Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -3,7 +3,9 @@ import json
 import os
 import pandas as pd
 import datasets
+import sys
 import pickle
+from .cohort import task_cohort
 import subprocess
 import shutil
 from urllib.request import urlretrieve
@@ -19,6 +21,7 @@ _HOMEPAGE = "https://huggingface.co/datasets/thbndi/Mimic4Dataset"
 _CITATION = "https://proceedings.mlr.press/v193/gupta22a.html"
 _URL = "https://github.com/healthylaife/MIMIC-IV-Data-Pipeline"
 _DATA_GEN = 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/data_generation_icu_modify.py'
+_COHORT = 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/cohort.py'
 _CONFIG_URLS = {'los' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/config/los.config',
                 'mortality' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/config/mortality.config',
                 'phenotype' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/config/phenotype.config',
@@ -154,13 +157,19 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         if not os.path.exists(path_bench+'/config/'+self.config_path.split('/')[-1]):
             shutil.move(file_path, path_bench+'/config')
         
-        file_path, head = urlretrieve(_DATA_GEN, "data_generation_icu_modify.py")
 
         if not os.path.exists(path_bench+'/model/data_generation_icu_modify.py'):
+            file_path, head = urlretrieve(_DATA_GEN, "data_generation_icu_modify.py")
             shutil.move(file_path, path_bench+'/model')
         
+        if not os.path.exists(path_bench+'cohort.py'):
+            file_path, head = urlretrieve(_COHORT, "cohort.py")
+            shutil.move(file_path, path_bench)
+        
         data_dir = path_bench + "/data/dataDic"
-        task_cohort(self.config.name,self.mimic_path, path_bench, self.config_path)
+        sys.path.append(path_bench)
+        import cohort
+        cohort.task_cohort(self.config.name,self.mimic_path, path_bench, self.config_path)
         return [
             datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir}),
         ]