Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -254,6 +254,8 @@ def getXY_deep(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds):
     for key in range(len(keys)):
         dyn_temp=dyn_df[keys[key]]
         dyn_temp=dyn_temp.to_numpy()
+        dyn_temp=np.nan_to_num(dyn_temp,copy=False)
+        dyn_temp=list(dyn_temp)
         dyn[key]=dyn_temp
     
     for k in range(len(keys)):
@@ -269,7 +271,7 @@ def getXY_deep(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds):
             lab=dyn[k]
     
     stat=cond_df
-    stat=stat.to_numpy()
+    stat=list(stat.to_numpy())
 
     y = demo['label']
     
@@ -289,6 +291,8 @@ def getXY(dyn,stat,demo,concat_cols,concat):
         dyna=dyn.copy()
         dyna.columns=dyna.columns.droplevel(0)
         dyna=dyna.to_numpy()
+        dyna=np.nan_to_num(dyna, copy=False)
+        dyna=list(dyna)
         dyna=dyna.reshape(1,-1)
         dyn_df=pd.DataFrame(data=dyna,columns=concat_cols)
     else:
@@ -361,11 +365,6 @@ def generate_split_deep(path,task,feat_cond,feat_chart,feat_proc, feat_meds, fea
     taskf=task.replace(" ","_")
     for hid, data in tqdm(X.iterrows(),desc='Encoding Splits Data for '+task+' task'):
         stat, demo, meds, chart, out, proc, lab, y = getXY_deep(data, taskf, feat_cond, feat_proc, feat_out, feat_chart,feat_meds)
-        meds=np.nan_to_num(meds, copy=False)
-        chart=np.nan_to_num(chart, copy=False)
-        out=np.nan_to_num(out, copy=False)
-        proc=np.nan_to_num(proc, copy=False)
-        lab=np.nan_to_num(lab, copy=False)
         X_dict[hid] = {'stat': stat, 'demo': demo, 'meds': meds, 'chart': chart, 'out': out, 'proc': proc, 'lab': lab, 'y': y}
         
     return X_dict
@@ -750,7 +749,13 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         features = datasets.Features(
             {
                 "label": datasets.ClassLabel(num_classes=2,names=["0", "1"]),
-                "DEMO": datasets.Array2D(shape=(1, None), dtype='int32'),
+                "DEMO": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
+                "COND" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
+                "MEDS" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
+                "PROC" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
+                "CHART" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
+                "OUT" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
+                "LAB" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
                 
             }
         )