Aditya's rdkit featurizer added

src/data/rdkit_featurizer.py

@@ -0,0 +1,46 @@
+from pathlib import Path
+import numpy as np
+from rdkit import Chem, DataStructs
+from rdkit.Chem import AllChem
+import pandas as pd
+
+df = pd.read_csv('../../src/data/target.csv')
+
+def get_ecfp_molecule(index):
+    """
+    Gets the Morgan Fingerprint of a molecule using SMILES
+    
+    args:
+        indices: Indices for the MOBOQM9 model.
+    
+    returns:
+        int: Morgan Fingerprint of a molecule using SMILES
+    """
+
+    content = Path(f'../../../moboqm9/dataxyz/dsgdb9nsd_{index+1:06d}.xyz').read_text().split("\n")
+    smiles = content[-3].split('\t')[0]
+    mol = Chem.MolFromSmiles(smiles)
+    fp = AllChem.GetHashedMorganFingerprint(mol, 3, nBits=1024)
+    array = np.zeros((0,), dtype=np.int8)
+    DataStructs.ConvertToNumpyArray(fp,array)
+
+    return array
+
+def get_ecfp_matrix(indices,targets):
+    """
+    Gets the Morgan Fingerprint matrix using SMILES
+    
+    args:
+        indices: Indices for the MOBOQM9 model.
+    
+    returns:
+        int: Morgan Fingerprint matrix using SMILES
+    """
+    ecfp_matrix= np.zeros((0,1024), dtype=np.int8)
+    samples_targets = np.zeros((0,len(targets)))
+    for i in indices:
+        ecfp_vector=get_ecfp_molecule(i)
+        ecfp_matrix=np.vstack((ecfp_matrix,ecfp_vector))
+        samples_targets=np.vstack((samples_targets,np.array(df[targets].iloc[i])))
+
+    return ecfp_matrix,samples_targets