inputFiles = [r.TFile.Open(f) for f in inputFileNames]
assert len(inputFileNames) == len(
inputFiles), "Cannot open some of the input files"
refHistoType = HistoType(pr='',
ch=channel,
var=referenceHisto,
syst=referenceSyst)
histosByType = collections.defaultdict(list)
classifier = HistoNameClassifier()
for fname, infile in zip(inputFileNames, inputFiles):
samplename = guessSampleFromFilename(fname)
histoNames = [
n for n in getAllHistoNames(infile, onlyTH1=True)
if refHistoType.matchAllAvailabeAttrs(classifier.histoType(n))
]
histos = [infile.Get(hn) for hn in histoNames]
for h in histos:
setHistoType(h, classifier.histoType(h.GetName()))
setHistoSample(h, samplename)
histos = [h for h in histos if h.type.pr in plotRegions]
organizeHistosByType(histosByType, histos)
refHistos = histosByType # already filtered histonames, all histosByType are refHistos
def isSignal(sampleName):
return 'WH_' in sampleName
allSamples = list(
referenceSyst = options.syst
verbose = options.verbose
assert channel in validChannels,"Invalid channel %s (should be one of %s)" % (channel, str(validChannels))
inputFileNames = glob.glob(inputDir+'/'+'*'+prodTag+'*.root') + glob.glob(signalFname)
inputFiles = [r.TFile.Open(f) for f in inputFileNames]
assert len(inputFileNames)==len(inputFiles),"Cannot open some of the input files"
refHistoType = HistoType(pr='', ch=channel, var=referenceHisto, syst=referenceSyst)
histosByType = collections.defaultdict(list)
classifier = HistoNameClassifier()
for fname, infile in zip(inputFileNames, inputFiles) :
samplename = guessSampleFromFilename(fname)
histoNames = [n for n in getAllHistoNames(infile, onlyTH1=True)
if refHistoType.matchAllAvailabeAttrs( classifier.histoType( n ) )]
histos = [infile.Get(hn) for hn in histoNames]
for h in histos :
setHistoType(h, classifier.histoType(h.GetName()))
setHistoSample(h, samplename)
histos = [h for h in histos if h.type.pr in plotRegions]
organizeHistosByType(histosByType, histos)
refHistos = histosByType # already filtered histonames, all histosByType are refHistos
def isSignal(sampleName) : return 'WH_' in sampleName
allSamples = list(set([h.sample for histos in refHistos.values() for h in histos]))
allBkgNames = [s for s in allSamples if not isSignal(s)]
sigName = next(s for s in allSamples if isSignal(s))
if verbose : print '\n'.join("%s : %s" % (s,l) for s,l in zip(['bkg','sig'], [str(allBkgNames), sigName]))
bkgHistosByType, sigHistosByType = dict(), dict()
print 'input files:\n'+'\n'.join(inputFileNames)
inputFiles = [r.TFile.Open(f) for f in inputFileNames]
histosByType = collections.defaultdict(list)
classifier = HistoNameClassifier()
for fname, infile in zip(inputFileNames, inputFiles) :
print '-'*3 + fname + '-'*3
samplename = guessSampleFromFilename(fname)
histoNames = getAllHistoNames(inputFiles[0], onlyTH1=True)
histoNames = [h for h in histoNames if any([h.startswith(p) for p in ['sr6', 'sr7', 'sr8', 'sr9']])]
if justTest : histoNames = histoNames[:10] # just get 10 histos to run quick tests
histos = [infile.Get(hn) for hn in histoNames]
for h in histos :
setHistoType(h, classifier.histoType(h.GetName()))
setHistoSample(h, samplename)
organizeHistosByType(histosByType, histos)
def isSignal(sampleName) : return 'WH_' in sampleName
def cumsum(l, leftToRight=True) :
#return numpy.cumsum(l) # not available ?
return [sum(l[:i]) for i in range(1,len(l)+1)] if leftToRight \
else [sum(l[-i:]) for i in range(1,len(l)+1)][::-1]
def mergeOuter(bc, nOuter=2) : # add over/underflow in the first/last bin
return [sum(bc[:nOuter])] + bc[nOuter:-nOuter] + [sum(bc[-nOuter:])]
def cumSumHisto(histo, leftToRight=True) :
hCs = histo.Clone(histo.GetName()+'_cs')
nBinsX = 1+hCs.GetNbinsX() # TH1 starts from 1 (0 underflow, N+1 overflow)
