def doPlot(datasetsEmb, analyses, path, name, text):
histos = []
legends = {"Plus": "#tau-jet energy scale variated by +3 %",
"Minus": "#tau-jet energy scale variated by -3 %"}
for aname, analysis in analyses:
(rootHisto, tmp) = datasetsEmb.getHistogram("Data", analysis+"/"+path)
h = histograms.Histo(rootHisto, aname)
h.setLegendLabel(legends.get(aname, aname))
h.setDrawStyle("EP")
h.setLegendStyle("p")
histos.append(h)
p = plots.ComparisonManyPlot(histos[0], histos[1:])
p.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(20))
styles.dataStyle(p.histoMgr.getHisto("Baseline"))
styles.mcStyle(p.histoMgr.getHisto("Plus"))
styles.mcStyle2(p.histoMgr.getHisto("Minus"))
p.histoMgr.getHisto("Minus").getRootHisto().SetMarkerSize(2)
p.setLuminosity(datasetsEmb.getLuminosity())
p.createFrame(name, createRatio=True, opts2={"ymax": 2}, opts={"ymax": 35})
yaxis = p.getFrame2().GetYaxis()
yaxis.SetTitle("Ratio")
#yaxis.SetTitleSize(yaxis.GetTitleSize()*0.8)
p.setLegend(histograms.moveLegend(histograms.createLegend()))
p.appendPlotObject(histograms.PlotText(0.5, 0.55, text, size=20))
p.frame.GetXaxis().SetTitle("m_{T}(#tau jet, E_{T}^{miss}) (GeV/c^{2})")
p.frame.GetYaxis().SetTitle("Events / 20 GeV/c^{2}")
p.draw()
p.addStandardTexts()
p.save()
def doPlot(datasets, analyses, path, name, rootFile=None, rootHistoName=None):
histos = []
legends = {
"Plus": "#tau-jet energy scale variated by +3 %",
"Minus": "#tau-jet energy scale variated by -3 %"
}
for aname, analysis in analyses:
p = None
if isinstance(path, basestring):
p = plots.DataMCPlot(datasets, analysis + "/" + path)
else:
p = plots.DataMCPlot(datasets, path.clone(tree=analysis + "/tree"))
if normalize:
tauEmbedding.scaleNormalization(p)
h = p.histoMgr.getHisto("Data")
h.setName(aname)
h.setLegendLabel(legends.get(aname, aname))
histos.append(h)
p = plots.ComparisonManyPlot(histos[0], histos[1:])
p.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(20))
if rootFile:
baseline = histos[0].getRootHisto().Clone("EWKtau_" + rootHistoName)
baseline.SetDirectory(rootFile)
baseline.Write()
plus = histos[1].getRootHisto().Clone("EWKtau_JESUp_" + rootHistoName)
plus.SetDirectory(rootFile)
plus.Write()
minus = histos[2].getRootHisto().Clone("EWKtau_JESDown_" +
rootHistoName)
minus.SetDirectory(rootFile)
minus.Write()
styles.mcStyle(p.histoMgr.getHisto("Plus"))
styles.mcStyle2(p.histoMgr.getHisto("Minus"))
p.histoMgr.getHisto("Minus").getRootHisto().SetMarkerSize(2)
p.setLuminosity(datasets.getDataset("Data").getLuminosity())
p.createFrame(name, createRatio=True, opts2={"ymax": 2}, opts={"ymax": 40})
yaxis = p.getFrame2().GetYaxis()
yaxis.SetTitle("Ratio")
#yaxis.SetTitleSize(yaxis.GetTitleSize()*0.8)
p.setLegend(histograms.moveLegend(histograms.createLegend()))
p.frame.GetXaxis().SetTitle("m_{T}(#tau jet, E_{T}^{miss}) (GeV/c^{2})")
p.frame.GetYaxis().SetTitle("Events / 20 GeV/c^{2}")
p.draw()
p.addStandardTexts()
p.save()
def doPlot(datasets, analyses, path, name, rootFile=None, rootHistoName=None):
histos = []
legends = {"Plus": "#tau-jet energy scale variated by +3 %",
"Minus": "#tau-jet energy scale variated by -3 %"}
for aname, analysis in analyses:
p = None
if isinstance(path, basestring):
p = plots.DataMCPlot(datasets, analysis+"/"+path)
else:
p = plots.DataMCPlot(datasets, path.clone(tree=analysis+"/tree"))
if normalize:
tauEmbedding.scaleNormalization(p)
h = p.histoMgr.getHisto("Data")
h.setName(aname)
h.setLegendLabel(legends.get(aname, aname))
histos.append(h)
p = plots.ComparisonManyPlot(histos[0], histos[1:])
p.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(20))
if rootFile:
baseline = histos[0].getRootHisto().Clone("EWKtau_"+rootHistoName)
baseline.SetDirectory(rootFile)
baseline.Write()
plus = histos[1].getRootHisto().Clone("EWKtau_JESUp_"+rootHistoName)
plus.SetDirectory(rootFile)
plus.Write()
minus = histos[2].getRootHisto().Clone("EWKtau_JESDown_"+rootHistoName)
minus.SetDirectory(rootFile)
minus.Write()
styles.mcStyle(p.histoMgr.getHisto("Plus"))
styles.mcStyle2(p.histoMgr.getHisto("Minus"))
p.histoMgr.getHisto("Minus").getRootHisto().SetMarkerSize(2)
p.setLuminosity(datasets.getDataset("Data").getLuminosity())
p.createFrame(name, createRatio=True, opts2={"ymax": 2}, opts={"ymax": 40})
yaxis = p.getFrame2().GetYaxis()
yaxis.SetTitle("Ratio")
#yaxis.SetTitleSize(yaxis.GetTitleSize()*0.8)
p.setLegend(histograms.moveLegend(histograms.createLegend()))
p.frame.GetXaxis().SetTitle("m_{T}(#tau jet, E_{T}^{miss}) (GeV/c^{2})")
p.frame.GetYaxis().SetTitle("Events / 20 GeV/c^{2}")
p.draw()
histograms.addCmsPreliminaryText()
histograms.addEnergyText()
p.addLuminosityText()
p.save()
def doPlot(datasetsEmb, analyses, path, name, text):
histos = []
legends = {
"Plus": "#tau-jet energy scale variated by +3 %",
"Minus": "#tau-jet energy scale variated by -3 %"
}
for aname, analysis in analyses:
(rootHisto, tmp) = datasetsEmb.getHistogram("Data",
analysis + "/" + path)
h = histograms.Histo(rootHisto, aname)
h.setLegendLabel(legends.get(aname, aname))
h.setDrawStyle("EP")
h.setLegendStyle("p")
histos.append(h)
p = plots.ComparisonManyPlot(histos[0], histos[1:])
p.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(20))
styles.dataStyle(p.histoMgr.getHisto("Baseline"))
styles.mcStyle(p.histoMgr.getHisto("Plus"))
styles.mcStyle2(p.histoMgr.getHisto("Minus"))
p.histoMgr.getHisto("Minus").getRootHisto().SetMarkerSize(2)
p.setLuminosity(datasetsEmb.getLuminosity())
p.createFrame(name, createRatio=True, opts2={"ymax": 2}, opts={"ymax": 35})
yaxis = p.getFrame2().GetYaxis()
yaxis.SetTitle("Ratio")
#yaxis.SetTitleSize(yaxis.GetTitleSize()*0.8)
p.setLegend(histograms.moveLegend(histograms.createLegend()))
p.appendPlotObject(histograms.PlotText(0.5, 0.55, text, size=20))
p.frame.GetXaxis().SetTitle("m_{T}(#tau jet, E_{T}^{miss}) (GeV/c^{2})")
p.frame.GetYaxis().SetTitle("Events / 20 GeV/c^{2}")
p.draw()
histograms.addCmsPreliminaryText()
histograms.addEnergyText()
p.addLuminosityText()
p.save()
def doPlot(datasetsEmb, analyses, path, name, text):
histos = []
legends = {"Plus": taujetH+" energy scale varied by +3 %",
"Minus": taujetH+" energy scale varied by -3 %"}
for aname, analysis in analyses:
(rootHisto, tmp) = datasetsEmb.getHistogram("Data", analysis+"/"+path)
h = histograms.Histo(rootHisto, aname)
h.setLegendLabel(legends.get(aname, aname))
h.setDrawStyle("EP")
h.setLegendStyle("p")
histos.append(h)
p = plots.ComparisonManyPlot(histos[0], histos[1:])
styles.dataStyle(p.histoMgr.getHisto("Nominal"))
styles.mcStyle(p.histoMgr.getHisto("Plus"))
styles.mcStyle2(p.histoMgr.getHisto("Minus"))
p.histoMgr.getHisto("Minus").getRootHisto().SetMarkerSize(2)
p.setLuminosity(datasetsEmb.getLuminosity())
p.appendPlotObject(histograms.PlotText(0.45, 0.55, text, size=20))
plots.drawPlot(p, name, "m_{T}(^{}%s, ^{}E_{T}^{miss}) (GeV/^{}c^{2})"%taujet, ylabel="Events / %d GeV/^{}c^{2}",
rebin=20, ratio=True, opts={"ymax": 35, "xmax": 300}, opts2={"ymax": 2}, addLuminosityText=True)
def doQCDfactorisedResultPlots(opts, dsetMgr, moduleInfoString, myDir, luminosity):
# Set here the names of the histograms you want to access
myBasicName = "QCDfactorised/MtAfterStandardSelections"
myLeg1Name = "QCDfactorised/MtAfterLeg1"
myLeg2Name = "QCDfactorised/MtAfterLeg2"
# Obtain QCD shapes
myBasicShape = DataDrivenQCDShape(dsetMgr, "Data", "EWK", myBasicName, luminosity)
myLeg1Shape = DataDrivenQCDShape(dsetMgr, "Data", "EWK", myLeg1Name, luminosity)
myLeg2Shape = DataDrivenQCDShape(dsetMgr, "Data", "EWK", myLeg2Name, luminosity)
# Calculate final shape in signal region (leg1 * leg2 / basic)
myResult = QCDFactorisedResult(myBasicShape, myLeg1Shape, myLeg2Shape, myHistoSpecs, moduleInfoString)
hTotalQCD = myResult.getResultShape().Clone()
# Do plotting - this needs to be edited to use tdr style ...
c1 = ROOT.TCanvas()
c1.Draw()
hTotalQCD.Draw()
c1.Print("%s/QCDShape_total_%s.png"%(myDir, moduleInfoString))
for i in range(0,len(myResult.getNQCDHistograms())):
c = ROOT.TCanvas()
c.Draw()
myResult.getNQCDHistograms()[i].Draw()
myBinTitle = myBasicShape.getPhaseSpaceBinFileFriendlyTitle(i)
c.Print("%s/QCDShape_%s_%s.png"%(myDir, myBinTitle, moduleInfoString))
# Do systematics coming from met shape difference
# Set here the names of the histograms you want to access
myCtrlRegionName = "QCDfactorised/MtAfterStandardSelections"
mySignalRegionName = "QCDfactorised/MtAfterLeg2"
# Obtain QCD shapes
myCtrlRegion = DataDrivenQCDShape(dsetMgr, "Data", "EWK", myCtrlRegionName, luminosity)
mySignalRegion = DataDrivenQCDShape(dsetMgr, "Data", "EWK", mySignalRegionName, luminosity)
# Calculate
mySyst = SystematicsForMetShapeDifference(mySignalRegion, myCtrlRegion, myResult.getResultShape(), myHistoSpecs, moduleInfoString)
print "Evaluated MET shape systematics"
# Do plotting
#mySyst
hNominal = myResult.getResultShape().Clone()
hUp = mySyst.getUpHistogram().Clone()
hDown = mySyst.getDownHistogram().Clone()
hNominal.SetLineColor(ROOT.kBlack)
hUp.SetLineColor(ROOT.kBlue)
hDown.SetLineColor(ROOT.kRed)
hNominal.Draw()
myYmax = 15
if "2012" in moduleInfoString:
myYmax = 70
plot = plots.ComparisonManyPlot(histograms.Histo(hNominal, "Nominal"),
[histograms.Histo(hUp, "Up"), histograms.Histo(hDown, "Down")])
plot.createFrame("%s/QCDShapeWithMetSyst_%s_%s"%(myDir, myBinTitle, moduleInfoString), createRatio=True, opts2={"ymin": -2.5, "ymax": 2.5}, opts={"addMCUncertainty": True, "ymin": -5, "ymax": myYmax, "xmin": 0, "xmax": 500})
plot.frame.GetXaxis().SetTitle("Transverse mass, GeV/c^{2}")
plot.frame.GetYaxis().SetTitle("N_{events}")
plot.setLegend(histograms.createLegend(0.59, 0.70, 0.87, 0.90))
plot.legend.SetFillColor(0)
plot.legend.SetFillStyle(1001)
styles.mcStyle(plot.histoMgr.getHisto("Up"))
plot.histoMgr.getHisto("Up").getRootHisto().SetMarkerSize(0)
styles.mcStyle2(plot.histoMgr.getHisto("Down"))
#hRatioDown = hDown.Clone()
#hRatioUp = hUp.Clone()
#hRatioDown.Divide(hNominal)
#hRatioUp.Divide(hNominal)
#plot.setRatios([hRatioUp,hRatioDown])
plot.setLuminosity(luminosity)
if "2012" in moduleInfoString:
plot.setEnergy("8")
else:
plot.setEnergy("7")
plot.addStandardTexts()
#plot.setDrawOptions({addMCUncertainty: True})
plot.draw()
plot.save()
if False:
c2 = ROOT.TCanvas()
c2.Draw()
hNominal = myResult.getResultShape().Clone()
hUp = mySyst.getUpHistogram().Clone()
hDown = mySyst.getDownHistogram().Clone()
hNominal.SetLineColor(ROOT.kBlack)
hUp.SetLineColor(ROOT.kBlue)
hDown.SetLineColor(ROOT.kRed)
hNominal.Draw()
hUp.Draw("same")
hDown.Draw("same")
c2.Print("%s/QCDShapeWithMetSyst_%s_%s.png"%(myDir, myBinTitle, moduleInfoString))
print HighlightStyle()+"doQCDfactorisedResultPlots is ready"+NormalStyle()