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/data/refman/pasoursint/CMSSW_5_3_10_patch2/src/RecoEgamma/EgammaPhotonProducers/python/conversions_cfi.py

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00001 import FWCore.ParameterSet.Config as cms
00002 
00003 #from RecoEgamma.EgammaTools.PhotonConversionMVAComputer_cfi import *
00004 #
00005 #  configuration for producer of converted photons
00006 #  
00007 #
00008 conversions = cms.EDProducer("ConvertedPhotonProducer",
00009     scHybridBarrelProducer = cms.InputTag("correctedHybridSuperClusters"),
00010     scIslandEndcapProducer = cms.InputTag("correctedMulti5x5SuperClustersWithPreshower"),
00011     bcEndcapCollection = cms.InputTag("multi5x5SuperClusters","multi5x5EndcapBasicClusters"),
00012     bcBarrelCollection = cms.InputTag("hybridSuperClusters","hybridBarrelBasicClusters"),
00013     conversionIOTrackProducer = cms.string('ckfInOutTracksFromConversions'),
00014     outInTrackCollection = cms.string(''),
00015     conversionOITrackProducer = cms.string('ckfOutInTracksFromConversions'),
00016     inOutTrackCollection = cms.string(''),
00017     inOutTrackSCAssociation = cms.string('inOutTrackSCAssociationCollection'),
00018     outInTrackSCAssociation = cms.string('outInTrackSCAssociationCollection'),
00019     convertedPhotonCollection = cms.string('uncleanedConversions'),
00020     hcalTowers = cms.InputTag("towerMaker"),                         
00021     cleanedConvertedPhotonCollection = cms.string(''),                         
00022     AlgorithmName = cms.string('ecalSeeded'),
00023     minSCEt = cms.double(20.0),
00024     hOverEConeSize = cms.double(0.15),
00025     maxHOverE = cms.double(0.15),                         
00026     recoverOneTrackCase = cms.bool(True),
00027     dRForConversionRecovery = cms.double(0.3),                      
00028     deltaCotCut = cms.double(0.05),
00029     minApproachDisCut  = cms.double(0.),
00030     maxNumOfCandidates = cms.int32(3),
00031     risolveConversionAmbiguity = cms.bool(True),
00032     maxDelta = cms.double(0.01),#delta of parameters
00033     maxReducedChiSq = cms.double(225.),#maximum chi^2 per degree of freedom before fit is terminated
00034     minChiSqImprovement = cms.double(50.),#threshold for "significant improvement" in the fit termination logic
00035     maxNbrOfIterations = cms.int32(40), #maximum number of convergence iterations
00036     MVA_weights_location = cms.string('RecoEgamma/EgammaTools/data/TMVAnalysis_Likelihood.weights.txt')
00037 #    MVA_weights_location = cms.string('RecoEgamma/EgammaTools/data/TMVAnalysis_Likelihood.weights.xml')
00038 
00039  )
00040