Python Histogram_properties.mc_errors_label方法代码示例

# 需要导入模块: from tools.plotting import Histogram_properties [as 别名]
# 或者: from tools.plotting.Histogram_properties import mc_errors_label [as 别名]

#.........这里部分代码省略.........

    selection = 'SolutionCategory == 1'
    histogramsCorrect = get_histograms_from_trees( trees = [signal_region_tree], branch = branchName, weightBranch = '1', selection = selection, files = histogram_files, nBins = nBins, xMin = x_limits[0], xMax = x_limits[-1] )

    selection = 'SolutionCategory == 2'
    histogramsNotSL = get_histograms_from_trees( trees = [signal_region_tree], branch = branchName, weightBranch = '1', selection = selection, files = histogram_files, nBins = nBins, xMin = x_limits[0], xMax = x_limits[-1] )

    selection = 'SolutionCategory == 3'
    histogramsNotReco = get_histograms_from_trees( trees = [signal_region_tree], branch = branchName, weightBranch = '1', selection = selection, files = histogram_files, nBins = nBins, xMin = x_limits[0], xMax = x_limits[-1] )

    selection = 'SolutionCategory > 3'
    histogramsWrong = get_histograms_from_trees( trees = [signal_region_tree], branch = branchName, weightBranch = '1', selection = selection, files = histogram_files, nBins = nBins, xMin = x_limits[0], xMax = x_limits[-1] )

    # Split histograms up into signal/control (?)
    signal_region_hists = {}
    inclusive_control_region_hists = {}
    for sample in histograms.keys():
        signal_region_hists[sample] = histograms[sample][signal_region_tree]
        if use_qcd_data_region:
            inclusive_control_region_hists[sample] = histograms[sample][control_region_tree]

    prepare_histograms( histograms, rebin = 1, scale_factor = measurement_config.luminosity_scale )
    prepare_histograms( histogramsNoSolution, rebin = 1, scale_factor = measurement_config.luminosity_scale )
    prepare_histograms( histogramsCorrect, rebin = 1, scale_factor = measurement_config.luminosity_scale )
    prepare_histograms( histogramsNotSL, rebin = 1, scale_factor = measurement_config.luminosity_scale )
    prepare_histograms( histogramsNotReco, rebin = 1, scale_factor = measurement_config.luminosity_scale )
    prepare_histograms( histogramsWrong, rebin = 1, scale_factor = measurement_config.luminosity_scale )

    qcd_from_data = signal_region_hists['QCD']

    # Which histograms to draw, and properties
    histograms_to_draw = [signal_region_hists['data'], qcd_from_data,
                          signal_region_hists['V+Jets'],
                          signal_region_hists['SingleTop'],
                          histogramsNoSolution['TTJet'][signal_region_tree],
                          histogramsNotSL['TTJet'][signal_region_tree],
                          histogramsNotReco['TTJet'][signal_region_tree],
                          histogramsWrong['TTJet'][signal_region_tree],
                          histogramsCorrect['TTJet'][signal_region_tree]
                          ]
    histogram_lables = ['data', 'QCD', 'V+Jets', 'Single-Top', 
                        samples_latex['TTJet'] + ' - no solution',
                        samples_latex['TTJet'] + ' - not SL',
                        samples_latex['TTJet'] + ' - not reconstructible',
                        samples_latex['TTJet'] + ' - wrong reco',
                        samples_latex['TTJet'] + ' - correct',
                        ]
    histogram_colors = ['black', 'yellow', 'green', 'magenta',
                        'black',
                        'burlywood',
                        'chartreuse',
                        'blue',
                        'red'
                        ]

    histogram_properties = Histogram_properties()
    histogram_properties.name = name_prefix + b_tag_bin
    if category != 'central':
        histogram_properties.name += '_' + category
    histogram_properties.title = title
    histogram_properties.x_axis_title = x_axis_title
    histogram_properties.y_axis_title = y_axis_title
    histogram_properties.x_limits = x_limits
    histogram_properties.y_limits = y_limits
    histogram_properties.y_max_scale = y_max_scale
    histogram_properties.xerr = None
    # workaround for rootpy issue #638
    histogram_properties.emptybins = True
    if b_tag_bin:
        histogram_properties.additional_text = channel_latex[channel] + ', ' + b_tag_bins_latex[b_tag_bin]
    else:
        histogram_properties.additional_text = channel_latex[channel]
    histogram_properties.legend_location = legend_location
    histogram_properties.cms_logo_location = cms_logo_location
    histogram_properties.preliminary = preliminary
    histogram_properties.set_log_y = log_y
    histogram_properties.legend_color = legend_color
    if ratio_y_limits:
        histogram_properties.ratio_y_limits = ratio_y_limits

    if normalise_to_fit:
        histogram_properties.mc_error = get_normalisation_error( normalisation )
        histogram_properties.mc_errors_label = 'fit uncertainty'
    else:
        histogram_properties.mc_error = mc_uncertainty
        histogram_properties.mc_errors_label = 'MC unc.'

    # Actually draw histograms
    make_data_mc_comparison_plot( histograms_to_draw, histogram_lables, histogram_colors,
                                 histogram_properties, save_folder = output_folder,
                                 show_ratio = False, normalise = normalise,
                                 )
    histogram_properties.name += '_with_ratio'
    loc = histogram_properties.legend_location
    # adjust legend location as it is relative to canvas!
    histogram_properties.legend_location = ( loc[0], loc[1] + 0.05 )
    make_data_mc_comparison_plot( histograms_to_draw, histogram_lables, histogram_colors,
                                 histogram_properties, save_folder = output_folder,
                                 show_ratio = True, normalise = normalise,
                                 )

# 需要导入模块: from tools.plotting import Histogram_properties [as 别名]
# 或者: from tools.plotting.Histogram_properties import mc_errors_label [as 别名]
def plot_fit_variable( histograms, fit_variable, variable, bin_range,
                      fit_variable_distribution, qcd_fit_variable_distribution,
                      title, save_path ):
    global fit_variable_properties, b_tag_bin, save_as, b_tag_bin_ctl
    mc_uncertainty = 0.10
    prepare_histograms( histograms, rebin = fit_variable_properties[fit_variable]['rebin'], scale_factor = measurement_config.luminosity_scale )
    
    histogram_properties = Histogram_properties()
    histogram_properties.x_axis_title = fit_variable_properties[fit_variable]['x-title']
    histogram_properties.y_axis_title = fit_variable_properties[fit_variable]['y-title']
    histogram_properties.x_limits = [fit_variable_properties[fit_variable]['min'], fit_variable_properties[fit_variable]['max']]

    histogram_lables = ['data', 'QCD', 'V+Jets', 'Single-Top', samples_latex['TTJet']]
    histogram_colors = ['black', 'yellow', 'green', 'magenta', 'red']
#     qcd_from_data = histograms['data'][qcd_fit_variable_distribution].Clone()
    # clean against other processes
    histograms_for_cleaning = {'data':histograms['data'][qcd_fit_variable_distribution],
                               'V+Jets':histograms['V+Jets'][qcd_fit_variable_distribution],
                               'SingleTop':histograms['SingleTop'][qcd_fit_variable_distribution],
                               'TTJet':histograms['TTJet'][qcd_fit_variable_distribution]}
    qcd_from_data = clean_control_region( histograms_for_cleaning, subtract = ['TTJet', 'V+Jets', 'SingleTop'] )
    
    
    histograms_to_draw = [histograms['data'][qcd_fit_variable_distribution],
                          histograms['QCD'][qcd_fit_variable_distribution],
                          histograms['V+Jets'][qcd_fit_variable_distribution],
                          histograms['SingleTop'][qcd_fit_variable_distribution],
                          histograms['TTJet'][qcd_fit_variable_distribution]]
    
    histogram_properties.title = title + ', ' + b_tag_bins_latex[b_tag_bin_ctl]
    histogram_properties.name = variable + '_' + bin_range + '_' + fit_variable + '_%s_QCDConversions' % b_tag_bin_ctl
    make_data_mc_comparison_plot( histograms_to_draw, histogram_lables, histogram_colors,
                                 histogram_properties,
                                 save_folder = save_path + '/qcd/',
                                 show_ratio = False,
                                 save_as = save_as,
                                 )
    
    histograms_to_draw = [qcd_from_data,
                          histograms['QCD'][qcd_fit_variable_distribution],
                          ]
    
    histogram_properties.name = variable + '_' + bin_range + '_' + fit_variable + '_%s_QCDConversions_subtracted' % b_tag_bin_ctl
    make_data_mc_comparison_plot( histograms_to_draw,
                                  histogram_lables = ['data', 'QCD'],
                                  histogram_colors = ['black', 'yellow'],
                                  histogram_properties = histogram_properties,
                                  save_folder = save_path + '/qcd/',
                                  show_ratio = False,
                                  save_as = save_as,
                                  )
    
    # scale QCD to predicted
    n_qcd_predicted_mc = histograms['QCD'][fit_variable_distribution].Integral()
    n_qcd_fit_variable_distribution = qcd_from_data.Integral()
    if not n_qcd_fit_variable_distribution == 0:
        qcd_from_data.Scale( 1.0 / n_qcd_fit_variable_distribution * n_qcd_predicted_mc )
    
    histograms_to_draw = [histograms['data'][fit_variable_distribution], qcd_from_data,
                          histograms['V+Jets'][fit_variable_distribution],
                          histograms['SingleTop'][fit_variable_distribution], histograms['TTJet'][fit_variable_distribution]]
    
    histogram_properties.title = title + ', ' + b_tag_bins_latex[b_tag_bin]
    histogram_properties.name = variable + '_' + bin_range + '_' + fit_variable + '_' + b_tag_bin
    make_data_mc_comparison_plot( histograms_to_draw,
                                  histogram_lables,
                                  histogram_colors,
                                  histogram_properties,
                                  save_folder = save_path,
                                  show_ratio = False,
                                  save_as = save_as,
                                 )
    histogram_properties.mc_error = mc_uncertainty
    histogram_properties.mc_errors_label = '$\mathrm{t}\\bar{\mathrm{t}}$ uncertainty'
    histogram_properties.name = variable + '_' + bin_range + '_' + fit_variable + '_' + b_tag_bin + '_templates'
    # change histogram order for better visibility
    histograms_to_draw = [histograms['TTJet'][fit_variable_distribution] + histograms['SingleTop'][fit_variable_distribution], 
                          histograms['TTJet'][fit_variable_distribution],
                          histograms['SingleTop'][fit_variable_distribution],
                          histograms['V+Jets'][fit_variable_distribution],
                          qcd_from_data]
    histogram_lables = ['QCD', 'V+Jets', 'Single-Top', samples_latex['TTJet'], samples_latex['TTJet'] + ' + ' + 'Single-Top']
    histogram_lables.reverse()
    # change QCD color to orange for better visibility
    histogram_colors = ['orange', 'green', 'magenta', 'red', 'black']
    histogram_colors.reverse()
    make_shape_comparison_plot( shapes = histograms_to_draw,
                                names = histogram_lables,
                                colours = histogram_colors,
                                histogram_properties = histogram_properties,
                                fill_area = False,
                                alpha = 1,
                                save_folder = save_path,
                                save_as = save_as,
                                )

# 需要导入模块: from tools.plotting import Histogram_properties [as 别名]
# 或者: from tools.plotting.Histogram_properties import mc_errors_label [as 别名]
            'TTJet': path_to_files + 'TTJet_%spb_PFElectron_%sPF2PATJets_PFMET.root' % (str(lumi), pfmuon),
            'data' : path_to_files + '%s_%spb_PFElectron_%sPF2PATJets_PFMET.root' % (data, str(lumi), pfmuon),
            'WJets': path_to_files + 'WJetsToLNu_%spb_PFElectron_%sPF2PATJets_PFMET.root' % (str(lumi), pfmuon),
            'ZJets': path_to_files + 'DYJetsToLL_%spb_PFElectron_%sPF2PATJets_PFMET.root' % (str(lumi), pfmuon),
            'QCD': path_to_files + 'QCD_%spb_PFElectron_%sPF2PATJets_PFMET.root' % (str(lumi), pfmuon),
            'SingleTop': path_to_files + 'SingleTop_%spb_PFElectron_%sPF2PATJets_PFMET.root' % (str(lumi), pfmuon),
                       }
    
    b_tag_bin = '0btag'
    control_region = 'topReconstruction/backgroundShape/mttbar_3jets_conversions_withMETAndAsymJets_' + b_tag_bin
    histograms = get_histograms_from_files([control_region], histogram_files)
    prepare_histograms(histograms, rebin=50)
    
    histograms_to_draw = [histograms['data'][control_region], histograms['QCD'][control_region], 
                          histograms['ZJets'][control_region], histograms['WJets'][control_region], 
                          histograms['SingleTop'][control_region], histograms['TTJet'][control_region]]
    histogram_lables = ['data', 'QCD', samples_latex['ZJets'], samples_latex['WJets'], 'Single-Top', samples_latex['TTJet']]
    histogram_colors = ['black', 'yellow', 'blue', 'green', 'magenta', 'red']
    
    histogram_properties = Histogram_properties()
    histogram_properties.name = 'Mttbar'
    histogram_properties.title = 'CMS Preliminary, $\mathcal{L}$ = 5.1 fb$^{-1}$ at $\sqrt{s}$ = 7 TeV \n e+jets, $\geq$4 jets, ' + b_tag_bins_latex[b_tag_bin]
    histogram_properties.x_axis_title = '$m_{\mathrm{t}\\bar{\mathrm{t}}}$ [GeV]'
    histogram_properties.y_axis_title = 'Events/(50 GeV)'
    histogram_properties.x_limits=[300,1800]
    histogram_properties.mc_error = 0.15
    histogram_properties.mc_errors_label = '$\mathrm{t}\\bar{\mathrm{t}}$ uncertainty'
    
    make_data_mc_comparison_plot(histograms_to_draw, histogram_lables, histogram_colors, 
                                 histogram_properties)