Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -38,11 +38,11 @@ _CONFIG_URLS = {'los' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/re
   
 
 def onehot(data,task,feat_cond=False,feat_proc=False,feat_out=False,feat_chart=False,feat_meds=False):
-    meds=data['MEDS']
-    proc = data['PROC']
-    out = data['OUT']
-    chart = data['CHART']
-    cond= data['COND']
+    meds=data['Med']
+    proc = data['Proc']
+    out = data['Out']
+    chart = data['Chart']
+    cond= data['Cond']['fids']
 
     cond_df=pd.DataFrame()
     proc_df=pd.DataFrame()
@@ -82,8 +82,8 @@ def onehot(data,task,feat_cond=False,feat_proc=False,feat_out=False,feat_chart=F
         with open("./data/dict/"+task+"/procVocab", 'rb') as fp:
             procDic = pickle.load(fp)
 
-        feat=proc['id']
-        proc_val=proc['value']
+        feat=proc.keys()
+        proc_val=[proc[key] for key in feat]
         procedures=pd.DataFrame(procDic,columns=['PROC'])
         features=pd.DataFrame(np.zeros([1,len(procedures)]),columns=procedures['PROC'])
         features.columns=pd.MultiIndex.from_product([["PROC"], features.columns])
@@ -101,8 +101,8 @@ def onehot(data,task,feat_cond=False,feat_proc=False,feat_out=False,feat_chart=F
         with open("./data/dict/"+task+"/outVocab", 'rb') as fp:
             outDic = pickle.load(fp)
 
-        feat=out['id']
-        out_val=out['value']
+        feat=out.keys()
+        out_val=[out[key] for key in feat]
         outputs=pd.DataFrame(outDic,columns=['OUT'])
         features=pd.DataFrame(np.zeros([1,len(outputs)]),columns=outputs['OUT'])
         features.columns=pd.MultiIndex.from_product([["OUT"], features.columns])
@@ -121,8 +121,8 @@ def onehot(data,task,feat_cond=False,feat_proc=False,feat_out=False,feat_chart=F
             chartDic = pickle.load(fp)
 
         charts=chart['val']
-        feat=charts['id']
-        chart_val=charts['value']
+        feat=charts.keys()
+        chart_val=[charts[key] for key in feat]
         charts=pd.DataFrame(chartDic,columns=['CHART'])
         features=pd.DataFrame(np.zeros([1,len(charts)]),columns=charts['CHART'])
         features.columns=pd.MultiIndex.from_product([["CHART"], features.columns])
@@ -140,8 +140,8 @@ def onehot(data,task,feat_cond=False,feat_proc=False,feat_out=False,feat_chart=F
         with open("./data/dict/"+task+"/medVocab", 'rb') as fp:
                 medDic = pickle.load(fp)
 
-        feat=meds['signal']['id']
-        med_val=meds['amount']['value']
+        feat=meds['signal'].keys()
+        med_val=[meds['amount'][key] for key in feat]
         meds=pd.DataFrame(medDic,columns=['MEDS'])
         features=pd.DataFrame(np.zeros([1,len(meds)]),columns=meds['MEDS'])
         features.columns=pd.MultiIndex.from_product([["MEDS"], features.columns])
@@ -204,10 +204,11 @@ def generate_split(path,task,concat,feat_cond=True,feat_chart=True,feat_proc=Tru
     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()   
     #y_df=pd.DataFrame(df['label'],columns=['label'])
-    for hid, data in df.iterrows():
+    for hid, data in tqdm(df.iterrows()):
         concat_cols=[]
         sample=data
         dyn_df,cond_df,demo=onehot(sample,task,feat_cond,feat_chart,feat_proc, feat_meds, feat_out)