Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -239,36 +239,6 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
                 verif=False
         return verif
 
-    def open_dict(self,cond, proc, out, chart, lab, med):
-        if cond:
-            with open("./data/dict/"+self.config.name.replace(" ","_")+"/condVocab", 'rb') as fp:
-            	condDict = pickle.load(fp)
-        else :
-            condDict=None
-        if proc:
-            with open("./data/dict/"+self.config.name.replace(" ","_")+"/procVocab", 'rb') as fp:
-                procDict = pickle.load(fp)
-        else :
-            procDict=None
-        if out:
-            with open("./data/dict/"+self.config.name.replace(" ","_")+"/outVocab", 'rb') as fp:
-                outDict = pickle.load(fp)
-        else :
-            outDict=None
-        if chart:
-            with open("./data/dict/"+self.config.name.replace(" ","_")+"/chartVocab", 'rb') as fp:
-                chartDict = pickle.load(fp)
-        elif lab:
-            with open("./data/dict/"+self.config.name.replace(" ","_")+"/labsVocab", 'rb') as fp:
-                chartDict = pickle.load(fp)
-        else :
-            chartDict=None
-        if med:
-            with open("./data/dict/"+self.config.name.replace(" ","_")+"/medVocab", 'rb') as fp:
-                medDict = pickle.load(fp)
-        else :
-            medDict=None
-        return condDict, procDict, outDict, chartDict, medDict
 ###########################################################RAW##################################################################
 
     def _info_raw(self):
@@ -462,11 +432,11 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         ins_encoder.fit(insVocab)
         with open(filepath, 'rb') as fp:
             dico = pickle.load(fp)
+
         df = pd.DataFrame.from_dict(dico, orient='index')
-            
         for i, data in df.iterrows():
             concat_cols=[]
-            dyn_df,cond_df,demo=concat_data(data,self.config.name.replace(" ","_"),self.feat_cond,self.feat_proc,self.feat_out, self.feat_chart, self.feat_meds,self.feat_lab,self.outDict,self.chartDict,self.condDict,self.procDict,self.medDict)
+            dyn_df,cond_df,demo=concat_data(data,self.config.name.replace(" ","_"),self.feat_cond,self.feat_proc,self.feat_out, self.feat_chart, self.feat_meds,self.feat_lab)
             dyn=dyn_df.copy()
             dyn.columns=dyn.columns.droplevel(0)
             cols=dyn.columns
@@ -474,7 +444,6 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
             for t in range(time):
                 cols_t = [str(x) + "_"+str(t) for x in cols]
                 concat_cols.extend(cols_t)
-
             demo['gender']=gen_encoder.transform(demo['gender'])
             demo['ethnicity']=eth_encoder.transform(demo['ethnicity'])
             demo['insurance']=ins_encoder.transform(demo['insurance'])
@@ -482,7 +451,8 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
             demo=demo.drop(['label'],axis=1)
             X= generate_ml(dyn_df,cond_df,demo,concat_cols,self.concat)
             X=X.values.tolist()[0]
-            interv = (self.timeW//self.bucket)+1
+            
+            interv = (self.timeW//self.bucket) + 1
             size_concat = self.size_cond+ self.size_proc * interv + self.size_meds * interv+ self.size_out * interv+ self.size_chart *interv+ self.size_lab * interv + 4
             size_aggreg = self.size_cond+ self.size_proc + self.size_meds+ self.size_out+ self.size_chart+ self.size_lab + 4
 
@@ -517,8 +487,9 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
     def _generate_examples_deep(self, filepath):
         with open(filepath, 'rb') as fp:
             dico = pickle.load(fp)
+
         for key, data in dico.items():   
-            stat, demo, meds, chart, out, proc, lab, y = generate_deep(data, self.config.name.replace(" ","_"), self.feat_cond,  self.feat_proc,  self.feat_out,  self.feat_chart, self.feat_meds,self.feat_lab,self.outDict,self.chartDict,self.condDict,self.procDict,self.medDict)
+            stat, demo, meds, chart, out, proc, lab, y = generate_deep(data, self.config.name.replace(" ","_"), self.feat_cond,  self.feat_proc,  self.feat_out,  self.feat_chart, self.feat_meds,self.feat_lab)
             
             if self.verif_dim_tensor(proc, out, chart, meds, lab):
                 if self.data_icu:
@@ -546,7 +517,8 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         features = datasets.Features(
             {
                 "label": datasets.ClassLabel(num_classes=2,names=["0", "1"]),
-                "text" : datasets.Value(dtype='string', id=None),
+                "COND" : datasets.Value(dtype='string', id=None),
+                "CHART/LAB" : datasets.Value(dtype='string', id=None),
             }
         )
         return datasets.DatasetInfo(
@@ -572,7 +544,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
                     if not desc.empty:
                         cond_text.append(desc['description'].to_string(index=False))
                 template = 'The patient is diagnosed with {}.'
-                cond_text = template.format(';'.join(cond_text))
+                cond_text = template.format('; '.join(cond_text))
             else :
                 cond_text=''
                 
@@ -590,21 +562,20 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
                     for mean_val, feat_label in zip(chart_mean, feat_text):
                         text = template.format(mean_val,feat_label)
                         chart_text.append(text)
-                    chart_text='The chart events mesured are : {}.' + ';'.join(chart_text)
+                    chart_text='The chart events mesured are : ' + '; '.join(chart_text)
             else:
                 chart_text=''
             
             yield int(key),{
                 'label' : data['label'],
-                'text': cond_text+chart_text
+                'COND': cond_text,
+                'CHART/LAB': chart_text,
             }
 
 #############################################################################################################################
     def _info(self):
         self.path = self.init_cohort()
         self.size_cond, self.size_proc, self.size_meds, self.size_out, self.size_chart, self.size_lab, eth_vocab,gender_vocab,age_vocab,ins_vocab=vocab(self.config.name.replace(" ","_"),self.feat_cond,self.feat_proc,self.feat_out,self.feat_chart,self.feat_meds,self.feat_lab)
-        self.outDict,self.chartDict,self.condDict,self.procDict,self.medDict = self.open_dict(self.feat_cond,self.feat_proc,self.feat_out, self.feat_chart, self.feat_lab, self.feat_meds)
-        
         if (self.encoding == 'concat' or self.encoding =='aggreg'):
             return self._info_encoded()