Delete cohort.py

cohort.py

@@ -1,126 +0,0 @@
-
-import sys
-from pathlib import Path
-import os
-import importlib
-import shutil
-import time
-import yaml
-import os
-
-def task_cohort(task,mimic_path,path_benchmark, config_path):
-    root_dir = os.path.dirname(os.path.abspath('UserInterface.ipynb'))
-    config_path='./config/'+config_path
-    with open(config_path) as f:
-        config = yaml.safe_load(f)
-    version_path = mimic_path+'/'
-    version = mimic_path.split('/')[-1][0]
-    start = time.time()
-    #----------------------------------------------config----------------------------------------------------
-    disease_label =  config['disease_label']
-    tim = config['time']
-    label = config['label']
-    timeW = config['timeW']
-    include=int(timeW.split()[1])
-    bucket = config['bucket']
-    radimp = config['radimp']
-    predW = config['predW']
-    diag_flag = config['diagnosis']
-    out_flag = config['output']
-    chart_flag = config['chart']
-    proc_flag= config['proc']
-    med_flag = config['meds']
-    disease_filter = config['disease_filter']
-    icu_no_icu = config['icu_no_icu']
-    groupingICD = config['groupingICD']
-    # -------------------------------------------------------------------------------------------------------------
-
-    data_icu=icu_no_icu=="ICU"
-    data_mort=label=="Mortality"
-    data_admn=label=='Readmission'
-    data_los=label=='Length of Stay'
-
-    if (disease_filter=="Heart Failure"):
-        icd_code='I50'
-    elif (disease_filter=="CKD"):
-        icd_code='N18'
-    elif (disease_filter=="COPD"):
-        icd_code='J44'
-    elif (disease_filter=="CAD"):
-        icd_code='I25'
-    else:
-        icd_code='No Disease Filter'
-
-    #-----------------------------------------------EXTRACT MIMIC-----------------------------------------------------
-    if version == '2':
-        print('in0')
-        cohort_output = day_intervals_cohort_v22.extract_data(icu_no_icu,label,tim,icd_code, root_dir,version_path,disease_label)
-        print('out0')
-    elif version == '1':
-        cohort_output = day_intervals_cohort.extract_data(icu_no_icu,label,tim,icd_code, root_dir,version_path,disease_label)
-    #----------------------------------------------FEATURES-------------------------------------------------------
-    print(data_icu)
-    if data_icu :
-        feature_selection_icu.feature_icu(cohort_output, version_path,diag_flag,out_flag,chart_flag,proc_flag,med_flag)
-    #----------------------------------------------GROUPING-------------------------------------------------------
-    group_diag=False
-    group_med=False
-    group_proc=False
-    if data_icu:
-        if diag_flag:
-            group_diag=groupingICD
-        feature_selection_icu.preprocess_features_icu(cohort_output, diag_flag, group_diag,False,False,False,0,0)
-    #----------------------------------------------SUMMARY-------------------------------------------------------
-    if data_icu:
-        feature_selection_icu.generate_summary_icu(diag_flag,proc_flag,med_flag,out_flag,chart_flag)
-    #----------------------------------------------FEATURE SELECTION---------------------------------------------
-
-    select_diag= config['select_diag']
-    select_med= config['select_med']
-    select_proc=  config['select_proc']
-    #select_lab= config['select_lab']
-    select_out= config['select_out']
-    select_chart=  config['select_chart']
-
-    feature_selection_icu.features_selection_icu(cohort_output, diag_flag,proc_flag,med_flag,out_flag, chart_flag,select_diag,select_med,select_proc,select_out,select_chart)
-    #---------------------------------------CLEANING OF FEATURES-----------------------------------------------
-    thresh=0
-    if data_icu:
-        if chart_flag:
-            outlier_removal=config['outlier_removal']
-            clean_chart=outlier_removal!='No outlier detection'
-            impute_outlier_chart=outlier_removal=='Impute Outlier (default:98)'
-            thresh=config['outlier']
-            left_thresh=config['left_outlier']
-        feature_selection_icu.preprocess_features_icu(cohort_output, False, False,chart_flag,clean_chart,impute_outlier_chart,thresh,left_thresh)
-    # ---------------------------------------tim-Series Representation--------------------------------------------
-    if radimp == 'forward fill and mean' :
-        impute='Mean'
-    elif radimp =='forward fill and median':
-        impute = 'Median'
-    else :
-        impute = False
-    
-    if data_icu:
-        gen=data_generation_icu_modify.Generator(task,cohort_output,data_mort,data_admn,data_los,diag_flag,proc_flag,out_flag,chart_flag,med_flag,impute,include,bucket,predW)
-    end = time.time()
-    print("Time elapsed : ", round((end - start)/60,2),"mins")
-    print("[============TASK COHORT SUCCESSFULLY CREATED============]")
-
-if __name__ == '__main__':
-    
-    
-    task = sys.argv[1]
-    mimic_path = sys.argv[2]
-    path_benchmark = sys.argv[3]
-    config = sys.argv[4]
-    sys.path.append('./preprocessing/day_intervals_preproc')
-    sys.path.append('./utils')
-    sys.path.append('./preprocessing/hosp_module_preproc')
-    sys.path.append('./model')
-    import day_intervals_cohort_v22
-    import day_intervals_cohort
-    import feature_selection_icu
-    import data_generation_icu_modify
-    
-    task_cohort(task, mimic_path, path_benchmark, config)