#--------------------------
# QCD Gamma Fakes - for CRY
#--------------------------
qcdGammaFakeSample = Sample(zlFitterConfig.qcdSampleName+"GammaFakes", kOrange+2)
qcdGammaFakeSample.setTreeName("QCD_SRAll")
qcdGammaFakeSample.setNormFactor("mu_"+zlFitterConfig.qcdSampleName+"GammaFakes", 1., 0., 500.)
qcdGammaFakeSample.setFileList(qcdGammaFakeFiles)
qcdGammaFakeSample.setStatConfig(zlFitterConfig.useStat)
# qcdGammaFakeSample.setStatConfig(False)
qcdGammaFakeSample.addSampleSpecificWeight("(phTruthOrigin!=38)")
if zlFitterConfig.doSetNormRegion:
if "CRYQ" in zlFitterConfig.constrainingRegionsList:
qcdGammaFakeSample.setNormRegions([("CRYQ", zlFitterConfig.binVar)])
# Define samples
#FakePhotonSample = Sample("Bkg",kGreen-9)
#FakePhotonSample.setStatConfig(False)
#FakePhotonSample.buildHisto([nbkg],"UserRegion","cuts")
# ucb = Systematic("ucb", configMgr.weights, 1 + nbkgErr/nbkg, 1 - nbkgErr/nbkg, "user","userOverallSys")
#FakePhotonSample.addSystematic(ucb)
#--------------------------
# Top
#--------------------------
topSample = Sample(zlFitterConfig.topSampleName, kGreen-9)
wzKtScale = Systematic("KtScaleWZ", configMgr.weights, ktScaleWHighWeights,
ktScaleWLowWeights, "weight", "normHistoSys")
# JES uncertainty as shapeSys - one systematic per region (combine WR and TR), merge samples
jes = Systematic("JES", "_NoSys", "_JESup", "_JESdown", "tree", "normHistoSys")
mcstat = Systematic("mcstat", "_NoSys", "_NoSys", "_NoSys", "tree",
"shapeStat")
# name of nominal histogram for systematics
configMgr.nomName = "_NoSys"
# List of samples and their plotting colours
topSample = Sample("Top", kGreen - 9)
topSample.setNormFactor("mu_Top", 1., 0., 5.)
topSample.setStatConfig(useStat)
topSample.setNormRegions([("SLWR", "nJet"), ("SLTR", "nJet")])
wzSample = Sample("WZ", kAzure + 1)
wzSample.setNormFactor("mu_WZ", 1., 0., 5.)
wzSample.setStatConfig(useStat)
wzSample.setNormRegions([("SLWR", "nJet"), ("SLTR", "nJet")])
bgSample = Sample("BG", kYellow - 3)
bgSample.setNormFactor("mu_BG", 1., 0., 5.)
bgSample.setStatConfig(useStat)
bgSample.setNormRegions([("SLWR", "nJet"), ("SLTR", "nJet")])
qcdSample = Sample("QCD", kGray + 1)
qcdSample.setQCD(True, "histoSys")
qcdSample.setStatConfig(useStat)
dataSample = Sample("Data", kBlack)
dataSample.setData()
dataSample.buildHisto([86., 66., 62., 35., 11., 7., 2., 0.], "SLTR", "nJet", 2)
dataSample.buildHisto([1092., 426., 170., 65., 27., 9., 4., 1.], "SLWR",
higgsSample = addSys(higgsSample, False, sysObj)
# ----------------------------------------------------- #
# ZV #
# ----------------------------------------------------- #
zvSample.setStatConfig(useStat)
if userOpts.splitMCSys :
zvSample.addSystematic(sysObj.AR_mcstat_ZV)
# Determine the normalization region :
# --> If zero jet : pick "a" CR
# --> If one jet : pick "b" CR
if userOpts.doSimFit2LZV :
if('Super0a' in SR or 'Super0b' in SR or 'Super0c' in SR) :
zvSample.setNormRegions([("emCRZV14a", "cuts")])
userPrint(" >>> Normalization region for ZV : emCRZV14a")
elif('Super1a' in SR or 'Super1b' in SR or 'Super1c' in SR) :
zvSample.setNormRegions([("emCRZV14b", "cuts")])
userPrint(" >>> Normalization region for ZV : emCRZV14b")
# add systematics
zvSample = addSys(zvSample, userOpts.doSimFit2LZV, sysObj)
# set normalization factor
if userOpts.doSimFit2LZV :
if('Super0a' in SR or 'Super0b' in SR or 'Super0c' in SR) :
zvSample.setNormFactor("mu_ZV14a", 1.,0.,10.)
userPrint(" >>> Normalization factor for ZV : mu_ZV14a")
elif('Super1a' in SR or 'Super1b' in SR or 'Super1c' in SR) :
zvSample.setNormFactor("mu_ZV14b", 1., 0., 10.)
userPrint(" >>> Normalization factor for ZV : mu_ZV14b")
else :
dibosonSample.setFileList(dibosonFiles)
dibosonSample.setStatConfig(useStat)
if useSyst: dibosonSample.addSystematic(theoSysDiboson)
topSample = Sample("ttbar",kGreen-9)
topSample.setTreeName("Top_SRAll")
topSample.setNormFactor("mu_Top",1.,0.,500.)
topSample.setFileList(topFiles)
topSample.setStatConfig(useStat)
if useTheoSys:
if useSyst: topSample.addSystematic(theoSysTop)
####topSample.addSystematic(mu1ScaleSysTop)
####topSample.addSystematic(mu2ScaleSysTop)
####topSample.addSystematic(matchScaleSysTop)
topSample.setNormRegions([("CRT","meffInc"),("CRW","meffInc")])
qcdSample = Sample("Multijets",kOrange+2)
qcdSample.setTreeName("QCDdd")
qcdSample.setNormFactor("mu_Multijets",1.,0.,500.)
qcdSample.setFileList(qcdFiles)
qcdSample.setStatConfig(useStat)
qcdSample.addWeight("0.000001")#qcd prenormalisation
#qcdSample.addSystematic(QCDGausSys)
#qcdSample.addSystematic(QCDTailSys)
qcdSample.setNormRegions([("CRQCD","meffInc")])
wSample = Sample("Wjets",kAzure+1)
wSample.setTreeName("W_SRAll")
# JES uncertainty as shapeSys - one systematic per region (combine WR and TR), merge samples
jes = Systematic("JES","_NoSys","_JESup","_JESdown","tree","overallNormHistoSys")
statWRwz = Systematic("SLWR_wz", "_NoSys","","","tree","shapeStat")
statWRtop = Systematic("SLWR_top","_NoSys","","","tree","shapeStat")
# name of nominal histogram for systematics
configMgr.nomName = "_NoSys"
# List of samples and their plotting colours
topSample = Sample("Top",kGreen-9)
topSample.setNormFactor("mu_Top",1.,0.,5.)
topSample.setStatConfig(useStat)
topSample.setNormRegions([("SLWR","nJet"),("SLTR","nJet")])
wzSample = Sample("WZ",kAzure+1)
wzSample.setNormFactor("mu_WZ",1.,0.,5.)
wzSample.setStatConfig(useStat)
wzSample.setNormRegions([("SLWR","nJet"),("SLTR","nJet")])
bgSample = Sample("BG",kYellow-3)
bgSample.setNormFactor("mu_BG",1.,0.,5.)
bgSample.setStatConfig(useStat)
bgSample.setNormRegions([("SLWR","nJet"),("SLTR","nJet")])
qcdSample = Sample("QCD",kGray+1)
qcdSample.setQCD(True,"histoSys")
qcdSample.setStatConfig(useStat)
dataSample = Sample("Data",kBlack)
dataSample.setData()
# create SR channel and add them to signal_channels
for sr in srs:
signal_channels.append(fitconfig.addChannel(variable, [sr], *binning))
# -----------------
# Control regions
# -----------------
CRQ = fitconfig.addChannel(variable, ['CRQ'], *binning)
CRW = fitconfig.addChannel(variable, ['CRW'], *binning)
CRT = fitconfig.addChannel(variable, ['CRT'], *binning)
constraint_channels.append(CRQ)
constraint_channels.append(CRW)
constraint_channels.append(CRT)
wgamma_sample.setNormRegions(['CRW', variable])
ttbarg_sample.setNormRegions(['CRT', variable])
photonjet_sample.setNormRegions(['CRQ', variable])
# -------------------
# Validation regions
# -------------------
if do_validation:
VRQ = fitconfig.addChannel(variable, ['VRQ'], *binning)
VRM1L = fitconfig.addChannel(variable, ['VRM1L'], *binning)
VRM2L = fitconfig.addChannel(variable, ['VRM2L'], *binning)
VRM1H = fitconfig.addChannel(variable, ['VRM1H'], *binning)
VRM2H = fitconfig.addChannel(variable, ['VRM2H'], *binning)
VRL1 = fitconfig.addChannel(variable, ['VRL1'], *binning)
signal_channels.append(SR)
# -----------------
# Control regions
# -----------------
CRQ = fitconfig.addChannel(variable, ['CRQ'], *binning)
CRW = fitconfig.addChannel(variable, ['CRW'], *binning)
CRT = fitconfig.addChannel(variable, ['CRT'], *binning)
constraint_channels.append(CRQ)
constraint_channels.append(CRW)
constraint_channels.append(CRT)
wgamma_sample .setNormRegions(['CRW', variable])
ttbarg_sample .setNormRegions(['CRT', variable])
photonjet_sample.setNormRegions(['CRQ', variable])
# -------------------
# Validation regions
# -------------------
if do_validation:
VRM1L = fitconfig.addChannel(variable, ['VRM1L'], *binning)
VRM2L = fitconfig.addChannel(variable, ['VRM2L'], *binning)
VRM3L = fitconfig.addChannel(variable, ['VRM3L'], *binning)
VRM1H = fitconfig.addChannel(variable, ['VRM1H'], *binning)
VRM2H = fitconfig.addChannel(variable, ['VRM2H'], *binning)
VRM3H = fitconfig.addChannel(variable, ['VRM3H'], *binning)
validation_channels.append(VRM1H)
topSample.setFileList(topFiles)
topSample.setStatConfig(useStat)
if useTheoSys:
topSample.addSystematic(theoSysTop)
if useSyst :
topSample.addSystematic(pileup)
topSample.addSystematic(jes)
topSample.addSystematic(jer)
topSample.addSystematic(scalest)
topSample.addSystematic(resost)
if useSyst and useCRWTY:
#topSample.setNormRegions([("CRT","cuts"),("CRW","cuts")])
topSample.setNormRegions([("CRT", binVar)])
# QCD
qcdSample = Sample("Multijets", kOrange+2)
qcdSample.setTreeName("QCDdd")
qcdSample.setNormFactor("mu_Multijets", 1., 0., 500.)
qcdSample.setFileList(qcdFiles)
qcdSample.setStatConfig(useStat)
qcdSample.addWeight("0.0000013")#ATT: qcd prenormalisation
## if useSyst :
## if useQCDMethodSyst:
## qcdSample.addSystematic(QCDTailSys )
## qcdSample.addSystematic(QCDGausSys )
## else:
## qcdSample.addSystematic(theoSysQCD)
# phoScaleMuttgamma = Systematic("phoScale",configMgr.weights, 1.015,1-.015, "user","userOverallSys")
# phoScaleMuttbarDilep = Systematic("phoScale",configMgr.weights, 1.028, 1-.028, "user","userOverallSys")
# phoScaleMust = Systematic("phoScale",configMgr.weights, 1.023, 1-.023, "user","userOverallSys")
# phoScaleMudiboson = Systematic("phoScale",configMgr.weights, 1.040, 1-.040, "user","userOverallSys")
# phoScaleMuZgamma = Systematic("phoScale",configMgr.weights, 1.025, 1-.025, "user","userOverallSys")
## List of samples and their plotting colours. Associate dedicated systematics if applicable.
ttbargamma = Sample("ttbargamma",46) # brick
ttbargamma.setNormByTheory()
ttbargamma.setStatConfig(True)
ttbargamma.addSystematic(ttbargammaNorm)
Wgamma = Sample("Wgamma",7) # cyan
Wgamma.setNormFactor("mu_Wgamma",1.,0.,5.)
Wgamma.setNormRegions([("WCRhHTEl", "cuts")])
Wgamma.setStatConfig(True)
#Wgamma.addSystematic(WgammaNorm)
Zgamma = Sample("Zgamma",kViolet) # cyan
Zgamma.setNormByTheory()
Zgamma.setStatConfig(True)
Zgamma.addSystematic(ZgammaNorm)
Zjets = Sample("Zjets",kBlue) # cyan
Zjets.setNormByTheory()
Zjets.setStatConfig(True)
Zjets.addSystematic(ZjetsNorm)
Wjets = Sample("Wjets",3) # green
Wjets.setNormByTheory(False)
for region in yields_dict :
configMgr.cutsDict[region] = "1."
# if "CR" in region :
# sample_for_cr = region.split("_")[1].lower()
# if sample.name.lower() == sample_for_cr :
# set_norm_by_theory = False
# sample.setNormFactor("mu_%s" % sample.name.lower(), 1.0, 0.0, 10.0)
# sample.setNormRegions([ (region, "cuts") ])
if set_norm_by_theory :
sample.setNormByTheory()
# add the samples
tlx.addSamples(all_samples)
# signal
if myFitType == FitType.Exclusion :
sample_sig.setStatConfig(True)
sample_sig.setNormFactor("mu_Test", 1.0, 0.0, 10.0)
sample_sig.setNormRegions( [ ("CR_BKG0", "cuts") ] )#, ("CR_BKG1", "cuts") ] )
sample_sig.setNormByTheory()
tlx.addSamples(sample_sig)
# tlx.setSignalSample(sample_sig)
# tlx.addSignalChannels(sr_channels)
if myFitType == FitType.Background :
#tlx.addSignalChannels(sr_channels)
tlx.addValidationChannels(sr_channels)
higgsSample = addSys(higgsSample, False, sysObj)
#------------------------------------------------#
# ZV #
#------------------------------------------------#
zvSample.setStatConfig(useStat)
if userOpts.splitMCSys:
zvSample.addSystematic(sysObj.AR_mcstat_ZV)
# Determine the normalization region
# This should be done only if we fit
# Regardless of channel combined ee+mm
if 'SR1' in SR and userOpts.doSimFit2LZV:
zvSample.setNormRegions([("emZVCRmet","cuts")])
if 'SR2a' in SR and userOpts.doSimFit2LZV:
zvSample.setNormRegions([("emZVCRmt2a","cuts")])
if 'SR2b' in SR and userOpts.doSimFit2LZV:
zvSample.setNormRegions([("emZVCRmt2a","cuts")])
if 'SR4a' in SR and userOpts.doSimFit2LZV:
zvSample.setNormRegions([("emZVCRmt2a","cuts")])
if 'SR4b' in SR and userOpts.doSimFit2LZV:
zvSample.setNormRegions([("emZVCRmt2a","cuts")])
if 'SR4c' in SR and userOpts.doSimFit2LZV:
zvSample.setNormRegions([("emZVCRmt2a","cuts")])
# ucb = Systematic("ucb", configMgr.weights, 1 + nbkgErr/nbkg, 1 - nbkgErr/nbkg, "user","userOverallSys")
# FakePhotonSample.addSystematic(ucb)
# --------------------------
# Top
# --------------------------
topSample = Sample(zlFitterConfig.topSampleName, kGreen - 9)
topSample.setTreeName("Top_SRAll")
topSample.setNormFactor("mu_" + zlFitterConfig.topSampleName, 1.0, 0.0, 500.0)
topSample.setFileList(topFiles)
topSample.setStatConfig(zlFitterConfig.useStat)
if zlFitterConfig.doSetNormRegion:
if "CRT" in zlFitterConfig.constrainingRegionsList and "CRW" in zlFitterConfig.constrainingRegionsList:
topSample.setNormRegions([("CRT", zlFitterConfig.binVar), ("CRW", zlFitterConfig.binVar)])
if not zlFitterConfig.usePreComputedTopGeneratorSys:
topSample.addSystematic(
Systematic(
"generatorTop",
configMgr.weights,
"_aMcAtNloHerwigpp",
"_aMcAtNloHerwigpp",
"tree",
"overallNormHistoSysOneSideSym",
)
)
if not zlFitterConfig.usePreComputedTopFragmentationSys:
topSample.addSystematic(
Systematic(
