diff --git a/.github/workflows/check.yml b/.github/workflows/check.yml
index ec5ffc5..1fe7fc5 100644
--- a/.github/workflows/check.yml
+++ b/.github/workflows/check.yml
@@ -15,13 +15,15 @@ jobs:
name: Run lint
runs-on: ubuntu-latest
steps:
- - uses: actions/checkout@v4
- - name: Setup Python
- uses: actions/setup-python@v5
+ - uses: actions/checkout@v6
+ - name: Install uv
+ uses: astral-sh/setup-uv@v8.1.0
with:
- python-version: 3.11
- - name: Install tox
- run: python -m pip install tox
+ version: "0.11.16"
+ python-version: "3.11"
+ enable-cache: true
+ - name: Install tox with tox-uv
+ run: uv tool install tox --with tox-uv
- name: check-manifest
run: tox -e check-manifest
- name: flake8
@@ -39,10 +41,10 @@ jobs:
fail-fast: false
matrix:
py:
+ - "3.14"
+ - "3.13"
- "3.12"
- "3.11"
- - "3.10"
- - "3.9"
os:
- ubuntu-latest
- macos-13
@@ -50,15 +52,17 @@ jobs:
env:
MPLBACKEND: Agg # https://github.com/orgs/community/discussions/26434
steps:
- - uses: actions/checkout@v4
+ - uses: actions/checkout@v6
with:
fetch-depth: 0
- - name: Setup python for test ${{ matrix.py }}
- uses: actions/setup-python@v5
+ - name: Install uv
+ uses: astral-sh/setup-uv@v8.1.0
with:
+ version: "0.11.16"
python-version: ${{ matrix.py }}
- - name: Install tox
- run: python -m pip install tox-gh>=1.2
+ enable-cache: true
+ - name: Install tox with tox-uv
+ run: uv tool install tox --with tox-uv
- name: Setup test suite
run: tox -vv --notest
- name: Run test suite
diff --git a/.github/workflows/documentation.yml b/.github/workflows/documentation.yml
index 5fd5a0f..a11ff2d 100644
--- a/.github/workflows/documentation.yml
+++ b/.github/workflows/documentation.yml
@@ -12,34 +12,32 @@ jobs:
name: Test if documentation can be rendered
runs-on: ubuntu-latest
steps:
- - uses: actions/checkout@v4
- - name: Setup Python
- uses: actions/setup-python@v5
+ - uses: actions/checkout@v6
+ - name: Install uv
+ uses: astral-sh/setup-uv@v8.1.0
with:
- python-version: 3.11
- - name: Install package and sphinx
- run: |
- pip install .
- pip install sphinx>=4.5 sphinx-book-theme pytest sphinx_gallery plotly
- sphinx-build -b doctest doc .
+ version: "0.11.16"
+ enable-cache: true
+ - name: Install the project
+ run: uv sync --locked --all-extras --extra doc
+ - name: Run doctest
+ run: uv run sphinx-build -b doctest doc .
docdeploy:
name: Render the documentation and push it to gh-pages
runs-on: ubuntu-latest
needs: doctest
if: ${{github.ref == 'refs/heads/main'}}
steps:
- - uses: actions/checkout@v4
- - name: Setup Python
- uses: actions/setup-python@v5
+ - uses: actions/checkout@v6
+ - name: Install uv
+ uses: astral-sh/setup-uv@v8.1.0
with:
- python-version: 3.11
- - name: Install package and sphinx
- run: |
- pip install .
- pip install sphinx>=4.5 sphinx-book-theme pytest sphinx_gallery plotly
+ version: "0.11.16"
+ enable-cache: true
+ - name: Install the project
+ run: uv sync --locked --all-extras --extra doc
- name: Sphinx build
- run: |
- sphinx-build doc _build
+ run: uv run sphinx-build doc _build
- name: Deploy
uses: peaceiris/actions-gh-pages@v3
with:
diff --git a/.github/workflows/publish-to-pypi.yml b/.github/workflows/publish-to-pypi.yml
index aac8cb1..d6df6c7 100644
--- a/.github/workflows/publish-to-pypi.yml
+++ b/.github/workflows/publish-to-pypi.yml
@@ -10,17 +10,14 @@ jobs:
runs-on: ubuntu-latest
steps:
- - uses: actions/checkout@v4
- - name: Set up Python
- uses: actions/setup-python@v5
+ - uses: actions/checkout@v6
+ - name: Install uv
+ uses: astral-sh/setup-uv@v8.1.0
with:
- python-version: "3.x"
- - name: Install dependencies
- run: |
- python3 -m pip install --upgrade pip
- python3 -m pip install build twine
+ version: "0.11.16"
+ enable-cache: true
- name: Build a binary wheel and a source tarball
- run: python3 -m build
+ run: uv build
- name: Store the distribution packages
uses: actions/upload-artifact@v4
with:
@@ -46,8 +43,12 @@ jobs:
with:
name: resourcecode
path: dist/
+ - name: Install uv
+ uses: astral-sh/setup-uv@v8.1.0
+ with:
+ version: "0.11.16"
- name: Publish Resourcecode 📦 to PyPI
- uses: pypa/gh-action-pypi-publish@release/v1
+ run: uv publish
github-release:
name: >-
@@ -62,7 +63,7 @@ jobs:
id-token: write # IMPORTANT: mandatory for sigstore
steps:
- - uses: actions/checkout@v4
+ - uses: actions/checkout@v6
- name: Download all the dists
uses: actions/download-artifact@v4
with:
@@ -113,8 +114,9 @@ jobs:
with:
name: resourcecode
path: dist/
- - name: Publish Resourcecode 📦 to TestPyPI
- uses: pypa/gh-action-pypi-publish@release/v1
+ - name: Install uv
+ uses: astral-sh/setup-uv@v8.1.0
with:
- repository-url: https://test.pypi.org/legacy/
- verbose: true
+ version: "0.11.16"
+ - name: Publish Resourcecode 📦 to TestPyPI
+ run: uv publish --token ${{ secrets.TEST_PYPI_TOKEN }} --publish-url https://test.pypi.org/legacy/
diff --git a/.gitignore b/.gitignore
index b96edf4..d40efb6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,192 +1,6 @@
-# Created by https://www.toptal.com/developers/gitignore/api/python,jupyternotebooks
-# Edit at https://www.toptal.com/developers/gitignore?templates=python,jupyternotebooks
+# uv
+uv.lock
+.venv/
-### JupyterNotebooks ###
-# gitignore template for Jupyter Notebooks
-# website: http://jupyter.org/
-
-.ipynb_checkpoints
-*/.ipynb_checkpoints/*
-
-# IPython
-profile_default/
-ipython_config.py
-
-# Remove previous ipynb_checkpoints
-# git rm -r .ipynb_checkpoints/
-
-### Python ###
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$py.class
-
-# C extensions
-*.so
-
-# Distribution / packaging
-.Python
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-share/python-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
-.doctrees/*
-public/*
-output.txt
-
-# Sphinx documentation
-doc/_build/
-doc/auto_examples
-
-# PyInstaller
-# Usually these files are written by a python script from a template
-# before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
-
-# Installer logs
-pip-log.txt
-pip-delete-this-directory.txt
-
-# Unit test / coverage reports
-htmlcov/
-.tox/
-.nox/
-.coverage
-.coverage.*
-.cache
-nosetests.xml
-coverage.xml
-*.cover
-*.py,cover
-.hypothesis/
-.pytest_cache/
-cover/
-tests/output/*.png
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-db.sqlite3
-db.sqlite3-journal
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-
-# PyBuilder
-.pybuilder/
-target/
-
-# Jupyter Notebook
-
-# IPython
-
-# pyenv
-# For a library or package, you might want to ignore these files since the code is
-# intended to run in multiple environments; otherwise, check them in:
-# .python-version
-
-# pipenv
-# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-# However, in case of collaboration, if having platform-specific dependencies or dependencies
-# having no cross-platform support, pipenv may install dependencies that don't work, or not
-# install all needed dependencies.
-#Pipfile.lock
-
-# poetry
-# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
-# This is especially recommended for binary packages to ensure reproducibility, and is more
-# commonly ignored for libraries.
-# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
-#poetry.lock
-
-# pdm
-# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
-#pdm.lock
-# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
-# in version control.
-# https://pdm.fming.dev/#use-with-ide
-.pdm.toml
-
-# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
-__pypackages__/
-
-# Celery stuff
-celerybeat-schedule
-celerybeat.pid
-
-# SageMath parsed files
-*.sage.py
-
-# Environments
-.env
-.venv
-env/
-venv/
-ENV/
-env.bak/
-venv.bak/
-
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
-# mkdocs documentation
-/site
-
-# mypy
-.mypy_cache/
-.dmypy.json
-dmypy.json
-
-# Pyre type checker
-.pyre/
-
-# pytype static type analyzer
-.pytype/
-
-# Cython debug symbols
-cython_debug/
-
-# PyCharm
-# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
-# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
-# and can be added to the global gitignore or merged into this file. For a more nuclear
-# option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
-
-# End of https://www.toptal.com/developers/gitignore/api/python,jupyternotebooks
-
-#Additional stuff
-joss_paper/paper.log
-joss_paper/paper.Rmd
-joss_paper/paper.html
-joss_paper/paper.bib.bak
-joss_paper/paper.pdf
+# Jupyter checkpoints
+**/.ipynb_checkpoints/
\ No newline at end of file
diff --git a/MANIFEST.in b/MANIFEST.in
index 355dbf4..c088349 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -2,16 +2,19 @@ include LICENSE
include CITATION.cff
include tox.ini
include mypy.ini
-include config/config.ini
-include dev_requirements.txt
include fp_hs.png
exclude .gitlab-ci.yml .gitlab-ci-ifremer.yml
include *.md
+include uv.lock
+include *.txt
+recursive-include config *.ini
recursive-include notebooks *.ipynb
+global-exclude **/.ipynb_checkpoints/*
recursive-include resourcecode *.py
recursive-include resourcecode/data *.feather *.json
recursive-include resourcecode *.csv
+recursive-include resourcecode/config *.ini
recursive-include examples *.py
recursive-include examples *.rst
@@ -22,6 +25,7 @@ recursive-include CLA *.pdf
recursive-exclude joss_paper *
exclude joss_paper
+exclude dev_requirements.txt
prune codes_to_migrate
prune doc
diff --git a/README.md b/README.md
index 9428c3a..acd6e9b 100644
--- a/README.md
+++ b/README.md
@@ -24,58 +24,43 @@ in expected environmental conditions,and de-risk investment in future technology
## Installation
-### Dependencies
+### Requirements
-To install the toolbox, the following packages are necessary:
+- Python (>= 3.11, < 3.14)
+- pandas (>= 2.2, < 3)
+- numpy (>= 2.0, < 3)
+- scipy (>= 1.14.1, < 2)
+- xarray (>= 2024.11.0)
+- netCDF4 (>= 1.7.0, < 2)
+- And other dependencies (see `pyproject.toml` for the complete list)
-- python (>= 3.9, <3.13)
-- pandas (>= 1.0.0)
-- requests (>= 2.23.0)
-- numpy (>= 1.20.1, < 2.0.0)
-- scipy (>= 1.6.1)
-- pyextremes (>= 2.0.0)
-- pytest (>7.0.0)
-- pyarrow (>= 6.0.0)
-- plotly (>= 4.12.0)
-- numexpr (>= 2.7.0)
-- xarray (>= 0.19.0)
+### Using uv (recommended)
-
-### Using an environment
-
-Maybe the easiest way to install the toolbox is to create a dedicated virtual
-environment:
+The recommended way to install the toolbox is to use [`uv`](https://docs.astral.sh/uv/), a fast Python package installer:
```shell
-$ cd /your/work/directory
-$ python3 -m venv env-resourcecode
+$ uv pip install resourcecode
```
-then, you activate it:
+### Using pip
+
+Alternatively, you can use pip:
```shell
-$ source env-resourcecode/bin/activate
-(env-resourcecode)$
+$ python -m pip install resourcecode
```
-In this virtual environment, you can now install the library. The library is
-available on PyPI, and installation is straightforward, using the following
-command:
-
-```
-(env-resourcecode)$ python -m pip install resourcecode
-[…]
-```
+### Development installation
-To test whether the install has been successful, you can run:
+For development, clone the repository and install with all dependencies:
-```bash
-(env-resourcecode)$ python -c "import resourcecode ; print(resourcecode.__version__)"
-1.1.2
+```shell
+$ git clone https://github.com/Resourcecode-project/py-resourcecode
+$ cd py-resourcecode
+$ uv sync --all-extras --dev
+$ uv run pytest
```
-which should print the current locally installed version of `resourcecode`.
-
## Example of use
Once the library is installed and the configuration is done, you can use the
diff --git a/dev_requirements.txt b/dev_requirements.txt
deleted file mode 100644
index e079f8a..0000000
--- a/dev_requirements.txt
+++ /dev/null
@@ -1 +0,0 @@
-pytest
diff --git a/doc/conf.py b/doc/conf.py
index 076974a..051e530 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -70,9 +70,7 @@
sphinx_gallery_conf = {
"examples_dirs": "../examples", # path to your example scripts
"gallery_dirs": "auto_examples", # path to where to save gallery generated output
- "within_subsection_order": (
- sphinx_gallery.sorting.FileNameSortKey
- ), # to sort gallery examples by file name
+ "within_subsection_order": (sphinx_gallery.sorting.FileNameSortKey), # to sort gallery examples by file name
}
# Add any paths that contain templates here, relative to this directory.
diff --git a/doc/doc_installation.rst b/doc/doc_installation.rst
index ac60f06..d769024 100644
--- a/doc/doc_installation.rst
+++ b/doc/doc_installation.rst
@@ -5,7 +5,7 @@ Create a dedicated virtual environment
--------------------------------------
To install the library, you may first of all, create a dedicated virtual
-environment with a python version at least `3.9`:
+environment with a python version at least `3.11`:
.. code-block:: shell
@@ -33,7 +33,7 @@ Install the library
In this virtual environment, you can now install the library. The library is
available on PyPI, and installation is straightforward, using the following
-command :
+command :
.. code-block:: shell
@@ -46,25 +46,24 @@ To test whether the install has been successful, you can run:
.. code-block:: shell
(env-resourcecode)$ python -c "import resourcecode ; print(resourcecode.__version__)"
- 0.6.0
which should print the current locally installed version of `resourcecode`.
+Alternative installation with uv
+--------------------------------
-Known issues
-------------
+For a faster and more reliable installation, you can use `uv `_,
+a modern Python package installer:
-During the `pip install` step, you may have an error say
-
- Could not install packages due to an EnvironmentError: 404 Client Error: Not
- Found for url: https://pypi.org/simple/resourcecode/
+.. code-block:: shell
+ $ uv venv env-resourcecode --python 3.11
+ $ source env-resourcecode/bin/activate
+ (env-resourcecode)$ uv pip install resourcecode
-this is a known issue, which occurs with `pip <= 19.0`. To overcome this issue,
-you simply have to update `pip` to it latest version:
+For development, you can also use uv to sync all dependencies:
.. code-block:: shell
- (env-resourcecode)$ python -m pip install --upgrade pip
-
-and re-run the install step which should be fine.
+ $ uv sync --all-extras --dev
+ $ uv run pytest
diff --git a/examples/plot_0_Database_exploration.py b/examples/plot_0_Database_exploration.py
index d638dab..30b54ee 100644
--- a/examples/plot_0_Database_exploration.py
+++ b/examples/plot_0_Database_exploration.py
@@ -3,6 +3,7 @@
Visualize the database configuration: nodes, bathymetry...
==========================================================
"""
+
import resourcecode
import numpy as np
import matplotlib.pyplot as plot
@@ -27,9 +28,7 @@
# the requested location (in meters).
# We select the closest node from given coordinates
-selected_node = resourcecode.data.get_closest_point(
- latitude=48.3026514, longitude=-4.6861533
-)
+selected_node = resourcecode.data.get_closest_point(latitude=48.3026514, longitude=-4.6861533)
selected_node
# %%
@@ -80,9 +79,7 @@
# of code shows and example of such a map.
# Importing the data for plotting
-tri = (
- resourcecode.get_triangles().to_numpy() - 1
-) # The '-1' is due to the Zero-based numbering of python
+tri = resourcecode.get_triangles().to_numpy() - 1 # The '-1' is due to the Zero-based numbering of python
field_mesh = resourcecode.data.get_grid_field().to_numpy()
triang = mtri.Triangulation(field_mesh[:, 1], field_mesh[:, 2], tri)
diff --git a/examples/plot_1_data_extraction.py b/examples/plot_1_data_extraction.py
index 9094143..d6062de 100644
--- a/examples/plot_1_data_extraction.py
+++ b/examples/plot_1_data_extraction.py
@@ -3,6 +3,7 @@
Extract some time-series from the database and analysis
==========================================================
"""
+
import resourcecode
import resourcecode.spectrum
import matplotlib.pyplot as plot
@@ -15,14 +16,10 @@
# Below, we will look for data next to the location of interest, located in the vicinity of Brest Bay.
# We will look at the time-series data and also some spectral data
#
-selected_node = resourcecode.data.get_closest_point(
- latitude=48.3026514, longitude=-4.6861533
-)
+selected_node = resourcecode.data.get_closest_point(latitude=48.3026514, longitude=-4.6861533)
selected_node
# %%
-selected_specPoint = resourcecode.data.get_closest_station(
- latitude=48.3026514, longitude=-4.6861533
-)
+selected_specPoint = resourcecode.data.get_closest_station(latitude=48.3026514, longitude=-4.6861533)
selected_specPoint
# %%
@@ -77,9 +74,7 @@
# corresponding to the orange dots of the web portal. This is possible thanks to the `get_2D_spectrum` and
# `get_1D_spectrum` from the *spectrum* module. An example is shown below:
-spec = resourcecode.spectrum.get_2D_spectrum(
- selected_specPoint[0], years=["2010"], months=["01"]
-)
+spec = resourcecode.spectrum.get_2D_spectrum(selected_specPoint[0], years=["2010"], months=["01"])
# %%
# And we offer function to represent the spectral data, both for 2D and 1D spectrum.
@@ -97,7 +92,5 @@
# Among the functionalities of the toolbox, it is possible to compute the sea-state parameters from spectral data. Small
# discrepancies can be found between the Hindcast sea-state parameters and the one computed with the toolbox.
-parameters_df = resourcecode.spectrum.compute_parameters_from_2D_spectrum(
- spec, use_depth=True
-)
+parameters_df = resourcecode.spectrum.compute_parameters_from_2D_spectrum(spec, use_depth=True)
parameters_df.head()
diff --git a/examples/plot_2_Multivariate_Extremes.py b/examples/plot_2_Multivariate_Extremes.py
index bbd4f0c..0ce9d26 100644
--- a/examples/plot_2_Multivariate_Extremes.py
+++ b/examples/plot_2_Multivariate_Extremes.py
@@ -3,6 +3,7 @@
Modelling multivariate extremes
===============================
"""
+
# %%
# Extreme value modelling is a central topic in the design of offshore structures.
#
diff --git a/examples/plot_3_Operation_Planning.py b/examples/plot_3_Operation_Planning.py
index 2c36470..2ec1ac5 100644
--- a/examples/plot_3_Operation_Planning.py
+++ b/examples/plot_3_Operation_Planning.py
@@ -3,6 +3,7 @@
Use-case example of the Operational Planning module
===================================================
"""
+
# %%
#
# In this page, we will present some of the functionalities offered by the toolbox
@@ -34,9 +35,7 @@
#
# We have selected a location next to Ushant island, node number `36855`
-data = client.get_dataframe_from_url(
- "https://resourcecode.ifremer.fr/explore?pointId=136855", parameters=("hs", "tp")
-)
+data = client.get_dataframe_from_url("https://resourcecode.ifremer.fr/explore?pointId=136855", parameters=("hs", "tp"))
# %%
# Weather windows
@@ -69,12 +68,7 @@
windetect = ww_calc(data_matching_criteria, winlen=winlen, concurrent_windows=False)
results = wwmonstats(windetect)
-stats = (
- results.describe(percentiles=percentiles)
- .drop(["count", "std"])
- .transpose()
- .sort_index()
-)
+stats = results.describe(percentiles=percentiles).drop(["count", "std"]).transpose().sort_index()
# %%
# Plotting the monthly statistics
@@ -142,12 +136,7 @@
oplendetect = oplen_calc(data_matching_criteria, oplen, critical_operation)
results = olmonstats(oplendetect)
-stats = (
- results.describe(percentiles=percentiles)
- .drop(["count", "std"])
- .transpose()
- .sort_index()
-)
+stats = results.describe(percentiles=percentiles).drop(["count", "std"]).transpose().sort_index()
# %%
# And finally produce visual exploration of the durations.
diff --git a/examples/plot_4_Producible.py b/examples/plot_4_Producible.py
index bbe285e..1612f08 100644
--- a/examples/plot_4_Producible.py
+++ b/examples/plot_4_Producible.py
@@ -7,6 +7,7 @@
data as an input and capture width data of a standard WEC to simulate the behaviour and estimate
energy that can be harvested with this device from the slected location.
"""
+
# %%
# .. seealso::
# In addition, a demonstration tool based on this module can be accessed on
@@ -57,9 +58,7 @@
# For this example, we used the data from the SEMREVO location.
# We only need the frequency spectrum in this case, so we convert it to a pandas DataFrame.
-spec1D = resourcecode.spectrum.download_data.get_1D_spectrum(
- "SEMREVO", ["2014"], ["02"]
-)
+spec1D = resourcecode.spectrum.download_data.get_1D_spectrum("SEMREVO", ["2014"], ["02"])
spec = spec1D.ef.to_pandas()
# The frequency has been truncated, so here we reconcile both
@@ -172,9 +171,7 @@
ax=ax2,
bins=len(pto.capture_width.columns),
legend=False,
- weights=np.ones_like(pto_damp_kn[pto_damp_kn.columns[0]])
- * 100.0
- / len(pto_damp_kn),
+ weights=np.ones_like(pto_damp_kn[pto_damp_kn.columns[0]]) * 100.0 / len(pto_damp_kn),
)
ax2.grid()
ax2.set_xlabel("PTO damping (kN.s/m)")
@@ -214,9 +211,7 @@
ax=ax4,
bins=len(pto.capture_width.columns),
legend=False,
- weights=np.ones_like(pto_damp_kn[pto_damp_kn.columns[0]])
- * 100.0
- / len(pto_damp_kn),
+ weights=np.ones_like(pto_damp_kn[pto_damp_kn.columns[0]]) * 100.0 / len(pto_damp_kn),
)
ax4.grid()
ax4.set_xlabel("PTO damping (kN.s/m) - JONWSAP")
diff --git a/fp_hs.png b/fp_hs.png
index fc227fb..cf861ef 100644
Binary files a/fp_hs.png and b/fp_hs.png differ
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..e9d3355
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,110 @@
+[build-system]
+requires = ["setuptools>=77.0.3", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "resourcecode"
+dynamic = ["version"]
+description = "The ResourceCODE Marine Data Toolbox is a python package to facilitate the access to recent hindcast database of sea-state, along with a set of state-of-the-art methods for data analysis."
+readme = "README.md"
+license = {text = "GPL-3.0-or-later"}
+requires-python = ">=3.11, <3.14"
+authors = [
+ {name = "Nicolas Raillard", email = "nicolas.raillard@ifremer.fr"}
+]
+classifiers = [
+ "Development Status :: 5 - Production/Stable",
+ "Intended Audience :: Science/Research",
+ "Intended Audience :: Developers",
+ "Programming Language :: Python",
+ "Programming Language :: Python :: 3.11",
+ "Programming Language :: Python :: 3.12",
+ "Programming Language :: Python :: 3.13",
+ "Programming Language :: Python :: 3 :: Only",
+ "Operating System :: OS Independent",
+ "License :: OSI Approved :: GNU General Public License v3 (GPL-3.0-or-later)",
+ "Topic :: Scientific/Engineering",
+ "Topic :: Scientific/Engineering :: Mathematics",
+ "Topic :: Scientific/Engineering :: Physics",
+]
+keywords = [
+ "statistics",
+ "extreme",
+ "extreme value analysis",
+ "eva",
+ "coastal",
+ "ocean",
+ "marine",
+ "environmental",
+ "engineering",
+ "renewable",
+ "MRE",
+ "offshore",
+ "data",
+ "hindcast",
+]
+
+# Minimal version of dependencies are chosen to be compatible with marimo-wasm 0.23 compatible (cf
+# https://wasm.marimo.app/pyodide-lock.json?v=0.23.7)
+dependencies = [
+ "pandas>=2.2,<3",
+ "requests>=2.31.0,<3",
+ "numpy>=2.0,<3",
+ "scipy>=1.14.1,<2",
+ "pyextremes>=2.5.0,<3",
+ "pyarrow>=18.1.0,<19",
+ "plotly>=6,<7",
+ "xarray>=2024.11.0",
+ "netCDF4>=1.7.0,<2",
+]
+
+[project.urls]
+Homepage = "https://resourcecode-project.github.io/py-resourcecode/"
+GitHub = "https://github.com/Resourcecode-project/py-resourcecode"
+"Web Portal" = "https://resourcecode.ifremer.fr"
+PyPI = "https://pypi.org/project/resourcecode"
+
+[project.optional-dependencies]
+dev = [
+ "flake8>=3.6",
+ "black>=19.10b0",
+ "mypy",
+ "nbqa",
+ "check-manifest",
+ "tox",
+ "tox-uv",
+]
+doc = [
+ "sphinx>=4.5",
+ "sphinx-book-theme",
+ "sphinx_gallery",
+ "plotly",
+]
+
+[tool.setuptools.dynamic]
+version = {attr = "resourcecode.__version__.__version__"}
+
+[tool.setuptools.packages.find]
+include = ["resourcecode*"]
+
+[dependency-groups]
+dev = [
+ "flake8>=3.6",
+ "black>=19.10b0",
+ "mypy",
+ "nbqa",
+ "check-manifest",
+ "tox",
+ "tox-uv",
+ "pytest>=9.0.3",
+]
+
+[tool.black]
+line-length = 120
+target-version = ["py311", "py312", "py313"]
+
+[tool.mypy]
+python_version = "3.11"
+warn_return_any = true
+warn_unused_configs = true
+ignore_missing_imports = true
diff --git a/resourcecode/__version__.py b/resourcecode/__version__.py
index c856d37..bd425de 100644
--- a/resourcecode/__version__.py
+++ b/resourcecode/__version__.py
@@ -17,5 +17,5 @@
# You should have received a copy of the GNU General Public License along
# with Resourcecode. If not, see .
-numversion = (1, 3, 1)
+numversion = (2, 0, 0)
__version__ = ".".join(str(num) for num in numversion)
diff --git a/resourcecode/client.py b/resourcecode/client.py
index 035e331..81f26fd 100644
--- a/resourcecode/client.py
+++ b/resourcecode/client.py
@@ -114,9 +114,7 @@ def get_dataframe(
return self.get_dataframe_from_criteria(criteria)
- def get_dataframe_from_url(
- self, selection_url: str, parameters: Iterable[str] = ("hs",)
- ) -> pd.DataFrame:
+ def get_dataframe_from_url(self, selection_url: str, parameters: Iterable[str] = ("hs",)) -> pd.DataFrame:
"""Get the pandas dataframe of the data described by the url
Parameters
@@ -214,15 +212,10 @@ def get_dataframe_from_criteria(self, criteria: Union[str, dict]) -> pd.DataFram
try:
node_id = int(parsed_criteria["node"])
except ValueError: # failed to convert node to an integer
- raise BadPointIdError(
- "Point Id must be an integer, can not be "
- f"{parsed_criteria['node']!r}"
- )
+ raise BadPointIdError("Point Id must be an integer, can not be " f"{parsed_criteria['node']!r}")
else:
if node_id not in self.possible_points_id:
- raise BadPointIdError(
- f"{parsed_criteria['node']} is an unknown pointId."
- )
+ raise BadPointIdError(f"{parsed_criteria['node']} is an unknown pointId.")
# Cassandra database start indexing at 1, so decrement node
parsed_criteria["node"] = parsed_criteria["node"] - 1
@@ -305,7 +298,4 @@ def _get_rawdata_from_criteria(self, single_parameter_criteria):
if response.ok:
return response.json()
- raise ValueError(
- "Unable to get a response from the database"
- "(status code = {})".format(response.status_code)
- )
+ raise ValueError("Unable to get a response from the database" "(status code = {})".format(response.status_code))
diff --git a/resourcecode/config/config.ini b/resourcecode/config/config.ini
new file mode 100644
index 0000000..a36a074
--- /dev/null
+++ b/resourcecode/config/config.ini
@@ -0,0 +1,4 @@
+[default]
+
+cassandra-base-url = https://resourcecode-datacharts.ifremer.fr/
+min-start-date = 1994-01-01T00:00:00
diff --git a/resourcecode/eva/censgaussfit.py b/resourcecode/eva/censgaussfit.py
index 978bcee..f107687 100644
--- a/resourcecode/eva/censgaussfit.py
+++ b/resourcecode/eva/censgaussfit.py
@@ -19,7 +19,7 @@
# with Resourcecode. If not, see .
import numpy as np
-from scipy.stats import norm, mvn
+from scipy.stats import norm, multivariate_normal
from scipy.optimize import minimize, Bounds, OptimizeResult
from resourcecode.utils import set_trig
@@ -64,15 +64,17 @@ def fitness(cov):
else:
sigma = cov
- return (
- tail_dependency_obs
- - mvn.mvnun(
- means=np.zeros_like(cov),
- covar=sigma,
- lower=np.full(len(cov), th_norm),
- upper=np.full(len(cov), np.inf),
- )[0]
- ) ** 2
+ # Check if sigma is positive semi-definite
+ eigenvalues = np.linalg.eigvalsh(sigma)
+ if not np.all(eigenvalues >= -1e-10):
+ # Return a large penalty for non-PSD matrices
+ return 1e10
+
+ rv = multivariate_normal(mean=np.zeros(len(cov)), cov=sigma, allow_singular=True)
+ upper_point = np.full(len(cov), th_norm)
+ prob = 1 - rv.cdf(upper_point)
+
+ return (tail_dependency_obs - prob) ** 2
# to get the same result as R, I needed to transpose
cov0 = np.corrcoef(data.T)[np.triu_indices(data.shape[1], k=1)]
diff --git a/resourcecode/eva/huseby.py b/resourcecode/eva/huseby.py
index a51951f..344ef5a 100644
--- a/resourcecode/eva/huseby.py
+++ b/resourcecode/eva/huseby.py
@@ -79,10 +79,7 @@ def huseby(X: np.ndarray, prob: np.ndarray, ntheta: int):
Y.sort()
C[i, :] = (Y[kc] - Y[kf]) * dk + Y[kf]
- ps = (
- ctheta[:, np.newaxis] @ ctheta[:, np.newaxis].T
- + stheta[:, np.newaxis] @ stheta[:, np.newaxis].T
- )
+ ps = ctheta[:, np.newaxis] @ ctheta[:, np.newaxis].T + stheta[:, np.newaxis] @ stheta[:, np.newaxis].T
ps[ps < 0] = 0
for iprob in range(len(prob)):
@@ -99,9 +96,7 @@ def huseby(X: np.ndarray, prob: np.ndarray, ntheta: int):
if M == 3:
C = np.ones((ntheta, ntheta, len(prob)), dtype=float)
- indj = np.hstack(
- (np.arange(0, ntheta / 4 + 1), ntheta - np.arange(1, ntheta / 4 + 1))
- ).astype(int)
+ indj = np.hstack((np.arange(0, ntheta / 4 + 1), ntheta - np.arange(1, ntheta / 4 + 1))).astype(int)
nindj = ntheta / 2 + 1
ncdir = int(ntheta * nindj)
cdir = np.zeros((ncdir, M))
@@ -120,12 +115,8 @@ def huseby(X: np.ndarray, prob: np.ndarray, ntheta: int):
ps[ps < 0] = 0
a = np.arange(ntheta / 4 + 1, ntheta - ntheta / 4).astype(int)
- b = np.hstack((np.arange(ntheta / 2, ntheta), np.arange(0, ntheta / 2))).astype(
- int
- )
- c = np.hstack(
- (np.arange(ntheta / 4 - 1, -1, -1), ntheta - np.arange(1, ntheta / 4))
- ).astype(int)
+ b = np.hstack((np.arange(ntheta / 2, ntheta), np.arange(0, ntheta / 2))).astype(int)
+ c = np.hstack((np.arange(ntheta / 4 - 1, -1, -1), ntheta - np.arange(1, ntheta / 4))).astype(int)
d = ctheta[:, np.newaxis] @ ctheta[np.newaxis, indj]
e = np.repeat(stheta[indj], ntheta).reshape((-1, ntheta)).T
f = stheta[:, np.newaxis] @ ctheta[np.newaxis, indj]
@@ -159,11 +150,7 @@ def huseby(X: np.ndarray, prob: np.ndarray, ntheta: int):
+ X_mean[2]
)
- Yres[:, iprob] = (
- L[0, 1] * X_std[1] * Xres[:, iprob]
- + L[1, 1] * X_std[1] * Yres[:, iprob]
- + X_mean[1]
- )
+ Yres[:, iprob] = L[0, 1] * X_std[1] * Xres[:, iprob] + L[1, 1] * X_std[1] * Yres[:, iprob] + X_mean[1]
Xres[:, iprob] = L[0, 0] * X_std[0] * Xres[:, iprob] + X_mean[0]
diff --git a/resourcecode/io.py b/resourcecode/io.py
index 20f9517..293f064 100644
--- a/resourcecode/io.py
+++ b/resourcecode/io.py
@@ -38,9 +38,7 @@
NETCFD_DESCRIPTION = json.load(fobj)
-def to_netcdf(
- dataframe: pd.DataFrame, path: Union[str, Path, None] = None
-) -> Union[bytes, "Delayed", None]:
+def to_netcdf(dataframe: pd.DataFrame, path: Union[str, Path, None] = None) -> Union[bytes, "Delayed", None]:
"""Write dataframe contents to a netCFD file.
Parameters
@@ -84,9 +82,7 @@ def to_mat(
"""
- df = dataframe.reset_index(
- names="time"
- ) # convert the pandas index to a proper variable
+ df = dataframe.reset_index(names="time") # convert the pandas index to a proper variable
df.time = 719529 + pd.to_numeric(df.time) / (
3600 * 1e9 * 24
) # 1970-01-01 + time in fractional days from nanoseconds
diff --git a/resourcecode/opsplanning/__init__.py b/resourcecode/opsplanning/__init__.py
index ede33ef..424b6a8 100644
--- a/resourcecode/opsplanning/__init__.py
+++ b/resourcecode/opsplanning/__init__.py
@@ -56,6 +56,7 @@
@author: david.darbinyan
"""
+
from itertools import product
import pandas as pd
@@ -92,9 +93,7 @@ def _get_timestep(data: pd.DataFrame) -> pd.Timedelta:
return tstep
-def ww_calc(
- critsubs: pd.DataFrame, winlen: float, concurrent_windows: bool = True
-) -> pd.Series:
+def ww_calc(critsubs: pd.DataFrame, winlen: float, concurrent_windows: bool = True) -> pd.Series:
"""
Method that calculates and returns start date of each weather window
@@ -127,9 +126,7 @@ def ww_calc(
strtwin = critsubs.index.values[k]
thistime = strtwin
nexttime = critsubs.index.values[k + 1]
- while pd.Timedelta(nexttime - thistime) <= tstep and k < (
- critsubs.shape[0] - 2
- ):
+ while pd.Timedelta(nexttime - thistime) <= tstep and k < (critsubs.shape[0] - 2):
k += 1
if pd.Timedelta(nexttime - strtwin) >= dt.timedelta(seconds=3600 * winlen):
windetect.append(strtwin)
@@ -202,10 +199,7 @@ def oplen_calc(critsubs, oplen, critical_operation=False, date=1, monstrt=True):
elif isinstance(date, int) and date >= 1:
dayval = date
else:
- msg = (
- "Variable date in monthly results calculation should be"
- " positive integer or datetime object"
- )
+ msg = "Variable date in monthly results calculation should be" " positive integer or datetime object"
raise NameError(msg)
yerng = [min(critsubs.index).year, max(critsubs.index).year]
morng = [min(critsubs.index).month, max(critsubs.index).month]
@@ -215,20 +209,13 @@ def oplen_calc(critsubs, oplen, critical_operation=False, date=1, monstrt=True):
freq="MS",
)
daterng = daterng.shift(dayval - 1, freq="D")
- oplendetect = pd.Series(
- np.zeros(daterng.shape[0], dtype="timedelta64[s]"), index=daterng
- )
+ oplendetect = pd.Series(np.zeros(daterng.shape[0], dtype="timedelta64[s]"), index=daterng)
elif monstrt is False:
if isinstance(date, dt.datetime):
daterng = pd.date_range(start=date, end=date)
- oplendetect = pd.Series(
- np.zeros(daterng.shape[0], dtype="timedelta64[s]"), index=daterng
- )
+ oplendetect = pd.Series(np.zeros(daterng.shape[0], dtype="timedelta64[s]"), index=daterng)
else:
- msg = (
- "Variable date in single result calculation should be"
- " a datetime object"
- )
+ msg = "Variable date in single result calculation should be" " a datetime object"
raise NameError(msg)
else:
raise NameError("Input option monstrt should be boolean")
@@ -284,9 +271,7 @@ def wwmonstats(windetect):
yeun = windetect.dt.year.unique()
moun = windetect.dt.month.unique()
yeun.sort()
- wwmonres = pd.DataFrame(
- np.zeros([yeun.shape[0], moun.shape[0]]), columns=moun, index=yeun
- )
+ wwmonres = pd.DataFrame(np.zeros([yeun.shape[0], moun.shape[0]]), columns=moun, index=yeun)
for ye, mo in product(yeun, moun):
subs = windetect[(windetect.dt.year == ye) & (windetect.dt.month == mo)]
@@ -318,12 +303,8 @@ def olmonstats(oplendetect):
moun.sort()
yeun.sort()
- olmonres = pd.DataFrame(
- np.zeros([yeun.shape[0], moun.shape[0]]), columns=moun, index=yeun
- )
+ olmonres = pd.DataFrame(np.zeros([yeun.shape[0], moun.shape[0]]), columns=moun, index=yeun)
for ye, mo in product(yeun, moun):
- subs = oplendetect[
- (oplendetect.index.year == ye) & (oplendetect.index.month == mo)
- ]
+ subs = oplendetect[(oplendetect.index.year == ye) & (oplendetect.index.month == mo)]
olmonres.at[ye, mo] = subs[0].days * 24 + subs[0].seconds / 3600
return olmonres
diff --git a/resourcecode/producible_assessment/main.py b/resourcecode/producible_assessment/main.py
index 854be06..4b800e7 100644
--- a/resourcecode/producible_assessment/main.py
+++ b/resourcecode/producible_assessment/main.py
@@ -40,25 +40,19 @@ def __init__(self, capture_width, s):
self.times = s.index # time vector
self.freqs = s.columns # frequency vector
# time domain data
- self.power = pd.DataFrame(
- np.zeros(len(self.times)), index=self.times
- ) # absorbed power (W)
+ self.power = pd.DataFrame(np.zeros(len(self.times)), index=self.times) # absorbed power (W)
# absorbed power, no reduction (W)
self.power_no_red = pd.DataFrame(np.zeros(len(self.times)), index=self.times)
self.mean_power = None # mean absorbed power (W)
self.mean_power_no_red = None # mean absorbed power, no reduction (W)
self.median_power = None # median absorbed power (W)
self.median_power_no_red = None # median absorbed power, no reduction (W)
- self.pto_damp = pd.DataFrame(
- np.zeros(len(self.times)), index=self.times
- ) # PTO damping (Ns/m)
+ self.pto_damp = pd.DataFrame(np.zeros(len(self.times)), index=self.times) # PTO damping (Ns/m)
# PTO damping, no reduction (Ns/m)
self.pto_damp_no_red = pd.DataFrame(np.zeros(len(self.times)), index=self.times)
self.cumulative_power = None # cumulative power (W)
# frequency domain data
- self.freq_data = (
- None # contains Hs, Tp, absorbed power and PTO damping in frequency domain
- )
+ self.freq_data = None # contains Hs, Tp, absorbed power and PTO damping in frequency domain
# interpolate frequencies (if needed) to match sea-state and PTO capture width data
self.interp_freq()
# power computation
@@ -95,9 +89,7 @@ def interp_freq(self):
continue
known_freqs.add(freq)
- self.capture_width = self.capture_width.append(
- pd.Series(name=freq, dtype="float64")
- )
+ self.capture_width = self.capture_width.append(pd.Series(name=freq, dtype="float64"))
self.capture_width.sort_index(inplace=True)
self.capture_width = self.capture_width.interpolate()
@@ -133,7 +125,7 @@ def get_power_pto_damp(self):
power_t = pd.DataFrame(
(
(self.rho * self.g * self.width)
- * np.trapz(
+ * np.trapezoid(
(((c_g * s).to_numpy())[:, np.newaxis] * self.capture_width).T,
x=self.freqs,
)
@@ -164,7 +156,7 @@ def get_power_pto_damp(self):
tp_list.append(tp)
self.wave_power = pd.DataFrame(
- self.rho * self.g * self.width * np.trapz(c_g * self.s, x=self.freqs),
+ self.rho * self.g * self.width * np.trapezoid(c_g * self.s, x=self.freqs),
index=self.times,
) # incident wave power (W)
@@ -176,16 +168,12 @@ def get_power_pto_damp(self):
"PTO damping": self.pto_damp.values.flatten(),
}
)
- self.mean_power = pd.DataFrame(
- data=self.power.mean()[0] * np.ones(len(self.times)), index=self.times
- )
+ self.mean_power = pd.DataFrame(data=self.power.mean()[0] * np.ones(len(self.times)), index=self.times)
self.mean_power_no_red = pd.DataFrame(
data=self.power_no_red.mean()[0] * np.ones(len(self.times)),
index=self.times,
)
- self.median_power = pd.DataFrame(
- data=self.power.median()[0] * np.ones(len(self.times)), index=self.times
- )
+ self.median_power = pd.DataFrame(data=self.power.median()[0] * np.ones(len(self.times)), index=self.times)
self.median_power_no_red = pd.DataFrame(
data=self.power_no_red.median()[0] * np.ones(len(self.times)),
index=self.times,
@@ -195,9 +183,7 @@ def get_cumulative_power(self):
"""Compute PTO cumulative power"""
power_ordered = self.power.sort_values(by=0)
- self.cumulative_power = pd.DataFrame(
- data=100 * power_ordered.cumsum() / power_ordered.sum()
- )
+ self.cumulative_power = pd.DataFrame(data=100 * power_ordered.cumsum() / power_ordered.sum())
@staticmethod
def compute_spectrum_moment(f, s, n=0):
@@ -219,7 +205,7 @@ def compute_spectrum_moment(f, s, n=0):
s0 = np.interp(f0, f, s)
fn = np.power(f0, n)
- mn = np.trapz(s0 * fn, x=f0)
+ mn = np.trapezoid(s0 * fn, x=f0)
return mn
diff --git a/resourcecode/resassess/__init__.py b/resourcecode/resassess/__init__.py
index 0ccdf82..895f9ca 100644
--- a/resourcecode/resassess/__init__.py
+++ b/resourcecode/resassess/__init__.py
@@ -36,6 +36,7 @@
@author: david.darbinyan
"""
+
from pathlib import Path
from typing import Tuple
@@ -45,7 +46,6 @@
import plotly.express as px
import plotly.graph_objects as go
-
pd.options.plotting.backend = "plotly"
@@ -71,9 +71,7 @@ def exceed(df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]:
return datasrt, exceedance
-def univar_monstats(
- df: pd.DataFrame, varnm: str
-) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
+def univar_monstats(df: pd.DataFrame, varnm: str) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
"""
Method to calculate univariate statistics for any input variable. Used in
resource assessment to produce deliverables as per IEC
@@ -101,10 +99,7 @@ def univar_monstats(
"""
if varnm not in df.columns:
existing_col = ", ".join(sorted(df.columns))
- raise NameError(
- f"Parameter {varnm} is not in the dataframe. "
- f"Possible values are: {existing_col}"
- )
+ raise NameError(f"Parameter {varnm} is not in the dataframe. " f"Possible values are: {existing_col}")
# sort rows according to the variable selected
sorted_df = df[[varnm]].sort_values(by=varnm)
sorted_df.index = pd.to_datetime(df.index, format="%d/%m/%Y %H:%M")
@@ -113,9 +108,7 @@ def univar_monstats(
sorted_df["month_index"] = sorted_df.index.month
sorted_df["month"] = sorted_df.index.month_name()
sorted_df["year"] = sorted_df.index.year
- sorted_df["Exceedance"] = sorted_df.groupby("month")[varnm].rank(
- method="min", pct=True
- )
+ sorted_df["Exceedance"] = sorted_df.groupby("month")[varnm].rank(method="min", pct=True)
res = [sorted_df]
diff --git a/resourcecode/spectrum/compute_parameters.py b/resourcecode/spectrum/compute_parameters.py
index 581949e..19ae022 100644
--- a/resourcecode/spectrum/compute_parameters.py
+++ b/resourcecode/spectrum/compute_parameters.py
@@ -141,19 +141,19 @@ def raw_compute_parameters_from_1D_spectrum(
raise ValueError("Depth must be positive")
# Total energy
- M0 = np.trapz(Ef, x=freq)
+ M0 = np.trapezoid(Ef, x=freq)
# Significant Wave Height
Hm0 = 4 * np.sqrt(M0)
# Periods
- M01 = np.trapz(freq * Ef, x=freq)
+ M01 = np.trapezoid(freq * Ef, x=freq)
T01 = M0 / M01
- M02 = np.trapz(freq**2 * Ef, x=freq)
+ M02 = np.trapezoid(freq**2 * Ef, x=freq)
T02 = np.sqrt(M0 / M02)
- Me = np.trapz(Ef / freq, x=freq)
+ Me = np.trapezoid(Ef / freq, x=freq)
Te = Me / M0
# fp evaluaton using spline fitting around Ef peak
@@ -171,7 +171,7 @@ def raw_compute_parameters_from_1D_spectrum(
k = dispersion(freq, depth, n_iter=200, tol=1e-6)
kd = k * depth
- km = np.trapz(k * Ef, x=freq) / M0
+ km = np.trapezoid(k * Ef, x=freq) / M0
lm = 2 * np.pi / km
# Group velocity
@@ -180,7 +180,7 @@ def raw_compute_parameters_from_1D_spectrum(
cg = 0.5 * c1 * c2
# Energy flux
- cgef = np.trapz(cg * Ef, x=freq)
+ cgef = np.trapezoid(cg * Ef, x=freq)
CgE = water_density * g * cgef / 1000
return SeaStatesParameters(
@@ -244,7 +244,7 @@ def raw_compute_parameters_from_2D_spectrum(
kd = k * depth
if not np.isfinite(depth):
- c1 = 1
+ c1 = np.ones_like(kd)
else:
c1 = 1 + 2 * kd / np.sinh(2 * kd)
@@ -252,37 +252,37 @@ def raw_compute_parameters_from_2D_spectrum(
cg = 0.5 * c1 * c2
# Energy flux
- cgef = np.trapz(cg[:, np.newaxis] * E.T, x=vdir, axis=1)
- parameters.CgE = water_density * g * np.trapz(cgef, x=freq) / 1000
+ cgef = np.trapezoid(cg[:, np.newaxis] * E.T, x=vdir, axis=1)
+ parameters.CgE = water_density * g * np.trapezoid(cgef, x=freq) / 1000
# compute direction from (°)
aa = (E.T * np.cos(vdir)).T
bb = (E.T * np.sin(vdir)).T
- af = np.trapz(aa, x=vdir, axis=0)
- am = np.trapz(af, x=freq)
+ af = np.trapezoid(aa, x=vdir, axis=0)
+ am = np.trapezoid(af, x=freq)
- bf = np.trapz(bb, x=vdir, axis=0)
- bm = np.trapz(bf, x=freq)
+ bf = np.trapezoid(bb, x=vdir, axis=0)
+ bm = np.trapezoid(bf, x=freq)
Thetam = (np.arctan2(bm, am) * 180 / np.pi) % 360
Spr = np.sqrt(2 * (1 - np.sqrt((am**2 + bm**2) / M0**2)))
Spr = (Spr * 180 / np.pi) % 360
- iEfm = np.trapz(E, x=vdir, axis=0).argmax()
+ iEfm = np.trapezoid(E, x=vdir, axis=0).argmax()
aap = E[:, iEfm] * np.cos(vdir)
- apm = np.trapz(aap, x=vdir)
+ apm = np.trapezoid(aap, x=vdir)
bbp = E[:, iEfm] * np.sin(vdir)
- bpm = np.trapz(bbp, x=vdir)
+ bpm = np.trapezoid(bbp, x=vdir)
# Mean direction at peak frequency
Thetapm = (np.arctan2(bpm, apm) * 180 / np.pi) % 360
S2 = E**2
- Qpf = np.trapz((S2 * freq).T, x=vdir)
- MQ = np.trapz(Qpf, x=freq)
+ Qpf = np.trapezoid((S2 * freq).T, x=vdir)
+ MQ = np.trapezoid(Qpf, x=freq)
Qp = 2 * MQ / (M0**2)
diff --git a/resourcecode/spectrum/convert2D1D.py b/resourcecode/spectrum/convert2D1D.py
index 0e9575c..893df16 100644
--- a/resourcecode/spectrum/convert2D1D.py
+++ b/resourcecode/spectrum/convert2D1D.py
@@ -22,9 +22,7 @@
import xarray
-def raw_convert_spectrum_2Dto1D(
- spectrum_2D: np.ndarray, vdir: np.ndarray
-) -> np.ndarray:
+def raw_convert_spectrum_2Dto1D(spectrum_2D: np.ndarray, vdir: np.ndarray) -> np.ndarray:
"""
Converts the 2D spectrum to a 1D spectrum
@@ -46,7 +44,7 @@ def raw_convert_spectrum_2Dto1D(
vd = ((vdir + 180) % 360 * np.pi) / 180
ivd = vd.argsort()
- return np.trapz(spectrum_2D[ivd, :], x=vd[ivd], axis=0)
+ return np.trapezoid(spectrum_2D[ivd, :], x=vd[ivd], axis=0)
def convert_spectrum_2Dto1D(spectrumDataSet: xarray.Dataset) -> xarray.Dataset:
diff --git a/resourcecode/spectrum/download_data.py b/resourcecode/spectrum/download_data.py
index 63b2ccb..13ae3ef 100644
--- a/resourcecode/spectrum/download_data.py
+++ b/resourcecode/spectrum/download_data.py
@@ -22,6 +22,7 @@
import tempfile
import urllib.request
import xarray
+import numpy as np
from typing import Iterable
import contextlib
@@ -53,26 +54,12 @@ def download_single_2D_file(
A dataset object with the data read from the downloaded netCDF file.
"""
base = "ftp://ftp.ifremer.fr/ifremer/dataref/ww3/resourcecode/HINDCAST/"
- url = (
- base
- + year
- + "/"
- + month
- + "/SPEC_NC/RSCD_WW3-RSCD-UG-"
- + point
- + "_"
- + year
- + month
- + "_spec.nc"
- )
+ url = base + year + "/" + month + "/SPEC_NC/RSCD_WW3-RSCD-UG-" + point + "_" + year + month + "_spec.nc"
if point not in set(get_grid_spec().name):
raise ValueError(f"{point} is an unkown location")
- if (
- int(year) < get_covered_period()["start"].year
- or int(year) > get_covered_period()["end"].year
- ):
+ if int(year) < get_covered_period()["start"].year or int(year) > get_covered_period()["end"].year:
raise ValueError(f"{year} is outsite the covered period")
if int(month) < 1 or int(month) > 12:
@@ -81,12 +68,19 @@ def download_single_2D_file(
with contextlib.closing(urllib.request.urlopen(url)) as response:
with tempfile.NamedTemporaryFile(delete=False, suffix=".nc") as tmp_file:
shutil.copyfileobj(response, tmp_file)
- with xarray.open_dataset(tmp_file.name) as ds:
+ with xarray.open_dataset(tmp_file.name, decode_cf=False) as ds:
# Remove the 'string40' dimension which is not very indicative
ds = ds.drop_dims("string40").squeeze()
# Convert the log-spectrum to the actual value
- # the value is already scaled internally by xarray so we do not need the scale factor of 0.004
- ds = ds.assign(Ef=pow(10, ds["efth"]) - 1e-12)
+ # Manually apply scale_factor and add_offset to avoid xarray segfault
+ # This affects xarray >= 2024.x with numpy 2.x where CF decoding can cause
+ # segfaults when applying scale_factor/add_offset on certain NetCDF files.
+ efth_encoded = ds["efth"]
+ scale_factor = ds["efth"].encoding.get("scale_factor", 1.0)
+ add_offset = ds["efth"].encoding.get("add_offset", 0.0)
+ efth_decoded = efth_encoded * scale_factor + add_offset
+ # Compute Ef using numpy to avoid xarray segfault with CF decoding
+ ds = ds.assign(Ef=np.power(10.0, efth_decoded) - 1e-12)
ds = ds.drop_vars(["efth", "station"])
# We sort the direction to start at 0
ds = ds.sortby("direction")
@@ -117,32 +111,16 @@ def download_single_1D_file(
A dataset object with the data read from the downloaded netCDF file.
"""
base = "ftp://ftp.ifremer.fr/ifremer/dataref/ww3/resourcecode/HINDCAST/"
- url = (
- base
- + year
- + "/"
- + month
- + "/FREQ_NC/RSCD_WW3-RSCD-UG-"
- + point
- + "_"
- + year
- + month
- + "_freq.nc"
- )
+ url = base + year + "/" + month + "/FREQ_NC/RSCD_WW3-RSCD-UG-" + point + "_" + year + month + "_freq.nc"
if point not in set(get_grid_spec().name):
raise ValueError(f"{point} is an unkown location")
- if (
- int(year) < get_covered_period()["start"].year
- or int(year) > get_covered_period()["end"].year
- ):
+ if int(year) < get_covered_period()["start"].year or int(year) > get_covered_period()["end"].year:
raise ValueError(f"{year} is outsite the covered period")
if int(month) < 1 or int(month) > 12:
- raise ValueError(
- f"{month} must by between 1 and 12 with a leading zero if needed."
- )
+ raise ValueError(f"{month} must by between 1 and 12 with a leading zero if needed.")
with contextlib.closing(urllib.request.urlopen(url)) as response:
with tempfile.NamedTemporaryFile(delete=False, suffix=".nc") as tmp_file:
diff --git a/resourcecode/spectrum/jonswap.py b/resourcecode/spectrum/jonswap.py
index e74c88d..b14fb40 100644
--- a/resourcecode/spectrum/jonswap.py
+++ b/resourcecode/spectrum/jonswap.py
@@ -20,7 +20,6 @@
import numpy as np
import pandas as pd
-import numexpr as ne
def jonswap(hs: float, tp: float, gamma: float, freq: np.ndarray) -> np.ndarray:
@@ -44,30 +43,20 @@ def jonswap(hs: float, tp: float, gamma: float, freq: np.ndarray) -> np.ndarray:
out: vector containing the spectrum on input freq
"""
- freq = freq[freq > 0]
-
- expr = (
- "5"
- "/ (16 * freq ** 5)"
- "* (hs ** 2)"
- "/ (tp ** 4)"
- "* exp(-5.0 / (4 * tp ** 4) /(freq ** 4))"
- "* gamma ** ("
- " exp("
- " -((freq - 1 / tp) ** 2)"
- " * (tp ** 2)"
- " / (2 * (where(freq < (1.0 / tp), 0.07, 0.09) ** 2))"
- " )"
- ")"
+
+ sf = (
+ 5
+ / (16 * freq**5)
+ * (hs**2)
+ / (tp**4)
+ * np.exp(-5.0 / (4 * tp**4) / (freq**4))
+ * gamma ** (np.exp(-((freq - 1 / tp) ** 2) * (tp**2) / (2 * (np.where(freq < (1.0 / tp), 0.07, 0.09) ** 2))))
)
- sf = ne.evaluate(expr)
- alpha = (hs**2) / (16 * np.trapz(sf, x=freq))
+ alpha = (hs**2) / (16 * np.trapezoid(sf, x=freq))
return alpha * sf
-def compute_jonswap_wave_spectrum(
- seastate_data: pd.DataFrame, freq: np.ndarray, gamma: float = 1
-) -> pd.DataFrame:
+def compute_jonswap_wave_spectrum(seastate_data: pd.DataFrame, freq: np.ndarray, gamma: float = 1) -> pd.DataFrame:
"""Computes JONSWAP wave spectrum time series from Hs and Tp time series
Parameters
diff --git a/resourcecode/spectrum/plots.py b/resourcecode/spectrum/plots.py
index 91b9237..3b1cc92 100644
--- a/resourcecode/spectrum/plots.py
+++ b/resourcecode/spectrum/plots.py
@@ -100,7 +100,7 @@ def plot_2D_spectrum(
f"Mean direction at Tp: {params.Thetapm:.2f}°",
f"Directionnal spreading: {params.Spr:.2f}°",
f"Wind speed: {float(data.wnd[time]):.2f}m/s",
- f"\u27F6, wind direction: {float(data.wnddir[time]):.2f}°",
+ f"\u27f6, wind direction: {float(data.wnddir[time]):.2f}°",
]
)
diff --git a/resourcecode/utils.py b/resourcecode/utils.py
index ec7edb3..2f4af0e 100644
--- a/resourcecode/utils.py
+++ b/resourcecode/utils.py
@@ -33,6 +33,7 @@
"./resourcecode.ini",
"~/.config/resourcecode.ini",
f"{sys.prefix}/etc/resourcecode/config.ini",
+ Path(__file__).parent / "config" / "config.ini",
]
LOGGER = logging.getLogger("resourcecode.default")
diff --git a/resourcecode/weatherwindow/__init__.py b/resourcecode/weatherwindow/__init__.py
index 15f4754..dd51aa1 100644
--- a/resourcecode/weatherwindow/__init__.py
+++ b/resourcecode/weatherwindow/__init__.py
@@ -24,7 +24,6 @@
@author: Christophe Maisondieu
"""
-
from resourcecode.weatherwindow.weatherwindow import (
compute_weather_windows,
fit_weibull_distribution,
diff --git a/resourcecode/weatherwindow/weatherwindow.py b/resourcecode/weatherwindow/weatherwindow.py
index 2ad2d09..1bf92cb 100644
--- a/resourcecode/weatherwindow/weatherwindow.py
+++ b/resourcecode/weatherwindow/weatherwindow.py
@@ -240,7 +240,7 @@ def fit_weibull_distribution(hs: pd.Series) -> WeibullDistributionResult:
x0 = x0 + dx
X = np.log(bins - x0)
- ([p0, p1], [residual], _, _, _) = np.polyfit(X, Y, 1, full=True)
+ [p0, p1], [residual], _, _, _ = np.polyfit(X, Y, 1, full=True)
if residual <= previous_residual:
# SC: in my opinion, we should update k and b, and then break if the
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 4716ad8..0000000
--- a/setup.py
+++ /dev/null
@@ -1,109 +0,0 @@
-# coding: utf-8
-
-# Copyright 2020-2023 IFREMER (Brest, FRANCE), all rights reserved.
-# contact -- mailto:nicolas.raillard@ifremer.fr
-#
-# This file is part of Resourcecode.
-#
-# Resourcecode is free software: you can redistribute it and/or modify it under
-# the terms of the GNU General Public License as published by the Free
-# Software Foundation, either version 3.0 of the License, or any later version.
-#
-# Resourcecode is distributed in the hope that it will be useful, but WITHOUT
-# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
-# details.
-#
-# You should have received a copy of the GNU General Public License along
-# with Resourcecode. If not, see .
-
-from pathlib import Path
-from setuptools import find_packages, setup
-
-HERE = Path(__file__).parent
-
-version_context = {}
-with open(HERE / "resourcecode" / "__version__.py") as f:
- exec(f.read(), version_context)
-
-author = "Nicolas Raillard (IFREMER, Brest)"
-author_email = "nicolas.raillard@ifremer.fr"
-__version__ = version_context["__version__"]
-
-description = "The ResourceCODE Marine Data Toolbox is a python package to facilitate the\
- access to recent hindcast database of sea-state , along with a set of state-of-the-art methods for data analysis."
-url = "https://resourcecode-project.github.io/py-resourcecode/"
-license = "GPL-v3.0"
-
-install_requires = [
- "pandas >= 1.0.0, < 3.0.0",
- "requests >= 2.23.0",
- "numpy >= 1.20.1, < 2.0.0",
- "scipy >= 1.6.1, < 1.14.0",
- "pyextremes >= 2.0.0",
- "pytest >= 7.0.0",
- "pyarrow >= 6.0.0",
- "plotly >= 4.12.0",
- "numexpr >= 2.7.0",
- "xarray >= 0.19.0",
- "netCDF4 >= 1.6.0",
-]
-
-classifiers = [
- "Development Status :: 5 - Production/Stable",
- "Intended Audience :: Science/Research",
- "Intended Audience :: Developers",
- "Programming Language :: Python",
- "Programming Language :: Python :: 3.9",
- "Programming Language :: Python :: 3.10",
- "Programming Language :: Python :: 3.11",
- "Programming Language :: Python :: 3.12",
- "Programming Language :: Python :: 3 :: Only",
- "Operating System :: OS Independent",
- "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
- "Topic :: Scientific/Engineering",
- "Topic :: Scientific/Engineering :: Mathematics",
- "Topic :: Scientific/Engineering :: Physics",
-]
-
-keywords = [
- "statistics",
- "extreme",
- "extreme value analysis",
- "eva",
- "coastal",
- "ocean",
- "marine",
- "environmental",
- "engineering",
- "renewable",
- "MRE",
- "offshore",
- "data",
- "hindcast",
-]
-
-setup(
- name="resourcecode",
- version=__version__,
- license=license,
- python_requires=">=3.9, <3.13",
- description=description,
- author=author,
- author_email=author_email,
- long_description=open("README.md", "r").read(),
- long_description_content_type="text/markdown",
- install_requires=install_requires,
- classifiers=classifiers,
- keywords=keywords,
- url=url,
- packages=find_packages(exclude=["test"]),
- data_files=[("etc/resourcecode", ["config/config.ini"])],
- include_package_data=True,
- zip_safe=False,
- project_urls={
- "GitHub": "https://github.com/Resourcecode-project/py-resourcecode",
- "Web Portal": "https://resourcecode.ifremer.fr",
- "PyPI": "https://pypi.org/project/resourcecode",
- },
-)
diff --git a/tests/conftest.py b/tests/conftest.py
new file mode 100644
index 0000000..472c5ea
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,27 @@
+# coding: utf-8
+
+# Copyright 2020-2026 IFREMER (Brest, FRANCE), all rights reserved.
+# contact -- mailto:nicolas.raillard@ifremer.fr
+#
+# This file is part of Resourcecode.
+#
+# Resourcecode is free software: you can redistribute it and/or modify it under
+# the terms of the GNU General Public License as published by the Free
+# Software Foundation, either version 3.0 of the License, or any later version.
+#
+# Resourcecode is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
+# details.
+#
+# You should have received a copy of the GNU General Public License along
+# with Resourcecode. If not, see .
+
+import numpy as np
+import pytest
+
+
+@pytest.fixture(autouse=True)
+def set_random_seed():
+ """Set random seed for reproducibility across all tests"""
+ np.random.seed(42)
diff --git a/tests/test_client.py b/tests/test_client.py
index 6a42224..901f74a 100644
--- a/tests/test_client.py
+++ b/tests/test_client.py
@@ -60,9 +60,7 @@ def mock_requests_get_raw_data(query_url, parameters):
for date, value in data["result"]["data"]:
# start_date and end_date must be multiplied by 1e3, because
# cassandra returns milliseconds
- if date is not None and (
- start_date is not None and date < start_date * 1e3
- ):
+ if date is not None and (start_date is not None and date < start_date * 1e3):
continue
if date and end_date is not None and date > end_date * 1e3:
@@ -139,9 +137,7 @@ def test_get_raw_data():
parameter = "fp"
client = resourcecode.Client()
- with mock.patch(
- "requests.get", side_effect=mock_requests_get_raw_data
- ) as mock_requests_get:
+ with mock.patch("requests.get", side_effect=mock_requests_get_raw_data) as mock_requests_get:
json_data = client._get_rawdata_from_criteria(
{
"parameter": [
@@ -150,9 +146,7 @@ def test_get_raw_data():
}
)
- mock_requests_get.assert_called_once_with(
- client.cassandra_base_url + "api/timeseries", {"parameter": [parameter]}
- )
+ mock_requests_get.assert_called_once_with(client.cassandra_base_url + "api/timeseries", {"parameter": [parameter]})
assert json_data["query"]["parameterCode"] == parameter
dataset_size = json_data["result"]["dataSetSize"]
diff --git a/tests/test_resassess.py b/tests/test_resassess.py
index b7864dc..fca8a99 100644
--- a/tests/test_resassess.py
+++ b/tests/test_resassess.py
@@ -36,14 +36,14 @@ def data():
return df
-def test_exceed():
+def test_exceed(data):
data = pd.Series(np.arange(1, 5))
sorted_data, exceedance = exceed(data)
np.testing.assert_array_equal(sorted_data.values, np.arange(4, 0, -1))
np.testing.assert_array_equal(exceedance, [0.75, 0.5, 0.25, 0.0])
-def test_bivar_stats_missing_column():
+def test_bivar_stats_missing_column(data):
data = pd.DataFrame()
with pytest.raises(NameError) as e:
bivar_stats(data)
@@ -55,7 +55,7 @@ def test_bivar_stats_missing_column():
assert e.match("Crucial parameter missing: t0m1")
-def test_univar_monstats_missing_columns():
+def test_univar_monstats_missing_columns(data):
data = pd.DataFrame({"toto": []})
with pytest.raises(NameError) as e:
univar_monstats(data, "hs")
@@ -81,21 +81,21 @@ def test_bivar_stats(data):
def test_univar_monstats(data):
- exceed, dtm, dty = univar_monstats(data, "hs")
+ _exceed, dtm, dty = univar_monstats(data, "hs")
stored_results = ("monthly_stat.csv", "yearly_stat.csv")
for result, expected_result_path in zip((dtm, dty), stored_results):
path = DATA_DIR / "resassess" / expected_result_path
- expected_result = pd.read_csv(path, index_col=0)
- expected_result = expected_result.astype(
- {col: "int32" for col in expected_result.select_dtypes("int64").columns}
- )
- # count is the first column returned by 'describe()'
+ expected_result = pd.read_csv(path, index_col=0, dtype={"month_index": np.int32})
+ # count is the first column return by describe
count_index = result.columns.get_loc("count")
# Check the first columns that could either be int (month_index, year) or
# string (month)
- assert result.iloc[:, :count_index].equals(
- expected_result.iloc[:, :count_index]
+ # Use check_dtype=False to handle int32 vs int64 differences
+ pd.testing.assert_frame_equal(
+ result.iloc[:, :count_index],
+ expected_result.iloc[:, :count_index],
+ check_dtype=False,
)
# Check the remaining columns (floats) using numpy
np.testing.assert_allclose(
diff --git a/tests/test_spectrum.py b/tests/test_spectrum.py
index 129483a..0947c71 100644
--- a/tests/test_spectrum.py
+++ b/tests/test_spectrum.py
@@ -51,9 +51,7 @@ def test_compute_parameter_1D():
depth = float(np.loadtxt(DATA_DIR / "spectrum" / "depth.csv", delimiter=","))
etfh = np.loadtxt(DATA_DIR / "spectrum" / "Etfh.csv", delimiter=",")
- expected_parameters = SeaStatesParameters(
- *np.loadtxt(DATA_DIR / "spectrum" / "parameters_1D.csv", delimiter=",")
- )
+ expected_parameters = SeaStatesParameters(*np.loadtxt(DATA_DIR / "spectrum" / "parameters_1D.csv", delimiter=","))
got_parameters = raw_compute_parameters_from_1D_spectrum(etfh, freq, depth)
assert got_parameters.approx(expected_parameters)
@@ -65,21 +63,28 @@ def test_compute_parameter_2D():
vdir = np.loadtxt(DATA_DIR / "spectrum" / "dir.csv", delimiter=",")
depth = float(np.loadtxt(DATA_DIR / "spectrum" / "depth.csv", delimiter=","))
- expected_parameters = SeaStatesParameters(
- *np.loadtxt(DATA_DIR / "spectrum" / "parameters_2D.csv", delimiter=",")
- )
+ expected_parameters = SeaStatesParameters(*np.loadtxt(DATA_DIR / "spectrum" / "parameters_2D.csv", delimiter=","))
got_parameters = raw_compute_parameters_from_2D_spectrum(spec, freq, vdir, depth)
assert got_parameters.approx(expected_parameters)
def test_download_2D_file():
+ # Use decode_cf=False to avoid xarray segfault with scale_factor/add_offset
+ # This is a workaround for xarray >= 2024.x with numpy 2.x where applying
+ # CF conventions (scale_factor, add_offset) causes a segfault in some cases.
+ # See, probably related to https://github.com/pydata/xarray/issues/11205 / numpy / xarray and
+ # python 3.14
expected_spectrum = xarray.open_dataset(
- DATA_DIR / "spectrum" / "W001933N55743_201605.nc"
- )
- expected_spectrum = expected_spectrum.assign(
- Ef=pow(10, expected_spectrum["efth"]) - 1e-12
+ DATA_DIR / "spectrum" / "W001933N55743_201605.nc",
+ decode_cf=False,
)
+ # Manually apply scale_factor and add_offset
+ efth_encoded = expected_spectrum["efth"]
+ scale_factor = expected_spectrum["efth"].encoding.get("scale_factor", 1.0)
+ add_offset = expected_spectrum["efth"].encoding.get("add_offset", 0.0)
+ efth_decoded = efth_encoded * scale_factor + add_offset
+ expected_spectrum = expected_spectrum.assign(Ef=np.power(10.0, efth_decoded) - 1e-12)
expected_spectrum = expected_spectrum.drop_vars("efth")
got_spectrum = get_2D_spectrum("W001933N55743", ["2016"], ["05"])
@@ -88,9 +93,7 @@ def test_download_2D_file():
def test_download_1D_file():
- expected_spectrum = xarray.open_dataset(
- DATA_DIR / "spectrum" / "RSCD_WW3-RSCD-UG-W001933N55743_201605_freq.nc"
- )
+ expected_spectrum = xarray.open_dataset(DATA_DIR / "spectrum" / "RSCD_WW3-RSCD-UG-W001933N55743_201605_freq.nc")
expected_spectrum = expected_spectrum.drop_dims("string40").squeeze()
expected_spectrum = expected_spectrum.drop_vars(["station"])
diff --git a/tests/test_weather_window.py b/tests/test_weather_window.py
index 7368c06..b9ed74d 100644
--- a/tests/test_weather_window.py
+++ b/tests/test_weather_window.py
@@ -82,12 +82,6 @@ def test_weather_windows(hs):
result = compute_weather_windows(hs, month)
assert result.PT.mean() == pytest.approx(expected_month_stats["PT_mean"])
- assert result.number_events.mean() == pytest.approx(
- expected_month_stats["number_events_mean"]
- )
- assert result.number_access_hours.mean() == pytest.approx(
- expected_month_stats["number_access_hours_mean"]
- )
- assert result.number_waiting_hours.mean() == pytest.approx(
- expected_month_stats["number_waiting_hours_mean"]
- )
+ assert result.number_events.mean() == pytest.approx(expected_month_stats["number_events_mean"])
+ assert result.number_access_hours.mean() == pytest.approx(expected_month_stats["number_access_hours_mean"])
+ assert result.number_waiting_hours.mean() == pytest.approx(expected_month_stats["number_waiting_hours_mean"])
diff --git a/tox.ini b/tox.ini
index 2ab8937..291706c 100644
--- a/tox.ini
+++ b/tox.ini
@@ -1,45 +1,50 @@
[gh]
python =
+ 3.13 = test
3.12 = test
3.11 = test
- 3.10 = test
- 3.9 = test
[tox]
-envlist=py{312, 311,310,39}
+requires = tox-uv
+envlist = py{311,312,313}
[testenv:flake8]
+runner = uv-venv-lock-runner
skip_install = true
deps =
- flake8 >= 3.6
+ flake8>=3.6
nbqa
commands =
flake8
[testenv:black]
basepython = python3
+runner = uv-venv-lock-runner
skip_install = true
deps =
- black >= 19.10b0
+ black>=19.10b0
nbqa
commands =
black --check .
[testenv:test]
-deps = -rdev_requirements.txt
+runner = uv-venv-lock-runner
+extras = dev
commands = pytest {posargs:--verbose --doctest-glob README.md}
[testenv:black-run]
basepython = python3
+runner = uv-venv-lock-runner
skip_install = true
deps =
- black >= 19.10b0
+ black>=19.10b0
nbqa
commands =
black .
[testenv:pypi-publish]
basepython = python3
+runner = uv-venv-lock-runner
skip_install = true
allowlist_externals = rm
deps =
@@ -50,18 +55,20 @@ setenv =
TWINE_USERNAME = {env:TWINE_USERNAME:__token__}
commands =
rm -rf build dist .egg .egg-info
- python3 setup.py sdist bdist_wheel
+ uv build
twine check dist/*
twine upload --skip-existing dist/*
[testenv:check-manifest]
basepython = python3
+runner = uv-venv-lock-runner
skip_install = true
deps = check-manifest
commands = check-manifest
[testenv:mypy]
+runner = uv-venv-lock-runner
deps = mypy
commands = mypy --install-types --non-interactive {posargs} resourcecode/
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..e63b68d
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,1589 @@
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+revision = 3
+requires-python = ">=3.11, <3.14"
+resolution-markers = [
+ "python_full_version >= '3.12' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+ "python_full_version < '3.12' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+ "(python_full_version >= '3.12' and platform_machine != 'ARM64') or (python_full_version >= '3.12' and sys_platform != 'win32')",
+ "(python_full_version < '3.12' and platform_machine != 'ARM64') or (python_full_version < '3.12' and sys_platform != 'win32')",
+]
+
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