Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -398,11 +398,17 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         data=data.T
         train_data, test_data = train_test_split(data, test_size=self.test_size, random_state=42)
         train_data, val_data = train_test_split(test_data, test_size=self.val_size, random_state=42)
+        
         csv_dir = "./data/dict/"+self.config.name.replace(" ","_")
 
         train_data.to_csv(csv_dir+'/train_data.csv',index=False)
         val_data.to_csv(csv_dir+'/val_data.csv',index=False)
         test_data.to_csv(csv_dir+'/test_data.csv',index=False)
+
+        train_data.to_pickle(csv_dir+'/train_data.pkl',index=False)
+        val_data.to_pickle(csv_dir+'/val_data.pkl',index=False)
+        test_data.to_pickle(csv_dir+'/test_data.pkl',index=False)
+        
         return feat_cond, feat_chart, feat_proc, feat_meds, feat_out
   
 ###########################################################RAW##################################################################
@@ -470,14 +476,15 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         csv_dir = "./data/dict/"+self.config.name.replace(" ","_")
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": csv_dir+'/train_data.csv'}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": csv_dir+'/val_data.csv'}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": csv_dir+'/test_data.csv'}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": csv_dir+'/train_data.pkl'}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": csv_dir+'/val_data.pkl'}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": csv_dir+'/test_data.pkl'}),
         ]
 
     def _generate_examples_raw(self, filepath):
-        df = pd.read_csv(filepath, header=0)
-        for hid, data in df.iterrows():
+        with open(filepath, 'rb') as fp:
+            dataDic = pickle.load(fp)
+        for hid, data in dataDic.items():
             proc_features = data['Proc']
             chart_features = data['Chart']
             meds_features = data['Med']