canvas.lumi = sum(sample.lumi for sample in allsamples.getmany(snames))
for tname, (_, _, title, variables) in confs[oname].items():
if len(omname) > 2 and tname != omname[2]:
continue
print ' ', tname
trigDir = source.GetDirectory(tname)
for vname, (vtitle, _, _, binning) in variables.items():
print ' ', vname
eff = trigDir.Get(vname + '_eff')
canvas.Clear()
canvas.SetGrid()
canvas.legend.Clear()
if title:
canvas.legend.add('eff',
title=title,
opt='LP',
color=ROOT.kBlack,
mstyle=8)
canvas.legend.apply('eff', eff)
else:
eff.SetMarkerColor(ROOT.kBlack)
eff.SetMarkerStyle(8)
canvas.addHistogram(eff, drawOpt='EP', clone=False)
if name == 'ht':
monophHt = monophDist
# znng efficiency
monophEff = eff.Clone('monoph_' + eff.GetName())
effCanvas.legend.apply('monoph', monophEff)
mcMonoph.Draw(
'electrons.size == 0 && muons.size == 0:' + expr + '>>' +
monophEff.GetName(), weight, 'prof goff')
# print plots
distCanvas.addHistogram(dataDist, drawOpt='HIST')
distCanvas.addHistogram(mumugDist, drawOpt='HIST')
distCanvas.addHistogram(monophDist, drawOpt='HIST')
distCanvas.printWeb('veto_eff', 'dist_' + name)
distCanvas.Clear()
effCanvas.addHistogram(dataEff, drawOpt='EP')
effCanvas.addHistogram(mumugEff, drawOpt='EP')
if name == 'incl':
effCanvas.addHistogram(datajetEff, drawOpt='EP')
effCanvas.addHistogram(mumugjetEff, drawOpt='EP')
effCanvas.addHistogram(monophEff, drawOpt='EP')
effCanvas.addHistogram(sf, drawOpt='P')
effCanvas.printWeb('veto_eff', 'eff_' + name, logy=False)
effCanvas.Clear()
effCanvas.SetGrid(True)
# save histograms
outputFile.cd()
for iX in range(hnominal.GetNbinsX() + 2):
if ROOT.TMath.IsNaN(hnominal.GetBinContent(iX)) or ROOT.TMath.IsNaN(hnominal.GetBinError(iX)):
print hnominal.GetName(), 'cannot be plotted because it contains NaN'
plot = False
break
if huncert and (ROOT.TMath.IsNaN(huncert.GetBinContent(iX)) or ROOT.TMath.IsNaN(huncert.GetBinError(iX))):
print huncert.GetName(), 'cannot be plotted because it contains NaN'
plot = False
break
if not plot:
continue
canvas1.legend.apply('stat', hnominal)
if huncert:
canvas1.Clear()
canvas1.legend.apply('total', huncert)
canvas1.addHistogram(huncert, drawOpt = 'E2')
canvas1.addHistogram(hnominal, drawOpt = 'EP')
canvas1.printWeb(plotDir, hnominal.GetName(), logy = not proc.startswith('tf_'))
else:
canvas2.Clear()
canvas2.addHistogram(hnominal, drawOpt = 'EP')
canvas2.printWeb(plotDir, hnominal.GetName(), logy = not proc.startswith('tf_'))
rcanvas = RatioCanvas(name = 'datamc', lumi = 36400)
rcanvas.legend.setPosition(0.7, 0.7, 0.9, 0.9)
logy=False)
for iBin, (bin, _) in enumerate(fitBins):
if dataType == 'mc':
print '%15s [%.3f +- %.3f (stat.) +- %.3f (syst.)] x 10^{-2} (mc %.3f)' % (
bin, result.GetBinContent(iBin + 1) * 100., staterrs[iBin] * 100.,
systerrs[iBin] * 100., trueResult.GetBinContent(iBin + 1) * 100.)
else:
print '%15s [%.3f +- %.3f (stat.) +- %.3f (syst.)] x 10^{-2}' % (
bin, result.GetBinContent(iBin + 1) * 100., staterrs[iBin] * 100.,
systerrs[iBin] * 100.)
if uncSource:
for conf in meas:
for bin, _ in fitBins:
canvas.Clear(full=True)
canvas.ylimits = (0., 0.1)
canvas.xtitle = '(N_{Z}^{toy}-N_{Z}^{orig})/N_{Z}^{orig}'
canvas.legend.setPosition(0.7, 0.7, 0.9, 0.9)
canvas.legend.add('toys',
title='Toys',
opt='LF',
color=ROOT.kBlue - 7,
lwidth=2,
fstyle=3003)
for ip in range(nomparams.numEntries()):
nompset = nomparams.get(ip)
if nompset.find('tpconf').getLabel() == conf and nompset.find(
'binName').getLabel() == bin:
dataHist.GetXaxis().SetTitle('#Delta#phi(#gamma, E_{T}^{miss})')
dataHist.GetYaxis().SetTitle(
'(E_{55}^{#gamma} - E_{T}^{#gamma}) / E_{T}^{miss}')
dataHist.Sumw2()
dataTree.Draw(
yString + ":" + xString + ">>" + sample,
'(photons.pt[0] > 175. && t1Met.minJetDPhi > 0.5 && t1Met.met > 170.)',
'goff')
ColorGrad()
canvas.addHistogram(dataHist, drawOpt='COLZ TEXT')
canvas.printWeb('monophoton/phoMet',
'DiffVsPhi' + '_' + sample,
logy=False)
canvas.Clear(xmax=0.90)
dataTree = ROOT.TChain('events')
dataTree.Add('/scratch5/ballen/hist/monophoton/skim/sph-d*_monoph.root')
xString = "photons.eta[0]"
yString = "photons.phi[0]"
dataHist = ROOT.TH2D("lego", "", 30, -1.5, 1.5, 30, -math.pi, math.pi)
dataHist.GetXaxis().SetTitle('#eta')
dataHist.GetYaxis().SetTitle('#phi')
dataHist.Sumw2()
dataTree.Draw(
yString + ":" + xString + ">>lego",
'photons.pt[0] > 175. && t1Met.minJetDPhi > 0.5 && t1Met.met > 170. && t1Met.photonDPhi < 2.',
'goff')