# cuts['lnujj_ttbar_mu_mV_b'] = findCut(categories, cat="lnujj", lep="mu", mJ="V", reg="b") # cuts['lnujj_ttbar_e_mV_b'] = findCut(categories, cat="lnujj", lep="e", mJ="V", reg="b") # cuts['lnujj_mu_SP_veto_mV'] = findCut(categories, cat="lnujj", lep="mu", tau21="SP", mJ="VetoV") # cuts['lnujj_e_SP_veto_mV'] = findCut(categories, cat="lnujj", lep="e", tau21="SP", mJ="VetoV") # cuts['lnujj_e_HP_veto_mV_nob'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", mJ="VetoV", reg="nob") # cuts['lnujj_mu_HP_veto_mV_nob'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", mJ="VetoV", reg="nob") # cuts['lnujj_e_HP_veto_mV'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", mJ="VetoV") # cuts['lnujj_mu_HP_veto_mV'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", mJ="VetoV") # cuts['lnujj_ttbar_e_HP_b'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", reg="b") # cuts['lnujj_ttbar_mu_HP_b'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", reg="b") # -> Command line analysis_dir = '/data/clange/ntuples/FixMass/' tree_prod_name = '' samples_mc, samples_data, samples, all_samples, sampleDict = createSampleLists( analysis_dir, channel='WV', weight=weight_MC, reweightVJets=False) # Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis']) variables = generic_vars + lnujj_vars + lnujj_vbf_vars # variables = [lnujj_vars[0]] # variables = getVars(['l1_reliso05', 'l2_reliso05']) # variables = [ # VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}') # ] for cut_name in cuts: cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut='',
cuts['lnujj_mu_HP_veto_mV_nob'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", mJ="VetoV", reg="nob") # cuts['lnujj_e_HP_veto_mV'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", mJ="VetoV") # cuts['lnujj_mu_HP_veto_mV'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", mJ="VetoV") # cuts['lnujj_ttbar_e_HP_b'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", reg="b") # cuts['lnujj_ttbar_mu_HP_b'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", reg="b") # -> Command line analysis_dir = '/data/clange/ntuples/FixNeutrino/' tree_prod_name = '' samples_mc, samples_data, samples, all_samples, sampleDict = createSampleLists( analysis_dir, channel='WV', weight=weight_MC, vJetsKFac=0.92) # Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis']) variables = generic_vars + lnujj_vars + lnujj_vbf_vars # variables = [lnujj_vars[0]] # variables = getVars(['l1_reliso05', 'l2_reliso05']) # variables = [ # VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}') # ] for cut_name in cuts: cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut='',
vbfCuts = {} for cutName, cut in cuts.iteritems(): # vbfCuts[cutName+"_vbf_DEta"] = cut + "*(lnujj_vbfDEta>4.0)" # vbfCuts[cutName+"_vbf_Mass"] = cut + "*(lnujj_vbfMass>400)" vbfCuts[cutName + "_vbf_DEta_Mass"] = cut + "*(lnujj_vbfDEta>4.0&&lnujj_vbfMass>400)" # vbfCuts[cutName+"_novbf"] = cut + "*(lnujj_vbfDEta<=4.0||lnujj_vbfMass<=400)" cuts.update(vbfCuts) # -> Command line analysis_dir = '/data/clange/ntuples/FixNeutrino/' tree_prod_name = '' samples_mc, samples_data, samples, all_samples, sampleDict = createSampleLists( analysis_dir, channel='WV', weight=weight_MC, signalSample='VBF_RadionToWW_narrow_2500') # Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis']) variables = generic_vars + lnujj_vars + lnujj_vbf_vars # variables = [lnujj_vars[0]] # variables = getVars(['l1_reliso05', 'l2_reliso05']) # variables = [ # VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}') # ] for cut_name in cuts: cfg_example = HistogramCfg(name='example', var=None,
vbfCuts = {} for cutName, cut in cuts.iteritems(): # vbfCuts[cutName+"_vbf_DEta"] = cut + "*(lnujj_vbfDEta>4.0)" # vbfCuts[cutName+"_vbf_Mass"] = cut + "*(lnujj_vbfMass>400)" # vbfCuts[cutName+"_vbf_DEta_Mass"] = cut + "*(lnujj_vbfDEta>4.0&&lnujj_vbfMass>400)" vbfCuts[cutName + "_novbf"] = cut + "&&((lnujj_vbfDEta<=4.0)||(lnujj_vbfMass<=400))" cuts = vbfCuts # -> Command line analysis_dir = '/data/clange/ntuples/FixNeutrino/' tree_prod_name = '' samples_mc, samples_data, samples, all_samples, sampleDict = createSampleLists( analysis_dir, channel='WV', weight=weight_MC, signalSample='BulkGravToWW_narrow_2000') # Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis']) variables = generic_vars + lnujj_vars + lnujj_vbf_vars # variables = [lnujj_vars[0]] # variables = getVars(['l1_reliso05', 'l2_reliso05']) # variables = [ # VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}') # ] for cut_name in cuts: cfg_example = HistogramCfg(name='example', var=None,
# if adding additional cuts, join with * and not &&, e.g. # inc_cut = '*'.join([jj_inc]) cuts['jj_l1_tau21_all_l2_tau21_all'] = categories[ "jj_l1_tau21_all_l2_tau21_all"] cuts['jj_l1_tau21_HP_mJ_W_l2_tau21_HP_mJ_W'] = categories[ "jj_l1_tau21_HP_mJ_W_l2_tau21_HP_mJ_W"] cuts['jj_l1_tau21_HP_l2_tau21_all'] = categories["jj_l1_tau21_HP_l2_tau21_all"] cuts['jj_l1_tau21_HP_l2_tau21_HP_mJ_W'] = categories[ "jj_l1_tau21_HP_l2_tau21_HP_mJ_W"] # -> Command line analysis_dir = '/data/clange/ntuples/VV_20161203/' tree_prod_name = '' samples_mc, samples_data, samples, all_samples, sampleDict = createSampleLists( analysis_dir, channel='VV', weight=weight_MC) # Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis']) variables = jj_l1_vars + jj_l2_vars + generic_vars # variables = [jj_l1_vars[0]] # variables = getVars(['l1_reliso05', 'l2_reliso05']) # variables = [ # VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}') # ] for cut_name in cuts: cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut='',
# cuts['lnujj_mu_SP_veto_mV'] = findCut(categories, cat="lnujj", lep="mu", tau21="SP", mJ="VetoV") # cuts['lnujj_e_SP_veto_mV'] = findCut(categories, cat="lnujj", lep="e", tau21="SP", mJ="VetoV") # cuts['lnujj_e_HP_veto_mV_nob'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", mJ="VetoV", reg="nob") # cuts['lnujj_mu_HP_veto_mV_nob'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", mJ="VetoV", reg="nob") # cuts['lnujj_e_HP_veto_mV'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", mJ="VetoV") # cuts['lnujj_mu_HP_veto_mV'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", mJ="VetoV") # cuts['lnujj_ttbar_e_HP_b'] = findCut(categories, cat="lnujj", lep="e", tau21="HP", reg="b") # cuts['lnujj_ttbar_mu_HP_b'] = findCut(categories, cat="lnujj", lep="mu", tau21="HP", reg="b") # -> Command line analysis_dir = '/data/clange/ntuples/FixMass/' tree_prod_name = '' samples_mc, samples_data, samples, all_samples, sampleDict = createSampleLists(analysis_dir, channel='WV', weight=weight_MC, useTopMcatnlo=True) # Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis']) variables = generic_vars + lnujj_vars + lnujj_vbf_vars # variables = [lnujj_vars[0]] # variables = getVars(['l1_reliso05', 'l2_reliso05']) # variables = [ # VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}') # ] for cut_name in cuts: cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut='', lumi=int_lumi, weight=total_weight) cfg_example.cut = cuts[cut_name] cfg_example.vars = variables