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CSCSegmentAlgorithmST_cfi.py
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1 import FWCore.ParameterSet.Config as cms
2 
3 # The following algorithms looks how far a rechit is from the
4 # proto segment in terms of its error ellipse. This is different
5 # from the other algorithms which use a cylinder around the proto
6 # segment and look for rechits within that cylinder
7 ST_ME1234 = cms.PSet(
8 
9  #Parameters for showering segments
10  useShowering = cms.bool(False),
11  maxRatioResidualPrune = cms.double(3),
12  dRPhiFineMax = cms.double(8.0),
13  dPhiFineMax = cms.double(0.025),
14  tanThetaMax = cms.double(1.2),
15  tanPhiMax = cms.double(0.5),
16  maxDPhi = cms.double(999.),
17  maxDTheta = cms.double(999.),
18 
19 
20  curvePenaltyThreshold = cms.double(0.85),
21  minHitsPerSegment = cms.int32(3),
22  yweightPenaltyThreshold = cms.double(1.0),
23  curvePenalty = cms.double(2.0),
24  dXclusBoxMax = cms.double(4.0),
25  BrutePruning = cms.bool(True),
26  BPMinImprovement = cms.double(10000.),
27  yweightPenalty = cms.double(1.5),
28  hitDropLimit5Hits = cms.double(0.8),
29  preClustering = cms.bool(True),
30  preClusteringUseChaining = cms.bool(True),
31  hitDropLimit4Hits = cms.double(0.6),
32  hitDropLimit6Hits = cms.double(0.3333),
33  maxRecHitsInCluster = cms.int32(20),
34  CSCDebug = cms.untracked.bool(False),
35  onlyBestSegment = cms.bool(False),
36  Pruning = cms.bool(True),
37  dYclusBoxMax = cms.double(8.0),
38  # Correction to improove fit
39  CorrectTheErrors = cms.bool(True),
40  NormChi2Cut2D = cms.double(20.0),
41  NormChi2Cut3D = cms.double(10.0),
42  prePrun = cms.bool(True),
43  prePrunLimit = cms.double(3.17),
44  SeedSmall = cms.double(0.000200),
45  SeedBig = cms.double(0.001500),
46  ForceCovariance = cms.bool(False),
47  ForceCovarianceAll = cms.bool(False),
48  Covariance = cms.double(0.0)
49 
50 )
51 ST_ME1A = cms.PSet(
52 
53  #Parameters for showering segments
54  useShowering = cms.bool(False),
55  maxRatioResidualPrune = cms.double(3),
56  dRPhiFineMax = cms.double(8.0),
57  dPhiFineMax = cms.double(0.025),
58  tanThetaMax = cms.double(1.2),
59  tanPhiMax = cms.double(0.5),
60  maxDPhi = cms.double(999.),
61  maxDTheta = cms.double(999.),
62 
63 
64  curvePenaltyThreshold = cms.double(0.85),
65  minHitsPerSegment = cms.int32(3),
66  yweightPenaltyThreshold = cms.double(1.0),
67  curvePenalty = cms.double(2.0),
68  dXclusBoxMax = cms.double(4.0),
69  BrutePruning = cms.bool(True),
70  BPMinImprovement = cms.double(10000.),
71  yweightPenalty = cms.double(1.5),
72  hitDropLimit5Hits = cms.double(0.8),
73  preClustering = cms.bool(True),
74  preClusteringUseChaining = cms.bool(True),
75  hitDropLimit4Hits = cms.double(0.6),
76  hitDropLimit6Hits = cms.double(0.3333),
77  maxRecHitsInCluster = cms.int32(24),
78  CSCDebug = cms.untracked.bool(False),
79  onlyBestSegment = cms.bool(False),
80  Pruning = cms.bool(True),
81  dYclusBoxMax = cms.double(8.0),
82  # Correction to improove fit
83  CorrectTheErrors = cms.bool(True),
84  NormChi2Cut2D = cms.double(20.0),
85  NormChi2Cut3D = cms.double(10.0),
86  prePrun = cms.bool(True),
87  prePrunLimit = cms.double(3.17),
88  SeedSmall = cms.double(0.000200),
89  SeedBig = cms.double(0.001500),
90  ForceCovariance = cms.bool(False),
91  ForceCovarianceAll = cms.bool(False),
92  Covariance = cms.double(0.0)
93 
94 )
95 CSCSegAlgoST = cms.PSet(
96  algo_name = cms.string('CSCSegAlgoST'),
97  algo_psets = cms.VPSet( cms.PSet(ST_ME1234), cms.PSet(ST_ME1A) ),
98  chamber_types = cms.vstring('ME1/a','ME1/b','ME1/2','ME1/3','ME2/1','ME2/2','ME3/1','ME3/2','ME4/1','ME4/2'),
99  parameters_per_chamber_type = cms.vint32(2, 1, 1, 1, 1, 1, 1, 1, 1, 1)
100 )
101 
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