Data = MergedPlotter(dataPlotters)
fout = ROOT.TFile(outTag + '.root', 'recreate')
canvas = ROOT.TCanvas('c1', 'c1', 600, 630)
canvas.Print(outTag + '.ps[')
# 1d variables
#deltaR(mu,mu)
hdRZmm = ZJets.drawTH1('llnunu_l1_deltaR',
cuts + '&&(abs(llnunu_l1_l1_pdgId)==13)',
str(lumi * 1000),
50,
0,
5,
titlex='#Delta R(#mu,#mu)',
units='',
drawStyle="HIST")
hdRZmm.SetName('hdRZmm')
hdRZmm.GetYaxis().SetTitle("Events")
canvas.Clear()
hdRZmm.Draw()
canvas.Print(outTag + '.ps')
canvas.Clear()
hdRZmm.Write()
#deltaPhi(Zmumu,MET)
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
if options.data == 0:
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
pvars = options.vars.split(',')
pmins = options.mins.split(',')
pmaxes = options.maxes.split(',')
pbins = options.bins.split(',')
if len(pvars) == 1:
histo = data.drawTH1(pvars[0], options.cut, "1", int(pbins[0]),
float(pmins[0]), float(pmaxes[0]))
if len(pvars) == 2:
histo = data.drawTH2(pvars[1] + ":" + pvars[0], options.cut, "1",
int(pbins[0]), float(pmins[0]), float(pmaxes[0]),
int(pbins[1]), float(pmins[1]), float(pmaxes[1]))
if len(pvars) == 3:
histo = data.drawTH3(pvars[2] + ":" + pvars[1] + ":" + pvars[0],
options.cut, "1", int(pbins[0]), float(pmins[0]),
float(pmaxes[0]), int(pbins[1]), float(pmins[1]),
float(pmaxes[1]), int(pbins[2]), float(pmins[2]),
float(pmaxes[2]))
histo.Scale(options.factor)
class NtupleStacker:
def __init__(self,
indir="/afs/cern.ch/work/m/mewu/public/76X_new",
outdir='./NtuplePlots',
lumi=2.169126704526,
sepSig=True,
LogY=True,
doRatio=True):
if not os.path.exists(outdir): os.system('mkdir ' + outdir)
#self.Channel=raw_input("Please choose a channel (el or mu): \n")
self.outdir = outdir
self.lumi = lumi
self.sepSig = sepSig
#self.whichregion=raw_input("Please choose a benchmarck Region (SR or VR): \n")
#self.cuts = python.SetCuts.Cuts(self.Channel, self.whichregion)
#self.preCuts = python.SetCuts.Cuts(self.Channel, self.whichregion, True)
#######----------- Prepare samples to plot:
wwPlotters = []
wwSamples = ['WWTo2L2Nu', 'WWToLNuQQ', 'WZTo1L1Nu2Q']
for sample in wwSamples:
wwPlotters.append(
TreePlotter(indir + '/' + sample + '/vvTreeProducer/tree.root',
'tree'))
wwPlotters[-1].setupFromFile(indir + '/' + sample +
'/skimAnalyzerCount/SkimReport.pck')
wwPlotters[-1].addCorrectionFactor('xsec', 'tree')
wwPlotters[-1].addCorrectionFactor('genWeight', 'tree')
wwPlotters[-1].addCorrectionFactor('puWeight', 'tree')
WW = MergedPlotter(wwPlotters)
WW.setFillProperties(1001, ROOT.kOrange)
vvPlotters = []
vvSamples = ['WZTo2L2Q', 'WZTo3LNu', 'ZZTo2L2Nu', 'ZZTo2L2Q', 'ZZTo4L']
for sample in vvSamples:
vvPlotters.append(
TreePlotter(indir + '/' + sample + '/vvTreeProducer/tree.root',
'tree'))
vvPlotters[-1].setupFromFile(indir + '/' + sample +
'/skimAnalyzerCount/SkimReport.pck')
vvPlotters[-1].addCorrectionFactor('xsec', 'tree')
vvPlotters[-1].addCorrectionFactor('genWeight', 'tree')
vvPlotters[-1].addCorrectionFactor('puWeight', 'tree')
VV = MergedPlotter(vvPlotters)
VV.setFillProperties(1001, ROOT.kMagenta)
wjetsPlotters = []
wjetsSamples = ['WJetsToLNu']
for sample in wjetsSamples:
wjetsPlotters.append(
TreePlotter(indir + '/' + sample + '/vvTreeProducer/tree.root',
'tree'))
wjetsPlotters[-1].setupFromFile(
indir + '/' + sample + '/skimAnalyzerCount/SkimReport.pck')
wjetsPlotters[-1].addCorrectionFactor('xsec', 'tree')
wjetsPlotters[-1].addCorrectionFactor('genWeight', 'tree')
wjetsPlotters[-1].addCorrectionFactor('puWeight', 'tree')
WJets = MergedPlotter(wjetsPlotters)
WJets.setFillProperties(1001, ROOT.kBlue - 6)
zjetsPlotters = []
#zjetsSamples = ['DYJetsToLL_M50_HT100to200','DYJetsToLL_M50_HT200to400','DYJetsToLL_M50_HT400to600','DYJetsToLL_M50_HT600toInf']
#zjetsSamples = ['DYJetsToLL_M50','DYJetsToLL_M50_Ext']
zjetsSamples = ['DYJetsToLL_M50_BIG'] # M50_BIG = M50 + M50_Ext
for sample in zjetsSamples:
zjetsPlotters.append(
TreePlotter(indir + '/' + sample + '/vvTreeProducer/tree.root',
'tree'))
zjetsPlotters[-1].setupFromFile(
indir + '/' + sample + '/skimAnalyzerCount/SkimReport.pck')
zjetsPlotters[-1].addCorrectionFactor('xsec', 'tree')
zjetsPlotters[-1].addCorrectionFactor('genWeight', 'tree')
zjetsPlotters[-1].addCorrectionFactor('puWeight', 'tree')
self.ZJets = MergedPlotter(zjetsPlotters)
self.ZJets.setFillProperties(1001, ROOT.kGreen + 2)
ttPlotters = []
ttSamples = ['TTTo2L2Nu'] #,'TTZToLLNuNu','TTWJetsToLNu']
for sample in ttSamples:
ttPlotters.append(
TreePlotter(indir + '/' + sample + '/vvTreeProducer/tree.root',
'tree'))
ttPlotters[-1].setupFromFile(indir + '/' + sample +
'/skimAnalyzerCount/SkimReport.pck')
ttPlotters[-1].addCorrectionFactor('xsec', 'tree')
ttPlotters[-1].addCorrectionFactor('genWeight', 'tree')
ttPlotters[-1].addCorrectionFactor('puWeight', 'tree')
TT = MergedPlotter(ttPlotters)
TT.setFillProperties(1001, ROOT.kAzure - 9)
sigPlotters = []
sigSamples = [
'BulkGravToZZToZlepZinv_narrow_800',
'BulkGravToZZToZlepZinv_narrow_1000',
'BulkGravToZZToZlepZinv_narrow_1200',
]
k = 1000
sigSampleNames = [
str(k) + ' x BulkG-800',
str(k) + ' x BulkG-1000',
str(k) + ' x BulkG-1200',
]
sigXsec = {
'BulkGravToZZToZlepZinv_narrow_800': 4.42472e-04 * k,
'BulkGravToZZToZlepZinv_narrow_1000': 1.33926e-04 * k,
'BulkGravToZZToZlepZinv_narrow_1200': 4.76544e-05 * k,
}
for sample in sigSamples:
sigPlotters.append(
TreePlotter(indir + '/' + sample + '/vvTreeProducer/tree.root',
'tree'))
sigPlotters[-1].setupFromFile(indir + '/' + sample +
'/skimAnalyzerCount/SkimReport.pck')
sigPlotters[-1].addCorrectionFactor(str(sigXsec[sample]), 'tree')
sigPlotters[-1].addCorrectionFactor('genWeight', 'tree')
sigPlotters[-1].addCorrectionFactor('puWeight', 'tree')
sigPlotters[-1].setFillProperties(0, ROOT.kWhite)
dataPlotters = []
dataSamples = [
'SingleElectron_Run2015C_25ns_16Dec',
'SingleElectron_Run2015D_16Dec', 'SingleMuon_Run2015C_25ns_16Dec',
'SingleMuon_Run2015D_16Dec'
]
for sample in dataSamples:
dataPlotters.append(
TreePlotter(indir + '/' + sample + '/vvTreeProducer/tree.root',
'tree'))
self.Data = MergedPlotter(dataPlotters)
self.Stack = StackPlotter()
self.Stack.addPlotter(self.Data, "data_obs", "Data", "data")
#Stack.addPlotter(WJets, "WJets","W+Jets", "background")
self.Stack.addPlotter(WW, "WW", "WW, WZ non-reson.", "background")
self.Stack.addPlotter(TT, "TT", "TT", "background")
self.Stack.addPlotter(VV, "ZZ", "ZZ, WZ reson.", "background")
self.Stack.addPlotter(self.ZJets, "ZJets", "Z+Jets", "background")
for i in range(len(sigSamples)):
sigPlotters[i].setLineProperties(2, ROOT.kRed + i, 2)
self.Stack.addPlotter(sigPlotters[i], sigSamples[i],
sigSampleNames[i], 'signal')
self.Stack.setLog(LogY)
self.Stack.doRatio(doRatio)
ROOT.gROOT.ProcessLine('.x tdrstyle.C')
def GetStack(self):
return self.Stack
def DrawRegion(self, cuts):
tag = 'looseCuts_'
self.Stack.rmPlotter(self.Data, "data_obs", "Data", "data")
self.Stack.drawStack('met_pt',
cuts,
str(lumi * 1000),
50,
0,
500,
titlex="E_{T}^{miss}",
units="GeV",
output=tag + 'met_low',
outDir=outdir,
separateSignal=sepSig,
blinding=Blind,
blindingCut=200)
file = ROOT.TFile(self.outdir + '/' + tag + 'met_low.root')
hdata = self.Data.drawTH1('met_JECJER_pt',
cuts,
str(self.lumi * 1000),
50,
0,
500,
titlex='E_{T}^{miss}',
units='GeV',
drawStyle="HIST")
hframe = file.Get(tag + 'met_low_frame')
hs = file.Get(tag + 'met_low_stack')
hs.Add(h_met_zjets)
#hdata=file.Get(tag+'met_low_data')
hratio = GetRatio_TH1(hdata, hs, True)
legend = file.Get(tag + 'met_low_legend')
myentry = ROOT.TLegendEntry(hdata, "data", "p")
legend.GetListOfPrimitives().AddFirst(myentry)
# Let's remove the signal entries in the legend
#for i in legend.GetListOfPrimitives():
#if ROOT.TString(i.GetLabel()).Contains("Bulk"):
# legend.GetListOfPrimitives().Remove(i)
drawStack_simple(hframe,
hs,
hdata,
hratio,
legend,
hstack_opt="A, HIST",
outDir=self.outdir,
output=tag + 'JER_met_low',
channel=ROOT.TString(self.Channel),
xmin=xMin,
xmax=xMax,
xtitle="E_{T}^{miss}",
units="GeV",
lumi=self.lumi,
notes="MET with JEC and JER corrected jets")
return
class NtupleStacker:
def __init__(self, indir="/afs/cern.ch/work/m/mewu/public/76X_new", outdir='./NtuplePlots',
lumi = 2.169126704526, sepSig=True,
LogY=True, doRatio=True):
if not os.path.exists(outdir): os.system('mkdir '+outdir)
#self.Channel=raw_input("Please choose a channel (el or mu): \n")
self.outdir = outdir
self.lumi = lumi
self.sepSig = sepSig
#self.whichregion=raw_input("Please choose a benchmarck Region (SR or VR): \n")
#self.cuts = python.SetCuts.Cuts(self.Channel, self.whichregion)
#self.preCuts = python.SetCuts.Cuts(self.Channel, self.whichregion, True)
#######----------- Prepare samples to plot:
wwPlotters=[]
wwSamples = ['WWTo2L2Nu','WWToLNuQQ','WZTo1L1Nu2Q']
for sample in wwSamples:
wwPlotters.append(TreePlotter(indir+'/'+sample+'/vvTreeProducer/tree.root','tree'))
wwPlotters[-1].setupFromFile(indir+'/'+sample+'/skimAnalyzerCount/SkimReport.pck')
wwPlotters[-1].addCorrectionFactor('xsec','tree')
wwPlotters[-1].addCorrectionFactor('genWeight','tree')
wwPlotters[-1].addCorrectionFactor('puWeight','tree')
WW = MergedPlotter(wwPlotters)
WW.setFillProperties(1001,ROOT.kOrange)
vvPlotters=[]
vvSamples = ['WZTo2L2Q','WZTo3LNu',
'ZZTo2L2Nu',
'ZZTo2L2Q','ZZTo4L']
for sample in vvSamples:
vvPlotters.append(TreePlotter(indir+'/'+sample+'/vvTreeProducer/tree.root','tree'))
vvPlotters[-1].setupFromFile(indir+'/'+sample+'/skimAnalyzerCount/SkimReport.pck')
vvPlotters[-1].addCorrectionFactor('xsec','tree')
vvPlotters[-1].addCorrectionFactor('genWeight','tree')
vvPlotters[-1].addCorrectionFactor('puWeight','tree')
VV = MergedPlotter(vvPlotters)
VV.setFillProperties(1001,ROOT.kMagenta)
wjetsPlotters=[]
wjetsSamples = ['WJetsToLNu']
for sample in wjetsSamples:
wjetsPlotters.append(TreePlotter(indir+'/'+sample+'/vvTreeProducer/tree.root','tree'))
wjetsPlotters[-1].setupFromFile(indir+'/'+sample+'/skimAnalyzerCount/SkimReport.pck')
wjetsPlotters[-1].addCorrectionFactor('xsec','tree')
wjetsPlotters[-1].addCorrectionFactor('genWeight','tree')
wjetsPlotters[-1].addCorrectionFactor('puWeight','tree')
WJets = MergedPlotter(wjetsPlotters)
WJets.setFillProperties(1001,ROOT.kBlue-6)
zjetsPlotters=[]
#zjetsSamples = ['DYJetsToLL_M50_HT100to200','DYJetsToLL_M50_HT200to400','DYJetsToLL_M50_HT400to600','DYJetsToLL_M50_HT600toInf']
#zjetsSamples = ['DYJetsToLL_M50','DYJetsToLL_M50_Ext']
zjetsSamples = ['DYJetsToLL_M50_BIG'] # M50_BIG = M50 + M50_Ext
for sample in zjetsSamples:
zjetsPlotters.append(TreePlotter(indir+'/'+sample+'/vvTreeProducer/tree.root','tree'))
zjetsPlotters[-1].setupFromFile(indir+'/'+sample+'/skimAnalyzerCount/SkimReport.pck')
zjetsPlotters[-1].addCorrectionFactor('xsec','tree')
zjetsPlotters[-1].addCorrectionFactor('genWeight','tree')
zjetsPlotters[-1].addCorrectionFactor('puWeight','tree')
self.ZJets = MergedPlotter(zjetsPlotters)
self.ZJets.setFillProperties(1001,ROOT.kGreen+2)
ttPlotters=[]
ttSamples = ['TTTo2L2Nu']#,'TTZToLLNuNu','TTWJetsToLNu']
for sample in ttSamples:
ttPlotters.append(TreePlotter(indir+'/'+sample+'/vvTreeProducer/tree.root','tree'))
ttPlotters[-1].setupFromFile(indir+'/'+sample+'/skimAnalyzerCount/SkimReport.pck')
ttPlotters[-1].addCorrectionFactor('xsec','tree')
ttPlotters[-1].addCorrectionFactor('genWeight','tree')
ttPlotters[-1].addCorrectionFactor('puWeight','tree')
TT = MergedPlotter(ttPlotters)
TT.setFillProperties(1001,ROOT.kAzure-9)
sigPlotters=[]
sigSamples = [
'BulkGravToZZToZlepZinv_narrow_800',
'BulkGravToZZToZlepZinv_narrow_1000',
'BulkGravToZZToZlepZinv_narrow_1200',
]
k=1000
sigSampleNames = [
str(k)+' x BulkG-800',
str(k)+' x BulkG-1000',
str(k)+' x BulkG-1200',
]
sigXsec = {
'BulkGravToZZToZlepZinv_narrow_800' : 4.42472e-04*k,
'BulkGravToZZToZlepZinv_narrow_1000' : 1.33926e-04*k,
'BulkGravToZZToZlepZinv_narrow_1200' : 4.76544e-05*k,
}
for sample in sigSamples:
sigPlotters.append(TreePlotter(indir+'/'+sample+'/vvTreeProducer/tree.root','tree'))
sigPlotters[-1].setupFromFile(indir+'/'+sample+'/skimAnalyzerCount/SkimReport.pck')
sigPlotters[-1].addCorrectionFactor(str(sigXsec[sample]),'tree')
sigPlotters[-1].addCorrectionFactor('genWeight','tree')
sigPlotters[-1].addCorrectionFactor('puWeight','tree')
sigPlotters[-1].setFillProperties(0,ROOT.kWhite)
dataPlotters=[]
dataSamples = ['SingleElectron_Run2015C_25ns_16Dec',
'SingleElectron_Run2015D_16Dec',
'SingleMuon_Run2015C_25ns_16Dec',
'SingleMuon_Run2015D_16Dec']
for sample in dataSamples:
dataPlotters.append(TreePlotter(indir+'/'+sample+'/vvTreeProducer/tree.root','tree'))
self.Data = MergedPlotter(dataPlotters)
self.Stack = StackPlotter()
self.Stack.addPlotter(self.Data, "data_obs", "Data", "data")
#Stack.addPlotter(WJets, "WJets","W+Jets", "background")
self.Stack.addPlotter(WW, "WW","WW, WZ non-reson.", "background")
self.Stack.addPlotter(TT, "TT","TT", "background")
self.Stack.addPlotter(VV, "ZZ","ZZ, WZ reson.", "background")
self.Stack.addPlotter(self.ZJets, "ZJets","Z+Jets", "background")
for i in range(len(sigSamples)):
sigPlotters[i].setLineProperties(2,ROOT.kRed+i,2)
self.Stack.addPlotter(sigPlotters[i],sigSamples[i],sigSampleNames[i],'signal')
self.Stack.setLog(LogY)
self.Stack.doRatio(doRatio)
ROOT.gROOT.ProcessLine('.x tdrstyle.C')
def GetStack(self):
return self.Stack
def DrawRegion(self, cuts):
tag ='looseCuts_'
self.Stack.rmPlotter(self.Data, "data_obs","Data", "data")
self.Stack.drawStack('met_pt', cuts, str(lumi*1000), 50, 0, 500, titlex = "E_{T}^{miss}", units = "GeV",output=tag+'met_low',outDir=outdir,separateSignal=sepSig,blinding=Blind,blindingCut=200)
file=ROOT.TFile(self.outdir+'/'+tag+'met_low.root')
hdata=self.Data.drawTH1('met_JECJER_pt', cuts,str(self.lumi*1000), 50, 0, 500,titlex='E_{T}^{miss}',units='GeV',drawStyle="HIST")
hframe=file.Get(tag+'met_low_frame')
hs=file.Get(tag+'met_low_stack')
hs.Add(h_met_zjets)
#hdata=file.Get(tag+'met_low_data')
hratio=GetRatio_TH1(hdata,hs,True)
legend=file.Get(tag+'met_low_legend')
myentry=ROOT.TLegendEntry(hdata,"data","p")
legend.GetListOfPrimitives().AddFirst(myentry)
# Let's remove the signal entries in the legend
#for i in legend.GetListOfPrimitives():
#if ROOT.TString(i.GetLabel()).Contains("Bulk"):
# legend.GetListOfPrimitives().Remove(i)
drawStack_simple(hframe, hs, hdata,hratio,legend,
hstack_opt="A, HIST",
outDir=self.outdir, output=tag+'JER_met_low',channel=ROOT.TString(self.Channel),
xmin=xMin, xmax=xMax, xtitle="E_{T}^{miss}" ,units="GeV",
lumi=self.lumi, notes="MET with JEC and JER corrected jets")
return