diff --git a/ml_peg/analysis/conformers/Glucose205/analyse_Glucose205.py b/ml_peg/analysis/conformers/Glucose205/analyse_Glucose205.py new file mode 100644 index 00000000..bab17a63 --- /dev/null +++ b/ml_peg/analysis/conformers/Glucose205/analyse_Glucose205.py @@ -0,0 +1,148 @@ +""" +Analyse the glucose conformer energy dataset. + +Journal of Chemical Theory and Computation, +2016 12 (12), 6157-6168. +DOI: 10.1021/acs.jctc.6b00876 +""" + +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_d3_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) + +EV_TO_KCAL = units.mol / units.kcal +CALC_PATH = CALCS_ROOT / "conformers" / "Glucose205" / "outputs" +OUT_PATH = APP_ROOT / "data" / "conformers" / "Glucose205" + +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_glucose205.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_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 / "glucose205_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_glucose205(metrics: dict[str, dict]) -> None: + """ + Run Glucose205 test. + + Parameters + ---------- + metrics + All new benchmark metric names and dictionary of values for each model. + """ + return diff --git a/ml_peg/analysis/conformers/Glucose205/metrics.yml b/ml_peg/analysis/conformers/Glucose205/metrics.yml new file mode 100644 index 00000000..033d1a57 --- /dev/null +++ b/ml_peg/analysis/conformers/Glucose205/metrics.yml @@ -0,0 +1,7 @@ +metrics: + MAE: + good: 0.0 + bad: 20.0 + unit: kcal/mol + tooltip: Mean Absolute Error for all systems + level_of_theory: CCSD(T) diff --git a/ml_peg/app/conformers/Glucose205/app_Glucose205.py b/ml_peg/app/conformers/Glucose205/app_Glucose205.py new file mode 100644 index 00000000..5befa145 --- /dev/null +++ b/ml_peg/app/conformers/Glucose205/app_Glucose205.py @@ -0,0 +1,90 @@ +"""Run Glucose205 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 = "Glucose205" +DOCS_URL = ( + "https://ddmms.github.io/ml-peg/user_guide/benchmarks/conformers.html#glucose205" +) +DATA_PATH = APP_ROOT / "data" / "conformers" / "Glucose205" + + +class Glucose205App(BaseApp): + """Glucose205 benchmark app layout and callbacks.""" + + def register_callbacks(self) -> None: + """Register callbacks to app.""" + scatter = read_plot( + DATA_PATH / "figure_glucose205.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/Glucose205/{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() -> Glucose205App: + """ + Get Glucose205 benchmark app layout and callback registration. + + Returns + ------- + Glucose205App + Benchmark layout and callback registration. + """ + return Glucose205App( + name=BENCHMARK_NAME, + description=( + "Performance in predicting relative conformer energies for " + "205 glucose structures. " + "Reference data from DLPNO-CCSD(T) calculations." + ), + docs_url=DOCS_URL, + table_path=DATA_PATH / "glucose205_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=8064, debug=True) diff --git a/ml_peg/calcs/conformers/Glucose205/calc_Glucose205.py b/ml_peg/calcs/conformers/Glucose205/calc_Glucose205.py new file mode 100644 index 00000000..093c9962 --- /dev/null +++ b/ml_peg/calcs/conformers/Glucose205/calc_Glucose205.py @@ -0,0 +1,156 @@ +""" +Calculate the glucose conformer energy dataset. + +Journal of Chemical Theory and Computation, +2016 12 (12), 6157-6168. +DOI: 10.1021/acs.jctc.6b00876 +""" + +from __future__ import annotations + +from pathlib import Path + +from ase import Atoms, units +from ase.io import read, write +import mlipx +from mlipx.abc import NodeWithCalculator +import pandas as pd +from tqdm import tqdm +import zntrack + +from ml_peg.calcs.utils.utils import chdir, download_s3_data +from ml_peg.models.get_models import load_models +from ml_peg.models.models import current_models + +MODELS = load_models(current_models) + +KCAL_TO_EV = units.kcal / units.mol + +OUT_PATH = Path(__file__).parent / "outputs" + + +class Glucose205Benchmark(zntrack.Node): + """Benchmark the Glucose205 dataset.""" + + model: NodeWithCalculator = zntrack.deps() + model_name: str = zntrack.params() + + @staticmethod + def get_atoms(atoms_path: Path) -> Atoms: + """ + Read atoms object and add charge and spin. + + Parameters + ---------- + atoms_path + Path to atoms object. + + Returns + ------- + atoms + ASE atoms object. + """ + atoms = read(atoms_path) + atoms.info["charge"] = 0 + atoms.info["spin"] = 1 + return atoms + + def get_labels(self, data_path: Path) -> None: + """ + Get system labels. + + Parameters + ---------- + data_path + Path to the structure. + """ + self.labels = [] + for system_path in sorted((data_path / "Glucose_structures").glob("*.xyz")): + self.labels.append(system_path.stem) + + def get_ref_energies(self, data_path: Path) -> None: + """ + Get reference conformer energies. + + Parameters + ---------- + data_path + Path to the structure. + """ + df = pd.read_csv(data_path / "glucose.csv") + self.get_labels(data_path) + self.ref_energies = {} + for i, label in enumerate(self.labels): + self.ref_energies[label] = df[" dlpno/cbs(3-4)"][i] * KCAL_TO_EV + + def run(self) -> None: + """Run new benchmark.""" + data_path = ( + download_s3_data( + filename="Glucose205.zip", + key="inputs/conformers/Glucose205/Glucose205.zip", + ) + / "Glucose205" + ) + + self.get_ref_energies(data_path) + # Read in data and attach calculator + calc = self.model.get_calculator() + # Add D3 calculator for this test + calc = self.model.add_d3_calculator(calc) + + lowest_conf_label = "alpha_002" + + conf_lowest = self.get_atoms( + data_path / "Glucose_structures" / f"{lowest_conf_label}.xyz" + ) + conf_lowest.calc = calc + e_conf_lowest_model = conf_lowest.get_potential_energy() + + for label, e_ref in tqdm(self.ref_energies.items()): + # Skip the reference conformer for which the error is automatically zero + if label == lowest_conf_label: + continue + + atoms = self.get_atoms(data_path / "Glucose_structures" / f"{label}.xyz") + atoms.calc = calc + atoms.info["model_rel_energy"] = ( + atoms.get_potential_energy() - e_conf_lowest_model + ) + atoms.info["ref_energy"] = e_ref + + write_dir = OUT_PATH / self.model_name + write_dir.mkdir(parents=True, exist_ok=True) + write(write_dir / f"{label}.xyz", atoms) + + +def build_project(repro: bool = False) -> None: + """ + Build mlipx project. + + Parameters + ---------- + repro + Whether to call dvc repro -f after building. + """ + project = mlipx.Project() + benchmark_node_dict = {} + + for model_name, model in MODELS.items(): + with project.group(model_name): + benchmark = Glucose205Benchmark( + model=model, + model_name=model_name, + ) + benchmark_node_dict[model_name] = benchmark + + if repro: + with chdir(Path(__file__).parent): + project.repro(build=True, force=True) + else: + project.build() + + +def test_glucose205(): + """Run Glucose205 benchmark via pytest.""" + build_project(repro=True) diff --git a/ml_peg/calcs/conformers/glucose205/.dvc/.gitignore b/ml_peg/calcs/conformers/glucose205/.dvc/.gitignore new file mode 100644 index 00000000..528f30c7 --- /dev/null +++ b/ml_peg/calcs/conformers/glucose205/.dvc/.gitignore @@ -0,0 +1,3 @@ +/config.local +/tmp +/cache diff --git a/ml_peg/calcs/conformers/glucose205/.dvc/config b/ml_peg/calcs/conformers/glucose205/.dvc/config new file mode 100644 index 00000000..e69de29b diff --git a/ml_peg/calcs/conformers/glucose205/.dvcignore b/ml_peg/calcs/conformers/glucose205/.dvcignore new file mode 100644 index 00000000..51973055 --- /dev/null +++ b/ml_peg/calcs/conformers/glucose205/.dvcignore @@ -0,0 +1,3 @@ +# Add patterns of files dvc should ignore, which could improve +# the performance. Learn more at +# https://dvc.org/doc/user-guide/dvcignore