# File Names
var_exist_summary_file_name = '{}_var_exist_summary.csv'.format(date)
trip_enviro_stats_summary_file_name = '{}_trip_enviro_stats_summary.csv'.format(
date)
trip_cf_stats_summary_file_name = '{}_trip_cf_summary.csv'.format(date)
trip_cf_enviro_stats_summary_file_name = '{}_trip_cf_enviro_stats_summary.csv'.format(
date)
trip_cf_enviro_stats_demo_behav_summary_file_name = '{}_trip_cf_enviro_stats_demo_behav_summary.csv'.format(
date)
TS_summary_file_name = '{}_TS_summary.csv'.format(date)
CFS_summary_file_name = '{}_CFS_summary.csv'.format(date)
phase1_trip_enviro_stats_summary_file_name = '{}_ph1_trip_enviro_stats_summary.csv'.format(
date)
# Read in trip numbers from file
trip_num = import_trip_ids(open_global_input_path, trip_no_for_processing)
# Check validity of each trip number before starting analysis
check_files_exist(trip_num, open_nds_data_path, nds_file_name_start)
# Initialize multi-trip summary files
if generate_variable_exist_summary_file is True:
var_exist_summary_file = open(
os.path.join(save_path_start, var_exist_summary_file_name), 'a')
NDSfile = '{}_{}.csv'.format(nds_file_name_start, trip_num[0][0])
point_collection = import_wy_nds(nds_file_name=NDSfile,
path=open_nds_data_path)
initiate_var_exist_summary_file(file=var_exist_summary_file,
point_collection=point_collection)
del NDSfile
del point_collection
print "---------------------------------------------------------------------------"
# GA Inputs - Identified from sensitivity analysis!
# ----------------------------------------------------------------------------------------
cxpb, mutpb, m_indpb, ngen, npop = 0.5, 0.2, 0.4, 60, 800
# Car-Following Event Requirements ** MUST MATCH MATCHING CRITERIA!
# ----------------------------------------------------------------------------------------
min_cf_time, max_cf_dist, min_speed = 20, 60, 1 # s, m, m/s
# Input Trip Numbers
# ----------------------------------------------------------------------------------------
nds_file_name_start = 'Event_ID'
# Read in trip numbers from file
trip_no_list = import_trip_ids(trip_id_input_path, trip_no_for_processing)
# Check validity of each trip number before starting analysis
check_files_exist(trip_no_list, nds_data_input_path, nds_file_name_start)
# Initiate Summary File
# ----------------------------------------------------------------------------------------
summary_file = open(
os.path.join(save_path,
'{}_summary_{}'.format(date, trip_no_for_processing)), 'a')
initiate_201802Calib_gipps_summary_file(summary_file)
summary_file.close() # Only open file when writing!
print "---------------------------------------------------------------------------"
for iterator in range(len(trip_no_list)):
# GA Inputs - Identified from sensitivity analysis!
# ----------------------------------------------------------------------------------------
cxpb, mutpb, m_indpb, ngen, npop = 0.7, 0.4, 0.6, 60, 800
# Car-Following Event Requirements ** MUST MATCH MATCHING CRITERIA!
# ----------------------------------------------------------------------------------------
min_cf_time, max_cf_dist, min_speed = 20, 60, 1 # s, m, m/s
# Input Trip Numbers
# ----------------------------------------------------------------------------------------
nds_file_name_start = 'Event_ID'
# Iterate for each input file:
for trip_nos_filename in trip_nos_filename_list:
# Read in trip numbers from file
trip_no_list = import_trip_ids(trip_id_input_path, trip_nos_filename)
# Check validity of each trip number before starting analysis
check_files_exist(trip_no_list, nds_data_input_path, nds_file_name_start)
print "---------------------------------------------------------------------------"
cf_collections_all = list()
for iterator in range(len(trip_no_list)):
start_time = timeit.default_timer()
trip_no_this = trip_no_list[iterator][0] # trip number for current iteration
print "{}: {}".format(iterator + 1, trip_no_this)
point_collection, cf_collections, stac_data_available = generate_cf_collections_nds(