s3 download for calc, calc analysis and app fixes

Author: joehart2001

ml_peg/analysis/conformers/Folmsbee/analyse_Folmsbee.py

@@ -75,7 +75,7 @@ def conformer_energies() -> dict[str, list]:
 
             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)
+                results["ref"].append(atoms.info["ref_rel_energy"] * EV_TO_KCAL)
 
             # Write structures for app
             structs_dir = OUT_PATH / model_name
@@ -132,3 +132,14 @@ def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
     return {
         "MAE": get_mae,
     }
+
+
+def test_folmsbee(metrics: dict[str, dict]) -> None:
+    """
+    Run Folmsbee analysis.
+
+    Parameters
+    ----------
+    metrics : dict[str, dict]
+        Folmsbee metric results provided by fixtures.
+    """

ml_peg/app/conformers/Folmsbee/app_Folmsbee.py

@@ -37,7 +37,7 @@ def register_callbacks(self) -> None:
         if model_dir.exists():
             labels = sorted([f.stem for f in model_dir.glob("*.xyz")])
             structs = [
-                f"assets/conformers/Folmsbee/{MODELS[0]}/{label}.xyz"
+                f"/assets/conformers/Folmsbee/{MODELS[0]}/{label}.xyz"
                 for label in labels
             ]
         else:

ml_peg/calcs/conformers/Folmsbee/calc_Folmsbee.py

@@ -20,6 +20,7 @@
 import pytest
 from tqdm import tqdm
 
+from ml_peg.calcs.utils.utils import download_s3_data
 from ml_peg.models.get_models import load_models
 from ml_peg.models.models import current_models
 
@@ -66,10 +67,16 @@ def test_folmsbee(mlip: tuple[str, Any]) -> None:
     # Add D3 calculator for this test
     calc = model.add_d3_calculator(calc)
 
-    data_path = Path(__file__).parent / "data" / "folmsbee_dataset.json"
+    data_path = (
+        download_s3_data(
+            key="inputs/conformers/Folmsbee/Folmsbee.zip",
+            filename="Folmsbee.zip",
+        )
+        / "Folmsbee"
+    )
     out_path = OUT_PATH / model_name
 
-    with open(data_path) as f:
+    with open(data_path / "folmsbee_dataset.json") as f:
         data = json.load(f)
     progress = tqdm(total=len(data))
     for structure_data in data:
@@ -79,7 +86,7 @@ def test_folmsbee(mlip: tuple[str, Any]) -> None:
         raw_energies = structure_data["dft_energy_profile"]
         ref_min_conformer_idx = raw_energies.index(min(raw_energies))
         ref_energies = get_relative_energies(raw_energies, ref_min_conformer_idx)
-        ref_energies *= KCAL_TO_EV
+        ref_energies = [e * KCAL_TO_EV for e in ref_energies]
 
         for i, conf_positions in enumerate(structure_data["conformer_coordinates"]):
             conf_atoms = Atoms(