Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -21,7 +21,7 @@ Available tasks are: Mortality, Length of Stay, Readmission, Phenotype.
 The data is extracted from the mimic4 database using this pipeline: 'https://github.com/healthylaife/MIMIC-IV-Data-Pipeline/tree/main'
 mimic path should have this form : "path/to/mimic4data/from/username/mimiciv/2.2"
 If you choose a Custom task provide a configuration file for the Time series.
-Currently working with Mimic-IV ICU data.
+Currently working with Mimic-IV version 1 and 2
 """
 _BASE_URL = "https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main"
 _HOMEPAGE = "https://huggingface.co/datasets/thbndi/Mimic4Dataset"
@@ -430,8 +430,17 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
             dico = pickle.load(fp)
 
         df = pd.DataFrame.from_dict(dico, orient='index')
+        feat_tocsv=True
         for i, data in df.iterrows():
             dyn_df,cond_df,demo=concat_data(data,self.interval,self.feat_cond,self.feat_proc,self.feat_out, self.feat_chart, self.feat_meds,self.feat_lab,self.condDict, self.procDict, self.outDict, self.chartDict, self.medDict)
+            if feat_tocsv:
+                #save the features of the vector for analysis purposes if needed
+                feats = list(dyn_df.columns)
+                feats= feats.append(list(cond_df.columns))
+                feats= feats.append(list(demo.columns))
+                df_feats = pd.DataFrame(columns=feats)
+                df_feats.to_csv('./data/dict/'+self.config.name.replace(" ","_")+'/features_'+self.encoding'.csv')
+                feat_tocsv=False
             dyn=dyn_df.copy()
             dyn.columns=dyn.columns.droplevel(0)
             concat_cols = [f"{col}_{t}" for t in range(dyn.shape[0]) for col in dyn.columns]