def gen_card(self, file_name, **kwargs):
doDataDriven = kwargs.pop("doDataDriven", True)
# get the plotter
nl = 3
sigMap = getSigMap(nl)
intLumiMap = getIntLumiMap()
mergeDict = getMergeDict(self.period)
channelBackground = getChannelBackgrounds(self.period)
channels, leptons = getChannels(nl)
saves = "%s_%s_%iTeV" % (self.analysis, self.region, self.period)
plotter = Plotter(
self.region,
ntupleDir=self.ntuple_dir,
saveDir=saves,
period=self.period,
rootName="plots_limits_wz",
mergeDict=mergeDict,
scaleFactor=self.scalefactor,
datadriven=True,
)
plotter.initializeBackgroundSamples(
[sigMap[self.period][x] for x in channelBackground[self.region + "datadriven"]]
)
plotter.initializeDataSamples([sigMap[self.period]["data"]])
plotter.setIntLumi(intLumiMap[self.period])
# set expected and observed yields
sources = (
[
x
for x in channelBackground[self.region + "datadriven"]
if x not in ["TT", "T", "DY", "Z", "Zfiltered", "WW"]
]
+ ["datadriven"]
if doDataDriven
else channelBackground[self.region]
)
for bg in sources:
self.log.info("Processing {0}".format(bg))
val, err = plotter.getNumEntries(self.selection, sigMap[self.period][bg], doError=True)
statname = "stat_{0}_{1}".format(bg, file_name.split(".")[0])
staterrs = {bg: err / val + 1.0 if val else 1.0}
if self.doStat:
self.add_systematics(statname, "lnN", **staterrs)
if bg in ["WZ"]:
self.datacard.add_sig(bg, val)
else:
self.datacard.add_bkg(bg, val)
self.log.info("Processing observed")
self.datacard.set_observed(plotter.getDataEntries(self.selection))
# write out the datacard
self.log.info("Saving card to file")
with open("%s/%s" % (self.out_dir, file_name), "w") as outfile:
outfile.write(self.datacard.dump())
def getPlotter(self,analysis,region,runPeriod,mass,runTau,plotName,doFakes):
nl = 3 if analysis=='Hpp3l' or analysis=='WZ' else 4
ntuples = getNtupleDirectory(analysis,region,runPeriod)
saves = '%s_%s_%iTeV' % (analysis,region,runPeriod)
sigMap = getSigMap(nl,mass)
intLumiMap = getIntLumiMap()
mergeDict = getMergeDict(runPeriod)
regionBackground = getChannelBackgrounds(runPeriod)
channels, leptons = getChannels(nl,runTau=runTau)
plotter = Plotter(region,ntupleDir=ntuples,saveDir=saves,period=runPeriod,rootName=plotName,mergeDict=mergeDict,scaleFactor=self.scalefactor)
if not doFakes: plotter.initializeBackgroundSamples([sigMap[runPeriod][x] for x in regionBackground[analysis]])
if runPeriod==8: plotter.initializeDataSamples([sigMap[runPeriod]['data']])
plotter.setIntLumi(intLumiMap[runPeriod])
return plotter
def calculateLeptonSystematic(mass,chanCuts,chanScales,**kwargs):
do4l = kwargs.pop('do4l',False)
analysis = 'Hpp3l'
region = 'Hpp3l'
runPeriod = 8
nl = 3
ntuples = getNtupleDirectory(analysis,region,runPeriod)
saves = '%s_%s_%sTeV' % (analysis,region,runPeriod)
sigMap = getSigMap(4,mass) if do4l else getSigMap(nl,mass)
intLumiMap = getIntLumiMap()
mergeDict = getMergeDict(runPeriod)
regionBackground = {
'Hpp3l' : ['T','TT', 'TTV','W','Z','VVV','WW','ZZ','WZ'],
'Hpp4l' : ['TT','Z','DB']
}
channels, leptons = getChannels(nl)
plotter = Plotter(analysis,ntupleDir=ntuples,saveDir=saves,period=runPeriod,rootName='systematics',mergeDict=mergeDict)
plotter.initializeBackgroundSamples([sigMap[runPeriod][x] for x in regionBackground[analysis]])
plotter.initializeSignalSamples([sigMap[runPeriod]['Sig']])
plotter.initializeDataSamples([sigMap[runPeriod]['data']])
plotter.setIntLumi(intLumiMap[runPeriod])
fullCut = 'finalstate.mass>100 && finalstate.sT>1.1*%f+60. && fabs(z1.mass-%f)>80. && h1.dPhi<%f/600.+1.95' %(mass,ZMASS,mass)
finalSRCut = 'h1.mass>0.9*%f && h1.mass<1.1*%f' %(mass,mass)
totBG = 0
totBG_scaled = 0
for c,s in zip(chanCuts,chanScales):
chanBG = s*plotter.getNumEntries('%s && %s && %s' %(c,fullCut,finalSRCut),plotter.signal[0],scaleup=False)
chanBG_scaled = s*plotter.getNumEntries('%s && %s && %s' %(c,fullCut,finalSRCut),plotter.signal[0],scaleup=True)
totBG += chanBG
totBG_scaled += chanBG_scaled
sigSelSys = (totBG_scaled-totBG)/totBG
return sigSelSys+1
def limit(analysis,region,period,mass,**kwargs):
cut = kwargs.pop('cut','1')
doChannels = kwargs.pop('doChannels',False)
doAlphaTest = kwargs.pop('doAlphaTest',False)
unblind = kwargs.pop('unblind',False)
name = kwargs.pop('name','card')
bp = kwargs.pop('bp','')
directory = kwargs.pop('directory','')
channelScales = kwargs.pop('channelScales',[1.0])
channelCuts = kwargs.pop('channelCuts',['1'])
recoChannels = kwargs.pop('recoChannels',['1'])
genChannels = kwargs.pop('genChannels',['1'])
mode = kwargs.pop('mode','sideband')
scalefactor = kwargs.pop('scalefactor','event.gen_weight*event.pu_weight*event.lep_scale*event.trig_scale')
datacardDir = kwargs.pop('datacardDir','./datacards')
do4l = kwargs.pop('do4l',False)
doBoth = kwargs.pop('doBoth',False)
logging.info("Processing BP %s; mass-point %i; card name %s" % (bp,mass,name))
# get the cut maps for each gen channel
genCutMap = {}
alphaGenCuts = {}
for genChan in genChannels:
genCutMap[genChan] = getChannelCutFlowMap(analysis,genChan,mass=mass)
alphaGenCuts[genChan] = getChannelSidebandSignalRegion(analysis,genChan,mass=mass)
# and the reco channel
recoCutMap = {}
alphaRecoCuts = {}
for recoChan in recoChannels:
recoCutMap[recoChan] = getChannelCutFlowMap(analysis,recoChan,mass=mass)
alphaRecoCuts[recoChan] = getChannelSidebandSignalRegion(analysis,recoChan,mass=mass)
# if we are testing a tau hypothesis, explicitly use a wider mass window and the tau cuts
# otherwise we need to just use reco
if bp in ['et100','mt100','tt100']:
theCutMap = getChannelCutFlowMap(analysis,bp[:2]+bp[:2],mass=mass)
theAlphaCuts = getChannelSidebandSignalRegion(analysis,bp[:2]+bp[:2],mass=mass)
else:
theCutMap = recoCutMap[recoChannels[0]] # only support 1 reco channel at a time
theAlphaCuts = alphaRecoCuts[recoChannels[0]]
fullCut = ' && '.join(theCutMap['cuts'])
# setup sideband stuff
chanCuts = '(' + ' || '.join(channelCuts) + ')' # gen cuts for h++ ORed with the default for BG 'aaa'
sbCut = theAlphaCuts['sbcut']
srCut = theAlphaCuts['srcut']
finalSRCut = theAlphaCuts['srcut']
channels, leptons = getChannels(3 if analysis=='Hpp3l' or analysis=='WZ' else 4)
nl = 3 if analysis in ['Hpp3l', 'WZ'] else 4
sigMap = getSigMap(4,mass) if do4l else getSigMap(nl,mass)
intLumiMap = getIntLumiMap()
# setup for final selection
myCut = cut
sbcut = '%s && %s && %s' %(myCut,sbCut,chanCuts)
srcut = '%s && %s && %s && %s' %(myCut,srCut,fullCut, chanCuts)
base_selections = '%s && %s && %s' %(myCut, srCut, fullCut)
if region=='WZ': srcut = '%s && %s && %s' %(myCut,srCut, chanCuts)
if doAlphaTest:
sbcut = '%s && finalstate.sT<150. && z1.mass<110. && h1.mass<130.' %(chanCuts)
srcut = '%s && finalstate.sT<400. && finalstate.sT>150. && z1.mass<110. && h1.mass<130.' %(chanCuts)
if doAlphaTest: unblind = True
logging.debug('Sideband cut: %s' % sbcut)
logging.debug('Signal region cut: %s' % srcut)
logging.debug('Base cut: %s' % base_selections)
# create the limits object
# base_selections is the cut applied on top of individual channel cuts
# sbcut is the sideband selection for alpha calculation
# srcut is the signal ragion selection for alpha calculation
limits = Limits(analysis,region, period, base_selections, getNtupleDirectory(analysis,region,period),
'%s/%s_%itev_%s/%s/%s' % (datacardDir, analysis, period, region, directory, mass),
channels=['dblh%s' % analysis], lumi=intLumiMap[period],
blinded=not unblind, bgMode=mode, scalefactor=scalefactor,
sbcut=sbcut, srcut=srcut)
signal = sigMap[period]['SigPP'] if do4l or analysis in ['Hpp4l'] else sigMap[period]['SigAP']
if mode=='sideband':
# add groups, signal scales must be list of floats with same length as cuts list in gen card
signame = "hpp%i_PP" % mass if do4l or analysis in ['Hpp4l'] else "hpp%i_AP" % mass
limits.add_group(signame, signal, scale=channelScales, isSignal=True)
if doBoth:
signame_PP = "hpp%i_PP" % mass
signal_PP = sigMap[period]['SigPP']
limits.add_group(signame_PP, signal_PP, scale=channelScales, isSignal=True)
limits.add_group("bg", "bg")
limits.add_group("data", "data_R*", isData=True)
# luminosity systematics, 2.6 % for mc
lumi = {signame: 1.026}
if doBoth: lumi = {signame: 1.026, signame_PP: 1.026}
limits.add_systematics("lumi", "lnN", **lumi)
# lepton systematics, electron and muon separately for mc
chanNames = recoChannels # only one supported for now
scaleMap = calculateChannelLeptonSystematic(mass,chanNames,do4l=do4l,doBoth=doBoth)
eid = {signame: "%0.3f" %scaleMap[chanNames[0]]['e']}
if doBoth: eid = {signame: "%0.3f" %scaleMap[chanNames[0]]['e'], signame_PP: "%0.3f" %scaleMap[chanNames[0]]['e']}
chgid = {signame: "%0.3f" %scaleMap[chanNames[0]]['chg']}
if doBoth: chgid = {signame: "%0.3f" %scaleMap[chanNames[0]]['chg'], signame_PP: "%0.3f" %scaleMap[chanNames[0]]['chg']}
mid = {signame: "%0.3f" %scaleMap[chanNames[0]]['m']}
if doBoth: mid = {signame: "%0.3f" %scaleMap[chanNames[0]]['m'], signame_PP: "%0.3f" %scaleMap[chanNames[0]]['m']}
limits.add_systematics('eid', 'lnN', **eid)
limits.add_systematics('chgid', 'lnN', **chgid)
limits.add_systematics('mid', 'lnN', **mid)
# signal mc uncertainty
sigmc = {signame: 1.15}
if doBoth: sigmc = {signame: 1.15, signame_PP: 1.15}
limits.add_systematics("sig_mc_err", "lnN", **sigmc)
# uncertainty on bg estimation
alpha_str = recoChannels[0] # only one supported for now
alpha_pdf = {'bg': 1.1}
limits.add_systematics("alpha_%s" %alpha_str, "lnN", **alpha_pdf)
# generate the card, passing the cuts to be applied for each gen channel
limits.gen_card("%s.txt" % name, mass=mass, cuts=channelCuts, doAlphaTest=doAlphaTest)
elif mode=='mc':
logging.error('MC needs to be reimplemented')
#add_systematics_mc(limits,mass,signal,name,channelCuts,scale,period,bp,doAlphaTest,do4l)
else:
return 0