def jetFlavour(self,event):
def isFlavour(x,f):
id = abs(x.pdgId())
if id > 999: return (id/1000)%10 == f
if id > 99: return (id/100)%10 == f
return id % 100 == f
self.bqObjects = [ p for p in event.genParticles if (p.status() == 2 and isFlavour(p,5)) ]
self.cqObjects = [ p for p in event.genParticles if (p.status() == 2 and isFlavour(p,4)) ]
self.partons = [ p for p in event.genParticles if ((p.status() == 23 or p.status() == 3) and abs(p.pdgId())>0 and (abs(p.pdgId()) in [1,2,3,4,5,21]) ) ]
match = matchObjectCollection2(self.cleanJetsAll,
self.partons,
deltaRMax = 0.3)
for jet in self.cleanJetsAll:
parton = match[jet]
jet.partonId = (parton.pdgId() if parton != None else 0)
jet.partonMotherId = (parton.mother(0).pdgId() if parton != None and parton.numberOfMothers()>0 else 0)
for jet in self.jets:
(bmatch, dr) = bestMatch(jet, self.bqObjects)
if dr < 0.4:
jet.mcFlavour = 5
else:
(cmatch, dr) = bestMatch(jet, self.cqObjects)
if dr < 0.4:
jet.mcFlavour = 4
else:
jet.mcFlavour = 0
self.heaviestQCDFlavour = 5 if len(self.bqObjects) else (4 if len(self.cqObjects) else 1);
def isKstLL(b0meson, togenmatchleptons, togenmatchhadrons, flav=13):
# isB0 = (b0meson.pdgId()==511)
# isAntiB0 = (not isB0)
# positive-charged leptons
lps = [ip for ip in b0meson.finaldaughters if ip.pdgId() == -abs(flav)]
# negative-charged leptons
lms = [ip for ip in b0meson.finaldaughters if ip.pdgId() == abs(flav)]
# pions from K*
pis = [ip for ip in b0meson.finaldaughters if abs(ip.pdgId()) == 211]
# kaons from K*
ks = [ip for ip in b0meson.finaldaughters if abs(ip.pdgId()) == 321]
for ilep in lps + lms:
# avoid matching the same particle twice, use the charge to distinguish (charge flip not accounted...)
tomatch = [
jj for jj in togenmatchleptons if jj.charge() == ilep.charge()
]
bm, dr = bestMatch(ilep, tomatch)
if dr < 0.3:
ilep.reco = bm
for ihad in pis + ks:
# avoid matching the same particle twice, use the charge to distinguish (charge flip not accounted...)
tomatch = [
jj for jj in togenmatchhadrons if jj.charge() == ihad.charge()
]
bm, dr = bestMatch(ihad, tomatch)
if dr < 0.3:
ihad.reco = bm
if len(lps) == len(lms) == len(pis) == len(ks) == 1:
return True, lps[0], lms[0], pis[0], ks[0]
else:
return False, None, None, None, None
def jetFlavour(self,event):
def isFlavour(x,f):
id = abs(x.pdgId())
if id > 999: return (id/1000)%10 == f
if id > 99: return (id/100)%10 == f
return id % 100 == f
self.bqObjects = [ p for p in event.genParticles if (p.status() == 2 and isFlavour(p,5)) ]
self.cqObjects = [ p for p in event.genParticles if (p.status() == 2 and isFlavour(p,4)) ]
self.partons = [ p for p in event.genParticles if ((p.status() == 23 or p.status() == 3) and abs(p.pdgId())>0 and (abs(p.pdgId()) in [1,2,3,4,5,21]) ) ]
match = matchObjectCollection2(self.cleanJetsAll,
self.partons,
deltaRMax = 0.3)
for jet in self.cleanJetsAll:
parton = match[jet]
jet.partonId = (parton.pdgId() if parton != None else 0)
jet.partonMotherId = (parton.mother(0).pdgId() if parton != None and parton.numberOfMothers()>0 else 0)
for jet in self.jets:
(bmatch, dr) = bestMatch(jet, self.bqObjects)
if dr < 0.4:
jet.mcFlavour = 5
else:
(cmatch, dr) = bestMatch(jet, self.cqObjects)
if dr < 0.4:
jet.mcFlavour = 4
else:
jet.mcFlavour = 0
self.heaviestQCDFlavour = 5 if len(self.bqObjects) else (4 if len(self.cqObjects) else 1);
def process(self, event):
if event.input.eventAuxiliary().isRealData():
return True
# match the refitted tau to gen tau
tau = event.tau3muRefit.p4Muons()
best_match, dRmin = bestMatch(tau, event.gentaus)
tau_match = best_match if dRmin < 0.3 else None
muons = [
event.tau3muRefit.mu1(),
event.tau3muRefit.mu2(),
event.tau3muRefit.mu3()
]
# now match the three muons:
# first try to match to any stable gen particle
stableGenParticles = [
pp for pp in event.genParticles if pp.status() == 2
]
for mu in muons:
best_match, dRmin = bestMatch(mu, stableGenParticles)
if dRmin < 0.1:
mu.genp = best_match
# then match to tau daughters
# but only if the reco tau is matched to a gen tau itself
if tau_match:
# append the gen tau to the event
event.gentau = tau_match
tau_daughters = list(tau_match.daughterRefVector())
for mu in muons:
best_match, dRmin = bestMatch(mu, tau_daughters)
if dRmin < 0.1:
mu.genp = best_match
# check if the tau comes from a w
tau_genw = [
pp for pp in list(tau_match.motherRefVector())
if abs(pp.pdgId()) == 24
]
if tau_genw:
event.genw = tau_genw[0]
neutrinos = [
pp for pp in event.genParticles if abs(pp.pdgId()) in [12, 14, 16]
]
for i, nn in enumerate(neutrinos):
if i == 0:
event.genmet = nn.p4()
else:
event.genmet += nn.p4()
# import pdb ; pdb.set_trace()
return True
def process(self, event):
self.readCollections(event.input)
event.taus = [Tau(tau) for tau in self.handles['taus'].product()]
event.gen = self.handles['gen'].product()
event.genParticles = event.gen
event.genJets = self.handles['gen_jets'].product()
for pu_info in self.handles['pu'].product():
if pu_info.getBunchCrossing() == 0:
event.n_true_interactions = pu_info.getTrueNumInteractions()
event.genleps = [p for p in event.gen if abs(p.pdgId()) in [11, 13] and p.statusFlags().isPrompt()]
event.gentauleps = [p for p in event.gen if abs(p.pdgId()) in [11, 13] and p.statusFlags().isDirectPromptTauDecayProduct()]
event.gentaus = [p for p in event.gen if abs(p.pdgId()) == 15 and p.statusFlags().isPrompt() and not any(abs(HTTGenAnalyzer.getFinalTau(p).daughter(i_d).pdgId()) in [11, 13] for i_d in xrange(HTTGenAnalyzer.getFinalTau(p).numberOfDaughters()))]
HTTGenAnalyzer.getGenTauJets(event) # saves event.genTauJets
for gen_tau in event.genTauJets:
gen_tau.charged = [d for d in gen_tau.daughters if d.charge()]
gen_tau.pizeros = [daughters(d) for d in gen_tau.daughters if d.pdgId() == 111]
pf_candidates = self.handles['pf_candidates'].product()
for tau in event.taus:
TauIsoAnalyzer.addInfo(tau, event, [c for c in pf_candidates if abs(c.pdgId()) == 211], maxDeltaR=0.8)
matched_gen_jet, dr2 = bestMatch(tau, event.genJets)
if dr2 < 0.25:
tau.gen_jet = matched_gen_jet
return True
def XZZmatchObjectCollection(objects,
matchCollection,
deltaR2Max,
dPtMaxFactor,
filter=lambda x, y: True):
''' @ Apr-6-16 Adds genJets matching for JER according to
https://github.com/cms-sw/cmssw/blob/518995a62433825453d7ccf9ec222d782086cad9/PhysicsTools/PatUtils/interface/SmearedJetProducerT.h
used to produce the sync table:
https://twiki.cern.ch/twiki/bin/view/CMS/JERCReference
'''
pairs = {}
if len(objects) == 0:
return pairs
if len(matchCollection) == 0:
return dict(zip(objects, [None] * len(objects)))
for object in objects:
bm, dr2 = bestMatch(
object, [mob for mob in matchCollection if filter(object, mob)])
dPt = abs(bm.pt() - object.pt())
if dr2 < deltaR2Max and dPt < dPtMaxFactor * object.pt(
) * object.resolution:
pairs[object] = bm
else:
pairs[object] = None
return pairs
def genMatch(self, event, dR=0.3):
dR2 = dR * dR
# match the tau_h leg
# to generated had taus
l1match, dR2best = bestMatch(self.l1, event.gentaus)
if dR2best < dR2:
self.l1.genp = l1match
self.l1.isTauHad = True
# to generated leptons from taus
if not self.l1.isTauHad:
l1match, dR2best = bestMatch(self.l1, self.ptSelGentauleps)
if dR2best < dR2:
self.l1.genp = l1match
self.l1.isTauLep = True
# to generated prompt leptons
elif not self.l1.isTauLep:
l1match, dR2best = bestMatch(self.l1, self.ptSelGenleps)
if dR2best < dR2:
self.l1.genp = l1match
self.l1.isPromptLep = True
# match with any other gen particle
elif not self.l1.isPromptLep:
l1match, dR2best = bestMatch(self.l1, event.genParticles)
if dR2best < dR2:
self.l1.genp = l1match
# match the mu leg
# to generated had taus
l2match, dR2best = bestMatch(self.l2, event.gentaus)
if dR2best < dR2:
self.l2.genp = l2match
self.l2.isTauHad = True
# to generated leptons from taus
if not self.l2.isTauHad:
l2match, dR2best = bestMatch(self.l2, self.ptSelGentauleps)
if dR2best < dR2:
self.l2.genp = l2match
self.l2.isTauLep = True
# to generated prompt leptons
elif not self.l2.isTauLep:
l2match, dR2best = bestMatch(self.l2, self.ptSelGenleps)
if dR2best < dR2:
self.l2.genp = l2match
self.l2.isPromptLep = True
# match with any other gen particle
elif not self.l2.isPromptLep:
l2match, dR2best = bestMatch(self.l2, event.genParticles)
if dR2best < dR2:
self.l2.genp = l2match
def attachJets(self, quad, jets):
# must clean jets from the leptons in the candidate in addition to the ones already cleaned
leptonsAndPhotons = quad.daughterLeptons() + quad.daughterPhotons()
quad.cleanJets = []
quad.cleanJetIndices = []
for ij, j in enumerate(jets):
bm, dr2 = bestMatch(j, leptonsAndPhotons)
if dr2 < 0.4**2:
continue
quad.cleanJets.append(j)
quad.cleanJetIndices.append(ij)
def matchL1TriggerObject(self, to):
l1to, dR2 = bestMatch(to, self.l1tos)
if hasattr(self.cfg_comp, 'channel') and self.cfg_comp.channel == 'tt':
ptcut = 31.9999
else:
ptcut = 0
if dR2 < 0.25 and l1to.Pt() > ptcut:
return True
# for l1to in self.l1tos:
# if deltaR2(to.eta(),to.phi(),l1to.Eta(),l1to.Phi()) < 0.25 and l1to.Pt()>31.9999:# because some come with 31.999999999996 and are passed by KIT
# return True
return False
def single_muon(muons, pt, eta=2.5, qual=8, matches=[], cone=0.3, onlymuons=False, atvtx=True):
cone2 = cone * cone
results = []
for mu in muons:
matched = False
dRmin = 999.
if mu.hwQual() < qual: continue
if mu.pt() < pt : continue
if abs(mu.eta()) > eta : continue
mu_for_matching = mu.clone()
if atvtx:
mu_for_matching.eta = mu.etaAtVtx
mu_for_matching.phi = mu.phiAtVtx
match_index = -99
for ii, imatch in enumerate(matches):
imatch.matched = False
matched = False
if onlymuons:
best_match, dRmin = bestMatch(mu_for_matching, imatch.finalmuondaughters)
else:
best_match, dRmin = bestMatch(mu_for_matching, imatch.finalchargeddaughters)
matched = dRmin<cone2
if matched:
match_index = ii
imatch.matched = True
break
results.append((1, int(matched), match_index))
if len(results)>0:
results.sort(key = lambda x : (x[0], x[1]), reverse=True)
return int(results[0][0]), int(results[0][1]), int(results[0][2])
return 0, 0, -1
def makeVetoLeptons(self, event):
### selected leptons = subset of inclusive leptons passing some basic id definition and pt requirement
### other leptons = subset of inclusive leptons failing some basic id definition and pt requirement
event.vetoLeptons = []
event.vetoMuons = []
event.vetoElectrons = []
#the selected leptons are the ones with the corrections / calibrations applied
# make veto leptons
for mu in event.selectedMuons:
if (mu.pt() > self.cfg_ana.veto_muon_pt
and abs(mu.eta()) < self.cfg_ana.veto_muon_eta
and abs(mu.dxy()) < self.cfg_ana.veto_muon_dxy
and abs(mu.dz()) < self.cfg_ana.veto_muon_dz
and self.muIsoCut(mu)):
mu.vetoIdMonoX = True
event.vetoLeptons.append(mu)
event.vetoMuons.append(mu)
else:
mu.vetoIdMonoX = False
vetoMuons = event.vetoLeptons[:]
for ele in event.selectedElectrons:
if (ele.pt() > self.cfg_ana.veto_electron_pt
and abs(ele.eta()) < self.cfg_ana.veto_electron_eta and
(abs(ele.dxy()) <
(self.cfg_ana.veto_electron_dxy[0] if ele.isEB() else
self.cfg_ana.veto_electron_dxy[1]) and abs(ele.dz()) <
(self.cfg_ana.veto_electron_dz[0] if ele.isEB() else
self.cfg_ana.veto_electron_dxy[1])) and self.eleIsoCut(ele)
and ele.passConversionVeto() and ele.lostInner() <=
(self.cfg_ana.veto_electron_lostHits[0]
if ele.isEB() else self.cfg_ana.veto_electron_lostHits[1])
and (True if getattr(self.cfg_ana, 'notCleaningElectrons',
False) else
(bestMatch(ele, vetoMuons)[1] >
(self.cfg_ana.min_dr_electron_muon**2)))):
event.vetoLeptons.append(ele)
event.vetoElectrons.append(ele)
ele.vetoIdMonoX = True
else:
ele.vetoIdMonoX = False
event.vetoLeptons.sort(key=lambda l: l.pt(), reverse=True)
event.vetoMuons.sort(key=lambda l: l.pt(), reverse=True)
event.vetoElectrons.sort(key=lambda l: l.pt(), reverse=True)
for lepton in event.vetoLeptons:
if hasattr(self, 'efficiency'):
self.efficiency.attachToObject(lepton)
def genMatch(self, event, leg, dR=0.3, matchAll=True):
dR2 = dR * dR
leg.isTauHad = False
leg.isTauLep = False
leg.isPromptLep = False
leg.genp = None
# match the tau_h leg
# to generated had taus
l1match, dR2best = bestMatch(leg, event.gentaus)
if dR2best < dR2:
leg.genp = l1match
leg.isTauHad = True
return
# to generated leptons from taus
l1match, dR2best = bestMatch(leg, self.ptSelGentauleps)
if dR2best < dR2:
leg.genp = l1match
leg.isTauLep = True
return
# to generated prompt leptons
l1match, dR2best = bestMatch(leg, self.ptSelGenleps)
if dR2best < dR2:
leg.genp = l1match
leg.isPromptLep = True
return
# match with any other relevant gen particle
if matchAll:
l1match, dR2best = bestMatch(leg, self.ptSelGenSummary)
if dR2best < dR2:
leg.genp = l1match
def MatchTausToJets(refObjs):
# For each Jet, get the closest RecoTau
Match = {}
for jetidx, refObj in enumerate(refObjs):
tau, _dr2_ = bestMatch(refObj, taus) # dR2=0.25 == dR=0.5
for tauidx, itau in enumerate(taus):
if itau == tau: break
if _dr2_ < 0.25: Match[jetidx] = tauidx
# Is the same Tau assinged to more than one Jet?
DoubleCheck = []
for ijet, itau in Match.iteritems():
for jjet, jtau in Match.iteritems():
if jjet >= ijet: continue
if itau == jtau:
if ijet not in DoubleCheck: DoubleCheck.append(ijet)
if jjet not in DoubleCheck: DoubleCheck.append(jjet)
# Get all distances between all conflicting Jets and corresponding Taus
Distances = {}
for ijet in DoubleCheck:
for jjet in DoubleCheck:
itau = Match[jjet]
Distances[str(ijet) + "_" + str(itau)] = deltaR(
taus[itau].eta(), taus[itau].phi(), refObjs[ijet].eta(),
refObjs[ijet].phi())
#print Distances
# Remove all conflicting Jets, to re-assign later
for ijet in DoubleCheck:
del Match[ijet]
# Assign shortest distance between Tau and Jet, then move on ignoring the already assigned Taus/Jets
while Distances != {}:
keepthis = min(Distances, key=Distances.get)
thisjet = int(keepthis[:keepthis.find("_")])
thistau = int(keepthis[keepthis.rfind("_") + 1:])
Match[thisjet] = thistau
deletethis = []
for element in Distances:
if element.startswith(str(thisjet)) or element.endswith(
str(thistau)):
deletethis.append(element)
for element in deletethis:
del Distances[element]
return Match
def makeVetoLeptons(self, event):
### selected leptons = subset of inclusive leptons passing some basic id definition and pt requirement
### other leptons = subset of inclusive leptons failing some basic id definition and pt requirement
event.vetoLeptons = []
event.vetoMuons = []
event.vetoElectrons = []
#the selected leptons are the ones with the corrections / calibrations applied
# make veto leptons
for mu in event.selectedMuons:
if (mu.pt() > self.cfg_ana.veto_muon_pt and abs(mu.eta()) < self.cfg_ana.veto_muon_eta and
abs(mu.dxy()) < self.cfg_ana.veto_muon_dxy and abs(mu.dz()) < self.cfg_ana.veto_muon_dz and
self.muIsoCut(mu)):
mu.vetoIdMonoX = True
event.vetoLeptons.append(mu)
event.vetoMuons.append(mu)
else:
mu.vetoIdMonoX = False
vetoMuons = event.vetoLeptons[:]
for ele in event.selectedElectrons:
if ( ele.pt() > self.cfg_ana.veto_electron_pt and abs(ele.eta())<self.cfg_ana.veto_electron_eta and
(abs(ele.dxy()) < (self.cfg_ana.veto_electron_dxy[0] if ele.isEB() else self.cfg_ana.veto_electron_dxy[1]) and
abs(ele.dz()) < (self.cfg_ana.veto_electron_dz[0] if ele.isEB() else self.cfg_ana.veto_electron_dxy[1])) and
self.eleIsoCut(ele) and
ele.passConversionVeto() and ele.lostInner() <= (self.cfg_ana.veto_electron_lostHits[0] if ele.isEB() else self.cfg_ana.veto_electron_lostHits[1]) and
( True if getattr(self.cfg_ana,'notCleaningElectrons',False) else (bestMatch(ele, vetoMuons)[1] > (self.cfg_ana.min_dr_electron_muon**2)) )):
event.vetoLeptons.append(ele)
event.vetoElectrons.append(ele)
ele.vetoIdMonoX = True
else:
ele.vetoIdMonoX = False
event.vetoLeptons.sort(key = lambda l : l.pt(), reverse = True)
event.vetoMuons.sort(key = lambda l : l.pt(), reverse = True)
event.vetoElectrons.sort(key = lambda l : l.pt(), reverse = True)
for lepton in event.vetoLeptons:
if hasattr(self,'efficiency'):
self.efficiency.attachToObject(lepton)
def process(self, event):
self.counters.counter('LegTriggerMatcher').inc('all events')
dR2max = getattr(self.cfg_ana, 'dRmax', 0.1)**2
collection = getattr(event, self.cfg_ana.collection)
tomatch = self.cfg_ana.paths_and_filters
for icoll in collection:
if not hasattr(icoll, 'trig_obj'):
icoll.trig_obj = OrderedDict()
for ihlt, ifilter in tomatch.iteritems():
infos = [info for info in event.trigger_infos if ihlt=='_'.join(info.name.split('_')[:-1])]
if len(infos)!=1:
continue
else:
info = infos[0]
objects = info.objects
objects = [obj for obj in objects if obj.filter(ifilter[0]) and obj.triggerObjectTypes()[0]==ifilter[1]]
# temporary collection to save only trig matched objects
tmp_coll = []
for icoll in collection:
icoll.trig_obj[ifilter] = -1
bestmatch, dR2 = bestMatch(icoll, objects)
if dR2 < dR2max:
icoll.trig_obj[ifilter] = bestmatch
tmp_coll.append(icoll)
if getattr(self.cfg_ana, 'filter', False):
setattr(event, self.cfg_ana.collection + '_matched', tmp_coll)
if len(tmp_coll)>0:
self.counters.counter('LegTriggerMatcher').inc('matched events')
#### Fill tree ####
tree.kaonCharged = abs_final_part.count(321)
tree.pionCharged = abs_final_part.count(211)
tree.kaonNeutrals = abs_final_part.count(130)+abs_final_part.count(310)
tree.pionNeutrals = abs_final_part.count(111)
tree.muons = abs_final_part.count(13)
tree.electrons = abs_final_part.count(11)
tree.neutrals = abs_final_part.count(130)+abs_final_part.count(310)+abs_final_part.count(111)+abs_final_part.count(16)+abs_final_part.count(14)+abs_final_part.count(12)
tree.charged = abs_final_part.count(321)+abs_final_part.count(211)+abs_final_part.count(13)+abs_final_part.count(11)
tree.dMeson = dMeson
####### Let's match the jets #######
jets = [jet for jet in recoJets]
matchedJet, _ = bestMatch(maj_neutrinos[0], jets)
#pt eta phi mass btagging discriminator #isolamento
#B tagging discriminator: look for displaced vertexes and traks in a jet
if matchedJet:
tree.pt_Jet = matchedJet.pt()
tree.eta_Jet= matchedJet.eta()
tree.phi_Jet= matchedJet.phi()
tree.mass_Jet= matchedJet.mass()
tree.et_Jet= matchedJet.et()
jet_particles = matchedJet.getPFConstituents()
deposits = [0]*9
for prt in jet_particles:
dr = deltaR(prt, matchedJet)
idx = min(int(floor(dr/0.05)), 8)
def makeLeptons(self, event):
### inclusive leptons = all leptons that could be considered somewhere in the analysis, with minimal requirements (used e.g. to match to MC)
event.inclusiveLeptons = []
### selected leptons = subset of inclusive leptons passing some basic id definition and pt requirement
### other leptons = subset of inclusive leptons failing some basic id definition and pt requirement
event.selectedLeptons = []
event.selectedMuons = []
event.selectedElectrons = []
event.otherLeptons = []
if self.doMiniIsolation:
self.IsolationComputer.setPackedCandidates(self.handles['packedCandidates'].product())
if self.miniIsolationVetoLeptons == "any":
for lep in self.handles['muons'].product():
self.IsolationComputer.addVeto(lep)
for lep in self.handles['electrons'].product():
self.IsolationComputer.addVeto(lep)
#muons
allmuons = self.makeAllMuons(event)
#electrons
allelectrons = self.makeAllElectrons(event)
#make inclusive leptons
inclusiveMuons = []
inclusiveElectrons = []
for mu in allmuons:
if (mu.track().isNonnull() and mu.muonID(self.cfg_ana.inclusive_muon_id) and
mu.pt()>self.cfg_ana.inclusive_muon_pt and abs(mu.eta())<self.cfg_ana.inclusive_muon_eta and
abs(mu.dxy())<self.cfg_ana.inclusive_muon_dxy and abs(mu.dz())<self.cfg_ana.inclusive_muon_dz):
inclusiveMuons.append(mu)
for ele in allelectrons:
if ( ele.electronID(self.cfg_ana.inclusive_electron_id) and
ele.pt()>self.cfg_ana.inclusive_electron_pt and abs(ele.eta())<self.cfg_ana.inclusive_electron_eta and
abs(ele.dxy())<self.cfg_ana.inclusive_electron_dxy and abs(ele.dz())<self.cfg_ana.inclusive_electron_dz and
ele.lostInner()<=self.cfg_ana.inclusive_electron_lostHits ):
inclusiveElectrons.append(ele)
event.inclusiveLeptons = inclusiveMuons + inclusiveElectrons
if self.doMiniIsolation:
if self.miniIsolationVetoLeptons == "inclusive":
for lep in event.inclusiveLeptons:
self.IsolationComputer.addVeto(lep)
for lep in event.inclusiveLeptons:
self.attachMiniIsolation(lep)
# make loose leptons (basic selection)
for mu in inclusiveMuons:
if (mu.muonID(self.cfg_ana.loose_muon_id) and
mu.pt() > self.cfg_ana.loose_muon_pt and abs(mu.eta()) < self.cfg_ana.loose_muon_eta and
abs(mu.dxy()) < self.cfg_ana.loose_muon_dxy and abs(mu.dz()) < self.cfg_ana.loose_muon_dz and
self.muIsoCut(mu)):
mu.looseIdSusy = True
event.selectedLeptons.append(mu)
event.selectedMuons.append(mu)
else:
mu.looseIdSusy = False
event.otherLeptons.append(mu)
looseMuons = event.selectedLeptons[:]
for ele in inclusiveElectrons:
if (ele.electronID(self.cfg_ana.loose_electron_id) and
ele.pt()>self.cfg_ana.loose_electron_pt and abs(ele.eta())<self.cfg_ana.loose_electron_eta and
abs(ele.dxy()) < self.cfg_ana.loose_electron_dxy and abs(ele.dz())<self.cfg_ana.loose_electron_dz and
self.eleIsoCut(ele) and
ele.lostInner() <= self.cfg_ana.loose_electron_lostHits and
( True if getattr(self.cfg_ana,'notCleaningElectrons',False) else (bestMatch(ele, looseMuons)[1] > (self.cfg_ana.min_dr_electron_muon**2)) )):
event.selectedLeptons.append(ele)
event.selectedElectrons.append(ele)
ele.looseIdSusy = True
else:
event.otherLeptons.append(ele)
ele.looseIdSusy = False
event.otherLeptons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedLeptons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedMuons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedElectrons.sort(key = lambda l : l.pt(), reverse = True)
event.inclusiveLeptons.sort(key = lambda l : l.pt(), reverse = True)
for lepton in event.selectedLeptons:
if hasattr(self,'efficiency'):
self.efficiency.attachToObject(lepton)
def genMatch(event, leg, ptSelGentauleps, ptSelGenleps, ptSelGenSummary, dR=0.3, matchAll=True):
dR2 = dR * dR
leg.isTauHad = False
leg.isTauLep = False
leg.isPromptLep = False
leg.genp = None
# match the tau_h leg
# to generated had taus
l1match, dR2best = bestMatch(leg, event.gentaus)
if dR2best < dR2:
leg.genp = l1match
leg.isTauHad = True
return
# to generated leptons from taus
l1match, dR2best = bestMatch(leg, ptSelGentauleps)
if dR2best < dR2:
leg.genp = l1match
leg.isTauLep = True
return
# to generated prompt leptons
l1match, dR2best = bestMatch(leg, ptSelGenleps)
if dR2best < dR2:
leg.genp = l1match
leg.isPromptLep = True
return
# match with any other relevant gen particle
if matchAll:
l1match, dR2best = bestMatch(leg, ptSelGenSummary)
if dR2best < dR2:
leg.genp = l1match
return
# Ok do one more Pythia 8 trick...
# This is to overcome that the GenAnalyzer doesn't like particles
# that have daughters with same pdgId and status 71
if not hasattr(event, "pythiaQuarksGluons"):
event.pythiaQuarksGluons = []
for gen in event.genParticles:
pdg = abs(gen.pdgId())
status = gen.status()
if pdg in [1, 2, 3, 4, 5, 21] and status > 3:
if gen.isMostlyLikePythia6Status3():
event.pythiaQuarksGluons.append(gen)
l1match, dR2best = bestMatch(leg, event.pythiaQuarksGluons)
if dR2best < dR2:
leg.genp = l1match
return
# Now this may be a pileup lepton, or one whose ancestor doesn't
# appear in the gen summary because it's an unclear case in Pythia 8
# To check the latter, match against jets as well...
l1match, dR2best = bestMatch(leg, event.genJets)
# Check if there's a gen jet with pT > 10 GeV (otherwise it's PU)
if dR2best < dR2 and l1match.pt() > 10.0:
leg.genp = PhysicsObject(l1match)
jet, dR2best = bestMatch(l1match, event.jets)
if dR2best < dR2:
leg.genp.detFlavour = jet.partonFlavour()
else:
print "no match found", leg.pt(), leg.eta()
def process(self, event):
self.readCollections(event.input)
self.counters.counter('RecoGenTreeAnalyzer').inc('all events')
# produce collections and map our objects to convenient Heppy objects
event.muons = map(Muon, self.handles['muons'].product())
event.electrons = map(Electron, self.handles['electrons'].product())
event.photons = map(Photon, self.handles['photons'].product())
event.taus = map(Tau, self.handles['taus'].product())
event.jets = map(Jet, self.handles['jets'].product())
event.dsmuons = self.buildDisplacedMuons(
self.handles['dsmuons'].product())
event.dgmuons = self.buildDisplacedMuons(
self.handles['dgmuons'].product())
# vertex stuff
event.pvs = self.handles['pvs'].product()
event.svs = self.handles['svs'].product()
event.beamspot = self.handles['beamspot'].product()
# met
event.met = self.handles['met'].product().at(0)
# assign to the leptons the primary vertex, will be needed to compute a few quantities
# FIXME! understand exactly to which extent it is reasonable to assign the PV to *all* leptons
# regardless whether they're displaced or not
if len(event.pvs):
myvtx = event.pvs[0]
else:
myvtx = event.beamspot
self.assignVtx(event.muons, myvtx)
self.assignVtx(event.electrons, myvtx)
self.assignVtx(event.photons, myvtx)
self.assignVtx(event.taus, myvtx)
# all matchable objects
# matchable = event.electrons + event.photons + event.muons + event.taus + event.dsmuons + event.dgmuons
# matchable = event.electrons + event.photons + event.muons + event.taus + event.dsmuons
# matchable = event.electrons + event.photons + event.taus + event.muons + event.dsmuons + event.dgmuons
matchable = event.electrons + event.photons + event.taus + event.muons
#define the dr to cut on
dr_cut = 0.2
# match gen to reco
for ip in [event.the_hnl.l0(), event.the_hnl.l1(), event.the_hnl.l2()]:
ip.bestmatch = None
ip.bestmatchtype = None
ip.matches = inConeCollection(
ip, matchable, getattr(self.cfg_ana, 'drmax', dr_cut), 0.)
# matches the corresponding "slimmed electron" to the gen particle
if len(event.electrons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.electrons)
if dr2 < dr_cut * dr_cut:
ip.bestelectron = match
# # matches the corresponding "slimmed photon" to the gen particle
# if len(event.photons):
# dr2 = np.inf
# match, dr2 = bestMatch(ip,event.photons)
# if dr2 < dr_cut * dr_cut:
# ip.bestphoton = match
# matches the corresponding "slimmed muon" to the gen particle
if len(event.muons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.muons)
if dr2 < dr_cut * dr_cut:
ip.bestmuon = match
# # matches the corresponding "slimmed tau" to the gen particle
# if len(event.taus):
# dr2 = np.inf
# match, dr2 = bestMatch(ip,event.taus)
# if dr2 < dr_cut * dr_cut:
# ip.besttau = match
# matches the corresponding "displaced stand alone muon" to the gen particle
if len(event.dsmuons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.dsmuons)
if dr2 < dr_cut * dr_cut:
ip.bestdsmuon = match
# matches the corresponding "displaced global muon" to the gen particle
if len(event.dgmuons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.dgmuons)
if dr2 < dr_cut * dr_cut:
ip.bestdgmuon = match
# to find the best match, give precedence to any matched
# particle in the matching cone with the correct PDG ID
# then to the one which is closest
ip.matches.sort(key=lambda x:
(x.pdgId() == ip.pdgId(), -deltaR(x, ip)),
reverse=True)
if len(ip.matches) and abs(ip.pdgId()) == abs(
ip.matches[0].pdgId()):
ip.bestmatch = ip.matches[0]
ip.bestmatchdR = deltaR(ip, ip.bestmatch)
# remove already matched particles, avoid multiple matches to the same candidate while recording the type of reconstruction
matchable.remove(ip.bestmatch)
# record which is which
if ip.bestmatch in event.electrons: ip.bestmatchtype = 11
if ip.bestmatch in event.photons: ip.bestmatchtype = 22
if ip.bestmatch in event.muons: ip.bestmatchtype = 13
if ip.bestmatch in event.taus: ip.bestmatchtype = 15
if ip.bestmatch in event.dsmuons: ip.bestmatchtype = 26
if ip.bestmatch in event.dgmuons: ip.bestmatchtype = 39
else:
ip.bestmatchtype = -1
# clear it before doing it again
event.recoSv = None
# let's refit the secondary vertex, IF both leptons match to some reco particle
pair = [event.the_hnl.l1().bestmatch, event.the_hnl.l2().bestmatch]
if (pair[0] != None) and\
(pair[1] != None) and\
(pair[0].physObj != pair[1].physObj):
event.recoSv = fitVertex(pair)
if event.recoSv:
# primary vertex
pv = event.goodVertices[0]
event.recoSv.disp3DFromBS = ROOT.VertexDistance3D().distance(
event.recoSv, pv)
event.recoSv.disp3DFromBS_sig = event.recoSv.disp3DFromBS.significance(
)
# create an 'ideal' vertex out of the BS
point = ROOT.reco.Vertex.Point(
event.beamspot.position().x(),
event.beamspot.position().y(),
event.beamspot.position().z(),
)
error = event.beamspot.covariance3D()
chi2 = 0.
ndof = 0.
bsvtx = ROOT.reco.Vertex(point, error, chi2, ndof,
2) # size? say 3? does it matter?
event.recoSv.disp2DFromBS = ROOT.VertexDistanceXY().distance(
event.recoSv, bsvtx)
event.recoSv.disp2DFromBS_sig = event.recoSv.disp2DFromBS.significance(
)
event.recoSv.prob = ROOT.TMath.Prob(event.recoSv.chi2(),
int(event.recoSv.ndof()))
dilep_p4 = event.the_hnl.l1().bestmatch.p4(
) + event.the_hnl.l2().bestmatch.p4()
perp = ROOT.math.XYZVector(dilep_p4.px(), dilep_p4.py(), 0.)
dxybs = ROOT.GlobalPoint(
-1 * ((event.beamspot.x0() - event.recoSv.x()) +
(event.recoSv.z() - event.beamspot.z0()) *
event.beamspot.dxdz()),
-1 * ((event.beamspot.y0() - event.recoSv.y()) +
(event.recoSv.z() - event.beamspot.z0()) *
event.beamspot.dydz()), 0)
vperp = ROOT.math.XYZVector(dxybs.x(), dxybs.y(), 0.)
cos = vperp.Dot(perp) / (vperp.R() * perp.R())
event.recoSv.disp2DFromBS_cos = cos
return True
'<ROOT::Math::PtEtaPhiM4D<double> >')()
for idau in xrange(itau.numberOfDaughters()):
if abs(itau.daughter(idau).pdgId()) not in [12, 14, 16]:
itau_vis += itau.daughter(idau).p4()
# gen decay mode
itau.gen_dm = tauDecayModes.genDecayModeInt([
d for d in finalDaughters(itau)
if abs(d.pdgId()) not in [12, 14, 16]
])
# reco tau
reco_tau = None
match = None
dr2 = 1e3
match, dr2 = bestMatch(itau_vis, event.taus)
if dr2 < 0.2 * 0.2:
reco_tau = match
# reco tau
reco_tau_bis = None
match = None
dr2 = 1e3
match, dr2 = bestMatch(itau_vis, event.taus_bis)
if dr2 < 0.2 * 0.2:
reco_tau_bis = match
# identify the primary vertex
event.the_pv = event.the_hn.vertex()
def genMatch(event, leg, ptSelGentauleps, ptSelGenleps, ptSelGenSummary,
dR=0.2, matchAll=True):
dR2 = dR * dR
leg.isTauHad = False
leg.isTauLep = False
leg.isPromptLep = False
leg.genp = None
best_dr2 = dR2
# The following would work for pat::Taus, but we also want to flag a
# muon/electron as coming from a hadronic tau with the usual definition
# if this happens
# if hasattr(leg, 'genJet') and leg.genJet():
# if leg.genJet().pt() > 15.:
# dr2 = deltaR2(leg.eta(), leg.phi(), leg.genJet().eta(), leg.genJet().phi())
# if dr2 < best_dr2:
# best_dr2 = dr2
# leg.genp = leg.genJet()
# leg.genp.setPdgId(-15 * leg.genp.charge())
# leg.isTauHad = True
# RM: needed to append genTauJets to the events,
# when genMatch is used as a static method
if not hasattr(event, 'genTauJets'):
HTTGenAnalyzer.getGenTauJets(event)
l1match, dR2best = bestMatch(leg, event.genTauJets)
if dR2best < best_dr2:
best_dr2 = dR2best
# leg.genp = GenParticle(l1match)
leg.genp = l1match
leg.genp.setPdgId(-15 * leg.genp.charge())
leg.isTauHad = True
# if not leg.genJet():
# print 'Warning, tau does not have matched gen tau'
# elif leg.genJet().pt() < 15.:
# print 'Warning, tau has matched gen jet but with pt =', leg.genJet().pt()
# to generated leptons from taus
l1match, dR2best = bestMatch(leg, ptSelGentauleps)
if dR2best < best_dr2:
best_dr2 = dR2best
leg.genp = l1match
leg.isTauLep = True
leg.isTauHad = False
# to generated prompt leptons
l1match, dR2best = bestMatch(leg, ptSelGenleps)
if dR2best < best_dr2:
best_dr2 = dR2best
leg.genp = l1match
leg.isPromptLep = True
leg.isTauLep = False
leg.isTauHad = False
if best_dr2 < dR2:
return
# match with any other relevant gen particle
if matchAll:
l1match, dR2best = bestMatch(leg, ptSelGenSummary)
if dR2best < best_dr2:
leg.genp = l1match
return
# Ok do one more Pythia 8 trick...
# This is to overcome that the GenAnalyzer doesn't like particles
# that have daughters with same pdgId and status 71
if not hasattr(event, 'pythiaQuarksGluons'):
event.pythiaQuarksGluons = []
for gen in event.genParticles:
pdg = abs(gen.pdgId())
status = gen.status()
if pdg in [1, 2, 3, 4, 5, 21] and status > 3:
if gen.isMostlyLikePythia6Status3():
event.pythiaQuarksGluons.append(gen)
l1match, dR2best = bestMatch(leg, event.pythiaQuarksGluons)
if dR2best < best_dr2:
leg.genp = l1match
return
# Now this may be a pileup lepton, or one whose ancestor doesn't
# appear in the gen summary because it's an unclear case in Pythia 8
# To check the latter, match against jets as well...
l1match, dR2best = bestMatch(leg, getattr(event, 'genJets', []))
# Check if there's a gen jet with pT > 10 GeV (otherwise it's PU)
if dR2best < dR2 and l1match.pt() > 10.:
leg.genp = PhysicsObject(l1match)
jet, dR2best = bestMatch(l1match, event.jets)
if dR2best < dR2:
leg.genp.detFlavour = jet.partonFlavour()
else:
print 'no match found', leg.pt(), leg.eta()
def genMatch(event,
leg,
ptSelGentauleps,
ptSelGenleps,
ptSelGenSummary,
dR=0.2,
matchAll=True):
dR2 = dR * dR
leg.isTauHad = False
leg.isTauLep = False
leg.isPromptLep = False
leg.genp = None
best_dr2 = dR2
# if hasattr(leg, 'genJet') and leg.genJet():
# if leg.genJet().pt() > 15.:
# dr2 = deltaR2(leg.eta(), leg.phi(), leg.genJet().eta(), leg.genJet().phi())
# if dr2 < best_dr2:
# best_dr2 = dr2
# leg.genp = leg.genJet()
# leg.genp.setPdgId(-15 * leg.genp.charge())
# leg.isTauHad = True
l1match, dR2best = bestMatch(leg, event.genTauJets)
if dR2best < best_dr2:
best_dr2 = dR2best
leg.genp = GenParticle(l1match)
leg.genp.setPdgId(-15 * leg.genp.charge())
leg.isTauHad = True
# to generated leptons from taus
l1match, dR2best = bestMatch(leg, ptSelGentauleps)
if dR2best < best_dr2:
best_dr2 = dR2best
leg.genp = l1match
leg.isTauLep = True
leg.isTauHad = False
# to generated prompt leptons
l1match, dR2best = bestMatch(leg, ptSelGenleps)
if dR2best < best_dr2:
best_dr2 = dR2best
leg.genp = l1match
leg.isPromptLep = True
leg.isTauLep = False
leg.isTauHad = False
if best_dr2 < dR2:
return
# match with any other relevant gen particle
if matchAll:
l1match, dR2best = bestMatch(leg, ptSelGenSummary)
if dR2best < best_dr2:
leg.genp = l1match
return
# Ok do one more Pythia 8 trick...
# This is to overcome that the GenAnalyzer doesn't like particles
# that have daughters with same pdgId and status 71
if not hasattr(event, 'pythiaQuarksGluons'):
event.pythiaQuarksGluons = []
for gen in event.genParticles:
pdg = abs(gen.pdgId())
status = gen.status()
if pdg in [1, 2, 3, 4, 5, 21] and status > 3:
if gen.isMostlyLikePythia6Status3():
event.pythiaQuarksGluons.append(gen)
l1match, dR2best = bestMatch(leg, event.pythiaQuarksGluons)
if dR2best < best_dr2:
leg.genp = l1match
return
# Now this may be a pileup lepton, or one whose ancestor doesn't
# appear in the gen summary because it's an unclear case in Pythia 8
# To check the latter, match against jets as well...
l1match, dR2best = bestMatch(leg, event.genJets)
# Check if there's a gen jet with pT > 10 GeV (otherwise it's PU)
if dR2best < dR2 and l1match.pt() > 10.:
leg.genp = PhysicsObject(l1match)
jet, dR2best = bestMatch(l1match, event.jets)
if dR2best < dR2:
leg.genp.detFlavour = jet.partonFlavour()
else:
print 'no match found', leg.pt(), leg.eta()
final_particles_pi0.append(p)
else:
final_particles.append(p)
tree.numbOfDaughters = len(final_particles)
muon_gen = [(x,x.pt()) for x in final_particles if (abs(x.pdgId())==13)]
muon_gen.sort(key=lambda tup: tup[1], reverse=True)
####### Let's match the jets #######
jets = [jet for jet in recoJets if jet.pt() > 20]
#print len(jets)
if len(jets)!=0:
jet_HNL, deltaR_HNL = bestMatch(maj_neutrinos[0], jets)
tree.deltaR_HNL = deltaR_HNL
#tree.jet_HNL_p = jet_HNL.p()
tree.jet_HNL_pt = jet_HNL.pt()
tree.jet_HNL_eta = jet_HNL.eta()
tree.jet_HNL_phi = jet_HNL.phi()
#let's check the fraction of the HNL daughters within a cone of .4 from the jet axes
daughter_deltaR_HNL = []
for part in final_particles:
daughter_deltaR_HNL.append(deltaR(part,jet_HNL))
tree.frac_HNLjet = float(sum(i < 0.4 for i in daughter_deltaR_HNL))/float(len(daughter_deltaR_HNL))
matchJetlist = bestMatchedJet(muon_gen[0][0], jets)
def makeLeptons(self, event):
### inclusive leptons = all leptons that could be considered somewhere in the analysis, with minimal requirements (used e.g. to match to MC)
event.inclusiveLeptons = []
### selected leptons = subset of inclusive leptons passing some basic id definition and pt requirement
### other leptons = subset of inclusive leptons failing some basic id definition and pt requirement
event.selectedLeptons = []
event.selectedMuons = []
event.selectedElectrons = []
event.otherLeptons = []
#muons
allmuons = self.makeAllMuons(event)
for mu in allmuons:
# inclusive, very loose, selection
if (mu.track().isNonnull() and mu.muonID(self.cfg_ana.inclusive_muon_id) and
mu.pt()>self.cfg_ana.inclusive_muon_pt and abs(mu.eta())<self.cfg_ana.inclusive_muon_eta and
abs(mu.dxy())<self.cfg_ana.inclusive_muon_dxy and abs(mu.dz())<self.cfg_ana.inclusive_muon_dz):
event.inclusiveLeptons.append(mu)
# basic selection
if (mu.muonID(self.cfg_ana.loose_muon_id) and
mu.pt() > self.cfg_ana.loose_muon_pt and abs(mu.eta()) < self.cfg_ana.loose_muon_eta and
abs(mu.dxy()) < self.cfg_ana.loose_muon_dxy and abs(mu.dz()) < self.cfg_ana.loose_muon_dz and
mu.relIso03 < self.cfg_ana.loose_muon_relIso and
mu.absIso03 < (self.cfg_ana.loose_muon_absIso if hasattr(self.cfg_ana,'loose_muon_absIso') else 9e99)):
mu.looseIdSusy = True
event.selectedLeptons.append(mu)
event.selectedMuons.append(mu)
else:
mu.looseIdSusy = False
event.otherLeptons.append(mu)
#electrons
allelectrons = self.makeAllElectrons(event)
looseMuons = event.selectedLeptons[:]
for ele in allelectrons:
## remove muons if muForEleCrossCleaning is not empty
## apply selection
if ( ele.electronID(self.cfg_ana.inclusive_electron_id) and
ele.pt()>self.cfg_ana.inclusive_electron_pt and abs(ele.eta())<self.cfg_ana.inclusive_electron_eta and
abs(ele.dxy())<self.cfg_ana.inclusive_electron_dxy and abs(ele.dz())<self.cfg_ana.inclusive_electron_dz and
ele.lostInner()<=self.cfg_ana.inclusive_electron_lostHits ):
event.inclusiveLeptons.append(ele)
# basic selection
if (ele.electronID(self.cfg_ana.loose_electron_id) and
ele.pt()>self.cfg_ana.loose_electron_pt and abs(ele.eta())<self.cfg_ana.loose_electron_eta and
abs(ele.dxy()) < self.cfg_ana.loose_electron_dxy and abs(ele.dz())<self.cfg_ana.loose_electron_dz and
ele.relIso03 <= self.cfg_ana.loose_electron_relIso and
ele.absIso03 < (self.cfg_ana.loose_electron_absIso if hasattr(self.cfg_ana,'loose_electron_absIso') else 9e99) and
ele.lostInner() <= self.cfg_ana.loose_electron_lostHits and
( True if (hasattr(self.cfg_ana,'notCleaningElectrons') and self.cfg_ana.notCleaningElectrons) else (bestMatch(ele, looseMuons)[1] > self.cfg_ana.min_dr_electron_muon) )):
event.selectedLeptons.append(ele)
event.selectedElectrons.append(ele)
ele.looseIdSusy = True
else:
event.otherLeptons.append(ele)
ele.looseIdSusy = False
event.otherLeptons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedLeptons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedMuons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedElectrons.sort(key = lambda l : l.pt(), reverse = True)
event.inclusiveLeptons.sort(key = lambda l : l.pt(), reverse = True)
for lepton in event.selectedLeptons:
if hasattr(self,'efficiency'):
self.efficiency.attachToObject(lepton)
d for d in finalDaughters(refObj)
if abs(d.pdgId()) not in [12, 14, 16]
])
all_var_dict['tau_gendm'].fill(gen_dm)
all_var_dict['tau_gendm_rough'].fill(returnRough(gen_dm))
all_var_dict['tau_genpt'].fill(visP4.pt())
all_var_dict['tau_geneta'].fill(visP4.eta())
all_var_dict['tau_genphi'].fill(visP4.phi())
else:
all_var_dict['tau_gendm'].fill(-1)
all_var_dict['tau_gendm_rough'].fill(-1)
all_var_dict['tau_genpt'].fill(refObj.pt())
all_var_dict['tau_geneta'].fill(refObj.eta())
all_var_dict['tau_genphi'].fill(refObj.phi())
tau, _dr_ = bestMatch(refObj, taus)
if _dr_ > 0.5:
tau = None
tau_vtxTovtx_dz = 99
for i in range(0, len(vertices) - 1):
for j in range(i + 1, len(vertices)):
vtxdz = abs(vertices[i].z() - vertices[j].z())
if vtxdz < tau_vtxTovtx_dz:
tau_vtxTovtx_dz = vtxdz
all_var_dict['tau_vtxTovtx_dz'].fill(tau_vtxTovtx_dz)
# Fill reco-tau variables if it exists...
if tau != None:
all_var_dict['tau_dm'].fill(tau.decayMode())
def process(self, event):
if not self.enable:
self.dummyProcess(event)
return True
self.readCollections( event.input )
pf = self.handles['pf'].product()
leptons = getattr(event,self.leptonTag)
self.IsolationComputer.setPackedCandidates(self.handles['pf'].product())
forIso = []
for ipf,p in enumerate(pf):
if p.pdgId() != 22 or not( p.pt() > 2.0 and abs(p.eta()) < 2.4 ):
continue
if self.cfg_ana.electronVeto != None:
scVetoed = False
for l in leptons:
if abs(l.pdgId())==11 and self.electronID(l):
#print "Testing photon pt %5.1f eta %+7.4f phi %+7.4f vs ele pt %.1f eta %+7.4f phi %+7.4f sc eta %+7.4f phi %+7.4f" % ( p.pt(), p.eta(), p.phi(), l.pt(), l.eta(), l.phi(), l.superCluster().eta(), l.superCluster().phi() )
#print "Testing deta %+7.4f dphi %+7.4f sc deta %+7.4f dphi %+7.4f" % ( abs(p.eta()-l.eta()), deltaPhi(p.phi(),l.phi()), abs(p.eta()-l.superCluster().eta()), deltaPhi(p.phi(),l.superCluster().phi()))
if self.cfg_ana.electronVeto == "superclusterEta":
if (abs(p.eta()-l.superCluster().eta())<0.05 and abs(deltaPhi(p.phi(),l.superCluster().phi()))<2) or deltaR(p.eta(),p.phi(),l.superCluster().eta(),l.superCluster().phi())<0.15:
scVetoed = True; break
elif self.cfg_ana.electronVeto == "electronEta":
if (abs(p.eta()-l.eta())<0.05 and abs(deltaPhi(p.phi(),l.phi()))<2) or deltaR(p.eta(),p.phi(),l.eta(),l.phi())<0.15:
scVetoed = True; break
elif self.cfg_ana.electronVeto == "pfCandReference":
pfcrefs = l.associatedPackedPFCandidates()
for iref in xrange(pfcrefs.size()):
pfcref = pfcrefs[iref]
if pfcref.key() == ipf:
#print "Testing photon pt %5.1f eta %+7.4f phi %+7.4f " % ( p.pt(), p.eta(), p.phi() )
#print " pfcand ref pt %5.1f eta %+7.4f phi %+7.4f " % ( pfcref.get().pt(), pfcref.get().eta(), pfcref.get().phi() )
#print " from elec pt %5.1f eta %+7.4f phi %+7.4f " % ( l.pt(), l.eta(), l.phi() )
scVetoed = True;
else:
raise RuntimeError, "electronVeto option %r not implemented" % self.cfg_ana.electronVeto
if scVetoed: continue
closestLepton, minDR2 = bestMatch(p, leptons)
if minDR2 >= 0.5*0.5: continue
p.globalClosestLepton = closestLepton
forIso.append(p)
isolatedPhotons = []
relIsoCut = self.cfg_ana.relIsoCut
for g in forIso:
g.absIsoCH = self.IsolationComputer.chargedAbsIso(g,0.3,0.0001,0.2)
g.absIsoPU = self.IsolationComputer.puAbsIso(g,0.3,0.0001,0.2)
g.absIsoNH = self.IsolationComputer.neutralHadAbsIsoRaw(g,0.3,0.01,0.5)
g.absIsoPH = self.IsolationComputer.photonAbsIsoRaw(g,0.3,0.01,0.5)
g.relIso = (g.absIsoCH+g.absIsoPU+g.absIsoNH+g.absIsoPH)/g.pt()
if g.relIso < relIsoCut:
isolatedPhotons.append(g)
event.fsrPhotonsNoIso = forIso
event.fsrPhotonsIso = isolatedPhotons
event.attachedFsrPhotons = []
drOverET2Cut = self.cfg_ana.drOverET2Cut
for l in leptons:
best = None
for p in event.fsrPhotonsIso:
if p.globalClosestLepton != l: continue
drOverET2 = deltaR(p.eta(),p.phi(),l.eta(),l.phi())/p.et2()
if drOverET2 >= drOverET2Cut: continue
p.drOverET2 = drOverET2
if best == None or best.drOverET2 > drOverET2:
best = p
if best:
event.attachedFsrPhotons.append(best)
l.ownFsrPhotons = [ best ]
else:
l.ownFsrPhotons = [ ]
#now attach FSR photons to all leptons (for isolation)
for l in leptons:
l.fsrPhotons = inConeCollection(l, event.attachedFsrPhotons, 0.5, -1)
l.relIsoAfterFSR = l.absIsoWithFSR(R=0.3)/l.pt()
#define list of FSR photons attached to photons that pass post-FSR iso, for jet cleaning
event.selectedPhotons = []
for l in leptons:
if l.tightId() and l.relIsoAfterFSR < 0.35:
event.selectedPhotons += l.ownFsrPhotons
return True
def process(self, event):
self.readCollections(event.input)
self.counters.counter('BKstLLGenAnalyzer').inc('all events')
# attach qscale (pt hat) to the event
event.qscale = self.mchandles['genInfo'].product().qScale()
# get the tracks
allpf = map(PhysicsObject, self.handles['pfcands'].product())
losttracks = map(PhysicsObject, self.handles['losttracks'].product())
# merge the track collections
event.alltracks = sorted([
tt for tt in allpf + losttracks
if tt.charge() != 0 and abs(tt.pdgId()) not in (11, 13)
],
key=lambda x: x.pt(),
reverse=True)
# import pdb ; pdb.set_trace()
# get the offline electrons and muons
event.electrons = map(Electron, self.handles['electrons'].product())
event.muons = map(Muon, self.handles['muons'].product())
# find the gen B mesons from the hard scattering
pruned_gen_particles = self.mchandles['prunedGenParticles'].product()
packed_gen_particles = self.mchandles['packedGenParticles'].product()
all_gen_particles = [ip for ip in pruned_gen_particles
] + [ip for ip in packed_gen_particles]
# match gen mu to offline mu
genmus = [
ii for ii in all_gen_particles
if abs(ii.pdgId()) == 13 and ii.status() == 1
]
for imu in genmus:
bm, dr = bestMatch(imu, event.muons)
if dr < 0.3:
imu.reco = bm
if len(genmus) > 0:
event.thetagmu = sorted(genmus, key=lambda x: x.pt(),
reverse=True)[0]
# match gen ele to offline ele
geneles = [
ii for ii in all_gen_particles
if abs(ii.pdgId()) == 11 and ii.status() == 1
]
for iele in geneles:
bm, dr = bestMatch(iele, event.electrons)
if dr < 0.3:
iele.reco = bm
event.gen_bmesons = [
pp for pp in pruned_gen_particles if abs(pp.pdgId()) > 500
and abs(pp.pdgId()) < 600 and pp.isPromptDecayed()
]
event.gen_b0mesons = [
pp for pp in pruned_gen_particles if abs(pp.pdgId()) == 511
]
# walk down the lineage of the B mesons and find the final state muons and charged particles
for ip in event.gen_b0mesons + event.gen_bmesons:
if getattr(self.cfg_ana, 'verbose', False):
print 'PdgId : %s pt : %s eta : %s phi : %s' % (
ip.pdgId(), ip.pt(), ip.eta(), ip.phi())
print ' daughters'
finaldaughters = []
finalcharged = []
finalmuons = []
for ipp in packed_gen_particles:
mother = ipp.mother(0)
if mother and self.isAncestor(ip, mother):
if abs(ipp.pdgId()) == 13:
finalmuons.append(ipp)
if abs(ipp.charge()) == 1:
finalcharged.append(ipp)
if getattr(self.cfg_ana, 'verbose', False):
print ' PdgId : %s pt : %s eta : %s phi : %s' % (
ipp.pdgId(), ipp.pt(), ipp.eta(), ipp.phi())
finaldaughters.append(ipp)
if getattr(self.cfg_ana, 'verbose', False):
print ' PdgId : %s pt : %s eta : %s phi : %s' % (
ipp.pdgId(), ipp.pt(), ipp.eta(), ipp.phi())
ip.finalmuondaughters = sorted(finalmuons,
key=lambda x: x.pt(),
reverse=True)
ip.finalchargeddaughters = sorted(finalcharged,
key=lambda x: x.pt(),
reverse=True)
ip.finaldaughters = sorted(finaldaughters,
key=lambda x: x.pt(),
reverse=True)
for ib0 in event.gen_b0mesons:
if abs(self.cfg_ana.flavour) == 11:
togenmatchleptons = event.electrons
elif abs(self.cfg_ana.flavour) == 13:
togenmatchleptons = event.muons
else:
print 'you can only pick either pdgId 11 or 13'
raise
isit, lp, lm, pi, k = self.isKstLL(ib0, togenmatchleptons,
event.alltracks,
abs(self.cfg_ana.flavour))
if isit:
event.kstll = ib0
event.kstll.lp = lp
event.kstll.lm = lm
event.kstll.pi = pi
event.kstll.k = k
event.kstll.dr = min(
[deltaR(event.kstll, jj) for jj in [lp, lm, pi, k]])
break # yeah, only one at a time, mate!
# if hasattr(event.kstll.lp, 'reco') and hasattr(event.kstll.lm, 'reco'):
# if event.kstll.lp.reco.pt() == event.kstll.lm.reco.pt():
# import pdb ; pdb.set_trace()
if not hasattr(event, 'kstll'):
return False
self.counters.counter('BKstLLGenAnalyzer').inc(
'has a good gen B0->K*LL')
toclean = None
if event.kstll.isPromptDecayed():
toclean = event.kstll
else:
for ip in event.gen_bmesons:
if self.isAncestor(ip, event.kstll):
toclean = ip
break
# if toclean is None:
# print 'nothing to clean lumi %d, ev %d' %(event.lumi, event.eventId)
# return False
# import pdb ; pdb.set_trace()
#
# self.counters.counter('BKstLLGenAnalyzer').inc('no f**k ups')
# elif abs(event.kstll.mother(0).pdgId())>500 and abs(event.kstll.mother(0).pdgId())<600:
# if toclean = event.kstll.mother(0)
# elif abs(event.kstll.mother(0).mother(0).pdgId())>500 and abs(event.kstll.mother(0).mother(0).pdgId())<600:
# else:
# print 'nothing to clean lumi %d, ev %d' %(event.lumi, event.eventId)
# import pdb ; pdb.set_trace()
if toclean is not None:
event.clean_gen_bmesons = [
ib for ib in event.gen_bmesons if ib != toclean
]
else:
event.clean_gen_bmesons = event.gen_bmesons
# import pdb ; pdb.set_trace()
# now find the L1 muons from BX = 0
L1muons_allbx = self.handles['L1muons'].product()
L1_muons = []
for jj in range(L1muons_allbx.size(0)):
L1_muons.append(L1muons_allbx.at(0, jj))
event.L1_muons = L1_muons
event.selectedLeptons = [
] # don't really care about isolated leptons, right?
return True
def process(self, event):
'''
'''
self.readCollections(event.input)
self.tree.reset()
self.event = event
# event variables
self.fillEvent(self.tree, event)
self.fill(self.tree, 'n_cands', len(event.dimuonsvtx))
self.fill(self.tree, 'rho', event.rho)
# reco HNL
self.fillHNL(self.tree, 'hnl', event.the_3lep_cand)
self.fill(self.tree, 'hnl_iso03_abs_rhoArea',
event.the_3lep_cand.abs_tot_iso03_rhoArea)
self.fill(self.tree, 'hnl_iso04_abs_rhoArea',
event.the_3lep_cand.abs_tot_iso04_rhoArea)
self.fill(self.tree, 'hnl_iso05_abs_rhoArea',
event.the_3lep_cand.abs_tot_iso05_rhoArea)
self.fill(self.tree, 'hnl_iso03_abs_deltaBeta',
event.the_3lep_cand.abs_tot_iso03_deltaBeta)
self.fill(self.tree, 'hnl_iso04_abs_deltaBeta',
event.the_3lep_cand.abs_tot_iso04_deltaBeta)
self.fill(self.tree, 'hnl_iso05_abs_deltaBeta',
event.the_3lep_cand.abs_tot_iso05_deltaBeta)
# self.fill (self.tree, 'hnl_iso_abs_met' , event.the_3lep_cand.abs_ch_iso_met )
self.fill(self.tree, 'hnl_iso03_rel_rhoArea',
event.the_3lep_cand.rel_tot_iso03_rhoArea)
self.fill(self.tree, 'hnl_iso04_rel_rhoArea',
event.the_3lep_cand.rel_tot_iso04_rhoArea)
self.fill(self.tree, 'hnl_iso05_rel_rhoArea',
event.the_3lep_cand.rel_tot_iso05_rhoArea)
self.fill(self.tree, 'hnl_iso03_rel_deltaBeta',
event.the_3lep_cand.rel_tot_iso03_deltaBeta)
self.fill(self.tree, 'hnl_iso04_rel_deltaBeta',
event.the_3lep_cand.rel_tot_iso04_deltaBeta)
self.fill(self.tree, 'hnl_iso05_rel_deltaBeta',
event.the_3lep_cand.rel_tot_iso05_deltaBeta)
# self.fill (self.tree, 'hnl_iso_rel_met' , event.the_3lep_cand.rel_ch_iso_met )
self.fillMuon(self.tree, 'l1', event.the_3lep_cand.l1())
self.fillMuon(self.tree, 'l2', event.the_3lep_cand.l2())
if self.cfg_ana.promptLepType == 'ele':
self.fillEle(self.tree, 'l0', event.the_3lep_cand.l0())
if self.cfg_ana.promptLepType == 'mu':
self.fillMuon(self.tree, 'l0', event.the_3lep_cand.l0())
# output of MC analysis ONLY FOR SIGNAL
if hasattr(event, 'the_hnl'):
self.fillHNL(self.tree, 'hnl_gen', event.the_hnl)
self.fillParticle(self.tree, 'l0_gen', event.the_hnl.l0())
self.fillParticle(self.tree, 'l1_gen', event.the_hnl.l1())
self.fillParticle(self.tree, 'l2_gen', event.the_hnl.l2())
self.fillParticle(self.tree, 'n_gen', event.the_hnl.met())
# reco primary vertex
pv = event.goodVertices[0]
self.fill(self.tree, 'pv_x', pv.x())
self.fill(self.tree, 'pv_y', pv.y())
self.fill(self.tree, 'pv_z', pv.z())
self.fill(self.tree, 'pv_xe', pv.xError())
self.fill(self.tree, 'pv_ye', pv.yError())
self.fill(self.tree, 'pv_ze', pv.zError())
# true primary vertex
if hasattr(event, 'the_hnl'):
self.fill(self.tree, 'pv_gen_x', event.the_hn.vx())
self.fill(self.tree, 'pv_gen_y', event.the_hn.vy())
self.fill(self.tree, 'pv_gen_z', event.the_hn.vz())
# beamspot
self.fill(self.tree, 'bs_x', event.beamspot.x0())
self.fill(self.tree, 'bs_y', event.beamspot.y0())
self.fill(self.tree, 'bs_z', event.beamspot.z0())
self.fill(self.tree, 'bs_sigma_x', event.beamspot.BeamWidthX())
self.fill(self.tree, 'bs_sigma_y', event.beamspot.BeamWidthY())
self.fill(self.tree, 'bs_sigma_z', event.beamspot.sigmaZ())
self.fill(self.tree, 'bs_dxdz', event.beamspot.dxdz())
self.fill(self.tree, 'bs_dydz', event.beamspot.dydz())
# true HN decay vertex
if hasattr(event, 'the_hn'):
self.fill(self.tree, 'sv_gen_x',
event.the_hn.lep1.vertex().x()
) # don't use the final lepton to get the vertex from!
self.fill(self.tree, 'sv_gen_y',
event.the_hn.lep1.vertex().y()
) # don't use the final lepton to get the vertex from!
self.fill(self.tree, 'sv_gen_z',
event.the_hn.lep1.vertex().z()
) # don't use the final lepton to get the vertex from!
# displacements
self.fill(self.tree, 'hnl_2d_gen_disp',
displacement2D(event.the_hn.lep1, event.the_hn))
self.fill(self.tree, 'hnl_3d_gen_disp',
displacement3D(event.the_hn.lep1, event.the_hn))
# HLT bits & matches
trig_list = [trig.name for trig in event.trigger_infos if trig.fired]
if self.cfg_ana.promptLepType == 'ele':
self.fill(
self.tree, 'hlt_Ele27_WPTight_Gsf',
any('HLT_Ele27_WPTight_Gsf' in name for name in trig_list))
self.fill(
self.tree, 'hlt_Ele32_WPTight_Gsf',
any('HLT_Ele32_WPTight_Gsf' in name for name in trig_list))
self.fill(
self.tree, 'hlt_Ele35_WPTight_Gsf',
any('HLT_Ele35_WPTight_Gsf' in name for name in trig_list))
self.fill(
self.tree, 'hlt_Ele115_CaloIdVT_GsfTrkIdT',
any('HLT_Ele115_CaloIdVT_GsfTrkIdT' in name
for name in trig_list))
self.fill(
self.tree, 'hlt_Ele135_CaloIdVT_GsfTrkIdT',
any('HLT_Ele135_CaloIdVT_GsfTrkIdT' in name
for name in trig_list))
if self.cfg_ana.promptLepType == 'mu':
self.fill(self.tree, 'hlt_soMu24',
any('HLT_IsoMu24' in name for name in trig_list))
self.fill(self.tree, 'hlt_soMu27',
any('HLT_IsoMu27' in name for name in trig_list))
self.fill(self.tree, 'hlt_u50',
any('HLT_Mu50' in name for name in trig_list))
# reco secondary vertex and displacement
self.fill(self.tree, 'sv_x', event.recoSv.x())
self.fill(self.tree, 'sv_y', event.recoSv.y())
self.fill(self.tree, 'sv_z', event.recoSv.z())
self.fill(self.tree, 'sv_xe', event.recoSv.xError())
self.fill(self.tree, 'sv_ye', event.recoSv.yError())
self.fill(self.tree, 'sv_ze', event.recoSv.zError())
self.fill(self.tree, 'sv_prob', event.recoSv.prob)
self.fill(self.tree, 'sv_cos', event.recoSv.disp2DFromBS_cos)
self.fill(self.tree, 'hnl_2d_disp',
event.recoSv.disp2DFromBS.value()) # from beamspot
self.fill(self.tree, 'hnl_3d_disp',
event.recoSv.disp3DFromBS.value()) # from PV
self.fill(self.tree, 'hnl_2d_disp_sig',
event.recoSv.disp2DFromBS_sig) # from beamspot
self.fill(self.tree, 'hnl_3d_disp_sig',
event.recoSv.disp3DFromBS_sig) # from PV
# jet/met variables
self.fillExtraMetInfo(self.tree, event)
# set_trace()
# met filter flags
self.fill(self.tree, 'Flag_goodVertices', event.Flag_goodVertices)
self.fill(self.tree, 'Flag_globalSuperTightHalo2016Filter',
event.Flag_globalSuperTightHalo2016Filter)
self.fill(self.tree, 'Flag_HBHENoiseFilter',
event.Flag_HBHENoiseFilter)
self.fill(self.tree, 'Flag_HBHENoiseIsoFilter',
event.Flag_HBHENoiseIsoFilter)
self.fill(self.tree, 'Flag_EcalDeadCellTriggerPrimitiveFilter',
event.Flag_EcalDeadCellTriggerPrimitiveFilter)
self.fill(self.tree, 'Flag_BadPFMuonFilter',
event.Flag_BadPFMuonFilter)
self.fill(self.tree, 'Flag_BadChargedCandidateFilter',
event.Flag_BadChargedCandidateFilter)
self.fill(self.tree, 'Flag_eeBadScFilter', event.Flag_eeBadScFilter)
self.fill(self.tree, 'Flag_ecalBadCalibFilter',
event.Flag_ecalBadCalibFilter)
# self.fill(self.tree, 'Flag_any_met_filters', event.Flag_goodVertices or event.Flag_globalSuperTightHalo2016Filter or event.Flag_HBHENoiseFilter or event.Flag_HBHENoiseIsoFilter or event.Flag_EcalDeadCellTriggerPrimitiveFilter or event.Flag_BadPFMuonFilter or event.Flag_BadChargedCandidateFilter or event.Flag_eeBadScFilter or event.Flag_ecalBadCalibFilter)
if len(event.cleanJets) > 0:
self.fillJet(self.tree, 'j1', event.cleanJets[0], fill_extra=False)
if len(event.cleanJets) > 1:
self.fillJet(self.tree, 'j2', event.cleanJets[1], fill_extra=False)
if len(event.cleanBJets) > 0:
self.fillJet(self.tree,
'bj1',
event.cleanBJets[0],
fill_extra=False)
if len(event.cleanBJets) > 1:
self.fillJet(self.tree,
'bj2',
event.cleanBJets[1],
fill_extra=False)
self.fill(self.tree, 'htj', event.HT_cleanJets)
self.fill(self.tree, 'htbj', event.HT_bJets)
self.fill(self.tree, 'nj', len(event.cleanJets))
self.fill(self.tree, 'nbj', len(event.cleanBJets))
# gen match
if self.cfg_comp.isMC == True:
stable_genp = [
pp for pp in event.genParticles
if ((pp.status() == 23 or pp.status() == 1) and (
pp.vertex().z() != 0))
]
stable_genp += [
pp for pp in event.genp_packed
if ((pp.status() == 23 or pp.status() == 1) and (
pp.vertex().z() != 0))
]
# particle status: http://home.thep.lu.se/~torbjorn/pythia81html/ParticleProperties.html
# 1 ... stable; 23 ... from hardest scattering subprocess
tomatch = [(event.the_3lep_cand.l0(), 0.05 * 0.05),
(event.the_3lep_cand.l1(), 0.2 * 0.2),
(event.the_3lep_cand.l2(), 0.2 * 0.2)]
for ilep, idr2 in tomatch:
bestmatch, dr2 = bestMatch(ilep, stable_genp)
if (dr2 < idr2 and abs(
(ilep.pt() - bestmatch.pt()) / ilep.pt()) < 0.2):
ilep.bestmatch = bestmatch
# relevant for signal: check if reco matched with gen, save a bool
if hasattr(event.the_3lep_cand.l0(), 'bestmatch'):
self.fillSimpleGenParticle(self.tree, 'l0_gen_match',
event.the_3lep_cand.l0().bestmatch)
if hasattr(event.the_3lep_cand.l1(), 'bestmatch'):
self.fillSimpleGenParticle(self.tree, 'l1_gen_match',
event.the_3lep_cand.l1().bestmatch)
if hasattr(event.the_3lep_cand.l2(), 'bestmatch'):
self.fillSimpleGenParticle(self.tree, 'l2_gen_match',
event.the_3lep_cand.l2().bestmatch)
# FIXME! matching by pointer does not work, so let's trick it with deltaR
if hasattr(event, 'the_hnl'):
if hasattr(event.the_3lep_cand.l0(), 'bestmatch'):
self.fill(
self.tree, 'l0_is_real',
deltaR(event.the_3lep_cand.l0().bestmatch,
event.the_hnl.l0()) < 0.01)
if hasattr(event.the_3lep_cand.l1(), 'bestmatch'):
self.fill(
self.tree, 'l1_is_real',
deltaR(event.the_3lep_cand.l1().bestmatch,
event.the_hnl.l1()) < 0.05)
if hasattr(event.the_3lep_cand.l2(), 'bestmatch'):
self.fill(
self.tree, 'l2_is_real',
deltaR(event.the_3lep_cand.l2().bestmatch,
event.the_hnl.l2()) < 0.05)
# extra lepton veto
self.fill(self.tree, 'pass_e_veto', len(event.veto_eles) == 0)
self.fill(self.tree, 'pass_m_veto', len(event.veto_mus) == 0)
# save vetoing lepton invariant masses
if len(event.veto_eles):
self.fillEle(self.tree, 'veto_ele', event.veto_save_ele)
self.fill(self.tree, 'hnl_m_0Vele',
(event.veto_save_ele.p4() +
event.the_3lep_cand.l0().p4()).mass())
self.fill(self.tree, 'hnl_m_1Vele',
(event.veto_save_ele.p4() +
event.the_3lep_cand.l1().p4()).mass())
self.fill(self.tree, 'hnl_m_2Vele',
(event.veto_save_ele.p4() +
event.the_3lep_cand.l2().p4()).mass())
if len(event.veto_mus):
self.fillMuon(self.tree, 'veto_mu', event.veto_save_mu)
self.fill(self.tree, 'hnl_m_0Vmu',
(event.veto_save_mu.p4() +
event.the_3lep_cand.l0().p4()).mass())
self.fill(self.tree, 'hnl_m_1Vmu',
(event.veto_save_mu.p4() +
event.the_3lep_cand.l1().p4()).mass())
self.fill(self.tree, 'hnl_m_2Vmu',
(event.veto_save_mu.p4() +
event.the_3lep_cand.l2().p4()).mass())
# LHE weight
self.fill(self.tree, 'lhe_weight',
np.sign(getattr(event, 'LHE_originalWeight', 1.)))
self.fillTree(event)
def makeLeptons(self, event):
### inclusive leptons = all leptons that could be considered somewhere in the analysis, with minimal requirements (used e.g. to match to MC)
event.inclusiveLeptons = []
### selected leptons = subset of inclusive leptons passing some basic id definition and pt requirement
### other leptons = subset of inclusive leptons failing some basic id definition and pt requirement
event.selectedLeptons = []
event.selectedMuons = []
event.selectedElectrons = []
event.otherLeptons = []
#muons
allmuons = self.makeAllMuons(event)
for mu in allmuons:
# inclusive, very loose, selection
if (mu.track().isNonnull() and mu.muonID(self.cfg_ana.inclusive_muon_id) and
mu.pt()>self.cfg_ana.inclusive_muon_pt and abs(mu.eta())<self.cfg_ana.inclusive_muon_eta and
abs(mu.dxy())<self.cfg_ana.inclusive_muon_dxy and abs(mu.dz())<self.cfg_ana.inclusive_muon_dz):
event.inclusiveLeptons.append(mu)
# basic selection
if (mu.muonID(self.cfg_ana.loose_muon_id) and
mu.pt() > self.cfg_ana.loose_muon_pt and abs(mu.eta()) < self.cfg_ana.loose_muon_eta and
abs(mu.dxy()) < self.cfg_ana.loose_muon_dxy and abs(mu.dz()) < self.cfg_ana.loose_muon_dz and
mu.relIso03 < self.cfg_ana.loose_muon_relIso and
mu.absIso03 < (self.cfg_ana.loose_muon_absIso if hasattr(self.cfg_ana,'loose_muon_absIso') else 9e99)):
mu.looseIdSusy = True
event.selectedLeptons.append(mu)
event.selectedMuons.append(mu)
else:
mu.looseIdSusy = False
event.otherLeptons.append(mu)
#electrons
allelectrons = self.makeAllElectrons(event)
looseMuons = event.selectedLeptons[:]
for ele in allelectrons:
## remove muons if muForEleCrossCleaning is not empty
## apply selection
if ( ele.electronID(self.cfg_ana.inclusive_electron_id) and
ele.pt()>self.cfg_ana.inclusive_electron_pt and abs(ele.eta())<self.cfg_ana.inclusive_electron_eta and
abs(ele.dxy())<self.cfg_ana.inclusive_electron_dxy and abs(ele.dz())<self.cfg_ana.inclusive_electron_dz and
ele.lostInner()<=self.cfg_ana.inclusive_electron_lostHits ):
event.inclusiveLeptons.append(ele)
# basic selection
if (ele.electronID(self.cfg_ana.loose_electron_id) and
ele.pt()>self.cfg_ana.loose_electron_pt and abs(ele.eta())<self.cfg_ana.loose_electron_eta and
abs(ele.dxy()) < self.cfg_ana.loose_electron_dxy and abs(ele.dz())<self.cfg_ana.loose_electron_dz and
ele.relIso03 <= self.cfg_ana.loose_electron_relIso and
ele.absIso03 < (self.cfg_ana.loose_electron_absIso if hasattr(self.cfg_ana,'loose_electron_absIso') else 9e99) and
ele.lostInner() <= self.cfg_ana.loose_electron_lostHits and
( True if (hasattr(self.cfg_ana,'notCleaningElectrons') and self.cfg_ana.notCleaningElectrons) else (bestMatch(ele, looseMuons)[1] > (self.cfg_ana.min_dr_electron_muon**2)) )):
event.selectedLeptons.append(ele)
event.selectedElectrons.append(ele)
ele.looseIdSusy = True
else:
event.otherLeptons.append(ele)
ele.looseIdSusy = False
event.otherLeptons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedLeptons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedMuons.sort(key = lambda l : l.pt(), reverse = True)
event.selectedElectrons.sort(key = lambda l : l.pt(), reverse = True)
event.inclusiveLeptons.sort(key = lambda l : l.pt(), reverse = True)
for lepton in event.selectedLeptons:
if hasattr(self,'efficiency'):
self.efficiency.attachToObject(lepton)
abs(jet.eta()) < 3.0 and
jet.pt() < 200.5)
]
jets = removeOverlap(all_jets, genLeptons)
event.getByLabel("slimmedGenJets", genJetH)
all_gen_jets = [
jet for jet in genJetH.product()
if (jet.pt() > 20 and
abs(jet.eta()) < 3.0 and
jet.pt() < 200.5)
]
gen_jets = removeOverlap(all_gen_jets, genLeptons)
matched_jets = []
for jet in jets:
genjet, dr2 = bestMatch(jet, gen_jets)
if dr2 < 0.01:
matched_jets.append(jet)
refObjs = copy.deepcopy(matched_jets)
elif runtype in ele_run_types:
refObjs = copy.deepcopy(genElectrons)
elif runtype in muon_run_types:
refObjs = copy.deepcopy(genMuons)
###
Matched = MatchTausToJets(refObjs)
###
h_ngen.Fill(len(refObjs))
for refidx,refObj in enumerate(refObjs):
for var in all_vars:
def process(self, event, fill=True):
'''
'''
self.readCollections(event.input)
self.tree.reset()
self.counters.counter('HNLTreeProducer').inc('all events')
# save the event only if it is in the correct final state
if not eval(self.finalStateFilter):
return True
self.counters.counter('HNLTreeProducer').inc('pass final state')
# get ahold of the objects to save
final_state = self.cfg_ana.promptLepType + self.cfg_ana.L1L2LeptonType
dileptonsvtx = event.dileptonsvtx_dict[final_state]
the_3lep_cand = event.the_3lep_cand_dict[final_state]
recoSv = event.recoSv_dict[final_state]
# save the event only if it passes the skim selection (if it exists)
# import pdb ; pdb.set_trace()
if not eval(self.skimFilter):
return True
self.counters.counter('HNLTreeProducer').inc('pass skim')
# also cleaned jet collections depend on the final state
cleanJets = event.cleanJets[final_state]
cleanBJets = event.cleanBJets[final_state]
cleanJets30 = event.cleanJets30[final_state]
# adjust the weights, according to the final state
event.eventWeight = getattr(event, 'puWeight', 1.) * \
getattr(event, 'LHE_originalWeight', 1.) * \
getattr(event, 'weight_%s' %final_state, 1.)
the_3lep_cand.l0().weight = getattr(the_3lep_cand.l0(),
'weight_%s' % final_state, 1.)
the_3lep_cand.l0().weight_id = getattr(the_3lep_cand.l0(),
'weight_%s_id' % final_state,
1.)
the_3lep_cand.l0().weight_iso = getattr(the_3lep_cand.l0(),
'weight_%s_iso' % final_state,
1.)
the_3lep_cand.l0().weight_reco = getattr(
the_3lep_cand.l0(), 'weight_%s_reco' % final_state, 1.)
the_3lep_cand.l0().weight_idiso = getattr(
the_3lep_cand.l0(), 'weight_%s_idiso' % final_state, 1.)
the_3lep_cand.l0().weight_trigger = getattr(
the_3lep_cand.l0(), 'weight_%s_trigger' % final_state, 1.)
the_3lep_cand.l0().weight_tracking = getattr(
the_3lep_cand.l0(), 'weight_%s_tracking' % final_state, 1.)
the_3lep_cand.l1().weight = getattr(the_3lep_cand.l1(),
'weight_%s' % final_state, 1.)
the_3lep_cand.l1().weight_id = getattr(the_3lep_cand.l1(),
'weight_%s_id' % final_state,
1.)
the_3lep_cand.l1().weight_iso = getattr(the_3lep_cand.l1(),
'weight_%s_iso' % final_state,
1.)
the_3lep_cand.l1().weight_reco = getattr(
the_3lep_cand.l1(), 'weight_%s_reco' % final_state, 1.)
the_3lep_cand.l1().weight_idiso = getattr(
the_3lep_cand.l1(), 'weight_%s_idiso' % final_state, 1.)
the_3lep_cand.l1().weight_trigger = getattr(
the_3lep_cand.l1(), 'weight_%s_trigger' % final_state, 1.)
the_3lep_cand.l1().weight_tracking = getattr(
the_3lep_cand.l1(), 'weight_%s_tracking' % final_state, 1.)
the_3lep_cand.l2().weight = getattr(the_3lep_cand.l2(),
'weight_%s' % final_state, 1.)
the_3lep_cand.l2().weight_id = getattr(the_3lep_cand.l2(),
'weight_%s_id' % final_state,
1.)
the_3lep_cand.l2().weight_iso = getattr(the_3lep_cand.l2(),
'weight_%s_iso' % final_state,
1.)
the_3lep_cand.l2().weight_reco = getattr(
the_3lep_cand.l2(), 'weight_%s_reco' % final_state, 1.)
the_3lep_cand.l2().weight_idiso = getattr(
the_3lep_cand.l2(), 'weight_%s_idiso' % final_state, 1.)
the_3lep_cand.l2().weight_trigger = getattr(
the_3lep_cand.l2(), 'weight_%s_trigger' % final_state, 1.)
the_3lep_cand.l2().weight_tracking = getattr(
the_3lep_cand.l2(), 'weight_%s_tracking' % final_state, 1.)
# event variables
self.fillEvent(self.tree, event)
self.fill(self.tree, 'n_cands', len(dileptonsvtx))
# these are PRESELECTED leptons according to the preselection given via cfg
# reco HNL
self.fillHNL(self.tree, 'hnl', the_3lep_cand)
if self.cfg_ana.L1L2LeptonType == 'mm':
self.fillMuon(self.tree, 'l1', the_3lep_cand.l1())
self.fillMuon(self.tree, 'l2', the_3lep_cand.l2())
if self.cfg_ana.L1L2LeptonType == 'ee':
self.fillEle(self.tree, 'l1', the_3lep_cand.l1())
self.fillEle(self.tree, 'l2', the_3lep_cand.l2())
if self.cfg_ana.L1L2LeptonType == 'em':
self.fillEle(self.tree, 'l1', the_3lep_cand.l1())
self.fillMuon(self.tree, 'l2', the_3lep_cand.l2())
if self.cfg_ana.promptLepType == 'e':
self.fillEle(self.tree, 'l0', the_3lep_cand.l0())
if self.cfg_ana.promptLepType == 'm':
self.fillMuon(self.tree, 'l0', the_3lep_cand.l0())
# output of MC analysis ONLY FOR SIGNAL
if hasattr(event, 'the_hnl'):
self.fillHNL(self.tree, 'hnl_gen', event.the_hnl)
self.fillParticle(self.tree, 'l0_gen', event.the_hnl.l0())
self.fillParticle(self.tree, 'l1_gen', event.the_hnl.l1())
self.fillParticle(self.tree, 'l2_gen', event.the_hnl.l2())
self.fillParticle(self.tree, 'n_gen', event.the_hnl.met())
# reco primary vertex
pv = event.goodVertices[0]
self.fill(self.tree, 'pv_x', pv.x())
self.fill(self.tree, 'pv_y', pv.y())
self.fill(self.tree, 'pv_z', pv.z())
self.fill(self.tree, 'pv_xe', pv.xError())
self.fill(self.tree, 'pv_ye', pv.yError())
self.fill(self.tree, 'pv_ze', pv.zError())
# true primary vertex
if hasattr(event, 'the_hnl'):
self.fill(self.tree, 'pv_gen_x', event.the_hn.vx())
self.fill(self.tree, 'pv_gen_y', event.the_hn.vy())
self.fill(self.tree, 'pv_gen_z', event.the_hn.vz())
# beamspot
self.fill(self.tree, 'bs_x', event.beamspot.x0())
self.fill(self.tree, 'bs_y', event.beamspot.y0())
self.fill(self.tree, 'bs_z', event.beamspot.z0())
self.fill(self.tree, 'bs_sigma_x', event.beamspot.BeamWidthX())
self.fill(self.tree, 'bs_sigma_y', event.beamspot.BeamWidthY())
self.fill(self.tree, 'bs_sigma_z', event.beamspot.sigmaZ())
self.fill(self.tree, 'bs_dxdz', event.beamspot.dxdz())
self.fill(self.tree, 'bs_dydz', event.beamspot.dydz())
# true HN decay vertex
if hasattr(event, 'the_hn'):
self.fill(self.tree, 'sv_gen_x',
event.the_hn.lep1.vertex().x()
) # don't use the final lepton to get the vertex from!
self.fill(self.tree, 'sv_gen_y',
event.the_hn.lep1.vertex().y()
) # don't use the final lepton to get the vertex from!
self.fill(self.tree, 'sv_gen_z',
event.the_hn.lep1.vertex().z()
) # don't use the final lepton to get the vertex from!
# displacements
self.fill(self.tree, 'hnl_2d_gen_disp',
displacement2D(event.the_hn.lep1, event.the_hn))
self.fill(self.tree, 'hnl_3d_gen_disp',
displacement3D(event.the_hn.lep1, event.the_hn))
# HLT bits & matches
trig_list = [trig.name for trig in event.trigger_infos if trig.fired]
if self.cfg_ana.promptLepType == 'e':
self.fill(
self.tree, 'hlt_Ele25_eta2p1_WPTight_Gsf',
any('HLT_Ele25_eta2p1_WPTight_Gsf' in name
for name in trig_list))
self.fill(
self.tree, 'hlt_Ele27_WPTight_Gsf',
any('HLT_Ele27_WPTight_Gsf' in name for name in trig_list))
self.fill(
self.tree, 'hlt_Ele32_WPTight_Gsf',
any('HLT_Ele32_WPTight_Gsf' in name for name in trig_list))
self.fill(
self.tree, 'hlt_Ele35_WPTight_Gsf',
any('HLT_Ele35_WPTight_Gsf' in name for name in trig_list))
self.fill(
self.tree, 'hlt_Ele115_CaloIdVT_GsfTrkIdT',
any('HLT_Ele115_CaloIdVT_GsfTrkIdT' in name
for name in trig_list))
self.fill(
self.tree, 'hlt_Ele135_CaloIdVT_GsfTrkIdT',
any('HLT_Ele135_CaloIdVT_GsfTrkIdT' in name
for name in trig_list))
if self.cfg_ana.promptLepType == 'm':
self.fill(self.tree, 'hlt_IsoMu22',
any('HLT_IsoMu22' in name for name in trig_list))
self.fill(self.tree, 'hlt_IsoTkMu22',
any('HLT_IsoTkMu22' in name for name in trig_list))
self.fill(self.tree, 'hlt_IsoMu22_eta2p1',
any('HLT_IsoMu22_eta2p1' in name for name in trig_list))
self.fill(
self.tree, 'hlt_IsoTkMu22_eta2p1',
any('HLT_IsoTkMu22_eta2p1' in name for name in trig_list))
self.fill(self.tree, 'hlt_IsoMu24',
any('HLT_IsoMu24' in name for name in trig_list))
self.fill(self.tree, 'hlt_IsoTkMu24',
any('HLT_IsoTkMu24' in name for name in trig_list))
self.fill(self.tree, 'hlt_IsoMu27',
any('HLT_IsoMu27' in name for name in trig_list))
self.fill(self.tree, 'hlt_IsoTkMu27',
any('HLT_IsoTkMu27' in name for name in trig_list))
self.fill(self.tree, 'hlt_Mu50',
any('HLT_Mu50' in name for name in trig_list))
self.fill(self.tree, 'hlt_TkMu50',
any('HLT_TkMu50' in name for name in trig_list))
# reco secondary vertex and displacement
self.fillVertex(self.tree, 'sv', recoSv)
self.fill(self.tree, 'hnl_2d_disp',
recoSv.disp2DFromBS.value()) # from beamspot
self.fill(self.tree, 'hnl_3d_disp',
recoSv.disp3DFromBS.value()) # from PV
self.fill(self.tree, 'hnl_2d_disp_sig',
recoSv.disp2DFromBS_sig) # from beamspot
self.fill(self.tree, 'hnl_3d_disp_sig',
recoSv.disp3DFromBS_sig) # from PV
# jet/met variables
self.fillExtraMetInfo(self.tree, event)
# met filter flags
self.fill(self.tree, 'pass_met_filters', event.pass_met_filters)
if len(cleanJets) > 0:
self.fillJet(self.tree, 'j1', cleanJets[0], fill_extra=False)
if len(cleanJets) > 1:
self.fillJet(self.tree, 'j2', cleanJets[1], fill_extra=False)
if len(cleanBJets) > 0:
self.fillJet(self.tree, 'bj1', cleanBJets[0], fill_extra=False)
if len(cleanBJets) > 1:
self.fillJet(self.tree, 'bj2', cleanBJets[1], fill_extra=False)
self.fill(self.tree, 'nj', len(cleanJets))
self.fill(self.tree, 'nj30', len(cleanJets30))
self.fill(self.tree, 'nbj', len(cleanBJets))
# FIXME! RM what is this?
# gen match
if self.cfg_comp.isMC == True and hasattr(event, 'genParticles'):
stable_genp = [
pp for pp in event.genParticles if pp.status() == 1
] # and pp.vertex().z()!=0)]
stable_genp += [
pp for pp in event.genp_packed if pp.status() == 1
] # and pp.vertex().z()!=0)]
# particle status: http://home.thep.lu.se/~torbjorn/pythia81html/ParticleProperties.html
# 1 ... stable; 23 ... from hardest scattering subprocess
# stable_genp += [pp for pp in event.genParticles if (pp.status()==23 and pp.vertex().z()!=0)]
# stable_genp += [pp for pp in event.genp_packed if (pp.status()==23 and pp.vertex().z()!=0)]
tomatch = [(the_3lep_cand.l0(), 0.05 * 0.05),
(the_3lep_cand.l1(), 0.2 * 0.2),
(the_3lep_cand.l2(), 0.2 * 0.2)]
for ilep, idr2 in tomatch:
bestmatch, dr2 = bestMatch(ilep, stable_genp)
if (dr2 < idr2 and abs(
(ilep.pt() - bestmatch.pt()) / ilep.pt()) < 0.2):
ilep.bestmatch = bestmatch
# relevant for mc: check if reco matched with gen, save a float
if hasattr(the_3lep_cand.l0(), 'bestmatch'):
LEP0 = the_3lep_cand.l0()
self.fillSimpleGenParticle(self.tree, 'l0_gen_match',
LEP0.bestmatch)
self.fill(self.tree, 'l0_good_match',
deltaR(LEP0.bestmatch, LEP0))
# if deltaR(LEP0.bestmatch, LEP0) < 0.04 and LEP0.pdgId() == LEP0.bestmatch.pdgId():
# self.fill(self.tree, 'l0_good_match', 1)
if hasattr(the_3lep_cand.l1(), 'bestmatch'):
LEP1 = the_3lep_cand.l1()
self.fillSimpleGenParticle(self.tree, 'l1_gen_match',
LEP1.bestmatch)
self.fill(self.tree, 'l1_good_match',
deltaR(LEP1.bestmatch, LEP1))
# if deltaR(LEP1.bestmatch, LEP1) < 0.04 and LEP1.pdgId() == LEP1.bestmatch.pdgId():
# self.fill(self.tree, 'l1_good_match', 1)
if hasattr(the_3lep_cand.l2(), 'bestmatch'):
LEP2 = the_3lep_cand.l2()
self.fillSimpleGenParticle(self.tree, 'l2_gen_match',
LEP2.bestmatch)
self.fill(self.tree, 'l2_good_match',
deltaR(LEP2.bestmatch, LEP2))
# if deltaR(LEP2.bestmatch, LEP2) < 0.04 and LEP2.pdgId() == LEP2.bestmatch.pdgId():
# self.fill(self.tree, 'l2_good_match', 1)
# matching by pointer does not work, so let's trick it with deltaR
if hasattr(event, 'the_hnl'):
if hasattr(the_3lep_cand.l0(), 'bestmatch'):
self.fill(
self.tree, 'l0_is_real',
deltaR(the_3lep_cand.l0().bestmatch,
event.the_hnl.l0()) < 0.01)
if hasattr(the_3lep_cand.l1(), 'bestmatch'):
self.fill(
self.tree, 'l1_is_real',
deltaR(the_3lep_cand.l1().bestmatch,
event.the_hnl.l1()) < 0.05)
if hasattr(the_3lep_cand.l2(), 'bestmatch'):
self.fill(
self.tree, 'l2_is_real',
deltaR(the_3lep_cand.l2().bestmatch,
event.the_hnl.l2()) < 0.05)
# print('event:', event.eventId, 'lumi:', event.lumi)
# extra lepton veto
self.fill(self.tree, 'pass_e_veto', len(event.veto_eles) == 0)
self.fill(self.tree, 'pass_m_veto', len(event.veto_mus) == 0)
# LHE weight
self.fill(self.tree, 'lhe_weight',
np.sign(getattr(event, 'LHE_originalWeight', 1.)))
# weights for ctau reweighing (only for signal!)
if 'HN3L' in self.cfg_comp.name:
for iv2 in new_v2s:
# 'stringify' the coupling
# reduce precision to avoid nasty numbers e.g. 6.000000000000001e-05
iv2_name = np.format_float_scientific(iv2,
unique=False,
precision=1,
exp_digits=2)
iv2_name = iv2_name.replace('-', 'm')
self.fill(self.tree, 'ctau_w_v2_%s' % iv2_name,
event.ctau_weights[iv2]['ctau_weight'])
self.fill(self.tree, 'xs_w_v2_%s' % iv2_name,
event.ctau_weights[iv2]['xs_weight'])
if event.the_gen_w is not None:
self.fillParticle(self.tree, 'w_gen', event.the_gen_w)
self.fill(self.tree, 'pass_mmm', getattr(event, 'pass_mmm', -1.))
self.fill(self.tree, 'pass_mem', getattr(event, 'pass_mem', -1.))
self.fill(self.tree, 'pass_eee', getattr(event, 'pass_eee', -1.))
self.fill(self.tree, 'pass_eem', getattr(event, 'pass_eem', -1.))
# import pdb ; pdb.set_trace()
if fill:
self.fillTree(event)
def process(self, event):
self.tree.reset()
ntuple.fillEvent(self.tree, event)
ntuple.fillParticle(self.tree, 'b', event.theb)
ntuple.fillParticle(self.tree, 'jpsi', event.theb.jpsi())
ntuple.fillMuon(self.tree, 'mu1' , event.theb.l0())
ntuple.fillParticle(self.tree, 'tk2' , event.theb.l1())
mu2, dR2 = bestMatch(event.theb.l1(), event.muons)
if dR2<0.005*0.005 and mu2.physObj != event.theb.l0().physObj:
ntuple.fillMuon(self.tree, 'mu2', mu2)
ntuple.fillParticle(self.tree, 'k', event.theb.k())
ntuple.fill(self.tree, 'dr_mm' , deltaR(event.theb.l0() , event.theb.l1()))
ntuple.fill(self.tree, 'dr_jpsi_k' , deltaR(event.theb.jpsi() , event.theb.k() ))
ntuple.fill(self.tree, 'dr_jpsi_mu1' , deltaR(event.theb.jpsi() , event.theb.l0()))
ntuple.fill(self.tree, 'dr_jpsi_mu2' , deltaR(event.theb.jpsi() , event.theb.l1()))
ntuple.fill(self.tree, 'dr_mu1_k' , deltaR(event.theb.l0() , event.theb.k() ))
ntuple.fill(self.tree, 'dr_mu2_k' , deltaR(event.theb.l1() , event.theb.k() ))
ntuple.fill(self.tree, 'dphi_mm' , deltaPhi(event.theb.l0() .phi(), event.theb.l1().phi()))
ntuple.fill(self.tree, 'dphi_jpsi_k' , deltaPhi(event.theb.jpsi().phi(), event.theb.k() .phi()))
ntuple.fill(self.tree, 'dphi_jpsi_mu1', deltaPhi(event.theb.jpsi().phi(), event.theb.l0().phi()))
ntuple.fill(self.tree, 'dphi_jpsi_mu2', deltaPhi(event.theb.jpsi().phi(), event.theb.l1().phi()))
ntuple.fill(self.tree, 'dphi_mu1_k' , deltaPhi(event.theb.l0() .phi(), event.theb.k() .phi()))
ntuple.fill(self.tree, 'dphi_mu2_k' , deltaPhi(event.theb.l1() .phi(), event.theb.k() .phi()))
ntuple.fill(self.tree, 'b_cone' , event.theb.bcone())
ntuple.fill(self.tree, 'bs_x', event.beamspot.x0())
ntuple.fill(self.tree, 'bs_y', event.beamspot.y0())
ntuple.fill(self.tree, 'bs_z', event.beamspot.z0())
ntuple.fill(self.tree, 'pv_x', event.pv.x())
ntuple.fill(self.tree, 'pv_y', event.pv.y())
ntuple.fill(self.tree, 'pv_z', event.pv.z())
if event.theb.vtx().isValid():
ntuple.fill(self.tree, 'sv_x', event.theb.vtx().position().x())
ntuple.fill(self.tree, 'sv_y', event.theb.vtx().position().y())
ntuple.fill(self.tree, 'sv_z', event.theb.vtx().position().z())
ntuple.fill(self.tree, 'sv_chi2', event.theb.vtx().normalisedChiSquared())
ntuple.fill(self.tree, 'sv_prob', ROOT.TMath.Prob(event.theb.vtx().normalisedChiSquared(), 1))
ntuple.fill(self.tree, 'sv_2d_disp' , event.theb.disp2d().value())
ntuple.fill(self.tree, 'sv_2d_disp_err' , event.theb.disp2d().error())
ntuple.fill(self.tree, 'sv_2d_disp_sig' , event.theb.ls2d())
ntuple.fill(self.tree, 'sv_2d_cos' , event.theb.vtxcos())
for info, hlt in product(event.trigger_infos, ['HLT_Mu7p5_Track2_Jpsi', 'HLT_Mu7p5_Track3p5_Jpsi', 'HLT_Mu7p5_Track7_Jpsi']):
if hlt in info.name:
ntuple.fill(self.tree, hlt, info.fired)
ntuple.fill(self.tree, hlt+'_ps', info.prescale)
# ntuple.fill(self.tree, 'HLT_Mu7p5_Track2_Jpsi_v9' , any([True for info in event.trigger_infos if info.name == 'HLT_Mu7p5_Track2_Jpsi_v9' and info.fired]))
# ntuple.fill(self.tree, 'HLT_Mu7p5_Track3p5_Jpsi_v9', any([True for info in event.trigger_infos if info.name == 'HLT_Mu7p5_Track3p5_Jpsi_v9' and info.fired]))
# ntuple.fill(self.tree, 'HLT_Mu7p5_Track7_Jpsi_v9' , any([True for info in event.trigger_infos if info.name == 'HLT_Mu7p5_Track7_Jpsi_v9' and info.fired]))
#
# ntuple.fill(self.tree, 'HLT_Mu7p5_Track2_Jpsi_v9_ps' , any([True for info in event.trigger_infos if info.name == 'HLT_Mu7p5_Track2_Jpsi_v9' and info.fired]))
# ntuple.fill(self.tree, 'HLT_Mu7p5_Track3p5_Jpsi_v9_ps', any([True for info in event.trigger_infos if info.name == 'HLT_Mu7p5_Track3p5_Jpsi_v9' and info.fired]))
# ntuple.fill(self.tree, 'HLT_Mu7p5_Track7_Jpsi_v9_ps' , any([True for info in event.trigger_infos if info.name == 'HLT_Mu7p5_Track7_Jpsi_v9' and info.fired]))
self.tree.tree.Fill()
charged_p4 = sum(
(d.p4() for d in refObj.final_ds if d.charge()),
ROOT.math.XYZTLorentzVectorD())
neutral_p4 = sum(
(d.p4() for d in refObj.final_ds
if abs(d.pdgId()) not in [12, 14, 16] and not d.charge()),
ROOT.math.XYZTLorentzVectorD())
all_var_dict['gen_charged_pt'].fill(charged_p4.pt())
all_var_dict['gen_neutral_pt'].fill(neutral_p4.pt())
else:
all_var_dict['gen_dm'].fill(-1)
all_var_dict['gen_pt'].fill(refObj.pt())
all_var_dict['gen_eta'].fill(refObj.eta())
all_var_dict['gen_phi'].fill(refObj.phi())
electron, dr = bestMatch(refObj, electrons)
if dr < 0.5:
# Fill reco-tau variables if it exists...
NMatchedTaus += 1
all_var_dict['electron_pt'].fill(electron.pt())
all_var_dict['electron_eta'].fill(electron.eta())
all_var_dict['electron_phi'].fill(electron.phi())
e_p = electron.trackMomentumAtVtx().R()
e_sc = electron.eSuperClusterOverP() * e_p
e_sc_o_p = 2 * e_sc / (e_p + e_sc)
all_var_dict['electron_eSuperClusterOverP_norm'].fill(e_sc_o_p)
e_seed = electron.eSeedClusterOverP() * e_p
hcal = electron.hcalOverEcal() * e_seed
def process(self, event):
self.readCollections(event.input)
self.counters.counter('RecoGenTreeAnalyzer').inc('all events')
# produce collections and map our objects to convenient Heppy objects
event.muons = map(Muon, self.handles['muons'].product())
event.electrons = map(Electron, self.handles['electrons'].product())
event.photons = map(Photon, self.handles['photons'].product())
event.taus = map(Tau, self.handles['taus'].product())
event.jets = map(Jet, self.handles['jets'].product())
event.dsmuons = self.buildDisplacedMuons(
self.handles['dsmuons'].product())
event.dgmuons = self.buildDisplacedMuons(
self.handles['dgmuons'].product())
# vertex stuff
event.pvs = self.handles['pvs'].product()
event.svs = self.handles['svs'].product()
event.beamspot = self.handles['beamspot'].product()
# met
event.met = self.handles['met'].product().at(0)
# assign to the leptons the primary vertex, will be needed to compute a few quantities
# FIXME! understand exactly to which extent it is reasonable to assign the PV to *all* leptons
# regardless whether they're displaced or not
if len(event.pvs):
myvtx = event.pvs[0]
else:
myvtx = event.beamspot
self.assignVtx(event.muons, myvtx)
self.assignVtx(event.electrons, myvtx)
self.assignVtx(event.photons, myvtx)
self.assignVtx(event.taus, myvtx)
# all matchable objects
# matchable = event.electrons + event.photons + event.muons + event.taus + event.dsmuons + event.dgmuons
matchable = event.electrons + event.photons + event.muons + event.taus + event.dsmuons
# match gen to reco
for ip in [event.the_hnl.l0(), event.the_hnl.l1(), event.the_hnl.l2()]:
ip.bestmatch = None
ip.bestmatchtype = None
ip.matches = inConeCollection(ip, matchable,
getattr(self.cfg_ana, 'drmax', 0.2),
0.)
# matches the corresponding "slimmed electron" to the gen particle
if len(event.electrons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.electrons)
if dr2 < 0.04:
ip.bestelectron = match
# matches the corresponding "slimmed photon" to the gen particle
if len(event.photons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.photons)
if dr2 < 0.04:
ip.bestphoton = match
# matches the corresponding "slimmed muon" to the gen particle
if len(event.muons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.muons)
if dr2 < 0.04:
ip.bestmuon = match
# matches the corresponding "slimmed tau" to the gen particle
if len(event.taus):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.taus)
if dr2 < 0.04:
ip.besttau = match
# matches the corresponding "displaced stand alone muon" to the gen particle
if len(event.dsmuons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.dsmuons)
if dr2 < 0.04:
ip.bestdsmuon = match
# matches the corresponding "displaced global muon" to the gen particle
if len(event.dgmuons):
dr2 = np.inf
match, dr2 = bestMatch(ip, event.dgmuons)
if dr2 < 0.04:
ip.bestdgmuon = match
# to find the best match, give precedence to any matched
# particle in the matching cone with the correct PDG ID
# then to the one which is closest
ip.matches.sort(key=lambda x:
(x.pdgId() == ip.pdgId(), -deltaR(x, ip)),
reverse=True)
if len(ip.matches) and abs(ip.pdgId()) == abs(
ip.matches[0].pdgId()):
ip.bestmatch = ip.matches[0]
# remove already matched particles, avoid multiple matches to the same candidate while recording the type of reconstruction
matchable.remove(ip.bestmatch)
# record which is which
if ip.bestmatch in event.electrons: ip.bestmatchtype = 11
if ip.bestmatch in event.photons: ip.bestmatchtype = 22
if ip.bestmatch in event.muons: ip.bestmatchtype = 13
if ip.bestmatch in event.taus: ip.bestmatchtype = 15
if ip.bestmatch in event.dsmuons: ip.bestmatchtype = 26
if ip.bestmatch in event.dgmuons: ip.bestmatchtype = 39
else:
ip.bestmatchtype = -1
# clear it before doing it again
event.recoSv = None
# if hasattr(event.the_hnl.l2().bestmatch, 'pt'):
# set_trace()
# if (abs(event.the_hnl.l1().pt()-13.851562)<0.001):
# set_trace()
######### DEBUG VTX MADE OUT OF DSA MUONS
# if len(event.dsmuons) > 2:
# # clear the vector
# self.tofit.clear()
# # create a RecoChargedCandidate for each reconstructed lepton and flush it into the vector
# for il in [event.dsmuons[0], event.dsmuons[1]]:
# # if the reco particle is a displaced thing, it does not have the p4() method, so let's build it
# myp4 = ROOT.Math.LorentzVector('<ROOT::Math::PxPyPzE4D<double> >')(il.px(), il.py(), il.pz(), math.sqrt(il.mass()**2 + il.px()**2 + il.py()**2 + il.pz()**2))
# ic = ROOT.reco.RecoChargedCandidate() # instantiate a dummy RecoChargedCandidate
# ic.setCharge(il.charge()) # assign the correct charge
# ic.setP4(myp4) # assign the correct p4
# ic.setTrack(il.track()) # set the correct TrackRef
# if ic.track().isNonnull(): # check that the track is valid, there are photons around too!
# self.tofit.push_back(ic)
# # further sanity check: two *distinct* tracks
# if self.tofit.size()==2 and self.tofit[0].track() != self.tofit[1].track():
# # fit it!
# svtree = self.vtxfit.Fit(self.tofit) # actual vertex fitting
# # check that the vertex is good
# if not svtree.get().isEmpty() and svtree.get().isValid():
# svtree.movePointerToTheTop()
# sv = svtree.currentDecayVertex().get()
# event.recoSv = makeRecoVertex(sv, kinVtxTrkSize=2) # need to do some gymastics
# print 'good double dsa vertex! vx=%.2f, vy=%.2f, vz=%.2f' %(event.recoSv.x(), event.recoSv.y(), event.recoSv.z())
# import pdb ; pdb.set_trace()
# let's refit the secondary vertex, IF both leptons match to some reco particle
if not(event.the_hnl.l1().bestmatch is None or \
event.the_hnl.l2().bestmatch is None):
# clear the vector
self.tofit.clear()
# create a RecoChargedCandidate for each reconstructed lepton and flush it into the vector
for il in [
event.the_hnl.l1().bestmatch,
event.the_hnl.l2().bestmatch
]:
# if the reco particle is a displaced thing, it does not have the p4() method, so let's build it
myp4 = ROOT.Math.LorentzVector(
'<ROOT::Math::PxPyPzE4D<double> >')(
il.px(), il.py(), il.pz(),
math.sqrt(il.mass()**2 + il.px()**2 + il.py()**2 +
il.pz()**2))
ic = ROOT.reco.RecoChargedCandidate(
) # instantiate a dummy RecoChargedCandidate
ic.setCharge(il.charge()) # assign the correct charge
ic.setP4(myp4) # assign the correct p4
ic.setTrack(il.track()) # set the correct TrackRef
if ic.track().isNonnull(
): # check that the track is valid, there are photons around too!
self.tofit.push_back(ic)
# further sanity check: two *distinct* tracks
if self.tofit.size(
) == 2 and self.tofit[0].track() != self.tofit[1].track():
# fit it!
svtree = self.vtxfit.Fit(self.tofit) # actual vertex fitting
# check that the vertex is good
if not svtree.get().isEmpty() and svtree.get().isValid():
svtree.movePointerToTheTop()
sv = svtree.currentDecayVertex().get()
event.recoSv = makeRecoVertex(
sv, kinVtxTrkSize=2) # need to do some gymastics
if event.recoSv:
# primary vertex
pv = event.goodVertices[0]
event.recoSv.disp3DFromBS = ROOT.VertexDistance3D().distance(
event.recoSv, pv)
event.recoSv.disp3DFromBS_sig = event.recoSv.disp3DFromBS.significance(
)
# create an 'ideal' vertex out of the BS
point = ROOT.reco.Vertex.Point(
event.beamspot.position().x(),
event.beamspot.position().y(),
event.beamspot.position().z(),
)
error = event.beamspot.covariance3D()
chi2 = 0.
ndof = 0.
bsvtx = ROOT.reco.Vertex(point, error, chi2, ndof,
2) # size? say 3? does it matter?
event.recoSv.disp2DFromBS = ROOT.VertexDistanceXY().distance(
event.recoSv, bsvtx)
event.recoSv.disp2DFromBS_sig = event.recoSv.disp2DFromBS.significance(
)
event.recoSv.prob = ROOT.TMath.Prob(event.recoSv.chi2(),
int(event.recoSv.ndof()))
dilep_p4 = event.the_hnl.l1().bestmatch.p4(
) + event.the_hnl.l2().bestmatch.p4()
perp = ROOT.math.XYZVector(dilep_p4.px(), dilep_p4.py(), 0.)
dxybs = ROOT.GlobalPoint(
-1 * ((event.beamspot.x0() - event.recoSv.x()) +
(event.recoSv.z() - event.beamspot.z0()) *
event.beamspot.dxdz()),
-1 * ((event.beamspot.y0() - event.recoSv.y()) +
(event.recoSv.z() - event.beamspot.z0()) *
event.beamspot.dydz()), 0)
vperp = ROOT.math.XYZVector(dxybs.x(), dxybs.y(), 0.)
cos = vperp.Dot(perp) / (vperp.R() * perp.R())
event.recoSv.disp2DFromBS_cos = cos
# if (abs(event.the_hnl.l1().pdgId()) == 11 or abs(event.the_hnl.l2().pdgId()) == 11):
# if (abs(event.the_hnl.l1().bestmatch.pdgId()) == 11 or abs(event.the_hnl.l2().bestmatch.pdgId()) == 11):
# if event.recoSv:
# print 'lept1 \t', event.the_hnl.l1()
# print 'lept2 \t', event.the_hnl.l2()
# print 'lept1 match\t', event.the_hnl.l1().bestmatch
# print 'lept2 match\t', event.the_hnl.l2().bestmatch
# import pdb ; pdb.set_trace()
return True
mcmatch = dict((d,[]) for d in matches )
# first, match and remove the charged
charged = [d for d in matches if d.charge() != 0]
neutral = [d for d in matches if d.charge() == 0]
ch_match = matchObjectCollection3( charged, c_tomatch, 0.07, filter = lambda d,g: abs(d.pt()-g.pt())/(d.pt()+g.pt()) < 0.2 )
gen_notused = a_tomatch[:]
reco_notused = matches[:]
for c in charged:
g = ch_match[c]
if g == None: continue
mcmatch[c] = [g]
gen_notused.remove(g)
reco_notused.remove(c)
# then assign each gen to the nearest unmatched reco that has reco pt > 0.5 * gen pt
for g in gen_notused[:]:
d, dr2 = bestMatch(g, reco_notused)
if dr2 < 0.01 and d.pt() > 0.5*g.pt():
gen_notused.remove(g)
mcmatch[d].append(g)
# then take any remaining gen and just attach it to the nearest reco, except well-matched tracks
rematch = neutral + [ c for c in charged if c in reco_notused ]
for g in gen_notused:
d, dr2 = bestMatch(g, rematch)
if dr2 < 0.01: mcmatch[d].append(g)
matchletters = [ "X" for mm in matchmaps ]
allmatches = [ [] for mm in matchmaps ]
for im,d in enumerate(matches):
keyer[d.uid()] = "%s%02d" % (layerlabel,im)
revkey["%s%02d" % (layerlabel,im)] = d
if d.pt() < 0.8: continue
print " %s%02d pt %6.2f eta %+5.2f phi %+5.2f ch %+1d dr %.2f id % +5d" % (layerlabel,im, d.pt(), d.eta(), d.phi(), d.charge(), d.dr, d.pdgId()),
