thbndi commited on
Commit
3694c35
·
1 Parent(s): cad1204

Update Mimic4Dataset.py

Browse files
Files changed (1) hide show
  1. Mimic4Dataset.py +5 -4
Mimic4Dataset.py CHANGED
@@ -10,7 +10,7 @@ from sklearn.model_selection import train_test_split
10
  from sklearn.preprocessing import LabelEncoder
11
  import yaml
12
  import numpy as np
13
- from .dataset_utils import vocab, concat_data, generate_deep, generate_ml, generate_text
14
  from .task_cohort import create_cohort
15
 
16
 
@@ -238,7 +238,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
238
  if (len(lab)!=interv):
239
  verif=False
240
  return verif
241
-
242
  ###########################################################RAW##################################################################
243
 
244
  def _info_raw(self):
@@ -436,7 +436,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
436
  df = pd.DataFrame.from_dict(dico, orient='index')
437
  for i, data in df.iterrows():
438
  concat_cols=[]
439
- 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)
440
  dyn=dyn_df.copy()
441
  dyn.columns=dyn.columns.droplevel(0)
442
  cols=dyn.columns
@@ -489,7 +489,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
489
  dico = pickle.load(fp)
490
 
491
  for key, data in dico.items():
492
- 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)
493
 
494
  if self.verif_dim_tensor(proc, out, chart, meds, lab):
495
  if self.data_icu:
@@ -545,6 +545,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
545
  def _info(self):
546
  self.path = self.init_cohort()
547
  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)
 
548
  if (self.encoding == 'concat' or self.encoding =='aggreg'):
549
  return self._info_encoded()
550
 
 
10
  from sklearn.preprocessing import LabelEncoder
11
  import yaml
12
  import numpy as np
13
+ from .dataset_utils import vocab, concat_data, generate_deep, generate_ml, generate_text, open_dict
14
  from .task_cohort import create_cohort
15
 
16
 
 
238
  if (len(lab)!=interv):
239
  verif=False
240
  return verif
241
+
242
  ###########################################################RAW##################################################################
243
 
244
  def _info_raw(self):
 
436
  df = pd.DataFrame.from_dict(dico, orient='index')
437
  for i, data in df.iterrows():
438
  concat_cols=[]
439
+ 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.condDict, self.procDict, self.outDict, self.chartDict, self.medDict)
440
  dyn=dyn_df.copy()
441
  dyn.columns=dyn.columns.droplevel(0)
442
  cols=dyn.columns
 
489
  dico = pickle.load(fp)
490
 
491
  for key, data in dico.items():
492
+ 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.condDict, self.procDict, self.outDict, self.chartDict, self.medDict)
493
 
494
  if self.verif_dim_tensor(proc, out, chart, meds, lab):
495
  if self.data_icu:
 
545
  def _info(self):
546
  self.path = self.init_cohort()
547
  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)
548
+ self.condDict, self.procDict, self.outDict, self.chartDict, self.medDict = open_dict(self.config.name.replace(" ","_"),self.feat_cond,self.feat_proc,self.feat_out,self.feat_chart,self.feat_lab,self.feat_meds)
549
  if (self.encoding == 'concat' or self.encoding =='aggreg'):
550
  return self._info_encoded()
551