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 closure(filenames, plot):
commonCut = "[email protected]() && [email protected]()"
#if plot != "met": commonCut += " && met>=100"
gHist = getHists(filenames,
plot,
cut="(photons[0].isStatus(1)) && " + commonCut)
eHist = multiDimFakeRate(filenames, plot, commonCut, isData=False)
gHist.SetName("gHist")
eHist.SetName("eHist")
eHistSys = eHist.Clone("eHistSys")
eHistSys = setRelativeUncertainty(eHistSys, 0.11)
eHistSys.SetFillColor(eHistSys.GetLineColor())
eHistSys.SetFillStyle(3354)
eHistSys.SetMarkerSize(0)
eHistSys.SetName("eHistSys")
gDatasetAbbrs = [getDatasetAbbr(f) for f in filenames]
gDatasetAbbrs = mergeDatasetAbbr(gDatasetAbbrs)
multihisto = Multihisto()
multihisto.leg = myLegend(.63, .75, .96, .94)
multihisto.leg.SetTextSize(0.035)
multihisto.leg.SetTextFont(42)
multihisto.leg.SetHeader(",".join(
[datasetToLatex(x) for x in gDatasetAbbrs]))
multihisto.addHisto(gHist, "Direct Simulation", draw="p e x0")
multihisto.addHisto(eHist, "", draw="hist")
multihisto.addHisto(eHistSys, "Prediction", draw="e2")
infoText = ROOT.TLatex()
infoText.SetNDC()
infoText.SetTextFont(gHist.GetLabelFont())
infoText.SetTextSize(gHist.GetLabelSize())
infoText.SetText(
.02, .96,
"CMS Simulation 19.7fb^{-1} (8 TeV) #geq1#gamma,#geq2jets"
)
can = ROOT.TCanvas("c1", "", 600, 600)
can.cd()
multihisto.Draw()
infoText.Draw()
r = Ratio("Direct/Pred.", gHist, eHist, eHistSys)
r.draw(0, 2)
SaveAs(can,
"ewkClosure_%s_%s" % (getSaveNameFromDatasets(filenames), plot))
ROOT.gPad.SaveAs("plots/ewkClosure_%s_%s.C" %
(getSaveNameFromDatasets(filenames), plot))
ewkOut = ROOT.TFile("ewkOout.root", "recreate")
ewkOut.cd()
for h in gHist, eHist, eHistSys:
h.Write()
ewkOut.Close()
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 closure(filenames, plot):
commonCut = "[email protected]() && [email protected]()"
# if plot != "met": commonCut += " && met>=100"
gHist = getHists(filenames, plot, cut="(photons[0].isStatus(1)) && " + commonCut)
eHist = multiDimFakeRate(filenames, plot, commonCut, isData=False)
gHist.SetName("gHist")
eHist.SetName("eHist")
eHistSys = eHist.Clone("eHistSys")
eHistSys = setRelativeUncertainty(eHistSys, 0.11)
eHistSys.SetFillColor(eHistSys.GetLineColor())
eHistSys.SetFillStyle(3354)
eHistSys.SetMarkerSize(0)
eHistSys.SetName("eHistSys")
gDatasetAbbrs = [getDatasetAbbr(f) for f in filenames]
gDatasetAbbrs = mergeDatasetAbbr(gDatasetAbbrs)
multihisto = Multihisto()
multihisto.leg = myLegend(0.63, 0.75, 0.96, 0.94)
multihisto.leg.SetTextSize(0.035)
multihisto.leg.SetTextFont(42)
multihisto.leg.SetHeader(",".join([datasetToLatex(x) for x in gDatasetAbbrs]))
multihisto.addHisto(gHist, "Direct Simulation", draw="p e x0")
multihisto.addHisto(eHist, "", draw="hist")
multihisto.addHisto(eHistSys, "Prediction", draw="e2")
infoText = ROOT.TLatex()
infoText.SetNDC()
infoText.SetTextFont(gHist.GetLabelFont())
infoText.SetTextSize(gHist.GetLabelSize())
infoText.SetText(
0.02, 0.96, "CMS Simulation 19.7fb^{-1} (8 TeV) #geq1#gamma,#geq2jets"
)
can = ROOT.TCanvas("c1", "", 600, 600)
can.cd()
multihisto.Draw()
infoText.Draw()
r = Ratio("Direct/Pred.", gHist, eHist, eHistSys)
r.draw(0, 2)
SaveAs(can, "ewkClosure_%s_%s" % (getSaveNameFromDatasets(filenames), plot))
ROOT.gPad.SaveAs("plots/ewkClosure_%s_%s.C" % (getSaveNameFromDatasets(filenames), plot))
ewkOut = ROOT.TFile("ewkOout.root", "recreate")
ewkOut.cd()
for h in gHist, eHist, eHistSys:
h.Write()
ewkOut.Close()
ROOT.SetOwnership(can, False)
del can
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 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 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 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 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 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 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 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 compareTrees( plot="met", filenames=["slimAllQCD_V02.28_tree.root"], drawRatio=False ):
cut = "1"
fcut = cut
fcut += "&& photons[0].chargedIso/10<2.6 && photons[0].neutralIso/10<3.5+0.04*photons[0].pt && photonIso/10<1.3+0.005*photons[0].pt"
fcut += "&& photons[0].chargedIso*10>2.6 && photons[0].neutralIso*10>3.5+0.04*photons[0].pt && photonIso*10>1.3+0.005*photons[0].pt"
gH = getHistoFromFiles( plot, "photonTree", filenames, cut )
fH = getHistoFromFiles( plot, "photonJetTree", filenames, fcut, color=1 )
#fH = getHistoFromFiles( plot, "photonTree", filenames, cut+"&& fabs(photons[0].eta)>=%s"%etaCut )
ratio = gH.Clone( randomName() )
ratio.Divide( fH )
ratio.SetYTitle( "#gamma_{tight}/#gamma_{loose}" )
can = ROOT.TCanvas()
can.SetLogy(0)
can.cd()
ratio.Draw(" e")
pc1 = ROOT.TLatex(0,.96, "CMS Private Work")
pc2 = ROOT.TLatex( .42,.96, "\SI{19.8}{fb^{-1}} #sqrt{s}=\SI{8}{TeV}#, #geq1#ggamma(#geq1#fgamma),#geq2#text{jets}")
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( "ratioCompare2_%s_%s"%(plot,shortName( filenames )) )
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 compareTrees(plot="met",
filenames=["slimAllQCD_V02.28_tree.root"],
drawRatio=False):
cut = "1"
fcut = cut
fcut += "&& photons[0].chargedIso/10<2.6 && photons[0].neutralIso/10<3.5+0.04*photons[0].pt && photonIso/10<1.3+0.005*photons[0].pt"
fcut += "&& photons[0].chargedIso*10>2.6 && photons[0].neutralIso*10>3.5+0.04*photons[0].pt && photonIso*10>1.3+0.005*photons[0].pt"
gH = getHistoFromFiles(plot, "photonTree", filenames, cut)
fH = getHistoFromFiles(plot, "photonJetTree", filenames, fcut, color=1)
#fH = getHistoFromFiles( plot, "photonTree", filenames, cut+"&& fabs(photons[0].eta)>=%s"%etaCut )
ratio = gH.Clone(randomName())
ratio.Divide(fH)
ratio.SetYTitle("#gamma_{tight}/#gamma_{loose}")
can = ROOT.TCanvas()
can.SetLogy(0)
can.cd()
ratio.Draw(" e")
pc1 = ROOT.TLatex(0, .96, "CMS Private Work")
pc2 = ROOT.TLatex(
.42, .96,
"\SI{19.8}{fb^{-1}} #sqrt{s}=\SI{8}{TeV}#, #geq1#ggamma(#geq1#fgamma),#geq2#text{jets}"
)
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("ratioCompare2_%s_%s" % (plot, shortName(filenames)))
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 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 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)
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 finalDistributionMC(plot):
# Sample names
treeVersion = 12
g1 = "slimGJets_200_400_V03.%s_tree.root" % treeVersion
g2 = "slimGJets_400_inf_V03.%s_tree.root" % treeVersion
q1 = "slimQCD_250_500_V03.%s_tree.root" % treeVersion
q2 = "slimQCD_500_1000_V03.%s_tree.root" % treeVersion
q3 = "slimQCD_1000_inf_V03.%s_tree.root" % treeVersion
tt = "slimTTJets_V03.%s_tree.root" % treeVersion
w1 = "slimWJets_250_300_V03.%s_tree.root" % treeVersion
w2 = "slimWJets_300_400_V03.%s_tree.root" % treeVersion
w3 = "slimWJets_400_inf_V03.%s_tree.root" % treeVersion
wg1 = "slimWGamma_50_130_V03.%s_tree.root" % treeVersion
wg2 = "slimWGamma_130_inf_V03.%s_tree.root" % treeVersion
tg = "slimTTGamma_V03.%s_tree.root" % treeVersion
zgn = "slimZGammaNuNu_V03.%s_tree.root" % treeVersion
data = [g1, g2, q1, q2, q3, tt, w1, w2, w3, zgn, wg1, wg2, tg]
# 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]()"
# Compute the weights:
#weight2D = getMixedWeigthHisto( data, data, commonCut )
#attachWeightsToFiles( data, weight2D, "foWeights" )
#from qcdClosure import drawWeightHisto
#drawWeightHisto( weight2D, "MC" )
# Get Histograms
dataHist = getHists(data, plot, commonCut)
fgammaHist, fgammaWeightError = predictionHistos(data,
plot,
commonCut,
modifyEmptyBins=False)
egammaHist = multiDimFakeRate(data, plot, commonCut, isData=False)
egammaHistsys = setRelativeUncertainty(egammaHist.Clone(randomName()),
ewkUncertainty)
fsrZ = getHists([zgn], plot, commonCut)
fsrZsys = setRelativeUncertainty(fsrZ, isrUncertaintyZ)
fsrW = getHists([wg1, wg2], plot, commonCut)
fsrWsys = setRelativeUncertainty(fsrW, isrUncertaintyW)
fsrT = getHists([tg], plot, commonCut)
fsrTsys = setRelativeUncertainty(fsrT, isrUncertaintyT)
fsr = addHistos([fsrT, fsrW, fsrZ])
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.orderByIntegral = False
mh.addHisto(fsrT, "#gamma t#bar{t}", True)
mh.addHisto(fsrW, "#gamma W", True)
mh.addHisto(fsrZ, "#gamma Z", True)
mh.addHisto(egammaHist, "e#rightarrow#gamma", True)
mh.addHisto(fgammaHist, "Multijet", True)
dataLegName = "Data"
mh.addHisto(dataHist, dataLegName, draw="pe")
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( fsrTsys )
#systematicUncertHistStack.Add( fsrWsys )
#systematicUncertHistStack.Add( fsrZsys )
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()
errorBand = mh.stack.GetStack().Last().Clone(randomName())
sysUncert = systematicUncertHistStack.GetStack().Last()
for bin in range(errorBand.GetNbinsX() + 2):
errorBand.SetBinError(
bin,
errorBand.GetBinError(bin) | qPlus | sysUncert.GetBinError(bin))
errorBand.SetFillStyle(3002)
errorBand.SetMarkerSize(0)
errorBand.SetFillColor(1)
errorBand.Draw("e2 same")
from myRatio import Ratio
r = Ratio("Data / Bkg", dataHist,
mh.stack.GetStack().Last(),
systematicUncertHistStack.GetStack().Last())
r.draw(0.5, 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)
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 )
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 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 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 finalDistributionMC( plot ): # Sample names treeVersion = 12 g1 = "slimGJets_200_400_V03.%s_tree.root"%treeVersion g2 = "slimGJets_400_inf_V03.%s_tree.root"%treeVersion q1 = "slimQCD_250_500_V03.%s_tree.root"%treeVersion q2 = "slimQCD_500_1000_V03.%s_tree.root"%treeVersion q3 = "slimQCD_1000_inf_V03.%s_tree.root"%treeVersion tt = "slimTTJets_V03.%s_tree.root"%treeVersion w1 = "slimWJets_250_300_V03.%s_tree.root"%treeVersion w2 = "slimWJets_300_400_V03.%s_tree.root"%treeVersion w3 = "slimWJets_400_inf_V03.%s_tree.root"%treeVersion wg1 = "slimWGamma_50_130_V03.%s_tree.root"%treeVersion wg2 = "slimWGamma_130_inf_V03.%s_tree.root"%treeVersion tg = "slimTTGamma_V03.%s_tree.root"%treeVersion zgn = "slimZGammaNuNu_V03.%s_tree.root"%treeVersion data = [ g1, g2, q1, q2, q3, tt, w1, w2, w3, zgn, wg1,wg2,tg ] # 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]()" # Compute the weights: #weight2D = getMixedWeigthHisto( data, data, commonCut ) #attachWeightsToFiles( data, weight2D, "foWeights" ) #from qcdClosure import drawWeightHisto #drawWeightHisto( weight2D, "MC" ) # Get Histograms dataHist = getHists( data, plot, commonCut ) fgammaHist, fgammaWeightError = predictionHistos( data, plot, commonCut, modifyEmptyBins=False ) egammaHist = multiDimFakeRate( data, plot, commonCut, isData=False ) egammaHistsys = setRelativeUncertainty( egammaHist.Clone(randomName()), ewkUncertainty ) fsrZ = getHists( [zgn], plot, commonCut ) fsrZsys = setRelativeUncertainty( fsrZ, isrUncertaintyZ ) fsrW = getHists( [wg1,wg2], plot, commonCut ) fsrWsys = setRelativeUncertainty( fsrW, isrUncertaintyW ) fsrT = getHists( [tg], plot, commonCut ) fsrTsys = setRelativeUncertainty( fsrT, isrUncertaintyT ) fsr = addHistos( [fsrT, fsrW, fsrZ ] ) 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.orderByIntegral = False mh.addHisto( fsrT, "#gamma t#bar{t}", True ) mh.addHisto( fsrW, "#gamma W", True ) mh.addHisto( fsrZ, "#gamma Z", True ) mh.addHisto( egammaHist, "e#rightarrow#gamma", True ) mh.addHisto( fgammaHist, "Multijet", True ) dataLegName = "Data" mh.addHisto( dataHist, dataLegName, draw="pe" ) 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( fsrTsys ) #systematicUncertHistStack.Add( fsrWsys ) #systematicUncertHistStack.Add( fsrZsys ) 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() errorBand = mh.stack.GetStack().Last().Clone( randomName() ) sysUncert = systematicUncertHistStack.GetStack().Last() for bin in range(errorBand.GetNbinsX()+2): errorBand.SetBinError( bin, errorBand.GetBinError(bin) |qPlus| sysUncert.GetBinError(bin) ) errorBand.SetFillStyle(3002) errorBand.SetMarkerSize(0) errorBand.SetFillColor(1) errorBand.Draw("e2 same") from myRatio import Ratio r = Ratio( "Data / Bkg", dataHist, mh.stack.GetStack().Last(), systematicUncertHistStack.GetStack().Last() ) r.draw(0.5,1.5) infoText.Draw() SaveAs( can, "finalDistributionData_%s"%plot )
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 )