Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -201,7 +201,9 @@ def encoding(X_data):
     return X_data
 
 def generate_split(path,task,concat,feat_cond=True,feat_chart=True,feat_proc=True, feat_meds=True, feat_out=False):
-    print(path)
+    with open(path, 'rb') as fp:
+        dico = pickle.load(fp)
+    df = pd.DataFrame.from_dict(dico, orient='index')
     df = pd.DataFrame.from_dict(path)
     task=task.replace(" ","_")
     X_df=pd.DataFrame()   
@@ -587,23 +589,19 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
 
 ###########################################################ENCODED##################################################################
        
-    def _info_encoded(self):
+    def _info_encoded(self,X_encoded):
 
+        columns = {col: self.map_dtype(X_encoded[col].dtype) for col in X_encoded.columns}
+        features = datasets.Features(columns)
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
+            features=features,
             homepage=_HOMEPAGE,
             citation=_CITATION,
         )
     
     def __split_generators_encoded(self):
         data_dir = "./data/dict/"+self.config.name.replace(" ","_")
-        X_train_encoded=generate_split(self.path+'/train_data.pkl',self.config.name,True,self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out)
-        X_test_encoded=generate_split(self.path+'/test_data.pkl',self.config.name,True,self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out)
-        X_val_encoded=generate_split(self.path+'/val_data.pkl',self.config.name,True,self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out)
-        
-        X_train_encoded.to_csv(self.path+"/X_train_encoded.csv", index=False)
-        X_test_encoded.to_csv(self.path+"/X_test_encoded.csv", index=False)
-        X_val_encoded.to_csv(self.path+"/X_val_encoded.csv", index=False)
 
         return [
             datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir+'/X_train_encoded.csv'}),
@@ -620,7 +618,15 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
 #############################################################################################################################
     def _info(self):
         self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out,self.path = self.create_cohort()
+
         if self.encoding :
+            X_train_encoded=generate_split(self.path+'/train_data.pkl',self.config.name,True,self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out)
+            X_test_encoded=generate_split(self.path+'/test_data.pkl',self.config.name,True,self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out)
+            X_val_encoded=generate_split(self.path+'/val_data.pkl',self.config.name,True,self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out)
+            
+            X_train_encoded.to_csv(self.path+"/X_train_encoded.csv", index=False)
+            X_test_encoded.to_csv(self.path+"/X_test_encoded.csv", index=False)
+            X_val_encoded.to_csv(self.path+"/X_val_encoded.csv", index=False)
             return self._info_encoded()
         else:
             return self._info_raw()