Merge pull request #206 from kreczko/latex-checks

[MRG] Latex checks

Author: kreczko

config/latex_labels.py

@@ -18,8 +18,8 @@
 
 measurements_latex = {'unfolded': 'unfolded',
                         'measured': 'measured',
-                        'MADGRAPH': '$t\\bar{t}$ (MADPGRAPH+Pythia)',
-                        'MADGRAPH_ptreweight': '$t\\bar{t}$ (MADPGRAPH+$p_\mathrm{T}^\mathrm{reweight}$)',
+                        'MADGRAPH': '$t\\bar{t}$ (MADGRAPH+Pythia)',
+                        'MADGRAPH_ptreweight': '$t\\bar{t}$ (MADGRAPH+$p_\mathrm{T}^\mathrm{reweight}$)',
                         'MCATNLO': '$t\\bar{t}$ (MC@NLO+Herwig)',
                         'POWHEG_PYTHIA': '$t\\bar{t}$ (POWHEG+Pythia)',
                         'POWHEG_HERWIG': '$t\\bar{t}$ (POWHEG+Herwig)',
@@ -99,8 +99,8 @@
                        'angle_bl' : r'angle$(b,l)$',
                        }
 
-typical_systematics_latex = {"typical_systematics_electron": "Trigger efficiency \& electron selection",
-                      "typical_systematics_muon": "Trigger efficiency \& muon selection",
+typical_systematics_latex = {"typical_systematics_electron": "Electron trigger efficiency \& electron selection",
+                      "typical_systematics_muon": "Muon trigger efficiency \& muon selection",
                       "typical_systematics_btagging": "btagging",
                       "typical_systematics_JES": "Jet Energy Scale",
                       "typical_systematics_JER": "Jet Energy Resolution",

setup.sh

@@ -77,7 +77,7 @@ echo "Installing matplotlib"
 export LDFLAGS="$LDFLAGS -L$VO_CMS_SW_DIR/$SCRAM_ARCH/external/freetype/2.4.7/lib -L$VO_CMS_SW_DIR/$SCRAM_ARCH/external/libpng/1.2.46/lib"
 export CFLAGS="$CFLAGS -I$VO_CMS_SW_DIR/$SCRAM_ARCH/external/freetype/2.4.7/include -I$VO_CMS_SW_DIR/$SCRAM_ARCH/external/freetype/2.4.7/include/freetype2 -I$VO_CMS_SW_DIR/$SCRAM_ARCH/external/libpng/1.2.46/include"
 #pip install -e $base/external/matplotlib
-pip install matplotlib==1.3.1 &> /dev/null
+pip install matplotlib==1.4.3 &> /dev/null
 success $? matplotlib
 echo "Installing rootpy"
 pip install -e $base/external/rootpy &> /dev/null

src/cross_section_measurement/04_make_plots_matplotlib.py

@@ -22,16 +22,10 @@
 import matplotlib.gridspec as gridspec
 from matplotlib.ticker import MultipleLocator
 from config import CMS
-from matplotlib import rc, rcParams
-rc( 'font', **CMS.font )
-rc( 'text', usetex = True )
-rcParams['text.latex.preamble'] = [
-       r'\usepackage{siunitx}',   # i need upright \micro symbols, but you need...
-       r'\sisetup{detect-all}',   # ...this to force siunitx to actually use your fonts
-       r'\usepackage{helvet}',    # set the normal font here
-       r'\usepackage{sansmath}',  # load up the sansmath so that math -> helvet
-       r'\sansmath'               # <- tricky! -- gotta actually tell tex to use!
-]
+from tools.latex import setup_matplotlib
+# latex, font, etc
+setup_matplotlib()
+
 import matplotlib.patches as mpatches
 
 def read_xsection_measurement_results( category, channel ):
@@ -653,7 +647,7 @@ def get_unit_string(fit_variable):
                 if met_type == 'PFMETJetEnDown':
                     met_type = 'patPFMetJetEnDown'
 
-            if not channel == 'combined':
+            if not channel == 'combined' and options.additional_plots:
                 #Don't make additional plots for e.g. generator systematics, mass systematics, k value systematics and pdf systematics because they are now done \
                 #in the unfolding process with BLT unfolding files.
                 if category in ttbar_generator_systematics or category in ttbar_mass_systematics or category in kValue_systematics or category in pdf_uncertainties:

src/cross_section_measurement/make_control_plots.py

@@ -8,17 +8,9 @@
 make_control_region_comparison
 from tools.hist_utilities import prepare_histograms, clean_control_region
 from tools.ROOT_utils import get_histograms_from_files, set_root_defaults
-from matplotlib import rc, rcParams
-from config import CMS
-rc( 'font', **CMS.font )
-rc( 'text', usetex = True )
-rcParams['text.latex.preamble'] = [
-       r'\usepackage{siunitx}',  # i need upright \micro symbols, but you need...
-       r'\sisetup{detect-all}',  # ...this to force siunitx to actually use your fonts
-       r'\usepackage{helvet}',  # set the normal font here
-       r'\usepackage{sansmath}',  # load up the sansmath so that math -> helvet
-       r'\sansmath'  # <- tricky! -- gotta actually tell tex to use!
-]
+from tools.latex import setup_matplotlib
+# latex, font, etc
+setup_matplotlib()
 
 def get_fitted_normalisation( variable, channel ):
     '''
@@ -106,7 +98,6 @@ def make_plot( channel, x_axis_title, y_axis_title,
               signal_region,
               name_prefix, x_limits,
               qcd_data_region_btag = '',
-              qcd_data_region = '',
               use_qcd_data_region = True,
               y_limits = [],
               y_max_scale = 1.2,
@@ -120,19 +111,20 @@ def make_plot( channel, x_axis_title, y_axis_title,
     global output_folder, measurement_config, category, normalise_to_fit
     global preliminary, norm_variable, sum_bins, b_tag_bin, histogram_files
 
+    qcd_data_region = ''
     title = title_template % ( measurement_config.new_luminosity / 1000., measurement_config.centre_of_mass_energy )
     normalisation = None
     if channel == 'electron':
         histogram_files['data'] = measurement_config.data_file_electron
         histogram_files['QCD'] = measurement_config.electron_QCD_MC_category_templates[category]
         normalisation = normalisations_electron[norm_variable]
-        if qcd_data_region_btag and qcd_data_region == '':
+        if use_qcd_data_region:
             qcd_data_region = 'QCDConversions'
     if channel == 'muon':
         histogram_files['data'] = measurement_config.data_file_muon
         histogram_files['QCD'] = measurement_config.muon_QCD_MC_category_templates[category]
         normalisation = normalisations_muon[norm_variable]
-        if qcd_data_region_btag and qcd_data_region == '':
+        if use_qcd_data_region:
             qcd_data_region = 'QCD non iso mu+jets ge3j'
 
     multi = isinstance( signal_region, list )
@@ -164,31 +156,39 @@ def make_plot( channel, x_axis_title, y_axis_title,
         else:
             histograms = get_histograms_from_files( [signal_region], histogram_files )
 
+    signal_region_hists = {}
+    inclusive_control_region_hists = {}
+    for sample in histograms.keys():
+        signal_region_hists[sample] = histograms[sample][signal_region]
+        if use_qcd_data_region:
+            inclusive_control_region_hists[sample] = histograms[sample][qcd_control_region]
+
     if normalise_to_fit:
-        prepare_histograms( histograms, rebin = rebin,
+        # only scale signal region to fit (results are invalid for control region)
+        prepare_histograms( signal_region_hists, rebin = rebin,
                             scale_factor = measurement_config.luminosity_scale,
                             normalisation = normalisation )
     else:
-        prepare_histograms( histograms, rebin = rebin,
+        prepare_histograms( signal_region_hists, rebin = rebin,
+                            scale_factor = measurement_config.luminosity_scale )
+    prepare_histograms( inclusive_control_region_hists, rebin = rebin,
                             scale_factor = measurement_config.luminosity_scale )
     qcd_from_data = None
     if use_qcd_data_region:
-        inclusive_control_region_hists = {}
-        for sample in histograms.keys():
-            inclusive_control_region_hists[sample] = histograms[sample][qcd_control_region]
         qcd_from_data = clean_control_region( inclusive_control_region_hists,
                           subtract = ['TTJet', 'V+Jets', 'SingleTop'] )
     else:
-        qcd_from_data = histograms['QCD'][signal_region]
+        qcd_from_data = signal_region_hists['QCD']
 
     n_qcd_predicted_mc = histograms['QCD'][signal_region].Integral()
     n_qcd_control_region = qcd_from_data.Integral()
     if not n_qcd_control_region == 0:
         qcd_from_data.Scale( 1.0 / n_qcd_control_region * n_qcd_predicted_mc )
 
-    histograms_to_draw = [histograms['data'][signal_region], qcd_from_data,
-                          histograms['V+Jets'][signal_region],
-                          histograms['SingleTop'][signal_region], histograms['TTJet'][signal_region]]
+    histograms_to_draw = [signal_region_hists['data'], qcd_from_data,
+                          signal_region_hists['V+Jets'],
+                          signal_region_hists['SingleTop'],
+                          signal_region_hists['TTJet']]
     histogram_lables = ['data', 'QCD', 'V+Jets', 'Single-Top', samples_latex['TTJet']]
     histogram_colors = ['black', 'yellow', 'green', 'magenta', 'red']
 
@@ -643,7 +643,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   rebin = 2,
                   legend_location = ( 0.95, 0.78 ),
                   cms_logo_location = 'right',
-                  ratio_y_limits = [0.5, 1.5],
+                  ratio_y_limits = [0.25, 1.75],
                   )
         tmp = 'TTbar_plus_X_analysis/MuPlusJets/Ref selection/Binned_MT_Analysis/MT_with_patType1CorrectedPFMet_bin_%s/angle_bl_' + b_tag_bin
         regions = [tmp % bin_i for bin_i in variable_bins_ROOT['MT']]
@@ -670,6 +670,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Normalised events/(10 GeV)',
                   signal_region = 'TTbar_plus_X_analysis/EPlusJets/Ref selection/bjet_invariant_mass_' + b_tag_bin,
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'EPlusJets_BJets_invmass_',
                   x_limits = [0, 800],
                   rebin = 10,
@@ -681,6 +682,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Normalised events/(10 GeV)',
                   signal_region = 'TTbar_plus_X_analysis/MuPlusJets/Ref selection/bjet_invariant_mass_' + b_tag_bin,
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'MuPlusJets_BJets_invmass_',
                   x_limits = [0, 800],
                   rebin = 10,
@@ -697,6 +699,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Events',
                   signal_region = 'TTbar_plus_X_analysis/EPlusJets/Ref selection/N_BJets',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'EPlusJets_N_BJets',
                   x_limits = [1.5, 7.5],
                   rebin = 1,
@@ -708,6 +711,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Events',
                   signal_region = 'TTbar_plus_X_analysis/MuPlusJets/Ref selection/N_BJets',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'MuPlusJets_N_BJets',
                   x_limits = [1.5, 7.5],
                   rebin = 1,
@@ -721,6 +725,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Events',
                   signal_region = 'TTbar_plus_X_analysis/EPlusJets/Ref selection/N_BJets_reweighted',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'EPlusJets_N_BJets_reweighted',
                   x_limits = [1.5, 7.5],
                   rebin = 1,
@@ -732,6 +737,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Events',
                   signal_region = 'TTbar_plus_X_analysis/MuPlusJets/Ref selection/N_BJets',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'MuPlusJets_N_BJets',
                   x_limits = [1.5, 7.5],
                   rebin = 1,
@@ -748,6 +754,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Events',
                   signal_region = 'TTbar_plus_X_analysis/EPlusJets/Ref selection/Jets/N_Jets_' + b_tag_bin,
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'EPlusJets_N_Jets_',
                   x_limits = [3.5, 9.5],
                   rebin = 1,
@@ -759,6 +766,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'Events',
                   signal_region = 'TTbar_plus_X_analysis/MuPlusJets/Ref selection/Jets/N_Jets_' + b_tag_bin,
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'MuPlusJets_N_Jets_',
                   x_limits = [3.5, 9.5],
                   rebin = 1,
@@ -775,6 +783,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'arbitrary units',
                   signal_region = 'TTbar_plus_X_analysis/EPlusJets/Ref selection/Vertices/nVertex',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'EPlusJets_nVertex_',
                   x_limits = [0, 50],
                   rebin = 1,
@@ -787,6 +796,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'arbitrary units',
                   signal_region = 'TTbar_plus_X_analysis/MuPlusJets/Ref selection/Vertices/nVertex',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'MuPlusJets_nVertex_',
                   x_limits = [0, 50],
                   rebin = 1,
@@ -800,6 +810,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'arbitrary units',
                   signal_region = 'TTbar_plus_X_analysis/EPlusJets/Ref selection/Vertices/nVertex_reweighted',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'EPlusJets_nVertex_reweighted_',
                   x_limits = [0, 50],
                   rebin = 1,
@@ -812,6 +823,7 @@ def make_plot( channel, x_axis_title, y_axis_title,
                   y_axis_title = 'arbitrary units',
                   signal_region = 'TTbar_plus_X_analysis/MuPlusJets/Ref selection/Vertices/nVertex_reweighted',
                   qcd_data_region_btag = '',
+                  use_qcd_data_region = False,
                   name_prefix = 'MuPlusJets_nVertex_reweighted_',
                   x_limits = [0, 50],
                   rebin = 1,

src/cross_section_measurement/make_fit_variable_plots.py

@@ -15,17 +15,9 @@
 from config.latex_labels import b_tag_bins_latex, samples_latex, channel_latex
 from config.variable_binning import variable_bins_ROOT, fit_variable_bin_edges, bin_edges
 from config import XSectionConfig
-from config import CMS
-from matplotlib import rc, rcParams
-rc( 'font', **CMS.font )
-rc( 'text', usetex = True )
-rcParams['text.latex.preamble'] = [
-       r'\usepackage{siunitx}',  # i need upright \micro symbols, but you need...
-       r'\sisetup{detect-all}',  # ...this to force siunitx to actually use your fonts
-       r'\usepackage{helvet}',  # set the normal font here
-       r'\usepackage{sansmath}',  # load up the sansmath so that math -> helvet
-       r'\sansmath'  # <- tricky! -- gotta actually tell tex to use!
-]
+from tools.latex import setup_matplotlib
+# latex, font, etc
+setup_matplotlib()
 
 common_fit_variables = ['M3', 'M_bl', 'angle_bl']
 electron_fit_variables = copy( common_fit_variables )

test/tools_plotting.py

@@ -0,0 +1,28 @@
+'''
+Created on 5 May 2015
+
+@author: kreczko
+'''
+from tools.plotting import get_best_max_y
+from tools.hist_utilities import value_errors_tuplelist_to_graph
+from tools.hist_utilities import value_error_tuplelist_to_hist
+
+data_h =  [( 3, 1 ),
+         ( 2, 1 ),
+         ( 1, 1 ),
+        ]
+data_g =  [( 3, 1, 1 ),
+         ( 2, 1, 1 ),
+         ( 1, 1, 1 ),
+        ]
+bin_edges = [0, 1, 2, 3]
+
+def test_get_max_y_hist():
+    h = value_error_tuplelist_to_hist(data_h, bin_edges)
+    max_y = get_best_max_y([h])
+    assert max_y == 3 + 1
+    
+def test_get_max_y_graph():
+    g = value_errors_tuplelist_to_graph(data_g, bin_edges)
+    max_y = get_best_max_y([g])
+    assert max_y == 3 + 1

tools/hist_utilities.py

@@ -95,25 +95,38 @@ def scale_histogram_errors( histogram, total_error ):
 def prepare_histograms( histograms, rebin = 1, scale_factor = 1.,
                         normalisation = {}, exclude_from_scaling = ['data'] ):
     for sample, histogram_dict in histograms.iteritems():
+        # check if this is a simple dict
+        if histogram_dict.__class__.__name__ == 'Hist':
+            h = histogram_dict
+            scale = 1.
+            norm = None
+            if not sample in exclude_from_scaling:
+                scale = scale_factor
+            if sample in normalisation.keys():
+                norm = normalisation[sample]
+            scale_and_rebin_histogram( histogram = h, scale_factor = scale,
+                                      normalisation = norm, rebin = rebin )
+            continue
+        # otherwise go a level deeper
         for _, histogram in histogram_dict.iteritems():
-            histogram.Rebin( rebin )
+            scale = 1.
+            norm = None
             if not sample in exclude_from_scaling:
-                histogram.Scale( scale_factor )
-            if normalisation != {} and histogram.Integral() != 0:
-                # TODO: this can be simplyfied and generalised 
-                # by using normalisation.keys() + for loop
-                if sample == 'TTJet':
-                    histogram.Scale( normalisation['TTJet'][0] / histogram.Integral() )
-                    scale_histogram_errors( histogram, normalisation['TTJet'][1] )
-                if sample == 'SingleTop':
-                    histogram.Scale( normalisation['SingleTop'][0] / histogram.Integral() )
-                    scale_histogram_errors( histogram, normalisation['SingleTop'][1] )
-                if sample == 'V+Jets':
-                    histogram.Scale( normalisation['V+Jets'][0] / histogram.Integral() )
-                    scale_histogram_errors( histogram, normalisation['V+Jets'][1] )
-                if sample == 'QCD':
-                    histogram.Scale( normalisation['QCD'][0] / histogram.Integral() )
-                    scale_histogram_errors( histogram, normalisation['QCD'][1] )
+                scale = scale_factor
+            if sample in normalisation.keys():
+                norm = normalisation[sample]
+            scale_and_rebin_histogram( histogram = histogram,
+                                       scale_factor = scale,
+                                       normalisation = norm, rebin = rebin )
+
+def scale_and_rebin_histogram(histogram, scale_factor,
+                              normalisation = None,
+                              rebin = 1):
+    histogram.Rebin( rebin )
+    histogram.Scale( scale_factor )
+    if not normalisation is None and histogram.Integral() != 0:
+        histogram.Scale( normalisation[0] / histogram.Integral() )
+        scale_histogram_errors( histogram, normalisation[1] )
 
 def rebin_asymmetric( histogram, bins ):
     bin_array = array( 'd', bins )