def load_tree(infiles):
from rootpy.tree import TreeChain
from rootpy.ROOT import gROOT
gROOT.SetBatch(True)
print('[INFO] Opening files: {0}'.format(infiles))
tree = TreeChain('ntupler/tree', infiles)
tree.define_collection(name='hits', prefix='vh_', size='vh_size')
tree.define_collection(name='simhits', prefix='vc_', size='vc_size')
tree.define_collection(name='tracks', prefix='vt_', size='vt_size')
tree.define_collection(name='particles', prefix='vp_', size='vp_size')
return tree
class MuonTypeLJEvents(object):
def __init__(self, files=None, type='MC', maxevents=-1):
if type.upper() not in ['MC', 'DATA']:
raise ValueError("Argument `type` need to be MC/DATA")
self.Type = type
self.MaxEvents = maxevents
if not files: raise ValueError("Argument `files` need to be non-empty")
if isinstance(files, str): files = [
files,
]
self.Chain = TreeChain('ffNtuplizer/ffNtuple', files)
## register collections ###
self.Chain.define_collection('pvs', prefix='pv_', size='pv_n')
self.Chain.define_collection('muons', prefix='muon_', size='muon_n')
self.Chain.define_collection('dsamuons',
prefix='dsamuon_',
size='dsamuon_n')
self.Chain.define_collection('ak4jets',
prefix='akjet_ak4PFJetsCHS_',
size='akjet_ak4PFJetsCHS_n')
self.Chain.define_collection('leptonjets',
prefix='pfjet_',
size='pfjet_n',
mix=LeptonJetMix)
self.Chain.define_collection('trigobjs',
prefix='trigobj_',
size='trigobj_n')
self.Chain.define_object('hlt', prefix='HLT_')
self.Chain.define_object('metfilters', prefix='metfilters_')
self.Chain.define_object('cosmicveto', prefix='cosmicveto_')
self.Histos = {}
self.LookupWeight = root_open(
os.path.join(
os.getenv('CMSSW_BASE'),
'src/FireROOT/Analysis/data/puWeights_10x_56ifb.root')).Get(
'puWeights')
self.Scale = 1.
def bookHisto(self, name, hist):
self.Histos[name] = hist
def setScale(self, scale):
self.Scale = scale
def process(self):
for i, event in enumerate(self.Chain):
if self.MaxEvents > 0 and i > self.MaxEvents: break
## event-level mask ##
if not event.cosmicveto.result: continue
if not event.metfilters.PrimaryVertexFilter: continue
aux = {}
## event weight ##
aux['wgt'] = self.Scale
if self.Type == 'MC':
aux['wgt'] *= event.weight # gen weight
aux['wgt'] *= self.LookupWeight.GetBinContent(
self.LookupWeight.GetXaxis().FindBin(
event.trueInteractionNum)) ## pileup correction
leptonjets = [
lj for lj in event.leptonjets if lj.passSelection(event)
]
leptonjets.sort(key=lambda lj: lj.p4.pt(), reverse=True)
leptonjets = leptonjets[:2]
muontypeljs = [lj for lj in leptonjets if lj.isMuonType()]
egmtypeljs = [lj for lj in leptonjets if lj.isEgmType()]
# if not muontypeljs: continue
aux['muontype'] = muontypeljs
aux['egmtype'] = egmtypeljs
aux['leptonjets'] = leptonjets
looseMuonIdx, mediumMuonIdx = [], []
for i, mu in enumerate(event.muons):
if mu.p4.pt() < 5: continue
if abs(mu.p4.eta()) > 2.4: continue
if (mu.selectors & (1 << 0)) != (1 << 0): continue # ID-loose
if (mu.selectors & (1 << 7)) != (1 << 7): continue # Iso-loose
looseMuonIdx.append(i)
if (mu.selectors & (1 << 1)) != (1 << 1): continue # ID-medium
mediumMuonIdx.append(i)
if not mediumMuonIdx: continue
muonpairs = []
for m in mediumMuonIdx:
for l in looseMuonIdx:
if m == l: continue
if (l, m) in muonpairs: continue
muonpairs.append((m, l))
if not muonpairs: continue
aux['muonpairs'] = muonpairs
self.processEvent(event, aux)
def processEvent(self, event, aux):
"""To be override by daughter class"""
pass
@property
def histos(self):
return self.Histos
class Events(object):
def __init__(self,
files=None,
outname=None,
type='MC',
dtag='',
maxevents=-1,
channel=['4mu', '2mu2e'],
ctau=None,
chargedlj=False):
if type.upper() not in ['MC', 'DATA']:
raise ValueError("Argument `type` need to be MC/DATA")
self.OutName = outname
self.Type = type.upper()
self.ChargedLJ = chargedlj
self.MaxEvents = maxevents
self.Channel = channel
self.Dtag = dtag
self.Ctau = ctau
__signal_sample_param = dict(
[substr.split('-') for substr in self.Dtag.split('_')])
self.SignalParam = {
k.upper(): float(v.replace('p', '.'))
for k, v in __signal_sample_param.items()
}
if not files: raise ValueError("Argument `files` need to be non-empty")
if isinstance(files, str): files = [
files,
]
self.Chain = TreeChain('ffNtuplizer/ffNtuple', files)
### register collections ###
# self.Chain.define_collection('pvs', prefix='pv_', size='pv_n')
self.Chain.define_collection('electrons',
prefix='electron_',
size='electron_n')
self.Chain.define_collection('muons', prefix='muon_', size='muon_n')
self.Chain.define_collection('dsamuons',
prefix='dsamuon_',
size='dsamuon_n')
self.Chain.define_collection('photons',
prefix='photon_',
size='photon_n')
self.Chain.define_collection('ak4jets',
prefix='akjet_ak4PFJetsCHS_',
size='akjet_ak4PFJetsCHS_n')
self.Chain.define_collection('hftagscores',
prefix='hftagscore_',
size='hftagscore_n')
self.Chain.define_collection('leptonjets',
prefix='pfjet_',
size='pfjet_n',
mix=LeptonJetMix)
self.Chain.define_collection('ljsources',
prefix='ljsource_',
size='ljsource_n')
self.Chain.define_collection('cosmicmuons',
prefix='cosmicmuon_',
size='cosmicmuon_n')
self.Chain.define_collection('trigobjs',
prefix='trigobj_',
size='trigobj_n')
# self.Chain.define_collection('',)
self.Chain.define_object('hlt', prefix='HLT_')
self.Chain.define_object('metfilters', prefix='metfilters_')
self.Chain.define_object('cosmicveto', prefix='cosmicveto_')
self.Triggers = [
"DoubleL2Mu23NoVtx_2Cha",
"DoubleL2Mu23NoVtx_2Cha_NoL2Matched",
"DoubleL2Mu23NoVtx_2Cha_CosmicSeed",
"DoubleL2Mu23NoVtx_2Cha_CosmicSeed_NoL2Matched",
"DoubleL2Mu25NoVtx_2Cha_Eta2p4",
"DoubleL2Mu25NoVtx_2Cha_CosmicSeed_Eta2p4",
]
#self.addTRG = [
# "DoubleL2Mu23NoVtx_2Cha",]
self.Histos = {}
for chan in channel:
self.Histos['{}/cutflow'.format(chan)] = ROOT.Hist(
20, 0, 20, title='cutflow', drawstyle='hist')
self.KeepCutFlow = False
self.RawCutFlow = False
self.LookupWeight = root_open(
os.path.join(
os.getenv('CMSSW_BASE'),
'src/FireROOT/Analysis/data/PUWeights_2018.root')).Get(
'puWeights')
self.LookupMuonSFLowpT = root_open(
os.path.join(os.getenv('CMSSW_BASE'),
'src/FireROOT/Analysis/data/mu_Loose_pt7.root')).Get(
'ratio_syst')
self.LookupMuonSF = root_open(
os.path.join(os.getenv('CMSSW_BASE'),
'src/FireROOT/Analysis/data/RunABCD_SF_ID.root')).Get(
'NUM_LooseID_DEN_TrackerMuons_pt_abseta_syst')
self.LookupElectronSF = root_open(
os.path.join(
os.getenv('CMSSW_BASE'),
'src/FireROOT/Analysis/data/2018_ElectronLoose.root')).Get(
'EGamma_SF2D')
self.LookupPhotonSF = root_open(
os.path.join(
os.getenv('CMSSW_BASE'),
'src/FireROOT/Analysis/data/2018_PhotonsLoose.root')).Get(
'EGamma_SF2D')
self.Scale = 1.
def setTriggers(self, triggers):
self.Triggers = triggers
def addTrigger(self, trigger):
self.Triggers.append(trigger)
def bookHisto(self, name, hist):
self.Histos[name] = hist
def setScale(self, scale):
self.Scale = scale
def process(self):
for i, event in enumerate(self.Chain):
if self.MaxEvents > 0 and i > self.MaxEvents: break
## event weight ##
aux = {}
aux['wgt'] = self.Scale
if self.Type == 'MC':
aux['wgt'] *= event.weight # gen weight
aux['wgt'] *= self.LookupWeight.GetBinContent(
self.LookupWeight.GetXaxis().FindBin(
event.trueInteractionNum)) ## pileup correction
for ch in self.Channel:
if self.RawCutFlow:
self.Histos['{}/cutflow'.format(ch)].Fill(0)
else:
self.Histos['{}/cutflow'.format(ch)].Fill(0, aux['wgt'])
## trigger ##
#if not any([getattr(event.hlt, t) for t in self.Triggers]): continue
#if not any([getattr(event.hlt, t) for t in self.addTRG]): continue
for ch in self.Channel:
if self.RawCutFlow:
self.Histos['{}/cutflow'.format(ch)].Fill(1)
else:
self.Histos['{}/cutflow'.format(ch)].Fill(1, aux['wgt'])
## 2 leptonjets in channel definition ##
leptonjets = [lj for lj in event.leptonjets]
if len(leptonjets) < 2: continue
#print len(leptonjets)#js
#LJ2 = none
leptonjets.sort(key=lambda lj: lj.p4.pt(), reverse=True)
LJ0 = leptonjets[0]
LJ1 = leptonjets[1]
#LJ2 = leptonjets[2]
#if len(event.leptonjets)>2:#
#LJ2 = leptonjets[2]#
#aux['lj2'] = LJ2
if self.ChargedLJ:
if not LJ0.passChargedSelection(event): continue
if not LJ1.passChargedSelection(event): continue
#if not LJ2.passChargedSelection(event): continue
else:
if not LJ0.passSelection(event): continue
if not LJ1.passSelection(event): continue
#if not LJ2.passSelection(event): continue
if LJ0.isMuonType() and LJ1.isMuonType(): aux['channel'] = '4mu'
elif LJ0.isMuonType() and LJ1.isEgmType(): aux['channel'] = '2mu2e'
elif LJ0.isEgmType() and LJ1.isMuonType(): aux['channel'] = '2mu2e'
else: continue
aux['lj0'] = LJ0
aux['lj1'] = LJ1
#aux['lj2'] = LJ2
if self.Type == 'MC':
aux['sf_electron'] = 1.
aux['sf_electron_up'] = 1.
aux['sf_electron_low'] = 1.
aux['sf_photon'] = 1.
aux['sf_photon_up'] = 1.
aux['sf_photon_low'] = 1.
aux['sf_pfmuon'] = 1.
aux['sf_pfmuon_up'] = 1.
aux['sf_pfmuon_low'] = 1.
for lj in [LJ0, LJ1]:
## muon scale factor
for i in lj.pfcand_pfmuonIdx:
_pfmu_p4 = event.muons[i].p4
pt, eta = _pfmu_p4.pt(), _pfmu_p4.eta()
if pt >= 20:
xbin = self.LookupMuonSF.xaxis.FindBin(pt)
xbin = min(max(xbin, 1),
self.LookupMuonSF.nbins(0))
ybin = self.LookupMuonSF.yaxis.FindBin(abs(eta))
sf = self.LookupMuonSF.GetBinContent(xbin, ybin)
err_up = self.LookupMuonSF.GetBinErrorUp(
xbin, ybin)
err_lo = self.LookupMuonSF.GetBinErrorLow(
xbin, ybin)
else:
for i in range(self.LookupMuonSFLowpT.num_points):
x = self.LookupMuonSFLowpT.x(i)
xh = x + self.LookupMuonSFLowpT.xerrh(i)
xl = x - self.LookupMuonSFLowpT.xerrl(i)
if xl <= eta and eta <= xh:
sf = self.LookupMuonSFLowpT.y(i)
err_up = self.LookupMuonSFLowpT.yerrh(i)
err_lo = self.LookupMuonSFLowpT.yerrl(i)
break
aux['wgt'] *= sf
aux['sf_pfmuon'] *= sf
aux['sf_pfmuon_up'] *= sf + err_up
aux['sf_pfmuon_low'] *= sf - err_lo
## NOTE DSA scale factor, nothing for now
for i in lj.pfcand_dsamuonIdx:
#print dsamu.pt.P4()
sf = 1.
aux['wgt'] *= sf
## electron scale factor
for i in lj.pfcand_electronIdx:
_electron = event.electrons[i]
xbin = self.LookupElectronSF.xaxis.FindBin(
_electron.scEta)
ybin = self.LookupElectronSF.xaxis.FindBin(
_electron.p4.pt())
ybin = min(max(ybin, 1),
self.LookupElectronSF.nbins(1))
sf = self.LookupElectronSF.GetBinContent(xbin, ybin)
aux['wgt'] *= sf
aux['sf_electron'] *= sf
aux['sf_electron_up'] *= sf + self.LookupElectronSF.GetBinErrorUp(
xbin, ybin)
aux['sf_electron_low'] *= sf - self.LookupElectronSF.GetBinErrorLow(
xbin, ybin)
## photon scale factor
for i in lj.pfcand_photonIdx:
_photon = event.photons[i]
xbin = self.LookupPhotonSF.xaxis.FindBin(_photon.scEta)
ybin = self.LookupPhotonSF.xaxis.FindBin(
_photon.p4.pt())
ybin = min(max(ybin, 1), self.LookupPhotonSF.nbins(1))
sf = self.LookupPhotonSF.GetBinContent(xbin, ybin)
aux['wgt'] *= sf
aux['sf_photon'] *= sf
aux['sf_photon_up'] *= sf + self.LookupPhotonSF.GetBinErrorUp(
xbin, ybin)
aux['sf_photon_low'] *= sf - self.LookupPhotonSF.GetBinErrorLow(
xbin, ybin)
aux['wgt_electron_up'] = aux['wgt'] / aux['sf_electron'] * aux[
'sf_electron_up']
aux['wgt_electron_low'] = aux['wgt'] / aux[
'sf_electron'] * aux['sf_electron_low']
aux['wgt_photon_up'] = aux['wgt'] / aux['sf_photon'] * aux[
'sf_photon_up']
aux['wgt_photon_low'] = aux['wgt'] / aux['sf_photon'] * aux[
'sf_photon_low']
aux['wgt_pfmuon_up'] = aux['wgt'] / aux['sf_pfmuon'] * aux[
'sf_pfmuon_up']
aux['wgt_pfmuon_low'] = aux['wgt'] / aux['sf_pfmuon'] * aux[
'sf_pfmuon_low']
# for t, pt, eta in zip(list(lj.pfcand_type), list(lj.pfcand_pt), list(lj.pfcand_eta)):
# ## muon scale factor, DSA same as muon for now
# if t==3 or t==8:
# xbin = self.LookupMuonSF.xaxis.FindBin(pt)
# xbin = min(max(xbin, 1), self.LookupMuonSF.nbins(0))
# ybin = self.LookupMuonSF.yaxis.FindBin(abs(eta))
# sf = self.LookupMuonSF.GetBinContent(xbin, ybin)
# aux['wgt'] *= sf
# ## electron scale factor, using eta instead of SC eta for now
# if t==2:
# xbin = self.LookupElectronSF.xaxis.FindBin(eta)
# ybin = self.LookupElectronSF.xaxis.FindBin(pt)
# ybin = min(max(ybin, 1), self.LookupElectronSF.nbins(1))
# sf = self.LookupElectronSF.GetBinContent(xbin, ybin)
# aux['wgt'] *= sf
# ## photon scale factor, using eta instead of SC eta for now
# if t==4:
# xbin = self.LookupPhotonSF.xaxis.FindBin(eta)
# ybin = self.LookupPhotonSF.xaxis.FindBin(pt)
# ybin = min(max(ybin, 1), self.LookupPhotonSF.nbins(1))
# sf = self.LookupPhotonSF.GetBinContent(xbin, ybin)
# aux['wgt'] *= sf
for ch in self.Channel:
if self.RawCutFlow:
self.Histos['{}/cutflow'.format(ch)].Fill(2)
else:
self.Histos['{}/cutflow'.format(ch)].Fill(2, aux['wgt'])
## event-level mask ##
if not event.metfilters.PrimaryVertexFilter: continue
for ch in self.Channel:
if self.RawCutFlow:
self.Histos['{}/cutflow'.format(ch)].Fill(3)
else:
self.Histos['{}/cutflow'.format(ch)].Fill(3, aux['wgt'])
nppCOSMIC, cosmicShowerTagged = globalCosmicShower(
event.cosmicmuons, aux['channel'])
if cosmicShowerTagged: continue
for ch in self.Channel:
if self.RawCutFlow:
self.Histos['{}/cutflow'.format(ch)].Fill(4)
else:
self.Histos['{}/cutflow'.format(ch)].Fill(4, aux['wgt'])
self.processEvent(event, aux)
def processEvent(self, event, aux):
"""To be override by daughter class"""
pass
def postProcess(self):
if self.KeepCutFlow:
labels = [
'total', 'trigger_pass', 'leptonjet_ge2', 'pv_good',
'cosmicveto_pass'
]
for ch in self.Channel:
xaxis = self.Histos['{}/cutflow'.format(ch)].axis(0)
for i, s in enumerate(labels, start=1):
xaxis.SetBinLabel(i, s)
# binNum., labAngel, labSize, labAlign, labColor, labFont, labText
xaxis.ChangeLabel(i, 315, -1, 11, -1, -1, s)
else:
for ch in self.Channel:
self.Histos.pop('{}/cutflow'.format(ch))
@property
def histos(self):
return self.Histos
@property
def channel(self):
return self.Channel
elif mystate == 1:
tree_name_i = '/home/jlow/L1MuonTrigger/CRAB3/P2_9_2_3_patch1/crab_projects/crab_ntuple_SingleNeutrino_PU200/results/ntuple_SingleNeutrino_PU200_%i.root'
tree = TreeChain('ntupler/tree',
[(tree_name_i % (i + 1)) for i in range(50)])
else:
raise Exception("Unexpected state: %i" % mystate)
maxEvents = -1
#maxEvents = 2000
# ROOT globals
gROOT.SetBatch(batch_mode)
# Define collection
tree.define_collection(name='hits', prefix='vh_', size='vh_size')
tree.define_collection(name='tracks', prefix='vt_', size='vt_size')
tree.define_collection(name='genparticles', prefix='vp_', size='vp_size')
# Enums
kDT, kCSC, kRPC, kGEM, kTT = 0, 1, 2, 3, 20
# Lambdas
deg_to_rad = lambda x: x * np.pi / 180.
rad_to_deg = lambda x: x * 180. / np.pi
# Functions
def delta_phi(lhs, rhs): # in degrees
deg = lhs - rhs
def work(self):
# trigger config tool to read trigger info in the ntuples
trigger_config = get_trigger_config()
OutputModel = (RecoTauBlock + EventVariables + SkimExtraModel +
TrueTauBlock)
onfilechange = []
# update the trigger config maps on every file change
onfilechange.append((update_trigger_config, (trigger_config,)))
cutflow = Hist(2, 0, 2, name='cutflow', type='D')
# initialize the TreeChain of all input files (each containing one tree named self.metadata.treename)
chain = TreeChain(self.metadata.treename,
files=self.files,
events=self.events,
cache=True,
cache_size=10000000,
learn_entries=30,
onfilechange=onfilechange)
# create output tree
self.output.cd()
tree = Tree(name='higgstautauhh', model=OutputModel)
copied_variables = ['actualIntPerXing',
'averageIntPerXing',
'RunNumber',
'EventNumber',
'lbn']
tree.set_buffer(
chain.buffer,
branches=copied_variables,
create_branches=True,
visible=False)
chain.always_read(copied_variables)
# set the event filters
event_filters = EventFilterList([
#Triggers(
# datatype=self.metadata.datatype,
# year=YEAR,
# skim=False),
PriVertex(),
LArError(),
LArHole(datatype=self.metadata.datatype),
JetCleaning(
datatype=self.metadata.datatype,
year=YEAR),
TauAuthor(1),
TauHasTrack(1),
TauPT(1, thresh=25 * GeV),
TauEta(1),
TauCrack(1),
TauLArHole(1),
#TauTriggerMatch(
# config=trigger_config,
# year=YEAR,
# datatype=self.metadata.datatype,
# skim=False,
# tree=tree,
# min_taus=1),
])
self.filters['event'] = event_filters
chain.filters += event_filters
# define tree collections
chain.define_collection(name="taus", prefix="tau_", size="tau_n", mix=TauFourMomentum)
chain.define_collection(name="taus_EF", prefix="trig_EF_tau_",
size="trig_EF_tau_n", mix=TauFourMomentum)
# jet_* etc. is AntiKt4LCTopo_* in tau-perf D3PDs
chain.define_collection(name="jets", prefix="jet_", size="jet_n", mix=FourMomentum)
chain.define_collection(name="truetaus", prefix="trueTau_", size="trueTau_n", mix=MCTauFourMomentum)
chain.define_collection(name="mc", prefix="mc_", size="mc_n", mix=MCParticle)
chain.define_collection(name="muons", prefix="mu_staco_", size="mu_staco_n")
chain.define_collection(name="electrons", prefix="el_", size="el_n")
chain.define_collection(name="vertices", prefix="vxp_", size="vxp_n")
from externaltools import PileupReweighting
from ROOT import Root
# Initialize the pileup reweighting tool
pileup_tool = Root.TPileupReweighting()
if YEAR == 2011:
pileup_tool.AddConfigFile(PileupReweighting.get_resource('mc11b_defaults.prw.root'))
pileup_tool.AddLumiCalcFile('lumi/2011/hadhad/ilumicalc_histograms_None_178044-191933.root')
elif YEAR == 2012:
pileup_tool.AddConfigFile(PileupReweighting.get_resource('mc12a_defaults.prw.root'))
pileup_tool.SetDataScaleFactors(1./1.11)
pileup_tool.AddLumiCalcFile('lumi/2012/hadhad/ilumicalc_histograms_None_200841-205113.root')
else:
raise ValueError('No pileup reweighting defined for year %d' %
YEAR)
# discard unrepresented data (with mu not simulated in MC)
pileup_tool.SetUnrepresentedDataAction(2)
pileup_tool.Initialize()
# entering the main event loop...
for event in chain:
tree.reset()
event.vertices.select(vertex_selection)
tree.number_of_good_vertices = len(event.vertices)
# match only with visible true taus
event.truetaus.select(lambda tau: tau.vis_Et > 10 * GeV and abs(tau.vis_eta) < 2.5)
if len(event.truetaus) == 1:
true_tau = event.truetaus[0]
TrueTauBlock.set(tree, 1, true_tau)
else:
continue
# Truth-matching
matched_reco = None
reco_index = true_tau.tauAssoc_index
tau = event.taus.getitem(reco_index)
if tau in event.taus:
matched_reco = tau
else:
continue
tree.MET = event.MET_RefFinal_BDTMedium_et
# fill tau block
RecoTauBlock.set(event, tree, matched_reco, None)
# set the event weight
tree.pileup_weight = pileup_tool.GetCombinedWeight(event.RunNumber,
event.mc_channel_number,
event.averageIntPerXing)
tree.mc_weight = event.mc_event_weight
tree.Fill(reset=True)
self.output.cd()
tree.FlushBaskets()
tree.Write()
total_events = event_filters[0].total
cutflow[0] = total_events
cutflow[1] = total_events
cutflow.Write()
def work(self):
D4PD_model = RecoTauBlock + RecoJetBlock + EventVariables + TrueTauBlock + PartonBlock
# initialize the TreeChain of all input files (each containing one tree named self.metadata.treename)
tree = TreeChain(self.metadata.treename,
files=self.files,
events=self.events,
cache=True,
cache_size=10000000,
learn_entries=30)
# create output tree
self.output.cd()
D4PD = Tree(name=self.metadata.name, model=D4PD_model)
copied_variables = ['actualIntPerXing',
'averageIntPerXing']
copied_variables += mc_triggers
D4PD.set_buffer(tree.buffer, variables=copied_variables, create_branches=True, visible=False)
tree.always_read(copied_variables)
# set the event filters
# passthrough for MC for trigger acceptance studies
self.event_filters = EventFilterList([
GRLFilter(self.grl, passthrough = self.metadata.datatype != datasets.DATA),
PriVertex(),
LArError(),
JetCleaningLoose(passthrough = self.metadata.datatype != datasets.DATA),
#JetCleaningMedium(passthrough = self.metadata.datatype != datasets.DATA),
LArHole(),
#JetCrackVeto(),
ElectronVeto(),
MuonVeto(),
TauElectronVeto(),
TauMuonVeto(),
TauAuthorTrack(),
])
self.event_filters.insert(1, MCTriggers())
tree.filters += self.event_filters
cutflow = Cutflow()
# define tree collections
tree.define_collection(name="taus", prefix="tau_", size="tau_n", mix=TauFourMomentum)
# jet_eta etc is AntiKt4LCTopo in tau-perf D3PDs
tree.define_collection(name="jets", prefix="jet_", size="jet_n", mix=FourMomentum)
tree.define_collection(name="truetaus", prefix="trueTau_", size="trueTau_n", mix=MCTauFourMomentum)
tree.define_collection(name="mc", prefix="mc_", size="mc_n", mix=MCParticle)
tree.define_collection(name="muons", prefix="mu_staco_", size="mu_staco_n")
tree.define_collection(name="electrons", prefix="el_", size="el_n")
tree.define_collection(name="vertices", prefix="vxp_", size="vxp_n")
# define tree objects
D4PD.define_object(name='tau1', prefix='tau1_')
D4PD.define_object(name='tau2', prefix='tau2_')
D4PD.define_object(name='jet1', prefix='jet1_')
D4PD.define_object(name='jet2', prefix='jet2_')
"""
tree.define_association(origin='taus', target='truetaus', prefix='trueTauAssoc_', link='index')
tree.define_association(origin='truetaus', target='taus', prefix='tauAssoc_', link='index')
"""
# entering the main event loop...
for event in tree:
D4PD.reset()
cutflow.reset()
# tau selection
event.taus.select(lambda tau: tau.pt > 15*GeV)
# Jet selection
event.jets.select(lambda jet: jet.fourvect.P() > 25*GeV and abs(jet.emscale_eta) < 4.5)
"""
Get VBF jets
"""
# get partons (already sorted by eta in hepmc)
parton1, parton2 = hepmc.get_VBF_partons(event)
PartonBlock.set(D4PD, parton1, parton2)
D4PD.dR_quarks = parton1.fourvect.DeltaR(parton2.fourvect)
"""
Get true taus
"""
event.truetaus.select(lambda tau: tau.vis_Et > 10 * GeV and abs(tau.vis_eta) < 2.5)
if len(event.truetaus) > 2:
print "ERROR: too many true taus: %i" % len(event.truetaus)
D4PD.error = 1
D4PD.Fill()
continue
elif len(event.truetaus) < 2:
print "ERROR: too few true taus: %i" % len(event.truetaus)
D4PD.error = 2
D4PD.Fill()
continue
"""
fourvects = []
colors = []
radii = []
for thing in event.jets:
fourvects.append(thing.fourvect)
colors.append('blue')
radii.append(.4)
for parton in (parton1, parton2):
fourvects.append(parton.fourvect)
colors.append('green')
radii.append(.1)
for thing in event.taus:
fourvects.append(thing.fourvect)
colors.append('red')
radii.append(.2)
for tau in event.truetaus:
fourvects.append(tau.fourvect)
colors.append('purple')
radii.append(.1)
eventview.draw(event, fourvects, colors=colors, radii=radii)
"""
TrueTauBlock.set(D4PD, 1, event.truetaus[0])
TrueTauBlock.set(D4PD, 2, event.truetaus[1])
D4PD.dR_truetaus = event.truetaus[0].fourvect.DeltaR(event.truetaus[1].fourvect)
D4PD.dR_quark_tau = min([
parton1.fourvect.DeltaR(event.truetaus[0].fourvect),
parton2.fourvect.DeltaR(event.truetaus[0].fourvect),
parton1.fourvect.DeltaR(event.truetaus[1].fourvect),
parton2.fourvect.DeltaR(event.truetaus[1].fourvect),
])
taus = []
if event.taus:
for truetau in event.truetaus:
closest_tau = min(event.taus, key=lambda tau: utils.dR(tau.seedCalo_eta, tau.seedCalo_phi, truetau.vis_eta, truetau.vis_phi))
if utils.dR(closest_tau.seedCalo_eta, closest_tau.seedCalo_phi, truetau.vis_eta, truetau.vis_phi) < 0.2:
if closest_tau in taus:
# collision
D4PD.error = 3
break
taus.append(closest_tau)
if len(taus) < 2:
# collision
D4PD.Fill()
continue
"""
# Overlap removal between taus and jets
event.jets.select(lambda jet: not any([tau for tau in taus if
utils.dR(jet.emscale_eta, jet.emscale_phi, tau.seedCalo_eta, tau.seedCalo_phi) < .2]))
"""
jets = []
if event.jets:
for quark in (parton1, parton2):
closest_jet = min(event.jets, key=lambda jet: utils.dR(jet.eta, jet.phi, quark.eta, quark.phi))
if utils.dR(closest_jet.eta, closest_jet.phi, quark.eta, quark.phi) < 0.4:
if closest_jet in jets:
# collision
D4PD.error = 4
break
jets.append(closest_jet)
if len(jets) < 2:
# collision
D4PD.Fill()
continue
"""
Jet variables
"""
RecoJetBlock.set(D4PD, jets[0], jets[1])
"""
Reco tau variables
This must come after the RecoJetBlock is filled since
that sets the jet_beta for boosting the taus
"""
RecoTauBlock.set(event, D4PD, taus[0], taus[1])
D4PD.true_Mvis_tau1_tau2 = (D4PD.trueTau1_fourvect_vis + D4PD.trueTau2_fourvect_vis).M()
"""
MET
"""
METx = event.MET_RefFinal_etx
METy = event.MET_RefFinal_ety
MET_vect = Vector2(METx, METy)
MET_3vect = Vector3(METx, METy, 0.)
D4PD.MET = event.MET_RefFinal_et
D4PD.MET_phi = event.MET_RefFinal_phi
# HT TODO: Fix
sumET = event.MET_RefFinal_sumet
D4PD.HT = sumET
D4PD.numVertices = len([vtx for vtx in event.vertices if (vtx.type == 1 and vtx.nTracks >= 4) or
(vtx.type == 3 and vtx.nTracks >= 2)])
# fill output ntuple
# use reset=True to reset all variables to their defaults after the fill
# to avoid any values from this event carrying over into the next
D4PD.cutflow = cutflow.int()
D4PD.Fill()
self.output.cd()
D4PD.FlushBaskets()
D4PD.Write()
