def plotStackedHistos(histos={},
datakey=None,
stackkeys=[],
outputDir='',
region='',
colors={},
verbose=False):
"input: a dictionary of histos[group]"
mkdirIfNeeded(outputDir)
bkg_histos = dict([(k, h) for k, h in histos.iteritems()
if k in stackkeys])
tot_bkg = summedHisto(bkg_histos.values(), label='')
err_band = None # tmp disable
# err_band = buildErrBandGraph(tot_bkg, computeStatErr2(tot_bkg))
empty_bkg = tot_bkg.Integral() == 0
if empty_bkg:
if verbose: print "empty backgrounds, skip %s" % tot_bkg.GetName()
return
histoname = tot_bkg.GetName()
can = r.TCanvas('c_' + histoname, histoname, 800, 600)
can.cd()
pm = tot_bkg # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_' + tot_bkg.GetName(), '')
can.Update()
r.SetOwnership(stack, False)
for s, h in bkg_histos.iteritems():
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
# err_band.Draw('E2 same')
data = histos[datakey] if datakey and datakey in histos else None
if data and data.GetEntries():
data.SetMarkerStyle(r.kFullDotLarge)
data.Draw('p same')
if verbose:
print "data : nEntries {:.1f} totWeight {:.1f} ".format(
data.GetEntries(), data.Integral())
yMin, yMax = getMinMax([h for h in [tot_bkg, data, err_band] if h])
# pm.SetMinimum(0.5)
pm.SetMaximum(1.1 * yMax)
can.Update()
# can.SetLogy()
topRightLabel(can,
"#splitline{%s}{%s}" % (histoname, region),
xpos=0.125,
align=13)
drawLegendWithDictKeys(can,
dictSum(bkg_histos, {'stat err': err_band}),
opt='f')
can.RedrawAxis()
can._stack = stack
can._histos = [h for h in stack.GetHists()] + [data]
can.Update()
if verbose: print os.path.join(outputDir, histoname + '.png')
can.SaveAs(os.path.join(outputDir, histoname + '.png'))
def drawBottom(pad, totBkg, bkgHistos, sigHisto, llnjvar) :
pad.cd()
totBkg.SetStats(False)
totBkg.SetMinimum(0.) # force this to avoid negative fluct due to fake
totBkg.Draw('axis')
pad.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_'+llnjvar,'')
pad.Update()
r.SetOwnership(stack, False)
for s, h in bkgHistos.iteritems() :
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
pad.Update()
sigHisto.SetLineColor(r.kRed)
sigHisto.SetLineWidth(2*sigHisto.GetLineWidth())
sigHisto.Draw('same')
pad.Update()
topRightLabel(pad, llnjvar, xpos=0.125, align=13)
drawLegendWithDictKeys(pad, dictSum(bkgHistos, {'signal' : sigHisto}), opt='f')
pad.RedrawAxis()
pad._stack = stack
pad._histos = [h for h in stack.GetHists()]
pad.Update()
def plot1dEfficiencies(effs={}, canvasName='', outputDir='./', frameTitle='title;p_{T} [GeV]; efficiency', zoomIn=False) :
can = r.TCanvas(canvasName, '', 800, 600)
can.cd()
padMaster = None
colors, markers = SampleUtils.colors, SampleUtils.markers
for s,h in effs.iteritems() :
h.SetLineColor(colors[s] if s in colors else r.kBlack)
h.SetMarkerColor(h.GetLineColor())
h.SetMarkerStyle(markers[s] if s in markers else r.kFullCircle)
drawOpt = 'ep same' if padMaster else 'ep'
h.Draw(drawOpt)
if not padMaster : padMaster = h
minY, maxY = getMinMax(effs.values()) if zoomIn else (0.0, 1.0)
padMaster.GetYaxis().SetRangeUser(min([0.0, minY]), 1.1*maxY)
padMaster.SetMinimum(0.0)
padMaster.SetMaximum(1.1*maxY)
padMaster.SetMaximum(0.25 if (maxY < 0.25 and zoomIn) else 1.1)
padMaster.SetTitle(frameTitle)
padMaster.SetStats(False)
drawLegendWithDictKeys(can, effs)
can.Update()
for ext in ['png','eps'] :
outFilename = outputDir+'/'+canvasName+'.'+ext
rmIfExists(outFilename)
can.SaveAs(outFilename)
def plotPerSourceEff(histosPerVar={}, outputDir='', lepton='', region='', sample='', verbose=False, zoomIn=True):
"plot efficiency for each source (and 'anysource') as a function of each var; expect histos[var][source][loose,tight]"
variables = histosPerVar.keys()
sources = [s for s in first(histosPerVar).keys() if s!='real'] # only fake eff really need a scale factor
colors = colorsLineSources
mkdirIfNeeded(outputDir)
for var in filter(lambda x : x in ['pt1', 'eta1'], histosPerVar.keys()):
histosPerSource = dict((s, histosPerVar[var][s]) for s in sources)
canvasBasename = region+'_efficiency_'+lepton+'_'+var+("_%s"%sample if sample else '')
missingSources = [s for s, h in histosPerSource.iteritems() if not h['loose'] or not h['tight']]
if missingSources:
if verbose : print "skip %s, missing histos for %s"%(var, str(missingSources))
continue
anySourceLoose = summedHisto([h['loose'] for h in histosPerSource.values()])
anySourceTight = summedHisto([h['tight'] for h in histosPerSource.values()])
anySourceLoose.SetName(histoNamePerSource(var, 'any', 'loose', region))
anySourceTight.SetName(histoNamePerSource(var, 'any', 'tight', region))
histosPerSource['any'] = { 'loose' : anySourceLoose, 'tight' : anySourceTight }
emptyBkg = anySourceLoose.Integral()==0 or anySourceTight.Integral()==0
if emptyBkg:
if verbose : print "empty backgrounds, skip %s"%canvasBasename
continue
def computeEfficiencies(histosPerSource={}) :
sources = histosPerSource.keys()
num = dict((s, histosPerSource[s]['tight']) for s in sources)
den = dict((s, histosPerSource[s]['loose']) for s in sources)
eff = dict((s, h.Clone(h.GetName().replace('tight', 'tight_over_loose')))
for s, h in num.iteritems())
[eff[s].Divide(den[s]) for s in sources]
return eff
effs = computeEfficiencies(histosPerSource)
can = r.TCanvas('c_'+canvasBasename, canvasBasename, 800, 600)
can.cd()
pm = first(effs) # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update()
for s, h in effs.iteritems() :
h.SetMarkerColor(colors[s] if s in colors else r.kBlack)
h.SetLineColor(h.GetMarkerColor())
h.SetLineWidth(2*h.GetLineWidth())
h.SetMarkerStyle(markersSources[s] if s in markersSources else r.kDot)
h.Draw('ep same')
h.SetDirectory(0)
#pprint.pprint(effs)
yMin, yMax = getMinMax(effs.values())
pm.SetMinimum(0.0)
pm.SetMaximum(0.25 if yMax < 0.5 and zoomIn else 1.1)
can.Update()
topRightLabel(can, canvasBasename, xpos=0.125, align=13)
drawLegendWithDictKeys(can, effs, opt='lp')
can.RedrawAxis()
can._histos = effs
can.Update()
outFname = os.path.join(outputDir, canvasBasename+'.png')
utils.rmIfExists(outFname)
can.SaveAs(outFname)
def plotHistRatioAndFit(histos, ratio, fitfunc, outfname, graphics_attributes={}) :
can = r.TCanvas('can_'+outfname, outfname, 800, 600)
botPad, topPad = buildBotTopPads(can, splitFraction=0.35)
can.cd()
topPad.Draw()
topPad.cd()
pm = first(histos)
pm.Draw('axis')
xAx, yAx = pm.GetXaxis(), pm.GetYaxis()
xAx.SetTitle('')
xAx.SetLabelSize(0)
yAx.SetRangeUser(0.0, 1.2)
yAx.SetNdivisions(505) # for some reason some of the inputs are already ratios with -201
textScaleUp = 1.0/topPad.GetHNDC()
yAx.SetLabelSize(textScaleUp*0.04)
yAx.SetTitleSize(textScaleUp*0.04)
yAx.SetTitle(graphics_attributes['ytitle'])
yAx.SetTitleOffset(yAx.GetTitleOffset()/textScaleUp)
for k, h in histos.iteritems() :
h.SetMarkerStyle(graphics_attributes['markers'][k])
h.SetMarkerColor(graphics_attributes['colors'][k])
h.SetLineColor(graphics_attributes['colors'][k])
h.Draw('same')
labels = graphics_attributes['labels']
drawLegendWithDictKeys(topPad, dict([(labels[s], histos[s]) for s in histos.keys()]), legWidth=0.4)
can.cd()
botPad.Draw()
botPad.cd()
ratio.Draw('axis')
textScaleUp = 1.0/botPad.GetHNDC()
xAx, yAx = ratio.GetXaxis(), ratio.GetYaxis()
yAx.SetRangeUser(0.0, 2.0)
xAx.SetTitle(graphics_attributes['xtitle'])
yAx.SetNdivisions(-202)
yAx.SetTitle('Data/Sim')
yAx.CenterTitle()
for a in [xAx, yAx] :
if a.GetLabelSize()>0.04 : continue
a.SetLabelSize(a.GetLabelSize()*textScaleUp)
a.SetTitleSize(a.GetTitleSize()*textScaleUp)
a.SetTitleOffset(a.GetTitleOffset()/textScaleUp)
ratio.SetMarkerStyle(graphics_attributes['markers']['data'])
fitfunc.SetLineWidth(2)
fitfunc.SetLineStyle(2)
fitfunc.Draw('same')
ratio.Draw('same')
tex = r.TLatex()
tex.SetNDC(True)
p0, p0Err, chi2, ndf = fitResults(fitfunc)
fitParLabel = "Const. fit : %s #pm %s"%(pdgRound(p0, p0Err))
fitGoodLabel = "#chi^{2}/DOF : %.2f / %d"%(chi2, ndf)
tex.SetTextSize(yAx.GetTitleSize())
tex.SetTextFont(yAx.GetTitleFont())
tex.DrawLatex(0.15, 0.40, "#splitline{%s}{%s}"%(fitParLabel, fitGoodLabel))
can.Update()
outfname = outfname+'.png'
rmIfExists(outfname) # avoid root warnings
can.SaveAs(outfname)
def plotStackedHistos(histosPerGroup={}, outputDir='', region='', verbose=False):
groups = histosPerGroup.keys()
variables = first(histosPerGroup).keys()
leptonTypes = first(first(histosPerGroup)).keys()
colors = getGroupColor()
mkdirIfNeeded(outputDir)
histosPerName = dict([(region+'_'+var+'_'+lt, # one canvas for each histo, so key with histoname w/out group
dict([(g, histosPerGroup[g][var][lt]) for g in groups]))
for var in variables for lt in leptonTypes])
for histoname, histosPerGroup in histosPerName.iteritems():
missingGroups = [g for g, h in histosPerGroup.iteritems() if not h]
if missingGroups:
if verbose : print "skip %s, missing histos for %s"%(histoname, str(missingGroups))
continue
bkgHistos = dict([(g, h) for g, h in histosPerGroup.iteritems() if g not in ['data', 'signal']])
totBkg = summedHisto(bkgHistos.values())
err_band = None # buildErrBandGraph(totBkg, computeStatErr2(totBkg))
emptyBkg = totBkg.Integral()==0
if emptyBkg:
if verbose : print "empty backgrounds, skip %s"%histoname
continue
can = r.TCanvas('c_'+histoname, histoname, 800, 600)
can.cd()
pm = totBkg # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_'+histoname,'')
can.Update()
r.SetOwnership(stack, False)
for s, h in bkgHistos.iteritems() :
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
# err_band.Draw('E2 same')
data = histosPerGroup['data']
if data and data.GetEntries():
data.SetMarkerStyle(r.kFullDotLarge)
data.Draw('p same')
# yMin, yMax = getMinMax([h for h in [totBkg, data, err_band] if h]) # fixme with err_band
yMin, yMax = 0.0, data.GetMaximum()
pm.SetMinimum(0.0)
pm.SetMaximum(1.1*yMax)
can.Update()
topRightLabel(can, histoname, xpos=0.125, align=13)
# drawLegendWithDictKeys(can, dictSum(bkgHistos, {'stat err':err_band}), opt='f')
drawLegendWithDictKeys(can, bkgHistos, opt='f')
can.RedrawAxis()
can._stack = stack
can._histos = [h for h in stack.GetHists()]+[data]
can.Update()
outFname = os.path.join(outputDir, histoname+'.png')
utils.rmIfExists(outFname)
can.SaveAs(outFname)
def plotStackedHistosSources(histosPerVar={},
outputDir='',
region='',
verbose=False):
variables = histosPerVar.keys()
sources = first(histosPerVar).keys()
colors = colorsFillSources
mkdirIfNeeded(outputDir)
for var in variables:
for lOrT in ['loose', 'tight']:
histos = dict((s, histosPerVar[var][s][lOrT]) for s in sources)
canvasBasename = region + '_region_' + var + '_' + lOrT
missingSources = [s for s, h in histos.iteritems() if not h]
if missingSources:
if verbose:
print "skip %s, missing histos for %s" % (
var, str(missingSources))
continue
totBkg = summedHisto(histos.values())
err_band = None # buildErrBandGraph(totBkg, computeStatErr2(totBkg))
emptyBkg = totBkg.Integral() == 0
if emptyBkg:
if verbose: print "empty backgrounds, skip %s" % canvasBasename
continue
can = r.TCanvas('c_' + canvasBasename, canvasBasename, 800, 600)
can.cd()
pm = totBkg # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_' + canvasBasename, '')
can.Update()
r.SetOwnership(stack, False)
for s, h in histos.iteritems():
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
# err_band.Draw('E2 same')
yMin, yMax = getMinMax(
[h for h in [totBkg, err_band] if h is not None])
pm.SetMinimum(0.0)
pm.SetMaximum(1.1 * yMax)
can.Update()
topRightLabel(can, canvasBasename, xpos=0.125, align=13)
# drawLegendWithDictKeys(can, dictSum(histos, {'stat err':err_band}), opt='f')
drawLegendWithDictKeys(can, histos, opt='f')
can.RedrawAxis()
can._stack = stack
can._histos = [h for h in stack.GetHists()]
can.Update()
outFname = os.path.join(outputDir, canvasBasename + '.png')
utils.rmIfExists(outFname)
can.SaveAs(outFname)
def plotStackedHistosWithData(histosPerGroup={}, outputDir='', canvasname='', canvastitle='', colors={}, verbose=False):
"histosPerGroup[group], where group=data is treated as special"
groups = histosPerGroup.keys()
mkdirIfNeeded(outputDir)
missingGroups = [g for g, h in histosPerGroup.iteritems() if not h]
if missingGroups:
if verbose : print "skip %s, missing histos for %s"%(histoname, str(missingGroups))
return
bkgHistos = dict([(g, h) for g, h in histosPerGroup.iteritems() if not isDataSample(g)])
totBkg = summedHisto(bkgHistos.values())
err_band = buildErrBandGraph(totBkg, computeStatErr2(totBkg))
emptyBkg = totBkg.Integral()==0
histoname, region = totBkg.GetName(), 'emu' # tmp replacement vars, to be fixed
if emptyBkg:
if verbose : print "empty backgrounds, skip %s"%histoname
return
can = r.TCanvas(canvasname, canvastitle, 800, 600)
can.cd()
pm = totBkg # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_'+histoname,'')
can.Update()
r.SetOwnership(stack, False)
for s, h in bkgHistos.iteritems() :
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
err_band.Draw('E2 same')
data = histosPerGroup['data'] if 'data' in histosPerGroup else None
if data and data.GetEntries():
data.SetMarkerStyle(r.kFullDotLarge)
data.Draw('p same')
if verbose :
print "integrals : {0} tot.bkg.: {1}, data: {2}".format(histoname, totBkg.Integral(), data.Integral())
else:
print "no data"
yMin, yMax = getMinMax([h for h in [totBkg, data, err_band] if h])
pm.SetMinimum(0.0)
pm.SetMaximum(1.1*yMax)
can.Update()
topRightLabel(can, "#splitline{%s}{%s}"%(histoname, region), xpos=0.15, ypos=(1.0-0.5*can.GetTopMargin()), align=13)
drawLegendWithDictKeys(can, dictSum(bkgHistos, {'stat err':err_band}), opt='f')
can.RedrawAxis()
can._stack = stack
can._histos = [h for h in stack.GetHists()]+[data]
can.Update()
filename=os.path.join(outputDir, histoname+'.png')
rmIfExists(filename)
can.SaveAs(filename)
def plotStackedHistosSources(histosPerVar={}, outputDir='', region='', verbose=False):
variables = histosPerVar.keys()
sources = first(histosPerVar).keys()
colors = colorsFillSources
mkdirIfNeeded(outputDir)
for var in variables:
for lOrT in ['loose', 'tight']:
histos = dict((s, histosPerVar[var][s][lOrT]) for s in sources)
canvasBasename = region+'_region_'+var+'_'+lOrT
missingSources = [s for s, h in histos.iteritems() if not h]
if missingSources:
if verbose : print "skip %s, missing histos for %s"%(var, str(missingSources))
continue
totBkg = summedHisto(histos.values())
err_band = None # buildErrBandGraph(totBkg, computeStatErr2(totBkg))
emptyBkg = totBkg.Integral()==0
if emptyBkg:
if verbose : print "empty backgrounds, skip %s"%canvasBasename
continue
can = r.TCanvas('c_'+canvasBasename, canvasBasename, 800, 600)
can.cd()
pm = totBkg # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_'+canvasBasename,'')
can.Update()
r.SetOwnership(stack, False)
for s, h in histos.iteritems() :
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
# err_band.Draw('E2 same')
yMin, yMax = getMinMax([h for h in [totBkg, err_band] if h is not None])
pm.SetMinimum(0.0)
pm.SetMaximum(1.1*yMax)
can.Update()
topRightLabel(can, canvasBasename, xpos=0.125, align=13)
# drawLegendWithDictKeys(can, dictSum(histos, {'stat err':err_band}), opt='f')
drawLegendWithDictKeys(can, histos, opt='f')
can.RedrawAxis()
can._stack = stack
can._histos = [h for h in stack.GetHists()]
can.Update()
outFname = os.path.join(outputDir, canvasBasename+'.png')
utils.rmIfExists(outFname)
can.SaveAs(outFname)
def plotComparison(histo1, histo2, canvas, outname, label1, label2, verbose):
h1, h2 = histo1, histo2
if not h1.Integral() and not h2.Integral(): return
canvas.cd()
canvas.Clear()
h1.SetMarkerColor(r.kBlack)
h2.SetMarkerColor(r.kRed)
h1.SetMarkerStyle(r.kFullCircle)
h2.SetMarkerStyle(r.kOpenCircle)
h1.SetMaximum(1.1 * max([h.GetMaximum() for h in [h1, h2]]))
h1.SetStats(0)
h1.SetStats(0)
h1.Draw()
h2.Draw('same')
ks = h1.KolmogorovTest(h2) if h2.Integral() and h1.Integral() else 0.0
leg = drawLegendWithDictKeys(canvas, {
label1: h1,
label2: h2,
},
legWidth=0.35,
legHeight=0.275)
header = "%s : KS=%.3f" % (h1.GetName(), ks)
leg.SetHeader(header)
if ks < 0.05: print header
canvas.Update()
canvas.SaveAs(outname + '.png')
if verbose: print "saving %s" % outname
def plotComparison(histo1, histo2, canvas, outname, label1, label2, verbose) :
h1, h2 = histo1, histo2
if not h1.Integral() and not h2.Integral() : return
canvas.cd()
canvas.Clear()
h1.SetMarkerColor(r.kBlack)
h2.SetMarkerColor(r.kRed)
h1.SetMarkerStyle(r.kFullCircle)
h2.SetMarkerStyle(r.kOpenCircle)
# h1.SetMaximum(1.1*max([h.GetMaximum() for h in [h1, h2]]))
# h1.SetMinimum(0.5*max([h.GetMinimum() for h in [h1, h2]]))
h1.SetMaximum(1.1)
h1.SetMinimum(0.0)
h1.SetStats(0)
h1.SetStats(0)
h1.Draw()
h2.Draw('same')
ks = h1.KolmogorovTest(h2) if h2.Integral() and h1.Integral() else 0.0
leg = drawLegendWithDictKeys(canvas, {label1 : h1, label2 : h2, },
legWidth=0.35, legHeight=0.275)
header = "%s : KS=%.3f"%(h1.GetName(), ks)
leg.SetHeader(header)
if ks<0.05 : print header
canvas.Update()
canvas.SaveAs(outname+'.png')
if verbose : print "saving %s"%outname
def plotStackedHistos(histos={}, datakey=None, stackkeys=[], outputDir='', region='', colors={}, verbose=False):
"input: a dictionary of histos[group]"
mkdirIfNeeded(outputDir)
bkg_histos = dict([(k,h) for k,h in histos.iteritems() if k in stackkeys])
tot_bkg = summedHisto(bkg_histos.values(), label='')
err_band = None # tmp disable
# err_band = buildErrBandGraph(tot_bkg, computeStatErr2(tot_bkg))
empty_bkg = tot_bkg.Integral()==0
if empty_bkg:
if verbose : print "empty backgrounds, skip %s"%tot_bkg.GetName()
return
histoname = tot_bkg.GetName()
can = r.TCanvas('c_'+histoname, histoname, 800, 600)
can.cd()
pm = tot_bkg # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_'+tot_bkg.GetName(),'')
can.Update()
r.SetOwnership(stack, False)
for s, h in bkg_histos.iteritems() :
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
# err_band.Draw('E2 same')
data = histos[datakey] if datakey and datakey in histos else None
if data and data.GetEntries():
data.SetMarkerStyle(r.kFullDotLarge)
data.Draw('p same')
if verbose:
print "data : nEntries {:.1f} totWeight {:.1f} ".format(data.GetEntries(), data.Integral())
yMin, yMax = getMinMax([h for h in [tot_bkg, data, err_band] if h])
# pm.SetMinimum(0.5)
pm.SetMaximum(1.1*yMax)
can.Update()
# can.SetLogy()
topRightLabel(can, "#splitline{%s}{%s}"%(histoname, region), xpos=0.125, align=13)
drawLegendWithDictKeys(can, dictSum(bkg_histos, {'stat err':err_band}), opt='f')
can.RedrawAxis()
can._stack = stack
can._histos = [h for h in stack.GetHists()]+[data]
can.Update()
if verbose : print os.path.join(outputDir, histoname+'.png')
can.SaveAs(os.path.join(outputDir, histoname+'.png'))
def plotHistos(histos1=[], histos2=[], histosRatio=[], label1='label1', label2='label2',
canvas=None, canPrefix='', scaleXlabelsBot=1.0,
colors={}, markers={},lineStyle1=1, lineStyle2=2, splitFraction=0.80) :
"Assume again that the histos are in dict[sample]"
can = canvas if canvas is not None else r.TCanvas(canPrefix+'percent_histos','')
can.Clear()
can.cd()
padTop, padBot = getPad(can, splitFraction, top=True), getPad(can, splitFraction, bot=True)
# top pad with ratios
can.cd()
padTop.Draw()
padTop.cd()
markersr = dict(zip(colors.keys(), len(colors.keys())*[r.kOpenDiamond]))
for h in histosRatio.values() :
yAx = h.GetYaxis()
yAx.SetRangeUser(0.0, 2.0)
yAx.SetNdivisions(-202)
yAx.SetLabelSize(1.0/(1.0-splitFraction)*yAx.GetLabelSize())
h.SetTitle('')
h.SetStats(0)
#print 'fh: ',firstHisto(histos1).GetName(),' nratios :',len(histosRatio) # debug
def bc(h) : return ["%.2f"%h.GetBinContent(b) for b in xrange(1, h.GetNbinsX()+1)]
# print '\n'.join(["%s : %s"%(s, bc(h)) for s,h in histosRatio.iteritems()]) # debug
draw(padTop, histosRatio, colors, markersr, asFirst=True)
drawUnitLine(padTop, histosRatio)
labelR = "%s/%s ratio"%(label1[0], label2[0])
drawLegendWithDictKeys(padTop, {label1 : firstHisto(histos1),
label2 : firstHisto(histos2),
labelR : firstHisto(histosRatio)
},
legWidth=0.225, legHeight=0.75)
# bot pad with histos
can.cd()
padBot.Draw()
padBot.cd()
markers1 = dict(zip(colors.keys(), len(colors.keys())*[r.kOpenTriangleUp]))
markers2 = dict(zip(colors.keys(), len(colors.keys())*[r.kOpenTriangleDown]))
for h in histos1.values()+histos2.values() :
h.GetYaxis().SetRangeUser(0.0, 1.08)
h.GetXaxis().SetLabelSize(scaleXlabelsBot*h.GetXaxis().GetLabelSize())
h.SetStats(0)
draw(padBot, histos1, colors, markers1, lineStyle1)
draw(padBot, histos2, colors, markers2, lineStyle2, asFirst=False)
drawLegendWithDictKeys(padBot, histos1, legWidth=0.225)
padBot.Update()
return can
def plotHistos(histos1=[], histos2=[], histosRatio=[], label1='label1', label2='label2',
canvas=None, canPrefix='', scaleXlabelsBot=1.0,
colors={}, markers={},lineStyle1=1, lineStyle2=2, splitFraction=0.80) :
"Assume again that the histos are in dict[sample]"
can = canvas if canvas is not None else r.TCanvas(canPrefix+'percent_histos','')
can.Clear()
can.cd()
padTop, padBot = getPad(can, splitFraction, top=True), getPad(can, splitFraction, bot=True)
# top pad with ratios
can.cd()
padTop.Draw()
padTop.cd()
markersr = dict(zip(colors.keys(), len(colors.keys())*[r.kOpenDiamond]))
for h in histosRatio.values() :
yAx = h.GetYaxis()
yAx.SetRangeUser(0.0, 2.0)
yAx.SetNdivisions(-202)
yAx.SetLabelSize(1.0/(1.0-splitFraction)*yAx.GetLabelSize())
h.SetTitle('')
h.SetStats(0)
#print 'fh: ',firstHisto(histos1).GetName(),' nratios :',len(histosRatio) # debug
def bc(h) : return ["%.2f"%h.GetBinContent(b) for b in xrange(1, h.GetNbinsX()+1)]
# print '\n'.join(["%s : %s"%(s, bc(h)) for s,h in histosRatio.iteritems()]) # debug
draw(padTop, histosRatio, colors, markersr, asFirst=True)
drawUnitLine(padTop, histosRatio)
labelR = "%s/%s ratio"%(label1[0], label2[0])
drawLegendWithDictKeys(padTop, {label1 : firstHisto(histos1),
label2 : firstHisto(histos2),
labelR : firstHisto(histosRatio)
},
legWidth=0.225, legHeight=0.75)
# bot pad with histos
can.cd()
padBot.Draw()
padBot.cd()
markers1 = dict(zip(colors.keys(), len(colors.keys())*[r.kOpenTriangleUp]))
markers2 = dict(zip(colors.keys(), len(colors.keys())*[r.kOpenTriangleDown]))
for h in histos1.values()+histos2.values() :
h.GetYaxis().SetRangeUser(0.0, 1.08)
h.GetXaxis().SetLabelSize(scaleXlabelsBot*h.GetXaxis().GetLabelSize())
h.SetStats(0)
draw(padBot, histos1, colors, markers1, lineStyle1)
draw(padBot, histos2, colors, markers2, lineStyle2, asFirst=False)
drawLegendWithDictKeys(padBot, histos1, legWidth=0.225)
padBot.Update()
return can
def plot(histos, var) :
c = r.TCanvas('c_'+var,'')
c.cd()
pm = first(histos)
pm.SetMaximum(1.1*max([h.GetMaximum() for h in histos.values()]))
pm.Draw('axis')
markers = dict(zip(histos.keys(),
[r.kPlus, r.kCircle, r.kMultiply, r.kOpenSquare, r.kOpenTriangleUp, r.kOpenTriangleDown]))
for s,h in histos.iteritems() :
h.SetLineColor(colors[s] if s in colors else r.kBlack)
h.SetMarkerColor(h.GetLineColor())
h.SetLineWidth(2*h.GetLineWidth())
h.SetMarkerStyle(markers[s])
h.Draw('same')
leg = drawLegendWithDictKeys(c, histos)
leg.Draw()
c.Update()
c.SaveAs(var+'.png')
def plot(histos, var):
c = r.TCanvas('c_' + var, '')
c.cd()
pm = first(histos)
pm.SetMaximum(1.1 * max([h.GetMaximum() for h in histos.values()]))
pm.Draw('axis')
markers = dict(
zip(histos.keys(), [
r.kPlus, r.kCircle, r.kMultiply, r.kOpenSquare, r.kOpenTriangleUp,
r.kOpenTriangleDown
]))
for s, h in histos.iteritems():
h.SetLineColor(colors[s] if s in colors else r.kBlack)
h.SetMarkerColor(h.GetLineColor())
h.SetLineWidth(2 * h.GetLineWidth())
h.SetMarkerStyle(markers[s])
h.Draw('same')
leg = drawLegendWithDictKeys(c, histos)
leg.Draw()
c.Update()
c.SaveAs(var + '.png')
def plotHistRatioAndFit(histos,
ratio,
fitfunc,
outfname,
graphics_attributes={}):
can = r.TCanvas('can_' + outfname, outfname, 800, 600)
botPad, topPad = buildBotTopPads(can, splitFraction=0.35)
can.cd()
topPad.Draw()
topPad.cd()
pm = first(histos)
pm.Draw('axis')
xAx, yAx = pm.GetXaxis(), pm.GetYaxis()
xAx.SetTitle('')
xAx.SetLabelSize(0)
yAx.SetRangeUser(0.0, 1.2)
yAx.SetNdivisions(
505) # for some reason some of the inputs are already ratios with -201
textScaleUp = 1.0 / topPad.GetHNDC()
yAx.SetLabelSize(textScaleUp * 0.04)
yAx.SetTitleSize(textScaleUp * 0.04)
yAx.SetTitle(graphics_attributes['ytitle'])
yAx.SetTitleOffset(yAx.GetTitleOffset() / textScaleUp)
for k, h in histos.iteritems():
h.SetMarkerStyle(graphics_attributes['markers'][k])
h.SetMarkerColor(graphics_attributes['colors'][k])
h.SetLineColor(graphics_attributes['colors'][k])
h.Draw('same')
labels = graphics_attributes['labels']
drawLegendWithDictKeys(topPad,
dict([(labels[s], histos[s])
for s in histos.keys()]),
legWidth=0.4)
can.cd()
botPad.Draw()
botPad.cd()
ratio.Draw('axis')
textScaleUp = 1.0 / botPad.GetHNDC()
xAx, yAx = ratio.GetXaxis(), ratio.GetYaxis()
yAx.SetRangeUser(0.0, 2.0)
xAx.SetTitle(graphics_attributes['xtitle'])
yAx.SetNdivisions(-202)
yAx.SetTitle('Data/Sim')
yAx.CenterTitle()
for a in [xAx, yAx]:
if a.GetLabelSize() > 0.04: continue
a.SetLabelSize(a.GetLabelSize() * textScaleUp)
a.SetTitleSize(a.GetTitleSize() * textScaleUp)
a.SetTitleOffset(a.GetTitleOffset() / textScaleUp)
ratio.SetMarkerStyle(graphics_attributes['markers']['data'])
fitfunc.SetLineWidth(2)
fitfunc.SetLineStyle(2)
fitfunc.Draw('same')
ratio.Draw('same')
tex = r.TLatex()
tex.SetNDC(True)
p0, p0Err, chi2, ndf = fitResults(fitfunc)
fitParLabel = "Const. fit : %s #pm %s" % (pdgRound(p0, p0Err))
fitGoodLabel = "#chi^{2}/DOF : %.2f / %d" % (chi2, ndf)
tex.SetTextSize(yAx.GetTitleSize())
tex.SetTextFont(yAx.GetTitleFont())
tex.DrawLatex(0.15, 0.40,
"#splitline{%s}{%s}" % (fitParLabel, fitGoodLabel))
can.Update()
outfname = outfname + '.png'
rmIfExists(outfname) # avoid root warnings
can.SaveAs(outfname)
def subtractRealAndComputeScaleFactor(histosPerGroup={}, variable='', outRatiohistoname='',outDataeffhistoname='',
outputDir='./', region='', subtractReal=True, verbose=False):
"efficiency scale factor"
groups = histosPerGroup.keys()
mkdirIfNeeded(outputDir)
histosPerType = dict([(lt,
dict([(g,
histosPerGroup[g][variable][lt])
for g in groups]))
for lt in leptonTypes])
for lt in leptonTypes :
histosPerType[lt]['totSimBkg'] = summedHisto([histo for group,histo in histosPerType[lt].iteritems()
if group not in ['data', 'signal']])
simuTight = histosPerType['fake_tight']['totSimBkg']
simuLoose = histosPerType['fake_loose']['totSimBkg']
dataTight = histosPerType['tight' ]['data' ]
dataLoose = histosPerType['loose' ]['data' ]
# subtract real contribution from data
# _Note to self_: currently estimating the real contr from MC; in
# the past also used iterative corr, which might be more
# appropriate in cases like here, where the normalization is
# so-so. Todo: investigate the normalization.
dataSubTight = dataTight.Clone(dataTight.GetName().replace('data_tight','data_minus_prompt_tight'))
dataSubLoose = dataLoose.Clone(dataLoose.GetName().replace('data_loose','data_minus_prompt_loose'))
dataSubTight.SetDirectory(0)
dataSubLoose.SetDirectory(0)
dataSubTight.Add(histosPerType['real_tight']['totSimBkg'], -1.0 if subtractReal else 0.0)
dataSubLoose.Add(histosPerType['real_loose']['totSimBkg'], -1.0 if subtractReal else 0.0)
effData = dataSubTight.Clone(outDataeffhistoname)
effData.SetDirectory(0)
effData.Divide(dataSubLoose)
effSimu = simuTight.Clone(simuTight.GetName().replace('fake_tight','fake_eff'))
effSimu.SetDirectory(0)
effSimu.Divide(simuLoose)
print "eff(T|L) vs. ",variable
def formatFloat(floats): return ["%.4f"%f for f in floats]
print "efficiency data : ",formatFloat(getBinContents(effData))
print "efficiency simu : ",formatFloat(getBinContents(effSimu))
ratio = effData.Clone(outRatiohistoname)
ratio.SetDirectory(0)
ratio.Divide(effSimu)
print "sf data/simu : ",formatFloat(getBinContents(ratio))
print " +/- : ",formatFloat(getBinErrors(ratio))
can = r.TCanvas('c_'+outRatiohistoname, outRatiohistoname, 800, 600)
botPad, topPad = rootUtils.buildBotTopPads(can)
can.cd()
topPad.Draw()
topPad.cd()
pm = effData
pm.SetStats(0)
pm.Draw('axis')
xAx, yAx = pm.GetXaxis(), pm.GetYaxis()
xAx.SetTitle('')
xAx.SetLabelSize(0)
yAx.SetRangeUser(0.0, 0.25)
textScaleUp = 1.0/topPad.GetHNDC()
yAx.SetLabelSize(textScaleUp*0.04)
yAx.SetTitleSize(textScaleUp*0.04)
yAx.SetTitle('#epsilon(T|L)')
yAx.SetTitleOffset(yAx.GetTitleOffset()/textScaleUp)
effSimu.SetLineColor(r.kRed)
effSimu.SetMarkerStyle(r.kOpenCross)
effSimu.SetMarkerColor(effSimu.GetLineColor())
effData.Draw('same')
effSimu.Draw('same')
leg = drawLegendWithDictKeys(topPad, {'data':effData, 'simulation':simuTight}, legWidth=0.4)
leg.SetHeader('scale factor '+region+' '+('electron' if '_el_'in outRatiohistoname else
'muon' if '_mu_' in outRatiohistoname else ''))
can.cd()
botPad.Draw()
botPad.cd()
ratio.SetStats(0)
ratio.Draw()
textScaleUp = 1.0/botPad.GetHNDC()
xAx, yAx = ratio.GetXaxis(), ratio.GetYaxis()
yAx.SetRangeUser(0.0, 2.0)
xAx.SetTitle({'pt1':'p_{T}', 'eta1':'|#eta|', 'pt1_eta1':'p_{T}'}[variable])
yAx.SetNdivisions(-202)
yAx.SetTitle('Data/Sim')
yAx.CenterTitle()
xAx.SetLabelSize(textScaleUp*0.04)
xAx.SetTitleSize(textScaleUp*0.04)
yAx.SetLabelSize(textScaleUp*0.04)
yAx.SetTitleSize(textScaleUp*0.04)
refLine = rootUtils.referenceLine(xAx.GetXmin(), xAx.GetXmax())
refLine.Draw()
can.Update()
outFname = os.path.join(outputDir, region+'_'+outRatiohistoname)
for ext in ['.eps','.png']:
utils.rmIfExists(outFname+ext)
can.SaveAs(outFname+ext)
return {outRatiohistoname : ratio,
outDataeffhistoname : effData,
outDataeffhistoname.replace('_fake_rate_data_', '_tight_data_minus_prompt') : dataSubTight,
outDataeffhistoname.replace('_fake_rate_data_', '_loose_data_minus_prompt') : dataSubLoose
}
def plotStackedHistos(histosPerGroup={},
outputDir='',
region='',
verbose=False):
groups = histosPerGroup.keys()
variables = first(histosPerGroup).keys()
leptonTypes = first(first(histosPerGroup)).keys()
colors = getGroupColor()
mkdirIfNeeded(outputDir)
histosPerName = dict([
(
region + '_' + var + '_' +
lt, # one canvas for each histo, so key with histoname w/out group
dict([(g, histosPerGroup[g][var][lt]) for g in groups]))
for var in variables for lt in leptonTypes
])
for histoname, histosPerGroup in histosPerName.iteritems():
missingGroups = [g for g, h in histosPerGroup.iteritems() if not h]
if missingGroups:
if verbose:
print "skip %s, missing histos for %s" % (histoname,
str(missingGroups))
continue
bkgHistos = dict([(g, h) for g, h in histosPerGroup.iteritems()
if g not in ['data', 'signal']])
totBkg = summedHisto(bkgHistos.values())
err_band = None # buildErrBandGraph(totBkg, computeStatErr2(totBkg))
emptyBkg = totBkg.Integral() == 0
if emptyBkg:
if verbose: print "empty backgrounds, skip %s" % histoname
continue
can = r.TCanvas('c_' + histoname, histoname, 800, 600)
can.cd()
pm = totBkg # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update() # necessary to fool root's dumb object ownership
stack = r.THStack('stack_' + histoname, '')
can.Update()
r.SetOwnership(stack, False)
for s, h in bkgHistos.iteritems():
h.SetFillColor(colors[s] if s in colors else r.kOrange)
h.SetDrawOption('bar')
h.SetDirectory(0)
stack.Add(h)
stack.Draw('hist same')
# err_band.Draw('E2 same')
data = histosPerGroup['data']
if data and data.GetEntries():
data.SetMarkerStyle(r.kFullDotLarge)
data.Draw('p same')
# yMin, yMax = getMinMax([h for h in [totBkg, data, err_band] if h]) # fixme with err_band
yMin, yMax = 0.0, data.GetMaximum()
pm.SetMinimum(0.0)
pm.SetMaximum(1.1 * yMax)
can.Update()
topRightLabel(can, histoname, xpos=0.125, align=13)
# drawLegendWithDictKeys(can, dictSum(bkgHistos, {'stat err':err_band}), opt='f')
drawLegendWithDictKeys(can, bkgHistos, opt='f')
can.RedrawAxis()
can._stack = stack
can._histos = [h for h in stack.GetHists()] + [data]
can.Update()
outFname = os.path.join(outputDir, histoname + '.png')
utils.rmIfExists(outFname)
can.SaveAs(outFname)
def plotPerSourceEff(histosPerVar={},
outputDir='',
lepton='',
region='',
sample='',
verbose=False,
zoomIn=True):
"plot efficiency for each source (and 'anysource') as a function of each var; expect histos[var][source][loose,tight]"
variables = histosPerVar.keys()
sources = [s for s in first(histosPerVar).keys()
if s != 'real'] # only fake eff really need a scale factor
colors = colorsLineSources
mkdirIfNeeded(outputDir)
for var in filter(lambda x: x in ['pt1', 'eta1'], histosPerVar.keys()):
histosPerSource = dict((s, histosPerVar[var][s]) for s in sources)
canvasBasename = region + '_efficiency_' + lepton + '_' + var + (
"_%s" % sample if sample else '')
missingSources = [
s for s, h in histosPerSource.iteritems()
if not h['loose'] or not h['tight']
]
if missingSources:
if verbose:
print "skip %s, missing histos for %s" % (var,
str(missingSources))
continue
anySourceLoose = summedHisto(
[h['loose'] for h in histosPerSource.values()])
anySourceTight = summedHisto(
[h['tight'] for h in histosPerSource.values()])
anySourceLoose.SetName(histoNamePerSource(var, 'any', 'loose', region))
anySourceTight.SetName(histoNamePerSource(var, 'any', 'tight', region))
histosPerSource['any'] = {
'loose': anySourceLoose,
'tight': anySourceTight
}
emptyBkg = anySourceLoose.Integral() == 0 or anySourceTight.Integral(
) == 0
if emptyBkg:
if verbose: print "empty backgrounds, skip %s" % canvasBasename
continue
def computeEfficiencies(histosPerSource={}):
sources = histosPerSource.keys()
num = dict((s, histosPerSource[s]['tight']) for s in sources)
den = dict((s, histosPerSource[s]['loose']) for s in sources)
eff = dict(
(s, h.Clone(h.GetName().replace('tight', 'tight_over_loose')))
for s, h in num.iteritems())
[eff[s].Divide(den[s]) for s in sources]
return eff
effs = computeEfficiencies(histosPerSource)
can = r.TCanvas('c_' + canvasBasename, canvasBasename, 800, 600)
can.cd()
pm = first(effs) # pad master
pm.SetStats(False)
pm.Draw('axis')
can.Update()
for s, h in effs.iteritems():
h.SetMarkerColor(colors[s] if s in colors else r.kBlack)
h.SetLineColor(h.GetMarkerColor())
h.SetLineWidth(2 * h.GetLineWidth())
h.SetMarkerStyle(markersSources[s] if s in
markersSources else r.kDot)
h.Draw('ep same')
h.SetDirectory(0)
#pprint.pprint(effs)
yMin, yMax = getMinMax(effs.values())
pm.SetMinimum(0.0)
pm.SetMaximum(0.25 if yMax < 0.5 and zoomIn else 1.1)
can.Update()
topRightLabel(can, canvasBasename, xpos=0.125, align=13)
drawLegendWithDictKeys(can, effs, opt='lp')
can.RedrawAxis()
can._histos = effs
can.Update()
outFname = os.path.join(outputDir, canvasBasename + '.png')
utils.rmIfExists(outFname)
can.SaveAs(outFname)
def subtractRealAndComputeScaleFactor(histosPerGroup={},
variable='',
outRatiohistoname='',
outDataeffhistoname='',
outputDir='./',
region='',
subtractReal=True,
verbose=False):
"efficiency scale factor"
groups = histosPerGroup.keys()
mkdirIfNeeded(outputDir)
histosPerType = dict([(lt,
dict([(g, histosPerGroup[g][variable][lt])
for g in groups])) for lt in leptonTypes])
for lt in leptonTypes:
histosPerType[lt]['totSimBkg'] = summedHisto([
histo for group, histo in histosPerType[lt].iteritems()
if group not in ['data', 'signal']
])
simuTight = histosPerType['fake_tight']['totSimBkg']
simuLoose = histosPerType['fake_loose']['totSimBkg']
dataTight = histosPerType['tight']['data']
dataLoose = histosPerType['loose']['data']
# subtract real contribution from data
# _Note to self_: currently estimating the real contr from MC; in
# the past also used iterative corr, which might be more
# appropriate in cases like here, where the normalization is
# so-so. Todo: investigate the normalization.
dataSubTight = dataTight.Clone(dataTight.GetName().replace(
'data_tight', 'data_minus_prompt_tight'))
dataSubLoose = dataLoose.Clone(dataLoose.GetName().replace(
'data_loose', 'data_minus_prompt_loose'))
dataSubTight.SetDirectory(0)
dataSubLoose.SetDirectory(0)
dataSubTight.Add(histosPerType['real_tight']['totSimBkg'],
-1.0 if subtractReal else 0.0)
dataSubLoose.Add(histosPerType['real_loose']['totSimBkg'],
-1.0 if subtractReal else 0.0)
effData = dataSubTight.Clone(outDataeffhistoname)
effData.SetDirectory(0)
effData.Divide(dataSubLoose)
effSimu = simuTight.Clone(simuTight.GetName().replace(
'fake_tight', 'fake_eff'))
effSimu.SetDirectory(0)
effSimu.Divide(simuLoose)
print "eff(T|L) vs. ", variable
def formatFloat(floats):
return ["%.4f" % f for f in floats]
print "efficiency data : ", formatFloat(getBinContents(effData))
print "efficiency simu : ", formatFloat(getBinContents(effSimu))
ratio = effData.Clone(outRatiohistoname)
ratio.SetDirectory(0)
ratio.Divide(effSimu)
print "sf data/simu : ", formatFloat(getBinContents(ratio))
print " +/- : ", formatFloat(getBinErrors(ratio))
can = r.TCanvas('c_' + outRatiohistoname, outRatiohistoname, 800, 600)
botPad, topPad = rootUtils.buildBotTopPads(can)
can.cd()
topPad.Draw()
topPad.cd()
pm = effData
pm.SetStats(0)
pm.Draw('axis')
xAx, yAx = pm.GetXaxis(), pm.GetYaxis()
xAx.SetTitle('')
xAx.SetLabelSize(0)
yAx.SetRangeUser(0.0, 0.25)
textScaleUp = 1.0 / topPad.GetHNDC()
yAx.SetLabelSize(textScaleUp * 0.04)
yAx.SetTitleSize(textScaleUp * 0.04)
yAx.SetTitle('#epsilon(T|L)')
yAx.SetTitleOffset(yAx.GetTitleOffset() / textScaleUp)
effSimu.SetLineColor(r.kRed)
effSimu.SetMarkerStyle(r.kOpenCross)
effSimu.SetMarkerColor(effSimu.GetLineColor())
effData.Draw('same')
effSimu.Draw('same')
leg = drawLegendWithDictKeys(topPad, {
'data': effData,
'simulation': simuTight
},
legWidth=0.4)
leg.SetHeader('scale factor ' + region + ' ' +
('electron' if '_el_' in outRatiohistoname else
'muon' if '_mu_' in outRatiohistoname else ''))
can.cd()
botPad.Draw()
botPad.cd()
ratio.SetStats(0)
ratio.Draw()
textScaleUp = 1.0 / botPad.GetHNDC()
xAx, yAx = ratio.GetXaxis(), ratio.GetYaxis()
yAx.SetRangeUser(0.0, 2.0)
xAx.SetTitle({
'pt1': 'p_{T}',
'eta1': '|#eta|',
'pt1_eta1': 'p_{T}'
}[variable])
yAx.SetNdivisions(-202)
yAx.SetTitle('Data/Sim')
yAx.CenterTitle()
xAx.SetLabelSize(textScaleUp * 0.04)
xAx.SetTitleSize(textScaleUp * 0.04)
yAx.SetLabelSize(textScaleUp * 0.04)
yAx.SetTitleSize(textScaleUp * 0.04)
refLine = rootUtils.referenceLine(xAx.GetXmin(), xAx.GetXmax())
refLine.Draw()
can.Update()
outFname = os.path.join(outputDir, region + '_' + outRatiohistoname)
for ext in ['.eps', '.png']:
utils.rmIfExists(outFname + ext)
can.SaveAs(outFname + ext)
return {
outRatiohistoname:
ratio,
outDataeffhistoname:
effData,
outDataeffhistoname.replace('_fake_rate_data_', '_tight_data_minus_prompt'):
dataSubTight,
outDataeffhistoname.replace('_fake_rate_data_', '_loose_data_minus_prompt'):
dataSubLoose
}