Update dataset_utils.py

dataset_utils.py

@@ -227,7 +227,7 @@ def concat_data(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds,feat
 
 
 
-def generate_deep(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds,feat_lab,outDict,chartDict,condDict,procDict,medDict):
+def generate_deep(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds,feat_lab):
     stat_df = torch.zeros(size=(1,0))
     demo_df = torch.zeros(size=(1,0))
     meds = torch.zeros(size=(0,0))
@@ -239,7 +239,7 @@ def generate_deep(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds,fe
     demo_df = torch.zeros(size=(1,0))
     
     size_cond, size_proc, size_meds, size_out, size_chart, size_lab, eth_vocab,gender_vocab,age_vocab,ins_vocab=vocab(task.replace(" ","_"),feat_cond,feat_proc,feat_out,feat_chart,feat_meds,False)
-    dyn,cond_df,demo=concat_data(data,task.replace(" ","_"),feat_cond,feat_proc,feat_out,feat_chart,feat_meds,feat_lab,outDict,chartDict,condDict,procDict,medDict)
+    dyn,cond_df,demo=concat_data(data,task.replace(" ","_"),feat_cond,feat_proc,feat_out,feat_chart,feat_meds,feat_lab)
     if feat_chart:
         charts = dyn['CHART']
         charts=charts.to_numpy()
@@ -315,6 +315,7 @@ def generate_ml(dyn,stat,demo,concat_cols,concat):
         dyna=np.nan_to_num(dyna, copy=False)
         dyna=dyna.reshape(1,-1)
         dyn_df=pd.DataFrame(data=dyna,columns=concat_cols)
+        print('AVANT :',dyn_df)
     else:
         dyn_df=pd.DataFrame()
         for key in dyn.columns.levels[0]:     
@@ -333,6 +334,7 @@ def generate_ml(dyn,stat,demo,concat_cols,concat):
         dyn_df=dyn_df.T
         dyn_df.columns = dyn_df.iloc[0]
         dyn_df=dyn_df.iloc[1:,:]
+        print('APRES: ',dyn_df)
         
     X_df=pd.concat([dyn_df,stat],axis=1)
     X_df=pd.concat([X_df,demo],axis=1)