def addMCStatError(self):
histoData = filter(lambda x: x.isMC(), self.histos.getHistoDataList())
if len(histoData) == 0:
# Only data histograms
return
ROOT.gStyle.SetErrorX(0.5)
hse = HistoTotalUncertainty(histoData, "MC Stat. Err.")
hse.call(styles.getErrorStyle())
self.histos.append(hse)
def addMCStatError(self):
histoData = filter(lambda x: x.isMC(), self.histos.getHistoDataList())
if len(histoData) == 0:
# Only data histograms
return
ROOT.gStyle.SetErrorX(0.5)
hse = HistoTotalUncertainty(histoData, "MC Stat. Err.")
hse.call(styles.getErrorStyle())
self.histos.append(hse)
tauPts.setHistoLegendStyle("Data", "p")
# Apply the default styles (for all histograms, for MC histograms, for a single histogram)
# tauPts.forEachHisto(styles.generator())
# tauPts.forEachMCHisto(styles.generator(fill=True, fillStyle=3002)) # Example how to set non-default fill style
tauPts.forEachMCHisto(styles.generator(fill=True)) # Apply SetFillColor too, needed for histogram stacking
tauPts.forHisto("Data", styles.getDataStyle())
tauPts.setHistoDrawStyle("Data", "EP")
# Example how to stack all MC datasets
# Note: this MUST be done after all legend/style manipulation
tauPts.stackMCHistograms()
# Example how to add MC uncertainty
tauPts.addMCUncertainty(styles.getErrorStyle())
# tauPts.addMCUncertainty(styles.getErrorStyle(), "MC uncertainty")
# Create TCanvas and TH1F such that they cover all histograms
cf = histograms.CanvasFrame(tauPts, "taupt")
# cf = histograms.CanvasFrame(tauPts, "taupt", ymin=10, ymax=1e9) # for logy
# Set the frame options, e.g. axis labels
cf.frame.GetXaxis().SetTitle("Tau p_{T} (GeV/c)")
cf.frame.GetYaxis().SetTitle(ylabel)
# Legend
legend = histograms.createLegend(0.7, 0.5, 0.9, 0.8)
tauPts.addToLegend(legend)
# Draw the plots
def Save(self, name):
if len(self.histogramsNotFound) > 0:
for name in self.histogramsNotFound:
print "Histo", name, "not found"
self.histogramsNotFound = []
return
hObserved = self.histograms[self.FindHistoIndex(
self.dataHistos[0].name)].Clone("Data")
hObserved.Reset()
for histo in self.dataHistos:
hObserved.Add(self.histograms[self.FindHistoIndex(histo.label)])
print " Data: ", hObserved.Integral(
0, hObserved.GetNbinsX()), "events"
hEstimatedEWKfake = self.histograms[self.FindHistoIndex(
"EWKfake")].Clone("hEstimatedEWKfake")
print " EWKfake: ", hEstimatedEWKfake.Integral(
0, hEstimatedEWKfake.GetNbinsX()), "events"
hEstimatedEWK = self.histograms[self.FindHistoIndex("EWK")].Clone(
"hEstimatedEWK")
print " EWK: ", hEstimatedEWK.Integral(
0, hEstimatedEWK.GetNbinsX()), "events"
hEstimatedEWK.Add(hEstimatedEWKfake)
hEstimatedQCD = self.histograms[self.FindHistoIndex("QCD")].Clone(
"hEstimatedQCD")
print " QCD: ", hEstimatedQCD.Integral(
0, hEstimatedQCD.GetNbinsX()), "events"
hEstimatedQCD.Add(hEstimatedEWK)
hUncertainty = hEstimatedQCD.Clone("BackgrUncertainty")
hUncertainty.SetFillColor(1)
hUncertainty.SetFillStyle(3354)
hUncertainty.SetLineColor(0)
hUncertainty.SetLineStyle(0)
hUncertainty.SetLineWidth(0)
hUncertainty.SetMarkerColor(0)
hUncertainty.SetMarkerSize(0)
hSignal = self.histograms[self.FindHistoIndex("Signal")].Clone(
"hSignal")
print " Signal: ", hSignal.Integral(0,
hSignal.GetNbinsX()), "events"
hSignal.Add(hEstimatedQCD)
style = tdrstyle.TDRStyle()
plot = plots.ComparisonManyPlot(histograms.Histo(hObserved, "Data"), [
histograms.Histo(hUncertainty, "Backgr.Uncertainty"),
histograms.Histo(hEstimatedEWKfake, "EWKfake"),
histograms.Histo(hEstimatedEWK, "EWK"),
histograms.Histo(hEstimatedQCD, "QCD"),
histograms.Histo(hSignal, "Signal")
])
plot.histoMgr.forHisto("Data", styles.getDataStyle())
plot.histoMgr.forHisto("EWK", styles.getEWKStyle())
plot.histoMgr.forHisto("EWKfake", styles.getEWKFakeStyle())
plot.histoMgr.forHisto("QCD", styles.getQCDStyle())
plot.histoMgr.forHisto("Signal", styles.getSignalStyle())
plot.histoMgr.forHisto("Backgr.Uncertainty", styles.getErrorStyle())
plot.histoMgr.setHistoDrawStyleAll("HIST")
plot.histoMgr.setHistoDrawStyle("Data", "EP")
plot.histoMgr.setHistoDrawStyle("Backgr.Uncertainty", "E2")
plot.histoMgr.setHistoLegendStyleAll("F")
plot.histoMgr.setHistoLegendStyle("Data", "P")
plot.histoMgr.setHistoLegendStyle("Signal", "L")
plot.createFrame(name, opts={"ymin": 0, "ymaxfactor": 1.2})
plot.frame.GetXaxis().SetTitle(self.xtitle)
plot.frame.GetYaxis().SetTitle(self.ytitle)
plot.histoMgr.reorderLegend(
["Data", "Signal", "QCD", "EWK", "EWKfake", "Backgr.Uncertainty"])
self.setLegendLabels(plot)
plot.setLegend(histograms.createLegend(0.55, 0.68, 0.9, 0.93))
histograms.addCmsPreliminaryText()
histograms.addEnergyText()
histograms.addLuminosityText(x=None, y=None, lumi=self.lumi)
plot.draw()
plot.save()
tauPts.setHistoLegendStyle("Data", "p")
# Apply the default styles (for all histograms, for MC histograms, for a single histogram)
#tauPts.forEachHisto(styles.generator())
#tauPts.forEachMCHisto(styles.generator(fill=True, fillStyle=3002)) # Example how to set non-default fill style
tauPts.forEachMCHisto(styles.generator(fill=True)) # Apply SetFillColor too, needed for histogram stacking
tauPts.forHisto("Data", styles.getDataStyle())
tauPts.setHistoDrawStyle("Data", "EP")
# Example how to stack all MC datasets
# Note: this MUST be done after all legend/style manipulation
tauPts.stackMCHistograms()
# Example how to add MC uncertainty
tauPts.addMCUncertainty(styles.getErrorStyle())
#tauPts.addMCUncertainty(styles.getErrorStyle(), "MC uncertainty")
# Create TCanvas and TH1F such that they cover all histograms
cf = histograms.CanvasFrame(tauPts, "taupt")
#cf = histograms.CanvasFrame(tauPts, "taupt", ymin=10, ymax=1e9) # for logy
# Set the frame options, e.g. axis labels
cf.frame.GetXaxis().SetTitle("Tau p_{T} (GeV/c)")
cf.frame.GetYaxis().SetTitle(ylabel)
# Legend
legend = histograms.createLegend(0.7, 0.5, 0.9, 0.8)
tauPts.addToLegend(legend)
# Draw the plots
def Save(self, name):
if len(self.histogramsNotFound) > 0:
for name in self.histogramsNotFound:
print "Histo",name,"not found"
self.histogramsNotFound = []
return
hObserved = self.histograms[self.FindHistoIndex(self.dataHistos[0].name)].Clone("Data")
hObserved.Reset()
for histo in self.dataHistos:
hObserved.Add(self.histograms[self.FindHistoIndex(histo.label)])
print " Data: ", hObserved.Integral(0,hObserved.GetNbinsX()),"events"
hEstimatedEWKfake = self.histograms[self.FindHistoIndex("EWKfake")].Clone("hEstimatedEWKfake")
print " EWKfake: ",hEstimatedEWKfake.Integral(0,hEstimatedEWKfake.GetNbinsX()),"events"
hEstimatedEWK = self.histograms[self.FindHistoIndex("EWK")].Clone("hEstimatedEWK")
print " EWK: ",hEstimatedEWK.Integral(0,hEstimatedEWK.GetNbinsX()),"events"
hEstimatedEWK.Add(hEstimatedEWKfake)
hEstimatedQCD = self.histograms[self.FindHistoIndex("QCD")].Clone("hEstimatedQCD")
print " QCD: ",hEstimatedQCD.Integral(0,hEstimatedQCD.GetNbinsX()),"events"
hEstimatedQCD.Add(hEstimatedEWK)
hUncertainty = hEstimatedQCD.Clone("BackgrUncertainty")
hUncertainty.SetFillColor(1)
hUncertainty.SetFillStyle(3354)
hUncertainty.SetLineColor(0)
hUncertainty.SetLineStyle(0)
hUncertainty.SetLineWidth(0)
hUncertainty.SetMarkerColor(0)
hUncertainty.SetMarkerSize(0)
hSignal = self.histograms[self.FindHistoIndex("Signal")].Clone("hSignal")
print " Signal: ",hSignal.Integral(0,hSignal.GetNbinsX()),"events"
hSignal.Add(hEstimatedQCD)
style = tdrstyle.TDRStyle()
plot = plots.ComparisonManyPlot(
histograms.Histo(hObserved, "Data"),
[
histograms.Histo(hUncertainty, "Backgr.Uncertainty"),
histograms.Histo(hEstimatedEWKfake, "EWKfake"),
histograms.Histo(hEstimatedEWK, "EWK"),
histograms.Histo(hEstimatedQCD, "QCD"),
histograms.Histo(hSignal, "Signal")
]
)
plot.histoMgr.forHisto("Data", styles.getDataStyle())
plot.histoMgr.forHisto("EWK",styles.getEWKStyle())
plot.histoMgr.forHisto("EWKfake",styles.getEWKFakeStyle())
plot.histoMgr.forHisto("QCD",styles.getQCDStyle())
plot.histoMgr.forHisto("Signal",styles.getSignalStyle())
plot.histoMgr.forHisto("Backgr.Uncertainty",styles.getErrorStyle())
plot.histoMgr.setHistoDrawStyleAll("HIST")
plot.histoMgr.setHistoDrawStyle("Data", "EP")
plot.histoMgr.setHistoDrawStyle("Backgr.Uncertainty", "E2")
plot.histoMgr.setHistoLegendStyleAll("F")
plot.histoMgr.setHistoLegendStyle("Data", "P")
plot.histoMgr.setHistoLegendStyle("Signal", "L")
plot.createFrame(name, opts={"ymin":0, "ymaxfactor": 1.2})
plot.frame.GetXaxis().SetTitle(self.xtitle)
plot.frame.GetYaxis().SetTitle(self.ytitle)
plot.histoMgr.reorderLegend(["Data", "Signal", "QCD", "EWK", "EWKfake", "Backgr.Uncertainty"])
self.setLegendLabels(plot)
plot.setLegend(histograms.createLegend(0.55,0.68,0.9,0.93))
histograms.addCmsPreliminaryText()
histograms.addEnergyText()
histograms.addLuminosityText(x=None, y=None, lumi=self.lumi)
plot.draw()
plot.save()