added loopity_loop to run multiple models with stratified k-fold, got stuck in infinite loops and nested dicts

imports.py

@@ -50,10 +50,10 @@ os.chdir(homedir + "/git/ML_AI_training/")
 # my function
 from MultClassPipe import MultClassPipeline
 from MultClassPipe2 import MultClassPipeline2
-from MultClassPipe3 import MultClassPipeSKF
+from loopity_loop import MultClassPipeSKF
 
-gene = 'pncA'
-drug = 'pyrazinamide'
+gene = 'rpoB'
+drug = 'rifampicin'
 
 #==============
 # directories
@@ -82,12 +82,19 @@ mycols = my_df.columns
 my_df['active_aa_pos'].dtype
 my_df['active_aa_pos'] = my_df['active_aa_pos'].astype(object)
 
+if gene.lower() in geneL_na_ppi2:
+    x_stabilityN = common_cols_stabiltyN + ['mcsm_na_affinity'] + ['mcsm_ppi2_affinity', 'interface_dist'] 
+    #D1148 get rid of
+    na_index = my_df['mutationinformation'].index[my_df['mcsm_na_affinity'].apply(np.isnan)]
+    my_df = my_df.drop(index=na_index)
+
 #%%============================================================================
 # GET Y
 
 # Target1: mutation_info_labels
 dm_om_map = {'DM': 1, 'OM': 0}
 target1 = my_df['mutation_info_labels'].map(dm_om_map)
+target1.value_counts()
 
 # Target2: drug
 drug_labels = drug + '_labels'