def cal_estimation(case_config, input_file, results_file, utility_parameter):
process = subprocess.call([
'Rscript --vanilla {r_script_file} {input_file} '
'{number_of_alternatives} {case_config} {utility_parameter} {city_list} {results_file} '
'{alternative_2_variables} {alternative_3_variables} {alternative_4_variables} '
'{alternative_5_variables} {alternative_6_variables} {alternative_7_variables} {alternative_8_variables}'
.format(
r_script_file=RUNNER_MDCEV,
input_file=input_file,
number_of_alternatives=STATE_LISTS.__len__(),
case_config=case_config,
utility_parameter=convert_list_to_str(utility_parameter),
city_list=convert_list_to_str(STATE_LISTS),
results_file=results_file,
alternative_2_variables=convert_list_to_str(utility_parameter),
alternative_3_variables=convert_list_to_str(utility_parameter),
alternative_4_variables=convert_list_to_str(utility_parameter),
alternative_5_variables=convert_list_to_str(utility_parameter),
alternative_6_variables=convert_list_to_str(utility_parameter),
alternative_7_variables=convert_list_to_str(utility_parameter),
alternative_8_variables=convert_list_to_str(utility_parameter),
)
],
shell=True)
return process
def cal_estimation(case_config, input_file, results_file, utility_parameter):
process = subprocess.call([
'Rscript --vanilla {r_script_file} {input_file} {number_of_alternatives} {case_config} {utility_parameter} {city_list} {results_file}'
.format(r_script_file=RUNNER_MDCEV,
input_file=input_file,
number_of_alternatives=CITY_LISTS.__len__(),
case_config=case_config,
utility_parameter=utility_parameter,
city_list=convert_list_to_str(CITY_LISTS),
results_file=results_file)
],
shell=True)
return process
def estimation(self):
for case_config in self.case_config_list:
estimation_output_file = self._create_estimation_output_filename(
case_config)
print('This is the estimation file', estimation_output_file)
process = subprocess.call([
'Rscript --vanilla {r_script} {input_file} '
'{number_of_alternatives} {case_config} {utility_parameters} {state_list} {results_file} '
'{alternative_2_variables} {alternative_3_variables} {alternative_4_variables} '
'{alternative_5_variables} {alternative_6_variables} {alternative_7_variables} {alternative_8_variables}'
.format(
r_script=self.r_estimation,
input_file=self.model_data_file,
number_of_alternatives=self.alternative_list.__len__(),
case_config=case_config,
utility_parameters=convert_list_to_str(
self.utility_variables),
state_list=convert_list_to_str(self.alternative_list),
results_file=estimation_output_file,
alternative_2_variables=convert_list_to_str(
self.alternatives_utility_variables[0]),
alternative_3_variables=convert_list_to_str(
self.alternatives_utility_variables[1]),
alternative_4_variables=convert_list_to_str(
self.alternatives_utility_variables[2]),
alternative_5_variables=convert_list_to_str(
self.alternatives_utility_variables[3]),
alternative_6_variables=convert_list_to_str(
self.alternatives_utility_variables[4]),
alternative_7_variables=convert_list_to_str(
self.alternatives_utility_variables[5]),
alternative_8_variables=convert_list_to_str(
self.alternatives_utility_variables[6]),
)
],
shell=True)
return
estimation_output_file = RESULTS_PATH + '/results' + '_{}'.format(
case_config) + '_{}'.format('MDCEV_2') + '.txt'
forecast_output_file = RESULTS_PATH + '/results' + '_{}'.format(
case_config) + '_{}'.format('MDCEV_2') + '.txt'
print estimation_output_file
process = subprocess.call([
'Rscript --vanilla {r_script_file} {input_file} '
'{number_of_alternatives} {case_config} {utility_parameters} {state_list} {results_file} '
'{alternative_2_variables} {alternative_3_variables} {alternative_4_variables} '
'{alternative_5_variables} {alternative_6_variables}'.format(
r_script_file=RUNNER_MDCEV,
input_file=input_file_path,
number_of_alternatives=STATE_LISTS.__len__(),
case_config=case_config,
utility_parameters=convert_list_to_str(UTILITY_VARIABLES),
state_list=convert_list_to_str(STATE_LISTS),
results_file=estimation_output_file,
alternative_2_variables=convert_list_to_str(
UTILITY_VARIABLES_ALTERNATIVES[0]),
alternative_3_variables=convert_list_to_str(
UTILITY_VARIABLES_ALTERNATIVES[1]),
alternative_4_variables=convert_list_to_str(
UTILITY_VARIABLES_ALTERNATIVES[2]),
alternative_5_variables=convert_list_to_str(
UTILITY_VARIABLES_ALTERNATIVES[3]),
alternative_6_variables=convert_list_to_str(
UTILITY_VARIABLES_ALTERNATIVES[4]),
)
],
shell=True)
variable_in_names = ''
for i, item in enumerate(variable_combination):
variable_in_names += str(item)
if i != len(variable_combination) - 1:
variable_in_names += '-'
# write the file
input_file_path = INPUT_DIR_PATH + '/input' + '_{}'.format(
case_config) + '_{}'.format(variable_in_names) + '.csv'
write_data_to_csv(input_file_path, results)
output_file_path = RESULTS_PATH + '/results' + '_{}'.format(
case_config) + '_{}'.format(variable_in_names) + '.txt'
list_of_estimations.append(
(case_config, input_file_path, output_file_path,
convert_list_to_str(variable_combination)))
# multiprocessing CAREFUL, DANGEROURS !!!!!! Monster !!!!!
pool = Pool(processes=6)
for item in list_of_estimations:
print item
pool.apply_async(cal_estimation, (item[0], item[1], item[2], item[3]))
pool.close()
pool.join()
#
# for case_config in case_config_list:
# # To exclude the parameter
# list_of_variables = case_config_excluding_variables(case_config)
#
# # generate the combination of the lists