def fitBin(name, allProbeCondition, passingProbeCondition):
ROOT.gDirectory.mkdir(name).cd()
fitter = PassFailSimulFitter(name, fitVariable)
fitter.addDataFromTree(tmc,
'mcData',
allProbeCondition + mcTruthCondition,
passingProbeCondition,
separatePassFail=True)
fitter.addDataFromTree(tmcAlt,
'mcAltData',
allProbeCondition + mcTruthCondition,
passingProbeCondition,
separatePassFail=True)
nMCPass = fitter.workspace.data('mcDataPass').sumEntries()
nMCFail = fitter.workspace.data('mcDataFail').sumEntries()
mcEff = nMCPass / (nMCPass + nMCFail)
mcEffLo = ROOT.TEfficiency.ClopperPearson(int(nMCPass + nMCFail),
int(nMCPass), 0.68, False)
mcEffHi = ROOT.TEfficiency.ClopperPearson(int(nMCPass + nMCFail),
int(nMCPass), 0.68, True)
h = ROOT.TH1F('mc_cutCount', 'Cut & Count', 2, 0, 2)
h.SetBinContent(1, nMCPass)
h.SetBinContent(2, nMCPass + nMCFail)
# All MC templates must be set up by now
fitter.setPdf(pdfDefinition)
print '-' * 40, 'Central value fit'
fitter.addDataFromTree(tdata, 'data', allProbeCondition,
passingProbeCondition)
res = fitter.fit('simPdf', 'data')
effValue = res.floatParsFinal().find('efficiency')
dataEff = effValue.getVal()
dataEffErrHi = effValue.getErrorHi()
dataEffErrLo = effValue.getErrorLo()
scaleFactor = dataEff / mcEff
maxSf = (dataEff + dataEffErrHi) / mcEffLo
minSf = (dataEff + dataEffErrLo) / mcEffHi
res.SetName('fitresults')
c = fitter.drawFitCanvas(res)
c.Write()
h.Write()
res.Write()
print '-' * 40, 'Fit with alternate MC template'
resAlt = fitter.fit('simAltPdf', 'data')
dataAltEff = resAlt.floatParsFinal().find('efficiency').getVal()
resAlt.SetName('fitresults_systAltTemplate')
resAlt.Write()
print '-' * 40, 'Fit with tag pt > 30 (vs. 25)'
fitter.addDataFromTree(tdata, 'dataTagPt30',
allProbeCondition + ['tag_tag_pt>30'],
passingProbeCondition)
resTagPt30 = fitter.fit('simPdf', 'dataTagPt30')
dataTagPt30Eff = resTagPt30.floatParsFinal().find(
'efficiency').getVal()
resTagPt30.Write()
print '-' * 40, 'Fit with CMSShape background (vs. Bernstein)'
resCMSBkg = fitter.fit('simCMSBkgPdf', 'data')
dataCMSBkgEff = resCMSBkg.floatParsFinal().find('efficiency').getVal()
resCMSBkg.Write()
fitter.workspace.Write()
print name, ': Data=%.2f, MC=%.2f, Ratio=%.2f' % (dataEff, mcEff,
dataEff / mcEff)
condition = ' && '.join(allProbeCondition + [passingProbeCondition])
variations = {
'CENTRAL': (scaleFactor, res),
'STAT_UP': (maxSf, res),
'STAT_DOWN': (minSf, res),
'SYST_ALT_TEMPL': (dataAltEff / mcEff, resAlt),
'SYST_TAG_PT30': (dataTagPt30Eff / mcEff, resTagPt30),
'SYST_CMSSHAPE': (dataCMSBkgEff / mcEff, resCMSBkg),
'EFF_DATA': (dataEff, res),
'EFF_DATA_ERRSYM': ((dataEffErrHi - dataEffErrLo) / 2, res),
'EFF_MC': (mcEff, res),
'EFF_MC_ERRSYM': ((mcEffHi - mcEffLo) / 2, res),
}
cutString = ''
for varName, value in variations.items():
(value, fitResult) = value
cutString += ' if ( variation == Variation::%s && (%s) ) return %f;\n' % (
varName, condition, value)
print ' Variation {:>15s} : {:.4f}, edm={:f}, status={:s}'.format(
varName, value, fitResult.edm(), statusInfo(fitResult))
if 'STAT' not in varName and fitResult.statusCodeHistory(0) < 0:
cBad = fitter.drawFitCanvas(fitResult)
cBad.Print('badFit_%s_%s.png' % (name, varName))
ROOT.TNamed('cutString', cutString).Write()
print
ROOT.gDirectory.cd('..')
