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