NLO systematic

config/cross_section_config.py

@@ -209,7 +209,8 @@ def __fill_defaults__( self ):
                                         # 'matchingup', 'matchingdown', 
                                         'scaleup', 'scaledown',
                                         'massup', 'massdown',
-                                        'hadronisation'
+                                        'hadronisation',
+                                        'NLOgenerator'
                                       ]
         self.k_values = {
                          'electron' : self.k_values_electron,
@@ -251,7 +252,7 @@ def __fill_defaults__( self ):
         self.central_general_template = path_to_files + 'central/%s' + middle + '.root'
         self.generator_systematic_vjets_templates = {}
         for systematic in self.generator_systematics:
-            if 'mass' in systematic or 'hadronisation' in systematic:
+            if 'mass' in systematic or 'hadronisation' in systematic or 'NLOgenerator' in systematic:
                 continue
             tmp = path_to_files + 'central/VJets-{0}_{1}pb_PFElectron_PFMuon_PF2PATJets_PFMET.root'
             tmp = tmp.format(systematic, self.luminosity)
@@ -401,8 +402,9 @@ def __fill_defaults__( self ):
             'Theory': [('TTJets_scaledown', 'TTJets_scaleup'),
                        ('TTJets_massdown', 'TTJets_massup')],
             'Hadronisation': [('TTJets_hadronisation', 'TTJets_hadronisation')],
+            'NLO generator': [('TTJets_NLOgenerator', 'TTJets_NLOgenerator')],
             'PDF': [('PDF_total_lower', 'PDF_total_upper')],
-            'others': [('QCD_shape', 'QCD_shape')]
+            'QCD shape': [('QCD_shape', 'QCD_shape')]
                                     }
         self.typical_systematics = []
         for _, values in self.typical_systematics_summary.items():

config/latex_labels.py

@@ -87,6 +87,7 @@
     'central': 'central',
     #'ptreweight_max': '$p_\mathrm{T}(t,\\bar{t})$ reweighting',
     'TTJets_hadronisation': 'Hadronisation uncertainty',
+    'TTJets_NLOgenerator': 'NLO generator',
     'PDF_total_lower': 'PDF uncertainty $-1\sigma$',
     'PDF_total_upper': 'PDF uncertainty $+1\sigma$',
     'QCD_shape': 'QCD shape uncertainty',

experimental/condor/01b/01_fit.description

@@ -15,4 +15,4 @@ request_memory=500
 # use the ENV that is provided
 getenv = true
 
-queue 7
+queue 14

src/cross_section_measurement/02_unfold_and_measure.py

@@ -64,6 +64,7 @@ def get_unfolded_normalisation( TTJet_fit_results, category, channel, tau_value,
                              ttbar_theory_systematic_prefix + 'massdown'        :  file_for_massdown,
                              ttbar_theory_systematic_prefix + 'massup'          :  file_for_massup,
                              ttbar_theory_systematic_prefix + 'hadronisation'   :  file_for_powheg_herwig,
+                             ttbar_theory_systematic_prefix + 'NLOgenerator'   :  file_for_amcatnlo,
                              }
 
     h_truth, h_measured, h_response, h_fakes = None, None, None, None
@@ -438,25 +439,17 @@ def calculate_normalised_xsections( normalisation, category, channel, normalise_
     categories.extend( ttbar_generator_systematics )
     ### categories.extend( vjets_generator_systematics )
 
-    ### ttbar theory systematics, including pt reweighting and hadronisation systematic
-    ttbar_theory_systematics = [] #[ ttbar_theory_systematic_prefix + 'ptreweight' ]
-    ttbar_theory_systematics.extend( [ttbar_theory_systematic_prefix + 'powheg_pythia', ttbar_theory_systematic_prefix + 'powheg_herwig'] )
-    categories.extend( ttbar_theory_systematics )
-
-    ### Add mass systematics
-    ### ttbar_mass_systematics = measurement_config.topMass_systematics
-    ### categories.extend( measurement_config.topMass_systematics )
-
-    ### Add k Value systematic
-    ### kValue_systematics = measurement_config.kValueSystematic
-    ### categories.extend( measurement_config.kValueSystematic )
+    # ### ttbar theory systematics, including pt reweighting and hadronisation systematic
+    # ttbar_theory_systematics = [] #[ ttbar_theory_systematic_prefix + 'ptreweight' ]
+    # ttbar_theory_systematics.extend( [ttbar_theory_systematic_prefix + 'powheg_pythia', ttbar_theory_systematic_prefix + 'powheg_herwig'] )
+    # categories.extend( ttbar_theory_systematics )
 
     pdf_uncertainties = ['PDFWeights_%d' % index for index in range( 0, 100 )]
     rate_changing_systematics = [systematic for systematic in measurement_config.rate_changing_systematics_names]
     #  all MET uncertainties except JES as this is already included
     met_uncertainties = [suffix for suffix in measurement_config.met_systematics_suffixes if not 'JetEn' in suffix and not 'JetRes' in suffix]
     all_measurements = deepcopy( categories )
-    all_measurements.extend( pdf_uncertainties )
+    # all_measurements.extend( pdf_uncertainties )
     all_measurements.extend( ['QCD_shape'] )
     all_measurements.extend( rate_changing_systematics )
 

src/cross_section_measurement/05_make_tables.py

@@ -476,7 +476,11 @@ def print_typical_systematics_table(central_values, errors, channel, toFile = Tr
         assert(errors.has_key(s))
 
     group_errors = {}
+    for group in measurement_config.typical_systematics_summary:
+        group_errors[group] = []
+
     for bin_i, _ in enumerate(bins):
+
         central_value = central_values[measurement][bin_i][0]
         uncertainties = {}
         # calculate all relative errors
@@ -486,12 +490,13 @@ def print_typical_systematics_table(central_values, errors, channel, toFile = Tr
             uncertainties[systematic] = relative_error
         # add errors in a group in quadrature
         for group, u_list in measurement_config.typical_systematics_summary.items():
+
             group_error_squared = 0
             for subgroup in u_list:
                 # use the biggest of up and down
                 subgroup_error = max(uncertainties[subgroup[0]], uncertainties[subgroup[1]])
                 group_error_squared += pow(subgroup_error, 2)
-            group_errors[group] = math.sqrt(group_error_squared)
+            group_errors[group].append(math.sqrt(group_error_squared))
 
     summarised_typical_systematics = {}
     # calculate the median