def plotHoTime(self):
c3 = TCanvas("c3","HO Time",1200,1200)
skipNoisePlot = False
if not skipNoisePlot:
c3.Divide(1,2)
c3.cd(1).SetLogy()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTime = self.fileHandler.getHistogram('hoRecHits_Time')
hHoTime.SetStats(0)
hHoTime.SetTitle("Time distribution for all HO Rec Hits")
hHoTime.SetLineColor(colorRwthDarkBlue)
hHoTime.SetLineWidth(3)
hHoTime.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTimeAboveThr = self.fileHandler.getHistogram('hoRecHitsAboveThr_Time')
c3.cd(2).SetLogy()
hHoTimeAboveThr.SetStats(0)
hHoTimeAboveThr.SetTitle("Time distribution for HO Rec Hits > 0.2 GeV")
hHoTimeAboveThr.SetLineColor(colorRwthDarkBlue)
hHoTimeAboveThr.SetLineWidth(3)
setupAxes(hHoTimeAboveThr)
hHoTimeAboveThr.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
self.debug(80*'#')
self.debug( 'Integral of HO > 0.2 GeV time histogram:')
self.debug( hHoTimeAboveThr.Integral())
self.debug('')
xLow = -5
xHigh = 5
histogramBetween = hHoTimeAboveThr.Integral(hHoTimeAboveThr.FindBin(xLow),hHoTimeAboveThr.FindBin(xHigh))
histogramTotal = float(hHoTimeAboveThr.Integral())
self.debug( 'Histogram integral between %.f ns and %.f ns' % (xLow,xHigh) )
self.debug( '%d/%d => %.2f +/- %f' % (histogramBetween,histogramTotal
,histogramBetween/histogramTotal,calcSigma(histogramBetween, histogramTotal)))
self.debug( 80*'#')
fit = TF1("fit","gaus",-10,10)
hHoTimeAboveThr.Fit(fit)
pText = TPaveText(0.7,0.8,0.9,0.9,'NDC')
pText.AddText('Mean: %.2f ns' % (fit.GetParameter(1)))
pText.AddText('#sigma: %.2f ns' % (fit.GetParameter(2)))
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
c3.Update()
self.storeCanvas(c3,"hoTime")
return c3,label,hHoTimeAboveThr,pText
def plotHoTime(self):
c3 = TCanvas("c3","HO Time",1200,1200)
skipNoisePlot = False
if not skipNoisePlot:
c3.Divide(1,2)
c3.cd(1).SetLogy()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTime = self.fileHandler.getHistogram('hoRecHits_Time')
hHoTime.SetStats(0)
hHoTime.SetTitle("Time distribution for all HO Rec Hits")
hHoTime.SetLineColor(colorRwthDarkBlue)
hHoTime.SetLineWidth(3)
hHoTime.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTimeAboveThr = self.fileHandler.getHistogram('hoRecHitsAboveThr_Time')
c3.cd(2).SetLogy()
hHoTimeAboveThr.SetStats(0)
hHoTimeAboveThr.SetTitle("Time distribution for HO Rec Hits > 0.2 GeV")
hHoTimeAboveThr.SetLineColor(colorRwthDarkBlue)
hHoTimeAboveThr.SetLineWidth(3)
setupAxes(hHoTimeAboveThr)
hHoTimeAboveThr.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
self.debug(80*'#')
self.debug( 'Integral of HO > 0.2 GeV time histogram:')
self.debug( hHoTimeAboveThr.Integral())
self.debug('')
xLow = -5
xHigh = 5
histogramBetween = hHoTimeAboveThr.Integral(hHoTimeAboveThr.FindBin(xLow),hHoTimeAboveThr.FindBin(xHigh))
histogramTotal = float(hHoTimeAboveThr.Integral())
self.debug( 'Histogram integral between %.f ns and %.f ns' % (xLow,xHigh) )
self.debug( '%d/%d => %.2f +/- %f' % (histogramBetween,histogramTotal
,histogramBetween/histogramTotal,calcSigma(histogramBetween, histogramTotal)))
self.debug( 80*'#')
fit = TF1("fit","gaus",-10,10)
hHoTimeAboveThr.Fit(fit)
pText = TPaveText(0.7,0.8,0.9,0.9,'NDC')
pText.AddText('Mean: %.2f ns' % (fit.GetParameter(1)))
pText.AddText('#sigma: %.2f ns' % (fit.GetParameter(2)))
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
c3.Update()
self.storeCanvas(c3,"hoTime")
return c3,label,hHoTimeAboveThr,pText
def plotHoTimeLog(self):
c3 = TCanvas("c3Log","HO Time Log",1200,1200)
skipNoisePlot = True
if not skipNoisePlot:
c3.Divide(1,2)
c3.cd(1).SetLogy()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTime = self.fileHandler.getHistogram('hoRecHits_Time')
hHoTime.SetStats(0)
hHoTime.SetTitle()
hHoTime.SetLineColor(colorRwthDarkBlue)
hHoTime.SetLineWidth(3)
hHoTime.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTimeAboveThr = self.fileHandler.getHistogram('hoRecHitsAboveThr_Time')
c3.cd(2).SetLogy()
hHoTimeAboveThr.SetStats(0)
hHoTimeAboveThr.SetTitle('')
hHoTimeAboveThr.SetLineColor(colorRwthDarkBlue)
hHoTimeAboveThr.SetLineWidth(3)
hHoTimeAboveThr.GetXaxis().SetRangeUser(-50,50)
setupAxes(hHoTimeAboveThr)
hHoTimeAboveThr.Draw()
fit = TF1("fit","gaus",-10,10)
fit.SetParameter(1,0)
fit.SetParameter(2,1)
fit.SetLineWidth(3)
hHoTimeAboveThr.Fit(fit,'','R',-12.5,7)
self.debug(80*'#')
self.debug('Chi^2: %5.2f' % fit.GetChisquare())
self.debug('NDF: %d' % fit.GetNDF())
self.debug(80*'#')
legend = getLegend(x1=.1, y1=.85, x2=.415, y2=.95)
legend.AddEntry(hHoTimeAboveThr,'HO (E_{Rec} > 0.2 GeV)','l')
legend.AddEntry(fit,'Fit','l')
legend.Draw()
pText = TPaveText(0.78,0.85,0.97,0.95,'NDC')
pText.AddText('Mean: %.2f ns' % (fit.GetParameter(1)))
pText.AddText('#sigma: %.2f ns' % (fit.GetParameter(2)))
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
c3.Update()
self.storeCanvas(c3,"hoTimeLog",marginRight=.03)
return c3,pText,hHoTimeAboveThr,legend
def plotHoTimeLog(self):
c3 = TCanvas("c3Log","HO Time Log",1200,1200)
skipNoisePlot = True
if not skipNoisePlot:
c3.Divide(1,2)
c3.cd(1).SetLogy()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTime = self.fileHandler.getHistogram('hoRecHits_Time')
hHoTime.SetStats(0)
hHoTime.SetTitle("Time distribution for all HO Rec Hits")
hHoTime.SetLineColor(colorRwthDarkBlue)
hHoTime.SetLineWidth(3)
hHoTime.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTimeAboveThr = self.fileHandler.getHistogram('hoRecHitsAboveThr_Time')
c3.cd(2).SetLogy()
hHoTimeAboveThr.SetStats(0)
hHoTimeAboveThr.SetTitle("Time distribution for HO Rec Hits > 0.2 GeV")
hHoTimeAboveThr.SetLineColor(colorRwthDarkBlue)
hHoTimeAboveThr.SetLineWidth(3)
setupAxes(hHoTimeAboveThr)
hHoTimeAboveThr.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
fit = TF1("fit","gaus",-10,10)
fit.SetParameter(1,0)
fit.SetParameter(2,1)
hHoTimeAboveThr.Fit(fit,'','R',-12.5,12.5)
self.debug(80*'#')
self.debug('Chi^2: %5.2f' % fit.GetChisquare())
self.debug('NDF: %d' % fit.GetNDF())
self.debug(80*'#')
pText = TPaveText(0.7,0.8,0.9,0.9,'NDC')
pText.AddText('Mean: %.2f ns' % (fit.GetParameter(1)))
pText.AddText('#sigma: %.2f ns' % (fit.GetParameter(2)))
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
c3.Update()
self.storeCanvas(c3,"hoTimeLog")
return c3,pText,hHoTimeAboveThr
def plotHoTimeLog(self):
c3 = TCanvas("c3Log","HO Time Log",1200,1200)
skipNoisePlot = True
if not skipNoisePlot:
c3.Divide(1,2)
c3.cd(1).SetLogy()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTime = self.fileHandler.getHistogram('hoMuonAnalyzer/hoRecHits_Time')
hHoTime.SetStats(0)
hHoTime.SetTitle("Time distribution for all HO Rec Hits")
hHoTime.SetLineColor(colorRwthDarkBlue)
hHoTime.SetLineWidth(3)
hHoTime.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
hHoTimeAboveThr = self.fileHandler.getHistogram('hoMuonAnalyzer/hoRecHitsAboveThr_Time')
c3.cd(2).SetLogy()
hHoTimeAboveThr.SetStats(0)
hHoTimeAboveThr.SetTitle("Time distribution for HO Rec Hits > 0.2 GeV")
hHoTimeAboveThr.SetLineColor(colorRwthDarkBlue)
hHoTimeAboveThr.SetLineWidth(3)
setupAxes(hHoTimeAboveThr)
hHoTimeAboveThr.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
fit = TF1("fit","gaus",-10,10)
fit.SetParameter(1,0)
fit.SetParameter(2,1)
hHoTimeAboveThr.Fit(fit,'','R',-12.5,12.5)
self.output(80*'#')
self.output('Chi^2: %5.2f' % fit.GetChisquare())
self.output('NDF: %d' % fit.GetNDF())
self.output(80*'#')
pText = TPaveText(0.7,0.8,0.9,0.9,'NDC')
pText.AddText('Mean: %.2f ns' % (fit.GetParameter(1)))
pText.AddText('#sigma: %.2f ns' % (fit.GetParameter(2)))
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
c3.Update()
self.storeCanvas(c3,"hoTimeLog")
return c3,pText,hHoTimeAboveThr
def plotFractionInTimeWindow():
c = TCanvas("cFraction","Fraction in Time Window",900,900)
fileVaried = TFile.Open('condor/FractionTimeWindow.root')
if(fileVaried.IsZombie()):
print 'Error opening file: condor/FractionTimeWindow.root'
sys.exit(1)
hVaried = fileVaried.Get('hist')
min = 94
max = 99.6
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('Fraction of HO Rec Hits in [-12.5,12.5], GEN cone varied')
hVaried.Draw('colz')
label = getLabelCmsPrivateSimulation()
label.Draw()
c.Update()
c.SaveAs('fractionInTimeWindow.pdf')
c.SaveAs('fractionInTimeWindow.png')
return fileVaried,c,hVaried,label
def plotRecHitVsDigiTime():
canvas = TCanvas("canvasRecHitVsDigi", "RecHitTime Vs Simple Digi", 1200,
1200)
hoDigiTime = fileHandler.getGraph(
'hoDigiAnalyzer/correlation/hoTimeRecHitVsDigi')
setupAxes(hoDigiTime)
hoDigiTime.GetXaxis().SetTitle('digi time / ns')
hoDigiTime.GetYaxis().SetTitle('rec hit time / ns')
hoDigiTime.GetYaxis().SetTitleOffset(1.2)
hoDigiTime.SetMarkerStyle(6)
hoDigiTime.SetMarkerColor(colorRwthDarkBlue)
hoDigiTime.SetTitle('HORecHit time vs. simple digi time estimation')
hoDigiTime.Draw('ap')
#Label for CMS private
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiTimeVsRecHitTime.png')
return canvas, label, hoDigiTime
def plotPtAndPhiOfWrongBxId(self):
#Prepare canvas
canvas = TCanvas("canvasPtPhiBxWrong","PtPhiBxWrong",1200,1200)
canvas.cd().Draw()
#prepare histogram
hist = self.fileHandler.getHistogram("etaPhi/3D/BxWrongGen_EtaPhiPt")
stack = THStack(hist,"zy","2dStack","",-1,-1,-1,-1,"zy","")
#Create new histogram and add the histograms from the stack
histNew = TH2D("histPtPhiBxWrong","p_{T} vs. #phi distribution for wrong BX ID;#phi;p_{T} / 5 GeV;#",80,-3.2,3.2,40,0,200)
histNew.GetYaxis().SetTitleOffset(1.2)
for i in stack.GetHists():
histNew.Add(i)
gStyle.SetPalette(1)
histNew.SetStats(0)
setupAxes(histNew)
histNew.Draw('COLZ')
canvas.Update()
palette = histNew.FindObject("palette")
palette.SetX1NDC(0.9)
palette.SetX2NDC(0.92)
#add label
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.Update()
self.storeCanvas(canvas,"bxWrongPtPhi")
return canvas,hist,stack,histNew,label
def plotAverageEMaxAroundL1(self):
canvas = TCanvas('canvasAverageEMax','Average EMax',1200,1200)
canvas.cd().SetLogz()
hSum = self.fileHandler.getHistogram('hoMuonAnalyzer/deltaEtaDeltaPhiEnergy/averageEMaxAroundPoint' + self.key + '_2dSummedWeights')
hCounter = self.fileHandler.getHistogram('hoMuonAnalyzer/deltaEtaDeltaPhiEnergy/averageEMaxAroundPoint' + self.key + '_2dCounter')
hSum = setupEAvplot(hSum, hCounter,same=True,limitForAll=0.3)
hSum.SetTitle('Mean E_{Max} in HO tiles around L1 direction')
hSum.SetMaximum(2)
hSum.Draw('colz')
setupEAvplot(hCounter,same=True,limitForAll=0.3).Draw('same,text')
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.Update()
setupPalette(hSum)
canvas.Update()
self.storeCanvas(canvas, 'averageEmax')
hCounter.SaveAs('histogramEMaxCounter.root')
return canvas,hSum,label,hCounter
def plotAverageEMaxAroundL1(self):
canvas = TCanvas('canvasAverageEMax','Average EMax',1200,1200)
canvas.cd().SetLogz()
hSum = self.fileHandler.getHistogram('deltaEtaDeltaPhiEnergy/averageEMaxAroundPoint' + self.key + '_2dSummedWeights')
hCounter = self.fileHandler.getHistogram('deltaEtaDeltaPhiEnergy/averageEMaxAroundPoint' + self.key + '_2dCounter')
hSum = setupEAvplot(hSum, hCounter,same=True,limitForAll=0.3)
hSum.SetTitle('Mean E_{Max} in HO tiles around L1 direction')
hSum.SetMaximum(2)
hSum.Draw('colz')
setupEAvplot(hCounter,same=True,limitForAll=0.3).Draw('same,text')
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.Update()
setupPalette(hSum)
canvas.Update()
self.storeCanvas(canvas, 'averageEmax')
hCounter.SaveAs('histogramEMaxCounter.root')
return canvas,hSum,label,hCounter
def plotPtAndPhiOfWrongBxId(self):
#Prepare canvas
canvas = TCanvas("canvasPtPhiBxWrong","PtPhiBxWrong",1200,1200)
canvas.cd().Draw()
#prepare histogram
hist = self.fileHandler.getHistogram("etaPhi/3D/BxWrongGen_EtaPhiPt")
stack = THStack(hist,"zy","2dStack","",-1,-1,-1,-1,"zy","")
#Create new histogram and add the histograms from the stack
histNew = TH2D("histPtPhiBxWrong","p_{T} vs. #phi distribution for wrong BX ID;#phi;p_{T} / 5 GeV;#",80,-3.2,3.2,40,0,200)
histNew.GetYaxis().SetTitleOffset(1.2)
for i in stack.GetHists():
histNew.Add(i)
gStyle.SetPalette(1)
histNew.SetStats(0)
setupAxes(histNew)
histNew.Draw('COLZ')
canvas.Update()
palette = histNew.FindObject("palette")
palette.SetX1NDC(0.9)
palette.SetX2NDC(0.92)
#add label
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.Update()
self.storeCanvas(canvas,"bxWrongPtPhi")
return canvas,hist,stack,histNew,label
def plotFractionInTimeWindow():
c = TCanvas("cFraction", "Fraction in Time Window", 900, 900)
fileVaried = TFile.Open('condor/FractionTimeWindow.root')
if (fileVaried.IsZombie()):
print 'Error opening file: condor/FractionTimeWindow.root'
sys.exit(1)
hVaried = fileVaried.Get('hist')
min = 94
max = 99.6
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle(
'Fraction of HO Rec Hits in [-12.5,12.5], GEN cone varied')
hVaried.Draw('colz')
label = getLabelCmsPrivateSimulation()
label.Draw()
c.Update()
c.SaveAs('fractionInTimeWindow.pdf')
c.SaveAs('fractionInTimeWindow.png')
return fileVaried, c, hVaried, label
def plotHoMatchEfficiency():
c = TCanvas("cHoEff","hoEff",1800,900)
c.Divide(2,1)
fileVaried = TFile.Open('condor/HoEff.root')
if(fileVaried.IsZombie()):
print 'Error opening file: condor/HoEff.root'
sys.exit(1)
fileFixed = TFile.Open('condorFixedGenDeltaR/HoEff.root')
if(fileFixed.IsZombie()):
print 'Error opening file: condorFixedGenDeltaR/HoEff.root'
sys.exit(1)
fileNL1Varied = TFile.Open('condor/Histtotal.root')
fileNL1Fixed = TFile.Open('condorFixedGenDeltaR/Histtotal.root')
histNL1Varied = fileNL1Varied.Get('histTotalTruth')
histNL1Varied.SetName('histTotalTruthVaried')
histNL1Fixed = fileNL1Fixed.Get('histTotalTruth')
histNL1Fixed.SetName('histTotalTruthFixed')
hVaried = fileVaried.Get('histEff')
hVaried.SetName('histEffVaried')
hFixed = fileFixed.Get('histEff')
hFixed.SetName('histEffFixed')
min = 18
max = 100
label = getLabelCmsPrivateSimulation()
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('HO matched to "true" L1, GEN cone varied')
hVaried.Draw('colz')
label.Draw()
# histNL1Varied.Draw('Same,box')
c.cd(2)
hFixed.SetMinimum(min)
hFixed.SetMaximum(max)
hFixed.SetTitle('HO matched to "true" L1, GEN cone fixed')
hFixed.Draw('colz')
# histNL1Fixed.Draw('same,box')
label.Draw()
c.Update()
c.SaveAs('hoMatchEfficiency.png')
c.SaveAs('hoMatchEfficiency.pdf')
return c,hFixed,hVaried,fileFixed,fileVaried,histNL1Varied,histNL1Fixed,fileNL1Fixed,fileNL1Varied,label
def plotHoMatchEfficiency():
c = TCanvas("cHoEff", "hoEff", 1800, 900)
c.Divide(2, 1)
fileVaried = TFile.Open('condor/HoEff.root')
if (fileVaried.IsZombie()):
print 'Error opening file: condor/HoEff.root'
sys.exit(1)
fileFixed = TFile.Open('condorFixedGenDeltaR/HoEff.root')
if (fileFixed.IsZombie()):
print 'Error opening file: condorFixedGenDeltaR/HoEff.root'
sys.exit(1)
fileNL1Varied = TFile.Open('condor/Histtotal.root')
fileNL1Fixed = TFile.Open('condorFixedGenDeltaR/Histtotal.root')
histNL1Varied = fileNL1Varied.Get('histTotalTruth')
histNL1Varied.SetName('histTotalTruthVaried')
histNL1Fixed = fileNL1Fixed.Get('histTotalTruth')
histNL1Fixed.SetName('histTotalTruthFixed')
hVaried = fileVaried.Get('histEff')
hVaried.SetName('histEffVaried')
hFixed = fileFixed.Get('histEff')
hFixed.SetName('histEffFixed')
min = 18
max = 100
label = getLabelCmsPrivateSimulation()
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('HO matched to "true" L1, GEN cone varied')
hVaried.Draw('colz')
label.Draw()
# histNL1Varied.Draw('Same,box')
c.cd(2)
hFixed.SetMinimum(min)
hFixed.SetMaximum(max)
hFixed.SetTitle('HO matched to "true" L1, GEN cone fixed')
hFixed.Draw('colz')
# histNL1Fixed.Draw('same,box')
label.Draw()
c.Update()
c.SaveAs('hoMatchEfficiency.png')
c.SaveAs('hoMatchEfficiency.pdf')
return c, hFixed, hVaried, fileFixed, fileVaried, histNL1Varied, histNL1Fixed, fileNL1Fixed, fileNL1Varied, label
def compareHistogramMethods(self):
canvas = TCanvas('cComparison','Comparison btween histograms')
# canvas.Divide(2,1)
histNormal = self.fileHandler.getHistogram('averageEnergy/averageEnergyAroundPoint' + self.key + '_SummedEnergy')
histNormalCounter = self.fileHandler.getHistogram('averageEnergy/averageEnergyAroundPoint' + self.key + '_Counter')
histNormal = setupEAvplot(histNormal, histNormalCounter,same=True,limitForAll=0.6)
# histNew = self.fileHandler.getHistogram('deltaEtaDeltaPhiEnergy/averageEnergyAroundPoint_2dSummedWeightsIEtaIPhi')
# histNewCounter = self.fileHandler.getHistogram('deltaEtaDeltaPhiEnergy/averageEnergyAroundPoint_2dCounterIEtaIPhi')
canvas.cd(1).SetLogz()
histNormal.SetTitle('Average Energy in HO tiles around L1 direction, i#eta by binning')
histNormal.SetStats(1)
histNormal.Draw('colz')
label = getLabelCmsPrivateSimulation()
label.Draw()
# canvas.cd(2).SetLogz()
# histNew = average2DHistogramBinwise(histNew, histNewCounter)
# histNew.GetXaxis().SetRangeUser(-8,8)
# histNew.GetYaxis().SetRangeUser(-8,8)
# histNew.GetXaxis().SetTitle('#Delta#eta')
# histNew.GetYaxis().SetTitle('#Delta#phi')
# histNew.GetZaxis().SetTitle('Reconstructed Energy / GeV')
# histNew.SetTitle('Mean Energy in HO tiles around L1 direction, i#eta by binning')
# histNew.Draw('colz')
# label2 = getLabelCmsPrivateSimulation()
# label2.Draw()
canvas.Update()
#Setup plot style
setStatBoxOptions(histNormal,1100)
setStatBoxPosition(histNormal)
setupPalette(histNormal)
# setupAxes(histNew)
# setStatBoxOptions(histNew,1100)
# setStatBoxPosition(histNew)
# setupPalette(histNew)
canvas.Update()
#TODO: Print the bin contents subtracted
return canvas, histNormal,label#,histNew,label2
def compareHistogramMethods(self):
canvas = TCanvas('cComparison','Comparison btween histograms')
# canvas.Divide(2,1)
histNormal = self.fileHandler.getHistogram('averageEnergy/averageEnergyAroundPoint' + self.key + '_SummedEnergy')
histNormalCounter = self.fileHandler.getHistogram('averageEnergy/averageEnergyAroundPoint' + self.key + '_Counter')
histNormal = setupEAvplot(histNormal, histNormalCounter,same=True,limitForAll=0.6)
# histNew = self.fileHandler.getHistogram('deltaEtaDeltaPhiEnergy/averageEnergyAroundPoint_2dSummedWeightsIEtaIPhi')
# histNewCounter = self.fileHandler.getHistogram('deltaEtaDeltaPhiEnergy/averageEnergyAroundPoint_2dCounterIEtaIPhi')
canvas.cd(1).SetLogz()
histNormal.SetTitle('Average Energy in HO tiles around L1 direction, i#eta by binning')
histNormal.SetStats(1)
histNormal.Draw('colz')
label = getLabelCmsPrivateSimulation()
label.Draw()
# canvas.cd(2).SetLogz()
# histNew = average2DHistogramBinwise(histNew, histNewCounter)
# histNew.GetXaxis().SetRangeUser(-8,8)
# histNew.GetYaxis().SetRangeUser(-8,8)
# histNew.GetXaxis().SetTitle('#Delta#eta')
# histNew.GetYaxis().SetTitle('#Delta#phi')
# histNew.GetZaxis().SetTitle('Reconstructed Energy / GeV')
# histNew.SetTitle('Mean Energy in HO tiles around L1 direction, i#eta by binning')
# histNew.Draw('colz')
# label2 = getLabelCmsPrivateSimulation()
# label2.Draw()
canvas.Update()
#Setup plot style
setStatBoxOptions(histNormal,1100)
setStatBoxPosition(histNormal)
setupPalette(histNormal)
# setupAxes(histNew)
# setStatBoxOptions(histNew,1100)
# setStatBoxPosition(histNew)
# setupPalette(histNew)
canvas.Update()
#TODO: Print the bin contents subtracted
return canvas, histNormal,label#,histNew,label2
def plotRpcVsHo():
hist =fileHandler.getHistogram('hoMuonAnalyzer/correlation/RpcHoAboveThr_TimeCorrelation')
canvas = TCanvas('canvasRpcVsHo',"RPC vs. HO",1200,1200)
canvas.cd().SetLogz()
histNew = getTH2D("histRpcVsHo","RPC BX ID vs. HO > E_{Thr};HO time / ns;BX ID",5,-37.5,87.5#24,-56.25,93.75
,5,-2.5,2.5)
xAxis = hist.GetXaxis()
yAxis = hist.GetYaxis()
nBinsX = xAxis.GetNbins()
nBinsY = yAxis.GetNbins()
#Fill new histogram with fewer bins
for i in range( 1 , nBinsX + 1 ):
for j in range( 1 , nBinsY + 1 ):
histNew.Fill(xAxis.GetBinCenter(i),yAxis.GetBinCenter(j)/25.,hist.GetBinContent(i,j))
histNew.SetStats(0)
histNew.Draw('colz')
canvas.Update()
pal = histNew.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
#Calcualte fraction at (0,0)
nCentral = histNew.GetBinContent(histNew.FindBin(0,0))
nTotal = histNew.Integral()
fraction = nCentral/float(nTotal)
fractionUncert = calcSigma(nCentral,nTotal)
sliceFraction = 0
for i in range(0,5):
sliceFraction += histNew.GetBinContent(histNew.FindBin(0,-2.5+i))
sliceFractionUncert = calcSigma(sliceFraction,nTotal)
sliceFraction /= nTotal
paveTextAboveThr = TPaveText(0.1,0.8,0.5,0.9,'NDC')
paveTextAboveThr.AddText('Fraction at (0,0): %5.2f%% #pm %5.2f%%' % (fraction*100, fractionUncert*100))
paveTextAboveThr.AddText('Fraction at (0,x): %5.2f%% #pm %5.2f%%' % (sliceFraction*100, sliceFractionUncert*100))
paveTextAboveThr.SetBorderSize(1)
paveTextAboveThr.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.SaveAs('plots/timeCorrelation/rpcVsHo.pdf')
canvas.SaveAs('plots/timeCorrelation/rpcVsHo.png')
return hist,canvas,paveTextAboveThr,label
def plotCorrectedL1MatchEfficiency():
c = TCanvas("cL1EffCorrected", "L1EffCorected", 1800, 900)
c.Divide(2, 1)
fileVaried = TFile.Open('condor/L1Eff.root')
if (fileVaried.IsZombie()):
print 'Error opening file: condor/L1Eff.root'
sys.exit(1)
hVaried = fileVaried.Get('histL1Eff')
hOriginal = hVaried.Clone('clone')
hVaried.SetName('histL1EffVariedCorrected')
min = 0
max = 100
label = getLabelCmsPrivateSimulation()
correctionsFile = open('geometricEfficiencies.txt')
correctionsList = []
for line in correctionsFile.readlines():
if line.startswith('#'):
continue
correctionsList.append(float((line.split())[1]))
print correctionsList
print hVaried.GetNbinsX()
for i in range(2, hVaried.GetNbinsX()):
for j in range(2, hVaried.GetNbinsY()):
if (correctionsList[i - 2] != 0):
print hVaried.GetBinContent(i, j), hVaried.GetBinContent(
i, j) / correctionsList[i - 2] * 100, correctionsList[i -
2]
hVaried.SetBinContent(
i, j,
hVaried.GetBinContent(i, j) / correctionsList[i - 2] * 100)
c.cd(1)
hOriginal.SetMinimum(min)
hOriginal.SetMaximum(max)
hOriginal.Draw('colz')
c.cd(2)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('L1 matched to GEN, GEN cone varied, Corrected')
hVaried.Draw('colz')
label.Draw()
c.Update()
c.SaveAs('L1MatchEfficiencyCorr.png')
c.SaveAs('L1MatchEfficiencyCorr.pdf')
return c, hVaried, fileVaried, label
def plotCorrectedL1MatchEfficiency():
c = TCanvas("cL1EffCorrected","L1EffCorected",1800,900)
c.Divide(2,1)
fileVaried = TFile.Open('condor/L1Eff.root')
if(fileVaried.IsZombie()):
print 'Error opening file: condor/L1Eff.root'
sys.exit(1)
hVaried = fileVaried.Get('histL1Eff')
hOriginal = hVaried.Clone('clone')
hVaried.SetName('histL1EffVariedCorrected')
min = 0
max = 100
label = getLabelCmsPrivateSimulation()
correctionsFile = open('geometricEfficiencies.txt')
correctionsList = []
for line in correctionsFile.readlines():
if line.startswith('#'):
continue
correctionsList.append(float((line.split())[1]))
print correctionsList
print hVaried.GetNbinsX()
for i in range(2,hVaried.GetNbinsX()):
for j in range(2,hVaried.GetNbinsY()):
if(correctionsList[i-2] != 0):
print hVaried.GetBinContent(i,j),hVaried.GetBinContent(i,j)/correctionsList[i-2]*100,correctionsList[i-2]
hVaried.SetBinContent(i,j,
hVaried.GetBinContent(i,j)/correctionsList[i-2]*100
)
c.cd(1)
hOriginal.SetMinimum(min)
hOriginal.SetMaximum(max)
hOriginal.Draw('colz')
c.cd(2)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('L1 matched to GEN, GEN cone varied, Corrected')
hVaried.Draw('colz')
label.Draw()
c.Update()
c.SaveAs('L1MatchEfficiencyCorr.png')
c.SaveAs('L1MatchEfficiencyCorr.pdf')
return c,hVaried,fileVaried,label
def plotProduct():
c = TCanvas("cProduct", "product", 1800, 900)
c.Divide(2, 1)
fileVaried = TFile.Open('condor/product.root')
if (fileVaried.IsZombie()):
print 'Error opening file: condor/product.root'
sys.exit(1)
fileFixed = TFile.Open('condorFixedGenDeltaR/product.root')
if (fileFixed.IsZombie()):
print 'Error opening file: condorFixedGenDeltaR/product.root'
sys.exit(1)
hVaried = fileVaried.Get('histEffp')
hVaried.SetName('histEffpVaried')
hFixed = fileFixed.Get('histEffp')
min = 15
max = 97
label = getLabelCmsPrivateSimulation()
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle(
'Fraction in TimeWindow #times HO matched to "true" L1, GEN cone varied'
)
hVaried.Draw('colz')
label.Draw()
c.cd(2)
hFixed.SetMinimum(min)
hFixed.SetMaximum(max)
hFixed.SetTitle(
'Fraction in TimeWindow #times HO matched to "true" L1, GEN cone fixed'
)
hFixed.Draw('colz')
label.Draw()
c.Update()
c.SaveAs('productTimeWindowAndEfficiency.png')
c.SaveAs('productTimeWindowAndEfficiency.pdf')
return c, hVaried, hFixed, fileFixed, fileVaried, label
def plotDigiDeltaTime():
canvas = TCanvas("canvasDigiDeltaTime", "Simple Digi Delta Time", 1200,
1200)
canvas.SetLogy()
histHoTime = fileHandler.getHistogram(
'hoDigiAnalyzer/hoTimeFromDigi_DeltaTime')
setupAxes(histHoTime)
histHoTime.GetXaxis().SetTitle('#Deltatime / ns')
histHoTime.SetLineColor(colorRwthDarkBlue)
histHoTime.SetStats(0)
histHoTime.SetLineWidth(3)
histHoTime.SetTitle(
'#DeltaTime of L1 and simple time reconstruction from HO digi')
histHoTime.Draw()
#Label for CMS private
label = getLabelCmsPrivateSimulation()
label.Draw()
#Add legend
legend = TLegend(0.65, 0.75, 0.9, 0.9)
legend.AddEntry(histHoTime, "L1 - Digi time", "l")
legend.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiTimeDeltaTime.pdf')
canvas.SaveAs('plots/timing/digiTimeDeltaTime.png')
histRecHitTime = fileHandler.getHistogram(
'hoMuonAnalyzer/L1MuonAboveThr_DeltaTime')
histRecHitTime.SetLineColor(colorRwthMagenta)
histRecHitTime.SetLineWidth(3)
histRecHitTime.Draw('same')
legend.AddEntry(histRecHitTime, "L1 - RecHit time", "l")
legend.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiTimeDeltaTimePlusRecHit.pdf')
canvas.SaveAs('plots/timing/digiTimeDeltaTimePlusRecHit.png')
return canvas, label, histHoTime, histRecHitTime, legend
def plotL1MatchEfficiency():
c = TCanvas("cL1Eff", "L1Eff", 1800, 900)
c.Divide(2, 1)
fileVaried = TFile.Open('condor/L1Eff.root')
if (fileVaried.IsZombie()):
print 'Error opening file: condor/L1Eff.root'
sys.exit(1)
fileFixed = TFile.Open('condorFixedGenDeltaR/L1Eff.root')
if (fileFixed.IsZombie()):
print 'Error opening file: condorFixedGenDeltaR/L1Eff.root'
sys.exit(1)
hVaried = fileVaried.Get('histL1Eff')
hVaried.SetName('histL1EffVaried')
hFixed = fileFixed.Get('histL1Eff')
min = 0
max = 100
label = getLabelCmsPrivateSimulation()
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('L1 matched to GEN, GEN cone varied')
hVaried.Draw('colz')
label.Draw()
c.cd(2)
hFixed.SetMinimum(min)
hFixed.SetMaximum(max)
hFixed.SetTitle('L1 matched to GEN, GEN cone fixed')
hFixed.Draw('colz')
label.Draw()
c.Update()
c.SaveAs('L1MatchEfficiency.png')
c.SaveAs('L1MatchEfficiency.pdf')
return c, hFixed, hVaried, fileFixed, fileVaried, label
def plotProduct():
c = TCanvas("cProduct","product",1800,900)
c.Divide(2,1)
fileVaried = TFile.Open('condor/product.root')
if(fileVaried.IsZombie()):
print 'Error opening file: condor/product.root'
sys.exit(1)
fileFixed = TFile.Open('condorFixedGenDeltaR/product.root')
if(fileFixed.IsZombie()):
print 'Error opening file: condorFixedGenDeltaR/product.root'
sys.exit(1)
hVaried = fileVaried.Get('histEffp')
hVaried.SetName('histEffpVaried')
hFixed = fileFixed.Get('histEffp')
min = 15
max = 97
label = getLabelCmsPrivateSimulation()
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('Fraction in TimeWindow #times HO matched to "true" L1, GEN cone varied')
hVaried.Draw('colz')
label.Draw()
c.cd(2)
hFixed.SetMinimum(min)
hFixed.SetMaximum(max)
hFixed.SetTitle('Fraction in TimeWindow #times HO matched to "true" L1, GEN cone fixed')
hFixed.Draw('colz')
label.Draw()
c.Update()
c.SaveAs('productTimeWindowAndEfficiency.png')
c.SaveAs('productTimeWindowAndEfficiency.pdf')
return c,hVaried,hFixed,fileFixed,fileVaried,label
def plotL1MatchEfficiency():
c = TCanvas("cL1Eff","L1Eff",1800,900)
c.Divide(2,1)
fileVaried = TFile.Open('condor/L1Eff.root')
if(fileVaried.IsZombie()):
print 'Error opening file: condor/L1Eff.root'
sys.exit(1)
fileFixed = TFile.Open('condorFixedGenDeltaR/L1Eff.root')
if(fileFixed.IsZombie()):
print 'Error opening file: condorFixedGenDeltaR/L1Eff.root'
sys.exit(1)
hVaried = fileVaried.Get('histL1Eff')
hVaried.SetName('histL1EffVaried')
hFixed = fileFixed.Get('histL1Eff')
min = 0
max = 100
label = getLabelCmsPrivateSimulation()
c.cd(1)
hVaried.SetMinimum(min)
hVaried.SetMaximum(max)
hVaried.SetTitle('L1 matched to GEN, GEN cone varied')
hVaried.Draw('colz')
label.Draw()
c.cd(2)
hFixed.SetMinimum(min)
hFixed.SetMaximum(max)
hFixed.SetTitle('L1 matched to GEN, GEN cone fixed')
hFixed.Draw('colz')
label.Draw()
c.Update()
c.SaveAs('L1MatchEfficiency.png')
c.SaveAs('L1MatchEfficiency.pdf')
return c,hFixed,hVaried,fileFixed,fileVaried,label
def plotEtaPhiOfWrongBxId(self):
canvasEtaPhiBxWrong = TCanvas("canvasEtaPhiBxWrong","canvasEtaPhiBxWrong",1200,1200)
hWrong = self.fileHandler.getHistogram('hoMuonAnalyzer/BxWrongGen_Pt')
hRight = self.fileHandler.getHistogram('hoMuonAnalyzer/BxRightGen_Pt')
nRight = hRight.Integral()
nWrong = hWrong.Integral()
nEventsWithL1 = self.fileHandler.getHistogram('hoMuonAnalyzer/count/L1MuonPresent_Count').GetBinContent(2)
etaPhiBxWrongNC = self.fileHandler.getGraph("hoMuonAnalyzer/graphs/BxWrongGen")
etaPhiBxWrong = convertToHcalCoords(etaPhiBxWrongNC)
etaPhiBxWrong.GetXaxis().SetTitle("i#eta / a.u.")
etaPhiBxWrong.GetYaxis().SetTitle("i#phi / a.u.")
etaPhiBxWrong.SetMarkerStyle(6)
etaPhiBxWrong.SetMarkerColor(colorRwthDarkBlue)
etaPhiBxWrong.SetTitle("#eta #phi plot of events with BX ID wrong")
etaPhiBxWrong.Draw("AP")
pText = TPaveText(0.7,0.85,0.9,0.9,'NDC')
pText.AddText('Events with L1 objects: %d' % (nEventsWithL1))
pText.AddText('Events in Plot: %d' % (etaPhiBxWrong.GetN()))
pText.SetBorderSize(1)
pText.Draw()
chimney1Converted = convertToHcalCoords(chimney1)
chimney2Converted = convertToHcalCoords(chimney2)
chimney1Converted.SetLineColor(colorRwthMagenta)
chimney2Converted.SetLineColor(colorRwthMagenta)
chimney1Converted.Draw("same,l")
chimney2Converted.Draw("same,l")
labelCmsPrivateSimulation = getLabelCmsPrivateSimulation()
labelCmsPrivateSimulation.Draw()
legend = TLegend(0.1,0.87,0.3,0.9)
legend.AddEntry(chimney2Converted,"chimney","l")
legend.Draw()
canvasEtaPhiBxWrong.Update()
self.storeCanvas(canvasEtaPhiBxWrong,"bxWrongEtaPhi")
def plotAdcTimeSliceCorrelation():
hist = fileHandler.getHistogram('hoDigiAnalyzer/correlation/MaxTimeSliceVsAdc_Correlation')
canvas = TCanvas('canvasTSvsADC',"ADC vs. TS",1200,1200)
canvas.cd().SetLogz()
hist.GetXaxis().SetRangeUser(-1,11)
hist.GetYaxis().SetRangeUser(10,130)
hist.SetTitle("Max ADC Value vs. Time Slice;Time slice ID;ADC")
hist.SetStats(0)
setupAxes(hist)
hist.Draw('colz')
canvas.Update()
pal = hist.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.SaveAs('plots/timeCorrelation/adcVsTs.pdf')
canvas.SaveAs('plots/timeCorrelation/adcVsTs.png')
return hist,canvas,label
def plotAdcTimeSliceCorrelation():
hist = fileHandler.getHistogram(
'hoDigiAnalyzer/correlation/MaxTimeSliceVsAdc_Correlation')
canvas = TCanvas('canvasTSvsADC', "ADC vs. TS", 1200, 1200)
canvas.cd().SetLogz()
hist.GetXaxis().SetRangeUser(-1, 11)
hist.GetYaxis().SetRangeUser(10, 130)
hist.SetTitle("Max ADC Value vs. Time Slice;Time slice ID;ADC")
hist.SetStats(0)
setupAxes(hist)
hist.Draw('colz')
canvas.Update()
pal = hist.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.SaveAs('plots/timeCorrelation/adcVsTs.pdf')
canvas.SaveAs('plots/timeCorrelation/adcVsTs.png')
return hist, canvas, label
def plotAverageEnergyAroundL1(self):
canvas = TCanvas('canvasAverageEnergy','Average energy',1200,1200)
canvas.cd().SetLogz()
hSum = self.fileHandler.getHistogram('hoMuonAnalyzer/averageEnergy/averageEnergyAroundPoint' + self.key + '_SummedEnergy')
hCounter = self.fileHandler.getHistogram('hoMuonAnalyzer/averageEnergy/averageEnergyAroundPoint' + self.key + '_Counter')
for i in range(0,hSum.GetNbinsX()):
for j in range(0,hSum.GetNbinsY()):
if hCounter.GetBinContent(hCounter.GetBin(i,j)) != 0:
hSum.SetBinContent(hSum.GetBin(i,j),hSum.GetBinContent(hSum.GetBin(i,j))/hCounter.GetBinContent(hCounter.GetBin(i,j)))
pass
hSum.GetXaxis().SetRangeUser(-0.6,0.6)
hSum.GetYaxis().SetRangeUser(-0.6,0.6)
# hSum.SetStats(0)
hSum.GetXaxis().SetTitle('#Delta#eta')
hSum.GetYaxis().SetTitle('#Delta#phi')
hSum.GetZaxis().SetTitle('Reconstructed Energy / GeV')
hSum.SetTitle('Average Energy in HO tiles around L1 direction')
hSum.Draw('colz')
# hCounter.Draw('same,text')
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.Update()
#Setup plot style
setupAxes(hSum)
setStatBoxOptions(hSum,1100)
setStatBoxPosition(hSum)
setupPalette(hSum)
canvas.Update()
self.storeCanvas(canvas,'averageEnergy')
return canvas,hSum,label,hCounter
def plotEtaPhiOfWrongBxId(self):
canvasEtaPhiBxWrong = TCanvas("canvasEtaPhiBxWrong","canvasEtaPhiBxWrong",1200,1200)
nEventsWithL1 = self.fileHandler.getHistogram('count/L1MuonPresent_Count').GetBinContent(2)
etaPhiBxWrongNC = self.fileHandler.getGraph("graphs/BxWrongGen")
etaPhiBxWrong = convertToHcalCoords(etaPhiBxWrongNC)
etaPhiBxWrong.GetXaxis().SetTitle("i#eta / a.u.")
etaPhiBxWrong.GetYaxis().SetTitle("i#phi / a.u.")
etaPhiBxWrong.SetMarkerStyle(6)
etaPhiBxWrong.SetMarkerColor(colorRwthDarkBlue)
etaPhiBxWrong.SetTitle("#eta #phi plot of events with BX ID wrong")
etaPhiBxWrong.Draw("AP")
pText = TPaveText(0.7,0.85,0.9,0.9,'NDC')
pText.AddText('Events with L1 objects: %d' % (nEventsWithL1))
pText.AddText('Events in Plot: %d' % (etaPhiBxWrong.GetN()))
pText.SetBorderSize(1)
pText.Draw()
chimney1Converted = convertToHcalCoords(chimney1)
chimney2Converted = convertToHcalCoords(chimney2)
chimney1Converted.SetLineColor(colorRwthMagenta)
chimney2Converted.SetLineColor(colorRwthMagenta)
chimney1Converted.Draw("same,l")
chimney2Converted.Draw("same,l")
labelCmsPrivateSimulation = getLabelCmsPrivateSimulation()
labelCmsPrivateSimulation.Draw()
legend = TLegend(0.1,0.87,0.3,0.9)
legend.AddEntry(chimney2Converted,"chimney","l")
legend.Draw()
canvasEtaPhiBxWrong.Update()
self.storeCanvas(canvasEtaPhiBxWrong,"bxWrongEtaPhi")
def plotDigiVsPhi():
canvas = TCanvas("canvasDigiPhi", "Simple Digi Phi", 1200, 1200)
hoDigiTime = fileHandler.getGraph(
'hoDigiAnalyzer/correlation/hoTimeFromDigiPhi')
setupAxes(hoDigiTime)
hoDigiTime.GetXaxis().SetTitle('#phi')
hoDigiTime.GetYaxis().SetTitle('time / ns')
hoDigiTime.GetYaxis().SetTitleOffset(1.4)
hoDigiTime.SetMarkerStyle(5)
hoDigiTime.SetMarkerColor(colorRwthDarkBlue)
hoDigiTime.SetTitle('Simple time reco vs. #phi')
hoDigiTime.Draw('ap')
#Label for CMS private
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiTimeVsphi.png')
return canvas, hoDigiTime, label
def plotRpcVsHo():
hist = fileHandler.getHistogram(
'hoMuonAnalyzer/correlation/RpcHoAboveThr_TimeCorrelation')
canvas = TCanvas('canvasRpcVsHo', "RPC vs. HO", 1200, 1200)
canvas.cd().SetLogz()
histNew = getTH2D(
"histRpcVsHo",
"RPC BX ID vs. HO > E_{Thr};HO time / ns;BX ID",
5,
-37.5,
87.5 #24,-56.25,93.75
,
5,
-2.5,
2.5)
xAxis = hist.GetXaxis()
yAxis = hist.GetYaxis()
nBinsX = xAxis.GetNbins()
nBinsY = yAxis.GetNbins()
#Fill new histogram with fewer bins
for i in range(1, nBinsX + 1):
for j in range(1, nBinsY + 1):
histNew.Fill(xAxis.GetBinCenter(i),
yAxis.GetBinCenter(j) / 25., hist.GetBinContent(i, j))
histNew.SetStats(0)
histNew.Draw('colz')
canvas.Update()
pal = histNew.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
#Calcualte fraction at (0,0)
nCentral = histNew.GetBinContent(histNew.FindBin(0, 0))
nTotal = histNew.Integral()
fraction = nCentral / float(nTotal)
fractionUncert = calcSigma(nCentral, nTotal)
sliceFraction = 0
for i in range(0, 5):
sliceFraction += histNew.GetBinContent(histNew.FindBin(0, -2.5 + i))
sliceFractionUncert = calcSigma(sliceFraction, nTotal)
sliceFraction /= nTotal
paveTextAboveThr = TPaveText(0.1, 0.8, 0.5, 0.9, 'NDC')
paveTextAboveThr.AddText('Fraction at (0,0): %5.2f%% #pm %5.2f%%' %
(fraction * 100, fractionUncert * 100))
paveTextAboveThr.AddText('Fraction at (0,x): %5.2f%% #pm %5.2f%%' %
(sliceFraction * 100, sliceFractionUncert * 100))
paveTextAboveThr.SetBorderSize(1)
paveTextAboveThr.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
canvas.SaveAs('plots/timeCorrelation/rpcVsHo.pdf')
canvas.SaveAs('plots/timeCorrelation/rpcVsHo.png')
return hist, canvas, paveTextAboveThr, label
def plotDigiTest():
#Prepare canvas
canvas = TCanvas("canvasBxId", "BXID", 1200, 1200)
canvas.SetLogy()
histBx = fileHandler.getHistogram("hoDigiAnalyzer/hoDigi_BxId")
histBx.GetXaxis().SetRangeUser(-3, 3)
histBx.SetLineWidth(3)
histBx.Scale(1 / histBx.Integral())
histBx.SetStats(0)
histBx.SetLineColor(colorRwthDarkBlue)
histBx.Draw('')
#Add label
label = getLabelCmsPrivateSimulation()
label.Draw()
# #Add legend
# legend = TLegend(0.7,0.65,0.9,0.8)
# legend.AddEntry(histBx,"DT Only","l")
# legend.AddEntry(histNew,"DT shifted with HO","l")
# legend.SetBorderSize(1)
# legend.Draw()
# #Add text object
# pText = TPaveText(0.52,0.8,0.9,0.9,'NDC')
# pText.AddText('Fraction in BX ID 0: %6.3f%% #pm %6.3f%%' % (dtBx0/float(dtBxTotal)*100,calcSigma(dtBx0, dtBxTotal)))
# pText.AddText('Fraction in BX ID 0 (HO corr.): %6.3f%% #pm %6.3f%%' % (correctedRightFraction*100,calcSigma(correctedBxId0, correctedTotal)))
# pText.SetBorderSize(1)
# pText.SetFillColor(0)
# pText.Draw()
#
pText2 = TPaveText(0.7, 0.85, 0.9, 0.9, 'NDC')
pText2.AddText('Entries: %d' % (histBx.GetEntries()))
pText2.SetBorderSize(1)
pText2.SetFillColor(0)
pText2.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiBxId.pdf')
canvas.SaveAs('plots/timing/digiBxId.png')
canvasAdcSum = TCanvas("cavasAdcSum", "ADC Sum", 1200, 1200)
canvasAdcSum.SetLogy()
histAdcSum = fileHandler.getHistogram(
"hoMuonAnalyzer/hoDigiAdcSum_Multiplicity")
histAdcSum.GetXaxis().SetRangeUser(-0.5, 500)
histAdcSum.GetXaxis().SetTitle('ADC counts')
histAdcSum.GetYaxis().SetTitle('#')
histAdcSum.SetLineWidth(3)
histAdcSum.SetStats(0)
histAdcSum.SetLineColor(colorRwthDarkBlue)
histAdcSum.Draw()
canvasAdcSum.Update()
canvasAdcSum.SaveAs('plots/timing/digiAdcSum.pdf')
canvasAdcSum.SaveAs('plots/timing/digiAdcSum.png')
canvasTS4 = TCanvas("cavasTS4", "TS4", 1200, 1200)
canvasTS4.SetLogy()
histAdcTS4 = fileHandler.getHistogram(
"hoMuonAnalyzer/hoDigiAdcTS4_Multiplicity")
histAdcTS4.GetXaxis().SetRangeUser(-0.5, 500)
histAdcTS4.GetXaxis().SetTitle('ADC counts')
histAdcTS4.GetYaxis().SetTitle('#')
histAdcTS4.SetLineWidth(3)
histAdcTS4.SetStats(0)
histAdcTS4.SetLineColor(colorRwthDarkBlue)
histAdcTS4.Draw()
canvasTS4.Update()
canvasTS4.SaveAs('plots/timing/digiAdcTs4.pdf')
canvasTS4.SaveAs('plots/timing/digiAdcTs4.png')
print histAdcSum.Integral(histAdcSum.FindBin(17), histAdcSum.FindBin(500))
return canvas, histBx, label, canvasAdcSum, histAdcSum, canvasTS4, histAdcTS4
def plotDeltaTime(self):
hDeltaTAllHo = self.fileHandler.getHistogram('L1MuonPresentHoMatch_DeltaTime')
hDeltaTCleanHo = self.fileHandler.getHistogram('timingSupport_UnmatchedDtHo_DeltaTime')
c = TCanvas("c","Delta Time",1200,1200)
c.SetLogy()
hDeltaTAllHo.SetLineColor(colorRwthDarkBlue)
hDeltaTAllHo.SetLineWidth(3)
hDeltaTAllHo.SetFillColor(colorRwthDarkBlue)
hDeltaTAllHo.SetFillStyle(3017)
hDeltaTAllHo.SetTitle("#Delta time")
hDeltaTAllHo.SetStats(0)
hDeltaTCleanHo.SetLineColor(8)
hDeltaTCleanHo.SetFillColor(8)
hDeltaTCleanHo.SetLineWidth(3)
hDeltaTCleanHo.SetFillStyle(3002)
#hDeltaTAllHo.Scale(1/hDeltaTAllHo.Integral())
#hDeltaTCleanHo.Scale(1/hDeltaTCleanHo.Integral())
print hDeltaTCleanHo.Integral(),hDeltaTAllHo.Integral()
fitFirstMin = TF1("fitFirstMin","[0]+x*[1]+[2]*x**2")
fitSecondMin = TF1("fitsecondMin","[0]+x*[1]+[2]*x**2",10,20)
hDeltaTCleanHo.Fit(fitFirstMin,"+q","",-20,-10)
hDeltaTCleanHo.Fit(fitSecondMin,"R+q","")
hDeltaTAllHo.Draw()
legend = TLegend(0.6,0.75,0.9,0.9)
legend.AddEntry(hDeltaTAllHo,"L1Muon matched to any HO","le")
legend.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
c.Update()
self.storeCanvas(c,"deltaTimeAllHo")
hDeltaTCleanHo.Draw('same')
fitFirstMin.SetRange(-50,50)
fitSecondMin.SetRange(-50,50)
#fitFirstMin.Draw('lSame')
#fitSecondMin.Draw('lSame')
lineFirstMin = TLine(fitFirstMin.GetMinimumX(-20,-10),hDeltaTAllHo.GetMinimum(),fitFirstMin.GetMinimumX(-20,-10),hDeltaTAllHo.GetMaximum())
lineFirstMin.SetLineWidth(3)
lineFirstMin.SetLineColor(colorRwthRot)
lineFirstMin.Draw()
lineSecondMin = TLine(fitSecondMin.GetMinimumX(10,20),hDeltaTAllHo.GetMinimum(),fitSecondMin.GetMinimumX(10,20),hDeltaTAllHo.GetMaximum())
lineSecondMin.SetLineWidth(3)
lineSecondMin.SetLineColor(colorRwthRot)
lineSecondMin.Draw()
legend.AddEntry(hDeltaTCleanHo,"L1Muon matched to HO > 0.2 GeV","le")
legend.AddEntry(lineFirstMin,"Integral boundaries","e")
legend.Draw()
integralCenter = hDeltaTCleanHo.Integral(hDeltaTCleanHo.FindBin(fitFirstMin.GetMinimumX(-20,-10)),hDeltaTCleanHo.FindBin(fitSecondMin.GetMinimumX(10,20)))
integralCenterAll = hDeltaTAllHo.Integral(hDeltaTAllHo.FindBin(fitFirstMin.GetMinimumX(-20,-10)),hDeltaTAllHo.FindBin(fitSecondMin.GetMinimumX(10,20)))
self.debug(80*'#')
self.debug('Integral of center area in clean histogram :%d' % integralCenter)
self.debug('==> %.2f%% +/- %.2f%%' % (integralCenter/hDeltaTCleanHo.Integral()*100
,calcSigma(integralCenter, hDeltaTCleanHo.Integral())*100))
self.debug('Integral of center area in all matched HO events:%d' % integralCenterAll)
self.debug('==> %.2f%% +/- %.2f%%' % (integralCenterAll/hDeltaTAllHo.Integral()*100
,calcSigma(integralCenterAll, hDeltaTAllHo.Integral())*100))
self.debug(80*'#')
paveText = TPaveText(0.6,0.7,0.9,0.75,'NDC')
paveText.AddText('%s' % ('Central peak contains (filtered hist.)'))
paveText.AddText('%.2f%% +/- %.2f%%' % (integralCenter/hDeltaTCleanHo.Integral()*100,calcSigma(integralCenter, hDeltaTCleanHo.Integral())*100))
paveText.SetBorderSize(1)
paveText.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
c.Update()
self.storeCanvas(c,"deltaTime")
return c, hDeltaTCleanHo
def plotHoL1Correlation():
#Select whether matching to all HO should also be plotted
plotBoth = True
histAll = fileHandler.getHistogram(
'hoMuonAnalyzer/correlation/L1MuonPresentHoMatch_TimeCorrelation')
histAboveThr = fileHandler.getHistogram(
'hoMuonAnalyzer/correlation/L1MuonAboveThr_TimeCorrelation')
label = getLabelCmsPrivateSimulation()
canvas = TCanvas("canvasHoL1Correlation", "canvasHoL1Correlation", 1600,
1200)
if (plotBoth):
canvas.Divide(2, 1)
canvas.cd(1).SetLogz()
histNew = getTH2D(
"histNew",
"Correlation between L1 BX ID and HO;HO time / ns;L1 / BX ID",
5,
-37.5,
87.5 #24,-56.25,93.75
,
5,
-2.5,
2.5)
xAxis = histAll.GetXaxis()
yAxis = histAll.GetYaxis()
nBinsX = xAxis.GetNbins()
nBinsY = yAxis.GetNbins()
#Fill new histogram with fewer bins
for i in range(1, nBinsX + 1):
for j in range(1, nBinsY + 1):
histNew.Fill(xAxis.GetBinCenter(i),
yAxis.GetBinCenter(j) / 25.,
histAll.GetBinContent(i, j))
histNew.SetStats(0)
histNew.Draw('colz')
canvas.Update()
pal = histNew.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
#Calcualte fraction at (0,0)
nCentral = histNew.GetBinContent(histNew.FindBin(0, 0))
nTotal = histNew.Integral()
fraction = nCentral / float(nTotal)
fractionUncert = calcSigma(nCentral, nTotal)
sliceFraction = 0
for i in range(0, 5):
sliceFraction += histNew.GetBinContent(histNew.FindBin(
0, -2.5 + i))
sliceFractionUncert = calcSigma(sliceFraction, nTotal)
sliceFraction /= nTotal
paveText = TPaveText(0.1, 0.8, 0.5, 0.9, 'NDC')
paveText.AddText('Fraction at (0,0): %5.2f%% #pm %5.2f%%' %
(fraction * 100, fractionUncert * 100))
paveText.AddText('Fraction at (0,x): %5.2f%% #pm %5.2f%%' %
(sliceFraction * 100, sliceFractionUncert * 100))
paveText.SetBorderSize(1)
paveText.Draw()
label.Draw()
canvas.cd(2).SetLogz()
histAboveThr.SetStats(0)
xAxis = histAboveThr.GetXaxis()
yAxis = histAboveThr.GetYaxis()
nBinsX = xAxis.GetNbins()
nBinsY = yAxis.GetNbins()
histNewAboveThr = getTH2D(
"histNewAboveThr",
"Correlation between L1 BX ID and HO > E_{Thr};HO time / ns;L1 / BX ID",
5,
-37.5,
87.5 #,12,-56.25,93.75
,
5,
-2.5,
2.5)
for i in range(1, nBinsX + 1):
for j in range(1, nBinsY + 1):
histNewAboveThr.Fill(xAxis.GetBinCenter(i),
yAxis.GetBinCenter(j) / 25.,
histAboveThr.GetBinContent(i, j))
histNewAboveThr.SetStats(0)
histNewAboveThr.Draw('colz')
canvas.Update()
pal = histNewAboveThr.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
#Calcualte fraction at (0,0)
nCentral = histNewAboveThr.GetBinContent(histNewAboveThr.FindBin(0, 0))
nTotal = histNewAboveThr.Integral()
fraction = nCentral / float(nTotal)
fractionUncert = calcSigma(nCentral, nTotal)
sliceFraction = 0
for i in range(0, 5):
sliceFraction += histNewAboveThr.GetBinContent(
histNewAboveThr.FindBin(0, -2.5 + i))
sliceFractionUncert = calcSigma(sliceFraction, nTotal)
sliceFraction /= nTotal
paveTextAboveThr = TPaveText(0.1, 0.8, 0.5, 0.9, 'NDC')
paveTextAboveThr.AddText('Fraction at (0,0): %5.2f%% #pm %5.2f%%' %
(fraction * 100, fractionUncert * 100))
paveTextAboveThr.AddText('Fraction at (0,x): %5.2f%% #pm %5.2f%%' %
(sliceFraction * 100, sliceFractionUncert * 100))
paveTextAboveThr.SetBorderSize(1)
paveTextAboveThr.Draw()
label.Draw()
canvas.Update()
canvas.SaveAs('plots/timeCorrelation/l1AndHoCorrelation.pdf')
canvas.SaveAs('plots/timeCorrelation/l1AndHoCorrelation.png')
return canvas, histAll, histAboveThr, label, histNewAboveThr, histNew, paveTextAboveThr
def plotDigiTime(truth=False):
additionalString = 'Truth' if truth else ''
canvas = TCanvas("canvasDigiSimpleTime" + additionalString,
"Simple Digi Time " + additionalString, 1200, 1200)
canvas.SetLogy()
histHoTime = fileHandler.getHistogram('hoDigiAnalyzer/hoTimeFromDigi_Time')
setupAxes(histHoTime)
histHoTime.GetXaxis().SetTitle('time / ns')
histHoTime.GetXaxis().SetRangeUser(-100, 100)
histHoTime.SetLineColor(colorRwthDarkBlue)
histHoTime.SetStats(0)
histHoTime.SetFillStyle(3004)
histHoTime.SetFillColor(colorRwthDarkBlue)
histHoTime.SetLineWidth(3)
histHoTime.SetTitle('Simple time reconstruction from HO digi')
histHoTime.Draw()
#Label for CMS private
label = getLabelCmsPrivateSimulation()
label.Draw()
#Add legend
legend = TLegend(0.65, 0.75, 0.9, 0.9)
legend.AddEntry(histHoTime, "All Digi times", "f")
legend.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiTimeAllHo.pdf')
canvas.SaveAs('plots/timing/digiTimeAllHo.png')
#Now add next plot
histHoTimeAboveThr = fileHandler.getHistogram(
'hoDigiAnalyzer/hoTimeFromDigiAboveThr' + additionalString + '_Time')
histHoTimeAboveThr.SetLineColor(colorRwthTuerkis)
histHoTimeAboveThr.SetStats(0)
histHoTimeAboveThr.SetLineWidth(3)
histHoTimeAboveThr.SetFillStyle(3005)
histHoTimeAboveThr.SetFillColor(colorRwthTuerkis)
histHoTimeAboveThr.Draw('same')
legend.AddEntry(histHoTimeAboveThr,
"4 TS sum > E_{Thr} " + additionalString, "f")
legend.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiTimePlusThr' + additionalString + '.pdf')
canvas.SaveAs('plots/timing/digiTimePlusThr' + additionalString + '.png')
#Now add Ho rec hit time plot
histHoRecHitTime = fileHandler.getHistogram(
'hoMuonAnalyzer/hoRecHitsAboveThr_Time')
histHoRecHitTime.SetLineColor(colorRwthMagenta)
histHoRecHitTime.SetStats(0)
histHoRecHitTime.SetLineWidth(3)
histHoRecHitTime.Draw('same')
legend.AddEntry(histHoRecHitTime, "HO Rec Hit Time > E_{Thr}", "l")
legend.Draw()
canvas.Update()
canvas.SaveAs('plots/timing/digiTime' + additionalString +
'PlusRecHits.pdf')
canvas.SaveAs('plots/timing/digiTime' + additionalString +
'PlusRecHits.png')
return canvas, label, histHoTime, legend, histHoTimeAboveThr, histHoRecHitTime
def plotFractionsOfBxId(self):
##BX right plotting pt
canvasBxRightPt = TCanvas("cBxRightPt","cBxRightPt",1200,1200)
canvasBxRightPt.cd().SetLeftMargin(0.15)
hBxRightPt = self.fileHandler.getHistogram('BxRightGen_Pt').Clone()
setPlotStyle()
hBxRightPt.Rebin(50)
hBxRightPt.GetXaxis().SetRangeUser(0,200)
hBxRightPt.GetYaxis().SetTitle("normalized Entries / 5 GeV")
hBxRightPt.GetXaxis().SetTitle("p_{T} Gen")
hBxRightPt.GetYaxis().SetTitleOffset(2)
hBxRightPt.SetTitle("Events with right BX ID vs. p_{T}")
hBxRightPt.SetStats(0)
hBxRightPt.SetLineWidth(2)
hBxRightPt.Scale(1/hBxRightPt.Integral())
hBxRightPt.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
self.storeCanvas(canvasBxRightPt,"bxRightPt")
##BX wrong plotting pt
canvasBxWrongPt = TCanvas("cBxWrongPt","cBxWrongPt",1200,1200)
canvasBxWrongPt.cd().SetLeftMargin(0.15)
hBxWrongPt = self.fileHandler.getHistogram('BxWrongGen_Pt').Clone()
setPlotStyle()
hBxWrongPt.Rebin(50)
hBxWrongPt.GetXaxis().SetRangeUser(0,200)
hBxWrongPt.GetYaxis().SetTitle("normalized Entries / 5 GeV")
hBxWrongPt.GetXaxis().SetTitle("p_{T} Gen")
hBxWrongPt.GetYaxis().SetTitleOffset(2)
hBxWrongPt.SetTitle("Events with wrong BX ID vs. p_{T}")
hBxWrongPt.SetStats(0)
hBxWrongPt.SetLineWidth(2)
hBxWrongPt.Scale(1/hBxWrongPt.Integral())
hBxWrongPt.DrawCopy()
label = getLabelCmsPrivateSimulation()
label.Draw()
self.storeCanvas(canvasBxWrongPt,"bxWrongPt")
#Plot the histogram stack
canvasStack = TCanvas("cStacked","cStacked",1200,1200)
canvasStack.cd().SetLeftMargin(0.15)
hWrong = self.fileHandler.getHistogram('BxWrongGen_Pt')
hRight = self.fileHandler.getHistogram('BxRightGen_Pt')
hRightFraction = TH1D('hRightFraction','',100,0,500)
hWrongFraction = TH1D('hWrongFraction','',100,0,500)
#hWrong.Rebin(50)
#hRight.Rebin(50)
#Fill the histograms with the bin wise fractions
for i in range(0,hRight.GetNbinsX()):
nRight = hRight.GetBinContent(i+1)
nWrong = hWrong.GetBinContent(i+1)
if(nRight + nWrong == 0):
continue
hRightFraction.SetBinContent(i+1,nRight/(nRight+nWrong))
hWrongFraction.SetBinContent(i+1,nWrong/(nRight+nWrong))
#Create the stack
stack = THStack("hstack","Fractions of events for BX ID correct and wrong")
nRight = hRight.Integral()
nWrong = hWrong.Integral()
hRightFraction.SetLineColor(colorRwthDarkBlue)
hRightFraction.SetFillColor(colorRwthDarkBlue)
hRightFraction.SetFillStyle(3002)
hWrongFraction.SetLineColor(colorRwthMagenta)
hWrongFraction.SetFillColor(colorRwthMagenta)
hWrongFraction.SetFillStyle(3002)
stack.Add(hRightFraction)
stack.Add(hWrongFraction)
stack.Draw()
stack.GetXaxis().SetRangeUser(0.5,201)
stack.GetYaxis().SetTitle('rel. fraction / 5 GeV')
stack.GetYaxis().SetTitleOffset(2)
stack.GetXaxis().SetTitle('p_{T} Gen')
stack.SetMinimum(0.9)
stack.SetMaximum(1)
legend = TLegend(0.6,0.75,0.9,0.9)
legend.AddEntry(hRightFraction,"BX ID right","f")
legend.AddEntry(hWrongFraction,"BX ID wrong","f")
legend.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
canvasStack.Update()
self.storeCanvas(canvasStack,"bxStacked")
def plotDetectorContributionsToTiming(self):
#Prepare canvas
canvas = TCanvas("canvasDetectorContributions","detectorContributions",1200,600)
canvas.Divide(2,1)
canvas.cd(1).SetGridx(0)
canvas.cd(1).SetGridy(0)
canvas.cd(1).SetLogy()
#prepare histogram
hist = self.fileHandler.getHistogram("multiplicity/detectorIndexBxWrong_Multiplicity")
hist.GetXaxis().SetRangeUser(0.5,5.5)
hist.SetLineColor(colorRwthDarkBlue)
hist.SetFillColor(colorRwthDarkBlue)
#Prepare the bin labels
x = ['RPC','DT','DT/RPC','CSC','CSC/RPC']
for i in range(1,6):
hist.GetXaxis().SetBinLabel(i+1,x[i-1])
hist.GetXaxis().SetLabelFont(62)
hist.GetYaxis().SetLabelFont(62)
hist.GetYaxis().SetTitleFont(62)
hist.Scale(1/hist.Integral())
hist.GetYaxis().SetTitle('rel. fraction')
hist.SetStats(0)
hist.SetTitle('Subdetectors in wrong L1 BX ID')
hist.Draw()
#add label
label = getLabelCmsPrivateSimulation()
label.Draw()
#Make a histogram to grey out the CSC parts
histGrey = TH1D('greyHist','grey hist',2,3.5,5.5)
histGrey.SetBinContent(1,1)
histGrey.SetBinContent(2,1)
histGrey.SetFillStyle(3004)
histGrey.SetLineWidth(2)
histGrey.SetLineColor(1)
histGrey.SetFillColor(1)
histGrey.Draw('same')
pText = TPaveText(0.7,0.33,0.79,0.62,"NDC")
tTextPointer = pText.AddText('Not in #eta range')
tTextPointer.SetTextAngle(90)
tTextPointer.SetTextSize(0.039)
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
canvas.cd(2).SetGridx(0)
canvas.cd(2).SetGridy(0)
canvas.cd(2).SetLogy()
#prepare second histogram
hist2 = self.fileHandler.getHistogram("multiplicity/detectorIndexBxRight_Multiplicity")
hist2.GetXaxis().SetRangeUser(0.5,5.5)
hist2.SetLineColor(colorRwthDarkBlue)
hist2.SetFillColor(colorRwthDarkBlue)
#Prepare the bin labels
x = ['RPC','DT','DT/RPC','CSC','CSC/RPC']
for i in range(1,6):
hist2.GetXaxis().SetBinLabel(i+1,x[i-1])
hist2.GetXaxis().SetLabelFont(62)
hist2.GetYaxis().SetLabelFont(62)
hist2.GetYaxis().SetTitleFont(62)
hist2.Scale(1/hist2.Integral())
hist2.GetYaxis().SetTitle('rel. fraction')
hist2.SetStats(0)
hist2.SetTitle('Subdetectors in right L1 BX ID')
hist2.Draw()
#add label
label2 = getLabelCmsPrivateSimulation()
label2.Draw()
histGrey.DrawCopy('same')
pText2 = pText.Clone("pText2")
pText2.Draw()
canvas.Update()
self.storeCanvas(canvas,"bxWrongDetectorContributions")
return canvas,hist,label,histGrey,pText,pText2,label2,hist2
def plotDetectorContributionsToTiming(self):
#Prepare canvas
canvas = TCanvas("canvasDetectorContributions","detectorContributions",1200,600)
canvas.Divide(2,1)
canvas.cd(1).SetGridx(0)
canvas.cd(1).SetGridy(0)
canvas.cd(1).SetLogy()
#prepare histogram
hist = self.fileHandler.getHistogram("multiplicity/detectorIndexBxWrong_Multiplicity")
hist.GetXaxis().SetRangeUser(0.5,5.5)
hist.SetLineColor(colorRwthDarkBlue)
hist.SetFillColor(colorRwthDarkBlue)
#Prepare the bin labels
x = ['RPC','DT','DT/RPC','CSC','CSC/RPC']
for i in range(1,6):
hist.GetXaxis().SetBinLabel(i+1,x[i-1])
hist.GetXaxis().SetLabelFont(62)
hist.GetYaxis().SetLabelFont(62)
hist.GetYaxis().SetTitleFont(62)
hist.Scale(1/hist.Integral())
hist.GetYaxis().SetTitle('rel. fraction')
hist.SetStats(0)
hist.SetTitle('Subdetectors in wrong L1 BX ID')
hist.Draw()
#add label
label = getLabelCmsPrivateSimulation()
label.Draw()
#Make a histogram to grey out the CSC parts
histGrey = TH1D('greyHist','grey hist',2,3.5,5.5)
histGrey.SetBinContent(1,1)
histGrey.SetBinContent(2,1)
histGrey.SetFillStyle(3004)
histGrey.SetLineWidth(2)
histGrey.SetLineColor(1)
histGrey.SetFillColor(1)
histGrey.Draw('same')
pText = TPaveText(0.7,0.33,0.79,0.62,"NDC")
tTextPointer = pText.AddText('Not in #eta range')
tTextPointer.SetTextAngle(90)
tTextPointer.SetTextSize(0.039)
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
canvas.cd(2).SetGridx(0)
canvas.cd(2).SetGridy(0)
canvas.cd(2).SetLogy()
#prepare second histogram
hist2 = self.fileHandler.getHistogram("multiplicity/detectorIndexBxRight_Multiplicity")
hist2.GetXaxis().SetRangeUser(0.5,5.5)
hist2.SetLineColor(colorRwthDarkBlue)
hist2.SetFillColor(colorRwthDarkBlue)
#Prepare the bin labels
x = ['RPC','DT','DT/RPC','CSC','CSC/RPC']
for i in range(1,6):
hist2.GetXaxis().SetBinLabel(i+1,x[i-1])
hist2.GetXaxis().SetLabelFont(62)
hist2.GetYaxis().SetLabelFont(62)
hist2.GetYaxis().SetTitleFont(62)
hist2.Scale(1/hist2.Integral())
hist2.GetYaxis().SetTitle('rel. fraction')
hist2.SetStats(0)
hist2.SetTitle('Subdetectors in right L1 BX ID')
hist2.Draw()
#add label
label2 = getLabelCmsPrivateSimulation()
label2.Draw()
histGrey.DrawCopy('same')
pText2 = pText.Clone("pText2")
pText2.Draw()
canvas.Update()
self.storeCanvas(canvas,"bxWrongDetectorContributions")
return canvas,hist,label,histGrey,pText,pText2,label2,hist2
def plotFractionsOfBxId(self):
##BX right plotting pt
canvasBxRightPt = TCanvas("cBxRightPt","cBxRightPt",1200,1200)
canvasBxRightPt.cd().SetLeftMargin(0.15)
hBxRightPt = self.fileHandler.getHistogram('BxRightGen_Pt').Clone()
setPlotStyle()
hBxRightPt.Rebin(50)
hBxRightPt.GetXaxis().SetRangeUser(0,200)
hBxRightPt.GetYaxis().SetTitle("normalized Entries / 5 GeV")
hBxRightPt.GetXaxis().SetTitle("p_{T} Gen")
hBxRightPt.GetYaxis().SetTitleOffset(2)
hBxRightPt.SetTitle("Events with right BX ID vs. p_{T}")
hBxRightPt.SetStats(0)
hBxRightPt.SetLineWidth(2)
hBxRightPt.Scale(1/hBxRightPt.Integral())
hBxRightPt.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
self.storeCanvas(canvasBxRightPt,"bxRightPt")
##BX wrong plotting pt
canvasBxWrongPt = TCanvas("cBxWrongPt","cBxWrongPt",1200,1200)
canvasBxWrongPt.cd().SetLeftMargin(0.15)
hBxWrongPt = self.fileHandler.getHistogram('BxWrongGen_Pt').Clone()
setPlotStyle()
hBxWrongPt.Rebin(50)
hBxWrongPt.GetXaxis().SetRangeUser(0,200)
hBxWrongPt.GetYaxis().SetTitle("normalized Entries / 5 GeV")
hBxWrongPt.GetXaxis().SetTitle("p_{T} Gen")
hBxWrongPt.GetYaxis().SetTitleOffset(2)
hBxWrongPt.SetTitle("Events with wrong BX ID vs. p_{T}")
hBxWrongPt.SetStats(0)
hBxWrongPt.SetLineWidth(2)
hBxWrongPt.Scale(1/hBxWrongPt.Integral())
hBxWrongPt.DrawCopy()
label = getLabelCmsPrivateSimulation()
label.Draw()
self.storeCanvas(canvasBxWrongPt,"bxWrongPt")
#Plot the histogram stack
canvasStack = TCanvas("cStacked","cStacked",1200,1200)
canvasStack.cd().SetLeftMargin(0.15)
hWrong = self.fileHandler.getHistogram('BxWrongGen_Pt')
hRight = self.fileHandler.getHistogram('BxRightGen_Pt')
hRightFraction = TH1D('hRightFraction','',100,0,500)
hWrongFraction = TH1D('hWrongFraction','',100,0,500)
#hWrong.Rebin(50)
#hRight.Rebin(50)
#Fill the histograms with the bin wise fractions
for i in range(0,hRight.GetNbinsX()):
nRight = hRight.GetBinContent(i+1)
nWrong = hWrong.GetBinContent(i+1)
if(nRight + nWrong == 0):
continue
hRightFraction.SetBinContent(i+1,nRight/(nRight+nWrong))
hWrongFraction.SetBinContent(i+1,nWrong/(nRight+nWrong))
#Create the stack
stack = THStack("hstack","Fractions of events for BX ID correct and wrong")
nRight = hRight.Integral()
nWrong = hWrong.Integral()
hRightFraction.SetLineColor(colorRwthDarkBlue)
hRightFraction.SetFillColor(colorRwthDarkBlue)
hRightFraction.SetFillStyle(3002)
hWrongFraction.SetLineColor(colorRwthMagenta)
hWrongFraction.SetFillColor(colorRwthMagenta)
hWrongFraction.SetFillStyle(3002)
stack.Add(hRightFraction)
stack.Add(hWrongFraction)
stack.Draw()
stack.GetXaxis().SetRangeUser(0.5,201)
stack.GetYaxis().SetTitle('rel. fraction / 5 GeV')
stack.GetYaxis().SetTitleOffset(2)
stack.GetXaxis().SetTitle('p_{T} Gen')
stack.SetMinimum(0.9)
stack.SetMaximum(1)
legend = TLegend(0.6,0.75,0.9,0.9)
legend.AddEntry(hRightFraction,"BX ID right","f")
legend.AddEntry(hWrongFraction,"BX ID wrong","f")
legend.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
canvasStack.Update()
self.storeCanvas(canvasStack,"bxStacked")
def plotImprovementInDt(self):
#Prepare canvas
canvas = TCanvas("canvasDtImprovement","DT improvement",1200,1200)
canvas.SetLogy()
histDt = self.fileHandler.getHistogram("hoMuonAnalyzer/timingSupport_UnmatchedDtHo_BxId")
histDtNoHo = self.fileHandler.getHistogram("hoMuonAnalyzer/timingSupport_UnmatchedDt_BxId")
#print 'DtBxNoHo Integral: ', histDtNoHo.Integral()
#Define variables for integrals
histHoTime = self.fileHandler.getHistogram('hoMuonAnalyzer/timingSupport_UnmatchedDtHo_Time')
integralHoCorrect = histHoTime.Integral(histHoTime.FindBin(-12.5),histHoTime.FindBin(12.5))
integralHoTotal = histHoTime.Integral()
integralHoOutside = integralHoTotal - integralHoCorrect
hoFractionWrong = integralHoOutside/float(integralHoTotal)
hoFractionRight = integralHoCorrect/float(integralHoTotal)
#Print some information
heading = 'Integrals of the Ho timing:'
print 80*'#'
print heading
print len(heading)*'-'
print 'Timing correct:\t%d\t=>\t%6.3f%% +/- %6.3f%%'%(integralHoCorrect,hoFractionRight*100,calcSigma(integralHoCorrect, integralHoTotal)*100)
print 'Timing outside:\t%d\t=>\t%6.3f%% +/- %f%%'%(integralHoOutside,hoFractionWrong*100,calcSigma(integralHoOutside, integralHoTotal)*100)
print 'Timing total:%d'%(integralHoTotal)
print
#Define Variables for bx id counts
dtBx0 = histDt.GetBinContent(6)
dtBxM1 = histDt.GetBinContent(5)
dtBxP1 = histDt.GetBinContent(7)
dtBxTotal = dtBx0 + dtBxM1 + dtBxP1
dtFractionWrongM1 = dtBxM1/float(dtBxTotal)
dtFractionWrongP1 = dtBxP1/float(dtBxTotal)
#Print some information
heading = 'Bin contents for DT timing:'
print heading
print len(heading)*'-'
print 'BX ID 0:\t%d\t=>\t%6.3f%% +/- %6.3f%%'%(dtBx0,dtBx0/float(dtBxTotal)*100,calcSigma(dtBx0, dtBxTotal)*100)
print 'BX ID -1:\t%d\t=>\t%6.3f%% +/- %6.3f%%'%(dtBxM1,dtFractionWrongM1*100,calcSigma(dtBxM1, dtBxTotal)*100)
print 'BX ID +1:\t%d\t=>\t%6.3f%% +/- %6.3f%%'%(dtBxP1,dtFractionWrongP1*100,calcSigma(dtBxP1, dtBxTotal)*100)
print 'BX ID total:\t%d' % (dtBxTotal)
print
#Calculate corrected numbers
correctedBxIdM1 = dtBxM1 + hoFractionWrong*dtBx0/2. - hoFractionRight*dtBxM1
correctedBxId0 = dtBx0 - hoFractionWrong*dtBx0 + hoFractionRight*dtBxM1 + hoFractionRight*dtBxP1
correctedBxIdP1 = dtBxP1 + hoFractionWrong*dtBx0/2. - hoFractionRight*dtBxP1
correctedTotal = correctedBxIdM1 + correctedBxId0 + correctedBxIdP1
correctedRightFraction = correctedBxId0/float(correctedTotal)
heading = 'DT After correction:'
print heading
print len(heading)*'-'
print 'BX -1:\t',int(correctedBxIdM1)
print 'BX 0:\t',int(correctedBxId0)
print 'BX +1:\t',int(correctedBxIdP1)
print
#Fill corrected histogram
histNew = TH1D("histNew","BX ID in DT only triggers;BX ID;rel. fraction",6,-2.5,3.5)
histNew.SetBinContent(histNew.FindBin(-1),correctedBxIdM1)
histNew.SetBinContent(histNew.FindBin(0),correctedBxId0)
histNew.SetBinContent(histNew.FindBin(1),correctedBxIdP1)
histNew.SetLineColor(colorRwthMagenta)
histNew.SetStats(0)
histNew.Scale(1/histNew.Integral())
histNew.SetLineStyle(9)
setupAxes(histNew)
setBigAxisTitles(histNew)
histDt.GetXaxis().SetRangeUser(-3,3)
histDt.SetLineWidth(3)
histDt.Scale(1/histDt.Integral())
histDt.SetLineColor(colorRwthDarkBlue)
histNew.Draw()
histDt.Draw('same')
histNew.Draw('same')
histDtNoHo.Scale(1/histDtNoHo.Integral())
histDtNoHo.SetLineWidth(3)
#histDtNoHo.Draw('same')
#Add label
label = getLabelCmsPrivateSimulation()
label.Draw()
#Add legend
legend = TLegend(0.7,0.65,0.9,0.8)
legend.AddEntry(histDt,"DT Only + HO","l")
legend.AddEntry(histNew,"DT shifted with HO","l")
legend.SetBorderSize(1)
legend.Draw()
#Add text object
pText = TPaveText(0.52,0.8,0.9,0.9,'NDC')
pText.AddText('Fraction in BX ID 0: %5.2f%% #pm %5.2f%%' % (dtBx0/float(dtBxTotal)*100,calcSigma(dtBx0, dtBxTotal)*100))
pText.AddText('Fraction in BX ID 0 (HO corr.): %5.2f%% #pm %5.2f%%' % (correctedRightFraction*100,calcSigma(correctedBxId0, correctedTotal)*100))
pText.SetBorderSize(1)
pText.SetFillColor(0)
pText.Draw()
pText2 = TPaveText(0.7,0.6,0.9,0.65,'NDC')
pText2.AddText('Entries: %d' % (histDt.GetEntries()))
pText2.SetBorderSize(1)
pText2.SetFillColor(0)
pText2.Draw()
#Print again some information
heading = 'Fraction of correct BXID:'
print heading
print len(heading)*'-'
print 'Uncorrected:\t%5.2f%% #pm %f%%' % (dtBx0/float(dtBxTotal)*100,calcSigma(dtBx0, dtBxTotal)*100)
print 'Corrected\t%5.2f%% #pm %f%%' % (correctedRightFraction*100,calcSigma(correctedBxId0, correctedTotal)*100)
print 80*'#'
canvas.Update()
self.storeCanvas(canvas, 'correctedDt')
return canvas, histDt,histNew,label,legend,pText2,pText,histDtNoHo
def plotDeltaTime(self):
hDeltaTAllHo = self.fileHandler.getHistogram('L1MuonPresentHoMatch_DeltaTime')
hDeltaTCleanHo = self.fileHandler.getHistogram('timingSupport_UnmatchedDtHo_DeltaTime')
c = TCanvas("c","Delta Time",1200,1200)
c.SetLogy()
hDeltaTAllHo.SetLineColor(colorRwthDarkBlue)
hDeltaTAllHo.SetLineWidth(3)
hDeltaTAllHo.SetFillColor(colorRwthDarkBlue)
hDeltaTAllHo.SetFillStyle(3017)
hDeltaTAllHo.SetTitle("#Delta time")
hDeltaTAllHo.SetStats(0)
hDeltaTCleanHo.SetLineColor(8)
hDeltaTCleanHo.SetFillColor(8)
hDeltaTCleanHo.SetLineWidth(3)
hDeltaTCleanHo.SetFillStyle(3002)
#hDeltaTAllHo.Scale(1/hDeltaTAllHo.Integral())
#hDeltaTCleanHo.Scale(1/hDeltaTCleanHo.Integral())
print hDeltaTCleanHo.Integral(),hDeltaTAllHo.Integral()
fitFirstMin = TF1("fitFirstMin","[0]+x*[1]+[2]*x**2")
fitSecondMin = TF1("fitsecondMin","[0]+x*[1]+[2]*x**2",10,20)
hDeltaTCleanHo.Fit(fitFirstMin,"+q","",-20,-10)
hDeltaTCleanHo.Fit(fitSecondMin,"R+q","")
hDeltaTAllHo.Draw()
legend = TLegend(0.6,0.75,0.9,0.9)
legend.AddEntry(hDeltaTAllHo,"L1Muon matched to any HO","le")
legend.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
c.Update()
self.storeCanvas(c,"deltaTimeAllHo")
hDeltaTCleanHo.Draw('same')
fitFirstMin.SetRange(-50,50)
fitSecondMin.SetRange(-50,50)
#fitFirstMin.Draw('lSame')
#fitSecondMin.Draw('lSame')
lineFirstMin = TLine(fitFirstMin.GetMinimumX(-20,-10),hDeltaTAllHo.GetMinimum(),fitFirstMin.GetMinimumX(-20,-10),hDeltaTAllHo.GetMaximum())
lineFirstMin.SetLineWidth(3)
lineFirstMin.SetLineColor(colorRwthRot)
lineFirstMin.Draw()
lineSecondMin = TLine(fitSecondMin.GetMinimumX(10,20),hDeltaTAllHo.GetMinimum(),fitSecondMin.GetMinimumX(10,20),hDeltaTAllHo.GetMaximum())
lineSecondMin.SetLineWidth(3)
lineSecondMin.SetLineColor(colorRwthRot)
lineSecondMin.Draw()
legend.AddEntry(hDeltaTCleanHo,"L1Muon matched to HO > 0.2 GeV","le")
legend.AddEntry(lineFirstMin,"Integral boundaries","e")
legend.Draw()
integralCenter = hDeltaTCleanHo.Integral(hDeltaTCleanHo.FindBin(fitFirstMin.GetMinimumX(-20,-10)),hDeltaTCleanHo.FindBin(fitSecondMin.GetMinimumX(10,20)))
integralCenterAll = hDeltaTAllHo.Integral(hDeltaTAllHo.FindBin(fitFirstMin.GetMinimumX(-20,-10)),hDeltaTAllHo.FindBin(fitSecondMin.GetMinimumX(10,20)))
self.debug(80*'#')
self.debug('Integral of center area in clean histogram :%d' % integralCenter)
self.debug('==> %.2f%% +/- %.2f%%' % (integralCenter/hDeltaTCleanHo.Integral()*100
,calcSigma(integralCenter, hDeltaTCleanHo.Integral())*100))
self.debug('Integral of center area in all matched HO events:%d' % integralCenterAll)
self.debug('==> %.2f%% +/- %.2f%%' % (integralCenterAll/hDeltaTAllHo.Integral()*100
,calcSigma(integralCenterAll, hDeltaTAllHo.Integral())*100))
self.debug(80*'#')
paveText = TPaveText(0.6,0.7,0.9,0.75,'NDC')
paveText.AddText('%s' % ('Central peak contains (filtered hist.)'))
paveText.AddText('%.2f%% +/- %.2f%%' % (integralCenter/hDeltaTCleanHo.Integral()*100,calcSigma(integralCenter, hDeltaTCleanHo.Integral())*100))
paveText.SetBorderSize(1)
paveText.Draw()
label = getLabelCmsPrivateSimulation()
label.Draw()
c.Update()
self.storeCanvas(c,"deltaTime")
return c, hDeltaTCleanHo
def plotHoL1Correlation():
#Select whether matching to all HO should also be plotted
plotBoth = True
histAll = fileHandler.getHistogram('hoMuonAnalyzer/correlation/L1MuonPresentHoMatch_TimeCorrelation')
histAboveThr = fileHandler.getHistogram('hoMuonAnalyzer/correlation/L1MuonAboveThr_TimeCorrelation')
label = getLabelCmsPrivateSimulation()
canvas = TCanvas("canvasHoL1Correlation","canvasHoL1Correlation",1600,1200)
if(plotBoth):
canvas.Divide(2,1)
canvas.cd(1).SetLogz()
histNew = getTH2D("histNew","Correlation between L1 BX ID and HO;HO time / ns;L1 / BX ID",5,-37.5,87.5#24,-56.25,93.75
,5,-2.5,2.5)
xAxis = histAll.GetXaxis()
yAxis = histAll.GetYaxis()
nBinsX = xAxis.GetNbins()
nBinsY = yAxis.GetNbins()
#Fill new histogram with fewer bins
for i in range( 1 , nBinsX + 1 ):
for j in range( 1 , nBinsY + 1 ):
histNew.Fill(xAxis.GetBinCenter(i),yAxis.GetBinCenter(j)/25.,histAll.GetBinContent(i,j))
histNew.SetStats(0)
histNew.Draw('colz')
canvas.Update()
pal = histNew.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
#Calcualte fraction at (0,0)
nCentral = histNew.GetBinContent(histNew.FindBin(0,0))
nTotal = histNew.Integral()
fraction = nCentral/float(nTotal)
fractionUncert = calcSigma(nCentral,nTotal)
sliceFraction = 0
for i in range(0,5):
sliceFraction += histNew.GetBinContent(histNew.FindBin(0,-2.5+i))
sliceFractionUncert = calcSigma(sliceFraction,nTotal)
sliceFraction /= nTotal
paveText = TPaveText(0.1,0.8,0.5,0.9,'NDC')
paveText.AddText('Fraction at (0,0): %5.2f%% #pm %5.2f%%' % (fraction*100, fractionUncert*100))
paveText.AddText('Fraction at (0,x): %5.2f%% #pm %5.2f%%' % (sliceFraction*100, sliceFractionUncert*100))
paveText.SetBorderSize(1)
paveText.Draw()
label.Draw()
canvas.cd(2).SetLogz()
histAboveThr.SetStats(0)
xAxis = histAboveThr.GetXaxis()
yAxis = histAboveThr.GetYaxis()
nBinsX = xAxis.GetNbins()
nBinsY = yAxis.GetNbins()
histNewAboveThr = getTH2D("histNewAboveThr","Correlation between L1 BX ID and HO > E_{Thr};HO time / ns;L1 / BX ID",5,-37.5,87.5#,12,-56.25,93.75
,5,-2.5,2.5)
for i in range( 1 , nBinsX + 1 ):
for j in range( 1 , nBinsY + 1 ):
histNewAboveThr.Fill(xAxis.GetBinCenter(i),yAxis.GetBinCenter(j)/25.,histAboveThr.GetBinContent(i,j))
histNewAboveThr.SetStats(0)
histNewAboveThr.Draw('colz')
canvas.Update()
pal = histNewAboveThr.GetListOfFunctions().FindObject("palette")
pal.SetX2NDC(0.92)
#Calcualte fraction at (0,0)
nCentral = histNewAboveThr.GetBinContent(histNewAboveThr.FindBin(0,0))
nTotal = histNewAboveThr.Integral()
fraction = nCentral/float(nTotal)
fractionUncert = calcSigma(nCentral,nTotal)
sliceFraction = 0
for i in range(0,5):
sliceFraction += histNewAboveThr.GetBinContent(histNewAboveThr.FindBin(0,-2.5+i))
sliceFractionUncert = calcSigma(sliceFraction,nTotal)
sliceFraction /= nTotal
paveTextAboveThr = TPaveText(0.1,0.8,0.5,0.9,'NDC')
paveTextAboveThr.AddText('Fraction at (0,0): %5.2f%% #pm %5.2f%%' % (fraction*100, fractionUncert*100))
paveTextAboveThr.AddText('Fraction at (0,x): %5.2f%% #pm %5.2f%%' % (sliceFraction*100, sliceFractionUncert*100))
paveTextAboveThr.SetBorderSize(1)
paveTextAboveThr.Draw()
label.Draw()
canvas.Update()
canvas.SaveAs('plots/timeCorrelation/l1AndHoCorrelation.pdf')
canvas.SaveAs('plots/timeCorrelation/l1AndHoCorrelation.png')
return canvas,histAll,histAboveThr,label,histNewAboveThr, histNew,paveTextAboveThr
