remove the mol_idx property as it was unused and also added extra req…

pyproject.toml

@@ -16,7 +16,6 @@ dependencies = [
   "torch_geometric",
   "lightning",
   "tqdm",
-  "pandas",
 ]
 
 [project.urls]

torchmdnet/datasets/ace.py

@@ -9,7 +9,6 @@
 from torchmdnet.datasets.memdataset import MemmappedDataset
 from torch_geometric.data import Data
 from tqdm import tqdm
-import pandas as pd
 
 
 class Ace(MemmappedDataset):
@@ -133,7 +132,6 @@ def __init__(
         paths=None,
         max_gradient=None,
         subsample_molecules=1,
-        index_csv=None,
     ):
         assert isinstance(paths, (str, list))
 
@@ -143,13 +141,8 @@ def __init__(
         self.paths = paths
         self.max_gradient = max_gradient
         self.subsample_molecules = int(subsample_molecules)
-        if index_csv is not None:
-            df = pd.read_csv(index_csv, dtype=int, converters={"name": str})
-            self.mol_indexes = {mol_id: i for i, mol_id in enumerate(df.name)}
 
         props = ["y", "neg_dy", "q", "pq", "dp"]
-        if index_csv is not None:
-            props += ["mol_idx"]
         super().__init__(
             root,
             transform,
@@ -239,7 +232,7 @@ def _load_confs_2_0(mol, n_atoms):
     def sample_iter(self, mol_ids=False):
         assert self.subsample_molecules > 0
 
-        for path in tqdm(self.raw_paths, desc="Files"):
+        for i_path, path in tqdm(enumerate(self.raw_paths), desc="Files"):
             h5 = h5py.File(path)
             assert h5.attrs["layout"] == "Ace"
             version = h5.attrs["layout_version"]
@@ -285,10 +278,9 @@ def sample_iter(self, mol_ids=False):
                         z=z, pos=pos, y=y.view(1, 1), neg_dy=neg_dy, q=q, pq=pq, dp=dp
                     )
                     if mol_ids:
+                        args["i_path"] = i_path
                         args["mol_id"] = mol_id
                         args["i_conf"] = i_conf
-                    if "mol_idx" in self.properties:
-                        args["mol_idx"] = self.mol_indexes[mol_id]
 
                     data = Data(**args)
 

torchmdnet/datasets/memdataset.py

@@ -86,10 +86,6 @@ def __init__(
             self.mmaps["dp"] = np.memmap(
                 fnames["dp"], mode="r", dtype=np.float32, shape=(num_all_confs, 3)
             )
-        if "mol_idx" in self.properties:
-            self.mmaps["mol_idx"] = np.memmap(
-                fnames["mol_idx"], mode="r", dtype=np.uint64
-            )
 
         assert self.mmaps["idx"][0] == 0
         assert self.mmaps["idx"][-1] == len(self.mmaps["z"])
@@ -178,13 +174,6 @@ def process(self):
                 dtype=np.float32,
                 shape=(num_all_confs, 3),
             )
-        if "mol_idx" in self.properties:
-            mmaps["mol_idx"] = np.memmap(
-                fnames["mol_idx"] + ".tmp",
-                mode="w+",
-                dtype=np.uint64,
-                shape=(num_all_confs,),
-            )
 
         print("Storing data...")
         i_atom = 0
@@ -204,8 +193,6 @@ def process(self):
                 mmaps["pq"][i_atom:i_next_atom] = data.pq
             if "dp" in self.properties:
                 mmaps["dp"][i_conf] = data.dp
-            if "mol_idx" in self.properties:
-                mmaps["mol_idx"][i_conf] = data.mol_idx
             i_atom = i_next_atom
 
         mmaps["idx"][-1] = num_all_atoms
@@ -231,8 +218,6 @@ def process(self):
             os.rename(fnames["pq"] + ".tmp", fnames["pq"])
         if "dp" in self.properties:
             os.rename(fnames["dp"] + ".tmp", fnames["dp"])
-        if "mol_idx" in self.properties:
-            os.rename(fnames["mol_idx"] + ".tmp", fnames["mol_idx"])
 
     def len(self):
         return len(self.mmaps["idx"]) - 1
@@ -249,7 +234,6 @@ def get(self, idx):
             - :obj:`q`: Total charge of the molecule.
             - :obj:`pq`: Partial charges of the atoms.
             - :obj:`dp`: Dipole moment of the molecule.
-            - :obj:`mol_idx`: The index of the molecule of the conformer.
 
         Args:
             idx (int): Index of the data object.
@@ -272,8 +256,6 @@ def get(self, idx):
             props["pq"] = pt.tensor(self.mmaps["pq"][atoms])
         if "dp" in self.properties:
             props["dp"] = pt.tensor(self.mmaps["dp"][idx])
-        # if "mol_idx" in self.properties:
-        #     props["mol_idx"] = pt.tensor(self.mmaps["mol_idx"][idx], dtype=pt.int64).view(1, 1)
         return Data(z=z, pos=pos, **props)
 
     def __del__(self):