diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 7066c22a4..6febbc5b2 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -2,7 +2,7 @@
# pre-commit install
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
- rev: v5.0.0
+ rev: v6.0.0
hooks:
- id: end-of-file-fixer
- id: mixed-line-ending
@@ -11,7 +11,7 @@ repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
# Ruff version.
- rev: v0.11.13
+ rev: v0.15.5
hooks:
# Run the linter.
- id: ruff-check
@@ -20,7 +20,7 @@ repos:
- id: ruff-format
- repo: https://github.com/numpy/numpydoc
- rev: v1.8.0
+ rev: v1.10.0
hooks:
- id: numpydoc-validation
files: ^ml_peg/
diff --git a/docs/source/user_guide/benchmarks/conformers.rst b/docs/source/user_guide/benchmarks/conformers.rst
new file mode 100644
index 000000000..5e9ed6d30
--- /dev/null
+++ b/docs/source/user_guide/benchmarks/conformers.rst
@@ -0,0 +1,42 @@
+==========
+Conformers
+==========
+
+ACONFL
+======
+
+Summary
+-------
+
+Performance in predicting relative conformer energies of 12 C12H26,
+16 C16H34 and 20 C20H42 conformers. Reference data from PNO-LCCSD(T)-F12/ AVQZ calculations.
+
+Metrics
+-------
+
+1. Conformer energy error
+
+For each complex, the the relative energy is calculated by taking the difference in energy
+between the given conformer and the reference (zero-energy) conformer. This is
+compared to the reference conformer energy, calculated in the same way.
+
+Computational cost
+------------------
+
+Low: tests are likely to take minutes to run on CPU.
+
+Data availability
+-----------------
+
+Input structures:
+
+* Conformational Energy Benchmark for Longer n-Alkane Chains
+ Sebastian Ehlert, Stefan Grimme, and Andreas Hansen
+ The Journal of Physical Chemistry A 2022 126 (22), 3521-3535
+ DOI: 10.1021/acs.jpca.2c02439
+
+Reference data:
+
+* Same as input data
+* :math:`PNO-LCCSD(T)-F12/ AVQZ` level of theory: a local, explicitly
+ correlated coupled cluster method.
diff --git a/docs/source/user_guide/benchmarks/index.rst b/docs/source/user_guide/benchmarks/index.rst
index 83afd6ec5..ad3c82f96 100644
--- a/docs/source/user_guide/benchmarks/index.rst
+++ b/docs/source/user_guide/benchmarks/index.rst
@@ -14,3 +14,5 @@ Benchmarks
bulk_crystal
lanthanides
non_covalent_interactions
+ tm_complexes
+ conformers
diff --git a/docs/source/user_guide/benchmarks/molecular.rst b/docs/source/user_guide/benchmarks/molecular.rst
index 21460d29c..7b1857d9e 100644
--- a/docs/source/user_guide/benchmarks/molecular.rst
+++ b/docs/source/user_guide/benchmarks/molecular.rst
@@ -124,3 +124,53 @@ Reference data:
* Same as input data
* DLPNO-CCSD(T)/CBS
+
+
+BMIM Cl RDF
+===========
+
+Summary
+-------
+
+Tests whether MLIPs incorrectly predict covalent bond formation between chloride
+anions (Cl⁻) and carbon atoms in 1-butyl-3-methylimidazolium (BMIM⁺) cations.
+Such Cl-C bonds should NOT form in the ionic liquid under normal conditions.
+
+This benchmark runs NVT molecular dynamics simulations of BMIM Cl at
+353.15 K and analyses the Cl-C RDF to detect any unphysical bond formation.
+
+
+Metrics
+-------
+
+1. Cl-C Bonds Formed
+
+Binary metric indicating whether unphysical Cl-C bonds formed during the MD simulation.
+
+The Cl-C RDF is computed from the MD trajectory. If the RDF shows a peak (g(r) > 0.1)
+at distances below 2.5 Å, this indicates bond formation and the model fails the test.
+
+* 0 = no bonds formed (correct physical behaviour)
+* 1 = bonds formed (unphysical, model failure)
+
+
+Computational cost
+------------------
+
+Medium: tests require running 10,000 steps of Langevin MD for a system of 10 ion
+pairs, which may take tens of minutes on GPU.
+
+
+Data availability
+-----------------
+
+Input structures:
+
+* Generated using molify from SMILES representations of BMIM⁺ (CCCCN1C=C[N+](=C1)C)
+ and Cl⁻ ions, packed to experimental density of 1052 kg/m³ at 353.15 K.
+* Zills, F. molify: Molecular Structure Interface. Journal of Open Source Software
+ 10, 8829 (2025). https://doi.org/10.21105/joss.08829
+* Density from: Yang, F., Wang, D., Wang, X. & Liu, Z. Volumetric Properties of
+ Binary and Ternary Mixtures of Bis(2-hydroxyethyl)ammonium Acetate with Methanol,
+ N,N-Dimethylformamide, and Water at Several Temperatures. J. Chem. Eng. Data 62,
+ 3958-3966 (2017). https://doi.org/10.1021/acs.jced.7b00654
diff --git a/docs/source/user_guide/benchmarks/molecular_dynamics.rst b/docs/source/user_guide/benchmarks/molecular_dynamics.rst
new file mode 100644
index 000000000..dcae3cfb1
--- /dev/null
+++ b/docs/source/user_guide/benchmarks/molecular_dynamics.rst
@@ -0,0 +1,38 @@
+
+==================
+Molecular dynamics
+==================
+
+Water density
+================
+
+Summary
+-------
+
+Performance in predicting the density of water at temperatures of 270, 290, 300, and 330 K.
+The water systems consist of 333 molecules.
+
+Metrics
+-------
+
+1. Density error
+
+For each system, the density is calculated by taking the average density of an NPT molecular
+dynamics run. The initial part of the simulation, here 500 ps, is omitted from the density
+calculation. This is compared to the reference density, obtained from experiment.
+
+Computational cost
+------------------
+
+Low: tests are likely to take several days to run on GPU.
+
+Data availability
+-----------------
+
+Input structures:
+
+*
+
+Reference data:
+
+* Experiment
diff --git a/docs/source/user_guide/benchmarks/nebs.rst b/docs/source/user_guide/benchmarks/nebs.rst
index e081babf1..9a741711e 100644
--- a/docs/source/user_guide/benchmarks/nebs.rst
+++ b/docs/source/user_guide/benchmarks/nebs.rst
@@ -46,3 +46,60 @@ Reference data:
* Manually taken from https://doi.org/10.1149/1.1633511.
* Meta-GGA (Perdew-Wang) exchange correlation functional
+
+
+Si defects
+==========
+
+Summary
+-------
+
+Performance in predicting DFT singlepoint energies and forces along fixed nudged-elastic-band
+(NEB) images for a silicon interstitial migration pathway.
+
+Metrics
+-------
+
+For each of the three NEB datasets (64 atoms, 216 atoms, and 216 atoms di-to-single), MLIPs are
+evaluated on the same ordered NEB images as the reference.
+
+1. Energy MAE
+
+Mean absolute error (MAE) of *relative* energies along the NEB, shifting image 0 to 0 eV
+for both the DFT reference and the MLIP predictions.
+
+2. Force MAE
+
+Mean absolute error (MAE) of forces across all atoms and images along the NEB.
+
+Computational cost
+------------------
+
+Medium: tests are likely to take several minutes to run on CPU.
+
+Data availability
+-----------------
+
+Input/reference data:
+
+* Reference extxyz trajectories (including per-image DFT energies and forces) are distributed as a
+ separate zip archive and downloaded on-demand from the ML-PEG data store.
+ The calculation script uses the public ML-PEG S3 bucket to retrieve these inputs.
+* The reference DFT energies/forces come from Quantum ESPRESSO (PWscf) single-point calculations
+ with:
+
+ - Code/version: Quantum ESPRESSO PWSCF v.7.0
+ - XC functional: ``input_dft='PBE'``
+ - Cutoffs: ``ecutwfc=30.0`` Ry, ``ecutrho=240.0`` Ry
+ - Smearing: ``occupations='smearing'``, ``smearing='mv'``, ``degauss=0.01`` Ry
+ - SCF convergence/mixing: ``conv_thr=1.0d-6``, ``electron_maxstep=250``, ``mixing_beta=0.2``,
+ ``mixing_mode='local-TF'``
+ - Diagonalization: ``diagonalization='david'``
+ - Symmetry: ``nosym=.false.``, ``noinv=.false.`` (symmetry enabled)
+ - Pseudopotential: ``Si.pbe-n-kjpaw_psl.1.0.0.UPF`` (PSLibrary)
+
+ K-points by case:
+
+ - 64 atoms: Γ-only (``K_POINTS automatic 1 1 1 0 0 0``)
+ - 216 atoms: Γ-only (``K_POINTS gamma``)
+ - 216 atoms di-to-single: Γ-only (``K_POINTS gamma``)
diff --git a/docs/source/user_guide/benchmarks/tm_complexes.rst b/docs/source/user_guide/benchmarks/tm_complexes.rst
new file mode 100644
index 000000000..80f8a1a29
--- /dev/null
+++ b/docs/source/user_guide/benchmarks/tm_complexes.rst
@@ -0,0 +1,42 @@
+==========================
+Transition Metal Complexes
+==========================
+
+3dTMV
+=======
+
+Summary
+-------
+
+Performance in predicting vertical ionization energies for 28 transition metal
+complexes.
+
+Metrics
+-------
+
+1. Ionization energy error
+
+For each complex, the ionization energy is calculated by taking the difference in energy
+between the complex in its oxidized state and initial state, which differ by one electron
+and spin multiplicity. This is compared to the reference ionization energy, calculated in the same way.
+
+Computational cost
+------------------
+
+Low: tests are likely to take minutes to run on CPU.
+
+Data availability
+-----------------
+
+Input structures:
+
+* Toward Benchmark-Quality Ab Initio Predictions for 3d Transition Metal
+ Electrocatalysts: A Comparison of CCSD(T) and ph-AFQMC Hagen Neugebauer, Hung T.
+ Vuong, John L. Weber, Richard A. Friesner, James Shee, and Andreas Hansen Journal of
+ Chemical Theory and Computation 2023 19 (18), 6208-6225,
+ DOI: 10.1021/acs.jctc.3c00617
+
+Reference data:
+
+* Same as input data
+* ph-AFQMC level of theory: Auxiliary-Field Quantum Monte Carlo.
diff --git a/ml_peg/analysis/conformers/37Conf8/analyse_37Conf8.py b/ml_peg/analysis/conformers/37Conf8/analyse_37Conf8.py
index 226ad111c..cbc7ca78c 100644
--- a/ml_peg/analysis/conformers/37Conf8/analyse_37Conf8.py
+++ b/ml_peg/analysis/conformers/37Conf8/analyse_37Conf8.py
@@ -13,14 +13,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "conformers" / "37Conf8" / "outputs"
@@ -113,7 +117,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "37conf8_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/conformers/ACONFL/analyse_ACONFL.py b/ml_peg/analysis/conformers/ACONFL/analyse_ACONFL.py
new file mode 100644
index 000000000..f15d642e1
--- /dev/null
+++ b/ml_peg/analysis/conformers/ACONFL/analyse_ACONFL.py
@@ -0,0 +1,153 @@
+"""
+Analyse the ACONFL dataset for molecular conformer relative energies.
+
+Conformational Energy Benchmark for Longer n-Alkane Chains
+Sebastian Ehlert, Stefan Grimme, and Andreas Hansen
+The Journal of Physical Chemistry A 2022 126 (22), 3521-3535
+DOI: 10.1021/acs.jpca.2c02439
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from ase import units
+from ase.io import read, write
+import pytest
+
+from ml_peg.analysis.utils.decorators import build_table, plot_parity
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
+from ml_peg.app import APP_ROOT
+from ml_peg.calcs import CALCS_ROOT
+from ml_peg.models.get_models import load_models
+from ml_peg.models.models import current_models
+
+MODELS = load_models(current_models)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
+
+EV_TO_KCAL = units.mol / units.kcal
+CALC_PATH = CALCS_ROOT / "conformers" / "ACONFL" / "outputs"
+OUT_PATH = APP_ROOT / "data" / "conformers" / "ACONFL"
+
+METRICS_CONFIG_PATH = Path(__file__).with_name("metrics.yml")
+DEFAULT_THRESHOLDS, DEFAULT_TOOLTIPS, DEFAULT_WEIGHTS = load_metrics_config(
+ METRICS_CONFIG_PATH
+)
+
+
+def labels() -> list:
+ """
+ Get list of system names.
+
+ Returns
+ -------
+ list
+ List of all system names.
+ """
+ for model_name in MODELS:
+ labels_list = [path.stem for path in sorted((CALC_PATH / model_name).glob("*"))]
+ break
+ return labels_list
+
+
+@pytest.fixture
+@plot_parity(
+ filename=OUT_PATH / "figure_aconfl.json",
+ title="Energies",
+ x_label="Predicted energy / kcal/mol",
+ y_label="Reference energy / kcal/mol",
+ hoverdata={
+ "Labels": labels(),
+ },
+)
+def conformer_energies() -> dict[str, list]:
+ """
+ Get conformer energies for all systems.
+
+ Returns
+ -------
+ dict[str, list]
+ Dictionary of all reference and predicted conformer energies.
+ """
+ results = {"ref": []} | {mlip: [] for mlip in MODELS}
+ ref_stored = False
+
+ for model_name in MODELS:
+ for label in labels():
+ atoms = read(CALC_PATH / model_name / f"{label}.xyz")
+
+ results[model_name].append(atoms.info["model_rel_energy"] * EV_TO_KCAL)
+ if not ref_stored:
+ results["ref"].append(atoms.info["ref_rel_energy"] * EV_TO_KCAL)
+
+ # Write structures for app
+ structs_dir = OUT_PATH / model_name
+ structs_dir.mkdir(parents=True, exist_ok=True)
+ write(structs_dir / f"{label}.xyz", atoms)
+ ref_stored = True
+ return results
+
+
+@pytest.fixture
+def get_mae(conformer_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for conformer energies.
+
+ Parameters
+ ----------
+ conformer_energies
+ Dictionary of reference and predicted conformer energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted conformer energies errors for all models.
+ """
+ results = {}
+ for model_name in MODELS:
+ results[model_name] = mae(
+ conformer_energies["ref"], conformer_energies[model_name]
+ )
+ return results
+
+
+@pytest.fixture
+@build_table(
+ filename=OUT_PATH / "aconfl_metrics_table.json",
+ metric_tooltips=DEFAULT_TOOLTIPS,
+ thresholds=DEFAULT_THRESHOLDS,
+ mlip_name_map=DISPERSION_NAME_MAP,
+)
+def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
+ """
+ Get all metrics.
+
+ Parameters
+ ----------
+ get_mae
+ Mean absolute errors for all models.
+
+ Returns
+ -------
+ dict[str, dict]
+ Metric names and values for all models.
+ """
+ return {
+ "MAE": get_mae,
+ }
+
+
+def test_aconfl(metrics: dict[str, dict]) -> None:
+ """
+ Run ACONFL test.
+
+ Parameters
+ ----------
+ metrics
+ All new benchmark metric names and dictionary of values for each model.
+ """
+ return
diff --git a/ml_peg/analysis/conformers/ACONFL/metrics.yml b/ml_peg/analysis/conformers/ACONFL/metrics.yml
new file mode 100644
index 000000000..40d89a17d
--- /dev/null
+++ b/ml_peg/analysis/conformers/ACONFL/metrics.yml
@@ -0,0 +1,7 @@
+metrics:
+ MAE:
+ good: 0.0
+ bad: 2.0
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for all systems
+ level_of_theory: PNO-LCCSD(T)-F12/ AVQZ
diff --git a/ml_peg/analysis/conformers/DipCONFS/analyse_DipCONFS.py b/ml_peg/analysis/conformers/DipCONFS/analyse_DipCONFS.py
index b5b9e7d4d..e959f3005 100644
--- a/ml_peg/analysis/conformers/DipCONFS/analyse_DipCONFS.py
+++ b/ml_peg/analysis/conformers/DipCONFS/analyse_DipCONFS.py
@@ -13,14 +13,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "conformers" / "DipCONFS" / "outputs"
@@ -113,7 +117,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "dipconfs_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/conformers/Glucose205/analyse_Glucose205.py b/ml_peg/analysis/conformers/Glucose205/analyse_Glucose205.py
index bab17a63e..6a1b8b611 100644
--- a/ml_peg/analysis/conformers/Glucose205/analyse_Glucose205.py
+++ b/ml_peg/analysis/conformers/Glucose205/analyse_Glucose205.py
@@ -15,14 +15,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "conformers" / "Glucose205" / "outputs"
@@ -115,7 +119,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "glucose205_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/conformers/MPCONF196/analyse_MPCONF196.py b/ml_peg/analysis/conformers/MPCONF196/analyse_MPCONF196.py
index 000b9d9ef..efc62faab 100644
--- a/ml_peg/analysis/conformers/MPCONF196/analyse_MPCONF196.py
+++ b/ml_peg/analysis/conformers/MPCONF196/analyse_MPCONF196.py
@@ -14,14 +14,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "conformers" / "MPCONF196" / "outputs"
@@ -115,7 +119,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "mpconf196_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/conformers/Maltose222/analyse_Maltose222.py b/ml_peg/analysis/conformers/Maltose222/analyse_Maltose222.py
index 7ee1f4483..a05e64aa3 100644
--- a/ml_peg/analysis/conformers/Maltose222/analyse_Maltose222.py
+++ b/ml_peg/analysis/conformers/Maltose222/analyse_Maltose222.py
@@ -15,14 +15,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "conformers" / "Maltose222" / "outputs"
@@ -115,7 +119,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "maltose222_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/conformers/OpenFF_Tors/analyse_OpenFF_Tors.py b/ml_peg/analysis/conformers/OpenFF_Tors/analyse_OpenFF_Tors.py
index f5df1a643..3f7378a94 100644
--- a/ml_peg/analysis/conformers/OpenFF_Tors/analyse_OpenFF_Tors.py
+++ b/ml_peg/analysis/conformers/OpenFF_Tors/analyse_OpenFF_Tors.py
@@ -14,14 +14,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "conformers" / "OpenFF_Tors" / "outputs"
OUT_PATH = APP_ROOT / "data" / "conformers" / "OpenFF_Tors"
@@ -117,7 +121,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "openff_tors_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/conformers/UpU46/analyse_UpU46.py b/ml_peg/analysis/conformers/UpU46/analyse_UpU46.py
index d93bb89b9..8f35e4268 100644
--- a/ml_peg/analysis/conformers/UpU46/analyse_UpU46.py
+++ b/ml_peg/analysis/conformers/UpU46/analyse_UpU46.py
@@ -15,14 +15,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
@@ -118,7 +122,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "upu46_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/conformers/solvMPCONF196/analyse_solvMPCONF196.py b/ml_peg/analysis/conformers/solvMPCONF196/analyse_solvMPCONF196.py
index e28fa5abf..550931053 100644
--- a/ml_peg/analysis/conformers/solvMPCONF196/analyse_solvMPCONF196.py
+++ b/ml_peg/analysis/conformers/solvMPCONF196/analyse_solvMPCONF196.py
@@ -13,14 +13,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "conformers" / "solvMPCONF196" / "outputs"
OUT_PATH = APP_ROOT / "data" / "conformers" / "solvMPCONF196"
@@ -128,7 +132,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "solv_mpconf196_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular/BMIMCl_RDF/analyse_BMIMCl_RDF.py b/ml_peg/analysis/molecular/BMIMCl_RDF/analyse_BMIMCl_RDF.py
new file mode 100644
index 000000000..1831dcad5
--- /dev/null
+++ b/ml_peg/analysis/molecular/BMIMCl_RDF/analyse_BMIMCl_RDF.py
@@ -0,0 +1,199 @@
+"""Analyse BMIMCl RDF benchmark for unphysical Cl-C bond formation."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from ase.data import atomic_numbers
+from ase.geometry.rdf import get_rdf
+import ase.io as aio
+import numpy as np
+import pytest
+from tqdm import tqdm
+
+from ml_peg.analysis.utils.decorators import build_table, plot_scatter
+from ml_peg.analysis.utils.utils import load_metrics_config
+from ml_peg.app import APP_ROOT
+from ml_peg.calcs import CALCS_ROOT
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+CALC_PATH = CALCS_ROOT / "molecular" / "BMIMCl_RDF" / "outputs"
+OUT_PATH = APP_ROOT / "data" / "molecular" / "BMIMCl_RDF"
+
+METRICS_CONFIG_PATH = Path(__file__).with_name("metrics.yml")
+DEFAULT_THRESHOLDS, DEFAULT_TOOLTIPS, DEFAULT_WEIGHTS = load_metrics_config(
+ METRICS_CONFIG_PATH
+)
+
+# RDF parameters
+ELEMENT1 = "Cl"
+ELEMENT2 = "C"
+Z1 = atomic_numbers[ELEMENT1]
+Z2 = atomic_numbers[ELEMENT2]
+BINS_PER_ANG = 50
+UNPHYSICAL_CUTOFF = 2.5
+# Angstrom - any Cl-C closer than this indicates
+# a bond which should not be there
+PEAK_THRESHOLD = 0.1 # g(r) threshold for bond detection
+
+
+def compute_rdf_from_trajectory(traj_path: Path) -> tuple[np.ndarray, np.ndarray]:
+ """
+ Compute Cl-C RDF from MD trajectory.
+
+ Parameters
+ ----------
+ traj_path
+ Path to trajectory xyz file.
+
+ Returns
+ -------
+ tuple[np.ndarray, np.ndarray]
+ (r, rdf) arrays - distances and averaged g(r) values.
+ """
+ images = aio.read(traj_path, index=":")
+
+ # Infer rmax from cell (NVT)
+ cell_lengths = images[0].cell.lengths()
+ rmax = min(cell_lengths) / 2 - 0.01
+ nbins = int(rmax * BINS_PER_ANG)
+
+ # Compute RDFs with progress bar
+ rdfs = []
+ r = None
+ for atoms in tqdm(images, desc="Computing RDF"):
+ rdf_frame, distances = get_rdf(
+ atoms, rmax, nbins, elements=(Z1, Z2), no_dists=False
+ )
+ rdfs.append(rdf_frame)
+ if r is None:
+ r = distances
+
+ rdf = np.mean(rdfs, axis=0)
+
+ return r, rdf
+
+
+def check_bond_formation(r: np.ndarray, rdf: np.ndarray) -> int:
+ """
+ Check if Cl-C bonds formed based on RDF.
+
+ Parameters
+ ----------
+ r
+ Distance array.
+ rdf
+ The g(r) values.
+
+ Returns
+ -------
+ int
+ 1 if bonds formed (bad), 0 if no bonds (good).
+ """
+ mask = r < UNPHYSICAL_CUTOFF
+ max_gr = rdf[mask].max() if mask.any() else 0.0
+ return 1 if max_gr > PEAK_THRESHOLD else 0
+
+
+@pytest.fixture
+@plot_scatter(
+ title="Cl-C Radial Distribution Function",
+ x_label="r / Å",
+ y_label="g(r)",
+ show_line=True,
+ filename=str(OUT_PATH / "figure_rdf.json"),
+)
+def rdf_data() -> dict[str, list]:
+ """
+ Compute RDF for all models.
+
+ Returns
+ -------
+ dict[str, list]
+ Dictionary mapping model names to [r, g(r)] arrays.
+ """
+ results = {}
+
+ OUT_PATH.mkdir(parents=True, exist_ok=True)
+
+ for model_name in MODELS:
+ traj_path = CALC_PATH / model_name / "md.xyz"
+ if not traj_path.exists():
+ continue
+
+ r, rdf = compute_rdf_from_trajectory(traj_path)
+ results[model_name] = [r.tolist(), rdf.tolist()]
+
+ rdf_out = OUT_PATH / model_name
+ rdf_out.mkdir(parents=True, exist_ok=True)
+ np.savetxt(
+ rdf_out / "rdf.dat",
+ np.column_stack([r, rdf]),
+ header="r/A g(r)",
+ fmt="%.6f",
+ )
+
+ return results
+
+
+@pytest.fixture
+def bond_formation(rdf_data: dict[str, list]) -> dict[str, int]:
+ """
+ Check bond formation for all models.
+
+ Parameters
+ ----------
+ rdf_data
+ Dictionary of RDF data per model.
+
+ Returns
+ -------
+ dict[str, int]
+ Dictionary mapping model names to bond formation flag (0 or 1).
+ """
+ results = {}
+ for model_name, (r, rdf) in rdf_data.items():
+ r_arr = np.array(r)
+ rdf_arr = np.array(rdf)
+ results[model_name] = check_bond_formation(r_arr, rdf_arr)
+ return results
+
+
+@pytest.fixture
+@build_table(
+ filename=str(OUT_PATH / "bmimcl_metrics_table.json"),
+ metric_tooltips=DEFAULT_TOOLTIPS,
+ thresholds=DEFAULT_THRESHOLDS,
+ weights=DEFAULT_WEIGHTS,
+)
+def metrics(bond_formation: dict[str, int]) -> dict[str, dict]:
+ """
+ Build metrics table.
+
+ Parameters
+ ----------
+ bond_formation
+ Bond formation flags per model.
+
+ Returns
+ -------
+ dict[str, dict]
+ Metrics dictionary for table building.
+ """
+ return {
+ "Cl-C Bonds Formed": bond_formation,
+ }
+
+
+def test_bmimcl_rdf(metrics: dict[str, dict]) -> None:
+ """
+ Run BMIMCl RDF analysis.
+
+ Parameters
+ ----------
+ metrics
+ Benchmark metrics generated by fixtures.
+ """
+ return
diff --git a/ml_peg/analysis/molecular/BMIMCl_RDF/metrics.yml b/ml_peg/analysis/molecular/BMIMCl_RDF/metrics.yml
new file mode 100644
index 000000000..75df3aab6
--- /dev/null
+++ b/ml_peg/analysis/molecular/BMIMCl_RDF/metrics.yml
@@ -0,0 +1,7 @@
+metrics:
+ Cl-C Bonds Formed:
+ good: 0.0
+ bad: 1.0
+ unit: null
+ tooltip: "Whether Cl-C bonds formed (g(r) > 0.1 for r < 2.5 A). 0 = no bonds (correct), 1 = bonds formed (wrong)."
+ weight: 1.0
diff --git a/ml_peg/analysis/molecular/GMTKN55/analyse_GMTKN55.py b/ml_peg/analysis/molecular/GMTKN55/analyse_GMTKN55.py
index 149e87e19..20272be20 100644
--- a/ml_peg/analysis/molecular/GMTKN55/analyse_GMTKN55.py
+++ b/ml_peg/analysis/molecular/GMTKN55/analyse_GMTKN55.py
@@ -11,14 +11,14 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config
+from ml_peg.analysis.utils.utils import build_dispersion_name_map, load_metrics_config
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular" / "GMTKN55" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular" / "GMTKN55"
@@ -291,7 +291,7 @@ def weighted_error(subset_errors: dict[str, dict[str, float]]) -> dict[str, floa
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
weights=DEFAULT_WEIGHTS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(
category_errors: dict[str, dict[str, float]], weighted_error: dict[str, float]
diff --git a/ml_peg/analysis/molecular/Wiggle150/analyse_Wiggle150.py b/ml_peg/analysis/molecular/Wiggle150/analyse_Wiggle150.py
index bfbf10479..d94545c15 100644
--- a/ml_peg/analysis/molecular/Wiggle150/analyse_Wiggle150.py
+++ b/ml_peg/analysis/molecular/Wiggle150/analyse_Wiggle150.py
@@ -9,14 +9,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular" / "Wiggle150" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular" / "Wiggle150"
@@ -161,7 +165,7 @@ def wiggle150_mae(relative_energies) -> dict[str, float]:
filename=OUT_PATH / "wiggle150_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(wiggle150_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular_crystal/CPOSS209/analyse_CPOSS209.py b/ml_peg/analysis/molecular_crystal/CPOSS209/analyse_CPOSS209.py
index 93bb44594..81d0229c9 100644
--- a/ml_peg/analysis/molecular_crystal/CPOSS209/analyse_CPOSS209.py
+++ b/ml_peg/analysis/molecular_crystal/CPOSS209/analyse_CPOSS209.py
@@ -9,14 +9,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular_crystal" / "CPOSS209" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular_crystal" / "CPOSS209"
@@ -971,7 +975,7 @@ def cposs209_errors(
filename=OUT_PATH / "cposs209_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
weights=DEFAULT_WEIGHTS,
)
def metrics(
diff --git a/ml_peg/analysis/molecular_crystal/DMC_ICE13/analyse_DMC_ICE13.py b/ml_peg/analysis/molecular_crystal/DMC_ICE13/analyse_DMC_ICE13.py
index a3f1e0a9b..3c5f0b080 100644
--- a/ml_peg/analysis/molecular_crystal/DMC_ICE13/analyse_DMC_ICE13.py
+++ b/ml_peg/analysis/molecular_crystal/DMC_ICE13/analyse_DMC_ICE13.py
@@ -8,14 +8,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular_crystal" / "DMC_ICE13" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular_crystal" / "DMC_ICE13"
@@ -136,7 +140,7 @@ def dmc_ice13_errors(lattice_energies) -> dict[str, float]:
filename=OUT_PATH / "dmc_ice13_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(dmc_ice13_errors: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular_crystal/X23/analyse_X23.py b/ml_peg/analysis/molecular_crystal/X23/analyse_X23.py
index fc180e3e5..d7110c24f 100644
--- a/ml_peg/analysis/molecular_crystal/X23/analyse_X23.py
+++ b/ml_peg/analysis/molecular_crystal/X23/analyse_X23.py
@@ -9,14 +9,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular_crystal" / "X23" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular_crystal" / "X23"
@@ -139,7 +143,7 @@ def x23_errors(lattice_energies) -> dict[str, float]:
filename=OUT_PATH / "x23_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(x23_errors: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular_dynamics/water_density/analyse_water_density.py b/ml_peg/analysis/molecular_dynamics/water_density/analyse_water_density.py
new file mode 100644
index 000000000..b8516743c
--- /dev/null
+++ b/ml_peg/analysis/molecular_dynamics/water_density/analyse_water_density.py
@@ -0,0 +1,182 @@
+"""Analyse the water density benchmark."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from ase.io import Trajectory, write
+import numpy as np
+import pytest
+
+from ml_peg.analysis.utils.decorators import build_table, plot_parity
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
+from ml_peg.app import APP_ROOT
+from ml_peg.calcs import CALCS_ROOT
+from ml_peg.models.get_models import load_models
+from ml_peg.models.models import current_models
+
+MODELS = load_models(current_models)
+D3_MODEL_NAMES = build_dispersion_name_map(MODELS)
+
+INTERVAL_PS = 0.1
+EQUILIB_TIME_PS = 500
+
+CALC_PATH = CALCS_ROOT / "molecular_dynamics" / "water_density" / "outputs"
+OUT_PATH = APP_ROOT / "data" / "molecular_dynamics" / "water_density"
+
+
+METRICS_CONFIG_PATH = Path(__file__).with_name("metrics.yml")
+DEFAULT_THRESHOLDS, DEFAULT_TOOLTIPS, DEFAULT_WEIGHTS = load_metrics_config(
+ METRICS_CONFIG_PATH
+)
+
+EXPERIMENTAL_DATA = {
+ "water_270.0_K": 0.9998,
+ "water_290.0_K": 0.9991,
+ "water_300.0_K": 0.9970,
+ "water_330.0_K": 0.9802,
+}
+
+
+def labels() -> list:
+ """
+ Get list of system names.
+
+ Returns
+ -------
+ list
+ List of all system names.
+ """
+ for model_name in MODELS:
+ return [path.stem for path in (CALC_PATH / model_name).glob("*.log")]
+ return []
+
+
+def compute_density(fname, density_col=13):
+ """
+ Compute average density from NPT log file.
+
+ Parameters
+ ----------
+ fname
+ Path to the log file.
+ density_col
+ Which column the density numbers are in.
+
+ Returns
+ -------
+ float
+ Average density in g/cm3.
+ """
+ density_series = []
+ with open(fname) as lines:
+ for line in lines:
+ items = line.strip().split()
+ if len(items) != 15:
+ continue
+ density_series.append(float(items[13]))
+ skip_frames = int(EQUILIB_TIME_PS / INTERVAL_PS)
+ return np.mean(density_series[skip_frames:])
+
+
+@pytest.fixture
+@plot_parity(
+ filename=OUT_PATH / "figure_water_density.json",
+ title="Densities",
+ x_label="Predicted density / kcal/mol",
+ y_label="Reference density / kcal/mol",
+ hoverdata={
+ "Labels": labels(),
+ },
+)
+def water_density() -> dict[str, list]:
+ """
+ Get water densities for all temperatures.
+
+ Returns
+ -------
+ dict[str, list]
+ Dictionary of all reference and predicted densities.
+ """
+ results = {"ref": []} | {mlip: [] for mlip in MODELS}
+ ref_stored = False
+
+ for model_name in MODELS:
+ for label in labels():
+ atoms = Trajectory(CALC_PATH / model_name / f"{label}.traj")[-1]
+
+ results[model_name].append(
+ compute_density(CALC_PATH / model_name / f"{label}.log")
+ )
+ if not ref_stored:
+ results["ref"].append(EXPERIMENTAL_DATA[label])
+
+ # Write structures for app
+ structs_dir = OUT_PATH / model_name
+ structs_dir.mkdir(parents=True, exist_ok=True)
+ write(structs_dir / f"{label}.xyz", atoms)
+ ref_stored = True
+ return results
+
+
+@pytest.fixture
+def get_mae(water_density) -> dict[str, float]:
+ """
+ Get mean absolute error for water densities.
+
+ Parameters
+ ----------
+ water_density
+ Dictionary of reference and predicted water densities.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted water density errors for all models.
+ """
+ results = {}
+ for model_name in MODELS:
+ results[model_name] = mae(water_density["ref"], water_density[model_name])
+ return results
+
+
+@pytest.fixture
+@build_table(
+ filename=OUT_PATH / "water_density_metrics_table.json",
+ metric_tooltips=DEFAULT_TOOLTIPS,
+ thresholds=DEFAULT_THRESHOLDS,
+ mlip_name_map=D3_MODEL_NAMES,
+)
+def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
+ """
+ Get all metrics.
+
+ Parameters
+ ----------
+ get_mae
+ Mean absolute errors for all models.
+
+ Returns
+ -------
+ dict[str, dict]
+ Metric names and values for all models.
+ """
+ return {
+ "MAE": get_mae,
+ }
+
+
+def test_water_density(metrics: dict[str, dict]) -> None:
+ """
+ Run water density test.
+
+ Parameters
+ ----------
+ metrics
+ All new benchmark metric names and dictionary of values for each model.
+ """
+ return
diff --git a/ml_peg/analysis/molecular_dynamics/water_density/metrics.yml b/ml_peg/analysis/molecular_dynamics/water_density/metrics.yml
new file mode 100644
index 000000000..0754e9a91
--- /dev/null
+++ b/ml_peg/analysis/molecular_dynamics/water_density/metrics.yml
@@ -0,0 +1,8 @@
+metrics:
+ MAE:
+ good: 0.0
+ bad: 0.2
+ unit: g/cm^3
+ tooltip: Mean Absolute Error in density for all systems
+ level_of_theory: Experimental density
+ weight: 1
diff --git a/ml_peg/analysis/molecular_reactions/BH2O_36/analyse_BH2O_36.py b/ml_peg/analysis/molecular_reactions/BH2O_36/analyse_BH2O_36.py
index 9519ef837..ccaef305d 100644
--- a/ml_peg/analysis/molecular_reactions/BH2O_36/analyse_BH2O_36.py
+++ b/ml_peg/analysis/molecular_reactions/BH2O_36/analyse_BH2O_36.py
@@ -13,14 +13,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular_reactions" / "BH2O_36" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular_reactions" / "BH2O_36"
@@ -174,7 +178,7 @@ def get_mae(barrier_heights) -> dict[str, float]:
filename=OUT_PATH / "bh2o_36_barriers_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular_reactions/BH9/analyse_BH9.py b/ml_peg/analysis/molecular_reactions/BH9/analyse_BH9.py
index 6828aef19..757763f8f 100644
--- a/ml_peg/analysis/molecular_reactions/BH9/analyse_BH9.py
+++ b/ml_peg/analysis/molecular_reactions/BH9/analyse_BH9.py
@@ -14,14 +14,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular_reactions" / "BH9" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular_reactions" / "BH9"
@@ -174,7 +178,7 @@ def get_mae(barrier_heights: dict[str, list]) -> dict[str, float]:
filename=OUT_PATH / "bh9_barriers_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular_reactions/CYCLO70/analyse_CYCLO70.py b/ml_peg/analysis/molecular_reactions/CYCLO70/analyse_CYCLO70.py
index ce113d3f1..52f9dc7c4 100644
--- a/ml_peg/analysis/molecular_reactions/CYCLO70/analyse_CYCLO70.py
+++ b/ml_peg/analysis/molecular_reactions/CYCLO70/analyse_CYCLO70.py
@@ -17,14 +17,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "molecular_reactions" / "CYCLO70" / "outputs"
OUT_PATH = APP_ROOT / "data" / "molecular_reactions" / "CYCLO70"
@@ -130,7 +134,7 @@ def get_mae(barrier_heights) -> dict[str, float]:
filename=OUT_PATH / "cyclo70_barriers_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular_reactions/Criegee22/analyse_Criegee22.py b/ml_peg/analysis/molecular_reactions/Criegee22/analyse_Criegee22.py
index 867335abb..7f2917b95 100644
--- a/ml_peg/analysis/molecular_reactions/Criegee22/analyse_Criegee22.py
+++ b/ml_peg/analysis/molecular_reactions/Criegee22/analyse_Criegee22.py
@@ -13,14 +13,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "molecular_reactions" / "Criegee22" / "outputs"
@@ -119,7 +123,7 @@ def get_mae(barrier_heights) -> dict[str, float]:
filename=OUT_PATH / "criegee22_barriers_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/molecular_reactions/RDB7/analyse_RDB7.py b/ml_peg/analysis/molecular_reactions/RDB7/analyse_RDB7.py
index 234396d76..a1d31efe6 100644
--- a/ml_peg/analysis/molecular_reactions/RDB7/analyse_RDB7.py
+++ b/ml_peg/analysis/molecular_reactions/RDB7/analyse_RDB7.py
@@ -19,9 +19,10 @@
from ml_peg.analysis.utils.decorators import build_table, plot_density_scatter
from ml_peg.analysis.utils.utils import (
- build_d3_name_map,
+ build_dispersion_name_map,
load_metrics_config,
mae,
+ write_density_trajectories,
)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
@@ -29,7 +30,7 @@
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "molecular_reactions" / "RDB7" / "outputs"
@@ -110,6 +111,7 @@ def barrier_density(barrier_heights: dict[str, list]) -> dict[str, dict]:
Mapping of model name to density-scatter data.
"""
ref_vals = barrier_heights["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = barrier_heights.get(model_name, [])
@@ -118,6 +120,14 @@ def barrier_density(barrier_heights: dict[str, list]) -> dict[str, dict]:
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}_ts.xyz",
+ )
return density_inputs
@@ -147,7 +157,7 @@ def get_mae(barrier_heights) -> dict[str, float]:
filename=OUT_PATH / "rdb7_barriers_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/nebs/si_defects/analyse_si_defects.py b/ml_peg/analysis/nebs/si_defects/analyse_si_defects.py
new file mode 100644
index 000000000..43ea77029
--- /dev/null
+++ b/ml_peg/analysis/nebs/si_defects/analyse_si_defects.py
@@ -0,0 +1,294 @@
+"""Analyse Si defects DFT singlepoints (energies + forces)."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from pathlib import Path
+
+from ase.atoms import Atoms
+from ase.io import read, write
+import numpy as np
+import pandas as pd
+import pytest
+
+from ml_peg.analysis.utils.decorators import build_table, plot_scatter
+from ml_peg.analysis.utils.utils import load_metrics_config, mae
+from ml_peg.app import APP_ROOT
+from ml_peg.calcs import CALCS_ROOT
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+
+BENCHMARK_DIR = "si_defects"
+CALC_PATH = CALCS_ROOT / "nebs" / BENCHMARK_DIR / "outputs"
+OUT_PATH = APP_ROOT / "data" / "nebs" / BENCHMARK_DIR
+
+METRICS_CONFIG_PATH = Path(__file__).with_name("metrics.yml")
+DEFAULT_THRESHOLDS, DEFAULT_TOOLTIPS, DEFAULT_WEIGHTS = load_metrics_config(
+ METRICS_CONFIG_PATH
+)
+
+
+@dataclass(frozen=True)
+class _Case:
+ """Definition of a single Si defects NEB dataset."""
+
+ key: str
+ label: str
+
+
+CASES: tuple[_Case, ...] = (
+ _Case(key="64_atoms", label="64"),
+ _Case(key="216_atoms", label="216"),
+ _Case(key="216_atoms_di_to_single", label="216 di-to-single"),
+)
+
+
+@dataclass(frozen=True)
+class _Results:
+ """Computed errors and assets for one (case, model) pair."""
+
+ energy_mae: float
+ force_mae: float
+ x: list[float]
+ energy_error: list[float]
+ force_rms: list[float]
+ structs: list[Atoms]
+
+
+def _load_structs(case_key: str, model: str) -> list[Atoms] | None:
+ """
+ Load MLIP-evaluated NEB frames (with DFT reference stored).
+
+ Parameters
+ ----------
+ case_key
+ Case key.
+ model
+ Model name.
+
+ Returns
+ -------
+ list[ase.atoms.Atoms] | None
+ Frames if the calculation output exists, otherwise ``None``.
+ """
+ path = CALC_PATH / case_key / model / f"{BENCHMARK_DIR}.extxyz"
+ if not path.exists():
+ return None
+ structs = read(path, index=":")
+ if not isinstance(structs, list) or not structs:
+ raise ValueError(f"Unexpected output content: {path}")
+ return structs
+
+
+def _compute(structs: list[Atoms]) -> _Results:
+ """
+ Compute per-image errors and global MAEs.
+
+ Parameters
+ ----------
+ structs
+ Ordered NEB frames with ``ref_energy_ev``, ``ref_forces``, ``pred_energy_ev``,
+ and ``pred_forces``.
+
+ Returns
+ -------
+ _Results
+ Computed errors and frames for downstream plotting/app.
+ """
+ ref_e = np.asarray([float(s.info["ref_energy_ev"]) for s in structs])
+ pred_e = np.asarray([float(s.info["pred_energy_ev"]) for s in structs])
+ # Compare *relative* energies along the NEB (shift image 0 to 0 eV for both
+ # reference and predictions). This removes any constant energy offset.
+ ref_e_rel = ref_e - ref_e[0]
+ pred_e_rel = pred_e - pred_e[0]
+ energy_error = pred_e_rel - ref_e_rel
+
+ ref_f = np.asarray([s.arrays["ref_forces"] for s in structs], dtype=float)
+ pred_f = np.asarray([s.arrays["pred_forces"] for s in structs], dtype=float)
+ force_error = pred_f - ref_f
+
+ x = [float(s.info.get("image_index", idx)) for idx, s in enumerate(structs)]
+ return _Results(
+ energy_mae=mae(ref_e_rel, pred_e_rel),
+ force_mae=mae(ref_f.reshape(-1), pred_f.reshape(-1)),
+ x=x,
+ energy_error=[float(v) for v in energy_error],
+ force_rms=[float(v) for v in np.sqrt(np.mean(force_error**2, axis=(1, 2)))],
+ structs=structs,
+ )
+
+
+def _write_assets(case_key: str, model: str, results: _Results) -> None:
+ """
+ Write structure trajectory and per-image CSV for the app.
+
+ Parameters
+ ----------
+ case_key
+ Case key.
+ model
+ Model name.
+ results
+ Computed errors and frames.
+ """
+ out_dir = OUT_PATH / case_key / model
+ out_dir.mkdir(parents=True, exist_ok=True)
+ write(out_dir / f"{model}-neb-band.extxyz", results.structs)
+ pd.DataFrame(
+ {
+ "image": results.x,
+ "energy_error_ev": results.energy_error,
+ "force_rms_ev_per_ang": results.force_rms,
+ }
+ ).to_csv(out_dir / f"{model}-per_image_errors.csv", index=False)
+
+
+def _write_plots(case_key: str, case_label: str, model: str, results: _Results) -> None:
+ """
+ Write Dash/Plotly JSON plots for one (case, model) pair.
+
+ Parameters
+ ----------
+ case_key
+ Case key.
+ case_label
+ Human-friendly case label.
+ model
+ Model name.
+ results
+ Computed errors and frames.
+ """
+ OUT_PATH.mkdir(parents=True, exist_ok=True)
+
+ @plot_scatter(
+ filename=OUT_PATH / f"figure_{model}_{case_key}_energy_error.json",
+ title=f"Energy error along NEB ({case_label})",
+ x_label="Image",
+ y_label="Energy error / eV",
+ show_line=True,
+ )
+ def plot_energy() -> dict[str, tuple[list[float], list[float]]]:
+ """
+ Plot per-image energy errors for a single model and case.
+
+ Returns
+ -------
+ dict[str, tuple[list[float], list[float]]]
+ Mapping of model name to x/y arrays.
+ """
+ return {model: [results.x, results.energy_error]}
+
+ @plot_scatter(
+ filename=OUT_PATH / f"figure_{model}_{case_key}_force_rms.json",
+ title=f"Force RMS error along NEB ({case_label})",
+ x_label="Image",
+ y_label="Force RMS error / (eV/Å)",
+ show_line=True,
+ )
+ def plot_forces() -> dict[str, tuple[list[float], list[float]]]:
+ """
+ Plot per-image force RMS errors for a single model and case.
+
+ Returns
+ -------
+ dict[str, tuple[list[float], list[float]]]
+ Mapping of model name to x/y arrays.
+ """
+ return {model: [results.x, results.force_rms]}
+
+ plot_energy()
+ plot_forces()
+
+
+@pytest.fixture
+def case_results() -> dict[tuple[str, str], _Results]:
+ """
+ Compute results for all available (case, model) combinations.
+
+ Returns
+ -------
+ dict[tuple[str, str], _Results]
+ Results indexed by ``(case_key, model_name)``.
+ """
+ OUT_PATH.mkdir(parents=True, exist_ok=True)
+ results: dict[tuple[str, str], _Results] = {}
+ for case in CASES:
+ for model in MODELS:
+ structs = _load_structs(case.key, model)
+ if structs is None:
+ continue
+ computed = _compute(structs)
+ _write_assets(case.key, model, computed)
+ _write_plots(case.key, case.label, model, computed)
+ results[(case.key, model)] = computed
+ return results
+
+
+@pytest.fixture
+def metrics_dict(
+ case_results: dict[tuple[str, str], _Results],
+) -> dict[str, dict[str, float]]:
+ """
+ Build raw metric dict for the benchmark table.
+
+ Parameters
+ ----------
+ case_results
+ Results indexed by ``(case_key, model_name)``.
+
+ Returns
+ -------
+ dict[str, dict[str, float]]
+ Metric values for all models.
+ """
+ metrics: dict[str, dict[str, float]] = {}
+ for case in CASES:
+ energy_key = f"Energy MAE ({case.label})"
+ force_key = f"Force MAE ({case.label})"
+ metrics[energy_key] = {}
+ metrics[force_key] = {}
+ for model in MODELS:
+ result = case_results.get((case.key, model))
+ if result is None:
+ continue
+ metrics[energy_key][model] = result.energy_mae
+ metrics[force_key][model] = result.force_mae
+ return metrics
+
+
+@pytest.fixture
+@build_table(
+ filename=OUT_PATH / f"{BENCHMARK_DIR}_metrics_table.json",
+ metric_tooltips=DEFAULT_TOOLTIPS,
+ thresholds=DEFAULT_THRESHOLDS,
+ weights=DEFAULT_WEIGHTS,
+)
+def metrics(metrics_dict: dict[str, dict[str, float]]) -> dict[str, dict]:
+ """
+ Build the benchmark table JSON.
+
+ Parameters
+ ----------
+ metrics_dict
+ Metric values for all models.
+
+ Returns
+ -------
+ dict[str, dict]
+ Metric names and values for all models.
+ """
+ return metrics_dict
+
+
+def test_si_defects(metrics: dict[str, dict]) -> None:
+ """
+ Run analysis for Si defects DFT singlepoints.
+
+ Parameters
+ ----------
+ metrics
+ Benchmark metrics table.
+ """
+ return
diff --git a/ml_peg/analysis/nebs/si_defects/metrics.yml b/ml_peg/analysis/nebs/si_defects/metrics.yml
new file mode 100644
index 000000000..fdd5cb755
--- /dev/null
+++ b/ml_peg/analysis/nebs/si_defects/metrics.yml
@@ -0,0 +1,37 @@
+metrics:
+ Energy MAE (64):
+ good: 0.02
+ bad: 0.2
+ unit: eV
+ tooltip: "MAE between MLIP and DFT (PBE) relative single-point energies along the NEB (image 0 shifted to 0 eV)."
+ level_of_theory: PBE
+ Force MAE (64):
+ good: 0.05
+ bad: 0.5
+ unit: eV/Å
+ tooltip: "MAE between MLIP and DFT (PBE) single-point forces across all atoms and images along the NEB."
+ level_of_theory: PBE
+ Energy MAE (216):
+ good: 0.02
+ bad: 0.2
+ unit: eV
+ tooltip: "MAE between MLIP and DFT (PBE) relative single-point energies along the NEB (image 0 shifted to 0 eV)."
+ level_of_theory: PBE
+ Force MAE (216):
+ good: 0.05
+ bad: 0.5
+ unit: eV/Å
+ tooltip: "MAE between MLIP and DFT (PBE) single-point forces across all atoms and images along the NEB."
+ level_of_theory: PBE
+ Energy MAE (216 di-to-single):
+ good: 0.02
+ bad: 0.2
+ unit: eV
+ tooltip: "MAE between MLIP and DFT (PBE) relative single-point energies along the NEB (image 0 shifted to 0 eV)."
+ level_of_theory: PBE
+ Force MAE (216 di-to-single):
+ good: 0.05
+ bad: 0.5
+ unit: eV/Å
+ tooltip: "MAE between MLIP and DFT (PBE) single-point forces across all atoms and images along the NEB."
+ level_of_theory: PBE
diff --git a/ml_peg/analysis/non_covalent_interactions/IONPI19/analyse_IONPI19.py b/ml_peg/analysis/non_covalent_interactions/IONPI19/analyse_IONPI19.py
index 92c6d6491..bdb21d5b0 100644
--- a/ml_peg/analysis/non_covalent_interactions/IONPI19/analyse_IONPI19.py
+++ b/ml_peg/analysis/non_covalent_interactions/IONPI19/analyse_IONPI19.py
@@ -10,7 +10,7 @@
from ml_peg.analysis.utils.decorators import build_table, plot_parity
from ml_peg.analysis.utils.utils import (
- build_d3_name_map,
+ build_dispersion_name_map,
load_metrics_config,
mae,
)
@@ -20,7 +20,7 @@
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
@@ -166,7 +166,7 @@ def get_mae(conformer_energies) -> dict[str, float]:
filename=OUT_PATH / "ionpi19_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_D1200/analyse_NCIA_D1200.py b/ml_peg/analysis/non_covalent_interactions/NCIA_D1200/analyse_NCIA_D1200.py
index 7e33b47e6..b30930574 100644
--- a/ml_peg/analysis/non_covalent_interactions/NCIA_D1200/analyse_NCIA_D1200.py
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_D1200/analyse_NCIA_D1200.py
@@ -13,9 +13,10 @@
plot_density_scatter,
)
from ml_peg.analysis.utils.utils import (
- build_d3_name_map,
+ build_dispersion_name_map,
load_metrics_config,
mae,
+ write_density_trajectories,
)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
@@ -23,7 +24,7 @@
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_D1200" / "outputs"
@@ -104,6 +105,7 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
Mapping of model names to density-plot payloads.
"""
ref_vals = interaction_energies["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = interaction_energies.get(model_name, [])
@@ -112,6 +114,14 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}.xyz",
+ )
return density_inputs
@@ -143,7 +153,7 @@ def get_mae(interaction_energies) -> dict[str, float]:
filename=OUT_PATH / "ncia_d1200_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_D442x10/analyse_NCIA_D442x10.py b/ml_peg/analysis/non_covalent_interactions/NCIA_D442x10/analyse_NCIA_D442x10.py
index feacb87b6..fa9f38bbf 100644
--- a/ml_peg/analysis/non_covalent_interactions/NCIA_D442x10/analyse_NCIA_D442x10.py
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_D442x10/analyse_NCIA_D442x10.py
@@ -13,9 +13,10 @@
plot_density_scatter,
)
from ml_peg.analysis.utils.utils import (
- build_d3_name_map,
+ build_dispersion_name_map,
load_metrics_config,
mae,
+ write_density_trajectories,
)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
@@ -23,7 +24,7 @@
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_D442x10" / "outputs"
@@ -104,6 +105,7 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
Mapping of model names to density-plot inputs.
"""
ref_vals = interaction_energies["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = interaction_energies.get(model_name, [])
@@ -112,6 +114,14 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}.xyz",
+ )
return density_inputs
@@ -143,7 +153,7 @@ def get_mae(interaction_energies) -> dict[str, float]:
filename=OUT_PATH / "ncia_d442x10_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/analyse_NCIA_HB300SPXx10.py b/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/analyse_NCIA_HB300SPXx10.py
index fc62b9669..8a4cf3670 100644
--- a/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/analyse_NCIA_HB300SPXx10.py
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/analyse_NCIA_HB300SPXx10.py
@@ -12,14 +12,19 @@
build_table,
plot_density_scatter,
)
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+ write_density_trajectories,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_HB300SPXx10" / "outputs"
@@ -100,6 +105,7 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
Mapping of model names to density-plot payloads.
"""
ref_vals = interaction_energies["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = interaction_energies.get(model_name, [])
@@ -108,6 +114,14 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}.xyz",
+ )
return density_inputs
@@ -139,7 +153,7 @@ def get_mae(interaction_energies) -> dict[str, float]:
filename=OUT_PATH / "ncia_hb300spxx10_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_HB375x10/analyse_NCIA_HB375x10.py b/ml_peg/analysis/non_covalent_interactions/NCIA_HB375x10/analyse_NCIA_HB375x10.py
index c709ea493..a9282f12e 100644
--- a/ml_peg/analysis/non_covalent_interactions/NCIA_HB375x10/analyse_NCIA_HB375x10.py
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_HB375x10/analyse_NCIA_HB375x10.py
@@ -12,14 +12,19 @@
build_table,
plot_density_scatter,
)
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+ write_density_trajectories,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_HB375x10" / "outputs"
@@ -100,6 +105,7 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
Mapping of model names to density-plot payloads.
"""
ref_vals = interaction_energies["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = interaction_energies.get(model_name, [])
@@ -108,6 +114,14 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}.xyz",
+ )
return density_inputs
@@ -139,7 +153,7 @@ def get_mae(interaction_energies) -> dict[str, float]:
filename=OUT_PATH / "ncia_hb375x10_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_IHB100x10/analyse_NCIA_IHB100x10.py b/ml_peg/analysis/non_covalent_interactions/NCIA_IHB100x10/analyse_NCIA_IHB100x10.py
index 778c50042..6ae6c6d88 100644
--- a/ml_peg/analysis/non_covalent_interactions/NCIA_IHB100x10/analyse_NCIA_IHB100x10.py
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_IHB100x10/analyse_NCIA_IHB100x10.py
@@ -12,14 +12,19 @@
build_table,
plot_density_scatter,
)
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+ write_density_trajectories,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_IHB100x10" / "outputs"
@@ -100,6 +105,7 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
Mapping of model names to density-plot payloads.
"""
ref_vals = interaction_energies["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = interaction_energies.get(model_name, [])
@@ -108,6 +114,14 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}.xyz",
+ )
return density_inputs
@@ -139,7 +153,7 @@ def get_mae(interaction_energies) -> dict[str, float]:
filename=OUT_PATH / "ncia_ihb100x10_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_R739x5/analyse_NCIA_R739x5.py b/ml_peg/analysis/non_covalent_interactions/NCIA_R739x5/analyse_NCIA_R739x5.py
index 333e01f2e..c7b7336c1 100644
--- a/ml_peg/analysis/non_covalent_interactions/NCIA_R739x5/analyse_NCIA_R739x5.py
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_R739x5/analyse_NCIA_R739x5.py
@@ -12,14 +12,19 @@
build_table,
plot_density_scatter,
)
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+ write_density_trajectories,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_R739x5" / "outputs"
@@ -100,6 +105,7 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
Mapping of model names to density-plot payloads.
"""
ref_vals = interaction_energies["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = interaction_energies.get(model_name, [])
@@ -108,6 +114,14 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}.xyz",
+ )
return density_inputs
@@ -139,7 +153,7 @@ def get_mae(interaction_energies) -> dict[str, float]:
filename=OUT_PATH / "ncia_r739x5_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_SH250x10/analyse_NCIA_SH250x10.py b/ml_peg/analysis/non_covalent_interactions/NCIA_SH250x10/analyse_NCIA_SH250x10.py
index f623ae9eb..d51aabe84 100644
--- a/ml_peg/analysis/non_covalent_interactions/NCIA_SH250x10/analyse_NCIA_SH250x10.py
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_SH250x10/analyse_NCIA_SH250x10.py
@@ -12,14 +12,19 @@
build_table,
plot_density_scatter,
)
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+ write_density_trajectories,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_SH250x10" / "outputs"
@@ -100,6 +105,7 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
Mapping of model names to density-plot payloads.
"""
ref_vals = interaction_energies["ref"]
+ label_list = labels()
density_inputs: dict[str, dict] = {}
for model_name in MODELS:
preds = interaction_energies.get(model_name, [])
@@ -108,6 +114,14 @@ def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict
"pred": preds,
"meta": {"system_count": len([val for val in preds if val is not None])},
}
+ write_density_trajectories(
+ labels_list=label_list,
+ ref_vals=ref_vals,
+ pred_vals=preds,
+ struct_dir=OUT_PATH / model_name,
+ traj_dir=OUT_PATH / model_name / "density_traj",
+ struct_filename_builder=lambda label: f"{label}.xyz",
+ )
return density_inputs
@@ -139,7 +153,7 @@ def get_mae(interaction_energies) -> dict[str, float]:
filename=OUT_PATH / "ncia_sh250x10_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/non_covalent_interactions/QUID/analyse_QUID.py b/ml_peg/analysis/non_covalent_interactions/QUID/analyse_QUID.py
new file mode 100644
index 000000000..687b68f38
--- /dev/null
+++ b/ml_peg/analysis/non_covalent_interactions/QUID/analyse_QUID.py
@@ -0,0 +1,245 @@
+"""
+Analyse the QUID benchmark for ligand-pocket interactions.
+
+Puleva, M., Medrano Sandonas, L., Lőrincz, B.D. et al,
+Extending quantum-mechanical benchmark accuracy to biological ligand-pocket
+interactions,
+Nat Commun 16, 8583 (2025). https://doi.org/10.1038/s41467-025-63587-9
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from ase import units
+from ase.io import read, write
+import pytest
+
+from ml_peg.analysis.utils.decorators import build_table, plot_parity
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
+from ml_peg.app import APP_ROOT
+from ml_peg.calcs import CALCS_ROOT
+from ml_peg.models.get_models import load_models
+from ml_peg.models.models import current_models
+
+MODELS = load_models(current_models)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
+
+CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "QUID" / "outputs"
+OUT_PATH = APP_ROOT / "data" / "non_covalent_interactions" / "QUID"
+
+METRICS_CONFIG_PATH = Path(__file__).with_name("metrics.yml")
+DEFAULT_THRESHOLDS, DEFAULT_TOOLTIPS, DEFAULT_WEIGHTS = load_metrics_config(
+ METRICS_CONFIG_PATH
+)
+
+EV_TO_KCAL = units.mol / units.kcal
+
+
+def labels() -> dict[str, list[int]]:
+ """
+ Get dictionary of info for QUID structures.
+
+ Returns
+ -------
+ dict[str, list[int]]
+ Dictionary of system indices, complex atom counts, and complex charges.
+ """
+ info = {"all": [], "equilibrium": [], "dissociation": []}
+
+ for model_name in MODELS:
+ model_dir = CALC_PATH / model_name
+ if model_dir.exists():
+ xyz_files = sorted(model_dir.glob("*.xyz"))
+
+ info["all"] = [path.stem for path in xyz_files]
+ info["equilibrium"] = [label for label in info["all"] if "_" not in label]
+ info["dissociation"] = [label for label in info["all"] if "_" in label]
+
+ return info
+
+
+LABELS = labels()
+
+
+@pytest.fixture
+@plot_parity(
+ filename=OUT_PATH / "figure_quid.json",
+ title="Interaction energies",
+ x_label="Predicted energy / kcal/mol",
+ y_label="Reference energy / kcal/mol",
+ hoverdata={"Labels": LABELS["all"]},
+)
+def interaction_energies() -> dict[str, list]:
+ """
+ Get interaction energies for all systems.
+
+ Returns
+ -------
+ dict[str, list]
+ Dictionary of all reference and predicted interaction energies.
+ """
+ results = {"ref": []} | {mlip: [] for mlip in MODELS}
+
+ ref_stored = False
+
+ for model_name in MODELS:
+ for label in LABELS["all"]:
+ atoms = read(CALC_PATH / model_name / f"{label}.xyz", index=0)
+
+ if not ref_stored:
+ results["ref"].append(atoms.info["ref_int_energy"][()] * EV_TO_KCAL)
+
+ results[model_name].append(atoms.info["model_int_energy"][()] * EV_TO_KCAL)
+
+ # Write structures for app
+ structs_dir = OUT_PATH / model_name
+ structs_dir.mkdir(parents=True, exist_ok=True)
+ write(structs_dir / f"{label}.xyz", atoms)
+
+ ref_stored = True
+ return results
+
+
+@pytest.fixture
+def total_mae(interaction_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for energies for all systems.
+
+ Parameters
+ ----------
+ interaction_energies
+ Dictionary of reference and predicted energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted energy errors for all models.
+ """
+ results = {}
+ for model_name in MODELS:
+ results[model_name] = mae(
+ interaction_energies["ref"], interaction_energies[model_name]
+ )
+ return results
+
+
+@pytest.fixture
+def equilibrium_mae(interaction_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for charged systems only.
+
+ Parameters
+ ----------
+ interaction_energies
+ Dictionary of reference and predicted interaction energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted interaction energy errors for charged systems.
+ """
+ equilibrium_indices = [
+ i for i, label in enumerate(LABELS["all"]) if label in LABELS["equilibrium"]
+ ]
+
+ results = {}
+ for model_name in MODELS:
+ if interaction_energies[model_name]:
+ ref_equilibrium = [
+ interaction_energies["ref"][i] for i in equilibrium_indices
+ ]
+ pred_equilibrium = [
+ interaction_energies[model_name][i] for i in equilibrium_indices
+ ]
+ results[model_name] = mae(ref_equilibrium, pred_equilibrium)
+ else:
+ results[model_name] = None
+ return results
+
+
+@pytest.fixture
+def dissociation_mae(interaction_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for dissociation systems only.
+
+ Parameters
+ ----------
+ interaction_energies
+ Dictionary of reference and predicted interaction energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted interaction energy errors for dissociation systems.
+ """
+ dissociation_indices = [
+ i for i, label in enumerate(LABELS["all"]) if label in LABELS["dissociation"]
+ ]
+
+ results = {}
+ for model_name in MODELS:
+ if interaction_energies[model_name]:
+ ref_dissociation = [
+ interaction_energies["ref"][i] for i in dissociation_indices
+ ]
+ pred_dissociation = [
+ interaction_energies[model_name][i] for i in dissociation_indices
+ ]
+ results[model_name] = mae(ref_dissociation, pred_dissociation)
+ else:
+ results[model_name] = None
+ return results
+
+
+@pytest.fixture
+@build_table(
+ filename=OUT_PATH / "quid_metrics_table.json",
+ metric_tooltips=DEFAULT_TOOLTIPS,
+ thresholds=DEFAULT_THRESHOLDS,
+ weights=DEFAULT_WEIGHTS,
+ mlip_name_map=DISPERSION_NAME_MAP,
+)
+def metrics(
+ total_mae: dict[str, float],
+ equilibrium_mae: dict[str, float],
+ dissociation_mae: dict[str, float],
+) -> dict[str, dict]:
+ """
+ Get all metrics.
+
+ Parameters
+ ----------
+ total_mae
+ Mean absolute errors for all models.
+ equilibrium_mae
+ Mean absolute errors for all models for equilibrium systems.
+ dissociation_mae
+ Mean absolute errors for all models for dissociation systems.
+
+ Returns
+ -------
+ dict[str, dict]
+ Metric names and values for all models.
+ """
+ return {
+ "Equilibrium MAE": equilibrium_mae,
+ "Dissociation MAE": dissociation_mae,
+ "Overall MAE": total_mae,
+ }
+
+
+def test_quid(metrics: dict[str, dict]) -> None:
+ """
+ Run QUID test.
+
+ Parameters
+ ----------
+ metrics
+ All new benchmark metric names and dictionary of values for each model.
+ """
+ return
diff --git a/ml_peg/analysis/non_covalent_interactions/QUID/metrics.yml b/ml_peg/analysis/non_covalent_interactions/QUID/metrics.yml
new file mode 100644
index 000000000..f1aed47a1
--- /dev/null
+++ b/ml_peg/analysis/non_covalent_interactions/QUID/metrics.yml
@@ -0,0 +1,22 @@
+metrics:
+ Overall MAE:
+ good: 0.3
+ bad: 2.0
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for all systems
+ level_of_theory: CCSD(T)
+ weight: 1
+ Equilibrium MAE:
+ good: 0.3
+ bad: 2.0
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for neutral systems
+ level_of_theory: CCSD(T)
+ weight: 0
+ Dissociation MAE:
+ good: 0.3
+ bad: 2.0
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for charged systems
+ level_of_theory: CCSD(T)
+ weight: 0
diff --git a/ml_peg/analysis/supramolecular/PLA15/analyse_PLA15.py b/ml_peg/analysis/supramolecular/PLA15/analyse_PLA15.py
index f8da46021..1fb5c79d0 100644
--- a/ml_peg/analysis/supramolecular/PLA15/analyse_PLA15.py
+++ b/ml_peg/analysis/supramolecular/PLA15/analyse_PLA15.py
@@ -9,14 +9,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "supramolecular" / "PLA15" / "outputs"
OUT_PATH = APP_ROOT / "data" / "supramolecular" / "PLA15"
@@ -258,7 +262,7 @@ def pla15_ion_neutral_mae(interaction_energies) -> dict[str, float]:
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
weights=DEFAULT_WEIGHTS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(
pla15_mae: dict[str, float],
diff --git a/ml_peg/analysis/supramolecular/PLF547/analyse_PLF547.py b/ml_peg/analysis/supramolecular/PLF547/analyse_PLF547.py
index d7ca36b5d..d5b716f8e 100755
--- a/ml_peg/analysis/supramolecular/PLF547/analyse_PLF547.py
+++ b/ml_peg/analysis/supramolecular/PLF547/analyse_PLF547.py
@@ -9,14 +9,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "supramolecular" / "PLF547" / "outputs"
OUT_PATH = APP_ROOT / "data" / "supramolecular" / "PLF547"
@@ -193,7 +197,7 @@ def neutral_mae(interaction_energies) -> dict[str, float]:
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
weights=DEFAULT_WEIGHTS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(
total_mae: dict[str, float],
diff --git a/ml_peg/analysis/supramolecular/S30L/analyse_S30L.py b/ml_peg/analysis/supramolecular/S30L/analyse_S30L.py
index a2b66e92f..82b53053f 100644
--- a/ml_peg/analysis/supramolecular/S30L/analyse_S30L.py
+++ b/ml_peg/analysis/supramolecular/S30L/analyse_S30L.py
@@ -9,14 +9,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "supramolecular" / "S30L" / "outputs"
OUT_PATH = APP_ROOT / "data" / "supramolecular" / "S30L"
@@ -221,7 +225,7 @@ def s30l_neutral_mae(interaction_energies) -> dict[str, float]:
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
weights=DEFAULT_WEIGHTS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(
s30l_mae: dict[str, float],
diff --git a/ml_peg/analysis/surfaces/OC157/analyse_OC157.py b/ml_peg/analysis/surfaces/OC157/analyse_OC157.py
index 96a932930..a0b447560 100644
--- a/ml_peg/analysis/surfaces/OC157/analyse_OC157.py
+++ b/ml_peg/analysis/surfaces/OC157/analyse_OC157.py
@@ -9,14 +9,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "surfaces" / "OC157" / "outputs"
OUT_PATH = APP_ROOT / "data" / "surfaces" / "OC157"
@@ -186,7 +190,7 @@ def ranking_error(relative_energies: dict[str, list]) -> dict[str, float]:
filename=OUT_PATH / "oc157_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(
oc157_mae: dict[str, float], ranking_error: dict[str, float]
diff --git a/ml_peg/analysis/surfaces/S24/analyse_S24.py b/ml_peg/analysis/surfaces/S24/analyse_S24.py
index 9d8f0aef7..e3966f852 100644
--- a/ml_peg/analysis/surfaces/S24/analyse_S24.py
+++ b/ml_peg/analysis/surfaces/S24/analyse_S24.py
@@ -8,14 +8,18 @@
import pytest
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
from ml_peg.app import APP_ROOT
from ml_peg.calcs import CALCS_ROOT
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
MODELS = get_model_names(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
CALC_PATH = CALCS_ROOT / "surfaces" / "S24" / "outputs"
OUT_PATH = APP_ROOT / "data" / "surfaces" / "S24"
@@ -165,7 +169,7 @@ def s24_mae(adsorption_energies) -> dict[str, float]:
filename=OUT_PATH / "s24_metrics_table.json",
metric_tooltips=DEFAULT_TOOLTIPS,
thresholds=DEFAULT_THRESHOLDS,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics(s24_mae: dict[str, float]) -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/tm_complexes/3dTMV/analyse_3dTMV.py b/ml_peg/analysis/tm_complexes/3dTMV/analyse_3dTMV.py
new file mode 100644
index 000000000..0391cfa50
--- /dev/null
+++ b/ml_peg/analysis/tm_complexes/3dTMV/analyse_3dTMV.py
@@ -0,0 +1,283 @@
+"""Analyse the 3dTMV benchmark."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from ase import units
+from ase.io import read, write
+import pytest
+
+from ml_peg.analysis.utils.decorators import (
+ build_table,
+ plot_parity,
+)
+from ml_peg.analysis.utils.utils import (
+ build_dispersion_name_map,
+ load_metrics_config,
+ mae,
+)
+from ml_peg.app import APP_ROOT
+from ml_peg.calcs import CALCS_ROOT
+from ml_peg.models.get_models import load_models
+from ml_peg.models.models import current_models
+
+MODELS = load_models(current_models)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
+
+EV_TO_KCAL = units.mol / units.kcal
+CALC_PATH = CALCS_ROOT / "tm_complexes" / "3dTMV" / "outputs"
+OUT_PATH = APP_ROOT / "data" / "tm_complexes" / "3dTMV"
+
+METRICS_CONFIG_PATH = Path(__file__).with_name("metrics.yml")
+DEFAULT_THRESHOLDS, DEFAULT_TOOLTIPS, DEFAULT_WEIGHTS = load_metrics_config(
+ METRICS_CONFIG_PATH
+)
+
+SUBSETS = {
+ 1: "SR",
+ 2: "SR",
+ 3: "SR",
+ 4: "SR",
+ 5: "SR",
+ 6: "SR",
+ 7: "SR",
+ 8: "SR",
+ 9: "SR",
+ 10: "SR",
+ 11: "SR",
+ 12: "SR",
+ 13: "SR/MR",
+ 14: "SR/MR",
+ 15: "SR/MR",
+ 16: "SR/MR",
+ 17: "SR/MR",
+ 18: "SR/MR",
+ 19: "SR/MR",
+ 20: "SR/MR",
+ 21: "SR/MR",
+ 22: "SR/MR",
+ 23: "MR",
+ 24: "MR",
+ 25: "MR",
+ 26: "MR",
+ 27: "MR",
+ 28: "MR",
+}
+
+
+def labels():
+ """
+ Get complex ids.
+
+ Returns
+ -------
+ list
+ IDs of the complexes.
+ """
+ return list(range(1, 29))
+
+
+@pytest.fixture
+@plot_parity(
+ filename=OUT_PATH / "figure_3dtmv.json",
+ title="Ionization energies",
+ x_label="Predicted ionization energy / kcal/mol",
+ y_label="Reference ionization energy / kcal/mol",
+ hoverdata={
+ "Labels": labels(),
+ },
+)
+def ionization_energies() -> dict[str, list]:
+ """
+ Get ionization energies for all systems.
+
+ Returns
+ -------
+ dict[str, list]
+ Dictionary of all reference and predicted energies.
+ """
+ results = {"ref": []} | {mlip: [] for mlip in MODELS}
+ ref_stored = False
+
+ for model_name in MODELS:
+ for complex_id in labels():
+ atoms = read(CALC_PATH / model_name / f"{complex_id}.xyz")
+ model_ion_energy = atoms.info["model_ionization_energy"]
+ ref_ion_energy = atoms.info["ref_ionization_energy"]
+ # Write structures for app
+ structs_dir = OUT_PATH / model_name
+ structs_dir.mkdir(parents=True, exist_ok=True)
+ write(structs_dir / f"{complex_id}.xyz", atoms)
+ results[model_name].append(model_ion_energy * EV_TO_KCAL)
+ if not ref_stored:
+ results["ref"].append(ref_ion_energy * EV_TO_KCAL)
+ ref_stored = True
+ return results
+
+
+@pytest.fixture
+def sr_mae(ionization_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for SR subset.
+
+ Parameters
+ ----------
+ ionization_energies
+ Dictionary of reference and predicted energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted energy errors for all models.
+ """
+ results = {}
+
+ for model_name in MODELS:
+ subsampled_ref_e = [
+ ionization_energies["ref"][i - 1] for i in labels() if SUBSETS[i] == "SR"
+ ]
+ subsampled_model_e = [
+ ionization_energies[model_name][i - 1]
+ for i in labels()
+ if SUBSETS[i] == "SR"
+ ]
+ results[model_name] = mae(subsampled_ref_e, subsampled_model_e)
+ return results
+
+
+@pytest.fixture
+def mr_mae(ionization_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for MR subset.
+
+ Parameters
+ ----------
+ ionization_energies
+ Dictionary of reference and predicted energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted energy errors for all models.
+ """
+ results = {}
+
+ for model_name in MODELS:
+ subsampled_ref_e = [
+ ionization_energies["ref"][i - 1] for i in labels() if SUBSETS[i] == "MR"
+ ]
+ subsampled_model_e = [
+ ionization_energies[model_name][i - 1]
+ for i in labels()
+ if SUBSETS[i] == "MR"
+ ]
+ results[model_name] = mae(subsampled_ref_e, subsampled_model_e)
+ return results
+
+
+@pytest.fixture
+def sr_mr_mae(ionization_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for SR/MR subset.
+
+ Parameters
+ ----------
+ ionization_energies
+ Dictionary of reference and predicted energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted energy errors for all models.
+ """
+ results = {}
+
+ for model_name in MODELS:
+ subsampled_ref_e = [
+ ionization_energies["ref"][i - 1] for i in labels() if SUBSETS[i] == "SR/MR"
+ ]
+ subsampled_model_e = [
+ ionization_energies[model_name][i - 1]
+ for i in labels()
+ if SUBSETS[i] == "SR/MR"
+ ]
+ results[model_name] = mae(subsampled_ref_e, subsampled_model_e)
+ return results
+
+
+@pytest.fixture
+def total_mae(ionization_energies) -> dict[str, float]:
+ """
+ Get mean absolute error for all conmplexes.
+
+ Parameters
+ ----------
+ ionization_energies
+ Dictionary of reference and predicted energies.
+
+ Returns
+ -------
+ dict[str, float]
+ Dictionary of predicted energy errors for all models.
+ """
+ results = {}
+
+ for model_name in MODELS:
+ results[model_name] = mae(
+ ionization_energies["ref"], ionization_energies[model_name]
+ )
+ return results
+
+
+@pytest.fixture
+@build_table(
+ filename=OUT_PATH / "3dtmv_metrics_table.json",
+ metric_tooltips=DEFAULT_TOOLTIPS,
+ thresholds=DEFAULT_THRESHOLDS,
+ mlip_name_map=DISPERSION_NAME_MAP,
+ weights=DEFAULT_WEIGHTS,
+)
+def metrics(
+ total_mae: dict[str, float],
+ sr_mae: dict[str, float],
+ mr_mae: dict[str, float],
+ sr_mr_mae: dict[str, float],
+) -> dict[str, dict]:
+ """
+ Get all metrics.
+
+ Parameters
+ ----------
+ total_mae
+ Mean absolute errors for all models, all complexes.
+ sr_mae
+ Mean absolute errors for all models, single-reference complexes.
+ mr_mae
+ Mean absolute errors for all models, multi-reference complexes.
+ sr_mr_mae
+ Mean absolute errors for all models, intermediate complexes.
+
+ Returns
+ -------
+ dict[str, dict]
+ Metric names and values for all models.
+ """
+ return {
+ "Overall MAE": total_mae,
+ "SR MAE": sr_mae,
+ "MR MAE": mr_mae,
+ "SR/MR MAE": sr_mr_mae,
+ }
+
+
+def test_3dtmv(metrics: dict[str, dict]) -> None:
+ """
+ Run 3dTMV test.
+
+ Parameters
+ ----------
+ metrics
+ All new benchmark metric names and dictionary of values for each model.
+ """
+ return
diff --git a/ml_peg/analysis/tm_complexes/3dTMV/metrics.yml b/ml_peg/analysis/tm_complexes/3dTMV/metrics.yml
new file mode 100644
index 000000000..0d7ba50b3
--- /dev/null
+++ b/ml_peg/analysis/tm_complexes/3dTMV/metrics.yml
@@ -0,0 +1,29 @@
+metrics:
+ Overall MAE:
+ good: 0.0
+ bad: 50
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for all systems
+ level_of_theory: ph-AFQMC
+ weight: 1
+ SR MAE:
+ good: 0.0
+ bad: 50
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for the single reference (SR) subset
+ level_of_theory: ph-AFQMC
+ weight: 0
+ MR MAE:
+ good: 0.0
+ bad: 50
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for the multireference (MR) subset
+ level_of_theory: ph-AFQMC
+ weight: 0
+ SR/MR MAE:
+ good: 0.0
+ bad: 50
+ unit: kcal/mol
+ tooltip: Mean Absolute Error for the SR/MR (intermediate category) subset
+ level_of_theory: ph-AFQMC
+ weight: 0
diff --git a/ml_peg/analysis/utils/analyse_gscdb138.py b/ml_peg/analysis/utils/analyse_gscdb138.py
index cdffc72da..6c943c519 100644
--- a/ml_peg/analysis/utils/analyse_gscdb138.py
+++ b/ml_peg/analysis/utils/analyse_gscdb138.py
@@ -8,13 +8,13 @@
from ase.io import read, write
from ml_peg.analysis.utils.decorators import build_table, plot_parity
-from ml_peg.analysis.utils.utils import build_d3_name_map, mae
+from ml_peg.analysis.utils.utils import build_dispersion_name_map, mae
from ml_peg.app.utils.utils import Thresholds
from ml_peg.models.get_models import load_models
from ml_peg.models.models import current_models
MODELS = load_models(current_models)
-D3_MODEL_NAMES = build_d3_name_map(MODELS)
+DISPERSION_NAME_MAP = build_dispersion_name_map(MODELS)
EV_TO_KCAL = units.mol / units.kcal
@@ -176,7 +176,7 @@ def get_gscdb138_metrics(
metric_tooltips=metric_tooltips,
thresholds=thresholds,
weights=weights,
- mlip_name_map=D3_MODEL_NAMES,
+ mlip_name_map=DISPERSION_NAME_MAP,
)
def metrics() -> dict[str, dict]:
"""
diff --git a/ml_peg/analysis/utils/decorators.py b/ml_peg/analysis/utils/decorators.py
index cdcc72ba8..05a098931 100644
--- a/ml_peg/analysis/utils/decorators.py
+++ b/ml_peg/analysis/utils/decorators.py
@@ -2,7 +2,6 @@
from __future__ import annotations
-from collections import defaultdict
from collections.abc import Callable
import functools
import json
@@ -15,7 +14,13 @@
import pandas as pd
import plotly.graph_objects as go
-from ml_peg.analysis.utils.utils import calc_table_scores
+from ml_peg.analysis.utils.utils import (
+ DENSITY_GRID_SIZE,
+ DENSITY_MAX_POINTS_PER_CELL,
+ DENSITY_SAMPLE_SEED,
+ calc_table_scores,
+ sample_density_grid,
+)
from ml_peg.app.utils.utils import Thresholds
from ml_peg.models.get_models import get_model_names, load_model_configs
@@ -541,9 +546,9 @@ def plot_density_scatter(
y_label: str | None = None,
filename: str = "density_scatter.json",
colorbar_title: str = "Density",
- grid_size: int = 80,
- max_points_per_cell: int = 5,
- seed: int = 0,
+ grid_size: int = DENSITY_GRID_SIZE,
+ max_points_per_cell: int = DENSITY_MAX_POINTS_PER_CELL,
+ seed: int = DENSITY_SAMPLE_SEED,
hover_metadata: dict[str, str] | None = None,
annotation_metadata: dict[str, str] | None = None,
) -> Callable:
@@ -621,70 +626,6 @@ def plot_density_wrapper(*args, **kwargs) -> dict[str, Any]:
dict
Results dictionary.
"""
-
- def _downsample(
- ref_vals: np.ndarray, pred_vals: np.ndarray
- ) -> tuple[list[float], list[float], list[int]]:
- """
- Downsample data points while keeping dense regions representative.
-
- Parameters
- ----------
- ref_vals
- Reference (x-axis) values for all systems.
- pred_vals
- Predicted (y-axis) values for all systems.
-
- Returns
- -------
- tuple[list[float], list[float], list[int]]
- Downsampled reference values, predicted values, and density counts
- corresponding to each retained point.
- """
- if ref_vals.size == 0:
- return [], [], []
-
- delta_x = ref_vals.max() - ref_vals.min()
- delta_y = pred_vals.max() - pred_vals.min()
- eps = 1e-9
-
- norm_x = np.clip(
- # Normalise to [0, 1). Clamp to avoid hitting the upper bound so
- # bin indices always live in [0, grid_size - 1].
- (ref_vals - ref_vals.min()) / max(delta_x, eps),
- 0.0,
- 0.999999,
- )
- norm_y = np.clip(
- (pred_vals - pred_vals.min()) / max(delta_y, eps),
- 0.0,
- 0.999999,
- )
- bins_x = (norm_x * grid_size).astype(int)
- bins_y = (norm_y * grid_size).astype(int)
- cell_points: dict[tuple[int, int], list[int]] = defaultdict(list)
- for idx, (cx, cy) in enumerate(zip(bins_x, bins_y, strict=True)):
- cell_points[(int(cx), int(cy))].append(idx)
-
- rng = np.random.default_rng(seed)
- sampled_x: list[float] = []
- sampled_y: list[float] = []
- sampled_density: list[int] = []
- for indices in cell_points.values():
- if len(indices) > max_points_per_cell:
- chosen = rng.choice(
- indices, size=max_points_per_cell, replace=False
- )
- else:
- chosen = indices
- density = len(indices)
- for idx in chosen:
- sampled_x.append(float(ref_vals[idx]))
- sampled_y.append(float(pred_vals[idx]))
- sampled_density.append(density)
-
- return sampled_x, sampled_y, sampled_density
-
results = func(*args, **kwargs)
if not isinstance(results, dict):
raise TypeError(
@@ -724,7 +665,16 @@ def _downsample(
if ref_vals.size == 0 or pred_vals.size == 0:
sampled = ([], [], [])
else:
- sampled = _downsample(ref_vals, pred_vals)
+ sampled_indices, sampled_density, _ = sample_density_grid(
+ ref_vals,
+ pred_vals,
+ grid_size=grid_size,
+ max_points_per_cell=max_points_per_cell,
+ seed=seed,
+ )
+ sampled_x = [float(ref_vals[idx]) for idx in sampled_indices]
+ sampled_y = [float(pred_vals[idx]) for idx in sampled_indices]
+ sampled = (sampled_x, sampled_y, sampled_density)
global_min = min(global_min, ref_vals.min(), pred_vals.min())
global_max = max(global_max, ref_vals.max(), pred_vals.max())
diff --git a/ml_peg/analysis/utils/utils.py b/ml_peg/analysis/utils/utils.py
index d317b00f6..ff6c92e73 100644
--- a/ml_peg/analysis/utils/utils.py
+++ b/ml_peg/analysis/utils/utils.py
@@ -2,10 +2,12 @@
from __future__ import annotations
+from collections import defaultdict
from collections.abc import Callable, Iterable
from pathlib import Path
from typing import Any
+from ase.io import read, write
from matplotlib import cm
from matplotlib.colors import Colormap
import numpy as np
@@ -24,31 +26,42 @@
TableRow = dict[str, object]
-def build_d3_name_map(
+def build_dispersion_name_map(
models: Iterable[str],
suffix: str = "-D3",
) -> dict[str, str]:
"""
- Return a suffix map for models requiring runtime D3 corrections.
+ Return a suffix map for models requiring runtime dispersion corrections.
Parameters
----------
models
Iterable of model identifiers to inspect.
suffix
- String appended to model names that need the D3 indicator.
+ String appended to model names that need the dispersion correction indicator.
+ Defaults to "-D3" for D3 dispersion corrections.
Returns
-------
dict[str, str]
- Mapping of model -> display name for models not trained with D3 dispersion.
+ Mapping of model -> display name for models not trained with dispersion.
"""
configs, _ = load_model_configs(tuple(models))
- return {
- model: f"{model}{suffix}"
- for model in models
- if not configs[model]["trained_on_d3"]
- }
+ name_map: dict[str, str] = {}
+
+ for model in models:
+ if configs[model]["trained_on_dispersion"]:
+ continue
+ dispersion_kwargs = configs[model].get("dispersion_kwargs") or {}
+ label = dispersion_kwargs.get("label")
+ suffix_to_use = (
+ label.strip() if isinstance(label, str) and label.strip() else suffix
+ )
+ if not suffix_to_use.startswith("-"):
+ suffix_to_use = f"-{suffix_to_use}"
+ name_map[model] = f"{model}{suffix_to_use}"
+
+ return name_map
def load_metrics_config(config_path: Path) -> tuple[Thresholds, dict[str, str]]:
@@ -165,6 +178,83 @@ def rmse(ref: list, prediction: list) -> float:
return mean_squared_error(ref, prediction)
+DENSITY_GRID_SIZE = 80
+DENSITY_MAX_POINTS_PER_CELL = 5
+DENSITY_SAMPLE_SEED = 0
+
+
+def sample_density_grid(
+ ref_vals: list[float] | np.ndarray,
+ pred_vals: list[float] | np.ndarray,
+ *,
+ grid_size: int = DENSITY_GRID_SIZE,
+ max_points_per_cell: int = DENSITY_MAX_POINTS_PER_CELL,
+ seed: int = DENSITY_SAMPLE_SEED,
+) -> tuple[list[int], list[int], list[list[int]]]:
+ """
+ Sample indices from a density grid, returning density and cell memberships.
+
+ This is the shared implementation used by ``plot_density_scatter`` so the
+ sampling order stays consistent across density-driven artifacts.
+
+ Parameters
+ ----------
+ ref_vals
+ Reference (x-axis) values for all systems, in the same order as the
+ data passed to the density scatter fixture.
+ pred_vals
+ Predicted (y-axis) values, same order as ``ref_vals``.
+ grid_size
+ Number of bins per axis. Must match ``@plot_density_scatter`` default.
+ max_points_per_cell
+ Maximum sampled points per cell. Must match decorator default.
+ seed
+ RNG seed for deterministic sampling. Must match decorator default.
+
+ Returns
+ -------
+ tuple[list[int], list[int], list[list[int]]]
+ ``sampled_indices``: original indices kept in plotting order.
+ ``sampled_density``: density value per sampled index.
+ ``sampled_mapping``: list of source indices for each sampled point.
+ """
+ ref_arr = np.asarray(ref_vals, dtype=float)
+ pred_arr = np.asarray(pred_vals, dtype=float)
+
+ if ref_arr.size == 0 or pred_arr.size == 0:
+ return [], [], []
+
+ delta_x = ref_arr.max() - ref_arr.min()
+ delta_y = pred_arr.max() - pred_arr.min()
+ eps = 1e-9
+
+ norm_x = np.clip((ref_arr - ref_arr.min()) / max(delta_x, eps), 0.0, 0.999999)
+ norm_y = np.clip((pred_arr - pred_arr.min()) / max(delta_y, eps), 0.0, 0.999999)
+ bins_x = (norm_x * grid_size).astype(int)
+ bins_y = (norm_y * grid_size).astype(int)
+
+ cell_points: dict[tuple[int, int], list[int]] = defaultdict(list)
+ for idx, (cx, cy) in enumerate(zip(bins_x, bins_y, strict=True)):
+ cell_points[(int(cx), int(cy))].append(idx)
+
+ rng = np.random.default_rng(seed)
+ sampled_indices: list[int] = []
+ sampled_density: list[int] = []
+ sampled_mapping: list[list[int]] = []
+ for indices in cell_points.values():
+ if len(indices) > max_points_per_cell:
+ chosen = rng.choice(indices, size=max_points_per_cell, replace=False)
+ else:
+ chosen = indices
+ density = len(indices)
+ for idx in chosen:
+ sampled_indices.append(int(idx))
+ sampled_density.append(density)
+ sampled_mapping.append(indices)
+
+ return sampled_indices, sampled_density, sampled_mapping
+
+
def build_density_inputs(
models: list[str],
model_results: dict[str, dict[str, Any]],
@@ -214,6 +304,61 @@ def build_density_inputs(
return inputs
+def write_density_trajectories(
+ *,
+ labels_list: list[str],
+ ref_vals: list[float],
+ pred_vals: list[float],
+ struct_dir: Path,
+ traj_dir: Path,
+ struct_filename_builder: Callable[[str], str],
+ grid_size: int = DENSITY_GRID_SIZE,
+ max_points_per_cell: int = DENSITY_MAX_POINTS_PER_CELL,
+ seed: int = DENSITY_SAMPLE_SEED,
+) -> None:
+ """
+ Write one extxyz trajectory per sampled density point for WEAS display.
+
+ Parameters
+ ----------
+ labels_list
+ Ordered system labels matching ``ref_vals``/``pred_vals``.
+ ref_vals
+ Reference values passed to the density scatter.
+ pred_vals
+ Predicted values passed to the density scatter.
+ struct_dir
+ Directory containing per-system structure files.
+ traj_dir
+ Output directory for sampled density trajectories.
+ struct_filename_builder
+ Function to convert each label into the source structure filename.
+ grid_size
+ Number of bins per axis. Must match ``@plot_density_scatter``.
+ max_points_per_cell
+ Maximum sampled points per occupied density cell.
+ seed
+ RNG seed for deterministic sampling.
+ """
+ _, _, sampled_mapping = sample_density_grid(
+ ref_vals,
+ pred_vals,
+ grid_size=grid_size,
+ max_points_per_cell=max_points_per_cell,
+ seed=seed,
+ )
+
+ traj_dir.mkdir(parents=True, exist_ok=True)
+
+ for point_idx, source_indices in enumerate(sampled_mapping):
+ frames = []
+ for source_idx in source_indices:
+ label = labels_list[source_idx]
+ struct_path = struct_dir / struct_filename_builder(label)
+ frames.append(read(struct_path))
+ write(traj_dir / f"{point_idx}.extxyz", frames)
+
+
def calc_metric_scores(
metrics_data: list[MetricRow],
thresholds: Thresholds | None = None,
diff --git a/ml_peg/app/build_app.py b/ml_peg/app/build_app.py
index ff7b61ef3..6867dc10f 100644
--- a/ml_peg/app/build_app.py
+++ b/ml_peg/app/build_app.py
@@ -7,7 +7,7 @@
from dash import Dash, Input, Output, callback
from dash.dash_table import DataTable
-from dash.dcc import Store, Tab, Tabs
+from dash.dcc import Loading, Store, Tab, Tabs
from dash.html import H1, H3, Div
from yaml import safe_load
@@ -382,7 +382,25 @@ def build_tabs(
[
H1("ML-PEG"),
Tabs(id="all-tabs", value="summary-tab", children=all_tabs),
- Div(id="tabs-content"),
+ Loading(
+ Div(id="tabs-content"),
+ type="circle",
+ color="#119DFF",
+ fullscreen=False,
+ # dont trigger both start up load wheel + tab change load wheel
+ # (when switching to summary tab)
+ target_components={"tabs-content": "children"},
+ style={
+ # Pin near the top so the spinner is visible on long pages
+ # (default is centre of page)
+ "position": "fixed",
+ "top": "300px",
+ "left": "50%",
+ "transform": "translateX(-50%)",
+ "zIndex": "1100",
+ },
+ parent_style={"position": "relative"},
+ ),
],
style={"flex": "1", "marginBottom": "40px"},
),
diff --git a/ml_peg/app/conformers/ACONFL/app_ACONFL.py b/ml_peg/app/conformers/ACONFL/app_ACONFL.py
new file mode 100644
index 000000000..d8d85b91a
--- /dev/null
+++ b/ml_peg/app/conformers/ACONFL/app_ACONFL.py
@@ -0,0 +1,87 @@
+"""Run ACONFL app."""
+
+from __future__ import annotations
+
+from dash import Dash
+from dash.html import Div
+
+from ml_peg.app import APP_ROOT
+from ml_peg.app.base_app import BaseApp
+from ml_peg.app.utils.build_callbacks import (
+ plot_from_table_column,
+ struct_from_scatter,
+)
+from ml_peg.app.utils.load import read_plot
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+BENCHMARK_NAME = "ACONFL"
+DOCS_URL = "https://ddmms.github.io/ml-peg/user_guide/benchmarks/conformers.html#aconfl"
+DATA_PATH = APP_ROOT / "data" / "conformers" / "ACONFL"
+
+
+class ACONFLApp(BaseApp):
+ """ACONFL benchmark app layout and callbacks."""
+
+ def register_callbacks(self) -> None:
+ """Register callbacks to app."""
+ scatter = read_plot(
+ DATA_PATH / "figure_aconfl.json",
+ id=f"{BENCHMARK_NAME}-figure",
+ )
+
+ model_dir = DATA_PATH / MODELS[0]
+ if model_dir.exists():
+ labels = sorted([f.stem for f in model_dir.glob("*.xyz")])
+ structs = [
+ f"assets/conformers/ACONFL/{MODELS[0]}/{label}.xyz" for label in labels
+ ]
+ else:
+ structs = []
+
+ plot_from_table_column(
+ table_id=self.table_id,
+ plot_id=f"{BENCHMARK_NAME}-figure-placeholder",
+ column_to_plot={"MAE": scatter},
+ )
+
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-figure",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=structs,
+ mode="struct",
+ )
+
+
+def get_app() -> ACONFLApp:
+ """
+ Get ACONFL benchmark app layout and callback registration.
+
+ Returns
+ -------
+ ACONFLApp
+ Benchmark layout and callback registration.
+ """
+ return ACONFLApp(
+ name=BENCHMARK_NAME,
+ description=(
+ "Performance in predicting relative conformer energies "
+ "of 12 C12H26, 16 C16H34 and 20 C20H42 conformers. "
+ "Reference data from PNO-LCCSD(T)-F12/ AVQZ calculations."
+ ),
+ docs_url=DOCS_URL,
+ table_path=DATA_PATH / "aconfl_metrics_table.json",
+ extra_components=[
+ Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
+ ],
+ )
+
+
+if __name__ == "__main__":
+ full_app = Dash(__name__, assets_folder=DATA_PATH.parent.parent)
+ benchmark_app = get_app()
+ full_app.layout = benchmark_app.layout
+ benchmark_app.register_callbacks()
+ full_app.run(port=8062, debug=True)
diff --git a/ml_peg/app/molecular/BMIMCl_RDF/app_BMIMCl_RDF.py b/ml_peg/app/molecular/BMIMCl_RDF/app_BMIMCl_RDF.py
new file mode 100644
index 000000000..c8dbc5c06
--- /dev/null
+++ b/ml_peg/app/molecular/BMIMCl_RDF/app_BMIMCl_RDF.py
@@ -0,0 +1,66 @@
+"""Run BMIMCl RDF benchmark app."""
+
+from __future__ import annotations
+
+from dash import Dash
+from dash.html import Div
+
+from ml_peg.app import APP_ROOT
+from ml_peg.app.base_app import BaseApp
+from ml_peg.app.utils.build_callbacks import plot_from_table_column
+from ml_peg.app.utils.load import read_plot
+
+BENCHMARK_NAME = "BMIMCl Cl-C RDF"
+DOCS_URL = (
+ "https://ddmms.github.io/ml-peg/user_guide/benchmarks/molecular.html#bmimcl-rdf"
+)
+DATA_PATH = APP_ROOT / "data" / "molecular" / "BMIMCl_RDF"
+
+
+class BMIMClRDFApp(BaseApp):
+ """BMIMCl RDF benchmark app layout and callbacks."""
+
+ def register_callbacks(self) -> None:
+ """Register callbacks to app."""
+ rdf_plot = read_plot(
+ DATA_PATH / "figure_rdf.json",
+ id=f"{BENCHMARK_NAME}-figure",
+ )
+
+ plot_from_table_column(
+ table_id=self.table_id,
+ plot_id=f"{BENCHMARK_NAME}-figure-placeholder",
+ column_to_plot={"Cl-C Bonds Formed": rdf_plot},
+ )
+
+
+def get_app() -> BMIMClRDFApp:
+ """
+ Get BMIMCl RDF benchmark app layout and callback registration.
+
+ Returns
+ -------
+ BMIMClRDFApp
+ Benchmark layout and callback registration.
+ """
+ return BMIMClRDFApp(
+ name=BENCHMARK_NAME,
+ description=(
+ "Tests whether MLIPs incorrectly predict Cl-C bond formation "
+ "in BMIMCl ionic liquid. Bonds should NOT form."
+ ),
+ docs_url=DOCS_URL,
+ table_path=DATA_PATH / "bmimcl_metrics_table.json",
+ extra_components=[
+ Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ ],
+ )
+
+
+if __name__ == "__main__":
+ full_app = Dash(__name__, assets_folder=DATA_PATH.parent.parent)
+ bmimcl_app = get_app()
+ full_app.layout = bmimcl_app.layout
+ bmimcl_app.register_callbacks()
+
+ full_app.run(port=8054, debug=True)
diff --git a/ml_peg/app/molecular_dynamics/water_density/app_water_density.py b/ml_peg/app/molecular_dynamics/water_density/app_water_density.py
new file mode 100644
index 000000000..b5f7c5769
--- /dev/null
+++ b/ml_peg/app/molecular_dynamics/water_density/app_water_density.py
@@ -0,0 +1,69 @@
+"""Run water density app."""
+
+from __future__ import annotations
+
+from dash import Dash
+from dash.html import Div
+
+from ml_peg.app import APP_ROOT
+from ml_peg.app.base_app import BaseApp
+from ml_peg.app.utils.build_callbacks import (
+ plot_from_table_column,
+)
+from ml_peg.app.utils.load import read_plot
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+BENCHMARK_NAME = "WaterDensity"
+DOCS_URL = "https://ddmms.github.io/ml-peg/user_guide/benchmarks/molecular_dynamics.html#Water_Density"
+DATA_PATH = APP_ROOT / "data" / "molecular_dynamics" / "water_density"
+
+
+class WaterDensityApp(BaseApp):
+ """Water density benchmark app layout and callbacks."""
+
+ def register_callbacks(self) -> None:
+ """Register callbacks to app."""
+ scatter = read_plot(
+ DATA_PATH / "figure_water_density.json",
+ id=f"{BENCHMARK_NAME}-figure",
+ )
+
+ plot_from_table_column(
+ table_id=self.table_id,
+ plot_id=f"{BENCHMARK_NAME}-figure-placeholder",
+ column_to_plot={"MAE": scatter},
+ )
+
+
+def get_app() -> WaterDensityApp:
+ """
+ Get water density benchmark app layout and callback registration.
+
+ Returns
+ -------
+ WaterDensityApp
+ Benchmark layout and callback registration.
+ """
+ return WaterDensityApp(
+ name=BENCHMARK_NAME,
+ description=(
+ "Performance in predicting water density at different temperatures."
+ "Reference data is experimental densities."
+ ),
+ docs_url=DOCS_URL,
+ table_path=DATA_PATH / "water_density_metrics_table.json",
+ extra_components=[
+ Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
+ ],
+ )
+
+
+if __name__ == "__main__":
+ full_app = Dash(__name__, assets_folder=DATA_PATH.parent.parent)
+ benchmark_app = get_app()
+ full_app.layout = benchmark_app.layout
+ benchmark_app.register_callbacks()
+ full_app.run(port=8063, debug=True)
diff --git a/ml_peg/app/molecular_reactions/RDB7/app_RDB7.py b/ml_peg/app/molecular_reactions/RDB7/app_RDB7.py
index fd471061e..199452a12 100644
--- a/ml_peg/app/molecular_reactions/RDB7/app_RDB7.py
+++ b/ml_peg/app/molecular_reactions/RDB7/app_RDB7.py
@@ -9,8 +9,9 @@
from ml_peg.app.base_app import BaseApp
from ml_peg.app.utils.build_callbacks import (
plot_from_table_cell,
+ struct_from_scatter,
)
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -49,6 +50,20 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/molecular_reactions/RDB7",
+ models=MODELS,
+ )
+
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-barrier-figure",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> RDB7App:
"""
@@ -70,6 +85,7 @@ def get_app() -> RDB7App:
table_path=DATA_PATH / "rdb7_barriers_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/nebs/si_defects/app_si_defects.py b/ml_peg/app/nebs/si_defects/app_si_defects.py
new file mode 100644
index 000000000..a15a6936c
--- /dev/null
+++ b/ml_peg/app/nebs/si_defects/app_si_defects.py
@@ -0,0 +1,123 @@
+"""Run app for Si defects benchmark."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+from dash import Dash
+from dash.html import Div
+
+from ml_peg.app import APP_ROOT
+from ml_peg.app.base_app import BaseApp
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import read_plot
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+
+BENCHMARK_NAME = "Si defects"
+DOCS_URL = "https://ddmms.github.io/ml-peg/user_guide/benchmarks/nebs.html#si-defects"
+DATA_PATH = APP_ROOT / "data" / "nebs" / "si_defects"
+
+
+@dataclass(frozen=True)
+class _Case:
+ """Definition of a single Si defects NEB dataset."""
+
+ key: str
+ label: str
+
+
+CASES: tuple[_Case, ...] = (
+ _Case(key="64_atoms", label="64"),
+ _Case(key="216_atoms", label="216"),
+ _Case(key="216_atoms_di_to_single", label="216 di-to-single"),
+)
+
+
+class SiDefectNebSinglepointsApp(BaseApp):
+ """Si defects benchmark app layout and callbacks."""
+
+ def register_callbacks(self) -> None:
+ """Register interactive callbacks for plot and structure viewing."""
+ scatter_plots: dict[str, dict] = {}
+
+ for model in MODELS:
+ model_plots: dict[str, object] = {}
+ for case in CASES:
+ energy_plot_path = (
+ DATA_PATH / f"figure_{model}_{case.key}_energy_error.json"
+ )
+ force_plot_path = (
+ DATA_PATH / f"figure_{model}_{case.key}_force_rms.json"
+ )
+ if energy_plot_path.exists():
+ model_plots[f"Energy MAE ({case.label})"] = read_plot(
+ energy_plot_path,
+ id=f"{BENCHMARK_NAME}-{model}-{case.key}-energy-figure",
+ )
+ if force_plot_path.exists():
+ model_plots[f"Force MAE ({case.label})"] = read_plot(
+ force_plot_path,
+ id=f"{BENCHMARK_NAME}-{model}-{case.key}-force-figure",
+ )
+ if model_plots:
+ scatter_plots[model] = model_plots
+
+ plot_from_table_cell(
+ table_id=self.table_id,
+ plot_id=f"{BENCHMARK_NAME}-figure-placeholder",
+ cell_to_plot=scatter_plots,
+ )
+
+ for model in scatter_plots:
+ for case in CASES:
+ structs = (
+ f"assets/nebs/si_defects/{case.key}/{model}/{model}-neb-band.extxyz"
+ )
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-{case.key}-energy-figure",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=structs,
+ mode="traj",
+ )
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-{case.key}-force-figure",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=structs,
+ mode="traj",
+ )
+
+
+def get_app() -> SiDefectNebSinglepointsApp:
+ """
+ Get Si defects app.
+
+ Returns
+ -------
+ SiDefectNebSinglepointsApp
+ App instance.
+ """
+ return SiDefectNebSinglepointsApp(
+ name=BENCHMARK_NAME,
+ description=(
+ "Energy/force MAE of MLIPs on fixed Si interstitial migration NEB images, "
+ "referenced to DFT singlepoints."
+ ),
+ docs_url=DOCS_URL,
+ table_path=DATA_PATH / "si_defects_metrics_table.json",
+ extra_components=[
+ Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
+ ],
+ )
+
+
+if __name__ == "__main__":
+ # Use APP_ROOT/data as assets root so `assets/nebs/...` resolves correctly.
+ full_app = Dash(__name__, assets_folder=DATA_PATH.parent.parent)
+ benchmark_app = get_app()
+ full_app.layout = benchmark_app.layout
+ benchmark_app.register_callbacks()
+ full_app.run(port=8060, debug=True)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_D1200/app_NCIA_D1200.py b/ml_peg/app/non_covalent_interactions/NCIA_D1200/app_NCIA_D1200.py
index 9d4b4ea32..e249dac79 100644
--- a/ml_peg/app/non_covalent_interactions/NCIA_D1200/app_NCIA_D1200.py
+++ b/ml_peg/app/non_covalent_interactions/NCIA_D1200/app_NCIA_D1200.py
@@ -7,8 +7,8 @@
from ml_peg.app import APP_ROOT
from ml_peg.app.base_app import BaseApp
-from ml_peg.app.utils.build_callbacks import plot_from_table_cell
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -39,6 +39,21 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/non_covalent_interactions/NCIA_D1200",
+ models=MODELS,
+ traj_dirname="density_traj",
+ suffix=".extxyz",
+ )
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-density",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> NCIAD1200App:
"""
@@ -60,6 +75,7 @@ def get_app() -> NCIAD1200App:
table_path=DATA_PATH / "ncia_d1200_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_D442x10/app_NCIA_D442x10.py b/ml_peg/app/non_covalent_interactions/NCIA_D442x10/app_NCIA_D442x10.py
index af22dd273..5202f89fc 100644
--- a/ml_peg/app/non_covalent_interactions/NCIA_D442x10/app_NCIA_D442x10.py
+++ b/ml_peg/app/non_covalent_interactions/NCIA_D442x10/app_NCIA_D442x10.py
@@ -7,8 +7,8 @@
from ml_peg.app import APP_ROOT
from ml_peg.app.base_app import BaseApp
-from ml_peg.app.utils.build_callbacks import plot_from_table_cell
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -39,6 +39,21 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/non_covalent_interactions/NCIA_D442x10",
+ models=MODELS,
+ traj_dirname="density_traj",
+ suffix=".extxyz",
+ )
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-density",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> NCIAD442x10App:
"""
@@ -60,6 +75,7 @@ def get_app() -> NCIAD442x10App:
table_path=DATA_PATH / "ncia_d442x10_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_HB300SPXx10/app_NCIA_HB300SPXx10.py b/ml_peg/app/non_covalent_interactions/NCIA_HB300SPXx10/app_NCIA_HB300SPXx10.py
index 2b3288dec..16ae5db9f 100644
--- a/ml_peg/app/non_covalent_interactions/NCIA_HB300SPXx10/app_NCIA_HB300SPXx10.py
+++ b/ml_peg/app/non_covalent_interactions/NCIA_HB300SPXx10/app_NCIA_HB300SPXx10.py
@@ -7,8 +7,8 @@
from ml_peg.app import APP_ROOT
from ml_peg.app.base_app import BaseApp
-from ml_peg.app.utils.build_callbacks import plot_from_table_cell
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -42,6 +42,21 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/non_covalent_interactions/NCIA_HB300SPXx10",
+ models=MODELS,
+ traj_dirname="density_traj",
+ suffix=".extxyz",
+ )
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-density",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> NCIANHB300SPXx10App:
"""
@@ -63,6 +78,7 @@ def get_app() -> NCIANHB300SPXx10App:
table_path=DATA_PATH / "ncia_hb300spxx10_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_HB375x10/app_NCIA_HB375x10.py b/ml_peg/app/non_covalent_interactions/NCIA_HB375x10/app_NCIA_HB375x10.py
index 578a55e6c..6b1f9d39e 100644
--- a/ml_peg/app/non_covalent_interactions/NCIA_HB375x10/app_NCIA_HB375x10.py
+++ b/ml_peg/app/non_covalent_interactions/NCIA_HB375x10/app_NCIA_HB375x10.py
@@ -7,8 +7,8 @@
from ml_peg.app import APP_ROOT
from ml_peg.app.base_app import BaseApp
-from ml_peg.app.utils.build_callbacks import plot_from_table_cell
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -42,6 +42,21 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/non_covalent_interactions/NCIA_HB375x10",
+ models=MODELS,
+ traj_dirname="density_traj",
+ suffix=".extxyz",
+ )
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-density",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> NCIANHB375x10App:
"""
@@ -63,6 +78,7 @@ def get_app() -> NCIANHB375x10App:
table_path=DATA_PATH / "ncia_hb375x10_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_IHB100x10/app_NCIA_IHB100x10.py b/ml_peg/app/non_covalent_interactions/NCIA_IHB100x10/app_NCIA_IHB100x10.py
index f21bb8be6..5ef64908f 100644
--- a/ml_peg/app/non_covalent_interactions/NCIA_IHB100x10/app_NCIA_IHB100x10.py
+++ b/ml_peg/app/non_covalent_interactions/NCIA_IHB100x10/app_NCIA_IHB100x10.py
@@ -7,8 +7,8 @@
from ml_peg.app import APP_ROOT
from ml_peg.app.base_app import BaseApp
-from ml_peg.app.utils.build_callbacks import plot_from_table_cell
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -42,6 +42,21 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/non_covalent_interactions/NCIA_IHB100x10",
+ models=MODELS,
+ traj_dirname="density_traj",
+ suffix=".extxyz",
+ )
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-density",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> NCIANIHB100x10App:
"""
@@ -63,6 +78,7 @@ def get_app() -> NCIANIHB100x10App:
table_path=DATA_PATH / "ncia_ihb100x10_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_R739x5/app_NCIA_R739x5.py b/ml_peg/app/non_covalent_interactions/NCIA_R739x5/app_NCIA_R739x5.py
index f9ea4f6c6..d508d184f 100644
--- a/ml_peg/app/non_covalent_interactions/NCIA_R739x5/app_NCIA_R739x5.py
+++ b/ml_peg/app/non_covalent_interactions/NCIA_R739x5/app_NCIA_R739x5.py
@@ -7,8 +7,8 @@
from ml_peg.app import APP_ROOT
from ml_peg.app.base_app import BaseApp
-from ml_peg.app.utils.build_callbacks import plot_from_table_cell
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -42,6 +42,21 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/non_covalent_interactions/NCIA_R739x5",
+ models=MODELS,
+ traj_dirname="density_traj",
+ suffix=".extxyz",
+ )
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-density",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> NCIAR739x5App:
"""
@@ -63,6 +78,7 @@ def get_app() -> NCIAR739x5App:
table_path=DATA_PATH / "ncia_r739x5_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_SH250x10/app_NCIA_SH250x10.py b/ml_peg/app/non_covalent_interactions/NCIA_SH250x10/app_NCIA_SH250x10.py
index d6a7c0391..c213b6053 100644
--- a/ml_peg/app/non_covalent_interactions/NCIA_SH250x10/app_NCIA_SH250x10.py
+++ b/ml_peg/app/non_covalent_interactions/NCIA_SH250x10/app_NCIA_SH250x10.py
@@ -7,8 +7,8 @@
from ml_peg.app import APP_ROOT
from ml_peg.app.base_app import BaseApp
-from ml_peg.app.utils.build_callbacks import plot_from_table_cell
-from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell, struct_from_scatter
+from ml_peg.app.utils.load import collect_traj_assets, read_density_plot_for_model
from ml_peg.models.get_models import get_model_names
from ml_peg.models.models import current_models
@@ -42,6 +42,21 @@ def register_callbacks(self) -> None:
cell_to_plot=density_plots,
)
+ struct_trajs = collect_traj_assets(
+ data_path=DATA_PATH,
+ assets_prefix="assets/non_covalent_interactions/NCIA_SH250x10",
+ models=MODELS,
+ traj_dirname="density_traj",
+ suffix=".extxyz",
+ )
+ for model in struct_trajs:
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-{model}-density",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=struct_trajs[model],
+ mode="traj",
+ )
+
def get_app() -> NCIASH250x10App:
"""
@@ -63,6 +78,7 @@ def get_app() -> NCIASH250x10App:
table_path=DATA_PATH / "ncia_sh250x10_metrics_table.json",
extra_components=[
Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
],
)
diff --git a/ml_peg/app/non_covalent_interactions/QUID/app_QUID.py b/ml_peg/app/non_covalent_interactions/QUID/app_QUID.py
new file mode 100644
index 000000000..c8947295d
--- /dev/null
+++ b/ml_peg/app/non_covalent_interactions/QUID/app_QUID.py
@@ -0,0 +1,92 @@
+"""Run QUID app."""
+
+from __future__ import annotations
+
+from dash import Dash
+from dash.html import Div
+
+from ml_peg.app import APP_ROOT
+from ml_peg.app.base_app import BaseApp
+from ml_peg.app.utils.build_callbacks import (
+ plot_from_table_column,
+ struct_from_scatter,
+)
+from ml_peg.app.utils.load import read_plot
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+BENCHMARK_NAME = "QUID"
+DOCS_URL = "https://ddmms.github.io/ml-peg/user_guide/benchmarks/non_covalent_interactions.html#quid"
+DATA_PATH = APP_ROOT / "data" / "non_covalent_interactions" / "QUID"
+
+
+class QUIDApp(BaseApp):
+ """QUID benchmark app layout and callbacks."""
+
+ def register_callbacks(self) -> None:
+ """Register callbacks to app."""
+ scatter = read_plot(
+ DATA_PATH / "figure_quid.json",
+ id=f"{BENCHMARK_NAME}-figure",
+ )
+
+ model_dir = DATA_PATH / MODELS[0]
+ if model_dir.exists():
+ # Note: sorting different to rxn_count order in calc
+ ts_files = sorted(model_dir.glob("*.xyz"))
+ structs = [
+ f"assets/non_covalent_interactions/QUID/{MODELS[0]}/{ts_file.name}"
+ for ts_file in ts_files
+ ]
+ else:
+ structs = []
+
+ plot_from_table_column(
+ table_id=self.table_id,
+ plot_id=f"{BENCHMARK_NAME}-figure-placeholder",
+ column_to_plot={
+ "Overall MAE": scatter,
+ "Equilibrium MAE": scatter,
+ "Dissociation MAE": scatter,
+ },
+ )
+
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-figure",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=structs,
+ mode="struct",
+ )
+
+
+def get_app() -> QUIDApp:
+ """
+ Get QUID benchmark app layout and callback registration.
+
+ Returns
+ -------
+ QUIDApp
+ Benchmark layout and callback registration.
+ """
+ return QUIDApp(
+ name=BENCHMARK_NAME,
+ description=(
+ "Performance in predicting ligand-pocket interaction energies "
+ "for the QUID dataset."
+ ),
+ docs_url=DOCS_URL,
+ table_path=DATA_PATH / "quid_metrics_table.json",
+ extra_components=[
+ Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
+ ],
+ )
+
+
+if __name__ == "__main__":
+ full_app = Dash(__name__, assets_folder=DATA_PATH.parent.parent)
+ benchmark_app = get_app()
+ full_app.layout = benchmark_app.layout
+ benchmark_app.register_callbacks()
+ full_app.run(port=8071, debug=True)
diff --git a/ml_peg/app/tm_complexes/3dTMV/app_3dTMV.py b/ml_peg/app/tm_complexes/3dTMV/app_3dTMV.py
new file mode 100644
index 000000000..2ac3a0fb8
--- /dev/null
+++ b/ml_peg/app/tm_complexes/3dTMV/app_3dTMV.py
@@ -0,0 +1,94 @@
+"""Run 3dTMV barriers app."""
+
+from __future__ import annotations
+
+from dash import Dash
+from dash.html import Div
+
+from ml_peg.app import APP_ROOT
+from ml_peg.app.base_app import BaseApp
+from ml_peg.app.utils.build_callbacks import (
+ plot_from_table_column,
+ struct_from_scatter,
+)
+from ml_peg.app.utils.load import read_plot
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+BENCHMARK_NAME = "3dTMV"
+DOCS_URL = "https://ddmms.github.io/ml-peg/user_guide/benchmarks/tm_complexes.html#dtmv"
+DATA_PATH = APP_ROOT / "data" / "tm_complexes" / "3dTMV"
+
+
+class Benchmark3dTMVApp(BaseApp):
+ """3dTMV benchmark app layout and callbacks."""
+
+ def register_callbacks(self) -> None:
+ """Register callbacks to app."""
+ scatter = read_plot(
+ DATA_PATH / "figure_3dtmv.json",
+ id=f"{BENCHMARK_NAME}-figure",
+ )
+
+ model_dir = DATA_PATH / MODELS[0]
+ if model_dir.exists():
+ # Note: sorting different to rxn_count order in calc
+ ts_files = sorted(model_dir.glob("*.xyz"), key=lambda path: int(path.stem))
+ structs = [
+ f"assets/tm_complexes/3dTMV/{MODELS[0]}/{ts_file.name}"
+ for ts_file in ts_files
+ ]
+ else:
+ structs = []
+
+ plot_from_table_column(
+ table_id=self.table_id,
+ plot_id=f"{BENCHMARK_NAME}-figure-placeholder",
+ column_to_plot={
+ "Overall MAE": scatter,
+ "SR MAE": scatter,
+ "MR MAE": scatter,
+ "SR/MR MAE": scatter,
+ },
+ )
+
+ struct_from_scatter(
+ scatter_id=f"{BENCHMARK_NAME}-figure",
+ struct_id=f"{BENCHMARK_NAME}-struct-placeholder",
+ structs=structs,
+ mode="struct",
+ )
+
+
+def get_app() -> Benchmark3dTMVApp:
+ """
+ Get 3dTMV benchmark app layout and callback registration.
+
+ Returns
+ -------
+ Benchmark3dTMVApp
+ Benchmark layout and callback registration.
+ """
+ return Benchmark3dTMVApp(
+ name=BENCHMARK_NAME,
+ description=(
+ "Performance in predicting vertical ionization energies for the "
+ "3dTMV dataset of 28 transition metal complexes."
+ "Reference data from ph-AFQMC calculations."
+ ),
+ docs_url=DOCS_URL,
+ table_path=DATA_PATH / "3dtmv_metrics_table.json",
+ extra_components=[
+ Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+ Div(id=f"{BENCHMARK_NAME}-struct-placeholder"),
+ ],
+ )
+
+
+if __name__ == "__main__":
+ full_app = Dash(__name__, assets_folder=DATA_PATH.parent.parent)
+ benchmark_app = get_app()
+ full_app.layout = benchmark_app.layout
+ benchmark_app.register_callbacks()
+ full_app.run(port=8071, debug=True)
diff --git a/ml_peg/app/utils/load.py b/ml_peg/app/utils/load.py
index 861c395c4..78abc20be 100644
--- a/ml_peg/app/utils/load.py
+++ b/ml_peg/app/utils/load.py
@@ -334,3 +334,49 @@ def read_density_plot_for_model(
return None
return Graph(id=id, figure=filtered_fig)
+
+
+def collect_traj_assets(
+ *,
+ data_path: Path,
+ assets_prefix: str,
+ models: list[str],
+ traj_dirname: str = "density_traj",
+ suffix: str = ".extxyz",
+) -> dict[str, list[str]]:
+ """
+ Collect trajectory asset paths for each model.
+
+ Parameters
+ ----------
+ data_path
+ Base data directory containing per-model folders.
+ assets_prefix
+ Assets URL prefix (e.g., ``"assets/molecular_reactions/RDB7"``).
+ models
+ Ordered list of model names to include.
+ traj_dirname
+ Subdirectory name containing trajectories (default: ``"density_traj"``).
+ suffix
+ File suffix to match (default: ``".extxyz"``).
+
+ Returns
+ -------
+ dict[str, list[str]]
+ Mapping of model name to list of asset paths.
+ """
+ assets_base = assets_prefix.rstrip("/")
+ struct_trajs: dict[str, list[str]] = {}
+
+ for model in models:
+ traj_dir = data_path / model / traj_dirname
+ traj_files = sorted(
+ traj_dir.glob(f"*{suffix}"), key=lambda path: int(path.stem)
+ )
+ if traj_files:
+ struct_trajs[model] = [
+ f"{assets_base}/{model}/{traj_dirname}/{traj_file.name}"
+ for traj_file in traj_files
+ ]
+
+ return struct_trajs
diff --git a/ml_peg/app/utils/weas.py b/ml_peg/app/utils/weas.py
index 1a178f7bf..d790ccd59 100644
--- a/ml_peg/app/utils/weas.py
+++ b/ml_peg/app/utils/weas.py
@@ -42,6 +42,14 @@ def generate_weas_html(
+