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)
