def __init__(self, fname, **kwargs):
kwargs['channel'] = 'etau'
super(ModuleETau,self).__init__(fname,**kwargs)
self.out = TreeProducerETau(fname,self)
# TRIGGERS
jsonfile = os.path.join(datadir,"trigger/tau_triggers_%d.json"%(self.year))
self.trigger = TrigObjMatcher(jsonfile,trigger='SingleElectron',isdata=self.isdata)
self.eleCutPt = self.trigger.ptmins[0]
self.tauCutPt = 20
self.eleCutEta = 2.3
self.tauCutEta = 2.3
# CORRECTIONS
if self.ismc:
self.eleSFs = ElectronSFs(year=self.year) # electron id/iso/trigger SFs
self.tesTool = TauESTool(tauSFVersion[self.year]) # real tau energy scale corrections
self.fesTool = TauFESTool(tauSFVersion[self.year]) # e -> tau fake energy scale
self.tauSFs = TauIDSFTool(tauSFVersion[self.year],'DeepTau2017v2p1VSjet','Tight')
self.etfSFs = TauIDSFTool(tauSFVersion[self.year],'DeepTau2017v2p1VSe', 'VLoose')
self.mtfSFs = TauIDSFTool(tauSFVersion[self.year],'DeepTau2017v2p1VSmu', 'Tight')
# CUTFLOW
self.out.cutflow.addcut('none', "no cut" )
self.out.cutflow.addcut('trig', "trigger" )
self.out.cutflow.addcut('electron', "electron" )
self.out.cutflow.addcut('tau', "tau" )
self.out.cutflow.addcut('pair', "pair" )
self.out.cutflow.addcut('weight', "no cut, weighted", 15 )
self.out.cutflow.addcut('weight_no0PU', "no cut, weighted, PU>0", 16 ) # use for normalization
def printTESTable(year):
testool = TauESTool(year)
dmvals = [0,1,5,6,10,11]
print ">>> "
print ">>> TES for '%s'"%(year)
print ">>> "
print ">>> %10s"%('var \ DM')+''.join("%9d"%dm for dm in dmvals)
print ">>> %10s"%("central") +''.join("%9.5f"%testool.getTES(dm,5) for dm in dmvals)
print ">>> %10s"%("up") +''.join("%9.5f"%testool.getTES(dm,5,'Up') for dm in dmvals)
print ">>> %10s"%("down") +''.join("%9.5f"%testool.getTES(dm,5,'Down') for dm in dmvals)
print ">>> "
def printTESTable(year,id):
testool = TauESTool(year,id)
ptvals = [25,102,175] #[25,30,102,170,175]
dmvals = [0,1,5,10,11]
for pt in ptvals:
print(">>> ")
print(">>> TES for '%s' ('%s') and pT = %s GeV"%(green(id),year,pt))
print(">>> ")
print(">>> %10s"%('var \ DM')+''.join("%9d"%dm for dm in dmvals))
print(">>> %10s"%("central") +''.join("%9.5f"%testool.getTES(pt,dm,5) for dm in dmvals))
print(">>> %10s"%("up") +''.join("%9.5f"%testool.getTES(pt,dm,5,'Up') for dm in dmvals))
print(">>> %10s"%("down") +''.join("%9.5f"%testool.getTES(pt,dm,5,'Down') for dm in dmvals))
print(">>> ")
def __init__(self, fname, **kwargs):
kwargs['channel'] = 'mutau'
super(ModuleMuTau, self).__init__(fname, **kwargs)
self.out = TreeProducerMuTau(fname, self)
# TRIGGERS
if self.year == 2016:
self.trigger = lambda e: e.HLT_IsoMu22 or e.HLT_IsoMu22_eta2p1 or e.HLT_IsoTkMu22 or e.HLT_IsoTkMu22_eta2p1 #or e.HLT_IsoMu19_eta2p1_LooseIsoPFTau20_SingleL1
self.muonCutPt = lambda e: 23
self.muonCutEta = lambda e: 2.4 if e.HLT_IsoMu22 or e.HLT_IsoTkMu22 else 2.1
elif self.year == 2017:
self.trigger = lambda e: e.HLT_IsoMu24 or e.HLT_IsoMu27 #or e.HLT_IsoMu20_eta2p1_LooseChargedIsoPFTau27_eta2p1_CrossL1
self.muonCutPt = lambda e: 25 if e.HLT_IsoMu24 else 28
self.muonCutEta = lambda e: 2.4
else:
self.trigger = lambda e: e.HLT_IsoMu24 or e.HLT_IsoMu27 #or e.HLT_IsoMu20_eta2p1_LooseChargedIsoPFTau27_eta2p1_CrossL1
self.muonCutPt = lambda e: 25
self.muonCutEta = lambda e: 2.4
self.tauCutPt = 20
self.tauCutEta = 2.3
# CORRECTIONS
if self.ismc:
self.muSFs = MuonSFs(
era=self.era, verb=self.verbosity) # muon id/iso/trigger SFs
self.tesTool = TauESTool(
tauSFVersion[self.year]) # real tau energy scale corrections
self.fesTool = TauFESTool(
tauSFVersion[self.year]) # for mu -> tau fake negligible
self.tauSFs = TauIDSFTool(tauSFVersion[self.year],
'DeepTau2017v2p1VSjet', 'Tight')
self.etfSFs = TauIDSFTool(tauSFVersion[self.year],
'DeepTau2017v2p1VSe', 'VLoose')
self.mtfSFs = TauIDSFTool(tauSFVersion[self.year],
'DeepTau2017v2p1VSmu', 'Tight')
# CUTFLOW
self.out.cutflow.addcut('none', "no cut")
self.out.cutflow.addcut('trig', "trigger")
self.out.cutflow.addcut('muon', "muon")
self.out.cutflow.addcut('tau', "tau")
self.out.cutflow.addcut('pair', "pair")
self.out.cutflow.addcut('weight', "no cut, weighted", 15)
self.out.cutflow.addcut('weight_no0PU', "no cut, weighted, PU>0",
16) # use for normalization
def __init__(self, fname, **kwargs):
kwargs['channel'] = 'mutau'
super(ModuleTauTau, self).__init__(fname, **kwargs)
self.out = TreeProducerTauTau(fname, self)
# TRIGGERS
jsonfile = os.path.join(datadir,
"trigger/tau_triggers_%d.json" % (self.year))
self.trigger = TrigObjMatcher(jsonfile,
trigger='ditau',
isdata=self.isdata)
self.tauCutPt = 40
self.tauCutEta = 2.1
# CORRECTIONS
if self.ismc:
self.trigTool = TauTriggerSFs('tautau', 'Medium', year=self.year)
self.trigTool_tight = TauTriggerSFs('tautau',
'Tight',
year=self.year)
self.tesTool = TauESTool(
tauSFVersion[self.year]) # real tau energy scale
self.fesTool = TauFESTool(
tauSFVersion[self.year]) # e -> tau fake energy scale
self.tauSFs = TauIDSFTool(tauSFVersion[self.year],
'DeepTau2017v2p1VSjet',
'Medium',
dm=True)
self.tauSFs_tight = TauIDSFTool(tauSFVersion[self.year],
'DeepTau2017v2p1VSjet',
'Tight',
dm=True)
self.etfSFs = TauIDSFTool(tauSFVersion[self.year],
'DeepTau2017v2p1VSe', 'VVLoose')
self.mtfSFs = TauIDSFTool(tauSFVersion[self.year],
'DeepTau2017v2p1VSmu', 'Loose')
# CUTFLOW
self.out.cutflow.addcut('none', "no cut")
self.out.cutflow.addcut('trig', "trigger")
self.out.cutflow.addcut('tau', "tau")
self.out.cutflow.addcut('pair', "ditau pair")
self.out.cutflow.addcut('weight', "no cut, weighted", 15)
self.out.cutflow.addcut('weight_no0PU', "no cut, weighted, PU>0",
16) # use for normalization
def __init__(self, year, algorithm):
self.testool = TauESTool(YEARLIB[year], algorithm)
self.tfestool = TauESTool(YEARLIB[year])
import ROOT
import math
ROOT.PyConfig.IgnoreCommandLineOptions = True
from PhysicsTools.NanoAODTools.postprocessing.framework.datamodel import Collection
from PhysicsTools.NanoAODTools.postprocessing.framework.eventloop import Module
from TauPOG.TauIDSFs.TauIDSFTool import TauIDSFTool
tauSFTool_jet = TauIDSFTool('2018ReReco', 'DeepTau2017v2p1VSjet', 'VVTight')
tauSFTool_ele = TauIDSFTool('2018ReReco', 'DeepTau2017v2p1VSe', 'VVTight')
tauSFTool_muo = TauIDSFTool('2018ReReco', 'DeepTau2017v2p1VSmu', 'Tight')
from TauPOG.TauIDSFs.TauIDSFTool import TauESTool
testool_jet = TauESTool('2018ReReco', 'DeepTau2017v2p1VSjet')
from TauPOG.TauIDSFs.TauIDSFTool import TauFESTool
testool_ele = TauFESTool('2018ReReco', 'DeepTau2017v2p1VSe')
from MuonPOG.MuonSFs.MuonSFTool import MuonSFTool
muonSFTool = MuonSFTool()
from PhysicsTools.NanoAODTools.postprocessing.tools import deltaR
class ZMuTauProducer(Module):
def __init__(self, isMC_):
self.isMC__ = isMC_
pass
def beginJob(self):
pass
def endJob(self):