plotOpts = { 'comment':False }
regionsOrder = ["0BSusySync", "1BSusySync", "2BSusySync"]
regions = {
"0BSusySync":Analysis("SusySync", tag=tag, nbMax=0),
"1BSusySync":Analysis("SusySync", tag=tag, nbMin=1),
"2BSusySync":Analysis("SusySync", tag=tag, nbMin=2),
}
for region in regionsOrder:
analysis = regions[region]
name = region
#apply extra lepton cuts
if args.muons:
analysis.cutsData += " && abs(lep1Type) == 13"
analysis.cutsMC += " && abs(lep1Type) == 13"
name += "_Muons"
if args.electrons:
analysis.cutsData += " && abs(lep1Type) == 11"
analysis.cutsMC += " && abs(lep1Type) == 11"
name += "_Electrons"
#make output directory
outdir = 'Plots/'+tag+'/'+name
os.system('mkdir -p '+outdir)
#perform analysis
hists = makeControlSampleHistsForAnalysis( analysis, plotOpts=plotOpts,
printdir=outdir, debugLevel=debugLevel )
#export histograms
macro.exportHists(hists, outFileName='controlHistograms'+name+'.root',
outDir=outdir, debugLevel=debugLevel)
"data/ScaleFactors/RazorMADD2015/RazorTTJetsDileptonCrossCheck_%s.root"
% (tag), "RECREATE")
for region in regionsOrder:
analysis = regions[region]
analysis.weightOpts.append('ttbardileptonmt')
analysis.dataWeightOpts.append('ttbardileptonmt')
#make output directory
outdir = 'Plots/' + tag + '/' + region
os.system('mkdir -p ' + outdir)
#prepare analysis
auxSFs = razorWeights.getNJetsSFs(analysis, jetName='NJets40')
#perform analysis
hists = makeControlSampleHistsForAnalysis(analysis,
plotOpts=plotOpts,
sfHists=sfHists,
printdir=outdir,
auxSFs=auxSFs,
debugLevel=debugLevel)
#record discrepancies > 1 sigma
tmpSFHists = copy.copy(sfHists)
if 'TTJets2L' in tmpSFHists: del tmpSFHists["TTJets2L"]
appendScaleFactors("TTJets2L",
hists,
tmpSFHists,
lumiData=analysis.lumi,
debugLevel=debugLevel,
signifThreshold=1.0,
printdir=outdir)
#write out scale factors
print "Writing histogram", tmpSFHists["TTJets2L"].GetName(), "to file"
outfile.cd()
"data/ScaleFactors/RazorMADD2015/RazorNJetsScaleFactors_%s.root"%(tag))
sfHists['NJetsInv'] = sfNJetsFile.Get("GJetsInvScaleFactors")
razorWeights.loadPhotonPurityHists(sfHists, tag, debugLevel)
for region in regionsOrder:
analysis = regions[region]
print "\nRegion:",region,"\n"
#make output directory
outdir = 'Plots/'+tag+'/'+region
os.system('mkdir -p '+outdir)
#set up analysis
(xbins,cols) = analysis.unrollBins
auxSFs = razorWeights.getNJetsSFs(analysis, jetName=analysis.jetVar)
razorWeights.getPhotonPuritySFs(auxSFs)
#perform analysis
hists = makeControlSampleHistsForAnalysis( analysis, plotOpts=plotOpts, sfHists=sfHists,
sfVars=sfVars, printdir=outdir, auxSFs=auxSFs, btags=analysis.nbMin,
dataDrivenQCD=True, debugLevel=debugLevel, noFill=args.noFill )
#compute scale factors
appendScaleFactors( region+"MR", hists, sfHists, lumiData=analysis.lumi,
var="MR_NoPho", debugLevel=debugLevel, signifThreshold=1.0, printdir=outdir )
appendScaleFactors( region+"Rsq", hists, sfHists, lumiData=analysis.lumi,
var="Rsq_NoPho", debugLevel=debugLevel, signifThreshold=1.0, printdir=outdir )
#export histograms
macro.exportHists( hists, outFileName='controlHistograms'+region+'.root',
outDir=outdir, debugLevel=debugLevel )
if not args.noSave:
#write out scale factors
outfile = rt.TFile(
"data/ScaleFactors/RazorMADD2015/RazorGJetsBTagClosureTests_%s.root"%(tag),
"UPDATE")
print "Writing scale factor histogram",sfHists[region+"MR"].GetName(),"to file"
os.system('mkdir -p '+outdir)
#prepare analysis
auxSFs = razorWeights.getNJetsSFs(analysis,jetName='NJets_NoZ')
auxSFs = razorWeights.addAllBTagSFs(analysis, auxSFs)
auxSFs = razorWeights.addAllBTagSFs(analysis, auxSFs, var='MR_NoZ',
gjets=True)
bclosure.adjustForRegionBInclusive(analysis, sfHists, auxSFs)
bclosure.adjustForRegionBInclusive(analysis, sfHists, auxSFs, gjets=True)
#use the correct set of scale factors
if 'NoSFs' in region:
sfHistsToUse = {}
auxSFs = { proc:{} for proc in auxSFs }
else:
sfHistsToUse = sfHists
#perform analysis
hists = makeControlSampleHistsForAnalysis( analysis, plotOpts=plotOpts, sfHists=sfHistsToUse,
sfVars=sfVars, printdir=outdir, auxSFs=auxSFs, debugLevel=debugLevel, noFill=args.noFill )
for v in ['MR', 'Rsq']:
tmpSFHists = copy.copy(sfHists)
del tmpSFHists["DYJetsInv"]
appendScaleFactors("DYJetsInv", hists, tmpSFHists, lumiData=analysis.lumi,
debugLevel=debugLevel, var=v+'_NoZ', printdir=outdir)
histName = region+v+'ScaleFactors'
tmpSFHists['DYJetsInv'].SetName(histName)
if not args.noSave:
print "Writing histogram",tmpSFHists["DYJetsInv"].GetName(),"to file"
outfile.cd()
tmpSFHists["DYJetsInv"].Write(histName)
#in the first pass, update the normalization of the G+jets scale factor histogram
if updateNorm:
dataNorm = hists["Data"]["1"].GetBinContent(1)
def makeSMSTemplates(box, inFile, uncertainties=[], debugLevel=0,
tag="Razor2016_MoriondRereco", opts=None, boostCuts=True,
doUncorrelate=True):
"""Returns a dictionary of histograms representing predicted
yields for the indicated signal sample.
'opts' should be an SMSOpts instance containing desired
values for configurable parameters."""
print '\nInput file is %s' % inFile
uncerts = copy.copy(uncertainties)
# process configuration options
if opts is None:
opts = SMSOpts()
xBR = opts.xBR
yBR = opts.yBR
doMCStat = True
if opts.doNPVExtrap:
uncerts.append('npvextrap')
doMCStat = False
if opts.doGenMetVsPFMet:
uncerts.append('genmetvspfmet')
# get mass point information
model, m1, m2 = getModelInfoFromFilename(inFile, xBR, yBR)
isGluinos = ("T1" in model or "T5" in model)
if isGluinos:
thyXsec, _ = getTheoryCrossSectionAndError(
mGluino=m1)
else:
thyXsec, _ = getTheoryCrossSectionAndError(
mStop=m1)
print "\n--- %s %s %s ---\n"%(model, m1, m2)
print "Theory cross section: %.3f pb"%thyXsec
minBtags = 0
maxBtags = getMaxBtags(box)
# special case: 1L control regions
if box == "TTJetsSingleLeptonForSignal":
minBtags = maxBtags = 1
elif box == "WJetsSingleLeptonForSignal":
minBtags = maxBtags = 0
hists = []
unrollBins = []
for nb in range(minBtags, maxBtags+1):
# get analysis info
nbMax = nb
if nb == maxBtags:
nbMax = -1
# special case: 1L control regions
if box == "WJetsSingleLeptonForSignal":
nbMax = 0
analysis = Analysis(box, tag, nbMin=nb, nbMax=nbMax,
boostCuts=boostCuts)
unrollBins.append(analysis.unrollBins)
# modify for signal sample
analysis.filenames = { 'Signal':inFile }
analysis.samples = ['Signal']
analysis.samplesReduced = analysis.samples
# scale according to cross section
f = rt.TFile.Open(inFile)
nEvents = f.Get('NEvents').Integral()
globalScaleFactor = thyXsec/nEvents
nisrFactor = getGlobalNISRScaleFactor(f)
globalScaleFactor *= nisrFactor
print "Number of events: %d"%nEvents
print "Integrated luminosity: %d /pb"%analysis.lumi
print "Overall NISR scale factor: {}".format(nisrFactor)
print "Overall scale factor: %.3f"%(
analysis.lumi * globalScaleFactor)
# fill the histograms
hists.append(makeControlSampleHistsForAnalysis(analysis,
treeName="RazorInclusive", shapeErrors=uncerts,
boxName=box, btags=nb, makePlots=False,
exportShapeErrs=True, propagateScaleFactorErrs=False,
lumiMC=1./globalScaleFactor, debugLevel=debugLevel))
makeRazor2DTable(pred=None,
boxName='{}-{}-{}-{}-'.format(box, model, m1, m2),
mcNames=['{} {} {}'.format(model, m1, m2)],
mcHists=[hists[-1]['Signal'][('MR','Rsq')]],
btags=nb, unrollBins=unrollBins[-1], listAllMC=True)
signalHists = unrollAndStitch(hists, box, samples=analysis.samples,
debugLevel=debugLevel, unrollBins=unrollBins,
addStatUnc=doMCStat)
# apply pileup weight extrapolation procedure
if 'Signal_npvextrapUp' in signalHists:
npvLowHighHist = getNPVLowHighHist(analysis)
npvHist = getNPVHist(tag)
doNPVExtrapolation(signalHists, npvHist, npvLowHighHist,
scale=analysis.lumi*globalScaleFactor)
# need this extrapolation to be uncorrelated across bins & boxes
for sysName in ['Signal_npvextrapUp', 'Signal_npvextrapDown']:
signalHists[sysName.replace(
'npvextrap','npvextrap'+box)] = signalHists[sysName]
del signalHists[sysName]
if doUncorrelate:
uncorrelate(signalHists, 'npvextrap'+box, suppressLevel=0.1)
# apply gen-MET vs PF MET systematic
if 'Signal_genmetvspfmetUp' in signalHists:
doGenMetVsPFMetSystematic(signalHists)
return signalHists
if region == "WJetsInvForNJets":
auxSFs["WJetsInv"] = {}
if region == "GJetsInvForNJets":
dataDrivenQCD = True
razorWeights.getPhotonPuritySFs(auxSFs)
razorWeights.loadPhotonPurityHists(sfHists, tag, debugLevel)
else:
dataDrivenQCD = False
if args.tightCuts:
if (region == "GJetsInvForNJets" or region == "WJetsInvForNJets"):
continue
analysis.cutsData += " && MR > 500 && Rsq > 0.25 && NJets80 >= 2"
analysis.cutsMC += " && MR > 500 && Rsq > 0.25 && NJets80 >= 2"
#perform analysis
hists = makeControlSampleHistsForAnalysis( analysis, plotOpts=plotOpts,
sfHists=sfHists, sfVars=sfVarsToUse,
printdir=outdir, auxSFs=auxSFs, noFill=args.noFill,
dataDrivenQCD=dataDrivenQCD, debugLevel=debugLevel )
#compute scale factors
sfHistsCopy = sfHists.copy()
appendScaleFactors( process, hists, sfHistsCopy, lumiData=analysis.lumi,
debugLevel=debugLevel, var=njetsName, printdir=outdir )
if region == "TTJetsForNJets":
sfHists["NJetsTTJets"] = sfHistsCopy["TTJets"]
tmpTTJets = sfHists["NJetsTTJets"].Clone()
elif region == "WJetsForNJets":
sfHists["NJetsWJets"] = sfHistsCopy["WJets"]
if not args.noSave:
#export histograms
macro.exportHists( hists, outFileName='controlHistograms'+region+'.root',
outDir=outdir, debugLevel=debugLevel )
#write out scale factors
sfHists['NJetsTTJets'] = sfNJetsFile.Get("TTJetsScaleFactors")
sfHists['NJetsWJets'] = sfNJetsFile.Get("WJetsScaleFactors")
for region in regionsOrder:
print "\nRegion:", region, "\n"
outdir = 'Plots/' + tag + '/' + region
os.system('mkdir -p ' + outdir)
analysis = regions[region]
auxSFs = razorWeights.getNJetsSFs(analysis)
auxSFs = razorWeights.addBTagSFs(analysis, auxSFs)
adjustForRegion(analysis, sfHists, auxSFs)
hists = makeControlSampleHistsForAnalysis(analysis,
plotOpts=plotOpts,
sfHists=sfHists,
sfVars=sfVars,
printdir=outdir,
auxSFs=auxSFs,
btags=analysis.nbMin,
debugLevel=debugLevel,
noFill=args.noFill)
sfHistName = getSFHistName(analysis)
sfProcs = ['TTJets', 'WJets']
sfHistsTmp = sfHists.copy()
if 'MRCorr' in region:
sfHistName = sfHistName.replace('MR', 'Rsq')
appendScaleFactors(sfProcs,
hists,
sfHistsTmp,
lumiData=analysis.lumi,
var="Rsq",
if args.noSys:
shapesToUse = []
if args.noSFs:
print "Ignoring all Data/MC scale factors"
sfHistsToUse = {}
auxSFsToUse = {}
shapesToUse = removeSFShapes(shapesToUse)
if args.fineGrained:
(analysis, sfHistsToUse, auxSFsToUse, shapesToUse,
plotOpts) = adjustForFineGrainedMCPred(
analysis, sfHistsToUse, auxSFsToUse, shapesToUse, plotOpts)
print "\nBox:",region,"("+boxName,str(btags),"B-tag)"
#make output directory
outdir = "Plots/"+tag+"/"+region
os.system('mkdir -p '+outdir)
#run analysis
hists = makeControlSampleHistsForAnalysis(analysis,
sfHists=sfHistsToUse, treeName="RazorInclusive",
shapeErrors=shapesToUse, fitToyFiles=toysToUse, boxName=boxName,
blindBins=blindBins, btags=btags, debugLevel=debugLevel,
auxSFs=auxSFsToUse, dataDrivenQCD=dataDrivenQCD, printdir=outdir,
plotOpts=plotOpts, noFill=args.noFill, exportShapeErrs=True,
propagateScaleFactorErrs=False, makePlots=False)
if not args.noSave:
#export histograms
macro.exportHists(hists, outFileName='razorHistograms'+region+'.root',
outDir=outdir, debugLevel=debugLevel)
for region, analysis in regions.iteritems():
#make output directory
outdir = 'Plots/' + tag + '/' + region
os.system('mkdir -p ' + outdir)
#set up analysis
process = sfNames[region]
(xbins, cols) = analysis.unrollBins
sfHistsToUse = sfHists[region]
sfVarsToUse = sfVars[region]
njetsName = njetsNames[region]
dataDrivenQCD = (region == "GJetsInvForNJets")
#perform analysis
hists = makeControlSampleHistsForAnalysis(analysis,
plotOpts=plotOpts,
sfHists=sfHistsToUse,
sfVars=sfVarsToUse,
printdir=outdir,
debugLevel=debugLevel,
dataDrivenQCD=dataDrivenQCD)
#compute scale factors
appendScaleFactors(process,
hists,
sfHistsToUse,
lumiData=analysis.lumi,
debugLevel=debugLevel,
var=njetsName,
printdir=outdir)
#export histograms
macro.exportHists(hists,
outFileName='controlHistograms' + region + '.root',
outDir=outdir,
for proc in analysis.samples:
auxSFsToUse[proc][region.replace(
'PtCorr', '')] = ("leadingGenLeptonPt",
"abs(leadingGenLeptonType) == 15")
#sanity check
print "\nRegion:", region
print "Tree name:", treeName
print "Aux SFs to use:", auxSFsToUse
print "Variable for correction:", varForCorrection
print "Signal region variable for correction:", sigVarForCorrection, "\n"
#perform analysis
hists[region] = makeControlSampleHistsForAnalysis(
analysis,
plotOpts=plotOpts,
sfHists=sfHistsToUse,
sfVars=sfVars,
printdir=outdir,
auxSFs=auxSFsToUse,
treeName=treeName,
debugLevel=debugLevel)
#export histograms
macro.exportHists(hists[region],
outFileName='controlHistograms' + region + '.root',
outDir=outdir,
debugLevel=debugLevel,
delete=False)
#compute correction factors
if region.startswith('Veto'):
#make control region scale factors
sfHists[region] = makeVetoLeptonCorrectionHist(
hists[region],
for region in regionsOrder:
analysis = regions[region]
print "\nRegion:", region, "\n"
#make output directory
outdir = 'Plots/' + tag + '/' + region
os.system('mkdir -p ' + outdir)
#set up analysis
(xbins, cols) = analysis.unrollBins
auxSFs = razorWeights.getNJetsSFs(analysis, jetName=analysis.jetVar)
razorWeights.getPhotonPuritySFs(auxSFs)
#perform analysis
hists = makeControlSampleHistsForAnalysis(analysis,
plotOpts=plotOpts,
sfHists=sfHists,
sfVars=sfVars,
printdir=outdir,
auxSFs=auxSFs,
btags=analysis.nbMin,
dataDrivenQCD=True,
debugLevel=debugLevel)
#compute scale factors
appendScaleFactors(region + "MR",
hists,
sfHists,
lumiData=analysis.lumi,
var="MR_NoPho",
debugLevel=debugLevel,
signifThreshold=1.0,
printdir=outdir)
appendScaleFactors(region + "Rsq",
hists,
analysis.cutsData += " && abs(%s) < 2.8" % (dPhiVar)
analysis.cutsMC += " && abs(%s) < 2.8" % (dPhiVar)
if args.njets80Cut:
njets80Var = "NJets80"
if region == 'GJetsInv':
njets80Var += '_NoPho'
analysis.cutsData += " && %s >= 2" % (njets80Var)
analysis.cutsMC += " && %s >= 2" % (njets80Var)
analysis, plotOpts = adjustForFineGrainedMCPred(analysis,
plotOpts=plotOpts)
#perform analysis
hists = makeControlSampleHistsForAnalysis(analysis,
plotOpts=plotOpts,
sfHists=sfHists,
sfVars=sfVars,
printdir=outdir,
debugLevel=debugLevel,
auxSFs=auxSFs,
noFill=args.noFill,
dataDrivenQCD=dataDrivenQCD)
#compute scale factors
normErrFractions = getNormErrFractions()
normErrFractions['QCD'] = 0.02
appendScaleFactors(process,
hists,
sfHists,
lumiData=analysis.lumi,
th2PolyXBins=xbins,
th2PolyCols=cols,
debugLevel=debugLevel,
var=sfVars,