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import os
import sys
import yaml
import time
from .check_config import check_config
from .day_intervals_cohort_v22 import *
from .data_generation_icu_modify import *
from .data_generation_modify import *
def task_cohort(task, mimic_path, config_path):
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
import feature_selection_icu
import feature_selection_hosp
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+'/'
print(version_path)
version = mimic_path.split('/')[-1][0]
start = time.time()
#----------------------------------------------config----------------------------------------------------
label, tim, disease_label, predW = check_config(task,config_path)
icu_no_icu = config['icu_no_icu']
timeW = config['timeWindow']
include=int(timeW.split()[1])
bucket = config['timebucket']
radimp = config['radimp']
diag_flag = config['diagnosis']
proc_flag= config['proc']
med_flag = config['meds']
disease_filter = config['disease_filter']
groupingDiag = config['groupingDiag']
select_diag= config['select_diag']
select_med= config['select_med']
select_proc= config['select_proc']
if icu_no_icu=='ICU':
out_flag = config['output']
chart_flag = config['chart']
select_out= config['select_out']
select_chart= config['select_chart']
lab_flag = False
select_lab = False
else:
lab_flag = config['lab']
groupingMed = config['groupingMed']
groupingProc = config['groupingProc']
select_lab= config['select_lab']
out_flag = False
chart_flag = False
select_out= False
select_chart= False
# -------------------------------------------------------------------------------------------------------------
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':
cohort_output = extract_data(icu_no_icu,label,tim,icd_code, root_dir,version_path,disease_label)
elif version == '1':
cohort_output = day_intervals_cohort.extract_data(icu_no_icu,label,tim,icd_code, root_dir,version_path,disease_label)
#----------------------------------------------FEATURES-------------------------------------------------------
if data_icu :
feature_selection_icu.feature_icu(cohort_output, version_path,diag_flag,out_flag,chart_flag,proc_flag,med_flag)
else:
feature_selection_hosp.feature_nonicu(cohort_output, version_path,diag_flag,lab_flag,proc_flag,med_flag)
#----------------------------------------------GROUPING-------------------------------------------------------
if data_icu:
if diag_flag:
group_diag=groupingDiag
feature_selection_icu.preprocess_features_icu(cohort_output, diag_flag, group_diag,False,False,False,0,0)
else:
if diag_flag:
group_diag=groupingDiag
if med_flag:
group_med=groupingMed
if proc_flag:
group_proc=groupingProc
feature_selection_hosp.preprocess_features_hosp(cohort_output, diag_flag,proc_flag,med_flag,False,group_diag,group_med,group_proc,False,False,0,0)
#----------------------------------------------SUMMARY-------------------------------------------------------
if data_icu:
feature_selection_icu.generate_summary_icu(diag_flag,proc_flag,med_flag,out_flag,chart_flag)
else:
feature_selection_hosp.generate_summary_hosp(diag_flag,proc_flag,med_flag,lab_flag)
#----------------------------------------------FEATURE SELECTION---------------------------------------------
#----------------------------------------------FEATURE SELECTION---------------------------------------------
if data_icu:
if select_chart or select_out or select_diag or select_med or select_proc:
if select_chart:
input('Please edit list of codes in ./data/summary/chart_features.csv to select the chart items to keep and press enter to continue')
if select_out:
input('Please edit list of codes in ./data/summary/out_features.csv to select the output items to keep and press enter to continue')
if select_diag:
input('Please edit list of codes in ./data/summary/diag_features.csv to select the diagnosis ids to keep and press enter to continue')
if select_med:
input('Please edit list of codes in ./data/summary/med_features.csv to select the meds items to keep and press enter to continue')
if select_proc:
input('Please edit list of codes in ./data/summary/proc_features.csv to select the procedures ids to keep and press enter to continue')
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)
else:
if select_diag or select_med or select_proc or select_lab:
if select_diag:
input('Please edit list of codes in ./data/summary/diag_features.csv to select the diagnosis ids to keep and press enter to continue')
if select_med:
input('Please edit list of codes in ./data/summary/med_features.csv to select the meds items to keep and press enter to continue')
if select_proc:
input('Please edit list of codes in ./data/summary/proc_features.csv to select the procedures ids to keep and press enter to continue')
if select_lab:
input('Please edit list of codes in ./data/summary/labs_features.csv to select the labs items to keep and press enter to continue')
feature_selection_hosp.features_selection_hosp(cohort_output, diag_flag,proc_flag,med_flag,lab_flag,select_diag,select_med,select_proc,select_lab)
#---------------------------------------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)
else:
if lab_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_hosp.preprocess_features_hosp(cohort_output, False,False, False,lab_flag,False,False,False,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=Generator(task,cohort_output,data_mort,data_admn,data_los,diag_flag,proc_flag,out_flag,chart_flag,med_flag,impute,include,bucket,predW)
else:
gen=Generator(cohort_output,data_mort,data_admn,data_los,diag_flag,lab_flag,proc_flag,med_flag,impute,include,bucket,predW)
end = time.time()
print("Time elapsed : ", round((end - start)/60,2),"mins")
print("[============TASK COHORT SUCCESSFULLY CREATED============]")
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