if options.signal is None:
signalEstimators = []
isFastSim = False
elif options.signal == "DM":
signalEstimators = [ MCBasedEstimate(name=s.name, sample={channel:s for channel in allChannels}, cacheDir=setup.defaultCacheDir() ) for s in signals_TTDM ]
isFastSim = False
elif options.signal == "T2tt":
signalEstimators = [ MCBasedEstimate(name=s.name, sample={channel:s for channel in allChannels}, cacheDir=setup.defaultCacheDir() ) for s in [T2tt_450_0] ]
isFastSim = True
elif options.signal == "allT2tt":
signalEstimators = [ MCBasedEstimate(name=s.name, sample={channel:s for channel in allChannels}, cacheDir=setup.defaultCacheDir() ) for s in signals_T2tt ]
isFastSim = True
else:
raise Exception("Unknown signal estimator choice")
signalSetup = setup.sysClone(parameters={'useTriggers':False})
def wrapper(args):
r,channel,setup = args
res = estimate.cachedEstimate(r, channel, setup, save=True)
return (estimate.uniqueKey(r, channel, setup), res )
for isSignal, estimators_ in [ [ True, signalEstimators ], [ False, allEstimators ] ]:
for estimate in estimators_:
setup_ = signalSetup if isSignal else setup
if options.skipIfCachefileExists and estimate.cache.cacheFileLoaded:
print "Cache file %s was loaded -> Skipping."%estimate.cache.filename
continue
jobs=[]
for channel in ['MuMu' ,'EE', 'EMu']:
argParser.add_argument("--regions", action='store', default='defaultRegions', nargs='?', choices=["defaultRegions","reducedRegionsA","reducedRegionsB","reducedRegionsAB","reducedRegionsNew"], help="which regions setup?")
argParser.add_argument("--signal", action='store', default='T2tt', nargs='?', choices=["T2tt","DM"], help="which signal to plot?")
argParser.add_argument("--estimateDY", action='store', default='DY', nargs='?', choices=["DY","DY-DD"], help="which DY estimate?")
argParser.add_argument("--estimateTTZ", action='store', default='TTZ', nargs='?', choices=["TTZ","TTZ-DD","TTZ-DD-Top16009"], help="which DY estimate?")
args = argParser.parse_args()
if args.regions == "defaultRegions": regions = defaultRegions
elif args.regions == "reducedRegionsA": regions = reducedRegionsA
elif args.regions == "reducedRegionsB": regions = reducedRegionsB
elif args.regions == "reducedRegionsAB": regions = reducedRegionsAB
elif args.regions == "reducedRegionsNew": regions = reducedRegionsNew
else: raise Exception("Unknown regions setup")
detailedEstimators = constructEstimatorList(['TTJets','other-detailed', args.estimateDY, args.estimateTTZ])
signalSetup = setup.sysClone(parameters={'useTriggers':False})
for estimator in detailedEstimators:
estimator.style = styles.fillStyle( getattr( color, estimator.name.split('-')[0] ) )
from StopsDilepton.samples.cmgTuples_FastSimT2tt_mAODv2_25ns_postProcessed import *
from StopsDilepton.samples.cmgTuples_FullSimTTbarDM_mAODv2_25ns_postProcessed import *
signalEstimators = [ MCBasedEstimate(name=s.name, sample={channel:s for channel in allChannels}, cacheDir=setup.defaultCacheDir() ) for s in ([T2tt_450_0] if args.signal == "T2TT" else [TTbarDMJets_scalar_Mchi1_Mphi100])]
for estimator in signalEstimators:
estimator.style = styles.lineStyle( getattr(color, estimator.name ), width=2 )
estimators = detailedEstimators + signalEstimators
for e in estimators:
e.initCache(setup.defaultCacheDir())
def wrapper(s):
c = cardFileWriter.cardFileWriter()
c.releaseLocation = combineReleaseLocation
cardFileName = os.path.join(limitDir, s.name + '.txt')
if not os.path.exists(cardFileName) or overWrite:
counter = 0
c.reset()
c.addUncertainty('PU', 'lnN')
c.addUncertainty('topPt', 'lnN')
c.addUncertainty('JEC', 'lnN')
c.addUncertainty('JER', 'lnN')
c.addUncertainty('SFb', 'lnN')
c.addUncertainty('SFl', 'lnN')
if fastSim:
c.addUncertainty('SFFS', 'lnN')
c.addUncertainty('leptonSF', 'lnN')
eSignal = MCBasedEstimate(
name=s.name,
sample={channel: s
for channel in allChannels},
cacheDir=setup.defaultCacheDir())
for r in regions[1:]:
for channel in ['MuMu', 'EE', 'EMu']: # for channel in ['all']:
niceName = ' '.join([channel, r.__str__()])
binname = 'Bin' + str(counter)
counter += 1
total_exp_bkg = 0
c.addBin(binname, [e.name for e in estimators], niceName)
for e in estimators:
expected = e.cachedEstimate(r, channel, setup)
total_exp_bkg += expected.val
c.specifyExpectation(binname, e.name, expected.val)
if expected.val > 0:
c.specifyUncertainty(
'PU', binname, e.name,
1 + e.PUSystematic(r, channel, setup).val)
c.specifyUncertainty(
'JEC', binname, e.name,
1 + e.JECSystematic(r, channel, setup).val)
c.specifyUncertainty(
'JER', binname, e.name,
1 + e.JERSystematic(r, channel, setup).val)
c.specifyUncertainty(
'topPt', binname, e.name,
1 + e.topPtSystematic(r, channel, setup).val)
c.specifyUncertainty(
'SFb', binname, e.name,
1 + e.btaggingSFbSystematic(r, channel, setup).val)
c.specifyUncertainty(
'SFl', binname, e.name,
1 + e.btaggingSFlSystematic(r, channel, setup).val)
#MC bkg stat (some condition to neglect the smaller ones?)
uname = 'Stat_' + binname + '_' + e.name
c.addUncertainty(uname, 'lnN')
c.specifyUncertainty('Stat_' + binname + '_' + e.name,
binname, e.name,
1 + expected.sigma / expected.val)
c.specifyObservation(binname, int(total_exp_bkg))
#signal
e = eSignal
if fastSim:
signalSetup = setup.sysClone(
sys={'reweight': ['reweightLeptonFastSimSF']},
parameters={'useTriggers': False})
else:
signalSetup = setup.sysClone(
parameters={'useTriggers': False})
signal = e.cachedEstimate(r, channel, signalSetup)
c.specifyExpectation(binname, 'signal', signal.val)
if signal.val > 0:
c.specifyUncertainty(
'PU', binname, 'signal',
1 + e.PUSystematic(r, channel, signalSetup).val)
c.specifyUncertainty(
'JEC', binname, 'signal',
1 + e.JECSystematic(r, channel, signalSetup).val)
c.specifyUncertainty(
'JER', binname, 'signal',
1 + e.JERSystematic(r, channel, signalSetup).val)
c.specifyUncertainty(
'SFb', binname, 'signal', 1 +
e.btaggingSFbSystematic(r, channel, signalSetup).val)
c.specifyUncertainty(
'SFl', binname, 'signal', 1 +
e.btaggingSFlSystematic(r, channel, signalSetup).val)
if fastSim:
c.specifyUncertainty(
'leptonSF', binname, 'signal', 1 +
e.leptonFSSystematic(r, channel, signalSetup).val)
c.specifyUncertainty(
'SFFS', binname, 'signal',
1 + e.btaggingSFFSSystematic(
r, channel, signalSetup).val)
#signal MC stat added in quadrature with PDF uncertainty: 10% uncorrelated
uname = 'Stat_' + binname + '_signal'
c.addUncertainty(uname, 'lnN')
c.specifyUncertainty(
uname, binname, 'signal',
1 + sqrt(0.1**2 + signal.sigma / signal.val))
if signal.val <= 0.01 and total_exp_bkg <= 0.01 or total_exp_bkg <= 0: # or (total_exp_bkg>300 and signal.val<0.05):
if verbose:
print "Muting bin %s. Total sig: %f, total bkg: %f" % (
binname, signal.val, total_exp_bkg)
c.muted[binname] = True
else:
if verbose:
print "NOT Muting bin %s. Total sig: %f, total bkg: %f" % (
binname, signal.val, total_exp_bkg)
c.addUncertainty('Lumi', 'lnN')
c.specifyFlatUncertainty('Lumi', 1.046)
cardFileName = c.writeToFile(cardFileName)
else:
print "File %s found. Reusing." % cardFileName
if args.signal == "DM": sConfig = s.mChi, s.mPhi, s.type
elif args.signal == "T2tt": sConfig = s.mStop, s.mNeu
if useCache and not overWrite and limitCache.contains(s):
res = limitCache.get(sConfig)
else:
res = c.calcLimit(cardFileName)
limitCache.add(sConfig, res, save=True)
try:
if res:
if args.signal == "DM":
sString = "mChi %i mPhi %i type %i" % sConfig
elif args.signal == "T2tt":
sString = "mStop %i mNeu %i" % sConfig
print "Result: %i obs %5.3f exp %5.3f -1sigma %5.3f +1sigma %5.3f" % (
sString, res['-1.000'], res['0.500'], res['0.160'],
res['0.840'])
except:
print "Something wrong with the limit: %r" % res
return sConfig, res
def wrapper(s):
c = cardFileWriter.cardFileWriter()
c.releaseLocation = combineReleaseLocation
cardFileName = os.path.join(limitDir, s.name + ".txt")
if not os.path.exists(cardFileName) or overWrite:
counter = 0
c.reset()
c.addUncertainty("PU", "lnN")
c.addUncertainty("topPt", "lnN")
c.addUncertainty("JEC", "lnN")
c.addUncertainty("JER", "lnN")
c.addUncertainty("SFb", "lnN")
c.addUncertainty("SFl", "lnN")
if fastSim:
c.addUncertainty("SFFS", "lnN")
c.addUncertainty("leptonSF", "lnN")
eSignal = MCBasedEstimate(
name=s.name, sample={channel: s for channel in allChannels}, cacheDir=setup.defaultCacheDir()
)
for r in regions[1:]:
for channel in ["MuMu", "EE", "EMu"]: # for channel in ['all']:
niceName = " ".join([channel, r.__str__()])
binname = "Bin" + str(counter)
counter += 1
total_exp_bkg = 0
c.addBin(binname, [e.name for e in estimators], niceName)
for e in estimators:
expected = e.cachedEstimate(r, channel, setup)
total_exp_bkg += expected.val
c.specifyExpectation(binname, e.name, expected.val)
if expected.val > 0:
c.specifyUncertainty("PU", binname, e.name, 1 + e.PUSystematic(r, channel, setup).val)
c.specifyUncertainty("JEC", binname, e.name, 1 + e.JECSystematic(r, channel, setup).val)
c.specifyUncertainty("JER", binname, e.name, 1 + e.JERSystematic(r, channel, setup).val)
c.specifyUncertainty("topPt", binname, e.name, 1 + e.topPtSystematic(r, channel, setup).val)
c.specifyUncertainty("SFb", binname, e.name, 1 + e.btaggingSFbSystematic(r, channel, setup).val)
c.specifyUncertainty("SFl", binname, e.name, 1 + e.btaggingSFlSystematic(r, channel, setup).val)
# MC bkg stat (some condition to neglect the smaller ones?)
uname = "Stat_" + binname + "_" + e.name
c.addUncertainty(uname, "lnN")
c.specifyUncertainty(
"Stat_" + binname + "_" + e.name, binname, e.name, 1 + expected.sigma / expected.val
)
c.specifyObservation(binname, int(total_exp_bkg))
# signal
e = eSignal
if fastSim:
signalSetup = setup.sysClone(
sys={"reweight": ["reweightLeptonFastSimSF"]}, parameters={"useTriggers": False}
)
else:
signalSetup = setup.sysClone(parameters={"useTriggers": False})
signal = e.cachedEstimate(r, channel, signalSetup)
c.specifyExpectation(binname, "signal", signal.val)
if signal.val > 0:
c.specifyUncertainty("PU", binname, "signal", 1 + e.PUSystematic(r, channel, signalSetup).val)
c.specifyUncertainty("JEC", binname, "signal", 1 + e.JECSystematic(r, channel, signalSetup).val)
c.specifyUncertainty("JER", binname, "signal", 1 + e.JERSystematic(r, channel, signalSetup).val)
c.specifyUncertainty(
"SFb", binname, "signal", 1 + e.btaggingSFbSystematic(r, channel, signalSetup).val
)
c.specifyUncertainty(
"SFl", binname, "signal", 1 + e.btaggingSFlSystematic(r, channel, signalSetup).val
)
if fastSim:
c.specifyUncertainty(
"leptonSF", binname, "signal", 1 + e.leptonFSSystematic(r, channel, signalSetup).val
)
c.specifyUncertainty(
"SFFS", binname, "signal", 1 + e.btaggingSFFSSystematic(r, channel, signalSetup).val
)
# signal MC stat added in quadrature with PDF uncertainty: 10% uncorrelated
uname = "Stat_" + binname + "_signal"
c.addUncertainty(uname, "lnN")
c.specifyUncertainty(uname, binname, "signal", 1 + sqrt(0.1 ** 2 + signal.sigma / signal.val))
if (
signal.val <= 0.01 and total_exp_bkg <= 0.01 or total_exp_bkg <= 0
): # or (total_exp_bkg>300 and signal.val<0.05):
if verbose:
print "Muting bin %s. Total sig: %f, total bkg: %f" % (binname, signal.val, total_exp_bkg)
c.muted[binname] = True
else:
if verbose:
print "NOT Muting bin %s. Total sig: %f, total bkg: %f" % (binname, signal.val, total_exp_bkg)
c.addUncertainty("Lumi", "lnN")
c.specifyFlatUncertainty("Lumi", 1.046)
cardFileName = c.writeToFile(cardFileName)
else:
print "File %s found. Reusing." % cardFileName
if args.signal == "DM":
sConfig = s.mChi, s.mPhi, s.type
elif args.signal == "T2tt":
sConfig = s.mStop, s.mNeu
if useCache and not overWrite and limitCache.contains(s):
res = limitCache.get(sConfig)
else:
res = c.calcLimit(cardFileName)
limitCache.add(sConfig, res, save=True)
try:
if res:
if args.signal == "DM":
sString = "mChi %i mPhi %i type %i" % sConfig
elif args.signal == "T2tt":
sString = "mStop %i mNeu %i" % sConfig
print "Result: %i obs %5.3f exp %5.3f -1sigma %5.3f +1sigma %5.3f" % (
sString,
res["-1.000"],
res["0.500"],
res["0.160"],
res["0.840"],
)
except:
print "Something wrong with the limit: %r" % res
return sConfig, res
