def makePlots():
# gROOT.SetStyle('Plain') # white background
# gStyle.SetOptStat(222211)
ROOT.gROOT.ProcessLine('.L ../tdrstyle.C')
ROOT.gROOT.Reset()
ROOT.gROOT.ProcessLine('setTDRStyle()') #Set CMS TDR style
inputFile = TFile(output_name + '.root', 'READ')
histos_SR1 = dict()
histos_SR2 = dict()
histos_LSB = dict()
histos_RSB = dict()
histos_MC = dict()
keys = [
'photon_pt', 'photon_eta', 'dimuon_pt', 'dimuon_rapidity', 'chib_pt'
]
for key in keys:
histos_SR1[key] = inputFile.Get(key + '_SR1')
histos_SR2[key] = inputFile.Get(key + '_SR2')
histos_LSB[key] = inputFile.Get(key + '_LSB')
histos_RSB[key] = inputFile.Get(key + '_RSB')
histos_MC[key] = inputFile.Get(key + '_MC')
titles = dict(
photon_pt='photon E_{T};E_{T}(#gamma) [GeV];Entries / 100 MeV',
photon_eta='photon_eta;#eta(#gamma);Entries / 0.05',
dimuon_pt='#Upsilon p_{T};p_{T}(#Upsilon) [GeV];Entries / GeV',
dimuon_rapidity='#Upsilon rapidity(#Upsilon);y(#Upsilon);Entries / 0.1',
chib_pt='#chi_{b} p_{T};p_{T}(#chi_{b}) [GeV];Entries / GeV',
)
titles_chib = dict(
photon_pt='photon E_{T};E_{T}(#gamma) [GeV];A.U.',
photon_eta='photon_eta;#eta(#gamma);A.U.',
dimuon_pt='#Upsilon p_{T};p_{T}(#Upsilon) [GeV];A.U.',
dimuon_rapidity='#Upsilon rapidity(#Upsilon);y(#Upsilon);A.U.',
chib_pt='#chi_{b} p_{T};p_{T}(#chi_{b}) [GeV];A.U.',
)
logY = dict(
photon_pt=0,
photon_eta=0,
dimuon_pt=0,
dimuon_rapidity=0,
chib_pt=0,
)
maxY = dict(
photon_pt=750,
photon_eta=350,
dimuon_pt=800,
dimuon_rapidity=400,
chib_pt=800,
)
integralData1 = histos_SR1[keys[0]].Integral()
integralData2 = histos_SR2[keys[0]].Integral()
integralData = integralData1 + integralData2
for histo in histos_LSB.values() + histos_RSB.values() + histos_MC.values(
):
if (histo.Integral() != 0):
histo.Scale(1. / histo.Integral())
histo.Rebin(3)
for histo in histos_SR1.values() + histos_SR2.values():
histo.Rebin(3)
fBG = 0.48 #0.28
fLSB = 0.5
histos_BG = dict()
for key in keys:
histos_BG[key] = histos_RSB[key].Clone()
histos_BG[key].SetNameTitle(key + '_BG', 'bgd from side-bands')
histos_BG[key].Scale(1 - fLSB)
histos_BG[key].Add(histos_LSB[key], fLSB)
histos_Signal1 = dict()
histos_Signal2 = dict()
histos_Signal = dict()
histos_SR = dict()
for key in keys:
histos_Signal1[key] = histos_SR1[key].Clone()
histos_Signal1[key].SetNameTitle(key + '_signal1', 'Signal1')
histos_Signal1[key].Add(histos_BG[key], -1 * integralData1 * fBG)
histos_Signal2[key] = histos_SR2[key].Clone()
histos_Signal2[key].SetNameTitle(key + '_signal2', 'Signal2')
histos_Signal2[key].Add(histos_BG[key], -1 * integralData2 * fBG)
histos_Signal[key] = histos_Signal1[key].Clone()
histos_Signal[key].Add(histos_Signal2[key])
histos_Signal[key].SetNameTitle(key + '_signal', 'data bkg-subtracted')
histos_SR[key] = histos_SR1[key].Clone()
histos_SR[key].Add(histos_SR2[key])
histos_SR[key].SetNameTitle(key + '_SR', 'data')
for histo in histos_Signal.values() + histos_BG.values():
if (histo.Integral() != 0):
histo.Scale(1. / histo.Integral())
# Normalize SR to their original value, MC to be comparable with signal background-subtracted and background such that Signal+background = SR
for histo in histos_MC.values():
histo.Scale(integralData * (1 - fBG))
for histo in histos_BG.values():
histo.Scale(integralData * fBG)
for histo in histos_LSB.values():
histo.Scale(integralData * fBG * fLSB)
for histo in histos_RSB.values():
histo.Scale(integralData * fBG * (1 - fLSB))
chi2Prob = dict()
kolmogorovProb = dict()
h_ratio = dict()
for key in histos_Signal.keys():
h_ratio[key] = histos_SR[key].Clone()
histo_sum_MC_BG = histos_MC[key].Clone()
histo_sum_MC_BG.Add(histos_BG[key])
h_ratio[key].Divide(histo_sum_MC_BG)
h_ratio[key].SetNameTitle(key + '_ratio', titles[key])
h_ratio[key].SetMarkerStyle(20)
h_ratio[key].SetMarkerSize(1)
h_ratio[key].GetYaxis().SetLabelSize(0.18)
h_ratio[key].GetYaxis().SetTitle('DATA/MC')
h_ratio[key].GetYaxis().SetTitleSize(0.22)
h_ratio[key].GetYaxis().SetTitleOffset(0.2)
h_ratio[key].GetYaxis().SetNdivisions(005)
h_ratio[key].GetXaxis().SetLabelSize(0.16)
h_ratio[key].GetXaxis().SetTitleSize(0.16)
h_ratio[key].SetMaximum(1.5)
h_ratio[key].SetMinimum(0.667)
chi2Prob[key] = histos_SR[key].Chi2Test(
histo_sum_MC_BG) #, 'UW')#, 'NORM')
kolmogorovProb[key] = histos_SR[key].KolmogorovTest(histo_sum_MC_BG)
for histo in histos_SR.values():
histo.SetLineColor(ROOT.kBlack)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kBlack)
histo.SetMarkerStyle(20)
for histo in histos_SR1.values() + histos_Signal1.values():
histo.SetLineColor(ROOT.kBlue)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kBlue)
histo.SetMarkerStyle(22)
for histo in histos_SR2.values() + histos_Signal2.values():
histo.SetLineColor(ROOT.kRed)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kRed)
histo.SetMarkerStyle(23)
for histo in histos_Signal.values():
histo.SetLineColor(ROOT.kBlack)
histo.SetLineWidth(2)
# histo.SetMarkerColor(ROOT.kBlack)
# histo.SetMarkerStyle(21)
for histo in histos_BG.values():
histo.SetLineColor(ROOT.kRed)
histo.SetLineWidth(2)
histo.SetFillColor(ROOT.kRed)
# histo.SetMarkerColor(ROOT.kRed)
# histo.SetMarkerStyle(22)
# for histo in histos_RSB.values():
# histo.SetLineColor(ROOT.kViolet)
# histo.SetLineWidth(2)
for histo in histos_MC.values():
histo.SetLineColor(ROOT.kBlue)
histo.SetLineWidth(2)
histo.SetFillColor(ROOT.kBlue)
# histo.SetMarkerColor(ROOT.kBlue)
# histo.SetMarkerStyle(20)
outputFile = TFile(output_name + '_plots.root', 'RECREATE')
for histo in histos_Signal.values() + histos_MC.values(
) + histos_BG.values() + histos_SR.values():
histo.Write()
outputFile.Close()
canvas = TCanvas("canvas", "canvas")
canvas.Print(outputFile_name + "[") #apre file .ps
for key in keys:
pad1 = TPad("pad1", "The pad 80% of the height", 0.0, 0.2, 1.0, 1.0)
pad1.cd()
pad1.SetLogy(logY[key])
hs = THStack('hs', titles[key])
#hs.Add(histos_SR[key])
#hs.Add(histos_Signal[key])
hs.Add(histos_BG[key])
hs.Add(histos_MC[key])
#hs.Add(histos_LSB[key])
#hs.Add(histos_RSB[key])
#maxHisto = max(hs.GetMaximum(), histos_SR[key].GetMaximum())
hs.SetMaximum(maxY[key]) #maxHisto)
hs.Draw('HIST')
histos_SR[key].Draw('same')
leg = pad1.BuildLegend(.65, .93, .95, .7)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.Draw("SAME")
pad2 = TPad("pad2", "The pad 20% of the height", 0.0, 0.01, 1.0, 0.2)
pad2.cd()
h_ratio[key].Draw()
xmin = h_ratio[key].GetBinLowEdge(1)
xmax = h_ratio[key].GetBinLowEdge(
h_ratio[key].GetNbinsX()) + h_ratio[key].GetBinWidth(
h_ratio[key].GetNbinsX())
line0 = TLine(xmin, 1, xmax, 1)
line0.SetLineColor(ROOT.kBlue)
line0.SetLineWidth(2)
line0.Draw('same')
canvas.cd()
pad1.Draw()
pad2.Draw()
canvas.Update()
canvas.Print(outputFile_name)
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.png')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.pdf')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.root')
# Make comparisison between chib1 and chib2
histos_SR1[key].Scale(1. / histos_SR1[key].Integral())
histos_SR2[key].Scale(1. / histos_SR2[key].Integral())
histos_Signal1[key].Scale(1. / histos_Signal1[key].Integral())
histos_Signal2[key].Scale(1. / histos_Signal2[key].Integral())
# histos_SR1[key].Rebin(3)
# histos_SR2[key].Rebin(3)
# histos_Signal1[key].Rebin(3)
# histos_Signal2[key].Rebin(3)
hsc = THStack('hsc', titles_chib[key])
hsc.Add(histos_Signal1[key])
hsc.Add(histos_Signal2[key])
#hsc.SetMaximum(maxY[key])
hsc.Draw('nostack')
legc = canvas.BuildLegend(.65, .93, .95, .7)
legc.SetFillStyle(0)
legc.SetBorderSize(0)
legc.Draw("SAME")
print 'kolmogorov prob SR ' + key + ' ' + str(
histos_SR1[key].KolmogorovTest(histos_SR2[key]))
print 'kolmogorov prob Signal ' + key + ' ' + str(
histos_Signal1[key].KolmogorovTest(histos_Signal2[key]))
cfr = 2 if key not in ['dimuon_pt', 'chib_pt'] else 5
kolmogorovProb_chi = round(
histos_Signal1[key].KolmogorovTest(histos_Signal2[key]), cfr)
pvtxt = TPaveText(.2, .0, 0.5, 0.1, "NDC")
pvtxt.SetFillStyle(0)
pvtxt.SetBorderSize(0)
pvtxt.SetTextSize(0.04)
pvtxt.AddText('Kolmogorov prob = ' + str(kolmogorovProb_chi))
pvtxt.Draw()
canvas.Update()
canvas.Print(outputFile_name)
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.png')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.pdf')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.root')
canvas.Clear()
canvas.Print(outputFile_name + "]") #chiude file .ps
for key in keys:
print '\n'
print key + ' Kolmogorov probability: ' + str(chi2Prob[key])
print key + ' chiSqure probability: ' + str(kolmogorovProb[key])
#print 'Kolmogorov probability with sidebands: '+str(histos_MC['dimuon_pt'].KolmogorovTest(histos_LSB['dimuon_pt'])) #
inputFile.Close()
