sfFilename="data/ScaleFactors/RazorMADD2015/RazorScaleFactors_%s_Uncorr.root"%(tag),
processNames=regions.itervalues().next().samples, debugLevel=debugLevel)
sfVars = ("MR_NoPho","Rsq_NoPho")
sfNJetsFile = rt.TFile.Open(
"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
err = sfHists["DYJetsInv"].GetBinError(bn)
sysErr = sfHists["DYJetsInv"].GetBinContent(bn) - downHist.GetBinContent(bn)
newErr = ( err*err + sysErr*sysErr )**(0.5)
sfHists["DYJetsInv"].SetBinError(bn-1, newErr) # adjust bin number by 1 to account for bug in ROOT
print "Increasing error on DYJets scale factor bin",bn,"from",err,"to",sfHists["DYJetsInv"].GetBinError(bn)
updateNorm = (not closure)
for region in regionsOrder:
analysis = regions[region]
#make output directory
outdir = 'Plots/'+tag+'/'+region
if closure:
outdir += '_Closure'
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']:
(tag))
sfHists['NJetsTTJets'] = sfNJetsFile.Get("TTJetsScaleFactors")
sfHists['NJetsWJets'] = sfNJetsFile.Get("WJetsScaleFactors")
outfile = rt.TFile(
"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,
'DYJetsInv'].replace('DYJets_', 'DYJetsPtBinned_')
if not args.noSave:
outfile = rt.TFile(
"data/ScaleFactors/RazorMADD2015/RazorDYJetsDileptonInvNLOCrossCheck_%s.root"%(tag), "RECREATE")
for region in regionsOrder:
analysis = regions[region]
outdir = 'Plots/'+tag+'/'+region
os.system('mkdir -p '+outdir)
if region in wjetsRegionNames:
jetName = 'NJets_NoW'
else:
jetName = 'NJets_NoZ'
auxSFs = razorWeights.getNJetsSFs(analysis,jetName=jetName)
if 'WJetsInv' in auxSFs:
# W+jets invisible njets SFs are not computed yet
auxSFs['WJetsInv'] = {}
sfHistsToUse = sfHists
hists = makeControlSampleHistsForAnalysis(analysis, plotOpts=plotOpts,
sfHists=sfHistsToUse, sfVars=sfVars, printdir=outdir,
auxSFs=auxSFs, debugLevel=debugLevel, noFill=args.noFill)
if region == 'WJetsSingleLeptonInvNLO':
xbins, cols = analysis.unrollBins
appendScaleFactors('WJetsInv', hists, sfHists, lumiData=analysis.lumi,
th2PolyXBins=xbins, th2PolyCols=cols, debugLevel=debugLevel,
var=sfVars['WJetsInv'], printdir=outdir)
sfHists['DYJetsInv'] = sfHists['WJetsInv']
% (tag),
processNames=regions.itervalues().next().samples,
debugLevel=debugLevel)
sfVars = ("MR", "Rsq")
sfNJetsFile = rt.TFile.Open(
"data/ScaleFactors/RazorMADD2015/RazorNJetsScaleFactors_%s.root" %
(tag))
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()
debugLevel=debugLevel)
sfVars = ("MR_NoPho", "Rsq_NoPho")
sfNJetsFile = rt.TFile.Open(
"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,
for region in regionsOrder:
analysis = regions[region]
#make output directory
outdir = 'Plots/'+tag+'/'+region
if args.tightCuts:
outdir += "_TightCuts"
os.system('mkdir -p '+outdir)
#set up analysis
process = sfNames[region]
(xbins,cols) = analysis.unrollBins
sfVarsToUse = sfVars[region]
njetsName = njetsNames[region]
#use proper set of NJets correction factors.
#do not correct WJets until WJets scale factors have been derived
auxSFs = razorWeights.getNJetsSFs(analysis,
jetName=njetsNames[region])
if region == "TTJetsForNJets" or region == "WJetsForNJets":
auxSFs["WJets"] = {}
if region == "TTJetsForNJets":
auxSFs["TTJets"] = {}
if region == "GJetsInvForNJets":
auxSFs["GJetsInv"] = {}
if region == "WJetsInvForNJets":
auxSFs["WJetsInv"] = {}
if region == "GJetsInvForNJets":
dataDrivenQCD = True
razorWeights.getPhotonPuritySFs(auxSFs)
razorWeights.loadPhotonPurityHists(sfHists, tag, debugLevel)
else:
dataDrivenQCD = False
if args.tightCuts:
def getAllAuxSFs(analysis):
auxSFs = razorWeights.getNJetsSFs(analysis, jetName='nSelectedJets')
auxSFs = razorWeights.addBTagSFs(analysis, auxSFs)
auxSFs = razorWeights.addBTagSFs(analysis, auxSFs, gjets=True)
auxSFs = razorWeights.addBTagDoubleRatioSFs(analysis, auxSFs)
return auxSFs
#modify cuts and output dir if running with ele/mu separately
if args.electrons:
analysis.cutsData += " && abs(lep1Type) == 11"
analysis.cutsMC += " && abs(lep1Type) == 11"
outdir = outdir.replace('Lepton','Electron')
if 'Tau' in region: continue
if args.muons:
analysis.cutsData += " && abs(lep1Type) == 13"
analysis.cutsMC += " && abs(lep1Type) == 13"
outdir = outdir.replace('Lepton','Muon')
if 'Tau' in region: continue
os.system('mkdir -p '+outdir)
#set up analysis
if region.startswith('Veto'):
sfHistsToUse = sfHists
auxSFsToUse = razorWeights.getNJetsSFs(analysis,jetName='NJets40')
treeName = "ControlSampleEvent"
bjetsName = 'NBJetsMedium'
else:
sfHistsToUse = sfHistsSignal
auxSFsToUse = razorWeights.getNJetsSFs(analysis,jetName='nSelectedJets')
treeName = "RazorInclusive"
bjetsName = 'nBTaggedJets'
auxSFsToUse = razorWeights.addAllBTagSFs(analysis, auxSFsToUse, bjetsName=bjetsName)
bclosure.adjustForRegionBInclusive(analysis, sfHistsToUse, auxSFsToUse)
#set up lepton pt correction
varForCorrection = "lep1.Pt()"
# The non-closure on the lepton pt distribution is taken as a
# correlated shape systematic. For lepton eta, on the other hand,
# in the absence of any systematic non-closure we take the
# uncertainty on the data/MC ratio as a systematic in each bin
#modify cuts and output dir if running with ele/mu separately
if args.electrons:
analysis.cutsData += " && abs(lep1Type) == 11"
analysis.cutsMC += " && abs(lep1Type) == 11"
outdir = outdir.replace('Lepton', 'Electron')
if 'Tau' in region: continue
if args.muons:
analysis.cutsData += " && abs(lep1Type) == 13"
analysis.cutsMC += " && abs(lep1Type) == 13"
outdir = outdir.replace('Lepton', 'Muon')
if 'Tau' in region: continue
os.system('mkdir -p ' + outdir)
#set up analysis
if region.startswith('Veto'):
sfHistsToUse = sfHists
auxSFsToUse = razorWeights.getNJetsSFs(analysis, jetName='NJets40')
treeName = "ControlSampleEvent"
else:
sfHistsToUse = sfHistsSignal
auxSFsToUse = razorWeights.getNJetsSFs(analysis,
jetName='nSelectedJets')
treeName = "RazorInclusive"
#set up lepton pt correction
varForCorrection = "lep1.Pt()"
sigVarForCorrection = "leadingGenLeptonPt"
if "PtCorr" in region:
varForCorrection = "abs(lep1.Eta())"
sigVarForCorrection = "abs(leadingGenLeptonEta)"
if region.startswith('VetoLepton'):
for proc in analysis.samples:
auxSFsToUse[proc][region.replace(
jetsOrder = ["SevenJet", "MultiJet", "DiJet"]
jetsLimit = [(7,-1),(4,6),(2,3)]
for name,jets in zip(jetsOrder, jetsLimit):
regionName = 'OneLepton'+name
regions[regionName] = razor.Analysis("SingleLepton",tag=tag,
njetsMin=jets[0], njetsMax=jets[1], boostCuts=boostCuts)
regionsOrder.append(regionName)
sfHists = macro.loadScaleFactorHists(
sfFilename="data/ScaleFactors/RazorMADD2015/RazorScaleFactors_%s.root"%(tag),
processNames=regions.itervalues().next().samples, debugLevel=debugLevel)
sfVars = ("MR","Rsq")
sfNJetsFile = rt.TFile.Open(
"data/ScaleFactors/RazorMADD2015/RazorNJetsScaleFactors_%s.root"%(tag))
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)
adjustForRegion(analysis)
hists = makeControlSampleHistsForAnalysis( analysis, plotOpts=plotOpts, sfHists=sfHists,
sfVars=sfVars, printdir=outdir, auxSFs=auxSFs,
debugLevel=debugLevel, noFill=args.noFill )
if not args.noSave:
macro.exportHists( hists, outFileName='controlHistograms'+region+'.root',
outDir=outdir, debugLevel=debugLevel )
sfHists['ZInv' + jtype + bs + 'BDown'] = macro.invertHistogram(
sfHists['ZInv' + jtype + bs + 'BUp'])
#check that everything came out correctly
for h, hist in sfHists.iteritems():
if debugLevel > 0:
print "Checking scale factor histogram:", h
assert hist
#estimate yields in signal region
for region in regionsOrder:
analysis = regions[region]
boxName = region.replace(dirSuffix, '')[:-2]
btags = int(region.replace(dirSuffix, '')[-2])
#get correct NJets scale factors
auxSFs = razorWeights.getNJetsSFs(analysis, jetName='nSelectedJets')
print "\nBox:", region, "(" + boxName, str(btags), "B-tag)"
#make output directory
outdir = "Plots/" + tag + "/" + region
os.system('mkdir -p ' + outdir)
blindBins = [(x, y) for x in range(2,
len(analysis.binning["MR"]) + 1)
for y in range(2,
len(analysis.binning["Rsq"]) + 1)]
#apply options
dataDrivenQCD = True
if args.unblind: blindBins = None
