def plotStackedHistos(histosFlavorSlice={}, canvasName='', outputDir='./', frameTitle='stack', colors={}) :
"Plot the input histos used to compute the fractions"
histos = histosFlavorSlice
can = r.TCanvas(canvasName, canvasName, 800, 600)
can.cd()
stack = r.THStack('stack_'+canvasName, '')
leg = topRightLegend(can, 0.275, 0.475, shift=-0.025)
leg.SetBorderSize(0)
colors = SampleUtils.colors if not colors else colors
procs = sorted(histos.keys())
for p in procs:
h = histos[p]
h.SetFillColor(colors[p])
h.SetLineColor(h.GetFillColor())
h.SetDrawOption('bar')
stack.Add(h)
for s in procs[::-1] : leg.AddEntry(histos[s], s, 'F') # stack goes b-t, legend goes t-b
stack.Draw('hist e')
leg.Draw('same')
tex = r.TLatex()
tex.SetNDC(True)
tex.SetTextFont(first(histos).GetTitleFont())
tex.SetTextSize(first(histos).GetTitleSize())
tex.DrawLatex(0.1, 0.925, frameTitle.split(';')[0])
can.Update() # force stack to create canMaster
canMaster = stack.GetHistogram()
canMaster.SetTitle(frameTitle)
canMaster.Draw('axis same')
can._graphical_objects = [stack, canMaster, leg, tex] + [h for h in stack.GetStack()]
can.Update()
for ext in ['png','eps'] :
outFilename = outputDir+'/'+canvasName+'.'+ext
rmIfExists(outFilename)
can.SaveAs(outFilename)
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 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 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 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 plotFractionsStacked(histos={}, canvasName='', canvasTitle='', outputDir='./', frameTitle='title;p_{T} [GeV]; efficiency',
histos2={}, h1Label='', h2Label='') :
"plot stack of histos; optional histos2 are also stacked with the same colors, but with different fill style"
can = r.TCanvas(canvasName, '', 800, 600)
can.cd()
stack = r.THStack('stack_'+canvasName, '')
leg = topRightLegend(can, 0.275, 0.475, shift=+0.010)
leg.SetBorderSize(0)
leg.SetX1NDC(0.9)
leg.SetX2NDC(1.0)
colors = SampleUtils.colors
procs = sorted(histos.keys())
def setHistoAtts(histo, process, colors=colors, fillStyle=None) :
h, p = histo, process
h.SetMarkerSize(0)
h.SetFillColor(colors[p])
h.SetLineColor(h.GetFillColor())
h.SetDrawOption('bar')
paleColors = {'ttbar':r.kRed-9,
'zjets' : r.kOrange-4,
'wjets' : r.kBlue-8,
'diboson' : r.kSpring+1,
'singletop' : r.kAzure+6,
'multijet' : r.kGray,
'heavyflavor' : r.kViolet-9}
if fillStyle :
h.SetFillColor(paleColors[p])
h.SetLineColor(h.GetFillColor())
for p in procs:
h = histos[p]
setHistoAtts(h, p)
stack.Add(h)
for s in procs[::-1] : leg.AddEntry(histos[s], ('bb/cc' if s=='heavyflavor' else s), 'F') # stack goes b-t, legend goes t-b
for p in filter(lambda p: p in histos2, procs) :
setHistoAtts(histos2[p], p, fillStyle=3001)
stack.Add(histos2[p])
stack.Draw('hist')
if h1Label or h2Label:
leg.SetHeader(', '.join(["%s : %s"%(f,l) if l else '' for f,l in [('darker',h1Label), ('lighter',h2Label)]]))
leg.Draw('same')
tex = r.TLatex()
tex.SetNDC(True)
tex.DrawLatex(0.1, 0.9, 'fractions: '+frameTitle[:frameTitle.find(';')-1])
can.Update() # force stack to create canMaster
canMaster = stack.GetHistogram()
canMaster.SetTitle(frameTitle)
canMaster.Draw('axis same')
can._graphical_objects = [stack, canMaster, leg, tex] + [h for h in stack.GetStack()]
can.Update()
for ext in ['png','eps'] :
outFilename = outputDir+'/'+canvasName+'.'+ext
rmIfExists(outFilename)
can.SaveAs(outFilename)
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 main() :
parser = optparse.OptionParser(usage=usage)
parser.add_option('-t', '--tag')
parser.add_option('-f', '--input_fake')
parser.add_option('-i', '--input_dir')
parser.add_option('-o', '--output_dir')
parser.add_option('-v','--verbose', action='store_true', default=False)
(opts, args) = parser.parse_args()
requiredOptions = ['tag', 'input_fake', 'input_dir', 'output_dir',]
otherOptions = ['verbose']
allOptions = requiredOptions + otherOptions
def optIsNotSpecified(o) : return not hasattr(opts, o) or getattr(opts,o) is None
if any(optIsNotSpecified(o) for o in requiredOptions) : parser.error('Missing required option')
tag = opts.tag.strip('_')
inputFakeFile = opts.input_fake
inputDirname = opts.input_dir
outputDir = opts.output_dir
outputDir = outputDir if outputDir.endswith('/') else outputDir+'/'
verbose = opts.verbose
if verbose : print '\nUsing the following options:\n'+'\n'.join("%s : %s"%(o, str(getattr(opts, o))) for o in allOptions)
inputFiles = getInputFiles(inputDirname, tag, verbose)
inputFiles[fakeSample()] = r.TFile.Open(inputFakeFile)
assert all(f for f in inputFiles.values()), ("missing inputs: \n%s"%'\n'.join(["%s : %s"%kv for kv in inputFiles.iteritems()]))
mkdirIfNeeded(outputDir)
for region in ['cr8lptee', 'cr8lptmm', 'cr9lpt', 'sr8', 'sr9', 'srSsEwk', 'crSsEwkLoose'] :
for channel in ['ee', 'em', 'mm'] :
for varname in ['l0_pt', 'l1_pt', 'll_M', 'metrel', 'met', 'njets', 'nbjets'] :
histo_basename = region+'_'+channel+'_'+varname
hists, err2s = buildHists(inputFiles, histo_basename)
if not hists[dataSample()].GetEntries() : continue
err_band = buildErrBandGraph(hists['sm'], err2s)
err_band_r = buildErrBandRatioGraph(err_band)
can = r.TCanvas('can_'+histo_basename, histo_basename, 800, 600)
botPad, topPad = buildBotTopPads(can)
can.cd()
topPad.Draw()
drawTop(topPad, hists, err_band, (channel, region))
can.cd()
botPad.Draw()
drawBot(botPad, hists[dataSample()], hists['sm'], err_band_r, xaxisLabel(varname))
can.Update()
outFilename = outputDir+histo_basename+'.png'
rmIfExists(outFilename) # avoid root warnings
can.SaveAs(outFilename)
if verbose : print "output saved to \n%s"%outputDir
def plotFractionsStacked(histos={}, canvasName='', outputDir='./', frameTitle='title;p_{T} [GeV]; fraction'):
"plot stack of histos[source][group]"
can = r.TCanvas(canvasName, '', 800, 600)
can.cd()
can.SetRightMargin(2.0*can.GetRightMargin())
stack = r.THStack('stack_'+canvasName, '')
leg = rightLegend(can)
leg.SetBorderSize(0)
colors = SampleUtils.colors
sources = sorted(histos.keys())
groups = sorted(first(histos).keys())
fillStyles = {'light':3365, 'heavy':3356, 'conv':3663}
assert len(sources)<4,"can only plot up to three sources, %s"%str(sources)
def setHistoAtts(histo, group, colors=colors, fillStyle=None) :
h, g = histo, group
h.SetMarkerSize(0)
h.SetFillColor(colors[g])
h.SetLineColor(h.GetFillColor())
h.SetDrawOption('bar')
if fillStyle : h.SetFillStyle(fillStyle)
for s in sources:
for g in groups:
h = histos[s][g]
setHistoAtts(h, g, fillStyle=fillStyles[s])
stack.Add(h)
for s in sources[::-1]: # stack goes b-t, legend goes t-b
leg.AddEntry(r.TObject(), s, '')
def niceLabel(group) : return 'bb/cc' if group=='heavyflavor' else group
for g in groups[::-1] : leg.AddEntry(histos[s][g], niceLabel(g) , 'F')
stack.Draw('hist')
leg.Draw('same')
tex = r.TLatex()
tex.SetNDC(True)
tex.DrawLatex(0.1, 0.9, 'fractions: '+frameTitle[:frameTitle.find(';')-1])
can.Update() # force stack to create canMaster
canMaster = stack.GetHistogram()
canMaster.SetTitle(frameTitle)
canMaster.Draw('axis same')
can._graphical_objects = [stack, canMaster, leg, tex] + [h for h in stack.GetStack()]
can.Update()
for ext in ['png','eps'] :
outFilename = outputDir+'/'+canvasName+'.'+ext
rmIfExists(outFilename)
can.SaveAs(outFilename)
def plot2dEfficiencies(effs={}, canvasName='', outputDir='./', frameTitle='efficiency; #eta; p_{T} [GeV]', textFormat='.3f', zoomIn=False) :
can = r.TCanvas(canvasName, '', 800, 600)
can.cd()
origTextFormat = r.gStyle.GetPaintTextFormat()
r.gStyle.SetPaintTextFormat(textFormat)
for s,h in effs.iteritems() :
can.Clear()
# todo minZ, maxZ = getMinMax(effs.values()) if zoomIn else (0.0, 1.0)
minZ, maxZ = (0.0, 1.0)
h.SetMarkerSize(1.5*h.GetMarkerSize())
h.Draw('colz')
h.Draw('text e same')
h.GetZaxis().SetRangeUser(min([0.0, minZ]), maxZ)
def dropCrPrefix(sr) : return sr.replace('CR_', '')
h.SetTitle(dropCrPrefix(s)+' : '+frameTitle)
h.SetStats(False)
can.Update()
for ext in ['png','eps'] :
outFilename = outputDir+'/'+canvasName+'_'+s+'.'+ext
rmIfExists(outFilename)
can.SaveAs(outFilename)
r.gStyle.SetPaintTextFormat(origTextFormat)
def plotVar(bkgHistos, sigHistos, llnjvar, plotdir='./') :
def preferredSignal(signals):
pref = 'Herwigpp_sM_wA_noslep_notauhad_WH_2Lep_1'
return pref if pref in signals else first(sorted(signals))
signalSample = preferredSignal(sigHistos.keys())
allHistos = bkgHistos.values() + [sigHistos[signalSample],]
allHistosEmpty = all([h.GetEntries()==0 for h in allHistos])
if allHistosEmpty : return
can = r.TCanvas('can_'+llnjvar, llnjvar, 800, 800)
botPad, topPad = buildBotTopPads(can, splitFraction=0.75, squeezeMargins=False)
totBkg = summedHisto(bkgHistos.values())
totBkg.SetDirectory(0)
can._totBkg = totBkg
can._histos = [bkgHistos, sigHistos]
can.cd()
botPad.Draw()
drawBottom(botPad, totBkg, bkgHistos, sigHistos[signalSample], llnjvar)
can.cd()
topPad.Draw()
drawTop(topPad, totBkg, sigHistos[signalSample])
mkdirIfNeeded(plotdir)
outFilename = plotdir+'/'+llnjvar+'.png'
rmIfExists(outFilename) # avoid root warnings
can.SaveAs(outFilename)
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 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 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
}