e88b5f50f0d0bd24e5f25496a81795d7425fe0 + requires_dist: + - numpy + - scipy + - matplotlib +- pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip + name: filterpy + version: 1.4.5 + sha256: 4f2a4d39e4ea601b9ab42b2db08b5918a9538c168cff1c6895ae26646f3d73b1 + requires_dist: + - numpy + - scipy + - matplotlib +- pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl + name: flake8 + version: 7.3.0 + sha256: b9696257b9ce8beb888cdbe31cf885c90d31928fe202be0889a7cdafad32f01e + requires_dist: + - mccabe>=0.7.0,<0.8.0 + - pycodestyle>=2.14.0,<2.15.0 + - pyflakes>=3.4.0,<3.5.0 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/0b/a1/d16318232964d786907b9b3613b8409f74cf0be2da400854509d3a864e43/fonttools-4.62.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 31a804c16d76038cc4e3826e07678efb0a02dc4f15396ea8e07088adbfb2578e + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/1a/64/61f69298aa6e7c363dcf00dd6371a654676900abe27d1effd1a74b43e5d0/fonttools-4.62.0-cp314-cp314-macosx_10_15_universal2.whl + name: fonttools + version: 4.62.0 + sha256: 4fa5a9c716e2f75ef34b5a5c2ca0ee4848d795daa7e6792bf30fd4abf8993449 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/2e/9f/91081ffe5881253177c175749cce5841f5ec6e931f5d52f4a817207b7429/fonttools-4.62.0-cp314-cp314-win_amd64.whl + name: fonttools + version: 4.62.0 + sha256: a5f974006d14f735c6c878fc4b117ad031dc93638ddcc450ca69f8fd64d5e104 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/4d/8b/ba59069a490f61b737e064c3129453dbd28ee38e81d56af0d04d7e6b4de4/fonttools-4.62.0-cp312-cp312-macosx_10_13_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 7199c73b326bad892f1cb53ffdd002128bfd58a89b8f662204fbf1daf8d62e85 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/5c/57/a23a051fcff998fdfabdd33c6721b5bad499da08b586d3676993410071f0/fonttools-4.62.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 3e2ff573de2775508c8a366351fb901c4ced5dc6cf2d87dd15c973bedcdd5216 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/77/ce/f5a4c42c117f8113ce04048053c128d17426751a508f26398110c993a074/fonttools-4.62.0-cp311-cp311-win_amd64.whl + name: fonttools + version: 4.62.0 + sha256: 4da779e8f342a32856075ddb193b2a024ad900bc04ecb744014c32409ae871ed + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + name: fonttools + version: 4.62.0 + sha256: 274c8b8a87e439faf565d3bcd3f9f9e31bca7740755776a4a90a4bfeaa722efa + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/82/e0/9db48ec7f6b95bae7b20667ded54f18dba8e759ef66232c8683822ae26fc/fonttools-4.62.0-cp310-cp310-macosx_10_9_universal2.whl + name: fonttools + version: 4.62.0 + sha256: 62b6a3d0028e458e9b59501cf7124a84cd69681c433570e4861aff4fb54a236c + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/86/c8/c6669e42d2f4efd60d38a3252cebbb28851f968890efb2b9b15f9d1092b0/fonttools-4.62.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 840632ea9c1eab7b7f01c369e408c0721c287dfd7500ab937398430689852fd1 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/8a/d7/8e4845993ee233c2023d11babe9b3dae7d30333da1d792eeccebcb77baab/fonttools-4.62.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 591220d5333264b1df0d3285adbdfe2af4f6a45bbf9ca2b485f97c9f577c49ff + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ab/9d/7ad1ffc080619f67d0b1e0fa6a0578f0be077404f13fd8e448d1616a94a3/fonttools-4.62.0-cp312-cp312-macosx_10_13_universal2.whl + name: fonttools + version: 4.62.0 + sha256: 22bde4dc12a9e09b5ced77f3b5053d96cf10c4976c6ac0dee293418ef289d221 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c0/7a/9aeec114bc9fc00d757a41f092f7107863d372e684a5b5724c043654477c/fonttools-4.62.0-cp311-cp311-macosx_10_9_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 153afc3012ff8761b1733e8fbe5d98623409774c44ffd88fbcb780e240c11d13 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 93e27131a5a0ae82aaadcffe309b1bae195f6711689722af026862bede05c07c + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c6/57/6b08756fe4455336b1fe160ab3c11fccc90768ccb6ee03fb0b45851aace4/fonttools-4.62.0-cp314-cp314-macosx_10_15_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 625f5cbeb0b8f4e42343eaeb4bc2786718ddd84760a2f5e55fdd3db049047c00 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/cd/06/cc96468781a4dc8ae2f14f16f32b32f69bde18cb9384aad27ccc7adf76f7/fonttools-4.62.0-cp312-cp312-win_amd64.whl + name: fonttools + version: 4.62.0 + sha256: 658ab837c878c4d2a652fcbb319547ea41693890e6434cf619e66f79387af3b8 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/dd/45/86eccfdc922cb9fafc63189a9793fa9f6dd60e68a07be42e454ef2c0deae/fonttools-4.62.0-cp310-cp310-macosx_10_9_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 966557078b55e697f65300b18025c54e872d7908d1899b7314d7c16e64868cb2 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e4/33/63d79ca41020dd460b51f1e0f58ad1ff0a36b7bcbdf8f3971d52836581e9/fonttools-4.62.0-cp311-cp311-macosx_10_9_universal2.whl + name: fonttools + version: 4.62.0 + sha256: 196cafef9aeec5258425bd31a4e9a414b2ee0d1557bca184d7923d3d3bcd90f9 + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e9/ee/08c0b7f8bac6e44638de6fe9a3e710a623932f60eccd58912c4d4743516d/fonttools-4.62.0-cp310-cp310-win_amd64.whl + name: fonttools + version: 4.62.0 + sha256: 9bf75eb69330e34ad2a096fac67887102c8537991eb6cac1507fc835bbb70e0a + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + name: fonttools + version: 4.62.0 + sha256: 6826a5aa53fb6def8a66bf423939745f415546c4e92478a7c531b8b6282b6c3b + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: fonttools + version: 4.62.0 + sha256: 106aec9226f9498fc5345125ff7200842c01eda273ae038f5049b0916907acee + requires_dist: + - lxml>=4.0 ; extra == 'lxml' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'woff' + - zopfli>=0.1.4 ; extra == 'woff' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'unicode' + - lz4>=1.7.4.2 ; extra == 'graphite' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'interpolatable' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'interpolatable' + - pycairo ; extra == 'interpolatable' + - matplotlib ; extra == 'plot' + - sympy ; extra == 'symfont' + - xattr ; sys_platform == 'darwin' and extra == 'type1' + - skia-pathops>=0.5.0 ; extra == 'pathops' + - uharfbuzz>=0.45.0 ; extra == 'repacker' + - lxml>=4.0 ; extra == 'all' + - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'all' + - brotlicffi>=0.8.0 ; platform_python_implementation != 'CPython' and extra == 'all' + - zopfli>=0.1.4 ; extra == 'all' + - unicodedata2>=17.0.0 ; python_full_version < '3.15' and extra == 'all' + - lz4>=1.7.4.2 ; extra == 'all' + - scipy ; platform_python_implementation != 'PyPy' and extra == 'all' + - munkres ; platform_python_implementation == 'PyPy' and extra == 'all' + - pycairo ; extra == 'all' + - matplotlib ; extra == 'all' + - sympy ; extra == 'all' + - xattr ; sys_platform == 'darwin' and extra == 'all' + - skia-pathops>=0.5.0 ; extra == 'all' + - uharfbuzz>=0.45.0 ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl + name: fqdn + version: 1.5.1 + sha256: 3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014 + requires_dist: + - cached-property>=1.3.0 ; python_full_version < '3.8' + requires_python: '>=2.7,!=3.0,!=3.1,!=3.2,!=3.3,!=3.4,<4' +- pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl + name: h11 + version: 0.16.0 + sha256: 63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/54/a4/974b666f64c339e5b0b44fc782edee92ab3341c17367a040e41f5132c15b/h5py-3.7.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl + name: h5py + version: 3.7.0 + sha256: 04e2e1e2fc51b8873e972a08d2f89625ef999b1f2d276199011af57bb9fc7851 + requires_dist: + - numpy>=1.14.5 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/6e/5e/f34fb9d87cec244d59604ef506d82727a1e35d03713dc5771bd95dcffa5d/h5py-3.7.0-cp310-cp310-macosx_10_9_x86_64.whl + name: h5py + version: 3.7.0 + sha256: d77af42cb751ad6cc44f11bae73075a07429a5cf2094dfde2b1e716e059b3911 + requires_dist: + - numpy>=1.14.5 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/af/60/0b59c97efe8450ed8fbcc9fffa367a31385e2f197eaf3bd55cfca74846ea/h5py-3.7.0-cp310-cp310-macosx_11_0_arm64.whl + name: h5py + version: 3.7.0 + sha256: 63beb8b7b47d0896c50de6efb9a1eaa81dbe211f3767e7dd7db159cea51ba37a + requires_dist: + - numpy>=1.14.5 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/bd/18/f5eed64fc06b9d17ef11647d6c5016b8a97e3abf0afe6d080c070027a195/h5py-3.7.0-cp310-cp310-win_amd64.whl + name: h5py + version: 3.7.0 + sha256: f514b24cacdd983e61f8d371edac8c1b780c279d0acb8485639e97339c866073 + requires_dist: + - numpy>=1.14.5 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/03/c1/0976b235cf29ead553e22f2fb6385a8252b533715e00d0ae52ed7b900582/h5py-3.16.0-cp312-cp312-win_amd64.whl + name: h5py + version: 3.16.0 + sha256: 96b422019a1c8975c2d5dadcf61d4ba6f01c31f92bbde6e4649607885fe502d6 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl + name: h5py + version: 3.16.0 + sha256: 370a845f432c2c9619db8eed334d1e610c6015796122b0e57aa46312c22617d9 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3a/6b/231413e58a787a89b316bb0d1777da3c62257e4797e09afd8d17ad3549dc/h5py-3.16.0-cp310-cp310-macosx_10_9_x86_64.whl + name: h5py + version: 3.16.0 + sha256: e06f864bedb2c8e7c1358e6c73af48519e317457c444d6f3d332bb4e8fa6d7d9 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3e/14/615a450205e1b56d16c6783f5ccd116cde05550faad70ae077c955654a75/h5py-3.16.0-cp314-cp314-win_amd64.whl + name: h5py + version: 3.16.0 + sha256: fa48993a0b799737ba7fd21e2350fa0a60701e58180fae9f2de834bc39a147ab + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/48/3c/7fcd9b4c9eed82e91fb15568992561019ae7a829d1f696b2c844355d95dd/h5py-3.16.0-cp314-cp314-macosx_10_15_x86_64.whl + name: h5py + version: 3.16.0 + sha256: 9c9d307c0ef862d1cd5714f72ecfafe0a5d7529c44845afa8de9f46e5ba8bd65 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/52/a0/c1f604538ff6db22a0690be2dc44ab59178e115f63c917794e529356ab23/h5py-3.16.0-cp311-cp311-manylinux_2_28_x86_64.whl + name: h5py + version: 3.16.0 + sha256: fb1720028d99040792bb2fb31facb8da44a6f29df7697e0b84f0d79aff2e9bd3 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/66/35/d88fd6718832133c885004c61ceeeb24dbd6397ef877dbed6b3a64d6a286/h5py-3.16.0-cp310-cp310-win_amd64.whl + name: h5py + version: 3.16.0 + sha256: bdef06507725b455fccba9c16529121a5e1fbf56aa375f7d9713d9e8ff42454d + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/6a/b7/9366ed44ced9b7ef357ab48c94205280276db9d7f064aa3012a97227e966/h5py-3.16.0-cp314-cp314-macosx_11_0_arm64.whl + name: h5py + version: 3.16.0 + sha256: 8c1eff849cdd53cbc73c214c30ebdb6f1bb8b64790b4b4fc36acdb5e43570210 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/74/f9/557ce3aad0fe8471fb5279bab0fc56ea473858a022c4ce8a0b8f303d64e9/h5py-3.16.0-cp310-cp310-macosx_11_0_arm64.whl + name: h5py + version: 3.16.0 + sha256: ec86d4fffd87a0f4cb3d5796ceb5a50123a2a6d99b43e616e5504e66a953eca3 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/9e/e9/1a19e42cd43cc1365e127db6aae85e1c671da1d9a5d746f4d34a50edb577/h5py-3.16.0-cp312-cp312-manylinux_2_28_x86_64.whl + name: h5py + version: 3.16.0 + sha256: dfc21898ff025f1e8e67e194965a95a8d4754f452f83454538f98f8a3fcb207e + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/b0/42/c84efcc1d4caebafb1ecd8be4643f39c85c47a80fe254d92b8b43b1eadaf/h5py-3.16.0-cp312-cp312-macosx_11_0_arm64.whl + name: h5py + version: 3.16.0 + sha256: 42b012933a83e1a558c673176676a10ce2fd3759976a0fedee1e672d1e04fc9d + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl + name: h5py + version: 3.16.0 + sha256: 42108e93326c50c2810025aade9eac9d6827524cdccc7d4b75a546e5ab308edb + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ba/95/a825894f3e45cbac7554c4e97314ce886b233a20033787eda755ca8fecc7/h5py-3.16.0-cp311-cp311-macosx_10_9_x86_64.whl + name: h5py + version: 3.16.0 + sha256: 719439d14b83f74eeb080e9650a6c7aa6d0d9ea0ca7f804347b05fac6fbf18af + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl + name: h5py + version: 3.16.0 + sha256: 9300ad32dea9dfc5171f94d5f6948e159ed93e4701280b0f508773b3f582f402 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/bf/3b/38ff88b347c3e346cda1d3fc1b65a7aa75d40632228d8b8a5d7b58508c24/h5py-3.16.0-cp311-cp311-macosx_11_0_arm64.whl + name: h5py + version: 3.16.0 + sha256: c3f0a0e136f2e95dd0b67146abb6668af4f1a69c81ef8651a2d316e8e01de447 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl + name: h5py + version: 3.16.0 + sha256: 18f2bbcd545e6991412253b98727374c356d67caa920e68dc79eab36bf5fedad + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c8/c0/5d4119dba94093bbafede500d3defd2f5eab7897732998c04b54021e530b/h5py-3.16.0-cp312-cp312-macosx_10_13_x86_64.whl + name: h5py + version: 3.16.0 + sha256: c5313566f4643121a78503a473f0fb1e6dcc541d5115c44f05e037609c565c4d + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/cb/92/a8851d936547efe30cc0ce5245feac01f3ec6171f7899bc3f775c72030b3/h5py-3.16.0-cp310-cp310-manylinux_2_28_x86_64.whl + name: h5py + version: 3.16.0 + sha256: 8975273c2c5921c25700193b408e28d6bdd0111c37468b2d4e25dcec4cd1d84d + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f1/16/d905e7f53e661ce2c24686c38048d8e2b750ffc4350009d41c4e6c6c9826/h5py-3.16.0-cp314-cp314-manylinux_2_28_x86_64.whl + name: h5py + version: 3.16.0 + sha256: e4360f15875a532bc7b98196c7592ed4fc92672a57c0a621355961cafb17a6dd + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f7/20/e6c0ff62ca2ad1a396a34f4380bafccaaf8791ff8fccf3d995a1fc12d417/h5py-3.16.0-cp311-cp311-win_amd64.whl + name: h5py + version: 3.16.0 + sha256: 17d1f1630f92ad74494a9a7392ab25982ce2b469fc62da6074c0ce48366a2999 + requires_dist: + - numpy>=1.21.2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl + name: httpcore + version: 1.0.9 + sha256: 2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55 + requires_dist: + - certifi + - h11>=0.16 + - anyio>=4.0,<5.0 ; extra == 'asyncio' + - h2>=3,<5 ; extra == 'http2' + - socksio==1.* ; extra == 'socks' + - trio>=0.22.0,<1.0 ; extra == 'trio' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl + name: httpx + version: 0.28.1 + sha256: d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad + requires_dist: + - anyio + - certifi + - httpcore==1.* + - idna + - brotli ; platform_python_implementation == 'CPython' and extra == 'brotli' + - brotlicffi ; platform_python_implementation != 'CPython' and extra == 'brotli' + - click==8.* ; extra == 'cli' + - pygments==2.* ; extra == 'cli' + - rich>=10,<14 ; extra == 'cli' + - h2>=3,<5 ; extra == 'http2' + - socksio==1.* ; extra == 'socks' + - zstandard>=0.18.0 ; extra == 'zstd' + requires_python: '>=3.8' +- conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + sha256: 142a722072fa96cf16ff98eaaf641f54ab84744af81754c292cb81e0881c0329 + md5: 186a18e3ba246eccfc7cff00cd19a870 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + - libstdcxx >=14 + license: MIT + license_family: MIT + purls: [] + size: 12728445 + timestamp: 1767969922681 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + sha256: 24bc62335106c30fecbcc1dba62c5eba06d18b90ea1061abd111af7b9c89c2d7 + md5: 114e6bfe7c5ad2525eb3597acdbf2300 + depends: + - __osx >=11.0 + license: MIT + license_family: MIT + purls: [] + size: 12389400 + timestamp: 1772209104304 +- pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl + name: idna + version: '3.11' + sha256: 771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea + requires_dist: + - ruff>=0.6.2 ; extra == 'all' + - mypy>=1.11.2 ; extra == 'all' + - pytest>=8.3.2 ; extra == 'all' + - flake8>=7.1.1 ; extra == 'all' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl + name: iniconfig + version: 2.3.0 + sha256: f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl + name: ipykernel + version: 7.2.0 + sha256: 3bbd4420d2b3cc105cbdf3756bfc04500b1e52f090a90716851f3916c62e1661 + requires_dist: + - appnope>=0.1.2 ; sys_platform == 'darwin' + - comm>=0.1.1 + - debugpy>=1.6.5 + - ipython>=7.23.1 + - jupyter-client>=8.8.0 + - jupyter-core>=5.1,!=6.0.* + - matplotlib-inline>=0.1 + - nest-asyncio>=1.4 + - packaging>=22 + - psutil>=5.7 + - pyzmq>=25 + - tornado>=6.4.1 + - traitlets>=5.4.0 + - coverage[toml] ; extra == 'cov' + - matplotlib ; extra == 'cov' + - pytest-cov ; extra == 'cov' + - trio ; extra == 'cov' + - intersphinx-registry ; extra == 'docs' + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx-autodoc-typehints ; extra == 'docs' + - sphinx<8.2.0 ; extra == 'docs' + - sphinxcontrib-github-alt ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - trio ; extra == 'docs' + - pyqt5 ; extra == 'pyqt5' + - pyside6 ; extra == 'pyside6' + - flaky ; extra == 'test' + - ipyparallel ; extra == 'test' + - pre-commit ; extra == 'test' + - pytest-asyncio>=0.23.5 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest>=7.0,<10 ; extra == 'test' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/9f/df/db59624f4c71b39717c423409950ac3f2c8b2ce4b0aac843112c7fb3f721/ipython-8.38.0-py3-none-any.whl + name: ipython + version: 8.38.0 + sha256: 750162629d800ac65bb3b543a14e7a74b0e88063eac9b92124d4b2aa3f6d8e86 + requires_dist: + - colorama ; sys_platform == 'win32' + - decorator + - exceptiongroup ; python_full_version < '3.11' + - jedi>=0.16 + - matplotlib-inline + - pexpect>4.3 ; sys_platform != 'emscripten' and sys_platform != 'win32' + - prompt-toolkit>=3.0.41,<3.1.0 + - pygments>=2.4.0 + - stack-data + - traitlets>=5.13.0 + - typing-extensions>=4.6 ; python_full_version < '3.12' + - black ; extra == 'black' + - docrepr ; extra == 'doc' + - exceptiongroup ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - ipykernel ; extra == 'doc' + - ipython[test] ; extra == 'doc' + - matplotlib ; extra == 'doc' + - setuptools>=18.5 ; extra == 'doc' + - sphinx-rtd-theme ; extra == 'doc' + - sphinx>=1.3 ; extra == 'doc' + - sphinxcontrib-jquery ; extra == 'doc' + - tomli ; python_full_version < '3.11' and extra == 'doc' + - typing-extensions ; extra == 'doc' + - ipykernel ; extra == 'kernel' + - nbconvert ; extra == 'nbconvert' + - nbformat ; extra == 'nbformat' + - ipywidgets ; extra == 'notebook' + - notebook ; extra == 'notebook' + - ipyparallel ; extra == 'parallel' + - qtconsole ; extra == 'qtconsole' + - pytest ; extra == 'test' + - pytest-asyncio<0.22 ; extra == 'test' + - testpath ; extra == 'test' + - pickleshare ; extra == 'test' + - packaging ; extra == 'test' + - ipython[test] ; extra == 'test-extra' + - curio ; extra == 'test-extra' + - jupyter-ai ; extra == 'test-extra' + - matplotlib!=3.2.0 ; extra == 'test-extra' + - nbformat ; extra == 'test-extra' + - numpy>=1.23 ; extra == 'test-extra' + - pandas ; extra == 'test-extra' + - trio ; extra == 'test-extra' + - matplotlib ; extra == 'matplotlib' + - ipython[black,doc,kernel,matplotlib,nbconvert,nbformat,notebook,parallel,qtconsole] ; extra == 'all' + - ipython[test,test-extra] ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3d/aa/898dec789a05731cd5a9f50605b7b44a72bd198fd0d4528e11fc610177cc/ipython-9.10.0-py3-none-any.whl + name: ipython + version: 9.10.0 + sha256: c6ab68cc23bba8c7e18e9b932797014cc61ea7fd6f19de180ab9ba73e65ee58d + requires_dist: + - colorama>=0.4.4 ; sys_platform == 'win32' + - decorator>=4.3.2 + - ipython-pygments-lexers>=1.0.0 + - jedi>=0.18.1 + - matplotlib-inline>=0.1.5 + - pexpect>4.3 ; sys_platform != 'emscripten' and sys_platform != 'win32' + - prompt-toolkit>=3.0.41,<3.1.0 + - pygments>=2.11.0 + - stack-data>=0.6.0 + - traitlets>=5.13.0 + - typing-extensions>=4.6 ; python_full_version < '3.12' + - black ; extra == 'black' + - docrepr ; extra == 'doc' + - exceptiongroup ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - ipykernel ; extra == 'doc' + - ipython[matplotlib,test] ; extra == 'doc' + - setuptools>=70.0 ; extra == 'doc' + - sphinx-toml==0.0.4 ; extra == 'doc' + - sphinx-rtd-theme>=0.1.8 ; extra == 'doc' + - sphinx>=8.0 ; extra == 'doc' + - typing-extensions ; extra == 'doc' + - pytest>=7.0.0 ; extra == 'test' + - pytest-asyncio>=1.0.0 ; extra == 'test' + - testpath>=0.2 ; extra == 'test' + - packaging>=20.1.0 ; extra == 'test' + - setuptools>=61.2 ; extra == 'test' + - ipython[test] ; extra == 'test-extra' + - curio ; extra == 'test-extra' + - jupyter-ai ; extra == 'test-extra' + - ipython[matplotlib] ; extra == 'test-extra' + - nbformat ; extra == 'test-extra' + - nbclient ; extra == 'test-extra' + - ipykernel>6.30 ; extra == 'test-extra' + - numpy>=1.27 ; extra == 'test-extra' + - pandas>2.1 ; extra == 'test-extra' + - trio>=0.1.0 ; extra == 'test-extra' + - matplotlib>3.9 ; extra == 'matplotlib' + - ipython[doc,matplotlib,terminal,test,test-extra] ; extra == 'all' + - argcomplete>=3.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/b2/90/45c72becc57158facc6a6404f663b77bbcea2519ca57f760e2879ae1315d/ipython-9.11.0-py3-none-any.whl + name: ipython + version: 9.11.0 + sha256: 6922d5bcf944c6e525a76a0a304451b60a2b6f875e86656d8bc2dfda5d710e19 + requires_dist: + - colorama>=0.4.4 ; sys_platform == 'win32' + - decorator>=5.1.0 + - ipython-pygments-lexers>=1.0.0 + - jedi>=0.18.2 + - matplotlib-inline>=0.1.6 + - pexpect>4.6 ; sys_platform != 'emscripten' and sys_platform != 'win32' + - prompt-toolkit>=3.0.41,<3.1.0 + - pygments>=2.14.0 + - stack-data>=0.6.0 + - traitlets>=5.13.0 + - black ; extra == 'black' + - docrepr ; extra == 'doc' + - exceptiongroup ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - ipykernel ; extra == 'doc' + - ipython[matplotlib,test] ; extra == 'doc' + - setuptools>=80.0 ; extra == 'doc' + - sphinx-toml==0.0.4 ; extra == 'doc' + - sphinx-rtd-theme>=0.1.8 ; extra == 'doc' + - sphinx>=8.0 ; extra == 'doc' + - typing-extensions ; extra == 'doc' + - pytest>=7.0.0 ; extra == 'test' + - pytest-asyncio>=1.0.0 ; extra == 'test' + - testpath>=0.2 ; extra == 'test' + - packaging>=23.0.0 ; extra == 'test' + - setuptools>=80.0 ; extra == 'test' + - ipython[test] ; extra == 'test-extra' + - curio ; extra == 'test-extra' + - jupyter-ai ; extra == 'test-extra' + - ipython[matplotlib] ; extra == 'test-extra' + - nbformat ; extra == 'test-extra' + - nbclient ; extra == 'test-extra' + - ipykernel>6.30 ; extra == 'test-extra' + - numpy>=2.0 ; extra == 'test-extra' + - pandas>2.1 ; extra == 'test-extra' + - trio>=0.22.0 ; extra == 'test-extra' + - matplotlib>3.9 ; extra == 'matplotlib' + - ipython[doc,matplotlib,terminal,test,test-extra] ; extra == 'all' + - argcomplete>=3.0 ; extra == 'all' + - types-decorator ; extra == 'all' + requires_python: '>=3.12' +- pypi: https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl + name: ipython-pygments-lexers + version: 1.1.1 + sha256: a9462224a505ade19a605f71f8fa63c2048833ce50abc86768a0d81d876dc81c + requires_dist: + - pygments + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl + name: ipywidgets + version: 8.1.8 + sha256: ecaca67aed704a338f88f67b1181b58f821ab5dc89c1f0f5ef99db43c1c2921e + requires_dist: + - comm>=0.1.3 + - ipython>=6.1.0 + - traitlets>=4.3.1 + - widgetsnbextension~=4.0.14 + - jupyterlab-widgets~=3.0.15 + - jsonschema ; extra == 'test' + - ipykernel ; extra == 'test' + - pytest>=3.6.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytz ; extra == 'test' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/7b/55/e5326141505c5d5e34c5e0935d2908a74e4561eca44108fbfb9c13d2911a/isoduration-20.11.0-py3-none-any.whl + name: isoduration + version: 20.11.0 + sha256: b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042 + requires_dist: + - arrow>=0.15.0 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl + name: jedi + version: 0.19.2 + sha256: a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9 + requires_dist: + - parso>=0.8.4,<0.9.0 + - jinja2==2.11.3 ; extra == 'docs' + - markupsafe==1.1.1 ; extra == 'docs' + - pygments==2.8.1 ; extra == 'docs' + - alabaster==0.7.12 ; extra == 'docs' + - babel==2.9.1 ; extra == 'docs' + - chardet==4.0.0 ; extra == 'docs' + - commonmark==0.8.1 ; extra == 'docs' + - docutils==0.17.1 ; extra == 'docs' + - future==0.18.2 ; extra == 'docs' + - idna==2.10 ; extra == 'docs' + - imagesize==1.2.0 ; extra == 'docs' + - mock==1.0.1 ; extra == 'docs' + - packaging==20.9 ; extra == 'docs' + - pyparsing==2.4.7 ; extra == 'docs' + - pytz==2021.1 ; extra == 'docs' + - readthedocs-sphinx-ext==2.1.4 ; extra == 'docs' + - recommonmark==0.5.0 ; extra == 'docs' + - requests==2.25.1 ; extra == 'docs' + - six==1.15.0 ; extra == 'docs' + - snowballstemmer==2.1.0 ; extra == 'docs' + - sphinx-rtd-theme==0.4.3 ; extra == 'docs' + - sphinx==1.8.5 ; extra == 'docs' + - sphinxcontrib-serializinghtml==1.1.4 ; extra == 'docs' + - sphinxcontrib-websupport==1.2.4 ; extra == 'docs' + - urllib3==1.26.4 ; extra == 'docs' + - flake8==5.0.4 ; extra == 'qa' + - mypy==0.971 ; extra == 'qa' + - types-setuptools==67.2.0.1 ; extra == 'qa' + - django ; extra == 'testing' + - attrs ; extra == 'testing' + - colorama ; extra == 'testing' + - docopt ; extra == 'testing' + - pytest<9.0.0 ; extra == 'testing' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl + name: jinja2 + version: 3.1.6 + sha256: 85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67 + requires_dist: + - markupsafe>=2.0 + - babel>=2.7 ; extra == 'i18n' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl + name: joblib + version: 1.5.3 + sha256: 5fc3c5039fc5ca8c0276333a188bbd59d6b7ab37fe6632daa76bc7f9ec18e713 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/d7/9e/038522f50ceb7e74f1f991bf1b699f24b0c2bbe7c390dd36ad69f4582258/json5-0.13.0-py3-none-any.whl + name: json5 + version: 0.13.0 + sha256: 9a08e1dd65f6a4d4c6fa82d216cf2477349ec2346a38fd70cc11d2557499fbcc + requires_python: '>=3.8.0' +- pypi: https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl + name: jsonpointer + version: 3.0.0 + sha256: 13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl + name: jsonschema + version: 4.26.0 + sha256: d489f15263b8d200f8387e64b4c3a75f06629559fb73deb8fdfb525f2dab50ce + requires_dist: + - attrs>=22.2.0 + - jsonschema-specifications>=2023.3.6 + - referencing>=0.28.4 + - rpds-py>=0.25.0 + - fqdn ; extra == 'format' + - idna ; extra == 'format' + - isoduration ; extra == 'format' + - jsonpointer>1.13 ; extra == 'format' + - rfc3339-validator ; extra == 'format' + - rfc3987 ; extra == 'format' + - uri-template ; extra == 'format' + - webcolors>=1.11 ; extra == 'format' + - fqdn ; extra == 'format-nongpl' + - idna ; extra == 'format-nongpl' + - isoduration ; extra == 'format-nongpl' + - jsonpointer>1.13 ; extra == 'format-nongpl' + - rfc3339-validator ; extra == 'format-nongpl' + - rfc3986-validator>0.1.0 ; extra == 'format-nongpl' + - rfc3987-syntax>=1.1.0 ; extra == 'format-nongpl' + - uri-template ; extra == 'format-nongpl' + - webcolors>=24.6.0 ; extra == 'format-nongpl' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl + name: jsonschema-specifications + version: 2025.9.1 + sha256: 98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe + requires_dist: + - referencing>=0.31.0 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/38/64/285f20a31679bf547b75602702f7800e74dbabae36ef324f716c02804753/jupyter-1.1.1-py2.py3-none-any.whl + name: jupyter + version: 1.1.1 + sha256: 7a59533c22af65439b24bbe60373a4e95af8f16ac65a6c00820ad378e3f7cc83 + requires_dist: + - notebook + - jupyter-console + - nbconvert + - ipykernel + - ipywidgets + - jupyterlab +- pypi: https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl + name: jupyter-client + version: 8.8.0 + sha256: f93a5b99c5e23a507b773d3a1136bd6e16c67883ccdbd9a829b0bbdb98cd7d7a + requires_dist: + - jupyter-core>=5.1 + - python-dateutil>=2.8.2 + - pyzmq>=25.0 + - tornado>=6.4.1 + - traitlets>=5.3 + - ipykernel ; extra == 'docs' + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx-autodoc-typehints ; extra == 'docs' + - sphinx>=4 ; extra == 'docs' + - sphinxcontrib-github-alt ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - orjson ; extra == 'orjson' + - anyio ; extra == 'test' + - coverage ; extra == 'test' + - ipykernel>=6.14 ; extra == 'test' + - msgpack ; extra == 'test' + - mypy ; platform_python_implementation != 'PyPy' and extra == 'test' + - paramiko ; sys_platform == 'win32' and extra == 'test' + - pre-commit ; extra == 'test' + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-jupyter[client]>=0.6.2 ; extra == 'test' + - pytest-timeout ; extra == 'test' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ca/77/71d78d58f15c22db16328a476426f7ac4a60d3a5a7ba3b9627ee2f7903d4/jupyter_console-6.6.3-py3-none-any.whl + name: jupyter-console + version: 6.6.3 + sha256: 309d33409fcc92ffdad25f0bcdf9a4a9daa61b6f341177570fdac03de5352485 + requires_dist: + - ipykernel>=6.14 + - ipython + - jupyter-client>=7.0.0 + - jupyter-core>=4.12,!=5.0.* + - prompt-toolkit>=3.0.30 + - pygments + - pyzmq>=17 + - traitlets>=5.4 + - flaky ; extra == 'test' + - pexpect ; extra == 'test' + - pytest ; extra == 'test' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl + name: jupyter-core + version: 5.9.1 + sha256: ebf87fdc6073d142e114c72c9e29a9d7ca03fad818c5d300ce2adc1fb0743407 + requires_dist: + - platformdirs>=2.5 + - traitlets>=5.3 + - intersphinx-registry ; extra == 'docs' + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx-autodoc-typehints ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - traitlets ; extra == 'docs' + - ipykernel ; extra == 'test' + - pre-commit ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest<9 ; extra == 'test' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e2/48/577993f1f99c552f18a0428731a755e06171f9902fa118c379eb7c04ea22/jupyter_events-0.12.0-py3-none-any.whl + name: jupyter-events + version: 0.12.0 + sha256: 6464b2fa5ad10451c3d35fabc75eab39556ae1e2853ad0c0cc31b656731a97fb + requires_dist: + - jsonschema[format-nongpl]>=4.18.0 + - packaging + - python-json-logger>=2.0.4 + - pyyaml>=5.3 + - referencing + - rfc3339-validator + - rfc3986-validator>=0.1.1 + - traitlets>=5.3 + - click ; extra == 'cli' + - rich ; extra == 'cli' + - jupyterlite-sphinx ; extra == 'docs' + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme>=0.16 ; extra == 'docs' + - sphinx>=8 ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - click ; extra == 'test' + - pre-commit ; extra == 'test' + - pytest-asyncio>=0.19.0 ; extra == 'test' + - pytest-console-scripts ; extra == 'test' + - pytest>=7.0 ; extra == 'test' + - rich ; extra == 'test' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl + name: jupyter-lsp + version: 2.3.0 + sha256: e914a3cb2addf48b1c7710914771aaf1819d46b2e5a79b0f917b5478ec93f34f + requires_dist: + - jupyter-server>=1.1.2 + - importlib-metadata>=4.8.3 ; python_full_version < '3.10' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl + name: jupyter-server + version: 2.17.0 + sha256: e8cb9c7db4251f51ed307e329b81b72ccf2056ff82d50524debde1ee1870e13f + requires_dist: + - anyio>=3.1.0 + - argon2-cffi>=21.1 + - jinja2>=3.0.3 + - jupyter-client>=7.4.4 + - jupyter-core>=4.12,!=5.0.* + - jupyter-events>=0.11.0 + - jupyter-server-terminals>=0.4.4 + - nbconvert>=6.4.4 + - nbformat>=5.3.0 + - overrides>=5.0 ; python_full_version < '3.12' + - packaging>=22.0 + - prometheus-client>=0.9 + - pywinpty>=2.0.1 ; os_name == 'nt' + - pyzmq>=24 + - send2trash>=1.8.2 + - terminado>=0.8.3 + - tornado>=6.2.0 + - traitlets>=5.6.0 + - websocket-client>=1.7 + - ipykernel ; extra == 'docs' + - jinja2 ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - myst-parser ; extra == 'docs' + - nbformat ; extra == 'docs' + - prometheus-client ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - send2trash ; extra == 'docs' + - sphinx-autodoc-typehints ; extra == 'docs' + - sphinxcontrib-github-alt ; extra == 'docs' + - sphinxcontrib-openapi>=0.8.0 ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - sphinxemoji ; extra == 'docs' + - tornado ; extra == 'docs' + - typing-extensions ; extra == 'docs' + - flaky ; extra == 'test' + - ipykernel ; extra == 'test' + - pre-commit ; extra == 'test' + - pytest-console-scripts ; extra == 'test' + - pytest-jupyter[server]>=0.7 ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest>=7.0,<9 ; extra == 'test' + - requests ; extra == 'test' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl + name: jupyter-server-terminals + version: 0.5.4 + sha256: 55be353fc74a80bc7f3b20e6be50a55a61cd525626f578dcb66a5708e2007d14 + requires_dist: + - pywinpty>=2.0.3 ; os_name == 'nt' + - terminado>=0.8.3 + - jinja2 ; extra == 'docs' + - jupyter-server ; extra == 'docs' + - mistune<4.0 ; extra == 'docs' + - myst-parser ; extra == 'docs' + - nbformat ; extra == 'docs' + - packaging ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinxcontrib-github-alt ; extra == 'docs' + - sphinxcontrib-openapi ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - sphinxemoji ; extra == 'docs' + - tornado ; extra == 'docs' + - jupyter-server>=2.0.0 ; extra == 'test' + - pytest-jupyter[server]>=0.5.3 ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest>=7.0 ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + name: jupyterlab + version: 4.5.5 + sha256: a35694a40a8e7f2e82f387472af24e61b22adcce87b5a8ab97a5d9c486202a6d + requires_dist: + - async-lru>=1.0.0 + - httpx>=0.25.0,<1 + - importlib-metadata>=4.8.3 ; python_full_version < '3.10' + - ipykernel>=6.5.0,!=6.30.0 + - jinja2>=3.0.3 + - jupyter-core + - jupyter-lsp>=2.0.0 + - jupyter-server>=2.4.0,<3 + - jupyterlab-server>=2.28.0,<3 + - notebook-shim>=0.2 + - packaging + - setuptools>=41.1.0 + - tomli>=1.2.2 ; python_full_version < '3.11' + - tornado>=6.2.0 + - traitlets + - build ; extra == 'dev' + - bump2version ; extra == 'dev' + - coverage ; extra == 'dev' + - hatch ; extra == 'dev' + - pre-commit ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - ruff==0.11.12 ; extra == 'dev' + - jsx-lexer ; extra == 'docs' + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme>=0.13.0 ; extra == 'docs' + - pytest ; extra == 'docs' + - pytest-check-links ; extra == 'docs' + - pytest-jupyter ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx>=1.8,<8.2.0 ; extra == 'docs' + - altair==6.0.0 ; extra == 'docs-screenshots' + - ipython==8.16.1 ; extra == 'docs-screenshots' + - ipywidgets==8.1.5 ; extra == 'docs-screenshots' + - jupyterlab-geojson==3.4.0 ; extra == 'docs-screenshots' + - jupyterlab-language-pack-zh-cn==4.3.post1 ; extra == 'docs-screenshots' + - matplotlib==3.10.0 ; extra == 'docs-screenshots' + - nbconvert>=7.0.0 ; extra == 'docs-screenshots' + - pandas==2.2.3 ; extra == 'docs-screenshots' + - scipy==1.15.1 ; extra == 'docs-screenshots' + - coverage ; extra == 'test' + - pytest-check-links>=0.7 ; extra == 'test' + - pytest-console-scripts ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-jupyter>=0.5.3 ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-tornasync ; extra == 'test' + - pytest>=7.0 ; extra == 'test' + - requests ; extra == 'test' + - requests-cache ; extra == 'test' + - virtualenv ; extra == 'test' + - copier>=9,<10 ; extra == 'upgrade-extension' + - jinja2-time<0.3 ; extra == 'upgrade-extension' + - pydantic<3.0 ; extra == 'upgrade-extension' + - pyyaml-include<3.0 ; extra == 'upgrade-extension' + - tomli-w<2.0 ; extra == 'upgrade-extension' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl + name: jupyterlab-pygments + version: 0.3.0 + sha256: 841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl + name: jupyterlab-server + version: 2.28.0 + sha256: e4355b148fdcf34d312bbbc80f22467d6d20460e8b8736bf235577dd18506968 + requires_dist: + - babel>=2.10 + - importlib-metadata>=4.8.3 ; python_full_version < '3.10' + - jinja2>=3.0.3 + - json5>=0.9.0 + - jsonschema>=4.18.0 + - jupyter-server>=1.21,<3 + - packaging>=21.3 + - requests>=2.31 + - autodoc-traits ; extra == 'docs' + - jinja2<3.2.0 ; extra == 'docs' + - mistune<4 ; extra == 'docs' + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinxcontrib-openapi>0.8 ; extra == 'docs' + - openapi-core~=0.18.0 ; extra == 'openapi' + - ruamel-yaml ; extra == 'openapi' + - hatch ; extra == 'test' + - ipykernel ; extra == 'test' + - openapi-core~=0.18.0 ; extra == 'test' + - openapi-spec-validator>=0.6.0,<0.8.0 ; extra == 'test' + - pytest-console-scripts ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-jupyter[server]>=0.6.2 ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest>=7.0,<8 ; extra == 'test' + - requests-mock ; extra == 'test' + - ruamel-yaml ; extra == 'test' + - sphinxcontrib-spelling ; extra == 'test' + - strict-rfc3339 ; extra == 'test' + - werkzeug ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl + name: jupyterlab-widgets + version: 3.0.16 + sha256: 45fa36d9c6422cf2559198e4db481aa243c7a32d9926b500781c830c80f7ecf8 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/0a/aa/510dc933d87767584abfe03efa445889996c70c2990f6f87c3ebaa0a18c5/kiwisolver-1.5.0-cp311-cp311-macosx_11_0_arm64.whl + name: kiwisolver + version: 1.5.0 + sha256: 0df54df7e686afa55e6f21fb86195224a6d9beb71d637e8d7920c95cf0f89aac + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/11/60/37b4047a2af0cf5ef6d8b4b26e91829ae6fc6a2d1f74524bcb0e7cd28a32/kiwisolver-1.5.0-cp311-cp311-macosx_10_9_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: 3c4923e404d6bcd91b6779c009542e5647fef32e4a5d75e115e3bbac6f2335eb + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/2b/0a/7b98e1e119878a27ba8618ca1e18b14f992ff1eda40f47bccccf4de44121/kiwisolver-1.5.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: 332b4f0145c30b5f5ad9374881133e5aa64320428a57c2c2b61e9d891a51c2f3 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/49/b2/97980f3ad4fae37dd7fe31626e2bf75fbf8bdf5d303950ec1fab39a12da8/kiwisolver-1.5.0-cp314-cp314-macosx_11_0_arm64.whl + name: kiwisolver + version: 1.5.0 + sha256: 0cbe94b69b819209a62cb27bdfa5dc2a8977d8de2f89dfd97ba4f53ed3af754e + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/75/2b/3f641dfcbe72e222175d626bacf2f72c3b34312afec949dd1c50afa400f5/kiwisolver-1.5.0-cp310-cp310-win_amd64.whl + name: kiwisolver + version: 1.5.0 + sha256: 94eff26096eb5395136634622515b234ecb6c9979824c1f5004c6e3c3c85ccd2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/80/46/bddc13df6c2a40741e0cc7865bb1c9ed4796b6760bd04ce5fae3928ef917/kiwisolver-1.5.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: 2517e24d7315eb51c10664cdb865195df38ab74456c677df67bb47f12d088a27 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/84/eb/8476a0818850c563ff343ea7c9c05dcdcbd689a38e01aa31657df01f91fa/kiwisolver-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: cc0b66c1eec9021353a4b4483afb12dfd50e3669ffbb9152d6842eb34c7e29fd + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/99/9f/795fedf35634f746151ca8839d05681ceb6287fbed6cc1c9bf235f7887c2/kiwisolver-1.5.0-cp312-cp312-macosx_11_0_arm64.whl + name: kiwisolver + version: 1.5.0 + sha256: ed3a984b31da7481b103f68776f7128a89ef26ed40f4dc41a2223cda7fb24819 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a3/36/4e551e8aa55c9188bca9abb5096805edbf7431072b76e2298e34fd3a3008/kiwisolver-1.5.0-cp314-cp314-win_amd64.whl + name: kiwisolver + version: 1.5.0 + sha256: d76e2d8c75051d58177e762164d2e9ab92886534e3a12e795f103524f221dd8e + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a8/3a/d0a972b34e1c63e2409413104216cd1caa02c5a37cb668d1687d466c1c45/kiwisolver-1.5.0-cp313-cp313-macosx_11_0_arm64.whl + name: kiwisolver + version: 1.5.0 + sha256: dda366d548e89a90d88a86c692377d18d8bd64b39c1fb2b92cb31370e2896bbd + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ad/cf/0348374369ca588f8fe9c338fae49fa4e16eeb10ffb3d012f23a54578a9e/kiwisolver-1.5.0-cp312-cp312-win_amd64.whl + name: kiwisolver + version: 1.5.0 + sha256: f18c2d9782259a6dc132fdc7a63c168cbc74b35284b6d75c673958982a378384 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/be/6c/28f17390b62b8f2f520e2915095b3c94d88681ecf0041e75389d9667f202/kiwisolver-1.5.0-cp311-cp311-win_amd64.whl + name: kiwisolver + version: 1.5.0 + sha256: beb7f344487cdcb9e1efe4b7a29681b74d34c08f0043a327a74da852a6749e7b + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/be/8a/be60e3bbcf513cc5a50f4a3e88e1dcecebb79c1ad607a7222877becaa101/kiwisolver-1.5.0-cp313-cp313-win_amd64.whl + name: kiwisolver + version: 1.5.0 + sha256: 0bf3acf1419fa93064a4c2189ac0b58e3be7872bf6ee6177b0d4c63dc4cea276 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/bf/d9/405320f8077e8e1c5c4bd6adc45e1e6edf6d727b6da7f2e2533cf58bff71/kiwisolver-1.5.0-cp312-cp312-macosx_10_13_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: 72ec46b7eba5b395e0a7b63025490d3214c11013f4aacb4f5e8d6c3041829588 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c2/a7/78da680eadd06ff35edef6ef68a1ad273bad3e2a0936c9a885103230aece/kiwisolver-1.5.0-cp314-cp314-macosx_10_15_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: 1d49a49ac4cbfb7c1375301cd1ec90169dfeae55ff84710d782260ce77a75a02 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c4/13/680c54afe3e65767bed7ec1a15571e1a2f1257128733851ade24abcefbcc/kiwisolver-1.5.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: bb5136fb5352d3f422df33f0c879a1b0c204004324150cc3b5e3c4f310c9049f + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ce/48/adbb40df306f587054a348831220812b9b1d787aff714cfbc8556e38fccd/kiwisolver-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: c0e1403fd7c26d77c1f03e096dc58a5c726503fa0db0456678b8668f76f521e3 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e7/f9/b06c934a6aa8bc91f566bd2a214fd04c30506c2d9e2b6b171953216a65b6/kiwisolver-1.5.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: 80aa065ffd378ff784822a6d7c3212f2d5f5e9c3589614b5c228b311fd3063ac + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f1/0e/ba4ae25d03722f64de8b2c13e80d82ab537a06b30fc7065183c6439357e3/kiwisolver-1.5.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl + name: kiwisolver + version: 1.5.0 + sha256: 62f59da443c4f4849f73a51a193b1d9d258dcad0c41bc4d1b8fb2bcc04bfeb22 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f3/c4/f9c8a6b4c21aed4198566e45923512986d6cef530e7263b3a5f823546561/kiwisolver-1.5.0-cp310-cp310-macosx_11_0_arm64.whl + name: kiwisolver + version: 1.5.0 + sha256: 86e0287879f75621ae85197b0877ed2f8b7aa57b511c7331dce2eb6f4de7d476 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/82/3d/14ce75ef66813643812f3093ab17e46d3a206942ce7376d31ec2d36229e7/lark-1.3.1-py3-none-any.whl + name: lark + version: 1.3.1 + sha256: c629b661023a014c37da873b4ff58a817398d12635d3bbb2c5a03be7fe5d1e12 + requires_dist: + - regex ; extra == 'regex' + - js2py ; extra == 'nearley' + - atomicwrites ; extra == 'atomic-cache' + - interegular>=0.3.1,<0.4.0 ; extra == 'interegular' + requires_python: '>=3.8' +- conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda + sha256: 565941ac1f8b0d2f2e8f02827cbca648f4d18cd461afc31f15604cd291b5c5f3 + md5: 12bd9a3f089ee6c9266a37dab82afabd + depends: + - __glibc >=2.17,<3.0.a0 + - zstd >=1.5.7,<1.6.0a0 + constrains: + - binutils_impl_linux-64 2.45.1 + license: GPL-3.0-only + license_family: GPL + purls: [] + size: 725507 + timestamp: 1770267139900 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda + sha256: d78f1d3bea8c031d2f032b760f36676d87929b18146351c4464c66b0869df3f5 + md5: e7f7ce06ec24cfcfb9e36d28cf82ba57 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + constrains: + - expat 2.7.4.* + license: MIT + license_family: MIT + purls: [] + size: 76798 + timestamp: 1771259418166 +- conda: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.7.4-h991f03e_0.conda + sha256: 8d9d79b2de7d6f335692391f5281607221bf5d040e6724dad4c4d77cd603ce43 + md5: a684eb8a19b2aa68fde0267df172a1e3 + depends: + - __osx >=10.13 + constrains: + - expat 2.7.4.* + license: MIT + license_family: MIT + purls: [] + size: 74578 + timestamp: 1771260142624 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda + sha256: 03887d8080d6a8fe02d75b80929271b39697ecca7628f0657d7afaea87761edf + md5: a92e310ae8dfc206ff449f362fc4217f + depends: + - __osx >=11.0 + constrains: + - expat 2.7.4.* + license: MIT + license_family: MIT + purls: [] + size: 68199 + timestamp: 1771260020767 +- conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.7.4-hac47afa_0.conda + sha256: b31f6fb629c4e17885aaf2082fb30384156d16b48b264e454de4a06a313b533d + md5: 1c1ced969021592407f16ada4573586d + depends: + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + constrains: + - expat 2.7.4.* + license: MIT + license_family: MIT + purls: [] + size: 70323 + timestamp: 1771259521393 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda + sha256: 31f19b6a88ce40ebc0d5a992c131f57d919f73c0b92cd1617a5bec83f6e961e6 + md5: a360c33a5abe61c07959e449fa1453eb + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + license: MIT + license_family: MIT + purls: [] + size: 58592 + timestamp: 1769456073053 +- conda: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.5.2-hd1f9c09_0.conda + sha256: 951958d1792238006fdc6fce7f71f1b559534743b26cc1333497d46e5903a2d6 + md5: 66a0dc7464927d0853b590b6f53ba3ea + depends: + - __osx >=10.13 + license: MIT + license_family: MIT + purls: [] + size: 53583 + timestamp: 1769456300951 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda + sha256: 6686a26466a527585e6a75cc2a242bf4a3d97d6d6c86424a441677917f28bec7 + md5: 43c04d9cb46ef176bb2a4c77e324d599 + depends: + - __osx >=11.0 + license: MIT + license_family: MIT + purls: [] + size: 40979 + timestamp: 1769456747661 +- conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda + sha256: 59d01f2dfa8b77491b5888a5ab88ff4e1574c9359f7e229da254cdfe27ddc190 + md5: 720b39f5ec0610457b725eb3f396219a + depends: + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + license: MIT + license_family: MIT + purls: [] + size: 45831 + timestamp: 1769456418774 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda + sha256: faf7d2017b4d718951e3a59d081eb09759152f93038479b768e3d612688f83f5 + md5: 0aa00f03f9e39fb9876085dee11a85d4 + depends: + - __glibc >=2.17,<3.0.a0 + - _openmp_mutex >=4.5 + constrains: + - libgcc-ng ==15.2.0=*_18 + - libgomp 15.2.0 he0feb66_18 + license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL + purls: [] + size: 1041788 + timestamp: 1771378212382 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_18.conda + sha256: e318a711400f536c81123e753d4c797a821021fb38970cebfb3f454126016893 + md5: d5e96b1ed75ca01906b3d2469b4ce493 + depends: + - libgcc 15.2.0 he0feb66_18 + license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL + purls: [] + size: 27526 + timestamp: 1771378224552 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda + sha256: 21337ab58e5e0649d869ab168d4e609b033509de22521de1bfed0c031bfc5110 + md5: 239c5e9546c38a1e884d69effcf4c882 + depends: + - __glibc >=2.17,<3.0.a0 + license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL + purls: [] + size: 603262 + timestamp: 1771378117851 +- conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda + sha256: 755c55ebab181d678c12e49cced893598f2bab22d582fbbf4d8b83c18be207eb + md5: c7c83eecbb72d88b940c249af56c8b17 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + constrains: + - xz 5.8.2.* + license: 0BSD + purls: [] + size: 113207 + timestamp: 1768752626120 +- conda: https://conda.anaconda.org/conda-forge/osx-64/liblzma-5.8.2-h11316ed_0.conda + sha256: 7ab3c98abd3b5d5ec72faa8d9f5d4b50dcee4970ed05339bc381861199dabb41 + md5: 688a0c3d57fa118b9c97bf7e471ab46c + depends: + - __osx >=10.13 + constrains: + - xz 5.8.2.* + license: 0BSD + purls: [] + size: 105482 + timestamp: 1768753411348 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda + sha256: 7bfc7ffb2d6a9629357a70d4eadeadb6f88fa26ebc28f606b1c1e5e5ed99dc7e + md5: 009f0d956d7bfb00de86901d16e486c7 + depends: + - __osx >=11.0 + constrains: + - xz 5.8.2.* + license: 0BSD + purls: [] + size: 92242 + timestamp: 1768752982486 +- conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.2-hfd05255_0.conda + sha256: f25bf293f550c8ed2e0c7145eb404324611cfccff37660869d97abf526eb957c + md5: ba0bfd4c3cf73f299ffe46ff0eaeb8e3 + depends: + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + constrains: + - xz 5.8.2.* + license: 0BSD + purls: [] + size: 106169 + timestamp: 1768752763559 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_1.conda + sha256: fe171ed5cf5959993d43ff72de7596e8ac2853e9021dec0344e583734f1e0843 + md5: 2c21e66f50753a083cbe6b80f38268fa + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + license: BSD-2-Clause + license_family: BSD + purls: [] + size: 92400 + timestamp: 1769482286018 +- conda: https://conda.anaconda.org/conda-forge/osx-64/libmpdec-4.0.0-hf3981d6_1.conda + sha256: 1096c740109386607938ab9f09a7e9bca06d86770a284777586d6c378b8fb3fd + md5: ec88ba8a245855935b871a7324373105 + depends: + - __osx >=10.13 + license: BSD-2-Clause + license_family: BSD + purls: [] + size: 79899 + timestamp: 1769482558610 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libmpdec-4.0.0-h84a0fba_1.conda + sha256: 1089c7f15d5b62c622625ec6700732ece83be8b705da8c6607f4dabb0c4bd6d2 + md5: 57c4be259f5e0b99a5983799a228ae55 + depends: + - __osx >=11.0 + license: BSD-2-Clause + license_family: BSD + purls: [] + size: 73690 + timestamp: 1769482560514 +- conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda + sha256: 40dcd0b9522a6e0af72a9db0ced619176e7cfdb114855c7a64f278e73f8a7514 + md5: e4a9fc2bba3b022dad998c78856afe47 + depends: + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + license: BSD-2-Clause + license_family: BSD + purls: [] + size: 89411 + timestamp: 1769482314283 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda + sha256: 927fe72b054277cde6cb82597d0fcf6baf127dcbce2e0a9d8925a68f1265eef5 + md5: d864d34357c3b65a4b731f78c0801dc4 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=13 + license: LGPL-2.1-only + license_family: GPL + purls: [] + size: 33731 + timestamp: 1750274110928 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda + sha256: d716847b7deca293d2e49ed1c8ab9e4b9e04b9d780aea49a97c26925b28a7993 + md5: fd893f6a3002a635b5e50ceb9dd2c0f4 + depends: + - __glibc >=2.17,<3.0.a0 + - icu >=78.2,<79.0a0 + - libgcc >=14 + - libzlib >=1.3.1,<2.0a0 + license: blessing + purls: [] + size: 951405 + timestamp: 1772818874251 +- conda: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.52.0-h77d7759_0.conda + sha256: f500d1cd50cfcd288d02b8fc3c3b7ecf8de6fec7b86e57ea058def02908e4231 + md5: d553eb96758e038b04027b30fe314b2d + depends: + - __osx >=11.0 + - libzlib >=1.3.1,<2.0a0 + license: blessing + purls: [] + size: 996526 + timestamp: 1772819669038 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.52.0-h1ae2325_0.conda + sha256: beb0fd5594d6d7c7cd42c992b6bb4d66cbb39d6c94a8234f15956da99a04306c + md5: f6233a3fddc35a2ec9f617f79d6f3d71 + depends: + - __osx >=11.0 + - icu >=78.2,<79.0a0 + - libzlib >=1.3.1,<2.0a0 + license: blessing + purls: [] + size: 918420 + timestamp: 1772819478684 +- conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.52.0-hf5d6505_0.conda + sha256: 5fccf1e4e4062f8b9a554abf4f9735a98e70f82e2865d0bfdb47b9de94887583 + md5: 8830689d537fda55f990620680934bb1 + depends: + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + license: blessing + purls: [] + size: 1297302 + timestamp: 1772818899033 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda + sha256: 78668020064fdaa27e9ab65cd2997e2c837b564ab26ce3bf0e58a2ce1a525c6e + md5: 1b08cd684f34175e4514474793d44bcb + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc 15.2.0 he0feb66_18 + constrains: + - libstdcxx-ng ==15.2.0=*_18 + license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL + purls: [] + size: 5852330 + timestamp: 1771378262446 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda + sha256: 1a7539cfa7df00714e8943e18de0b06cceef6778e420a5ee3a2a145773758aee + md5: db409b7c1720428638e7c0d509d3e1b5 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 40311 + timestamp: 1766271528534 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libxcrypt-4.4.36-hd590300_1.conda + sha256: 6ae68e0b86423ef188196fff6207ed0c8195dd84273cb5623b85aa08033a410c + md5: 5aa797f8787fe7a17d1b0821485b5adc + depends: + - libgcc-ng >=12 + license: LGPL-2.1-or-later + purls: [] + size: 100393 + timestamp: 1702724383534 +- conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda + sha256: d4bfe88d7cb447768e31650f06257995601f89076080e76df55e3112d4e47dc4 + md5: edb0dca6bc32e4f4789199455a1dbeb8 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=13 + constrains: + - zlib 1.3.1 *_2 + license: Zlib + license_family: Other + purls: [] + size: 60963 + timestamp: 1727963148474 +- conda: https://conda.anaconda.org/conda-forge/osx-64/libzlib-1.3.1-hd23fc13_2.conda + sha256: 8412f96504fc5993a63edf1e211d042a1fd5b1d51dedec755d2058948fcced09 + md5: 003a54a4e32b02f7355b50a837e699da + depends: + - __osx >=10.13 + constrains: + - zlib 1.3.1 *_2 + license: Zlib + license_family: Other + purls: [] + size: 57133 + timestamp: 1727963183990 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.3.1-h8359307_2.conda + sha256: ce34669eadaba351cd54910743e6a2261b67009624dbc7daeeafdef93616711b + md5: 369964e85dc26bfe78f41399b366c435 + depends: + - __osx >=11.0 + constrains: + - zlib 1.3.1 *_2 + license: Zlib + license_family: Other + purls: [] + size: 46438 + timestamp: 1727963202283 +- conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda + sha256: ba945c6493449bed0e6e29883c4943817f7c79cbff52b83360f7b341277c6402 + md5: 41fbfac52c601159df6c01f875de31b9 + depends: + - ucrt >=10.0.20348.0 + - vc >=14.2,<15 + - vc14_runtime >=14.29.30139 + constrains: + - zlib 1.3.1 *_2 + license: Zlib + license_family: Other + purls: [] + size: 55476 + timestamp: 1727963768015 +- conda: https://conda.anaconda.org/conda-forge/osx-64/llvm-openmp-22.1.0-h0d3cbff_0.conda + sha256: b63df4e592b3362e7d13e3d1cf8e55ce932ff4f17611c8514b5d36368ec2094c + md5: 3921780bab286f2439ba483c22b90345 + depends: + - __osx >=11.0 + constrains: + - openmp 22.1.0|22.1.0.* + - intel-openmp <0.0a0 + license: Apache-2.0 WITH LLVM-exception + license_family: APACHE + purls: [] + size: 311938 + timestamp: 1772024731611 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-22.1.0-hc7d1edf_0.conda + sha256: 0daeedb3872ad0fdd6f0d7e7165c63488e8a315d7057907434145fba0c1e7b3d + md5: ff0820b5588b20be3b858552ecf8ffae + depends: + - __osx >=11.0 + constrains: + - openmp 22.1.0|22.1.0.* + - intel-openmp <0.0a0 + license: Apache-2.0 WITH LLVM-exception + license_family: APACHE + purls: [] + size: 285558 + timestamp: 1772028716784 +- pypi: https://files.pythonhosted.org/packages/03/15/d4a377b385ab693ce97b472fe0c77c2b16ec79590e688b3ccc71fba19884/lxml-6.0.2-cp314-cp314-macosx_10_13_universal2.whl + name: lxml + version: 6.0.2 + sha256: b0c732aa23de8f8aec23f4b580d1e52905ef468afb4abeafd3fec77042abb6fe + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/12/64/27bcd07ae17ff5e5536e8d88f4c7d581b48963817a13de11f3ac3329bfa2/lxml-6.0.2-cp310-cp310-macosx_10_9_x86_64.whl + name: lxml + version: 6.0.2 + sha256: 5d444858b9f07cefff6455b983aea9a67f7462ba1f6cbe4a21e8bf6791bf2153 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/20/cf/cab09478699b003857ed6ebfe95e9fb9fa3d3c25f1353b905c9b73cfb624/lxml-6.0.2-cp310-cp310-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: lxml + version: 6.0.2 + sha256: a8ffaeec5dfea5881d4c9d8913a32d10cfe3923495386106e4a24d45300ef79c + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/28/66/1ced58f12e804644426b85d0bb8a4478ca77bc1761455da310505f1a3526/lxml-6.0.2-cp311-cp311-macosx_10_9_x86_64.whl + name: lxml + version: 6.0.2 + sha256: 3b1675e096e17c6fe9c0e8c81434f5736c0739ff9ac6123c87c2d452f48fc938 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/29/9c/47293c58cc91769130fbf85531280e8cc7868f7fbb6d92f4670071b9cb3e/lxml-6.0.2-cp314-cp314-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: lxml + version: 6.0.2 + sha256: 98a5e1660dc7de2200b00d53fa00bcd3c35a3608c305d45a7bbcaf29fa16e83d + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/37/6f/9aae1008083bb501ef63284220ce81638332f9ccbfa53765b2b7502203cf/lxml-6.0.2-cp312-cp312-macosx_10_13_x86_64.whl + name: lxml + version: 6.0.2 + sha256: e8113639f3296706fbac34a30813929e29247718e88173ad849f57ca59754924 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/53/fd/4e8f0540608977aea078bf6d79f128e0e2c2bba8af1acf775c30baa70460/lxml-6.0.2-cp313-cp313-macosx_10_13_universal2.whl + name: lxml + version: 6.0.2 + sha256: 9b33d21594afab46f37ae58dfadd06636f154923c4e8a4d754b0127554eb2e77 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/5d/f4/2a94a3d3dfd6c6b433501b8d470a1960a20ecce93245cf2db1706adf6c19/lxml-6.0.2-cp313-cp313-macosx_10_13_x86_64.whl + name: lxml + version: 6.0.2 + sha256: 6c8963287d7a4c5c9a432ff487c52e9c5618667179c18a204bdedb27310f022f + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/77/d5/becbe1e2569b474a23f0c672ead8a29ac50b2dc1d5b9de184831bda8d14c/lxml-6.0.2-cp311-cp311-macosx_10_9_universal2.whl + name: lxml + version: 6.0.2 + sha256: 13e35cbc684aadf05d8711a5d1b5857c92e5e580efa9a0d2be197199c8def607 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/b8/89/ea8f91594bc5dbb879734d35a6f2b0ad50605d7fb419de2b63d4211765cc/lxml-6.0.2-cp311-cp311-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: lxml + version: 6.0.2 + sha256: 7d2de809c2ee3b888b59f995625385f74629707c9355e0ff856445cdcae682b7 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/c6/d1/232b3309a02d60f11e71857778bfcd4acbdb86c07db8260caf7d008b08f8/lxml-6.0.2-cp312-cp312-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: lxml + version: 6.0.2 + sha256: 90a345bbeaf9d0587a3aaffb7006aa39ccb6ff0e96a57286c0cb2fd1520ea192 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/c8/e8/c128e37589463668794d503afaeb003987373c5f94d667124ffd8078bbd9/lxml-6.0.2-cp314-cp314-macosx_10_13_x86_64.whl + name: lxml + version: 6.0.2 + sha256: 4468e3b83e10e0317a89a33d28f7aeba1caa4d1a6fd457d115dd4ffe90c5931d + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/d0/34/9e591954939276bb679b73773836c6684c22e56d05980e31d52a9a8deb18/lxml-6.0.2-cp313-cp313-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: lxml + version: 6.0.2 + sha256: ef9266d2aa545d7374938fb5c484531ef5a2ec7f2d573e62f8ce722c735685fd + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/d1/70/bd42491f0634aad41bdfc1e46f5cff98825fb6185688dc82baa35d509f1a/lxml-6.0.2-cp310-cp310-win_amd64.whl + name: lxml + version: 6.0.2 + sha256: dacf3c64ef3f7440e3167aa4b49aa9e0fb99e0aa4f9ff03795640bf94531bcb0 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/db/8a/f8192a08237ef2fb1b19733f709db88a4c43bc8ab8357f01cb41a27e7f6a/lxml-6.0.2-cp310-cp310-macosx_10_9_universal2.whl + name: lxml + version: 6.0.2 + sha256: e77dd455b9a16bbd2a5036a63ddbd479c19572af81b624e79ef422f929eef388 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/e2/7d/ca6fb13349b473d5732fb0ee3eec8f6c80fc0688e76b7d79c1008481bf1f/lxml-6.0.2-cp311-cp311-win_amd64.whl + name: lxml + version: 6.0.2 + sha256: e5867f2651016a3afd8dd2c8238baa66f1e2802f44bc17e236f547ace6647078 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/e3/e0/c96cf13eccd20c9421ba910304dae0f619724dcf1702864fd59dd386404d/lxml-6.0.2-cp314-cp314-win_amd64.whl + name: lxml + version: 6.0.2 + sha256: fa25afbadead523f7001caf0c2382afd272c315a033a7b06336da2637d92d6ed + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/f3/c8/8ff2bc6b920c84355146cd1ab7d181bc543b89241cfb1ebee824a7c81457/lxml-6.0.2-cp312-cp312-macosx_10_13_universal2.whl + name: lxml + version: 6.0.2 + sha256: a59f5448ba2ceccd06995c95ea59a7674a10de0810f2ce90c9006f3cbc044456 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/f7/d7/0cdfb6c3e30893463fb3d1e52bc5f5f99684a03c29a0b6b605cfae879cd5/lxml-6.0.2-cp312-cp312-win_amd64.whl + name: lxml + version: 6.0.2 + sha256: 72c87e5ee4e58a8354fb9c7c84cbf95a1c8236c127a5d1b7683f04bed8361e1f + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/fe/0a/4643ccc6bb8b143e9f9640aa54e38255f9d3b45feb2cbe7ae2ca47e8782e/lxml-6.0.2-cp313-cp313-win_amd64.whl + name: lxml + version: 6.0.2 + sha256: b30d46379644fbfc3ab81f8f82ae4de55179414651f110a1514f0b1f8f6cb2d7 + requires_dist: + - cssselect>=0.7 ; extra == 'cssselect' + - html5lib ; extra == 'html5' + - beautifulsoup4 ; extra == 'htmlsoup' + - lxml-html-clean ; extra == 'html-clean' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/05/73/c4abe620b841b6b791f2edc248f556900667a5a1cf023a6646967ae98335/markupsafe-3.0.3-cp313-cp313-win_amd64.whl + name: markupsafe + version: 3.0.3 + sha256: 9a1abfdc021a164803f4d485104931fb8f8c1efd55bc6b748d2f5774e78b62c5 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/08/db/fefacb2136439fc8dd20e797950e749aa1f4997ed584c62cfb8ef7c2be0e/markupsafe-3.0.3-cp311-cp311-macosx_10_9_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: 1cc7ea17a6824959616c525620e387f6dd30fec8cb44f649e31712db02123dad + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/28/52/182836104b33b444e400b14f797212f720cbc9ed6ba34c800639d154e821/markupsafe-3.0.3-cp314-cp314-win_amd64.whl + name: markupsafe + version: 3.0.3 + sha256: bdc919ead48f234740ad807933cdf545180bfbe9342c2bb451556db2ed958581 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/30/ac/0273f6fcb5f42e314c6d8cd99effae6a5354604d461b8d392b5ec9530a54/markupsafe-3.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: 0bf2a864d67e76e5c9a34dc26ec616a66b9888e25e7b9460e1c76d3293bd9dbf + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/33/8a/8e42d4838cd89b7dde187011e97fe6c3af66d8c044997d2183fbd6d31352/markupsafe-3.0.3-cp314-cp314-macosx_10_13_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: eaa9599de571d72e2daf60164784109f19978b327a3910d3e9de8c97b5b70cfe + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/38/2f/907b9c7bbba283e68f20259574b13d005c121a0fa4c175f9bed27c4597ff/markupsafe-3.0.3-cp313-cp313-macosx_10_13_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: e1cf1972137e83c5d4c136c43ced9ac51d0e124706ee1c8aa8532c1287fa8795 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/3c/2e/8d0c2ab90a8c1d9a24f0399058ab8519a3279d1bd4289511d74e909f060e/markupsafe-3.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: d6dd0be5b5b189d31db7cda48b91d7e0a9795f31430b7f271219ab30f1d3ac9d + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/41/3c/a36c2450754618e62008bf7435ccb0f88053e07592e6028a34776213d877/markupsafe-3.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: 457a69a9577064c05a97c41f4e65148652db078a3a509039e64d3467b9e7ef97 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/5a/72/147da192e38635ada20e0a2e1a51cf8823d2119ce8883f7053879c2199b5/markupsafe-3.0.3-cp312-cp312-macosx_10_13_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: d53197da72cc091b024dd97249dfc7794d6a56530370992a5e1a08983ad9230e + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/83/8a/4414c03d3f891739326e1783338e48fb49781cc915b2e0ee052aa490d586/markupsafe-3.0.3-cp311-cp311-win_amd64.whl + name: markupsafe + version: 3.0.3 + sha256: de8a88e63464af587c950061a5e6a67d3632e36df62b986892331d4620a35c01 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/98/1b/fbd8eed11021cabd9226c37342fa6ca4e8a98d8188a8d9b66740494960e4/markupsafe-3.0.3-cp310-cp310-macosx_11_0_arm64.whl + name: markupsafe + version: 3.0.3 + sha256: e1c1493fb6e50ab01d20a22826e57520f1284df32f2d8601fdd90b6304601419 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/9a/81/7e4e08678a1f98521201c3079f77db69fb552acd56067661f8c2f534a718/markupsafe-3.0.3-cp312-cp312-macosx_11_0_arm64.whl + name: markupsafe + version: 3.0.3 + sha256: 1872df69a4de6aead3491198eaf13810b565bdbeec3ae2dc8780f14458ec73ce + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/9c/d9/5f7756922cdd676869eca1c4e3c0cd0df60ed30199ffd775e319089cb3ed/markupsafe-3.0.3-cp313-cp313-macosx_11_0_arm64.whl + name: markupsafe + version: 3.0.3 + sha256: 116bb52f642a37c115f517494ea5feb03889e04df47eeff5b130b1808ce7c219 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/a9/21/9b05698b46f218fc0e118e1f8168395c65c8a2c750ae2bab54fc4bd4e0e8/markupsafe-3.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: ccfcd093f13f0f0b7fdd0f198b90053bf7b2f02a3927a30e63f3ccc9df56b676 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/aa/5b/bec5aa9bbbb2c946ca2733ef9c4ca91c91b6a24580193e891b5f7dbe8e1e/markupsafe-3.0.3-cp312-cp312-win_amd64.whl + name: markupsafe + version: 3.0.3 + sha256: 26a5784ded40c9e318cfc2bdb30fe164bdb8665ded9cd64d500a34fb42067b1c + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/af/cd/ce6e848bbf2c32314c9b237839119c5a564a59725b53157c856e90937b7a/markupsafe-3.0.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: f42d0984e947b8adf7dd6dde396e720934d12c506ce84eea8476409563607591 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/b5/64/7660f8a4a8e53c924d0fa05dc3a55c9cee10bbd82b11c5afb27d44b096ce/markupsafe-3.0.3-cp314-cp314-macosx_11_0_arm64.whl + name: markupsafe + version: 3.0.3 + sha256: c47a551199eb8eb2121d4f0f15ae0f923d31350ab9280078d1e5f12b249e0026 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/d6/25/55dc3ab959917602c96985cb1253efaa4ff42f71194bddeb61eb7278b8be/markupsafe-3.0.3-cp310-cp310-win_amd64.whl + name: markupsafe + version: 3.0.3 + sha256: c4ffb7ebf07cfe8931028e3e4c85f0357459a3f9f9490886198848f4fa002ec8 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/e1/2e/5898933336b61975ce9dc04decbc0a7f2fee78c30353c5efba7f2d6ff27a/markupsafe-3.0.3-cp311-cp311-macosx_11_0_arm64.whl + name: markupsafe + version: 3.0.3 + sha256: 4bd4cd07944443f5a265608cc6aab442e4f74dff8088b0dfc8238647b8f6ae9a + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/e8/4b/3541d44f3937ba468b75da9eebcae497dcf67adb65caa16760b0a6807ebb/markupsafe-3.0.3-cp310-cp310-macosx_10_9_x86_64.whl + name: markupsafe + version: 3.0.3 + sha256: 2f981d352f04553a7171b8e44369f2af4055f888dfb147d55e42d29e29e74559 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/2d/4a/3262e792d1db92939f820c8fae5ac298b201769e12bb11c89de33ac7bae2/matplotlib-3.5.3-cp310-cp310-macosx_10_9_x86_64.whl + name: matplotlib + version: 3.5.3 + sha256: cd45a6f3e93a780185f70f05cf2a383daed13c3489233faad83e81720f7ede24 + requires_dist: + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.0.1 + - numpy>=1.17 + - packaging>=20.0 + - pillow>=6.2.0 + - pyparsing>=2.2.1 + - python-dateutil>=2.7 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/61/1a/584f2e77e2f88239d66314dab14839a199424319df242c783b84ae23ae41/matplotlib-3.5.3-cp310-cp310-macosx_11_0_arm64.whl + name: matplotlib + version: 3.5.3 + sha256: d62880e1f60e5a30a2a8484432bcb3a5056969dc97258d7326ad465feb7ae069 + requires_dist: + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.0.1 + - numpy>=1.17 + - packaging>=20.0 + - pillow>=6.2.0 + - pyparsing>=2.2.1 + - python-dateutil>=2.7 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/90/81/b73cb7d615a70a01bd349b8e85a7648c51f3a6346695354c1ce569db6d8f/matplotlib-3.5.3-cp310-cp310-win_amd64.whl + name: matplotlib + version: 3.5.3 + sha256: 2e6d184ebe291b9e8f7e78bbab7987d269c38ea3e062eace1fe7d898042ef804 + requires_dist: + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.0.1 + - numpy>=1.17 + - packaging>=20.0 + - pillow>=6.2.0 + - pyparsing>=2.2.1 + - python-dateutil>=2.7 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/e5/ca/3ed0e1de9df496392a4c9d75b0c78f82fe5758c66bb875903cf7a9402f0b/matplotlib-3.5.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: matplotlib + version: 3.5.3 + sha256: c995f7d9568f18b5db131ab124c64e51b6820a92d10246d4f2b3f3a66698a15b + requires_dist: + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.0.1 + - numpy>=1.17 + - packaging>=20.0 + - pillow>=6.2.0 + - pyparsing>=2.2.1 + - python-dateutil>=2.7 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/30/4e/c10f171b6e2f44d9e3a2b96efa38b1677439d79c99357600a62cc1e9594e/matplotlib-3.10.8-cp312-cp312-win_amd64.whl + name: matplotlib + version: 3.10.8 + sha256: dd80ecb295460a5d9d260df63c43f4afbdd832d725a531f008dad1664f458adf + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3c/43/9c0ff7a2f11615e516c3b058e1e6e8f9614ddeca53faca06da267c48345d/matplotlib-3.10.8-cp314-cp314-macosx_10_13_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: b53285e65d4fa4c86399979e956235deb900be5baa7fc1218ea67fbfaeaadd6f + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3d/b9/15fd5541ef4f5b9a17eefd379356cf12175fe577424e7b1d80676516031a/matplotlib-3.10.8-cp313-cp313-macosx_10_13_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: 3f2e409836d7f5ac2f1c013110a4d50b9f7edc26328c108915f9075d7d7a91b6 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3e/f3/c5195b1ae57ef85339fd7285dfb603b22c8b4e79114bae5f4f0fcf688677/matplotlib-3.10.8-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: 3ab4aabc72de4ff77b3ec33a6d78a68227bf1123465887f9905ba79184a1cc04 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/58/27/ca01e043c4841078e82cf6e80a6993dfecd315c3d79f5f3153afbb8e1ec6/matplotlib-3.10.8-cp310-cp310-macosx_11_0_arm64.whl + name: matplotlib + version: 3.10.8 + sha256: 37b3c1cc42aa184b3f738cfa18c1c1d72fd496d85467a6cf7b807936d39aa656 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/58/be/a30bd917018ad220c400169fba298f2bb7003c8ccbc0c3e24ae2aacad1e8/matplotlib-3.10.8-cp310-cp310-macosx_10_12_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: 00270d217d6b20d14b584c521f810d60c5c78406dc289859776550df837dcda7 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/64/40/37612487cc8a437d4dd261b32ca21fe2d79510fe74af74e1f42becb1bdb8/matplotlib-3.10.8-cp313-cp313-win_amd64.whl + name: matplotlib + version: 3.10.8 + sha256: e8ea3e2d4066083e264e75c829078f9e149fa119d27e19acd503de65e0b13149 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/6f/ca/e8ae28649fcdf039fda5ef554b40a95f50592a3c47e6f7270c9561c12b07/matplotlib-3.10.8-cp314-cp314-macosx_11_0_arm64.whl + name: matplotlib + version: 3.10.8 + sha256: 32f8dce744be5569bebe789e46727946041199030db8aeb2954d26013a0eb26b + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/6f/d3/a4bbc01c237ab710a1f22b4da72f4ff6d77eb4c7735ea9811a94ae239067/matplotlib-3.10.8-cp311-cp311-win_amd64.whl + name: matplotlib + version: 3.10.8 + sha256: 18821ace09c763ec93aef5eeff087ee493a24051936d7b9ebcad9662f66501f9 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/75/97/a471f1c3eb1fd6f6c24a31a5858f443891d5127e63a7788678d14e249aea/matplotlib-3.10.8-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: a0a7f52498f72f13d4a25ea70f35f4cb60642b466cbb0a9be951b5bc3f45a486 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/7e/65/07d5f5c7f7c994f12c768708bd2e17a4f01a2b0f44a1c9eccad872433e2e/matplotlib-3.10.8-cp312-cp312-macosx_11_0_arm64.whl + name: matplotlib + version: 3.10.8 + sha256: b9a5ca4ac220a0cdd1ba6bcba3608547117d30468fefce49bb26f55c1a3d5c58 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/8d/a0/2ba3473c1b66b9c74dc7107c67e9008cb1782edbe896d4c899d39ae9cf78/matplotlib-3.10.8-cp313-cp313-macosx_11_0_arm64.whl + name: matplotlib + version: 3.10.8 + sha256: 56271f3dac49a88d7fca5060f004d9d22b865f743a12a23b1e937a0be4818ee1 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/8f/a0/7024215e95d456de5883e6732e708d8187d9753a21d32f8ddb3befc0c445/matplotlib-3.10.8-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: efb30e3baaea72ce5928e32bab719ab4770099079d66726a62b11b1ef7273be4 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/93/a5/de89ac80f10b8dc615807ee1133cd99ac74082581196d4d9590bea10690d/matplotlib-3.10.8-cp314-cp314-win_amd64.whl + name: matplotlib + version: 3.10.8 + sha256: 83d282364ea9f3e52363da262ce32a09dfe241e4080dcedda3c0db059d3c1f11 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/9e/67/f997cdcbb514012eb0d10cd2b4b332667997fb5ebe26b8d41d04962fa0e6/matplotlib-3.10.8-cp312-cp312-macosx_10_13_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: 64fcc24778ca0404ce0cb7b6b77ae1f4c7231cdd60e6778f999ee05cbd581b9a + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/cb/aa/7ab67f2b729ae6a91bcf9dcac0affb95fb8c56f7fd2b2af894ae0b0cf6fa/matplotlib-3.10.8-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: ee40c27c795bda6a5292e9cff9890189d32f7e3a0bf04e0e3c9430c4a00c37df + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/e2/e2/fd0bbadf837f81edb0d208ba8f8cb552874c3b16e27cb91a31977d90875d/matplotlib-3.10.8-cp310-cp310-win_amd64.whl + name: matplotlib + version: 3.10.8 + sha256: f9b587c9c7274c1613a30afabf65a272114cd6cdbe67b3406f818c79d7ab2e2a + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f5/26/4221a741eb97967bc1fd5e4c52b9aa5a91b2f4ec05b59f6def4d820f9df9/matplotlib-3.10.8-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: 2cf5bd12cecf46908f286d7838b2abc6c91cda506c0445b8223a7c19a00df008 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f8/86/de7e3a1cdcfc941483af70609edc06b83e7c8a0e0dc9ac325200a3f4d220/matplotlib-3.10.8-cp311-cp311-macosx_10_12_x86_64.whl + name: matplotlib + version: 3.10.8 + sha256: 6be43b667360fef5c754dda5d25a32e6307a03c204f3c0fc5468b78fa87b4160 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/fd/14/baad3222f424b19ce6ad243c71de1ad9ec6b2e4eb1e458a48fdc6d120401/matplotlib-3.10.8-cp311-cp311-macosx_11_0_arm64.whl + name: matplotlib + version: 3.10.8 + sha256: a2b336e2d91a3d7006864e0990c83b216fcdca64b5a6484912902cef87313d78 + requires_dist: + - contourpy>=1.0.1 + - cycler>=0.10 + - fonttools>=4.22.0 + - kiwisolver>=1.3.1 + - numpy>=1.23 + - packaging>=20.0 + - pillow>=8 + - pyparsing>=3 + - python-dateutil>=2.7 + - meson-python>=0.13.1,<0.17.0 ; extra == 'dev' + - pybind11>=2.13.2,!=2.13.3 ; extra == 'dev' + - setuptools-scm>=7 ; extra == 'dev' + - setuptools>=64 ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl + name: matplotlib-inline + version: 0.2.1 + sha256: d56ce5156ba6085e00a9d54fead6ed29a9c47e215cd1bba2e976ef39f5710a76 + requires_dist: + - traitlets + - flake8 ; extra == 'test' + - nbdime ; extra == 'test' + - nbval ; extra == 'test' + - notebook ; extra == 'test' + - pytest ; extra == 'test' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl + name: mccabe + version: 0.7.0 + sha256: 6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl + name: mistune + version: 3.2.0 + sha256: febdc629a3c78616b94393c6580551e0e34cc289987ec6c35ed3f4be42d0eee1 + requires_dist: + - typing-extensions ; python_full_version < '3.11' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/fe/75/0b4a10da17a44cf13567d08a9c7632a285297e46253263f1ae119129d10a/narwhals-2.18.0-py3-none-any.whl + name: narwhals + version: 2.18.0 + sha256: 68378155ee706ac9c5b25868ef62ecddd62947b6df7801a0a156bc0a615d2d0d + requires_dist: + - cudf-cu12>=24.10.0 ; extra == 'cudf' + - dask[dataframe]>=2024.8 ; extra == 'dask' + - duckdb>=1.1 ; extra == 'duckdb' + - ibis-framework>=6.0.0 ; extra == 'ibis' + - packaging ; extra == 'ibis' + - pyarrow-hotfix ; extra == 'ibis' + - rich ; extra == 'ibis' + - modin ; extra == 'modin' + - pandas>=1.1.3 ; extra == 'pandas' + - polars>=0.20.4 ; extra == 'polars' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - pyspark>=3.5.0 ; extra == 'pyspark' + - pyspark[connect]>=3.5.0 ; extra == 'pyspark-connect' + - duckdb>=1.1 ; extra == 'sql' + - sqlparse ; extra == 'sql' + - sqlframe>=3.22.0,!=3.39.3 ; extra == 'sqlframe' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl + name: nbclient + version: 0.10.4 + sha256: 9162df5a7373d70d606527300a95a975a47c137776cd942e52d9c7e29ff83440 + requires_dist: + - jupyter-client>=6.1.12 + - jupyter-core>=4.12,!=5.0.* + - nbformat>=5.1.3 + - traitlets>=5.4 + - pre-commit ; extra == 'dev' + - autodoc-traits ; extra == 'docs' + - flaky ; extra == 'docs' + - ipykernel>=6.19.3 ; extra == 'docs' + - ipython ; extra == 'docs' + - ipywidgets ; extra == 'docs' + - mock ; extra == 'docs' + - moto ; extra == 'docs' + - myst-parser ; extra == 'docs' + - nbconvert>=7.1.0 ; extra == 'docs' + - pytest-asyncio>=1.3.0 ; extra == 'docs' + - pytest-cov>=4.0 ; extra == 'docs' + - pytest>=9.0.1,<10 ; extra == 'docs' + - sphinx-book-theme ; extra == 'docs' + - sphinx>=1.7 ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - testpath ; extra == 'docs' + - xmltodict ; extra == 'docs' + - flaky ; extra == 'test' + - ipykernel>=6.19.3 ; extra == 'test' + - ipython ; extra == 'test' + - ipywidgets ; extra == 'test' + - nbconvert>=7.1.0 ; extra == 'test' + - pytest-asyncio>=1.3.0 ; extra == 'test' + - pytest-cov>=4.0 ; extra == 'test' + - pytest>=9.0.1,<10 ; extra == 'test' + - testpath ; extra == 'test' + - xmltodict ; extra == 'test' + requires_python: '>=3.10.0' +- pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl + name: nbconvert + version: 7.17.0 + sha256: 4f99a63b337b9a23504347afdab24a11faa7d86b405e5c8f9881cd313336d518 + requires_dist: + - beautifulsoup4 + - bleach[css]!=5.0.0 + - defusedxml + - importlib-metadata>=3.6 ; python_full_version < '3.10' + - jinja2>=3.0 + - jupyter-core>=4.7 + - jupyterlab-pygments + - markupsafe>=2.0 + - mistune>=2.0.3,<4 + - nbclient>=0.5.0 + - nbformat>=5.7 + - packaging + - pandocfilters>=1.4.1 + - pygments>=2.4.1 + - traitlets>=5.1 + - flaky ; extra == 'all' + - intersphinx-registry ; extra == 'all' + - ipykernel ; extra == 'all' + - ipython ; extra == 'all' + - ipywidgets>=7.5 ; extra == 'all' + - myst-parser ; extra == 'all' + - nbsphinx>=0.2.12 ; extra == 'all' + - playwright ; extra == 'all' + - pydata-sphinx-theme ; extra == 'all' + - pyqtwebengine>=5.15 ; extra == 'all' + - pytest>=7 ; extra == 'all' + - sphinx>=5.0.2 ; extra == 'all' + - sphinxcontrib-spelling ; extra == 'all' + - tornado>=6.1 ; extra == 'all' + - intersphinx-registry ; extra == 'docs' + - ipykernel ; extra == 'docs' + - ipython ; extra == 'docs' + - myst-parser ; extra == 'docs' + - nbsphinx>=0.2.12 ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx>=5.0.2 ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - pyqtwebengine>=5.15 ; extra == 'qtpdf' + - pyqtwebengine>=5.15 ; extra == 'qtpng' + - tornado>=6.1 ; extra == 'serve' + - flaky ; extra == 'test' + - ipykernel ; extra == 'test' + - ipywidgets>=7.5 ; extra == 'test' + - pytest>=7 ; extra == 'test' + - playwright ; extra == 'webpdf' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl + name: nbformat + version: 5.10.4 + sha256: 3b48d6c8fbca4b299bf3982ea7db1af21580e4fec269ad087b9e81588891200b + requires_dist: + - fastjsonschema>=2.15 + - jsonschema>=2.6 + - jupyter-core>=4.12,!=5.0.* + - traitlets>=5.1 + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx ; extra == 'docs' + - sphinxcontrib-github-alt ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - pep440 ; extra == 'test' + - pre-commit ; extra == 'test' + - pytest ; extra == 'test' + - testpath ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl + name: nbval + version: 0.11.0 + sha256: 307aecc866c9a1e8a13bb5bbb008a702bacfda2394dff6fe504a3108a58042a0 + requires_dist: + - pytest>=7 + - jupyter-client + - nbformat + - ipykernel + - coverage + requires_python: '>=3.7,<4' +- conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda + sha256: 3fde293232fa3fca98635e1167de6b7c7fda83caf24b9d6c91ec9eefb4f4d586 + md5: 47e340acb35de30501a76c7c799c41d7 + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=13 + license: X11 AND BSD-3-Clause + purls: [] + size: 891641 + timestamp: 1738195959188 +- conda: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.5-h0622a9a_3.conda + sha256: ea4a5d27ded18443749aefa49dc79f6356da8506d508b5296f60b8d51e0c4bd9 + md5: ced34dd9929f491ca6dab6a2927aff25 + depends: + - __osx >=10.13 + license: X11 AND BSD-3-Clause + purls: [] + size: 822259 + timestamp: 1738196181298 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.5-h5e97a16_3.conda + sha256: 2827ada40e8d9ca69a153a45f7fd14f32b2ead7045d3bbb5d10964898fe65733 + md5: 068d497125e4bf8a66bf707254fff5ae + depends: + - __osx >=11.0 + license: X11 AND BSD-3-Clause + purls: [] + size: 797030 + timestamp: 1738196177597 +- pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl + name: nest-asyncio + version: 1.6.0 + sha256: 87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c + requires_python: '>=3.5' +- pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + name: notebook + version: 7.5.4 + sha256: 860e31782b3d3a25ca0819ff039f5cf77845d1bf30c78ef9528b88b25e0a9850 + requires_dist: + - jupyter-server>=2.4.0,<3 + - jupyterlab-server>=2.28.0,<3 + - jupyterlab>=4.5.5,<4.6 + - notebook-shim>=0.2,<0.3 + - tornado>=6.2.0 + - hatch ; extra == 'dev' + - pre-commit ; extra == 'dev' + - myst-parser ; extra == 'docs' + - nbsphinx ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx>=1.3.6 ; extra == 'docs' + - sphinxcontrib-github-alt ; extra == 'docs' + - sphinxcontrib-spelling ; extra == 'docs' + - importlib-resources>=5.0 ; python_full_version < '3.10' and extra == 'test' + - ipykernel ; extra == 'test' + - jupyter-server[test]>=2.4.0,<3 ; extra == 'test' + - jupyterlab-server[test]>=2.28.0,<3 ; extra == 'test' + - nbval ; extra == 'test' + - pytest-console-scripts ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-tornasync ; extra == 'test' + - pytest>=7.0 ; extra == 'test' + - requests ; extra == 'test' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl + name: notebook-shim + version: 0.2.4 + sha256: 411a5be4e9dc882a074ccbcae671eda64cceb068767e9a3419096986560e1cef + requires_dist: + - jupyter-server>=1.8,<3 + - pytest ; extra == 'test' + - pytest-console-scripts ; extra == 'test' + - pytest-jupyter ; extra == 'test' + - pytest-tornasync ; extra == 'test' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/13/c1/a5c78ae637402c5550e2e0ba175275d2515d432ec28af0cdc23c9b476e65/numexpr-2.14.1-cp314-cp314-macosx_11_0_arm64.whl + name: numexpr + version: 2.14.1 + sha256: 2eac7a5a2f70b3768c67056445d1ceb4ecd9b853c8eda9563823b551aeaa5082 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/18/af/26773a246716922794388786529e5640676399efabb0ee217ce034df9d27/numexpr-2.14.1-cp310-cp310-win_amd64.whl + name: numexpr + version: 2.14.1 + sha256: 823cd82c8e7937981339f634e7a9c6a92cb2d0b9d0a5cf627a5e394fffc05377 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/1f/67/ffe750b5452eb66de788c34e7d21ec6d886abb4d7c43ad1dc88ceb3d998f/numexpr-2.14.1-cp312-cp312-win_amd64.whl + name: numexpr + version: 2.14.1 + sha256: fdd886f4b7dbaf167633ee396478f0d0aa58ea2f9e7ccc3c6431019623e8d68f + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/25/95/d64f680ea1fc56d165457287e0851d6708800f9fcea346fc1b9957942ee6/numexpr-2.14.1-cp311-cp311-macosx_11_0_arm64.whl + name: numexpr + version: 2.14.1 + sha256: 2773ee1133f77009a1fc2f34fe236f3d9823779f5f75450e183137d49f00499f + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/34/d4/d1a410901c620f7a6a3c5c2b1fc9dab22170be05a89d2c02ae699e27bd3f/numexpr-2.14.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: 75440c54fc01e130396650fdf307aa9d41a67dc06ddbfb288971b591c13a395b + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/35/ae/d58558d8043de0c49f385ea2fa789e3cfe4d436c96be80200c5292f45f15/numexpr-2.14.1-cp313-cp313-macosx_11_0_arm64.whl + name: numexpr + version: 2.14.1 + sha256: dce0b5a0447baa7b44bc218ec2d7dcd175b8eee6083605293349c0c1d9b82fb6 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/45/93/b6760dd1904c2a498e5f43d1bb436f59383c3ddea3815f1461dfaa259373/numexpr-2.14.1-cp312-cp312-macosx_11_0_arm64.whl + name: numexpr + version: 2.14.1 + sha256: 47041f2f7b9e69498fb311af672ba914a60e6e6d804011caacb17d66f639e659 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/4c/1a/edbe839109518364ac0bd9e918cf874c755bb2c128040e920f198c494263/numexpr-2.14.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: 2a381e5e919a745c9503bcefffc1c7f98c972c04ec58fc8e999ed1a929e01ba6 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/4f/3e/d83e9401a1c3449a124f7d4b3fb44084798e0d30f7c11e60712d9b94cf11/numexpr-2.14.1-cp314-cp314-win_amd64.whl + name: numexpr + version: 2.14.1 + sha256: 587c41509bc373dfb1fe6086ba55a73147297247bedb6d588cda69169fc412f2 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/64/72/4ca9bd97b2eb6dce9f5e70a3b6acec1a93e1fb9b079cb4cba2cdfbbf295d/numexpr-2.14.1-cp311-cp311-win_amd64.whl + name: numexpr + version: 2.14.1 + sha256: e9b2f957798c67a2428be96b04bce85439bed05efe78eb78e4c2ca43737578e7 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/73/b4/9f6d637fd79df42be1be29ee7ba1f050fab63b7182cb922a0e08adc12320/numexpr-2.14.1-cp313-cp313-macosx_10_13_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: 09078ba73cffe94745abfbcc2d81ab8b4b4e9d7bfbbde6cac2ee5dbf38eee222 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/88/e1/3db65117f02cdefb0e5e4c440daf1c30beb45051b7f47aded25b7f4f2f34/numexpr-2.14.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: 439ec4d57b853792ebe5456e3160312281c3a7071ecac5532ded3278ede614de + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/9d/20/c473fc04a371f5e2f8c5749e04505c13e7a8ede27c09e9f099b2ad6f43d6/numexpr-2.14.1-cp312-cp312-macosx_10_13_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: 91ebae0ab18c799b0e6b8c5a8d11e1fa3848eb4011271d99848b297468a39430 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ac/36/9db78dfbfdfa1f8bf0872993f1a334cdd8fca5a5b6567e47dcb128bcb7c2/numexpr-2.14.1-cp314-cp314-macosx_10_13_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: ede79f7ff06629f599081de644546ce7324f1581c09b0ac174da88a470d39c21 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/b2/a3/67999bdd1ed1f938d38f3fedd4969632f2f197b090e50505f7cc1fa82510/numexpr-2.14.1-cp311-cp311-macosx_10_9_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: 2d03fcb4644a12f70a14d74006f72662824da5b6128bf1bcd10cc3ed80e64c34 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/cc/23/9281bceaeb282cead95f0aa5f7f222ffc895670ea689cc1398355f6e3001/numexpr-2.14.1-cp313-cp313-win_amd64.whl + name: numexpr + version: 2.14.1 + sha256: 9fdcd4735121658a313f878fd31136d1bfc6a5b913219e7274e9fca9f8dac3bb + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d9/43/560e9ba23c02c904b5934496486d061bcb14cd3ebba2e3cf0e2dccb6c22b/numexpr-2.14.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: eee6d4fbbbc368e6cdd0772734d6249128d957b3b8ad47a100789009f4de7083 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/db/91/ccd504cbe5b88d06987c77f42ba37a13ef05065fdab4afe6dcfeb2961faf/numexpr-2.14.1-cp310-cp310-macosx_10_9_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: d0fab3fd06a04f6b86102552b26aa5d85e20ac7d8296c15764c726eeabae6cc8 + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f3/89/6b07977baf2af75fb6692f9e7a1fb612a15f600fc921f3f565366de01f4a/numexpr-2.14.1-cp310-cp310-macosx_11_0_arm64.whl + name: numexpr + version: 2.14.1 + sha256: 64ae5dfd62d74a3ef82fe0b37f80527247f3626171ad82025900f46ffca4b39a + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/fc/f9/c9457652dfe28e2eb898372da2fe786c6db81af9540c0f853ee04a0699cc/numexpr-2.14.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numexpr + version: 2.14.1 + sha256: 05f9366d23a2e991fd5a8b5e61a17558f028ba86158a4552f8f239b005cdf83c + requires_dist: + - numpy>=1.23.0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/95/6a/319e9fafb828e4a651b03b9622b781dfd80b5f1f5f31cfa6c9b734ce7cda/numpy-1.22.4-cp310-cp310-macosx_10_15_x86_64.whl + name: numpy + version: 1.22.4 + sha256: 1ce7ab2053e36c0a71e7a13a7475bd3b1f54750b4b433adc96313e127b870887 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/9b/12/14529e4a0749c165c2f9df5cb09873f35ffe1bac7cfdf9a26fe90bfd587a/numpy-1.22.4-cp310-cp310-macosx_11_0_arm64.whl + name: numpy + version: 1.22.4 + sha256: 7228ad13744f63575b3a972d7ee4fd61815b2879998e70930d4ccf9ec721dce0 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/b0/f4/d67c8c39efe3c45dfd32bb2a3fc49cbbe5496e575cc42b8bac60fe7b6701/numpy-1.22.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: numpy + version: 1.22.4 + sha256: a911e317e8c826ea632205e63ed8507e0dc877dcdc49744584dfc363df9ca08c + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/b5/50/d7978137464251c393df28fe0592fbb968110f752d66f60c7a53f7158076/numpy-1.22.4-cp310-cp310-win_amd64.whl + name: numpy + version: 1.22.4 + sha256: 3e1ffa4748168e1cc8d3cde93f006fe92b5421396221a02f2274aab6ac83b077 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/22/c2/4b9221495b2a132cc9d2eb862e21d42a009f5a60e45fc44b00118c174bff/numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl + name: numpy + version: 2.2.6 + sha256: 8e41fd67c52b86603a91c1a505ebaef50b3314de0213461c7a6e99c9a3beff90 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/9a/3e/ed6db5be21ce87955c0cbd3009f2803f59fa08df21b5df06862e2d8e2bdd/numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl + name: numpy + version: 2.2.6 + sha256: b412caa66f72040e6d268491a59f2c43bf03eb6c96dd8f0307829feb7fa2b6fb + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a3/dd/4b822569d6b96c39d1215dbae0582fd99954dcbcf0c1a13c61783feaca3f/numpy-2.2.6-cp310-cp310-win_amd64.whl + name: numpy + version: 2.2.6 + sha256: f0fd6321b839904e15c46e0d257fdd101dd7f530fe03fd6359c1ea63738703f3 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/b4/63/3de6a34ad7ad6646ac7d2f55ebc6ad439dbbf9c4370017c50cf403fb19b5/numpy-2.2.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: numpy + version: 2.2.6 + sha256: fc7b73d02efb0e18c000e9ad8b83480dfcd5dfd11065997ed4c6747470ae8915 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl + name: numpy + version: 2.4.3 + sha256: 2629289168f4897a3c4e23dc98d6f1731f0fc0fe52fb9db19f974041e4cc12b9 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/48/39/c56ef87af669364356bb011922ef0734fc49dad51964568634c72a009488/numpy-2.4.3-cp314-cp314-win_amd64.whl + name: numpy + version: 2.4.3 + sha256: 0448e7f9caefb34b4b7dd2b77f21e8906e5d6f0365ad525f9f4f530b13df2afc + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/70/ae/3936f79adebf8caf81bd7a599b90a561334a658be4dcc7b6329ebf4ee8de/numpy-2.4.3-cp314-cp314-macosx_10_15_x86_64.whl + name: numpy + version: 2.4.3 + sha256: 5884ce5c7acfae1e4e1b6fde43797d10aa506074d25b531b4f54bde33c0c31d4 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/74/1b/ee2abfc68e1ce728b2958b6ba831d65c62e1b13ce3017c13943f8f9b5b2e/numpy-2.4.3-cp312-cp312-macosx_11_0_arm64.whl + name: numpy + version: 2.4.3 + sha256: 7395e69ff32526710748f92cd8c9849b361830968ea3e24a676f272653e8983e + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/76/1d/edccf27adedb754db7c4511d5eac8b83f004ae948fe2d3509e8b78097d4c/numpy-2.4.3-cp311-cp311-win_amd64.whl + name: numpy + version: 2.4.3 + sha256: 77e76d932c49a75617c6d13464e41203cd410956614d0a0e999b25e9e8d27eec + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/78/51/9f5d7a41f0b51649ddf2f2320595e15e122a40610b233d51928dd6c92353/numpy-2.4.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numpy + version: 2.4.3 + sha256: 715de7f82e192e8cae5a507a347d97ad17598f8e026152ca97233e3666daaa71 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numpy + version: 2.4.3 + sha256: d5f51900414fc9204a0e0da158ba2ac52b75656e7dce7e77fb9f84bfa343b4cc + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/9b/62/760f2b55866b496bb1fa7da2a6db076bef908110e568b02fcfc1422e2a3a/numpy-2.4.3-cp314-cp314-macosx_11_0_arm64.whl + name: numpy + version: 2.4.3 + sha256: 297837823f5bc572c5f9379b0c9f3a3365f08492cbdc33bcc3af174372ebb168 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/a9/7e/4f120ecc54ba26ddf3dc348eeb9eb063f421de65c05fc961941798feea18/numpy-2.4.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numpy + version: 2.4.3 + sha256: 679f2a834bae9020f81534671c56fd0cc76dd7e5182f57131478e23d0dc59e24 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/a9/ed/6388632536f9788cea23a3a1b629f25b43eaacd7d7377e5d6bc7b9deb69b/numpy-2.4.3-cp312-cp312-macosx_10_13_x86_64.whl + name: numpy + version: 2.4.3 + sha256: 61b0cbabbb6126c8df63b9a3a0c4b1f44ebca5e12ff6997b80fcf267fb3150ef + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl + name: numpy + version: 2.4.3 + sha256: 0a60e17a14d640f49146cb38e3f105f571318db7826d9b6fef7e4dce758faecd + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/b5/7c/c061f3de0630941073d2598dc271ac2f6cbcf5c83c74a5870fea07488333/numpy-2.4.3-cp311-cp311-macosx_11_0_arm64.whl + name: numpy + version: 2.4.3 + sha256: 8ba7b51e71c05aa1f9bc3641463cd82308eab40ce0d5c7e1fd4038cbf9938147 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl + name: numpy + version: 2.4.3 + sha256: b346845443716c8e542d54112966383b448f4a3ba5c66409771b8c0889485dd3 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/bd/79/cc665495e4d57d0aa6fbcc0aa57aa82671dfc78fbf95fe733ed86d98f52a/numpy-2.4.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: numpy + version: 2.4.3 + sha256: e7dd01a46700b1967487141a66ac1a3cf0dd8ebf1f08db37d46389401512ca97 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/d7/7c/f5ee1bf6ed888494978046a809df2882aad35d414b622893322df7286879/numpy-2.4.3-cp312-cp312-win_amd64.whl + name: numpy + version: 2.4.3 + sha256: 65f3c2455188f09678355f5cae1f959a06b778bc66d535da07bf2ef20cd319d5 + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/f9/51/5093a2df15c4dc19da3f79d1021e891f5dcf1d9d1db6ba38891d5590f3fe/numpy-2.4.3-cp311-cp311-macosx_10_9_x86_64.whl + name: numpy + version: 2.4.3 + sha256: 33b3bf58ee84b172c067f56aeadc7ee9ab6de69c5e800ab5b10295d54c581adb + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/31/1e/9e366f36efc550f07d6737f199e3f6bffafdf28795d007f10a77dd274f5c/nvidia_nccl_cu12-2.29.7-py3-none-manylinux_2_18_x86_64.whl + name: nvidia-nccl-cu12 + version: 2.29.7 + sha256: ecd0a012051abc20c1aa87328841efa8cade3ced65803046e38c2f03c0891fea + requires_python: '>=3' +- conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.1-h35e630c_1.conda + sha256: 44c877f8af015332a5d12f5ff0fb20ca32f896526a7d0cdb30c769df1144fb5c + md5: f61eb8cd60ff9057122a3d338b99c00f + depends: + - __glibc >=2.17,<3.0.a0 + - ca-certificates + - libgcc >=14 + license: Apache-2.0 + license_family: Apache + purls: [] + size: 3164551 + timestamp: 1769555830639 +- conda: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.6.1-hb6871ef_1.conda + sha256: e02e5639b0e4d6d4fcf0f3b082642844fb5a37316f5b0a1126c6271347462e90 + md5: 30bb8d08b99b9a7600d39efb3559fff0 + depends: + - __osx >=10.13 + - ca-certificates + license: Apache-2.0 + license_family: Apache + purls: [] + size: 2777136 + timestamp: 1769557662405 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.6.1-hd24854e_1.conda + sha256: 361f5c5e60052abc12bdd1b50d7a1a43e6a6653aab99a2263bf2288d709dcf67 + md5: f4f6ad63f98f64191c3e77c5f5f29d76 + depends: + - __osx >=11.0 + - ca-certificates + license: Apache-2.0 + license_family: Apache + purls: [] + size: 3104268 + timestamp: 1769556384749 +- conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.1-hf411b9b_1.conda + sha256: 53a5ad2e5553b8157a91bb8aa375f78c5958f77cb80e9d2ce59471ea8e5c0bd6 + md5: eb585509b815415bc964b2c7e11c7eb3 + depends: + - ca-certificates + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + license: Apache-2.0 + license_family: Apache + purls: [] + size: 9343023 + timestamp: 1769557547888 +- pypi: https://files.pythonhosted.org/packages/2c/ab/fc8290c6a4c722e5514d80f62b2dc4c4df1a68a41d1364e625c35990fcf3/overrides-7.7.0-py3-none-any.whl + name: overrides + version: 7.7.0 + sha256: c7ed9d062f78b8e4c1a7b70bd8796b35ead4d9f510227ef9c5dc7626c60d7e49 + requires_dist: + - typing ; python_full_version < '3.5' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl + name: packaging + version: '26.0' + sha256: b36f1fef9334a5588b4166f8bcd26a14e521f2b55e6b9de3aaa80d3ff7a37529 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/0f/29/b1b0e546affca223467bde08f000c3163a17d80982c0271151ad0a7af3c8/pandas-1.4.4-cp310-cp310-macosx_11_0_arm64.whl + name: pandas + version: 1.4.4 + sha256: 94f2ed1fd51e545ebf71da1e942fe1822ee01e10d3dd2a7276d01351333b7c6b + requires_dist: + - python-dateutil>=2.8.1 + - pytz>=2020.1 + - numpy>=1.18.5 ; python_full_version < '3.10' and platform_machine != 'aarch64' and platform_machine != 'arm64' + - numpy>=1.19.2 ; python_full_version < '3.10' and platform_machine == 'aarch64' + - numpy>=1.20.0 ; python_full_version < '3.10' and platform_machine == 'arm64' + - numpy>=1.21.0 ; python_full_version >= '3.10' + - hypothesis>=5.5.3 ; extra == 'test' + - pytest>=6.0 ; extra == 'test' + - pytest-xdist>=1.31 ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/48/0c/a1a3a8b3e3b70c5387dea1cafbc94f7ca7d0d6aa1895babcc2be738cfab9/pandas-1.4.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: pandas + version: 1.4.4 + sha256: d0022fe6a313df1c4869b5edc012d734c6519a6fffa3cf70930f32e6a1078e49 + requires_dist: + - python-dateutil>=2.8.1 + - pytz>=2020.1 + - numpy>=1.18.5 ; python_full_version < '3.10' and platform_machine != 'aarch64' and platform_machine != 'arm64' + - numpy>=1.19.2 ; python_full_version < '3.10' and platform_machine == 'aarch64' + - numpy>=1.20.0 ; python_full_version < '3.10' and platform_machine == 'arm64' + - numpy>=1.21.0 ; python_full_version >= '3.10' + - hypothesis>=5.5.3 ; extra == 'test' + - pytest>=6.0 ; extra == 'test' + - pytest-xdist>=1.31 ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/4a/5b/d74c7faadceffce80a6fde9823bdfca69b1b6bdc307ce6df5b06e109f210/pandas-1.4.4-cp310-cp310-win_amd64.whl + name: pandas + version: 1.4.4 + sha256: 785e878a6e6d8ddcdb8c181e600855402750052497d7fc6d6b508894f6b8830b + requires_dist: + - python-dateutil>=2.8.1 + - pytz>=2020.1 + - numpy>=1.18.5 ; python_full_version < '3.10' and platform_machine != 'aarch64' and platform_machine != 'arm64' + - numpy>=1.19.2 ; python_full_version < '3.10' and platform_machine == 'aarch64' + - numpy>=1.20.0 ; python_full_version < '3.10' and platform_machine == 'arm64' + - numpy>=1.21.0 ; python_full_version >= '3.10' + - hypothesis>=5.5.3 ; extra == 'test' + - pytest>=6.0 ; extra == 'test' + - pytest-xdist>=1.31 ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/d7/14/8ff04ffc7b3839e388b974ede2b1e81919164d86ce20a6f0196213645bfe/pandas-1.4.4-cp310-cp310-macosx_10_9_x86_64.whl + name: pandas + version: 1.4.4 + sha256: 7cd1d69a387f7d5e1a5a06a87574d9ef2433847c0e78113ab51c84d3a8bcaeaa + requires_dist: + - python-dateutil>=2.8.1 + - pytz>=2020.1 + - numpy>=1.18.5 ; python_full_version < '3.10' and platform_machine != 'aarch64' and platform_machine != 'arm64' + - numpy>=1.19.2 ; python_full_version < '3.10' and platform_machine == 'aarch64' + - numpy>=1.20.0 ; python_full_version < '3.10' and platform_machine == 'arm64' + - numpy>=1.21.0 ; python_full_version >= '3.10' + - hypothesis>=5.5.3 ; extra == 'test' + - pytest>=6.0 ; extra == 'test' + - pytest-xdist>=1.31 ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/13/4f/66d99628ff8ce7857aca52fed8f0066ce209f96be2fede6cef9f84e8d04f/pandas-2.3.3-cp310-cp310-macosx_11_0_arm64.whl + name: pandas + version: 2.3.3 + sha256: e19d192383eab2f4ceb30b412b22ea30690c9e618f78870357ae1d682912015a + requires_dist: + - numpy>=1.22.4 ; python_full_version < '3.11' + - numpy>=1.23.2 ; python_full_version == '3.11.*' + - numpy>=1.26.0 ; python_full_version >= '3.12' + - python-dateutil>=2.8.2 + - pytz>=2020.1 + - tzdata>=2022.7 + - hypothesis>=6.46.1 ; extra == 'test' + - pytest>=7.3.2 ; extra == 'test' + - pytest-xdist>=2.2.0 ; extra == 'test' + - pyarrow>=10.0.1 ; extra == 'pyarrow' + - bottleneck>=1.3.6 ; extra == 'performance' + - numba>=0.56.4 ; extra == 'performance' + - numexpr>=2.8.4 ; extra == 'performance' + - scipy>=1.10.0 ; extra == 'computation' + - xarray>=2022.12.0 ; extra == 'computation' + - fsspec>=2022.11.0 ; extra == 'fss' + - s3fs>=2022.11.0 ; extra == 'aws' + - gcsfs>=2022.11.0 ; extra == 'gcp' + - pandas-gbq>=0.19.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.0 ; extra == 'excel' + - python-calamine>=0.1.7 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.0.5 ; extra == 'excel' + - pyarrow>=10.0.1 ; extra == 'parquet' + - pyarrow>=10.0.1 ; extra == 'feather' + - tables>=3.8.0 ; extra == 'hdf5' + - pyreadstat>=1.2.0 ; extra == 'spss' + - sqlalchemy>=2.0.0 ; extra == 'postgresql' + - psycopg2>=2.9.6 ; extra == 'postgresql' + - adbc-driver-postgresql>=0.8.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.0 ; extra == 'mysql' + - pymysql>=1.0.2 ; extra == 'mysql' + - sqlalchemy>=2.0.0 ; extra == 'sql-other' + - adbc-driver-postgresql>=0.8.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=0.8.0 ; extra == 'sql-other' + - beautifulsoup4>=4.11.2 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'xml' + - matplotlib>=3.6.3 ; extra == 'plot' + - jinja2>=3.1.2 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.3.0 ; extra == 'clipboard' + - zstandard>=0.19.0 ; extra == 'compression' + - dataframe-api-compat>=0.1.7 ; extra == 'consortium-standard' + - adbc-driver-postgresql>=0.8.0 ; extra == 'all' + - adbc-driver-sqlite>=0.8.0 ; extra == 'all' + - beautifulsoup4>=4.11.2 ; extra == 'all' + - bottleneck>=1.3.6 ; extra == 'all' + - dataframe-api-compat>=0.1.7 ; extra == 'all' + - fastparquet>=2022.12.0 ; extra == 'all' + - fsspec>=2022.11.0 ; extra == 'all' + - gcsfs>=2022.11.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.46.1 ; extra == 'all' + - jinja2>=3.1.2 ; extra == 'all' + - lxml>=4.9.2 ; extra == 'all' + - matplotlib>=3.6.3 ; extra == 'all' + - numba>=0.56.4 ; extra == 'all' + - numexpr>=2.8.4 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.0 ; extra == 'all' + - pandas-gbq>=0.19.0 ; extra == 'all' + - psycopg2>=2.9.6 ; extra == 'all' + - pyarrow>=10.0.1 ; extra == 'all' + - pymysql>=1.0.2 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.0 ; extra == 'all' + - pytest>=7.3.2 ; extra == 'all' + - pytest-xdist>=2.2.0 ; extra == 'all' + - python-calamine>=0.1.7 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.3.0 ; extra == 'all' + - scipy>=1.10.0 ; extra == 'all' + - s3fs>=2022.11.0 ; extra == 'all' + - sqlalchemy>=2.0.0 ; extra == 'all' + - tables>=3.8.0 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2022.12.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.0.5 ; extra == 'all' + - zstandard>=0.19.0 ; extra == 'all' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/3d/f7/f425a00df4fcc22b292c6895c6831c0c8ae1d9fac1e024d16f98a9ce8749/pandas-2.3.3-cp310-cp310-macosx_10_9_x86_64.whl + name: pandas + version: 2.3.3 + sha256: 376c6446ae31770764215a6c937f72d917f214b43560603cd60da6408f183b6c + requires_dist: + - numpy>=1.22.4 ; python_full_version < '3.11' + - numpy>=1.23.2 ; python_full_version == '3.11.*' + - numpy>=1.26.0 ; python_full_version >= '3.12' + - python-dateutil>=2.8.2 + - pytz>=2020.1 + - tzdata>=2022.7 + - hypothesis>=6.46.1 ; extra == 'test' + - pytest>=7.3.2 ; extra == 'test' + - pytest-xdist>=2.2.0 ; extra == 'test' + - pyarrow>=10.0.1 ; extra == 'pyarrow' + - bottleneck>=1.3.6 ; extra == 'performance' + - numba>=0.56.4 ; extra == 'performance' + - numexpr>=2.8.4 ; extra == 'performance' + - scipy>=1.10.0 ; extra == 'computation' + - xarray>=2022.12.0 ; extra == 'computation' + - fsspec>=2022.11.0 ; extra == 'fss' + - s3fs>=2022.11.0 ; extra == 'aws' + - gcsfs>=2022.11.0 ; extra == 'gcp' + - pandas-gbq>=0.19.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.0 ; extra == 'excel' + - python-calamine>=0.1.7 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.0.5 ; extra == 'excel' + - pyarrow>=10.0.1 ; extra == 'parquet' + - pyarrow>=10.0.1 ; extra == 'feather' + - tables>=3.8.0 ; extra == 'hdf5' + - pyreadstat>=1.2.0 ; extra == 'spss' + - sqlalchemy>=2.0.0 ; extra == 'postgresql' + - psycopg2>=2.9.6 ; extra == 'postgresql' + - adbc-driver-postgresql>=0.8.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.0 ; extra == 'mysql' + - pymysql>=1.0.2 ; extra == 'mysql' + - sqlalchemy>=2.0.0 ; extra == 'sql-other' + - adbc-driver-postgresql>=0.8.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=0.8.0 ; extra == 'sql-other' + - beautifulsoup4>=4.11.2 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'xml' + - matplotlib>=3.6.3 ; extra == 'plot' + - jinja2>=3.1.2 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.3.0 ; extra == 'clipboard' + - zstandard>=0.19.0 ; extra == 'compression' + - dataframe-api-compat>=0.1.7 ; extra == 'consortium-standard' + - adbc-driver-postgresql>=0.8.0 ; extra == 'all' + - adbc-driver-sqlite>=0.8.0 ; extra == 'all' + - beautifulsoup4>=4.11.2 ; extra == 'all' + - bottleneck>=1.3.6 ; extra == 'all' + - dataframe-api-compat>=0.1.7 ; extra == 'all' + - fastparquet>=2022.12.0 ; extra == 'all' + - fsspec>=2022.11.0 ; extra == 'all' + - gcsfs>=2022.11.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.46.1 ; extra == 'all' + - jinja2>=3.1.2 ; extra == 'all' + - lxml>=4.9.2 ; extra == 'all' + - matplotlib>=3.6.3 ; extra == 'all' + - numba>=0.56.4 ; extra == 'all' + - numexpr>=2.8.4 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.0 ; extra == 'all' + - pandas-gbq>=0.19.0 ; extra == 'all' + - psycopg2>=2.9.6 ; extra == 'all' + - pyarrow>=10.0.1 ; extra == 'all' + - pymysql>=1.0.2 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.0 ; extra == 'all' + - pytest>=7.3.2 ; extra == 'all' + - pytest-xdist>=2.2.0 ; extra == 'all' + - python-calamine>=0.1.7 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.3.0 ; extra == 'all' + - scipy>=1.10.0 ; extra == 'all' + - s3fs>=2022.11.0 ; extra == 'all' + - sqlalchemy>=2.0.0 ; extra == 'all' + - tables>=3.8.0 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2022.12.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.0.5 ; extra == 'all' + - zstandard>=0.19.0 ; extra == 'all' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/40/a8/4dac1f8f8235e5d25b9955d02ff6f29396191d4e665d71122c3722ca83c5/pandas-2.3.3-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + name: pandas + version: 2.3.3 + sha256: dd7478f1463441ae4ca7308a70e90b33470fa593429f9d4c578dd00d1fa78838 + requires_dist: + - numpy>=1.22.4 ; python_full_version < '3.11' + - numpy>=1.23.2 ; python_full_version == '3.11.*' + - numpy>=1.26.0 ; python_full_version >= '3.12' + - python-dateutil>=2.8.2 + - pytz>=2020.1 + - tzdata>=2022.7 + - hypothesis>=6.46.1 ; extra == 'test' + - pytest>=7.3.2 ; extra == 'test' + - pytest-xdist>=2.2.0 ; extra == 'test' + - pyarrow>=10.0.1 ; extra == 'pyarrow' + - bottleneck>=1.3.6 ; extra == 'performance' + - numba>=0.56.4 ; extra == 'performance' + - numexpr>=2.8.4 ; extra == 'performance' + - scipy>=1.10.0 ; extra == 'computation' + - xarray>=2022.12.0 ; extra == 'computation' + - fsspec>=2022.11.0 ; extra == 'fss' + - s3fs>=2022.11.0 ; extra == 'aws' + - gcsfs>=2022.11.0 ; extra == 'gcp' + - pandas-gbq>=0.19.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.0 ; extra == 'excel' + - python-calamine>=0.1.7 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.0.5 ; extra == 'excel' + - pyarrow>=10.0.1 ; extra == 'parquet' + - pyarrow>=10.0.1 ; extra == 'feather' + - tables>=3.8.0 ; extra == 'hdf5' + - pyreadstat>=1.2.0 ; extra == 'spss' + - sqlalchemy>=2.0.0 ; extra == 'postgresql' + - psycopg2>=2.9.6 ; extra == 'postgresql' + - adbc-driver-postgresql>=0.8.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.0 ; extra == 'mysql' + - pymysql>=1.0.2 ; extra == 'mysql' + - sqlalchemy>=2.0.0 ; extra == 'sql-other' + - adbc-driver-postgresql>=0.8.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=0.8.0 ; extra == 'sql-other' + - beautifulsoup4>=4.11.2 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'xml' + - matplotlib>=3.6.3 ; extra == 'plot' + - jinja2>=3.1.2 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.3.0 ; extra == 'clipboard' + - zstandard>=0.19.0 ; extra == 'compression' + - dataframe-api-compat>=0.1.7 ; extra == 'consortium-standard' + - adbc-driver-postgresql>=0.8.0 ; extra == 'all' + - adbc-driver-sqlite>=0.8.0 ; extra == 'all' + - beautifulsoup4>=4.11.2 ; extra == 'all' + - bottleneck>=1.3.6 ; extra == 'all' + - dataframe-api-compat>=0.1.7 ; extra == 'all' + - fastparquet>=2022.12.0 ; extra == 'all' + - fsspec>=2022.11.0 ; extra == 'all' + - gcsfs>=2022.11.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.46.1 ; extra == 'all' + - jinja2>=3.1.2 ; extra == 'all' + - lxml>=4.9.2 ; extra == 'all' + - matplotlib>=3.6.3 ; extra == 'all' + - numba>=0.56.4 ; extra == 'all' + - numexpr>=2.8.4 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.0 ; extra == 'all' + - pandas-gbq>=0.19.0 ; extra == 'all' + - psycopg2>=2.9.6 ; extra == 'all' + - pyarrow>=10.0.1 ; extra == 'all' + - pymysql>=1.0.2 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.0 ; extra == 'all' + - pytest>=7.3.2 ; extra == 'all' + - pytest-xdist>=2.2.0 ; extra == 'all' + - python-calamine>=0.1.7 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.3.0 ; extra == 'all' + - scipy>=1.10.0 ; extra == 'all' + - s3fs>=2022.11.0 ; extra == 'all' + - sqlalchemy>=2.0.0 ; extra == 'all' + - tables>=3.8.0 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2022.12.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.0.5 ; extra == 'all' + - zstandard>=0.19.0 ; extra == 'all' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/85/72/530900610650f54a35a19476eca5104f38555afccda1aa11a92ee14cb21d/pandas-2.3.3-cp310-cp310-win_amd64.whl + name: pandas + version: 2.3.3 + sha256: 503cf027cf9940d2ceaa1a93cfb5f8c8c7e6e90720a2850378f0b3f3b1e06826 + requires_dist: + - numpy>=1.22.4 ; python_full_version < '3.11' + - numpy>=1.23.2 ; python_full_version == '3.11.*' + - numpy>=1.26.0 ; python_full_version >= '3.12' + - python-dateutil>=2.8.2 + - pytz>=2020.1 + - tzdata>=2022.7 + - hypothesis>=6.46.1 ; extra == 'test' + - pytest>=7.3.2 ; extra == 'test' + - pytest-xdist>=2.2.0 ; extra == 'test' + - pyarrow>=10.0.1 ; extra == 'pyarrow' + - bottleneck>=1.3.6 ; extra == 'performance' + - numba>=0.56.4 ; extra == 'performance' + - numexpr>=2.8.4 ; extra == 'performance' + - scipy>=1.10.0 ; extra == 'computation' + - xarray>=2022.12.0 ; extra == 'computation' + - fsspec>=2022.11.0 ; extra == 'fss' + - s3fs>=2022.11.0 ; extra == 'aws' + - gcsfs>=2022.11.0 ; extra == 'gcp' + - pandas-gbq>=0.19.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.0 ; extra == 'excel' + - python-calamine>=0.1.7 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.0.5 ; extra == 'excel' + - pyarrow>=10.0.1 ; extra == 'parquet' + - pyarrow>=10.0.1 ; extra == 'feather' + - tables>=3.8.0 ; extra == 'hdf5' + - pyreadstat>=1.2.0 ; extra == 'spss' + - sqlalchemy>=2.0.0 ; extra == 'postgresql' + - psycopg2>=2.9.6 ; extra == 'postgresql' + - adbc-driver-postgresql>=0.8.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.0 ; extra == 'mysql' + - pymysql>=1.0.2 ; extra == 'mysql' + - sqlalchemy>=2.0.0 ; extra == 'sql-other' + - adbc-driver-postgresql>=0.8.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=0.8.0 ; extra == 'sql-other' + - beautifulsoup4>=4.11.2 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'html' + - lxml>=4.9.2 ; extra == 'xml' + - matplotlib>=3.6.3 ; extra == 'plot' + - jinja2>=3.1.2 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.3.0 ; extra == 'clipboard' + - zstandard>=0.19.0 ; extra == 'compression' + - dataframe-api-compat>=0.1.7 ; extra == 'consortium-standard' + - adbc-driver-postgresql>=0.8.0 ; extra == 'all' + - adbc-driver-sqlite>=0.8.0 ; extra == 'all' + - beautifulsoup4>=4.11.2 ; extra == 'all' + - bottleneck>=1.3.6 ; extra == 'all' + - dataframe-api-compat>=0.1.7 ; extra == 'all' + - fastparquet>=2022.12.0 ; extra == 'all' + - fsspec>=2022.11.0 ; extra == 'all' + - gcsfs>=2022.11.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.46.1 ; extra == 'all' + - jinja2>=3.1.2 ; extra == 'all' + - lxml>=4.9.2 ; extra == 'all' + - matplotlib>=3.6.3 ; extra == 'all' + - numba>=0.56.4 ; extra == 'all' + - numexpr>=2.8.4 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.0 ; extra == 'all' + - pandas-gbq>=0.19.0 ; extra == 'all' + - psycopg2>=2.9.6 ; extra == 'all' + - pyarrow>=10.0.1 ; extra == 'all' + - pymysql>=1.0.2 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.0 ; extra == 'all' + - pytest>=7.3.2 ; extra == 'all' + - pytest-xdist>=2.2.0 ; extra == 'all' + - python-calamine>=0.1.7 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.3.0 ; extra == 'all' + - scipy>=1.10.0 ; extra == 'all' + - s3fs>=2022.11.0 ; extra == 'all' + - sqlalchemy>=2.0.0 ; extra == 'all' + - tables>=3.8.0 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2022.12.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.0.5 ; extra == 'all' + - zstandard>=0.19.0 ; extra == 'all' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/09/f8/8ce132104074f977f907442790eaae24e27bce3b3b454e82faa3237ff098/pandas-3.0.1-cp314-cp314-win_amd64.whl + name: pandas + version: 3.0.1 + sha256: 93325b0fe372d192965f4cca88d97667f49557398bbf94abdda3bf1b591dbe66 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/0b/48/aad6ec4f8d007534c091e9a7172b3ec1b1ee6d99a9cbb936b5eab6c6cf58/pandas-3.0.1-cp313-cp313-macosx_10_13_x86_64.whl + name: pandas + version: 3.0.1 + sha256: 5272627187b5d9c20e55d27caf5f2cd23e286aba25cadf73c8590e432e2b7262 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/1f/67/af63f83cd6ca603a00fe8530c10a60f0879265b8be00b5930e8e78c5b30b/pandas-3.0.1-cp311-cp311-win_amd64.whl + name: pandas + version: 3.0.1 + sha256: 84f0904a69e7365f79a0c77d3cdfccbfb05bf87847e3a51a41e1426b0edb9c79 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/2e/7c/870c7e7daec2a6c7ff2ac9e33b23317230d4e4e954b35112759ea4a924a7/pandas-3.0.1-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + name: pandas + version: 3.0.1 + sha256: 830994d7e1f31dd7e790045235605ab61cff6c94defc774547e8b7fdfbff3dc7 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/37/51/b467209c08dae2c624873d7491ea47d2b47336e5403309d433ea79c38571/pandas-3.0.1-cp312-cp312-macosx_10_13_x86_64.whl + name: pandas + version: 3.0.1 + sha256: 476f84f8c20c9f5bc47252b66b4bb25e1a9fc2fa98cead96744d8116cb85771d + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/3d/fe/89d77e424365280b79d99b3e1e7d606f5165af2f2ecfaf0c6d24c799d607/pandas-3.0.1-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + name: pandas + version: 3.0.1 + sha256: 532527a701281b9dd371e2f582ed9094f4c12dd9ffb82c0c54ee28d8ac9520c4 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/55/77/6ea82043db22cb0f2bbfe7198da3544000ddaadb12d26be36e19b03a2dc5/pandas-3.0.1-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + name: pandas + version: 3.0.1 + sha256: c1a9f55e0f46951874b863d1f3906dcb57df2d9be5c5847ba4dfb55b2c815249 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/72/3a/5b39b51c64159f470f1ca3b1c2a87da290657ca022f7cd11442606f607d1/pandas-3.0.1-cp314-cp314-macosx_11_0_arm64.whl + name: pandas + version: 3.0.1 + sha256: 3b66857e983208654294bb6477b8a63dee26b37bdd0eb34d010556e91261784f + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/75/08/67cc404b3a966b6df27b38370ddd96b3b023030b572283d035181854aac5/pandas-3.0.1-cp312-cp312-win_amd64.whl + name: pandas + version: 3.0.1 + sha256: 536232a5fe26dd989bd633e7a0c450705fdc86a207fec7254a55e9a22950fe43 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/7c/f1/e2567ffc8951ab371db2e40b2fe068e36b81d8cf3260f06ae508700e5504/pandas-3.0.1-cp312-cp312-macosx_11_0_arm64.whl + name: pandas + version: 3.0.1 + sha256: 0ab749dfba921edf641d4036c4c21c0b3ea70fea478165cb98a998fb2a261955 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/a8/14/5990826f779f79148ae9d3a2c39593dc04d61d5d90541e71b5749f35af95/pandas-3.0.1-cp313-cp313-macosx_11_0_arm64.whl + name: pandas + version: 3.0.1 + sha256: 661e0f665932af88c7877f31da0dc743fe9c8f2524bdffe23d24fdcb67ef9d56 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/bb/8b/4bb774a998b97e6c2fd62a9e6cfdaae133b636fd1c468f92afb4ae9a447a/pandas-3.0.1-cp314-cp314-macosx_10_15_x86_64.whl + name: pandas + version: 3.0.1 + sha256: 99d0f92ed92d3083d140bf6b97774f9f13863924cf3f52a70711f4e7588f9d0a + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/c1/27/90683c7122febeefe84a56f2cde86a9f05f68d53885cebcc473298dfc33e/pandas-3.0.1-cp311-cp311-macosx_11_0_arm64.whl + name: pandas + version: 3.0.1 + sha256: 24ba315ba3d6e5806063ac6eb717504e499ce30bd8c236d8693a5fd3f084c796 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/d6/7d/216a1588b65a7aa5f4535570418a599d943c85afb1d95b0876fc00aa1468/pandas-3.0.1-cp313-cp313-win_amd64.whl + name: pandas + version: 3.0.1 + sha256: 9fea306c783e28884c29057a1d9baa11a349bbf99538ec1da44c8476563d1b25 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/f2/85/ab6d04733a7d6ff32bfc8382bf1b07078228f5d6ebec5266b91bfc5c4ff7/pandas-3.0.1-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl + name: pandas + version: 3.0.1 + sha256: 1ff8cf1d2896e34343197685f432450ec99a85ba8d90cce2030c5eee2ef98791 + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/ff/07/c7087e003ceee9b9a82539b40414ec557aa795b584a1a346e89180853d79/pandas-3.0.1-cp311-cp311-macosx_10_9_x86_64.whl + name: pandas + version: 3.0.1 + sha256: de09668c1bf3b925c07e5762291602f0d789eca1b3a781f99c1c78f6cac0e7ea + requires_dist: + - numpy>=1.26.0 ; python_full_version < '3.14' + - numpy>=2.3.3 ; python_full_version >= '3.14' + - python-dateutil>=2.8.2 + - tzdata ; sys_platform == 'win32' + - tzdata ; sys_platform == 'emscripten' + - hypothesis>=6.116.0 ; extra == 'test' + - pytest>=8.3.4 ; extra == 'test' + - pytest-xdist>=3.6.1 ; extra == 'test' + - pyarrow>=13.0.0 ; extra == 'pyarrow' + - bottleneck>=1.4.2 ; extra == 'performance' + - numba>=0.60.0 ; extra == 'performance' + - numexpr>=2.10.2 ; extra == 'performance' + - scipy>=1.14.1 ; extra == 'computation' + - xarray>=2024.10.0 ; extra == 'computation' + - fsspec>=2024.10.0 ; extra == 'fss' + - s3fs>=2024.10.0 ; extra == 'aws' + - gcsfs>=2024.10.0 ; extra == 'gcp' + - odfpy>=1.4.1 ; extra == 'excel' + - openpyxl>=3.1.5 ; extra == 'excel' + - python-calamine>=0.3.0 ; extra == 'excel' + - pyxlsb>=1.0.10 ; extra == 'excel' + - xlrd>=2.0.1 ; extra == 'excel' + - xlsxwriter>=3.2.0 ; extra == 'excel' + - pyarrow>=13.0.0 ; extra == 'parquet' + - pyarrow>=13.0.0 ; extra == 'feather' + - pyiceberg>=0.8.1 ; extra == 'iceberg' + - tables>=3.10.1 ; extra == 'hdf5' + - pyreadstat>=1.2.8 ; extra == 'spss' + - sqlalchemy>=2.0.36 ; extra == 'postgresql' + - psycopg2>=2.9.10 ; extra == 'postgresql' + - adbc-driver-postgresql>=1.2.0 ; extra == 'postgresql' + - sqlalchemy>=2.0.36 ; extra == 'mysql' + - pymysql>=1.1.1 ; extra == 'mysql' + - sqlalchemy>=2.0.36 ; extra == 'sql-other' + - adbc-driver-postgresql>=1.2.0 ; extra == 'sql-other' + - adbc-driver-sqlite>=1.2.0 ; extra == 'sql-other' + - beautifulsoup4>=4.12.3 ; extra == 'html' + - html5lib>=1.1 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'html' + - lxml>=5.3.0 ; extra == 'xml' + - matplotlib>=3.9.3 ; extra == 'plot' + - jinja2>=3.1.5 ; extra == 'output-formatting' + - tabulate>=0.9.0 ; extra == 'output-formatting' + - pyqt5>=5.15.9 ; extra == 'clipboard' + - qtpy>=2.4.2 ; extra == 'clipboard' + - zstandard>=0.23.0 ; extra == 'compression' + - pytz>=2024.2 ; extra == 'timezone' + - adbc-driver-postgresql>=1.2.0 ; extra == 'all' + - adbc-driver-sqlite>=1.2.0 ; extra == 'all' + - beautifulsoup4>=4.12.3 ; extra == 'all' + - bottleneck>=1.4.2 ; extra == 'all' + - fastparquet>=2024.11.0 ; extra == 'all' + - fsspec>=2024.10.0 ; extra == 'all' + - gcsfs>=2024.10.0 ; extra == 'all' + - html5lib>=1.1 ; extra == 'all' + - hypothesis>=6.116.0 ; extra == 'all' + - jinja2>=3.1.5 ; extra == 'all' + - lxml>=5.3.0 ; extra == 'all' + - matplotlib>=3.9.3 ; extra == 'all' + - numba>=0.60.0 ; extra == 'all' + - numexpr>=2.10.2 ; extra == 'all' + - odfpy>=1.4.1 ; extra == 'all' + - openpyxl>=3.1.5 ; extra == 'all' + - psycopg2>=2.9.10 ; extra == 'all' + - pyarrow>=13.0.0 ; extra == 'all' + - pyiceberg>=0.8.1 ; extra == 'all' + - pymysql>=1.1.1 ; extra == 'all' + - pyqt5>=5.15.9 ; extra == 'all' + - pyreadstat>=1.2.8 ; extra == 'all' + - pytest>=8.3.4 ; extra == 'all' + - pytest-xdist>=3.6.1 ; extra == 'all' + - python-calamine>=0.3.0 ; extra == 'all' + - pytz>=2024.2 ; extra == 'all' + - pyxlsb>=1.0.10 ; extra == 'all' + - qtpy>=2.4.2 ; extra == 'all' + - scipy>=1.14.1 ; extra == 'all' + - s3fs>=2024.10.0 ; extra == 'all' + - sqlalchemy>=2.0.36 ; extra == 'all' + - tables>=3.10.1 ; extra == 'all' + - tabulate>=0.9.0 ; extra == 'all' + - xarray>=2024.10.0 ; extra == 'all' + - xlrd>=2.0.1 ; extra == 'all' + - xlsxwriter>=3.2.0 ; extra == 'all' + - zstandard>=0.23.0 ; extra == 'all' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl + name: pandocfilters + version: 1.5.1 + sha256: 93be382804a9cdb0a7267585f157e5d1731bbe5545a85b268d6f5fe6232de2bc + requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*' +- pypi: https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl + name: parso + version: 0.8.6 + sha256: 2c549f800b70a5c4952197248825584cb00f033b29c692671d3bf08bf380baff + requires_dist: + - pytest ; extra == 'testing' + - docopt ; extra == 'testing' + - flake8==5.0.4 ; extra == 'qa' + - zuban==0.5.1 ; extra == 'qa' + - types-setuptools==67.2.0.1 ; extra == 'qa' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl + name: patsy + version: 1.0.2 + sha256: 37bfddbc58fcf0362febb5f54f10743f8b21dd2aa73dec7e7ef59d1b02ae668a + requires_dist: + - numpy>=1.4 + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - scipy ; extra == 'test' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl + name: pexpect + version: 4.9.0 + sha256: 7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523 + requires_dist: + - ptyprocess>=0.5 +- pypi: https://files.pythonhosted.org/packages/05/30/5db1236b0d6313f03ebf97f5e17cda9ca060f524b2fcc875149a8360b21c/pillow-12.1.1-cp314-cp314-macosx_11_0_arm64.whl + name: pillow + version: 12.1.1 + sha256: f7ed2c6543bad5a7d5530eb9e78c53132f93dfa44a28492db88b41cdab885202 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/07/d3/8df65da0d4df36b094351dce696f2989bec731d4f10e743b1c5f4da4d3bf/pillow-12.1.1-cp312-cp312-macosx_10_13_x86_64.whl + name: pillow + version: 12.1.1 + sha256: ab323b787d6e18b3d91a72fc99b1a2c28651e4358749842b8f8dfacd28ef2052 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/0c/7b/f9b09a7804ec7336effb96c26d37c29d27225783dc1501b7d62dcef6ae25/pillow-12.1.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: pillow + version: 12.1.1 + sha256: 9f51079765661884a486727f0729d29054242f74b46186026582b4e4769918e4 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/14/a1/16c4b823838ba4c9c52c0e6bbda903a3fe5a1bdbf1b8eb4fff7156f3e318/pillow-12.1.1-cp313-cp313-macosx_10_13_x86_64.whl + name: pillow + version: 12.1.1 + sha256: 6c6db3b84c87d48d0088943bf33440e0c42370b99b1c2a7989216f7b42eede60 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/1d/30/5bd3d794762481f8c8ae9c80e7b76ecea73b916959eb587521358ef0b2f9/pillow-12.1.1-cp310-cp310-macosx_10_10_x86_64.whl + name: pillow + version: 12.1.1 + sha256: 1f1625b72740fdda5d77b4def688eb8fd6490975d06b909fd19f13f391e077e0 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/2b/46/5da1ec4a5171ee7bf1a0efa064aba70ba3d6e0788ce3f5acd1375d23c8c0/pillow-12.1.1-cp311-cp311-macosx_10_10_x86_64.whl + name: pillow + version: 12.1.1 + sha256: e879bb6cd5c73848ef3b2b48b8af9ff08c5b71ecda8048b7dd22d8a33f60be32 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/31/03/bef822e4f2d8f9d7448c133d0a18185d3cce3e70472774fffefe8b0ed562/pillow-12.1.1-cp311-cp311-win_amd64.whl + name: pillow + version: 12.1.1 + sha256: fbfa2a7c10cc2623f412753cddf391c7f971c52ca40a3f65dc5039b2939e8563 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3d/17/688626d192d7261bbbf98846fc98995726bddc2c945344b65bec3a29d731/pillow-12.1.1-cp312-cp312-win_amd64.whl + name: pillow + version: 12.1.1 + sha256: 21329ec8c96c6e979cd0dfd29406c40c1d52521a90544463057d2aaa937d66a6 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3f/eb/b0834ad8b583d7d9d42b80becff092082a1c3c156bb582590fcc973f1c7c/pillow-12.1.1-cp313-cp313-win_amd64.whl + name: pillow + version: 12.1.1 + sha256: 344cf1e3dab3be4b1fa08e449323d98a2a3f819ad20f4b22e77a0ede31f0faa1 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/40/72/4c245f7d1044b67affc7f134a09ea619d4895333d35322b775b928180044/pillow-12.1.1-cp314-cp314-win_amd64.whl + name: pillow + version: 12.1.1 + sha256: 50480dcd74fa63b8e78235957d302d98d98d82ccbfac4c7e12108ba9ecbdba15 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/59/04/dc5c3f297510ba9a6837cbb318b87dd2b8f73eb41a43cc63767f65cb599c/pillow-12.1.1-cp314-cp314-macosx_10_15_x86_64.whl + name: pillow + version: 12.1.1 + sha256: 2815a87ab27848db0321fb78c7f0b2c8649dee134b7f2b80c6a45c6831d75ccd + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/71/24/538bff45bde96535d7d998c6fed1a751c75ac7c53c37c90dc2601b243893/pillow-12.1.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: pillow + version: 12.1.1 + sha256: 47b94983da0c642de92ced1702c5b6c292a84bd3a8e1d1702ff923f183594717 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/78/93/a29e9bc02d1cf557a834da780ceccd54e02421627200696fcf805ebdc3fb/pillow-12.1.1-cp311-cp311-macosx_11_0_arm64.whl + name: pillow + version: 12.1.1 + sha256: 365b10bb9417dd4498c0e3b128018c4a624dc11c7b97d8cc54effe3b096f4c38 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a2/c8/46dfeac5825e600579157eea177be43e2f7ff4a99da9d0d0a49533509ac5/pillow-12.1.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: pillow + version: 12.1.1 + sha256: 597bd9c8419bc7c6af5604e55847789b69123bbe25d65cc6ad3012b4f3c98d8b + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/bb/ad/ad9dc98ff24f485008aa5cdedaf1a219876f6f6c42a4626c08bc4e80b120/pillow-12.1.1-cp313-cp313-macosx_11_0_arm64.whl + name: pillow + version: 12.1.1 + sha256: 8b7e5304e34942bf62e15184219a7b5ad4ff7f3bb5cca4d984f37df1a0e1aee2 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/bd/c1/aab9e8f3eeb4490180e357955e15c2ef74b31f64790ff356c06fb6cf6d84/pillow-12.1.1-cp310-cp310-macosx_11_0_arm64.whl + name: pillow + version: 12.1.1 + sha256: 178aa072084bd88ec759052feca8e56cbb14a60b39322b99a049e58090479713 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d1/ee/c85a38a9ab92037a75615aba572c85ea51e605265036e00c5b67dfafbfe2/pillow-12.1.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: pillow + version: 12.1.1 + sha256: a37691702ed687799de29a518d63d4682d9016932db66d4e90c345831b02fb4e + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d6/71/5026395b290ff404b836e636f51d7297e6c83beceaa87c592718747e670f/pillow-12.1.1-cp312-cp312-macosx_11_0_arm64.whl + name: pillow + version: 12.1.1 + sha256: adebb5bee0f0af4909c30db0d890c773d1a92ffe83da908e2e9e720f8edf3984 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f8/f9/9f6b01c0881d7036063aa6612ef04c0e2cad96be21325a1e92d0203f8e91/pillow-12.1.1-cp310-cp310-win_amd64.whl + name: pillow + version: 12.1.1 + sha256: c6008de247150668a705a6338156efb92334113421ceecf7438a12c9a12dab23 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ff/79/6df7b2ee763d619cda2fb4fea498e5f79d984dae304d45a8999b80d6cf5c/pillow-12.1.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: pillow + version: 12.1.1 + sha256: 7aac39bcf8d4770d089588a2e1dd111cbaa42df5a94be3114222057d68336bd0 + requires_dist: + - furo ; extra == 'docs' + - olefile ; extra == 'docs' + - sphinx>=8.2 ; extra == 'docs' + - sphinx-autobuild ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - sphinx-inline-tabs ; extra == 'docs' + - sphinxext-opengraph ; extra == 'docs' + - olefile ; extra == 'fpx' + - olefile ; extra == 'mic' + - arro3-compute ; extra == 'test-arrow' + - arro3-core ; extra == 'test-arrow' + - nanoarrow ; extra == 'test-arrow' + - pyarrow ; extra == 'test-arrow' + - check-manifest ; extra == 'tests' + - coverage>=7.4.2 ; extra == 'tests' + - defusedxml ; extra == 'tests' + - markdown2 ; extra == 'tests' + - olefile ; extra == 'tests' + - packaging ; extra == 'tests' + - pyroma>=5 ; extra == 'tests' + - pytest ; extra == 'tests' + - pytest-cov ; extra == 'tests' + - pytest-timeout ; extra == 'tests' + - pytest-xdist ; extra == 'tests' + - trove-classifiers>=2024.10.12 ; extra == 'tests' + - defusedxml ; extra == 'xmp' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl + name: platformdirs + version: 4.9.4 + sha256: 68a9a4619a666ea6439f2ff250c12a853cd1cbd5158d258bd824a7df6be2f868 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/58/f3/a49d3281cc7275164ecf89ad3497556b11d9661faa119becdf7f9d3b2125/plotly-4.0.0-py2.py3-none-any.whl + name: plotly + version: 4.0.0 + sha256: b4ae32398e5b862e6d65c8ae8579044df31fd989174f77e25ad91952f3aa5c78 + requires_dist: + - retrying>=1.3.3 + - six +- pypi: https://files.pythonhosted.org/packages/52/d2/c6e44dba74f17c6216ce1b56044a9b93a929f1c2d5bdaff892512b260f5e/plotly-6.6.0-py3-none-any.whl + name: plotly + version: 6.6.0 + sha256: 8d6daf0f87412e0c0bfe72e809d615217ab57cc715899a1e5145135a7800d1d0 + requires_dist: + - narwhals>=1.15.1 + - packaging + - numpy ; extra == 'express' + - kaleido>=1.1.0 ; extra == 'kaleido' + - pytest ; extra == 'dev-core' + - requests ; extra == 'dev-core' + - ruff==0.11.12 ; extra == 'dev-core' + - plotly[dev-core] ; extra == 'dev-build' + - build ; extra == 'dev-build' + - jupyter ; extra == 'dev-build' + - plotly[dev-build] ; extra == 'dev-optional' + - plotly[kaleido] ; extra == 'dev-optional' + - anywidget ; extra == 'dev-optional' + - colorcet ; extra == 'dev-optional' + - fiona<=1.9.6 ; python_full_version < '3.9' and extra == 'dev-optional' + - geopandas ; extra == 'dev-optional' + - inflect ; extra == 'dev-optional' + - numpy ; extra == 'dev-optional' + - orjson ; extra == 'dev-optional' + - pandas ; extra == 'dev-optional' + - pdfrw ; extra == 'dev-optional' + - pillow ; extra == 'dev-optional' + - plotly-geo ; extra == 'dev-optional' + - polars[timezone] ; extra == 'dev-optional' + - pyarrow ; extra == 'dev-optional' + - pyshp ; extra == 'dev-optional' + - pytz ; extra == 'dev-optional' + - scikit-image ; extra == 'dev-optional' + - scipy ; extra == 'dev-optional' + - shapely ; extra == 'dev-optional' + - statsmodels ; extra == 'dev-optional' + - vaex ; python_full_version < '3.10' and extra == 'dev-optional' + - xarray ; extra == 'dev-optional' + - plotly[dev-optional] ; extra == 'dev' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl + name: pluggy + version: 1.6.0 + sha256: e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746 + requires_dist: + - pre-commit ; extra == 'dev' + - tox ; extra == 'dev' + - pytest ; extra == 'testing' + - pytest-benchmark ; extra == 'testing' + - coverage ; extra == 'testing' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/74/c3/24a2f845e3917201628ecaba4f18bab4d18a337834c1df2a159ee9d22a42/prometheus_client-0.24.1-py3-none-any.whl + name: prometheus-client + version: 0.24.1 + sha256: 150db128af71a5c2482b36e588fc8a6b95e498750da4b17065947c16070f4055 + requires_dist: + - twisted ; extra == 'twisted' + - aiohttp ; extra == 'aiohttp' + - django ; extra == 'django' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl + name: prompt-toolkit + version: 3.0.52 + sha256: 9aac639a3bbd33284347de5ad8d68ecc044b91a762dc39b7c21095fcd6a19955 + requires_dist: + - wcwidth + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/5c/6c/94d8e520b20a2502e508e1c558f338061cf409cbee78fd6a3a5c6ae812bd/property_cached-1.6.4-py2.py3-none-any.whl + name: property-cached + version: 1.6.4 + sha256: 135fc059ec969c1646424a0db15e7fbe1b5f8c36c0006d0b3c91ba568c11e7d8 + requires_python: '>=3.5' +- pypi: https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl + name: psutil + version: 7.2.2 + sha256: 1a7b04c10f32cc88ab39cbf606e117fd74721c831c98a27dc04578deb0c16979 + requires_dist: + - psleak ; extra == 'dev' + - pytest ; extra == 'dev' + - pytest-instafail ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - setuptools ; extra == 'dev' + - abi3audit ; extra == 'dev' + - black ; extra == 'dev' + - check-manifest ; extra == 'dev' + - coverage ; extra == 'dev' + - packaging ; extra == 'dev' + - pylint ; extra == 'dev' + - pyperf ; extra == 'dev' + - pypinfo ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - requests ; extra == 'dev' + - rstcheck ; extra == 'dev' + - ruff ; extra == 'dev' + - sphinx ; extra == 'dev' + - sphinx-rtd-theme ; extra == 'dev' + - toml-sort ; extra == 'dev' + - twine ; extra == 'dev' + - validate-pyproject[all] ; extra == 'dev' + - virtualenv ; extra == 'dev' + - vulture ; extra == 'dev' + - wheel ; extra == 'dev' + - colorama ; os_name == 'nt' and extra == 'dev' + - pyreadline3 ; os_name == 'nt' and extra == 'dev' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - psleak ; extra == 'test' + - pytest ; extra == 'test' + - pytest-instafail ; extra == 'test' + - pytest-xdist ; extra == 'test' + - setuptools ; extra == 'test' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl + name: psutil + version: 7.2.2 + sha256: eb7e81434c8d223ec4a219b5fc1c47d0417b12be7ea866e24fb5ad6e84b3d988 + requires_dist: + - psleak ; extra == 'dev' + - pytest ; extra == 'dev' + - pytest-instafail ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - setuptools ; extra == 'dev' + - abi3audit ; extra == 'dev' + - black ; extra == 'dev' + - check-manifest ; extra == 'dev' + - coverage ; extra == 'dev' + - packaging ; extra == 'dev' + - pylint ; extra == 'dev' + - pyperf ; extra == 'dev' + - pypinfo ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - requests ; extra == 'dev' + - rstcheck ; extra == 'dev' + - ruff ; extra == 'dev' + - sphinx ; extra == 'dev' + - sphinx-rtd-theme ; extra == 'dev' + - toml-sort ; extra == 'dev' + - twine ; extra == 'dev' + - validate-pyproject[all] ; extra == 'dev' + - virtualenv ; extra == 'dev' + - vulture ; extra == 'dev' + - wheel ; extra == 'dev' + - colorama ; os_name == 'nt' and extra == 'dev' + - pyreadline3 ; os_name == 'nt' and extra == 'dev' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - psleak ; extra == 'test' + - pytest ; extra == 'test' + - pytest-instafail ; extra == 'test' + - pytest-xdist ; extra == 'test' + - setuptools ; extra == 'test' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl + name: psutil + version: 7.2.2 + sha256: 076a2d2f923fd4821644f5ba89f059523da90dc9014e85f8e45a5774ca5bc6f9 + requires_dist: + - psleak ; extra == 'dev' + - pytest ; extra == 'dev' + - pytest-instafail ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - setuptools ; extra == 'dev' + - abi3audit ; extra == 'dev' + - black ; extra == 'dev' + - check-manifest ; extra == 'dev' + - coverage ; extra == 'dev' + - packaging ; extra == 'dev' + - pylint ; extra == 'dev' + - pyperf ; extra == 'dev' + - pypinfo ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - requests ; extra == 'dev' + - rstcheck ; extra == 'dev' + - ruff ; extra == 'dev' + - sphinx ; extra == 'dev' + - sphinx-rtd-theme ; extra == 'dev' + - toml-sort ; extra == 'dev' + - twine ; extra == 'dev' + - validate-pyproject[all] ; extra == 'dev' + - virtualenv ; extra == 'dev' + - vulture ; extra == 'dev' + - wheel ; extra == 'dev' + - colorama ; os_name == 'nt' and extra == 'dev' + - pyreadline3 ; os_name == 'nt' and extra == 'dev' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - psleak ; extra == 'test' + - pytest ; extra == 'test' + - pytest-instafail ; extra == 'test' + - pytest-xdist ; extra == 'test' + - setuptools ; extra == 'test' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl + name: psutil + version: 7.2.2 + sha256: ed0cace939114f62738d808fdcecd4c869222507e266e574799e9c0faa17d486 + requires_dist: + - psleak ; extra == 'dev' + - pytest ; extra == 'dev' + - pytest-instafail ; extra == 'dev' + - pytest-xdist ; extra == 'dev' + - setuptools ; extra == 'dev' + - abi3audit ; extra == 'dev' + - black ; extra == 'dev' + - check-manifest ; extra == 'dev' + - coverage ; extra == 'dev' + - packaging ; extra == 'dev' + - pylint ; extra == 'dev' + - pyperf ; extra == 'dev' + - pypinfo ; extra == 'dev' + - pytest-cov ; extra == 'dev' + - requests ; extra == 'dev' + - rstcheck ; extra == 'dev' + - ruff ; extra == 'dev' + - sphinx ; extra == 'dev' + - sphinx-rtd-theme ; extra == 'dev' + - toml-sort ; extra == 'dev' + - twine ; extra == 'dev' + - validate-pyproject[all] ; extra == 'dev' + - virtualenv ; extra == 'dev' + - vulture ; extra == 'dev' + - wheel ; extra == 'dev' + - colorama ; os_name == 'nt' and extra == 'dev' + - pyreadline3 ; os_name == 'nt' and extra == 'dev' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'dev' + - psleak ; extra == 'test' + - pytest ; extra == 'test' + - pytest-instafail ; extra == 'test' + - pytest-xdist ; extra == 'test' + - setuptools ; extra == 'test' + - pywin32 ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wheel ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + - wmi ; implementation_name != 'pypy' and os_name == 'nt' and extra == 'test' + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl + name: ptyprocess + version: 0.7.0 + sha256: 4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35 +- pypi: https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl + name: pure-eval + version: 0.2.3 + sha256: 1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0 + requires_dist: + - pytest ; extra == 'tests' +- pypi: https://files.pythonhosted.org/packages/fd/04/9aea6b3ed8f1cba49c0f1cab70ff9e0cc5ff03555ffe8a41a2558047358b/pvlib-0.13.1-py3-none-any.whl + name: pvlib + version: 0.13.1 + sha256: 7de5c71b2f6b92f66eb4ac5d7d26a145c209cc6036dd1c90a7a323bc097b3e46 + requires_dist: + - numpy>=1.21.2 + - pandas>=1.3.3 + - pytz + - requests + - scipy>=1.7.2 + - h5py + - cython ; extra == 'optional' + - ephem ; extra == 'optional' + - nrel-pysam ; extra == 'optional' + - numba>=0.17.0 ; extra == 'optional' + - solarfactors ; extra == 'optional' + - statsmodels ; extra == 'optional' + - ipython ; extra == 'doc' + - pickleshare ; extra == 'doc' + - matplotlib ; extra == 'doc' + - sphinx==7.3.7 ; extra == 'doc' + - pydata-sphinx-theme==0.15.4 ; extra == 'doc' + - sphinx-gallery ; extra == 'doc' + - docutils==0.21 ; extra == 'doc' + - pillow ; extra == 'doc' + - sphinx-toggleprompt==0.5.2 ; extra == 'doc' + - sphinx-favicon ; extra == 'doc' + - solarfactors ; extra == 'doc' + - sphinx-hoverxref~=1.4.2 ; extra == 'doc' + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-mock ; extra == 'test' + - requests-mock ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-rerunfailures ; extra == 'test' + - pytest-remotedata ; extra == 'test' + - packaging ; extra == 'test' + - pvlib[doc,optional,test] ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/33/f0/7f5bcda6df968f1c8d178920c0202f844898d607407de5e1524443e890c4/pvlib-0.15.0-py3-none-any.whl + name: pvlib + version: 0.15.0 + sha256: d40aed5188b75e2ac21299af506a91ea1fac013d837caa73e20e27dd49239c5a + requires_dist: + - numpy>=1.21.2 + - pandas>=1.3.3 + - pytz + - requests + - scipy>=1.7.2 + - h5py + - cython ; extra == 'optional' + - ephem ; extra == 'optional' + - nrel-pysam ; extra == 'optional' + - numba>=0.17.0 ; extra == 'optional' + - solarfactors>=1.6.1 ; extra == 'optional' + - statsmodels ; extra == 'optional' + - ipython ; extra == 'doc' + - pickleshare ; extra == 'doc' + - matplotlib ; extra == 'doc' + - sphinx==7.3.7 ; extra == 'doc' + - pydata-sphinx-theme==0.15.4 ; extra == 'doc' + - sphinx-gallery ; extra == 'doc' + - docutils==0.21 ; extra == 'doc' + - pillow ; extra == 'doc' + - sphinx-toggleprompt==0.5.2 ; extra == 'doc' + - sphinx-favicon ; extra == 'doc' + - solarfactors>=1.6.1 ; extra == 'doc' + - sphinx-hoverxref~=1.4.2 ; extra == 'doc' + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-mock ; extra == 'test' + - requests-mock ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-rerunfailures ; extra == 'test' + - pytest-remotedata ; extra == 'test' + - packaging ; extra == 'test' + - pvlib[doc,optional,test] ; extra == 'all' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl + name: pycodestyle + version: 2.14.0 + sha256: dd6bf7cb4ee77f8e016f9c8e74a35ddd9f67e1d5fd4184d86c3b98e07099f42d + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl + name: pycparser + version: '3.0' + sha256: b727414169a36b7d524c1c3e31839a521725078d7b2ff038656844266160a992 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl + name: pyflakes + version: 3.4.0 + sha256: f742a7dbd0d9cb9ea41e9a24a918996e8170c799fa528688d40dd582c8265f4f + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl + name: pygments + version: 2.19.2 + sha256: 86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b + requires_dist: + - colorama>=0.4.6 ; extra == 'windows-terminal' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl + name: pyparsing + version: 3.3.2 + sha256: 850ba148bd908d7e2411587e247a1e4f0327839c40e2e5e6d05a007ecc69911d + requires_dist: + - railroad-diagrams ; extra == 'diagrams' + - jinja2 ; extra == 'diagrams' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl + name: pytest + version: 9.0.2 + sha256: 711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b + requires_dist: + - colorama>=0.4 ; sys_platform == 'win32' + - exceptiongroup>=1 ; python_full_version < '3.11' + - iniconfig>=1.0.1 + - packaging>=22 + - pluggy>=1.5,<2 + - pygments>=2.7.2 + - tomli>=1 ; python_full_version < '3.11' + - argcomplete ; extra == 'dev' + - attrs>=19.2 ; extra == 'dev' + - hypothesis>=3.56 ; extra == 'dev' + - mock ; extra == 'dev' + - requests ; extra == 'dev' + - setuptools ; extra == 'dev' + - xmlschema ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ee/49/1377b49de7d0c1ce41292161ea0f721913fa8722c19fb9c1e3aa0367eecb/pytest_cov-7.0.0-py3-none-any.whl + name: pytest-cov + version: 7.0.0 + sha256: 3b8e9558b16cc1479da72058bdecf8073661c7f57f7d3c5f22a1c23507f2d861 + requires_dist: + - coverage[toml]>=7.10.6 + - pluggy>=1.2 + - pytest>=7 + - process-tests ; extra == 'testing' + - pytest-xdist ; extra == 'testing' + - virtualenv ; extra == 'testing' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/5a/cc/06253936f4a7fa2e0f48dfe6d851d9c56df896a9ab09ac019d70b760619c/pytest_mock-3.15.1-py3-none-any.whl + name: pytest-mock + version: 3.15.1 + sha256: 0a25e2eb88fe5168d535041d09a4529a188176ae608a6d249ee65abc0949630d + requires_dist: + - pytest>=6.2.5 + - pre-commit ; extra == 'dev' + - pytest-asyncio ; extra == 'dev' + - tox ; extra == 'dev' + requires_python: '>=3.9' +- conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.10.20-h3c07f61_0_cpython.conda + sha256: 8ff2ce308faf2588b69c65b120293f59a8f2577b772b34df4e817d220b09e081 + md5: 5d4e2b00d99feacd026859b7fa239dc0 + depends: + - __glibc >=2.17,<3.0.a0 + - bzip2 >=1.0.8,<2.0a0 + - ld_impl_linux-64 >=2.36.1 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.4,<4.0a0 + - libgcc >=14 + - liblzma >=5.8.2,<6.0a0 + - libnsl >=2.0.1,<2.1.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libuuid >=2.41.3,<3.0a0 + - libxcrypt >=4.4.36 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.10.* *_cp310 + license: Python-2.0 + purls: [] + size: 25455342 + timestamp: 1772729810280 +- conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.11.15-hd63d673_0_cpython.conda + sha256: bf6a32c69889d38482436a786bea32276756cedf0e9805cc856ffd088e8d00f0 + md5: a5ebcefec0c12a333bcd6d7bf3bddc1f + depends: + - __glibc >=2.17,<3.0.a0 + - bzip2 >=1.0.8,<2.0a0 + - ld_impl_linux-64 >=2.36.1 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - libgcc >=14 + - liblzma >=5.8.2,<6.0a0 + - libnsl >=2.0.1,<2.1.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libuuid >=2.41.3,<3.0a0 + - libxcrypt >=4.4.36 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.11.* *_cp311 + license: Python-2.0 + purls: [] + size: 30949404 + timestamp: 1772730362552 +- conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.12.13-hd63d673_0_cpython.conda + sha256: a44655c1c3e1d43ed8704890a91e12afd68130414ea2c0872e154e5633a13d7e + md5: 7eccb41177e15cc672e1babe9056018e + depends: + - __glibc >=2.17,<3.0.a0 + - bzip2 >=1.0.8,<2.0a0 + - ld_impl_linux-64 >=2.36.1 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - libgcc >=14 + - liblzma >=5.8.2,<6.0a0 + - libnsl >=2.0.1,<2.1.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libuuid >=2.41.3,<3.0a0 + - libxcrypt >=4.4.36 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.12.* *_cp312 + license: Python-2.0 + purls: [] + size: 31608571 + timestamp: 1772730708989 +- conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.12-hc97d973_100_cp313.conda + build_number: 100 + sha256: 8a08fe5b7cb5a28aa44e2994d18dbf77f443956990753a4ca8173153ffb6eb56 + md5: 4c875ed0e78c2d407ec55eadffb8cf3d + depends: + - __glibc >=2.17,<3.0.a0 + - bzip2 >=1.0.8,<2.0a0 + - ld_impl_linux-64 >=2.36.1 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - libgcc >=14 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libuuid >=2.41.3,<3.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.13.* *_cp313 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + license: Python-2.0 + purls: [] + size: 37364553 + timestamp: 1770272309861 + python_site_packages_path: lib/python3.13/site-packages +- conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.3-h32b2ec7_101_cp314.conda + build_number: 101 + sha256: cb0628c5f1732f889f53a877484da98f5a0e0f47326622671396fb4f2b0cd6bd + md5: c014ad06e60441661737121d3eae8a60 + depends: + - __glibc >=2.17,<3.0.a0 + - bzip2 >=1.0.8,<2.0a0 + - ld_impl_linux-64 >=2.36.1 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - libgcc >=14 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libuuid >=2.41.3,<3.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.14.* *_cp314 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - zstd >=1.5.7,<1.6.0a0 + license: Python-2.0 + purls: [] + size: 36702440 + timestamp: 1770675584356 + python_site_packages_path: lib/python3.14/site-packages +- conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.10.20-hea035f4_0_cpython.conda + sha256: b6b9d6a85003b21ac17cc1485e196906bd704759caaab1315f6f8eeb85f26202 + md5: bc2a1cfdea76213972b98c65be1e2023 + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.4,<4.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.10.* *_cp310 + license: Python-2.0 + purls: [] + size: 13083662 + timestamp: 1772730522090 +- conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.11.15-ha9537fe_0_cpython.conda + sha256: e02e12cd8d391f18bb3bf91d07e16b993592ec0d76ee37cf639390b766e0e687 + md5: 93b802a91de90b2c17b808608726bf45 + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.11.* *_cp311 + license: Python-2.0 + purls: [] + size: 15664115 + timestamp: 1772730794934 +- conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.12.13-ha9537fe_0_cpython.conda + sha256: fb592ceb1bc247d19247d5535083da4a79721553e29e1290f5d81c07d4f086b5 + md5: ec05996c0d914a4e98ee3c7d789083f8 + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.12.* *_cp312 + license: Python-2.0 + purls: [] + size: 13672169 + timestamp: 1772730464626 +- conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.13.12-h894a449_100_cp313.conda + build_number: 100 + sha256: 9548dcf58cf6045aa4aa1f2f3fa6110115ca616a8d5fa142a24081d2b9d91291 + md5: 99b1fa1fe8a8ab58224969f4568aadca + depends: + - __osx >=10.13 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.13.* *_cp313 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + license: Python-2.0 + purls: [] + size: 17570178 + timestamp: 1770272361922 + python_site_packages_path: lib/python3.13/site-packages +- conda: https://conda.anaconda.org/conda-forge/osx-64/python-3.14.3-h4f44bb5_101_cp314.conda + build_number: 101 + sha256: f64e357aa0168a201c9b3eedf500d89a8550d6631d26a95590b12de61f8fd660 + md5: 030ec23658b941438ac42303aff0db2b + depends: + - __osx >=10.13 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.14.* *_cp314 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - zstd >=1.5.7,<1.6.0a0 + license: Python-2.0 + purls: [] + size: 14387288 + timestamp: 1770676578632 + python_site_packages_path: lib/python3.14/site-packages +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.10.20-h1b19095_0_cpython.conda + sha256: f0f6fcbb6cfdee5a6b9c03b5b94d2bbe737f3b17a618006c7685cc48992ae667 + md5: 55ec25b0d09379eb11c32dbe09ee28c4 + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.4,<4.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.10.* *_cp310 + license: Python-2.0 + purls: [] + size: 12468674 + timestamp: 1772730636766 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.11.15-h8561d8f_0_cpython.conda + sha256: 9a846065863925b2562126a5c6fecd7a972e84aaa4de9e686ad3715ca506acfa + md5: 49c7d96c58b969585cf09fb01d74e08e + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.11.* *_cp311 + license: Python-2.0 + purls: [] + size: 14753109 + timestamp: 1772730203101 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.12.13-h8561d8f_0_cpython.conda + sha256: e658e647a4a15981573d6018928dec2c448b10c77c557c29872043ff23c0eb6a + md5: 8e7608172fa4d1b90de9a745c2fd2b81 + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + constrains: + - python_abi 3.12.* *_cp312 + license: Python-2.0 + purls: [] + size: 12127424 + timestamp: 1772730755512 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.13.12-h20e6be0_100_cp313.conda + build_number: 100 + sha256: 9a4f16a64def0853f0a7b6a7beb40d498fd6b09bee10b90c3d6069b664156817 + md5: 179c0f5ae4f22bc3be567298ed0b17b9 + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.13.* *_cp313 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + license: Python-2.0 + purls: [] + size: 12770674 + timestamp: 1770272314517 + python_site_packages_path: lib/python3.13/site-packages +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-3.14.3-h4c637c5_101_cp314.conda + build_number: 101 + sha256: fccce2af62d11328d232df9f6bbf63464fd45f81f718c661757f9c628c4378ce + md5: 753c8d0447677acb7ddbcc6e03e82661 + depends: + - __osx >=11.0 + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - ncurses >=6.5,<7.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.14.* *_cp314 + - readline >=8.3,<9.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - zstd >=1.5.7,<1.6.0a0 + license: Python-2.0 + purls: [] + size: 13522698 + timestamp: 1770675365241 + python_site_packages_path: lib/python3.14/site-packages +- conda: https://conda.anaconda.org/conda-forge/win-64/python-3.10.20-hc20f281_0_cpython.conda + sha256: e71595dd281a9902d7b84f545f16d7d4c0fb62cc6816431301f8f4870c94dc8c + md5: 6c18c24d33a7ac8a4f81c68b8eb8581b + depends: + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.4,<4.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - openssl >=3.5.5,<4.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + constrains: + - python_abi 3.10.* *_cp310 + license: Python-2.0 + purls: [] + size: 16028082 + timestamp: 1772728853200 +- conda: https://conda.anaconda.org/conda-forge/win-64/python-3.11.15-h0159041_0_cpython.conda + sha256: a1f1031088ce69bc99c82b95980c1f54e16cbd5c21f042e9c1ea25745a8fc813 + md5: d09dbf470b41bca48cbe6a78ba1e009b + depends: + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - openssl >=3.5.5,<4.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + constrains: + - python_abi 3.11.* *_cp311 + license: Python-2.0 + purls: [] + size: 18416208 + timestamp: 1772728847666 +- conda: https://conda.anaconda.org/conda-forge/win-64/python-3.12.13-h0159041_0_cpython.conda + sha256: a02b446d8b7b167b61733a3de3be5de1342250403e72a63b18dac89e99e6180e + md5: 2956dff38eb9f8332ad4caeba941cfe7 + depends: + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.4,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - openssl >=3.5.5,<4.0a0 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + constrains: + - python_abi 3.12.* *_cp312 + license: Python-2.0 + purls: [] + size: 15840187 + timestamp: 1772728877265 +- conda: https://conda.anaconda.org/conda-forge/win-64/python-3.13.12-h09917c8_100_cp313.conda + build_number: 100 + sha256: da70aec20ff5a5ae18bbba9fdd1e18190b419605cafaafb3bdad8becf11ce94d + md5: 4440c24966d0aa0c8f1e1d5006dac2d6 + depends: + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.13.* *_cp313 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + license: Python-2.0 + purls: [] + size: 16535316 + timestamp: 1770270322707 + python_site_packages_path: Lib/site-packages +- conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.3-h4b44e0e_101_cp314.conda + build_number: 101 + sha256: 3f99d83bfd95b9bdae64a42a1e4bf5131dc20b724be5ac8a9a7e1ac2c0f006d7 + md5: 7ec2be7eaf59f83f3e5617665f3fbb2e + depends: + - bzip2 >=1.0.8,<2.0a0 + - libexpat >=2.7.3,<3.0a0 + - libffi >=3.5.2,<3.6.0a0 + - liblzma >=5.8.2,<6.0a0 + - libmpdec >=4.0.0,<5.0a0 + - libsqlite >=3.51.2,<4.0a0 + - libzlib >=1.3.1,<2.0a0 + - openssl >=3.5.5,<4.0a0 + - python_abi 3.14.* *_cp314 + - tk >=8.6.13,<8.7.0a0 + - tzdata + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + - zstd >=1.5.7,<1.6.0a0 + license: Python-2.0 + purls: [] + size: 18273230 + timestamp: 1770675442998 + python_site_packages_path: Lib/site-packages +- pypi: https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl + name: python-dateutil + version: 2.9.0.post0 + sha256: a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427 + requires_dist: + - six>=1.5 + requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*' +- pypi: https://files.pythonhosted.org/packages/51/e5/fecf13f06e5e5f67e8837d777d1bc43fac0ed2b77a676804df5c34744727/python_json_logger-4.0.0-py3-none-any.whl + name: python-json-logger + version: 4.0.0 + sha256: af09c9daf6a813aa4cc7180395f50f2a9e5fa056034c9953aec92e381c5ba1e2 + requires_dist: + - typing-extensions ; python_full_version < '3.10' + - orjson ; implementation_name != 'pypy' and extra == 'dev' + - msgspec ; implementation_name != 'pypy' and extra == 'dev' + - validate-pyproject[all] ; extra == 'dev' + - black ; extra == 'dev' + - pylint ; extra == 'dev' + - mypy ; extra == 'dev' + - pytest ; extra == 'dev' + - freezegun ; extra == 'dev' + - backports-zoneinfo ; python_full_version < '3.9' and extra == 'dev' + - tzdata ; extra == 'dev' + - build ; extra == 'dev' + - mkdocs ; extra == 'dev' + - mkdocs-material>=8.5 ; extra == 'dev' + - mkdocs-awesome-pages-plugin ; extra == 'dev' + - mdx-truly-sane-lists ; extra == 'dev' + - mkdocstrings[python] ; extra == 'dev' + - mkdocs-gen-files ; extra == 'dev' + - mkdocs-literate-nav ; extra == 'dev' + - mike ; extra == 'dev' + requires_python: '>=3.8' +- conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda + build_number: 8 + sha256: 210bffe7b121e651419cb196a2a63687b087497595c9be9d20ebe97dd06060a7 + md5: 94305520c52a4aa3f6c2b1ff6008d9f8 + constrains: + - python 3.13.* *_cp313 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 7002 + timestamp: 1752805902938 +- conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda + build_number: 8 + sha256: ad6d2e9ac39751cc0529dd1566a26751a0bf2542adb0c232533d32e176e21db5 + md5: 0539938c55b6b1a59b560e843ad864a4 + constrains: + - python 3.14.* *_cp314 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 6989 + timestamp: 1752805904792 +- pypi: https://files.pythonhosted.org/packages/10/99/781fe0c827be2742bcc775efefccb3b048a3a9c6ce9aec0cbf4a101677e5/pytz-2026.1.post1-py2.py3-none-any.whl + name: pytz + version: 2026.1.post1 + sha256: f2fd16142fda348286a75e1a524be810bb05d444e5a081f37f7affc635035f7a +- pypi: https://files.pythonhosted.org/packages/28/88/2ff917caff61e55f38bcdb27de06ee30597881b2cae44fbba7627be015c4/pywinpty-3.0.3-cp314-cp314-win_amd64.whl + name: pywinpty + version: 3.0.3 + sha256: d4b6b7b0fe0cdcd02e956bd57cfe9f4e5a06514eecf3b5ae174da4f951b58be9 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/62/28/a652709bd76ca7533cd1c443b03add9f5051fdf71bc6bdb8801dddd4e7a3/pywinpty-3.0.3-cp310-cp310-win_amd64.whl + name: pywinpty + version: 3.0.3 + sha256: ff05f12d775b142b11c6fe085129bdd759b61cf7d41da6c745e78e3a1ef5bf40 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/79/c3/3e75075c7f71735f22b66fab0481f2c98e3a4d58cba55cb50ba29114bcf6/pywinpty-3.0.3-cp311-cp311-win_amd64.whl + name: pywinpty + version: 3.0.3 + sha256: dff25a9a6435f527d7c65608a7e62783fc12076e7d44487a4911ee91be5a8ac8 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/7c/d4/aeb5e1784d2c5bff6e189138a9ca91a090117459cea0c30378e1f2db3d54/pywinpty-3.0.3-cp312-cp312-win_amd64.whl + name: pywinpty + version: 3.0.3 + sha256: c9081df0e49ffa86d15db4a6ba61530630e48707f987df42c9d3313537e81fc0 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/e5/cb/58d6ed3fd429c96a90ef01ac9a617af10a6d41469219c25e7dc162abbb71/pywinpty-3.0.3-cp313-cp313-win_amd64.whl + name: pywinpty + version: 3.0.3 + sha256: 9c91dbb026050c77bdcef964e63a4f10f01a639113c4d3658332614544c467ab + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/05/14/52d505b5c59ce73244f59c7a50ecf47093ce4765f116cdb98286a71eeca2/pyyaml-6.0.3-cp310-cp310-macosx_11_0_arm64.whl + name: pyyaml + version: 6.0.3 + sha256: 02ea2dfa234451bbb8772601d7b8e426c2bfa197136796224e50e35a78777956 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/16/19/13de8e4377ed53079ee996e1ab0a9c33ec2faf808a4647b7b4c0d46dd239/pyyaml-6.0.3-cp311-cp311-macosx_11_0_arm64.whl + name: pyyaml + version: 6.0.3 + sha256: 652cb6edd41e718550aad172851962662ff2681490a8a711af6a4d288dd96824 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/23/20/bb6982b26a40bb43951265ba29d4c246ef0ff59c9fdcdf0ed04e0687de4d/pyyaml-6.0.3-cp314-cp314-win_amd64.whl + name: pyyaml + version: 6.0.3 + sha256: 4a2e8cebe2ff6ab7d1050ecd59c25d4c8bd7e6f400f5f82b96557ac0abafd0ac + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/2a/fa/926c003379b19fca39dd4634818b00dec6c62d87faf628d1394e137354d4/pyyaml-6.0.3-cp310-cp310-win_amd64.whl + name: pyyaml + version: 6.0.3 + sha256: bdb2c67c6c1390b63c6ff89f210c8fd09d9a1217a465701eac7316313c915e4c + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/6d/16/a95b6757765b7b031c9374925bb718d55e0a9ba8a1b6a12d25962ea44347/pyyaml-6.0.3-cp311-cp311-macosx_10_13_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: 44edc647873928551a01e7a563d7452ccdebee747728c1080d881d68af7b997e + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/71/60/917329f640924b18ff085ab889a11c763e0b573da888e8404ff486657602/pyyaml-6.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: b8bb0864c5a28024fac8a632c443c87c5aa6f215c0b126c449ae1a150412f31d + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: 0f29edc409a6392443abf94b9cf89ce99889a1dd5376d94316ae5145dfedd5d6 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/7a/1e/7acc4f0e74c4b3d9531e24739e0ab832a5edf40e64fbae1a9c01941cabd7/pyyaml-6.0.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: 9c7708761fccb9397fe64bbc0395abcae8c4bf7b0eac081e12b809bf47700d0b + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/86/bf/899e81e4cce32febab4fb42bb97dcdf66bc135272882d1987881a4b519e9/pyyaml-6.0.3-cp312-cp312-win_amd64.whl + name: pyyaml + version: 6.0.3 + sha256: 5fcd34e47f6e0b794d17de1b4ff496c00986e1c83f7ab2fb8fcfe9616ff7477b + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/88/f9/16491d7ed2a919954993e48aa941b200f38040928474c9e85ea9e64222c3/pyyaml-6.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: c458b6d084f9b935061bc36216e8a69a7e293a2f1e68bf956dcd9e6cbcd143f5 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/89/a0/6cf41a19a1f2f3feab0e9c0b74134aa2ce6849093d5517a0c550fe37a648/pyyaml-6.0.3-cp312-cp312-macosx_11_0_arm64.whl + name: pyyaml + version: 6.0.3 + sha256: fc09d0aa354569bc501d4e787133afc08552722d3ab34836a80547331bb5d4a0 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/8b/9d/b3589d3877982d4f2329302ef98a8026e7f4443c765c46cfecc8858c6b4b/pyyaml-6.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: ba1cc08a7ccde2d2ec775841541641e4548226580ab850948cbfda66a1befcdc + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl + name: pyyaml + version: 6.0.3 + sha256: 79005a0d97d5ddabfeeea4cf676af11e647e41d81c9a7722a193022accdb6b7c + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/9d/8c/f4bd7f6465179953d3ac9bc44ac1a8a3e6122cf8ada906b4f96c60172d43/pyyaml-6.0.3-cp314-cp314-macosx_10_13_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: 8d1fab6bb153a416f9aeb4b8763bc0f22a5586065f86f7664fc23339fc1c1fac + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl + name: pyyaml + version: 6.0.3 + sha256: 2283a07e2c21a2aa78d9c4442724ec1eb15f5e42a723b99cb3d822d48f5f7ad1 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/bd/9c/4d95bb87eb2063d20db7b60faa3840c1b18025517ae857371c4dd55a6b3a/pyyaml-6.0.3-cp314-cp314-macosx_11_0_arm64.whl + name: pyyaml + version: 6.0.3 + sha256: 34d5fcd24b8445fadc33f9cf348c1047101756fd760b4dacb5c3e99755703310 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: 8da9669d359f02c0b91ccc01cac4a67f16afec0dac22c2ad09f46bee0697eba8 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/d1/33/422b98d2195232ca1826284a76852ad5a86fe23e31b009c9886b2d0fb8b2/pyyaml-6.0.3-cp312-cp312-macosx_10_13_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: 7f047e29dcae44602496db43be01ad42fc6f1cc0d8cd6c83d342306c32270196 + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/da/e3/ea007450a105ae919a72393cb06f122f288ef60bba2dc64b26e2646fa315/pyyaml-6.0.3-cp311-cp311-win_amd64.whl + name: pyyaml + version: 6.0.3 + sha256: 9f3bfb4965eb874431221a3ff3fdcddc7e74e3b07799e0e84ca4a0f867d449bf + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/f4/a0/39350dd17dd6d6c6507025c0e53aef67a9293a6d37d3511f23ea510d5800/pyyaml-6.0.3-cp310-cp310-macosx_10_13_x86_64.whl + name: pyyaml + version: 6.0.3 + sha256: 214ed4befebe12df36bcc8bc2b64b396ca31be9304b8f59e25c11cf94a4c033b + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/06/5d/305323ba86b284e6fcb0d842d6adaa2999035f70f8c38a9b6d21ad28c3d4/pyzmq-27.1.0-cp311-cp311-macosx_10_15_universal2.whl + name: pyzmq + version: 27.1.0 + sha256: 226b091818d461a3bef763805e75685e478ac17e9008f49fce2d3e52b3d58b86 + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/23/6d/d8d92a0eb270a925c9b4dd039c0b4dc10abc2fcbc48331788824ef113935/pyzmq-27.1.0-cp311-cp311-win_amd64.whl + name: pyzmq + version: 27.1.0 + sha256: 190cbf120fbc0fc4957b56866830def56628934a9d112aec0e2507aa6a032b97 + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/30/76/8f099f9d6482450428b17c4d6b241281af7ce6a9de8149ca8c1c649f6792/pyzmq-27.1.0-cp310-cp310-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: pyzmq + version: 27.1.0 + sha256: 03ff0b279b40d687691a6217c12242ee71f0fba28bf8626ff50e3ef0f4410e1e + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/62/b2/f4ab56c8c595abcb26b2be5fd9fa9e6899c1e5ad54964e93ae8bb35482be/pyzmq-27.1.0-cp310-cp310-win_amd64.whl + name: pyzmq + version: 27.1.0 + sha256: c0bb87227430ee3aefcc0ade2088100e528d5d3298a0a715a64f3d04c60ba02f + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/67/b9/52aa9ec2867528b54f1e60846728d8b4d84726630874fee3a91e66c7df81/pyzmq-27.1.0-cp310-cp310-macosx_10_15_universal2.whl + name: pyzmq + version: 27.1.0 + sha256: 508e23ec9bc44c0005c4946ea013d9317ae00ac67778bd47519fdf5a0e930ff4 + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl + name: pyzmq + version: 27.1.0 + sha256: 452631b640340c928fa343801b0d07eb0c3789a5ffa843f6e1a9cee0ba4eb4fc + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/b1/c4/2a6fe5111a01005fc7af3878259ce17684fabb8852815eda6225620f3c59/pyzmq-27.1.0-cp311-cp311-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: pyzmq + version: 27.1.0 + sha256: 5bbf8d3630bf96550b3be8e1fc0fea5cbdc8d5466c1192887bd94869da17a63e + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/f8/9b/c108cdb55560eaf253f0cbdb61b29971e9fb34d9c3499b0e96e4e60ed8a5/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl + name: pyzmq + version: 27.1.0 + sha256: 43ad9a73e3da1fab5b0e7e13402f0b2fb934ae1c876c51d0afff0e7c052eca31 + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/fc/7f/a21b20d577e4100c6a41795842028235998a643b1ad406a6d4163ea8f53e/pyzmq-27.1.0-cp312-abi3-win_amd64.whl + name: pyzmq + version: 27.1.0 + sha256: 9ce490cf1d2ca2ad84733aa1d69ce6855372cb5ce9223802450c9b2a7cba0ccf + requires_dist: + - cffi ; implementation_name == 'pypy' + requires_python: '>=3.8' +- pypi: ./ + name: rdtools + version: 3.1.1.dev17+g20899bcc8.d20260311 + sha256: 62688b3090071bdcbe9e6b1e0a1568e140a61dbaf6c24cd7a38f7bd9af2f90a3 + requires_dist: + - matplotlib>=3.5.3 + - numpy>=1.22.4 + - pandas>=1.4.4 + - statsmodels>=0.13.5 + - scipy>=1.8.1 + - h5py>=3.7.0 + - plotly>=4.0.0 + - xgboost>=1.7.0 + - pvlib>=0.13.1 + - scikit-learn>=1.1.3,!=1.6.0 + - arch>=5.6 + - filterpy>=1.4.2 + - sphinx==7.4.7 ; extra == 'doc' + - nbsphinx==0.9.5 ; extra == 'doc' + - nbsphinx-link==1.3.1 ; extra == 'doc' + - sphinx-rtd-theme==3.0.1 ; extra == 'doc' + - ipython ; extra == 'doc' + - sphinx-gallery==0.18.0 ; extra == 'doc' + - pytest>=3.10.1 ; extra == 'test' + - pytest-cov ; extra == 'test' + - coverage ; extra == 'test' + - flake8 ; extra == 'test' + - nbval>=0.10.0 ; extra == 'test' + - pytest-mock ; extra == 'test' + - jupyter ; extra == 'notebooks' + - ipywidgets ; extra == 'notebooks' + - numexpr>=2.10.2 ; extra == 'notebooks' + - tabulate>=0.9.0 ; extra == 'notebooks' + - lxml ; extra == 'notebooks' + - rdtools[notebooks,test] ; extra == 'dev' + - rdtools[dev,doc] ; extra == 'all' + requires_python: '>=3.10' +- conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda + sha256: 12ffde5a6f958e285aa22c191ca01bbd3d6e710aa852e00618fa6ddc59149002 + md5: d7d95fc8287ea7bf33e0e7116d2b95ec + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + - ncurses >=6.5,<7.0a0 + license: GPL-3.0-only + license_family: GPL + purls: [] + size: 345073 + timestamp: 1765813471974 +- conda: https://conda.anaconda.org/conda-forge/osx-64/readline-8.3-h68b038d_0.conda + sha256: 4614af680aa0920e82b953fece85a03007e0719c3399f13d7de64176874b80d5 + md5: eefd65452dfe7cce476a519bece46704 + depends: + - __osx >=10.13 + - ncurses >=6.5,<7.0a0 + license: GPL-3.0-only + license_family: GPL + purls: [] + size: 317819 + timestamp: 1765813692798 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/readline-8.3-h46df422_0.conda + sha256: a77010528efb4b548ac2a4484eaf7e1c3907f2aec86123ed9c5212ae44502477 + md5: f8381319127120ce51e081dce4865cf4 + depends: + - __osx >=11.0 + - ncurses >=6.5,<7.0a0 + license: GPL-3.0-only + license_family: GPL + purls: [] + size: 313930 + timestamp: 1765813902568 +- pypi: https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl + name: referencing + version: 0.37.0 + sha256: 381329a9f99628c9069361716891d34ad94af76e461dcb0335825aecc7692231 + requires_dist: + - attrs>=22.2.0 + - rpds-py>=0.7.0 + - typing-extensions>=4.4.0 ; python_full_version < '3.13' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl + name: requests + version: 2.32.5 + sha256: 2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6 + requires_dist: + - charset-normalizer>=2,<4 + - idna>=2.5,<4 + - urllib3>=1.21.1,<3 + - certifi>=2017.4.17 + - pysocks>=1.5.6,!=1.5.7 ; extra == 'socks' + - chardet>=3.0.2,<6 ; extra == 'use-chardet-on-py3' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/67/f3/6cd296376653270ac1b423bb30bd70942d9916b6978c6f40472d6ac038e7/retrying-1.4.2-py3-none-any.whl + name: retrying + version: 1.4.2 + sha256: bbc004aeb542a74f3569aeddf42a2516efefcdaff90df0eb38fbfbf19f179f59 + requires_python: '>=3.6' +- pypi: https://files.pythonhosted.org/packages/7b/44/4e421b96b67b2daff264473f7465db72fbdf36a07e05494f50300cc7b0c6/rfc3339_validator-0.1.4-py2.py3-none-any.whl + name: rfc3339-validator + version: 0.1.4 + sha256: 24f6ec1eda14ef823da9e36ec7113124b39c04d50a4d3d3a3c2859577e7791fa + requires_dist: + - six + requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*' +- pypi: https://files.pythonhosted.org/packages/9e/51/17023c0f8f1869d8806b979a2bffa3f861f26a3f1a66b094288323fba52f/rfc3986_validator-0.1.1-py2.py3-none-any.whl + name: rfc3986-validator + version: 0.1.1 + sha256: 2f235c432ef459970b4306369336b9d5dbdda31b510ca1e327636e01f528bfa9 + requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*' +- pypi: https://files.pythonhosted.org/packages/7e/71/44ce230e1b7fadd372515a97e32a83011f906ddded8d03e3c6aafbdedbb7/rfc3987_syntax-1.1.0-py3-none-any.whl + name: rfc3987-syntax + version: 1.1.0 + sha256: 6c3d97604e4c5ce9f714898e05401a0445a641cfa276432b0a648c80856f6a3f + requires_dist: + - lark>=1.2.2 + - pytest>=8.3.5 ; extra == 'testing' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/03/e7/98a2f4ac921d82f33e03f3835f5bf3a4a40aa1bfdc57975e74a97b2b4bdd/rpds_py-0.30.0-cp312-cp312-macosx_10_12_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: a161f20d9a43006833cd7068375a94d035714d73a172b681d8881820600abfad + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/06/0c/0c411a0ec64ccb6d104dcabe0e713e05e153a9a2c3c2bd2b32ce412166fe/rpds_py-0.30.0-cp310-cp310-macosx_10_12_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: 679ae98e00c0e8d68a7fda324e16b90fd5260945b45d3b824c892cec9eea3288 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/19/6a/4ba3d0fb7297ebae71171822554abe48d7cab29c28b8f9f2c04b79988c05/rpds_py-0.30.0-cp310-cp310-macosx_11_0_arm64.whl + name: rpds-py + version: 0.30.0 + sha256: 4cc2206b76b4f576934f0ed374b10d7ca5f457858b157ca52064bdfc26b9fc00 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/2b/60/19f7884db5d5603edf3c6bce35408f45ad3e97e10007df0e17dd57af18f8/rpds_py-0.30.0-cp314-cp314-macosx_11_0_arm64.whl + name: rpds-py + version: 0.30.0 + sha256: ec7c4490c672c1a0389d319b3a9cfcd098dcdc4783991553c332a15acf7249be + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/39/3b/f786af9957306fdc38a74cef405b7b93180f481fb48453a114bb6465744a/rpds_py-0.30.0-cp312-cp312-win_amd64.whl + name: rpds-py + version: 0.30.0 + sha256: a090322ca841abd453d43456ac34db46e8b05fd9b3b4ac0c78bcde8b089f959b + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/3e/d2/1aaac33287e8cfb07aab2e6b8ac1deca62f6f65411344f1433c55e6f3eb8/rpds_py-0.30.0-cp314-cp314-win_amd64.whl + name: rpds-py + version: 0.30.0 + sha256: 95f0802447ac2d10bcc69f6dc28fe95fdf17940367b21d34e34c737870758950 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/4d/6e/f964e88b3d2abee2a82c1ac8366da848fce1c6d834dc2132c3fda3970290/rpds_py-0.30.0-cp311-cp311-macosx_10_12_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: a2bffea6a4ca9f01b3f8e548302470306689684e61602aa3d141e34da06cf425 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/4d/a1/bca7fd3d452b272e13335db8d6b0b3ecde0f90ad6f16f3328c6fb150c889/rpds_py-0.30.0-cp312-cp312-macosx_11_0_arm64.whl + name: rpds-py + version: 0.30.0 + sha256: 6abc8880d9d036ecaafe709079969f56e876fcf107f7a8e9920ba6d5a3878d05 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/60/1b/6f8f29f3f995c7ffdde46a626ddccd7c63aefc0efae881dc13b6e5d5bb16/rpds_py-0.30.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: 47f236970bccb2233267d89173d3ad2703cd36a0e2a6e92d0560d333871a3d23 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/61/b5/707f6cf0066a6412aacc11d17920ea2e19e5b2f04081c64526eb35b5c6e7/rpds_py-0.30.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: 0c0e95f6819a19965ff420f65578bacb0b00f251fefe2c8b23347c37174271f3 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/86/81/dad16382ebbd3d0e0328776d8fd7ca94220e4fa0798d1dc5e7da48cb3201/rpds_py-0.30.0-cp314-cp314-macosx_10_12_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: 68f19c879420aa08f61203801423f6cd5ac5f0ac4ac82a2368a9fcd6a9a075e0 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/94/ba/24e5ebb7c1c82e74c4e4f33b2112a5573ddc703915b13a073737b59b86e0/rpds_py-0.30.0-cp311-cp311-macosx_11_0_arm64.whl + name: rpds-py + version: 0.30.0 + sha256: dc4f992dfe1e2bc3ebc7444f6c7051b4bc13cd8e33e43511e8ffd13bf407010d + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/96/cb/156d7a5cf4f78a7cc571465d8aec7a3c447c94f6749c5123f08438bcf7bc/rpds_py-0.30.0-cp310-cp310-win_amd64.whl + name: rpds-py + version: 0.30.0 + sha256: 1726859cd0de969f88dc8673bdd954185b9104e05806be64bcd87badbe313169 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/b7/de/f7192e12b21b9e9a68a6d0f249b4af3fdcdff8418be0767a627564afa1f1/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: 9027da1ce107104c50c81383cae773ef5c24d296dd11c99e2629dbd7967a20c6 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ce/81/9a91c0111ce1758c92516a3e44776920b579d9a7c09b2b06b642d4de3f0f/rpds_py-0.30.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: 47e77dc9822d3ad616c3d5759ea5631a75e5809d5a28707744ef79d7a1bcfcad + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ed/dc/d61221eb88ff410de3c49143407f6f3147acf2538c86f2ab7ce65ae7d5f9/rpds_py-0.30.0-cp313-cp313-macosx_10_12_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: f83424d738204d9770830d35290ff3273fbb02b41f919870479fab14b9d303b2 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f2/e1/485132437d20aa4d3e1d8b3fb5a5e65aa8139f1e097080c2a8443201742c/rpds_py-0.30.0-cp313-cp313-win_amd64.whl + name: rpds-py + version: 0.30.0 + sha256: 806f36b1b605e2d6a72716f321f20036b9489d29c51c91f4dd29a3e3afb73b15 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f8/1e/372195d326549bb51f0ba0f2ecb9874579906b97e08880e7a65c3bef1a99/rpds_py-0.30.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: rpds-py + version: 0.30.0 + sha256: 33f559f3104504506a44bb666b93a33f5d33133765b0c216a5bf2f1e1503af89 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/fa/5b/e7b7aa136f28462b344e652ee010d4de26ee9fd16f1bfd5811f5153ccf89/rpds_py-0.30.0-cp311-cp311-win_amd64.whl + name: rpds-py + version: 0.30.0 + sha256: a51033ff701fca756439d641c0ad09a41d9242fa69121c7d8769604a0a629825 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/fd/32/55fb50ae104061dbc564ef15cc43c013dc4a9f4527a1f4d99baddf56fe5f/rpds_py-0.30.0-cp313-cp313-macosx_11_0_arm64.whl + name: rpds-py + version: 0.30.0 + sha256: e7536cd91353c5273434b4e003cbda89034d67e7710eab8761fd918ec6c69cf8 + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/22/17/0b7adb6df00a30bc2c4a9e30e7f1c0c611035e2a5e22721b1bec0c2a5ffc/scikit_learn-1.1.3-cp310-cp310-macosx_10_9_x86_64.whl + name: scikit-learn + version: 1.1.3 + sha256: 8e9dd76c7274055d1acf4526b8efb16a3531c26dcda714a0c16da99bf9d41900 + requires_dist: + - numpy>=1.17.3 + - scipy>=1.3.2 + - joblib>=1.0.0 + - threadpoolctl>=2.0.0 + - matplotlib>=3.1.2 ; extra == 'benchmark' + - pandas>=1.0.5 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.1.2 ; extra == 'docs' + - scikit-image>=0.16.2 ; extra == 'docs' + - pandas>=1.0.5 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=4.0.1 ; extra == 'docs' + - sphinx-gallery>=0.7.0 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=7.1.2 ; extra == 'docs' + - sphinx-prompt>=1.3.0 ; extra == 'docs' + - sphinxext-opengraph>=0.4.2 ; extra == 'docs' + - matplotlib>=3.1.2 ; extra == 'examples' + - scikit-image>=0.16.2 ; extra == 'examples' + - pandas>=1.0.5 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - matplotlib>=3.1.2 ; extra == 'tests' + - scikit-image>=0.16.2 ; extra == 'tests' + - pandas>=1.0.5 ; extra == 'tests' + - pytest>=5.0.1 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - flake8>=3.8.2 ; extra == 'tests' + - black>=22.3.0 ; extra == 'tests' + - mypy>=0.961 ; extra == 'tests' + - pyamg>=4.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/23/b6/5d339516e3fbb6cde8ad87e85d9f17a3270c9e508c860785f0b6239ea33a/scikit_learn-1.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: scikit-learn + version: 1.1.3 + sha256: 701181792a28c82fecae12adb5d15d0ecf57bffab7cf4bdbb52c7b3fd428d540 + requires_dist: + - numpy>=1.17.3 + - scipy>=1.3.2 + - joblib>=1.0.0 + - threadpoolctl>=2.0.0 + - matplotlib>=3.1.2 ; extra == 'benchmark' + - pandas>=1.0.5 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.1.2 ; extra == 'docs' + - scikit-image>=0.16.2 ; extra == 'docs' + - pandas>=1.0.5 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=4.0.1 ; extra == 'docs' + - sphinx-gallery>=0.7.0 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=7.1.2 ; extra == 'docs' + - sphinx-prompt>=1.3.0 ; extra == 'docs' + - sphinxext-opengraph>=0.4.2 ; extra == 'docs' + - matplotlib>=3.1.2 ; extra == 'examples' + - scikit-image>=0.16.2 ; extra == 'examples' + - pandas>=1.0.5 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - matplotlib>=3.1.2 ; extra == 'tests' + - scikit-image>=0.16.2 ; extra == 'tests' + - pandas>=1.0.5 ; extra == 'tests' + - pytest>=5.0.1 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - flake8>=3.8.2 ; extra == 'tests' + - black>=22.3.0 ; extra == 'tests' + - mypy>=0.961 ; extra == 'tests' + - pyamg>=4.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/9a/3b/e7aca9745952d3abe278fcf68ed8106ea98b8e049f05a4047a3b5a6cb706/scikit_learn-1.1.3-cp310-cp310-macosx_12_0_arm64.whl + name: scikit-learn + version: 1.1.3 + sha256: ee47f68d973cee7009f06edb956f2f5588a0f230f24a2a70175fd0ecf36e2653 + requires_dist: + - numpy>=1.17.3 + - scipy>=1.3.2 + - joblib>=1.0.0 + - threadpoolctl>=2.0.0 + - matplotlib>=3.1.2 ; extra == 'benchmark' + - pandas>=1.0.5 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.1.2 ; extra == 'docs' + - scikit-image>=0.16.2 ; extra == 'docs' + - pandas>=1.0.5 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=4.0.1 ; extra == 'docs' + - sphinx-gallery>=0.7.0 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=7.1.2 ; extra == 'docs' + - sphinx-prompt>=1.3.0 ; extra == 'docs' + - sphinxext-opengraph>=0.4.2 ; extra == 'docs' + - matplotlib>=3.1.2 ; extra == 'examples' + - scikit-image>=0.16.2 ; extra == 'examples' + - pandas>=1.0.5 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - matplotlib>=3.1.2 ; extra == 'tests' + - scikit-image>=0.16.2 ; extra == 'tests' + - pandas>=1.0.5 ; extra == 'tests' + - pytest>=5.0.1 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - flake8>=3.8.2 ; extra == 'tests' + - black>=22.3.0 ; extra == 'tests' + - mypy>=0.961 ; extra == 'tests' + - pyamg>=4.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/fe/28/2b78c8efceeb07e73cef24af458dd8241cc6c4b39abc7bf375ba38b07d28/scikit_learn-1.1.3-cp310-cp310-win_amd64.whl + name: scikit-learn + version: 1.1.3 + sha256: 30e27721adc308e8fd9f419f43068e43490005f911edf4476a9e585059fa8a83 + requires_dist: + - numpy>=1.17.3 + - scipy>=1.3.2 + - joblib>=1.0.0 + - threadpoolctl>=2.0.0 + - matplotlib>=3.1.2 ; extra == 'benchmark' + - pandas>=1.0.5 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.1.2 ; extra == 'docs' + - scikit-image>=0.16.2 ; extra == 'docs' + - pandas>=1.0.5 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=4.0.1 ; extra == 'docs' + - sphinx-gallery>=0.7.0 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=7.1.2 ; extra == 'docs' + - sphinx-prompt>=1.3.0 ; extra == 'docs' + - sphinxext-opengraph>=0.4.2 ; extra == 'docs' + - matplotlib>=3.1.2 ; extra == 'examples' + - scikit-image>=0.16.2 ; extra == 'examples' + - pandas>=1.0.5 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - matplotlib>=3.1.2 ; extra == 'tests' + - scikit-image>=0.16.2 ; extra == 'tests' + - pandas>=1.0.5 ; extra == 'tests' + - pytest>=5.0.1 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - flake8>=3.8.2 ; extra == 'tests' + - black>=22.3.0 ; extra == 'tests' + - mypy>=0.961 ; extra == 'tests' + - pyamg>=4.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/1c/ce/af9d99533b24c55ff4e18d9b7b4d9919bbc6cd8f22fe7a7be01519a347d5/scikit_learn-1.7.2-cp310-cp310-macosx_12_0_arm64.whl + name: scikit-learn + version: 1.7.2 + sha256: 36749fb62b3d961b1ce4fedf08fa57a1986cd409eff2d783bca5d4b9b5fce51c + requires_dist: + - numpy>=1.22.0 + - scipy>=1.8.0 + - joblib>=1.2.0 + - threadpoolctl>=3.1.0 + - numpy>=1.22.0 ; extra == 'build' + - scipy>=1.8.0 ; extra == 'build' + - cython>=3.0.10 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.22.0 ; extra == 'install' + - scipy>=1.8.0 ; extra == 'install' + - joblib>=1.2.0 ; extra == 'install' + - threadpoolctl>=3.1.0 ; extra == 'install' + - matplotlib>=3.5.0 ; extra == 'benchmark' + - pandas>=1.4.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.5.0 ; extra == 'docs' + - scikit-image>=0.19.0 ; extra == 'docs' + - pandas>=1.4.0 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=8.4.0 ; extra == 'docs' + - pooch>=1.6.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.14.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.5.0 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.5.0 ; extra == 'examples' + - scikit-image>=0.19.0 ; extra == 'examples' + - pandas>=1.4.0 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - pooch>=1.6.0 ; extra == 'examples' + - plotly>=5.14.0 ; extra == 'examples' + - matplotlib>=3.5.0 ; extra == 'tests' + - scikit-image>=0.19.0 ; extra == 'tests' + - pandas>=1.4.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=4.2.1 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.6.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/58/0e/8c2a03d518fb6bd0b6b0d4b114c63d5f1db01ff0f9925d8eb10960d01c01/scikit_learn-1.7.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + name: scikit-learn + version: 1.7.2 + sha256: 7a58814265dfc52b3295b1900cfb5701589d30a8bb026c7540f1e9d3499d5ec8 + requires_dist: + - numpy>=1.22.0 + - scipy>=1.8.0 + - joblib>=1.2.0 + - threadpoolctl>=3.1.0 + - numpy>=1.22.0 ; extra == 'build' + - scipy>=1.8.0 ; extra == 'build' + - cython>=3.0.10 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.22.0 ; extra == 'install' + - scipy>=1.8.0 ; extra == 'install' + - joblib>=1.2.0 ; extra == 'install' + - threadpoolctl>=3.1.0 ; extra == 'install' + - matplotlib>=3.5.0 ; extra == 'benchmark' + - pandas>=1.4.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.5.0 ; extra == 'docs' + - scikit-image>=0.19.0 ; extra == 'docs' + - pandas>=1.4.0 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=8.4.0 ; extra == 'docs' + - pooch>=1.6.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.14.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.5.0 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.5.0 ; extra == 'examples' + - scikit-image>=0.19.0 ; extra == 'examples' + - pandas>=1.4.0 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - pooch>=1.6.0 ; extra == 'examples' + - plotly>=5.14.0 ; extra == 'examples' + - matplotlib>=3.5.0 ; extra == 'tests' + - scikit-image>=0.19.0 ; extra == 'tests' + - pandas>=1.4.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=4.2.1 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.6.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/7f/9b/87961813c34adbca21a6b3f6b2bea344c43b30217a6d24cc437c6147f3e8/scikit_learn-1.7.2-cp310-cp310-win_amd64.whl + name: scikit-learn + version: 1.7.2 + sha256: ca250e6836d10e6f402436d6463d6c0e4d8e0234cfb6a9a47835bd392b852ce5 + requires_dist: + - numpy>=1.22.0 + - scipy>=1.8.0 + - joblib>=1.2.0 + - threadpoolctl>=3.1.0 + - numpy>=1.22.0 ; extra == 'build' + - scipy>=1.8.0 ; extra == 'build' + - cython>=3.0.10 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.22.0 ; extra == 'install' + - scipy>=1.8.0 ; extra == 'install' + - joblib>=1.2.0 ; extra == 'install' + - threadpoolctl>=3.1.0 ; extra == 'install' + - matplotlib>=3.5.0 ; extra == 'benchmark' + - pandas>=1.4.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.5.0 ; extra == 'docs' + - scikit-image>=0.19.0 ; extra == 'docs' + - pandas>=1.4.0 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=8.4.0 ; extra == 'docs' + - pooch>=1.6.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.14.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.5.0 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.5.0 ; extra == 'examples' + - scikit-image>=0.19.0 ; extra == 'examples' + - pandas>=1.4.0 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - pooch>=1.6.0 ; extra == 'examples' + - plotly>=5.14.0 ; extra == 'examples' + - matplotlib>=3.5.0 ; extra == 'tests' + - scikit-image>=0.19.0 ; extra == 'tests' + - pandas>=1.4.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=4.2.1 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.6.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/ba/3e/daed796fd69cce768b8788401cc464ea90b306fb196ae1ffed0b98182859/scikit_learn-1.7.2-cp310-cp310-macosx_10_9_x86_64.whl + name: scikit-learn + version: 1.7.2 + sha256: 6b33579c10a3081d076ab403df4a4190da4f4432d443521674637677dc91e61f + requires_dist: + - numpy>=1.22.0 + - scipy>=1.8.0 + - joblib>=1.2.0 + - threadpoolctl>=3.1.0 + - numpy>=1.22.0 ; extra == 'build' + - scipy>=1.8.0 ; extra == 'build' + - cython>=3.0.10 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.22.0 ; extra == 'install' + - scipy>=1.8.0 ; extra == 'install' + - joblib>=1.2.0 ; extra == 'install' + - threadpoolctl>=3.1.0 ; extra == 'install' + - matplotlib>=3.5.0 ; extra == 'benchmark' + - pandas>=1.4.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.5.0 ; extra == 'docs' + - scikit-image>=0.19.0 ; extra == 'docs' + - pandas>=1.4.0 ; extra == 'docs' + - seaborn>=0.9.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=8.4.0 ; extra == 'docs' + - pooch>=1.6.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.14.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.5.0 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.5.0 ; extra == 'examples' + - scikit-image>=0.19.0 ; extra == 'examples' + - pandas>=1.4.0 ; extra == 'examples' + - seaborn>=0.9.0 ; extra == 'examples' + - pooch>=1.6.0 ; extra == 'examples' + - plotly>=5.14.0 ; extra == 'examples' + - matplotlib>=3.5.0 ; extra == 'tests' + - scikit-image>=0.19.0 ; extra == 'tests' + - pandas>=1.4.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=4.2.1 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.6.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/01/18/d154dc1638803adf987910cdd07097d9c526663a55666a97c124d09fb96a/scikit_learn-1.8.0-cp311-cp311-macosx_12_0_arm64.whl + name: scikit-learn + version: 1.8.0 + sha256: f984ca4b14914e6b4094c5d52a32ea16b49832c03bd17a110f004db3c223e8e1 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/03/aa/e22e0768512ce9255eba34775be2e85c2048da73da1193e841707f8f039c/scikit_learn-1.8.0-cp313-cp313-macosx_10_13_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: 0d6ae97234d5d7079dc0040990a6f7aeb97cb7fa7e8945f1999a429b23569e0a + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/1c/f9/9b7563caf3ec8873e17a31401858efab6b39a882daf6c1bfa88879c0aa11/scikit_learn-1.8.0-cp313-cp313-win_amd64.whl + name: scikit-learn + version: 1.8.0 + sha256: 2de443b9373b3b615aec1bb57f9baa6bb3a9bd093f1269ba95c17d870422b271 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/24/05/1af2c186174cc92dcab2233f327336058c077d38f6fe2aceb08e6ab4d509/scikit_learn-1.8.0-cp314-cp314-macosx_10_15_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: c22a2da7a198c28dd1a6e1136f19c830beab7fdca5b3e5c8bba8394f8a5c45b3 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/36/4d/4a67f30778a45d542bbea5db2dbfa1e9e100bf9ba64aefe34215ba9f11f6/scikit_learn-1.8.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: ada8121bcb4dac28d930febc791a69f7cb1673c8495e5eee274190b73a4559c1 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/38/cf/06896db3f71c75902a8e9943b444a56e727418f6b4b4a90c98c934f51ed4/scikit_learn-1.8.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: 8fdf95767f989b0cfedb85f7ed8ca215d4be728031f56ff5a519ee1e3276dc2e + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/49/d8/9be608c6024d021041c7f0b3928d4749a706f4e2c3832bbede4fb4f58c95/scikit_learn-1.8.0-cp312-cp312-macosx_12_0_arm64.whl + name: scikit-learn + version: 1.8.0 + sha256: 5025ce924beccb28298246e589c691fe1b8c1c96507e6d27d12c5fadd85bfd76 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/58/37/31b83b2594105f61a381fc74ca19e8780ee923be2d496fcd8d2e1147bd99/scikit_learn-1.8.0-cp313-cp313-macosx_12_0_arm64.whl + name: scikit-learn + version: 1.8.0 + sha256: edec98c5e7c128328124a029bceb09eda2d526997780fef8d65e9a69eead963e + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/76/18/a8def8f91b18cd1ba6e05dbe02540168cb24d47e8dcf69e8d00b7da42a08/scikit_learn-1.8.0-cp314-cp314-win_amd64.whl + name: scikit-learn + version: 1.8.0 + sha256: 56079a99c20d230e873ea40753102102734c5953366972a71d5cb39a32bc40c6 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/89/3c/45c352094cfa60050bcbb967b1faf246b22e93cb459f2f907b600f2ceda5/scikit_learn-1.8.0-cp311-cp311-win_amd64.whl + name: scikit-learn + version: 1.8.0 + sha256: c57b1b610bd1f40ba43970e11ce62821c2e6569e4d74023db19c6b26f246cb3b + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/90/74/e6a7cc4b820e95cc38cf36cd74d5aa2b42e8ffc2d21fe5a9a9c45c1c7630/scikit_learn-1.8.0-cp312-cp312-macosx_10_13_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: 5fb63362b5a7ddab88e52b6dbb47dac3fd7dafeee740dc6c8d8a446ddedade8e + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/97/74/b7a304feb2b49df9fafa9382d4d09061a96ee9a9449a7cbea7988dda0828/scikit_learn-1.8.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: a0bcfe4d0d14aec44921545fd2af2338c7471de9cb701f1da4c9d85906ab847a + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/9f/c4/0ab22726a04ede56f689476b760f98f8f46607caecff993017ac1b64aa5d/scikit_learn-1.8.0-cp312-cp312-win_amd64.whl + name: scikit-learn + version: 1.8.0 + sha256: 35c007dedb2ffe38fe3ee7d201ebac4a2deccd2408e8621d53067733e3c74809 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/a8/25/01c0af38fe969473fb292bba9dc2b8f9b451f3112ff242c647fee3d0dfe7/scikit_learn-1.8.0-cp314-cp314-macosx_12_0_arm64.whl + name: scikit-learn + version: 1.8.0 + sha256: 6b595b07a03069a2b1740dc08c2299993850ea81cce4fe19b2421e0c970de6b7 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/b8/cb/861b41341d6f1245e6ca80b1c1a8c4dfce43255b03df034429089ca2a2c5/scikit_learn-1.8.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: fb65db5d7531bccf3a4f6bec3462223bea71384e2cda41da0f10b7c292b9e7c4 + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/c9/92/53ea2181da8ac6bf27170191028aee7251f8f841f8d3edbfdcaf2008fde9/scikit_learn-1.8.0-cp311-cp311-macosx_10_9_x86_64.whl + name: scikit-learn + version: 1.8.0 + sha256: 146b4d36f800c013d267b29168813f7a03a43ecd2895d04861f1240b564421da + requires_dist: + - numpy>=1.24.1 + - scipy>=1.10.0 + - joblib>=1.3.0 + - threadpoolctl>=3.2.0 + - numpy>=1.24.1 ; extra == 'build' + - scipy>=1.10.0 ; extra == 'build' + - cython>=3.1.2 ; extra == 'build' + - meson-python>=0.17.1 ; extra == 'build' + - numpy>=1.24.1 ; extra == 'install' + - scipy>=1.10.0 ; extra == 'install' + - joblib>=1.3.0 ; extra == 'install' + - threadpoolctl>=3.2.0 ; extra == 'install' + - matplotlib>=3.6.1 ; extra == 'benchmark' + - pandas>=1.5.0 ; extra == 'benchmark' + - memory-profiler>=0.57.0 ; extra == 'benchmark' + - matplotlib>=3.6.1 ; extra == 'docs' + - scikit-image>=0.22.0 ; extra == 'docs' + - pandas>=1.5.0 ; extra == 'docs' + - seaborn>=0.13.0 ; extra == 'docs' + - memory-profiler>=0.57.0 ; extra == 'docs' + - sphinx>=7.3.7 ; extra == 'docs' + - sphinx-copybutton>=0.5.2 ; extra == 'docs' + - sphinx-gallery>=0.17.1 ; extra == 'docs' + - numpydoc>=1.2.0 ; extra == 'docs' + - pillow>=10.1.0 ; extra == 'docs' + - pooch>=1.8.0 ; extra == 'docs' + - sphinx-prompt>=1.4.0 ; extra == 'docs' + - sphinxext-opengraph>=0.9.1 ; extra == 'docs' + - plotly>=5.18.0 ; extra == 'docs' + - polars>=0.20.30 ; extra == 'docs' + - sphinx-design>=0.6.0 ; extra == 'docs' + - sphinxcontrib-sass>=0.3.4 ; extra == 'docs' + - pydata-sphinx-theme>=0.15.3 ; extra == 'docs' + - sphinx-remove-toctrees>=1.0.0.post1 ; extra == 'docs' + - towncrier>=24.8.0 ; extra == 'docs' + - matplotlib>=3.6.1 ; extra == 'examples' + - scikit-image>=0.22.0 ; extra == 'examples' + - pandas>=1.5.0 ; extra == 'examples' + - seaborn>=0.13.0 ; extra == 'examples' + - pooch>=1.8.0 ; extra == 'examples' + - plotly>=5.18.0 ; extra == 'examples' + - matplotlib>=3.6.1 ; extra == 'tests' + - pandas>=1.5.0 ; extra == 'tests' + - pytest>=7.1.2 ; extra == 'tests' + - pytest-cov>=2.9.0 ; extra == 'tests' + - ruff>=0.11.7 ; extra == 'tests' + - mypy>=1.15 ; extra == 'tests' + - pyamg>=5.0.0 ; extra == 'tests' + - polars>=0.20.30 ; extra == 'tests' + - pyarrow>=12.0.0 ; extra == 'tests' + - numpydoc>=1.2.0 ; extra == 'tests' + - pooch>=1.8.0 ; extra == 'tests' + - conda-lock==3.0.1 ; extra == 'maintenance' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/2e/46/6d56589815f106f8851e4636d838740aaf8f26bb5ec857b2f6c0780a33de/scipy-1.8.1-cp310-cp310-macosx_12_0_arm64.whl + name: scipy + version: 1.8.1 + sha256: e013aed00ed776d790be4cb32826adb72799c61e318676172495383ba4570aa4 + requires_dist: + - numpy>=1.17.3,<1.25.0 + requires_python: '>=3.8,<3.11' +- pypi: https://files.pythonhosted.org/packages/31/c2/0b8758ebaeb43e089eb56168390824a830f9f419ae07d755d99a46e5a937/scipy-1.8.1-cp310-cp310-win_amd64.whl + name: scipy + version: 1.8.1 + sha256: 4e53a55f6a4f22de01ffe1d2f016e30adedb67a699a310cdcac312806807ca81 + requires_dist: + - numpy>=1.17.3,<1.25.0 + requires_python: '>=3.8,<3.11' +- pypi: https://files.pythonhosted.org/packages/32/1b/774c35c1246fbb2ce379272d6e8ffc61f85f2a1afeb13855f9cc2ad0b8b9/scipy-1.8.1-cp310-cp310-macosx_12_0_universal2.macosx_10_9_x86_64.whl + name: scipy + version: 1.8.1 + sha256: 02b567e722d62bddd4ac253dafb01ce7ed8742cf8031aea030a41414b86c1125 + requires_dist: + - numpy>=1.17.3,<1.25.0 + requires_python: '>=3.8,<3.11' +- pypi: https://files.pythonhosted.org/packages/bc/fe/72b611ba221c3367b06163992af4807515d6e0e09b3b9beee8ec22162d6f/scipy-1.8.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: scipy + version: 1.8.1 + sha256: a0aa8220b89b2e3748a2836fbfa116194378910f1a6e78e4675a095bcd2c762d + requires_dist: + - numpy>=1.17.3,<1.25.0 + requires_python: '>=3.8,<3.11' +- pypi: https://files.pythonhosted.org/packages/78/2f/4966032c5f8cc7e6a60f1b2e0ad686293b9474b65246b0c642e3ef3badd0/scipy-1.15.3-cp310-cp310-macosx_10_13_x86_64.whl + name: scipy + version: 1.15.3 + sha256: a345928c86d535060c9c2b25e71e87c39ab2f22fc96e9636bd74d1dbf9de448c + requires_dist: + - numpy>=1.23.5,<2.5 + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.0,<2.1.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.0.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.0.292 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + - rich-click ; extra == 'dev' + - doit>=0.36.0 ; extra == 'dev' + - pydevtool ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/8e/6d/41991e503e51fc1134502694c5fa7a1671501a17ffa12716a4a9151af3df/scipy-1.15.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: scipy + version: 1.15.3 + sha256: 9e2abc762b0811e09a0d3258abee2d98e0c703eee49464ce0069590846f31d40 + requires_dist: + - numpy>=1.23.5,<2.5 + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.0,<2.1.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.0.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.0.292 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + - rich-click ; extra == 'dev' + - doit>=0.36.0 ; extra == 'dev' + - pydevtool ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/a0/6e/0c3bf90fae0e910c274db43304ebe25a6b391327f3f10b5dcc638c090795/scipy-1.15.3-cp310-cp310-macosx_12_0_arm64.whl + name: scipy + version: 1.15.3 + sha256: ad3432cb0f9ed87477a8d97f03b763fd1d57709f1bbde3c9369b1dff5503b253 + requires_dist: + - numpy>=1.23.5,<2.5 + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.0,<2.1.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.0.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.0.292 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + - rich-click ; extra == 'dev' + - doit>=0.36.0 ; extra == 'dev' + - pydevtool ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/d1/84/55bc4881973d3f79b479a5a2e2df61c8c9a04fcb986a213ac9c02cfb659b/scipy-1.15.3-cp310-cp310-win_amd64.whl + name: scipy + version: 1.15.3 + sha256: 9d61e97b186a57350f6d6fd72640f9e99d5a4a2b8fbf4b9ee9a841eab327dc13 + requires_dist: + - numpy>=1.23.5,<2.5 + - pytest ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.0,<2.1.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.0.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.0.292 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + - rich-click ; extra == 'dev' + - doit>=0.36.0 ; extra == 'dev' + - pydevtool ; extra == 'dev' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/01/8e/1e35281b8ab6d5d72ebe9911edcdffa3f36b04ed9d51dec6dd140396e220/scipy-1.17.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scipy + version: 1.17.1 + sha256: 02ae3b274fde71c5e92ac4d54bc06c42d80e399fec704383dcd99b301df37458 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/09/7d/af933f0f6e0767995b4e2d705a0665e454d1c19402aa7e895de3951ebb04/scipy-1.17.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scipy + version: 1.17.1 + sha256: 43af8d1f3bea642559019edfe64e9b11192a8978efbd1539d7bc2aaa23d92de4 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/0b/2e/7eea398450457ecb54e18e9d10110993fa65561c4f3add5e8eccd2b9cd41/scipy-1.17.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scipy + version: 1.17.1 + sha256: eee2cfda04c00a857206a4330f0c5e3e56535494e30ca445eb19ec624ae75118 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/35/48/b992b488d6f299dbe3f11a20b24d3dda3d46f1a635ede1c46b5b17a7b163/scipy-1.17.1-cp312-cp312-macosx_10_14_x86_64.whl + name: scipy + version: 1.17.1 + sha256: 35c3a56d2ef83efc372eaec584314bd0ef2e2f0d2adb21c55e6ad5b344c0dcb8 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/35/e5/d6d0e51fc888f692a35134336866341c08655d92614f492c6860dc45bb2c/scipy-1.17.1-cp313-cp313-win_amd64.whl + name: scipy + version: 1.17.1 + sha256: 37425bc9175607b0268f493d79a292c39f9d001a357bebb6b88fdfaff13f6448 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/4b/39/f0e8ea762a764a9dc52aa7dabcfad51a354819de1f0d4652b6a1122424d6/scipy-1.17.1-cp314-cp314-win_amd64.whl + name: scipy + version: 1.17.1 + sha256: 3877ac408e14da24a6196de0ddcace62092bfc12a83823e92e49e40747e52c19 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/76/27/07ee1b57b65e92645f219b37148a7e7928b82e2b5dbeccecb4dff7c64f0b/scipy-1.17.1-cp313-cp313-macosx_10_14_x86_64.whl + name: scipy + version: 1.17.1 + sha256: 5e3c5c011904115f88a39308379c17f91546f77c1667cea98739fe0fccea804c + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/95/da/0d1df507cf574b3f224ccc3d45244c9a1d732c81dcb26b1e8a766ae271a8/scipy-1.17.1-cp311-cp311-win_amd64.whl + name: scipy + version: 1.17.1 + sha256: d30e57c72013c2a4fe441c2fcb8e77b14e152ad48b5464858e07e2ad9fbfceff + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/a2/84/dc08d77fbf3d87d3ee27f6a0c6dcce1de5829a64f2eae85a0ecc1f0daa73/scipy-1.17.1-cp312-cp312-win_amd64.whl + name: scipy + version: 1.17.1 + sha256: 41b71f4a3a4cab9d366cd9065b288efc4d4f3c0b37a91a8e0947fb5bd7f31d87 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/b2/02/cf107b01494c19dc100f1d0b7ac3cc08666e96ba2d64db7626066cee895e/scipy-1.17.1-cp312-cp312-macosx_12_0_arm64.whl + name: scipy + version: 1.17.1 + sha256: fcb310ddb270a06114bb64bbe53c94926b943f5b7f0842194d585c65eb4edd76 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/cf/83/333afb452af6f0fd70414dc04f898647ee1423979ce02efa75c3b0f2c28e/scipy-1.17.1-cp314-cp314-macosx_10_14_x86_64.whl + name: scipy + version: 1.17.1 + sha256: a48a72c77a310327f6a3a920092fa2b8fd03d7deaa60f093038f22d98e096717 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/df/75/b4ce781849931fef6fd529afa6b63711d5a733065722d0c3e2724af9e40a/scipy-1.17.1-cp311-cp311-macosx_10_14_x86_64.whl + name: scipy + version: 1.17.1 + sha256: 1f95b894f13729334fb990162e911c9e5dc1ab390c58aa6cbecb389c5b5e28ec + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/ec/ae/db19f8ab842e9b724bf5dbb7db29302a91f1e55bc4d04b1025d6d605a2c5/scipy-1.17.1-cp313-cp313-macosx_12_0_arm64.whl + name: scipy + version: 1.17.1 + sha256: 6fac755ca3d2c3edcb22f479fceaa241704111414831ddd3bc6056e18516892f + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/ed/a6/d05a85fd51daeb2e4ea71d102f15b34fedca8e931af02594193ae4fd25f7/scipy-1.17.1-cp314-cp314-macosx_12_0_arm64.whl + name: scipy + version: 1.17.1 + sha256: 45abad819184f07240d8a696117a7aacd39787af9e0b719d00285549ed19a1e9 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/f5/5f/f17563f28ff03c7b6799c50d01d5d856a1d55f2676f537ca8d28c7f627cd/scipy-1.17.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl + name: scipy + version: 1.17.1 + sha256: 581b2264fc0aa555f3f435a5944da7504ea3a065d7029ad60e7c3d1ae09c5464 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/f7/58/bccc2861b305abdd1b8663d6130c0b3d7cc22e8d86663edbc8401bfd40d4/scipy-1.17.1-cp311-cp311-macosx_12_0_arm64.whl + name: scipy + version: 1.17.1 + sha256: e18f12c6b0bc5a592ed23d3f7b891f68fd7f8241d69b7883769eb5d5dfb52696 + requires_dist: + - numpy>=1.26.4,<2.7 + - pytest>=8.0.0 ; extra == 'test' + - pytest-cov ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-xdist ; extra == 'test' + - asv ; extra == 'test' + - mpmath ; extra == 'test' + - gmpy2 ; extra == 'test' + - threadpoolctl ; extra == 'test' + - scikit-umfpack ; extra == 'test' + - pooch ; extra == 'test' + - hypothesis>=6.30 ; extra == 'test' + - array-api-strict>=2.3.1 ; extra == 'test' + - cython ; extra == 'test' + - meson ; extra == 'test' + - ninja ; sys_platform != 'emscripten' and extra == 'test' + - sphinx>=5.0.0,<8.2.0 ; extra == 'doc' + - intersphinx-registry ; extra == 'doc' + - pydata-sphinx-theme>=0.15.2 ; extra == 'doc' + - sphinx-copybutton ; extra == 'doc' + - sphinx-design>=0.4.0 ; extra == 'doc' + - matplotlib>=3.5 ; extra == 'doc' + - numpydoc ; extra == 'doc' + - jupytext ; extra == 'doc' + - myst-nb>=1.2.0 ; extra == 'doc' + - pooch ; extra == 'doc' + - jupyterlite-sphinx>=0.19.1 ; extra == 'doc' + - jupyterlite-pyodide-kernel ; extra == 'doc' + - linkify-it-py ; extra == 'doc' + - tabulate ; extra == 'doc' + - click<8.3.0 ; extra == 'dev' + - spin ; extra == 'dev' + - mypy==1.10.0 ; extra == 'dev' + - typing-extensions ; extra == 'dev' + - types-psutil ; extra == 'dev' + - pycodestyle ; extra == 'dev' + - ruff>=0.12.0 ; extra == 'dev' + - cython-lint>=0.12.2 ; extra == 'dev' + requires_python: '>=3.11' +- pypi: https://files.pythonhosted.org/packages/1c/78/504fdd027da3b84ff1aecd9f6957e65f35134534ccc6da8628eb71e76d3f/send2trash-2.1.0-py3-none-any.whl + name: send2trash + version: 2.1.0 + sha256: 0da2f112e6d6bb22de6aa6daa7e144831a4febf2a87261451c4ad849fe9a873c + requires_dist: + - pytest>=8 ; extra == 'test' + - pywin32>=305 ; sys_platform == 'win32' and extra == 'nativelib' + - pyobjc>=9.0 ; sys_platform == 'darwin' and extra == 'nativelib' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/9d/76/f789f7a86709c6b087c5a2f52f911838cad707cc613162401badc665acfe/setuptools-82.0.1-py3-none-any.whl + name: setuptools + version: 82.0.1 + sha256: a59e362652f08dcd477c78bb6e7bd9d80a7995bc73ce773050228a348ce2e5bb + requires_dist: + - pytest>=6,!=8.1.* ; extra == 'test' + - virtualenv>=13.0.0 ; extra == 'test' + - wheel>=0.44.0 ; extra == 'test' + - pip>=19.1 ; extra == 'test' + - packaging>=24.2 ; extra == 'test' + - jaraco-envs>=2.2 ; extra == 'test' + - pytest-xdist>=3 ; extra == 'test' + - jaraco-path>=3.7.2 ; extra == 'test' + - build[virtualenv]>=1.0.3 ; extra == 'test' + - filelock>=3.4.0 ; extra == 'test' + - ini2toml[lite]>=0.14 ; extra == 'test' + - tomli-w>=1.0.0 ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest-perf ; sys_platform != 'cygwin' and extra == 'test' + - jaraco-develop>=7.21 ; python_full_version >= '3.9' and sys_platform != 'cygwin' and extra == 'test' + - pytest-home>=0.5 ; extra == 'test' + - pytest-subprocess ; extra == 'test' + - pyproject-hooks!=1.1 ; extra == 'test' + - jaraco-test>=5.5 ; extra == 'test' + - sphinx>=3.5 ; extra == 'doc' + - jaraco-packaging>=9.3 ; extra == 'doc' + - rst-linker>=1.9 ; extra == 'doc' + - furo ; extra == 'doc' + - sphinx-lint ; extra == 'doc' + - jaraco-tidelift>=1.4 ; extra == 'doc' + - pygments-github-lexers==0.0.5 ; extra == 'doc' + - sphinx-favicon ; extra == 'doc' + - sphinx-inline-tabs ; extra == 'doc' + - sphinx-reredirects ; extra == 'doc' + - sphinxcontrib-towncrier ; extra == 'doc' + - sphinx-notfound-page>=1,<2 ; extra == 'doc' + - pyproject-hooks!=1.1 ; extra == 'doc' + - towncrier<24.7 ; extra == 'doc' + - packaging>=24.2 ; extra == 'core' + - more-itertools>=8.8 ; extra == 'core' + - jaraco-text>=3.7 ; extra == 'core' + - importlib-metadata>=6 ; python_full_version < '3.10' and extra == 'core' + - tomli>=2.0.1 ; python_full_version < '3.11' and extra == 'core' + - wheel>=0.43.0 ; extra == 'core' + - jaraco-functools>=4 ; extra == 'core' + - more-itertools ; extra == 'core' + - pytest-checkdocs>=2.4 ; extra == 'check' + - pytest-ruff>=0.2.1 ; sys_platform != 'cygwin' and extra == 'check' + - ruff>=0.13.0 ; sys_platform != 'cygwin' and extra == 'check' + - pytest-cov ; extra == 'cover' + - pytest-enabler>=2.2 ; extra == 'enabler' + - pytest-mypy ; extra == 'type' + - mypy==1.18.* ; extra == 'type' + - importlib-metadata>=7.0.2 ; python_full_version < '3.10' and extra == 'type' + - jaraco-develop>=7.21 ; sys_platform != 'cygwin' and extra == 'type' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl + name: six + version: 1.17.0 + sha256: 4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 + requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*' +- pypi: https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl + name: soupsieve + version: 2.8.3 + sha256: ed64f2ba4eebeab06cc4962affce381647455978ffc1e36bb79a545b91f45a95 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl + name: stack-data + version: 0.6.3 + sha256: d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695 + requires_dist: + - executing>=1.2.0 + - asttokens>=2.1.0 + - pure-eval + - pytest ; extra == 'tests' + - typeguard ; extra == 'tests' + - pygments ; extra == 'tests' + - littleutils ; extra == 'tests' + - cython ; extra == 'tests' +- pypi: https://files.pythonhosted.org/packages/34/43/f47848a73f8d0a57b54a00bc5a75ca3e4671e90d66d335de341066900960/statsmodels-0.13.5-cp310-cp310-macosx_10_9_x86_64.whl + name: statsmodels + version: 0.13.5 + sha256: c75319fddded9507cc310fc3980e4ae4d64e3ff37b322ad5e203a84f89d85203 + requires_dist: + - pandas>=0.25 + - patsy>=0.5.2 + - packaging>=21.3 + - scipy>=1.3 ; (python_full_version < '3.10' and platform_machine != 'x86') or (python_full_version < '3.10' and sys_platform != 'win32') or (python_full_version >= '3.10' and python_full_version < '3.12') + - numpy>=1.17 ; python_full_version != '3.10.*' or (platform_python_implementation != 'PyPy' and sys_platform != 'win32') or platform_python_implementation == 'PyPy' + - numpy>=1.22.3 ; python_full_version == '3.10.*' and platform_python_implementation != 'PyPy' and sys_platform == 'win32' + - scipy>=1.3,<1.8 ; python_full_version == '3.7.*' + - scipy>=1.3,<1.9 ; python_full_version == '3.8.*' and platform_machine == 'x86' and sys_platform == 'win32' + - scipy>=1.3,<1.9 ; python_full_version == '3.9.*' and platform_machine == 'x86' and sys_platform == 'win32' + - cython>=0.29.32 ; extra == 'build' + - cython>=0.29.32 ; extra == 'develop' + - cython>=0.29.32,<3.0.0 ; extra == 'develop' + - setuptools-scm[toml]~=7.0.0 ; extra == 'develop' + - oldest-supported-numpy>=2022.4.18 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest~=7.0.1 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/b1/a5/3e573d7e0f79e8052628357ae75109b34293556fcd0709e75dee25eed0e4/statsmodels-0.13.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl + name: statsmodels + version: 0.13.5 + sha256: 072950d6f7820a6b0bd6a27b2d792a6d6f952a1d2f62f0dcf8dd808799475855 + requires_dist: + - pandas>=0.25 + - patsy>=0.5.2 + - packaging>=21.3 + - scipy>=1.3 ; (python_full_version < '3.10' and platform_machine != 'x86') or (python_full_version < '3.10' and sys_platform != 'win32') or (python_full_version >= '3.10' and python_full_version < '3.12') + - numpy>=1.17 ; python_full_version != '3.10.*' or (platform_python_implementation != 'PyPy' and sys_platform != 'win32') or platform_python_implementation == 'PyPy' + - numpy>=1.22.3 ; python_full_version == '3.10.*' and platform_python_implementation != 'PyPy' and sys_platform == 'win32' + - scipy>=1.3,<1.8 ; python_full_version == '3.7.*' + - scipy>=1.3,<1.9 ; python_full_version == '3.8.*' and platform_machine == 'x86' and sys_platform == 'win32' + - scipy>=1.3,<1.9 ; python_full_version == '3.9.*' and platform_machine == 'x86' and sys_platform == 'win32' + - cython>=0.29.32 ; extra == 'build' + - cython>=0.29.32 ; extra == 'develop' + - cython>=0.29.32,<3.0.0 ; extra == 'develop' + - setuptools-scm[toml]~=7.0.0 ; extra == 'develop' + - oldest-supported-numpy>=2022.4.18 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest~=7.0.1 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/bf/0b/7f303511e59a4434dd0e9a8c4d550b7a5f32acb7c94821ccd3a465ef3137/statsmodels-0.13.5-cp310-cp310-win_amd64.whl + name: statsmodels + version: 0.13.5 + sha256: 159ae9962c61b31dcffe6356d72ae3d074bc597ad9273ec93ae653fe607b8516 + requires_dist: + - pandas>=0.25 + - patsy>=0.5.2 + - packaging>=21.3 + - scipy>=1.3 ; (python_full_version < '3.10' and platform_machine != 'x86') or (python_full_version < '3.10' and sys_platform != 'win32') or (python_full_version >= '3.10' and python_full_version < '3.12') + - numpy>=1.17 ; python_full_version != '3.10.*' or (platform_python_implementation != 'PyPy' and sys_platform != 'win32') or platform_python_implementation == 'PyPy' + - numpy>=1.22.3 ; python_full_version == '3.10.*' and platform_python_implementation != 'PyPy' and sys_platform == 'win32' + - scipy>=1.3,<1.8 ; python_full_version == '3.7.*' + - scipy>=1.3,<1.9 ; python_full_version == '3.8.*' and platform_machine == 'x86' and sys_platform == 'win32' + - scipy>=1.3,<1.9 ; python_full_version == '3.9.*' and platform_machine == 'x86' and sys_platform == 'win32' + - cython>=0.29.32 ; extra == 'build' + - cython>=0.29.32 ; extra == 'develop' + - cython>=0.29.32,<3.0.0 ; extra == 'develop' + - setuptools-scm[toml]~=7.0.0 ; extra == 'develop' + - oldest-supported-numpy>=2022.4.18 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest~=7.0.1 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/e0/9c/3f92cb98d9e632ad8e38b9bb45f332be57c6cc74852da936a18f97f76ab7/statsmodels-0.13.5-cp310-cp310-macosx_11_0_arm64.whl + name: statsmodels + version: 0.13.5 + sha256: 6f148920ef27c7ba69a5735724f65de9422c0c8bcef71b50c846b823ceab8840 + requires_dist: + - pandas>=0.25 + - patsy>=0.5.2 + - packaging>=21.3 + - scipy>=1.3 ; (python_full_version < '3.10' and platform_machine != 'x86') or (python_full_version < '3.10' and sys_platform != 'win32') or (python_full_version >= '3.10' and python_full_version < '3.12') + - numpy>=1.17 ; python_full_version != '3.10.*' or (platform_python_implementation != 'PyPy' and sys_platform != 'win32') or platform_python_implementation == 'PyPy' + - numpy>=1.22.3 ; python_full_version == '3.10.*' and platform_python_implementation != 'PyPy' and sys_platform == 'win32' + - scipy>=1.3,<1.8 ; python_full_version == '3.7.*' + - scipy>=1.3,<1.9 ; python_full_version == '3.8.*' and platform_machine == 'x86' and sys_platform == 'win32' + - scipy>=1.3,<1.9 ; python_full_version == '3.9.*' and platform_machine == 'x86' and sys_platform == 'win32' + - cython>=0.29.32 ; extra == 'build' + - cython>=0.29.32 ; extra == 'develop' + - cython>=0.29.32,<3.0.0 ; extra == 'develop' + - setuptools-scm[toml]~=7.0.0 ; extra == 'develop' + - oldest-supported-numpy>=2022.4.18 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest~=7.0.1 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/05/30/affbabf3c27fb501ec7b5808230c619d4d1a4525c07301074eb4bda92fa9/statsmodels-0.14.6-cp312-cp312-macosx_11_0_arm64.whl + name: statsmodels + version: 0.14.6 + sha256: 26d4f0ed3b31f3c86f83a92f5c1f5cbe63fc992cd8915daf28ca49be14463a1c + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/10/b9/fd41f1f6af13a1a1212a06bb377b17762feaa6d656947bf666f76300fc05/statsmodels-0.14.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: 730f3297b26749b216a06e4327fe0be59b8d05f7d594fb6caff4287b69654589 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/25/ce/308e5e5da57515dd7cab3ec37ea2d5b8ff50bef1fcc8e6d31456f9fae08e/statsmodels-0.14.6-cp312-cp312-macosx_10_13_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: fe76140ae7adc5ff0e60a3f0d56f4fffef484efa803c3efebf2fcd734d72ecb5 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/26/33/f1652d0c59fa51de18492ee2345b65372550501ad061daa38f950be390b6/statsmodels-0.14.6-cp314-cp314-win_amd64.whl + name: statsmodels + version: 0.14.6 + sha256: 151b73e29f01fe619dbce7f66d61a356e9d1fe5e906529b78807df9189c37721 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/34/0e/2408735aca9e764643196212f9069912100151414dd617d39ffc72d77eee/statsmodels-0.14.6-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: 3414e40c073d725007a6603a18247ab7af3467e1af4a5e5a24e4c27bc26673b4 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/40/c6/9ae8e9b0721e9b6eb5f340c3a0ce8cd7cce4f66e03dd81f80d60f111987f/statsmodels-0.14.6-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: a3764ba8195c9baf0925a96da0743ff218067a269f01d155ca3558deed2658ca + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/53/dd/d8cfa7922fc6dc3c56fa6c59b348ea7de829a94cd73208c6f8202dd33f17/statsmodels-0.14.6-cp313-cp313-macosx_11_0_arm64.whl + name: statsmodels + version: 0.14.6 + sha256: aa60d82e29fcd0a736e86feb63a11d2380322d77a9369a54be8b0965a3985f71 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/60/15/3daba2df40be8b8a9a027d7f54c8dedf24f0d81b96e54b52293f5f7e3418/statsmodels-0.14.6-cp312-cp312-win_amd64.whl + name: statsmodels + version: 0.14.6 + sha256: b5eb07acd115aa6208b4058211138393a7e6c2cf12b6f213ede10f658f6a714f + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/71/de/09540e870318e0c7b58316561d417be45eff731263b4234fdd2eee3511a8/statsmodels-0.14.6-cp314-cp314-macosx_10_15_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: 00781869991f8f02ad3610da6627fd26ebe262210287beb59761982a8fa88cae + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/81/59/a5aad5b0cc266f5be013db8cde563ac5d2a025e7efc0c328d83b50c72992/statsmodels-0.14.6-cp313-cp313-macosx_10_13_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: 47ee7af083623d2091954fa71c7549b8443168f41b7c5dce66510274c50fd73e + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/81/68/dddd76117df2ef14c943c6bbb6618be5c9401280046f4ddfc9fb4596a1b8/statsmodels-0.14.6-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: 19b58cf7474aa9e7e3b0771a66537148b2df9b5884fbf156096c0e6c1ff0469d + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/82/af/ec48daa7f861f993b91a0dcc791d66e1cf56510a235c5cbd2ab991a31d5c/statsmodels-0.14.6-cp311-cp311-macosx_11_0_arm64.whl + name: statsmodels + version: 0.14.6 + sha256: 341fa68a7403e10a95c7b6e41134b0da3a7b835ecff1eb266294408535a06eb6 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/86/8f/338c5568315ec5bf3ac7cd4b71e34b98cb3b0f834919c0c04a0762f878a1/statsmodels-0.14.6-cp310-cp310-macosx_11_0_arm64.whl + name: statsmodels + version: 0.14.6 + sha256: 109012088b3e370080846ab053c76d125268631410142daad2f8c10770e8e8d9 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/94/55/b86c861c32186403fe121d9ab27bc16d05839b170d92a978beb33abb995e/statsmodels-0.14.6-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: 06eec42d682fdb09fe5d70a05930857efb141754ec5a5056a03304c1b5e32fd9 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/98/08/b79f0c614f38e566eebbdcff90c0bcacf3c6ba7a5bbb12183c09c29ca400/statsmodels-0.14.6-cp313-cp313-win_amd64.whl + name: statsmodels + version: 0.14.6 + sha256: 8021271a79f35b842c02a1794465a651a9d06ec2080f76ebc3b7adce77d08233 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/9a/1c/2e10b7c7cc44fa418272996bf0427b8016718fd62f995d9c1f7ab37adf35/statsmodels-0.14.6-cp310-cp310-win_amd64.whl + name: statsmodels + version: 0.14.6 + sha256: e83a9abe653835da3b37fb6ae04b45480c1de11b3134bd40b09717192a1456ea + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/a9/4d/df4dd089b406accfc3bb5ee53ba29bb3bdf5ae61643f86f8f604baa57656/statsmodels-0.14.6-cp311-cp311-macosx_10_9_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: 6ad5c2810fc6c684254a7792bf1cbaf1606cdee2a253f8bd259c43135d87cfb4 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/ab/f0/63c1bfda75dc53cee858006e1f46bd6d6f883853bea1b97949d0087766ca/statsmodels-0.14.6-cp314-cp314-macosx_11_0_arm64.whl + name: statsmodels + version: 0.14.6 + sha256: 73f305fbf31607b35ce919fae636ab8b80d175328ed38fdc6f354e813b86ee37 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/b5/6d/9ec309a175956f88eb8420ac564297f37cf9b1f73f89db74da861052dc29/statsmodels-0.14.6-cp310-cp310-macosx_10_9_x86_64.whl + name: statsmodels + version: 0.14.6 + sha256: f4ff0649a2df674c7ffb6fa1a06bffdb82a6adf09a48e90e000a15a6aaa734b0 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/bf/cc/018f14ecb58c6cb89de9d52695740b7d1f5a982aa9ea312483ea3c3d5f77/statsmodels-0.14.6-cp311-cp311-win_amd64.whl + name: statsmodels + version: 0.14.6 + sha256: 2738a00fca51196f5a7d44b06970ace6b8b30289839e4808d656f8a98e35faa7 + requires_dist: + - numpy>=1.22.3,<3 + - scipy>=1.8,!=1.9.2 + - pandas>=1.4,!=2.1.0 + - patsy>=0.5.6 + - packaging>=21.3 + - cython>=3.0.10 ; extra == 'build' + - cython>=3.0.10 ; extra == 'develop' + - cython>=3.0.10,<4 ; extra == 'develop' + - setuptools-scm[toml]~=8.0 ; extra == 'develop' + - matplotlib>=3 ; extra == 'develop' + - colorama ; extra == 'develop' + - joblib ; extra == 'develop' + - jinja2 ; extra == 'develop' + - pytest>=7.3.0,<8 ; extra == 'develop' + - pytest-randomly ; extra == 'develop' + - pytest-xdist ; extra == 'develop' + - pytest-cov ; extra == 'develop' + - pywinpty ; os_name == 'nt' and extra == 'develop' + - flake8 ; extra == 'develop' + - isort ; extra == 'develop' + - sphinx ; extra == 'docs' + - nbconvert ; extra == 'docs' + - jupyter-client ; extra == 'docs' + - ipykernel ; extra == 'docs' + - matplotlib ; extra == 'docs' + - nbformat ; extra == 'docs' + - numpydoc ; extra == 'docs' + - pandas-datareader ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/99/55/db07de81b5c630da5cbf5c7df646580ca26dfaefa593667fc6f2fe016d2e/tabulate-0.10.0-py3-none-any.whl + name: tabulate + version: 0.10.0 + sha256: f0b0622e567335c8fabaaa659f1b33bcb6ddfe2e496071b743aa113f8774f2d3 + requires_dist: + - wcwidth ; extra == 'widechars' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl + name: terminado + version: 0.18.1 + sha256: a4468e1b37bb318f8a86514f65814e1afc977cf29b3992a4500d9dd305dcceb0 + requires_dist: + - ptyprocess ; os_name != 'nt' + - pywinpty>=1.1.0 ; os_name == 'nt' + - tornado>=6.1.0 + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx ; extra == 'docs' + - pre-commit ; extra == 'test' + - pytest-timeout ; extra == 'test' + - pytest>=7.0 ; extra == 'test' + - mypy~=1.6 ; extra == 'typing' + - traitlets>=5.11.1 ; extra == 'typing' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl + name: threadpoolctl + version: 3.6.0 + sha256: 43a0b8fd5a2928500110039e43a5eed8480b918967083ea48dc3ab9f13c4a7fb + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl + name: tinycss2 + version: 1.4.0 + sha256: 3a49cf47b7675da0b15d0c6e1df8df4ebd96e9394bb905a5775adb0d884c5289 + requires_dist: + - webencodings>=0.4 + - sphinx ; extra == 'doc' + - sphinx-rtd-theme ; extra == 'doc' + - pytest ; extra == 'test' + - ruff ; extra == 'test' + requires_python: '>=3.8' +- conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda + sha256: cafeec44494f842ffeca27e9c8b0c27ed714f93ac77ddadc6aaf726b5554ebac + md5: cffd3bdd58090148f4cfcd831f4b26ab + depends: + - __glibc >=2.17,<3.0.a0 + - libgcc >=14 + - libzlib >=1.3.1,<2.0a0 + constrains: + - xorg-libx11 >=1.8.12,<2.0a0 + license: TCL + license_family: BSD + purls: [] + size: 3301196 + timestamp: 1769460227866 +- conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda + sha256: 7f0d9c320288532873e2d8486c331ec6d87919c9028208d3f6ac91dc8f99a67b + md5: 6e6efb7463f8cef69dbcb4c2205bf60e + depends: + - __osx >=10.13 + - libzlib >=1.3.1,<2.0a0 + license: TCL + license_family: BSD + purls: [] + size: 3282953 + timestamp: 1769460532442 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda + sha256: 799cab4b6cde62f91f750149995d149bc9db525ec12595e8a1d91b9317f038b3 + md5: a9d86bc62f39b94c4661716624eb21b0 + depends: + - __osx >=11.0 + - libzlib >=1.3.1,<2.0a0 + license: TCL + license_family: BSD + purls: [] + size: 3127137 + timestamp: 1769460817696 +- conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h6ed50ae_3.conda + sha256: 0e79810fae28f3b69fe7391b0d43f5474d6bd91d451d5f2bde02f55ae481d5e3 + md5: 0481bfd9814bf525bd4b3ee4b51494c4 + depends: + - ucrt >=10.0.20348.0 + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + license: TCL + license_family: BSD + purls: [] + size: 3526350 + timestamp: 1769460339384 +- pypi: https://files.pythonhosted.org/packages/23/d1/136eb2cb77520a31e1f64cbae9d33ec6df0d78bdf4160398e86eec8a8754/tomli-2.4.0-py3-none-any.whl + name: tomli + version: 2.4.0 + sha256: 1f776e7d669ebceb01dee46484485f43a4048746235e683bcdffacdf1fb4785a + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/2c/23/f6c6112a04d28eed765e374435fb1a9198f73e1ec4b4024184f21faeb1ad/tornado-6.5.5-cp39-abi3-win_amd64.whl + name: tornado + version: 6.5.5 + sha256: 6443a794ba961a9f619b1ae926a2e900ac20c34483eea67be4ed8f1e58d3ef7b + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/59/8c/77f5097695f4dd8255ecbd08b2a1ed8ba8b953d337804dd7080f199e12bf/tornado-6.5.5-cp39-abi3-macosx_10_9_universal2.whl + name: tornado + version: 6.5.5 + sha256: 487dc9cc380e29f58c7ab88f9e27cdeef04b2140862e5076a66fb6bb68bb1bfa + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/ab/5e/7625b76cd10f98f1516c36ce0346de62061156352353ef2da44e5c21523c/tornado-6.5.5-cp39-abi3-macosx_10_9_x86_64.whl + name: tornado + version: 6.5.5 + sha256: 65a7f1d46d4bb41df1ac99f5fcb685fb25c7e61613742d5108b010975a9a6521 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/b2/04/7b5705d5b3c0fab088f434f9c83edac1573830ca49ccf29fb83bf7178eec/tornado-6.5.5-cp39-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + name: tornado + version: 6.5.5 + sha256: e74c92e8e65086b338fd56333fb9a68b9f6f2fe7ad532645a290a464bcf46be5 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl + name: traitlets + version: 5.14.3 + sha256: b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f + requires_dist: + - myst-parser ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - sphinx ; extra == 'docs' + - argcomplete>=3.0.3 ; extra == 'test' + - mypy>=1.7.0 ; extra == 'test' + - pre-commit ; extra == 'test' + - pytest-mock ; extra == 'test' + - pytest-mypy-testing ; extra == 'test' + - pytest>=7.0,<8.2 ; extra == 'test' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl + name: typing-extensions + version: 4.15.0 + sha256: f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548 + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl + name: tzdata + version: '2025.3' + sha256: 06a47e5700f3081aab02b2e513160914ff0694bce9947d6b76ebd6bf57cfc5d1 + requires_python: '>=2' +- conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda + sha256: 1d30098909076af33a35017eed6f2953af1c769e273a0626a04722ac4acaba3c + md5: ad659d0a2b3e47e38d829aa8cad2d610 + license: LicenseRef-Public-Domain + purls: [] + size: 119135 + timestamp: 1767016325805 +- conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda + sha256: 3005729dce6f3d3f5ec91dfc49fc75a0095f9cd23bab49efb899657297ac91a5 + md5: 71b24316859acd00bdb8b38f5e2ce328 + constrains: + - vc14_runtime >=14.29.30037 + - vs2015_runtime >=14.29.30037 + license: LicenseRef-MicrosoftWindowsSDK10 + purls: [] + size: 694692 + timestamp: 1756385147981 +- pypi: https://files.pythonhosted.org/packages/e7/00/3fca040d7cf8a32776d3d81a00c8ee7457e00f80c649f1e4a863c8321ae9/uri_template-1.3.0-py3-none-any.whl + name: uri-template + version: 1.3.0 + sha256: a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363 + requires_dist: + - types-pyyaml ; extra == 'dev' + - mypy ; extra == 'dev' + - flake8 ; extra == 'dev' + - flake8-annotations ; extra == 'dev' + - flake8-bandit ; extra == 'dev' + - flake8-bugbear ; extra == 'dev' + - flake8-commas ; extra == 'dev' + - flake8-comprehensions ; extra == 'dev' + - flake8-continuation ; extra == 'dev' + - flake8-datetimez ; extra == 'dev' + - flake8-docstrings ; extra == 'dev' + - flake8-import-order ; extra == 'dev' + - flake8-literal ; extra == 'dev' + - flake8-modern-annotations ; extra == 'dev' + - flake8-noqa ; extra == 'dev' + - flake8-pyproject ; extra == 'dev' + - flake8-requirements ; extra == 'dev' + - flake8-typechecking-import ; extra == 'dev' + - flake8-use-fstring ; extra == 'dev' + - pep8-naming ; extra == 'dev' + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl + name: urllib3 + version: 2.6.3 + sha256: bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4 + requires_dist: + - brotli>=1.2.0 ; platform_python_implementation == 'CPython' and extra == 'brotli' + - brotlicffi>=1.2.0.0 ; platform_python_implementation != 'CPython' and extra == 'brotli' + - h2>=4,<5 ; extra == 'h2' + - pysocks>=1.5.6,!=1.5.7,<2.0 ; extra == 'socks' + - backports-zstd>=1.0.0 ; python_full_version < '3.14' and extra == 'zstd' + requires_python: '>=3.9' +- conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h41ae7f8_34.conda + sha256: 9dc40c2610a6e6727d635c62cced5ef30b7b30123f5ef67d6139e23d21744b3a + md5: 1e610f2416b6acdd231c5f573d754a0f + depends: + - vc14_runtime >=14.44.35208 + track_features: + - vc14 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 19356 + timestamp: 1767320221521 +- conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda + sha256: 02732f953292cce179de9b633e74928037fa3741eb5ef91c3f8bae4f761d32a5 + md5: 37eb311485d2d8b2c419449582046a42 + depends: + - ucrt >=10.0.20348.0 + - vcomp14 14.44.35208 h818238b_34 + constrains: + - vs2015_runtime 14.44.35208.* *_34 + license: LicenseRef-MicrosoftVisualCpp2015-2022Runtime + license_family: Proprietary + purls: [] + size: 683233 + timestamp: 1767320219644 +- conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda + sha256: 878d5d10318b119bd98ed3ed874bd467acbe21996e1d81597a1dbf8030ea0ce6 + md5: 242d9f25d2ae60c76b38a5e42858e51d + depends: + - ucrt >=10.0.20348.0 + constrains: + - vs2015_runtime 14.44.35208.* *_34 + license: LicenseRef-MicrosoftVisualCpp2015-2022Runtime + license_family: Proprietary + purls: [] + size: 115235 + timestamp: 1767320173250 +- pypi: https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl + name: wcwidth + version: 0.6.0 + sha256: 1a3a1e510b553315f8e146c54764f4fb6264ffad731b3d78088cdb1478ffbdad + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/e2/cc/e097523dd85c9cf5d354f78310927f1656c422bd7b2613b2db3e3f9a0f2c/webcolors-25.10.0-py3-none-any.whl + name: webcolors + version: 25.10.0 + sha256: 032c727334856fc0b968f63daa252a1ac93d33db2f5267756623c210e57a4f1d + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl + name: webencodings + version: 0.5.1 + sha256: a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78 +- pypi: https://files.pythonhosted.org/packages/34/db/b10e48aa8fff7407e67470363eac595018441cf32d5e1001567a7aeba5d2/websocket_client-1.9.0-py3-none-any.whl + name: websocket-client + version: 1.9.0 + sha256: af248a825037ef591efbf6ed20cc5faa03d3b47b9e5a2230a529eeee1c1fc3ef + requires_dist: + - pytest ; extra == 'test' + - websockets ; extra == 'test' + - python-socks ; extra == 'optional' + - wsaccel ; extra == 'optional' + - sphinx>=6.0 ; extra == 'docs' + - sphinx-rtd-theme>=1.1.0 ; extra == 'docs' + - myst-parser>=2.0.0 ; extra == 'docs' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl + name: widgetsnbextension + version: 4.0.15 + sha256: 8156704e4346a571d9ce73b84bee86a29906c9abfd7223b7228a28899ccf3366 + requires_python: '>=3.7' +- pypi: https://files.pythonhosted.org/packages/19/10/96bb5b2985677cf6cd8f1f0a85e5e58710ad7946c5a6f202a57e9f13dc3b/xgboost-1.7.0.post0-py3-none-manylinux2014_x86_64.whl + name: xgboost + version: 1.7.0.post0 + sha256: fdc1d50a535fa1485b85dc4a259e5be21149464b29be8ea0cb702891fdb662c5 + requires_dist: + - numpy + - scipy + - dask ; extra == 'dask' + - pandas ; extra == 'dask' + - distributed ; extra == 'dask' + - datatable ; extra == 'datatable' + - pandas ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - pyspark ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - cloudpickle ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/74/89/3faeac4661c2431422207c6694a84b6ab52ce85e1d87aac0420e9d83b82f/xgboost-1.7.0.post0-py3-none-macosx_12_0_arm64.whl + name: xgboost + version: 1.7.0.post0 + sha256: 1f788078b5d7d1adece948ad42d2e5422a05ac5b31177530f60ba4a6aed25cb0 + requires_dist: + - numpy + - scipy + - dask ; extra == 'dask' + - pandas ; extra == 'dask' + - distributed ; extra == 'dask' + - datatable ; extra == 'datatable' + - pandas ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - pyspark ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - cloudpickle ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/85/ef/d8910ec6229a45b4d8d920858b91f7196eafabad254be9eb508b934d3c18/xgboost-1.7.0.post0-py3-none-win_amd64.whl + name: xgboost + version: 1.7.0.post0 + sha256: 5058fcc6aa262eb5cc00ef028e0f2eeeba23c414863fa1c06bddebef2728989c + requires_dist: + - numpy + - scipy + - dask ; extra == 'dask' + - pandas ; extra == 'dask' + - distributed ; extra == 'dask' + - datatable ; extra == 'datatable' + - pandas ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - pyspark ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - cloudpickle ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/f3/75/f2b9d58d9bfa2dfa7e5fd287eb724d956c587e1facf3e133dab8c78544b7/xgboost-1.7.0.post0-py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64.whl + name: xgboost + version: 1.7.0.post0 + sha256: f5a1d52c6e82419eba14766013d8e4abd7d186a83a00ab51f93b852ee6ceca81 + requires_dist: + - numpy + - scipy + - dask ; extra == 'dask' + - pandas ; extra == 'dask' + - distributed ; extra == 'dask' + - datatable ; extra == 'datatable' + - pandas ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - pyspark ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - cloudpickle ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/1f/3d/1661dd114a914a67e3f7ab66fa1382e7599c2a8c340f314ad30a3e2b4d08/xgboost-3.2.0-py3-none-win_amd64.whl + name: xgboost + version: 3.2.0 + sha256: 0d169736fd836fc13646c7ab787167b3a8110351c2c6bc770c755ee1618f0442 + requires_dist: + - numpy + - nvidia-nccl-cu12 ; sys_platform == 'linux' + - scipy + - dask ; extra == 'dask' + - distributed ; extra == 'dask' + - pandas ; extra == 'dask' + - pandas>=1.2 ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - cloudpickle ; extra == 'pyspark' + - pyspark>=3.4 ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/2d/49/6e4cdd877c24adf56cb3586bc96d93d4dcd780b5ea1efb32e1ee0de08bae/xgboost-3.2.0-py3-none-macosx_10_15_x86_64.whl + name: xgboost + version: 3.2.0 + sha256: 2f661966d3e322536d9c448090a870fcba1e32ee5760c10b7c46bac7a342079a + requires_dist: + - numpy + - nvidia-nccl-cu12 ; sys_platform == 'linux' + - scipy + - dask ; extra == 'dask' + - distributed ; extra == 'dask' + - pandas ; extra == 'dask' + - pandas>=1.2 ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - cloudpickle ; extra == 'pyspark' + - pyspark>=3.4 ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/79/98/679de17c2caa4fd3b0b4386ecf7377301702cb0afb22930a07c142fcb1d8/xgboost-3.2.0-py3-none-manylinux_2_28_x86_64.whl + name: xgboost + version: 3.2.0 + sha256: 99b4a6bbcb47212fec5cf5fbe12347215f073c08967431b0122cfbd1ee70312c + requires_dist: + - numpy + - nvidia-nccl-cu12 ; sys_platform == 'linux' + - scipy + - dask ; extra == 'dask' + - distributed ; extra == 'dask' + - pandas ; extra == 'dask' + - pandas>=1.2 ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - cloudpickle ; extra == 'pyspark' + - pyspark>=3.4 ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/93/f1/c09ef1add609453aa3ba5bafcd0d1c1a805c1263c0b60138ec968f8ec296/xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl + name: xgboost + version: 3.2.0 + sha256: eabbd40d474b8dbf6cb3536325f9150b9e6f0db32d18de9914fb3227d0bef5b7 + requires_dist: + - numpy + - nvidia-nccl-cu12 ; sys_platform == 'linux' + - scipy + - dask ; extra == 'dask' + - distributed ; extra == 'dask' + - pandas ; extra == 'dask' + - pandas>=1.2 ; extra == 'pandas' + - graphviz ; extra == 'plotting' + - matplotlib ; extra == 'plotting' + - cloudpickle ; extra == 'pyspark' + - pyspark>=3.4 ; extra == 'pyspark' + - scikit-learn ; extra == 'pyspark' + - scikit-learn ; extra == 'scikit-learn' + requires_python: '>=3.10' +- conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda + sha256: 68f0206ca6e98fea941e5717cec780ed2873ffabc0e1ed34428c061e2c6268c7 + md5: 4a13eeac0b5c8e5b8ab496e6c4ddd829 + depends: + - __glibc >=2.17,<3.0.a0 + - libzlib >=1.3.1,<2.0a0 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 601375 + timestamp: 1764777111296 +- conda: https://conda.anaconda.org/conda-forge/osx-64/zstd-1.5.7-h3eecb57_6.conda + sha256: 47101a4055a70a4876ffc87b750ab2287b67eca793f21c8224be5e1ee6394d3f + md5: 727109b184d680772e3122f40136d5ca + depends: + - __osx >=10.13 + - libzlib >=1.3.1,<2.0a0 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 528148 + timestamp: 1764777156963 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.7-hbf9d68e_6.conda + sha256: 9485ba49e8f47d2b597dd399e88f4802e100851b27c21d7525625b0b4025a5d9 + md5: ab136e4c34e97f34fb621d2592a393d8 + depends: + - __osx >=11.0 + - libzlib >=1.3.1,<2.0a0 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 433413 + timestamp: 1764777166076 +- conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda + sha256: 368d8628424966fd8f9c8018326a9c779e06913dd39e646cf331226acc90e5b2 + md5: 053b84beec00b71ea8ff7a4f84b55207 + depends: + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + - ucrt >=10.0.20348.0 + - libzlib >=1.3.1,<2.0a0 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 388453 + timestamp: 1764777142545 diff --git a/pyproject.toml b/pyproject.toml index cba8f683a..228386be3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -35,6 +35,7 @@ classifiers = [ "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", + "Programming Language :: Python :: 3.14", "Topic :: Scientific/Engineering", ] dependencies = [ @@ -45,10 +46,10 @@ dependencies = [ "scipy >= 1.8.1", "h5py >= 3.7.0", "plotly >= 4.0.0", - "xgboost >= 1.6.0", - "pvlib >= 0.12.0", + "xgboost >= 1.7.0", + "pvlib >= 0.13.1", "scikit-learn >= 1.1.3, != 1.6.0", - "arch >= 5.0", + "arch >= 5.6", "filterpy >= 1.4.2", ] @@ -69,19 +70,18 @@ test = [ "nbval >= 0.10.0", "pytest-mock", ] +notebooks = [ + "jupyter", + "ipywidgets", + "numexpr >= 2.10.2", + "tabulate >= 0.9.0", + "lxml", +] +dev = [ + "rdtools[notebooks,test]", +] all = [ - "coverage", - "flake8", - "ipython", - "nbsphinx==0.9.5", - "nbsphinx-link==1.3.1", - "nbval >= 0.10.0", - "pytest >= 3.10.1", - "pytest-cov", - "pytest-mock", - "sphinx==7.4.7", - "sphinx-gallery==0.18.0", - "sphinx_rtd_theme==3.0.1", + "rdtools[dev,doc]", ] [project.urls] @@ -103,3 +103,92 @@ addopts = "--verbose" filterwarnings = [ "ignore:The .* module is currently experimental:UserWarning:rdtools", ] + +# --- Pixi configuration --- + +[tool.pixi.workspace] +channels = ["conda-forge"] +platforms = ["win-64", "linux-64", "osx-64", "osx-arm64"] + +[tool.pixi.pypi-dependencies] +rdtools = { path = ".", editable = true } + +[tool.pixi.dependencies] +python = ">=3.10" + +# macOS requires llvm-openmp for XGBoost +[tool.pixi.target.osx-64.dependencies] +llvm-openmp = "*" + +[tool.pixi.target.osx-arm64.dependencies] +llvm-openmp = "*" + +# --- Python version features --- + +[tool.pixi.feature.py310.dependencies] +python = "~=3.10.0" + +[tool.pixi.feature.py311.dependencies] +python = "~=3.11.0" + +[tool.pixi.feature.py312.dependencies] +python = "~=3.12.0" + +[tool.pixi.feature.py313.dependencies] +python = "~=3.13.0" + +[tool.pixi.feature.py314.dependencies] +python = "~=3.14.0" + +# --- Extra features --- + +[tool.pixi.feature.notebooks.pypi-dependencies] +rdtools = { path = ".", editable = true, extras = ["notebooks"] } + +[tool.pixi.feature.test.pypi-dependencies] +rdtools = { path = ".", editable = true, extras = ["test"] } + +[tool.pixi.feature.dev.pypi-dependencies] +rdtools = { path = ".", editable = true, extras = ["dev"] } + +# Minimum version pins (matching lower bounds in [project.dependencies]) +[tool.pixi.feature.min.pypi-dependencies] +matplotlib = "==3.5.3" +numpy = "==1.22.4" +pandas = "==1.4.4" +statsmodels = "==0.13.5" +scipy = "==1.8.1" +h5py = "==3.7.0" +plotly = "==4.0.0" +xgboost = "==1.7.0.post0" +pvlib = "==0.13.1" +scikit-learn = "==1.1.3" +arch = "==5.6.0" +filterpy = "==1.4.2" + +# --- Environments --- + +[tool.pixi.environments] +core = { features = ["py313"], solve-group = "default" } +default = { features = ["notebooks", "py313"], solve-group = "default" } +dev = { features = ["notebooks", "dev", "py313"], solve-group = "default" } +dev-py310 = { features = ["notebooks", "dev", "py310"] } +dev-py311 = { features = ["notebooks", "dev", "py311"] } +dev-py312 = { features = ["notebooks", "dev", "py312"] } +dev-py313 = { features = ["notebooks", "dev", "py313"], solve-group = "default" } +dev-py314 = { features = ["notebooks", "dev", "py314"] } +dev-min = { features = ["test", "min", "py310"] } + +# --- Tasks --- + +[tool.pixi.tasks] + +[tool.pixi.feature.notebooks.tasks] +lab = "jupyter lab docs/" + +[tool.pixi.feature.test.tasks] +test = "pytest --cov=rdtools --cov-report=xml rdtools/test/" + +[tool.pixi.feature.dev.tasks] +test = "pytest --cov=rdtools --cov-report=xml rdtools/test/" +nbval = "pytest --nbval --nbval-sanitize-with docs/nbval_sanitization_rules.cfg docs/" diff --git a/requirements-min.txt b/requirements-min.txt deleted file mode 100644 index 2362cd30e..000000000 --- a/requirements-min.txt +++ /dev/null @@ -1,12 +0,0 @@ -matplotlib==3.5.3 -numpy==1.22.4 -pandas==1.4.4 -statsmodels==0.13.5 -scipy==1.8.1 -h5py==3.7.0 -plotly==4.0.0 -xgboost==1.7.0.post0 -pvlib==0.13.1 -scikit-learn==1.1.3 -arch==5.6 -filterpy==1.4.5 diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index f1a4f7f92..000000000 --- a/requirements.txt +++ /dev/null @@ -1,35 +0,0 @@ -cached-property==1.5.2 -certifi==2024.7.4 -chardet==5.2.0 -cycler==0.12.1 -fonttools==4.58.4 -h5py==3.12.0 -idna==3.8 -joblib==1.5.2 -kiwisolver==1.4.6 -matplotlib==3.9.4 -numpy==2.1.1 -packaging==26.0 -pandas==2.2.3 -patsy==1.0.0 -Pillow==12.1.1 -plotly==6.1.1 -pvlib==0.14.0 -pyparsing==3.2.0 -python-dateutil==2.9.0 -pytz==2025.2 -arch==7.0.0 -filterpy==1.4.5 -requests==2.32.4 -retrying==1.3.4 -scikit-learn==1.7.2 -scipy==1.14.1 -setuptools-scm==9.2.2 -six==1.17.0 -statsmodels==0.14.6 -threadpoolctl==3.6.0 -tomli==2.0.2 -typing_extensions==4.15.0 -urllib3==2.6.3 -xgboost==3.1.3 - From 2538d16ff384cc864de2fce3583e9b517f08633b Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 11:33:21 -0400 Subject: [PATCH 11/18] move changelog from pending to 3.2.1 --- docs/sphinx/source/changelog.rst | 1 + docs/sphinx/source/changelog/pending.rst | 54 ------------------------ docs/sphinx/source/changelog/v3.2.1.rst | 54 ++++++++++++++++++++++++ 3 files changed, 55 insertions(+), 54 deletions(-) create mode 100644 docs/sphinx/source/changelog/v3.2.1.rst diff --git a/docs/sphinx/source/changelog.rst b/docs/sphinx/source/changelog.rst index 273b0124b..3a2174c86 100644 --- a/docs/sphinx/source/changelog.rst +++ b/docs/sphinx/source/changelog.rst @@ -1,6 +1,7 @@ RdTools Change Log ================== .. include:: changelog/pending.rst +.. include:: changelog/v3.2.1.rst .. include:: changelog/v3.2.0.rst .. include:: changelog/v3.1.1.rst .. include:: changelog/v3.1.0.rst diff --git a/docs/sphinx/source/changelog/pending.rst b/docs/sphinx/source/changelog/pending.rst index 1ea5559a9..e69de29bb 100644 --- a/docs/sphinx/source/changelog/pending.rst +++ b/docs/sphinx/source/changelog/pending.rst @@ -1,54 +0,0 @@ -******* -Pending -******* - -Maintenance ------------ -* Migrated project configuration from ``setup.py``/``setup.cfg`` to - ``pyproject.toml`` using ``setuptools`` as the build backend. - (:pull:`488`) -* Replaced ``versioneer`` with ``setuptools-scm`` for automatic version - management from git tags. (:pull:`488`) -* Removed legacy build files: ``setup.py``, ``setup.cfg``, ``versioneer.py``, - ``MANIFEST.in``, and ``rdtools/_version.py``. (:pull:`488`) -* Updated ``rdtools/__init__.py`` to use ``importlib.metadata`` for version - retrieval instead of versioneer. (:pull:`488`) -* Updated GitHub URLs and references from ``NREL/rdtools`` to - ``NatLabRockies/rdtools`` and email addresses from ``@nrel.gov`` to - ``@nlr.gov``. (:pull:`492`) -* Adopted `pixi `_ for reproducible environment management. - Replaced ``requirements.txt``, ``requirements-min.txt``, and - ``docs/notebook_requirements.txt`` with pixi environments and a lockfile. - (:pull:`492`) -* Rewrote CI workflows (``pytest.yaml``, ``nbval.yaml``) to use pixi via - ``prefix-dev/setup-pixi`` and removed the ``requirements.yaml`` workflow. - (:pull:`492`) -* Bumped minimum ``arch`` version from 5.0 to 5.6. (:pull:`492`) -* Added Python 3.14 to the test matrix and package classifiers. - (:pull:`492`) -* Simplified pixi environments: ``core`` (bare), ``default`` (notebooks), - ``dev`` (notebooks + test, alias for ``dev-py313``), ``dev-py310`` through - ``dev-py314`` (full dev per Python version), and ``dev-min`` (minimum - dependency versions). All shared environments pin Python 3.13. - (:pull:`492`) -* Added composable pip extras: ``[notebooks]``, ``[test]``, ``[dev]``, - ``[doc]``, and ``[all]``. (:pull:`492`) -* Updated documentation (README, Sphinx index, developer notes, and example - notebook setup cells) for pixi and pip extras. (:pull:`492`) - -Bug Fixes ---------- -* Fixed broken link to TrendAnalysis example in Sphinx index page. - (:pull:`492`) - -Requirements ------------- -* Added ``llvm-openmp`` (the conda-forge name for libomp) as a platform-specific - conda dependency for macOS (osx-64 and osx-arm64) to fix XGBoost installation - issues. Users no longer need to install libomp via Homebrew. (:pull:`493`) -* Bumped minimum ``xgboost`` version from 1.6.0 to 1.7.0 to fix - ``pkg_resources`` import error in environments without ``setuptools``. - (:pull:`493`) -* Bumped minimum ``pvlib`` version from 0.12.0 to 0.13.1 to include the - ``detect_clearsky()`` bug fix (pvlib GH2550). (:pull:`493`) - diff --git a/docs/sphinx/source/changelog/v3.2.1.rst b/docs/sphinx/source/changelog/v3.2.1.rst new file mode 100644 index 000000000..816b33b07 --- /dev/null +++ b/docs/sphinx/source/changelog/v3.2.1.rst @@ -0,0 +1,54 @@ +******************** +v 3.2.1 (2026-04-XX) +******************** + +Maintenance +----------- +* Migrated project configuration from ``setup.py``/``setup.cfg`` to + ``pyproject.toml`` using ``setuptools`` as the build backend. + (:pull:`488`) +* Replaced ``versioneer`` with ``setuptools-scm`` for automatic version + management from git tags. (:pull:`488`) +* Removed legacy build files: ``setup.py``, ``setup.cfg``, ``versioneer.py``, + ``MANIFEST.in``, and ``rdtools/_version.py``. (:pull:`488`) +* Updated ``rdtools/__init__.py`` to use ``importlib.metadata`` for version + retrieval instead of versioneer. (:pull:`488`) +* Updated GitHub URLs and references from ``NREL/rdtools`` to + ``NatLabRockies/rdtools`` and email addresses from ``@nrel.gov`` to + ``@nlr.gov``. (:pull:`492`) +* Adopted `pixi `_ for reproducible environment management. + Replaced ``requirements.txt``, ``requirements-min.txt``, and + ``docs/notebook_requirements.txt`` with pixi environments and a lockfile. + (:pull:`492`) +* Rewrote CI workflows (``pytest.yaml``, ``nbval.yaml``) to use pixi via + ``prefix-dev/setup-pixi`` and removed the ``requirements.yaml`` workflow. + (:pull:`492`) +* Bumped minimum ``arch`` version from 5.0 to 5.6. (:pull:`492`) +* Added Python 3.14 to the test matrix and package classifiers. + (:pull:`492`) +* Simplified pixi environments: ``core`` (bare), ``default`` (notebooks), + ``dev`` (notebooks + test, alias for ``dev-py313``), ``dev-py310`` through + ``dev-py314`` (full dev per Python version), and ``dev-min`` (minimum + dependency versions). All shared environments pin Python 3.13. + (:pull:`492`) +* Added composable pip extras: ``[notebooks]``, ``[test]``, ``[dev]``, + ``[doc]``, and ``[all]``. (:pull:`492`) +* Updated documentation (README, Sphinx index, developer notes, and example + notebook setup cells) for pixi and pip extras. (:pull:`492`) + +Bug Fixes +--------- +* Fixed broken link to TrendAnalysis example in Sphinx index page. + (:pull:`492`) + +Requirements +------------ +* Added ``llvm-openmp`` (the conda-forge name for libomp) as a platform-specific + conda dependency for macOS (osx-64 and osx-arm64) to fix XGBoost installation + issues. Users no longer need to install libomp via Homebrew. (:pull:`493`) +* Bumped minimum ``xgboost`` version from 1.6.0 to 1.7.0 to fix + ``pkg_resources`` import error in environments without ``setuptools``. + (:pull:`493`) +* Bumped minimum ``pvlib`` version from 0.12.0 to 0.13.1 to include the + ``detect_clearsky()`` bug fix (pvlib GH2550). (:pull:`493`) + From 02eb66dd44d9586559724170947779e04ec2c3ac Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 11:48:13 -0400 Subject: [PATCH 12/18] re-run notebooks to account for formatting changes in warning messages --- docs/TrendAnalysis_example.ipynb | 30722 +------------ docs/degradation_and_soiling_example.ipynb | 45732 +------------------ 2 files changed, 448 insertions(+), 76006 deletions(-) diff --git a/docs/TrendAnalysis_example.ipynb b/docs/TrendAnalysis_example.ipynb index a7c2146c8..af0da9abc 100644 --- a/docs/TrendAnalysis_example.ipynb +++ b/docs/TrendAnalysis_example.ipynb @@ -26,10 +26,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:04:22.284754Z", - "iopub.status.busy": "2026-02-11T21:04:22.283768Z", - "iopub.status.idle": "2026-02-11T21:04:25.589287Z", - "shell.execute_reply": "2026-02-11T21:04:25.589287Z" + "iopub.execute_input": "2026-03-20T15:29:44.743776Z", + "iopub.status.busy": "2026-03-20T15:29:44.743475Z", + "iopub.status.idle": "2026-03-20T15:29:47.975720Z", + "shell.execute_reply": "2026-03-20T15:29:47.974031Z" } }, "outputs": [], @@ -47,10 +47,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:04:25.592292Z", - "iopub.status.busy": "2026-02-11T21:04:25.592292Z", - "iopub.status.idle": "2026-02-11T21:04:25.603222Z", - "shell.execute_reply": "2026-02-11T21:04:25.603222Z" + "iopub.execute_input": "2026-03-20T15:29:47.978760Z", + "iopub.status.busy": "2026-03-20T15:29:47.978253Z", + "iopub.status.idle": "2026-03-20T15:29:47.993628Z", + "shell.execute_reply": "2026-03-20T15:29:47.992308Z" } }, "outputs": [], @@ -72,10 +72,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:04:25.606226Z", - "iopub.status.busy": "2026-02-11T21:04:25.605234Z", - "iopub.status.idle": "2026-02-11T21:04:25.608284Z", - "shell.execute_reply": "2026-02-11T21:04:25.608284Z" + "iopub.execute_input": "2026-03-20T15:29:47.996947Z", + "iopub.status.busy": "2026-03-20T15:29:47.996591Z", + "iopub.status.idle": "2026-03-20T15:29:48.002335Z", + "shell.execute_reply": "2026-03-20T15:29:48.000959Z" } }, "outputs": [], @@ -103,10 +103,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:04:25.610288Z", - "iopub.status.busy": "2026-02-11T21:04:25.610288Z", - "iopub.status.idle": "2026-02-11T21:04:25.664306Z", - "shell.execute_reply": "2026-02-11T21:04:25.663802Z" + "iopub.execute_input": "2026-03-20T15:29:48.005036Z", + "iopub.status.busy": "2026-03-20T15:29:48.004684Z", + "iopub.status.idle": "2026-03-20T15:29:48.072552Z", + "shell.execute_reply": "2026-03-20T15:29:48.071267Z" } }, "outputs": [], @@ -131,10 +131,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:04:25.667312Z", - "iopub.status.busy": "2026-02-11T21:04:25.667312Z", - "iopub.status.idle": "2026-02-11T21:04:25.839426Z", - "shell.execute_reply": "2026-02-11T21:04:25.839426Z" + "iopub.execute_input": "2026-03-20T15:29:48.075944Z", + "iopub.status.busy": "2026-03-20T15:29:48.075485Z", + "iopub.status.idle": "2026-03-20T15:29:54.946024Z", + "shell.execute_reply": "2026-03-20T15:29:54.944160Z" } }, "outputs": [], @@ -178,16 +178,16 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:04:25.842760Z", - "iopub.status.busy": "2026-02-11T21:04:25.841760Z", - "iopub.status.idle": "2026-02-11T21:04:47.653193Z", - "shell.execute_reply": "2026-02-11T21:04:47.653193Z" + "iopub.execute_input": "2026-03-20T15:29:54.949501Z", + "iopub.status.busy": "2026-03-20T15:29:54.949027Z", + "iopub.status.idle": "2026-03-20T15:30:22.572026Z", + "shell.execute_reply": "2026-03-20T15:30:22.570726Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -227,10 +227,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:04:47.683740Z", - "iopub.status.busy": "2026-02-11T21:04:47.683740Z", - "iopub.status.idle": "2026-02-11T21:05:04.841064Z", - "shell.execute_reply": "2026-02-11T21:05:04.840432Z" + "iopub.execute_input": "2026-03-20T15:30:22.610500Z", + "iopub.status.busy": "2026-03-20T15:30:22.609688Z", + "iopub.status.idle": "2026-03-20T15:30:44.433665Z", + "shell.execute_reply": "2026-03-20T15:30:44.432244Z" } }, "outputs": [], @@ -262,10 +262,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:05:04.844914Z", - "iopub.status.busy": "2026-02-11T21:05:04.844351Z", - "iopub.status.idle": "2026-02-11T21:05:59.907315Z", - "shell.execute_reply": "2026-02-11T21:05:59.907315Z" + "iopub.execute_input": "2026-03-20T15:30:44.436737Z", + "iopub.status.busy": "2026-03-20T15:30:44.436360Z", + "iopub.status.idle": "2026-03-20T15:32:01.618020Z", + "shell.execute_reply": "2026-03-20T15:32:01.616062Z" } }, "outputs": [ @@ -273,7 +273,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:851: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + "D:\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:851: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", " from rdtools import soiling\n" ] } @@ -294,10 +294,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:05:59.912324Z", - "iopub.status.busy": "2026-02-11T21:05:59.911334Z", - "iopub.status.idle": "2026-02-11T21:05:59.915394Z", - "shell.execute_reply": "2026-02-11T21:05:59.915394Z" + "iopub.execute_input": "2026-03-20T15:32:01.622527Z", + "iopub.status.busy": "2026-03-20T15:32:01.621892Z", + "iopub.status.idle": "2026-03-20T15:32:01.627994Z", + "shell.execute_reply": "2026-03-20T15:32:01.626154Z" } }, "outputs": [], @@ -311,10 +311,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:05:59.919401Z", - "iopub.status.busy": "2026-02-11T21:05:59.919401Z", - "iopub.status.idle": "2026-02-11T21:05:59.923591Z", - "shell.execute_reply": "2026-02-11T21:05:59.923591Z" + "iopub.execute_input": "2026-03-20T15:32:01.632409Z", + "iopub.status.busy": "2026-03-20T15:32:01.631938Z", + "iopub.status.idle": "2026-03-20T15:32:01.638599Z", + "shell.execute_reply": "2026-03-20T15:32:01.636932Z" } }, "outputs": [ @@ -338,10 +338,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:05:59.925622Z", - "iopub.status.busy": "2026-02-11T21:05:59.925622Z", - "iopub.status.idle": "2026-02-11T21:05:59.929012Z", - "shell.execute_reply": "2026-02-11T21:05:59.929012Z" + "iopub.execute_input": "2026-03-20T15:32:01.642162Z", + "iopub.status.busy": "2026-03-20T15:32:01.641535Z", + "iopub.status.idle": "2026-03-20T15:32:01.648753Z", + "shell.execute_reply": "2026-03-20T15:32:01.647121Z" } }, "outputs": [ @@ -373,16 +373,16 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:05:59.932029Z", - "iopub.status.busy": "2026-02-11T21:05:59.932029Z", - "iopub.status.idle": "2026-02-11T21:06:00.891966Z", - "shell.execute_reply": "2026-02-11T21:06:00.890963Z" + "iopub.execute_input": "2026-03-20T15:32:01.651886Z", + "iopub.status.busy": "2026-03-20T15:32:01.651524Z", + "iopub.status.idle": "2026-03-20T15:32:02.642287Z", + "shell.execute_reply": "2026-03-20T15:32:02.640871Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -404,16 +404,16 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:06:00.894966Z", - "iopub.status.busy": "2026-02-11T21:06:00.893965Z", - "iopub.status.idle": "2026-02-11T21:06:01.203313Z", - "shell.execute_reply": "2026-02-11T21:06:01.203313Z" + "iopub.execute_input": "2026-03-20T15:32:02.645249Z", + "iopub.status.busy": "2026-03-20T15:32:02.644738Z", + "iopub.status.idle": "2026-03-20T15:32:02.910699Z", + "shell.execute_reply": "2026-03-20T15:32:02.909080Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -435,16 +435,16 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:06:01.207624Z", - "iopub.status.busy": "2026-02-11T21:06:01.207624Z", - "iopub.status.idle": "2026-02-11T21:06:05.690507Z", - "shell.execute_reply": "2026-02-11T21:06:05.690507Z" + "iopub.execute_input": "2026-03-20T15:32:02.913785Z", + "iopub.status.busy": "2026-03-20T15:32:02.913166Z", + "iopub.status.idle": "2026-03-20T15:32:08.379865Z", + "shell.execute_reply": "2026-03-20T15:32:08.377456Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -471,10 +471,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:06:05.693511Z", - "iopub.status.busy": "2026-02-11T21:06:05.693511Z", - "iopub.status.idle": "2026-02-11T21:06:27.538984Z", - "shell.execute_reply": "2026-02-11T21:06:27.538984Z" + "iopub.execute_input": "2026-03-20T15:32:08.383437Z", + "iopub.status.busy": "2026-03-20T15:32:08.382945Z", + "iopub.status.idle": "2026-03-20T15:32:36.477182Z", + "shell.execute_reply": "2026-03-20T15:32:36.475574Z" } }, "outputs": [ @@ -482,13 +482,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:1144: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + "D:\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:1146: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", " fig = plotting.soiling_monte_carlo_plot(\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -507,10 +507,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:06:27.542988Z", - "iopub.status.busy": "2026-02-11T21:06:27.541998Z", - "iopub.status.idle": "2026-02-11T21:06:27.743424Z", - "shell.execute_reply": "2026-02-11T21:06:27.742907Z" + "iopub.execute_input": "2026-03-20T15:32:36.480352Z", + "iopub.status.busy": "2026-03-20T15:32:36.479974Z", + "iopub.status.idle": "2026-03-20T15:32:36.728061Z", + "shell.execute_reply": "2026-03-20T15:32:36.726634Z" } }, "outputs": [ @@ -518,13 +518,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:1176: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + "D:\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:1178: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", " fig = plotting.soiling_interval_plot(\n" ] }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAawAAAEOCAYAAADVHCNJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABo8UlEQVR4nO2dd3hU1fb3v2d6eiMkhMQQeg0JEQICUpQiiCCG3kXhvl5EEIQfIFIuiIpSlItXpCOKGkBEEOlIkxIgoYUSQnoCIb1M3+8fw5zMZCZlJpMysD7PM5A59XvOnLPX3muvvTbHGGMgCIIgiDqOoLYFEARBEERlIINFEARB2AVksAiCIAi7gAwWQRAEYReQwSIIgiDsAjJYBEEQhF1ABosgCIKwC8hgEQRBEHaBqLYF1EW0Wi1SU1Ph4uICjuNqWw5BEMQzC2MM+fn58PPzg0BQfhuKDJYZUlNTERAQUNsyCIIgnhuSkpLg7+9f7jZksMzg4uICQHcDXV1da1kNQRDEs0teXh4CAgL4crc8yGCZQe8GdHV1JYNFEARRA1Sm+4WCLgiCIAi7gAwWQRAEYReQwSIIgiDsAjJYBEEQhF1ABosgCIKwC8hgPcPEJOdgy9l4xCTn1LYUgiCIKkMG6xkmKiEbOUUqRCVk17YUgiCIKkMG6xkmLNAD7o5ihAV61LYUgiCIKkMDh6uRmOQcRCVkIyzQA8H+7jV+/mB/91o5L0EQRHVABqsa2R+dirsZBUjNKa4Rw1HbBrIy2INGgiDqJuQSrEYe5ytw/1E+/nnwpEYCHzaficcP/yRg85n4aj+XtZTVr2bvASL2rt+eiEnOwfIDt7D8wC26388ZVhmstLQ0W+t45ohJzkFGnhwcx0EsFFgc+GBNAZiRJ0ehQo1rSTl19kU2168Wk5yDBXuvY9OZ+DptbMtjf3QqTt55jP3RqWbX25tBq8t690en4njsI0QlZFNA0XOGVS7BgIAA9O7dG+PGjcPQoUPh5ORka112z+Yz8UjMKoJMLERYoEelAx/0LrPopBxkF6kscidGhPnj+9PxeMHTAVEJ2XXS5WauX23zmXjcyyiAQKAzuvbI43wFkrOL4OEoNrt+85l4XE/JRXRSDtaMDK1hdZZj2BKubXd2THIOXxEY1N4PACASAFmFSrjKSoqw3VFJOHIrA31a++CtsIAKj0vYH1a1sJYuXYrU1FRMmDABPj4+GDt2LA4dOgStVmtrfXZL3OMCFCk1/Pf90akV1lZjknOw/sR9nI97gmtJOciXqyw6ZzMfFxQrVTgR+xiHbthPKzgjTw4nqRAcAwoUauyOSrK6hl/efhUds/R6SzQkZhUiLVeOxKxCs8e9EP8Ej/IViHtcYMHV1B65RUr8di0FJ+88qpFW1v7oVOyPTsWKg7eN7v+MXVcx/Lvz+P50PDadicfi32/gbkY+0nLkYIwhNj2fP0ZkVDKuJeXgm+P3+WPQ0I7qpyZb41a1sObPn4/58+fj6tWr2LlzJ3bt2oUff/wR9evXx6hRozBmzBi8+OKLttZqV3g6SZD4pAjpeXL8cjkZvq5S+Lk7lFvL09fCC+QqSMUiuMi0fI2yMuyPTkVilhwMwIX4bMzbHY0Vb7Wv+sXYkN1RSdh67iGKlBq0a+iGt7sFITzIE9lFKmQVKpCcXYzP/owFx3EIqucIABbVjMsLdCmv1aCvLLg7SvhlC/ZeR0auHD5uMix/s125OrIKVRALOGQVmlYyohKyIREKoVSrUKTUICY5p9LXZNhC0B/LmtbC7qgkREYlw8dVhre7BVW4/7HYR0jPKcaTAgX2R6fWSOskt1gFNwcx//tEJWTjekou5CpdRVjLgOspuZCKhChWaaHMU+BxvgKA7j4VKNQoVmmNjhEW6GF0/0pjrlVW3Txrrb6abI1XKUowNDQUoaGhWLlyJY4fP44ff/wRW7Zswddff40WLVpg7NixGDt2LF544QVb6bUbmvu4IDm7GKk5xZCr1ciTC8p1C8Yk5+DQjXTI1bqXU6rWwkUmsqhgu5GSCwEHaJhu2b5rqRgVHlirL8WU7ZdwLu4JXmrihQ3jO2LruYe4mZIHLYC4x4U4F5eJJt7OeMHTEYlPCiFXaaEF4CgWID6zyKoxZOm5RbiRkoN/HjzBxJca8QWRq0yECw+eoE9rH5N9ohKykV2kwpXEHPi6SrH5TDxupeVBowXyFeoKC+0ujT3xR0wa1FotdkclGRV+YYEe2Hj6AdQaLR5mFmLkd+cxOMQPLzbyrLCw3B+diqiELOy5kgxnqQiBXk5IzSnG5jPxyMiTIyLM3+y++kIxt0iJC/FZuJuRD6VaixspuTgX9wSjOwVgRp8W5d5HtZZBrdTgbkZ+udvZgpa+LriRkgsfVxn/m+cWKVGoVEMs4KDS6h5qATio1FowLYOKMRyPzcCU7ZdwN6MA+XIVmFYLJ6kQqTnFiEnOwb2MfOy5kow9V5KNngU9kVHJSM0pRm6xyiKDVRmjY84Y7o5K4t32gGWVsZpCf22uMhHy5OoKDWt575WtsUmUIMdx6N69OwYMGIDOnTuDMYZ79+5h8eLFaNy4MYYNG1apQI2CggIsWrQI/fv3h6enJziOw9atWyutIycnB1OmTIG3tzecnJzQq1cvXLlypQpXZj0tfV1Q30UKL2cJvF2kaO7jgqiE7DKbzVEJ2VBpSlyqSjVDZoGi0s3srw7fQUxyLmRiIWQiAYQc4Oogxv7o1Eo116urWX8u7gnkKg1O3nnMH9vQcfw4X4m4x4W4npIDoYDj1xWptPBwFGHzmXiLosEGtfdDnlyNJ4UqXE/Jw7w91zFj11XEJOcgT65GC19X5MnVJvu5ykS4l5EPhUqN366l4npKLthTwy8UVDyxXHNfV7g5SpBbpDJySQG6QkksFIDjOGgYIFdp8UdMGr4/HY+k7GIcuZVR5nHvZuQjNr0AydnFyCpU4FpSDh7nK3A9JRfxmYX4+vh9s/cnKiEbh26kY92J+7wxLlRoUKDQILtQgW9PxvH3xRwTX2oENwcx3B3FUKpt7+ov/bzlydVwkYkRm56Pe08N5IX4LIAB9Vwk6NG8HrycxHCUCiGTCOEoEULLgAK5BsdiHyFfrkKeXA2OA26n5ePvu7oAmCO3MvAwsxB30/NNfpfdUUm4m5GP9Fw5bqXmlXs/SlORq3F3VBKWH7iN83GZ+PTgbYzacB5rjtzB96fjkV+swvm4J9hzJRlrjtypc8EtUQnZuJOej+9Px+NOen651/ivHZdx+l5mme+VramywTpx4gTeeecd+Pj4YPjw4UhPT8eXX36J5ORkpKWl4bPPPsOxY8cwbty4Co+VmZmJpUuX4vbt22jf3jJXllarxcCBA/Hjjz9i2rRp+OKLL/Do0SP07NkT9+7ds/byrCZPrkanIC+81rYBXmvXAFmFSuy6mGjkozckLNADTes7QcgBHHSFpFRU+ejCuxn5UKi14Digf1tftPZzhZNUhH8ePCn3odPz1eE7WHf8Pr46fKfCc1li3AK9HKHWAmoNw8yfr+GVlvXhKCl57BiAJ4UK5BarIBJyRg9k3OMiHL6Vjj1XUvDV4TuVDmXOKy55cZQahlN3H2HFwduITsrBtaRs/PBPAl756qRRAZUnV8PbRYoChQZJWUXIKlTAUSIEB11Lo6CC/kRXmQj5xUrkKzRIyCrC4t9vGK0fEuIHF5kIIoHumhl0v/HjfAVa+pY9NbhSrYWDWIBCuQoPnxRBpdbg0sMsJD0pxON8BTLz5Nh3LdXkucotUuLywyyotbp7oGW6igIDoNICCg3DubjMMp+LZj4uaOfvBrVGi7sZBVhzpOLnwhJKF/iuMhEuPczCw8wCLPztBubtjuZdfBKhABl5CoiFAhQoNChSaqBlDAy6a9I/MxIhh3y5BsUqLe49KsDdjHz0ae0DJ5kIAgGHIqXaKIozMioZ+XIVFBqGfLkaJ+48KjPK05CY5BxEJ+XgYvwTo6APQ47cykCBQoVcuQZPClW4EJ+FHf8kIr9YhZRcOYpVWjzOV+Dny0l1aijK7qgk7LmSjFN3H0Gp1uB47CPkFinNbhsZlYzzcZn483oariWV7Xa1JVa5BKOjo7Fz50789NNPSE1Nha+vL9555x2MHz8e7dq1M9p29uzZkMlkmD17doXHbdCgAdLS0uDr64vLly+jY8eOldYUGRmJc+fO4ddff0VERAQAYPjw4WjevDkWLVqEH3/80bKLrCJ63/krreojKiEbecUqJGYVQ8ABM3++htUjQoya2cH+7vhrZk/8a8dl3M0oQHaREi81qVfph6CBmwxZhSq4O4rh7SLF7bR8JGYVQfS0dTA6vGy37O6oJPzz4Ak0WlYp948lPusAD0fcTS+AWsuQkSeHm6MEfVv74tDNdL5vQqMFOHCQioVwkTHkyzXQQu+SYihWKnHmXiZiknPhJBHicb4C7QPczboqzBXAecVqXHqYBa1WV8BxAAQCIDNfgYw8OeYNaIWwQA+k5hTj3qMCXc1doUYTbxfEPy4AGHA1Kbfc68yTq+HiIEGuvBhgwMPMIqP1M/q0QICnI1YevoPsAiU0WoasQgVCAtxxIT4Lyw/cwqD2fibX08jLEVcSsqHSAtAyPMgsAsfp+nMAoFClRbFKAZVGa+S2jE3PB8dBZ6HKIDNfiS//isX+6BQsfqOt0bl195GDQs2gUOtanRW5EM1R2nVm6G4CdO/J7qgkfHn4DvKKVU/d2Qy/RCXjxUAPtG6gM+ZaBsQ/LoBa89RQaRmEAt2zo9YChUoNnCRC3TPFAMZ0UYTNfFzQOcgLp+89BgC+zwsAfFxl0DDdTdLdXmai3ZzrdX90Ki4nZEOp0iAyKhnNfFxMfrc+rX1w7PYj/gfQMuBJoRL6trpay1Cs0qCesxRqDbNZdKy1/WP6SMw9V5KRV6yCgOMgFHDwdZPhQnwWZuy6irjHBWji7cz3gUpEAuQrNOCge17uZeTXzT6s0NBQODg4YMiQIRg/fjz69OkDgaDsxlqbNm3QpUuXCo8rlUrh6+trjSRERkbCx8cHQ4cO5Zd5e3tj+PDh+OGHH6BQKCCVSq06tjWUDt/edu4h8LR/6WFmITafiTcb3qz3A1vaCRwW6AlA1ypr6euCw7cyoGUMxSqG2PQ8fHX4Dmb1bWH2gTpyKwMcOGi0rMwaoyG5RUr8dTMD/dtU7LNu6euCY7EZYAA0WobopBx0b1YPcY8LcDM1jy941VoGb2cplDIJFJpCKFS61iIH3T3TMCC7SIWcIhWyb2cgMavIbGBFWKAHXmzkgevJuShUqqFUM10haFAW6bQARUo14h4XYH90KhYMbI1gf3f8cjkJucVqqDWAm4MIrg5iZBYo8eBxQblBLGGBHohOykGBXIVilQYvNjKtaOTJ1fBzc0BWgRJqrRZKtRZxjwuQWaBEVqGuFlu6sMkuUkEiEkChKYk4LVWuQvt0u58uJsJJIoSbowQejmIIOQ5qgwsXPS3gGXT3VQugSKnFrdR8k8qH3oDfTstFnlwNTyfz4foVUbolteLgbWQVKuHpJMG8Aa0AAF8evoP0XIWRbRVyHNLzFGjk5cjfGw8nCdLzFBBygLNUiHouMiRnF0GrBZQqLdQaLbxdJMiXqyHgdKZBF4hUhMKnEbvZBq2Ft7sFIbtIiTP3M6HV6tyLe66kwEkiRO9WPlh/4j6uJGZDpWGIjErm38fH+QpkFypRrNIgJyEbXx2+g21vhxtdt66F6ooricYVHf01CjigSKFGkkINgVCAFr7O2HI23upADL2hSs0phqNEZFEAhL5fjTGGArlaVzmC7qVLyCqCUqNFbHoeCuQaxD0q4PtAm/vo+h2zClUQCTgcuZVR7YErVrkEN2/ejIyMDOzcuRP9+vUr11gBQK9evXDixAmrBFaWq1evokOHDiZaOnXqhKKiIty9e7fMfRUKBfLy8ow+NuPSJgTv6YVVjaPgKNZp0zLgQrz57BdvhQXgY99/0Ofoa0g+sq7SpxnU3g9vaQ/jm8x30ODeT3gzxA+OYqEuCEOr60sy53aISc5B74I/8JdoBt51OAFPp4qNemx6PtwcdP0NuLQJ+DpU978ZOj3Zh2PiDzFGeBRylRYD7y7EkD9CsN1tA9r4uUIkANaK1+GGaAw+lq+CRMTBy0kCB4kA9V2kcJaKjB5SBqBYoUHc4wKj2jIiJwNLvRD8azdsS+yHKO1wfOf4Lbhyup9UWqBP0UF8cLEXNIs9kLX6JfwlnIExwqMYIzyKL1InYZTgqG5bDcP+mLQy3ZHBabux5tHbWN8iGj2a10diVjF2RyXpVj69R32KDiAs0AMBno6QioQYxg5jS/5UDNUcQnjWbxh76U2oL2w0aiX2ae2DRvWc8LvkY8RLR2Of5GMA5l/cAoUGP19OQk6RCm3T9uC2eBTipaMRLxuNP2QfI9DLCa39XOHrJoWnkxhrxetwVzoOXwq+xsk7j7D8wC2sOXIH/9pxGeoLG7EgbgyW+F1AeJDX0wqR5bRP340xF4egffpuRCVkY3PqYBzKeQObUwdj/Yn72B+dimKlBqOFR3FSMhOTJMcgE3EQCQXwchIjJGMPdj2JwG9P3sBXgm/g6yrFOul/cYUbg2OBO/D/ejSBl4sE48THcFzyId51OIWfpnRB16b10MbPDR0e7cG6zMkYjsMYgcNYnjSBf6+C/5mFbckDsMHxWwC6ZyurUImfLychKiEb3XL340/l2zimnYxuub/zv/3M+Km4wY3AXvHHT13OmZiy/ZLRdTvtn4rIRwMRL9P9ZobdoEKBrsKg0gJKLaBQaXE9JRctz85Em01NdM+yhRSc2YDhJ3phxtXXEP7kN4QFeuDK7i+R9p9W+OXbxSbPbey6YVAt9sT5L4ag3cEh+DN7EL7InoErwgmIl47GTclEALqyIzVbjpwiNVRahiKVFk8KFNh8Jh4N7/+EvZr3McXhBCQiYY0EXXCMla6v1Q30LsEtW7Zg4sSJFW7v7OyMESNGYNMm44Lz4MGDGDhwIA4dOoR+/fqZ3Xfx4sVYsmSJyfLc3Fy4urpapb/k4O7Q12lH+f351L3DEODhgIldgzCpa5DJLsqlDSDRFkEpcITkk8qPp9IudocAOpfJZrf38Qv6oEChRnquHFqmc4N1a1rPqKW1/MAtTIvqDzdtLhiAO/X6ouW0X8s9z5ojd3DoaQtrxu2RQNYD3QqZB/B/D401LfGAgGmh0grQTPkDHkhH8y+vSuKOd3x/wZbEvhA8vUtqiPDOC38iX67Ek0IVwBgKFGrky1XQD2sTcoCDRIhXW/mUtFKXeADMODhA/2DnaJ0Qqvxe547hAI6VBH6ckMxEkCCD354DUAgZ5EwCLy4PDMB+zUuYrpoGLycxhnbwx4KBrU1vylJvQKuECmKEC36Eu6MYzX1c8L9xL+oMusE92t3nNL4+fh/HC9+EEAwacFAxIWScGnImwv+6nTNyv8Uk56DdxkBwKGldfef6bxx2GICribn8dQo5wNdNhnYN3bAiZSI85Ekm96L0DeI43TGVTIgWyh0QcoC7oxjnNaMggRpagRjbXrlU6Yix0qiX1IOIqcAApDq2hF9RrNF16FFABBmnaw/e5ppiDLcC/h4O+D53CnzVqfw1qCGCEBr+OVeIXHF34nU02PYSvFUpYACUTg1xZ9Q57I9Oxeyo3pBqi6EFhyImhTMnRxZccWLQObz1RzDAtGAoeUb0BHo64Cf5e/DTpvHnPhT4EV6b9DHYYjeja4hhjTFYuQwysQBvhvhhxVvtoV3qBYFWbXLvi7QSdBHsAADkyXUPtFCg++1iRSXvBtpGABHmK4HmyP6srdHvjYGroD4wGyJooYIAP/S5YlTWaBe76d65p+L0z0Hpv/XkMOP7wwG4LJkKL0F+pcuNssjLy4Obm1ulylurWljbt28v97Njxw78+uuvOH/+PBQKRcUHtAHFxcVmXX4ymYxfXxbz5s1Dbm4u/0lKSipzW8th/P//LZwFT2cJ3BxEEAkFfOhtacTaIqP/K0NMcg64p+fiAEzMXYf0PAU6NvJEo3pOvBvsWlKOST8PZ/B/88zDFXawFyo18HGV6dwsXaaVrJBnm9QOBU+NiEigxRjhURg2eMTKHHyXGsEr4ACIoMbmxH4IC/REaIA7REIB6jlL4SITQyYWQCrUXaXqqTuNv39iRxOd3NOPu6AQ8bLRiJOOxljhUaMCZKNmYMmL+nSZA+SQiAT8steF5+DhKIJay4xbdYZoda4mEVSQiDikZBfjRmqurpVlcI+YPBuOMdvQwscFAuhDtRmknK5wk0Kti44zwPD34jjdZ2r+f/Fzzhi83LweHMUCODxtvRco1NAyhtuNxvNBFob3wujDlRxTwmkQLx2NPeKPdWPKoNMj0KrQ+txMzN0dg3XH71UqKMEQIVPx5/crijW5Dv1H+vR8HIBW7P7TPt8iHHKJMLoGEdRGz7lUnYegHeFQdHqPr3BIClMAAElZRRBrFfw9duJ0/UTuLB85f3/HPzP6Z+S87ANeX0JWMb5XDzQ6d7+ElUbXptcezD3AHck4yFVa7L6Sgt1RSchtNMDsvXcUKBGNEYjGCMRLR+N7x28R4OEIkVBo9G7gRqRF93mPdIjRc6098CGET6tlImgx+txAY+0G14Ay/jb8uHOFutb6089pyXQwruS9bZ55xCK91mKVwZo4cSImTZqESZMmYeLEiUYf/bIRI0agW7du8PX1xRdffGFr3SY4ODiYNY5yuZxfXxZSqRSurq5Gn+rAM/cmXg/2Q1A9Z+QUqbDvagoW7L1uYrQMDUhZrrbSRCVkQy50LfGRg+EnzIO3ixTtGrpB/LTqJhUZjwcb1N4PN5pPK3m5GLCpUhGAT/foWMp9UcaLxgFYLNyKFFbP6MWSqvPAwPGFKwdACC3mX+qCfsUH0K6hGzydJKjnLIOLVARwgPip0crIU5REx/VZaqKudIEh4IClos14IBuNs7LpcJQI8JP2VRQxCRiDkeEq0IiMvr+uPIQCuRrXU3IrvDfLNGshFHJ4UqBEZFSy0T3SFXxf6sKw4cxfs+EGnz35wOh4YYEeyHRpbXJNYmUOtiX2xQ8hN+EiEwMckFusxok7j3HRazAEi3PByTyM7oe5D2Bc+J6WTIcKJX1WHQtOQK0FnhSqyjbYZVBUL9jo91ZqdeHozOCjP7/hdnvEHyNfrsbq7K6QQ2ryWxrcLjgr0uEfb/zcOe2fCndHCS479TRpXQo4huH5O4yeGQ6ALx7zLlcA2KLsjSJIjM6tWeKFm559jCsDBgb/V+ECzPo1BqG3RiIHTgbVVWP9+grDq9rTOFE4BDcFI3T3w3D7ZQ3M3lNzXG/wFpRaodEzq/999Ubc8LlNdWxp0qJirMRoMZj+PoafhlwmvJBn0BJjNRKeb5XBunbtGoKDg9GrVy/s3r0b0dHRiI6ORmRkJHr27ImQkBCcPXsWu3fvRocOHTBv3jx8++23ttZuhD7CsDT6ZX5+lc8YYVPaRvB/MgAzrg9FfRcplGoNHhcocTst30zfksEreXhhpU4TFuiBXb3/NjpCK3YfLX1dkF2khIADnKRCOEp0QRX60HQAcO42xehYO7Xzyq1JD2rvh+Y+LvxxCg0KJQYAnzUq2djg+kWcFt2VXyNG29joBRZCC4HIERxX8jhyAPonrMRwHMG8Aa3wcvN6aFrfGSEBHvB1c0B9VymKFCVBE+g4GVicC7gFgAHIk/gaFfKlCww/ZOKmYCRuSiehjXIrghQ/4nftS/wL7ssyjbQsEGyHhgGpOcXm743Emd+2t+YM3BzEcJGJ4OOqa+HDL9RAA8NnTz7AANl2o3Poz/2C4o7JOC7vWefBLc6FGiKTArjD9f/gnGoE/12lYdh+PkHXuvu/h8DiXHAGn+vvJGBrn2vYM+gGDgV+ZFL4NhRk4nTjD0u0ccAYoa4v7/S9zJK+uUqwJug75MJJVxgCkAg0OCrsjmD8jCDFj3xlQaehpFUbzD0AxwEqLcOY+nvxacfzAGe+uOIAIPUqOIOWelDGIbTwdYFs1BYjA6e/Tpm2EDEN3gL8Qo2OEyx4YGS02im2QvX0nnMABFo1WmSdwIqO56GWuJs1+HckuiE8ofLvdboX5+J8ywX8fTb3PHLQXR4zCIqBughY3bZS9/ntbkHo6fALlEzI32ujihADnLa+yj9XT0b/hduCJsZGiyvRttntffR334ebXONyKzh8Kx2o1PCZqmKVwVq9ejV8fHxw9OhRvPnmm2jXrh3atWuHoUOH4ujRo/D29samTZswZMgQHDlyBJ07d8b69ettrd2IkJAQXLlyxSSf4YULF+Do6IjmzZtX6/nLJGITIPPgH0JHeRrmF38Fp6fReFrGTPPLtX2r5G9V5dyCwf7umNQ1CJyBgeAADPzzJSRnF0MmFqBYoUFGnhyLf7+BFQdv8/nbohKykeGkK9w5DmjHPcDx2LJzyAX7u8PP3QGOEhH2R6fiHckXfC2YA4xdg4Z+eA44LZmOma6rkOlSqh9IXQQ0aG9UKHEAusQuR/A/s7BgYGvMG9AK/dv6YnrvpmAMKFZpUKzU4HG+oqR2N/MGrr+TgD09DiFtxJ8lBbXAOMpN/0LLoEC8bDTuSMfhn5DPSl5yDjgm6s6/oFKBblCqQqU1f28MausCMHw37kX8v55N8Xa3IN3CKSeNWs4vKO6gaX0XXU3XzD0W7HnH7L2//U4cb4gNEUKN+5KSoIysIhXm7r5u1r2rT1l05FYGTrm+gRUdz6NQ4MIXSEqnhnhl/HwYumrniX7U9e8p1OUOdDZHuGoj/zcHXauibUM3BHo6IkSzDa21uzDY6w+kdv0PDDfcI/oYHg5i1HeR6lKULcoG3Ayi0ASlIxdL7ooAwCTJcV1/m1DKn9vwfkUlZANTTvKVHP02wdwDrBXrAjMYA1rItxsV7CKoMetST9weHw1u4KoyW1tnJNP5MXZpzUbhvSbHsGeQ7vlUC2Qmv6G+1WV0RblJwIae5m+sAcH+7ggP8sJL4p+hZhxvtGCgu7G6xKUb7O+O26/vw1+Crk/H6HE4IeqOTqJIvCTdjfy24zCyUyDuDPodW/tcw6cdz2NN10vIEfuYNWBqiJFTpKz2sVhWGazffvsNgwcPNruO4zi88cYb2LNnj+4EAgHeeust3L9/33qVpUhLS0NsbCxUqpLBnBEREcjIyODPC+gGIv/6668YNGhQjYa0m2AQiMAB8E89iM5BXnCUCiEScFCqNcaDYiM28TV2SCzMhP/UQOqRqvPwBdbCw0kKsZCDXKXFlURd1nB9pJ2rTITFvt8YHaZH3v5yp8pIzSlGkVLX75CaU4wQ9TbjjQxdg09rsRx0tfdxXRohbcSfRq0v3YGu6golg4KI0x/L4KWNTc9HbrFKFyzwNDuIYei03ngbBQd8ksm3wAzRGy4Jp0FzX1ejQiQs0MOokNsn/phPKfXezihjo2Xg9mMAVD9Pwg//JGDB3uslLZJS17suYxyejP7L2AX89P/WWUfMtmQMW1sQlfTb6a8jWFBSw1drGX67Zv43jErIhrujBDlFSrT0dcGvr5zGnkE3sLXPNdwZde6p3rf4++HIySESACqttsyM9OYY1N4PUrEAMayxkbtq3oBW6NvGBwPbNcDYzoFY/mY7+PeZxv8++mvJlavRp7VPyW8584bud1ycq/tN3coOo9YenI0tZ+OR3PkTE+OghrBkCMfMGyiQ+hoZnUGCc5CKOAifDvReqH7bSL8UCt3z1nEybryTgKKnBl+/v76l2v+AbjiPYZaVYH93iD/J0P2Gi3OBthG80cuBE05JXjYyoCz1aqUihrs3q4fmPs7oLvvVSAvvtmNA75vz+e3fCgtA/0UHcePdBGzrcxU5r32LsEAP9GheH26OEkzqGoS3wgJ4I1SkVCNpwkWj1jo3cBUUro1wqeUcvNerabWPw7LKYGm1Wty5U3bHfGxsrFFLRyqV8sEPFbFu3TosW7YMmzdvBgDs378fy5Ytw7Jly5CbmwtAFyTRqlUrpKSk8PtFRESgc+fOmDRpEpYuXYr169ejZ8+e0Gg0ZiMAaxrOyCUEfPjwX2BPR+snZcsRlZCNuxkGTeo+SwHPxiZ9M5WilIEMyz+Or0eFwt/TkddQpNJCwHHwdpHyLxO/DwfMYVsRlWDc+a8nKiEbjhIR/NwdMKi9H5Qa3RgYQ1cfgBJ3xpSTRnom3Zyke7AjNhkX4nr3zCeZprXn1KsI2hGOnCJdJcXHVQaJWABnqQgnYjPw3an7+PrYXQz65nT5Lit9gVfKeGg5EXKKVFAJSzriPR7sNypA2wkelMjJkZsadIOafGj+caTmFONhZiG+Px1fUhERiPhtXBTpCE7brdPCCaCC2OgZiYxKLvs6AODjNGDgKgDGLiaJoKSGH+hlGowC6IxxC18XvNerKfLkauQUqRAZlWw8p1fEJiMjOll2EoGejsguqvwsAsH+7ni7axCmu6zS9ekwIJ9zRrC/OxYMbI01I0P5MXAAdL+PAb+JPy4/5c/MG0YVNEM4pkVOkQpHHAearBNBgwb3fuK/x4+7AIXI1aigvyEah7BAT0iFHH7SvIqPDYwWAL4gD/Z3h9MnyTjeeK5JoIujNp/ftvQ8cHpiOn+FSS8cRpjgV7wu2453C/6le5cMDKTf2QUVZ3h5ml3H3VGKzwTvokArhYYJjK4pvOiE0XEMBxq/FRaA93o1RQtfFyOdhu+7iUHqOBnSD6Px0sg5NZIX0SqD9cYbb2D9+vVYt24dH9QA6AIcvvnmG/zvf//DoEGD+OXnz59H06ZNK3XsL7/8EgsXLuT7vPbs2YOFCxdi4cKFyM4u2z8qFApx8OBBjBgxAl9//TU++ugj1KtXD8ePH0eLFpaP0Lc5U07yfTQcgAB5LKQiITRahmKlBtHJuhYPX+vrOBmYftU0qKGyGPjmASD41254r2cTo7RISrWGb2G5O4qR5FcS2STl1IhNyzdb+Bu+fMH+7nCViaBhwGDlMmiZQZskN6kkaERo0MJNvVryd8SmkhqzgWHDJ5kmBZGzIh3vXB6EQe39sHpECMKDPJFXrEt/I1czZBepcSstD1vPPaz4/hied3Eubk6Og7ujGI86LzDYiJkUoGOf9uWYzS/Yf4XRVwEHFKk0yC1SlhiB10oFIB2YhZjOX2HLq1fwUUuDSCsGLH30fsXX8bTvjjO4V3rXUkNBJtYXmc8wY9gK1f+eEpEAydlFpQIrStyCs9gWaJ66Yi3pXJ/RpwW+GRWKCNcfESL4Be8H7Cl/BwOj3kR9r2I30/89LHneSz33Y2MmICzQA0wgMbgandu248OSfvVgf3fIPk4CJyqpsIigxg8ZQ/BauwYIecEdu7m++F37ElRMiNPSHiYFdGKTUVjb9RLfWmMAlCJX/vgmrf6nRCVkIyTAA2+F+UP1NHPHYOUy5DAnI6PVZHP5/VlhgR4oUqrhKBHgB80raK/agnbsR3wmeLfkOMzY3Vx6YLc5neUZ25rGKoO1du1avPjii5g+fTrc3d0RFBSEoKAguLu744MPPkCHDh2wdu1aADoj5uDggA8//LCCo+p4+PChruVh5tOoUSMAwNatW42+6/Hw8MDGjRuRmZmJwsJCnDx5sm5NczLgS6Ovp/E2H46s1eqmqDCc36dKTDlp1B/EcpPQ4uxMBHg4wFEigLNUCIlIgOspuYhNz8ekrkE41uZTo0NEij42219R+qFWqBlfEHyinmQ8huPALN3/pQrzSvF/D42MFt8q+UGX1spBLIRYJDTaRavV5VW0NPed/pr8+0wzXhE5GYaF9iLxVrhIhajnLDHNAVgqGvBLwTcQCzjkytUlRqDj5FKFKuMLDW8XKWK5pny0VlO1BTkw/+8h39oy1OCUGVPhrvprb+7jAn8PB3i7GFQuDPpTRUyFRl46F7WlnetRCdmQqzQQcFzFyXQNjDoHIPjgkIpPMOVkSaXHwAXtnX8Lwf7uELz2Gb+p/vEUKs3MTfZxSeAWB0CslWO211nUd5HCx1WGj7TvI1i7EyudPzIx2vqCPX7cBWztcw1rul7Cj73+RkXo92vp64JWDVwgFurGZXVQfm/aWiunP0vftwxwfAYZgEN+23G8peY4nbu59LnLM0blGduaxiqD5enpibNnzyIyMhITJkxAixYt0KJFC0yYMIHP6efpqRsZL5PJ8P3332PUqFE2FW6XdJzMF8AcAGdtPra7bYBMrGu2642XzRjwpdED3zrrCHzdHNG3tS/CAj2g0TIUKtS48TRU2zB8muOAVtr7JvnVzDEkxA/OUp3h2Kl5tVToOtO5BjtOLmllCS3oT/y/h6b9FPJs4LNG6NPaB028ndDQXQaZSFAy+FjD8PPlKoyl0/cfAsCt34wLbWjhJBNBrtLiy8N3TFugBm7BfjgLiVCAgNJGwLAliZJCY1B7P9x6/beSFQw4tt24ElEu+khJQ4NYqsVRHoPa+6Fni/rGc7CVGrz6UcEXaO7jYnFtOyzQAx0beaKlrwsiwvzL37jjZL6VBcC4RV4ZSt1fbOhppqIAQFuGa7OU4fe/vQnv9WqKvm180MLXBV7OUoiFpompzbVaK3Of9PvlydUICfBAWKBu7KRIwJn0nVXUnxUW6AGpSACRQJctxNNRjOa+rjrviUEr68ruL0002wMWZ7ooLi7GggUL0KtXLyO337OEJSOvrWKxG/+nFsAA9/1IzylGkUqDtzo0tOmki4XrusMxM4YPm9ZnBlh/4j6uJ+ficYECzXycEeDhyHeaGo7kX8omQxT+jtnErIYsP3ALkVFJyCnSZSuIk42B0LBHa3Guzj14fp1uIK2lrs7VbXUuRkNEjoiZeBvrT9zHmfuZKFZqoGG6zAGNvJxwbFZPy86h59Im3XACdTHQZuhT96HuN2MA7gmbYmDxUmgZ0NrPFfvf726874EP+W3Xdr2IC/FZphMnRk7WGcPWQ0yMgv7+A7oMENLFT6y7Dlvxn/qAxsBNuDi3+s9pcB8hlAILH1m2/+q2YLlJJcMFDDRrl3hCwDTQQICb78Sbf64jJwM39+gGF/dZyj+v+iSxACp8JyzFMDFwbHo+jsc+QmaBEjvZXLTBA/6Z0AIQlPMb6JP2GiarjUrIxsQjIfwxVBDgdlnXXsNUa6YLBwcHfPfdd8jIsCy09XnGZDoOg5qeAMCP7P+g0GghFHA4/8B8oIO1OE07bdR3JlPnIfifWejT2gfFKg3EQg7xjwuhZcw0AwYHzOW2GQeDlMGg9n6ICAuAq0zX0vpENck0XNvCfjmj+zbzhmkNWV2EVhub4FG+HA5iXcSlm0yoM749m1TqHGbpOBlYkKqLWNQbEwM3UzPNfQgEumzWJnOWlbo28bWtiEnJxbm4TOMgjYhNwCdPzKbf4dqWZHeQQF37cyUZuHMZdJWTGbuuWjRPmcV0nKxr6Xg2ts6dXKrv0RB99hUOps88T8Qm3e8/P8XkN9UHG9m6sNe3dt4KC8CCga2xekQIQgLc8K50JT+WTacbxmMdzRxnzchQ7H+/O9aMDOVbfOdkPfljiJgWBWc22FR/TWCVDyosLAw3bpT9QBDGmEz2Vspl4Zl7E52CPOEoEZUZ1VUlSvWd4UYk3goLQDt/NzBwcHUQQ8BxvPsip/EbRsEXydnFFWZx10d9vfC0j2On5lWkaJ+6BssJPS4Ps/etlNESQY1fHg2Ck1SEHi3qo0uTevh6VKjts0aX+s0OyD4BB91kjCYDvw3cgu8UbkCxUoOcIguyRJQyYmWNyaoxShXYvW/Ox+WELByPrdz8UVU6bxUCjzQQGv0P6CpBSqEu6w0HoE/RAYuOWdHEjbbAcFC/g1iIFzyd0Euw1TjUXZ4NxUozOS3LINjfHS5jtxn1ZXW8U/0ZiGyNVQZrzZo12LVrFzZu3Ai1uvpnmbR3zPqzS4VVb0wfjmm9m2JW32qIaDTnv1/dFh5Pp6HwdpEajaHwGL+jZPwRA2bmfl7pYJCJLzWCTKTbu5vyazRX/YQ1bXdbJdvsfZty0qiPgYMuU8axwqEQcKjesSAGIe5NngZE6NM1GWHQIpBADQeJkJ+nrLIYRrUZdpLXGgYtzPCiE9BoGT/XWl0lpt18PBI3REy7krFHUQnZOB04HVpw4MDgf9GCPkLUTMScoVHs09oHHo5idGzkgU9K9WdJClMsyuwe7O+OJFlLg1aWqtKp3+oKVucSFAgEmDp1KlxdXdGsWTMEBwcbfSydMfhZxmzHZqkBvmJlDialLau+wrZU1CByk9Cv+ACa1ndB58ZepufVtxI4YAB3rtKtg7fCAtC/bQMIn5ZlqioEQJTZIax3Fz2FAyCAFt/GvaIb11RdlHIzDcMRgGN4nC83Dr4o1SJY5PsPmng7lzuzcGkEr31mVKOudUqNpXvB0wnZRSo4SYRl7lLbdHhrNuovuIUOb5WE9ocFeiCxyciSe1rJTDJ6qjtIwXBQvn5s1P/GvQiFWotdrI8ufZiha9CCJLkxyTn4tOF/S1pZAFSHPi53n7qG1VGCLVq0wMsvv4zw8HD4+/vDy8vL6KOPEiTKodRUHJZmaLaYUq7BfglfomcLb+OoMD39VxgVmEaZ0Svg7W5BqO9a0poQlM43Ywv0EXEG/XMcABz8yPbnMsI4xB2MAwfOdJCvgVvwzUfrIBEJLRuyUNoNZsUcSdXJx2nvIbdYN3dUrfexWQCfwkyoa8FC/38doaxBuglPiiAVCTBDNU0XhWvYQVzJZ0Of3eSOoCm/v0Bjm5mOawqrDNbJkydx4sSJCj9EJSidnqiSyS6touNko/4kAVhJ1glz2xrwedaMSvdXBPu7Y3bfFmjgJkV9Fwk6NqrGysuibOOWI9OUva0tKBXi7igRIF+hRlZhqRaogVtQxFQoY0aqcnkoaVGSn/HWb9aotS0GbsG2eACVhkGu0lZ7wtNqQepi/H8doSyX45AQP9RzkcLbRYLXuP/qkgbrV1by2dBnN/lf8404KuwOFYS4V+9Vm+qvbmw88IewmIhNJq66aqV09FTq1TL92PqpIThOl/n9bkZ+pacQeCssACNeDICnkxSNqiOQxBDDpKhWBnhUmlIBETu08yDgYJo+qJTB/0SxynxLthyu9NuNS069oeVEuvD3CjCJRrU1pQJP1sv+C08nSZnzutVpes3XRSD2ml/xtjVIWS7HGX1aYOJLjdC7pQ+cZSKEarbhD+1LUEGI7EYDLDq2t4sUnznNxoj6+3E+1L4CL6w2WHl5efjss8/Qr18/hIaG4uLFiwCArKwsrFq1yqbJbp95DF11gvKj8WxC6VadPhtFKZymnS75woBmib/wGd4rQ2x6PtwcxLbL3lEe+hyB5YQz2wyDlkY7wQNIREJ+upWytmuSccjifo+3wgLQ6aO9ECwyH/5empqIYDN0dfZlZ5FdqOTHD9kVVU19VgvoW0j1nKUQcMB05TR0EuzCeq95Fh1nUHs/9G5ZH2GBHnUi3ZIlWGWwkpOTERoaik8++QTJycmIiYlBQYEuzYmnpye+++47fPPNNxUcheAxHHNSOtdcdRCxqVRLhFXoB+c4YLZ2K+IzCyt9Gn2EU5/WPlYKraOUamnscPvOfHRn6YwL1UyN5HwzcHVy0M1wfD05t8JhD3WRam+R2hh9C2niS43gJBXpclUq1Dge+8iiMXH6IShGSYftBKsM1kcffYT8/Hxcu3YNp06dQulkGUOGDMHRo0dtIvC5oaZrfKVbImX4wUuPydJotZV2bekjnGw+JqouYJCgNTT/OKISsisuMKo5cKJG0uyUej5XCr6Bg0SII7cy7Kbg11MjLdJqoNnT1ryGAUoNw6M8efWPiasjWGWwDh8+jOnTp6N169bgzESANW7cGElJ1dwXQ1SdthHg4+vK6CPxGL/D6PsK9jXuZdSAi6+u89oXRlGU7jd3mC/4DPMSVncUaE3xdKocDsAg4Tm4yMRwd5TYXcFfl7KQW0JUQjaEAoFuOIcA0DCGrAIF/ohJtWg2aHvEKoNVXFwMb2/vMtfn51OBZhdEbAIW5+g+5fSR8INYOeA1nMU3x+/bXW3a5nScbDRX1IDUtebdYtbMZ1bXKTV78vu9TedQsgfsLfGrnrBAD7zUxAuNvZ3g6yqDg1gIuVqLAoWm4jnU7ByrDFbr1q3x999lp83/7bffEBpa+SzRRN0mtcsio9ZE74I/ngv3Q4UYTMopgdr8RIPWZqm3I7oeH4bDN9Ox+Yz99AfZM/pcgcdm9YRMLEROkQrFKi1EAg4+rpWbKNdescpgzZgxA7t27cLnn3/OzwKs1Wpx//59jBs3DufPn8fMmTNtKpSoPQxnbOU4YA624i65BY1aGgDwys0yQqT7r7A+iWtdxcAt6FNwG1cSsnEuLtPu3IL2TqFSDS3T/Q5uDmK83S2otiVVK1YZrLFjx2Lp0qX4+OOP0bx5cwBA//790aJFC+zatQuffvophgwZYkudRC0SFuiBBz79S4IvoEuIS8AozNs/9aD5bewwhLpCSkVADsMRaLSwO7egvTPyxQA4S3W5KkMC3O3OvWkpFs+HZUhiYiJ2796N+/fvQ6vVokmTJhg6dCgaN25sS401TrXPh2WnGM6TdYjriobv/PjMvyAVcmkT2IEPzc679Myz2B36DB4KiPCS8Cd0b+ZtPO8XUW0Yzp+VJ9flHrTH+25JeVulwRMvvPACuf6eI5hAAk6rBMfpZtPdlpBtly+ITek4GdyfcwCtGlxNDPquS7R9i498lECNYqUGJ+48greLlJ6LGkAflg8Ak7o+265APVVOzVRQUICkpCQkJiaafIhni9IZxMn985TXvqi5Qd91iVKRpW+xw8grVuPvuxbODkxYhb2G5VcFqwyWXC7HvHnzUL9+fbi5uaFRo0YICgoy+ViDQqHA3Llz4efnBwcHB4SHh+PIkcrNB3T06FH06tUL9erVg7u7Ozp16oQdO3ZUvCNROUr1wVAt+inPYh9VJYhJzoGaK5m3a4FgOzgOSM2xrwzg9oq9huVXBat8GO+99x62bduGIUOGoHv37vDwsJ2FnzhxIiIjIzFjxgw0a9YMW7duxYABA3DixAl069atzP1+//13DBkyBF26dMHixYvBcRx++eUXjB8/HpmZmTXuutT7l+3Vr1wWnF8okHpV9z/xXBOVkI3HQR+i94PPwAGQCtT8tBWjNpxHRJj/s5nlhKg1rAq6cHd3x4gRI/Ddd9/ZVMzFixcRHh6OlStXYvZs3aRrcrkcbdu2Rf369XHu3Lky9+3bty9u3ryJBw8eQCrVRW6p1Wq0bNkSTk5OiI6OrrQOWwRdbDkbj5wiFdwdxc+Nf5l4vtBXyiYeCeGDTg6hK6Yp/g2pWID2/u74aUqX2pZJ1HEsKW+tcglyHIcOHTpYJa48IiMjIRQKMWXKFH6ZTCbD5MmTcf78+XLTPeXl5cHDw4M3VgAgEolQr149ODg42FxrRTyP/mXi+aJkMsSS0P5+OAsNA4qVWjzKV9BAYsKmWGWwBg8eXC3Jba9evYrmzZubWNlOnToBAK5du1bmvj179sTNmzexcOFC3L9/H3FxcfjPf/6Dy5cvY86cOTbXWh7PqjuQIMxSKoP7WOFRcBwgEnA0kJiwKVb1YS1cuBDDhw/HlClTMHXqVLzwwgsQCoUm23l6WjbTbFpaGho0aGCyXL8sNbXsdEALFy5EfHw8li9fjmXLlgEAHB0dsXv3bgwePLjc8yoUCigUJTPG5uXlWaS7NPujU3E3owCpOcVksIhnn46Tn86pxsAB+Fi0HXu0faFQa+1y2hGi7mLV09SsWTMAuhbRpk1lJ03VaCybrry4uNjIpadHJpPx68tCKpWiefPmiIiIwNChQ6HRaLBhwwaMHTsWR44cQefOncvcd8WKFViyZIlFWsvjcb4CydlF8HAU2+yYBFGnMRiTJeXU0DCGjDw51p+MQzMfF6q4ETbBKoP1ySefmJ1WpKo4ODgYtXT0yOVyfn1ZTJs2Df/88w+uXLkCgUDn6Rw+fDjatGmDDz74ABcuXChz33nz5uHDDz/kv+fl5SEggKKbCKLSRGwymj5llOAotqteQUaeHFE0wJywEVYZrMWLF9tYho4GDRogJSXFZHlaWhoAwM/P/MSBSqUSmzZtwpw5c3hjBQBisRivvfYa1q1bB6VSCYlEYnZ/qVRqtmVnLd4uUvh7OMDb5dnMzk0QZhFKAY0CHIB5gm3YgVcgV2nwwz8JcJWJKMSdqDJVznQBALm5uRa7/8wREhKCu3fvmvQh6VtHISEhZvd78uQJ1Gq1WQ0qlQpardYm+ipLS18XOIiFaOnrUmPnJIhaxyD4QgI1pGIhOI5DVqESR25l1KIw4lnBaoN1+fJl9O/fH46OjvDy8sKpU6cAAJmZmRg8eDBOnjxp8TEjIiL4vic9CoUCW7ZsQXh4OO+mS0xMRGxsLL9N/fr14e7ujr1790KpVPLLCwoKsH//frRs2bJGQ9vz5Gq08HU1Pz8SQTyrlMr0sVa0DkIAAo6jyhthE6wyWOfOnUO3bt1w7949jB07Flqtll9Xr1495ObmWjWoODw8HMOGDcO8efMwZ84cbNiwAb1798bDhw/xxRcledrGjx+PVq1a8d+FQiFmz56Nu3fvonPnzlizZg2++uordOrUCcnJyfj444+tuUyroTFYxHOLwZisV7SnIZUIUc9ZAjdH8+742iImOQdbztKEk/aGVQZr/vz5aNWqFW7duoVPP/3UZH2vXr3KDXIoj+3bt2PGjBnYsWMHpk+fDpVKhT/++AMvv/xyufstWLAAO3fuhFgsxpIlS7Bw4UK4uroiMjISY8aMsUoLQRAWUmpMllbLkCdX1bnKmz7TOY0Tsy+sCrq4dOkSVqxYAalUioKCApP1DRs2RHp6ulWCZDIZVq5ciZUrV5a5TVnuxtGjR2P06NFWndeW0Dgs4rml42TgQEnE7U/cPKz0+V+dew/CAj34wf2E/WCVwRKLxUZuwNKkpKTA2dnZalHPBlbPi0kQ9o0+QTKANniA5j51r/8q2P/Zn533WcQql2Dnzp0RGRlpdl1hYSG2bNmCHj16VEmYPTOovR96tqiPQe3Nh+ETxDPNlJNGX+k9IGyFVQZryZIluHz5MgYOHIg///wTABAdHY2NGzciLCwMjx8/xsKFC20q1J54HuepIZ5fzAcwcPy/wQeH1IIq4lnEKoMVHh6OgwcP4v79+xg/fjwAYNasWZgyZQo0Gg0OHjyI4OBgmwolCKJuYjaAoe1bJX+nXq15UcQziVXzYRly7do13Lt3D1qtFk2aNEFYWFi1pG2qSWwxHxZBPC+UOTvBYreSvweueu5mZCYqhyXlbZVTKYeEhJSZgYIgiGeb8qfS0U/rCODwQjJYRJWxSWomgiCeT8odz2ToFlSXPdMCQVQWMlgEQVhNuVldIjYBbSMAgQhoM7TmxRHPHDS7WjVAMw4TxFMiNgEoe848grAEamFVA5T2hXheoGedqEnIYFUDlPyWeF6gZ52oSaoc1v4sQmHtBEEQNYPNw9oFAoFVY6tqctJEgiAI4tmmUgbrk08+MTFYe/fuxc2bN9GvXz+0aNECABAbG4vDhw+jbdu2GDJkiM3FEgRBEM8vlTJYixcvNvq+YcMGPHr0CDdu3OCNlZ7bt2+jd+/e8POjhJcEQRCE7bAq6GLlypWYNm2aibECgFatWmHatGlGMwQTBEEQRFWxymAlJydDLBaXuV4sFiM5OdlqUQRBEARRGqsMVtu2bbF+/XqkpKSYrEtOTsb69evRrl27KosjCIIgCD1WZbpYvXo1+vXrh+bNm+PNN99E06ZNAQD37t3Db7/9BsYYfvjhB5sKJQiCIJ5vrDJY3bp1w4ULF7Bw4ULs3bsXxcW6xJYODg7o168flixZQi0sgiAIwqZUeeCwVqvF48ePAQDe3t4QCOw/eQYNHCYIgqgZLClvq2xdBAIBZDIZ6tWrZxNjpVAoMHfuXPj5+cHBwQHh4eE4cuRIpff/+eef0aVLFzg5OcHd3R0vvfQSjh8/XmVdBEEQRO1itYW5fPky+vfvD0dHR3h5eeHUqVMAgMzMTAwePBgnT5606rgTJ07EqlWrMGbMGKxduxZCoRADBgzAmTNnKtx38eLFGDVqFAICArBq1SosW7YMwcHBZoNDCIIgCDuDWcHZs2eZVCpljRs3Zu+++y7jOI4dO3aMX9+jRw82cuRIi4974cIFBoCtXLmSX1ZcXMyaNGnCunTpUu6+58+fZxzHsVWrVll83tLk5uYyACw3N7fKxyKIZ4XopGy2+cwDFp2UXdtSiGcIS8pbq1pY8+fPR6tWrXDr1i18+umnJut79eqFCxcuWHzcyMhICIVCTJkyhV8mk8kwefJknD9/HklJSWXuu2bNGvj6+uKDDz4AYwwFBQUWn58giLKhqUSI2sYqg3Xp0iVMmjQJUqnUbFLchg0bIj093eLjXr16Fc2bNzfpeOvUqRMA4Nq1a2Xue+zYMXTs2BFff/01vL294eLiggYNGmDdunUVnlehUCAvL8/oQxCEMTSVCFHbWBXWLhaLodVqy1yfkpICZ2dni4+blpaGBg0amCzXL0tNTTW7X3Z2NjIzM3H27FkcP34cixYtwgsvvIAtW7bg/fffh1gsxtSpU8s874oVK7BkyRKL9RLE80SwvzvNoE3UKla1sDp37ozIyEiz6woLC7Flyxb06NHD4uMWFxdDKpWaLJfJZPx6c+jdf0+ePMHGjRsxe/ZsDB8+HAcOHEDr1q2xbNmycs87b9485Obm8p/yXI8EQRBE7WCVwVqyZAkuX76MgQMH4s8//wQAREdHY+PGjQgLC8Pjx4+xcOFCi4/r4OAAhUJhslwul/Pry9oP0LX8IiIi+OUCgQAjRoxAcnIyEhMTyzyvVCqFq6ur0YcgCIKoW1hlsMLDw3Hw4EHcv38f48ePBwDMmjULU6ZMgUajwcGDBxEcHGzxcRs0aIC0tDST5fplZU1Z4unpCZlMBi8vLwiFQqN19evXB6BzGxIEQRD2i1V9WADQu3dv3LlzB9euXcO9e/eg1WrRpEkThIWFWTU7MQCEhITgxIkTyMvLM2rl6CMOQ0JCzO4nEAgQEhKCS5cuQalUQiKR8Ov0/V7e3t5WaSIIgiDqBlVOTRESEoJhw4ZhxIgRePHFF602VgAQEREBjUaDDRs28MsUCgW2bNmC8PBwBAQEAAASExMRGxtrtO+IESOg0Wiwbds2fplcLsfOnTvRunVrmlCSIAjCzrGqhSUQCODj44Off/4ZL7/8ssn6nTt3Yvz48dBoNBYdNzw8HMOGDcO8efPw6NEjNG3aFNu2bcPDhw+xadMmfrvx48fj1KlTYAZpEKdOnYqNGzfi3//+N+7evYsXXngBO3bsQEJCAvbv32/NZRIEQRB1CKtbWHK5HK+++irWrl1rSz3Yvn07ZsyYgR07dmD69OlQqVT4448/zBpGQxwcHHD8+HGMHj0amzdvxkcffQSBQIADBw7gtddes6lGgiAIouaxKlu7QCDAli1bcPHiRXz77bcYM2YMvv/+ez783NoWVl2BsrUTBEHUDDWSrV0sFuO///0vtm7dij179qBr167lho4TBEEQRFWoctDF+PHjcfbsWeTk5CAsLAzHjh2zhS6CIAiCMMLqsHZDQkJCEBUVhdGjR6N///7o3r27LQ5LEARBEDw2mx7Y3d0dBw4cwPz58/m5sQiCIAjCVljVwoqPjzc7EJfjOCxZsgTDhg3DkydPqiyOIAiCIPRYZbACAwPLXd+2bVurxBAEQRBEWVTKYC1duhQcx2HBggUQCARYunRphftwHGdVAlyCIAiCMEelxmEJBAJwHIfi4mJIJBIIBBV3fXEcR+OwCIIgiHKxpLytVAur9GSN5U3eSBAEQRDVgc2iBAmCIAiiOiGDRRCEXROTnIMtZ+MRk5xT21KIaqZSLsGgoCCLpw3hOA5xcXFWiSIIgqgsUQnZyClSISohG8H+7rUth6hGKmWwevToUaV5rgiCIKqLsEAPRCVkIyzQo7alENWMVdnan3UoSpAgCKJmqJFs7QRBEETVoT64ylOl5LcqlQqxsbHIzc01G+pe0aSLBEEQzzvUB1d5rDJYWq0W8+bNw/r161FUVFTmdvY6cJggCKKmoD64ymOVwfr000+xcuVKTJ06Fd26dcO4cePw+eefw93dHevXrwfHcfjiiy9srZUgCOKZI9jfnVpWlcSqPqytW7di+PDh+Pbbb9G/f38AQFhYGN59911cuHABHMfh+PHjNhVKEARBPN9YZbCSk5PRu3dvAIBUKgUAyOVyAIBEIsHYsWOxY8cOG0kkCIIgCCsNlpeXFwoKCgAAzs7OcHV1xYMHD4y2yc7OtkqQQqHA3Llz4efnBwcHB4SHh+PIkSMWH6dPnz7gOA7Tpk2zSgdBEARRt7DKYIWGhuLSpUv89169emHNmjU4e/YsTp8+ja+//hrt27e3StDEiROxatUqjBkzBmvXroVQKMSAAQNw5syZSh9jz549OH/+vFXnJwiCIOomVhmsKVOmQKFQQKFQAACWL1+OnJwcvPzyy+jRowfy8vLw1VdfWXzcixcvYteuXVixYgVWrlyJKVOm4Pjx4wgMDMScOXMqdQy5XI5Zs2Zh7ty5Fp+fIAiCqLtYZbDeeOMN7Nmzh++/at26NeLi4rBnzx78/vvvuHfvHjp37mzxcSMjIyEUCjFlyhR+mUwmw+TJk3H+/HkkJSVVeIwvvvgCWq0Ws2fPtvj8BEEQRN2lSgOHDXFzc8PgwYOrdIyrV6+iefPmJuk5OnXqBAC4du0aAgICytw/MTERn332GTZv3gwHB4cqaSEIgiDqFlXOdJGSkoLs7GyYS0nYoUMHi46XlpaGBg0amCzXL0tNTS13/1mzZiE0NBQjR4606LyG7k1Al9uKIAiCqFtYZbBycnIwe/Zs7Ny5E0ql0mQ9Ywwcx1mc6aK4uJh3Mxoik8n49WVx4sQJ7N69GxcuXLDonACwYsUKLFmyxOL9CIIgiJrDKoM1ceJE7N+/HyNHjkR4eDjc3NxsIsbBwcGopaNHP8arLDefWq3G9OnTMW7cOHTs2NHi886bNw8ffvgh/z0vL69c1yNBEARR81hlsA4fPozp06dj9erVNhXToEEDpKSkmCxPS0sDAPj5+Zndb/v27bhz5w6+++47PHz40Ghdfn4+Hj58iPr168PR0dHs/lKp1GzLjiAIgqg7WD1wuGnTprbWgpCQENy9e9ekD0nv5gsJCTG7X2JiIlQqFbp27YqgoCD+A+iMWVBQEA4fPmxzvQRBEETNYfU4rF27dpmdUqQqREREQKPRYMOGDfwyhUKBLVu2IDw8nHfTJSYmIjY2lt9m5MiR2Lt3r8kHAAYMGIC9e/ciPDzcploJgiCImsUql+DChQuhUCjw4osvYty4cfD394dQKDTZbujQoRYdNzw8HMOGDcO8efPw6NEjNG3aFNu2bcPDhw+xadMmfrvx48fj1KlTfGRiy5Yt0bJlS7PHDAoKwpAhQyzSQRAEQdQ9rDJYKSkpOH78OK5du4Zr166Z3caaKEFA58JbuHAhduzYgezsbAQHB+OPP/6gySAJgiCeczhmbgBVBfTr1w+nTp3CrFmzyo0S7NGjR5UF1gZ5eXlwc3NDbm6uySBmgiAIwnZYUt5a1cI6c+YM5s6dS2OXCIIgiBrDqqALX19feHp62loLQRBEjRCTnIMtZ+MRk5xT21IIC7DKYM2aNQsbN27k58QiCIKwJ6ISspFTpEJUgnXz9hG1g1UuQblcDrFYjKZNm2L48OEICAgwiRLkOA4zZ860iUiCIAhbEhbogaiEbIQFetS2FMICrAq6EAgqbphZGyVYF6CgC4IgiJqh2oMu4uPjrRJGEARBENZiscEqLi7G2rVr0atXLwwaNKg6NBEEQRCECRYHXTg4OOC7775DRkZGdeghCIIgCLNYFSUYFhaGGzdu2FoLQRAEQZSJVQZrzZo12LVrFzZu3Ai1Wm1rTQRBEARhglVRgsHBwcjMzERGRgakUikaNmxoMrkix3GIjo62mdCahKIECYIgaoZqjxL09PSEl5cXWrRoYZVAgiAIgrAUqwzWyZMnbSyDIAiCIMrHqj4sgiAIgqhprGphAYBGo8EPP/yAAwcOICEhAQAQGBiI119/HWPGjDE7oSNBEARBWItVQRe5ubno168fLl26BBcXFzRu3BiALgNGXl4eOnXqhL/++stuAxYo6IIgCKJmsKS8tcoluGDBAkRFReGbb77B48ePceXKFVy5cgWPHj3CunXrcPnyZSxYsMAq8QRBEARhDqtaWA0bNkRERATWrl1rdv306dMRGRmJ1NTUKgusDaiFRRAEUTNUewvryZMn5Ya0t2zZEllZWdYcmiAIgiDMYpXBatq0KX7//fcy1//+++9o0qSJ1aIIgiAIojRWGaz33nsPhw8fxoABA3D48GE8fPgQDx8+xF9//YWBAwfiyJEjmDZtmlWCFAoF5s6dCz8/Pzg4OCA8PBxHjhypcL89e/ZgxIgRaNy4MRwdHdGiRQvMmjULOTk5VukgCIIg6hZW9WEBwOLFi/HZZ59BpVIZLReLxZg3bx4WLVpklaBRo0YhMjISM2bMQLNmzbB161ZcunQJJ06cQLdu3crcr169evDz88OQIUPwwgsv4Pr16/jf//6Hxo0b48qVKyapo8qD+rAIgiBqBkvKW6sNFgBkZmbi6NGjRuOwXn31VdSrV8+q4128eBHh4eFYuXIlZs+eDQCQy+Vo27Yt6tevj3PnzpW578mTJ9GzZ0+jZdu3b8eECRPw/fff45133qm0DjJYBEEQNUO15xLUU69ePYwcObIqhzAiMjISQqEQU6ZM4ZfJZDJMnjwZ8+fPR1JSEgICAszuW9pYAcCbb76JCRMm4Pbt2zbTSBAEQdQOVTJY+fn5SEhIQHZ2Nsw11F5++WWLjnf16lU0b97cxMp26tQJAHDt2rUyDZY50tPTAcDqFh9BEARRd7DKYD158gTTpk3D7t27odFoAACMMXAcZ/S3fl1lSUtLQ4MGDUyW65dZOq7r888/h1AoRERERLnbKRQKKBQK/nteXp5F5yEIgiCqH6sM1rvvvov9+/dj+vTp6N69Ozw8PGwipri4GFKp1GS5TCbj11eWH3/8EZs2bcKcOXPQrFmzcrddsWIFlixZYplYgiAIokaxymAdPnwYM2fOxBdffGFTMQ4ODkYtHT1yuZxfXxlOnz6NyZMno1+/fli+fHmF28+bNw8ffvgh/z0vL88i1yNBEARR/VhlsBwdHdGoUSMbS9G5/lJSUkyWp6WlAQD8/PwqPEZ0dDTeeOMNtG3bFpGRkRCJKr5EqVRqtmVHEARB1B2sGjg8duxY7N2719ZaEBISgrt375r0IV24cIFfXx5xcXHo378/6tevj4MHD8LZ2dnmGgmCIIjawSqDFRERgaysLPTv3x979uzBpUuX+Izthh9rjqvRaLBhwwZ+mUKhwJYtWxAeHs676RITExEbG2u0b3p6Ovr27QuBQIC//voL3t7e1lwaQRAEUUexauCwQFBi5/SRgYZYGyUIAMOHD8fevXsxc+ZMNG3aFNu2bcPFixdx7NgxPky+Z8+eOHXqlFEofUhICKKjozFnzhy0a9fO6Jg+Pj7o06dPpTXQwGGCIIiaodoHDm/ZssUqYZVh+/btWLhwIXbs2IHs7GwEBwfjjz/+qHBMV3R0NACYDQTp0aOHRQaLIAiCqHtUKTXTswq1sAiCIGqGap8Py5C0tDRER0ejsLCwqociCIIgiDKx2mDt27cPLVu2hL+/Pzp06MBH8mVmZiI0NLRaoggJgiCI5xerDNb+/fsxdOhQ1KtXD4sWLTIKfqhXrx4aNmyIrVu32kojQRAEQVhnsJYuXYqXX34ZZ86cwb///W+T9V26dMHVq1erLI4gCIIg9FhlsG7cuIHhw4eXud7HxwePHj2yWhRBEARBlMYqg+Xo6FhukMWDBw/g5eVltSiCIAiCKI1VBqtXr17Ytm0b1Gq1ybr09HR8//336Nu3b5XFEQRBEEBMcg62nI1HTHJObUupVawyWMuXL0dycjI6duyI7777DhzH4a+//sLHH3+Mdu3agTGGRYsW2VorQRDEc0lUQjZyilSISsiubSm1itUDh2/evIkPPvgAJ06cMIoS7NmzJ/773/+iVatWNhNZ09DAYYIg6hIxyTmISshGWKAHgv3da1uOTbGkvK1ypovs7Gzcv38fWq0WjRs35pPOGs5AbG+QwSKIZ59n2QjYEzWa6cLDwwMdO3ZEeHg4vL29oVQqsWHDBrRo0aKqhyYIgqg2yM1mf1iU/FapVOL3339HXFwcPDw88Prrr/OTKhYVFWHdunVYs2YN0tPT0aRJk2oRTBAEYQvCAj34FhZhH1TaYKWmpqJnz56Ii4vj+6wcHBzw+++/QyKRYPTo0UhJSUGnTp3wzTffYOjQodUmmiAIoqoE+7uTK9DOqLTBWrBgAeLj4zFnzhx0794d8fHxWLp0KaZMmYLMzEy0adMGP/zwA3r06FGdegmCIIjnlEobrCNHjmDSpElYsWIFv8zX1xfDhg3DwIEDsW/fPqOJHQmCIAjCllTawmRkZKBz585Gy/Tf3377bTJWBPGMQINUibpKpa2MRqOBTCYzWqb/7ubmZltVBEHUGhQ9R9RVLIoSfPjwIa5cucJ/z83NBQDcu3cP7u7uJtt36NChauoIgqhxKHqOqKtUeuCwQCAwOxDY3ABh/TKNRmMblTUMDRwmCIKoGSwpbyvdwtqyZUuVhREEQRCEtVTaYE2YMKE6dRAEQRBEudS50D6FQoG5c+fCz88PDg4OCA8Px5EjRyq1b0pKCoYPHw53d3e4urpi8ODBePDgQTUrJgiCIGqCOmewJk6ciFWrVmHMmDFYu3YthEIhBgwYgDNnzpS7X0FBAXr16oVTp05h/vz5WLJkCa5evYoePXrgyZMnNaSeIAiCqC6qnK3dlly8eBHh4eFYuXIlZs+eDQCQy+Vo27Yt6tevj3PnzpW57xdffIG5c+fi4sWL6NixIwAgNjYWbdu2xZw5c/Dpp59WWgcFXRDEs0tMcg72R6cCAAa196P0TLVMjWZrtyWRkZEQCoWYMmUKv0wmk2Hy5Mk4f/48kpKSyt23Y8eOvLECgJYtW+KVV17BL7/8Uq26CYKwH6ISsnE3owB3M/JprJmdUacM1tWrV9G8eXMTK9upUycAwLVr18zup9VqERMTgxdffNFkXadOnRAXF4f8/Pwyz6tQKJCXl2f0IQji2SQs0APNfZzR3MeFxprZGRYNHK5u0tLS0KBBA5Pl+mWpqalm98vKyoJCoahw37Lm6FqxYgWWLFlirWyCIOwIytJuv9SpFlZxcTGkUqnJcn0KqOLi4jL3A2DVvgAwb9485Obm8p/yXI8EQRBE7VCnWlgODg5QKBQmy+VyOb++rP0AWLUvoDN05owdQRAEUXeoUy2sBg0aIC0tzWS5fpl+duPSeHp6QiqVWrUvQRAEYR/UKYMVEhKCu3fvmgQ9XLhwgV9vDoFAgHbt2uHy5csm6y5cuIDGjRvDxcXF5noJgiCImqNOGayIiAhoNBps2LCBX6ZQKLBlyxaEh4cjICAAAJCYmIjY2FiTfS9dumRktO7cuYPjx49j2LBhNXMBBEEQRLVRpwYOA8Dw4cOxd+9ezJw5E02bNsW2bdtw8eJFHDt2DC+//DIAoGfPnjh16hQMpefn5yM0NBT5+fmYPXs2xGIxVq1aBY1Gg2vXrsHb27vSGmjgMEEQRM1QLdnaa4rt27dj4cKF2LFjB7KzsxEcHIw//viDN1Zl4eLigpMnT2LmzJlYtmwZtFotevbsidWrV1tkrADwhpDGYxEEQVQv+nK2Mm2nOtfCqgskJyfz7keCIAii+klKSoK/v3+525DBMoNWq0VqaipcXFzMTlqZl5eHgIAAJCUl2Z3LkLTXPPaqGyDttYG96gas084YQ35+Pvz8/CAQlB9WUedcgnUBgUBQoaUHAFdXV7t7oPSQ9prHXnUDpL02sFfdgOXa3dzcKrVdnYoSJAiCIIiyIINFEARB2AVksKxAKpVi0aJFdpnOibTXPPaqGyDttYG96gaqXzsFXRAEQRB2AbWwCIIgCLuADBZBEARhF5DBIgiCIOwCMlgEQRCEXUAGiyAIgqgUtR2jRwaLqFVq+wUgiJoiNze3tiVYzc8//wwAZlPV1SRksABcvXoViYmJRg+UvRSkRUVFtS3BKh48eICioiLI5fLalmIx0dHRuHfvHpKTk/ll9vK87Nu3D++99x4ePHgAQJc30x746aef4OLigrNnz9a2FIvZs2cP+vbti9WrV+Phw4e1Lccidu3ahSZNmmDUqFE4c+ZMbct5vg3W7du30a1bN7zyyito3749OnXqhN27d0OtVoPjuDpdCN25cwdhYWF45513aluKRcTExGDgwIEYNGgQgoKC0LNnT5w9e7ZO32s9MTEx6NOnD15//XWEhYWhffv2+Prrr/nnpa5z5MgRvPnmm9ixYwf++OMPAKgw2Whtc/XqVYSHh+Ptt9/GwIED7Sq3XmpqKgYOHIjx48dDIpHA0dERjo6OtS2rUujv+4QJE+Di4gKZTAaFQlHbsgD2nJKRkcFCQ0PZSy+9xDZv3sw2b97MOnfuzNzd3dmiRYsYY4xptdraFWkGrVbLIiMjWfPmzRnHcYzjOHby5MnallUharWaff3118zb25v16NGDffLJJ+y9995jAQEBrGXLlnX6GpRKJVu+fDlzd3dnPXr0YN988w376aefWM+ePZmrqyvbs2dPbUssF/1zHBUVxby8vJiDgwMLDw9n165dY4wxptFoalOeWYqKitikSZMYx3GsR48ebN++fSwjI6O2ZVnEokWLWKtWrdjOnTtZYmJibcupFLm5uWz8+PGM4zjWs2dPtm/fPnbgwAEmk8nYl19+yRjTvcu1xXNrsHbt2sVEIhGLjIzklyUnJ7MRI0YwjuPY0aNHa1Fd2cTFxbG2bdsyLy8vtmzZMta6dWvWuXNnplKpaltauRw6dIg1btyYvf322yw2NpZffvbsWcZxHJs7d26dvYYDBw6wDh06sBkzZrC7d+/yL+y9e/cYx3Hsiy++qJOVm9JERkayvn37sv/973+M4zg2f/58/lrqkn61Ws2WL1/OOI5j7777Lnv8+HGZz0Zd0m1IYmIi8/HxYdOnTzdZbkhd0l9YWMiaNWvGGjduzL799luWkJDAGGPswYMHzMPDgw0dOrTWKzfPrcH6/PPPmZubG/8DKJVKxpiuFtqpUyfWtm3bOlmjS0hIYPPnz+drx//9738Zx3Fs48aNtaysfFatWsVatWrFHj16xC9TKBSMMcY6d+7M+vTpwxirWy+wnjNnzrCvvvrKSDtjjO3du5fVr1+f/fzzz4yxuqmdsRJdFy5cYG5ubowxxl599VXWoEEDduTIEaNt6gqXL19mXbt2ZS1btuSX7du3j02YMIHNmTOHbd68mX9+6iJ///03c3R0ZHfv3mWMMbZ9+3bWunVr1rp1azZkyBD2448/1rJCY/Tl4Llz59iNGzf48lBPx44dWc+ePZlcLq/VZ+WZN1j6H6L0TV69ejVzcXFhJ06cYIwxo5rmzz//zKRSKfv000/N7ltTlKVdLpfzf9+5c4f17duX+fv7s8zMzBrVVxaGug2137lzx2g9Y7r73rNnT9atWzdWXFxcs0LNUNY9L83p06dZ27ZtmaurK1u8eDG7fv06y87ONjpGTVOR9sjISNa0aVPGGGNXr15lHMexCRMmsKysrHL3q27K0q1vCc6aNYv17duXcRzHmjZtylxcXBjHcWzo0KHsxo0bRseoacrSfvnyZSYSidjevXvZ5s2bmUAgYBEREWzChAmsfv36jOM4tmXLllpQXEJlnnWtVss0Gg3797//zdzc3PhnvLaelWfWYOn7HUq3PPQ3+siRI0wqlbLFixfzy/Q/YHp6Ohs+fDjz9vaulVpcWdrL4ueff2YODg5szpw51aysfCzVrTdooaGhbMSIEfyy2qAy2vXPx9y5cxnHcaxXr15swoQJbPLkyczd3Z2NHDmypuQaUZF2/T29ePEic3FxYampqYwxxiZPnsykUilf2y8sLKwZwU+p6B1NSEhgERERjOM41rt3b3bo0CGWkJDAUlJS2H/+8x8mEAjYsGHDalSznoru+eXLl1m9evXY2LFjWfv27dnChQtZfn4+Y4yxmJgY1q9fP+bl5cVu375dk7IZY5a/p4wxtnDhQsZxHPv999+rUVnFPJMG6++//2Zt2rRhHMexvn37slu3bjHGTAvDDh06sNDQUHb9+nWT9Tt37mQikYh9++23Zvetbe2Gyx49esTefvttJpPJ+BpnTRf8lug2JCkpiTk5ObEVK1YwxmqnQ7ey2vXf9+7dy37++WeWmZnJL5s3bx4TCARs5cqVjLGaq/Fbct9/+eUX1rx5c97VnZeXxxwdHVmvXr3YpEmT2Lhx43hjVld079y5k02cOJGdPXvWZN2YMWOYm5sbX4jWtXe0a9euTCAQsHr16rFz584ZrTt8+DDz9PRkH3zwAWOsbj4vhrpOnz7NOI5jv/zyS7nbVzfPnME6f/48a9myJWvUqBEbNmwY4ziOff7550adtvpCcd++fYzjOLZs2TLeHaVfd+fOHebv78+mTJlSYw9TZbSXxbFjx1jDhg3Zm2++WQNKjamK7r///ptxHMf++uuvGlBqiiXay3tJ7927x5o2bcrat29v5LKtTiqrXa/79OnTzNHRkSUlJfHrRo0axYRCIROLxWzRokWsoKCgTujWa87NzTXpO9Rv988//zCO44y8JHVBu74MOXToEB/Jq29J6T02jx49Yv3792cBAQF17nkxx40bN5iHhwd7//33GWNksGzGrVu3mFQqZb/++itjjLHu3buzZs2asbNnz5rdfsCAAczPz4/t37+fMWZcw2/Tpg0bP348Y6xmfiBLtRvqKigo4Jvtx44dY4wxdurUKbZv3z6j7eqKbj3r169nIpGId5eo1WoWFxfHLl++XO26GauadsaMa8ZdunRhnTt3rrECqLT2l19+uVztu3btYi1atGA5OTnsxIkTrFu3bkwoFDJXV1fWtGlTdvr0acZY3b3npV33jx8/Zu7u7jXqCrdU+5gxYxjHcWzq1KmMMWZkHCIiIljr1q1Zbm5u9QtnVXvWHz16xAIDA9krr7zC8vLyqltqmTxTBktvbAxrZPoa/PTp0/kHw7CQSUhIYM7Ozqxz587sypUr/PJ//vmHubq6siVLltQp7eYKE/31xMbGsg4dOrB27dqxJUuWsICAAObl5VWt0Y5V0c0YY4MGDWIvvfQSY0znHvzhhx9YaGgo69ChA3vy5Em16a6q9tKt7r/++ouJxWI2Y8aMalRcgiXa9fqPHTvGJBIJe/3115lQKGRdu3Zlf//9N/vll1/4QrW6+2xtec/Xr1/POI5j33//fTUqLsGa8iUpKYm5urqaeBFu3rzJmjRpwsaOHVsjlWFb3PehQ4eyNm3asIKCAmphWcquXbvY1KlT2Weffcb+/vtvfrnhjdTf6AkTJjB3d3f222+/GR1D/yNu3bqVvfDCCywoKIh9/fXXbOPGjWzQoEEsICCAxcTE1Ent5khISGATJ07k3RCDBw82cv/UJd1arZbl5+ezBg0asJEjR7KjR4+yN954g3Ecx/r378+Sk5NtptvW2g1JTU1l+/fvZz169GCtW7fm+0ProvazZ8+y4OBg1qpVK7Zu3TqWlJTEvwNdu3Zl7777rk0NVnXd8/T0dLZ3714WHBzMevToUS3RsbYsX3bt2sUaNGjAPD092bvvvss+/fRT9tprrzEPD49qcYVXx33XarVs2bJljOM4Ptq3NoyW3Rms9PR01q9fP+bk5MQ6dOjAPDw8mFQqZYsWLeJDLksPhkxOTmbOzs5s6NChfAGu0WiMbvjJkydZ165dmZubG/Py8mLBwcHszJkzdVZ7aU6fPs369+/PBAIBCw0NrbRLqzZ1379/nzk6OrIOHTowZ2dn1qJFC96dWde1nzx5kr377rssIiKCubi4sPbt27NLly7VSe16N5RSqWR///03u379Om+Y9PvZckhBdd7zf/3rX2zUqFHM2dmZdejQgR+PWBe1G5YvZ8+eZf369WPu7u6sfv36LDQ01MiY1DXt5li9ejXjOM4o2UJNY3cGa9u2bczT05Pt3LmTpaamsidPnrCJEycyFxcX9t5775lsr/9hli9fzgQCAduwYYPRg2T4d3FxMcvIyLB5wVNd2g05evQok0gkbN26dXaj+/jx44zjOFa/fv1q0V2d2vfv38+aNm3KevbsyTZv3mw32muiVlxd9zwyMpI5Ozuz8PDwanMDVmf5olAoWHZ2NouOjrYL7Xr0BiwtLY1t3bq1WrRXFrszWD169GCdO3c2WlZYWMgmTJjAOI5jBw4cYIyZ1hKUSiVr0qQJCw8P50efx8XFGfl0qzsasDq1M1Z9IeG21m3Yp/bdd9+ZjKq3F+1xcXHV+szYUvv9+/dNnhd70F36nkdHR1fr0AcqX8xrryuZUOzGYGk0GiaXy1m/fv1Y165d+eV6d0dUVBQLCwtjjRs3Nrm5pcPY586dy7Zs2cI6dOjApk+fXu0DJu1Ve3Xqru5Io+rUXt2h39WpvaioyC512/M9p/LFdtRJg3X79m32wQcfsPfff58tWLCAt/qMMTZkyBDWokULvnPbsLawYcMGxnEcW716NWPMtMWhUqlYx44dmVAoZBzHsQYNGrBDhw6RdjvWTdprR7u96ibttafdFtQpg6VQKNjs2bOZg4MDe/HFF1mzZs0Yx3GscePG/NiByMhIxnEc27x5M/+D6G/+w4cP2SuvvMKCgoJMOpWvXLnCFixYwJydnZmLiwtbs2YNabdj3aSdnhfSbh/abUmdMVj5+fls/vz5rHHjxuzzzz9nd+7cYRqNhh09epT5+fmx7t27s6KiIqZWq1n79u3Zyy+/zB4+fGhynMWLFzN3d3feX8uY7oeZNm0an+xTP0j1eddur7pJe+1ot1fdpL32tNuaOmOw4uPjWVBQEJs6dSrLyckxWjd16lTm7e3NZz/YsWMH4ziOrVq1ivex6msNV69eZQKBgO3du5cxVuLHvXjxIp83i7Tbt27STs8LabcP7bamzhgsrVbLNmzYYLRMHz32yy+/MJFIxOfjysnJYUOHDmW+vr4mA94uXrzIOI5j27ZtqxnhzH6126tuxkg7Y/S8WAJprx3ttqbOGCzGSix+6Q7BlStXMqFQaDRTbVJSEvPx8WFt2rThOwdTUlLYtGnTWGBgIEtPT6854cx+tdurbsZIOz0vlkHaa0e7LalTBqs0+o7DDz74gPn6+vK1Cv2P9tdff7EOHTowjuNYSEgI69KlCxOLxWzJkiVMrVbX6tgBe9Vur7pJOz0vpN0+tFcFjjHGUMd58cUX0ahRI0RGRkKj0UAoFPLrMjMzsWnTJsTFxSEvLw8ffPABunTpUotqjbFX7faqGyDttYG96gZIu11R2xazIh49esQcHBz4ifEY09Uu9NN612XsVbu96maMtNcG9qqbMdJubwhq22BWxI0bNyCXy9GxY0cAQHp6On788Uf069cPjx8/rmV15WOv2u1VN0DaawN71Q2Qdnujzhos9tRTeenSJbi5ucHPzw8nT57Ee++9h7fffhuMMQgEAn67uoS9ardX3QBprw3sVTdA2u2WmmvMWcfQoUNZkyZN2LvvvstcXFxYs2bN2OHDh2tbVqWwV+32qpsx0l4b2Ktuxki7vVGnDVZxcTELCQlhHMcxV1dXPg+WPWCv2u1VN2OkvTawV92MkXZ7pM5HCc6dOxccx2HJkiWQSqW1Lcci7FW7veoGSHttYK+6AdJub9R5g6XVaiEQ1NmutnKxV+32qhsg7bWBveoGSLu9UecNFkEQBEEAdThKkCAIgiAMIYNFEARB2AVksAiCIAi7gAwWQRAEYReQwSIIgiDsAjJYBEEQhF1ABosgCIKwC8hgEQRBEHYBGSyCIAjCLiCDRRAEQdgFZLAIgiAIu+D/A9B+QIWF65XZAAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -543,10 +543,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:06:27.746429Z", - "iopub.status.busy": "2026-02-11T21:06:27.745431Z", - "iopub.status.idle": "2026-02-11T21:06:27.857048Z", - "shell.execute_reply": "2026-02-11T21:06:27.857048Z" + "iopub.execute_input": "2026-03-20T15:32:36.731263Z", + "iopub.status.busy": "2026-03-20T15:32:36.730787Z", + "iopub.status.idle": "2026-03-20T15:32:36.870873Z", + "shell.execute_reply": "2026-03-20T15:32:36.869761Z" } }, "outputs": [ @@ -554,13 +554,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:1206: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + "D:\\repos\\public\\rdtools\\rdtools\\analysis_chains.py:1208: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", " fig = plotting.soiling_rate_histogram(results_dict[\"calc_info\"], **kwargs)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -586,10 +586,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:06:27.860568Z", - "iopub.status.busy": "2026-02-11T21:06:27.860568Z", - "iopub.status.idle": "2026-02-11T21:06:27.876158Z", - "shell.execute_reply": "2026-02-11T21:06:27.876158Z" + "iopub.execute_input": "2026-03-20T15:32:36.875441Z", + "iopub.status.busy": "2026-03-20T15:32:36.874356Z", + "iopub.status.idle": "2026-03-20T15:32:36.895223Z", + "shell.execute_reply": "2026-03-20T15:32:36.893758Z" } }, "outputs": [ @@ -736,10 +736,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:06:27.879397Z", - "iopub.status.busy": "2026-02-11T21:06:27.879397Z", - "iopub.status.idle": "2026-02-11T21:07:20.419721Z", - "shell.execute_reply": "2026-02-11T21:07:20.419721Z" + "iopub.execute_input": "2026-03-20T15:32:36.898985Z", + "iopub.status.busy": "2026-03-20T15:32:36.898365Z", + "iopub.status.idle": "2026-03-20T15:33:41.447754Z", + "shell.execute_reply": "2026-03-20T15:33:41.444806Z" } }, "outputs": [], @@ -765,10 +765,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:20.422736Z", - "iopub.status.busy": "2026-02-11T21:07:20.422736Z", - "iopub.status.idle": "2026-02-11T21:07:20.429051Z", - "shell.execute_reply": "2026-02-11T21:07:20.429051Z" + "iopub.execute_input": "2026-03-20T15:33:41.450438Z", + "iopub.status.busy": "2026-03-20T15:33:41.450134Z", + "iopub.status.idle": "2026-03-20T15:33:41.459780Z", + "shell.execute_reply": "2026-03-20T15:33:41.458373Z" } }, "outputs": [ @@ -870,10 +870,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:20.431495Z", - "iopub.status.busy": "2026-02-11T21:07:20.431495Z", - "iopub.status.idle": "2026-02-11T21:07:20.436814Z", - "shell.execute_reply": "2026-02-11T21:07:20.436579Z" + "iopub.execute_input": "2026-03-20T15:33:41.462987Z", + "iopub.status.busy": "2026-03-20T15:33:41.462579Z", + "iopub.status.idle": "2026-03-20T15:33:41.470405Z", + "shell.execute_reply": "2026-03-20T15:33:41.468973Z" } }, "outputs": [ @@ -903,42 +903,13 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:20.438850Z", - "iopub.status.busy": "2026-02-11T21:07:20.438850Z", - "iopub.status.idle": "2026-02-11T21:07:21.663431Z", - "shell.execute_reply": "2026-02-11T21:07:21.662914Z" + "iopub.execute_input": "2026-03-20T15:33:41.473107Z", + "iopub.status.busy": "2026-03-20T15:33:41.472787Z", + "iopub.status.idle": "2026-03-20T15:33:44.892098Z", + "shell.execute_reply": "2026-03-20T15:33:44.890924Z" } }, "outputs": [ - { - "data": { - "text/html": [ - " \n", - " " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, { "data": { "application/vnd.plotly.v1+json": { @@ -25202,24250 +25173,10 @@ "2013-01-21T23:59:00-07:00" ], "xaxis": "x", - "y": [ - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.1232292, - 0.15561508333333332, - 0.18510966666666667, - 0.19399958333333336, - 0.18918074999999998, - 0.1786457833333333, - 0.21624929999999998, - 0.3378168333333333, - 0.4889288, - 0.5976350333333333, - 0.6651153166666667, - 0.7205152833333333, - 0.7905545333333334, - 0.8745185499999999, - 0.9732547833333334, - 1.1157427, - 1.2492243833333334, - 1.3228528333333331, - 1.138607233333333, - 0.7569224, - 0.3741076333333333, - 0.25149325, - 0.33693615, - 0.42801210000000006, - 0.38680276666666663, - 0.35260566666666665, - 0.2902100833333333, - 0.18419575, - 0.13504365000000002, - 0.11620035, - 0.10915488333333333, - 0.10760953333333333, - 0.10870623333333335, - 0.10875608333333332, - 0.1109661, - 0.1147547, - 0.11964, - 0.12636975, - 0.13580801666666667, - 0.14616019999999996, - 0.15727675, - 0.16794464999999997, - 0.1789781166666667, - 0.19164001666666666, - 0.20388649999999997, - 0.2135906333333333, - 0.22140046666666668, - 0.2301242166666667, - 0.24567741666666668, - 0.29389898333333336, - 0.3381657833333333, - 0.3102996333333333, - 0.36601531666666665, - 0.3619442333333333, - 0.3664141166666666, - 0.37357589999999996, - 0.3802558, - 0.3860384, - 0.3931004833333333, - 0.4004284333333334, - 0.40775638333333336, - 0.4156659166666667, - 0.42387455, - 0.43195025, - 0.44019211666666663, - 0.44889925, - 0.4575897666666667, - 0.46651291666666667, - 0.474572, - 0.4849075666666666, - 0.49889880000000003, - 0.51171025, - 0.5259174999999999, - 0.5385960166666667, - 0.5488318833333334, - 0.5604967833333333, - 0.5720786, - 0.58508945, - 0.6000610666666667, - 0.6166611166666666, - 0.6347234333333334, - 0.6536165833333334, - 0.6728586833333333, - 0.72407125, - 0.7475506, - 0.5701178333333333, - 0.8373636833333333, - 0.8178224833333333, - 0.8382942166666666, - 0.8620394333333333, - 0.88448855, - 0.9056914166666667, - 0.92287305, - 0.9374624833333333, - 0.9507059666666666, - 0.9627696666666666, - 0.9769270666666667, - 0.9914168, - 1.00622225, - 1.0244673499999999, - 1.0322107166666665, - 1.0522504166666669, - 1.10532405, - 1.1354002166666666, - 1.1614717666666665, - 1.2290351333333334, - 1.2645283333333333, - 1.2929926833333334, - 1.3163557166666666, - 1.3396855166666668, - 1.3611043999999999, - 1.37959875, - 1.3766742166666663, - 1.3888874666666666, - 1.4216223, - 1.4108214666666665, - 1.4675839999999998, - 1.4901826666666667, - 1.5241637499999998, - 1.5922422333333335, - 1.61419285, - 1.6460636166666667, - 1.66952635, - 1.7005995166666668, - 1.7341984166666664, - 1.7358268499999998, - 1.7885183, - 1.82406135, - 1.8403290666666665, - 1.8809069666666665, - 1.8834327, - 1.9272840833333333, - 1.9433690166666666, - 1.9729633, - 2.00392015, - 2.0276819833333333, - 2.0835804500000004, - 2.1022742, - 2.1495984666666668, - 2.1913395333333336, - 2.23552325, - 2.2616114166666668, - 2.2745558, - 2.267759583333333, - 2.3384302666666663, - 2.3471374000000003, - 2.4581533499999995, - 2.5462050666666665, - 2.6199664499999997, - 2.6725249666666664, - 2.72774215, - 2.8356341666666665, - 2.9037791166666667, - 2.8485120833333335, - 2.7826934666666667, - 2.6922821833333335, - 2.62933825, - 2.6098801333333332, - 2.5976336499999997, - 2.6016216500000002, - 2.6026851166666662, - 2.5992787, - 2.590687883333333, - 2.607769816666667, - 2.6176899666666666, - 2.621594883333333, - 2.6620232333333336, - 2.6868485333333334, - 2.7372967333333333, - 2.741434283333333, - 2.8396055500000004, - 2.8791366000000003, - 2.9396877333333338, - 3.013000466666667, - 3.0846349166666664, - 3.1647106333333337, - 3.2412802333333337, - 3.327421033333333, - 3.3732165666666667, - 3.46452515, - 3.5739791333333333, - 3.6715854333333335, - 3.8068451, - 3.999548583333333, - 4.625033149999999, - 4.992876299999999, - 5.364225566666667, - 5.415521216666666, - 5.530591633333334, - 6.300956916666666, - 7.022984316666666, - 7.102112883333334, - 7.2564318666666665, - 7.379212416666666, - 7.3371224, - 6.999322183333334, - 6.690102633333332, - 6.9223537833333335, - 7.26169935, - 7.259223466666667, - 7.177436233333334, - 7.0361447166666675, - 7.1841826, - 7.530623483333333, - 7.4448981000000005, - 7.378614216666666, - 7.310087083333333, - 7.216285999999999, - 7.166751716666666, - 7.079132033333334, - 6.9966469, - 6.957946683333334, - 6.8931583, - 6.836312683333333, - 6.719048866666666, - 6.659810449999999, - 6.5808812833333326, - 6.500872033333334, - 6.414382283333333, - 6.3395740499999995, - 6.225301233333333, - 6.1532679833333335, - 6.128143583333333, - 6.046389583333333, - 5.96250865, - 5.897088833333333, - 5.805946416666666, - 5.729011249999999, - 5.666898149999999, - 5.594532566666667, - 5.51874395, - 5.467032883333333, - 5.388834849999999, - 5.309157933333333, - 5.207148216666667, - 5.135713166666666, - 5.041014783333333, - 4.966638583333333, - 4.8987595, - 4.690602516666667, - 3.9145211, - 2.776910866666667, - 1.1961673666666668, - 0.49072340000000003, - 0.29531140000000006, - 0.28160265, - 0.2745904166666666, - 0.2675117166666666, - 0.26020038333333334, - 0.25147663333333337, - 0.23738569999999998, - 0.22015421666666668, - 0.20257378333333334, - 0.18404620000000002, - 0.16415605, - 0.14393356666666668, - 0.1248244, - 0.11400695000000001, - 0.10569861666666668, - 0.09775584999999999, - 0.09110918333333333, - 0.0821528, - 0.07497439999999998, - 0.06766306666666666, - 0.060800383333333326, - 0.05420356666666667, - 0.0471581, - 0.0400794, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.207998, - 0.3471724, - 0.34763720000000004, - 0.2772532, - 0.1914146, - 0.1249316, - 0.10414839999999999, - 0.141349, - 0.179446, - 0.2119322, - 0.2670442, - 0.29705699999999996, - 0.2044788, - 0.0817882, - 0.0444382, - 0.046662600000000005, - 0.09674479999999999, - 0.5151478, - 0.8954869999999999, - 0.4953274, - 0.3318008, - 0.6246911999999999, - 0.7338196, - 0.48734279999999996, - 0.6414572000000001, - 1.2187886, - 1.8584861999999998, - 2.0967128, - 2.1442552, - 2.3197836, - 2.546523, - 2.6211732000000003, - 2.8440945999999996, - 3.0455356, - 3.2174286, - 3.3814531999999997, - 3.5413111999999995, - 3.7122746, - 3.895024, - 4.1458334, - 4.3790468, - 4.5010069999999995, - 4.7206914, - 4.9761321999999995, - 5.113049, - 5.1757804, - 5.2860542, - 5.3674108, - 5.424049999999999, - 5.5415282, - 5.638073800000001, - 5.713554, - 5.7689482, - 5.881728600000001, - 5.968745800000001, - 6.0242064, - 6.143759599999999, - 6.249866800000002, - 6.3312068, - 6.4174438, - 6.500062, - 6.5660304, - 6.627301, - 6.6559194, - 6.797866, - 6.8944614, - 6.938551, - 7.0451064, - 7.112220199999999, - 7.1892608000000005, - 7.28408, - 3.197697833333333, - 2.0336141666666663, - 2.4973504999999996, - 6.065868249999999, - 6.4111995833333335, - 3.4234965, - 4.311019916666667, - 1.9387574999999997, - 1.4387865833333333, - 1.3199006666666666, - 1.4006615, - 1.743439, - 2.2238415833333334, - 3.2276804999999995, - 7.718646166666667, - 2.9087995833333333, - 2.4608505833333334, - 2.1865788333333334, - 1.825891333333333, - 1.82089975, - 2.7265985, - 3.653656583333333, - 3.0175199166666666, - 2.5954409166666665, - 2.0737955833333332, - 1.8818269166666666, - 1.6746513333333333, - 1.5908225833333334, - 1.7259104166666666, - 1.9345121666666667, - 1.8144156666666666, - 1.6603399166666664, - 1.8169860833333331, - 4.421100083333333, - 2.0034325, - 1.8568689999999999, - 1.6686315833333332, - 1.7158940833333334, - 2.703630583333333, - 7.782077416666667, - 5.622894250000001, - 4.143544833333333, - 3.5401104999999995, - 4.4336702500000005, - 4.500252333333334, - 5.940680666666667, - 6.719135499999999, - 4.016533083333333, - 3.6822462499999995, - 3.7784627499999996, - 7.356499333333334, - 5.171031583333334, - 4.426439916666666, - 4.0855695, - 4.091672166666667, - 4.035703416666667, - 4.021193, - 4.11745925, - 6.748471416666666, - 6.363920500000001, - 4.013100333333333, - 3.855989833333333, - 3.42981475, - 3.339302916666667, - 3.272588166666667, - 3.1977807499999997, - 2.739798833333334, - 2.501761666666667, - 2.423388833333333, - 2.373274, - 2.3004731666666665, - 3.5405085, - 2.45003825, - 2.12039475, - 2.1239104166666665, - 2.24457075, - 2.4053793333333333, - 2.4700709166666663, - 2.3579344166666667, - 2.4243672499999995, - 2.568061833333333, - 2.44416775, - 2.3969384166666665, - 2.354485083333333, - 2.697229416666667, - 4.024095083333333, - 4.02004875, - 2.586071333333333, - 2.455875583333333, - 2.568360333333333, - 3.4945063333333333, - 4.565822833333334, - 5.1451615833333335, - 5.2819575, - 6.199330916666667, - 4.74371225, - 7.60961075, - 5.7480155, - 5.951708583333333, - 7.444755833333334, - 7.56433825, - 7.4839754166666665, - 7.4357179166666665, - 7.3883725, - 7.330645916666667, - 7.259503416666666, - 7.213501249999999, - 7.116024416666667, - 7.0391440833333325, - 6.956376666666667, - 6.892696666666667, - 6.810161416666666, - 6.733728833333332, - 6.623897416666666, - 6.530052333333333, - 6.479622416666666, - 6.411846333333333, - 6.34367225, - 6.246809, - 6.140261083333333, - 6.070494999999999, - 6.0147086666666665, - 5.938790166666667, - 5.841429416666667, - 5.748396916666666, - 5.669393916666667, - 5.602330916666666, - 5.550226083333333, - 5.484854583333333, - 5.438686583333333, - 5.352702, - 5.266203333333333, - 5.174281916666667, - 5.06519675, - 4.94271225, - 4.862332833333333, - 4.773877333333333, - 4.697079916666667, - 4.638822666666667, - 4.358680416666667, - 3.5052689166666666, - 2.3704714166666663, - 0.8832946666666667, - 0.3964411666666666, - 0.3117169166666667, - 0.3005563333333333, - 0.29115358333333335, - 0.2824473333333334, - 0.27427175, - 0.26488558333333334, - 0.2509555833333333, - 0.23178525000000003, - 0.21321191666666664, - 0.19478783333333333, - 0.1750205, - 0.15517024999999998, - 0.1368125, - 0.12644791666666666, - 0.11752608333333335, - 0.10969875, - 0.10130758333333333, - 0.09354658333333334, - 0.08621675, - 0.07905275, - 0.07192191666666667, - 0.06500666666666666, - 0.057593916666666675, - 0.05052941666666667, - 0.043630749999999996, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.2124178, - 0.37694136666666667, - 0.5013736, - 0.5753603333333333, - 0.6237847, - 0.6889745333333334, - 0.7542969, - 0.8222036666666667, - 0.8893318, - 0.9512414333333332, - 1.0562409666666666, - 1.1893044333333334, - 1.2984125, - 1.4440169333333335, - 1.5066057999999998, - 1.5210519333333332, - 1.6840513666666665, - 1.8218197666666667, - 1.8739219333333332, - 1.9673413666666666, - 2.1599288666666667, - 2.374732266666667, - 2.5557396666666667, - 2.7238582, - 2.9061578, - 3.0044644, - 3.1389028999999997, - 3.338713466666667, - 3.4866372333333335, - 3.534233266666667, - 3.7049030666666667, - 3.9021126666666666, - 4.081132066666667, - 4.162540666666667, - 4.301534999999999, - 4.3894543, - 4.5023561333333335, - 4.594483366666667, - 4.699615433333334, - 4.7920739999999995, - 4.882378900000001, - 4.975152233333333, - 5.067412, - 5.1709868, - 5.2737001333333335, - 5.294541, - 5.452702966666665, - 5.4771388000000005, - 5.562308033333334, - 5.719857033333334, - 5.804197933333334, - 5.878781066666666, - 5.965076833333333, - 6.0640626666666675, - 6.1459019999999995, - 6.230507966666666, - 6.3186592, - 6.411531933333333, - 6.502217866666667, - 6.5631335, - 6.639257333333333, - 6.7197382, - 6.804609233333333, - 6.9014413999999995, - 6.969762333333333, - 7.051551966666667, - 7.076319133333333, - 7.199409466666666, - 7.462792199999999, - 7.38787035, - 7.31740045, - 7.238456950000001, - 7.181640799999999, - 7.1081257, - 7.0341141, - 6.95886125, - 6.8736453, - 6.789654049999999, - 6.69333305, - 6.653877850000001, - 6.5732297, - 6.49033075, - 6.36743045, - 6.268080799999999, - 6.18461915, - 6.064747499999999, - 6.05182195, - 5.996263600000001, - 5.897178749999999, - 5.8440698, - 5.7318608, - 5.6746309, - 5.60219155, - 5.531953349999998, - 5.44490035, - 5.359551999999999, - 5.266011399999999, - 5.1704517, - 5.10350695, - 5.0013107, - 4.658709149999999, - 3.7127939, - 2.2633118, - 1.0321242, - 0.31468169999999995, - 0.23909784999999997, - 0.23118695, - 0.2256427, - 0.21905580000000002, - 0.21314745, - 0.20361465, - 0.1892989, - 0.1735764, - 0.15760564999999999, - 0.14194935, - 0.12258585, - 0.10500975, - 0.09124014999999999, - 0.0838423, - 0.07758639999999999, - 0.0716946, - 0.06567039999999999, - 0.0596462, - 0.05400264999999999, - 0.0483591, - 0.04294725, - 0.036774100000000004, - 0.031254675, - 0.025735249999999998, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.32189445, - 0.4524138, - 0.5615711999999999, - 0.6550443, - 0.7525467, - 0.8207284499999999, - 0.9001156500000002, - 0.97101135, - 1.0697625, - 1.12402485, - 1.1446209, - 1.2543943499999999, - 1.37837025, - 1.5310008, - 1.6634349, - 1.78552935, - 1.8576571499999999, - 1.99065735, - 2.1305007, - 2.2843799999999996, - 2.37776985, - 2.5193115, - 2.6773533000000005, - 2.8560577499999997, - 2.9732571, - 3.05156205, - 3.2081386500000004, - 3.3294838499999995, - 3.49305345, - 3.6302661, - 3.7242053999999993, - 3.8269359, - 3.9130330499999997, - 4.0251208499999995, - 4.1242383, - 4.22059185, - 4.30906995, - 4.41100125, - 4.497880949999999, - 4.5859761, - 4.668493499999999, - 4.773604949999999, - 4.86791055, - 4.9527423, - 5.0509773000000004, - 5.117077800000001, - 5.198696100000001, - 5.2767846, - 5.387989950000001, - 5.47936515, - 5.574403350000001, - 5.63184585, - 5.689454850000001, - 5.8004604, - 5.89743, - 5.951842200000001, - 6.0230709, - 6.1475463, - 6.224419350000001, - 6.31775925, - 6.405071850000001, - 6.471571950000001, - 6.5584849499999995, - 6.63893775, - 6.7095837, - 6.77869785, - 6.86531115, - 6.9262002, - 6.990802200000001, - 7.069406849999999, - 7.14832785, - 7.2138123, - 13.7165697, - 13.73663295, - 13.71062565, - 13.724977949999998, - 13.7243286, - 13.722080849999998, - 13.730289299999997, - 13.72451175, - 13.721098500000002, - 13.7370159, - 13.730705549999998, - 13.73017275, - 13.726676249999999, - 13.72864095, - 13.731871049999999, - 13.719933, - 13.7571624, - 13.757079150000003, - 13.721098500000002, - 13.7559303, - 13.78158795, - 13.7456073, - 13.722164099999999, - 13.7538324, - 13.71565395, - 13.697705249999999, - 13.73243715, - 13.75275015, - 13.764788099999999, - 13.7594934, - 13.723862400000002, - 13.7385144, - 13.743659250000002, - 13.7524338, - 13.779323549999999, - 13.7913282, - 13.801001849999999, - 13.777875, - 13.79893725, - 13.7797065, - 13.769250299999998, - 13.75251705, - 13.751567999999999, - 13.754681549999999, - 13.7438424, - 13.737981599999998, - 13.731504750000001, - 13.732903349999999, - 13.71994965, - 13.71239055, - 13.712024249999999, - 13.701784499999999, - 7.532360099999999, - 7.445547, - 7.366309649999999, - 7.29378225, - 7.24656285, - 7.201091700000002, - 7.13467485, - 7.0508087999999995, - 6.9790806, - 6.888654450000001, - 6.7993272000000005, - 6.728631300000001, - 6.668774549999999, - 6.585058350000001, - 6.498761399999999, - 6.428115449999999, - 6.3504765, - 6.2671599, - 6.1829442, - 6.1000438500000005, - 5.9823116999999995, - 5.92585155, - 5.838888600000001, - 5.7718224000000005, - 5.65795305, - 5.5887057, - 5.52988125, - 5.4436509, - 5.32392075, - 5.19358455, - 5.11489665, - 5.02445385, - 4.959035999999999, - 4.86378135, - 4.76451405, - 4.687807500000001, - 4.314780900000001, - 3.37400595, - 1.9254892499999998, - 0.9328662, - 0.30014955, - 0.251415, - 0.24422219999999997, - 0.2378619, - 0.2309688, - 0.22564079999999997, - 0.21733245, - 0.20784195000000003, - 0.1909089, - 0.1730601, - 0.15421230000000002, - 0.13438215, - 0.11581740000000001, - 0.1037628, - 0.09538785000000001, - 0.08729594999999998, - 0.0798534, - 0.07355969999999999, - 0.0663003, - 0.05989005, - 0.05372955, - 0.04710285, - 0.040426199999999995, - 0.034448849999999996, - 0.028546424999999997, - 0.022644, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.3392867333333333, - 0.43103620000000004, - 0.5032415, - 0.5793889, - 0.6609587666666668, - 0.7242818666666666, - 0.7847440333333333, - 0.8594443333333333, - 0.9444073999999999, - 0.9949228333333333, - 1.0603916333333334, - 1.1976, - 1.2869376333333336, - 1.4185904666666667, - 1.5992284666666667, - 1.7656449666666667, - 1.9128998666666668, - 2.0427064, - 2.2203670333333334, - 2.3134139, - 2.4034002333333335, - 2.5326079666666668, - 2.7198826666666664, - 2.8551615666666663, - 3.0421535, - 3.191437666666667, - 3.3457118333333336, - 3.570810733333333, - 3.679642633333333, - 3.7551246999999996, - 3.8663351666666665, - 3.9663846666666664, - 4.0609451666666665, - 4.088539866666666, - 4.209896666666666, - 4.3117093, - 4.425464666666667, - 4.497254133333333, - 4.549100233333333, - 4.692712433333333, - 4.787339466666666, - 4.8701901, - 4.992278766666667, - 5.032797566666666, - 5.1712368, - 5.271668866666667, - 5.361688466666666, - 5.445503833333333, - 5.534226033333333, - 5.608710099999999, - 5.677538833333333, - 5.763583066666667, - 5.850641933333334, - 5.9438385, - 6.0200358, - 6.125274899999999, - 6.171199533333334, - 6.2852543, - 6.367007133333333, - 6.450024099999999, - 6.529298566666667, - 6.592172566666666, - 6.695166166666667, - 6.7619989, - 6.857939966666666, - 6.925055466666667, - 6.976036633333334, - 6.988411833333333, - 7.124838433333333, - 7.216754233333335, - 7.5910375, - 7.5006686, - 7.4378445, - 7.373989133333333, - 7.312911533333334, - 7.2386437, - 7.1501211, - 7.057889266666667, - 7.008321933333333, - 6.9461299, - 6.834836266666667, - 6.782690766666666, - 6.763728766666667, - 6.248544533333333, - 6.5542652, - 6.4236769, - 5.701607266666667, - 6.282592966666667, - 6.128967500000001, - 6.1967317, - 5.382130833333333, - 2.4622157000000002, - 1.2129691999999999, - 1.7038022333333336, - 1.2393663000000001, - 1.0108076666666665, - 1.2863055666666665, - 1.1220680333333335, - 1.6798169666666667, - 2.241241866666667, - 3.7867779333333336, - 4.764169233333333, - 5.081932433333333, - 5.1530233, - 4.937970933333333, - 4.9025752, - 4.582932433333332, - 3.461346766666667, - 2.1569441333333335, - 0.7380875333333333, - 0.7428779333333333, - 0.4417480666666667, - 0.3904342333333334, - 0.3620744, - 0.3315023333333333, - 0.31009523333333333, - 0.29667213333333325, - 0.2804712666666667, - 0.26503553333333335, - 0.2421148, - 0.21907763333333333, - 0.2001489, - 0.1810372, - 0.16568463333333336, - 0.15766736666666667, - 0.15335933333333335, - 0.14818636666666665, - 0.14023563333333336, - 0.1322682666666667, - 0.12343596666666667, - 0.11490306666666666, - 0.10500623333333332, - 0.09446069999999998, - 0.0855286, - 0.07677946666666667, - 0.06824656666666666, - 0.05924793333333333, - 0.0498501, - 0.03973703333333333, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.43723435, - 0.5973027, - 0.7474841333333334, - 0.8750835166666666, - 0.9618391333333333, - 1.080266116666667, - 1.1452705166666668, - 1.2259444333333334, - 1.3219223, - 1.4494718333333334, - 1.5359948166666666, - 1.5542565333333334, - 1.70023395, - 1.8831003666666666, - 1.9952961, - 2.15745815, - 2.3268650666666666, - 2.49544115, - 2.6268125166666665, - 2.7729893333333333, - 2.85545785, - 3.0138479166666663, - 3.1992068333333337, - 3.3570651666666667, - 3.486575466666667, - 3.5755577166666668, - 3.6486212, - 3.7430371000000004, - 3.7682944333333332, - 3.97469005, - 4.08017265, - 4.18336215, - 4.266113150000001, - 4.378990166666666, - 4.500408149999999, - 4.575897666666666, - 4.666225866666666, - 4.768983333333334, - 4.861189216666666, - 4.9746145833333335, - 5.052513516666666, - 5.1251782, - 5.25643325, - 5.317781983333333, - 5.428232966666667, - 5.515786183333334, - 5.612777666666665, - 5.68633965, - 5.7792102, - 5.846823416666667, - 5.9389462166666664, - 6.041404583333333, - 6.104930100000001, - 6.1916192500000005, - 6.277976066666667, - 6.355509433333334, - 6.4408692499999995, - 6.527043283333333, - 6.606437716666666, - 6.69490485, - 6.755090416666666, - 6.846664866666667, - 6.931858516666667, - 7.0040246999999995, - 7.0864766, - 7.0453005, - 6.757233966666666, - 6.430068416666667, - 6.390404433333333, - 6.300923683333333, - 5.592256083333334, - 5.743451133333334, - 5.8068271, - 6.007888766666668, - 5.7611645, - 5.626635966666667, - 6.412737233333334, - 7.233500866666666, - 6.218870583333333, - 6.131716166666666, - 5.596759199999999, - 5.021922233333333, - 4.738109566666666, - 4.921557566666666, - 5.049804999999999, - 5.202229683333333, - 5.4760225, - 5.6463101, - 6.08085255, - 6.41584455, - 6.737277349999999, - 6.296370716666667, - 5.655200016666667, - 6.008686366666667, - 5.584678883333334, - 4.901468016666667, - 4.552335233333333, - 3.9672125499999997, - 4.556805116666666, - 4.911487866666667, - 4.8984936333333335, - 4.813682166666666, - 4.589490099999999, - 4.684072166666667, - 5.1631639, - 4.642331099999999, - 4.489906416666667, - 4.420382283333334, - 4.140025883333333, - 3.42384755, - 3.1250964999999997, - 3.431790316666666, - 2.86732215, - 2.6572044, - 2.6976992166666665, - 2.4454416, - 2.2252209166666663, - 2.0231290166666667, - 1.9476228833333336, - 1.8848783500000001, - 1.8409605000000002, - 1.7883853666666667, - 1.74719265, - 1.7052023333333333, - 1.669975, - 1.6466618166666664, - 1.6347809, - 1.64420255, - 1.7065981333333333, - 1.8863572333333334, - 2.4666777, - 3.9359233666666666, - 5.604951216666667, - 5.266486333333333, - 5.277951833333333, - 5.259407633333334, - 5.058728149999999, - 4.859793416666666, - 3.863142366666666, - 3.3139449166666664, - 3.2912133166666666, - 3.2657067333333334, - 3.1249801833333333, - 2.9074846333333335, - 2.8290041166666664, - 2.7157116833333332, - 2.9023999333333337, - 3.3528943833333336, - 3.6678134499999997, - 3.4287993166666664, - 2.8147636333333335, - 2.0561463333333334, - 1.5311759833333334, - 1.1616047000000003, - 1.0297182166666667, - 0.9766113500000001, - 0.9184031666666667, - 0.8806833333333334, - 0.8466191666666667, - 0.81250515, - 0.7812492000000001, - 0.7479161666666666, - 0.7153474999999999, - 0.6829283833333333, - 0.6490303833333333, - 0.60941625, - 0.5702673833333333, - 0.5284930833333333, - 0.49537606666666667, - 0.4644026, - 0.4367524666666666, - 0.4093682, - 0.3818676166666667, - 0.35443349999999996, - 0.3277139, - 0.29966496666666664, - 0.2745405666666667, - 0.2524404, - 0.23092181666666667, - 0.20958601666666665, - 0.1893303, - 0.17219851666666666, - 0.1532721333333333, - 0.13266746666666665, - 0.11189663333333333, - 0.08954721666666665, - 0.05199355, - 0.03152181666666667, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.031955, - 0.03688519999999999, - 0.0462476, - 0.06027459999999999, - 0.07642639999999999, - 0.08492560000000002, - 0.090304, - 0.1048456, - 0.12786979999999998, - 0.16239779999999998, - 0.1858536, - 0.2849888, - 0.3074652, - 0.2836276, - 0.3245632, - 0.38633180000000006, - 0.4639036, - 0.5510535999999999, - 0.5508045999999999, - 0.4706266, - 0.6884683999999999, - 0.7051181999999999, - 0.7130198, - 0.7123392000000001, - 0.745091, - 0.8278751999999999, - 0.8943416000000001, - 0.866769, - 0.9710169999999999, - 1.0692557999999999, - 0.9626506000000001, - 0.9843136000000001, - 0.993178, - 1.03003, - 1.184659, - 1.2483698, - 1.2925756, - 1.3098561999999998, - 1.3981682000000002, - 1.472254, - 1.7056167999999998, - 1.8950394, - 2.4834595999999998, - 3.0076378, - 3.1952675999999998, - 4.079599399999999, - 4.6616618, - 4.8065299999999995, - 4.9775598, - 5.2388936, - 4.984249599999999, - 5.2896896, - 5.4124798, - 5.674992200000001, - 6.0320582, - 6.0399598, - 6.351193199999999, - 6.4425762, - 6.5929888000000005, - 6.651371, - 6.579244, - 6.9748386, - 6.1289524, - 4.8860108, - 3.6114960000000003, - 4.0620864, - 6.023973999999999, - 7.123143, - 7.0965332, - 6.6409794, - 6.1536532, - 6.114709599999999, - 6.454661, - 6.867752, - 6.8024642, - 6.574015, - 0.042346600000000005, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 6.6981332, - 6.4806068, - 6.0863236, - 6.1090324, - 5.9216018, - 5.4890224, - 5.2801944, - 6.0459689999999995, - 5.9238096, - 7.144556999999999, - 6.8693456, - 7.091685999999999, - 7.097413, - 7.309893000000001, - 7.305128799999999, - 7.275946, - 7.2051967999999995, - 7.0518792, - 6.829738, - 6.91307, - 6.602666599999999, - 6.5406987999999995, - 6.6132408, - 6.7055866, - 6.628214000000001, - 6.5342746, - 6.35531, - 6.1125184, - 6.066553, - 5.8218689999999995, - 5.683093, - 5.7226175999999995, - 5.8417724, - 5.786295199999999, - 5.6426222, - 5.538258, - 5.2699688, - 4.7252066, - 4.625341000000001, - 4.958984400000001, - 5.060659400000001, - 5.022413, - 4.9288056000000005, - 4.389903199999999, - 3.2519897999999996, - 1.7317286, - 0.9383316, - 0.5735466, - 0.537425, - 0.5164758, - 0.4983984, - 0.480155, - 0.4612808, - 0.445627, - 0.43296120000000005, - 0.413091, - 0.384373, - 0.3491478, - 0.3122294, - 0.28635, - 0.269252, - 0.2532994, - 0.2403348, - 0.22843259999999999, - 0.21737700000000001, - 0.20670319999999998, - 0.1979218, - 0.1910826, - 0.18432639999999997, - 0.1771718, - 0.16853980000000002, - 0.1597086, - 0.1473416, - 0.13912460000000001, - 0.1282848, - 0.1165984, - 0.10258799999999998, - 0.072044, - 0.05272160000000001, - 0.04246280000000001, - 0.0343952, - 0.026833900000000004, - 0.019272599999999997, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.2006251666666667, - 0.24241516666666665, - 0.18788916666666666, - 0.09357974999999999, - 0.037014000000000005, - 0.032320916666666664, - 0.04111008333333333, - 0.05119275, - 0.05961708333333334, - 0.07032991666666667, - 0.07953366666666667, - 0.08611724999999999, - 0.09465766666666664, - 0.10551975000000001, - 0.114425, - 0.12339658333333332, - 0.1376416666666667, - 0.1531305, - 0.17269883333333333, - 0.1915375, - 0.20510266666666666, - 0.22311216666666667, - 0.24671025000000002, - 0.26505141666666665, - 0.28732283333333336, - 0.3116671666666667, - 0.34043925, - 0.37169883333333337, - 0.4149481666666666, - 0.43194608333333334, - 0.42192975000000005, - 0.5095560833333334, - 0.7041283333333334, - 0.9864761666666666, - 0.8638921666666667, - 1.90935525, - 2.2798103333333333, - 1.6366423333333333, - 1.3090883333333332, - 1.2987900833333335, - 1.40867125, - 1.2972312499999998, - 1.1986765, - 1.13335475, - 1.06251075, - 1.08768425, - 1.3469646666666664, - 1.6203409166666667, - 1.368722, - 1.2816595, - 1.01226325, - 0.8957984999999999, - 0.8862465, - 0.8999940833333333, - 0.8948532500000002, - 0.8426986666666667, - 0.8294485833333334, - 0.8368945, - 0.85246625, - 0.8813875833333333, - 0.9075560833333333, - 0.9343547500000001, - 0.9723471666666664, - 1.0121471666666666, - 1.0414664999999999, - 1.0562588333333334, - 1.0789282500000001, - 1.0955945, - 1.12857875, - 1.1537356666666667, - 1.1754598333333335, - 1.2036846666666667, - 1.2545623333333333, - 1.302770083333333, - 1.3689873333333333, - 1.4477415833333334, - 1.507823, - 1.5457325, - 1.5964443333333334, - 1.6843525833333333, - 1.7307693333333332, - 1.793189, - 1.8310155833333333, - 1.91194225, - 2.037544416666667, - 2.28267925, - 2.4663728333333332, - 2.6135001666666664, - 2.7566806666666666, - 2.8530464166666665, - 3.098098333333333, - 3.210848416666667, - 3.3661181666666664, - 3.6114520000000003, - 4.2459635, - 4.4678485000000006, - 4.72082725, - 4.549372166666667, - 4.385661499999999, - 4.716100999999999, - 5.159804666666666, - 5.819522833333333, - 5.635447833333333, - 5.928176833333334, - 6.9093795, - 7.00853125, - 7.142541166666667, - 6.849812166666666, - 6.5605325, - 6.726166833333334, - 6.643416, - 6.736349, - 7.062990916666666, - 6.926792, - 7.1126414166666665, - 6.4190103333333335, - 5.6164765, - 4.03358075, - 3.948441916666667, - 4.535210000000001, - 4.44242625, - 4.739898083333332, - 4.777608583333333, - 4.388032916666666, - 4.647827416666667, - 5.0090787500000005, - 4.8684355, - 4.652387833333333, - 4.560516166666666, - 4.391697833333334, - 4.647512333333334, - 5.169671750000001, - 6.057576583333333, - 6.243293333333333, - 6.421812916666667, - 7.180516999999999, - 6.815866083333334, - 6.542755166666667, - 5.9886065, - 6.146712, - 6.3096266666666665, - 7.078828, - 7.18584025, - 7.086821166666667, - 6.986326166666667, - 7.047319666666667, - 7.142342166666666, - 7.051233333333333, - 6.827524166666666, - 6.601791833333333, - 6.466007500000001, - 6.214355416666667, - 5.9884406666666665, - 5.93044875, - 5.878526333333333, - 5.831877416666667, - 5.761066583333333, - 5.7307025, - 5.885590833333334, - 5.983415916666668, - 5.9848255, - 6.1159665, - 6.157839416666667, - 6.174555416666666, - 6.220375166666667, - 6.160641999999999, - 6.089880916666667, - 6.0120553333333335, - 5.9221570833333335, - 5.882390249999999, - 5.815493083333334, - 5.939105249999999, - 6.091671916666667, - 6.278068583333334, - 6.389060833333333, - 6.607015583333333, - 6.741141583333333, - 6.825617083333333, - 7.02365525, - 7.0717800833333335, - 6.910341333333333, - 7.091580583333332, - 7.047352833333334, - 6.787807083333333, - 6.485940666666667, - 6.304187333333333, - 6.150012083333333, - 6.298018333333332, - 6.46038575, - 6.232713166666667, - 5.884745083333334, - 5.733173416666666, - 5.751431666666666, - 5.775411166666667, - 5.732344250000001, - 5.716092583333333, - 5.780916833333333, - 5.949105, - 6.115601666666666, - 6.239446000000002, - 6.227771333333333, - 6.109814083333333, - 6.193277999999999, - 6.272645833333333, - 6.420735, - 6.595340916666667, - 6.850458916666667, - 6.870292583333334, - 6.730246333333333, - 6.6471306666666665, - 6.41023775, - 6.244338083333333, - 6.269577916666666, - 6.461115416666666, - 6.492275500000001, - 6.413090083333333, - 6.42098375, - 6.532589583333333, - 6.662188333333334, - 6.657113833333334, - 6.456438916666667, - 6.726863333333332, - 7.02465025, - 7.142723583333333, - 7.207929249999999, - 7.072974083333333, - 6.905764333333335, - 6.783230083333334, - 6.78614875, - 6.707891999999999, - 6.696830916666667, - 6.685720083333333, - 6.3659105, - 5.975406166666668, - 5.841446000000001, - 5.9804474999999995, - 6.112683, - 6.285282333333333, - 6.079848, - 6.0402967499999995, - 5.73314025, - 5.512581916666666, - 5.2489566666666665, - 4.928997833333333, - 4.749151583333332, - 4.521943333333333, - 4.357818083333333, - 4.270258083333333, - 4.255200416666667, - 4.279693999999999, - 4.3132255, - 4.315049666666667, - 4.370073166666667, - 4.426622333333333, - 4.479523166666667, - 4.582572, - 4.754524583333334, - 5.061001166666666, - 5.069292833333333, - 5.261294666666667, - 5.207315916666667, - 5.349534583333333, - 5.247696333333334, - 5.116041249999999, - 4.824887666666666, - 4.671126999999999, - 4.807110333333332, - 4.8897285, - 4.976127666666667, - 4.997437250000001, - 5.093023583333333, - 4.9827112499999995, - 4.776116083333333, - 4.69635025, - 4.394384333333333, - 4.12900125, - 4.131472166666667, - 4.029335416666666, - 3.98940275, - 3.9206814166666666, - 3.798793916666667, - 3.682262833333333, - 3.6374546666666663, - 3.5951505833333335, - 3.62175025, - 3.5961124166666663, - 3.57747275, - 3.5767596666666672, - 3.6294117500000005, - 3.6951812499999996, - 3.854746083333333, - 3.899239166666667, - 3.886387083333333, - 3.85477925, - 3.7128590833333335, - 3.6051337500000002, - 3.562912583333333, - 3.515567166666667, - 3.4372938333333334, - 3.3909268333333333, - 3.35359775, - 3.3166003333333336, - 3.358257666666667, - 3.3784893333333335, - 3.3069819999999996, - 3.266551833333333, - 3.2038336666666667, - 3.1044995, - 3.0190621666666666, - 2.9386495833333335, - 2.8761801666666664, - 2.845235666666667, - 2.8037441666666667, - 2.8015883333333336, - 2.8085864999999997, - 2.8203606666666667, - 2.8381380000000003, - 2.8421511666666666, - 2.8860804166666667, - 2.942828583333333, - 2.987371416666667, - 3.0656613333333333, - 3.116754583333333, - 3.1596390833333334, - 3.2334680833333334, - 3.3114760833333334, - 3.3359696666666663, - 3.3587054166666666, - 3.3589707499999997, - 3.3355385, - 3.3267659166666665, - 3.23180975, - 3.0578174166666665, - 2.914935416666667, - 2.826513083333333, - 2.7804611666666665, - 2.7596988333333337, - 2.7892337499999997, - 2.8312227500000002, - 2.7959002500000003, - 2.71719575, - 2.6895015833333336, - 2.710744833333334, - 2.6985892499999995, - 2.661392833333333, - 2.6678934999999995, - 2.645141166666667, - 2.630299083333333, - 2.598475666666667, - 2.57680125, - 2.5608149166666663, - 2.5512795, - 2.56744825, - 2.592140833333333, - 2.59894, - 2.5953579999999996, - 2.5931690000000005, - 2.5903995833333333, - 2.6035833333333334, - 2.615921333333333, - 2.61898925, - 2.5964525, - 2.5480955, - 2.4892578333333333, - 2.449822666666666, - 2.4351298333333338, - 2.3979334166666666, - 2.3440873333333334, - 2.315630333333333, - 2.259645, - 2.1912719166666665, - 2.128504, - 2.0581575, - 1.9821063333333333, - 1.9303331666666668, - 1.8884104999999998, - 1.8511643333333334, - 1.79960675, - 1.767186333333333, - 1.7383479166666667, - 1.7185474166666665, - 1.7577006666666666, - 1.7633058333333334, - 1.7549146666666664, - 1.7309351666666666, - 1.718365, - 1.6952644166666668, - 1.6663596666666665, - 1.6384333333333332, - 1.6103411666666665, - 1.5871244999999998, - 1.5491154999999999, - 1.51931525, - 1.5079888333333331, - 1.5010901666666667, - 1.4975579166666666, - 1.490709, - 1.4854520833333333, - 1.483147, - 1.4643249166666665, - 1.4539271666666664, - 1.4357518333333332, - 1.4030163333333334, - 1.370314, - 1.3331175833333333, - 1.302455, - 1.2689400833333333, - 1.2292064166666667, - 1.2018936666666666, - 1.1687601666666667, - 1.18181125, - 1.1930215833333333, - 1.2031871666666667, - 1.1940829166666664, - 1.1756256666666665, - 1.1806835833333333, - 1.1772508333333331, - 1.1607835833333333, - 1.1432384166666665, - 1.1311159999999998, - 1.115361833333333, - 1.1105858333333332, - 1.0952296666666665, - 1.0569884999999999, - 1.049526, - 1.0321798333333332, - 1.0043032500000002, - 0.98370675, - 0.9696606666666666, - 0.9558799166666668, - 0.9444208333333334, - 0.9289485833333334, - 0.9051017499999999, - 0.8785518333333333, - 0.8557, - 0.8340421666666666, - 0.8145733333333333, - 0.7962653333333334, - 0.7782226666666666, - 0.7586875000000001, - 0.7393015833333334, - 0.7155542500000001, - 0.69008225, - 0.6618076666666667, - 0.6351416666666666, - 0.6128039166666668, - 0.5945290833333333, - 0.5772160833333332, - 0.5599528333333333, - 0.5473494999999999, - 0.5394558333333334, - 0.5295887499999999, - 0.52441475, - 0.5320265000000001, - 0.5250946666666667, - 0.5087269166666667, - 0.490137, - 0.47088375, - 0.4521943333333333, - 0.43413508333333334, - 0.37771858333333336, - 0.3776190833333333, - 0.35398783333333333, - 0.31894725, - 0.2962778333333333, - 0.2762783333333333, - 0.2533933333333333, - 0.23085658333333334, - 0.21064149999999998, - 0.19445616666666665, - 0.17973016666666664, - 0.164772, - 0.15235108333333333, - 0.13798991666666666, - 0.12455741666666666, - 0.10926758333333335, - 0.094326, - 0.07906933333333332, - 0.06411116666666666, - 0.04946808333333333, - 0.03684816666666667, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.2598813, - 0.4848069333333333, - 0.5834282999999999, - 0.6003925666666666, - 0.5920429666666666, - 0.5574020666666667, - 0.5025664, - 0.45631226666666663, - 0.5202761666666667, - 0.7184466333333333, - 0.9465033666666667, - 1.1294159333333333, - 1.21268, - 1.2316488333333333, - 1.1966269, - 1.2204994666666666, - 1.4122255, - 1.5728890333333332, - 1.6259686333333334, - 1.6837034666666668, - 1.7328401999999998, - 1.7177148333333332, - 1.655507, - 1.6570642666666666, - 1.689336133333333, - 1.9061772333333336, - 2.1380443000000002, - 2.3529636666666667, - 2.5437951, - 2.7754136666666667, - 2.8807445333333335, - 3.0355600333333332, - 3.2044075000000003, - 3.270889533333333, - 3.3923563333333333, - 3.6378411999999996, - 3.7725116333333335, - 3.9507524, - 4.126822933333334, - 4.2570700666666665, - 4.3527757, - 4.549637399999999, - 4.770023766666667, - 4.862913066666667, - 4.945845800000001, - 5.031246966666667, - 5.1486218, - 5.225756199999999, - 5.2729215, - 5.390644233333334, - 5.485206766666666, - 5.581972666666667, - 5.610268533333334, - 5.670206733333333, - 5.8020277, - 5.893873299999999, - 5.9643976, - 6.054089533333335, - 6.1072519666666665, - 6.1616072000000015, - 6.287911466666667, - 6.346375233333333, - 6.393905, - 6.410968666666666, - 6.4806480666666655, - 6.622906033333334, - 6.761171433333334, - 6.883946999999999, - 6.953460733333333, - 7.024680833333333, - 7.114869766666666, - 7.3488739333333335, - 7.272385633333332, - 7.202027, - 7.091295399999999, - 7.031638833333333, - 6.9984061, - 6.926274833333333, - 6.855336366666667, - 6.771442766666667, - 6.691989033333333, - 6.6175053, - 6.5347548, - 6.4603539, - 6.398593366666666, - 6.330173033333334, - 6.273100866666667, - 6.1888925, - 6.1090743000000005, - 6.0252304, - 5.942065733333333, - 5.836767999999999, - 5.748832133333333, - 5.689705700000001, - 5.634588399999999, - 5.553444866666667, - 5.4703796, - 5.377904466666667, - 5.3187117666666675, - 5.2308753, - 5.1513553000000005, - 5.066318600000001, - 5.0163369666666675, - 4.9238452666666666, - 4.8234844, - 4.7502100333333335, - 4.655117366666666, - 4.554889033333334, - 4.423018366666667, - 3.9369855, - 3.0411595666666664, - 1.9158853, - 0.6775435333333334, - 0.3127124, - 0.29225256666666666, - 0.28355506666666663, - 0.2747416, - 0.26675646666666664, - 0.2574128666666667, - 0.24841716666666666, - 0.23837776666666663, - 0.22436236666666665, - 0.2063544, - 0.1869217, - 0.16891373333333334, - 0.15547816666666667, - 0.1425396, - 0.13395806666666668, - 0.1257907, - 0.1171926, - 0.10900866666666666, - 0.1005431, - 0.09221006666666667, - 0.08412553333333334, - 0.07625636666666666, - 0.06830436666666667, - 0.0609322, - 0.0529802, - 0.04605533333333333, - 0.037921100000000006, - 0.02955493333333333, - 0.020923699999999996, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.15214414999999998, - 0.28702665, - 0.43139229999999995, - 0.57215005, - 0.6532946999999999, - 0.720587, - 0.7847513500000001, - 0.8700335, - 0.9483646499999999, - 0.9379215999999999, - 0.85141475, - 0.7342573000000001, - 0.5805078, - 0.4209658, - 0.4174903, - 0.5068271999999999, - 0.5974053500000001, - 0.7883261500000001, - 0.9546536499999999, - 1.0101623499999999, - 0.9955487000000001, - 1.0237829999999999, - 1.17003535, - 1.2383868500000002, - 1.2587599000000003, - 1.19419835, - 1.2328757000000001, - 1.46293725, - 1.7025647, - 1.8240086, - 2.28027555, - 2.6836487, - 3.12766865, - 3.37866595, - 3.5486013499999998, - 4.0170491, - 4.774757749999999, - 5.269470350000001, - 5.398245899999999, - 4.88037985, - 4.6085461, - 3.7851835999999994, - 3.5787554499999996, - 3.02317195, - 2.6540242000000003, - 2.6570859500000004, - 2.8015177999999996, - 2.7810951, - 2.6942738, - 2.5130016499999996, - 2.32340485, - 2.1660309, - 2.0572312, - 2.1121772, - 2.2055192, - 2.3229745499999996, - 2.2584791999999996, - 2.24413035, - 2.1515331000000004, - 2.0039402, - 1.9414474000000002, - 1.9491597, - 1.9295645, - 1.98555315, - 2.0199275, - 2.0771077499999997, - 2.1157023500000003, - 2.1791054, - 2.2452226499999997, - 2.3176289, - 2.4221090499999995, - 2.468929, - 2.4915363, - 2.4021000999999997, - 2.2968089999999997, - 2.2779419999999995, - 2.3952649499999996, - 2.4383776999999998, - 2.5270195, - 2.5610463, - 2.4930258, - 2.4001803, - 2.3436124, - 2.2862500999999997, - 2.3139051499999996, - 2.3754215000000003, - 2.4423662499999996, - 2.5291875499999996, - 2.64907575, - 2.7319581499999996, - 2.5416828, - 2.437815, - 2.4403140499999996, - 2.4274050499999995, - 2.3966386, - 2.4068168500000002, - 2.42753745, - 2.4032916999999996, - 2.35091095, - 2.3192011499999996, - 2.34770025, - 2.3733693000000002, - 2.3936596, - 2.3928817500000004, - 2.3985418500000004, - 2.35696825, - 2.3212368, - 2.2691705000000004, - 2.2133638999999996, - 2.1769042499999998, - 2.1346521, - 2.15896405, - 2.1790391999999996, - 2.157789, - 2.1916172000000005, - 2.20341735, - 2.2112620499999998, - 2.1837724999999995, - 2.2076541499999998, - 2.2011169, - 2.1440194, - 2.1395178, - 2.10415045, - 2.0580586999999997, - 1.9587587, - 1.8982850000000002, - 1.8769354999999999, - 1.8457884, - 1.8308437499999999, - 1.80459545, - 1.7894522, - 1.7783636999999999, - 1.7787278, - 1.7920505500000001, - 1.8027583999999999, - 1.8003420999999997, - 1.8077565, - 1.804612, - 1.79383795, - 1.7898990499999998, - 1.7872676, - 1.79757825, - 1.79549295, - 1.810901, - 1.8062669999999998, - 1.8190105, - 1.8441499499999998, - 1.85378205, - 1.8597400499999999, - 1.86530085, - 1.8607165, - 1.8451098499999998, - 1.83028105, - 1.8201028000000001, - 1.7969493499999998, - 1.7943013499999998, - 1.7847188999999997, - 1.7673248500000003, - 1.7406959, - 1.72555265, - 1.7485737, - 1.7661994499999998, - 1.7823357000000002, - 1.7801676499999999, - 1.8343357999999998, - 1.8451595, - 1.8648208999999998, - 1.8888846000000001, - 1.8866834499999998, - 1.8651188, - 1.83190295, - 1.8279640499999998, - 1.8201690000000001, - 1.8318367500000001, - 1.85295455, - 1.8755784, - 1.8947101999999998, - 1.9146364, - 1.93616795, - 1.9644684499999998, - 1.9871419499999998, - 2.0026162000000003, - 2.0077963499999996, - 1.9853876499999998, - 1.97827115, - 2.0367423, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 2.0176601499999998, - 2.5337718999999996, - 2.50135045, - 2.5308922, - 2.5190423999999996, - 2.49976165, - 2.46063745, - 2.45602, - 2.42310205, - 2.3989059499999996, - 2.36855325, - 2.3763483, - 2.36269455, - 2.3247123000000003, - 2.3331858999999993, - 2.3090229, - 2.27623735, - 2.2219698999999995, - 2.18206785, - 2.1554057999999996, - 2.15939435, - 2.1694236499999997, - 2.2420947, - 2.3523177, - 2.4694917, - 2.5923258, - 2.747399299999999, - 2.7998793500000003, - 2.8649539500000003, - 2.9074709, - 2.9026383, - 2.8996096500000004, - 2.82933835, - 2.7594973499999997, - 2.69419105, - 2.61058045, - 2.5197540500000004, - 2.4499296, - 2.4004450999999998, - 2.3785328999999997, - 2.3636378999999996, - 2.3667162, - 2.3608409499999996, - 2.33551945, - 2.37461055, - 2.3642005999999998, - 2.35845775, - 2.3197472999999995, - 2.3198135, - 2.2540107, - 2.2388178, - 2.2692698, - 2.2568573, - 2.2402742, - 2.1996605, - 2.15436315, - 2.10646745, - 2.08912305, - 2.07303645, - 2.0577938999999996, - 2.04566275, - 2.0203246999999998, - 2.0096334, - 1.9906670999999998, - 2.0036423, - 2.02030815, - 1.9961782499999998, - 2.0427830499999997, - 2.05039605, - 2.03162835, - 2.00733295, - 1.9762354999999998, - 1.9396269, - 1.90260455, - 1.8580354, - 1.8064987, - 1.78857505, - 1.79516195, - 1.7938875999999997, - 1.8010537500000001, - 1.8019143499999999, - 1.7937386499999999, - 1.79175265, - 1.8378443999999998, - 1.8990132, - 1.9451215, - 1.9305409500000001, - 1.903581, - 1.8692397499999998, - 1.8275006500000002, - 1.79784305, - 1.7846857999999999, - 1.7728359999999999, - 1.76944325, - 1.7766424999999997, - 1.7863573499999998, - 1.80621735, - 1.84838675, - 1.8649698499999998, - 1.8845153999999997, - 1.9334206499999997, - 1.9465117, - 1.93937865, - 1.98101845, - 1.9839809, - 1.9786849000000002, - 1.9901209499999999, - 2.04169075, - 2.12636055, - 2.2476223999999996, - 2.3763648500000003, - 2.5157655, - 2.69783205, - 2.85528875, - 3.0167008999999996, - 3.11035735, - 3.1453275, - 3.1275031500000003, - 3.1677362, - 3.1619437, - 3.1986681499999996, - 3.3118205, - 3.3899530499999995, - 3.3233889500000005, - 3.32371995, - 3.2242048000000003, - 3.17417415, - 3.1126578, - 3.1312599999999997, - 3.0363292000000004, - 2.9451387, - 2.8560997, - 2.7796055999999996, - 2.7406468999999998, - 2.7490212000000005, - 2.71362075, - 2.6807689999999997, - 2.68257295, - 2.7297735499999995, - 2.79782715, - 2.6940752, - 2.56808005, - 2.51962165, - 2.5084503999999996, - 2.50611685, - 2.5075567000000003, - 2.4599919999999997, - 2.39483465, - 2.32386825, - 2.2909172000000004, - 2.2806893, - 2.2732748999999997, - 2.2269349, - 2.1673218, - 2.10060875, - 2.0516869499999997, - 2.0041056999999998, - 1.9783042499999999, - 1.99793255, - 2.0071012500000003, - 2.0290962, - 2.0555762, - 2.07624715, - 2.1069805, - 2.11682775, - 2.11626505, - 2.07988815, - 2.0384635, - 2.0284011, - 2.0371560499999997, - 2.07541965, - 2.1045476499999998, - 2.1191944, - 2.1249703500000003, - 2.13572785, - 2.1265757, - 2.1184, - 2.1443834999999996, - 2.13840895, - 2.13198755, - 2.0914069499999997, - 2.0614845500000003, - 2.0309829, - 2.0105933, - 1.98505665, - 1.9400240999999998, - 1.8827776500000002, - 1.8254484500000001, - 1.80598565, - 1.7683674999999999, - 1.7570473, - 1.7417881999999998, - 1.7461905000000002, - 1.7541676, - 1.79655215, - 1.84646695, - 1.89889735, - 1.9357872999999997, - 1.9474054, - 1.9682915, - 2.0021197, - 2.08296645, - 2.1700029, - 2.1793702, - 2.22519715, - 2.301443, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 1.48504805, - 1.7482757999999998, - 1.7240466, - 1.7864732, - 1.8574396, - 1.9520890499999997, - 2.02808665, - 2.1158844, - 2.0376028999999996, - 1.9843118999999998, - 2.1102574, - 2.1646241500000003, - 2.07267235, - 2.00458565, - 1.9752425, - 1.9306568000000002, - 2.0556258499999998, - 2.1347845000000003, - 1.9919249, - 1.90763575, - 1.9613074, - 1.8677006, - 1.74931845, - 1.6669822, - 1.6232570999999998, - 1.62191655, - 1.6257065, - 1.6425875, - 1.5908853, - 1.5431219999999999, - 1.4769882, - 1.4911384500000002, - 1.4620931999999998, - 1.4849321999999998, - 1.54793805, - 1.67381735, - 1.78400725, - 1.9300940999999998, - 2.1036704999999998, - 1.9935302499999998, - 1.86993485, - 1.8657477, - 1.9431024000000001, - 1.9339337, - 1.9514104999999997, - 2.1040015, - 2.3731375999999997, - 2.1691092, - 1.9889955499999998, - 1.9731903, - 1.935357, - 1.6738669999999998, - 1.5538795, - 1.5486662500000001, - 1.5725644500000002, - 1.5943938999999998, - 1.5940298000000002, - 1.5194058499999998, - 1.46201045, - 1.40137125, - 1.4757800500000002, - 1.50960825, - 1.42622935, - 1.3129777, - 1.14199965, - 1.0444374, - 1.0001826999999999, - 0.9630610500000001, - 0.857952, - 0.6810987000000001, - 0.5645039500000001, - 0.49671515000000005, - 0.44772714999999996, - 0.40929805, - 0.3758836, - 0.34460409999999997, - 0.3189516, - 0.29809860000000005, - 0.27875165, - 0.26382355, - 0.2595371, - 0.25594574999999997, - 0.2514938, - 0.24762109999999998, - 0.24277195, - 0.2387172, - 0.23256059999999998, - 0.22102525, - 0.20626264999999996, - 0.19140075, - 0.17341089999999998, - 0.15369985000000003, - 0.13216830000000002, - 0.11025610000000001, - 0.08685439999999998, - 0.0667958, - 0.0485246, - 0.0322394, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.11269119999999999, - 0.2607968, - 0.47220853333333335, - 0.6207274666666666, - 0.6894565333333333, - 0.7595413333333333, - 0.8309818666666667, - 0.8907664000000001, - 0.9725898666666667, - 1.103848, - 1.2271205333333335, - 1.3666949333333331, - 1.5137093333333336, - 1.6459264, - 1.6511013333333333, - 1.7598410666666666, - 1.8832128, - 2.0372042666666665, - 2.1357594666666664, - 2.2271392, - 2.3235946666666663, - 2.5244415999999994, - 2.7063082666666665, - 2.8853146666666665, - 3.0534586666666663, - 3.154841066666667, - 3.1957445333333334, - 2.7854864, - 1.8526096, - 0.8171930666666667, - 0.5669610666666667, - 0.6996245333333333, - 0.6307797333333334, - 0.5947205333333333, - 0.40179306666666664, - 0.3136869333333333, - 0.2612928, - 0.24021280000000003, - 0.23350026666666665, - 0.22968106666666666, - 0.22806079999999998, - 0.2263413333333333, - 0.22258826666666665, - 0.21549546666666666, - 0.20517866666666665, - 0.1908608, - 0.1712192, - 0.14673333333333333, - 0.121272, - 0.101432, - 0.0889824, - 0.07828533333333333, - 0.06576960000000001, - 0.05394826666666666, - 0.04745066666666667, - 0.0452352, - 0.0488064, - 0.05727146666666666, - 0.06439733333333333, - 0.06841493333333333, - 0.05140213333333333, - 0.05497333333333333, - 0.05794933333333333, - 0.05404746666666666, - 0.04545013333333334, - 0.038721066666666665, - 0.031992, - null, - null, - null, - null, - null, - null, - null, - 0.06479413333333334, - 0.10040693333333334, - 0.1293568, - 0.15324746666666667, - 0.18051093333333332, - 0.22455573333333334, - 0.27579253333333326, - 0.3332128, - 0.40915039999999997, - 0.4947434666666667, - 0.5738389333333332, - 0.6311269333333333, - 0.6782469333333334, - 0.6183466666666666, - 0.5733925333333333, - 0.5156085333333333, - 0.5493365333333333, - 0.6441056, - 0.7410074666666666, - 0.6547861333333334, - 0.7603514666666666, - 1.2449103999999998, - 1.8544613333333333, - 1.8857423999999998, - 4.003645866666666, - 5.589142933333334, - 3.7268117333333337, - 3.774229333333333, - 3.4901866666666663, - 6.152565866666666, - 7.194959466666666, - 2.1969658666666665, - 1.7566997333333332, - 1.5960784000000001, - 1.4723429333333333, - 1.3981744, - 1.4085408000000001, - 1.2730005333333336, - 1.1305328, - 1.0346064, - 0.9729370666666667, - 0.9099946666666666, - 0.8690581333333331, - 0.8548394666666665, - 0.8447871999999998, - 0.8126629333333333, - 0.7734623999999999, - 0.7376842666666668, - 0.7091642666666667, - 0.6903493333333334, - 0.6737829333333334, - 0.6566378666666667, - 0.6439237333333333, - 0.6219839999999999, - 0.5936128, - 0.5687632, - 0.5461952, - 0.5152613333333333, - 0.47384533333333334, - 0.4321152, - 0.39081493333333334, - 0.36067466666666664, - 0.3308816, - 0.30146880000000004, - 0.2877130666666667, - 0.29158186666666663, - 0.2864234666666667, - 0.27835519999999997, - 0.26805493333333336, - 0.2649301333333333, - 0.2636736, - 0.2864565333333333, - 0.2561178666666667, - 0.23650933333333332, - 0.21875253333333333, - 0.2002352, - 0.16992960000000001, - 0.16683786666666664, - 0.1772704, - 0.19294399999999998, - 0.19157173333333333, - 0.1998384, - 0.19752373333333334, - 0.18724, - 0.17593119999999998, - 0.15685173333333333, - 0.1543056, - 0.15566133333333332, - 0.13939253333333335, - 0.1314069333333333, - 0.14059946666666664, - 0.1343664, - 0.13041493333333332, - 0.12249546666666666, - 0.11548533333333333, - 0.11052533333333332, - 0.112344, - 0.11336906666666667, - 0.10794613333333333, - 0.11249279999999999, - 0.10315146666666666, - 0.12456213333333332, - 0.14431946666666665, - 0.13210133333333332, - 0.12980319999999998, - 0.14362506666666666, - 0.14903146666666664, - 0.16270453333333332, - 0.17500533333333335, - 0.19296053333333332, - 0.20779093333333334, - 0.21511519999999998, - 0.2105354666666667, - 0.21050239999999998, - 0.2317808, - 0.21175893333333334, - 0.20987413333333335, - 0.21177546666666663, - 0.21592533333333333, - 0.20099573333333334, - 0.18156906666666664, - 0.16900373333333332, - 0.15242079999999997, - 0.15166026666666665, - 0.15759573333333332, - 0.18785173333333333, - 0.21900053333333333, - 0.21233760000000002, - 0.2091797333333333, - 0.19320853333333332, - 0.18603306666666666, - 0.211048, - 0.24403199999999997, - 0.24371786666666664, - 0.2644010666666667, - 0.2945082666666667, - 0.31590239999999997, - 0.3530858666666667, - 0.3815232, - 0.4312389333333333, - 0.48679093333333334, - 0.5324229333333333, - 0.5709952, - 0.6144282666666666, - 0.6493466666666666, - 0.6752213333333333, - 0.7089327999999999, - 0.7548458666666668, - 0.8284357333333333, - 0.9074650666666667, - 0.9961333333333333, - 1.1251098666666666, - 1.2677264, - 1.3498309333333334, - 1.5014416, - 1.6906490666666667, - 1.8627280000000002, - 2.0558373333333333, - 2.3997802666666668, - 2.8084512000000004, - 3.4128437333333332, - 4.287953066666667, - 5.0387648, - 6.4469088, - 6.356769066666668, - 6.1369088000000005, - 6.4547456, - 17.264090133333333, - 17.553671466666668, - 17.1699824, - 17.288013866666667, - 16.93112533333333, - 5.967409066666667, - 5.262741866666666, - 4.807992533333333, - 5.593772266666667, - 17.842574933333335, - 17.29533813333333, - 17.303373333333337, - 6.009767466666666, - 4.948079466666667, - 4.6036405333333335, - 4.5774186666666665, - 4.611675733333334, - 4.613775466666667, - 4.660201066666668, - 4.805744000000001, - 4.958181333333333, - 5.159474666666667, - 5.5340207999999995, - 6.653310933333334, - 6.52736, - 6.257469866666667, - 5.592168533333333, - 5.4457493333333336, - 4.1340938666666665, - 3.861922133333333, - 3.9025114666666663, - 3.8190016, - 3.067644266666667, - 2.8756592, - 2.743640533333333, - 2.733439466666667, - 2.8507269333333336, - 2.555259733333334, - 2.1568890666666665, - 1.7335530666666668, - 1.6859701333333332, - 1.697312, - 1.6631376, - 1.6605088, - 1.6412970666666666, - 1.6723301333333334, - 1.7256832, - 1.7557407999999999, - 1.7599733333333332, - 1.9031685333333332, - 1.9038133333333334, - 1.8151119999999998, - 1.8088789333333333, - 1.8697711999999997, - 1.8413338666666665, - 1.8584789333333334, - 1.9518096, - 2.0537045333333332, - 2.145762133333333, - 2.234463466666667, - 2.339665066666667, - 2.2679269333333334, - 2.240184, - 2.1265834666666663, - 2.025399466666667, - 1.8917274666666666, - 1.8110778666666665, - 1.713547733333333, - 1.5986245333333333, - 1.5132629333333334, - 1.4519408, - 1.4200645333333335, - 1.3065632, - 1.0819743999999998, - 0.7626826666666667, - 0.5639189333333334, - 0.48277333333333333, - 0.46328053333333336, - 0.47812746666666667, - 0.4687696, - 0.4396213333333333, - 0.4384309333333334, - 0.458552, - 0.4469621333333333, - 0.42027733333333334, - 0.4420352, - 0.4121098666666666, - 0.36012906666666666, - 0.3096528, - 0.26767466666666667, - 0.22973066666666667, - 0.20259946666666664, - 0.18299093333333333, - 0.16068746666666664, - 0.14327786666666667, - 0.12636426666666667, - 0.10578026666666666, - 0.08706453333333333, - 0.07694613333333332, - 0.07139093333333334, - 0.06481066666666667, - 0.05748639999999999, - 0.0521296, - 0.04467306666666667, - null, - null, - null, - null, - null, - null, - null, - null, - 0.041101866666666674, - 0.04753333333333333, - 0.05507253333333333, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.07952533333333332, - 0.08236906666666666, - 0.09792693333333331, - 0.11484053333333334, - 0.10592906666666665, - 0.07707839999999999, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.07992213333333333, - 0.07952533333333332, - 0.08041813333333334, - 0.07972373333333334, - 0.07651626666666667, - 0.07332533333333333, - 0.051501333333333336, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.11409713333333334, - 0.12868135, - 0.17109615000000003, - 0.18837258333333332, - 0.19316241666666667, - 0.21912661666666666, - 0.25642125, - 0.28719179999999994, - 0.3729958833333333, - 0.34201061666666666, - 0.3490136833333333, - 0.4693541166666667, - 0.6350328, - 0.5685697333333334, - 0.9658946666666667, - 1.2156762166666668, - 0.8450091833333334, - 1.3025869166666666, - 0.9943363666666666, - 0.5527632833333332, - 0.5102328666666667, - 0.516311, - 0.6265762666666665, - 0.6249411166666667, - 0.5432992333333333, - 0.4279138, - 0.5522843000000001, - 0.7084493833333333, - 0.7796857666666667, - 0.6403181333333333, - 0.6216047499999999, - 0.7254945833333333, - 0.8907107999999999, - 1.0080617166666666, - 0.97004035, - 0.9390550833333332, - 0.9178476833333334, - 1.1026031166666668, - 1.3997379500000002, - 1.4755329333333334, - 1.4266270833333332, - 1.4298808666666667, - 1.4266931499999997, - 1.4921156666666666, - 1.4177080833333333, - 1.3671505666666666, - 1.4032229666666667, - 1.45067535, - 1.2747398166666668, - 1.1378827166666667, - 1.1229351333333333, - 1.16338445, - 1.1366604833333334, - 1.1800662833333333, - 1.1505344833333333, - 1.26238535, - 1.2053863333333334, - 1.2407485166666667, - 1.1722704166666666, - 1.0999769666666666, - 0.9729142500000001, - 0.9542339, - 0.92990485, - 0.8905621499999999, - 0.8872092666666667, - 0.8528546, - 0.8779599333333334, - 0.9216465166666666, - 0.9777701499999999, - 0.9905210166666666, - 0.9552083833333334, - 0.9454305166666668, - 0.8925276333333333, - 0.8424160666666667, - 0.7911483333333333, - 0.7592546499999999, - 0.7512605833333333, - 0.7544152666666667, - 0.7573387166666666, - 0.7954261499999999, - 0.8273363499999999, - 0.8554642333333332, - 0.9042379500000001, - 0.9148581666666666, - 0.9794053, - 1.0840383833333331, - 1.2023803000000002, - 1.3907859166666665, - 1.5864258333333332, - 1.6144546166666667, - 1.5234643, - 1.4388989666666665, - 1.3428049999999998, - 1.3058572166666667, - 1.33690855, - 1.3285015666666666, - 1.3892663833333332, - 1.5479585166666667, - 1.7663418833333333, - 1.8883835333333332, - 1.9288493666666664, - 1.8817108, - 1.82854365, - 1.7858480666666665, - 1.7763674999999999, - 1.7839321333333333, - 1.7156522333333333, - 1.6727089, - 1.6966415499999998, - 1.7128774333333334, - 1.6907451, - 1.6123404833333335, - 1.5335394666666666, - 1.6245793333333334, - 1.9689022833333332, - 2.619444233333333, - 3.0290080166666664, - 2.9456318833333333, - 2.6806715166666666, - 2.5572259500000003, - 2.64780335, - 2.91844545, - 3.1032008833333338, - 3.110022266666667, - 3.0596794666666662, - 2.7431870999999997, - 2.4999957, - 2.574205083333333, - 3.11307785, - 3.6672946, - 4.275091416666666, - 5.728343366666666, - 5.661417833333333, - 4.352323350000001, - 3.571497933333333, - 3.495884633333333, - 3.9122698, - 4.457930916666666, - 4.903088116666667, - 4.90966175, - 5.3045422166666665, - 4.265891633333334, - 3.5927053333333334, - 3.3568143, - 3.452313666666667, - 4.493061866666666, - 5.620621666666667, - 7.411210016666666, - 4.9186468166666675, - 3.8080496333333334, - 3.732485883333333, - 4.161952250000001, - 4.672829266666667, - 5.444917366666667, - 4.355114666666666, - 3.2351855666666665, - 2.803753716666666, - 2.3671191166666667, - 2.1298076499999996, - 2.0784408166666664, - 2.142921883333333, - 2.295519366666667, - 2.5731645333333333, - 2.963106516666666, - 3.19037585, - 4.78499395, - 4.867874583333333, - 4.196620733333333, - 4.020404416666667, - 3.76545315, - 3.4222203, - 3.4773529333333335, - 4.035335483333333, - 4.696960116666666, - 4.906870433333334, - 5.141687883333333, - 5.266405233333334, - 4.958253783333333, - 4.5996439166666665, - 4.96238295, - 5.617466983333333, - 6.2230836, - 6.911712983333333, - 8.444426616666666, - 7.915397783333334, - 7.370628566666667, - 7.434448966666667, - 7.21938545, - 8.303572483333333, - 7.301621933333334, - 6.465168383333335, - 5.013815849999999, - 4.34261155, - 4.211816066666667, - 4.173613016666667, - 3.8376474999999997, - 3.5157541833333332, - 3.4369036166666667, - 3.4565914833333333, - 3.650777933333333, - 3.9260116666666667, - 4.0520999, - 4.016671649999999, - 4.0255741333333335, - 4.2264168, - 4.573498033333333, - 4.819034799999999, - 4.806118766666667, - 4.583457583333333, - 4.4697073, - 4.516515533333333, - 4.59937965, - 4.51682935, - 4.414591183333333, - 4.52465825, - 4.8872156, - 6.09876265, - 9.287751100000001, - 7.477458366666666, - 8.868789333333334, - 6.532671999999999, - 5.955629216666667, - 5.4050131, - 5.8858297833333335, - 6.1448771833333335, - 5.197646349999999, - 4.8580802, - 4.646435633333333, - 4.490402683333333, - 4.378006766666665, - 4.233039983333333, - 4.1335105500000004, - 4.171746633333333, - 4.312600766666666, - 4.4206197666666665, - 4.403541533333334, - 4.35301705, - 4.230859783333333, - 4.087594216666666, - 4.009569483333333, - 4.151431133333333, - 4.371730433333332, - 4.655189466666667, - 4.2400926000000005, - 3.8886014166666665, - 3.702838466666666, - 3.566724616666667, - 3.541123783333333, - 3.73493035, - 4.28404345, - 4.982467216666667, - 5.2402098, - 5.189487116666667, - 4.970971616666666, - 4.897191666666667, - 5.192129783333334, - 7.3917699, - 8.98623935, - 8.4560048, - 7.986353383333334, - 7.120401066666666, - 7.028403233333333, - 6.948264366666667, - 7.250519366666667, - 7.340700366666667, - 6.170494533333333, - 5.6726822, - 5.316483766666667, - 5.186976583333333, - 5.512569633333333, - 5.963458116666668, - 7.361626983333333, - 7.6922411, - 7.0994249, - 8.38440505, - 7.720187299999999, - 5.5744575833333325, - 4.9126843, - 5.543323666666667, - 3.8071412166666665, - 4.465115666666666, - 6.2250656, - 7.862478383333333, - 7.516322083333333, - 7.025744050000002, - 6.656101050000001, - 6.207657033333333, - 6.5332831166666665, - 6.9118286, - 7.056332916666666, - 6.950114233333333, - 7.132557333333332, - 7.0247035, - 6.781677266666667, - 7.127288516666667, - 6.305518283333333, - 5.718499433333333, - 6.034711016666666, - 6.210332733333334, - 5.563457483333334, - 5.060624083333333, - 4.792476, - 5.290833383333334, - 5.162845733333333, - 5.6231322, - 5.5739786, - 5.295094683333334, - 5.066966483333333, - 5.82564305, - 6.06209565, - 6.101570483333333, - 6.1325887833333335, - 6.286788383333333, - 6.592759633333333, - 6.412645383333333, - 6.348808466666666, - 6.2316062, - 6.579083833333333, - 6.2820811333333335, - 6.045826733333333, - 6.244307516666666, - 6.933283749999999, - 6.8063366499999995, - 6.509300916666667, - 6.704676566666667, - 6.5142063666666665, - 5.913610816666666, - 5.522760416666667, - 5.632546699999999, - 4.957015033333334, - 5.243001116666666, - 4.744594183333334, - 4.933346650000001, - 5.1231727000000005, - 5.23936745, - 4.9394412999999995, - 4.461069083333333, - 4.945238649999999, - 5.159773633333334, - 4.78618315, - 4.740613666666666, - 4.397017449999999, - 4.528523150000001, - 4.66865055, - 5.192245400000001, - 4.505366783333333, - 4.460524033333333, - 4.152207416666667, - 3.8637438333333334, - 3.8068769499999995, - 4.665561933333334, - 5.775927883333334, - 5.030051733333334, - 4.188742283333333, - 3.35557555, - 3.68607405, - 3.443791066666666, - 3.8168530166666663, - 3.5107991833333334, - 3.4171661999999996, - 2.796238633333333, - 2.5799363666666664, - 2.5428399333333336, - 2.7765177333333337, - 3.1359864666666666, - 3.2328402, - 3.1400991166666667, - 3.0130198833333335, - 2.9415522666666662, - 2.940214416666666, - 3.00436515, - 2.72143465, - 2.6554340499999998, - 2.399095383333333, - 2.1090792333333335, - 2.0657064666666667, - 1.8706776666666667, - 1.7871859166666666, - 1.6862690833333331, - 1.5211519666666664, - 1.5159161833333332, - 1.2361899166666668, - 1.1015130166666667, - 0.9985976666666667, - 0.9712791, - 1.0128680666666667, - 0.9818828, - 0.8773653333333333, - 0.76579525, - 0.7321838333333334, - 0.7180125333333334, - 0.7138173000000001, - 0.7139329166666666, - 0.7167242333333332, - 0.7218443999999999, - 0.7297063333333332, - 0.7380307333333334, - 0.7508146333333332, - 0.7645730166666667, - 0.77441695, - 0.7747638, - 0.7732112333333332, - 0.7774560166666667, - 0.7899261000000001, - 0.8033541500000001, - 0.8080613999999999, - 0.8030733666666666, - 0.7955748, - 0.7909501333333333, - 0.7851197499999999, - 0.780908, - 0.7784635333333333, - 0.74171395, - 0.5618639666666667, - 0.8090524, - 0.7916438333333333, - 0.7784139833333333, - 0.7584122999999999, - 0.7322499, - 0.7075905166666666, - 0.6880843333333332, - 0.6734670833333333, - 0.6622687833333334, - 0.6530029333333334, - 0.6397565666666666, - 0.6229426, - 0.6086556833333333, - 0.598564, - 0.5985474833333332, - 0.6013057666666666, - 0.6059964999999999, - 0.6080610833333332, - 0.6042787666666667, - 0.5967802, - 0.5904708333333333, - 0.5895128666666667, - 0.5914618333333334, - 0.5931795666666667, - 0.5889513, - 0.5818491333333334, - 0.5731283333333334, - 0.5642588833333333, - 0.5541011333333333, - 0.5430845166666667, - 0.52656785, - 0.4910239833333333, - 0.3922708333333333, - 0.4802220833333333, - 0.44907165, - 0.42888828333333334, - 0.40576495, - 0.38381430000000005, - 0.36746280000000003, - 0.3623261166666667, - 0.36382913333333333, - 0.3624912833333333, - 0.35220140000000005, - 0.33347150000000003, - 0.3125614, - 0.2931212833333333, - 0.27521721666666665, - 0.26235073333333336, - 0.25313443333333335, - 0.24481003333333332, - 0.23503216666666668, - 0.22520475, - 0.21420465, - 0.2030393833333333, - 0.19274950000000002, - 0.18647316666666663, - 0.18146861666666667, - 0.17591901666666665, - 0.17127783333333332, - 0.16587688333333334, - 0.16075671666666666, - 0.15773416666666668, - 0.15446386666666667, - 0.15408398333333334, - 0.1431995, - 0.11697103333333335, - 0.10572318333333332, - 0.09406241666666666, - 0.08528380833333334, - 0.0765052, - 0.07292108333333334, - 0.06933696666666667, - 0.06646306666666667, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.1714845, - 0.22565399999999997, - 0.283767, - 0.33668250000000005, - 0.37562249999999997, - 0.41842350000000006, - 0.47572800000000004, - 0.5372729999999999, - 0.6006495, - 0.66396, - 0.728772, - 0.788898, - 0.8485455, - 0.9156345, - 0.9767175, - 1.0948740000000001, - 1.2259665, - 1.2691305, - 1.3522740000000002, - 1.392963, - 1.5123075, - 1.6366515, - 1.707684, - 1.7916195, - 2.014122, - 2.2090035, - 2.317689, - 2.3307239999999996, - 2.1927345, - 2.0913585, - 2.2288695, - 2.1290115, - 1.8641204999999998, - 2.1337305, - 2.470974, - 2.7145305, - 2.8199655000000003, - 3.0329970000000004, - 3.615546, - 3.913734, - 4.111437, - 4.2285375, - 4.282509, - 4.3899075, - 4.4355795, - 4.4731335, - 4.584838500000001, - 4.673756999999999, - 4.8152115, - 4.9019025, - 5.0176004999999995, - 5.111997, - 5.205189000000001, - 5.2983315, - 5.379989999999999, - 5.472324, - 5.572578, - 5.646366, - 5.7180089999999995, - 5.82516, - 5.911768499999999, - 5.9997135, - 6.072214499999999, - 6.143263500000001, - 6.233733, - 6.288315, - 6.4018185, - 6.4663005, - 6.586701000000001, - 6.676956, - 6.7642904999999995, - 6.8213805, - 6.8827275, - 6.9993165, - 7.0750515, - 7.161528, - 7.2552315, - 7.3490174999999995, - 7.450690499999999, - 7.3925445000000005, - 7.454337, - 6.7921095, - 6.3539685, - 6.2024325, - 5.7820455, - 5.9127915, - 6.1181505000000005, - 5.3230815, - 4.898289, - 4.202616, - 4.0620525, - 3.8994285, - 3.733851, - 3.6388770000000004, - 3.8510009999999997, - 4.111635, - 4.3022595, - 4.1190435, - 3.432099, - 3.3471569999999997, - 3.2871135, - 3.20463, - 3.1377555, - 3.0907139999999997, - 3.0282780000000002, - 2.9461245, - 2.8857014999999997, - 2.9211435000000003, - 2.8786064999999996, - 2.7844739999999994, - 2.6673075, - 2.610267, - 2.5649414999999998, - 2.489784, - 2.3845140000000002, - 2.2798545, - 2.2336875000000003, - 2.2293645, - 2.2076339999999997, - 2.2011990000000003, - 2.2035089999999995, - 2.1893024999999997, - 2.1633645, - 2.1359084999999998, - 2.1248205000000002, - 2.1133695, - 2.0906985000000002, - 2.0676645000000002, - 2.0363805, - 2.0026875, - 1.966107, - 1.917828, - 1.8565304999999999, - 1.7883194999999998, - 1.7203395, - 1.6632825000000002, - 1.618188, - 1.572945, - 1.5373545, - 1.5015, - 1.4682359999999999, - 1.4471655, - 1.444938, - 1.463385, - 1.4921445, - 1.5193695, - 1.545555, - 1.5732585000000001, - 1.578225, - 1.60182, - 1.630101, - 1.6623584999999999, - 1.7005065000000001, - 1.7358164999999999, - 1.779096, - 1.8378194999999997, - 1.869978, - 1.8982919999999999, - 1.9151715, - 1.896642, - 1.9124984999999999, - 1.934625, - 1.948584, - 1.9684994999999998, - 2.0061855, - 2.041578, - 2.050983, - 2.0627145000000002, - 2.0753865, - 2.0806335, - 2.086293, - 2.0707994999999997, - 2.067153, - 2.0679285, - 2.1374759999999995, - 2.1277245000000002, - 2.1613680000000004, - 2.3190584999999997, - 2.2903155, - 2.2471844999999995, - 2.843313, - 2.7316575, - 3.0831239999999998, - 3.9784305, - 4.085895, - 4.335078, - 4.2721635000000004, - 3.3165, - 2.5924305000000003, - 2.177274, - 2.0465445, - 1.958451, - 1.9009485, - 1.8654404999999998, - 1.7586855, - 1.654224, - 1.5585735, - 1.4957084999999999, - 1.4623455000000003, - 1.4411759999999998, - 1.4263095, - 1.4322659999999998, - 1.4283555000000001, - 1.4464725, - 1.4406809999999997, - 1.4231744999999996, - 1.3904055000000002, - 1.3447829999999998, - 1.2888975, - 1.2288209999999997, - 1.1822415000000002, - 1.1339624999999998, - 1.08504, - 1.0359855, - 0.9905609999999999, - 0.95106, - 0.9328274999999999, - 0.922416, - 0.933966, - 0.9586829999999998, - 0.969243, - 0.971553, - 0.96954, - 0.9633855, - 0.9544424999999999, - 0.9438659999999999, - 0.9305505, - 0.916047, - 0.9027315, - 0.8983095000000001, - 0.8999264999999999, - 0.8991674999999999, - 0.8965274999999999, - 0.8963625000000001, - 0.8974844999999999, - 0.8979465000000001, - 0.8987715, - 0.8980125, - 0.8915609999999999, - 0.8869904999999999, - 0.886743, - 0.8908679999999999, - 0.897699, - 0.8501624999999999, - 0.600039, - 0.9187695, - 0.9079785, - 0.9121035000000001, - 0.9198915000000001, - 0.926937, - 0.9359790000000001, - 0.9352035000000001, - 0.9295275, - 0.925551, - 0.928389, - 0.9376289999999999, - 0.9470670000000001, - 0.949839, - 0.9429915, - 0.9087704999999999, - 0.8706719999999999, - 0.842424, - 0.8158755000000001, - 0.784608, - 0.7506179999999999, - 0.724317, - 0.715143, - 0.7153574999999999, - 0.6945839999999999, - 0.6669959999999999, - 0.6331545000000001, - 0.5876804999999999, - 0.549351, - 0.5106915, - 0.46510199999999996, - 0.4257495, - 0.375606, - 0.325512, - 0.337788, - 0.29797350000000006, - 0.27073200000000003, - 0.247368, - 0.229449, - 0.21778350000000002, - 0.2074545, - 0.2011845, - 0.1944855, - 0.1872255, - 0.1808565, - 0.173712, - 0.1646205, - 0.15572700000000003, - 0.149721, - 0.137973, - 0.12002099999999999, - 0.10294350000000001, - 0.089364, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.09594948333333335, - 0.1185811, - 0.14831703333333332, - 0.17894306666666668, - 0.21759648333333334, - 0.28329905, - 0.38615505, - 0.38969896666666665, - 0.33042489999999997, - 0.34657856666666664, - 0.40801194999999996, - 0.4603630166666666, - 0.46183003333333333, - 0.68710775, - 0.7384203666666667, - 0.6916241833333334, - 0.7304754, - 0.7744529333333333, - 0.7737276666666666, - 0.5909110166666667, - 1.01120305, - 0.9434565500000001, - 0.8754463166666666, - 0.8872154166666667, - 0.8892428666666666, - 0.9186491333333332, - 0.9434071, - 0.9941592833333334, - 0.9952801499999999, - 1.0133623666666667, - 0.9987911, - 0.9892637333333334, - 1.0004064666666668, - 1.057850883333333, - 1.1278556, - 1.1596519500000002, - 1.2471454833333333, - 1.366798, - 1.48582415, - 1.6013723166666665, - 1.74335975, - 1.8872757333333332, - 1.874319833333333, - 1.9044019166666664, - 1.9529782999999998, - 2.0536255333333333, - 2.0837900333333335, - 2.0702077666666665, - 2.1079710833333336, - 2.2365081166666663, - 2.353935383333334, - 2.6080259666666668, - 2.6573111333333332, - 2.764765983333333, - 2.97258785, - 3.0861085666666668, - 3.475576766666667, - 3.564619733333333, - 3.696206183333333, - 3.71443675, - 3.6862997, - 4.00411485, - 4.2008599166666665, - 4.097888533333333, - 4.1088994, - 4.354204366666667, - 4.11765205, - 4.261996600000001, - 4.697782966666667, - 4.980785316666666, - 4.967763483333332, - 4.878357883333333, - 5.2692931000000005, - 5.395967516666667, - 5.492592816666667, - 4.998290616666667, - 5.3708139500000005, - 5.4835104999999995, - 5.736529666666667, - 6.036345016666667, - 5.986845566666666, - 6.95232385, - 7.208244083333333, - 7.004477116666666, - 6.851709583333333, - 6.775853283333333, - 6.5934981666666665, - 6.908890266666666, - 6.224353916666667, - 6.740315216666666, - 6.2689083666666665, - 5.762556849999999, - 7.233381166666666, - 5.6498438166666665, - 3.625739933333334, - 3.3520671499999994, - 3.38984695, - 3.4092643166666665, - 3.9045884833333333, - 5.2704799, - 6.069591900000001, - 5.5652019, - 5.251458133333333, - 6.086141166666667, - 6.18970595, - 6.713760566666666, - 5.162349233333333, - 6.0768940166666665, - 4.831396866666666, - 6.763309466666667, - 7.311330850000001, - 6.527432966666667, - 6.173321516666666, - 6.080141233333333, - 6.1045036, - 5.2284309166666665, - 4.962472333333333, - 4.531317783333334, - 4.348814316666666, - 4.0805150999999995, - 3.800545683333333, - 3.38223165, - 3.0427738833333335, - 2.896797483333333, - 2.655926533333333, - 2.5026974666666666, - 2.4195884999999997, - 2.357841933333333, - 2.3102875166666665, - 2.26891435, - 2.2317774, - 2.2036898000000003, - 2.1596133666666666, - 2.1004217166666668, - 2.0649001333333334, - 2.018186366666667, - 1.9847911333333332, - 1.9698901999999998, - 1.9626869833333334, - 1.948643183333333, - 1.9363960666666666, - 1.95767605, - 1.9362971666666666, - 1.9215775499999999, - 1.9575112166666668, - 1.981181283333333, - 2.006615066666667, - 2.018614933333333, - 2.0230984, - 2.0342576166666664, - 2.02225775, - 1.9736154333333331, - 1.9182973666666667, - 1.8774022166666668, - 1.84136965, - 1.8348917, - 1.81615015, - 1.8021228333333332, - 1.7802329666666665, - 1.7724693166666667, - 1.7661397166666666, - 1.7679858499999999, - 1.7623650333333334, - 1.7604694499999998, - 1.7708704333333332, - 1.77846925, - 1.7872548666666666, - 1.78509555, - 1.7944910500000002, - 1.8086996833333333, - 1.82356765, - 1.8158369666666667, - 1.8063095999999998, - 1.7726341499999998, - 1.7636012833333332, - 1.7971778333333333, - 1.7844856666666666, - 1.7808922999999999, - 1.7555079666666666, - 1.7281126666666669, - 1.7464091666666666, - 1.7866779499999998, - 1.8018261333333332, - 1.7550134666666664, - 1.7559695, - 1.7370466333333332, - 1.6291302499999998, - 1.5291753166666666, - 1.4675441333333334, - 1.41847325, - 1.3853912, - 1.3157491166666668, - 1.2557827499999998, - 1.1965910999999998, - 1.1043174, - 1.0751254166666664, - 1.1067734166666665, - 1.08794945, - 1.1070701166666665, - 1.12286115, - 1.1003778833333333, - 1.06421345, - 1.0783067, - 1.1271468166666667, - 1.1487399833333334, - 1.15233335, - 1.1643826666666666, - 1.1839648666666667, - 1.2399257833333333, - 1.2893263333333331, - 1.4311654166666665, - 1.6019162666666666, - 1.7146622666666664, - 1.8264192666666665, - 1.8407597666666666, - 1.7572552, - 1.5393949833333336, - 1.25603, - 0.9737034666666667, - 0.8436994166666667, - 0.7832220666666668, - 0.7389808, - 0.6943439333333334, - 0.6320863833333334, - 0.5725156166666667, - 0.5404885, - 0.5012087166666667, - 0.4632311166666667, - 0.4366105333333334, - 0.4131217833333333, - 0.38903963333333336, - 0.36663878333333333, - 0.3452763833333333, - 0.3216557666666667, - 0.2926780666666666, - 0.2654476, - 0.24708516666666666, - 0.2341952, - 0.2240085, - 0.21542068333333336, - 0.20816801666666665, - 0.19977799999999998, - 0.19081106666666667, - 0.1767343, - 0.1608114, - 0.1401577833333333, - 0.11549871666666667, - 0.09332863333333336, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.2887924, - 0.39711013333333334, - 0.48303319999999994, - 0.5316592666666666, - 0.5866908666666666, - 0.6475846, - 0.7035054, - 0.7506494666666668, - 0.7355001333333333, - 0.6871869333333332, - 0.6582385333333333, - 0.5419179999999999, - 0.23226233333333335, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.1199926, - 0.13912686666666665, - 0.15350226666666664, - 0.16094519999999998, - 0.16552293333333334, - 0.1781528666666667, - 0.19521233333333332, - 0.21176133333333333, - 0.22949593333333332, - 0.2705308666666667, - 0.2978161333333333, - 0.2860918666666667, - 0.32498613333333337, - 0.3228619333333333, - 0.3307165333333333, - 0.35273246666666663, - 0.37567053333333333, - 0.38220779999999993, - 0.3810386666666667, - 0.3908857333333334, - 0.40972359999999997, - 0.4388860666666667, - 0.4728074, - 0.5007019333333333, - 0.5143527999999999, - 0.5189964, - 0.5375543333333334, - 0.5658440666666666, - 0.5916967333333333, - 0.605891, - 0.6109133333333333, - 0.6316448666666667, - 0.6530021333333332, - 0.6876479999999999, - 0.7408024, - 0.7859539999999999, - 0.8531874, - 1.0618200666666668, - 0.9606159333333334, - 1.6870923333333332, - 1.4584032666666669, - 1.2409115333333331, - 1.0919705333333334, - 1.0910813333333333, - 1.0735772666666668, - 1.0488278666666666, - 1.0303687333333333, - 1.0142478666666666, - 1.0155981333333333, - 1.0378281333333335, - 1.0394089333333334, - 1.0140008666666664, - 1.0111027333333333, - 1.0867176666666667, - 1.2239344, - 1.2629604, - 1.2977874, - 1.3241176, - 1.4456086666666665, - 1.4978409333333333, - 1.4816377333333333, - 1.5038348, - 1.5072598666666666, - 1.5629830666666669, - 1.6171419333333332, - 1.6637755333333333, - 1.753831733333333, - 1.8182658, - 1.9584465333333332, - 2.1325156666666665, - 2.2896735333333336, - 2.5516088, - 2.9474674666666663, - 3.345878466666667, - 3.757446333333333, - 3.658646333333333, - 4.0132066, - 3.910833333333333, - 4.00387, - 4.1120066, - 4.0609269999999995, - 3.179548666666667, - 2.6743183999999998, - 3.783727133333333, - 6.873153733333333, - 5.769854133333334, - 3.1666882000000007, - 3.2132229999999997, - 3.7114714, - 5.670856533333334, - 6.030422666666667, - 5.012288666666667, - 4.407846733333333, - 4.0575019333333335, - 3.9624234, - 3.9083468666666668, - 3.7925203333333335, - 3.7444047333333335, - 3.5853532, - 3.3842128666666667, - 3.0964084666666665, - 2.826552733333333, - 2.587012133333333, - 2.4339709333333337, - 2.3448698, - 2.293016266666667, - 2.2589631999999997, - 2.203075333333333, - 2.1483730666666663, - 2.111438333333333, - 2.1374721333333335, - 2.1821462, - 2.1897702666666663, - 2.1404525999999997, - 2.098791933333333, - 2.1044564666666665, - 2.0899658, - 2.062367666666667, - 2.0211186666666663, - 1.9760823333333333, - 1.9331866666666668, - 1.9098369333333334, - 1.9288230000000002, - 1.9173292666666666, - 1.8593336666666669, - 1.8359674666666665, - 1.8404958, - 1.889303, - 1.8884961333333334, - 1.8963672, - 1.8947040666666666, - 1.8831444666666668, - 1.8921188, - 1.9068235333333334, - 1.8756850666666667, - 1.8631868666666667, - 1.9175597999999998, - 1.9613775999999998, - 1.950591933333333, - 1.9083878666666667, - 1.8518742666666668, - 1.8270096, - 1.7845914666666667, - 1.7645186, - 1.765934733333333, - 1.7730154, - 1.7673508666666666, - 1.7344504666666667, - 1.7338576666666665, - 1.7363770666666665, - 1.7830271333333334, - 1.8587902666666667, - 1.9064942, - 1.9100180666666666, - 1.9542804666666667, - 2.0402364666666664, - 2.1321534, - 2.157281533333333, - 2.1270157999999997, - 2.1440752666666665, - 2.183891666666667, - 2.275199333333333, - 2.370985933333333, - 2.3194782000000003, - 2.3073258, - 2.3330138, - 2.4050060666666666, - 2.4668054666666666, - 2.5150692666666665, - 2.5411524666666665, - 2.5600561999999996, - 2.5431284666666665, - 2.5108538, - 2.489694133333333, - 2.475697466666667, - 2.490089333333333, - 2.5192353333333335, - 2.5377603333333334, - 2.504843466666667, - 2.465916266666667, - 2.4361774666666665, - 2.4081841333333336, - 2.438499266666667, - 2.407509, - 2.339649866666667, - 2.318852466666667, - 2.3668034000000002, - 2.3936440666666665, - 2.399176866666666, - 2.465932733333333, - 2.487899266666667, - 2.4954904, - 2.4642037333333335, - 2.4538956000000005, - 2.458868533333333, - 2.463199266666667, - 2.466015066666666, - 2.4551964666666666, - 2.4138157333333328, - 2.3432725333333333, - 2.2928680666666663, - 2.201889733333333, - 2.1264394666666666, - 2.0309492666666666, - 1.9969785333333334, - 1.9423092, - 1.8931562, - 1.8813166666666667, - 1.8450570666666666, - 1.8453040666666667, - 1.902147, - 1.9534736, - 2.0234898666666665, - 2.1011796, - 2.172249733333333, - 2.188979866666666, - 2.2008358666666665, - 2.225700533333333, - 2.1895561999999997, - 2.1509748, - 2.138410733333333, - 2.1201656666666664, - 2.088121533333333, - 2.1041765333333333, - 2.104571733333333, - 2.0935555333333333, - 2.112475733333333, - 2.173353, - 2.2071590666666667, - 2.1986128666666667, - 2.1692692666666664, - 2.165020866666666, - 2.2085916666666665, - 2.2568225333333336, - 2.300541533333333, - 2.3293911333333335, - 2.3347757333333328, - 2.3580596, - 2.3789393333333333, - 2.370212, - 2.3704096, - 2.3420539999999996, - 2.304180666666667, - 2.279842933333333, - 2.2599018, - 2.250894533333333, - 2.2382316666666666, - 2.2638043999999997, - 2.2880762666666663, - 2.3332607999999997, - 2.3673468, - 2.4019432666666667, - 2.4206494, - 2.465537533333333, - 2.5506866666666665, - 2.584789133333333, - 2.6823706, - 2.7462612666666666, - 2.798938133333333, - 2.867917, - 2.9249245999999998, - 2.9622874666666665, - 3.0836467999999995, - 3.1337878, - 3.0277424666666666, - 2.903238, - 3.0192127333333336, - 3.1004921999999997, - 3.1242865333333336, - 3.1124305333333333, - 3.1602168, - 3.2085299999999997, - 3.299179, - 3.3841634666666662, - 3.399214, - 3.3763912, - 3.3621146, - 3.3362948666666665, - 3.372570933333334, - 3.4764756, - 3.5898486, - 3.642047933333333, - 3.6567361999999997, - 3.6323490666666665, - 3.5169012666666664, - 3.4169650666666667, - 3.2568431999999996, - 3.103439733333333, - 3.0312663333333334, - 3.0272813999999997, - 2.9671616, - 2.829697866666667, - 2.710462733333333, - 2.7073999333333334, - 2.7364636000000004, - 2.8126713333333333, - 2.9044894666666665, - 2.9365335999999997, - 2.9689564666666666, - 3.044258533333333, - 3.1699979999999996, - 3.3618840666666667, - 3.317671066666667, - 3.1857401333333333, - 3.107276466666667, - 2.9685448, - 2.764950933333333, - 2.6175083999999997, - 2.522742733333333, - 2.4472430666666667, - 2.4152648000000005, - 2.3891980666666663, - 2.4015480666666664, - 2.462326533333333, - 2.5682730666666664, - 2.6299736666666664, - 2.6052901333333334, - 2.6045820666666666, - 2.6201924666666665, - 2.5955748, - 2.569063466666666, - 2.5351256666666666, - 2.5123028666666665, - 2.5076921999999997, - 2.4722888666666667, - 2.451458533333333, - 2.4904022, - 2.5148387333333333, - 2.5078074666666668, - 2.515019866666667, - 2.5347469333333335, - 2.5467017333333333, - 2.6001196, - 2.6531422666666664, - 2.6340738666666668, - 2.4999363999999993, - 2.330280333333333, - 2.2011157999999997, - 2.184056333333333, - 2.3617316666666666, - 2.589515066666666, - 2.748434866666667, - 3.012296733333333, - 3.2827452666666668, - 3.3520040666666664, - 3.4287551999999994, - 3.3097999999999996, - 3.046728533333333, - 3.022324933333333, - 3.0066486666666665, - 2.981322933333333, - 3.0054795333333337, - 3.108742, - 3.201745733333333, - 3.148476066666667, - 3.0750841333333336, - 3.0175001999999997, - 2.9836447333333336, - 2.9030568666666667, - 2.827326666666666, - 2.778371266666667, - 2.7990039999999996, - 2.8744213333333333, - 2.8158164666666665, - 2.7076963333333333, - 2.6100489999999996, - 2.5709406666666665, - 2.521507733333333, - 2.4785791333333336, - 2.2861990666666667, - 2.1199680666666665, - 2.0035652, - 2.0497047999999998, - 2.0826875333333335, - 2.032316, - 1.9581501333333333, - 1.8963507333333331, - 1.8441184666666668, - 1.7998231333333334, - 1.7840974666666667, - 1.7822531999999998, - 1.8069532, - 1.8775458, - 1.9853366, - 2.083692, - 2.1135789999999997, - 2.0531463333333333, - 1.9416176, - 1.8140009333333333, - 1.8807732666666666, - 1.9388676666666667, - 1.9282302, - 1.9781242, - 1.9972255333333333, - 1.9382254666666665, - 1.8507874666666666, - 1.7468663333333332, - 1.6113292, - 1.6763725333333332, - 1.7647326666666667, - 1.7242575999999998, - 1.7087789333333332, - 1.7668568666666669, - 1.8503428666666666, - 1.9208860666666665, - 1.8647182666666668, - 1.7457136666666666, - 1.6934978666666665, - 1.7022416666666667, - 1.6544224666666667, - 1.5734888, - 1.5488546666666667, - 1.5490028666666666, - 1.5055143999999998, - 1.4644136, - 1.4157216666666665, - 1.3284318666666666, - 1.3061359999999997, - 1.2617254, - 1.1869996666666665, - 1.1635840666666666, - 1.1747155333333332, - 1.2180722666666666, - 1.2640801333333334, - 1.2883025999999997, - 1.2832802666666665, - 1.2361362, - 1.2063644666666669, - 1.1806270666666667, - 1.2846964, - 1.4134657333333331, - 1.5091370666666666, - 1.5562811333333333, - 1.5737193333333332, - 1.6123007333333332, - 1.5891321333333333, - 1.5284524666666668, - 1.4880103333333332, - 1.2086368666666667, - 1.0010580666666666, - 1.079175933333333, - 1.1429678, - 1.2338473333333335, - 1.426161533333333, - 1.6108845999999999, - 1.6280593333333333, - 1.5026821333333333, - 1.4128894, - 1.5221951333333334, - 1.6071466666666665, - 1.5652225333333334, - 1.444703, - 1.3598996666666665, - 1.3386247333333334, - 1.2263385333333332, - 1.1405471999999999, - 1.1797213999999998, - 1.1800507333333332, - 1.1386370666666668, - 1.0030834666666666, - 0.9055184666666668, - 0.9729988666666666, - 0.9881152666666666, - 0.9205854666666667, - 0.8741494666666668, - 0.9207501333333333, - 0.958113, - 0.9251467333333333, - 0.8191508, - 0.7362740666666667, - 0.7468127333333334, - 0.7226890666666667, - 0.7400614000000001, - 0.7453801333333334, - 0.7743944, - 0.8030958, - 0.7764527333333333, - 0.7519832666666667, - 0.7590968666666666, - 0.7788404, - 0.7651401333333333, - 0.7120680666666668, - 0.6669494, - 0.6251405333333333, - 0.5809934, - 0.5161641333333333, - 0.4931272666666667, - 0.49215573333333335, - 0.4661878, - 0.36266186666666667, - 0.40659493333333335, - 0.41249, - 0.3940802666666666, - 0.37846986666666665, - 0.3645555333333333, - 0.35467553333333335, - 0.3409258666666667, - 0.3171150666666666, - 0.29705866666666664, - 0.30211393333333336, - 0.3023938666666667, - 0.31123646666666666, - 0.31586359999999997, - 0.2975197333333333, - 0.26351606666666666, - 0.2321141333333333, - 0.22840913333333335, - 0.2213614, - 0.20456539999999998, - 0.186238, - 0.15236606666666666, - 0.1263158, - 0.11498673333333331, - 0.10291666666666666, - 0.0888706, - 0.08197106666666666, - 0.07515386666666667, - 0.06346253333333333, - 0.053747199999999995, - 0.049647000000000004, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.366177, - 0.4690553, - 0.48769314999999996, - 0.4969215999999999, - 0.52858785, - 0.6316964500000001, - 0.73746995, - 0.8200160499999999, - 0.8776897499999999, - 0.8958999000000001, - 0.9868355, - 1.0998799, - 1.21751385, - 1.3393261, - 1.41698655, - 1.4852705, - 1.59777205, - 1.73430705, - 1.89739235, - 2.00872595, - 2.0007477000000002, - 2.2752159499999998, - 2.45508025, - 2.5031965, - 2.49080965, - 2.5564615999999996, - 2.71130545, - 2.9031453500000004, - 3.0449279, - 3.2106780999999995, - 3.3696015500000005, - 3.5138022499999995, - 3.5958712999999998, - 3.6925972999999996, - 3.79286005, - 3.89238255, - 3.9620154, - 4.05668515, - 4.11156235, - 4.1178462499999995, - 4.3114627500000005, - 4.4290638, - 4.47665365, - 4.60417405, - 4.6866708, - 4.778823699999999, - 4.8560564500000005, - 4.943965250000001, - 5.036101700000001, - 5.11955255, - 5.16692855, - 5.2914715, - 5.358274949999999, - 5.451332600000001, - 5.53511245, - 5.6040050500000005, - 5.63529295, - 5.75481865, - 5.830965699999999, - 5.9198615, - 6.0136265, - 6.09191205, - 6.1767776, - 6.24917405, - 6.32405445, - 6.41117365, - 6.50108935, - 6.48964015, - 6.581348899999999, - 6.7289054, - 6.7737152, - 6.5969764, - 6.24190315, - 6.069030100000002, - 5.091636899999999, - 5.2124292500000005, - 6.415072299999999, - 6.899343849999999, - 5.846790600000001, - 6.6433653999999995, - 6.81840985, - 6.34517625, - 5.2781141, - 6.941242, - 6.24187025, - 5.864309850000001, - 4.3039615499999995, - 6.8371464, - 4.49080065, - 4.360960800000001, - 3.21691265, - 7.3605525, - 6.80890175, - 5.845211399999999, - 4.2544470500000005, - 5.467651, - 5.12159235, - 3.9172713999999997, - 3.36519295, - 3.2380509, - 5.1644445999999995, - 6.635699700000001, - 6.76323655, - 7.36491175, - 7.30579045, - 7.158842600000002, - 7.13576325, - 7.1164016000000005, - 7.04584755, - 6.968943799999999, - 6.8736983, - 6.71655145, - 6.620105100000002, - 6.574752449999999, - 6.5450273, - 6.5168649, - 6.4472485, - 6.45572025, - 5.63456915, - 4.0860484, - 3.6140649999999996, - 3.6327192999999998, - 3.82993835, - 4.5940573, - 5.42210095, - 5.658174900000001, - 5.6339934, - 5.5470222499999995, - 5.4599195, - 5.3792816, - 5.292639449999999, - 5.195239, - 5.113383799999999, - 5.0242906, - 4.938191300000001, - 4.85845815, - 4.75502055, - 4.666536, - 4.584763049999999, - 4.5042896500000005, - 4.401592300000001, - 4.2969538499999995, - 4.01184245, - 3.21069455, - 1.9953192000000002, - 0.9378145, - 0.31388245000000004, - 0.2438548, - 0.2352021, - 0.2275364, - 0.22029839999999998, - 0.20957299999999998, - 0.1941429, - 0.17807125, - 0.1632498, - 0.14987594999999998, - 0.1366666, - 0.12400009999999999, - 0.11052754999999999, - 0.09957185, - 0.09078755, - 0.08325344999999999, - 0.0761635, - 0.0693861, - 0.0634641, - 0.0573118, - 0.0509292, - 0.0449743, - 0.03939775, - 0.03423245, - 0.029067149999999996, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.29852793333333333, - 0.36787659999999994, - 0.42761176666666667, - 0.49375593333333334, - 0.5689548666666667, - 0.6479827666666667, - 0.7002900666666666, - 0.7513813, - 0.8078133666666666, - 0.8684852333333333, - 0.9351059666666667, - 1.0046189666666667, - 1.0934247, - 1.1434970666666666, - 1.2813727333333333, - 1.3423568333333333, - 1.3754207, - 1.4746616000000001, - 1.6478853666666666, - 1.8359155666666667, - 1.9959926666666665, - 2.112225633333333, - 2.2100039666666667, - 2.3531876, - 2.5497302666666664, - 2.6828402666666666, - 2.8454809666666665, - 2.9667589666666663, - 3.067462433333333, - 3.2028237999999996, - 3.284234533333333, - 3.4089799666666667, - 3.4608106999999997, - 3.592310233333333, - 3.7506454, - 3.9059239666666663, - 4.0317047, - 4.123320533333334, - 4.2212632, - 4.313667833333333, - 4.388998233333334, - 4.460483233333334, - 4.5426992, - 4.650879833333333, - 4.717993566666666, - 4.8269137, - 4.927715766666666, - 5.014779566666666, - 5.1048671, - 5.177486, - 5.2536052, - 5.348672033333334, - 5.4258758333333335, - 5.509061366666668, - 5.596568866666665, - 5.690666133333334, - 5.760754300000001, - 5.845862533333333, - 5.915671333333334, - 5.981930533333333, - 6.092839100000001, - 6.154792766666667, - 6.243516333333333, - 6.326981233333333, - 6.396954366666666, - 6.4471582000000005, - 6.538642566666667, - 6.632690533333333, - 6.7100257999999995, - 6.767821833333333, - 6.830745066666666, - 6.8947036, - 6.9771825, - 13.5766284, - 13.593817666666666, - 13.595083033333331, - 13.613669133333334, - 13.624778066666666, - 13.633586333333334, - 13.603644799999998, - 13.606997199999999, - 13.6001445, - 13.590695333333331, - 13.5980739, - 13.633668499999999, - 13.616314899999999, - 13.5608031, - 13.604203533333333, - 13.625977699999998, - 13.634030033333332, - 13.590810366666664, - 13.639272266666667, - 13.608788433333334, - 13.5993064, - 13.601738533333334, - 13.559636333333332, - 13.563514600000001, - 13.5647471, - 13.5668177, - 13.565355133333334, - 13.566406866666664, - 13.561969866666665, - 13.588969833333332, - 13.600916866666665, - 13.610908333333333, - 13.608854166666667, - 13.589758633333334, - 13.553523133333334, - 13.585601, - 13.564139066666666, - 13.583645433333333, - 13.602938166666666, - 13.594721499999999, - 13.600292399999999, - 13.593751933333333, - 13.596562033333331, - 13.569972899999998, - 7.230535199999999, - 7.162090366666666, - 7.0816985, - 7.011183066666666, - 6.925663999999999, - 6.8594541, - 6.787739033333334, - 6.7115212333333325, - 6.6371604, - 6.567565233333333, - 6.498742433333334, - 6.434471666666667, - 6.367752333333333, - 6.285667833333333, - 6.222859633333333, - 6.163666766666667, - 6.080037533333334, - 5.9843791, - 5.922918433333333, - 5.8177943999999995, - 5.7610501, - 5.6615134000000005, - 5.5758135666666675, - 5.5278118, - 5.456655466666667, - 5.383379233333333, - 5.280062866666667, - 5.233359333333333, - 5.149993033333333, - 5.048977333333333, - 4.978231833333334, - 4.897987866666667, - 4.8136684333333335, - 4.743514533333332, - 4.6641086666666665, - 4.590454466666667, - 4.494845333333333, - 4.402259933333333, - 4.129581633333333, - 3.2142614, - 1.8590865666666667, - 0.7427373666666667, - 0.27713173333333335, - 0.25913723333333333, - 0.24993456666666666, - 0.2406826, - 0.22349333333333332, - 0.20577820000000002, - 0.1912347, - 0.1755573, - 0.16065226666666665, - 0.14739056666666664, - 0.13460543333333333, - 0.1228556, - 0.11110576666666666, - 0.09999683333333334, - 0.09079416666666668, - 0.08377713333333332, - 0.0768094, - 0.07054830000000001, - 0.06415573333333333, - 0.05796036666666667, - 0.05183073333333333, - 0.0461448, - 0.040327400000000006, - 0.034871533333333336, - 0.024830766666666663, - 0.020788166666666663, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.2658843333333333, - 0.3887466666666667, - 0.4621784166666666, - 0.5259735833333333, - 0.5913775833333333, - 0.6618871666666667, - 0.7341205000000001, - 0.7981947500000001, - 0.8499729166666666, - 0.9155575, - 1.0419986666666667, - 1.1774361666666666, - 1.2144393333333334, - 1.3318513333333333, - 1.3739436666666667, - 1.5176715833333332, - 1.6619905, - 1.7774160833333332, - 1.81244925, - 1.9487896666666666, - 2.1172903333333335, - 2.2407600833333334, - 2.3887234999999998, - 2.4748453333333336, - 2.5508380833333333, - 2.752943666666667, - 2.9341508333333333, - 3.098678666666667, - 3.1327596666666664, - 3.2881598333333333, - 3.4800214166666663, - 3.681650916666667, - 3.7697920000000003, - 3.820880666666667, - 3.9854741666666667, - 4.081725083333334, - 4.17349425, - 4.254838833333333, - 4.3295510833333335, - 4.440642666666666, - 4.527831583333334, - 4.61571, - 4.7069702499999995, - 4.814023333333334, - 4.897830416666667, - 4.984083583333333, - 5.069187583333333, - 5.164043083333333, - 5.232533416666667, - 5.310906583333334, - 5.392563083333333, - 5.4864664166666675, - 5.559323583333334, - 5.649631666666666, - 5.7197965, - 5.764515500000001, - 5.848749416666666, - 5.956557666666667, - 6.045568833333333, - 6.140572083333334, - 6.218616916666666, - 6.297531833333333, - 6.360555416666667, - 6.446857833333333, - 6.5018864999999995, - 6.572921416666666, - 6.654233166666667, - 6.731293, - 6.789637833333333, - 6.855468666666666, - 7.224745166666667, - 7.172901333333334, - 7.0853348333333335, - 7.0163519999999995, - 6.950767416666666, - 6.879913083333333, - 6.802360750000001, - 6.743244333333333, - 6.679120833333333, - 6.6131915, - 6.538807583333335, - 6.479412083333333, - 6.399085333333333, - 6.306593833333333, - 6.244489583333333, - 6.186867083333333, - 6.096476916666666, - 6.030941583333333, - 5.959036583333333, - 5.875886166666667, - 5.790814999999999, - 5.680905416666667, - 5.579696666666666, - 5.5149165, - 5.465453083333333, - 5.375079333333333, - 5.284098166666667, - 5.18981725, - 5.140583666666667, - 5.052130666666668, - 4.990141333333333, - 4.920780916666667, - 4.810411666666666, - 4.731660916666667, - 4.5214126666666665, - 3.7588420833333336, - 2.5770719166666667, - 1.1438476666666666, - 0.3775833333333333, - 0.22986616666666668, - 0.22001616666666665, - 0.2136793333333333, - 0.20355024999999996, - 0.19003933333333334, - 0.17393458333333334, - 0.15906108333333335, - 0.14497558333333332, - 0.1323511666666667, - 0.12138483333333333, - 0.11117366666666667, - 0.10015808333333333, - 0.09106325, - 0.083528, - 0.07748666666666666, - 0.07177366666666667, - 0.06645466666666666, - 0.061168499999999994, - 0.05529133333333334, - 0.050021583333333335, - 0.04475183333333334, - 0.039153749999999994, - 0.034327250000000004, - 0.026053249999999997, - 0.022474416666666667, - 0.016695750000000002, - 0.010917083333333334, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.2108384, - 0.3571756, - 0.42384160000000004, - 0.4853908, - 0.5450212000000001, - 0.6095552, - 0.6712191999999999, - 0.7321288, - 0.788758, - 0.85444, - 0.9538732, - 1.0726747999999997, - 1.163662, - 1.2845136, - 1.40835, - 1.4893004, - 1.6069867999999998, - 1.66952, - 1.8270419999999998, - 1.9909763999999999, - 2.1430044, - 2.3103664, - 2.47517, - 2.6105028000000003, - 2.7241548, - 2.8743624, - 3.0323436, - 3.1611491999999997, - 3.2578436, - 3.3361536, - 3.451298, - 3.5484188, - 3.6445556, - 3.74371, - 3.8407488, - 3.9417071999999997, - 4.0311856, - 4.13239, - 4.227198399999999, - 4.3106252000000005, - 4.3987752, - 4.488843999999999, - 4.5994947999999996, - 4.695648, - 4.758476399999999, - 4.854760799999999, - 4.9635748, - 5.0440988, - 5.1153732, - 5.206524399999999, - 5.298462799999999, - 5.362718, - 5.462266, - 5.4858492000000005, - 5.5830684, - 5.6710216, - 5.763763600000001, - 5.8689368, - 5.9508548, - 6.0214732, - 6.1063596, - 6.202725999999999, - 6.2765588, - 6.362970399999999, - 6.441116399999999, - 6.510455599999999, - 6.596162, - 6.6589903999999995, - 6.7374643999999995, - 6.8116416, - 13.978015199999998, - 13.9911352, - 13.99535, - 13.9921192, - 14.003172799999998, - 14.0198844, - 14.0524876, - 14.041696400000001, - 14.0494208, - 14.040089200000002, - 14.033988400000002, - 14.056932, - 14.0450748, - 14.0597692, - 14.0479776, - 14.041745599999999, - 14.0597036, - 14.0594412, - 14.055128, - 14.026559200000001, - 14.0059444, - 14.0025496, - 14.003074400000001, - 13.9980232, - 14.0050752, - 14.014702, - 13.991282799999999, - 13.9739972, - 13.9789992, - 14.013455599999999, - 14.0199828, - 14.001893599999997, - 13.9960552, - 14.006666000000001, - 13.9778512, - 13.9971704, - 14.0202944, - 14.028166400000002, - 14.0261328, - 14.001565599999998, - 13.9796716, - 14.009536, - 14.005518, - 13.993709999999998, - 13.988937599999998, - 13.9933984, - 7.0410775999999995, - 6.353524, - 4.931348799999999, - 2.6689032, - 1.5322684, - 1.3372232, - 1.3803224, - 1.6488068, - 2.1539596, - 2.5252556, - 2.3899064, - 2.3286032, - 2.8798564, - 4.1155472, - 6.170745999999999, - 7.2121788, - 7.205422, - 7.0823892, - 7.0129024, - 6.94171, - 6.8516904, - 6.758603999999999, - 6.680047999999999, - 6.605903599999999, - 6.5294304, - 6.4616328, - 6.362314400000001, - 6.2999616000000005, - 6.221635200000001, - 6.138438, - 6.0297716, - 5.893504, - 5.8307248, - 5.7946447999999995, - 5.7007548, - 5.604290000000001, - 5.5338848, - 5.470318399999999, - 5.379085200000001, - 5.287425600000001, - 5.1922236, - 5.1040244, - 5.022663999999999, - 4.9199836, - 4.814712, - 4.4063191999999995, - 3.8770748000000004, - 2.8585528, - 1.6613692, - 0.4743864, - 0.3480408, - 0.3374136, - 0.32718, - 0.3148308, - 0.299874, - 0.282736, - 0.264696, - 0.246082, - 0.23224039999999999, - 0.2193992, - 0.2080832, - 0.1998996, - 0.19279839999999998, - 0.1865992, - 0.18107240000000002, - 0.17484039999999998, - 0.1695432, - 0.164246, - 0.159572, - 0.15447160000000001, - 0.1502404, - 0.14577959999999998, - 0.1397608, - 0.1355132, - 0.1322332, - 0.122426, - 0.11525919999999999, - 0.10666559999999999, - 0.097662, - 0.0793924, - 0.056891599999999994, - 0.0506924, - 0.044362, - 0.038638399999999996, - 0.0347516, - 0.0310452, - 0.0278144, - 0.023140400000000002, - 0.0188764, - 0.014973199999999999, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.2785985833333333, - 0.3891041666666667, - 0.4747234666666666, - 0.5576559000000001, - 0.6236479666666667, - 0.6847578000000001, - 0.7537316333333333, - 0.8272272666666666, - 0.8975773, - 1.0076241499999998, - 1.0449945333333333, - 1.1279597333333333, - 1.1651826666666667, - 1.2549305666666666, - 1.3607668999999998, - 1.5124110333333332, - 1.6036334333333333, - 1.6323697999999998, - 1.7313742833333334, - 1.89350375, - 2.0667575, - 2.1522948833333335, - 2.1699397333333326, - 2.3546454333333333, - 2.494296966666667, - 2.590811183333333, - 2.750171866666667, - 2.880452133333333, - 3.0782481166666664, - 3.202826983333333, - 3.3547332499999993, - 3.440614683333333, - 3.526872933333333, - 3.7034197333333334, - 3.7847302166666665, - 3.986884166666666, - 4.203291616666667, - 4.318679433333333, - 4.40841095, - 4.510757633333333, - 4.5932641, - 4.67627845, - 4.7811317833333336, - 4.880611383333333, - 4.9713095166666665, - 5.074475366666666, - 5.160749999999999, - 5.206819933333334, - 5.295535683333333, - 5.425439133333333, - 5.5036367833333335, - 5.5648285333333325, - 5.676743083333333, - 5.7378693, - 5.828321683333333, - 5.912744999999999, - 5.985306783333333, - 6.069599033333333, - 6.153809366666666, - 6.264544316666669, - 6.3409234166666675, - 6.413714566666667, - 6.4759057, - 6.561443083333333, - 6.644391900000001, - 6.715643016666666, - 6.806455833333333, - 5.63942185, - 6.7031916833333325, - 6.072056533333334, - 6.336794816666667, - 6.284040483333334, - 6.179809716666667, - 6.5727312, - 6.571142016666666, - 6.383487316666666, - 6.697473899999999, - 6.618063883333334, - 7.141478616666666, - 6.373870299999999, - 5.451947366666667, - 4.89538915, - 4.103058383333333, - 3.9735645166666664, - 3.8877650000000004, - 3.74596725, - 3.8041117, - 3.88565155, - 3.96389835, - 4.1408875, - 4.374628516666666, - 4.332048233333333, - 4.498126083333333, - 5.0719687166666665, - 5.6740398333333335, - 5.814739899999999, - 5.136748416666666, - 5.425996166666667, - 5.244583516666667, - 5.971462866666666, - 6.241099766666666, - 6.746050483333333, - 6.152138266666666, - 6.1675386, - 5.921018583333333, - 5.9672032, - 6.609904983333333, - 6.892927066666666, - 5.956209983333334, - 6.29115085, - 5.606229216666666, - 5.0328617, - 5.057895433333333, - 5.185062866666668, - 5.0736889666666665, - 4.8799232833333335, - 4.2697588, - 3.925774333333333, - 3.182921233333333, - 3.1949957499999995, - 3.2022535666666663, - 2.764359833333333, - 2.4784051333333332, - 2.5757548999999997, - 2.7996986833333333, - 2.4984583333333332, - 2.495181666666667, - 2.0020105666666668, - 2.0822233666666663, - 2.0802245999999998, - 2.2324585333333338, - 2.3509100333333333, - 2.2758252166666666, - 2.5758531999999996, - 3.104314, - 2.9966427333333328, - 2.823192383333333, - 3.524906933333333, - 3.5400779, - 3.4164165, - 2.7196497166666664, - 2.6127484666666665, - 2.7575607499999997, - 2.9277672, - 2.9520473, - 2.6508069499999998, - 2.7284967166666667, - 2.8407389333333333, - 3.238673716666667, - 3.5011019500000002, - 4.071225566666667, - 3.233119766666667, - 3.7544701999999996, - 3.4173012, - 3.1396528499999996, - 3.7274868499999996, - 5.245156933333333, - 5.138370366666667, - 7.193708683333333, - 6.54112775, - 6.921810883333333, - 6.6111664999999995, - 6.6989647833333335, - 5.817459533333333, - 5.3759287, - 5.6807242333333345, - 5.75639885, - 6.181316983333334, - 5.770570433333333, - 5.848227433333333, - 5.760740433333334, - 5.660048466666667, - 6.21211765, - 6.024249966666666, - 6.1444708666666665, - 5.4749659500000005, - 5.641174866666666, - 5.33734595, - 5.035302816666667, - 5.658590349999999, - 5.450259883333333, - 6.112818266666666, - 5.96833365, - 6.3124328, - 6.051036716666667, - 5.983389933333333, - 5.923328633333333, - 6.2601535833333335, - 6.150942283333333, - 6.001919483333334, - 5.672843849999999, - 5.333577783333334, - 5.665717099999998, - 5.512598466666666, - 5.465987883333332, - 5.443837616666666, - 5.446213200000001, - 5.275597166666667, - 5.12413325, - 5.09926335, - 5.034794933333333, - 4.79659765, - 4.944408083333333, - 4.80554295, - 4.7633231, - 4.45490685, - 3.946384566666666, - 3.6651318833333333, - 3.0646663333333333, - 2.182866183333333, - 1.76305965, - 0.6180448666666666, - 0.38702348333333336, - 0.35643579999999997, - 0.33153313333333334, - 0.3056802333333334, - 0.28082671666666664, - 0.25492466666666663, - 0.22777748333333334, - 0.19946708333333335, - 0.17112391666666668, - 0.14564783333333334, - 0.12970685, - 0.11250435000000002, - 0.10003663333333333, - 0.09810340000000001, - 0.08958406666666667, - 0.08073706666666666, - 0.0754944, - 0.06967831666666666, - 0.0635018, - 0.054277983333333335, - 0.04657781666666666, - 0.0421707, - 0.042154316666666664, - 0.038107633333333335, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.1473491, - 0.2505409333333333, - 0.33263613333333336, - 0.3979391333333333, - 0.4740277666666667, - 0.5360247, - 0.5780215666666667, - 0.6436518999999999, - 0.7000350666666666, - 0.7500025000000001, - 0.8185624666666667, - 0.8742745999999999, - 0.9228836000000001, - 1.0012963, - 1.0589069666666666, - 1.1658140333333336, - 1.1801185, - 1.278564, - 1.4140963666666668, - 1.5063389, - 1.5968793000000001, - 1.6885817333333333, - 1.8479112333333332, - 1.9902357666666664, - 2.0299904, - 2.132249333333333, - 2.2868815999999996, - 2.4641162333333337, - 2.6086011666666664, - 2.766850466666667, - 2.8890276333333333, - 3.089110133333334, - 3.2813366333333334, - 3.482892133333333, - 3.6570825666666664, - 3.7753481, - 3.8808476333333335, - 3.9592766999999998, - 4.070553666666667, - 4.124236333333333, - 4.259686866666667, - 4.343369633333334, - 4.424401, - 4.498558366666667, - 4.5871184, - 4.664090833333334, - 4.761390666666667, - 4.8328638999999995, - 4.935270133333334, - 5.013044533333333, - 5.1091005, - 5.198184266666667, - 5.290934166666665, - 5.362194633333333, - 5.430918266666667, - 5.514551933333334, - 5.595566933333334, - 5.6805262999999995, - 5.7588899, - 5.761754066666667, - 5.905829833333334, - 5.955469933333333, - 6.063735433333334, - 6.144586766666668, - 6.231608333333333, - 6.311313999999999, - 6.3789247, - 6.449645066666666, - 6.536322933333334, - 6.624408333333333, - 6.699629533333334, - 6.767420266666667, - 6.830955666666667, - 6.873590833333334, - 6.574768233333333, - 6.184750566666667, - 2.177650466666667, - 5.815469466666667, - 1.2311334, - 1.5995961666666667, - 4.3807511, - 5.389166899999999, - 2.151496533333334, - 6.262263100000001, - 5.585321399999999, - 7.3736907, - 7.224361233333332, - 7.184933933333334, - 7.130580233333333, - 7.016373633333333, - 6.792674033333333, - 6.837289566666667, - 6.753966866666666, - 6.3048328, - 4.4485091, - 4.560669866666667, - 3.0219904333333334, - 2.1141805333333337, - 2.4355727666666667, - 1.0544388666666666, - 1.5125909666666666, - 3.5307319, - 4.635711033333333, - 5.6445359999999996, - 5.902458299999999, - 5.7974988666666665, - 5.7331123999999996, - 5.623619399999999, - 5.528201733333333, - 5.444960866666666, - 5.374305966666667, - 5.286286033333332, - 5.1256471999999995, - 5.0723737, - 5.030475033333333, - 4.9518823, - 4.542830199999999, - 4.185840466666666, - 3.7222219, - 3.3233498666666668, - 2.9884387666666665, - 2.012739933333333, - 1.4661423666666666, - 0.35643326666666664, - 0.23009896666666665, - 0.22589273333333332, - 0.22556539999999997, - 0.21682559999999998, - 0.2096406333333333, - 0.21150643333333333, - 0.2043214666666667, - 0.1880039, - 0.17157176666666668, - 0.17376490000000003, - 0.17846213333333336, - 0.18386313333333337, - 0.17854396666666666, - 0.1641413, - 0.15528693333333332, - 0.14885483333333335, - 0.14880573333333336, - 0.1498859333333333, - 0.15734913333333334, - 0.15419036666666666, - 0.14104793333333332, - 0.1337975, - 0.12932939999999998, - 0.12720173333333334, - 0.12142429999999999, - 0.10700526666666665, - 0.09414106666666668, - 0.08224250000000001, - 0.07224246666666666, - 0.04008196666666666, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null - ], + "y": { + "bdata": "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", + "dtype": "f8" + }, "yaxis": "y" }, { @@ -55460,6006 +31191,10 @@ "2013-01-21T15:46:00-07:00" ], "xaxis": "x", - "y": [ - 7.650163783333333, - 8.0061094, - 8.108983183333333, - 7.735639916666667, - 7.649399416666667, - 8.5986265, - 8.102303283333333, - 8.055743383333333, - 8.5016184, - 8.12908935, - 7.9226438833333335, - 8.003916, - 8.18970695, - 8.341267566666668, - 7.7585543, - 7.490677016666667, - 7.516815033333333, - 7.485658783333333, - 7.5896957333333335, - 7.451810633333333, - 8.221694033333334, - 8.684950083333332, - 8.585931366666667, - 8.312254866666667, - 8.086151883333335, - 8.336897383333334, - 8.972667666666666, - 9.262844516666666, - 9.244682500000001, - 9.347323649999998, - 9.399898783333333, - 10.690714683333335, - 10.776672699999999, - 10.781624466666667, - 11.001346649999999, - 11.349449200000002, - 11.193900583333331, - 10.681226566666666, - 10.149775716666666, - 9.721614066666666, - 9.689111866666668, - 9.8075887, - 9.347074399999999, - 9.644712133333334, - 10.512002433333333, - 11.080658, - 11.162860649999999, - 11.126303983333333, - 11.10712835, - 11.533944049999999, - 11.459800483333332, - 12.072407133333332, - 12.463397299999999, - 12.880060216666665, - 12.926105, - 11.902800816666666, - 11.237153766666667, - 10.150656399999999, - 9.463889566666666, - 9.637915916666666, - 10.144092816666667, - 10.06027835, - 9.974370183333333, - 9.8278278, - 9.967175166666667, - 11.028099483333333, - 11.008441966666664, - 11.419455216666666, - 11.542717649999998, - 11.806291216666665, - 11.662041933333333, - 12.0753649, - 12.2996899, - 12.35088585, - 12.196317616666668, - 12.920355633333331, - 13.856854349999999, - 13.998062783333333, - 14.479214983333332, - 14.500467700000002, - 14.48935115, - 14.405071416666665, - 14.431126350000001, - 14.4456327, - 14.409208966666666, - 14.260174083333332, - 14.301782216666664, - 14.28805685, - 14.376756616666666, - 14.360389199999998, - 14.311104166666667, - 14.32188838333333, - 14.313015083333333, - 14.339651600000002, - 14.268399333333331, - 14.205820966666666, - 14.237691733333332, - 14.23003145, - 14.226907516666667, - 14.200337466666666, - 14.171358, - 14.127423533333335, - 14.093841249999999, - 14.04628435, - 13.953098083333332, - 13.946767133333333, - 14.006587133333333, - 14.046018483333334, - 14.06682255, - 14.060258966666666, - 14.039072716666665, - 14.020229416666666, - 14.0016686, - 14.035566600000001, - 14.01687285, - 13.993426733333333, - 13.990468966666667, - 13.95785045, - 13.918219700000002, - 13.898811433333332, - 13.88786105, - 13.878007366666667, - 13.875564716666666, - 13.832245066666667, - 13.84718345, - 13.831530549999998, - 13.81099235, - 13.820148133333333, - 13.827260066666666, - 13.814996966666664, - 13.811407766666667, - 13.839523166666666, - 13.837728566666666, - 13.816077049999999, - 13.758616616666668, - 13.694758766666666, - 13.714167033333332, - 13.689175566666668, - 13.654679366666668, - 13.616261633333332, - 13.620365950000002, - 13.600791516666668, - 13.574204850000001, - 13.5379639, - 13.488595783333334, - 13.467143666666667, - 13.428028033333336, - 13.409965716666663, - 13.372628066666666, - 13.348201566666667, - 13.322694983333331, - 13.300860683333333, - 13.291621816666666, - 13.246972833333334, - 13.253137616666667, - 13.258288783333334, - 13.245560416666665, - 13.204068600000001, - 13.1869202, - 13.12854585, - 13.123943033333333, - 13.107592233333333, - 13.06154745, - 13.013624983333331, - 12.965619433333334, - 12.9454468, - 12.9354768, - 12.908026066666666, - 12.828465466666666, - 12.849867733333333, - 12.83383265, - 12.787438916666666, - 12.740181116666667, - 12.70631635, - 12.686708683333334, - 12.640431266666669, - 12.6077629, - 12.592458950000001, - 12.570392016666666, - 12.549189149999998, - 12.50512175, - 12.467850566666668, - 12.417668233333334, - 12.386728000000002, - 12.327472966666665, - 12.332075783333334, - 12.285549116666667, - 12.284967533333335, - 12.259876366666667, - 12.2419636, - 12.199474783333335, - 12.173469700000002, - 12.14211405, - 12.117936799999999, - 12.091017799999998, - 12.03035035, - 11.880052599999999, - 11.960460649999998, - 11.871528249999997, - 11.850857116666667, - 11.812705249999999, - 11.799594700000002, - 11.784905566666666, - 11.750226583333333, - 11.247040683333333, - 11.708452283333335, - 11.6576219, - 11.612640583333333, - 11.6036842, - 11.5807532, - 11.499730333333332, - 11.444579616666667, - 11.4108644, - 11.353935700000001, - 11.279409950000002, - 11.218426783333335, - 11.187237299999998, - 11.143036966666665, - 11.09566285, - 11.050930783333335, - 11.031190183333335, - 10.997973466666664, - 10.930144233333332, - 10.741678000000002, - 10.66416125, - 10.6729847, - 10.681841383333333, - 10.666470966666665, - 10.648624666666668, - 10.584467716666667, - 10.525162833333333, - 10.492045816666664, - 10.433123116666668, - 10.37592855, - 10.2991097, - 10.2568369, - 10.21012745, - 10.148745483333332, - 10.07313965, - 9.9848553, - 9.956706666666667, - 9.883526866666665, - 9.821064816666667, - 9.763056033333331, - 9.694429199999998, - 9.653784833333333, - 9.579840666666666, - 9.501925116666666, - 9.472064966666666, - 9.4219491, - 9.36756275, - 9.29817155, - 9.2273347, - 9.167381766666667, - 9.100748933333334, - 9.055701149999999, - 8.992524583333333, - 8.94543295, - 8.8906478, - 8.811768483333333, - 8.720792233333333, - 8.71034035, - 8.641314716666667, - 8.573186383333333, - 8.505290683333333, - 8.462502766666667, - 8.39798025, - 8.3196659, - 8.26308615, - 8.177859266666667, - 8.097152116666667, - 8.042283883333333, - 7.981682899999999, - 7.888546483333333, - 7.832598166666667, - 7.756410750000001, - 7.666597666666666, - 7.610267166666667, - 7.355045, - 7.4263752, - 7.5116328, - 7.5593411999999995, - 7.652683, - 7.761844600000001, - 7.822932600000001, - 7.891391, - 7.9804334, - 8.0514482, - 8.1201058, - 8.1804468, - 8.2387792, - 8.320916, - 8.4032686, - 8.4596256, - 8.533728, - 8.5866654, - 8.595729, - 8.688705599999999, - 8.7457764, - 8.8250912, - 8.878344, - 8.9465866, - 9.028291800000002, - 9.082939, - 9.1499864, - 9.193843600000001, - 9.259313999999998, - 9.3265606, - 9.394952600000002, - 9.4321864, - 9.5293794, - 9.582964199999997, - 9.6640552, - 9.6766048, - 9.777333599999999, - 9.8254404, - 9.8803532, - 9.937175, - 10.0082396, - 10.052677800000001, - 10.077445, - 10.090227, - 10.2083194, - 10.263348399999998, - 10.310874199999999, - 10.343875, - 10.4045314, - 10.4727574, - 10.5321356, - 10.596676400000002, - 10.632615399999999, - 10.698953083333333, - 10.697924916666667, - 10.833394166666666, - 10.910075499999998, - 10.9665915, - 11.029641333333332, - 11.088794083333335, - 11.138411416666667, - 11.22054866666667, - 11.287081, - 11.334376666666666, - 11.396332000000001, - 11.429681083333332, - 11.349484083333333, - 11.246750333333333, - 11.33359725, - 11.155077666666667, - 11.344459333333335, - 11.577737083333332, - 11.720884416666664, - 11.409781083333332, - 10.941898916666666, - 11.386265916666666, - 11.52196733333333, - 11.824430750000001, - 11.787168000000001, - 11.383430166666667, - 11.666839333333334, - 11.967760499999999, - 11.884611666666666, - 11.747616749999997, - 11.786803166666665, - 11.996084833333333, - 12.038637666666666, - 11.987461499999998, - 11.98064575, - 12.02979875, - 11.862340249999999, - 11.547256916666667, - 12.122002083333335, - 12.20491875, - 12.382028749999998, - 12.4121275, - 12.435244666666666, - 12.458345249999999, - 12.494198416666666, - 12.521958916666668, - 12.564976083333333, - 12.609668166666665, - 12.648837999999998, - 12.652917500000001, - 12.666565583333332, - 12.679052833333335, - 12.702551416666667, - 12.710445083333331, - 12.724739916666667, - 12.735834166666667, - 12.75594975, - 12.794986916666666, - 12.795335166666666, - 12.835201499999998, - 12.887322916666667, - 12.871784333333332, - 12.908814916666667, - 12.915066833333332, - 12.927836, - 12.973489916666667, - 13.048131499999998, - 13.13086575, - 13.160699166666667, - 13.196088, - 13.289982833333335, - 13.377957416666668, - 13.403628416666665, - 13.4952845, - 13.539097666666667, - 13.577372000000002, - 13.580738416666666, - 13.657983583333333, - 13.702261083333331, - 13.7245325, - 13.758296166666668, - 13.804381249999999, - 13.857779583333333, - 13.863616916666667, - 13.865308416666666, - 13.9028365, - 13.977527833333335, - 14.035204666666665, - 13.992966916666667, - 14.022816916666667, - 14.234801666666666, - 14.268681416666666, - 14.020130416666666, - 14.472341333333333, - 12.125982083333334, - 10.029981416666665, - 9.51613025, - 15.255107833333334, - 6.621774750000001, - 15.089639333333334, - 15.38663025, - 15.317262166666666, - 15.267064416666667, - 15.161975833333331, - 14.958249583333332, - 14.858766166666667, - 14.836312333333332, - 10.686698, - 14.98962525, - 15.062641666666664, - 15.193898749999999, - 14.017875083333333, - 12.24133575, - 15.970861083333332, - 16.168318833333334, - 15.397989833333334, - 15.267396083333333, - 8.094109416666667, - 10.461612416666666, - 9.6161775, - 7.586559916666666, - 14.430733750000002, - 7.665065416666666, - 8.81757391666667, - 9.128096833333332, - 7.772724416666667, - 9.333481416666666, - 9.437641333333335, - 8.653117, - 9.421787666666667, - 10.020877166666665, - 10.534993666666665, - 9.926700416666668, - 10.339509333333334, - 8.907405833333334, - 7.193501749999999, - 8.4000885, - 9.848510000000001, - 8.138685416666666, - 8.184040833333333, - 8.1985015, - 9.892372916666666, - 11.379649166666667, - 11.051498166666667, - 9.122292666666667, - 8.175351166666667, - 8.711191833333334, - 10.684409499999997, - 10.768603083333335, - 10.045785333333333, - 10.256741916666666, - 10.433669499999999, - 10.961782333333332, - 10.484497416666667, - 9.72269225, - 9.206419916666666, - 11.423876916666666, - 12.003248833333334, - 11.709375583333333, - 9.49573275, - 8.09765825, - 7.661367333333334, - 8.240274916666667, - 9.286335000000001, - 10.286426083333332, - 9.129008916666667, - 9.448039083333333, - 8.907787250000002, - 10.83012725, - 11.723653833333334, - 11.97586975, - 11.979484916666669, - 12.186743416666665, - 11.999981916666666, - 12.129696749999999, - 12.031987749999999, - 11.975256166666668, - 11.932703333333333, - 11.888409249999999, - 11.824049333333335, - 11.799025083333332, - 11.751712833333334, - 11.70781675, - 11.647204666666665, - 11.589362000000001, - 11.54175125, - 11.476960166666666, - 11.40573475, - 11.38235225, - 11.331806250000001, - 11.286948333333333, - 11.2734495, - 11.224694500000002, - 11.181926083333332, - 11.114730416666667, - 11.082028083333334, - 10.998414916666666, - 10.939112916666666, - 10.863393416666668, - 10.825003, - 10.783909499999998, - 10.757425916666667, - 10.697178666666668, - 10.577728916666668, - 10.545540666666664, - 10.518227916666666, - 10.484082833333334, - 10.42959, - 10.400171166666667, - 10.332876, - 10.274569, - 10.220374666666666, - 10.17223325, - 10.129265833333333, - 10.060179666666667, - 9.984294333333333, - 9.948822583333333, - 9.907297916666666, - 9.887165750000001, - 9.842374166666668, - 9.77662125, - 9.73831375, - 9.628830583333333, - 9.574404083333333, - 9.52568225, - 9.4866285, - 9.441024333333333, - 9.36459175, - 9.284709833333332, - 9.216917166666667, - 9.1471345, - 9.08439975, - 8.99017325, - 8.926111833333334, - 8.85097275, - 8.777176916666665, - 8.74679625, - 8.681491083333333, - 8.62699825, - 8.569619916666666, - 8.515176833333335, - 8.451049083333334, - 8.391713916666667, - 8.305132333333333, - 8.19705875, - 8.107591666666666, - 8.053579749999999, - 7.990115333333333, - 7.866950916666667, - 7.800584416666666, - 7.728281083333333, - 7.64035625, - 7.278846633333333, - 7.381874733333333, - 7.372729933333333, - 7.516611433333334, - 7.605359066666667, - 7.671625733333333, - 7.750648733333334, - 7.831427799999999, - 7.9055802, - 7.971730899999999, - 8.042884733333333, - 8.056485966666667, - 8.169371233333333, - 8.256926066666667, - 8.300165066666667, - 8.369314333333334, - 8.450225933333334, - 8.519938466666666, - 8.587745833333335, - 8.640759166666667, - 8.722648200000002, - 8.777019999999998, - 8.823025633333334, - 8.887320866666668, - 8.945271066666667, - 9.006219833333333, - 9.049144066666665, - 9.102604699999999, - 9.147450666666666, - 9.211199200000001, - 9.276190233333333, - 9.312073633333334, - 9.375407999999998, - 9.431834066666665, - 9.492186433333334, - 9.542466266666668, - 9.598130266666667, - 9.641435533333334, - 9.699965566666666, - 9.733248, - 9.793517533333333, - 9.870519400000001, - 9.9198715, - 9.958753466666664, - 9.939801200000002, - 9.9770265, - 10.094600133333334, - 10.182767933333334, - 10.220225166666665, - 10.246466766666666, - 10.3055435, - 10.354034133333332, - 10.403286833333334, - 10.443958, - 10.495645999999999, - 10.510191533333334, - 10.574205133333331, - 10.620906566666667, - 10.688067833333331, - 10.742141433333332, - 10.760712666666667, - 10.8182487, - 10.871311733333332, - 10.902689, - 10.941173366666668, - 11.020461433333333, - 11.082553299999999, - 11.122296733333336, - 11.169263233333334, - 11.200657066666668, - 11.238130866666667, - 11.282927133333335, - 11.324807666666667, - 11.355588533333332, - 11.4059015, - 11.446191633333333, - 11.482621733333335, - 11.534773599999998, - 11.569447633333333, - 11.602995133333332, - 11.612471266666665, - 11.666213533333332, - 11.698717333333333, - 11.710529366666668, - 11.760693233333335, - 11.7922693, - 11.838871333333334, - 11.892050333333335, - 11.938105666666667, - 11.981858233333334, - 12.006360333333333, - 12.042525366666666, - 12.086625833333335, - 12.118218466666665, - 12.146895366666667, - 12.175737933333332, - 12.202095499999999, - 12.238293666666667, - 12.2954321, - 12.332342633333331, - 12.399139433333332, - 12.434674933333332, - 12.44985, - 12.46573743333333, - 12.502167533333333, - 12.533776733333333, - 12.573387633333333, - 12.605245333333333, - 12.606289033333333, - 12.576469033333334, - 12.639339533333333, - 12.701331999999999, - 12.698996099999999, - 12.691441700000002, - 12.715397099999999, - 12.775003966666667, - 12.825996166666668, - 12.880384533333334, - 12.900297666666667, - 12.971335533333335, - 13.010847033333334, - 13.032218033333333, - 13.064622433333332, - 13.058658433333331, - 13.1109594, - 13.1276089, - 13.143264400000001, - 13.192633066666668, - 13.2202994, - 13.2749197, - 13.299471499999997, - 13.336763066666668, - 13.352832733333335, - 13.394431633333333, - 13.425842033333334, - 13.4282442, - 13.440652633333334, - 13.497509433333333, - 13.490932466666667, - 13.473322099999999, - 13.495190099999999, - 13.515600233333332, - 13.584037133333334, - 13.616739733333334, - 13.655803933333331, - 13.680537966666664, - 13.691538233333333, - 13.672552833333333, - 13.691405699999999, - 13.706613900000002, - 13.729128000000001, - 13.750167666666666, - 13.781992233333334, - 13.774023666666666, - 13.764033966666666, - 13.766187633333333, - 13.7963721, - 13.826506866666668, - 13.861661333333334, - 13.887058033333332, - 13.886892366666668, - 13.895606433333333, - 13.919644666666667, - 13.901901766666665, - 13.881143733333333, - 13.883761266666665, - 13.9106324, - 13.902796366666665, - 13.939309299999998, - 13.922676366666666, - 13.9133659, - 13.971713700000002, - 13.966312966666665, - 13.9586923, - 13.994211233333333, - 14.016460266666666, - 14.025638200000001, - 14.017073233333335, - 14.014074666666666, - 14.011341166666666, - 14.007928433333332, - 14.033722733333335, - 14.053735266666665, - 14.063592433333334, - 14.062101433333334, - 14.060593866666668, - 14.059086299999999, - 14.108189900000001, - 14.097239333333334, - 14.088939433333334, - 14.1248394, - 14.1207143, - 14.140196699999999, - 14.159894466666666, - 14.190559366666665, - 14.1825411, - 14.168409733333334, - 14.123812266666667, - 14.1244418, - 14.161335766666665, - 14.189731033333333, - 14.205121466666666, - 14.245792633333332, - 14.214597599999998, - 14.216751266666668, - 14.257836599999997, - 14.252750633333333, - 14.240275933333331, - 14.281924533333333, - 14.282355266666665, - 14.262574666666666, - 14.249586400000002, - 14.2587312, - 14.277534366666666, - 14.286795133333332, - 14.300678000000001, - 14.296254699999999, - 14.305598299999998, - 14.293587466666665, - 14.298921933333332, - 14.318420900000001, - 14.3118605, - 14.288915666666666, - 14.251690366666667, - 14.211251133333333, - 14.189366566666669, - 14.187096933333331, - 14.177007833333333, - 14.183617933333332, - 14.196307999999998, - 14.195479666666667, - 14.189747599999999, - 14.210555333333332, - 14.212245133333333, - 14.190012666666666, - 14.167100966666665, - 14.147833933333331, - 14.130687433333332, - 14.099575233333333, - 14.093611233333332, - 14.080341333333333, - 14.067651266666667, - 14.068728099999998, - 14.090480133333331, - 14.076315633333333, - 14.064371066666666, - 14.031569066666668, - 14.0291669, - 13.992422033333334, - 13.976965333333332, - 13.940700900000001, - 13.912603833333332, - 13.871269999999997, - 13.869298566666666, - 13.844050966666664, - 13.8899075, - 13.9003445, - 13.876024633333332, - 13.807786533333335, - 13.776574933333332, - 13.7930919, - 13.809244399999999, - 13.799536333333332, - 13.758219066666669, - 13.731231966666666, - 13.707210299999998, - 13.748742933333332, - 13.781395833333333, - 13.798393233333336, - 13.803512333333332, - 13.766336733333333, - 13.7363345, - 13.748511, - 13.7483619, - 13.716785833333333, - 13.697800433333333, - 13.685458266666666, - 13.645747966666667, - 13.603950266666667, - 13.589951433333333, - 13.559419066666669, - 13.525838433333332, - 13.517737333333335, - 13.494229233333334, - 13.446268733333335, - 13.420524133333332, - 13.396403066666668, - 13.386678433333332, - 13.367461099999998, - 13.339098966666667, - 13.2940045, - 13.2999188, - 13.272848866666667, - 13.250135966666667, - 13.202225166666667, - 13.15438063333333, - 13.135527766666664, - 13.116161333333334, - 13.055129733333334, - 12.955232733333334, - 12.994876766666664, - 12.935385866666666, - 12.8860172, - 12.8720018, - 12.870792433333332, - 12.860024099999999, - 12.8356214, - 12.816089299999998, - 12.744388766666667, - 12.770796033333335, - 12.766604666666666, - 12.7463602, - 12.7583379, - 12.689900999999999, - 12.649246400000001, - 12.597740633333334, - 12.5748455, - 12.533031233333334, - 12.489543733333335, - 12.461496366666665, - 12.430549833333334, - 12.373444533333334, - 12.341520566666667, - 12.319702266666665, - 12.318575733333333, - 12.294438099999999, - 12.231352233333332, - 12.223880666666668, - 12.185810466666666, - 12.170767933333334, - 12.145536900000002, - 12.1009063, - 12.081606133333333, - 12.0386819, - 11.9968842, - 11.926011999999998, - 11.9077224, - 11.565123733333333, - 11.839086700000001, - 11.805671733333334, - 11.7405813, - 11.714936099999997, - 11.6669259, - 11.6289054, - 11.582535299999998, - 11.507869333333334, - 11.475663733333334, - 11.4309503, - 11.400682999999999, - 11.360293466666667, - 11.323151, - 11.267371033333333, - 11.2156702, - 11.162445400000001, - 11.130023949999998, - 11.080191899999999, - 11.01950305, - 10.97958445, - 10.94519355, - 10.8946002, - 10.8676899, - 10.8278706, - 10.772643249999998, - 10.734462400000002, - 10.69121725, - 10.648832699999998, - 10.5876308, - 10.507545349999997, - 10.4876026, - 10.44098125, - 10.387392349999999, - 10.32470095, - 10.2536187, - 10.1847045, - 10.122906799999999, - 10.06622305, - 10.00806635, - 9.9481057, - 9.9068962, - 9.830369, - 9.797186250000001, - 9.739310900000001, - 9.679697799999998, - 9.63496315, - 9.5774188, - 9.51447915, - 9.431861549999999, - 9.393399350000001, - 9.327331749999999, - 9.2652527, - 9.2116307, - 9.145248650000003, - 9.0708895, - 9.00477225, - 8.938406750000002, - 8.868516099999999, - 8.81845235, - 8.75377495, - 8.70885825, - 8.6518104, - 8.586024149999998, - 8.52101575, - 8.46186605, - 8.39689075, - 8.329946, - 8.2574901, - 8.189850250000001, - 8.1323721, - 8.06426885, - 7.99330245, - 7.92819475, - 7.8757147000000005, - 7.8150093, - 7.7422720499999995, - 7.67590655, - 7.602424549999999, - 7.54251355, - 7.28765505, - 7.364544749999999, - 7.43630625, - 7.4594331, - 7.4823768, - 7.624884150000001, - 7.70360535, - 7.7785470000000005, - 7.83733815, - 7.91432775, - 7.9907013000000005, - 8.064294299999998, - 8.122169699999999, - 8.20160685, - 8.2541376, - 8.3320929, - 8.392815449999999, - 8.4665916, - 8.527647149999998, - 8.5881699, - 8.6498748, - 8.7144435, - 8.78828625, - 8.85082365, - 8.91441, - 8.9759484, - 9.03424005, - 9.091599299999997, - 9.1499076, - 9.19910835, - 9.254069999999999, - 9.3058848, - 9.36271125, - 9.405934649999999, - 9.4543029, - 9.5109129, - 9.55754955, - 9.582174899999998, - 9.6284952, - 9.68275755, - 9.7081821, - 9.7644924, - 9.81702315, - 9.8598636, - 9.9078822, - 9.93387285, - 9.9993573, - 10.056267, - 10.1170395, - 10.15611705, - 10.197026099999999, - 10.2401496, - 10.2860037, - 10.32927705, - 10.37080215, - 10.409563350000003, - 10.4503392, - 10.4903325, - 10.5350544, - 10.572417, - 10.619486550000001, - 10.65501765, - 10.7108451, - 10.7531361, - 10.77459795, - 10.80796455, - 10.85678235, - 10.895260500000001, - 10.943645400000001, - 10.9813077, - 11.020535099999998, - 11.041946999999999, - 11.059945650000001, - 11.148140699999999, - 11.177111700000001, - 11.19697515, - 11.2243977, - 11.29970565, - 11.330441549999998, - 11.36563965, - 11.4107112, - 11.478410099999998, - 11.5070148, - 11.532156299999999, - 11.56700475, - 11.6082468, - 11.655799199999999, - 11.6655894, - 11.688666299999998, - 11.726711550000001, - 11.757647249999998, - 11.794177349999998, - 11.77023465, - 11.86850295, - 11.894210549999999, - 11.9130417, - 11.89021455, - 11.88185625, - 11.8840707, - 11.934287099999999, - 12.060144450000001, - 12.122748450000001, - 12.170733750000002, - 12.216321450000002, - 12.263723999999998, - 12.3333543, - 12.34452645, - 12.40003755, - 12.416754150000001, - 12.461908950000002, - 12.4887654, - 12.49950465, - 12.5281926, - 12.518485650000002, - 12.5548326, - 12.60816255, - 12.624696, - 12.648672, - 12.6675198, - 12.685585049999998, - 12.70070325, - 12.70546515, - 12.7541664, - 12.76410645, - 12.7836702, - 12.81562155, - 12.8417454, - 12.84415965, - 12.871082699999999, - 12.919184549999999, - 12.953849849999997, - 12.97472895, - 13.0133736, - 13.032970650000001, - 13.065821099999999, - 13.08698325, - 13.07529495, - 13.128791400000003, - 13.156413749999999, - 13.15727955, - 13.182804, - 13.1050152, - 13.1339529, - 13.2140394, - 13.2515685, - 13.280106599999998, - 13.300619399999999, - 13.3107093, - 13.33107225, - 13.311292049999999, - 13.37156505, - 13.391311949999999, - 13.3998201, - 13.38045615, - 13.410009900000002, - 13.41185805, - 13.43197125, - 13.46360625, - 13.518867599999998, - 13.536516599999999, - 13.5463734, - 13.5599598, - 13.57312995, - 13.61748555, - 13.6162701, - 13.6089774, - 13.571215200000003, - 13.627059299999999, - 13.631288399999999, - 13.64122845, - 13.658377949999998, - 13.6484712, - 13.668101549999998, - 13.6750446, - 13.686266700000001, - 13.69560735, - 13.66943355, - 13.6032165, - 13.694691599999999, - 13.68951345, - 13.67299665, - 13.683935700000001, - 13.667418900000001, - 13.639646699999998, - 13.6309887, - 13.624528499999998, - 13.60513125, - 13.55358285, - 13.5262935, - 13.498920900000002, - 13.4699166, - 13.486117049999999, - 13.480106400000002, - 13.461774749999998, - 13.4366499, - 13.41968355, - 13.407579, - 13.4306892, - 13.434868349999997, - 13.40459865, - 13.40479845, - 13.418351549999997, - 13.399353900000001, - 13.403949299999999, - 13.384352250000001, - 13.380289650000002, - 13.383386549999999, - 13.37749245, - 13.3288578, - 13.294325700000002, - 13.249587150000002, - 13.2027174, - 13.190679450000001, - 13.203899549999997, - 13.1675859, - 13.15108575, - 13.108744799999998, - 13.1124744, - 13.14945405, - 13.149687150000002, - 13.1310891, - 13.10080275, - 13.115637900000001, - 13.085817749999999, - 13.050253349999998, - 13.03100595, - 13.0033836, - 12.972031650000002, - 12.94159545, - 12.943327049999999, - 12.9192012, - 12.87802575, - 12.848089049999999, - 12.812557949999999, - 12.789714150000002, - 12.7940931, - 12.810959550000002, - 12.7968903, - 12.750936300000001, - 12.73406985, - 12.733353900000001, - 12.7165041, - 12.6954585, - 12.65055345, - 12.62005065, - 12.587633099999998, - 12.547506599999998, - 12.52920825, - 12.529441349999997, - 12.5268273, - 12.52238175, - 12.517952849999999, - 12.477460049999998, - 12.4356852, - 12.4024185, - 12.3710832, - 12.33084015, - 12.295026000000002, - 12.25461645, - 12.22431345, - 12.215172599999997, - 12.2001543, - 12.17629485, - 12.173847299999998, - 12.1002543, - 12.039698249999999, - 12.0305574, - 12.0040506, - 11.9580966, - 11.907813599999999, - 11.86087725, - 11.819951549999997, - 11.7684864, - 11.7383832, - 11.733138449999998, - 11.67502995, - 11.646358650000002, - 11.640531150000001, - 11.6075475, - 11.58082425, - 11.54762415, - 11.519069400000001, - 11.4914637, - 11.4533352, - 11.432889, - 11.379276, - 11.3575977, - 11.3218335, - 11.289366, - 11.2819734, - 11.243145599999998, - 11.1928293, - 11.1456432, - 11.069352900000002, - 10.999106549999999, - 10.963758599999998, - 10.9336887, - 10.8895995, - 10.854967499999999, - 10.816489350000001, - 10.76151105, - 10.7241984, - 10.677278699999999, - 10.6335891, - 10.589100299999998, - 10.5245982, - 10.4764131, - 10.432989899999999, - 10.368487799999999, - 10.333372950000001, - 10.27879425, - 10.223649450000002, - 10.1837727, - 10.120985549999999, - 10.07516475, - 10.0111455, - 9.951871500000001, - 9.8735166, - 9.8236332, - 9.764892, - 9.70029, - 9.652454549999998, - 9.6356214, - 9.559880549999999, - 9.5132106, - 9.438968249999999, - 9.3941964, - 9.35415315, - 9.26780625, - 9.2511729, - 9.19444635, - 9.1446129, - 9.09741015, - 9.006834150000001, - 8.920104299999998, - 8.8911333, - 8.855918549999998, - 8.7831081, - 8.7260652, - 8.65032435, - 8.61299505, - 8.5696218, - 8.5240674, - 8.4593655, - 8.40253905, - 8.33487345, - 8.30350485, - 8.2126458, - 8.1720198, - 8.09781075, - 8.0317269, - 7.96111425, - 7.899958799999999, - 7.8405349499999994, - 7.78029525, - 7.72614945, - 7.66018215, - 7.6026564, - 7.269714766666667, - 7.384967133333333, - 7.450352766666667, - 7.511679866666666, - 7.579610400000001, - 7.642600833333334, - 7.7195799, - 7.796193033333334, - 7.817101133333334, - 7.934532466666667, - 7.990337299999999, - 8.066700933333333, - 8.162076466666667, - 8.207036366666665, - 8.282767933333332, - 8.335063133333334, - 8.412907133333333, - 8.476596166666667, - 8.514303933333332, - 8.580770733333335, - 8.635361333333332, - 8.6954742, - 8.7106937, - 8.789119866666665, - 8.866248633333331, - 8.959528366666666, - 8.996188233333333, - 9.063054233333334, - 9.113918966666667, - 9.207132166666666, - 9.260026166666668, - 9.349596666666667, - 9.4163795, - 9.473365299999998, - 9.527107599999999, - 9.566844633333332, - 9.623680733333334, - 9.674146266666666, - 9.7060989, - 9.733111433333333, - 9.787901633333332, - 9.875076933333334, - 9.928686166666665, - 9.968689333333336, - 10.0116366, - 10.065146033333333, - 10.095252366666667, - 10.142158366666667, - 10.2034522, - 10.2472644, - 10.277853099999998, - 10.324809, - 10.381412233333332, - 10.3674735, - 10.5088901, - 10.558074866666667, - 10.592805266666666, - 10.641457766666665, - 10.686251333333333, - 10.739910466666666, - 10.778832466666666, - 10.8214138, - 10.87321, - 10.923609, - 10.963096533333331, - 11.003748400000001, - 10.996862199999999, - 11.0873808, - 11.111648833333334, - 11.147526933333333, - 11.167187533333331, - 11.222842666666669, - 11.229263133333333, - 11.290240933333333, - 11.2937173, - 11.337113666666665, - 11.368467500000001, - 11.3994055, - 11.421012199999998, - 11.484485000000001, - 11.530792199999999, - 11.561863266666666, - 11.580825266666666, - 11.622757900000002, - 11.660898133333333, - 11.708502733333333, - 11.740305666666668, - 11.8025476, - 11.842550766666667, - 11.884566566666669, - 11.935580999999999, - 11.981888199999998, - 12.034050333333333, - 12.098354800000003, - 12.1499514, - 12.203061633333334, - 12.254525166666667, - 12.284598233333332, - 12.319578133333334, - 12.345027133333334, - 12.3764974, - 12.402262433333332, - 12.428210433333334, - 12.455904933333333, - 12.461643433333334, - 12.557900533333333, - 12.611044033333334, - 12.656303333333334, - 12.6683625, - 12.6545901, - 12.667347866666665, - 12.760910366666668, - 12.806868266666667, - 12.853973866666665, - 12.8810862, - 12.892080833333333, - 12.928807233333332, - 12.9952075, - 13.030703033333333, - 13.030802833333333, - 13.053590499999999, - 13.090217099999998, - 13.085060766666667, - 13.131417866666665, - 13.142562199999997, - 13.160792333333333, - 13.1788894, - 13.201078266666665, - 13.2238493, - 13.2296876, - 13.2574819, - 13.274531066666666, - 13.287455166666666, - 13.2911145, - 13.3194078, - 13.34992996666667, - 13.362987133333334, - 13.407963666666667, - 13.453888300000001, - 13.475079166666665, - 13.481765766666665, - 13.483445733333333, - 13.477357933333332, - 13.472584166666666, - 13.484992633333333, - 13.508063066666667, - 13.562986333333333, - 13.573298999999999, - 13.569140666666666, - 13.5853249, - 13.5997959, - 13.608994133333335, - 13.635790433333332, - 13.6362728, - 13.643092466666669, - 13.656698533333332, - 13.6354245, - 13.635357966666668, - 13.5953548, - 13.611988133333336, - 13.602357433333333, - 13.6340273, - 13.665780333333332, - 13.682064366666665, - 13.692742966666666, - 13.7754938, - 13.735340933333331, - 13.744073433333334, - 13.789216300000001, - 13.693508099999999, - 13.698464833333333, - 13.793141766666665, - 13.797000699999998, - 13.804269466666666, - 13.813051866666665, - 13.852622566666666, - 13.887203266666665, - 13.919970933333332, - 13.925110633333334, - 13.947598900000001, - 13.961787133333335, - 13.95559953333333, - 13.979268766666666, - 13.966477733333333, - 14.037036333333333, - 14.047282466666669, - 14.069371533333333, - 14.080116666666667, - 14.0944546, - 14.097132566666666, - 14.107012766666665, - 14.102322166666667, - 14.106563666666666, - 14.1032869, - 14.1126681, - 14.119787166666667, - 14.11927153333333, - 14.098513133333336, - 14.131047933333333, - 14.141959400000001, - 14.150808333333332, - 14.102405333333333, - 14.116260899999999, - 14.128852333333333, - 14.120702, - 14.161902766666664, - 14.134990033333333, - 14.132295433333333, - 14.111653466666668, - 14.063034233333333, - 14.077854533333332, - 14.100359433333333, - 14.120153099999998, - 14.1746938, - 14.187102266666667, - 14.2265399, - 14.258026800000001, - 14.244803300000001, - 14.243389466666667, - 14.245086066666666, - 14.209840033333332, - 14.2288353, - 14.280332099999997, - 14.303618766666666, - 14.270718033333333, - 14.263266300000002, - 14.246250400000001, - 14.264913, - 14.265145866666666, - 14.274859733333335, - 14.272414633333334, - 14.2627174, - 14.2391646, - 14.223030266666665, - 14.206263866666665, - 14.184856766666666, - 14.183659166666667, - 14.173363133333336, - 14.186852766666666, - 14.226706233333331, - 14.2158114, - 14.165678533333331, - 14.156397133333334, - 14.171167533333332, - 14.190761599999998, - 14.183941933333333, - 14.172365133333335, - 14.162484933333333, - 14.111453866666665, - 13.940413300000001, - 14.106380699999999, - 14.0718499, - 14.0294848, - 14.019388366666666, - 14.005749033333332, - 14.0324289, - 14.0192054, - 13.999677866666667, - 13.966827033333331, - 13.9427586, - 13.875044299999999, - 13.930765966666668, - 13.919871133333336, - 13.882113466666667, - 13.885040933333332, - 13.854901333333332, - 13.830616666666666, - 13.8175595, - 13.775161133333334, - 13.776009433333334, - 13.771418633333333, - 13.753887099999998, - 13.752805933333333, - 13.692959199999999, - 13.716844666666667, - 13.682446933333333, - 13.656365866666663, - 13.5808339, - 13.564050866666665, - 13.6111731, - 13.605401333333333, - 13.588634933333333, - 13.552440800000001, - 13.515198766666664, - 13.464284133333335, - 13.501875466666668, - 13.482863566666667, - 13.452857033333332, - 13.407364866666665, - 13.3979504, - 13.358096933333334, - 13.341430333333333, - 13.326293999999999, - 13.275229666666666, - 13.226427466666665, - 13.179222066666668, - 13.154588099999998, - 13.116464500000001, - 13.094441966666668, - 13.073134666666668, - 13.059262466666668, - 13.025164133333334, - 12.963171699999998, - 12.902676266666667, - 12.8364756, - 12.801545599999999, - 12.780271566666668, - 12.736592433333332, - 12.707550633333335, - 12.697055, - 12.649566833333333, - 12.6286421, - 12.6025444, - 12.5584328, - 12.491699866666664, - 12.472205599999999, - 12.470509, - 12.4183635, - 12.386660366666666, - 12.351713733333334, - 12.320942066666667, - 12.294212300000002, - 12.2890227, - 12.2168673, - 12.177546099999999, - 12.155157633333335, - 12.094778633333334, - 12.073920433333333, - 12.026665133333333, - 11.964040633333333, - 11.91394103333333, - 11.874386966666668, - 11.829510233333334, - 11.8235056, - 11.781157133333334, - 11.739723499999998, - 11.709966466666668, - 11.667751066666668, - 11.618449866666664, - 11.5901732, - 11.571976333333334, - 11.538476800000002, - 11.535998433333333, - 11.471760499999998, - 11.4446149, - 11.404961033333333, - 11.348840166666665, - 11.299954800000002, - 11.2757533, - 11.2495558, - 11.171928033333334, - 11.108654833333334, - 11.073475333333333, - 11.0364329, - 11.007174866666666, - 10.957391300000001, - 10.903782066666668, - 10.8567929, - 10.780213033333334, - 10.730945099999998, - 10.67199656666667, - 10.651321333333334, - 10.596364800000002, - 10.549874633333333, - 10.497679233333335, - 10.4436708, - 10.340460966666665, - 10.3112362, - 10.243571800000002, - 10.1814463, - 10.123845066666666, - 10.0664767, - 10.020352466666665, - 9.957545, - 9.928469933333332, - 9.845852166666667, - 9.785290199999999, - 9.706681066666667, - 9.663983299999998, - 9.598847166666667, - 9.539582599999997, - 9.450161799999998, - 9.4262098, - 9.363186099999998, - 9.275145866666668, - 9.2390349, - 9.1744144, - 9.1354924, - 9.0795545, - 8.988453733333333, - 8.9170801, - 8.870190733333335, - 8.808015333333334, - 8.782815833333332, - 8.7229192, - 8.6334984, - 8.566416166666666, - 8.509862833333333, - 8.461609533333334, - 8.409148, - 8.325083133333333, - 8.228277133333332, - 8.182718433333333, - 8.139371966666667, - 8.039655133333333, - 7.972523, - 7.915221166666667, - 7.844462966666667, - 7.776349466666667, - 7.720710966666666, - 7.6662867, - 7.158027966666666, - 7.248671883333333, - 7.324327566666667, - 7.384546366666667, - 7.44813835, - 7.54345155, - 7.618309633333332, - 7.667893766666667, - 7.755746083333333, - 7.8175600833333325, - 7.8854724, - 7.922743583333333, - 7.999545816666666, - 8.0944436, - 8.152701633333333, - 8.225532483333334, - 8.283707433333332, - 8.319300333333334, - 8.345454966666665, - 8.462752016666666, - 8.533389466666668, - 8.607117616666667, - 8.649390416666668, - 8.727272733333333, - 8.793938800000001, - 8.843406616666668, - 8.930261933333332, - 8.966984766666666, - 9.037821616666665, - 9.068080566666666, - 9.118994033333333, - 9.217397933333334, - 9.274692199999999, - 9.3403945, - 9.383348583333335, - 9.43815035, - 9.492918883333331, - 9.542752266666668, - 9.6030043, - 9.639378183333333, - 9.703933933333333, - 9.7647177, - 9.8355047, - 9.875118833333332, - 9.850725566666666, - 9.939458566666666, - 10.0484639, - 10.080534066666665, - 10.137612316666667, - 10.1819622, - 10.2130686, - 10.2691997, - 10.283639583333333, - 10.17264025, - 10.332824916666667, - 10.442212433333333, - 10.500387383333333, - 10.545634566666667, - 10.565624416666665, - 10.6428753, - 10.678783916666667, - 10.70673315, - 10.738437750000001, - 10.793505383333333, - 10.844385616666667, - 10.911633266666666, - 10.946528266666666, - 10.998754450000002, - 11.051379433333333, - 11.088102266666667, - 11.131820716666665, - 11.171401616666667, - 11.212727266666667, - 11.225655033333334, - 11.286671433333334, - 11.317179633333332, - 11.354500666666667, - 11.365151950000001, - 11.435922333333334, - 11.469504616666667, - 11.5247218, - 11.566462866666667, - 11.6013911, - 11.635355566666666, - 11.716079333333335, - 11.749694850000001, - 11.775949183333333, - 11.825284066666665, - 11.858932816666666, - 11.89136855, - 11.925731816666666, - 11.9421657, - 11.976994233333333, - 12.0201311, - 12.061789083333334, - 12.10333075, - 12.1403693, - 12.189787266666666, - 12.212635183333335, - 12.249906366666666, - 12.294339333333333, - 12.32855305, - 12.358429816666666, - 12.396498600000001, - 12.42934975, - 12.469462383333333, - 12.4939055, - 12.510920966666667, - 12.492293683333335, - 12.5142443, - 12.571156383333332, - 12.63293715, - 12.6989884, - 12.718712383333333, - 12.7102545, - 12.715256116666668, - 12.807545083333334, - 12.848056516666666, - 12.879943899999999, - 12.897507716666667, - 12.923213700000002, - 12.905982216666667, - 13.003405733333333, - 13.013458816666665, - 13.047921783333335, - 13.074890633333332, - 13.1154353, - 13.160233833333333, - 13.200313233333333, - 13.243034683333333, - 13.247703966666664, - 13.256693583333332, - 13.354615599999999, - 13.360963166666668, - 13.400560683333334, - 13.43711735, - 13.433112733333331, - 13.456592083333334, - 13.325902, - 13.236537566666668, - 13.2499306, - 13.3910061, - 13.526814116666667, - 13.443331983333332, - 13.425336133333333, - 13.633410033333332, - 13.578043299999997, - 13.483710483333333, - 13.308205249999999, - 13.387566450000001, - 13.333479200000001, - 13.194480783333333, - 13.33781615, - 13.422843633333335, - 13.484391766666668, - 13.61577975, - 13.728257966666666, - 13.855126216666665, - 13.877309466666665, - 13.791783483333331, - 13.667008933333335, - 13.783342216666664, - 13.829503316666665, - 13.962469883333332, - 13.715147416666667, - 13.724369666666668, - 13.896451866666668, - 13.9654775, - 14.14857655, - 14.244953216666664, - 14.260755666666666, - 14.28825625, - 14.327405116666668, - 14.293905916666667, - 14.292161166666666, - 14.288638433333333, - 14.238323166666667, - 14.325178483333334, - 14.3350654, - 14.333636366666669, - 14.341662216666666, - 14.387058950000002, - 14.353543133333332, - 14.431707933333335, - 14.3340684, - 14.228369783333335, - 14.214478249999997, - 14.199057983333331, - 14.036580216666666, - 13.714000866666666, - 13.34997955, - 13.582695966666668, - 13.40760615, - 13.3423525, - 13.3364702, - 13.479257216666666, - 13.216099066666665, - 12.931422333333334, - 13.256394483333333, - 13.587996683333333, - 13.755160349999999, - 13.603749283333334, - 13.802135666666667, - 13.8787385, - 14.151717099999999, - 14.138889033333335, - 13.981944616666667, - 14.034287116666667, - 14.073735083333334, - 13.838675716666666, - 13.764316133333331, - 12.117421683333335, - 11.513040283333336, - 12.081513066666668, - 12.895114916666666, - 11.97671175, - 12.259078766666669, - 12.852659333333333, - 13.302887916666666, - 14.388355049999998, - 14.505170216666667, - 14.476656016666666, - 12.371889316666666, - 12.840263299999998, - 12.587839516666666, - 13.300395416666666, - 12.565955366666667, - 13.559482483333333, - 13.167960583333333, - 12.930940450000001, - 13.199665183333334, - 13.360032633333331, - 13.062428133333333, - 12.892356549999997, - 12.094390983333334, - 11.921112383333334, - 11.610131466666667, - 11.250613266666667, - 11.487301066666667, - 11.239064683333334, - 11.34660775, - 11.485506466666665, - 11.7577207, - 11.602803516666667, - 11.673141866666668, - 12.2188332, - 12.692391583333333, - 11.856008283333335, - 12.406368899999999, - 11.986864533333335, - 11.4665967, - 11.058258733333332, - 11.2236278, - 12.832303916666666, - 12.754488066666665, - 12.662930233333332, - 13.149482850000002, - 13.022448433333333, - 12.892140533333334, - 13.026918316666666, - 12.401716233333334, - 13.160200600000001, - 12.836574399999998, - 12.375977016666667, - 12.435448066666664, - 11.864050749999999, - 11.764616616666668, - 11.8444597, - 11.722077950000001, - 10.767633233333333, - 10.876306233333333, - 11.664800299999998, - 12.35128465, - 12.372986016666667, - 12.368998016666668, - 12.2115551, - 13.336237566666666, - 13.379324583333332, - 13.022182566666666, - 11.795540233333332, - 11.374640066666666, - 9.63236595, - 9.574240849999999, - 11.41091425, - 10.56894775, - 9.060486749999999, - 9.66995285, - 10.853740799999999, - 10.93225455, - 8.575346549999999, - 9.5274317, - 11.04212395, - 11.040528749999998, - 10.42677555, - 10.193361233333333, - 9.90703945, - 9.9046965, - 9.751972716666668, - 9.698001783333332, - 9.001746833333334, - 8.341932233333333, - 8.5156761, - 9.167032816666667, - 8.833486466666667, - 8.244874283333333, - 8.187297533333334, - 7.711462666666666, - 7.33258605, - 7.809866566666667, - 8.062672533333334, - 8.447265283333333, - 8.22709445, - 7.931899366666667, - 8.270995683333332, - 8.09210065, - 8.089275816666667, - 7.578363166666667, - 7.3921567999999995, - 8.02659775, - 8.618051383333333, - 9.138618316666665, - 9.563107683333333, - 10.448460299999999, - 11.859913200000001, - 11.614966916666667, - 11.294348333333335, - 11.456310983333333, - 11.183365616666668, - 10.749138883333334, - 10.07383755, - 9.603203699999998, - 9.454501149999999, - 9.604416716666666, - 9.483264600000002, - 9.447389216666666, - 9.673276183333334, - 10.200456550000002, - 10.155957116666666, - 10.180583016666667, - 10.7404816, - 10.896927516666667, - 10.650618666666668, - 10.017590133333334, - 10.593889366666666, - 10.426094266666666, - 10.457582850000001, - 10.754705466666667, - 10.5121686, - 9.9374978, - 10.103465066666665, - 10.001621516666667, - 9.611163083333333, - 9.207295, - 9.296875449999998, - 9.247723350000001, - 8.735979866666666, - 8.4292362, - 8.530946816666665, - 8.753344283333332, - 9.121935183333335, - 8.464313983333334, - 8.0233575, - 7.341243333333334, - 7.55362095, - 7.418344666666667, - 7.2535028, - 7.6190846, - 7.4995978, - 7.7898156, - 8.0289386, - 8.2338324, - 8.7197808, - 8.732745399999999, - 9.1558462, - 9.409494200000001, - 9.6553568, - 9.652617800000002, - 9.7976686, - 9.848863, - 9.763704999999998, - 9.742241199999999, - 9.680920799999999, - 9.998196599999998, - 10.146418, - 10.2625516, - 10.1930308, - 10.3270592, - 10.3207678, - 10.237950399999999, - 10.4174296, - 10.3456014, - 10.371812799999999, - 10.5680248, - 10.628399, - 10.5807902, - 10.4593778, - 10.4717946, - 10.513776, - 10.7349212, - 10.650228, - 10.7494462, - 10.677203, - 10.860533400000001, - 11.006447399999999, - 11.0374396, - 11.081579000000001, - 11.133404200000001, - 11.169393, - 11.1965008, - 11.217184399999999, - 11.2583856, - 11.325333399999998, - 11.3564418, - 11.3938748, - 11.403884600000001, - 11.4427784, - 11.5022728, - 11.534858600000002, - 11.568805600000001, - 11.6146548, - 11.641679600000002, - 11.660520600000002, - 11.7203304, - 11.7718568, - 11.8145022, - 11.8571144, - 11.8854008, - 11.955884399999999, - 12.022566600000001, - 12.018234, - 11.793121399999999, - 11.9444968, - 12.0680672, - 12.268313, - 12.284248999999999, - 12.32052, - 12.304650399999998, - 12.147099800000001, - 12.244259600000001, - 12.3339992, - 12.370768199999999, - 12.411903, - 12.4777718, - 12.464508399999998, - 12.503037, - 12.545599399999997, - 12.5711634, - 12.5714954, - 12.62928, - 12.6214282, - 12.681470399999998, - 12.734457600000002, - 12.788457399999999, - 12.832629999999998, - 12.6918454, - 12.006199, - 12.2453884, - 12.353387999999999, - 11.8199802, - 12.557385399999998, - 11.705307399999999, - 9.052643999999999, - 9.924824599999999, - 11.7392876, - 12.595864199999998, - 13.271019399999998, - 13.235927, - 12.2063618, - 12.4464144, - 12.727469, - 13.0228826, - 13.3495872, - 13.3330536, - 13.342615199999997, - 13.3518282, - 13.126433399999998, - 12.195272999999998, - 13.279983399999997, - 13.431209399999998, - 13.376379600000002, - 13.2964174, - 13.4107582, - 13.490404999999997, - 13.518542, - 13.554796399999999, - 13.542728199999999, - 13.495252199999998, - 13.457935399999998, - 13.4488884, - 13.443593, - 13.397976199999999, - 13.319790199999998, - 13.291869, - 13.21858, - 13.3911038, - 13.5552114, - 13.285295399999999, - 13.616465399999997, - 13.6525538, - 13.663958000000001, - 13.668191, - 13.7294616, - 13.601542, - 13.3026258, - 13.3853436, - 13.145523399999998, - 12.9604666, - 13.2248548, - 13.5108562, - 13.560672799999999, - 13.5128814, - 13.557668199999998, - 13.5968276, - 13.6255456, - 13.747489199999999, - 13.7522866, - 13.7573662, - 13.8294268, - 13.74812, - 13.6855546, - 13.539408199999999, - 13.4683104, - 13.5764428, - 13.8081456, - 13.9612474, - 14.097218, - 13.448440199999999, - 13.6234208, - 13.9665926, - 14.048098600000001, - 14.0758372, - 13.9074302, - 13.933625000000001, - 14.0300046, - 14.185397199999997, - 14.220871399999998, - 14.184484199999998, - 14.2643634, - 14.333104, - 14.347878000000001, - 14.349687399999999, - 14.245788, - 14.0096364, - 13.6361862, - 13.007660399999999, - 13.0200274, - 12.884405399999999, - 12.777816800000002, - 12.763192199999999, - 11.630292, - 10.569054000000001, - 11.526475600000001, - 11.8003092, - 11.0933152, - 11.9173558, - 11.7377438, - 12.203008600000002, - 10.8180706, - 12.9923718, - 10.7059542, - 11.9609308, - 10.165923, - 9.770793199999998, - 11.3662192, - 11.4233564, - 11.2964162, - 9.7630576, - 7.7281466, - 7.557731, - 7.5636904, - 9.7269526, - 10.851586000000001, - 10.412233800000001, - 11.972501, - 11.9619268, - 12.8122452, - 14.0114126, - 13.695182600000003, - 12.3849944, - 12.679827, - 12.426228799999999, - 13.0096192, - 12.4091474, - 13.1201918, - 12.9437172, - 12.641265199999998, - 12.956947399999999, - 12.694999399999999, - 12.3745364, - 12.2622208, - 11.2906228, - 12.265142399999998, - 13.97139, - 14.416286600000001, - 14.6221598, - 14.638112399999999, - 14.581921399999999, - 14.419673, - 13.353438399999998, - 12.8531642, - 13.032195199999999, - 13.8645358, - 14.192950199999999, - 14.099708, - 13.658861799999999, - 12.6015248, - 13.4320228, - 13.292035, - 13.5447368, - 13.7183064, - 13.679893999999999, - 14.0834068, - 14.008906, - 14.120690399999999, - 13.889402599999999, - 13.780838600000001, - 13.245438799999999, - 13.3658552, - 13.915365, - 13.585556199999997, - 13.722672199999998, - 13.112555799999999, - 13.155898399999996, - 13.23601, - 13.325782799999999, - 13.515006199999998, - 13.4487556, - 13.043732199999999, - 13.0586058, - 13.122980600000002, - 12.867905, - 12.8765204, - 12.97124, - 12.2558796, - 11.9974674, - 12.1509012, - 11.734440399999997, - 12.0174704, - 12.057891399999997, - 11.886928000000001, - 11.6360522, - 11.0105476, - 10.5035172, - 10.853860199999998, - 11.0027788, - 9.4336638, - 8.020854400000001, - 6.9166888, - 7.035329, - 8.4141748, - 8.1353446, - 7.736977800000001, - 9.9468694, - 10.631470000000002, - 11.353619799999999, - 11.0913564, - 11.017918000000002, - 11.1105958, - 10.671774800000001, - 10.795145999999999, - 11.0385186, - 11.241802199999999, - 11.235129, - 11.073893199999999, - 10.8330604, - 10.0418214, - 10.1490408, - 10.4058262, - 10.738905200000001, - 10.7871614, - 10.7213092, - 10.2387804, - 9.464489999999998, - 9.9283438, - 10.2493878, - 10.2664194, - 9.811197599999998, - 9.696724, - 9.984402, - 10.0059986, - 9.569319, - 9.9758364, - 10.011094799999999, - 10.0732286, - 5.8539734, - 2.94816, - 7.405758, - 8.5689698, - 8.347326599999999, - 8.416648200000001, - 8.072115199999999, - 7.680869799999999, - 7.553996, - 7.735450599999999, - 7.7965552, - 8.2761624, - 8.6207452, - 8.22198, - 7.818849, - 7.576522199999999, - 7.5059224, - 8.296613599999999, - 7.774029, - 7.889664600000001, - 8.40707, - 8.719631399999999, - 8.586150800000002, - 7.8206916, - 8.4829984, - 8.50916, - 8.3513106, - 7.966008, - 8.4145732, - 8.0865904, - 7.722486, - 7.511549799999999, - 7.5469244, - 7.830137, - 7.785151, - 7.603961999999999, - 7.658260599999999, - 7.5399192, - 7.5068188000000005, - 7.399417000000001, - 7.978042666666667, - 8.2104415, - 8.590614416666664, - 9.126902833333332, - 9.690520583333333, - 9.56319375, - 8.458428666666666, - 9.747036583333333, - 10.104904916666667, - 10.272114666666665, - 10.564512, - 10.74634825, - 10.882994916666668, - 11.04285825, - 9.80945625, - 11.278656666666667, - 11.95895475, - 12.151885249999998, - 12.351250083333332, - 11.696440583333333, - 10.423785833333335, - 8.962180583333332, - 7.93726425, - 8.404566, - 8.019782916666667, - 8.59754625, - 9.183684166666666, - 8.279328666666666, - 7.849986166666667, - 7.568533833333333, - 8.775618083333333, - 9.677253916666666, - 9.239371, - 9.421472583333333, - 9.542381666666666, - 9.203683666666667, - 8.558193999999999, - 8.1513385, - 7.896469249999999, - 7.915158666666667, - 8.1589005, - 8.5256575, - 8.014741583333333, - 7.635397833333333, - 7.429863999999999, - 7.644369416666666, - 8.020462833333333, - 7.613905833333333, - 7.32046375, - 7.418603916666667, - 7.634850583333333, - 7.3087393333333335, - 7.435436, - 7.65587825, - 7.5720660833333335, - 7.7442176666666676, - 7.650886666666667, - 7.592728916666666, - 7.6410859166666665, - 7.5959295, - 7.403595999999999, - 7.321226583333333, - 7.2883915833333335, - 7.887564, - 7.749491166666666, - 8.08014625, - 8.149066583333333, - 7.804962416666667, - 7.6971541666666665, - 7.587554916666666, - 7.596858166666666, - 7.486744833333333, - 7.176862233333334, - 7.223331733333333, - 7.3070927999999995, - 7.3779153, - 7.413964366666667, - 7.4526144, - 7.546911866666666, - 7.5732363000000005, - 7.647272733333334, - 7.7187082, - 7.717581666666667, - 7.808549233333333, - 7.930860933333333, - 8.0090556, - 8.047142366666668, - 8.121046266666667, - 8.1856397, - 8.223096933333332, - 8.3056652, - 8.372644233333332, - 8.431605, - 8.460596666666666, - 8.551315733333333, - 8.602639266666667, - 8.643111633333332, - 8.707390299999998, - 8.776904033333333, - 8.837256400000001, - 8.900309133333334, - 8.9368055, - 8.968961399999998, - 9.032047266666666, - 9.103035433333334, - 9.160588033333333, - 9.201292333333333, - 9.240671299999999, - 9.303740600000001, - 9.381090366666667, - 9.464238466666666, - 9.522934166666667, - 9.570066333333333, - 9.628149066666664, - 9.684657966666666, - 9.771980866666668, - 9.820637166666666, - 9.875058666666668, - 9.920434766666666, - 9.966307866666668, - 10.005256099999999, - 10.090955466666665, - 10.1288103, - 10.191664233333334, - 10.242209133333331, - 10.282648366666667, - 10.334336366666665, - 10.397372533333334, - 10.448099666666664, - 10.514747366666665, - 10.5734762, - 10.6359988, - 10.672594566666668, - 10.725823266666666, - 10.788693766666666, - 10.826581733333333, - 10.866325166666666, - 10.880241166666668, - 10.9359383, - 10.967762866666668, - 11.024222066666667, - 11.047001233333333, - 11.088351633333334, - 11.134572633333333, - 11.179683666666667, - 11.223751, - 11.244409633333333, - 11.286306733333335, - 11.341374333333334, - 11.384646466666666, - 11.398015766666665, - 11.390577333333333, - 11.424621833333333, - 11.470296133333333, - 11.491667133333332, - 11.522663366666668, - 11.539263166666666, - 11.588764366666666, - 11.618153633333334, - 11.673453166666667, - 11.68793243333333, - 11.729100599999999, - 11.744043733333335, - 11.745319366666669, - 11.772289900000002, - 11.864350866666665, - 11.897152866666667, - 11.914547866666666, - 11.949669199999999, - 11.992079866666668, - 12.064293966666666, - 12.113977400000003, - 12.149678566666667, - 11.885738433333332, - 10.560040633333333, - 11.2517818, - 11.4011303, - 11.629667466666666, - 11.608926, - 11.699810733333335, - 11.625558933333332, - 11.875781866666667, - 11.353567400000001, - 11.287002533333332, - 11.167059866666667, - 10.798186466666667, - 11.630727733333334, - 11.4728971, - 11.267221933333332, - 11.4112691, - 11.740167133333332, - 12.123205033333333, - 12.0285431, - 12.533196900000002, - 12.562437066666668, - 12.576469033333334, - 12.640813966666665, - 12.859990966666665, - 12.875033499999999, - 13.073402766666666, - 12.143466066666667, - 12.302241, - 13.146345799999999, - 13.298941366666668, - 13.381343966666666, - 13.280370133333331, - 13.01094643333333, - 12.9793041, - 13.267680066666667, - 13.2625941, - 13.3024038, - 13.382006633333333, - 13.384044333333332, - 13.426156800000001, - 13.467324966666665, - 13.515699633333332, - 13.549247133333331, - 13.558789533333334, - 13.580077700000002, - 13.592486133333333, - 13.580674099999998, - 13.481903633333333, - 13.391068599999999, - 13.304789400000002, - 13.303828533333332, - 13.070387633333333, - 13.005661666666667, - 12.7885058, - 12.7740928, - 12.663245233333335, - 12.383533633333332, - 12.695235466666666, - 12.119162766666667, - 12.445807733333336, - 12.901391066666667, - 13.155308366666668, - 13.315060733333334, - 13.187928133333335, - 13.159814500000001, - 13.224921499999999, - 13.626033633333332, - 13.4833118, - 13.324801933333333, - 13.7145162, - 13.8223155, - 13.761548966666666, - 13.404172833333332, - 13.6179988, - 13.614337566666668, - 13.701146900000001, - 13.647404633333332, - 13.808283533333334, - 13.839693933333331, - 13.8024355, - 13.738952033333334, - 13.763719199999999, - 13.744203666666666, - 13.723279966666666, - 13.844547966666665, - 13.808946200000001, - 13.810404066666669, - 13.749289633333333, - 13.459969366666668, - 13.626911666666667, - 13.698645333333333, - 13.497940166666666, - 13.631981066666668, - 13.698280866666668, - 13.768656066666669, - 13.788867399999999, - 13.739581566666669, - 13.649475466666665, - 13.639966200000002, - 13.602542099999999, - 13.674524266666666, - 13.640927066666668, - 13.678500266666667, - 13.641440633333334, - 13.587168233333333, - 13.548153733333333, - 13.607379566666667, - 13.648266099999999, - 13.6394692, - 13.633057899999999, - 13.642931633333331, - 13.625818266666666, - 13.634449499999999, - 13.6301753, - 13.600670066666666, - 13.613708033333333, - 13.507548833333333, - 13.4754592, - 13.40680693333333, - 13.4243179, - 13.399732966666667, - 13.282739166666666, - 13.484537733333333, - 13.434224766666667, - 13.467888233333333, - 13.39015743333333, - 13.505478000000002, - 13.568679833333332, - 13.600703200000002, - 13.582247933333331, - 13.559435633333333, - 13.639634866666665, - 13.660823633333333, - 13.627889099999999, - 13.612316433333332, - 13.6228197, - 13.637116733333334, - 13.639999333333334, - 13.6324118, - 13.6002062, - 13.594490700000001, - 13.579166533333334, - 13.557182566666667, - 13.546198866666666, - 13.565167699999998, - 13.512800466666667, - 13.517886433333333, - 13.479899066666666, - 13.444728033333332, - 13.426355599999999, - 13.3802837, - 13.383149733333333, - 13.354953266666664, - 13.298875099999998, - 13.269038533333331, - 13.218775266666666, - 13.19334543333333, - 13.195797299999997, - 13.160758799999998, - 13.165414033333333, - 13.168694233333333, - 13.1570313, - 13.1733329, - 13.134086466666668, - 13.08104, - 13.054168866666666, - 13.0962482, - 13.087186233333334, - 13.065715833333334, - 13.015883299999997, - 13.014193500000001, - 13.028937833333332, - 13.007450866666666, - 12.996434033333335, - 12.921469866666667, - 12.936595233333334, - 12.898806666666667, - 12.854043533333334, - 12.820479466666665, - 12.786633766666665, - 12.778549233333333, - 12.7851262, - 12.747039433333333, - 12.738921766666666, - 12.7011332, - 12.668927599999998, - 12.637997633333333, - 12.594460433333332, - 12.594841466666665, - 12.593300766666665, - 12.582648400000002, - 12.572956900000001, - 12.560349666666665, - 12.542441099999998, - 12.541728733333334, - 12.511312333333334, - 12.5011404, - 12.479736266666666, - 12.418555566666669, - 12.421156533333335, - 12.4075056, - 12.376227733333334, - 12.346788766666666, - 12.318410066666667, - 12.293377833333333, - 12.292963666666665, - 12.264982566666667, - 12.257229366666667, - 12.276165066666668, - 12.247372200000001, - 12.238310233333335, - 12.205359133333333, - 12.186440000000001, - 12.1464315, - 12.123089066666667, - 12.091165099999998, - 12.045076633333334, - 12.0359484, - 12.014743066666668, - 11.984310099999998, - 11.936796900000001, - 11.895579033333332, - 11.873462533333335, - 11.839716233333332, - 11.796129333333333, - 11.633709733333333, - 11.676932166666667, - 11.6862592, - 11.6494812, - 11.619975966666665, - 11.5793545, - 11.539213466666665, - 11.499204966666666, - 11.453133066666666, - 11.407375933333332, - 11.362662499999999, - 11.3254869, - 11.278835166666667, - 11.240914066666669, - 11.205809299999999, - 11.1677888, - 11.1189834, - 11.061397666666668, - 11.008931033333335, - 10.987560033333333, - 10.955039666666666, - 10.905886366666666, - 10.869207766666666, - 10.833937333333333, - 10.7895221, - 10.745670133333332, - 10.704435700000001, - 10.668717966666666, - 10.621585799999998, - 10.568141733333333, - 10.5158242, - 10.4531028, - 10.397819833333333, - 10.322756266666667, - 10.2917766, - 10.273520133333333, - 10.232964933333333, - 10.175611133333332, - 10.155366666666666, - 10.104473866666666, - 10.052984666666667, - 9.94, - 9.952441566666666, - 9.896247433333334, - 9.852180100000002, - 9.800276733333334, - 9.742575033333335, - 9.678014733333333, - 9.622350733333333, - 9.555437966666664, - 9.497554033333333, - 9.434998299999998, - 9.370056966666665, - 9.351982733333333, - 9.298339866666666, - 9.2222823, - 9.167181566666667, - 9.105056566666667, - 9.009549733333333, - 8.970286733333333, - 8.902264, - 8.862007, - 8.7983413, - 8.750413933333332, - 8.705021266666668, - 8.638986533333334, - 8.578203433333332, - 8.522522866666666, - 8.447691233333334, - 8.371302333333333, - 8.2971665, - 8.249918366666666, - 8.1822601, - 8.1229183, - 8.039405733333334, - 7.9617909, - 7.905663033333332, - 7.858431466666666, - 7.771870633333333, - 7.684332366666667, - 7.6623484, - 7.596578733333333, - 7.5217471, - 7.458810333333333, - 7.408778999999999, - 8.022056, - 8.843911466666666, - 8.515691733333334, - 8.6190912, - 9.0243232, - 9.252218666666666, - 9.3795088, - 9.467135466666667, - 9.669685333333332, - 9.670330133333332, - 9.706951466666666, - 9.756286933333335, - 9.788559999999999, - 9.872102933333334, - 9.917536533333333, - 9.978924799999998, - 10.040147733333331, - 10.093980266666668, - 10.130717333333333, - 10.189559466666665, - 10.295885333333333, - 10.396143466666667, - 10.515414933333332, - 10.659569066666666, - 10.763778666666665, - 10.974710933333334, - 11.292713066666666, - 11.579103466666664, - 11.752405866666667, - 11.819101333333332, - 8.707279999999999, - 10.554632, - 11.942274666666668, - 11.696424, - 11.712031466666666, - 7.070430399999999, - 9.067905066666667, - 11.528180799999998, - 8.935688, - 12.272511466666666, - 12.525273066666667, - 12.859973866666666, - 11.944043733333334, - 6.427399466666667, - 7.561486933333333, - 8.559984533333333, - 10.138124266666667, - 11.330805866666665, - 9.401597333333333, - 8.104077866666666, - 11.5846256, - 6.961442666666667, - 8.238477333333334, - 9.621374933333334, - 12.857179733333332, - 16.891445333333333, - 16.58923253333333, - 13.927713066666664, - 9.4526688, - 8.2855808, - 15.644203733333333, - 15.423301866666666, - 15.194348266666665, - 15.585196266666665, - 10.7563552, - 8.6213232, - 11.616204266666667, - 7.423136, - 8.23608, - 10.656295466666666, - 13.525424, - 17.183986133333335, - 14.336995733333332, - 11.569960533333333, - 10.229322133333335, - 9.007690666666667, - 9.035383999999999, - 7.460699733333333, - 11.906992533333334, - 10.502072533333333, - 11.180484799999999, - 11.044547733333332, - 9.290460266666665, - 9.786427199999999, - 11.165571733333334, - 12.409159466666667, - 13.960531733333333, - 14.608952533333335, - 14.417248533333334, - 9.374730666666666, - 9.403978133333334, - 8.864330133333334, - 13.468119466666664, - 12.993232533333334, - 10.534709333333332, - 10.230843199999999, - 10.824389866666667, - 10.417620266666667, - 11.639450133333332, - 10.347419733333334, - 10.648690133333334, - 11.2550336, - 10.635529600000002, - 10.7018448, - 8.620099733333332, - 8.3273936, - 8.960752533333332, - 9.395727999999998, - 14.0817376, - 12.787375999999998, - 11.935198399999999, - 10.9294592, - 9.935739733333332, - 10.118317333333332, - 9.476261866666666, - 9.804779199999999, - 10.374613833333333, - 11.605914816666665, - 8.856517449999998, - 8.166219883333333, - 9.5214289, - 9.715136366666666, - 12.807469283333333, - 13.8513061, - 10.130514016666666, - 10.370385566666668, - 13.401672883333333, - 14.204102100000002, - 14.252875816666666, - 13.927398383333333, - 13.783653833333332, - 13.607503583333333, - 13.376204183333334, - 13.209237199999999, - 13.380201216666668, - 12.494329800000001, - 10.76754533333333, - 9.939168433333332, - 8.878633266666668, - 8.195949883333334, - 7.5436185, - 7.643971499999999, - 7.747360499999999, - 7.856607, - 7.9455089999999995, - 8.062790999999999, - 8.169051, - 8.2742385, - 8.3443305, - 8.420015999999999, - 8.4870885, - 8.537198999999998, - 8.6082645, - 8.6527155, - 8.706274500000001, - 8.771119500000001, - 8.834693999999999, - 8.880927, - 8.9749605, - 9.049755000000001, - 9.098199, - 9.173274, - 9.20502, - 9.2753925, - 9.3689475, - 9.427605, - 9.499545000000001, - 9.552807000000001, - 9.5917965, - 9.697776000000001, - 9.741632999999998, - 9.802188, - 9.8465235, - 9.900132, - 9.976345499999999, - 10.0634325, - 10.139794499999999, - 10.2131865, - 10.252142999999998, - 10.31184, - 10.362049500000001, - 10.421928, - 10.483142999999998, - 10.578760499999998, - 10.6413615, - 10.708401, - 10.7533635, - 10.8522645, - 10.93554, - 11.018898, - 11.080360499999998, - 11.153769000000002, - 11.2105455, - 11.2382655, - 11.2817925, - 11.3260125, - 11.380776, - 11.3969955, - 11.161309499999998, - 11.199077999999998, - 11.403199500000001, - 11.4857655, - 11.534341500000002, - 11.5617975, - 11.665549500000001, - 11.722359, - 11.8674105, - 11.96943, - 12.042062999999999, - 12.006324000000001, - 11.945620499999999, - 11.863813499999997, - 11.180878499999999, - 10.909899, - 10.4576835, - 10.316608500000001, - 8.774749499999999, - 7.8766875, - 9.273099, - 9.593397000000001, - 9.408563999999998, - 10.594914, - 11.279664, - 11.741268, - 12.197262, - 12.866799, - 12.683302499999998, - 12.6576945, - 12.482299500000002, - 11.957550000000001, - 11.577159, - 11.281198499999999, - 11.282287499999999, - 9.522579, - 8.403615, - 9.4035645, - 10.4027055, - 9.370382999999999, - 9.093991499999998, - 8.520055499999998, - 8.930262, - 9.492681, - 10.054077000000001, - 10.9992795, - 11.928378, - 12.077620499999998, - 11.6295135, - 11.569833, - 10.6606335, - 11.274614999999997, - 11.6180625, - 11.21241, - 11.595342, - 11.679987, - 11.770027500000001, - 12.469247999999999, - 12.1851675, - 10.890313499999998, - 12.221121, - 13.5441735, - 13.934398499999997, - 14.1159645, - 14.228956500000002, - 14.238196499999999, - 14.167494000000001, - 14.057389500000001, - 14.0792685, - 14.0664645, - 14.250175499999997, - 14.205708, - 14.051482499999999, - 13.8521295, - 13.090010999999999, - 12.2355585, - 11.933691, - 11.259830999999998, - 11.405938499999998, - 11.741960999999998, - 12.1560945, - 12.546797999999999, - 13.072025999999997, - 13.988023499999999, - 14.099563499999997, - 14.327659500000001, - 14.184192, - 14.042523, - 14.218809, - 13.584845999999999, - 12.786872999999998, - 11.9345655, - 11.894058, - 12.0639915, - 12.184639500000001, - 11.568282000000002, - 11.714900999999998, - 12.245986499999999, - 12.946691999999999, - 12.3805605, - 11.672446500000001, - 11.742835499999998, - 12.108590999999999, - 12.591760499999998, - 13.171141500000001, - 12.974923499999997, - 13.409203499999998, - 14.0305935, - 14.1611745, - 14.385327, - 14.394302999999999, - 14.354538, - 14.2810965, - 14.273688, - 13.994541, - 13.689142499999999, - 12.7505895, - 11.860893, - 11.8530225, - 12.0742545, - 12.717704999999999, - 13.037112, - 13.2729795, - 13.2196515, - 13.464940499999999, - 13.909153499999999, - 14.353250999999998, - 14.482016999999999, - 14.670710999999997, - 14.683135499999999, - 14.703909000000001, - 14.7376185, - 14.740390499999998, - 14.839307999999999, - 14.823896999999999, - 14.844654, - 14.914746, - 14.930322, - 14.966704499999999, - 14.9232765, - 14.951112, - 14.953983, - 14.903608499999999, - 14.78895, - 14.669044499999998, - 14.799675, - 14.772961500000001, - 14.695065, - 14.5615305, - 14.661306, - 14.911215, - 14.06757, - 12.6482565, - 12.913906500000001, - 13.544585999999997, - 13.3970265, - 13.551350999999999, - 13.504474499999999, - 13.134610499999999, - 12.609432000000002, - 12.510069, - 12.035083499999997, - 10.9880925, - 9.955605, - 8.193636, - 8.005866000000001, - 9.459648, - 9.991047000000002, - 10.242276, - 11.639660999999998, - 10.907390999999999, - 9.4936215, - 9.334776000000002, - 9.230429999999998, - 8.573878500000001, - 8.828522999999999, - 8.460441, - 8.567757, - 8.189544, - 7.546901999999999, - 7.703025, - 7.9401135, - 8.4802905, - 8.5915995, - 9.7326075, - 9.835253999999999, - 10.301049, - 9.472452, - 8.9920875, - 8.5376775, - 8.0046285, - 8.7562035, - 10.811196, - 12.326687999999999, - 12.925275000000001, - 12.740639999999999, - 12.0916125, - 11.143407, - 9.5140815, - 9.854856000000002, - 10.541965499999998, - 8.6848245, - 7.6126875, - 7.440972266666666, - 7.250029333333333, - 7.3029738, - 7.400571616666666, - 7.448818333333333, - 7.5934431, - 8.017905416666666, - 8.356126933333334, - 8.1901068, - 8.237117266666667, - 7.9804388, - 7.814797783333334, - 7.796765016666667, - 7.846000733333333, - 7.8999342, - 8.1799201, - 8.389835349999998, - 8.044806216666666, - 8.678293683333333, - 8.7405842, - 9.414703083333333, - 9.320336000000001, - 9.375752966666665, - 9.624090866666668, - 10.023828183333334, - 10.327846783333333, - 11.355747449999999, - 12.405801716666666, - 12.959773583333332, - 13.084585383333332, - 12.76457795, - 12.698743516666665, - 12.560464833333333, - 12.411818133333332, - 12.396950166666667, - 12.758759333333332, - 12.646870466666664, - 12.601442400000002, - 12.712226883333333, - 12.618651, - 12.590250216666668, - 13.120766299999998, - 13.197034683333332, - 13.065646033333334, - 13.325126666666668, - 13.365065783333334, - 13.491361083333333, - 13.388224866666667, - 13.112771883333332, - 13.238243016666665, - 13.496668716666667, - 13.588101766666664, - 13.666084416666665, - 13.61571135, - 13.611557549999999, - 13.538750666666667, - 13.04753085, - 12.939218866666668, - 12.944196833333333, - 13.233644166666666, - 13.228682683333332, - 13.225633266666664, - 13.299923650000002, - 12.610607133333334, - 10.804478849999999, - 13.78156665, - 13.281857916666667, - 10.517289733333335, - 11.585953683333333, - 14.1797875, - 13.965998666666666, - 14.182721533333334, - 14.138925316666668, - 14.104771849999999, - 13.9511307, - 13.924889233333333, - 13.820318966666667, - 13.796945599999997, - 13.55350325, - 12.945977033333333, - 13.897675249999999, - 14.066579966666666, - 14.2715667, - 14.309000349999998, - 14.3475219, - 14.452767983333334, - 14.433762699999999, - 14.320110116666667, - 14.289797266666666, - 14.404488299999999, - 14.405263016666666, - 14.374290833333333, - 14.3848072, - 14.327659483333333, - 14.321906799999999, - 14.393790616666669, - 14.415120049999997, - 14.37704355, - 14.418317816666667, - 14.529464933333331, - 14.592398299999997, - 14.624705633333331, - 14.574860033333334, - 14.51392115, - 14.64051315, - 14.611996983333334, - 14.61974415, - 14.545321900000001, - 14.502316883333332, - 14.538778016666667, - 14.525756183333332, - 14.53409675, - 14.54814055, - 14.517498033333334, - 14.481514916666665, - 14.505646516666665, - 14.532679183333332, - 14.5578822, - 14.513904666666665, - 14.505547616666666, - 14.420229883333333, - 14.437224200000001, - 14.416916733333334, - 14.420988116666669, - 14.514992566666665, - 14.53330555, - 14.513228849999997, - 14.438427483333333, - 14.44835045, - 14.484778616666667, - 14.481976450000001, - 14.45695475, - 14.499943283333332, - 14.485833549999999, - 14.52489905, - 14.431389099999997, - 14.304714683333332, - 14.274204033333334, - 14.355005333333333, - 14.331763833333333, - 14.470586466666665, - 14.477443533333334, - 14.295698299999998, - 14.01803655, - 13.681051283333334, - 13.990558833333333, - 14.121881549999998, - 14.287308283333333, - 14.30662675, - 14.411131083333332, - 14.423262816666668, - 14.47703145, - 14.461817333333332, - 14.408131116666667, - 14.26548435, - 14.096843366666667, - 14.0389539, - 14.037866, - 14.170210683333332, - 14.255858083333333, - 14.180595183333333, - 13.965289883333332, - 13.7746931, - 13.665540466666666, - 13.75644605, - 13.884290783333334, - 13.858148216666665, - 14.040552783333334, - 14.102365283333334, - 14.212375049999999, - 14.395257633333333, - 14.317274983333334, - 14.2036224, - 13.900230166666665, - 13.746078033333333, - 13.664683333333333, - 13.444367099999997, - 13.455312033333334, - 13.469289900000001, - 13.401823616666666, - 13.564629499999999, - 13.602656549999999, - 13.479591983333334, - 12.869395466666667, - 12.518465299999999, - 12.746314416666667, - 13.500674166666666, - 13.831527633333332, - 14.22750675, - 14.294429083333334, - 14.298038933333332, - 13.941240700000002, - 13.761951483333334, - 13.79798405, - 13.958136116666665, - 14.1314254, - 14.333956116666666, - 14.1622822, - 13.969905216666666, - 13.947356016666665, - 13.952548266666666, - 13.992058816666667, - 13.905356483333334, - 13.96468, - 13.839489083333332, - 13.891197299999998, - 14.115716783333335, - 14.090546733333333, - 14.0743601, - 13.957625133333332, - 13.765511883333332, - 13.845175833333334, - 13.824670566666667, - 13.709583933333333, - 13.679831516666667, - 13.585035866666667, - 13.513267433333333, - 13.543398966666667, - 13.435400166666666, - 13.293379766666666, - 13.283737016666665, - 13.360071333333334, - 13.279715083333334, - 13.141947383333331, - 13.1822821, - 13.411087250000001, - 13.358390033333334, - 13.117865233333333, - 13.089118299999999, - 13.119332249999998, - 13.071728383333332, - 12.989295233333335, - 12.605035766666665, - 12.415493916666668, - 11.822720283333334, - 12.138837650000001, - 12.418246633333332, - 12.353467133333334, - 12.374186683333333, - 12.44493315, - 12.359681349999999, - 12.194815049999999, - 12.183029466666666, - 12.54422875, - 12.86219225, - 12.825071783333332, - 12.824132233333334, - 12.5413112, - 12.824560799999999, - 12.90649945, - 12.900763249999999, - 12.531948666666667, - 12.35236275, - 12.436889283333333, - 12.021377416666665, - 11.374274716666667, - 11.323473083333335, - 10.95213655, - 10.324533633333331, - 10.780693399999999, - 11.099926116666667, - 10.768248483333332, - 10.53982245, - 9.475098016666667, - 10.995652549999999, - 10.8990767, - 10.263924416666665, - 9.889142866666667, - 10.33846205, - 10.349604783333334, - 10.142211483333332, - 10.340918066666665, - 10.308857983333333, - 10.098448233333333, - 9.656117983333333, - 9.279819966666665, - 8.665782833333333, - 7.902077033333334, - 7.692903533333334, - 8.701101933333332, - 9.484141333333334, - 7.936093533333334, - 8.906079, - 11.3137362, - 13.450137999999997, - 13.1605552, - 10.3111138, - 9.584900866666667, - 9.089138933333334, - 9.934866933333332, - 9.839063866666667, - 8.189449666666667, - 7.23005465, - 7.39761435, - 7.442769599999999, - 7.471096500000001, - 7.5495959, - 7.617336999999999, - 7.6804063000000005, - 7.747160399999999, - 7.811167350000001, - 7.902909, - 7.97283795, - 8.059513, - 8.13704185, - 8.208829649999998, - 8.2803378, - 8.37629065, - 8.444640399999999, - 8.5400833, - 8.63057475, - 8.6596419, - 7.79014425, - 9.2230544, - 8.09956875, - 8.62600165, - 8.887786949999999, - 9.542842399999998, - 9.36292875, - 7.4888954000000005, - 8.011001949999999, - 9.138402699999999, - 9.5464943, - 7.148742299999999, - 8.956498600000002, - 10.21592705, - 10.287172, - 10.381627899999998, - 10.463647600000002, - 10.50649985, - 10.59908045, - 9.109697449999999, - 8.726511149999999, - 8.806162050000001, - 7.6269767, - 7.210281749999999, - 9.99967535, - 9.46876805, - 9.238385800000001, - 10.53828125, - 9.6292707, - 7.471902549999999, - 7.6348069, - 10.27932535, - 7.83406575, - 10.050407149999998, - 10.939727049999998, - 11.28073555, - 11.331763450000002, - 11.530232700000001, - 11.5394447, - 11.537569399999999, - 11.52600505, - 11.62967295, - 11.02302985, - 11.063134950000002, - 11.842881400000001, - 11.842470149999999, - 11.9362516, - 12.04776615, - 12.12929235, - 10.7402708, - 11.9842856, - 12.0236011, - 11.95173105, - 12.064841249999999, - 9.447975249999999, - 7.19824035, - 7.383138349999999, - 7.91703955, - 10.61648455, - 10.4742414, - 9.007197499999998, - 9.7771891, - 10.1239551, - 8.963654349999999, - 11.17680445, - 10.84829795, - 7.9630502000000005, - 8.227270099999998, - 11.591262200000001, - 7.4732185499999995, - 8.40718375, - 11.978199100000001, - 12.205538100000002, - 13.01265735, - 13.18567845, - 13.162582649999997, - 13.0308017, - 12.785795399999998, - 13.247053399999999, - 13.23802235, - 13.24279285, - 13.268833200000001, - 13.28135165, - 13.30694785, - 13.353122999999998, - 13.39071125, - 13.41535335, - 13.4518559, - 13.4836373, - 13.53244445, - 13.35396195, - 13.60304785, - 13.62239305, - 13.650785749999999, - 12.926113899999999, - 12.10550565, - 13.62476185, - 13.661823700000001, - 12.692112649999999, - 9.6926032, - 10.981888399999999, - 12.971762649999999, - 12.808578649999998, - 13.13162375, - 11.556223700000002, - 13.3234801, - 10.277071699999999, - 10.542262149999999, - 11.4013634, - 12.7483552, - 13.5245978, - 13.1851685, - 13.206208049999999, - 13.4837689, - 13.60153445, - 13.633463899999997, - 13.62936785, - 13.6172442, - 13.550457200000002, - 13.318923450000002, - 12.843732299999997, - 13.4261281, - 13.618296999999998, - 13.6185931, - 13.618938549999998, - 13.63627685, - 13.65878045, - 13.6726478, - 13.679540350000002, - 13.669259100000001, - 13.6591259, - 13.700810200000001, - 13.752380950000001, - 13.749831200000001, - 13.760490799999998, - 13.71003865, - 13.66670935, - 13.767498499999999, - 13.63940235, - 13.775509649999998, - 13.216999249999999, - 12.331150299999997, - 12.8550499, - 13.0390596, - 13.4928164, - 13.351708299999999, - 13.8066824, - 13.895676899999998, - 13.903145199999999, - 13.905530449999999, - 13.98077275, - 13.97343605, - 13.951853649999999, - 13.96820495, - 13.9217337, - 14.01423205, - 13.931455649999998, - 13.82742585, - 13.638036999999999, - 13.74464945, - 13.901598899999998, - 13.850077500000001, - 13.5981951, - 13.300713299999998, - 13.09280175, - 13.0803162, - 12.77650115, - 13.17380155, - 13.34192055, - 13.52283765, - 13.396863549999999, - 13.499100299999997, - 13.71559875, - 13.9573315, - 13.8149732, - 13.878519549999998, - 13.846096600000001, - 13.91243945, - 13.930830549999998, - 13.93704865, - 13.8339236, - 13.79284795, - 13.5991821, - 13.630650950000001, - 13.77981955, - 13.832821449999999, - 13.84759355, - 13.87957235, - 13.9121269, - 13.62160345, - 13.828347049999998, - 13.855505999999998, - 13.85469995, - 13.842707899999999, - 13.83074875, - 13.817029450000001, - 13.822737599999998, - 13.8273107, - 13.810038200000001, - 13.80146775, - 13.774391049999998, - 13.7490087, - 13.7014682, - 13.731456549999997, - 13.707011849999999, - 13.7095287, - 13.673749950000001, - 13.653746749999998, - 13.673207099999999, - 13.6870251, - 13.6835048, - 13.646788399999998, - 13.544880649999998, - 13.63959975, - 13.6494862, - 13.4759387, - 13.533497250000002, - 13.48924675, - 13.536277299999998, - 13.51921865, - 13.4504412, - 13.483308300000001, - 13.479146450000002, - 13.51786975, - 13.520435950000001, - 13.4880459, - 13.449717399999999, - 13.3791469, - 13.3342384, - 13.29592635, - 13.2741301, - 13.238236200000001, - 13.173373849999999, - 13.086057249999998, - 13.05243345, - 13.1459846, - 13.171926249999999, - 13.09184765, - 13.036740149999998, - 12.98768625, - 12.9411492, - 12.90994355, - 12.79522125, - 12.837645799999999, - 12.881616649999998, - 12.888575, - 12.800304299999999, - 12.80719685, - 12.920997949999999, - 12.748141350000001, - 12.9286472, - 12.99225935, - 12.960099600000001, - 12.935046250000001, - 12.8803171, - 12.7914542, - 12.759278, - 12.762716049999998, - 12.770513349999998, - 12.7946455, - 12.793938149999999, - 12.767272700000001, - 12.754672, - 12.74807555, - 12.71241195, - 12.665562349999998, - 12.4870634, - 12.511656149999999, - 12.543355299999998, - 12.520687200000001, - 12.47753885, - 12.4579469, - 12.41009385, - 12.3600036, - 12.329274999999999, - 12.213006400000001, - 12.246482149999999, - 12.22838715, - 12.191144350000002, - 12.143406449999999, - 12.08645655, - 12.066387549999998, - 11.99275735, - 11.9591829, - 11.9367451, - 11.906181, - 11.874827299999998, - 11.84299655, - 11.8046845, - 11.7811939, - 11.728669049999999, - 11.712186149999999, - 11.6795987, - 11.6598916, - 11.62533015, - 11.60736675, - 11.55768775, - 11.507136899999999, - 11.456388650000001, - 11.406495799999998, - 11.3516186, - 11.304752549999998, - 11.2615055, - 11.25290215, - 11.2313691, - 11.192020700000002, - 11.164927549999998, - 11.126270049999999, - 11.07840055, - 11.038723150000001, - 10.99615055, - 10.95025505, - 10.9037509, - 10.875818799999998, - 10.874486349999998, - 10.8233433, - 10.7447781, - 10.70070855, - 10.6937502, - 10.665982600000001, - 10.609098499999998, - 10.560998699999999, - 10.5160244, - 10.452297100000001, - 10.41293225, - 10.347115800000001, - 10.3079648, - 10.2573317, - 10.19684505, - 10.18825815, - 10.142757450000001, - 10.120895399999998, - 10.054075500000001, - 9.990759449999999, - 10.0068969, - 9.955688050000001, - 9.91742535, - 9.857366399999998, - 9.8216699, - 9.789263400000001, - 9.7229041, - 9.642332, - 9.5789337, - 9.55792705, - 9.089069149999998, - 9.18806525, - 9.1413637, - 9.0802684, - 8.6841195, - 9.1064568, - 9.09393835, - 9.144752399999998, - 9.204449449999998, - 9.14305805, - 8.988197750000001, - 8.01333785, - 8.06318135, - 7.9575559, - 8.047833500000001, - 8.0801742, - 8.0356934, - 7.621498850000001, - 7.8465019499999995, - 7.8633632, - 7.660452449999999, - 7.4451877500000005, - 7.4302018, - 7.461210050000001, - 7.48173965, - 7.3830561, - 7.072955966666667, - 7.132592533333333, - 7.2152522, - 7.282661733333333, - 7.339751133333333, - 7.409477766666666, - 7.472105200000001, - 7.531528133333335, - 7.5635074, - 7.654235833333333, - 7.742384233333333, - 7.762646533333334, - 7.863415733333333, - 7.951580566666667, - 8.029392399999999, - 8.117672266666666, - 8.179001466666667, - 8.2426149, - 8.286952033333332, - 8.358190533333334, - 8.421195933333333, - 8.458811833333334, - 8.531956600000001, - 8.5780521, - 8.627335666666665, - 8.6811384, - 8.769286800000001, - 8.837633033333333, - 8.8857827, - 8.921886733333332, - 8.981408266666666, - 8.994752133333334, - 9.089769666666665, - 9.146020966666667, - 9.189092733333332, - 9.238228399999999, - 9.297536299999999, - 9.331832666666665, - 9.390713299999998, - 9.411452166666667, - 9.472682766666669, - 9.517775833333332, - 9.560601099999998, - 9.594404466666669, - 9.608849366666666, - 9.711722033333333, - 9.777603266666667, - 9.829631199999998, - 9.880147266666667, - 9.918321899999999, - 9.9861587, - 10.028671733333335, - 10.0654824, - 10.104412966666668, - 10.1413551, - 10.181534599999999, - 10.231508366666667, - 10.263142533333331, - 10.3304699, - 10.395858133333334, - 10.445684, - 10.490333366666666, - 10.543511633333335, - 10.588621133333335, - 10.627387366666666, - 10.654157266666667, - 10.683720833333332, - 10.719923466666666, - 10.752757266666666, - 10.786248399999998, - 10.865654266666667, - 10.927953033333331, - 10.9858641, - 11.0413266, - 11.072648533333332, - 11.121718466666668, - 11.171840133333331, - 11.204575333333334, - 11.262502833333334, - 11.310553899999999, - 11.3382605, - 11.386985333333334, - 11.409844099999999, - 11.486144066666666, - 11.526800133333333, - 11.550924266666668, - 11.563923033333333, - 11.556281533333333, - 11.609591266666666, - 11.656081166666667, - 11.709127966666667, - 11.745051233333331, - 11.768830266666667, - 11.813183833333333, - 11.828088866666665, - 11.873379133333334, - 11.905949999999999, - 11.924240300000001, - 11.926984666666666, - 11.9481508, - 11.973441699999999, - 12.017335133333333, - 12.064449499999998, - 12.076495133333335, - 12.098137833333334, - 12.117627766666667, - 12.164249133333334, - 12.1936155, - 12.200040933333334, - 12.183903399999998, - 12.270161966666667, - 12.331277533333331, - 12.330012166666666, - 12.377225133333333, - 12.365508166666668, - 12.3984077, - 12.4312415, - 12.46537353333333, - 12.4661952, - 12.4920777, - 12.5462091, - 12.52054023333333, - 12.585057500000001, - 12.601540133333334, - 12.642607033333332, - 12.672334933333333, - 12.704478533333333, - 12.730361033333333, - 12.763112666666666, - 12.788715800000002, - 12.823850266666668, - 12.838360899999998, - 12.857571466666666, - 12.8690748, - 12.893264666666667, - 12.8988027, - 12.9199031, - 12.939803866666665, - 12.950699166666666, - 12.925556166666667, - 12.968857999999997, - 12.988200033333332, - 12.968430733333332, - 12.995693633333333, - 13.043876166666665, - 13.059339933333332, - 13.086093399999998, - 13.101836533333332, - 13.093192600000002, - 13.117760433333334, - 13.128902233333331, - 13.1441195, - 13.1555078, - 13.137940566666664, - 13.1401755, - 13.170379966666667, - 13.1526977, - 13.167849233333333, - 13.204627033333333, - 13.218316, - 13.218200966666668, - 13.199006833333332, - 13.2405503, - 13.250098066666665, - 13.283802833333334, - 13.310145466666665, - 13.342798499999999, - 13.395779566666667, - 13.419525733333332, - 13.4001837, - 13.385886699999999, - 13.365903766666666, - 13.400758866666665, - 13.420856833333332, - 13.408203166666665, - 13.348106466666666, - 13.424505033333332, - 13.434529366666665, - 13.452293800000001, - 13.452901833333332, - 13.451636466666665, - 13.457305966666667, - 13.4802469, - 13.497534766666668, - 13.500081933333334, - 13.537812866666666, - 13.643775, - 13.6571846, - 13.663922266666669, - 13.658630733333332, - 13.651613699999999, - 13.654045833333333, - 13.530598633333334, - 13.5088409, - 13.516285199999999, - 13.493607199999998, - 13.496450166666667, - 13.486787366666666, - 13.481446533333331, - 13.478061266666666, - 13.494954733333332, - 13.5062773, - 13.512489100000002, - 13.520311366666666, - 13.534329, - 13.479343066666665, - 13.454627333333333, - 13.489203066666667, - 13.491273666666666, - 13.505225566666667, - 13.524978433333334, - 13.538059366666666, - 13.527131199999998, - 13.532570633333334, - 13.4851276, - 13.494395999999998, - 13.494050899999998, - 13.491898133333335, - 13.489170199999998, - 13.5187502, - 13.5120454, - 13.505504933333333, - 13.4774368, - 13.499917600000002, - 13.492111766666667, - 13.478948666666668, - 13.448481266666668, - 13.394629233333331, - 13.371523966666667, - 13.338542266666666, - 13.338476533333333, - 13.335321333333333, - 13.328813733333332, - 13.324672533333334, - 13.315667066666666, - 13.3039994, - 13.273416966666668, - 13.275947699999998, - 13.257493066666665, - 13.191135266666667, - 13.2072235, - 13.196623999999998, - 13.167027566666665, - 13.1242023, - 13.079437899999999, - 13.068657633333332, - 13.064877966666668, - 13.0498579, - 13.032159199999999, - 13.024961399999999, - 13.025158600000001, - 13.010845166666666, - 12.9852749, - 12.947379633333334, - 12.910831899999998, - 12.8725751, - 12.845312199999999, - 12.811196599999999, - 12.752808966666667, - 12.7100823, - 12.696491933333334, - 12.683690366666667, - 12.650347133333332, - 12.633141433333334, - 12.618433600000001, - 12.599765333333332, - 12.585977766666668, - 12.548674100000001, - 12.394299366666667, - 12.550268133333335, - 12.530630299999999, - 12.507738666666667, - 12.429450266666668, - 12.356239766666668, - 12.335336566666664, - 12.344391333333332, - 12.2797426, - 12.221601466666668, - 12.1704445, - 12.145071433333333, - 12.103610133333333, - 12.064087966666667, - 12.0401446, - 12.024976633333333, - 12.026274866666666, - 11.9932603, - 11.950960899999998, - 11.916237266666668, - 11.871900133333332, - 11.820513100000001, - 11.775288566666665, - 11.715931366666666, - 11.690032433333334, - 11.6602388, - 11.639105533333332, - 11.606370333333333, - 11.598843866666668, - 11.592155499999999, - 11.545534133333332, - 11.529347300000001, - 11.485388133333334, - 11.421051633333333, - 11.377454, - 11.329715166666665, - 11.2883689, - 11.241418866666667, - 11.215076233333331, - 11.164938133333333, - 11.115342333333333, - 11.0591239, - 10.98897, - 10.944435666666667, - 10.905521533333333, - 10.895973766666668, - 10.855350566666665, - 10.810816233333332, - 10.767350066666667, - 10.722372033333333, - 10.698790199999998, - 10.6525961, - 10.604906566666667, - 10.5469955, - 10.489791066666667, - 10.448855633333334, - 10.412094266666665, - 10.376154566666665, - 10.3202648, - 10.272476666666668, - 10.210062866666668, - 10.161206566666667, - 10.114404433333334, - 10.0605031, - 9.9730449, - 9.901789966666666, - 9.883023099999999, - 9.803715833333335, - 9.776124266666667, - 9.753364099999999, - 9.7031767, - 9.639382500000002, - 9.593664966666667, - 9.536904233333335, - 9.480357133333333, - 9.448082066666666, - 9.390943366666667, - 9.337699366666666, - 9.270339133333334, - 9.228253366666667, - 9.163522466666668, - 9.0805177, - 9.029426466666669, - 8.980077166666668, - 8.9105313, - 8.851502766666666, - 8.7812667, - 8.698853533333333, - 8.661024, - 8.594929133333332, - 8.516772199999998, - 8.4509074, - 8.402609833333333, - 8.347344533333333, - 8.279803533333332, - 8.221136533333333, - 8.155025233333333, - 8.085232866666667, - 8.017428933333333, - 7.954094866666666, - 7.8849434, - 7.793705533333333, - 7.720511466666668, - 7.663011233333334, - 7.618674099999999, - 7.5534009, - 7.505267666666667, - 7.441374866666666, - 7.358452266666666, - 7.3070488000000005, - 6.915652166666666, - 6.968579500000001, - 7.032555250000001, - 7.062499249999999, - 7.1544325833333335, - 7.188841916666666, - 7.290690916666667, - 7.377961916666666, - 7.4660701666666665, - 7.5308339166666665, - 7.603477666666667, - 7.659048083333333, - 7.700155416666666, - 7.7752945, - 7.845245916666666, - 7.925539833333334, - 7.974428666666666, - 8.019393916666667, - 8.097143249999998, - 8.162580083333333, - 8.2287885, - 8.27661025, - 8.328782416666666, - 8.382579833333333, - 8.438445749999998, - 8.524797416666665, - 8.592746, - 8.638482833333335, - 8.68508975, - 8.735718749999998, - 8.781422749999999, - 8.862997166666668, - 8.931717333333332, - 8.999813666666666, - 9.065053500000001, - 9.120016499999998, - 9.174421333333333, - 9.192693083333333, - 9.294033166666665, - 9.353576416666666, - 9.4208355, - 9.493659833333334, - 9.567863166666665, - 9.633103, - 9.693516333333333, - 9.7450975, - 9.77745475, - 9.807644999999999, - 9.869322416666668, - 9.898232166666666, - 9.953047416666665, - 10.014330833333332, - 10.071789166666665, - 10.127967000000002, - 10.187657999999999, - 10.260728583333334, - 10.299537583333333, - 10.37288725, - 10.400500083333332, - 10.407789083333334, - 10.507700916666666, - 10.553798916666667, - 10.599979, - 10.645863583333334, - 10.684229333333333, - 10.72088775, - 10.749879583333334, - 10.806090249999997, - 10.836855083333333, - 10.911862833333334, - 10.976840000000001, - 11.034954999999998, - 11.066475, - 11.132535666666664, - 11.1585725, - 11.189616416666668, - 11.186776333333334, - 11.2308715, - 11.315450166666668, - 11.371348916666667, - 11.407662583333332, - 11.447653583333333, - 11.477531916666665, - 11.493899333333335, - 11.530836833333334, - 11.540243583333332, - 11.588410083333335, - 11.672167916666666, - 11.706347416666667, - 11.742431250000001, - 11.75513775, - 11.802992333333332, - 11.828520249999999, - 11.853736249999999, - 11.880938666666665, - 11.910193166666664, - 11.949921499999999, - 11.974612166666667, - 12.02837675, - 12.055201583333334, - 12.091909249999999, - 12.116829749999999, - 12.146314083333332, - 12.18248, - 12.220599499999999, - 12.264021583333335, - 12.282638083333334, - 12.323285749999998, - 12.33106725, - 12.357301083333333, - 12.380317250000001, - 12.423033416666668, - 12.444407916666666, - 12.472940083333333, - 12.487173333333335, - 12.515754750000003, - 12.537605333333332, - 12.501291666666667, - 12.607852250000002, - 12.646415, - 12.636482916666667, - 12.67512775, - 12.700507916666666, - 12.700491499999998, - 12.741598833333335, - 12.772806916666667, - 12.7773215, - 12.8293295, - 12.863049333333333, - 12.926072916666667, - 12.957100416666666, - 12.984467, - 13.007335416666669, - 13.03169775, - 13.041432833333332, - 13.070276916666666, - 13.065220583333335, - 13.111942416666666, - 13.172716916666666, - 13.186391999999998, - 13.209900666666666, - 13.238761166666668, - 13.232096, - 13.247347083333333, - 13.285548666666665, - 13.288306666666667, - 13.329643833333334, - 13.339887833333334, - 13.350509416666664, - 13.371801833333334, - 13.36914233333333, - 13.436762583333334, - 13.457841583333332, - 13.46233975, - 13.491922583333334, - 13.4975535, - 13.503332166666667, - 13.524214166666665, - 13.519896583333333, - 13.556128166666666, - 13.548806333333332, - 13.585431916666666, - 13.583346999999998, - 13.617017583333334, - 13.593032833333332, - 13.630561333333333, - 13.695505666666666, - 13.716880166666668, - 13.734019166666666, - 13.720820166666668, - 13.710083666666666, - 13.710953749999998, - 13.694372916666666, - 13.713990833333332, - 13.73636675, - 13.730013499999998, - 13.6898255, - 13.750714916666665, - 13.7475465, - 13.769315, - 13.778606833333333, - 13.801458833333333, - 13.818400833333333, - 13.83752625, - 13.818942583333333, - 13.881637833333334, - 13.864433166666666, - 13.873790666666665, - 13.912057916666665, - 13.894951749999999, - 13.858638083333332, - 13.877894833333333, - 13.885298749999999, - 13.882064666666666, - 13.917294833333331, - 13.9163755, - 13.9410005, - 13.952098166666666, - 13.960109499999998, - 14.00717608333333, - 13.982239166666666, - 13.98842825, - 13.986885083333334, - 14.004713583333332, - 13.996341083333332, - 13.915669583333333, - 13.998606583333332, - 14.033393499999999, - 14.048710249999997, - 14.034542666666667, - 14.006864166666668, - 13.999230416666665, - 13.982649583333334, - 13.952065333333334, - 13.939129, - 13.914733833333335, - 13.896642666666667, - 13.945121083333332, - 13.919576750000001, - 13.896527749999997, - 13.881375166666666, - 13.867634416666666, - 13.855453249999998, - 13.886103166666665, - 13.864351083333332, - 13.878912666666666, - 13.879208166666666, - 13.815921916666666, - 13.903948083333333, - 13.959354333333334, - 13.927341833333335, - 13.962768999999996, - 13.967382083333332, - 13.889173083333334, - 13.972471249999998, - 13.981697416666666, - 13.950932583333334, - 13.92706275, - 13.93464725, - 13.942642166666667, - 13.900484166666667, - 13.894114499999999, - 13.878141083333333, - 13.870490916666666, - 13.847737416666666, - 13.8322565, - 13.824951083333332, - 13.812802749999998, - 13.796763666666665, - 13.776932333333331, - 13.784057166666667, - 13.792478916666667, - 13.77556975, - 13.732853583333332, - 13.665824333333333, - 13.62486475, - 13.592244833333332, - 13.583314166666666, - 13.563220166666667, - 13.559903999999998, - 13.517532583333333, - 13.463012833333332, - 13.491134583333332, - 13.4536225, - 13.395770166666669, - 13.414189666666667, - 13.384097916666665, - 13.395162749999999, - 13.413549416666665, - 13.403863583333331, - 13.352446583333332, - 13.361886166666666, - 13.372557, - 13.35054225, - 13.298485, - 13.225742749999998, - 13.206863583333332, - 13.201232666666668, - 13.16230875, - 13.12822775, - 13.046916000000001, - 13.074725833333332, - 13.066993583333332, - 13.05514075, - 13.029514333333335, - 13.028086083333333, - 13.019927, - 13.006333999999997, - 13.005414666666669, - 12.99958675, - 12.970299416666665, - 12.976422833333332, - 12.928387666666667, - 12.900167416666667, - 12.898788416666667, - 12.878349666666667, - 12.864050749999999, - 12.863049333333333, - 12.893485833333333, - 12.885753583333333, - 12.872702333333333, - 12.866989333333333, - 12.867219166666667, - 12.884079083333333, - 12.873999249999999, - 12.852115833333333, - 12.833368000000002, - 12.82839375, - 12.831742749999998, - 12.800452583333335, - 12.774317250000001, - 12.762201750000001, - 12.734129249999999, - 12.717991666666668, - 12.683828583333332, - 12.671007166666667, - 12.660763166666666, - 12.623349583333331, - 12.590368500000002, - 12.566613583333332, - 12.518742583333333, - 12.502243833333333, - 12.499288833333335, - 12.448741916666666, - 12.397407, - 12.355675833333333, - 12.301139666666666, - 12.243188833333333, - 12.185041000000002, - 12.161286083333332, - 12.109475083333335, - 12.086738, - 12.076477583333334, - 12.04453075, - 12.007494750000001, - 11.991455666666665, - 11.965500916666667, - 11.910948333333332, - 11.891511000000001, - 11.851519999999999, - 11.809181416666666, - 11.766678666666664, - 11.681673166666664, - 11.682461166666664, - 11.651039666666668, - 11.615497583333333, - 11.563341833333336, - 11.541721083333332, - 11.520855500000001, - 11.492848666666667, - 11.455664916666667, - 11.434077, - 11.392083166666666, - 11.359528916666667, - 11.304057, - 11.29277875, - 11.237684416666667, - 11.215439833333333, - 11.163957166666668, - 11.1101105, - 11.107451, - 11.08523925, - 11.04160375, - 10.990679250000001, - 10.94763475, - 10.902505333333332, - 10.871658416666667, - 10.826102166666667, - 10.775867166666668, - 10.733742, - 10.692831666666669, - 10.653464499999998, - 10.593231750000001, - 10.540107416666666, - 10.493270666666666, - 10.442461083333335, - 10.403996833333332, - 10.30275525, - 10.328496583333331, - 10.297764583333333, - 10.238878, - 10.177528916666667, - 10.119676583333334, - 10.066388083333333, - 10.011720583333332, - 9.993695083333334, - 9.934923416666667, - 9.895293583333334, - 9.835947333333333, - 9.766783916666668, - 9.72387075, - 9.675572916666665, - 9.609889833333334, - 9.565449916666665, - 9.504478416666666, - 9.445920166666665, - 9.384095, - 9.315177833333333, - 9.264089166666665, - 9.199982083333333, - 9.149878416666667, - 9.090794833333332, - 9.040083749999999, - 8.992770916666666, - 8.935460333333332, - 8.868234083333334, - 8.81097275, - 8.77245925, - 8.7013915, - 8.647823916666665, - 8.589232833333334, - 8.531117833333331, - 8.47400425, - 8.388128666666667, - 8.307424333333334, - 8.259684666666667, - 8.217099833333332, - 8.164451583333333, - 8.080414666666666, - 8.03636875, - 7.9774493333333325, - 7.902720666666667, - 7.828763583333333, - 7.787836833333333, - 7.723713333333333, - 7.646325166666667, - 7.579394416666666, - 7.503303166666666, - 7.446879083333333, - 7.368899916666667, - 7.305827083333332, - 6.899135599999999, - 6.967835200000001, - 7.029204, - 7.1074155999999995, - 7.186201200000001, - 7.2613788, - 7.3117431999999996, - 7.4051903999999995, - 7.4646896, - 7.5399492, - 7.6074352, - 7.6551756, - 7.7357488, - 7.797543999999999, - 7.877707200000001, - 7.943438399999999, - 8.007299999999999, - 8.0768688, - 8.138336, - 8.1887004, - 8.26437, - 8.3259848, - 8.3925032, - 8.4415064, - 8.517372799999999, - 8.5229324, - 8.561833199999999, - 8.703644, - 8.7705396, - 8.8350736, - 8.8905876, - 8.9457736, - 9.0278884, - 9.0989824, - 9.1565464, - 9.215799599999999, - 9.273872, - 9.33324, - 9.39351, - 9.4463016, - 9.493681200000001, - 9.546932, - 9.6134012, - 9.668095200000002, - 9.696040799999999, - 9.7151304, - 9.77891, - 9.8712256, - 9.916178, - 9.9824012, - 10.0299284, - 10.0695508, - 10.121948799999998, - 10.181612000000001, - 10.222103599999999, - 10.2674988, - 10.31806, - 10.3731312, - 10.4135408, - 10.4601168, - 10.506217200000002, - 10.586790399999998, - 10.630644, - 10.697523200000001, - 10.7505772, - 10.793299200000002, - 10.8360868, - 10.8581448, - 10.911231599999999, - 10.9577912, - 10.99948, - 11.035494400000001, - 11.090582000000001, - 11.139519599999998, - 11.154706, - 11.166645200000001, - 11.228030400000002, - 11.305520400000002, - 11.333515199999999, - 11.3389272, - 11.38201, - 11.436933599999998, - 11.4707996, - 11.5035668, - 11.5487488, - 11.592586, - 11.5914708, - 11.640211599999997, - 11.6737824, - 11.7005636, - 11.7400548, - 11.7641792, - 11.7782176, - 11.791583599999997, - 11.850213599999998, - 11.8996104, - 11.940987599999998, - 11.9669488, - 11.9914832, - 12.0134428, - 12.038092, - 12.0567388, - 12.091982400000001, - 12.1379516, - 12.1783448, - 12.2288076, - 12.2226412, - 12.315006, - 12.3619592, - 12.3864772, - 12.4308884, - 12.458751999999999, - 12.501392, - 12.5238108, - 12.538603599999998, - 12.5621868, - 12.609369599999999, - 12.647712799999999, - 12.658077599999999, - 12.7003076, - 12.729598000000001, - 12.7322876, - 12.793754799999999, - 12.81127, - 12.8537952, - 12.8851848, - 12.914672, - 12.8996824, - 12.9592964, - 12.952949599999998, - 12.966774799999998, - 13.000755599999998, - 13.027668, - 13.045019199999999, - 13.076884400000003, - 13.101025200000002, - 13.108175600000001, - 13.106224, - 13.1301516, - 13.141631599999998, - 13.158753200000001, - 13.150258000000001, - 13.154604, - 13.151159999999999, - 13.179351599999999, - 13.267829599999999, - 13.348255199999999, - 13.434338799999999, - 13.475125599999998, - 13.475174799999998, - 13.5589952, - 13.591581999999999, - 13.6030784, - 13.5728532, - 13.5472036, - 13.5270644, - 13.477848, - 13.476667200000001, - 13.4618088, - 13.404671200000001, - 13.4525428, - 13.546809999999999, - 13.58535, - 13.606227200000001, - 13.655492799999998, - 13.744561200000001, - 13.7604692, - 13.775098, - 13.804503200000001, - 13.831087599999998, - 13.832399599999999, - 13.845962400000001, - 13.858114799999997, - 13.872940400000001, - 13.862083599999998, - 13.875137999999998, - 13.876532, - 13.8436664, - 13.858180400000002, - 13.8648552, - 13.8876348, - 13.9049368, - 13.9068064, - 13.9154984, - 13.944362400000001, - 13.9675028, - 13.960713199999999, - 13.9489544, - 13.972291599999998, - 13.967683199999998, - 14.0709212, - 13.9699792, - 13.9564, - 13.939622799999999, - 13.960598400000002, - 13.9479048, - 13.940278799999998, - 13.941377599999997, - 13.917761599999999, - 13.884994400000002, - 13.8791888, - 13.8955232, - 13.869316000000001, - 13.843125200000001, - 13.8465364, - 13.812654, - 13.792563999999999, - 13.7741304, - 13.746233999999998, - 13.7521872, - 13.7444136, - 13.7608792, - 13.750760399999999, - 13.757828799999999, - 13.743937999999998, - 13.7336552, - 13.722273599999998, - 13.694656, - 13.6705972, - 13.630351599999997, - 13.611130799999998, - 13.631926, - 13.630745200000002, - 13.5734108, - 13.5707376, - 13.558913200000001, - 13.565456799999998, - 13.5478268, - 13.5252932, - 13.484588400000002, - 13.4594144, - 13.437520400000002, - 13.438438799999998, - 13.4470324, - 13.3819572, - 13.3787592, - 13.3732488, - 13.350256, - 13.325590400000001, - 13.299990000000001, - 13.306386, - 13.3049756, - 13.2822944, - 13.2620896, - 13.2764396, - 13.2582684, - 13.2291256, - 13.2164156, - 13.168970400000001, - 13.129003599999999, - 13.1135712, - 13.091578799999999, - 13.052514, - 13.0002964, - 12.974122, - 12.9539336, - 12.924462799999999, - 12.8915972, - 12.8508268, - 12.822733599999998, - 12.814304, - 12.816222799999998, - 12.773369599999999, - 12.792229599999997, - 12.7615124, - 12.7398972, - 12.688007599999999, - 12.688844, - 12.6536496, - 12.6249168, - 12.5754052, - 12.5575948, - 12.519218799999999, - 12.4791208, - 12.4681, - 12.441138400000002, - 12.426919599999998, - 12.3717992, - 12.334751599999999, - 12.2892088, - 12.238778799999999, - 12.1931868, - 12.1800996, - 12.163289599999999, - 12.135868799999999, - 12.110826000000001, - 12.0653652, - 12.031400799999998, - 11.9671948, - 11.931902, - 11.8670072, - 11.853477199999999, - 11.798438799999998, - 11.7321992, - 11.711322, - 11.674143200000001, - 11.6108392, - 11.550667599999999, - 11.504911599999998, - 11.4869372, - 11.4610908, - 11.4072988, - 11.362133199999999, - 11.3085544, - 11.276476, - 11.2588132, - 11.190966400000002, - 11.1588716, - 11.170449999999999, - 11.1474244, - 11.118462000000001, - 11.0795284, - 11.034412000000001, - 10.96586, - 10.949443599999999, - 10.924056400000003, - 10.885729599999998, - 10.836398400000002, - 10.7918396, - 10.7555628, - 10.7284208, - 10.668872399999998, - 10.6497008, - 10.619, - 10.532358799999999, - 10.4703012, - 10.4518512, - 10.398551199999998, - 10.3595028, - 10.338428799999999, - 10.305678, - 10.262545999999999, - 10.217413200000001, - 10.17743, - 10.134494799999999, - 10.1115184, - 10.0747824, - 10.015742399999999, - 9.9435496, - 9.900138799999999, - 9.8368676, - 9.784092399999999, - 9.7213624, - 9.678115600000002, - 9.6246352, - 9.5592812, - 9.497764799999999, - 9.462308, - 9.3937232, - 9.325384399999999, - 9.286499999999998, - 9.247058, - 9.1843772, - 9.1502488, - 9.10323, - 9.0753992, - 9.02902, - 8.9852156, - 8.894294, - 8.8366808, - 8.8871436, - 8.8681524, - 8.8427488, - 8.7903344, - 8.5739528, - 8.6129684, - 8.4263036, - 7.4125048, - 8.0831828, - 7.6100756, - 7.360451200000002, - 7.589017999999999, - 7.6488616, - 7.5301092, - 7.3885116, - 7.3064296, - 6.886766933333333, - 6.949007216666666, - 7.02269945, - 7.106811483333333, - 7.185271266666666, - 7.27198825, - 7.329657583333333, - 7.4016623333333325, - 7.484152416666666, - 7.519425733333334, - 7.631979233333333, - 7.705966366666666, - 7.7454502, - 7.82354955, - 7.7109141333333335, - 7.724250166666667, - 6.9514811, - 8.127411233333332, - 8.342737383333333, - 8.417101333333333, - 8.417216016666666, - 8.499689716666666, - 8.612341516666667, - 8.648171866666667, - 8.695618, - 8.738099983333335, - 8.7769121, - 8.835859333333334, - 8.898509200000001, - 8.95537575, - 9.014945549999998, - 9.08228105, - 9.157693533333335, - 9.216100116666667, - 9.238987633333332, - 9.327179116666665, - 9.399396849999999, - 9.4320816, - 9.495894683333331, - 9.557790916666667, - 9.61880245, - 9.6856956, - 9.735648383333334, - 9.78148895, - 9.82100555, - 9.846694616666667, - 9.920796433333331, - 9.976385083333332, - 9.997945549999999, - 10.086513849999998, - 10.117511116666666, - 10.198608616666666, - 10.26620625, - 10.318075883333332, - 10.367275033333332, - 10.400598733333332, - 10.449126166666666, - 10.488560849999999, - 10.54410035, - 10.58450165, - 10.649264966666665, - 10.699823933333333, - 10.762391883333333, - 10.797730733333333, - 10.852582133333334, - 10.913003866666665, - 10.9587789, - 11.017824433333331, - 11.059536399999999, - 11.108866616666665, - 11.156132533333333, - 11.2078711, - 11.245044883333334, - 11.269357750000001, - 11.2960462, - 11.323619349999998, - 11.3483418, - 11.427080099999998, - 11.481456383333333, - 11.515173283333331, - 11.520514249999998, - 11.60780465, - 11.673993316666666, - 11.70895535, - 11.72676403333333, - 11.80922135, - 11.870724383333334, - 11.924543633333334, - 11.95313255, - 11.970367816666666, - 11.9609474, - 12.019337599999998, - 12.071305533333334, - 12.111985349999998, - 12.168098266666666, - 12.240447066666666, - 12.285206333333333, - 12.31271395, - 12.3400905, - 12.397088116666666, - 12.448286033333332, - 12.471075250000002, - 12.506397716666669, - 12.5380667, - 12.550976766666665, - 12.57792735, - 12.660269983333334, - 12.68605735, - 12.7089121, - 12.700441916666668, - 12.765844183333334, - 12.860523466666669, - 12.931758199999999, - 12.932921416666666, - 13.012036533333331, - 13.013674866666666, - 13.029271800000002, - 12.874170783333334, - 12.51648985, - 12.656125, - 12.721117683333333, - 12.558840766666666, - 12.530923566666667, - 12.315138683333334, - 12.448826683333332, - 12.589084399999999, - 12.320610716666668, - 12.722690483333333, - 12.790877916666666, - 13.336246316666667, - 12.2995909, - 11.45593115, - 12.134184766666666, - 12.2305843, - 12.797693383333334, - 12.20841765, - 12.621490633333334, - 10.752479966666668, - 9.707632883333332, - 8.067005883333334, - 8.914302733333335, - 7.16149905, - 10.048226000000001, - 12.712647500000001, - 12.690022116666665, - 11.339806083333333, - 10.129110516666666, - 9.549943299999999, - 12.742137499999998, - 12.755883116666666, - 13.355021616666667, - 13.716667316666667, - 12.981285016666666, - 12.535003016666664, - 11.127183183333333, - 9.147126283333332, - 9.525482983333333, - 7.388146083333332, - 7.267302616666667, - 7.07057155, - 7.153143549999999, - 7.7486941, - 7.686257216666666, - 7.376939883333334, - 7.680211766666666, - 9.0925534, - 9.97484505, - 11.875328099999999, - 13.119199916666666, - 11.450508266666665, - 10.382937499999999, - 9.9925882, - 10.988252516666668, - 11.45435835, - 11.772620983333333, - 11.66373735, - 12.4358347, - 12.497747316666668, - 13.072884233333333, - 12.208352116666667, - 12.812045183333332, - 12.590427833333333, - 12.740400866666665, - 12.922288633333334, - 13.403073933333333, - 13.303168366666664, - 12.609219516666665, - 12.918717066666666, - 13.699546733333333, - 13.411200066666666, - 13.484122283333333, - 13.619497766666665, - 13.374714383333334, - 12.385095516666667, - 12.481757183333333, - 12.472222083333332, - 12.760388533333332, - 13.03266315, - 13.04672005, - 12.182155166666666, - 12.351558833333334, - 13.0626938, - 13.700595266666665, - 13.842098116666664, - 13.633669349999998, - 13.801549366666665, - 13.680738666666665, - 13.639813099999998, - 13.786984583333332, - 13.834987750000002, - 13.8447686, - 14.048708333333334, - 14.131968433333332, - 14.199992033333332, - 14.270292916666667, - 14.2535983, - 14.242687, - 14.261495066666667, - 14.197649216666667, - 14.079328783333331, - 14.0019503, - 14.040664116666663, - 13.957633383333333, - 13.834119433333333, - 13.81611415, - 13.876781633333335, - 13.935007999999998, - 13.953177116666666, - 13.932321133333334, - 13.924620966666666, - 13.8962778, - 13.95891128333333, - 13.9323539, - 13.91126855, - 13.897228033333331, - 13.863363683333333, - 13.823060683333333, - 13.778285033333331, - 13.766357966666668, - 13.724744300000001, - 13.725497933333331, - 13.68753775, - 13.667419016666665, - 13.673742983333334, - 13.610896516666665, - 13.5547836, - 13.5107452, - 13.484957833333334, - 13.516954483333333, - 13.520329449999998, - 13.471277749999999, - 13.446194866666666, - 13.395275466666668, - 13.352678800000001, - 13.351171533333334, - 13.342062400000001, - 13.286211616666666, - 13.20773545, - 13.185093683333331, - 13.167678199999997, - 13.170954866666667, - 13.146314333333331, - 13.155947733333333, - 13.126146449999998, - 13.079503099999998, - 13.050832266666667, - 13.021489716666666, - 13.004369133333334, - 12.9790405, - 12.963394416666667, - 12.944963166666666, - 12.833671183333333, - 12.759978949999999, - 12.7240503, - 12.774887783333332, - 12.74100705, - 12.755588216666666, - 12.754556066666666, - 12.723984766666666, - 12.712319833333332, - 12.699458916666666, - 12.671640016666666, - 12.611824466666667, - 12.582072333333334, - 12.4404548, - 12.430985233333333, - 12.411996949999999, - 12.47304125, - 12.268200433333334, - 12.167066116666664, - 11.838989866666664, - 11.896937716666667, - 12.0317234, - 11.8852564, - 11.814562316666667, - 11.928426483333334, - 11.983834916666668, - 11.9082586, - 12.078989316666668, - 12.206681016666666, - 12.115114566666668, - 12.050908283333333, - 11.749913683333332, - 11.540534683333332, - 11.376095166666666, - 11.2207484, - 10.995952683333332, - 10.792094866666666, - 10.04060775, - 9.439716233333334, - 9.0901942, - 8.335921916666667, - 8.718194233333334, - 8.644321783333334, - 8.575036666666668, - 8.47144485, - 7.5428702833333325, - 7.4193399499999995, - 7.505925866666666, - 7.089019183333333, - 7.654801216666667, - 8.769818116666666, - 8.479358, - 9.059131399999998, - 8.951869716666666, - 7.688075766666667, - 7.6075680666666665, - 8.057536316666669, - 7.31366745, - 7.552765816666666, - 7.1284702499999995, - 6.984213133333332, - 7.034671566666666, - 7.1196964, - 7.169581999999999, - 7.2414153, - 7.291268166666667, - 7.3606628333333335, - 7.4204175333333335, - 7.487259, - 7.5433803, - 7.6174231, - 7.679550966666667, - 7.7415479, - 7.7914335, - 7.862415733333333, - 7.880582733333333, - 7.9633489666666675, - 8.0473427, - 8.1026784, - 8.175231833333333, - 8.255903133333334, - 8.305854199999999, - 8.3692914, - 8.428833333333333, - 8.489897366666666, - 8.545085766666666, - 8.584742199999999, - 8.622581933333334, - 8.706821166666666, - 8.740061866666665, - 8.799391033333333, - 8.833368233333331, - 8.888998533333334, - 8.938376766666668, - 9.009588133333333, - 9.059375533333332, - 9.103663733333333, - 9.159604999999999, - 9.224302433333333, - 9.261356566666667, - 9.306250333333333, - 9.3613078, - 9.417445466666667, - 9.4596551, - 9.526103766666667, - 9.584058133333334, - 9.622012433333333, - 9.679934066666668, - 9.738444899999998, - 9.7747298, - 9.8060556, - 9.824108033333331, - 9.869623733333333, - 9.9257123, - 9.9430446, - 10.011620933333333, - 10.0552872, - 10.064256133333334, - 10.1516214, - 10.202472633333334, - 10.2458443, - 10.287890266666668, - 10.334338866666664, - 10.372865999999998, - 10.45519033333333, - 10.5172691, - 10.590346266666666, - 10.679430033333333, - 10.734602066666666, - 10.811639966666664, - 10.847319299999999, - 10.8916075, - 10.950756633333333, - 11.0077781, - 11.034472133333333, - 11.083424833333334, - 11.153866966666666, - 11.223179799999999, - 11.246633233333332, - 11.131739233333331, - 11.3409216, - 11.3748497, - 11.4035241, - 11.426290133333332, - 11.446470233333333, - 11.462378633333334, - 11.467959666666667, - 11.498205266666668, - 11.5297602, - 11.597894633333333, - 11.647207399999997, - 11.699122466666665, - 11.785816700000002, - 11.832821766666667, - 11.860170466666666, - 11.879515866666665, - 11.911185366666668, - 11.967814033333335, - 12.0247864, - 12.060465733333332, - 12.103886499999998, - 12.200957200000001, - 12.236669266666667, - 12.294738200000001, - 12.325065633333333, - 12.346489600000002, - 12.346325933333334, - 12.397684533333333, - 12.427242733333333, - 12.4510726, - 12.4766537, - 12.494935266666666, - 12.601007633333332, - 12.678831133333333, - 12.717701966666665, - 12.755312566666667, - 12.807276733333332, - 12.816392966666665, - 12.865001966666666, - 12.886687799999999, - 12.885493033333333, - 12.898750033333334, - 12.9278336, - 12.985133299999998, - 13.04659013333333, - 13.105297366666667, - 13.124119033333335, - 13.159176433333334, - 13.165346666666666, - 13.167294299999996, - 13.201778866666668, - 13.278031166666667, - 13.308718666666666, - 13.359995433333333, - 13.387098633333332, - 13.3972296, - 13.414741933333334, - 13.3972787, - 13.423285333333332, - 13.477328066666667, - 13.5002905, - 13.494251200000003, - 13.479472100000002, - 13.449062833333333, - 13.488293733333332, - 13.48014313333333, - 13.546526333333334, - 13.5364772, - 13.454905733333334, - 13.6705202, - 13.653728, - 13.527622833333332, - 13.293857733333333, - 12.737718399999999, - 12.763610466666666, - 12.313674433333333, - 12.384247499999999, - 13.106672166666668, - 13.467622633333331, - 13.501976266666668, - 13.508408366666668, - 13.631583899999997, - 13.685953966666665, - 13.665299233333334, - 13.623858833333331, - 13.617770433333334, - 13.6572632, - 13.661944066666665, - 13.636362966666667, - 13.635380966666666, - 13.6041861, - 13.6283924, - 13.608883333333333, - 13.562172866666668, - 13.627868666666666, - 13.658801666666667, - 13.649456299999999, - 13.638392433333333, - 13.635790133333332, - 13.649521766666666, - 13.650389200000001, - 13.644939099999998, - 13.684431866666669, - 13.665692033333332, - 13.671878633333332, - 13.693466266666666, - 13.719734766666667, - 13.709571066666665, - 13.688408966666664, - 13.686657733333332, - 13.61541363333333, - 13.6489162, - 13.685692099999999, - 13.715954066666665, - 13.686755933333334, - 13.706395933333335, - 13.7239901, - 13.737590799999998, - 13.724595666666668, - 13.746756133333331, - 13.817067333333334, - 13.880979166666666, - 13.894350733333333, - 13.9183279, - 13.914776333333334, - 13.874154266666668, - 13.830455266666666, - 13.895365466666666, - 13.872223, - 13.878115000000001, - 13.9181806, - 13.906805766666665, - 13.880635466666664, - 13.865659966666666, - 13.8523375, - 13.879915333333331, - 13.911142933333334, - 13.899440766666666, - 13.983467233333332, - 13.973270799999998, - 13.980570333333334, - 14.111732799999999, - 14.001683333333332, - 14.079588666666666, - 14.111405466666666, - 14.340015066666666, - 14.116642799999997, - 13.585364433333332, - 13.186868833333333, - 12.3885683, - 11.596650766666666, - 11.396568266666666, - 11.338826666666666, - 11.626208966666665, - 10.72288353333333, - 9.865041066666665, - 9.673911133333334, - 10.344027933333335, - 10.975290266666667, - 11.884933233333332, - 12.391530666666666, - 11.959908933333335, - 11.116076333333334, - 10.687580633333333, - 9.711603566666666, - 9.674778566666665, - 8.697393966666665, - 8.5020087, - 8.126017266666668, - 8.157915899999999, - 8.545249433333334, - 9.528165966666666, - 10.974291899999999, - 10.890396366666668, - 11.0806916, - 12.464853333333334, - 13.257671033333335, - 12.355867700000001, - 12.380548633333332, - 12.409468533333333, - 12.806933033333335, - 13.8379021, - 14.1485087, - 14.021012366666668, - 13.316361899999999, - 13.9133197, - 13.724595666666668, - 13.86680563333333, - 13.968393533333334, - 13.987755299999998, - 13.734857566666667, - 12.930746866666667, - 12.670025866666668, - 11.102230133333332, - 10.6734071, - 10.3227349, - 9.899640199999999, - 11.821185066666665, - 10.657924233333333, - 10.171785133333334, - 10.273913133333334, - 9.356512366666667, - 9.925450433333333, - 10.943260700000002, - 11.521282266666667, - 11.962560333333332, - 12.704264933333333, - 12.935116766666667, - 13.5480157, - 13.685037433333333, - 13.662500533333334, - 13.588359533333334, - 13.5390304, - 13.253661200000002, - 11.383147600000001, - 11.3474028, - 13.504627666666666, - 13.502892799999998, - 13.5022054, - 13.4084244, - 13.327867666666666, - 13.289831533333334, - 13.283153933333333, - 13.271926399999998, - 13.2538576, - 13.208554666666664, - 13.176279599999999, - 13.143611733333334, - 13.107261366666668, - 13.078636066666666, - 13.0297161, - 13.0128257, - 12.972612799999999, - 12.970206899999999, - 12.941516133333332, - 12.937833633333332, - 12.881515933333333, - 12.878095299999998, - 12.86911, - 12.837816933333333, - 12.796081933333335, - 12.770075299999998, - 12.724183166666668, - 12.706114366666666, - 12.668912933333333, - 12.653724666666667, - 12.515868233333332, - 12.633380899999999, - 12.580631133333332, - 12.544493533333334, - 12.484607899999999, - 12.434689566666666, - 12.393952933333335, - 12.391383366666668, - 12.372103433333333, - 12.374001966666667, - 12.3282244, - 12.294378133333334, - 12.310466566666665, - 12.268960700000001, - 12.167225499999999, - 12.150940666666665, - 12.127929133333332, - 12.072364299999998, - 12.065146599999999, - 12.015228266666668, - 11.972036633333332, - 11.937961233333333, - 11.8771427, - 11.818582766666669, - 11.7463894, - 11.708795166666667, - 11.636078066666666, - 11.579187533333336, - 11.490365633333333, - 11.4622477, - 11.3768137, - 11.384653333333333, - 11.337075433333332, - 11.299432099999999, - 11.246878733333332, - 11.173965233333332, - 11.123130366666667, - 11.097254666666664, - 11.040135, - 10.995797699999999, - 10.958252566666667, - 10.920331000000001, - 10.881542, - 10.859856166666667, - 10.801639933333334, - 10.6471386, - 10.563799533333334, - 9.9733393, - 10.431016766666668, - 10.546107166666667, - 10.506548933333333, - 10.4544211, - 10.4078743, - 10.372751433333333, - 10.318594133333335, - 10.2418672, - 10.136727733333334, - 10.0971204, - 10.0801318, - 10.0224393, - 9.678133733333333, - 9.580130133333334, - 9.6699995, - 9.789885333333332, - 9.7048114, - 9.300456533333332, - 9.3608659, - 9.449180433333336, - 9.061290433333333, - 7.7738066, - 8.3716482, - 7.918258799999999, - 8.039077533333334, - 8.294053833333333, - 8.353235699999999, - 8.8057904, - 9.045856666666666, - 9.018115166666666, - 8.526149533333333, - 7.6704183666666665, - 7.980730366666666, - 7.7388965, - 7.973709066666667, - 7.955853033333333, - 8.2690292, - 7.376162066666667, - 7.07531, - 8.000566766666667, - 7.7237246, - 7.866196433333335, - 7.610058100000001, - 7.734853933333333, - 7.390973899999999, - 7.382479599999999, - 7.290793533333333 - ], + "y": { + "bdata": "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", + "dtype": "f8" + }, "yaxis": "y" } ], @@ -61549,7 +31284,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61585,7 +31320,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -61609,7 +31344,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61645,64 +31380,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "type": "heatmap" } ], - "heatmapgl": [ - { - "colorbar": { - "outlinewidth": 0, - "ticks": "" - }, - "colorscale": [ - [ - 0, - "#0d0887" - ], - [ - 0.1111111111111111, - "#46039f" - ], - [ - 0.2222222222222222, - "#7201a8" - ], - [ - 0.3333333333333333, - "#9c179e" - ], - [ - 0.4444444444444444, - "#bd3786" - ], - [ - 0.5555555555555556, - "#d8576b" - ], - [ - 0.6666666666666666, - "#ed7953" - ], - [ - 0.7777777777777778, - "#fb9f3a" - ], - [ - 0.8888888888888888, - "#fdca26" - ], - [ - 1, - "#f0f921" - ] - ], - "type": "heatmapgl" - } - ], "histogram": [ { "marker": { @@ -61723,7 +31407,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61759,7 +31443,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -61774,7 +31458,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61810,7 +31494,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -61903,6 +31587,17 @@ "type": "scattergl" } ], + "scattermap": [ + { + "marker": { + "colorbar": { + "outlinewidth": 0, + "ticks": "" + } + }, + "type": "scattermap" + } + ], "scattermapbox": [ { "marker": { @@ -61955,7 +31650,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61991,7 +31686,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -62082,7 +31777,7 @@ ], "sequential": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -62118,13 +31813,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "sequentialminus": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -62160,7 +31855,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ] @@ -62292,8 +31987,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "datetime" @@ -62302,42 +31997,15 @@ "yaxis": { "anchor": "x", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "energy_Wh" } } } - }, - "text/html": [ - "
" - ] + } }, "metadata": {}, "output_type": "display_data" @@ -62357,16 +32025,16 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:21.698441Z", - "iopub.status.busy": "2026-02-11T21:07:21.698441Z", - "iopub.status.idle": "2026-02-11T21:07:21.946782Z", - "shell.execute_reply": "2026-02-11T21:07:21.946782Z" + "iopub.execute_input": "2026-03-20T15:33:44.902566Z", + "iopub.status.busy": "2026-03-20T15:33:44.901944Z", + "iopub.status.idle": "2026-03-20T15:33:45.238713Z", + "shell.execute_reply": "2026-03-20T15:33:45.237164Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -62396,10 +32064,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:21.951059Z", - "iopub.status.busy": "2026-02-11T21:07:21.950061Z", - "iopub.status.idle": "2026-02-11T21:07:21.954565Z", - "shell.execute_reply": "2026-02-11T21:07:21.954565Z" + "iopub.execute_input": "2026-03-20T15:33:45.242207Z", + "iopub.status.busy": "2026-03-20T15:33:45.241757Z", + "iopub.status.idle": "2026-03-20T15:33:45.247344Z", + "shell.execute_reply": "2026-03-20T15:33:45.246345Z" } }, "outputs": [], @@ -62422,10 +32090,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:21.956579Z", - "iopub.status.busy": "2026-02-11T21:07:21.956579Z", - "iopub.status.idle": "2026-02-11T21:07:39.084657Z", - "shell.execute_reply": "2026-02-11T21:07:39.084657Z" + "iopub.execute_input": "2026-03-20T15:33:45.249882Z", + "iopub.status.busy": "2026-03-20T15:33:45.249567Z", + "iopub.status.idle": "2026-03-20T15:34:09.736527Z", + "shell.execute_reply": "2026-03-20T15:34:09.734614Z" } }, "outputs": [], @@ -62444,10 +32112,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:39.089664Z", - "iopub.status.busy": "2026-02-11T21:07:39.088667Z", - "iopub.status.idle": "2026-02-11T21:07:39.489161Z", - "shell.execute_reply": "2026-02-11T21:07:39.488155Z" + "iopub.execute_input": "2026-03-20T15:34:09.740210Z", + "iopub.status.busy": "2026-03-20T15:34:09.739801Z", + "iopub.status.idle": "2026-03-20T15:34:10.176131Z", + "shell.execute_reply": "2026-03-20T15:34:10.173600Z" } }, "outputs": [], @@ -62470,16 +32138,16 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:07:39.492773Z", - "iopub.status.busy": "2026-02-11T21:07:39.491741Z", - "iopub.status.idle": "2026-02-11T21:08:02.616739Z", - "shell.execute_reply": "2026-02-11T21:08:02.616739Z" + "iopub.execute_input": "2026-03-20T15:34:10.179742Z", + "iopub.status.busy": "2026-03-20T15:34:10.179183Z", + "iopub.status.idle": "2026-03-20T15:35:24.528417Z", + "shell.execute_reply": "2026-03-20T15:35:24.525101Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1YAAAFECAYAAAAk3a/SAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjgsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvwVt1zgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAuYBJREFUeJztnQV8XFXah9+41N2NGk6hUNxdF/cP98V2YbHC4ouzuHvxxaFYcW2xIkVKqbu3SZvG5/s9J5xwM5lJJhObSf4Pv2HSO3funHuunf95LSUUCoVMCCGEEEIIIUTcpMb/VSGEEEIIIYQQElZCCCGEEEII0QDIYiWEEEIIIYQQ9UTCSgghhBBCCCHqiYSVEEIIIYQQQtQTCSshhBBCCCGEqCcSVkIIIYQQQghRTySshBBCCCGEEKKeSFgJIYQQQgghRD2RsBJCiGbio48+spSUFLviiita3DGYMWOG27fjjjuuQbbHtnbYYQdr6Tz22GNuX3lvTDgu/A7HSSTucRJCJBcSVkKIBqesrMwefPBB23777a1z586WkZFh3bt3tw033NBOOukke+2119TrQjQiiHUG/oh30XQMHDjQvYQQrZP05m6AEKLliap99tnH3n77bevYsaPtvffe1rdvXysuLraff/7Znn76afvtt99sv/32a+6mCtFque666+yiiy6yPn36NHdThBCixSBhJYRoUJ555hknqjbaaCP7+OOPrUOHDlU+LygosAkTJqjXhWhGevXq5V5CCCEaDrkCCiEalC+++KIyhiNcVEFubq7tuOOOUUUZn2Hpys7OtnXWWceuueYaKyoqihpzs2TJEjvllFPcIDErK8vWW289e/TRR6utHwqF7PHHH7etttrKunXr5rbfr18/23333e25556rtv63335rBx10kHNhZLsDBgywM844w+bPnx81XmXatGl25513OpfHnJycOsUEffnll7bLLru4PmvXrp1r1zfffFNtvXnz5tlVV11lW2+9tfXs2dMyMzOtd+/eduSRR9ovv/wScdu4Xu68886VfcT6uGnec8891dZdtmyZXXzxxa7v2Qfaw3fffffdiNvOz8+3f/7zn84qSZ+uvfbaduutt1p5ebnVFayaV199tQ0ePNi1c9CgQXbppZdGPP6e0tJStx9bbLGFtW/f3p1fG2+8sd11110R28B5cPvtt9u6667r2ovF5swzz7SVK1dGdOMKxtIwYcAxpU9Y5nnllVfs6KOPtmHDhlmbNm3ca+TIkXbHHXdE7Yc//vjDDjnkEOvUqZNbn/Ny7NixUffzww8/dOc57WY/OTbrr7++XXnllVZYWFhlXfaB5cD1RFv9K5YYq+eff9622247t5/8zgYbbOAsXJGOg++z1atX27/+9S/r37+/O3ZDhgyxG264wfV3rNC3tInzgHN8+PDhblvBOL05c+a447XWWmu5z7p06eKs319//XXEc5PziX6iz7iuOLcOO+wwd33HGusYi3uf38bMmTPdK9jnwfZ/+umntu+++7rrhfZzDXPu+uMlhEhuZLESQjQoDHTg999/r9P3TjjhBCeIGHAgaBBX48ePt8suu8zef/99GzdunKWnV71lrVixwgkMxMXBBx/sBn7/+9//3LZSU1Pt2GOPrVx39OjRbnDIYP3QQw91g0ZEEgMyvsNgy/PGG2+4NjAoZLuIKgZi9957r7366qv22Wefue2Ec84557iBE+6Pe+21l6WlpcW071jwaBvC6u9//7sbdL/00kv2ySefOEGz7bbbVq7Lsuuvv94NmGlj27ZtbcqUKfbCCy84AfX55587a6HngQcesFNPPdUN4BjQde3a1RYtWmQ//vij62/EoocBIYNbBtv85h577OEGzPQHf99///128sknV65PfyO66EN+86ijjnLHhMEs1sq6QF9zXOhfBr8MnhlgP/LII/bTTz9F/E5JSYnbp3feeccNwhGXiCVEyFlnneX6dcyYMVW+Q/9yHBGXCBXOHfrtq6++ctsjHjAS9C/Cas8997TTTjvN9ZUHlzrOt80339wJNUTaBx984M4H+ia8DRyvLbfc0pYuXeq2N2LECHfM999/f/fvSCBScKFFgHF+IaY41ogBBvXvvfde5fl27rnnOrHHMeAaqEvMzyWXXOLORc4T+pPz66233nLL6WfOR/os/DgwEYDop/1cp/w+/UI7L7/8cqsLnNf0G9uiT5jcgO+++8522203J/75vQMPPNBNrPBb22yzjb388svuuvPnE+csEz30NbGdtAthxvnB+Y34bSjoY/bztttuqzwGHo4vcP5w7BB5iEHOFfbl119/dZMDde0nIUQCEhJCiAbku+++C2VkZIRSUlJCRx99dOjFF18MzZgxo8bvPProo0xrhw444IBQQUFBlc8uv/xy99ltt91WZTnLeJ144omh0tLSyuU///xzKC0tLbTOOutUWb9z586hPn36hFavXl3t9xcvXlz5d35+vls3NTU19Mknn1RZ7/rrr3e/ueuuu1ZZfuyxx7rlvXv3Dk2bNi0UKx9++GHlftx5551VPnvllVfc8iFDhoTKysoqly9cuDCUl5dXbVvff/99qE2bNqE99tijyvJNNtkklJmZ6b5X037D9ttv747bM888U2X58uXLQxtttFEoOzs7tGDBgsrl1157rWvjgQceWKWN9EGnTp3cZ/RNLDz11FNu/S222CK0Zs2ayuVLly4NrbXWWu4z2hfp3DjzzDOrnAP8fcIJJ7jP6EcPx5Nlw4YNc/vkKSoqCm277bbuswEDBkQ8N+mXt956K2Lb//jjj2rL6I9jjjnGfXf8+PFVPuP8iXRO+2POi98NMnXq1FB5eXm137n00kvd+s8++2zEvuEci4Q/Z6dPn1657IsvvnDL+vXrF5o/f37l8pKSktA+++zjPuOYB6G/WL7nnntWuXY53zp06OBexcXFoVjg+LKtDTbYoNq5SRsGDx4cysrKCn300UdVPps7d6679nr27BkqLCx0y3788Ue3rf333z/isVm2bFm165A+iwT7GO28CD9Okdb1cJ3wHa7VcML3VwiRnEhYCSEanOeee84NcvwgkRdihUHOa6+9Vm39ESNGhNLT06sMdoOD5C5duoQ222yzqjcvs1Bubm5o5cqV1b6z3Xbbuc8RSR5+f+DAgZUDr2g8+eST7rtHHHFEtc8Y3LENPp85c2a1QWr4QLk2/IAuXDyFDzTDB5LR2Hfffd3AMziQRVjRT8GBZCQY7PFbBx98cMTP/aD/7rvvrlxGuxGgkYSFH9jHKqx22WUXt/4HH3xQ7TM/iA0KK/qLY8p5xnEJh3MJMXTIIYdULkOEs53HH3+82vqfffZZjcIq0gC9Nr799lv33SuvvLJy2ezZs92yQYMGVRGD4cc8fMAeDYQn6x9//PH1FlYnnXSSW3b//fdXW3/y5MnuWNPuSMJqypQp1b7jheVPP/0U0774fQ+K4fDz7/zzz4/4Xa49Ph87dmwVYRXpOg6nqYUVfSmEaJnIFVAI0eDg0nXAAQc4lxvc5iZOnOjecdnhdcwxx1TGrpDM4ocffnCuR96NJhxiEXCXCWfo0KHOrSYcYqdg+fLlzpUJcFMj/okYFdpHjBEuQuFxYLgbwU477VRtu7gSEXuCqxz7RDxJkFGjRlX59/fff+/2NwgujkE3IcAtCVeycHDLw52L36K9HmJx7rvvPheDhSsUcUZBWOYTE7Df5513ntvvww8/3G0H90nizMJjvAA3tkixJosXL3bv/jgQv4L7Gn2N616kttclboR+pw9w6Yq0rXBwNcWNinOAOLxIEB8UPG/oR4j0G8S5hLua1nRsg+DSd9NNN9mbb77p4uxwnwwyd+7ciG2I5Crqj3k4bJPYMNzd2Hf6Pxi/FPyNeKnp3Cd+DDfd6dOnu3MkeN3wNzFVNV2HdSFSX/vzExfMSOcn7pXA8cYdkPMdFzziNvnO3/72N9fnm266aTVXxqaCaxEXX1xGcT3GnZdrkX4VQrQMJKyEEI0CsSrEQ/DyadhffPFFF//0xBNPOOFF/ASDLgaIDNzrGsCNSImEHyDzm57//ve/LuCduCJilHixHoOwW265pXJgyKARomVM88uJJQqHOKZwYRW+T8RrhQurHj16RPwtvz3fJmBwzfdJerDrrrs6cUfCBkQqIg6RGkwyQGIJRCsxHCRTQLyyLgILMcBA04sDIJaNVzRWrVpVpU21tT1W2J6veRbLtnx7GVDXdN749tbWZkSOjw+sy/5wHmy22WZOcCAImDRgPzi3+IzjFTwe8fQbMUyIHeLASMTAoBxh7PuK/a8pwUesxHLuz5o1y+1XUFjV5TqMhZqON/GQNeGPN8eTODeSYBAfd+GFF7rlJLAg7ow4Mj/p0lQQE0a8IvcbYgeJWQRivWgP17MQIrmRsBJCNAkMdLAUkYgACwODHoSVH6CRyc3PmDfW7yNIeJG8AQvas88+6wZq1NfihWXMt2fBggURt+OzAkbKeBjMugZkAwtmBIvGwoULIy73bfC/hWWK2XoGnvRV+ADYz+qHw2CfFwNigvmxejCwIwEACREYpPvfQAicffbZtbbZr19b22OF7WGBipRAItK2/O8j0LECxIK3btJmRHYQBv8M3qPVdQo/tp6HHnrIiSoSD4RbUjge9Gd9+42EHogqzqXwjJecjw2VUS547keyQtZ07jckkfra/yZ9EWsNPCYfmFDhhXUVSyBihoyRXAs+qYi3Fodbfj2sG0081hWSV/DCAklyFYQWyVSo/Yc1E0ubECJ5Ubp1IUSTwowxeDcmZo1JkY6wYWDdFJBljNlj0kpjCZg6dapNmjSpUuABmdbCYeBF1j/YZJNNGqw9iLxIabl9G3ybcPFjkEdmuHBRxUx9bcKUwSEWugcffNAN0ulvsgx6Vzjw+xfLccTKhwsa/Ret7bFCf9IH9EUs2yKtu88ciRiLBd+PkX6D7UQbWNcEA3afyS6cSC59wTZEsuRE2lf/G5yzsfwGeDfDuliLajr3aQMZ9ciG2VAioy7U9fwMh3P1xBNPdP3FPQeBFhRgMHv27Ij7HbQY1wb9Hkufk2Kfew+lCci4SAZMsi8KIZIbCSshRINCTAOuZJGEAjPhDOqBWKWguxoDC9wEI7nY4S5YH2sWblKkpg6HAbkXc7jTAVY0XLnYDwbbQXCjwzpBWvTw+Kr6gDtbeE0pBn4MAhkQ+nTrCELaSer3oIsb+0Fqb4RXOMS5RaolhNUuuN+4BPI7WH+wZkUCa6P/Hhx//PHuOONmFTze9BFuh3WBbfm0+MG6TByfSDFUuJmRUh0rCha2NWvWVFuHz4K1vbDawbXXXltlsMy5x+A2Hnwq83AxgvUB965wiKfB5Ys+wnIS6ZjH+hvEc3kXt3C8WyOue7HC9Qf0t4+pA4TC+eef744x4qQ5IEYKK9rdd9/tYtkigYWQmE2gf+mfSPcS7gfE3wVFOtZM+j94fnNOxWK9De93+i7S+cgkRiTx7q2X/loUQiQvcgUUQjQouLfg/oS7GsHivt4TAx2SLjDgYJBEfajggA6xgLhg8ISLGsKFQTXfY0DCwJuEDfHAb9IWRArxDMQ5MXhHABLsjmsRBXGB2WyEBcVbiUPinbbQPmr4sF8+NqKhoN4OCSaYsaYelK9jRU0m2uJdlXhnoEd8GEVb6UdEAeKJviIYnr+D4CrHPjHjzwAdkcWsP3WC6AtEoufpp592s+gMnhFGBNljncBSQd0rrHoMXn1dIdpMXBexc1icOG4IY19glvpQsXLEEUe4Qs18hzgi9g3BSHwMMUyRrGLUOCOmjPPi9ddfd23HlY/BMWIVMY2I8u5VHE9qV1HbCyspVibcDvkurmbUtoqURKQmEGvEquFiSt+TTIPfxsULC1Ok4tOIAxKn8B3OKX/McdGkLhftCcIyzl2sG4hbLEsIJn4Dt7JI4olzgX2h2DPHzVtlKLgcDSyhF1xwgd14443uGHCNYlnhvGQbXEMUAW4OOE5cE5xj7DNtJTkFYgRLE+czQgoxzTLOC/qfc4drm2OL4EE8cV4FBSnbZmKC+mv0LdcMAoj7A9/jFSu+rhvXNNcA7sUcX44h1y4WXhJWcC2SRIP7Cm7R3JNILiOESHKaOy2hEKJlMWvWrNBdd93l0lNTL6hdu3aurhVpsal1M2bMmIipxeH1118P7b333qFu3bq57/To0cOlWR89enTo119/rbJupLpG0VJJk378hhtucDWeqNFDSvKuXbuGNt9889C9997r6hiF89VXX7l9YD3awvdOO+00VzOntt+LlWCaZ2oI7bzzzq6/2rZt62od0YZwSC1+yy23uDpd1JWij6gXRq2wSO1g/9gP0mTn5OS4+lKkt6c/ItXDYhm1ikjTTl0sfoMU83vttZdLw71q1aoq65Pu/h//+IerI0S/Dh8+PHTzzTe7ukt1SbcOHAdSk9NWam+RtvqSSy5xKfKjHW9qOz3xxBOhnXbaye0bx4q2bL311m4/OB+DcO7deuutrp38Rq9evUJnnHFGaMWKFa7fqdcVS1rtINROI9U95y2p7em7Bx980B2HaH1AevKDDjrI1XniO9TveuONN6L+Hvtx5JFHun3jmKy77rruGHI+ROsbrjVff8yXPYjlnKWOGf1Hf3BM+a1rrrmmSn2xWNKL15byPVq69ZqgPtaFF14YWm+99dz5zDlK2n/6kv31qfdJa3/xxReHttpqK3eNcKypY8c94M0334x4Hl133XWuZpq/3v/1r3+5und1SbfO9cF9gt+inl7w+FOG4vDDD3ftpd1c6+wH5/iiRYti6iMhRGKTwv+aW9wJIYQQzQlWJlKKYzXADVQIIYSoK4qxEkII0Wogzi88/o+4HJ8CHzcwIYQQIh4UYyWEEKLVQAISLFIU4iWzIkLr/fffd3Fke+65p4upE0IIIeJBwkoIIUSrgYx8JDYgaQQJP8guiAsgiQWwWkWrVyWEEELUhmKshBBCCCGEEKKeKMZKCCGEEEIIIeqJhJUQQgghhBBC1BMJKyGEEEIIIYSoJxJWQgghhBBCCFFPJKyEEEIIIYQQop5IWAkhhBBCCCFEPZGwEkIIIYQQQoh6ImElhBBCCCGEEPVEwkoIIYQQQggh6kl6fTfQEikvL7d58+ZZu3btLCUlpbmbI4QQrYZQKGT5+fnWu3dvS03V3J9HzyUhhEj8Z5OEVQQQVf369WvM4yOEEKIGZs+ebX379lUf/YmeS0IIkfjPJgmrCGCp8p3Xvn37xjs6QgghqpCXl+cmtvx9WOi5JGJjyZIlNnjw4CrLpk6dal27dlUXCtFEzyYJqwh49z9EVTILqx/nrLBvZy63kQM62YZ9OzZ3c4QQImbkht0yn0ui8SgqKqq2jEGgzhchmu7ZJAf2FgyiakVBiXsXQgghhBBCNB4SVi0YLFUdczPcuxBCCCGEEKLxkCtgCwb3P7kACiGEEC2fDh062IcfflhtmRCi6ZCwEkIIIYRIcjIzM22HHXZo7mYI0aqRK6AQQgghhBBC1BMJKyGEEEIIIYSoJxJWjZzu/NHPp7t3IYQQQgghRMtFMVaNyOs/zLPfF66yeSvWKImEEEIIIeJm4EVjG733Zly/d6P/hhAtGQmrRidkTUWyFAROlnYKIYQQyUIoVG7la/KrLEvNaWcpKXJOEqKpkLBqRNbu2c4mzV1pi/OLnJhobBGBhQzB8u7PC+zivdZJWNESLFycqG0UiQ/XFOc87LtRb51LQohWDaJqzp1HVVnW96ynLC1XKdeFaCo0jdGI5BWWWmZ6mi0vKHYioilYuabEikrLm+z3GrJwsWLSRF3gHMfV9veF+Ql9vgshhBCidRCXsJo/f37Dt6QFgnAY1qOtDevRrpqIaAyYtd9p7e7ut5ri9+IFK9XxWw+qYmFAVN3z4R82eUHyDpLZh2vH/uJeSljS8q4v0Xr47rvvbL/99rPOnTtbbm6urb/++nbHHXdUWeeLL76wbbbZxn3es2dPO/vss23VqlXVtlVUVGQXXnih9e7d23JycmzzzTe3cePGNeHeCCGESGhXwH79+tlOO+1k//d//2cHHnigtWnTpuFbluT4OKKmdFHid3j53/bLkgHau7ygxL6btcJ6ts+yZLagEFcXyc0xGWPLEqnN4W3x7UlWIS4Sk3fffdf23Xdf23jjje2yyy6ztm3b2tSpU23OnDmV63z//fe288472zrrrGO33nqr++zmm2+2KVOm2FtvvVVle8cdd5y98MILdu6559rQoUPtscces7322ss+/PBDJ8yEEEK0cmF11VVX2dNPP23HHnusnX766bb//vvb0Ucfbbvttpulpsq78K+MgPn1yggY76A2GWOY2men2/Qlq61tVpr9tqBq8G2ywHHiePu/w+F4YJGbMG2pnbHjkKQ4Nol0LkVqS6TMm4kkBkVykZeXZ8ccc4ztvffeTgxFe55dcskl1qlTJ/voo4+sffv2btnAgQPt5JNPdsKMZyF89dVX9uyzz9pNN91k559/vlvG9rGAXXDBBc7qJYQQouUQlwrioTJp0iT79ttv7bTTTnMPF2bgcHX4xz/+Yd98803DtzQpSYnrWz7W6JHPpttHkxdXBujXN4YpkUFMdcrNsPKQ2a7r9rBkpXfHnKhWSsTj+GlLnYCs6zFtLpr6XKopzo7++2r6Uvth9oqwz0MRBSyupX49xe+JWGDCcOHChXbttdc6UbV69WorLy+vJr5w5WMy0YsqL5iwbj3//POVyxBnaWlpdsopp1Quy87OthNPPNG+/PJLmz17tg6MEEK0IOplXsJVAvcHHg48aJjle/TRR50P+brrrmv/+c9/bNasWdZaMwLmZKRam8y0OhcJ9jPzC/MK65yu/cVvZ9t1b/7qBp/JRs8O2TagS66N+2Wh2494qWkQXdsAO/zzugzIEcIPfTrNRr/8U8T1EY8lZeW2urgsrv1qDUQSRTUlg+H6WphX5N49iMCZS1fbovyiSgEbtHaJxiWZRex7773nxNLcuXNt+PDhTijxbzwzCgu5H5v99NNPVlpaaptuummV72ZmZtqIESNs4sSJlcv4e9iwYVUEGIwaNarSpVAIIUTLoUH89lJSUmzbbbd1VqstttjCQqGQ8zW/4oorbK211rJDDjmk1SW8YBA4vGd7N5iONlCszUpw8Mi+tsPw7s4CEgts/8FPp9sv8/Ls3V8WuoF+ssA+sq/FpeUu1gpxFe8AraZBdG0D7PDP6zIgRwgXFJfZ8tXRs0D2aJ/tLHOQDANPhAkvxHpTtBer1PezV1h5qCJOzYPQRrR+NmWxfTZliT32+XSXJGTC9GXWISejivso1kL6mQyZlDpIVituspLMIpbnFqLpb3/7m+2+++724osv2gknnGD33XefHX/88W4d/yzr1atXte+zbN68v6zRrBttPQiuGynpBdax4EsIIUQLr2NFAO5TTz3lHkDc+DfYYANnxTrqqKMsPT3dWbCwXJHogtnA1gIDxJe+m2PLVhe7QeIGfTrUGqfiY0P4Lgzt0a7OsVVpqSmWX1RqWWmpboDaFPWzGqL+kH+x74gqxMcFL/xo/TvnuPXqsg9sgzimSC6FDKx9/E0kgp/TTh8ztfM63Wv9XYTwC9/OcYP6SNtnX3EVZJu5menNErcUT+0nBAripSnay4TEiH4dbUVBcZU+5JzgWir704A7Z0WhvTJxrhWXllluVrptuVa/Ktvp1i7L+nbKde8QTHYhGpfarrFEhqx+BQUFzsXdZwEkQVNxcbHdf//9Lr54zZqKe0JWVvUkO7j5+c+Bv6Ot5z+PxnXXXWdXXnllg+yXEEKIBBZWP/zwgxNTzzzzjJtxI9XsSSed5HzMEVZBCNjlIeIDd1sLDBCxXuStKbHUlBTLLyytdaDh3aC+nLbUstNT61zol+0//sUMy0xLscLScissKXOD6EQbUNKmD35bZOmpKTZ7WYFL5OD3f2VBsfv7qxnLbXVRqduHM3caGpe1kPdw6jLApj0cN9zKgt+PxkEj+zkxXNtMPW6itK0uA8+g6Pbfjee4+r5HKCHyatsGLnariyv60Qv+xsT3Sfj+IZKnLFpls5etttJys/SUCsGXnpbiRGqH3MwqwhFLFanY62Ltbepiwy01yUYyi1jSocMRRxxRZfmRRx7phBVxUaRX9xalcHAX9Nvw24u2XvD3InHxxRfbP//5z8p/M3FJRl4hhBCJS3q8sVU8EMgGiJjadddda8wGuN5669mWW25prQkGS8Q5fVpQ7KxIWDFqG2wgKhj0lpWX2+KSioDpulgJWI/Z/nfziywzvdxK/PR+M4MbFxYHBseIj29nLrMZSwkKN5u1rMAW5Rda93bZ1jE304nKopIyy19TYp3aZrn9qesgzc+YIwRwJazLwDWYuY/2fjplsS1YWWiT5q10n9e2HQbnbCOSKPafIQhyM9Pc+XHCNoMqf7emdvosk7hKjhrUpVK81SYGgoN3IHkGYhGwnNVm0cTFLiutIn4pklBtikG5P3/O2GGwawMJXaYuzreiknJnDYaPJi+qtC76PqamW12Oe02p8usrkCKt0xCZQxNN/CW7WCQB088//2w9elS1dnfvXmGxXr58uQ0ePNj9Hcm9nWVsI+jyR7xWpPX870UDS1cka5cQQogWJqweeeQRO/jgg11gbyzsuOOO7tWaYFBx2+EbuzgQBk/eJakm3v9tka0qLHHWpqz0VCstD9XZqsHvrN2zrc1fWWi9OlS4mzS3O+A9H011g0csDgirpatLLMVSLGQhW1NSbr8tWGXDerR3liGsWIvWlLjv4Q7ohUddYF8/+HWh3fH+FCeuwgeuNQ3+WIYoKiqlXfm2prjMZSpcXVRWGa9TH9c54rDYDnGIiEp/XoSnDI8EAi+vsMSJ9J3XGeS270WE3+9o8S7E21XsT6llpKVYQXFpTLXOvKWI9b01sbEJPz6IKh93h3WzQkCFnMikL+hH3F6nLlplg7u3tZlLC6yotMxdd0FL32s/zHOf7T+it5276/Aqv8nnuBVGc+Osb0r6cBFFuybNXenOs0TG75ufFKhNMCVSev54GDlypEvE5JNXeHwsVLdu3VyqdNzcyX576KGHVq6DuyDJKILLSGaBuzzWpmACiwkTJlR+LoQQopUnr6DgYayiqrXjkzLg/lVbIgZiSBBVkJ2RZt3bZcU8OGG7JMjAGoH159BN+7t33KQYFMWSBKKxsnkxKC8rD9ni/EK37QNG9LYOOenu5EtLqUhKj6hiULvZwM5OXPHClZIBGhaLurbrle/nub6Yu2KNG9AGv19TcP2Uhfk2felqm7O8wH1vYNdc51rJsYhFHHOcWbd/59xqA3TOhc5tMi01NcWJtYo+8WItVOt2ERc5GWnOPZLzgu0jwBFx0fBJG6YuXuX6f+HKQpdVb1Vhqc1ZvsYN7mvqV+fe2L2t9e/cpsnqiyECnxw/szL5CvuOeOQdcGEc1qOds9xxTOgD525bVOauoeyMVCsvD9nEmctdhkYskIiy72evdOKUcyOcT6cscQLt6xnLXKKO8KyUNV0bsSfG+Kv8AufegC5t3LkSq7tic+D3DWJJSJHsSUK8KHr44YerLH/ooYecmNphhx2sQ4cOtssuu9iTTz5p+fl/XRNjxoxxMVoka/IwAVlWVmYPPPBA5TJcA332XLn2CSFEyyIui9UTTzxRa5ZA4qr69u1rm2yySat0ZwjOuh+/9SA3KKttJpdBd0VMllnfTjlOaMRqbUI8/Tp/peUXltmmAzvZ5AV5biDaITfDCZtYZpEba7b5sE372dNfzbZBXXPdtrEWkHIcyxDComvbTMtMr9D4JC1g4MwAmLZ8OXWpEzj0TV1cpjq3ybAZSwvc39/8GSvlv19TcD0DcDROWbk5i8i2Q7vbyAGdXZtqGyxyrPh+u+wMJ37C4be3WKuLsxhVWBT/iq9AKNQ0wK6o85VuRaWhSpFOe0iYwW/6tP7hFgVvvcP1srQsZOnpqW54X2GFK3GCCwGDdbUmq5V35WxoIlkPseqVlpX/WW7AXPwULqH0AeeNj3vj+gCsU7jPdsrNtMHd2trgbmaf/L7YUlIqJis4p7zlDaHN9xFOiEYPv8W15+MiIfh5TddGbTFFt42b7LJ0dmmT4c7lIx740gZ2yXXbwyqLkGNfth3atV7xc42BbwfXDveRaElcmiNGrTHAzZ0sgHhlkB1w++23d3Ua//e//7mYJ++6R52rrbbayn1Ojao5c+bYLbfc4goD77HHHpXbQzwhtPjuokWLbMiQIfb444/bjBkzqok3IYTZO++8U+UaYkJjwIABrm4cNVQpa5AMMIHy73//20244EK84YYb2jXXXONCZ+oK95tLL73UhdVQQ9bz9ddfu/sJVnHuKV26dHGZufkdyjwEwQrPverTTz91Y/MbbrjB9t133yrrvPTSSy5xD9lRmUCKBHX9cJX+17/+5YqciwYSVlisEE+AS1OQ4HL+xv2Bh0prOwDhVhEGJoiIguKsqGLpuK0GugEsA2fSSDODXpfkEyvWlLoBM25lfxvRx4kqRF14nE1DZPOqSyxFv8651qN9lhu0BhMgpKelVliB/jxnGNw6UYIrZEaqs6q8/+tCl8gDt8i6gBj6ZX5FHE5BUZmzQGFFQnzUlISBATiDb9h8UGcnSGgXx6S2/aQ/aCZWD36DAXN4nJUXT5wL3gKGVZFZ/loTSWRlWOc2qU5cLMjLd1knl6wqsvbZGa7NndtkVROfCIh7P5paEW+XYq62Wog/UsyKS3DGLK0UMNGOM4IGCyrvDe1WGi5Y2L5376PvL37xB2ubneGEFBYe+HneSle7ivM8JzPNCScsVAgmBAtCjP1886f5trwEwZVRmViETJPEPHKdBYUTx9rFk6WHXLyoF20Nkenu5e/nuT6et3yNtf3z3GPfOG4fLlltaWkp1jYz3SbOXmFd6jiB0Jj42DaOPS/6ORreLZX9xApal6Q7iQap1fv37++sSi+//LIb1P33v/+1c889t3IdJgzJcnvhhRfaP/7xD2vXrp0r+ksmv0gTkZdddlmVAdYbb7xh2223XRPvmRCJD8nR4NZbb3Wut2TpZGKDDJmIlUjXWCLCOJkC4dw3hg4dao899pgrSYQI2mabbWLeDpM2ZNZu06bi+RcEcfT555+7yRvuKwsWLLC77rrL3Z/Gjx/v3JY9xx57rBNXwe/89ttvNnDgwMqEOiSZQ5RFE1Xw1Vdf2ZIlS1zdWtGAwgo/cg4S6vjvf/+7m4UDVO7dd99tK1ascAeXCvZ33nmnE1Y8eCiy2FoIDsR8djk/QI1mEfIDPWpREQuD8IgVBuwkJsBdjCK7DNSJiTltzDdOLCCwaoIBLZYLBkaIglhERKzWLVKQE/9S/qfLFfuJUKG9s5YVOQvdpLmlznKFJadn+2w3s4+YQpyXhsz6dcpx3yFmze9vTb+LBScrLcWKSs2lnke8+CQHWDGwGiFMsHAgcPz2aBttRBwR89Y2K91mLS2wy1/72WUwDI/NCcKxJukFrmlzVqxx1odwYczf/nxge+zTbwvyarUGsR6D3PzCEvt57krLykhz7nFloZAtXVXsrFCd2hS5OKGg+OE7SFLnYBqqsMLxb+ZDnFQtNSdGakvqgDUUKx6CsCbrVl0JFyzeRQ6LE66S7/y80P5vy4G2fp+/bvQIdPoBq9aqogoLHP9rR5r96ctcEeFlq4ucdY/kFl9OW1alHznHw/sb6ybup+VpKS7FP9ajWKxSsVhq6F/cLkPlIXd9ts9Ks9w2mbYAy1woZKEyc+IqO73imDY3ftIEizLn8KqiUndPyEhLjTrRw/HDfXPp6mLXj8kaYwUZGRl2+eWXu1dNMDhigFIbeG/cdNNN7iVEY5KamWtd/3ZRtWXJxI8//uiumbPPPtvS/kychEhhguO5555LCmGF+Hj22WfdNe8zYpPoDaGDkeGLL76IeVt8HysULsUImiBkDX366aerWPEOO+wwl537+uuvd+7KvqzDBx984KzvTOhglaINWAdPPfVUtw5lkhBUZPiuiTfffNMdC6xn9WH16tURxWKrjbFi9g5TIDN2BxxwgDuIvKj3wTJmGXBzIGsggcCcFPfcc0+t28U/nYcZZuDOnTu7QTUqP1YQdJg6+X0OGAkzvvvuO2sOGFQgZrzrGbO9xMIQZF+TxYSBMDPqWHHIalaX+AvczPZcv6edt9tw9xuPfznTCQSETW0gqnBXQtA4d7haqEssBbP/iCQGyrieAQM2LCwsX1VY5tyMGMAxOOZvFzfzp0Aa2KXCZY7kA29NWmBv/TS/cjAbDURsTma6ZaSmOOGGxQyLALPpFFD+aU6ezViy2okoP9vuoY2L8gpdbA5uZisLS9xg8e2fa+4XjjXJFRA9tN9nrAuHY4OonL5ktRMCZEOkz2uKJWN/SsrKbeWaUmfRYwCLqHIui39mf6T/ECXBfUFI0Hb6MvVPBcJ//E3zcMHkuOOeFh5XBBxf0pZX/E555fFrjOskeF51a5dpBSVlVlRW7qxVvgYYApmMiriGZqSnOmtUpzYZNqBzjmvf7OUFNnVRvhNfiGcsiLiFAv3CxAbXIdarIIgt3DdJpkKB5/B4Mo4Jop5X8Pj49PUIwWhFwLke1+3VrjLEKq+ozJUScLGEKSnOYEudu+2Gda3zNV8T9S2wzXXLNduzfVZlJkngPGHCJvx8YV2uV+7byRpjJUQyk5KeYW3W3qbKi2XJZrFi0O5FFSAccMNdubIiO2+ig6WK9jMe9SAWsWpTsmH27OrP2kh88sknblu33XZbxM9xRw53jcQ6Rv/9+uuvlcuwRuFF1qlTxX2Ze3THjh2dNRCwZCHEbr/99hozfMPYsWOdtQrLG9vBqh/O008/7T5jX+GKK65w//7ll19c6QraURerXasQVq+88oqrTB8JOm+//fZzvpruB1JT7aCDDrI//vij1u2ixinAyAmx0UYb1alN+H1ysDmgZ555pt14443Op51gYyxpzYkfcCMYsJY89sWMqIMdZtKxzpy90xAbvfe6dUoXzaDT1yZioE5A/6qiMjfgrm1w5QbMoZAbvMcSSxM+IK4JMvsN79nODdSwEAWzsOVmMBCriPlh0Lte7w7OSoTrWpvsdOvVMcdZIH6Zt9I+m7KkIjNdSoqznNQ0aGQf2B7CoX1Ohv06P88WrFjjMhK6xBHOVdWsbRbWjeIqYpc2pqWmuhpJWelpdtI2g6xnhxzbY73Y+oVjt1Hfjrbj8MiDZEQlwos4skX5RU44eHFVU4IAwtBw5CspD1UKI965iBGo6/Vu7wR8cF+wxCBAcK3skJ1uXdtl2gZ921vXdllu3zne/OZ3s5a78zLS/nAeYsEh0YI/fvUd6Eca9DNQJ9nEQ59OsyWrKsRs6p+ix09QcA3RBpKc8BrUtY2L4eMcQUytLChx4ogYRaxcg7u1cceQbeNi5/s6vI+JVevSNsvaZKVVuqYG8QIqXIRzHiLIyNYYabu+D3deu3sgdYXZgrwiJ7yZRMElcPLCVe7abcj4pJqStNSEF7dY2hCnfyxa7R7KnLO0j4kaJoju/OAvIclvECfYrV22bblWZycyIwl1IYSIBpk1J0+eXG38R1ZOBuWbbbZZvTuvpKTEjTVjeTGujIeJEye6GKdgJlAYNWpUpddXbWChOuuss5wFKbw+bE1wr8ZbrGvXv7wuEDKUicClcPr06a4OLW3w7cGKtueee9bqnoyrIfuGSyNja5LvsK1wnnrqKfd74WWWcD9EzNGOk08+2VoqcbkCcrJx8kcDv83gCUnyCl9pviao+UF9DwoOk8q2LhcRqh7TJr64ZGLyGZ44ubGCIbiaG2Z9VxWVWNGy6IV7cUULxn7UZTDENhl4MtjxsUI+tuvUMd/Y5oO6OJET6XexAMxKS3UD7vDZ/FhqU9UEv0f8mLec0T7EBVndKv690gkDBqgIA+JdEGEM3nDLmrp4tcv4xsAUVzYGeAhBhJPffjg+puaWdye7FNtYCIoCdb0Y0BLPhehCzAVrNNFHZM7je7TFu/95i1VN7oDB3442oPUp3YmVwnrCvrLfPtlIpNl+BrRY1zq3rYglCv2ZUREByn9d22Ta97NWOCHpY8TYJ/qJTIJYeQZ2aeMsWlgFsdwhKJesqkjuwHYQJjWl8a+vNSV8oO/rhTHpwDHk/Phj0Sp3jGkvwrZDdkX/hMf7cG6Q0ALBjsDH8sd+InCIryKRBceRAb4XrRSN9n0dbjX2xwzL7ed/LLHnvp7lSh9cd9BfD3gyWXLuhR8f2st19/Hvi5x1J1L/ce4wYZD357HjXKbP1+7Vzol9XH8f/nSa/TC7s2t3fWpBBVPMQ7zWI1xhceEtJE6xuGKCAjjH/PVC/3L8fN0+LIiT5uW5SZ7wODYhhKgJxBPCZ9CgQU7Y8DeugcQyYgEi/qe+4L4ba/kfRIiPQaoLjGMZz4bjl/nyDbXFes6cOdN5gdUFRA0WKIwUQchMytgYF0Ug9mvrrbd242asTkELV01ugIzld9ppJ2dEIaEIsXBYEn1c1uLFi+3dd9+10aNHV/s+gjkRxuIJKaywSOHaR2wVatqLJsyNDz74oDsh8PP0YA70cVg1gQBDVMUDwgr3RNwRPbgEIq7wMyXosamyE6LIuSnQL/71zYxlblA3f8Uay0qvsLg0JD52xw9cGWz6GB/cmhiE/zR3ZdTYB2abiQOJVn8pnGBtoZoGT36QR2yTr9V0z4dllVYxhAsxQ6FUrFYhN/hFXNy26/DKwTTWB4SR67MUc8Kh459ulZsNjD5oZB9IdU9mwfeXV5i8vYgk6QExOrQHoRIcEPt9Zznug/DcN7NdLNMjnxfYTuv0iKlQcLTaVPyb4H4G8QgfXmQI5DjRL5HqS/E3FrNnv5ntRIcf5GLVwSK5KK/IidPisjJn4fFCAutOn44V8WlYr7DYMDCmfhL9sE6v9k5I4E6IO1pN1tBYEmzEGk9FpkIsQD5TJGC9Q3QQy0OShx2GdbNhPdu79RnAz16+xu1r7w7ZLhEJAsmLBp8dcY3LxpjihKC3FHuRwfVA8hgEM3GMEH7u0nec1wif939bXHkOc+5h+eJ3wvsAgYxIQoBESknP79Ne2ta/S67lrSl1SUcQaaSx79/Z7MPfFjlrGy6F4F064+lvfx+A2mIro5VtQIwitDlPmCLDCojV9x/Pfe+uR1z+iHNjmU/SwsSIzzGDwGqMLJJCiJYLIgpI9sLLg3Xks88+q7Xu2z777ONczXhFg8E9ISqxEO94lJimSONNP1bm85pYunSpyyhIHzCOjRWMGuQ9wFJEHoQgiKFZs2a5Aui4VWJtwgBCLNt5553n4qbuvfde5w6I1YukPMRihQsrRGlOTk5l3Bgxb4y/cXOE5557zmVURXSFE769lkpcwoqOnzp1qjsgBNZ5FY5Kx5SLeZF1vNjiIBBk15hgniQTSrh/KG1Bqf/+++91MqfWB4IEw9NYQmpGpllapqWmZdivmZn2v4vaWreObSsterz4m5opC4ozq81a07/MRgTX999xF2xeiS1bXmJ9B3SxyZOLrVdakQ1rX2pZ5em2sthsaK+KQWok4eNrBMU6wx1rCm4/yGMwS7oEBqjDe4bcINenod9icFeXBQ7hgKhiEEwsC1YVBpj9stOdNYJB3JwVhZaaUu5SYm/Yt6qlKRLsy3Nfz3axLGUWcjWp1u/T3hasXGN/LFrjakr5zG0MkOkHtjlpbp4Tc8SceQsXwoVxY+wD3uiZDPk+g3/EbkVqcbIEZto1Y391LneRBBnZ7ob3aG9TF1e0CSHEYPa7WSsqfyszPcW11Vu/KCTMdujn5bNXOlGFhQWrFWKa9RB23lrlXbuCCRnqkxEvWhZJBu/sPy5x7CsvRD37g7AiXtBn0APOM8TQ8B5tK7MDRrL0BpNJ+CQe4cWho2UGpH3LViNIQoZxE3Hg2835SWKJcOHEPrTPTrOFeRVp2ombC8+cyD6zfySVob+xPE6YvtTFJLFd3DHxPsTFEyHDZ2w3Wmrz2oh0vGrK4hnsM0DAfvbHEuvTMduJb/a7Ikayot6cByHJZAxt5nhWJGLJt0M37StLlRAi7oyAxPEQO4RLGwP3b7/9tsZMdR6sLsFMeJHALY46dPWFse6yZX8lRgJEEJY1xrxM5ofDeBi8MIkGqdXJM4ArYKzgpkc4DP3kY7zCof4sJSA8ZD7lexdddJGzjJFCHUME1ijEKUXSvXUP6yGCNJg8ZO2113aeZYxLvbB66qmnXF6FSMYULJGtgbiEFQcccyrmQ7KKYK4EanjsvvvuLmmFFzgM+LFiNTaIjkj+oUHTazRhxQUQvAjy8vLq1ZZIFxSUlxSblRS7GeDS1Wbzli+0eRVdVwXU/rczV1fLujdt2jR34sdLx/88ZbbtWlWWsf3pM2bZmGvOsr5dO7jj9WUU4Rb+9ybZ2bZqUpbN67VrZX2XcB/hHil5trxgje26Vq69OmmxkcMNMbH7ehUzQX7wt/t6PSpr+PhMdCSOYCBHrIx3bWz/ZyY8UrjPWrbGdl+v5lP4L0tPsa0pLnOWLlzgyD7IYLasLOQsCIib57+ebblZabb9sO6VRVERHww8sVYgSjLT0mpMPuJBkIQP8IOwDOGIxamsPMW5tWHVLCohlXrk9Of0DZa/POoftamwyvA7xCXlrymx9LSK1O1YvxCJ5+46qPK3GNgjFPiOF4++r0kiUlBc4DL/ITp8MWIEhrd+1jfuJzyLpLegEcdDm3Gloz30CS6aWKPmr1zjrFq4mJGJ0LtX+nZHykoZbrmN1G4vJnEpDB4b76K5vCDLiYU2WemVv8dyjpUvqOxTw1eWmOBcCpkTVtEyQdIm+n2jfh3t1/n5Ttwjqog15HgRz4Q8JubKx0rGQ6QMhrTJZ/oLT4XOZ6SmZz+ISZu+eJVr14wlBbbF4C7OrXLWstX2w5yVhoc3YhBh6q1TXE+f/rHE1Qn772EjkjYboBCi+S1WWE6I4fEwYb7uuus6L6maMmsiWkhNzmC/roIoGl4oRQIXunCXQu86yLgTd7xI41SINF7ykBMAYwAJK4Iug+wf4oZ6VcRuMQ734IpHjBQJ3KhTVdP2g+Nc3PXIBkiyt2eeeca5CjJ+B/5GJPl9xGLId4LHxlutzjnnHNf3jH3Hjx/vsoJHojZB2WqFFSZMDgadjdtd0PWuOamP6RUFTo2EhsLPSsQLbR45ILfarHN9t/vFjHw3CL/2gA2qDCYn/vCTzfjtJ6ueuiA23n///YgXMhf53ltHMN2nptlRV2fbaW1y3DFLTc/E2GYp6ZnWvk2O9ezc3lYUmW178InWdsAGrh8Y0DJ7ziAOfn37SevRqa29Orez5f3YJ6Lw8/8uWr7Ydh+YZQvyS+y7eattST4pIFLdQJJ7ZsfsdFtWUOKsV8wHMKg/Y4fBVcQH1pQl+UXOhTCSu1ckSKfuExqEDzZ9WnG2i2jktxCSiAhcInG1CuItDliburbLdjFg3p2U43n2MxNt+eoiFxeEpS38txAv3dqZG7AjUHx7cMmbvDDPCklhXlRqaS4xSKFtO7SbE2ENld3N9yOiFOsZQgL3uG9nLrPvZy13taqGdG/r3GW9YMTFjKLGuOdFsrj4f4d/VpOFzWcGXLyq6E/xaJXp472LJr+LQPpjYb69/sNcJ0pxASQGDMHlhZNPmw9MI1U4IZoTg5yvfMdbxMLbhMAhUQb/xnKWmZbq3HVxMwV+M96aYdGsU1ieorn6ci0UlzCRUeDO8YLV5cYpyPnm+2fnWz5y8Y7lKEiXeIPkKWQ1ZHIg5NwbvYBLpCLHQrQWygpW2pw7j6qyrO9ZT1labu3WnkQRVj6hgmedddaxTTfd1F588cUqwooJaFzlCD2h9A/Fg0mYUFsB4UiCKJ4Yq0guhd51EJdFsuYhRIIJLCZMmFD5eTQQZN5Fj1ckqw9CxmcKZFyIhxReWVidEKGxQAwW2zrqqIrzBRFHgXQPY7pgkg2siGw7vD8OP/xw55GGMGOcnZGRUSUUqDVSZ2GF4rz//vtjPnhNRX1Mr9TZCroqcjHgf9qcwmrDzrnVBib13W5Zarpz3QkOrHjvnJ1S7/bWxXJn5WVWtGa1e4WDDWDWn39fd/E59mtWhbscA0L3WxlpVlhUYtPfetCIkhlvZmPq2N5ee/7dem25n3VIT7WColJXWDk7gyLEZjOeuNjKO6Tb5PZt3H69mpVlheWptqig3JasLrcFlmYLxuXY7Pf6Wf9uFRY+/+LmT5E+H6fCwB2rDHFgWHWx4nrht2GvNs6PedOBnauIXO+mFi7egimwXS2k7HTXLwxkydp31k5D7Ia3J1tbV2+5whUQAcM2/aAeq1C4JccVxU1Ls7yy0oo6V+Uhl0zhi6lLXJHp+hSGjmRFoU20ARdLtoPrH/2+srDMCUWy/BWWtKmMvyPpA+/hVqigVcZvsyYXzWBCB4QzhaNXlpRUSx/vxVWFUC22H+fkudg6RLLv+/C6ZcRJVSQTSXHCljT+WHWIB/PCKtyKxG/4fuQ7xHON6NfBicqK+m4VMYHxiJOK+L78Ku6kwaQj4YKTcwUxiDBH3OMWisgD/u1rxxFbheCsyKqJq2SmlZZRU6zMJRrB2gWx1rcTQggPLmlkco7kyocn1LXXXutc/RBaQEIL/o34yc/Pd6nHw7PQNWaMVU0uhVh7sARhefJ1rBgP4XqHK54fXxKPT9wTGfx8Fj/2P1IKc9wD2U/CbBCQ3isIEUMeg1dffTWm/QdEGFYl0rk7jwvK4vTo4WK0PPRtcP+JryKGLRzajbUMF0LGqHvssUeVjIStkbhcAUeOHGmTJk2yRMJnFIzH9MpgtyETWxA0SFpJLiRONF7+70mzFtsLE6ZZTlrIurdJta0GdqjyOa9obWFWhpM2fP1I/46UJjQjI9PKysurubKt1bnmGZ7aiNbehhCY+27413HDikP2t9Wp9Sui2q9bB9tyaDfnjkVWPGbei0tDlpuZanmzf7Mfp9YcWLqI9PTvV1/OjR9hxaASS9WvC/KtS5tMJ14uOvxv1UoOOItZRqalZ2RZ2zY51iYn29aUpdqa8jTr3L6Nbf9QhXCjXMEWex3qtkvMFGB5ZJD/ydgXLevXikw9IwsLbPLiQltvUDf75L3frag81QnEAzcbZCPbZVuX0iKbvKTIBnbt7qyJU5cVO6HaPifdurTNcNYKRBUszi+2l76bW6UgMMlEiHMiUyPEM3D2Ig9LSPd22W6g7iEBBPE9xCKxDlat3D+POeKKLIKRYvoiFRkOZh/kHZHhi0ST0GLuip+ccIqUPp79wjWT72A9xDWzZ4dsZ53BLdWLFJ8cAxE9qGt3+3neShcr5ww63k8uCkGhRfu6t8+xyQvynAssVlmf8TIeOGZkV2Q7QasX1spIgrjCWopLYrmtobZZWoqlWYor2I0LLO3DaojFuFeHbFdDjZjHrm0zbMoiyh9UWK5GDqhwTUHAxxsfJoRo3fFVkUI2CDPh+YrVBGGFdYUQE56p1GPihbCKpWhtQ8VY1QTiiTEgk/aIReKNHn/8cefGR43XYCFhrGdkrqbWEyBKvDteEG+hCn5G0onXXnvNWaxwb/QFgT2REkgAiSkQZEHrIGKQMkpY/uD111+3N954w/2NeEVokdwiErgD+mzcV199tbV24hJWHGD8LFHWVMROT49rMw0KplV8SxEUwQQWmF5zc3Nd2vWmgv4Ir1/g+alouq0/qo+bNR9KIDuDxRG1pywHAgLfeuutmNrw3Ywldve4X6xNesiW5622kuJim7omxzYe2LlawofdtxzhZlJYf1neamubUW4HbtQzqmjj39MXLrc1awotVFoSNai0QSx3fw5AvRWI+JuFi+u33XN2X8/W32aQc/kqLMl2A2gGh3mFZVZeWlJvy50f4P++MM+JFRJFRLLeYbEqLS5yr8LVeRasqZ4/z2zmn5NHiLVTwiweJHfAKvH+w8/bu1OqTnJ8GPY7N0Rp75a772+HnHeDi/nx6fpf+HZ2Rda6cffbwvmTbUZ2tv38cHe3bxNm5tma8lQbn5Fls4f2tEkvdYnogol7wa677hrxN7/6+Q/74Oe51rV9GytKK7O2aaVWFEqz0lCKsxq2zUxzg3TE/7tzVzoLKxATxz5HSlYSbg0KCq1ghjxf0Nqn/8cFj/pckWA5SSZISIGbHoKJ348U+0S8H2DpwSXOw79vGzfZCUSIVKPKx78BohERTixc8PO6ClisXkDfYXnDmkm/RbMk0dfE6JWUV7gyIqZG9O9YmdwEF0jnKlha7tw3qR/myxG0yyLFPVbHcifERw7oaFsO7iprlRAiroyAkSxWWGLatWvnrCZYgAg/IGlC9+5/TeCQ5ru2xBVNyRNPPOFcFceMGWPLly93z3GESm21ouqCd9VDBPEKJ5Kwog+xVGG1CoI1CvF65513urEJITJYovx3GOeRnj0SCDsEK+Pv/fbbz1o7cSkixBTi5dRTT3U+oH369KnmaseD2M9ANDRYoQjWwxyKPyeglsmEQmFir5xJeU5dKw56U6Varw0/6GYww+x/pOxkDcEmA7vaOXtuWCXV9O8L8mzi7JW2bq+KOCUPJmCOabsNZrtBFC5PB0SpdxXJJWxIlPWYWVq9enWlGLv5zZ/s3R9nu7837tPGTt92QI3Wt5I23Srd2bwViBTr/Tq3sW7rbkk2EEspK3HisW16KKIQJFA1HM4F7/LFdp8cP9PmLCuwUHmpGa848eeYH+gTR0PtIgak9RGZkVwtGfDinpYWir+9vTq3rxQbPl4oKyPNemVl2NKV82zNvN+NIf9706p/9+3vzd6Osl2ut3Bh5c+Xay6/1GZOeKfad1LT0s3SMly83ZTcHHs5K8vKU9NtdWmqhdIynLV1/lrD7Zh//Dui2MC1440PPnMum4N7drIhvTrbz7OybMWqMpu1ssTW7dfFhnfqaqWLltsvedn2x9RF1iM9zeYtXGyrV3d2wbtBXvthnnPlI2lkTma6E8e8fIyYF2jBVPRkaZy7fI073rgFMnnywCfTXLKaHu2yKkVZ8NoJfj94D8D9DutVtHp3NYGAw51w6epVrv3cX3za+UhxZ9wbSMwCyEJyX5LSnjgxrF9YC82Wuf4gLpDaYYAFkeQyM5autmWrip1L4/fu/tK+Sh8JIURtkJgrWnIuxnnBpGKM7YLuZrgREjtFvFWiwHObmLCaEm6QRh4REwsfffRRTMtqA6MILoWRIDsgr3CwFGI1jGZEQQ/wGc/+7AjjFaxx3iLXGog7KyBuaaRibGjw+8RNyWdDQYWTbQRIPYlqxryKWTUYWIiYwqJz/PHHuyJzXHRkkcEHtSETU9QXP+hm4LSmuMTFJ+zaAG4zkWJfwmfyTxvzjYtVipR8wRftZYD19YxlLvYkmOQi2n7UBOIaayEvOHb3HPtonllxYaktyc11N5WaCMbO+AEh8Uq0c78nnnMWBdqJO1d44WPfHxv362Brd8+tIro4d4P7wGD55ncn29K8Muuz//m2drcc23/D7nbPe7/Y8vwCa5cRssGds+zbaYuspLjIiZmRfdtaVkpZFREX7m4ajBEa28DCij6gTtUr9dhu7y7tq9Q5Il6oQ3amK2KdFqq/5S4Ix4J6YitX/VVPLEg5MV5lpVZevMZWFKys9jl72TmXQscVmfqqZb17/XU30xYPdwwZ4jIxBcEaQxbApd+8abMmvmU/Z2Ta17k5lumSrWRZekaGrdevq2VmZ7lEK327tresrGzLmpFn+WvKrcTSbGVGjuWut5PbHskygq6K8xYusYWzp9sma3W3vKJCG963u5sEYABB7BzCCCvZstVFdbZasS7WNQQeBZO9W6G3SlI/zScI8ck+cHXEOkc9sxRLsXd+XuhEFuKdODiKeSOigsWVfU00jklhVrlzM6YuGec8rpS+LUII0ZAw9rz++utt9uzZ7nlD+AXjjVjqpYq6w1ht2223jfr5K6+84iyGuASKOIVVPCo5Vgj48+nbAQsUL2/WjOZ2RkpMzJXMeNxxxx0uOwmm4scee6xRBGBDCJ/0tDQb2DXb1SeqL7WlmOb3GWClppQ4l6Pw9vjv417GO+mWYw1ADyYG8Jn0In2PZczaE9xPHEZtA8agS1ckIYdAZBBKoH94W/3+YKEb0b9z1AQbQJa8gV3aODeu7pvvYTtu0MvO3Htd+6PrRLd9LBEItytem2Q/z82zTm0ybTvSnO9dcwIXjitp5aknxU3Hi7CgGPtp5mL7adYSy7RSW7GqwAZ0zLQebdKqCEF8x6P1zTbbbW+rl61duT7bmLVopZUUF1a4NZaVWGp5qZWVFFWLu/MWNn/8vCsalorpKRXua/EQyTpMex//YoaVRrAgxkqvzu0qLWwN6naa9pfrnWf/Eb1dbbPFq5Za4YKpblm4JJxakeApKqk57SuFFfFJwSQlH7w0xp689fJq32FwkJGZZaHUdAulZToht/vNOdajU7sqbpe4BIfX7AOKP/KQm7x4ja1eVmxtsrNt6oJsO/3DkK0qSXH17FLSM2xA945WtqSPZW85xDpkZdk/t+lhd31SaHNWVcS6UVNtVVGZO9d91kqKKyOivDtmZnqazVleYB1y0m1o97aVte065GRWKd4shBANCbHmuKkRU9W3b19X/JZnbKR7oqg/F1xwQcTlhNrgwklcFRkFt99+e3V3vMKqMSG4rzYQS7zCwceT4rq8Eo1IdXzIxEWtnpUF8Q82PTWlmPZJBxgAkcnL1wMKtsd/n7iKX+blORfFmuo1BYVZRRayVa4eDzPbNQkyYlt8AoTahFssVjGsCgTph7e1LkVtfepzCCYnIM6G2Xreace+G/Wx1UVlLuGFT3VeE8E2+AQp4bF3wThd36fZ2enOqrdtDa5Uvm+O3/qxalY+LENYHXHqapOVYXuu39Mu2Wsdl542KOq8JTEYh4RYpB09886zTikF1v1PkffZb/Msf/Uam7cszxYuy7d0K7WebdOcdS/cBTNaPCPnVBm13OIEkRG0sDWUsCJuLAj7jyjeDaH5avyulpQPAOpTbfpnYgdPaZR+wC2kuOivfSldZVaw1GzBrKoxnNEGELhfkz2qNrjLfmxm4dLu2LvHWc8ePZzbYzDZBbVJrjv/RCtNSbeObXMtKzvblheGrCwl3drk5pj17GQfjG9nBYi30lS7+qqrZK0SQjQK3P+ijQNF00EyCxJmkONAx6IBhBX+rrjakaufrCekYCfDCJlJ6GAC2GSWjV7Hh3pFDGYZdMVaF6kmahIhzCLjFvTzvDzbanCXysK14LN3+e/TTpJEEM8UKVGAJzzzGoN4YrOiWRQ8xJEEC73WB1yRyCpHGujwtsYiyjy+HUdu3r/Kd7y7nd826xGPRaA+wfu1UVsbolkNic3CxSqYLjtWOL+Iq6Eo8idTlrgU2tSKwvLGtnA1o/p6pOQJwXPhv+cfX2W7O/3ZVva/eFmBZaSn2kGj+tdqtfPw3fTUVOtz+JWWkVJm263V0f691zAnxn6YscjG/TTHJfEYNaC99WmXXinUpsxbZq9+O8OKigqt7/Dobh7c2Ln31JQt0/8dHndHZsbwtnqhmZtePbtmrKSkZbiMk+2y0qskyWD7eatqzjxZEzVZX+ubMOa0XdaxXxf/ZW3y1zd9O+W3irTrkQhG0xJkvuEjd9SrHUIIIRIbidsGFFbEPGHyw7916NChLvf9qlWrKuOvEFm485FvX0Su40P64rZZqS7GCutVY4KLDvWUSGP949yVbrBEUgVmpIP1bTy4DCJaiGeKxRrDYJ5YDAaPsSThqIvoiQaC4IupS10Ws0X5RdWSCtSFaO0Jt3qxDum/S0rLbeKs5c4SWJ+kI9GshghU3BtxyatrfI0Xg6TuXrGmxNaUlDtrYjTrYDB5AkTrQ99HL303x4m+ttnpEc+daLBNBOPytjkuycEnM9fYnV8utusO2shlEdx/x80jfo9YxMyiYZaVkmLrrh+9pgh16IK16GoCl0hE1v8mTLX3fppj2w3rVq2tFantu9vgC86029Za1/JXrbHi4iIrLiqyvNUFzsUSq12nzBTrnJNiqeUl1rd9hhM2i1essukLV1hxVgfrmJPpMuUFhT/bf8UaNoatoYTVpmv1sC2GpVeLcexQh+3W1D4hhBCiJROXsCKOiawipHok3WUw5aXPs+/z3wuLOGg7eGRfZ0kiOzN1ehhARkrH3BB4KxGWqHkrCm3lmhI3YEJABWv9+LYxqGedWC1pDBqxcLE//E5TBKx7971pi1fZsB5tXVujJTaIlXALUiTBRaKMX+fnGePkez6aGlVY+W19OXWJy5S289rdnIioTbjxQrDd9O5kKy8PuUQDvo5ULPhtItY/mbLYLeMci+bWGSk1ORbNaEWAceX0mSPrgs/CyLafGl8RQ0lR3Fjo0T7LpQCvi5Cr6bjiRkIW09mrUy2lTWdbWFo1o2nwuG/YdwfL6DHYndv0KdcqcYirCkttvT7t7ajNB0SMK/SihFhC71IX3P4rD99uJffdHNG6dtHz39gf85Zb/04Zds4Og+zylybaohX5lplSZodt3NMGdItcygEGDBjgapFMnb/c1hQVWnFhka1Ytdq5YPIqL614D5WVWKi0GN/DKi6GwaxPwXPj51m1u756EiUDqxBCCJEUwurdd991BcbWXXddW7p0abXP11prLWfNEtUJ1mUiqx3pw7PSU527FlYf0iI3hjDxxUy/nvGVy6mcnpZS6W7mi6f6QRRWCQqG1hRHFLS2eGsE34knPXRdCCbKQJzSdtKEk0UNKxzLGisBCJDE4oPfFrpYKwL3o1mt/La8VS2SiIhmKUMkrikud5YVLJvxWkY36NPRFa1dr/df7oy1tYF2Iwai9QP7SvviSQXufwtrKP0yol/kRDRB4hVTNR1Xfw5VnN+hmK2AJCHh/Lrh7cnu/JuycJU99sUMJzbD+yFo9fJtAL8eSSoyMzPdKxh3R9va91tl6/Uqd9so6tnOModmW4fCUldselmv9nb4jtFdIvfee2/38vuIy/Gv81fa/BWFLhEFLqzEDZaHUmyrwZ3t4WNGVhF10c6NDlttZU8//bRzzfxj/jKXYKVLTmpEYRgtwZAQQgjR0olLWJFxr1u3qu4zQaLlyBd/4S1DZN8jUJwZeaw+9bG41Abb3XZoN/v8jyVOWGF9QVAxkA4WT2U560yYvjSqcAjP2EfSB/4dj/taXQjGv5DIgN+i0C8ih1TR1NqJ12oWa8KLId3bOisUk/0MrGvqH2Lavp6x3Pp2yo65Xxjwp1jIUlIqUrbHA79P+vStBnd1MVd1iWdrk5lmvy3Icy6k0Ymt9kYksDQWlYYqE4bURDD2LN5rI/y4+u2RctwXR47l+4gpLFeDurZxx7K4DDfLfGfBCz8HgqIk6FJXW/u9JZaserhMXvrKJHeeZaalWHpaqosp5HzH+hdL4hcs4bOWZVib7FLr0jbLBnZt49pMBszObbJczB0v4qKiZS/1ljBeQgghhIhOXLkpsVRRuTkapPsl9aKIDoM0stkxwMHiwgCawpuNnaIYiws1a8rKQi6hAaIKqwAixQ+kGHCS7AJ3JwaNkajISPfXdxiMT1mU76wZuK81FvRPMEGGF3WkiF5TXGa/zc+z4x75ym4bN7nO2w7fp0gw6GyXnemsjAx4C4rLatzWA8dsZmfvPNS2Hdo9kOijZuh/BsG9OuS4/mSwG6+FcsvBXWK2gnrBwW8Gk3aEw/myw/Du9bQmheI+5vU9rn574ed9bd+nP3CrxE12nV7tnCttRlpqRLdIjhmCive6tJ91uA9wzCgVUFpWboWl5S5ZCPcKLE5YtoMJaKLhzxvO1f6d27hzdb+Netvmg7q4dlMDLvzcqp6URgghWg5jxoyxtdde200odezYsbJOU211NX2pIbwNGrPkUFPQUvYjFihMzL4mvLA699xz7dlnn7UbbrjBVq6sKOaJ29Iff/xh//d//2dffvmlcxUU0WGQRhFP3OdwzSF2w8+MxzOQrutvY9lZsqrC1S+8sC6QnKD8z8QQsbTn9R/nu0Qcy8lq98tCZ+lqDMIHybQNCw+Dx4zUFCstZ/9K7JXvax94xgPHiJgu4mZ6dMh2Na5qgvbhjvXV9KU1pq8PDsaJ5SHT4fwVa1w8VyyD6HiFYhAvALBU1UfI1Ab7l5ORFnPSlrruR2Ntj/7A+kfxW4TKhn062C7r9HCTFeHEK1CCbSOzI1YqJi2wbJOKvbC4zNpkxeZo4BOTMPHQKTfDtZtrH+HORAQW8/BJkPqKWCGESFRItHbcccfZ4MGD7cEHH7QHHniguZuUdMybN8+JFXIsiAZ0BaRQL1n/qJcyevToyoJtPPgJDP/Pf/7jEliI6PiBy8RZy+yPxatdBrdb3p1sI/pViKvGdKUb3qOd5a0pcWLEB+V7VyY/GOvfOdey84usQ05GTO3BdcmD5ejmdyc3SSILRMc3M5dZWkqKdW6b6axsiFVqJjWGS6LfHmKO+KdgGu2aXD5ZF+tfTX0SdHNEeGSkp9niGGtmNXT8X02CgM8mL8h3roZ1jQlk2/QDx6ghygw0Jd4KyP4T24fFKnje15YUpK7X9bm7Drd+nXNdf3EOLV1d7MozUGw4Fmuh/23cSrGy0V6W8Xrjx3kuOQpWq/B9bIrkM0KIhiclI9s673patWWiAiw0GAHIWB0sB0TegNbEdttt50J6iPGNR1hdeeWVNnDgQFfmRDRgHSsEFdapF1980VmqOFmZBTjwwANd8gpRM34AQ9KH1MUFzuXnxzkrXYFeH/DeEITHTHhBt/t6PeyOD/5w1rJgjEgwa6Ef+MYye82s+IRpy5zbEk5eWMQaUyAGcTEoGWm26YBObjaeRBa4OjVWIg32C8scyT9qqvUFPhnIqqIy5/pZU5+Ep7D/fs4KS0tNs6amNiHg47fiiQlkfUQVA/1EIFpMUSzic/TLP7nzIFLmxkhJQepiBQomaWFyAzfANSVllpGW4a61WNsKp475xk04cE36Zb06ZNtva1Y5oSaEaBmkZmRZu032ae5mJCzUXAXvAuiJR2AkMxhAEq0sxurVq61Nm9rjrpOBuFwBPf3793cuf3fffberwHz++edLVNURBEz/LrmuPpJ3MWtIMRAcJAcHkQipjft1dG5FwRgR74qEZcXXuYqlPeftNtw27t/RsjNSjbEaw7XaXN8aAtq31wa9bM/1ezrrEdYdrAkks2gsS493B+yUm+l+K5qrpO9vkoEM7pbrLA01Da6DbmAcHyyLZeUWUzHihqQ2dzBvuYknJtBbTHZau74xWg1DfVz2yEKJpbS2zI3xuB76dmFRRsAiRttmpllxSZmbOIjV1ZbtIMqImcT1l3OS17LVJe76JGmOEEI0NXPnzrUTTzzRevfu7Uo0UM/w9NNPr1LAfdq0aXbIIYe4+qi5ubm2xRZb2NixYyPGCz3//PN27bXXWt++fZ1o2Hnnnd2kvwcLy+WXX+7+Jvka38GlLVqMFfVa8bxisE9JIca6ZD6NxIQJE5zXFhlRaSd1Xj///POIsT60CXdExB3rH3/88VZQUFBtm08++aSNGjXKba9Tp07OyhRuWXvrrbds2223dW0kAREZYX/++ee4YqzY//XXX99++eUX23HHHd3v9unTx2688cYq39tss83c37SbbfCiUHA8ffHLL7/YkUce6fZvm222sZtvvtktxyMunIsvvtgJ4OXLK57Vn376qTs30CGcP/369XPHCEtcbSxZssS5hUbq94ag3iNfCgOzo7gBhsMOi5phAM2LgRKDqIYWI9FckjwIOgh3m6uoZbTMWdRqy0AWTCKB0EDQrNMrevKDhiTcgjBl0SpnPU1PS2v03zz32Yn2wW+L3P5GqjUVKftcXQbXWLjKQyH33pTE4g4Wr8tYormaxZoJMhK+Fl3N2RPr1y62zXWEOx8p+1NTy50bL78bS3FqtkNmSMo6MBngr30s45MX5jura2PW0BNCiEjuZIiGFStW2CmnnOKSSSC0XnjhBTfYZQC9cOFC22qrrdy/zz77bOvSpYs9/vjjtt9++7n1DjjggCrbvP76650lhgl+Yv8RBEcddZQb6MNtt91mTzzxhL388svOENC2bVvbcMMNIx4cBucIs1mzZrnfRvyR9OKDDz6oti7L9txzTxs5cqQTbrTh0UcftZ122skN/tnPIIceeqgTkdddd51999139tBDDznhRs4CD652iA/2/6qrrnL9wX7wW7vttptbh/Yce+yxtvvuu7vv0k/sFwJl4sSJTkjWFcbyiCI8z2gn/XzhhRfaBhts4PZxnXXWce3597//7Y4bog5oZzx9ccghh9jQoUNd+BAaYp999rELLrjAiWTq5QZhGfuOCIP//e9/bp8R45wbX331ld15551OEPNZTdx1112ujz/88MOYkpbUlbhG8dQqoVEPP/xwxDpWnrKyyBnTRHVe+2GeTZqb59x9YhkwxUo0lyTvzkamMCwikVy6FuYVudmDWF3qGJyRsaxnhxLn6tUUFiuP359QecglsGiTVS9jbEwQn4LoCY9T8fh+7t+5IrsfohNiHcBi4aKgM++icVz+6iP0/KRIYxDeLpKahCzF1SUD7hOxCCI+Q/QH9x8q6r+VuIykpF9vKrddIYTA+rBgwQInFjbddNPKDmHQ7ifpEUqIKwbkiAU4+eSTnRj65z//6QqhM3APjktJqODd+hiAn3POOTZp0iRnicH6xOcIq4MPPti6do0eH01Si99//90N5hn8+9/eaKONqqxHW0877TRn4cF65LPPnXrqqbbeeuu5PAThViYyZjN29jCG5t9eWGHRoh8Qjgib4D76vsGggeA76aSTqiTgQGgNHz7cCZV4EnMgeBGfhPkAFkXKbNA+BFOPHj3cO8Jqyy23dPkW6tMXG220kauPGASr5HPPPVdFWH399dfOeuktjEB/5eTkVP4boUfc3CWXXOIEcXMaduIa+Z5xxhlu5oATFcXqFaSIHwY3q4sqBjmNRfhgrWKgX+EmtLKg2A3e/MCThBYEuBcWVxTfjSURhHcRw3K0bFWRq/HUFAksABFH5rOy8nLLTEt12dSwFDUmxKfgohUtTiVYrJeCuvR1XQawWBUY+HJ8GrM2WGsgWtxYXWOsmgsviI7cvL9rL5MdWEuhLrFhHrYxc2mBzVuY7xLVKAugEKIpwKOEkjz77rtvFVHl8QPyN99801k4vKgCrEwMoBFmuJEhmDy4pgVjpbw1hQF5cL1Y4Ld79erlBJgHtzZ+G4uKB6E2ZcoUJxrCjQxYvLAqsb9BcYT4CEI7EXt5eXmuWDx9w3cQL8HvBftm3Lhxztp3xBFHOLc2T1pamm2++ebOEhMP9G9QLNGfHAP6sDYaoi/gsMMOc5nHp06d6vI2AEILdz/EtCcoqojPwsqI5QyBh8WuJmGFQAuKtIQQVi+99JJTyvfff3/Dt6iVwiAaixXvTUGwgChijnTvowZ1qRx44n7UPjvTlq1e7WJIYrVa+diTqUWllrdoVcTA/saA9u60dg9Xl8vT2DE8xKd0a0tNq5rdDhm0emtVXQawtJ+Cy4i3xkrE0VqI5vJX3+LDTUW4MMJFl6QW8UI/PDl+pou7op6dEEI0BYsXL3YiojaxQ5wNIiEc3NH858FthA+k/YS/j8mpC2wb60d4/SOsQUEQEt5SFA3cEoPGh5raibBCUCA+qBcbDf+7uNhFgu3EA/Fp4ftM+3788cdavxtPXwwaVL1UCRZCLJKIKaxPCCVc+7CUBfcLqxTi87XXXqt2jH0ZqOYiLmFFx2+yySYN35oWSiyz4hTuJMV2Y8Rr1ATxQXOWr3F1k4IJC3hn8La8IN1ZgOrCwC65Nn7aMvf31zMq3uMlVosCn/t6T00RL0K7fNIPYm1qg0QgdbWK+Li1CmtX4pEs1p6aXP7ijbFq6n3n9/z5jTWZc48Jj1hrgYVDm5mEoC6WLzic6MdQCFEzZQUrbd5Dp1dZ1vukey0tt+Z6iy0BrDWRiBT/31BggYGbbropaupxrEAN3U7/u1iBevbsWe3z9PT4wjDq07Z4+iInYHXyEM+GFQ83TITV+PHjnYgKxqARZrTrrrvasmXLXAwYMXok8CBOj8Qgvi3NRVy9jznuvffec76TonZimRXH4jK8Z9MkfAgO1hicMfONpYzMZR7aSdKKoFiJFWKd0tNSrLQs5JIvNHbfBesuUYOrKawP/MaALm2cuyHHrCZXPdb9cupS5xpJJkYKysbaPorDzli62rkRJpI7IG2558M/rDxkcdWzakpqEkHxxlg1laXLtx2Lp3cnxYo5e3kBf9arFhjXPNkBfQIbIUTyU74mzxIZMvJheSD2qSaI7Zk8eXK15WRz8583Fmyb9iEoghac8PZ4VzX2Z5dddmmQ32abCANcHaMJFP+7JL1oqN+NlXCLVmP0xWGHHeZCjuhvLFe4YeI66vnpp59cDBwhScccc0zlclwkE4G4Ivwvu+wy53OJv+m3337rTLsox/CXiC19dazrNDQM2NplZ7gEFpFmvhkwIqiwttQFtpWbkWo5mWm2w7Bu9WpjLP3iC9Yy4GQWvin60LcLakvXzboUeC0qKXNuV3VJ7e0GziFzVsW6pgRvTGgLacBxI12UX1QpwBMR2vbR5MXV2ohoIf4tWrr8mmiq6zVYNJqsfoghrFXFpSFbvqbExVnhzhvPPlAigTIFXK/xWr6EEKIu4OZGfP7rr79u33zzTVTryF577eUyvX355ZdVYmlIykDGu5pc5eoLv00iB5JHeMhAF54Qgux3CArShJNQIhzGxnWFvqGPSGARbnnxfUMmQAQMSSpKSkoa5HdjxdeaIsarsfrioIMOctazZ555xrkBki0wWOPKW9aCljT+pvBzLCRkunXSIwIBYsHsJuEoK2Djp6+uD77Q64h+FTFV4TBYu+7NX12MDzPmsbavQ26mjejf2WYsyXcpom8bN9nO3bWqb3KsxNIvfj+wIDV0HbCa2gUfTV7kxAUD3mhuYSzbuF8He/vnhda7Y3qdBuO4hpJhkcF0IiUY8G2hwDQWysQn1KBWp6a6Xr2rIkXD/e9xXZKJctaycpfZL96sfqyPxZXjVx/LlxBC1AUEARniqHHEBD1xU/Pnz3eD6M8++8zVeLrooovcwJrYGjLgUcsKC8X06dPtxRdfrJbYoSEhAyApubGGYDwgkQVud1hOgtAG0qXTRjLfkUCD2k+4pJFAAvGDgKwLxHaNHj3arr76aucSR+pzEjeQGQ83OdK0s11Sq5O9j7Ccww8/3FkCcZmjztfWW2/t2t8YIJ44Pvfdd5+rnYXgIRaOeKmG6ovu3bu77IK33nqr5efnOwtWEFz/aAep9dk+2+aciDWeLiHTrRMwFs0cKJIHn8UvWowJM/y/zs9zFi0G97HGLrGtH2avsC9WFhoTLo98Pt12WqdHow1Ea9uPxnSFm7p4tRWWlFdalKLtI4NXxBeZC+vSD42Z0rs++H1AcDM4T4Riv9GgbZHOjfrUsGoqahJwqSnmiv9SqDqefeAcJuPn8tXF7rwUQoimgAE3qdbxfnrqqadcMguWMSj34oXU3l988YWLoaE+EenUSbXO4JxCuI0JbXj//fftrLPOcr/Nv6mJRfuo8xSEgTlWNYQQA3asNcQ9ITbiDZfBWoVQ4bcRWfw+++7ToAOFdRFapKUnronixfQhYgxR01hkZGQ4gUtmRrL6lZaWulpVtLch++Kwww5zIUeINyyI4W3gPEBwIzQpCE16+jPPPLNaSvzmICXUmJF9SQoXOVWjySwSb3aVZKGm+BMK4L798wI3eOvRLstO3HatKnFYNYGL1a3vTrb8ojLLSk+xY7YcaKP3bjzTfVPD/uF+SF2hBSsLnQvi8J7t7Ir91o84EPYFoLFAJaJQircPsPjgEhfreSHqD65/b02ab0tXFTs7HKLo/N2G1+m88hMDTJxwDPt3ybVrD9ggIeLkWtP9ty6oX8TAi8bWmrxizp1HVVnW96yn6pS8Ysb1jStahGjp9+AGsaXyI3L7S06C7lDhYIkY0DmnokZUm8w6FfxFqLXPyTBKPNU1q2AywP4hpBiMdmmb5epmzVwaPQ6KQe99/7dpixFVvg8QlFit4onxEfFn8mQ6jDkxapwtWVVsL3w7J64YOTwP2uVkWEZaakLF8AkhhBDJSNwjXoIOMYliouzSpYt9/PHHlUFhZA386KOPGrKdopGoKQgfF6rthnV3Lmy9OuQ4i0usA2hmvik8yrYZtLW04Hj2z7uSET/FIHX9Pu2jumTVJ1FCfb7b2OBK9takBa5emWhYajru2RlpFRMXqSmWnppSmfq/rhMDZ+00xDYd0Mmy0lPrNHEihBBCiAYSVvi9Ug2bgmBUaQ5mLunatauzYKl4cPIIBNy4oiVdIBkESSHIaod4qMusNvWd2mZnOMtXSwyO99kIiZ86e6chtsPw7rWui/tVXQVSRVa7RQmXeY99Il3/4rxCmzB9aUIKv5ZoTeZ66tsp14mpDfq0d8lnSOEfz3WPBZXtZaantshrVAghhEh4YUXRLrK4kGef7C7hkM2DwESR/DCz3S473VmceK9LkDyDtt3W7WE9O9RtNj1ZoC9WFBQ7wYkrVqSU3pHWjc/lKvGSxbBPDO6zM9OtfXaGXMkaoX8jWZOxJJN6fXC3tjZyQGdXby7e2CjEMGUK8puwfp4QQgjRUolLWJH2kawjpICMlB2QzCQLFixoiPaJZsYP2HxK7boO4BgEYslJ5Kxx9c1GiOCkltPURfku/qWmdXG/qmsGt4o+7JZwfcg+EWN26KZ9bbth3RI6u15LsiYHLcm8T1mYb6eN+cYlSGnoWnZCCCGEiJ24nOpJdRheuCwIeeXbtm0bz6ZFgpJfWOxmtpnhToTMYYkCfYGVinpOTDLgVlXTuvH0XXPUOKsLDO6j1fASjYOP7/t9QZ69/uN8y8lIsxlLC2xoj3Z1Og611bITQgghRCNbrLbYYosqFamDUBmbnPYUfhMtAywl3dtluxnyurqxJWp8UEPhXanaZqVbv045CWFVaspkFz4OiOObqAk2WrI1a+Lsle7fy1YXW4ec9Dpfn/WxpAohhBCiAYQVFYvJCkiRtrfeesst++GHH1zV5ZEjR9rixYtd4TfR8lze4kutnXjxQQ0FA1kE56CubeoV69JUKfQbK+U64pLkHErZ3bTssV4Py81MtwFdcm3lmtK4MvvVlMBGCCGakhUrVtgpp5xi3bp1szZt2riY/e+++y7m7+NNde+999qIESMsJyfHZa3eaaed3BjVc8UVVzgPk2ivzz//vMbfePPNN902mpJff/3VZeLGG6xz586uWDBj7dpYunSpKyC83XbbuT7t2LGjM44899xzEdf/9ttv3e9Qp4nivLvttpt9//33MbWRfttkk03c9ygW/Ntvv1Vbh6K+u+++e43bOe+882zddddtXa6AVFHmxDr99NPtmGOOqewIGDx4sPuMKtGiZRUR/n1hvs1ZvsbFEd12+MYxfRcLji9A3BLx+5VIrnDeTawp+ty7QhaVltnMpavtyM37N/pvir84d9fh1q9zrj346XTr3zlH7nxCiKQFUcSEPSLoX//6l8syfc8997hBOgP+oUOH1rqNE044wZ566ik3Nj3zzDOdF9XEiRNt0aJFlesceOCBNmTIkIiJ2VatWmWbbbZZjb/BGPfuu+9uMnE1Z84cJ4woTkvCONp48803208//WRfffWVZWZmRv3ul19+aaNHj7a99trLLr30UktPT7cXX3zRDj/8cJeADkOJBwFLxu9+/frZ5Zdf7o4H/Y8HGr8zfPjwqL9DNnBKLW2xxRZOGD/22GN20EEH2Y8//mhpaWlunZ9//tkefPBBdyxrYuzYsbbvvvtashJ34RJmACZPnuyULGnXOQCIKixWkRJaiOSFQTpZ736dn2e5GWnWvYY4omSLD6ovibh/TdkmRDe1rEhuQj2kROuL1gCxUcRIIWy9RVnHQYjWR0p6lnXY+ohqy5IFQkwo5/O///3PDj74YLfs0EMPtWHDhrmB/tNPP13j959//nl7/PHH7aWXXrIDDjgg6npM/IdP/s+ePdsJmJNOOqlGodIcIKYQiAiS/v0rJi9HjRplu+66qxMwCJlorLfeem6MPmDAgMplZ5xxhu2yyy52ww032AUXXOAsg4CnGVY+xBiWPqCkEv2P6ESQRYPvrFmzxh3D7OxsZ/UaNGiQ/fHHH5WC7Nxzz7WTTz65RmvUtGnTnLa47777rL7QZ37fkqJAsAdz6yGHHGKHHXaYbbrpphJVLRDci8g8hl4uLit39alE4hfvbSrRXVwasjXFZZasJPsxXFlQbF9OW+oyU85cWhBXrTQhRPKTmpltHbc5qsqLZckCg/IePXo4i5IH9zXE1auvvmpFRZGz7npuvfVWJzgQVUz2M7COlWeeecZCoZAdddRRNa533HHHOWsVBN0HPfwmHlxYfcicjajAusS24wVBs88++1SKKkAYIXgQkzWBuAmKKt/u/fff3/UnQsbz6aefuu16UQW9evVyFqs33njDWcqigahCUGVnV5xvuCtCQUGBe3/llVec5TBoIYtmrcIyh+Xsww8/dG19+eWXq62HyOYzBJ0/LrhJTp061VnncEes7VgmrLASrWNGnGxjmWmptn6f9u5vUT2eKdkH6PGAu2HnNhnWtW2mKxacjPvelDFpDQ39/fbPC62opMxlpoynkLcQQiQCDLyJ0UlNrTo0RSwxQP/999+jfjcvL8+5q+HGh3WFwTkD7bXWWqtW8QG4DyKGcLmriVNPPdVZimDMmDGVL0A87bfffvbf//7XWWwQeggr3Br/+c9/WjyQZRs3RgwX4dAv9Fk8+JJIuFt6EFpYrMLJzc214uJimzRpUtTtbbzxxs4d8JZbbrGZM2c6CyPHgP1nu4hNRFWnTp1qdbOkf3FZxAWUY8KxCYdleMltueWWlctKS0td/Fb37t2dmMUVsTmQsBIxDZ63GtzFhnQnhX5Ki83wV98irsk8QI8XXM5I2kHyDuohJaO1JFoh3mSAc61DToatLiq17Iw0l8xCGf6EEMnI/PnznYUkHL9s3rzoYw8sFQibZ5991h555BG78cYb3eAbixfxRG+//XbU7xL7QyzQEUccUavXFQN5LEXeTc6/4LXXXrMPPvjArr76ahdL9Pe//90tw63x9ttvd22Mp0+CfRCEZcuWLavVkhcO3yHZ3Lbbbltlu4ig8ePHW1nZXx4oCKoJEyZUirxoDBw40K6//nq78MIL3d/333+/SyKCKENs8X7aaafV2C7E80cffeTi7IBjQd9iLUO0eUja8e6771b2u4d+wIMO90gEMAk+mgMJK1ErviBpcWm5czWKVgS3NRLMqJbMA/T6QgKF/MKSpLSWJHNWPM611BSznMw0Z7WilpUQQiQjuJPhPheOdy/j82h4NzWy4OE2SHK1I4880t5//33n2nbNNddE/a63iNTXdQxrC4kayHwXBGsNos9n0a4Lfp/j7ZdwcJFkP8m+eOedd1b5jNgrrIInnniiS2yBhYokIF7c1fY7559/vhNfuOfxjlBFDF933XV22223OYvSWWed5VwasbaFZ19ElCKO9txzz8pl/D7LgiWeyGjItsKFFXDcmxsJKxHzAK60PGSFpWX205+FgkUF3gUQknWAXh8QUqT8Xr9PB1lLmhjONfo9Iy2V6T2buniVvf7DXLvuzV91jTYQ1157rZs5XX/99at9RqA9sQDMxvbs2dMNqCLFITAwYCa3d+/eztWGzLrjxo1rqCYKkTRgAcENLfjyFhKujUjWl8LCwsrPo+E/I6aI68uDOyAZ5nATZDAeDoKHeB2u7/pms8YFjmuc+J4g66yzTuXn0eC+EewTn0rd71e8/RIOwgbrHRarjTbaqMpnWJRwo6Q/SHqxwQYbOCsbCS58X9ZGjx49XGZA7/LHfW/nnXd2Lyx5CF2EETFeWKYQeMH4Klwe2YZn7bXXdu6dQXdA/uY3wjM74j7Yt2/z5wCQsBIxD+DIBkicFTPjyWaVaExae5Fcb6kjtX5rFJbNDf2+1wa9bM/1e9rgbm1tYV6RzV6+Ri67DQBZwsjIFSmzFBlxGSzgvkIsBdnEHnjgAeeKEg6B1azDTDEuQcxqE2D92WefNUQzhUgamIzA/Sz4IiMf8Le3jgTxyxAt0fCfBQflHmJuSkpKIiazwGqC4GmuRAceYoKCfeJTvntXvWj9QpKISNasSBDjRPp0XPaiuckxkbRw4UKXyAL3yK+//tpZucC7QMbK+PHjnaUJV0CfIASRhjulj4PDzS9o8eO+GA5Wq48//tjdjxF6bDeStYp+CI/PS6p066L1QTZA0q73aJ/dKt3douHjqyiU62OsWpO4SMSU860J3/8I+kc+m26FJeWGAUsuu/UH1xZmRplRX7JkSZXPGBgwK0tMAMU0gdgC0gnj/09hTWCmnLgPinSyPT9QYIacQQYDTSEagrI1+bbwqQurLOtx1A2WlpM4CaewkoRba7H2+izTDOgZyAcHyMT4YBWuaWCPsGI7keKAcEfDbS7ckuStH1ikcRuMlWhxWGTfe++99yw/P7/Kb/lCueHZ+YJwT8D67fFWqD59+rg4sW+++abad7i30Gex4OtukfIcK1JNcF8LtoV9whKE9ShWQqGQs+Cfc845LsmEPw5Bcczf/njhdjhr1qzK+KogxMiR/ANhhjtiRkaGy0SeqMQk7TjBmWGr60u0LA4a2c+JK7K/MYBrbZaZ2mJ0sBy01hgraI1ZERMJLKZfz1jm3HUz09OsWx3qzYnqfPLJJ262ldiASBnIGBwya+pFlR8c4S4TzELGNngeBmvNMMgjjoFYBD9bL0S9CZVbydJZVV4sSyQYtJPSO/jysUIkecBaQh0qDxMa1LXCnS9omcFyEZ4MgsE211NQuPF9Yq6ovRpuzcCKxbYREcFU5rXhLdhBNzbA2sIkzF133VVlOVkCEWPB2KFwyF4Y7JOtt9668jOy22HZCd4rcKkjHipoIWd/EHHh1i1c7xA5WOWwnNcFvovVCkFWF2vQY4895tpLcWIP1kQvMmkrNa68qMZaxeeRsh+SuZC+e/LJJ50QJuNiMJthohGTxerf//53NYVOXnkyqZDa0Bf/osOYqWMmDv9J0XJgsIwl5qXv5tiMJavtl/l5buAmS8VftFbLjT83fpi9wqX7fvfnBS5TYGvsi+bk94X5zkrFnbrTn66ZIj4YHBGLgHsfcQbh/PTTTy5eI3wQQGFRZpCDKZD5m5n2oAADgre9SyEphYVo7SCssBAff/zxLnkCg2dc17gew+sf4YYLM2bMqFx28cUXu0kNhAgWDlzNKDTLIB6X3nDeeecdl+yirm6AI0eOdO+IFcbATJxgVUH87bjjjk5M0C6sc4yJEXYIE2+5qStYxxGAbBsLEPFYWMC5N9FXHqw/xHMde+yxTth4qxYTPiTwoM/CU5dvtdVWTtT5yaSrrrrKWdtZH5e7Rx991AkZfjdW8vPzXZvp86DljuPL9rFI4oJJjJh3/SO+CvEUzRrIPvii0cRqJTIxCSvMh0HwIyevPqY7L6o8v/76q5sZqMkXViRvHBGUh5gEC8nVSFQ5N0icgLDKSk911hMJq6aFrJ30fWpqim2xVhf1fz1gMEbcBS4w8aRAxp2pvimkCVYPBqxjJROiJYNAwXJB3ac77rjDuX0Ra4RICB9rRgKLB3GLuNxiJUJQEc+DpSM8UQMgMnArixQXWRMUMGbiBRdfto3bG8IKiw7p1TFGYOlBlOAejAgiM2C8MPFCjBFi8aKLLnITOLjMEbtUW3wVApWEISTDOOGEE6p9Thu9sMLtkGNAexFHJAIhmyK/S2KIWLn66qud6yCxpUEQx7SDdyxVWPNxcySVOi7RZ555ZtRtIlqxdiLKqBWWyMQVY0Wn0wGRTnTUMp9RQwBfc9Gy4oiO22qgPfbFDFv+p8gSVa029FNrExTss69tlpWeZpnpzR882hrBTXdVUUXWq7V7Jk5MRbLBDDYDo8suu8w99ONJgRxMSxxvCmlSFIfP0gvR0mHwTMY6XjURtFQFQSQEXQlrgpideEB8IPx4hYMrMO52dXW5qw2y9GFhqwlEHCIvCOImXOBEA4tabb8RCzfeeGNUF8rHH3+82nL/mz4uNRKIVsQdAsvfO4Mgvr2VrrmJawREZg5UfjT4jHVEy4sjGtqjnbXNSncZAhXD8RetsThweJ2zXh1yXD2lTQd0khtaM8VAHrhJX9tp7R6WV1g9rbCIjUsvvdRl2mJGOhq1pUAOpj+ON4U0bk3M5PqXYrGEEC2Rjh07OpGK62Y0XnnlFWftwiUw0YnLYkUMFX6vZFHBdBgEQcVnkfzSRfKDZWLZ6iIrKg1pVjyCRa+1Jq5gvydMW2pbrtXF1bJqbVa7RKG1n4f1ZcqUKc7VnYQVQRc9RBBuRcySEytVWwrkoCs860bKVFZbCmmsXLGmURZCiGRltxosVWSEJO077oUbb7yxbb/99tYihRW+qwTsEZB7wAEHVBbp4qGEqsQUid+paJmUlpt1bpOpWfEArTVxhYd9P2PHIRrUJ8BxaM3nYX1BAOHDT1A6r3CIOSCIGxc93FJIgXzooYdWfk4sA8kogstIZvHhhx+6GKlgAgsGDP5zIYQQ1bn33nudnuA+mSiufo0irEhNyUMBH3SyA3ofcVwaEFw8dGSxapkQuzF+2lIrKSu39tkqgyb+ggH9lIX5dt2bv7paZydso2LBTUVrjvFrSPDG4JkWyT2QYG6K+xKHgMsKKZF54PMc9JmvxowZ4zJ2BYPhyWRF8U8sYb6OFa6BBI1vvvnmyggohBBRSKTYqVhJr+8DiNk9/B6BQN9EqHosGg9iNzq3wT0lJIuVqAYFpH9bkG+zlxXYRv1kPWmOGD8Jq/ghvXOkUiG+llXws2uvvdalKsY1hRpVuMGTpQu3FtITexBPCC1ipsimi4cHAdy4FT788MP1aK0QQohEo94qCCFFhg4eSBJVLR9mxKmRQ2pnWaxEOFiq0lNTrCwU0vnRxNdlay5O3RxssskmLh07nhr/+Mc/nEWKor+kEA7niSeecHVssGjhYki8FgU/t9tuu2ZpuxBCiASzWOFbjnsEBcXwK6cIGvWrqHLNw4UHzQ477NCwrRXNDrPhWCKYHVfmMREO7n8L8wqtqLTcWa5E012XslQ1Hh999FFUt3gKXdYGk4+UKeElhBCi5RKXxYpCXjxQSFZx9NFHO3dAD5YrUsPef//9DdlOkUBodlxEg8F9UWmZE1XfzlymjhJCCCFEqyEui9Ull1ziCgGPHz/eBfSGF3LbcccdIxYBEy0DzY6Lmli6usQy0lLcuxBCCCFEayEuYfX111+7qvDU2CADUjjUtlqwYEFDtE8IkUQZ6aBLmwzLX1NiW63VubmbJoQQQgiR2MIqIyOjivtfpFogbdu2rU+7hBBJmJGughTLyUyzr2YstyMe+NIOHtnXDhrZr5lbKYQQLZuUtAxru/He1ZYJIRJcWG2xxRYu8xFZjsJZvXq1q8+RDNWRGxPVlRGtBSxVQYvVuz8vsJSUFFuyqthKy8pt3C8LJayEEKKRSc3KtS67na5+FiLZkldQAJisgHvvvbe99dZbbtkPP/zgYq1Gjhzp6lpRNLE1U30WX4iWG3N3/NYVxYB5XbzXOrbpgE7WtW2mtc/JsF3X7dHcTRRCCCGESExhRcHDN9980/744w875phj3LLzzjvPFUksKytzn2244YZxNYiK9BdeeKH17t3b1Qfht8aNGxfTd6kpQuIMMhN27NjRRo0a5eqGNAfKnCdae0r+wd3aWklZqLmbI4QQQgiR2HWsqFk1efJk+/77713adWKuBg8e7CxWuAHFy3HHHVfpZjh06FB77LHHbK+99rIPP/zQpXiPxmuvvWb777+/bbnllnbFFVe4Njz//PNO+FFbi7paTYky54nWDMWjv56xzN0X7vzgDxvao53qLAkhhBCiRZMSCoUSZkr5q6++chYqiiief/75bllhYaGtv/761r17d1c/Kxq77bab/fzzzzZt2jSXrRBKS0tt7bXXtjZt2jhXxVjJy8uzDh06uHpc7du3b4A9E6J1ce3YX+zV7+e6ItIDOufa4aP6O3dBIWpD91/1i4jMwIvGNnrXzLi+avILIUTdnk1xuQKmpqZar1697JNPPon4+VNPPWVpaWl13i6WKr6HS2GwYv2JJ55oX375pc2ePbvGHe7UqVOlqIL09HTnFohLYVMnrnj08+nuXYjWyOL8IstIS7U+HXNsu2HdKhNbCCGEEEK0VOISVt6StMsuu9jtt9/eYI2ZOHGiDRs2rJoSJFYKcDuMxg477OAsViTNIPZr6tSpdvXVV7skGxdccIE1JUpcIVo73dplWY/2Wda9XZbtu1FvuQEKIUQjU164yhY8fVGVF8uEEEkQY3Xbbbc51z1ilxAvDz74oLMu1Yf58+c7S1g4ftm8efOifhdBNX36dLv22mvtmmuucctyc3PtxRdftL/97W+1JszgFbR+NWT6aSFaG2v3bGefTlnirFb3fPiHnbHjEIkrIYRoRELlZVY0e1K1ZUKIJLBYUST47rvvdsklXnrpJdt6661t1qxZ9WrMmjVrqrjyebxg4/No8D2sXQcffLA988wz9uSTT9qmm25qRx99tI0fP77G373uuuuc36R/9etXv2KmUxbm24RpS927EK0RYqtG9OtoK9eUWsfcTJUdEEIIIUSLJ25h5SHr3ueff24rVqxwGQHff//9uLdFLFTQchR0O/SfR+PMM8+0119/3Z599lk7/PDD7aijjnLp17F2nXPOOTX+7sUXX+yC0fyrpliuWKAg6vKCEvcuRGsEa+3wnu1sj/V62Mylq+2H2SsUcyiEEEKIFk29hRWMGDHCvv32W9tss81sjz32sIcffjiu7SCCcAcMxy+jtlUkiouL3W9SsJjEGkGr2p577ulcFVmnJmsXcV3BV32gIGqnXBVGFa0XXzR44uwV9sOclTZx1nJZrYQQQgjRomkQYQUU5B07dqxdcskl9vHHH8ct0H7//fdqMU4TJkyo/DwSS5cudanVKU4cTklJiaulE+mzxuKgkf1cTAnuUMoMKFozvy/Mt9KyclteUKyYQyGEEEK0aOISViSJoBhvOBTlvfLKK13NqA8++KDO2yU+CgH0wAMPVC7DNfDRRx919a187BOxXL/99lvlOtS4Qti9/PLLVSxTq1atcu6B1LJq6pTrygwohNmwHu2sXXaGbdy/k5JXCCGEEKJFE1dWwAEDBtT4OQV94wHxdMghh7iYp0WLFtmQIUPs8ccftxkzZlRxLySuC6uYr21M7SsKCl966aW2xRZbuM8RaHxnzpw5LpFFU6PMgEKY7bdRb1u2uti9Xvx2trPmCiGEEEK0WmF11VVXOWvU6NGjXQwT/64N1icFel154okn3PfGjBljy5cvtw033NDeeOMN22677Wr8Hm0bNGiQq6uF1QxLF9+l6PBBBx1kzRFjwkuI1gzusAXFZbaioNhueHuyWyZxJYQQQoiWSErIm31qADGFUCLdeWZmZpUEEVE3nJLSpHFNDQkxXqRdJ0NgfRNZCNGaIcbwlncn29fTl1mnNpm2QZ8Odt//bdrczRIJjO6/6hcRmYEXja2xa8oKVtqcO4+qsqzvWU9ZWm6HmLt0xvV7q/uFqMezKSaLFckfavq3qD6Y9AWCZbUSrRnO/x2Gd7es9DSbtazAZcwUQgghhGiJNFhWQPEXSlwhxF8wwTCgS65tO7SrDe3RTl0jhBBCiBZJXMkrRM0ocYUQVZk0d6UVlVZYumXFFUIIIUSrFVYkhSBmqi6w/tSpU601osQVQvzF6z/Mc26Adb2HCCFES4l/EkK0DmISVttvv70GRUKIuOnRPtuy0lNt3416qxeFEEII0XqF1WOPPdb4LRFCtEgQU7075iiZixBCNCIpaemWO3zrasuEEE2HrrhGgEKo435Z6DKgqWaPEImLMngKIVoKqVltrNv+Fzd3M4Ro1dRLWJWUlNhvv/3mcrpHSsFeW1HflgqianlBiXuXsBKtHWKsfl+Yb/NWrEm4xBXBDJ6J1jYhhBBCtAJhhYi6+OKL7Z577rGCgoKo6yVrgeD6gqXKW6yEEJCYiSuUwVMIIYQQzSqs/vOf/9hNN91kp556qm2zzTb2f//3f3bDDTdYx44dndgi+9eNN95orRWsVLJUCfFXjJUvmJ1oKIOnEEIIIZq1QDDJLA499FC79957bY899nDLRo4caSeffLJNmDDBCasPPvigwRophEheEC/Hbz1IrnZCCCGEaNHEJazmzJljO+20k/s7KyvLvRcWFrr3zMxMO/roo23MmDEN2U4hhBBCCCGEaFmugF26dLFVq1a5v9u2bWvt27e3adOmVVln+fLlDdNCIYQQQghRI+VFq23pW3dUWdZlz7NdtkAhRAILq4033ti+/vrryn/vuOOOdtttt7nlJLa44447bKONNmrIdgohEhylLhdCiOYjVFZqBZM/r7Ks825nNFt7hGiNxOUKeMopp1hRUZF7wbXXXmsrVqxw6dW33357y8vLs1tuuaWh2yqESGCCqcuFEEIIIVobcVms9ttvP/fyrLvuujZ16lT76KOPLC0tzbbaaivr3LlzQ7ZTCJHgKHW5EEIIIVoz9SoQHKRDhw72t7/9raE2J4RIMpS6XAghhBCtmXoJq5KSEps7d65LVBEKhap9vskmm9Rn80IIIYQQQgjRcoUV8VTnn3++PfXUU1ZcXFztc0QWtazKysoaoo1CCCGEEEII0fKE1XHHHWevv/66HX744bb55ps7N0AhhBBCCCGEaK3EJazeffddO/vss+2///1vw7dICCGEEEI0OQMvGtvovzHj+r0b/TeESKp06xQIHjJkSMO3RgghhBBCCCFaUx2rZ5991hUDFkIIigM/+vl09y6EEEII0RqJyxXwsssuc8WBN910U/u///s/69u3r6tfFc6BBx7YEG0UQiRRcWDSrgshhBBCtDbiElakWP/ggw/s+++/d69IKCugEK0HFQcWQgghRGsnLmF1wgkn2HfffWcXX3yxsgIKIVQcWAghhBCtnriE1WeffWYXXnihXXnlla2+AyNBnAkuUcziyy1KCCGEEEKIlk9cySt69uxpnTt3bvjWtMB4EyFaC0pgIZKdr7/+2s4880xbb731rE2bNta/f3879NBD7ffff6+27q+//mp77LGHtW3b1j0PiTdevHhxtfVI8nTjjTfaoEGDLDs72zbccEN75plnmmiPRGsiJTXNsvqtX+XFMiFEgluszjvvPLv33nvtxBNPdA8VURXFm4jWiBJYiGTnhhtusM8//9wOOeQQJ4AWLFhgd911l22yySY2fvx4W3/99d16c+bMse222846dOhg//nPf2zVqlV28803208//WRfffWVZWZmVm5z9OjRdv3119vJJ59sm222mb366qt25JFHujjkww8/vBn3VrQ0UrPbWs8jr2/uZgjRqolLWBUWFlpGRoarZcVsXr9+/aplBeSh8Y9//MNaI7j/yQVQtDY0oSCSnX/+85/29NNPVxFGhx12mG2wwQZOHD355JNuGWJq9erV9u233zqrFowaNcp23XVXe+yxx1xJEp/o6ZZbbrG///3vTqDBSSedZNtvv73961//cgIuUkZdIYQQyUlKKBQK1fVLqam1exAmc1bAvLw8NxO5cuVKa9++fXM3RwghWg2JeP8dOXKke0dIQY8ePZw4ev7556usN3z4cDfR+N5777l/33PPPU5U/fzzz7buuutWrocrIFarTz/91LbZZpuk7RfxFwMvGqvuiJEZ1++tvhJJR6z34LgsVtOnT69P24QQQoikgLnHhQsXurgrb4VatGiRq+MYDlarN998s/LfEydOdLFa66yzTrX1/OexCishhBCJT52F1Zo1a+z222+3HXfc0fbdd9/GaZUQQgiRADz11FNOTF111VXu3/Pnz3fvvXr1qrYuy5YtW2ZFRUWWlZXl1sW6hQdH+Howb968qL/LNngFZ0uFEEK0sKyAOTk5dv/997sZPCGEEKKl8ttvvzlXvi233NKOPfbYyslFQDiFQ9a/4Dq8x7JeJK677jrnduJfuBgKIYRIbNLj9TefNGlSw7dGCCGESADICLj33ns7UfPCCy9UJplgchGC1qRgYqfgOrzHsl4kLr74YpdMI2ixkrgSNVFeVGDLP368yrJO2x9rqVm56jghEllY3XbbbbbXXnu51LPHHXecpafHtRkhhBAi4SA4ec8997QVK1a4BBO9e/eu5sbnXQKDsIyaVt5Kxboffvihi9MKugP67wa3Gw7biGTtEiIaobISWzWxahKNjtscqQ4TItELBCOmyAx46qmnuswYQ4cOdTU/gq+NNtqo4VsrhBBCNCJYk4gfpijwG2+8USWbH/Tp08e6detm33zzTbXvUsNqxIgRlf/m74KCAldMOMiECRMqPxdCCNHKhRUzcqSVpUDi5ptvbn379rUuXbpUebGOEEIIkSxQIoS6VV9++aX973//c7FVkTjooIOc6Jo9e3blsvfff9+JMWpTef72t7+5mo+kXfdgvbrvvvucQNtqq60aeY+EEEI0JXH58H300UcN3xIhhBCiGTnvvPPstddecxYrsvv5gsCeo48+2r1fcsklTniRHfecc86xVatW2U033eQKCR9//PGV6zPpeO6557rPSkpKbLPNNrNXXnnFuReSbVDFgYUQomWh4CghhBDCzL7//nvXD6+//rp7heOFFUkkPv74Y5dc4qKLLrLMzEyX6OKWW26pFhd1/fXXW6dOnVw23ccee8y5ziPYKBAshBCiZZFeH5cJHg5jx461mTNnumUDBgywffbZx4466ijNxAkhhEgq6uKNQcHgd955p9b1iEcmwx8vIYQQLZvUeDMmbb311nbCCSfYu+++61wceI0bN865QVBJXsUMhRBCCCGEEK2FuITV6NGj7dtvv7U777zTFi9ebN999517LVq0yO666y6XLYl1hBBCCCGEEKI1EJewevnll+2MM85wLzIeefj79NNPd68XX3yxIdsphBBCCCGEEC1LWC1dutSlW4/G2muv7TIqCSGEEEIIIURrIC5hNWTIEJeSNhp8Nnjw4Pq0SwghhBBCCCFatrDCBZCkFXvttZd7nzFjhnuRIYmUsySxOPPMMxu+tUIIIYQQQgjRUtKtI6xIVEF9jvB0s8RZ/fvf/3ZxVkIIIYQQQgjRGoi7jtUVV1zhrFLvvfdelTpWu+yyi3Xt2rUh2yiEEEIIIYQQLVNYAQLq8MMPb7jWCCGEEEKIupOSahld+ldbJoRIEmGVn5/vrFXLly+3UChU7fPtttuuPpsXQgghhBAxkJbTznqfdI/6SohkE1akW8cNkFpVZWVlbhnCKiUlpcrf/jMhhBBCCCGEaMnEJaxOPvlke/311+3ss8+2bbfd1jp16tTwLRNCCCGEEEKIliysSLH+j3/8w2688caGb5EQQgghhBBCJBlxRTXm5ubawIEDG741ZlZUVGQXXnih9e7d23JycmzzzTd3dbFi5bnnnrMtt9zS2rRpYx07drStttrKPvjgg0ZpqxBCCCGEEELELayOPvpoe/nllxulB4877ji79dZb7aijjrLbb7/d0tLSXCHizz77LKYU8EcccYT169fPbeOaa66xDTfc0ObOndsobRVCCCGEEEKIuF0BDz74YPv4449tjz32sFNOOcUJGQRQOJtsskmdtvvVV1/Zs88+azfddJOdf/75btkxxxxj66+/vl1wwQX2xRdfRP3u+PHj7aqrrrJbbrnFuSkKIYQQQrQWyosLLe+rF6ssaz/qIEvNzG62NgnR2ohLWG2zzTaVf0dy04s3K+ALL7zgBBpizZOdnW0nnniiXXLJJTZ79mwn4iJx2223Wc+ePe2cc85xv7969Wpr27ZtnX5fCCGEEC2PgReNtZZOqLTIVn7+TJVl7TbZx0zCSojEFlaPPvpow7fEzCZOnGjDhg2z9u3bV1k+atQo9/79999HFVbvv/++i6e64447nAsgKeERWqNHj3ap4YUQQgghhBAioYTVscce2/AtMbP58+dbr169qi33y+bNmxfxexQoXrJkiX3++ecuUcXll19u/fv3dwLwrLPOsoyMDDv11FNrTJjBy5OXl9cg+yOEEEIIIYRoHcSVvCJcDP3www/O9a6+rFmzxrKysqotxx3Qfx6JVatWuXesVA899JCLzzr00ENt7Nixtu666zoLVk1cd9111qFDh8pXNKuYEEIIIYQQQjSosHr11Vdt7bXXtr59+7okFRMmTHDLsRxtvPHGcWUNJL160HLkKSwsrPw82vcAyxSJNTypqal22GGH2Zw5c2zWrFlRf/fiiy+2lStXVr6I5RJCCCGEEEKIRhVWr7/+uh144IHWtWtX53ZHsggPy/r06WOPPfZYnbeLyx8WsHD8MmpbRaJz587OqtWlS5dq2Qm7d+9e6S4YDaxkxHUFX0IIIYQQQgjRqMKKtObbbbedqy3197//vdrnFOglEUVdGTFihP3+++/VYpy8NYzPI4Flis8WL15sxcXFVT7zcVndunWrc3uEEEIIIYQQotGE1aRJk1wMUzR69OhhixYtqvN2ceMjRfsDDzxQuQzXQJJQbL755pWxT7j1/fbbb1W+i8sf33388ceruBA+9dRTLs4qmrVLCCGEEEIIIZolK2Bubm6NySqmTZvm3PLqCuLpkEMOcTFPCLMhQ4Y4oTRjxgx7+OGHK9ejaDAFioMuiGT9I3EFFjSsXmQFHDNmjM2cOdO5LgohGoYf56ywb2cut5EDOtmGfTuqW4UQQggh4rVY7bjjjk7wlJaWVvtswYIF9uCDD9puu+0WVwc/8cQTdu655zpRdPbZZ1tJSYm98cYbzvWwJkhgQar1I4880h555BH717/+5VwEyQy45557xtUWIUR1EFUrCkrcuxBCCCGEqIfF6tprr7UtttjCNttsM2dhSklJsXfeeccJm/vvv99ZkkhqEQ8kobjpppvcKxofffRRxOUkqognaYYQInawVHmLlRBCCCGEqIewGj58uEtccc4559hll13mhJQXQjvssIPdfffdNnDgwHg2LYRIcHD/kwugEEIIIUQDCCtYb7317L333nNpzP/44w8rLy+3tdZaqzL7HmILS5YQQgghhBAw8KKxjd4RM67fW50tkqtAsKdTp07OJZDEE4gq0p2T1Q+rlhBCCCGEEEK0BupksUI0vfbaazZ16lQnqPbZZ5/KNOYFBQV211132W233eYSWAwePLix2iyEEEIIIcJIzWmvPhEiGYQVhXaJn0JU+TTnZOJDaGVmZrpsfHPnzrVRo0bZnXfeaQceeGBjtlsIIYQQQvxJWm4H63f20+oPIZJBWI0ePdqmT59uF1xwgW277bbu76uuuspOOeUUW7JkiYu5evLJJ2377bdv3BYLIYQQQgghRLIKq3Hjxtnxxx9v1113XeWynj17unTre++9t7366quubpQQQgghhBBCtDZiVkILFy50tauC+H+fcMIJElVCCCGEEEKIVkvMwqqsrMwV7w3i/92hQ4eGb5kQQgghhBBCtMSsgDNmzLDvvvuu8t8rV65071OmTLGOHTtWW3+TTTZpiDYKIYQQQggRE6qVJZJCWF122WXuFc4ZZ5xR5d++ODBWLiGEEEII0biUlxTZ6p/GVVnWZoNdLTUjS10vRKIJq0cffbRxWyKEEEIIIeIiVFJoy8bdV2VZ7trbmklYCZF4wurYY49t3JYIIYQQQgghRGtwBRRCCCGESLZ4GCGEaApUeEoIIYQQQggh6omElRBCCCGEEELUEwkrIYQQQgghhKgnElZCCCGEEEIIUU+UvEIIIYQQQog6oCLEIhKyWAkhhBBCCCFEPZGwEkIIIRqRoqIiu/DCC613796Wk5Njm2++uY0bN059LoQQLQwJKyGEEKIROe644+zWW2+1o446ym6//XZLS0uzvfbayz777DP1uxBCtCAUYyWEEEI0El999ZU9++yzdtNNN9n555/vlh1zzDG2/vrr2wUXXGBffPGF+l4IIVoIElZCCCFEI/HCCy84C9Upp5xSuSw7O9tOPPFEu+SSS2z27NnWr1+/uLat4HkhhEgs5AoohBBCNBITJ060YcOGWfv27assHzVqlHv//vvv1fdCCNFCkMUqAqFQyL3n5eU19fEQQohWjb/v+vtwsjN//nzr1atXteV+2bx586ImvODlWblyZbXnUnlRgTU2/f/xv0b/DdEwlBcXRFyWkpahLk5SmuL6m3Tl7o3+G63p2SRhFYH8/Hz3Hq97hhBCiPrfhzt06JD03bhmzRrLysqqthx3QP95JK677jq78sorqy3Xc0nUhXn3n6wOEzXS4TZ1UEM+mySsIkBKXPze27VrZykpKVGVKw841gt38Uh01Hb1u86Z5KA1XqvMBvLg4j7cEiC9etDy5CksLKz8PBIXX3yx/fOf/6z8d3l5uS1btsy6dOkS9bmUqCTzeZzMqN/V762JvEa+z8T6bJKwikBqaqr17ds3po7m4CXrg0JtV7/rnEkOWtu12hIsVUGXv7lz50Z0EYRoD2msXOGWro4dO1oyk8zncTKjfle/tybaN+J9JpZnk5JXCCGEEI3EiBEj7Pfff68WszthwoTKz4UQQrQMJKyEEEKIRuLggw+2srIye+CBByqX4Rr46KOP2uabb66YKSGEaEHIFTBOcNG4/PLLIwYlJzpqu/pd50xyoGs1+UE8HXLIIS5matGiRTZkyBB7/PHHbcaMGfbwww9bayCZz+NkRv2ufm9NZCXIfSYl1FJy2gohhBAJCIkqLrvsMnvyySdt+fLltuGGG9rVV19tu++uNMdCCNGSkLASQgghhBBCiHqiGCshhBBCCCGEqCcSVkIIIYQQQghRTySshBBCCCGEEKKeSFgJIYSoM8p7JIQQoikoLy9Pmo6WsBLNjgZoorWxcuVKS1aee+45956SktLcTREJhO7jTZdhUv0uWgtTpkxxdQBTU5NHriRPSxuRiRMn2qxZs6oMdpLlIVFQUGDJyrRp01z7wx8UycAPP/zgLvg5c+Yk3TkDr776qp1xxhnuGCTbbNAzzzxj7dq1s88//9ySjZdeesl22203++9//+vqGCUTzz77rA0ePNiOOOII++yzz5q7OaIZGTdunF100UV277332hdffOGWSWg3LpMmTXL10A4//HA77bTT7KuvvlK/N9FEEv19ww03VLnvJdPzPhkZM2aMDRs2zD0v1113XbvqqquSZkKyVQurX3/91bbZZhvbeeedbaONNrJRo0bZiy++aKWlpe4hkcgXzuTJk23kyJF20kknWbLx448/2t5772377ruvDRo0yHbYYQc3SE7k/g62fdddd7V99tnH9T/nzR133FF5ziTLoOiAAw5wN6433njDLUuG2SAmQCi2esIJJ7jzp3379pYszJs3z7X5mGOOsczMTMvNzXWvZMD3+7HHHusEbXZ2thUVFTV3s0QzwMDmsMMOc/fusWPH2nnnnedqcXEPXLZsmVsnGe7jyYLvS+7VW265pc2dO9dKSkrc5BLPoZtvvrm5m9hiWbhwoe2xxx524okn2tdff+2E1S677GJXXHGFrVixIuHHiMnMgw8+aKeffrrttNNOboy7ySabuH5nMnjq1KmJPxkcaqUsXLgwtPHGG4e22mqr0COPPOJeW2yxRahjx46hyy+/3K1TXl4eSjRo0wsvvBAaNmxYKCUlxb0++uijUDJQWloauuOOO0LdunULbb/99qF///vfoTPOOCPUr1+/0Nprr53Q+1FcXBy69tpr3flB2++8887QM888E9phhx1C7du3D7300kuhRMefz99++22oS5cuoZycnNDmm28e+v77793ysrKyUCJSUFAQOv744925Tt+/+uqr7vpNJrinrLPOOqGnnnoqNGvWrFAysHLlytAxxxzj+p3znH4fO3ZsKDs7O3TzzTdXXtOi9fD888+HOnXqFHrggQfcefzrr7+6cyQrKyt03nnnNXfzWizbbbddaI899gjNmDHD/Xv69Omho446yl2bPIeKioqau4ktjscffzzUuXNnd8+eN29eaOnSpaHjjjsu1K5dOzduEY3DqlWr3Lh8l112Cc2fP79y+Q033ODGWocffnjCd32rFVbPPvtsKD093YkUz5w5c0KHHXaYu1m99957oURk6tSpofXXX98NjK+55prQuuuu6wRhSUlJKNF5++23Q2uttVbohBNOCP3222+Vyz///HPX5xdeeGHC7gcDyk022SR07rnnhn7//ffKAeWUKVNc22+88caEFOKR4JzfbbfdQvfdd59r+yWXXFK5P4m2D7QLQUs7Tz755NDixYujniOJ1nYPA9AePXqEzj777GrLE7X9q1evDg0dOtRdr/fee29o5syZbvm0adPcwPrAAw9MWCEuGo/99tvPPXPC2X///d2kE89VkOBuOL777rtQ27ZtQ7feemuV5VyTO++8c2jIkCGhzz77rAF/UQCTeIytwu+LiCueR4wJEu2+3RJYtmxZqGvXrm58G34vOe2009zE3sMPP+z+najPoMT3/2kkZs6caW3atHEuUYB5vU+fPnbBBRfYZpttZueee64tWrTIEo309HTbb7/97P3337fRo0fb3//+d5swYYI9/vjjluj88ssvlpWVZddff70NHz7cLSsuLratttrKuRp99913bv8S0bzeoUMHO+qoo+ySSy6xoUOHWlpaWqXfe7du3WzAgAEJ7xrg29avXz93zpx66qnODfbRRx+1Dz/80BIR+hlXI86RTz/91Lp27erOkddee82OO+44u/DCC137OY8S1RWTWKr8/Hw788wzK9161ltvPedmwv0Htx5IlPbjYoGbIvcU+hlXmP79+7vPcN0dMmSIc/vinpnI57toWHD/5Drr2LFj5TL+DTyLODcuvvhi5xbt74+i/vTs2dP1M+MVfxyAaxJXQNwDH3vsMVuyZIm6u4Huf/QxLs88azyc19wXzzrrLOeadvbZZ7v7X6Lct5ORsWPHur4Mxq7l5eW5Pp0/f747DtxLSF4BPENHjBjh3AKJzU/YEIZQC8cr2vBZhf/+97/OpPvhhx+6fwdn7J977jnn2vCf//wn4nebu+2FhYWVf0+ePNlZH/r27RtasmRJKFEItj3Yftob/Nz3Pa5G22yzTWjNmjWh5iZav4fz6aefOush5ukrrrgi9NNPP4WWL19eZRuJ2H4sVsxywsSJE93s27HHHutmimr6XnO23VvXcDfifOdv9oFrmL+xoEyaNKnKNhKl7d98842zjr/88svO5Tg1NTV08MEHuz7v3r27a/+jjz4aSvRzns9Y7+9//3uoQ4cOlee6ZmxbFtwHsMr7+0GQQw45xLmh+/t4+DOV2WQszIk8m5xs5OXlhTbaaKPQjjvuWLkseM3961//cvfB999/v5lamLzgynrOOeeEzjrrrNDo0aPdeR+0wg4fPtw918PPZ1xhuW9zzod/JmIDd9YBAwa4fjzggAOqfMZ4cNSoUc6LLJzbb7/dne/XX399wj5/Wqyw8jExDz30UJXl/iCMGzfOiScGxH6ZvzgWLFgQOvTQQ10sUHP4LkdrezQQgsTLXHDBBaHmpq5t98KLeDfcMP2yRG27P0dwW+SGwMOOAfKJJ57oXGGa0/+3tvb7fv3qq6/cjQm/caDtXAtPP/10pbtDol2vuL0gRujznXbaybmVsmzu3Lmhq6++2okVBn2J2O8IK1wbjj76aDdAuuyyy0L5+fnusx9//DG0++67O9deHvKJfr0C7ec4vPbaa43aNtH04BbMYLJXr16hzMzM0EUXXVRFROH+5ON6PH5Scvbs2W5yjHMcl13RcCCeevbsGXr33Xer9Dn88ccf7v5y/vnnJ+xAM9FgXEd/MW7adNNNndsz5zWuz//73/8qJyBZxmSYf+77fifWDTfMQYMGKb6tHjG8HTt2DK233nrOMPDEE09UfjZmzJhQWlpalVAd3/e40HOPQXz5yb1Eo0UKq08++cQdLC4KZrd/+eWXiDccYmYY0PsZieDnBCwyy0x8QaTvNnfbg8sWLVrk4paYLfSz9s1xc61L24PwQG7Tpk3ouuuuazb//Fjb7v+N9QFBi5XQL7v44ovdAP+mm25q8lmsuvQ9AejMOvsEEMyI5ubmOpFIkoj/+7//qxRdidR2rkn824nJC/+MQG6sKH6wn2jX69Zbb+3ODQZAX3zxRZXPGCwRJM3MaVOeN3W9Xn27sNTyHc6jmtYXyQMCn5gSBjiIK7w1eKZwnJl48XGN3Ks322wzdz4HBzX+HGCikkkbLwBEw8C9mnvEkUceWfl89NcjkzTc/0gCJWqH/uIcR0SREIGJA/oSi1/v3r1D2267rUuYRD8zgOffPmlIkCuvvNIJAx9rJWKnvLzc3UsQR0zsMZnDfYXEFT52nX+TXCs4SePP+TPPPNNN/hDzm4i0OGH15ZdfugxzAwcOdDPYPBi4eIIB7/7GRJYrPidIzrug+c+42HjInHLKKU020Iml7dHgptCnT59qJtWmoj5tZ4DH+u+8804o0dte0yCSmwHuadyMg+6aidJ+33YGxggpbmyeI444ws0QZWRkuAx2/gaXCG337WaGi0mEIH698ePHu+8GLdCJ0HZ/P8HC5rN4esuUt4azT2T8YmDUVOdNfa5XJm9IYIH7DEhYJTcIJCYsuHeR3TRosf7b3/7mPDe4ZwDnx4MPPugmCe6+++7K8xvLp39uci75LKlykWo4rrrqKncsfOB+cAISDwrcikluJWp3QcPSdOqpp4ZWrFhR5TOW0cd4GXjLCecziUP8deHv27jRcx0wyQq6D9aNRYsWOWMAz0Pc+kjQ4hNW8BwkKyNjEibcfd/75yNWRcYqkVySE4EWJ6yYdcWtyZtzmW3AzMssdyT22msvN0vx+uuvV7tZMZtLKtmmumjq2vZguxgIexcd72v98ccfO/HYFO2Pp+2ee+65x1kHvXsUx4AHhL+5JXLbwwcPW265pcsk1JTCKrz9pOatqf1k7mKGiIcKMYa473ADI1aMwZUfRCXqOR9sm+97ZrWYPWxKd9i6tt2nR+bhDUERg5sj2dYQj4nY9vAHIr7xuMJg7RTJDbFUzA77AXtQKHF/CD5TgLgHYhp5bvJ58D6BYOe8IiZSNCw8U4jp5R4dPlNP+m+EVaK6RiUSnK/ESAXx5ztWeMYifvKLZyTnOm6Yr7zySpXv4FLPtYEAEHWjrKzMufEzDmFinfAbxk0IXi+WWIa1HMGFwA0ev5NOOskdEyaHE1HQtihh5UVRcFbbW0NIdewHLcGBMHEaHDgOKmlNPcyAM9DE3JtIbY90Evn9IYU57o0bbLCBazcz4MRuNHbNn/q0Hfbdd19XtwC4UJ588knnosm+UDsiUdsePhuLxY1ZFFKyNxV1ab/fBwZJxE/ss88+TlDh1sN3eKj4gX9TxBY2ZN8jzvkes+mJeq/h3OaeEm6d/fnnn0ODBw92MVhN8ZBoiH5nsMHEExM6ifhgE7HhjycDyUgJTHDpY6CJ23MQ3OfxkBg5cmTlucxzhokNBFck1ylRfxCu9DvPeCbAiDd566233ID0H//4h67FGPGTWuFhB7jx80wMloPhvk25DO53eB4AogB3NCaYEAAivgmd3Nzcysm8+++/37m7IqaAMAv6FndA3PwvvfRSdz8iHhhPi0SuJZa0wopZdwaAmBAZFHiCDwX/oCC5ALPZ4TMO/qJ67LHHQv3793c3JwrYcuAY7CNM8D1PxLZHApHoayzwwo0j6O6VaG3nO1ip8JUl6QO1w6iTQttxjYqUESZR2h6EeCQsnsQoYHXwMXsNTUO1nxvZhhtu6ArW3nXXXe4c8dcCIot6UQ0trBqr77nx4orB/tD/jZEZsyHvNWyL850HCP1MLMuee+7pXOsawxW2Mfqd7+KywXXqZxclrloW/ngSs8hx9gPN4HGmoDtxKnzOfQMLJtYqEi1w/9A50Th88MEHrt+ZxGNChskaJiGbI/lNS8HfA4lzxRLiLVj+vs29mT7mXB8xYoTzTKH/mcBmHZ3rdWfatGku1ts/b7hnEMpCHDKJzOjvb7/91q3HM4y+5/mE+yChC03l3dEqhBUDKbJokeyAjmdAws2cuBBvBg8vdsoAHasUs6xeaHAhhT8keDigjLHyMFBr6KJ7Ddn2cJi9Qozg84u1J1Y3tuZuOxmNmLVgm6yLabih08Y2Vts5Zxgc48ZFwDaxVV9//XWDtr0h2+9n6XhoMMhGAHoB5b/X0OnuG7PvKRbIDZZ12fb333+fFPcark22y0MC9x2u16DoSbS2R4I0wzzoglmbRMuDrICcO5wzkeIeuX8T18hAiOfPG2+80YytbT3Q7yTz+fe//13FTUrUDyywBx10UERrFu7mTFDxzOd8D09CJOrG0qVL3TMpOM5mUgZvGqyGpL8PelsxcYDrsU/QlsgknbDCn5XZXm4qWAo4OFhpGNhGMg36BwCZRxAd+NYGBznBvxlUciAbY3DcGG0PgrWHExILRDK1ndk3BmgMMJOt7Vip8Hcnsw0pWRuLxmh/U82wNVbfM6BHBOAm0Fjuf415r0HQMlj94YcfkqLtHi+05s+f7yz9omXijzPinNn5WNcXIlnBNZr06z6rrz+vI9VzE/Vn6tSpzmKFex8ilThfBBWxvlhhfZxmc2SJbnXCCncf4qGCkDEENxYG6D71ZfiNnll6zOYMxHwROA5sMM6gsR8Ojdn2xj4BG7rtwZkIfGu96T3Z2s6/k+m8YaYz/LxJlraH9z2iJJnO+ZZyr5HbS8uhpvOQawurKkmRPAh0JsNIRw06F0RLwU/y4g3hJ4+wBpLYpSmfma2FOXPmOIsVrpXEcTKBg8jCo4N4NmIJk1XUWjI9AMiKwwwaLnse756ALyZmXHyPw2/24enVSU366KOPOhcZgrUbuyCq2h653xs7o1hj9ntTpCNvzPb7gVEytr2x+17Xa/PcJ0XTwTUXFFXEKZLlLAjJnHxGQLw5mFX2ta18fUchkh3//KHcBBMJTCjhcka8D3FUFBAO1qsUDUNpaamrmYnXz5133ukSsfhnP5M5ZOQmjioZ+z0hhRW+lAQRUicFP0s/cwr777+/i8PxCQKCDwfcV7jp4/8P4bPZDOqYfcDcyHoEkfssL2q7+r25zhmd87peW9s5I5qP4PEmXoGkExxnEqkEBzG33367OwdwuyVZCbHHBPY//fTTzdRyIRoPYkux1hNDhcs0LmkqdN34VqtJkyZVK08TSz3FRCahhBVxB+eff77zc2WWgBObGz6z2r7eCjd5lhHT4gcL/kFBilceEmT3Cw/KZ/aNwQdxGVw0t912m9qufm/Wc0bnvK7X1nbOiMQQVGRjPeWUU9w5MmrUqMpYPPDny+mnn+6Sn3Be4arDeSFESwSLLC5pXA/E9/hJJyGSWlhxo7/kkkvcTRyTLGl8ucGTlIG6GAS24b7Ew4HsaxRBjVQrgwxFmHN9DIEfNFBzgIuGGANfiFZtV7831zmjc17Xa2s7Z0TzEKxhBwwaEc3EMNx4442hKVOmRIy1woWXc4H6aooxES0darDh/hxuPREiaYXV9OnT3Qwq+eqpdh2EZd26dQt988037t8EFHLDv/XWWyv9/v3M68SJE11WK3zGgyZF/Md/+eUXtV39nhDnjM55Xa+t7ZwRzQvunGuvvbarA0NmSI51pPIK3rI1YcKEynNJiJaOMluKFiesmFHD9z+IzxT3/PPPO1cEXwCPAQX+sPh7hxez5GHBYIJ0w2q7+j1RzxnQOa/rtTWdM6L5BoyXXnqpO94Uvn/rrbcqa5kJIYRoocIqOGsaHkxNXQGCaH31d6CAZY8ePVxaRh9YPXfuXOfKMmDAAFcgU21XvyfyOQM653W9tqZzRjQPZDlDRBMsLoQQopUIq2imWTJfMevqZ2b9gOKdd95xqYCZiSPwkDz4pMe88sor3TrNmaZRbVe/67zR9ap7jUjEOKtkTGEshBDJQAr/swRn0003tYEDB9oLL7xgZWVllpaWVvnZkiVL7OGHH7apU6daXl6enXPOObbllltaoqC2q9913uh61b1GCCGEaAWEEhyyEZFWGDeXoDUoGSoyq+3qd503ul51rxFCCCFaB6mW4EyaNMkKCwtts802c/9esGCBPf3007b77rvb4sWLLZFR29XvOm90vepeI4QQQrQOElZYeQ/Fr7/+2jp06GC9e/e2jz76yM444ww74YQT3OepqamV6yUSarv6XeeNrlfda4QQQojWRbolKCkpKe59woQJ1qVLF7vpppvs2WeftZ49e9rYsWNt1113tURFbVe/67zR9ap7jRBCCNHKCCUwFC8k2x9Z/9q3b+8qxicLarv6XeeNrlfda4QQQojWQ8JnBbzwwgudBejKK6+0rKwsSybUdvW7zpvkQderEEIIIepDwgur8vJyF0uVjKjt6nedN8mDrlchhBBCtGhhJYQQQgghhBCJTnKagoQQQgghhBAigZCwEkIIIYQQQoh6ImElhBBCCCGEEPVEwkoIIYQQIsl47LHHXNbkGTNmxPX94447zgYOHGitdf8jwbbYJttuLvbaay87+eSTG2x7hx9+uB166KENtj1RMxJWQgghhGg13HPPPW7wvPnmmzd3U0Qz8fTTT9ttt92WcP3/+eef27vvvuvKf3hWrFhhRx11lHXq1MnWWmste/jhh6t975tvvrHc3FybPn16tc/Y1osvvmg//PBDo7dfSFgJIYQQohXx1FNPOUvNV199ZX/88UdzN0ckkLAaMGCArVmzxv7v//6vWY7LTTfdZDvvvLMNGTKkctn5559vH330kavnus8++zhr1hdffFH5Ocm9zz77bDv33HNt0KBB1ba58cYb26abbmq33HJLk+1Ha0YWKyGEEEK0CpjRZ1B66623Wrdu3ZzIEk3L6tWrE7bLsWRmZ2dbWlpak//2okWLbOzYsdXc9t544w277rrrnHi64447bLvttrPXX3+98nPO4ZkzZ9oll1wSddts86WXXrJVq1Y16j4ICSshhBBCtBIYhOJStffee9vBBx8cUVj5OJubb77ZHnjgARs8eLBlZWXZZpttZl9//XW1OKW2bdva3Llzbf/993d/I9iwMpSVlVWuh8WBbfJeW0zPjz/+6LaL2xeD/J49e9oJJ5xgS5cujXu/X3nlFVt//fXd9nh/+eWXoxZKx5Kz3nrruXV79Ohhp556qi1fvrzaeldccYX17t3buaDtuOOO9ssvvzhLIG0Pj4P6+OOP7YwzzrDu3btb37593WeIAZYNHz7ccnJyrEuXLnbIIYdEjJn6+eefbaeddnLr8f1rrrnGtSGcV1991R1b2sUx49hdffXVVY7FDjvs4AQMv0/bePlYs2gxVh988IFtu+221qZNG+vYsaP97W9/s19//bXKOvQH38UKSh+wXocOHez444+3goKCWo8RbSotLbVddtmlynIsaJyzns6dO1duD5F60UUXOeHFuReNXXfd1a07bty4Wtsh6kd6Pb8vhGhAuJlzE/bwYOAmusEGG7iHBZ+1a9euzttlhha/bVwFuNkLIURrBCF14IEHWmZmph1xxBF27733OrGEaIrkLpafn++EBQPmG2+80X132rRplpGRUbkeg/bdd9/dxWwhxt577z3ndsWg/vTTT69zGxn88hvc7xFViAoEHu/jx493bakL3PsPOuggW3fddd0AHIHGtr3ACcK++ucQFhIsfHfddZdNnDjRxf/4/b744otdf+y7775u34nf4b2wsDBiGxBQCM5///vflRYr+p1nE8kVaAuihuOB8EGkIdhgwYIFTrghOhARiBv6A5EVDm1HYPzzn/907wgifjMvL8+52cHo0aNt5cqVNmfOHPvvf//rltUkSjiee+65pxO6iCeEzp133mlbb721fffdd9USgGAdwiWPvubzhx56yAnKG264ocbjRF8gLnFHDMK5iYV17bXXdufF22+/bQ8++KD77D//+Y/16dOnVtdFjj39xTE84IADalxX1JOQECJhePTRR0NclldddVVozJgxoUceeST0n//8J7TbbruFUlJSQgMGDAj98MMPdd7uTTfd5LY7ffr0Rmm3EEIkOt988427D44bN879u7y8PNS3b9/QOeecU2U97pOs16VLl9CyZcsql7/66qtu+euvv1657Nhjj628ZwfZeOONQyNHjqz894cffujW4z3Sb3Hv9xQUFFRr+zPPPOPW++STT6o9L2q7r48YMSLUq1ev0IoVKyqXvfvuu+67PFM8n376qVv21FNPVfn+22+/XWX5ggULQunp6aH999+/ynpXXHGFW48+CW/jNttsEyotLa2yfqT9/PLLL936TzzxROWyc8891y2bMGFC5bJFixaFOnToUG3/I23z1FNPDeXm5oYKCwsrl+29995V9r2m40H/de/ePbR06dLKZTyHU1NTQ8ccc0zlsssvv9x994QTTqiyzQMOOMCdS7VBHwXPGc+PP/7ozlO2zeuggw4KlZWVhaZNmxbKyclxfRYLw4YNC+25554xrSviRzFWQiQgzI4dffTRbtaQmcF33nnHzZrhg73ffvu5GTMhhBB1s1bh2ob1A7D8HHbYYfbss89WcRXz8FnQBQtXMMBqEM5pp51W5d+sG2m9WAhaYrAALVmyxLbYYgv3bywgdWH+/Pn2/fff27HHHuvc0oKuYVgxgvzvf/9z6/AZv+lfI0eOdBadDz/80K33/vvvO+sRVqggZ511VtR2kHAhPG4puJ8lJSXOkkbSBrwqgvv55ptvuv0fNWpU5TKsX2TKCye4TayNtJ9jgevcb7/9ZnXF9x+ufXiPeDbccEPXT7QtlnOBfcNqVhOsEzzfPHisTJkyxVn4eH/hhRcsNTXVzjvvPGeJpG+In9poo42cpeyqq65yCS3CYdv0h2hcJKyESBLwL7/sssucX/iTTz4Zsy8+rgv/+te/3N/cdL1PedCPne3x8OShxMMD14zZs2c3w14KIUTDg3BCQCGqcG8jDoYX7nsLFy50YiGc/v37V/m3H/SGxxtx72WgH75u+HqxsmzZMjvnnHOcCOSezLZ9tjdc2OoCzwsYOnRotc+IbQrCoJ3t47bGbwZfJD1gYi+4zWDmOuDZEUkYQKRsdUwQ4qbXr18/5/betWtX91ukFw/uJ78XS/sBd0lc3RCI7du3d9tjkjKevgvua6TfWmeddZxQCU/GEet5E4lIgsifY2T2832OiyMuntdff71NnjzZPbNx9X/kkUdcOYFIdbjYdl3dSEXdUYyVEEkEftRk/uGGygxgLL74xAT8/vvv9swzzzh/ch5e4AcC1157rRNs+IWfdNJJtnjxYuc/TuYh/OoVkyWESHYYiGJ9QFzximTN2m233aosi5YZLnzwG0sGuWgD2kiWMu7FxNswITZixAhnLSJRwx577BExYUNDwbYRVdEyJYaLx7oQKR4KC9ejjz7qBMGWW27pxBD9hEiIZz8RZNtvv70TVFhtiHFDkGD9opZTY/ZdPOdNOMRXxSK+OGcQ3sSbEV9Fco6tttqqMj6bODmOYTBeG9h2JIEqGhYJKyGSCAJ8efhMnTrV/RtXDNwBguAWQFD2Z5995lwQcFnYZJNNnLAia1Uw0JbZuMsvv9xlWAqmakWMUfuCma+aUrgKIUQywEAT0XD33XdX+ww3KrLk3XfffREFQEPgrRYM/iNZRIKDX6xn1CzCmhO0JsWDT4QQ6ftYOoIgRHA5JylDTf3gt4nFL2iJwlOiLlY6XNpwUQzWV8L1MbyP+L1Y2k/GRdrA8WRi0BOpaG6slhu/r+G/BbgWMlFJMo2GgOQUFPKtDRJ84OZI5kmYN2+ey4Lo4W+yVAbBdRMvFEIJROMiV0AhkgxmL7mpNoQvPg8gZvGYIQ361GP9YmbL+9QLIUSygssZ9zqKq5JiPfx15plnunvqa6+91mhtYICOJeOTTz6pspzJq0jWjnDrRqRitrHQq1cvZ/V6/PHHq7jC4e1A5r0gPAewhmABCYeBuRc8FLBNT093A/wgZA+sC+xr+H7iLRFuxdtrr72cBwYFnT14VoRb1iL1XXFxcbU+BsRQLK6Bwf4LCr5JkyY5zxHa1lBgtUOY1hSbh5sok6FkOMQaB7iMBuPHSAPPMzwIx5oxApYt0bjIYiVEkoGvOzOv/ibLzCauLd7/3RPLQ4NZQB5C0dwDgimFhRAiGUEwIZyizdYzGeWLBZOwojHA04AaTQgHrCVYhyj8Gn7fxo0NawupzEnogKsXA/hIVpdYIe035Tq22WYbF4PLc4N2UKsqWDAWNzrcyFifhA24RvIM4DlBYovbb7/dCVEG8riiYWmiT3FRJN36W2+95Sw4sVqDELpjxoxxfUMijS+//NJZzHCJC3LBBRe49fgdftenW0esEmfsQTRgGcQKRqp42sH3IrngEVP83HPPubTspDNnwpLU8ZFAxJBQCuFz4oknVqZbp93EMDcUHCMEK31wyimnRFwHt32SWXAueUhggesjqf3pk/vvv9+lZw+CkCZ9PQk3ROMiYSVEEkHdDQSTD2Ctry8+6/Dw4YEYyS+8ptoeQgiRDCCYmN2PNqgkwxqDWtarTxHe2mAwjljC5ZBkDdy/GbRTsDe8fhbxR7gtIgoQONyjg+5edYHnAcLo0ksvdVlmEXXENlFMN7xgMW1DdDA4xw2cgT7u4ySAwEXQQ00mBurUU0IIIDoQgIg3b0mpDYQazx36HWsK22db1MMKtxrhPUGfkKwB4UXmPfoDoeNhOWIV93j2FZFFu7GwhW8TN3rEI/1A7DGCJJqwomAvtaOwFOGeidhEhNIHkZJyxAuCFQvY888/H1FY/fTTT64m1oQJE6osR2ixH4g8JhDYt/Dvc/xx8Y+nDqaoI/VI1S6EaGB8zY+vv/464ufUtOLzhx56yNVX4e8rr7yyyjq///67W05NDc/NN98csd7JjTfe6JZPnjxZx1IIIUTcLF++3D1PrrnmGvVinFCnjPpYPMcbiokTJ7o6mLyLxkcxVkIkUVYrfN+ZIaN+R1188X1wbXhQMDNYbAd3wvDt8O/GnL0VQgiRnESqpeifPTvssEMztKhlQMIpLJS4gjYUWPlw4cSrRTQ+cgUUIgHB7YNgVAKGqbGCqMJHGncF4gVwteAVqy8+rh0wevRol8oWVwbcHnAJISMg7iHUtSJrIK4CbIMsWbgT+MxDQgghBBCfRK0kXNdwGScLLZlnEQVBl0ER3/O/IYlUXkA0HhJWQiQgPs1uZmamK7qIDzWzgdSlCPpIx+qLT3Au1i785/EVJ7YK8YQli1oYw4YNc37mWK6Ago1sS6lZhRBChEMZD+KvmNjLy8urTGjBRJ0QrZkU/AGbuxFCCCGEEEIIkcwoxkoIIYQQQggh6omElRBCCCGEEELUEwkrIYQQQgghhKgnElZCCCGEEEIIUU8krIQQQgghhBCinkhYCSGEEEIIIUQ9kbASQgghhBBCiHoiYSWEEEIIIYQQ9UTCSgghhBBCCCHqiYSVEEIIIYQQQtQTCSshhBBCCCGEqCcSVkIIIYQQQghRTySshBBCCCGEEMLqx/8DhkNWzr8K7+gAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -62512,10 +32180,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:08:02.619824Z", - "iopub.status.busy": "2026-02-11T21:08:02.619824Z", - "iopub.status.idle": "2026-02-11T21:08:02.625093Z", - "shell.execute_reply": "2026-02-11T21:08:02.625093Z" + "iopub.execute_input": "2026-03-20T15:35:24.537844Z", + "iopub.status.busy": "2026-03-20T15:35:24.536643Z", + "iopub.status.idle": "2026-03-20T15:35:24.552905Z", + "shell.execute_reply": "2026-03-20T15:35:24.549599Z" } }, "outputs": [ @@ -62546,16 +32214,16 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:08:02.628276Z", - "iopub.status.busy": "2026-02-11T21:08:02.627285Z", - "iopub.status.idle": "2026-02-11T21:08:26.293436Z", - "shell.execute_reply": "2026-02-11T21:08:26.293436Z" + "iopub.execute_input": "2026-03-20T15:35:24.561080Z", + "iopub.status.busy": "2026-03-20T15:35:24.559954Z", + "iopub.status.idle": "2026-03-20T15:36:48.870411Z", + "shell.execute_reply": "2026-03-20T15:36:48.867937Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -62589,16 +32257,16 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:08:26.296789Z", - "iopub.status.busy": "2026-02-11T21:08:26.296789Z", - "iopub.status.idle": "2026-02-11T21:08:26.604345Z", - "shell.execute_reply": "2026-02-11T21:08:26.603840Z" + "iopub.execute_input": "2026-03-20T15:36:48.877254Z", + "iopub.status.busy": "2026-03-20T15:36:48.876340Z", + "iopub.status.idle": "2026-03-20T15:36:49.605633Z", + "shell.execute_reply": "2026-03-20T15:36:49.602871Z" } }, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1YAAAFECAYAAAAk3a/SAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAADtYUlEQVR4nOydd3hUZfbHP9NLMmkkJISEEOkdiQIiVaWLIEVddVEs6PrbZdG1gQ1URBfXsrrWXVERsaCiCCqooCCIEumhBAghhfRMMsn0mfv7Y5hrJjPpofp+nofnIfe+995z37mTvOeec75HIUmShEAgEAgEAoFAIBAImo3yTBsgEAgEAoFAIBAIBOc6wrESCAQCgUAgEAgEghYiHCuBQCAQCAQCgUAgaCHCsRIIBAKBQCAQCASCFiIcK4FAIBAIBAKBQCBoIcKxEggEAoFAIBAIBIIWIhwrgUAgEAgEAoFAIGghwrESCAQCgUAgEAgEghYiHCuBQCAQCAQCgUAgaCHCsRIIBIIzxMaNG1EoFCxYsOBMm9LqHDt2DIVCwc0339wq51MoFIwcObJVznU28/bbb6NQKHj77bdP6XVuvvlmFAoFx44dO6XXOV85XZ+TQCA4txCOlUAgaHU8Hg9vvvkmI0aMICYmBo1GQ9u2benbty+33XYbX3zxxZk2USA4r1mwYAEKhYKNGzeeaVP+UHTs2JGOHTueaTMEAsEZQn2mDRAIBOcXHo+HK6+8kq+//pqoqCgmTpxIUlISTqeTffv28f7773PgwAGuuuqqM22qQPCHZfHixTz44IO0b9/+TJsiEAgE5w3CsRIIBK3KihUr+Prrr+nXrx8//PADkZGRAfutVivbtm07Q9YJBAKAdu3a0a5duzNthkAgEJxXiFRAgUDQqmzZsgXw1XDUdqoAjEYjo0aNCnnsihUrGDVqFFFRUej1enr06MGTTz6Jw+EIGuuvuSkpKWH27Nm0a9cOnU5Hr169WLp0adB4SZJ45513GDJkCHFxcej1epKTkxk7diwffvhh0Pj09HSmTZtG27Zt0el0pKSkcNddd3HixImgsf56laNHj/LSSy/Rt29fDAZDk2qCtm7dyhVXXEFkZCQmk4mxY8eyffv2oHH5+fk8/vjjXHrppSQkJKDVaklMTOT6668nIyMj5Lm/+OILLr/8cnmOEhMTGTFiBK+88krQ2LKyMubNm0ePHj0wGAxERkZy+eWXs27dupDntlgs3HPPPSQlJaHX6+nevTvPPfccXq+30ffux+l08sQTT9CpUyd0Oh2pqak8/PDDIT9/P263m1deeYXBgwcTERGB0Wjkwgsv5OWXXw5pgyRJvPjii/Ts2RO9Xk/79u3561//SkVFRcg0rpq1NF9//TUjR44kMjIShUIhj1m1ahU33ngjXbt2JSwsjLCwMNLS0vj3v/9d5zwcPnyYGTNmEB0dTVhYGEOGDGHNmjV13ueGDRuYPXs2PXv2JCIiAoPBQO/evVm4cCF2uz1gbMeOHVm4cCEAo0aNQqFQyP/81Fdj9dFHHzF8+HAiIyMxGAz06dOHxYsXh/wc/HNWXV3NfffdR4cOHdDpdHTu3JlnnnkGSZLqvKfajBw5EoVCgdPp5PHHH6dbt27odLqAOr3c3Fz++te/csEFF6DT6WjTpg1XXXUVv/76a9D5LBYLTzzxBL179yYiIgKTyUSnTp249tprSU9Pl8c1VOvYmPQ+/zmys7PJzs4OmPOa9m/atIlJkyaRlJSETqcjISGBwYMHy5+XQCA4txERK4FA0Kq0adMGgEOHDjXpuFtuuYWlS5eSlJTEtGnTiIqK4ueff+aRRx7hu+++Y/369ajVgb+yzGYzl156KVqtlunTp+NwOPj444+55ZZbUCqV3HTTTfLYhx56iMWLF5Oamso111xDZGQkJ06c4Ndff+Xjjz/m2muvlcd++eWXTJs2DUmSmD59OikpKaSnp/Pqq6/y+eefs3nzZlJTU4Pu4e9//zubNm1i4sSJTJgwAZVK1ah737ZtG4sXL+aKK67g//7v/zh8+DCffvopP/74I+vWrWPYsGHy2B9//JGnn36aUaNGMW3aNMLDw8nMzGTlypV88cUX/PTTT/Tr108e/8Ybb3DHHXeQkJDApEmTiI2NpaioiN27d7N06VLuuusueWx2djYjR47k2LFjDBs2jHHjxlFdXc2XX37JuHHjeP3117n99tvl8Q6Hg8svv5xff/2Vfv36ccMNN2A2m3niiSf44YcfGnXvfiRJ4pprruHzzz+nU6dO/PWvf8XpdPLWW2+xZ8+ekMe4XC4mTZrEN998Q7du3bj++uvR6/Vs2LCBv/3tb2zbto1ly5YFHPN///d/vPrqqyQmJjJ79my0Wi1ffPEFv/zyCy6XC41GE/JaK1eu5Ouvv2b8+PHceeedZGdny/sefPBBlEolgwYNon379lRUVPD999/z97//nV9//TXIhszMTC655BJKS0sZP348/fv35/Dhw0yZMoXx48eHvP4zzzzDgQMHGDJkCBMnTsRut/PTTz+xYMECNm7cyLfffis/b3PnzmXVqlX88MMP3HTTTU2q+Zk/fz6LFy8mNjaW66+/nvDwcL766ivmz5/PN998w7p169BqtUGfw9ixY8nPz2f8+PGo1WpWrVrFgw8+iN1u57HHHmv09QGmTZvGr7/+yvjx45kyZQpt27YF4LfffmPMmDGUlZUxduxYpk6dSklJCatWrWLo0KF89tlnTJgwAfA9T+PGjWPLli1ccskl3HbbbajVanJzc9mwYQPDhg0jLS2tSXbVR8eOHXnsscd44YUXAN9n4Kd///4AfP3110ycOJGIiAiuuuoq2rdvT1lZGfv37+eVV15p8jwJBIKzEEkgEAhakd9++03SaDSSQqGQbrzxRumTTz6Rjh07Vu8xS5culQDp6quvlqxWa8C+xx57TAKkF154IWA7IAHSrbfeKrndbnn7vn37JJVKJfXo0SNgfExMjNS+fXupuro66PrFxcXy/y0WixQTEyMplUrpxx9/DBj39NNPS4A0evTogO033XSTBEiJiYnS0aNH673XmmzYsEG+j5deeilg36pVqyRA6ty5s+TxeOTthYWFUmVlZdC5du7cKYWFhUnjxo0L2D5gwABJq9VKhYWF9d63JEnSiBEjJIVCIa1YsSJge3l5udSvXz9Jr9dLBQUF8vZFixZJgDR16tQAG48ePSpFR0dLgHTTTTc1PBGSJC1fvlwCpMGDB0s2m03eXlpaKl1wwQUSII0YMSLgGP+z8de//jXgGXC73dItt9wiAdKqVavk7T/++KMESF27dpXKy8vl7Q6HQxo2bJgESCkpKQHX8D+bCoVC+uqrr0Lafvjw4aBtHo9HmjlzpgRIP//8c8C+0aNHh3ym/Z85IC1dujRg35EjRySv1xt0nYcfflgCpA8++CDk3GzYsCGkzf5nNisrS962ZcsWCZCSk5OlEydOyNtdLpd05ZVXSoC0aNGigPOkpKRIgDR+/PiA725hYaEUGRkpRUZGSk6nM6QNtRkxYoQESH369Al6Nl0ul9SpUydJp9NJGzduDNiXl5cnJSYmSgkJCZLdbpckSZJ2794tAdKUKVOCruPxeKSysjL5Z//38LHHHgtpV0pKSp3PRe3PKdRYP1OnTpUAaefOnUH7at+vQCA4NxGOlUAgaHU+/PBDKSEhQV4kAlJMTIw0ZcoU6Ysvvgga379/f0mtVgcsdv243W6pTZs20sUXXxywHZCMRqNUUVERdMzw4cMlQLJYLPK2mJgYqWPHjvLCqy7ee+89CZD+9Kc/Be1zuVxSx44dJUDKzs6Wt/sXqbUXyg3hX9DVdp78+BeatReSdTFp0iRJp9MFLGQHDBggGY3GgIVkKHbu3CkB0vTp00Pu9y/6//Of/8jbOnfuLCmVypCOhX9h31jH6oorrpAA6fvvvw/a51/E1nSsPB6PFBMTIyUkJEgulyvomPLyckmhUEgzZsyQt916660SIL3zzjtB4zdv3lyvYxVqgd4Q6enpEiAtXLhQ3paTkyMBUmpqaoAz6Mf/mddesNdFaWmpBEizZs0K2N4cx+q2226TAOn1118PGn/w4EFJqVRKqampAdv9jlVmZmbQMX7Hcs+ePY26F/+913SG/fifv3vvvTfksS+88IIESGvWrJEk6XfHKtT3uDan27E6ePBggzYJBIJzE5EKKBAIWp1rrrmGq6++mg0bNrB582Z27NjB5s2bWbVqFatWrWLmzJly7YrVamXXrl3ExsbKaTS10el07N+/P2h7ly5diIiICNqenJwMQHl5OeHh4QDccMMNvPTSS/Ts2ZNrrrmGESNGcMkllwTVgf32228AXHbZZUHnVavVDB8+nGPHjrFjxw46dOgQsH/gwIEBP+/cuZNVq1YFbIuKigpIEwIYNmwYSmVwyevIkSP54Ycf2LFjByNGjJC3r1mzhtdee43t27dTUlKC2+0OOK6kpEQWJrjhhhv4xz/+Qc+ePbnuuusYMWIEl156KXFxcQHHbN26FYCKioqQtSbFxcUA8udgsVg4fPgwycnJdOrUKaTtTakb+e2331AqlQwdOjTkuWpz6NAhysrK6NKlC08++WTIcxoMhoDnZseOHQAhrzF48OCgVNOa1P5sa1JaWsqSJUtYu3YtR48epbq6OmB/Xl5eSBtCpYr6P/PaVFdX8+KLL/LZZ59x6NAhLBZLQP1SzWs0l/qe/a5du5KUlERWVhYVFRUB35vIyEg6d+4cdEzN72FTCDXX/uczOzs75POZmZkJ+J7PCRMm0LNnT/r378+KFSvIzs5m8uTJDB06lIsuuigolfF0ccMNN/Dpp58yaNAgrr32WkaNGsWll15KUlLSGbFHIBC0PsKxEggEpwSNRsOYMWMYM2YM4JNh/+STT7jlllt49913ufrqq5kyZQrl5eVIkkRxcXGTC7ijoqJCbvcvkD0ej7zt+eef54ILLmDp0qU8/fTTPP3006jVaiZMmMC//vUveWFYUVEBUKdimn+72WwO2peQkBDw886dO4PuKSUlJcixio+PD3kt//n8NgG8+OKLzJ07l+joaEaPHk2HDh0wGo0oFApWrVrFrl27AkQG7rnnHmJjY3nllVf497//zQsvvIBCoWDEiBEsWbKEiy66CPA5BwDr169n/fr1Ie0BqKqqCrCpIdsbS0VFhdzzrDHn8tubmZlZ73Pjt7chm1UqlVwfGIq67sdsNnPxxReTlZXFwIEDmTlzJjExMajVasxmMy+++GLA59GceXO5XFx22WX88ssv9O7dm2uvvZa4uDh5rhYuXFivwEdjacyzf/z4ccxmc4Bj1ZTvYWOo7/P++OOP6z3W/3mrVCq+//57Hn/8cVauXMkDDzwAgMlk4qabbmLx4sXyS5fTxdSpU/nyyy/517/+xVtvvcXrr78OQFpaGosXL2b06NGn1R6BQND6CMdKIBCcFlQqFddccw179uzhySef5Pvvv2fKlCnyAu3CCy+U35ifquvPnTuXuXPnUlRUxObNm/nggw/4+OOP2bdvH/v27UOn08n2FBQUhDyPXxUwlOJhTdU18Cmv1VQEq4vCwsKQ2/02+K/ldrtZsGABCQkJ/Pbbb0ELYP9b/drMnDmTmTNnYjab2bJlC5999hlvvfUWY8eO5cCBA8TFxcnXePHFF5kzZ06DNvvHN2R7Y4mMjKSsrCykgESoc/mvf/XVV/Ppp5826hr+6GZhYSEXXHBBwD6Px0NpaWmdfZ1qf7Z+/vvf/5KVlcVjjz0WFEnZunUrL774Yki7mzJvn3/+Ob/88gs333xzkOLliRMnWk1RruazHyoKWd+z35qEmmv/NT///PNG98CLjo7m+eef5/nnn+fw4cP88MMPvP7667z88suYzWZZVMQfLa4d+fVjNpvrdB6bysSJE5k4cSLV1dVs27aNL7/8kldffZUrr7ySHTt20LNnz1a5jkAgODMIuXWBQHBaMZlMAHIaU3h4OL169WLfvn2UlZWdFhvatm3L1KlT+eijj7jssss4cuQIe/fuBXwOHvjkk2vjdrvZtGkTAAMGDGg1ezZv3hxSlttvg9+mkpISzGYzQ4YMCXKqqqqqGnRMo6KimDBhAm+++SY333wzZWVl/Pjjj4AvFQ6Q768hTCYTnTt3Ji8vjyNHjtRpe2MZMGAAXq+XzZs3N+pc3bt3l5UjXS5Xo67hn8dQ1/j555/rXFjXx+HDhwGfkl1tQqX01bQhVCQn1L36rzF16tRGXQOQ0wybEi2q79k/fPgwubm5pKamtpqT0RSa+nzWpnPnztx666388MMPhIeH8/nnn8v7oqOjAcjJyQk67vDhwwER44ZQqVSNmvOwsDAuu+wynnvuOebPn4/T6eSrr75q9HUEAsHZiXCsBAJBq7JixQrWr18f0lEoKCjgzTffBGD48OHy9nvuuQen08ktt9wSMsWuvLy8RdEsh8PBTz/9FLTd5XLJzpzRaARgypQpxMTEsGLFCn7++eeA8S+88AJZWVlcccUVQfVVLSEzMzOop9Tnn3/ODz/8QOfOnWW59bZt22I0GklPTw9IcXO5XPz973+npKQk6NwbNmwI2UuoqKgI+P2+L7roIoYNG8ann37KW2+9FdLOPXv2yMcBzJo1C6/XywMPPBDweWdlZfHvf/+7sbcvnwt8svg1+zKVlZWFrKFSq9X87W9/48SJE8yZMwebzRY05sSJEwG9vWbOnAnAokWLAhbLTqeT+fPnN8leP34p89rOyI4dO1i8eHHQ+KSkJEaPHk1WVhYvv/xywD7/Z97Yaxw9elROcauNP63x+PHjjbgLH7fccgsATz75pFxTBz7n7N5778Xr9XLrrbc2+nytyeTJk+nUqRP/+c9/WLt2bcgxW7duxWq1Ar5n8OjRo0FjysvLcTgcGAwGeVv37t2JiIjg888/D3i+bTZbo6K3NWnTpg3FxcUhn8cff/wxpPPuj176v4sCgeDcRaQCCgSCVmXbtm28+OKLJCQkMHToULnfU1ZWFmvWrMFmszF58mSmT58uH3PLLbeQnp7OK6+8QqdOnRg7diwdOnSgrKyMrKwsfvzxR2bNmsVrr73WLJtsNhtDhw6lc+fOpKWlkZKSgt1uZ/369ezfv5+rrrqKHj16AL4I2ltvvcWMGTMYMWIEM2bMoEOHDqSnp7Nu3ToSEhLk2ojWYty4cfzjH//gq6++ol+/fnIfK71ez1tvvSWnKimVSubMmcPTTz9Nnz59mDx5Mk6nkw0bNlBWVsaoUaPYsGFDwLmvvvpqwsPDGTx4MB07dkSSJDZt2sSvv/5KWloaV1xxhTz2/fff57LLLuPWW2/l3//+N4MGDSIqKorc3Fx2797N3r172bp1q9xX6B//+AerVq3ik08+YcCAAYwdOxaz2Sw3mP3iiy8aPQd/+tOf+PDDD/niiy/o3bs3kydPxuVysXLlSi6++OKQUbFHHnmEXbt28dprr7F69Wouu+wy2rdvT1FREZmZmfz0008sWrRITq8aMWIEs2fP5o033qBXr15MmzYNjUbD6tWriYyMJDExMaSISH3MnDmTJUuWMHfuXDZs2ECXLl3IzMzkyy+/ZOrUqSGbT//nP//hkksuYe7cuaxbt07+zD/77DMmTZrE6tWrA8ZPmjSJzp0789xzz7Fnzx4uvPBCjh8/zpdffsnEiRNDOk+jRo1CqVQyb9489u7dK0dlHn744TrvZciQIdx///3885//pHfv3kyfPp2wsDC++uor9u7dy9ChQ7nvvvuaND+thUaj4dNPP2Xs2LFMnDiRIUOG0L9/f4xGIzk5Ofz6668cPXqUEydOYDQa2bVrF1OnTuXiiy+mR48eJCYmUlxczOeff47L5QpwSDUaDX//+9954oknuPDCC7n66qtxu92sX7+exMREEhMTG22nv6/buHHjGD58ODqdjn79+jFp0iTmzJlDXl4el156KR07dkSr1ZKens73339PSkoK11133amYOoFAcDo5o5qEAoHgvOP48ePSyy+/LE2ZMkXq2rWrZDKZJI1GIyUkJEjjx4+Xli1bFlJaXJIkafXq1dLEiROluLg4SaPRSPHx8dLFF18sPfTQQ9L+/fsDxhKir5Gf2lLSTqdTeuaZZ6Rx48ZJycnJkk6nk2JjY6VBgwZJr776quRwOILO8csvv0hTpkyRYmNjJY1GIyUnJ0t33nmnlJeX1+D1GktNmectW7ZIl19+uWQymaTw8HBp9OjR0i+//BJ0jMvlkv71r39JPXr0kPR6vRQfHy/deOON0rFjx0La8eqrr0pTpkyRUlNTJYPBIEVHR0v9+/eXnnnmmZD9sCorK6VFixZJAwYMkMLCwiS9Xi917NhRmjBhgvT6669LVVVVAeMrKiqku+++W0pMTJR0Op3UrVs36dlnn5WOHDnSJLl1SfL1k1q4cKGUmpoqabVaKSUlRZo/f75kt9vr/Ly9Xq/07rvvSpdddpkUHR0taTQaKTExUbr00kulRYsWScePHw8Y7/F4pOeee07q1q2bpNVqpXbt2kl33XWXZDabpfDwcKlfv34B4+uS1a7Jvn37pEmTJklxcXGS0WiUBgwYIL355ptSVlZWnXOQmZkpTZs2TYqMjJSMRqM0ePBg6csvv6zzesePH5euv/56KTExUdLr9VLPnj2lZ555RnK5XHXOzbJly+T+Y5xse+Cnvmd2xYoV0qWXXiqFh4dLOp1O6tmzp/Tkk08G9BfzU5+8eEOS77Xxy63XR2FhofTAAw9IvXr1kgwGgxQWFiZ17txZmjZtmrRs2TJZej8nJ0eaN2+eNGTIECk+Pl7SarVS+/btpXHjxklr164NOq/X65UWL14sXXDBBfL3/b777pOqq6ubJLdeVVUl3XnnnVL79u0llUoV8Pl/+OGH0nXXXSd17txZCgsLk0wmk9SrVy9p/vz5UlFRUaPmSCAQnN0oJClEjohAIBAIBH8gMjMz6dq1K9dddx0rVqw40+YIBAKB4BxE1FgJBAKB4A9DQUFBUP2f1WqVJfCvvvrqM2CVQCAQCM4HRI2VQCAQCP4wvPDCC6xYsYKRI0fSrl07CgoK+O6778jNzWX8+PHMmDHjTJsoEAgEgnMU4VgJBAKB4A/D6NGj2bVrF+vWraOsrAy1Wk3Xrl2ZM2cOc+fOrbNflUAgEAgEDSFqrAQCgUAgEAgEAoGghYgaK4FAIBAIBAKBQCBoIcKxEggEAoFAIBAIBIIWIhwrgUAgEAgEAoFAIGghwrESCAQCgUAgEAgEghYiHCuBQCAQCAQCgUAgaCHCsRIIBAKBQCAQCASCFiIcK4FAIBAIBAKBQCBoIcKxEggEAoFAIBAIBIIWIhwrgUAgEAgEAoFAIGgh6jNtwNmI1+slPz8fk8mEQqE40+YIBALBHwZJkrBYLCQmJqJUind/fsTfJYFAIDhzNPZvk3CsQpCfn09ycvKZNkMgEAj+sOTk5JCUlHSmzThrEH+XBAKB4MzT0N8m4ViFwGQyAb7Ji4iIOMPWNJ+9eWZ25pjpnxxF7/ZRZ9ocwVnAez8fo8LqJtKo5sbBHc+0OQJBEJWVlSQnJ8u/hwU+zpe/S4JTR0lJCZ06dQrYduTIEWJjY8+QRQLB+UNj/zYJxyoE/jSLiIiIc/oP2ME9pTgUeg6WeRjS49y9D0HrMbRnB9Kzy0lLiT6nn23B+Y9IdwvkfPm7JDh1OByOoG0mk0k8LwJBK9LQ3yaRwH4ek5YSTZRRQ1pK9Jk2RXCW0DcpilmXptI3KepMmyIQnHVs3LgRhUIR8t/PP/8cMHbLli0MHToUo9FIQkICc+bMoaqqKuicDoeDBx54gMTERAwGA4MGDWL9+vWn65YEAoFAcBoREavzmL5JUWIBLRAIBE1kzpw5XHzxxQHbOnfuLP9/586dXH755fTo0YPnnnuO3Nxcnn32WTIzM/nqq68Cjrv55ptZuXIlc+fOpUuXLrz99ttMmDCBDRs2MHTo0NNyPwKBQCA4PQjH6jxjd65ZTvUSTpVAIBA0nWHDhjF9+vQ698+fP5/o6Gg2btwop1l17NiR22+/nXXr1jFmzBgAfvnlFz744AOWLFnCvffeC8DMmTPp3bs3999/P1u2bDn1NyP4wxAZGcmGDRuCtgkEgtOHSAU8z0jPLsdsdZGeXX6mTREIBIJzFovFgtvtDtpeWVnJ+vXrufHGGwNqV2bOnEl4eDgfffSRvG3lypWoVCpmz54tb9Pr9dx6661s3bqVnJycU3sTgj8UWq2WkSNHBvzTarVn2iyB4A+FcKzOM0RdlUAgELSMWbNmERERgV6vZ9SoUWzfvl3et2fPHtxuNxdddFHAMVqtlv79+7Njxw55244dO+jatWuQeMDAgQMBX0qhQCAQCM4fRCrgKeRMpOWJuiqBQCBoHlqtlmnTpjFhwgRiY2PJyMjg2WefZdiwYWzZsoULL7yQEydOANCuXbug49u1a8emTZvkn0+cOFHnOPD1pqoLh8MRoPJWWVnZ7PsSCAQCwelBOFankNW78jlUWEW+2SacnRqIOjCBQHA2MmTIEIYMGSL/fNVVVzF9+nT69u3LvHnz+Prrr7HZbADodLqg4/V6vbwfwGaz1TnOv78uFi9ezMKFC5t9LwKBQCA4/QjH6hRSbHFwuMhCWbWD3bnmU+5EfJKew/qMQkb3jGdaWvIpvVZLqFkHJhwrQUsQTrrgVNO5c2cmT57Mp59+isfjwWAwAKF7Btntdnk/gMFgqHOcf39dzJs3j3vuuUf+2d+cUnD+0vHBNa1+zmNPT2z1cwoEgroRjtUpJM6kQ69RoVEpT4sTsT6jkJxyG29uyqJLvOmsXWimpUTLi2GBoLnszjXzyobDRBl9xdln6/MuOPdJTk7G6XRSXV0tp/H5UwJrcuLECRITE+Wf27VrR15eXshxQMDY2uh0upDRLoGgLiTJi9dmCdjm9XpRKkU5vUBwuhCO1SlkUr/f/2ieDididM943tyURYcYw1kdDQpVB7Y718zqXb56g0n9Es9a2+tDRE9OL+nZ5UQZtZitTuGkC04pR48eRa/XEx4eTu/evVGr1Wzfvp1rrrlGHuN0Otm5c2fAtv79+7NhwwYqKysDBCy2bdsm7xcIWguvzULuSzcEbCt9ZDRxcXFnyCKB4I+HeI1xivAvsif1S+ShiT1Py0J7Wloy/5zel5Q2YeSbbezONZ/ya7YW6dnl/HiomE9/y+OtzVln2pxmkZ5dzsECC69sOBxy7nfnmln6U9Y59bmczaSlRGPSq0mOMZ5pUwTnCcXFxUHbdu3axRdffMGYMWNQKpVERkZyxRVX8N5772Gx/B4dWLZsGVVVVcyYMUPeNn36dDweD2+88Ya8zeFwsHTpUgYNGiRS+wQCgeA8o1kRq7qUjgS/4xOusLRIuKI5EZC+SVHnZA1ThF5NkcWBUgGFlfYzbU6zSEuJZtvRUqKM2pBz73e8th0t5a5Rnc+Jz+ZsjsLV9ayfzTYLzm6uvfZaDAYDQ4YMoW3btmRkZPDGG29gNBp5+umn5XGLFi1iyJAhjBgxgtmzZ5Obm8u//vUvxowZw7hx4+RxgwYNYsaMGcybN4+ioiI6d+7MO++8w7Fjx/jf//53Jm5RIBAIBKeQZkWskpOTGTNmDMuWLaO6urq1bTqPUDTrKH9kY/Wu/GY1+z0Xe1kdKLDQ1qTDpNcwPS3pTJvTbJJjjJj06pBzH6FXszPHjFeS5M/0bI9ine6G0/XNx+5cM4vWZLBoTYa8P0Kv5mBBJRH6398RhbL5bJ9nwdnBlClTKCkp4bnnnuOuu+7iww8/ZOrUqWzfvp0ePXrI4wYMGMC3336LwWDg7rvv5o033uDWW29l5cqVQed89913mTt3LsuWLWPOnDm4XC6+/PJLhg8ffjpvTSAQCASngWY5Vo8//jj5+fncdNNNxMfHc+ONN/L111/j9Xpb275zlu4JJgwaJWFaVZMXdP6FYbHFEbRobIjT8bb+VC1SEyL19E+OotLuPmUL4FO5wE7PLseoVZMYZQg59wcKLEiSl0OFVfJnerodl6YSynE5ldSXTpmeXc6hwioOFVrk+TpQYMHm8nKg4PeUrLSUaLJLq1m3r4BP0nPkY8/meRacHcyZM4dt27ZRWlqKy+UiPz+fZcuW0blz56CxQ4cO5aeffsJms1FUVMTLL7+MyWQKGqfX61myZAknTpzAbrfzyy+/MHbs2NNxOwKBQCA4zTTLsZo/fz579+4lPT2dO++8k40bNzJhwgQSExO5++67A7rU/1GptLvplhDBgQJLvXU3ofBHnOJMOrolRFBpdzf6uqt35fP2T0e5+a1feGH9wWZaXz+nYpE6qV8iI7u1BWDjwWJZyKI51Oc8NWR77WOb4ohVWJ2s2pnHxoNFdY53eyEmTCt/pmd7dDGU43IqCRXVA7+4SR7bjpSwM8fMoYJKlv6UxaFCC7nlVootv0ta902KorDSTr7Zxsr0XODsn+fzCREdFAgEAsEflRaJV1x44YU8++yz5OTksH79eiZOnCgX5fbs2ZOnnnqK48ePt5at5xT+t+aZRVX8cKgoaKEYCv+CJLPQt4jtnmBq0mJwd66Z7w8UkVNup9rh5ut9hS2+j1CcikVq36QoZl2aSpxJB0gcKrTwpze2MveDHU1eoK3elV+nc9aQ7TUdL7+c98ECS6OcyAMFFpAgt9wWcvykfolc1r0tHWKMsriI/77P5logi93J3ryK07JQrrS76Z8chVKhCPiMVu/KJyPfgt0jUWFzs2bPCb7eW8Bv2eVY7K6g88RH6FGrlMRH+BqxngvzfL4gooMCgUAg+KPSKvk9CoWCYcOGYTabycvLY926dWRmZrJgwQIeffRRrr76av7973//4QQvDhRYMFuduD0SFru7QUfEvyDZdrSUbgk+ad5Zl6Y2+nrp2eU43F5UCnB7JYxa5SlpTBxKLr0p+KXViy0O4kw6WZY+PbucMK0Kg0ZFZlEVZdVOcsqs9EtuzvWkZtkeoVez7Wgpo3vGy3Le2aXVmPTqBudydM94Kmwu4iP0dX7WiVG+hqBGrbpJ4iKtleL5SXoOK9NziY/Qc8vQhh2NMK2KrBIrEXo1q3fln3LHxD9voe7ToFVid/vSjW1OD3tyzWhUCjxeTjrkPnbnmokz6bise9uAlgcNcbpFL85XkQ3Rp04gEAgEf1Ra7Fht2LCB5cuX88knn1BZWUmfPn149tlnueGGG1Cr1SxdupSnnnqKP//5z3z77betYfM5QXp2OR1ijOSVWzFoVcRH6BtcPPlSyfJB8rIr10zXeFOTFl1pKdFsPFhEpdWJBBRVOhq1GD7VC7za5//XuoNsOVKK2yOhUSlIzy6jrUkvOzEOtxez1YlGpSQ6TNvkBdqkfomkZ5cToVez9KesJt2XP4Wz8qQjvPFgEfvyK8g324D6m9BOS0umS7ypzjf1PqXIKkDC6fYSH6GXo0ANzb9fZXJXjpl+yVGNvqeacw/w7+8PU1bl4EhRFXaXp0F1wgMFFnRqJVUOT4PXag3q6nEGMKJrW/bkVVBYacfjldBpVCgVEGXUcKjQwqI1GXRPMLE+o5Aoo5ZuCY1vkn2qmw2H+o61hnJoU695Os7R0hcvAoFAIBCcqzTLsdq1axfLly9nxYoV5Ofnk5CQwG233cbMmTPp06dPwNh7770XvV7Pvffe2yoGnyv4F7JGrYpyqzPgjXpdfHegiAKzDZdXQqNScqSoqsmS6QaNiugwHQWVdqqdbjmFq75z+Bf8p2qBt+CLvRwoqKJ7Qjif3jWUQ4UW3B4JCXB5JA4XVdE1PoLs0mqKLA4KK+1oVAq6xoUxb0KPJtvUNymKzEIL//7+MHq1Mui+6lsspqVE89bmLH7JshOhV3Oo0EKV3UO1wxZQx1MXq3flk55dzrp9BSFtL6iwklNuQ5LApFfLz0Vj5r+gws6e3Aqszt9r7t7anEVhpZ3paUlMSwvuiVM7LUuvVuGVoMrpJqukukHHe3TPePJOOpXdE4IL808Hfgeka7yJ56/tz+pd+fx8tBSNSolOrcTh9rIzx8yRoip+PlpKscVOpc3N5P6J8mcdoVezKbOkzrlqSbPhxjgftZ2o3blm9uZV4HCfOsGf1mi70NRznK9ROIFAIBAIGkOzaqwuvPBC/vOf/zB8+HDWrl1LTk4OS5YsCXKq/PTq1YtLLrmkRYaea/hrOm4ZmsrIbo1LSSqrduL0SHglkCTfG/mm1Fe9suEwXglQQMc2RiINWlLahLF6V34jisklii2OU1J0fqzEisfj5ViJFYCu8SaMWhUqBWhUCqKNGsxWJ/EReiINGiQJvJJCjvI1pxh+ZXouZVUOCkL0xGqoBmRHjpmskmre3nIMp1sCBWjVykY5xwAVNhcOtzfo/JP6JWJ3S7jcXuwuL5U2dw1nLXTqYs1jFQoFUUYtx8tscrrVnjxfNG19Ruh6On9NWYXVyae/5VLlcBFhUBMXrqPK4W6wdmpaWjKDL2hDTJjutAlYfJKew53LtsuKfsUWB7nlvzu2iVEGLu/elrYmHYNSY9CplejUKlD42htU2j0oFAq2HC2Ta+TWZxSyPbucAwUWWdCiJhVWJ1uPlmJzNT0y1/iaot/bL6Rnl5PSJoy2NVJhWwv/9yVCr25xLaT/+fFHfxv6Dor6KoFAIBD8kWmWY/XWW29RWFjI8uXLGTt2LEpl/acZNWoUGzZsaJaB5yr+xQ38XifV0MIkJkxLuE6FTq2gbYSePu0jG/3Wd/WufLJKfFLUV/dP5LqBHfjbZZ3pdjLKUN9ix6/IF2fSnZJF0dhe8Rh1ajrGGtmda+YfY7oxumc8bSN0tIvUo1Ao5RQsnVpJmE4FSBwvq2bRmgwWr93faAEJP9qTkYwqh5t1+07wpze2ygv1+gQsVu/Kx+Z0ywvstJRokmOMjO2V0KgFcPcEn9Po8niDJMr7JkVxYXIUUUYtRq2SlDZGeV/XeFO9588stKBRKQjTqRjXK16OwiRFG1AoFHVGk/omRRGhV/PO1myOFFdRYXXh9khUOdxU2d0cKa7irc1ZDd5XQ45fa7IyPZf9J353gOJMOiINagor7azelc/BAgtf7yvEK/lSFTu2MaJU+p6dy7u35eKO0eg1SqrsbsqtTsxWJ6N7xqNTK3F6vBRZHEHfw21ZZVTaXPyWXc5t72wPUtSsz7lvSBDFf0zX+HDCtCruXLadCquTbgkmRveMZ/Wu/IDeXC3F79xU2t0tFuzwvyCqtLsb/N2wO9dMvtmG1dlwPalAIBAIBOcjzUoFvPnmm1vZjPOP2m9u/dGkbUdL66xruXlIR9ZnFGJzeSiosLEzx8wn6TkhU7xCUe30giRxrNRKP6OWLvEmOeJTXzG5vyaioXE1aUrKz58GpXCs1IrD7WX1rnwemtgTu8uDEgV5Zhux4TqyS6vp3T4SvUbFgQILaqXCJ1VfWIUSOFFh5+KOjV+sRRu1eCQJjxeOl9mpcnhYn1HItLTkBmtAoo1aHG4vl3dvy7FSK4mReoZ1iW1UrdrK9FwKKx1o1cqQEZ5bhvqUD/3CHeATsogyauo9//qMQoxaNdFGDZFGLWari105ZrJLrejUSo6VWkPWk32SnsOC1fuocniQJFAqwCNJ6DU+x9MLFIaI6tVkUr9EWWGxtcVQQj1H8RF69p+opNzqYN4nuwjXa9CpVaS0CQMgu7QaSZLYk2cmQq9hS4UNt1fC5vRwrNTKyG5tcbq9VNrdVNjcPDSxJ32TojhQYGHtnhPyc1jzPrRqJU63F5vLg0qp4Ot9hcwd3U3eX19KXEPP07/WHWTncTPhejVeSUKSILOoCqNWRb7ZhkqpICnaKF+npWl0rSUeUTONcleOWU6jrGusv0atKbVtAoFAIBCcTzTLsXr33Xfr3a9QKNDr9SQlJTFgwAB0usalUJ1P1FzcpGeX45VgZ46Z/smRddYr+B2olem5VNrdxITpZGegISb1S+Tno6WUW10cKa6SUwD9NjRFXbAxNKX24q3NWew47utNZDoZxemeYGLz4RI0KiXlVhdhFgfFJ+urEqMMHC2uwu3x4pFArVQQE6blQIFPoMB/v/7rhlqcl1udKFAAEiolSBJEGzXcuWw70UYN5VYX3RNMRBq1AcfVnMfvDhQRrlNTWOngma99EYz6Pgu/KqPF7sLl8fLpb3l0TzAFHNM3KUpuJOxPsVqfUcjonvH1zuHonvG8veUYueVWMouqUCshp8yGQqlAr1ZxpLiKcqsrqE5rfUYhdpcX6WTASQE4XF7sbi9KBUhuiY41Ime18Ss4fn+gCIfbS7HFwQvXXVivrU2h9nPkV/TznnSKv9lXyJ8v6Ujv9pHyMVq1kiqHG6fbS7XT5zA63F50ahWFlXbMVhcOt4fDhRYUSgUrtmXTNymKSf0S66xr6hpv4khxFVKVT1jkwuTIgP11OSv++YHAZ7Im2aVWbC4PFrsbpRL0GhUKhS/1t8ruRqlUYNK75LqxltY6tpZ4hO/3Rxll1S50aiVur1RnOqj/d9zWo6XYXZ5TokYqEAiazoAn1qMyRjY8sAkce3piq56vJt988w3jxo2Tf1ar1aSkpHDjjTcyf/58tFrtKbt2a+JwOHj00UdZtmwZ5eXl9O3blyeffJLRo0c3eOzGjRsZNWpUyH1bt25l8ODBTb5OXl4es2fPZtOmTSQlJfHMM88wadKkgDGffvopd955J5mZmURGhn5mvF4v8fHx3Hfffdx///0N3ssfkWZHrBQn6xkkKTBFqOZ2hUJBREQE8+bN+8N9ALUXN9uOlpIaG8bxMhtje9U97eszfClOseE62kcZGlxw1yRcp0ajUtIhxojV6ZYXw7tyzA0uhl9Yf5B3tmYToVc3amHXlLfihZX2k88DOE8uaiONWoZ0imXz4WIkr0RRpZ09QJ/2kUQaPFTZXZyosKNT+ZwqnVpJscXB8TIrFTZf3yK/jaGcPKfbS5hWicXuQatW0SU+nO8OFKNRQoXdTVuTnm1ZZbQ16QKEJvzHV1idckpTudWJUuFzeOtzrNJSosk32zhRYaOsyonT7QnpGEfo1Xz6my/NrVNcuKxC2FAUsLDSQYXNCRJ4JVCrFNgcHuwuDxa7i5gwB0534KJ2dM94fswsxuP1fU/9kRkF4PGCWgnrMgo5Vrq1TlGHQ4VVlFQ5UCoUDUa3mkrt58jvdJr0GkqqnISpFFidblnp0Wx1UVbtxO7yPUfVDjeRRg0xCi0KhQKTXs03+wpweby4vRJej8TX+wpZPM13Pb+DVjvtMkyrosLqwuOViDRqCNdrAvbXfNZq/ux3OtVKBTll1pDR6Cn9E/nf5ixcHg9ur++z69Pe94JFQkJ58nemRqWUn+3WoLlCEv7jii0OKmxuJEmiyOKgbT01hhF6NXvyzFjsbvafqGyRYIZAIPjjsmvXLgCee+454uLisFqtfPzxxyxcuBCHw8HixYvPsIWN4+abb2blypXMnTuXLl268PbbbzNhwgQ2bNjA0KFDG3WOOXPmcPHFFwds69y5c7Ouc9NNN5GXl8czzzzDTz/9xIwZMzhw4AAdO3YEwG63c++99/Lkk0/W6VQB/PLLL5SUlDBx4qlzrs91muVY7dy5k5tuuok2bdrwf//3f/IHnZmZyX/+8x/MZjMvv/wyhYWFvPTSS8ybNw+TycRf/vKXVjX+XKFvUhR3jerMQ5/toazaydtbjslperUZ3TOe9RmFXHNRaJW3uvAXw5utTm4ZmsrqXfmUVDlweSR25pgbfIO8amc+1Q53o4v3m/JWfHpaEkUWB1anm0GpMYBvIaZU+NLuyqud2N0e3B4vhZV2BqXGsCvXjE6tJFyvJj5Cx/EyK8fLrHgliQi9RhbaSEuJDunkTU9L4pnialxeCZ1aSWZhFQoFlFe7UCoUZJdVE2U4uXjXBfaU6hQXztHiasBn34iucezJq5CbzTY0J90TTLy95RhASMe40u7G6vRQ7XBTafcp/FmdOvLNtjr7W63PKCRcp6a82gn4Uvq8Xgm1UuFzIJAor3aSGGUISnPzCYK40GuUJEUb0agUHC6sOnkcWJ0eWdSh9jPndxYtdidl1S7582staj5Hn6Tn8N7P2ZRY7KBQYNQq0apV8jhAjg7FhmsptjhIjDIQoVdT5XBTWGHn56OlJMeEoVGpCNepsbk8pJ6s7fOn4yoVwXYcKLAQplPj9Ljka9akLjn2YosDu8uDV5KIMmpDfnZzR3djR46ZHw6VAL75/uFQCZEG34sQP/7nt7XELJqrCug/DjiZrugiQq8mJkzLpH6JvLD+IJ/tzKdjGyP/GNONvklRVNrdqJRKFEBJlYN1+wqI0Kub9DtMIBC0DKXWSOzkB4O2nUvs3r0bvV7PnDlzUKl8v4tvvvlmUlJS+PDDD88Jx+qXX37hgw8+YMmSJbIi9syZM+nduzf3338/W7ZsadR5hg0bxvTp01t8HZvNxvfff8/GjRsZPnw4d955J1u2bOGbb77hjjvuAODZZ58lMjKS2267rV6b1q5dS0pKCr169WrUPdRFdXU1YWFhLTrH2UqzxCuef/554uPj+fbbb7n66qvp06cPffr0YerUqXz77bfExcXxv//9jylTprB+/XoGDx7MK6+80uB5q6qqeOyxxxg3bhwxMTEoFArefvvtRttlNpuZPXs2cXFxhIWFMWrUKH777bfm3OIpoaTKQXm1Q5a5DsW0tGRe+/NFTV6QpKVEY9KrSY75/ZdolEEDkoRSAfev3C2LN4QipY0RjUpJmFbdKFntpij1TUtL5sbBKYzo2pYDBRZ255rlflExYb5Ig1rp65XkcHvZllVGu0gDWrWKdpEGTlTYKaq0U1BhR5LA7vZypLhKFrTwF9jXXDxOS0vmgXHdaBdpQK9RolUrqLS78Ujg9PrqXFxuLyltDOjUygChiVuGpnJBXJi8iL5laCp92kdSWGmvdw5rXnv134ax+m/DQn6OaSnRJEUbcLq9JEToKKy0c6iwimKLo04RhNE94wnTqYgwqNFrlKjVStQqpV8ID6UCXF6JzEILPx8t5ZP0HJb+lMXbW44hST71xbYmPeE6NQuu6s1jV/WiX3IUKTEGPF4vVXY3DnewU+1PoWtr0jP4gjZEGpufhlHzmQn1/KxMzyXfbKPK4cHrlXB7fFG24pNiE/5oUbtIA3a3l46xRiL0aqanJRGuU+M6eUx2aTW9EyNYdtsgbhrSkbSUGFbvyifKqOVQoYUiiyPo+ze6ZzypsWEMviCGtiYt6zMKAwQsVu/Kp8jiILu0OuDziTPpiI/QY9SqyS6tDhIs8d93dqmVGj7UyZRRN0atCpNeQ6XNxfqMQsK0qhZHelqqCugX4yi3Osk323G6PZitLqocvpcAq3bmU1hhZ2fO759JWko0F6VE07t9JIlRBrwSdSpVCgSCU4NCrSGs+9CAfwq1puEDzyJ27dpFr169ZKcKQKvVkpiYSEVFxRm0rPGsXLkSlUrF7Nmz5W16vZ5bb72VrVu3kpPT8DrCj8Viwe12h9zX2OvY7b6soeho398ChUJBVFQUVqtPqTkvL4+nn36aF198sUExujVr1jBx4kQ2bNiAQqHgs88+Cxrz/vvvo1Ao2Lp1KwALFixAoVCQkZHB9ddfT3R0dKOjducizXKsVq1axeTJk0PuUygUXHXVVXz66ae+CyiVTJs2jcOHDzd43pKSEh5//HH2799Pv379mmST1+tl4sSJvP/++/z1r3/ln//8J0VFRYwcOZLMzMwmnetU4CsC18ipko3pidQU+iZFkRhlkCMek/ol0qNdBH2SoiiyOLDYnLy5qW5H6Kp+iSTHGElLiZKjKPWxelc+Gw8W1+kg+vEv8g4VVPL9gSJyyq28suGwvOi7vHtblAq/UraESa8hPkJPWko0w7rEkpYSTdd4EwqFAgmfc1pa5avH2pljDrmQ9VPToSu3unCdlLJXSKBSKNBrVVTY3BRZHGzKLAmYS41KQVm1k+Nl1fRNimJPXgW/ZZfz1NoDjXIm63M8+yZFMbJbWy7qGENBpYMii4OCChuFlb7eWenZ5UHHTUtLJlznu1e7y4MC8Eq+aFxMmAadWolKoaDa6cHp9rI+o1COOoTp1HRuGy6nyq3elc/6jEJS2oShUPikytUqhU+yPAQt6fFU+zz+CMpbm7P476ajPPTZHvletWolSoUCvUZFx9gwBqRE0ykujDiTjtW78uX+VRa7izZhWkx6DWN6JTAtLZnpaUkna+Y0pLQJo9zqCvhOAHRLMNE/OQogSGZ+Wloy8yb0INqoZV9eJYWVdl+z7pP40uJcQY2+uyeYKK12UlbtJKfMGrIGKT27nK7xJuJMOsK0KhT4fvEqFb7UxPgIHRaHm3yzjf9uzuKF9Qdb1PagtVQBc8ttVNqcVDk8WJ1uDhZYuPvDnfLzplUpWbevgE/Sc+ibFMWwLrFEGjT0Towg2qhpUhqzQCAQOJ1ODh48GLT+y8/PJyMjIygtrjm4XC5KSkoa9c/rbV6fwR07dtC1a1ciIiICtg8cOBDwZX01hlmzZhEREYFer2fUqFFs3769WdeJjo6mU6dOPPXUU2RlZbF8+XJ27twpj7v//vsZP348w4cPr9eegoICduzYwYQJExg5ciTJycksX748aNzy5cvp1KlTUJulGTNmYLVaeeqpp7j99tsbNQfnIs1KBfR6vRw8eLDO/QcOHAh4IHU6HXp9/WlUAO3atePEiRMkJCSwffv2Jn2JVq5cyZYtW/j444/l0Ok111xD165deeyxx3j//fcbfa5TQVpKNBsPFpFbZsXrldiWVVqv4l9z6iNqpsT50w9f2XCYXomRZJVU0yHGUGdaUKXdTf/kqCYunhuW4PYv8rYeLcPj9ZJVXE37KIO86Fv6UxaJUQZKqpz0bh/ByG5xROjVAQvUq/olUlbt5HBRFQ63F4fbF9HomxTZoBOYlhLNun0FeGr8fow1+Rbl/sWwSa+Wa4f8836iwo5GqaCs2uecWJ2+aJfD7WlUalVDTZd/t0sCScJi96JWKXhyzX7amnQhj4uP0HOosAq9RoVSoSAyTINGpcTu8lAtefAioVcrqbS7ZCfj5iEdqbT7Fu3Zpb50Sn+0pMLm4sLkSIotdpQeCa1aKaeM1nz+/M9DS9Tq/FLcAJf3aMu6fQVYnR4UOOWoh9PtJSnagFatZPAFbQjT+hQiuyeYOFBgocLm8i3c20fKQid+x3paWjLT0pL5JD2Hlem56DUqduea5e/E5T3ayve1eO3+kMqA6dnlbM8ux+31FbGplArZuSmstBNp0AT1MjtQYKHS5vJFdOxuDhUGO1b+dMqUNka6J5j4Ylc+e3IrZCEX4OTn5kYjwbtbsxnTKwGgWfPdHFXAmgqAb285RrnV5aufVShQKyXcXlAofNHAvkmRxJp0HC+rZndeBcdKqzlQYGFvXgUnS/l47c8XNdlugUDwxyYjIwOXy0VqaiolJSW4XC52797NAw88gEql4sknn2zxNX766ac6hSFqk5WVJdcgNYUTJ07Qrl27oO3+bfn59b+Q1mq1TJs2jQkTJhAbG0tGRgbPPvssw4YNY8uWLVx44YVNvs4bb7zB9OnT+eCDDwCYO3cul156KVu2bOGzzz5j//79Dd7X2rVr0ev1XHbZZSgUCm688Uaee+45Kioq5Lqs4uJi1q1bx0MPPRR0fL9+/c74Wvx00CzH6qqrruKVV16hc+fO3HbbbbLTZLfbefPNN3nttde49tpr5fFbt24NKrgLhU6nIyEhoTkmsXLlSuLj45k6daq8LS4ujmuuuYb33nsPh8Nx2tQJbTYbJSUlGI1GDAYDer3vLbdBo8Jk0FBa7UQ6mSpTl2PVnPqIUHVPyTFG9BoH7SL1xJl0IVXN/AuqbgmmRi+e/WICDS3e/Iu8lDZGtmeXI+GTTq+5WPcvuP2qakt/yuJQYRW55VaSog0kRhlYdHUf7li2nbIqJyigT1IkSoWiwev3TYoiPkJPuE5Fpd2NQavCqFUTaVBzvMyKAl/NS77ZysglG0hpY6R/cjTtIvXkltu55IIYdueaaRepp9LqkpX8GoPF7pQjI6Ekunu3j8Th9lBW7aJ/chQ7c8woFVBS5Qx5vluGplJudbIju5wooy9aM6lfInNW7ECndiO5FOg0KjlyNXe0TwnS79RY7L7rZJdWY9Kr6RpvIjHKQH6Fg9xyX0pAzfYA/lTIlvZC8p+3pqz89LQkVqbnolX7VPB8jocv0qRRKTlUaMHp9sqy9TXrjmoKWdR2rKelJQf0XKptu3/e07PLgz6btJRoPv0tlwqrE6fHS2y4Vp4Pk15DfqFFTkv0O2l78yqwuzxI+FIxt2WVBb0w8StB+u0d2a0tdpdXdsKcbg82lxfdyfROk17douhgqN8D9b2o+SQ9h39/fxi9WklMmJbcchsVVhcatZILYo0UW5wYNEoKKn0CJgcLLLg8Em4PuD0elMDaPSfQa1S0NelEpEogEDSL3bt3A/DII4/wyCOPyNtHjhzJ5s2b6d+/f73HX3nllVx//fVcf/31dY7p168f69evb5Q9zV2P2my2kOtN/1rZZrPVe/yQIUMYMmSI/PNVV13F9OnT6du3L/PmzePrr79u8nUuu+wyjh8/zr59+0hMTCQ5ORmv18ucOXP4xz/+QUpKCq+++iovvvgikiRx9913c+eddwacd+3atYwaNQqDwQD46rkWL17MypUrufXWWwH48MMPcbvd3HjjjUF21T7f+UqzHKsXX3yRI0eOMGfOHO69917ZOz5x4gROp5OBAwfy4osvAj5ny2AwcM8997Se1SHYsWMHAwYMCMoPHThwIG+88QaHDh2iT58+p9QGPxs3bmTChAkB2/R6PWqtDo9Sg1Kjp1irozTKxKi3ojAYDBgMBtkRW7RoUci3zuXl5fz444/y+JrH1Py/RqMJKLYvrLRTVu1kZ46X7rV6zNQsVG+KJHtjxSv849JSorlj2XYqrC5KqhwB+8Enyb547X6mpyXJzla00Zcbnm+2ySmBOx2+fkDtIg1B0YO6iDPp6JcchcXuIqvEit3l4UCBL0LlPilukWd2oFYqqLC56BpvIi0lhmFdfI6Ab3GtQK1SAoo6Jadr0j3BxKbMEmLDdSGdY38kJC0lhu4JJirtbtqEaVh3si4lTBuclud3zmNNeqocbvmz/NtlnXlyzX70GvB4vLSNCCwI9Ts18RF6zFYng1JjZJn5zEILZdU+AYZdOWZ2HC+nc9twusZHtDj1ryb+5zlCr5brf3q3j+T7A0Xsz6/EZNDQp32kXN8XZ9JxqNBCbrmN6JMOXmKUIcAxqMuxr/3dqd2frdji4ESFjQi9JiBq1TcpikVX9+H+lbux2FwcKqyiXaSZYV1iUSqgTZiWcqtT/jzTs8sx6TWolX5hf3B5vCxZd5CV6bkBKou1bfrw1xwSowwYNCocbsmXHqhU0LOdifgIfaOf7VCEcqL8rRdqKmD6WZ9RiMPlwVztPNkPzI0X8Hi9xITpWDKjP+nZ5XzwSzaHCqtxeXx1mwp8tXteSaK02km8SUfv9pGywqVQBRQIBE3Brwi4Zs0atFothYWFLF68mPT09HqV6vzs37+f3r171zsmOjqaK664osW2Op1OysrKArbFxcWhUqkwGAw4HMHlHna7b93hd0yaQufOnZk8eTKffvopHo+nWdcJDw9n0KBB8s9Lly6loKCABx98kG+//Zb77ruP9957D4VCwfXXX0+3bt3k6J7L5WL9+vUB4iHdu3fn4osvZvny5bJjtXz5cgYPHhwymJKa2rptf85WmuVYxcTE8NNPP/HZZ5/xzTffkJ2dDcCYMWMYO3YsU6ZMkR0cvV7Pm2++2XoW18GJEydC5ofWDInW5Vg5HI6Ah7OysrJFtoR6G2G328EeKFVdkQehKs8effRR+ibFBS1M9u/fz5QpUxq8vkqlQqXVoVDrUGl16HR6bJKatpP+wbNuT4AiYVpKNB9uzuCL/73L+vcjkdRaOreLoUtim5BOm///R8ud7C92MLhLAv2SG158902Komu8iV+PlaNVKQOcjfTscvbkVeD2eAOa+AIsWpMhRxfiI/TEmnSolQp25JhpExao0FYX/ghHvtlGtcNLTrkVlUKBRwFKpU9IQIGE0yORaNTLC/iaC+F1+wrQaU42xGoEDaVW1ozg+BffS3/K4pdj5bg93iDnzb9Y7p5g4liplVSTkfUZhXSJ9/XJ2pRZwk+HS/BKEh1ifClntVUTrU6dL1pn1MhO9Opd+VidHlweiUq7G68Evx2voMji4O4rurba4tjvYC/9KQuz1cW2o6UUWRzklFlxeyUsDjcer0TXeBNKhe8ze2tzFrnlNnm+akZwazr2DaXNpmeXc7DAwrajpSTHGCm3urC7PFTYglP3+iZFcfuwVJ5ddxCXx8uO4+UUVtqJj9Bj0qtxur1yxDItJZptR0vpmRjJ4SILbo8XtxdKLU4qT8qm+z/b2i8ibh+WKvcv655gklX2ruqXyMr0XI6XWeXjmkpd0W5/KmXt7d0TTOwvsKBSKrDYXSfFZCT0GhVatVKuo/SrJUoACmgXqcfq9FBpd6FWKnCezLdtjhKhQCAQ7N69m5SUlIAX0wMGDKBnz5688sorLFmypM5j7XY7ubm5dO/evd5rhHKI6sLvKIViy5YtQSmF/tTBdu3akZeXF3TMiRMnAEhMbJ7ya3JyMk6nk+rqaiIiIlp0ncrKSh566CGeffZZwsLCWLFiBdOnT5fXmNOnT2f58uXyPW7evJnKysqgoMHMmTP5+9//Tm5uLg6Hg59//pmXX3455DWb41CeizTZsbLZbDz00EOMGjWKqVOnBqTenUlaEnpdvHgxCxcubDVb/EorzcVoDC2P2lD42I/H48FjswI+O6zydi92lzdg0dM3KYrVnmo2fvh6s+399ttvufzyy4O2WywWrr32WtkpO1Bsx+mAYr2BX4uSKNkSjdFopMQmoc224PQoiAtLZtMmGwaDQX7j4V8Qxpl0XNa9LT+fXJSbrU46xDReSrZ7gom9eRWAAbdXOlkX40KlVKBRKdGpVBRZHFRYnUFRkXkTevDW5iyOFFcFpIOFwp96d6LChtPtJbPQEjC2Zr1RhxhDgAO08WAR2aXWIGVG/2I5yqjln9P78tBne8gzV/LW5ixeuO5CbhmayoECCxabiy1HSgFIaRMWkA5XO3LjT2VTKxWolL46H+vJ/lAnzHbe3JQFBDZFbm5vJD9+Jy/aqGFbVhker09QxObyUlRpp9Lm4qKOvjFxJh2RBnVALVVdTmrNxXzNn4GT9WXVpLTxRfK6xodzqLASnfr3vmo1mZaWzMr0XDLyK3wCDnY3DreXtiYd/ZOj5fTDmnWMo3smcKLCxs9HSn0y9i5fzVpd+GvC/HMaadTKzaLLTkaOmkuF1cmqk46a/3PyP/t+YZiaRBq1dIs3sfVIiTwfYVoVHdqEEX1SQr7C5iIp2oBBo8Tu9mLUqNColFgdDjxeX/RqUGqbRqcICwSC1sdjrSD3pRsCtiX9bXmrNwg+VezevVsWVPDTo0cPLrroIj755JMAx8rtdvPII4/w2muv0aZNG+bPn0+nTp0abCAcyiGqi/pqrEKlFPpTB/v378+GDRuorKwMEJbYtm2bvL85HD16FL1eT3h4eIuv8/jjj5OamsoNN/iel/z8fLl2C3xOWU2RjTVr1tCzZ8+g+bjuuuu45557WLFiBTabDY1GE1AK9EekyY6VwWDg9ddfp2fPnqfCnmbTktDrvHnzAlIVKysrSU5ufv+VxjpAdVGXra1xXr1GGVQj1Cm6ZXKsdQmTWCwWvvrqq5D79n8d+lybAX956kcffcSkS3zdw4stPiXAOJOOC9oY+Wb+ZBRqLcf0etY9FUVMRHidqZGHSp14FBoiTEa6JLZBn9wbKdK3ADxSXIXXK+F0ealyeFBazXyV7uaOoR3YfqyMCptbdk76JUdRbnUFpIOFwh+NOlRowe7y8vaWYwHOiX+/1elmfUYhUUYt+WYbiVEGusab6J8cTaQx8DOpLUwSrlNTaXPJohv+SMuiNftRKOBIcRX9kqMCFri1oyb+3meRBg3dE0xsyypjx3EzTrcXCcgz2wJsn/fJLlbtzCfKoGHQBW3k8zfFwcos9EWO8sy+FL8Km0tOo7O7vUQYNCgVCiL0anZZHJyosKNVKXl7yzEGX9Am5II9Qq9m29FSuban5lz559ovA+63N0yr4ut9hXX25ZqelsSCvAokwGJ3UWFzyY23L+/RNmBO7xrVmfTscn44VITLIyEBaqWC7FJrvQI1NT8HfxQvyqglJswl90xrTkrdgQILSHC4qIpXNhzmrlGdqbS7GZjaRq5xq0laSjTvbDmGR/LZbtCqMZ3sWxVn8rUDUCsVON1eZg+/gG1ZZRRZHLg9Xlwe6eTnJ2HQKFvkdAsEgj8uBQUFFBUVhUzlGzt2LIsWLWL//v306NEDgAceeID9+/eTlZWFxWJhyJAhQSp0oWitGqv6UgqnT5/Os88+yxtvvCH3l3I4HCxdupRBgwbJ60ur1crx48eJjY0lNjZWPr64uJi4uLiAc+7atYsvvviC8ePHyxlhjb1ObQ4dOsTLL7/Mjz/+KCtVx8fHc+DAAXnM/v37A+5/7dq1XHnllUHnio2NZfz48bz33nvY7XbGjRsXcC9/RJqVCpiWlsbevXtb25YW4VcUrE1jQqI6na5VhS1mzZqFs8NA9ueUUFZhYXr/eJIj1NhsNj7fnkVZRRVaXKi8LnYfKyI1WkPnNjqsVis2m61OR0Wj0XDBBRdgs9mw2WxYrVacztBCB6HoGB+FKdIQlGaWFNGsx0DmVDmCRqMxIIVs48FijpdVo/K6cFWdVJIDKguym3TeN998k4HDfaplHWKMfH+gELdPCI5jr8/miMOKcZ5vrEKtRac38EhkOA5JjU3y5TXvT4hhZZQpwIGbNm0aY8aMCVjQ212+z+e7777D6/X6nL5KN3llTsxOBVXVXg7neWnXJoJDhRaijVriTD4VwpqL6tpO0aDUmCDHoEu8ifbRBgorfS8YGlrg1hQQSc8uZ2BqG7RqJYWVDsqqfc2la7JmzwnsLi9Fbp8iX1NSvvyRrnX7CvBKPsGQKoebdhE6Ku1unB4JBRKVNpdcc+ZP2SupclJpd5OeXUZOmZW7RnUOuKa/J1rNSFJtB9KvCugn0qhlbK+EIAfWz/ZjZVidHpBAr/WJMqS0CcPqdMuRsNpRwK7xJgorHSglcEsSLreHJesO8vaWY3SKC+eWoaEjh/7o5eie8VTa3Vw/qIOsKllbubAxjO4ZT57ZRr7ZLvfMayiSZHW6sTm9KBUQrlMRplXKaZL+Z80rSRwosDBvQg9W78rn+wNFtI3QUVrlRKVU8PnOfIZ2cZJvtgkHSyAQNAl/fVWoko0xY8awaNEi1qxZQ48ePcjPz+fNN9/k8OHDREVFERUVxZAhQxrVtLa1aqzqY9CgQcyYMYN58+ZRVFRE586deeeddzh27Bj/+9//5HG//PILo0aN4rHHHmPBggXy9muvvRaDwcCQIUNo27YtGRkZvPHGGxiNRp5++ukmX6c2d999N9dee21AdHD69OlMnjyZ+fPnA7B69Wq+/PJLwBe5279/P6+++mrI882cOVNW437iiSeaPmHnGc1aUb/wwgtMmDCB3r17c/PNN6NWt2xh3hr079+fTZs24fV6AwQstm3bhtFopGvXrqfNFrVazbBeKRjDI4IWF1EX9JWL+P/9/WHcPTy4Y8N4bHbDb1rGjh3LkSNHArZ5PB7sdjvbjxTwa+YJusbq6BCpwWazsTe7iL3Hi0mOUBNnUPCroh37i+1BPbSio6O55pprsNlsHM4vxWaz4XU7MSjcAU6czWYL2dehpamLdZFf5QlIk8s329ibV0GcJriRbVOo6bAB3PTWNrYeKfW9eXcFOqqS24m9ykle1e+NCauBkqPB5+3SpQtjxoyRz11hdfL1vkIu796WW24Zw/Hjx+u1S6FSodXq0en1qLV6/mMw0C4mglmzZvHXv/41YKzfMdixfiWLtyswGAzsyLci2SXMpU5KUXPdrm38eVhXJl7YMSia51eqrPlsrt6VT1m1E0ny9RNra9IxPS1J3m/Sa6iye9ColScFMBrffNZf51TlcBOuU9OnfSRWp4fjZVaGd43jl2Pl5JZbiQ7TcqDAwl2jOp/8vM1olAqUCtCpVUSdTE2raXdtYYya37m6RFZqR7lq892BYtRKBW6vRKRBIzcHjjPp6kw7/MeYbr62AIVVuL1eiqucuD0SBRUOjpVU0y85KmSqYu1aO3+KZlm1E6fb0+So1bS0ZA4UWFi75wTVTk/APPj7q9UWAXGcTAH1SFDlcKNRKdGqVOSW2zBoVPRPjmLr0VJcHkl21MAXSd6TV0Ge2YZCATtzKjBq1XI/PeFYCQSCxuBXBAwVsbrkkkswmUysXbuWe++9l++++46LL76Ytm1/zx4oLi5uULjidPLuu+/yyCOPsGzZMsrLy+nbty9ffvllg72iAKZMmcLy5ct57rnnqKysJC4ujqlTp/LYY48FiUI09Tpr167lxx9/5NChQwHbr7zyShYtWsRLL72EJEksXryY8ePHy8dERkZy6aWXhjznpEmTiI6Oxuv1ctVVVzVmes5rmuUR3XzzzSiVSu644w7mzJlD+/btg6IWCoVCfgPR2pw4cYKKigo6deqERuN74zx9+nRWrlzJp59+KnvOJSUlfPzxx0yaNOm0Sa37qb2gq/mWetalqSxak4HN6avd8Kf9NAeVSkVYWBgj+nZiRN9OAftqR8Vz12RgcSuIM+kCa2V69eKhf71OenY5W4+U8OuxclJjjSy4qnfAPUiShNPpDHK2qjTRstJbpd0tL9ri4uJ45pln5HE5xWa+25Pjy8PFTY84HSqvSz5fzXPabDaOmV3ExgTKZu/ONbP+l33Nni8IjrBd1S+RY6VWKqrs4G24OXJjz1szKtKYujvJ48Fhq8Zhq5a3nThGULEo/O5M/Pzl+7y7v+75mP8/mF/HvjvuuIPXXntNfhYANCol+WY71Vvfp8JWwOeb41h30hmLr3RTVGAjKiKc7dUxXN6nAxk5BrJqpV7GxcXRoUOHIHs//S2X3HIbeo3PMTtQYKF/chQbDxX5ZPRPXn90z3j5++NfuPdpH8ktQ1NDRl1qC2M0ZkF/oMBCkcXByvRcWcyl5nfi8u5xfL2vEJAotjhQq3zpEkatCqvTQ1K0gXyzTa6F89vUKS6c7NJqJLcCp1vC/xrC6fEGRQj9P9e+J7/a4JHialLaGJvloPhfnuhO1nl9kp7DpswSduaYiY/Qse1oqRz5S0uJpn+HKLYdLcXpkXC6vejUCuxuiaRogxxJs7s8lFsDXzwUVtrpFBeOUavCYncTH+FLHYwz6QJSJgUCgaA+7rvvPu67776Q+zQaTYCoWElJSUC6WUFBAVu2bOG111475XY2Fr1ez5IlS+oV3Bg5cqSvX2At5syZw5w5c1rtOjWZMGECFktoZeMHH3yQBx98MGj7mjVrGDNmTJ1BFKVSiVqtZtKkSSEzrhYsWBAQkTvfabYqYJs2bejWrVtr28PLL7+M2WyWG5utXr2a3NxcAP72t78RGRnJvHnzeOeddwIKC6dPn87gwYOZNWsWGRkZxMbG8sorr+DxeFpVmKK51C6wL7Y4fLUskkTHNo0XYGgO/qapDrcHnVpF9wRTnQX/O3Mq8EoS2aW2oAWdQqGQ0yaPV0F6gZ20lCT21KgR6ZYQIR8XHx/P/fffH2DLojUZfH+giEiDhkn9EuuVeK+dMgW+RXSXNgPo/+23vP3jQXYfK8ZhtzH8ggi6x+llpyy7sJzcEjMRagldrchbfHxglKLS7uaSC9pwOK+IlrwKqB25q7mAbkn0LlSqpd+ZeMoVXFfYWPwvJWpK7qelRNMhxsiqD/dwcF866SGOOwxsA4L7rfuYNm0aK1euDNpusbs5uup5rEd3kGE0kBQbhUuhpsQOTtSoNDrC28WwITuRnz/wOWuSS4G+1MmxYzp+cvfhLzdOC3nNiooKOkdAhsODSacPiMrUJbhRWyWv5ndi8bR+dE3I4t/fZeL0SLLYidsjUVhp53iZlWMl1SRGGeRneOlPWZRbXbSL1FNkceLyuOQe2iO6/q7yWfulS6iap21HS+mfHIVSEVqwoyHiTDriI3Rkl9r4fEceX6oUeLw+YYu8chsDUqICFBbfuWUQi9ZksHbPCRQKBTFhOrkmq2YkrWbt2qHCKhxuD5EKDYuu9qXv+Fs8JEYZRLRKIBCcErp168bTTz9NTk4Oer2em266CYVC0ah+qYKmM3LkSIYNG1bn/lWrVlFcXMzMmTNPo1VnL81yrDZu3NjKZvzOs88+K8u3A3z66ad8+umnANx444119jJQqVSsXbuW++67j3//+9/YbDYuvvhi3n777VPiADaVUH2pnB5fwXdj+iK1hPUZheSb7VQ53PRuHxFwPf9bZb99l3ePY8OhYsK06nob4dZchPrTqronmBpMD6vZ6LUxzX1DLc4MBgOXX3455qiuFG/KokOMgUs6xTapD1dN/Hb8aWAy/51ZLjtgL369lyMF5bQLUzC9fzz7c0pYtvkQlVXVJJnUTOjZJiDKVju/u6b97dq1o6qqSnbwmlIbV5/wSksdtpoKhf4GzQA//UtB0yrXAs9bm/TscsJ0atyWMtwVhVRWQEZwSSS/7YPfvg193j2bBtfpWD3wwAO8/vrvypYanR6tTk90RDgu1Ci1Ogx6Aynx0RgMBpyoya90k63QYNzfg1mXLg7Za8trzsN1Ih+1VocyxkSlQkO1DZQaLQUuA2Hq35+5mv3XwnTV7M2rwOvx1Sz5FQmhccqKyTFGWawls9DS5JqlSf0SySmzkltux2J3YdKp8Ug+B1GlVFBY6Qj6/tX8bnZPMHGgwBJQ61f7+xjqufELeQhVQIFAcKoYN24c48ePp1evXiQlJXHZZZdRXFwc1MdU0DrUfkHuZ9u2bezevZsnnniCCy+8kBEjRpxmy85OznxxVC2OHTvW4Ji3336bt99+O2h7dHQ0//3vf/nvf//b+oa1kNo1DgDJ0QYcbm+ddR6thb+Y3e31crioikOFFjrEGOXGq7XtKz8p6+0XAwhFTUdx9a58bC4P1U4Pc0fX79zU5Sw1h02ZJVjsLk5UKELW1zSW2jZFRfn+f9vkNgEL2nFAtmkHvx4rwxSmZdzVfRp9rczMzICfPR4Pb3y/nxJzFQalmyt7xbLrWBG7jxWxP6eEE2UVKD0uxvdow5gxdedkjx07lqKiItm5yyupwGazYrPasNvteFx2JLczZP8to9EY0E+r5r20doQtLSWaD3/NQeV1Nfu8Gm3d6by1Uy1dDjsuh53qSnPA9qMZwce6i44Ai4NSCgFSS39h9we+9JJQFXLXLoHrVWoMRgNhJ1MhnWiwuBUowuNoN+0hIg2BAhnp2eXsTP+VNcu2M6xH+6D6t7d+zuOY2UWY0cil3RNZddhNt6RYnA47fdpHyipO9eFXK3xrcxZ78iowalVoVAqqHRbcXi8qZfA5an8P6kutrOt73Jrfb4FAIAiFUqmscx0oOH28+uqrvPfee/Tv3198FjVotmNVWVnJK6+8woYNGygqKuL1119n4MCBlJWV8fbbb3PVVVeJsGwI/JGeOJOOOFMcxRYHBwoszZJVbizT0pKptLvZeLCYncfLcXm87LFWMLRLbNCiKT27HK8EO3PMXNyx8W+dLXY3e/MqTul91GR3rpltWaVU2NyyWlldBfON7b1Ue1xdi0Sz1Se/7e8hVd95VmzL5rsDxVzePY7F0/oF7Lu0R5L8/+5JUXTv3p1rTx7/0Gd7KLe6KGkXXa/SUW3lH//5K6xOXt14BJfXFxX9+6hUZvSPD0iJjI2NpdhjkG3wHxuhV5M24XqGjanEpPYGHPNLZgGlFRaUXhfROgm7zY7C48TttMvj6kpdvH1YKukvu2lufDYlPrQ0OrTMEVRqAh22mi8NfmuEYqbH46bKYqGqVt66vk0VPRNNpKXEBEVq1yz7lU9ef5ZPGjj3j7V+vhNo06YNJSUlIcd/++23vPbaazhQY3EpCQ8zcKLcDWotqDTYPCrskppjYQb+WbGXm4Z1C3DsunXrJr/1DRVlb2kfs3ORRYsW8fDDD9OrV68gNdwtW7Zw//3389tvvxEREcE111zDU089JfeZ8eNwOHj00UcDCsyffPJJRo8efTpvRSAQCFoN4dyGplmOVW5uLiNGjCAnJ4cuXbpw4MABqqqqAF/91euvv052djYvvvhiqxp7PiCn3PVoy+pd+ew52aB1b14FvdtHBqTVtPZ18802DhdZKLY40KmVnKiwk2+28Ul6jiw64RcZqLK72JRZUmcPnpqpgJP6JbI3rwKH29sseeim4F/Y5ZttROg1VNjcROh9EYGoOtIQa9eT1UVjxsWZdHgkCYfTy7qMwpB9ivwKeNuOlvJLVhkuj5fvDhQHXcMvyBEKi92N2+OV+1TVNxehVPCW/pRFdJiWIosDtUpJm4gwoqOjiY4OnJ92/F7j449QbDtaSv/R04kyaoLSK3fnmlm9y1f/WNezGqoYF3wOftLyN3n0g5/IyCmhU7SGawckBImW1Pz/kROl5BZXoPK66Nip7hc1LWnK7SIwolTToW6JwxYdEc6kfu3l77z/3AAOe92fa0PU1zv40KFDfPJJQ+4aFAFHCa6Tc7lcsmNVcx6+/vpr7rrrLhySGqVGi8FgIDUhJqhnnMFgIDw8nMcee6xZ93a2kZuby1NPPUVYWFjQvp07d3L55ZfTo0cPnnvuOXJzc3n22WfJzMwM6t938803s3LlSubOnUuXLl14++23mTBhAhs2bGDo0KGn63YEAoFAcIpplmN13333YbFY2LlzJ23btg2QvASfVKRf/14QSM2Uu5+PlmKxu1EpIUznayh7qiSKa6qsrc8o9NfUY9SqWZ9RKItOzLo0lXCdmmKLg5055jojULUb1vZuH8mhwqpWt7s2NYUWhnf1RfzKrU6+P1CEUasiQq8OKQbQmLqPxozrnmBCq1LgdANIrM8oDHKs/OIDUUYtHWONZJVYSYrWszvX3KhrrN6VL6u51ZQ7r2suQj0zaSnRpMaGoVYpaWvS1ZvWWfv+ffU1lXRPMIWUL2+ox1J9qWqDBg3iOndbzFZXSMctFH6HL6qOnlMAK1asoKqqih1HC/ntaAEXRGtJilBjtVrZn1vCgdwSEsNVxOhg0/48KquslJorsdvtDL6wbolek8lEbNt4qq1W3E4HribVxhnlOa0tFFNV3XxH0CGp6/xetsQRVKvVdao+lZWVkZWVFbAtc3fo84SFhZ03jtW9997L4MGD8Xg8QVHC+fPnEx0dzcaNG4mIiACgY8eO3H777axbt44xY8YAvl41H3zwAUuWLJGbeM6cOZPevXtz//33s2XLltN7UwKBQCA4ZTTLsVq3bh133303PXv2pLS0NGj/BRdcQE5OTouNO59ZvSufcqsLl9uDSqvCpFfTNd50you+40w6tGoF1Q4PZdVOrE63LKfsv/ag1Bg5AlVXulvtNLkwrYq9eb7+O2FaFXNHnxrBkJoRP//171y2naJKO3aXh0dX7eXtLce4eUhH2eGpK6Wvsal/Nam0u+nRLpKdx8sBBdEhFvv++pb07HKuH9Sh0VEqP8UWB1UONzFhWrrEmxqci1DPTN+kKLmRq39sY6l2euiWEMGBgsoAlcdA6gmbNEBDPaRqU/s+Q0XqIiIiiIiI4JssB+HtwnAaNYy4NJXduWYKIsr56/jfx45sQjrb888/z/PPPy9f9+XvDhKuktiaeYKS8grcTieXpJj4v+EdAiJuh/JKKXaqQ9qflhLNj526MOzyMWgkN1arlfLKKsyWaux2G26HHZfTgdNhD1kbp9QE9/Ly0xpiJqHmpinnrauv3bnGjz/+yMqVK9mxYwd/+9vfAvZVVlayfv167r77btmpAp/DdPfdd/PRRx/JjtXKlStRqVTMnj1bHqfX67n11luZP38+OTk5JCeHzgwQCAQCwblFsxwrm81GXFxcnfvr0sj/o9FQPUJbk5bDNieSBE63l0n9EoNShlqbSf0SWZdRiNvjQAEkRhmCIi6RRi2RRi3VDne9qWg12ZZVRnm1Cy/w6g9HSI4x1plG2BJC9QfTa1QoFb7mplaXl4wTlby95ViD129simBN/NGoSKMGl0fiWGnoyENtOxsTMavZT0qvUeF0e3llw2G531BD12jq/trUjAZGGTVBDrcf/3Pa3JcABwos2FyeRqthhprL+iJ1tXtE1R7bXIGF9OxyUKjIKLHSp1MSvx4LI0KvplevBC69tGfA2KU/ZRFehzPdNymKpU8/CAT3C6n5O+OpNRn8llWE3e4g3iBh0kC11Ypeo6pTsXP48OE89thjWK1WcorN5JVUUGGpothswWG3yzVzlVXVSC4HBqUHye3EarViMBjk+Vq9Kz/gd1dTUi3rU7E8V/B4PPztb3/jtttuo0+fPkH79+zZg9vt5qKLLgrYrtVq6d+/Pzt27JC37dixg65duwY4YAADBw4EfCmFwrESCASC84NmOVY9e/bkxx9/5I477gi5f9WqVVx4YXCU449GfQvASf0SSYwysHpXHhn5FnblVvCvdQfpnxx9ytIB/VyYHMWevArsLg+f/pZLhF4d0Ksm32yjrUnLCa8XrVrZKEEKh9sjN0N1eyRe+v6w3Hj1VLJ6Vz77T1QgSb6oWbXDg7IRqmnQ+BTBmvijUX5xiYaaO+/ONfPW5iyOFFexK8fMsC6xAU2Ua1JT2CQp2sCO7HLsLs8pr1vz45+PDjEGDhRYyKfuOqp8s02W226Kbf4U2HKrK0CVsjl21hWpq2lPcz7j+q7r7y9ltjq5uGMMx8uscpPgumxsiuBDTftnXJTM0RIrmshwrC4vVSoFDlU07ePC60ztHD58OMOH+1Qk/SmUO3PKOVZqpWMbI/8Y44skz1mxA7vLQ2psGCtm+zqJezwe9p3wpSNbne6A312TJk0iJSUFm83Gut3HqaisQiW56ZNgCKiJs9lssqrmucxrr71GdnY2334bWvv/xAlfr4B27doF7WvXrh2bNm0KGFvXOEDu2Vgbh8OBw/F7n7qaDVIFAkHzWLZsGYsWLeLIkSOEhYVhNpsZOXIk0HAroY0bNzJq1Cg2bNggH3Mucr7cR2NYsGABCxcurLP2+1TQLMdq7ty53HTTTfTt25cZM2YA4PV6OXz4MAsXLmTr1q2NKqA+32nMAnBXjpk9eZVIHonduRV0jTfJvaVag9qLuvTsclLahGF3ediTV0FuuY2V6bmyY+WX325r0mPSawGpUY6eyyNh1Cixubx4JbDYmxYJagklVS40aiXheg0DUozklvsW/KGEJWrSEmnoTnHhFFbaGdYlts4xu3PNvLLhMHvzK6l2uLE6PdhdnjrT62qmOb6y4TAKhYL8CjuHCk9PBLim8IWvXi70Z+9vDtvYZ6P2sRqVUq4ha45EflM+t9aU/66Z4hmhV/P2lmNUOdwhRV5qXrc+2fL6mJaWTE6Zlc925iM5PZitbnRq39w1xlH0P09Ot5eECD0GjUq+vk6tIM/sJNLw+58AlUoVUANa83dXx44d5WbsPS49v5UBS0tLefTRR3nkkUfqzMzwp0bqdMEtAPR6fUDqpM1mq3NczXPVZvHixWdFc3uB4HzhwIED3HzzzYwbN44HH3zwvElbPp3k5+fzxhtvMGXKFPr373+mzTkraZZjdeONN5Kdnc3DDz/MQw89BPgatkmShFKp5KmnnmLKlCmtaec5SWMWdXEmHYmROootTrrGh5MYZWjVxUrNqBn83tTT39tKgTMg6uJfjI3uGS+najVmEdcpLpyyaiduiwOlQoEkNa2up7lM6pdIscVBYaWdQakxRBq1fPpbLpU2d4DD2JqkZ5dTbnWhVSvrFYVYvSufIosDSZLQa5QkRRvqTK+DwOdldM94fjpcgkaloKy68YIJrYFfQdL//6bub+y5gUY5HHVFfFpD+rup56j5Ga1M9z1nDaXLNidq5rer2umhY5sw0qt8qbtatZLe7UM3SQ9lK8DqXXkcLqyic3y4HH12uCWMGhUOd+i3ePX97mpNZ/Vs5OGHHyYmJiaorqom/nTHmhElP3a7PSAd0mAw1Dmu5rlqM2/ePO655x7558rKSpEyKKgXhUZPzOg7g7YJfGzcuBGv18uLL74Y0A5o3bp1Z9Cq08/w4cOx2WxotU3PGsnPz2fhwoV07NhROFZ10Ow+Vg899BB//vOf+eSTTzh8+DBer5dOnToxdepULrjggta08bzGnxJYYXVyoMBSZ+1Ec6m5qKvZDLZLvInBF7Sh2OIgzqSTF1w131g3tgYG4JahqRSeFJCosrvpGHt63gT1TYrihesuZHeumcVr95NvtlFc5SBcp24wTa+5+J2DQ4UW1u0rCEilrI1Jr0anNjIwtQ1RRk2jHb1pacl8sSufvXmVxIQ1L2WuJSRGGep0NlqysK55bO2oSF3UlVLbnBq5xp67MUxPS2J9RmGDIhzNma+a9W5d48M5XGTBbHPh9khNqsNMzy6nwuZGpVJSYXPLx6a08X0/p/RPrO/wPxyZmZm88cYbvPDCCwEpena7HZfLxbFjx4iIiJDT+PwpgTU5ceIEiYm/z2u7du3Iy8sLOQ4IGFsTnU4XMtIlENSFUqPDNODKM23GWUtRURFAULpycxyMcxmlUilHzM8WqqurQ7a1OBdRtuTgDh06cPfdd/Of//yHV199lXvvvVc4VU2kb1IUsy5NpdrpwebyNsmZacr5+yZFkZYSLfd6Ss8ux2J3c6DAgsX++4LLz+pd+azdc4Kv9hbIynINXad3+0iiTgpfVNjcjTqutUjPLqes2kV+hR2vV8Lq9NCxzalx7vomRfHQxJ6UVfuc4be3HAs5blK/REZ2a8v0tKQ6e2ydjdSOcp4qaj6b9VHzuW3M9qaQlhJNdmk1n/6Wy9wPdrA719zoY6elJfPany86JVFR/71N6pfIQxN7MqFPOxIi9Og0SipsLootDpb+lNWgvWkp0fRpH0lStIE+7SPl7367SAPtIvUcK7WyaE1Gk+77fCYvLw+v18ucOXNITU2V/23bto1Dhw6RmprK448/Tu/evVGr1Wzfvj3geKfTyc6dOwPe5Pbv359Dhw4F1Uht27ZN3i8Q/NHIy8vj1ltvJTExEZ1OR2pqKn/5y19w1mhpcfToUWbMmEFMTAxGo5HBgwezZs2agPNs3LgRhULBRx99xKJFi0hKSkKv13P55Zdz+PBheVzHjh3lNhBxcXEoFAoWLFgAwMiRI4NqjXJzc5kyZQphYWG0bduWu+++O2TkGXzf5XHjxhEZGYnRaGTEiBH89NNPAWMWLFiAQqHg8OHD3HzzzURFRREZGcmsWbNCigO99957DBw4EKPRSHR0NMOHDw+KrH311VcMGzaMsLAwTCYTEydOZN++ffVPfI05q1lTNnLkSHr37k1GRgajRo3CaDTSvn17/vnPfwYcd/HFFwMwa9YsFAoFCoUioElwU+YiIyOD66+/nujoaIYOHcqzzz6LQqEgOzs7yOZ58+ah1WopL/etSzZt2sSMGTPo0KEDOp2O5ORk7r777kYp2JaUlHDgwIEW9b+sjxaHR6qqqigvLw9ZGNahQ4eWnv4PQ3p2GQcKqrDYT13aV+0359uOltIhxojZ6gxanBZbHJhtLhQn/98YJvXzvXn9/kARDpen0ce1BhF6NXa3hwi9mkqbmzbhmlZ3Umvjr5myOj0h99eM/q3eld9ksQen24tGpSC71NooAZHWojUFH1qDuiI+DUWCakfEQqX89U2Kwu7yUGlzsyev4rTVBTZE7Xvzf7f836nCSjsHTz7fDSlDhmqXsO1oKQ63lz15FSRFG86a+z7T9O7dm88++yxo+8MPP4zFYuHFF1+kU6dOREZGcsUVV/Dee+/xyCOPYDL5BEyWLVtGVVWVXHsMMH36dJ599lneeOMNuY+Vw+Fg6dKlDBo0SKT3Cf5w5OfnM3DgQMxmM7Nnz6Z79+7k5eWxcuVKrFYrWq2WwsJChgwZgtVqZc6cObRp04Z33nmHq666ipUrV3L11VcHnPPpp59GqVRy7733UlFRwT//+U9uuOEG+QXGCy+8wLvvvstnn33Gq6++Snh4OH379g1pn81m4/LLL+f48ePMmTOHxMREli1bxvfffx809vvvv2f8+PGkpaXx2GOPoVQqWbp0KZdddhmbNm2S1T/9XHPNNaSmprJ48WJ+++03/vvf/9K2bVueeeYZeczChQtZsGABQ4YM4fHHH0er1bJt2za+//57uY3DsmXLuOmmmxg7dizPPPMMVquVV199laFDh7Jjxw65JrYplJeXM27cOKZOnco111zDypUreeCBB+jTpw/jx4+nR48ePP744zz66KPMnj2bYcOGATBkyJBmzcWMGTPo0qULTz31FJIkceWVV3L//ffz0Ucfcd999wWM9bewiI72/T3/+OOPsVqt/OUvf6FNmzb88ssvvPTSS+Tm5vLxxx/Xe58vv/wyCxcuPGXiHc1yrOx2OwsXLuR///tfyD5Wfjye0AtOQTBl1S40SgVl1a7Tcj1/If5bm7MorLTz/f7CgIVnnElHmFZFpd3NtqzSBoUg/Ofsm+RrQvzT4ZJGH9caVNrdXHJBG3bmmOncVkOFzdXoPknNJSnagNnqIim6fnnp5oo9TE9L4qXvD6NTK0+bMiCcPzU0tSNvoVL+/HL9EQY1neLCzxpnsja1xTC2HillZ46Zizs2vW4rLSWau0Z15l/rDpJdWg3Q6inI5yqxsbEh64NfeOEFgIB9ixYtYsiQIYwYMYLZs2eTm5vLv/71L8aMGcO4cePkcYMGDWLGjBnMmzePoqIiOnfuzDvvvMOxY8f43//+d4rvSCA4+5g3bx4FBQVs27YtoGXB448/Lr+kf/rppyksLGTTpk0MHToUgNtvv52+fftyzz33MHnyZJTK35Ou7HY7O3fulNP6oqOj+fvf/87evXvp3bs3U6ZMYefOnXz22WdMnz6d2Ni6hafeeOMNDh06xEcffSS/JLn99tvp169fwDhJkrjzzjsZNWoUX331FYqTisR33HEHvXr14uGHHw6KMl144YUB3/vS0lL+97//yY7V4cOHefzxx7n66qtZuXJlwD3656aqqoo5c+Zw22238cYbb8j7b7rpJrp168ZTTz0VsL2x5Ofn8+677/LnP/8ZgFtvvZWUlBT+97//MX78eOLj4xk/fjyPPvool1xyCTfeeGOL5qJfv368//77AdsGDx7Mhx9+GOBY/frrrxw9elSOMAI888wzAfWps2fPpnPnzsyfP5/jx4+f0cBOs/6a3nXXXbzzzjtMmTKFYcOGyR6koPlM6Z/I1/sKGdfr1DoDNfG/rfdK8PW+Qsb2SvhdXrlfInvzKsg4YUGSYH1GYZMcpAqbCwka1U+qPhorLuBfEF/cMbpOOfPWZHeuGafbS0obI11PNvGty9bmij1MS0vmQIHlpFN29tEa4hGnEn/kLUKvlqOXtRU3/SqZ/ZJ9aYlnM/75rrA6OVhoQa9WNikqW7tRta9BuAeV0lWvCIsgNAMGDODbb7/lgQce4O6778ZkMnHrrbeyePHioLHvvvsujzzyCMuWLaO8vJy+ffvy5ZdfytL4AsEfBa/Xy6pVq5g0aVJQHzhAXpCvXbuWgQMHyk4VQHh4OLNnz2bevHlkZGTQu3dved+sWbMCaqX80ZSjR48GjGsMa9eupV27dkyfPl3eZjQamT17Nvfff7+8befOnWRmZvLwww8HBRkuv/xyli1bhtfrDXCO7rwzUFxk2LBhfPbZZ1RWVhIREcGqVavwer08+uijAcfVnJv169djNpv505/+RElJibxfpVIxaNAgNmzY0KT79RMeHh7gLGm1WgYOHMjRo0cbPLY15gLg2muvZe7cuRw5coROnToB8OGHH6LT6Zg8ebI8rqZTVV1djc1mY8iQIUiSxI4dO+p1rBYsWBDgpLU2zXKsPv30U2677TZef/311rbnvKQxC9DLesQTadSe1jfmu3PN2FweCivtXHJBTEC9St+kKOZN6CFHtJoa/fF4JbwSLVa0a4y4gH9+I/Tq0+JU+e1KaRMmv/H321CXrcUWB0eKqyi2OLhlaMN1RX66J5jYm1dBscVxWtMBof7n1i8l75V8aWV1NTE+k/ijPIvWZHCo0ELXEH3Vmpv2eLqdSv98Rxm1ZJdW4/F6qXZ4Gz6wBrXv1er04PZ4qXJ4Wi1idbY7282lrv42Q4cODaofCIVer2fJkiUsWbKklS0TCM4tiouLqaysbNDZyc7OZtCgQUHbe/ToIe+veY7aC2n/C39/TU5TyM7OpnPnzrIj46dbt24BP2dmZgK+SFFdVFRUBAQf6rMzIiKCI0eOoFQq6dkzsOl8qOtedtllIffXbkbeWJKSkoLuOTo6mt27dzd4bHPmIjU1+GXmjBkzuOeee/jwww+ZP38+kiTx8ccfM378+ID7On78OI8++ihffPFF0GdcUVHRoL2nkmb9NVUoFAwYMKC1bTlvqZ2SFGrh0RoKZ82xy2J3o1IqCNdrgt7Y11Wf0RBxJh0GrQqXx9tiRbv6Fr7+RVy+2YZRq2bb0dI6e0S1Nn57THo1Rq06QHmxtq3p2eXsyauQIwR++xqzCD1QYKHI4sDh9p72Opj6nsn07HKijFp+PlpKTJj2tKYqNo/QTaObm/Z4ur6vNZ/xKKMWs9XXHiHfbMPicBOmVTX6XLXvtU/7SEosDnSapkW+6uNM/B4TCAQ+PNYK8v/7l4Btibe9isrYuBYN5zIqVejfhaeyMazX63u5tWTJkjpFaMLDwwN+bg07/dddtmwZCQkJQfvV6ua9KGuJbc2Zi1CtJhITExk2bBgfffQR8+fP5+eff+b48eMBNWgej4fRo0dTVlbGAw88QPfu3QkLCyMvL4+bb75ZtuVM0azZnzx5Mt9++y133HFHa9tzXlJb8jzUwuNMCAakpUSzbl8BkQZNyP27c81yxGp6WlKjU/q6J5iIj9BTYrFjdXpaVGdV38K3piS11elGr1FhdbpbtcFyQ3a9sP4gX+8rYFyv+DptTUuJZvWuPIor7UQa1AFiCo1ZhEYa1I1uCtua1PdM+rfZXR7KraenLrC5TOqXGPI+WhJdOV3f15rPeLcEk3y9OSvMKBTw4fYcqp0eJvVLbPI93DI0lSPFVZRbXa0mNHO2CZ8IBH80vLbKhgedQeLi4oiIiGDv3r31jktJSeHgwYNB2w8cOCDvP1WkpKSwd+9eJEkKiODUtsefqhYREcEVV1zRKtfu1KkTXq+XjIyMOh0U/3Xbtm3batdtLLUjWn5acy6uvfZa7rrrLg4ePMiHH36I0Whk0qRJ8v49e/Zw6NAh3nnnHWbOnClvX79+fYuu21o0S279kUce4ejRo8yePZv09HSKi4spKysL+ifwUZfkeV1jTqdd8yb0YFK/RFl1rCb+SEtWSTVvbmpY2tlPpd1NpEGD1eUlt8xapxx5S6kpSZ0YZSClTVirN1iui925ZhatyWDVznycbi9f7yusc376JkXR1qSnR2IkbU162b7GyIX7Ppv2zJvQ47RHAOp7Jv37bhmayshucSGfn7OFuu6jJbLyp+v7WvMZ91+vb1IU/ZOjAAUer8ShQkuz72HwBW3oFBdGnKl1+iWdid9jAoHg3EGpVDJlyhRWr14d1K4Afo+OTJgwgV9++YWtW7fK+6qrq3njjTfo2LFjvalyLWXChAnk5+ezcuVKeZvVag0ShEhLS6NTp048++yzVFUF10IXFxc3+dpTpkxBqVTy+OOPB0Ve/HMzduxYIiIieOqpp3C5gl9sNue6jcXfa8psNgdsb825mDZtGiqVihUrVvDxxx9z5ZVXBvS48kfWakbSJEnixRdfbNT5z0q59S5dugCwY8eOelWNhCpgMP4FR1OafJ4pIvTqkxEJJ7Hh2kan9/gjYUrA6ZE4Ulx9StQBa0eITuebcr/Sn06tIN9sx6BV8dbmrDpTJ0f3jA9qJtuYNLSzWaHvXK+nOReiK6E+f78Dr9coqbK7yC23NatGaneumUOFFrJLrVyYHNXgeIFAIGgNnnrqKdatWycravbo0YMTJ07w8ccfs3nzZqKionjwwQdZsWIF48ePZ86cOcTExPDOO++QlZXFJ598EiTs0JrcfvvtvPzyy8ycOZP09HTatWvHsmXLMBoDe2MqlUr++9//Mn78eHr16sWsWbNo3749eXl5bNiwgYiICFavXt2ka3fu3JmHHnqIJ554gmHDhjF16lR0Oh2//voriYmJLF68mIiICF599VX+/Oc/M2DAAK677jri4uI4fvw4a9as4dJLL+Xll19uzSmR6dSpE1FRUbz22muYTCbCwsIYNGgQqamprTYXbdu2ZdSoUTz33HNYLBauvfbagP3du3enU6dO3HvvveTl5REREcEnn3zS6Hq6s1Ju/dFHH60zHChomLOpDqE+Ww4UWLC7vITr1Li9jVe080fC7v5wJ9mlVjRKRZNVBWvT0CL+dDsgfqW/rvHhfH+giKJKO9uySusUmJiWlnxaZOdPBXXN/dn0HDeHs9lprY/Vu/Llmj2n24tHsje5RsovhnGkuBq3xxdxvaxH/Dk5HwKB4Nyiffv2bNu2jUceeYTly5dTWVlJ+/btGT9+vOy8xMfHs2XLFh544AFeeukl7HY7ffv2ZfXq1UycOPGU2mc0Gvnuu+/429/+xksvvYTRaOSGG25g/PjxAa0UwNdYd+vWrTzxxBO8/PLLVFVVkZCQwKBBg5pdLvP444+TmprKSy+9xEMPPYTRaKRv376yDDrA9ddfT2JiIk8//TRLlizB4XDQvn17hg0bxqxZs1p0//Wh0Wh45513mDdvHnfeeSdut5ulS5eSmpraqnNx7bXX8u2332IymZgwYUKQDatXr2bOnDksXrwYvV7P1VdfzV//+tcgSfwzgUI6lZV95yiVlZVERkZSUVHRbHWV+jjTb/ob0zgVYNGaDH48VESl3c2g1DZNUrMDuOmtbWw7WoZSqWD2sFTmju7W8EF1sPSnLMxWF1HGYJGNM4V/HjceLGJvXiWx4VquG9ghpH1n+jNvCXXNfXNr8ASNo65n5qa3trHzuE/R0+OVUCkVTOjTrklCM0t/yuJggYV9+RWUVDmI0GsY3jWOhyaeuvSaxnKqf/+eq4h5Of/p+OCaFh3vsVaQ+9INAduS/ra81cUrjj19ah0bgeBspLG/g1slllpRUSHS/prAma5DqB1pqMuWSf0SGd61LR3bhGF1enhlw+FG11kBON1eDFoVMUYNkcaWqwM2VI90uvHPY9d4E8O6xBITpq0zJSs9u5yDBZYmzyH4FthLf2p8jVtrU9/c78wxk1VSzcr03DNg2flNXTVgTreXKKOWOJOOCIOGdpH6JtdIpaVE0y3BxKKr+3Bl30QSIutvci0QCAQCgaBhmu1Ybd++nXHjxmE0GmnTpg0//PAD4CsKmzx5cp19PwRnHv9COUKvrnfB3jcpisQoAya9hp05ZryS1KQi+elpSSRFG4iux+FoLGfaGQ1FWko0VqevsWqcScfA1DZBjVb9TlGEXo3Z6iTKqG2y0MDqXflsPFjE6l35rWZ7U6hP/EGSJMqtLopO9tkStB51ObTT05Lo0c7ExR1jGNsrgR7tIposHlLzM+2eYMKgUdI9wdSa5gsEAoFA8IejWY7Vli1bGDp0KJmZmdx4440ByiWxsbFUVFSI5sEnOdPRhlD4F1WVdneDqmhpKdEoFdA/OQqlQtGkiNG0tGSmDkjisu7xQQ7H+YDf8TRq1RRbHBwsqAxyIP1Rh0q7m7tGdQ6QzG4aZ19NY1pKNIlRBuJMOiINmmYp051OzsbvYk1q21eXQzstLZm7RnUmzqTDpFczumc86dnlzbqv3blm1mcUEmXUnpffUYFAIBAITifNcqzmz59Pjx49yMjI4KmnngraP2rUKLZt29Zi484HWiLpfKppTHpd36QoRveMR6nwKds1p9/P2ZbC15r4o1ZHiqsosjiCRARq3n9zo26T+iWelZLmfZOimJ6WRHK0gQ4xxrP+Mz6bv4vQNPvSs8sxatUkRhk4UGBpdkQzPbscr+RL6WxpVFkgEAgEgj86zXKsfv31V2bNmoVOpwupDti+fXsKCgpabNz5wNnsWDR2oV9pdxNl1LI+o+5eTXWRWWhh29FSMgubplp2ruCfu7JqJ0Uhmqy2RgpjU8/RnMhMc6M5lXY3A1PbEGfSNTtqcrpobArsmaIpvyv8Yw8VVPLBL8f5Lbucn4+WNvmeakakRcRKIBAIBIKW0SzHSqPRBDUuq0leXh7h4eHNNup84mysDWoqaSnRmK1OvBJNFl9Yn1FIudXF+ozCU2fgGWR3rpm9eRWE69QkRxvOiqhScyIzzY3m+Bf4wFkdDYLAFNjmComcSpryu8I/dkdOBV4J7G4vGpUyYP4b4yz3TYpqYYqqQCAQCAQCP81yrAYPHhzQkbom1dXVLF26lBEjRrTIMMHZRXKMkRMVNoosjialHI3uGU+0URPQGPd8Ij27nJQ2YaTGhjFvQo+zwoFuTpS0uZHVvklRROjV7M2rILu0+pxYnPtfFDRHSORsY1yveEwGNVEGDS6PNyCdr7HO8vnw8kcgEAgEgrOBZjlWCxcuZPv27UycOJGvvvoKgF27dvHf//6XtLQ0iouLeeSRR1rVUMGZIz27nOxSK8dKq8ktt1IcIuWtLqalJfPany86b3sc+WWr7xrV+axZmDZnodySxfXK9FzyzXYKK+1nzRzUx/kUpZk7uht3DO9Ez8RIYsICBSjO5jRkgUAgCIXZbGb27NnExcURFhbGqFGj+O233xp1rEKhqPPf6NGjA8YuWrSIq666ivj4eBQKBQsWLGi0jVu2bGHBggWYzeYm3FnLyMvL45prriEqKoqIiAgmT57M0aNHG3XsU089xeDBg4mLi0Ov19OlSxfmzp1LcXFxvcctX74chULR6Ay0jIwMhg0bhslk4qKLLmLr1q1BY5577jl69eqF21136vlLL71EZGQkLperUdc922hWtfKgQYNYu3Ytf/nLX5g5cyYA//jHPwDo1KkTa9eupW/fvq1n5XnGudYsNkKvZuuREqwuD5JEk3vmtIRzba7+aOzONVNkcWC2OekYazzT5jSavklR583zFKFXU1btwOr0sCvHzO5cs3x/58s9CgSC8x+v18vEiRPZtWsX9913H7GxsbzyyiuMHDmS9PR0unTpUu/xy5YtC9q2fft2XnzxRcaMGROw/eGHHyYhIYELL7yQb775pkl2btmyhYULF3LzzTcTFRXVpGObQ1VVFaNGjaKiooL58+ej0Wh4/vnnGTFiBDt37qRNmzb1Hp+enk7//v257rrrMJlM7N+/nzfffJM1a9awc+dOwsLCQl7z/vvvD7kvFB6Ph6lTpxITE8OSJUv44osvmDx5MocPH5ab6RYVFfH444/z0UcfoVbX7X6sWbOGMWPGoNFoGnXts41my0BddtllHDx4kJ07d5KZmYnX66VTp06kpaWFFLQQ/E7tBr1nO5V2NwatGrvLg1LBae13c7bP1dlu36kmPbucSIMGu8uD0+2VF/XnEue6836gwILV6cHh9nK8rJpXNhw+qyKoAoHg9KBQ64i89E9B284VVq5cyZYtW/j444+ZPn06ANdccw1du3blscce4/3336/3+BtvvDFo28aNG1EoFPzpT4HzkpWVRceOHSkpKSEuLq71buIU8Morr5CZmckvv/zCxRdfDMD48ePp3bs3//rXv0Kqc9fkk08+Cdp2ySWXMH36dFavXs11110XtP/JJ5/EZDIxatQoVq1a1aCNmZmZHDx4kOzsbDp06MDMmTOJjY1l69atjB07FvApig8fPjzIya2J1Wrlhx9+4NVXX23wmg1RXV3daMewNWl2g2A//fv3Z8aMGVx77bVcdNFFwqlqBOdaik5aSjQ92pkwaFVEG7VBkuKn+tpn81zVtO9s75N0KkhLiSYtJZoOMUZS2oSddTVLjflMznYZdj+h7sUvnuL2ePF4vbg80nlROyYQCJqOUqsnaugNAf+UWv2ZNqvRrFy5kvj4eKZOnSpvi4uL45prruHzzz/H4Wh8GQKAw+Hgk08+YcSIESQlJQXs69ixY7NsXLBgAffddx8AqampcqrhsWPHAHC73TzxxBN06tQJnU5Hx44dmT9/fpNtr8nKlSu5+OKLZacKoHv37lx++eV89NFHzTqn//5DpTNmZmby/PPP89xzz9UbWaqJzWYDIDrat1YzGo0YDAasVisAv/32G8uXL+e5556r9zzfffcdDoeD8ePHc/ToURQKBc8//3zQuC1btqBQKFixYgXg+1wUCgUZGRlcf/31REdHM3To0EbZ3tq02LESNJ1zrVi8b1IUI7u1pXNbE2rV6X1kzva5qmnfubJAb036JkUxqV8ivdtHYnd5yDfbzirHsjGfydnovIdyokLdi78PVZHFgValJCZMi9nqFD2pBALBOceOHTsYMGAASmXgOmPgwIFYrVYOHTrUpPOtXbsWs9nMDTfc0Go2Tp06VY5+Pf/88yxbtoxly5bJUa/bbruNRx99lAEDBsjpeosXLw4ZFWoMXq+X3bt3c9FFFwXtGzhwIEeOHMFiafhltyRJlJSUUFBQwKZNm5gzZw4qlYqRI0cGjZ07dy6jRo1iwoQJjbaza9euREZGsmDBArKzs1myZAmVlZUMGDAAgDlz5vDXv/6Vzp0713uetWvXkpaWRnx8PBdccAGXXnopy5cvDxq3fPlyTCYTkydPDtg+Y8YMrFYrTz31FLfffnuj7W9NxF9fQRChUqPSUqLZlWOmsNJ+WlMBzyXSUqLlefsj4W9Wa3dZMWrVZ1VaZGM+k7OxFilUimmoe0lLiebDX3MwalVUOTyUVTuJCTu9UWWBQCBoDU6cOMHw4cODtrdr1w6A/Px8+vTp0+jzLV++HJ1OJ6cVtgZ9+/ZlwIABrFixgilTpgREvnbt2sU777zDbbfdxptvvgnAXXfdRdu2bXn22WfZsGEDo0aNatL1ysrKcDgc8hzUpOa8dOvWrd7zFBYWBpwjKSmJ999/n+7duweMW7NmDevWrWPXrl1NsjMsLIxXX32VW2+9leeeew6VSsUzzzxDSkoK77//PocPH2bt2rUNnmft2rXMmjVL/nnmzJnccccdHDhwQLbV5XLx0UcfMXXqVIzGwNrufv36NZgyeqoREStBEOnZ5UF9fvyLu+NlVt7ecuysikqcafzRBeCsjq6dKvwRn9E948+6yM/ZHvGsi1BRtFD30jcpituHpdI13sSwLrF0igunoMLOl7vzmfvBDvE9FQgE5ww2mw2dLrgmTK/Xy/sbS2VlJWvWrGHChAmnRWACkB2He+65J2C7X9xtzZo1TT6n/55bOi8xMTGsX7+e1atX8/jjjxMbG0tVVVXAGKfTyd13382dd95Jz549m2zrn/70J/Ly8ti6dSt5eXn84x//wGq18sADD7Bo0SLCw8NZuHAhF1xwAX379uWzzz4LOH7v3r0cP36ciRMnytuuueYa9Hp9QNTqm2++oaSkJGRN3Z133tlku1sbEbE6zZwLhfJpKdFsO1oq12r47SystGN1evj/9u47LIqz+xv4d5aOVBEFBBELGitCEHtvEU3sPdaokVgTG/oY0dixRM3PFqMQJRpr1GgUC3YjdmPEDiiIonSks+f9g3cnrAsKC8sWzue6vJK9p+yZ2WF3ztxNQJZG1UqomywRDf73FRpUtUTPxg7iudGGz7ukNLHGR9sV55z29XASpzO4G5WImfvuggj4JzqJ/04ZYxolKysL8fHxcmW2trbQ09ODiYlJgX2RMjIyAAAmJiZFfp/9+/cjIyOjVJsBfkxkZCQkEolCczc7OztYWVkhMjKy0G3T09ORlJSksJ3smEt6XgwNDdGpUycAQI8ePdCxY0e0bNkSlStXRo8ePQDkNW18+/YtFixY8NH9Fcba2hrNmjUTXy9duhSVK1fGqFGjsG3bNmzatAlBQUGIiIjAwIEDcf/+ffF8HT16FFWqVJFr9mhlZYWePXvit99+ww8//AAgryayatWq6NChg8L7u7i4KB17aeEaqzKmDf1wCpvnp5+HIxytTWBkoCcO68z+m3A2M0eKR69TFPrAaPrnzXTD3ahEHLnzEqaGEggC4GhtolG1h4wxdvnyZdjb28v9e/HiBYC8pm0xMTEK28jKHBwcivw+QUFBsLS0FJOGsqTMIG6///67wnkB8mqajIyMSu28yLRo0QL29vZiTVBSUhIWLVqEsWPHIjk5GREREYiIiEBqaiqICBEREYiNjS3We0RERGDVqlVYu3YtJBIJdu3ahfHjx6NDhw4YPXo0mjdvjt27d4vrHzt2DN26dVM4f8OHD8ezZ89w+fJlpKSk4PDhwxg8eLBCXzygeMm3qnCNVRnTln44BT0x7+vhhAevUnDsnxhcj0yArbkRPw3Hf4nokTsvAUChD4w2fN6loTzUzmmybRfDEfIgFrlEcK1ijnZ1KvPnwFg5kpuegtdBs+TKqgxdDj0TzekX3bhxY5w8eVKuzM7ODkDeKNMXLlyAVCqVu2m+evUqTE1N4erqWqT3iImJQUhICEaOHFlgE7qSKixxcnZ2hlQqxePHj/HJJ5+I5a9fv0ZiYiKcnZ0L3WfXrl0VzgsASCQSNGzYENevX1dYdvXqVdSoUQPm5sp9vhkZGWItWUJCAlJTU7FixQqsWLFCYV0XFxd88cUXRRp6XWb69On4/PPPxdH5Xr58KZcEOjg4IDo6GkDe6ISXL1/GxIkTFfbTrVs32NraIigoCF5eXkhLS8OXX35ZnEMtU0VKrCQSiVIZeG5ubrG30XXa2mxKdtP86HUKUjNzYKTPlZ35Ffa5fujz1pVERHYcZx/G4klsKg7cNMTi3g21+pi00dM3qUjLygEByM6VlotknjGWD0mRHfdcoUyTWFtbi03S3tevXz/s27cPBw4cEAecePv2Lfbu3YuePXvKJUlPnz4FANSsWVNhP7t374ZUKlVZM0DZ3EjvD1XevXt3zJkzBz/++CM2b94slsuGGM/fd+h9+Wup3tevXz/Mnj0b169fF5vJPXz4EGfOnMH06dPl1n3w4AFMTU1RrVo1AHlzOQmCoDDIw/79+5GQkCDur3Llygp9ngBg3bp1uHLlCnbt2lVofAUJCQnBsWPH8ODBA7GsSpUqcq/DwsLQu3dvAEBwcDAAFDjHlb6+PgYPHozffvsNYWFhaNiwIRo1alTkWMpakRKr77//XiGxOnjwIP7991907dpVHI3kwYMHCA4ORoMGDdCrV69SD5apx92oRGwIeQIrU0Nk5UhhZaKPlIxcVDDUU3doWk1XJheWHUdkXBqS07ORmpmDI3deau0xaWvCW9PWDM/j02CkL0GzGjZaFTtjjPXr1w/NmjXDqFGjcP/+fVSqVAkbNmxAbm6uQr+fjh07AoA4f1R+QUFBcHBwKHAocZkdO3YgMjJSnGfp/PnzWLRoEQDgyy+//GDtkoeHBwBg7ty5GDRoEAwMDNCzZ080btwYI0aMwJYtW5CYmIi2bdsiNDQUgYGB6NWrV7FHBJTx8fHBzz//DG9vb0yfPh0GBgZYvXo1qlSpIg6MIfPJJ5+gbdu2OHv2LIC8Oak6deqEgQMHom7dupBIJLh+/Tp27tyJ6tWrY8qUKQDy5p0q6L79jz/+QGhoaLHu6XNzczF16lTMmDFDTPCAvM935syZsLW1RWRkJP755x+xKeLRo0fRqlUrWFpaFrjP4cOHY926dQgJCcHy5cuLHIs6FCmx8vPzk3u9ZcsWxMbG4t69ewpDPIaFhaFDhw5KtflkmulGZAKsTPPmx+nn4YifL4TDzJiHdAb+uwm3MNZHckZOsW7GdaWZoIezNY7ceQlnG1Nk5uTCwthA3SGViLYmvKNb5XXa5SkRlPfvv//Cz88PN27cwKtXr2Bqaop69ephxowZ6Nmzp9y6YWFhmDZtGi5evAhDQ0N4e3tj9erV4nw2MlKpFCtXrsTGjRsRExMDV1dX+Pr6inPhMMby6Onp4dixY5gxYwbWrVuH9PR0eHp6IiAg4KPDics8fPgQN27cwLfffltgHxyZX375BefOnRNfh4SEICQkBADQqlWrDyZWnp6e+OGHH7Bp0yYcP34cUqkU4eHhqFChArZu3YoaNWogICAABw8ehJ2dHXx9fTF//vwingVF5ubmOHv2LKZNm4ZFixZBKpWiXbt2WLNmjcL3zfscHR3Rt29fnDlzBoGBgcjOzoazszMmTpyIuXPnwsbGRum4CrN582bEx8dj1iz5Zqlff/01wsPDsXr1alSoUAHbt29H/fr1QUQ4fvy4Qu1bfh4eHqhfvz7CwsLKdEASZQhERMXdqHbt2hg1ahTmzJlT4PLFixcjICAAjx8/LnGA6pCcnAxLS0skJSXBwsJC3eGoXf4n+EBeX47XyRno5+EojkZWXm2/FI7EtGw8fJWMOnYWsDI1wKiWLlpb66Gs7ZfC8fBVCiLj3imMjKhttPmzk12PsutQG6nz+/fYsWNYt24dmjdvDgcHB6SlpWH//v24cOECNm/ejHHjxgEAoqKi0KRJE1haWmLy5MlITU3FypUrUa1aNYSGhsLQ0FDcp6+vL5YtW4axY8fC09MThw4dwtGjR7Fr165iTRrKv0u6r/rs4g/HnV9uWhKi1svfdDpOCoKeacG1AMqKWFZ4kzbGiis0NBReXl74999/PzjMe5MmTVCxYkWcPn26DKP7T1G/g5UavCIqKgoGBoU/lTYwMEBUVJQyu2YaKH8/ocVH7+N5/DsY6euhdhV+Ki6rdepcr4pYYwVob62HsmRD9DvbVICDlYlWH7O29oMEdKcWVF26d++O7t27y5VNnDgRHh4eWL16tZhYLVmyBO/evcONGzfEpi5NmzZF586dERAQIK4XHR2NVatW4ZtvvsFPP/0EAPjqq6/Qtm1bzJgxA/3794eeHjepZoyVb0uWLPlgUnX9+nXcvn0bAQEBZReUkpQagaBBgwbYsGGDOJpHflFRUdiwYUOxZsdm2uNNSiYi49IR/y6LhxDHf5O29vVwkpu8taAJXnVZ/iH6LYz1sf1SOA/HrwbaOiGyJtPT04OTk5NcR/X9+/ejR48ecv0HOnXqBFdXV+zZs0csO3ToELKzs+Hj4yOWCYKACRMmICoqCleuXCmTY2CMMU3VtGlT+Pr6Frjs3r17CAwMxOjRo2Fvb4+BAweWcXTFp1SN1Zo1a9C1a1e4urqid+/e4uRejx8/xh9//AEiws6dO0s1UFY6lGnmlH8bW3MjVDIzQGaOFBbGPFp/YbS51kNZjRyt8Ph1Cn6+EI5qFU3EMqZ62tx8URO9e/dOnLDz8OHD+Ouvv8Qf9OjoaMTGxspNYinTtGlTHDt2THx969YtVKhQQW7oZdl6suWyoYgZY4zJ27dvHxYuXIg6depg165dMDY2VndIH6XUnXGrVq1w9epVzJs3DwcPHkR6ejqAvIm5unbtigULFnCNlYZSpola/m16NnbAvegkZOZIefCKcqI4N+37bkThTUoGYpMz0LW+XdkEyMpd01NV++6778ThkiUSCfr06SM25ZNNylnQ0MP29vaIj49HZmamOKlnlSpVFEbVlW378uXLQmPIzMxEZmam+Do5OblkB8UYY1rGz89PYQA9Taf0ZEQNGjTAwYMHkZKSgpiYGMTExCAlJQUHDhzgpEqDKdNELf82jRyt0KCqJcy1fOQ3VnT5b9o/poqFMXJyCfp6AifeZai8NT1VtalTp+LkyZMIDAzEZ599htzcXGRlZQGA+CCxoIlHZU9TZeukp6cXab2CLF26FJaWluI/J6fyPVAQY4xpgxK35ZJIJDA2NoaZmdkHh7YsrzStiY4yTdTe36ZnYwfuIF+OFGdAhNGtXPD0TSoS3mXhTUrmR9dnpaM8Nj1Vpbp166Ju3boA8uZP6dKlC3r27ImrV6/CxCSvmWv+2iSZjIwMABDXMTExKdJ6BfH19cW3334rvk5OTubkijHGNJzSmdD169fRrVs3mJqawsbGRpwP4O3bt/jiiy/EycnKu+I87dcWmtZB/m5Uok4MlqCpx1Gcz7uRoxUqVjBEerYUCWlZqg+OsTLQr18/XLt2DY8ePRKb8cmaBOYXExODihUrirVU9vb2ePXqFd6f1US27YfmezQyMoKFhYXcP8YYY5pNqcTq8uXLaNWqFR4/foxhw4ZBKpWKyypVqoSkpCSxfXp5x010VE9XkldtPY73E8KsHCnMjPSRlSP98IaMaQlZk72kpCRUrVoVtra2uH79usJ6oaGhcHNzE1+7ubkhLS0NYWFhcutdvXpVXM4YY0x3KJVYzZkzB5988gnu37+PJUuWKCxv3769+MNR3mla7Y4ueP9GXleSV209jvwJ4d2oRBjqS5CVmwtDfYnG1b4x9iGxsbEKZdnZ2fj1119hYmIizrPSt29f/Pnnn3jx4oW43unTp/Ho0SP0799fLPviiy9gYGCADRs2iGVEhE2bNqFq1apo0aKFCo+GMcZYWVOqj9W1a9ewdOlSGBkZITU1VWF51apV8erVqxIHp800rW+VLnl/BDRd6V+irceRvw/WjcgEpGTkICuHEPH2HWbuu4uxrfPm+WJM040fPx7Jyclo06aN+DsWFBSEBw8eYNWqVTAzMwOQ93Bx7969aN++PaZMmYLU1FT4+/ujYcOGGDVqlLg/R0dHTJ06Ff7+/sjOzoanpyf++OMPXLhwAUFBQTw5MGOM6RilEisDAwO55n/vi46OFn+Ayise/lh1ijOYAlO99xPC4H9foZKZId6kZMLM2AAn77/mxIpphYEDB+KXX37Bxo0bERcXB3Nzc3h4eGD58uX4/PPPxfWcnJxw7tw5fPvtt5g9ezYMDQ3h7e2NVatWKYwCuGzZMlhbW2Pz5s0ICAhA7dq1sXPnTgwZMqSsD4/pOEHPAGZNvBXKGGNlR6D3e9UWQbdu3ZCamoqLFy8iLi4Otra2OHXqFDp06IB3796hfv368PT0xN69e1URs8olJyfD0tISSUlJSncY5hor1eLzq7nuRiXiyJ2XePQ6BVk5UvTzcOTEihVZaXz/6iI+L7qv+uyj6g6hSCKWeX98JcZ0TFG/g5XqY7VgwQJcv34d3t7e+OuvvwAAd+7cwdatW+Hh4YE3b95g3rx5ykWuI7hvlWpp60AP5UEjRys4WJnASF8PCWnZ6g4HgOaOuMgYY4wx3aFUYuXl5YVjx47hyZMnGD58OIC8merHjRuH3NxcHDt2DI0aNVIqoMzMTMyaNQsODg4wMTGBl5cXTp48WaRtT506hfbt26NSpUqwsrJC06ZNsWPHDqXiYJpNWwd60DSqSjgsjPVxLSIeMYlpWH/midoTGk7EGWOMMaZqSk8Q3KFDBzx8+BC3b9/G48ePIZVKUbNmTXh4eEAQBKUDGjlyJPbt24epU6eidu3aCAgIQPfu3RESEoJWrVoVut3hw4fRq1cvNG/eHH5+fhAEAXv27MHw4cPx9u1bTJs2TemYmObR1oEe3qfuJo2q6gt44fFbZOVKkZ0jhZ2+RO19DblfHmOMMcZUTak+VqoSGhoKLy8v+Pv7Y/r06QDyZqhv0KABKleujMuXLxe6bZcuXfDvv//i2bNnYufhnJwc1K1bFxUqVMCdO3eKHEdJ27Kr+2aZaY/FR+/j0etUuFYxw1zvemX+/qq6VgdvuYLwt+8gCECPRg7o2diB/xZYkXBfooLxedF93MeKMc2l0j5WEokE9vb2OH/+fIHLlR1Gdt++fdDT08O4cePEMmNjY4wZMwZXrlyRmzPkfcnJybC2tpYbkUlfXx+VKlWCiYlJsWMpCW52xIpHfc82VNUXsJ+HI1wqVYCXiw0nVYwxxhgrF5RKrIC8mqROnTph7dq1pRbMrVu34OrqqpAJNm3aFABw+/btQrdt164d/v33X8ybNw9PnjzB06dP8cMPP+D69euYOXNmqcVYFBbG+nj4KhkWxkq3tGTlRM/GDmhXpzJ6NnZQdyilqnYVc1iaGCAtKxcbQtTfx4oxxnSdNCMVr36bLfdPmqE41yhjTHWUvvP/8ccfERoaimnTpuH69ev4+eefYWxsXKJgYmJiYG9vr1AuK3v58mWh286bNw/h4eFYvHgxFi1aBAAwNTXF/v378cUXX3zwfTMzM5GZmSm+Tk5OVib8/7bPyEEdOwskZ+SUaD9M9xWlr5g2Ni29EZkAK1ND3H6RiGoVTbEh5Al82tfSmvgZY0zbkDQXmS/uKZQxxsqO0jVWBgYG+L//+z8EBATgwIEDaNmyJZ4/f16iYNLT0xUmVwQgJmzp6emFbmtkZARXV1f069cPu3btws6dO/Hpp59i2LBh+Pvvvz/4vkuXLoWlpaX4z8mpZHPucI0VK03a1LRUNsqghbE+6tiZo1v9KngenwYpkVbEzxhjjDGmLKUTK5nhw4fj0qVLSExMhIeHB06fPq30vkxMTORqjmQyMjLE5YWZOHEijhw5gt27d2PQoEEYOnQoTp06BXt7e0yZMuWD7+vr64ukpCTx34f6chUF11ix0qRJQ8t/bHh2WRKYnJGDUS1dcP7xG4S/fYf7MckaET9jjDHGmKqUOLECADc3N9y4cQOenp7o1q0bfvnlF6X2Y29vj5iYGIVyWZmDQ8H9ULKysvDLL7/A29sbEsl/h2RgYIDPPvsM169fR1ZWVqHva2RkBAsLC7l/JeHhbI20rBy8TEznviWsSD6UsGjSZNMfqz17PwmMeJsGECEtM1cj4meMMcYYU5VSSawAwMrKCkePHsWcOXNw7tw5pfbh5uaGR48eKfRxunr1qri8IHFxccjJyUFurmJb4uzsbEil0gKXqUojRys4WJnA1FCfmz+xItH05n75m/h9qPbs/SSwa/0qMDXSR/VKpvyQgTHGGGM6TanEKjw8HL169VIoFwQBCxYswJ07d3DmzJli77dfv37Izc3Fli1bxLLMzExs374dXl5eYt+n58+f48GDB+I6lStXhpWVFQ4ePChXM5WamoojR46gbt26ZT7kuiY132Jl52NN5Qqj6dfL+038ilr7NNjLGXXtzPEuMxdLj4VxcsUYY4wxnaXU6ArOzs4fXN6gQQOlgvHy8kL//v3h6+uL2NhY1KpVC4GBgYiIiJBrXjh8+HCcO3cOsrmN9fT0MH36dPzvf/9Ds2bNMHz4cOTm5uKXX35BVFQUdu7cqVQ8JVGU0d6Y7slf81Scz1/TrxcPZ2txZMLiuBGZgPh3WYiMS0NCWhaO3Hmp0cfJGGOMMaasIiVWCxcuhCAImDt3LiQSCRYuXPjRbQRBwLx584od0K+//op58+Zhx44dSEhIQKNGjfDnn3+iTZs2H9xu7ty5cHFxwdq1a7FgwQJkZmaiUaNG2LdvH/r27VvsOBhThrIJiKZTNvHzcLZG8L+vkJCWDUP9Umt5zBhjjDGmcQSSVft8gEQigSAISE9Ph6GhodwAEYXuWBDKtF9TaUpOToalpSWSkpKUGshCG+cdYppL26+nu1GJOHInbw66no0dVHYM2n6eWJ6Sfv/qKj4vuq/67KMl2j43LQlR64fKlTlOCoKeqWWJ9vu+iGXepbo/xrRBUb+Di/QIWTb4g6Ghofj6Y/+0NakqDZo+EAErfcr2rSoKbb+eGjlaoWdjBzhYqbafo7afJ8YYY4xpN26bowKaPhABK32qvKnX9uvpblQilh4Lw5E7L8WaK1XQ9vPEGGOMMe2m1OAV7MM0fSACVvpU2bdK26+nI3de4nl8GgRBUOn7aPt5Yowxxph2K1Ji5eLiUuybIkEQ8PTpU6WCYkzb8E39h1WxMIaRvgQ9Gxc8ybe6cL8sxhhjjJWWIiVWbdu2VfnTZl3CN2uM/UfWv0oT/x6UHR6fMcYYY+x9RUqsAgICVByGbjly5yUevU7Fy8R0vlkrZzip1jwf+kx0dXh8xlj5I+jpw7ROS4UyxljZ4b84lfnoKPasFGhaIqPKGhBNO9aiynvQkKK2Bw0f+ky4CSdjTFdIjCrAtpevusNgrFwrUWKVnZ2NBw8eICkpCVKpVGH5xyb11VU9GzvwU/AyomlNuVRZA6Jpx1o86mtKzLVSjDHGGCsLSiVWUqkUvr6+2LBhA9LS0gpdr7zOZaUtT8G1tQYkP027aVblZ69px1pU6n7QIPs8ZEPha+u1zhhjjDHNplRitWTJEvj7+2P8+PFo1aoVvvzySyxfvhxWVlbYsGEDBEHAihUrSjtWVsq0uwYkj7YksaVBW49VE+LWhWudMcYYY5pNqcQqICAAAwYMwMaNGxEXFwcA8PDwQIcOHTBixAg0b94cZ86cQadOnUo1WFa6tLUGhLHi0rZrXRdqk7XRtWvXEBgYiJCQEERERMDGxgbNmjXDokWL4OrqKrduWFgYpk2bhosXL8LQ0BDe3t5YvXo1bG1t5daTSqVYuXIlNm7ciJiYGLi6usLX1xeDBw8uy0Njpaz67KPqDoExpoEkymwUFRWFDh06AACMjIwAABkZGQAAQ0NDDBs2DDt27CilEJmqNHK0wqiWLnzjxnSetl3r+WvYWNlZvnw59u/fj44dO2Lt2rUYN24czp8/D3d3d9y7d09cLyoqCm3atMGTJ0+wZMkSTJ8+HUePHkXnzp2RlZUlt8+5c+di1qxZ6Ny5M9avX49q1aphyJAh2L17d1kfHmOMMRVTqsbKxsYGqampAAAzMzNYWFjg2bNncuskJPANAWNFoSu1E7pyHJqgtGrY+DMpnm+//Ra//fYbDA0NxbKBAweiYcOGWLZsGXbu3Akgrzn8u3fvcOPGDVSrVg0A0LRpU3Tu3BkBAQEYN24cACA6OhqrVq3CN998g59++gkA8NVXX6Ft27aYMWMG+vfvDz09vTI+SqarpJnvEPfXOrkym88mQ2JUQU0RMVb+KFVj1aRJE1y7dk183b59e/z444+4dOkSLly4gHXr1qFx48alFiRjukxXaid05TjU4W5UIrZfCsfdqEQApVfDxp9J8bRo0UIuqQKA2rVro379+ggLCxPL9u/fjx49eohJFQB06tQJrq6u2LNnj1h26NAhZGdnw8fHRywTBAETJkxAVFQUrly5osKjYeUN5eYg7eEluX+Um6PusBgrV5RKrMaNG4fMzExkZmYCABYvXozExES0adMGbdu2RXJyMlatWlWqgTKmqzycrWFlaqA1/X8KoyvHoQ6qSoD4Myk5IsLr169RqVIlAHm1ULGxsfj0008V1m3atClu3bolvr516xYqVKiATz75RGE92XLGGGO6Q6mmgJ9//jk+//xz8XW9evXw9OlTnD17Fnp6emjRogUqVqxYakEypss0YdS80qArx6EOqhpcgz+TkgsKCkJ0dDQWLlwIAIiJiQEA2NvbK6xrb2+P+Ph4ZGZmwsjICDExMahSpQoEQVBYDwBevnxZ6Pvmf3gJAMnJySU+FsYYY6pVogmC87O0tMQXX3xRWrtjjGk47r9TcvnP4aiWLuoOh73nwYMH+Oabb9C8eXOMGDECAJCeng7gv4Gb8jM2NhbXMTIyEv/7ofUKs3TpUixYsKDEx8AYY6zslCixys7ORnR0NBISEkBECsvd3d1LsnvGmAbjuaFKjs+h5nr16hW8vb1haWmJffv2iYNMmJiYAIBcbZKMbHRc2TomJiZFWq8gvr6++Pbbb8XXycnJcHJyUvJoGGOMlQWlEqvExERMnz4dQUFBCkPLAnlt0gVBQG5ubokDZIxpJm2bG0oT8TnUTElJSfjss8+QmJiICxcuwMHBQVwma8YnaxKYX0xMDCpWrCjWUtnb2yMkJET8Tcy/HgC5/b7PyMiowNouxhhjmkupxGrkyJE4cuQIBg0aBC8vL1haWpZ2XIwxDZe//w43C1QO94HSPBkZGejZsycePXqEU6dOoV69enLLq1atCltbW1y/fl1h29DQULi5uYmv3dzcsHXrVoSFhcnt5+rVq+JyxhhjukOpxCo4OBiTJ0/GmjVrSjsexpgW4iZtTBfk5uZi4MCBuHLlCg4dOoTmzZsXuF7fvn0RGBiIFy9eiM3zTp8+jUePHmHatGniel988QWmTZuGDRs2iPNYERE2bdqEqlWrokWLFqo/KMYYY2VG6QmCa9WqVdqxMMa0FDdpY7rgu+++w+HDh9GzZ0/Ex8eLEwLLDBs2DAAwZ84c7N27F+3bt8eUKVOQmpoKf39/NGzYEKNGjRLXd3R0xNSpU+Hv74/s7Gx4enrijz/+wIULFxAUFMSTAzPGmI5RKrEaN24cdu/ejQkTJkAiUWoqLMaYDuEmbUwX3L59GwBw5MgRHDlyRGG5LLFycnLCuXPn8O2332L27NkwNDSEt7c3Vq1apdAvatmyZbC2tsbmzZsREBCA2rVrY+fOnRgyZIjKj4cxxljZUiqxmjdvHjIzM/Hpp5/iyy+/hKOjY4FP3vr06VPiABlj2oH7WTFtd/bs2SKvW79+fZw4ceKj60kkEvj6+sLX17cEkTHGGNMGSiVW0dHROHPmDG7fvi0+4XtfeR4VkG8wWXnE/awYY4wxVp4plViNHj0aN2/ehK+vL48KWAC+wWTlEfezYowxxlh5plRidfHiRcyaNYtnhS8E32Cy8kbXa2l1/fgYY4wxVnJKJVZ2dnaoWLFiaceiM7gjPytvdL2WVtePjzGm/QSJHoycGiiUMcbKjlKJ1XfffYeNGzdizJgxMDMzK+2YGCs1XNNQNnS9llbXj48xpv0kxmawG7JM3WEwVq4plVhlZGTAwMAAtWrVwoABA+Dk5KQwKqAgCHITJTKmDtpQ06ALyZ+21NIqe6615fgYY4wxpj5KJVbTp08X/182m/z7OLFimkAbahq0IfkrCm1IEHXlXBdEG84/Y4wxpsuUSqzCw8NLOw7GVEIbahq0IfkrCm1IWrTxXBc1YdKG888YY4zpsmInVunp6Vi7di3at2+Pnj17qiImxsqV/MmfNtc6aEPSog2J9vuKmjBpw/lnjDHGdFmxEysTExNs3rwZ9erVU0U8jOmc4iRL2lzroI1JizYoasLE558xxhhTL6WaAnp4eODevXulHQtjOqk4yZI21Dpoc62aNuKEiTFWFNLMNCScC5Qrs247AhIjUzVFxFj5o1Ri9eOPP6J79+5o0KABRo4cCX19pXbDWLlQnGSpoJtoTUtktLlWjTHGdBXlZiP11lG5MqtWQ9QUDWPlk1IZ0ciRIyGRSDB+/HhMnjwZVatWhYmJidw6giDgzp07pRIkY9qspDUOmpbIaEOtGmOMMcZYWVMqsapYsSJsbGxQp06d0o6HMfYeTUtkuGkaY4wxxpgipRKrs2fPlnIYjLHCcCLDGGNMU1SfffTjKykhYpm3SvbLWFmSqDsAxhhjjDHGGNN2So86kZubi507d+Lo0aOIjIwEADg7O6NHjx4YOnQo9PT0Si1IxhhjjDHGGNNkStVYJSUloWXLlhg9ejSCg4ORnZ2N7OxsnDx5EqNGjUKrVq2QnJxc2rEyBiBvlLztl8JxNypR3aEwxhhjjDEGQMnEau7cubhx4wbWr1+PN2/e4ObNm7h58yZiY2Px008/4fr165g7d25px8oYAPlR8hhjjDHGGNMESiVWBw8ehI+PD3x8fGBgYCCWGxgYYMKECZgwYQL2799fakEylp+HszWsTA00ZpQ8xhhjjDHGlOpjFRcX98Gh1uvWrYv4+Hilg2KqoWkTzRZFQTHzKHmMMcYYY0zTKFVjVatWLRw+fLjQ5YcPH0bNmjWVDoqphjY2odPGmBkrC9zXkDHGGNMsSiVWPj4+CA4ORvfu3REcHIyIiAhERETgxIkT8Pb2xsmTJzFx4sTSjpWVkDY2odPGmBkrC/zQgTHGGNMsSjUF9PHxQWxsLJYtW4YTJ07ILTMwMMD333+PCRMmlEqArPRoYxM6bYyZsbLg4WwtNpNljDHGmPopPY+Vn58fJk6ciFOnTsnNY9WpUydUqlSp1AJkjDGmiB86MMYYY5pF6cQKACpVqoRBgwaVViyMMcaYWqWmpsLf3x9Xr15FaGgoEhISsH37dowcOVJh3bCwMEybNg0XL16EoaEhvL29sXr1atja2sqtJ5VKsXLlSmzcuBExMTFwdXWFr68vBg8eXEZHVb5Vn31U3SGUDUECA5tqCmWMsbJTosQqJSUFkZGRSEhIABEpLG/Tpk1Jds8YY+WCNo7Yqavevn2LhQsXolq1amjcuDHOnj1b4HpRUVFo06YNLC0tsWTJEqSmpmLlypX4559/EBoaCkNDQ3HduXPnYtmyZRg7diw8PT1x6NAhDBkyBIIg8MNJVmr0TMzh8NUGdYfBWLmm9HDrEydOxP79+5GbmwsAICIIgiD3/7JljDHGCpd/IApOrNTL3t4eMTExsLOzw/Xr1+Hp6VngekuWLMG7d+9w48YNVKuWV0vQtGlTdO7cGQEBARg3bhwAIDo6GqtWrcI333yDn376CQDw1VdfoW3btpgxYwb69+8PPT29sjk4xhhjKqVUYjV27FgcOXIEkydPRuvWrWFtzZ2nGWNMWTwQheYwMjKCnZ3dR9fbv38/evToISZVANCpUye4urpiz549YmJ16NAhZGdnw8fHR1xPEARMmDABQ4YMwZUrV9CqVavSPxDGGGNlTqnEKjg4GNOmTcOKFStKOx7GGCt3eCAK7RIdHY3Y2Fh8+umnCsuaNm2KY8eOia9v3bqFChUq4JNPPlFYT7acEyvGGNMNSvVqNDU1RfXq1Us5lDyZmZmYNWsWHBwcYGJiAi8vL5w8ebLI2//+++9o3rw5KlSoACsrK7Ro0QJnzpxRSayMlRZtmuxVm2JlTBViYmIA5DUbfJ+9vT3i4+ORmZkprlulShWxqXz+9QDg5cuXBb5HZmYmkpOT5f4xxhjTbEolVsOGDcPBgwdLOxYAwMiRI7F69WoMHToUa9euhZ6eHrp3746LFy9+dFs/Pz8MHjwYTk5OWL16NRYtWoRGjRohOjpaJbFqMr751S7aNNmrNsXKykZ5+75JT08HkNds8H3GxsZy66SnpxdpvfctXboUlpaW4j8nJ6dSiZ0xxpjqKNUUsF+/fjh37hy6deuGcePGwcnJqcDOt+7u7sXab2hoKHbv3g1/f39Mnz4dADB8+HA0aNAAM2fOxOXLlwvd9u+//8bChQuxatUqTJs2rXgHpIO4M7x20aY+NtoUKysb5e37xsTEBADEWqn8MjIy5NYxMTEp0nrv8/X1xbfffiu+Tk5O5uSKfZA0KwPJofvlyiya9oXE0FhNETFW/iiVWOVvD15QMz1lRwXct28f9PT0xE6/QN5TvTFjxmDOnDl48eJFoT8sP/74I+zs7DBlyhQQEd69ewczM7Nivb8u4Ztf7fJ+HxtNHn6b+wOx95W37xtZMz5Zk8D8YmJiULFiRbGWyt7eHiEhIXIj5+bf1sHBocD3MDIyKrCmi7HCUE4mki7tkiszd+8BcGLFWJlRKrHavn17accBIK8Tr6urKywsLOTKZZ18b9++XWhidfr0abRo0QLr1q3DokWLEBcXBzs7O8ydOxcTJ05USbyajG9+tVt5qwFg2q28fd9UrVoVtra2uH79usKy0NBQuLm5ia/d3NywdetWhIWFoV69emL51atXxeWMMcZ0g1KJ1YgRI0o7DgB5T/AK6wwMFN7JNyEhAW/fvsWlS5dw5swZzJ8/H9WqVcP27dsxadIkGBgYYPz48YW+b2ZmplxTDe4kzNStLGoANLlWjDFN17dvXwQGBsq1pDh9+jQePXok1xz9iy++wLRp07BhwwZxHisiwqZNm1C1alW0aNFCLfEzxhgrfUolVvnFxMQgNjYWtWrVQoUKFUq0L2U7+aampgLIm7h49+7dGDhwIIC8vmANGzbEokWLPphYLV26FAsWLChR7IyVprKoAShurRgnYuxjdOUa+emnn5CYmCg+zDty5AiioqIAAJMmTYKlpSXmzJmDvXv3on379pgyZQpSU1Ph7++Phg0bYtSoUeK+HB0dMXXqVPj7+yM7Oxuenp74448/cOHCBQQFBfHkwIwxpkOUGhUQyJv0sG7dunB0dIS7u7vYrOHt27do0qSJUqMGKtvJV1ZuYGCAfv36ieUSiQQDBw5EVFQUnj9/Xuj7+vr6IikpSfz34sWLYsfOmLbxcLaGlalBkWvFijsaYHkbKY7pzoiRK1euxLx587Bx40YAwIEDBzBv3jzMmzcPCQl5x+bk5IRz586hZs2amD17NlasWIHu3bvj5MmTCg8Ily1bhiVLluDEiRP45ptvEBERgZ07d2LIkCFlfmyMMcZUR6kaqyNHjqBPnz5o3rw5hgwZAj8/P3FZpUqVULVqVQQEBKB3797F2q+9vX2BQ6N/rJNvxYoVYWxsDCsrK4Wnf5UrVwaQ11ywWrVqBW7PnYRZeVTcWrHiNk/kfmLlj64MYhEREVGk9erXr48TJ058dD2JRAJfX1/4+vqWMDLGGGOaTKkaq4ULF6JNmza4ePEivvnmG4XlzZs3x61bt4q9Xzc3Nzx69Eihj9PHOvlKJBK4ubnhzZs3yMrKklsma8pha2tb7HgYY/9p5GiFUS1dPpgk5a+lKm6NGNN+RblGGGOMMV2lVGJ17949DBgwoNDlVapUQWxsbLH3269fP+Tm5mLLli1iWWZmJrZv3w4vLy+xg/Dz58/x4MEDuW0HDhyI3NxcBAYGimUZGRkICgpCvXr1Cq3tYrqDm56p3/u1VHyTzRhjjLHyQqmmgKampnj37l2hy589ewYbG5ti79fLywv9+/eHr6+vOCBGYGAgIiIi8Msvv4jrDR8+HOfOnQMRiWXjx4/H1q1b8c033+DRo0eoVq0aduzYgcjISBw5cqTYsTDtw03P1E9XmoIxxhgrW9VnHy31fUYs8y71fTL2IUrVWLVv3x6BgYHIyclRWPbq1Sv8/PPP6NKli1IB/frrr5g6dSp27NiByZMnIzs7G3/++SfatGnzwe1MTExw5swZDBkyBNu2bcOMGTMgkUhw9OhRfPbZZ0rFwrQLNz1TP66lYowxxlh5pVSN1eLFi9GsWTN4enqif//+EAQBJ06cwJkzZ7B582YQEebPn69UQMbGxvD394e/v3+h65w9e7bA8sqVKyMgIECp92Xar7xNUqrJdGXYbcYYY4yxolKqxqpOnTq4ePEibGxsMG/ePBAR/P39sWTJEjRs2BAXLlxA9erVSzlUxpi20JVhtxljjDHGikrpCYLr16+PU6dOISEhAU+ePIFUKkWNGjXE0feICIIglFqgjDHtwX2tGGOMMVbeKJ1YyVhbW8PT01N8nZWVhYCAAKxcuRKPHj0q6e4ZY1qIm2UyxhhjrLwpVmKVlZWFw4cP4+nTp7C2tkaPHj3EYczT0tLw008/4ccff8SrV69Qs2ZNlQTMGGOMMcYUSUws1B0CY+VakROrly9fol27dnj69Kk4zLmJiQkOHz4MQ0NDDBkyBNHR0WjatCnWr1+PPn36qCxoxhhjjDH2Hz1TSzhN/k3dYTBWrhU5sZo7dy7Cw8Mxc+ZMtG7dGuHh4Vi4cCHGjRuHt2/fon79+ti5cyfatm2ryngZY4wxpqNUMZcRY4yVlSInVidPnsSoUaOwdOlSsczOzg79+/eHt7c3Dh06BIlEqUEGGWOMMcYYY0yrFTmxev36NZo1ayZXJns9evRoTqoYY4wxxpjGUEUNaMQy71LfJ9MdRc6GcnNzYWxsLFcme21paVm6UTGmg+5GJWL7pXDcjUpUdyiMMcYYY6yUFWtUwIiICNy8eVN8nZSUBAB4/PgxrKysFNZ3d3cvWXSM6ZD8k+Zq+1Dkd6MSxXmqtP1YGGOMMcZKg0CyIf4+QiKRFDjhb0ETAcvKcnNzSyfKMpacnAxLS0skJSXBwoKHLmWlQ5eSke2XwpGYlg0rUwOMaumi7nDKPV26tvj7t2Dl5bzw4BXKk2Zn4t0/J+XKKjTsDImBkZoiYkXFzQs1X1G/g4tcY7V9+/ZSCYyx8kqXJs31cLYWb+SZ+ulSbShjTDmUnYH4k5vkykzrtgY4sWKszBQ5sRoxYoQq42CMaRFdShJ1ASe6jDHGmPoVq48VY4xpG11qJlcYTnQZY4wx9eMx0hljOi1/MzldxyNPMsYYY+rDiRVjTKd5OFvDytSgXDSTK09JJGOMMaZpuCkgYxqkPDRbK2vlqZkc97VijDHG1IcTK8Y0CI/uxkqiPCWRrOhUMYQ5Dw/NGGOKuCkgYxqkPDVbY4wxxhjTJVxjxZgG4RoHxhhjjDHtxIkVY4wxpkKZmZn4/vvvsWPHDiQkJKBRo0ZYtGgROnfurO7QGGMagJvr6g5uCsgYY4yp0MiRI7F69WoMHToUa9euhZ6eHrp3746LFy+qOzTGGGOliGusGCsDPNofY+VTaGgodu/eDX9/f0yfPh0AMHz4cDRo0AAzZ87E5cuXi7W/BvNPQGJkqopQGWM6hGvB1IMTK8bKAI/2x5TBCbn227dvH/T09DBu3DixzNjYGGPGjMGcOXPw4sULODk5qTFC5ajipo0xxrQdJ1aMlQGeX4gpgxNy7Xfr1i24urrCwsJCrrxp06YAgNu3b2tlYsUYK3/K8wMVaWZakdbjxKoARAQASE5OVnMkTFdUt5CgekMbAHxdsaKrU1EPt9+loE5F43Jz3ciOU/Y9rO1iYmJgb2+vUC4re/nyZYHbZWZmIjMzU3ydlJQEoOg/7qz8kWYpXhvSrDQIegZqiIYx3SL77v3YbxMnVgVISUkBAH6KyBhjapKSkgJLS0t1h1Fi6enpMDIyUig3NjYWlxdk6dKlWLBggUJ59MaRpRof020vN49VdwiM6ZSP/TZxYlUABwcHvHjxAubm5hAEocB1kpOT4eTkhBcvXig08dB0HLt6cOzqwbGrh7KxExFSUlLg4OCgwujKjomJiVzNk0xGRoa4vCC+vr749ttvxddSqRTx8fGwsbEp9HdJU2nzdazN+LyrB5939VD1eS/qbxMnVgWQSCRwdHQs0roWFhZa+4fDsasHx64eHLt6KBO7LtRUydjb2yM6OlqhPCYmBgAK/ZE2MjJSqOmysrIq9fjKkjZfx9qMz7t68HlXD1We96L8NvE8VowxxpiKuLm54dGjRwp95K5evSouZ4wxphs4sWKMMcZUpF+/fsjNzcWWLVvEsszMTGzfvh1eXl7cl5cxxnQINwVUkpGREebPn19gp2RNx7GrB8euHhy7emhz7KXJy8sL/fv3h6+vL2JjY1GrVi0EBgYiIiICv/zyi7rDKxN8LagHn3f14POuHppy3gXSlTFtGWOMMQ2UkZGBefPmYefOnUhISECjRo3www8/oGvXruoOjTHGWCnixIoxxhhjjDHGSoj7WDHGGGOMMcZYCXFixRhjjDHGGGMlxIkVY4wxxhhjjJUQJ1aMMcaKjbvnMsYYKwtSqVTdIRQZJ1ZM7fgGjZU3SUlJ6g5Bab///jsAQBAENUfCNAl/j5eNjIwMudd83pkue/z4MXJzcyGRaE+6oj2RqtCtW7fw/PlzuZsdbfmySktLU3cISnv27BnS0tIUfii0wZ07d/D48WNERUWJZdpyzQDAoUOH4OPjg2fPngHQrqdBu3btgrm5OS5duqTuUIrtwIED6NKlC9asWYOIiAh1h1Msu3fvRs2aNTF48GBcvHhR3eEwNTp58iRmz56NjRs34vLlywA40Va1e/fuoX///hg0aBC+/vprhIaGAuDzrmq///47vv76ayxfvlzue0+bfu+10Y4dO+Dq6oouXbqgXr16WLhwodY8kCzXiVVYWBhatWqFjh07onHjxmjatCn279+PnJwcCIKg0X84Dx8+hIeHB7766it1h1Jsd+/ehbe3N3r27AkXFxe0a9cOly5d0ujzLXP37l107twZPXr0gIeHBxo3box169aJ14w2OHnyJHr37o0dO3bgzz//BACteBp069YteHl5YfTo0fD29oaFhYW6Qyqyly9fwtvbG8OHD4ehoSFMTU1hamqq7rCKRHbeR4wYAXNzcxgbGyMzM1PdYTE1SEpKwsCBA9GzZ08cPXoU3333Hbp27Yp169YhPj4eAN9wlibZudyxYweaN2+O6OhoZGdnY9euXejcuTNWrlyp5gh11+vXr9GtWzeMGTMG165dw/Lly9GpUyf4+fkhMTFR4+8RtdnPP/+MCRMmoEOHDvjqq6/g7u4OPz8/+Pj44OnTpwA0/GEwlVOvX7+mJk2aUIsWLWjbtm20bds2atasGVlZWdH8+fOJiEgqlao3yAJIpVLat28fubq6kiAIJAgCnT17Vt1hFUlOTg6tW7eObG1tqW3btvT999+Tj48POTk5Ud26dTX6OLKysmjx4sVkZWVFbdu2pfXr19OuXbuoXbt2ZGFhQQcOHFB3iB8lu55v3LhBNjY2ZGJiQl5eXnT79m0iIsrNzVVneIVKS0ujUaNGkSAI1LZtWzp06BC9fv1a3WEVy/z58+mTTz6hoKAgev78ubrDKZKkpCQaPnw4CYJA7dq1o0OHDtHRo0fJ2NiYVq5cSUR5f9Os/NizZw9ZW1vTli1b6Pnz5xQWFkbDhw8nIyMj+u6779Qdns5q06YNdevWjSIiIoiIKDw8nIYOHUqCINCuXbsoMzNTzRHqnsDAQKpYsSIFBQXRy5cvKS4ujkaOHEnm5ubk4+Oj7vB0VmpqKrVo0YI6depEMTExYvny5cvJwsKCBg0apMboiqbcJla7d+8mfX192rdvn1gWFRVFAwcOJEEQ6NSpU2qMrnBPnz6lBg0akI2NDS1atIjq1atHzZo1o+zsbHWH9lHHjx+nGjVq0OjRo+nBgwdi+aVLl0gQBJo1a5bGHsfRo0fJ3d2dpk6dSo8ePRJvKB8/fkyCINCKFSs0MhEvyL59+6hLly60adMmEgSB5syZIx6Pph1DTk4OLV68mARBoLFjx9KbN28KvUY0LXaZ58+fU5UqVWjy5MkK5flpUvzv3r2j2rVrU40aNWjjxo0UGRlJRETPnj0ja2tr6tOnj8Ym4kx1Pv/8c6pXr55Cea9evcjKyop2795NRJxwl6abN2+SmZkZrV69Wq48MjKSOnbsSLVq1aKLFy+qKTrd1bZtW2rWrJlc2bt372jkyJEkCAIdPXqUiDTre1sXxMfHU6VKlWjRokVEJP9d8vXXX5OxsTH98ssvRKS5D4M1v/2PikRGRqJChQro3bs3ACA7OxtVq1bFzJkz4enpialTpyI2NlbNUSrS19fH559/jtOnT2Pu3Ln45ptvcPXqVQQGBqo7tI+6f/8+jIyMsGzZMtSpUwcAkJWVhRYtWsDLyws3b96Evr6+RlavW1paYujQoZgzZw5q164NPT09AHnt3m1tbeHs7KzxTQNksTk5OeHq1asYP348OnbsiO3btyMkJETN0RVMT08PXbt2RYsWLXDhwgVUqlQJ+vr6OHz4MEaOHIlZs2Zh+/btyMrK0timmBEREUhJScHEiRMB5DXrqV+/Prp164bevXtj165dADSnr4RUKoWpqSkCAwNx+PBhjBkzBtWqVQMAuLi4oFatWoiPj0d2drZGX++sdGVmZiIrKwtWVlZiWVZWFgBg7ty5cHFxga+vL3JycsTvR1ZydnZ2yMrKQoUKFQBAbIZbrVo1rFy5EtHR0QgICMDbt2/VGabOkEqlyMzMhLGxMfT19cXynJwcmJqaYtKkSXB3d8fkyZNBRBrzva2Njh49Cnd3d7m+a8nJyRAEATExMcjMzISenh5yc3MBABMnToSbmxv8/PyQkZGhuV0Y1JrWlQFZRvv+U4U1a9aQubk5hYSEEBHJPbH//fffycjIiJYsWVLgtmWlsNgzMjLE/3/48CF16dKFHB0d6e3bt2Ua34fkjz1//A8fPpRbTpR37tu1a0etWrWi9PT0sg20AIWd9/dduHCBGjRoQBYWFuTn50f//PMPJSQkyO1DHT4W/759+6hWrVpERHTr1i0SBIFGjBhB8fHxH9yuLBQWu6x27bvvvqMuXbqQIAhUq1YtMjc3J0EQqE+fPnTv3j25fZS1wmK/fv066evr08GDB2nbtm0kkUioX79+NGLECKpcuTIJgkDbt29XQ8T/Kco1L5VKKTc3l7755huytLQUr3V+Yqtb4uPj6dGjR+L3QX79+/cnV1dX8Xs8vzVr1pCxsTEtXryYiDT3abK2SU5OpsaNG1P79u3Fsvx/czNmzCBzc3M6ffq0OsLTamFhYTRlyhSaNGkSzZ07lx49eiQu69WrF9WpU4f++ecfIpK/nrds2UKCINCaNWsUlrGiCQ8PJ2dnZxIEgXr37i23rF27dtS0aVOKiopS2G7t2rVkbm5Oy5YtIyLN/P3R2cRK1idm69atcuWyD+HkyZNkZGREfn5+Ypnsj+PVq1c0YMAAsrW1VUvb5cJiL8zvv/9OJiYmNHPmTBVH9nHFjV2WeDVp0oQGDhwolqlDUWKXXSOzZs0iQRCoffv2NGLECBozZgxZWVmptf3vx+KXndfQ0FAyNzenly9fEhHRmDFjyMjIiH777TciymvuUNY+9vcaGRlJ/fr1I0EQqEOHDnT8+HGKjIyk6Oho+uGHH0gikVD//v3LPG6ij5/369evU6VKlWjYsGHUuHFjmjdvHqWkpBAR0d27d6lr165kY2NDYWFhZRk2ERX/75WIaN68eSQIAh0+fFiFkTF1mDNnDtWpU4fs7e3J0NCQZs+eLZdEHT16VOzXIyN7KPnixQtq1aoVNW7cmN68eVPmseuyGTNmkJ2dHQUHBxORfPOoJ0+eUKVKlWj69OlEpJk3mpomMzOTpk+fTiYmJvTpp59S7dq1SRAEqlGjBu3du5eI8h5ACoJA27ZtE3/3Zec9IiKCOnbsSC4uLty/TUlJSUlkZWVF9evXJ0dHR/r111/FZTt27CA9PT25rjqyc//8+XNq3LgxtWvXTny4p2l0MrE6f/481a9fnwRBoC5dutD9+/eJSPELx93dnZo0aSI+kci/PCgoiPT19Wnjxo0Fbqvu2POXxcbG0ujRo8nY2Fh8aq+OL9fixJ7fixcvqEKFCrR06VIiUk/7/KLGLnt98OBB+v333+nt27dima+vL0kkEvL39yeisn2KVZxzv2fPHnJ1dRUHgEhOTiZTU1Nq3749jRo1ir788ksx6dKk2IOCgmjkyJF06dIlhWVDhw4lS0tL8WZf0/5eW7ZsSRKJhCpVqkSXL1+WWxYcHEwVK1akKVOmEFHZXTfF/XuVxXXhwgUSBIH27NnzwfWZ9rh79y61bduWHB0dac6cObRkyRIaPXo0CYJAY8aMEfs1vnjxgjw9Pally5ZyNzWya8DPz4/Mzc3FBICVjtevX1PFihVpyJAh4u+j7O8xJSWFhg4dSk5OTuoMUWukpKTQnDlzqEaNGrR8+XJ6+PAh5ebm0unTp8nBwYFat25NaWlplJOTQ40bN6bWrVuLg4bkt2DBArKyshL7WrGik0ql9OLFC2rXrh0tXryY6tSpQ56enpSamkpEeX3XPT09ycvLS+4hjeyanzhxItnb29OzZ8/UEv/H6FxideXKFapbty5Vr16d+vfvT4Ig0PLly+U6vMu+mA4dOkSCINCiRYvEJmiyZQ8fPiRHR0caN25cmd3oFCX2wpw+fZqqVq2qUKVaVkoS+/nz50kQBDpx4kQZRKqoOLF/6Cby8ePHVKtWLWrcuLFcc01VK2r8stgvXLhApqam9OLFC3HZ4MGDSU9PjwwMDGj+/PniF5wmxC6LOykpiWJjY+W2l633999/kyAIcjXQmhC77Pvk+PHj4iiespop2ZPO2NhY6tatGzk5OZXZdVOSv9d79+6RtbU1TZo0iYg4sdJ2CQkJNHLkSKpVqxYdOHBArsb6iy++IFtbW7pw4QIR5f29/fzzzySRSOj//u//xOs7KyuLiPJ+NwVBEEdJ5SZSpWfhwoVka2srdtzP/wBy1qxZVLlyZXr69Km6wtMa4eHh5OLiQuPHj6fExES5ZePHjydbW1u6fv06EeXVnAiCQKtXrxb/LmTf27du3SKJREIHDx4kIv4eLK7Y2FgyNjamsLAwWrZsGZmZmYkDVmRkZFBgYCDp6enR0qVLxXMv+33cu3cvGRgYFNgkWRPoXGJ1//59MjIyEqtzW7duTbVr16ZLly4VuH737t3JwcGBjhw5QkTyX1b169en4cOHE1HZ/NEUN/b8caWmpopNdGRtrc+dO0eHDh2SW0+TYpfZsGED6evri82jcnJy6OnTp+KXmybHTiR/89C8eXNq1qxZmSZW78ffpk2bD8a/e/duqlOnDiUmJlJISAi1atWK9PT0yMLCgmrVqiXeRGnqNZ8/Ntm5f/PmDVlZWZVpc9jixi4bHnn8+PFERHJJTL9+/ahevXqUlJSk+sCpZNd8bGwsOTs7U8eOHSk5OVnVoTIVi4+PJ09PT/GGnei/RCkkJETuN4Uob/TcPn36kIODA4WEhMh9T1y5coWMjIxo06ZNZXcA5URGRgY1aNCAatWqpfCk3sfHhypXrqyxTaM0iVQqpS1btsiVya73PXv2kL6+vvjwKzExkfr06UN2dnb0xx9/yG0TGhpKgiBQYGBg2QSuQ3Jzcyk6Oprq1KlD58+fp1evXlGzZs3IxcVFTJZevXpFY8aMITMzM9qxY4e4rVQqpa+++ors7OzoxYsXGpnQ6lRiJUuK8j/VltWGTJ48WbxpyX8jHBkZSWZmZtSsWTO6efOmWP7333+ThYUFLViwQKNiL+gikh3PgwcPyN3dnRo2bEgLFiwgJycnsrGxUfmcPyWJnYioZ8+e1KJFCyLKa2qyc+dOatKkCbm7u1NcXJzGxv7+09gTJ06QgYEBTZ06VYURyytO/LJjOH36NBkaGlKPHj1IT0+PWrZsSefPn6c9e/aIN/5l0W68NM/9hg0bSBAE+vnnn1UY8X+U+a558eIFWVhYKNTO/vvvv1SzZk0aNmxYmfxIlMZ579OnD9WvX59SU1M18oeNFY3s8wwLCytwAJPg4GDS19en33//XW67f/75h6pWrUoeHh7itfz69WuaOXMmOTg4FNh0ipXclStXqGrVqtSwYUO6cOECPX/+nP766y9ycXGhadOm8d9iEckear3f7cDf35/09PTkpoN58eIFValSherXr0/Hjx8nIqLo6GiaOHEiOTs706tXr8oucB0SHx9Ppqam4sO8zZs3U8WKFWnMmDFERPT27Vt69eoVeXl5kaWlJf3vf/+j4OBg2rp1K1WvXl2j5xLT2sRq9+7dNH78eFq2bBmdP39eLM//xSL7oRgxYgRZWVkpPHGQ/VEFBARQtWrVyMXFhdatW0dbt26lnj17kpOTE929e1cjYy9IZGSkOMeCIAj0xRdfyDX30rTYpVIppaSkkL29PQ0aNIhOnTpFn3/+OQmCQN26dStwRBhNiT2/ly9f0pEjR6ht27ZUr149sc9eaSut+C9dukSNGjWiTz75hH766Sd68eKF+LfQsmVLGjt2bKknVqo6969evaKDBw9So0aNqG3btioZGbM0v2t2795N9vb2VLFiRRo7diwtWbKEPvvsM7K2tlZJU1hVnHepVEqLFi0iQRDEp4t8Q6dbZJ/n4cOHSRAE8UYz/+d89uxZqlGjBgmCQC1btqSOHTuSkZERzZgxgzIzM/maUJEzZ85QjRo1yMDAgGrWrEkWFhbk7u6ulsFvdIXsO3DKlClkZ2cn1mDJvrdPnDhB7u7uJAgCubm5UfPmzcnAwIAWLFhAOTk5fK0r4dmzZ+Tq6ir+3mRmZlLv3r2pUqVKNHDgQHJ3d6cbN27Qs2fPaPz48SQIAllZWZGxsTENHjy4zFp3KEPrEqtXr15R165dqUKFCuTu7k7W1tZkZGRE8+fPF6vB35/sNCoqiszMzKhPnz5iopGbm6vwI9GyZUuytLQkGxsbatSoUalPuleasb/vwoUL1K1bN5JIJNSkSZMiN2NTd+xPnjwhU1NTcnd3JzMzM6pTp06pDxurqtjPnj1LY8eOpX79+pG5uTk1btyYrl27Vqqxl2b8sqd0WVlZdP78efrnn3/EBEq2XWkPd6/Kc//111/T4MGDyczMjNzd3en27dsaG3v+75pLly5R165dycrKiipXrkxNmjSRS3o0LfaCrFmzhgRBkBu1ieme2bNnk7W1NSUkJBTY7/HJkyfk5+dHAwcOpG7dutGff/6prlDLlSdPnlBQUBB9//33cs2kWMl4eHhQ3759iUixNuvNmze0bNkyGjt2LA0cOFBhECJWPHFxcWRkZCR3nz1jxgwyNDQkPT09mjt3rlxrq7CwMAoJCREHaNNkWpdYBQYGUsWKFSkoKIhevnxJcXFxNHLkSDI3Ny+walD2A7B48WKSSCS0ZcsWuZuc/P+fnp5Or1+/VsnNsSpiz+/UqVNkaGhIP/30k1bFfubMGRIEgSpXrqx1sR85coRq1apF7dq1o23btqkkdlXFX1ZP2FR17vft20dmZmbk5eWlsuZ/qvyuyczMpISEBLpz545WxC4jS7RiYmIoICBAJbEz9ZN9zl27dqXmzZsXeX3GtFVsbCyZmJiIo/oS5V3XBc3nxkru6dOn5OrqSsHBwXT58mVq3bo16enpUe3atcnCwkLsp6mOUaJLSusSq7Zt21KzZs3kyt69e0cjRowgQRDEoS/f/6LPysqimjVrkpeXlzgJ3NOnT+X6Gaj6x0GVsROp9gIs7djzP4nYvHmzWPWubbE/ffpUq66bJ0+eKFw3qqTKc3/nzh2tuuZ15buGm73ojg9dhzk5OWRlZUXz5s0Ty+Li4ujMmTOUlpZGRHwtMN0he8h79uxZIsp7eLRjxw7y9PQs09/M8iIqKoqMjIzIzc2N9PX1qXnz5hQcHEyXLl2i+vXrU9WqVbU2qdWaxCo3N5cyMjKoa9eu1LJlS7Fc1jzhxo0b5OHhQTVq1FD4sn9/ePVZs2bR9u3byd3dnSZPnqzyCVE59oJjV/WIYqqMvSyGI1dl/LIbI22MXdXnnv9e1RM7KztSqVQuqTp48CCFhobKrXPz5k1xRMD09HS6fPmyOLeVbH5HxrSd7Htw+fLlZGVlRY8ePaKQkBDq3bs3GRgY0Keffio3XyUrHTk5OfTll19SrVq1aP369fT8+XPxN2jevHk0fPhwSkpK0srzrpGJVVhYGE2ZMoUmTZpEc+fOFZ+cEhH16tWL6tSpIw4QkP/HYcuWLSQIAq1Zs4aIFGtwsrOzydPTk/T09EgQBLK3txdHeeHYOXZ1xa7t8XPsHDvTHvk/73v37lHHjh1JEARasmSJ3E3M2rVrSU9Pj/bt20eLFi0iGxsbsrOzo99++00dYTOmUn369KGaNWvS2LFjydzcnGrXrs0TXatYVFQU3bt3T2F6mqLMp6jJNCqxyszMpOnTp5OJiQl9+umnVLt2bRIEgWrUqCHOt7Jv3z4SBIG2bdsm3izIfigiIiKoY8eO5OLiotAp/+bNmzR37lwyMzMjc3Nz+vHHHzl2jl2tsWt7/Bw7x860R/6EKiUlhcaNG0eCIFDTpk3FvnhE/yXhEyZMoAoVKlCNGjVIX1+f5s6dq5a4GVO19PR0cnNzI0EQyMLCQnzoxJgyNCaxSklJoTlz5lCNGjVo+fLl9PDhQ8rNzaVTp06Rg4MDtW7dmtLS0ignJ4caN25Mbdq0KXCuDD8/P7KyshL7EBDl3TRMnDiRBEGgESNGiBPRcuwcu7pi1/b4OXaOnWmH/HPYEeWN6Ghubk5Vq1alFStW0OPHjwvsa9WyZUsSBIGGDRvGfUyYzps5cybNmjVLofaEseLSmMQqPDycXFxcaPz48ZSYmCi3bPz48WRra0vXr18nIqIdO3aQIAi0evVqsd2/7MnrrVu3SCKR0MGDB4novyrF0NBQun//PsfOsWtE7NoeP8fOsTPtcvz4capbty4ZGxuTj48PhYaGFji9gqxm6+rVq+K1xJiu45EtWWnRmMRKKpXSli1b5MpkI8Xt2bOH9PX1xQnwEhMTqU+fPmRnZ6cwmWVoaCgJgkCBgYFlEzhx7EQcuzK0OX6OnWNn2iE3N5f+97//kSAI1LNnT/rrr7/EucwYY4yVLo1JrIj+e2r6fmdqf39/0tPTE2d/JyJ68eIFValSherXry92rI6OjqaJEyeSs7MzvXr1quwCJ46dY1eONsfPsXPsTDuEhIRQYGAgRUVFqTsUxhjTaRqVWL1PVjU7ZcoUsrOzE5/Mym4oTpw4Qe7u7iQIArm5uVHz5s3JwMCAFixYQDk5OWodppFj59iVoc3xc+wcO9NM7/ez4s+cMcZUQyAigob79NNPUb16dezbtw+5ubnQ09MTl719+xa//PILnj59iuTkZEyZMgXNmzdXY7TyOHb10ObYAe2On2NXD22OnTHGGNMJ6s7sPiY2NpZMTEzI399fLMvNzdWKGZk5dvXQ5tiJtDt+jl09tDl2xhhjTFdI1J3Yfcy9e/eQkZEBT09PAMCrV6/w22+/oWvXrnjz5o2ao/swjl09tDl2QLvj59jVQ5tjZ4wxxnSFxiZW9P9bKF67dg2WlpZwcHDA2bNn4ePjg9GjR4OIIJFIxPU0CceuHtocO6Dd8XPs6qHNsTPGGGO6Rl/dARRGEAQAwNWrV2FjYwN/f3/s3r0bdnZ2OHr0KDp37qzmCAvHsauHNscOaHf8HLt6aHPsjDHGmM4pu1aHxZeenk5ubm4kCAJZWFjQmjVr1B1SkXHs6qHNsRNpd/wcu3poc+yMMcaYLtH4UQFnzZoFQRCwYMECGBkZqTucYuHY1UObYwe0O36OXT20OXbGGGNMV2h8YiWVSiGRaGxXsA/i2NVDm2MHtDt+jl09tDl2xhhjTFdofGLFGGOMMcYYY5qOH3EyxhhjjDHGWAlxYsUYY4wxxhhjJcSJFWOMMcYYY4yVECdWjDHGGGNaJiAgAIIgICIiQqntR44cierVq5dqTGWppMdfkIiICAiCgICAgFLbZ3F1794dY8eOLbX9DRo0CAMGDCi1/bEP48SKMcYYY+XGhg0bIAgCvLy81B0KU5PffvsNP/74o7rDUHDp0iUEBwdj1qxZYlliYiKGDh0Ka2tr1KhRA7/88ovCdtevX4epqSnCw8MVls2aNQv79+/HnTt3VBo7y8OJFWOMMcbKjaCgIFSvXh2hoaF48uSJusNhalBYYuXs7Iz09HR8+eWXZR8UAH9/f3Ts2BG1atUSy6ZPn46zZ89iwYIF6NGjB8aOHYvLly+Ly4kIkydPxtSpU+Hi4qKwzyZNmuDTTz/FqlWryuQYyjtOrBhjjDFWLoSHh+Py5ctYvXo1bG1tERQUpO6Qyp13796pO4RCCYIAY2Nj6Onplfl7x8bG4ujRowrN9v78808sXboUkydPxrp169CmTRscOXJEXB4UFITIyEjMmTOn0H0PGDAABw4cQGpqqsriZ3k4sWKMMcZYuRAUFARra2t4e3ujX79+BSZWsn42K1euxJYtW1CzZk0YGRnB09MT165dk1t35MiRMDMzQ3R0NHr16gUzMzPY2tpi+vTpyM3NFdc7e/YsBEHA2bNnC3yv/H167t69i5EjR6JGjRowNjaGnZ0dRo8ejbi4OKWP+48//kCDBg1gbGyMBg0a4ODBgwWuJ5VK8eOPP6J+/fowNjZGlSpVMH78eCQkJCis5+fnBwcHB5iamqJ9+/a4f/8+qlevjpEjR4rryfpBnTt3Dj4+PqhcuTIcHR0BAJGRkfDx8UGdOnVgYmICGxsb9O/fv8A+U//++y86dOgAExMTODo6YtGiRZBKpQrrHTp0CN7e3nBwcICRkRFq1qyJH374Qe6zaNeuHY4ePYrIyEgIggBBEMS+ZoX1sTpz5gxat26NChUqwMrKCl988QXCwsLk1vHz84MgCHjy5AlGjhwJKysrWFpaYtSoUUhLSyvsoxEdPXoUOTk56NSpk1x5eno6rK2txdcVK1YU9/fu3TvMnj0bS5cuhZmZWaH77ty5M969e4eTJ09+NA5WMvrqDoAx9p+AgACMGjVKfG1kZISKFSuiYcOG8Pb2xqhRo2Bubl7s/V6+fBnBwcGYOnUqrKysSjFixhjTHkFBQejTpw8MDQ0xePBgbNy4EdeuXYOnp6fCur/99htSUlIwfvx4CIKAFStWoE+fPnj27BkMDAzE9XJzc9G1a1d4eXlh5cqVOHXqFFatWoWaNWtiwoQJxY7x5MmTePbsGUaNGgU7Ozv8+++/2LJlC/7991/8/fffEAShWPsLDg5G3759Ua9ePSxduhRxcXEYNWqUmODkN378ePF3aPLkyQgPD8dPP/2EW7du4dKlS+Jx+/r6YsWKFejZsye6du2KO3fuoGvXrsjIyCgwBh8fH9ja2uL7778Xa6yuXbuGy5cvY9CgQXB0dERERAQ2btyIdu3a4f79+zA1NQUAvHr1Cu3bt0dOTg5mz56NChUqYMuWLTAxMVF4n4CAAJiZmeHbb7+FmZkZzpw5g++//x7Jycnw9/cHAMydOxdJSUmIiorCmjVrAOCDScmpU6fw2WefoUaNGvDz80N6ejrWr1+Pli1b4ubNmwoDgAwYMAAuLi5YunQpbt68ia1bt6Jy5cpYvnz5Bz+ny5cvw8bGBs7OznLlnp6eWL16NerWrYtnz57h+PHj+PnnnwEAS5YsQdWqVT/adLFevXowMTHBpUuX0Lt37w+uy0qIGGMaY/v27QSAFi5cSDt27KBt27bRkiVLqEuXLiQIAjk7O9OdO3eKvV9/f38CQOHh4aUfNGOMaYHr168TADp58iQREUmlUnJ0dKQpU6bIrRceHk4AyMbGhuLj48XyQ4cOEQA6cuSIWDZixAjxOzu/Jk2akIeHh/g6JCSEAFBISEiB77V9+3axLC0tTSH2Xbt2EQA6f/68WCb7vfjY97qbmxvZ29tTYmKiWBYcHEwAyNnZWSy7cOECAaCgoCC57Y8fPy5X/urVK9LX16devXrJrefn50cAaMSIEQoxtmrVinJycuTWL+g4r1y5QgDo119/FcumTp1KAOjq1atiWWxsLFlaWiocf0H7HD9+PJmamlJGRoZY5u3tLXfsMgV9Hm5ublS5cmWKi4sTy+7cuUMSiYSGDx8uls2fP58A0OjRo+X22bt3b7KxsVF4r/e1atVK7pqRuXv3Ljk6OhIAAkB9+/al3NxcevbsGZmYmNCVK1c+um8iIldXV/rss8+KtC5THjcFZEwDffbZZxg2bBhGjRoFX19fnDhxAqdOnUJsbCw+//xzpKenqztExhjTKkFBQahSpQrat28PIK8/zcCBA7F79265pmIyAwcOlGuC1bp1awDAs2fPFNb9+uuv5V63bt26wPWKIn9NTEZGBt6+fYtmzZoBAG7evFmsfcXExOD27dsYMWIELC0txfLOnTujXr16cuvu3bsXlpaW6Ny5M96+fSv+8/DwgJmZGUJCQgAAp0+fRk5ODnx8fOS2nzRpUqFxjB07VqHfUv7jzM7ORlxcHGrVqgUrKyu54zx27BiaNWuGpk2bimW2trYYOnSowvvk32dKSgrevn2L1q1bIy0tDQ8ePCg0vsLIzt/IkSNRsWJFsbxRo0bo3Lkzjh07prBNQddCXFwckpOTP/hecXFxctebTMOGDfH48WNcu3YNjx8/xr59+yCRSPDdd9+hb9++aNasGQ4cOIDGjRvDxcUFCxcuBBEp7Mfa2hpv374t6qEzJXFixZiW6NChA+bNm4fIyEjs3LkTQNHa4vv5+WHGjBkAABcXF7FNef527Dt37oSHhwdMTExQsWJFDBo0CC9evCjT42OMMVXJzc3F7t270b59e4SHh+PJkyd48uQJvLy88Pr1a5w+fVphm2rVqsm9lt30vt/fyNjYGLa2tgrrvr9eUcXHx2PKlCmoUqUKTExMYGtrK472lpSUVKx9RUZGAgBq166tsKxOnTpyrx8/foykpCRUrlwZtra2cv9SU1MRGxsrt8/8I9cBeX1/CkoMABQ4Wl16ejq+//57ODk5wcjICJUqVYKtrS0SExPljjMyMrJI8QN5fbF69+4NS0tLWFhYwNbWFsOGDQNQ/HMne+/C3uuTTz7B27dvFQbjKOp1U5CCEiIg7xr79NNPxXN+5swZBAcHY9myZXj48CEGDRqEqVOnYtu2bdiwYUOB83ARUbGbkbLi4z5WjGmRL7/8EnPmzEFwcDDGjh1bpLb4ffr0waNHj7Br1y6sWbMGlSpVAgDxRmDx4sWYN28eBgwYgK+++gpv3rzB+vXr0aZNG9y6dYv7ZDHGtN6ZM2cQExOD3bt3Y/fu3QrLg4KC0KVLF7mywkaGe//mtygjyBV2Q1tQTdmAAQNw+fJlzJgxA25ubjAzM4NUKkW3bt0KHLChtEilUlSuXLnQkRLfTx6Lo6D+UJMmTcL27dsxdepUNG/eHJaWlhAEAYMGDVLqOBMTE9G2bVtYWFhg4cKFqFmzJoyNjXHz5k3MmjVLpecuv6JeN++zsbEpUvKVm5uLKVOmYPbs2ahatSp++OEHtGjRQuyfPX78eAQFBcn11wbyEruCElRWujixYkyLODo6wtLSEk+fPgWQ1yH4u+++k1unWbNmGDx4MC5evIjWrVujUaNGcHd3x65du9CrVy+5jraRkZGYP38+Fi1aJDdUa58+fdCkSRNs2LDhg0O4MsaYNggKCkLlypXxf//3fwrLDhw4gIMHD2LTpk0FJgClQVZrkZiYKFcuqxGRSUhIwOnTp7FgwQJ8//33Yvnjx4+Vel/ZQAgFbf/w4UO51zVr1sSpU6fQsmXLD54H2T6fPHkiVxMVFxdXrFq6ffv2YcSIEXLzK2VkZCicI2dn5yLFf/bsWcTFxeHAgQNo06aNWF7QpLlFrbmRHev77wUADx48QKVKlVChQoUi7etj6tati/379390vY0bNyIlJQXTp08HALx8+RIODg7icgcHB0RHR8ttk5OTgxcvXuDzzz8vlVhZ4bgpIGNaxszMDCkpKQBK3hb/wIEDkEqlGDBggFybejs7O9SuXVtsU88YY9oqPT0dBw4cQI8ePdCvXz+FfxMnTkRKSgoOHz6sshicnZ2hp6eH8+fPy5Vv2LBB7rWstuP92o2CJrMtCnt7e7i5uSEwMFCuKdzJkydx//59uXUHDBiA3Nxc/PDDDwr7ycnJEROejh07Ql9fHxs3bpRb56effipWbHp6egrHuX79eoVavO7du+Pvv/9GaGioWPbmzRuFmrWCzl1WVpbCOQaAChUqFKlpYP7zlz/hu3fvHoKDg9G9e/eP7qOomjdvjoSEhA/2zYuPj8f8+fPh7+8PY2NjAECVKlXk+o+FhYXBzs5Obrv79+8jIyMDLVq0KLV4WcG4xooxLZOamorKlSsDyPuSXbBgAXbv3i22f5cpyo/G48ePQUSFNg/IP6QwY4xpo8OHDyMlJaXQp/XNmjUTJwseOHCgSmKwtLRE//79sX79egiCgJo1a+LPP/9U+N62sLBAmzZtsGLFCmRnZ6Nq1aoIDg4usNalqJYuXQpvb2+0atUKo0ePRnx8PNavX4/69evLTRjbtm1bjB8/HkuXLsXt27fRpUsXGBgY4PHjx9i7dy/Wrl2Lfv36oUqVKpgyZQpWrVqFzz//HN26dcOdO3fw119/oVKlSkWuDerRowd27NgBS0tL1KtXD1euXMGpU6dgY2Mjt97MmTOxY8cOdOvWDVOmTBGHW3d2dsbdu3fF9Vq0aAFra2uMGDECkydPhiAI2LFjR4FN8Dw8PPD777/j22+/haenJ8zMzNCzZ88C4/T398dnn32G5s2bY8yYMeJw65aWlvDz8yvSsRaFt7c39PX1cerUKYwbN67AdebNm4eGDRuif//+Ylnfvn2xcOFCTJgwAc7Ozti8eTNWr14tt93JkydhamqKzp07l1q8rGCcWDGmRaKiopCUlCR2YC1pW3ypVApBEPDXX38V2C78Q3N7MMaYNggKCoKxsXGhN5USiQTe3t4ICgoq0SS8H7N+/XpkZ2dj06ZNMDIywoABA+Dv748GDRrIrffbb79h0qRJ+L//+z8QEbp06YK//vpLrrlXcXTr1g179+7F//73P/j6+qJmzZrYvn07Dh06pDBh8aZNm+Dh4YHNmzdjzpw50NfXR/Xq1TFs2DC0bNlSXG/58uUwNTXFzz//jFOnTqF58+YIDg5Gq1atxJqUj1m7di309PQQFBSEjIwMtGzZEqdOnULXrl3l1rO3t0dISAgmTZqEZcuWwcbGBl9//TUcHBwwZswYcT0bGxv8+eef+O677/C///0P1tbWGDZsGDp27KiwTx8fH9y+fRvbt2/HmjVr4OzsXGhi1alTJxw/fhzz58/H999/DwMDA7Rt2xbLly8vcFAOZVWpUgXdu3fHnj17Ckys/vnnH2zduhVXr16VK2/YsCG2b98OPz8/pKSkwMfHR2H7vXv3ok+fPkrNg8mKSU3DvDPGCiCb8+PatWsFLl+yZAkBoK1bt1J8fDwBoAULFsit8+jRIwJA8+fPF8tWrlxZ4HwnK1asIAD08OHD0j4Uxhhj5UhCQgIBoEWLFqk7FK11/vx5kkgk9OjRo1Lb561bt0gQBLp161ap7ZMVjvtYMaYlzpw5gx9++AEuLi4YOnRosdriyzrXvt8puE+fPtDT08OCBQsU9kNEKn16yxhjTDsVNJei7LenXbt2ZRuMDmndujW6dOmCFStWlNo+ly1bhn79+sHNza3U9skKx00BGdNAf/31Fx48eICcnBy8fv0aZ86cwcmTJ+Hs7IzDhw/D2NgYxsbGRW6L7+HhAQCYO3cuBg0aBAMDA/Ts2RM1a9bEokWL4Ovri4iICPTq1Qvm5uYIDw/HwYMHMW7cOHHkIcYYYwwAfv/9dwQEBKB79+4wMzPDxYsXsWvXLnTp0kWuySArvr/++qtU91fQ9AJMdTixYkwDyYbZNTQ0RMWKFdGwYUP8+OOPGDVqlFwb6aK2xff09MQPP/yATZs24fjx45BKpQgPD0eFChUwe/ZsuLq6Ys2aNViwYAEAwMnJCV26dOGhWRljjClo1KgR9PX1sWLFCiQnJ4sDWixatEjdoTGmVgK93/6HMcYYY4wxxlixcB8rxhhjjDHGGCshTqwYY4wxxhhjrIQ4sWKMMcYYY4yxEuLEijHGGGOMMcZKiBMrxhhjjDHGGCshTqwYY4wxxhhjrIQ4sWKMMcYYY4yxEuLEijHGGGOMMcZKiBMrxhhjjDHGGCshTqwYY4wxxhhjrIQ4sWKMMcYYY4yxEuLEijHGGGOMMcZKiBMrxhhjjDHGGCuh/wdAfruaZc12+QAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -62634,10 +32302,10 @@ "execution_count": 31, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:08:26.607365Z", - "iopub.status.busy": "2026-02-11T21:08:26.607365Z", - "iopub.status.idle": "2026-02-11T21:08:26.611357Z", - "shell.execute_reply": "2026-02-11T21:08:26.611357Z" + "iopub.execute_input": "2026-03-20T15:36:49.611718Z", + "iopub.status.busy": "2026-03-20T15:36:49.610907Z", + "iopub.status.idle": "2026-03-20T15:36:49.622914Z", + "shell.execute_reply": "2026-03-20T15:36:49.619735Z" } }, "outputs": [], @@ -62659,10 +32327,10 @@ "execution_count": 32, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:08:26.614776Z", - "iopub.status.busy": "2026-02-11T21:08:26.614776Z", - "iopub.status.idle": "2026-02-11T21:09:21.048064Z", - "shell.execute_reply": "2026-02-11T21:09:21.048064Z" + "iopub.execute_input": "2026-03-20T15:36:49.629556Z", + "iopub.status.busy": "2026-03-20T15:36:49.628553Z", + "iopub.status.idle": "2026-03-20T15:39:25.065032Z", + "shell.execute_reply": "2026-03-20T15:39:25.062151Z" } }, "outputs": [], @@ -62675,10 +32343,10 @@ "execution_count": 33, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:09:21.051410Z", - "iopub.status.busy": "2026-02-11T21:09:21.050411Z", - "iopub.status.idle": "2026-02-11T21:09:22.604868Z", - "shell.execute_reply": "2026-02-11T21:09:22.604868Z" + "iopub.execute_input": "2026-03-20T15:39:25.073917Z", + "iopub.status.busy": "2026-03-20T15:39:25.072963Z", + "iopub.status.idle": "2026-03-20T15:39:31.110810Z", + "shell.execute_reply": "2026-03-20T15:39:31.106718Z" } }, "outputs": [ @@ -62813,10 +32481,10 @@ "execution_count": 34, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:09:22.606878Z", - "iopub.status.busy": "2026-02-11T21:09:22.606878Z", - "iopub.status.idle": "2026-02-11T21:09:22.610884Z", - "shell.execute_reply": "2026-02-11T21:09:22.610884Z" + "iopub.execute_input": "2026-03-20T15:39:31.120834Z", + "iopub.status.busy": "2026-03-20T15:39:31.119736Z", + "iopub.status.idle": "2026-03-20T15:39:31.136387Z", + "shell.execute_reply": "2026-03-20T15:39:31.132879Z" } }, "outputs": [ @@ -62846,16 +32514,16 @@ "execution_count": 35, "metadata": { "execution": { - "iopub.execute_input": "2026-02-11T21:09:22.613401Z", - "iopub.status.busy": "2026-02-11T21:09:22.612418Z", - "iopub.status.idle": "2026-02-11T21:09:23.184578Z", - "shell.execute_reply": "2026-02-11T21:09:23.184578Z" + "iopub.execute_input": "2026-03-20T15:39:31.145052Z", + "iopub.status.busy": "2026-03-20T15:39:31.143642Z", + "iopub.status.idle": "2026-03-20T15:39:32.738885Z", + "shell.execute_reply": "2026-03-20T15:39:32.735873Z" } }, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2sAAALOCAYAAAA3E4t5AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3hUxfrA8e/2kt57IaH3KiJdmhQVFVFUBFSwglh/6r2AYMHeFazgRb0qqIhKF7iKYqGK9JqQQnrfzdbz+2PJkiUBEmrA9/M8eWBnz86Z03bPOzNnRqUoioIQQgghhBBCiAZFfb4LIIQQQgghhBCiJgnWhBBCCCGEEKIBkmBNCCGEEEIIIRogCdaEEEIIIYQQogGSYE0IIYQQQgghGiAJ1oQQQgghhBCiAZJgTQghhBBCCCEaIO35LoAQZ4rD4cDlcp3vYgghhBAXLY1Gg06nO9/FEOIfQ4I1ccErLS0lPz8fm812vosihBBCXPQMBgPh4eEEBgae76IIcdGTYE1c0EpLS8nMzMTf35/w8HB0Oh0qlep8F0sIIYS46CiKgsPhoKSkhMzMTAAJ2IQ4y1SKoijnuxBCnKr9+/ej0+mIj4+XIE0IIYQ4BxRFISMjA4fDQUpKyvkujhAXNRlgRFywHA4HNpuNoKAgCdSEEEKIc0SlUhEUFITNZsPhcJzv4ghxUZNgTVywqgYTkQedhRBCiHOr6rdXBvYS4uySYE1c8KRVTQghhDi35LdXiHNDgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSHEeZOcnMzYsWPPaJ5jx44lOTn5jOZ5MXjyySel25IQQghxgZFgTYgGau7cuahUKu+f0WgkNjaWQYMG8cYbb1BWVna+i3jeZGVl8eSTT7J58+bzXRSvhlgmIYQQQlzYZFJsIRq4GTNm0KhRIxwOB4cPH2bNmjVMnjyZV155hUWLFtG2bdvzXcRzLisri+nTp5OcnEz79u193nv//fdxu90NqkxCCCGEEKdCgjUhGrjBgwfTuXNn7+vHH3+cVatWMWzYMK666ip27NiByWQ6Z+VRFIXKyspzus76uFCmcrBYLJjN5vNdDCGEEEI0YNINUogL0OWXX86UKVNIS0vjk08+8Xlv586djBgxgtDQUIxGI507d2bRokU18vjrr7/o3bs3JpOJ+Ph4nn76aebMmYNKpeLgwYPe5ZKTkxk2bBjLli2jc+fOmEwm3n33XQDmzJnD5ZdfTmRkJAaDgZYtWzJr1qwa61IUhaeffpr4+HjMZjN9+/Zl27ZtNZYrLCzk4Ycfpk2bNvj7+xMYGMjgwYPZsmWLd5k1a9bQpUsXAMaNG+ftJjp37lyg9mfWKioqeOihh0hISMBgMNCsWTNeeuklFEXxWU6lUnHfffexcOFCWrdujcFgoFWrVixduvT4B6MOZerTpw+tW7dmw4YN9OrVC7PZzBNPPAGAzWZj2rRpNG7cGIPBQEJCAo8++ig2m+2Uy7Z27Vq6dOmC0WgkNTXVe7yEEEIIcWGRljUhLlCjR4/miSeeYPny5YwfPx6Abdu20b17d+Li4njsscfw8/Pjyy+/ZPjw4Xz11Vdcc801AGRmZtK3b19UKhWPP/44fn5+fPDBBxgMhlrXtWvXLkaNGsWdd97J+PHjadasGQCzZs2iVatWXHXVVWi1Wr777jvuuece3G439957r/fzU6dO5emnn2bIkCEMGTKEjRs3MnDgQOx2u8969u/fz8KFC7n++utp1KgROTk5vPvuu/Tu3Zvt27cTGxtLixYtmDFjBlOnTmXChAn07NkTgMsuu6zWsiuKwlVXXcXq1au5/fbbad++PcuWLeORRx4hMzOTV1991Wf5tWvX8vXXX3PPPfcQEBDAG2+8wXXXXUd6ejphYWG1rqMuZSooKGDw4MHceOON3HLLLURFReF2u7nqqqtYu3YtEyZMoEWLFmzdupVXX32V3bt3s3DhwnqXbevWrQwcOJCIiAiefPJJnE4n06ZNIyoqqtayCyGEEKIBU4S4QFmtVmX79u2K1Wqt8V6FvULZkLWhQfxV2CtOafvmzJmjAMqff/553GWCgoKUDh06eF/369dPadOmjVJZWelNc7vdymWXXaY0adLEmzZx4kRFpVIpmzZt8qYVFBQooaGhCqAcOHDAm56UlKQAytKlS2us32Kx1EgbNGiQkpKS4n2dm5ur6PV6ZejQoYrb7famP/HEEwqgjBkzxptWWVmpuFwun/wOHDigGAwGZcaMGd60P//8UwGUOXPm1Fj/mDFjlKSkJO/rhQsXKoDy9NNP+yw3YsQIRaVSKXv37vWmAYper/dJ27JliwIob775Zo11VXeiMvXu3VsBlNmzZ/ukz5s3T1Gr1crPP//skz579mwFUH755Zd6l2348OGK0WhU0tLSvGnbt29XNBqNIl/5Qogz5US/wUKIM0da1sRFaWf+Tjq91+l8FwOADRM20DGm41nJ29/f3zsqZGFhIatWrWLGjBmUlZX5jBY5aNAgpk2bRmZmJnFxcSxdupRu3br5DIQRGhrKzTffzJtvvlljPY0aNWLQoEE10qs/t1ZSUoLD4aB3794sW7aMkpISgoKCWLlyJXa7nYkTJ/oMHT958mSeffZZn/yqt+y5XC6Ki4vx9/enWbNmbNy4sf47CFi8eDEajYZJkyb5pD/00EMsWLCAJUuWcN9993nT+/fvT2pqqvd127ZtCQwMZP/+/ae0/ioGg4Fx48b5pM2fP58WLVrQvHlz8vPzvemXX345AKtXr/ZpnTtZ2VwuF8uWLWP48OEkJiZ6l2vRogWDBg1i8eLFp7UNQgghhDi3JFgTF6Xm4c3ZMGHD+S4G4CnL2VJeXk5kZCQAe/fuRVEUpkyZwpQpU2pdPjc3l7i4ONLS0ujWrVuN9xs3blzr5xo1alRr+i+//MK0adNYt24dFovF572qYC0tLQ2AJk2a+LwfERFBSEiIT5rb7eb111/nnXfe4cCBA7hcLu97x+uCeDJpaWnExsYSEBDgk96iRQvv+9VVD3KqhISEUFRUdErrrxIXF4der/dJ27NnDzt27CAiIqLWz+Tm5tarbHl5eVit1hr7GqBZs2YSrAkhhBAXGAnWxEXJrDOftdashiIjI4OSkhJvgFU1XP3DDz9caysYHD8YO5naRn7ct28f/fr1o3nz5rzyyiskJCSg1+tZvHgxr7766ikNn//ss88yZcoUbrvtNp566ilCQ0NRq9VMnjz5nA3Hr9Foak1XjhmMpL5q24dut5s2bdrwyiuv1PqZhISEc1I2IYQQQjRMEqwJcYGaN28egDcwS0lJATxD1/fv3/+En01KSmLv3r010mtLO57vvvsOm83GokWLfFp8Vq9eXWNd4GlFqiojeFqBjm2tWrBgAX379uXDDz/0SS8uLiY8PNz7unp3ypNJSkpi5cqVlJWV+bSu7dy506d8p6s+ZaqSmprKli1b6Nev3yl9/lgRERGYTCb27NlT471du3addv5CCCGEOLdk6H4hLkCrVq3iqaeeolGjRtx8880AREZG0qdPH959912ys7NrfCYvL8/7/0GDBrFu3To2b97sTSssLOTTTz+tcxmqWnmqt+qUlJQwZ84cn+X69++PTqfjzTff9Fn2tddeqzXPY1uJ5s+fT2Zmpk+an58f4AniTmbIkCG4XC7eeustn/RXX30VlUrF4MGDT5pHXdSnTFVGjhxJZmYm77//fo33rFYrFRUV9SqDRqNh0KBBLFy4kPT0dG/6jh07WLZsWb3yEkIIIcT5Jy1rQjRwS5YsYefOnTidTnJycli1ahUrVqwgKSmJRYsWYTQavcu+/fbb9OjRgzZt2jB+/HhSUlLIyclh3bp1ZGRkeOcre/TRR/nkk08YMGAAEydO9A7dn5iYSGFhYZ1aeQYOHIher+fKK6/kzjvvpLy8nPfff5/IyEifYDEiIoKHH36YmTNnMmzYMIYMGcKmTZtYsmSJT2sZwLBhw5gxYwbjxo3jsssuY+vWrXz66ac+LXLgaZEKDg5m9uzZBAQE4OfnR9euXWt9tu7KK6+kb9++/Otf/+LgwYO0a9eO5cuX8+233zJ58mSfATtOR33KVGX06NF8+eWX3HXXXaxevZru3bvjcrnYuXMnX375pXduu/qYPn06S5cupWfPntxzzz04nU7efPNNWrVqxV9//XW6mymEEEKIc+l8DkUpxOm42IcNrhq6v+pPr9cr0dHRyoABA5TXX39dKS0trfVz+/btU2699VYlOjpa0el0SlxcnDJs2DBlwYIFPstt2rRJ6dmzp2IwGJT4+Hhl5syZyhtvvKEAyuHDh73LJSUlKUOHDq11XYsWLVLatm2rGI1GJTk5WXn++eeVjz76qMbw/y6XS5k+fboSExOjmEwmpU+fPsrff/+tJCUl1Ri6/6GHHvIu1717d2XdunVK7969ld69e/us+9tvv1VatmypaLVanyHzjx26X1EUpaysTHnggQeU2NhYRafTKU2aNFFefPFFn6kEFMUzPP69995bYzuPLefxHK9MvXv3Vlq1alXrZ+x2u/L8888rrVq1UgwGgxISEqJ06tRJmT59ulJSUnJKZfvf//6ndOrUSdHr9UpKSooye/ZsZdq0aTJ0vxDijLnYf4OFaChUiiJPposLU2VlJQcOHKBRo0Y+rUvi1E2ePJl3332X8vLy4w5mIYQQQshvsBDnhjyzJsQ/lNVq9XldUFDAvHnz6NGjhwRqQgghhBANgDyzJsQ/VLdu3ejTpw8tWrQgJyeHDz/8kNLS0uPO0SaEEEIIIc4tCdaE+IcaMmQICxYs4L333kOlUtGxY0c+/PBDevXqdb6LJoQQQgghAHlmTVywpL+8EEIIcX7Ib7AQ54Y8syaEEEIIIYQQDZAEa0IIIYQQQgjRAEmwJoQQQgghhBANkARrQgghhBBCCNEASbAmhBBCCCGEEA2QBGtCCCGEEEII0QBJsCaEEEIIIYQQDZAEa0KI8yY5OZmxY8ee0TzHjh1LcnLyGc1TnFtn47wQ/1x9+vShT58+J11uzZo1qFQq1qxZc1bLo1KpePLJJ087nyeffBKVSkV+fv5Jl63tmtqzZw8DBw4kKCgIlUrFwoULT7tMQogzT4I1IRqouXPnolKpvH9Go5HY2FgGDRrEG2+8QVlZ2fku4nmTlZXFk08+yebNm893UWolwaK40H322We89tpr9f5cnz59OHjw4BkvjzjzxowZw9atW3nmmWeYN28enTt3PuXjLoQ4eyRYE6KBmzFjBvPmzWPWrFlMnDgRgMmTJ9OmTRv++uuv81y68yMrK4vp06fXGqy9//777Nq165yXadmyZTXSXC4XK1euPOdlEeJ01eem/aeffqKysrJG+o8//ojT6TzDJau/5cuXs3z58vNdjPNq165dvP/++97XVquVdevWcfvtt3Pfffdxyy23EB8fL8GaEA2QBGtCNHCDBw/mlltuYdy4cTz++OMsW7aMlStXkpuby1VXXYXVaj2n5VEU5Zyvsz50Oh0Gg+GcrrO8vJznn3+egQMHelsVtmzZQrdu3fjoo49QFOWclkeIc+nbb7+lQ4cO3u6DeXl53HzzzTz22GPk5OTUK6+KioozXj69Xo9erz/j+V5IDAYDOp3O+zovLw+A4ODg81QiIURdSbAmxAXo8ssvZ8qUKaSlpfHJJ5/4vLdz505GjBhBaGgoRqORzp07s2jRohp5/PXXX/Tu3RuTyUR8fDxPP/00c+bMQaVS+XRjSk5OZtiwYSxbtozOnTtjMpl49913AZgzZw6XX345kZGRGAwGWrZsyaxZs2qsS1EUnn76aeLj4zGbzfTt25dt27bVWK6wsJCHH36YNm3a4O/vT2BgIIMHD2bLli3eZdasWUOXLl0AGDdunLeb6Ny5c4Han1mrqKjgoYceIiEhAYPBQLNmzXjppZdqBFEqlYr77ruPhQsX0rp1awwGA61atWLp0qXHPxiAv78/q1at4t577+Waa64hOzubu+66i1deeYXPPvsMlUp13M8ePnyYcePGER8fj8FgICYmhquvvrpGV7IlS5bQs2dP/Pz8CAgIYOjQoTX24V9//cXYsWNJSUnBaDQSHR3NbbfdRkFBgc9yZWVlTJ48meTkZAwGA5GRkQwYMICNGzf6LDd//nw6deqEyWQiPDycW265hczMTJ9lxo4di7+/P5mZmQwfPhx/f38iIiJ4+OGHcblcPsu+9NJLXHbZZYSFhWEymejUqRMLFiw44b49Ebfbzeuvv06bNm0wGo1ERERwxRVXsH79eu8yTqeTp556itTUVAwGA8nJyTzxxBPYbDafvKrO8zVr1njP8zZt2ngDkK+//tq7nk6dOrFp06Za98P+/fsZNGgQfn5+xMbGMmPGjBrn2dk4HzMzM7ntttuIioryLvfRRx/5LFP1TNaXX37JM888Q3x8PEajkX79+rF3717vcn369OGHH34gLS3Ne32dqGvvyy+/zBdffMEzzzzDH3/8wU033cSAAQP4448/iIuLO+7nqrp6/+9//+Oee+4hMjKS+Ph47/t1Oefrcv3U9sxaRkYGw4cPx8/Pj8jISB544IEa5wQc//nJY/O02+1MnTqVTp06ERQUhJ+fHz179mT16tXH3f6TefPNN2nVqhVms5mQkBBvN8VjFRcXM3bsWIKDgwkKCmLcuHFYLJbjbseTTz5JUlISAI888oj3+Nb3uAshzg3t+S6AEOLUjB49mieeeILly5czfvx4ALZt20b37t2Ji4vjsccew8/Pjy+//JLhw4fz1Vdfcc011wCeG7u+ffuiUql4/PHH8fPz44MPPjhui9SuXbsYNWoUd955J+PHj6dZs2YAzJo1i1atWnHVVVeh1Wr57rvvuOeee3C73dx7773ez0+dOpWnn36aIUOGMGTIEDZu3MjAgQOx2+0+69m/fz8LFy7k+uuvp1GjRuTk5PDuu+/Su3dvtm/fTmxsLC1atGDGjBlMnTqVCRMm0LNnTwAuu+yyWsuuKApXXXUVq1ev5vbbb6d9+/YsW7aMRx55hMzMTF599VWf5deuXcvXX3/NPffcQ0BAAG+88QbXXXcd6enphIWFnfCYqNVqn8DsREFaleuuu45t27YxceJEkpOTyc3NZcWKFaSnp3tvlObNm8eYMWMYNGgQzz//PBaLhVmzZtGjRw82bdrkXW7FihXs37+fcePGER0dzbZt23jvvffYtm0bv/32m7c8d911FwsWLOC+++6jZcuWFBQUsHbtWnbs2EHHjh0Bz430uHHj6NKlCzNnziQnJ4fXX3+dX375hU2bNvnUyLtcLgYNGkTXrl156aWXWLlyJS+//DKpqancfffd3uVef/11rrrqKm6++Wbsdjuff/45119/Pd9//z1Dhw496b461u23387cuXMZPHgwd9xxB06nk59//pnffvuNzp07A3DHHXfw8ccfM2LECB566CF+//13Zs6cyY4dO/jmm2988tu7dy833XQTd955J7fccgsvvfQSV155JbNnz+aJJ57gnnvuAWDmzJmMHDmSXbt2oVYfrfN0uVxcccUVXHrppbzwwgssXbqUadOm4XQ6mTFjBnB2zsecnBwuvfRSb3AXERHBkiVLuP322yktLWXy5Mk+eT733HOo1WoefvhhSkpKeOGFF7j55pv5/fffAfjXv/5FSUkJGRkZ3vL4+/uf8FhUP/erbvTr6p577iEiIoKpU6d6W9bqes7X5fo5ltVqpV+/fqSnpzNp0iRiY2OZN28eq1atqnOZj1VaWsoHH3zAqFGjGD9+PGVlZXz44YcMGjSIP/74g/bt29crv/fff59JkyYxYsQI7r//fiorK/nrr7/4/fffuemmm3yWHTlyJI0aNWLmzJls3LiRDz74gMjISJ5//vla87722msJDg7mgQceYNSoUQwZMgR/f3/8/PzqfdyFEOeAIsQFymq1Ktu3b1esVmvNN20VipK5qWH82SpOafvmzJmjAMqff/553GWCgoKUDh06eF/369dPadOmjVJZWelNc7vdymWXXaY0adLEmzZx4kRFpVIpmzZt8qYVFBQooaGhCqAcOHDAm56UlKQAytKlS2us32Kx1EgbNGiQkpKS4n2dm5ur6PV6ZejQoYrb7famP/HEEwqgjBkzxptWWVmpuFwun/wOHDigGAwGZcaMGd60P//8UwGUOXPm1Fj/mDFjlKSkJO/rhQsXKoDy9NNP+yw3YsQIRaVSKXv37vWmAYper/dJ27JliwIob775Zo11VSkrK1MGDBigDBgwQNm/f7+SlJSkbN68WenSpYty0003+Wx3dUVFRQqgvPjiiyfMOzg4WBk/frxP+uHDh5WgoCCf9NqOx3//+18FUH766SdvWlBQkHLvvfced512u12JjIxUWrdu7XN9ff/99wqgTJ061Zs2ZswYBfA5PoqiKB06dFA6derkk3Zs+ex2u9K6dWvl8ssv90lPSkryOS9qs2rVKgVQJk2aVOO9qv29efNmBVDuuOMOn/cffvhhBVBWrVrls05A+fXXX71py5YtUwDFZDIpaWlp3vR3331XAZTVq1d706r2w8SJE33KMXToUEWv1yt5eXmKopyd8/H2229XYmJilPz8fJ88b7zxRiUoKMi731evXq0ASosWLRSbzeZd7vXXX1cAZevWrd60oUOH+lxHJ/LII48ozZs3V1avXq307t1b+eOPP5RRo0YpnTt3VjIyMo77uarvuB49eihOp9ObXtdzvi7Xj6IoSu/evZXevXt7X7/22msKoHz55ZfetIqKCqVx48Y1juvxzsVj83Q6nT77tKp8UVFRym233eaTDijTpk07YZmvvvpqpVWrVidcZtq0aQpQI/9rrrlGCQsL80k7djsOHDhQ676rz3E/4W+wEOKMkW6Q4uKUvxve690w/vJ3n7XN9Pf3944KWVhYyKpVqxg5ciRlZWXk5+eTn59PQUEBgwYNYs+ePd4ubEuXLqVbt24+tb2hoaHcfPPNta6nUaNGDBo0qEa6yWTy/r+kpIT8/Hx69+7N/v37KSkpAWDlypXY7XYmTpzoU9t+bG0/eJ6rqGqpcLlcFBQU4O/vT7NmzWp00aurxYsXo9FomDRpkk/6Qw89hKIoLFmyxCe9f//+pKamel+3bduWwMBA9u/ff9x1+Pv78+CDD7J8+XIaNWoEQLt27Vi3bh1jx449biuDyWRCr9ezZs0aioqKal1mxYoVFBcXM2rUKO8xzc/PR6PR0LVrV59uVtWPR2VlJfn5+Vx66aUAPvsvODiY33//naysrFrXuX79enJzc7nnnnswGo3e9KFDh9K8eXN++OGHGp+56667fF737Nmzxj6rXr6ioiJKSkro2bPnKR3br776CpVKxbRp02q8V7W/Fy9eDMCDDz7o8/5DDz0EUGM7WrZsSbdu3byvu3btCni6HScmJtZIr+2cuO+++3zKcd9992G3270DzZzp81FRFL766iuuvPJKFEXxOUcGDRpESUlJjf07btw4n2e4qlqnT3SOn8jQoUPZuHGjt1tgREQEn332Gc899xxRUVEn/fz48ePRaDTe13U95+ty/dRm8eLFxMTEMGLECG+a2WxmwoQJdc7jWBqNxrtP3W43hYWFOJ1OOnfufErnd3BwMBkZGfz5558nXba2a6+goIDS0tJ6r1cI0fBIN0hxcQpvChP+d75L4RHe9KxlXV5eTmRkJODpwqUoClOmTGHKlCm1Lp+bm0tcXBxpaWk+N6VVGjduXOvnqgKQY/3yyy9MmzaNdevW1XhGoqSkhKCgINLS0gBo0qSJz/sRERGEhIT4pFU9g/TOO+9w4MABn2eeTtYF8XjS0tKIjY0lICDAJ71Fixbe96urflNeJSQk5KQ3g1dccUWNNI1Gw4ABA477GYPBwPPPP89DDz1EVFQUl156KcOGDePWW28lOjoa8MyFBJ6AoTaBgYHe/xcWFjJ9+nQ+//xzcnNzfZarCp4BXnjhBcaMGUNCQgKdOnViyJAh3HrrraSkpABH90lVd9fqmjdvztq1a33Sqp4Xq662ffb999/z9NNPs3nzZp/ng+rTZa7Kvn37iI2NJTQ09LjLpKWloVara5zX0dHRBAcHn/TYBwUFAZCQkFBr+rHbp1arvfuwStOmnuu/6hmqM30+5uXlUVxczHvvvcd7771XY1mgxrlwbJ5V12F9Ap7qevfuXWt6v3796vT5Y79f6nrO1+X6qU1aWhqNGzeucd7Vdr7Xx8cff8zLL7/Mzp07cTgc3vTjfX+eyP/93/+xcuVKLrnkEho3bszAgQO56aab6N69e41lT3Q8q38/CCEuTBKsiYuT3gyx7c93Kc6qjIwMSkpKvDeibrcbgIcffrjWVjA4fjB2MtVbRKrs27ePfv360bx5c1555RUSEhLQ6/UsXryYV1991Vue+nj22WeZMmUKt912G0899RShoaGo1WomT558Svmdiuo1/NUp9RjRsT7zTE2ePJkrr7yShQsXsmzZMqZMmcLMmTNZtWoVHTp08G73vHnzar0B1WqPfo2PHDmSX3/9lUceeYT27dvj7++P2+3miiuu8Nl/I0eOpGfPnnzzzTcsX76cF198keeff56vv/6awYMH17nsVY63z6r7+eefueqqq+jVqxfvvPMOMTEx6HQ65syZU+ugCWdSXYPB423HmTgnTtXJ1l11XG+55RbGjBlT67Jt27atV56n41QmlD72+6U+5/zJrp/Tdbxzx+Vy+ezHTz75hLFjxzJ8+HAeeeQRIiMj0Wg0zJw5k3379tV7vS1atGDXrl18//33LF26lK+++op33nmHqVOnMn36dJ9lz+f5KYQ4+yRYE+ICNW/ePABvYFZVo6/T6ejfv/8JP5uUlOQz+luV2tKO57vvvsNms7Fo0SKfmt1jRz+rGnVsz549Pq0OeXl5NWryFyxYQN++ffnwww990ouLiwkPD/e+rk9LTFJSEitXrqSsrMynNWPnzp0+5TufUlNTeeihh3jooYfYs2cP7du35+WXX+aTTz7xdoGLjIw84XEtKirixx9/ZPr06UydOtWbXtVKcayYmBjuuece7rnnHnJzc+nYsSPPPPMMgwcP9u6TXbt21Wjd2LVr1ynts6+++gqj0ciyZct8BrKZM2dOvfMCzz5btmwZhYWFx21dS0pKwu12s2fPHm/LFXgG5CguLj7jx97tdrN//35vaxrA7t2ebtBVg12c6fMxIiKCgIAAXC7XSa/7+jiV1s4zpa7nfPXlj3f91CYpKYm///4bRVF8trO2+RlDQkIoLi6ukZ6WlubzfbZgwQJSUlL4+uuvffKsrZtuXfn5+XHDDTdwww03YLfbufbaa3nmmWd4/PHHfbonn0nn87gLIWonz6wJcQFatWoVTz31FI0aNfI+ZxYZGUmfPn149913yc7OrvGZqnl1wBPgrVu3zmdS6cLCQj799NM6l6GqNrd67W1JSUmNm+/+/fuj0+l48803fZatbeJVjUZTozZ4/vz5NYaL9/PzA6j1JupYQ4YMweVy8dZbb/mkv/rqq6hUqlNqSTpTLBZLjcmEU1NTCQgI8HYTHDRoEIGBgTz77LM+XauqVB3X2o4H1NzPLpfLp0skeM6d2NhY7zo7d+5MZGQks2fP9umuuGTJEnbs2HFKIzdqNBpUKpVP19aDBw+ycOHCeucFnlEAFUWp0coAR/fBkCFDgJr74JVXXgE4pe04mernmaIovPXWW+h0Om+XwDN9Pmo0Gq677jq++uor/v777xrvV7/u66NqZMDzoa7nfF2un9oMGTKErKwsn2kjLBZLrd1IU1NT+e2333xGrv3+++85dOiQz3K1XX+///4769atO9GmHtex023o9XpatmyJoii17pMz5XwedyFE7aRlTYgGbsmSJezcuROn00lOTg6rVq1ixYoVJCUlsWjRIp8a1rfffpsePXrQpk0bxo8fT0pKCjk5Oaxbt46MjAzvfGWPPvoon3zyCQMGDGDixIneofsTExMpLCysU+3qwIED0ev1XHnlldx5552Ul5fz/vvvExkZ6RMsVs25NXPmTIYNG8aQIUPYtGkTS5Ys8WktAxg2bBgzZsxg3LhxXHbZZWzdupVPP/20xnNAqampBAcHM3v2bAICAvDz86Nr1661Phty5ZVX0rdvX/71r39x8OBB2rVrx/Lly/n222+ZPHmyz+AN59ru3bvp168fI0eOpGXLlmi1Wr755htycnK48cYbAc/zObNmzWL06NF07NiRG2+8kYiICNLT0/nhhx/o3r07b731FoGBgfTq1YsXXngBh8NBXFwcy5cv58CBAz7rLCsrIz4+nhEjRtCuXTv8/f1ZuXIlf/75Jy+//DLgaZ19/vnnGTduHL1792bUqFHeofuTk5N54IEH6r2tQ4cO5ZVXXuGKK67gpptuIjc3l7fffpvGjRvz119/1Tu/vn37Mnr0aN544w327Nnj7er5888/07dvX+677z7atWvHmDFjeO+99yguLqZ379788ccffPzxxwwfPpy+ffvWe70nYjQaWbp0KWPGjKFr164sWbKEH374gSeeeML7TN/ZOB+fe+45Vq9eTdeuXRk/fjwtW7aksLCQjRs3snLlSgoLC+udZ6dOnfjiiy948MEH6dKlC/7+/lx55ZX1zudU1PWcr8v1U5vx48fz1ltvceutt7JhwwZiYmKYN28eZrO5xrJ33HEHCxYs4IorrmDkyJHs27fPp8W7yrBhw/j666+55pprGDp0KAcOHGD27Nm0bNmS8vLyeu+DgQMHEh0dTffu3YmKimLHjh289dZbDB06tMbzjmfS+TzuQojjOLeDTwpx5lzswwZXDWtd9afX65Xo6GhlwIAByuuvv66UlpbW+rl9+/Ypt956qxIdHa3odDolLi5OGTZsmLJgwQKf5TZt2qT07NlTMRgMSnx8vDJz5kzljTfeUADl8OHD3uWSkpKUoUOH1rquRYsWKW3btlWMRqOSnJysPP/888pHH31UY/h/l8ulTJ8+XYmJiVFMJpPSp08f5e+//64xnHRlZaXy0EMPeZfr3r27sm7duhrDZCuKonz77bdKy5YtFa1W6zOM/7FD9yuKZyjwBx54QImNjVV0Op3SpEkT5cUXX6wxpD5Q65D2dRlK/lTk5+cr9957r9K8eXPFz89PCQoKUrp27eozpHiV1atXK4MGDVKCgoIUo9GopKamKmPHjlXWr1/vXSYjI0O55pprlODgYCUoKEi5/vrrlaysLJ+hwm02m/LII48o7dq1UwICAhQ/Pz+lXbt2yjvvvFNjnV988YXSoUMHxWAwKKGhocrNN99cYyj2MWPGKH5+fjU+WzWseHUffvih0qRJE8VgMCjNmzdX5syZU+tydd3fTqdTefHFF5XmzZsrer1eiYiIUAYPHqxs2LDBu4zD4VCmT5+uNGrUSNHpdEpCQoLy+OOP+0xvUbXO2s7z2s6J2oY9r9oP+/btUwYOHKiYzWYlKipKmTZtWo3pKM7G+ZiTk6Pce++9SkJCgqLT6ZTo6GilX79+ynvvveddpmro/vnz59e6PdWnwigvL1duuukmJTg4WAHqPJx7fZxsepKTnfN1vX5q+/5IS0tTrrrqKsVsNivh4eHK/fffryxdurTG0P2Koigvv/yyEhcXpxgMBqV79+7K+vXra+TpdruVZ599VklKSlIMBoPSoUMH5fvvv6/1+6j69Xg87777rtKrVy8lLCxMMRgMSmpqqvLII48oJSUl3mWqrp2qaSGO3a/HTsFSl6H763PcL/bfYCEaCpWiyBOo4sJUWVnJgQMHaNSo0Vnrv/9PM3nyZN59913Ky8vrNGiEEMJj7NixLFiw4JRaUYS4EMlvsBDnhjyzJsQ/lNVq9XldUFDAvHnz6NGjhwRqQgghhBANgDyzJsQ/VLdu3ejTpw8tWrQgJyeHDz/8kNLS0uPO0SaEEEIIIc4tCdaE+IcaMmQICxYs4L333kOlUtGxY0c+/PBDevXqdb6LJoQQQgghAHlmTVywpL+8EEIIcX7Ib7AQ54Y8syaEEEIIIYQQDZAEa0IIIYQQQgjRAEmwJoQQQgghhBANkARrQgghhBBCCNEASbAmhBBCCCGEEA2QBGtCCCGEEEII0QBJsCaEEEIIIYQQDZAEa0KIWh08eBCVSsXcuXPr/dk1a9agUqlYs2bNSZf9888/ueyyy/Dz80OlUrF582aefPJJVCpV/QsthBBCCHER0Z7vAggh/rkcDgfXX389RqORV199FbPZTFJSUq3LPvvss7Rs2ZLhw4ef20IKIYQQQpwn0rImhDhv9u3bR1paGg8//DATJkzglltuISQkhH//+99YrVafZZ999lkWLlx4fgoqhBBCCHEeSMuaEOK8yc3NBSA4ONgnXavVotXK15MQQggh/tmkZU2IBqrqua3du3dzyy23EBQUREREBFOmTEFRFA4dOsTVV19NYGAg0dHRvPzyyzXyyM3N5fbbbycqKgqj0Ui7du34+OOPayxXXFzM2LFjCQoKIjg4mDFjxlBcXFxruXbu3MmIESMIDQ3FaDTSuXNnFi1aVO/tGzt2LL179wbg+uuvR6VS0adPH59tr6JSqaioqODjjz9GpVKhUqkYO3ZsvdcphBBCCHEhkaprIRq4G264gRYtWvDcc8/xww8/8PTTTxMaGsq7777L5ZdfzvPPP8+nn37Kww8/TJcuXejVqxcAVquVPn36sHfvXu677z4aNWrE/PnzGTt2LMXFxdx///0AKIrC1Vdfzdq1a7nrrrto0aIF33zzDWPGjKlRlm3bttG9e3fi4uJ47LHH8PPz48svv2T48OF89dVXXHPNNXXerjvvvJO4uDieffZZJk2aRJcuXYiKiqp12Xnz5nHHHXdwySWXMGHCBABSU1PruyuFEEIIIS4sihAXKKvVqmzfvl2xWq3nuyhnxbRp0xRAmTBhgjfN6XQq8fHxikqlUp577jlvelFRkWIymZQxY8Z401577TUFUD755BNvmt1uV7p166b4+/srpaWliqIoysKFCxVAeeGFF3zW07NnTwVQ5syZ403v16+f0qZNG6WystKb5na7lcsuu0xp0qSJN2316tUKoKxevfqE21i13Pz582vd9ur8/Px8tk8IIcT5c7H/BgvRUEjLmrgoWSwWdu7ceb6LAUDz5s0xm82n/Pk77rjD+3+NRkPnzp3JyMjg9ttv96YHBwfTrFkz9u/f701bvHgx0dHRjBo1ypum0+mYNGkSo0aN4n//+x/Dhg1j8eLFaLVa7r77bp/1TJw4kZ9//tmbVlhYyKpVq5gxYwZlZWWUlZV53xs0aBDTpk0jMzOTuLi4U95WIYQQQghxlARr4qK0c+dOOnXqdL6LAcCGDRvo2LHjKX8+MTHR53VQUBBGo5Hw8PAa6QUFBd7XaWlpNGnSBLXa99HUFi1aeN+v+jcmJgZ/f3+f5Zo1a+bzeu/evSiKwpQpU5gyZUqtZc3NzZVgTQghhBDiDJFgTVyUmjdvzoYNG853MQBPWU6HRqOpUxp4nj87W9xuNwAPP/wwgwYNqnWZxo0bn7X1CyGEEEL800iwJi5KZrP5tFqzLgZJSUn89ddfuN1un9a1qu6hVZNPJyUl8eOPP1JeXu7TurZr1y6f/FJSUgBPV8r+/fuf7eLXUH10SCGEEEKIfwIZul+Ii9SQIUM4fPgwX3zxhTfN6XTy5ptv4u/v7x02f8iQITidTmbNmuVdzuVy8eabb/rkFxkZSZ8+fXj33XfJzs6usb68vLyztCUefn5+x51OQAghhBDiYiQta0JcpCZMmMC7777L2LFj2bBhA8nJySxYsIBffvmF1157jYCAAACuvPJKunfvzmOPPcbBgwdp2bIlX3/9NSUlJTXyfPvtt+nRowdt2rRh/PjxpKSkkJOTw7p168jIyGDLli1nbXs6derEypUreeWVV4iNjaVRo0Z07dr1rK1PCCGEEOJ8k2BNiIuUyWRizZo1PPbYY3z88ceUlpbSrFkz5syZ4zOhtFqtZtGiRUyePJlPPvkElUrFVVddxcsvv0yHDh188mzZsiXr169n+vTpzJ07l4KCAiIjI+nQoQNTp049q9vzyiuvMGHCBP79739jtVoZM2aMBGtCCCGEuKiplLM5IoEQZ1FlZSUHDhygUaNGGI3G810cIYQQ4h9DfoOFODfkmTUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjVxwZPZJ4QQQohzS357hTg3JFgTFyydTodKpaKiouJ8F0UIIYT4R6moqEClUqHT6c53UYS4qGnPdwGEOFUajYagoCDy8vKw2WwEBgai1WpRqVTnu2hCCCHERUdRFJxOJ6WlpZSWlhIcHIxGoznfxRLioqZSpB1bXMAURaGkpITc3FxcLtf5Lo4QQghx0dNoNERGRhIUFCQVpEKcZRKsiYuCoii4XC6cTuf5LooQQghx0dJqtWg0GgnShDhHJFgTQgghhBBCiAZIBhgRQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkh7vgvwT+B2u8nKyiIgIACVSnW+iyOEEEIIIYQ4TxRFoaysjNjYWNTqE7edSbB2DmRlZZGQkHC+iyGEEEIIIYRoIA4dOkR8fPwJl5Fg7RwICAgAPAckMDDwPJdGCCGEEEIIcb6UlpaSkJDgjRFORIK1c6Cq62NgYKAEa0IIIYQQQog6PR4lA4wIIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDJMGaEEIIIYQQQjRAEqwJIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDJMGaEEIIIYQQQjRAEqwJIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDJMGaEEIIIYQQQjRAEqwJIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDdNEHa+Xl5UybNo0rrriC0NBQVCoVc+fOrfPni4uLmTBhAhEREfj5+dG3b182btx49goshBBCCCGEEPwDgrX8/HxmzJjBjh07aNeuXb0+63a7GTp0KJ999hn33XcfL7zwArm5ufTp04c9e/acpRILIYQQQgghBGjPdwHOtpiYGLKzs4mOjmb9+vV06dKlzp9dsGABv/76K/Pnz2fEiBEAjBw5kqZNmzJt2jQ+++yzs1VsIYQQQgghxD/cRd+yZjAYiI6OPqXPLliwgKioKK699lpvWkREBCNHjuTbb7/FZrOdqWIKIYQQQgghhI+LPlg7HZs2baJjx46o1b676ZJLLsFisbB79+7zVDIhhBBCCCHExU6CtRPIzs4mJiamRnpVWlZWVq2fs9lslJaW+vwJIYQQQgghRH1IsHYCVqsVg8FQI91oNHrfr83MmTMJCgry/iUkJJzVcgohhBBCCCEuPhKsnYDJZKr1ubTKykrv+7V5/PHHKSkp8f4dOnTorJZTCCGEEEIIcfG56EeDPB1VI0keqyotNja21s8ZDIZaW+SEEEIIIYQQoq6kZe0E2rdvz8aNG3G73T7pv//+O2azmaZNm56nkgkhhBBCCCEudhKsHZGdnc3OnTtxOBzetBEjRpCTk8PXX3/tTcvPz2f+/PlceeWV0nomhBBCCCGEOGv+Ed0g33rrLYqLi72jN3733XdkZGQAMHHiRIKCgnj88cf5+OOPOXDgAMnJyYAnWLv00ksZN24c27dvJzw8nHfeeQeXy8X06dPP1+YIIYQQQggh/gHqFaw1atQIlUpVrxWoVCr27dtXr8+caS+99BJpaWne119//bW3teyWW24hKCio1s9pNBoWL17MI488whtvvIHVaqVLly7MnTuXZs2anZOyCyGEEEIIIf6ZVIqiKHVdeOzYsTWCtfXr17Nt2zZatmzpDWB27drF9u3bad26NZ06dWLOnDlnttQXmNLSUoKCgigpKSEwMPB8F0cIIYQQQghxntQnNqhXy9rcuXN9Xi9cuJCFCxeyYsUK+vXr5/PeihUrGDlyJE899VR9ViGEEEIIIYQQgtMcYGTq1KlMnDixRqAGMGDAAO677z7+/e9/n84qhBBCCCGEEOIf6bSCtT179hAWFnbc98PCws7782pCCCGEEEIIcSE6rWAtNTWVOXPmUF5eXuO9srIyPvroI1JSUk5nFUIIIYQQQgjxj3RaQ/c//fTTjBgxgubNmzN27FgaN24MeFrcPv74Y3Jycpg/f/4ZKagQQgghhBBC/JPUazTI2ixfvpz/+7//Y8uWLT7p7du3Z+bMmQwaNOi0CngxkNEghRBCCCGEEFC/2OC0g7Uqhw8f9s5llpSURHR09JnI9qIgwZoQQgghhBACzuLQ/ScSHR0tAZoQQgghhBBCnCGnNcAIQHp6OnfddRfNmjUjNDSUn376CYD8/HwmTZrEpk2bTruQQgghhBBCCPFPc1ota9u3b6dnz5643W66du3K3r17cTqdAISHh7N27VoqKir48MMPz0hhhRBCCCGEEOKf4rSCtUcffZTg4GB+++03VCoVkZGRPu8PHTqUL7744rQKKIQQQgghhBD/RKfVDfKnn37i7rvvJiIiApVKVeP9xMREMjMzT2cVQgghhBBCCPGPdFrBmtvtxmw2H/f9vLw8DAbD6axCCCGEEEIIIf6RTitY69ixIz/88EOt7zmdTj7//HMuvfTSOuf3xRdfUFlZeTpFEkIIIYQQQoiLwmkFa48//jhLly7l7rvv5u+//wYgJyeHlStXMnDgQHbs2MFjjz1W5/xGjRpFdHQ0t99+O6tXrz6dogkhhBBCCCHEBe20J8WeN28e999/PyUlJSiKgkqlQlEUAgMDmTVrFqNGjapzXr/++iuffvop8+fPp6CggLi4OG666SZuueUWWrdufTrFPK9kUmwhhBBCCCEE1C82OO1gDaCiooIVK1awZ88e3G43qampDBo0iICAgFPKz+l0snTpUj799FO+++47rFYrbdq0YfTo0dx0003ExMScbpHPKQnWhBBCCCGEEHAegrWzqby8nG+++Ya5c+eyZs0a1Go1ffr0YcyYMYwcORK9Xn++i3hSEqwJIYQQQgghoH6xwWk9s5aSkkK3bt3YtWtXre9/++23pKSknM4q+Pvvv/njjz/YunUriqLQvHlzCgoKuPXWW0lNTWXt2rWnlb8QQgghhBBCNESnFawdPHiQjRs3cskll7Bw4cIa75eXl5OWllbvfHfv3s20adNo0qQJ3bt358svv+Smm25i/fr1bN26lY0bN/LHH38QGhrKXXfddTqbIIQQQgghhBAN0mkFawCvvPIKvXr14rrrrmPKlCmnldfrr7/OJZdcQosWLXjxxRfp2LEjixYtIisri9dee42OHTt6l+3cuTMPPvggO3fuPN1NEEIIIYQQQogG57SDtZCQEL777jumTZvGzJkzGTp0KCUlJaeU1wMPPIDBYGD27NlkZ2fzxRdfMHToUDQaTa3Ld+7c+bQDRCGEEEIIIYRoiLRnKqOpU6dyySWXcMstt9ClSxe++eabeuexb98+GjVqVOflW7VqRatWreq9HiGEEEIIIYRo6E67Za26K664gj///BM/Pz8uvfRSvv3223p9vj6BmhBCCCGEEEJczM5Yy1qVRo0asW7dOu68807mzZuHSqWq82dvu+22E76vUqkwGo3Ex8fTp08funXrdrrFFeKkMoospBdYSAwzEx9iPt/FEUIIIYQQ/xCnFaytXr2aFi1a1Eg3Go18/PHHjBw5kvz8/Drnt2rVKqxWK3l5eYDneTiAoqIiACIiInC73RQUFKBSqRg0aBALFizAbJYbaHH2pBdYsNhdpBdYJFgTQgghhBDnzGl1g+zduzeRkZHHfX/o0KGMGTOmzvktWbIEg8HAk08+SUFBgfcvPz+fadOmYTKZ+OWXXygqKmLKlCksXbpUBhgRZ11imBmzXkNimARqQgghhBDi3FEpiqLUdeH//Oc/AIwePRqVSuV9fcIVqFSMHj26Tvn369ePJk2aMHv27Frfv+uuu9i/fz/Lly8H4KabbuKXX345pbnczqX6zFIuhBBCCCGEuHjVJzaoVzfIsWPHolKpuPHGG9Hr9YwdO/akn6lPsPbbb78xYsSI477frl07PvnkE+/rnj178vXXX9cpbyGEEEIIIYS4kNQrWDtw4AAAer3e5/WZEhwczPLly7n77rtrfX/p0qUEBQV5X5eXl0tL1Rkig2gIIYQQQgjRsNQrWEtKSjrh69M1fvx4ZsyYwYgRI7j77rtp3LgxAHv37mXWrFl8//33Ps+oLV68mPbt25/RMvxTpRdYOFRoYVtWCYPbxEjAJoQQQgghxHl2xofuPx3Tpk3DarXy6quv1phUW6PR8OCDDzJt2jQAKisrGTt2LG3btj0fRb3o6LVq/sooJiHUzIaDRf+YVrb1BwvZlF5Eh8QQOieHnu/iXNSk9VYI8U9X/XsQkO9EIcRJ1WuAkcsvv7z+K1Cp+PHHH+v1mdzcXH788UfvwCFJSUn069fvhCNPNmQXwgAjv+7N51ChhdJKB5GBRvz0Wsx6DZc1Dj/fRTur3v9pH4eKrLhcbu7u21h+MM+iX/fmY7G76nVeSYAnhLiYVP8eBOr9nSiEuDictQFG3G53vSa5BqhrLGixWOjZsyfjx4/nrrvuYtSoUfVajzg1VTfDeq2ahFBzjdq+i12HxBAO5lf841oUz4fEMHO9zquMIgtLtmYTYNIByDFp4DKKLGw4WAQq6JQUIsdLiFokhnl+ayrsTuKCTd40IYQ4nnoFa2vWrDlLxQCz2cyBAwfqHQyKU1f9ZjgxxOxTs3e+brTOdUtK5+RQooOMpBdYyCu3yeTXZ1F8SP2O6Ya0IvblllNgsXFZaoQE0Q1ceoGF9EILABH+hlM+VhL0NQzSqn12xId4Kq0sdhd2p1t6GQghTuq0JsU+06644gqWLVt2vovxj5FeYCHQqKPM6jhvNXsZRRZ+3ZtPRpHnJm/DwSI2pBV5btbOkfgjgWqnpBCZ/LohUaC00kmJxUlWsZX0Asv5LpE4Ab1Wjc3pwt+oPa1raMPBItbuzefvjBI55udRVUDxTzoGx/4enU4e6w8WHjevxDAzZr0GvVZd5/VVDQK2ZGv2SZc/E9shhGg4ztgAI2VlZZSUlOB2u2u8l5iYWKc8pkyZwvXXX8/o0aO58847adSoESaTqcZyoaEyEMSZkBhmJq/MhvFI33k497V31W8I4kPMUNWweo4bWNcfLGTNrlw0ahV55TZAut2db52SQ9iTW0aASYteo0avVfPtpswG1+JyOtfMmbre6pLP2by2M4osbEovwulW2JtTRpu4oFNaR0aRhd05ZVQ6nOS6XOi1Dao+8R9Fr1Xz6758wvwN/5jWnGMD1PpcL1XX166cMsornVQ6XHRIDDlhT42tmSWUVzrJK7OddB2JYWZ+2ZtPQYWN//6RzqhLEo/7mRq/q0KIC9ppB2uzZs3ilVdeYf/+/cddxuVy1SmvVq1aAbB9+3Y+++yz085PnFhVd4y/MoqZtb+AHk0iyCiyEGDSkVdmO6s3dlV5V++/n1FkoVNSCBFHbg7OhaqyLN12mG1ZJVRUOunZNOK0unGJMyM+xMyNlyR6z5Vju9kB3u5yccEm7E73ebmp3HCwiPRCS51uuI51pm6qTpRP1TmeV27DT689KzdwVa30v+0vIC7EzKb0olMaXTW9wEJiqJlii502CcFkFlmxO/P/McFCQ2J3ujFoNWQVWVmyNfsfMaVL9d+jul4vVd12d+eW4W/Q8su+fMqtDgxaDbtzS2kZE1zjWfAV23P480ABpTYXLaID6lQ5GR9ipmlUAGv32rA73CcsV32fDxbin+JC7U58WsHa7Nmzuffeexk0aBC33XYb//rXv3jggQcwGo3MnTuXqKgoJk2aVOf8pk6dKs+snWN6rZo/DxYSbNazdk8eCaFmth4qpnFUAH6GM39jV/WcnNOteOd0A8+PGApc3SHunF5AVV1L9ueVU2yxY9RqOJhfzq5gk+diDjKC2wEuO7gcnj+1BjR60Bo8/8o5W2cZRRZWbMshv8JG32aR3ucFa/viPHaI612Hy8gtryQl3N9zU5Xm6S4XbNaRW1pJo3D/81OTfBqtwWfipiqjyBMoooLmMQE13q8K5FCgwub0Voycyf1UVf4RnRLIKLLQITHklPLRa9WUVjro0SSCIJPuvDxH2pB/zKs/z3e2KyhKrA725pZhc7pRVJ5KiYa2P8606s+TVdicdeoWX1WJZHe4yaiwoFOrqbC5KaiwU2HXY3cUEWzS4XS7vYMlFZTbKLE60WvVRAYY6JR04uul6pyMCzHRo3E4qE48KEl9nw8+2Xob4rVwtv2Tt/1idqG2Op9WsPbmm28yaNAglixZQkFBAf/6178YOnQol19+OY8++iidO3emoKCgzvk9+eSTp1MccQrsTjddkkM5VGjxtqzFh5opKLcR6qev9ebvdKQXWHC5FdYfLKRLcqinRjKnjIIKG5VO1xm/iayVoxLKsqA0i+Z5+9Hu2c09lkOY3AX4V5ZhyirDlF5K4KoKcNWhz7/eH0yhYA4Fcxj4RUBwAgQnQUgShCRDYDyoL94uXXUdFGL++kN8tyULvVbNzuxSEkPNHMy3oNWouLN3qk/wll5gocxSyd8ZOyjN2Enajl1YivKIap+IKl9L3OHDXGuz4KdxExuoRdlnx0+vgi0m0OpBYwCtEUzBYArxHBtzGATEeI6PrmYX61NRvTW4voNjnImbqvQCC34GLRU2p7f7VvU89Vo1S7dlk1tqo9zuIv7ICHRn8jqr2o5DhRVYKsrYc+AAxRk7aB1lItpfc7SiQ6U6WtGhNXqOgSkUdEbA833kcius3ZPHNR3j6ZQUwoptOewvKGdXThkDWkadMKg/E9u0Ia3I2xIJeEfLPTYwOhvzZR1vW6q3jqYXWii1OvhjfwHxoWZ+3ZdPk6iAM941OKPIQkKoHxlFFagU2J1bdm6+n8+zqu+e5jEBJ93WjCKLTyVSm7ggtmaU8Mv+fBS3QrHVTkywifwKGwEGraciNMKfPs0iKa10ACpvgLg1o8Rb0VHVKl29a2VWkRW9Tn3C7o9nWvVr4Xwc9zN9bdc1PxmJ+Nw4lwFx9ZHP4cIbgfW0grV9+/Zx7733AqDTeU5qu90OQFBQEHfccQfvvPMODz300CnlX1JSgr+/PxqN5uQLi1NSdcIOaxdLfIjZ+yUVH2o+K10B9+eV892WLAw6NTsOl2J1uCg4cgOSHOZ3Rmo7FLebwsz9pG1fz96/17Nn5zb27j+I1llO80AbLQLLaRWhITFIRahKRUd9EBXGaGx+4TgNcfxdqMJqCCAwJJKE6CgqFS06vZ5msWHkW93kl1qIMKsIMwAuG9jKwVoIlgLPX9EBOPA/KMs+WiidGSKaQ2RLiGwOkS08/w+IAZXqgq/FW7E9hyVbs/EzeL5SjrcNB/MrMGo15FfYaBUbxJ7DJbhKs4lTssn/aRXRpgJSyjLRVmTz0WebmPN7Me5jZv/4PEDFrGsj6N48CrfORKDejMFhBI0WXBooLfIcF2clOG1gLfYcH7fTNyP/KE9AHZpy9HhEtoCg+Hq1llYFKusPFvLJbwcpsTppHOlf5+vndI991c3l1swS1u7No2VsEOO6N/K+b3e6sdrdHCq0Yne6cDhchPnp63/j7aiE4jQozYRST2UHJRlQmkXGoTR6v7yFzBIHNidM72NgVG9D3fPW+YE5lAN/O/ns10JCw8PJjoqjV9eO5JhSOKRvQUahFafLXaM73ul0Q63VkfOtsNzuvWErszpqtNxWr6HNK7edkZvaY2t9q4L/9emFGLQa4oJM+Bu07M0rIzbIxK7DpdhdCjan29s12NOV1ES8oRJKPceH8hywFnmuhcpiz/9tZUeD6KreAyoNaA1UONUs/WArzRLCePDqbmSWmShTB3LYHkd8u/YQnOi5fi7CCqjqx7f669qkF1gotzmJ9DfSLCqAzsmhdE4OZUCrKDYcLKLQYifUT49eo/b2XKkaAdLudGOxu9h8qAiDRkXm4RxSA5wcKt1OZ5cf+cUl7DyQi0njZsfKdeQXl+FnNvHVL6EkRYbg5x+A0xiCOzie9u07EhcV6fNboteq2ZpR4u3FUJ9uyceed9R5Nt4z60y2gtQ1AKve+6fM6iCx8YX3e3yhqO34nq17IW8PE7gg5zQ8rWAtKCgIp9NzAxQYGIjZbObQoUPe9wMCAjh8+HC98ly/fj3//ve/+emnn7Db7SxfvpzLL7+c/Px8br/9dh544AH69OlzOsX+R3MrbtZ/fz9lQbGUBCWQZ1ORX24nsshIuL8RlUqF2mwnrdyOVW2kcLeRgnI7eWU2ogKNRASYUKFCpVLV+FetUh/3vap/V+7bS7nbQk6Zi+iwMA6WaiiyOHBrXazPPERgYDT+OcF1yrsk8yDpG9dxYOtm9u3Zx579mezJKiGzxIGj2mONoSY1qVFm7Oj4LLsci80BQEBwCHEt2tHu0h5MvP0G2jRO5Pf9hWzPKiGzyMrV7eNRgkzkFVpJDPXDHurH9n0FWA1u8vRaujeJ8JalVk4bFB+CooOQtxNyd0Dudtj2NTiOtNiZwyC2A4qxGX5BrThsaUd8cKsLrmtlfpkNl1uhwuaksNzOr3urPWdUWQL5e9m6biV88wP6jGyaqh0kbnIxs7UVPZ7j4d6vwuEXQ6VfPKWmGP7I2U6X1qmMHjkcV2A8hCYQFBTC/z3yKFf/ZyOdhg3mzZeeQ1Fr0WvVZBZZfVq0fL70g01gK4WKfE8QXZQGxeme4KNgL+z8Aexlno3RBxwJqFtCbHuI7QCRrTytdSewZlcuhwqtlFjtlFjsOF0KeeU29Bp1jRrz6s7UDUmhxUaJ1cGWQ0VkFB1tgdJr1Zj0ahJCTZgNWvwNWhKOBHg+63PaPTf15blQcshT6VC4HwqP/Fuahc9dm18EBMZBYBwH1SnsL1jPwzf3Z+P+Amb8/Bch182kXctmNIsNISo4ADQ6UJQjgbTd86/dUq2io5Al337CX+lFxBaVcuiPncz5aiUA39zoR5eWSVRWNMOd3xqad2KvM5LDhkYUWjwVhGdiUKKMIguFFXYqj4xqGWjUUWp10CExhMwiq08X0updWPPKbJRaHew+fHqtT1V5llgdvP/TPrQaNVlFVnZllxHubyAu2ITT5aZ5dCDOiiKaKQcJrDxEZEY24Zk52EvTae7II8iRB25btZxVYAz0tDAbgz3/GgI8LZxqnefYaHTgdoHLzv592Xy9PgvWZ9HEv5IbWqnQ2YrQHbLBhiNZagyeoC2i2ZHKjhYQ0QLCGp/0Wmnoqq7JFdtycLrdx712E8PM7DpcRn6F59qr/r1X1eJdZqlk798bMO3fxP6svewtzSE90Y9BqRp0lhx6lGejd5SgptrgbOshHOgP7Mp38eI7FScs7/P9DTza0x8CYggwxpBsiuOAM4xKSxhWYwo/u1vUq8tsVRfzSoeTQKPOO7hTVfB5rgZ4OlPP3h0bgOkjPKNw1vjdCDKQfeggyZUHoDSTLmGVqH/JYVd2NliLiDHYCKQcKktwOuy4nXa0ihO14gRU1Xp0GDwVtOZqPW7M4Z6KwJAkz3UTGH/BXyenq7bjW6/fQ1uZ5zfdWnSkEqrY83+HBVwOSioslJZbCDKqaK3WUWyDwAB/KA6Fzred1W0701RKXWetrkW/fv1ITk7mww8/BKB///4UFhby3Xff4Xa7GTZsGGq1mk2bNtUpv19//ZXLL7+cuLg4+vXrxwcffMDKlSu5/PLLAejTpw8xMTH897//PdUinxf1maX8bHNai3A+n4QRFT8edPDIahvBkSrUcVDSUuFvvZvKBhQnqFwQWwLR+Wr88lW486E0XyEz303ViNJqFSSGqIiMUGEKU+EOUrD7Q2mQQlaoQkn1690NlAKHgfQjf5l4bvQaA12BFE7pxq+uwasaFcmoaKWoaO+GDgq0d0PkkXxyVLBZrWaLRs1WtZq/NBry1Op6B8bV/3W5weFS0GvV6DWaEy5f37xVKhUWqwNzaTkJThuN3Haaq100Vuw0clUS6vIEY9d+YWHpPicpETqsLtif46B5iwAuvSGVgqBAcnUmXGoNMUFmbA43Pz++nMg20XQc14ms4koUVFhtLuwON3mr91G0dBfm+GAaje2CPdCETq1Bq1Hhp9eh06hRq9UEGDz/jw02n3gbgBB7BdGWIqItRURZCompKCCyogANCk6Vhhz/cLIDosgKiOZwYDT5fuEoai0qlYrMYit/Hig60o0PdBo1FTYXgUY9LrdCeICRELOey1IjKLE6KLI4CPMzEupnoNji4FChFZVKRVKYH6FmQ732/Z6ccuxOhcIK+5GRFBVig80MbBlNuL+RXYfLKCi3k19uJzbYRKLOTmDFYZKUQqJtefiXZuNXmo2pPAe1cvSG0aEzYw2MoTIgxvNvYCy2gGjs/lE4/MJAc7Scm3/fzF0j7uLpLz5CHRjMc6PHE5rShFFTHkerVtOzSQTRgeaTbs+DEx6kIL+Alz7+gDU7DmMuz2bOs8+SmXaIL/49mMaqLGJt6RQXFBL7SjkBBhUDWkcy/b6rMTXqRGBKZ5SQJFSqU7te1u0rYGNaMSqVisRQMxEBR0dC/HVvPha7y/scU1V31zKrgz8PFqJRq7kkJZTEELPP+/W5sV1/sJBN6UWsTyukvMJKcOHfhFjTaRpgJVmTS7SqiEBnIf62bPxdpd7PWTSB5GpjyNFEYzXFEBbbiDYtWh4JpmPBP9LzrG0dbd26lbZt29KiVWv27dnDG18so8wURZTRyYBYG9GuHE9lR/WKqPIjFbNqLYQ1geg2noqO2PYQ3RYM/nVe/9lS11r7quNwqMhKbmklOaWVTOiV6n3Guno+6fkVlGbvZ+fGn3Dmp1GSm0FZbia7D2ayL7uQtAIbtmqVh0FGFSWVCv1aRfLM7f0JiUtlXY4KmzaQUvxo0ySZ8PAoYiLC+HHTfrKys3hsws18/O0qgiIi+X79PhS7hYrSYpJNFWz+eSVLFy/lpYkjeOiqVlhy9+MqOIi27BAmeyEAbjQUmxKoDG5KbNOOnsA6tr2nZ0EtFYPfbsrk78wSDhRU0CjcD5vTjdXuosLupEV0IJ2SQs5a68TZ6Pr47v/2sTe3HLUKesW4IHMLpenb2L1jG4czD+G0ltEkyEWqv43kIIXkYDVJwWoCzEYshnDynH5UagIwBIaSmphAqWJmT4ENp0oHai3NYkMJNumOVkQ5Kz0Bg+VIRZS10BNUVK/wUqk9j0hU9ei4iCo76qLqGquqCKk67iVWh6dyMyGIzmH2o5WFJRlHenVU69lhK62ZsUrjCZQ1OirdamyKFkWlwaRVyCm2sDnDQsfkMOKn7zz3G32M+sQGpxWszZkzh9mzZ/PTTz9hMBj45Zdf6N+/v7crpE6n46uvvmLo0KF1yq9Pnz6UlJTw22+/UVZWRmRkpE+wNn36dD7++OMTjjzZEDWkYE1RFMqthajydvHK8y/w1HuLSA03sivHygv9DTzcw8yGylhmb3QSkdSY4MbtCWpxCYbwOBQUTDoNRp2aTskhKIqCguL91624a6Qd798FG9Ipq3Tib1BzTYdYft+6h+y0A5jz93Hgz03kZOWwL6OQvbmVVB7pvWbWQZMoEynxISQlxxLfNJWYVq0IbdUOrclc53UrisKe3FJW78zBrbjxc9nRHtjD7z/8xMEdB4lunMjA8dfSuVdbtmYUk1tWSUSAgVaxAYSY9SfN262461wOBYVDhRXszS0lwlVBB1URbSgiyZJLTGk2ZmclAGV6P7ICIsny9/xl+kdQavCr8zoyiy04XG60aogOMtavvFX/V9wEO6xE2cqJriwj2lZBtK2cCEsZw2flcUcHPXd30WNBzX6VgQydiRyjHwV+ARwymPj81b/BoKHT5E4UW+zsXnuI/C/2oDFpibq1KfZII/4GDQFGLRa7k4NPbyS4cwStRjWm0uGisMKGW1GwuZxoVODKspIz7yCOYjsBQ6PRdg7EpNficLnQqFU43W78DRpMejVatQq7yzMJLUe2R6tRoVFzwv2gV9w0dzpp63LRxuWkrctNU7cbDVAJbFerWGtVWLzfSVakmn0hKtx6FW7laD6goEJBo1EBCk6XpwyoQEX14+BZVjkDfY78FWiCmmaoMabD4e0K8UY1M3saCNd4uq65UTiAwi5c7MTNLtwcxM1hFDJRKDhSxjo5AHwMTATCgE3At8DtQEI9Cj4fsAK3VksrBN4BLsXT1ACE5EDRLGjVVs3Ov92M66rj/YGmI4srrMfFhmp/B+uzLdV4wvgj4Xy1wA5AUY5kqKhRH0lTqzz7tir4AxVqtRqDRoNGXXslQZQCqYpCilth/8/l5Kc7OJzr5EC+2+cmPyZITVyEhtAILX5ROhzhekqjjWSYdJSoNLjc4FLAqNUQ6mfAz6BFhQqHS8HhUjBoNRi0mjoFrxUZFfzx7z9o9mA7Dn62B5VWRfykttgUMBu0xAWbMem0Pp8LdDlJtFeQZLOSaCsnpbKM5Moy9IobN5Bl8Ge/KYgD5mAOmoJJNwfhUOtq2SfHL5f6mCC8vv9mFllxHqlMSQz1O27e6YUWnC7PICt/Z5Z6Klz0Km5qYiTJWYY6/zDh1kIydmcy8T+ZHC4/Wslh1EJ8iI6ESDOhEQH4RYZiDwkjpHEj9unDKHFrKdy6m6xFP2KvsHLZ+OuI6tyWfbnlxIeYCQ8w0j4hhLLCEp4YOpmQRgkUHTjEBz99wJ85lWQWV5JWYCHMz4DV7qZDQjC7Fy1l1SffcteUu7hq9FWoVCryy22UFhbTmHzsGfvwLzlEkjOHONth9JUlADgMAZSHNaY8vAnl4U2oiGiKwy+SvHI7fx4oZmtWMXqNBofTjV6rpazSQXyI55m71nE1e8DU9d8TnX/rDxSSVVxJVkklqREBtE8IJi7Er055e/JVUJVkoi7Yh6pgLz/9/BNTP1pBVkE52SUOLI6j36+hJhXxoSbMfn4UVLg5lF9K5ZGeNwAGsz+BEbEYQ6IJjIhhSPcO3H3rSLJdARwq9Iyk3SYhmMQjc7WelNPu6ZpclOap6Mjf4+ltc2xlR0RziGl/tGdHVGvvc70XotoC8Pd/2kdR1n50+TsY2EgLlny0FTnY8g8Q7com1J6F1lV5NBP/KE/lU1Dc0UqowDhPDw9TsG+PAZWKXYdyefY/P7B543oqDu0i78A2SvM9+zg2Npbdu3fj5+d37ndGNecsWKvN/v37+e6779BoNAwcOJCmTZvW+bN+fn7MnDmTSZMmUVBQQEREhE+w9sEHHzBp0iQslgtroseGFKxV9+yzz/Laa6+Rm5tLbGwsd918NVNvuIQxj77AFz/vwuVWcB75DYryV5MY7kdISBAxUZE0T0kgMT6BgNBIAoJCCAgMxmAyodLoPV+WioPU+Gj0Go6OpGgtYs7nC9m2ex9pWTlk5ZXQPVHLzF4KGjwR2b0/WPlws5NLU0No3iiOFs2b0bxtR5p36kNCyy6otWdmasBf9+azemcuxVY7PZpEcHX7OBRF4fOFPzDz6Rls3fgn7XsMoPWI+3GbwwgyaemQGHLGh69ef7CQWWv2YncpqIHOyaFHay0VxVN7nb0ZsjYf/dfqqS3FP8rzpR7W+MhfKgQleGrRTaE+z5PUqbbS7QZLPpQd9vyVH/Z04yzYCwV7oGA/OI50x1FpPLWCYY0pNSYQNOIVAEY/OA1Nq8GUVjppFRdEQoiJ8b1SAbj88suJioriv//9L7/uzff82O3cw4KXHmHv9r9oe809JPW+nt7NotiTU8bc+wYx/KZxfPbOiz4DdwBU2l1syy5Br9j5dvbzrF82n+ade/Dcq++gDwpn6d/ZuBWFYLPeu083HCzi78wScssq6dY43PsDW++aXHsFZP/lPR7Pzl3Mv77LADw3as2i/UhJiiU+pTmuqBaEtbiMTu070alRKJ//kc62rFJMOg2DWkVzdYc4lmzN5uuNhyi2OEmN9CfMX49Rq6HEYsdid9A6IYj4YBPdUsN8K0eclVB4EFXhfijYy9YNfxJDDuayNMKUYm9xu82xsavARanVxYBLmzPk5hvI1sVR6R/LQ0PbnXZlg6Io/L72d8aPGM/zX82jbasU/s4o4pmxd+PW6bn0wcdoGhPIzV0TT5rXtLunYbVYmTlnJgoKf2cWk1tayepPvuKPBd9x/YvTiGkUh/twFm/cNYVJ7z3N7o3bWDr7v9w2bTwjukRiyt1HVFkaceUZBNo9N6U2nZmi4EQKQxIoDE4gPziBMnMYikpVoxLH5nSTV2YlzF/PzuwSymwOSq0Ogv10BBm12J0ugvx07M8tQ69V43C5cCkKGhXY3W4cThc6jYrwAD0GrWd+QH+3jUsCHSQ6SwmxFBBqKSLMUkiYtQjDkZbnXItC1ItlpEbpSUjwxxAZhBITRq7Rn/JSJ5bDxVgPl1CZU4w1r8xbQa8P98eYFIZfSjh+zaIwhJoI9zeQEGpCQSG9oAKtVoWfXkNkgMG3AuY4/xYdLGLpw0vpPqMvNqeTDc+sJbxfMqZ+iWjUKiICDEQHGU56PNVuF4l2K00qy2lqq6CprYIUuxU9Ci4gTWdgl97ELp2RnXoju3VGLCpVvc8/n+viBJWGTpcbh8uNRu35ejz2fVwuomwuUnGToig0URQaA40VhcRq0X4hCrtV8PZvNj5bYafLNTqKQlUUhSgUGRUUNVRVvByttDmGDfge2IqnImIgUP0RwBxgVrXXU4DjNY4qwHJgHTAKaHbir7AoRUVHNHRGTWc0dEZD7JGV5+JmI26fyo70U6zsOGsUCEdFU9Q1/hqjxnSksJUoPPm7jReX2el+iQZNENgDoCgEDoe6KTapQaVCfSTYUxSgQgXFChQrKEWglChHXxe40TXX4X9rIIrCkYobFVq1Co26/j1SqgevwW6Fxi4nTZ1OmrsctHLYaeK0owMcwD6tnp16Izt0BnbqjezTGXGoNXWu3LA73dicVRXu2lMq56lUnOjcbnSFRUTby0lwWmhMJc9+sJd1eywUWz3XhUED7WO1tE4wEB1tRhsWgDE2nODUOEr8gykyBVLsgJwSGzanG1Bh1muJDjJhUqCiqIKijCLyDuaRn5ZP9p5s8g7mobgV1HotfomRRDaNJSApipDoENRlDuY+8dF5Hx+gPrHBGZsUu0pKSgr333//KX1Wp9PVOql2lczMTPz9z39XiouFoiioj9zQq9Vq3H5R0HkcG3Jf5rbxd/HaS8+zbtX3/PLzGrZs2UxhTjbFxSXsTc/hi5UbvS1exzPxEj1vDD5aG5RX4ea2l8qJD9aTEhVAZFgIL/8vDVdMf16e+gAExlK6+1kuMWWz5qefzuKWe/pKxwab0OvUxB0ZHU+lUjHqmmHcOHwoM157nzdmTmPHEzfSe+wjmC65gsIKO+/9tI8Ao47WsUEEmXSn3VVjU3oROo2a9IJyUiP98Tdqj/bfVqmOjCaZBC2v9qQpiqc7QFXglr8bDv0Omz8Dp/VoxioN+IWDIRC0RiLRYnRqABU2PRhULs+AG26nJ5C2V0BF7jGDcKg8AWF4E4jrBG1vOBIUNvGUSeN5UNtVVAS8gk6n44u3ZnLb0yn4xbUiu9hCo3A/7zM8drsdg8Hg3f95ZTYuaduc21es4pFHH+Pr/7xJyf4tOG/4PwKCQ3A7bKTGhPo8GF7VxWzJ1mz0Wg1BxkAGTvg37XoMYMFr/2bslb1488036duqD99uymJ7dj4ZRVbPzYwKiq0O3IrCur35WBNDvH3m6/XMmN4Pkrp5/oDKzVOJ/vM9Zs18jHX/+5FdO7ax90AG36/bg8P9HQBJwWqaxwaQEBlMakIMHdq2RGeN5svftBTb1bRwaCiyKyRjIrZSi8rtwGZ3YNS4cG6y0TjCjW5HyZFAOsfz3J0l31ukH9O19J9TSPvkUMYO701g065U+CURENecvM9uYNydw+jWrRs33HADqti9NL5mGAaNls/WldV78IHa5AbnAnB9h+40atSI1pEWyh+byfT7biEws5yOHfoR71dzJMdjhRpDsavt9EvpB0DzEE8gfdsrQ+i5tiN/zvmBof/3NqHqIACuaTsEXZ8J5O0o5L8vfc4l/13K0OHtSS+wEBBmJlBXDtlbMGRtJjp7M9HZW2D3Cs/KdH4QlnK0siOkEZmhSfy+rwT/qCQO2oNRAt3kl9kJCdWh1ahxKwoBBi2KAlddGsjunFJyS8pJNFSgKc/BVJmHwZ1LY2M5Uc48/EvSCbamE+wu8m6jyxyJJqIJ5REdydYn4B/XnPCkVjgsOngxlVZjXyayZVcCjFpig0yUVjqJCTJSYXN6R320Wq38umEr27ZtY/XPv5C1azPZX21CcbuJTGlBdLd+BF7anyJDJE30GppHBzKqa91HEfzrr79YylJeveJ5unTpwiPOabzy/DPcPuRFEhu3oE1sEFd3iKvvaeLhtEPudjTZm0nJ2kxK9hYG52zzdCFDBeFNIaad57nRsMYQmuoZBEhfs+wnqmg57mid/irPdVRSVRG1DyV/L6NeXsEv+4rZUqqgi1XTo52Zbh0boY9MpTKsMR8VB5GjSyAgtjn3DevKpcCa554j8PcXeWXmLp/1VM3RZtZrvIPP+Bu1hJh0FFhshPjp6JgYTOwMI7NnzeaByQ/QI3AQXcY9jtWtwa24iYjP5ClupNOwG3CVFjDv7rnEBpu8wd/irVlkFFowG9SkRvgRfZueqfdO4ufvfubdWz/DFJPoGWXZ7qTc5iDUX3/kRl1Fh8QQn0CyRFEor8jFkLsTU+4OLsvbRe/DOzDZPOdtucafg/oE9ukTKAhKoTw0hRx1CI1jgmgeHXjc4HlrZjG5pVb25ZXRKMKPCH8DLWNrX74qyN6eXUJ+WSVphRWEaB20NVZA3iEibXmkqkpIopiAshz0jqOV9hWmUEoDIin1i2CrfySlfuEUB0RSbgphf/Ey9Gu/p81jT3K4tJKsYguKxU6gw0WkToVeq8asV1NidXj2e5iBTr2CCTbr+GVPHg63G61aRbfUUL59fj6Zafm08L+GJlEBNIn0825DQYmFcqebQJOWAKP2lCscClD4WXHzk6KgcTuJsRSRWJFPYkUhHSsKuLIkHw0KLlRkmQJJM4Vw0BzMQXMQ6cZAbGoNiqJQYXNQbnNiNqgx6TTklVWixYVGBUFG/ckrPdx1r7RTuV1EOm3EOSqJd9hIcFSS4LSR4LAT5XJ46yDKVGrS1FqW/FVBuzYmOrfyI9ugIT3XyaYMG+t3VOL6tQLIA/Z7HgMM1KIyqECrQtGA262AUwGHgmJxo1QerQhRGVRoo7ToYnX4dwpAFatFFalGpbaT695PDvtRFDfm8KB/1tD91bndbkpKSqitoS40tG43ApdeeikLFixg8uTJNd6rqKhgzpw59O7d+3SLKo5wu93eLj0ajQaXy4Xb7Wb//v3ccccd6M0B9B42Cl3zAZRuzsR2uJQgjZq2fnpSw/0IooLLIuyY3RbKSoqwV1pRXHYUlZqJU18mPy4F7nvN+/C6vcACLzXh3U+/YciQIQC8/fbb3HfffaR2H8499wym3Go/JwF5fIiZZtEBJNjNR7rGHaVSqbh97C1c2rsfH7w4lQXvTOOS7esIuu3fWNVGSq1Oiivs9G0eddoXfILJzg8bf6RTjyuICzbTLOokw0WrVEemBUiAFlceTXe7PdMRlGR6gq7yXKjI8zyA67RRVFhCUalnAA23yUxksN/RgQXUWk8f74Doo3/+0Z4WuiMB2YlUVbD8+8W3+WH+p8x98l5GzfiIgLhUTHqNd1S1wjILDk+Vs898RofLnHz18Wxe7dWbx++/i8PP3Uafu57Gaa8kJizIO+Fy6ZGRueJDzHRIDGHNrlz8jVp6REawza8nT81byuo5zzN69GgGD7ua+CsnolFpyS62sj+/HBTILrEAakLMOrZnlXgflq8+MXt9j6fT6cRoNDF87GSGj53svUlUOyz8tGoJGdt+J2vfDjLT09mw4TD5a9IwaH+nV7KOYU00XNlEQ6OQIz9nOUf+jnCptLhUWuxFwZT5R6MNisaU2NVzfAKiIKQRWdo4flmwErgTXUQqk1/7hibtD5Mw5E5aat0UFhUTHBzMiBEj+PDDDxk3bhw3R8Wi6XAtBwsq2Jldyt19Gp9WwFZ1DlRV/sSHmHny3pv59duP+f3zNxl+5ZV1mljZ7XZ786jKp2r5F155jVtHXkP6hpXsVnvSCivhknA/HnzqVe4bOYinHhxPv59+9raYfrvHQaGlMaFBLenU9l5PXhX5kL3F0/2oYJ/nhj39dyjL4p0fK3l2rd27fp0azDrVkS6MoFGDRgVuRfF0O3QrqFQq+iRruKm1jiFNtBh0WsrtYZRqw8lUR/OzriUV/smUBSTRqGk7YiMjuaxxOH9VewYuPCIc+4EDADSKCMTP38A1HeOJDjL6TLicW+rpFmQymQiOb0L3hCaMvHEUm9KLUDksZGz5lZVLf2DtN3P48dO3CEpoRvwlg+h9z+2n9T017OY7mf/F5/z00Uw+mL+Y5IjT+I7W6o9072oPnY6kuRyermDZWzwVUdlbYM8yz+BEVfwiwC/SUwnlHwmGQNTlbmLQoeiMEOZXbWRLJ19/twG9VkVky1DClSLaWnIwVuaBvdpzLioNjsBEDqli+GJTEZe0b0GHJm05cPAQDy//HdXKXVw1oiPPT5+AKlfLoQMFhLuM3u8Ji8WC3mDkUKHFZwqFYwefAc8gTAkhZiIDjT5d5iZNnERyUjI33ngjBUVl9L//JZIiw9DneqY9GjzidiLjkymtMNA65ug1enlTszcwNGm0OOwaFny+gB49evDYXZN5e/4KIk0R5DoriQjVkV1kJb3cRo8mETQJi6l5XCJaQPIx91dlh8nf/Ts7N/1MaMl2epZvJLRkOaSDEy0lxjjCElt6gumAaM8x8o8gx+VPVrmKXoHJ/FJYhsbgJtyp5ZrkKGL9tdUqCu2eZ7qOVEDt272Tz+esAIeFoclurkux4q/33KOUqoNxBKcQltjd04skLPVIMJ+Cn86EH1DLVpGxOJsfjWu4pukYDhVaOFBQTnZJJUatBpfbTViApwJxT04ZJRYH8YFmRrf2TCOTrPfMCVpVObsxdA+Zu34lXnsTQQ4DrQOiQAUHf1vCK088xuuf/UDjxqlnd7RBRyXkbEOTvZmE7M0kZG2mR9Y2z3mvUnt620Q055AugZLARNyhqbRt3ZYMm4n0ItupVTC73Z7jVH6ksrDkEBTug4J9FB/aycA3tpISqebO7noaR5pRhaZAWCqlfsn8XBGKIySVoNjmdGndjOSKCpgaQKfhz1IY1Zk4m4sgm5OIAD1J4X4E6dxkHTpERcFhItUVlBXmoFPsFJaUs/1QPi7UaPV6EiOCiYmKxKINIDg8kg6tm3NF19Ykhvl+N1Wv7DVpjzRNn2SewobotII1h8PB888/z0cffcShQ4eO2yrmcrlqTT/W9OnT6d27N0OHDmXUqFEAbNmyhf379/PSSy+Rl5fHlClTTqfIoprqN0ZqtRqXy0V2djZWq5XU1FTvcolhZrqlhqPXacgvt6FRwZ7ccppGBfCHVc/gNjE0OebiD3vnCxwaE4Q39qa5itMBfKZiuPfee9m3bx8TJ07EogumoLiU6Iiws7nZPtt1vJGmPF9mMTzw1Ot06TWAp/7vfnLSxzJhxiyspihCzXoq7M7Tnodu97oVfPvaY7ROjiYxtf+pf4Go1Z6RpoLia33bUWRhV7UBDziDNUre61uj5+Z/vUbuA7cw/9l7GfPsf1i02UaX5DDyym3YbHYq3Uf70hy7/7v2HsDUj77nrSkTWf7C3bhcTkwmk/f96j8ydqeb9gkhVNicBJl0NIkKwE8fQqdn3+KmkSO46667+G3dL1x262O07t6fnIIStu/agy6yEVEBGtQqUKtV7D5c5pknLcBwyiMyulwutNW651YPMOKjRzNrdTcS+7ixZpcyyE/PoQP7cBzcwIY//8fKZVu4f4mLpORkOnS5lNDG7bFHtkLlF0KHpDAKrQ7Ps0YaNR0SQ9iaUUx+uY0WoYGkBPqTGOzZh8Vl5QD89ttvfPfdd4y/7wH2Pnc7h3pfS1F+LkFBnpao/leP5PZJO/jwjRfoNSEAfbMeJIaZ2ZRedEaDtSovvvgiHTp04If58+h59S0nDdiO3ZfVjb5+OP8ddjU/znmZ/mMf9Cyv0pFeYKFpQhTXPPQi/3niVv7vkYd5/c23WLI1m5wyGyUWh2ewkKqpFPzCoXE/z191jkqKDk2gccYaXn9iPHsOpLMj7TCK04bDbseoUSi1uQAVOp2OhLAA7IqKnJJK/vxrDyPm78doMpPUqRetB4wkIbUNZTYnJq2GSqcTg1ZDRlolo2OPzvNT/fyveta7aWwIV/X1fG9W3WQ0jQwgt6ySAJPOW/mRXuj5N8LfwOA2MaQXWLii42iGXXs9f+w9zMZfVrP6u/nsWPgOt337Dh/1HcDVo8Zy3VVDatzQHPuw/7GVrqkxwTwy/QXuu2U4O39aRI877qj9RDhVGh3EtPX8MdqTpiieARoK9nr+SrOOVkSVZmG37CDAaiHI7cCocsBBlafiSa0FjY7731kPwKDWobwwtjvhsT0o9o/GaggnOCqRiLhUCE7iz4OlrNm8F1hKQM9xDLn2GjRqFSHqSlYu/C/ffvohzb+Yx7Dh15LafzSGkMZsSCvyBmsBAf6UVjqodLpJL7AQ4W/gssbhPud4RICBEquDA/nltU4Yf9VVV7F48WIGDxmC3+zHuO/Lr9i7xRO8Bwf4Uel0eeeHqlL1PVO9BdHPz8yXX35J+w4dmD3zX7z34UeAp7XvUKGFED8DGUWWunf9Dohmd1B3Mtt2YElGMU5FgbJc/Ip3EunIpKU+ly72Ykx7lnmOy5EBH6KO/AG0rZ7fBo7PEMjijSr++8shmsUG8dnvJYzXaYlr0pqoS4agb9qLRHMQTdQBtA8IplNM3QbusdlsmIxGzHoNof56EkIjqbAd6UFS9XsIrNiWwy/78zFqNazelUvTqAASQj2VugA/78ljX7ETm7UCp9vtmY5hbz7BJh0Z+9IoLirgX/eN5b/frThpmU6LzgjxnTx/VZw2T+VT9hZvj5s7nvuSMouND68yQoSGeJWaeHOYp8LDFHxkvksjaPVYHArWykrMWjBp3EcqPVyeQVLKczx/1XvdqNSewWnCGnPIvwN/Zm7mz0wXH2520q57NybePYFbrr2av9NLOVxoYVt2Ccp+B2sP70Zl9VTAuLUGuqaE8ceBAkL9dfgbdDSPDqTC5qQkOgltWALppZUM6htNTJCJ3LJKOlXY2ZNTRkyQkZzSSgotDsx6LRbAZghlU3oJGUWVPqN8At7K3h5twi+o1rTqTitYu/POO/n444+59NJLGT58uPeG4FR17dqVxYsXc/fdd3PrrZ4nzKvmaEtNTWXx4sW0bdv2RFmIeqgerGk0GtxuN/v27QPwCdaq33xWPfPTJCqA3TlldEkOrfUGV6/X43A4fNKqbuqPnTfvxRdfZP3WnUy5fzwBgUE0bnTFmd3Q4zjRhMTVa2N6DBjGxv7dGT58OM/dfS3/fnEWsR16siGtkN059e9GVv2HsqzM09r1n5en8H+3XUtAwNn5Itm54VeiIuNxm898jV/VjbpJr+OyFomkzP2S8dcP4ZMn76LXQ+/w2z6FwgobdrudsMCjD/Qeu/8Tw8y0apLCm58sZNFHr/Kf2W+QZvWMinVsTWXVjW6F3emZO0UBs16DXqsmtn0fVvzyJ08+OplFrz6M68BIbLoAVs//kJi2Pbnmrv/jih4dySiyeG9+9Vo127JKar2ROhmn03ncACM+xMw1HeP5ZmMGHRKDURS4olV31qe1oFn/GwnWOrClb8WatoW1a1azd/7noFLhH5vKHy0voW3XHqS26YTNYGJrZjF/pnnmPTpcWkl0kMnzHB9QWl6GyWxGrVZz9dVXkxvUnI9mv82fX78L4P1uTi+wcMOEB9j09w5+nfMU1017HzdBHCqysv5g4SkHbMcL1tq1a8d1N97E4o/fokXPYTRJiDxhQOx2u487r2ZGkYXxj05n1cBu/PKl52Ge4AA/77kwsFc3bJOm8OnLUwhNbUfHvkOxO104FbdnCoVjbnZr0BlxaU0Eh0cxZPwU7zqXbM2moMJOmdVBlFZNuc1Fy5hAxvVo5PPxn/7cwqwP/8OyhV/y1dofiGragb4j7+CyQVdwsMBCfrmNmCCjtyX/2PO/KljrlBLpHX2y+k0GeOaUyyu3ERdsIjHU7K0hrp5XeoEFtVZPVJuevHXttew4cIjfVn7Pmm8/53+33cCM6ARa9x/BLbeMoU1qnDdYL7E6jxu0x4eYuffmq/lj+a089thjjBgxguDg4BPvz9OlUoFfmOcvsWuNt9dXa5ms7dlT7YN64pu04Y/cw3T8vyX0ueZmWg26isiYWForQXTShJB+sBS9Vo3W7dn3l7dJpG18sHcS9H//6wlee/rfvPL2u7z56sss+noB7XtdQcjkx6F9HBaLhUB/Pwa3iWHFNk8rzPGCql/35qPT+NfoyVGlT58+/PD99wwbNoz7xt3EmDFjAGiVGIHWHHjczx17HjVp0oR33n6bsWPH8sctI7mkr+f3tHVskLdF8PM/0ql0umkTG1TjWvzPf/7DF198wQ033EDPnj1JCPWMU5wa6U9mkZXduQbyAyJZV1zJNqOWr9Qq2jcJ8UxY76+CinxyDmeQW1hCWXkZTrsNW6WFQD8Ter0evd5Aq/gwb1CNKcTTKqf3I2fGs5iWPs+jX2xi3759/G/59+xYu5SDc59FY3ydfa17sKN9X0ou7+d9ZvNko67abDbMJqPPOVLbhOfNogPIKrayO6cMu8Pt/U2pqkzZvbYMjd6M01pBn6aRVDo8A1bpdWrMGgWjyUxeZhoPTbqXBV98RkLoORy8Qms4MvJqB29r9cHnmrE7YzftP7DzfxNGMvXmPmhthZ4eN9bioyNXVpZit9iwu1QUO1WYjEaC/YMwGw2eYC718mq9bmI8j0b4R3lHrHRu2gTMYezM/7B753bSfl7I7TeP5OGJYVx5zXXEdezPfnU0FieUVzoJcXqeuU+NCadXkwj6t4jy7Mcj11ximJnDJZW8umIXLkXhu7+yMOk06DQq/A06OieHsv5gIcVWB4XlNvIVG5ckh3qP018Zxfx5sJCIAANxwWYSQ80YdRqM+gt7vubTCtbmz5/P6NGjmTt37hkqjmcQgl27drF582b27NmD2+0mNTWVTp06HX8+K3FKqj+zVtUNsmqkzUaNGtVYvlOypwVCr1WzKb2IoORQNGpVra1BOp3Oe/NR5XjBmkaj4YM5H3P1kIHs3Lq5QTyXmF5gweVW2HqomMYR/jRJbsJvv/3GmDFjePyeW7n6nn/jatYflxt255SSWRxX5yG6X3jxZbSBEbS4bADZBZ4uagUFBUx++P+4/ZEZZ2Vi7DvuuAMXat747xLgxBO91lfVjXqr+GDPjV5yKK/P/ZLbRwzm13ce5YpH38ao0+B2OnyCtWMd7RqppceoSTTtdyMBwWG13twfW6tc9eNbNXDJoSIb4558mz6DhvLk449QWlpKaHQ81sN7eW/SNRSNGc+TTz7JLwfL+WVfPlq1Cq3aUxvXObl+2+90Oo8bYADem9/qLRcBRt3RobHb96L10CsZfve/Wf7HNn7/5ScK9mwg/Y/l7FrxGRqtjsjGbQhv0pHmbdriCk2iTdMUVu/MITzASJu4IDROGwHVrpvB7RJo9fRUdFMm8c2nHzF48GDgaJD75jvvMvraIax883FGP/9fAoOiTqt1reocqP4dXXVsrhhzP4u+/or1388jeuwk9BHHD5pcLleNgK+K5zm0aG6772FmvfQUAH1ax6PTHe2qO/OJB8jbs4V5Lz5BQuMWdGrTytsSdbyb3eqqjmX1G//BbWJYsjWb5HA/DhVYsNpd/Lo/D1R4blCPnJu9urSjV5eXSXv6Saa+Podln3/A50/fy7qv2jNgzINEN29P67gg7/flscFF1felXu+5CaqtRbmq67Dd6T7uM2OJYWZ++CsLzZGJmNvGR9Okzwg6XHEjq/73M1uXf8kv/32TX794h6RLBtD/ujFc0787JdYStEfmBKxy7G/uc889x4IFC3juued47rnnztoEtnVxbMtk9WdP44JNOB0Oeg8bgSP5Mnb++AVrl3zK6m8+JeXSK7jsutv4Liwek1ZDsJ8OS1ExAOHBgT75Vm1Tn6tvJqnbML5d8Dmr//sOk66/nM233caBAwcwm80n7FZ/vPJWV7Ufm3a4lO+++45hw4Z5pzxqHBdGboXnZtZn/srjyCiy0PiyIfS/YgiTJk1izvdrUelNBJl0DG6Tyq9787E53OzLLSOvrJK4EJPPdb9q1SpWrFjB4sWLATCbzURERBAREUFoaChG/0DsGjNOrYm/HDr8Q6M4EJ3AtoNN6dc2mSCTicSodoREwf5qgdThkkrWpxfRISEEjvM9k1tUht6gx+ly06dzG1JTUikYfRf5Gfv5beX3bP7fYjauX8bf/w3kx8sG0bb/ddiCEkgJ9z/acn6MyspK77PSJ6qgTQwz0zouiNgQU61zyfVtFskWf39cNgtRZhUpMZHe1psdZRb8g0PpPOIelr75BK+8+jqvPvXEcY/RuWBzOOlx9WgUjZZn3vmYpb/vZs6cObTq3arGsuVHKqVyymwEGXX1mpqh6r7Oho6B195CyZAbyNy3k7zNP7Lk++/I+/A99OYA/Bq1I6JZZ0pDPPl2SI3xrqP6RO5V10j/FtGs2ZVLZrGVnJJKjDoNLWK1xAabGNEpgRU7DlNqddA4wh+TQcOenDI0ahXbs0uwOd0UVtjolhpOp6SQMzq5+vlyWsGa2Wzm0ksvPVNl8dG+fXvat29/RvKy2WxMnTqVefPmUVRURNu2bXn66acZMGDAST+7cuVKnnnmGbZu3YrT6aRp06ZMnDiR0aNHn5GynU/Vn1lTq9W43W7S09OJjIzEZDLVWL76DXJkgPGEtVk6nY6KCt+JPI8XrAE0jY9g9fIldO/enZSUlDOxeadFr1VzqNBCoEnHpvQiooOMxIcEsGDBAibcO4kP35pBy8FpxA8YS3mli7V78oC6BUFLv/qMAwf2MWXW5+QWlBAXF8dtt93Gww8/THFsV1q168SE3iln9EvF4XCQlZXF1Afu5INP55+xfOHoca1+k31Zx9a89tEXTLxlOLs+fYprX/0QxeXw3ogeT9UNTYfEEDKPnGMn6hpaW+vctqwSKp1uDhVa6TrwWv6+cjB33jORlp0vo8eQEcx9722+/mQWv61awoAJUzEltyOv3EZskAl/Y/2/Ek/Uda+K3emmUfjRWvWqio/YnDLKK53eAVCaN25E59ZNQLmdTYcKCbHn8fsvP7Hlt5/ZsfJztn73AQDf+QcQkdgEbXgSofEpaHJ2+lRyHL1WzQy77UHsOnON/fXZ558zoFc3lr49hesef4Mw/8BTntC5qttc9XOg6gcyPDKWa28ex7dffETPq2/mm3zP90JtgeGxLWvVg4Gqc2P0+HtY8s0XpB/Yy+EyO4cKS0gMOzp09r+efZm/Nm/iP89MZu43y9njdBHmb6hTF+OqY1n9x/2yxuHeboaNI/z5ZmMGoGJ7Vkmtz5gmhQfwzIN3cM0117L595+Y+/pMPnjsVroNHE7o3Y95W+PtTrfPDcSxwVptN5YnmyS4an/1aBLhPZZBJh2BJh1r9+TRvF0XwlPasDctk5z1S8j843ve/+V7fr+kB60H30xg486gQMfj9O6OiYlhwr3388qrrxDWZRj4h5MQevTcOpcO79tO2p49XHbkkQm9Vs2v+/IJ8zcQE+gJ4K1OFUF+ZjpeOZb+I8bwy3efs+GHefzn1x+IbNmN6K7DiG7ZFX2xZ7CeAH//Wm/sqr5X+l51Ax36DuOvFfP573/eobykiJat25BRZPE8m6biuF3jTxQoVF9nv379+Prrr7n66qtRqVSkRofQWKXyzvN37A3nsQFzeoEFq8PN3Y89zeghPfjyvZcZ9+A0n+C/dVwQueWVBJn0tVbSdO3alfnz57NhwwZ2795Nfn4+eXl5FBYWUlRUSGHhXg7nFVBUWIjNevR3/p2QKJq07kCzth3p2q07saktKbd7fh+O/Q6sjUmjYNAb6JAYgt3pPtJt0Yw59RLuu7YP6w88weKffmPtsm/Z+esS/loxn+CkFnToN5xBTcbz615qBLM2mw2j8eTD3p/o+ACkRPhzz83Xcs/C2Xz71jQ++eQT7zWcUVCKWqOjx8CrceXs5a3npnHNgB706tXrpOs9WxwOF061jqZDJtBn4DC+eu1ftG/fnsmTJzN16lQCAo6ep8c+B16fxzGcTk/3yKTwALRqFYeLregiGhHd7zbueOAJVvxvLbs3/Mr+zevYs/BNFLfnfEiNPRoMVnXTrZoKIa/MRqifnj7NI/lxZy5qtWfU3k6JoUQc+S6vug/NLraSXVLJjqwyyiodBBh1RAQa6JIcytXt4+p0bV4ITitYGzVqFN9//z133XXXmSoPANu3b2f//v0UFRXVOmBJVRfJuho7dqx34JImTZowd+5chgwZwurVq+nRo8dxP7do0SKGDx9Ot27dePLJJ1GpVHz55Zfceuut5Ofn88ADD9R72xqSY7tBulwuDh06RGJi4gk/l15gwc/gGemq+pdb9ecedDpdnbtBVomOjmb37t0nbKU4E+pSG2x3umkbH8xfGcUkhft5fyDVajXjHpxGpS6IT998Fn93OfE3PoRGrfJ2yzgZxe3E6XDw+mN30aZtO/z8/Jg0aRKvzPqQVR88jf/Uj+s0GEN9uN1uOnTtzpY/f+btl56h66zXzki+VXmD73GNDzFz+zX9sbwzl/tvu5EZ/3qUckslVteJW8er/2DWt4Wr6vOD28R4u8Z4fnTM/PvVD7w3uqPG30+Xy4fywzvTee/xcTTpNZwet0wmMTSMUL/6T0Z6om6QVY69ya7azmPTq36I0gssmPUaSiuDubL3JcxbN4KCcjuu8lz8yrP466+/yD6wm9zdmzj4y3e4XU66dq3ZVWzF9hz+PFBAeICRCb18KwC6tmnGky/P4qHbb+Snrz/GdOMd3mdx6qu2bpBV29E8JoDLnpvOoi/+w8ez32DguIeP24p3bMvasUFTVevp+Ckv87+li9iYXoyfXuu9PjOKLOwqcPDg87OZetvVzPz3I9z6f89TWumosa7auFwuNBrNcY9XlUVbMgHVcbtWVi0/vONN3DbyKl54YzZzX3+W9T+toOM1d1AwfDQjLmnk3U+A9/vyRBUaJ7uhrNpfVa0oVX7dm0/b+GAOFVnomBRCTLCJ7OTxqK67jcDDG1nxxQd8Nv1uguNSKRp1B21u6H/cdQy9eQLvvfceLz87naETn0EFmHSaUw70T9V7773H+++/z4bdh5g86T7sTjcGrYbySif7DxcD0CgqCI2/gR5NIogIMKDVj6PtwBvYsnoRu1Z/xV8fPcG+sBhCU9oAsCXbSpMWR58prC4ywMju3DIyy5xUNBnEVc9eTvGfi+javpX3N7HC5vS25NZnXxx7vg0ePJj58+fzzTf/z955hzdZfXH8m6Rt2nTv3bL33lMKskEZsvdSNggCypAlyEYEBEWQJRtBREVUBH4CCoqAskEoZRRK90ibtkl+fxxvkrbpTpu0PZ/nydPmzTvu+9773nvOPeMe1U2oZqeoZ1Yude9dnapYsGAB5syZgxlTJyHgP4uGKFd0Uioik1RZXL+FzOXj44Nu3bplu07un6HR+ObaU0RGRSP++WNcv3UHaREP8OLhDdy6tAaHPvkQTm4eaNCyHeJe74k+PbrhWVyqTtA2NgbLpRooFHY6dzjDew6LUuLGs3hYeZRH9dfGwu/VEXh27Rzirv2IsztX4tcv16BOi/Z4pVsftG7TDnGpGrjZ2+BpVDxStdIc22d25ck8WYRq1bB246eYOGY46tWrh4FjJiIsSgk3WynsbOWoFeCMwRs/wqBn99Gjdx+s2fs9OjauYRZrjlSihUJujSo+jvBzqY9pnxzFkV2fYsPGT7Bnzx6sXr0aAwcO1LUvEQeeWa7LDSHXxanUuP84FmqNBompqXCwkeL0nUj069oezm90gY2VFHfDXuDU6dN4HBaK8y+t4eCtb7MX/o1EulaLx1FKVPFxREqqGulqDQY3Ccow8STagpMtTchU93VCeGwyjl97hlS1BjFKFQLdFXCzt9HJpCKTdOYYz5JkZSuUsrZy5UqMGjUK3bt3x6hRoxAYGGhU0G7QoEGezvfvv/9iyJAhuHTpklElDSC3jPwoa5cuXcL+/fuxatUqzJgxAwApe7Vq1cKsWbNw4cKFbI/duHEjfH198csvv+jM6GPHjkW1atWwY8eOUqWsiQQjYWFhCAzUr2JrrGEbdqCG5uujfz1BcroGoZFJSNVK8uwGaUhRK2pA1sHNGGJArOjloBs4BMEe9pgwZRqa1KyA6RPHQpOWglfHLoK/a1ZrpDHS09Px5ptv4uTJkzj7y89o27YtrKyssPyjjRj6+qu4ceoQfN1G4KcbL1DVx9EknYpWq0X79u3RIqQDPlmxEN3btkC/fv0KdU6BMcuawLZ8fTQePBOXdi8HADyKSc2yj6kwbKuGLmKGM9JihrxipUpYue0Q9uz8Al+s/QAJoX+jzspPAfca+DM0WlfneXnu6enpUGslObooZSdkZ95uzJIith396wnUbsF48NIDnq1qoGIHa8ikgFwKNPVIQ/dGlZCZh5GJeBSVjOQ04zPyFeu3Qqtew3DhwCdQVGgIVYO6eXbnNcSYspbx3hToP3I8dm/ZgJodB6B99YZGzpLVsmZMQA1yV8CzfHWMnF4nS1yJbhD3K4/laz/G2+PfhGfleuj8xsA8ucAIZS0npahROTfdjHpeXCuD3B0waOgI1G/VEZ+uW4ZL+zfgztlvoHlvCfq91hkn/glHgKsCdx+SdT4363PO1zIu0IushJW9aWa5aXl3PI5RorK3I/xdaqDza73x46lT+OXQNhxYPRvSp38DyOoGCQDVgrxQs/to/LFnJULvDEY132ZG21dRIzxD1ix8F6mwRvnmXXHzeRxq+LrAy4HakJO9HZpU80aSiuLxAtwUkMkkaNK1L9r1HAjZy/v49uBOXD17ApBIILOj/j6zC5hQxqp4OeLu8wRoAEhsFHhr6kxdggrDGNr8Pgtj7a1Hjx7o0aNHjvsA2U8EAcCUKVOwceNGvP/++zh48CCAjPHYLX08Cuz6nJquQXKqBnFqOay8K6NzldpITlPDzd4GUYlKxIXeRNK9S/jzfz9j5vGDWDvfF8OHD8eECRPwV6QUYdFk8TC8p5SUFEhk1lkmaAQ2VlL4u9qhsrcDHkUlobrfa5B2ew2+1in47shB3Pzfcfw1cxQ+dXKHb8MO8G/cEaGPXsJeI8uxTrKTCYxNFrWoNAyP79/Ce++9hxYtWqBly5bYKZfAw9le53I3dtF6TOnXCbMnjMTzNbsx7JUqxa4YSKBF7QBXtK3qhTsvEnD+YRyC2g3Bwq698efB9Rg8eDA+++wzbNy4EbVr10aQu0KXFdlwDBTPIbuxTVjW3B3sEJUM2NhYIVWjRYJKjZT0ZFx/FoeBTWjZEB9nW9yIbAVp+ca4/TwB1X2dde21srcj5FbUlzcMdsWJf8KRrtHiSYwy24lrEd9270UCmpR3w7UnsbCX0xJg9jZWuBIWAydbazyOJvf1l4mUmdVwgq+kUChlTaVSQaPR4MSJEzhx4kSW37VaSmuc12yQY8eOxT///IN169ahdevWcHXNf7B/Zg4fPgyZTIa33npLt83W1hajR4/GnDlz8Pjx4wzKiSHx8fFwdXXVKWoAYGVlBQ+PIkzLWoxkjlnTaDR4/PgxOnbsqNvHWCdmOBgIQfjGszgEuinwR2g0qpRzwz9qSb4ta8VFbq5EQO4z2C8TVAhu2hkfbtyGOZPfRHpaGoIXrPvPXTJ7FxWAZtD9/Pxw7NgxtGzZEla2ZC0IadkUPQcMx/dfb0WFJh1gYyVDoJvCJJ2KRqOBi8IGk8dNxd0bf2P4iBEIDAxE8+bNs5QTyLlzNnZuwLiyVj/IFZ3eGISoZ2H499RePI6ML7IZ+OwG3MwxKMKlLchdgbkzpqBNSFsseectzBr2GnqOfQ+NuvZHgyDjiXOMoVaroYbEpD7xmdufEKjO3IlArDIN9nIrWEkleLWGt25x78w8iVECWgm8nOQIdFMYnZG3l1thyMT3cOPi/3BpxwcILr+zQNa1nNqAYMaM6Ti4ayuizh2A82vG3eczW9aMvYeZ6zBzXev+1h6EU6fPYv+6hWjXqhmCKjXO9T5yiz80vE5ufUjm/QE/bP7kE6zd9zp+2b4Cq6YMxo+HO6NGr4mQ2LsjIImSDRVGWTN8Xsbc45SpaiSp0hHopoCtjUwn0JT3cMCQXt2waeZwlCtXDvHx8UbPL845YewYTPt5LyL+tweOnVrpYnuLE61Wixp16sM9uCo2Lp6B1m8qUbV5JzjIZfBUkGjj5+4IhY0MSanplKwlJQ0Ng91w7l4kXsSnwM4hGP1nLMeAyfPw6MF9NKkebLRODa3E0UmpuBkejxq+TuhRTz8plHnWvrjIaayytbXFwoULMXr0aPz1119o0KABLofGICJehbBoZbYW0bzkBwhyV6CGrxNsbaSwkkigkFtBqUrHjWfxiEpMhZ9XdVSt1gAfrVmF639fxcbNn2PDJ5uxavVqVG/RCeXb9ke9+vXRsJxe2Y2OT4K9wjbDBIzhfQ5sGqTzmqjm44Rz917Cyc4a8clW6DZkLBwb90JM2B2EXTyBxxe/x8PT+yGRWaFCnWY51klOkxzGtn/wwQf49ddfMXjwYFy7dg0qlQpyuVz3jrm4emD4/I3YPHMI9q+dgzY1dha7YqDRaOBiT5lJ7zxPgFRCroTtm9RC3eobYF2jPc7tXo369eujTc8hGDftPcSqrRGVlIoDf4QhyE2B5hU8cs2ULOS6QHcHuMndkK7RQqlKx81n8UhQpePhyyTdmBIWpUSgmwKJqnTU8HPO8FwbBrvqPEtEHy8mFQyvbaxfk1vJILeS4bU6/kjXaBDgqoDCRqZzp7X9bwmhxJR0BLkpjLYvS6dQytqoUaNw9OhRDBgwAE2bNi10Nsjz589jzpw5mDx5cqHOY8iVK1dQpUqVLKuDN2nSBABw9erVbJW1kJAQrFixAu+//z6GDx8OiUSCvXv34s8//9TNUpVkMsesGbOs5SaUBLkr8NONFwiLUcJNYYNa/s5IUKXDxib/bpDFRW6KWE6IWUkRiNuqfTds3b0Pbw4biM8XTEK1z3ZmGLTF4qiGnU1aWhqsrKxQr149nDp1Crdf6JWMxR8sxo/fHsXtb7eg6tQPTLI8AKC3oj6OTsbURWvw4vlTvPbaazh//jyqVq2Ky6ExupnO/KaxN+YGKWhUzg2Nyrmhe+2PMXeJP0I6di2yGa3s2qox65Xh9wEdmqLnpYt4Y8R4HNqwCFcu/oohMz9Et0aV83Td9PR02MltinwAEG4qlb0cdYl+Mlt9DQmLUqKmnxMC3eyMzkyK5+Xj7oQZH27AvFE9cfHoVni7TM23dS0vylqNYF+8PX0Gli9ZiIXz3gOQVcEUlq2Cknkiaey7H+DW31fw/pTRiNv0FZpXC8zRkpCX+MPM18lruQBKxV+nXj2UW7YTto8uYPWS+bj+e1/U6j4SynLkFlkYZc2QbN3j/kvGI/ooIdAYtqPsPFvEOav4umL+/PcxfeJYfH3qHBo1aGAQ21s8QlBiShqS0zTo9NZcPAyPwq+fL4DE2gbNK/XBo5eUHtzPzTFLpkgAiE5MxdUnMbCzliE1TQMvF1e8O/z1bMtuWN8danqjqo8jbKykOHblaYbY7cKMLUXFsGHDsGrVKsyfPx/ffvstIAGc7Kxhky6FvY0V9f0Gwm92dS8wfJYiI6pI7HTs2lMo09SQW0mg1mgQ6KbA4+hkpLqUQ40+0xDQaTSunfoaN3/aj+v/+w5/1WyCxJHjUa1RKzgpbBAdnwQne+OTT0DG9TkfRibqXHs9HOUIjUqCq70NVH6VUaVXZTTuNwVP/rmAqGu/oFPH9vl2gRTXM3aclZUVvvzyS9StWxcTJkyAVquFXC7P8I41LNcV6rg12DR/EnZtWoOWHxVvQh5Dzyk3BxtU8nKAjbUUPs62OPrXE7hVbYLByw/g/plDOL5jA37/6Ru8MW4W4gNaQAMJbj6LR1UfJzQs55qjDCgsa13qBuhkxycxSlwOjcGfYZS9WISIiHMI7wRDjI3ThpNyAmP9mohJy27coolL5LiPpVMoZe3kyZOYPHkyPvroI5MUxsPDo9AKX2bCw8Ph65t1qUSx7dmzZ9ke+/777+Phw4dYunQplixZAoCSqnz11VcZ3BMyo1KpoFKpdN+zm6U0N5lj1qKiopCUlJQhZi3zC5S5swlwVSBdo4GzrQ0iE1TwcbaDUpWGmGQNlCmqDNezFGWtMAg3q7jkNAS5K2BjJUWVRm0wfeVWrJn1FsYPH4hvjx9DRBK5SUUnpiJCk5IhLiA9PV2Xwa5Zs2YIyPBMPTB3wSLMnfE2WnQfgGiPpgWKgciMqGvR6e05+BX6d++Izp0748KFC4hWpiIsOgkOtla5ds6ZyckNUtCkgge2r1lYpLPOBRWURJueNPdDSPxq4afPFmHdxDfgv+kLNCrXMct+mQdatVoNe1ubol0IFcgibOdlf/E3JxfMJzFKeDo0w2vDJ+L4zk9QqdEr+MnTHlW98+6CmxdlDQDmzJyGbZ9uxGcfrUDLXbuMnie3cwD5c2X+YvdedGzTAtuWz0HKe6tzdHEtrLKYW5lFnMWQZsEIcK2Lyk3aYu3ypbj89RbcsCYl7Xp4Itq4F3ytSUPXdCD7BD05vS/ZCeyGEyLp7V6Hq+9S3Dj+Bex8KukE6eJU1mQyKf59mYRWY+bjvCYN5z6dCyc7OY44+gBAtlkAR7Yqjycx3rmmfTeG2G/fxTA8jEqCv4tdtpkILQErKyvMnj0bw4cPx/Xr19EwuAI8HfSTPfl13TT27gn38joBLgiPTUY5D3u4KGzgZm+DIHcF7jxPQJIqHZEpUlRt1w+uDbsh7tZ53P5pLz6aMRJegRXRuvcwaFKVkMvlOSo1og0aWk2uP4lDWroGCrkMVX2dkKxSw8NRjpZV30D96WOgyCFte176EmOUK1cOn376KQYNGgQAaNOuPS6HxiBamYqXiSo0DHbF4IH9oYx8gi3rlqNt03oIatQej6OVuPEszqQx6cYw7EsbBrsiIl6/TmOryp44d+8lWlX2RJsaU+HX4FX8eWgjdq+cjUqNXoH/6+/Azc0N/zyNM5oZ0xChrGWOWQ9wVWSRJcT27JLlZMZYH5VbPHFez1PSyH1UzAEnJydUqpQ1TqKgjBs3Dl9++WWe3SbzQnJycgY3RoHIDpScnJztsXK5HFWqVEGfPn2wb98+fPnll2jUqBGGDBmC33//Pdvjli1bBmdnZ90nO8uducmsrIWGhgJAjuU17NgE9YNc4WxnhVaVPRHkpkCKWg2VRoLEZBWexChx4X4knsQodfWal5lrSyXIXYFANwUGNAlCj3r+utgVq6B66DR9Le7/fQldXuuF83fDceUxCQKZM2AJy5og4D83NtGZvPv2JARVroFjm5bgwYuELM+7IGg0WoRFU1tvUckDtcr748SJE0hLS0PXrl1hq1HBxY4UbrFPXju3nCxrhmS+T0tBtOknMUrUatkebWZthbWjK8YP7I6PPvpIJ7gaa/tA3hKMmILMz8/w3crL/rmdd/bsOfAMroKfNr2P3b/exb5LYbp13HLDWDZIQ0RZo1XAsAnT8eWXX+Ldz7/FsatPM5Q/r8pSkHvurizivlo3qoNpi9fi2tnvcfG7/fj7SSw2n76PP0OjsxyTVzfIgiD6DiGkPYlRQmHviH6T5+K1+Ttg51UOVrb2uBmR/ZiUF0Q7FbFXov6Ntd/c2lBmdzjDNlXB2wl9Rr+NJ9d+havyMR5HK3Nfy86EKGyksLOxQp+GgWgQ7I55qzejTvMQfPfRTIRePQcg92QtPer7o0c9/3z3SWFRSurTtYCNTFpkE1D5Iae6HDBgAAICArB69WpdHTb6b22q6MRUXHkco6s7Eb6SHcbePWEFeaWyJ2Z2roam5d2hsJYhIj4FAFl2qvs6oVVlD1jJJKgR4IbyTdqj69wv0HD8Ojj7BuHI+oU4+d3xDO6ExsY9w/K3qESp2eXWUvi5KtCigic61fDBK1U90aqyB9pW88q1n8hLX5IdAwcOxODBgwEAz19EICxaiT8eRuPcvUhcDo1BkLsCYyZNR+9+AzBixAhc/P13/HjzOR5FJeHEP+H4MzQ6x/evMIj4X0MLetB/lqgutX0xvm0lpKZrcOFBJLz8/PHuik3Ysf8rhN/9G1fWj0Pkwxu4FhaD/ZfCsO9iWLZlzEmuy24Myu8zN2zblipHFDWF6lnffPNN7Nu3z2TKVZUqVaBWq1G3bl2sXbsWhw4dwpEjR7J88oOdnV0GK5cgJSVF93t2TJo0CcePH8f+/fsxYMAADB48GD///DN8fX0xderUbI+bPXs24uLidJ/Hjx/nq8zFReYEIw8fPgSAHLNBGnvJfJxtUdPPGZ6OpBRLIIFMZgV1enqGTjc8llL8vkxMLapbKnIydxTiebSq7InK9Zqh1fjleHDtN3wyfyqexyQCAJJU6XiZqNJ1dsKylt3gKpPJMG72Ejz/9wb+Pv01Tt9+gbjkvGWzy450tRppGm2GwS8oKAgnTpzAgwcPsPn9CZBq0pGq1uDyo7wJ6IK8WlUsCcNnL+qwfpArPBzkqFSpIiau2o1uA0Zh+vTpaNa2Mw6eu4kL/0bicUxWy2BRCvg5kZNAUxA0EhnGzV+DhJfP8PCnXbj3IgF/hkVnUaiMHmtknbXsylquRXc4evhi/+bVuP4kDif+CdedP6dFsQ3J74DdtF03vNJzKI59thyXLv0BmYzWisxMUVrWMpdZxAx62MtRt15d9Hx/Gwau/QblPAvnXZKdIGRsu7E2lNf1TANcFdi8cAoqVq6CP49+jgA3Wly7KARPY9hZy+BkZ4MutX0xo1M1vBlSFYcOHkC1Bs1x/cgGAEBMSu4JYApCkDulv29c3g1VfCwjHXhO/YGNjQ1GvDUBe/buxR/X72U4JlGVDlsrWZ6S5QDZv3uG24PcFYhPSdNZchoGu6JhsCtaV/ZEq0qe8HG2RZdavtAAKF+nMUImLsey/b+g04AxqPFKd9hYSfMszAe40uRpu6pe6FDTGz3q+2Nky/LoUc8fPs55S9lfGOF/wwZqaxpI4GBrBQ9HOVwU1oCEzt2ysidWrPsE5avVxrxJIyBJikR4HFm5roTF6Oost4mT/CLku8yTNwC5rV5+RKEPUQmpeBajxN2IBLzasTNOnfsdvr6+OL9uEp6eP4rH0UkIi1Zm6KcNMWZZy438PnNTj3UlkUJNB9eoUQPHjh1DgwYNMHz48GyzQfbu3TtP5+vfv7/uf5G5MTP5SVgCkLvj06dPs2wPDw8HAPj5+Rk9LjU1Fdu2bcOsWbMyCKHW1tbo0qULNm7ciNTUVKMzd3K53Kg1z9IwnEETbpBWVlbw9vbO9hhj5mQR75SSpoattQypaWqkqIHUtLQMrjh/XSRl7UVCyVXWMmP4PGoHOGOfiwLWUOPUxvfw9cfz4DVvDdzsbTLErQnLWk7uF0N7dsLJQ73w486P4FazNQ7Hp8DTUV7gzF2AFnLrrOun1K5dG8eOHUPnzp2RsOodNBn9AaKSUvHgZSLSNVq0reqV6zXz4gZpaRjL8gXQxINwjao3/X14VamPPSvfxZher6LLlOWoUqcBLofa4KebLwAAbvY2SExJhdwM1uL8JrnIy/kCKlRB675v4teDn6Fis464b2+NqP/e15wG1twUdsOy2lh5o8vwyTiwejZePLiBis2b6t6BnBbFLhQSoN2w6Xh46xqOr5uFocv3IaBCVlfDvMasmQLxTGgtKS8EuipQ3sMhR5etvJCdy092LkUiA5xhoonc4pYEMpkMixcuwODBg/Hk7nXUrt+g2FwhjVmAKvq44vLZH9Dy1S7468IZPIgumrEmv+5cxUFu/cEr3Qdg7cpl2LhpE3Zu+kh3jIj3MTwurwp7dmSONzKM2RRZKFtU8kCaRos/HkYhTaNFtMwV3u3HwNXb0WhGzoJQUBfH/ODq6oqvzl5BmlaKQG9HdKjhrXND3n7uISKTVFCq1Kg9fDGeLBuDY8snY8nWI0hITkOAqwJJqnQkpaYbjW8vDIahD5mThylT1YAWcJBbwd3RBkkqNVTpGlwOjUGP+lXx95+/YeSEt7F32wYkhf0Dv+Fz8eK/sTFz2bKzrJkyPs/UY11JpFCjkqmVq9OnTxemOEapV68eTp8+jfj4+AxJRi5evKj73RhRUVGUkttI2dPS0qDRaEzqrmkOMlvWAFJe8z2z/F+/7uEoh5vCBinpasjlciiTEhEWlYjeDclSJwUJdHIba9PcgAVSxdsRT5q3g1y6DN9//B6OfbIQksmLUNXXGdV8HaHVanWWtew6INHJDXt7Dn47/QPOffU5Xh02Hbt/C8XT2OQCBchqNRpU9DIe6xQSEkKLsPbshRfx76LqoPdx+5kN0jVanLkdgUntKqNL7axxn4K8ukFaErklIxEB0s3bdoRP+SrYPH8yDi0ajdYDpyD5tWF4GqNEUqoaNfyckahUwd61eDPhGZbVlOfrUtsXVd6fi2F/nMLNA6tQe/x62Fpb5bqGYG7KWuayThwzEhePfoHzBzfj1Vda6Oohr5a13MgsKIiYjbcWfoylb/bAD5vnw3bGR1kmQIrSspYZw7aWXaKP4iiDSDABLbIoa3kR2vv374/5Cxfhpz2b0KTJ9mIrf3buera2tnjrg0349vg3sPPKec3QwmJJQmRu/UH1ct7o3LMvTny1F2kfr4S1tbXRY/KqqOe3PCJm87FBFsoONbwRmaBCVJIKkUmp8HWxhY11/t1Ks1PKspuMMDVNalfJEst/4X4kbobHI02tQUR8CuSOrmgzaQ3OfTQBG+aOw6gPtiLV0VZX/nS1Bg62VlnWvSsoQr4zrAfDBaJFPFngfxZxW2uZTpazsbHBnq2bEFS9AT5eMB0nl46EatIq2NvUz3Kd7CxrplSUS0PMWWEplLJmauWqTZs2AChBx19//YWIiAi0bNmyUKny+/Tpg9WrV2PLli06hVKlUmH79u1o2rSpLj4rLCwMSqUS1apVAwB4eXnBxcUFR48exeLFi3UWtMTERBw/fhzVqlXL0YWyJJA5Zg2A0WQsuZE55eqfodG4ULURVPs/wa6dO/Egsi/cHeSIiKdYDI22cLN2lopwa6oX4Ipafr1RzdMWa+dNhY2tHSRvzQag79iyGyjFeZSparh7+mLIm5Ow69OPIes9BHZe/giLUhYomN1wmQZjdO3aFbNWfYbl77wJ9b4lqDZgLlI1UthYSbD2xzv47UEUmldw1y1KaXj9kmhZy63zFy4iDrZWUNu5Y9AH23Hp4Cb878uP8OLOX6jUdyZcXD0QlZiC5NQ0pJbseRsd4plMmLcS743qicDL36Jp/1G69NrZkR9X2LAoJVRqoEWfsdi7YgbuXLuMhsHtceF+JFSp6SZpR5kFBaGI7k9OQ9dJS3Bk+RQ4Hd4OV4dxGZQ1c7i0ml0QkWT8m1+rikwmw+Cxb2PxjAl4cOs6PB1oDb2ividjyWiE4qtUS1GtReci75PMXnf5IMBVgYWz3kadL7/AsWPH0KdPn2K9vlDAxJIRwquhircjwqJlsLOSIVqZCqsC1FlOk2/FYV3Lzmpdw9cJkUkqNAp2xa3weNTyr4uaSz7F2mlDsfmDd9Bu7GKoJRJ42Mvh7mCTJb69MBjzUhAyisJGhudxKbjwbyTcHeRoW83L6ETRxFGD0KB+PUwcORA/rBiL5Emr0bqyZ5YJLiCrZc2SJjJKAwXuyVJSUnDt2jVIJBK0adMmx09+WL9+PXx9fdGqVSv07t0bf/9Ni3NGRkbCw8MDX3zxRb7O17RpU/Tt2xezZ8/GrFmzsGXLFrRr1w6hoaFYuXKlbr9hw4ahevXquu8ymQwzZszA3bt30axZM6xbtw5r1qxBkyZN8OTJE8ybNy9f5bBEjClrOblAZkdm/+PUdA0aNWqCKs064NSeTxD6IgZ/PIzCkyiK4Qp0L34rhCnIyadczFglpaajQ01vvPlKRayeMxnL1qzH2aO78cOXn+D6kzh8d5XiF3NytRKxJQ3LuWL9sgXw9HBH2I9foHkFDwS5Z10vKy8YLtOQHeOH9cOExRsRef0c4n5Yh9p+dB21Vot/IxJw7t5Lo37jJdGyliv/TS5HJqgQ6KaAg60cG9atwUfb9uHJnWu4sGoMvBPvoYafC+KVKjyNVxVbrE5RExalRMMmTdGi+0BcPfoZAq2TchVy8qqsGb4n7br2gHdQRezetAYn/glHWIwSKWlpJmlH2SVBqOztiJD2nVG321BcOrgRf/7+W5YEJyU5AVJBEPFEYnFnIP/WlZHDBiMguDwObl1XbLElxixrQjBXa7QIclPATWGaZRBKC7Vr10aLFi3w2Wef6bYZG9cK6wZpDCEnNAx2zfBuNixHbU9hawWJRIJnscp8t5+cYqAKk0CksFT1ccTAJkEY0rwcejUIQHxyGsrXbICBs1bi/u8/4qdd66BK1SA5NR0eDnIkpaabrJzGJjOC3BW6GPpvrj3D3RcJuGokdlcQ4KpA33aNsP+bk3D1K4/TH03B6m0HMrQVMQGdud8sq4lAiooCK2u2trZ49913cefOHZMVZvv27Xj77bfRuXNnbNu2LcOA4eHhgXbt2mH//v35Pu+uXbvw9ttvY/fu3ZgyZQrS0tLw7bff4pVXXsnxuLlz52LPnj2wtrbGokWL8P7778PJyQmHDx/WZQAqyRgOduKl9vHxKfR5RfD1tNnzkRwfhVunDiJNo4X8PxksoIQqazkFuYoZq8xWr3enTcKEGXPxy55P8P2hnYj6z7oYr8p+9sywk7O3t8eMuQvw7ddf4acz/4O/i12BOr+8pEQPcFVgw5yxWLZhK/45dxL/7FuBzjW84KKwhqOtNTwcjQ8mJTHBSG4IAaJtNS/UCXDB+LaV4ONsizS/ehi26gCcfYKwdtpQHNz0IRISk6BMQ54zJ1o6QrhZunQpnJ2dsX3NQqw+eRvbzz/MViHNLRukwPA96VTbDxOmv4vrl/6H5/f+RkJyGmQS07Sj7AQFoZRMmvk+fCrXwXcfv4dfrtzX/V6cbpCWgrFnlV9lrZynEz5YOB+///IDnj24XSyCsTFlTbTdkKpeVNe5WITLIuPGjcPPP/+M+/ep3Wce10zlBpkdmdub+N62qhcCXO2yLJZs6usVF5mfa2q6BnUCXCCTSjBlzFB0GDkDD3/ZhztnvoJMJsXT2OQMrsiFxdiYH+CqgKejHPY2VtBqtVClaWBnY5Uh0UlmnsQoYWvvhE/3HEH5Ok1xePlU7N53SPd7aViSqSRQqCnEWrVq6dK9m4I1a9agR48e2Lt3L6KiorL83rBhQ6xfvz7f57W1tcWqVauwatWqbPc5c+aM0e2DBg3SraNR2jBmWTOFsqZzCajvj+tjx2L7zi9Qvnl3XA6lOn2RoEIBvC3NTk5m/Zx+G/TWVNx48AT/271Kt85STHLe/ebKN+8K18AqOLBhKaTeVQoUt5bX9asAoFWH7pizajM+nDkeEokUg2cuw92IJCT9F5ScXYBxaVLWjLm1XLgfSesSyZzRecZG3PppH37dtwEadTrc/IL07mQlHP29e2Dj+nXo378/nOp1gneN5nBT2Bhtd7llgxQYvicBrgqMGDIQ2zaswVdb12HrvqNQpaZDmVY0GfwA/b0FuStwfeYqfDatLxa9Mx4hP59EkLtDmVTWciI/FpbBgwdj8eLFOL5zI4Z1P5T7AYXEmLJWktwSi4K8JHXo06cPpkyZgu3bt2Pp0qVGx66isKzlRqNyboVIoGV5ZH6umde9nDh5KlJjI/C/fWtQpXwQZHVa6cYQw7USc1oXMieyG/NFuXrU88fTmGRAAvi72GUbLyuUTi9XJ+zaewDjxozAvMmjEZ2gxNS3hiM9nVzXzdFmyhKFkq6WLl2Kzz77DD///LNJCnP//n106dIl29/d3NyMKnFMwTB8mcWLZgplzZD58+dDo1HjwpGtwH8zduFxJTMbZE4zdDn9Fuxhj6lzPsArXXri5OcfAgBs5eSek5d0vVKJFJ1GzqB1T/53AtefxOGnGy/w+f/+NbpWlDFyi1kzJMhdgS6v9cLHn27FxZ+OYefKOYhTqvAsNhkPIhOzXLdUukEaIOrIxkqKWv7OCKnmhSYVPTB83GT0+2AnvMpXh19wpQxuZKWFvn37oknLNriwezWUycm4nE1q9ry42QLG1opLwbCJ7+Da7//Dnxd/g0ajRoKq6AMAA1wVaNugGl6bugwPrv2GoZPexZ+h0WZbhsGSKKjQZW1tjblz5+Lw4cO4fv26iUuVlfz0aWWFvKQ4t7OzQ79+/fDll19Co9Ho3kmAJqSSVIVbJoYhsrMgiu8Ng13xwYcrENKxKw6tngmPpEe6MSQsSonH0Uoc/esJwmLy7xYKZJ+sSZSjUTk33TqDYs263NxIXySmo9mohQhs3AFr5kzCZ1u3c59ZTBTKsrZx40a4ubmhU6dOKF++PMqXL58l6YZEIsGxY8fydD4XFxdERkZm+/vNmzdNrkyUZQyVtdjYWACmV9a8vLwwedoMrF3xIV4ZSPFwQZ4l0w2yoAS4KhDQUIHuXx9As7ad8Nf507jxPFEfDJ9L8HPDcq7wHNoLt385iL+Pbkanbq8hMkkKCSS4EhaTp9nIvArTuvK6KtCi0gi42Fph2LBhSFUDjQbPxM3weMgkEvz+IArjQyqhUTk3i7OsmTJlMGCQ6hhAj/r+Gc5f278z2rVsivpB+c/QWRJ4GpuMt+cvx9Bur+Dp2f2oN2KK0baaH8utITZWUgTUD0GlqjWwZ/NqaDUauNrnvjaSKWhYzhXo3R1ht67gfwc2Y2+TZmUyZs0YBXWFGzp0KD744APMXbAI767YbLJ30Bj56dPKCjZWUtx4FpdrRsEhQ4Zgy5Yt+PXXX3V5BUQ/pyyGyRJG76Hy/qpNmDFmID6YPBQ1A79DwKutYWMlxd9PYiGRAP88jkWlAshMBe2TjZVTlPWnmy8QnpCKoJ7ToZFaYem7k9GoSTPuM4uBQtXk33//jbS0NAQFBUGtVuP+/fv4559/snzySteuXbFlyxad4mDIjRs38Pnnn+P1118vTJEZAwwHu5cvXwLIqKyZapHGhXNmwcvLC38e2wEACHK3jEVEi5sXiWl4Y+ZqNH5jLPwq19EJ/LkFP4uZsHVrViEhOgKJl79B26pecLbLW5rfvMYTGWPIkCFYs/FT/P3LUfx1YC3S0tT492UiUtUanL4dAcDyYtZMtYCmoUXNsI4Mz9+onBvefKViqXLfMSQsSgnPgPLoOXQs/vxmB9w1MbCxkmbpFwoqGKSma6CFBHVeG41zZ88gMuJ5sabOb1jOFX1HT0FgzSbY9sE0PHsRgeQidMMsKRRUWYtISke/0ZNx/OhXuHXrFi6HxuDYlad5Wli9IGVkZU3PkxglroTFwNHOOteMgi1btkS5cuXw5Zdf6raJsUghlxX7czX1gtCWRnb3FxalhFpqgxELP0FwpaoY1Ps1XL16FU9jk6GwscLzBBUUciuKZ8snplLWDHGzt4G/iwIKWxs0Gvwu6nbshz8u/saWtWKgUDUZGhqKhw8f5vh58OBBns+3ZMkSqNVq1KpVC/PmzYNEIsHOnTsxZMgQNGrUCF5eXpg/f35hiswYYOhGEhFBgrehsmYqoVehUGDMtDlIiI8DUHrd5XLjcmgMtDJbdBoyEY2rBelmnfMa/NymST0MG/Um1q9ZhejIl6jp5wwf59ytEIVVpqZNeAsrP/4EV04ewuUDH8HXUQ4pJLCSSTKc31Lq1VTZv0T7F778YVFKPInJm4JdWhD3+uHi+fD18cahDR/gr0fRWVxzCioYBLkr8DhaiaCGIXALrAy1Wo34lOKb2Q+LUsLGxhrjFqyDVGaFyBfPkZRWtAkWLB1DQT2/QntYlBIhr/WFu7cvDm5dD0iAsGhqK6bOEMnKWkbEOmYJyWm59k1SqRRDhgzBwYOHcPrGE90aZC0qecDOuvj7cVPJGpZKdvcn+tfm1QLx0RcHUL5iRbRt2xY3Ll9EQkoaohNUeB6XjLvPE/AkRplnpbYwE7Q50TDYFZ1q+qBTTR8Ee9qj+7i5GDZuSoZM6kzRYBlT4f/h5+eHy5cvo3Pnzjhw4AC0Wi12796N48ePY+DAgfj9998LteYakxFjbpCGqftNKZSOGTkMVWvWAWA5Qn2xIwGc7KzJV7yef4Hcg/qMngotJJg9bz6uPYnFiX/Ci6XjnjF5PCa8vwLXfzqIvw6vh6OtDDfD4/DRT3dw7u6LQp/flJgq+5dh+8/srlpWUhIHuCpgYyXF2QfxmDx3CX756SR++O44fvvP4igoaPxQgKsCvRoEQKMFmvUZCwBwcyweN0iA6jjITYGalQKx8pNtkMlkcHcq/fWaGwW1rAW5K+DioMDb78zEz98egWtaJILcFAVeciS3MlpKn2MJBLkrEOhG6wnmpW8aMmQI4uPj8MuPJ8yuJJX2CbDs7s8wfqxj/Qo4+8sp1KtXD4snDsLdiz+jnKcDlKlqBP43BuVVqS0qb5cAVwV61PdH30aB8He2Q6pag1o9xuPIyTMmvQ6TFZM4mp49exbfffcdHj16BAAIDg5Gt27d8r3GGkAxTlu3bsXWrVvx8uVLaDQaeHp6cqdcBBibDVcoMq5LZCqBNMjdAbu3b8X69et1C4yXNfxd7BARnwJ/l4Ivpi6xc0KVzsNw5chmfNusB14LaZLrYp95zdSXG7OnTUJckgp71s5HulqLGr0n48ydCKTrsnymIrBQV7AsMrf/srrA55WwGMQlp8OpanM0aNkWp3asRs/KjbD5zH20reqFCp4OiE5MKXAf3aicG57GJqOi52tIffgnurYPMe0N5ECGOq7nj8peP6NixYrFdn1LpaDKmnieDSaNw6aPVmHD2pWY9sHHRRK7xjFrGcnveF21alXUbdAQZ78/irEj9EsRmcNiWdqzeOb1/lxcXLD0072YNnEsjq6ege7DJ6H94In47X4kLstkSIcGjnJrvF7XL8fzFIWyZhirHRalhCpNg9CXSYiIV2HfxTAMbBpUquvQ3BRKWUtNTcXAgQPx9ddfQ6vVwsXFBQBZadasWYNevXph3759sLa2LtD5PT09C1M8JheKwqc5Jxo3bozdu3cX2/UsjdR0Dcp7OOQaT5ATT2KUqN95AO6eOYrb32xC2+YN8DJRpXNjMYapOu4AVwWWz3sHvk62WL1wFtLVGri1HwNZYgoAIDwupVDnt2RKuzCRE/WDXHElLAYBrgqMfmchpvR9FVe/+xINeozG6TsR8HG2Q1SiqlDtq2GwKzwd5Oj9xTazPueQkBCzXdtSKIwbpECswzpt+nRU7zISDWtXN3m9shtk4Rk2eBBmz54NRylngLQUbrxQouPEJbDzCsZ3uz5B6O1/UH/YPDxMkMDWWobKXo65yhBFkfTL0Kon1tJVqTV4HJ2Eh1FJuPwopsyOkcVBoWpy0aJFOHr0KN555x2Eh4cjOjoa0dHReP78OWbMmIEjR45g8eLFpiorY2IMB7uOHTvC0bFsJv4oLkzh6lE/yBUBHk5oN2waHlw5j8R/L8PexgqXQ2Oy9WU3pf96gKsCqxbMxJJVH+HfM4cQe2YH0tJpYAh0ty/0+RnLQyRRcbazRpWqVdFvxFu4c3I3pMpoBLnZIyk1Hc62skK1L+FueeKf8DwvR2FqSnuSg/xgioWRu/QZDIWTKw59sQEPIhNN/mxZWSs8ffv2RWpqapaM3fxcTUd++5UAVwWexaWgy9AJWLPtAB7f+RtfLxyO1BcPYC2VwsNRnqsMURSWNUP5RbhDvvVKBdT0c4afix1QtkN9i5xC1eTevXsxfPhwrFy5MkOsk5eXF1asWIFhw4aVaUuKpWNoWTt58iTi4uLMXKLSjSlinRqVc0Pnmr6YMmow6jVujt0fL8H957GIVqZm68teFB333BlvY+y7i3Hv5314fu4ggDIci1hGEIP1W1Nmwk5hj39PfI5qPo6IiE+B1gQuacLd8kpYjIlKnD8uP4rRfco6plDWXiq1aN17FO6e+w7Xbt7Nc4xtXuGYtcITGBiIli1b4sCBA7ptpqh7Rk9+k6c421mjYw0fuNnboG/Pbrh65S94eXjgr42ToAg9izdbl89VhiiKMd+Y/PL8P28afxc7WgqFKTIKVZPh4eFo2rRptr83bdoUz58/L8wlmCIksxskz6aVDILcFbCXW2HpilV4cPc2zhw/CGiRrdXOVDFrmfl0+fuYs/ADPL1zDQDwNFZl0vMzloUYrG0UDug3bgbOfncEJ0//DxEJKjyOTiq0YFA/yDXPy1EUCdpMf5lCEeSuwIhRb0Lh6IL7P+3Bk2glHO2sTZbMgmPWTMOAAQPw448/IjraPBbt0k5+PWoME8UAwLN0B+w8egLd3hiIrz6ej7lvj8fdJy9zXBKjuDI0XwmLQXxKOu6/SCjS6zCFVNYCAgJw5syZbH8/e/YsAgICCnMJpggp7pg1xjQIoblr25Zo270Pvt2+Do8jIrMN4i/KddCWLpiHIRNnwtbeEammyVfEWDhB7go0aN8LgZVr4vsty6HWaExi5TD3mnUNy7miYbBrkc8QW7q7pSli1gDqp/q1qIRR4ybj95NHUNlehaD/3F1Ncf/sBmka+vTpA41Gg6NHj+q28XM1Hfn1qDHcX1jlJDIbfL1vBxZ/9CkOHPoKLVs0x/H/XcK5e5H46cYLo+teAkWfobl+kCvUag0C3RRmzyha2ilUTQ4fPhwHDx7EuHHjcOfOHajVamg0Gty5cwfjx4/HoUOHMGLECBMVlTE1PNiVfFYs+xCpKUpcPrZd11lmFgaLas0VwSv9xmLhwd/wIqn41sdizIuPiz26j52NFw9u4OGF7+HrbFviJ36Ka0mGkrCmlCld4V4bMBwOjo74ZtdmtKjkgdR0jUnun8cv0+Dj44M2bdroXCHZDdJyyGyV82nQHv2X7IJao8HOdwfjyplv8TAqKcv7VFzKWqNybhjfthLqBLiUyUzJxUmhanLOnDkYNmwYtmzZgho1asDW1hZyuRw1atTAZ599hmHDhmHOnDmmKitjYtiyVvLx9fdH7+Hj8f2+bUAiLWx+OfS/2JtQir0p6o67fpAr3Bxszee+xhQrYVFK2Mut0KldCNp364XvvlgDrarwbpBlhZKwppQpBfZqQV5o3280vjn0Jb777R+T3T/HrJmO/v3745dffsHLly8BsGXNUsg8gVQ/yBXlKlXBW2v2o26rDji1aR5+3f4hZNqMC6EXl7JmrIxM0VCompTJZNixYweuXLmCJUuWYMyYMRgzZgyWLl2Kq1evYvv27dyZWjCsrJV8wqKU6DLoLdg5umDEhLcx/eBVnL0bgfiUNOC/8baoYtYE5nZfY4qPJzFKvExQISk1HQ3LueKLzR8jMSEBq1at4r4kj1i6cGMqN0hBgKsCdTv1h5WNHWbN/wCXH8WYZN01jlkzHW+88QYA4OjRo2xZs2AalXNDwyA3+Hu4YsKCj/DukrX47YcjmDKoOy78dUPnTVOcyhpTPJgkyKRu3bqoW7euKU7FFCOsrJV8gtwVuPHMGo36TMDpLQvxa4NfUaFWQ/g626FhMFm6uONmTIWwqilsZCRsuyrw3nvvYcGCBXj27Jm5i8eYCFML7AGebqjeYSD+/nY7LlybgIj4QHSp7VsohY3dIE2Hh4cHfHx8EB4ejuRUNWKVqTmu3cmYEQkQn5yGlHQ1+gwejmq162H2pJEY1as95i5fj6ED++LKv2Qh5TG/9JBvZa1OnTr52l8ikeDatWv5vQxTDPDMZMknwFWB+kGuCOvcE9d+2If7325G02a7UMXHUTfQFnXMGlN2CHJX6BZFFcyYMQMLFiwAABbwSgmmVtY61PSGfNpUvPnzPlz4+gvUn7MEl0NjdG2pIG2GlTXTo9VqoUxNh0YrQVgUv8uWiL+LHX659QJ2NjKcvh2BIJ+KmLDuEE5sWog5E0fg2p+/o/vAUQB4zC9N5FtZc3Nzy1MH+fz5c9y5c4c7UwuGff5LB6npGrSp6oPkd+ZjzdTBeHL5Z/i3ekv3O1vWGFMR4JpVsFYoFFi/+yiuXv6DBbxSQFGM2QGuCgx6pTouT5yMjetWY/TEabDz8NIlRiiossZ9mumxs5ZBKYVFx1SWZVLTNfBytMXTWCVUag2exCpR3ccVqzbvwJ/f78U7M2bg1E8/AuAxvzSRb2Utp1T9AClpK1aswGeffQaZTIahQ4cWtGxMEcNukKUDYe0Y8HpnnDzQHr98+TGqNW+Hp7H+aBjsCkkRx6wxZZMnMUqdZaRXt45o2KwVC3ilDFP3GR36jsCnn6zHj/u3YuWqVVmstPmBPUNMi3iWdjYyuChseNLFQglyV6CWvzNsrKVQpWsg0QIyqQTBHvZoOXUqntv4Y9P8yQCAiw9jUJO9HUoFJpPUX7x4gWnTpqFixYr45JNPMGDAANy+fRtffPGFqS7BmBhW1koHImFBo3JumDhrAZJiIvHLgS8QFkXCNFvWmKKgJKSgZwpGUSWZqFXBD/2Gv4Wje7cDSdGFSrTCbpCmR9Q7P1fLJcBVgR71/TGwSRBq+zmjVoCzbgHtY1eewqtSbby+aBca9pkAjWcV7p9LCYWW3p4/f45p06ahQoUK+OSTT9C/f3+dklaxYkVTlJEpInhmsvTR/ZUG6DHkTVz5dgfuPniAiw+jcPJ6OABW1hjTYpiCnRW30kVRKWsBrgp8/OF8ODk6YtrMdwu1ODYra6ZFPEvOBlkyEEpbj3r+CHBV4PKjGJy7H4kX8Slwd3NH+wFvwd5Bwd4OpYQCS2/Pnz/H22+/ncGSdufOHXzxxReoUKGCKcvIFBFpaWmwtrY2dzEYEyAWwgaAnRtWwNHJBSe3rca9F4m4/SwOABCVlGrOIjKlDMMU9CVh7TAmbxSVAiT6qHi1FRYvXozD+/fi7PmL2H8pDMeuPs230sYxa6aHLWsllwcvExEWlYQnMcnwcbaDTCJB26pe7AJZSsh3TxceHo6pU6eiQoUK2LRpEwYOHIg7d+5g27ZtKF++fFGUkSkilEol7O3tzV0MxgQYWjYcHR0xYtpc3Lv4M17c/gNhMUkAgHsRSWYuJVNasfS1w5j8URRCu2EfNXr0aFSpVh1b1yzCP09jcfL6c1x+FJOv87FniGlhy1rJJl2thbPCGnbWUsikEtQOdEFqusbcxWJMRL4TjFSsWBEqlQr16tXDnDlzUL58ecTExCAmJvuOtkGDBoUqJFM0JCUlQaFg4ao0kDml+rRxo/DDoS9xbvdqvDZ9FQCeLWVMj2GSEVbUSg9FIbAb9lHPE1IxduYCvDN6AHwvnUHlpu2AfF6S3SBNDytqJZe21bwQq0xFoJsCvs528HSUs6dDKSLfylpKSgoA4MqVK+jXr1+O+4rOVK1WF6x0TJGiVCpZWSslZE6pLpFI0Gfy+1jyZg9cOr4HAFDNz9lcxWNKKYbWElbWSgdFpQAZ9lEX7keiTrMQVGnYCjePbULXrp3RsJxrvs7HypppMXyW/FxLHo3KucHH2ZYnz0op+VbWtm/fXhTlYMwAK2ull7AoJfwqVEPVkF64/ssRAICPM9c1Y1qMLZLNlB6KSmgX7WbpitUY1OUVvDx3EGg9DxfuR+ZZ0OSYNdOj1WrZulaCMbYOJlM6yLeyNnz48KIoB2MGOGat9BLkrsCNZ3EYPfU9LPjzFJTxsXiZoDJ3sZhSBgsHpZOiFth17aaSB06MnYwN61YjtXxLtG5UW/d7bnDMmmlhy1rJg93Qyw48LVVG0Wg0SElJYctaKSXAVYEutX1ROdAXnUdMAwBEp/CMKcMwOSORSIrVutLg9ZGwd/XC8c1L8DgqCS8TVXnKDMlukKaHrWolC14ypezAyloZJTk5GQBYWSvFBLgq4OkoR5+BwzB11Rfo8EozcxeJYRgmA00r+6LPxHl4/M/vuPbrD3gWm4wT/4TnqrCxsmZaOBtkyYOXTCk75NsNkikdKJU0ELKyVroRnXjr0f3ZTYJhmDxRnOttNSrnhm3zx+Hm2WM4tnkZUrxqon3dCrkmreGYNdPD66yVLNgNvezAPV0ZJSmJ1txiZa10w+tfMQyTX4rKuiIWxs5sNXsSo0T7Ue8hNUWJm0c/weNoJWyschZP2LJmWtiyxjCWCytrZRRhWfs3OjVP8QEMwzBM6acoFaDsYmzCopSoVbk8Oo6agVtnv8HzW5dw5k4Etp9/iGNXnxodozjBiOlhRY1hLBNW1sooQlmDlS0HpzIMwzA6isodLrsYmyB3BQLdFBg9egxqNW6Jw+vmIy4+ATefxSMsSml0jGLLmmnhbJAMY7mwslZGEcqai5MDB6cyDMMwOorKwpKdW7bY3qicGxas+BipSXE4vXsdYpNVSNdojY5RHLNmenidNYaxTLinK6MIZa1VdX+OZ2IYhmEAmNeqEuCqQLN61TFuxjycP74XcQ/+wfWnsfjnSVyWWDe2rJkWtqwxjOXCyloZhbNBMgzDMJbG5UcxcGv0Gvyq1sOJzQthL1Pj3L2XWWLdOGbN9LBljWEsE1bWyiiPI6IBANEqMxeEYRiGsSjMmsJdC8Sr1Og3bSlS4yLx1+FP4OEoR1JqegZ3SLasmRZ+lgxjubCyVkZ5+jIOEokELxLV5i4KwzAMYyFIJBKzWlcalnNFq0oeqFOrOoZNnYPz3+xB6qNrgJayRgpXSI5ZKzpYcWMYy4J7ujJKemoKbGztILeWmbsoDMMwDAOA4tZ61PdHVW9H9B06BnWbtsaaeW8jMSEWylQ1LofG4ML9SKSp2Q3S1LAbJMNYJqyslVEiYuJhI7fD09hkcxeFYRiGsSAsQWAPclfAwdYan2/dhmRlEtYsfA+PY5SABFCmqpGals7KmgnhBCMMY7mwslZGUSUnQ2Zji7vPE3hRbIZhGEaHWWPW/kOk8/f190e7Ue/hyulvsWvPPtjIpFDYyCCTSlipMDGWoKQzDJMVVtbKKM42Gtgp7BDoruBFsRmGYRgAlmdVCYtSonOPPvCr3xa/7VqJExdvIMhdAZkEHLNmQkS9s8LGMJYH93RlFJkmDZ6uTghyVfCi2AzDMIxFEuSuQN1AV8z7cA0kMit8s3Eh/gyNRkqaGteexOLP0GhzF7HUYAkWVYZhssLKWhklKSkJLo4OaFHJgxfFZhiGYXRYktAu3CHrVgpE90mL8OjaeRzZsx0pqelITdfiSliMuYtYKmDLGsNYLlbmLgBT/DyJUeJxRCyk1nJzF4VhGIaxIMyduj87gtwVaPrKqwi72h8HPvkQVjIZ5NYy1A9yNXfRSg2WWO8Mw7BlrUwSFqWEUqkErFhZYxiGYSyfAFcFBjQJwrLlK+EfEARlUhIqezuhUTk3cxetVMDZIBnGcmFlrQwS5K5AmioZ7i6O5i4KwzAMY2FYqoUlwFWBKgEeaD9hKaRW1ngcl2buIpUqeJ01hrFM2A2yDBLgqoCVNg0eLk7mLgrDMAxjQRi6QVqihSUsSgkrz/LoNHsr6taubO7ilBrUGuBZbDJS0tSwt8B6Z5iyDCtrZZAnMUpExSZALbU2d1EYhmEYJs8EuSvQuJwbyns2QduqXuYuTqkhVa1BWroGKWlqcxeFYZhMsBtkGSQsSolEpRLPEjW8IDbDMAxTYngel4J0jQZtq3pxvJoJsbGSwkomgdyKxUKGsTT4rSyDBLkrkKJMgqODPS+IzTAMw2TAkt0gr4TFIC45nVP2mxhrmRS+zrawtZZZZL0zTFmmTChrKpUK7777Lvz8/GBnZ4emTZvip59+yvPxBw4cQPPmzWFvbw8XFxe0aNECv/zySxGWuGgJcFVAnaaCj5szL4jNMAzD6LDU1P2C+kGucLaz4pT9JobXWWMYy6VMxKyNGDEChw8fxttvv43KlStjx44d6Nq1K06fPo1WrVrleOzChQuxePFi9OnTByNGjEBaWhquX7+Op0+fFlPpTY9Wq0WyUomawV68IDbDMAxTYmhUzo3dH4sIS7aoMkxZptQra5cuXcL+/fuxatUqzJgxAwAwbNgw1KpVC7NmzcKFCxeyPfb333/H4sWLsWbNGkybNq24ilzkpKSkAAAUClbUGIZhmIywdaXswQoaw1gupd4N8vDhw5DJZHjrrbd022xtbTF69Gj89ttvePz4cbbHrlu3Dj4+Ppg6dSq0Wi0SExOLo8hFjlJJcWqsrDEMwzCGWHrqfqbo4HXWGMYyKfXK2pUrV1ClShU4OWVcU6xJkyYAgKtXr2Z77KlTp9C4cWOsX78enp6ecHR0hK+vLzZu3FiURS5yWFljGIZhzMmTGCUu3I/kjMQWgqFizko6w1gWpd4NMjw8HL6+vlm2i23Pnj0zelxMTAwiIyNx/vx5/PLLL1iwYAGCgoKwfft2TJ48GdbW1hg7dqzRY1UqFVQqle57XFwcACA+Pr6wt2MSIiIiANAsmqWUiWEYhjE/arUaajWttZWQkFBkY8St0Cgo09RISkiAk8y9SK7B5B21Wg2VSoX09HSkpaWxbMAwRYx4x/JkzdaWcipUqKDt0qVLlu3//vuvFoD2o48+MnpcWFiYFoAWgHb//v267Wq1WlujRg1tQEBAttdcsGCB7lj+8Ic//OEPf/jDH/7whz/8yfx5/PhxrrpMqbes2dnZZbByCUSSDTs7u2yPAwBra2v06dNHt10qlaJ///5YsGABwsLCEBQUlOXY2bNnY/r06brvGo0G0dHRcHd3N4l7QXx8PAIDA/H48eMs7p2M+eH6sVy4biwbrh/LhuvHcuG6sWy4fiwbc9SPVqtFQkIC/Pz8ct231Ctrvr6+RtPsh4eHA0C2D8nNzQ22trZwcXGBTCbL8JuXlxcAcpU0pqzJ5XLI5fIM21xcXApS/BxxcnLil96C4fqxXLhuLBuuH8uG68dy4bqxbLh+LJvirh9nZ+c87VfqE4zUq1cPd+/ezeJ/ffHiRd3vxpBKpahXrx5evnyJ1NTUDL+JODdPT0/TF5hhGIZhGIZhGAZlQFnr06cP1Go1tmzZotumUqmwfft2NG3aFIGBgQCAsLAw3L59O8Ox/fv3h1qtxs6dO3XbUlJSsGfPHtSoUSNPpkuGYRiGYRiGYZiCUOrdIJs2bYq+ffti9uzZiIiIQKVKlbBz506EhoZi27Ztuv2GDRuGs2fPZsjKMnbsWGzduhUTJ07E3bt3ERQUhN27d+PRo0c4fvy4OW4HALlZLliwIIurJWMZcP1YLlw3lg3Xj2XD9WO5cN1YNlw/lo2l149Eqy39KyCmpKTg/fffx5dffomYmBjUqVMHH3zwATp16qTbJyQkJIuyBlCa+1mzZuH48eNISkpCvXr1sGjRogzHMgzDMAzDMAzDmJoyoawxDMMwDMMwDMOUNEp9zBrDMAzDMAzDMExJhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC8TK3AUoC2g0Gjx79gyOjo6QSCTmLg7DMAzDMAzDMGZCq9UiISEBfn5+kEpztp2xslYMPHv2DIGBgeYuBsMwDMMwDMMwFsLjx48REBCQ4z6srBUDjo6OAKhCnJyczFwahmEYhmEYhmHMRXx8PAIDA3U6Qk6UemUtMTERq1atwsWLF3Hp0iXExMRg+/btGDFiRJ6Oj42NxaxZs3D06FEolUo0adIEa9asQYMGDfJcBuH66OTkxMoawzAMwzAMwzB5Co8q9QlGIiMjsXjxYty6dQt169bN17EajQbdunXD3r17MWnSJKxcuRIREREICQnBvXv3iqjEDMMwDMMwDMMwZcCy5uvri/DwcPj4+ODPP/9E48aN83zs4cOHceHCBRw6dAh9+vQBAPTr1w9VqlTBggULsHfv3qIqNsMwDMMwDMMwZZxSb1mTy+Xw8fEp0LGHDx+Gt7c3evfurdvm6emJfv364dixY1CpVKYqJsMwDMMwDMMwTAZKvWWtMFy5cgUNGjTIklKzSZMm2LJlC+7evYvatWtnOU6lUmVQ5OLj44u8rAXi22+B0aMBjQaQSICPPwZeew3Yvh1YtChv55BIAK1W/78hs2cD06frv6ekAA0bAi9e6LfVrw989BFQvjx9/+IL/bUlEtN8xLmsrYGKFYGaNYFatehv+fKATGb8vmxsAKtS9Iqo1cbvtbCkpwMdOgBNmwJLlmT/zBYvBjZs0LeXli2B996jNmBjA2ROXTtlCrBvn74epVIqf9u2wNSpQKNGpr+XgnDkCDB+PN2XVKr/yGQZv0ul9Gz8/IBKlehTuTL9rVABsLUteBlCQ4FRo4Du3YHhwwF3d/1vU6YAX30FBAXRO96kSaFvOQuPHwOtWwNJSXSfU6YAc+Zk7RNyY+1aYPlyek4yGf11cAA++ADo2VO/X1wc3Ud8PBAYSMfVqUN9DEDvuo2N/m9e2bqV+i2JRF9/hvUIZN0mk1H9dexI70GlSvm/bwBQqah/fPmS7lt8rK2pn6pdmz61agHVq2dtL9HR9C4K5HI6XioF7OzyV5bISHqffXyAHTuonZY0Xn8dUCqBwYNpXHNxyb5vUquBZs2A8HBAoaDn26sXHWf4LmXm9Glg0CA6Hsj4rhv2W4Z/AarPceOAHj1yH2Oio6ku4uKorRm2TamU2vegQTTW5iFRgUXzyy/A0KF0H61a0fvUrh3g6Vnwc546BQwZQnJO5nfa8K+XF9VL5o+fX9axqSTw0UfAkyfAG29Q2y6qe4iOBl55hfrAYcOAbt1y72/atAHu3qU+ytaW+vA6dehTuzZQo0bhxkNjpKUBYWE0VlatCuSSfdHSKEWSqOkJDw/HK6+8kmW7r68vAErJb0xZW7ZsGRblVdkxJ//8AyQmApMmAZ98Apw7B9StC2zZQi/b0KH6fdPS6GMohGi11MlpNPRdIqGXz9GRlK5LlzJeLyoKuHmThK5y5eh8X38NNG8OLFwIdO4M/PgjXbt3b71Qr9Vm/eRnu9iWmgo8fAj8+isQE0Pb7eyAevVISGrUiO7f2pp+s7UFnJ0BJ6f8CXyWSHIyEBEBuLmZfkBPTATOnKHP//4H7N1L9ZuZ8+fp+l26UN0fPw60aEGD8ZQp1A5sben5W1vT+apUISE4PZ3aV2oqcOAA8OWXdOzUqdRWzKlUX71Kz3fkSGpnGg19tFoS4sT/AH1//hw4exbYuZOOA+jeAgJoMqFSJaBaNRLKa9QA/P0zvneGEySC338nwfHcOVKS+vUjYbB5c+DkSaqP1FR6ZosWkZJsSsU9NBR49IgURqUSmDeP6mzBgvyd588/STkbNoz6C5UKuH+f6njZMmDWLLr/R49osB87lp5/69akpM6eTe07IYGerUJBgoB4p/NyfZmMhN/UVL0CrlDQfQllSKWiNizq+N49aovp6XS97t2pDlq3zvtzDg8HbtwgJcPfn86rVtM5X74EDh0CVq2ifWUyUqCE8lajBn03FGpjY+kerK1J6XJ2zmstUFkePKCPGBOGDMn78ZbA8eP099Qp6uc7dgT696f+x8kpo/AaE0N1378/vYe//UZtWSolQbR3bxoPMz/Dy5dJiZo9W/+8xcSgUAQA/fur0dB+Fy8CffqQIjBrFrXjzMJpairwzjvUZ96/D8yYQe0wNpbOK5TxiAh6NzZupPduwoS8t3dTkN1kbUG4coXe+169qD/bto22169PiluHDlQf+RmPr1yhZzZvnr4/1mj0/4t37Plz4M4d4IcfMk4o29gAwcHUh5YvT31DmzaFv9eiZvNmajdr11I769WLFLfWrU07Xj5+TP3WjRv0zjk4UP/XpQu9c5k921JSSE544w1SmlJSqJ85dozKCtC7ExxMz7tcOfr4+gKurvQREy9iAkStpj4/Lo4m8F68oHI9fkwKq/grZFV3dxo/3NxM9xyKGFbWciA5ORlyuTzLdtv/OtVkIWhlYvbs2ZhuYFES6TktDrWaXqyhQ4E9e/TCwY0b1EmOHEn7paWRkmNjk7WTTE/Xz/ap1fSyODuTMJqURL9bWZHgFBVFx3TvDrz6Ku0/aRLw7rs0EP31FwklderQNoExRQzIaDkT3w3/ZodWS9e5fRv4+29SKnftosHOxYUGhK5daTbq+XMayF1d6b6KcxA0Ja+/Th3V4sU0a+zqaprBFdALsKNGkbJdrx5ZKP6L89SRlETXnjiRhN1Jk2j/jz8mBb5NG7JQ1alDbSYykhS5oUPpWJmMBJpp04CffgI++4yEKz8/Eu7HjCFlp7hJSaFOf/JkEqayQwgFhgLCixc02xcWRgrI48c0mbBrFwlrAAmWwgonPpUqAd7e9LtEAty6Re/m+fNk6du7F9i9m4T5R4+At94ihXjRImD+fHruBw5kHUgLimgDAwbQIOvjQxMwTk5UX3klLY3ub84c6nNSUuh93bWLFMybN0kBfPyY9n/7bdp/0yb6/ccfqV20bk2Dc0IC9Tve3nlr76mp1J6mTycBz8WFzmFjQwK/RkP3lphIfYhKpZ/8iIgg4f3PP8lrYfNmum7fvsCbb1K7zomkJPor3gUhvMfE0DN1cCBB5MYNmmgTn48/ptltgNpFmzZkta5Zk9qjVErKl0RC9ZEXRB/7yy80qTB0KPDHH8Dq1ZbTB168SErV2LFZZ/KFpWvrVuoTjh0jQfLYMXoGbdvSc+7alQQ38fzGj9cL4uHhwDffAIcPkyI+cyYdM3o09UtSKR3n7U0K18OH9Lw1GmoX4p0QQqWYhEpKom1Xr9Kk0zvvkBK+YAH1oUK5v3ePxiTBBx/QfT18qB9z3dyoL3//fXq3p08nz5itWwvuefDjjzT+e3qSQqhW00RFfDx9EhL0/4vvajXdu709vTMBAfQpV46U/Xr16P/c3sHERKoPcd9PnwI//0yfXbuAlSvpfevUiayeXbsCHh65n9PNDZg7N+/PICmJJqAePqSP+P/oUVKATp3KuL94RpZk2UxPp7bati0pvseO0aS8pye14zfeoHZc2PdZjFM//kh1f/w49X/799P2evWA9u2pHK1akYwI0HjduXPGcyUmAtevk1x2/z4982vXaFJfyI95QS6n9ufnR38bNKB+28+PyhgdbTn9WB5hZS0H7OzsjMalpfznamOXjalXLpcbVfIsDmEps7WlwUSrpZdDq6WXSiCTUcOOi8vqjmA4QyOT6YUbrZaEjNBQOjYlRS9gOTlRZ2hjQ53cypVA48bA0qW0X9++esuXmNk2VMTE/5mVOEFmq4NWm3WQsLamQaRhQ+o0pFISeH/4gT6HDtG99u1Ls6oqFd2/uzt1yKaySpw+TQP95s1F69Z3/Topnteu0aDfuzcNcqmpdC+FsRwKoaRePRocli6l5/bWW+SKIRSYpCTqONPS6Bmq1dSJd+hAHf2GDSTst2tHik98PLVNlYoEEoDaR2QkzbR++ikp3AcP0uC+fDm12xEjyKphbOBMT6fjhYuctbXe3aygpKbS+VQq+hi6sBnOrstkWduNiwvNLgqEZS41lRS4O3dIaLt/nwawr7+mawB0f0Jxe/KEBBIXF5pkGTqUlL49e+hcbm70Tr33Hj3zgQOpvR05Yhq3SEM3MJmM6i8piYRHe3tqC3lBtKXUVDqX6E9Gj6bnNHUqKSv9++ufn7he06ak5L3+OtW/cMOMjqY2mBdFRdSlQkF1ERdHbS8ujupFoaB6dXEhBSE6mp6rRELCQNeuJOy//TbN3J46RcL+xo00+fPWW1R2Y0q9Ukl/vb2pnQtPBUA/I+zkRNbS5s31x2m1NDP944804XXxot4iERBA9duqFdV37do06ZTXiZrERHrPmjShZ3/rFrnUWoJQum0b8Pnn1MesW0cCqLgvofgqFOSeNXYstaEHD0gBPXmS3hMbG1Jsq1Sh/VUq6ietrakt9OxJroo3b5IAeuwYCaFBQTRu3L1L7UOMRcJ9XvSnWq1+giY9nSYtNRp6J5o1o35s1Ci6j7feookG0VbEGLhyJbU5W1t6FwBqB2lpNEGQmEhj1eefk7I5Zgy9C/PnkxKXX/e3PXvoXj089BY8e3tqN87OdC1HR73XiaMj7adU0icqipSsu3eB77+nSQ2AnlObNtS/t2tH1uDM7TAhIWPb8vMji+6gQfTc/v4b+O47Kt/w4XTdZs3ovevWjfoIQ/kAoHfU3p6ek8DQRVX0WYZ9s709TXbUrJmxfJMn05idmS+/pPpbtozefUtwmxQT6c2bUzubMoXGkjNn6Bl+/jn1Y6+/Topbx44Fcz0U41F8PNVX//5UX3FxNJly7hw9n9Wr6blUqkT7u7rqZVDxsbenttusWVaZLj2dJtBiYuiTlqaf9NRq6VhbW3r3xCSD4bgkxnpra711ugTByloOiEySmRHb/Pz8irtIpsVQIBAK2bVrJNiJFwrQC03JycYVH0OkUurEHR3pZZVKMwpAAP2fnk6DgXihRo8GQkJImOzQgQbDzD7/QMa/xpS1nJQ3Q9dItZpedpWKyqdSkfvSW2+R5efff0nI2ruXZu1feYUG94YNaYByd6fOoSDWKeGSKZcDFy7QTHyrVqSwCWumqVGrKXbjyRNykzl7lmZyRacmBl07u/zfkxCwra3JVWHNGupwly+njnr/fhISk5L0M+A2NhQjkJhIHWeXLjSAC8tIr160n7d3RtcjhSKjoNu8OV1rwQIagL76ioSVqVPpnH370oxeUhJZUBs00A8uwo1XKG1OTtTZC0Urr89BtG9XV7o/pZLeLTG7bijIGQoImeMqBWIf4XbTubN+P7Wa6vDePfrcvUuC5L17NMAZPpvu3emTkED3KYSmwECyTI4ZQxaoTz8tfLsTg6K9Pd2/kxNNQiiV5I5pb0/tLy/PUqOhwVgup+cqJnZataL6HT6cFDEgY9vw96cYx59+ovr/6SeyhnTvTvcul+uVn5yuLwZ1Ly/6npBA13n+nKxbArmcFDRHRypvfDwdJ4TNOnVICRg3jt7zgwepn5s+nSxtkyZRPycQgrinJ137+XP9JIJQ1owhkdC9v/46CbaOjiSg/vorvU8//URKOUDladuWhNu2bbNXukSfGRdH7W3wYHLN7dmT3tPvvqMymhO1mhQxPz+afOrYkSZ8qlTRK2t2dvrxSyaj7xUqUD//8iUpbidOkOAqkVD9xsToxyVra3r27u5Ub+PHUz/y7bfUvymV5CUi+oDYWKoz0dYkEuoL0tKoPMJFUqWiv3I5CdIrVpCQu3w59WmjRpESCdDEi7CAK5XUR8XE0L24utK9Pn5M43adOlS+Dz8kS9vFi6R8icmuvKDVkiJ18CB9F/2Y6CtFzJy9vd7dU0xKiX5A9GFaLfDsGSlZly+T+9uMGfS8fH31StYrr9B9RUfTfT15QtdUq/X9p0ZD7XXAAHpWL1/SOHb6NMVKz5tH71NICLXt+vWpfOHhVDePHmW9V0NlTdSboSu+jU3G/tnbm7whMstBYWFU1nfeoXdj507zx0Slp1P5RZtxdNT3SRMmUJs5dYosYbt2Udvv1o28VDp3zrsyIyxr1tZ0DSsrehZyOfW9nTtT+3/8mKzzf/xB17KyIuOAsfwCAmMT71IptXXhzipyLgD6tii8cIxNqhvKjSUIVtZyoF69evj111+h0WgyJBm5ePEiFAoFqojZuJKK6IDj4/UJHi5fJoE2swApOuboaPpNoaCXQQgRmV9sOzvq5A1nasSApdXS746OGYVLX18S7osbobilpVHHk5REyur06TSTdvYsuZWMHEmD2PDh5Ibh7U2dRn6tUn360AC2eDENJBUq0IA/ahQNtOvW5S5UFuQeAwNJqdm9m9xuLl6k761bk7UpOpo6UWdnqu+8Wg+FsubsTAODiHesW5eU78aNyRfdUFkTHaqYnU1LI6GmXz8Sun7+maxIDRuSwKhW6xN0iIFVKFRCGBs8mD4PH5KgcewYKdxeXjQxcPMm7Vu7Nj3vNm3of4Dq/elT/fllMmqbdnbUhnOqD5VK7yYnfOrFTKAQODLHR4jZdvEBMk4qGG7LPNng6Un306xZxvoFslqkraz0M/3CRUsk4di2jYTEUaPI4rB4ccFdY8X1ra31ligHB5rdVyrpnbG3z5gkxBiiT4qOpv7B15fOHR9PxwcHk9V77FgSmkT/YugaPWgQtaFp00ipO3aM2rmtLZ0vJyEkLU0vkMrl9I4/e0b3YEzZEwK+QqF3rxGJIOzsaHtaGgmPLVvS+374MMWArV1Lz2PaNIolFAqGoyP1K6mpdD4rK/pra5v7zLeoPzc3sgj16EH1fe0a9WN//EGufZ99RmVs0oTehVdfJSUh8/0JV6GnT8nKcOoUuZ+1akWKjjkFUo2G3oVNm+jeVqyg+L1p08hyDOj7G2FZdXWlScfERHquffuScKpUUt0YxtqKyUzxzghFrFUrUgRmziQrRf36esXO35/6g6QkageiH/Dy0reF5GT9OCPCBBQKah+7d1N7/egjivsGMipaGg3Vkaur3qrr5ETXiYykc3p5UXtv1ozehVdeIaX9v1j7fGHY5jUaKr/4+/Jlxnh1qTTjpIJ4zzQaUhCqVqXyJCeTBfjcObJwbttG9dSyJSlpjo56mUQohsYmbR0daewcOZLOee4cjRsnT5LyIdxdHzygccaYwmoYv5aeTvUs3O2EwubgQOWTy2lMi4ykSZFPP9VPdiQmUtvZsoXaU+3a9LvwADAHajX1Fx4e+klRmUw/4eTvT+P02LFkof3hB3Lz7NaN5J/Jk2lsMJygMoZQ1tzd9XG9hmO1kPXc3cn7ZswY/RhnLO9AdoqUYRvIPOlpiDi3Wk1lMxx/hZJtZ1fikseVrNIWIeHh4YiLi0PFihVh/d8A1adPHxw+fBhHjhzRrbMWGRmJQ4cO4bXXXisZro45IQRgGxt6qdVqUtaMzYBbW+tjZJRK6rCkUuoExAyara1+cLS11QuFAiHUa7V0vvxmKCsqDGdiAOpUhPIQH0+K2auv0uzgtm0UT/fJJzQ7/sYbNAhmDljPib//pgGkc2cSqsqXB9avJ8Fp4kSKQ/n669x98fODqOvAQJrdb9SIhPNRo8ht8L336P6TkvSCsa9v3pRGw9gMHx8SouVyusbevaQYTpxI+4g6N3xWhq5DDg4k9PbuTc9duBcKpVgIOioVtT2tlraL+pNI6Hm++y5Zdq5eJavCsWM0I9uwIQlY27aRsOzsTHXbrRspb9bW+o49JkbvMunmln3Mopglzxw/KQb7vJCThTinxDmZz2E4UAm3q5QUvYudeEcVCto+cyZZJpYsIUFpy5aC+fKLNiCTkVAkl5MA4OBAs/zJySS4fPstWc6zIy0t40SQVErnS0jQC2hSKSnjIvbBEFEHHh4k+PbvT5at3r3JkjVrVs6Z5YRlTZzHwYHa9NOnVLbs3nGplMpmb0/vUGwsPfOEBDqfrS2dy8mJLAujR9OM9t69euFfTByIe/Tw0LvNpaRQGfz8jPebOSV5sLUlIdPDg2a67e3JlfTaNbLqb95M9W9nRxM3r75KE3YAtSPhMvzyJT27X37RW8LPnKEymQND4atbNxLMN22iGL5PP6V9xGSgqDdh+RQKcUIC1ZVEQn1jQgK1XamUnr2Njd5tWyhICQl6xbljR701HaC+S1iYxHuXkED1bm+vL7uYIExNpXacmEj34+xM429ICE3aPX5s3EvE3Z3ak1DYrKz0VrYnT6iu27cnBaZDB6rXs2dJQM/Lc5VI6LkIbwMhHGc3HmT2HjDso4R8IHB2pvrq1o2237tHyuSPP5Lbd8+etI+hQC/cSDM/C8O+sWVL+sybR+37zBmyut28SRY8MZGVGcOskMLlUyaj66Wm0hggZJa6dckKO306TawePEjvblIS1Ue7djR+jxtH483Bg2TtNcc7Iia+vLyovSQn09ielKTv5+Ry2s/eniY4xowhV+etW8lKuGQJyQbjx2cvrxnGVovEcSqVfqxOScloIRV9lKHiBWSfcyBzQq3M46BhAq/MFjapVD/ZKuQE4QrJMWuWx8aNGxEbG4tnz54BAI4fP44nT54AACZPngxnZ2fMnj0bO3fuxMOHD1Huv9m1Pn36oFmzZhg5ciRu3rwJDw8PbNq0CWq1umRke8wNkcrdxYUa87Nn1NGLgdoQw+B04fObkkKDgqMjvZixsfqZYBGnZoiwrDk75z3g31wYzqoJpa1hQ+qsHz+mDvj990m4ffNNmk3z9s6bz3dKCilJfn6kMHh7k4vG66/T7GOfPjQr+v33+liKwiLq2taWBmwrK1JYjhwhZerHH+lvmzb6eMOYGOroc1NCDd0g3d3pOuHhdB5vb4pha9qU/PkrVMhd6HVyoueekEADpbDWiMFCDNxiJlTEE4mZQxFXJJHQQFq/fkar0aBBdOyVKzSY//ADPQeFggbbzp1JCBMudikp5JIWH0+WhMyWVOECVRgf+LwmxykI6ek0eIokAYbPyd2dBmg3NxJynj0jy09+Y5KEZU0Mkh4eVP8REXSulSspZqJHD5r5bt3a+HnS0qjuDAU/hYLqIiaG+ioXF72bTUoKtYvslJXu3cmCPHs2uecKlzfDmC9DhHuyIU5O1L6eP8/ZHRHQK20ODnSu5GRqx0JoF65W/v40oz1sGCk/u3bRB9A/exsbUo4eP6ZtiYlUP/7+WfuZ3Nx6bG2pv3n2jIS12rXJStmvH9XVgwdkNTt1iqyRr71Gxzk7U5tRKOgdFK6e33xD+7RtS0JxQaw2hUUo8y4u+knDd9+lNrZ6Nb3bwlXT2LsprEbOznR8dDS1XSFg2tvT+y5SvtvY0Lb4eLK+KJX0XaMhRdYwFlC4Cdrb07uV+fqGE4SOjvoxJjaW3oHAQOqPk5NpbHBxyWrhEG649vZ0feEaaWNDE2YpKTRxde4cWdc6dSI3xNwy4In79fLSWxTF9YTCJDwJDNtdcnLGGCTAeH9maBkBqB2OHUsKQVQUnUPEFBlb9kCcw/A3wzqWSMhS3aoVWfbFpJHozw2VSTGxJRRntZr6StGfiVhBEbqRkkJj81dfkTLTsiUpNomJ+vpxdSXX/zfeoD6venWy+r71VvHGSQmrrUSScZJC9EtxcdSGhQVOKqU26OtLY/Z779Ek8qxZ1Hd++CFZ4jLfgwgrEJNSok0D+rFaWLcMPUwMPUuMTURmnpTMbFHLbokcQ1dIYZUtBZQJZW316tV4ZOCvfOTIERz5z4d/yJAhcM4mpbFMJsP333+PmTNnYv369UhOTkbjxo2xY8cOVDVMClBSES4/Tk70Ml+8SNsbNsz5OFtbGiTkcr0ALQKQDYWSuDjqfEW8gFDW7O1zzppnSQiTuZ2dXmCUSmkgnTKFOrP580kAnDCBXDI8PHJ2IUxOpmcwdizNZonZnogI6ihPniSFolkzsrAZWT4i3xiusSYsYFIpWR6aN6fOedAgEt4WLKA2ERVF++Zm4RP1Ks7v4kLP7flzfcB4nz4005tX10oR+6hQkHBpKEALa7Bw7XN11WfjErPUIuBYzJ5l9oO3siJXj6pVSVkR/vs//EAWGBsbmt3u0oVmpl1dqe7j4uh5GJ5PuEFa6qAgXEaF4Ciek0gE5OBAs8Du7hQc3749tUEXl7xfwzCQG6BnIdpNRAS1p7Vr6R3p1o0EfGOTQqJPSknJ+EydnanM4nexZIhwu808a2uInx9NFHTponf7nT6dYnoyzxanpRmPRRVjRF4D8IUbpVAGhAKQmKhPxCD26dqVlMq//iJlylAoF4qfSkX1ERtL75WfX8ZJg5wsawI7O1L0wsOp7l1c6N0KDyehfsYM+ohlHgB6zr6+VIdqNd1LcjLVweHDZLEUFjbheVFcCAuQsIpFRpKwWakSWQujovT1ldNzEZNBTk60n7BIa7VZFXehHIoU+tHR+sQz2bW/3Pq8zGNMXBz1NcLSJpIiRUZmdcUVk6gKBR0XHU3tTCxfkZpKStePP5Ly8vrrNDmQF9d9JycaJ4R1PjGRric8MCIjM96b6IszC+ACQyFcCO6G8eMajd4C7eamz2SaWbkzFuebE/mJrRQeCSIsQqnUKzaiPYj47l27KMPk4MF03w0a6MdZiYTG0g4dSNkZP56SbHz6KbnqFgfZrasqxk4nJ731NzaW7lO0RTFGzpxJLuwff0weOJ9+SglwDGVEw5i1zIixmik0xajmm4/Q0FBotVqjH2FF27FjR4bvAldXV2zduhWRkZFISkrCmTNn0MhSFuMtLCJDjlyuD8R1dibrR05IJPpsaIZYW9PxAQHUUSmV1JlFR9MLLSwwpl7ssLgQMS/BwdTRBQRQbMGPP9JM9ezZpPh8/rk+/sQYKSk0EIk4FHt7qgM3N/0s2L59FAzcvj118oVFzEILZDISrvz86DqbNpFA+8MPNFt+8iSVMSLCuLuZIYZukAJnZ70FLyaGOn9h8QoIyLvlxtpa71qUHeKZiToJDtYnxImNzbhQcFoaPXchZLm70zG1atHM5969NPs8bRrd+7RpZE0dOJD8+W/cIIHacNmOzK5zloxMRs/e35+C8Z2d9ZafTp1oAeS7d8nCKhKS5AXDmWhDNxcPD7IOJSTQs16/nvqXzp3J5SkzaWn6mBzDWVERc2T4XsnlJJwbc4MxRCiOjRvT5MeECSR81K1LdW2IsJIac8VxcSlY3yWUMvFOlC9PbdTTk34Trnjly9P7ntmCIJQ1rVZvBXrxImO7Ntw/J4SFzc6OlBkxBjx7RsJ35vhJiUT/jgjXOFtbfaKfffuof+jYUZ/+vrgQFiBAbwXz8dFbSXx8qEwqVd4micQMvY0NPeecJitEgqSgIGqXIntpYbG1pX5ZnDc+nu7HxUU/GWqsjq2sqJ4CA/WWRpE86skTamvffEOue2+/nXMZDJVOEePk4UFtNjiY2rCfn34sFO05KIj28/KiZ+/rS/uJj78/fUQfXaECfTIvQl2uHI2FwqIlEv5kF6NkSmQyem4ODtQH+ftnXOfL2lo/IW1nR4rLrFl6b4XQUHqPhLLv6krywOnT1J/Wq0exYMXxrmSnrAmEYubuTvcXHKyf+ExOpuegUNB9L15MSVNiYqgfHT1aH9snlDVWyoqUMqGsMdkgYoUAvaBds6ZpOsPWrckV4LvvaEY9MVEv4JYwX+EsKBTUiYvFdn19SQg9cYIGrPHjye3v0CG91ckQlUo/AKpU1AGKDk8kqbC1pZgFsRjr6tWFK7OxjlvMEvv60gDauzcN6PXrk+IyaZJ+Jj+nwcWYsgbQPQrFTChNEklGi5epEW5zfn56ZSQpiZ6x8NW3t6e68/XVu9UFBuqFkfr1yery/fc0yM6bR+detIisCN26kYvIzz/r0/WXFGVNIOrBz4/u2c6O6qhePcoe9/QpvcNPn+btfIYxa4bPQSolQdHdnQRPb2+K9xTrGYrlPAzPI5PR/pljy4TFVlxLLtfP+ufmBiiX610zp0+nd9PVlaynM2boXbaLQ/G2sqJ3w9NTLwh6e1MdGLu2cIETcXsuLqQghYfrJ1JysixmRrhh+vjo3ZTs7Og9/y9UIMvzFAq+sChZWemTNuzaRe2kc2eq4+LC2ASUhwe9ywoFlcXBIet+pkSMBUFB+cu4mNfzijEmJobaaG6xNmJC0c9Pb72ysaG6rViRxqnNm2kttuzIKcGD6ONF+xXJdRwcCracjUggIiaNxULfloTwSnB31y+OHRBA952aSuPz3r2ktAE0kfLoESnJ8fFUByEhFMu2fDkpPWJtSGMTLqZCuEHmBaGUCwVcTLQmJlL5HR3pHo4epbHv0CHKDrt1q34NVFMtZ8QYhZW1soyhAC8GgOrVTXf+Xr3oZd61i2aXRGrq0jADI9xPgoKog9NoaGDdtYvcg+Rysi62bk1CvRgARayViDcIDtYrbSJeQSRScHUlRWHcOHJHePfdgqeczWmWTSKha4kZz1WraEC/dIlctI4ezSgYZsZQUM+MXE6Cg5ub3s2iuJQaobSVK0fP2spKP8vu7EzP3VDwEdYPBwd9/TRsSO4fmzfTgtNr1tBAtm0bKRvBweS+JpISlDSE5SYgQJ95sVw5mmiJiaH2++BB7ufJ7AZpiFSqD3IXcX+ffkptuWNHmokWCDdHa+usrtIiq5iwrslkdA6lMm9ugCIbYFISWdW2bCG3yA0bKBnOlSv66xcXUindp4cHPXdjiQgMYwBFvKdwyY6I0Fvd8oOwDAmhLCVF74InXMGAjM9TuFEKd0ytVj/Zs307WWS7d9cn2yhqRNKkzCgU1Ma8vbPGUBUFYizIJpyi0OcNCtJbNlNTc69rkZQnIIDqLDmZ/r58SW6QI0dSwidjlm0mZ4QbqJjgK1eO/rZoQe9ucrI+iVNSEqX0Dw3Vr8U4Ywa9Jz170mRogwbklloUZPd+5IZYhkZMXgp3SZGhc+JEChlo1Iji9RcsKPkT8CWAEihdMCbDUIAXf02prAE0MKxdSzN6e/fSttL0YgsrQFCQPrtYrVqUfXDHDhJqOnQgF7M//tAH44q4A0O3F1dXvf+4SAXt5kaBzDNnUpKGUaPyPxsnZt1z67jFbK6rK8U3nDpFZZ89m+Lr/vwz48KiguwsawIRI+fuXvyKuqGrh5gVzWuWTaE0BwXRx8eHlIu1aymj5/79FAfl5kazjCVRWRMYtmNHR7rXAwdIOAwJoUW5c8KYG2Tm8wuFLSGBZvk//ZQUtS5d9BM5aWnZB4ULq5Lh0gZyOSkY4r3KSSgXbpkiU62TE6VuP32ayt20Kd2nuaykInbVGPb2evc2sa+bm36SR5Dfctvb0ztvZ0fPUSgc4nlmxtqa2oanZ0YXvYoVaULur79oki67401JThYzmYzK6O+vz65ZUhFJwIKC6H4Ms0rmhOjPRZyqWMT93XdJkRsyxLjnR14ttIx+gk8obmI9PBHf5+hIz/PpU7K2RUZSXW7dSpOhDg6UfbVDB/puKoRreGGslFIplc/fn8ZOkUQoNpba4CefkJXQzk6fNZQpMkpwD8YUGkNlTSz+bWplDaC4n3nz9AlMSvqSB8YQlpigIPo/NlZvVVu/Hrh9m4TBfv30+xtiZ0edoWGsgkiUoVCQn/vSpZSOvFevjDFTuWGYqS83hDAmMpitXUvXDA2l7G/Ll2cUDoGM2SCzQyrVxzqYCzH45FXYMTzO0ZEG5KAgGpSSk8nqtmQJzYwOG1ayBUKBiGny8SHlavduGvjbt89ZYRNtIKeYkswKW82aZLG8c4dm/FNS6Dw5KUsKhX7hbVHe5GR9XGRuQqaNDU2OiAkMuZzK8/PPNCkilDhLE1aF9VtYhwF61vb2eVdWs0PUubOz/t3OyXoj6tHXV++G6uKiX1vqf/+jxEXGFAFTYrgYbnaUhMzDecXaWp99OT/H+PjQMxCZU9PTaeLvyhXqvzLDylr+EZOCIrZPuOIqlXrXe5F0KzSUXCQrV6bEPEeOkPzVtCllMj1/vvCLNhtOnpkCW1t9bJuYWNZoaAz85huaiC8NHlMWTCmQLpgCY6isCUGsKJQ1gAJUJ02igcaU64dZEmImTcRDpaeT0tWzJ/Drr/QM/vyT9s0uG6aY6TaMVRCueyNGkJ/7Tz/RTFxeg5Tzo6wB1MF7e+sXN65fn1w7+/Sh9L1t2ugVbyB3y5ohJVmhMVTahFtSTAw93+J07yxqhNtdQADd6/btJHB06JC9wiZcbnJ7DoYKW2IiDfYbNwK//04ZKUVbz+4cIs5SuIOJhBBiDaW81IGIt1Eq9YphbCxldb18meI1LbEuhfuVoZuhtbU+NXZhsLEhoV5Y1nITFkXiEX9/un5iIim5jRvT5NT339MERmHLlRNFGYtWmhAWZT8//dIUVaqQO9uSJdTmGdOROdmVm5t+MXSR9VOppHjdR48oKdn582SlunWLvFoaNiQ37YImIjGcPDMlIkGViG0LDKR+o1w5fheLGH66ZRlDZU24IQUHF821JBIaxJ8+tbwAYlNj6FIm1ilSqcgl9Px5yiDZrFn2x4tYBdERpqaSMKnRUEzIl1+SG15ISNYEDcbIKZ4op3vw9tavaRUURNbR3buprbRuTe6RKlXW1P2lHREzFBSkX2zUEoX7wiIEjipVKEYvJYXcQO/dy7qvWp2/YHZvb3p2SUkknKxZQ8mIwsNzd0N0cNDH4ojvMln+XO/c3PQxdPb21IafPyflw8HBcuvTySnjMihizSjxjhem3CJZUuYF63NCZLiUSqmPcnCgfmn1aloQ+K23cl+brqCwspZ3hGVWJB6RySjeqEoVyuxn6FrPljXTIJJdidh0Hx96tmJpI2Epj47WJ3T67TeyVPn5UaIyHx/yaNmzx3gIQnbkZwK1oIhlnwyTVDFFBvd0ZRlDZU24hhXl4CcsT2UF4V4UGEjPOSaG/nbpkreOTaxxJuKIxELkLVrQopzPnlF2wtu3cz5Pfi1rhtcXLpEioLpVK8oENWYMJSKpX58GGLF/WUK4GPn5ldwEI7kh2nCdOqSwKZWU9e/WrYzWF8O+JC+CnlSqV9jEOZcs0Qfw52adc3HRZ3AE6P3IT/YziYSsa46OZD0WywIUV3KMgiIWnBXlFMpafrJB5oRIkZ4fRIIakSnSzo4SE334IfDFF5QqvrBuXcYwTN3P5A3DJVWkUuCDDyhL4bJl+n0MF6RnTIPIRmsY+yW8Mpydqf9JT6fJqipVgM8+I/fwVasoRf6QIdRf9elD429u/VRBx/yCkl2sMmMySqF0weQZQwHr9u3chX4m/wgrWXAwCaepqSQU5kd4EVnYfH1pRj0uDqhRg3zdExPJ2nH5cvYz2IXpuMW6aAoFlUPEM02YQFkiAX3cQ1kUnCQSUmYDA0unsgboldKGDSkwPiGBYsxu39a3ufT0jIvW5gWhsHl4kPDRpw+5AvXvn/s5HB3Jdc8wfis/1waobXt50f0lJ+uzHAq3VktEIiHhztCaBphWyRQKoPg/L9jaUh8l4t5sbKg+58+nbJtz5piufIK8xKwxWXFw0K+1V706uat++CElhykKpZrRY22t97rx99e70iuV9A65uenXj1SpyJPmm2+AmzeBhQuBhw8p7t3Tk9zGjx41Hr+eU4ZmpkRSSqULJk8YKmsBAUDVquYtT2nGyoo6WOE6l98kK1KpftFTOzvq4IODKeukVEoz2efOGc8UWRA3yOwQgru7Oy1geuQIJT9p3pyEAKZ0ImLNmjUja0lMDAXD376tX8+pIJZVkdbfw4OEjgYN8pYARixcLASVgloD7Ozo+qmpdA8KhT49vqVib08TQIZuUWIhaFMpLwUR2oUbpYcHCZsyGTB8OGWyXb6cEiSZEnaDLDhiAtDRkdzt3N0phi0qit0giwNra3KDFKn/bWzonRFLYhguyv7iBW3r1w/48Ufg+nWa/Lh9m9ZG9fIiy9vx4/rJq+Jwg2SKFe7pyjJiAVqm+LCz0ytsBUGsIeTpSRY6V1fg66/pb8+e1Jlnjt0xdWYoEXMkFtWdPJmy+nHq3tKNREKCeOvWtJ5gVBRZT+7cIUUhP26QhhgqbPmJvXJ0zLhIdkFxcqJrJySUDOHfcAkDtVqfprsorCL5rUuh1Pv46Ne/mzCBPvPmUbyuqSjoOlIMYWNDFjZ/f2DuXErys38/K2vFiVjzMyiIFDdXV+rPoqOpP5LJaJujI7X38HDaNmwYZV29fp0W4756lbwdvL0pEdmJE/rzM6UC7unKMgWdDWcKR2HjAYT7VkAACSvW1uTHHhRErhHHjmWcdS8K/3Vh6fP317vCsbJWNnB2piQSu3dT3OSAAZTopjCCs1DY3Nzy3ifZ2ZE1Nz/LWBhDZDYU8WslAXv7jAuEmzLOyNANsiCIvsHXl5T49HSyro0cCUyfTvE4poAta4VHxCX36kXvX27rKTJFg1iGw9dXnx7f0ZHen+ho6uNsbKh/VCjovX/8mMbcCRMoDOL6dWDqVFK6R42i85amNW3LONzTlWUM3SCZkoWIhQsIoFl2iYSsHbVq0czawYN6l4qiSuMr4md8fWkAKaqsb4zloVDQ2mt79lAcxbZthe9LpFKa6ff2ztv+ov2lpxc+fklYhEQCJEu3LAjrmnBBNXWK/PzGrGVGZB8UkzkqFcWv9e9Pbne7dxe+jByzZhpE2xdLb7BlzbyILIv+/qS4BQRQ2IRSSYpbaipNUgk3yfBwWrvNxYXWivz7b+DaNXI7btzYfPfBmBQ2q5RlWFkr+cjlpCzZ2gIvX5I74vTpwLhxNPs2cGDRp9Z3ctKvd8WUHWxsgE6daEHUAQNoW2EXQpZK8xfPaW+vXxg7p/XZ8oKdHc1cW3pGSIG9PX0Ke9+ZKaxlzRCx1EB4ONXR8uWUxXPkSHreffoU/NycDdJ0SKWsrFkiNjb6+NyUFOqb4uIovg3Q91lpaeQ2GRND/adwh+SEMaUGVtbKMqyslQ6E25GtLRARQWtWzZsHTJtG7pBt29J+RVnXnFykbGJlBXTrRlnJ/vyz+IUDmYyElcePTdO+3d31lmpLRywQ/uSJadc4Kkg2yJywtycrwfPnNIH00UckeA4aRP3TiBEFOy+7QZqWzEp6SXgHygoSiX5BbVdXUtoSEuiTlEQKmlgfUqWieGKAJkuYUoHFKWtJSUk4e/YsHj16BAAIDg5GmzZtYJ+XDGFM/khJyX9WQsZyEUKRXE4uEAoFZY0aNox+Z8GGKQqkUqBDB6BRo8Jb1gqCgwO1fVO5ApakCSx7e3rfU1NpBt6c2SBzQiz78fw5KWiffEIuWyNHkqI9b17+yy6UNVYqTIPhmn38TC0XqZT6PAcHmlxKSqKQh7g4+k2hoEmcmBge80sRFqWsbdiwAfPmzUNiYiK0BoOFo6Mjli5dikmTJpmxdKWQmBialWZKDzY2FDAulwMLFpCQtGsX/VaShFCmZCHWmzMH1tYkoJQU90VTYm1Nn5QU07khm9qyJpDL9QpbXBzw8cf0ff58ICyMXLjzk/CKLWumxVBZY0oGhm6SwkUyMZE+hhl6mRKPxShru3btwtSpU9G8eXNMmTIF1atXBwDcunULGzZswNSpU+Hs7IyhQ4eauaSliOhoMqkzpQvhFimXA++/T4Lsp5+yYs6UXtzcym4Mk50d9eWmpKgEdrEWm0xGZX73Xfq+aBHw4AFltc1rP8UJRhiGMLS2paSQsiYsbUypwGKUtbVr1+KVV17BqVOnIDMYcOvUqYM+ffrg1VdfxZo1a1hZMxVaLVvWSjsODrTg5ty5lJqZFz1nSityObkAl0UcHCw7Zi0zIl28TAZERgJDh1LGu+nTKXvdsWOU1TY3eJ0108JukKUDW1v6lJTYWyZPWExPd+fOHfTt2zeDoiaQyWTo27cv7ty5Y4aSlVKUSjKTs7JWuhHZIuvVIwsbwzClC5EV0lTrrBUHUing6UlZ65KSgDZtgMOHSZFr1owS1uQGW9ZMCytrpQsrq7LpaVBKsRhlzdnZGaGhodn+HhoaCifObGM6hNsMK2ulH7GODr8/DFM6cXCw/Ji1zBgunp2SQmtKHT4MtGoF9O5NsWw5rd1YVt1eiwpW0BjGYrEYZa1bt27YsGED9u/fn+W3AwcOYOPGjXjttdfMULJSilDWOGaNYRimZOPmRq6FpqK4kkyIxDT+/rS4uVxOmSKnTgWWLAFee43c9Y3BCUZMS2bLGitvDGMxWExPt3z5clSoUAGDBw+Gv78/QkJCEBISAn9/fwwaNAgVKlTA8uXLzV3M0oMYANmyxjAMU/LJTybFnDDloth5xdmZMkNKJLT8w9tvk9J24QItCXHtWtZjWFkzPVotu5cyjAViMT2dp6cn/vrrL6xduxa1a9fGixcv8OLFC9SuXRsfffQRLl++DA8PD3MXs/TAbpAMwzCMMcyRvt3RkSxs1tYUU921K7B3LyVPad4c+PLLjPuzUmFa+FkyjMViMdkgAcDW1hZTp07F1KlTzV2U0k90NHXOzs7mLgnDMAxjKUgk+lix4hbgFQpS2J4/BxISgBo1gB07gBUrKGvk778Da9dSfB5b1kwLJxhhGIuFe7qySnQ0KWocoM0wDMMYYs6FkW1tySXS2ZkUNk9PYMECimHbsgUICQGePmVlrShgZY1hLBKzWdbatm0LqVSKkydPwsrKCu3atcv1GIlEglOnThVD6coA0dHsAskwDMNkpLiyQeaEjQ1libSyAqKiKNtlr15AtWrAlClAgwZAcjIra6bEHLGKDMPkCbP1dFqtFhqDtLwajQZarTbHjyanNL5M/uAFsRmGYRhLxcqK1mHz8qK12ORyoGZN4KuvSGlLSGBlzZSwGyTDWCxms6ydOXMmx+9MEcOWNYZhGCYz5oxZy4xYPNvaGnjxgr67uVGmyJMngSZNzFu+0gSn7mcYi8VipqX+97//4eXLl9n+HhkZif/973/FWKJSDitrDMMwTGYszR1OIqH1QAMCKMY6PZ3i2rp0ASpUMHfpGIZhihyLUdbatm2Ln376KdvfT506hbZt2xZjiUo50dG8IDbDMAyTFXPHrBnDwYEyRdrbAykpFNeW3YLZTP4xtKwxDGNRWIyyps2lg1CpVJBx5kLTwZY1hmEYJjOWZlkzxNaWFDZ3d1LY1GpK988UHo5ZYxiLxazrrIWFhSE0NFT3/fbt20ZdHWNjY/HZZ58hODi4GEtXyuEEIwzDMIwxLNGyJhCJR6ytKVOkpSqWJQ1LrGuGYQCYWVnbvn07Fi1aBIlEAolEgqVLl2Lp0qVZ9tNqtZDJZPjss8/MUMpSSFoaZdJiZY1hGIYxxJItawKpFPDwIEubjY25lO2JOgAAgUtJREFUS1M6YMsaw1gsZlXW+vXrh1q1akGr1aJfv36YMmUKWrdunWEfiUQCe3t71KtXD97e3mYqaSlD+PlzzBrDMAyTGUu2rBni4GDuEpQeWFljGIvFrMpa9erVUb16dQBkZWvTpg3KlStnziKVDaKj6S9b1hiGYRhDSoJljSl6WGFjGIvBrMqaIcOHDzd3EcoOrKwxDMMw2VFSLGuM6WDLGsNYLBajrAFASkoKvvrqK/z111+Ii4uDRizM+R8SiQTbtm0zU+lKEcINkpU1hmEYxhAW1MsmrKwxjMViMcrao0eP0LZtW4SGhsLFxQVxcXFwc3NDbGws1Go1PDw84MD+6aZBWNY4Zo1hGIbJDFvWyh7s/sowFovFrLM2c+ZMxMXF4ffff8fdu3eh1Wpx4MABJCYmYsWKFbCzs8PJkyfNXczSQXQ0YGdHmbQYhmEYRsBCe9mELWsMY7FYjLL2yy+/YMKECWjSpAmkUiqWVquFXC7HzJkz8eqrr+Ltt982byFLC7wgNsMwDJMdbFkre7CyxjAWi8Uoa0qlUpcJ0snJCRKJBHFxcbrfmzdvjnPnzpmpdKUMXhCbYRiGMQZb1hiGYSwKi1HWgoKC8OTJEwCAlZUV/P398fvvv+t+v3nzJmzZbc80sGWNYRiGyQ5W1soemS1rbF1jGIvBYhKMtGvXDseOHcOCBQsAACNGjMCyZcsQExMDjUaD3bt3Y9iwYWYuZSkhOpqTizAMwzBZYcta2UQoZ1z3DGNxWIyy9t577+GPP/6ASqWCXC7HnDlz8OzZMxw+fBgymQyDBg3CmjVrzF3M0kF0NFCzprlLwTAMw1gahsoaW1fKDqykM4zFYjHKWlBQEIKCgnTfbW1tsXXrVmzdutWMpSqlsBskwzAMkx0stJc9hLKm0bCSzjAWhsXErOXGnTt3MGrUKHMXo3TACUYYhmEYYxgK6iy0lx3YosowFotFKGsvX77ExYsXcffu3Sy/Xbp0Cb1790bNmjXx5ZdfmqF0pQyNhmPWGIZhmOxhyxrDMIzFYFZlTaVSYejQofD19UWLFi1QvXp11KtXD6GhoXjx4gV69uyJ5s2b48cff8T48eNx584dcxa3dJCWBgwZAtSqZe6SMAzDMJYGW1jKJuwGyTAWi1lj1j788EPs2bMHzZo1Q6tWrfDw4UMcOXIEw4cPR0REBMLDwzF//nxMnjwZbuy2ZxrkcmDnTnOXgmEYhrFU2LJW9uBFsRnGYjGrsrZ//3507NgRP/zwg27bmjVrMHPmTNSoUQO3b9+Gj4+PGUvIMAzDMGUItqyVTTJng+S6ZxiLwaxukI8ePUKPHj0ybOvVqxcAYNasWayoMQzDMExxw5a1sgcr6QxjsZhVWUtNTYWzs3OGbeJ7QECAOYrEMAzDMGUXFtrLJhyzxjAWi9mzQUqy6RSy284wDMMwTBHCljWGYRiLweyLYo8ePRpjx47Nsr179+6QyWQZtkkkEsTFxRVX0RiGYRimbMGWtbIJ1zvDWCxmVdaGDx9uzsszDMMwDMMwQkFjN0iGsTjMqqxt377dnJdnGIZhGMYQtrCUTTJng2QYxmIwe8wawzAMwzAWBAvtZY/M66yxos4wFgMrawzDMAzDEGxZK5sYKmsMw1gUrKwxDMMwDEOwOxzDMIxFwcoawzAMwzB62LJW9sjsBskwjMXAyhrDMAzDMARb1somrKwxjMXCyhrDMAzDMHpYWSt7sJLOMBZLmVDWVCoV3n33Xfj5+cHOzg5NmzbFTz/9lOtxCxcuhEQiyfKxtbUthlIzDMMwTDHDQnvZhC1rDGOxmHWdNUOkUikkuXQQtra2CAgIQNu2bTFz5kxUrFgxT+ceMWIEDh8+jLfffhuVK1fGjh070LVrV5w+fRqtWrXK9fjNmzfDwcFB910mk+XpugzDMAxT4mBlreyROQsoK2wMYzFYjLI2f/58HDt2DDdu3ECXLl1QqVIlAMC9e/fwww8/oHbt2mjXrh3u37+P7du3Y9++ffjf//6HunXr5njeS5cuYf/+/Vi1ahVmzJgBABg2bBhq1aqFWbNm4cKFC7mWrU+fPvDw8Cj8TTIMwzCMJcOp+8s2rKgzjMVhMcqan58fIiMjcfv2bVSoUCHDb/fv30dISAhq1KiBVatW4d69e2jevDnmzJmD7777LsfzHj58GDKZDG+99ZZum62tLUaPHo05c+bg8ePHCAwMzPEcWq0W8fHxcHR0zNX6xzAMwzAlGhbYyx5CtmE3SIaxOCwmZm3VqlWYOHFiFkUNACpVqoSJEydi2bJlAIDKlStj3LhxebKKXblyBVWqVIGTk1OG7U2aNAEAXL16NddzVKhQAc7OznB0dMSQIUPw4sWLHPdXqVSIj4/P8GEYhmEYi4cta2UTrneGsVgsxrL25MkTWFllXxwrKys8fvxY971cuXJQqVS5njc8PBy+vr5Ztottz549y/ZYV1dXTJo0Cc2bN4dcLsevv/6KTz75BJcuXcKff/6ZRQEULFu2DIsWLcq1bAzDMAxjcbBlrexhmGCEYRiLwmKUtZo1a2Lz5s0YOnQovL29M/z2/PlzbN68GTVr1tRte/DgAXx8fHI9b3JyMuRyeZbtIqNjcnJytsdOnTo1w/c33ngDTZo0weDBg7Fp0ya89957Ro+bPXs2pk+frvseHx+fq6slwzAMw5gdtrCUTbjeGcZisRhlbfXq1brEIj179tQlGLl//z6+/vprpKWl4YsvvgAApKSkYMeOHejSpUuu57WzszNqgUtJSdH9nh8GDRqEd955Bz///HO2yppcLjeqIDIMwzCMxcPWlbKHRAJoNByzxjAWiMUoayEhIbhw4QIWLFiAI0eO6Cxetra2aN++PRYuXIgGDRrotuXkvmiIr68vnj59mmV7eHg4AEpskl8CAwMRHR2d7+MYhmEYxqJhCwsDcN0zjAVhMcoaANSvXx/ffPMNNBoNIiIiAABeXl6QSgueB6VevXo4ffo04uPjM8SYXbx4Ufd7ftBqtQgNDUX9+vULXCaGYRiGYRiLgWPWGMZisZhskIZIpVL4+PjAx8enUIoaQGukqdVqbNmyRbdNpVJh+/btaNq0qS6WLCwsDLdv385w7MuXL7Ocb/PmzXj58iU6d+5cqHIxDMMwjMVhaFFh60rZwVBZ43pnGIvCoixrMTEx2LdvHx48eICYmBhoM83wSCQSbNu2LV/nbNq0Kfr27YvZs2cjIiIClSpVws6dOxEaGprhXMOGDcPZs2czXDM4OBj9+/dH7dq1YWtri3PnzmH//v2oV68exo4dW7ibZRiGYRhLgwX1somh+yvDMBaFxShrJ0+eRJ8+fZCUlAQnJye4urpm2aegC1Lv2rUL77//Pnbv3o2YmBjUqVMH3377LV555ZUcjxs8eDAuXLiAr776CikpKQgODsasWbMwd+5cKBSKApWFYRiGYUoErLiVHdiyxjAWi0Sb2XxlJmrVqgWVSoUjR46gdu3a5i6OSYmPj4ezszPi4uKyXZuNYRiGYcxOx47ATz/R/3fuAFWqmLc8TPHQoweQmAiEhQHt2gGbNgEymblLxTCllvzoBhYTs3b//n1MmTKl1ClqDMMwDFMiYQsLwzCM2bEYN8jKlSsjISHB3MWwCNRqNdLS0sxdDIZhLAhra2vIeKabKWpYQSubZHaD5HbAMBaDxShrS5YswcSJEzFo0CCUK1fO3MUxC1qtFs+fP0dsbKy5i8IwjAXi4uICHx+fAsfvMky+4HZWduCYNYaxWCxGWTt16hQ8PT1RvXp1dOjQAYGBgVlmkSUSCT7++GMzlbDoEYqal5cXFAoFC2QMwwCgiRylUqlbf9LX19fMJWJKLTzulE04GyTDWCwWo6xt3LhR9/+3335rdJ/SrKyp1Wqdoubu7m7u4jAMY2HY2dkBACIiIuDl5cUukUzRw4pb2YEtawxjsViMsqbRaMxdBLMiYtR4SQCGYbJD9A9paWmsrDFFAwvqZRNW1hjGYrGYbJAMwa6PDMNkB/cPDMMwDFO2YGWNYRiGYRiCJwTKJoYxa9wGGMaiMJsbpFQqhVQqhVKphI2NDaRSaa6zxhKJBOnp6cVUQoZhGIYpw7DQXnZgN0iGsVjMpqzNnz8fEokEVlZWGb4zTF4ICQkBAJw5cwYAEBoaivLly2P79u0YMWIEAGDhwoVYtGgRtGUgw1Xm58EwDFMgeBwum2TOBsntgGEsBrMpawsXLszxO1O6+Oeff7Bo0SL88ccfePHiBdzd3VGjRg28/vrrmDx5srmLZ3JGjBiBnTt36r7b2NggODgYAwYMwJw5c2Bra5vvc968eRMHDx7EiBEjyuxahAzDFCMssJcdDC1rDMNYFBaTDZIpvVy4cAFt27ZFUFAQ3nzzTfj4+ODx48f4/fff8fHHHxdIWfvxxx9z3WfevHl47733ClJkkyCXy7F161YAQFxcHI4dO4YPPvgA//77L/bs2ZPv8928eROLFi1CSEhIFmUtL8+DYRgmV1hBK5uIemc3SIaxOMymrO3atatAxw0bNszEJWGKmqVLl8LZ2Rl//PEHXFxcMvwmFvnNLzY2NrnuY2VlpXOzNQdWVlYYMmSI7vuECRPQokUL7Nu3D2vXroW3t7fJrpWX58EwDJMvWGhnGIYxO2aTZEVcUX6QSCSsrJVA/v33X9SsWTOLogYAXl5eGb6np6dj2bJl2LFjB548eQJfX18MGjQICxYsgFwu1+2XlxgtYzFrEokEEydORPv27TFv3jzcu3cPlSpVwpo1a9C5c+cMx585cwYzZszA9evX4e/vj1mzZiE8PLzAcXASiQStWrXC77//jgcPHuiUtUePHmHFihU4deoUwsLCoFAo0K5dO6xatUpnQduxYwdGjhwJAGjbtq3unKdPn0ZISIjR5xEREYHZs2fj22+/RVxcHKpWrYrp06dj+PDh+S47wzBlBFbQyiacYIRhLBazKWsPHz4016WZYiY4OBi//fYbrl+/jlq1auW475gxY7Bz50706dMH77zzDi5evIhly5bh1q1bOHr0qEnKc+7cORw5cgQTJkyAo6Mj1q9fjzfeeANhYWFwd3cHAFy5cgWdO3eGr68vFi1aBLVajcWLF8PT07NQ1w4NDQUAuLq66rb98ccfuHDhAgYMGICAgACEhoZi8+bNCAkJwc2bN6FQKPDKK69gypQpWL9+PebMmYPq1asDgO5vZpKTkxESEoL79+9j0qRJKF++PA4dOoQRI0YgNjYWU6dOLdR9MAxTSjEU1FloLzuwssYwFovZlLXg4GBzXbpkoVQCt2+buxR6qlUDFIp8HTJjxgx06dIF9erVQ5MmTdC6dWu8+uqraNu2LaytrXX7Xbt2DTt37sSYMWPw+eefAyDXQS8vL6xevRqnT5/OYFUqKLdu3cLNmzdRsWJFAGSpqlu3Lvbt24dJkyYBABYsWACZTIbz58/Dz88PANCvX79slaPsiIyMBEAxa19//TW++uor1KpVC1WrVtXt061bN/Tp0yfDca+99hqaN2+Or776CkOHDkWFChXQunVrrF+/Hh06dNBZ0rJjy5YtuHXrFr788ksMHjwYADBu3Di0adMG8+bNw6hRo+Do6Jive2EYhmFKKZmzQTIMYzFwghFL5/ZtoGFDc5dCz+XLQIMG+TqkQ4cO+O2337Bs2TKcPHkSv/32G1auXAlPT09s3boVr7/+OgDg+++/BwBMnz49w/HvvPMOVq9eje+++84kylr79u11ihoA1KlTB05OTnjw4AEAQK1W4+eff0avXr10ihoAVKpUCV26dMHx48fzdJ2kpKQslrhWrVph586dGZapsLOz0/2flpaG+Ph4VKpUCS4uLvjrr78wdOjQfN/j999/Dx8fHwwcOFC3zdraGlOmTMHAgQNx9uxZdO/ePd/nZRimlMOWtbJJZssa1z3DWAxmU9batm0LqVSKkydPwsrKCu3atcv1GIlEglOnThVD6SyIatVIQbIUqlUr0GGNGzfGkSNHkJqaimvXruHo0aP46KOP0KdPH1y9ehU1atTAo0ePIJVKUalSpQzH+vj4wMXFBY8ePTLFHSAoKCjLNldXV8TExACgWK/k5OQs5QBgdFt22Nra6hS7J0+eYOXKlYiIiMignAHksrhs2TJs374dT58+zRAPFxcXl+frGfLo0SNUrlwZUqk0w3ZhGTTVs2QYhmFKAewGyTAWi9mUNa1WC41Go/uu0WhyXRS7LCxunAWFIt+WLEvGxsYGjRs3RuPGjVGlShWMHDkShw4dwoIFC3T7FPXi6DKZzOh2U7cvmUyG9u3b67536tQJ1apVw9ixY/HNN9/otk+ePBnbt2/H22+/jebNm8PZ2RkSiQQDBgzI8I4wDMMUOWxZYxiGsSjMpqxlzuKXU1Y/pnTSqFEjAEB4eDgAimPUaDS4d+9ehtiwFy9eIDY2ttjiHL28vGBra4v79+9n+c3Ytrzi6+uLadOmYdGiRfj999/RrFkzAMDhw4cxfPhwrFmzRrdvSkoKYmNjMxyfHyU2ODgYf//9NzQaTQbr2u3/4h85ZpRhGIbRwZY1hrFYpLnvwjCF4/Tp00atViJGTSTb6Nq1KwBg3bp1GfZbu3YtAErEURwIi9jXX3+NZ8+e6bbfv38fJ06cKNS5J0+eDIVCgeXLl2e4Xubns2HDBqjV6gzb7O3tASCLEmeMrl274vnz5zhw4IBuW3p6OjZs2AAHBwe0adOmEHfBMEyphS1rZROpVJ9ghOudYSwKi0swcvbsWXz33Xe6mJrg4GB069aNhcsSzOTJk6FUKtGrVy9Uq1YNqampuHDhAg4cOIBy5crp1g+rW7cuhg8fji1btiA2NhZt2rTBpUuXsHPnTvTs2dMkyUXyysKFC/Hjjz+iZcuWGD9+PNRqNTZu3IhatWrh6tWrBT6vu7s7Ro4ciU2bNuHWrVuoXr06unfvjt27d8PZ2Rk1atTAb7/9hp9//lm3jICgXr16kMlkWLFiBeLi4iCXy9GuXbssa9UBwFtvvYXPPvsMI0aMwOXLl1GuXDkcPnwY58+fx7p16zgTJMMwDKNHKgWSk81dCoZhjGAxylpqaioGDhyIr7/+GlqtVreAcmxsLNasWYNevXph3759GVK9MyWD1atX49ChQ/j++++xZcsWpKamIigoCBMmTMC8efMyLJa9detWVKhQATt27MDRo0fh4+OD2bNnZ4hpKw4aNmyIEydOYMaMGXj//fcRGBiIxYsX49atWzpXwoIyffp0fPrpp1ixYgV27NiBjz/+GDKZDHv27EFKSgpatmyJn3/+GZ06dcpwnI+PDz799FMsW7YMo0ePhlqtxunTp40qa3Z2djhz5gzee+897Ny5E/Hx8ahatSq2b99eoAXpGYYpI7BlrWzSvj3wxReAlRXXO8NYGBKthWTtmDt3LpYtW4YZM2bgnXfegbe3NwDKzLdmzRqsWrUKc+fOxQcffGDmkuaf+Ph4ODs7Iy4uDk5OTkb3SUlJwcOHD1G+fHnY2toWcwmZvNKzZ0/cuHED9+7dM3dRmDII9xNMkdO7N3D0KP3/5Ang72/e8jDFg1IJVK1KdT5jBrBqlblLxDClmrzoBgKLiVnbu3cvhg8fjpUrV+oUNYCSPaxYsQLDhg3D7t27zVhCpqyRnMkl5N69e/j+++9zXZCaYRimxMKWtbKJXA4MG2buUjAMYwSLcYMMDw9H06ZNs/29adOm2L9/fzGWiCnrVKhQASNGjECFChXw6NEjbN68GTY2Npg1a5a5i8YwDMMwpkMqBQYPBjZsoCWDGIaxGCxGWQsICMCZM2cwbtw4o7+fPXsWAQEBxVwqpizTuXNn7Nu3D8+fP4dcLkfz5s3x4YcfonLlyuYuGsMwTNHA1rSyiUQCVKsG/PwzYBBHzjCM+bEYZW348OFYsGABXFxcMG3aNFSqVAkSiQT37t3DunXrcOjQISxatMjcxWTKENu3bzd3ERiGYRimeJBKgcaNgbQ0c5eEYRgDLEZZmzNnDv79919s2bIFn3/+uW4hX41GA61Wi+HDh2POnDlmLiXDMAzDlGKEZY0tbGUTiQSwsTF3KRiGMcBilDWZTIYdO3Zg+vTp+P777zOss9a1a1fUqVPHzCVkGIZhmFIOK2kMwzAWhcUoa4I6deqwYsYwDMMw5oSVNoZhGIvA4pQ1we3bt3Ho0CGEh4ejWrVqGDFiRK7rEDAMwzAMUwhYSWMYhrEozKqsbdy4EevXr8eFCxfg4eGh2378+HH07dsXqampum3r16/H77//nmE/hmEYhmGKAImEFTeGYRgLwKyLYn/zzTeoWLFiBgUsPT0dY8aMgUwmw/bt2/HPP/9g+fLlePToEZYuXWrG0jIMwzBMKYcVNIZhGIvCrMrazZs30axZswzbTp8+jZcvX2LatGkYPnw4atasiVmzZqFfv374/vvvzVRShmEYhilDsNLGMAxjEZhVWYuKikJgYGCGbadOnYJEIkGvXr0ybG/ZsiXCwsKKs3gMY1Z++OEH1KtXD7a2tpBIJIiNjcWIESNQrly5XI8NDQ2FRCLBjh07irycRUlpuY+8sGPHDkgkEoSGhpq7KExZhpU0hmEYi8Ksypq3tzeeP3+eYduvv/4KhUKBunXrZthuY2MDm7K69odaTYtUmvujVhf4Fi5fvozOnTvDyckJjo6O6NixI65evZplv5CQEEgkkiyfzp0753oNlUqFyZMnw9PTEwEBAViyZEmWfZ48eQIHBwecP3++wPdSHERFRaFfv36ws7PDJ598gt27d8Pe3t7cxSpRKJVKLFy4EGfOnDF3URim5MFKG8MwjEVg1gQjjRo1ws6dOzF58mQ4Ojrixo0buHTpEnr06AErq4xFu337NgICAsxUUjOiVgOPHwMGyVbMho0NEBgIyGT5Ouyvv/5Cq1atEBgYiAULFkCj0WDTpk1o06YNLl26hKpVq2bYPyAgAMuWLcuwzc/PL9frrFq1Crt27cLcuXORkJCAxYsXo2LFihg4cKBun5kzZ+L1119Hy5Yt83UPxc0ff/yBhIQEfPDBB2jfvr1u++effw6NRmPGkhUvwcHBSE5OhrW1db6PVSqVWLRoEQCaBGAYJg+wksYwDGNRmFVZW7BgARo3bozKlSujZs2auHz5MiQSCWbPnp1l36NHj6Jdu3ZmKKWZ0WhIUZPJACszVld6OpVDo8m3svb+++/Dzs4Ov/32G9zd3QEAQ4YMQZUqVTBnzhx89dVXGfZ3dnbGkCFD8l3Eb7/9Fu+88w5mzZoFAHj8+DG++eYbnbJ27tw5HD9+HLdv3873uYubiIgIAICLi0uG7QVRWkoyEokEtra25i5GBpKSktjKyZR+WGljGIaxCMzqBlm7dm388ssvaNiwIZ49e4ZmzZrh+++/R8OGDTPsd+bMGSgUCvTt29dMJbUArKwAa2vzfQqhKP76669o3769TlEDAF9fX7Rp0wbffvstEhMTsxyTnp5udHtOJCcnw9XVVffdzc0NSqUSAKDRaDB16lTMmjUr3xba2NhYTJs2DeXKlYNcLkdAQACGDRuGyMhI3T4REREYPXo0vL29YWtri7p162Lnzp0ZziPir1avXo0tW7agYsWKkMvlaNy4Mf744w/dfiEhIRg+fDgAoHHjxpBIJBgxYgQAGI1ZE7Fszs7OcHFxwfDhwxEbG2v0Xm7fvo0+ffrAzc0Ntra2aNSoEb755psM+4jYqfPnz2P69Onw9PSEvb09evXqhZcvX2Y554kTJ9CmTRs4OjrCyckJjRs3xt69ezPsc/HiRXTu3BnOzs5QKBRo06ZNnlxRjcWsjRgxAg4ODnj69Cl69uwJBwcHeHp6YsaMGVD/56obGhoKT09PAMCiRYt07rQLFy4s0LM4e/YsJkyYAC8vLwQEBODw4cO67Zn57LPPIJFIcP36dQDA33//jREjRqBChQqwtbWFj48PRo0ahaioqFzvn2GKHVbSGIZhLAqzL4rdokULfPfddznuExISgn/++aeYSsSYGpVKBTs7uyzbFQoFUlNTcf369QxZQe/evQt7e3ukpqbC29sbb775JubPn5+rValx48bYsmULQkJCkJiYiH379mHSpEkAgG3btiEyMhIzZ87MV9kTExPRunVr3Lp1C6NGjUKDBg0QGRmJb775Bk+ePIGHhweSk5MREhKC+/fvY9KkSShfvjwOHTqEESNGIDY2FlOnTs1wzr179yIhIQFjx46FRCLBypUr0bt3bzx48ADW1taYO3cuqlatii1btmDx4sUoX748KlasaLR8Wq0WPXr0wLlz5zBu3DhUr14dR48e1Sl7hty4cQMtW7aEv78/3nvvPdjb2+PgwYPo2bMnvvrqqyxJfSZPngxXV1csWLAAoaGhWLduHSZNmoQDBw7o9tmxYwdGjRqFmjVrYvbs2XBxccGVK1fwww8/YNCgQQCAX375BV26dEHDhg2xYMECSKVSbN++He3atcOvv/6KJk2a5KtOAECtVqNTp05o2rQpVq9ejZ9//hlr1qxBxYoVMX78eHh6emLz5s0YP348evXqhd69ewMA6tT5f3v3HR1F2bYB/NoUEkIaPdRI6DUUaVJ90dDEghQBFRARXpWmSBHpICAqHRRRAigvaOiCtCgtNKlKh0BiIIEAgSSQnr2/P/LNuJvdTTYhmx2S63fOnLM79Zl5dmbnnqdMg1wdi/fffx+lS5fGpEmT8PjxY3Tt2hXu7u74+eef0a5dO6N5169fj7p166JevXoAgD179uD69esYOHAgfHx8cP78eSxfvhznz5/H0aNHoePNMWkRf5dERNogZHOxsbECQGJjYy3Ok5iYKBcuXJDExETjCSkpIpcvi4SFidy6Zb8hLCwjHSkpOd7/+vXrS40aNSQtLU0dl5ycLJUrVxYAEhQUpI5/5513ZMqUKbJhwwZZvXq1vPzyywJAevXqle12IiIipG7dugJAAEibNm0kPj5eHj58KKVLl5Z169blOO2TJk0SALJx40aTaXq9XkRE5s+fLwDkxx9/VKelpKRIy5Ytxd3dXeLi4kRE5MaNGwJASpYsKTExMeq8W7ZsEQCybds2ddzKlSsFgPz5559G2+zfv7/4+vqq3zdv3iwA5IsvvlDHpaWlSZs2bQSArFy5Uh3foUMHqV+/viQlJRntw3PPPSfVq1c32fYLL7yg7qOIyKhRo8TR0VEePnwoIiIPHz4UDw8Pad68ucnvVllOr9dL9erVpWPHjkbrSkhIkCpVqsiLL75oclwNKcfMcD/69+8vAGTatGlG8zZq1EiaNGmifr97964AkMmTJ5usN6fHonXr1ka/XxGRPn36SJkyZYzGR0VFiYODg1HaEhISTLb/v//9TwDIgQMHTLZ148YNi8fD4nWCKK/06ycCiLi4iERG2js1REQFkjWxgcKu1SCpcHj//fdx5coVDBo0CBcuXMC5c+fw9ttvIyoqCkBG9UXF999/j8mTJ6N79+546623sGXLFgwePBg///wzjh49muV2KlasiNOnT+P06dM4f/489u3bB3d3d0ydOhU1a9ZE7969cejQITRv3hyVKlXC8OHDkZJNxy0bNmyAv7+/SUkLALVEZMeOHfDx8THqyMTZ2RnDhw/Ho0ePTKrK9e7d26i6Zps2bQAA169fzzIt5uzYsQNOTk7473//q45zdHTEsGHDjOaLiYnB77//jl69eiE+Ph737t3DvXv3cP/+fXTs2BFXr17FrVu3jJZ57733jEp92rRpg/T0dISHhwPIKDGKj4/HuHHjTNqVKcudOXMGV69eRd++fXH//n11u48fP0aHDh1w4MCBXHeYMnToUKPvbdq0seoY5uZYDB48GI6Z2mr27t0b0dHRRr1NBgUFQa/Xo3fv3uo4w1LlpKQk3Lt3Ty1JPnXqlNX7S5SvdDqWrhERaQCDNbK5oUOH4tNPP8XatWtRt25d1K9fH6GhoWpHIO7u7lku//HHHwMA9u7dm+22nJ2d0bBhQ9SpUwcODg64dOkSli5digULFiAmJgZdu3bFq6++il9++QV79uzBzJkzs1xfaGioWp3NkvDwcFSvXh0ODsanU+3atdXphipXrmz0XQncHjx4kO3+mdt2uXLlTI5h5h42r127BhHBxIkTUbp0aaNh8uTJAP7t1MTadIaGhgJAlsfn6tWrAID+/fubbHfFihVITk5GbGxsTncbrq6uaps0w/RZcwxzcyyqVKlish6lDZ5htdD169ejYcOGqFGjhjouJiYGI0aMQNmyZVG0aFGULl1aXV9u9p3IphigERFpit3brFHhMHPmTIwePRrnz5+Hl5cX6tevj08//RQAjG5szVFenB4TE5Pj7Y4aNQpvvvkmGjdujDVr1qBEiRJqb6NjxozBzJkz1e7d80vmEhqFiNhsm0rp1ejRo9GxY0ez81SrVs3oe16kU9nu3Llz0bBhQ7PzZBesm2MpbTlJU06Ohbk2ly4uLnj11VexadMmLF26FHfu3EFISAg+//xzo/l69eqFw4cP45NPPkHDhg3h7u4OvV6PTp06FarXMNBTgsEaEZGmMFijfFO8eHG0bt1a/b53715UrFgRtWrVynI5pWpb5pKU7Pz66684fPiwWroTGRmJcuXKqdPLly9vUt0ts6pVq6q9+lni6+uLv/76C3q93qh0TXlFgK+vb47SnRO+vr4IDg7Go0ePjIKey5cvG83n5+cHIKPk0fC9bU9C6fTk3LlzJsFN5nk8PT3zbLvWstRxR14ei969e2PVqlUIDg7GxYsXISJGVSAfPHiA4OBgTJ06FZMmTVLHK79JIs1hsEZEpCmsBkl2sX79evz5558YOXKkGuDExcUhOTnZaD4RwYwZMwDAYimIOSkpKfjoo4/w2WefoUyZMgCAsmXL4tq1a0hLSwMAXLx4ET4+Plmu5/XXX8fZs2exadMmk2lKCVOXLl1w+/Zto+pwaWlpWLRoEdzd3U16C8xLXbp0QVpaGpYtW6aOS09Px6JFi4zmK1OmDNq3b49vv/1WbStoyFyX/NkJCAiAh4cHZs2ahaSkJKNpyrFp0qQJqlatii+//NLsqxhys11rubm5AYDJawzy8li88MILKFGiBNavX4/169ejWbNmRlUmlRLAzKWR8+fPt3obRPlKCdYYtBERaQJL1sjmDhw4gGnTpiEgIAAlS5bE0aNHsXLlSnTq1MmoW/tTp06hT58+6NOnD6pVq4bExERs2rQJISEheO+999C4cWOrt7lgwQIAMFp/ly5d8MEHH6Bv37547rnnMH36dLz77rtZrueTTz5BUFAQevbsiXfeeQdNmjRBTEwMtm7dim+++Qb+/v5477338O2332LAgAE4efIknnnmGQQFBSEkJATz58+Hh4dHDo+Y9bp164ZWrVph3LhxCAsLQ506dbBx40azbaGWLFmC1q1bo379+hg8eDD8/Pxw584dHDlyBDdv3sTZs2dztG1PT0/MmzcP7777Lpo2bYq+ffuiePHiOHv2LBISErBq1So4ODhgxYoV6Ny5M+rWrYuBAweiQoUKuHXrFv744w94enpi27ZteXU4jBQtWhR16tTB+vXrUaNGDZQoUQL16tVDvXr18uxYODs7o3v37li3bh0eP36ML7/80mi6p6cn2rZtiy+++AKpqamoUKECdu/ejRs3bthil4mIiKiAYbD2tPj/0qCncfsVKlSAo6Mj5s6di/j4eFSpUgUzZszARx99BCeDl237+vqiTZs22LRpE27fvg0HBwfUrl0b33zzDd577z2rt3fnzh1Mnz4dP/30E4oUKaKOL1OmDDZs2IBRo0Zhz549ePnll9UOJSxxd3fHwYMHMXnyZGzatAmrVq1CmTJl0KFDB/Xl2kWLFsW+ffswbtw4rFq1CnFxcahZsyZWrlypvszaVhwcHLB161aMHDkSP/74I3Q6HV5++WV89dVXaNSokdG8derUwYkTJzB16lQEBgbi/v37KFOmDBo1amRURS8nBg0ahDJlymD27NmYPn06nJ2dUatWLYwaNUqdp3379jhy5AimT5+OxYsX49GjR/Dx8UHz5s0xZMiQJ9r/7KxYsQLDhg3DqFGjkJKSgsmTJ6NevXp5eix69+6NFStWQKfToVevXibT165di2HDhmHJkiUQEQQEBOC3335D+fLl82o3ifIOS9aIiDRFJ7bs1YAAZFTv8/LyQmxsLDw9Pc3Ok5SUhBs3bqBKlSrG3aCnpwMREUA2XczniyJFgEqVgCfo3IGIcs/idYIorwwcCAQGAm5uQGgokE1VcSIiyjlrYgMFS9a0ztExI0DSQq9xDg4M1IiICjKWrBERaQqDtaeBoyODJCIiyl8M2IiI7I69QRIREVEGlqwREWkKgzUiIiIiIiINYrBGREREGViyRkSkKQzWiIiIiIiINIjBmsbwTQpEZAmvD2RzLFkjItIUBmsa4ezsDABISEiwc0qISKuU64NyvSAiIqKCjV33a4SjoyO8vb0RHR0NAHBzc4OOTzaJCBklagkJCYiOjoa3tzcc+SoPshWWrBERaQqDNQ3x8fEBADVgIyIy5O3trV4niGyiZ0/g9GnAw8PeKSEiIjBY0xSdTody5cqhTJkySE1NtXdyiEhDnJ2dWaJGtvfii0CjRsDjxwB/b0REdsdgTYMcHR15U0ZERPZRqlRGyRrbRhIR2R2DNSIiIjLm4mLvFBAREdgbJBERERERkSYxWCMiIiIiItIgBmtEREREREQaxGCNiIiIiIhIg9jBSD4QEQBAXFycnVNCRERERET2pMQESoyQFQZr+SA+Ph4AUKlSJTunhIiIiIiItCA+Ph5eXl5ZzqMTa0I6eiJ6vR6RkZHw8PCATqd74vXFxcWhUqVKiIiIgKenZx6kkPIS80e7mDfaxvzRNuaPdjFvtI35o232yB8RQXx8PMqXLw8Hh6xbpbFkLR84ODigYsWKeb5eT09PnvQaxvzRLuaNtjF/tI35o13MG21j/mhbfudPdiVqCnYwQkREREREpEEM1oiIiIiIiDSIwdpTyMXFBZMnT4aLi4u9k0JmMH+0i3mjbcwfbWP+aBfzRtuYP9qm9fxhByNEREREREQaxJI1IiIiIiIiDWKwRkREREREpEEM1oiIiIiIiDSIwRoREREREZEGMVgjIiIiIiLSIAZrREREREREGsRgjYiIiIiISIMYrBEREREREWkQgzUiIiIiIiINYrBGRERERESkQQzWiIiIiIiINIjBGhERERERkQYxWCMiIiIiItIgBmtEREREREQaxGCNiIiIiIhIgxisERERERERaRCDNSIiIiIiIg1isEZERERERKRBDNaIiIiIiIg0iMEaERERERGRBjFYIyIiIiIi0iAGa0RERERERBrEYI2IiIiIiEiDGKwRERERERFpkJO9E1AY6PV6REZGwsPDAzqdzt7JISIiIiIiOxERxMfHo3z58nBwyLrsjMFaPoiMjESlSpXsnQwiIiIiItKIiIgIVKxYMct5Cnyw9ujRI8ydOxfHjh3D8ePH8eDBA6xcuRIDBgywavmHDx9izJgx2LRpExISEtCsWTN89dVXaNy4sdVp8PDwAJCRIZ6enrnZDSIiIiIiKgDi4uJQqVIlNUbISoEP1u7du4dp06ahcuXK8Pf3x759+6xeVq/Xo2vXrjh79iw++eQTlCpVCkuXLkX79u1x8uRJVK9e3ar1KFUfPT09GawREREREZFVzaMKfLBWrlw5REVFwcfHBydOnEDTpk2tXjYoKAiHDx/GL7/8gh49egAAevXqhRo1amDy5MlYu3atrZJNRERERESFXIHvDdLFxQU+Pj65WjYoKAhly5ZF9+7d1XGlS5dGr169sGXLFiQnJ+dVMomIiIiIiIwU+GDtSZw+fRqNGzc26aWlWbNmSEhIwJUrV8wul5ycjLi4OKOBiIiIiIgoJxisZSEqKgrlypUzGa+Mi4yMNLvcrFmz4OXlpQ7sCZKIiIi0bN68eahVq5a9k0FEmTBYy0JiYiJcXFxMxru6uqrTzRk/fjxiY2PVISIiwqbpJCIiInoSiYmJiImJsXcyiCgTBmtZKFq0qNl2aUlJSep0c1xcXNSeH7XWA2Rqaiq8vb1NOkeJjIzEqVOn7JQqIiIisicRsXcSiMiMAt8b5JNQepLMTBlXvnz5/E7SE3N0dERsbKxJqeAnn3yCy5cv48SJE3ZKGREREdmTNd2IE1H+YslaFho2bIhTp05Br9cbjT927Bjc3NxQo0YNO6Us9xwcHODg4IC0tDSj8S+++CJOnjzJzlCIiIgKIZasEWkTg7X/FxUVhUuXLiE1NVUd16NHD9y5cwcbN25Ux927dw+//PILunXrZrY929PAycnJaD8BqI2Kw8LC7JAiIiIisicRYckakQYVimqQixcvxsOHD9XeG7dt24abN28CAIYNGwYvLy+MHz8eq1atwo0bN/DMM88AyAjWWrRogYEDB+LChQsoVaoUli5divT0dEydOtVeu/PEnJ2dTUrWlH0OCwtDgwYN7JAqIiIisicGa0TaUyiCtS+//BLh4eHq940bN6qlZW+++Sa8vLzMLufo6IgdO3bgk08+wcKFC5GYmIimTZsiMDAQNWvWzJe024KTk5NJsFa2bFnMmjXrqd4vIiIiyh1WgyTSpkIRrFlTtS8wMBCBgYEm44sXL44VK1ZgxYoVeZ8wO3F2djapBqnT6TBu3Dg7pYiIiIjsjSVrRNrDNmuFkLmSNSIiIiq8WLJGpE0M1gqh27dvY9KkSQgNDbV3UoiIiEgjWLJGpD0M1gqx69ev2zsJREREpAEsWSPSJgZrhRifoBEREZGC9wVE2sNgrRDL3MkImafT6TBnzhx7J4OIiChPPXr0CHfv3gXAkjUirWKwVohlDtauXLmCzp074/79+3ZKkfYof16rVq2yc0qIiIienIjg119/xdKlS9GoUSOUKVNGncaSNSLtKRRd95N5KSkpRt89PDywf/9+rFixAmPHjrVTqrQlOTnZ3kkgIiLKM1u2bMFrr71mMp4la0TaxGCtEMtcslauXDnUrl2bvUQaSEpKAsCnjURE9HRKT0+Ho6MjgIyHtOYCtddeew0nTpzgfx2RBrEaZCFmrs2ar68vvvvuO0ybNi3Pt/fXX3/h6NGjeb5eW1KCNSKtmj17Nm7cuGHvZBBRDoWHh9ukNCs0NNSoOcP777+PN998EyKC6Ohoo3lfffVVAEBwcDBu3ryZ52kpqG7duoWpU6fin3/+sXdSqBBgsFaImQvWBgwYAAB4/Phxnm/P398fLVu2NBp34MAB/PXXX0Zpys9XCgQFBeH7779HUFCQ2emJiYk23X58fDzi4+Ntug2t+PjjjzF8+HB7J0NTNm7ciGbNmuV6+ZSUFIwfPx6dO3fOw1QRFU7x8fHYtGkTAODu3bsICQnJ820kJiZiz549iI6OxjPPPINFixaZnW/WrFm57tjK398f33//PaZMmYJq1aqhTp06+Omnn9C5c2fs378fAHDixAkUKVIEJUuWxIABA5CUlAQHBwejkrVFixap9wT0r/T0dPz222+YMmUKfH1982Sd7PCNsiRkc7GxsQJAYmNj7Z0UERFp2LChAJAvvvhCAgICpEGDBuq09PR0KVKkiCxcuDDPtwtAAEhkZKSkp6eLiEjdunUFgNSuXVsaNGgg7777rtSuXVudbmtKmgDI0KFDZeDAgUbTL1y4IACkTp06IiISGRkpAwYMkOTkZKvWf/fuXYmMjLQ4vUiRIuLs7Cyff/657Nu3T/R6vVXrTU9Pt3iM9uzZI+vXr7dqPeYsXrxY9uzZYzL+7NmzVqfPnICAAHn99ddztIxer5f79+/nepvWePTokRw4cCDXy6ekpMi9e/dytWzFihUFgMTHx+dq+ejoaPX327t3b0lMTLQ4b2JionzxxRfy8OHDXG0rOw8fPpS0tDSbrPtJhIaGSkJCgtXzJyQkyN9//200Li4uLss8TkpKyvLYm3PkyBHZtm1bjpZ5GoWFhRn9LoKDg+XQoUNWLfsk1xtz7t+/L5cuXbI4ff369QJAzp07J61atRIAOU5DfHy83Llzx+L0jz/+WABI/fr1BYC0aNFCRDL21fAeoX///vLss8/maNuKihUrioODg3ptiImJUT+/9NJLAkBu374tJUuWlM8//1xEREqWLClOTk5SuXJluXXrljRo0EBdZu3atbJgwQLp2bOnREREWJUGvV4ver1ekpKS5MKFC/LZZ5/l+FieP39eLl++nOP9t7Wvv/7a6N4hL/Tt21fefvtto3ExMTHy1Vdf5fl5YMnNmzdlzpw5Nv/PpQw5iQ0YrOUDrQVrIiJFixY1utgoF+Dbt28LAKlQoYL07NnzibczYcIEWbZsmSQkJBhtz9/fXx4/fizNmjUzGv/hhx9KmTJlJDQ09Im3bQ3DbSvDn3/+qd5EzZ071yhYGzp0qACQY8eOWXWDXq1aNQEgN2/etGr7ISEhFtd19+5duXXrloiIzJ8/X1xcXOTcuXMiIvLhhx/KypUrRUTE09NTAEhqaqo8ePBAPv30UwEg8+fPt7juqKgo+eeff4zSpHjw4IGcPHlSAMiPP/5ocR3p6ely5coVefDggaxevVoNClJTU2XChAlSo0YNk2A4swEDBkj58uXltddek9WrV6tpCQ8Pt7iMXq+XGjVqyPbt243GT5s2TV599VX1+6NHj+TevXty4MABadWqlZw8eVJERObNm6fmaW6MGzdOPb+VmxNr+fn5qft49+5ddfzmzZvl8ePHsnXr1iwDyStXrhj9fhYtWmQyT3h4uGzevFnWrFmjznft2jWr0hceHq7+5jLT6/Xyww8/qPsNQLy9vaVPnz5WrduSJUuWyIwZM+Srr76yKshKTU21+OBi3bp1AkBee+01q7ffuHFjASCnTp0SPz8/mTFjhppPhq5fvy7PPPOMREdHi6enp3Ts2FFOnz4ter1ePv74Yxk9erRcv35dAgMDRUQkJCTE6MFNbm707t+/LytWrJBbt27J9evXZcWKFaLX6yUlJSVH67HG7t275bvvvhMRUfPhzp07Rr+ds2fPSrdu3WTHjh2ydu1ak3UkJiYKAPnss89k9erVsm3bNnn++eelR48ecuTIEUlNTZXk5GSL+Tdv3jypVKmSHDx4UPr06SN6vV4OHTqk3ryOGjVK5syZIyIix48flxo1asipU6cs7pNyPc6cxsjISJk9e7YkJSWJg4ODLFiwQLy9vQWAHDlyxORmGYDMmjVLRDKC7vHjx8vatWtlypQp6vUXgGzYsEFdRgle3n77bZPr/q1bt+S9994TAOp1SbnGK3m7ePFiiYyMtOrGvX79+uqDUOV8nzlzppQoUUKSk5Plxo0bIiJSpUoVGT9+vIiIeHt7S5EiRcTX11fef/99s/+NOfnN/v333+Lo6CjOzs7qcpb+By3Jy2Aor8TGxsoLL7yQJ8FacHCwVKtWTW7cuCHFihWT6dOni0jGA6Zvv/1WvT+6fv26PHz4UAYNGiRxcXG52taWLVvkypUrZqeFh4eLTqeT0aNHq9c+xddffy1fffVVrrapOH78uOzfv/+J1pFXtm/fLo8ePbJ3MkSEwZrmaDFYy3zx1el0kpKSInq9Xu7evSsDBw6UevXqiYjItWvXcv00/vnnn7d4wZ85c6Zs3rxZXFxc1HE///xzjm52n1RWf0hKgAJA6tatKyIi7du3FwDqH2tISIjMnTtXKlasaLTekJAQ2bx5s7q8t7e3HDx4UPR6vTx48MDi9pVgKCYmRl566SX53//+J7t375b4+Hj1JiA8PFyd38PDQzZs2KB+nz59utEf43PPPWe0/ilTppg9DnXq1BEAcvXq1SyPSZkyZcTBwUGqV68u169fl549e0rt2rVlxYoV6jwVKlRQP+/YsUOCg4PV788//7ysW7dOjh8/LiIin332mVSoUEE6d+4sDx8+tLjdVatWyb59++Tq1aty9epVEfn3CfWUKVOMjt+BAwckICBAHfftt99KWlqadOvWzWS9R44ckS+//FLNU5GMG+IbN24Y3RTp9XqZNGmSepPz4MEDGTVqlNy6dUt8fX0FgMyZM8do3Y8ePZLw8HAZPny4GlSLZJSGBQcHi4hI7dq1szzehulMT09Xb/iUtP35558m83bp0kV+//13dXtNmzY1madRo0YSHh4uL7zwgvj4+MiRI0dk79696jKnT5+Wu3fvqr+xiIgI9YZ65syZMmvWLPn9998FyCghuHHjhtmbl/Pnz6vrDQkJkW3btsnIkSMlNTVVRDIeQERFRcnzzz8vN2/elOXLlxutJy4uTo4ePSorV66UZ599Vs6cOSNbt241Op5TpkyRTp06qetU8mfGjBlGT8AVx48ft3hDP3bsWHX+4sWLmxy32bNni0hGKaLh79xwMCyRUIbOnTsLAGnXrp26LXM3evfv35dBgwaZ3ExcvXpVdu7cKTt37jS6phhuY86cOVKlShX5+uuvjZbdvXu3nDlzxuz+KjZu3GgS6Ge+plSvXl0ASMmSJdV5vLy8jNIQGBhoFNybOz7du3dXS5SHDRsmOp1OevToIZs3b5YFCxZIu3bt5OrVq0a/BeWmde3atep2lHUAkPT0dLO/P0NpaWlmp1euXFkdf+XKFSlXrpzZdI8ePVouXrwoqampAkCqVaumniNZDd999516XR02bJgMHz7caLphUKUM0dHRsn//fgEgf//9t1HJGAA5evRolvnZrl076du3r/r/e/ToUVm6dKk4OjoaXdf8/f3lgw8+EBERDw8PKVq0qPj6+kp6eroUK1ZMypYta/Z4DB48WCpXrmwxcLh69aq4u7ubPR5Z0ev1smzZMomNjZXJkyery6xevVq2bNmS5bLZiYiIkD179siyZcuynXf9+vUybNgwAaBe8xXt2rUTR0dHcXNzU4+ZtSVf586dk1WrVgmQ8QAp87FR/hcyj583b560adNGgIySUUNJSUmycOHCbGs1ABBPT0+z05RrufIQv2XLlvLpp5+qD+Gyy7esZD7vUlNT1eO1fft28ff3N5r/0KFD4u3tLY8fP871Ns05efKkHD58WADIkCFD8nTducVgTWO0Hqw5ODiYVHubPXu2eHl5yV9//SUApG/fvtK7d2+LT9kzCw8Pl2PHjslHH31ktK2hQ4dKnz591O9K4KLceBveMNpSenq6nD592iht33zzjdFTwPnz5xtNf/HFF7P8U1YkJydbnOeNN94QAGrJXXZ/9OaGH374IVfLWbroGl6QbTFYuqk1F0RYGgx/MwDkq6++MjtfixYt1KfnhoO5QM3c8Mknn8jMmTPF0dHRqLRiz549Zue3dGOXeejVq5ekp6dLr1691HFvvvlmjo7juHHjpHLlyuof6jfffCM7duwQANKkSROTP/+XX35Zzp07JzVr1rR6G8WKFZPXX3/d4nRLwfyxY8eMvvft29fo+9mzZ42+BwYGSosWLbJNj1IqnHlwcHBQ8+a7774TAGoAp9fr5cMPPxQAsn//fvW38+mnn8qBAwfUdYwfP15SU1MlLS1N0tPTJSUlRX2ynNXg5uYmL7/8co7yThlKlSolv/32m9G5v2PHDunTp48cOXJEBg8eLACkffv2MmDAADl//ryULVtWnbdkyZJWbWf+/PmyatUq0el0AkD++9//Gp3vys1STEyM0fVKuSG+d++eOu6tt94yWX9ycrJMnjzZKGD08PAQADJq1CgR+fd/z9ygpMtwUKrnZzUoD2Ey/77+97//GX1fuXKlHDp0SD3WTZo0kREjRqjTlZK0zDU79uzZY3RO16pVS31Apwy//vqrOm3kyJHZprljx45GpW2Zf9OZa7ko6VOO3+rVq40CSgDSpk0bEcl4WBMTE2NyTX/11Velc+fOcuvWLTXNP/30kwAwehDQunVreeutt0RExM3NTYoVKybPPPOM+h+p1+uNHsSZG7777jsZN26ciGSUCMXGxqr/5+YGEZFPPvlE9u3bJ2FhYfLw4UP1mGT+T8487Ny5U9auXavWQlBqFuzcuVPdp9TUVLlz54789ttvsmHDBvHy8jL5vZ05c0b0er0kJCTI7t27ja71M2bMMJrX19dXRowYIbt27ZKHDx+KTqeThQsXSkJCgkRERKil6deuXTMJXu/du6dWcTcMWswNfn5+EhMTI3Fxcdn+piIiIqRt27Zy9OhRNX+UUtx169bJoEGD5NChQ1K3bl15+PBhtkHXli1bst2mYc2V9PR0OXv2rNl1GTpy5IjROooVKyZt27aVOnXqyK5du9TxFy9elGrVqsmQIUPUcZlrV0VGRsru3btlz5498ujRo2ybDuj1epkyZYp06dJFfcCiDJ06dco27fmBwZrGaD1YGzt2rMn0wMBAAf6t3244fPTRRzJ06NAsn+RMnz5dypYtK48fP1b/JIB/6/9v3LhRnnvuOfWplfIHqFTFs7WpU6eqaZo/f766XXM3JkDGU/YmTZpkeTELCAiQXbt2Se/evbO98HXv3l1E/s2H8ePHW9x2Xg+ZpaWlyYQJE0zmW7NmjWzfvt3kptrJycnsejPf+Fga2rVrZ/R948aNJut85pln1ONer149o9LXrIbRo0cbVS18//335cKFC2bzbt68eRb3Bci4qenfv7/FQK18+fJWH3NnZ2cZOHCgxelbt27NdX6WLVtWvbH6+eef1RIQIKPUq0qVKjb/TS1cuDDL6ZMmTTL6rjy1zm5QqpiaG+7evSu7du2SH3/8UQBIlSpVJDk52aikIigoSMLCwtTvr7zyisl6KlSoIG3btpXKlStLqVKlLAaIWQ3bt2+XqlWrms2bzA+sgIxzwLBE2NaDUprj5uamjlPOCcO8cXd3l7S0NLl69ar06NFDAMgHH3xgsr5atWqZjDt37px4eXmp1QOVkqEnHczVzsjuWmw4LF26VCpVqpSrbffu3dvoOp15sFR6VKRIEQFgdC5aGjp27Gj0e9m8ebN6bba0jJeXl4SEhAgAmTx5ssk1fcOGDbJ27VpJT0+XO3fuSGpqqvofa/jAddy4cWqbNRcXF/H09FSDNYVer5fo6Gg5evRolrUfSpQooX5u2bKlxfkyB7+Gg2FAnZPB8BpnGBhnNRhev8eMGSP37983ekiReahdu7YcPnxYevfubVKNfNu2bQJk1Dz57LPPRETUBwuNGjUSEVFLdSwNSgBq6f/GcOjSpYv6WTl/lX4GMs/7xx9/GOWbSEY764iICJPmKdYMo0aNUpuHKFV2z58/L//5z3+kZ8+ecuXKFbXNplJjJzdDcHCwHDhwQG0LXLp0aZN5oqOjLTYdUa5fgOlD1Y4dO5pdJr8xWNMYLQdrmYugFUpbD6WRtbmhVKlSFhvVjx8/XqpUqaJ+j4+Pz7YdWn5Vf9Tr9UYXd8PSvOTkZPnjjz9M9jUtLc2qIMxw+PDDD42qJRoOysVe+T5x4kQREZMqMj4+Pupnw2qZ5r4rDdaHDBlidIMzdOhQad26tdEFzpzVq1fLxIkT5fnnn5euXbuaHDNle3v37pX79+/LnTt3JD4+Xl1vr169JDo6Wrp27SqXL1+W119/Xb1p8fHxkY4dO8o///wjKSkpRunW6/Vy48YNoxub7777TmrXri1hYWHqH4M1g+E6lKfPIhkB6fXr143m/fLLLyUqKkoaNmwo/v7+JuvKHFRmHjZt2iQeHh6yZ88e9Xhv3bpVQkJC5NatW3L16lXp1q2b0W/NXGmScp4o3w1LcEeMGCF79+41qc5qOOzevdskLzOXPE6aNEkeP35stO8AzP4BAhk3gHq9Xi3B6NSpk8Xt63Q6iwFhgwYNpEuXLhIQEGB0I+To6Gjxhvv69esSGhoqt2/fVm+GDQMbw8A2ICDAqNRUeSpdrFgxASBLliwxOrYAxMXFJcubd71eL0WLFpXZs2fL/fv3Lc5XoUIFOXTokJw/f15EMp42h4WFyc2bN+Xw4cOyZs0auXv3riQmJpq9QVVK0cwNNWrUsDht2bJlRt9//vlnGTNmTJYltWPGjDE73tnZWX2q3rlzZ5POI1q3bi1vvvmmXL161agk3PDmR3kYt337dgEgK1asEBFRayYoQYIyZC5JcnR0FABG1RqVYdGiRbJy5cosz8O8GCw9FFBKrXK6vnr16gmQcY2wNE9ERIT6P6D8T2zdutXo+Fuzra1bt6oPTg1LTTO7fPmyjBw50qhtrCEnJyfx9vY2+t82p3bt2jJy5Ei1Wl52Q3Ylc9YMGzZssPoBT14M5h48uru7S5cuXaRDhw4mxyTzvJlL0TKf60pVSMNBKR1UmlgYDnq9Xu1PwNKgtG3OPN7Pz0+6du1qtC7lXPvll1/U8U5OTnLmzBlZs2aNREZGyp07d6Rhw4ZGD3gyD506dTL5X1UGw+rgly9flmvXruUqL7p06SIzZ87Mdr4//vhDQkNDJTIyUkaNGpXlg9iAgIAsf+P5hcGaxmgxWFOCMaUtVmbKn4xyExscHGxStaFx48YW1z9ixAiL67Y35QZMCYSioqKMppu7+IhkVC0xHKdUr8pcwrJ37171Bi4tLU127dpl1Lbh+vXr6raUcZMmTRIR4yqJJ06cUDuF2LVrl4j82/lB6dKljUoMgIw/xdDQUNHr9Wr+AhnV5d599131e1admOTGiRMn1Au/tYKDg2XEiBGydOlSdZzyBHfGjBlGHQ4Y3jC/9tpr8u2336rflTZfStU9w2pZ5hpTBwUFyeeffy7AvwHyG2+8If/5z3/kjz/+kGHDhsmSJUtkwYIFWf4xNG/eXERETafypNNc2yDD9MfExIher5dBgwbJqVOnZMaMGWpvZ3FxcbJmzRrR6/VqsGJIOf8mTJgg586dM/ptmmMYxJw+fVpEMqql7N69W0JDQwXIuIkXyWhHd+jQIVm8eLEAUNs9LV26VADI22+/bdJGKvMwZcoUmTp1quj1erX6Vd26dSU8PFxtf6DMW7RoUVmyZInZ9RjebBru4/Tp06Vp06ZG1esaNGggzZs3l6+//lqWL18uixYtEp1Opz7Znzp1qoj8W3JfrVo1WbVqlYhkdKqjBAKG54dIRi+1SvvO2NhY+f3339WnuMp8rq6uFo+9Ocq1dMiQIVK7dm05efKkVKtWTU6cOCFvvPGGxMXFye+//y4pKSlGDzSCgoLUBylAxoOMI0eOSKtWrWT16tVG2zB3PI8dO2ZUojhnzhwpVaqUVK1aVa5cuWK2xEXx119/GbXZMTxGsbGxkpSUJMnJyfLTTz/JqVOnBPi3KmVUVJT6IMywJC7z9XLevHnSvn17eemll+Tx48dGT+MXLlwocXFxMnfuXImLizNqU6gMn376qSxZskRu3rwpwL8lcYZBgrL9S5cuyc6dO6VatWri5+cn48ePV6/VyrzKzakh5aFT5raZQMZDS8Pv/fv3l/DwcDVvMt/svvXWW+r5qFDaDGXu+fDs2bNqrQ6l5Or9999Xr09169aVdu3aqW1w7t27Jw4ODkalc9bS6XRSsmTJbIO1tm3bSr9+/SQ6Olq+/PJLmTBhQpZVmiMjI82Ov337drY34ZGRkbJx40YRyfgvNSwFVqoiGwZCrq6uMn36dJkyZYrcv3/f6GGpYcnWb7/9JmPHjrX4wOTLL78UV1dX9bthkwhzJZmZl4+IiDC73tatW8uQIUPkn3/+UTvfqVOnjuzfv18eP34ser1ePDw8ZMKECeq1xrDDJsNOtwyH3r17y82bN02aAJirkaL0cG1uMCcoKEgcHR2fqJRM0b9/f6NeSr/55pscPQTPKgDLyWAu4LYHBmsao8VgTWmoXrVqVbPTlaekSkmF8odt+IOfO3euJCUlyY0bN9QG9EppxeDBg6Vp06b5uEfWu3jxogAZ7ROUBr2GkpKS1LYhjo6OarUGpbrKxx9/LEFBQZKWliZpaWkSFBQkAKRHjx7qzaE5SrUIczejho2egYx68orMAYBht/2nT59Wn9ItWLDAaL67d+/KqlWrJDU1Va2Cd/jwYesPlEYof1rTpk1TxyldbMfExMjOnTvVqiNK+zhLHako6tatKyNGjBCRjOpaSjCsUALCzB2AKKVTP/zwg9H8SrAWFhZmdns7d+6UN954Ixd7/y+9Xm9UTz+rP1gRUUsGlTZEmW3YsMGkNDs1NVWmTZumbkf5Y587d65RD3GZe0MbOnSoUZfoShuBLl26GK1fmX/WrFlqBzzz58+XnTt3ysSJE9VzLbt9nDt3rnh5eUnv3r2Nqm1duHBBFixYID169JA2bdpY1fA/ISFBfUji4eGhtmGzRNk3c9XHsxIXFye3b9+WcePGWbzuGpo5c6ZRD6W3bt2SKlWqZFlDYc6cOWrbMcNjZ/jAwLBbbsPOiazpUTKr35zykMvcaz9ERL744gsBTKtQLlmyRAIDA9UOTq5cuSIbNmyQ2bNnm/3PVJY7ePCgUe+aycnJ0qBBAzlx4oQ67vjx47J48WK5f/++XLhwwap9i4qKMmoDJZLRpblSCpa5/UvmEk3DHmhFMmqVPHjwQPbt2ycALPZEl92rH8qUKSMAjErRRERef/11efHFF0VE1M6nMqc/O8rvv3Tp0uLn55flvK+//rrZkom4uDg1ON++fbtUrlxZbVuq1+vl/PnzZm/gDUt3atSoYdT21pzTp0/L3r17JS0tTZKTk43yI/OxNZwmIvLPP/+YtHVSHmR0795dihUrJrVq1ZLIyEhJSUmRZ599Vv1NGP4+MstcVXfjxo1G35VzMvN/dFhYmFGHY0o+KKXT8fHxRh0nKQ8kMg8pKSlG532vXr3k8uXLai2hwMBAWb9+vYwfP1797zQ3ZEWpXq60QzMXOPXt21d++eUX+c9//qOOO3LkiMm6DI+lXq83qulgqXp4hQoVJDo6Wr3XBIxLBq0ZfHx8ZOjQoWrVVHtjsKYxWgzWlBvgypUrm52+d+9eAf5tO6Q0nFV+9MePH5ekpCT1D9hw8PX1lb59+xr1fKYlSicDFy9etDjPr7/+alIy07ZtWwFg8qevBL7KE3tLHj16ZNJ1sbe3t7Rv396o/d/vv/9u9btsRER+++03AWByo2soMjJShg8frsn3YGUnMTFRTp48mWU1WaUkR2nzkFXQLJIRyHz44YdZzvP222/Lc889Z9RI2hKlumB+vp8mMjIyy3f4hYWFPdH79hTKH6qIqKUImav5mHu1ws6dO02Oh+Fx1Ov1sn379iwDquyO+/z58832xtapUye1Xag1UlNTZebMmWobjOwkJCTk+l2QkyZNMuk9Ni8pHRB5enrK8uXL1fFKNWlDhlW+rXHs2DG1N9bMlGpO5h6AiYhaaqvcACvDt99+a+WeZVBKTXP6XrvsnD59OtuATnHnzh1ZvXq1+Pn5qe27larFtvrf69Chg9l8Gj16tBr8Kw8ic/reSCWoKVu2bLbBWnR0dK57h753754kJCSYXLcy/wZz8psUEenXr5/F+U+ePJnl6xyUh7DmOjdTHlAlJSXJP//8Y/G4tm/f3qjN3qBBgwSA2hZcqYWjvArDEqVXUyVYM2f9+vUSGxsr6enpMmHCBPH19ZXr16+rAY8SuItkVH0FMqoIKpYuXWo20Bo+fHiWaVOq9iYmJsqFCxdMqohnllUeKtMMr6EnTpyQ559/XhISEiQ+Pl62b9+udh4FQH2VlFINXLmfVs45IKNwYcCAAWobQsC4nXKFChVk0qRJUqFChSz3Nb8wWNMYLQZrSi+PPj4+ZqcrAc327dtlwoQJ6s1Q5hPQ8MmsYaPXatWqmTxV1wqlJCynN9ZKPfbMLzzV6/WyYcOGXN28FS1aNMv3n1nj8ePH8tJLL+X4HTYFkVJ917AULre6deumtt2rXLlylgHg/fv3s/0jLggWLFggRYsWFZGMrrC///77bB98GPrzzz+N3j2VncDAQPnmm28sTr97965cuXLFJFhr3bq1yQtmtWLmzJlSpkwZm60/LCxMnJycTLocj4qKMnmXoNI+Ly+CR6WnUMMbQ0PffPONAKbtNr///vscbef27dtW/97yk16vl7feeivb1yTk1oMHD8zWjNi1a5d8+umnkpycrPbKau1DB0VSUpIAGW0RrSn1zWuZ7ysOHz6co/depqam5vr9Y0r1ZHMl1klJSVYdy3bt2kmfPn3k0qVL8uDBA7VXS6WKsVKrJrsHuspDMGvPiVmzZkmJEiVEJCPQe/jwodF9SHJysuzfv98ouB4xYoTUrFlT7fVy06ZN6ns9s7J582aTh/vKe1XNvQ8TyOgIx5ycBOPKg9j+/fuLiKi9eCqUV05lFh8fr9Z+OnjwoDRs2FC8vLxkz5496rsF7S0nsYETqFDy8PAAAKSkpJid7uLiAgCoUKECZsyYoY4/c+aM0XzVqlUDAJQrVw4dOnTAjh07AADXrl1Dw4YN8zjVeeOFF17A0aNH4e3tnaPllGNVokQJo/E6nQ7du3fPVVqSk5Ph6uqaq2UVbm5u2LZt2xOto6BwdnbOs3UNHz5c/RweHp7lvCVKlMC7776bZ9vWquHDh6vHpWLFimjTpg1eeeUV9XqRnWeffRbPPvus1dvr379/ltNLlSqFUqVKmYxfs2YNHB0drd5OfipSpAiSk5Nttn5fX1+kpqaajPfx8YGPj4/ROJ1Oh9u3byM2NvaJt6vX6wEADg4OZqc7OWXcboiI2fHWKlu2LMqWLZuLFNqWTqfD6tWrbbZ+b29vtGzZ0mR8QEAAAgICMH36dEyaNAkAUKxYsRytOz09HQDsds6MHTvW6F7E3H5mxcnJSb2nyalu3brh7NmzqFKlisk0FxcXNG7cONt1iAgcHBxQs2ZNABn3RQcOHFC/v/rqqyhbtqzV9wk6nc6q+Tw8PPDo0SMAGeedl5eX0fQiRYqgbdu2RuNefPFF1K1bF4MHD8aECROs2g4AvPLKK3jllVeMxlWvXt3i/GFhYXBzczM77dKlS+pvLjvlypXDggUL0K9fPwAZx6Zo0aLqdEv/+e7u7urn1q1bIzg4GHFxcXjmmWfwwgsvWLVtLWGwVkh5enoCgMnJrVBuvjLfVPj7+xt9r1evHurXr49Ro0ahf//+qFevHv773//i+vXrJn/KWuHl5YXmzZvneLm1a9di7dq1Ob65sEREcOjQIbN/EmR/T+MFPb9Vr14dmzdvtncyTDzzzDP2ToJFLi4uFh+S2YOnp6f6f/AklGDN0o2mpUAgr66nhd3Dhw/Vz5Zuki0xDLStDRTy0uzZs/N9m4pp06Zh4sSJT7TfImK0vLu7O9q0aaOOd3R0tCqQz+k9k7u7O1JSUpCSkoIiRYpYtUzXrl1ztI3c8vX1tThNCWKtodPpjB6c5laJEiVMHrQ/TXiVLKS8vLzg4eGB+fPnm52unPjZ3VQ4ODjgr7/+Ur8HBATg0KFD8PPzw6BBg/IsvVpQu3ZtTJ8+Pc/Wp9PpcvwEkaxjjxsOImvYumTNXpQbTUsla2XKlAEAlC5d2mg8g7W8YVg6+rSVrNmTTqezOtCxJHOwZrhud3d3tfTLmvUoy1kjICAAf/zxh8VzjgoOXiULKUdHR8TFxVmcbqlkzRrlypVDYmJirtNG9KQYrJFWubi4QK/XIz09vUDdHGdXDbJz587Yvn07Hjx4gF9//VUdz2AtbxiWrOU2WLNXydrTTqkGaU779u3VBxXWsjYPypUrh3LlyuVo3fR0YjhOZllbskakJc899xyqVKmCvn372jspRGYp19aCVrqWXbCm0+nQpUsXk/EFKWC1p9jYWLRr1w6///57jkuKDIM1yjlLJWsAsHXrVrz55ptWr4fIHD7SIrNcXFzg4uJidSNQIi0oXrw4rl+/bu9kEFmk1FpISUnJcdsiLcuuzZriSTsYIfNiY2Ph7++P559/PsfLGgZrDBhyLqtgLafrAVgzhEzxKklmlS5dGklJSfZOBhFRgVKvXj3MnDnzidvJaE12bdYsYbCWN3bv3q0GzDll2GYtLS0tL5NVKOj1+jwNsBisUWa8ShIREeWTmjVr4tNPP7V3MvJcdtUgFSxZs42cvorGENusPZm8LlkjyowVlImIiOiJWFsNMjMGa/ZnWLJ2+fJlTJkyxb4JesqwGiTZ2lMRrKWkpODx48f2TgYRERGZwZK1p1fmDkb27t1rz+Q8dRiska1pKlhbt24dRo0aZTRu6tSpcHd3h7e3N1577TWr31dBRERE+cPaNmsM1rQn83vWGCzkTF4Fa0SWaCpY++qrr4xK0A4fPoypU6eiY8eOGDVqFHbu3ImZM2faMYVERESUmbUla5mx6377y1yyxsAjZ1iyRramqUdaoaGh6N+/v/p97dq18PHxwaZNm+Dk5AS9Xo8NGzZg1qxZdkwlERERGWKbtadX5kCbwULOZPVS7JyuB+DxJ1OaKllLTk6Gq6ur+n337t3o3LmzejGvU6cObt68aa/kERERkRm56bp/+fLl8PPzs1WSyErFihVD586dUbx4cQB8OXZOsRok2ZqmzsgqVaqoDVtPnDiBa9euoVOnTur0O3fuwN3d3V7JIyIiIjNy08HIyy+/DE9PT5umi7JXpUoV7NixAzVq1ADAkp2cYjVIsjVN1T8YMmQIRowYgQsXLuDmzZuoWLEiXnrpJXV6SEgI6tata8cUEhERUWa5abPG9mraxGAhZ/LqpdgM1sgSTQVrw4YNg6urK3bs2IEmTZpg7NixKFq0KAAgJiYGt2/fxtChQ+2cSiIiIjJkbZs1FxcX9TOr22kLg4XcyetqkDz+lJmmgjUAGDx4MAYPHmwyvkSJEjhx4oQdUkRERERZsbbNWs+ePbF48WIcPnyYJWsaxWAhZ/K6GiRRZnysRURERE/E2mqQTk5O+Oyzz1CrVi32BKkxLFnLHbZZI1uz65XyP//5T46X0el0CA4OtkFqiIiIKDdy0nV/586d0blzZ1sniXKJwULOsBok2Zpdg7XcNMpkMTEREZG25Pal2KQdLNnJnbx+zxpRZnYN1vbt22fPzRMREVEeyM171kibGKzlDKtBkq3xqkpERERPhCVrTz8GC7nDapBka5pt3RsfH4/Y2Fj1D8BQ5cqV7ZAiIiIiMicnbdZI25iHOcPeIMnWNBesLVu2DF9//TWuX79ucZ709PR8TBERERFlhdUgn34sWcsdvhSbbE1TV9VvvvkGH3zwAapVq4YZM2ZARDBy5EiMGzcOPj4+8Pf3x/fff2/vZBIREZEBVoMsOBgs5AyrQZKtaeqqumjRInTs2BG//fYb3nvvPQBA165dMXPmTFy4cAHx8fG4f/++nVNJREREhhisPf1YOpo7rAZJtqapMzI0NBTdunUDADg7OwMAUlJSAABeXl549913sXTpUrulj4iIiEyxzVrBwTzMGfYGSbamqWDNy8sLaWlpAABPT0+4ubkhIiJCne7h4YHbt2/bK3lERERkBktlnn4MFnInr96zpuDxp8w0dVWtV68ezp49q35v0aIFli1bhlu3biEiIgLffvstatSoYccUEhERUWasBllwMFjIGVaDJFvTVG+Qb775Jr755hskJyfDxcUFU6dOxQsvvKB21e/s7IwNGzbYOZVERERkiMHa048la7nDapBka5oK1gYOHIiBAweq31u1aoXz589j27ZtcHR0REBAAEvWiIiINIZt1goO5mHOsDdIsjVNBWvm+Pn5YcSIEfZOBhEREVnANmtPP5bs5A6rQZKt8apKRERET4TVIAsOBms5w2qQZGuaKllzcHCw6keanp6eD6khIiIia7Aa5NOPwULu6PV6VoMkm9JUsDZp0iSTH2l6ejrCwsKwefNm1KxZEy+99JKdUkdERETmsBpkwcFgIWdYDZJsTVPB2pQpUyxOi4qKQosWLdjBCBERkcawZO3px5K13Mmr96zx+JMlT80jsHLlymHo0KGYPn26vZNCREREBpSqYLzRfHoxWMgd9gZJtvbUBGsAUKxYMdy4ccPeySAiIiIDed1uh+yH+ZgzrAZJtvbUBGvnzp3DwoULWQ2SiIhIY6pWrYqePXvaOxn0BNjuMHfYGyTZmqbOyCpVqsDPz89kKFGiBPz9/XHnzh18/fXXOV5vcnIyxo4di/Lly6No0aJo3rw59uzZk+1yU6ZMUat1GA6urq652T0iIqIC6cUXX8S6devsnQzKAwwWcobVIMnWNNXBSLt27Ux+pDqdDsWLF0fVqlXxxhtvoESJEjle74ABAxAUFISRI0eievXqCAwMRJcuXfDHH3+gdevW2S6/bNkyuLu7q98dHR1znAYiIiIirWLJTu6wGiTZmqaCtcDAwDxf5/Hjx7Fu3TrMnTsXo0ePBgC8/fbbqFevHsaMGYPDhw9nu44ePXqgVKlSeZ42IiIiIi1hsJYzrAZJtqapapC2EBQUBEdHR7z33nvqOFdXVwwaNAhHjhxBREREtusQEcTFxfGpBxERERVIDBZyhy/FJluza8natGnTcryMTqfDxIkTrZ7/9OnTqFGjBjw9PY3GN2vWDABw5swZVKpUKct1+Pn54dGjRyhWrBheffVVfPXVVyhbtqzF+ZOTk5GcnKx+j4uLszq9RERERPbCYCFn8vo9a0SZ2TVYM/cSbOUikflHq9Pp1KLmnARrUVFRKFeunMl4ZVxkZKTFZYsXL44PP/wQLVu2hIuLCw4ePIglS5bg+PHjOHHihEkAqJg1axamTp1qdRqJiIiI7Ikla7nDapBka3YN1vR6vdH3W7duoWvXrqhXrx5GjhyJmjVrAgAuXbqE+fPn48KFC9i+fXuOtpGYmAgXFxeT8UqPjomJiRaXHTFihNH3119/Hc2aNUO/fv2wdOlSjBs3zuxy48ePx0cffaR+j4uLy7b0joiIiMjeGCzkDIM1sjVNtVn74IMPUL16dfz444949tln4eHhAQ8PDzRt2hQ//fQTqlatig8++CBH6yxatKhRlURFUlKSOj0n+vbtCx8fH+zdu9fiPC4uLvD09DQaiIiIiLSKwULu5HXX/USZaSpY+/333/Gf//zH4vQOHTogODg4R+ssV64coqKiTMYr48qXL5+zRAKoVKkSYmJicrwcERERkZYx8MgZlqyRrWkqWHN1dcWRI0csTj98+HCOX0jdsGFDXLlyxaSTj2PHjqnTc0JEEBYWhtKlS+doOSIiIiKtYrCQOwzWyNY0Faz169cPP/30E4YPH46rV69Cr9dDr9fj6tWrGDZsGNauXYt+/frlaJ09evRAeno6li9fro5LTk7GypUr0bx5c7Ut2T///INLly4ZLXv37l2T9S1btgx3795Fp06dcrGHRERERNrFYCFn8roaJI8/Zaapl2LPmTMH9+7dw+LFi7FkyRK1K1S9Xg8RQZ8+fTBnzpwcrbN58+bo2bMnxo8fj+joaFSrVg2rVq1CWFgYvv/+e3W+t99+G/v37zfqhdLX1xe9e/dG/fr14erqikOHDmHdunVo2LAhhgwZkjc7TURERGRnLNnJnbwuWSPKTFPBWpEiRbBmzRp88skn2LFjB8LDwwFkBE2dO3eGv79/rta7evVqTJw4EWvWrMGDBw/QoEED/Prrr2jbtm2Wy/Xr1w+HDx/Ghg0bkJSUBF9fX4wZMwYTJkyAm5tbrtJCREREpFUM1nJGr9fn6XvWePwpM00Fa4oGDRqgQYMGebY+V1dXzJ07F3PnzrU4z759+0zGfffdd3mWBiIiIiKtUoKFvAg8ChNWgyRb4xlJRERERAAYLOQUq0GSrdm1ZM3BwQEODg5ISEhAkSJF4ODgkO0PXqfTIS0tLZ9SSERERFTwsRpe7rA3SLI1uwZrkyZNgk6ng5OTk9F3IiIiIsp/vA/LGVaDJFuza7A2ZcqULL8TERERke2xZCf3WA2SbIlt1oiIiIgIAIO1nMjLAJfBMlmiqWAtODjYpMfGH374AZUrV0bZsmUxatQopKen2yl1RERERAUTg4Wcs8Ux4/GnzDQVrE2ZMgVnz55Vv//9998YMmQISpcujfbt22PhwoX48ssv7ZhCIiIiooKLwYL1bFGyRpSZpt6zdvHiRbz++uvq9zVr1sDT0xMHDx6Em5sbhg4ditWrV2Ps2LF2TCURERFRwcKStZxzcHBAeno6q0GSTWmqZO3x48fw9PRUv+/cuROdOnWCm5sbAKBp06YIDw+3V/KIiIiICjQGC9bT6XRWvXYqp+skMqSpYK1SpUr4888/AQDXrl3DuXPnEBAQoE6PiYmBi4uLvZJHREREVCCxZMe+WA2SLNFUNch+/fph2rRpuHXrFs6fP4/ixYvjlVdeUaefPHkSNWrUsGMKiYiIiAouBmv2wWCZLNFUsDZhwgSkpKRgx44dqFy5MgIDA+Ht7Q0go1Rt3759GDFihH0TSURERFTAMFjQBh5/ykxTwZqTkxNmzpyJmTNnmkwrUaIEbt++bYdUERERERUODg6aaiFTaLAaJFmi2TMyKioKZ8+exePHj+2dFCIiIqICjSVr9sXjT5ZoLljbsmULatWqhYoVK6Jx48Y4duwYAODevXto1KgRNm3aZOcUEhERERVMDBbsi8efMtNUsLZt2zZ0794dpUqVwuTJk42KhEuVKoUKFSogMDDQfgkkIiIiKoBYsmNfrAZJlmgqWJs2bRratm2LQ4cO4YMPPjCZ3rJlS5w+fdoOKSMiIiIq+Bis2QeDZbJEU8HauXPn0KtXL4vTy5Yti+jo6HxMEREREVHBx2BBG3j8KTNNBWtubm5Zdihy/fp1lCxZMh9TRERERFR4MFiwD1aDJEs0Faw9//zzWLVqFdLS0kym3b59G9999x0CAgLskDIiIiKigosla/bF40+WaCpYmzlzJm7evImmTZvi22+/hU6nw65du/DZZ5+hfv360Ov1mDx5sr2TSURERFQgMViwLx5/ykxTwVrNmjVx6NAhlCxZEhMnToSIYO7cufj8889Rv359hISEwNfX197JJCIiIipQWLJjX6wGSZY42TsBmdWtWxd79+7FgwcPcO3aNej1evj5+cHLywuBgYF4+eWXceXKFXsnk4iIiKjAYbBmHwyWyRJNBGspKSnYunUrQkNDUbx4cbz00ksoX748mjZtioSEBCxevBjz58/H7du3UbVqVXsnl4iIiKhAERH4+vri3XfftXdSCjUGa5SZ3YO1yMhItG/fHqGhoepTBVdXV2zbtg1FihRB3759cevWLTRr1gyLFi1C9+7d7ZxiIiIiooKnXr168PHxsXcyCiVWgyRL7B6sTZgwATdu3MCYMWPQpk0b3LhxA9OmTcN7772He/fuoW7duvjxxx/Rrl07eyeViIiIqEBisGBfrAZJltg9WNuzZw8GDhyIWbNmqeN8fHzQs2dPdO3aFVu2bIGDg6b6QSEiIiIqcBgo2A+DNbLE7lHQnTt30KJFC6Nxyvd33nmHgRoRERGRjbFkjUib7B4Jpaenw9XV1Wic8t3Ly8seSSIiIiIqdFiqYz8sWSNL7F4NEgDCwsJw6tQp9XtsbCwA4OrVq/D29jaZv3HjxvmVNCIiIqICT0QYKNgRgzWyRBPB2sSJEzFx4kST8e+//77Rd+VCkp6enl9JIyIiIioUGCjYH/OAMrN7sLZy5Up7J4GIiIioUGObNfvi8SdL7B6s9e/f395JICIiIir0WKpjP6wGSZbYvYMRIiIiIrIvluxoA4M1yozBGhERERExULAjBstkCYM1IiIiokKOwYJ9sRokWcJgjYiIiIgYKGgA84AyY7BGREREVMixZM2+ePzJEgZrRERERMRSHTtiNUiyhMEaERERUSHHkh1tYLBGmTFYIyIiIiIGCnbEYJksYbBGREREVMgxWLAvVoMkSxisERERERVyIsJAQQOYB5QZgzUiIiIiYqBgRyzZJEsYrBEREREVcgwW7IvVIMkSBmtERERExEBBA5gHlBmDNSIiIqJCjiVr9sXjT5YwWCMiIiIilurYEatBkiUM1oiIiIgKOZbsaAODNcqMwRoRERERMVCwIwbLZAmDNSIiIqJCjsGCffn4+KBXr15wc3Ozd1JIY5zsnQAiIiIisj+WrNlPo0aNsH79ensngzSIJWtEREREhRxL1oi0icEaEREREbFkjUiDGKwRERERFXIsWSPSJgZrRERERMSSNSINYrBGREREVMixZI1ImxisERERERFL1og0iMEaERERUSHHkjUibWKwRkREREQsWSPSoEIRrCUnJ2Ps2LEoX748ihYtiubNm2PPnj1WLXvr1i306tUL3t7e8PT0xCuvvILr16/bOMVERERE+ee5555Dw4YN7Z0MIspEJ4Wg3LtPnz4ICgrCyJEjUb16dQQGBuLPP//EH3/8gdatW1tc7tGjR2jcuDFiY2Px8ccfw9nZGfPmzYOI4MyZMyhZsqRV24+Li4OXlxdiY2Ph6emZV7tFRERERERPmZzEBgU+WDt+/DiaN2+OuXPnYvTo0QCApKQk1KtXD2XKlMHhw4ctLvvFF19g7NixOH78OJo2bQoAuHTpEurVq4cxY8bg888/tyoNDNaIiIiIiAjIWWxQ4KtBBgUFwdHREe+99546ztXVFYMGDcKRI0cQERGR5bJNmzZVAzUAqFWrFjp06ICff/7ZpukmIiIiIqLCrcAHa6dPn0aNGjVMotZmzZoBAM6cOWN2Ob1ej7/++gvPPvusybRmzZohNDQU8fHxZpdNTk5GXFyc0UBERERERJQTBT5Yi4qKQrly5UzGK+MiIyPNLhcTE4Pk5ORcLTtr1ix4eXmpQ6VKlXKbfCIiIiIiKqQKfLCWmJgIFxcXk/Gurq7qdEvLAcjVsuPHj0dsbKw6ZFXVkoiIiIiIyBwneyfA1ooWLYrk5GST8UlJSep0S8sByNWyLi4uZoM8IiIiIiIiaxX4krVy5cohKirKZLwyrnz58maXK1GiBFxcXHK1LBERERER0ZMq8MFaw4YNceXKFZNOPo4dO6ZON8fBwQH169fHiRMnTKYdO3YMfn5+8PDwyPP0EhERERERAYWgGmSPHj3w5ZdfYvny5ep71pKTk7Fy5Uo0b95c7fzjn3/+QUJCAmrVqmW07Lhx43DixAm1V8jLly/j999/V9dlDeVVduwVkoiIiIiocFNiAmted13gX4oNAL169cKmTZswatQoVKtWDatWrcLx48cRHByMtm3bAgDat2+P/fv3Gx20+Ph4NGrUCPHx8Rg9ejScnZ3x9ddfIz09HWfOnEHp0qWt2v7NmzfZIyQREREREakiIiJQsWLFLOcpFMFaUlISJk6ciB9//BEPHjxAgwYNMH36dHTs2FGdx1ywBmQEWqNGjcLu3buh1+vRvn17zJs3D9WqVbN6+3q9HpGRkfDw8IBOp3vi/YmLi0OlSpUQERGR7VvPKf8xf7SLeaNtzB9tY/5oF/NG25g/2maP/BERxMfHo3z58nBwyLpVWqEI1gqauLg4eHl5ITY2lie9BjF/tIt5o23MH21j/mgX80bbmD/apvX8KfAdjBARERERET2NGKwRERERERFpEIO1p5CLiwsmT57MF29rFPNHu5g32sb80Tbmj3Yxb7SN+aNtWs8ftlkjIiIiIiLSIJasERERERERaRCDNSIiIiIiIg1isEZERERERKRBDNaIiIiIiIg0iMEaEREREREVOAWhH0UGa0T01CsIF2MiInp6xMbG2jsJlIX169cDAHQ6nZ1T8uQYrGnA6dOn8c8//xid+Lz51IaEhAR7J4GycP36dSQkJCApKcneSSEzzp49i6tXr+LmzZvqOF7btGHLli14//33cf36dQCAXq+3c4rI0P/+9z94eHggJCTE3kmhTDZu3IiAgADMmzcPYWFh9k4OZbJu3TpUrVoVffr0waFDh+ydnDzBYM2OLl68iNatW6NDhw7w9/dHs2bNsGHDBqSlpUGn0/Gmxo4uX76MJk2a4N1337V3UsiMv/76C127dkW3bt1QpUoVtG/fHiEhITxnNOKvv/7Ciy++iJdeeglNmjSBv78/Fi5cqF7byL727NmD1157DWvWrMGvv/4KAHBw4O2AFpw+fRrNmzfHO++8g65du8LT09PeSaL/FxkZia5du+Ltt99GkSJF4ObmBjc3N3sni/6fcu70798fHh4ecHV1RXJysr2TlSd4dbaT6Oho9OvXDyKCr776Cl9//TVKlCiBd999FzNmzLB38gotEcGGDRvw8ssv4/Tp01i3bh32799v72TR/0tPT8eiRYvwwgsv4PHjx+jRowd69OiBqKgovPvuuzhw4IC9k1iopaam4vPPP0e7du2QmpqKsWPHYvny5WjQoAEmTpyIbdu22TuJhZryMKNkyZIoUaIE0tPTsXbtWpw9exYAS9fsKTExEe+88w6aNGmCokWLYv369Vi4cCHq169v76TR/1u+fDlu3LiB5cuXY9myZRgzZgzKlClj72QVenFxcejfvz+aNGkCNzc3/PLLL/j8888hIjhz5gyAjHuHp5qQXaxbt06cnJwkKChIHXfz5k3p3bu36HQ62bt3rx1TV3iFhoZKvXr1pGTJkjJjxgypU6eOtGjRQlJTU+2dNBKRnTt3ip+fn7zzzjty6dIldXxISIjodDoZO3Ys88qOtm/fLo0bN5aRI0fKlStXJC0tTURErl69KjqdTr744gvR6/V2TiUFBQVJQECAfPPNN6LT6eTTTz9V84r5k//S0tJk5syZotPpZPDgwXL37l2L1zHmj338888/UrZsWRk+fLjJeEPMn/z1+PFjqV69uvj5+cmyZcskPDxcRESuX78uxYsXl+7du0t6erqdU/nknOwdLBZW4eHhKFasGF577TUAGU+kK1SogDFjxuDGjRsYOXIkgoOD+dQmnzk5OeHll19Gr1694O/vj+LFi+PDDz/EqlWrMGjQIHsnr9C7cOECXFxcMHv2bJQuXRoAkJKSgueeew7NmzfHqVOn4OTkBBFhdTs78PLyQr9+/fDWW2+p+QMA586dQ+nSpeHr66tW8Wb+5D/luFeqVAnHjh3Drl27EBQUhJUrV+L555/HCy+8YO8kFkqOjo7o2LEjduzYgYMHD6JUqVIAgK1bt2Ljxo0oW7YsatWqhX79+qFIkSJ2Tm3hFBYWhvj4eHz44YcAgDVr1mD27NkAgBo1aqBXr17o06cPr2v5SK/Xw83NDatWrYKnpydq1KgBZ2dnAECVKlVQrVo1xMTEIDU1FUWKFHmq84bVIG1MqVYimdrSFClSBHq9Xq22pbQXaNSoET7++GNcvXoV33//vdllKW+Yy5vKlStj0qRJ8Pf3BwC88MILePHFFzFlyhTcv3/fLuksrAzzR8mjUaNGYfPmzShdurQ6vUiRIkhPT4erqysSExORlJT0VF+Unxbmzp9WrVrho48+MgrUDh06hIkTJyIpKQkXL17EuXPn1M6UWO3ONiz97yjnRUREhJpHc+fOxe3bt/Hjjz/iwYMHbC+dD8zlT5MmTfDWW2/h8uXLGD16NDp27IhXX30VISEhWLZsGQYNGoQ+ffrg/PnzRuugvGXp3HFzc0NKSgrOnz+PlStXYsCAAahTpw6aNm2Kw4cPo1+/fggMDLRDigsXw/xR7ptbtmyJunXrqoGaiECv16NZs2Y4ffo0EhMTn/rrGoM1G1HabqxcuRLAv3+Syo+lXr16SElJwf79+yEicHR0hF6vh06nQ7t27fDKK69g3rx5SElJ4Y1nHrOUNwoXFxf1c40aNTBo0CDcv38fX3zxRb6ms7Aylz+GeVSjRg0A/z7gUC7asbGxqFChAlxdXZ/qi7LWZXf+AP/+oY4bNw5t27ZF6dKl8dprryEiIgJt2rTBf//7XwDs1CKvZZc3ynlRuXJl3LlzB1FRUWjYsCHeeecdrFu3Djt37gSQ0X6K8l529wWdO3fG66+/jq+//hppaWn47bffEBwcjEuXLmHatGnYvHkzpk6dCoDnTl6z5rrm7e2NDRs2YMGCBZgwYQJWrlyJwMBA7N27FwEBARg9ejQuXbqU30kvFKzJH4VOp4ODgwNKlCiBuLg4HDx4MNtlNC8/61wWFgcOHJC6deuKTqeTgIAAuXDhgoiY1mVu3LixNGrUSP7++2+T6T/99JM4OTnJsmXLzC5LuWNt3hiOi46OlnfeeUdcXV3l3LlzFuenJ5eT/DEUEREhxYoVk1mzZomIqO1vKG9Zmz/K902bNsn69evl3r176rjx48eLg4ODzJ07V0SkQLQn0IKcnDs///yz1KhRQ+7cuSMiInFxceLm5ibPP/+8DBw4UN566y2JjIzM1/QXdNbmz08//SQDBgyQkJAQk2n9+vUTLy8v2bp1q9llKXeszZtWrVqJg4ODlCpVSg4fPmw0bffu3VKiRAkZMWKEiPC6lpdyel+gHPuDBw+KTqeTn3/+Ocv5nwYM1vLYkSNHpFatWvLMM89Iz549RafTyZw5c4waCys3klu2bBGdTiczZsyQxMREo2mXL1+WihUrynvvvceTPo9YkzeWBAcHS4UKFeS1117Lh5QWTk+SPwcOHBCdTie7du3Kh5QWTjnJn6z+FK9evSrVqlUTf39/SUpKsmWSCw1r80bJl4MHD4qbm5tERESo0/r06SOOjo7i7OwskydPlkePHuXrPhRk1uSPkjexsbESHR1ttLwy39GjR0Wn08mUKVOe6htPLcnJPdvOnTtFp9OJTqeTixcviohIcnKyiGQ81O3UqZNUqlSJ17U89CT3BefOnZPixYvLsGHDRITBGhm4cOGCuLi4yC+//CIiIm3atJHq1atLSEiI2fm7dOki5cuXl23btomIcYlA3bp15e233xaRp/tHphU5zRuRf4/7o0ePZOLEiaLT6SQ4OFhERPbv3y9btmwxmo9yLzf5o1i6dKk4OTlJfHy8iGScR6GhoXLixAkRYf7khSfJHxHjJ80tW7aUFi1a8KYmj2TOm7Zt22aZN+vWrZOaNWvKw4cP5Y8//pDWrVuLo6OjeHp6SrVq1eTgwYMiwvMmr+T23FGOv3Lu3L17V7y9vWXMmDG2TXAhktO86devn+h0OhkyZIiIiFHQ0KNHD6lTp47ExsbaPuGFxJP870RHR4uvr6906NBB4uLibJ1Um2KwloeUQMvwqZjyxH/48OHqCWx40xIeHi7u7u7SokULOXXqlDr+6NGj4unpKVOnTs2n1Bds1uaNuZsTJb8uXbokjRs3lvr168vUqVOlUqVKUrJkSbUqEeXek+SPiEi3bt3kueeeE5GMKpE//vijNGrUSBo3biz379+3ceoLvrw4fxS7du0SZ2dnGTlypA1TXHjkJG+U/AkODpYiRYrISy+9JI6OjtKqVSs5cOCA/Pzzz+qNqFJiQE8mL8+dpUuXik6nk++++86GKS48cnPPFhERIZ6eniY1Oc6fPy9Vq1aVN998kw858khenDvdu3eXunXryqNHj57qfGGwlkvr1q2TIUOGyOzZs+XAgQPqeMMfg/Jj6d+/v3h7e8vmzZuN1qH8EAMDA6Vy5cpSpUoVWbhwoaxYsUK6desmlSpVkr/++isf9qZgyYu8MSc8PFwGDBigVoN45ZVXjKoRkXXyMn/0er3Ex8dLuXLl5I033pC9e/fKyy+/LDqdTjp16iQ3b9607c4UQLY6fyIjI2Xbtm3Srl07qVOnjtpWl6yXV3kTEhIiDRo0kNq1a8vixYslIiJC/T9q1aqVDB48mMFaLtjq3Ll9+7Zs2rRJGjRoIO3atZN79+7lfeILuLy8Z1u3bp2UK1dOSpQoIYMHD5bPP/9cOnfuLMWLF2dV/Fyyxbmj1+tlxowZotPp5PLlyybre5owWMuh27dvS8eOHaVYsWLSuHFjKV68uLi4uMjkyZPlwYMHIiImLxe9efOmuLu7S/fu3dWb+/T0dKMfzb59+6RVq1bi5eUlJUuWlAYNGsihQ4fyd+eecnmZN5kdPHhQOnXqJA4ODtKoUSOrq37Rv2yVP9euXRM3Nzdp3LixuLu7S82aNdWqqmQ9W+XPvn37ZPDgwdKjRw/x8PAQf39/+fPPP/NvxwqAvMobpcpWSkqKHDhwQP7++281KFOWU9pPk/Vsee4MHTpU+vTpI+7u7tK4cWM5c+ZM/u1YAWCre7aQkBDp2LGjeHt7S5kyZaRRo0ZGQQZZx5b3bSIi8+bNE51OJ0FBQbbfGRtisJZDq1atkhIlSshPP/0kkZGRcv/+fRkwYIB4eHjI+++/bzK/8uOaOXOmODg4yPLly41OeMPPiYmJcufOHd7I5FJe542hvXv3SpEiRWTx4sU23YeCzFb58/vvv4tOp5MyZcowf56ArfJn27ZtUq1aNWnfvr388MMPNt+PgsgWefO0PmHWIludO0FBQeLu7i7Nmzdn1cdcsuU9W3Jysjx48EDOnj1r+x0poGx17ijBW1RUlAQGBtp2J/IBg7UcateunbRo0cJo3OPHj6V///6i0+lk+/btImIa5aekpEjVqlWlefPmcuXKFRERCQ0NNaqLy14fn4wt80aE3cE/qbzOH8O2gt9++62kpKTYeA8KNlvmT2hoKK9vTyAv8+batWsm1zZ6MrY8d86ePcv/nifAezZts2X+FKQHUgzWrJSeni5JSUnSsWNHadWqlTpeqVZy8uRJadKkifj5+Zn8QDJ31T927FhZuXKlNG7cWIYPHy6PHz/Ovx0pgJg32mbL/Hnae3jSAlvmD7t/fzK2zJuEhIT825ECiueOdvG+QNuYPznDYM2MixcvyogRI2TYsGEyYcIENWoXEXn11VelZs2aauN4w2h/+fLlotPpZN68eSJiWhKTmpoqTZs2FUdHR9HpdFKuXDnZuXOn7XeoAGHeaBvzR9uYP9rFvNE25o92MW+0jfnz5BisGUhOTpbRo0dL0aJF5dlnn5Xq1auLTqcTPz8/9R0PQUFBotPp5IcfflB/VMoPKCwsTDp06CBVqlQxabR96tQpmTBhgri7u4uHh4fMnz/fDnv49GLeaBvzR9uYP9rFvNE25o92MW+0jfmTdxis/b/4+Hj59NNPxc/PT+bMmSOXL1+W9PR02bt3r5QvX17atGkjCQkJkpaWJv7+/tK2bVsJCwszWc+UKVPE29tbrWcrkvHj+vDDD0Wn00n//v3VF/eSdZg32sb80Tbmj3Yxb7SN+aNdzBttY/7kLQZr/+/GjRtSpUoVGTJkiDx8+NBo2pAhQ6R06dJy4sQJERFZs2aN6HQ6+frrr9W6sUrUf/r0aXFwcJBNmzaJyL/1b48fPy4XLlzIp70pWJg32sb80Tbmj3Yxb7SN+aNdzBttY/7kLQZr/0+v18vy5cuNxim9y/3888/i5OQkFy9eFBGRhw8fSvfu3cXHx8fkpXzHjx8XnU4nq1atyp+EFwLMG21j/mgb80e7mDfaxvzRLuaNtjF/8haDNQNKxJ65EePcuXPF0dFRLl26pI6LiIiQsmXLSt26ddUGjbdu3ZIPP/xQfH195fbt2/mX8EKAeaNtzB9tY/5oF/NG25g/2sW80TbmT95hsJYFpbHjiBEjxMfHR30qoPzwdu3aJY0bNxadTicNGzaUli1birOzs0ydOlXS0tIK1DsetIZ5o23MH21j/mgX80bbmD/axbzRNuZP7ulEREBZevbZZ/HMM88gKCgI6enpcHR0VKfdu3cP33//PUJDQxEXF4cRI0agZcuWdkxt4cK80Tbmj7Yxf7SLeaNtzB/tYt5oG/MnF+wdLWpddHS0FC1aVObOnauOS09Pl5iYGDumikSYN1rH/NE25o92MW+0jfmjXcwbbWP+5I6DvYNFrTt37hySkpLQtGlTAMDt27exdu1adOzYEXfv3rVz6go35o22MX+0jfmjXcwbbWP+aBfzRtuYP7nDYM0C+f/aoX/++Se8vLxQvnx57Nu3D++//z7eeecdiAgcHBzU+Sj/MG+0jfmjbcwf7WLeaBvzR7uYN9rG/HkyTvZOgFbpdDoAwLFjx1CyZEnMnTsX69atg4+PD7Zv344XX3zRziksvJg32sb80Tbmj3Yxb7SN+aNdzBttY/48ofyrcfn0SUxMlIYNG4pOpxNPT0+ZN2+evZNE/495o23MH21j/mgX80bbmD/axbzRNuZP7rE3yGyMHTsWOp0OU6dOhYuLi72TQwaYN9rG/NE25o92MW+0jfmjXcwbbWP+5A6DtWzo9Xo4OLBpnxYxb7SN+aNtzB/tYt5oG/NHu5g32sb8yR0Ga0RERERERBrE8JaIiIiIiEiDGKwRERERERFpEIM1IiIiIiIiDWKwRkREREREpEEM1oiIiIiIiDSIwRoREREREZEGMVgjIiIiIiLSIAZrREREREREGsRgjYiIiIiISIMYrBEREREREWkQgzUiIiIiIiIN+j9F/vZDxzyJrwAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -62924,7 +32592,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.7" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/docs/degradation_and_soiling_example.ipynb b/docs/degradation_and_soiling_example.ipynb index 3f32d0e4b..db9405dd7 100644 --- a/docs/degradation_and_soiling_example.ipynb +++ b/docs/degradation_and_soiling_example.ipynb @@ -32,10 +32,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:13.141622Z", - "iopub.status.busy": "2026-02-04T19:26:13.140622Z", - "iopub.status.idle": "2026-02-04T19:26:17.065980Z", - "shell.execute_reply": "2026-02-04T19:26:17.065980Z" + "iopub.execute_input": "2026-03-20T15:40:03.434045Z", + "iopub.status.busy": "2026-03-20T15:40:03.433440Z", + "iopub.status.idle": "2026-03-20T15:40:06.636469Z", + "shell.execute_reply": "2026-03-20T15:40:06.635075Z" } }, "outputs": [], @@ -53,10 +53,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:17.068991Z", - "iopub.status.busy": "2026-02-04T19:26:17.068991Z", - "iopub.status.idle": "2026-02-04T19:26:17.080496Z", - "shell.execute_reply": "2026-02-04T19:26:17.079990Z" + "iopub.execute_input": "2026-03-20T15:40:06.638962Z", + "iopub.status.busy": "2026-03-20T15:40:06.638591Z", + "iopub.status.idle": "2026-03-20T15:40:06.649321Z", + "shell.execute_reply": "2026-03-20T15:40:06.648220Z" } }, "outputs": [], @@ -78,10 +78,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:17.083512Z", - "iopub.status.busy": "2026-02-04T19:26:17.083512Z", - "iopub.status.idle": "2026-02-04T19:26:17.085952Z", - "shell.execute_reply": "2026-02-04T19:26:17.085952Z" + "iopub.execute_input": "2026-03-20T15:40:06.652063Z", + "iopub.status.busy": "2026-03-20T15:40:06.651704Z", + "iopub.status.idle": "2026-03-20T15:40:06.655295Z", + "shell.execute_reply": "2026-03-20T15:40:06.654606Z" } }, "outputs": [], @@ -111,16 +111,16 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:17.087964Z", - "iopub.status.busy": "2026-02-04T19:26:17.087964Z", - "iopub.status.idle": "2026-02-04T19:27:47.520756Z", - "shell.execute_reply": "2026-02-04T19:27:47.520756Z" + "iopub.execute_input": "2026-03-20T15:40:06.657430Z", + "iopub.status.busy": "2026-03-20T15:40:06.657147Z", + "iopub.status.idle": "2026-03-20T15:41:50.529683Z", + "shell.execute_reply": "2026-03-20T15:41:50.528520Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -198,16 +198,16 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:27:47.574769Z", - "iopub.status.busy": "2026-02-04T19:27:47.573846Z", - "iopub.status.idle": "2026-02-04T19:28:55.133218Z", - "shell.execute_reply": "2026-02-04T19:28:55.132714Z" + "iopub.execute_input": "2026-03-20T15:41:50.576933Z", + "iopub.status.busy": "2026-03-20T15:41:50.576427Z", + "iopub.status.idle": "2026-03-20T15:43:03.651629Z", + "shell.execute_reply": "2026-03-20T15:43:03.650121Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -241,16 +241,16 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:28:55.141223Z", - "iopub.status.busy": "2026-02-04T19:28:55.141223Z", - "iopub.status.idle": "2026-02-04T19:30:37.831763Z", - "shell.execute_reply": "2026-02-04T19:30:37.830763Z" + "iopub.execute_input": "2026-03-20T15:43:03.655034Z", + "iopub.status.busy": "2026-03-20T15:43:03.654640Z", + "iopub.status.idle": "2026-03-20T15:44:52.903880Z", + "shell.execute_reply": "2026-03-20T15:44:52.902048Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -298,16 +298,16 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:30:37.835763Z", - "iopub.status.busy": "2026-02-04T19:30:37.835763Z", - "iopub.status.idle": "2026-02-04T19:31:13.058697Z", - "shell.execute_reply": "2026-02-04T19:31:13.058188Z" + "iopub.execute_input": "2026-03-20T15:44:52.909279Z", + "iopub.status.busy": "2026-03-20T15:44:52.908586Z", + "iopub.status.idle": "2026-03-20T15:45:28.982781Z", + "shell.execute_reply": "2026-03-20T15:45:28.981346Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -353,10 +353,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:13.063214Z", - "iopub.status.busy": "2026-02-04T19:31:13.062204Z", - "iopub.status.idle": "2026-02-04T19:31:13.552492Z", - "shell.execute_reply": "2026-02-04T19:31:13.551984Z" + "iopub.execute_input": "2026-03-20T15:45:28.985578Z", + "iopub.status.busy": "2026-03-20T15:45:28.985130Z", + "iopub.status.idle": "2026-03-20T15:45:30.314151Z", + "shell.execute_reply": "2026-03-20T15:45:30.312645Z" } }, "outputs": [], @@ -376,42 +376,13 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:13.558508Z", - "iopub.status.busy": "2026-02-04T19:31:13.557508Z", - "iopub.status.idle": "2026-02-04T19:31:14.936742Z", - "shell.execute_reply": "2026-02-04T19:31:14.936742Z" + "iopub.execute_input": "2026-03-20T15:45:30.317892Z", + "iopub.status.busy": "2026-03-20T15:45:30.317498Z", + "iopub.status.idle": "2026-03-20T15:45:33.184924Z", + "shell.execute_reply": "2026-03-20T15:45:33.183490Z" } }, "outputs": [ - { - "data": { - "text/html": [ - " \n", - " " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, { "data": { "application/vnd.plotly.v1+json": { @@ -5935,5510 +5906,10 @@ "2010-03-07T17:44:00-07:00" ], "xaxis": "x", - "y": [ - 62.464, - 84.915, - 94.197, - 27.059, - 79.618, - 67.46300000000001, - 40.778, - 169.49900000000002, - 151.93200000000002, - 150.47799999999998, - 209.925, - 42.622, - 104.47, - 165.442, - 67.942, - 50.572, - 128.297, - 124.697, - 109.259, - 20.237, - 0.556, - 82.806, - 110.702, - 95.232, - 104.321, - 123.959, - 128.264, - 176.315, - 79.442, - 93.861, - 133.208, - 133.72, - 91.747, - 136.616, - 114.572, - 123.342, - 125.693, - 152.42700000000002, - 69.164, - 13.053, - 85.256, - 45.524, - 167.98, - 152.334, - 146.173, - 141.785, - 181.479, - 236.137, - 258.202, - 205.064, - 249.933, - 229.574, - 207.085, - 238.036, - 124.152, - 220.435, - 163.289, - 76.266, - 218.112, - 214.506, - 106.342, - 58.313, - 200.269, - 49.003, - 174.21200000000002, - 170.68900000000002, - 160.465, - 140.541, - 118.305, - 96.531, - 33.654, - 58.676, - 45.17100000000001, - 24.229, - 39.969, - 31.975, - 28.143, - 26.805, - 15.784, - 17.555999999999997, - 7.838999999999999, - 15.050999999999998, - 7.058, - 5.285, - 3.512, - 6.777, - 5.235, - 4.965, - -4.763, - -3.006, - 6.815, - 3.892, - 6.865, - 10.52, - 10.13, - 21.751, - 9.953, - 31.54, - 3.859, - 10.867, - 34.931, - 31.656, - 28.595, - 14.6, - 18.283, - 13.857, - 6.942, - 9.689, - 7.553, - 3.941, - 3.897, - 5.4, - 7.282999999999999, - 7.861000000000001, - 5.433, - 5.472, - 5.2075000000000005, - 4.9430000000000005, - -0.815, - -0.193, - 5.307, - 4.5360000000000005, - 7.146, - 2.009, - 7.058, - 4.96, - 6.265, - 5.7860000000000005, - 2.02, - 7.443, - 2.824, - 5.053999999999999, - 7.3, - 4.96, - 5.684, - 6.408, - 3.149, - 1.971, - 2.67, - 2.081, - -1.492, - -1.669, - -2.219, - -1.481, - -0.672, - -3.628, - -5.638, - -0.397, - -0.534, - 1.079, - 3.451, - 3.65, - -0.738, - 0.759, - -1.294, - 2.857, - 1.596, - 2.51, - 1.514, - 1.8, - 2.736, - -1.47, - 0.754, - 4.6080000000000005, - 1.2990000000000002, - 3.589, - 3.033, - 3.2645, - 3.4960000000000004, - 3.49, - 1.855, - 5.702999999999999, - 3.567, - 1.927, - 6.683, - 1.585, - 5.587999999999999, - 2.516, - 6.738, - 1.249, - 2.989, - 9.568, - 10.504, - 9.524, - 11.17, - 15.503, - 17.11, - 13.939, - 8.037, - 6.54, - 16.02, - 13.824000000000002, - 16.202, - 5.318, - 15.442, - 22.792, - 17.875999999999998, - 20.931, - 12.513, - 6.082999999999999, - 20.882, - 12.029000000000002, - 18.316, - 0.589, - 8.913, - 17.76, - 19.72, - 19.384, - 29.536, - 28.545, - 30.582, - 25.886, - 23.078000000000003, - 32.509, - 6.457000000000001, - 0.5720000000000001, - 41.857, - 33.819, - 19.775, - 45.342, - 48.084, - 17.435, - 31.375, - 51.618, - 53.6, - 59.17100000000001, - 20.425, - 39.649, - 33.643, - 67.33, - 42.82, - 9.364, - 86.836, - 73.35300000000001, - 75.979, - 83.478, - 97.225, - 36.385, - 91.345, - 123.227, - 78.204, - 123.293, - 146.674, - 3.011, - 76.205, - 150.632, - 15.970999999999998, - 65.827, - 220.914, - 166.02, - 280.02, - 303.121, - 335.624, - 148.072, - 145.898, - 11.478, - 497.169, - 207.266, - 596.558, - 640.1990000000001, - 630.46, - 360.399, - 528.313, - 725.6310000000001, - 451.617, - 93.244, - 718.199, - 649.217, - 524.283, - 204.75, - 344.686, - 551, - 668.64, - 652.889, - 485.25, - 71.206, - 540.865, - 415.04, - 773.0989999999999, - 625.9730000000001, - 669.1460000000001, - 721.442, - 306.253, - 482.728, - 607.849, - 180.053, - 691.492, - 531.721, - 11.88, - 746.034, - 567.456, - 609.528, - 374.057, - 734.33, - 626.099, - 229.238, - 590.474, - 571.409, - 340.298, - 192.44, - 482.453, - 726.341, - 377.641, - 125.61, - 31.689, - 625.604, - 337.023, - 666.823, - 225.555, - 526.496, - 721.1610000000001, - 425.957, - 742.324, - 789.455, - 705.828, - 174.15099999999998, - 610.145, - 445.699, - 87.992, - 406.027, - 474.762, - 674.541, - 390.348, - 669.0360000000001, - 227.02, - 404.64, - 473.6830000000001, - 731.186, - 676.055, - 233.626, - 734.7919999999999, - 550.967, - 412.386, - 445.859, - 587.132, - 662.039, - 559.451, - 668.7389999999999, - 772.1410000000001, - 342.68800000000005, - 417.682, - 766.5360000000001, - 463.872, - 615.457, - 565.045, - 524.756, - 706.544, - 286.659, - 467.539, - 209.87, - 31.292, - 592.489, - 119.499, - 505.757, - 564.109, - 749.7280000000001, - 494.086, - 342.36800000000005, - 711.681, - 607.965, - 641.663, - 236.472, - 285.151, - 610.508, - 762.5889999999999, - 141.582, - 653.434, - 776.633, - 652.151, - 583.653, - 645.577, - 523.441, - 416.504, - 774.574, - 166.025, - 658.95, - 409.661, - 245.534, - 615.48, - 786.581, - 732.54, - 261.885, - 567.307, - 180.703, - 489.973, - 122.533, - 90.47, - 561.808, - 633.8290000000001, - 611.549, - 629.689, - 690.7660000000001, - 712.765, - 766.602, - 488.459, - 672.824, - 423.254, - 658.262, - 184.48, - 602.58, - 438.465, - 454.67800000000005, - 277.62, - 594.394, - 694.735, - 282.844, - 675.158, - 562.215, - 578.9069999999999, - 493.585, - 629.5840000000001, - 750.345, - 767.5269999999999, - 275.863, - 759.847, - 721.21, - 380.961, - 0.4679999999999999, - 377.454, - 713.409, - 204.596, - 427.261, - 655.096, - 767.423, - 765.419, - 338.305, - 348.51800000000003, - 289.588, - 479.64, - 440.32, - 502.399, - 417.6880000000001, - 744.8889999999999, - 745.4010000000001, - 742.5269999999999, - 738.6569999999999, - 599.448, - 484.804, - 306.132, - 257.222, - 46.058, - 579.304, - 542.891, - 570.346, - 697.35, - 362.452, - 410.019, - 693.706, - 417.165, - 457.277, - 501.485, - 567.462, - 437.986, - 423.529, - 280.02, - 460.806, - 525.819, - 501.612, - 657.948, - 638.514, - 20.276, - 456.027, - 626.991, - 576.606, - 376.48, - 15.057, - 631.2080000000001, - 439.17, - 622.24, - 498.628, - 566.052, - 513.492, - 390.304, - 406.594, - 603.599, - 479.535, - 409.441, - 408.262, - 490.832, - 494.895, - 581.842, - 575.433, - 403.071, - 333.521, - 299.559, - 386.72, - 512.7330000000001, - 555.614, - 551.65, - 411.42800000000005, - 431.099, - 541.746, - 535.927, - 435.608, - 443.811, - 413.437, - 232.156, - 463.569, - 338.79, - 497.3730000000001, - 333.819, - 404.932, - 337.07199999999995, - 322.307, - 258.956, - 470.126, - 455.273, - 397.852, - 291.014, - 435.305, - 355.031, - 0.402, - 389.77, - 362.722, - 207.938, - 358.907, - 197.731, - 365.552, - 380.576, - 347.219, - 73.485, - 211.373, - 263.096, - 59.403, - 90.756, - 250.891, - 269.648, - 223.557, - 219.11900000000003, - 224.762, - 245.105, - 202.466, - 60.674, - 240.998, - 185.327, - 52.675, - 189.264, - 119.566, - 90.673, - 121.702, - 88.37799999999999, - 116.037, - 88.76299999999999, - 102.438, - 107.85, - 97.764, - 103.952, - 92.253, - 80.791, - 61.445, - 44.213, - 0.429, - 39.936, - 51.13399999999999, - 54.354, - 64.15899999999999, - 26.227, - 0.335, - 43.156000000000006, - 41.059, - 40.954, - 48.133, - 37.183, - 25.748, - 35.311, - 28.848000000000003, - 20.342, - 24.763, - 29.96, - 28.506, - 23.535, - 31.386, - 21.707, - 22.852, - 23.155, - 23.618, - 19.059, - 23.089, - 14.897, - 3.859, - 12.018, - 15.013, - 13.515, - 5.769, - 6.727, - 2.962, - 10.152, - 12.645, - 9.106, - 0.451, - 3.991, - 5.059, - 5.516, - 0.528, - 6.215, - 0.589, - 3.782, - -1.019, - 0.09050000000000002, - 1.2, - 0.748, - -2.395, - -1.779, - 0.297, - -1.024, - 1.238, - 2.989, - 1.915, - 5.092, - 6.155, - 4.591, - 8.467, - 7.245, - 12.233, - 13.548, - 19.56, - 30.499, - 43.558, - 40.36, - 24.647, - 29.668000000000003, - 46.983, - 43.696000000000005, - 0.6659999999999999, - 0.677, - 16.059, - 31.441, - 62.458, - 69.428, - 51.877, - 52.697, - 93.938, - 62.965, - 77.4, - 75.638, - 96.476, - 79.387, - 41.852, - 92.044, - 87.34299999999999, - 63.438, - 84.116, - 80.65899999999999, - 117.98, - 121.867, - 153.159, - 131.066, - 48.188, - 226.486, - 162.739, - 42.969, - 121.735, - 112.871, - 125.021, - 129.31, - 11.148, - 116.917, - 131.408, - 95.92, - 96.074, - 130.158, - 142.512, - 78.473, - 100.308, - 213.036, - 224.526, - 113.79, - 131.892, - 130.918, - 202.504, - 215.15, - 141.59799999999998, - 164.55, - 116.45, - 167.91400000000002, - 160.74, - 152.179, - 9.469, - 124.019, - 247.246, - 227.889, - 160.939, - 138.43200000000002, - 138.493, - 36.935, - 107.619, - 116.251, - 92.897, - 11.561, - 5.7860000000000005, - 126.849, - 134.314, - 134.81, - 116.18, - 139.908, - 118.255, - 0.638, - 71.184, - 118.894, - 145.16, - 10.074, - 60.41, - 148.17700000000002, - 118.723, - 157.079, - 157.239, - 83.5, - 171.43200000000002, - 168.602, - 171.861, - 94.934, - 185.674, - 113.02, - 65.58, - 151.233, - 101.2, - 87.095, - 164.055, - 259.777, - 306.815, - 29.987, - 12.359000000000002, - 152.091, - 86.324, - 302.46, - 282.718, - 17.127, - 260.9, - 315.48, - 25.534, - 156.336, - 240.37, - 171.845, - 189.401, - 197.781, - 171.856, - 170.391, - 160.482, - 264.54400000000004, - 171.696, - 281.435, - 312.66700000000003, - 355.75800000000004, - 436.912, - 318.183, - 316.025, - 264.941, - 246.679, - 123.62850000000002, - 0.578, - 299.459, - 346.646, - 326.205, - 101.8, - 262.172, - 318.882, - 77.334, - 249.878, - 75.39, - 87.486, - 161.731, - 336.621, - 247.885, - 215.453, - 237.706, - 135.311, - 367.655, - 439.17, - 312.568, - 400.401, - 392.319, - 455.46, - 485.5580000000001, - 366.829, - 378.236, - 450.252, - 408.224, - 400.979, - 345.36300000000006, - 357.222, - 446.789, - 129.376, - 38.031, - 388.14, - 521.965, - 170.887, - 609.198, - 623.765, - 618.056, - 457.304, - 51.145, - 336.059, - 189.032, - 136.47799999999998, - 245.11, - 580.383, - 432.117, - 622.064, - 579.986, - 598.44, - 264.588, - 522.5930000000001, - 615.1709999999999, - 339.324, - 324.14, - 107.206, - 622.477, - 402.454, - 206.771, - 445.974, - 305.466, - 337.7, - 336.92400000000004, - 403.566, - 217.308, - 156.782, - 334.788, - 354.50199999999995, - 382.552, - 404.761, - 437.21, - 446.305, - 463.608, - 121.509, - 471.503, - 451.628, - 441.339, - 111.908, - 191.482, - 473.523, - 34.788000000000004, - 250.263, - 353.577, - 457.86, - 268.828, - 415.051, - 394.081, - 361.362, - 30.516, - 128.154, - 36.754, - 65.767, - 370.077, - 393.376, - 422.18, - 216.13, - 488.547, - 328.908, - 538.602, - 540.529, - 518.645, - 426.909, - 161.97899999999998, - 67.997, - 204.938, - 0.4679999999999999, - 181.033, - 44.153, - 262.331, - 462.909, - 371.844, - 560.442, - 563.487, - 378.698, - 657.42, - 682.689, - 531.297, - 731.153, - 747.9939999999999, - 758.295, - 465.739, - 608.818, - 616.25, - 543.535, - 587.573, - 746.965, - 234.694, - 767.659, - 672.9169999999999, - 394.565, - 516.14, - 487.171, - 583.234, - 321.569, - 530.658, - 593.915, - 596.365, - 565.447, - 560.453, - 443.833, - 661.554, - 511.45, - 748.9689999999999, - 593.987, - 650.653, - 572.906, - 515.48, - 725.835, - 666.7510000000001, - 436.164, - 474.635, - 670.187, - 252.036, - 562.187, - 354.684, - 346.096, - 659.0110000000001, - 339.528, - 529.3480000000001, - 486.857, - 493.469, - 491.162, - 662.936, - 619.752, - 428.853, - 545.9630000000001, - 757.0010000000001, - 714.23, - 666.663, - 472.697, - 517.974, - 261.241, - 520.495, - 679.65, - 565.188, - 612.297, - 773.6, - 212.827, - 595.341, - 662.903, - 572.8290000000001, - 371.376, - 741.388, - 649.332, - 745.676, - 784.44, - 764.285, - 697.548, - 697.201, - 680.5039999999999, - 600.4304999999999, - 520.357, - 759.798, - 600.9780000000001, - 448.6830000000001, - 730.454, - 720.4839999999999, - 635.1669999999999, - 688.569, - 419.229, - 541.592, - 420.528, - 442.198, - 464.07, - 293.475, - 208.896, - 653.346, - 631.225, - 345.54, - 358.329, - 347.736, - 577.586, - 264.181, - 619.476, - 352.163, - 563.663, - 549.3430000000001, - 311.577, - 516.405, - 512.375, - 490.849, - 301.293, - 371.608, - 238.366, - 0.385, - 95.391, - 130.136, - 375.726, - 364.517, - 298.815, - 153.148, - 163.476, - 320.452, - 294.207, - 89.759, - 282.811, - 360.371, - 359.435, - 354.745, - 217.011, - 260.47, - 198.634, - 314.434, - 304.172, - 161.715, - 218.31, - 317.715, - 177.46599999999998, - 311.687, - 223.782, - 293.8, - 292.627, - 186.627, - 193.817, - 110.041, - 94.99, - 279.541, - 229.761, - 155.53799999999998, - 295.848, - 303.952, - 306.594, - 301.133, - 129.28799999999998, - 176.497, - 300.384, - 302.933, - 204.927, - 250.065, - 299.988, - 199.796, - 229.002, - 202.014, - 224.57, - 195.688, - 148.502, - 210.834, - 246.492, - 196.988, - 247.544, - 304.023, - 229.238, - 127.433, - 128.22, - 57.646, - 177.93900000000002, - 133.219, - 273.232, - 196.61900000000003, - 166.136, - 219.642, - 175.03799999999998, - 222.604, - 181.551, - 180.84, - 178.81400000000002, - 200.594, - 50.28, - 184.061, - 218.993, - 162.656, - 150.153, - 199.129, - 106.644, - 195.424, - 153.89700000000002, - 204.095, - 78.672, - 159.1, - 141.16299999999998, - 189.511, - 183.841, - 179.128, - 176.387, - 176.541, - 29.811, - 141.295, - 173.072, - 173.072, - 132.745, - 165.453, - 97.693, - 105.984, - 135.526, - 148.92, - 51.75, - 113.256, - 144.422, - 120.056, - 32.949, - 133.07, - 93.542, - 77.846, - 124.096, - 129.844, - 133.076, - 33.527, - 113.141, - 106.375, - 0.462, - 0.517, - 111.864, - 111.076, - 56.199, - 109.551, - 99.812, - 102.46, - 106.088, - 76.657, - 92.033, - 80.94, - 76.156, - 83.5, - 54.608, - 86.28, - 80.626, - 66.24, - 77.604, - 78.86399999999999, - 56.705, - 76.882, - 81.182, - 51.112, - 82.646, - 87.98700000000001, - 85.069, - 0.484, - 0.517, - 45.381, - 90.376, - 91.769, - 68.999, - 35.278, - 88.09700000000001, - 98.227, - 96.944, - 90.431, - 9.001, - 77.626, - 35.845, - 35.339, - 95.705, - 62.458, - 117.545, - 87.822, - 83.979, - 116.185, - 158.423, - 28.33, - 165.26, - 27.642, - 0.49, - 168.101, - 189.5, - 143.72899999999998, - 194.191, - 189.401, - 195.947, - 213.372, - 36.5, - 44.268, - 288.944, - 315.238, - 224.83900000000003, - 296.426, - 244.923, - 69.544, - 16.02, - 194.918, - 68.024, - 234.931, - 214.704, - 334.975, - 329.546, - 302.587, - 26.238000000000003, - 290.634, - 149.944, - 233.835, - 256.336, - 113.08, - 195.512, - 168.382, - 162.276, - 28.435, - 126.855, - 160.751, - 121.239, - 132.894, - 113.515, - 105.819, - 99.207, - 8.291, - 50.545, - 56.788, - 54.982, - 39.87, - 44.676, - 41.631, - 41.196000000000005, - 36.043, - 38.741, - 18.377, - 37.855, - 31.067, - 30.725, - 25.864, - 35.449, - 20.711, - 14.06, - 30.29, - 0.534, - 19.808, - 20.166, - 20.992, - 14.914, - 20.314, - 21.036, - 14.308, - 14.771, - 9.205, - 12.706, - 3.077, - 6.303, - 11.401, - 11.313, - 5.197, - 4.09, - 9.43, - 7.691, - 5.676, - 0.143, - 3.584, - 0.5720000000000001, - -5.148, - 0.016, - -9.178, - 2.637, - 0.413, - 3.1239999999999997, - 5.835, - 2.78, - 6.105, - 8.731, - 6.034, - 11.77, - 8.693, - 15.156, - 16.125, - 16.257, - 14.38, - 20.893, - 23.089, - 30.439, - 29.222, - 33.77, - 33.478, - 24.625, - 16.516, - 14.903, - 20.182, - 42.22, - 29.2, - 15.31, - 45.078, - 43.36600000000001, - 46.542, - 29.261, - 48.018, - 39.506, - 36.814, - 54.051, - 47.109, - 53.154, - 0.517, - 58.863, - 60.878, - 39.589, - 0.5670000000000001, - 42.386, - 32.927, - 34.529, - 38.212, - 56.93600000000001, - 43.503, - 55.235, - 50.467, - 50.556, - 16.747, - 20.898000000000003, - 61.027, - 46.658, - 57.173, - 65.172, - 67.727, - 62.706, - 71.421, - 83.77, - 26.783, - 41.461000000000006, - 78.044, - 74.124, - 59.63399999999999, - 115.508, - 118.156, - 107.745, - 79.59100000000001, - 126.271, - 122.638, - 188.741, - 166.05900000000003, - 138.108, - 126.805, - 122.39, - 119.037, - 140.387, - 100.264, - 136.451, - 158.615, - 121.377, - 125.346, - 167.886, - 163.036, - 172.555, - 116.609, - 119.758, - 82.70100000000001, - 158.208, - 125.814, - 124.834, - 156.18200000000002, - 89.572, - 148.832, - 146.68, - 105.83, - 119.599, - 35.113, - 90.409, - 117.215, - 33.467, - 67.738, - 97.291, - 92.809, - 108.742, - 107.195, - 98.849, - 99.587, - 113.801, - 117.418, - 115.057, - 110.702, - 48.915, - 88.851, - 114.159, - 143.404, - 159.689, - 106.71, - 136.847, - 85.322, - 169.53799999999998, - 120.303, - 46.845, - 134.782, - 107.096, - 161.252, - 195.958, - 190.447, - 174.608, - 0.578, - 278.302, - 374.173, - 327.955, - 394.879, - 482.904, - 450.235, - 329.337, - 283.235, - 63.091, - 302.256, - 191.73, - 256.215, - 121.603, - 260.889, - 248.067, - 235.443, - 229.068, - 167.58900000000003, - 167.89700000000002, - 225.467, - 144.08700000000002, - 126.579, - 203.523, - 270.215, - 286.907, - 317.803, - 220.997, - 273.529, - 305.884, - 150.809, - 356.281, - 501.089, - 540.1659999999999, - 598.1759999999999, - 477.206, - 603.368, - 338.476, - 31.138, - 413.658, - 485.866, - 178.347, - 424.47, - 685.684, - 715.248, - 735.998, - 538.3, - 680.074, - 689.962, - 594.3330000000001, - 649.607, - 619.317, - 597.389, - 608.113, - 315.034, - 458.158, - 419.592, - 551.612, - 286.203, - 377.162, - 325.076, - 300.252, - 294.16900000000004, - 221.927, - 138.68, - 70.925, - 275.357, - 278.077, - 255.422, - 218.519, - 71.25, - 204.337, - 228.159, - 461.527, - 470.374, - 384.898, - 347.764, - 341.87300000000005, - 441.509, - 522.923, - 507.1230000000001, - 41.841, - 446.007, - 166.46, - 587.512, - 587.754, - 549.63, - 393.932, - 578.258, - 596.569, - 105.125, - 712.2260000000001, - 503.555, - 469.895, - 526.391, - 528.66, - 756.0369999999999, - 756.1419999999999, - 168.28799999999998, - 626.887, - 589.665, - 739.5210000000001, - 659.7919999999999, - 518.381, - 412.386, - 631.996, - 601.595, - 677.068, - 258.439, - 781.687, - 209.424, - 732.37, - 662.666, - 445.996, - 736.681, - 714.835, - 463.817, - 379.007, - 669.933, - 504.931, - 597.02, - 179.035, - 628.4119999999999, - 782.414, - 749.073, - 552.085, - 628.77, - 508.196, - 788.8330000000001, - 734.456, - 98.26, - 784.115, - 328.495, - 471.029, - 5.6370000000000005, - 515.656, - 310.97700000000003, - 44.037, - 74.565, - 30.621, - 455.251, - 384.512, - 505.05300000000005, - 717.059, - 377.55300000000005, - 594.57, - 652.944, - 406.6, - 464.7480000000001, - 697.658, - 353.539, - 314.654, - 705.949, - 662.628, - 445.253, - 451.089, - 698.9580000000001, - 392.572, - 720.17, - 434.044, - 782.331, - 160.509, - 250.885, - 777.057, - 721.205, - 517.726, - 740.4630000000001, - 693.293, - 187.552, - 397.009, - 728.8739999999999, - 651.727, - 752.712, - 79.883, - 625.406, - 676.765, - 744.586, - 353.082, - 616.685, - 493.706, - 756.643, - 508.648, - 563.244, - 328.407, - 403.049, - 551.898, - 419.747, - 272.472, - 437.705, - 303.88, - 378.55, - 364.753, - 520.4730000000001, - 478.929, - 460.096, - 418.431, - 381.203, - 296.844, - 289.996, - 258.472, - 302.17400000000004, - 356.19199999999995, - 158.334, - 355.807, - 0.264, - 353.654, - 308.907, - 153.55, - 219.708, - 355.802, - 0.512, - 152.645, - 304.778, - 380.537, - 383.785, - 108.549, - 546.508, - 642.572, - 357.602, - 531.82, - 384.143, - 493.612, - 620.71, - 429.095, - 181.942, - 515.612, - 433.312, - 42.887, - 596.315, - 512.606, - 16.912, - 375.643, - 205.725, - 311.54900000000004, - 316.4, - 222.588, - 206.782, - 276.986, - 285.514, - 393.607, - 115.778, - 53.528, - 0.457, - 75.01, - 229.882, - 255.593, - 0.473, - 121.558, - 152.38299999999998, - 113.878, - 128.418, - 96.652, - 114.297, - 82.156, - 114.379, - 74.086, - 136.775, - 132.327, - 119.329, - 97.599, - 60.757, - 128.374, - 135.42700000000002, - 140.695, - 144.813, - 146.404, - 127.719, - 157.828, - 100.743, - 116.796, - 42.914, - 39.126, - 95.612, - 21.157, - 72.192, - 32.79, - 106.364, - 84.094, - 35.509, - 99.24, - 72.896, - 83.781, - 81.87, - 44.621, - 80.169, - 13.796, - 50.985, - 72.825, - 18.916, - 0.413, - 45.463, - 35.372, - 42.253, - 79.211, - 67.617, - 22.764, - 21.691, - 33.511, - 33.83, - 34.271, - 33.164, - 20.397, - 28.451, - 32.503, - 19.158, - 28.798, - 5.142, - 21.278, - 23.309, - 14.3765, - 5.444, - 12.255, - 7.977, - 7.625, - 9.15, - 4.189, - 5.626, - 12.387, - 12.1, - 12.265999999999998, - 6.331, - 12.007, - 15.178, - 7.746, - 11.886, - 9.579, - 11.495, - 7.3, - 11.803, - 3.402, - 4.872, - 6.023, - 5.428, - 5.318, - 5.207999999999999, - 2.505, - 6.237, - 3.039, - 1.3430000000000002, - 2.758, - 0.644, - 1.899, - -0.413, - 2.158, - -7.317, - 5.197, - 2.9065, - 0.616, - 6.485, - 1.123, - 5.8020000000000005, - 9.975, - 9.458, - 8.693, - 7.564, - 5.312, - 4.913, - 4.513999999999999, - 1.315, - 0, - 3.033, - 4.993, - 3.363, - -6.31, - -3.4635, - -0.617, - 1.695, - -1.514, - -0.088, - -0.36350000000000005, - -0.639, - -7.178999999999999, - -2.715, - -1.872, - -1.4455, - -1.019, - -1.696, - -0.127, - -3.045, - -1.861, - -1.454, - 0.974, - -1.052, - 0.825, - 0.148, - 2.84, - 3.749, - 4.668, - 4.008, - 3.474, - -3.623, - 4.723, - 7.867000000000001, - 3.297, - 7.162000000000001, - 11.462, - 7.377000000000001, - 10.146, - 6.193, - 6.903, - 7.806, - 3.523, - 13.257, - 5.537999999999999, - 1.888, - 13.042, - 14.528, - 7.256, - 9.452, - 13.807, - 10.273, - 18.867, - 12.607, - 15.905, - 14.627, - 8.461, - 16.852, - 18.701, - 21.157, - 11.087, - 13.13, - 24.174, - 24.581, - 33.434, - 17.182000000000002, - 8.379, - 32.503, - 31.782, - 32.107, - 59.562, - 34.1, - 26.453000000000003, - 36.869, - 1.403, - 25.688, - 28.336, - 17.925, - 45.358, - 89.792, - 110.317, - 93.663, - 116.152, - 116.906, - 106.755, - 71.972, - 145.518, - 154.07299999999998, - 172.362, - 178.40200000000002, - 191.114, - 208.637, - 212.772, - 182.85, - 183.957, - 303.886, - 224.333, - 347.186, - 361.175, - 269.56, - 104.729, - 351.039, - 265.502, - 535.288, - 571.211, - 241.207, - 2.543, - 666.597, - 538.63, - 455.3, - 665.446, - 197.136, - 494.609, - 615.067, - 398.259, - 502.746, - 669.3989999999999, - 677.184, - 437.65, - 302.317, - 402.746, - 261.775, - 718.887, - 716.6189999999999, - 434.352, - 479.232, - 654.276, - 737.7489999999999, - 360.811, - 289.599, - 715.727, - 642.929, - 499.641, - 638.624, - 730.327, - 732.75, - 501.639, - 167.143, - 751.941, - 726.573, - 572.295, - 421.844, - 738.508, - 642.026, - 704.81, - 775.637, - 787.325, - 613.971, - 672.2510000000001, - 498.055, - 385.5580000000001, - 590.259, - 525.279, - 584.534, - 381.352, - 622.196, - 527.036, - 220.556, - 264.286, - 274.603, - 510.5630000000001, - 590.254, - 525.1469999999999, - 406.06, - 502.19, - 754.056, - 477.911, - 705.1289999999999, - 601.369, - 779.4960000000001, - 755.597, - 323.991, - 581.005, - 60.862, - 673.066, - 664.665, - 603.764, - 452.999, - 536.4, - 313.096, - 143.806, - 725.1189999999999, - 498.259, - 142.033, - 305.703, - 535.976, - 383.962, - 494.466, - 546.3919999999999, - 320.87, - 229.982, - 643.766, - 721.012, - 535.283, - 668.3480000000001, - 705.922, - 274.146, - 762, - 599.007, - 787.2589999999999, - 504.854, - 785.4860000000001, - 146.94899999999998, - 574.217, - 614.3009999999999, - 746.6560000000001, - 721.095, - 578.181, - 600.554, - 142.76, - 308.901, - 33.604, - 167.204, - 143.53, - 496.64, - 420.462, - 711.0089999999999, - 275.214, - 553.401, - 748.176, - 670.676, - 566.8340000000001, - 113.906, - 312.85400000000004, - 739.13, - 343.101, - 711.3889999999999, - 732.59, - 680.658, - 327.003, - 332.43699999999995, - 6.9910000000000005, - 18.233, - 316.956, - 520.4680000000001, - 283.868, - 293.123, - 19.516, - 528.175, - 770.7919999999999, - 36.264, - 441.92800000000005, - 704.623, - 705.7510000000001, - 772.7189999999999, - 80.053, - 604.265, - 352.796, - 540.54, - 587.435, - 286.01, - 248.579, - 400.847, - 760.53, - 509.528, - 678.8960000000001, - 485.47, - 721.585, - 452.839, - 382.233, - 516.173, - 728.5989999999999, - 289.654, - 83.02600000000001, - 380.62, - 486.951, - 244.637, - 593.254, - 124.752, - 417.247, - 781.742, - 530.526, - 164.842, - 271.03, - 70.628, - 516.531, - 118.817, - 209.546, - 657.943, - 679.683, - 710.992, - 222.946, - 70.116, - 482.431, - 404.5630000000001, - 149.124, - 432.282, - 0.143, - 183.241, - 570.765, - 778.5210000000001, - 437.826, - 382.646, - 218.172, - 753.775, - 313.603, - 359.017, - 258.087, - 312.72700000000003, - 491.003, - 5.956, - 616.432, - 602.035, - 116.769, - 412.43, - 390.359, - 295.82, - 214.28, - 136.203, - 255.268, - 212.183, - 178.358, - 421.1230000000001, - 627.211, - 503.693, - 534.627, - 230.989, - 19.175, - 195.672, - 150.352, - 209.722, - 179.205, - 203.022, - 126.574, - 158.907, - 129.987, - 341.686, - 507.222, - 653.379, - 766.701, - 534.5830000000001, - 547.433, - 684.8860000000001, - 566.195, - 662.985, - 374.878, - 769.801, - 784.836, - 627.878, - 618.194, - 766.25, - 466.11300000000006, - 515.43, - 789.18, - 596.0840000000001, - 604.122, - 588.09, - 575.56, - 404.117, - 738.437, - 514.99, - 564.747, - 512.2040000000001, - 439.671, - 486.989, - 599.448, - 365.298, - 675.995, - 413.151, - 345.936, - 211.654, - 126.86, - 178.82, - 264.92400000000004, - 220.088, - 77.218, - 229.866, - 212.799, - 91.516, - 559.826, - 278.055, - 236.379, - 531.01, - 550.5880000000001, - 142.67700000000002, - 84.177, - 425.8080000000001, - 577.636, - 580.702, - 332.50300000000004, - 583.763, - 570.4069999999999, - 544.488, - 543.893, - 545.66, - 197.698, - 430.372, - 342.06, - 503.715, - 335.82300000000004, - 348.292, - 312.86, - 315.59, - 134.17700000000002, - 205.422, - 473.782, - 479.629, - 18.586, - 138.95, - 44.065, - 286.076, - 259.452, - 399.79, - 346.459, - 382.728, - 150.93, - 122.979, - 323.777, - 36.71, - 442.489, - 448.931, - 311.059, - 438.366, - 432.035, - 302.988, - 232.294, - 257.16200000000003, - 425.555, - 420.82, - 421.519, - 416.614, - 416.075, - 216.835, - 302.361, - 335.23900000000003, - 406.512, - 307.29900000000004, - 233.533, - 277.9, - 292.275, - 100.434, - 106.76, - 129.877, - 221.459, - 201.74400000000003, - 72.45, - 109.474, - 135.762, - 159.17700000000002, - 244.885, - 173.49599999999998, - 232.129, - 263.961, - 290.166, - 189.974, - 79.574, - 141.356, - 26.398000000000003, - 207.833, - 18.944000000000003, - 152.334, - 183.841, - 157.734, - 163.96099999999998, - 165.94299999999998, - 106.529, - 151.018, - 199.84, - 81.7, - 162.64, - 39.523, - 125.087, - 144.554, - 101.376, - 80.67, - 72.671, - 73.436, - 64.952, - 62.414, - 38.912, - 38.427, - 39.633, - 40.272, - 40.057, - 38.235, - 28.132, - 34.194, - 20.788, - 13.835, - 26.381, - 7.673999999999999, - 11.627, - 9.161, - 20.849, - 6.457000000000001, - 0.446, - 5.566, - 14.479, - 9.909, - 15.453, - 10.058, - 5.4110000000000005, - 0.379, - 5.502000000000001, - 10.625, - 7.267, - 6.155, - 8.23, - 7.388, - 5.0760000000000005, - 5.874, - 2.8510000000000004, - 1.7009999999999998, - 1.69, - 2.939, - 3.028, - 0.847, - 0.589, - -1.223, - 0.919, - -2.45, - 0.479, - 3.991, - 3.545, - 6.237, - 6.76, - 9.067, - 10.526, - 13.598, - 17.039, - 17.413, - 15.8, - 23.276, - 16.108, - 19.67, - 26.673, - 12.595999999999998, - 32.338, - 37.612, - 23.717, - 24.543000000000003, - 38.774, - 33.401, - 36.897, - 50.968, - 76.563, - 90.266, - 101.089, - 64.737, - 61.429, - 97.274, - 126.502, - 101.37, - 131.661, - 110.487, - 110.851, - 137.232, - 130.494, - 153.826, - 86.186, - 120.21, - 184.127, - 94.318, - 172.984, - 114.6, - 167.63299999999998, - 26.767, - 210.157, - 180.466, - 221.255, - 153.991, - 154.673, - 233.863, - 184.623, - 163.64700000000002, - 191.356, - 218.211, - 157.52, - 184.182, - 277.069, - 117.545, - 284.347, - 169.764, - 245.782, - 194.125, - 306.93, - 259.298, - 186.269, - 268.866, - 150.599, - 250.841, - 340.93699999999995, - 111.687, - 233.246, - 329.18300000000005, - 90.822, - 287.111, - 247.852, - 296.476, - 377.273, - 377.691, - 387.804, - 267.693, - 328.407, - 275.214, - 305.879, - 320.072, - 347.131, - 311.648, - 317.605, - 430.267, - 327.036, - 344.527, - 387.948, - 334.589, - 322.78, - 197.946, - 272.841, - 374.272, - 348.51199999999994, - 393.519, - 358.708, - 362.24300000000005, - 282.288, - 225.935, - 461.588, - 395.512, - 351.37, - 374.867, - 456.379, - 256.176, - 517.065, - 516.977, - 85.096, - 441.096, - 533.681, - 295.92, - 540.122, - 539.814, - 545.501, - 414.021, - 43.916, - 28.16, - 19.324, - 469.339, - 567.555, - 552.828, - 387.061, - 503.566, - 583.565, - 586.477, - 592.8580000000001, - 596.8, - 277.862, - 576.716, - 447.103, - 229.728, - 586.224, - 620.264, - 625.587, - 101.139, - 453.792, - 505.763, - 439.318, - 367.7480000000001, - 639.158, - 644.377, - 644.4209999999999, - 653.186, - 659.115, - 659.291, - 626.154, - 0.523, - 224.454, - 453.318, - 580.151, - 604.981, - 460.283, - 438.096, - 159.116, - 692.186, - 475.109, - 701.485, - 704.6010000000001, - 460.25, - 0.545, - 129.013, - 503.461, - 329.04, - 208.373, - 538.823, - 709.0160000000001, - 571.761, - 438.559, - 741.944, - 741.5139999999999, - 744.944, - 744.168, - 500.505, - 336.64300000000003, - 371.861, - 754.837, - 755.8889999999999, - 234.914, - 719.796, - 298.507, - 770.841, - 530.405, - 775.972, - 633.064, - 666.08, - 547.873, - 464.318, - 579.3969999999999, - 736.488, - 318.574, - 651.231, - 534.126, - 479.458, - 436.384, - 648.451, - 735.86, - 664.169, - 711.0360000000001, - 729.925, - 476.436, - 352.586, - 644.724, - 625.967, - 160.21200000000002, - 462.122, - 507.976, - 387.111, - 204.2, - 379.359, - 699.668, - 708.284, - 490.705, - 339.963, - 521.668, - 386.445, - 689.1360000000001, - 676.732, - 136.17, - 269.85200000000003, - 698.765, - 357.431, - 680.1619999999999, - 574.035, - 116.235, - 436.94, - 639.9069999999999, - 215.271, - 124.218, - 226.243, - 350.329, - 463.74, - 181.209, - 303.732, - 228.611, - 447.918, - 633.548, - 458.389, - 489.687, - 629.5459999999999, - 359.47900000000004, - 604.034, - 767.924, - 547.163, - 730.57, - 21.019, - 491.0580000000001, - 209.474, - 468.106, - 481.225, - 524.492, - 43.255, - 308.274, - 620.346, - 717.654, - 402.449, - 653.29, - 515.849, - 705.933, - 410.041, - 621.447, - 54.2, - 284.766, - 133.048, - 749.596, - 417.765, - 606.737, - 422.86300000000006, - 389.214, - 93.872, - 503.087, - 3.094, - 478.093, - 177.273, - 786.212, - 701.204, - 716.834, - 593.689, - 667.9839999999999, - 765.694, - 670.247, - 527.7180000000001, - 679.931, - 764.466, - 706.467, - 765.76, - 638.866, - 619.289, - 560.002, - 730.779, - 514.555, - 613.4540000000001, - 329.117, - 243.106, - 591.404, - 348.76, - 248.584, - 715.8760000000001, - 734.539, - 729.8810000000001, - 790.2860000000001, - 190.546, - 783.807, - 384.798, - 254.453, - 626.066, - 700.125, - 597.4, - 638.118, - 567.153, - 284.909, - 718.8710000000001, - 217.914, - 642.109, - 558.069, - 605.306, - 585.15, - 529.485, - 560.244, - 672.956, - 496.338, - 470.402, - 318.651, - 447.196, - 416.955, - 253.379, - 216.29, - 627.823, - 469.989, - 465.606, - 506.853, - 70.788, - 356.391, - 756.742, - 644.179, - 92.474, - 102.014, - 504.75, - 157.778, - 731.698, - 790.0060000000001, - 768.27, - 352.619, - 134.16, - 774.5139999999999, - 780.465, - 569.763, - 773.721, - 674.1560000000001, - 272.868, - 780.2339999999999, - 379.656, - 779.931, - 776.903, - 776.0880000000001, - 494.499, - 0.363, - 111.753, - 765.253, - 534.6709999999999, - 560.0840000000001, - 501.254, - 438.922, - 284.47900000000004, - 745.3960000000001, - 737.303, - 468.216, - 719.096, - 484.165, - 526.854, - 723.578, - 717.318, - 714.549, - 503.77, - 705.5260000000001, - 639.367, - 228.897, - 682.717, - 670.4889999999999, - 413.283, - 676.408, - 671.805, - 668.788, - 661.62, - 161.671, - 435.068, - 422.009, - 620.946, - 601.793, - 596.238, - 606.643, - 350.759, - 620.798, - 209.898, - 624.288, - 269.295, - 457.205, - 531.6990000000001, - 421.101, - 455.823, - 494.146, - 562.683, - 369.697, - 460.206, - 5.428, - 47.214, - 555.2669999999999, - 483.389, - 175.412, - 360.575, - 270.402, - 397.186, - 547.686, - 567.318, - 569.686, - 555.509, - 529.5740000000001, - 443.607, - 513.399, - 454.607, - 538.911, - 398.848, - 338.036, - 535.613, - 549.332, - 540.821, - 108.858, - 220.551, - 533.9830000000001, - 218.101, - 530.548, - 504.128, - 471.943, - 307.712, - 259.606, - 427.713, - 282.073, - 468.244, - 468.1830000000001, - 266.46, - 444.477, - 401.573, - 350.48900000000003, - 229.459, - 141.884, - 306.396, - 277.251, - 251.766, - 210.267, - 0.391, - 339.786, - 332.095, - 268.932, - 315.546, - 271.129, - 275.362, - 220.033, - 157.178, - 222.604, - 236.21400000000003, - 121.779, - 195.259, - 140.855, - 131.85399999999998, - 234.105, - 233.318, - 198.48, - 105.736, - 140.921, - 0.363, - 109.094, - 253.682, - 85.32799999999999, - 244.648, - 178.15900000000002, - 226.073, - 215.012, - 96.487, - 136.467, - 179.21599999999998, - 179.695, - 171.856, - 137.904, - 148.315, - 61.242, - 128.226, - 164.192, - 163.179, - 98.221, - 115.156, - 44.874, - 127.736, - 122.219, - 88.796, - 88.086, - 43.619, - 69.268, - 41.918, - 45.039, - 57.878, - 54.211000000000006, - 52.218, - 50.187, - 39.231, - 49.06399999999999, - 40.376, - 7.927, - 26.128, - 33.048, - 34.653000000000006, - 36.258, - 15.8, - 26.304, - 23.821, - 32.564, - 29.47, - 25.82, - 30.12, - 28.462, - 14.082, - 26.712, - 20.48, - 24.113000000000003, - 13.46, - 16.609, - 15.211, - 3.363, - 9.744, - 10.917, - 9.353, - 7.773, - 0.517, - 9.838, - 7.982, - 3.0610000000000004, - 5.577000000000001, - 0.847, - 4.668, - -0.997, - 0.858, - 0.925, - -4.256, - 0.655, - -0.342, - 0.407, - -0.969, - -2.417, - 2.494, - 10.636, - 20.43, - 21.663, - 26.458, - 25.06, - 21.597, - 32.861, - 38.653, - 32.272, - 41.136, - 53.138000000000005, - 48.519, - 49.807, - 62.018, - 35.262, - 63.857, - 72.005, - 65.29899999999999, - 20.193, - 90.684, - 98.331, - 43.553, - 43.773, - 118.222, - 121.135, - 95.931, - 80.031, - 141.092, - 147.445, - 158.329, - 168.61900000000003, - 114.798, - 114.457, - 176.40900000000002, - 78.936, - 104.398, - 203.842, - 36.632, - 208.406, - 117.617, - 199.889, - 176.959, - 223.248, - 214.528, - 194.648, - 198.937, - 91.527, - 47.66, - 115.926, - 53.567, - 270.237, - 255.515, - 160.129, - 104.707, - 210.61900000000003, - 268.772, - 243.194, - 272.323, - 277.091, - 262.045, - 284.85400000000004, - 262.072, - 351.606, - 355.945, - 201.64, - 369.829, - 250.555, - 378.676, - 257.916, - 281.231, - 295.171, - 266.141, - 269.009, - 324.448, - 340.921, - 342.886, - 338.87800000000004, - 327.449, - 258.472, - 333.797, - 312.92, - 348.033, - 449.509, - 453.775, - 294.163, - 384.43, - 256.033, - 316.339, - 459.831, - 247.219, - 403.418, - 322.032, - 219.246, - 506.974, - 248.601, - 458.295, - 481.022, - 182.789, - 291.064, - 315.634, - 422.318, - 469.967, - 477.63, - 397.263, - 503.583, - 495.28, - 390.24300000000005, - 263.988, - 279.772, - 193.305, - 270.347, - 241.719, - 317.446, - 132.239, - 448.072, - 400.401, - 5.747000000000001, - 0.55, - 290.772, - 333.362, - 527.735, - 43.129, - 0.5670000000000001, - 365.497, - 116.604, - 171.34400000000002, - 183.186, - 495.814, - 485.035, - 562.22, - 384.275, - 368.9980000000001, - 477.427, - 268.453, - 509.385, - 425.384, - 502.4980000000001, - 554.964, - 513.294, - 677.36, - 685.304, - 484.429, - 205.367, - 439.918, - 407.761, - 155.94, - 212.375, - 265.656, - 715.457, - 714.345, - 702.443, - 717.885, - 724.1339999999999, - 727.547, - 706.307, - 539.1419999999999, - 227.768, - 250.484, - 751.05, - 414.5, - 508.559, - 772.691, - 755.316, - 750.174, - 242.071, - 732.078, - 634.743, - 614.004, - 581.974, - 767.571, - 322.538, - 181.804, - 378.153, - 591.482, - 541.7180000000001, - 358.956, - 150.275, - 757.942, - 692.962, - 274.316, - 0.457, - 204.205, - 610.2769999999999, - 448.986, - 611.918, - 549.619, - 512.523, - 391.256, - 429.805, - 453.93, - 100.253, - 398.87, - 190.613, - 0.4679999999999999, - 105.714, - 445.435, - 0.473, - 602.982, - 465.915, - 704.27, - 649.536, - 447.912, - 585.806, - 646.122, - 583.658, - 654.375, - 536.967, - 642.786, - 730.096, - 703.885, - 53.468, - 235.107, - 627.002, - 787.638, - 532.018, - 494.895, - 528.247, - 773.6439999999999, - 621.304, - 620.269, - 730.977, - 755.5310000000001, - 578.869, - 491.603, - 743.7, - 343.772, - 716.5360000000001, - 474.299, - 604.4630000000001, - 717.0210000000001, - 383.422, - 479.711, - 609.187, - 695.297, - 616.625, - 599.63, - 535.321, - 754.832, - 694.801, - 638.9540000000001, - 629.722, - 639.422, - 586.4, - 523.281, - 72.12, - 665.865, - 728.654, - 774.525, - 428.737, - 603.665, - 765.2760000000001, - 644.735, - 694.355, - 629.992, - 23.386, - 175.137, - 493.607, - 457.838, - 71.382, - 655.493, - 562.65, - 414.032, - 743.4580000000001, - 762.7819999999999, - 770.941, - 87.28200000000001, - 632.32, - 531.236, - 743.1, - 505.311, - 502.245, - 621.398, - 115.954, - 568.7719999999999, - 639.378, - 149.454, - 679.2589999999999, - 780.971, - 731.544, - 704.182, - 368.084, - 0.721, - 620.434, - 2.582, - 659.423, - 462.204, - 758.311, - 781.6210000000001, - 415.777, - 788.079, - 372.268, - 415.518, - 547.0419999999999, - 417.809, - 635.42, - 612.072, - 480.108, - 594.884, - 512.127, - 373.138, - 697.46, - 397.918, - 697.1410000000001, - 620.7040000000001, - 582.266, - 688.393, - 552.828, - 550.274, - 493.034, - 145.32, - 628.9019999999999, - 782.915, - 620.418, - 548.523, - 666.5419999999999, - 683.427, - 39.556, - 393.915, - 581.0269999999999, - 137.827, - 377.652, - 623.98, - 551.711, - 699.393, - 105.637, - 598.991, - 527.812, - 697.24, - 637.2919999999999, - 606.985, - 730.8610000000001, - 108.213, - 678.957, - 585.448, - 46.487, - 602.85, - 396.288, - 735.508, - 109.045, - 494.587, - 450.109, - 467.302, - 627.118, - 729.931, - 22.203000000000003, - 763.2660000000001, - 500.522, - 638.938, - 790.8810000000001, - 496.035, - 691.883, - 621.205, - 790.1489999999999, - 271.327, - 145.391, - 689.1089999999999, - 574.382, - 779.914, - 415.601, - 0.346, - 271.222, - 555.906, - 731.368, - 515.711, - 772.449, - 769.955, - 763.7339999999999, - 667.6160000000001, - 461.577, - 757.8710000000001, - 749.673, - 751.903, - 633.009, - 411.367, - 739.395, - 607.948, - 681.357, - 727.685, - 125.165, - 483.262, - 680.7289999999999, - 596.139, - 725.7189999999999, - 299.597, - 172.417, - 714.8739999999999, - 682.084, - 434.44, - 531.451, - 0.379, - 223.199, - 701.6610000000001, - 442.566, - 399.982, - 538.085, - 558.124, - 687.677, - 672.135, - 404.166, - 678.2739999999999, - 674.706, - 673.2810000000001, - 650.4169999999999, - 665.331, - 661.317, - 222.467, - 316.895, - 626.7330000000001, - 411.604, - 260.29400000000004, - 426.447, - 640.226, - 602.988, - 626.1709999999999, - 628.313, - 627.806, - 622.499, - 624.283, - 466.581, - 543.656, - 163.075, - 117.573, - 132.22799999999998, - 122.093, - 596.5409999999999, - 398.199, - 406.781, - 25.49, - 386.103, - 546.7280000000001, - 523.7819999999999, - 482.871, - 276.579, - 354.144, - 259.171, - 330.014, - 317.721, - 209.837, - 0.418, - 0.385, - 297.527, - 263.999, - 334.958, - 60.988, - 217.991, - 169.868, - 383.24, - 293.002, - 130.565, - 264.92400000000004, - 229.673, - 168.696, - 271.377, - 252.592, - 101.535, - 253.209, - 256.198, - 272.533, - 84.50200000000001, - 318.541, - 240.552, - 50.649, - 0.391, - 0.352, - 77.559, - 323.782, - 365.304, - 260.371, - 338.856, - 214.517, - 214.027, - 360.01300000000003, - 209.155, - 254.91, - 392.082, - 147.208, - 280.405, - 303.41200000000003, - 215.436, - 315.728, - 346.668, - 343.37, - 254.805, - 172.62099999999998, - 87.287, - 244.285, - 191.455, - 47.093, - 126.128, - 353.517, - 253.401, - 335.47, - 228.693, - 303.126, - 242.33, - 185.129, - 81.991, - 332.194, - 245.485, - 325.599, - 216.361, - 48.073, - 206.71, - 304.849, - 224.311, - 278.41200000000003, - 187.067, - 290.66200000000003, - 260.36, - 263.878, - 247.968, - 213.807, - 93.597, - 46.9, - 74.487, - 87.915, - 40.949, - 69.654, - 53.688, - 44.637, - 78.391, - 6.909, - 68.78399999999999, - 20.849, - 16.554000000000002, - 39.49, - 47.01, - 21.751, - 0.418, - 48.909, - 48.998000000000005, - 46.487, - 39.633, - 36.319, - 33.654, - 16.102999999999998, - 12.987, - 31.788, - 29.387, - 19.544, - 20.188, - 10.454, - 16.885, - 17.854, - 13.482, - 12.062, - 10.642, - 14.237, - 11.583, - 13.719, - 17.54, - 11.913, - 7.702000000000001, - 6.287000000000001, - 3.11, - 6.678, - 6.43, - 4.184, - -1.426, - 4.822, - 4.894, - -2.902, - -5.131, - -0.7490000000000001, - -2.698, - 0.969, - 1.668, - -0.21, - 4.685, - 3.947, - 2.752, - 6.7, - 7.096, - 8.929, - 13.279000000000002, - 15.371, - 7.454, - 13.075, - 17.149, - 17.578, - 18.393, - 28.54, - 27.031, - 13.961, - 0.693, - 30.384, - 32.278, - 41.725, - 37.833, - 52.328, - 57.388000000000005, - 58.445, - 66.752, - 59.067, - 55.78, - 65.706, - 84.414, - 37.376, - 28.099, - 75.23100000000001, - 14.237, - 39.985, - 64.952, - 84.006, - 61.467, - 38.741, - 55.153, - 57.09, - 56.87, - 72.918, - 32.971, - 64.016, - 68.712, - 36.445, - 0.5670000000000001, - 0.561, - 51.75, - 39.958, - 74.229, - 27.703000000000003, - 14.11, - 83.081, - 56.54, - 62.458, - 66.851, - 68.046, - 85.427, - 65.514, - 65.92699999999999, - 98.766, - 101.425, - 95.001, - 100.076, - 149.129, - 91.538, - 159.755, - 96.382, - 115.271, - 154.134, - 148.838, - 8.494, - 104.844, - 164.088, - 155.477, - 154.183, - 160.65200000000002, - 166.708, - 130.907, - 203.545, - 192.495, - 235.448, - 206.848, - 166.928, - 153.082, - 160.118, - 153.275, - 168.65200000000002, - 130.472, - 226.992, - 130.07, - 138.493, - 197.296, - 174.95, - 56.749, - 158.52700000000002, - 20.76, - 164.75400000000002, - 46.228, - 116.995, - 147.004, - 101.211, - 175.203, - 113.609, - 120.49, - 85.81200000000001, - 15.2, - 139.22, - 172.78599999999997, - 239.115, - 225.093, - 287.463, - 289.561, - 143.822, - 213.432, - 273.80400000000003, - 275.495, - 258.89, - 291.934, - 283.91200000000003, - 284.121, - 28.226, - 267.842, - 255.598, - 249.322, - 97.99, - 59.221, - 0.5720000000000001, - 115.635, - 335.432, - 366.218, - 89.258, - 49.851000000000006, - 329.932, - 357.569, - 117.396, - 263.774, - 213.928, - 210.03, - 210.878, - 59.353, - 321.795, - 296.36, - 150.864, - 307.31, - 190.045, - 315.337, - 308.411, - 213.598, - 0.561, - 116.317, - 355.31199999999995, - 228.996, - 179.778, - 367.214, - 388.828, - 420.853, - 396.365, - 233.995, - 192.451, - 272.769, - 477.206, - 337.35900000000004, - 340.50199999999995, - 422.753, - 446.068, - 355.405, - 274.933, - 540.887, - 507.838, - 518.309, - 400.059, - 215.056, - 430.174, - 407.668, - 428.137, - 434.73800000000006, - 390.32, - 346.36, - 586.174, - 402.052, - 555.7959999999999, - 550.549, - 500.026, - 590.309, - 395.171, - 524.509, - 511.263, - 658.163, - 434.462, - 571.007, - 510.806, - 466.454, - 228.864, - 680.1289999999999, - 684.2860000000001, - 665.6610000000001, - 250.153, - 416.388, - 364.687, - 662.5889999999999, - 375.296, - 585.998, - 309.986, - 565.524, - 518.106, - 213.405, - 551.909, - 517.698, - 325.076, - 288.306, - 587.65, - 549.305, - 480.691, - 463.652, - 463.404, - 442.126, - 473.931, - 484.149, - 516.7130000000001, - 517.197, - 36.71, - 19.648, - 399.966, - 496.112, - 488.657, - 529.783, - 388.773, - 587.375, - 141.95600000000002, - 527.905, - 669.8560000000001, - 670.4839999999999, - 683.322, - 184.755, - 426.601, - 623.424, - 630.432, - 643.1990000000001, - 639.015, - 323.969, - 187.375, - 26.673, - 563.944, - 154.569, - 364.36800000000005, - 654.331, - 716.487, - 693.188, - 689.709, - 416.174, - 357.249, - 424.487, - 228.225, - 605.823, - 532.668, - 419.659, - 398.30300000000005, - 276.838, - 233.973, - 317.258, - 245.545, - 460.382, - 183.83, - 223.518, - 472.114, - 497.851, - 414.06, - 536.086, - 621.431, - 486.086, - 552.9490000000001, - 454.943, - 419.251, - 371.767, - 274.768, - 609.429, - 631.153, - 614.885, - 545.181, - 198.74400000000003, - 275.021, - 500.241, - 568.309, - 580.63, - 351.342, - 563.299, - 252.196, - 520.143, - 331.033, - 21.779, - 396.206, - 532.937, - 530.4209999999999, - 298.876, - 304.431, - 508.202, - 490.089, - 68.184, - 505.702, - 304.822, - 553.88, - 183.907, - 358.934, - 566.091, - 548.908, - 194.318, - 530.84, - 553.0319999999999, - 575.725, - 339.649, - 175.97400000000002, - 396.371, - 575.742, - 539.687, - 225.572, - 558.851, - 599.861, - 433.714, - 54.597, - 631.313, - 512.314, - 450.307, - 433.615, - 440.436, - 586.631, - 671.789, - 525.054, - 727.3710000000001, - 720.5880000000001, - 550.659, - 225.329, - 618.095, - 524.729, - 731.605, - 470.903, - 384.237, - 768.3919999999999, - 491.542, - 683.179, - 570.115, - 691.8560000000001, - 525.538, - 636.015, - 341.537, - 48.722, - 648.385, - 676.27, - 288.66900000000004, - 624.365, - 131.077, - 499.756, - 358.69199999999995, - 705.03, - 579.205, - 742.7810000000001, - 715.0939999999999, - 690.821, - 748.77, - 587.182, - 554.2819999999999, - 761.961, - 776.688, - 336.329, - 535.855, - 504.419, - 764.813, - 775.1080000000001, - 620.7869999999999, - 533.46, - 620.0319999999999, - 442.3130000000001, - 446.712, - 626.3969999999999, - 730.421, - 626.094, - 611.075, - 457.431, - 454.21, - 635.91, - 350.522, - 32.9, - 480.328, - 302.438, - 642.1419999999999, - 624.982, - 709.2860000000001, - 695.743, - 769.873, - 506.897, - 316.768, - 501.81, - 718.9860000000001, - 703.252, - 721.4639999999999, - 713.58, - 684.627, - 394.95, - 376.386, - 595.693, - 302.421, - 124.163, - 675.0260000000001, - 347.389, - 402.818, - 710.09, - 781.137, - 761.1189999999999, - 263.113, - 21.366, - 347.582, - 445.104, - 417.44, - 342.886, - 446.288, - 655.795, - 16.185, - 264.555, - 467.456, - 471.139, - 582.871, - 580.471, - 426.199, - 624.492, - 181.953, - 368.591, - 610.145, - 629.788, - 598.49, - 434.628, - 550.78, - 595.104, - 664.643, - 326.59, - 785.431, - 445.848, - 781.797, - 587.248, - 696.288, - 572.9169999999999, - 97.742, - 572.516, - 480.955, - 745.9680000000001, - 370.55, - 332.53, - 743.727, - 575.18, - 315.629, - 743.8430000000001, - 743.4580000000001, - 737.066, - 700.9010000000001, - 134.535, - 405.289, - 524.943, - 719.674, - 475.279, - 472.923, - 708.498, - 394.361, - 628.781, - 412.947, - 664.703, - 584.203, - 417.082, - 684.567, - 477.966, - 584.98, - 606.55, - 695.3739999999999, - 533.124, - 585.58, - 685.563, - 511.78, - 598.798, - 544.466, - 489.318, - 477.454, - 321.652, - 495.6880000000001, - 657.293, - 507.745, - 651.248, - 644.851, - 319.906, - 438.289, - 640.865, - 396.354, - 432.321, - 348.62300000000005, - 630.6080000000001, - 522.962, - 0.368, - 69.048, - 568.139, - 461.307, - 607.7, - 196.382, - 127.279, - 591.393, - 597.741, - 403.407, - 588.404, - 583.9830000000001, - 582.106, - 54.888000000000005, - 455.911, - 402.504, - 565.375, - 432.954, - 562.32, - 559.76, - 141.405, - 219.708, - 432.161, - 296.244, - 542.247, - 537.76, - 395.875, - 378.297, - 525.857, - 390.155, - 520.099, - 247.687, - 356.22, - 425.918, - 325.588, - 486.334, - 352.49800000000005, - 324.647, - 482.871, - 378.886, - 239.264, - 395.082, - 319.98400000000004, - 435.778, - 346.93800000000005, - 454.48, - 190.728, - 200.17, - 299.316, - 405.543, - 199.955, - 433.009, - 255.136, - 276.601, - 376.348, - 256.633, - 31.193, - 257.42, - 365.254, - 354.849, - 352.735, - 300.214, - 76.805, - 332.585, - 234.826, - 339.792, - 342.19800000000004, - 352.163, - 175.638, - 146.49200000000002, - 0.374, - 252.774, - 311.88, - 311.599, - 103.991, - 252.333, - 297.285, - 293.007, - 288.906, - 280.147, - 274.531, - 251.431, - 251.139, - 267.187, - 241.152, - 60.476000000000006, - 245.143, - 265.166, - 273.391, - 231.017, - 261.472, - 252.333, - 223.403, - 124.289, - 143.393, - 225.952, - 217.198, - 144.461, - 62.49100000000001, - 118.387, - 71.146, - 195.925, - 161.627, - 150.03799999999998, - 143.28799999999998, - 137.408, - 152.813, - 82.167, - 29.156, - 26.481, - 24.075, - 29.899, - 23.067, - 26.348000000000003, - 23.073, - 25.363000000000003, - 22.572, - 23.838, - 17.413, - 2.45, - 20.023, - 19.335, - 19.076, - 16.279, - 13.708, - 14.55, - 15.497, - 8.748, - 15.921, - 6.16, - 15.91, - 8.913, - 11.109000000000002, - 7.652, - 8.115, - 8.77, - 7.718, - 2.807, - 9.271, - 5.422000000000001, - 7.68, - 2.174, - 3.867, - 5.56, - 3.1210000000000004, - 3.661, - 0.7809999999999999, - 3.275, - 4.52, - -4.977, - -7.152, - 0.479, - -4.409999999999999, - -9.299, - -3.997, - -2.748, - -1.066, - 0.616, - 0.71, - 1.822, - 0.115, - 4.9430000000000005, - 9.529, - 2.516, - 7.68, - 11.489, - 12.380999999999998, - 10.339, - 11.682, - 12.265999999999998, - 11.963, - 23.1, - 38.559, - 60.603, - 40.723, - 63.168, - 41.604, - 32.046, - 16.857, - 10.708, - 15.321, - 15.91, - 17.71, - 18.745, - 25.633000000000003, - 23.161, - 28.628, - 25.556, - 27.725, - 26.365, - 16.769000000000002, - 40.536, - 46.603, - 71.465, - 68.872, - 49.625, - 89.633, - 106.81, - 150.654, - 118.641, - 222.703, - 176.706, - 194.874, - 306.04900000000004, - 194.609, - 264.48900000000003, - 274.922, - 183.687, - 132.05200000000002, - 69.747, - 309.04400000000004, - 177.614, - 142.369, - 303.203, - 111.368, - 370.517, - 378.759, - 380.554, - 349.76800000000003, - 35.669000000000004, - 192.523, - 241.284, - 250.847, - 312.904, - 285.388, - 307.222, - 309.639, - 320.897, - 348.601, - 342.19800000000004, - 251.876, - 211.291, - 438.135, - 208.912, - 260.707, - 408.741, - 301.078, - 342.969, - 377.829, - 352.041, - 286.456, - 434.27, - 250.957, - 0.611, - 38.543, - 239.80900000000003, - 308.83, - 498.584, - 304.893, - 515.656, - 185.669, - 434, - 413.856, - 373.843, - 528.55, - 185.036, - 495.936, - 563.6080000000001, - 400.081, - 582.8330000000001, - 591.8340000000001, - 594.405, - 485.954, - 270.308, - 80.84100000000001, - 121.63, - 264.39, - 243.057, - 146.096, - 122.737, - 0.556, - 231.325, - 473.408, - 400.847, - 181.055, - 432.068, - 586.56, - 37.354, - 170.991, - 423.033, - 0.556, - 281.303, - 318.712, - 512.931, - 313.317, - 287.904, - 363.256, - 283.676, - 9.436, - 432.492, - 461.312, - 478.869, - 400.324, - 87.414, - 428.963, - 745.825, - 92.98, - 472.896, - 694.586, - 748.2310000000001, - 713.09, - 437.523, - 764.94, - 332.492, - 277.565, - 489.478, - 670.676, - 0.539, - 520.781, - 604.425, - 459.595, - 242.446, - 294.92900000000003, - 506.919, - 735.304, - 743.893, - 734.935, - 429.073, - 686.868, - 449.244, - 496.354, - 749.7230000000001, - 343.789, - 637.33, - 694.1289999999999, - 493.321, - 542.346, - 652.674, - 297.01, - 779.3910000000001, - 522.323, - 777.525, - 710.893, - 701.8639999999999, - 787.699, - 772.801, - 209.441, - 441.564, - 530.724, - 719.74, - 780.085, - 366.344, - 173.46900000000002, - 117.848, - 392.154, - 244.229, - 139.776, - 302.818, - 287.271, - 276.992, - 487.24300000000005, - 345.826, - 189.864, - 171.68, - 183.274, - 669.6360000000001, - 481.616, - 322.54900000000004, - 327.664, - 342.63800000000003, - 760.75, - 727.63, - 464.263, - 342.20300000000003, - 469.301, - 245.286, - 337.93699999999995, - 754.166, - 549.674, - 462.309, - 472.444, - 365.133, - 252.724, - 225.263, - 274.349, - 214.858, - 223.105, - 224.834, - 206.639, - 246.69, - 255.95, - 316.405, - 217.974, - 263.416, - 152.29, - 255.928, - 247.285, - 163.333, - 117.617, - 149.746, - 111.032, - 202.097, - 197.973, - 152.84, - 186.252, - 199.74, - 134.722, - 194.565, - 197.71400000000003, - 204.145, - 195.788, - 191.268, - 199.79, - 204.172, - 111.979, - 156.143, - 207.261, - 120.424, - 127.747, - 205.235, - 142.116, - 159.92600000000002, - 170.49599999999998, - 145.232, - 234.617, - 157.013, - 87.98100000000001, - 201.458, - 244.984, - 259.36400000000003, - 293.249, - 194.967, - 315.832, - 325.505, - 304.056, - 186.935, - 355.218, - 116.609, - 325.687, - 391.05300000000005, - 342.644, - 341.185, - 382.062, - 395.914, - 280.323, - 396.519, - 245.22, - 386.549, - 331.86400000000003, - 300.291, - 268.828, - 168.97099999999998, - 329.06199999999995, - 173.19299999999998, - 347.25699999999995, - 271.795, - 333.004, - 252.493, - 315.183, - 262.194, - 160.316, - 293.404, - 205.295, - 326.463, - 194.455, - 105.819, - 100.286, - 121.19, - 255.246, - 334.584, - 245.402, - 187.051, - 189.291, - 245.171, - 324.531, - 334.523, - 337.414, - 341.141, - 343.18300000000005, - 151.491, - 209.551, - 358.461, - 356.809, - 352.091, - 352.994, - 347.092, - 347.852, - 381.253, - 379.249, - 362.122, - 347.896, - 364.638, - 92.385, - 372.037, - 303.159, - 173.838, - 165.359, - 353.577, - 177.22299999999998, - 79.707, - 370.622, - 373.562, - 228.539, - 390.364, - 203.385, - 238.851, - 340.486, - 461.461, - 0.506, - 279.926, - 456.677, - 268.42, - 415.26, - 514.406, - 251.998, - 612.8919999999999, - 648.126, - 632.04, - 379.249, - 64.815, - 40.932, - 614.643, - 382.271, - 2.648, - 72.318, - 694.702, - 693.948, - 221.597, - 637.259, - 663.564, - 705.6410000000001, - 522.433, - 706.819, - 620.214, - 754.815, - 580.4209999999999, - 735.2819999999999, - 571.739, - 87.87700000000001, - 411.318, - 659.908, - 368.304, - 375.351, - 647.422, - 673.181, - 627.09, - 657.172, - 451.854, - 412.601, - 734.682, - 630.8009999999999, - 432.651, - 561.719, - 512.3530000000001, - 656.2139999999999, - 750.0419999999999, - 468.59, - 485.894, - 544.3330000000001, - 499.2, - 517.511, - 351.832, - 727.685, - 740.727, - 572.064, - 559.556, - 456.291, - 565.826, - 561.78, - 438.878, - 529.81, - 657.832, - 597.681, - 619.245, - 585.5740000000001, - 610.2330000000001, - 705.977, - 628.797, - 513.3330000000001, - 615.568, - 728.7689999999999, - 773.181, - 676.209, - 715.171, - 506.352, - 713.679, - 607.645, - 425.235, - 583.339, - 644.482, - 771.992, - 508.372, - 454.59, - 613.387, - 480.009, - 601.556, - 120.232, - 45.21, - 588.388, - 566.977, - 403.875, - 785.888, - 776.655, - 770.1419999999999, - 767.747, - 766.3710000000001, - 762.9739999999999, - 764.6039999999999, - 760.6619999999999, - 754.8810000000001, - 753.956, - 749.6460000000001, - 738.365, - 739.2239999999999, - 744.2560000000001, - 574.4590000000001, - 474.712, - 323.199, - 507.332, - 410.321, - 560.607, - 507.959, - 705.817, - 680.2669999999999, - 530.851, - 415.689, - 521.86, - 554.612, - 577.118, - 426.799, - 390.1, - 444.961, - 480.119, - 570.082, - 601.2919999999999, - 681.5939999999999, - 680.2560000000001, - 700.2510000000001, - 688.784, - 685.684, - 689.466, - 697.0139999999999, - 678.813, - 659.842, - 666.8610000000001, - 622.268, - 366.284, - 573.1709999999999, - 577.112, - 590.391, - 582.3430000000001, - 558.493, - 559.242, - 282.018, - 121.096, - 108.109, - 97.17, - 99.559, - 103.451, - 109.221, - 118.74, - 122.687, - 130.934, - 137.656, - 144.395, - 160.608, - 185.267, - 180.229, - 170.512, - 153.622, - 146.905, - 150.44, - 160.151, - 157.327, - 179.84400000000002, - 197.891, - 182.019, - 173.672, - 173.166, - 175.01, - 191.945, - 225.44, - 235.124, - 214.93, - 195.452, - 258.945, - 214.754, - 235.377, - 216.697, - 262.265, - 260.66900000000004, - 309.672, - 267.837, - 229.062, - 149.917, - 130.929, - 104.751, - 93.993, - 84.226, - 75.528, - 71.217, - 70.045, - 78.171, - 101.91, - 114.594, - 152.047, - 327.019, - 341.945, - 346.404, - 349.514, - 329.546, - 343.403, - 325.79200000000003, - 307.327, - 334.68300000000005, - 331.622, - 327.074, - 319.642, - 315.546, - 304.045, - 305.697, - 302.064, - 300.819, - 294.802, - 291.185, - 287.28700000000003, - 284.573, - 282.497, - 279.007, - 278.335, - 273.887, - 227.834, - 164.011, - 93.784, - 80.863, - 79.013, - 78.016, - 77.851, - 75.792, - 70.259, - 67.551, - 63.697, - 62.453, - 61.787, - 64.655, - 64.704, - 65.805, - 66.565, - 69.164, - 69.786, - 69.51100000000001, - 66.384, - 66.21300000000001, - 65.756, - 65.304, - 67.028, - 67.529, - 64.578, - 61.016000000000005, - 58.538, - 58.373000000000005, - 55.989, - 53.914, - 54.927, - 55.00899999999999, - 55.235, - 53.363, - 49.113, - 44.857, - 41.268, - 38.295, - 34.755, - 30.45, - 27.499, - 24.57, - 23.546, - 20.854, - 19.984, - 17.419, - 15.046, - 13.521, - 12.227, - 10.333, - 7.542000000000001, - 5.989, - 3.749, - 0.947, - -0.848, - -1.724, - -1.234, - -0.05, - 1.2, - 3.072, - 3.963, - 5.263, - 6.122000000000001, - 7.685, - 9.425, - 11.253, - 12.475, - 14.611, - 17.022000000000002, - 18.718, - 21.278, - 23.199, - 25.556, - 26.959, - 29.112, - 31.011, - 33.604, - 35.861999999999995, - 37.926, - 40.448, - 42.782, - 45.573, - 55.153, - 69.654, - 81.36399999999999, - 87.095, - 54.211000000000006, - 99.482, - 100.423, - 99.24, - 103.517, - 110.74, - 115.26, - 118.409, - 121.184, - 127.526, - 133.351, - 138.135, - 142.82, - 146.86700000000002, - 151.244, - 157.178, - 163.488, - 169.808, - 173.16, - 180.626, - 187.056, - 193.31, - 193.095, - 199.796, - 206.418, - 210.124, - 215.723, - 217.099, - 225.489, - 228.864, - 235.481, - 240.778, - 246.008, - 247.39, - 254.128, - 259.055, - 262.744, - 268.85, - 274.41, - 278.297, - 285.267, - 287.827, - 295.215, - 299.856, - 302.23400000000004, - 309.892, - 314.621, - 317.44, - 324.019, - 330.642, - 331.875, - 339.731, - 342.62699999999995, - 346.481, - 350.742, - 356.782, - 364.467, - 369.158, - 371.195, - 377.24, - 379.067, - 384.787, - 390.557, - 394.394, - 399.459, - 399.878, - 410.041, - 415.084, - 417.154, - 421.751, - 426.909, - 432.326, - 436.076, - 439.94, - 446.211, - 451.937, - 456.407, - 461.61, - 463.669, - 468.612, - 471.706, - 478.296, - 480.086, - 481.941, - 488.652, - 493.249, - 499.69, - 504.92, - 510.327, - 512.226, - 518.3430000000001, - 519.24, - 519.95, - 524.58, - 527.41, - 531.423, - 537.876, - 541.961, - 543.232, - 549.547, - 553.748, - 556.721, - 559.457, - 561.549, - 565.678, - 571.018, - 575.279, - 579.172, - 585.007, - 588.85, - 592.2909999999999, - 592.484, - 599.475, - 602.933, - 607.5409999999999, - 611.576, - 615.832, - 614.643, - 623.391, - 624.674, - 629.8430000000001, - 631.236, - 637.975, - 640.595, - 642.654, - 644.719, - 646.943, - 650.764, - 653.23, - 657.7, - 660.431, - 664.18, - 669.058, - 667.434, - 668.821, - 675.0039999999999, - 678.252, - 681.1419999999999, - 684.534, - 688.674, - 696.695, - 697.686, - 701.341, - 702.707, - 705.426, - 707.293, - 708.262, - 715.21, - 718.7719999999999, - 718.799, - 722.6310000000001, - 725.9010000000001, - 723.291, - 729.0060000000001, - 734.077, - 735.04, - 736.5319999999999, - 745.318, - 741.426, - 738.029, - 755.674, - 753.345, - 754.8480000000001, - 755.977, - 760.513, - 759.913, - 760.2330000000001, - 764.301, - 764.6310000000001, - 772.047, - 774.007, - 775.565, - 775.8510000000001, - 779.59, - 781.5110000000001, - 784.148, - 788.178, - 791.558, - 786.967, - 782.7439999999999, - 733.3660000000001, - 790.253, - 783.405, - 773.6110000000001, - 741.7289999999999, - 730.6360000000001, - 744.2610000000001, - 735.436, - 725.538, - 714.428, - 706.302, - 687.826, - 671.3539999999999, - 649.106, - 628.4169999999999, - 630.014, - 630.129, - 608.818, - 606.153, - 612.975, - 617.219, - 616.003, - 620.891, - 620.082, - 615.8919999999999, - 584.633, - 586.362, - 572.5930000000001, - 555.085, - 545.561, - 554.111, - 573.8480000000001, - 594.306, - 596.937, - 597.169, - 593.364, - 613.4590000000001, - 608.592, - 602.993, - 615.16, - 602.371, - 587.732, - 582.117, - 594.493, - 613.58, - 624.756, - 641.614, - 646.827, - 637.804, - 630.179, - 624.442, - 599.239, - 588.977, - 581.831, - 576.033, - 574.2, - 517.9630000000001, - 499.189, - 507.425, - 484.209, - 473.022, - 474.955, - 494.647, - 497.119, - 514.406, - 498.055, - 466.174, - 441.8730000000001, - 432.734, - 410.426, - 409.655, - 407.057, - 409.782, - 400.412, - 421.712, - 450.23, - 458.48800000000006, - 452.316, - 439.483, - 446.1830000000001, - 440.832, - 451.667, - 448.776, - 456.104, - 465.205, - 476.05, - 477.019, - 474.305, - 461.048, - 458.708, - 453.186, - 466.796, - 453.572, - 447.697, - 411.048, - 394.009, - 409.496, - 425.461, - 440.15, - 440.882, - 453.643, - 433.653, - 427.443, - 428.875, - 469.102, - 476.369, - 451.821, - 377.685, - 329.045, - 299.696, - 298.232, - 321.949, - 320.683, - 341.686, - 368.233, - 332.861, - 304.992, - 301.596, - 306.099, - 281.193, - 227.675, - 219.846, - 226.425, - 229.662, - 224.052, - 212.843, - 195.391, - 182.591, - 180.169, - 182.988, - 189.495, - 191.526, - 196.729, - 191.488, - 191.807, - 196.195, - 203.936, - 198.282, - 194.527, - 193.69, - 199.906, - 211.456, - 215.293, - 216.763, - 227.603, - 239.924, - 241.956, - 234.259, - 247.004, - 236.924, - 238.553, - 243.398, - 240.122, - 215.888, - 200.385, - 181.639, - 168.773, - 160.878, - 154.558, - 146.641, - 139.649, - 133.329, - 127.587, - 118.228, - 111.5, - 110.707, - 108.665, - 105.252, - 102.224, - 105.108, - 105.67, - 103.638, - 105.571, - 103.941, - 101.701, - 108.065, - 113.625, - 116.064, - 119.257, - 118.498, - 119.197, - 120.38, - 123.673, - 123.717, - 124.834, - 117.424, - 123.227, - 135.977, - 153.875, - 136.792, - 138.355, - 128.446, - 124.135, - 121.135, - 124.344, - 135.05200000000002, - 147.357, - 153.363, - 137.062, - 155.14700000000002, - 169.62599999999998, - 134.41899999999998, - 107.514, - 95.38, - 90.662, - 87.965, - 82.26100000000001, - 79.22800000000001, - 74.796, - 68.294, - 62.337, - 56.25899999999999, - 50.891000000000005, - 47.985, - 46.085, - 44.246, - 44.081, - 42.975, - 42.815, - 42.253, - 40.53, - 39.512, - 39.126, - 37.216, - 35.652, - 33.869, - 30.962, - 28.495, - 25.6, - 23.007, - 19.802, - 17.573, - 16.692, - 13.906, - 12.618, - 12.029000000000002, - 11.324000000000002, - 10.603, - 9.882, - 9.194, - 9.072, - 6.722, - 5.307, - 4.652, - 3.848, - 2.8510000000000004, - 2.741, - 2.196, - 0.836, - -0.204, - -1.294, - -2.048, - -1.509, - -0.92, - -0.8320000000000001, - -0.193, - 0.765, - 2.813, - 3.518, - 4.475, - 5.555, - 5.874, - 7.124, - 9.766, - 11.363, - 14.831, - 18.415, - 20.755, - 21.845, - 24.372, - 26.932, - 30.092, - 34.926, - 38.774, - 41.708, - 43.993, - 45.893, - 56.347, - 68.542, - 82.652, - 83.73100000000001, - 60.493, - 101.486, - 101.838, - 105.45, - 104.921, - 101.178, - 98.194, - 111.621, - 122.77, - 129.563, - 133.241, - 129.613, - 136.858, - 154.035, - 165.101, - 174.741, - 186.412, - 187.205, - 189.181, - 188.724, - 192.457, - 189.445, - 183.923, - 180.075, - 179.106, - 169.72, - 172.313, - 178.53400000000002, - 174.201, - 154.72299999999998, - 169.951, - 194.956, - 227.719, - 252.427, - 236.054, - 227.477, - 251.761, - 225.032, - 180.747, - 181.853, - 244.956, - 247.566, - 253.699, - 277.768, - 256.677, - 225.665, - 242.611, - 249.052, - 250.324, - 237.788, - 225.61, - 266.813, - 308.048, - 259.342, - 289.533, - 316.35, - 258.428, - 241.031, - 305.703, - 326.535, - 343.673, - 278.908, - 266.185, - 254.249, - 317.335, - 293.558, - 289.78700000000003, - 238.647, - 296.536, - 333.059, - 278.809, - 232.228, - 266.741, - 311.736, - 375.687, - 357.844, - 310.228, - 368.574, - 300.10900000000004, - 273.518, - 332.96, - 394.785, - 392.798, - 323.80400000000003, - 474.619, - 447.351, - 481.627, - 478.588, - 516.311, - 518.766, - 523.991, - 521.96, - 513.894, - 524.266, - 536.494, - 533.758, - 526.1709999999999, - 530.955, - 526.865, - 545.9580000000001, - 558.736, - 552.085, - 551.133, - 558.802, - 549.635, - 585.161, - 601.248, - 583.4159999999999, - 557.37, - 588.2330000000001, - 594.5369999999999, - 580.14, - 565.359, - 612.975, - 569.322, - 489.28, - 398.353, - 391.086, - 400.395, - 461.593, - 477.11300000000006, - 420.666, - 325.726, - 419.659, - 474.861, - 308.428, - 557.26, - 662.633, - 668.7660000000001, - 672.163, - 710.447, - 701.6439999999999, - 708.025, - 703.5, - 699.6460000000001, - 703.015, - 720.919, - 720.842, - 713.2719999999999, - 716.927, - 712.919, - 715.4739999999999, - 715.584, - 722.5319999999999, - 730.68, - 745.39, - 750.1080000000001, - 746.596, - 687.4789999999999, - 721.7439999999999, - 712.457, - 728.202, - 727.0239999999999, - 749.1389999999999, - 775.18, - 757.0060000000001, - 771.684, - 772.488, - 590.909, - 478.225, - 745.17, - 691.173, - 789.664, - 762.33, - 509.859, - 753.367, - 487.595, - 521.519, - 584.82, - 521.602, - 701.6110000000001, - 698.2919999999999, - 755.96, - 753.4830000000001, - 317.743, - 684.148, - 693.32, - 782.8380000000001, - 720.451, - 545.754, - 769.5310000000001, - 523.011, - 617.654, - 597.559, - 362.73800000000006, - 790.342, - 746.095, - 748.567, - 767.2239999999999, - 701.98, - 791.784, - 581.864, - 730.173, - 699.635, - 728.654, - 586.571, - 559.451, - 632.535, - 673.1210000000001, - 501.777, - 787.908, - 544.1519999999999, - 743.21, - 539.637, - 657.832, - 679.628, - 716.547, - 740.3969999999999, - 556.115, - 389.027, - 621.354, - 701.633, - 693.188, - 601.1659999999999, - 281.765, - 389.379, - 497.191, - 654.981, - 703.56, - 577.993, - 346.431, - 630.206, - 664.8960000000001, - 625.461, - 525.246, - 600.026, - 436.577, - 547.5319999999999, - 513.492, - 214.682, - 423.71, - 608.895, - 371.685, - 272.527, - 229.624, - 353.176, - 501.942, - 501.491, - 399.151, - 573.193, - 622.378, - 634.7040000000001, - 623.611, - 607.695, - 346.338, - 589.268, - 585.932, - 590.948, - 583.279, - 570.539, - 572.279, - 573.215, - 567.368, - 565.039, - 565.502, - 562.419, - 516.465, - 559.677, - 561.697, - 388.11300000000006, - 125.28, - 104.624, - 124.95, - 413.382, - 260.784, - 202.845, - 211.687, - 233.076, - 137.998, - 250.159, - 346.547, - 379.348, - 368.348, - 130.582, - 166.114, - 110.746, - 125.038, - 131.87, - 130.417, - 284.358, - 177.03599999999997, - 151.689, - 163.565, - 181.039, - 302.476, - 355.031, - 420.049, - 289.82, - 120.711, - 95.001, - 87.656, - 93.195, - 84.78299999999999, - 86.164, - 91.642, - 102.581, - 113.339, - 119.351, - 133.918, - 170.30900000000003, - 143.05200000000002, - 112.139, - 103.264, - 103.093, - 105.042, - 104.222, - 104.503, - 100.671, - 97.401, - 98.64, - 97.456, - 88.311, - 86.79799999999999, - 87.833, - 92.958, - 94.411, - 96.575, - 102.758, - 103.06, - 99.262, - 97.863, - 94.45, - 133.357, - 208.698, - 224.014, - 286.362, - 175.054, - 78.985, - 70.342, - 71.34899999999999, - 91.494, - 117.952, - 55.615, - 49.911, - 48.32, - 47.621, - 52.24, - 67.749, - 141.30100000000002, - 150.236, - 109.816, - 65.932, - 59.474, - 59.276, - 57.426, - 54.949, - 49.003, - 45.7, - 41.38399999999999, - 37.513000000000005, - 35.151, - 30.824, - 29.272, - 27.482, - 26.007, - 24.84, - 23.331, - 19.918, - 17.066, - 17.408, - 19.092, - 19.054, - 18.52, - 18.503, - 17.066, - 15.712, - 14.154000000000002, - 12.144, - 10.284, - 8.709, - 8.34, - 8.252, - 6.077999999999999, - 5.114, - 4.74, - 4.938, - 4.999, - 5.362, - 5.676, - 5.757999999999999, - 5.604, - 4.756, - 4.531000000000001, - 3.248, - 2.725, - 1.348, - 0.0819999999999999, - -1.663, - -1.3769999999999998, - -1.558 - ], + "y": { + "bdata": "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", + "dtype": "f8" + }, "yaxis": "y" }, { @@ -20953,9506 +15424,10 @@ "2010-03-08T00:15:00-07:00" ], "xaxis": "x", - "y": [ - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 798.7539999999999, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 796.073, - 792.4169999999999, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 800, - 800, - 800, - 800, - 799.1610000000001, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 797.306, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 795.5880000000001, - 795.5219999999999, - 800, - 800, - 800, - 800, - 800, - 800, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 796.6010000000001, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 792.164, - 800, - 800, - 797.025, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 793.325, - 800, - 800, - 800, - 800, - 800, - 795.054, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 796.227, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 796.342, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 796.904, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 795.8910000000001, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 794.52, - 800, - 800, - 800, - 800, - 800, - 797.196, - 800, - 800, - 800, - 800, - 796.238, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 800, - 800, - 800, - 800, - 800, - 796.909, - 800, - 800, - 793.27, - 800, - 795.395, - 800, - 800, - 800, - 800, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 792.8960000000001, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 793.81, - 794.3, - 800, - 796.497, - 800, - 800, - 798.418, - 800, - 799.8660000000001, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 793.485, - 797.053, - 796.1, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 792.362, - 800, - 795.175, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 798.132, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 797.5980000000001, - 795.23, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 793.678, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 797.878, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 795.258, - 800, - 800, - 800, - 800, - 796.909, - 794.8610000000001, - 800, - 800, - 800, - 800, - 800, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null - ], + "y": { + "bdata": "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", + "dtype": "f8" + }, "yaxis": "y" } ], @@ -30542,7 +15517,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -30578,7 +15553,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -30602,7 +15577,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -30638,64 +15613,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "type": "heatmap" } ], - "heatmapgl": [ - { - "colorbar": { - "outlinewidth": 0, - "ticks": "" - }, - "colorscale": [ - [ - 0, - "#0d0887" - ], - [ - 0.1111111111111111, - "#46039f" - ], - [ - 0.2222222222222222, - "#7201a8" - ], - [ - 0.3333333333333333, - "#9c179e" - ], - [ - 0.4444444444444444, - "#bd3786" - ], - [ - 0.5555555555555556, - "#d8576b" - ], - [ - 0.6666666666666666, - "#ed7953" - ], - [ - 0.7777777777777778, - "#fb9f3a" - ], - [ - 0.8888888888888888, - "#fdca26" - ], - [ - 1, - "#f0f921" - ] - ], - "type": "heatmapgl" - } - ], "histogram": [ { "marker": { @@ -30716,7 +15640,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -30752,7 +15676,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -30767,7 +15691,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -30803,7 +15727,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -30896,6 +15820,17 @@ "type": "scattergl" } ], + "scattermap": [ + { + "marker": { + "colorbar": { + "outlinewidth": 0, + "ticks": "" + } + }, + "type": "scattermap" + } + ], "scattermapbox": [ { "marker": { @@ -30948,7 +15883,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -30984,7 +15919,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -31075,7 +16010,7 @@ ], "sequential": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -31111,13 +16046,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "sequentialminus": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -31153,7 +16088,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ] @@ -31285,8 +16220,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "datetime" @@ -31295,42 +16230,15 @@ "yaxis": { "anchor": "x", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "ac_power" } } } - }, - "text/html": [ - "
" - ] + } }, "metadata": {}, "output_type": "display_data" @@ -31346,10 +16254,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:14.960748Z", - "iopub.status.busy": "2026-02-04T19:31:14.960748Z", - "iopub.status.idle": "2026-02-04T19:31:15.453321Z", - "shell.execute_reply": "2026-02-04T19:31:15.452315Z" + "iopub.execute_input": "2026-03-20T15:45:33.194287Z", + "iopub.status.busy": "2026-03-20T15:45:33.193686Z", + "iopub.status.idle": "2026-03-20T15:45:33.814847Z", + "shell.execute_reply": "2026-03-20T15:45:33.813137Z" } }, "outputs": [ @@ -45517,14151 +30425,10 @@ "2010-03-08T00:15:00-07:00" ], "xaxis": "x", - "y": [ - 62.464, - 84.915, - 94.197, - 27.059, - 79.618, - 67.46300000000001, - 40.778, - 169.49900000000002, - 151.93200000000002, - 150.47799999999998, - 209.925, - 42.622, - null, - null, - 104.47, - 165.442, - 67.942, - 50.572, - 128.297, - 124.697, - 109.259, - 20.237, - 0.556, - 82.806, - 110.702, - 95.232, - 104.321, - 123.959, - 128.264, - 176.315, - 79.442, - 93.861, - 133.208, - 133.72, - 91.747, - 136.616, - 114.572, - 123.342, - 125.693, - 152.42700000000002, - 69.164, - 13.053, - 85.256, - 45.524, - 167.98, - 152.334, - 146.173, - 141.785, - 181.479, - 236.137, - 258.202, - 205.064, - 249.933, - 229.574, - 207.085, - 238.036, - 124.152, - 220.435, - 163.289, - 76.266, - 218.112, - 214.506, - 106.342, - 58.313, - 200.269, - 49.003, - 174.21200000000002, - 170.68900000000002, - 160.465, - 140.541, - 118.305, - 96.531, - 33.654, - 58.676, - 45.17100000000001, - 24.229, - 39.969, - 31.975, - 28.143, - 26.805, - 15.784, - 17.555999999999997, - 7.838999999999999, - 15.050999999999998, - 7.058, - 5.285, - 3.512, - 6.777, - 5.235, - 4.965, - -4.763, - -3.006, - 6.815, - 3.892, - 6.865, - 10.52, - 10.13, - 21.751, - 9.953, - 31.54, - 3.859, - 10.867, - 34.931, - 31.656, - 28.595, - 14.6, - 18.283, - 13.857, - 6.942, - 9.689, - 7.553, - 3.941, - 3.897, - 5.4, - 7.282999999999999, - 7.861000000000001, - 5.433, - 5.472, - 5.2075000000000005, - 4.9430000000000005, - -0.815, - -0.193, - 5.307, - 4.5360000000000005, - 7.146, - 2.009, - 7.058, - 4.96, - 6.265, - 5.7860000000000005, - 2.02, - 7.443, - 2.824, - null, - null, - null, - null, - 5.053999999999999, - 7.3, - 4.96, - 5.684, - 6.408, - 3.149, - 1.971, - 2.67, - 2.081, - null, - null, - null, - -1.492, - -1.669, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -2.219, - null, - null, - null, - null, - null, - -1.481, - -0.672, - -3.628, - -5.638, - -0.397, - -0.534, - 1.079, - 3.451, - 3.65, - -0.738, - 0.759, - -1.294, - 2.857, - 1.596, - 2.51, - 1.514, - 1.8, - 2.736, - -1.47, - 0.754, - 4.6080000000000005, - 1.2990000000000002, - 3.589, - 3.033, - 3.2645, - 3.4960000000000004, - 3.49, - 1.855, - 5.702999999999999, - 3.567, - 1.927, - 6.683, - 1.585, - 5.587999999999999, - 2.516, - 6.738, - 1.249, - 2.989, - 9.568, - 10.504, - 9.524, - 11.17, - 15.503, - 17.11, - 13.939, - 8.037, - 6.54, - 16.02, - 13.824000000000002, - 16.202, - 5.318, - null, - null, - 15.442, - 22.792, - 17.875999999999998, - 20.931, - 12.513, - 6.082999999999999, - 20.882, - 12.029000000000002, - 18.316, - 0.589, - 8.913, - 17.76, - 19.72, - 19.384, - 29.536, - 28.545, - 30.582, - 25.886, - 23.078000000000003, - 32.509, - 6.457000000000001, - 0.5720000000000001, - 41.857, - 33.819, - 19.775, - 45.342, - 48.084, - 17.435, - 31.375, - 51.618, - 53.6, - 59.17100000000001, - 20.425, - 39.649, - 33.643, - 67.33, - 42.82, - 9.364, - 86.836, - 73.35300000000001, - 75.979, - 83.478, - 97.225, - 36.385, - 91.345, - 123.227, - 78.204, - 123.293, - 146.674, - 3.011, - 76.205, - 150.632, - 15.970999999999998, - 65.827, - 220.914, - 166.02, - 280.02, - 303.121, - 335.624, - 148.072, - 145.898, - 11.478, - 497.169, - 207.266, - 596.558, - 640.1990000000001, - 630.46, - 360.399, - 528.313, - 725.6310000000001, - 451.617, - 93.244, - 718.199, - 649.217, - 524.283, - 204.75, - 344.686, - 551, - 668.64, - 652.889, - 485.25, - 71.206, - 540.865, - 415.04, - 773.0989999999999, - 625.9730000000001, - 669.1460000000001, - 721.442, - 306.253, - 482.728, - 607.849, - 180.053, - 691.492, - 531.721, - 11.88, - 746.034, - 567.456, - 609.528, - 374.057, - 734.33, - 626.099, - 229.238, - 590.474, - 571.409, - 340.298, - 192.44, - 482.453, - 726.341, - 377.641, - 125.61, - 31.689, - 625.604, - 337.023, - 666.823, - 225.555, - 526.496, - 721.1610000000001, - 425.957, - 742.324, - 789.455, - 705.828, - 174.15099999999998, - 610.145, - 445.699, - 87.992, - 406.027, - 474.762, - 674.541, - 390.348, - 669.0360000000001, - 227.02, - 404.64, - 473.6830000000001, - 731.186, - 676.055, - 233.626, - 734.7919999999999, - 550.967, - 412.386, - 445.859, - 587.132, - 662.039, - 559.451, - 668.7389999999999, - 772.1410000000001, - 342.68800000000005, - 417.682, - 766.5360000000001, - 463.872, - 615.457, - 565.045, - 524.756, - 706.544, - 286.659, - 467.539, - 209.87, - 31.292, - 592.489, - 119.499, - 505.757, - 564.109, - 749.7280000000001, - 494.086, - 342.36800000000005, - 711.681, - 607.965, - 641.663, - 236.472, - 285.151, - 610.508, - 762.5889999999999, - 141.582, - 653.434, - 776.633, - 652.151, - 583.653, - 645.577, - 523.441, - 416.504, - 774.574, - 166.025, - 658.95, - 409.661, - 245.534, - 615.48, - 786.581, - 732.54, - 261.885, - 567.307, - 180.703, - 798.7539999999999, - 489.973, - 122.533, - 90.47, - 561.808, - 633.8290000000001, - 611.549, - 629.689, - 690.7660000000001, - 712.765, - 766.602, - 488.459, - 672.824, - 423.254, - 658.262, - 184.48, - 602.58, - 438.465, - 454.67800000000005, - 277.62, - 594.394, - 694.735, - 282.844, - 675.158, - 562.215, - 578.9069999999999, - 493.585, - 629.5840000000001, - 750.345, - 767.5269999999999, - 275.863, - 759.847, - 721.21, - 380.961, - 0.4679999999999999, - 377.454, - 713.409, - 204.596, - 427.261, - 655.096, - 767.423, - 765.419, - 338.305, - 348.51800000000003, - 289.588, - 479.64, - 440.32, - 502.399, - 417.6880000000001, - 744.8889999999999, - 745.4010000000001, - 742.5269999999999, - 738.6569999999999, - 599.448, - 484.804, - 306.132, - 257.222, - 46.058, - 579.304, - 542.891, - 570.346, - 697.35, - 362.452, - 410.019, - 693.706, - 417.165, - 457.277, - 501.485, - 567.462, - 437.986, - 423.529, - 280.02, - 460.806, - 525.819, - 501.612, - 657.948, - 638.514, - 20.276, - 456.027, - 626.991, - 576.606, - 376.48, - 15.057, - 631.2080000000001, - 439.17, - 622.24, - 498.628, - 566.052, - 513.492, - 390.304, - 406.594, - 603.599, - 479.535, - 409.441, - 408.262, - 490.832, - 494.895, - 581.842, - 575.433, - 403.071, - 333.521, - 299.559, - 386.72, - 512.7330000000001, - 555.614, - 551.65, - 411.42800000000005, - 431.099, - 541.746, - 535.927, - 435.608, - 443.811, - 413.437, - 232.156, - 463.569, - 338.79, - 497.3730000000001, - 333.819, - 404.932, - 337.07199999999995, - 322.307, - 258.956, - 470.126, - 455.273, - 397.852, - 291.014, - 435.305, - 355.031, - 0.402, - 389.77, - 362.722, - 207.938, - 358.907, - 197.731, - 365.552, - 380.576, - 347.219, - 73.485, - 211.373, - 263.096, - 59.403, - 90.756, - 250.891, - 269.648, - 223.557, - 219.11900000000003, - 224.762, - 245.105, - 202.466, - 60.674, - 240.998, - 185.327, - 52.675, - 189.264, - 119.566, - 90.673, - 121.702, - 88.37799999999999, - 116.037, - 88.76299999999999, - 102.438, - 107.85, - 97.764, - 103.952, - 92.253, - 80.791, - 61.445, - 44.213, - 0.429, - 39.936, - 51.13399999999999, - 54.354, - 64.15899999999999, - 26.227, - 0.335, - 43.156000000000006, - 41.059, - 40.954, - 48.133, - 37.183, - 25.748, - 35.311, - 28.848000000000003, - 20.342, - 24.763, - 29.96, - 28.506, - 23.535, - 31.386, - 21.707, - 22.852, - 23.155, - 23.618, - 19.059, - 23.089, - 14.897, - 3.859, - 12.018, - 15.013, - 13.515, - 5.769, - 6.727, - 2.962, - 10.152, - 12.645, - 9.106, - 0.451, - 3.991, - 5.059, - 5.516, - 0.528, - 6.215, - 0.589, - 3.782, - -1.019, - 0.09050000000000002, - 1.2, - 0.748, - -2.395, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -1.779, - 0.297, - -1.024, - 1.238, - 2.989, - 1.915, - 5.092, - 6.155, - 4.591, - 8.467, - 7.245, - 12.233, - 13.548, - 19.56, - 30.499, - 43.558, - 40.36, - 24.647, - 29.668000000000003, - 46.983, - 43.696000000000005, - 0.6659999999999999, - 0.677, - 16.059, - 31.441, - 62.458, - 69.428, - 51.877, - 52.697, - 93.938, - 62.965, - 77.4, - 75.638, - 96.476, - 79.387, - 41.852, - 92.044, - 87.34299999999999, - 63.438, - 84.116, - 80.65899999999999, - 117.98, - 121.867, - 153.159, - 131.066, - 48.188, - 226.486, - 162.739, - 42.969, - 121.735, - 112.871, - 125.021, - 129.31, - 11.148, - 116.917, - 131.408, - 95.92, - 96.074, - 130.158, - 142.512, - 78.473, - 100.308, - 213.036, - 224.526, - 113.79, - 131.892, - 130.918, - 202.504, - 215.15, - 141.59799999999998, - 164.55, - 116.45, - 167.91400000000002, - 160.74, - 152.179, - 9.469, - 124.019, - 247.246, - 227.889, - 160.939, - 138.43200000000002, - 138.493, - 36.935, - 107.619, - 116.251, - 92.897, - 11.561, - 5.7860000000000005, - 126.849, - 134.314, - 134.81, - 116.18, - 139.908, - 118.255, - 0.638, - 71.184, - 118.894, - 145.16, - 10.074, - 60.41, - 148.17700000000002, - 118.723, - 157.079, - 157.239, - 83.5, - 171.43200000000002, - 168.602, - 171.861, - 94.934, - 185.674, - 113.02, - 65.58, - 151.233, - 101.2, - 87.095, - 164.055, - 259.777, - 306.815, - 29.987, - 12.359000000000002, - 152.091, - 86.324, - 302.46, - 282.718, - 17.127, - 260.9, - 315.48, - 25.534, - 156.336, - 240.37, - 171.845, - 189.401, - 197.781, - 171.856, - 170.391, - 160.482, - 264.54400000000004, - 171.696, - 281.435, - 312.66700000000003, - 355.75800000000004, - 436.912, - 318.183, - 316.025, - 264.941, - 246.679, - 123.62850000000002, - 0.578, - 299.459, - 346.646, - 326.205, - 101.8, - 262.172, - 318.882, - 77.334, - 249.878, - 75.39, - 87.486, - 161.731, - 336.621, - 247.885, - 215.453, - 237.706, - 135.311, - 367.655, - 439.17, - 312.568, - 400.401, - 392.319, - 455.46, - 485.5580000000001, - 366.829, - 378.236, - 450.252, - 408.224, - 400.979, - 345.36300000000006, - 357.222, - 446.789, - 129.376, - 38.031, - 388.14, - 521.965, - 170.887, - 609.198, - 623.765, - 618.056, - 457.304, - 51.145, - 336.059, - 189.032, - 136.47799999999998, - 245.11, - 580.383, - 432.117, - 622.064, - 579.986, - 598.44, - 264.588, - 522.5930000000001, - 615.1709999999999, - 339.324, - 324.14, - 107.206, - 622.477, - 402.454, - 206.771, - 445.974, - 305.466, - 337.7, - 336.92400000000004, - 403.566, - 217.308, - 156.782, - 334.788, - 354.50199999999995, - 382.552, - 404.761, - 437.21, - 446.305, - 463.608, - 121.509, - 471.503, - 451.628, - 441.339, - 111.908, - 191.482, - 473.523, - 34.788000000000004, - 250.263, - 353.577, - 457.86, - 268.828, - 415.051, - 394.081, - 361.362, - 30.516, - 128.154, - 36.754, - 65.767, - 370.077, - 393.376, - 422.18, - 216.13, - 488.547, - 328.908, - 538.602, - 540.529, - 518.645, - 426.909, - 161.97899999999998, - 67.997, - 204.938, - 0.4679999999999999, - 181.033, - 44.153, - 262.331, - 462.909, - 371.844, - 560.442, - 563.487, - 378.698, - 657.42, - 682.689, - 531.297, - 731.153, - 747.9939999999999, - 758.295, - 465.739, - 608.818, - 616.25, - 800, - 800, - 543.535, - 587.573, - 746.965, - 234.694, - 767.659, - 672.9169999999999, - 394.565, - 516.14, - 487.171, - 583.234, - 321.569, - 530.658, - 593.915, - 800, - 800, - 596.365, - 800, - 565.447, - 560.453, - 800, - 443.833, - 800, - 661.554, - 800, - 511.45, - 748.9689999999999, - 593.987, - 650.653, - 572.906, - 515.48, - 725.835, - 666.7510000000001, - 436.164, - 474.635, - 800, - 800, - 670.187, - 800, - 252.036, - 562.187, - 354.684, - 346.096, - 659.0110000000001, - 339.528, - 529.3480000000001, - 486.857, - 493.469, - 796.073, - 491.162, - 662.936, - 619.752, - 428.853, - 545.9630000000001, - 757.0010000000001, - 714.23, - 666.663, - 472.697, - 517.974, - 261.241, - 520.495, - 679.65, - 565.188, - 612.297, - 773.6, - 212.827, - 595.341, - 662.903, - 792.4169999999999, - 572.8290000000001, - 371.376, - 741.388, - 649.332, - 745.676, - 784.44, - 764.285, - 697.548, - 697.201, - 680.5039999999999, - 600.4304999999999, - 520.357, - 759.798, - 600.9780000000001, - 448.6830000000001, - 730.454, - 720.4839999999999, - 635.1669999999999, - 688.569, - 419.229, - 541.592, - 420.528, - 442.198, - 464.07, - 293.475, - 208.896, - 653.346, - 631.225, - 345.54, - 358.329, - 347.736, - 577.586, - 264.181, - 619.476, - 352.163, - 563.663, - 549.3430000000001, - 311.577, - 516.405, - 512.375, - 490.849, - 301.293, - 371.608, - 238.366, - 0.385, - 95.391, - 130.136, - 375.726, - 364.517, - 298.815, - 153.148, - 163.476, - 320.452, - 294.207, - 89.759, - 282.811, - 360.371, - 359.435, - 354.745, - 217.011, - 260.47, - 198.634, - 314.434, - 304.172, - 161.715, - 218.31, - 317.715, - 177.46599999999998, - 311.687, - 223.782, - 293.8, - 292.627, - 186.627, - 193.817, - 110.041, - 94.99, - 279.541, - 229.761, - 155.53799999999998, - 295.848, - 303.952, - 306.594, - 301.133, - 129.28799999999998, - 176.497, - 300.384, - 302.933, - 204.927, - 250.065, - 299.988, - 199.796, - 229.002, - 202.014, - 224.57, - 195.688, - 148.502, - 210.834, - 246.492, - 196.988, - 247.544, - 304.023, - 229.238, - 127.433, - 128.22, - 57.646, - 177.93900000000002, - 133.219, - 273.232, - 196.61900000000003, - 166.136, - 219.642, - 175.03799999999998, - 222.604, - 181.551, - 180.84, - 178.81400000000002, - 200.594, - 50.28, - 184.061, - 218.993, - 162.656, - 150.153, - 199.129, - 106.644, - 195.424, - 153.89700000000002, - 204.095, - 78.672, - 159.1, - 141.16299999999998, - 189.511, - 183.841, - 179.128, - 176.387, - 176.541, - 29.811, - 141.295, - 173.072, - 173.072, - 132.745, - 165.453, - 97.693, - 105.984, - 135.526, - 148.92, - 51.75, - 113.256, - 144.422, - 120.056, - 32.949, - 133.07, - 93.542, - 77.846, - 124.096, - 129.844, - 133.076, - 33.527, - 113.141, - 106.375, - 0.462, - 0.517, - 111.864, - 111.076, - 56.199, - 109.551, - 99.812, - 102.46, - 106.088, - 76.657, - 92.033, - 80.94, - 76.156, - 83.5, - 54.608, - 86.28, - 80.626, - 66.24, - 77.604, - 78.86399999999999, - 56.705, - 76.882, - 81.182, - 51.112, - 82.646, - 87.98700000000001, - 85.069, - 0.484, - 0.517, - 45.381, - 90.376, - 91.769, - 68.999, - 35.278, - 88.09700000000001, - 98.227, - 96.944, - 90.431, - 9.001, - 77.626, - 35.845, - 35.339, - 95.705, - 62.458, - 117.545, - 87.822, - 83.979, - 116.185, - 158.423, - 28.33, - 165.26, - 27.642, - 0.49, - 168.101, - 189.5, - 143.72899999999998, - 194.191, - 189.401, - 195.947, - 213.372, - 36.5, - 44.268, - 288.944, - 315.238, - 224.83900000000003, - 296.426, - 244.923, - 69.544, - 16.02, - 194.918, - 68.024, - 234.931, - 214.704, - 334.975, - 329.546, - 302.587, - 26.238000000000003, - 290.634, - 149.944, - 233.835, - 256.336, - 113.08, - 195.512, - 168.382, - 162.276, - 28.435, - 126.855, - 160.751, - 121.239, - 132.894, - 113.515, - 105.819, - 99.207, - 8.291, - 50.545, - 56.788, - 54.982, - 39.87, - 44.676, - 41.631, - 41.196000000000005, - 36.043, - 38.741, - 18.377, - 37.855, - 31.067, - 30.725, - 25.864, - 35.449, - 20.711, - 14.06, - 30.29, - 0.534, - 19.808, - 20.166, - 20.992, - 14.914, - 20.314, - 21.036, - 14.308, - 14.771, - 9.205, - 12.706, - 3.077, - 6.303, - 11.401, - 11.313, - 5.197, - 4.09, - 9.43, - 7.691, - 5.676, - 0.143, - 3.584, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.5720000000000001, - -5.148, - 0.016, - null, - null, - -9.178, - 2.637, - 0.413, - 3.1239999999999997, - 5.835, - 2.78, - 6.105, - 8.731, - 6.034, - 11.77, - 8.693, - 15.156, - 16.125, - 16.257, - 14.38, - 20.893, - 23.089, - 30.439, - 29.222, - 33.77, - 33.478, - 24.625, - 16.516, - 14.903, - 20.182, - 42.22, - 29.2, - 15.31, - 45.078, - 43.36600000000001, - 46.542, - 29.261, - 48.018, - 39.506, - 36.814, - 54.051, - 47.109, - 53.154, - 0.517, - 58.863, - 60.878, - 39.589, - 0.5670000000000001, - 42.386, - 32.927, - 34.529, - 38.212, - 56.93600000000001, - 43.503, - 55.235, - 50.467, - 50.556, - 16.747, - 20.898000000000003, - 61.027, - 46.658, - 57.173, - 65.172, - 67.727, - 62.706, - 71.421, - 83.77, - 26.783, - 41.461000000000006, - 78.044, - 74.124, - 59.63399999999999, - 115.508, - 118.156, - 107.745, - 79.59100000000001, - 126.271, - 122.638, - 188.741, - 166.05900000000003, - 138.108, - 126.805, - 122.39, - 119.037, - 140.387, - 100.264, - 136.451, - 158.615, - 121.377, - 125.346, - 167.886, - 163.036, - 172.555, - 116.609, - 119.758, - 82.70100000000001, - 158.208, - 125.814, - 124.834, - 156.18200000000002, - 89.572, - 148.832, - 146.68, - 105.83, - 119.599, - 35.113, - 90.409, - 117.215, - 33.467, - 67.738, - 97.291, - 92.809, - 108.742, - 107.195, - 98.849, - 99.587, - 113.801, - 117.418, - 115.057, - 110.702, - 48.915, - 88.851, - 114.159, - 143.404, - 159.689, - 106.71, - 136.847, - 85.322, - 169.53799999999998, - 120.303, - 46.845, - 134.782, - 107.096, - 161.252, - 195.958, - 190.447, - 174.608, - 0.578, - 278.302, - 374.173, - 327.955, - 394.879, - 482.904, - 450.235, - 329.337, - 283.235, - 63.091, - 302.256, - 191.73, - 256.215, - 121.603, - 260.889, - 248.067, - 235.443, - 229.068, - 167.58900000000003, - 167.89700000000002, - 225.467, - 144.08700000000002, - 126.579, - 203.523, - 270.215, - 286.907, - 317.803, - 220.997, - 273.529, - 305.884, - 150.809, - 356.281, - 501.089, - 540.1659999999999, - 598.1759999999999, - 477.206, - 603.368, - 338.476, - 31.138, - 413.658, - 485.866, - 178.347, - 424.47, - 685.684, - 715.248, - 735.998, - 538.3, - 680.074, - 689.962, - 594.3330000000001, - 649.607, - 619.317, - 597.389, - 608.113, - 315.034, - 458.158, - 419.592, - 551.612, - 286.203, - 377.162, - 325.076, - 300.252, - 294.16900000000004, - 221.927, - 138.68, - 70.925, - 275.357, - 278.077, - 255.422, - 218.519, - 71.25, - 204.337, - 228.159, - 461.527, - 470.374, - 384.898, - 347.764, - 341.87300000000005, - 441.509, - 522.923, - 507.1230000000001, - 41.841, - 446.007, - 166.46, - 587.512, - 587.754, - 549.63, - 393.932, - 578.258, - 596.569, - 105.125, - 712.2260000000001, - 503.555, - 469.895, - 526.391, - 528.66, - 756.0369999999999, - 756.1419999999999, - 168.28799999999998, - 800, - 626.887, - 800, - 589.665, - 739.5210000000001, - 659.7919999999999, - 518.381, - 800, - 412.386, - 631.996, - 601.595, - 677.068, - 258.439, - 800, - 781.687, - 209.424, - 732.37, - 662.666, - 445.996, - 736.681, - 714.835, - 463.817, - 379.007, - 669.933, - 504.931, - 597.02, - 179.035, - 628.4119999999999, - 799.1610000000001, - 782.414, - 749.073, - 552.085, - 628.77, - 508.196, - 788.8330000000001, - 734.456, - 98.26, - 800, - 784.115, - 328.495, - 471.029, - 800, - 800, - 5.6370000000000005, - 515.656, - 800, - 310.97700000000003, - 44.037, - 74.565, - 30.621, - 455.251, - 384.512, - 505.05300000000005, - 717.059, - 377.55300000000005, - 594.57, - 800, - 800, - 652.944, - 406.6, - 464.7480000000001, - 800, - 800, - 697.658, - 800, - 800, - 800, - 353.539, - 800, - 800, - 800, - 800, - 314.654, - 705.949, - 800, - 800, - 662.628, - 445.253, - 451.089, - 698.9580000000001, - 392.572, - 800, - 800, - 720.17, - 434.044, - 800, - 800, - 782.331, - 160.509, - 800, - 800, - 797.306, - 250.885, - 800, - 800, - 777.057, - 721.205, - 517.726, - 800, - 800, - 800, - 740.4630000000001, - 693.293, - 800, - 187.552, - 397.009, - 800, - 800, - 800, - 728.8739999999999, - 800, - 651.727, - 752.712, - 79.883, - 625.406, - 800, - 676.765, - 800, - 744.586, - 353.082, - 800, - 800, - 616.685, - 800, - 800, - 800, - 800, - 493.706, - 800, - 756.643, - 508.648, - 795.5880000000001, - 795.5219999999999, - 800, - 800, - 563.244, - 328.407, - 800, - 403.049, - 800, - 551.898, - 800, - 800, - 419.747, - 272.472, - 437.705, - 303.88, - 378.55, - 364.753, - 520.4730000000001, - 478.929, - 460.096, - 418.431, - 381.203, - 296.844, - 289.996, - 258.472, - 302.17400000000004, - 356.19199999999995, - 158.334, - 355.807, - 0.264, - 353.654, - 308.907, - 153.55, - 219.708, - 355.802, - 0.512, - 152.645, - 304.778, - 380.537, - 383.785, - 108.549, - 546.508, - 642.572, - 357.602, - 531.82, - 384.143, - 493.612, - 620.71, - 429.095, - 181.942, - 515.612, - 433.312, - 42.887, - 596.315, - 512.606, - 16.912, - 375.643, - 205.725, - 311.54900000000004, - 316.4, - 222.588, - 206.782, - 276.986, - 285.514, - 393.607, - 115.778, - 53.528, - 0.457, - 75.01, - 229.882, - 255.593, - 0.473, - 121.558, - 152.38299999999998, - 113.878, - 128.418, - 96.652, - 114.297, - 82.156, - 114.379, - 74.086, - 136.775, - 132.327, - 119.329, - 97.599, - 60.757, - 128.374, - 135.42700000000002, - 140.695, - 144.813, - 146.404, - 127.719, - 157.828, - 100.743, - 116.796, - 42.914, - 39.126, - 95.612, - 21.157, - 72.192, - 32.79, - 106.364, - 84.094, - 35.509, - 99.24, - 72.896, - 83.781, - 81.87, - 44.621, - 80.169, - 13.796, - 50.985, - 72.825, - 18.916, - 0.413, - 45.463, - 35.372, - 42.253, - 79.211, - 67.617, - 22.764, - 21.691, - 33.511, - 33.83, - 34.271, - 33.164, - 20.397, - 28.451, - 32.503, - 19.158, - 28.798, - 5.142, - 21.278, - 23.309, - 14.3765, - 5.444, - 12.255, - 7.977, - 7.625, - 9.15, - 4.189, - 5.626, - 12.387, - 12.1, - 12.265999999999998, - 6.331, - 12.007, - 15.178, - 7.746, - 11.886, - 9.579, - 11.495, - 7.3, - 11.803, - 3.402, - 4.872, - 6.023, - 5.428, - 5.318, - 5.207999999999999, - 2.505, - 6.237, - 3.039, - 1.3430000000000002, - 2.758, - 0.644, - 1.899, - -0.413, - 2.158, - -7.317, - 5.197, - 2.9065, - 0.616, - 6.485, - 1.123, - 5.8020000000000005, - 9.975, - 9.458, - 8.693, - 7.564, - 5.312, - 4.913, - 4.513999999999999, - 1.315, - 0, - 3.033, - 4.993, - 3.363, - -6.31, - -3.4635, - -0.617, - 1.695, - -1.514, - -0.088, - -0.36350000000000005, - -0.639, - null, - null, - null, - -7.178999999999999, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -2.715, - null, - null, - -1.872, - -1.4455, - -1.019, - -1.696, - -0.127, - -3.045, - null, - null, - null, - null, - -1.861, - -1.454, - 0.974, - -1.052, - 0.825, - 0.148, - 2.84, - 3.749, - 4.668, - 4.008, - 3.474, - -3.623, - 4.723, - 7.867000000000001, - 3.297, - 7.162000000000001, - 11.462, - 7.377000000000001, - 10.146, - 6.193, - 6.903, - 7.806, - 3.523, - 13.257, - 5.537999999999999, - 1.888, - 13.042, - 14.528, - 7.256, - 9.452, - 13.807, - 10.273, - 18.867, - 12.607, - 15.905, - 14.627, - 8.461, - 16.852, - 18.701, - 21.157, - 11.087, - 13.13, - 24.174, - 24.581, - 33.434, - 17.182000000000002, - 8.379, - 32.503, - 31.782, - 32.107, - 59.562, - 34.1, - 26.453000000000003, - 36.869, - 1.403, - 25.688, - 28.336, - 17.925, - 45.358, - 89.792, - 110.317, - 93.663, - 116.152, - 116.906, - 106.755, - 71.972, - 145.518, - 154.07299999999998, - 172.362, - 178.40200000000002, - 191.114, - 208.637, - 212.772, - 182.85, - 183.957, - 303.886, - 224.333, - 347.186, - 361.175, - 269.56, - 104.729, - 351.039, - 265.502, - 535.288, - 571.211, - 241.207, - 2.543, - 666.597, - 538.63, - 455.3, - 665.446, - 197.136, - 494.609, - 615.067, - 398.259, - 502.746, - 669.3989999999999, - 677.184, - 437.65, - 302.317, - 402.746, - 261.775, - 718.887, - 716.6189999999999, - 434.352, - 479.232, - 654.276, - 737.7489999999999, - 360.811, - 289.599, - 715.727, - 642.929, - 499.641, - 638.624, - 730.327, - 732.75, - 501.639, - 167.143, - 751.941, - 726.573, - 572.295, - 421.844, - 738.508, - 642.026, - 704.81, - 775.637, - 787.325, - 613.971, - 672.2510000000001, - 498.055, - 385.5580000000001, - 590.259, - 525.279, - 584.534, - 381.352, - 622.196, - 527.036, - 220.556, - 264.286, - 274.603, - 510.5630000000001, - 590.254, - 525.1469999999999, - 406.06, - 502.19, - 754.056, - 477.911, - 705.1289999999999, - 601.369, - 779.4960000000001, - 755.597, - 323.991, - 581.005, - 60.862, - 673.066, - 664.665, - 603.764, - 452.999, - 536.4, - 313.096, - 143.806, - 725.1189999999999, - 498.259, - 142.033, - 305.703, - 535.976, - 383.962, - 494.466, - 546.3919999999999, - 320.87, - 229.982, - 643.766, - 796.6010000000001, - 721.012, - 535.283, - 668.3480000000001, - 705.922, - 274.146, - 762, - 599.007, - 787.2589999999999, - 504.854, - 785.4860000000001, - 146.94899999999998, - 574.217, - 614.3009999999999, - 746.6560000000001, - 721.095, - 578.181, - 600.554, - 142.76, - 308.901, - 33.604, - 167.204, - 143.53, - 496.64, - 420.462, - 711.0089999999999, - 275.214, - 553.401, - 748.176, - 670.676, - 566.8340000000001, - 113.906, - 312.85400000000004, - 739.13, - 343.101, - 711.3889999999999, - 732.59, - 680.658, - 327.003, - 332.43699999999995, - 6.9910000000000005, - 18.233, - 316.956, - 520.4680000000001, - 283.868, - 293.123, - 19.516, - 528.175, - 770.7919999999999, - 36.264, - 441.92800000000005, - 704.623, - 705.7510000000001, - 772.7189999999999, - 80.053, - 604.265, - 352.796, - 540.54, - 587.435, - 286.01, - 248.579, - 400.847, - 760.53, - 509.528, - 678.8960000000001, - 485.47, - 721.585, - 452.839, - 382.233, - 516.173, - 728.5989999999999, - 289.654, - 83.02600000000001, - 380.62, - 486.951, - 244.637, - 593.254, - 124.752, - 417.247, - 781.742, - 530.526, - 164.842, - 271.03, - 70.628, - 516.531, - 118.817, - 209.546, - 657.943, - 679.683, - 710.992, - 222.946, - 70.116, - 482.431, - 404.5630000000001, - 149.124, - 432.282, - 0.143, - 183.241, - 570.765, - 778.5210000000001, - 437.826, - 382.646, - 218.172, - 753.775, - 313.603, - 359.017, - 258.087, - 312.72700000000003, - 491.003, - 5.956, - 616.432, - 602.035, - 116.769, - 412.43, - 390.359, - 295.82, - 214.28, - 136.203, - 255.268, - 212.183, - 178.358, - 421.1230000000001, - 627.211, - 503.693, - 534.627, - 230.989, - 19.175, - 195.672, - 150.352, - 209.722, - 179.205, - 203.022, - 126.574, - 158.907, - 129.987, - 341.686, - 507.222, - 653.379, - 766.701, - 534.5830000000001, - 547.433, - 792.164, - 684.8860000000001, - 566.195, - 662.985, - 374.878, - 769.801, - 797.025, - 784.836, - 627.878, - 618.194, - 766.25, - 466.11300000000006, - 515.43, - 789.18, - 596.0840000000001, - 604.122, - 588.09, - 575.56, - 404.117, - 738.437, - 514.99, - 564.747, - 512.2040000000001, - 439.671, - 486.989, - 599.448, - 365.298, - 675.995, - 413.151, - 345.936, - 211.654, - 126.86, - 178.82, - 264.92400000000004, - 220.088, - 77.218, - 229.866, - 212.799, - 91.516, - 559.826, - 278.055, - 236.379, - 531.01, - 550.5880000000001, - 142.67700000000002, - 84.177, - 425.8080000000001, - 577.636, - 580.702, - 332.50300000000004, - 583.763, - 570.4069999999999, - 544.488, - 543.893, - 545.66, - 197.698, - 430.372, - 342.06, - 503.715, - 335.82300000000004, - 348.292, - 312.86, - 315.59, - 134.17700000000002, - 205.422, - 473.782, - 479.629, - 18.586, - 138.95, - 44.065, - 286.076, - 259.452, - 399.79, - 346.459, - 382.728, - 150.93, - 122.979, - 323.777, - 36.71, - 442.489, - 448.931, - 311.059, - 438.366, - 432.035, - 302.988, - 232.294, - 257.16200000000003, - 425.555, - 420.82, - 421.519, - 416.614, - 416.075, - 216.835, - 302.361, - 335.23900000000003, - 406.512, - 307.29900000000004, - 233.533, - 277.9, - 292.275, - 100.434, - 106.76, - 129.877, - 221.459, - 201.74400000000003, - 72.45, - 109.474, - 135.762, - 159.17700000000002, - 244.885, - 173.49599999999998, - 232.129, - 263.961, - 290.166, - 189.974, - 79.574, - 141.356, - 26.398000000000003, - 207.833, - 18.944000000000003, - 152.334, - 183.841, - 157.734, - 163.96099999999998, - 165.94299999999998, - 106.529, - 151.018, - 199.84, - 81.7, - 162.64, - 39.523, - 125.087, - 144.554, - 101.376, - 80.67, - 72.671, - 73.436, - 64.952, - 62.414, - 38.912, - 38.427, - 39.633, - 40.272, - 40.057, - 38.235, - 28.132, - 34.194, - 20.788, - 13.835, - 26.381, - 7.673999999999999, - 11.627, - 9.161, - 20.849, - 6.457000000000001, - 0.446, - 5.566, - 14.479, - 9.909, - 15.453, - 10.058, - 5.4110000000000005, - 0.379, - 5.502000000000001, - 10.625, - 7.267, - 6.155, - 8.23, - 7.388, - 5.0760000000000005, - 5.874, - 2.8510000000000004, - 1.7009999999999998, - 1.69, - 2.939, - 3.028, - 0.847, - 0.589, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -1.223, - 0.919, - -2.45, - 0.479, - 3.991, - 3.545, - 6.237, - 6.76, - 9.067, - 10.526, - 13.598, - 17.039, - 17.413, - 15.8, - 23.276, - 16.108, - 19.67, - 26.673, - 12.595999999999998, - 32.338, - 37.612, - 23.717, - 24.543000000000003, - 38.774, - 33.401, - 36.897, - 50.968, - 76.563, - 90.266, - 101.089, - 64.737, - 61.429, - 97.274, - 126.502, - 101.37, - 131.661, - 110.487, - 110.851, - 137.232, - 130.494, - 153.826, - 86.186, - 120.21, - 184.127, - 94.318, - 172.984, - 114.6, - 167.63299999999998, - 26.767, - 210.157, - 180.466, - 221.255, - 153.991, - 154.673, - 233.863, - 184.623, - 163.64700000000002, - 191.356, - 218.211, - 157.52, - 184.182, - 277.069, - 117.545, - 284.347, - 169.764, - 245.782, - 194.125, - 306.93, - 259.298, - 186.269, - 268.866, - 150.599, - 250.841, - 340.93699999999995, - 111.687, - 233.246, - 329.18300000000005, - 90.822, - 287.111, - 247.852, - 296.476, - 377.273, - 377.691, - 387.804, - 267.693, - 328.407, - 275.214, - 305.879, - 320.072, - 347.131, - 311.648, - 317.605, - 430.267, - 327.036, - 344.527, - 387.948, - 334.589, - 322.78, - 197.946, - 272.841, - 374.272, - 348.51199999999994, - 393.519, - 358.708, - 362.24300000000005, - 282.288, - 225.935, - 461.588, - 395.512, - 351.37, - 374.867, - 456.379, - 256.176, - 517.065, - 516.977, - 85.096, - 441.096, - 533.681, - 295.92, - 540.122, - 539.814, - 545.501, - 414.021, - 43.916, - 28.16, - 19.324, - 469.339, - 567.555, - 552.828, - 387.061, - 503.566, - 583.565, - 586.477, - 592.8580000000001, - 596.8, - 277.862, - 576.716, - 447.103, - 229.728, - 586.224, - 620.264, - 625.587, - 101.139, - 453.792, - 505.763, - 439.318, - 367.7480000000001, - 639.158, - 644.377, - 644.4209999999999, - 653.186, - 659.115, - 659.291, - 626.154, - 0.523, - 224.454, - 453.318, - 580.151, - 604.981, - 460.283, - 438.096, - 159.116, - 692.186, - 475.109, - 701.485, - 704.6010000000001, - 460.25, - 0.545, - 129.013, - 503.461, - 329.04, - 208.373, - 538.823, - 709.0160000000001, - 571.761, - 438.559, - 741.944, - 741.5139999999999, - 744.944, - 744.168, - 500.505, - 336.64300000000003, - 371.861, - 754.837, - 755.8889999999999, - 234.914, - 719.796, - 298.507, - 770.841, - 530.405, - 775.972, - 633.064, - 666.08, - 547.873, - 464.318, - 579.3969999999999, - 736.488, - 318.574, - 651.231, - 534.126, - 793.325, - 479.458, - 436.384, - 648.451, - 735.86, - 664.169, - 711.0360000000001, - 729.925, - 476.436, - 352.586, - 644.724, - 625.967, - 160.21200000000002, - 462.122, - 507.976, - 387.111, - 204.2, - 379.359, - 699.668, - 708.284, - 490.705, - 339.963, - 795.054, - 521.668, - 386.445, - 689.1360000000001, - 676.732, - 136.17, - 269.85200000000003, - 698.765, - 357.431, - 680.1619999999999, - 574.035, - 116.235, - 436.94, - 639.9069999999999, - 215.271, - 124.218, - 226.243, - 350.329, - 463.74, - 181.209, - 303.732, - 228.611, - 447.918, - 633.548, - 458.389, - 489.687, - 629.5459999999999, - 359.47900000000004, - 604.034, - 767.924, - 547.163, - 730.57, - 21.019, - 491.0580000000001, - 209.474, - 468.106, - 481.225, - 524.492, - 43.255, - 308.274, - 620.346, - 717.654, - 402.449, - 653.29, - 515.849, - 705.933, - 410.041, - 621.447, - 54.2, - 284.766, - 133.048, - 749.596, - 796.227, - 417.765, - 606.737, - 422.86300000000006, - 389.214, - 93.872, - 503.087, - 3.094, - 478.093, - 177.273, - 786.212, - 796.342, - 701.204, - 716.834, - 593.689, - 667.9839999999999, - 765.694, - 670.247, - 527.7180000000001, - 679.931, - 764.466, - 706.467, - 765.76, - 638.866, - 619.289, - 560.002, - 730.779, - 514.555, - 613.4540000000001, - 329.117, - 243.106, - 591.404, - 348.76, - 248.584, - 715.8760000000001, - 734.539, - 729.8810000000001, - 790.2860000000001, - 190.546, - 783.807, - 384.798, - 254.453, - 626.066, - 700.125, - 597.4, - 638.118, - 567.153, - 284.909, - 718.8710000000001, - 217.914, - 642.109, - 558.069, - 605.306, - 585.15, - 529.485, - 560.244, - 672.956, - 496.338, - 470.402, - 318.651, - 447.196, - 416.955, - 253.379, - 216.29, - 627.823, - 469.989, - 465.606, - 506.853, - 70.788, - 356.391, - 756.742, - 644.179, - 92.474, - 102.014, - 504.75, - 157.778, - 731.698, - 790.0060000000001, - 768.27, - 352.619, - 134.16, - 774.5139999999999, - 780.465, - 569.763, - 773.721, - 674.1560000000001, - 272.868, - 780.2339999999999, - 379.656, - 779.931, - 776.903, - 776.0880000000001, - 494.499, - 0.363, - 111.753, - 765.253, - 534.6709999999999, - 560.0840000000001, - 501.254, - 438.922, - 284.47900000000004, - 745.3960000000001, - 737.303, - 468.216, - 719.096, - 484.165, - 526.854, - 723.578, - 717.318, - 714.549, - 503.77, - 705.5260000000001, - 639.367, - 228.897, - 682.717, - 670.4889999999999, - 413.283, - 676.408, - 671.805, - 668.788, - 661.62, - 161.671, - 435.068, - 422.009, - 620.946, - 601.793, - 596.238, - 606.643, - 350.759, - 620.798, - 209.898, - 624.288, - 269.295, - 457.205, - 531.6990000000001, - 421.101, - 455.823, - 494.146, - 562.683, - 369.697, - 460.206, - 5.428, - 47.214, - 555.2669999999999, - 483.389, - 175.412, - 360.575, - 270.402, - 397.186, - 547.686, - 567.318, - 569.686, - 555.509, - 529.5740000000001, - 443.607, - 513.399, - 454.607, - 538.911, - 398.848, - 338.036, - 535.613, - 549.332, - 540.821, - 108.858, - 220.551, - 533.9830000000001, - 218.101, - 530.548, - 504.128, - 471.943, - 307.712, - 259.606, - 427.713, - 282.073, - 468.244, - 468.1830000000001, - 266.46, - 444.477, - 401.573, - 350.48900000000003, - 229.459, - 141.884, - 306.396, - 277.251, - 251.766, - 210.267, - 0.391, - 339.786, - 332.095, - 268.932, - 315.546, - 271.129, - 275.362, - 220.033, - 157.178, - 222.604, - 236.21400000000003, - 121.779, - 195.259, - 140.855, - 131.85399999999998, - 234.105, - 233.318, - 198.48, - 105.736, - 140.921, - 0.363, - 109.094, - 253.682, - 85.32799999999999, - 244.648, - 178.15900000000002, - 226.073, - 215.012, - 96.487, - 136.467, - 179.21599999999998, - 179.695, - 171.856, - 137.904, - 148.315, - 61.242, - 128.226, - 164.192, - 163.179, - 98.221, - 115.156, - 44.874, - 127.736, - 122.219, - 88.796, - 88.086, - 43.619, - 69.268, - 41.918, - 45.039, - 57.878, - 54.211000000000006, - 52.218, - 50.187, - 39.231, - 49.06399999999999, - 40.376, - 7.927, - 26.128, - 33.048, - 34.653000000000006, - 36.258, - 15.8, - 26.304, - 23.821, - 32.564, - 29.47, - 25.82, - 30.12, - 28.462, - 14.082, - 26.712, - 20.48, - 24.113000000000003, - 13.46, - 16.609, - 15.211, - 3.363, - 9.744, - 10.917, - 9.353, - 7.773, - 0.517, - 9.838, - 7.982, - 3.0610000000000004, - 5.577000000000001, - 0.847, - 4.668, - -0.997, - 0.858, - 0.925, - -4.256, - 0.655, - -0.342, - 0.407, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -0.969, - -2.417, - null, - null, - 2.494, - 10.636, - 20.43, - 21.663, - 26.458, - 25.06, - 21.597, - 32.861, - 38.653, - 32.272, - 41.136, - 53.138000000000005, - 48.519, - 49.807, - 62.018, - 35.262, - 63.857, - 72.005, - 65.29899999999999, - 20.193, - 90.684, - 98.331, - 43.553, - 43.773, - 118.222, - 121.135, - 95.931, - 80.031, - 141.092, - 147.445, - 158.329, - 168.61900000000003, - 114.798, - 114.457, - 176.40900000000002, - 78.936, - 104.398, - 203.842, - 36.632, - 208.406, - 117.617, - 199.889, - 176.959, - 223.248, - 214.528, - 194.648, - 198.937, - 91.527, - 47.66, - 115.926, - 53.567, - 270.237, - 255.515, - 160.129, - 104.707, - 210.61900000000003, - 268.772, - 243.194, - 272.323, - 277.091, - 262.045, - 284.85400000000004, - 262.072, - 351.606, - 355.945, - 201.64, - 369.829, - 250.555, - 378.676, - 257.916, - 281.231, - 295.171, - 266.141, - 269.009, - 324.448, - 340.921, - 342.886, - 338.87800000000004, - 327.449, - 258.472, - 333.797, - 312.92, - 348.033, - 449.509, - 453.775, - 294.163, - 384.43, - 256.033, - 316.339, - 459.831, - 247.219, - 403.418, - 322.032, - 219.246, - 506.974, - 248.601, - 458.295, - 481.022, - 182.789, - 291.064, - 315.634, - 422.318, - 469.967, - 477.63, - 397.263, - 503.583, - 495.28, - 390.24300000000005, - 263.988, - 279.772, - 193.305, - 270.347, - 241.719, - 317.446, - 132.239, - 448.072, - 400.401, - 5.747000000000001, - 0.55, - 290.772, - 333.362, - 527.735, - 43.129, - 0.5670000000000001, - 365.497, - 116.604, - 171.34400000000002, - 183.186, - 495.814, - 485.035, - 562.22, - 384.275, - 368.9980000000001, - 477.427, - 268.453, - 509.385, - 425.384, - 502.4980000000001, - 554.964, - 513.294, - 677.36, - 685.304, - 484.429, - 205.367, - 439.918, - 407.761, - 155.94, - 212.375, - 265.656, - 715.457, - 714.345, - 702.443, - 717.885, - 724.1339999999999, - 727.547, - 706.307, - 539.1419999999999, - 227.768, - 250.484, - 751.05, - 414.5, - 508.559, - 772.691, - 755.316, - 750.174, - 242.071, - 732.078, - 634.743, - 614.004, - 796.904, - 581.974, - 767.571, - 322.538, - 181.804, - 378.153, - 591.482, - 541.7180000000001, - 358.956, - 150.275, - 757.942, - 692.962, - 274.316, - 0.457, - 204.205, - 610.2769999999999, - 448.986, - 611.918, - 549.619, - 512.523, - 391.256, - 429.805, - 453.93, - 100.253, - 398.87, - 190.613, - 0.4679999999999999, - 105.714, - 445.435, - 0.473, - 602.982, - 465.915, - 704.27, - 649.536, - 447.912, - 585.806, - 646.122, - 583.658, - 654.375, - 536.967, - 642.786, - 730.096, - 703.885, - 53.468, - 235.107, - 627.002, - 787.638, - 532.018, - 494.895, - 528.247, - 773.6439999999999, - 621.304, - 620.269, - 730.977, - 755.5310000000001, - 578.869, - 491.603, - 743.7, - 343.772, - 716.5360000000001, - 474.299, - 604.4630000000001, - 717.0210000000001, - 383.422, - 479.711, - 609.187, - 695.297, - 616.625, - 599.63, - 535.321, - 754.832, - 694.801, - 638.9540000000001, - 629.722, - 639.422, - 586.4, - 523.281, - 72.12, - 665.865, - 728.654, - 774.525, - 428.737, - 603.665, - 795.8910000000001, - 765.2760000000001, - 644.735, - 694.355, - 629.992, - 23.386, - 175.137, - 493.607, - 457.838, - 71.382, - 655.493, - 562.65, - 414.032, - 743.4580000000001, - 762.7819999999999, - 770.941, - 87.28200000000001, - 632.32, - 531.236, - 743.1, - 505.311, - 502.245, - 621.398, - 115.954, - 568.7719999999999, - 639.378, - 149.454, - 679.2589999999999, - 780.971, - 731.544, - 704.182, - 368.084, - 0.721, - 620.434, - 2.582, - 659.423, - 462.204, - 758.311, - 781.6210000000001, - 415.777, - 788.079, - 372.268, - 415.518, - 547.0419999999999, - 417.809, - 635.42, - 612.072, - 480.108, - 594.884, - 512.127, - 373.138, - 697.46, - 397.918, - 697.1410000000001, - 620.7040000000001, - 582.266, - 688.393, - 552.828, - 550.274, - 493.034, - 145.32, - 628.9019999999999, - 782.915, - 620.418, - 548.523, - 666.5419999999999, - 683.427, - 39.556, - 393.915, - 581.0269999999999, - 137.827, - 377.652, - 794.52, - 623.98, - 551.711, - 699.393, - 105.637, - 598.991, - 527.812, - 697.24, - 637.2919999999999, - 606.985, - 730.8610000000001, - 108.213, - 678.957, - 585.448, - 46.487, - 602.85, - 396.288, - 735.508, - 109.045, - 494.587, - 450.109, - 467.302, - 797.196, - 627.118, - 729.931, - 22.203000000000003, - 763.2660000000001, - 500.522, - 638.938, - 790.8810000000001, - 496.035, - 691.883, - 621.205, - 790.1489999999999, - 796.238, - 271.327, - 145.391, - 689.1089999999999, - 574.382, - 779.914, - 415.601, - 0.346, - 271.222, - 555.906, - 731.368, - 515.711, - 772.449, - 769.955, - 763.7339999999999, - 667.6160000000001, - 461.577, - 757.8710000000001, - 749.673, - 751.903, - 633.009, - 411.367, - 739.395, - 607.948, - 681.357, - 727.685, - 125.165, - 483.262, - 680.7289999999999, - 596.139, - 725.7189999999999, - 299.597, - 172.417, - 714.8739999999999, - 682.084, - 434.44, - 531.451, - 0.379, - 223.199, - 701.6610000000001, - 442.566, - 399.982, - 538.085, - 558.124, - 687.677, - 672.135, - 404.166, - 678.2739999999999, - 674.706, - 673.2810000000001, - 650.4169999999999, - 665.331, - 661.317, - 222.467, - 316.895, - 626.7330000000001, - 411.604, - 260.29400000000004, - 426.447, - 640.226, - 602.988, - 626.1709999999999, - 628.313, - 627.806, - 622.499, - 624.283, - 466.581, - 543.656, - 163.075, - 117.573, - 132.22799999999998, - 122.093, - 596.5409999999999, - 398.199, - 406.781, - 25.49, - 386.103, - 546.7280000000001, - 523.7819999999999, - 482.871, - 276.579, - 354.144, - 259.171, - 330.014, - 317.721, - 209.837, - 0.418, - 0.385, - 297.527, - 263.999, - 334.958, - 60.988, - 217.991, - 169.868, - 383.24, - 293.002, - 130.565, - 264.92400000000004, - 229.673, - 168.696, - 271.377, - 252.592, - 101.535, - 253.209, - 256.198, - 272.533, - 84.50200000000001, - 318.541, - 240.552, - 50.649, - 0.391, - 0.352, - 77.559, - 323.782, - 365.304, - 260.371, - 338.856, - 214.517, - 214.027, - 360.01300000000003, - 209.155, - 254.91, - 392.082, - 147.208, - 280.405, - 303.41200000000003, - 215.436, - 315.728, - 346.668, - 343.37, - 254.805, - 172.62099999999998, - 87.287, - 244.285, - 191.455, - 47.093, - 126.128, - 353.517, - 253.401, - 335.47, - 228.693, - 303.126, - 242.33, - 185.129, - 81.991, - 332.194, - 245.485, - 325.599, - 216.361, - 48.073, - 206.71, - 304.849, - 224.311, - 278.41200000000003, - 187.067, - 290.66200000000003, - 260.36, - 263.878, - 247.968, - 213.807, - 93.597, - 46.9, - 74.487, - 87.915, - 40.949, - 69.654, - 53.688, - 44.637, - 78.391, - 6.909, - 68.78399999999999, - 20.849, - 16.554000000000002, - 39.49, - 47.01, - 21.751, - 0.418, - 48.909, - 48.998000000000005, - 46.487, - 39.633, - 36.319, - 33.654, - 16.102999999999998, - 12.987, - 31.788, - 29.387, - 19.544, - 20.188, - 10.454, - 16.885, - 17.854, - 13.482, - 12.062, - 10.642, - 14.237, - 11.583, - 13.719, - 17.54, - 11.913, - 7.702000000000001, - 6.287000000000001, - 3.11, - 6.678, - 6.43, - 4.184, - -1.426, - 4.822, - 4.894, - -2.902, - -5.131, - -0.7490000000000001, - -2.698, - 0.969, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 1.668, - -0.21, - 4.685, - 3.947, - 2.752, - 6.7, - 7.096, - 8.929, - 13.279000000000002, - 15.371, - 7.454, - 13.075, - 17.149, - 17.578, - 18.393, - 28.54, - 27.031, - 13.961, - 0.693, - 30.384, - 32.278, - 41.725, - 37.833, - 52.328, - 57.388000000000005, - 58.445, - 66.752, - 59.067, - 55.78, - 65.706, - 84.414, - 37.376, - 28.099, - 75.23100000000001, - 14.237, - 39.985, - 64.952, - 84.006, - 61.467, - 38.741, - 55.153, - 57.09, - 56.87, - 72.918, - 32.971, - 64.016, - 68.712, - 36.445, - 0.5670000000000001, - 0.561, - 51.75, - 39.958, - 74.229, - 27.703000000000003, - 14.11, - 83.081, - 56.54, - 62.458, - 66.851, - 68.046, - 85.427, - 65.514, - 65.92699999999999, - 98.766, - 101.425, - 95.001, - 100.076, - 149.129, - 91.538, - 159.755, - 96.382, - 115.271, - 154.134, - 148.838, - 8.494, - 104.844, - 164.088, - 155.477, - 154.183, - 160.65200000000002, - 166.708, - 130.907, - 203.545, - 192.495, - 235.448, - 206.848, - 166.928, - 153.082, - 160.118, - 153.275, - 168.65200000000002, - 130.472, - 226.992, - 130.07, - 138.493, - 197.296, - 174.95, - 56.749, - 158.52700000000002, - 20.76, - 164.75400000000002, - 46.228, - 116.995, - 147.004, - 101.211, - 175.203, - 113.609, - 120.49, - 85.81200000000001, - 15.2, - 139.22, - 172.78599999999997, - 239.115, - 225.093, - 287.463, - 289.561, - 143.822, - 213.432, - 273.80400000000003, - 275.495, - 258.89, - 291.934, - 283.91200000000003, - 284.121, - 28.226, - 267.842, - 255.598, - 249.322, - 97.99, - 59.221, - 0.5720000000000001, - 115.635, - 335.432, - 366.218, - 89.258, - 49.851000000000006, - 329.932, - 357.569, - 117.396, - 263.774, - 213.928, - 210.03, - 210.878, - 59.353, - 321.795, - 296.36, - 150.864, - 307.31, - 190.045, - 315.337, - 308.411, - 213.598, - 0.561, - 116.317, - 355.31199999999995, - 228.996, - 179.778, - 367.214, - 388.828, - 420.853, - 396.365, - 233.995, - 192.451, - 272.769, - 477.206, - 337.35900000000004, - 340.50199999999995, - 422.753, - 446.068, - 355.405, - 274.933, - 540.887, - 507.838, - 518.309, - 400.059, - 215.056, - 430.174, - 407.668, - 428.137, - 434.73800000000006, - 390.32, - 346.36, - 586.174, - 402.052, - 555.7959999999999, - 550.549, - 500.026, - 590.309, - 395.171, - 524.509, - 511.263, - 658.163, - 434.462, - 571.007, - 510.806, - 466.454, - 228.864, - 680.1289999999999, - 684.2860000000001, - 665.6610000000001, - 250.153, - 416.388, - 364.687, - 662.5889999999999, - 375.296, - 585.998, - 309.986, - 565.524, - 518.106, - 213.405, - 551.909, - 517.698, - 325.076, - 288.306, - 587.65, - 549.305, - 480.691, - 463.652, - 463.404, - 442.126, - 473.931, - 484.149, - 516.7130000000001, - 517.197, - 36.71, - 19.648, - 399.966, - 496.112, - 488.657, - 529.783, - 388.773, - 587.375, - 141.95600000000002, - 527.905, - 669.8560000000001, - 670.4839999999999, - 683.322, - 184.755, - 426.601, - 623.424, - 630.432, - 643.1990000000001, - 639.015, - 323.969, - 187.375, - 26.673, - 563.944, - 154.569, - 364.36800000000005, - 654.331, - 716.487, - 693.188, - 689.709, - 416.174, - 357.249, - 424.487, - 228.225, - 605.823, - 532.668, - 419.659, - 398.30300000000005, - 276.838, - 233.973, - 317.258, - 245.545, - 460.382, - 183.83, - 223.518, - 472.114, - 497.851, - 414.06, - 536.086, - 621.431, - 486.086, - 552.9490000000001, - 454.943, - 419.251, - 371.767, - 274.768, - 609.429, - 631.153, - 614.885, - 545.181, - 198.74400000000003, - 275.021, - 500.241, - 568.309, - 580.63, - 351.342, - 563.299, - 252.196, - 520.143, - 331.033, - 21.779, - 396.206, - 532.937, - 530.4209999999999, - 298.876, - 304.431, - 508.202, - 490.089, - 68.184, - 505.702, - 304.822, - 553.88, - 183.907, - 358.934, - 566.091, - 548.908, - 194.318, - 530.84, - 553.0319999999999, - 575.725, - 339.649, - 175.97400000000002, - 396.371, - 575.742, - 539.687, - 225.572, - 558.851, - 599.861, - 433.714, - 54.597, - 631.313, - 512.314, - 450.307, - 433.615, - 440.436, - 586.631, - 671.789, - 525.054, - 727.3710000000001, - 720.5880000000001, - 550.659, - 225.329, - 618.095, - 524.729, - 731.605, - 470.903, - 384.237, - 768.3919999999999, - 491.542, - 683.179, - 570.115, - 691.8560000000001, - 525.538, - 636.015, - 341.537, - 48.722, - 648.385, - 676.27, - 288.66900000000004, - 624.365, - 131.077, - 499.756, - 358.69199999999995, - 705.03, - 579.205, - 742.7810000000001, - 715.0939999999999, - 690.821, - 800, - 748.77, - 587.182, - 554.2819999999999, - 761.961, - 800, - 800, - 776.688, - 336.329, - 535.855, - 800, - 504.419, - 764.813, - 775.1080000000001, - 620.7869999999999, - 800, - 533.46, - 620.0319999999999, - 442.3130000000001, - 796.909, - 446.712, - 800, - 626.3969999999999, - 730.421, - 626.094, - 611.075, - 457.431, - 454.21, - 635.91, - 350.522, - 32.9, - 480.328, - 302.438, - 642.1419999999999, - 624.982, - 709.2860000000001, - 695.743, - 800, - 793.27, - 769.873, - 506.897, - 316.768, - 501.81, - 718.9860000000001, - 703.252, - 721.4639999999999, - 713.58, - 684.627, - 394.95, - 376.386, - 595.693, - 302.421, - 124.163, - 675.0260000000001, - 347.389, - 402.818, - 710.09, - 781.137, - 761.1189999999999, - 263.113, - 21.366, - 347.582, - 445.104, - 800, - 795.395, - 800, - 417.44, - 342.886, - 446.288, - 655.795, - 16.185, - 264.555, - 467.456, - 471.139, - 582.871, - 580.471, - 426.199, - 800, - 624.492, - 800, - 800, - 181.953, - 368.591, - 610.145, - 629.788, - 598.49, - 434.628, - 550.78, - 595.104, - 664.643, - 326.59, - 785.431, - 445.848, - 781.797, - 587.248, - 696.288, - 572.9169999999999, - 97.742, - 572.516, - 480.955, - 745.9680000000001, - 370.55, - 332.53, - 743.727, - 575.18, - 315.629, - 743.8430000000001, - 743.4580000000001, - 737.066, - 700.9010000000001, - 134.535, - 405.289, - 524.943, - 719.674, - 475.279, - 472.923, - 708.498, - 394.361, - 628.781, - 412.947, - 664.703, - 584.203, - 417.082, - 684.567, - 477.966, - 584.98, - 606.55, - 695.3739999999999, - 533.124, - 585.58, - 685.563, - 511.78, - 598.798, - 544.466, - 489.318, - 477.454, - 321.652, - 495.6880000000001, - 657.293, - 507.745, - 651.248, - 644.851, - 319.906, - 438.289, - 640.865, - 396.354, - 432.321, - 348.62300000000005, - 630.6080000000001, - 522.962, - 0.368, - 69.048, - 568.139, - 461.307, - 607.7, - 196.382, - 127.279, - 591.393, - 597.741, - 403.407, - 588.404, - 583.9830000000001, - 582.106, - 54.888000000000005, - 455.911, - 402.504, - 565.375, - 432.954, - 562.32, - 559.76, - 141.405, - 219.708, - 432.161, - 296.244, - 542.247, - 537.76, - 395.875, - 378.297, - 525.857, - 390.155, - 520.099, - 247.687, - 356.22, - 425.918, - 325.588, - 486.334, - 352.49800000000005, - 324.647, - 482.871, - 378.886, - 239.264, - 395.082, - 319.98400000000004, - 435.778, - 346.93800000000005, - 454.48, - 190.728, - 200.17, - 299.316, - 405.543, - 199.955, - 433.009, - 255.136, - 276.601, - 376.348, - 256.633, - 31.193, - 257.42, - 365.254, - 354.849, - 352.735, - 300.214, - 76.805, - 332.585, - 234.826, - 339.792, - 342.19800000000004, - 352.163, - 175.638, - 146.49200000000002, - 0.374, - 252.774, - 311.88, - 311.599, - 103.991, - 252.333, - 297.285, - 293.007, - 288.906, - 280.147, - 274.531, - 251.431, - 251.139, - 267.187, - 241.152, - 60.476000000000006, - 245.143, - 265.166, - 273.391, - 231.017, - 261.472, - 252.333, - 223.403, - 124.289, - 143.393, - 225.952, - 217.198, - 144.461, - 62.49100000000001, - 118.387, - 71.146, - 195.925, - 161.627, - 150.03799999999998, - 143.28799999999998, - 137.408, - 152.813, - 82.167, - 29.156, - 26.481, - 24.075, - 29.899, - 23.067, - 26.348000000000003, - 23.073, - 25.363000000000003, - 22.572, - 23.838, - 17.413, - 2.45, - 20.023, - 19.335, - 19.076, - 16.279, - 13.708, - 14.55, - 15.497, - 8.748, - 15.921, - 6.16, - 15.91, - 8.913, - 11.109000000000002, - 7.652, - 8.115, - 8.77, - 7.718, - 2.807, - 9.271, - 5.422000000000001, - 7.68, - 2.174, - 3.867, - 5.56, - 3.1210000000000004, - 3.661, - 0.7809999999999999, - 3.275, - 4.52, - -4.977, - -7.152, - null, - null, - 0.479, - -4.409999999999999, - -9.299, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -3.997, - null, - null, - -2.748, - -1.066, - 0.616, - 0.71, - 1.822, - 0.115, - 4.9430000000000005, - 9.529, - 2.516, - 7.68, - 11.489, - 12.380999999999998, - 10.339, - 11.682, - 12.265999999999998, - 11.963, - 23.1, - 38.559, - 60.603, - 40.723, - 63.168, - 41.604, - 32.046, - 16.857, - 10.708, - 15.321, - 15.91, - 17.71, - 18.745, - 25.633000000000003, - 23.161, - 28.628, - 25.556, - 27.725, - 26.365, - 16.769000000000002, - 40.536, - 46.603, - 71.465, - 68.872, - 49.625, - 89.633, - 106.81, - 150.654, - 118.641, - 222.703, - 176.706, - 194.874, - 306.04900000000004, - 194.609, - 264.48900000000003, - 274.922, - 183.687, - 132.05200000000002, - 69.747, - 309.04400000000004, - 177.614, - 142.369, - 303.203, - 111.368, - 370.517, - 378.759, - 380.554, - 349.76800000000003, - 35.669000000000004, - 192.523, - 241.284, - 250.847, - 312.904, - 285.388, - 307.222, - 309.639, - 320.897, - 348.601, - 342.19800000000004, - 251.876, - 211.291, - 438.135, - 208.912, - 260.707, - 408.741, - 301.078, - 342.969, - 377.829, - 352.041, - 286.456, - 434.27, - 250.957, - 0.611, - 38.543, - 239.80900000000003, - 308.83, - 498.584, - 304.893, - 515.656, - 185.669, - 434, - 413.856, - 373.843, - 528.55, - 185.036, - 495.936, - 563.6080000000001, - 400.081, - 582.8330000000001, - 591.8340000000001, - 594.405, - 485.954, - 270.308, - 80.84100000000001, - 121.63, - 264.39, - 243.057, - 146.096, - 122.737, - 0.556, - 231.325, - 473.408, - 400.847, - 181.055, - 432.068, - 586.56, - 37.354, - 170.991, - 423.033, - 0.556, - 281.303, - 318.712, - 512.931, - 313.317, - 287.904, - 363.256, - 283.676, - 9.436, - 432.492, - 461.312, - 478.869, - 400.324, - 87.414, - 428.963, - 745.825, - 92.98, - 472.896, - 694.586, - 748.2310000000001, - 713.09, - 437.523, - 764.94, - 332.492, - 277.565, - 489.478, - 670.676, - 0.539, - 520.781, - 604.425, - 459.595, - 242.446, - 294.92900000000003, - 506.919, - 735.304, - 743.893, - 734.935, - 429.073, - 686.868, - 449.244, - 496.354, - 749.7230000000001, - 343.789, - 637.33, - 694.1289999999999, - 493.321, - 542.346, - 652.674, - 297.01, - 779.3910000000001, - 522.323, - 777.525, - 710.893, - 800, - 701.8639999999999, - 800, - 787.699, - 772.801, - 209.441, - 800, - 441.564, - 530.724, - 800, - 719.74, - 780.085, - 800, - 800, - 800, - 366.344, - 173.46900000000002, - 117.848, - 392.154, - 244.229, - 139.776, - 302.818, - 287.271, - 276.992, - 487.24300000000005, - 345.826, - 189.864, - 171.68, - 183.274, - 669.6360000000001, - 481.616, - 322.54900000000004, - 327.664, - 342.63800000000003, - 760.75, - 727.63, - 464.263, - 342.20300000000003, - 469.301, - 245.286, - 337.93699999999995, - 754.166, - 549.674, - 462.309, - 800, - 472.444, - 365.133, - 252.724, - 225.263, - 274.349, - 214.858, - 223.105, - 224.834, - 206.639, - 246.69, - 255.95, - 316.405, - 217.974, - 263.416, - 152.29, - 255.928, - 247.285, - 163.333, - 117.617, - 149.746, - 111.032, - 202.097, - 197.973, - 152.84, - 186.252, - 199.74, - 134.722, - 194.565, - 197.71400000000003, - 204.145, - 195.788, - 191.268, - 199.79, - 204.172, - 111.979, - 156.143, - 207.261, - 120.424, - 127.747, - 205.235, - 142.116, - 159.92600000000002, - 170.49599999999998, - 145.232, - 234.617, - 157.013, - 87.98100000000001, - 201.458, - 244.984, - 259.36400000000003, - 293.249, - 194.967, - 315.832, - 325.505, - 304.056, - 186.935, - 355.218, - 116.609, - 325.687, - 391.05300000000005, - 342.644, - 341.185, - 382.062, - 395.914, - 280.323, - 396.519, - 245.22, - 386.549, - 331.86400000000003, - 300.291, - 268.828, - 168.97099999999998, - 329.06199999999995, - 173.19299999999998, - 347.25699999999995, - 271.795, - 333.004, - 252.493, - 315.183, - 262.194, - 160.316, - 293.404, - 205.295, - 326.463, - 194.455, - 105.819, - 100.286, - 121.19, - 255.246, - 334.584, - 245.402, - 187.051, - 189.291, - 245.171, - 324.531, - 334.523, - 337.414, - 341.141, - 343.18300000000005, - 151.491, - 209.551, - 358.461, - 356.809, - 352.091, - 352.994, - 347.092, - 347.852, - 381.253, - 379.249, - 362.122, - 347.896, - 364.638, - 92.385, - 372.037, - 303.159, - 173.838, - 165.359, - 353.577, - 177.22299999999998, - 79.707, - 370.622, - 373.562, - 228.539, - 390.364, - 203.385, - 238.851, - 340.486, - 461.461, - 0.506, - 279.926, - 456.677, - 268.42, - 415.26, - 514.406, - 251.998, - 612.8919999999999, - 648.126, - 632.04, - 379.249, - 64.815, - 40.932, - 800, - 800, - 614.643, - 382.271, - 2.648, - 72.318, - 800, - 694.702, - 693.948, - 800, - 800, - 221.597, - 800, - 637.259, - 800, - 663.564, - 705.6410000000001, - 522.433, - 706.819, - 620.214, - 754.815, - 800, - 580.4209999999999, - 735.2819999999999, - 800, - 800, - 571.739, - 800, - 800, - 800, - 87.87700000000001, - 411.318, - 800, - 800, - 800, - 659.908, - 800, - 800, - 368.304, - 375.351, - 800, - 647.422, - 673.181, - 627.09, - 657.172, - 451.854, - 412.601, - 734.682, - 630.8009999999999, - 432.651, - 561.719, - 512.3530000000001, - 656.2139999999999, - 750.0419999999999, - 468.59, - 485.894, - 544.3330000000001, - 499.2, - 517.511, - 351.832, - 727.685, - 740.727, - 572.064, - 559.556, - 456.291, - 565.826, - 561.78, - 438.878, - 529.81, - 657.832, - 597.681, - 619.245, - 585.5740000000001, - 610.2330000000001, - 705.977, - 628.797, - 513.3330000000001, - 615.568, - 728.7689999999999, - 773.181, - 676.209, - 715.171, - 506.352, - 713.679, - 607.645, - 425.235, - 583.339, - 644.482, - 771.992, - 508.372, - 800, - 454.59, - 800, - 613.387, - 800, - 480.009, - 800, - 601.556, - 120.232, - 45.21, - 588.388, - 566.977, - 792.8960000000001, - 403.875, - 785.888, - 776.655, - 770.1419999999999, - 767.747, - 766.3710000000001, - 762.9739999999999, - 764.6039999999999, - 760.6619999999999, - 754.8810000000001, - 753.956, - 749.6460000000001, - 738.365, - 739.2239999999999, - 744.2560000000001, - 574.4590000000001, - 474.712, - 323.199, - 507.332, - 410.321, - 560.607, - 507.959, - 705.817, - 680.2669999999999, - 530.851, - 415.689, - 521.86, - 554.612, - 577.118, - 426.799, - 390.1, - 444.961, - 480.119, - 570.082, - 601.2919999999999, - 681.5939999999999, - 680.2560000000001, - 700.2510000000001, - 688.784, - 685.684, - 689.466, - 697.0139999999999, - 678.813, - 659.842, - 666.8610000000001, - 622.268, - 366.284, - 573.1709999999999, - 577.112, - 590.391, - 582.3430000000001, - 558.493, - 559.242, - 282.018, - 121.096, - 108.109, - 97.17, - 99.559, - 103.451, - 109.221, - 118.74, - 122.687, - 130.934, - 137.656, - 144.395, - 160.608, - 185.267, - 180.229, - 170.512, - 153.622, - 146.905, - 150.44, - 160.151, - 157.327, - 179.84400000000002, - 197.891, - 182.019, - 173.672, - 173.166, - 175.01, - 191.945, - 225.44, - 235.124, - 214.93, - 195.452, - 258.945, - 214.754, - 235.377, - 216.697, - 262.265, - 260.66900000000004, - 309.672, - 267.837, - 229.062, - 149.917, - 130.929, - 104.751, - 93.993, - 84.226, - 75.528, - 71.217, - 70.045, - 78.171, - 101.91, - 114.594, - 152.047, - 327.019, - 341.945, - 346.404, - 349.514, - 329.546, - 343.403, - 325.79200000000003, - 307.327, - 334.68300000000005, - 331.622, - 327.074, - 319.642, - 315.546, - 304.045, - 305.697, - 302.064, - 300.819, - 294.802, - 291.185, - 287.28700000000003, - 284.573, - 282.497, - 279.007, - 278.335, - 273.887, - 227.834, - 164.011, - 93.784, - 80.863, - 79.013, - 78.016, - 77.851, - 75.792, - 70.259, - 67.551, - 63.697, - 62.453, - 61.787, - 64.655, - 64.704, - 65.805, - 66.565, - 69.164, - 69.786, - 69.51100000000001, - 66.384, - 66.21300000000001, - 65.756, - 65.304, - 67.028, - 67.529, - 64.578, - 61.016000000000005, - 58.538, - 58.373000000000005, - 55.989, - 53.914, - 54.927, - 55.00899999999999, - 55.235, - 53.363, - 49.113, - 44.857, - 41.268, - 38.295, - 34.755, - 30.45, - 27.499, - 24.57, - 23.546, - 20.854, - 19.984, - 17.419, - 15.046, - 13.521, - 12.227, - 10.333, - 7.542000000000001, - 5.989, - 3.749, - 0.947, - -0.848, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -1.724, - -1.234, - -0.05, - 1.2, - 3.072, - 3.963, - 5.263, - 6.122000000000001, - 7.685, - 9.425, - 11.253, - 12.475, - 14.611, - 17.022000000000002, - 18.718, - 21.278, - 23.199, - 25.556, - 26.959, - 29.112, - 31.011, - 33.604, - 35.861999999999995, - 37.926, - 40.448, - 42.782, - 45.573, - 55.153, - 69.654, - 81.36399999999999, - 87.095, - 54.211000000000006, - 99.482, - 100.423, - 99.24, - 103.517, - 110.74, - 115.26, - 118.409, - 121.184, - 127.526, - 133.351, - 138.135, - 142.82, - 146.86700000000002, - 151.244, - 157.178, - 163.488, - 169.808, - 173.16, - 180.626, - 187.056, - 193.31, - 193.095, - 199.796, - 206.418, - 210.124, - 215.723, - 217.099, - 225.489, - 228.864, - 235.481, - 240.778, - 246.008, - 247.39, - 254.128, - 259.055, - 262.744, - 268.85, - 274.41, - 278.297, - 285.267, - 287.827, - 295.215, - 299.856, - 302.23400000000004, - 309.892, - 314.621, - 317.44, - 324.019, - 330.642, - 331.875, - 339.731, - 342.62699999999995, - 346.481, - 350.742, - 356.782, - 364.467, - 369.158, - 371.195, - 377.24, - 379.067, - 384.787, - 390.557, - 394.394, - 399.459, - 399.878, - 410.041, - 415.084, - 417.154, - 421.751, - 426.909, - 432.326, - 436.076, - 439.94, - 446.211, - 451.937, - 456.407, - 461.61, - 463.669, - 468.612, - 471.706, - 478.296, - 480.086, - 481.941, - 488.652, - 493.249, - 499.69, - 504.92, - 510.327, - 512.226, - 518.3430000000001, - 519.24, - 519.95, - 524.58, - 527.41, - 531.423, - 537.876, - 541.961, - 543.232, - 549.547, - 553.748, - 556.721, - 559.457, - 561.549, - 565.678, - 571.018, - 575.279, - 579.172, - 585.007, - 588.85, - 592.2909999999999, - 592.484, - 599.475, - 602.933, - 607.5409999999999, - 611.576, - 615.832, - 614.643, - 623.391, - 624.674, - 629.8430000000001, - 631.236, - 637.975, - 640.595, - 642.654, - 644.719, - 646.943, - 650.764, - 653.23, - 657.7, - 660.431, - 664.18, - 669.058, - 667.434, - 668.821, - 675.0039999999999, - 678.252, - 681.1419999999999, - 684.534, - 688.674, - 696.695, - 697.686, - 701.341, - 702.707, - 705.426, - 707.293, - 708.262, - 715.21, - 718.7719999999999, - 718.799, - 722.6310000000001, - 725.9010000000001, - 723.291, - 729.0060000000001, - 734.077, - 735.04, - 736.5319999999999, - 745.318, - 741.426, - 738.029, - 755.674, - 753.345, - 754.8480000000001, - 755.977, - 760.513, - 759.913, - 760.2330000000001, - 764.301, - 764.6310000000001, - 772.047, - 774.007, - 775.565, - 775.8510000000001, - 779.59, - 781.5110000000001, - 784.148, - 788.178, - 791.558, - 793.81, - 794.3, - 796.497, - 786.967, - 782.7439999999999, - 733.3660000000001, - 790.253, - 783.405, - 773.6110000000001, - 741.7289999999999, - 730.6360000000001, - 744.2610000000001, - 735.436, - 725.538, - 714.428, - 706.302, - 687.826, - 671.3539999999999, - 649.106, - 628.4169999999999, - 630.014, - 630.129, - 608.818, - 606.153, - 612.975, - 617.219, - 616.003, - 620.891, - 620.082, - 615.8919999999999, - 584.633, - 586.362, - 572.5930000000001, - 555.085, - 545.561, - 554.111, - 573.8480000000001, - 594.306, - 596.937, - 597.169, - 593.364, - 613.4590000000001, - 608.592, - 602.993, - 615.16, - 602.371, - 587.732, - 582.117, - 594.493, - 613.58, - 624.756, - 641.614, - 646.827, - 637.804, - 630.179, - 624.442, - 599.239, - 588.977, - 581.831, - 576.033, - 574.2, - 517.9630000000001, - 499.189, - 507.425, - 484.209, - 473.022, - 474.955, - 494.647, - 497.119, - 514.406, - 498.055, - 466.174, - 441.8730000000001, - 432.734, - 410.426, - 409.655, - 407.057, - 409.782, - 400.412, - 421.712, - 450.23, - 458.48800000000006, - 452.316, - 439.483, - 446.1830000000001, - 440.832, - 451.667, - 448.776, - 456.104, - 465.205, - 476.05, - 477.019, - 474.305, - 461.048, - 458.708, - 453.186, - 466.796, - 453.572, - 447.697, - 411.048, - 394.009, - 409.496, - 425.461, - 440.15, - 440.882, - 453.643, - 433.653, - 427.443, - 428.875, - 469.102, - 476.369, - 451.821, - 377.685, - 329.045, - 299.696, - 298.232, - 321.949, - 320.683, - 341.686, - 368.233, - 332.861, - 304.992, - 301.596, - 306.099, - 281.193, - 227.675, - 219.846, - 226.425, - 229.662, - 224.052, - 212.843, - 195.391, - 182.591, - 180.169, - 182.988, - 189.495, - 191.526, - 196.729, - 191.488, - 191.807, - 196.195, - 203.936, - 198.282, - 194.527, - 193.69, - 199.906, - 211.456, - 215.293, - 216.763, - 227.603, - 239.924, - 241.956, - 234.259, - 247.004, - 236.924, - 238.553, - 243.398, - 240.122, - 215.888, - 200.385, - 181.639, - 168.773, - 160.878, - 154.558, - 146.641, - 139.649, - 133.329, - 127.587, - 118.228, - 111.5, - 110.707, - 108.665, - 105.252, - 102.224, - 105.108, - 105.67, - 103.638, - 105.571, - 103.941, - 101.701, - 108.065, - 113.625, - 116.064, - 119.257, - 118.498, - 119.197, - 120.38, - 123.673, - 123.717, - 124.834, - 117.424, - 123.227, - 135.977, - 153.875, - 136.792, - 138.355, - 128.446, - 124.135, - 121.135, - 124.344, - 135.05200000000002, - 147.357, - 153.363, - 137.062, - 155.14700000000002, - 169.62599999999998, - 134.41899999999998, - 107.514, - 95.38, - 90.662, - 87.965, - 82.26100000000001, - 79.22800000000001, - 74.796, - 68.294, - 62.337, - 56.25899999999999, - 50.891000000000005, - 47.985, - 46.085, - 44.246, - 44.081, - 42.975, - 42.815, - 42.253, - 40.53, - 39.512, - 39.126, - 37.216, - 35.652, - 33.869, - 30.962, - 28.495, - 25.6, - 23.007, - 19.802, - 17.573, - 16.692, - 13.906, - 12.618, - 12.029000000000002, - 11.324000000000002, - 10.603, - 9.882, - 9.194, - 9.072, - 6.722, - 5.307, - 4.652, - 3.848, - 2.8510000000000004, - 2.741, - 2.196, - 0.836, - -0.204, - -1.294, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -2.048, - -1.509, - -0.92, - -0.8320000000000001, - -0.193, - 0.765, - 2.813, - 3.518, - 4.475, - 5.555, - 5.874, - 7.124, - 9.766, - 11.363, - 14.831, - 18.415, - 20.755, - 21.845, - 24.372, - 26.932, - 30.092, - 34.926, - 38.774, - 41.708, - 43.993, - 45.893, - 56.347, - 68.542, - 82.652, - 83.73100000000001, - 60.493, - 101.486, - 101.838, - 105.45, - 104.921, - 101.178, - 98.194, - 111.621, - 122.77, - 129.563, - 133.241, - 129.613, - 136.858, - 154.035, - 165.101, - 174.741, - 186.412, - 187.205, - 189.181, - 188.724, - 192.457, - 189.445, - 183.923, - 180.075, - 179.106, - 169.72, - 172.313, - 178.53400000000002, - 174.201, - 154.72299999999998, - 169.951, - 194.956, - 227.719, - 252.427, - 236.054, - 227.477, - 251.761, - 225.032, - 180.747, - 181.853, - 244.956, - 247.566, - 253.699, - 277.768, - 256.677, - 225.665, - 242.611, - 249.052, - 250.324, - 237.788, - 225.61, - 266.813, - 308.048, - 259.342, - 289.533, - 316.35, - 258.428, - 241.031, - 305.703, - 326.535, - 343.673, - 278.908, - 266.185, - 254.249, - 317.335, - 293.558, - 289.78700000000003, - 238.647, - 296.536, - 333.059, - 278.809, - 232.228, - 266.741, - 311.736, - 375.687, - 357.844, - 310.228, - 368.574, - 300.10900000000004, - 273.518, - 332.96, - 394.785, - 392.798, - 323.80400000000003, - 474.619, - 447.351, - 481.627, - 478.588, - 516.311, - 518.766, - 523.991, - 521.96, - 513.894, - 524.266, - 536.494, - 533.758, - 526.1709999999999, - 530.955, - 526.865, - 545.9580000000001, - 558.736, - 552.085, - 551.133, - 558.802, - 549.635, - 585.161, - 601.248, - 583.4159999999999, - 557.37, - 588.2330000000001, - 594.5369999999999, - 580.14, - 565.359, - 612.975, - 569.322, - 489.28, - 398.353, - 391.086, - 400.395, - 461.593, - 477.11300000000006, - 420.666, - 325.726, - 419.659, - 474.861, - 308.428, - 557.26, - 662.633, - 668.7660000000001, - 672.163, - 710.447, - 701.6439999999999, - 708.025, - 703.5, - 699.6460000000001, - 703.015, - 720.919, - 720.842, - 713.2719999999999, - 716.927, - 712.919, - 715.4739999999999, - 715.584, - 722.5319999999999, - 730.68, - 745.39, - 750.1080000000001, - 746.596, - 687.4789999999999, - 721.7439999999999, - 712.457, - 728.202, - 727.0239999999999, - 749.1389999999999, - 775.18, - 757.0060000000001, - 771.684, - 772.488, - 590.909, - 478.225, - 745.17, - 691.173, - 789.664, - 762.33, - 509.859, - 753.367, - 487.595, - 521.519, - 584.82, - 521.602, - 701.6110000000001, - 698.2919999999999, - 755.96, - 753.4830000000001, - 317.743, - 684.148, - 693.32, - 782.8380000000001, - 720.451, - 545.754, - 769.5310000000001, - 523.011, - 617.654, - 597.559, - 362.73800000000006, - 746.095, - 748.567, - 767.2239999999999, - 701.98, - 581.864, - 730.173, - 699.635, - 728.654, - 586.571, - 559.451, - 632.535, - 673.1210000000001, - 501.777, - 787.908, - 544.1519999999999, - 743.21, - 539.637, - 657.832, - 679.628, - 716.547, - 740.3969999999999, - 556.115, - 389.027, - 621.354, - 701.633, - 693.188, - 601.1659999999999, - 281.765, - 389.379, - 497.191, - 654.981, - 703.56, - 577.993, - 346.431, - 630.206, - 664.8960000000001, - 625.461, - 525.246, - 600.026, - 436.577, - 547.5319999999999, - 513.492, - 214.682, - 423.71, - 608.895, - 371.685, - 272.527, - 229.624, - 353.176, - 501.942, - 501.491, - 399.151, - 573.193, - 622.378, - 634.7040000000001, - 623.611, - 607.695, - 346.338, - 589.268, - 585.932, - 590.948, - 583.279, - 570.539, - 572.279, - 573.215, - 567.368, - 565.039, - 565.502, - 562.419, - 516.465, - 559.677, - 561.697, - 388.11300000000006, - 125.28, - 104.624, - 124.95, - 413.382, - 260.784, - 202.845, - 211.687, - 233.076, - 137.998, - 250.159, - 346.547, - 379.348, - 368.348, - 130.582, - 166.114, - 110.746, - 125.038, - 131.87, - 130.417, - 284.358, - 177.03599999999997, - 151.689, - 163.565, - 181.039, - 302.476, - 355.031, - 420.049, - 289.82, - 120.711, - 95.001, - 87.656, - 93.195, - 84.78299999999999, - 86.164, - 91.642, - 102.581, - 113.339, - 119.351, - 133.918, - 170.30900000000003, - 143.05200000000002, - 112.139, - 103.264, - 103.093, - 105.042, - 104.222, - 104.503, - 100.671, - 97.401, - 98.64, - 97.456, - 88.311, - 86.79799999999999, - 87.833, - 92.958, - 94.411, - 96.575, - 102.758, - 103.06, - 99.262, - 97.863, - 94.45, - 133.357, - 208.698, - 224.014, - 286.362, - 175.054, - 78.985, - 70.342, - 71.34899999999999, - 91.494, - 117.952, - 55.615, - 49.911, - 48.32, - 47.621, - 52.24, - 67.749, - 141.30100000000002, - 150.236, - 109.816, - 65.932, - 59.474, - 59.276, - 57.426, - 54.949, - 49.003, - 45.7, - 41.38399999999999, - 37.513000000000005, - 35.151, - 30.824, - 29.272, - 27.482, - 26.007, - 24.84, - 23.331, - 19.918, - 17.066, - 17.408, - 19.092, - 19.054, - 18.52, - 18.503, - 17.066, - 15.712, - 14.154000000000002, - 12.144, - 10.284, - 8.709, - 8.34, - 8.252, - 6.077999999999999, - 5.114, - 4.74, - 4.938, - 4.999, - 5.362, - 5.676, - 5.757999999999999, - 5.604, - 4.756, - 4.531000000000001, - 3.248, - 2.725, - 1.348, - 0.0819999999999999, - -1.663, - -1.3769999999999998, - -1.558, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null - ], + "y": { + "bdata": "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", + "dtype": "f8" + }, "yaxis": "y" }, { @@ -60535,865 +31302,10 @@ "2010-03-07T14:36:00-07:00" ], "xaxis": "x", - "y": [ - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 798.418, - 800, - 799.8660000000001, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 793.485, - 797.053, - 796.1, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 792.362, - 800, - 795.175, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 798.132, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 797.5980000000001, - 795.23, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 793.678, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 797.878, - 800, - 800, - 800, - 790.342, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 795.258, - 800, - 800, - 800, - 800, - 796.909, - 791.784, - 794.8610000000001, - 800, - 800, - 800, - 800, - 800 - ], + "y": { + "bdata": "AAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlA001iEFjziEAAAAAAAACJQLFyaJHt/ohAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUB7FK5H4cuIQIGVQ4ts6IhAzczMzMzgiEAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQDeJQWDlwohAAAAAAAAAiUBmZmZmZtmIQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAkxgEVg7xiEAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQBFYObTI7IhApHA9CtfZiEAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAgZVDi2zNiEAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAGy/dJAbviEAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUDb+X5qvLKIQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUDy0k1iENqIQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAg8DKoUXniECDwMqhRb6IQNrO91Pj1ohAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQA==", + "dtype": "f8" + }, "yaxis": "y" } ], @@ -61483,7 +31395,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61519,7 +31431,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -61543,7 +31455,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61579,64 +31491,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "type": "heatmap" } ], - "heatmapgl": [ - { - "colorbar": { - "outlinewidth": 0, - "ticks": "" - }, - "colorscale": [ - [ - 0, - "#0d0887" - ], - [ - 0.1111111111111111, - "#46039f" - ], - [ - 0.2222222222222222, - "#7201a8" - ], - [ - 0.3333333333333333, - "#9c179e" - ], - [ - 0.4444444444444444, - "#bd3786" - ], - [ - 0.5555555555555556, - "#d8576b" - ], - [ - 0.6666666666666666, - "#ed7953" - ], - [ - 0.7777777777777778, - "#fb9f3a" - ], - [ - 0.8888888888888888, - "#fdca26" - ], - [ - 1, - "#f0f921" - ] - ], - "type": "heatmapgl" - } - ], "histogram": [ { "marker": { @@ -61657,7 +31518,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61693,7 +31554,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -61708,7 +31569,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61744,7 +31605,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -61837,6 +31698,17 @@ "type": "scattergl" } ], + "scattermap": [ + { + "marker": { + "colorbar": { + "outlinewidth": 0, + "ticks": "" + } + }, + "type": "scattermap" + } + ], "scattermapbox": [ { "marker": { @@ -61889,7 +31761,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -61925,7 +31797,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -62016,7 +31888,7 @@ ], "sequential": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -62052,13 +31924,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "sequentialminus": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -62094,7 +31966,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ] @@ -62226,8 +32098,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "datetime" @@ -62236,42 +32108,15 @@ "yaxis": { "anchor": "x", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "ac_power" } } } - }, - "text/html": [ - "
" - ] + } }, "metadata": {}, "output_type": "display_data" @@ -62287,10 +32132,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:15.475327Z", - "iopub.status.busy": "2026-02-04T19:31:15.474329Z", - "iopub.status.idle": "2026-02-04T19:31:15.907718Z", - "shell.execute_reply": "2026-02-04T19:31:15.907718Z" + "iopub.execute_input": "2026-03-20T15:45:33.822870Z", + "iopub.status.busy": "2026-03-20T15:45:33.822100Z", + "iopub.status.idle": "2026-03-20T15:45:34.424732Z", + "shell.execute_reply": "2026-03-20T15:45:34.423481Z" } }, "outputs": [ @@ -76360,14053 +46205,10 @@ "2010-03-08T00:15:00-07:00" ], "xaxis": "x", - "y": [ - 62.464, - 84.915, - 94.197, - 27.059, - 79.618, - 67.46300000000001, - 40.778, - 169.49900000000002, - 151.93200000000002, - 150.47799999999998, - 209.925, - 42.622, - null, - null, - 104.47, - 165.442, - 67.942, - 50.572, - 128.297, - 124.697, - 109.259, - 20.237, - 0.556, - 82.806, - 110.702, - 95.232, - 104.321, - 123.959, - 128.264, - 176.315, - 79.442, - 93.861, - 133.208, - 133.72, - 91.747, - 136.616, - 114.572, - 123.342, - 125.693, - 152.42700000000002, - 69.164, - 13.053, - 85.256, - 45.524, - 167.98, - 152.334, - 146.173, - 141.785, - 181.479, - 236.137, - 258.202, - 205.064, - 249.933, - 229.574, - 207.085, - 238.036, - 124.152, - 220.435, - 163.289, - 76.266, - 218.112, - 214.506, - 106.342, - 58.313, - 200.269, - 49.003, - 174.21200000000002, - 170.68900000000002, - 160.465, - 140.541, - 118.305, - 96.531, - 33.654, - 58.676, - 45.17100000000001, - 24.229, - 39.969, - 31.975, - 28.143, - 26.805, - 15.784, - 17.555999999999997, - 7.838999999999999, - 15.050999999999998, - 7.058, - 5.285, - 3.512, - 6.777, - 5.235, - 4.965, - -4.763, - -3.006, - 6.815, - 3.892, - 6.865, - 10.52, - 10.13, - 21.751, - 9.953, - 31.54, - 3.859, - 10.867, - 34.931, - 31.656, - 28.595, - 14.6, - 18.283, - 13.857, - 6.942, - 9.689, - 7.553, - 3.941, - 3.897, - 5.4, - 7.282999999999999, - 7.861000000000001, - 5.433, - 5.472, - 5.2075000000000005, - 4.9430000000000005, - -0.815, - -0.193, - 5.307, - 4.5360000000000005, - 7.146, - 2.009, - 7.058, - 4.96, - 6.265, - 5.7860000000000005, - 2.02, - 7.443, - 2.824, - null, - null, - null, - null, - 5.053999999999999, - 7.3, - 4.96, - 5.684, - 6.408, - 3.149, - 1.971, - 2.67, - 2.081, - null, - null, - null, - -1.492, - -1.669, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -2.219, - null, - null, - null, - null, - null, - -1.481, - -0.672, - -3.628, - -5.638, - -0.397, - -0.534, - 1.079, - 3.451, - 3.65, - -0.738, - 0.759, - -1.294, - 2.857, - 1.596, - 2.51, - 1.514, - 1.8, - 2.736, - -1.47, - 0.754, - 4.6080000000000005, - 1.2990000000000002, - 3.589, - 3.033, - 3.2645, - 3.4960000000000004, - 3.49, - 1.855, - 5.702999999999999, - 3.567, - 1.927, - 6.683, - 1.585, - 5.587999999999999, - 2.516, - 6.738, - 1.249, - 2.989, - 9.568, - 10.504, - 9.524, - 11.17, - 15.503, - 17.11, - 13.939, - 8.037, - 6.54, - 16.02, - 13.824000000000002, - 16.202, - 5.318, - null, - null, - 15.442, - 22.792, - 17.875999999999998, - 20.931, - 12.513, - 6.082999999999999, - 20.882, - 12.029000000000002, - 18.316, - 0.589, - 8.913, - 17.76, - 19.72, - 19.384, - 29.536, - 28.545, - 30.582, - 25.886, - 23.078000000000003, - 32.509, - 6.457000000000001, - 0.5720000000000001, - 41.857, - 33.819, - 19.775, - 45.342, - 48.084, - 17.435, - 31.375, - 51.618, - 53.6, - 59.17100000000001, - 20.425, - 39.649, - 33.643, - 67.33, - 42.82, - 9.364, - 86.836, - 73.35300000000001, - 75.979, - 83.478, - 97.225, - 36.385, - 91.345, - 123.227, - 78.204, - 123.293, - 146.674, - 3.011, - 76.205, - 150.632, - 15.970999999999998, - 65.827, - 220.914, - 166.02, - 280.02, - 303.121, - 335.624, - 148.072, - 145.898, - 11.478, - 497.169, - 207.266, - 596.558, - 640.1990000000001, - 630.46, - 360.399, - 528.313, - 725.6310000000001, - 451.617, - 93.244, - 718.199, - 649.217, - 524.283, - 204.75, - 344.686, - 551, - 668.64, - 652.889, - 485.25, - 71.206, - 540.865, - 415.04, - 773.0989999999999, - 625.9730000000001, - 669.1460000000001, - 721.442, - 306.253, - 482.728, - 607.849, - 180.053, - 691.492, - 531.721, - 11.88, - 746.034, - 567.456, - 609.528, - 374.057, - 734.33, - 626.099, - 229.238, - 590.474, - 571.409, - 340.298, - 192.44, - 482.453, - 726.341, - 377.641, - 125.61, - 31.689, - 625.604, - 337.023, - 666.823, - 225.555, - 526.496, - 721.1610000000001, - 425.957, - 742.324, - 789.455, - 705.828, - 174.15099999999998, - 610.145, - 445.699, - 87.992, - 406.027, - 474.762, - 674.541, - 390.348, - 669.0360000000001, - 227.02, - 404.64, - 473.6830000000001, - 731.186, - 676.055, - 233.626, - 734.7919999999999, - 550.967, - 412.386, - 445.859, - 587.132, - 662.039, - 559.451, - 668.7389999999999, - 772.1410000000001, - 342.68800000000005, - 417.682, - 766.5360000000001, - 463.872, - 615.457, - 565.045, - 524.756, - 706.544, - 286.659, - 467.539, - 209.87, - 31.292, - 592.489, - 119.499, - 505.757, - 564.109, - 749.7280000000001, - 494.086, - 342.36800000000005, - 711.681, - 607.965, - 641.663, - 236.472, - 285.151, - 610.508, - 762.5889999999999, - 141.582, - 653.434, - 776.633, - 652.151, - 583.653, - 645.577, - 523.441, - 416.504, - 774.574, - 166.025, - 658.95, - 409.661, - 245.534, - 615.48, - 786.581, - 732.54, - 261.885, - 567.307, - 180.703, - 489.973, - 122.533, - 90.47, - 561.808, - 633.8290000000001, - 611.549, - 629.689, - 690.7660000000001, - 712.765, - 766.602, - 488.459, - 672.824, - 423.254, - 658.262, - 184.48, - 602.58, - 438.465, - 454.67800000000005, - 277.62, - 594.394, - 694.735, - 282.844, - 675.158, - 562.215, - 578.9069999999999, - 493.585, - 629.5840000000001, - 750.345, - 767.5269999999999, - 275.863, - 759.847, - 721.21, - 380.961, - 0.4679999999999999, - 377.454, - 713.409, - 204.596, - 427.261, - 655.096, - 767.423, - 765.419, - 338.305, - 348.51800000000003, - 289.588, - 479.64, - 440.32, - 502.399, - 417.6880000000001, - 744.8889999999999, - 745.4010000000001, - 742.5269999999999, - 738.6569999999999, - 599.448, - 484.804, - 306.132, - 46.058, - 579.304, - 542.891, - 570.346, - 697.35, - 362.452, - 410.019, - 693.706, - 417.165, - 457.277, - 501.485, - 567.462, - 437.986, - 423.529, - 280.02, - 460.806, - 525.819, - 501.612, - 657.948, - 638.514, - 20.276, - 456.027, - 626.991, - 576.606, - 376.48, - 15.057, - 631.2080000000001, - 439.17, - 622.24, - 498.628, - 566.052, - 513.492, - 390.304, - 406.594, - 603.599, - 479.535, - 409.441, - 408.262, - 490.832, - 494.895, - 581.842, - 575.433, - 403.071, - 333.521, - 299.559, - 386.72, - 512.7330000000001, - 555.614, - 551.65, - 411.42800000000005, - 431.099, - 541.746, - 535.927, - 435.608, - 443.811, - 413.437, - 232.156, - 463.569, - 338.79, - 497.3730000000001, - 333.819, - 404.932, - 337.07199999999995, - 322.307, - 258.956, - 470.126, - 455.273, - 397.852, - 291.014, - 435.305, - 355.031, - 0.402, - 389.77, - 362.722, - 207.938, - 358.907, - 197.731, - 365.552, - 380.576, - 347.219, - 73.485, - 211.373, - 263.096, - 59.403, - 90.756, - 250.891, - 269.648, - 223.557, - 219.11900000000003, - 224.762, - 245.105, - 202.466, - 60.674, - 240.998, - 185.327, - 52.675, - 189.264, - 119.566, - 90.673, - 121.702, - 88.37799999999999, - 116.037, - 88.76299999999999, - 102.438, - 107.85, - 97.764, - 103.952, - 92.253, - 80.791, - 61.445, - 44.213, - 0.429, - 39.936, - 51.13399999999999, - 54.354, - 64.15899999999999, - 26.227, - 0.335, - 43.156000000000006, - 41.059, - 40.954, - 48.133, - 37.183, - 25.748, - 35.311, - 28.848000000000003, - 20.342, - 24.763, - 29.96, - 28.506, - 23.535, - 31.386, - 21.707, - 22.852, - 23.155, - 23.618, - 19.059, - 23.089, - 14.897, - 3.859, - 12.018, - 15.013, - 13.515, - 5.769, - 6.727, - 2.962, - 10.152, - 12.645, - 9.106, - 0.451, - 3.991, - 5.059, - 5.516, - 0.528, - 6.215, - 0.589, - 3.782, - -1.019, - 0.09050000000000002, - 1.2, - 0.748, - -2.395, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -1.779, - 0.297, - -1.024, - 1.238, - 2.989, - 1.915, - 5.092, - 6.155, - 4.591, - 8.467, - 7.245, - 12.233, - 13.548, - 19.56, - 30.499, - 43.558, - 40.36, - 24.647, - 29.668000000000003, - 46.983, - 43.696000000000005, - 0.6659999999999999, - 0.677, - 16.059, - 31.441, - 62.458, - 69.428, - 51.877, - 52.697, - 93.938, - 62.965, - 77.4, - 75.638, - 96.476, - 79.387, - 41.852, - 92.044, - 87.34299999999999, - 63.438, - 84.116, - 80.65899999999999, - 117.98, - 121.867, - 153.159, - 131.066, - 48.188, - 226.486, - 162.739, - 42.969, - 121.735, - 112.871, - 125.021, - 129.31, - 11.148, - 116.917, - 131.408, - 95.92, - 96.074, - 130.158, - 142.512, - 78.473, - 100.308, - 213.036, - 224.526, - 113.79, - 131.892, - 130.918, - 202.504, - 215.15, - 141.59799999999998, - 164.55, - 116.45, - 167.91400000000002, - 160.74, - 152.179, - 9.469, - 124.019, - 247.246, - 227.889, - 160.939, - 138.43200000000002, - 138.493, - 36.935, - 107.619, - 116.251, - 92.897, - 11.561, - 5.7860000000000005, - 126.849, - 134.314, - 134.81, - 116.18, - 139.908, - 118.255, - 0.638, - 71.184, - 118.894, - 145.16, - 10.074, - 60.41, - 148.17700000000002, - 118.723, - 157.079, - 157.239, - 83.5, - 171.43200000000002, - 168.602, - 171.861, - 94.934, - 185.674, - 113.02, - 65.58, - 151.233, - 101.2, - 87.095, - 164.055, - 259.777, - 306.815, - 29.987, - 12.359000000000002, - 152.091, - 86.324, - 302.46, - 282.718, - 17.127, - 260.9, - 315.48, - 25.534, - 156.336, - 240.37, - 171.845, - 189.401, - 197.781, - 171.856, - 170.391, - 160.482, - 264.54400000000004, - 171.696, - 281.435, - 312.66700000000003, - 355.75800000000004, - 436.912, - 318.183, - 316.025, - 264.941, - 246.679, - 123.62850000000002, - 0.578, - 299.459, - 346.646, - 326.205, - 101.8, - 262.172, - 318.882, - 77.334, - 249.878, - 75.39, - 87.486, - 161.731, - 336.621, - 247.885, - 215.453, - 237.706, - 135.311, - 367.655, - 439.17, - 312.568, - 400.401, - 392.319, - 455.46, - 485.5580000000001, - 366.829, - 378.236, - 450.252, - 408.224, - 400.979, - 345.36300000000006, - 357.222, - 446.789, - 129.376, - 38.031, - 388.14, - 521.965, - 170.887, - 609.198, - 623.765, - 618.056, - 457.304, - 51.145, - 336.059, - 189.032, - 136.47799999999998, - 245.11, - 580.383, - 432.117, - 622.064, - 579.986, - 598.44, - 264.588, - 522.5930000000001, - 615.1709999999999, - 339.324, - 324.14, - 107.206, - 622.477, - 402.454, - 206.771, - 445.974, - 305.466, - 337.7, - 336.92400000000004, - 403.566, - 217.308, - 156.782, - 334.788, - 354.50199999999995, - 382.552, - 404.761, - 437.21, - 446.305, - 463.608, - 121.509, - 471.503, - 451.628, - 441.339, - 111.908, - 191.482, - 473.523, - 34.788000000000004, - 250.263, - 353.577, - 457.86, - 268.828, - 415.051, - 394.081, - 361.362, - 30.516, - 128.154, - 36.754, - 65.767, - 370.077, - 393.376, - 422.18, - 216.13, - 488.547, - 328.908, - 538.602, - 540.529, - 518.645, - 426.909, - 161.97899999999998, - 67.997, - 204.938, - 0.4679999999999999, - 181.033, - 44.153, - 262.331, - 462.909, - 371.844, - 560.442, - 563.487, - 378.698, - 657.42, - 682.689, - 531.297, - 731.153, - 747.9939999999999, - 758.295, - 465.739, - 608.818, - 616.25, - 543.535, - 587.573, - 746.965, - 234.694, - 767.659, - 672.9169999999999, - 394.565, - 516.14, - 487.171, - 583.234, - 321.569, - 530.658, - 593.915, - 596.365, - 565.447, - 560.453, - 443.833, - 661.554, - 511.45, - 748.9689999999999, - 593.987, - 650.653, - 572.906, - 515.48, - 725.835, - 666.7510000000001, - 436.164, - 474.635, - 670.187, - 252.036, - 562.187, - 354.684, - 346.096, - 659.0110000000001, - 339.528, - 529.3480000000001, - 486.857, - 493.469, - 796.073, - 491.162, - 662.936, - 619.752, - 428.853, - 545.9630000000001, - 757.0010000000001, - 714.23, - 666.663, - 472.697, - 517.974, - 261.241, - 520.495, - 679.65, - 565.188, - 612.297, - 773.6, - 212.827, - 595.341, - 662.903, - 792.4169999999999, - 572.8290000000001, - 371.376, - 741.388, - 649.332, - 745.676, - 784.44, - 764.285, - 697.548, - 697.201, - 680.5039999999999, - 600.4304999999999, - 520.357, - 759.798, - 600.9780000000001, - 448.6830000000001, - 730.454, - 720.4839999999999, - 635.1669999999999, - 688.569, - 419.229, - 541.592, - 420.528, - 442.198, - 464.07, - 293.475, - 208.896, - 653.346, - 631.225, - 345.54, - 358.329, - 347.736, - 577.586, - 264.181, - 619.476, - 352.163, - 563.663, - 549.3430000000001, - 311.577, - 516.405, - 512.375, - 490.849, - 301.293, - 371.608, - 238.366, - 0.385, - 95.391, - 130.136, - 375.726, - 364.517, - 298.815, - 153.148, - 163.476, - 320.452, - 294.207, - 89.759, - 282.811, - 360.371, - 359.435, - 354.745, - 217.011, - 260.47, - 198.634, - 314.434, - 304.172, - 161.715, - 218.31, - 317.715, - 177.46599999999998, - 311.687, - 223.782, - 293.8, - 292.627, - 186.627, - 193.817, - 110.041, - 94.99, - 279.541, - 229.761, - 155.53799999999998, - 295.848, - 303.952, - 306.594, - 301.133, - 129.28799999999998, - 176.497, - 300.384, - 302.933, - 204.927, - 250.065, - 299.988, - 199.796, - 229.002, - 202.014, - 224.57, - 195.688, - 148.502, - 210.834, - 246.492, - 196.988, - 247.544, - 304.023, - 229.238, - 127.433, - 128.22, - 57.646, - 177.93900000000002, - 133.219, - 273.232, - 196.61900000000003, - 166.136, - 219.642, - 175.03799999999998, - 222.604, - 181.551, - 180.84, - 178.81400000000002, - 200.594, - 50.28, - 184.061, - 218.993, - 162.656, - 150.153, - 199.129, - 106.644, - 195.424, - 153.89700000000002, - 204.095, - 78.672, - 159.1, - 141.16299999999998, - 189.511, - 183.841, - 179.128, - 176.387, - 176.541, - 29.811, - 141.295, - 173.072, - 173.072, - 132.745, - 165.453, - 97.693, - 105.984, - 135.526, - 148.92, - 51.75, - 113.256, - 144.422, - 120.056, - 32.949, - 133.07, - 93.542, - 77.846, - 124.096, - 129.844, - 133.076, - 33.527, - 113.141, - 106.375, - 0.462, - 0.517, - 111.864, - 111.076, - 56.199, - 109.551, - 99.812, - 102.46, - 106.088, - 76.657, - 92.033, - 80.94, - 76.156, - 83.5, - 54.608, - 86.28, - 80.626, - 66.24, - 77.604, - 78.86399999999999, - 56.705, - 76.882, - 81.182, - 51.112, - 82.646, - 87.98700000000001, - 85.069, - 0.484, - 0.517, - 45.381, - 90.376, - 91.769, - 68.999, - 35.278, - 88.09700000000001, - 98.227, - 96.944, - 90.431, - 9.001, - 77.626, - 35.845, - 35.339, - 95.705, - 62.458, - 117.545, - 87.822, - 83.979, - 116.185, - 158.423, - 28.33, - 165.26, - 27.642, - 0.49, - 168.101, - 189.5, - 143.72899999999998, - 194.191, - 189.401, - 195.947, - 213.372, - 36.5, - 44.268, - 288.944, - 315.238, - 224.83900000000003, - 296.426, - 244.923, - 69.544, - 16.02, - 194.918, - 68.024, - 234.931, - 214.704, - 334.975, - 329.546, - 302.587, - 26.238000000000003, - 290.634, - 149.944, - 233.835, - 256.336, - 113.08, - 195.512, - 168.382, - 162.276, - 28.435, - 126.855, - 160.751, - 121.239, - 132.894, - 113.515, - 105.819, - 99.207, - 8.291, - 50.545, - 56.788, - 54.982, - 39.87, - 44.676, - 41.631, - 41.196000000000005, - 36.043, - 38.741, - 18.377, - 37.855, - 31.067, - 30.725, - 25.864, - 35.449, - 20.711, - 14.06, - 30.29, - 0.534, - 19.808, - 20.166, - 20.992, - 14.914, - 20.314, - 21.036, - 14.308, - 14.771, - 9.205, - 12.706, - 3.077, - 6.303, - 11.401, - 11.313, - 5.197, - 4.09, - 9.43, - 7.691, - 5.676, - 0.143, - 3.584, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 0.5720000000000001, - -5.148, - 0.016, - null, - null, - -9.178, - 2.637, - 0.413, - 3.1239999999999997, - 5.835, - 2.78, - 6.105, - 8.731, - 6.034, - 11.77, - 8.693, - 15.156, - 16.125, - 16.257, - 14.38, - 20.893, - 23.089, - 30.439, - 29.222, - 33.77, - 33.478, - 24.625, - 16.516, - 14.903, - 20.182, - 42.22, - 29.2, - 15.31, - 45.078, - 43.36600000000001, - 46.542, - 29.261, - 48.018, - 39.506, - 36.814, - 54.051, - 47.109, - 53.154, - 0.517, - 58.863, - 60.878, - 39.589, - 0.5670000000000001, - 42.386, - 32.927, - 34.529, - 38.212, - 56.93600000000001, - 43.503, - 55.235, - 50.467, - 50.556, - 16.747, - 20.898000000000003, - 61.027, - 46.658, - 57.173, - 65.172, - 67.727, - 62.706, - 71.421, - 83.77, - 26.783, - 41.461000000000006, - 78.044, - 74.124, - 59.63399999999999, - 115.508, - 118.156, - 107.745, - 79.59100000000001, - 126.271, - 122.638, - 188.741, - 166.05900000000003, - 138.108, - 126.805, - 122.39, - 119.037, - 140.387, - 100.264, - 136.451, - 158.615, - 121.377, - 125.346, - 167.886, - 163.036, - 172.555, - 116.609, - 119.758, - 82.70100000000001, - 158.208, - 125.814, - 124.834, - 156.18200000000002, - 89.572, - 148.832, - 146.68, - 105.83, - 119.599, - 35.113, - 90.409, - 117.215, - 33.467, - 67.738, - 97.291, - 92.809, - 108.742, - 107.195, - 98.849, - 99.587, - 113.801, - 117.418, - 115.057, - 110.702, - 48.915, - 88.851, - 114.159, - 143.404, - 159.689, - 106.71, - 136.847, - 85.322, - 169.53799999999998, - 120.303, - 46.845, - 134.782, - 107.096, - 161.252, - 195.958, - 190.447, - 174.608, - 0.578, - 278.302, - 374.173, - 327.955, - 394.879, - 482.904, - 450.235, - 329.337, - 283.235, - 63.091, - 302.256, - 191.73, - 256.215, - 121.603, - 260.889, - 248.067, - 235.443, - 229.068, - 167.58900000000003, - 167.89700000000002, - 225.467, - 144.08700000000002, - 126.579, - 203.523, - 270.215, - 286.907, - 317.803, - 220.997, - 273.529, - 305.884, - 150.809, - 356.281, - 501.089, - 540.1659999999999, - 598.1759999999999, - 477.206, - 603.368, - 338.476, - 31.138, - 413.658, - 485.866, - 178.347, - 424.47, - 685.684, - 715.248, - 735.998, - 538.3, - 680.074, - 689.962, - 594.3330000000001, - 649.607, - 619.317, - 597.389, - 608.113, - 315.034, - 458.158, - 419.592, - 551.612, - 286.203, - 377.162, - 325.076, - 300.252, - 294.16900000000004, - 221.927, - 138.68, - 70.925, - 275.357, - 278.077, - 255.422, - 218.519, - 71.25, - 204.337, - 228.159, - 461.527, - 470.374, - 384.898, - 347.764, - 341.87300000000005, - 441.509, - 522.923, - 507.1230000000001, - 41.841, - 446.007, - 166.46, - 587.512, - 587.754, - 549.63, - 393.932, - 578.258, - 596.569, - 105.125, - 712.2260000000001, - 503.555, - 469.895, - 526.391, - 528.66, - 756.0369999999999, - 756.1419999999999, - 168.28799999999998, - 626.887, - 589.665, - 739.5210000000001, - 659.7919999999999, - 518.381, - 412.386, - 631.996, - 601.595, - 677.068, - 258.439, - 781.687, - 209.424, - 732.37, - 662.666, - 445.996, - 736.681, - 714.835, - 463.817, - 379.007, - 669.933, - 504.931, - 597.02, - 179.035, - 628.4119999999999, - 799.1610000000001, - 782.414, - 749.073, - 552.085, - 628.77, - 508.196, - 788.8330000000001, - 734.456, - 98.26, - 784.115, - 328.495, - 471.029, - 5.6370000000000005, - 515.656, - 310.97700000000003, - 44.037, - 74.565, - 30.621, - 455.251, - 384.512, - 505.05300000000005, - 717.059, - 377.55300000000005, - 594.57, - 652.944, - 406.6, - 464.7480000000001, - 697.658, - 353.539, - 314.654, - 705.949, - 662.628, - 445.253, - 451.089, - 698.9580000000001, - 392.572, - 720.17, - 434.044, - 782.331, - 160.509, - 797.306, - 250.885, - 777.057, - 721.205, - 517.726, - 740.4630000000001, - 693.293, - 187.552, - 397.009, - 728.8739999999999, - 651.727, - 752.712, - 79.883, - 625.406, - 676.765, - 744.586, - 353.082, - 616.685, - 493.706, - 756.643, - 508.648, - 795.5880000000001, - 795.5219999999999, - 563.244, - 328.407, - 403.049, - 551.898, - 419.747, - 272.472, - 437.705, - 303.88, - 378.55, - 364.753, - 520.4730000000001, - 478.929, - 460.096, - 418.431, - 381.203, - 296.844, - 289.996, - 258.472, - 302.17400000000004, - 356.19199999999995, - 158.334, - 355.807, - 0.264, - 353.654, - 308.907, - 153.55, - 219.708, - 355.802, - 0.512, - 152.645, - 304.778, - 380.537, - 383.785, - 108.549, - 546.508, - 642.572, - 357.602, - 531.82, - 384.143, - 493.612, - 620.71, - 429.095, - 181.942, - 515.612, - 433.312, - 42.887, - 596.315, - 512.606, - 16.912, - 375.643, - 205.725, - 311.54900000000004, - 316.4, - 222.588, - 206.782, - 276.986, - 285.514, - 393.607, - 115.778, - 53.528, - 0.457, - 75.01, - 229.882, - 255.593, - 0.473, - 121.558, - 152.38299999999998, - 113.878, - 128.418, - 96.652, - 114.297, - 82.156, - 114.379, - 74.086, - 136.775, - 132.327, - 119.329, - 97.599, - 60.757, - 128.374, - 135.42700000000002, - 140.695, - 144.813, - 146.404, - 127.719, - 157.828, - 100.743, - 116.796, - 42.914, - 39.126, - 95.612, - 21.157, - 72.192, - 32.79, - 106.364, - 84.094, - 35.509, - 99.24, - 72.896, - 83.781, - 81.87, - 44.621, - 80.169, - 13.796, - 50.985, - 72.825, - 18.916, - 0.413, - 45.463, - 35.372, - 42.253, - 79.211, - 67.617, - 22.764, - 21.691, - 33.511, - 33.83, - 34.271, - 33.164, - 20.397, - 28.451, - 32.503, - 19.158, - 28.798, - 5.142, - 21.278, - 23.309, - 14.3765, - 5.444, - 12.255, - 7.977, - 7.625, - 9.15, - 4.189, - 5.626, - 12.387, - 12.1, - 12.265999999999998, - 6.331, - 12.007, - 15.178, - 7.746, - 11.886, - 9.579, - 11.495, - 7.3, - 11.803, - 3.402, - 4.872, - 6.023, - 5.428, - 5.318, - 5.207999999999999, - 2.505, - 6.237, - 3.039, - 1.3430000000000002, - 2.758, - 0.644, - 1.899, - -0.413, - 2.158, - -7.317, - 5.197, - 2.9065, - 0.616, - 6.485, - 1.123, - 5.8020000000000005, - 9.975, - 9.458, - 8.693, - 7.564, - 5.312, - 4.913, - 4.513999999999999, - 1.315, - 0, - 3.033, - 4.993, - 3.363, - -6.31, - -3.4635, - -0.617, - 1.695, - -1.514, - -0.088, - -0.36350000000000005, - -0.639, - null, - null, - null, - -7.178999999999999, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -2.715, - null, - null, - -1.872, - -1.4455, - -1.019, - -1.696, - -0.127, - -3.045, - null, - null, - null, - null, - -1.861, - -1.454, - 0.974, - -1.052, - 0.825, - 0.148, - 2.84, - 3.749, - 4.668, - 4.008, - 3.474, - -3.623, - 4.723, - 7.867000000000001, - 3.297, - 7.162000000000001, - 11.462, - 7.377000000000001, - 10.146, - 6.193, - 6.903, - 7.806, - 3.523, - 13.257, - 5.537999999999999, - 1.888, - 13.042, - 14.528, - 7.256, - 9.452, - 13.807, - 10.273, - 18.867, - 12.607, - 15.905, - 14.627, - 8.461, - 16.852, - 18.701, - 21.157, - 11.087, - 13.13, - 24.174, - 24.581, - 33.434, - 17.182000000000002, - 8.379, - 32.503, - 31.782, - 32.107, - 59.562, - 34.1, - 26.453000000000003, - 36.869, - 1.403, - 25.688, - 28.336, - 17.925, - 45.358, - 89.792, - 110.317, - 93.663, - 116.152, - 116.906, - 106.755, - 71.972, - 145.518, - 154.07299999999998, - 172.362, - 178.40200000000002, - 191.114, - 208.637, - 212.772, - 182.85, - 183.957, - 303.886, - 224.333, - 347.186, - 361.175, - 269.56, - 104.729, - 351.039, - 265.502, - 535.288, - 571.211, - 241.207, - 2.543, - 666.597, - 538.63, - 455.3, - 665.446, - 197.136, - 494.609, - 615.067, - 398.259, - 502.746, - 669.3989999999999, - 677.184, - 437.65, - 302.317, - 402.746, - 261.775, - 718.887, - 716.6189999999999, - 434.352, - 479.232, - 654.276, - 737.7489999999999, - 360.811, - 289.599, - 715.727, - 642.929, - 499.641, - 638.624, - 730.327, - 732.75, - 501.639, - 167.143, - 751.941, - 726.573, - 572.295, - 421.844, - 738.508, - 642.026, - 704.81, - 775.637, - 787.325, - 613.971, - 672.2510000000001, - 498.055, - 385.5580000000001, - 590.259, - 525.279, - 584.534, - 381.352, - 622.196, - 527.036, - 220.556, - 264.286, - 274.603, - 510.5630000000001, - 590.254, - 525.1469999999999, - 406.06, - 502.19, - 754.056, - 477.911, - 705.1289999999999, - 601.369, - 779.4960000000001, - 755.597, - 323.991, - 581.005, - 60.862, - 673.066, - 664.665, - 603.764, - 452.999, - 536.4, - 313.096, - 143.806, - 725.1189999999999, - 498.259, - 142.033, - 305.703, - 535.976, - 383.962, - 494.466, - 546.3919999999999, - 320.87, - 229.982, - 643.766, - 796.6010000000001, - 721.012, - 535.283, - 668.3480000000001, - 705.922, - 274.146, - 762, - 599.007, - 787.2589999999999, - 504.854, - 785.4860000000001, - 146.94899999999998, - 574.217, - 614.3009999999999, - 746.6560000000001, - 721.095, - 578.181, - 600.554, - 142.76, - 308.901, - 33.604, - 167.204, - 143.53, - 496.64, - 420.462, - 711.0089999999999, - 275.214, - 553.401, - 748.176, - 670.676, - 566.8340000000001, - 113.906, - 312.85400000000004, - 739.13, - 343.101, - 711.3889999999999, - 732.59, - 680.658, - 327.003, - 332.43699999999995, - 6.9910000000000005, - 18.233, - 316.956, - 520.4680000000001, - 283.868, - 293.123, - 19.516, - 528.175, - 770.7919999999999, - 36.264, - 441.92800000000005, - 704.623, - 705.7510000000001, - 772.7189999999999, - 80.053, - 604.265, - 352.796, - 540.54, - 587.435, - 286.01, - 248.579, - 400.847, - 760.53, - 509.528, - 678.8960000000001, - 485.47, - 721.585, - 452.839, - 382.233, - 516.173, - 728.5989999999999, - 289.654, - 83.02600000000001, - 380.62, - 486.951, - 244.637, - 593.254, - 124.752, - 417.247, - 781.742, - 530.526, - 164.842, - 271.03, - 70.628, - 516.531, - 118.817, - 209.546, - 657.943, - 679.683, - 710.992, - 222.946, - 70.116, - 482.431, - 404.5630000000001, - 149.124, - 432.282, - 0.143, - 183.241, - 570.765, - 778.5210000000001, - 437.826, - 382.646, - 218.172, - 753.775, - 313.603, - 359.017, - 258.087, - 312.72700000000003, - 491.003, - 5.956, - 616.432, - 602.035, - 116.769, - 412.43, - 390.359, - 295.82, - 214.28, - 136.203, - 255.268, - 212.183, - 178.358, - 421.1230000000001, - 627.211, - 503.693, - 534.627, - 230.989, - 19.175, - 195.672, - 150.352, - 209.722, - 179.205, - 203.022, - 126.574, - 158.907, - 129.987, - 341.686, - 507.222, - 653.379, - 766.701, - 534.5830000000001, - 547.433, - 792.164, - 684.8860000000001, - 566.195, - 662.985, - 374.878, - 769.801, - 797.025, - 784.836, - 627.878, - 618.194, - 766.25, - 466.11300000000006, - 515.43, - 789.18, - 596.0840000000001, - 604.122, - 588.09, - 575.56, - 404.117, - 738.437, - 514.99, - 564.747, - 512.2040000000001, - 439.671, - 486.989, - 599.448, - 365.298, - 675.995, - 413.151, - 345.936, - 211.654, - 126.86, - 178.82, - 264.92400000000004, - 220.088, - 77.218, - 229.866, - 212.799, - 91.516, - 559.826, - 278.055, - 236.379, - 531.01, - 550.5880000000001, - 142.67700000000002, - 84.177, - 425.8080000000001, - 577.636, - 580.702, - 332.50300000000004, - 583.763, - 570.4069999999999, - 544.488, - 543.893, - 545.66, - 197.698, - 430.372, - 342.06, - 503.715, - 335.82300000000004, - 348.292, - 312.86, - 315.59, - 134.17700000000002, - 205.422, - 473.782, - 479.629, - 18.586, - 138.95, - 44.065, - 286.076, - 259.452, - 399.79, - 346.459, - 382.728, - 150.93, - 122.979, - 323.777, - 36.71, - 442.489, - 448.931, - 311.059, - 438.366, - 432.035, - 302.988, - 232.294, - 257.16200000000003, - 425.555, - 420.82, - 421.519, - 416.614, - 416.075, - 216.835, - 302.361, - 335.23900000000003, - 406.512, - 307.29900000000004, - 233.533, - 277.9, - 292.275, - 100.434, - 106.76, - 129.877, - 221.459, - 201.74400000000003, - 72.45, - 109.474, - 135.762, - 159.17700000000002, - 244.885, - 173.49599999999998, - 232.129, - 263.961, - 290.166, - 189.974, - 79.574, - 141.356, - 26.398000000000003, - 207.833, - 18.944000000000003, - 152.334, - 183.841, - 157.734, - 163.96099999999998, - 165.94299999999998, - 106.529, - 151.018, - 199.84, - 81.7, - 162.64, - 39.523, - 125.087, - 144.554, - 101.376, - 80.67, - 72.671, - 73.436, - 64.952, - 62.414, - 38.912, - 38.427, - 39.633, - 40.272, - 40.057, - 38.235, - 28.132, - 34.194, - 20.788, - 13.835, - 26.381, - 7.673999999999999, - 11.627, - 9.161, - 20.849, - 6.457000000000001, - 0.446, - 5.566, - 14.479, - 9.909, - 15.453, - 10.058, - 5.4110000000000005, - 0.379, - 5.502000000000001, - 10.625, - 7.267, - 6.155, - 8.23, - 7.388, - 5.0760000000000005, - 5.874, - 2.8510000000000004, - 1.7009999999999998, - 1.69, - 2.939, - 3.028, - 0.847, - 0.589, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -1.223, - 0.919, - -2.45, - 0.479, - 3.991, - 3.545, - 6.237, - 6.76, - 9.067, - 10.526, - 13.598, - 17.039, - 17.413, - 15.8, - 23.276, - 16.108, - 19.67, - 26.673, - 12.595999999999998, - 32.338, - 37.612, - 23.717, - 24.543000000000003, - 38.774, - 33.401, - 36.897, - 50.968, - 76.563, - 90.266, - 101.089, - 64.737, - 61.429, - 97.274, - 126.502, - 101.37, - 131.661, - 110.487, - 110.851, - 137.232, - 130.494, - 153.826, - 86.186, - 120.21, - 184.127, - 94.318, - 172.984, - 114.6, - 167.63299999999998, - 26.767, - 210.157, - 180.466, - 221.255, - 153.991, - 154.673, - 233.863, - 184.623, - 163.64700000000002, - 191.356, - 218.211, - 157.52, - 184.182, - 277.069, - 117.545, - 284.347, - 169.764, - 245.782, - 194.125, - 306.93, - 259.298, - 186.269, - 268.866, - 150.599, - 250.841, - 340.93699999999995, - 111.687, - 233.246, - 329.18300000000005, - 90.822, - 287.111, - 247.852, - 296.476, - 377.273, - 377.691, - 387.804, - 267.693, - 328.407, - 275.214, - 305.879, - 320.072, - 347.131, - 311.648, - 317.605, - 430.267, - 327.036, - 344.527, - 387.948, - 334.589, - 322.78, - 197.946, - 272.841, - 374.272, - 348.51199999999994, - 393.519, - 358.708, - 362.24300000000005, - 282.288, - 225.935, - 461.588, - 395.512, - 351.37, - 374.867, - 456.379, - 256.176, - 517.065, - 516.977, - 85.096, - 441.096, - 533.681, - 295.92, - 540.122, - 539.814, - 545.501, - 414.021, - 43.916, - 28.16, - 19.324, - 469.339, - 567.555, - 552.828, - 387.061, - 503.566, - 583.565, - 586.477, - 592.8580000000001, - 596.8, - 277.862, - 576.716, - 447.103, - 229.728, - 586.224, - 620.264, - 625.587, - 101.139, - 453.792, - 505.763, - 439.318, - 367.7480000000001, - 639.158, - 644.377, - 644.4209999999999, - 653.186, - 659.115, - 659.291, - 626.154, - 0.523, - 224.454, - 453.318, - 580.151, - 604.981, - 460.283, - 438.096, - 159.116, - 692.186, - 475.109, - 701.485, - 704.6010000000001, - 460.25, - 0.545, - 129.013, - 503.461, - 329.04, - 208.373, - 538.823, - 709.0160000000001, - 571.761, - 438.559, - 741.944, - 741.5139999999999, - 744.944, - 744.168, - 500.505, - 336.64300000000003, - 371.861, - 754.837, - 755.8889999999999, - 234.914, - 719.796, - 298.507, - 770.841, - 530.405, - 775.972, - 633.064, - 666.08, - 547.873, - 464.318, - 579.3969999999999, - 736.488, - 318.574, - 651.231, - 534.126, - 793.325, - 479.458, - 436.384, - 648.451, - 735.86, - 664.169, - 711.0360000000001, - 729.925, - 476.436, - 352.586, - 644.724, - 625.967, - 160.21200000000002, - 462.122, - 507.976, - 387.111, - 204.2, - 379.359, - 699.668, - 708.284, - 490.705, - 339.963, - 795.054, - 521.668, - 386.445, - 689.1360000000001, - 676.732, - 136.17, - 269.85200000000003, - 698.765, - 357.431, - 680.1619999999999, - 574.035, - 116.235, - 436.94, - 639.9069999999999, - 215.271, - 124.218, - 226.243, - 350.329, - 463.74, - 181.209, - 303.732, - 228.611, - 447.918, - 633.548, - 458.389, - 489.687, - 629.5459999999999, - 359.47900000000004, - 604.034, - 767.924, - 547.163, - 730.57, - 21.019, - 491.0580000000001, - 209.474, - 468.106, - 481.225, - 524.492, - 43.255, - 308.274, - 620.346, - 717.654, - 402.449, - 653.29, - 515.849, - 705.933, - 410.041, - 621.447, - 54.2, - 284.766, - 133.048, - 749.596, - 796.227, - 417.765, - 606.737, - 422.86300000000006, - 389.214, - 93.872, - 503.087, - 3.094, - 478.093, - 177.273, - 786.212, - 796.342, - 701.204, - 716.834, - 593.689, - 667.9839999999999, - 765.694, - 670.247, - 527.7180000000001, - 679.931, - 764.466, - 706.467, - 765.76, - 638.866, - 619.289, - 560.002, - 730.779, - 514.555, - 613.4540000000001, - 329.117, - 243.106, - 591.404, - 348.76, - 248.584, - 715.8760000000001, - 734.539, - 729.8810000000001, - 790.2860000000001, - 190.546, - 783.807, - 384.798, - 254.453, - 626.066, - 700.125, - 597.4, - 638.118, - 567.153, - 284.909, - 718.8710000000001, - 217.914, - 642.109, - 558.069, - 605.306, - 585.15, - 529.485, - 560.244, - 672.956, - 496.338, - 470.402, - 318.651, - 447.196, - 416.955, - 216.29, - 627.823, - 469.989, - 465.606, - 506.853, - 70.788, - 356.391, - 756.742, - 644.179, - 92.474, - 102.014, - 504.75, - 157.778, - 731.698, - 790.0060000000001, - 768.27, - 352.619, - 134.16, - 774.5139999999999, - 780.465, - 569.763, - 773.721, - 674.1560000000001, - 272.868, - 780.2339999999999, - 379.656, - 779.931, - 776.903, - 776.0880000000001, - 494.499, - 0.363, - 111.753, - 765.253, - 534.6709999999999, - 560.0840000000001, - 501.254, - 438.922, - 284.47900000000004, - 745.3960000000001, - 737.303, - 468.216, - 719.096, - 484.165, - 526.854, - 723.578, - 717.318, - 714.549, - 503.77, - 705.5260000000001, - 639.367, - 228.897, - 682.717, - 670.4889999999999, - 413.283, - 676.408, - 671.805, - 668.788, - 661.62, - 161.671, - 435.068, - 422.009, - 620.946, - 601.793, - 596.238, - 606.643, - 350.759, - 620.798, - 209.898, - 624.288, - 269.295, - 457.205, - 531.6990000000001, - 421.101, - 455.823, - 494.146, - 562.683, - 369.697, - 460.206, - 5.428, - 47.214, - 555.2669999999999, - 483.389, - 175.412, - 360.575, - 270.402, - 397.186, - 547.686, - 567.318, - 569.686, - 555.509, - 529.5740000000001, - 443.607, - 513.399, - 454.607, - 538.911, - 398.848, - 338.036, - 535.613, - 549.332, - 540.821, - 108.858, - 220.551, - 533.9830000000001, - 218.101, - 530.548, - 504.128, - 471.943, - 307.712, - 259.606, - 427.713, - 282.073, - 468.244, - 468.1830000000001, - 266.46, - 444.477, - 401.573, - 350.48900000000003, - 229.459, - 141.884, - 306.396, - 277.251, - 251.766, - 210.267, - 0.391, - 339.786, - 332.095, - 268.932, - 315.546, - 271.129, - 275.362, - 220.033, - 157.178, - 222.604, - 236.21400000000003, - 121.779, - 195.259, - 140.855, - 131.85399999999998, - 234.105, - 233.318, - 198.48, - 105.736, - 140.921, - 0.363, - 109.094, - 85.32799999999999, - 244.648, - 178.15900000000002, - 226.073, - 215.012, - 96.487, - 136.467, - 179.21599999999998, - 179.695, - 171.856, - 137.904, - 148.315, - 61.242, - 128.226, - 164.192, - 163.179, - 98.221, - 115.156, - 44.874, - 127.736, - 122.219, - 88.796, - 88.086, - 43.619, - 69.268, - 41.918, - 45.039, - 57.878, - 54.211000000000006, - 52.218, - 50.187, - 39.231, - 49.06399999999999, - 40.376, - 7.927, - 26.128, - 33.048, - 34.653000000000006, - 36.258, - 15.8, - 26.304, - 23.821, - 32.564, - 29.47, - 25.82, - 30.12, - 28.462, - 14.082, - 26.712, - 20.48, - 24.113000000000003, - 13.46, - 16.609, - 15.211, - 3.363, - 9.744, - 10.917, - 9.353, - 7.773, - 0.517, - 9.838, - 7.982, - 3.0610000000000004, - 5.577000000000001, - 0.847, - 4.668, - -0.997, - 0.858, - 0.925, - -4.256, - 0.655, - -0.342, - 0.407, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -0.969, - -2.417, - null, - null, - 2.494, - 10.636, - 20.43, - 21.663, - 26.458, - 25.06, - 21.597, - 32.861, - 38.653, - 32.272, - 41.136, - 53.138000000000005, - 48.519, - 49.807, - 62.018, - 35.262, - 63.857, - 72.005, - 65.29899999999999, - 20.193, - 90.684, - 98.331, - 43.553, - 43.773, - 118.222, - 121.135, - 95.931, - 80.031, - 141.092, - 147.445, - 158.329, - 168.61900000000003, - 114.798, - 114.457, - 176.40900000000002, - 78.936, - 104.398, - 203.842, - 36.632, - 208.406, - 117.617, - 199.889, - 176.959, - 223.248, - 214.528, - 194.648, - 198.937, - 91.527, - 47.66, - 115.926, - 53.567, - 270.237, - 255.515, - 160.129, - 104.707, - 210.61900000000003, - 268.772, - 243.194, - 272.323, - 277.091, - 262.045, - 284.85400000000004, - 262.072, - 351.606, - 355.945, - 201.64, - 369.829, - 250.555, - 378.676, - 257.916, - 281.231, - 295.171, - 266.141, - 269.009, - 324.448, - 340.921, - 342.886, - 338.87800000000004, - 327.449, - 258.472, - 333.797, - 312.92, - 348.033, - 449.509, - 453.775, - 294.163, - 384.43, - 256.033, - 316.339, - 459.831, - 247.219, - 403.418, - 322.032, - 219.246, - 506.974, - 248.601, - 458.295, - 481.022, - 182.789, - 291.064, - 315.634, - 422.318, - 469.967, - 477.63, - 397.263, - 503.583, - 495.28, - 390.24300000000005, - 263.988, - 279.772, - 193.305, - 270.347, - 241.719, - 317.446, - 132.239, - 448.072, - 400.401, - 5.747000000000001, - 0.55, - 290.772, - 333.362, - 527.735, - 43.129, - 0.5670000000000001, - 365.497, - 116.604, - 171.34400000000002, - 183.186, - 495.814, - 485.035, - 562.22, - 384.275, - 368.9980000000001, - 477.427, - 268.453, - 509.385, - 425.384, - 502.4980000000001, - 554.964, - 513.294, - 677.36, - 685.304, - 484.429, - 205.367, - 439.918, - 407.761, - 155.94, - 212.375, - 265.656, - 715.457, - 714.345, - 702.443, - 717.885, - 724.1339999999999, - 727.547, - 706.307, - 539.1419999999999, - 227.768, - 250.484, - 751.05, - 414.5, - 508.559, - 772.691, - 755.316, - 750.174, - 242.071, - 732.078, - 634.743, - 614.004, - 796.904, - 581.974, - 767.571, - 322.538, - 181.804, - 378.153, - 591.482, - 541.7180000000001, - 358.956, - 150.275, - 757.942, - 692.962, - 274.316, - 0.457, - 204.205, - 610.2769999999999, - 448.986, - 611.918, - 549.619, - 512.523, - 391.256, - 429.805, - 453.93, - 100.253, - 398.87, - 190.613, - 0.4679999999999999, - 105.714, - 445.435, - 0.473, - 602.982, - 465.915, - 704.27, - 649.536, - 447.912, - 585.806, - 646.122, - 583.658, - 654.375, - 536.967, - 642.786, - 730.096, - 703.885, - 53.468, - 235.107, - 627.002, - 787.638, - 532.018, - 494.895, - 528.247, - 773.6439999999999, - 621.304, - 620.269, - 730.977, - 755.5310000000001, - 578.869, - 491.603, - 743.7, - 343.772, - 716.5360000000001, - 474.299, - 604.4630000000001, - 717.0210000000001, - 383.422, - 479.711, - 609.187, - 695.297, - 616.625, - 599.63, - 535.321, - 754.832, - 694.801, - 638.9540000000001, - 629.722, - 639.422, - 586.4, - 523.281, - 72.12, - 665.865, - 728.654, - 774.525, - 428.737, - 603.665, - 795.8910000000001, - 765.2760000000001, - 644.735, - 694.355, - 629.992, - 23.386, - 175.137, - 493.607, - 457.838, - 71.382, - 655.493, - 562.65, - 414.032, - 743.4580000000001, - 762.7819999999999, - 770.941, - 87.28200000000001, - 632.32, - 531.236, - 743.1, - 505.311, - 502.245, - 621.398, - 115.954, - 568.7719999999999, - 639.378, - 149.454, - 679.2589999999999, - 780.971, - 731.544, - 704.182, - 368.084, - 0.721, - 620.434, - 2.582, - 659.423, - 462.204, - 758.311, - 781.6210000000001, - 415.777, - 788.079, - 372.268, - 415.518, - 547.0419999999999, - 417.809, - 635.42, - 612.072, - 480.108, - 594.884, - 512.127, - 373.138, - 697.46, - 397.918, - 697.1410000000001, - 620.7040000000001, - 582.266, - 688.393, - 552.828, - 550.274, - 493.034, - 145.32, - 628.9019999999999, - 782.915, - 620.418, - 548.523, - 666.5419999999999, - 683.427, - 39.556, - 393.915, - 581.0269999999999, - 137.827, - 377.652, - 794.52, - 623.98, - 551.711, - 699.393, - 105.637, - 598.991, - 527.812, - 697.24, - 637.2919999999999, - 606.985, - 730.8610000000001, - 108.213, - 678.957, - 585.448, - 46.487, - 602.85, - 396.288, - 735.508, - 109.045, - 494.587, - 450.109, - 467.302, - 797.196, - 627.118, - 729.931, - 22.203000000000003, - 763.2660000000001, - 500.522, - 638.938, - 790.8810000000001, - 496.035, - 691.883, - 621.205, - 790.1489999999999, - 796.238, - 271.327, - 145.391, - 689.1089999999999, - 574.382, - 779.914, - 415.601, - 0.346, - 271.222, - 555.906, - 731.368, - 515.711, - 772.449, - 769.955, - 763.7339999999999, - 667.6160000000001, - 461.577, - 757.8710000000001, - 749.673, - 751.903, - 633.009, - 411.367, - 739.395, - 607.948, - 681.357, - 727.685, - 125.165, - 483.262, - 680.7289999999999, - 596.139, - 725.7189999999999, - 299.597, - 172.417, - 714.8739999999999, - 682.084, - 434.44, - 531.451, - 0.379, - 223.199, - 701.6610000000001, - 442.566, - 399.982, - 538.085, - 558.124, - 687.677, - 672.135, - 404.166, - 678.2739999999999, - 674.706, - 673.2810000000001, - 650.4169999999999, - 665.331, - 661.317, - 222.467, - 316.895, - 626.7330000000001, - 411.604, - 260.29400000000004, - 426.447, - 640.226, - 602.988, - 626.1709999999999, - 628.313, - 627.806, - 622.499, - 624.283, - 466.581, - 543.656, - 163.075, - 117.573, - 132.22799999999998, - 122.093, - 596.5409999999999, - 398.199, - 406.781, - 25.49, - 386.103, - 546.7280000000001, - 523.7819999999999, - 482.871, - 276.579, - 354.144, - 259.171, - 330.014, - 317.721, - 209.837, - 0.418, - 0.385, - 297.527, - 263.999, - 334.958, - 60.988, - 217.991, - 169.868, - 383.24, - 293.002, - 130.565, - 264.92400000000004, - 229.673, - 168.696, - 271.377, - 252.592, - 101.535, - 253.209, - 256.198, - 272.533, - 84.50200000000001, - 318.541, - 240.552, - 50.649, - 0.391, - 0.352, - 77.559, - 323.782, - 365.304, - 260.371, - 338.856, - 214.517, - 214.027, - 360.01300000000003, - 209.155, - 254.91, - 392.082, - 147.208, - 280.405, - 303.41200000000003, - 215.436, - 315.728, - 346.668, - 343.37, - 254.805, - 172.62099999999998, - 87.287, - 244.285, - 191.455, - 47.093, - 126.128, - 353.517, - 253.401, - 335.47, - 228.693, - 303.126, - 242.33, - 185.129, - 81.991, - 332.194, - 245.485, - 325.599, - 216.361, - 48.073, - 206.71, - 304.849, - 224.311, - 278.41200000000003, - 187.067, - 290.66200000000003, - 260.36, - 263.878, - 247.968, - 213.807, - 93.597, - 46.9, - 74.487, - 87.915, - 40.949, - 69.654, - 53.688, - 44.637, - 78.391, - 6.909, - 68.78399999999999, - 20.849, - 16.554000000000002, - 39.49, - 47.01, - 21.751, - 0.418, - 48.909, - 48.998000000000005, - 46.487, - 39.633, - 36.319, - 33.654, - 16.102999999999998, - 12.987, - 31.788, - 29.387, - 19.544, - 20.188, - 10.454, - 16.885, - 17.854, - 13.482, - 12.062, - 10.642, - 14.237, - 11.583, - 13.719, - 17.54, - 11.913, - 7.702000000000001, - 6.287000000000001, - 3.11, - 6.678, - 6.43, - 4.184, - -1.426, - 4.822, - 4.894, - -2.902, - -5.131, - -0.7490000000000001, - -2.698, - 0.969, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - 1.668, - -0.21, - 4.685, - 3.947, - 2.752, - 6.7, - 7.096, - 8.929, - 13.279000000000002, - 15.371, - 7.454, - 13.075, - 17.149, - 17.578, - 18.393, - 28.54, - 27.031, - 13.961, - 0.693, - 30.384, - 32.278, - 41.725, - 37.833, - 52.328, - 57.388000000000005, - 58.445, - 66.752, - 59.067, - 55.78, - 65.706, - 84.414, - 37.376, - 28.099, - 75.23100000000001, - 14.237, - 39.985, - 64.952, - 84.006, - 61.467, - 38.741, - 55.153, - 57.09, - 56.87, - 72.918, - 32.971, - 64.016, - 68.712, - 36.445, - 0.5670000000000001, - 0.561, - 51.75, - 39.958, - 74.229, - 27.703000000000003, - 14.11, - 83.081, - 56.54, - 62.458, - 66.851, - 68.046, - 85.427, - 65.514, - 65.92699999999999, - 98.766, - 101.425, - 95.001, - 100.076, - 149.129, - 91.538, - 159.755, - 96.382, - 115.271, - 154.134, - 148.838, - 8.494, - 104.844, - 164.088, - 155.477, - 154.183, - 160.65200000000002, - 166.708, - 130.907, - 203.545, - 192.495, - 235.448, - 206.848, - 166.928, - 153.082, - 160.118, - 153.275, - 168.65200000000002, - 130.472, - 226.992, - 130.07, - 138.493, - 197.296, - 174.95, - 56.749, - 158.52700000000002, - 20.76, - 164.75400000000002, - 46.228, - 116.995, - 147.004, - 101.211, - 175.203, - 113.609, - 120.49, - 85.81200000000001, - 15.2, - 139.22, - 172.78599999999997, - 239.115, - 225.093, - 287.463, - 289.561, - 143.822, - 213.432, - 273.80400000000003, - 275.495, - 258.89, - 291.934, - 283.91200000000003, - 284.121, - 28.226, - 267.842, - 255.598, - 249.322, - 97.99, - 59.221, - 0.5720000000000001, - 115.635, - 335.432, - 366.218, - 89.258, - 49.851000000000006, - 329.932, - 357.569, - 117.396, - 263.774, - 213.928, - 210.03, - 210.878, - 59.353, - 321.795, - 296.36, - 150.864, - 307.31, - 190.045, - 315.337, - 308.411, - 213.598, - 0.561, - 116.317, - 355.31199999999995, - 228.996, - 179.778, - 367.214, - 388.828, - 420.853, - 396.365, - 233.995, - 192.451, - 272.769, - 477.206, - 337.35900000000004, - 340.50199999999995, - 422.753, - 446.068, - 355.405, - 274.933, - 540.887, - 507.838, - 518.309, - 400.059, - 215.056, - 430.174, - 407.668, - 428.137, - 434.73800000000006, - 390.32, - 346.36, - 586.174, - 402.052, - 555.7959999999999, - 550.549, - 500.026, - 590.309, - 395.171, - 524.509, - 511.263, - 658.163, - 434.462, - 571.007, - 510.806, - 466.454, - 228.864, - 680.1289999999999, - 684.2860000000001, - 665.6610000000001, - 250.153, - 416.388, - 364.687, - 662.5889999999999, - 375.296, - 585.998, - 309.986, - 565.524, - 518.106, - 213.405, - 551.909, - 517.698, - 325.076, - 288.306, - 587.65, - 549.305, - 480.691, - 463.652, - 463.404, - 442.126, - 473.931, - 484.149, - 516.7130000000001, - 517.197, - 36.71, - 19.648, - 399.966, - 496.112, - 488.657, - 529.783, - 388.773, - 587.375, - 141.95600000000002, - 527.905, - 669.8560000000001, - 670.4839999999999, - 683.322, - 184.755, - 426.601, - 623.424, - 630.432, - 643.1990000000001, - 639.015, - 323.969, - 187.375, - 26.673, - 563.944, - 154.569, - 364.36800000000005, - 654.331, - 716.487, - 693.188, - 689.709, - 416.174, - 357.249, - 424.487, - 228.225, - 605.823, - 532.668, - 419.659, - 398.30300000000005, - 276.838, - 233.973, - 317.258, - 245.545, - 460.382, - 183.83, - 223.518, - 472.114, - 497.851, - 414.06, - 536.086, - 621.431, - 486.086, - 552.9490000000001, - 454.943, - 419.251, - 371.767, - 274.768, - 609.429, - 631.153, - 614.885, - 545.181, - 198.74400000000003, - 275.021, - 500.241, - 568.309, - 580.63, - 351.342, - 563.299, - 252.196, - 520.143, - 331.033, - 21.779, - 396.206, - 532.937, - 530.4209999999999, - 298.876, - 304.431, - 508.202, - 490.089, - 68.184, - 505.702, - 304.822, - 553.88, - 183.907, - 358.934, - 566.091, - 548.908, - 194.318, - 530.84, - 553.0319999999999, - 575.725, - 339.649, - 175.97400000000002, - 396.371, - 575.742, - 539.687, - 225.572, - 558.851, - 599.861, - 433.714, - 54.597, - 631.313, - 512.314, - 450.307, - 433.615, - 440.436, - 586.631, - 671.789, - 525.054, - 727.3710000000001, - 720.5880000000001, - 550.659, - 225.329, - 618.095, - 524.729, - 731.605, - 470.903, - 384.237, - 768.3919999999999, - 491.542, - 683.179, - 570.115, - 691.8560000000001, - 525.538, - 636.015, - 341.537, - 48.722, - 648.385, - 676.27, - 288.66900000000004, - 624.365, - 131.077, - 499.756, - 358.69199999999995, - 705.03, - 579.205, - 742.7810000000001, - 715.0939999999999, - 690.821, - 748.77, - 587.182, - 554.2819999999999, - 761.961, - 776.688, - 336.329, - 535.855, - 504.419, - 764.813, - 775.1080000000001, - 620.7869999999999, - 533.46, - 620.0319999999999, - 442.3130000000001, - 796.909, - 446.712, - 626.3969999999999, - 730.421, - 626.094, - 611.075, - 457.431, - 454.21, - 635.91, - 350.522, - 32.9, - 480.328, - 302.438, - 642.1419999999999, - 624.982, - 709.2860000000001, - 695.743, - 793.27, - 769.873, - 506.897, - 316.768, - 501.81, - 718.9860000000001, - 703.252, - 721.4639999999999, - 713.58, - 684.627, - 394.95, - 376.386, - 595.693, - 302.421, - 124.163, - 675.0260000000001, - 347.389, - 402.818, - 710.09, - 781.137, - 761.1189999999999, - 263.113, - 21.366, - 347.582, - 445.104, - 795.395, - 417.44, - 342.886, - 446.288, - 655.795, - 16.185, - 264.555, - 467.456, - 471.139, - 582.871, - 580.471, - 426.199, - 624.492, - 181.953, - 368.591, - 610.145, - 629.788, - 598.49, - 434.628, - 550.78, - 595.104, - 664.643, - 326.59, - 785.431, - 445.848, - 781.797, - 587.248, - 696.288, - 572.9169999999999, - 97.742, - 572.516, - 480.955, - 745.9680000000001, - 370.55, - 332.53, - 743.727, - 575.18, - 315.629, - 743.8430000000001, - 743.4580000000001, - 737.066, - 700.9010000000001, - 134.535, - 405.289, - 524.943, - 719.674, - 475.279, - 472.923, - 708.498, - 394.361, - 628.781, - 412.947, - 664.703, - 584.203, - 417.082, - 684.567, - 477.966, - 584.98, - 606.55, - 695.3739999999999, - 533.124, - 585.58, - 685.563, - 511.78, - 598.798, - 544.466, - 489.318, - 477.454, - 321.652, - 495.6880000000001, - 657.293, - 507.745, - 651.248, - 644.851, - 319.906, - 438.289, - 640.865, - 396.354, - 432.321, - 348.62300000000005, - 630.6080000000001, - 522.962, - 0.368, - 69.048, - 568.139, - 461.307, - 607.7, - 196.382, - 127.279, - 591.393, - 597.741, - 403.407, - 588.404, - 583.9830000000001, - 582.106, - 54.888000000000005, - 455.911, - 402.504, - 565.375, - 432.954, - 562.32, - 559.76, - 141.405, - 219.708, - 432.161, - 296.244, - 542.247, - 537.76, - 395.875, - 378.297, - 525.857, - 390.155, - 520.099, - 247.687, - 356.22, - 425.918, - 325.588, - 486.334, - 352.49800000000005, - 324.647, - 482.871, - 378.886, - 239.264, - 395.082, - 319.98400000000004, - 435.778, - 346.93800000000005, - 454.48, - 190.728, - 200.17, - 299.316, - 405.543, - 199.955, - 433.009, - 255.136, - 276.601, - 376.348, - 256.633, - 31.193, - 257.42, - 365.254, - 354.849, - 352.735, - 300.214, - 76.805, - 332.585, - 234.826, - 339.792, - 342.19800000000004, - 352.163, - 175.638, - 146.49200000000002, - 0.374, - 252.774, - 311.88, - 311.599, - 103.991, - 252.333, - 297.285, - 293.007, - 288.906, - 280.147, - 274.531, - 251.431, - 251.139, - 267.187, - 241.152, - 60.476000000000006, - 245.143, - 265.166, - 273.391, - 231.017, - 261.472, - 252.333, - 223.403, - 124.289, - 143.393, - 225.952, - 217.198, - 144.461, - 62.49100000000001, - 118.387, - 71.146, - 195.925, - 161.627, - 150.03799999999998, - 143.28799999999998, - 137.408, - 152.813, - 82.167, - 29.156, - 26.481, - 24.075, - 29.899, - 23.067, - 26.348000000000003, - 23.073, - 25.363000000000003, - 22.572, - 23.838, - 17.413, - 2.45, - 20.023, - 19.335, - 19.076, - 16.279, - 13.708, - 14.55, - 15.497, - 8.748, - 15.921, - 6.16, - 15.91, - 8.913, - 11.109000000000002, - 7.652, - 8.115, - 8.77, - 7.718, - 2.807, - 9.271, - 5.422000000000001, - 7.68, - 2.174, - 3.867, - 5.56, - 3.1210000000000004, - 3.661, - 0.7809999999999999, - 3.275, - 4.52, - -4.977, - -7.152, - null, - null, - 0.479, - -4.409999999999999, - -9.299, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -3.997, - null, - null, - -2.748, - -1.066, - 0.616, - 0.71, - 1.822, - 0.115, - 4.9430000000000005, - 9.529, - 2.516, - 7.68, - 11.489, - 12.380999999999998, - 10.339, - 11.682, - 12.265999999999998, - 11.963, - 23.1, - 38.559, - 60.603, - 40.723, - 63.168, - 41.604, - 32.046, - 16.857, - 10.708, - 15.321, - 15.91, - 17.71, - 18.745, - 25.633000000000003, - 23.161, - 28.628, - 25.556, - 27.725, - 26.365, - 16.769000000000002, - 40.536, - 46.603, - 71.465, - 68.872, - 49.625, - 89.633, - 106.81, - 150.654, - 118.641, - 222.703, - 176.706, - 194.874, - 306.04900000000004, - 194.609, - 264.48900000000003, - 274.922, - 183.687, - 132.05200000000002, - 69.747, - 309.04400000000004, - 177.614, - 142.369, - 303.203, - 111.368, - 370.517, - 378.759, - 380.554, - 349.76800000000003, - 35.669000000000004, - 192.523, - 241.284, - 250.847, - 312.904, - 285.388, - 307.222, - 309.639, - 320.897, - 348.601, - 342.19800000000004, - 251.876, - 211.291, - 438.135, - 208.912, - 260.707, - 408.741, - 301.078, - 342.969, - 377.829, - 352.041, - 286.456, - 434.27, - 250.957, - 0.611, - 38.543, - 239.80900000000003, - 308.83, - 498.584, - 304.893, - 515.656, - 185.669, - 434, - 413.856, - 373.843, - 528.55, - 185.036, - 495.936, - 563.6080000000001, - 400.081, - 582.8330000000001, - 591.8340000000001, - 594.405, - 485.954, - 270.308, - 80.84100000000001, - 121.63, - 264.39, - 243.057, - 146.096, - 122.737, - 0.556, - 231.325, - 473.408, - 400.847, - 181.055, - 432.068, - 586.56, - 37.354, - 170.991, - 423.033, - 0.556, - 281.303, - 318.712, - 512.931, - 313.317, - 287.904, - 363.256, - 283.676, - 9.436, - 432.492, - 461.312, - 478.869, - 400.324, - 87.414, - 428.963, - 745.825, - 92.98, - 472.896, - 694.586, - 748.2310000000001, - 713.09, - 437.523, - 764.94, - 332.492, - 277.565, - 489.478, - 670.676, - 0.539, - 520.781, - 604.425, - 459.595, - 242.446, - 294.92900000000003, - 506.919, - 735.304, - 743.893, - 734.935, - 429.073, - 686.868, - 449.244, - 496.354, - 749.7230000000001, - 343.789, - 637.33, - 694.1289999999999, - 493.321, - 542.346, - 652.674, - 297.01, - 779.3910000000001, - 522.323, - 777.525, - 710.893, - 701.8639999999999, - 787.699, - 772.801, - 209.441, - 441.564, - 530.724, - 719.74, - 780.085, - 366.344, - 173.46900000000002, - 117.848, - 392.154, - 244.229, - 139.776, - 302.818, - 287.271, - 276.992, - 487.24300000000005, - 345.826, - 189.864, - 171.68, - 183.274, - 669.6360000000001, - 481.616, - 322.54900000000004, - 327.664, - 342.63800000000003, - 760.75, - 727.63, - 464.263, - 342.20300000000003, - 469.301, - 245.286, - 337.93699999999995, - 754.166, - 549.674, - 462.309, - 472.444, - 365.133, - 252.724, - 225.263, - 274.349, - 214.858, - 223.105, - 224.834, - 206.639, - 246.69, - 255.95, - 316.405, - 217.974, - 263.416, - 152.29, - 255.928, - 247.285, - 163.333, - 117.617, - 149.746, - 111.032, - 202.097, - 197.973, - 152.84, - 186.252, - 199.74, - 134.722, - 194.565, - 197.71400000000003, - 204.145, - 195.788, - 191.268, - 199.79, - 204.172, - 111.979, - 156.143, - 207.261, - 120.424, - 127.747, - 205.235, - 142.116, - 159.92600000000002, - 170.49599999999998, - 145.232, - 234.617, - 157.013, - 87.98100000000001, - 201.458, - 244.984, - 259.36400000000003, - 293.249, - 194.967, - 315.832, - 325.505, - 304.056, - 186.935, - 355.218, - 116.609, - 325.687, - 391.05300000000005, - 342.644, - 341.185, - 382.062, - 395.914, - 280.323, - 396.519, - 245.22, - 386.549, - 331.86400000000003, - 300.291, - 268.828, - 168.97099999999998, - 329.06199999999995, - 173.19299999999998, - 347.25699999999995, - 271.795, - 333.004, - 252.493, - 315.183, - 262.194, - 160.316, - 293.404, - 205.295, - 326.463, - 194.455, - 105.819, - 100.286, - 121.19, - 255.246, - 334.584, - 245.402, - 187.051, - 189.291, - 245.171, - 324.531, - 334.523, - 337.414, - 341.141, - 343.18300000000005, - 151.491, - 209.551, - 358.461, - 356.809, - 352.091, - 352.994, - 347.092, - 347.852, - 381.253, - 379.249, - 362.122, - 347.896, - 364.638, - 92.385, - 372.037, - 303.159, - 173.838, - 165.359, - 353.577, - 177.22299999999998, - 79.707, - 370.622, - 373.562, - 228.539, - 390.364, - 203.385, - 238.851, - 340.486, - 461.461, - 0.506, - 279.926, - 456.677, - 268.42, - 415.26, - 514.406, - 251.998, - 612.8919999999999, - 648.126, - 632.04, - 379.249, - 64.815, - 40.932, - 614.643, - 382.271, - 2.648, - 72.318, - 694.702, - 693.948, - 221.597, - 637.259, - 663.564, - 705.6410000000001, - 522.433, - 706.819, - 620.214, - 754.815, - 580.4209999999999, - 735.2819999999999, - 571.739, - 87.87700000000001, - 411.318, - 659.908, - 368.304, - 375.351, - 647.422, - 673.181, - 627.09, - 657.172, - 451.854, - 412.601, - 734.682, - 630.8009999999999, - 432.651, - 561.719, - 512.3530000000001, - 656.2139999999999, - 750.0419999999999, - 468.59, - 485.894, - 544.3330000000001, - 499.2, - 517.511, - 351.832, - 727.685, - 740.727, - 572.064, - 559.556, - 456.291, - 565.826, - 561.78, - 438.878, - 529.81, - 657.832, - 597.681, - 619.245, - 585.5740000000001, - 610.2330000000001, - 705.977, - 628.797, - 513.3330000000001, - 615.568, - 728.7689999999999, - 773.181, - 676.209, - 715.171, - 506.352, - 713.679, - 607.645, - 425.235, - 583.339, - 644.482, - 771.992, - 508.372, - 454.59, - 613.387, - 480.009, - 601.556, - 120.232, - 45.21, - 588.388, - 566.977, - 792.8960000000001, - 403.875, - 785.888, - 776.655, - 770.1419999999999, - 767.747, - 766.3710000000001, - 762.9739999999999, - 764.6039999999999, - 760.6619999999999, - 754.8810000000001, - 753.956, - 749.6460000000001, - 738.365, - 739.2239999999999, - 744.2560000000001, - 574.4590000000001, - 474.712, - 323.199, - 507.332, - 410.321, - 560.607, - 507.959, - 705.817, - 680.2669999999999, - 530.851, - 415.689, - 521.86, - 554.612, - 577.118, - 426.799, - 390.1, - 444.961, - 480.119, - 570.082, - 601.2919999999999, - 681.5939999999999, - 680.2560000000001, - 700.2510000000001, - 688.784, - 685.684, - 689.466, - 697.0139999999999, - 678.813, - 659.842, - 666.8610000000001, - 622.268, - 366.284, - 573.1709999999999, - 577.112, - 590.391, - 582.3430000000001, - 558.493, - 559.242, - 282.018, - 121.096, - 108.109, - 97.17, - 99.559, - 103.451, - 109.221, - 118.74, - 122.687, - 130.934, - 137.656, - 144.395, - 160.608, - 185.267, - 180.229, - 170.512, - 153.622, - 146.905, - 150.44, - 160.151, - 157.327, - 179.84400000000002, - 197.891, - 182.019, - 173.672, - 173.166, - 175.01, - 191.945, - 225.44, - 235.124, - 214.93, - 195.452, - 258.945, - 214.754, - 235.377, - 216.697, - 262.265, - 260.66900000000004, - 309.672, - 267.837, - 229.062, - 149.917, - 130.929, - 104.751, - 93.993, - 84.226, - 75.528, - 71.217, - 70.045, - 78.171, - 101.91, - 114.594, - 152.047, - 327.019, - 341.945, - 346.404, - 349.514, - 329.546, - 343.403, - 325.79200000000003, - 307.327, - 334.68300000000005, - 331.622, - 327.074, - 319.642, - 315.546, - 304.045, - 305.697, - 302.064, - 300.819, - 294.802, - 291.185, - 287.28700000000003, - 284.573, - 282.497, - 279.007, - 278.335, - 273.887, - 227.834, - 164.011, - 93.784, - 80.863, - 79.013, - 78.016, - 77.851, - 75.792, - 70.259, - 67.551, - 63.697, - 62.453, - 61.787, - 64.655, - 64.704, - 65.805, - 66.565, - 69.164, - 69.786, - 69.51100000000001, - 66.384, - 66.21300000000001, - 65.756, - 65.304, - 67.028, - 67.529, - 64.578, - 61.016000000000005, - 58.538, - 58.373000000000005, - 55.989, - 53.914, - 54.927, - 55.00899999999999, - 55.235, - 53.363, - 49.113, - 44.857, - 41.268, - 38.295, - 34.755, - 30.45, - 27.499, - 24.57, - 23.546, - 20.854, - 19.984, - 17.419, - 15.046, - 13.521, - 12.227, - 10.333, - 7.542000000000001, - 5.989, - 3.749, - 0.947, - -0.848, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -1.724, - -1.234, - -0.05, - 1.2, - 3.072, - 3.963, - 5.263, - 6.122000000000001, - 7.685, - 9.425, - 11.253, - 12.475, - 14.611, - 17.022000000000002, - 18.718, - 21.278, - 23.199, - 25.556, - 26.959, - 29.112, - 31.011, - 33.604, - 35.861999999999995, - 37.926, - 40.448, - 42.782, - 45.573, - 55.153, - 69.654, - 81.36399999999999, - 87.095, - 54.211000000000006, - 99.482, - 100.423, - 99.24, - 103.517, - 110.74, - 115.26, - 118.409, - 121.184, - 127.526, - 133.351, - 138.135, - 142.82, - 146.86700000000002, - 151.244, - 157.178, - 163.488, - 169.808, - 173.16, - 180.626, - 187.056, - 193.31, - 193.095, - 199.796, - 206.418, - 210.124, - 215.723, - 217.099, - 225.489, - 228.864, - 235.481, - 240.778, - 246.008, - 247.39, - 254.128, - 259.055, - 262.744, - 268.85, - 274.41, - 278.297, - 285.267, - 287.827, - 295.215, - 299.856, - 302.23400000000004, - 309.892, - 314.621, - 317.44, - 324.019, - 330.642, - 331.875, - 339.731, - 342.62699999999995, - 346.481, - 350.742, - 356.782, - 364.467, - 369.158, - 371.195, - 377.24, - 379.067, - 384.787, - 390.557, - 394.394, - 399.459, - 399.878, - 410.041, - 415.084, - 417.154, - 421.751, - 426.909, - 432.326, - 436.076, - 439.94, - 446.211, - 451.937, - 456.407, - 461.61, - 463.669, - 468.612, - 471.706, - 478.296, - 480.086, - 481.941, - 488.652, - 493.249, - 499.69, - 504.92, - 510.327, - 512.226, - 518.3430000000001, - 519.24, - 519.95, - 524.58, - 527.41, - 531.423, - 537.876, - 541.961, - 543.232, - 549.547, - 553.748, - 556.721, - 559.457, - 561.549, - 565.678, - 571.018, - 575.279, - 579.172, - 585.007, - 588.85, - 592.2909999999999, - 592.484, - 599.475, - 602.933, - 607.5409999999999, - 611.576, - 615.832, - 614.643, - 623.391, - 624.674, - 629.8430000000001, - 631.236, - 637.975, - 640.595, - 642.654, - 644.719, - 646.943, - 650.764, - 653.23, - 657.7, - 660.431, - 664.18, - 669.058, - 667.434, - 668.821, - 675.0039999999999, - 678.252, - 681.1419999999999, - 684.534, - 688.674, - 696.695, - 697.686, - 701.341, - 702.707, - 705.426, - 707.293, - 708.262, - 715.21, - 718.7719999999999, - 718.799, - 722.6310000000001, - 725.9010000000001, - 723.291, - 729.0060000000001, - 734.077, - 735.04, - 736.5319999999999, - 745.318, - 741.426, - 738.029, - 755.674, - 753.345, - 754.8480000000001, - 755.977, - 760.513, - 759.913, - 760.2330000000001, - 764.301, - 764.6310000000001, - 772.047, - 774.007, - 775.565, - 775.8510000000001, - 779.59, - 781.5110000000001, - 784.148, - 788.178, - 791.558, - 793.81, - 794.3, - 796.497, - 798.418, - 799.8660000000001, - 786.967, - 782.7439999999999, - 733.3660000000001, - 790.253, - 783.405, - 773.6110000000001, - 741.7289999999999, - 730.6360000000001, - 744.2610000000001, - 735.436, - 725.538, - 714.428, - 706.302, - 687.826, - 671.3539999999999, - 649.106, - 628.4169999999999, - 630.014, - 630.129, - 608.818, - 606.153, - 612.975, - 617.219, - 616.003, - 620.891, - 620.082, - 615.8919999999999, - 584.633, - 586.362, - 572.5930000000001, - 555.085, - 545.561, - 554.111, - 573.8480000000001, - 594.306, - 596.937, - 597.169, - 593.364, - 613.4590000000001, - 608.592, - 602.993, - 615.16, - 602.371, - 587.732, - 582.117, - 594.493, - 613.58, - 624.756, - 641.614, - 646.827, - 637.804, - 630.179, - 624.442, - 599.239, - 588.977, - 581.831, - 576.033, - 574.2, - 517.9630000000001, - 499.189, - 507.425, - 484.209, - 473.022, - 474.955, - 494.647, - 497.119, - 514.406, - 498.055, - 466.174, - 441.8730000000001, - 432.734, - 410.426, - 409.655, - 407.057, - 409.782, - 400.412, - 421.712, - 450.23, - 458.48800000000006, - 452.316, - 439.483, - 446.1830000000001, - 440.832, - 451.667, - 448.776, - 456.104, - 465.205, - 476.05, - 477.019, - 474.305, - 461.048, - 458.708, - 453.186, - 466.796, - 453.572, - 447.697, - 411.048, - 394.009, - 409.496, - 425.461, - 440.15, - 440.882, - 453.643, - 433.653, - 427.443, - 428.875, - 469.102, - 476.369, - 451.821, - 377.685, - 329.045, - 299.696, - 298.232, - 321.949, - 320.683, - 341.686, - 368.233, - 332.861, - 304.992, - 301.596, - 306.099, - 281.193, - 227.675, - 219.846, - 226.425, - 229.662, - 224.052, - 212.843, - 195.391, - 182.591, - 180.169, - 182.988, - 189.495, - 191.526, - 196.729, - 191.488, - 191.807, - 196.195, - 203.936, - 198.282, - 194.527, - 193.69, - 199.906, - 211.456, - 215.293, - 216.763, - 227.603, - 239.924, - 241.956, - 234.259, - 247.004, - 236.924, - 238.553, - 243.398, - 240.122, - 215.888, - 200.385, - 181.639, - 168.773, - 160.878, - 154.558, - 146.641, - 139.649, - 133.329, - 127.587, - 118.228, - 111.5, - 110.707, - 108.665, - 105.252, - 102.224, - 105.108, - 105.67, - 103.638, - 105.571, - 103.941, - 101.701, - 108.065, - 113.625, - 116.064, - 119.257, - 118.498, - 119.197, - 120.38, - 123.673, - 123.717, - 124.834, - 117.424, - 123.227, - 135.977, - 153.875, - 136.792, - 138.355, - 128.446, - 124.135, - 121.135, - 124.344, - 135.05200000000002, - 147.357, - 153.363, - 137.062, - 155.14700000000002, - 169.62599999999998, - 134.41899999999998, - 107.514, - 95.38, - 90.662, - 87.965, - 82.26100000000001, - 79.22800000000001, - 74.796, - 68.294, - 62.337, - 56.25899999999999, - 50.891000000000005, - 47.985, - 46.085, - 44.246, - 44.081, - 42.975, - 42.815, - 42.253, - 40.53, - 39.512, - 39.126, - 37.216, - 35.652, - 33.869, - 30.962, - 28.495, - 25.6, - 23.007, - 19.802, - 17.573, - 16.692, - 13.906, - 12.618, - 12.029000000000002, - 11.324000000000002, - 10.603, - 9.882, - 9.194, - 9.072, - 6.722, - 5.307, - 4.652, - 3.848, - 2.8510000000000004, - 2.741, - 2.196, - 0.836, - -0.204, - -1.294, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - -2.048, - -1.509, - -0.92, - -0.8320000000000001, - -0.193, - 0.765, - 2.813, - 3.518, - 4.475, - 5.555, - 5.874, - 7.124, - 9.766, - 11.363, - 14.831, - 18.415, - 20.755, - 21.845, - 24.372, - 26.932, - 30.092, - 34.926, - 38.774, - 41.708, - 43.993, - 45.893, - 56.347, - 68.542, - 82.652, - 83.73100000000001, - 60.493, - 101.486, - 101.838, - 105.45, - 104.921, - 101.178, - 98.194, - 111.621, - 122.77, - 129.563, - 133.241, - 129.613, - 136.858, - 154.035, - 165.101, - 174.741, - 186.412, - 187.205, - 189.181, - 188.724, - 192.457, - 189.445, - 183.923, - 180.075, - 179.106, - 169.72, - 172.313, - 178.53400000000002, - 174.201, - 154.72299999999998, - 169.951, - 194.956, - 227.719, - 252.427, - 236.054, - 227.477, - 251.761, - 225.032, - 180.747, - 181.853, - 244.956, - 247.566, - 253.699, - 277.768, - 256.677, - 225.665, - 242.611, - 249.052, - 250.324, - 237.788, - 225.61, - 266.813, - 308.048, - 259.342, - 289.533, - 316.35, - 258.428, - 241.031, - 305.703, - 326.535, - 343.673, - 278.908, - 266.185, - 254.249, - 317.335, - 293.558, - 289.78700000000003, - 238.647, - 296.536, - 333.059, - 278.809, - 232.228, - 266.741, - 311.736, - 375.687, - 357.844, - 310.228, - 368.574, - 300.10900000000004, - 273.518, - 332.96, - 394.785, - 392.798, - 323.80400000000003, - 474.619, - 447.351, - 481.627, - 478.588, - 516.311, - 518.766, - 523.991, - 521.96, - 513.894, - 524.266, - 536.494, - 533.758, - 526.1709999999999, - 530.955, - 526.865, - 545.9580000000001, - 558.736, - 552.085, - 551.133, - 558.802, - 549.635, - 585.161, - 601.248, - 583.4159999999999, - 557.37, - 588.2330000000001, - 594.5369999999999, - 580.14, - 565.359, - 612.975, - 569.322, - 489.28, - 398.353, - 391.086, - 400.395, - 461.593, - 477.11300000000006, - 420.666, - 325.726, - 419.659, - 474.861, - 308.428, - 557.26, - 662.633, - 668.7660000000001, - 672.163, - 710.447, - 701.6439999999999, - 708.025, - 703.5, - 699.6460000000001, - 703.015, - 720.919, - 720.842, - 713.2719999999999, - 716.927, - 712.919, - 715.4739999999999, - 715.584, - 722.5319999999999, - 730.68, - 750.1080000000001, - 687.4789999999999, - 721.7439999999999, - 712.457, - 728.202, - 727.0239999999999, - 749.1389999999999, - 775.18, - 757.0060000000001, - 771.684, - 772.488, - 793.485, - 797.053, - 796.1, - 590.909, - 478.225, - 691.173, - 792.362, - 789.664, - 795.175, - 762.33, - 509.859, - 753.367, - 487.595, - 521.519, - 797.5980000000001, - 795.23, - 584.82, - 521.602, - 701.6110000000001, - 698.2919999999999, - 755.96, - 753.4830000000001, - 317.743, - 684.148, - 693.32, - 782.8380000000001, - 720.451, - 545.754, - 769.5310000000001, - 523.011, - 793.678, - 617.654, - 597.559, - 362.73800000000006, - 797.878, - 790.342, - 748.567, - 767.2239999999999, - 795.258, - 701.98, - 796.909, - 791.784, - 581.864, - 730.173, - 699.635, - 728.654, - 586.571, - 794.8610000000001, - 559.451, - 632.535, - 673.1210000000001, - 501.777, - 787.908, - 544.1519999999999, - 743.21, - 539.637, - 657.832, - 679.628, - 716.547, - 740.3969999999999, - 556.115, - 389.027, - 621.354, - 701.633, - 693.188, - 601.1659999999999, - 281.765, - 389.379, - 497.191, - 654.981, - 703.56, - 577.993, - 346.431, - 630.206, - 664.8960000000001, - 625.461, - 525.246, - 600.026, - 436.577, - 547.5319999999999, - 513.492, - 214.682, - 423.71, - 608.895, - 371.685, - 272.527, - 229.624, - 353.176, - 501.942, - 501.491, - 399.151, - 573.193, - 622.378, - 634.7040000000001, - 623.611, - 607.695, - 346.338, - 589.268, - 585.932, - 590.948, - 583.279, - 570.539, - 572.279, - 573.215, - 567.368, - 565.039, - 565.502, - 562.419, - 516.465, - 559.677, - 561.697, - 388.11300000000006, - 125.28, - 104.624, - 124.95, - 413.382, - 260.784, - 202.845, - 211.687, - 233.076, - 137.998, - 250.159, - 346.547, - 379.348, - 368.348, - 130.582, - 166.114, - 110.746, - 125.038, - 131.87, - 130.417, - 284.358, - 177.03599999999997, - 151.689, - 163.565, - 181.039, - 302.476, - 355.031, - 420.049, - 289.82, - 120.711, - 95.001, - 87.656, - 93.195, - 84.78299999999999, - 86.164, - 91.642, - 102.581, - 113.339, - 119.351, - 133.918, - 170.30900000000003, - 143.05200000000002, - 112.139, - 103.264, - 103.093, - 105.042, - 104.222, - 104.503, - 100.671, - 97.401, - 98.64, - 97.456, - 88.311, - 86.79799999999999, - 87.833, - 92.958, - 94.411, - 96.575, - 102.758, - 103.06, - 99.262, - 97.863, - 94.45, - 133.357, - 208.698, - 224.014, - 286.362, - 175.054, - 78.985, - 70.342, - 71.34899999999999, - 91.494, - 117.952, - 55.615, - 49.911, - 48.32, - 47.621, - 52.24, - 67.749, - 141.30100000000002, - 150.236, - 109.816, - 65.932, - 59.474, - 59.276, - 57.426, - 54.949, - 49.003, - 45.7, - 41.38399999999999, - 37.513000000000005, - 35.151, - 30.824, - 29.272, - 27.482, - 26.007, - 24.84, - 23.331, - 19.918, - 17.066, - 17.408, - 19.092, - 19.054, - 18.52, - 18.503, - 17.066, - 15.712, - 14.154000000000002, - 12.144, - 10.284, - 8.709, - 8.34, - 8.252, - 6.077999999999999, - 5.114, - 4.74, - 4.938, - 4.999, - 5.362, - 5.676, - 5.757999999999999, - 5.604, - 4.756, - 4.531000000000001, - 3.248, - 2.725, - 1.348, - 0.0819999999999999, - -1.663, - -1.3769999999999998, - -1.558, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null, - null - ], + "y": { + "bdata": "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", + "dtype": "f8" + }, "yaxis": "y" }, { @@ -91378,963 +47180,10 @@ "2010-03-07T14:36:00-07:00" ], "xaxis": "x", - "y": [ - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 798.7539999999999, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 257.222, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 253.379, - 800, - 800, - 800, - 800, - 800, - 253.682, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 745.39, - 746.596, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 745.17, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 798.132, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 746.095, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800, - 800 - ], + "y": { + "bdata": "AAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAeOkmMQj2iEAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAZDvfT40TcEAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQOOlm8QgrG9AAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQOf7qfHStW9AAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUCF61G4HkuHQFTjpZvEVIdAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQI/C9ShcSYdAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUCTGARWDvGIQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlA9ihcj8JQh0AAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUAAAAAAAACJQAAAAAAAAIlAAAAAAAAAiUA=", + "dtype": "f8" + }, "yaxis": "y" } ], @@ -92424,7 +47273,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -92460,7 +47309,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -92484,7 +47333,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -92520,64 +47369,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "type": "heatmap" } ], - "heatmapgl": [ - { - "colorbar": { - "outlinewidth": 0, - "ticks": "" - }, - "colorscale": [ - [ - 0, - "#0d0887" - ], - [ - 0.1111111111111111, - "#46039f" - ], - [ - 0.2222222222222222, - "#7201a8" - ], - [ - 0.3333333333333333, - "#9c179e" - ], - [ - 0.4444444444444444, - "#bd3786" - ], - [ - 0.5555555555555556, - "#d8576b" - ], - [ - 0.6666666666666666, - "#ed7953" - ], - [ - 0.7777777777777778, - "#fb9f3a" - ], - [ - 0.8888888888888888, - "#fdca26" - ], - [ - 1, - "#f0f921" - ] - ], - "type": "heatmapgl" - } - ], "histogram": [ { "marker": { @@ -92598,7 +47396,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -92634,7 +47432,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -92649,7 +47447,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -92685,7 +47483,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -92778,6 +47576,17 @@ "type": "scattergl" } ], + "scattermap": [ + { + "marker": { + "colorbar": { + "outlinewidth": 0, + "ticks": "" + } + }, + "type": "scattermap" + } + ], "scattermapbox": [ { "marker": { @@ -92830,7 +47639,7 @@ }, "colorscale": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -92866,7 +47675,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], @@ -92957,7 +47766,7 @@ ], "sequential": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -92993,13 +47802,13 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ], "sequentialminus": [ [ - 0, + 0.0, "#0d0887" ], [ @@ -93035,7 +47844,7 @@ "#fdca26" ], [ - 1, + 1.0, "#f0f921" ] ] @@ -93167,8 +47976,8 @@ "xaxis": { "anchor": "y", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "datetime" @@ -93177,42 +47986,15 @@ "yaxis": { "anchor": "x", "domain": [ - 0, - 1 + 0.0, + 1.0 ], "title": { "text": "ac_power" } } } - }, - "text/html": [ - "
" - ] + } }, "metadata": {}, "output_type": "display_data" @@ -93237,16 +48019,16 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:15.931724Z", - "iopub.status.busy": "2026-02-04T19:31:15.931724Z", - "iopub.status.idle": "2026-02-04T19:31:16.272228Z", - "shell.execute_reply": "2026-02-04T19:31:16.271164Z" + "iopub.execute_input": "2026-03-20T15:45:34.433116Z", + "iopub.status.busy": "2026-03-20T15:45:34.432647Z", + "iopub.status.idle": "2026-03-20T15:45:34.674717Z", + "shell.execute_reply": "2026-03-20T15:45:34.672917Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -93281,10 +48063,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:16.277304Z", - "iopub.status.busy": "2026-02-04T19:31:16.276756Z", - "iopub.status.idle": "2026-02-04T19:31:16.331817Z", - "shell.execute_reply": "2026-02-04T19:31:16.331264Z" + "iopub.execute_input": "2026-03-20T15:45:34.678637Z", + "iopub.status.busy": "2026-03-20T15:45:34.678152Z", + "iopub.status.idle": "2026-03-20T15:45:34.760162Z", + "shell.execute_reply": "2026-03-20T15:45:34.757983Z" } }, "outputs": [], @@ -93307,10 +48089,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:16.336479Z", - "iopub.status.busy": "2026-02-04T19:31:16.336479Z", - "iopub.status.idle": "2026-02-04T19:31:17.465298Z", - "shell.execute_reply": "2026-02-04T19:31:17.465298Z" + "iopub.execute_input": "2026-03-20T15:45:34.764365Z", + "iopub.status.busy": "2026-03-20T15:45:34.763720Z", + "iopub.status.idle": "2026-03-20T15:45:35.741155Z", + "shell.execute_reply": "2026-03-20T15:45:35.739807Z" }, "tags": [ "nbsphinx-thumbnail" @@ -93319,7 +48101,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -93359,10 +48141,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:17.469307Z", - "iopub.status.busy": "2026-02-04T19:31:17.469307Z", - "iopub.status.idle": "2026-02-04T19:31:17.474261Z", - "shell.execute_reply": "2026-02-04T19:31:17.474261Z" + "iopub.execute_input": "2026-03-20T15:45:35.744917Z", + "iopub.status.busy": "2026-03-20T15:45:35.744338Z", + "iopub.status.idle": "2026-03-20T15:45:35.751993Z", + "shell.execute_reply": "2026-03-20T15:45:35.750200Z" } }, "outputs": [ @@ -93383,10 +48165,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:17.477269Z", - "iopub.status.busy": "2026-02-04T19:31:17.477269Z", - "iopub.status.idle": "2026-02-04T19:31:17.481848Z", - "shell.execute_reply": "2026-02-04T19:31:17.481848Z" + "iopub.execute_input": "2026-03-20T15:45:35.756334Z", + "iopub.status.busy": "2026-03-20T15:45:35.755731Z", + "iopub.status.idle": "2026-03-20T15:45:35.762853Z", + "shell.execute_reply": "2026-03-20T15:45:35.761206Z" } }, "outputs": [ @@ -93420,10 +48202,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:17.485857Z", - "iopub.status.busy": "2026-02-04T19:31:17.484864Z", - "iopub.status.idle": "2026-02-04T19:32:02.443094Z", - "shell.execute_reply": "2026-02-04T19:32:02.442084Z" + "iopub.execute_input": "2026-03-20T15:45:35.766733Z", + "iopub.status.busy": "2026-03-20T15:45:35.766272Z", + "iopub.status.idle": "2026-03-20T15:46:17.789141Z", + "shell.execute_reply": "2026-03-20T15:46:17.787318Z" } }, "outputs": [ @@ -93431,10 +48213,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\soiling.py:27: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\2847556095.py:8: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " from rdtools.soiling import soiling_srr\n" ] } ], @@ -93457,10 +48237,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:02.449095Z", - "iopub.status.busy": "2026-02-04T19:32:02.449095Z", - "iopub.status.idle": "2026-02-04T19:32:02.457295Z", - "shell.execute_reply": "2026-02-04T19:32:02.456285Z" + "iopub.execute_input": "2026-03-20T15:46:17.792470Z", + "iopub.status.busy": "2026-03-20T15:46:17.791988Z", + "iopub.status.idle": "2026-03-20T15:46:17.799026Z", + "shell.execute_reply": "2026-03-20T15:46:17.797692Z" } }, "outputs": [ @@ -93481,10 +48261,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:02.462291Z", - "iopub.status.busy": "2026-02-04T19:32:02.461299Z", - "iopub.status.idle": "2026-02-04T19:32:02.467436Z", - "shell.execute_reply": "2026-02-04T19:32:02.467436Z" + "iopub.execute_input": "2026-03-20T15:46:17.801747Z", + "iopub.status.busy": "2026-03-20T15:46:17.801414Z", + "iopub.status.idle": "2026-03-20T15:46:17.806438Z", + "shell.execute_reply": "2026-03-20T15:46:17.805299Z" } }, "outputs": [ @@ -93506,10 +48286,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:02.473443Z", - "iopub.status.busy": "2026-02-04T19:32:02.472441Z", - "iopub.status.idle": "2026-02-04T19:32:13.806873Z", - "shell.execute_reply": "2026-02-04T19:32:13.806873Z" + "iopub.execute_input": "2026-03-20T15:46:17.808838Z", + "iopub.status.busy": "2026-03-20T15:46:17.808515Z", + "iopub.status.idle": "2026-03-20T15:46:28.311846Z", + "shell.execute_reply": "2026-03-20T15:46:28.310459Z" } }, "outputs": [ @@ -93517,15 +48297,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\plotting.py:173: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\3529624818.py:2: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " fig = rdtools.plotting.soiling_monte_carlo_plot(soiling_info, daily, profiles=200)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -93545,10 +48323,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:13.810883Z", - "iopub.status.busy": "2026-02-04T19:32:13.809883Z", - "iopub.status.idle": "2026-02-04T19:32:14.037492Z", - "shell.execute_reply": "2026-02-04T19:32:14.037492Z" + "iopub.execute_input": "2026-03-20T15:46:28.315914Z", + "iopub.status.busy": "2026-03-20T15:46:28.315366Z", + "iopub.status.idle": "2026-03-20T15:46:28.554677Z", + "shell.execute_reply": "2026-03-20T15:46:28.552355Z" } }, "outputs": [ @@ -93556,15 +48334,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\plotting.py:233: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\476338665.py:3: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " fig = rdtools.plotting.soiling_interval_plot(soiling_info, daily)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -93585,10 +48361,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.040511Z", - "iopub.status.busy": "2026-02-04T19:32:14.040511Z", - "iopub.status.idle": "2026-02-04T19:32:14.055614Z", - "shell.execute_reply": "2026-02-04T19:32:14.055614Z" + "iopub.execute_input": "2026-03-20T15:46:28.559543Z", + "iopub.status.busy": "2026-03-20T15:46:28.558578Z", + "iopub.status.idle": "2026-03-20T15:46:28.579159Z", + "shell.execute_reply": "2026-03-20T15:46:28.577403Z" } }, "outputs": [ @@ -93728,10 +48504,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.059622Z", - "iopub.status.busy": "2026-02-04T19:32:14.059622Z", - "iopub.status.idle": "2026-02-04T19:32:14.189628Z", - "shell.execute_reply": "2026-02-04T19:32:14.189123Z" + "iopub.execute_input": "2026-03-20T15:46:28.583419Z", + "iopub.status.busy": "2026-03-20T15:46:28.583036Z", + "iopub.status.idle": "2026-03-20T15:46:28.726081Z", + "shell.execute_reply": "2026-03-20T15:46:28.724330Z" } }, "outputs": [ @@ -93739,15 +48515,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\plotting.py:273: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\2137372672.py:2: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " fig = rdtools.plotting.soiling_rate_histogram(soiling_info, bins=50)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -93774,10 +48548,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.193634Z", - "iopub.status.busy": "2026-02-04T19:32:14.192634Z", - "iopub.status.idle": "2026-02-04T19:32:14.431183Z", - "shell.execute_reply": "2026-02-04T19:32:14.431183Z" + "iopub.execute_input": "2026-03-20T15:46:28.731338Z", + "iopub.status.busy": "2026-03-20T15:46:28.730759Z", + "iopub.status.idle": "2026-03-20T15:46:28.979829Z", + "shell.execute_reply": "2026-03-20T15:46:28.978513Z" } }, "outputs": [ @@ -93957,10 +48731,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.434192Z", - "iopub.status.busy": "2026-02-04T19:32:14.434192Z", - "iopub.status.idle": "2026-02-04T19:32:14.584214Z", - "shell.execute_reply": "2026-02-04T19:32:14.584214Z" + "iopub.execute_input": "2026-03-20T15:46:28.984212Z", + "iopub.status.busy": "2026-03-20T15:46:28.983560Z", + "iopub.status.idle": "2026-03-20T15:46:29.274678Z", + "shell.execute_reply": "2026-03-20T15:46:29.273085Z" } }, "outputs": [ @@ -94095,10 +48869,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.588233Z", - "iopub.status.busy": "2026-02-04T19:32:14.588233Z", - "iopub.status.idle": "2026-02-04T19:32:14.593665Z", - "shell.execute_reply": "2026-02-04T19:32:14.592648Z" + "iopub.execute_input": "2026-03-20T15:46:29.277515Z", + "iopub.status.busy": "2026-03-20T15:46:29.277002Z", + "iopub.status.idle": "2026-03-20T15:46:29.283797Z", + "shell.execute_reply": "2026-03-20T15:46:29.281735Z" } }, "outputs": [], @@ -94120,10 +48894,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.596664Z", - "iopub.status.busy": "2026-02-04T19:32:14.596664Z", - "iopub.status.idle": "2026-02-04T19:33:20.336974Z", - "shell.execute_reply": "2026-02-04T19:33:20.336974Z" + "iopub.execute_input": "2026-03-20T15:46:29.287390Z", + "iopub.status.busy": "2026-03-20T15:46:29.287044Z", + "iopub.status.idle": "2026-03-20T15:47:33.926072Z", + "shell.execute_reply": "2026-03-20T15:47:33.924844Z" } }, "outputs": [], @@ -94136,10 +48910,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:33:20.340994Z", - "iopub.status.busy": "2026-02-04T19:33:20.340994Z", - "iopub.status.idle": "2026-02-04T19:33:22.719457Z", - "shell.execute_reply": "2026-02-04T19:33:22.719457Z" + "iopub.execute_input": "2026-03-20T15:47:33.930049Z", + "iopub.status.busy": "2026-03-20T15:47:33.929611Z", + "iopub.status.idle": "2026-03-20T15:47:36.288210Z", + "shell.execute_reply": "2026-03-20T15:47:36.286410Z" } }, "outputs": [ @@ -94274,10 +49048,10 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:33:22.724543Z", - "iopub.status.busy": "2026-02-04T19:33:22.723543Z", - "iopub.status.idle": "2026-02-04T19:33:22.729988Z", - "shell.execute_reply": "2026-02-04T19:33:22.729468Z" + "iopub.execute_input": "2026-03-20T15:47:36.292378Z", + "iopub.status.busy": "2026-03-20T15:47:36.291795Z", + "iopub.status.idle": "2026-03-20T15:47:36.303433Z", + "shell.execute_reply": "2026-03-20T15:47:36.300670Z" } }, "outputs": [ @@ -94307,16 +49081,16 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:33:22.733003Z", - "iopub.status.busy": "2026-02-04T19:33:22.733003Z", - "iopub.status.idle": "2026-02-04T19:33:23.599906Z", - "shell.execute_reply": "2026-02-04T19:33:23.599906Z" + "iopub.execute_input": "2026-03-20T15:47:36.310169Z", + "iopub.status.busy": "2026-03-20T15:47:36.309336Z", + "iopub.status.idle": "2026-03-20T15:47:36.973775Z", + "shell.execute_reply": "2026-03-20T15:47:36.972458Z" } }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -94385,7 +49159,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, From 98907c1a44db5a879edf800c8fc94d897c124ef6 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 12:02:05 -0400 Subject: [PATCH 13/18] sanitize filterpy SyntaxWarning --- docs/nbval_sanitization_rules.cfg | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/docs/nbval_sanitization_rules.cfg b/docs/nbval_sanitization_rules.cfg index 1e58909e9..1ab555c1a 100644 --- a/docs/nbval_sanitization_rules.cfg +++ b/docs/nbval_sanitization_rules.cfg @@ -18,10 +18,21 @@ replace: NBVAL-FILEPATH: UserWarning: regex: ^\s*File ".*", line \d+.*$ replace: CODE-LINE +# filterpy emits a SyntaxWarning for invalid escape sequences in Python 3.13+. +# This warning only appears on first compilation (no cached .pyc), so it shows +# up in CI but not locally. Strip it from the comparison. [regex3] +regex: .*SyntaxWarning: invalid escape sequence.*\n? +replace: + +[regex4] +regex: \s*P = \\Sum \{A\[i\] B\[i\]\.T\} for i in 0\.\.N\n? +replace: + +[regex5] regex: \d{1,2}/\d{1,2}/\d{2,4} replace: DATE-STAMP -[regex4] +[regex6] regex: \d{2}:\d{2}:\d{2} replace: TIME-STAMP From e7b957b4aa64ed493005a85fece853ddf300ae17 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 15:14:28 -0400 Subject: [PATCH 14/18] replace unmaintained filterpy package with drop in replacement bayesian-filters --- docs/nbval_sanitization_rules.cfg | 13 +- docs/sphinx/source/changelog/v3.2.1.rst | 3 + pixi.lock | 952 ++++++++++++------------ pyproject.toml | 4 +- 4 files changed, 481 insertions(+), 491 deletions(-) diff --git a/docs/nbval_sanitization_rules.cfg b/docs/nbval_sanitization_rules.cfg index 1ab555c1a..1e58909e9 100644 --- a/docs/nbval_sanitization_rules.cfg +++ b/docs/nbval_sanitization_rules.cfg @@ -18,21 +18,10 @@ replace: NBVAL-FILEPATH: UserWarning: regex: ^\s*File ".*", line \d+.*$ replace: CODE-LINE -# filterpy emits a SyntaxWarning for invalid escape sequences in Python 3.13+. -# This warning only appears on first compilation (no cached .pyc), so it shows -# up in CI but not locally. Strip it from the comparison. [regex3] -regex: .*SyntaxWarning: invalid escape sequence.*\n? -replace: - -[regex4] -regex: \s*P = \\Sum \{A\[i\] B\[i\]\.T\} for i in 0\.\.N\n? -replace: - -[regex5] regex: \d{1,2}/\d{1,2}/\d{2,4} replace: DATE-STAMP -[regex6] +[regex4] regex: \d{2}:\d{2}:\d{2} replace: TIME-STAMP diff --git a/docs/sphinx/source/changelog/v3.2.1.rst b/docs/sphinx/source/changelog/v3.2.1.rst index 816b33b07..c94fb25bd 100644 --- a/docs/sphinx/source/changelog/v3.2.1.rst +++ b/docs/sphinx/source/changelog/v3.2.1.rst @@ -43,6 +43,9 @@ Bug Fixes Requirements ------------ +* Replaced the unmaintained ``filterpy`` dependency with its maintained fork + ``bayesian-filters``, which provides the same API and fixes + ``SyntaxWarning`` on Python 3.13+. (:pull:`494`) * Added ``llvm-openmp`` (the conda-forge name for libomp) as a platform-specific conda dependency for macOS (osx-64 and osx-arm64) to fix XGBoost installation issues. Users no longer need to install libomp via Homebrew. (:pull:`493`) diff --git a/pixi.lock b/pixi.lock index 1d6c91ef4..c4aca624a 100644 --- a/pixi.lock +++ b/pixi.lock @@ -12,7 +12,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -33,12 +33,12 @@ environments: - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda - pypi: https://files.pythonhosted.org/packages/d6/40/7b7ac152c35c32da2a00ba3523ea84c358478b12ee7b3b2b6892e5b9d81b/arch-8.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2b/58/a199d245894b12db0b957d627516c78e055adc3a0d978bc7f65ddaf7c399/charset_normalizer-3.4.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e2/98/8b1e801939839d405f1f122e7d175cebe9aeb4e114f95bfc45e3152af9a7/fonttools-4.62.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl @@ -83,12 +83,12 @@ environments: - conda: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h7142dee_3.conda - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda - pypi: https://files.pythonhosted.org/packages/d6/51/78f84f9e486e173356931b2bfaf0c2a6d6923f1e8975045e3416ac388215/arch-8.0.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/c5/0e3966edd5ec668d41dfe418787726752bc07e2f5fd8c8f208615e61fa89/fonttools-4.62.1-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl @@ -117,7 +117,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -133,12 +133,12 @@ environments: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-h010d191_3.conda - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda - pypi: https://files.pythonhosted.org/packages/cb/b8/73910773efffc2d35d2739be1bdc70dfcc58a83cff35c4d62e14acceca2b/arch-8.0.0-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/3b/56/6f389de21c49555553d6a5aeed5ac9767631497ac836c4f076273d15bd72/fonttools-4.62.1-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl @@ -183,12 +183,12 @@ environments: - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.44.35208-h818238b_34.conda - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda - pypi: https://files.pythonhosted.org/packages/f1/e7/2d15374129c03b6f97321f837190cb19863204dbcff289e23cc37f035c96/arch-8.0.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a1/5c/724b6b363603e419829f561c854b87ed7c7e31231a7908708ac086cdf3e2/charset_normalizer-3.4.6-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/38/60/35186529de1db3c01f5ad625bde07c1f576305eab6d86bbda4c58445f721/fonttools-4.62.1-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl @@ -227,7 +227,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -253,14 +253,15 @@ environments: - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2b/58/a199d245894b12db0b957d627516c78e055adc3a0d978bc7f65ddaf7c399/charset_normalizer-3.4.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl @@ -269,8 +270,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e2/98/8b1e801939839d405f1f122e7d175cebe9aeb4e114f95bfc45e3152af9a7/fonttools-4.62.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl @@ -297,7 +297,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -313,7 +313,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/fc/f9/c9457652dfe28e2eb898372da2fe786c6db81af9540c0f853ee04a0699cc/numexpr-2.14.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl @@ -396,14 +396,15 @@ environments: - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl @@ -412,8 +413,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/c5/0e3966edd5ec668d41dfe418787726752bc07e2f5fd8c8f208615e61fa89/fonttools-4.62.1-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl @@ -440,7 +440,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -456,7 +456,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/73/b4/9f6d637fd79df42be1be29ee7ba1f050fab63b7182cb922a0e08adc12320/numexpr-2.14.1-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl @@ -517,7 +517,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -539,14 +539,15 @@ environments: - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl @@ -555,8 +556,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/3b/56/6f389de21c49555553d6a5aeed5ac9767631497ac836c4f076273d15bd72/fonttools-4.62.1-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl @@ -583,7 +583,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -599,7 +599,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/35/ae/d58558d8043de0c49f385ea2fa789e3cfe4d436c96be80200c5292f45f15/numexpr-2.14.1-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl @@ -681,14 +681,15 @@ environments: - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a1/5c/724b6b363603e419829f561c854b87ed7c7e31231a7908708ac086cdf3e2/charset_normalizer-3.4.6-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl @@ -698,8 +699,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/38/60/35186529de1db3c01f5ad625bde07c1f576305eab6d86bbda4c58445f721/fonttools-4.62.1-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl @@ -726,7 +726,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -742,7 +742,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cc/23/9281bceaeb282cead95f0aa5f7f222ffc895670ea689cc1398355f6e3001/numexpr-2.14.1-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl @@ -811,7 +811,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -837,26 +837,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2b/58/a199d245894b12db0b957d627516c78e055adc3a0d978bc7f65ddaf7c399/charset_normalizer-3.4.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/e4/dc/b2442d10020c2f52617828862d8b6ee337859cd8f3a1f13d607dddda9cf7/coverage-7.13.4-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ac/68/1666e3a4462f8202d836920114fa7a5ee9275d1fa45366d336c551a162dd/coverage-7.13.5-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e2/98/8b1e801939839d405f1f122e7d175cebe9aeb4e114f95bfc45e3152af9a7/fonttools-4.62.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl @@ -884,7 +884,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -902,7 +902,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/fc/f9/c9457652dfe28e2eb898372da2fe786c6db81af9540c0f853ee04a0699cc/numexpr-2.14.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl @@ -991,26 +991,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/db/23/aad45061a31677d68e47499197a131eea55da4875d16c1f42021ab963503/coverage-7.13.4-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/74/8c/74fedc9663dcf168b0a059d4ea756ecae4da77a489048f94b5f512a8d0b3/coverage-7.13.5-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/c5/0e3966edd5ec668d41dfe418787726752bc07e2f5fd8c8f208615e61fa89/fonttools-4.62.1-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl @@ -1038,7 +1038,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -1056,7 +1056,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/73/b4/9f6d637fd79df42be1be29ee7ba1f050fab63b7182cb922a0e08adc12320/numexpr-2.14.1-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl @@ -1123,7 +1123,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -1145,26 +1145,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/a5/70/9b8b67a0945f3dfec1fd896c5cefb7c19d5a3a6d74630b99a895170999ae/coverage-7.13.4-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/0c/c9/44fb661c55062f0818a6ffd2685c67aa30816200d5f2817543717d4b92eb/coverage-7.13.5-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/3b/56/6f389de21c49555553d6a5aeed5ac9767631497ac836c4f076273d15bd72/fonttools-4.62.1-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl @@ -1192,7 +1192,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -1210,7 +1210,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/35/ae/d58558d8043de0c49f385ea2fa789e3cfe4d436c96be80200c5292f45f15/numexpr-2.14.1-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl @@ -1298,27 +1298,27 @@ environments: - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a1/5c/724b6b363603e419829f561c854b87ed7c7e31231a7908708ac086cdf3e2/charset_normalizer-3.4.6-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/e2/0c/dbfafbe90a185943dcfbc766fe0e1909f658811492d79b741523a414a6cc/coverage-7.13.4-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/66/40/7732d648ab9d069a46e686043241f01206348e2bbf128daea85be4d6414b/coverage-7.13.5-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/13/f7/a0b368ce54ffff9e9028c098bd2d28cfc5b54f9f6c186929083d4c60ba58/debugpy-1.8.20-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/38/60/35186529de1db3c01f5ad625bde07c1f576305eab6d86bbda4c58445f721/fonttools-4.62.1-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl @@ -1346,7 +1346,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -1364,7 +1364,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cc/23/9281bceaeb282cead95f0aa5f7f222ffc895670ea689cc1398355f6e3001/numexpr-2.14.1-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl @@ -1439,7 +1439,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -1462,20 +1462,20 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda - pypi: https://files.pythonhosted.org/packages/8c/b2/a4a3149e1dff8723f38a5698b03e606aebb53940765abed1deaf3da6ee8e/arch-5.6.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/4b/2f/8a1d989bfadd120c90114ab33e0d2a0cbde05278c1fc15e83e62d570f50a/charset_normalizer-3.4.5-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/fd/ce/865e4e09b041bad659d682bbd98b47fb490b8e124f9398c9448065f64fee/charset_normalizer-3.4.6-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f8/02/aa7ec01d1a5023c4b680ab7257f9bfde9defe8fdddfe40be096ac19e8177/coverage-7.13.4-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7d/d8/3217636d86c7e7b12e126e4f30ef1581047da73140614523af7495ed5f2d/coverage-7.13.5-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/5c/57/a23a051fcff998fdfabdd33c6721b5bad499da08b586d3676993410071f0/fonttools-4.62.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/42/09/7dbe3d7023f57d9b580cfa832109d521988112fd59dddfda3fddda8218f9/fonttools-4.62.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/54/a4/974b666f64c339e5b0b44fc782edee92ab3341c17367a040e41f5132c15b/h5py-3.7.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl @@ -1556,20 +1556,20 @@ environments: - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/45/b0e6e239d06b96dd2a2782610286449c58849ac0017361fe3a49a213314e/arch-5.6.0-cp310-cp310-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/e6/8c/2c56124c6dc53a774d435f985b5973bc592f42d437be58c0c92d65ae7296/charset_normalizer-3.4.6-cp310-cp310-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/44/d4/7827d9ffa34d5d4d752eec907022aa417120936282fc488306f5da08c292/coverage-7.13.4-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/69/33/e8c48488c29a73fd089f9d71f9653c1be7478f2ad6b5bc870db11a55d23d/coverage-7.13.5-cp310-cp310-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/dd/45/86eccfdc922cb9fafc63189a9793fa9f6dd60e68a07be42e454ef2c0deae/fonttools-4.62.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/85/e4/2318d2b430562da7227010fb2bb029d2fa54d7b46443ae8942bab224e2a0/fonttools-4.62.1-cp310-cp310-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/6e/5e/f34fb9d87cec244d59604ef506d82727a1e35d03713dc5771bd95dcffa5d/h5py-3.7.0-cp310-cp310-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl @@ -1635,7 +1635,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -1651,20 +1651,20 @@ environments: - pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/83/fa/4165805349e21ef83f42e29305a1c724ef68855ebbc5c11c115bec0ac510/arch-5.6.0-cp310-cp310-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/e6/8c/2c56124c6dc53a774d435f985b5973bc592f42d437be58c0c92d65ae7296/charset_normalizer-3.4.6-cp310-cp310-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/35/b0/d69df26607c64043292644dbb9dc54b0856fabaa2cbb1eeee3331cc9e280/coverage-7.13.4-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/da/bd/b0ebe9f677d7f4b74a3e115eec7ddd4bcf892074963a00d91e8b164a6386/coverage-7.13.5-cp310-cp310-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/82/e0/9db48ec7f6b95bae7b20667ded54f18dba8e759ef66232c8683822ae26fc/fonttools-4.62.0-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/5a/ff/532ed43808b469c807e8cb6b21358da3fe6fd51486b3a8c93db0bb5d957f/fonttools-4.62.1-cp310-cp310-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/af/60/0b59c97efe8450ed8fbcc9fffa367a31385e2f197eaf3bd55cfca74846ea/h5py-3.7.0-cp310-cp310-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl @@ -1745,21 +1745,21 @@ environments: - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.44.35208-h818238b_34.conda - pypi: https://files.pythonhosted.org/packages/2f/84/12132d3ee536b3147fd8c81cefbe6a2ced0105f6a0c9b8894a0bf3b6d839/arch-5.6.0-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/a5/c3/84fb174e7770f2df2e1a2115090771bfbc2227fb39a765c6d00568d1aab4/charset_normalizer-3.4.5-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d8/8f/78f5489ffadb0db3eb7aff53d31c24531d33eb545f0c6f6567c25f49a5ff/charset_normalizer-3.4.6-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/78/13/331f94934cf6c092b8ea59ff868eb587bc8fe0893f02c55bc6c0183a192e/coverage-7.13.4-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/9f/cc/d938417e7a4d7f0433ad4edee8bb2acdc60dc7ac5af19e2a07a048ecbee3/coverage-7.13.5-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/72/43/09d49106e770fe558ced5e80df2e3c2ebee10e576eda155dcc5670473663/debugpy-1.8.20-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/e9/ee/08c0b7f8bac6e44638de6fe9a3e710a623932f60eccd58912c4d4743516d/fonttools-4.62.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/dd/ec/f53f626f8f3e89f4cadd8fc08f3452c8fd182c951ad5caa35efac22b29ab/fonttools-4.62.1-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/bd/18/f5eed64fc06b9d17ef11647d6c5016b8a97e3abf0afe6d080c070027a195/h5py-3.7.0-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl @@ -1832,7 +1832,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -1859,17 +1859,18 @@ environments: - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/98/29/9b366e70e243eb3d14a5cb488dfd3a0b6b2f1fb001a203f653b93ccfac88/cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/4b/2f/8a1d989bfadd120c90114ab33e0d2a0cbde05278c1fc15e83e62d570f50a/charset_normalizer-3.4.5-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/fd/ce/865e4e09b041bad659d682bbd98b47fb490b8e124f9398c9448065f64fee/charset_normalizer-3.4.6-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/32/5c/1ee32d1c7956923202f00cf8d2a14a62ed7517bdc0ee1e55301227fc273c/contourpy-1.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/f8/02/aa7ec01d1a5023c4b680ab7257f9bfde9defe8fdddfe40be096ac19e8177/coverage-7.13.4-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/7d/d8/3217636d86c7e7b12e126e4f30ef1581047da73140614523af7495ed5f2d/coverage-7.13.5-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl @@ -1877,9 +1878,8 @@ environments: - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/5c/57/a23a051fcff998fdfabdd33c6721b5bad499da08b586d3676993410071f0/fonttools-4.62.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/42/09/7dbe3d7023f57d9b580cfa832109d521988112fd59dddfda3fddda8218f9/fonttools-4.62.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/92/a8851d936547efe30cc0ce5245feac01f3ec6171f7899bc3f775c72030b3/h5py-3.16.0-cp310-cp310-manylinux_2_28_x86_64.whl @@ -1906,7 +1906,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -1924,7 +1924,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/34/d4/d1a410901c620f7a6a3c5c2b1fc9dab22170be05a89d2c02ae699e27bd3f/numexpr-2.14.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/b4/63/3de6a34ad7ad6646ac7d2f55ebc6ad439dbbf9c4370017c50cf403fb19b5/numpy-2.2.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl @@ -2013,17 +2013,18 @@ environments: - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/93/d7/516d984057745a6cd96575eea814fe1edd6646ee6efd552fb7b0921dec83/cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/e6/8c/2c56124c6dc53a774d435f985b5973bc592f42d437be58c0c92d65ae7296/charset_normalizer-3.4.6-cp310-cp310-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/12/a3/da4153ec8fe25d263aa48c1a4cbde7f49b59af86f0b6f7862788c60da737/contourpy-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/44/d4/7827d9ffa34d5d4d752eec907022aa417120936282fc488306f5da08c292/coverage-7.13.4-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/69/33/e8c48488c29a73fd089f9d71f9653c1be7478f2ad6b5bc870db11a55d23d/coverage-7.13.5-cp310-cp310-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl @@ -2031,9 +2032,8 @@ environments: - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/dd/45/86eccfdc922cb9fafc63189a9793fa9f6dd60e68a07be42e454ef2c0deae/fonttools-4.62.0-cp310-cp310-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/85/e4/2318d2b430562da7227010fb2bb029d2fa54d7b46443ae8942bab224e2a0/fonttools-4.62.1-cp310-cp310-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/3a/6b/231413e58a787a89b316bb0d1777da3c62257e4797e09afd8d17ad3549dc/h5py-3.16.0-cp310-cp310-macosx_10_9_x86_64.whl @@ -2060,7 +2060,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -2078,7 +2078,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/db/91/ccd504cbe5b88d06987c77f42ba37a13ef05065fdab4afe6dcfeb2961faf/numexpr-2.14.1-cp310-cp310-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/9a/3e/ed6db5be21ce87955c0cbd3009f2803f59fa08df21b5df06862e2d8e2bdd/numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl @@ -2147,7 +2147,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -2167,17 +2167,18 @@ environments: - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9e/84/ad6a0b408daa859246f57c03efd28e5dd1b33c21737c2db84cae8c237aa5/cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/e6/8c/2c56124c6dc53a774d435f985b5973bc592f42d437be58c0c92d65ae7296/charset_normalizer-3.4.6-cp310-cp310-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2f/6c/330de89ae1087eb622bfca0177d32a7ece50c3ef07b28002de4757d9d875/contourpy-1.3.2-cp310-cp310-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/35/b0/d69df26607c64043292644dbb9dc54b0856fabaa2cbb1eeee3331cc9e280/coverage-7.13.4-cp310-cp310-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/da/bd/b0ebe9f677d7f4b74a3e115eec7ddd4bcf892074963a00d91e8b164a6386/coverage-7.13.5-cp310-cp310-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl @@ -2185,9 +2186,8 @@ environments: - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/82/e0/9db48ec7f6b95bae7b20667ded54f18dba8e759ef66232c8683822ae26fc/fonttools-4.62.0-cp310-cp310-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/5a/ff/532ed43808b469c807e8cb6b21358da3fe6fd51486b3a8c93db0bb5d957f/fonttools-4.62.1-cp310-cp310-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/74/f9/557ce3aad0fe8471fb5279bab0fc56ea473858a022c4ce8a0b8f303d64e9/h5py-3.16.0-cp310-cp310-macosx_11_0_arm64.whl @@ -2214,7 +2214,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -2232,7 +2232,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f3/89/6b07977baf2af75fb6692f9e7a1fb612a15f600fc921f3f565366de01f4a/numexpr-2.14.1-cp310-cp310-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/22/c2/4b9221495b2a132cc9d2eb862e21d42a009f5a60e45fc44b00118c174bff/numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl @@ -2320,18 +2320,19 @@ environments: - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/33/fa/072dd15ae27fbb4e06b437eb6e944e75b068deb09e2a2826039e49ee2045/cffi-2.0.0-cp310-cp310-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/a5/c3/84fb174e7770f2df2e1a2115090771bfbc2227fb39a765c6d00568d1aab4/charset_normalizer-3.4.5-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d8/8f/78f5489ffadb0db3eb7aff53d31c24531d33eb545f0c6f6567c25f49a5ff/charset_normalizer-3.4.6-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/54/ec/5162b8582f2c994721018d0c9ece9dc6ff769d298a8ac6b6a652c307e7df/contourpy-1.3.2-cp310-cp310-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/78/13/331f94934cf6c092b8ea59ff868eb587bc8fe0893f02c55bc6c0183a192e/coverage-7.13.4-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/9f/cc/d938417e7a4d7f0433ad4edee8bb2acdc60dc7ac5af19e2a07a048ecbee3/coverage-7.13.5-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/72/43/09d49106e770fe558ced5e80df2e3c2ebee10e576eda155dcc5670473663/debugpy-1.8.20-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl @@ -2339,9 +2340,8 @@ environments: - pypi: https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/e9/ee/08c0b7f8bac6e44638de6fe9a3e710a623932f60eccd58912c4d4743516d/fonttools-4.62.0-cp310-cp310-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/dd/ec/f53f626f8f3e89f4cadd8fc08f3452c8fd182c951ad5caa35efac22b29ab/fonttools-4.62.1-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/66/35/d88fd6718832133c885004c61ceeeb24dbd6397ef877dbed6b3a64d6a286/h5py-3.16.0-cp310-cp310-win_amd64.whl @@ -2368,7 +2368,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -2386,7 +2386,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/18/af/26773a246716922794388786529e5640676399efabb0ee217ce034df9d27/numexpr-2.14.1-cp310-cp310-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/a3/dd/4b822569d6b96c39d1215dbae0582fd99954dcbcf0c1a13c61783feaca3f/numpy-2.2.6-cp310-cp310-win_amd64.whl @@ -2463,7 +2463,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -2490,26 +2490,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d7/91/500d892b2bf36529a75b77958edfcd5ad8e2ce4064ce2ecfeab2125d72d1/cffi-2.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/03/f4/44d3b830a20e89ff82a3134912d9a1cf6084d64f3b95dcad40f74449a654/charset_normalizer-3.4.5-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/60/ac/3233d262a310c1b12633536a07cde5ddd16985e6e7e238e9f3f9423d8eb9/charset_normalizer-3.4.6-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/5f/4b/6157f24ca425b89fe2eb7e7be642375711ab671135be21e6faa100f7448c/contourpy-1.3.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/76/53/c16972708cbb79f2942922571a687c52bd109a7bd51175aeb7558dff2236/coverage-7.13.4-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/92/be/b1afb692be85b947f3401375851484496134c5554e67e822c35f28bf2fbc/coverage-7.13.5-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/8a/d7/8e4845993ee233c2023d11babe9b3dae7d30333da1d792eeccebcb77baab/fonttools-4.62.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/cc/a1/40a5c4d8e28b0851d53a8eeeb46fbd73c325a2a9a165f290a5ed90e6c597/fonttools-4.62.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/52/a0/c1f604538ff6db22a0690be2dc44ab59178e115f63c917794e529356ab23/h5py-3.16.0-cp311-cp311-manylinux_2_28_x86_64.whl @@ -2537,7 +2537,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -2555,7 +2555,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4c/1a/edbe839109518364ac0bd9e918cf874c755bb2c128040e920f198c494263/numexpr-2.14.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/78/51/9f5d7a41f0b51649ddf2f2320595e15e122a40610b233d51928dd6c92353/numpy-2.4.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl @@ -2643,26 +2643,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/12/4a/3dfd5f7850cbf0d06dc84ba9aa00db766b52ca38d8b86e3a38314d52498c/cffi-2.0.0-cp311-cp311-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/8f/9e/bcec3b22c64ecec47d39bf5167c2613efd41898c019dccd4183f6aa5d6a7/charset_normalizer-3.4.5-cp311-cp311-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/62/28/ff6f234e628a2de61c458be2779cb182bc03f6eec12200d4a525bbfc9741/charset_normalizer-3.4.6-cp311-cp311-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/91/2e/c4390a31919d8a78b90e8ecf87cd4b4c4f05a5b48d05ec17db8e5404c6f4/contourpy-1.3.3-cp311-cp311-macosx_10_9_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/b4/ad/b59e5b451cf7172b8d1043dc0fa718f23aab379bc1521ee13d4bd9bfa960/coverage-7.13.4-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4b/37/d24c8f8220ff07b839b2c043ea4903a33b0f455abe673ae3c03bbdb7f212/coverage-7.13.5-cp311-cp311-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c0/7a/9aeec114bc9fc00d757a41f092f7107863d372e684a5b5724c043654477c/fonttools-4.62.0-cp311-cp311-macosx_10_9_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/24/7f/66d3f8a9338a9b67fe6e1739f47e1cd5cee78bd3bc1206ef9b0b982289a5/fonttools-4.62.1-cp311-cp311-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ba/95/a825894f3e45cbac7554c4e97314ce886b233a20033787eda755ca8fecc7/h5py-3.16.0-cp311-cp311-macosx_10_9_x86_64.whl @@ -2690,7 +2690,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -2708,7 +2708,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b2/a3/67999bdd1ed1f938d38f3fedd4969632f2f197b090e50505f7cc1fa82510/numexpr-2.14.1-cp311-cp311-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/f9/51/5093a2df15c4dc19da3f79d1021e891f5dcf1d9d1db6ba38891d5590f3fe/numpy-2.4.3-cp311-cp311-macosx_10_9_x86_64.whl @@ -2776,7 +2776,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -2796,26 +2796,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4f/8b/f0e4c441227ba756aafbe78f117485b25bb26b1c059d01f137fa6d14896b/cffi-2.0.0-cp311-cp311-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/8f/9e/bcec3b22c64ecec47d39bf5167c2613efd41898c019dccd4183f6aa5d6a7/charset_normalizer-3.4.5-cp311-cp311-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/62/28/ff6f234e628a2de61c458be2779cb182bc03f6eec12200d4a525bbfc9741/charset_normalizer-3.4.6-cp311-cp311-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/0d/44/c4b0b6095fef4dc9c420e041799591e3b63e9619e3044f7f4f6c21c0ab24/contourpy-1.3.3-cp311-cp311-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/f1/17/0cb7ca3de72e5f4ef2ec2fa0089beafbcaaaead1844e8b8a63d35173d77d/coverage-7.13.4-cp311-cp311-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/35/8b/cd129b0ca4afe886a6ce9d183c44d8301acbd4ef248622e7c49a23145605/coverage-7.13.5-cp311-cp311-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/e4/33/63d79ca41020dd460b51f1e0f58ad1ff0a36b7bcbdf8f3971d52836581e9/fonttools-4.62.0-cp311-cp311-macosx_10_9_universal2.whl + - pypi: https://files.pythonhosted.org/packages/88/39/23ff32561ec8d45a4d48578b4d241369d9270dc50926c017570e60893701/fonttools-4.62.1-cp311-cp311-macosx_10_9_universal2.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/bf/3b/38ff88b347c3e346cda1d3fc1b65a7aa75d40632228d8b8a5d7b58508c24/h5py-3.16.0-cp311-cp311-macosx_11_0_arm64.whl @@ -2843,7 +2843,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -2861,7 +2861,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/25/95/d64f680ea1fc56d165457287e0851d6708800f9fcea346fc1b9957942ee6/numexpr-2.14.1-cp311-cp311-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/b5/7c/c061f3de0630941073d2598dc271ac2f6cbcf5c83c74a5870fea07488333/numpy-2.4.3-cp311-cp311-macosx_11_0_arm64.whl @@ -2948,27 +2948,27 @@ environments: - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ae/8f/dc5531155e7070361eb1b7e4c1a9d896d0cb21c49f807a6c03fd63fc877e/cffi-2.0.0-cp311-cp311-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/fe/1f/a853b73d386521fd44b7f67ded6b17b7b2367067d9106a5c4b44f9a34274/charset_normalizer-3.4.5-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/c6/e3/76f2facfe8eddee0bbd38d2594e709033338eae44ebf1738bcefe0a06185/charset_normalizer-3.4.6-cp311-cp311-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/98/4b/9bd370b004b5c9d8045c6c33cf65bae018b27aca550a3f657cdc99acdbd8/contourpy-1.3.3-cp311-cp311-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/61/08/3d9c8613079d2b11c185b865de9a4c1a68850cfda2b357fae365cf609f29/coverage-7.13.4-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/af/7f/4cd8a92531253f9d7c1bbecd9fa1b472907fb54446ca768c59b531248dc5/coverage-7.13.5-cp311-cp311-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d5/92/1cb532e88560cbee973396254b21bece8c5d7c2ece958a67afa08c9f10dc/debugpy-1.8.20-cp311-cp311-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/77/ce/f5a4c42c117f8113ce04048053c128d17426751a508f26398110c993a074/fonttools-4.62.0-cp311-cp311-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/d3/97/bf54c5b3f2be34e1f143e6db838dfdc54f2ffa3e68c738934c82f3b2a08d/fonttools-4.62.1-cp311-cp311-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f7/20/e6c0ff62ca2ad1a396a34f4380bafccaaf8791ff8fccf3d995a1fc12d417/h5py-3.16.0-cp311-cp311-win_amd64.whl @@ -2996,7 +2996,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -3014,7 +3014,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/64/72/4ca9bd97b2eb6dce9f5e70a3b6acec1a93e1fb9b079cb4cba2cdfbbf295d/numexpr-2.14.1-cp311-cp311-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/76/1d/edccf27adedb754db7c4511d5eac8b83f004ae948fe2d3509e8b78097d4c/numpy-2.4.3-cp311-cp311-win_amd64.whl @@ -3090,7 +3090,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -3117,26 +3117,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/78/2d/7fa73dfa841b5ac06c7b8855cfc18622132e365f5b81d02230333ff26e9e/cffi-2.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/67/5c/ae30362a88b4da237d71ea214a8c7eb915db3eec941adda511729ac25fa2/charset_normalizer-3.4.5-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4e/ef/79a463eb0fff7f96afa04c1d4c51f8fc85426f918db467854bfb6a569ce3/charset_normalizer-3.4.6-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cc/8f/ec6289987824b29529d0dfda0d74a07cec60e54b9c92f3c9da4c0ac732de/contourpy-1.3.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/5d/a0/2ea570925524ef4e00bb6c82649f5682a77fac5ab910a65c9284de422600/coverage-7.13.4-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/8c/49/cd14b789536ac6a4778c453c6a2338bc0a2fb60c5a5a41b4008328b9acc1/coverage-7.13.5-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/0b/a1/d16318232964d786907b9b3613b8409f74cf0be2da400854509d3a864e43/fonttools-4.62.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/9b/8a/99c8b3c3888c5c474c08dbfd7c8899786de9604b727fcefb055b42c84bba/fonttools-4.62.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9e/e9/1a19e42cd43cc1365e127db6aae85e1c671da1d9a5d746f4d34a50edb577/h5py-3.16.0-cp312-cp312-manylinux_2_28_x86_64.whl @@ -3164,7 +3164,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -3182,7 +3182,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d9/43/560e9ba23c02c904b5934496486d061bcb14cd3ebba2e3cf0e2dccb6c22b/numexpr-2.14.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/bd/79/cc665495e4d57d0aa6fbcc0aa57aa82671dfc78fbf95fe733ed86d98f52a/numpy-2.4.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl @@ -3269,26 +3269,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ea/47/4f61023ea636104d4f16ab488e268b93008c3d0bb76893b1b31db1f96802/cffi-2.0.0-cp312-cp312-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/9c/b6/9ee9c1a608916ca5feae81a344dffbaa53b26b90be58cc2159e3332d44ec/charset_normalizer-3.4.5-cp312-cp312-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/e5/62/c0815c992c9545347aeea7859b50dc9044d147e2e7278329c6e02ac9a616/charset_normalizer-3.4.6-cp312-cp312-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/be/45/adfee365d9ea3d853550b2e735f9d66366701c65db7855cd07621732ccfc/contourpy-1.3.3-cp312-cp312-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/d1/81/4ce2fdd909c5a0ed1f6dedb88aa57ab79b6d1fbd9b588c1ac7ef45659566/coverage-7.13.4-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/a0/c3/a396306ba7db865bf96fc1fb3b7fd29bcbf3d829df642e77b13555163cd6/coverage-7.13.5-cp312-cp312-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/4d/8b/ba59069a490f61b737e064c3129453dbd28ee38e81d56af0d04d7e6b4de4/fonttools-4.62.0-cp312-cp312-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/66/9e/a769c8e99b81e5a87ab7e5e7236684de4e96246aae17274e5347d11ebd78/fonttools-4.62.1-cp312-cp312-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c8/c0/5d4119dba94093bbafede500d3defd2f5eab7897732998c04b54021e530b/h5py-3.16.0-cp312-cp312-macosx_10_13_x86_64.whl @@ -3316,7 +3316,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -3334,7 +3334,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9d/20/c473fc04a371f5e2f8c5749e04505c13e7a8ede27c09e9f099b2ad6f43d6/numexpr-2.14.1-cp312-cp312-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/a9/ed/6388632536f9788cea23a3a1b629f25b43eaacd7d7377e5d6bc7b9deb69b/numpy-2.4.3-cp312-cp312-macosx_10_13_x86_64.whl @@ -3401,7 +3401,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -3421,26 +3421,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/df/a2/781b623f57358e360d62cdd7a8c681f074a71d445418a776eef0aadb4ab4/cffi-2.0.0-cp312-cp312-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/9c/b6/9ee9c1a608916ca5feae81a344dffbaa53b26b90be58cc2159e3332d44ec/charset_normalizer-3.4.5-cp312-cp312-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/e5/62/c0815c992c9545347aeea7859b50dc9044d147e2e7278329c6e02ac9a616/charset_normalizer-3.4.6-cp312-cp312-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/53/3e/405b59cfa13021a56bba395a6b3aca8cec012b45bf177b0eaf7a202cde2c/contourpy-1.3.3-cp312-cp312-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/5d/96/5238b1efc5922ddbdc9b0db9243152c09777804fb7c02ad1741eb18a11c0/coverage-7.13.4-cp312-cp312-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/a6/16/a68a19e5384e93f811dccc51034b1fd0b865841c390e3c931dcc4699e035/coverage-7.13.5-cp312-cp312-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/ab/9d/7ad1ffc080619f67d0b1e0fa6a0578f0be077404f13fd8e448d1616a94a3/fonttools-4.62.0-cp312-cp312-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/47/d4/dbacced3953544b9a93088cc10ef2b596d348c983d5c67a404fa41ec51ba/fonttools-4.62.1-cp312-cp312-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b0/42/c84efcc1d4caebafb1ecd8be4643f39c85c47a80fe254d92b8b43b1eadaf/h5py-3.16.0-cp312-cp312-macosx_11_0_arm64.whl @@ -3468,7 +3468,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -3486,7 +3486,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/45/93/b6760dd1904c2a498e5f43d1bb436f59383c3ddea3815f1461dfaa259373/numexpr-2.14.1-cp312-cp312-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/74/1b/ee2abfc68e1ce728b2958b6ba831d65c62e1b13ce3017c13943f8f9b5b2e/numpy-2.4.3-cp312-cp312-macosx_11_0_arm64.whl @@ -3572,27 +3572,27 @@ environments: - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f8/ed/13bd4418627013bec4ed6e54283b1959cf6db888048c7cf4b4c3b5b36002/cffi-2.0.0-cp312-cp312-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/70/53/e44a4c07e8904500aec95865dc3f6464dc3586a039ef0df606eb3ac38e35/charset_normalizer-3.4.5-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/ab/20/0567efb3a8fd481b8f34f739ebddc098ed062a59fed41a8d193a61939e8f/charset_normalizer-3.4.6-cp312-cp312-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/19/e8/6026ed58a64563186a9ee3f29f41261fd1828f527dd93d33b60feca63352/contourpy-1.3.3-cp312-cp312-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/77/4e/c0a25a425fcf5557d9abd18419c95b63922e897bc86c1f327f155ef234a9/coverage-7.13.4-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/29/3d/821a9a5799fac2556bcf0bd37a70d1d11fa9e49784b6d22e92e8b2f85f18/coverage-7.13.5-cp312-cp312-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a1/39/2bef246368bd42f9bd7cba99844542b74b84dacbdbea0833e610f384fee8/debugpy-1.8.20-cp312-cp312-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/cd/06/cc96468781a4dc8ae2f14f16f32b32f69bde18cb9384aad27ccc7adf76f7/fonttools-4.62.0-cp312-cp312-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/28/b1/0c2ab56a16f409c6c8a68816e6af707827ad5d629634691ff60a52879792/fonttools-4.62.1-cp312-cp312-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/03/c1/0976b235cf29ead553e22f2fb6385a8252b533715e00d0ae52ed7b900582/h5py-3.16.0-cp312-cp312-win_amd64.whl @@ -3620,7 +3620,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -3638,7 +3638,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1f/67/ffe750b5452eb66de788c34e7d21ec6d886abb4d7c43ad1dc88ceb3d998f/numexpr-2.14.1-cp312-cp312-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d7/7c/f5ee1bf6ed888494978046a809df2882aad35d414b622893322df7286879/numpy-2.4.3-cp312-cp312-win_amd64.whl @@ -3713,7 +3713,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -3739,26 +3739,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/2b/58/a199d245894b12db0b957d627516c78e055adc3a0d978bc7f65ddaf7c399/charset_normalizer-3.4.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/e4/dc/b2442d10020c2f52617828862d8b6ee337859cd8f3a1f13d607dddda9cf7/coverage-7.13.4-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/ac/68/1666e3a4462f8202d836920114fa7a5ee9275d1fa45366d336c551a162dd/coverage-7.13.5-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/e2/98/8b1e801939839d405f1f122e7d175cebe9aeb4e114f95bfc45e3152af9a7/fonttools-4.62.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/bd/98/ef2b6fe2903e377cbe870c3b2800d62552f1e3dbe81ce49e1923c53d1c5c/h5py-3.16.0-cp313-cp313-manylinux_2_28_x86_64.whl @@ -3786,7 +3786,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -3804,7 +3804,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/fc/f9/c9457652dfe28e2eb898372da2fe786c6db81af9540c0f853ee04a0699cc/numexpr-2.14.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/7e/eb/7daecbea84ec935b7fc732e18f532073064a3816f0932a40a17f3349185f/numpy-2.4.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl @@ -3893,26 +3893,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/db/23/aad45061a31677d68e47499197a131eea55da4875d16c1f42021ab963503/coverage-7.13.4-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/74/8c/74fedc9663dcf168b0a059d4ea756ecae4da77a489048f94b5f512a8d0b3/coverage-7.13.5-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/03/c5/0e3966edd5ec668d41dfe418787726752bc07e2f5fd8c8f208615e61fa89/fonttools-4.62.1-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/0f/9e/6142ebfda0cb6e9349c091eae73c2e01a770b7659255248d637bec54a88b/h5py-3.16.0-cp313-cp313-macosx_10_13_x86_64.whl @@ -3940,7 +3940,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -3958,7 +3958,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/73/b4/9f6d637fd79df42be1be29ee7ba1f050fab63b7182cb922a0e08adc12320/numexpr-2.14.1-cp313-cp313-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/b6/d0/1fe47a98ce0df229238b77611340aff92d52691bcbc10583303181abf7fc/numpy-2.4.3-cp313-cp313-macosx_10_13_x86_64.whl @@ -4025,7 +4025,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -4047,26 +4047,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/a5/70/9b8b67a0945f3dfec1fd896c5cefb7c19d5a3a6d74630b99a895170999ae/coverage-7.13.4-cp313-cp313-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/0c/c9/44fb661c55062f0818a6ffd2685c67aa30816200d5f2817543717d4b92eb/coverage-7.13.5-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl + - pypi: https://files.pythonhosted.org/packages/3b/56/6f389de21c49555553d6a5aeed5ac9767631497ac836c4f076273d15bd72/fonttools-4.62.1-cp313-cp313-macosx_10_13_universal2.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b0/65/5e088a45d0f43cd814bc5bec521c051d42005a472e804b1a36c48dada09b/h5py-3.16.0-cp313-cp313-macosx_11_0_arm64.whl @@ -4094,7 +4094,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -4112,7 +4112,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/35/ae/d58558d8043de0c49f385ea2fa789e3cfe4d436c96be80200c5292f45f15/numexpr-2.14.1-cp313-cp313-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/27/d9/4e7c3f0e68dfa91f21c6fb6cf839bc829ec920688b1ce7ec722b1a6202fb/numpy-2.4.3-cp313-cp313-macosx_11_0_arm64.whl @@ -4200,27 +4200,27 @@ environments: - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/a1/5c/724b6b363603e419829f561c854b87ed7c7e31231a7908708ac086cdf3e2/charset_normalizer-3.4.6-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/e2/0c/dbfafbe90a185943dcfbc766fe0e1909f658811492d79b741523a414a6cc/coverage-7.13.4-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/66/40/7732d648ab9d069a46e686043241f01206348e2bbf128daea85be4d6414b/coverage-7.13.5-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/13/f7/a0b368ce54ffff9e9028c098bd2d28cfc5b54f9f6c186929083d4c60ba58/debugpy-1.8.20-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/38/60/35186529de1db3c01f5ad625bde07c1f576305eab6d86bbda4c58445f721/fonttools-4.62.1-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c3/d9/a27997f84341fc0dfcdd1fe4179b6ba6c32a7aa880fdb8c514d4dad6fba3/h5py-3.16.0-cp313-cp313-win_amd64.whl @@ -4248,7 +4248,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -4266,7 +4266,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cc/23/9281bceaeb282cead95f0aa5f7f222ffc895670ea689cc1398355f6e3001/numexpr-2.14.1-cp313-cp313-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/b1/3c/88af0040119209b9b5cb59485fa48b76f372c73068dbf9254784b975ac53/numpy-2.4.3-cp313-cp313-win_amd64.whl @@ -4341,7 +4341,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda + - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_101.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.4-hecca717_0.conda - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda @@ -4367,26 +4367,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/09/52/94108adfdd6e2ddf58be64f959a0b9c7d4ef2fa71086c38356d22dc501ea/argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/47/d9/d83e293854571c877a92da46fdec39158f8d7e68da75bf73581225d28e90/cffi-2.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/38/9c/71336bff6934418dc8d1e8a1644176ac9088068bc571da612767619c97b3/charset_normalizer-3.4.5-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/76/7e/bc8911719f7084f72fd545f647601ea3532363927f807d296a8c88a62c0d/charset_normalizer-3.4.6-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/5f/9ff93450ba96b09c7c2b3f81c94de31c89f92292f1380261bd7195bea4ea/contourpy-1.3.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/06/90/2cdab0974b9b5bbc1623f7876b73603aecac11b8d95b85b5b86b32de5eab/coverage-7.13.4-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/22/e5/06b1f88f42a5a99df42ce61208bdec3bddb3d261412874280a19796fc09c/coverage-7.13.5-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/86/c8/c6669e42d2f4efd60d38a3252cebbb28851f968890efb2b9b15f9d1092b0/fonttools-4.62.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/28/63/cd0c3b26afe60995a5295f37c246a93d454023726c3261cfbb3559969bb9/fonttools-4.62.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f1/16/d905e7f53e661ce2c24686c38048d8e2b750ffc4350009d41c4e6c6c9826/h5py-3.16.0-cp314-cp314-manylinux_2_28_x86_64.whl @@ -4414,7 +4414,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -4432,7 +4432,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/88/e1/3db65117f02cdefb0e5e4c440daf1c30beb45051b7f47aded25b7f4f2f34/numexpr-2.14.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl - pypi: https://files.pythonhosted.org/packages/a9/7e/4f120ecc54ba26ddf3dc348eeb9eb063f421de65c05fc961941798feea18/numpy-2.4.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl @@ -4522,26 +4522,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/0a/08/a9bebdb2e0e602dde230bdde8021b29f71f7841bd54801bcfd514acb5dcf/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/c4/3ce07396253a83250ee98564f8d7e9789fab8e58858f35d07a9a2c78de9f/cffi-2.0.0-cp314-cp314-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/43/be/0f0fd9bb4a7fa4fb5067fb7d9ac693d4e928d306f80a0d02bde43a7c4aee/charset_normalizer-3.4.5-cp314-cp314-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/25/6f/ffe1e1259f384594063ea1869bfb6be5cdb8bc81020fc36c3636bc8302a1/charset_normalizer-3.4.6-cp314-cp314-macosx_10_15_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/72/8b/4546f3ab60f78c514ffb7d01a0bd743f90de36f0019d1be84d0a708a580a/contourpy-1.3.3-cp314-cp314-macosx_10_13_x86_64.whl - - pypi: https://files.pythonhosted.org/packages/92/11/a9cf762bb83386467737d32187756a42094927150c3e107df4cb078e8590/coverage-7.13.4-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/8e/77/39703f0d1d4b478bfd30191d3c14f53caf596fac00efb3f8f6ee23646439/coverage-7.13.5-cp314-cp314-macosx_10_15_x86_64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/c6/57/6b08756fe4455336b1fe160ab3c11fccc90768ccb6ee03fb0b45851aace4/fonttools-4.62.0-cp314-cp314-macosx_10_15_x86_64.whl + - pypi: https://files.pythonhosted.org/packages/4b/b2/e521803081f8dc35990816b82da6360fa668a21b44da4b53fc9e77efcd62/fonttools-4.62.1-cp314-cp314-macosx_10_15_x86_64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/48/3c/7fcd9b4c9eed82e91fb15568992561019ae7a829d1f696b2c844355d95dd/h5py-3.16.0-cp314-cp314-macosx_10_15_x86_64.whl @@ -4569,7 +4569,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -4587,7 +4587,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ac/36/9db78dfbfdfa1f8bf0872993f1a334cdd8fca5a5b6567e47dcb128bcb7c2/numexpr-2.14.1-cp314-cp314-macosx_10_13_x86_64.whl - pypi: https://files.pythonhosted.org/packages/70/ae/3936f79adebf8caf81bd7a599b90a561334a658be4dcc7b6329ebf4ee8de/numpy-2.4.3-cp314-cp314-macosx_10_15_x86_64.whl @@ -4654,7 +4654,7 @@ environments: osx-arm64: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-hd037594_9.conda - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.2.25-hbd8a1cb_0.conda - - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda + - conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.7.4-hf6b4638_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.5.2-hcf2aa1b_0.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.2-h8088a28_0.conda @@ -4677,26 +4677,26 @@ environments: - pypi: https://files.pythonhosted.org/packages/b6/02/d297943bcacf05e4f2a94ab6f462831dc20158614e5d067c35d4e63b9acb/argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/59/dd/27e9fa567a23931c838c6b02d0764611c62290062a6d4e8ff7863daf9730/cffi-2.0.0-cp314-cp314-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/43/be/0f0fd9bb4a7fa4fb5067fb7d9ac693d4e928d306f80a0d02bde43a7c4aee/charset_normalizer-3.4.5-cp314-cp314-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/25/6f/ffe1e1259f384594063ea1869bfb6be5cdb8bc81020fc36c3636bc8302a1/charset_normalizer-3.4.6-cp314-cp314-macosx_10_15_universal2.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/fd/e1/3542a9cb596cadd76fcef413f19c79216e002623158befe6daa03dbfa88c/contourpy-1.3.3-cp314-cp314-macosx_11_0_arm64.whl - - pypi: https://files.pythonhosted.org/packages/d3/28/56e6d892b7b052236d67c95f1936b6a7cf7c3e2634bf27610b8cbd7f9c60/coverage-7.13.4-cp314-cp314-macosx_11_0_arm64.whl + - pypi: https://files.pythonhosted.org/packages/e2/3e/51dff36d99ae14639a133d9b164d63e628532e2974d8b1edb99dd1ebc733/coverage-7.13.5-cp314-cp314-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/1a/64/61f69298aa6e7c363dcf00dd6371a654676900abe27d1effd1a74b43e5d0/fonttools-4.62.0-cp314-cp314-macosx_10_15_universal2.whl + - pypi: https://files.pythonhosted.org/packages/36/f0/2888cdac391807d68d90dcb16ef858ddc1b5309bfc6966195a459dd326e2/fonttools-4.62.1-cp314-cp314-macosx_10_15_universal2.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/6a/b7/9366ed44ced9b7ef357ab48c94205280276db9d7f064aa3012a97227e966/h5py-3.16.0-cp314-cp314-macosx_11_0_arm64.whl @@ -4724,7 +4724,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -4742,7 +4742,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/13/c1/a5c78ae637402c5550e2e0ba175275d2515d432ec28af0cdc23c9b476e65/numexpr-2.14.1-cp314-cp314-macosx_11_0_arm64.whl - pypi: https://files.pythonhosted.org/packages/9b/62/760f2b55866b496bb1fa7da2a6db076bef908110e568b02fcfc1422e2a3a/numpy-2.4.3-cp314-cp314-macosx_11_0_arm64.whl @@ -4831,27 +4831,27 @@ environments: - pypi: https://files.pythonhosted.org/packages/e2/c6/a759ece8f1829d1f162261226fbfd2c6832b3ff7657384045286d2afa384/argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/ed/c9/d7977eaacb9df673210491da99e6a247e93df98c715fc43fd136ce1d3d33/arrow-1.4.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/bb/92/882c2d30831744296ce713f0feb4c1cd30f346ef747b530b5318715cc367/cffi-2.0.0-cp314-cp314-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/40/65/e7c6c77d7aaa4c0d7974f2e403e17f0ed2cb0fc135f77d686b916bf1eead/charset_normalizer-3.4.5-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/80/94/8434a02d9d7f168c25767c64671fead8d599744a05d6a6c877144c754246/charset_normalizer-3.4.6-cp314-cp314-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/7d/c2/57f54b03d0f22d4044b8afb9ca0e184f8b1afd57b4f735c2fa70883dc601/contourpy-1.3.3-cp314-cp314-win_amd64.whl - - pypi: https://files.pythonhosted.org/packages/a7/4d/1f8e723f6829977410efeb88f73673d794075091c8c7c18848d273dc9d73/coverage-7.13.4-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/8d/b7/4758d4f73fb536347cc5e4ad63662f9d60ba9118cb6785e9616b2ce5d7fa/coverage-7.13.5-cp314-cp314-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/d9/1f07395b54413432624d61524dfd98c1a7c7827d2abfdb8829ac92638205/debugpy-1.8.20-cp314-cp314-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/2e/9f/91081ffe5881253177c175749cce5841f5ec6e931f5d52f4a817207b7429/fonttools-4.62.0-cp314-cp314-win_amd64.whl + - pypi: https://files.pythonhosted.org/packages/6b/67/74b070029043186b5dd13462c958cb7c7f811be0d2e634309d9a1ffb1505/fonttools-4.62.1-cp314-cp314-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/3e/14/615a450205e1b56d16c6783f5ccd116cde05550faad70ae077c955654a75/h5py-3.16.0-cp314-cp314-win_amd64.whl @@ -4879,7 +4879,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/1a/60/1f6cee0c46263de1173894f0fafcb3475ded276c472c14d25e0280c18d6d/jupyter_lsp-2.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/92/80/a24767e6ca280f5a49525d987bf3e4d7552bf67c8be07e8ccf20271f8568/jupyter_server-2.17.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/d1/2d/6674563f71c6320841fc300911a55143925112a72a883e2ca71fba4c618d/jupyter_server_terminals-0.5.4-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/e0/07/a000fe835f76b7e1143242ab1122e6362ef1c03f23f83a045c38859c2ae0/jupyterlab_server-2.28.0-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl @@ -4897,7 +4897,7 @@ environments: - pypi: https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/2c/5c/eb1e3ce54c4e94c7734b3831756c63f21badb3de91a98d77b9e23c0ca76a/nbval-0.11.0-py2.py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl - - pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl + - pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/4f/3e/d83e9401a1c3449a124f7d4b3fb44084798e0d30f7c11e60712d9b94cf11/numexpr-2.14.1-cp314-cp314-win_amd64.whl - pypi: https://files.pythonhosted.org/packages/48/39/c56ef87af669364356bb011922ef0734fc49dad51964568634c72a009488/numpy-2.4.3-cp314-cp314-win_amd64.whl @@ -6406,17 +6406,17 @@ packages: - pytest-cov ; extra == 'test' - pytest-xdist ; extra == 'test' requires_python: '>=3.8' -- pypi: https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl +- pypi: https://files.pythonhosted.org/packages/e5/e2/c2e3abf398f80732e58b03be77bde9022550d221dd8781bf586bd4d97cc1/async_lru-2.3.0-py3-none-any.whl name: async-lru - version: 2.2.0 - sha256: e2c1cf731eba202b59c5feedaef14ffd9d02ad0037fcda64938699f2c380eafe + version: 2.3.0 + sha256: eea27b01841909316f2cc739807acea1c623df2be8c5cfad7583286397bb8315 requires_dist: - typing-extensions>=4.0.0 ; python_full_version < '3.11' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl +- pypi: https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl name: attrs - version: 25.4.0 - sha256: adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373 + version: 26.1.0 + sha256: c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309 requires_python: '>=3.9' - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl name: babel @@ -6433,6 +6433,20 @@ packages: - pytz ; extra == 'dev' - setuptools ; extra == 'dev' requires_python: '>=3.8' +- pypi: https://files.pythonhosted.org/packages/a6/fe/b02bddcd0dd427cd96843946e51ecd81e4edfc37d3fcbd729dabfbe1bff6/bayesian_filters-1.4.5-py3-none-any.whl + name: bayesian-filters + version: 1.4.5 + sha256: 6d9a6e019ad5166a4a12e95220a6dad1a9bd96b1a97ca4b7d363e061a7d8d1fb + requires_dist: + - matplotlib + - numpy + - scipy + - pytest-cov>=4.0.0 ; extra == 'dev' + - pytest>=8.0.0 ; extra == 'dev' + - mkdocs-material>=9.0.0 ; extra == 'docs' + - mkdocs>=1.5.0 ; extra == 'docs' + - mkdocstrings[python]>=0.24.0 ; extra == 'docs' + requires_python: '>=3.9' - pypi: https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl name: beautifulsoup4 version: 4.14.3 @@ -6660,80 +6674,80 @@ packages: requires_dist: - pycparser ; implementation_name != 'PyPy' requires_python: '>=3.9' -- pypi: https://files.pythonhosted.org/packages/03/f4/44d3b830a20e89ff82a3134912d9a1cf6084d64f3b95dcad40f74449a654/charset_normalizer-3.4.5-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl name: charset-normalizer - version: 3.4.5 - sha256: 5bcb3227c3d9aaf73eaaab1db7ccd80a8995c509ee9941e2aae060ca6e4e5d81 + version: 3.4.6 + sha256: 11afb56037cbc4b1555a34dd69151e8e069bee82e613a73bef6e714ce733585f requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/38/9c/71336bff6934418dc8d1e8a1644176ac9088068bc571da612767619c97b3/charset_normalizer-3.4.5-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/25/6f/ffe1e1259f384594063ea1869bfb6be5cdb8bc81020fc36c3636bc8302a1/charset_normalizer-3.4.6-cp314-cp314-macosx_10_15_universal2.whl name: charset-normalizer - version: 3.4.5 - sha256: 01a1ed54b953303ca7e310fafe0fe347aab348bd81834a0bcd602eb538f89d66 + version: 3.4.6 + sha256: 9cc6e6d9e571d2f863fa77700701dae73ed5f78881efc8b3f9a4398772ff53e8 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/40/65/e7c6c77d7aaa4c0d7974f2e403e17f0ed2cb0fc135f77d686b916bf1eead/charset_normalizer-3.4.5-cp314-cp314-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/2b/58/a199d245894b12db0b957d627516c78e055adc3a0d978bc7f65ddaf7c399/charset_normalizer-3.4.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl name: charset-normalizer - version: 3.4.5 - sha256: 4481e6da1830c8a1cc0b746b47f603b653dadb690bcd851d039ffaefe70533aa + version: 3.4.6 + sha256: 530e8cebeea0d76bdcf93357aa5e41336f48c3dc709ac52da2bb167c5b8271d9 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/43/be/0f0fd9bb4a7fa4fb5067fb7d9ac693d4e928d306f80a0d02bde43a7c4aee/charset_normalizer-3.4.5-cp314-cp314-macosx_10_15_universal2.whl +- pypi: https://files.pythonhosted.org/packages/4e/ef/79a463eb0fff7f96afa04c1d4c51f8fc85426f918db467854bfb6a569ce3/charset_normalizer-3.4.6-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl name: charset-normalizer - version: 3.4.5 - sha256: 8197abe5ca1ffb7d91e78360f915eef5addff270f8a71c1fc5be24a56f3e4873 + version: 3.4.6 + sha256: 0e28d62a8fc7a1fa411c43bd65e346f3bce9716dc51b897fbe930c5987b402d5 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/4b/2f/8a1d989bfadd120c90114ab33e0d2a0cbde05278c1fc15e83e62d570f50a/charset_normalizer-3.4.5-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/60/ac/3233d262a310c1b12633536a07cde5ddd16985e6e7e238e9f3f9423d8eb9/charset_normalizer-3.4.6-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl name: charset-normalizer - version: 3.4.5 - sha256: 340810d34ef83af92148e96e3e44cb2d3f910d2bf95e5618a5c467d9f102231d + version: 3.4.6 + sha256: 9cc4fc6c196d6a8b76629a70ddfcd4635a6898756e2d9cac5565cf0654605d73 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/67/5c/ae30362a88b4da237d71ea214a8c7eb915db3eec941adda511729ac25fa2/charset_normalizer-3.4.5-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/62/28/ff6f234e628a2de61c458be2779cb182bc03f6eec12200d4a525bbfc9741/charset_normalizer-3.4.6-cp311-cp311-macosx_10_9_universal2.whl name: charset-normalizer - version: 3.4.5 - sha256: 7ad83b8f9379176c841f8865884f3514d905bcd2a9a3b210eaa446e7d2223e4d + version: 3.4.6 + sha256: 82060f995ab5003a2d6e0f4ad29065b7672b6593c8c63559beefe5b443242c3e requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/70/53/e44a4c07e8904500aec95865dc3f6464dc3586a039ef0df606eb3ac38e35/charset_normalizer-3.4.5-cp312-cp312-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/76/7e/bc8911719f7084f72fd545f647601ea3532363927f807d296a8c88a62c0d/charset_normalizer-3.4.6-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl name: charset-normalizer - version: 3.4.5 - sha256: 728c6a963dfab66ef865f49286e45239384249672cd598576765acc2a640a636 + version: 3.4.6 + sha256: 7bda6eebafd42133efdca535b04ccb338ab29467b3f7bf79569883676fc628db requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/8f/9e/bcec3b22c64ecec47d39bf5167c2613efd41898c019dccd4183f6aa5d6a7/charset_normalizer-3.4.5-cp311-cp311-macosx_10_9_universal2.whl +- pypi: https://files.pythonhosted.org/packages/80/94/8434a02d9d7f168c25767c64671fead8d599744a05d6a6c877144c754246/charset_normalizer-3.4.6-cp314-cp314-win_amd64.whl name: charset-normalizer - version: 3.4.5 - sha256: 610f72c0ee565dfb8ae1241b666119582fdbfe7c0975c175be719f940e110694 + version: 3.4.6 + sha256: 74119174722c4349af9708993118581686f343adc1c8c9c007d59be90d077f3f requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/a1/5c/724b6b363603e419829f561c854b87ed7c7e31231a7908708ac086cdf3e2/charset_normalizer-3.4.6-cp313-cp313-win_amd64.whl name: charset-normalizer - version: 3.4.5 - sha256: 0625665e4ebdddb553ab185de5db7054393af8879fb0c87bd5690d14379d6819 + version: 3.4.6 + sha256: 572d7c822caf521f0525ba1bce1a622a0b85cf47ffbdae6c9c19e3b5ac3c4389 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/9c/b6/9ee9c1a608916ca5feae81a344dffbaa53b26b90be58cc2159e3332d44ec/charset_normalizer-3.4.5-cp312-cp312-macosx_10_13_universal2.whl +- pypi: https://files.pythonhosted.org/packages/ab/20/0567efb3a8fd481b8f34f739ebddc098ed062a59fed41a8d193a61939e8f/charset_normalizer-3.4.6-cp312-cp312-win_amd64.whl name: charset-normalizer - version: 3.4.5 - sha256: ed97c282ee4f994ef814042423a529df9497e3c666dca19be1d4cd1129dc7ade + version: 3.4.6 + sha256: c8ae56368f8cc97c7e40a7ee18e1cedaf8e780cd8bc5ed5ac8b81f238614facb requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/a5/c3/84fb174e7770f2df2e1a2115090771bfbc2227fb39a765c6d00568d1aab4/charset_normalizer-3.4.5-cp310-cp310-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/c6/e3/76f2facfe8eddee0bbd38d2594e709033338eae44ebf1738bcefe0a06185/charset_normalizer-3.4.6-cp311-cp311-win_amd64.whl name: charset-normalizer - version: 3.4.5 - sha256: 02a9d1b01c1e12c27883b0c9349e0bcd9ae92e727ff1a277207e1a262b1cbf05 + version: 3.4.6 + sha256: a9e68c9d88823b274cf1e72f28cb5dc89c990edf430b0bfd3e2fb0785bfeabf4 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/a7/21/a2b1505639008ba2e6ef03733a81fc6cfd6a07ea6139a2b76421230b8dad/charset_normalizer-3.4.5-cp310-cp310-macosx_10_9_universal2.whl +- pypi: https://files.pythonhosted.org/packages/d8/8f/78f5489ffadb0db3eb7aff53d31c24531d33eb545f0c6f6567c25f49a5ff/charset_normalizer-3.4.6-cp310-cp310-win_amd64.whl name: charset-normalizer - version: 3.4.5 - sha256: 4167a621a9a1a986c73777dbc15d4b5eac8ac5c10393374109a343d4013ec765 + version: 3.4.6 + sha256: aa9cccf4a44b9b62d8ba8b4dd06c649ba683e4bf04eea606d2e94cfc2d6ff4d6 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/b9/0f/57072b253af40c8aa6636e6de7d75985624c1eb392815b2f934199340a89/charset_normalizer-3.4.5-cp313-cp313-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/e5/62/c0815c992c9545347aeea7859b50dc9044d147e2e7278329c6e02ac9a616/charset_normalizer-3.4.6-cp312-cp312-macosx_10_13_universal2.whl name: charset-normalizer - version: 3.4.5 - sha256: e37bd100d2c5d3ba35db9c7c5ba5a9228cbcffe5c4778dc824b164e5257813d7 + version: 3.4.6 + sha256: 2ef7fedc7a6ecbe99969cd09632516738a97eeb8bd7258bf8a0f23114c057dab requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl +- pypi: https://files.pythonhosted.org/packages/e6/8c/2c56124c6dc53a774d435f985b5973bc592f42d437be58c0c92d65ae7296/charset_normalizer-3.4.6-cp310-cp310-macosx_10_9_universal2.whl name: charset-normalizer - version: 3.4.5 - sha256: ac59c15e3f1465f722607800c68713f9fbc2f672b9eb649fe831da4019ae9b23 + version: 3.4.6 + sha256: 2e1d8ca8611099001949d1cdfaefc510cf0f212484fe7c565f735b68c78c3c95 requires_python: '>=3.7' -- pypi: https://files.pythonhosted.org/packages/fe/1f/a853b73d386521fd44b7f67ded6b17b7b2367067d9106a5c4b44f9a34274/charset_normalizer-3.4.5-cp311-cp311-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/fd/ce/865e4e09b041bad659d682bbd98b47fb490b8e124f9398c9448065f64fee/charset_normalizer-3.4.6-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl name: charset-normalizer - version: 3.4.5 - sha256: f8102ae93c0bc863b1d41ea0f4499c20a83229f52ed870850892df555187154a + version: 3.4.6 + sha256: 51fb3c322c81d20567019778cb5a4a6f2dc1c200b886bc0d636238e364848c89 requires_python: '>=3.7' - pypi: https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl name: colorama @@ -7247,143 +7261,143 @@ packages: - pytest-xdist ; extra == 'test-no-images' - wurlitzer ; extra == 'test-no-images' requires_python: '>=3.11' -- pypi: https://files.pythonhosted.org/packages/06/90/2cdab0974b9b5bbc1623f7876b73603aecac11b8d95b85b5b86b32de5eab/coverage-7.13.4-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/0c/c9/44fb661c55062f0818a6ffd2685c67aa30816200d5f2817543717d4b92eb/coverage-7.13.5-cp313-cp313-macosx_11_0_arm64.whl name: coverage - version: 7.13.4 - sha256: 0dd7ab8278f0d58a0128ba2fca25824321f05d059c1441800e934ff2efa52129 + version: 7.13.5 + sha256: 941617e518602e2d64942c88ec8499f7fbd49d3f6c4327d3a71d43a1973032f3 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/35/b0/d69df26607c64043292644dbb9dc54b0856fabaa2cbb1eeee3331cc9e280/coverage-7.13.4-cp310-cp310-macosx_11_0_arm64.whl +- pypi: https://files.pythonhosted.org/packages/22/e5/06b1f88f42a5a99df42ce61208bdec3bddb3d261412874280a19796fc09c/coverage-7.13.5-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl name: coverage - version: 7.13.4 - sha256: a32ebc02a1805adf637fc8dec324b5cdacd2e493515424f70ee33799573d661b + version: 7.13.5 + sha256: 6c36ddb64ed9d7e496028d1d00dfec3e428e0aabf4006583bb1839958d280510 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/44/d4/7827d9ffa34d5d4d752eec907022aa417120936282fc488306f5da08c292/coverage-7.13.4-cp310-cp310-macosx_10_9_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/29/3d/821a9a5799fac2556bcf0bd37a70d1d11fa9e49784b6d22e92e8b2f85f18/coverage-7.13.5-cp312-cp312-win_amd64.whl name: coverage - version: 7.13.4 - sha256: 0fc31c787a84f8cd6027eba44010517020e0d18487064cd3d8968941856d1415 + version: 7.13.5 + sha256: d2c87e0c473a10bffe991502eac389220533024c8082ec1ce849f4218dded810 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/5d/96/5238b1efc5922ddbdc9b0db9243152c09777804fb7c02ad1741eb18a11c0/coverage-7.13.4-cp312-cp312-macosx_11_0_arm64.whl +- pypi: https://files.pythonhosted.org/packages/35/8b/cd129b0ca4afe886a6ce9d183c44d8301acbd4ef248622e7c49a23145605/coverage-7.13.5-cp311-cp311-macosx_11_0_arm64.whl name: coverage - version: 7.13.4 - sha256: 40aa8808140e55dc022b15d8aa7f651b6b3d68b365ea0398f1441e0b04d859c3 + version: 7.13.5 + sha256: 145ede53ccbafb297c1c9287f788d1bc3efd6c900da23bf6931b09eafc931587 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/5d/a0/2ea570925524ef4e00bb6c82649f5682a77fac5ab910a65c9284de422600/coverage-7.13.4-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/4b/37/d24c8f8220ff07b839b2c043ea4903a33b0f455abe673ae3c03bbdb7f212/coverage-7.13.5-cp311-cp311-macosx_10_9_x86_64.whl name: coverage - version: 7.13.4 - sha256: 2c048ea43875fbf8b45d476ad79f179809c590ec7b79e2035c662e7afa3192e3 + version: 7.13.5 + sha256: 66a80c616f80181f4d643b0f9e709d97bcea413ecd9631e1dedc7401c8e6695d requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/61/08/3d9c8613079d2b11c185b865de9a4c1a68850cfda2b357fae365cf609f29/coverage-7.13.4-cp311-cp311-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/66/40/7732d648ab9d069a46e686043241f01206348e2bbf128daea85be4d6414b/coverage-7.13.5-cp313-cp313-win_amd64.whl name: coverage - version: 7.13.4 - sha256: 2421d591f8ca05b308cf0092807308b2facbefe54af7c02ac22548b88b95c98f + version: 7.13.5 + sha256: 631efb83f01569670a5e866ceb80fe483e7c159fac6f167e6571522636104a0b requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/76/53/c16972708cbb79f2942922571a687c52bd109a7bd51175aeb7558dff2236/coverage-7.13.4-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/69/33/e8c48488c29a73fd089f9d71f9653c1be7478f2ad6b5bc870db11a55d23d/coverage-7.13.5-cp310-cp310-macosx_10_9_x86_64.whl name: coverage - version: 7.13.4 - sha256: 8e264226ec98e01a8e1054314af91ee6cde0eacac4f465cc93b03dbe0bce2fd7 + version: 7.13.5 + sha256: e0723d2c96324561b9aa76fb982406e11d93cdb388a7a7da2b16e04719cf7ca5 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/77/4e/c0a25a425fcf5557d9abd18419c95b63922e897bc86c1f327f155ef234a9/coverage-7.13.4-cp312-cp312-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/74/8c/74fedc9663dcf168b0a059d4ea756ecae4da77a489048f94b5f512a8d0b3/coverage-7.13.5-cp313-cp313-macosx_10_13_x86_64.whl name: coverage - version: 7.13.4 - sha256: 9401ebc7ef522f01d01d45532c68c5ac40fb27113019b6b7d8b208f6e9baa126 + version: 7.13.5 + sha256: 5ec4af212df513e399cf11610cc27063f1586419e814755ab362e50a85ea69c1 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/78/13/331f94934cf6c092b8ea59ff868eb587bc8fe0893f02c55bc6c0183a192e/coverage-7.13.4-cp310-cp310-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/7d/d8/3217636d86c7e7b12e126e4f30ef1581047da73140614523af7495ed5f2d/coverage-7.13.5-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl name: coverage - version: 7.13.4 - sha256: 2cb0f1e000ebc419632bbe04366a8990b6e32c4e0b51543a6484ffe15eaeda95 + version: 7.13.5 + sha256: a1a6d79a14e1ec1832cabc833898636ad5f3754a678ef8bb4908515208bf84f4 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/92/11/a9cf762bb83386467737d32187756a42094927150c3e107df4cb078e8590/coverage-7.13.4-cp314-cp314-macosx_10_15_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/8c/49/cd14b789536ac6a4778c453c6a2338bc0a2fb60c5a5a41b4008328b9acc1/coverage-7.13.5-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl name: coverage - version: 7.13.4 - sha256: 300deaee342f90696ed186e3a00c71b5b3d27bffe9e827677954f4ee56969601 + version: 7.13.5 + sha256: 03ccc709a17a1de074fb1d11f217342fb0d2b1582ed544f554fc9fc3f07e95f5 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/a5/70/9b8b67a0945f3dfec1fd896c5cefb7c19d5a3a6d74630b99a895170999ae/coverage-7.13.4-cp313-cp313-macosx_11_0_arm64.whl +- pypi: https://files.pythonhosted.org/packages/8d/b7/4758d4f73fb536347cc5e4ad63662f9d60ba9118cb6785e9616b2ce5d7fa/coverage-7.13.5-cp314-cp314-win_amd64.whl name: coverage - version: 7.13.4 - sha256: 3599eb3992d814d23b35c536c28df1a882caa950f8f507cef23d1cbf334995ac + version: 7.13.5 + sha256: 2aa055ae1857258f9e0045be26a6d62bdb47a72448b62d7b55f4820f361a2633 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/a7/4d/1f8e723f6829977410efeb88f73673d794075091c8c7c18848d273dc9d73/coverage-7.13.4-cp314-cp314-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/8e/77/39703f0d1d4b478bfd30191d3c14f53caf596fac00efb3f8f6ee23646439/coverage-7.13.5-cp314-cp314-macosx_10_15_x86_64.whl name: coverage - version: 7.13.4 - sha256: 245e37f664d89861cf2329c9afa2c1fe9e6d4e1a09d872c947e70718aeeac505 + version: 7.13.5 + sha256: fbabfaceaeb587e16f7008f7795cd80d20ec548dc7f94fbb0d4ec2e038ce563f requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/b4/ad/b59e5b451cf7172b8d1043dc0fa718f23aab379bc1521ee13d4bd9bfa960/coverage-7.13.4-cp311-cp311-macosx_10_9_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/92/be/b1afb692be85b947f3401375851484496134c5554e67e822c35f28bf2fbc/coverage-7.13.5-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl name: coverage - version: 7.13.4 - sha256: d490ba50c3f35dd7c17953c68f3270e7ccd1c6642e2d2afe2d8e720b98f5a053 + version: 7.13.5 + sha256: ec10e2a42b41c923c2209b846126c6582db5e43a33157e9870ba9fb70dc7854b requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/d1/81/4ce2fdd909c5a0ed1f6dedb88aa57ab79b6d1fbd9b588c1ac7ef45659566/coverage-7.13.4-cp312-cp312-macosx_10_13_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/9f/cc/d938417e7a4d7f0433ad4edee8bb2acdc60dc7ac5af19e2a07a048ecbee3/coverage-7.13.5-cp310-cp310-win_amd64.whl name: coverage - version: 7.13.4 - sha256: 02231499b08dabbe2b96612993e5fc34217cdae907a51b906ac7fca8027a4459 + version: 7.13.5 + sha256: 3e1bb5f6c78feeb1be3475789b14a0f0a5b47d505bfc7267126ccbd50289999e requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/d3/28/56e6d892b7b052236d67c95f1936b6a7cf7c3e2634bf27610b8cbd7f9c60/coverage-7.13.4-cp314-cp314-macosx_11_0_arm64.whl +- pypi: https://files.pythonhosted.org/packages/a0/c3/a396306ba7db865bf96fc1fb3b7fd29bcbf3d829df642e77b13555163cd6/coverage-7.13.5-cp312-cp312-macosx_10_13_x86_64.whl name: coverage - version: 7.13.4 - sha256: 29e3220258d682b6226a9b0925bc563ed9a1ebcff3cad30f043eceea7eaf2689 + version: 7.13.5 + sha256: 460cf0114c5016fa841214ff5564aa4864f11948da9440bc97e21ad1f4ba1e01 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/db/23/aad45061a31677d68e47499197a131eea55da4875d16c1f42021ab963503/coverage-7.13.4-cp313-cp313-macosx_10_13_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/a6/16/a68a19e5384e93f811dccc51034b1fd0b865841c390e3c931dcc4699e035/coverage-7.13.5-cp312-cp312-macosx_11_0_arm64.whl name: coverage - version: 7.13.4 - sha256: b66a2da594b6068b48b2692f043f35d4d3693fb639d5ea8b39533c2ad9ac3ab9 + version: 7.13.5 + sha256: 0e223ce4b4ed47f065bfb123687686512e37629be25cc63728557ae7db261422 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/e2/0c/dbfafbe90a185943dcfbc766fe0e1909f658811492d79b741523a414a6cc/coverage-7.13.4-cp313-cp313-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/ac/68/1666e3a4462f8202d836920114fa7a5ee9275d1fa45366d336c551a162dd/coverage-7.13.5-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl name: coverage - version: 7.13.4 - sha256: e6f70dec1cc557e52df5306d051ef56003f74d56e9c4dd7ddb07e07ef32a84dd + version: 7.13.5 + sha256: 78e696e1cc714e57e8b25760b33a8b1026b7048d270140d25dafe1b0a1ee05a3 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/e4/dc/b2442d10020c2f52617828862d8b6ee337859cd8f3a1f13d607dddda9cf7/coverage-7.13.4-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/af/7f/4cd8a92531253f9d7c1bbecd9fa1b472907fb54446ca768c59b531248dc5/coverage-7.13.5-cp311-cp311-win_amd64.whl name: coverage - version: 7.13.4 - sha256: b720ce6a88a2755f7c697c23268ddc47a571b88052e6b155224347389fdf6a3b + version: 7.13.5 + sha256: 258354455f4e86e3e9d0d17571d522e13b4e1e19bf0f8596bcf9476d61e7d8a9 requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/f1/17/0cb7ca3de72e5f4ef2ec2fa0089beafbcaaaead1844e8b8a63d35173d77d/coverage-7.13.4-cp311-cp311-macosx_11_0_arm64.whl +- pypi: https://files.pythonhosted.org/packages/da/bd/b0ebe9f677d7f4b74a3e115eec7ddd4bcf892074963a00d91e8b164a6386/coverage-7.13.5-cp310-cp310-macosx_11_0_arm64.whl name: coverage - version: 7.13.4 - sha256: 19bc3c88078789f8ef36acb014d7241961dbf883fd2533d18cb1e7a5b4e28b11 + version: 7.13.5 + sha256: 52f444e86475992506b32d4e5ca55c24fc88d73bcbda0e9745095b28ef4dc0cf requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/f8/02/aa7ec01d1a5023c4b680ab7257f9bfde9defe8fdddfe40be096ac19e8177/coverage-7.13.4-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/e2/3e/51dff36d99ae14639a133d9b164d63e628532e2974d8b1edb99dd1ebc733/coverage-7.13.5-cp314-cp314-macosx_11_0_arm64.whl name: coverage - version: 7.13.4 - sha256: 8041b6c5bfdc03257666e9881d33b1abc88daccaf73f7b6340fb7946655cd10f + version: 7.13.5 + sha256: 9bb2a28101a443669a423b665939381084412b81c3f8c0fcfbac57f4e30b5b8e requires_dist: - tomli ; python_full_version <= '3.11' and extra == 'toml' requires_python: '>=3.10' @@ -7474,22 +7488,6 @@ packages: - pytest-benchmark ; extra == 'devel' - pytest-cache ; extra == 'devel' - validictory ; extra == 'devel' -- pypi: https://files.pythonhosted.org/packages/c2/a4/42e47d43b3e4b0927d5386965ed984c92c0b332b29914fd657c8bc4665da/filterpy-1.4.2.zip - name: filterpy - version: 1.4.2 - sha256: 6e247b3c9de934dee5a8baa152e88b5f50f0d0bd24e5f25496a81795d7425fe0 - requires_dist: - - numpy - - scipy - - matplotlib -- pypi: https://files.pythonhosted.org/packages/f6/1d/ac8914360460fafa1990890259b7fa5ef7ba4cd59014e782e4ab3ab144d8/filterpy-1.4.5.zip - name: filterpy - version: 1.4.5 - sha256: 4f2a4d39e4ea601b9ab42b2db08b5918a9538c168cff1c6895ae26646f3d73b1 - requires_dist: - - numpy - - scipy - - matplotlib - pypi: https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl name: flake8 version: 7.3.0 @@ -7499,10 +7497,10 @@ packages: - pycodestyle>=2.14.0,<2.15.0 - pyflakes>=3.4.0,<3.5.0 requires_python: '>=3.9' -- pypi: https://files.pythonhosted.org/packages/0b/a1/d16318232964d786907b9b3613b8409f74cf0be2da400854509d3a864e43/fonttools-4.62.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/03/c5/0e3966edd5ec668d41dfe418787726752bc07e2f5fd8c8f208615e61fa89/fonttools-4.62.1-cp313-cp313-macosx_10_13_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 31a804c16d76038cc4e3826e07678efb0a02dc4f15396ea8e07088adbfb2578e + version: 4.62.1 + sha256: 68959f5fc58ed4599b44aad161c2837477d7f35f5f79402d97439974faebfebe requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7533,10 +7531,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/1a/64/61f69298aa6e7c363dcf00dd6371a654676900abe27d1effd1a74b43e5d0/fonttools-4.62.0-cp314-cp314-macosx_10_15_universal2.whl +- pypi: https://files.pythonhosted.org/packages/24/7f/66d3f8a9338a9b67fe6e1739f47e1cd5cee78bd3bc1206ef9b0b982289a5/fonttools-4.62.1-cp311-cp311-macosx_10_9_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 4fa5a9c716e2f75ef34b5a5c2ca0ee4848d795daa7e6792bf30fd4abf8993449 + version: 4.62.1 + sha256: 9dde91633f77fa576879a0c76b1d89de373cae751a98ddf0109d54e173b40f14 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7567,10 +7565,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/2e/9f/91081ffe5881253177c175749cce5841f5ec6e931f5d52f4a817207b7429/fonttools-4.62.0-cp314-cp314-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/28/63/cd0c3b26afe60995a5295f37c246a93d454023726c3261cfbb3559969bb9/fonttools-4.62.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl name: fonttools - version: 4.62.0 - sha256: a5f974006d14f735c6c878fc4b117ad031dc93638ddcc450ca69f8fd64d5e104 + version: 4.62.1 + sha256: 8d337fdd49a79b0d51c4da87bc38169d21c3abbf0c1aa9367eff5c6656fb6dae requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7601,10 +7599,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/4d/8b/ba59069a490f61b737e064c3129453dbd28ee38e81d56af0d04d7e6b4de4/fonttools-4.62.0-cp312-cp312-macosx_10_13_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/28/b1/0c2ab56a16f409c6c8a68816e6af707827ad5d629634691ff60a52879792/fonttools-4.62.1-cp312-cp312-win_amd64.whl name: fonttools - version: 4.62.0 - sha256: 7199c73b326bad892f1cb53ffdd002128bfd58a89b8f662204fbf1daf8d62e85 + version: 4.62.1 + sha256: 9e7863e10b3de72376280b515d35b14f5eeed639d1aa7824f4cf06779ec65e42 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7635,10 +7633,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/5c/57/a23a051fcff998fdfabdd33c6721b5bad499da08b586d3676993410071f0/fonttools-4.62.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/36/f0/2888cdac391807d68d90dcb16ef858ddc1b5309bfc6966195a459dd326e2/fonttools-4.62.1-cp314-cp314-macosx_10_15_universal2.whl name: fonttools - version: 4.62.0 - sha256: 3e2ff573de2775508c8a366351fb901c4ced5dc6cf2d87dd15c973bedcdd5216 + version: 4.62.1 + sha256: fa1d16210b6b10a826d71bed68dd9ec24a9e218d5a5e2797f37c573e7ec215ca requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7669,10 +7667,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/77/ce/f5a4c42c117f8113ce04048053c128d17426751a508f26398110c993a074/fonttools-4.62.0-cp311-cp311-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/38/60/35186529de1db3c01f5ad625bde07c1f576305eab6d86bbda4c58445f721/fonttools-4.62.1-cp313-cp313-win_amd64.whl name: fonttools - version: 4.62.0 - sha256: 4da779e8f342a32856075ddb193b2a024ad900bc04ecb744014c32409ae871ed + version: 4.62.1 + sha256: 7aa21ff53e28a9c2157acbc44e5b401149d3c9178107130e82d74ceb500e5056 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7703,10 +7701,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/82/c7/985c1670aa6d82ef270f04cde11394c168f2002700353bd2bde405e59b8f/fonttools-4.62.0-cp313-cp313-macosx_10_13_universal2.whl +- pypi: https://files.pythonhosted.org/packages/3b/56/6f389de21c49555553d6a5aeed5ac9767631497ac836c4f076273d15bd72/fonttools-4.62.1-cp313-cp313-macosx_10_13_universal2.whl name: fonttools - version: 4.62.0 - sha256: 274c8b8a87e439faf565d3bcd3f9f9e31bca7740755776a4a90a4bfeaa722efa + version: 4.62.1 + sha256: c22b1014017111c401469e3acc5433e6acf6ebcc6aa9efb538a533c800971c79 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7737,10 +7735,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/82/e0/9db48ec7f6b95bae7b20667ded54f18dba8e759ef66232c8683822ae26fc/fonttools-4.62.0-cp310-cp310-macosx_10_9_universal2.whl +- pypi: https://files.pythonhosted.org/packages/42/09/7dbe3d7023f57d9b580cfa832109d521988112fd59dddfda3fddda8218f9/fonttools-4.62.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 62b6a3d0028e458e9b59501cf7124a84cd69681c433570e4861aff4fb54a236c + version: 4.62.1 + sha256: 7bca7a1c1faf235ffe25d4f2e555246b4750220b38de8261d94ebc5ce8a23c23 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7771,10 +7769,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/86/c8/c6669e42d2f4efd60d38a3252cebbb28851f968890efb2b9b15f9d1092b0/fonttools-4.62.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/47/d4/dbacced3953544b9a93088cc10ef2b596d348c983d5c67a404fa41ec51ba/fonttools-4.62.1-cp312-cp312-macosx_10_13_universal2.whl name: fonttools - version: 4.62.0 - sha256: 840632ea9c1eab7b7f01c369e408c0721c287dfd7500ab937398430689852fd1 + version: 4.62.1 + sha256: 90365821debbd7db678809c7491ca4acd1e0779b9624cdc6ddaf1f31992bf974 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7805,10 +7803,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/8a/d7/8e4845993ee233c2023d11babe9b3dae7d30333da1d792eeccebcb77baab/fonttools-4.62.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/4b/b2/e521803081f8dc35990816b82da6360fa668a21b44da4b53fc9e77efcd62/fonttools-4.62.1-cp314-cp314-macosx_10_15_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 591220d5333264b1df0d3285adbdfe2af4f6a45bbf9ca2b485f97c9f577c49ff + version: 4.62.1 + sha256: aa69d10ed420d8121118e628ad47d86e4caa79ba37f968597b958f6cceab7eca requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7839,10 +7837,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/ab/9d/7ad1ffc080619f67d0b1e0fa6a0578f0be077404f13fd8e448d1616a94a3/fonttools-4.62.0-cp312-cp312-macosx_10_13_universal2.whl +- pypi: https://files.pythonhosted.org/packages/5a/ff/532ed43808b469c807e8cb6b21358da3fe6fd51486b3a8c93db0bb5d957f/fonttools-4.62.1-cp310-cp310-macosx_10_9_universal2.whl name: fonttools - version: 4.62.0 - sha256: 22bde4dc12a9e09b5ced77f3b5053d96cf10c4976c6ac0dee293418ef289d221 + version: 4.62.1 + sha256: ad5cca75776cd453b1b035b530e943334957ae152a36a88a320e779d61fc980c requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7873,10 +7871,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/c0/7a/9aeec114bc9fc00d757a41f092f7107863d372e684a5b5724c043654477c/fonttools-4.62.0-cp311-cp311-macosx_10_9_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/66/9e/a769c8e99b81e5a87ab7e5e7236684de4e96246aae17274e5347d11ebd78/fonttools-4.62.1-cp312-cp312-macosx_10_13_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 153afc3012ff8761b1733e8fbe5d98623409774c44ffd88fbcb780e240c11d13 + version: 4.62.1 + sha256: 12859ff0b47dd20f110804c3e0d0970f7b832f561630cd879969011541a464a9 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7907,10 +7905,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/c1/dc/c409c8ceec0d3119e9ab0b7b1a2e3c76d1f4d66e4a9db5c59e6b7652e7df/fonttools-4.62.0-cp313-cp313-macosx_10_13_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/6b/67/74b070029043186b5dd13462c958cb7c7f811be0d2e634309d9a1ffb1505/fonttools-4.62.1-cp314-cp314-win_amd64.whl name: fonttools - version: 4.62.0 - sha256: 93e27131a5a0ae82aaadcffe309b1bae195f6711689722af026862bede05c07c + version: 4.62.1 + sha256: 1eecc128c86c552fb963fe846ca4e011b1be053728f798185a1687502f6d398e requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7941,10 +7939,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/c6/57/6b08756fe4455336b1fe160ab3c11fccc90768ccb6ee03fb0b45851aace4/fonttools-4.62.0-cp314-cp314-macosx_10_15_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/85/e4/2318d2b430562da7227010fb2bb029d2fa54d7b46443ae8942bab224e2a0/fonttools-4.62.1-cp310-cp310-macosx_10_9_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 625f5cbeb0b8f4e42343eaeb4bc2786718ddd84760a2f5e55fdd3db049047c00 + version: 4.62.1 + sha256: 0b3ae47e8636156a9accff64c02c0924cbebad62854c4a6dbdc110cd5b4b341a requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -7975,10 +7973,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/cd/06/cc96468781a4dc8ae2f14f16f32b32f69bde18cb9384aad27ccc7adf76f7/fonttools-4.62.0-cp312-cp312-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/88/39/23ff32561ec8d45a4d48578b4d241369d9270dc50926c017570e60893701/fonttools-4.62.1-cp311-cp311-macosx_10_9_universal2.whl name: fonttools - version: 4.62.0 - sha256: 658ab837c878c4d2a652fcbb319547ea41693890e6434cf619e66f79387af3b8 + version: 4.62.1 + sha256: 40975849bac44fb0b9253d77420c6d8b523ac4dcdcefeff6e4d706838a5b80f7 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -8009,10 +8007,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/dd/45/86eccfdc922cb9fafc63189a9793fa9f6dd60e68a07be42e454ef2c0deae/fonttools-4.62.0-cp310-cp310-macosx_10_9_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/9b/8a/99c8b3c3888c5c474c08dbfd7c8899786de9604b727fcefb055b42c84bba/fonttools-4.62.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 966557078b55e697f65300b18025c54e872d7908d1899b7314d7c16e64868cb2 + version: 4.62.1 + sha256: 149f7d84afca659d1a97e39a4778794a2f83bf344c5ee5134e09995086cc2392 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -8043,10 +8041,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/e4/33/63d79ca41020dd460b51f1e0f58ad1ff0a36b7bcbdf8f3971d52836581e9/fonttools-4.62.0-cp311-cp311-macosx_10_9_universal2.whl +- pypi: https://files.pythonhosted.org/packages/cc/a1/40a5c4d8e28b0851d53a8eeeb46fbd73c325a2a9a165f290a5ed90e6c597/fonttools-4.62.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 196cafef9aeec5258425bd31a4e9a414b2ee0d1557bca184d7923d3d3bcd90f9 + version: 4.62.1 + sha256: 1c5c25671ce8805e0d080e2ffdeca7f1e86778c5cbfbeae86d7f866d8830517b requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -8077,10 +8075,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/e9/ee/08c0b7f8bac6e44638de6fe9a3e710a623932f60eccd58912c4d4743516d/fonttools-4.62.0-cp310-cp310-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/d3/97/bf54c5b3f2be34e1f143e6db838dfdc54f2ffa3e68c738934c82f3b2a08d/fonttools-4.62.1-cp311-cp311-win_amd64.whl name: fonttools - version: 4.62.0 - sha256: 9bf75eb69330e34ad2a096fac67887102c8537991eb6cac1507fc835bbb70e0a + version: 4.62.1 + sha256: e8514f4924375f77084e81467e63238b095abda5107620f49421c368a6017ed2 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -8111,10 +8109,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/f5/7a/e25245a30457595740041dba9d0ea8ec1b2517f2f1a6a741f15eba1a4edc/fonttools-4.62.0-cp313-cp313-win_amd64.whl +- pypi: https://files.pythonhosted.org/packages/dd/ec/f53f626f8f3e89f4cadd8fc08f3452c8fd182c951ad5caa35efac22b29ab/fonttools-4.62.1-cp310-cp310-win_amd64.whl name: fonttools - version: 4.62.0 - sha256: 6826a5aa53fb6def8a66bf423939745f415546c4e92478a7c531b8b6282b6c3b + version: 4.62.1 + sha256: 5a648bde915fba9da05ae98856987ca91ba832949a9e2888b48c47ef8b96c5a9 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -8145,10 +8143,10 @@ packages: - skia-pathops>=0.5.0 ; extra == 'all' - uharfbuzz>=0.45.0 ; extra == 'all' requires_python: '>=3.10' -- pypi: https://files.pythonhosted.org/packages/fb/bc/60d93477b653eeb1ddf5f9ec34be689b79234d82dbdded269ac0252715b8/fonttools-4.62.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl +- pypi: https://files.pythonhosted.org/packages/e2/98/8b1e801939839d405f1f122e7d175cebe9aeb4e114f95bfc45e3152af9a7/fonttools-4.62.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl name: fonttools - version: 4.62.0 - sha256: 106aec9226f9498fc5345125ff7200842c01eda273ae038f5049b0916907acee + version: 4.62.1 + sha256: 6706d1cb1d5e6251a97ad3c1b9347505c5615c112e66047abbef0f8545fa30d1 requires_dist: - lxml>=4.0 ; extra == 'lxml' - brotli>=1.0.1 ; platform_python_implementation == 'CPython' and extra == 'woff' @@ -8389,9 +8387,9 @@ packages: - socksio==1.* ; extra == 'socks' - zstandard>=0.18.0 ; extra == 'zstd' requires_python: '>=3.8' -- conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda - sha256: 142a722072fa96cf16ff98eaaf641f54ab84744af81754c292cb81e0881c0329 - md5: 186a18e3ba246eccfc7cff00cd19a870 +- conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda + sha256: fbf86c4a59c2ed05bbffb2ba25c7ed94f6185ec30ecb691615d42342baa1a16a + md5: c80d8a3b84358cb967fa81e7075fbc8a depends: - __glibc >=2.17,<3.0.a0 - libgcc >=14 @@ -8399,18 +8397,18 @@ packages: license: MIT license_family: MIT purls: [] - size: 12728445 - timestamp: 1767969922681 -- conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.2-hef89b57_0.conda - sha256: 24bc62335106c30fecbcc1dba62c5eba06d18b90ea1061abd111af7b9c89c2d7 - md5: 114e6bfe7c5ad2525eb3597acdbf2300 + size: 12723451 + timestamp: 1773822285671 +- conda: https://conda.anaconda.org/conda-forge/osx-arm64/icu-78.3-hef89b57_0.conda + sha256: 3a7907a17e9937d3a46dfd41cffaf815abad59a569440d1e25177c15fd0684e5 + md5: f1182c91c0de31a7abd40cedf6a5ebef depends: - __osx >=11.0 license: MIT license_family: MIT purls: [] - size: 12389400 - timestamp: 1772209104304 + size: 12361647 + timestamp: 1773822915649 - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl name: idna version: '3.11' @@ -8922,10 +8920,10 @@ packages: - pytest-timeout ; extra == 'test' - pytest>=7.0 ; extra == 'test' requires_python: '>=3.8' -- pypi: https://files.pythonhosted.org/packages/b9/52/372d3494766d690dfdd286871bf5f7fb9a6c61f7566ccaa7153a163dd1df/jupyterlab-4.5.5-py3-none-any.whl +- pypi: https://files.pythonhosted.org/packages/e1/1b/dad6fdcc658ed7af26fdf3841e7394072c9549a8b896c381ab49dd11e2d9/jupyterlab-4.5.6-py3-none-any.whl name: jupyterlab - version: 4.5.5 - sha256: a35694a40a8e7f2e82f387472af24e61b22adcce87b5a8ab97a5d9c486202a6d + version: 4.5.6 + sha256: d6b3dac883aa4d9993348e0f8e95b24624f75099aed64eab6a4351a9cdd1e580 requires_dist: - async-lru>=1.0.0 - httpx>=0.25.0,<1 @@ -10471,14 +10469,14 @@ packages: version: 1.6.0 sha256: 87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c requires_python: '>=3.5' -- pypi: https://files.pythonhosted.org/packages/59/01/05e5387b53e0f549212d5eff58845886f3827617b5c9409c966ddc07cb6d/notebook-7.5.4-py3-none-any.whl +- pypi: https://files.pythonhosted.org/packages/f8/aa/cbd1deb9f07446241e88f8d5fecccd95b249bca0b4e5482214a4d1714c49/notebook-7.5.5-py3-none-any.whl name: notebook - version: 7.5.4 - sha256: 860e31782b3d3a25ca0819ff039f5cf77845d1bf30c78ef9528b88b25e0a9850 + version: 7.5.5 + sha256: a7c14dbeefa6592e87f72290ca982e0c10f5bbf3786be2a600fda9da2764a2b8 requires_dist: - jupyter-server>=2.4.0,<3 - jupyterlab-server>=2.28.0,<3 - - jupyterlab>=4.5.5,<4.6 + - jupyterlab>=4.5.6,<4.6 - notebook-shim>=0.2,<0.3 - tornado>=6.2.0 - hatch ; extra == 'dev' @@ -14521,8 +14519,8 @@ packages: requires_python: '>=3.8' - pypi: ./ name: rdtools - version: 3.1.1.dev17+g20899bcc8.d20260311 - sha256: 62688b3090071bdcbe9e6b1e0a1568e140a61dbaf6c24cd7a38f7bd9af2f90a3 + version: 3.1.2.dev24+g98907c1a4.d20260320 + sha256: ace3264e636d8b81492291d93d785111c3b043527ee0d311532c4a3d7e239be9 requires_dist: - matplotlib>=3.5.3 - numpy>=1.22.4 @@ -14535,7 +14533,7 @@ packages: - pvlib>=0.13.1 - scikit-learn>=1.1.3,!=1.6.0 - arch>=5.6 - - filterpy>=1.4.2 + - bayesian-filters>=1.4.5 - sphinx==7.4.7 ; extra == 'doc' - nbsphinx==0.9.5 ; extra == 'doc' - nbsphinx-link==1.3.1 ; extra == 'doc' diff --git a/pyproject.toml b/pyproject.toml index 228386be3..f4c264f2a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -50,7 +50,7 @@ dependencies = [ "pvlib >= 0.13.1", "scikit-learn >= 1.1.3, != 1.6.0", "arch >= 5.6", - "filterpy >= 1.4.2", + "bayesian-filters >= 1.4.5", ] [project.optional-dependencies] @@ -164,7 +164,7 @@ xgboost = "==1.7.0.post0" pvlib = "==0.13.1" scikit-learn = "==1.1.3" arch = "==5.6.0" -filterpy = "==1.4.2" +bayesian-filters = "==1.4.5" # --- Environments --- From 51ea5b61548f99a72a8753fa2e6332e8def16cc3 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 15:18:42 -0400 Subject: [PATCH 15/18] update package imports --- rdtools/soiling.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/rdtools/soiling.py b/rdtools/soiling.py index 9fbbe27c9..9a49ed9ab 100644 --- a/rdtools/soiling.py +++ b/rdtools/soiling.py @@ -13,8 +13,8 @@ import pandas as pd import numpy as np from scipy.stats.mstats import theilslopes -from filterpy.kalman import KalmanFilter -from filterpy.common import Q_discrete_white_noise +from bayesian_filters.kalman import KalmanFilter +from bayesian_filters.common import Q_discrete_white_noise import itertools import bisect import time From a5b226a2cd1847e33b311ea4ca0e7d4b53d78f00 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 15:28:39 -0400 Subject: [PATCH 16/18] delete duplicate line --- docs/sphinx/source/developer_notes.rst | 1 - 1 file changed, 1 deletion(-) diff --git a/docs/sphinx/source/developer_notes.rst b/docs/sphinx/source/developer_notes.rst index 4c2d9b0a2..dba986e09 100644 --- a/docs/sphinx/source/developer_notes.rst +++ b/docs/sphinx/source/developer_notes.rst @@ -168,7 +168,6 @@ Installing optional dependencies RdTools has extra dependencies for running its test suite and building its documentation. These packages aren't necessary for running RdTools itself and are only needed if you want to contribute source code to RdTools. -are only needed if you want to contribute source code to RdTools. .. note:: These will install RdTools along with other packages necessary to build its From 4e21a003fab3becfc635860f14bff84514b93c28 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 16:09:43 -0400 Subject: [PATCH 17/18] add new multi year nb to nbval --- .github/workflows/nbval.yaml | 3 +- docs/Multi-year_on_year_example.ipynb | 146 +++++++++++++++++++++---- docs/sphinx/source/developer_notes.rst | 7 +- 3 files changed, 130 insertions(+), 26 deletions(-) diff --git a/.github/workflows/nbval.yaml b/.github/workflows/nbval.yaml index 939edb00b..2f0c9768e 100644 --- a/.github/workflows/nbval.yaml +++ b/.github/workflows/nbval.yaml @@ -13,7 +13,8 @@ jobs: 'TrendAnalysis_example.ipynb', 'TrendAnalysis_example_NSRDB.ipynb', 'degradation_and_soiling_example.ipynb', - 'system_availability_example.ipynb' + 'system_availability_example.ipynb', + 'Multi-year_on_year_example.ipynb' ] steps: diff --git a/docs/Multi-year_on_year_example.ipynb b/docs/Multi-year_on_year_example.ipynb index 8c3dfa225..fc4deb26c 100644 --- a/docs/Multi-year_on_year_example.ipynb +++ b/docs/Multi-year_on_year_example.ipynb @@ -26,7 +26,14 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:05.523308Z", + "iopub.status.busy": "2026-03-20T20:03:05.522102Z", + "iopub.status.idle": "2026-03-20T20:03:08.334396Z", + "shell.execute_reply": "2026-03-20T20:03:08.333057Z" + } + }, "outputs": [], "source": [ "import pandas as pd\n", @@ -40,7 +47,14 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:08.337613Z", + "iopub.status.busy": "2026-03-20T20:03:08.337165Z", + "iopub.status.idle": "2026-03-20T20:03:08.352057Z", + "shell.execute_reply": "2026-03-20T20:03:08.350326Z" + } + }, "outputs": [], "source": [ "#Update the style of plots\n", @@ -58,7 +72,14 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:08.355271Z", + "iopub.status.busy": "2026-03-20T20:03:08.354904Z", + "iopub.status.idle": "2026-03-20T20:03:08.359508Z", + "shell.execute_reply": "2026-03-20T20:03:08.358516Z" + } + }, "outputs": [], "source": [ "# Set the random seed for numpy to ensure consistent results\n", @@ -82,7 +103,14 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:08.362269Z", + "iopub.status.busy": "2026-03-20T20:03:08.361991Z", + "iopub.status.idle": "2026-03-20T20:03:08.415433Z", + "shell.execute_reply": "2026-03-20T20:03:08.414310Z" + } + }, "outputs": [], "source": [ "# Import the example data\n", @@ -103,7 +131,14 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:08.418452Z", + "iopub.status.busy": "2026-03-20T20:03:08.418033Z", + "iopub.status.idle": "2026-03-20T20:03:12.953866Z", + "shell.execute_reply": "2026-03-20T20:03:12.952666Z" + } + }, "outputs": [], "source": [ "df = df.rename(columns = {\n", @@ -164,7 +199,14 @@ { "cell_type": "code", "execution_count": 6, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:12.956963Z", + "iopub.status.busy": "2026-03-20T20:03:12.956678Z", + "iopub.status.idle": "2026-03-20T20:03:29.918158Z", + "shell.execute_reply": "2026-03-20T20:03:29.916790Z" + } + }, "outputs": [], "source": [ "ta = rdtools.TrendAnalysis(df['power_ac'], df['poa'],\n", @@ -190,7 +232,14 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:29.921486Z", + "iopub.status.busy": "2026-03-20T20:03:29.921225Z", + "iopub.status.idle": "2026-03-20T20:03:56.435824Z", + "shell.execute_reply": "2026-03-20T20:03:56.434273Z" + } + }, "outputs": [], "source": [ "ta.sensor_analysis(analyses=['yoy_degradation'], yoy_kwargs={'label': 'center'})" @@ -206,7 +255,14 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:56.438819Z", + "iopub.status.busy": "2026-03-20T20:03:56.438474Z", + "iopub.status.idle": "2026-03-20T20:03:56.449342Z", + "shell.execute_reply": "2026-03-20T20:03:56.448434Z" + } + }, "outputs": [ { "name": "stdout", @@ -230,8 +286,15 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, + "execution_count": 9, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:56.477617Z", + "iopub.status.busy": "2026-03-20T20:03:56.477205Z", + "iopub.status.idle": "2026-03-20T20:03:56.482596Z", + "shell.execute_reply": "2026-03-20T20:03:56.481776Z" + } + }, "outputs": [ { "name": "stdout", @@ -256,11 +319,18 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:56.485483Z", + "iopub.status.busy": "2026-03-20T20:03:56.485208Z", + "iopub.status.idle": "2026-03-20T20:03:57.114696Z", + "shell.execute_reply": "2026-03-20T20:03:57.113542Z" + } + }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -287,11 +357,18 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:03:57.117714Z", + "iopub.status.busy": "2026-03-20T20:03:57.117373Z", + "iopub.status.idle": "2026-03-20T20:04:00.899061Z", + "shell.execute_reply": "2026-03-20T20:04:00.897200Z" + } + }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdAAAAElCAYAAABUArOqAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjgsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvwVt1zgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAejlJREFUeJztnQWYE1cXhk9kBdvFFnd3d3eXQqGUn9IiLVAKFCq4F1pa2gKFAqW4VqCluLu7uzssuthKkvmf72YnG5lkk6wmOe/zZDeZTJKRO3PuPfec76gkSZKIYRiGYRiXULu2OsMwDMMwbEAZhmEYxk14BMowDMMwbsAGlGEYhmHcgA0owzAMw7gBG1CGYRiGcQM2oAzDMAzjBmxAGYZhGMYN2IAyDMMwjBuwAY1nbty4QSqVirp06UJJCbahTp065AvMnz9f7C/+ezs4p9jXhMbT2s+OHTvENo8ePTqpN8Uj8PRrRpVM2meSG1C9Xk+///471a5dm9KnT09+fn6UKVMmKlWqFH388ce0atUqrzrxyY22bduK4/nzzz/bXefw4cPivOTNm5fCwsJi/U6dTkeVK1cW3/vvv//aXQ/vYR2si88wiUeePHnEw1NILh1TxnvYEQ+dLi0lsfFs0aIFbdiwgdKmTUvNmzenHDlyUGRkJJ09e5aWLl1KFy5coFatWiXlZno16LwcOHCAhg4dSg0bNqSSJUtavP/mzRv64IMPyGAw0KJFiygoKCjW79RqtbR48WIqW7YsffLJJ1SlShXKmjWrxToPHjygHj16UKpUqWjJkiXiM0zy4fz585QyZUryFCpVqiS2OWPGjEm9KR5BmzZtFK9LxjWS9K61bNkyYTxLly5NO3fupODgYJub98GDB5Ns+3yBDBky0Lx586hp06bUqVMnMdoMCAgwvf/ll1/SpUuXhIGtUaOG099bsGBBMart2bMnde3aldavX2/heuzWrRs9fvyYZs2aRQUKFIj3/WLiRpEiRTzqEMLYe9o2JyW411rfbxk3kJKQTz/9FJVgpEmTJjm1fu3atcX6So/r16+Lde7evSuNGTNGqlatmpQ5c2bJz89Pypo1q9SxY0fp7NmzNt+Jz+HzH330kXjeoUMHKUOGDFJAQIBUvnx5afXq1YrbEhYWJg0YMEDKnj27WLdw4cLSTz/9JF29etX0feZcvHhRGjRokPjOjBkzSv7+/lKuXLmkTz75RLp9+7bN92/fvl18z6hRo6SDBw9KzZo1k9KlS2exrxEREdLYsWOlfPnyie/LkyePNGzYMCk8PFysh+PlLH379hWfwT7JrF27VizDNkdGRoplz58/lwYPHiwVKlRI7HfatGmlRo0aSZs3b1b83latWonvmDJlimnZr7/+Kpa1bt1acoXLly9L7dq1E7+ZMmVKqWrVqtKaNWukefPmie/Df2twbD/77DMpb9684hilT59eatmypXTo0CHF37h3757UpUsXKSQkRAoMDJRKly4tzZ8/3+J8KLVJnAu0OxwX/I58/nG8fvjhB6lu3bqiraA94vxjG/bt22d3X5ctWyaVK1dObAO25YMPPhBtW/49c/DbU6dOlZo2bSraFH4fbaV+/frSunXrLNaV90PpYd5m7bUfV86/+TE7fvy4aMPBwcFSihQppFq1akl79+6VnAGft7fN8jmP7fyg/eL84FrBdmP7Z82aZVpvxowZUokSJcTxxnkaOXKkpNfrFbfnwIED0rvvvmu6v+TIkUPq0aOHOD+ugHsIrt/ixYtLadKkkVKnTi2277333pOOHDkSp9+NrV3G1zUT5uI+KCFvK+5buH/hPobfxfeMHj1a7IM1cW2fOA722hTakrNok3r0AzDCcQbMf8DV+99//1Hr1q2pTJkypvewHOzatYsmTJhAdevWpXfffZdSp05Nly9fpuXLl4v51L1794oRrzU3b94UbqB8+fJR586d6enTp/Tnn3+K39myZYv4PpmIiAiqX7++GK3huzBye/78OX3zzTdiJK3EP//8QzNnzhTfU61aNfL39xdu6tmzZ9Pq1avpyJEjlD17dpvP7d+/n7777jsx+pNHbfgs2tB7770njkX+/PmpT58+wvU9d+5cOn36NLnKDz/8QFu3bqXJkycLVzr2C7+Hnj1crJgDxT5Wr16dzp07RxUrVqT+/fuL7fnrr7+oUaNGNGPGDDHiNAf7B7fwoEGDqEGDBsJV+/XXX1PmzJmF+9hZcA6rVq1KT548EaNlnPsrV67QO++8I14rcezYMbFdOJeNGzcW873Y3pUrV4rjiTnYZs2amdZ/9OiR+A20hVq1aonzBFdz7969xfc4Am0N7QHbgm3CPD6AW3HYsGHi+3Bc06VLR7du3RJtEaNynPsmTZpYfNekSZPoiy++EG36ww8/FP83btwotkdp1ID9+/zzz8X7cMOHhITQ/fv3xXdj/3CcEU8AMO85atQocZ4BzqGM+fWkhDvnH6Bto33h2GI7sP8rVqwQ19CJEyeocOHCDn8XwSL47SlTpoh2iePr7DbLvP/++8KbheOBtoz7AaYQ8PzUqVO0YMECMZ2EbcK5GTt2rGj7aLfm4PrC5+ClwdRSzpw5RduUr2NMh+TKlSvW7cH1i/O+b98+03HBtXHnzh3avn071axZk8qXLx/n37XXLu3hyjUjubgPsYH7Gba1Xbt24rzg3ob5SbQfnJPYgudcaZ9yG8J5R/yNeUCSS7EBUhJy7Ngx0ZNSqVSih71ixQrpxo0bDj/jqOcEHj58KHpF1pw4cUJKlSqV1KRJE8URKB7o7ZizYcMGsRw9e3PGjx8vlrdt29ail3rt2jXTKNF6BHrnzh3Rw7Jm48aNklqtlnr16mV3pDBz5kybzy1ZskS8V6VKFent27em5U+ePBE9N1dHoACjBPT80APHPuM7pk+fbnofvV0sw3+DwWBafunSJSkoKEh8Vh4dmyOPZMuUKSNVrFhRPLceGcVGw4YNxecmT55ssXzlypU2oxEQFRUl5c+fX/RCd+zYYfEZ9NizZcsmZcmSxeKcdOvWTXzPwIEDbdoO9s3RCKdkyZJSaGioYo9YaTl6+fCMFClSxGI5jh+uCbQj82OJdob2Ju+rOdgHJS8GfhsjA3zXmzdvLN7LnTu3eNhDqf24ev7N27D19Yo2jeXwQjmDuadIidhGoBUqVJCePXtmWg5PEY4zRigY8eD6lMF68ELBU4B2ZO5FwmfQrszXB1u2bBHX8TvvvOPU/pw6dUpsl9L6ONdPnz6N0+/G1i6V7qOuXjOnXNgHR8jbWrBgQYvP4L6G+xveW7hwYYK1T+s24wpJakDBn3/+KU6K+RAaLgOclFWrVrlsQB0BNwQah+yONL8wcTPR6XQ2n4FLDBeTOQUKFBCN9sqVK3bdTfYudCXQyOEuMUc+uTA6SjRo0EC8v23bNrvHyFUDCr7//nvTeWjevLlpOdwocJvCRQMjbc3w4cPFZ+AucuSux6N3794ubROMAz6HY6R0juQL0LxNyIb1q6++UvxOGGK8D+Mu7x9ci3AxKnXAPv74Y4c3aPyeq8hu85s3b5qWjRs3TiyDC9Ea3PTR7lzp92JaAevv3LkzTgbUnfMvt+Hq1avbrI9rUKvViumBxDCgMDTWwK2O9+bMmWPzHtz4eM+8Q9+/f3+xDNMGSuCepdFoFNuPNbLxwdRSbLjzu7G1S6X7qKvXzCkX9sER8rZaG0nz81qnTp0Ea59xMaBJHvqIYTsiwjDk37NnDx0/flz8h8sAD7iw5NQVZ1m7dq1wl2LojyG8dYoElllHn8EVpNFobL4LrhK4UWVevnwpXIdYDtepNXAFjBkzxmY5zjlcodiXkydP0rNnz0QUsgzcskrArWzP1aJWqxUDe+KSH/XVV18JFyJclxMnTjQtv3jxogjqgosE6UbW1KtXj8aNGyfOnxI//fSTcKGAH3/80aVtkr8T+6p0jrC/1q5z+ZzBHasUpg73l+xihUsK+/f27VuqUKECpUmTxmZ9/DbcZfawd54Apg3gfsQ2wU0MV7s5d+/eNbnfcF4B3ErWYHoB7Q77ZA2mA3C+MIUB9214eLjNb8SFuJx/HFNr4KKDGx/XQWKgtA3ZsmUT/5XcjPJ0CtyRuXPntmhTaGtwNVqDc4trGlNS+E7cv+Citr7PwH1YrFgx8RyBlDifmCpCG8N2Wt8LXP1dZ9ulNa5eM8Vc2AdnUGrz8jVv774SX/cnd0lyAypfTPBRy/NMaAyYI8Ec3MKFC4WBNZ/3cARuVPB9Y64J80G4MWEuAwYYDRrGC3OY1shzqNbAp48UDpkXL16I/7j4lciSJYvicsxpYd4JhhtzC7hAU6RIId6DUVW6KTr6PmyHnDfr7GecAUZZjsKVt0/+PWAv7F1ejnkIJcy/y/y5M7hzzDFXCv7++2+H3/3q1SunfsPeckfbADBnhDmdwMBA0R7R6ULqDo4z8tBwUzRvj87sq3VbwfwXbhDoKGIOD3NkSDfCb+AGjrkkpTbvCnE5/46uLfNOZEKiNHcsp045ei8qKsqmTZl3LB21KdxvMMdmzkcffSTuZTAK27ZtE3OtmI+V51rRecM6iHtA/IY7v+vuvcDVa0bjwj44g1Kbx3lAahI6CY6I6/3Jow2oNTgxGJkiGAa9BpwkZwwobiDoOaHRoCdvfTDNR5LuIl9sDx8+VHwfIzdrcPJ/+eUXKlGihJhwtx7hoAdnD3sjb2wHJvpxgVsbUaVtiK/9tvfdGPWYr5cQv+3KMZc/A+PhTB6xnN9q7zfsLY/tPI0YMUL0xuENKVq0qMV7CGiwHjmb72vx4sWd2ldcIxg9w4tj7X3ATQzHwJPPf3JB3jfcrJ3Jh0bH2JHgCzr58PbgAa8W2sJvv/1G06ZNEzd65F2787vmuOK5c/WacWUfnAFt3joQCvd0eAxj2++kap9JrkTkCNnQGF3eRmQXnlLPFQcaJw3RiNbGE70m2T0W121C3iJcYlevXrV5H6MKa65duyZGsRhhWxtPuIjwvquUK1dOfCfc3c5sQ1xBpCRG8hjBK/XicPOWtyu+gSADwL4qnXel/UWSONi9e7dTv4EcQoyMEZEJN701SsfZGXBTgavL2njaO3fy8VOK5kY7uX37tuJvwBuh5Lq3FxWO68iV0V9Snv/YrvvEwtU25Qq4p3Tv3l2cL4zazDs9Cfm75sT1dwo42AdnUGqr8jUv3wPis33GR5tKUgOKkdfmzZstXKQy6EnIaQ5IAbBOfUEovDUI0cZBPHr0qIU7A6M0hPnDwMYHEAbANsNlYb7t169fFyNNa+SwaGsDgG2EUo87MnbYBoAUCfP5LoxKMSKJbzCKQroOjAtGVeagI4H9xkgYKUDxDdSp4P7E8UXP1hxcpEoXHuZj4C799ddfad26dYrfC48E5k3k/evQoYPo5VsfP1yUmEpwB5x7zB3du3fPtAwdQnhKEG5vDY4xjuPUqVOFfJ0M2hnSf5SuFfwGzjuMvzlz5swR6S9K4DoKDQ0VI9fkfv7lkQ5GU0rXfWKBVDHs44ABAxRT7zC37azxQVtW6jhjThjudvNpjvj8XUe4es1cd2EfnAFpgOZz4rivDRkyxOJ+F5/t05Et8QgXLvKyMGcJlysmi6G1Kp8YBALh4sZJxRySDPKNYCQxnwifvezj79u3rxie9+vXT+SBIvcQn0XjQu8DNxjkYMo9kbgAdR7Mb2CeFj0azGmi14N8Ixh7a/1ebCPy0P744w8x6Y6RKG7U6DxgbgzLrIMNYqNjx44iTxW/Bdcw9hUdBcxFIAdKaXQcV3BccaHCiCGYAcdTzrNCw8Vy+RzGN7ioce4xv71p0yaRD4iRF+YYW7ZsKXLhzMHFgtxbnBvkX8IrgeOMtoNRHLYfFz9cO7JkHfYP0wXIWUTbxGfwPvYPQRM455hXdAXc9Hr16iV60MjJw3YhqAjGU2m7YQyxHWhj+AyMOto1DCHaGDSirQ0ljgnexzWEqQ+sD5cxOmy4dtAmrJHzmJHHhzaLeW8cU2xTcjz/GNFAMxm/jxtloUKFxAgCrkYck8QAXgrkYyI2A+51HDtsB6473ISxbcjBhfxobKBThhxLXKvwTiCgCR0adAjxfeb5p/H5u45w9Zo56cI+OAO+A/tnngeK+xi2xZmOmavtE6NWxKLgvozfQ7AYOmn4LTlwLFakJOTWrVvStGnTRBg2lCOgZIF8J6S1IA9x0aJFimog69evF/lByOuUUyPk/B7kMiF0v2jRokJVBKodyDFFOLqsPmGeCxRbeLyS8gt48eKFUO1BbpSsRPTjjz/aVSJ6/fq1NHToUFOeFVREkM7x+PFjxd9wJsRaVhmRFUOQloDfcEeJyBx8j/VxMs+RQ54kUnnwm0j7QEoN8lljQymH0VUlIiix4DcRso42EJsSEfKCoQCFfEikqaDNYNvxPWhf5nl+AHl2H374ocgBNFci+vvvvxVVs+y1D3OwXfgebDNSotDekQIgpzwpKZ8sXbpUKlu2rGgr2JZOnTrZVSICUMyqXLmyCOPH8UHeLFJX7B2bV69eidxj5PwiBcK6zdprP66c/9jacGypNErnv0WLFiLNDbnjrigRKaF0P5BxdG5w7vBZc9UntC/kH27dutXp1KwhQ4aYFNPk/GvkqdvLkXbld2Nrl/Fxzdx2Yx9cUSLCfQ25+Ur58/HRPgHUlerVqyfyROU25YoSkSp6YxiGcQBc5d9++63QbkYPnWGY+EFOQ/NEU5Ssg4gYJrExn6uUQTQ45lAQqKOUq8YwjG+SLNNYGCapQBI4ogkxr4x8TQQAYT4ewTsIz8ecNcMwDGADyjBWuZkIFkKEOAIPIAIAly0UmuKi8MQwjPfBc6AMwzAM4wY8B8owDMMwbsAGlGEYhmHcgOdAzUCgCKIwIbfnioYkwzAM4zpIXUGsAUQYXBUp8XgDCpUHPGBsoJgvSyN5KjCeKBfFMAzDJB63b98Wkp1ebUBfv34tSt1AYglVRay1ZWFEIbeGyint27cXaQCehCz0jpPpatUDhmEYxjXCwsLEoEWpBq/XROFCcxZlkZAHB4FfaE+icCsK/ELkGV8BEWBo2ELIHVqdyJdDSsDgwYOFYfWUkwkdUXfKBjEMwzC+dc91agQKgWskl6OgKwSxIVzsCAgKQ2h91qxZ4oGDxDAMwzDehFMjUFR6cFf/My6fTWw8vTfEMAzjSYR5+D3XZSEFOWoK9de8TdbM008mwzCMJxHm4fdcl+OGUV8TotpKhaMZhmEYxldw2YCi8C4KROM/wzAMw/gqbmWudunShRYuXChGowzDMPHN9guPSKc38IFlvE9IoWTJkqJiRfHixYUxRZRuihQpbNZr27ZtfGwjwzA+xOEbT6nr/MP0dePC9FndAkm9OQwTv9VYnJFcgjqRXq8nT8LTJ7QZxhtYefwu9f/zhHj+brkc9NN7pZN6k5gEIszD77lujUC3b98e/1vCJAp6g0TDV56mPvUKUva0tl4DhklqInUxrtsVx+6wAWW8y4DWrl07/reESRTuPntLyw7dpjeRepryflk+6kyy49LDl0m9CQyTcEFEn376qdDCZTyPyOjADK0HVj5gvB+DQaJ/jt+1WBah86ypIMZ3cOsuunTpUqpZsyblz5+fRo0aRZcvX47/LWPijUcvwynP4LV0+s4L083IX8vl2pjkwY3Hr8XUArgfFk5PX1tG978M1yXRljFMAhjQR48e0R9//EElSpSgCRMmUJEiRahy5cr066+/2lRoYZKe8/eNLrEt5x/SizdR4nmgnyaJt4phYByjqM6PO2jqtsu04ugdqj5hm81hCXtrbLMM4xUGFCIKKFeGsmYPHjyg6dOni2X9+vWj7NmzU4sWLeivv/4SlVuYpOPmk9f0/qz9FB5lHHWiRvjd52/F8wyp/PnUMEnO2+i2OXPnVWFElXgQxvcRJnkS54kwlDND2bJdu3aJcmaoBbpu3Trq2LGjUCz6+OOPRXkzJvHBTenAtad0NfSVeB0eZaALD4yj0WO3ngu37o8bL/KpYZKO6CQ6tM0bT97YvK1Rq2jg8lN06s5zocPNMMmJeIkkQQFquHKbN28uCm5nyJBBBBp169aNVq1aReXKlaMZM2bEx08xDsANpu6PO2jDmfummxI4c/eFyaDO2XNdPN924ZH4P237FT6mTJIRFT33aQ/MjcJr0mraXtFmZSP6MCycNp59kEhbyTDxbECfP38uan0ipSVv3rw0evRoKlSoEP3zzz907949mjZtGv3888/CuLZq1YrGjh3r7k8xTvLkdSRdf/yaxq4+J17fePJa/F932vGNpuL4LfT7rmt8nJlEJ8os59Me8sCz+4Ij9MGcg+L50H9OU89FR03TEwzjMQa0TZs2wj3bq1cvoYc7depUun//viiiDReun5+faV3MjbZr144ePnwYn9vNKPDCKtji8asIp45T6MsIGr/uvEghYJjEJMpFvdu9V56I//JUhJyWxTAeI6Rw4sQJ+vrrr+nDDz+kggULxrp+w4YNWb0oEZB74/dehFOzKbvp9lNjwJCzlBqziYpkSUOFsqShpQdv0e6BdSln+pQJtLUMY2sAU1A4LfD/ntLSK/oocjDdpww2hwkdPQTEWasWMUyyNaBHjhyhChUqiOcIFnKFkJAQVi9KBOQ5T3DufpjLn38VoaMjN5+JB6j5w3aa37Ui1SmcyenvwKgXEb7QQmYYR2A+899jlqIJvbRrqJLaGNjWTHOA5uib23wu39B1bo9gGSZJXLiVKlWirFmzisAgzHO+fMlyW8mNKVvjX9Ciy7zDFtGPs3ZdpbP3XohAJeuoSLiCK4zbQt+sOU8bzjzg+SnGIXDDzo4OapN5XxOTB/o/8dzxtMKwf8/wUWaSvwE9efIkff7553T16lXq0KEDZcyYkerVq0c//fQTXbhwIWG3kokVuLV2XQpNkCO1+OAt0/Nv112g5r/soV6Lj1HeIeto8pZLpve2njfOc8/de516LT5K07Zd4dQDxi5PXlkqDgVSBGVWPTe9zq++T59r/nF4BBGZy4FEjEeVM0PpmQ0bNoh8T/yH+hBqgjZr1kyIKNSpU0cED3kanlpaB6H++c3cWo7AHFMwvaYHCnNLjuhaPY9QMbLWKQWTOpSmRftvitxSa7imI2OPv47cFjmeMiVV12h1wHB6JqWmdCpj7jLIE77U4UHc8kVtKpApNR9oDyTMQ++5cQoiwg5jFIoH7O+hQ4do/fr1tHbtWqFKhOLadevWFcYUUbmZM2eO/y1nTFx/HHOzscafoqiC+iKdMeQlA6lopf9IKqC+J96bomtDk3TtKZ/qHr2SUtAjSmf3e+btvWH3vQF/niS1nSnPiRsv0oMX4bTowE3qWCknfde2lCn4A7l8OdKl4PlSHwXtwpwiaqOn47whFx2XCtBn2lXidXoKo6dk/+Z6/n4YpQrQUNZgLs/HeIABNQfBItDBxQO5oEhXwcgUBnXQoEHi9ciRI+NnaxlF1pwyCico8ZX2L+qhXUvXDZkpr9oylehz7b9USnWNaqlPkUYl0fCornRVykb7DcVdPtKOMmBgPAHKqIW91dFXjQvTp4uPmlIR9g2uR9m4NqnPcd/KgBZW3Rb/L0i5aKLufaquPkNl1NeonWYnzdK3tPs9fZcdF/+Pj2hI6ViikklE4r2mFUabXbt2FVq4T548EYpETMIyeYty8JCaDMJ4AnPjOV3XyvS8ruakMJ5gnN88WuY/nj7SbEywbV17+r5QS5KNJ9h9OWHmbpnkzb1oXWZbA5pT/F+qry/+d9RsIxXFHm377I3lnCrDeIQBXbBgATVq1IiKFy9O9evXFwpFcO1qNBqRwsIkDZnImI5izmFDIfpB9z5VDJ9Of+jq0Gp9FfpHX4PeSjHi8mP8FlAHzXaXf2+8dg7dCPyfePzj77zXYdCK07T94iMqMWoj/X3EeBNlvJ87zyy1b4uojef+osFoQFfrq1KYlEJ0/qqpz8b6fYsPxAS7MYxHGNBvvvmGBg8eTNWqVRNRuiVLlqT+/fsL9y2TtGRUGTVwzflPX138D6W0NFjXg/pG9aMvonpTiYg59E5EjNxiV80Gyqu6L+ZQnSGAIqmTdqvpdTn1FcpAtr9vj67zDos81K+Xn3IpOX7zuYe0/Ogdp9dnkuccaDoKoxDVCzJIKrok5RDL3lIgrdVXEc8xzRAbiP7miFwmWc6B3rx5k3Lnzm2zfP78+aI2KDRxZSDzBx3cH374If62lFHEPIg6O4VSDc0ZUpEkIm0/jQ7CMOecwfYcAj1p6IRUQIxMDwf2FqOB7QFfive+jupBf+vrmNYNpleUS/VIzJe+JX+qpLpI3bW2UcA11KfpP4PRYBOpXBJjcHZO9JOFR8T/OoVDqOOsA7SgWyWeT/UAXkfo6HVkjI5tVtVT8f8JBQnDKXNOMrbXvCrnhOMjdAaudcskPwNarFgx+uKLL2jIkCGUMmWMvFuaNGmEcTXn1q1bYjmT8Oy4GDN/ONv/JyoaHclozjp9JZqta0ZvKYDOR9+Q7IGRKdy8FdUx+Z0T/WaJhxIvpRSURhUzl7VCX4Pe1ewRz6f4T6cpNF08X6hrSCN1XZwypNUmbKOaBTPS4KZFSKtWU+Essbeld37dS3eevaUPZh+kP3pWoUxpYm7CTPLjWqix0IG1t+SxFGyx/LqU1SUDytJ+TLI0oDt37hQuWow4UbqsU6dOYjkibFH7E8uzZcsmRBWOHz8uXjMJy9PXkdR1/mHx3I90JuN5yFCYnkuphak6L+WkxbqGDlNUrOke+RU11Rym8qpL9I5mD/mr7Fe8gPGEEV2rr0wr9LXosFSYVuur0US/mRSiipET/FC7mZbra9EpKb9pfvYFpaIIUi7svfvyY9p92WiI1/StQSWyW95YrYHxBNcevxZGdNOAGI8Ik/xoOc14bmXyRBvIUGsDasgi/hdU3xVtPCqWW1aEjquzMMnQgEIHd+/evbR48WIx54lyZb/88gu1bdtWFMxGHVCUMWvZsqUwniVKlEjYLWdo6raY6NtC0RGMeklFHSJHkBSH6e0wSk1/6uvSn1SXBup60iS/X6mNZq/p/Q36itQnqi+VUV0RCe+7DSUpnGKEM3YYylDFiJlUTnWJSquv0ii/RaZoylO6fFRcdYPWBgyj+1J6qhfxo4XLTokWU/dQ4cxpaOOAWuI1CoE7AiXdoMyktpecyiQ7yquNbfm6ZDSYMvfMBD+qqs/SLkNph99z/v5LypGOCyAwyTQP9IMPPhBGc/z48UJxqH379mJEOnz48ITZQsahApFMDpXRlYuUlLgYTyW+jPqU9hpK0D0pA+0TOaJGw3REKuJQqvSYVIiO6QtRGnpLX/gtp47a7eJxwpDfNO91PrAbFQpfQJEUUwJPiYsPXwrDubG/0Yg6Ikov0a/br1C1AhmofO70ru4uk4CguPvhG8b5zhgkqqo21rDdbKhg9Y6a7knpKZvqKbXS7DcZ0Kz0hB5TsM2IFHPimwfUooKZeQqJSXjcutNiDhQG9MyZM0KKCYW0v/vuO1EblEk81poJKASpjCkB2/WOe+juYCA1LdfXpn0GeBVcH9X9Y6hp8bqM+qrF61Iqy9eOaDx5l1Pr/bT5Er07Yz/XOE1mDP33NI2JLvguU0B1lzKpnlO45EeHDYVtPnPIUET8b6fZRRcDPhRpUvsD+9Iq/2GKv9FwknNthGES1YAeOHCAhg0bRgMGDBCRt3nz5hWVWVauXEnLli2jIkWKiNdM4vDkdUyHJYiMBvQlJT/31R0phObrGtl9P4+VQlJcMffcovTVEycLizPxOz9/+o5tGtONx5bBQ0DO8YTxVJoT/0cf0wELUOlMz4uqbyvmOlt7Z5Dm9Nfh29wOmKQzoHPnzqUaNWrQvn37RJRt9+7dhRYuQFUWFNlGlG6PHj3E69OnT8f/1jKKQKVlqHaJeP5ASp4uy9G6LpQ/3DgXKrNeX1H8f98N0QZXZAXLj9tC787YZ6oWwyQ85b7ZbBMotPfKYwoLjzGAICWFU2fNFpPLX4lrUjbTcwSiHTMUML3+xm+eyEG2Zt7e68JD02TyLvrq75M0cMUp0Q5WHr8rUr9gYOfvvS4Kx3+/wVhN6tSd5ybD++fhW3T8lrJxZhiX50Dhsu3Tpw9NnjxZvN64caOovnLt2jXKly8fqdVq8T6iczEfivqhb99aSnUxCZP/2Vx90CTHhwCf5ApyTdtGjKbO2s20U1+aHlI6Ee1bQX2JUtFbek1xEQOXKLfqId2UULggZgiqVatIZ5Do6M1n1H3BEVrxaVUqmzMdBxglIFce2dYKhjHqNPugzfLxfnNEhC2UsBDJrcQdKSOt0VcWQgvDorqJUWonzRYa7zeXGmuO0LuG3SbZP5lxa88rflf/P0/QzJ1XLaQkQd6MqURlmB618tHQZkWFOha4MaE5FR+5gfo3KESf1Mrn0nFgvB+nR6DPnj2jggULml7nz59f3MSfP7csYZUuXTr69ddf6fBhY3pFYhERESHUj5BKg2owELffvHkzeStXHsVUYOmlXS3+3zBkttuLd8RXjVz/jLtg+wZEfUYrDTWEaP1jyVhlo776WJy+t792Be0M+IK6aTZYLIfxNAfzossO3xIBSbFF8zLu8eJtzCgTo34EDnWYdUBx3cpqo6GbomtLl6I1cG1RUZ+oz6lD5EiTi3eJvj6dNuQRz7/1m0MDtH87vX3WxhPIZdUOXntisfzozadC8GH8uvN04UFMWhbDuGRAmzZtKqJtlyxZIsqWwVWbM2dOu+kqiZ3G0qVLF6F+hBHwlClThA4vRsh79li6kbyF0Jcx83qpyTjSn61v5tRngwK19F3bktS7Tn7KF5KKPq0T4xJLbJBDCgqobeuMOouG9NRfa5x7HylSZhyXuH3+JkpxroyJfzDqRxqSksCBlnSUJXoO03yeU2Z+14oU6GfvFqWi6brWFpWFCqriLun49E0kPQoLt+hwyWw+y1MAjJsGFHU+GzduTF999ZUwUjBQMKT+/sqJ8IkJ6pEiqAmRwBMnThTGfdu2bUJ6cODAgeSNROhjbkjBKmNgxgFDUac+O79bJepYKRcNbFKEtn1ZhzRqFW35Ivb0kIRggb6x+F8kOo/VHWqrT1q8jk14PG3KmJSZ15GWc3Jgy7mHYt6McQ9n5w5D6AWpVRJFShoKpRgBhazBgcJ1WqdwJiqW1X4d0KOGQvRKiskh3hwQ92v99tO3VOnbGE1nc6K4s8W4a0BRRHv27Nl0//594baFezS5iCUsX75cGHQYTpnAwEAR6LR//366fdv7Kny8jdYRbaQ+LMQMlGTQ7JHCT2OzrECmNHRoaH3aO7geJSYXo9129dTHaax2nimf1RWyqx5bvC6mspSWtEatUlloslrTc/FRFqiPA/bmH60pqjaeJ6hkybnLODNFzKQbS+VIK+axlcDn6kRMslhWXnWREooos04rwyRIPdCkANKByEUNCrLsrSKQCSBC2N68KfJYzR+ewu2nb0S6xqfR85/Qr31OziWP+2uVT3umoEDKnjYFXf3WOVew4ndrXGtSd6WM4r9WZRByf/P8XC9AkMFMMhDkU9kvMG49fxyls3XhpvI3djCgZsS4hrMucbhv5/r/aBM5Dm9I/pDUptcYgVrPY5sDMYUHUoxMZWn1tQQ7ZVEuVAlifAOn7nY9e/ak69evu/zlV69eFZ9NaDAqzprVKDptjrwMEoNKwOWLkbX8wJyup/DoZQSlUkdSWfUV8Xp0FITanSNQYQRqDm5isz+0VIRxFj+Niq5924zSBDoX4G2ddoOITGdB+sIw7WL6TPOfxfJMKscuxDl7Ytrymyidzag+dYDWrnuXccxDs/lDZ93u83RNLAxw3pBUptfFstl34cpAdlImONobkxC8iWKdXcYNAwoXaOHChUUgEXRuHblEb9y4IVy9KLANYYU7dxK+ViPSZQICYrRYzd248vtKoLLMixcvTA9PcvXC9dhRZcyfey6lovNSLrvrVs6bngpmMvbq4Q7DKDM2GhTLTH/3qurydvlp1CJF5KVVvp89IOF33mB/2x3RQH2MPtGuI79osfud+lLif+ZYDKg5TSbvpg6/7Rej0qIjN4j6ovei61S+eOtcLVQmhievnFMjg6oQ+F3XjNYajDU/Acaa+TLGjEALZk5NGjOXuxJTde+YnmdXWUbRxidK7n7Gt3FqmLBu3TohJP/jjz+KeUa9Xk8ZMmSgPHnyiLQVpLMgzQWjVPyXI2C3b98uxBcSGqStwB1rTXh4uOl9JWB0lQyvJxAWHkVFVY/EcxQghtyePca2LiFKgkEftkYBo8vUGSrmSU/BKfycMiRwJ8PTJruHJ3coI3LunKFd5Cg6G9jd9NqZqhsAuYDm7DKUpNqaU5RZZZlaFRsHrz8VhhMsORgzf4r9zuF8ERsGAWr7bjjlOZDTllDBx7odwWia1tVqxIjU3O1ujY609FlkP/rV/xdRBD6heOVkp5DxHZyesKpevTr9+++/dPfuXTHCfOedd8QIDyNMLIORgsg83sMyyPslhvGUXbVw41ojL0NuqDeBubn9V59QWjLeVDbGIp4gz0t9VrcAlc6Z1qXfgjtXiWHNitLUjmXFc4xoy+dORxgoyBGu75TN7vRvQEChSvhU0+vLgR9SWrLN1TOnvvooVdOcs0i2l4XIM9ALkdriCrIazd3osmiAR6CugVSVFccce5yKqm7Sj34zRYk8eE4uWOV+ls6RljKmtuzUls2ZNlYF5hvRVVxim/+OC6jywzBxqsYSEhJCXbt2FY/kQpkyZcRoF0FA5oFEBw8eNL3vTZy++4KevYmidH5GI/NMiumxx5a24Srfv1uKZu++RtULZKQmJbJQo2ih7o9r5qUH0fNdXavnoY9r5hO5qQYzhSRXeEAZ6K6UweSCm+Q3nbpGDbK7/hz/n0zPy4XPpDBKKUbhOkktApIyUJhLNVBlLpuNdMJccOHCC5N3yDoa27o4fVjVmODva8za5bgoQBP1IZrpb1QyizF6MaYRfbVs6Wy9RaVyBNPfRx0bZrkMGiLSMQqVC3HHJ6g1yzBeF4Xbrl074VaeNWuWaRlcuvPmzROKRJ4UHOQMWy88EvNCaaMDJp7FEn2bzYk5T3s0LJaZ/uxZlfrVL0iFMqehRd0rUfvyOUilUlHW4BSivFi36nnFuiFpAihzkOPano74RdfW9LyuBkEmysa4o2arhZ7uUwoSbjwY0FBK6/I8qD1eRehdFvZffdIyYK3znIP0tY/klMpzx8pI9IWVWtBWvdGDIQNHSecquW0+WThL7IFEb8xqyq62U6WFYZJ8BJocgZFEXVIEBT169IgKFChACxYsEAFNc+bMIW9j87kHpJckkwv3hRQTtWjNZ3WNtTfji5oFQ8RDBnOr9pj5QXnxv9fio059N6Ip1+ir0OmAj0WC/Y3ATtQ5cjDtNhiDg0B2CqXv/Izn9KChCH0W9bnFdzyU0oo6o92166h/VB+KCxBTePY60ikN1HvPja7f4BSWwiK7LxtzVCe2j/8yc8mN5UfsjxKbqg9RoegI6w4RI+gNBdBZyXKkXrtQCFXJF1NAW6ZSXucKJFwxZKMC6nuUWuVcJLC7uaAIlGMY4DUtYeHChdS/f39atGgR9evXj6KiomjNmjVUq1bSKOwkFJAZO3/f6Lp1ZgRaIDr6NimAyxePIU2N9RydnQ/dI+qOGrHOC22t2Wd63j3yK5vgqfMG4wimulAjinseJzRQnUGeO4V26p1nb4T+6wszycAh/5ymcC9Pg4h0IDTwebTU4j/6GnRQKkqnpXw2585Ryoqcm9uhgn1v0hdRn1pUKEoIvP0cMj5qQBHQBBk/BA4h+hbyfpAe9Da2XzRG3qIOYpDqLekllUUiuUzpHEZVIpUbBbDjm56189POr+s4vf78aHk/gPnM7f4D6FhAD1rk9y0N9PtTLB8Z9RG9Uqh9OlbXWfxH5Y4DAX3EZxIyMlPmbvQIFHPTHX47IPRfzUfeyw7doo1nH5C3gmo3jqJuC0Xr1E7VtbG73vsV7RtHCLrLc+9AqVN2Xopx/wZTwsxXytHaDONVBtRX2HIO859QXLlqSmF5azb/I1OjoDFdJWf65FFgO1f6lBRgRwHJmu2GMvR1VIwsY171Q0qvekU1NWfE6whJS9sM5RQ/i2Nx3mC8EWdRPROfmeD3OyU0956H2xjT/VaVPcxF7L0NeZ+VqKk+LVzyYVIKU7CPErkz2J+K+LBqbqqaLwMVzJyG1varQd1rGA2pOUh9CpNSKqpTxRc/bbqUIN/LeCZeMQfqK0To9LTrcijpJaKWWmOViJMG2znO1X1qUMkcwfRBldwi0Cc5gKCjC980Ef/hBisywrLsmDnQRf1bX4fW6qtQcdUNGuW3kEqojfmFPSMHiILKoQ4ibN+NHEPFVDcov/o+fe/3O5VRXRUuPVlvNSG49/xNrOuMWnWWPqrmnRG65tlObdW7xDkbG/UhrTDUFBHV4LKUwyLq1hWQyyxTPJvRu/Jj+9I2ov8ojxekekPp6SU5jgmO/44C43vwCNSDOHjtKUXoDBREr6mVJtqASrYGFMYTJBfjKQPjKUsJnhvbWJRUW9jNqFdsL7LysFSEWkR+S4XD51Oe8CW00VDRofGUP3dEKkIr9DVFWkuAKor+p9lGKSg8QeTpXkXo6Ngt18QbkjNd5x2iPw/fcukzg6LraQJoGger3tBP/jMpGz2hNKq3sbpvXZknl2lXHgbZEkRkJ+QIlGFcNqBqtVqoC7n6YOKXbRceCSm+AqoYvdjVeku5vaQqS+YqKf21oqRarUIh9G2bkrGubyyk7NroBaktZ6IjPcf7zaVN/oPEfJyrdF9gLA7/MjyKbpjlAh679UwUYP5g9kGhTewM5p9Prmy/GEqDVpx26TPyHCWQ5ztBYbVRHvOCISftMJRxOE8eHzyVjAF1yDeFF+J3v5/oRuD/aKv/l5TSzQ6UUs4vwzjtwh05cqRp9CADVaKzZ8+KQB3o5IILFy7Qpk2bRJkzKBUx8QcuWgShoDJFCrXxZo25PutAGpQl8zQq5U04vbxekQNorN98aqQ5SjnVodRMfZD+NdgWb3bEpQevaP3p+zRz1zU6efu5qFWJUWnb6TERwc7Sd9lxWt03cRS6XAFC+jqDgdIEui+6IaMxi4CV67zKZesSGrm6D1gXMNT0HO78P/y/oVaR4+P8G5cevnKYvsX4Dk4Z0NGjR1u8hmAB8i3PnDljMp4y58+fp3r16nmdfF5SczX0Fd2PTlRPET2KekueqeNrTUIafSgc9Yj6knobVtJAv7/oI+0m+jeypsvpGZ8uMWq3gp83X6Jftl52a3ti0UVPMur9tEO0L3QO4gq0jGVKRpcXu2iwdbcmBMv1tairdqPie6XU16mO+oRpJNxavYem+BvnZ7tHfkl3pBC66KAog0zjybvi5TgxPjoHinSRPn362BhPULRoUfHeDz+4XteRcey+lQM1UpJxBBouWSbt+ypV8hkT7Qc1KUI/v1easgYHKoo0IHq3jPoqlVDFrWaku8ZTFiTXJcPCzHLnzFpz+f6Lt2LU7EjMfUt0agfaZ1Z6IiJuZZppDon/VyXbDrW9QtmuUNwqd/SsZBudO1PXwvR8hHaRSGvypyiT8ZSlITcGDKYPNJspFcUECiFdrKdmtY37F5VZ8gxeSz9tSrgC3oyXGlCIxfv52Xf14L3EKGPmSyD/TJ56SR8dIPHUyQLansD4NjFRlq5SKkdak2JN23I5FI3BEwqmPQbjXGtv7SpKKqCnOvgf1+YXExp74gCofzlu7XkhT9jg5512P//xwiMmKb6e0QXe7Ym9m+OubrJ1epQ1DSKMnXeDpKK+kX1ogu5/9FHkIJMrd3vAl3QuQFnLe5zfPNoYMMg0ip7rP5GG+C2jr7XG/GOZp9HSjVO3XeHC6z6MWwYUc5zTp08XVVisgeHEeyVLxh4YwjgHqoIgUV2+3RSKnleCy8lbiMvc2xcNC9GIFsVE1Q5n5scwKmquPkDB0VKIic3aUwkv7BAbUEvCCOrig5ciCErm9tOYdJx2M1yf4w0xKyX3RjJOMUzTtVZ0jUYXCYoTOPfWXJFyUMHwhVQlYhqtNlQTy3YaStMBQ1ELgQ5w3FCAfojqILwTMjlUj2mG3yQRfCSnTxndwsYNDgrU0o5oQRPxHbfjrrvM+FAe6KRJk0TwUKFChahNmzZCexZcvnxZlDFDwMvixYvje1t9ll2XQs1uNhLVVBsFBcxvCJ5O4+KZ6eMaeWn9mQcu59ohLUYpsd6aWfoWIsUCoHYk5uUaRyb+VMPbZCAHd/L2C/F/56VHdMRMRehLs7zKCw9eUv5YpCCtU3xyR9eo/TjyS9piMGohJyQpA5RvYRBVsK7G81VUL5rv973QywVQ8RoW1Y3OSXnoN30Lmuk3mRpqjOpRDTTHbb5zhHYxfaPrTGHhOhrxH6Qijbw7w5hSNrplMeoSXViB8Q3cMqCo84lSYSNGjBDRuG/fGm94qAkKwzpmzBgegcYjW88/FHU5Udczl+qRiCaNlDR00IsMKAonD29RjDpVyU11f9wR6/oo3N23bgGnhN5lrEfshdV3qIV6P12RsgvBhsaaw3TKkI+KqG/TBN37dEfKRAkF5lFR4SapkPXQradjD11/arlAsp/7mjpAS5W/jamMoyaDKcXqsuR8Pdi4kDUokHrWzidUirrMM6YbOTr/DSJ/FPVikSeKbZTFNfSkoU+ivqT0UWE0038SVVJfpFApiLbry1Il9QXKo35I9dTH6BsySkUCldXhGb36HLUuk53SpfIXUc1z916nnrXykZbF570Wt5WI4MaF8TQYDBQaGmqqFYqcUSb+gNFE+TK5KDZk0cAxqZCNhN8P78ZULfFU8mZMRYObFqEJ640Fru2RI10K6uuGAYKG7li/BabX0/xjCnkDpLuAFpoD9FVUT1qur00JASJ5P62TP8kqe2iir9PYxNFR49Wa47eeURuFFJ7sqlAKVEVRhORHt13ofNQt7P5UhFqtoiFNjR1JiHMUG6kcgWs9H/5EMoqNKAkxvBc5ykK5Kg29oWMBPYWk5Gy/iaICEPKSlfoWa07do85V89Afh2/RxI0XqUiWNFS/aGa3949J3sT56oXBzJw5s3iw8Yx/Ttx+Ri/DY9ICakQb0D1626Cb9xyIcXsSvWrnp6vfNnO4Tkhq+yk8379rf/59ob4xlQ6fRUOjuse6HcgZdYS9GNLU9MYpAfv+f5ygZlN20/y91ymxQRQpmBJLRPGhGzEj0rP3XtDPmy4qGk9QQGV0jV6TstpUWrHHtW+b0dwuFSm+xDniq3yfuezjS0pJc/VNTK7dhmr75fmQp40pCBS9l0fqjPfi9gj02bNntGzZMrp27Zp4bq3OAeEFb6zFmRTpK7L7Fi6yaqJMF5kiSr0V7DNy7RDoYm+kao8OFXM5VNJ5Qalpqb6e6IwgoAhzoa8pkD6IHCpGFZXVF2i+/w+irqgjzFt8ZnoqRq0V1BepqcbWlbhGX5mGRXUXvy2z9vR9k+sPruvEHI32//OEy59p/sseh+8XjFYgcsV9ixFkfNK5Sh76dXv8q+B+p/sflVJdp6qac1RLfYrWGCwVwMzF5sesPmd6/fkfJ0SR+TI504q5ek/myasI+mnzJepSLQ9dC31F1QpkpPl7b1CdwiGmSHhfwy0DunHjRmrXrh29fv2agoKCKF06WyUZa+UiTwL7pSRFiGUom2a+nj0wGsecsDvrvnnzxtQhWXfsBkWFG+eYS6iukp/mNb3QpqJTknHuzxAVbrqTW/8GzkHKlDFh/pirhsvdHqlSpXJrXZSP0+v18bIutlduOxEREWSItE1JGd2qOLUqnU0cI/N1dbqY3r7151R+/qRSGQ2UpI8iSa+n3pE9KD29T4/J8uK/42/MKy2qvkVNpT20NqqC3e1Vaf0ot+YxLfMfRyGGxwSP6GuF3atLB+hDVTaaKrWP3gadeMgcvXKfSprdhAICAkirNV6eqG0bGWlfgtB8XRwDHAt7+Pv7m1LQJIOeJJ39CjEqjVY8nFk3h/YpfRmwXDy/pMuqeN5k1g+oQ0/eGihSZxBtTI6hUALbim0Gsa2LY5AxtXFdtA0pyv5xUKk14tw5t66aVFp/+lXfWhjQCvoTZIjEdtje417qjOvK4Di8N804p/9Jrbz0RcPC8X6PsNleq+velXUdXfdVxm6iKLU/LT1o1EnuXCErLdh3ndYfD6LlnxqjnV297h3ts0cguUHx4sWlAgUKSKdOnZK8iRcvXqCV2X00a9bMYv2UKVPaXbd27doW62bMmNHuuhUqVLBYN3fu3HbXLRailtYNry/lHrRGPPwy5LK7Lr7HHPyOvXWxfeZg++2ti/02B8fF0XEzp127dg7XffXqlWndjz76yOG6jx49Mq3bu3dvh+tm7zXHdMyCKrV1uG6OblOlyJHpJGlUkDSqtr/DdbN8+LO0eFgbse4PDQIcrju3cz7TNqRv2MvhumvWrDHt27x58xyu+9dff5nWxXNH6+K7RBsbtEYKaTfK4brYRnl7M3f81uG6TetVFscAj7IfDXO47qhRo0zbe+bMGYfrfvXVV6Z1r1+/7nBdtAHQ4pfdUo6+Sxyum6pEzDWUc8Byh+umLFxdrFdo0D/S25EZHK6bIl8F0/fiofILSPx7RLFiFuvidXzcI9Qpgiz2LSBniXi7R+De64m45TO6cuUK9evXjyNtkwhvd98mNXpSUyMX0ltyqYxKPOsM9ivLgIwq47yYNyLn1M7UtaT7UoYk3ZYln1SmgrGk37gDAoe8KfKdiTsqWFFXPwSRhI4dO9LQoTFizd5AWFgYBQcH071794RrOqlduD0WHaG9lx+LHFBIie0P6EMBaj01NUyim9HKLmp9BGVI5U8T2pakKvljhLS9xYULl2TR6NqhY1sXp/YVcjpcV0b+zLBmRWj8uguKLlx7yOsO0y6mj1RraWtkSeoZ9YXNeukojDanGk6ZNEbj0f7tYDoYVUgxqOhw4GcUqCWqFvkrPaT0Ni5c8FvnclSrUKZEceFibjk+XbjTAn+lVv5HaURUF1oYVd9iXY1KRV80KkjdauRz2S3rqgsXx0Jed8Lqk8LLOnPHNfq+XUkhgFAlX0YqO3azWy5cUFZ1mRarRlq8XzR8rsmda76u2A4rV/aOr+uIOdHk7sKVr5/z3zQxPRfb4R9z/zPgmEkSZQryp51f13Prusc9F7rpL168ULzneuUc6Lhx4+izzz6j//3vf5Qnj/cVCMaJNz/5jtZz5TudBQ0aeWSHbr8m8gsU8YBV1Ocpnb+Bbhsy0U19TFi8QRNAH9YsRPVL5Y71e80vwPhc17xTEZ/r4maIx/K+dYUW6/8q54p1XesLvWeD4vRe1YJU9hujgAJQafzEIzYOGwrTJ/7rqFbgZdKokLYQ47AJoWd0OLC/6XWUpKHzqgIWNxjz+qQ3tHmouPomNdAcoyX6BhbGSebTP8/RjQl5FY2II+lMayMiG9PYEEbEXxMv62bRGjsRT6Ug23VVRMFBaRSvARgGZ68NV9cd2rqsiIj959Rjql8yF2VKYzw3Uz+sIoJ7ZMa3KUnDVxrFSWLjuFSQTmmLi7lQmTQGEkFoitth1R4eviHKlzVVvNwjEmJd+bqXtxufVWrTYh0/4/Wm8Q+IddvtXfeOOtNea0C3bt0qcj4hHN+wYUPKmTOnTdANejZTpkyJr+30OfZfQ0BKTK9RVh/abShhE7zwIJaCz54ONG7xcIUp75ehx6+Mo7a0Kd2TCdxqKCcKcqdSRVBL9X5aZahuem+5/xjTcyTcN4j40aa0nDnnDLmFAUVd0kjS0t/6Oorr3Xv+lrKlTbhC6GfuvqB+y2xVduKGJIQHwJPogtYW70oQykiafNfsaVPQkeENLZZB7EA2oOs/r0lFswY5bUDBG6sqSOlUr+i15Nw5u/AgjKrmT1oXtytwGk4CGNBp06aZnq9Zs0ZxHTag8VM8G3llFvmfCvOf8aEp6m3gJhnXiHCo0+BmGURv6Rf/X0kXqaF1hiqkJR3lVsdooVaMmBnrd90yExZoq95j14DeevomQQ3ohjMPhKB9fJLWTFP4kp2yZVCOSo7AeMZGqRzBdOpOzPw1OkDmQM1qpr6VU7+HFJeuiST3Zx6l7grn7hmLVQBnVMF8GbdaNXzksT08fWie9MWzH5qMJ9yFkJ1DdYl9huI26/tpPDdlKLFATqk7NRyDVDFzbrXVp8T/itGjLTDECUEGWYd3p96oFFVYbUwDUMJcNMNTdHghiwfCpJRCyUeJZFjBTRGla2n2RxXsFu0GpaJrnjqLG2EnbtFn2XFqMXWP4qjSUUm9XotjhCJkLw6jTPLsFvo4Fx++tJBQqxHtvj0j5aHnCiXMtCyf6DRLP6ns9nlJFW1MM5DRYLyV/GmZvr7TEZwDo3qI50GEiifKN9HP/zgeq7xesjOg0cfjsWR/NIfaoskNaPlac3l8M1HZR2Zgk8KmuVOZ2bpmNE/XmKbrjKNOiHHki1ZhcgaI9CekEUXlJgSJoeoPXPY3rDwOJUZtpALD1ptKspnzJlInvCBMIhjQAwcO0HfffUcDBgwQlVjkiK9jx47Rq1dJUyrKG9h6PqZ4Nqihse++BakDPFvhJDGxvhnGRt2In0zPW2gO0hy/iVQvulLHbhfTiRBMJJfS8o+uN2mzTqSetpw3psUkBI6MM/RfB2uXUXuNa267kOj0HHujTyDZ6TAkFWv61qBtX9ZWHHm+VyHGDd27jrHSlDkPKAON0X1Ef+jrmpaN1sboK8dG0ym7af+1JxSfYEQJScj1p+/Tu1Zl6Or8uEMsg3CFeaWjct9stunY3HzCxjPB50ARUv/+++/Tf//9Z/Kzt2zZkgoWLCii3xo1aiSM6rBhw9z5ep/HvHg2bj3yCNTeDbtXnfjR//QFsgS7ZkCvS1mpTcQY+jdglHhd36zMlY5c67iYB58gLSmSlIObEnKw5siANlUfol7RBbG/0C6nLpEDFet4WtNcc0D8v2ywL+GXSF5LpymR3VJM/vjIRqbnqfy1FJzCj96vlNPp6j61NKcpRVS4TYEHezyJJ9coagVjWzHlA0lIR6PSQsPX2yyHQV166BbN2HGVKudNTwetq/Ew8T8CRRkzBA/NmDGDLl68aOGOQLhy+/bthXFlXAdulZN3npv664VUdyiz6rlwFx412OYYgpT+bksa+xxKbrvYOCMpB30s0ltGdzoTlISIXYrW200Kd+e60w8sXvuRjr7T/i6KR0/3/8W0HDrA4/yQ36hMUdVN8Rk84MIERyXL9gmNVJnkrpWKdiG3DejzHhvRkAY3KeLwMxDMrx8x0fR6it+vpuot8/y+F6P5hHSlo6NdeswmqvztFrr51L3AsJo/bBfGE7DxTCQDChH5Tz/9lHr06EHp09umFyC9BSLzjOugwLF5b10efR4yFLE7YmFcY2P/Wi6tj+LMrSPGUoRkaXztdWgcsVekIRF11cYkp1sjB4/FJx/OPWTj2gMt1fuoo3a76fVtQwj1i+wjnldUX6JiqhuK3/e7f4xrW+Y/fUyaD9yj87pUNAVvFcsW5HHFDMwjWEeazYuac1XKRnv0xU2l8LLRY+quXUd1NSfFaD5ntEqVNfExz336znPx/2FYBP2wISawLaHIoQqljzVrRaeLiYMBffTokUMZP+SEYi6UcW/+ExevTEz6im35MsY9CmdJI27q/RsUpPcr5qThzYvajJisOSkVoMIRC+jrqB7UPGI85Qlf6laHZkZ04AmEMZqpD9Ag7TKqrDpvsU6ELn4DfQ5ee0K7LoUKN54MKvugQPTP/jEpON9FdaTGkd/TKkM1kf8Kpvn9Quv9B1Fb9S7xGik8PTSrKYfqscVvjIvqJDoaADmfqJbjyQUlrGlgt6anijpHDaHrBuP7s/x/pv7af0zvdtJsU/wUXKcQS4kLiV1LdoX/KBrut4QGaI1FAxg350AhnHDhgn0X1N69e6lAAdvJdyb2QIDtZsWz0dOrrDbeXFn/Nv7p3yBmBIlSU/WKZKJqE5RveEZUdvM3nQVzio+ktJRJ9dzkMu2s2Ux9ovrSDkNZIXu37fwj+l+lXPFigDDS6TDLOEcpE0gRtMl/IOVSh5qWYdQJwymzwVBJlGfLpza6fGFoR0iLhWiAOev1FYXhXKBvbFqWKkDrVcYT5MqQkhZ1r0Sd5xjd1eZAoQrqUsPVS6iE2nLEjlHoBUNOWilEOIzHBP3j33Zeo+VH7tDREa5NA8ggIAilxRIPSUwlgd7aVcIjtsNQ2kFVXN/ArS4MJPx+++032r9/v2mZfMH8/vvv9Ndff9GHH34Yf1vpI2CE8NqsV1pOdVmo4GDe7ILkHcWykysfVMktBAz2D6knijxvHuCam9cVlugsU19Sq8Jpvv9EKq66QXpJoq0XHtGOSzHGzV2gOFTETMdUZqrfVAvjOUvXnNYaLNN7NultS7hZG881+ir0adQA6hfV1zT6BErpEd5AzYL2PRSz9c3omsGoTw0GRX1iej7ZfzpN1P5mei176J+8jqRLD1+aDOLyo3do6/mHVP+nHRRlJ08T8SbXH7+mjr9bdooSmiZqyxq3qJd7I7CTmAOvbrBfYNzbcWsEiuhapLDUqlVLzHfCeCLq9unTp3Tnzh1q1qyZeM24XzzbPH0F82bmOqxMwpE12KgCFOym/J9M+dzp6NPa+WnnpVBadOCmxXu/6NvQFkM5CqAouiJlp1OBxpttXfVxOqs3akufuPWc6haOUS9yh1UnlXMTG2qOmZ7DFa34WUM1ShP1hvKr7olo4x7amMLmP0a1p6X6+vTcrDi4rwCJSHMd3RhU9FnU5/S59h+aomtL56XclJ5e0iC/P8S77bW7aLLuXbpLlka40aRdit/5/E0UhaQJEB6prvMPi3l7TD2sOHaXvvr7ZILuo1DaUj2kfKr79Lv/z7Gu/5VuNpH+SyIrbWdfwK09RnWEDRs20JIlS2j58uVCdQgVIEqVKiWE5jt37ux1LpzEYOPZBybjaR5AxO7bxCdtipiKGs6ye2BditAZaMfFR/RxTWPlkQbFMtM375Sgq6GvqP5PO8UydIbOmkX2/quvTm00eykk2kUGCcfQV/argyQWcEuCAIo0GdDjhgI0Td+GfJWc6e3rHcNo9oqKGTjM0LeiGfqWtMu/vxjx7w38nMZGdaa5+qYWn1t2yFaZasL6C/RDu1LCeIIBf56gLtXz0MDlRjWshKKNejdN8p9h9/0q4VMplSpcGNfxfnPptRRAXwcMp+U+aDyBy3uNcjcYgdatW5c++OAD8WDizq0nb+iGWRJzEL2iUipjePkePQcQJTbuaLfKN9cCCrUoMZqwB4wSDKhx/kwSLr5XLkr6IfBo75XHVK+IvWAXGdcjfKGihACjPtqVtMxMPMAXCdS6Klqiogm6jqb57nc0e2wM6IFrtrmXK47dEXPyMufuh8Wb8UQZPohfXLKZFpLECNoePSP7CxEJNKGrUnbaHGF082cOtN+2vR2X7xIod4P5z4cPE04txRfZduGhxXR8VfU50qgkumLIZmy0dljysfvSdIxjLnzThNKmiJ/UoRR+9m+8oZIxR7K8+rKYK4MBXXf6vqjM4iyTNl+mbvOPiHk05AfeVpBjC6LXtNX/K7e2/zd9SyoZMYf+8nEDGuDnescKBQgaR0wQz3OpYooQxMZnS2Nc7a7QSH2Y9gT0ow3+g0ydcJlU9JZ2BQygTQGDaKDW6F4G/hQl5jTzqI339Y6Rw6hY+Fzh4i8T/pv4vzGWgvG+iFvj7vLly9OZM86X/2FiZ8v5RwSvt5wDWjM6fSU2ubjqBSyFrZn4A5G5eUNS0fFbRteqNUjXwCMsXEc9axtdtu6kHOw1FBcdpQLqe9RMc5AG6nqQzqAWEcFXxjclrRPpCrLBdDQ/1kazh/Kr75teIyUnISioMAL3FuBed4ebUmZRDCKt6jXlV90VI7iEID2F0Sz/ScYXKqI//b+h8bpO1FWzga5JWUW91jTRms6Ipn0lBdLv+hY03+9703es1Fej/WZFK5T0txkjbkWmTJ48mf744w+aPXs26XScVBsXoDpz+s4LOnDtiYWEW8z8J7tvkxKIAdjj5KhGdGp0Y5FTOqSpMZfUEfaqwYRRamoSOUEU5UbUdXZVjE7qMTvG2526jXIVmZm6lpQ3fHGcU3LssapPDfJWHHkSHBFOAXRSMkpuDtEqB265B24akmnaZ2uApYchhSqSxvnNEx0nBI910FrqHA/0+4t2BfSnamYFwr+M+jQet8+7ccuAdunSRWje9uzZk4KCgoQGLgKIzB+lSyNHiHHEk1cR1GPREWo5bY+F+kwO1SPhSkEy+wGDrQIKVy9LPFL4axyOUF1ljlVpLBkdaYWqDSiouiP+wyMBAQRnuPMsduESOUjprCF3gkV1Qw7P0THzdDIFuaalbA6ic0EDzXExCo0rGelFdCpJJ5rhN4lOBfYwpRr1i/yMdujt34N7Rfa3kG2UyR++SEhOMgnowoV8X4YMGahw4cLufJyJpvy4LaZjAceQZDX6PC4VoNdkW1xZLxENblqEKuROx8cygfG34z69NM4yEMRZ6ttVtCG6JOWgInSbCqtu03YqK9z5SG36qnHhWEefV0Mda6FmoBcirxhccEIg3l3Sp3I9etlT+e+z6tT6170i4Ax5nLGxw1CGdulLCuH5auqzdFUfNzfuUL8lpudNNTF5mjCcSEPC742QFlEh9R0aHJ2XiimCY4aCtN1Qlt6JGEsrA0aaPod6tWw8E8GA7tjBVcrjG/PYSJN8n155/hPTMB0r5opzriITO0jHShOgpTSBWvru3VL00dxDbkfpxsZFQ04izX4qqL4D5XnB+fthQpjAkWHad8VSVs/e/KefSk8nDPnoshRTriu+sacZ602g3NnFBy+pdM60tLZfDaH29O6MGFEZRxw0FBUGFApji/TGCjDDtIvpE+06EemMYC1nQGpRW41tsWwwS4+pAhWFUSr6WtfL4r3zutym5yckS7W4nmYpOEwCGtCFCxcKEYU8eYxJ39bcvHmTdu7cyWpEbgCN0urqs3YDiGA8q+bPwMYzETk9Jkambtr/ylKtQvYVaeICRqCgcLQLV+5Y7b4cSq3LKI9WHotpgKMOg0rm+k+kMmpjNGZCR9FWymdbXMLb+KFdjGu0eLZgkbtdvUAG2nsl9hqfkMCTa8vO0l2l01JeYTzBEL9ltFJfnR5S7MfwW7/ZDo20s0RKGvJX6U3ztIxruNWN7tq1K+3bZ1vZQQYqRViHcR3IuWEeI0xKYQo6MAduvWYls/KhTSJalMpGQYEJM/K/GJ2XV1B1V3Sk5KhPpTxBmenbLdMUrDkW2MtkPJ9JqWm1violJAl1bJIzUA9b8nEVp0rlmV/TqwJG0PVAyzz6TQEDqbn6gBhh4l6wzn+IiJDFa4C50wV+E+jd6NHneUNOOmYwjiTvS+mpSPg8l9ywPaO+EP9n6lo4/RkmjiNQ8/qfSrx+/Zq02sRRprh//z5NmTKFDh48SEeOHKFXr17R9u3bqU6dhIkwjC+ev1HWC5XTVxA8ZO9CaFgstmR5xhO5LYWIuq+InISUGop5I7gMSjV96hWg7Gkt58ORJ7pwv3K5MdBFY6mDWzfiJ3pJ9pV0wEdVc9OC/ZbSg84SFOibajQykNozr3ijBCr4TNe1EikkSgSr3tCv/r+IiGy43EExukkXNV0U1/8gcii9pQAxb35WyuNyhSDMhdaImEz3Jfu55ox9nG7xp06dohMnYvQad+/erZjC8vz5c5o5cyYVKuR6rUR3QEHv77//XkQCo8SaucB9cmb0KqOb1prqDtJXEGhUNldaypTG/UhAJvmCyNjLUnYqpbpOhVS3hQGVWXXiHn1aJ2b0ghs1RBPsdWVRycf8Jo2bZGz5fAObFKbedQpQ+wo5qcVU5fk1R8zv5tuJ9hlTx8xTNymehfrWL0DNf7E8jois/kH3Pk3UvSfk8DA3XVZ1RVTjyat6IEqF1dScMRlPe4yI6kJr9VXoKRnrrB6XCrq93XekuGku+zJOG9B///2XxowZYwqsgBoRHkqkTZtWzJMmBhB1ePLkiYgMhi5v+/btyRNYecJW6BtlpipE5+op6t+qiJqXMqY6MJ7L8RENqew3mxXfg7xaKbou5kE3UoxB8rPKXVIqjo1iznU0J8UoNqcqVJRMeyGlpAoRMy2qpdijWQmjwS6RPZgq5klHh284Hk1ZUy6Xb0eFp4l2X8Pt/kvHsiLQrGOlnLTs0G3TOrLzDp0liCn8qOtgeu+ZFESdo4ZSId1t6q39TxQb+FnXnsqqL9Nw7RIKUr2hM4Y89HnUZwkmxOAMudOnpJtmSld+iVyX1CMNaI8ePahFixbCfVupUiUaO3YsNW1qGcoPw5oqVSrKnz9/orlw06TxPJUMe26eSuoLFKDS0V0pg1ANsQYXX+Pi7L71dNKl8qd8GVPRtce2qScXDTkInnukG/yiN+YNgnFrz5sE6u21nyX+4ylvtBSbzL/6Gk4ZT5AnYyrT8+mdylPF8TFpVrHxXVvHilm+QMro/Nf8IalNUdrftS1FfesVtKgza56yZq8T1T+qj+n1ZX2OZCGhuLh7ZapRMKOICi9n1gGMdCKFx1tx2splzZpVPADmGFHGLFMmzx76o4IMHjJhYWEJ/pvI2VMaPVioD4n0FcsRB14VyZqGcqRzPIfFeAbr+9ekwsNta3XKAt9F1LcpO4XalL8CK4/bJuFD49TaeIKF0akS7hqD2Ng3uB5tOPOA3q/I9WoRTKQkr5k1OFCISyDdpWmJLOJ4xRJGkmxoXjIrrT1tlH/MFBSg2DbqFE6YqHRPwK2xd+3atT3eeILvvvuOgoODTY+cORP+JhARZX9uQw4gUpz/VBkjQBnvIECrEeXPdn5dh9qVj8nL3GemQVpdo6w3ba5aBfKo7tPZwO6m17ujq/ccMBSla9HqRvbY+mVtO9unVgwwWtO3hjACMihC3q1GXi5fSESPwoyd8Q+rxuRayp65wpnTULGsQdS9Rj4Lyc7kyojofF7zefdCmdMoto3v3y1FvkqyCpszGAwUGelcNfuAgIA4X7RDhgyhL74whnHLI9CENqJRkBGyI8tVVH3LVEDbGlx0TcxuXIznI5c/G9CwkAgIAnC3ztE1pe7a9aKYtbX0Y4bUAZQt2DKIrHy0whA4achHH0d9RZX154XijDvavAAC9vL7eQYba4GOaW1slzM+KG9axsQAdbDGJbJYuMJlRrcqLrxIuRzUE01OdK6SW3gVUgVoqWv1PPTkVcx9GfddCEj8dfi2KLPmy7Wfk5UB3bVrl6gz6gznz5+nIkWMScnuAiOMR2KC+QMlqkW7b6FTKkfWmZM3Yyoxt8J4P3clowtQzt80l36c1bm8mD9DoIo8Ei0fHXgGRkZ1EfU7dxniT4u6SJY0dOHBS4tlVfNloFsKJdN8vUNkr+B2mZzGknVvIx1H1yYHVnxaVczhyvO4o1rGeEXMBSTGtA4mXydZGVAYxHnz5jm1rjwf62l0i64wb42j8mWYW2lRyjP3l4kdjVUP/k60AYV2LQQVDGYzLbLqkFxWKw29ofc0O8XzjyO/pJNW8mz2+DoWfV1zVnxajd5Y3fiX9aji9OeZGMzdnw2KZia9wUDbLxoLBnSplofm77Of1+sKuGdcHteU8g01qhz927sa3X72lvotOy5eT+5QhoJSaEUNWXNqFswoorAZDzSgWbJkEZVevJVv152nB2HhCu9IVCN6vkspfQVSYY2Ls/vWW8kSHEi/dS5Pw/49I6T55E4UcgGhRnNasq01aoiOQsmnukdalTEKcquhrNO/aV5JZnqncg7rXMKNhwcTd9Rmx3n2RxVEVkPeIUYjV79opngxoPuH1KOswTGiG1BIKpsrnXhUyZteBDTJKTfIV91w9oFxez6sQA1YpMUl+KpIYLWhnzZdEhPya07do1m7rimuh7kulBSKkPzosMF2ZIAovuLZbN26jPeADhKiGzvPOURvKZA268tTQ81RIaxxWq9kQI3/oVgEDhqKuFSiDOL4MiwNmbiUzhFMH1Uz6ojL84chaQKoRoGM1L58Dvo7ej7c2fShRsUyW1R2MjeeC7tVopJmI0rrcmy/dipHL8OjhLs2pT+bA1dx+4g9e/aMli1bRteuXRPPreX90DDmzJlDicG4cePE/7Nnjeo+ixYtoj17jAogw4cPp8TkYVi46EV+3aiwMJiLDtykQlnS0Lg1MQVr7blvDxkKi/krJfetL0/U+wo1C4ZQ/pBUojTZXkNxYUBR9mqmvpXdz+SJNqA3DM55KN4tl4NqFcrIEd1JyH8KBcfhvsU1PrZ1CQsDirnT20/f0BOr2AlZvL5ekUwisOzEyIa06dxDqpbfUpIvtsIHuL+kTek7JeiShQHduHEjtWvXTmjeoqB2unS2CiSJecMfMWKExeu5c+eanie2AZ285ZJQHmlbNkYpZPR/Z63TOhXl+5Sib+G+5ehb3wFRmjCgcjpLRfVF8qcouxqn+dTGSN2bknMCG5mDAuxWdmGSBvNoaLhXUWt2yD+nacWxO7Tys+rG/NEpu+l6tPDGHz2q0Mnbz4UBlYuXwwi+V4FzcT3CgH755ZdivvKff/4R+rNJTWzi9omJ7AbBXOf0HVdN81X2NlFLOqqiPm83gAh1IMvm9G2JNF9CjnxEabNQKZhCVC+oqfog/WeooSieUE9tDAo5qTBPqkTG1FyyyhPawA/tStH4NiVM89V/9axqUoZCTmmlPOmpVZmEqwzEJKCQwpUrV6hfv37JwngmVzWS7mbRbfbMeyv1PprpN4nSqN7SEykNnZMsE7AR2AElEPPAA8a7iYl2VYmcTlBXYyziYN0K2mp2U5DqLV01ZLUQYGC84z5iHuiFOdKN/WvRxzXyCilI3BPM5zoZDxqBovLJy5eWeWGMEdlzHal3rA9ZXHWdfvGfZnqNG6B1EAjy/Nh961vsvvw45rmhFDXQHKc8qgcWHbGiqps0xW8aFVIbJf0W6BspBhDhJowpAHM4GM2zy6UNj1YIYjx4BIqgnenTp9ONG/GTs+QtIEl6zu7rTq1bTh2jHmPPfZsmQEuV8sZenZ7xPg8GkEeVZdTXTAWV5ZGnbDzBCn0txe8yH7Ei2OTMmMZUOR/XfWSYJB2Bbt26lUJCQoSgfMOGDYX8nUajsQkiQqFrX2Lu3us2OqX2+MZvvsXr/YZiNu7bxiUy+3SpIF9kx1d1qOYP28XzW2Z1Guf5/UD/ixpuEbUNfoh6j16TsivPvC2OaVVc5AMyDBN/uHVFTZsW43pcs2aN4jq+aEANThpPqMuYMzSqO922iqIU7tvirD7ka5hLwSGl6YQhnxiBVtOco2xRj0lFkqjUopPUVDFiOj1TkH209mK8jNDZlZhjGMZ91O6Kvsf20OuTv+ZjQkVQxkYjdUyAEYKHlurr26wT6KcWtfcY36ZN5Fg6bTAm3VdQX6Jc6kfi+XUpa6zGE4x9pzhd+7ZZgm8nw/gi7B+MR4JSOBdSXkZ9xfS8ScT3ivNgDYpktojCY3wHCMbLIDgIxhKEqJ5TSjJKQb4mS0UZe1q3gVoNR3EzTAIRp0mR69ev0/r16+nmzZvide7cualp06aUN29e8kWgGOIMxVTG4zUkqjuFkrFKg414QknWvvVVGlnpHj+S0poMqPz8jWSbz4n4I8wiQN5NrvpjHpTEMEwyMaAQU8AcJ9y15qjVaurfvz/9+OOP5GvIwgmOkaiY2mhAzxks8z5ltBoV1Sns+QXLmfgh1MyA5o1OaXlJtnOaMJ5FswZRx0q56NftRi8HS0AyTDJz4f700080adIkatu2Le3fv5+eP38uHngOiT+8h4evUSJ77HNSIfScMqrCSC+p6KJkK72lURHVLhjCEZOMCSgSgXc1e+gLv+Xi+WZDjJvXnNCXEeK/7P5HZ4xhmGQ0Av3999+pVatW9Ndff1ksr1y5Mv3xxx8UHh5Ov/32Gw0YMIB8iYp50tOF+y8dprI00RjrgV6TslE42brh9BJR05IcfevroFbklvNGofhjUkGL91C1Z7W+qsUymEm0upzpjSkt75bLTq8jdKLwNcMwyWgECgGFxo0b230f77HIgjKjtQvE//uSskACpqwaFGX3ra8z44NypuLLN6SsVDx8Dv2ma07zdY2oesQvNlV75C4bSmLJ4uL96hfkQDSGSW4j0EyZMtHJkyftvo/3ILTAWFJSdY00KuOt7k99XUXjWTlvBi4vxAgBDXg09lwxSvtBLOE7XSe7RyZbcCCt7FOdMqRisXiGSdYj0Pbt29Ps2bNpwoQJoqSZDJ5///334r0OHTrE53Z6BaXVMUFGaw2Vbd5HxZZmpdh9yxipHj2adIYu1fNQpjSBHHXLMMl9BPrNN9/QiRMnaOjQoTRy5EjKli2bWH7v3j3S6XRUt25dGjt2bHxvq8eTU2VMgp+ra6JQW8NI42LO1XVkvJ8q+ZzTQe5aPQ99UtO5cmYMwySxAU2ZMqXQw/3vv/8s8kCbNGlCzZo1o5YtW3L4vAI5VaHi/23J1r2tiq4+nynIcYI84zuUzG6Mvo2NkS2K8fXGMJ4mpNC6dWvxYGKnoOoONdMcshEJN6Eias7uW8b84tSoqWT2IDp9N8zucUGhZc71ZJikgaX8EonNAQNNzw9YVV6R5z8bWynQMMzqvjWpXC5btSpwclQjLnfHMMl9BAppPigMXbhwgfz8/MTr2Hq9eP/qVWeUebyf8qqLpuczdS0Uy09lShPAFTMYRf7pXZ3yDF5rs5zLkzGMBxjQ2rVrC4MII2r+mnGOXlpjybc/dHVogu5/iutw5RUmNnH4iRsvUvFsQUKyr2u1PBxxyzCeYEDnz5/v8DVjnwKqO9RQc5QMkopm6VvYXa9HLY6iZOzzWd0C4sEwjIfPgS5cuNCh0hCicrEOQ9RDY3S9bTJUEPJ9SrQqnY2KZIldR5dhGIbxcAPatWtX2rdvn933Dxw4INbxdbLQE3pHs0c8/01nf/QpS7YxDMMwXp7GIiFk1AFQJNJq45Qh4/EEUCQdCOwrnh80FKHjVoLgFuv6sQFlGIbxNJy2cqdOnRLqQzK7d+8WqkPWoKzZzJkzqVChQuTLlFNfNj2fq2vqcF1onjIMwzBeakD//fdfGjNmjHiOCFyUK8NDibRp0/r8HGhGemE6HhsNFewe13wZU1HrMtldO2sMwzCM5xjQHj16UIsWLYT7tlKlSkLrtmlTy5EVDGuqVKkof/78Pu/CzaAyqses0UM03n7Kz7av6sTl/DEMwzDJ3YBmzZpVPMD27dupaNGioqwZo0xGlXEE+liyr2daIFNqPnwMwzAeiluRPhBSYByTgYwj0CeS/fQUNYtRMAzDeCxuh8o+ePCA5syZQ8eOHaMXL16QwWCwceeiYouvkjHahfuE7I9ANRx8yzAM41sGFBG5derUobdv31LhwoXp9OnTVKxYMRGBe/fuXTEHmjNnTvJlMkS7cB2NQDVqlkNkGIbxVNwaAw0ePJhSp05NFy9epC1btojAoilTptDt27fpzz//pGfPntGECRPIl5FduKEO5kA17MJlGIbxLQO6d+9e6tmzJ+XKlcskMC+7cNu3b0+dOnWir7/+mnwZOYjoCTmYA+URKMMwjG8ZUBjLzJkzm3I+NRoNPX361PR+yZIl6ejRo+SrpKBwSqWKiNWFe/zW80TcKoZhGCbJDSjqgV6/ft34BWq1eA1Xrgx0cmFYfZUMqpfif7jkR68Uan/KDGhgX96PYRiG8UID2qhRI/r7779Nrz/99FOaPXs2NWjQgOrXr08LFiyg//1Pue6lL5COjAb0GaVxKKLweQPfljtkGIbxuSjcYcOGUceOHSkqKor8/Pyof//+QkB+xYoVwp07YsQIGjp0KPkqaVRvxP8wKWVSbwrDMAyTnAxounTpqHz58hY5n8OHDxcPhiiIjAb0JbEBZRiG8VY4lT8ByKV6KP7fl7jKCsMwjE+PQLt16+byF2NUCqUiXyQkOoXlrpQxqTeFYRiGSUoDum3bNmEQzXnz5g2FhoaaXLoAAgogJCREVGXxVdJHR+E+kxBExDAMw/isC/fGjRsibUV+rF27VgQPIVDo0aNH9OTJE/HA8yFDhpC/v79YJzGA3i5GyCjgnTJlSsqXLx99/PHHdP/+fUrqKNynIgqXYRiG8UbcCiLq27evqAU6btw4i+UZM2ak8ePHC0OKdcxzQxOKQYMGCREHKCAVLFiQrl27RtOmTaM1a9bQiRMnKEuWLJQcR6Cs4scwDOODBvTAgQPUrl07u++XLVuWli1bRonBzz//TDVq1DBJCoImTZqIkmswpNZGPjFIS6/E/6cODOjZMY0TcYsYhmGYZBGFmz59elq/fr3d99etW5doSkS1atWyMJ7yMmzj+fPnKTEJeXuNFmrHUR61MQr3OSkXzO5ZOx+l9He7khzDMAzjqQYUQvJwkbZu3Vq4aTFHisfmzZupVatWwrj26tWLkopXr16JB1zKjoiIiKCwsDCLR1x49/ooqqY+a3ptL41lyYFbcfodhmEYJulxaxgEwQQYn4kTJwpDavGFWq0od5aUogqTJ0+myMhI6tChg8P1vvvuOxozZky8/W768Dum56FSEL2lQMX1XkXo4u03GYZhmKRBJaGYp5s8fvxYjEBv3rwpXufOnVvo4cY28nNU5QWGzxkCAgJsUmvArl27hB5v27ZtRW1SR6ATgIcMRqAoBP7ixQsKCrJfRcUeb7/JQSn0xgCi44YC1CZyrOk9bKn5gb4xobnL388wDONNhIWFUXBwsNv33KQmThNxMJTvv/9+vG0MjF/dunWdWhfzm0WKFLFYduHCBWrTpg2VKFFCiNs7Y4TxSAhuSyEWr1H6s0SOtHTy9nNqXjJrgvwmwzAMk3jEOZLl5cuXovcgF9Q2BwW3XQEGcd68eU6tmzWrpRG6ffu2qBKD3gyCmNKkSfwcTI0UZXp+x8qA6iWikS2KUu4MqSh9Sv9E3zaGYRgmmRjQGTNmiBQS5F3aQ6/Xu/SdyNns0qWLy9sCEQcYT7hjIaxgbVwTC60hxoDekzJYvJfCX0Olc6QlrYblhxmGYbwBt+7mM2fOpM8++4wKFCgg8iwxjYqSZggeghEsXbp0oungooxas2bN6O7du2LkCTGFJOHecVKTscOwSV+e/tNXt3DfVs+fgY0nwzCMF+HWCHTq1KnUuHFjka6C0R/qgzZv3pzq1atHAwcOpAoVKojliUGnTp3o0KFDQs4P86LmuZ+pU6emd955J1G2g04vNz3tEfWFRSFthGnVLGjp0mUYhmF80IBevXpVjEABNHGBHD2LOUho0U6fPp2+/PJLSmgg1wfmzp0rHuYgKjjRDKjKfDBvGR2M6NsaBbkyC8MwDPm6CxdGUqcz5jIi9Bgi7gjikUEAz4MHDygxgIADXMhKD7yXaJQ2RiOfMOS3eStjan/Kl9F3q9MwDMN4I24ZUKSJnDx50vS6SpUqIqgI85AwpL/99puojuJTZC5Ok0usoE66kTZv1S2cSTFnlWEYhvExF+4HH3wgAokQ9Yo8Sqj5QEBBTluBW3fFihXka7wIyEoRBFEJS22KmoV4/pNhGMbbcMuAdu3aVTxkqlevTmfPnqXVq1eTRqMRKSU+NwKNRmewNJ6dKueiFiycwDAM43W4bEDDw8Np1qxZVKZMGVH1RAaFrD///PP43j6PZ3ybkkm9CQzDMExymAMNDAwURawvXryYENvDMAzDMN4dRJSoEa4MwzAM4w0GdPz48SLSFpVYGIZhGMYXcSuIaNq0aZQ+fXqhRpQ3b17xSJEihcU6SNv477//4ms7GYZhGMbzDeipU6eEgUTaCgTjr1y5YrMO5z0yDMMw3oxbBpTnPxmGYRhfh2trxSMQjWcYhmF8A7dGoLdu3XL4Pty3SHfJmDGjT7lyI3SWRcUbFcucZNvCMAzDJEMDmidPHqcMI4xozZo1acSIEUKtyNuJ0FkWEP+uLYsoMAzDeCtuGVAUy/7ll1+EcDzqcaKwNrh8+TItXbpUlBGD1B+CixYvXizqhG7YsIHq1q1L3sz95+Gm534aFaVP5Z+k28MwDMMkMwN67949Uf8TBjJt2rQW740ePZpq1KhBb9++pcmTJ4vRZ/ny5YXgvLcb0NBXEabnIakDfMp9zTAM42u4FUSESiwomm1tPAHyQ/EeckVBhgwZqFu3bnT06FHydnT6mDnQ7Oks82IZhmEY78ItA/rkyRN68+aN3fdfv35NoaGhptdZsmQRBa69nSh9zD7mSJcySbeFYRiGSYYGtGLFijRlyhQ6ffq0osjC1KlTqVKlSqZl58+fpxw5cpC3E2U2As2WNjBJt4VhGIZJhnOgMJCYzyxbtixVrVrVFESEOdH9+/dTUFCQCDKSy5/t2LGD2rVrR75kQMvnTpek28IwDMMkQwNaqlQpMfqcMGECbdy4kQ4fPiyWI/q2d+/eNHDgQNOIE6ksx48fJ19AZ+bCzZWeXbgMwzDejFsGFGTLls00ymSMRBmMI1B/jZrnQBmGYbycOEv53b9/n06ePCkCh3wdeQR6aXxTCvTTJPXmMAzDMMnRgKJUWZEiRYSrtly5cnTw4EGx/PHjx2JudOXKleRr6AzeH2nMMAzDxMGArl69mtq2bSu0bkeNGmWRooJl2bNnp3nz5rnz1QzDMAzjvQZ07NixVKtWLdqzZw999tlnNu8jMtdXAocYhmEY38QtA3rmzBl677337L6fOXNmevToUVy2i2EYhmG8z4CmTJnSYdDQtWvXhIQfwzAMw3grbhlQiCgsWLCAdDqdzXsPHjyg33//nRo1ahQf28cwDMMw3mNAx48fT3fu3BGSfr/99puoOgJBheHDh1PJkiVFUBGCixiGYRjGW3HLgBYuXFgEEMFNi3JlMJgTJ06kb7/9VhjQ3bt3i6LbDMMwDOOtuK1EVLx4cdqyZQs9e/ZMaOAaDAbKly8fhYSEkK+SOkBLryJs3doMwzCM9+G2AZVJly6dcOUyRFu+qE2PzYpqMwzDMN6LywY0IiKCFi9eTJs2baKrV6/Sy5cvKU2aNKIiS5MmTeh///sf+fv7ky+SJThQPBiGYRjvRyW5UOkaFVhat25NN2/eFPOewcHBlDp1anr16hW9ePFCBBPBjbtq1SoqWrQoeRphYWFin7AvKMnGMAzD8D03zkFEMJKtWrWihw8fiijc27dvi/lP8//jxo2je/fuUcuWLVlcnmEYhvFqnDag0La9desWrV27lgYPHiz0bs3B6yFDhgid3OvXr9P8+fMTYnsZhmEYxrNcuJjfhIt2/fr1Tq0LNmzYQJ4Eu3AZhmH4nhvvI1DMf9apU8epdevVqyfWZxiGYRhvxWkD+vTpU8qSJYtT60JMHuszDMMwDPl6GgvSV/z8/Jz7Uq2WIiMjydOQvdlw5TIMwzAJS1j0vdaFZBDPzQO9ceMGHTt2LNb1EETkiSCnFeTMmTOpN4VhGMZnePnypUgh9NogIrVaLYKInAFfiXX1ej15EpAjRBoOhCGc3de49LxgqJH+4405p7x/ng+fQ8/GE86fJEnCeGbLlk3YGK8dgSKNxdvBCcyRI0ei/iYadnJt3PEB75/nw+fQs0nu5y/YA0eeLhvQjz76KGG3hGEYhmE8CM8bMzMMwzBMMoANaBIREBAgio7jvzfC++f58Dn0bLz9/HmcmDzDMAzDMEZ4BMowDMMwbsAGlGEYhmHcgA0owzAMw7ABZRiGYZjEgUegDMMwDOMGbEAZl+CgbYZJOl68eMGHPxnBBjSeePPmDXkz165dE/sYHh5O3sjJkyfp8uXLdOfOHa/sLPz333/Uu3dvcR5l3WdvYtmyZULDeu/eveSN/PPPP9SoUSOaNGmSKOrBJA/YgMaRixcvUvny5enjjz8mb+TUqVPUvHlzatmyJeXNm1cUVcdNyluMC/avYcOG1KJFC3EeS5cuTb/88gvpdLoELyiQWGzevJnatGlDixYtojVr1ohlnijcrcTx48epcuXK1K1bN9FOk7PmqzuguAX268MPPyR/f39KmTKleDDJA++4ipIAGJAVK1ZQq1atxEX8xx9/0M6dO8lbQCWdqVOnUoMGDej169fUrl078bh//77oLOzatYs8maioKPr222+pdu3a4vmgQYNo1qxZVKpUKRoxYgStXr2aPB25k5MhQwZKnz69OKdLly4Vo21PH4W+fftWGE10elKkSEF//vmn6PiULFmSvAm0SZSHxP8ZM2bQwIEDKVOmTEm9WYwMlIgY17l69apUokQJKUOGDNK4ceOkYsWKSVWqVJGioqK84nBu2LBBypcvn9StWzfpwoULpuV79+6VVCqVNGjQII/e17Vr10rlypWT+vfvL126dEnS6XRi+eXLl8X+/fDDD5LBYJC8geXLl0uNGjWSZs6cKfZt6NChpv31xH3Eto8fP17syyeffCKFhobabYueuH8yt27dkjJnziz169fPZrm37KOn41JBbSYGrVYrRp/vvfeecPulS5eO+vTpQwsWLKDu3bt7/KE6d+6c0NCcMGEChYSEiGWRkZFUrVo14TJDYXUcA7n2q6eBEkqdOnWizp07m/YPnDlzRrzOnTu32C9P3T8gbztqQh48eJA2btxIy5cvF6UJ69atK7wLnohGo6HGjRvTunXraPfu3ZQxY0axfNWqVWKuMHPmzFSkSBFxfuH29FQw14lambivALjgcT2CQoUKiXtPx44dPbZ9egVJbcE9Ab1er9jTCw8PNz2/ePGi6OXnyJFDevz4seSp+2e+j9gn8/fl3n+dOnWkGjVqSG/fvpU8+fxZs3v3buFVCAoKkkaPHi2dPn1aevbsmcV3eOL+YQRaoEAB8fz48eNi5PbRRx9JT58+dfi55L5/8oj6yy+/FNcenmM/06RJI563bdtWOnPmjMV3eNL+HTlyRNJqtdK///4rzZ07V1Kr1VK7du3EucuUKZPYx3nz5iXRVjOADagDIiMjhato9uzZTrWWP//8U0qRIoU0cOBAr9w/2cCWLVtW6tChg2mZJ++ffPOCSxo3pLp164obVPfu3aW0adNK77//vuSp+yefm0OHDgmjcu/ePfEa+xYQECAtXbpUvH79+rXkSfsn79fNmzeFQcF5q1evnph2wLK7d+9K33zzjTA47du3lzz1/MGAZsyYUfrggw+k0qVLSyNGjJBevnwp3jt16pTUuHFjMYV0/vz5RN5yRoYNqB127dolFS9eXFyc6N2eO3fOrsGQlz169EjMGQYGBpp6vsnVwLiyf+bcvn1bSpUqlfTdd9+J1/Jcmqfun/wavXx0gOA9kJcNGTJE3IQnTpyY7EYxrpy/v/76SypUqJD08OFD8TosLExKmTKl6Cx07dpV6ty5s8m4etr+LVmyROrSpYuYm7d+r1OnTlJwcLC0atUqxc96wv5Vr15dtEEY0n379lm8t2nTJil9+vTS559/nuzap6/ABlSB/fv3S0WKFJHy5MkjerBo5N9//71TQTNbt26VsmfPLrVp00byxv3DhY/1N27cKHnD/jm6qSKgCC5B9P7N3fWesn/yvsE1DYOJzo9Mx44dJY1GI/n5+UmjRo2SXr16JXnS/sn79uLFC9FxNUde78CBA+KzcMcnJ+PpzP7JHVOMqvE+HvJIMyIiQvzHfjdp0kTKmTNnsmqfvgQbUAXQG4SL6++//xava9asKRUsWFD0cu0hX6C4EcHVggYPYwp27twp/ffffxbredr+yUyfPl3My8iuJFzoiEiGu8kb9s+6J1+1alURXZ2cblDW+1erVi2H+/fHH39IhQsXlp4/fy5t375dzF/DeGKuFx0EGNjkcu7icv7k7ZfPH6Jz4YZPblMqru4fRtK4n/Ts2VO8Nje0cGEjAwAdCSbxYQNqhdzzM+/VyqMuhJPLDVXpZiNfuEj7QIpEyZIlpTFjxogeIuYqZBeap+4faNmypVStWjXxHCOaxYsXizlR7O+TJ08kbzh/MhhlY4SGVJfkgiv7J+8jOnL+/v5SixYthOGEWxCfgWtXvjHLoxpvOn/o7OFzv//+u5RccHb/zPcF1xk6O9aen7Nnz0r58+cXc6TJpfPja/i0AUXPHDePCRMmiEYsY94Y5YaMwBL0ZleuXBnr9yKQAfMysuuldevWFu4zT9w/fAajzqxZs4rAmi1btkitWrUS+wc30p07dyRvOX+YD1y9erVUu3Zt0btHNG5SEF/7h5FNqVKlpKJFi0rTpk0TbVG+kcOYIpcyKQxoQp2/Bw8eiDlt7DPOYVJFxcfH/snnCd+Faw9znjhf3377rdS0aVMpXbp0yXo6xdvxSQOKCwwRbAiGwcgJjRAuFcwFyWkL1onmMBCpU6cWofGyMVSatIc7DAYFE/8YmTnrNvSE/bty5YqYS8N3Yl24BWU3tTfs344dO8TNCW4xRK1i7vPw4cMeu3+yqw/RnriBoyMgG0r5c0mRipSQ569Xr15ifhfr4rtPnDjh0ftnbmxxL8H3wtAijQX3F3PDzCQ+PmlAFyxYIHpyiODDaAOuR4wYcdPs3bu3zfpyI0bIOQzjrFmz7LpMMDKDuww9fW/bv23btokRJy5eb9w/jDoxJ4g8V+TdedP+JScXX0KdP+S7wghVrlw5Sd228b1/5s/RAYIRPnnyZCLtDeMInzSgcOsgMMQc5MLBjQIDAZk3pR4uevKYc8AFCvk3gAAa6yjApE7tiO/9M5+7/e2338R63rp/eJ3U6QDxuX/wGli3z6QmIc8fDIu3XX/m5y+p2ybjwwYUjQ/RlHCDYO5HRnZ1HT16VCpfvrzQgLXu4coXJaJpZS1YqIDARYPJ/+SQjJ6Q+4fcQW/ev+SQxpGQ+/fmzRspqeHz59n3F8aHDChyppBg3LdvX2nYsGGmHh145513xPydHBxi3quD+wQNeNKkSeK1dW8WN7OKFSuKaEash4l95GolNrx/fP64ffL1xyQtXmdAMUfw1VdfCUm9ChUqiPwqGDr0+uS8K8yVYBnmuWTjKRvKGzduSPXr15fy5s1rE3Bx7NgxYYwxz4L5jMmTJ/P+8fnj9snXn9fcXxgfNqBIs0CpJjRmKHtADB0NGIE92bJlEwnLcGWhMSPCEgnoaNDWQLkEkW7yXIXcyPv06WMS4paFBBIT3j8+f9w++fpjkg9eZUCvX78uenbIvYLqijlYFhISYlLMWbRokTCGP//8s2l+Qe4RomIFouGQS2Y+BwVRblmzMing/ePzx+2Trz8m+eBVBhSjRMxhmiNHjEJ1BRJ0sp4kDCxyrrJkyWKTvAxDCeOKcPTkBO8fnz/A7ZOvPyZ54FUG1Hy0aB38g4oaCPyBzJ4MEpZR8R1VEeRAIJRCgqs2d+7cIiE6ucH7x+eP2ydff0zywOsMqDXyJD4icjHalEeksoGFDBZCxTHiLFOmjBAPh/4pNGyxTnJKQFeC94/PX3KG26dnt0/GMSr8IR+gQoUKlCdPHlq+fDnp9XrSaDSm9x4/fkxz5syhq1evUlhYGH3++edUtWpV8iR4//j8JWe4fXp2+2TsIPkAUPJAWotcGFnuGT99+lTyBnj/PBs+f56Nt58/xj5q8gHOnDlD4eHhVLFiRfH6wYMHtHTpUmrcuDGFhoaSp8P759nw+fNsvP38MfbxagMqe6cPHz5MwcHBlC1bNtqxYwf17t2bunXrJt5Xq9Wm9TwN3j8+f8kZbp+e3T4ZJ5B8AKSrQKQZpaqg8AF1ok2bNkneAu+fZ8Pnz7Px9vPH2MfrDSjqHSL6DVFwqOoua9x6C7x/ng2fP8/G288f4xifiMIdNGgQqVQqGjNmDAUEBJC3wfvn2fD582y8/fwx9vEJA2owGMRchLfC++fZ8PnzbLz9/DE+bkAZhmEYJr7hbhPDMAzDuAEbUIZhGIZxAzagDMMwDOMGbEAZhmEYxg3YgDIMwzCMG7ABZRiGYRg3YAPKMAzDMG7ABpRhGIZh3IANKMMwDMO4ARtQhmEYhnEDNqAMwzAMQ67zf1N/YTfYh3vNAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -321,7 +398,14 @@ { "cell_type": "code", "execution_count": 12, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:04:00.902087Z", + "iopub.status.busy": "2026-03-20T20:04:00.901783Z", + "iopub.status.idle": "2026-03-20T20:04:28.333559Z", + "shell.execute_reply": "2026-03-20T20:04:28.331603Z" + } + }, "outputs": [], "source": [ "ta.sensor_analysis(analyses=['yoy_degradation'], yoy_kwargs={'label': 'center', 'multi_yoy': True})" @@ -330,7 +414,14 @@ { "cell_type": "code", "execution_count": 13, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:04:28.336376Z", + "iopub.status.busy": "2026-03-20T20:04:28.336076Z", + "iopub.status.idle": "2026-03-20T20:04:28.339809Z", + "shell.execute_reply": "2026-03-20T20:04:28.339014Z" + } + }, "outputs": [], "source": [ "calc_info_multi = ta.results['sensor']['yoy_degradation']['calc_info']\n" @@ -339,11 +430,18 @@ { "cell_type": "code", "execution_count": 14, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:04:28.341973Z", + "iopub.status.busy": "2026-03-20T20:04:28.341663Z", + "iopub.status.idle": "2026-03-20T20:04:28.816150Z", + "shell.execute_reply": "2026-03-20T20:04:28.815323Z" + } + }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -385,6 +483,12 @@ "cell_type": "code", "execution_count": 15, "metadata": { + "execution": { + "iopub.execute_input": "2026-03-20T20:04:28.818597Z", + "iopub.status.busy": "2026-03-20T20:04:28.818368Z", + "iopub.status.idle": "2026-03-20T20:04:35.134207Z", + "shell.execute_reply": "2026-03-20T20:04:35.133065Z" + }, "scrolled": true }, "outputs": [ @@ -392,13 +496,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\cdeline\\Documents\\Python Scripts\\rdtools_dev\\rdtools\\plotting.py:495: UserWarning: Input `yoy_info['YoY_values']` appears to have multiple annual slopes per day, which is the case if degradation_year_on_year(multi_yoy=True). Proceeding to plot with a daily mean which will average out the time-series trend. Recommend re-running with degradation_year_on_year(multi_yoy=False).\n", + "D:\\repos\\public\\rdtools\\rdtools\\plotting.py:493: UserWarning: Input `yoy_info['YoY_values']` appears to have multiple annual slopes per day, which is the case if degradation_year_on_year(multi_yoy=True). Proceeding to plot with a daily mean which will average out the time-series trend. Recommend re-running with degradation_year_on_year(multi_yoy=False).\n", " warnings.warn(\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -473,7 +577,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/docs/sphinx/source/developer_notes.rst b/docs/sphinx/source/developer_notes.rst index dba986e09..6c53b331f 100644 --- a/docs/sphinx/source/developer_notes.rst +++ b/docs/sphinx/source/developer_notes.rst @@ -279,13 +279,12 @@ and compare outputs for you: pixi run -e dev pytest --nbval docs/system_availability_example.ipynb -Some helpful options are ``--nbdime`` to display a visual before/after diff -and ``--sanitize-with docs/nbval_sanitization_rules.cfg`` to ignore nuisance -differences like the username shown in warning messages: +A helpful option is ``--sanitize-with docs/nbval_sanitization_rules.cfg`` to +ignore nuisance differences like the username shown in warning messages: :: - pixi run -e dev pytest --nbval --nbdime --sanitize-with docs/nbval_sanitization_rules.cfg docs/system_availability_example.ipynb + pixi run -e dev pytest --nbval --sanitize-with docs/nbval_sanitization_rules.cfg docs/system_availability_example.ipynb Or to run all notebooks at once using the pixi task: From f4544a70545022a35b5c88ae3d0319d7baa3a668 Mon Sep 17 00:00:00 2001 From: martin-springer Date: Fri, 20 Mar 2026 16:26:32 -0400 Subject: [PATCH 18/18] fix pytest status badges --- README.md | 4 ++-- docs/sphinx/source/changelog/v3.2.1.rst | 2 ++ 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 2e5c391ab..84b6b5398 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,10 @@ RdTools logo Master branch: -[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Amaster) +[![Build Status](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml/badge.svg?branch=master)](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml?query=branch%3Amaster) Development branch: -[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Adevelopment) +[![Build Status](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml/badge.svg?branch=development)](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml?query=branch%3Adevelopment) Code coverage: [![codecov](https://codecov.io/gh/NatLabRockies/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NatLabRockies/rdtools) diff --git a/docs/sphinx/source/changelog/v3.2.1.rst b/docs/sphinx/source/changelog/v3.2.1.rst index c94fb25bd..8220629d4 100644 --- a/docs/sphinx/source/changelog/v3.2.1.rst +++ b/docs/sphinx/source/changelog/v3.2.1.rst @@ -40,6 +40,8 @@ Bug Fixes --------- * Fixed broken link to TrendAnalysis example in Sphinx index page. (:pull:`492`) +* Fixed README CI status badges using a deprecated GitHub Actions badge URL + format. (:pull:`497`) Requirements ------------