text: from __future__ import absolute_import
  from __future__ import print_function
  import datetime as dt
  
  import csv
  import numpy as np
  import os
  import pandas as pd
  import sys
  
  from mimic3benchmark.util import *
  
  
  def read_patients_table(mimic3_path):
      pats = dataframe_from_csv(os.path.join(mimic3_path, 'PATIENTS.csv'))
      pats = pats[['SUBJECT_ID', 'GENDER', 'DOB', 'DOD']]
      pats.DOB = pd.to_datetime(pats.DOB)
      pats.DOD = pd.to_datetime(pats.DOD)
      return pats
  
  
  def read_admissions_table(mimic3_path):
      admits = dataframe_from_csv(os.path.join(mimic3_path, 'ADMISSIONS.csv'))
      admits = admits[['SUBJECT_ID', 'HADM_ID', 'ADMITTIME', 'DISCHTIME', 'DEATHTIME', 'ETHNICITY', 'DIAGNOSIS']]
      admits.ADMITTIME = pd.to_datetime(admits.ADMITTIME, errors='coerce')
      admits.DISCHTIME = pd.to_datetime(admits.DISCHTIME, errors='coerce')
      admits.DEATHTIME = pd.to_datetime(admits.DEATHTIME, errors='coerce')
      return admits
  
  
  def read_icustays_table(mimic3_path):
      stays = dataframe_from_csv(os.path.join(mimic3_path, 'ICUSTAYS.csv'))
      stays.INTIME = pd.to_datetime(stays.INTIME, errors='coerce')
      stays.OUTTIME = pd.to_datetime(stays.OUTTIME, errors='coerce')
      return stays
  
  
  def read_icd_diagnoses_table(mimic3_path):
      codes = dataframe_from_csv(os.path.join(mimic3_path, 'D_ICD_DIAGNOSES.csv'))
      codes = codes[['ICD9_CODE', 'SHORT_TITLE', 'LONG_TITLE']]
      diagnoses = dataframe_from_csv(os.path.join(mimic3_path, 'DIAGNOSES_ICD.csv'))
      diagnoses = diagnoses.merge(codes, how='inner', left_on='ICD9_CODE', right_on='ICD9_CODE')
      diagnoses[['SUBJECT_ID', 'HADM_ID', 'SEQ_NUM']] = diagnoses[['SUBJECT_ID', 'HADM_ID', 'SEQ_NUM']].astype(int)
      return diagnoses
  
  
  def read_events_table_by_row(mimic3_path, table):
      nb_rows = {'chartevents': 330712484, 'labevents': 27854056, 'outputevents': 4349219}
      reader = csv.DictReader(open(os.path.join(mimic3_path, table.upper() + '.csv'), 'r'))
      for i, row in enumerate(reader):
          if 'ICUSTAY_ID' not in row:
              row['ICUSTAY_ID'] = ''
          yield row, i, nb_rows[table.lower()]
  
  
  def count_icd_codes(diagnoses, output_path=None):
      codes = diagnoses[['ICD9_CODE', 'SHORT_TITLE', 'LONG_TITLE']].drop_duplicates().set_index('ICD9_CODE')
      codes['COUNT'] = diagnoses.groupby('ICD9_CODE')['ICUSTAY_ID'].count()
      codes.COUNT = codes.COUNT.fillna(0).astype(int)
      codes = codes.ix[codes.COUNT > 0]
      if output_path:
          codes.to_csv(output_path, index_label='ICD9_CODE')
      return codes.sort_values('COUNT', ascending=False).reset_index()
  
  
  def remove_icustays_with_transfers(stays):
      stays = stays.ix[(stays.FIRST_WARDID == stays.LAST_WARDID) & (stays.FIRST_CAREUNIT == stays.LAST_CAREUNIT)]
      return stays[['SUBJECT_ID', 'HADM_ID', 'ICUSTAY_ID', 'LAST_CAREUNIT', 'DBSOURCE', 'INTIME', 'OUTTIME', 'LOS']]
  
  
  def merge_on_subject(table1, table2):
      return table1.merge(table2, how='inner', left_on=['SUBJECT_ID'], right_on=['SUBJECT_ID'])
  
  
  def merge_on_subject_admission(table1, table2):
      return table1.merge(table2, how='inner', left_on=['SUBJECT_ID', 'HADM_ID'], right_on=['SUBJECT_ID', 'HADM_ID'])
  
  
  def add_age_to_icustays(stays):
      intime= stays.INTIME.dt.year
      dob= stays.DOB.dt.year
  
      stays['AGE'] = intime-dob
      # print('ok',type(stays.AGE[100]))
      stays.ix[stays.AGE < 0] = 90
      return stays
  
  
  def add_inhospital_mortality_to_icustays(stays):
      mortality = stays.DOD.notnull() & ((stays.ADMITTIME <= stays.DOD) & (stays.DISCHTIME >= stays.DOD))
      mortality = mortality | (stays.DEATHTIME.notnull() & ((stays.ADMITTIME <= stays.DEATHTIME) & (stays.DISCHTIME >= stays.DEATHTIME)))
      stays['MORTALITY'] = mortality.astype(int)
      stays['MORTALITY_INHOSPITAL'] = stays['MORTALITY']
      return stays
  
  
  def add_inunit_mortality_to_icustays(stays):
      mortality = stays.DOD.notnull() & ((stays.INTIME <= stays.DOD) & (stays.OUTTIME >= stays.DOD))
      mortality = mortality | (stays.DEATHTIME.notnull() & ((stays.INTIME <= stays.DEATHTIME) & (stays.OUTTIME >= stays.DEATHTIME)))
      stays['MORTALITY_INUNIT'] = mortality.astype(int)
      return stays
  
  
  def filter_admissions_on_nb_icustays(stays, min_nb_stays=1, max_nb_stays=1):
      to_keep = stays.groupby('HADM_ID').count()[['ICUSTAY_ID']].reset_index()
      to_keep = to_keep.ix[(to_keep.ICUSTAY_ID >= min_nb_stays) & (to_keep.ICUSTAY_ID <= max_nb_stays)][['HADM_ID']]
      stays = stays.merge(to_keep, how='inner', left_on='HADM_ID', right_on='HADM_ID')
      return stays
  
  
  def filter_icustays_on_age(stays, min_age=18, max_age=np.inf):
      stays = stays.ix[(stays.AGE >= min_age) & (stays.AGE <= max_age)]
      return stays
  
  
  def filter_diagnoses_on_stays(diagnoses, stays):
      return diagnoses.merge(stays[['SUBJECT_ID', 'HADM_ID', 'ICUSTAY_ID']].drop_duplicates(), how='inner',
                             left_on=['SUBJECT_ID', 'HADM_ID'], right_on=['SUBJECT_ID', 'HADM_ID'])
  
  
  def break_up_stays_by_subject(stays, output_path, subjects=None, verbose=1):
      subjects = stays.SUBJECT_ID.unique() if subjects is None else subjects
      nb_subjects = subjects.shape[0]
      for i, subject_id in enumerate(subjects):
          if verbose:
              sys.stdout.write('\rSUBJECT {0} of {1}...'.format(i+1, nb_subjects))
          dn = os.path.join(output_path, str(subject_id))
          try:
              os.makedirs(dn)
          except:
              pass
  
          stays.ix[stays.SUBJECT_ID == subject_id].sort_values(by='INTIME').to_csv(os.path.join(dn, 'stays.csv'), index=False)
      if verbose:
          sys.stdout.write('DONE!\n')
  
  
  def break_up_diagnoses_by_subject(diagnoses, output_path, subjects=None, verbose=1):
      subjects = diagnoses.SUBJECT_ID.unique() if subjects is None else subjects
      nb_subjects = subjects.shape[0]
      for i, subject_id in enumerate(subjects):
          if verbose:
              sys.stdout.write('\rSUBJECT {0} of {1}...'.format(i+1, nb_subjects))
          dn = os.path.join(output_path, str(subject_id))
          try:
              os.makedirs(dn)
          except:
              pass
  
          diagnoses.ix[diagnoses.SUBJECT_ID == subject_id].sort_values(by=['ICUSTAY_ID', 'SEQ_NUM']).to_csv(os.path.join(dn, 'diagnoses.csv'), index=False)
      if verbose:
          sys.stdout.write('DONE!\n')
  
  
  def read_events_table_and_break_up_by_subject(mimic3_path, table, output_path, items_to_keep=None, subjects_to_keep=None, verbose=1):
      obs_header = ['SUBJECT_ID', 'HADM_ID', 'ICUSTAY_ID', 'CHARTTIME', 'ITEMID', 'VALUE', 'VALUEUOM']
      if items_to_keep is not None:
          items_to_keep = set([str(s) for s in items_to_keep])
      if subjects_to_keep is not None:
          subjects_to_keep = set([str(s) for s in subjects_to_keep])
  
      class DataStats(object):
          def __init__(self):
              self.curr_subject_id = ''
              self.last_write_no = 0
              self.last_write_nb_rows = 0
              self.last_write_subject_id = ''
              self.curr_obs = []
  
      data_stats = DataStats()
  
      def write_current_observations():
          data_stats.last_write_no += 1
          data_stats.last_write_nb_rows = len(data_stats.curr_obs)
          data_stats.last_write_subject_id = data_stats.curr_subject_id
          dn = os.path.join(output_path, str(data_stats.curr_subject_id))
          try:
              os.makedirs(dn)
          except:
              pass
          fn = os.path.join(dn, 'events.csv')
          if not os.path.exists(fn) or not os.path.isfile(fn):
              f = open(fn, 'w')
              f.write(','.join(obs_header) + '\n')
              f.close()
          w = csv.DictWriter(open(fn, 'a'), fieldnames=obs_header, quoting=csv.QUOTE_MINIMAL)
          w.writerows(data_stats.curr_obs)
          data_stats.curr_obs = []
  
      for row, row_no, nb_rows in read_events_table_by_row(mimic3_path, table):
          if verbose and (row_no % 100000 == 0):
              if data_stats.last_write_no != '':
                  sys.stdout.write('\rprocessing {0}: ROW {1} of {2}...last write '
                                   '({3}) {4} rows for subject {5}'.format(table, row_no, nb_rows,
                                                                           data_stats.last_write_no,
                                                                           data_stats.last_write_nb_rows,
                                                                           data_stats.last_write_subject_id))
              else:
                  sys.stdout.write('\rprocessing {0}: ROW {1} of {2}...'.format(table, row_no, nb_rows))
  
          if (subjects_to_keep is not None) and (row['SUBJECT_ID'] not in subjects_to_keep):
              continue
          if (items_to_keep is not None) and (row['ITEMID'] not in items_to_keep):
              continue
  
          row_out = {'SUBJECT_ID': row['SUBJECT_ID'],
                     'HADM_ID': row['HADM_ID'],
                     'ICUSTAY_ID': '' if 'ICUSTAY_ID' not in row else row['ICUSTAY_ID'],
                     'CHARTTIME': row['CHARTTIME'],
                     'ITEMID': row['ITEMID'],
                     'VALUE': row['VALUE'],
                     'VALUEUOM': row['VALUEUOM']}
          if data_stats.curr_subject_id != '' and data_stats.curr_subject_id != row['SUBJECT_ID']:
              write_current_observations()
          data_stats.curr_obs.append(row_out)
          data_stats.curr_subject_id = row['SUBJECT_ID']
  
      if data_stats.curr_subject_id != '':
          write_current_observations()
  
      if verbose:
          sys.stdout.write('\rfinished processing {0}: ROW {1} of {2}...last write '
                           '({3}) {4} rows for subject {5}...DONE!\n'.format(table, row_no, nb_rows,
                                                                             data_stats.last_write_no,
                                                                             data_stats.last_write_nb_rows,
                                                                             data_stats.last_write_subject_id))
  