def draw_regularisation_histograms( h_truth, h_measured, h_response, h_fakes = None, h_data = None ):
global method, variable, output_folder, output_formats, test
k_max = h_measured.nbins()
unfolding = Unfolding( h_truth,
h_measured,
h_response,
h_fakes,
method = method,
k_value = k_max,
error_treatment = 4,
verbose = 1 )
RMSerror, MeanResiduals, RMSresiduals, Chi2 = unfolding.test_regularisation ( h_data, k_max )
histogram_properties = Histogram_properties()
histogram_properties.name = 'chi2_%s_channel_%s' % ( channel, variable )
histogram_properties.title = '$\chi^2$ for $%s$ in %s channel, %s test' % ( variables_latex[variable], channel, test )
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = '$\chi^2$'
histogram_properties.set_log_y = True
make_plot(Chi2, 'chi2', histogram_properties, output_folder, output_formats, draw_errorbar = True, draw_legend = False)
histogram_properties = Histogram_properties()
histogram_properties.name = 'RMS_error_%s_channel_%s' % ( channel, variable )
histogram_properties.title = 'Mean error for $%s$ in %s channel, %s test' % ( variables_latex[variable], channel, test )
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = 'Mean error'
make_plot(RMSerror, 'RMS', histogram_properties, output_folder, output_formats, draw_errorbar = True, draw_legend = False)
histogram_properties = Histogram_properties()
histogram_properties.name = 'RMS_residuals_%s_channel_%s' % ( channel, variable )
histogram_properties.title = 'RMS of residuals for $%s$ in %s channel, %s test' % ( variables_latex[variable], channel, test )
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = 'RMS of residuals'
if test == 'closure':
histogram_properties.set_log_y = True
make_plot(RMSresiduals, 'RMSresiduals', histogram_properties, output_folder, output_formats, draw_errorbar = True, draw_legend = False)
histogram_properties = Histogram_properties()
histogram_properties.name = 'mean_residuals_%s_channel_%s' % ( channel, variable )
histogram_properties.title = 'Mean of residuals for $%s$ in %s channel, %s test' % ( variables_latex[variable], channel, test )
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = 'Mean of residuals'
make_plot(MeanResiduals, 'MeanRes', histogram_properties, output_folder, output_formats, draw_errorbar = True, draw_legend = False)
def draw_regularisation_histograms(h_truth,
h_measured,
h_response,
h_fakes=None,
h_data=None):
global method, variable, output_folder, output_formats, test
k_max = h_measured.nbins()
unfolding = Unfolding(h_truth,
h_measured,
h_response,
h_fakes,
method=method,
k_value=k_max,
error_treatment=4,
verbose=1)
RMSerror, MeanResiduals, RMSresiduals, Chi2 = unfolding.test_regularisation(
h_data, k_max)
histogram_properties = Histogram_properties()
histogram_properties.name = 'chi2_%s_channel_%s' % (channel, variable)
histogram_properties.title = '$\chi^2$ for $%s$ in %s channel, %s test' % (
variables_latex[variable], channel, test)
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = '$\chi^2$'
histogram_properties.set_log_y = True
make_plot(Chi2,
'chi2',
histogram_properties,
output_folder,
output_formats,
draw_errorbar=True,
draw_legend=False)
histogram_properties = Histogram_properties()
histogram_properties.name = 'RMS_error_%s_channel_%s' % (channel, variable)
histogram_properties.title = 'Mean error for $%s$ in %s channel, %s test' % (
variables_latex[variable], channel, test)
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = 'Mean error'
make_plot(RMSerror,
'RMS',
histogram_properties,
output_folder,
output_formats,
draw_errorbar=True,
draw_legend=False)
histogram_properties = Histogram_properties()
histogram_properties.name = 'RMS_residuals_%s_channel_%s' % (channel,
variable)
histogram_properties.title = 'RMS of residuals for $%s$ in %s channel, %s test' % (
variables_latex[variable], channel, test)
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = 'RMS of residuals'
if test == 'closure':
histogram_properties.set_log_y = True
make_plot(RMSresiduals,
'RMSresiduals',
histogram_properties,
output_folder,
output_formats,
draw_errorbar=True,
draw_legend=False)
histogram_properties = Histogram_properties()
histogram_properties.name = 'mean_residuals_%s_channel_%s' % (channel,
variable)
histogram_properties.title = 'Mean of residuals for $%s$ in %s channel, %s test' % (
variables_latex[variable], channel, test)
histogram_properties.x_axis_title = '$i$'
histogram_properties.y_axis_title = 'Mean of residuals'
make_plot(MeanResiduals,
'MeanRes',
histogram_properties,
output_folder,
output_formats,
draw_errorbar=True,
draw_legend=False)
def make_plots(channel = 'electron'):
make_single_efficiency_plot(histograms['probe_passed_pt'], histograms['probe_total_pt'], 'probe_efficiency_pt', channel)
make_single_efficiency_plot(histograms['probe_passed_eta'], histograms['probe_total_eta'], 'probe_efficiency_eta', channel)
if channel == 'electron':
title_channel = 'e+jets'
else:
title_channel = '$\mu$+jets'
histogram_properties = Histogram_properties()
histogram_properties.name = 'btag_multiplicity'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'N btags'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['btag_multiplicity'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'reco_leptons_multiplicity'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'N reco leptons'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['reco_lepton_multiplicity'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'Z_mass_peak_reco'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'Inv. mass 2 reco leptons'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['reco_Z_peak'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'hlt_leptons_multiplicity'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'N HLT leptons'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['hlt_lepton_multiplicity'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'Z_mass_peak_hlt'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'Inv. mass 2 HLT leptons'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['hlt_Z_peak'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'reco_signal_lepton_pt'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'Reco signal lepton pt'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['reco_signal_lepton_pt'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'reco_signal_lepton_eta'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'Reco signal lepton eta'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['reco_signal_lepton_eta'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'hlt_signal_lepton_pt'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'HLT signal lepton pt'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['hlt_signal_lepton_pt'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'hlt_signal_lepton_eta'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'HLT signal lepton eta'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['hlt_signal_lepton_eta'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'reco_probe_lepton_pt'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'Reco probe lepton pt'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['reco_probe_lepton_pt'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'reco_probe_lepton_eta'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'Reco probe lepton eta'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['reco_probe_lepton_eta'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'hlt_probe_lepton_pt'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'HLT probe lepton pt'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['hlt_probe_lepton_pt'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
histogram_properties = Histogram_properties()
histogram_properties.name = 'hlt_probe_lepton_eta'
histogram_properties.title = title_channel + ', CMS Preliminary, $\sqrt{s}$ = 7 TeV'
histogram_properties.x_axis_title = 'HLT probe lepton eta'
histogram_properties.y_axis_title = 'Events'
make_plot(histograms['hlt_probe_lepton_eta'], 'data', histogram_properties, save_folder = output_folder, save_as = ['pdf'])
# We want to store this variable in a histogram
# 80 bins, from 0 to 400 (GeV)
h_gen_met = Hist(80, 0, 400)
# since we are planning to run over many events, let's cache the fill function
fill = h_gen_met.Fill
# ready to read all events
n_processed_events = 0
stop_at = 10**5 # this is enough for this example
for event in chain:
gen_met = event.__getattr__("unfolding.genMET")
fill(gen_met)
n_processed_events += 1
if (n_processed_events % 50000 == 0):
print 'Processed', n_processed_events, 'events.'
if n_processed_events >= stop_at:
break
print 'Processed', n_processed_events, 'events.'
# lets draw this histogram
# define the style
histogram_properties = Histogram_properties()
histogram_properties.name = 'read_ntuples_gen_met' # it will be saved as that
histogram_properties.title = 'My awesome MET plot'
histogram_properties.x_axis_title = 'MET [GeV]'
histogram_properties.y_axis_title = 'Events / 5 GeV'
make_plot(h_gen_met, r'$t\bar{t}$', histogram_properties,
save_folder = 'examples/plots/',
save_as = ['png'])
fill2(gen_met[0])
if len(muonq) > 0:
if (musel) > 0:
fill2(muonq[0])
fill3(muonq[0])
n_processed_events += 1
if (n_processed_events % 50000 == 0):
print 'Processed', n_processed_events, 'events.'
#if n_processed_events >= stop_at:
#break
print 'Processed', n_processed_events, 'events.'
histogram_properties = Histogram_properties()
histogram_properties.name = 'electrons_charge' # it will be saved as that
histogram_properties.title = 'leptons q'
histogram_properties.x_axis_title = 'q'
histogram_properties.y_axis_title = 'Events'
make_plot(h_gen_met,
histogram_properties,
save_folder='sb15165',
save_as=['png'])
histogram_properties.name = 'leptons_charge'
make_plot(leptonCharge,
histogram_properties,
save_folder='sb15165',
save_as=['png'])
histogram_properties.name = 'muons_charge'
make_plot(MuonCharge,
histogram_properties,
save_folder='sb15165',
save_as=['png'])
