def addFile(self, filename) :
sample = guessSampleFromFilename(filename)
mc1, mn1 = self.parDb.mc1Mn1ByReqid(self.reqDb.reqidBySample(sample))
fakeReqid = self.reqidProvider.reqidByMc1Mn1(mc1, mn1)
self.filenamesByReqid[fakeReqid].append(filename)
self.masspointByReqid[fakeReqid].append((mc1, mn1))
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)
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
referenceHisto = options.histo
plotRegions = options.regions.split(',')
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]))
def addFile(self, filename):
sample = guessSampleFromFilename(filename)
mc1, mn1 = self.parDb.mc1Mn1ByReqid(self.reqDb.reqidBySample(sample))
fakeReqid = self.reqidProvider.reqidByMc1Mn1(mc1, mn1)
self.filenamesByReqid[fakeReqid].append(filename)
self.masspointByReqid[fakeReqid].append((mc1, mn1))
