## 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)
])
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
)
def getLeptonSelection(mode):
if mode == "mumumumu": return "nMuons_tight_4l==4&&nElectrons_tight_4l==0"
elif mode == "mumumue": return "nMuons_tight_4l==3&&nElectrons_tight_4l==1"
elif mode == "mumuee": return "nMuons_tight_4l==2&&nElectrons_tight_4l==2"
elif mode == "mueee": return "nMuons_tight_4l==1&&nElectrons_tight_4l==3"
elif mode == "eeee": return "nMuons_tight_4l==0&&nElectrons_tight_4l==4"
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 mva in mvas:
reader_nonprompt.addMethod(method=mva)
sequence.append( makeDiscriminator(mva) )
#
# Loop over channels
#
yields = {}
allPlots = {}
allModes = ['mumu','mue','ee']
for index, mode in enumerate(allModes):
yields[mode] = {}
if not args.noData:
data_sample = Run2016
data_sample.texName = "data (legacy)"
data_sample.setSelectionString([getFilterCut(isData=True), getLeptonSelection(mode)])
data_sample.name = "data"
data_sample.read_variables = ["evt/I","run/I"]
data_sample.style = styles.errorStyle(ROOT.kBlack)
lumi_scale = data_sample.lumi/1000
# lumi_scale = 300
lumi_scale = 35.9
weight_ = lambda event, sample: event.weight
TTZ_mc = TTZtoLLNuNu
tWZ_sample = TWZ if args.nominalSignal else yt_TWZ_filter
if args.WZpowheg:
mc = [ tWZ_sample, TTZ_mc , TTX, WZ_powheg, rare, ZZ, nonprompt_TWZ_3l, Xgamma ]
else:
def selection(self,
dataMC,
mllMin,
metMin,
zWindow1,
zWindow2,
zMassRange,
nJets,
nBTags,
nElectrons=-1,
nMuons=-1,
hadronicSelection=False,
isFastSim=False):
'''Define full selection
dataMC: 'Data' or 'MC'
nElectrons, nMuons: Number of E and M. -1: all
zWindow: offZ, onZ, or allZ
hadronicSelection: whether to return only the hadronic selection
isFastSim: adjust filter cut etc. for fastsim
'''
nLeptons = self.nLeptons
# Get the right channel and do sanity checks
if nElectrons < 0 and nMuons < 0:
# this should be the new "all" case. Just
pass
else:
if nElectrons + nMuons != nLeptons:
raise NotImplementedError("Electrons and Muons don't add up!")
#Consistency checks
if self.sys['selectionModifier']:
assert self.sys[
'selectionModifier'] in jmeVariations + metVariations + [
'genMet'
], "Don't know about systematic variation %r, take one of %s" % (
self.sys['selectionModifier'],
",".join(jmeVariations + ['genMet']))
assert dataMC in ['Data',
'MC'], "dataMC = Data or MC, got %r." % dataMC
#Postfix for variables (only for MC and if we have a jme variation)
sysStr = ""
metStr = ""
if dataMC == "MC" and self.sys['selectionModifier'] in jmeVariations:
sysStr = "_" + self.sys['selectionModifier']
if dataMC == "MC" and self.sys['selectionModifier'] in metVariations:
metStr = "_" + self.sys['selectionModifier']
res = {'cuts': [], 'prefixes': []}
if nJets and not (nJets[0] == 0 and nJets[1] < 0):
assert nJets[0] >= 0 and (
nJets[1] >= nJets[0]
or nJets[1] < 0), "Not a good nJets selection: %r" % nJets
njetsstr = "nJetSelected" + sysStr + ">=" + str(nJets[0])
prefix = "nJets" + str(nJets[0])
if nJets[1] >= 0:
njetsstr += "&&" + "nJetSelected" + sysStr + "<=" + str(
nJets[1])
if nJets[1] != nJets[0]: prefix += str(nJets[1])
else:
prefix += 'p'
res['cuts'].append(njetsstr)
res['prefixes'].append(prefix)
if nBTags and not (nBTags[0] == 0 and nBTags[1] < 0):
assert nBTags[0] >= 0 and (
nBTags[1] >= nBTags[0]
or nBTags[1] < 0), "Not a good nBTags selection: %r" % nBTags
nbtstr = "nBTag" + sysStr + ">=" + str(nBTags[0])
prefix = "nbtag" + str(nBTags[0])
if nBTags[1] >= 0:
nbtstr += "&&nBTag" + sysStr + "<=" + str(nBTags[1])
if nBTags[1] != nBTags[0]: prefix += str(nBTags[1])
else:
prefix += 'p'
res['cuts'].append(nbtstr)
res['prefixes'].append(prefix)
if metMin and metMin > 0:
res['cuts'].append('met_pt' + sysStr + metStr + '>=' + str(metMin))
res['prefixes'].append('met' + str(metMin))
if not hadronicSelection:
if mllMin and mllMin > 0:
res['cuts'].append('min_dl_mass>=' + str(mllMin))
res['prefixes'].append('mll' + str(mllMin))
if nMuons >= 0 and nElectrons >= 0:
chStr = "(nMuons_%s==%i&&nElectrons_%s==%i)" % (
self.leptonId, nMuons, self.leptonId, nElectrons)
else:
# this is for the 'all' channel
if not self.nonprompt:
chStr = "nLeptons_%s==%i" % (self.leptonId, nLeptons)
else:
chStr = "nLeptons_%s>=%i" % (self.leptonId, nLeptons)
#Z window
# two different cases: Z_mass for 3l, Z1_mass_4l and Z2_mass_4l for 4l
if nLeptons == 3:
res['cuts'].append(getZCut(zWindow1, "Z_mass", zMassRange))
if not self.nonprompt: res['cuts'].append("Z_fromTight>0")
elif nLeptons == 4:
res['cuts'].append(getZCut(zWindow1, "Z1_mass_4l", zMassRange))
if zWindow2 == 'offZ':
# if number of muons is even, go off-Z
if nMuons % 2 == 0:
logger.info("Z window 2 off Z, nMuons %s", nMuons)
res['cuts'].append(
getZCut("offZ", "Z2_mass_4l", zMassRange))
else:
logger.info("Z window 2 all Z, nMuons %s", nMuons)
res['cuts'].append(
getZCut("allZ", "Z2_mass_4l", zMassRange))
else:
logger.info("Z window 2 %s, nMuons %s", zWindow2, nMuons)
res['cuts'].append(
getZCut(zWindow2, "Z2_mass_4l", zMassRange))
# no Z-mass cut for 2l case
res['cuts'].append(chStr)
if not self.nonprompt:
res['cuts'].append('nLeptons_%s==%i' %
(self.leptonId, nLeptons))
else:
res['cuts'].append('nLeptons_%s>=%i' %
(self.leptonId, nLeptons))
if nLeptons == 1:
lep_pt = "(lep_%s*(lep_pt - lep_ptCorr) + lep_ptCorr)" % self.tight_ID
res['cuts'].append("Sum$(%s>40&&lep_%s>0)>0" %
(lep_pt, self.leptonId))
res['cuts'].append("nlep==1") # loose lepton veto
elif nLeptons == 2:
raise NotImplementedError("Not yet thought about SS selection")
elif nLeptons == 3:
lep_pt = "(lep_%s*(lep_pt - lep_ptCorr) + lep_ptCorr)" % self.tight_ID
leptonSelection = [\
"Sum$(%s>40&&lep_%s>0)>0"%(lep_pt, self.leptonId),\
"Sum$(%s>20&&lep_%s>0)>1"%(lep_pt, self.leptonId),\
"Sum$(%s>10&&lep_%s>0)>2"%(lep_pt, self.leptonId),\
]
res['cuts'].append("&&".join(leptonSelection))
res['cuts'].append(
"!(nLeptons_tight_4l>=4)"
) # make sure to remove full overlap with 4l. This is enought, what is below shouldn't be necessary.
if self.nonprompt: res['cuts'].append("nLeptons_tight_3l<3")
#res['cuts'].append("min_dl_mass_FO_3l>12") #######################UPDATE
## need to veto 4l events to remove overlap
#baseline4l = Setup(self.year, nLeptons=4)
#baseline4l.parameters.update({'nJets':(2,-1), 'nBTags':(0,-1), 'zMassRange':20})
#for c in quadlepChannels:
# res['cuts'].append("!(%s)"%baseline4l.preselection(dataMC, nElectrons=c.nE, nMuons=c.nM, short=True)['cut'])
elif nLeptons == 4:
res['cuts'].append(
"Sum$(lep_pt>40&&lep_%s>0)>0 && Sum$(lep_pt>10&&lep_%s>0)>3"
% (self.leptonId,
self.leptonId)) #check if this is good enough
res['cuts'].append("min_dl_mass>12&&totalLeptonCharge==0")
else:
raise NotImplementedError(
"nLeptons has to be 1 or 2 or 3 or 4. That's already more than enough to think about."
)
# Need a better solution for the Setups for different eras
if self.year == 20167:
self.year = 2016 #FIXME since we use 2016 MC for now
if not self.short:
res['cuts'].append(
getFilterCut(isData=(dataMC == 'Data'),
isFastSim=isFastSim,
year=self.year))
# apply triggers in MC
if not dataMC == 'Data':
tr = triggerSelector(self.year)
if not self.short: res['cuts'].append(tr.getSelection("MC"))
res['cuts'].extend(self.externalCuts)
return {
'cut': "&&".join(res['cuts']),
'prefix': '-'.join(res['prefixes']),
'weightStr': (self.weightString() if dataMC == 'MC' else 'weight')
}
#
# Loop over channels
#
yields = {}
allPlots = {}
allModes = ['nLep']
for index, mode in enumerate(allModes):
yields[mode] = {}
logger.info("Working on mode %s", mode)
if not args.noData:
data_sample = Run2016 if args.year == 2016 else Run2017
data_sample.texName = "data"
data_sample.setSelectionString([
getFilterCut(isData=True, year=args.year),
getLeptonSelection(mode)
])
data_sample.name = "data"
data_sample.read_variables = ["evt/I", "run/I"]
data_sample.style = styles.errorStyle(ROOT.kBlack)
lumi_scale = data_sample.lumi / 1000
if args.noData: lumi_scale = 35.9 if args.year == 2016 else 41.0
weight_ = lambda event, sample: event.weight
lumi_scale = 300
TTZ_mc = TTZtoLLNuNu
if args.year == 2016:
mc = [yt_TWW]
DY_noGS.color = ROOT.kOrange + 8
DY_noGS.texName = "DY (LO), N_{true b-jets}#geq2, no GS"
DY_unknown = copy.deepcopy(DY_HT_LO)
DY_unknown.color = ROOT.kRed - 3
DY_unknown.texName = "DY (LO), N_{true b-jets}#geq2, unknown"
DY_fakeBs = copy.deepcopy(DY_HT_LO)
DY_fakeBs.color = ROOT.kGreen + 3
DY_fakeBs.texName = "DY (LO), N_{true b-jets}=0"
#mc = [DY_twoTrueBsElse, DY_twoTrueBsFromG, DY_twoTrueBsFromP, DY_twoTrueBsFromQ, DY_oneTrueBs, DY_fakeBs,TTX,boson, Top]
mc = [DY_GS, DY_noGS, DY_unknown, DY_fakeBs, TTX, boson, Top]
for s in mc:
s.setSelectionString([getFilterCut(isData=False), tr.getSelection("MC")])
s.read_variables = ['reweightPU36fb/F', 'reweightBTagDeepCSV_SF/F']
s.weight = lambda event, s: event.reweightBTagDeepCSV_SF * event.reweightPU36fb
s.style = styles.fillStyle(s.color)
s.scale = lumi_scale
#nBFromG = "Sum$(abs(genPartAll_pdgId)==5&&abs(genPartAll_motherId)>5&&(abs(genPartAll_motherId)==21))"
#nBFromP = "Sum$(abs(genPartAll_pdgId)==5&&abs(genPartAll_motherId)>5&&(abs(genPartAll_motherId)==2212))"
#nBFromQ = "Sum$(abs(genPartAll_pdgId)==5&&abs(genPartAll_motherId)<5)"
#
#DY_twoTrueBsFromG.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s>=2"%nBFromG])
#DY_twoTrueBsFromP.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s>=2 && %s<2"%(nBFromP,nBFromG)])
#DY_twoTrueBsFromQ.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s>=2 && %s<2 && %s<2"%(nBFromQ,nBFromP,nBFromG)])
#DY_twoTrueBsElse.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s<2 && %s<2 && %s<2"%(nBFromG,nBFromQ,nBFromP)])
#DY_oneTrueBs.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)==1"])
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())
DY_noGS.texName = "DY (LO), N_{true b-jets}#geq2, no GS"
DY_unknown = copy.deepcopy(DY_HT_LO)
DY_unknown.color = ROOT.kRed-3
DY_unknown.texName = "DY (LO), N_{true b-jets}#geq2, unknown"
DY_fakeBs = copy.deepcopy(DY_HT_LO)
DY_fakeBs.color = ROOT.kGreen+3
DY_fakeBs.texName = "DY (LO), N_{true b-jets}=0"
#mc = [DY_twoTrueBsElse, DY_twoTrueBsFromG, DY_twoTrueBsFromP, DY_twoTrueBsFromQ, DY_oneTrueBs, DY_fakeBs,TTX,boson, Top]
mc = [DY_GS,DY_noGS,DY_unknown,DY_fakeBs,TTX,boson, Top]
for s in mc:
s.setSelectionString([getFilterCut(isData=False), tr.getSelection("MC")])
s.read_variables = ['reweightPU36fb/F', 'reweightBTagDeepCSV_SF/F']
s.weight = lambda event, s: event.reweightBTagDeepCSV_SF*event.reweightPU36fb
s.style = styles.fillStyle(s.color)
s.scale = lumi_scale
#nBFromG = "Sum$(abs(genPartAll_pdgId)==5&&abs(genPartAll_motherId)>5&&(abs(genPartAll_motherId)==21))"
#nBFromP = "Sum$(abs(genPartAll_pdgId)==5&&abs(genPartAll_motherId)>5&&(abs(genPartAll_motherId)==2212))"
#nBFromQ = "Sum$(abs(genPartAll_pdgId)==5&&abs(genPartAll_motherId)<5)"
#
#DY_twoTrueBsFromG.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s>=2"%nBFromG])
#DY_twoTrueBsFromP.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s>=2 && %s<2"%(nBFromP,nBFromG)])
#DY_twoTrueBsFromQ.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s>=2 && %s<2 && %s<2"%(nBFromQ,nBFromP,nBFromG)])
#DY_twoTrueBsElse.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)>=2 && %s<2 && %s<2 && %s<2"%(nBFromG,nBFromQ,nBFromP)])
#DY_oneTrueBs.addSelectionString(["Sum$(jet_pt>30&&abs(jet_eta)<2.4&&jet_id>0&&jet_btagDeepCSV>0.6324&&jet_hadronFlavour==5)==1"])
def selection(self,
dataMC,
mllMin,
metMin,
zWindow,
nJets,
nBTags,
channel='all',
hadronicSelection=False,
isFastSim=False):
'''Define full selection
dataMC: 'Data' or 'MC'
channel: all, EE, MuMu or EMu
zWindow: offZ, onZ, or allZ
hadronicSelection: whether to return only the hadronic selection
isFastSim: adjust filter cut etc. for fastsim
'''
#Consistency checks
if self.sys['selectionModifier']:
assert self.sys[
'selectionModifier'] in jmeVariations + metVariations + [
'genMet'
], "Don't know about systematic variation %r, take one of %s" % (
self.sys['selectionModifier'],
",".join(jmeVariations + ['genMet']))
assert dataMC in ['Data',
'MC'], "dataMC = Data or MC, got %r." % dataMC
#Postfix for variables (only for MC and if we have a jme variation)
sysStr = ""
metStr = ""
if dataMC == "MC" and self.sys['selectionModifier'] in jmeVariations:
sysStr = "_" + self.sys['selectionModifier']
if dataMC == "MC" and self.sys['selectionModifier'] in metVariations:
metStr = "_" + self.sys['selectionModifier']
res = {'cuts': [], 'prefixes': []}
if nJets and not (nJets[0] == 0 and nJets[1] < 0):
assert nJets[0] >= 0 and (
nJets[1] >= nJets[0]
or nJets[1] < 0), "Not a good nJets selection: %r" % nJets
njetsstr = "nJetSelected" + sysStr + ">=" + str(nJets[0])
prefix = "nJets" + str(nJets[0])
if nJets[1] >= 0:
njetsstr += "&&" + "nJetSelected" + sysStr + "<=" + str(
nJets[1])
if nJets[1] != nJets[0]: prefix += str(nJets[1])
else:
prefix += 'p'
res['cuts'].append(njetsstr)
res['prefixes'].append(prefix)
if nBTags and not (nBTags[0] == 0 and nBTags[1] < 0):
assert nBTags[0] >= 0 and (
nBTags[1] >= nBTags[0]
or nBTags[1] < 0), "Not a good nBTags selection: %r" % nBTags
nbtstr = "nBTag" + sysStr + ">=" + str(nBTags[0])
prefix = "nbtag" + str(nBTags[0])
if nBTags[1] >= 0:
nbtstr += "&&nBTag" + sysStr + "<=" + str(nBTags[1])
if nBTags[1] != nBTags[0]: prefix += str(nBTags[1])
else:
prefix += 'p'
res['cuts'].append(nbtstr)
res['prefixes'].append(prefix)
if metMin and metMin > 0:
res['cuts'].append('met_pt' + sysStr + metStr + '>=' + str(metMin))
res['prefixes'].append('met' + str(metMin))
if not hadronicSelection:
if mllMin and mllMin > 0:
res['cuts'].append('Z_mass>=' + str(mllMin))
res['prefixes'].append('mll' + str(mllMin))
presel3mu = "(nGoodMuons==3&&nGoodElectrons==0)"
presel2mu1e = "(nGoodMuons==2&&nGoodElectrons==1)"
presel2e1mu = "(nGoodMuons==1&&nGoodElectrons==2)"
presel3e = "(nGoodMuons==0&&nGoodElectrons==3)"
allPresels = [presel3mu, presel2mu1e, presel2e1mu, presel3e]
#Z window
assert zWindow in [
'offZ', 'onZ', 'allZ'
], "zWindow must be one of onZ, offZ, allZ. Got %r" % zWindow
if zWindow == 'onZ':
res['cuts'].append(getZCut(zWindow, self.zMassRange))
if zWindow == 'offZ' and channel != "EMu":
res['cuts'].append(
getZCut(zWindow, self.zMassRange)
) # Never use offZ when in emu channel, use allZ instead
#lepton channel
assert channel in allChannels, "channel must be one of " + ",".join(
allChannels) + ". Got %r." % channel
if channel == "3mu": chStr = presel3mu
elif channel == "2mu1e": chStr = presel2mu1e
elif channel == "2e1mu": chStr = presel2e1mu
elif channel == "3e": chStr = presel3e
elif channel == "all": chStr = "(" + '||'.join(allPresels) + ')'
res['cuts'].append(chStr)
res['cuts'].append('nlep==3')
res['cuts'].append("lep_pt[0]>40&&lep_pt[1]>20&&lep_pt[2]>10")
res['cuts'].append(
getFilterCut(isData=(dataMC == 'Data'), isFastSim=isFastSim))
res['cuts'].extend(self.externalCuts)
return {
'cut': "&&".join(res['cuts']),
'prefix': '-'.join(res['prefixes']),
'weightStr': (self.weightString() if dataMC == 'MC' else 'weight')
}
SingleMuon_Run2016.setSelectionString("(HLT_SingleMuTTZ)")
SingleEleMu_Run2016.setSelectionString(
"(HLT_SingleEleTTZ && !HLT_SingleMuTTZ)")
#data_sample.texName = "data (2#mu, 1e)"
elif mode == "muee":
data_sample = [SingleEleMu_Run2016, SingleMuon_Run2016]
SingleMuon_Run2016.setSelectionString("(HLT_SingleMuTTZ)")
SingleEleMu_Run2016.setSelectionString(
"(HLT_SingleEleTTZ && !HLT_SingleMuTTZ)")
#data_sample.texName = "data (1#mu, 2e)"
elif mode == "all":
data_sample = [
SingleEleMu_Run2016, SingleMuon_Run2016, SingleElectron_Run2016
]
SingleMuon_Run2016.setSelectionString(
[getFilterCut(isData=True), "(HLT_SingleMuTTZ)"])
SingleEleMu_Run2016.setSelectionString([
getFilterCut(isData=True), "(HLT_SingleEleTTZ && !HLT_SingleMuTTZ)"
])
for d in data_sample:
d.texName = "data"
d.read_variables = ['weight/F']
d.style = styles.errorStyle(ROOT.kBlack)
lumi_scale = sum(d.lumi
for d in data_sample) / float(len(data_sample)) / 1000
data_weight = lambda event, sample: event.weight
data_weight_string = "weight"
logger.info('Lumi scale is ' + str(lumi_scale))
data_2017D_sample = SingleEleMu_Run2017EF
data_2017D_sample.texName = "data 2017EF (1#mu, 1e)"
data_2017EF_sample = SingleEleMu_Run2017EF
data_2017EF_sample.texName = "data 2017EF (1#mu, 1e)"
data_2017_samples = [
data_2017BC_sample, data_2017Cv2D_sample, data_2017EF_sample
]
data_2016_samples = [
copy.deepcopy(data_2016_sample) for x in data_2017_samples
]
else:
raise ValueError
for i_s, data_2017_sample in enumerate(data_2017_samples):
data_2017_sample.setSelectionString(
[getFilterCut(isData=True, year=2017),
getLeptonSelection(mode)])
data_2017_sample.read_variables = ["evt/I", "run/I"]
data_2017_sample.style = styles.errorStyle(colors[i_s])
lumi_2017_scale = data_2017_sample.lumi / 1000
for i_s, data_2016_sample in enumerate(data_2016_samples):
data_2016_sample.setSelectionString(
[getFilterCut(isData=True, year=2016),
getLeptonSelection(mode)])
data_2016_sample.read_variables = ["evt/I", "run/I"]
data_2016_sample.style = styles.lineStyle(colors[i_s] + 1, errors=True)
lumi_2016_scale = data_2016_sample.lumi / 1000
weight_ = lambda event, sample: event.weight
stack_samples = []
)
# define 3l selections
def getLeptonSelection(mode):
if mode == "mumumu": return "nGoodMuons==3&&nGoodElectrons==0"
elif mode == "mumue": return "nGoodMuons==2&&nGoodElectrons==1"
elif mode == "muee": return "nGoodMuons==1&&nGoodElectrons==2"
elif mode == "eee": return "nGoodMuons==0&&nGoodElectrons==3"
elif mode == 'all': return "nGoodMuons+nGoodElectrons==3"
# 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
sequence.append(getLooseLeptonMult)
#
# Loop over channels
#
yields = {}
allPlots = {}
allModes = ['mumumu', 'mumue', 'muee', 'eee']
for index, mode in enumerate(allModes):
yields[mode] = {}
if not args.noData:
data_sample = Run2016
data_sample.texName = "data (legacy)"
data_sample.setSelectionString(
[getFilterCut(isData=True),
getLeptonSelection(mode)])
data_sample.name = "data"
data_sample.read_variables = ["evt/I", "run/I"]
data_sample.style = styles.errorStyle(ROOT.kBlack)
lumi_scale = data_sample.lumi / 1000
if args.noData: lumi_scale = 35.9
weight_ = lambda event, sample: event.weight
TTZ_mc = TTZtoLLNuNu
if args.WZpowheg:
mc = [TWZ, TTZ_mc, TTX, WZ_powheg, rare, ZZ, nonpromptMC, Xgamma]
else:
mc = [TWZ, TTZ_mc, TTX, WZ_amcatnlo, rare, ZZ, nonpromptMC, Xgamma]
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())
elif mode=="all": return "nGoodLeptons==3"
#
# Loop over channels
#
allPlots = {}
allModes = ['mumumu','mumue','muee', 'eee', 'all']
allModes = ['all']
for index, mode in enumerate(allModes):
logger.info('Working on mode ' + str(mode))
if args.year == 2016:
data_sample = Run2016
data_sample.setSelectionString([getFilterCut(isData=True), getLeptonSelection(mode)])
elif args.year == 2017:
data_sample = Run2017
data_sample.setSelectionString([getFilterCut(isData=True, year=2017), getLeptonSelection(mode)])
lumi_scale = data_sample.lumi/1000
data_sample.texName = "data"
data_sample.read_variables = ['weight/F']
data_sample.style = styles.errorStyle( ROOT.kBlack )
data_weight = lambda event, sample: event.weight
data_weight_string = "weight"
logger.info('Lumi scale is ' + str(lumi_scale))
if args.year == 2016:
for s in quadlep_samples:
logger.info("Sample: %s", s.name)
hists[s.name] = mt2ll_hist.Clone()
hists[s.name].Reset()
hists[s.name].legendText = s.texName
met_hists[s.name] = met_hist.Clone()
met_hists[s.name].Reset()
met_hists[s.name].legendText = s.texName
# selection for data or MC. Trigger and filters and stuff!
for mode in modes:
logger.info("Working on mode %s", mode)
if s.isData:
s.setSelectionString([
getFilterCut(isData=True, year=2016), quadlepSelection,
getLeptonSelection(mode)
])
else:
s.setSelectionString([
getFilterCut(isData=False, year=2016), quadlepSelection,
tr.getSelection("MC"),
getLeptonSelection(mode)
])
reader = s.treeReader(variables=variables)
reader.start()
while reader.run():
r = reader.event
