def uponAcceptance(self, eventVars):
for particle, jet in eventVars[self.key].iteritems():
self.book.fill(utils.deltaR(particle, jet),
"DeltaR",
50,
0.0,
5.0,
title=";#DeltaR (%s);matches / bin" % self.key)
def triggerMatched(self, muon, trigger_object):
if self.triggerMatch:
trig_deltaR = math.pi
for trig_obj in trigger_object:
trig_deltaR = min(trig_deltaR, deltaR(trig_obj, muon))
if trig_deltaR < 0.1:
return True
else:
return False
else:
return True
def update(self, _):
self.value = {}
for particle in self.source[self.sourceKey]:
if self.minPt and particle.PT < self.minPt:
continue
dR = []
for jet in self.source[self.jetKey]:
dr = utils.deltaR(particle, jet)
if self.maxDR and self.maxDR < dr:
continue
dR.append((dr, jet))
if dR:
self.value[particle] = min(dR)[1]
def update(self, _):
self.value = {}
for particle in self.source[self.sourceKey]:
if self.minPt and particle.PT < self.minPt:
continue
dR = []
for jet in self.source[self.jetKey]:
dr = utils.deltaR(particle, jet)
if self.maxDR and self.maxDR < dr:
continue
dR.append((dr, jet))
if dR:
self.value[particle] = min(dR)[1]
def triggerMatched(self, electron, trigger_object):
if self.triggerMatch:
trig_deltaR = math.pi
for trig_obj in trigger_object:
if abs(trig_obj.id) != 11:
continue
trig_deltaR = min(trig_deltaR, deltaR(trig_obj, muon))
if trig_deltaR < 0.3:
return True
else:
return False
else:
return True
def overlap(eta, phi, ecol, drMax):
passed = True
drMin = 777
for e in ecol:
dr = utils.deltaR(eta, phi, e.eta, e.phi)
if (dr < drMin): drMin = dr
if (drMin < drMax):
passed = False
return passed, drMin
def uponAcceptance(self, eventVars):
for particle, jet in eventVars[self.sourceKey].iteritems():
dr = utils.deltaR(particle, jet) if jet else 999.9
if self.maxDR and self.maxDR < dr:
continue
if self.minPt and particle.PT < self.minPt:
continue
if self.maxAbsEta and self.maxAbsEta < abs(particle.Eta):
continue
x = getattr(particle, self.particleVar)
self.book.fill(x, self.tagTitle[0], *self.binsMinMax, title=self.tagTitle[1])
if jet and self.passFunc(particle, jet):
self.book.fill(x, self.probeTitle[0], *self.binsMinMax, title=self.probeTitle[1])
def overlap(eta, phi, ecol, drMax):
passed = True
idxMin = -1
drMin = 777
for eidx, e in enumerate(ecol):
dr = utils.deltaR(eta, phi, e.eta, e.phi)
if (dr < drMin):
idxMin = eidx
drMin = dr
if (drMin < drMax):
passed = False
return passed, drMin, idxMin
def uponAcceptance(self, eventVars):
for particle, jet in eventVars[self.sourceKey].iteritems():
dr = utils.deltaR(particle, jet) if jet else 999.9
if self.maxDR and self.maxDR < dr:
continue
if self.minPt and particle.PT < self.minPt:
continue
if self.maxAbsEta and self.maxAbsEta < abs(particle.Eta):
continue
x = getattr(particle, self.particleVar)
self.book.fill(x,
self.tagTitle[0],
*self.binsMinMax,
title=self.tagTitle[1])
if jet and self.passFunc(particle, jet):
self.book.fill(x,
self.probeTitle[0],
*self.binsMinMax,
title=self.probeTitle[1])
def analyze(self, event):
met = self.metInput(event)
rho = self.rhoInput(event)
jets = self.jetCollection(event)
lowPtJets = self.lowPtJetCollection(event)
genJets = self.genJetCollection(event)
muons = self.muonCollection(event)
electrons = self.electronCollection(event)
for lowPtJet in lowPtJets:
lowPtJet.pt = lowPtJet.rawPt
#dummy values
lowPtJet.rawFactor = 0
lowPtJet.mass = 0
lowPtJet.neEmEF = 0
lowPtJet.chEmEF = 0
def genjet_resolution_matching(jet, genjet):
resolution = self.jerUncertaintyCalculator.getResolution(jet, rho)
return abs(jet.pt - genjet.pt) < (3 * resolution * jet.pt)
genjet_match = matchObjectCollection(jets,
genJets,
dRmax=0.2,
presel=genjet_resolution_matching)
genjet_lowpt_match = matchObjectCollection(
lowPtJets, genJets, dRmax=0.2, presel=genjet_resolution_matching)
genjet_match.update(genjet_lowpt_match)
def metP4(obj):
p4 = ROOT.TLorentzVector()
p4.SetPtEtaPhiM(obj.pt, 0, obj.phi, 0)
return p4
met.uncertainty_p4 = {
'nominal': metP4(met),
'jerUp': metP4(met),
'jerDown': metP4(met)
}
self.jerUncertaintyCalculator.setSeed(event)
for ijet, jet in enumerate(itertools.chain(jets, lowPtJets)):
jet.uncertainty_p4 = {}
genJet = genjet_match[jet]
jerFactor = self.jerUncertaintyCalculator.getFactor(
jet, genJet, rho)
jet.uncertainty_p4['nominal'] = jet.p4() * jerFactor['nominal']
jet.uncertainty_p4['jerUp'] = jet.p4() * jerFactor['up']
jet.uncertainty_p4['jerDown'] = jet.p4() * jerFactor['down']
if self.propagateJER:
leptonP4 = ROOT.TLorentzVector(0, 0, 0, 0)
for muon in muons:
if deltaR(muon, jet) < 0.4:
leptonP4 += muon.p4()
for electron in electrons:
if deltaR(electron, jet) < 0.4:
leptonP4 += electron.p4()
if (jet.uncertainty_p4['nominal'] - leptonP4).Pt(
) > self.unclEnThreshold and (jet.neEmEF + jet.chEmEF) < 0.9:
met.uncertainty_p4['nominal'] -= jet.p4() * (
jerFactor['nominal'] - 1.)
if (jet.uncertainty_p4['jerUp'] - leptonP4).Pt(
) > self.unclEnThreshold and (jet.neEmEF + jet.chEmEF) < 0.9:
met.uncertainty_p4['jerUp'] -= jet.p4() * (
jerFactor['up'] - 1.)
if (jet.uncertainty_p4['jerDown'] - leptonP4).Pt(
) > self.unclEnThreshold and (jet.neEmEF + jet.chEmEF) < 0.9:
met.uncertainty_p4['jerDown'] -= jet.p4() * (
jerFactor['down'] - 1.)
for jesUncertaintyName in self.jesUncertaintyNames:
jecDelta = self.jesUncertaintyCaculators[
jesUncertaintyName].getDelta(jet.uncertainty_p4['nominal'])
jet.uncertainty_p4[
'jes' + jesUncertaintyName +
"Up"] = jet.uncertainty_p4['nominal'] * (1. + jecDelta)
jet.uncertainty_p4[
'jes' + jesUncertaintyName +
"Down"] = jet.uncertainty_p4['nominal'] * (1. - jecDelta)
for jesUncertaintyName in self.jesUncertaintyNames:
for mode in ["Up", "Down"]:
if self.propagateJER:
met.uncertainty_p4['jes' + jesUncertaintyName +
mode] = met.uncertainty_p4['nominal']
else:
met.uncertainty_p4['jes' + jesUncertaintyName +
mode] = metP4(met)
for jet in jets:
if jet.uncertainty_p4[
'jes' + jesUncertaintyName +
mode].Pt() > self.unclEnThreshold and (
jet.neEmEF + jet.chEmEF) < 0.9:
met.uncertainty_p4[
'jes' + jesUncertaintyName +
mode] -= jet.uncertainty_p4[
'jes' + jesUncertaintyName +
mode] - jet.uncertainty_p4['nominal']
unclMetDelta = ROOT.TLorentzVector()
unclMetDelta.SetXYZM(met.MetUnclustEnUpDeltaX,
met.MetUnclustEnUpDeltaY, 0, 0)
met.uncertainty_p4[
'unclEnUp'] = met.uncertainty_p4['nominal'] + unclMetDelta
met.uncertainty_p4[
'unclEnDown'] = met.uncertainty_p4['nominal'] - unclMetDelta
setattr(event, self.outputJetPrefix + "nominal",
self.makeNewJetCollection(jets, "nominal"))
setattr(event, self.outputMetPrefix + "nominal",
self.makeNewMetObject(met, "nominal"))
for jesUncertaintyName in self.jesUncertaintyNames:
for mode in ["Up", "Down"]:
setattr(
event,
self.outputJetPrefix + "jes" + jesUncertaintyName + mode,
self.makeNewJetCollection(
jets, "jes" + jesUncertaintyName + mode))
setattr(
event,
self.outputMetPrefix + "jes" + jesUncertaintyName + mode,
self.makeNewMetObject(met,
"jes" + jesUncertaintyName + mode))
for mode in ["Up", "Down"]:
setattr(event, self.outputJetPrefix + "jer" + mode,
self.makeNewJetCollection(jets, "jer" + mode))
setattr(event, self.outputMetPrefix + "jer" + mode,
self.makeNewMetObject(met, "jer" + mode))
setattr(event, self.outputMetPrefix + "unclEn" + mode,
self.makeNewMetObject(met, "unclEn" + mode))
return True
def passFunc(self, particle, jet):
return utils.deltaR(particle, jet) < 0.5
def update(self, _):
objs = self.source[self.key]
assert len(objs) == 2, len(objs)
assert all(objs), objs
self.value = utils.deltaR(*objs)
def process(self, event):
event.getByLabel(self.handles['genParticles'][1],
self.handles['genParticles'][0])
genparticles = self.handles['genParticles'][0].product()
event.getByLabel(self.handles['ak4GenJets'][1],
self.handles['ak4GenJets'][0])
genjets = self.handles['ak4GenJets'][0].product()
# per event weight
event.getByLabel(self.handles['generator'][1],
self.handles['generator'][0])
geninfo = self.handles['generator'][0].product()
weight = geninfo.weight()
try:
# per event weight computed by SusHi
event.getByLabel(self.handles['source'][1],
self.handles['source'][0])
lhesource = self.handles['source'][0].product()
if len(lhesource.weights()):
for w in lhesource.weights():
if w.id == '1009':
weight = w.wgt
except:
pass
#import pdb ; pdb.set_trace()
self.sumOfWeights += weight
gentau = [p for p in genparticles if abs(p.pdgId()) == 15]
genmu = [p for p in genparticles if abs(p.pdgId()) == 13]
genele = [p for p in genparticles if abs(p.pdgId()) == 11]
gennu = [p for p in genparticles if abs(p.pdgId()) in [12, 14, 16]]
genA = [
p for p in genparticles
if abs(p.pdgId()) == 36 and p.status() == 62
]
genZ = [p for p in genparticles if abs(p.pdgId()) == 23]
genh = [p for p in genparticles if abs(p.pdgId()) == 25]
if len(genA) != 1 or \
len(genZ) != 1 or \
len(genh) != 1:
print '\nERROR'
print 'num. of A %d, num. of Z %d, num. of h %d\n' % (
len(genA), len(genZ), len(genh))
import pdb
pdb.set_trace()
return
#raise
fill4vector(genA[0], self.histograms, 'h1_A_mass', weight)
fill4vector(genZ[0], self.histograms, 'h1_Z_mass', weight)
fill4vector(genh[0], self.histograms, 'h1_h_mass', weight)
if not ( (genA[0].daughter(0).pdgId() == 23 and genA[0].daughter(1).pdgId() == 25) or \
(genA[0].daughter(0).pdgId() == 25 and genA[0].daughter(1).pdgId() == 23) ):
print '\nERROR'
print 'A does not decay into Zh!'
print 'daughter pdgId %d, daughter pdgId %d\n' % (
genA[0].daughter(0).pdgId(), genA[0].daughter(1).pdgId())
raise
if abs(genh[0].daughter(0).pdgId()) != 15 or \
abs(genh[0].daughter(1).pdgId()) != 15:
print '\nERROR'
print 'h does not decay into taus!'
print 'leg1 pdgId %d, leg2 pdgId %d\n' % (
genh[0].daughter(0).pdgId(), genh[0].daughter(1).pdgId())
raise
final_state_tau_into_mu_from_h125 = []
final_state_tau_into_ele_from_h125 = []
final_state_tau_into_had_from_h125 = []
for tau in [genh[0].daughter(0), genh[0].daughter(1)]:
type, daughter = tauDecayMode(tau)
if type == 'ele':
final_state_tau_into_mu_from_h125.append(daughter)
elif type == 'muon':
final_state_tau_into_ele_from_h125.append(daughter)
elif type == 'tau':
final_state_tau_into_had_from_h125.append(daughter)
else:
print 'How the hell this tau decays?!'
raise
self.histograms['h1_delta_phi_ll'].Fill(
deltaPhi(genh[0].daughter(0), genh[0].daughter(1)), weight)
self.histograms['h1_delta_eta_ll'].Fill(
abs(genh[0].daughter(0).eta() - genh[0].daughter(1).eta()), weight)
self.histograms['h1_delta_r_ll'].Fill(
deltaR(genh[0].daughter(0), genh[0].daughter(1)), weight)
if len(final_state_tau_into_had_from_h125) == 2:
self.histograms['h1_channel'].Fill('tt', weight)
if final_state_tau_into_had_from_h125[0].pt(
) > final_state_tau_into_had_from_h125[1].pt():
fill4vector(final_state_tau_into_had_from_h125[0],
self.histograms, 'h1_tt_tau1_pt', weight)
fill4vector(final_state_tau_into_had_from_h125[1],
self.histograms, 'h1_tt_tau2_pt', weight)
else:
fill4vector(final_state_tau_into_had_from_h125[0],
self.histograms, 'h1_tt_tau2_pt', weight)
fill4vector(final_state_tau_into_had_from_h125[1],
self.histograms, 'h1_tt_tau1_pt', weight)
elif len(final_state_tau_into_had_from_h125) == 1:
if len(final_state_tau_into_mu_from_h125) == 1:
self.histograms['h1_channel'].Fill('mt', weight)
fill4vector(final_state_tau_into_mu_from_h125[0],
self.histograms, 'h1_mt_mu_pt', weight)
fill4vector(final_state_tau_into_had_from_h125[0],
self.histograms, 'h1_mt_tau_pt', weight)
elif len(final_state_tau_into_ele_from_h125) == 1:
self.histograms['h1_channel'].Fill('et', weight)
fill4vector(final_state_tau_into_ele_from_h125[0],
self.histograms, 'h1_et_ele_pt', weight)
fill4vector(final_state_tau_into_had_from_h125[0],
self.histograms, 'h1_et_tau_pt', weight)
if len(final_state_tau_into_ele_from_h125) == 2:
self.histograms['h1_channel'].Fill('ee', weight)
if final_state_tau_into_ele_from_h125[0].pt(
) > final_state_tau_into_ele_from_h125[1].pt():
fill4vector(final_state_tau_into_ele_from_h125[0],
self.histograms, 'h1_ee_ele1_pt', weight)
fill4vector(final_state_tau_into_ele_from_h125[1],
self.histograms, 'h1_ee_ele2_pt', weight)
else:
fill4vector(final_state_tau_into_ele_from_h125[0],
self.histograms, 'h1_ee_ele2_pt', weight)
fill4vector(final_state_tau_into_ele_from_h125[1],
self.histograms, 'h1_ee_ele1_pt', weight)
if len(final_state_tau_into_mu_from_h125) == 2:
self.histograms['h1_channel'].Fill('mm', weight)
if final_state_tau_into_mu_from_h125[0].pt(
) > final_state_tau_into_mu_from_h125[1].pt():
fill4vector(final_state_tau_into_mu_from_h125[0],
self.histograms, 'h1_mm_mu1_pt', weight)
fill4vector(final_state_tau_into_mu_from_h125[1],
self.histograms, 'h1_mm_mu2_pt', weight)
else:
fill4vector(final_state_tau_into_mu_from_h125[0],
self.histograms, 'h1_mm_mu2_pt', weight)
fill4vector(final_state_tau_into_mu_from_h125[1],
self.histograms, 'h1_mm_mu1_pt', weight)
if len(final_state_tau_into_ele_from_h125) == 1 and \
len(final_state_tau_into_mu_from_h125 ) == 1 :
self.histograms['h1_channel'].Fill('em', weight)
fill4vector(final_state_tau_into_mu_from_h125[0], self.histograms,
'h1_em_mu_pt', weight)
fill4vector(final_state_tau_into_ele_from_h125[0], self.histograms,
'h1_em_ele_pt', weight)
genjetsel = [
jet for jet in genjets if jet.pt() > 30 and abs(jet.eta()) < 5.
]
genjetsel = cleanCollection(genjetsel, gentau + genmu + genele)
self.histograms['h1_njets'].Fill(len(genjetsel), weight)
for i in xrange(min(len(genjetsel), 2)):
fill4vector(genjetsel[i], self.histograms,
'h1_jet{I}_eta'.format(I=str(i + 1)), weight)
if len(genjetsel) >= 2:
self.histograms['h1_delta_phi_jj'].Fill(
deltaPhi(genjetsel[0], genjetsel[1]), weight)
self.histograms['h1_delta_eta_jj'].Fill(
abs(genjetsel[0].eta() - genjetsel[1].eta()), weight)
self.histograms['h1_delta_r_jj'].Fill(
deltaR(genjetsel[0], genjetsel[1]), weight)
# just consider outgoing bquarks, i.e. about to hadronise, status 71
# http://home.thep.lu.se/~torbjorn/pythia81html/ParticleProperties.html
bquarks = [
p for p in genparticles if abs(p.pdgId()) == 5 and p.status() == 71
]
genbjetsel = [
jet for jet in genjets if jet.pt() > 20 and abs(jet.eta()) < 2.4
]
bjets = 0
bjets = cleanCollection(genbjetsel, bquarks, match=True)
self.histograms['h1_nbjets'].Fill(len(bjets), weight)
genmet = gennu[0].p4()
for nu in gennu[1:]:
genmet += nu.p4()
self.histograms['h1_met_pt'].Fill(genmet.pt(), weight)
self.histograms['h1_met_phi'].Fill(genmet.phi(), weight)
genlep_fromZ = [
p for p in genparticles
if p.mother() and abs(p.mother().pdgId()) == 23
]
genlep_fromh = [
p for p in genparticles
if p.mother() and abs(p.mother().pdgId()) == 25
]
if len(genlep_fromZ) != 2 or len(genlep_fromh) != 2:
print 'ERROR'
print 'Z has got %d daughters and h has got %d daughters' % (
len(genlep_fromZ), len(genlep_fromh))
raise
# sum pt
final_state_obj = genjetsel + genlep_fromZ + genlep_fromh
sumPt = final_state_obj[0].pt()
for obj in final_state_obj[1:]:
sumPt += obj.pt()
self.histograms['h1_sumpt'].Fill(sumPt, weight)
def update(self, _):
self.value = []
for j1 in self.source[self.key1]:
for j2 in self.source[self.key2]:
if utils.deltaR(j1, j2) < self.minDR:
self.value.append((j1, j2))
def update(self, _):
self.value = []
for j1 in self.source[self.key1]:
for j2 in self.source[self.key2]:
if utils.deltaR(j1, j2) < self.minDR:
self.value.append((j1, j2))
def analyze(self, event):
"""process event, return True (go to next module) or False (fail, go to next event)"""
electrons = self.inputCollection(event)
muons = Collection(event, "Muon")
triggerObjects = self.triggerObjectCollection(event)
selectedElectrons = []
unselectedElectrons = []
weight_reco_nominal = 1.
weight_reco_up = 1.
weight_reco_down = 1.
weight_id_nominal = 1.
weight_id_up = 1.
weight_id_down = 1.
for electron in electrons:
# https://twiki.cern.ch/twiki/bin/view/CMS/CutBasedElectronIdentificationRun2
if electron.pt>self.electronMinPt \
and math.fabs(electron.eta)<self.electronMaxEta \
and self.electronID(electron)\
and self.triggerMatched(electron, triggerObjects):
dxy = math.fabs(electron.dxy)
dz = math.fabs(electron.dz)
if math.fabs(electron.eta) < 1.479 and (dxy > 0.05
or dz > 0.10):
unselectedElectrons.append(electron)
continue
elif dxy > 0.10 or dz > 0.20:
unselectedElectrons.append(electron)
continue
#reject electron if close-by muon
if len(muons) > 0:
mindr = min(map(lambda muon: deltaR(muon, electron),
muons))
if mindr < 0.05:
unselectedElectrons.append(electron)
continue
selectedElectrons.append(electron)
#TODO: electron reco/ID SFs
else:
unselectedElectrons.append(electron)
if not Module.globalOptions["isData"] and self.storeWeights:
self.out.fillBranch(self.outputName + "_weight_reco_nominal",
weight_reco_nominal)
self.out.fillBranch(self.outputName + "_weight_reco_up",
weight_reco_up)
self.out.fillBranch(self.outputName + "_weight_reco_down",
weight_reco_down)
self.out.fillBranch(self.outputName + "_weight_id_nominal",
weight_id_nominal)
self.out.fillBranch(self.outputName + "_weight_id_up",
weight_id_up)
self.out.fillBranch(self.outputName + "_weight_id_down",
weight_id_down)
self.out.fillBranch("n" + self.outputName, len(selectedElectrons))
for variable in self.storeKinematics:
self.out.fillBranch(
self.outputName + "_" + variable,
map(lambda electron: getattr(electron, variable),
selectedElectrons))
setattr(event, self.outputName, selectedElectrons)
setattr(event, self.outputName + "_unselected", unselectedElectrons)
return True
def passFunc(self, particle, jet):
return utils.deltaR(particle, jet) < 0.5
def uponAcceptance(self, eventVars):
for particle, jet in eventVars[self.key].iteritems():
self.book.fill(utils.deltaR(particle, jet), "DeltaR",
50, 0.0, 5.0,
title=";#DeltaR (%s);matches / bin" % self.key)
def analyze(self, event):
"""process event, return True (go to next module) or False (fail, go to next event)"""
jets = self.inputCollection(event)
origJets = Collection(event, "Jet")
if not self.globalOptions["isData"]:
genJets = Collection(event, "GenJet")
selectedJets = []
unselectedJets = []
if self.flagDA:
flagsDA = [0.] * event.nJet
failedId = 0
for jet in jets:
if jet.pt > self.jetMinPt and jet.pt < self.jetMaxPt\
and math.fabs(jet.eta) < self.jetMaxEta\
and (jet.jetId > self.jetId):
leptons = self.leptonCollection(event)
leptonsToFind = self.leptonFinderCollection(event)
if self.dRCleaning > 0. and leptons is not None and len(
leptons) > 0:
mindr = min(
map(lambda lepton: deltaR(lepton, jet), leptons))
if mindr < self.dRCleaning:
unselectedJets.append(jet)
continue
if self.dRCleaning > 0. and leptonsToFind is not None and len(
leptonsToFind) > 0:
mindr = min(
map(lambda lepton: deltaR(lepton, jet), leptonsToFind))
setattr(jet, "muon_DeltaR", mindr)
selectedJets.append(jet)
else:
unselectedJets.append(jet)
continue
if self.flagDA:
flagsDA[jet._index] = 1.
'''
if not self.globalOptions["isData"]:
if jet.genJetIdx == -1:
selectedJets.append(jet)
continue
elif jet.genJetIdx >= len(genJets):
unselectedJets.append(jet)
continue
else:
genJet = genJets[jet.genJetIdx]
selectedJets.append(jet)
else:
unselectedJets.append(jet)
else:
selectedJets.append(jet)
'''
if self.addSize:
self.out.fillBranch("n" + self.outputName, len(selectedJets))
self.out.fillBranch("nfailedId" + self.outputName, failedId)
if self.flagDA:
self.out.fillBranch(self.outputName + "_forDA", flagsDA)
for variable in self.storeKinematics:
self.out.fillBranch(
self.outputName + "_" + variable,
map(lambda jet: getattr(jet, variable), selectedJets))
setattr(event, self.outputName, selectedJets)
setattr(event, self.outputName + "_unselected", unselectedJets)
return True
def update(self, _):
objs = self.source[self.key]
assert len(objs) == 2, len(objs)
assert all(objs), objs
self.value = utils.deltaR(*objs)
t.phoSubLeadEta[0] = Photons[1].eta
t.phoSubLeadPhi[0] = Photons[1].phi
t.higgsPt[0] = higgs.pt
t.higgsEta[0] = higgs.eta
t.higgsPhi[0] = higgs.phi
if nJetSelected > 0:
t.jet1Pt[0] = Jets[0].pt
t.jet1Eta[0] = Jets[0].eta
t.jet1Phi[0] = Jets[0].phi
t.jet1E[0] = Jets[0].E
t.jet1Btag[0] = Jets[0].btag
t.jet1deltaRLeadPho[0] = ut.deltaR(Jets[0].eta,
Jets[0].phi,
Photons[0].eta,
Photons[0].phi)
t.jet1deltaRSubLeadPho[0] = ut.deltaR(
Jets[0].eta, Jets[0].phi, Photons[1].eta,
Photons[1].phi)
t.jet1deltaRHiggs[0] = ut.deltaR(Jets[0].eta, Jets[0].phi,
higgs.eta, higgs.phi)
if nLepSelected >= 1:
t.jet1deltaRLep[0] = ut.deltaR(Jets[0].eta,
Jets[0].phi,
Leptons[0].eta,
Leptons[0].phi)
if nJetSelected > 1:
t.jet2Pt[0] = Jets[1].pt
