sigVal = sigScoreHist.GetBinContent(iBin)
bkgVal = bkgScoreHist.GetBinContent(iBin)
sigScoreHist.SetBinContent(iBin, 1.)
if sigVal > 0.:
bkgScoreHist.SetBinContent(iBin, bkgVal / sigVal)
else:
bkgScoreHist.SetBinContent(iBin, 0)
sigScoreHist.Scale(1. / sigScoreHist.Integral())
bkgScoreHist.Scale(1. / bkgScoreHist.Integral())
sigScoreHist.SetLineColor(r.kBlue)
sigScoreHist.Draw('hist')
bkgScoreHist.SetLineColor(r.kRed)
bkgScoreHist.Draw('hist,same')
useSty.drawCMS()
useSty.drawEnPu(lumi='35.9 fb^{-1}')
theCanv.SaveAs('%s/outputScores.pdf' % plotDir)
#draw sig vs background distribution
theCanv = useSty.setCanvas()
sigScoreW = diphoTestFW * (diphoTestY == 1)
sigScoreHist = r.TH1F('sigScoreHist', 'sigScoreHist', nOutputBins, 0., 1.)
useSty.formatHisto(sigScoreHist)
sigScoreHist.SetTitle('')
sigScoreHist.GetXaxis().SetTitle('Diphoton BDT score')
fill_hist(sigScoreHist, altDiphoPredY, weights=sigScoreW)
bkgScoreW = diphoTestFW * (diphoTestY == 0)
bkgScoreHist = r.TH1F('bkgScoreHist', 'bkgScoreHist', nOutputBins, 0., 1.)
useSty.formatHisto(bkgScoreHist)
bkgScoreHist.SetTitle('')
bkgScoreHist.GetXaxis().SetTitle('Diphoton BDT score')
for iBin, iPar in enumerate(pars.values()):
for jBin, jPar in enumerate(pars.values()):
proc = theMatrix.GetXaxis().GetBinLabel(iPar + 1)
#print 'Got proc %s, expecting proc %s'%(proc, revPars[iPar])
theVal = theMatrix.GetBinContent(iPar + 1, jPar + 1)
#print 'Value for correlation between %s and %s is %.3f'%(revPars[iPar],revPars[jPar],theVal)
theHist.GetXaxis().SetBinLabel(iBin + 1, prettyProc(revPars[iPar]))
theHist.GetYaxis().SetBinLabel(jBin + 1, prettyProc(revPars[jPar]))
theHist.Fill(iBin, jBin, theVal)
set_color_palette('frenchFlag')
r.gStyle.SetNumberContours(500)
r.gStyle.SetPaintTextFormat('1.2f')
#canv = r.TCanvas('canv','canv')
canv = setCanvas()
formatHisto(theHist)
theHist.GetXaxis().SetTickLength(0.)
theHist.GetXaxis().SetLabelSize(0.05)
theHist.GetYaxis().SetTickLength(0.)
theHist.GetYaxis().SetLabelSize(0.05)
theHist.GetZaxis().SetRangeUser(-1., 1.)
theHist.GetZaxis().SetTickLength(0.)
theHist.Draw('colz,text')
drawCMS(True)
drawEnPu(lumi='%2.1f fb^{-1}' % lumi)
canv.Print('Plots/corrMatrixFormal_%s.png' % ext)
canv.Print('Plots/corrMatrixFormal_%s.pdf' % ext)
else: wrongHist.Fill(true,w)
firstBinVal = -1.
for iBin in range(1,truthHist.GetNbinsX()+1):
if iBin==1: firstBinVal = truthHist.GetBinContent(iBin)
ratio = float(truthHist.GetBinContent(iBin)) / firstBinVal
print 'ratio for bin %g is %1.7f'%(iBin,ratio)
wrongHist.Add(rightHist)
rightHist.Divide(wrongHist)
effHist = r.TH1F
r.gStyle.SetOptStat(0)
truthHist.GetYaxis().SetRangeUser(0.,8.)
truthHist.Draw('hist')
useSty.drawCMS()
useSty.drawEnPu(lumi='35.9 fb^{-1}')
canv.Print('truthJetHist.pdf')
predHist.GetYaxis().SetRangeUser(0.,8.)
predHist.Draw('hist')
useSty.drawCMS()
useSty.drawEnPu(lumi='35.9 fb^{-1}')
canv.Print('recoPredJetHist.pdf')
rightHist.GetYaxis().SetRangeUser(0.,1.)
rightHist.Draw('hist')
useSty.drawCMS()
useSty.drawEnPu(lumi='35.9 fb^{-1}')
canv.Print('recoEfficiencyJetHist.pdf')
#setup 2D hists
canv = useSty.setCanvas()
truthHist = r.TH1F('truthHist','truthHist',nClasses,-0.5,nClasses-0.5)
else: wrongHist.Fill(true, w)
firstBinVal = -1.
for iBin in range(1, truthHist.GetNbinsX() + 1):
if iBin == 1: firstBinVal = truthHist.GetBinContent(iBin)
ratio = float(truthHist.GetBinContent(iBin)) / firstBinVal
print 'ratio for bin %g is %1.7f' % (iBin, ratio)
wrongHist.Add(rightHist)
rightHist.Divide(wrongHist)
effHist = r.TH1F
r.gStyle.SetOptStat(0)
truthHist.GetYaxis().SetRangeUser(0., 8.)
truthHist.Draw('hist')
useSty.drawCMS()
useSty.drawEnPu(lumi='%.1f fb^{-1}' % opts.intLumi)
canv.Print('%s/truthJetHist%s.pdf' % (plotDir, paramExt))
canv.Print('%s/truthJetHist%s.png' % (plotDir, paramExt))
predHist.GetYaxis().SetRangeUser(0., 8.)
predHist.Draw('hist')
useSty.drawCMS()
useSty.drawEnPu(lumi='%.1f fb^{-1}' % opts.intLumi)
canv.Print('%s/recoPredJetHist%s.pdf' % (plotDir, paramExt))
canv.Print('%s/recoPredJetHist%s.png' % (plotDir, paramExt))
rightHist.GetYaxis().SetRangeUser(0., 1.)
rightHist.Draw('hist')
useSty.drawCMS()
useSty.drawEnPu(lumi='%.1f fb^{-1}' % opts.intLumi)
canv.Print('%s/recoEfficiencyJetHist%s.pdf' % (plotDir, paramExt))
canv.Print('%s/recoEfficiencyJetHist%s.png' % (plotDir, paramExt))
def crossCheck(self, lumi, plotDir):
'''Run a check to ensure the random search found a good mimimum'''
for iName, name in enumerate(self.names):
for iCat in range(self.nCats):
best = self.boundaries[name][iCat]
rnge = 0.2 * self.highs[name] - self.lows[name]
graph = r.TGraph()
for iVal, val in enumerate(
np.arange(best - rnge / 2., best + rnge / 2.,
rnge / 10.)):
sigs = []
bkgs = []
nons = []
cuts = {}
cuts[name] = self.boundaries[name]
cuts[name][iCat] = val
bests = Bests(self.nCats)
for jCat in range(self.nCats):
lastCat = (jCat + 1 == self.nCats)
sigWeights = self.sigWeights
bkgWeights = self.bkgWeights
if self.addNonSig: nonSigWeights = self.nonSigWeights
for jName, jname in enumerate(self.names):
sigWeights = sigWeights * (self.sigDiscrims[jname]
> cuts[jname][jCat])
bkgWeights = bkgWeights * (self.bkgDiscrims[jname]
> cuts[jname][jCat])
if self.addNonSig:
nonSigWeights = nonSigWeights * (
self.nonSigDiscrims[jname] >
cuts[jname][jCat])
if not lastCat:
if jName == 0 or self.sortOthers:
sigWeights = sigWeights * (
self.sigDiscrims[jname] <
cuts[jname][jCat + 1])
bkgWeights = bkgWeights * (
self.bkgDiscrims[jname] <
cuts[jname][jCat + 1])
if self.addNonSig:
nonSigWeights = nonSigWeights * (
self.nonSigDiscrims[jname] <
cuts[jname][jCat + 1])
sigHist = r.TH1F('sigHistTemp', 'sigHistTemp', 160,
100, 180)
fill_hist(sigHist, self.sigMass, weights=sigWeights)
sigCount = 0.68 * lumi * sigHist.Integral()
sigWidth = self.getRealSigma(sigHist)
bkgHist = r.TH1F('bkgHistTemp', 'bkgHistTemp', 160,
100, 180)
fill_hist(bkgHist, self.bkgMass, weights=bkgWeights)
bkgCount = self.computeBkg(bkgHist, sigWidth)
if self.addNonSig:
nonSigHist = r.TH1F('nonSigHistTemp',
'nonSigHistTemp', 160, 100,
180)
fill_hist(nonSigHist,
self.nonSigMass,
weights=nonSigWeights)
nonSigCount = 0.68 * lumi * nonSigHist.Integral()
else:
nonSigCount = 0.
sigs.append(sigCount)
bkgs.append(bkgCount)
nons.append(nonSigCount)
bests.update(sigs, bkgs, nons)
graph.SetPoint(iVal, val - best, bests.getTotSignif())
canv = useSty.setCanvas()
graphName = 'CrossCheck_%s_Cat%g' % (name, iCat)
graph.SetTitle(graphName.replace('_', ' '))
graph.GetXaxis().SetTitle('Cut value - chosen value')
graph.GetYaxis().SetTitle('Significance (#sigma)')
graph.Draw()
useSty.drawCMS(text='Internal')
useSty.drawEnPu(lumi=lumi)
canv.Print('%s/%s.pdf' % (plotDir, graphName))
canv.Print('%s/%s.png' % (plotDir, graphName))