template_settings["params"], minimizer_settings,
args.save_steps, check_octant)
output[data_tag]["true_h_fiducial"] = trials
# If we do not run the alt_fit, then we simply continue in the for
# loop and the LLR distributions will be interpreted as the
# ability to discriminate between hierarchies, without fitting for
# the false hierarchy parameters that match best to the True
# hierarchy fiducial model.
if not args.no_alt_fit:
logging.info("Running false hierarchy best fit...")
output[data_tag]["false_h_best_fit"] = {}
false_h_params = fix_non_atm_params(template_settings['params'])
false_h_settings, llh_data = getAltHierarchyBestFit(
asimov_data, template_maker, false_h_params, minimizer_settings,
(not data_normal), check_octant)
asimov_data_null = get_asimov_fmap(
template_maker=template_maker,
fiducial_params=false_h_settings,
channel=false_h_settings['channel'])
# Store all data tag related inputs:
output[data_tag]['false_h_best_fit']['false_h_settings'] = false_h_settings
output[data_tag]['false_h_best_fit']['llh_null'] = llh_data
trials = get_llh_hypothesis(
data_tag, asimov_data_null, args.ntrials, template_maker,
'minimizer_settings': minimizer_settings
}
asimov_data = {}
asimov_data_null = {}
alt_mh_settings = {}
for data_tag, data_normal in [('true_NMH', True), ('true_IMH', False)]:
tprofile.info("Assuming: %s" % data_tag)
output[data_tag] = {}
# Get Asimov data set for assuming true: data_tag
asimov_data = getAsimovData(template_maker, template_settings['params'],
data_normal)
alt_params = fix_non_atm_params(template_settings['params'])
alt_mh_settings, llh_data = getAltHierarchyBestFit(
asimov_data, template_maker, alt_params, minimizer_settings,
(not data_normal), check_octant)
asimov_data_null = get_asimov_fmap(template_maker=template_maker,
fiducial_params=alt_mh_settings,
channel=alt_mh_settings['channel'])
# Store all data tag related inputs:
output[data_tag]['asimov_data'] = asimov_data
output[data_tag]['asimov_data_null'] = asimov_data_null
output[data_tag]['alt_mh_settings'] = alt_mh_settings
output[data_tag]['llh_null'] = llh_data
# If we are not taking the best fit of the asimov data to the