def filler(event):
event.run, event.lumi, event.evt = reader.evt
if reader.position % 100 == 0:
logger.info("At event %i/%i", reader.position, reader.nEvents)
if args.addReweights:
event.nrw = weightInfo.nid
lhe_weights = reader.products['lhe'].weights()
weights = []
param_points = []
for weight in lhe_weights:
# Store nominal weight (First position!)
if weight.id == 'rwgt_1': event.rw_nominal = weight.wgt
if not weight.id in weightInfo.id: continue
pos = weightInfo.data[weight.id]
event.rw_w[pos] = weight.wgt
weights.append(weight.wgt)
interpreted_weight = interpret_weight(weight.id)
for var in weightInfo.variables:
getattr(event, "rw_" + var)[pos] = interpreted_weight[var]
# weight data for interpolation
if not hyperPoly.initialized:
param_points.append(
tuple(interpreted_weight[var]
for var in weightInfo.variables))
# Initialize
if not hyperPoly.initialized: hyperPoly.initialize(param_points)
coeff = hyperPoly.get_parametrization(weights)
# = HyperPoly(weight_data, args.interpolationOrder)
event.np = hyperPoly.ndof
event.chi2_ndof = hyperPoly.chi2_ndof(coeff, weights)
#logger.debug( "chi2_ndof %f coeff %r", event.chi2_ndof, coeff )
logger.debug("chi2_ndof %f", event.chi2_ndof)
for n in xrange(hyperPoly.ndof):
event.p_C[n] = coeff[n]
# All gen particles
gp = reader.products['gp']
# for searching
search = GenSearch(gp)
# find heavy objects before they decay
tops = map(lambda t: {var: getattr(t, var)()
for var in top_varnames},
filter(lambda p: abs(p.pdgId()) == 6 and search.isLast(p), gp))
tops.sort(key=lambda p: -p['pt'])
fill_vector(event, "top", top_varnames, tops)
gen_Zs = filter(lambda p: abs(p.pdgId()) == 23 and search.isLast(p), gp)
gen_Zs.sort(key=lambda p: -p.pt())
if len(gen_Zs) > 0:
gen_Z = gen_Zs[0]
for var in Z_read_varnames:
setattr(event, "Z_" + var, getattr(gen_Z, var)())
else:
gen_Z = None
if gen_Z is not None:
d1, d2 = gen_Z.daughter(0), gen_Z.daughter(1)
if d1.pdgId() > 0:
lm, lp = d1, d2
else:
lm, lp = d2, d1
event.Z_daughterPdg = lm.pdgId()
event.Z_cosThetaStar = cosThetaStar(gen_Z.mass(), gen_Z.pt(),
gen_Z.eta(), gen_Z.phi(), lm.pt(),
lm.eta(), lm.phi())
gen_Gammas = filter(lambda p: abs(p.pdgId()) == 22 and search.isLast(p),
gp)
gen_Gammas.sort(key=lambda p: -p.pt())
if len(gen_Gammas) > 0:
gen_Gamma = gen_Gammas[0]
for var in gamma_read_varnames:
setattr(event, "gamma_" + var, getattr(gen_Gamma, var)())
else:
gen_Gamma = None
# find all leptons
leptons = [(search.ascend(l), l) for l in filter(
lambda p: abs(p.pdgId()) in [11, 13] and search.isLast(p) and p.pt() >=
0, gp)]
leps = []
for first, last in leptons:
mother_pdgId = first.mother(
0).pdgId() if first.numberOfMothers() > 0 else -1
leps.append({var: getattr(last, var)() for var in lep_varnames})
leps[-1]['motherPdgId'] = mother_pdgId
leps.sort(key=lambda p: -p['pt'])
fill_vector(event, "GenLep", lep_all_varnames, leps)
# MET
event.GenMet_pt = reader.products['genMET'][0].pt()
event.GenMet_phi = reader.products['genMET'][0].phi()
# jets
jets = map(lambda t: {var: getattr(t, var)()
for var in jet_read_varnames},
filter(lambda j: j.pt() > 30, reader.products['genJets']))
# jet/lepton disambiguation
jets = filter(
lambda j: (min([999] + [deltaR2(j, l) for l in leps
if l['pt'] > 10]) > 0.3**2), jets)
# find b's from tops:
b_partons = [
b for b in filter(
lambda p: abs(p.pdgId()) == 5 and p.numberOfMothers() == 1 and abs(
p.mother(0).pdgId()) == 6, gp)
]
for jet in jets:
jet['matchBParton'] = (min([999] + [
deltaR2(jet, {
'eta': b.eta(),
'phi': b.phi()
}) for b in b_partons
]) < 0.2**2)
jets.sort(key=lambda p: -p['pt'])
fill_vector(event, "GenJet", jet_write_varnames, jets)
def filler(event):
event.evt, event.lumi, event.run = reader.evt
if reader.position % 100 == 0:
logger.info("At event %i/%i", reader.position, reader.nEvents)
# All gen particles
gp = reader.products['gp']
# for searching
search = GenSearch(gp)
# find heavy objects before they decay
tops = map(lambda t: {var: getattr(t, var)()
for var in top_varnames},
filter(lambda p: abs(p.pdgId()) == 6 and search.isLast(p), gp))
tops.sort(key=lambda p: -p['pt'])
fill_vector(event, "top", top_varnames, tops)
gen_Zs = filter(lambda p: abs(p.pdgId()) == 23 and search.isLast(p), gp)
gen_Zs.sort(key=lambda p: -p.pt())
if len(gen_Zs) > 0:
gen_Z = gen_Zs[0]
for var in Z_read_varnames:
setattr(event, "Z_" + var, getattr(gen_Z, var)())
else:
gen_Z = None
if gen_Z is not None:
d1, d2 = gen_Z.daughter(0), gen_Z.daughter(1)
if d1.pdgId() > 0:
lm, lp = d1, d2
else:
lm, lp = d2, d1
event.Z_daughterPdg = lm.pdgId()
event.Z_cosThetaStar = cosThetaStar(gen_Z.mass(), gen_Z.pt(),
gen_Z.eta(), gen_Z.phi(), lm.pt(),
lm.eta(), lm.phi())
gen_Gammas = filter(lambda p: abs(p.pdgId()) == 22 and search.isLast(p),
gp)
gen_Gammas.sort(key=lambda p: -p.pt())
if len(gen_Gammas) > 0:
gen_Gamma = gen_Gammas[0]
for var in gamma_read_varnames:
setattr(event, "gamma_" + var, getattr(gen_Gamma, var)())
else:
gen_Gamma = None
# find all leptons
leptons = [(search.ascend(l), l) for l in filter(
lambda p: abs(p.pdgId()) in [11, 13] and search.isLast(p) and p.pt() >=
0, gp)]
leps = []
for first, last in leptons:
mother_pdgId = first.mother(
0).pdgId() if first.numberOfMothers() > 0 else -1
leps.append({var: getattr(last, var)() for var in lep_varnames})
leps[-1]['motherPdgId'] = mother_pdgId
leps.sort(key=lambda p: -p['pt'])
fill_vector(event, "GenLep", lep_all_varnames, leps)
# MET
event.GenMet_pt = reader.products['genMET'][0].pt()
event.GenMet_phi = reader.products['genMET'][0].phi()
# jets
jets = map(lambda t: {var: getattr(t, var)()
for var in jet_read_varnames},
filter(lambda j: j.pt() > 30, reader.products['genJets']))
# jet/lepton disambiguation
jets = filter(
lambda j: (min([999] + [deltaR2(j, l) for l in leps
if l['pt'] > 10]) > 0.3**2), jets)
# find b's from tops:
b_partons = [
b for b in filter(
lambda p: abs(p.pdgId()) == 5 and p.numberOfMothers() == 1 and abs(
p.mother(0).pdgId()) == 6, gp)
]
for jet in jets:
jet['matchBParton'] = (min([999] + [
deltaR2(jet, {
'eta': b.eta(),
'phi': b.phi()
}) for b in b_partons
]) < 0.2**2)
jets.sort(key=lambda p: -p['pt'])
fill_vector(event, "GenJet", jet_write_varnames, jets)
def filler(event):
# shortcut
r = reader.event
if isMC: gPart = getGenPartsAll(r)
# weight
if isMC:
event.weight = lumiScaleFactor * r.genWeight if lumiScaleFactor is not None else 1
elif isData:
event.weight = 1
else:
raise NotImplementedError("isMC %r isData %r " % (isMC, isData))
# lumi lists and vetos
if isData:
#event.vetoPassed = vetoList.passesVeto(r.run, r.lumi, r.evt)
event.jsonPassed = lumiList.contains(r.run, r.lumi)
# store decision to use after filler has been executed
event.jsonPassed_ = event.jsonPassed
if isMC:
event.reweightPU36fb = nTrueInt36fb_puRW(r.nTrueInt)
event.reweightPU36fbDown = nTrueInt36fb_puRWDown(r.nTrueInt)
event.reweightPU36fbUp = nTrueInt36fb_puRWUp(r.nTrueInt)
# top pt reweighting
if isMC and options.doTopPtReweighting:
event.reweightTopPt = topPtReweightingFunc(getTopPtsForReweighting(
r)) / topScaleF if doTopPtReweighting else 1.
# Leptons: Reading LepGood and LepOther and fill new LepGood collection in the output tree
mu_selector = muonSelector(isoVar="relIso04",
barrelIso=0.25,
endcapIso=0.25,
absEtaCut=2.4,
dxy=0.05,
dz=0.1)
ele_selector = eleSelector(isoVar="relIso03",
barrelIso=0.1,
endcapIso=0.1,
absEtaCut=2.5,
dxy=0.05,
dz=0.1,
eleId="M",
noMissingHits=False)
leptons = getGoodAndOtherLeptons(r,
ptCut=10,
mu_selector=mu_selector,
ele_selector=ele_selector)
leptons.sort(key=lambda p: -p['pt'])
# Store leptons
event.nlep = len(leptons)
for iLep, lep in enumerate(leptons):
lep['index'] = iLep # Index wrt to the output collection!
lep['relIso'] = lep["relIso04"] if abs(
lep['pdgId']) == 13 else lep["relIso03"]
for b in lepton_vars_store:
getattr(event, "lep_" + b)[iLep] = lep[b]
# Storing lepton counters
event.nGoodMuons = len(filter(lambda l: abs(l['pdgId']) == 13, leptons))
event.nGoodElectrons = len(filter(lambda l: abs(l['pdgId']) == 11,
leptons))
event.nGoodLeptons = len(leptons)
# Lepton convinience
if options.leptonConvinience:
for i in range(min(4, len(leptons))):
for var in lep_convinience_vars:
setattr(event, "l{n}_{var}".format(n=i + 1, var=var),
leptons[i][var])
# Identify best Z
(event.Z_mass, event.Z_l1_index,
event.Z_l2_index) = closestOSDLMassToMZ(leptons)
nonZ_lepton_indices = [
i for i in range(len(leptons))
if i not in [event.Z_l1_index, event.Z_l2_index]
]
event.nonZ_l1_index = nonZ_lepton_indices[0] if len(
nonZ_lepton_indices) > 0 else -1
event.nonZ_l2_index = nonZ_lepton_indices[1] if len(
nonZ_lepton_indices) > 1 else -1
# Store Z information
if event.Z_mass >= 0:
if leptons[event.Z_l1_index]['pdgId'] * leptons[
event.Z_l2_index]['pdgId'] > 0 or abs(
leptons[event.Z_l1_index]['pdgId']) != abs(
leptons[event.Z_l2_index]['pdgId']):
raise RuntimeError("not a Z! Should never happen")
Z_l1 = ROOT.TLorentzVector()
Z_l1.SetPtEtaPhiM(leptons[event.Z_l1_index]['pt'],
leptons[event.Z_l1_index]['eta'],
leptons[event.Z_l1_index]['phi'], 0)
Z_l2 = ROOT.TLorentzVector()
Z_l2.SetPtEtaPhiM(leptons[event.Z_l2_index]['pt'],
leptons[event.Z_l2_index]['eta'],
leptons[event.Z_l2_index]['phi'], 0)
Z = Z_l1 + Z_l2
event.Z_pt = Z.Pt()
event.Z_eta = Z.Eta()
event.Z_phi = Z.Phi()
event.Z_lldPhi = deltaPhi(leptons[event.Z_l1_index]['phi'],
leptons[event.Z_l2_index]['phi'])
event.Z_lldR = deltaR(leptons[event.Z_l1_index],
leptons[event.Z_l2_index])
## get the information for cos(theta*)
# get the Z and lepton (negative charge) vectors
lm_index = event.Z_l1_index if event.lep_pdgId[
event.Z_l1_index] > 0 else event.Z_l2_index
event.cosThetaStar = cosThetaStar(event.Z_mass, event.Z_pt,
event.Z_eta, event.Z_phi,
event.lep_pt[lm_index],
event.lep_eta[lm_index],
event.lep_phi[lm_index])
# Jets and lepton jet cross-cleaning
allJets = getAllJets(r,
leptons,
ptCut=0,
jetVars=jetVarNames,
absEtaCut=99,
jetCollections=["Jet", "DiscJet"]) #JetId is required
selected_jets, other_jets = [], []
for j in allJets:
if isAnalysisJet(j, ptCut=30, absEtaCut=2.4):
selected_jets.append(j)
else:
other_jets.append(j)
# Don't change analysis jets even if we keep all jets, hence, apply abs eta cut
bJets = filter(
lambda j: isBJet(j, tagger='CSVv2') and abs(j['eta']) <= 2.4,
selected_jets)
bJetsDeepCSV = filter(
lambda j: isBJet(j, tagger='DeepCSV') and abs(j['eta']) <= 2.4,
selected_jets)
nonBJets = filter(
lambda j: not (isBJet(j, tagger='CSVv2') and abs(j['eta']) <= 2.4),
selected_jets)
nonBJetsDeepCSV = filter(
lambda j: not (isBJet(j, tagger='DeepCSV') and abs(j['eta']) <= 2.4),
selected_jets)
# Store jets
event.nJetSelected = len(selected_jets)
jets_stored = allJets
event.njet = len(jets_stored)
for iJet, jet in enumerate(jets_stored):
for b in jetVarNames:
getattr(event, "jet_" + b)[iJet] = jet[b]
# ETmiss
event.met_pt = r.met_pt
event.met_phi = r.met_phi
# Analysis observables
event.ht = sum([j['pt'] for j in selected_jets])
event.metSig = event.met_pt / sqrt(event.ht) if event.ht > 0 else float(
'nan')
event.nBTag = len(bJets)
event.nBTagDeepCSV = len(bJetsDeepCSV)
# Systematics
jets_sys = {}
bjets_sys = {}
nonBjets_sys = {}
metVariants = [''] # default
if options.keepPhotons:
# Keep photons and estimate met including (leading pt) photon
photons = getGoodPhotons(r, ptCut=20, idLevel="loose", isData=isData)
event.nPhotonGood = len(photons)
if event.nPhotonGood > 0:
metVariants += [
'_photonEstimated'
] # do all met calculations also for the photonEstimated variant
event.photon_pt = photons[0]['pt']
event.photon_eta = photons[0]['eta']
event.photon_phi = photons[0]['phi']
event.photon_idCutBased = photons[0]['idCutBased']
if isMC:
genPhoton = getGenPhoton(gPart)
event.photon_genPt = genPhoton[
'pt'] if genPhoton is not None else float('nan')
event.photon_genEta = genPhoton[
'eta'] if genPhoton is not None else float('nan')
event.met_pt_photonEstimated, event.met_phi_photonEstimated = getMetPhotonEstimated(
r.met_pt, r.met_phi, photons[0])
event.metSig_photonEstimated = event.met_pt_photonEstimated / sqrt(
event.ht) if event.ht > 0 else float('nan')
event.photonJetdR = min(
deltaR(photons[0], j)
for j in selected_jets) if len(selected_jets) > 0 else 999
event.photonLepdR = min(
deltaR(photons[0], l)
for l in leptons) if len(leptons) > 0 else 999
if isMC:
event.TTGJetsEventType = getTTGJetsEventType(r)
if addSystematicVariations:
for j in allJets:
j['pt_JECUp'] = j['pt'] / j['corr'] * j['corr_JECUp']
j['pt_JECDown'] = j['pt'] / j['corr'] * j['corr_JECDown']
# JERUp, JERDown, JER
addJERScaling(j)
for var in ['JECUp', 'JECDown', 'JERUp', 'JERDown']:
jets_sys[var] = filter(
lambda j: isAnalysisJet(
j, ptCut=30, absEtaCut=2.4, ptVar='pt_' + var), allJets)
bjets_sys[var] = filter(
lambda j: isBJet(j) and abs(j['eta']) < 2.4, jets_sys[var])
nonBjets_sys[var] = filter(
lambda j: not (isBJet(j) and abs(j['eta']) < 2.4),
jets_sys[var])
setattr(event, "nJetSelected_" + var, len(jets_sys[var]))
setattr(event, "ht_" + var,
sum([j['pt_' + var] for j in jets_sys[var]]))
setattr(event, "nBTag_" + var, len(bjets_sys[var]))
for var in [
'JECUp', 'JECDown', 'JERUp', 'JERDown', 'UnclusteredEnUp',
'UnclusteredEnDown'
]:
for i in metVariants:
# use cmg MET correction values ecept for JER where it is zero. There, propagate jet variations.
if 'JER' in var or 'JECV' in var:
(met_corr_pt, met_corr_phi) = getMetJetCorrected(
getattr(event, "met_pt" + i),
getattr(event, "met_phi" + i), jets_sys[var], var)
else:
(met_corr_pt, met_corr_phi) = getMetCorrected(
r, var,
photons[0] if i.count("photonEstimated") else None)
setattr(event, "met_pt" + i + "_" + var, met_corr_pt)
setattr(event, "met_phi" + i + "_" + var, met_corr_phi)
ht = getattr(event, "ht_" +
var) if 'Unclustered' not in var else event.ht
setattr(
event, "metSig" + i + "_" + var,
getattr(event, "met_pt" + i + "_" + var) /
sqrt(ht) if ht > 0 else float('nan'))
if addSystematicVariations:
# B tagging weights method 1a, first for CSVv2
for j in selected_jets:
btagEff_CSVv2.addBTagEffToJet(j)
#print "CSVv2", selected_jets[0]['beff']['SF'], selected_jets[0]['pt']
for var in btagEff_CSVv2.btagWeightNames:
if var != 'MC':
setattr(
event, 'reweightBTagCSVv2_' + var,
btagEff_CSVv2.getBTagSF_1a(
var, bJets,
filter(lambda j: abs(j['eta']) < 2.4, nonBJets)))
# B tagging weights method 1a, now for DeepCSV
for j in selected_jets:
btagEff_DeepCSV.addBTagEffToJet(j)
#print "DeepCSV", selected_jets[0]['beff']['SF'], selected_jets[0]['pt']
for var in btagEff_DeepCSV.btagWeightNames:
if var != 'MC':
setattr(
event, 'reweightBTagDeepCSV_' + var,
btagEff_DeepCSV.getBTagSF_1a(
var, bJetsDeepCSV,
filter(lambda j: abs(j['eta']) < 2.4,
nonBJetsDeepCSV)))
# gen information on extra leptons
if isMC and not options.skipGenMatching:
genSearch.init(gPart)
# Start with status 1 gen leptons
# gLep = filter( lambda p:abs(p['pdgId']) in [11, 13] and p['status']==1 and p['pt']>10 and abs(p['eta'])<2.5, gPart )
# ... no acceptance cuts
gLep = filter(
lambda p: abs(p['pdgId']) in [11, 13] and p['status'] == 1, gPart)
for l in gLep:
ancestry = [gPart[x]['pdgId'] for x in genSearch.ancestry(l)]
l["n_D"] = sum([ancestry.count(p) for p in D_mesons])
l["n_B"] = sum([ancestry.count(p) for p in B_mesons])
l["n_W"] = sum([ancestry.count(p) for p in [24, -24]])
l["n_t"] = sum([ancestry.count(p) for p in [6, -6]])
l["n_tau"] = sum([ancestry.count(p) for p in [15, -15]])
matched_lep = bestDRMatchInCollection(
l, leptons) #FIXME -> fix all the gen / reco match indices!
if matched_lep:
l["lepGood2MatchIndex"] = matched_lep['index']
else:
l["lepGood2MatchIndex"] = -1
# store genleps
event.nGenLep = len(gLep)
for iLep, lep in enumerate(gLep):
for b in genLepVarNames:
getattr(event, "GenLep_" + b)[iLep] = lep[b]
# gen Z
genZs = filter(
lambda p: (abs(p['pdgId']) == 23 and genSearch.isLast(p)), gPart)
genZs.sort(key=lambda p: -p['pt'])
if len(genZs) > 0:
genZ = genZs[0]
event.genZ_pt = genZ['pt']
event.genZ_mass = genZ['mass']
event.genZ_eta = genZ['eta']
event.genZ_phi = genZ['phi']
lep_m = filter(lambda p: p['pdgId'] in [11, 13, 15],
genSearch.daughters(genZ))
event.genZ_daughter_flavor = max(
[p['pdgId'] for p in genSearch.daughters(genZ)])
if len(lep_m) == 1:
event.genZ_cosThetaStar = cosThetaStar(
event.genZ_mass, event.genZ_pt, event.genZ_eta,
event.genZ_phi, lep_m[0]['pt'], lep_m[0]['eta'],
lep_m[0]['phi'])
def filler(event):
if reader.position % 100 == 0:
logger.info("At event %i/%i", reader.position, reader.nEvents)
event.lumiweight1fb = lumiweight1fb
# read jets
jets = filter(lambda j: isGoodDelphesJet(j), reader.jets())
jets.sort(key=lambda p: -p['pt'])
addIndex(jets)
# make b jets
# for j in jets:
# print j['pt'], j['eta'], j['bTag'], j['bTagPhys'], j['bTagAlgo']
bJets = filter(lambda j: j['bTagPhys'] >= 4, jets)
nonBJets = filter(lambda j: not (j['bTagPhys'] < 4), jets)
bj0, bj1 = (bJets + nonBJets + [None, None])[:2]
fill_vector(event, "bj0", jet_write_varnames, bj0)
fill_vector(event, "bj1", jet_write_varnames, bj1)
event.nBTag = len(bJets)
# read leptons
allLeps = reader.muonsTight() + reader.electrons()
allLeps.sort(key=lambda p: -p['pt'])
leps = filter(isGoodDelphesLepton, allLeps)
# cross-cleaning of reco-objects
# leps = filter( lambda l: (min([999]+[deltaR2(l, j) for j in jets if j['pt']>30]) > 0.3**2 ), leps )
# give index to leptons
addIndex(leps)
# Store
fill_vector_collection(event, "lep", lep_varnames, leps)
fill_vector_collection(event, "jet", jet_varnames, jets)
event.nMuons = len(filter(lambda l: abs(l['pdgId']) == 13, leps))
event.nElectrons = len(filter(lambda l: abs(l['pdgId']) == 11, leps))
# MET
met = reader.met()[0]
event.met_pt = met['pt']
event.met_phi = met['phi']
# search for Z in leptons
(event.Z_mass, Z_l1_index, Z_l2_index) = closestOSDLMassToMZ(leps)
nonZ_indices = [
i for i in range(len(leps)) if i not in [Z_l1_index, Z_l2_index]
]
event.Z_l1_index = leps[Z_l1_index]['index'] if Z_l1_index >= 0 else -1
event.Z_l2_index = leps[Z_l2_index]['index'] if Z_l2_index >= 0 else -1
event.nonZ_l1_index = leps[
nonZ_indices[0]]['index'] if len(nonZ_indices) > 0 else -1
event.nonZ_l2_index = leps[
nonZ_indices[1]]['index'] if len(nonZ_indices) > 1 else -1
# Store Z information
if event.Z_mass >= 0:
if leps[event.Z_l1_index]['pdgId'] * leps[
event.Z_l2_index]['pdgId'] > 0 or abs(
leps[event.Z_l1_index]['pdgId']) != abs(
leps[event.Z_l2_index]['pdgId']):
raise RuntimeError("not a Z! Should not happen")
Z_l1 = ROOT.TLorentzVector()
Z_l1.SetPtEtaPhiM(leps[event.Z_l1_index]['pt'],
leps[event.Z_l1_index]['eta'],
leps[event.Z_l1_index]['phi'], 0)
Z_l2 = ROOT.TLorentzVector()
Z_l2.SetPtEtaPhiM(leps[event.Z_l2_index]['pt'],
leps[event.Z_l2_index]['eta'],
leps[event.Z_l2_index]['phi'], 0)
Z = Z_l1 + Z_l2
event.Z_pt = Z.Pt()
event.Z_eta = Z.Eta()
event.Z_phi = Z.Phi()
event.Z_lldPhi = deltaPhi(leps[event.Z_l1_index]['phi'],
leps[event.Z_l2_index]['phi'])
event.Z_lldR = deltaR(leps[event.Z_l1_index], leps[event.Z_l2_index])
lm_index = event.Z_l1_index if leps[
event.Z_l1_index]['pdgId'] > 0 else event.Z_l2_index
event.Z_cosThetaStar = cosThetaStar(event.Z_mass, event.Z_pt,
event.Z_eta, event.Z_phi,
leps[lm_index]['pt'],
leps[lm_index]['eta'],
leps[lm_index]['phi'])