def WriteTree(runSet):
print 'Writing tree'
# Make a tree
froot = TFile('mu.root', 'RECREATE')
tree = TTree("mu", "Flat ntuple for mu")
tree.SetDirectory(froot)
leaves = "run/F:lb/F:mu/F"
leafValues = array("f", [0.0, 0.0, 0.0])
newBranch = tree.Branch("mu_vars", leafValues, leaves)
for r, lbs in runSet.iteritems():
for i in range(lbs.FirstLB(), lbs.LastLB()):
leafValues[2] = lbs.GetMeanPileUp(i)
leafValues[0] = float(r)
leafValues[1] = i
print 'mu: %s run: %s lb: %s' % (leafValues[2], leafValues[0],
leafValues[1])
tree.Fill()
tree.Write()
#froot.Write()
froot.Close()
def makesample(sample): # help function to create file with tree
fname = "%s/%s_%s.root"%(outdir,sample,channel)
file = TFile(fname,'RECREATE')
hist = TH1D('cutflow','cutflow',20,0,20)
tree = TTree('tree','tree')
tree.Branch('m_vis', m_vis, 'm_vis/F')
tree.Branch('pt_1', pt_1, 'pt_1/F')
tree.Branch('pt_2', pt_2, 'pt_2/F')
tree.Branch('dm_2', dm_2, 'dm_2/I')
tree.Branch('eta_1', eta_1, 'eta_1/F')
tree.Branch('eta_2', eta_2, 'eta_2/F')
tree.Branch('njets', njets, 'njets/I')
tree.Branch('genmatch_2', genmatch_2, 'genmatch_2/I')
tree.Branch('NUP', NUP, 'NUP/I')
tree.Branch('weight', weight, 'weight/F')
tree.SetDirectory(file)
hist.SetDirectory(file)
hist.SetBinContent( 1,1)
hist.SetBinContent(17,1)
histdict[sample] = hist
filedict[sample] = (file,tree)
tree_ds.SetBranchAddress(branchName, branches[branchName])
tree_bu.SetBranchAddress(branchName, branches[branchName])
tree_bd.SetBranchAddress(branchName, branches[branchName])
tree_bkg.SetBranchAddress(branchName, branches[branchName])
branches['category'] = array('i', [-999])
tree_ds.SetBranchAddress('category', branches['category'])
tree_bu.SetBranchAddress('category', branches['category'])
tree_bd.SetBranchAddress('category', branches['category'])
tree_bkg.SetBranchAddress('category', branches['category'])
#Setup a new tree
T3MFMiniTree = TFile("T3MMiniTree" + "_" + args.weights_prefix + ".root",
"recreate")
T3MMiniTree = TTree('T3MMiniTree', 'T3MMiniTree')
T3MMiniTree.SetDirectory(T3MFMiniTree)
for branchName in branchList_miniTree:
branches_miniTree[branchName] = array('f', [-999])
T3MMiniTree.Branch(branchName, branches_miniTree[branchName],
branchName + '/F')
# Book methods
for reader in mvaReaderList:
mvaReaders[reader].BookMVA('BDT', mvaWeights[reader])
print branches_miniTree
# print some example classifications
print('Classifying signal events (Ds)')
for i in range(tree_ds.GetEntriesFast()):
#root_file = sys.argv[1]
filename = sys.argv[1]
#filename = root_files_directory + root_file
file = TFile(filename, 'read')
tree = file.Get('t1')
nb_entries = tree.GetEntries()
#newfilename = root_files_directory
#newfile = TFile(root_files_directory + root_file[:-5] + '-t2.root', 'recreate')
newfilename = filename[:-5] + '-t2.root'
newfile = TFile(newfilename, 'recreate')
newtree = TTree('t2', '')
newtree.SetDirectory(newfile)
#che eto takoe??
max_size = 1000000
eventid = array('i', [0])
etot_NR = array('f', [0.])
etot_ER = array('f', [0.])
ns_NR = array('i', [0])
ns_ER = array('i', [0])
ed_NR = array('f', max_size * [0.])
ed_ER = array('f', max_size * [0.])
xp_NR = array('f', max_size * [0.])
xp_ER = array('f', max_size * [0.])
yp_NR = array('f', max_size * [0.])
yp_ER = array('f', max_size * [0.])
class JetIDAnalyzer(Analyzer):
'''A simple jet analyzer.'''
def declareHandles(self):
super(JetIDAnalyzer, self).declareHandles()
self.handles['jets'] = AutoHandle(*self.cfg_ana.jetCollection)
if self.cfg_ana.useGenLeptons:
self.mchandles['leptons2'] = AutoHandle(
'genLeptonsStatus2', 'std::vector<reco::GenParticle>')
else:
self.mchandles['genParticles'] = AutoHandle(
'prunedGen', 'std::vector<reco::GenParticle>')
### self.mchandles['genJets'] = AutoHandle (
### *self.cfg_ana.genJetsCollection
### )
self.handles['vertices'] = AutoHandle('offlinePrimaryVertices',
'std::vector<reco::Vertex>')
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def beginLoop(self):
super(JetIDAnalyzer, self).beginLoop()
self.file = TFile('/'.join([self.looperName, 'testJets.root']),
'recreate')
if self.cfg_ana.applyPFLooseId:
from ROOT import PFJetIDSelectionFunctor
self.isPFLooseFunc = PFJetIDSelectionFunctor(
0, PFJetIDSelectionFunctor.LOOSE)
## Workaround: for some reason PyROOT does not bind PFJetIDSelectionFunctor(Jet) nor PFJetIDSelectionFunctor.getBitsTemplates
from ROOT import pat
self.isPFLooseFunc.bits = pat.strbitset()
for i in "CHF", "NHF", "CEF", "NEF", "NCH", "nConstituents":
self.isPFLooseFunc.bits.push_back(i)
## /Workaround
self.isPFLoose = lambda x: self.isPFLooseFunc(
x, self.isPFLooseFunc.bits)
else:
self.isPFLoose = lambda x: True
# general histograms
self.jetHistos = JetHistograms('Jets')
self.cleanJetHistos = JetHistograms('CleanJets')
self.matchedCleanJetHistos = JetHistograms('MatchedCleanJets')
self.unmatchedCleanJetHistos = JetHistograms('UnmatchedCleanJets')
## Pileup JetID
if self.cfg_ana.jetIdMva:
self.puidalgo = PileupJetIdNtupleAlgo(*self.cfg_ana.jetIdMva)
self.runMva = True
else:
self.puidalgo = PileupJetIdNtupleAlgo()
self.runMva = False
self.vtxBins = (0, 10, 15, 20, 30) ## (0,2,4,6,10,15,20,30,35)
self.vtxBinLabels = mkBinLabels(self.vtxBins)
self.ptBins = (20, 30, 50) ## (20,30,40,50,100)
self.etaBins = (0, 1.4, 2.5, 3.0)
self.puEtaLables = ["_barrel", "_endtk", "_endNOtk", "_fwd"]
reweight_f = TF1("f", "pol2(0)+expo(3)")
reweight_f.SetParameters(0.1955298, -0.003830591, 1.944794e-05,
4.649755, -0.1722024)
self.reweight = ("pt", reweight_f)
## PileUp histograms
if self.cfg_ana.doJetIdHisto:
# histograms for pileup jet identification variables
self.gluCleanHistosId = PileupJetHistograms(
"GluonMatchedCleanHistosId",
self.vtxBins,
self.ptBins,
self.etaBins,
etalabels=self.puEtaLables,
reweight=self.reweight)
self.quarkCleanHistosId = PileupJetHistograms(
"QuarkMatchedCleanHistosId",
self.vtxBins,
self.ptBins,
self.etaBins,
etalabels=self.puEtaLables,
reweight=self.reweight)
self.reweiMatchedCleanHistosId = PileupJetHistograms(
"ReweiMatchedCleanHistosId",
self.vtxBins,
self.ptBins,
self.etaBins,
etalabels=self.puEtaLables,
reweight=self.reweight)
self.unmatchedCleanHistosId = PileupJetHistograms(
"UnmatchedCleanHistosId",
self.vtxBins,
self.ptBins,
self.etaBins,
etalabels=self.puEtaLables)
### self.jetKin = []
### for vtx in self.vtxBinLabels:
### self.jetKin.append([])
### for eta in self.puEtaLables:
### self.jetKin[-1].append( JetHistograms('Jets%s%s' % (vtx,eta) ) )
if self.cfg_ana.dumpTree:
self.tree = TTree("tree", "tree")
self.tree.SetDirectory(self.file)
self.puidalgo.bookBranches(self.tree)
gROOT.ProcessLine(
"""struct MyTreeVars{ Int_t nvtx; Bool_t isMatched; Int_t jetFlavour; Float_t partonPt; Float_t genPt; Float_t genDr; }"""
)
from ROOT import MyTreeVars
self.treevars = MyTreeVars()
for i, j in ("nvtx", "I"), ("isMatched",
"O"), ("jetFlavour",
"I"), ("partonPt",
"F"), ("genPt",
"F"), ("genDr",
"F"):
self.tree.Branch(i, AddressOf(self.treevars, i),
"%s/%s" % (i, j))
self.h_nvtx = TH1F("h_nvtx", "", 50, 0, 50)
self.h_genjetspt = TH1F("h_genjetspt", "", 500, 0, 500)
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def process(self, iEvent, event):
#read all the handles defined beforehand
self.readCollections(iEvent)
jetEtaCut = 4.5
# get the vertexes
event.vertices = self.handles['vertices'].product()
self.h_nvtx.Fill(len(event.vertices))
event.vertexBin = int(len(event.vertices))
# get the jets in the jets variable
jets = self.handles['jets'].product()
# filter jets with some selections
event.jets = [
jet for jet in jets
if (abs(jet.eta()) < jetEtaCut and jet.pt() > self.cfg_ana.ptCut
and self.isPFLoose(jet))
]
self.jetHistos.fillEvent(event.jets)
try:
# get status 2 leptons
if 'leptons2' in self.mchandles:
event.genLeptons = map(GenParticle,
self.mchandles['leptons2'].product())
else:
event.genLeptons = [
lep for lep in self.mchandles['genParticles'].product()
if lep.status() == 3 and (abs(lep.pdgId()) == 11 or abs(
lep.pdgId()) == 13 or abs(lep.pdgId()) == 15)
]
except:
event.genLeptons = None
if event.genLeptons:
#FIXME why are there cases in which there's 4 or 6 leptons?
if len(event.genLeptons) != 2:
return
# in case I want to filter out taus
# 11, 13, 15 : e, u, T
# remove leptons from jets if closer than 0.2
event.cleanJets = cleanObjectCollection(event.jets,
event.genLeptons, 0.2)
else:
event.cleanJets = event.jets
### event.matchingCleanJets = matchObjectCollection2 (event.cleanJets, event.selGenJets, 0.25)
# assign to each jet its gen match (easy life :))
event.selGenJets = []
for jet in event.cleanJets:
try:
jet.gen = jet.genJet()
jet.gen.pt()
event.selGenJets.append(jet.gen)
except:
jet.gen = None
for jet in event.selGenJets:
self.h_genjetspt.Fill(jet.pt())
self.jetHistos.fillStats(len(event.selGenJets), len(event.jets))
### try:
### # get genJets
### event.genJets = map (GenJet, self.mchandles['genJets'].product ())
### event.selGenJets = event.genJets
### for jet in event.selGenJets :
### self.h_genjetspt.Fill (jet.pt ())
###
### # first stats plots
### self.jetHistos.fillStats (len (event.selGenJets), len (event.jets))
### except:
### pass
## run the PileupJetIdAlgo and attach the id to the jet
ijet = 0
for jet in event.cleanJets:
try:
jet.puIdentifier = self.puidalgo.computeIdVariables(
jet.sourcePtr().get(), 0., event.vertices[0], self.runMva)
except:
jet.puIdentifier = self.puidalgo.computeIdVariables(
jet, 0., event.vertices[0], self.runMva)
if self.cfg_ana.dumpTree:
## self.puidalgo.fillJet(jet.puIdentifier,ijet,0)
self.puidalgo.setIJetIEvent(ijet, 0)
self.treevars.nvtx = len(event.vertices)
self.treevars.isMatched = False
self.treevars.jetFlavour = -999
self.treevars.genPt = 0.
self.treevars.partonPt = 0.
self.treevars.genDr = -100.
if jet.gen:
self.treevars.isMatched = True
self.treevars.jetFlavour = jet.partonFlavour()
self.treevars.genPt = jet.gen.pt()
self.treevars.genDr = deltaR(jet.gen.eta(), jet.gen.phi(),
jet.eta(), jet.phi())
try:
self.treevars.partonPt = jet.genParton.pt()
except:
pass
self.tree.Fill()
ijet += 1
self.cleanJetHistos.fillEvent(event.cleanJets)
event.matchedCleanJets = [
jet for jet in event.cleanJets if jet.gen != None
]
event.unmatchedCleanJets = [
jet for jet in event.cleanJets if jet.gen == None
]
self.matchedCleanJetHistos.fillEvent(event.matchedCleanJets)
self.unmatchedCleanJetHistos.fillEvent(event.unmatchedCleanJets)
event.cleanGluJets = []
event.cleanQuarkJets = []
vtxbin = findBin(self.vtxBinLabels, len(event.vertices))
for jet in event.matchedCleanJets:
flav = abs(jet.partonFlavour())
if flav == 21:
event.cleanGluJets.append(jet)
elif flav > 0 and flav <= 3:
event.cleanQuarkJets.append(jet)
jet.weight = self.reweight[1](getattr(jet, self.reweight[0])())
etabin = findBin(self.etaBins, jet.eta())
### self.jetKin[vtxbin][etabin].fillJet(jet)
if self.cfg_ana.doJetIdHisto:
self.gluCleanHistosId.fillEvent(event.cleanGluJets, event.vertices)
self.quarkCleanHistosId.fillEvent(event.cleanQuarkJets,
event.vertices)
### self.matchedCleanHistosId.fillEvent(event.matchedCleanJets,event.vertices)
self.reweiMatchedCleanHistosId.fillEvent(event.matchedCleanJets,
event.vertices)
self.unmatchedCleanHistosId.fillEvent(event.unmatchedCleanJets,
event.vertices)
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def write(self):
from ROOT import gROOT
gROOT.SetBatch(True)
self.jetHistos.Write(self.file)
self.cleanJetHistos.Write(self.file)
self.matchedCleanJetHistos.Write(self.file)
self.unmatchedCleanJetHistos.Write(self.file)
if self.cfg_ana.doJetIdHisto:
self.gluCleanHistosId.summary()
self.gluCleanHistosId.Write(self.file)
self.quarkCleanHistosId.summary()
self.quarkCleanHistosId.Write(self.file)
self.reweiMatchedCleanHistosId.summary()
self.reweiMatchedCleanHistosId.Write(self.file)
### self.matchedCleanHistosId.Write(self.file)
self.unmatchedCleanHistosId.Write(self.file)
### for j in self.jetKin:
### for h in j:
### h.Write(self.file)
self.file.cd()
self.h_nvtx.Write()
self.h_genjetspt.Write()
if self.cfg_ana.dumpTree:
self.tree.Write()
self.file.Close()
def selectEvents(fileName,saveProbes=False,saveSummary=False,outputDir='./',xsec=-1,correctionsMap={}):
gSystem.ExpandPathName(fileName)
file=TFile.Open(fileName)
#exclusivity of triggers per PD
eTriggersOnly = ('SingleEle' in fileName)
muTriggersOnly = ('SingleMu' in fileName)
#normalizations and corrections
origEvents=1.0
puWeightsGr=None
if xsec>0 :
origEvents=file.Get('smDataAnalyzer/cutflow').GetBinContent(1)
if origEvents==0 :
print '[Warning] 0 initial events ?'
#derive pileup weights
origPileup=file.Get('smDataAnalyzer/pileup')
try:
dataPileupFile=TFile.Open(correctionsMap['pu'])
dataPileup=dataPileupFile.Get('pileup')
normF=origPileup.Integral()/dataPileup.Integral()
if normF>0 :
puWeightsGr=TGraph()
for xbin in xrange(1,origPileup.GetXaxis().GetNbins()+1) :
iweight=1.0
if origPileup.GetBinContent(xbin)>0 :
iweight=normF*dataPileup.GetBinContent(xbin)/origPileup.GetBinContent(xbin)
puWeightsGr.SetPoint( puWeightsGr.GetN(), origPileup.GetXaxis().GetBinCenter(xbin), iweight )
dataPileupFile.Close()
except :
print 'No data pileup file provided or other error occurred. If you wish add -w pu,pu_file.root'
jecCorrector=None
jecUncertainty=None
try:
prefix='Data'
if xsec>0 : prefix='MC'
jecDir=correctionsMap['jec']
gSystem.ExpandPathName(jecDir)
jetCorLevels='L1FastJet'
jetCorFiles=jecDir+'/'+prefix+'_L1FastJet_AK5PFchs.txt'
jetCorLevels=jetCorLevels+':L2Relative'
jetCorFiles=jetCorFiles+':'+jecDir+'/'+prefix+'_L2Relative_AK5PFchs.txt'
jetCorLevels=jetCorLevels+':L3Absolute'
jetCorFiles=jetCorFiles+':'+jecDir+'/'+prefix+'_L3Absolute_AK5PFchs.txt'
#if prefix=='Data':
# jetCorLevels=jetCorLevels+':L2L3Residual'
# jetCorFiles=jetCorFiles+':'+jecDir+'/'+prefix+'_L2L3Residual_AK5PFchs.txt'
jecCorrector=FactorizedJetCorrector(jetCorLevels,jetCorFiles)
print 'Jet energy corrector initialized with levels ',jetCorLevels,' for ',prefix
if prefix=='MC':
jecUncertainty=JetCorrectionUncertainty(jecDir+"/"+prefix+"_Uncertainty_AK5PFchs.txt")
print 'Jet uncertainty is ',jecUncertainty
except Exception as e:
print '[Error]',e
tree=file.Get("smDataAnalyzer/data")
nev = tree.GetEntries()
outUrl=outputDir+'/'+os.path.basename(fileName)
monitor=Monitor(outUrl)
#same the initial normalization and cross section
monitor.addValue(origEvents,'iniEvents')
monitor.addValue(xsec,'crossSection')
#some basic histograms
monitor.addHisto('nvtx', ';Vertices;Events', 50,0,50)
monitor.addHisto('nvtxraw', ';Vertices;Events', 50,0,50)
monitor.addHisto('vmass', ';Mass [GeV];Events', 50,0,250)
monitor.addHisto('vmt', ';Transverse mass [GeV];Events', 50,0,250)
monitor.addHisto('vpt', ';Boson transverse momentum [GeV];Events',50,0,250)
monitor.addHisto('leg1pt', ';Transverse momentum [GeV];Events', 50,0,250)
monitor.addHisto('leg2pt', ';Transverse momentum [GeV];Events', 50,0,250)
monitor.addHisto('leg1iso', ';Relative isolation;Events', 50,0,0.5)
monitor.addHisto('leg2iso', ';Relative isolation;Events', 50,0,0.5)
#save a summary ntuple for analysis
summaryTuple=None
if saveSummary :
varList='cat:weight:nvtx:njets'
varList=varList+':v_mass:v_mt:v_pt:genv_mass:genv_pt'
varList=varList+':leg1_pt:leg1_eta:leg1_phi:genleg1_pt:leg1_relIso'
varList=varList+':leg2_pt:leg2_eta:leg2_phi:genleg2_pt:leg2_relIso'
varList=varList+':sumEt:ht'
varList=varList+':met_lesup:met_lesdown:met_jesup:met_jesdown:met_jerup:met_jerdown:met_umetup:met_umetdown'
summaryTuple=TNtuple('data','summary',varList)
summaryTuple.SetDirectory(0)
monitor.addObject(summaryTuple)
#save a dedicated ntuple for Tag and Probe
probesTuple=None
probesId = array.array( 'f', [ 0 ] )
probesPt = array.array( 'f', [ 0 ] )
probesEta = array.array( 'f', [ 0 ] )
probesPhi = array.array( 'f', [ 0 ] )
probesNvtx = array.array( 'f', [ 0 ] )
probesMass = array.array( 'f', [ 0 ] )
probesIsMatched = array.array( 'i', [0] )
probesPassLoose = array.array( 'i', [ 0 ] )
probesPassTight = array.array( 'i', [ 0 ] )
probesFireTrigger = array.array( 'i', [ 0 ] )
if saveProbes :
probesTuple=TTree('tandp','summary for tandp')
probesTuple.Branch( 'id', probesId, 'id/F' )
probesTuple.Branch( 'pt', probesPt, 'pt/F' )
probesTuple.Branch( 'eta', probesEta, 'eta/F' )
probesTuple.Branch( 'phi', probesPhi, 'phi/F' )
probesTuple.Branch( 'nvtx', probesNvtx, 'nvtx/F' )
probesTuple.Branch( 'mass', probesMass, 'mass/F' )
probesTuple.Branch( 'isMatched', probesIsMatched, 'isMatched/I' )
probesTuple.Branch( 'passLoose', probesPassLoose, 'passLoose/I' )
probesTuple.Branch( 'passTight', probesPassTight, 'passTight/I' )
probesTuple.Branch( 'fireTrigger', probesFireTrigger, 'fireTrigger/I' )
probesTuple.SetDirectory(0)
monitor.addObject(probesTuple)
#
# LOOP OVER THE EVENTS
#
for iev in xrange(0,nev):
tree.GetEntry(iev)
if iev%10000 == 0 :
sys.stdout.write("\r[ %d/100 ] completed" %(100.*iev/nev))
sys.stdout.flush()
#check mc truth (select V bosons from the hard process
genBosonP4=TLorentzVector(0,0,0,0)
genNeutP4=TLorentzVector(0,0,0,0)
for g in xrange(0,tree.mcn):
if tree.mc_status[g]!=3 : continue
genP4=TLorentzVector(tree.mc_px[g],tree.mc_py[g],tree.mc_pz[g],tree.mc_en[g])
if abs(tree.mc_id[g])==12 or abs(tree.mc_id[g])==14 or abs(tree.mc_id[g])==14 : genNeutP4=genNeutP4+genP4
if abs(tree.mc_id[g])!=23 and abs(tree.mc_id[g])!=24 : continue
genBosonP4=genP4
#get triggers that fired
eFire,mFire,emFire=decodeTriggerWord(tree.tbits)
if eTriggersOnly : mFire=False
if muTriggersOnly : eFire=False
#select the leptons
leptonCands=[]
validTags=[]
lepSums=[TLorentzVector(0,0,0,0)]*3
lepFlux=TLorentzVector(0,0,0,0)
for l in xrange(0,tree.ln) :
lep=LeptonCand(tree.ln_id[l],tree.ln_px[l],tree.ln_py[l],tree.ln_pz[l],tree.ln_en[l])
if lep.p4.Pt()<20 : continue
if abs(tree.ln_id[l])==11 :
if math.fabs(lep.p4.Eta())>2.5 : continue
if math.fabs(lep.p4.Eta())>1.4442 and math.fabs(lep.p4.Eta())<1.566 : continue
if abs(tree.ln_id[l])==13 :
if math.fabs(lep.p4.Eta())>2.1 : continue
relIso, isLoose, isLooseIso, isTight, isTightIso = selectLepton(tree.ln_id[l],tree.ln_idbits[l],tree.ln_gIso[l],tree.ln_chIso[l],tree.ln_nhIso[l],tree.ln_puchIso[l],lep.p4.Pt())
lep.selectionInfo(relIso,isLoose, isLooseIso, isTight, isTightIso)
lep.triggerInfo(tree.ln_Tbits[l])
#check the generator level information
genMatchIdx=tree.ln_genid[l]
if genMatchIdx < tree.mcn :
lep.genMatch(tree.mc_id[genMatchIdx],tree.mc_px[genMatchIdx],tree.mc_py[genMatchIdx],tree.mc_pz[genMatchIdx],tree.mc_en[genMatchIdx])
else :
lep.genMatch(0,0,0,0,0)
leptonCands.append(lep)
if not saveProbes: continue
if not isTight or not isTightIso or lep.Tbits==0 : continue
if abs(lep.id)==11 and not eFire: continue
if abs(lep.id)==13 and not mFire: continue
validTags.append( len(leptonCands)-1 )
lepSums[1]=lepSums[1]+lep.getP4('lesup')-lep.p4
lepSums[2]=lepSums[2]+lep.getP4('lesdown')-lep.p4
lepFlux=lepFlux+lep.p4
#check if probes tree should be saved
if saveProbes and len(validTags)>0:
# choose a random tag
tagIdx=random.choice(validTags)
tag=leptonCands[tagIdx]
#find probe
probe=None
for l in xrange(0,len(leptonCands)) :
if l==tagIdx: continue
if abs(tag.id)!=abs(leptonCands[l].id) : continue
probe=leptonCands[l]
break
#for electrons save superclusters if probe is not found
matchToEle=1
#if abs(tag.id)==11 and probe is None :
# matchToEle=0
# for sc in xrange(0,tree.scn) :
# sc_en=tree.scn_e[sc]
# sc_eta=tree.scn_eta[sc]
# sc_phi=tree.scn_phi[sc]
# sc_pt=sc_en/math.cosh(sc_eta)
# sc_p4=TLorentzVector(0,0,0,0)
# sc_p4.SetPtEtaPhiE(sc_pt,sc_eta,sc_phi,sc_en)
# lscp4=tag.p4+sc_p4
# if math.fabs(lscp4.M()-91)>30 : continue
# scCand=LeptonCand(tag.id,sc_p4.Px(),sc_p4.Py(),sc_p4.Pz(),sc_p4.E())
# scCand.selectionInfo(0,0,0,0,0)
# scCand.triggerInfo(0)
# probe=scCand
# break
if abs(tag.id)==13 : matchToEle=0
#save info
if probe is not None:
tpp4=tag.p4+probe.p4
if math.fabs(tpp4.M()-91)<30 :
probesId[0]=probe.id
probesPt[0]=probe.p4.Pt()
probesEta[0]=probe.p4.Eta()
probesPhi[0]=probe.p4.Phi()
probesNvtx[0]=tree.nvtx
probesMass[0]=tpp4.M()
probesIsMatched[0]=(probe.genId!=0)
probesPassLoose[0]=(probe.passLoose and probe.passLooseIso)
probesPassTight[0]=(probe.passTight and probe.passTightIso)
probesFireTrigger[0]=(probe.Tbits>0)
probesTuple.Fill()
#jets
selJets=[]
jetSums=[TLorentzVector(0,0,0,0)]*5
jetFlux=TLorentzVector(0,0,0,0)
ht=0
for j in xrange(0,tree.jn) :
jet=JetCand(tree.jn_px[j],tree.jn_py[j],tree.jn_pz[j],tree.jn_en[j],tree.jn_area[j],tree.jn_torawsf[j])
#cross clean with loose isolated leptons
overlapFound=False
for l in leptonCands:
if not l.passLoose or not l.passLooseIso : continue
dR=jet.p4.DeltaR(l.p4)
if dR>0.4 : continue
overlapFound=True
break
if overlapFound: continue
#very loose kinematics cuts
if math.fabs(jet.p4.Eta())>4.7 or jet.p4.Pt()<10 : continue
#save it
jet.genMatch(tree.jn_genpx[j],tree.jn_py[j],tree.jn_pz[j],tree.jn_en[j],tree.jn_genid[j],tree.jn_genflav[j])
jet.updateJEC(jecCorrector,jecUncertainty,tree.rho,tree.nvtx)
selJets.append(jet)
#account for all the corrections you have applied
jetSums[0]=jetSums[0] + jet.getCorrectedJet() - jet.getCorrectedJet('raw')
jetSums[1]=jetSums[1] + jet.getCorrectedJet('jesup') - jet.getCorrectedJet()
jetSums[2]=jetSums[2] + jet.getCorrectedJet('jesdown') - jet.getCorrectedJet()
jetSums[3]=jetSums[3] + jet.getCorrectedJet('jerup') - jet.getCorrectedJet()
jetSums[4]=jetSums[4] + jet.getCorrectedJet('jerdown') - jet.getCorrectedJet()
jetFlux=jetFlux+jet.p4
ht=ht+jet.p4.Pt()
# met
metCand=METCand(tree.met_pt[0]*math.cos(tree.met_phi[0]),tree.met_pt[0]*math.sin(tree.met_phi[0]),0,tree.met_pt[0])
metCand.genMatch(genNeutP4.Px(),genNeutP4.Py(),genNeutP4.Pz(),genNeutP4.E())
metCand.addSumEts(tree.met_sumet[0], tree.met_chsumet[0])
metCand.addJetCorrections(jetSums)
metCand.addLeptonCorrections(lepSums)
unclFlux=-(metCand.p4+lepFlux+jetFlux)
unclSums=[TLorentzVector(0,0,0,0),unclFlux*0.10,unclFlux*(-0.10)]
metCand.addUnclusteredCorrections(unclSums)
#build the candidate
vCand=buildVcand(eFire,mFire,emFire,leptonCands,metCand)
if vCand is None : continue
#prepare to save
weight=1.0
if puWeightsGr is not None:
weight=puWeightsGr.Eval(tree.ngenITpu)
#show isolations
for ileg in [0,1]:
hname='leg'+str(ileg+1)+'iso'
lid=''
if abs(vCand.m_legs[ileg].id)==11 : lid='e'
elif abs(vCand.m_legs[ileg].id)==13 : lid='mu'
else : continue
monitor.fill(hname,[lid],vCand.m_legs[ileg].relIso,weight)
tags=[vCand.tag]
monitor.fill('nvtxraw',tags, tree.nvtx, 1.0)
monitor.fill('nvtx', tags, tree.nvtx, weight)
monitor.fill('vmass', tags, vCand.p4.M(), weight)
monitor.fill('vpt', tags, vCand.p4.Pt(), weight)
monitor.fill('leg1pt', tags, vCand.m_legs[0].p4.Pt(), weight)
monitor.fill('leg2pt', tags, vCand.m_legs[1].p4.Pt(), weight)
for var in ['','lesup','lesdown','jesup','jesdown','jerup','jerdown','umetup','umetdown']:
mtVar=vCand.computeMt(var)
monitor.fill('vmt', [vCand.tag+var], mtVar, weight)
if saveSummary :
values=[
vCand.id, weight, tree.nvtx, len(selJets),
vCand.p4.M(), vCand.mt, vCand.p4.Pt(), genBosonP4.M(), genBosonP4.Pt(),
vCand.m_legs[0].p4.Pt(),vCand.m_legs[0].p4.Eta(),vCand.m_legs[0].p4.Phi(), vCand.m_legs[0].genP4.Pt(), vCand.m_legs[0].relIso,
vCand.m_legs[1].p4.Pt(),vCand.m_legs[1].p4.Eta(),vCand.m_legs[1].p4.Phi(), vCand.m_legs[1].genP4.Pt(), vCand.m_legs[1].relIso,
metCand.sumet, ht,
metCand.p4Vars['lesup'].Pt(),metCand.p4Vars['lesdown'].Pt(),metCand.p4Vars['jesup'].Pt(),metCand.p4Vars['jesdown'].Pt(),metCand.p4Vars['jerup'].Pt(),metCand.p4Vars['jerdown'].Pt(),metCand.p4Vars['umetup'].Pt(),metCand.p4Vars['umetdown'].Pt()
]
summaryTuple.Fill(array.array("f",values))
file.Close()
monitor.close()
