from information_boards import productivity_summary_fpath from information_boards import shiftProDur_dpath, shiftProDur_prefix from information_boards import AM2, AM5 from information_boards import SEC3600, SEC60 from information_boards import ALL_DUR, ALL_FARE, ALL_NUM from information_boards import AP_DUR, AP_FARE, AP_QUEUE, AP_NUM from information_boards import NS_DUR, NS_FARE, NS_QUEUE, NS_NUM # from taxi_common.file_handling_functions import check_dir_create, check_path_exist, get_all_files from taxi_common.multiprocess import init_multiprocessor, put_task, end_multiprocessor from taxi_common.log_handling_functions import get_logger # import csv, gzip import time, datetime logger = get_logger() def run(): for dpath in [productivity_dpath, shiftProDur_dpath]: check_dir_create(dpath) # # init_multiprocessor(11) # count_num_jobs = 0 # for y in xrange(9, 11): # for m in xrange(1, 13): # yymm = '%02d%02d' % (y, m) # if yymm in ['0912', '1010']: # continue # # process_file(yymm) # # put_task(productive_duration, [yymm])
''' # from community_analysis import tfZ_TP_dpath, tfZ_TP_prefix from community_analysis import dpaths, prefixs from community_analysis import SIGINIFICANCE_LEVEL, MIN_PICKUP_RATIO # from taxi_common.file_handling_functions import check_dir_create, get_all_files, get_fn_only, check_path_exist, save_pickle_file from taxi_common.log_handling_functions import get_logger from taxi_common.multiprocess import init_multiprocessor, put_task, end_multiprocessor # import pandas as pd import numpy as np import statsmodels.api as sm from traceback import format_exc logger = get_logger() def run(): ir = 'influenceGraph' # for tm in ['spendingTime', 'roamingTime']: for tm in ['spendingTime']: for year in ['2009', '2010', '2011', '2012']: check_dir_create(dpaths[tm, year, ir]) yyyy = '20%02d' % 9 for tfZ_TP_fn in get_all_files(tfZ_TP_dpath, '%s%s*.csv' % (tfZ_TP_prefix, yyyy)): tfZ_TP_fpath = '%s/%s' % (tfZ_TP_dpath, tfZ_TP_fn) process_file(tfZ_TP_fpath)