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 main():
parser = optparse.OptionParser(usage=usage)
parser.add_option('-i', '--input-dir', default='./out/fakerate')
parser.add_option('-o', '--output-dir', default='./out/fakerate/efficiencies')
parser.add_option('-l', '--lepton', default='el', help='either el or mu')
parser.add_option('-m', '--mode', help='real, conv, hflf')
parser.add_option('-t', '--tag', help='tag used to select the input files (e.g. Apr_04)')
parser.add_option('-f', '--fill-histos', action='store_true', default=False, help='force fill (default only if needed)')
parser.add_option('-T', '--tight-def', help='on-the-fly tight def, one of defs in fakeUtils.py: fakeu.lepIsTight_std, etc.')
parser.add_option('-v', '--verbose', action='store_true', default=False)
(options, args) = parser.parse_args()
inputDir = options.input_dir
outputDir = options.output_dir
lepton = options.lepton
mode = options.mode
tag = options.tag
verbose = options.verbose
if not tag : parser.error('tag is a required option')
if lepton not in ['el', 'mu'] : parser.error("invalid lepton '%s'"%lepton)
validModesEl = ['real', 'hflf'] + ['conv']
validModesMu = ['real', 'hflf']
if mode not in (validModesEl if lepton=='el' else validModesMu) : parser.error("invalid mode %s"%mode)
tupleStem, treeName = {'conv' : ('mcconv_tuple', 'ConversionExtractionRegion'),
'hflf' : ('mcqcd_tuple', 'HfLfExtractionRegion'),
'real' : ('mcreal_tuple', 'RealExtractionRegion')
}[mode]
templateInputFilename = "*_%(stem)s_%(tag)s.root" % {'tag':tag, 'stem':tupleStem}
templateOutputFilename = "%(stem)s_%(l)s_eff.root" % {'stem':tupleStem.replace('tuple','histos'), 'l':lepton}
outputFileName = os.path.join(outputDir, templateOutputFilename)
cacheFileName = outputFileName.replace('.root', '_'+mode+'_cache.root')
doFillHistograms = options.fill_histos or not os.path.exists(cacheFileName)
onthefly_tight_def = eval(options.tight_def) if options.tight_def else None # eval will take care of aborting on typos
optionsToPrint = ['inputDir', 'outputDir', 'mode', 'tag', 'doFillHistograms', 'cacheFileName', 'onthefly_tight_def']
if verbose :
print "working from %s"%os.getcwd()
print "being called as : %s"%' '.join(os.sys.argv)
print "options parsed:\n"+'\n'.join(["%s : %s"%(o, eval(o)) for o in optionsToPrint])
# collect inputs
print 'input filenames: ',os.path.join(inputDir, templateInputFilename)
tupleFilenames = glob.glob(os.path.join(inputDir, templateInputFilename))
samples = setSameGroupForAllData(fastSamplesFromFilenames(tupleFilenames, verbose))
samplesPerGroup = collections.defaultdict(list)
filenamesPerGroup = collections.defaultdict(list)
mkdirIfNeeded(outputDir)
for s, f in zip(samples, tupleFilenames) :
samplesPerGroup[s.group].append(s)
filenamesPerGroup[s.group].append(f)
vars = ['pt', 'pt_eta']
groups = [g for g in samplesPerGroup.keys() if not isDataSample(g) and not g=='higgs']
if lepton=='el' : groups = [g for g in groups if g!='heavyflavor']
sourcesThisMode = {'real' : ['real'], # use same convention as in FakeLeptonSources.h
'conv' : ['conv'],
'hflf' : ['heavy', 'light', 'qcd']
}[mode]
#fill histos
if doFillHistograms :
start_time = time.clock()
num_processed_entries = 0
histosPerGroupPerSource = bookHistosPerSamplePerSource(vars, groups, sourcesThisMode, mode=mode)
for group in groups:
filenames = filenamesPerGroup[group]
histosThisGroupPerSource = dict((v, histosPerGroupPerSource[v][group]) for v in histosPerGroupPerSource.keys())
histosAnyGroupPerSource = dict((v, histosPerGroupPerSource[v]['anygroup']) for v in histosPerGroupPerSource.keys())
chain = r.TChain(treeName)
[chain.Add(fn) for fn in filenames]
if verbose: print "%s : %d entries"%(group, chain.GetEntries())
num_processed_entries += fillHistos(chain, histosThisGroupPerSource, histosAnyGroupPerSource,
lepton, mode,
onthefly_tight_def=onthefly_tight_def, verbose=verbose)
writeHistos(cacheFileName, histosPerGroupPerSource, verbose)
end_time = time.clock()
delta_time = end_time - start_time
if verbose:
print ("processed {0:d} entries ".format(num_processed_entries)
+"in "+("{0:d} min ".format(int(delta_time/60)) if delta_time>60 else
"{0:.1f} s ".format(delta_time))
+"({0:.1f} kHz)".format(num_processed_entries/delta_time))
# compute efficiencies
histosPerGroupPerSource = fetchHistos(cacheFileName, histoNamesPerSamplePerSource(vars, groups, sourcesThisMode, mode), verbose)
effs = computeEfficiencies(histosPerGroupPerSource) # still [var][gr][source][l/t]
for s in sourcesThisMode:
for v in vars:
groups = first(effs).keys()
varIs1D, varIs2D = v=='pt', v=='pt_eta'
effsThisSourceThisVar = dict((g, effs[v][g][s]) for g in groups)
densThisSourceThisVar = dict((g, histosPerGroupPerSource[v][g][s]['loose']) for g in groups if g!='anygroup')
numsThisSourceThisVar = dict((g, histosPerGroupPerSource[v][g][s]['tight']) for g in groups if g!='anygroup')
if varIs1D:
cname = 'eff_'+lepton+'_'+s
lT, lX, lY = '#varepsilon(T|L)', 'p_{T} [GeV]', '#varepsilon(T|L)'
title = lT+' '+s+' '+lepton+';'+lX+';'+lY
zoomIn = True
fakeu.plot1dEfficiencies(effsThisSourceThisVar, cname, outputDir, title, zoomIn)
cname = 'stack_loose_'+lepton+'_'+s
lT, lY = 'loose '+lepton+', denominator to #varepsilon(T|L)', '#varepsilon(T|L)'
title = lT+' '+s+' '+lepton+';'+lX+';'+lY
plotParametrizedFractions.plotStackedHistos(densThisSourceThisVar, cname, outputDir, title)
cname = 'stack_tight_'+lepton+'_'+s
lT, lY = 'tight '+lepton+', numerator to #varepsilon(T|L)', '#varepsilon(T|L)'
title = lT+' '+s+' '+lepton+';'+lX+';'+lY
plotParametrizedFractions.plotStackedHistos(numsThisSourceThisVar, cname, outputDir, title)
elif varIs2D:
cname = 'eff_'+lepton+'_'+s
lT, lX, lY = '#varepsilon(T|L)', 'p_{T} [GeV]', '#eta'
title = lT+' '+s+' '+lepton+';'+lX+';'+lY
fakeu.plot2dEfficiencies(effsThisSourceThisVar, cname, outputDir, title, zoomIn=zoomIn)
writeHistos(outputFileName, effs, verbose)
if verbose : print "saved scale factors to %s" % outputFileName
def main():
parser = optparse.OptionParser(usage=usage)
parser.add_option('-i', '--input-dir', default='./out/fakerate')
parser.add_option('-o', '--output-dir', default='./out/fake_el_scale_factor', help='dir for plots')
parser.add_option('-l', '--lepton', default='el', help='either el or mu')
parser.add_option('-r', '--region', help='where we want the compositions,'
' i.e. one of the regions for which we saved the fake nutples'
' (eg. ssinc1j_tuple*, emu_tuple*')
parser.add_option('-s', '--syst-fudge', help='scale down main group (el:wjets, mu:bb/cc) to evaluate fraction syst unc')
parser.add_option('-t', '--tag', help='tag used to select the input files (e.g. Apr_04)')
parser.add_option('-f', '--fill-histos', action='store_true', default=False, help='force fill (default only if needed)')
parser.add_option('-v', '--verbose', action='store_true', default=False)
(options, args) = parser.parse_args()
inputDir = options.input_dir
outputDir = options.output_dir
lepton = options.lepton
systfudge = options.syst_fudge
region = options.region
tag = options.tag
verbose = options.verbose
if not tag : parser.error('tag is a required option')
if not region : parser.error('region is a required option')
if lepton not in ['el', 'mu'] : parser.error("invalid lepton '%s'"%lepton)
outputDir = outputDir+'/'+lepton # split the output in subdirectories, so we don't overwrite things
templateInputFilename = "*_%(region)s_tuple_%(tag)s.root" % {'tag':tag, 'region':region}
templateOutputFilename = "%(l)s_composition_histos.root" % {'l':lepton}
treeName = dict(fakeu.tupleStemsAndNames)[region]
outputFileName = os.path.join(outputDir, templateOutputFilename)
cacheFileName = outputFileName.replace('.root', '_cache.root')
doFillHistograms = options.fill_histos or not os.path.exists(cacheFileName)
optionsToPrint = ['inputDir', 'outputDir', 'tag', 'doFillHistograms', 'systfudge']
if verbose :
print "working from %s"%os.getcwd()
print "being called as : %s"%' '.join(os.sys.argv)
print "options parsed:\n"+'\n'.join(["%s : %s"%(o, eval(o)) for o in optionsToPrint])
# collect inputs
print '----> input files ',os.path.join(inputDir, templateInputFilename)
tupleFilenames = glob.glob(os.path.join(inputDir, templateInputFilename))
samples = setSameGroupForAllData(fastSamplesFromFilenames(tupleFilenames, verbose))
samplesPerGroup = collections.defaultdict(list)
filenamesPerGroup = collections.defaultdict(list)
mkdirIfNeeded(outputDir)
for s, f in zip(samples, tupleFilenames) :
samplesPerGroup[s.group].append(s)
filenamesPerGroup[s.group].append(f)
vars = ['pt', 'eta', 'pt_eta', 'mt', 'mdeltar']
groups = samplesPerGroup.keys()
if lepton=='el' : groups = [g for g in groups if g!='heavyflavor']
selections = [region]
#fill histos
if doFillHistograms :
start_time = time.clock()
num_processed_entries = 0
histosPerGroupPerSource = bookHistosPerSamplePerSource(vars, groups, leptonSources, selections)
for group in groups:
isData = isDataSample(group)
filenames = filenamesPerGroup[group]
histosThisGroupPerSource = histosPerGroupPerSource[group]
chain = r.TChain(treeName)
[chain.Add(fn) for fn in filenames]
print "%s : %d entries (%d files)"%(group, chain.GetEntries(), chain.GetListOfFiles().GetEntries())
num_processed_entries += fillHistos(chain, histosThisGroupPerSource,
isData, lepton, group, region, verbose)
writeHistos(cacheFileName, histosPerGroupPerSource, verbose)
end_time = time.clock()
delta_time = end_time - start_time
if verbose:
print ("processed {0:d} entries ".format(num_processed_entries)
+"in "+("{0:d} min ".format(int(delta_time/60)) if delta_time>60 else
"{0:.1f} s ".format(delta_time))
+"({0:.1f} kHz)".format(num_processed_entries/delta_time))
# compute and plot fractions
histosPerGroupPerSource = fetchHistos(cacheFileName, histoNamesPerSamplePerSource(vars, groups, leptonSources, selections))
histosCompositions = dict()
for sel in selections:
histosCompositions[sel] = dict()
for var in vars:
hs, groups = histosPerGroupPerSource, histosPerGroupPerSource.keys()
groups = [g for g in groups if g!='data' and g!='higgs']
histosHeavy = dict((g, hs[g][sel]['heavy'][var]['loose']) for g in groups)
histosLight = dict((g, hs[g][sel]['light'][var]['loose']) for g in groups)
histosConv = dict((g, hs[g][sel]['conv' ][var]['loose']) for g in groups)
normalizeHistos = plotParametrizedFractions.normalizeHistos
plotStackedHistos = plotParametrizedFractions.plotStackedHistos
frameTitle = 'hf '+lepton+': '+sel+' loose;'+var
canvasName = lepton+'_hf'+sel+'_'+var+'_den'
plotStackedHistos(histosHeavy, canvasName, outputDir, frameTitle)
frameTitle = 'lf '+lepton+': '+sel+' loose;'+var
canvasName = lepton+'_lf'+sel+'_'+var+'_den'
plotStackedHistos(histosHeavy, canvasName, outputDir, frameTitle)
frameTitle = 'conv '+lepton+': '+sel+' loose;'+var
canvasName = lepton+'_conv'+sel+'_'+var+'_den'
plotStackedHistos(histosConv, canvasName, outputDir, frameTitle)
# normalize and draw fractions (den only)
histos = dict([(k+'_heavy', h) for k,h in histosHeavy.iteritems()] +
[(k+'_light', h) for k,h in histosLight.iteritems()] +
[(k+'_conv', h) for k,h in histosConv.iteritems()])
if systfudge: fudgeCompositions(histosHeavy, histosLight, histosConv if lepton=='el' else None)
normalizeHistos(histos)
anygroupCompositions = buildCompositionsAddingGroups({'heavy':histosHeavy, 'light':histosLight, 'conv':histosConv})
histosCompositions[sel][var] = {'bygroup':histos, 'anygroup': anygroupCompositions}
is1Dhisto = var!='pt_eta' # can only stack 1D plots
if is1Dhisto:
histosBySource = {'heavy':histosHeavy, 'light':histosLight, 'conv':histosConv}
frameTitle = lepton+': '+sel+';'+var
canvasBaseName = lepton+'_fake'+sel+'_'+var+'_frac'
plotFractionsStacked(histosBySource, canvasBaseName+'_stack', outputDir, frameTitle)
writeHistos(outputFileName, histosCompositions, verbose)
def main():
parser = optparse.OptionParser(usage=usage)
parser.add_option('-i', '--input-dir', default='./out/fakerate')
parser.add_option('-o', '--output-dir', default='./out/tight_variables_plots', help='dir for plots')
parser.add_option('-l', '--lepton', default='el', help='either el or mu')
parser.add_option('-r', '--region', help='one of the regions for which we saved the fake ntuples')
parser.add_option('-t', '--tag', help='tag used to select the input files (e.g. Apr_04)')
parser.add_option('-f', '--fill-histos', action='store_true', default=False, help='force fill (default only if needed)')
parser.add_option('-v', '--verbose', action='store_true', default=False)
(options, args) = parser.parse_args()
inputDir = options.input_dir
outputDir = options.output_dir
lepton = options.lepton
region = options.region
tag = options.tag
verbose = options.verbose
if not tag : parser.error('tag is a required option')
if lepton not in ['el', 'mu'] : parser.error("invalid lepton '%s'"%lepton)
filestems, treenames = utils.verticalSlice(fakeu.tupleStemsAndNames)
regions = filestems
assert region in regions,"invalid region '%s', must be one of %s"%(region, str(regions))
templateInputFilename = "*_%(region)s_tuple_%(tag)s.root" % {'tag':tag, 'region':region}
templateOutputFilename = "%(region)s_%(l)s_tight_plots.root" % {'region':region, 'l':lepton}
treeName = treenames[regions.index(region)]
outputDir = outputDir+'/'+region+'/'+lepton # split the output in subdirectories, so we don't overwrite things
mkdirIfNeeded(outputDir)
outputFileName = os.path.join(outputDir, templateOutputFilename)
cacheFileName = outputFileName.replace('.root', '_'+region+'_cache.root')
doFillHistograms = options.fill_histos or not os.path.exists(cacheFileName)
optionsToPrint = ['inputDir', 'outputDir', 'region', 'tag', 'doFillHistograms']
if verbose :
print "working from %s"%os.getcwd()
print "being called as : %s"%' '.join(os.sys.argv)
print "options:\n"+'\n'.join(["%s : %s"%(o, eval(o)) for o in optionsToPrint])
# collect inputs
if verbose : print 'input files ',os.path.join(inputDir, templateInputFilename)
tupleFilenames = glob.glob(os.path.join(inputDir, templateInputFilename))
samples = setSameGroupForAllData(fastSamplesFromFilenames(tupleFilenames, verbose))
if not samples : samples = [guessSampleFromFilename(f) for f in tupleFilenames] # if the fast guess didn't work, try the slow one
samplesPerGroup = collections.defaultdict(list)
filenamesPerGroup = collections.defaultdict(list)
for s, f in zip(samples, tupleFilenames) :
samplesPerGroup[s.group].append(s)
filenamesPerGroup[s.group].append(f)
vars = ['pt','eta','d0sig','z0SinTheta','etCone','ptCone','etConeCorr','ptConeCorr']
vars += ['relEtConeStd', 'relPtConeStd', 'relEtConeMod', 'relPtConeMod']
groups = samplesPerGroup.keys()
sources = leptonSources
#fill histos
if doFillHistograms :
lepLabel = "(probe %s)"%lepton
histosPerGroup = bookHistosPerGroup(vars, groups, lepLabel=lepLabel)
histosPerSource = bookHistosPerSource(vars, sources, lepLabel=lepLabel)
for group in groups:
isData = isDataSample(group)
filenames = filenamesPerGroup[group]
histosThisGroup = histosPerGroup[group]
chain = r.TChain(treeName)
[chain.Add(fn) for fn in filenames]
print "%s : %d entries"%(group, chain.GetEntries())
fillHistos(chain, histosThisGroup, histosPerSource, isData, lepton, group, verbose)
writeHistos(cacheFileName, {'perGroup':histosPerGroup, 'perSource':histosPerSource}, verbose)
# compute scale factors
histosPerGroup = fetchHistos(cacheFileName, histoNames(vars, groups), verbose)
histosPerSource = fetchHistos(cacheFileName, histoNames(vars, sources), verbose)
plotStackedHistos(histosPerGroup, outputDir+'/by_group', region, colors=SampleUtils.colors, verbose=verbose)
plotStackedHistos(histosPerSource, outputDir+'/by_source', region, colors=fakeu.colorsFillSources(), verbose=verbose)
plotIsoComparison(histosPerSource, outputDir+'/', region, lepton, verbose)
def main():
parser = optparse.OptionParser(usage=usage)
parser.add_option('-i', '--input-dir', default='./out/fakerate')
parser.add_option('-o', '--output-dir', default='./out/fake_scale_factor', help='dir for plots')
parser.add_option('-l', '--lepton', default='el', help='either el or mu')
parser.add_option('-r', '--region', help='one of the regions for which we saved the fake ntuples')
parser.add_option('-t', '--tag', help='tag used to select the input files (e.g. Apr_04)')
parser.add_option('-T', '--tight-def', help='on-the-fly tight def, one of defs in fakeUtils.py: fakeu.lepIsTight_std, etc.')
parser.add_option('-f', '--fill-histos', action='store_true', default=False, help='force fill (default only if needed)')
parser.add_option('-v', '--verbose', action='store_true', default=False)
(options, args) = parser.parse_args()
inputDir = options.input_dir
outputDir = options.output_dir
lepton = options.lepton
region = options.region
tag = options.tag
verbose = options.verbose
if not tag : parser.error('tag is a required option')
if lepton not in ['el', 'mu'] : parser.error("invalid lepton '%s'"%lepton)
filestems, treenames = utils.verticalSlice(fakeu.tupleStemsAndNames)
regions = filestems
assert region in regions,"invalid region '%s', must be one of %s"%(region, str(regions))
templateInputFilename = "*_%(region)s_tuple_%(tag)s.root" % {'tag':tag, 'region':region}
templateOutputFilename = "%(region)s_%(l)s_scale_histos.root" % {'region':region, 'l':lepton}
treeName = treenames[regions.index(region)]
outputDir = outputDir+'/'+region+'/'+lepton # split the output in subdirectories, so we don't overwrite things
mkdirIfNeeded(outputDir)
outputFileName = os.path.join(outputDir, templateOutputFilename)
cacheFileName = outputFileName.replace('.root', '_'+region+'_cache.root')
doFillHistograms = options.fill_histos or not os.path.exists(cacheFileName)
onthefly_tight_def = eval(options.tight_def) if options.tight_def else None # eval will take care of aborting on typos
optionsToPrint = ['inputDir', 'outputDir', 'region', 'tag', 'doFillHistograms', 'onthefly_tight_def']
if verbose :
print "working from %s"%os.getcwd()
print "being called as : %s"%' '.join(os.sys.argv)
print "options:\n"+'\n'.join(["%s : %s"%(o, eval(o)) for o in optionsToPrint])
# collect inputs
if verbose : print 'input files ',os.path.join(inputDir, templateInputFilename)
tupleFilenames = glob.glob(os.path.join(inputDir, templateInputFilename))
samples = setSameGroupForAllData(fastSamplesFromFilenames(tupleFilenames, verbose))
samplesPerGroup = collections.defaultdict(list)
filenamesPerGroup = collections.defaultdict(list)
mkdirIfNeeded(outputDir)
for s, f in zip(samples, tupleFilenames) :
samplesPerGroup[s.group].append(s)
filenamesPerGroup[s.group].append(f)
vars = ['mt0', 'mt1', 'pt0', 'pt1', 'eta1']
groups = samplesPerGroup.keys()
#fill histos
if doFillHistograms :
start_time = time.clock()
num_processed_entries = 0
histosPerGroup = bookHistos(vars, groups, region=region)
histosPerSource = bookHistosPerSource(vars, leptonSources, region=region)
histosPerGroupPerSource = bookHistosPerSamplePerSource(vars, groups, leptonSources, region=region)
for group in groups:
isData = isDataSample(group)
filenames = filenamesPerGroup[group]
if verbose:
print " --- group : %s ---".format(group)
print '\n\t'.join(filenames)
histosThisGroup = histosPerGroup[group]
histosThisGroupPerSource = dict((v, histosPerGroupPerSource[v][group]) for v in histosPerGroupPerSource.keys())
chain = r.TChain(treeName)
[chain.Add(fn) for fn in filenames]
if verbose: print "%s : %d entries"%(group, chain.GetEntries())
num_processed_entries += fillHistos(chain, histosThisGroup, histosPerSource,
histosThisGroupPerSource,
lepton, group, region,
onthefly_tight_def=onthefly_tight_def, verbose=verbose)
writeHistos(cacheFileName, histosPerGroup, histosPerSource, histosPerGroupPerSource, verbose)
end_time = time.clock()
delta_time = end_time - start_time
if verbose:
print ("processed {0:d} entries ".format(num_processed_entries)
+"in "+("{0:d} min ".format(int(delta_time/60)) if delta_time>60 else
"{0:.1f} s ".format(delta_time))
+"({0:.1f} kHz)".format(num_processed_entries/delta_time))
# compute scale factors
histosPerGroup = fetchHistos(cacheFileName, histoNames(vars, groups, region), verbose)
histosPerSource = fetchHistos(cacheFileName, histoNamesPerSource(vars, leptonSources, region), verbose)
histosPerSamplePerSource = fetchHistos(cacheFileName, histoNamesPerSamplePerSource(vars, groups, leptonSources, region), verbose)
plotStackedHistos(histosPerGroup, outputDir+'/by_group', region, verbose)
plotStackedHistosSources(histosPerSource, outputDir+'/by_source', region, verbose)
plotPerSourceEff(histosPerVar=histosPerSource, outputDir=outputDir+'/by_source', lepton=lepton, region=region, verbose=verbose)
for g in groups:
hps = dict((v, histosPerSamplePerSource[v][g])for v in vars)
plotPerSourceEff(histosPerVar=hps, outputDir=outputDir, lepton=lepton, region=region, sample=g, verbose=verbose)
hn_sf_eta = histoname_sf_vs_eta (lepton)
hn_sf_pt = histoname_sf_vs_pt (lepton)
hn_da_eta = histoname_data_fake_eff_vs_eta(lepton)
hn_da_pt = histoname_data_fake_eff_vs_pt (lepton)
objs_eta = subtractRealAndComputeScaleFactor(histosPerGroup, 'eta1', hn_sf_eta, hn_da_eta, outputDir, region, verbose)
objs_pt = subtractRealAndComputeScaleFactor(histosPerGroup, 'pt1', hn_sf_pt, hn_da_pt, outputDir, region, verbose)
rootUtils.writeObjectsToFile(outputFileName, dictSum(objs_eta, objs_pt), verbose)
if verbose : print "saved scale factors to %s" % outputFileName
def fillHistos(chain, histosThisGroup, histosPerSource, histosThisGroupPerSource,
lepton, group, region, onthefly_tight_def=None, verbose=False):
nLoose, nTight = 0, 0
totWeightLoose, totWeightTight = 0.0, 0.0
normFactor = 1.0 if group=='heavyflavor' else 1.0 # bb/cc hand-waving normalization factor, see notes 2014-04-17
addTlv, computeMt = kin.addTlv, kin.computeMt
isData = isDataSample(group)
isHflf = region=='hflf'
isConversion = region=='conv'
if group=='heavyflavor':
if lepton=='el' and not isConversion : normFactor = 1.6
if lepton=='mu' : normFactor = 0.87
num_processed_entries = 0
for iEvent, event in enumerate(chain) :
num_processed_entries += 1
pars = event.pars
weight, evtN, runN = pars.weight, pars.eventNumber, pars.runNumber
hasTrigmatch = pars.has2ltrigmatch==1
weight = weight*normFactor
tag, probe, met = addTlv(event.l0), addTlv(event.l1), addTlv(event.met)
isSameSign = tag.charge*probe.charge > 0.
isRightProbe = probe.isEl if lepton=='el' else probe.isMu if lepton=='mu' else False
isTight = onthefly_tight_def(probe) if onthefly_tight_def else probe.isTight
probeSource = probe.source
sourceReal = 3 # see FakeLeptonSources.h
isReal = probeSource==sourceReal and not isData
isFake = not isReal and not isData
jets = event.jets
jets = [addTlv(j) for j in jets] # only if needed
def isBjet(j, mv1_80=0.3511) : return j.mv1 > mv1_80 # see SusyDefs.h
hasBjets = any(isBjet(j) for j in jets) # compute only if necessary
hasFjets = any(abs(j.p4.Eta())>2.4 and j.p4.Pt()>30. for j in jets)
hasCLjets = any(abs(j.p4.Eta())<2.4 and j.p4.Pt()>30 and not isBjet(j) for j in jets)
hasJ30jets = any(j.p4.Pt()>30. for j in jets)
hasJets = hasBjets or hasFjets or hasCLjets
tag4m, probe4m, met4m = r.TLorentzVector(), r.TLorentzVector(), r.TLorentzVector()
tag4m.SetPxPyPzE(tag.px, tag.py, tag.pz, tag.E)
probe4m.SetPxPyPzE(probe.px, probe.py, probe.pz, probe.E)
met4m.SetPxPyPzE(met.px, met.py, met.pz, met.E)
pt = probe4m.Pt()
eta = abs(probe4m.Eta())
mt0 = computeMt(tag4m, met4m)
mt1 = computeMt(probe4m, met4m)
pt0 = tag4m.Pt()
pt1 = probe4m.Pt()
isLowMt = mt1 < 40.0 if region=='hflf' else True # used to reduce the contamination from real (mostly W+jets)
isMuMu = tag.isMu and probe.isMu
passTrigBias = True
probeIsFromPv = fakeu.lepIsFromPv(probe)
if isHflf : passTrigBias = pt0>20.0 and pt1>20.0
elif isConversion : passTrigBias = pt1>20.0
if tag.isMu and isRightProbe and isSameSign : # test 1 : no jet req
# if tag.isMu and isRightProbe and isSameSign and tag4m.Pt()>40.0 : # test 1a : harder tag
# if tag.isMu and isRightProbe and isSameSign and not hasBjets: # test 2 : veto b-jets
# if tag.isMu and isRightProbe and isSameSign and not hasJets: # test 3 : require no jets (cl30, bj, fj)
# if tag.isMu and isRightProbe and isSameSign and not hasJ30jets: # test 4 : require no jets (cl30, bj, fj)
# if tag.isMu and isRightProbe and isSameSign and not hasJets and tag4m.Pt()>40.0: # test 4 : require no jets (cl30, bj, fj)
# --last test-- if tag.isMu and isRightProbe and isSameSign and hasTrigmatch: # test 5 : no jet req, trig match
# if tag.isMu and (isSameSign or isConversion) and isRightProbe and isLowMt and passTrigBias:
# if tag.isMu and isRightProbe and isSameSign and hasTrigmatch and tag4m.Pt()>40.0: # test 6 : try again pt>40
# if tag.isMu and isRightProbe and isSameSign and hasTrigmatch and tag4m.Pt()>40.0 and abs(tag4m.DeltaPhi(probe4m))>2.3: # test 7 pt and deltaPhi
# if tag.isMu and isRightProbe and isSameSign and hasTrigmatch and probeIsFromPv: # test 8 loose only drops iso
# if isMuMu and isRightProbe and isLowMt and passTrigBias: # test emu mumu
# if (isSameSign or isConversion) and isRightProbe and isLowMt: # test sf conversion (not very important for now, 2014-04)
def fillHistosBySource(probe):
leptonSource = enum2source(probe)
def fill(tightOrLoose):
histosPerSource ['mt1' ][leptonSource][tightOrLoose].Fill(mt1, weight)
histosPerSource ['pt1' ][leptonSource][tightOrLoose].Fill(pt, weight)
histosPerSource ['eta1'][leptonSource][tightOrLoose].Fill(eta, weight)
histosThisGroupPerSource['mt1' ][leptonSource][tightOrLoose].Fill(mt1, weight)
histosThisGroupPerSource['pt1' ][leptonSource][tightOrLoose].Fill(pt, weight)
histosThisGroupPerSource['eta1'][leptonSource][tightOrLoose].Fill(eta, weight)
fill('loose')
if isTight : fill('tight')
sourceIsKnown = not isData
if sourceIsKnown : fillHistosBySource(probe)
nLoose, totWeightLoose = nLoose+1, totWeightLoose+weight
if isTight:
nTight, totWeightTight = nTight+1, totWeightTight+weight
histosThisGroup['mt0']['loose'].Fill(mt0, weight)
histosThisGroup['pt0']['loose'].Fill(pt0, weight)
histosThisGroup['mt1']['loose'].Fill(mt1, weight)
def fill(lepType=''):
histosThisGroup['pt1' ][lepType].Fill(pt, weight)
histosThisGroup['eta1'][lepType].Fill(eta, weight)
fill('loose')
if isTight : fill('tight')
if isReal : fill('real_loose')
if isFake : fill('fake_loose')
if isReal and isTight : fill('real_tight')
if isFake and isTight : fill('fake_tight')
if verbose:
counterNames = ['nLoose', 'nTight', 'totWeightLoose', 'totWeightTight']
print ', '.join(["%s : %.1f"%(c, eval(c)) for c in counterNames])
return num_processed_entries
