Adding synthetic_complexity_score

molgenevalmetric.py

@@ -51,6 +51,9 @@ import json
 import gzip
 import six
 
+from types import MethodType
+
+
 import os
 project_root = os.path.dirname(os.path.dirname(__file__))
 
@@ -64,32 +67,35 @@ def sigmoid(x):
   return 1 / (1 + np.exp(-x))
 
 class SCScorer():
+    self.mol_to_fp = MethodType(mol_to_fp, self)
+
     def __init__(self, score_scale=score_scale):
         self.vars = []
         self.score_scale = score_scale
         self._restored = False
 
-    def restore(self, weight_path=os.path.join('model.ckpt-10654.as_numpy.json.gz'), FP_rad=FP_rad, FP_len=FP_len):
-        self.FP_len = FP_len; self.FP_rad = FP_rad
+    def restore(self, weight_path='model.ckpt-10654.as_numpy.json.gz', FP_rad, FP_len):
+        self.FP_len = FP_len
+        self.FP_rad = FP_rad
         self._load_vars(weight_path)
-        # print('Restored variables from {}'.format(weight_path))
-
-        # if 'uint8' in weight_path or 'counts' in weight_path:
-        #     def mol_to_fp(self, mol):
-        #         if mol is None:
-        #             return np.array((self.FP_len,), dtype=np.uint8)
-        #         fp = AllChem.GetMorganFingerprint(mol, self.FP_rad, useChirality=True) # uitnsparsevect
-        #         fp_folded = np.zeros((self.FP_len,), dtype=np.uint8)
-        #         for k, v in six.iteritems(fp.GetNonzeroElements()):
-        #             fp_folded[k % self.FP_len] += v
-        #         return np.array(fp_folded)
-        # else:
-        def mol_to_fp(self, mol):
-            if mol is None:
-                return np.zeros((self.FP_len,), dtype=np.float32)
-            return np.array(AllChem.GetMorganFingerprintAsBitVect(mol, self.FP_rad, nBits=self.FP_len,
-                    useChirality=True), dtype=np.bool_)
-        self.mol_to_fp = mol_to_fp
+
+        if 'uint8' in weight_path or 'counts' in weight_path:
+            def mol_to_fp(mol):
+                if mol is None:
+                    return np.array((self.FP_len,), dtype=np.uint8)
+                fp = AllChem.GetMorganFingerprint(mol, self.FP_rad, useChirality=True)  # uint sparse vector
+                fp_folded = np.zeros((self.FP_len,), dtype=np.uint8)
+                for k, v in six.iteritems(fp.GetNonzeroElements()):
+                    fp_folded[k % self.FP_len] += v
+                return np.array(fp_folded)
+        else:
+            def mol_to_fp(mol):
+                if mol is None:
+                    return np.zeros((self.FP_len,), dtype=np.float32)
+                return np.array(AllChem.GetMorganFingerprintAsBitVect(mol, self.FP_rad, nBits=self.FP_len, useChirality=True), dtype=np.bool_)
+
+        # Set the mol_to_fp method for the instance
+        self.mol_to_fp = MethodType(mol_to_fp, self)
 
         self._restored = True
         return self