def run_all(mode, robust=False): _, configloc, _, _ = config_setup.get_locations(mode) fullrun_config = json.load( open(os.path.join(configloc, 'config_full' + '.json'))) # Flag indicating whether calculated results should be written to disk writeoutput = fullrun_config['writeoutput'] # Provide the mode and case names to calculate mode = fullrun_config['mode'] cases = fullrun_config['cases'] for case in cases: logging.info("Now attempting case: " + case) run_weightcalc(configloc, writeoutput, mode, case, robust) run_createarrays(writeoutput, mode, case, robust) run_trendextraction(writeoutput, mode, case, robust) run_noderank(writeoutput, mode, case, robust) run_graphreduce(writeoutput, mode, case, robust) run_plotting(writeoutput, mode, case, robust) logging.info("Done with case: " + case)
def run_all(mode, robust=False): _, configloc, _, _ = config_setup.get_locations(mode) with open(os.path.join(configloc, "config_full" + ".json")) as f: fullrun_config = json.load(f) f.close() # Flag indicating whether calculated results should be written to disk writeoutput = fullrun_config["writeoutput"] # Provide the mode and case names to calculate mode = fullrun_config["mode"] cases = fullrun_config["cases"] for case in cases: logging.info("Now attempting case: " + case) run_weightcalc(configloc, writeoutput, mode, case, robust) run_createarrays(writeoutput, mode, case, robust) run_trendextraction(writeoutput, mode, case, robust) run_noderank(writeoutput, mode, case, robust) run_graphreduce(writeoutput, mode, case, robust) run_plotting(writeoutput, mode, case, robust) logging.info("Done with case: " + case)
configuration file. """ # Standard modules import json import logging import multiprocessing import os import config_setup from ranking.gaincalc import weightcalc if __name__ == "__main__": multiprocessing.freeze_support() logging.basicConfig(level=logging.INFO) dataloc, configloc, _, _ = config_setup.get_locations() weightcalc_config = json.load( open(os.path.join(configloc, "config_weightcalc" + ".json"))) # Flag indicating whether calculated results should be written to disk writeoutput = weightcalc_config["writeoutput"] # Flag indicating whether single signal entropy values for each # signal involved should be calculated single_entropies = weightcalc_config["calc_single_entropies"] # Provide the mode and case names to calculate mode = weightcalc_config["mode"] cases = weightcalc_config["cases"] fftcalc = weightcalc_config["fft_calc"] do_multiprocessing = weightcalc_config["multiprocessing"] for case in cases:
# -*- coding: utf-8 -*- """Calculates and writes weight_array and delay_array for different weight types from data generated by run_weightcalc process. """ import json import logging import os import config_setup from ranking.data_processing import result_reconstruction logging.basicConfig(level=logging.INFO) dataloc, configloc, _, _ = config_setup.get_locations() createarrays_config = json.load( open(os.path.join(configloc, "config" "_createarrays" + ".json")) ) writeoutput = createarrays_config["writeoutput"] mode = createarrays_config["mode"] cases = createarrays_config["cases"] for case in cases: result_reconstruction(mode, case, writeoutput)