# 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
