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TWanalyzer_plotter.py
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TWanalyzer_plotter.py
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import os
import array
import glob
import math
import ROOT
import sys
from ROOT import *
from array import *
from optparse import OptionParser
gROOT.Macro("rootlogon.C")
gROOT.LoadMacro("insertlogo.C+")
parser = OptionParser()
parser.add_option('-s', '--set', metavar='F', type='string', action='store',
default = 'data',
dest = 'set',
help = 'data or QCD or ttbar')
parser.add_option('-v', '--var', metavar='F', type='string', action='store',
default = 'kinematics',
dest = 'var',
help = 'anaylzer or kinematics')
parser.add_option('-c', '--cuts', metavar='F', type='string', action='store',
default = 'default',
dest = 'cuts',
help = 'Cuts type (ie default, rate, etc)')
parser.add_option('-l', '--lumi', metavar='F', type='string', action='store',
default = '35851pb',
dest = 'lumi',
help = 'Lumi folder to look in')
parser.add_option('-x', '--pileup', metavar='F', type='string', action='store',
default = 'on',
dest = 'pileup',
help = 'If not data do pileup reweighting?')
parser.add_option('-u', '--ptreweight', metavar='F', type='string', action='store',
default = 'on',
dest = 'ptreweight',
help = 'on or off')
parser.add_option('--noExtraPtCorrection', metavar='F', action='store_false',
default=True,
dest='extraPtCorrection',
help='Call to turn off extraPtCorrection')
parser.add_option('-b', '--blinded', metavar='F', type='string', action='store',
default = 'off',
dest = 'blinded',
help = 'Hides data if on')
parser.add_option('-m', '--mcsf', metavar='F', type='string', action='store',
default = 'off',
dest = 'mcsf',
help = 'Turns QCD MC scale factor on and off')
parser.add_option('-A', '--alphabet', metavar='F', type='string', action='store',
default = 'off',
dest = 'alphabet',
help = 'on and off')
#Not used
parser.add_option('-y', '--modmass', metavar='F', type='string', action='store',
default = 'nominal',
dest = 'modmass',
help = 'nominal up or down')
parser.add_option('-p', '--bprime', metavar='F', action='store_true',
default = False,
dest = 'bprime',
help = 'True if running bprime. False if running bstar.')
parser.add_option('-C', '--printCanvas', metavar='F', type='string', action='store',
default = 'off',
dest = 'printCanvas',
help = 'on or off')
(options, args) = parser.parse_args()
if options.printCanvas == 'off':
ROOT.gROOT.SetBatch(True)
ROOT.PyConfig.IgnoreCommandLineOptions = True
cuts = options.cuts
import Bstar_Functions_local
from Bstar_Functions_local import *
#Consts = LoadConstants()
#lumi = Consts['lumi']
#Lumi = str(int(lumi/1000))+'fb'
Lumi = options.lumi
pie = TMath.Pi()
kinVar = ['Mtw', 'EtaTop', 'EtaW', 'PtTop', 'PtW', 'PtTopW', 'PhiTop', 'PhiW', 'dPhi', 'Mt']
kinBkg = ['', 'ET', 'EW', 'PT', 'PW', 'PTW', 'PhT', 'PhW', 'dPhi', 'Mt']
kinBin = [140, 12, 12, 50, 50, 35, 12, 12, 12, 25 ]
kinLow = [500, -2.4, -2.4, 450, 370, 0, -pie, -pie, 2.2, 105 ]
kinHigh= [4000, 2.4, 2.4, 1500, 1430, 700, pie, pie, pie, 210 ]
rebin = [4, 1, 1, 2, 2, 1, 1, 1, 1, 1 ]
st1_label= [";M_{tw} (GeV);Counts", ";Eta_{t} (rad);Counts", ";Eta_{W} (rad);Counts", ";top p_{T} (GeV);Counts", ";W p_{T} (GeV);Counts", ";tW pair p_{T} (GeV);Counts", ";Phi_{t} (rad)", ";Phi_{W} (rad);Counts", ";Delta Phi (rad);Counts", ";M_{t} (Gev);Counts"]
pull_label= [";M_{tw} (GeV);(Data-Bkg)/#sigma", ";Eta_{t} (rad);(Data-Bkg)/#sigma", ";Eta_{W} (rad);(Data-Bkg)/#sigma", ";top p_{T} (GeV);(Data-Bkg)/#sigma", ";W p_{T} (GeV);(Data-Bkg)/#sigma", ";tW pair p_{T} (GeV);(Data-Bkg)/#sigma", ";Phi_{t} (rad)", ";Phi_{W} (rad);(Data-Bkg)/#sigma", ";Delta Phi (rad);(Data-Bkg)/#sigma", ";M_{t} (GeV);(Data-Bkg)/#sigma"]
if options.var == 'analyzer':
iterations = 1
kin = ''
elif options.var == 'kinematics':
iterations = len(kinVar)
kin = ''
else:
print "Error in var option"
quit()
alphaString = ''
if options.alphabet == 'on':
alphaString = 'alphabet_on'
pustr = 'none'
if options.pileup == 'off':
pustr = 'pileup_unweighted'
ptString = ''
if options.ptreweight == 'off':
ptString = '_ptreweight_off'
elif not options.extraPtCorrection:
ptString = '_noExtraPtCorrection'
mmstr = ""
if options.modmass!="nominal":
print "using modm uncertainty"
mmstr = "_modm_"+options.modmass
if options.blinded == 'on':
sBlind = '_blinded'
else:
sBlind = ''
if options.cuts == 'default' and options.var == 'analyzer':
mod = ['none','none_pileup_up','none_pileup_down','JES_up','JES_down','JER_up','JER_down','JMS_up','JMS_down','JMR_up','JMR_down','none_pdf_up','none_pdf_down']
subtractPDF = -2
else:
mod = ['none']
subtractPDF = 0
#string lists for naming
SR1200sList = []
SR2800sList = []
SR2000sList = []
TTmcsList = []
for m in mod:
SR1200sList.append("rootfiles/"+Lumi+"/TWanalyzerweightedsignalRH1200_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root")
SR2800sList.append("rootfiles/"+Lumi+"/TWanalyzerweightedsignalRH2800_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root")
SR2000sList.append("rootfiles/"+Lumi+"/TWanalyzerweightedsignalRH2000_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root")
#BPB1200sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeBToTW1200_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
#BPB1400sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeBToTW1400_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
#BPB1600sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeBToTW1600_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
#BPB1800sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeBToTW1800_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
#BPT1200sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeTToTW1200_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
#BPT1400sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeTToTW1400_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
#BPT1600sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeTToTW1600_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
#BPT1800sList.append("rootfiles/"+Lumi+"/TWanalyzerBprimeTToTW1800_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+"weighted.root")
if m == 'none':
TTmcsList.append("rootfiles/"+Lumi+"/TWanalyzer"+"weightedttbar_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+ptString+kin+alphaString+".root")
else:
TTmcsList.append("rootfiles/"+Lumi+"/TWanalyzer"+"weightedttbar_Trigger_nominal_"+m+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root")
#Make root file lists by pulling from string lists
# Subtract 2 from signals because we don't want full PDF uncertainties
SR1200fList = []
for i in range(len(SR1200sList)-subtractPDF):
# print SR1200sList[i]
SR1200fList.append(ROOT.TFile(SR1200sList[i]))
SR2800fList = []
for i in range(len(SR2800sList)-subtractPDF):
SR2800fList.append(ROOT.TFile(SR2800sList[i]))
SR2000fList = []
for i in range(len(SR2000sList)-subtractPDF):
SR2000fList.append(ROOT.TFile(SR2000sList[i]))
TTmcfList = []
for i in range(len(TTmcsList)):
TTmcfList.append(ROOT.TFile(TTmcsList[i]))
#Have to also put the two extra ttbar files in TTmcfList
if options.cuts == 'default' and options.var == 'analyzer':
TTmcfList.append(ROOT.TFile("rootfiles/"+Lumi+"/TWanalyzer"+"weightedttbarscaleup_Trigger_nominal_"+pustr+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root"))
TTmcfList.append(ROOT.TFile("rootfiles/"+Lumi+"/TWanalyzer"+"weightedttbarscaledown_Trigger_nominal_"+pustr+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root"))
Data = ROOT.TFile("rootfiles/"+Lumi+"/TWanalyzer"+options.set+"_Trigger_nominal_"+pustr+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root")
print "rootfiles/"+Lumi+"/TWanalyzer"+options.set+"_Trigger_nominal_"+pustr+mmstr+"_PSET_"+options.cuts+kin+alphaString+".root"
DataMmup = ROOT.TFile("rootfiles/"+Lumi+"/TWanalyzer"+options.set+"_Trigger_nominal_"+pustr+"_modm_up_PSET_"+options.cuts+kin+alphaString+".root")
DataMmdown = ROOT.TFile("rootfiles/"+Lumi+"/TWanalyzer"+options.set+"_Trigger_nominal_"+pustr+"_modm_down_PSET_"+options.cuts+kin+alphaString+".root")
print "Root file opened"
#---------For ttbar closure test, using MtStack-----------------------------------
# Outdated
# st2 = ROOT.THStack('st2','st2')
# MtStackData = Data.Get('Mt')
# MtStackBE = Data.Get('QCDbkgMt')
# MtStackTTmc = TTmcfList[0].Get('Mt')
# MtStackTTmcBE = TTmcfList[0].Get('QCDbkgMt')
# MtStackData.Rebin(1)
# MtStackBE.Rebin(1)
# MtStackTTmc.Rebin(1)
# MtStackTTmcBE.Rebin(1)
# cMtStack = TCanvas('MtStack', 'Top mass with Full selection', 700, 700)
# legend = TLegend(0.7, 0.7, 0.93, 0.9)
# cMtStack.SetLeftMargin(0.16)
# cMtStack.SetRightMargin(0.05)
# cMtStack.SetTopMargin(0.13)
# cMtStack.SetBottomMargin(0.15)
# MtStackBE.Add(MtStackTTmcBE,-1)
# MtStackBE.SetFillColor(kYellow)
# MtStackTTmc.SetFillColor(kRed)
# st2.Add(MtStackBE)
# st2.Add(MtStackTTmc)
# legend.AddEntry( MtStackData, 'Data', 'P')
# legend.AddEntry( MtStackBE, 'QCD background prediction', 'F')
# legend.AddEntry( MtStackTTmc, 't#bar{t} MC prediction', 'F')
# st2.SetMaximum(MtStackData.GetMaximum() * 1.3)
# st2.SetMinimum(0.1)
# st2.SetTitle(";M_{t} (GeV);Counts")
# st2.Draw("hist")
# MtStackData.SetMaximum(MtStackData.GetMaximum() * 1.3)
# MtStackData.Draw("same")
# cMtStack.cd()
# legend.Draw()
# cMtStack.Print('rootfiles/'+Lumi+'/MtStack_'+Lumi+'_'+options.set+'_'+options.cuts+'.root')
# cMtStack.Print('rootfiles/'+Lumi+'/MtStack_'+Lumi+'_'+options.set+'_'+options.cuts+'.pdf')
# cMtStack.Print('rootfiles/'+Lumi+'/MtStack_'+Lumi+'_'+options.set+'_'+options.cuts+'.png')
#------------------Resume---------------------------------------------------------
for i in range(0, iterations):
print "kinVar = " + "'" + kinVar[i] + "'"
print "kinBkg = " + "'" + kinBkg[i] + "'"
st1 = ROOT.THStack('st1', 'st1')
if i == 0:
leg = TLegend(0.6, 0.55, 0.93, 0.9)
else:
leg = TLegend(0.0, 0.0, 1.0, 1.0)
leg.SetNColumns(1)
leg.SetFillColor(0)
leg.SetBorderSize(0)
#bins=[500,550,600,650,700,750,800,850,900,950,1000,1050,1100,1200,1300,1400,1500,1700,1900,2300,2700,3100]
#bins.append(3000)
#bins2=array('d',bins)
Mult = 1.0
#Kfac=1.2
DataFS = Data.Get(kinVar[i])
DataBE = Data.Get("QCDbkg" + kinBkg[i])
if options.alphabet == 'off':
DataBE2d = Data.Get("QCDbkg" + kinBkg[i]+"2D")
DataBEMmup = DataMmup.Get("QCDbkg" + kinBkg[i])
DataBEMmdown = DataMmdown.Get("QCDbkg" + kinBkg[i])
DataBE2dup = Data.Get("QCDbkg" + kinBkg[i]+"2Dup")
DataBE2ddown = Data.Get("QCDbkg" + kinBkg[i]+"2Ddown")
#Selections in order (Selection, PUup, PUdown, JESup, JESdown, JERup, JERdown, Wup, Wdown, trigup, trig down)
SR1200FS = []
for j in range(len(SR1200fList)):
SR1200FS.append(SR1200fList[j].Get(kinVar[i]))
SR2800FS = []
for j in range(len(SR2800fList)):
SR2800FS.append(SR2800fList[j].Get(kinVar[i]))
SR2000FS = []
for j in range(len(SR2000fList)):
SR2000FS.append(SR2000fList[j].Get(kinVar[i]))
#BPT1200FS = []
#for j in range(len(BPT1200fList)):
# BPT1200FS.append(BPT1200fList[j].Get(kinVar[i]))
#BPT1400FS = []
#for j in range(len(BPT1400fList)):
# BPT1400FS.append(BPT1400fList[j].Get(kinVar[i]))
#BPT1600FS = []
#for j in range(len(BPT1600fList)):
# BPT1600FS.append(BPT1600fList[j].Get(kinVar[i]))
#BPT1800FS = []
#for j in range(len(BPT1800fList)):
# BPT1800FS.append(BPT1800fList[j].Get(kinVar[i]))
if options.var == 'analyzer':
# Need to calculate the PDF shape uncertainty and then append it
SR1200fPDFup = TFile(SR1200sList[-2])
SR1200fPDFdown = TFile(SR1200sList[-1])
SR1200PDFup, SR1200PDFdown = PDFShapeUncert(SR1200fList[0].Get('Mtw'),SR1200fPDFup.Get('Mtw'),SR1200fPDFdown.Get('Mtw'))
SR1200FS.append(SR1200PDFup)
SR1200FS.append(SR1200PDFdown)
#[0] index is your regular full selection
SR1200trigup = SR1200fList[0].Get("Mtwtrigup")
SR1200trigdown = SR1200fList[0].Get("Mtwtrigdown")
SR1200Wup = SR1200fList[0].Get("MtwWup")
SR1200Wdown = SR1200fList[0].Get("MtwWdown")
SR1200ExtrapUp = SR1200fList[0].Get("MtwExtrapUp")
SR1200ExtrapDown = SR1200fList[0].Get("MtwExtrapDown")
SR1200FS.append(SR1200trigup)
SR1200FS.append(SR1200trigdown)
SR1200FS.append(SR1200Wup)
SR1200FS.append(SR1200Wdown)
SR1200FS.append(SR1200ExtrapUp)
SR1200FS.append(SR1200ExtrapDown)
# Need to calculate the PDF shape uncertainty and then append it
SR2800fPDFup = TFile(SR2800sList[-2])
SR2800fPDFdown = TFile(SR2800sList[-1])
SR2800PDFup, SR2800PDFdown = PDFShapeUncert(SR2800fList[0].Get('Mtw'),SR2800fPDFup.Get('Mtw'),SR2800fPDFdown.Get('Mtw'))
SR2800FS.append(SR2800PDFup)
SR2800FS.append(SR2800PDFdown)
#[0] index is your regular full selection
SR2800trigup = SR2800fList[0].Get("Mtwtrigup")
SR2800trigdown = SR2800fList[0].Get("Mtwtrigdown")
SR2800Wup = SR2800fList[0].Get("MtwWup")
SR2800Wdown = SR2800fList[0].Get("MtwWdown")
SR2800ExtrapUp = SR2800fList[0].Get("MtwExtrapUp")
SR2800ExtrapDown = SR2800fList[0].Get("MtwExtrapDown")
SR2800FS.append(SR2800trigup)
SR2800FS.append(SR2800trigdown)
SR2800FS.append(SR2800Wup)
SR2800FS.append(SR2800Wdown)
SR2800FS.append(SR2800ExtrapUp)
SR2800FS.append(SR2800ExtrapDown)
# Need to calculate the PDF shape uncertainty and then append it
SR2000fPDFup = TFile(SR2000sList[-2])
SR2000fPDFdown = TFile(SR2000sList[-1])
SR2000PDFup, SR2000PDFdown = PDFShapeUncert(SR2000fList[0].Get('Mtw'),SR2000fPDFup.Get('Mtw'),SR2000fPDFdown.Get('Mtw'))
SR2000FS.append(SR2000PDFup)
SR2000FS.append(SR2000PDFdown)
#[0] index is your regular full selection
SR2000trigup = SR2000fList[0].Get("Mtwtrigup")
SR2000trigdown = SR2000fList[0].Get("Mtwtrigdown")
SR2000Wup = SR2000fList[0].Get("MtwWup")
SR2000Wdown = SR2000fList[0].Get("MtwWdown")
SR2000ExtrapUp = SR2000fList[0].Get("MtwExtrapUp")
SR2000ExtrapDown = SR2000fList[0].Get("MtwExtrapDown")
SR2000FS.append(SR2000trigup)
SR2000FS.append(SR2000trigdown)
SR2000FS.append(SR2000Wup)
SR2000FS.append(SR2000Wdown)
SR2000FS.append(SR2000ExtrapUp)
SR2000FS.append(SR2000ExtrapDown)
#BPB1200FS = []
#for j in range(len(BPB1200fList)):
# BPB1200FS.append(BPB1200fList[j].Get(kinVar[i]))
#[0] index is your regular full selection
#BPB1200trigup = BPB1200fList[0].Get("Mtwtrigup")
#BPB1200trigdown = BPB1200fList[0].Get("Mtwtrigdown")
#BPB1200Wup = BPB1200fList[0].Get("MtwWup")
#BPB1200Tdown = BPB1200fList[0].Get("MtwTdown")
#BPB1200FS.append(BPB1200Wup)
#BPB1200FS.append(BPB1200Tdown)
#BPB1200FS.append(BPB1200trigup)
#BPB1200FS.append(BPB1200trigdown)
#BPB1400FS = []
#for j in range(len(BPB1400fList)):
# BPB1400FS.append(BPB1400fList[j].Get(kinVar[i]))
#[0] index is your regular full selection
#BPB1400trigup = BPB1400fList[0].Get("Mtwtrigup")
#BPB1400trigdown = BPB1400fList[0].Get("Mtwtrigdown")
#BPB1400Wup = BPB1400fList[0].Get("MtwWup")
#BPB1400Tdown = BPB1400fList[0].Get("MtwTdown")
#BPB1400FS.append(BPB1400Wup)
#BPB1400FS.append(BPB1400Tdown)
#BPB1400FS.append(BPB1400trigup)
#BPB1400FS.append(BPB1400trigdown)
#BPB1600FS = []
#for j in range(len(BPB1600fList)):
# BPB1600FS.append(BPB1600fList[j].Get(kinVar[i]))
#[0] index is your regular full selection
#BPB1600trigup = BPB1600fList[0].Get("Mtwtrigup")
#BPB1600trigdown = BPB1600fList[0].Get("Mtwtrigdown")
#BPB1600Wup = BPB1600fList[0].Get("MtwWup")
#BPB1600Tdown = BPB1600fList[0].Get("MtwTdown")
#BPB1600FS.append(BPB1600Wup)
#BPB1600FS.append(BPB1600Tdown)
#BPB1600FS.append(BPB1600trigup)
#BPB1600FS.append(BPB1600trigdown)
#BPB1800FS = []
#for j in range(len(BPB1800fList)):
# BPB1800FS.append(BPB1800fList[j].Get(kinVar[i]))
#[0] index is your regular full selection
#BPB1800trigup = BPB1800fList[0].Get("Mtwtrigup")
#BPB1800trigdown = BPB1800fList[0].Get("Mtwtrigdown")
#BPB1800Wup = BPB1800fList[0].Get("MtwWup")
#BPB1800Tdown = BPB1800fList[0].Get("MtwTdown")
#BPB1800FS.append(BPB1800Wup)
#BPB1800FS.append(BPB1800Tdown)
#BPB1800FS.append(BPB1800trigup)
#BPB1800FS.append(BPB1800trigdown)
#[0] index is your regular full selection
#BPT1200trigup = BPT1200fList[0].Get("Mtwtrigup")
#BPT1200trigdown = BPT1200fList[0].Get("Mtwtrigdown")
#BPT1200Wup = BPT1200fList[0].Get("MtwWup")
#BPT1200Tdown = BPT1200fList[0].Get("MtwTdown")
#BPT1200FS.append(BPT1200Wup)
#BPT1200FS.append(BPT1200Tdown)
#BPT1200FS.append(BPT1200trigup)
#BPT1200FS.append(BPT1200trigdown)
#[0] index is your regular full selection
#BPT1400trigup = BPT1400fList[0].Get("Mtwtrigup")
#BPT1400trigdown = BPT1400fList[0].Get("Mtwtrigdown")
#BPT1400Wup = BPT1400fList[0].Get("MtwWup")
#BPT1400Tdown = BPT1400fList[0].Get("MtwTdown")
#BPT1400FS.append(BPT1400Wup)
#BPT1400FS.append(BPT1400Tdown)
#BPT1400FS.append(BPT1400trigup)
#BPT1400FS.append(BPT1400trigdown)
#[0] index is your regular full selection
#BPT1600trigup = BPT1600fList[0].Get("Mtwtrigup")
#BPT1600trigdown = BPT1600fList[0].Get("Mtwtrigdown")
#BPT1600Wup = BPT1600fList[0].Get("MtwWup")
#BPT1600Tdown = BPT1600fList[0].Get("MtwTdown")
#BPT1600FS.append(BPT1600Wup)
#BPT1600FS.append(BPT1600Tdown)
#BPT1600FS.append(BPT1600trigup)
#BPT1600FS.append(BPT1600trigdown)
#[0] index is your regular full selection
#BPT1800trigup = BPT1800fList[0].Get("Mtwtrigup")
#BPT1800trigdown = BPT1800fList[0].Get("Mtwtrigdown")
#BPT1800Wup = BPT1800fList[0].Get("MtwWup")
#BPT1800Tdown = BPT1800fList[0].Get("MtwTdown")
#BPT1800FS.append(BPT1800Wup)
#BPT1800FS.append(BPT1800Tdown)
#BPT1800FS.append(BPT1800trigup)
#BPT1800FS.append(BPT1800trigdown)
c1 = TCanvas(kinVar[i], 'Data Full selection vs b pt tagging background', 700, 700)
if options.blinded == 'on':
main = ROOT.TPad("main", "main", 0, 0, 1, 1)
sub = ROOT.TPad("sub", "sub", 0, 0, 0, 0)
main.SetBottomMargin(0.15)
else:
main = ROOT.TPad("main", "main", 0, 0.3, 1, 1)
sub = ROOT.TPad("sub", "sub", 0, 0, 1, 0.3)
main.SetBottomMargin(0.0)
main.SetLeftMargin(0.16)
main.SetRightMargin(0.05)
main.SetTopMargin(0.1)
sub.SetLeftMargin(0.16)
sub.SetRightMargin(0.05)
sub.SetTopMargin(0)
sub.SetBottomMargin(0.3)
main.Draw()
sub.Draw()
main.cd()
#Selections in order (Selection, PUup, PUdown, JESup, JESdown, JERup, JERdown, JMSup, JMSdown, JMRup, JMRdown, PDFup, PDFdown, ScaleUp, ScaleDown, trigup, trig down)
TTmcFS = []
for j in range(len(TTmcfList)):
TTmcFS.append(TTmcfList[j].Get(kinVar[i]))
if options.var == 'analyzer':
TTmctrigup = TTmcfList[0].Get("Mtwtrigup")
TTmctrigdown = TTmcfList[0].Get("Mtwtrigdown")
# TTmcTup = TTmcfList[0].Get("MtwTup")
# TTmcTdown = TTmcfList[0].Get("MtwTdown")
# TTmcFS.append(TTmcTup)
# TTmcFS.append(TTmcTdown)
TTmcFS.append(TTmctrigup)
TTmcFS.append(TTmctrigdown)
#To be consistent with the SRs, switch the 13th and 14th entries with the 15th and 16th entries
#This puts scaleup and down at the end of the list
if options.cuts == 'default':
TTmcFS[13], TTmcFS[15] = TTmcFS[15], TTmcFS[13]
TTmcFS[14], TTmcFS[16] = TTmcFS[16], TTmcFS[14]
TTmcBE = TTmcfList[0].Get("QCDbkg" + kinBkg[i])
if options.alphabet == 'off':
TTmcBE2d = TTmcfList[0].Get("QCDbkg" + kinBkg[i]+"2D")
TTmcBEh = TTmcfList[0].Get("QCDbkg" + kinBkg[i]+"h")
TTmcBEl = TTmcfList[0].Get("QCDbkg" + kinBkg[i]+"l")
DataBEh = Data.Get("QCDbkg"+kinBkg[i]+"h")
DataBEl = Data.Get("QCDbkg"+kinBkg[i]+"l")
DataBE = DataBE.Rebin(rebin[i])
DataFS = DataFS.Rebin(rebin[i])
TTmcBE = TTmcBE.Rebin(rebin[i])
if options.alphabet == 'off':
TTmcBE2d = TTmcBE2d.Rebin(rebin[i])
print "DataFS.Integral() = " + str(DataFS.Integral())
DataBEl = DataBEl.Rebin(rebin[i])
DataBEh = DataBEh.Rebin(rebin[i])
setList = [SR1200FS, SR2000FS, SR2800FS, TTmcFS]#, BPT1200FS, BPT1400FS, BPT1600FS, BPT1800FS]# BPB1200FS, BPB1400FS, BPB1600FS, BPB1800FS,
x =1
for selection in setList:
# print '\n'
# print x,' : ',
y=1
x+=1
for item in selection:
item.Rebin(rebin[i])
# print y,
y+=1
if options.alphabet == 'off':
DataBEMmup = DataBEMmup.Rebin(rebin[i])
DataBEMmdown = DataBEMmdown.Rebin(rebin[i])
DataBE2d = DataBE2d.Rebin(rebin[i])
DataBE2ddown = DataBE2ddown.Rebin(rebin[i])
DataBE2dup = DataBE2dup.Rebin(rebin[i])
#subtract weighted TT pretags
if options.set == 'data':
DataBE.Add(TTmcBE,-1)
DataBEl.Add(TTmcBE,-1)
DataBEh.Add(TTmcBE,-1)
if options.alphabet == 'off':
DataBEMmup.Add(TTmcBE,-1)
DataBEMmdown.Add(TTmcBE,-1)
DataBE2d.Add(TTmcBE2d,-1)
DataBE2dup.Add(TTmcBE2d,-1)
DataBE2ddown.Add(TTmcBE2d,-1)
print "begin singletop"
main.cd()
stop = ['singletop_tW','singletop_tWB','singletop_t','singletop_tB']
sfiles = []
shists = []
ssubs = []
ssubsh = []
ssubsl =[]
ssubs2d = []
singletop = ROOT.TH1F("singletop", "singletop", kinBin[i], kinLow[i], kinHigh[i] )
singletop = singletop.Rebin(rebin[i])
singletop.SetFillColor(6)
schanst = ROOT.TH1F("schanst", "schanst", kinBin[i], kinLow[i], kinHigh[i] )
schanst = schanst.Rebin(rebin[i])
for ifile in range(0,len(stop)):
sfiles.append(ROOT.TFile("rootfiles/"+Lumi+"/TWanalyzerweighted"+stop[ifile]+"_Trigger_nominal_"+pustr+mmstr+"_PSET_"+options.cuts+kin+".root"))
shists.append(sfiles[ifile].Get(kinVar[i]))
ssubs.append(sfiles[ifile].Get("QCDbkg"+kinBkg[i]))
ssubsh.append(sfiles[ifile].Get("QCDbkg"+kinBkg[i]+"h"))
ssubsl.append(sfiles[ifile].Get("QCDbkg"+kinBkg[i]+"l"))
if options.alphabet == 'off':
ssubs2d.append(sfiles[ifile].Get("QCDbkg"+kinBkg[i]+"2D"))
shists[ifile] = shists[ifile].Rebin(rebin[i])
ssubs[ifile] = ssubs[ifile].Rebin(rebin[i])
ssubsh[ifile] = ssubsh[ifile].Rebin(rebin[i])
ssubsl[ifile] = ssubsl[ifile].Rebin(rebin[i])
if options.alphabet == 'off':
ssubs2d[ifile] = ssubs2d[ifile].Rebin(rebin[i])
print stop[ifile]
if options.set == 'data':
DataBE.Add(ssubs[ifile],-1)
DataBEl.Add(ssubsl[ifile],-1)
DataBEh.Add(ssubsh[ifile],-1)
if options.alphabet == 'off':
DataBE2d.Add(ssubs2d[ifile],-1)
DataBEMmup.Add(ssubs[ifile],-1)
DataBEMmdown.Add(ssubs[ifile],-1)
singletop.Add(shists[ifile])
if ifile<=1:
schanst.Add(shists[ifile])
if options.set == "QCD":
DataFS.Add(TTmcFS[0])
DataFS.Add(singletop)
st1.Add(singletop)
#output.cd()
if options.alphabet == 'off':
fittitles = ["pol0","pol2","pol3","FIT","Bifpoly","expofit"]
QCDbkg_ARR = []
for ihist in range(0,len(fittitles)):
print "Appending to QCDbkg_ARR - " + "QCDbkg"+kinBkg[i]+str(fittitles[ihist])
QCDbkg_ARR.append(Data.Get("QCDbkg"+kinBkg[i]+str(fittitles[ihist])))
QCDbkg_ARR[ihist] = QCDbkg_ARR[ihist].Rebin(rebin[i])
BEfiterrh = kinFit_Uncertainty(QCDbkg_ARR, kinBkg[i])
DataQCDBEH=DataBE.Clone("DataQCDBEH")
DataQCDBEL=DataBE.Clone("DataQCDBEL")
DataTOTALBEH=DataBE.Clone("DataTOTALBEH")
DataTOTALBEL=DataBE.Clone("DataTOTALBEL")
for ibin in range(1,DataBE.GetNbinsX()+1):
TTstat=TTmcFS[0].GetBinError(ibin)
# Normalization uncertainty for ttbar
FlatPtSFFile = open('bstar_theta_PtSF_onTOPgroupCorrection.txt','r')
FlatPtSFList = FlatPtSFFile.readlines()
TTnormUp = TTmcFS[0].GetBinContent(ibin)*float(FlatPtSFList[1])
TTnormDown = TTmcFS[0].GetBinContent(ibin)*float(FlatPtSFList[2])
if DataBE.GetBinContent(ibin)>0:
QCDstat=DataBE.GetBinError(ibin)
else:
QCDstat=0.
if options.alphabet == 'off':
QCDfit=abs(BEfiterrh.GetBinContent(ibin))
QCDfit1=abs((DataBEh.GetBinContent(ibin)-DataBEl.GetBinContent(ibin))/2)
#QCDfit2=abs(DataBE2d.GetBinContent(ibin)-DataBE.GetBinContent(ibin))
# QCDfit3=abs(extrasig.GetBinContent(ibin))
if options.alphabet == 'off':
QCDMm=abs((DataBEMmup.GetBinContent(ibin)-DataBEMmdown.GetBinContent(ibin))/2)
QCDsys=sqrt(QCDMm*QCDMm+ QCDfit1*QCDfit1+ QCDfit*QCDfit) #+QCDfit2*QCDfit2)
else:
QCDsys=QCDfit1
QCDerror= sqrt(QCDstat*QCDstat+QCDsys*QCDsys)
TTerrorup=sqrt(TTstat*TTstat+TTnormUp*TTnormUp)
TTerrordown=sqrt(TTstat*TTstat+TTnormDown*TTnormDown)
Totalerrorup=sqrt(QCDerror*QCDerror+TTerrorup*TTerrorup)
Totalerrordown=sqrt(QCDerror*QCDerror+TTerrordown*TTerrordown)
DataQCDBEH.SetBinContent(ibin,DataQCDBEH.GetBinContent(ibin)+QCDerror)
DataQCDBEL.SetBinContent(ibin,DataQCDBEL.GetBinContent(ibin)-QCDerror)
DataTOTALBEH.SetBinContent(ibin,DataTOTALBEH.GetBinContent(ibin)+Totalerrorup)
DataTOTALBEL.SetBinContent(ibin,DataTOTALBEL.GetBinContent(ibin)-Totalerrordown)
# print "TTstat: " + str(TTstat)
# print "TTnormUp: " + str(TTnormUp)
# print "TTerrorup: " + str(TTerrorup)
# if options.alphabet == 'off':
# print "QCDMm: " + str(QCDMm)
# print "QCDfit: " + str(QCDfit)
# print "QCDfit1: " + str(QCDfit1)
# print "QCDstat: " + str(QCDstat)
# #print "QCDfit2: " + str(QCDfit2)
# print "QCDerror: " + str(QCDerror)
# print "DataQCDBEH: " + str(DataQCDBEH.Integral())
# print "DataBE: " + str(DataBE.Integral())
# print "QCD total error: " + str((DataQCDBEH.Integral()-DataBE.Integral())/DataBE.Integral())
DataTOTALBEL.Add(TTmcFS[0])
DataTOTALBEH.Add(TTmcFS[0])
DataTOTALBEL.Add(singletop)
DataTOTALBEH.Add(singletop)
for ifile in range(0,len(stop)):
DataTOTALBEL.Add(shists[ifile])
DataTOTALBEH.Add(shists[ifile])
# -------- Systematic uncertainties ----------------------------------------------
#setList is a list of SR1200/2800/2000, TTmc
#each of those is a list with the necessary histos
#(Selection, PUup, PUdown, JESup, JESdown, JERup, JERdown, JMSup, JMSdown, JMRup, JMRdown, trig up, trig down, Wup, Wdown/ScaleUp, ScaleDown )
#ScaleUp and ScaleDown are ttbar only
# Indexes of relevant histos in *FS
if options.cuts == 'default' and options.var == 'analyzer':
myIndexes = {'Pileup':[0,1,2],'JES':[0,3,4],'JER':[0,5,6], 'JMS':[0,7,8], 'JMR':[0,9,10], 'PDF':[0,11,12], 'Trig':[0,13,14], 'WSF':[0,15,16], 'Scale':[0,15,16], 'Extrap':[0,17,18]}
# orderedKeys = ['Pileup','JES','JER','JMS','JMR','PDF','Trig','WSF','Scale']
strSetList = ['SR1200', 'SR2000', 'SR2800', 'TTmc']#, 'BPT1200', 'BPT1400', 'BPT1600', 'BPT1800','BPB1200', 'BPB1400', 'BPB1600', 'BPB1800', 'BPT1200', 'BPT1400', 'BPT1600', 'BPT1800']
for selection in setList:
if selection == TTmcFS:
orderedKeys = ['Pileup','JES','JER','JMS','JMR','PDF','Trig','Scale']
else:
orderedKeys = ['Pileup','JES','JER','JMS','JMR','PDF','Trig','WSF','Extrap']
indexRange = len(orderedKeys)
for x in range(indexRange):
sSet = strSetList[setList.index(selection)]
sUncertainty = orderedKeys[x]
print sUncertainty
c0 = TCanvas(sSet+sUncertainty, sSet+sUncertainty, 700, 700)
pad = ROOT.TPad(sSet, sSet, 0,0,1,1)
pad.SetLeftMargin(0.16)
pad.SetRightMargin(0.05)
pad.SetTopMargin(0.1)
pad.SetBottomMargin(0.15)
pad.Draw()
pad.cd()
leg0 = TLegend(0.7, 0.6, 0.93, 0.9)
leg0.SetNColumns(1)
leg0.SetFillColor(0)
leg0.SetBorderSize(0)
normal = selection[myIndexes[sUncertainty][0]]
up = selection[myIndexes[sUncertainty][1]]
down = selection[myIndexes[sUncertainty][2]]
normal.SetLineColor(kRed)
normal.SetLineWidth(2)
normal.SetTitle(sSet+' - ' + sUncertainty)
normal.GetXaxis().SetTitle('M_{tW} (GeV)')
normal.GetYaxis().SetTitle('Counts')
normal.GetXaxis().SetNdivisions(50504)
up.SetLineColor(kBlue)
up.SetLineWidth(2)
down.SetLineColor(kGreen+1)
down.SetLineWidth(2)
up.SetLineStyle(2)
down.SetLineStyle(2)
normal.SetStats(0)
up.SetStats(0)
down.SetStats(0)
leg0.AddEntry( normal, "nominal", 'L')
leg0.AddEntry( up, "up", 'L')
leg0.AddEntry( down, "down", 'L')
histList = [normal, up, down]
yMax = histList[0].GetMaximum()
maxHist = histList[0]
for h in range(1,len(histList)):
if histList[h].GetMaximum() > yMax:
yMax = histList[h].GetMaximum()
maxHist = histList[h]
for h in histList:
h.SetMaximum(yMax*1.1)
normal.Draw("samehist")
up.Draw("samehist")
down.Draw("samehist")
c0.Print('plots/Uncertainty'+sSet+sUncertainty+Lumi+'.root')
c0.Print('plots/Uncertainty'+sSet+sUncertainty+Lumi+'.png')
c0.Print('plots/Uncertainty'+sSet+sUncertainty+Lumi+'.pdf')
legUncert = TCanvas("Uncertainty legend", "Uncertainty legend")
leg0.Draw()
legUncert.Print("uncertLeg.pdf",'pdf')
c2 = TCanvas("QCD tagrate uncertainty", "QCD tagrate uncertainty", 700, 700)
QCDtagrate = ROOT.TPad("QCDtagrate", "QDCtagrate", 0, 0, 1, 1)
QCDtagrate.SetLeftMargin(0.16)
QCDtagrate.SetRightMargin(0.05)
QCDtagrate.SetTopMargin(0.1)
QCDtagrate.SetBottomMargin(0.15)
QCDtagrate.Draw()
QCDtagrate.cd()
DataBE.SetLineColor(kRed)
DataBEl.SetLineColor(kGreen+1)
DataBEh.SetLineColor(kBlue)
DataBEl.SetLineStyle(2)
DataBEh.SetLineStyle(2)
DataBE.SetLineWidth(2)
DataBEl.SetLineWidth(2)
DataBEh.SetLineWidth(2)
DataBE.SetStats(0)
DataBEl.SetStats(0)
DataBEh.SetStats(0)
c2Max = DataBEh.GetMaximum()
DataBE.SetMaximum(c2Max*1.1)
DataBEh.SetMaximum(c2Max*1.1)
DataBEl.SetMaximum(c2Max*1.1)
DataBE.SetTitle("QCD - Fit uncertainty")
DataBE.GetXaxis().SetTitle('M_{tW} (GeV)')
DataBE.GetYaxis().SetTitle('Counts')
DataBE.GetXaxis().SetNdivisions(50504)
DataBE.Draw("samehist")
DataBEl.Draw("samehist")
DataBEh.Draw("samehist")
c2.Print('plots/UncertaintyQCDtagrate.root')
c2.Print('plots/UncertaintyQCDtagrate.png')
c2.Print('plots/UncertaintyQCDtagrate.pdf')
if options.alphabet == 'off':
c3 = TCanvas("QCD 2D uncertainty", "QCD uncertainty", 700, 700)
QCD2D = ROOT.TPad("QCD2D", "QDC2D", 0, 0, 1, 1)
QCD2D.SetLeftMargin(0.16)
QCD2D.SetRightMargin(0.05)
QCD2D.SetTopMargin(0.1)
QCD2D.SetBottomMargin(0.15)
QCD2D.Draw()
QCD2D.cd()
DataBE2d.SetLineColor(kRed)
DataBE2ddown.SetLineColor(kGreen+1)
DataBE2dup.SetLineColor(kBlue)
DataBE2ddown.SetLineStyle(2)
DataBE2dup.SetLineStyle(2)
DataBE2d.SetLineWidth(2)
DataBE2dup.SetLineWidth(2)
DataBE2ddown.SetLineWidth(2)
DataBE2d.SetStats(0)
DataBE2ddown.SetStats(0)
DataBE2dup.SetStats(0)
c3Max = DataBE2dup.GetMaximum()
DataBE2d.SetMaximum(c3Max*1.1)
DataBE2dup.SetMaximum(c3Max*1.1)
DataBE2ddown.SetMaximum(c3Max*1.1)
DataBE2d.SetTitle("QCD - Parameterization")
DataBE2d.GetXaxis().SetTitle('M_{tW} (GeV)')
DataBE2d.GetYaxis().SetTitle('Counts')
DataBE2d.GetXaxis().SetNdivisions(50504)
DataBE2d.Draw("samehist")
DataBE2ddown.Draw("samehist")
DataBE2dup.Draw("samehist")
c3.Print('plots/UncertaintyQCD2D.root')
c3.Print('plots/UncertaintyQCD2D.png')
c3.Print('plots/UncertaintyQCD2D.pdf')
QCDup = DataBE.Clone()
QCDdown = DataBE.Clone()
for ibin in range(1,DataBE.GetNbinsX()+1):
# QCDfiterr=abs(BEfiterrh.GetBinContent(ibin))
QCDnominal=abs(DataBE.GetBinContent(ibin))
QCDup.SetBinContent(ibin,(QCDnominal + QCDfiterr))
QCDdown.SetBinContent(ibin,(QCDnominal - QCDfiterr))
c4 = TCanvas("QCD fit uncertainty", "QCD uncertainty", 700, 700)
QCDfit = ROOT.TPad("QCDfit", "QDCfit", 0, 0, 1, 1)
QCDfit.SetLeftMargin(0.16)
QCDfit.SetRightMargin(0.05)
QCDfit.SetTopMargin(0.1)
QCDfit.SetBottomMargin(0.15)
QCDfit.Draw()
QCDfit.cd()
DataBE.SetLineColor(kRed)
QCDdown.SetLineColor(kGreen+1)
QCDup.SetLineColor(kBlue)
QCDdown.SetLineStyle(2)
QCDup.SetLineStyle(2)
QCDup.SetLineWidth(2)
QCDdown.SetLineWidth(2)
QCDup.SetStats(0)
QCDdown.SetStats(0)
c4Max = QCDup.GetMaximum()
DataBE.SetMaximum(c4Max*1.1)
QCDdown.SetMaximum(c4Max*1.1)
QCDup.SetMaximum(c4Max*1.1)
DataBE.SetTitle("QCD - Alternative fits")
# DataBE.GetXaxis().SetTitle('M_{tW} (GeV)')
# DataBE.GetYaxis().SetTitle('Counts')
# DataBE.GetXaxis().SetNdivisions(50504)
DataBE.Draw("samehist")
QCDdown.Draw("samehist")
QCDup.Draw("samehist")
c4.Print('plots/UncertaintyQCDfit.root')
c4.Print('plots/UncertaintyQCDfit.png')
c4.Print('plots/UncertaintyQCDfit.pdf')
c5 = TCanvas("QCD mod mass uncertainty", "QCD mod mass uncertainty", 700, 700)
QCDModMass = ROOT.TPad("QCDMm", "QCDMm", 0, 0, 1, 1)
QCDModMass.SetLeftMargin(0.16)
QCDModMass.SetRightMargin(0.05)
QCDModMass.SetTopMargin(0.1)
QCDModMass.SetBottomMargin(0.15)
QCDModMass.Draw()
QCDModMass.cd()
DataBE.SetLineColor(kRed)
DataBEMmdown.SetLineColor(kGreen+1)
DataBEMmup.SetLineColor(kBlue)
DataBEMmdown.SetLineStyle(2)
DataBEMmup.SetLineStyle(2)
DataBEMmup.SetLineWidth(2)
DataBEMmdown.SetLineWidth(2)
DataBEMmup.SetStats(0)
DataBEMmdown.SetStats(0)
c5Max =DataBEMmup.GetMaximum()
DataBE.SetMaximum(c5Max*1.1)
DataBEMmdown.SetMaximum(c5Max*1.1)
DataBEMmup.SetMaximum(c5Max*1.1)
DataBE.SetTitle('QCD - Top mass shape correction')
DataBE.Draw("samehist")
DataBEMmdown.Draw("samehist")
DataBEMmup.Draw("samehist")
c5.Print('plots/UncertaintyQCDModMass.root')
c5.Print('plots/UncertaintyQCDModMass.png')
c5.Print('plots/UncertaintyQCDModMass.pdf')
#---------------------- Resume -----------------------------------------------------
# How the error bars get plotted:
# The st1 stack gets drawn first and then the sigst stack gets drawn on top
# The sigst stack is the ttbar mc, the low QCD background estimate, and sigma (the error bars)
# which is derived by taking the difference between the high and low estiamates.
# In the generic applicaltion, this plotting method works because the ttbar mc looks
# identical at the bottom of both the st1 and sigst stacks.
# However, when ttbar is moved up a spot in the stacks, there's an issue because the
# QCD estimates in the two different stacks are different. Thus, when plotting the Mt
# variable (whcih needs ttbar on top of the stack), the histograms added to the sigst
# stack need to be transparent. This maintains the position of the error bars while
# allowing the reader to see the nominal stack from st1.
main.cd()
DataBE.SetFillColor(kYellow)