remainingVars = vars[1:]
cuts = getCutsFromRegions(subRegions, var)
# print "At:", var, "remaining", remainingVars, "looping over",cuts,subRegions, var
for c in reversed(cuts):
# print "Looping", c
listRecursive(remainingVars, subRegions, requiredCuts + [c])
else:
assert len(subRegions) == 1, "Regions not unique!"
r = subRegions[0]
print ", ".join([c['name'] + ":" + str(c['cut']) for c in r['cuts']])
listRecursive()
from StopsDilepton.tools.cardFileWriter import cardFileWriter
c = cardFileWriter.cardFileWriter()
c.defWidth = 20
c.precision = 6
c.unique = False
limit = {}
signals = goodRegions[0]['sigYields'].keys()
for s in reversed(signals):
c.reset()
for i, r in enumerate(goodRegions):
c.addBin('Bin' + str(i), ['bkg'], 'Bin' + str(i))
bkg = r['bkgYield']
sig = r['sigYields'][s]
c.specifyObservation('Bin' + str(i), int(bkg))
c.specifyExpectation('Bin' + str(i), 'bkg', bkg)
c.specifyExpectation('Bin' + str(i), 'signal', sig)
def wrapper(s):
c = cardFileWriter.cardFileWriter()
c.releaseLocation = releaseLocation71XC
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')
c.addUncertainty('SFFS', 'lnN')
c.addUncertainty('leptonSF', 'lnN')
eSignal = MCBasedEstimate(name=s['name'],
sample={channel: s
for channel in allChannels},
cacheDir=setup.defaultCacheDir())
cardFileName = os.path.join(setup.analysisOutputDir, setup.prefix(),
'cardFiles', limitPrefix, s['name'] + '.txt')
if not os.path.exists(cardFileName) or overWrite:
for r in regions:
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 bkgEstimators], niceName)
for e in bkgEstimators:
expected = e.cachedEstimate(r, channel, setup)
total_exp_bkg += expected.val
c.specifyExpectation(binname, e.name, expected.val)
if expected.val > 0:
#PU bkg
c.specifyUncertainty(
'PU', binname, e.name,
1 + e.PUSystematic(r, channel, setup).val)
#JEC bkg
c.specifyUncertainty(
'JEC', binname, e.name,
1 + e.JECSystematic(r, channel, setup).val)
#JER bkg
c.specifyUncertainty(
'JER', binname, e.name,
1 + e.JERSystematic(r, channel, setup).val)
#topPt reweighting
c.specifyUncertainty(
'topPt', binname, e.name,
1 + e.topPtSystematic(r, channel, setup).val)
#b-tagging SF
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)
# assert total_exp_bkg>=0, "Total background is negative. Don't know what to do."
c.specifyObservation(binname, int(total_exp_bkg))
#signal
e = eSignal
signal = e.cachedEstimate(
r, channel,
setup.sysClone({'reweight': ['reweightLeptonFastSimSF']}))
c.specifyExpectation(binname, 'signal', signal.val)
if signal.val > 0:
#PU signal
c.specifyUncertainty(
'PU', binname, 'signal',
1 + e.PUSystematic(r, channel, setup).val)
#JEC signal
c.specifyUncertainty(
'JEC', binname, 'signal',
1 + e.JECSystematic(r, channel, setup).val)
#JER signal
c.specifyUncertainty(
'JER', binname, 'signal',
1 + e.JERSystematic(r, channel, setup).val)
#lepton FastSim SF uncertainty
c.specifyUncertainty(
'leptonSF', binname, 'signal',
1 + e.leptonFSSystematic(r, channel, setup).val)
#b-tagging SF (including FastSim SF)
c.specifyUncertainty(
'SFb', binname, 'signal',
1 + e.btaggingSFbSystematic(r, channel, setup).val)
c.specifyUncertainty(
'SFl', binname, 'signal',
1 + e.btaggingSFlSystematic(r, channel, setup).val)
c.specifyUncertainty(
'SFFS', binname, 'signal',
1 + e.btaggingSFFSSystematic(r, channel, setup).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>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
res = c.calcLimit(cardFileName)
mStop, mNeu = s['mStop'], s['mNeu']
try:
if res:
print "Result: mStop %i mNeu %i obs %5.3f exp %5.3f -1sigma %5.3f +1sigma %5.3f" % (
mStop, mNeu, res['-1.000'], res['0.500'], res['0.160'],
res['0.840'])
except:
print "Something wrong with the limit: %r" % res
return mStop, mNeu, 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
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")
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 bkgEstimators], niceName)
for e in bkgEstimators:
expected = e.cachedEstimate(r, channel, setup)
total_exp_bkg += expected.val
c.specifyExpectation(binname, e.name, expected.val)
if expected.val > 0:
# PU bkg
c.specifyUncertainty("PU", binname, e.name, 1 + e.PUSystematic(r, channel, setup).val)
# JEC bkg
c.specifyUncertainty("JEC", binname, e.name, 1 + e.JECSystematic(r, channel, setup).val)
# JER bkg
c.specifyUncertainty("JER", binname, e.name, 1 + e.JERSystematic(r, channel, setup).val)
# topPt reweighting
c.specifyUncertainty("topPt", binname, e.name, 1 + e.topPtSystematic(r, channel, setup).val)
# b-tagging SF
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
)
# assert total_exp_bkg>=0, "Total background is negative. Don't know what to do."
c.specifyObservation(binname, int(total_exp_bkg))
# signal
e = eSignal
signalSetup = setup.sysClone(
sys={"reweight": ["reweightLeptonFastSimSF"]}, parameters={"useTriggers": False}
)
signal = e.cachedEstimate(r, channel, signalSetup)
c.specifyExpectation(binname, "signal", signal.val)
if signal.val > 0:
# PU signal
c.specifyUncertainty("PU", binname, "signal", 1 + e.PUSystematic(r, channel, signalSetup).val)
# JEC signal
c.specifyUncertainty("JEC", binname, "signal", 1 + e.JECSystematic(r, channel, signalSetup).val)
# JER signal
c.specifyUncertainty("JER", binname, "signal", 1 + e.JERSystematic(r, channel, signalSetup).val)
# lepton FastSim SF uncertainty
c.specifyUncertainty(
"leptonSF", binname, "signal", 1 + e.leptonFSSystematic(r, channel, signalSetup).val
)
# b-tagging SF (including FastSim SF)
c.specifyUncertainty(
"SFb", binname, "signal", 1 + e.btaggingSFbSystematic(r, channel, signalSetup).val
)
c.specifyUncertainty(
"SFl", binname, "signal", 1 + e.btaggingSFlSystematic(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
mStop, mNeu = s.mStop, s.mNeu
if useCache and not overWrite and limitCache.contains((mStop, mNeu)):
res = limitCache.get((mStop, mNeu))
else:
res = c.calcLimit(cardFileName)
try:
if res:
print "Result: mStop %i mNeu %i obs %5.3f exp %5.3f -1sigma %5.3f +1sigma %5.3f" % (
mStop,
mNeu,
res["-1.000"],
res["0.500"],
res["0.160"],
res["0.840"],
)
except:
print "Something wrong with the limit: %r" % res
limitCache.add((mStop, mNeu), res, save=True)
return mStop, mNeu, res
var = vars[0]
remainingVars = vars[1:]
cuts = getCutsFromRegions(subRegions, var)
# print "At:", var, "remaining", remainingVars, "looping over",cuts,subRegions, var
for c in reversed(cuts):
# print "Looping", c
listRecursive(remainingVars, subRegions, requiredCuts+[c])
else:
assert len(subRegions)==1, "Regions not unique!"
r = subRegions[0]
print ", ".join([c['name']+":"+str(c['cut']) for c in r['cuts']])
listRecursive()
from StopsDilepton.tools.cardFileWriter import cardFileWriter
c = cardFileWriter.cardFileWriter()
c.defWidth=20
c.precision=6
c.unique=False
limit={}
signals = goodRegions[0]['sigYields'].keys()
for s in reversed(signals):
c.reset()
for i, r in enumerate(goodRegions):
c.addBin('Bin'+str(i), ['bkg'], 'Bin'+str(i))
bkg = r['bkgYield']
sig = r['sigYields'][s]
c.specifyObservation('Bin'+str(i), int(bkg))
c.specifyExpectation('Bin'+str(i), 'bkg', bkg)
c.specifyExpectation('Bin'+str(i), 'signal', sig)
def wrapper(s):
c = cardFileWriter.cardFileWriter()
c.releaseLocation = releaseLocation71XC
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')
c.addUncertainty('SFFS', 'lnN')
c.addUncertainty('leptonSF', 'lnN')
eSignal = MCBasedEstimate(name=s['name'], sample={channel:s for channel in allChannels}, cacheDir=setup.defaultCacheDir() )
cardFileName = os.path.join(setup.analysisOutputDir, setup.prefix(), 'cardFiles', limitPrefix, s['name']+'.txt')
if not os.path.exists(cardFileName) or overWrite:
for r in regions:
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 bkgEstimators], niceName)
for e in bkgEstimators:
expected = e.cachedEstimate(r, channel, setup)
total_exp_bkg += expected.val
c.specifyExpectation(binname, e.name, expected.val )
if expected.val>0:
#PU bkg
c.specifyUncertainty('PU', binname, e.name, 1 + e.PUSystematic(r, channel, setup).val )
#JEC bkg
c.specifyUncertainty('JEC', binname, e.name, 1 + e.JECSystematic(r, channel, setup).val )
#JER bkg
c.specifyUncertainty('JER', binname, e.name, 1 + e.JERSystematic(r, channel, setup).val )
#topPt reweighting
c.specifyUncertainty('topPt', binname, e.name, 1 + e.topPtSystematic(r, channel, setup).val )
#b-tagging SF
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 )
# assert total_exp_bkg>=0, "Total background is negative. Don't know what to do."
c.specifyObservation(binname, int(total_exp_bkg) )
#signal
e = eSignal
signal = e.cachedEstimate(r, channel, setup.sysClone({'reweight':['reweightLeptonFastSimSF']}))
c.specifyExpectation(binname, 'signal', signal.val )
if signal.val>0:
#PU signal
c.specifyUncertainty('PU', binname, 'signal', 1 + e.PUSystematic(r, channel, setup).val )
#JEC signal
c.specifyUncertainty('JEC', binname, 'signal', 1 + e.JECSystematic(r, channel, setup).val )
#JER signal
c.specifyUncertainty('JER', binname, 'signal', 1 + e.JERSystematic(r, channel, setup).val )
#lepton FastSim SF uncertainty
c.specifyUncertainty('leptonSF', binname, 'signal', 1 + e.leptonFSSystematic(r, channel, setup).val )
#b-tagging SF (including FastSim SF)
c.specifyUncertainty('SFb', binname, 'signal', 1 + e.btaggingSFbSystematic(r, channel, setup).val )
c.specifyUncertainty('SFl', binname, 'signal', 1 + e.btaggingSFlSystematic(r, channel, setup).val )
c.specifyUncertainty('SFFS', binname, 'signal', 1 + e.btaggingSFFSSystematic(r, channel, setup).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>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
res = c.calcLimit(cardFileName)
mStop, mNeu = s['mStop'], s['mNeu']
try:
if res: print "Result: mStop %i mNeu %i obs %5.3f exp %5.3f -1sigma %5.3f +1sigma %5.3f"%(mStop, mNeu, res['-1.000'], res['0.500'], res['0.160'], res['0.840'])
except:
print "Something wrong with the limit: %r"%res
return mStop, mNeu, res
