00001 import FWCore.ParameterSet.Config as cms
00002
00003
00004
00005
00006
00007 ST_ME1234 = cms.PSet(
00008
00009
00010 useShowering = cms.bool(False),
00011 maxRatioResidualPrune = cms.double(3),
00012 dRPhiFineMax = cms.double(8.0),
00013 dPhiFineMax = cms.double(0.025),
00014 tanThetaMax = cms.double(1.2),
00015 tanPhiMax = cms.double(0.5),
00016 maxDPhi = cms.double(999.),
00017 maxDTheta = cms.double(999.),
00018
00019
00020 curvePenaltyThreshold = cms.double(0.85),
00021 minHitsPerSegment = cms.int32(3),
00022 yweightPenaltyThreshold = cms.double(1.0),
00023 curvePenalty = cms.double(2.0),
00024 dXclusBoxMax = cms.double(4.0),
00025 BrutePruning = cms.bool(True),
00026 BPMinImprovement = cms.double(10000.),
00027 yweightPenalty = cms.double(1.5),
00028 hitDropLimit5Hits = cms.double(0.8),
00029 preClustering = cms.bool(True),
00030 preClusteringUseChaining = cms.bool(True),
00031 hitDropLimit4Hits = cms.double(0.6),
00032 hitDropLimit6Hits = cms.double(0.3333),
00033 maxRecHitsInCluster = cms.int32(20),
00034 CSCDebug = cms.untracked.bool(False),
00035 onlyBestSegment = cms.bool(False),
00036 Pruning = cms.bool(True),
00037 dYclusBoxMax = cms.double(8.0),
00038
00039 CorrectTheErrors = cms.bool(True),
00040 NormChi2Cut2D = cms.double(20.0),
00041 NormChi2Cut3D = cms.double(10.0),
00042 prePrun = cms.bool(True),
00043 prePrunLimit = cms.double(3.17),
00044 SeedSmall = cms.double(0.000200),
00045 SeedBig = cms.double(0.001500),
00046 ForceCovariance = cms.bool(False),
00047 ForceCovarianceAll = cms.bool(False),
00048 Covariance = cms.double(0.0)
00049
00050 )
00051 ST_ME1A = cms.PSet(
00052
00053
00054 useShowering = cms.bool(False),
00055 maxRatioResidualPrune = cms.double(3),
00056 dRPhiFineMax = cms.double(8.0),
00057 dPhiFineMax = cms.double(0.025),
00058 tanThetaMax = cms.double(1.2),
00059 tanPhiMax = cms.double(0.5),
00060 maxDPhi = cms.double(999.),
00061 maxDTheta = cms.double(999.),
00062
00063
00064 curvePenaltyThreshold = cms.double(0.85),
00065 minHitsPerSegment = cms.int32(3),
00066 yweightPenaltyThreshold = cms.double(1.0),
00067 curvePenalty = cms.double(2.0),
00068 dXclusBoxMax = cms.double(4.0),
00069 BrutePruning = cms.bool(True),
00070 BPMinImprovement = cms.double(10000.),
00071 yweightPenalty = cms.double(1.5),
00072 hitDropLimit5Hits = cms.double(0.8),
00073 preClustering = cms.bool(True),
00074 preClusteringUseChaining = cms.bool(True),
00075 hitDropLimit4Hits = cms.double(0.6),
00076 hitDropLimit6Hits = cms.double(0.3333),
00077 maxRecHitsInCluster = cms.int32(24),
00078 CSCDebug = cms.untracked.bool(False),
00079 onlyBestSegment = cms.bool(False),
00080 Pruning = cms.bool(True),
00081 dYclusBoxMax = cms.double(8.0),
00082
00083 CorrectTheErrors = cms.bool(True),
00084 NormChi2Cut2D = cms.double(20.0),
00085 NormChi2Cut3D = cms.double(10.0),
00086 prePrun = cms.bool(True),
00087 prePrunLimit = cms.double(3.17),
00088 SeedSmall = cms.double(0.000200),
00089 SeedBig = cms.double(0.001500),
00090 ForceCovariance = cms.bool(False),
00091 ForceCovarianceAll = cms.bool(False),
00092 Covariance = cms.double(0.0)
00093
00094 )
00095 CSCSegAlgoST = cms.PSet(
00096 algo_name = cms.string('CSCSegAlgoST'),
00097 algo_psets = cms.VPSet( cms.PSet(ST_ME1234), cms.PSet(ST_ME1A) ),
00098 chamber_types = cms.vstring('ME1/a','ME1/b','ME1/2','ME1/3','ME2/1','ME2/2','ME3/1','ME3/2','ME4/1','ME4/2'),
00099 parameters_per_chamber_type = cms.vint32(2, 1, 1, 1, 1, 1, 1, 1, 1, 1)
00100 )
00101