def create_fit_data( path, variables, fit_variables, mc_samples, COMEnergies, channels ): ''' Creates the fit data in path + fit_check_data.txt in the JSON format. The resulting dictionary is of the form {centre-of-mass-energy: { channel : { variable : { variable_bin : { fit_variable : { templates : { sample : []}, initial_values : { sample : []} } } } } } } ''' # first step is to read the data raw_data = {} # the folder structure is # path/fit_variable/centre-of-mass-energy/variable/fit_results/central/* for fit_variable in fit_variables: raw_data[fit_variable] = {} for COMEnergy in COMEnergies: raw_data[fit_variable][COMEnergy] = {} for variable in variables: raw_data[fit_variable][COMEnergy][variable] = {} for channel in channels: raw_data[fit_variable][COMEnergy][variable][channel] = {} data_path = path + '/' + fit_variable + '/' + str( COMEnergy ) + 'TeV' templates = read_fit_templates( data_path, variable, channel = channel ) initial_values = read_initial_normalisation( data_path, variable, channel = channel ) raw_data[fit_variable][COMEnergy][variable][channel]['templates'] = templates raw_data[fit_variable][COMEnergy][variable][channel]['initial_values'] = initial_values # put it into the new structure fit_data = {} for COMEnergy in COMEnergies: fit_data[COMEnergy] = {} for channel in channels: fit_data[COMEnergy][channel] = {} for variable in variables: fit_data[COMEnergy][channel][variable] = {} for v_bin in variable_bins_ROOT[variable]: fit_data[COMEnergy][channel][variable][v_bin] = {} for fit_variable in fit_variables: fit_data[COMEnergy][channel][variable][v_bin][fit_variable] = {} fit_data[COMEnergy][channel][variable][v_bin][fit_variable]['templates'] = raw_data[fit_variable][COMEnergy][variable][channel]['templates'] fit_data[COMEnergy][channel][variable][v_bin][fit_variable]['initial_values'] = raw_data[fit_variable][COMEnergy][variable][channel]['initial_values'] write_data_to_JSON( fit_data, path + '/fit_check_data.txt', indent = False )
def makeClosureTestTable(): fitVariable='absolute_eta_M3_angle_bl' for channel in channels: print 'CHANNEL :',channel for variable in variables: print '--->',variable # Read fit results dir = 'data/'+fitVariable+'/'+com+'/' if closureTest : dir = 'data/closure_test/simple/'+fitVariable+'/'+com+'/' fit_results = read_normalisation( dir, variable, 'central', channel, 'patType1CorrectedPFMet' ) # Read initial values initial_values = read_initial_normalisation( dir, variable, 'central', channel, 'patType1CorrectedPFMet' ) # for whichBin in range (0,len(bin_edges[variable])-1): for whichBin in range (0,1): for process in processes: scale = closure_tests['simple'][process] line = '%s ' % (samples_latex[process]) line += '& %.0f ' % initial_values[process][whichBin][0] line += '& %.0f ' % (initial_values[process][whichBin][0]*scale) line += '& %.0f \pm %.0f ' % (fit_results[process][whichBin][0],fit_results[process][whichBin][1]) line += '\\\\' print line # print process # print scale # print initial_values[process][whichBin][0] # print initial_values[process][whichBin][0]*scale # print fit_results[process][whichBin][0],'+/-',fit_results[process][whichBin][1] pass pass print '\n' pass pass pass
def makeClosureTestTable(): fitVariable = 'absolute_eta_M3_angle_bl' for channel in channels: print 'CHANNEL :', channel for variable in variables: print '--->', variable # Read fit results dir = 'data/' + fitVariable + '/' + com + '/' if closureTest: dir = 'data/closure_test/simple/' + fitVariable + '/' + com + '/' fit_results = read_normalisation(dir, variable, 'central', channel, 'patType1CorrectedPFMet') # Read initial values initial_values = read_initial_normalisation( dir, variable, 'central', channel, 'patType1CorrectedPFMet') # for whichBin in range (0,len(bin_edges[variable])-1): for whichBin in range(0, 1): for process in processes: scale = closure_tests['simple'][process] line = '%s ' % (samples_latex[process]) line += '& %.0f ' % initial_values[process][whichBin][0] line += '& %.0f ' % (initial_values[process][whichBin][0] * scale) line += '& %.0f \pm %.0f ' % ( fit_results[process][whichBin][0], fit_results[process][whichBin][1]) line += '\\\\' print line # print process # print scale # print initial_values[process][whichBin][0] # print initial_values[process][whichBin][0]*scale # print fit_results[process][whichBin][0],'+/-',fit_results[process][whichBin][1] pass pass print '\n' pass pass pass
def create_fit_data(path, variables, fit_variables, mc_samples, COMEnergies, channels): ''' Creates the fit data in path + fit_check_data.txt in the JSON format. The resulting dictionary is of the form {centre-of-mass-energy: { channel : { variable : { variable_bin : { fit_variable : { templates : { sample : []}, initial_values : { sample : []} } } } } } } ''' # first step is to read the data raw_data = {} # the folder structure is # path/fit_variable/centre-of-mass-energy/variable/fit_results/central/* for fit_variable in fit_variables: raw_data[fit_variable] = {} for COMEnergy in COMEnergies: raw_data[fit_variable][COMEnergy] = {} for variable in variables: raw_data[fit_variable][COMEnergy][variable] = {} for channel in channels: raw_data[fit_variable][COMEnergy][variable][channel] = {} data_path = path + '/' + fit_variable + '/' + str( COMEnergy) + 'TeV' templates = read_fit_templates(data_path, variable, channel=channel) initial_values = read_initial_normalisation( data_path, variable, channel=channel) raw_data[fit_variable][COMEnergy][variable][channel][ 'templates'] = templates raw_data[fit_variable][COMEnergy][variable][channel][ 'initial_values'] = initial_values # put it into the new structure fit_data = {} for COMEnergy in COMEnergies: fit_data[COMEnergy] = {} for channel in channels: fit_data[COMEnergy][channel] = {} for variable in variables: fit_data[COMEnergy][channel][variable] = {} for v_bin in variable_bins_ROOT[variable]: fit_data[COMEnergy][channel][variable][v_bin] = {} for fit_variable in fit_variables: fit_data[COMEnergy][channel][variable][v_bin][ fit_variable] = {} fit_data[COMEnergy][channel][variable][v_bin][ fit_variable]['templates'] = raw_data[ fit_variable][COMEnergy][variable][channel][ 'templates'] fit_data[COMEnergy][channel][variable][v_bin][ fit_variable]['initial_values'] = raw_data[ fit_variable][COMEnergy][variable][channel][ 'initial_values'] write_data_to_JSON(fit_data, path + '/fit_check_data.txt', indent=False)
def main(argv=None): '''Command line options.''' program_name = os.path.basename(sys.argv[0]) program_version = "v0.1" program_build_date = "%s" % __updated__ program_version_string = '%%prog %s (%s)' % ( program_version, program_build_date) # program_usage = '''usage: spam two eggs''' # optional - will be # autogenerated by optparse program_longdesc = '''''' # optional - give further explanation about what the program does program_license = "Copyright 2015 user_name (organization_name) \ Licensed under the Apache License 2.0\nhttp://www.apache.org/licenses/LICENSE-2.0" if argv is None: argv = sys.argv[1:] # setup option parser parser = OptionParser( version=program_version_string, epilog=program_longdesc, description=program_license) parser.add_option( "-i", "--in", dest="input_path", help="set input path [default: %default]") parser.add_option( "-o", "--out", dest="output_path", help="set output path [default: %default]") parser.add_option("-v", "--variable", dest="variable", help="set the variable to analyse (MET, HT, ST, MT, WPT) [default: %default]") parser.add_option("-c", "--centre-of-mass-energy", dest="com", type=int, help="set the centre of mass energy in TeV for analysis. [default: %default]") parser.add_option('--visiblePS', dest="visiblePS", action="store_true", help="Unfold to visible phase space") # set defaults parser.set_defaults( output_path="tables/background_subtraction/", input_path="data/normalisation/background_subtraction/", com=13, variable='MET', ) # process options (opts, _) = parser.parse_args(argv) # MAIN BODY # config = XSectionConfig(opts.com) met_type = config.translate_options['type1'] variable = opts.variable output_path = opts.output_path input_path = opts.input_path visiblePS = opts.visiblePS if not output_path.endswith('/'): output_path += '/' phase_space = 'FullPS' if visiblePS: phase_space = 'VisiblePS' path_to_JSON = '{path}/{com}TeV/{variable}/{phase_space}/'.format( path=input_path, com=opts.com, variable=variable, phase_space=phase_space, ) # categories_and_prefixes = config.categories_and_prefixes # categories = deepcopy(categories_and_prefixes.keys()) for channel in ['electron', 'muon']: # , 'combined']: # read results unfolded_normalisation = read_unfolded_normalisation( path_to_JSON=path_to_JSON, category='central', channel=channel, met_type=met_type, ) initial_normalisation = read_initial_normalisation( path_to_JSON=path_to_JSON, category='central', channel=channel, met_type=met_type, ) mylog.debug('initial normalisation entries: ') mylog.debug(initial_normalisation.keys()) mylog.debug('unfolded normalisation entries: ') mylog.debug(unfolded_normalisation.keys()) print_result_table( config, channel, opts, initial_normalisation, unfolded_normalisation, )
print_before_unfolding=False, ) print_error_table( normalised_xsection_measured_unfolded, normalised_xsection_measured_errors, channel, toFile=True, print_before_unfolding=True, ) if channel == "combined": print_typical_systematics_table( normalised_xsection_measured_unfolded, normalised_xsection_unfolded_errors, channel, toFile=True, print_before_unfolding=False, ) print_typical_systematics_table( normalised_xsection_measured_unfolded, normalised_xsection_measured_errors, channel, toFile=True, print_before_unfolding=True, ) if not channel == "combined" and not channel == "combinedBeforeUnfolding": fit_input = read_initial_normalisation(path_to_JSON, variable, "central", channel, met_type) fit_results = read_normalisation(path_to_JSON, variable, "central", channel, met_type) print_fit_results_table(fit_input, fit_results, channel, toFile=True)
fit_results_ = read_normalisation( 'data/closure_test/'+test+'/absolute_eta_M3_angle_bl/8TeV/', variable, 'central', 'electron', 'patType1CorrectedPFMet' ) fit_templates_ = read_fit_templates( 'data/closure_test/'+test+'/absolute_eta_M3_angle_bl/8TeV/', variable, 'central', 'electron', 'patType1CorrectedPFMet' ) initial_values_ = read_initial_normalisation( 'data/closure_test/'+test+'/absolute_eta_M3_angle_bl/8TeV/', variable, 'central', 'electron', 'patType1CorrectedPFMet' ) for whichBin in range (0,len(fit_results_['TTJet'])): for fitVariable in fit_variable_properties: fitTemplates = fit_templates_[fitVariable] histograms = {} for template in fitTemplates: nBins = len(fitTemplates[template][whichBin]) histograms[template] = Hist(nBins,fit_variable_properties[fitVariable]['min'],fit_variable_properties[fitVariable]['max'],name=template) for bin in range(0,nBins): histograms[template].SetBinContent( bin, fitTemplates[template][whichBin][bin] )