def rebin(h, name):
myBinning = []
if name.startswith("MT"):
myBinning = systematics.getBinningForPlot("shapeTransverseMass")
#myBinning = [0,20,40,60,80,100,120,140,160,200,400]
elif name.startswith("INVMASS"):
myBinning = systematics.getBinningForPlot("shapeInvariantMass")
else:
raise Exception("Unknown binning information")
myArray = array.array("d", myBinning)
# Rebin and move under/overflow bins to visible bins
h = h.Rebin(len(myBinning) - 1, "", myArray)
h.SetBinContent(1, h.GetBinContent(0) + h.GetBinContent(1))
h.SetBinError(1,
math.sqrt(h.GetBinContent(0)**2 + h.GetBinContent(1)**2))
h.SetBinContent(
h.GetNbinsX() + 1,
h.GetBinContent(h.GetNbinsX() + 1) +
h.GetBinContent(h.GetNbinsX() + 2))
h.SetBinError(
h.GetNbinsX() + 1,
math.sqrt(
h.GetBinError(h.GetNbinsX() + 1)**2 +
h.GetBinError(h.GetNbinsX() + 2)**2))
h.SetBinContent(0, 0.0)
h.SetBinError(0, 0.0)
h.SetBinContent(h.GetNbinsX() + 2, 0.0)
h.SetBinError(h.GetNbinsX() + 2, 0.0)
return h
def rebin(h, name):
myBinning = []
if name.startswith("MT"):
myBinning = systematics.getBinningForPlot("shapeTransverseMass")
elif name.startswith("INVMASS"):
myBinning = systematics.getBinningForPlot("shapeInvariantMass")
else:
raise Exception("Unknown binning information")
maxBin = h.GetXaxis().GetBinUpEdge(h.GetNbinsX())
if maxBin < myBinning[-1]:
print WarningLabel()+"Adjust rebinning last bin from %.0f to %.0f because that is the up edge of last bin in the historam" % (myBinning[-1], maxBin)
myBinning[-1] = 500
myArray = array.array("d",myBinning)
# Rebin and move under/overflow bins to visible bins
h = h.Rebin(len(myBinning)-1,"",myArray)
histogramsExtras.makeFlowBinsVisible(h)
return h
def doPurityPlots(opts, histoName, dsetMgr, moduleInfoString, myDir, luminosity, myShapePurityHistograms):
def handleOverflow(h):
h.SetBinContent(1, h.GetBinContent(0)+h.GetBinContent(1))
h.SetBinError(1, math.sqrt(h.GetBinContent(0)**2 + h.GetBinContent(1)**2))
h.SetBinContent(h.GetNbinsX()+1, h.GetBinContent(h.GetNbinsX()+1)+h.GetBinContent(h.GetNbinsX()+2))
h.SetBinError(h.GetNbinsX()+1, math.sqrt(h.GetBinError(h.GetNbinsX()+1)**2 + h.GetBinError(h.GetNbinsX()+2)**2))
h.SetBinContent(0, 0.0)
h.SetBinError(0, 0.0)
h.SetBinContent(h.GetNbinsX()+2, 0.0)
h.SetBinError(h.GetNbinsX()+2, 0.0)
myQCDShape = DataDrivenQCDShape(dsetMgr, "Data", "EWK", histoName, luminosity)
mySplit = histoName.split("/")
histoName = mySplit[len(mySplit)-1]
# Get data and EWK histograms
hData = myQCDShape.getIntegratedDataHisto()
hEWK = myQCDShape.getIntegratedEwkHisto()
# Rebin and handle overflow
myBinning = systematics.getBinningForPlot(histoName)
myArray = array.array("d",myBinning)
hData = hData.Rebin(len(myBinning)-1,"",myArray)
hEWK = hEWK.Rebin(len(myBinning)-1,"",myArray)
handleOverflow(hData)
handleOverflow(hEWK)
# Create purity histo
hPurity = aux.Clone(hData)
hPurity.Reset()
# Calculate purity
for i in xrange(1, hPurity.GetNbinsX()+1):
myPurity = 0.0
myUncert = 0.0
nData = hData.GetBinContent(i)
nEWK = hEWK.GetBinContent(i)
if (nData > 0.0):
myPurity = (nData - nEWK) / nData
if myPurity < 0.0:
myPurity = 0.0
myUncert = 0.0
else:
myUncert = sqrt(myPurity * (1.0-myPurity) / nData) # Assume binomial error
hPurity.SetBinContent(i, myPurity)
hPurity.SetBinError(i, myUncert)
# Find out tail killer scenario
myScenario = ""
if "QCDTailKillerLoose" in moduleInfoString:
myScenario = "Loose"
elif "QCDTailKillerMedium" in moduleInfoString:
myScenario = "Medium"
if "QCDTailKillerTight" in moduleInfoString:
myScenario = "Tight"
myScenario += " R_{bb}^{min.}"
# Make histogram
hPurity.SetLineColor(styles.styles[len(myShapePurityHistograms)].color)
hPurity.SetMarkerColor(styles.styles[len(myShapePurityHistograms)].color)
hPurity.SetMarkerStyle(styles.styles[len(myShapePurityHistograms)].marker)
# Plot
histo = histograms.Histo(hPurity, myScenario, drawStyle="", legendStyle="lp")
myShapePurityHistograms.append(histo)
def rebin(h, name):
myBinning = []
if name.startswith("MT"):
myBinning = systematics.getBinningForPlot("shapeTransverseMass")
elif name.startswith("INVMASS"):
myBinning = systematics.getBinningForPlot("shapeInvariantMass")
else:
raise Exception("Unknown binning information")
maxBin = h.GetXaxis().GetBinUpEdge(h.GetNbinsX())
if maxBin < myBinning[-1]:
print WarningLabel(
) + "Adjust rebinning last bin from %.0f to %.0f because that is the up edge of last bin in the historam" % (
myBinning[-1], maxBin)
myBinning[-1] = 500
myArray = array.array("d", myBinning)
# Rebin and move under/overflow bins to visible bins
h = h.Rebin(len(myBinning) - 1, "", myArray)
histogramsExtras.makeFlowBinsVisible(h)
return h
def rebin(h, name):
myBinning = []
if name.startswith("MT"):
myBinning = systematics.getBinningForPlot("shapeTransverseMass")
#myBinning = [0,20,40,60,80,100,120,140,160,200,400]
elif name.startswith("INVMASS"):
myBinning = systematics.getBinningForPlot("shapeInvariantMass")
else:
raise Exception("Unknown binning information")
myArray = array.array("d",myBinning)
# Rebin and move under/overflow bins to visible bins
h = h.Rebin(len(myBinning)-1,"",myArray)
h.SetBinContent(1, h.GetBinContent(0)+h.GetBinContent(1))
h.SetBinError(1, math.sqrt(h.GetBinContent(0)**2 + h.GetBinContent(1)**2))
h.SetBinContent(h.GetNbinsX()+1, h.GetBinContent(h.GetNbinsX()+1)+h.GetBinContent(h.GetNbinsX()+2))
h.SetBinError(h.GetNbinsX()+1, math.sqrt(h.GetBinError(h.GetNbinsX()+1)**2 + h.GetBinError(h.GetNbinsX()+2)**2))
h.SetBinContent(0, 0.0)
h.SetBinError(0, 0.0)
h.SetBinContent(h.GetNbinsX()+2, 0.0)
h.SetBinError(h.GetNbinsX()+2, 0.0)
return h
import cProfile
import HiggsAnalysis.HeavyChHiggsToTauNu.tools.dataset as dataset
import HiggsAnalysis.HeavyChHiggsToTauNu.tools.plots as plots
import HiggsAnalysis.HeavyChHiggsToTauNu.tools.systematics as systematics
from HiggsAnalysis.HeavyChHiggsToTauNu.tools.analysisModuleSelector import *
from HiggsAnalysis.HeavyChHiggsToTauNu.qcdCommon.dataDrivenQCDCount import *
from HiggsAnalysis.HeavyChHiggsToTauNu.qcdFactorised.qcdFactorisedResult import *
from HiggsAnalysis.HeavyChHiggsToTauNu.tools.ShellStyles import *
from HiggsAnalysis.HeavyChHiggsToTauNu.tools.pseudoMultiCrabCreator import *
myMtSpecs = {
"basicName": "QCDfactorised/MtAfterStandardSelections",
"leg1Name": "QCDfactorised/MtAfterLeg1",
"leg2Name": "QCDfactorised/MtAfterLeg2",
"binList": systematics.getBinningForPlot("shapeTransverseMass"),
}
myFullMassSpecs = {
"basicName": "QCDfactorised/MassAfterStandardSelections",
"leg1Name": "QCDfactorised/MassAfterLeg1",
"leg2Name": "QCDfactorised/MassAfterLeg2",
"binList": systematics.getBinningForPlot("shapeInvariantMass"),
}
def doNominalModule(myMulticrabDir, era, searchMode, optimizationMode,
myOutputCreator, myShapeString, myDisplayStatus):
# Construct info string of module
myModuleInfoString = "%s_%s_%s" % (era, searchMode, optimizationMode)
# Obtain dataset manager
def doPurityPlots(opts, histoName, dsetMgr, moduleInfoString, myDir,
luminosity, myShapePurityHistograms):
def handleOverflow(h):
h.SetBinContent(1, h.GetBinContent(0) + h.GetBinContent(1))
h.SetBinError(1,
math.sqrt(h.GetBinContent(0)**2 + h.GetBinContent(1)**2))
h.SetBinContent(
h.GetNbinsX() + 1,
h.GetBinContent(h.GetNbinsX() + 1) +
h.GetBinContent(h.GetNbinsX() + 2))
h.SetBinError(
h.GetNbinsX() + 1,
math.sqrt(
h.GetBinError(h.GetNbinsX() + 1)**2 +
h.GetBinError(h.GetNbinsX() + 2)**2))
h.SetBinContent(0, 0.0)
h.SetBinError(0, 0.0)
h.SetBinContent(h.GetNbinsX() + 2, 0.0)
h.SetBinError(h.GetNbinsX() + 2, 0.0)
myQCDShape = DataDrivenQCDShape(dsetMgr, "Data", "EWK", histoName,
luminosity)
mySplit = histoName.split("/")
histoName = mySplit[len(mySplit) - 1]
# Get data and EWK histograms
hData = myQCDShape.getIntegratedDataHisto()
hEWK = myQCDShape.getIntegratedEwkHisto()
# Rebin and handle overflow
if "EWKGenuineTaus" in histoName:
myBinning = [0, 20, 40, 60, 80, 100, 120, 140, 160, 200, 300, 700]
else:
myBinning = systematics.getBinningForPlot(
histoName) #(histoName.replace("EWKGenuineTaus",""))
myArray = array.array("d", myBinning)
hData = hData.Rebin(len(myBinning) - 1, "", myArray)
hEWK = hEWK.Rebin(len(myBinning) - 1, "", myArray)
handleOverflow(hData)
handleOverflow(hEWK)
# Create purity histo
hPurity = aux.Clone(hData)
hPurity.Reset()
# Calculate purity
for i in xrange(1, hPurity.GetNbinsX() + 1):
myPurity = 0.0
myUncert = 0.0
nData = hData.GetBinContent(i)
nEWK = hEWK.GetBinContent(i)
if (nData > 0.0):
myPurity = (nData - nEWK) / nData
if myPurity < 0.0:
myPurity = 0.0
myUncert = 0.0
else:
myUncert = sqrt(myPurity * (1.0 - myPurity) /
nData) # Assume binomial error
hPurity.SetBinContent(i, myPurity)
hPurity.SetBinError(i, myUncert)
# Find out tail killer scenario
myScenario = ""
if "QCDTailKillerLoose" in moduleInfoString:
myScenario = "Loose"
elif "QCDTailKillerMedium" in moduleInfoString:
myScenario = "Medium"
if "QCDTailKillerTight" in moduleInfoString:
myScenario = "Tight"
myScenario += " R_{bb}^{min.}"
# Make histogram
hPurity.SetLineColor(styles.styles[len(myShapePurityHistograms)].color)
hPurity.SetMarkerColor(styles.styles[len(myShapePurityHistograms)].color)
hPurity.SetMarkerStyle(styles.styles[len(myShapePurityHistograms)].marker)
# Plot
histo = histograms.Histo(hPurity,
myScenario,
drawStyle="",
legendStyle="lp")
myShapePurityHistograms.append(histo)
def createPlot(name):
if mtOnly and "shapeTransverseMass" not in name:
return None
drhEmb = getDRH(dsetEmb, name, systematicsEmbMC)
drhSig = getDRH(dsetSig, name, systematicsSigMC)
drhEmb.normalizeToLuminosity(lumi)
drhSig.normalizeToLuminosity(lumi)
drhEmb.setName("Embedded")
drhSig.setName("Normal")
if addData:
drhEmbData = getDRH(dsetEmbData, name, None)
drhEmbData.setName("Embedded data")
if "shapeTransverseMass" in name and "TTJets" in datasetName:
doScaleFactors(drhSig.getHistogramWithUncertainties(),
drhEmb.getHistogramWithUncertainties(), outputDir,
opts)
if addData:
p = plots.ComparisonManyPlot(drhSig, [drhEmb, drhEmbData])
else:
p = plots.ComparisonManyPlot(drhSig, [drhEmb])
p.setLuminosity(lumi)
legLabel = plots._legendLabels.get(datasetName, datasetName)
legEmb = "Embedded " + legLabel
#legSig = "Normal "+legLabel
#legSig = legLabel
legSig = "Non-emb. %s with ^{}#tau_{h}" % legLabel
if addEventCounts:
legEmb += " (" + strIntegral(drhEmb.getHistogram()) + ")"
legSig += " (" + strIntegral(drhSig.getHistogram()) + ")"
p.histoMgr.setHistoLegendLabelMany({
"Embedded": legEmb,
"Normal": legSig,
})
#p.histoMgr.forEachHisto(styles.generator())
hemb = p.histoMgr.getHisto("Embedded")
hemb.setDrawStyle("HIST E")
hemb.setLegendStyle("L")
themb = hemb.getRootHisto()
#styles.ttStyle.apply(themb)
themb.SetLineColor(ROOT.kBlue)
themb.SetLineWidth(2)
themb.SetMarkerColor(themb.GetLineColor())
themb.SetMarkerSize(0)
hsig = p.histoMgr.getHisto("Normal")
hsig.setLegendStyle("F")
thsig = hsig.getRootHisto()
thsig.SetFillColor(ROOT.kGray)
thsig.SetLineColor(thsig.GetFillColor())
histoOrder = ["Embedded", "Normal"]
if addData:
legData = "Embedded data"
histoOrder.append("Embedded data")
if addEventCounts:
legData += " (" + strIntegral(drhEmbData.getHistogram()) + ")"
p.histoMgr.setHistoLegendLabelMany({"Embedded data": legData})
p.histoMgr.forHisto("Embedded data", styles.dataStyle)
p.histoMgr.setHistoDrawStyle("Embedded data", "EP")
p.histoMgr.setHistoLegendStyle("Embedded data", "P")
p.histoMgr.reorderDraw(["Embedded data", "Embedded", "Normal"])
if opts.dofit:
p.setDrawOptions(ratioYlabel="Norm./Emb.",
ratioInvert=True,
ratioType="errorPropagation")
if "shapeTransverseMass" in name and "TTJets" in datasetName:
binning = systematics.getBinningForPlot("shapeTransverseMass")
p.setDrawOptions(
customizeBeforeSave=lambda p: doScaleFactorFit(
p, outputDir),
rebin=range(0, 160, 20) + binning[binning.index(160):])
else:
# p.setDrawOptions(ratioYlabel="Emb./Norm.")
p.setDrawOptions(ratioYlabel="Emb./Non-emb.")
p.histoMgr.reorder(histoOrder)
return p
def compare(step):
if step is None:
path = "shapeTransverseMass"
else:
path = "CommonPlots/AtEveryStep/%s/MET_MET" % step
#bins = range(0, 200, 20) + [200, 250, 300, 500]
bins = systematics.getBinningForPlot("shapeTransverseMass")
def getTH1(ds):
drh = ds.getDatasetRootHisto(path)
drh.normalizeToLuminosity(lumi)
th1 = drh.getHistogram()
#th1.Rebin(2)
#return th1
return th1.Rebin(len(bins)-1, th1.GetName(), array.array("d", bins))
th1NormalNum = getTH1(dsetNormalNum)
th1NormalDenom = getTH1(dsetNormalDenom)
#print th1NormalNum.Integral(0, th1NormalNum.GetNbinsX()+1), th1NormalDenom.Integral(0, th1NormalDenom.GetNbinsX()+1)
th1EmbNum = getTH1(dsetEmbNum)
th1EmbDenom = getTH1(dsetEmbDenom)
#print th1EmbNum.Integral(0, th1EmbNum.GetNbinsX()+1), th1EmbDenom.Integral(0, th1EmbDenom.GetNbinsX()+1)
effNormal = ROOT.TGraphAsymmErrors(th1NormalNum, th1NormalDenom, "n")
effEmb = ROOT.TGraphAsymmErrors(th1EmbNum, th1EmbDenom, "n")
effNormal.SetName("Normal ttbar")
effEmb.SetName("Embedded ttbar")
p = plots.ComparisonManyPlot(effNormal, [effEmb])
p.setLuminosity(lumi)
p.histoMgr.forEachHisto(styles.generator())
#p.histoMgr.forHisto("Normal ttbar", lambda h: doStyle(h, ROOT.kBlack, ROOT.kFullCircle))
#p.histoMgr.forHisto("Embedded ttbar", lambda h: doStyle(h, ROOT.kRed, ROOT.kFullSquare))
p.histoMgr.setHistoDrawStyleAll("EP")
p.histoMgr.setHistoLegendStyleAll("EPL")
unc1 = 1.12
unc2 = 0.88
p.prependPlotObjectToRatio(doLineStyle(ROOT.TLine(0, unc1, bins[-1], unc1)))
p.prependPlotObjectToRatio(doLineStyle(ROOT.TLine(0, unc2, bins[-1], unc2)))
p.appendPlotObject(histograms.PlotText(x=0.6, y=0.6, text="CaloMET > 70 GeV", size=20))
global ind
ind += 1
# plots.drawPlot(p, "calometComparison/eff_%02d_calomet_%s"%(ind, step), xlabel="Type I PF MET (GeV)", ylabel="CaloMET cut efficiency",
# ratio=True, ratioYlabel="Norm./emb.", ratioType="errorScale",
# opts={"xmin": 0, "xmax": 500},
# opts2={"ymin": 0.8, "ymax": 1.2},
# addLuminosityText=True, moveLegend={"dx": -0.2, "dy": -0.5})
plots.drawPlot(p, "calometComparison/eff_%d_calomet_shapeTransverseMass"%ind, xlabel="Transverse mass (GeV)", ylabel="CaloMET cut efficiency",
ratio=True, ratioYlabel="Emb./Norm.", ratioCreateLegend=True, ratioType="errorScale",
opts={"ymax": 1.2},
opts2={"ymin": 0.8, "ymax": 1.2},
addLuminosityText=True, moveLegend={"dx": -0.2, "dy": -0.5})
import cProfile
import HiggsAnalysis.HeavyChHiggsToTauNu.tools.dataset as dataset
import HiggsAnalysis.HeavyChHiggsToTauNu.tools.plots as plots
import HiggsAnalysis.HeavyChHiggsToTauNu.tools.systematics as systematics
from HiggsAnalysis.HeavyChHiggsToTauNu.tools.analysisModuleSelector import *
from HiggsAnalysis.HeavyChHiggsToTauNu.qcdCommon.dataDrivenQCDCount import *
from HiggsAnalysis.HeavyChHiggsToTauNu.qcdFactorised.qcdFactorisedResult import *
from HiggsAnalysis.HeavyChHiggsToTauNu.tools.ShellStyles import *
from HiggsAnalysis.HeavyChHiggsToTauNu.tools.pseudoMultiCrabCreator import *
myMtSpecs = {
"basicName": "QCDfactorised/MtAfterStandardSelections",
"leg1Name": "QCDfactorised/MtAfterLeg1",
"leg2Name": "QCDfactorised/MtAfterLeg2",
"binList": systematics.getBinningForPlot("shapeTransverseMass"),
}
myFullMassSpecs = {
"basicName": "QCDfactorised/MassAfterStandardSelections",
"leg1Name": "QCDfactorised/MassAfterLeg1",
"leg2Name": "QCDfactorised/MassAfterLeg2",
"binList": systematics.getBinningForPlot("shapeInvariantMass"),
}
def doNominalModule(myMulticrabDir,era,searchMode,optimizationMode,myOutputCreator,myShapeString,myDisplayStatus):
# Construct info string of module
myModuleInfoString = "%s_%s_%s"%(era, searchMode, optimizationMode)
# Obtain dataset manager
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=myMulticrabDir)
dsetMgr = dsetMgrCreator.createDatasetManager(dataEra=era,searchMode=searchMode,optimizationMode=optimizationMode)
def compare(step):
if step is None:
path = "shapeTransverseMass"
else:
path = "CommonPlots/AtEveryStep/%s/MET_MET" % step
#bins = range(0, 200, 20) + [200, 250, 300, 500]
bins = systematics.getBinningForPlot("shapeTransverseMass")
def getTH1(ds):
drh = ds.getDatasetRootHisto(path)
drh.normalizeToLuminosity(lumi)
th1 = drh.getHistogram()
#th1.Rebin(2)
#return th1
return th1.Rebin(
len(bins) - 1, th1.GetName(), array.array("d", bins))
th1NormalNum = getTH1(dsetNormalNum)
th1NormalDenom = getTH1(dsetNormalDenom)
#print th1NormalNum.Integral(0, th1NormalNum.GetNbinsX()+1), th1NormalDenom.Integral(0, th1NormalDenom.GetNbinsX()+1)
th1EmbNum = getTH1(dsetEmbNum)
th1EmbDenom = getTH1(dsetEmbDenom)
#print th1EmbNum.Integral(0, th1EmbNum.GetNbinsX()+1), th1EmbDenom.Integral(0, th1EmbDenom.GetNbinsX()+1)
effNormal = ROOT.TGraphAsymmErrors(th1NormalNum, th1NormalDenom, "n")
effEmb = ROOT.TGraphAsymmErrors(th1EmbNum, th1EmbDenom, "n")
effNormal.SetName("Normal ttbar")
effEmb.SetName("Embedded ttbar")
p = plots.ComparisonManyPlot(effNormal, [effEmb])
p.setLuminosity(lumi)
p.histoMgr.forEachHisto(styles.generator())
#p.histoMgr.forHisto("Normal ttbar", lambda h: doStyle(h, ROOT.kBlack, ROOT.kFullCircle))
#p.histoMgr.forHisto("Embedded ttbar", lambda h: doStyle(h, ROOT.kRed, ROOT.kFullSquare))
p.histoMgr.setHistoDrawStyleAll("EP")
p.histoMgr.setHistoLegendStyleAll("EPL")
unc1 = 1.12
unc2 = 0.88
p.prependPlotObjectToRatio(
doLineStyle(ROOT.TLine(0, unc1, bins[-1], unc1)))
p.prependPlotObjectToRatio(
doLineStyle(ROOT.TLine(0, unc2, bins[-1], unc2)))
p.appendPlotObject(
histograms.PlotText(x=0.6, y=0.6, text="CaloMET > 70 GeV",
size=20))
global ind
ind += 1
# plots.drawPlot(p, "calometComparison/eff_%02d_calomet_%s"%(ind, step), xlabel="Type I PF MET (GeV)", ylabel="CaloMET cut efficiency",
# ratio=True, ratioYlabel="Norm./emb.", ratioType="errorScale",
# opts={"xmin": 0, "xmax": 500},
# opts2={"ymin": 0.8, "ymax": 1.2},
# addLuminosityText=True, moveLegend={"dx": -0.2, "dy": -0.5})
plots.drawPlot(p,
"calometComparison/eff_%d_calomet_shapeTransverseMass" %
ind,
xlabel="Transverse mass (GeV)",
ylabel="CaloMET cut efficiency",
ratio=True,
ratioYlabel="Emb./Norm.",
ratioCreateLegend=True,
ratioType="errorScale",
opts={"ymax": 1.2},
opts2={
"ymin": 0.8,
"ymax": 1.2
},
addLuminosityText=True,
moveLegend={
"dx": -0.2,
"dy": -0.5
})