def main():
"""MAIN FUNCTION."""
cf, psa_mtd = get_psa_config()
print('### START TO PARAMETERS SENSITIVITY ANALYSIS ###')
start_t = time.time()
cfg = PSAConfig(cf, method=psa_mtd)
saobj = Sensitivity(cfg)
saobj.run()
print('### END OF PARAMETERS SENSITIVITY ANALYSIS ###')
print('Running time: %.2fs' % (time.time() - start_t))
# Plot figures
saobj.plot()
def write_sensitivity_config_file(mpaths, org_file_name):
org_cfg_file = mpaths.cfg_dir + os.path.sep + org_file_name
psa_cfg_file = mpaths.workspace + os.path.sep + org_file_name
cfg_items = list()
with open(org_cfg_file, 'r', encoding='utf-8') as f:
for line in f.readlines():
cfg_items.append(line.strip())
cfg_items.append('MODEL_DIR = %s' % mpaths.model_dir)
cfg_items.append('BIN_DIR = %s' % mpaths.bin_dir)
with open(psa_cfg_file, 'w', encoding='utf-8') as f:
for item in cfg_items:
f.write('%s\n' % item)
cf = ConfigParser()
cf.read(psa_cfg_file)
return PSAConfig(cf)
if 'NSE' in objn: # NSE series, i.e., NSE, lnNSE, NSE1, and NSE3
empirical_cdf(values, [0], self.param_values, param_names,
self.cfg.morris.num_levels,
self.cfg.psa_outpath, 'cdf_%s' % self.objnames[i],
{'histtype': 'step'})
elif 'R-square' in objn: # R-square, equally divided as two classes
empirical_cdf(values, 2, self.param_values, param_names,
self.cfg.morris.num_levels,
self.cfg.psa_outpath, 'cdf_%s' % self.objnames[i],
{'histtype': 'step'})
elif 'RSR' in objn: # RSR
empirical_cdf(values, [1], self.param_values, param_names,
self.cfg.morris.num_levels,
self.cfg.psa_outpath, 'cdf_%s' % self.objnames[i],
{'histtype': 'step'})
if __name__ == '__main__':
from config import get_psa_config
cf, method = get_psa_config()
cfg = PSAConfig(cf, method=method)
print(cfg.param_range_def)
saobj = Sensitivity(cfg)
saobj.write_param_values_to_mongodb()
# saobj.calculate_sensitivity()
# saobj.plot_samples_histogram()
# saobj.plot_morris()