Update MutagenLou2023 Preprocessing.py

MutagenLou2023 Preprocessing.py

@@ -76,7 +76,7 @@ from rdkit import DataStructs
 from rdkit.Chem import AllChem as Chem
 from rdkit.Chem import PandasTools 
 
-#7. Split the dataset into test and train
+# 7. Split the dataset into train and test
 
 class MolecularFingerprint:
     def __init__(self, fingerprint):
@@ -143,7 +143,7 @@ def butina_cluster(fingerprints, num_points, distance_threshold, reordering=Fals
 
 def hierarchal_cluster(fingerprints):
 
-      num_finger_prints = len(fingerprints)
+      num_fingerprints = len(fingerprints)
 
       av_cluster_size = 8
       dists = []
@@ -178,11 +178,9 @@ def cluster_fingerprints(fingerprints, method="Auto"):
         print("Butina clustering is selected. Dataset size is:", num_fingerprints)
         clusters = butina_cluster(fingerprints, num_fingerprints, cutoff)
 
-        return clusters
-
     elif method == "Hierarchy":
         print("Hierarchical clustering is selected. Dataset size is:", num_fingerprints)
-        clusters = hierarchal_cluster(fingerprints, num_fingerprints, 0.56)
+        clusters = hierarchal_cluster(fingerprints)
 
     return clusters
 
@@ -261,8 +259,8 @@ def split_df_into_train_and_test_sets(df):
     
 # 8. Test and train datasets have been made
 
-smiles_index = 0
-realistic = realistic_split(Mutagen.copy(), smiles_index, 0.8, split_for_exact_frac=True, cluster_method="Auto")
+smiles_index = 0  # Because smiles is in the first column
+realistic = realistic_split(newLou2023.copy(), smiles_index, 0.8, split_for_exact_frac=True, cluster_method="Auto")
 realistic_train, realistic_test = split_df_into_train_and_test_sets(realistic)
 
 #9. Select columns and name the datasets