# mc = [ TTZtoLLNuNu ]
#elif args.background == "All":
# mc = [ TTZtoLLNuNu , TTX, WZ, TTW, TZQ, rare ]#, nonprompt ]
#else:
# mc = []
mc = []
for sample in mc:
sample.style = styles.fillStyle(sample.color)
# reweighting
if args.reweightPtGToSM:
sel_string = "&&".join([
getFilterCut(isData=False),
getLeptonSelection('all'),
cutInterpreter.cutString(args.selection)
])
TTZ_ptG = TTZtoLLNuNu.get1DHistoFromDraw("gamma_pt[0]", [20, 0, 1000],
selectionString=sel_string,
weightString="weight")
TTZ_ptG.Scale(1. / TTZ_ptG.Integral())
def get_reweight(var, histo):
def reweight(event, sample):
i_bin = histo.FindBin(getattr(event, var))
return histo.GetBinContent(i_bin)
return reweight
for signal in signals:
logger.info("Computing PtG reweighting for signal %s", signal.name)
postfix = "ptZ0To100"
s = Sample.fromDirectory(
'TTZ_LO',
directory=[
'/afs/hephy.at/data/rschoefbeck02/cmgTuples/TopEFT_PP_v12/inclusive/TTZ_LO'
])
s_BSM = Sample.fromDirectory(
'ttZ0j_ll_DC1A_0p600000_DC1V_m0p240000_DC2A_m0p176700_DC2V_m0p176700',
directory=[
'/afs/hephy.at/data/rschoefbeck02/cmgTuples/TopEFT_PP_v12/inclusive/ttZ0j_ll_DC1A_0p600000_DC1V_m0p240000_DC2A_m0p176700_DC2V_m0p176700'
])
h_TTZ_LO = s.get1DHistoFromDraw(
'genZ_cosThetaStar',
[20, -1, 1],
selectionString=cutInterpreter.cutString('njet3p-btag1p') +
'&&genZ_pt<100&&nGenLep>=3',
#selectionString = cutInterpreter.cutString('lepSelTTZ-njet3p-btag1p-onZ')+'&&genZ_pt>0',
weightString='weight*100')
h_BSM = s_BSM.get1DHistoFromDraw(
'genZ_cosThetaStar',
[20, -1, 1],
selectionString=cutInterpreter.cutString('njet3p-btag1p') +
'&&genZ_pt<100&&nGenLep>=3',
#selectionString = cutInterpreter.cutString('lepSelTTZ-njet3p-btag1p-onZ')+'&&genZ_pt>0',
weightString='weight*100')
h_BSM.Scale(h_TTZ_LO.Integral() / h_BSM.Integral())
ZPolarisationFit(
h.Scale( 1./s )
return templates
if __name__ == "__main__":
# Sample
s = Sample.fromDirectory( 'TTZ_LO', directory = ['/afs/hephy.at/data/rschoefbeck02/cmgTuples/TopEFT_PP_v12/inclusive/TTZ_LO'] )
t_maker = PolarisationTemplateMaker(s, cacheDir = os.path.join( results_directory, 'PolarisationTemplateCache' ) )
# polarisation bin -> will be argument
genZ_pt_bin = (0,25)
genZ_eta_bin = (0, -1)
# kinematic preselection
cut_string = cutInterpreter.cutString('njet3p-btag1p')
kin_cut_string = "genZ_pt>=%i" % genZ_pt_bin[0]
if genZ_pt_bin[1]>0: kin_cut_string+="&&genZ_pt<%i"%( genZ_pt_bin[1] )
kin_cut_string+= "&&genZ_eta>=%i" % genZ_eta_bin[0]
if genZ_eta_bin[1]>0: kin_cut_string+="&&genZ_eta<%i"%( genZ_eta_bin[1] )
selectionString = kin_cut_string+"&&"+cut_string
templates = t_maker.cachedTemplate( selectionString, 'weight')
templates['p'].legendText = '+'
templates['m'].legendText = '-'
templates['L'].legendText = 'L'
templates['p'].style = styles.lineStyle( ROOT.kRed )
templates['m'].style = styles.lineStyle( ROOT.kGreen )
templates['L'].style = styles.lineStyle( ROOT.kBlue )
sample.read_variables = ['reweightBTagCSVv2_SF/F', 'reweightBTagDeepCSV_SF/F', 'reweightPU36fb/F', 'reweightLeptonSFSyst_tight_3l/F', 'reweightLeptonTrackingSF_tight_3l/F', 'reweightTrigger_tight_3l/F', "Z_pt/F"]
sample.weight = lambda event, sample: event.reweightBTagDeepCSV_SF*event.reweightPU36fb*event.reweightLeptonSFSyst_tight_3l*event.reweightLeptonTrackingSF_tight_3l*event.reweightTrigger_tight_3l
tr = triggerSelector(2016)
sample.setSelectionString([getFilterCut(isData=False), getLeptonSelection(mode), tr.getSelection("MC")])
if not args.noData:
stack = Stack(mc, data_sample)
else:
stack = Stack(mc)
if args.small:
for sample in stack.samples:
sample.reduceFiles( to = 1 )
# Use some defaults
Plot.setDefaults(stack = stack, weight = staticmethod(weight_), selectionString = cutInterpreter.cutString(args.selection), addOverFlowBin='upper')
plots = []
plots.append(Plot(
name = 'yield', texX = 'yield', texY = 'Number of Events',
attribute = lambda event, sample: 0.5 + index,
binning=[4, 0, 4],
))
plots.append(Plot(
name = 'flavor', texX = '', texY = 'Number of Events',
attribute = lambda event, sample: 0.5 + event.flavor_bin,
binning=[6, 0, 6],
))
h_target.Divide(h_source)
template = h_target
return template
if __name__ == "__main__":
# reweighting class
cacheDir = os.path.join(results_directory, 'WZReweightingTemplate')
if not os.path.isdir(cacheDir): os.makedirs(cacheDir)
WZReweighting = WZReweighting(cacheDir=cacheDir)
# reweighting selection
selection = cutInterpreter.cutString('trilep-Zcand-onZ-lepSelTTZ-njet1p')
# reweighting function
f = WZReweighting.cachedReweightingFunc(selection, weight='weight')
# plot the reweighting matrix
if args.makePlots:
histo = WZReweighting.cachedTemplate(selection,
weight='weight',
overwrite=False)
histo.style = styles.lineStyle(ROOT.kOrange + 3, errors=True)
histoPlot = Plot.fromHisto(target.name,
texY="a.u.",
texX="p_{T}(Z) (GeV)",
histos=[[histo]])
texName="t#bar{t}Z",
directory=directories['TTZ'])
TTZToLLNuNu = Sample.fromDirectory(name="TTZToLLNuNu",
treeName="Events",
isData=False,
color=color.TTZ,
texName="t#bar{t}Z(ll, #nu#nu)",
directory=directories['TTZToLLNuNu'])
TTZToQQ = Sample.fromDirectory(name="TTZToQQ",
treeName="Events",
isData=False,
color=color.WZ,
texName="t#bar{t}Z(qq)",
directory=directories['TTZToQQ'])
dilepSelection = cutInterpreter.cutString(
'lepSelDilepSUSY-njet3p-btag1p-mt2ll100-met80')
dilepSelection += '&&nlep==2&&nLeptons_tight_3l==2&&((nElectrons_tight_3l==1&&nMuons_tight_3l==1)||(nElectrons_tight_3l==2&&abs(Z_mass-91.2)>10)||(nMuons_tight_3l==2&&abs(Z_mass-91.2)>10))&&genZ_pt>=0'
#dilepSelection = cutInterpreter.cutString('njet3p-btag1p') + '&&genZ_pt>=0'
#dilepSelection += '&&(abs(genZ_daughter_flavor)==12||abs(genZ_daughter_flavor)==14||abs(genZ_daughter_flavor)==16)'
invisibleSelection = dilepSelection + '&&(abs(genZ_daughter_flavor)==12||abs(genZ_daughter_flavor)==14||abs(genZ_daughter_flavor)==16)'
leptonicSelection = dilepSelection + '&&(abs(genZ_daughter_flavor)==11||abs(genZ_daughter_flavor)==13)'
tauSelection = dilepSelection + '&&(abs(genZ_daughter_flavor)==15)'
hadronicSelection = dilepSelection + '&&(abs(genZ_daughter_flavor)<7)'
selection = "&&".join([dilepSelection])
## Sequence
read_variables = [
"weight/F",
"jet[pt/F,eta/F,phi/F,btagCSV/F,DFb/F,DFbb/F,id/I,btagDeepCSV/F]",
for dir in dirs[key]
]
for key in dirs.keys()
}
DYJetsToLL_M50_LO_ext_comb = Sample.fromDirectory(
name="DYJetsToLL_M50_LO_ext_comb",
treeName="Events",
isData=False,
color=color.TTJets,
texName="DY (LO)",
directory=directories['DYJetsToLL_M50_LO_ext_comb'])
## selections and plotting
selection = cutInterpreter.cutString(
'trilep-Zcand-lepSelTTZ-njet3p-btag1p-onZ')
WZselection = cutInterpreter.cutString(
'trilep-Zcand-lepSelTTZ-njet2p-btag2p-onZ')
DYselection = cutInterpreter.cutString('njet2p-btag2p-onZ')
DYselection += "&&Sum$(lep_pt>40&&lep_tight>0)>0 && Sum$(lep_pt>20&&lep_tight>0)>1 " #&& Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2"
trueVar = "jet_hadronFlavour"
#trueVar = "jet_mcFlavour"
#oneTrueB = "Sum$(jet_btagDeepCSV>0.6324&&abs(%s)==5)==1"
#moreTrueB = "Sum$(jet_btagDeepCSV>0.6324&&abs(%s)==5)>1"
oneTrueB = "Sum$(abs(%s)==5)==1" % trueVar
moreTrueB = "Sum$(abs(%s)==5)>1" % trueVar
trueCs = "Sum$(abs(%s)==4)>=1" % trueVar
onlyTrueB = "(Sum$(jet_btagDeepCSV>0.6324)==Sum$(jet_btagDeepCSV>0.6324&&abs(%s)==5))" % trueVar
offZ2 = "&&abs(Z2_mass_4l-91.2)>20" if args.selection.count("offZ2") else ""
offZ2 = "&&met_pt > 80" if args.selection.count("offZ2met") else offZ2
print offZ2
def getLeptonSelection( mode ):
if mode=="mumumumu": return "nMuons_tight_4l==4&&nElectrons_tight_4l==0" + offZ2
elif mode=="mumumue": return "nMuons_tight_4l==3&&nElectrons_tight_4l==1"
elif mode=="mumuee": return "nMuons_tight_4l==2&&nElectrons_tight_4l==2" + offZ2
elif mode=="mueee": return "nMuons_tight_4l==1&&nElectrons_tight_4l==3"
elif mode=="eeee": return "nMuons_tight_4l==0&&nElectrons_tight_4l==4" + offZ2
elif mode=='all': return "nMuons_tight_4l+nElectrons_tight_4l==4"
# reweighting
if args.reweightPtZToSM:
sel_string = "&&".join([getFilterCut(isData=False), getLeptonSelection('all'), cutInterpreter.cutString(args.selection)])
TTZ_ptZ = TTZtoLLNuNu.get1DHistoFromDraw("Z_pt", [20,0,1000], selectionString = sel_string, weightString="weight")
TTZ_ptZ.Scale(1./TTZ_ptZ.Integral())
def get_reweight( var, histo ):
def reweight(event, sample):
i_bin = histo.FindBin(getattr( event, var ) )
return histo.GetBinContent(i_bin)
return reweight
for signal in signals:
logger.info( "Computing PtZ reweighting for signal %s", signal.name )
signal_ptZ = signal.get1DHistoFromDraw("Z_pt", [20,0,1000], selectionString = sel_string, weightString="weight")
signal_ptZ.Scale(1./signal_ptZ.Integral())
dl_mt2ll_Z_smear = mt2Calc.mt2ll()
event.newMet_pt = newMet.Pt()
event.newMet_phi = newMet.Phi()
event.newMetSmeared_pt = newMetSmear.Pt()
event.dl_mt2ll_Z = dl_mt2ll_Z
event.dl_mt2ll_Z_smear = dl_mt2ll_Z_smear
event.dPhi_nonZ_l1_newMet = deltaPhi(newMet.Phi(), l1.Phi())
event.dPhi_nonZ_l2_newMet = deltaPhi(newMet.Phi(), l2.Phi())
return 1#newMet.Pt(), newMetSmear.Pt(), dl_mt2ll_Z, dl_mt2ll_Z_smear, newMet.Phi()
quadlepSelection = cutInterpreter.cutString('quadlep-lepSelQuad-njet1p-btag1p-onZ1-offZ2-min_mll12')
quadlepSelection += "&&lep_pt[nonZ1_l1_index_4l]>40&&lep_pt[nonZ1_l2_index_4l]>20"
#dilepSelection = cutInterpreter.cutString('dilepOS-njet3p-btag1p-offZ') # almost analysis like, no met cuts
#dilepSelection += '&&(abs(lep_pdgId[0])!=(lep_pdgId[1]))'
dilepSelection = cutInterpreter.cutString('lepSelDY-njet3p-btag1p')
dilepSelection += '&&nlep==2&&(nElectrons_tight_4l==1&&nMuons_tight_4l==1)'
dilepSelection += '&&(abs(genZ_daughter_flavor)==12||abs(genZ_daughter_flavor)==14||abs(genZ_daughter_flavor)==16)'
#dilepSelection = 'nlep==2&&(abs(lep_pdgId[0])!=(lep_pdgId[1]))'
sample = TTZToLLNuNu
dilepS = copy.deepcopy(TTZToLLNuNu)
quadlepS= copy.deepcopy(TTZToLLNuNu)
dilep = copy.deepcopy(TTZToLLNuNu)
quadlep = copy.deepcopy(TTZToLLNuNu)
#sample = TTLep_pow_17 if args.year == 2017 else TTLep_pow
# Trigger
from TopEFT.Tools.triggerSelector import triggerSelector
tr = triggerSelector(args.year)
# Event selection
nonpromptSelection = "nLeptons_FO_3l>=3 && Sum$((lep_tight_3l*(lep_pt - lep_ptCorr) + lep_ptCorr)>40&&lep_FO_3l>0)>0&&Sum$((lep_tight_3l*(lep_pt - lep_ptCorr) + lep_ptCorr)>20&&lep_FO_3l>0)>1&&Sum$((lep_tight_3l*(lep_pt - lep_ptCorr) + lep_ptCorr)>10&&lep_FO_3l>0)>2 && !(nLeptons_tight_4l>=4) && nLeptons_tight_3l<3"
promptSelection = "nLeptons_tight_3l==3 && nLeptons_FO_3l_genPrompt<=2 && Sum$(lep_pt>40&&lep_tight_3l>0)>0&&Sum$(lep_pt>20&&lep_tight_3l>0)>1&&Sum$(lep_pt>10&&lep_tight_3l>0)>2 && !(nLeptons_tight_4l>=4)"
#np_sel_string = "&&".join([getFilterCut(isData=False, year=args.year), tr.getSelection("MC"), nonpromptSelection, cutInterpreter.cutString(args.selection), "abs(Z_mass - 91.2)<10"])
#sel_string = "&&".join([getFilterCut(isData=False, year=args.year), tr.getSelection("MC"), promptSelection, cutInterpreter.cutString(args.selection), "abs(Z_mass - 91.2)<10 && Z_fromTight>0"])
np_sel_string = "&&".join([
getFilterCut(isData=False, year=args.year),
tr.getSelection("MC"), nonpromptSelection,
cutInterpreter.cutString(args.selection)
])
sel_string = "&&".join([
getFilterCut(isData=False, year=args.year),
tr.getSelection("MC"), promptSelection,
cutInterpreter.cutString(args.selection)
])
# weights
weight_central = "weight*reweightPU36fb*reweightBTagDeepCSV_SF*41.2"
# preparation for looper
loose_ID = "FO_3l"
tight_ID = "tight_3l"
nLeptons = 3
]
sample.read_variables += ["nBTag_%s/I" % s for s in jet_systematics]
sample.setSelectionString(
[getFilterCut(isData=False),
getLeptonSelection(mode)])
for s in signals:
s.scale = lumi_scale
#s.read_variables = ['reweightBTagCSVv2_SF/F','reweightPU36fb/F','nTrueInt/F']
#s.weight = lambda event, sample: event.reweightLeptonSF*event.reweightDilepTriggerBackup*event.reweightPU36fb
s.setSelectionString(
[getFilterCut(isData=False),
getLeptonSelection(mode)])
# Use some defaults
Plot.setDefaults(selectionString=cutInterpreter.cutString(args.selection))
stack_mc = Stack(mc)
stack_signal = Stack(mc[1:] + [dipole1])
if args.signal == "ewkDM": stack_data = Stack(data_sample, signals)
else: stack_data = Stack(data_sample)
sys_stacks = {
sys: copy.deepcopy(stack_mc)
for sys in [None] + weight_systematics + jme_systematics
}
plots = []
nBtagBinning = [5, 1, 6] if args.selection.count('btagM') else [1, 0, 1]
nbtags_data = Plot(
}
sample = Sample.fromDirectory(name="WZTo3LNu_amcatnlo",
treeName="Events",
isData=False,
color=color.TTJets,
texName="WZ MG (NLO)",
directory=directories['WZTo3LNu_amcatnlo'])
sample2 = Sample.fromDirectory(name="WZTo3LNu_powheg",
treeName="Events",
isData=False,
color=color.TTJets,
texName="WZ powheg (NLO)",
directory=directories['WZTo3LNu'])
selection = cutInterpreter.cutString(
'trilep-Zcand-lepSelTTZ-njet3p-btag1p-onZ')
WZselection = cutInterpreter.cutString(
'trilep-looseVeto-Zcand-lepSelTTZ-njet1p-btag0-onZ')
WZselection = cutInterpreter.cutString('trilep-Zcand-onZ-lepSelTTZ-njet1p')
selection = WZselection
weight_central = "weight"
weight_reweight = "weight * reweightTopPt"
# binning
binning = [25, 0, 500]
binning = [10, 0, 500]
binningCTS = [10, -1, 1]
# LO
elif mode=='all': return "nGoodMuons+nGoodElectrons==2"
## backgrounds / mc
#if args.background == "OnlyTTZ":
# mc = [ TTZtoLLNuNu ]
#elif args.background == "All":
# mc = [ TTZtoLLNuNu , TTX, WZ, TTW, TZQ, rare ]#, nonprompt ]
#else:
# mc = []
mc = []
for sample in mc: sample.style = styles.fillStyle(sample.color)
# reweighting
if args.reweightPtGToSM:
sel_string = "&&".join([getFilterCut(isData=False), getLeptonSelection('all'), cutInterpreter.cutString(args.selection)])
TTG_ptG = ttGamma0j_ll.get1DHistoFromDraw("photon_pt", [20,0,1000], selectionString = sel_string, weightString="weight")
TTG_ptG.Scale(1./TTG_ptG.Integral())
def get_reweight( var, histo ):
def reweight(event, sample):
i_bin = histo.FindBin(getattr( event, var ) )
return histo.GetBinContent(i_bin)
return reweight
for signal in signals:
logger.info( "Computing PtG reweighting for signal %s", signal.name )
signal_ptG = signal.get1DHistoFromDraw("photon_pt", [20,0,1000], selectionString = sel_string, weightString="weight")
signal_ptG.Scale(1./signal_ptG.Integral())
# reco signals
postProcessing_directory = "TopEFT_PP_v19/trilep/"
data_directory = "/afs/hephy.at/data/rschoefbeck02/cmgTuples/"
from TopEFT.samples.cmgTuples_ttZ0j_Summer16_mAODv2_postProcessed import *
source_reco = ttZ0j_ll
target_reco = ttZ0j_ll_DC1A_0p600000_DC1V_m0p240000_DC2A_0p176700_DC2V_0p176700
#target_reco = ttZ0j_ll_DC2A_0p200000_DC2V_0p200000
#target_reco = ttZ0j_ll_DC1A_0p500000_DC1V_0p500000
#target_reco = ttZ0j_ll_DC1A_1p000000
#target_reco = ttZ0j_ll_DC1A_0p600000_DC1V_m0p240000_DC2V_m0p250000
# cutInterpreter & selectionString
from TopEFT.Tools.cutInterpreter import cutInterpreter
reco_selection = cutInterpreter.cutString(
'lepSelTTZ-njet3p-btag1p-onZ')
logger.debug("Setting selectionString %s for reco samples",
reco_selection)
source_reco.setSelectionString(reco_selection)
target_reco.setSelectionString(reco_selection)
# Histos
pt_bins = [(0, 100), (100, 200), (200, -1), (-1, -1)]
h_pt = {
s: ROOT.TH1F('h_pt', 'h_pt', 10, 0, 500)
for s in ['source', 'target', 'source_reweighted']
}
h_pt['source'].legendText = "SM (reco)"
h_pt['source'].style = styles.lineStyle(ROOT.kBlue,
errors=True,
os.path.join(data_directory, postProcessing_directory, dir)
for dir in dirs[key]
]
for key in dirs.keys()
}
# Define samples
TTZ = Sample.fromDirectory(name="TTZ",
treeName="Events",
isData=False,
color=color.TTZ,
texName="t#bar{t}Z,Z to inv.",
directory=directories['TTZ'])
quadlepSelection = cutInterpreter.cutString(
'quadlep-lepSelQuad-njet1p-btag1p-onZ1-offZ2-min_mll12'
) # offZ2 in cutinterpreter doesn't do anything
quadlepSelection += "&&lep_pt[nonZ1_l1_index_4l]>40&&lep_pt[nonZ1_l2_index_4l]>20"
dilepSelection = cutInterpreter.cutString('lepSelDY-njet3p-btag1p')
dilepSelection += '&&nlep==2&&nLeptons_tight_4l==2&&(nElectrons_tight_4l==1&&nMuons_tight_4l==1)'
#dilepSelection += '&&nlep==2&&nLeptons_tight_4l==2&&((nElectrons_tight_4l==1&&nMuons_tight_4l==1)||(nElectrons_tight_4l==2&&abs(Z1_mass_4l-91.2)>10)||(nMuons_tight_4l==2&&abs(Z1_mass_4l-91.2)>10))'
dilepSelection += '&&genZ_pt>=0'
#dilepSelection += '&&(abs(genZ_daughter_flavor)==12||abs(genZ_daughter_flavor)==14||abs(genZ_daughter_flavor)==16)'
invisibleSelection = '(abs(genZ_daughter_flavor)==12||abs(genZ_daughter_flavor)==14||abs(genZ_daughter_flavor)==16)'
leptonicSelection = '(abs(genZ_daughter_flavor)==11||abs(genZ_daughter_flavor)==13)'
tauSelection = '(abs(genZ_daughter_flavor)==15)'
hadronicSelection = '(abs(genZ_daughter_flavor)<7)'
h_err.GetBinLowEdge(i_binx), central * (1 - relerr),
h_err.GetBinLowEdge(i_binx) +
h_err.GetBinWidth(i_binx), central * (1 + relerr)))
result.append(boxes)
return result
if __name__ == '__main__':
from TopEFT.samples.cmgTuples_Summer16_mAODv2_postProcessed import *
from TopEFT.samples.cmgTuples_signals_Summer16_mAODv2_postProcessed import *
from TopEFT.Tools.cutInterpreter import cutInterpreter
selection = "nGoodMuons+nGoodElectrons==3&&" + cutInterpreter.cutString(
"lepSelTTZ-njet3p-btag1p-onZ")
#weightString = "(1)"
weightString = "weight*36.9"
binning = [3, 0, 600]
bsm = getTheorySysFromChain(ewkDM_ttZ_ll_DC2A_0p20_DC2V_0p20.chain, 'Z_pt',
binning, selection, weightString)
res = getTheorySysFromChain(TTZtoLLNuNu.chain, 'Z_pt', binning, selection,
weightString)
bsm['h_nominal'].Scale(res['h_nominal'].Integral() /
bsm['h_nominal'].Integral())
#c1 = ROOT.TCanvas()
#res['h_nominal'].Draw()
