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File indexing completed on 2021-02-14 14:25:56

 import FWCore.ParameterSet.Config as cms
 
 # Produces a collection recoMuons_refitMuons__* consisting of the
 # reco::Muons from the src collection (default is the merged muons
 # collection, only taking those Muons for which isGlobalMuon() is
 # true) with the kinematics replaced by those from the refit tracks
 # chosen. The default below chooses the tracks using the "cocktail"
 # function found in DataFormats/MuonReco/src/MuonCocktails.cc.
 
 refitMuons = cms.EDProducer('MuonsFromRefitTracksProducer',
     # The input MuonCollection from which the starting Muon objects
     # will be taken. The module will only consider globalMuons from
     # the merged muon collection, i.e. trackerMuons, stand-alone muons
     # will be filtered out of the merged MuonCollection.
     src = cms.InputTag('muons1stStep'),
 
     # The particular set of refit tracks to use. Could also be
     # 'tevMuons:default', 'tevMuons:picky', or 'tevMuons:firstHit' to
     # use the corresponding refits; 'none' to use this module as just
     # a filter for globalMuons (as opposed to trackerMuons or
     # caloMuons); to make Muons out of the cocktail tracks, 'tevMuons'
     # by itself must be used (also specifying fromCocktail = True
     # below).
     tevMuonTracks = cms.string('tevMuons'),
 
     # Exactly one of the below boolean flags may be True (determines
     # the refit track picked for each muon).
 
     # Whether to call muon::tevOptimized as in the above code and use
     # the result of the cocktail choice.
     fromCocktail = cms.bool(True),
 
     # Whether to replace the input muons' kinematics with that of the
     # tracker-only fit. I.e., the muon's momentum, vertex, and charge are
     # taken from the track accessed by reco::Muon::innerTrack().
     fromTrackerTrack = cms.bool(False),
 
     # Whether to replace the input muons' kinematics with that of the
     # tracker-only fit. I.e., the muon's momentum, vertex, and charge are
     # taken from the track accessed by reco::Muon::innerTrack().
     fromGlobalTrack = cms.bool(False),
 
     # Whether to apply the TMR cocktail algorithm. For each muon track, we
     # start with the first-muon-hit fit. If the difference in -ln(chi^2
     # tail probability) between the first-muon-hit and tracker-only is
     # greater than the below prescribed cut value, the tracker-only fit
     # replaces the first-muon-hit. For further details see XXX.
     fromTMR = cms.bool(False),
 
     # The cut value used in the TMR cocktail.
     TMRcut = cms.double(4.0),
 
     # Whether to use Adam Everett's sigma-switch method, choosing
     # between the global track and the tracker track.
     fromSigmaSwitch = cms.bool(False),
 
     # The number of sigma to switch on in the above method.
     nSigmaSwitch = cms.double(2),
     
     # The pT threshold to switch at in the above method.
     ptThreshold = cms.double(200),
 )

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