csv.cov_both_xam¶

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Example and Test of covariate_both¶

Covariates¶

This example has two covariates, haqi and income.

haqi¶

This covariate only depends on age and time; i.e., it is the same for all nodes and both sexes.

income¶

This covariate depends on age, time, and sex. It is the same for all nodes.

covariate_table¶

The covariate table is shuffled, after it is created, to demonstrate the fact that the order of its rows does not matter.

haqi¶

This covariate is the same for all nodes and both sexes.

income¶

This covariate is different for each sex, but given sex it is the same for all nodes.

Source¶

# at_cascade
# import at_cascade with a preference current directory version
import os
import sys
import random
current_directory = os.getcwd()
if os.path.isfile( current_directory + '/at_cascade/__init__.py' ) :
   sys.path.insert(0, current_directory)
import at_cascade
#
# haqi
def haqi(node, sex, age, time) :
   value = age / 100.0 + (time - 2000) / 20.0 + 0.01
   value = round(value, 4)
   return value
#
# income
def income(node, sex, age, time) :
   value = age / 100.0 + (2000 - time) / 20.0
   if sex == 'female' :
      value += 1.0
   else :
      value += 2.0
   value = round(value, 4)
   return value
#
# main
def main() :
   #
   age_list  = [ 20.0, 80.0 ]
   time_list = [ 1980.0, 2020.0 ]
   node_list = [ 'n0', 'n1', 'n2' ]
   sex_list  = [ 'female', 'male' ]
   cov_list  = [ 'haqi', 'income' ]
   omega     = 0.02
   #
   # covariate_table_in
   covariate_table_in = list()
   for node_name in node_list :
      for sex in sex_list :
         for age in age_list :
            for time in time_list :
               row = {
                  'node_name' : node_name ,
                  'sex'       : sex ,
                  'age'       : age ,
                  'time'      : time ,
                  'omega'     : omega ,
                  'haqi'      : haqi(  node_name, sex, age, time) ,
                  'income'    : income(node_name, sex, age, time) ,
               }
               covariate_table_in.append(row)
   random.shuffle(covariate_table_in)
   #
   # same cov
   covariate_table_out = at_cascade.csv.covariate_both(covariate_table_in)
   #
   # count
   count = { 'female' : 0, 'male' : 0 , 'both' : 0 }
   for row in covariate_table_out :
      count[ row['sex'] ] += 1
   #
   for sex in count :
      assert count[sex] == len(node_list) * len(age_list) * len(time_list)
   #
   print('cov_both_xam.py: OK')
#
if __name__ == '__main__' :
   main()