Changes

deepchem/feat/base_classes.py

@@ -44,9 +44,11 @@ def featurize(self, datapoints, log_every_n=1000):
     for i, point in enumerate(datapoints):
       if i % log_every_n == 0:
         logger.info("Featurizing datapoint %i" % i)
-      if point is not None:
+      try:
         features.append(self._featurize(point))
-      else:
+      except:
+        logger.warning(
+            "Failed to featurize datapoint %d. Appending empty array")
         features.append(np.array([]))
 
     features = np.asarray(features)
@@ -139,12 +141,12 @@ class MolecularFeaturizer(Featurizer):
   In general, subclasses of this class will require RDKit to be installed.
   """
 
-  def featurize(self, mols, log_every_n=1000):
+  def featurize(self, molecules, log_every_n=1000):
     """Calculate features for molecules.
 
     Parameters
     ----------
-    mols : RDKit Mol / SMILES string /iterable
+    molecules: RDKit Mol / SMILES string /iterable
         RDKit Mol, or SMILES string or iterable sequence of RDKit mols/SMILES
         strings.
 
@@ -159,22 +161,24 @@ def featurize(self, mols, log_every_n=1000):
     except ModuleNotFoundError:
       raise ValueError("This class requires RDKit to be installed.")
     # Special case handling of single molecule
-    if isinstance(mols, str) or isinstance(mols, Mol):
-      mols = [mols]
+    if isinstance(molecules, str) or isinstance(molecules, Mol):
+      molecules = [molecules]
     else:
       # Convert iterables to list
-      mols = list(mols)
+      molecutes = list(molecules)
     features = []
-    for i, mol in enumerate(mols):
+    for i, mol in enumerate(molecules):
       if i % log_every_n == 0:
         logger.info("Featurizing datapoint %i" % i)
-      if mol is not None:
+      try:
         # Process only case of SMILES strings.
         if isinstance(mol, str):
           # mol must be a SMILES string so parse
           mol = Chem.MolFromSmiles(mol)
         features.append(self._featurize(mol))
-      else:
+      except:
+        logger.warning(
+            "Failed to featurize datapoint %d. Appending empty array")
         features.append(np.array([]))
 
     features = np.asarray(features)
@@ -191,16 +195,16 @@ def _featurize(self, mol):
     """
     raise NotImplementedError('Featurizer is not defined.')
 
-  def __call__(self, mols):
+  def __call__(self, molecules):
     """
     Calculate features for molecules.
 
     Parameters
     ----------
-    mols : iterable
-        RDKit Mol objects.
+    molecules: iterable
+        An iterable yielding RDKit Mol objects or SMILES strings.
     """
-    return self.featurize(mols)
+    return self.featurize(molecules)
 
 
 class UserDefinedFeaturizer(Featurizer):

deepchem/feat/graph_features.py

@@ -115,7 +115,7 @@ def safe_index(l, e):
 
 
 class GraphConvConstants(object):
-  """Allowed Atom Types."""
+  """This class defines a collection of constants which are useful for graph convolutions on molecules."""
   possible_atom_list = [
       'C', 'N', 'O', 'S', 'F', 'P', 'Cl', 'Mg', 'Na', 'Br', 'Fe', 'Ca', 'Cu',
       'Mc', 'Pd', 'Pb', 'K', 'I', 'Al', 'Ni', 'Mn'