def effective_area(self, area_cone_size, area_table):
'''Return effective area for this lepton.
area_cone_size: should be e.g. '03' or '04'.
area_table: defines the table of effective areas.
It can either be a string EffectiveArea+area_cone_size, e.g. EffectiveArea03,
or have be a dict like:
{ '03' :
[ (1.000, 0.13),
(1.479, 0.14),
(2.000, 0.07),
(2.200, 0.09),
(2.300, 0.11),
(2.400, 0.11),
(2.500, 0.14) ],
'04' :
[ (1.000, 0.208),
(1.479, 0.209),
(2.000, 0.115),
(2.200, 0.143),
(2.300, 0.183),
(2.400, 0.194),
(2.500, 0.261) ],
'eta' : lambda x: x.superCluster().eta()
}
Please see PhysicsTools/Heppy/python/physicsutils/EffectiveAreas.py for
more information.
If a string is provided, the corresponding attribute must be added to the
Lepton object beforehand: lepton.EffectiveArea03 = <the_area_table>,
or to its class: Electron.EffectiveArea03 = <the_area_table>.
'''
if area_table and not is_ea_table(area_table):
raise ValueError('area_table is not an area table')
if area_table is None:
# area table not provided by the user as argument to the isolation method.
# try to find it in the object or its class
ea_attr_name = ''.join(['EffectiveArea', area_cone_size])
area_table = getattr(self, ea_attr_name, None)
if area_table is None:
area_table = getattr(self.__class__, ea_attr_name, None)
if area_table is None:
raise ValueError(
ea_attr_name +
' not found. It should be added to the lepton object as an attribute or a class attribute.'
)
return effective_area(self, area_cone_size, area_table)
def passed(self, ele, rho, wp):
'''return true if the electron passes the cut based ID working point.
see https://twiki.cern.ch/twiki/bin/viewauth/CMS/CutBasedElectronIdentificationRun2#Offline_selection_criteria_for_V
ele: a reco::GsfElectron
rho: energy density in the event
wp: working point to test
example:
event.getByLabel(('slimmedElectrons'), ele_handle)
event.getByLabel(('fixedGridRhoFastjetAll'), rho_handle)
electrons = ele_handle.product()
rho = rho_handle.product()
is_veto = passed(electron[0], rho,'cutBasedElectronID-Fall17-94X-V2-veto')
'''
if ele.isEB():
WP = self.working_points[wp][0]
else:
WP = self.working_points[wp][1]
isoInputs = self.working_points[wp][2]
full5x5_sigmaIetaIeta = ele.full5x5_sigmaIetaIeta()
dEtaInSeed = sys.float_info.max
if ele.superCluster().isNonnull() and ele.superCluster().seed(
).isNonnull():
dEtaInSeed = ele.deltaEtaSuperClusterTrackAtVtx(
) - ele.superCluster().eta() + ele.superCluster().seed().eta()
dPhiIn = ele.deltaPhiSuperClusterTrackAtVtx()
h_over_e = ele.hadronicOverEm()
h_over_e_cut = WP.hOverECut_C0 + WP.hOverECut_CE / ele.superCluster(
).energy() + WP.hOverECut_Cr * rho / ele.superCluster().energy()
pfIso = ele.pfIsolationVariables()
chad = pfIso.sumChargedHadronPt
nhad = pfIso.sumNeutralHadronEt
pho = pfIso.sumPhotonEt
area_key = [key for key in areas.keys() if key in WP.idName][0]
ea_table = effective_area_table(ele, area_key)
eA = effective_area(ele, '03', ea_table)
iso = chad + max([0.0, nhad + pho - rho * eA])
relIsoWithEA = iso / ele.pt()
relIsoWithEA_cut = WP.relCombIsolationWithEACut_C0 + WP.relCombIsolationWithEACut_Cpt / ele.pt(
)
ecal_energy_inverse = 1.0 / ele.ecalEnergy()
eSCoverP = ele.eSuperClusterOverP()
absEInverseMinusPInverse = abs(1.0 - eSCoverP) * ecal_energy_inverse
missingHits = ele.gsfTrack().hitPattern().numberOfLostHits(
ROOT.reco.HitPattern.MISSING_INNER_HITS)
if full5x5_sigmaIetaIeta < WP.full5x5_sigmaIEtaIEtaCut and \
abs(dEtaInSeed) < WP.dEtaInSeedCut and \
abs(dPhiIn) < WP.dPhiInCut and \
h_over_e < h_over_e_cut and \
relIsoWithEA < relIsoWithEA_cut and \
absEInverseMinusPInverse < WP.absEInverseMinusPInverseCut and \
missingHits <= WP.missingHitsCut and \
ele.passConversionVeto() :
return True
return False