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)
# 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'])
# 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'])
