CUSTOM MDCATH

torchmdnet/datasets/mdcath.py

@@ -33,7 +33,10 @@ def __init__(
         transform=None,
         pre_transform=None,
         pre_filter=None,
+        source_file="mdcath_source.h5",
+        file_basename="mdcath_dataset",
         numAtoms=5000,
+        numNoHAtoms=None,
         numResidues=1000,
         temperatures=["348"],
         skip_frames=1,
@@ -52,16 +55,21 @@ def __init__(
             Root directory where the dataset should be stored. Data will be downloaded to 'root/'.
         numAtoms: int
             Max number of atoms in the protein structure.
+        source_file: str
+            Name of the source file with the information about the protein structures. Default is "mdcath_source.h5".
+        file_basename: str
+            Base name of the hdf5 files. Default is "mdcath_dataset".
         numNoHAtoms: int
-            Max number of non-hydrogen atoms in the protein structure.
+            Max number of non-hydrogen atoms in the protein structure, not available for original mdcath dataset. Default is None.
+            Be sure to have the attribute 'numNoHAtoms' in the source file.
         numResidues: int
             Max number of residues in the protein structure.
         temperatures: list
             List of temperatures (in Kelvin) to download. Default is ["348"]. Available temperatures are ['320', '348', '379', '413', '450']
         skip_frames: int
             Number of frames to skip in the trajectory. Default is 1.
         pdb_list: list or str
-            List of PDB IDs to download or path to a file with the PDB IDs. If None, all available PDB IDs from 'mdcath_source.h5' will be downloaded. 
+            List of PDB IDs to download or path to a file with the PDB IDs. If None, all available PDB IDs from 'source_file' will be downloaded. 
             The filters will be applied to the PDB IDs in this list in any case. Default is None.
         min_gyration_radius: float
             Minimum gyration radius (in nm) of the protein structure. Default is None.
@@ -76,7 +84,9 @@ def __init__(
         """
 
         self.url = "https://huggingface.co/datasets/compsciencelab/mdCATH/resolve/main/"
-        self.source_file = "mdcath_source.h5"
+        self.source_file = source_file
+        self.file_basename = file_basename
+        self.numNoHAtoms = numNoHAtoms
         self.root = root
         os.makedirs(root, exist_ok=True)
         self.numAtoms = numAtoms
@@ -103,33 +113,35 @@ def __init__(
 
     @property
     def raw_file_names(self):
-        return [f"mdcath_dataset_{pdb_id}.h5" for pdb_id in self.processed.keys()]
+        return [f"{self.file_basename}_{pdb_id}.h5" for pdb_id in self.processed.keys()]
 
     @property
     def raw_dir(self):
         # Override the raw_dir property to return the root directory
-        # The files will be downloaded to the root directory
+        # The files will be downloaded to the root directory, compatible only with original mdcath dataset
         return self.root
 
     def _ensure_source_file(self):
         """Ensure the source file is downloaded before processing."""
         source_path = os.path.join(self.root, self.source_file)
         if not os.path.exists(source_path):
+            assert self.source_file == "mdcath_source.h5", "Only 'mdcath_source.h5' is supported as source file for download."
             logger.info(f"Downloading source file {self.source_file}")
             urllib.request.urlretrieve(opj(self.url, self.source_file), source_path)
 
     def download(self):
         for pdb_id in self.processed.keys():
-            file_name = f"mdcath_dataset_{pdb_id}.h5"
+            file_name = f"{self.file_basename}_{pdb_id}.h5"
             file_path = opj(self.raw_dir, file_name)
             if not os.path.exists(file_path):
+                assert self.file_basename == "mdcath_dataset", "Only 'mdcath_dataset' is supported as file_basename for download."
                 # Download the file if it does not exist
                 urllib.request.urlretrieve(opj(self.url, 'data', file_name), file_path)
 
     def calculate_dataset_size(self):
         total_size_bytes = 0
         for pdb_id in self.processed.keys():
-            file_name = f"mdcath_dataset_{pdb_id}.h5"
+            file_name = f"{self.file_basename}_{pdb_id}.h5"
             total_size_bytes += os.path.getsize(opj(self.root, file_name))
         total_size_mb = round(total_size_bytes / (1024 * 1024), 4)
         return total_size_mb
@@ -161,7 +173,8 @@ def _evaluate_replica(self, pdb_id, temp, replica, pdb_group):
             self.numFrames is not None and pdb_group[temp][replica].attrs["numFrames"] < self.numFrames,
             self.min_gyration_radius is not None and pdb_group[temp][replica].attrs["min_gyration_radius"] < self.min_gyration_radius,
             self.max_gyration_radius is not None and pdb_group[temp][replica].attrs["max_gyration_radius"] > self.max_gyration_radius,
-            self._evaluate_structure(pdb_group, temp, replica)
+            self._evaluate_structure(pdb_group, temp, replica),
+            self.numNoHAtoms is not None and pdb_group.attrs["numNoHAtoms"] > self.numNoHAtoms,
         ]
         if any(conditions):
             return
@@ -180,7 +193,7 @@ def len(self):
         return self.num_conformers
 
     def _setup_idx(self):
-        files = [opj(self.root, f"mdcath_dataset_{pdb_id}.h5") for pdb_id in self.processed.keys()]
+        files = [opj(self.root, f"{self.file_basename}_{pdb_id}.h5") for pdb_id in self.processed.keys()]
         self.idx = []
         for i, (pdb, group_info) in enumerate(self.processed.items()):
             for temp, replica, num_frames in group_info: