def analyze(self, event):
all_leps = [l for l in Collection(event,"LepGood")]
nFO = getattr(event,"nLepFO"+self.inputlabel)
chosen = getattr(event,"iLepFO"+self.inputlabel)
leps = [all_leps[chosen[i]] for i in xrange(nFO)]
if len(leps) < 2: return True
ret = {}
for var in self.systsJEC:
ret['highestHjTagger%s'%self.systsJEC[var]] = -99
_var = var
if not hasattr(event,"nJet25"+self.systsJEC[var]+self.inputlabel):
_var = 0;
jets = [j for j in Collection(event,"JetSel"+self.inputlabel)]
jetptcut = 25
jets = filter(lambda x : getattr(x,'pt%s'%self.systsJEC[_var]) > jetptcut, jets)
allVars = []
for j in jets:
pseudoevent = emptyclass()
setattr(pseudoevent, 'v1', min( deltaR(j, leps[0]), deltaR(j, leps[1])))
setattr(pseudoevent, 'v2', max( 0, j.btagDeepFlavB))
setattr(pseudoevent, 'v3', max( 0, j.qgl ))
setattr(pseudoevent, 'v4', max( deltaR(j, leps[0]), deltaR(j, leps[1]) ))
setattr(pseudoevent, 'v5', getattr(j,'pt%s'%self.systsJEC[_var]))
allVars.append( self._MVA( pseudoevent ) )
del pseudoevent
if len(allVars):
ret['highestHjTagger%s'%self.systsJEC[var]] = max(allVars)
writeOutput(self, ret)
return True
def analyze(self, event):
myvars = [
event.iLepFO_Recl[0], event.iLepFO_Recl[1], event.iLepFO_Recl[2]
]
ret = []
for worker in self._MVAs:
ret.extend([(x, y) for x, y in worker(event).iteritems()])
writeOutput(self, dict(ret))
return True
def analyze(self,event):
myvars = [event.iLepFO_Recl[0],event.iLepFO_Recl[1],event.iLepFO_Recl[2]]
ret = []
for worker in self._MVAs:
name = worker.name
if not hasattr(event,"nJet25_jerUp_Recl") and ('_jes' in name or '_jer' in name or '_uncl' in name): continue # using jer bc components wont change
ret.extend( [(x,y) for x,y in worker(event).iteritems()])
writeOutput(self, dict(ret))
return True
def analyze(self, event):
myvars = [
event.iLepFO_Recl[0], event.iLepFO_Recl[1], event.iLepFO_Recl[2]
]
ret = []
for worker in self._MVAs:
name = worker.name
if not hasattr(event, "nJet25_jesDown_Recl") and (
'_jes' in name or '_jer' in name or '_uncl' in name):
continue
#if not ('_jes' in name or '_jer' in name or '_uncl' in name) and event.event == 259935: worker.debug=True
ret.extend([(x, y) for x, y in worker(event).iteritems()])
#if not ('_jes' in name or '_jer' in name or '_uncl' in name) and event.event == 259935: worker.debug=False
writeOutput(self, dict(ret))
return True
def analyze(self, event):
myvars = [
event.iLepFO_Recl[0], event.iLepFO_Recl[1], event.iLepFO_Recl[2]
]
ret = []
if self.fillInputs and self.inputHelper:
for var in self.inputHelper:
ret.append((var, self.inputHelper[var](event)))
for worker in self._MVAs:
name = worker.name
if (not hasattr(event, "nJet25_jerUp_Recl")
and not hasattr(event, "nJet25_jesBBEC1_yearDown_Recl")
) and ('_jes' in name or '_jer' in name or '_uncl' in name):
continue # using jer bc components wont change
ret.extend([(x, y) for x, y in worker(event).iteritems()])
writeOutput(self, dict(ret))
return True
def analyze(self, event):
jets = [ j for j in Collection(event, self.jetcoll)]
ret = {}
for var in self.vars:
res = 1
for jet in jets:
if jet.pt<25: continue
res *= getattr(jet,var)
ret[var] = res
if not self.isGroups:
resCorrUp =0; resCorrDown=0;
resUnCorrUp=0; resUnCorrDown=0;
for corr in self.corrs:
resCorrUp = (resCorrUp**2 + self.corrs[corr] *(ret['btagSF_shape_up_jes%s' %corr]-ret['btagSF_shape'])**2)**0.5
resCorrDown = (resCorrDown**2 + self.corrs[corr] *(ret['btagSF_shape_down_jes%s'%corr]-ret['btagSF_shape'])**2)**0.5
resUnCorrUp = (resUnCorrUp**2 + (1-self.corrs[corr])*(ret['btagSF_shape_up_jes%s' %corr]-ret['btagSF_shape'])**2)**0.5
resUnCorrDown = (resUnCorrDown**2 + (1-self.corrs[corr])*(ret['btagSF_shape_down_jes%s'%corr]-ret['btagSF_shape'])**2)**0.5
if self.corrs:
for corr in self.corrs:
ret.pop( 'btagSF_shape_up_jes%s'%corr)
ret.pop( 'btagSF_shape_down_jes%s'%corr)
ret['btagSF_shape_up_jesCorr'] = resCorrUp + ret['btagSF_shape']
ret['btagSF_shape_down_jesCorr'] = -resCorrDown + ret['btagSF_shape']
ret['btagSF_shape_up_jesUnCorr'] = resUnCorrUp + ret['btagSF_shape']
ret['btagSF_shape_down_jesUnCorr'] = -resUnCorrDown + ret['btagSF_shape']
else:
for corr in self.corrs:
ret['btagSF_shape_grouped_up_jes%s'%corr] =0; ret['btagSF_shape_grouped_down_jes%s'%corr] =0;
for comp in self.corrs[corr]:
if comp == "RelativeSample": continue # not here
ret['btagSF_shape_grouped_up_jes%s'%corr] = ( ret['btagSF_shape_grouped_up_jes%s'%corr]**2 + (ret['btagSF_shape_up_jes%s' %comp]-ret['btagSF_shape'])**2)**0.5
ret['btagSF_shape_grouped_down_jes%s'%corr] = ( ret['btagSF_shape_grouped_down_jes%s'%corr]**2 + (ret['btagSF_shape_down_jes%s' %comp]-ret['btagSF_shape'])**2)**0.5
ret.pop( 'btagSF_shape_up_jes%s'%comp)
ret.pop( 'btagSF_shape_down_jes%s'%comp)
ret['btagSF_shape_up_jes%s'%corr] = ret['btagSF_shape_grouped_up_jes%s'%corr] + ret['btagSF_shape']
ret['btagSF_shape_down_jes%s'%corr] = -ret['btagSF_shape_grouped_down_jes%s'%corr] + ret['btagSF_shape']
ret.pop( 'btagSF_shape_grouped_up_jes%s'%corr )
ret.pop( 'btagSF_shape_grouped_down_jes%s'%corr )
writeOutput(self, ret)
return True
def analyze(self, event):
jets = [j for j in Collection(event, self.jetcoll)]
ret = {}
for var in self.vars:
res = 1
for jet in jets:
res *= getattr(jet, var)
ret[var] = res
resCorrUp = 0
resCorrDown = 0
resUnCorrUp = 0
resUnCorrDown = 0
for corr in self.corrs:
resCorrUp = (
resCorrUp**2 + self.corrs[corr] *
(ret['btagSF_shape_up_jes%s' % corr] - ret['btagSF_shape'])**2
)**0.5
resCorrDown = (resCorrDown**2 + self.corrs[corr] *
(ret['btagSF_shape_down_jes%s' % corr] -
ret['btagSF_shape'])**2)**0.5
resUnCorrUp = (
resCorrUp**2 + (1 - self.corrs[corr]) *
(ret['btagSF_shape_up_jes%s' % corr] - ret['btagSF_shape'])**2
)**0.5
resUnCorrDown = (resCorrDown**2 + (1 - self.corrs[corr]) *
(ret['btagSF_shape_down_jes%s' % corr] -
ret['btagSF_shape'])**2)**0.5
if self.corrs:
for corr in self.corrs:
ret.pop('btagSF_shape_up_jes%s' % corr)
ret.pop('btagSF_shape_down_jes%s' % corr)
ret['btagSF_shape_up_jesCorr'] = resCorrUp
ret['btagSF_shape_down_jesCorr'] = resCorrDown
ret['btagSF_shape_up_jesUnCorr'] = resUnCorrUp
ret['btagSF_shape_down_jesUnCorr'] = resUnCorrDown
writeOutput(self, ret)
return True
def analyze(self, event):
writeOutput(self, self.runIt(event))
return True
def analyze(self, event):
writeOutput(self, self.run(event, NanoAODCollection, "MET"))
return True
def analyze(self, event):
myvars = [event.iLepFO_Recl[0],event.iLepFO_Recl[1],event.iLepFO_Recl[2]]
writeOutput(self, dict([ (name, mva(event)) for name, mva in self._MVAs.iteritems()]))
return True
