def zGammaMixture(plot="met"): cut = "1" nunuTree = readTree("slimZGammaNuNu_V03.18_tree.root", "photonTree") zIncTree = readTree("slimZGamma_V03.18_tree.root", "photonTree") nBins = range(80, 500, 10) if plot == "photons[0].pt" else readAxisConf(plot)[2] h_nunu = getHisto(nunuTree, plot, cut + "&&photons[0].pt>=130", nBins=nBins, color=2) h_zInc = getHisto(zIncTree, plot, cut + "&&photons[0].pt<130", nBins=nBins, color=4) mh = Multihisto() mh.addHisto(h_nunu, "#gammaZ#rightarrow#gamma#nu#nu(p_{T}#geq130GeV)", draw="e", toStack=True) mh.addHisto(h_zInc, "#gammaZ(p_{T}<130GeV)", draw="e", toStack=True) mh.Draw() if plot == "photons[0].pt": l = ROOT.TLine(130, 0, 130, 1) l.Draw() SavePad("inclusiveAndIsrSample_%s" % plot)
def closure( filenames, plot, treename="photonJetTree" ): commonCut = "[email protected]() && [email protected]()" #commonCut = "1" leptonPtCut = 15 # only larger than 15 make sense here, since this is the reprocessing cut commonCut = "([email protected]() || Max$(electrons.pt)<{0}) && ([email protected]() || Max$(muons.pt)<{0})".format(leptonPtCut) totalHist = getHists( filenames, plot, cut=commonCut, treeName=treename ) gGenHist = getHists( filenames, plot, cut="photons[0].isGen(0) && "+commonCut, treeName=treename ) eGenHist = getHists( filenames, plot, cut="photons[0].isGen(1) && "+commonCut, treeName=treename ) gGenHist.SetLineColor(2) eGenHist.SetLineColor(3) gDatasetAbbrs = [getDatasetAbbr(f) for f in filenames ] gDatasetAbbrs = mergeDatasetAbbr( gDatasetAbbrs ) multihisto = Multihisto() multihisto.leg.SetHeader( "/".join([ datasetToLatex(x) for x in gDatasetAbbrs]) ) multihisto.addHisto( totalHist, "Simulation", draw="e0 hist" ) multihisto.addHisto( gGenHist, "gen #gamma", toStack=True, draw="e0 hist" ) multihisto.addHisto( eGenHist, "gen e", toStack=True, draw="e0 hist" ) infoText = ROOT.TLatex(0.03,.96, "CMS Private Work - 8TeV #geq1#gamma,#geq2jets" ) infoText.SetNDC() can = ROOT.TCanvas() can.cd() multihisto.Draw() infoText.Draw() r = Ratio( "Sim./Pred.", totalHist, multihisto.stack.GetStack().Last() ) r.draw(0,2) SaveAs( can, "genMatches_%s_%s"%(getSaveNameFromDatasets(filenames), plot)) ROOT.SetOwnership( can, False ) del can
def compareFiles(plot, filenames, treename, diff): tree1 = readTree(filenames[0], treename) tree2 = readTree(filenames[1], treename) if diff: cut1, cut2 = getEventNumberDiff(tree1, tree2) tree1 = getTreeFriendsWithBooleanVariable(tree1, cut1) tree2 = getTreeFriendsWithBooleanVariable(tree2, cut2) h1 = createHistoFromTree(tree1, plot, "x") h2 = createHistoFromTree(tree2, plot, "x") else: h1 = getHisto(tree1, plot, weight="1") h2 = getHisto(tree2, plot, weight="1") mini = min(h1.GetBinLowEdge(1), h2.GetBinLowEdge(1)) maxi = max(h2.GetBinLowEdge(h2.GetNbinsX() + 2), h1.GetBinLowEdge(h1.GetNbinsX() + 2)) h1 = getHisto(tree1, plot, weight="1", firstBin=mini, lastBin=maxi) h2 = getHisto(tree2, plot, weight="1", firstBin=mini, lastBin=maxi) h2.SetLineColor(2) mh = Multihisto() name1 = getVersion(filenames[0]) name2 = getVersion(filenames[1]) mh.addHisto(h1, name1, draw="hist e") mh.addHisto(h2, name2, draw="hist e") mh.Draw() from myRatio import Ratio r = Ratio("%s/%s" % (name1, name2), h1, h2) r.draw() plot = "test" ROOT.gPad.GetCanvas().SaveAs("compareFiles_%s.pdf" % plot)
def drawGenComposition2Samples(treeName, sample1, sample2): histos = { "W": sample1.plot(treeName, cut="1"), "W (gen #gamma)": sample1.plot(treeName, cut="photons[0].isGen(0)"), "W (gen e)": sample1.plot(treeName, cut="photons[0].isGen(1)"), "W (gen had)": sample1.plot(treeName, cut="photons[0].isGen(3)"), "#gammaW": sample2.plot(treeName, cut="1"), "#gammaW (gen #gamma)": sample2.plot(treeName, cut="photons[0].isGen(0)"), "#gammaW (gen e)": sample2.plot(treeName, cut="photons[0].isGen(1)"), "#gammaW (gen had)": sample2.plot(treeName, cut="photons[0].isGen(2)"), } mh = Multihisto() for name, h in histos.iteritems(): if "(gen #gamma)" in name: h.SetLineStyle(2) if "(gen e)" in name: h.SetLineStyle(3) if "(gen had)" in name: h.SetLineStyle(4) mh.addHisto(h, name) can = ROOT.TCanvas() can.cd() mh.Draw() info = PlotCaption(treeName=treeName) info.Draw() allDatasetAbbr = sample1.datasetAbbr + sample2.datasetAbbr plot = "met" SaveAs(can, "composition2samples_%s_%s_%s" % (treeName, plot, allDatasetAbbr))
def drawSignalContamination(filename, xy, split): import array label, unit, binning = readAxisConf("met") metBinning = array.array("d", binning) gHisto = readHisto(filename, "gMet%s_%s" % xy).Rebin( len(metBinning) - 1, randomName(), metBinning) eHisto = readHisto(filename, "eMet%s_%s" % xy).Rebin( len(metBinning) - 1, randomName(), metBinning) fHisto = readHisto(filename, "fMet%s_%s" % xy).Rebin( len(metBinning) - 1, randomName(), metBinning) eHisto = applyFakeRateEWK(eHisto) eContamination = divideHistos(eHisto, gHisto) eContamination.SetLineColor(2) fContamination = divideHistos(fHisto, gHisto) fContamination.SetLineColor(4) totalContamination = divideHistos(addHistos([eHisto, fHisto]), gHisto) totalContamination.SetLineColor(1) totalContamination.SetMarkerColor(1) for h in [totalContamination, fContamination, eContamination]: h.Scale(100.) # in % h.GetYaxis().SetTitleOffset(0.9) h.SetTitle(";%s [#text{%s}];Signal Contamination [%s]" % ("#met", unit, "%")) h.SetLineWidth(2) h.SetMarkerSize(0) h.SetLabelSize(1. / 15.8447, "xy") h.SetTitleSize(1. / 15.8447, "xy") mh = Multihisto() mh.setMinimum(0) if split: mh.addHisto(totalContamination, "Total", draw="pe") mh.addHisto(fContamination, "b_{#text{signal}}^{#text{QCD}}/s", draw="hist") mh.addHisto(eContamination, "b_{#text{signal}}^{e#rightarrow#gamma}/s", draw="hist") else: mh.addHisto(totalContamination, "", draw="e0") can = ROOT.TCanvas() can.cd() can.SetLogy(False) mh.Draw() totalContamination.Draw("same") info.Draw() saveName = "signalContamination_%s_%s_%s_%s" % (xy + (split, filename[0:-4])) SaveAs(can, saveName) ROOT.gPad.SaveAs("/home/knut/master/documents/thesis/plots/%stex" % saveName) correctTiksPlot("/home/knut/master/documents/thesis/plots/%stex" % saveName)
def drawPileUpHistos(saveTex=False): inputHistPath = "../TreeWriter/pileUpReweighting/" data = readHisto(inputHistPath + "nTrueVertexData.root", "pileup") data.SetLineColor(1) data.SetMarkerColor(1) data.SetMarkerStyle(20) data.Sumw2() if saveTex: data.SetMarkerSize(.8) else: data.SetMarkerSize(1.2) mc = readHisto(inputHistPath + "nTrueVertexMC.root", "pileupS10") mc.SetLineColor(2) mc.SetMarkerColor(2) for h in [mc, data]: h.Scale(1. / h.Integral()) h.SetTitle(";Number of Pile-up Events;Normalized Entries") if saveTex: h.SetLineWidth(2) h.SetTitleSize(0.06311227345609463, "yx") h.SetLabelSize(0.06311227345609463, "yx") muhist = Multihisto() muhist.addHisto(data, "Data", draw="ep") muhist.addHisto(mc, "Simulation", draw="hist") muhist.setMinimum(0) if saveTex: muhist.leg.SetTextSize(0.063112267888) texStyle() pc1 = ROOT.TLatex(0, .96, "CMS Private Work") pc2 = ROOT.TLatex(.76, .96, "\SI{19.8}{fb^{-1}} #sqrt{s}=\SI{8}{TeV}") masterPath = "~/master/documents/thesis/plots/" can = ROOT.TCanvas("", "", 2000, 1000) can.cd() can.SetLogy(0) muhist.Draw() for pc in [pc1, pc2]: pc.SetNDC() if saveTex: pc.SetTextSize(0.06311227345609463) pc.Draw() ending = 'tex' if saveTex else 'pdf' ROOT.gPad.SaveAs(masterPath + "puDistribution.%s" % ending)
def drawClosure(filenames, predFilenames, plot, commonCut, infoText, additionalLabel="", modifyEmptyBins=True): infoText = ROOT.TLatex( 0, .96, "CMS Private Work 19.7fb^{-1} #sqrt{s}=8TeV #geq1#gamma,#geq2jets") infoText.SetNDC() infoText.SetTextSize(0.045) gHist = getHists(filenames, plot, commonCut) fHist, sysHist = predictionHistos(predFilenames, plot, commonCut, modifyEmptyBins) fHist.SetMarkerSize(0) sysHist.SetFillStyle(3254) sysHist.SetFillColor(sysHist.GetLineColor()) sysHist.SetLineColor(0) signalAbbrs = mergeDatasetAbbr([getDatasetAbbr(x) for x in filenames]) muhisto = Multihisto() muhisto.leg.SetHeader(",".join([datasetToLatex(x) for x in signalAbbrs])) muhisto.addHisto(gHist, "Simulation", draw="") muhisto.addHisto(fHist, "Prediction", draw="hist e") muhisto.addHisto(sysHist, "syst. uncert", draw="e2") muhisto.addHisto(gHist, "", draw="e0") ## add a second time to draw on top can = ROOT.TCanvas("", "", 1000, 1200) can.cd() muhisto.Draw() from myRatio import Ratio r = Ratio("Sim./Pred.", gHist, fHist, sysHist) r.draw(0., 2) infoText.Draw() muhisto.leg.AddEntry(r.totalUncert, "total uncert", "f") muhisto.leg.Draw() SaveAs(can, "qcdClosure_%s_%s" % ("".join(signalAbbrs) + additionalLabel, plot)) # Since root is too stupid to clear the canvas before python is ending, clean # the canvas yourself ROOT.SetOwnership(can, False) del can
def drawMCStack(treeName="photonTree"): mh = Multihisto() mh.orderByIntegral = False datasetsToStack = [gz, tt, wjets, qcd, gjets] mh = fillMh(mh, datasetsToStack, treeName) can = ROOT.TCanvas() can.cd() mh.Draw() info = PlotCaption(treeName=treeName) info.Draw() allDatasetAbbr = ''.join([x.datasetAbbr for x in datasetsToStack]) plot = "met" SaveAs(can, "stackedHisto_%s_%s_%s" % (treeName, plot, allDatasetAbbr))
def drawGenComposition(treeName, sample): mh = Multihisto() mh.addHisto(sample.plot(treeName, cut="photons[0].isGen(0)", color=2), "gen #gamma") mh.addHisto(sample.plot(treeName, cut="photons[0].isGen(1)", color=3), "gen e") mh.addHisto(sample.plot(treeName, cut="photons[0].isGen(2)", color=4), "gen hadron") mh.addHisto(sample.plot(treeName, cut="1", color=1), "inclusive") can = ROOT.TCanvas() can.cd() mh.Draw() info = PlotCaption(treeName=treeName) info.Draw() allDatasetAbbr = sample.datasetAbbr plot = "met" SaveAs(can, "composition_%s_%s_%s" % (treeName, plot, allDatasetAbbr))
def closure( filenames, plot ): leptonPtCut = 15 # only larger than 15 make sense here, since this is the reprocessing cut commonCut = "([email protected]() || Max$(electrons.pt)<{0}) && ([email protected]() || Max$(muons.pt)<{0})".format(leptonPtCut) #commonCut = "1" totalHist = getHists( filenames, plot, cut=commonCut ) gGenHist = getHists( filenames, plot, cut="photons[0].isGen(0) && "+commonCut ) eHist = multiDimFakeRate( filenames, plot, commonCut, False ) fakeHist = predictionHistos( filenames, plot, cut=commonCut )[0] fakeHist.SetLineColor(4) eHist.SetLineColor(3) gGenHist.SetLineColor(2) eHistSys = eHist.Clone( randomName() ) eHistSys = setRelativeUncertainty( eHistSys, 0.11 ) eHistSys.SetFillColor( eHistSys.GetLineColor() ) eHistSys.SetFillStyle(3354) eHistSys.SetMarkerSize(0) gDatasetAbbrs = [getDatasetAbbr(f) for f in filenames ] gDatasetAbbrs = mergeDatasetAbbr( gDatasetAbbrs ) multihisto = Multihisto() multihisto.setMinimum(0.01) multihisto.setMaximum(20) multihisto.leg.SetHeader( "/".join([ datasetToLatex(x) for x in gDatasetAbbrs]) ) multihisto.addHisto( totalHist, "Simulation", draw="e0 hist" ) multihisto.addHisto( fakeHist, "QCD", toStack=True, draw="hist" ) multihisto.addHisto( gGenHist, "gen#gamma", toStack=True, draw="e0 hist" ) multihisto.addHisto( eHist, "e#rightarrow#gamma", toStack=True, draw="hist" ) infoText = ROOT.TLatex(0.03,.96, "CMS Private Work - 8TeV #geq1#gamma,#geq2jets" ) infoText.SetNDC() can = ROOT.TCanvas() can.cd() multihisto.Draw() infoText.Draw() r = Ratio( "Sim./Pred.", totalHist, multihisto.stack.GetStack().Last() ) r.draw(0,2) SaveAs( can, "ewkPrediction_%s_%s"%(getSaveNameFromDatasets(filenames), plot)) ROOT.SetOwnership( can, False ) del can
def plotFakeRate(filenames, opts): mhisto = Multihisto() mhisto.legendOption = "lp" #mhisto.leg.SetHeader("Object matching") for iColor, filename in enumerate(filenames): mhisto.addHisto(getFakeRateHisto(filename, opts, iColor + 2), getDatasetAbbr(filename, slim=False), draw="") if opts.plot == "photons.pt": yuOrig = yutarosHistogramMC(1) mhisto.addHisto(yuOrig, "DY tag&probe", draw="") can = ROOT.TCanvas() can.cd() can.SetLogy(0) mhisto.Draw() saveName = "%s_%s_%s" % ("fakeRate", opts.plot, opts.savePrefix) can.SaveAs("plots/%s.pdf" % manipulateSaveName(saveName))
def compareTrees(plot="photons.pt", filename="slimQCD_V02.28_tree.root"): label, unit, binning = readAxisConf("photons[0].ptJet()") #binning = range(0,70,10) + binning #binning = range(0,1000, 30 ) import array gH = ROOT.TH1F(randomName(), ";jet_{x};", len(binning) - 1, array.array('d', binning)) fH = gH.Clone(randomName()) fH.SetLineColor(2) fH.SetMarkerColor(2) #cut = "!photons[0].isGen(0)" #cut = "1" gTree = readTree(filename, "photonTree") fTree = readTree(filename, "photonJetTree") #gH = getHisto( gTree, plot, color=1, cut=cut,firstBin=0,lastBin=1400 ) #fH = getHisto( fTree, plot, color=2, cut=cut,firstBin=0,lastBin=1400 ) for h, tree in [(gH, gTree), (fH, fTree)]: h.Sumw2() for event in tree: h.Fill(getFromEvent(event), event.weight) for h in [gH, fH]: h.Scale(1, "width") mh = Multihisto() mh.addHisto(gH, "#gamma", draw="hist e") mh.addHisto(fH, "#gamma_{jet}", draw="hist e") can = ROOT.TCanvas() can.cd() mh.Draw() from myRatio import Ratio r = Ratio("#gamma/#gamma_{jet}", gH, fH) r.draw(None, 2) SaveAs(can, "compare_test")
def drawTwoHists(gHist, fHist, sHist, saveName, minmax): for bin in range(sHist.GetNbinsX() + 2): sHist.SetBinError(bin, sHist.GetBinContent(bin)) sHist.SetBinContent(bin, fHist.GetBinContent(bin)) sHist.SetFillColor(sHist.GetLineColor()) sHist.SetLineColor(sHist.GetLineColor()) sHist.SetFillStyle(3254) sHist.SetMarkerSize(0) fHist.SetLineColor(2) sHist.SetLineColor(2) for h in gHist, fHist, sHist: from inheritRoot import H1F h.__class__ = H1F h.MergeOverflow() h.Scale(1., "width") muhisto = Multihisto() muhisto.addHisto(gHist, "Simulation", draw="hist e") muhisto.addHisto(fHist, "Prediction", draw="hist") muhisto.addHisto(sHist, "#sigma_{w}", draw="e2") can = ROOT.TCanvas(randomName(), "", 1000, 1200) can.cd() muhisto.Draw() text = ROOT.TLatex(.1, .965, "%i #leq p_{T^{*}} < %i, %i #leq H_{T} < %i" % minmax) text.SetNDC() text.Draw() from myRatio import Ratio r = Ratio("Sim./Pred.", gHist, fHist) r.draw(0, 2) can.SaveAs(saveName + ".pdf") ROOT.SetOwnership(can, False) del can
def compareBinnedSamples(histList1, histList2, plot="met"): cut = "[email protected]() && [email protected]()" treeName = "photonTree" mh = Multihisto() #if "ZGamma" in histList1[0]: # mh.setMinimum(0.01) # sum all histos in histList1 hist1 = None for fileName in histList1: datasetAbbr1 = getDatasetAbbr(fileName) tree = readTree(fileName, treeName) h = getHisto(tree, plot, cut=cut, color=colors[datasetAbbr1]) if hist1: hist1.Add(h) else: hist1 = h mh.addHisto(hist1, datasetToLatex(datasetAbbr1), draw="hist e") # stack histos in histList2 for fileName in histList2: datasetAbbr = getDatasetAbbr(fileName) tree = readTree(fileName, treeName) h = getHisto(tree, plot, cut=cut, color=colors[datasetAbbr]) mh.addHisto(h, datasetToLatex(datasetAbbr), toStack=True) mh.Draw() stack = mh.stack.GetStack().Last() stack.SetMarkerSize(0) stack.Draw("same e0") errorHist = mh.stack.GetStack().Last().Clone(randomName()) errorHist.SetMarkerColor(1) errorHist.Draw("same e") if plot != "met": datasetAbbr1 += plot SavePad("compareBinned" + datasetAbbr1)
def drawComparison( histName, mc, data ): hdata = getIsolationHist( data, histName ) hdata.SetLineColor(1) hmc = getIsolationHist( mc, histName ) hmc.SetLineColor(2) for h in hmc, hdata: h.SetLineWidth(2) hmc.Scale( hdata.Integral() / hmc.Integral() ) mh = Multihisto() mh.addHisto( hdata, "Data", draw="e0" ) mh.addHisto( hmc, "MC", draw="hist", toStack=True ) c = ROOT.TCanvas() mh.Draw() from myRatio import Ratio r = Ratio( "Data/Bkg", hdata, hmc ) r.draw(0,2) SavePad("isolationComparison_%s"%histName )
def compareTrees(plot="photons.pt", filename="slimAllQCD_V02.28_tree.root"): label, unit, binning = readAxisConf("ht") import array fH = ROOT.TH1F(randomName(), ";%s;" % label, len(binning) - 1, array.array('d', binning)) fH.SetLineColor(2) fH.SetMarkerColor(2) fH.Sumw2() #cut = "!photons[0].isGen(0)" cut = "1" gTree = readTree(filename, "photonTree") fTree = readTree(filename, "photonJetTree") gH = getHisto(gTree, "ht", color=1, cut=cut, firstBin=0, lastBin=1400) #fH = getHisto( fTree, plot, color=2, cut=cut,firstBin=0,lastBin=1400 ) for event in fTree: fH.Fill(getFromEvent(event)) for h in [gH, fH]: h.Scale(1. / h.Integral()) mh = Multihisto() mh.addHisto(gH, "new", draw="hist e") mh.addHisto(fH, "old (recalculated)", draw="hist e") can = ROOT.TCanvas() can.cd() mh.Draw() from myRatio import Ratio r = Ratio("#gamma/#gamma_{jet}", gH, fH) r.draw(0, 2) SaveAs(can, "compare_%s_norm" % plot)
def qcdCorrelation( filenames, plot ): signalCut = "met>=100" controlCut = "!(%s)"%signalCut commonCut = " && photons[0].ptJet()>100 && photons[0].ptJet()<120 " gControlHist = photonHisto( filenames, "photonTree", plot, controlCut+commonCut, True ) fControlHist = photonHisto( filenames, "photonJetTree", plot, controlCut+commonCut, True ) gSignalHist = photonHisto( filenames, "photonTree", plot, signalCut+commonCut, True ) fSignalHist = photonHisto( filenames, "photonJetTree", plot, signalCut+commonCut, True ) gSignalHist.SetLineColor(2) fSignalHist.SetLineColor(2) fSignalHist.SetLineStyle(2) fControlHist.SetLineStyle(2) for h in [gControlHist, fControlHist, gSignalHist, fSignalHist]: h.Scale( 1./h.Integral() ) h.SetMarkerSize(0) pass mh = Multihisto() mh.addHisto( gControlHist, "Control #gamma", draw="hist e" ) mh.addHisto( fControlHist, "Control #gamma_{jet}",draw="hist e" ) mh.addHisto( gSignalHist, "Signal #gamma",draw="hist e" ) mh.addHisto( fSignalHist, "Signal #gamma_{jet}",draw="hist e" ) can = ROOT.TCanvas() can.cd() mh.Draw() info = PlotCaption() info.Draw() abbrs = mergeDatasetAbbr( [ getDatasetAbbr(x) for x in filenames ] ) SaveAs( can, "correlation_%s_%s"%("".join(abbrs),plot ) )
def compareHists(filenames, tight, fcut, draw=False): loose = getHistoFromFiles("met", "photonJetTree", filenames, fcut) loose.SetLineColor(2) if loose.Integral(0, loose.FindBin(99)): loose.Scale( tight.Integral(0, loose.FindBin(99)) / loose.Integral(0, loose.FindBin(99))) option = "uu norm" if filenames[0].startswith("PhotonHad") else "ww" if draw: c = ROOT.TCanvas() c.cd() mh = Multihisto() mh.addHisto(tight.Clone(randomName()), "#gamma_{tight}", draw="hist e") mh.addHisto(loose, "#gamma_{loose}", draw="hist e") mh.Draw() from myRatio import Ratio r = Ratio("#gamma_{tight}/#gamma_{loose}", tight, loose) r.draw(0, 2) c.SaveAs("plots/findFoId_%s_twoDistributions_%s.pdf" % (getSaveNameFromDatasets(filenames), ''.join( [s for s in fcut if s.isdigit()]))) return tight.Chi2Test(loose, option)
def inclusiveAndIsrSamples(fList1, fList2, saveAffix=""): cut = "[email protected]() && [email protected]()" treeName = "photonTree" plot = "met" if saveAffix == "pt130": cut += " && photons[0].pt>130" saveAffix = "_" + saveAffix mh = Multihisto() h1 = getHists(fList1, plot, cut) h1gen = getHists(fList1, plot, cut + "&&photons[0].isGen(0)") h2 = getHists(fList2, plot, cut) h2gen = getHists(fList2, plot, cut + "&&photons[0].isGen(0)") for h in h2, h2gen: h.SetLineColor(2) for h in h1gen, h2gen: h.SetLineStyle(2) for h in [h2, h2gen, h1, h1gen]: h.SetLabelSize(1. / 31.5562 / 0.502113, "xyz") h.SetTitleSize(1. / 31.5562 / 0.502113, "xyz") h.GetXaxis().SetTitleOffset(1.1) h.GetYaxis().SetTitleOffset(0.85) if plot == "met": h.GetXaxis().SetTitle("#met#text{ [GeV]}") abbr1 = shortName(fList1) abbr2 = shortName(fList2) mh = Multihisto() if "ZGamma" in fList1[0]: mh.setMaximum(10) mh.setMinimum(2e-4) mh.leg.SetFillStyle(0) mh.leg.SetX1(0.6) mh.leg.SetY1(0.6) mh.addHisto(h1, datasetToLatex(abbr1)) mh.addHisto(h1gen, "#text{match to gen }#gamma") mh.addHisto(h2, datasetToLatex(abbr2)) mh.addHisto(h2gen, "#text{match to gen }#gamma") mh.Draw() info.SetTextSize(1. / 31.5562 / 0.502113) info.Draw() if "pt130" in saveAffix: cutInfo = ROOT.TLatex(.2, .8, "p_{T,#gamma}#geq#SI{130}{GeV}") cutInfo.SetNDC() info.SetTextSize(1. / 31.5562 / 0.502113) cutInfo.Draw() SavePad("inclusiveAndIsrSample_%s%s" % (abbr1, saveAffix)) ROOT.gPad.SaveAs( "/home/knut/master/documents/thesis/plots/inclusiveAndIsrSample_%s%s.tex" % (abbr1, saveAffix)) correctTiksPlot( "/home/knut/master/documents/thesis/plots/inclusiveAndIsrSample_%s%s.tex" % (abbr1, saveAffix))
def drawClosure(plot, gTree, foTree, cut, can, info, datasetAbbr, additionalInfo=""): # The first attempt to get the histogram is only to get the minimal # and maximal value on the x-axis, for not predefined binning h_gamma = getHisto(gTree, plot, cut=cut) h_fo = getHisto(foTree, plot, cut=cut) xMin, xMax = getXMinXMax([h_gamma, h_fo]) h_gamma = getHisto(gTree, plot, cut=cut, color=1, firstBin=xMin, lastBin=xMax) h_fo = getHisto(foTree, plot, cut=cut, weight="weight*w_qcd", color=46, firstBin=xMin, lastBin=xMax) h_fo_error = getQCDErrorHisto(foTree, plot, cut=cut, firstBin=xMin, lastBin=xMax) h_fo_error.SetFillColor(h_fo.GetLineColor()) h_fo_error.SetLineColor(h_fo_error.GetLineColor()) h_fo_error.SetFillStyle(3254) h_fo_error.SetMarkerSize(0) muhisto = Multihisto() muhisto.leg.SetHeader(datasetToLatex(datasetAbbr)) muhisto.addHisto(h_gamma, "#gamma", draw="hist e0") muhisto.addHisto(h_fo, "#gamma_{jet}#upointw", draw="hist e0") muhisto.addHisto(h_fo_error, "#sigma_{w}", draw="e2") hPad = ROOT.TPad("hPad", "Histogram", 0, 0.2, 1, 1) hPad.cd() muhisto.Draw() ratioPad = ROOT.TPad("ratioPad", "Ratio", 0, 0, 1, 0.2) ratioPad.cd() ratioPad.SetLogy(False) from myRatio import Ratio r = Ratio("#gamma/#gamma_{pred}", h_gamma, h_fo) ratio, sys, one = r.draw(0, 2) ratio.Draw("e1") sys.Draw("same e2") one.Draw() can.cd() hPad.Draw() ratioPad.Draw() info.Draw() SaveAs( can, "qcd_afterWeighting_%s_%s_%s" % (datasetAbbr + additionalInfo, plot, reweightVar)) ROOT.SetOwnership(hPad, False) ROOT.SetOwnership(ratioPad, False)
def drawBeforeClosure(plot, gTree, foTree, cut, can, info, datasetAbbr, additionalInfo="", norm=False): if plot == "met" and cut != "1": return # The first attempt to get the histogram is only to get the minimal # and maximal value on the x-axis, for not predefined binning h_gamma = getHisto(gTree, plot, cut=cut) h_fo = getHisto(foTree, plot, cut=cut) xMin, xMax = getXMinXMax([h_gamma, h_fo]) h_gamma = getHisto(gTree, plot, cut=cut, color=1, firstBin=xMin, lastBin=xMax) h_fo = getHisto(foTree, plot, cut=cut, color=46, firstBin=xMin, lastBin=xMax) if norm: for h in [h_gamma, h_fo]: h.Scale(1. / h.Integral()) h.GetYaxis().SetTitle("Normed Entries") muhisto = Multihisto() muhisto.leg.SetHeader(datasetToLatex(datasetAbbr)) muhisto.addHisto(h_gamma, "#gamma", draw="hist e0") muhisto.addHisto(h_fo, "#gamma_{jet}", draw="hist e0") hPad = ROOT.TPad("hPad", "Histogram", 0, 0.2, 1, 1) hPad.cd() muhisto.Draw() ROOT.TGaxis.SetMaxDigits(4) ratioPad = ROOT.TPad("ratioPad", "Ratio", 0, 0, 1, 0.2) ratioPad.cd() ratioPad.SetLogy(False) ratioGraph = ratios.RatioGraph(h_gamma, h_fo) ratioGraph.draw(ROOT.gPad, yMin=None, yMax=None, adaptiveBinning=False, errors="yx") ratioGraph.graph.Draw("same p e0") # draw nice points ratioGraph.hAxis.SetYTitle("#gamma/#gamma_{jet}") can.cd() hPad.Draw() ratioPad.Draw() info.Draw() SaveAs( can, "qcd_preWeight_%s_%s_%s" % (datasetAbbr + additionalInfo, plot, reweightVar)) ROOT.SetOwnership(hPad, False) ROOT.SetOwnership(ratioPad, False)
def zGammaCut(plot="photons[0].pt", merge=False): cut = "[email protected]() && [email protected]()" nunuTree = readTree("slimZGammaNuNu_V03.19b_tree.root", "photonTree") llTree = readTree("slimZGammaLL_V02.19b_tree.root", "photonTree") zIncTree = readTree("slimZGamma_V03.18_tree.root", "photonTree") nBins = range( 60, 500, 10 ) if plot == "photons[0].pt" or plot == "genPhotons[0].pt" else readAxisConf( plot)[2] h_nunu = getHisto(nunuTree, plot, cut + "&&genPhotons[0].pt>130", nBins=nBins, color=2) h_ll = getHisto(llTree, plot, cut, nBins=nBins, color=5) h_zInc = getHisto(zIncTree, plot, cut, nBins=nBins) llTree.AddFriend("photonTreeAddVariables", llTree.GetFile().GetName()) llPlot = "metLL" if plot == "met" else plot zMod = getHisto(llTree, llPlot, "genPhotons[0].pt<130", nBins=nBins, color=4) zMod.Scale(20. / (2. * 3.363)) mh = Multihisto() mh.orderByIntegral = False mh.setMinimum(0.01) mh.addHisto(h_nunu, "#gammaZ#rightarrow#gamma#nu#nu(p_{T#gamma}^{gen}#geq130GeV)", draw="e", toStack=True) mh.addHisto(zMod, "ll to #slash{E}_{T}", toStack=True) mh.addHisto(h_ll, "#gammaZ#rightarrow#gammall", draw="e", toStack=True) mh.addHisto(h_zInc, "#gammaZ", draw="e") if merge: h_nunuPart = getHisto(nunuTree, plot, cut + "&&genPhotons[0].pt>=130", nBins=nBins, color=6) h_zIncPart = getHisto(zIncTree, plot, cut + "&&genPhotons[0].pt<130", nBins=nBins, color=6) merged = addHistos([h_nunuPart, h_zIncPart]) mh.addHisto(merged, "merged", draw="e") mh.Draw() total = mh.stack.GetStack().Last().Clone(randomName()) total.SetFillStyle(3002) total.SetFillColor(1) total.Draw("same e2") if plot == "photons[0].pt": l = ROOT.TLine(130, 0, 130, 1) l.Draw() if merge: plot += "_merged" SavePad("zGammaCut_%s" % plot)
def drawPhi(filenames): t = readTree(filenames[0], "photonTree") for f in filenames[1:]: t.Add("%s/photonTree" % f) absolute = True label, unit, binning = readAxisConf("photons[0].phi") if absolute: binning = [x for x in binning if x >= 0] import array gH1 = ROOT.TH1F(randomName(), ";#Delta#phi(#gamma,#slash{E}_{T});", len(binning) - 1, array.array('d', binning)) gH2 = ROOT.TH1F(randomName(), ";#Delta#phi(#gamma,#slash{E}_{T});", len(binning) - 1, array.array('d', binning)) gH3 = ROOT.TH1F(randomName(), ";#Delta#phi(#gamma,#slash{E}_{T});", len(binning) - 1, array.array('d', binning)) gH2.SetLineColor(2) gH3.SetLineColor(3) for h in gH1, gH2, gH3: h.Sumw2() from math import fabs for e in t: dPhi = e.photons[0].DeltaPhi(e.metPhi) if absolute: dPhi = fabs(dPhi) if e.met < 10: gH1.Fill(dPhi) elif e.met < 100: gH2.Fill(dPhi) else: gH3.Fill(dPhi) ft = readTree(filenames[0], "photonJetTree") for f in filenames[1:]: ft.Add("%s/photonJetTree" % f) cutStr = "photons[0].chargedIso/100<2.6 && photons[0].neutralIso/100<3.5+0.04*photons[0].pt && photons[0].photonIso/100<1.3+0.005*photons[0].pt" cutStr += "&& (photons[0].chargedIso>0 || photons[0].neutralIso>0 || photons[0].photonIso>0)" ft = ft.CopyTree(cutStr) fH1 = ROOT.TH1F(randomName(), ";#Delta#phi(#gamma,#slash{E}_{T});", len(binning) - 1, array.array('d', binning)) fH2 = ROOT.TH1F(randomName(), ";#Delta#phi(#gamma,#slash{E}_{T});", len(binning) - 1, array.array('d', binning)) fH3 = ROOT.TH1F(randomName(), ";#Delta#phi(#gamma,#slash{E}_{T});", len(binning) - 1, array.array('d', binning)) fH2.SetLineColor(2) fH3.SetLineColor(3) for h in fH1, fH2, fH3: h.Sumw2() h.SetLineStyle(3) for e in ft: dPhi = e.photons[0].DeltaPhi(e.metPhi) if absolute: dPhi = fabs(dPhi) if e.met < 10: fH1.Fill(dPhi) elif e.met < 100: fH2.Fill(dPhi) else: fH3.Fill(dPhi) for h in gH1, gH2, gH3, fH1, fH2, fH3: if h.Integral(): h.Scale(1. / h.Integral(), "width") mh = Multihisto() mh.addHisto(gH1, "met<10", draw="hist ") mh.addHisto(fH1, "met<10, loose", draw="hist ") mh.addHisto(gH2, "10<met<100", draw="hist ") mh.addHisto(fH2, "10<met<100, loose", draw="hist ") mh.addHisto(gH3, "100<met", draw="hist ") mh.addHisto(fH3, "100<met, loose", draw="hist ") c = ROOT.TCanvas() c.cd() mh.Draw() c.SaveAs("plots/deltaPhi_%s.pdf" % getSaveNameFromDatasets(filenames))
def drawStackedBackground(plot, treeName, listOfFiles, sumBinned, order=False): tightCut = " photons[0].sigmaIetaIeta<0.011 && photons[0].chargedIso<0.7 && photons[0].neutralIso < 0.4+0.04*photons[0].pt && photons[0].photonIso < 0.5+0.005*photons[0].pt && photons[0].r9<0.9" cut = "[email protected]() && [email protected]()" #cut = cut +"&&" + tightCut cut = "std::abs(photons[0].eta)>1.4442" # if a data histogram is present, the mc integral will scaled to data mcHists = [] dataHists = [] for fileName in listOfFiles: datasetAbbr = getDatasetAbbr(fileName) try: color = colors[datasetAbbr] except: color = 1 tree = readTree(fileName, treeName) histo = getHisto(tree, plot, color=color, cut=cut) if "PhotonHad" in fileName: dataHists.append((datasetAbbr, histo)) else: mcHists.append((datasetAbbr, histo)) # merge datahists if there dataHist = addHistos([histo for datasetAbbr, histo in dataHists ]) if dataHists else None scale = 1. * dataHist.Integral() / addHistos( [histo for datasetAbbr, histo in mcHists]).Integral() if dataHists else 1 scale = 1. # combine MC datasets if sumBinned: for combiAbbr, abbrList in combinedDatasets.iteritems(): if set(abbrList).issubset(set([a for a, h in mcHists])): indices = [] for a, b in mcHists: if a in abbrList: indices.append(mcHists.index((a, b))) #print "a valid combination was found" histosToAdd = [h for a, h in mcHists if a in abbrList] thisSum = addHistos(histosToAdd) mcHists = [(a, h) for a, h in mcHists if a not in abbrList] mcHists.insert(min(indices), (combiAbbr, thisSum)) mh = Multihisto() mh.setMinimum(0.01) mh.leg.SetFillStyle(0) mh.leg.SetNColumns(2) mh.orderByIntegral = order if dataHist: mh.addHisto(dataHist, "Data", draw="ep") for abbr, hist in mcHists: hist.Scale(scale) mh.addHisto(hist, datasetToLatex(abbr), toStack=True, draw="hist") egammaHist = True if egammaHist: egammaHist = multiDimFakeRate( [filename for filename in listOfFiles if "PhotonHad" in filename], plot, cut) egammaHist.SetLineColor(ROOT.kGreen) mh.addHisto(egammaHist, "e#rightarrow#gamma", toStack=True) #totalBG = addHistos( [ h for abbr, h in mcHists ] ) #totalBG.SetLineColor(2) #mh.addHisto( totalBG, "SM Simulation", toStack=False, draw="hist" ) # add signal histos #signalFiles = ["slimW_1000_1020_375_V02.44_tree.root", "slimW_1200_1120_375_V02.44_tree.root"] signalFiles = ["slimW_1200_1120_375_V02.44_tree.root"] signalFiles = ["slimW_1700_720_375_V03.22_tree.root"] for iColor, sf in enumerate(signalFiles): tree = readTree(sf, treeName) histo = getHisto(tree, plot, color=ROOT.kBlue + iColor, cut=cut) #mh.addHisto( histo, datasetToLatex(getDatasetAbbr(sf)), draw="hist" ) mh.addHisto(histo, "Signal", draw="hist") infoText = ROOT.TLatex( 0, .97, "#text{CMS Private Work }#geq1#gamma_{#text{pixel}},#geq2#text{jets}") infoText.SetNDC() infoText.SetTextSize(0.05) can = ROOT.TCanvas() can.cd() mh.Draw() infoText.Draw() #if dataHist: # from myRatio import Ratio # den = totalBG #den = mh.stack.GetStack().Last().Clone( randomName() ) # den.SetLineColor(2) # r = Ratio( "Data/Sim.", dataHist, den ) # r.draw(0,2) allDatasetAbbr = getSaveNameFromDatasets(listOfFiles) SaveAs(can, "stackedHisto_%s_%s_%s" % (treeName, plot, allDatasetAbbr))
def finalDistributionData(plot): # Sample names treeVersion = "31" wg = [ "slimWGamma_50_130_V03.%s_tree.root"%treeVersion, \ "slimWGamma_130_inf_V03.%s_tree.root"%treeVersion ] tg = ["slimTTGamma_V03.%s_tree.root" % treeVersion] zgn = ["slimZGammaNuNu_V03.%s_tree.root" % treeVersion] zgll = ["slimZGammaLL_V02.19b_tree.root"] data = [ "PhotonHad%s_V03.%s_tree.root" % (x, treeVersion) for x in ["A", "B", "C", "D"] ] # additional ISR uncertainty ewkUncertainty = 0.11 isrUncertaintyZ = 0.5 isrUncertaintyW = 0.5 isrUncertaintyT = 0.5 isrUncertainty = 0.5 leptonPtCut = 25 # only larger than 15 make sense here, since this is the reprocessing cut #commonCut = "([email protected]() || Max$(electrons.pt)<{0}) && ([email protected]() || Max$(muons.pt)<{0})".format(leptonPtCut) commonCut = "[email protected]() && [email protected]() && thisPt>0 && recoilChr > 0" # Compute the weights: weight2D = getMixedWeigthHisto(data, data, commonCut) attachWeightsToFiles(data, weight2D, "foWeights") drawWeightHisto(weight2D, "Data", writeWeightFile=True) # Get Histograms dataHist = getHists(data, plot, commonCut) fgammaHist, fgammaWeightError = predictionHistos(data, plot, commonCut, modifyEmptyBins=False) egammaHist = multiDimFakeRate(data, plot, commonCut) egammaHistsys = setRelativeUncertainty(egammaHist.Clone(randomName()), ewkUncertainty) fsrZ = getHists(zgn, plot, commonCut + "&&genPhotons[0].pt>130") fsrZll = getHists(zgll, plot, commonCut) if plot == "met": fsrZ2 = getHists(zgll, plot + "LL", commonCut + "&&genPhotons[0].pt<130") else: fsrZ2 = getHists(zgll, plot, commonCut + "&&0") fsrZ2.Scale(20. / (2. * 3.363)) fsrW = getHists(wg, plot, commonCut) fsrT = getHists(tg, plot, commonCut) # apply common scale factor for h in fsrW, fsrT, fsrZ, fsrZ2, fsrZll: h.Scale(1.5) fsr = addHistos([fsrT, fsrW, fsrZ, fsrZ2, fsrZll]) fsr.SetLineColor(ROOT.kRed) fsrSys = setRelativeUncertainty(fsr, isrUncertainty) #signal1 = getMetHisto( "W", 900, 1720 ) #signal2 = getMetHisto( "B", 1700, 1120 ) signal1 = getHists(["slimW_1700_720_375_V03.06_tree.root"], plot, commonCut) signal2 = getHists(["slimW_900_1720_375_V03.06_tree.root"], plot, commonCut) signal3 = getHists(["slimB_1300_1720_375_V03.06_tree.root"], plot, commonCut) signal4 = getHists(["slimB_1700_1120_375_V03.06_tree.root"], plot, commonCut) for i, signal in enumerate([signal1, signal2, signal3, signal4]): signal.SetLineColor(ROOT.kGreen + i) signal.SetLineColor(ROOT.kBlue + i) #signal.SetLineStyle(5+i) # prettify histograms fgammaHist.SetLineColor(7) egammaHist.SetLineColor(3) fsrZ.SetLineColor(ROOT.kRed - 7) fsrW.SetLineColor(ROOT.kRed - 9) fsrT.SetLineColor(ROOT.kRed) mh = Multihisto() mh.setMinimum(0.2) mh.orderByIntegral = False mh.addHisto(fsr, "ISR", True) mh.addHisto(egammaHist, "e#rightarrow#gamma", True) mh.addHisto(fgammaHist, "Multijet", True) dataLegName = "Data" mh.addHisto(dataHist, dataLegName, draw="pe x0") mh.addHisto(signal2, "Bino-like #chi_{1}^{0}", draw="hist") mh.addHisto(signal1, "Wino-like #chi_{1}^{0}", draw="hist") # get all SYSTEMATICAL uncertainties: systematicUncertHistStack = ROOT.THStack() systematicUncertHistStack.Add(fgammaWeightError) systematicUncertHistStack.Add(egammaHistsys) systematicUncertHistStack.Add(fsrSys) if plot == "met": writeDataCard(treeVersion, dataHist, fgammaHist, fgammaWeightError, egammaHist, egammaHistsys, fsr, fsrSys) # draw stuff luminosity = 19.7 infoText = ROOT.TLatex( 0, .96, "CMS Private Work - %sfb^{-1} #sqrt{s}=8TeV #geq1#gamma_{tight},#geq2jets" % luminosity) infoText.SetNDC() infoText.SetTextSize(.04) can = ROOT.TCanvas() mh.Draw() statUncert = mh.stack.GetStack().Last().Clone(randomName()) systUncert = systematicUncertHistStack.GetStack().Last().Clone( randomName()) totalUncert = statUncert.Clone(randomName()) for bin in range(totalUncert.GetNbinsX() + 2): totalUncert.SetBinError( bin, statUncert.GetBinError(bin) | qPlus | systUncert.GetBinError(bin)) for h in statUncert, systUncert, totalUncert: h.SetMarkerSize(0) totalUncert.SetFillStyle(3002) totalUncert.SetFillColor(1) totalUncert.Draw("same e2") systUncert.SetFillStyle(3254) systUncert.SetFillColor(2) systUncert.Draw("same e2") statUncert.SetLineWidth(3) statUncert.SetLineColor(2) statUncert.Draw("same e x0") dataHist.Draw("same pe x0") from myRatio import Ratio r = Ratio("Data / Bkg", dataHist, mh.stack.GetStack().Last(), systematicUncertHistStack.GetStack().Last()) r.draw(.5, 1.5) infoText.Draw() SaveAs(can, "finalDistributionData_%s" % plot)
def compareTrees(plot="photons.pt", filenames=["slimAllQCD_V02.28_tree.root"], drawRatio=False): cut = "1" #cut = plot+">110" #cut = "!photons[0].isGen(0)" #cut = "ht < 600" gH = getHistoFromFiles(plot, "photonTree", filenames, cut) fH = getHistoFromFiles(plot, "photonJetTree", filenames, cut, color=2) weight2D = getMixedWeigthHisto(filenames, filenames, cut, control=True, fillEmptyBins=False) for filename in filenames: fTree = readTree(filename, "photonJetTree") writeWeight2DToFile(filename, fTree, weight2D, "foWeightsCompare") fgammaHist, fgammaWeightError = qcdPredictionHistos( filenames, plot, cut, True) for bin in range(fgammaHist.GetNbinsX() + 2): fgammaHist.SetBinError( bin, sqrt( fgammaHist.GetBinError(bin)**2 + fgammaWeightError.GetBinContent(bin)**2)) fH = fgammaHist for h in [gH, fH]: h.Scale(1. / h.Integral()) h.SetMarkerSize(0) h.GetXaxis().SetTitleOffset(1.03) h.GetYaxis().SetTitleOffset(1.5) h.GetXaxis().SetLabelSize(0.0633790992496425) h.GetXaxis().SetTitleSize(0.0633790992496425) h.GetYaxis().SetLabelSize(0.0633790992496425) h.GetYaxis().SetTitleSize(0.0633790992496425) h.GetYaxis().SetLabelOffset(0) if plot == "photons[0].pt": h.GetXaxis().SetTitle("$p_{T}$ [GeV]") if plot == "photons[0].ptJet()": h.GetXaxis().SetTitle("$p_{T^*}$ [GeV]") mh = Multihisto() mh.leg.SetX1(0.608) mh.leg.SetX2(0.95) mh.addHisto(gH, "#gamma_{#text{tight}}", draw="hist e") mh.addHisto(fH, "#gamma_{#text{loose}}", draw="hist e") can = ROOT.TCanvas() #can.SetBottomMargin(0) #can.SetTopMargin(0) #can.SetRightMargin(0) can.SetLeftMargin(0.19) can.cd() mh.Draw() pc1 = ROOT.TLatex(0, .96, "CMS Private Work") pc2 = ROOT.TLatex(.51, .96, "\SI{19.8}{fb^{-1}} #sqrt{s}=\SI{8}{TeV}") for pc in [pc1, pc2]: pc.SetNDC() pc.SetTextSize(0.06311227345609463) pc.Draw() if drawRatio: from myRatio import Ratio r = Ratio("#gamma/#gamma_{jet}", gH, fH) r.draw() #can.SetFillColor(ROOT.kGreen) SavePad("compare2_%s_%s" % (plot, shortName(filenames))) ROOT.gPad.SaveAs("~/master/documents/thesis/plots/compare_%s_%s.tex" % (manipulateSaveName(plot), shortName(filenames))) correctTiksPlot( "/home/knut/master/documents/thesis/plots/compare_%s_%s.tex" % (manipulateSaveName(plot), shortName(filenames))) ROOT.SetOwnership(can, False)
nestedBkgFiles = [bkg[a]["files"] for a in bkg.keys()] bkgFiles = [item for sublist in nestedBkgFiles for item in sublist] kFactor = getkFactor(dataFiles, bkgFiles, opts.plot, chi2Cut) #signal = getHists( ["slimW_1700_720_375_V03.24_tree.root" ], opts.plot, cut ) #signal.SetLineColor( ROOT.kGreen ) #signal.SetLineWidth(2) mh = Multihisto() mh.setMinimum(0) mh.addHisto(data, "Data", draw="pe") for name, d in bkg.iteritems(): histo = getHists(d["files"], opts.plot, cut) histo.SetLineColor(d["color"]) histo.Scale(kFactor) mh.addHisto(histo, d["title"], True) #mh.addHisto( signal, "Wino", False ) #combiBkg = getCombinatoricalBkg( dataFiles, opts.plot ) #combiBkg.SetLineWidth(2) #combiBkg.SetLineColor( ROOT.kBlue ) #combiBkg.Scale( data.Integral(0, data.FindBin(70), "width") / combiBkg.Integral(0,data.FindBin(70),"width")) #mh.addHisto( combiBkg, "bkg", draw="hist e" ) mh.Draw() ROOT.gPad.SaveAs("plots/isrkFactor_%s.pdf" % opts.plot)
S7scaledUsingS7.SetLineStyle(3) S7scaledUsingS10 = s7.Clone(randomName()) S7scaledUsingS10.Divide(s10) S7scaledUsingS10.Multiply(data) S7scaledUsingS10.SetLineStyle(8) mh = Multihisto() mh.setMaximum(0.07) mh.addHisto(data, "Data", draw="p") mh.addHisto(s10, "S10 Scenario", draw="hist") mh.addHisto(S10scaledUsingS10, "S10 scaled by data/S10", draw="hist") mh.addHisto(s7, "S7 Scenario", draw="hist") mh.addHisto(S7scaledUsingS7, "S7 scaled by data/S7", draw="hist") mh.addHisto(S7scaledUsingS10, "S7 scaled by data/S10", draw="hist") mh.Draw() mh.leg.SetX1(.65) mh.leg.SetY1(.7) mh.leg.SetX2(1) mh.leg.SetY2(1) ROOT.gPad.SetLogy(0) ROOT.gPad.SaveAs("plots/pileupScenarios.pdf") for name, h in [("data", data), ("s7", s7), ("s10", s10), ("s10scaleds10", S10scaledUsingS10), ("s7sceleds7", S7scaledUsingS7), ("s7sceleds10", S7scaledUsingS10)]: print name, h.GetBinContent(h.FindBin(20)) ##################### New plot ###################################
def drawStackedBackground( plot, treeName, listOfFiles, sumBinned, order=False ): cut = "[email protected]() && [email protected]()" # if a data histogram is present, the mc integral will scaled to data mcHists = [] dataHists = [] for fileName in listOfFiles: datasetAbbr = getDatasetAbbr( fileName ) try: color = colors[datasetAbbr] except: color = 1 tree = readTree( fileName, treeName ) histo = getHisto( tree, plot, color=color, cut=cut ) if "PhotonHad" in fileName: dataHists.append( (datasetAbbr, histo ) ) else: mcHists.append( ( datasetAbbr, histo ) ) # merge datahists if there dataHist = addHistos( [histo for datasetAbbr, histo in dataHists] ) if dataHists else None scale = 1.*dataHist.Integral()/addHistos( [histo for datasetAbbr, histo in mcHists] ).Integral() if dataHists else 1 scale = 1. # combine MC datasets if sumBinned: for combiAbbr, abbrList in combinedDatasets.iteritems(): if set(abbrList).issubset( set( [ a for a, h in mcHists ] ) ): #print "a valid combination was found" histosToAdd = [ h for a,h in mcHists if a in abbrList ] thisSum = addHistos( histosToAdd ) mcHists = [ (a,h) for a,h in mcHists if a not in abbrList]+[(combiAbbr,thisSum)] mh = Multihisto() mh.setMinimum(0.01) mh.leg.SetX1NDC(0.5) mh.leg.SetY1NDC(0.5) mh.orderByIntegral = order if dataHist: mh.addHisto( dataHist, "Data", draw="e0" ) for abbr, hist in mcHists: hist.Scale( scale ) mh.addHisto( hist, datasetToLatex(abbr), toStack=True, draw="hist" ) # add signal histos #signalFiles = ["slimW_1000_1020_375_V02.44_tree.root", "slimW_1200_1120_375_V02.44_tree.root"] signalFiles = ["slimW_1200_1120_375_V02.44_tree.root"] signalFiles = [] for iColor, sf in enumerate(signalFiles): tree = readTree( sf, treeName ) histo = getHisto( tree, plot, color=ROOT.kMagenta+iColor, cut=cut ) mh.addHisto( histo, datasetToLatex(getDatasetAbbr(sf)), draw="hist" ) can = ROOT.TCanvas() can.cd() mh.Draw() info = PlotCaption(treeName=treeName) info.Draw() if dataHist: from myRatio import Ratio den = mh.stack.GetStack().Last().Clone( randomName() ) den.SetLineColor(2) r = Ratio( "Data/Sim", dataHist, den ) r.draw(0,2) allDatasetAbbr = getSaveNameFromDatasets( listOfFiles ) SaveAs( can, "stackedHisto_%s_%s_%s"%(treeName, plot,allDatasetAbbr) )
def compareTrees(plot="met", filenames=["slimAllQCD_V02.28_tree.root"], drawRatio=False): #cut = "@electrons.size()==0 && @muons.size()==0" #cut = plot+">110" #cut = "!photons[0].isGen(0)" #cut = "ht < 600" cut = "1" gH = getHistoFromFiles(plot, "photonTree", filenames, "1") fH = getHistoFromFiles(plot, "photonJetTree", filenames, "1", color=2) for h in [gH, fH]: #h.Scale( 1./h.Integral() ) h.SetMarkerSize(0) h.GetXaxis().SetTitleOffset(1.03) h.GetYaxis().SetTitleOffset(1.5) h.GetXaxis().SetLabelSize(0.0633790992496425) h.GetXaxis().SetTitleSize(0.0633790992496425) h.GetYaxis().SetLabelSize(0.0633790992496425) h.GetYaxis().SetTitleSize(0.0633790992496425) h.GetYaxis().SetLabelOffset(0) if plot == "photons[0].pt": h.GetXaxis().SetTitle("$p_{T}$ [GeV]") if plot == "photons[0].ptJet()": h.GetXaxis().SetTitle("$p_{T^*}$ [GeV]") ratio = gH.Clone(randomName()) ratio.Divide(fH) mh = Multihisto() #mh.leg.SetX1(0.608) #mh.leg.SetX2(0.95) mh.addHisto(gH, "#gamma_{#text{tight}}", draw="hist e") mh.addHisto(fH, "#gamma_{#text{loose}}", draw="hist e") can = ROOT.TCanvas() #can.SetBottomMargin(0) #can.SetTopMargin(0) #can.SetRightMargin(0) #can.SetLeftMargin(0.19) can.cd() mh.Draw() pc1 = ROOT.TLatex(0, .96, "CMS Private Work") pc2 = ROOT.TLatex(.51, .96, "\SI{19.8}{fb^{-1}} #sqrt{s}=\SI{8}{TeV}") for pc in [pc1, pc2]: pc.SetNDC() pc.SetTextSize(0.06311227345609463) pc.Draw() if drawRatio: from myRatio import Ratio r = Ratio("#gamma/#gamma_{jet}", gH, fH) r.draw() #can.SetFillColor(ROOT.kGreen) SavePad("compare2_%s_%s" % ("test", shortName(filenames))) #ROOT.gPad.SaveAs("~/master/documents/thesis/plots/compare_%s_%s.tex"%(manipulateSaveName(plot),shortName( filenames )) ) ROOT.SetOwnership(can, False)