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TwoTagcountMethodv2.py
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TwoTagcountMethodv2.py
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import ROOT
import sys
import math
import csv
#ROOT.gROOT.ProcessLine('.L BTagCalibrationStandalone.cpp+')
#calib = ROOT.BTagCalibration("MyAlgo")
fileName=sys.argv[1]
print 'successfully opening file', fileName
tFile=ROOT.TFile.Open(fileName)
lowerPtBinEdges=[20,30,50,70,100,140,200,300,600]
def mistagrate_uncer(baseName):
tag=baseName.split("_")
var=(tag[len(tag)-2] if (baseName.find("Hi")!=-1 or baseName.find("Lo")!=-1) else tag[len(tag)-1])
wp= ("L" if var.find("L")!=-1 else ("M" if var.find("M")!=-1 else "T"))
pt=var.split(wp)
ptLabel=var.split(wp)
if var.find("Inclusive")!=-1:
x=0
elif var.find("Inf")!=-1:
pt=ptLabel[1].split("to")
x=(int(pt[0]))/2
else:
pt=ptLabel[1].split("to")
ptmin=pt[0]
ptmax=pt[1]
x=(int(ptmin)+int(ptmax))/2
if baseName.find("deepCSV")!=-1:
uncer=( (0.0559259+1.96455e-05*x+-3.60571e-08*x*x) if wp=="L" else ( (0.122811+0.000162564*x+-1.66422e-07*x*x) if wp=="M" else (0.207667+0.000165081*x+-1.45307e-07*x*x)))
else:
uncer=( (0.0631436+7.87525e-05*x+-1.10405e-07*x*x) if wp=="L" else ( (0.142253+0.000227323*x+-2.71704e-07*x*x) if wp=="M" else (0.223324+0.000231341*x+-2.34362e-07*x*x)))
return uncer
def ReturnPtLabel(iPT):
ptBinLabel=""
if(iPT==-1):
ptBinLabel="Inclusive"
else:
ptBinLabel+=str(lowerPtBinEdges[iPT])+"to"
if(iPT==len(lowerPtBinEdges)-1):
ptBinLabel+="Inf"
else:
ptBinLabel+=str(lowerPtBinEdges[iPT+1])
return ptBinLabel
def ComputeTwoTagEfficieny(basename):
for sample in samples:
histName=basename+"/"+basename+"_"+sample
print histName
hist=tFile.Get(histName)
if sample==samples[0]:
histBkg=hist.Clone("histBkg")
else:
histBkg.Add(hist)
tot={}
statError={}
tot["2bmc"]=0 # all the events in which both jets are 2b jet flav with 0 & 1 passing
tot["othermc"]=0 # 2 jets (bX,cX, ll) 1 at least is passing
tot["data"]=0 ## all data
tot["2bmc_2btag"]=0 ## number of events in which both jets are b-jets and both are passing
tot["othermc_2btag"]=0 ## 2jets (bX,CX,ll) both are btagged
tot["data_2btag"]=0 ## data where we have 2b jets flav && both passing (btagged)
for iBin in range(15):
if iBin%4==1:
tot["2bmc"]=tot["2bmc"]+histBkg.GetBinContent(iBin)
if iBin>9:
tot["2bmc_2btag"]=tot["2bmc_2btag"]+histBkg.GetBinContent(iBin)
else:
tot["othermc"]=tot["othermc"]+histBkg.GetBinContent(iBin)
if iBin>9:
tot["othermc_2btag"]=tot["othermc_2btag"]+histBkg.GetBinContent(iBin)
twoTagDataHist=basename+"/"+basename
hist=tFile.Get(twoTagDataHist)
print basename
for iBin in range(15):
print iBin,hist.GetBinContent(iBin),histBkg.GetBinContent(iBin)
tot["data"]=tot["data"]+hist.GetBinContent(iBin)
if iBin>9:
tot["data_2btag"]=tot["data_2btag"]+hist.GetBinContent(iBin)
if (histBkg.Integral()>0):
hist.Integral()/histBkg.Integral()
else:
pass
for name in tot:
if name.find("mc")!=-1:
tot[name]=tot[name]/histBkg.Integral()
else:
tot[name]=tot[name]/hist.Integral()
try:
eff=math.sqrt((tot["data_2btag"]-tot["othermc_2btag"])/(tot["2bmc"]))
effmc=math.sqrt(tot["2bmc_2btag"]/(tot["2bmc"]))
#effUp=math.sqrt((tot["data_2btag"]-tot["othermc_2btag"]*(1-mistagrate_uncer(basename)))/tot["2bmc"])
#effDown=math.sqrt((tot["data_2btag"]-tot["othermc_2btag"]*(1+mistagrate_uncer(basename)))/tot["2bmc"])
# 50 % conservative uncertainty
effUp=math.sqrt((tot["data_2btag"]-tot["othermc_2btag"]*1.5)/tot["2bmc"])
effDown=math.sqrt((tot["data_2btag"]-tot["othermc_2btag"]*0.5)/tot["2bmc"])
statError[basename.replace("emu_","")+"data_2btag"] = math.sqrt( tot["data_2btag"] * (1 - tot["data_2btag"]) / hist.Integral())
statError[basename.replace("emu_","")+"othermc_2btag"] = math.sqrt( tot["othermc_2btag"] * (1 - tot["othermc_2btag"]) / histBkg.GetEffectiveEntries())
statError[basename.replace("emu_","")+"2bmc"] = math.sqrt( tot["2bmc"] * (1 - tot["2bmc"]) / histBkg.GetEffectiveEntries())
statError[basename.replace("emu_","")+"eff"] = math.sqrt(math.pow(eff*statError[basename.replace("emu_","")+"2bmc"],2) + (math.pow(statError[basename.replace("emu_","")+"data_2btag"],2)+math.pow(statError[basename.replace("emu_","")+"othermc_2btag"],2) ) / math.pow(eff,2) )/(2*tot["2bmc"])
print [tot["2bmc_2btag"],tot["2bmc"],tot["data_2btag"],tot["othermc_2btag"],eff,effmc,eff/effmc,effUp/effmc,effDown/effmc, statError[basename.replace("emu_","")+"eff"]]
print "basename:", basename, "eff:",eff, "effmc:", effmc , "effUp:", effUp, "effDown:", effDown
return [tot["2bmc_2btag"],tot["2bmc"],tot["data_2btag"],tot["othermc_2btag"],eff,effmc,eff/effmc,effUp/effmc,effDown/effmc, statError[basename.replace("emu_","")+"eff"]]
except:
print "ERROR: ERROR in computing efficiencies from",basename
#tags=["twoTags_deepCSVL","only2_twoTags_deepCSVL","twoTags_deepCSVM","only2_twoTags_deepCSVM","twoTags_deepCSVT","only2_twoTags_deepCSVT","twoTags_deepFlavourL","only2_twoTags_deepFlavourL","twoTags_deepFlavourM","only2_twoTags_deepFlavourM","twoTags_deepFlavourT","only2_twoTags_deepFlavourT"]
tags=["only2_twoTags_deepCSVL","only2_twoTags_deepCSVM","only2_twoTags_deepCSVT","only2_twoTags_deepFlavourL","only2_twoTags_deepFlavourM","only2_twoTags_deepFlavourT"]
tags.sort()
samples=["t#bar{t} SL","t#bar{t} DL","t#bar{t} AH","ZZ","WZ","WW","tW","DY","W2Jets", "W3Jets", "W4Jets"]
systs=["","_fsrCon","_fsrDef","_fsrRed","_isrCon","_isrDef","_isrRed","_qcdScale"]
hiORlo=["Hi","Lo"]
tgraphs={}
results={}
can=ROOT.TCanvas("can","",800,800)
outputFile=ROOT.TFile("twoTagSFGraphs.root","RECREATE")
taggers=['DeepFlavour','DeepCSV']
#for tagger in taggers:
# with open('{tagger}_94XSF_Moriond19_2018DATA_syst_stat.csv'.format(tagger=tagger), mode='a') as csv_file:
# btag_params = csv.writer(csv_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
# btag_params.writerow([tagger,'OperatingPoint', 'measurementType', 'sysType', 'jetFlavor', 'etaMin','etaMax', 'ptMin','ptMax', 'discrMin','discrMax', 'SFs'])
#compute and save all the results
for syst in systs:
for tag in tags:
for ptBin in range(-1,len(lowerPtBinEdges)):
ptLabel=ReturnPtLabel(ptBin)
analysiskeys= (tag,ptLabel,syst)
print "---------------------------------------------------------------------------------------"
print "analysiskeys:" , analysiskeys
basename="emu_"+tag+ptLabel+syst
if syst=="":
results[analysiskeys]=ComputeTwoTagEfficieny(basename)
else:
print basename+"Hi"
resultsHi=ComputeTwoTagEfficieny(basename+"Hi")
resultsLo=ComputeTwoTagEfficieny(basename+"Lo")
statErrorHi=ComputeTwoTagEfficieny(basename+"Hi")
statErrorLo=ComputeTwoTagEfficieny(basename+"Lo")
#I just set the numbers to 1 because you don't really need them for systematics unless you're debugging
#return[tot["2bmc_2btag"],tot["2bmc"],tot["data_2btag"],tot["othermc_2btag"],eff,effmc,eff/effmc,effUp/effmc,effDown/effmc]
results[analysiskeys]=[1.,1.,1.,1.,1.,1.,(resultsHi[6] if resultsHi else 1.), (resultsLo[6] if resultsLo else 1.)]
print results[analysiskeys]
#make the tgraphs for all systematics
multiG={}
multiG2={}
for index, tag in enumerate(tags):
uncertainty2Hi=[]
uncertainty2Lo=[]
otheruncertainty2Hi=[]
otheruncertainty2Lo=[]
it=0
if index==0:
tgraphs["wp"]=ROOT.TGraphAsymmErrors()
tgraphs["wp"].SetTitle(";Jet P_{T};Scale Factor")
for syst in systs:
iGraph=0
graphKey=tag+syst
tgraphs[graphKey]=ROOT.TGraphAsymmErrors()
tgraphs[graphKey].SetTitle(graphKey+";Jet P_{T};Scale Factor")
if syst==systs[0]:
tgraphs[tag+"totalError"]=ROOT.TGraphAsymmErrors()
tgraphs[tag+"othersysts"]=ROOT.TGraphAsymmErrors()
tgraphs[tag+"statError"]=ROOT.TGraphErrors()
#for ptBin in range(-1,len(lowerPtBinEdges)): -1 for Inclusive
for ptBin in range(0,len(lowerPtBinEdges)):
ptLabel=ReturnPtLabel(ptBin)
# nominal must always be run for this to work
if ptBin>-1:
pt1=lowerPtBinEdges[ptBin]
pt2=1000
if pt1!=lowerPtBinEdges[-1]:
pt2=lowerPtBinEdges[ptBin+1]
try:
nominalSF=results[(tag,ptLabel,"")][6]
nominalSFUp=results[(tag,ptLabel,"")][7]
nominalSFDown=results[(tag,ptLabel,"")][8]
statError=results[(tag,ptLabel,"")][9]
if syst=="":
tgraphs[tag+"othersysts"].SetPoint(iGraph,(pt1+pt2)/2.,nominalSF)
tgraphs[tag+"othersysts"].SetPointEXhigh(iGraph,(-pt1+pt2)/2.)
tgraphs[tag+"othersysts"].SetPointEXlow(iGraph,(-pt1+pt2)/2.)
tgraphs[tag+"statError"].SetPoint(iGraph,(pt1+pt2)/2, nominalSF)
tgraphs[tag+"statError"].SetPointError(iGraph,(pt2-pt1)/2, statError)
uncertainty2Hi.append(math.pow(nominalSFUp-nominalSF,2))
uncertainty2Lo.append(math.pow(-nominalSFDown+nominalSF,2))
otheruncertainty2Hi.append(0)
otheruncertainty2Lo.append(0)
tgraphs[graphKey].SetPoint(iGraph,(pt1+pt2)/2.,nominalSF)
tgraphs[graphKey].SetPointEXhigh(iGraph, (-pt1+pt2)/2.)
tgraphs[graphKey].SetPointEXlow( iGraph, (pt2-pt1)/2.)
tgraphs[graphKey].SetPointEYhigh(iGraph, nominalSFUp-nominalSF)
tgraphs[graphKey].SetPointEYlow( iGraph, -nominalSFDown+nominalSF)
tgraphs["wp"].SetPoint(it,(pt1+pt2)/2.,nominalSF)
tgraphs["wp"].SetPointEXhigh(it, (-pt1+pt2)/2.)
tgraphs["wp"].SetPointEXlow( it, (pt2-pt1)/2.)
tgraphs["wp"].SetPointEYhigh(it, nominalSFUp-nominalSF)
tgraphs["wp"].SetPointEYlow( it, -nominalSFDown+nominalSF)
print "--------------------------------------------------------------------------"
print ("Nominal:{0}".format(nominalSF))
print ("Up :{0}".format(nominalSFUp))
print ("Down :{0}".format(nominalSFDown))
iGraph=iGraph+1
if index>=3:
it=it+1
wp= (0 if tag.find("L")==len(tag)-1 else (1 if tag.find("M")==len(tag)-1 else 2))
meas="twotag"
var="Central"
flav=0
etaMin=-2.4
etaMax=2.4
ptMin=(ptLabel.split("to"))[0]
ptMax=(ptLabel.split("to"))[1]
if ptMax==str("Inf"):
ptMax=ptMax.replace(str("Inf"),str(1000))
discrMin=0
discrMax=1
SFs=nominalSF
if index >= 3:
tagger="DeepFlavour"
else:
tagger="DeepCSV"
with open('{tagger}_94XSF_Moriond19_2018DATA_syst_stat.csv'.format(tagger=tagger), mode='a') as csv_file:
btag_params = csv.writer(csv_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
btag_params.writerow([wp, meas, var, flav, etaMin, etaMax, ptMin,ptMax ,discrMin,discrMax, SFs])
else:
systHiSF=results[(tag,ptLabel,syst)][6]
systLoSF=results[(tag,ptLabel,syst)][7]
tgraphs[tag+"totalError"].SetPoint(iGraph,(pt1+pt2)/2.,nominalSF)
tgraphs[tag+"totalError"].SetPointEXhigh(iGraph,(-pt1+pt2)/2.)
tgraphs[tag+"totalError"].SetPointEXlow(iGraph,(-pt1+pt2)/2.)
if (systHiSF-systLoSF >0.):
tgraphs[graphKey].SetPointEYhigh(iGraph,systHiSF-nominalSF)
tgraphs[graphKey].SetPointEYlow( iGraph,-systLoSF+nominalSF)
uncertainty2Hi[ptBin] += math.pow(systHiSF-nominalSF,2)
uncertainty2Lo[ptBin] += math.pow(-systLoSF+nominalSF,2)
otheruncertainty2Hi[ptBin] += math.pow(systHiSF-nominalSF,2)
otheruncertainty2Lo[ptBin] += math.pow(-systLoSF+nominalSF,2)
else:
tgraphs[graphKey].SetPointEYlow( iGraph,-systHiSF+nominalSF)
tgraphs[graphKey].SetPointEYhigh(iGraph,systLoSF-nominalSF)
uncertainty2Hi[ptBin] += math.pow(-systHiSF+nominalSF,2)
uncertainty2Lo[ptBin] += math.pow(systLoSF-nominalSF,2)
otheruncertainty2Hi[ptBin] += math.pow(-systHiSF+nominalSF,2)
otheruncertainty2Lo[ptBin] += math.pow(systLoSF-nominalSF,2)
tgraphs[graphKey].SetPoint(iGraph,(pt1+pt2)/2.,nominalSF)
tgraphs[graphKey].SetPointEXhigh(iGraph,(-pt1+pt2)/2.)
tgraphs[graphKey].SetPointEXlow(iGraph,(pt2-pt1)/2.)
iGraph=iGraph+1
print "-------------------------------------------------------------------------------"
print("High : {0}".format(systHiSF))
print("Low : {0}".format(systLoSF))
print("High syst -Nominal:{0}".format(systHiSF-nominalSF))
print("Nominal- Low syst :{0}".format(-systLoSF+nominalSF))
if math.copysign(1,systHiSF-nominalSF) != math.copysign(1,nominalSF-systLoSF):
print "Hi and Lo vary from nominal in the same direction",graphKey,"hi, nom, lo",systHiSF,nominalSF,systLoSF
except:
print "skip plotting the default value SF=1 ! "
tgraphs[graphKey].SetName(graphKey)
tgraphs[graphKey].Draw("APE")
can.Update()
can.SaveAs(graphKey+".png")
outputFile.cd()
tgraphs[graphKey].Write()
tgraphs["wp"].SetName("wp")
tgraphs["wp"].Draw("AP")
can.Update()
can.SaveAs("wp"+".png")
outputFile.cd()
tgraphs["wp"].Write()
try:
allSF=tgraphs[tag+"totalError"].GetY()
for iGraph in range(0,len(lowerPtBinEdges)):
tgraphs[tag+"totalError"].SetPointEYhigh(iGraph, math.sqrt(uncertainty2Hi[iGraph]))
tgraphs[tag+"totalError"].SetPointEYlow(iGraph, math.sqrt(uncertainty2Lo[iGraph]))
wp= (0 if tag.find("L")==len(tag)-1 else (1 if tag.find("M")==len(tag)-1 else 2))
meas="twotag"
SFsUp=allSF[iGraph]+ math.sqrt(uncertainty2Hi[iGraph])
SFsDown=allSF[iGraph]-math.sqrt(uncertainty2Lo[iGraph])
flav=0
etaMin=-2.4
etaMax=2.4
ptLabel=ReturnPtLabel(iGraph)
ptMin=(ptLabel.split("to"))[0]
ptMax=(ptLabel.split("to"))[1]
if ptMax==str("Inf"):
ptMax=ptMax.replace(str("Inf"),str(1000))
discrMin=0
discrMax=1
if index >= 3:
tagger="DeepFlavour"
else:
tagger="DeepCSV"
with open('{tagger}_94XSF_Moriond19_2018DATA_syst_stat.csv'.format(tagger=tagger), mode='a') as csv_file:
btag_params = csv.writer(csv_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
btag_params.writerow([wp, meas, "Up", flav, etaMin, etaMax, ptMin,ptMax ,discrMin,discrMax, SFsUp])
btag_params.writerow([wp, meas, "Down", flav, etaMin, etaMax, ptMin,ptMax ,discrMin,discrMax, SFsDown])
otherSF=tgraphs[tag+"othersysts"].GetY()
for iGraph in range(0,len(lowerPtBinEdges)):
tgraphs[tag+"othersysts"].SetPointEYhigh(iGraph, math.sqrt(otheruncertainty2Hi[iGraph]))
tgraphs[tag+"othersysts"].SetPointEYlow(iGraph, math.sqrt(otheruncertainty2Lo[iGraph]))
wp= (0 if tag.find("L")==len(tag)-1 else (1 if tag.find("M")==len(tag)-1 else 2))
meas="twotag"
SFsUp=otherSF[iGraph]+ math.sqrt(otheruncertainty2Hi[iGraph])
SFsDown=otherSF[iGraph]-math.sqrt(otheruncertainty2Lo[iGraph])
flav=0
etaMin=-2.4
etaMax=2.4
ptLabel=ReturnPtLabel(iGraph)
ptMin=(ptLabel.split("to"))[0]
ptMax=(ptLabel.split("to"))[1]
if ptMax==str("Inf"):
ptMax=ptMax.replace(str("Inf"),str(1000))
discrMin=0
discrMax=1
if index >= 3:
tagger="DeepFlavour"
else:
tagger="DeepCSV"
with open('{tagger}_94XSF_Moriond19_2018DATA_othersyst.csv'.format(tagger=tagger), mode='a') as csv_file:
csv_file.truncate()
btag_params = csv.writer(csv_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
btag_params.writerow([wp, meas, "Up", flav, etaMin, etaMax, ptMin,ptMax ,discrMin,discrMax, SFsUp])
btag_params.writerow([wp, meas, "Down", flav, etaMin, etaMax, ptMin,ptMax ,discrMin,discrMax, SFsDown])
except:
print ' ** Warning ***** unable to dump data in {tagger}_94XSF_Moriond19_2018DATA_othersyst.csv'.format(tagger=tagger)
# save the statError , othersystematics and totalError once per tag
tgraphs[tag+"statError"].SetName(tag+"statError")
tgraphs[tag+"statError"].Draw("APE")
tgraphs[tag+"statError"].GetXaxis().SetTitle( 'pT(GeV)' )
tgraphs[tag+"statError"].GetYaxis().SetTitle( 'Scale Factor' )
tgraphs[tag+"statError"].GetYaxis().SetLimits( 0,7)
can.Update()
can.SaveAs(tag+"_statError"+".png")
outputFile.cd()
tgraphs[tag+"statError"].Write()
tgraphs[tag+"totalError"].SetName(tag+"totalError")
tgraphs[tag+"totalError"].Draw("APE")
tgraphs[tag+"totalError"].GetXaxis().SetTitle( 'pT(GeV)' )
tgraphs[tag+"totalError"].GetYaxis().SetTitle( 'Scale Factor' )
tgraphs[tag+"totalError"].GetYaxis().SetLimits( 0,7)
can.Update()
can.SaveAs(tag+"_totalError"+".png")
outputFile.cd()
tgraphs[tag+"totalError"].Write()
tgraphs[tag+"othersysts"].SetName(tag+"othersysts")
tgraphs[tag+"othersysts"].Draw("APE")
tgraphs[tag+"othersysts"].GetXaxis().SetTitle( 'pT(GeV)' )
tgraphs[tag+"othersysts"].GetYaxis().SetTitle( 'Scale Factor' )
tgraphs[tag+"othersysts"].GetYaxis().SetLimits( 0,7)
can.Update()
can.SaveAs(tag+"_othersysts"+".png")
outputFile.cd()
tgraphs[tag+"othersysts"].Write()
#tgraphs[tag+"totalError"].SetFillColor(6)
#tgraphs[tag+"totalError"].SetFillStyle(3005)
# set Marker style
tgraphs[tag+"totalError"].SetMarkerStyle(21)
tgraphs[tag+"othersysts"].SetMarkerStyle(22)
tgraphs[tag].SetMarkerStyle(23)
tgraphs[tag+"statError"].SetMarkerStyle(24)
# set the line color
tgraphs[tag+"totalError"].SetLineColor(1)
tgraphs[tag+"othersysts"].SetLineColor(633)
tgraphs[tag].SetLineColor(417)
tgraphs[tag+"statError"].SetLineColor(601)
# set the line width
tgraphs[tag+"totalError"].SetLineWidth(5)
tgraphs[tag+"othersysts"].SetLineWidth(3)
tgraphs[tag].SetLineWidth(2)
tgraphs[tag+"statError"].SetLineWidth(1)
multiG[tag]=ROOT.TMultiGraph()
multiG[tag].SetMaximum(10)
multiG[tag].SetMinimum(0)
multiG[tag].Add(tgraphs[tag+"totalError"],"pe")
multiG[tag].Add(tgraphs[tag+"othersysts"],"pe")
multiG[tag].Add(tgraphs[tag+""] ,"pe")
multiG[tag].Add(tgraphs[tag+"statError"] ,"pe")
if tag==tags[0]:
leg=ROOT.TLegend(0.5,0.7,0.9,0.9)
leg.AddEntry(tgraphs[tag+"totalError"],"Total unc.","l" )
leg.AddEntry(tgraphs[tag+"othersysts"],"systs:isr/fsr & qcdScale","l" )
leg.AddEntry(tgraphs[tag+""] ,"Non-bb bkg sub","l" )
leg.AddEntry(tgraphs[tag+"statError"] ,"Statistics","l" )
multiG[tag].Draw("a4")
leg.Draw("same")
#multiG[tag].GetYaxis().SetLimits( 0, 7)
#multiG[tag].GetXaxis().SetTitle( 'pT(GeV)' )
#multiG[tag].GetYaxis().SetTitle( 'Scale Factor' )
can.Update()
can.SaveAs(tag+"_summary"+".png")
outputFile.cd()
outputFile.Close()
sortedResults=results.keys()
sortedResults.sort()
for result in sortedResults:
if result[2]!="":
print result[0]+result[1]+result[2]+"Hi", ":",results[result][6] , "//", result[0]+result[1]+result[2]+"Lo", ":",results[result][7]