File indexing completed on 2024-10-19 04:58:31
0001 import FWCore.ParameterSet.Config as cms
0002
0003 hltTiclTrackstersCLUE3DHighL1Seeded = cms.EDProducer("TrackstersProducer",
0004 detector = cms.string('HGCAL'),
0005 filtered_mask = cms.InputTag("hltFilteredLayerClustersCLUE3DHighL1Seeded","CLUE3DHigh"),
0006 itername = cms.string('CLUE3DHigh'),
0007 layer_clusters = cms.InputTag("hltHgcalMergeLayerClustersL1Seeded"),
0008 layer_clusters_hfnose_tiles = cms.InputTag("ticlLayerTileHFNose"),
0009 layer_clusters_tiles = cms.InputTag("hltTiclLayerTileProducerL1Seeded"),
0010 mightGet = cms.optional.untracked.vstring,
0011 original_mask = cms.InputTag("hltHgcalMergeLayerClustersL1Seeded","InitialLayerClustersMask"),
0012 patternRecognitionBy = cms.string('CLUE3D'),
0013 inferenceAlgo = cms.string('TracksterInferenceByCNNv4'),
0014 pluginPatternRecognitionByCA = cms.PSet(
0015 algo_verbosity = cms.int32(0),
0016 energy_em_over_total_threshold = cms.double(-1),
0017 etaLimitIncreaseWindow = cms.double(2.1),
0018 filter_on_categories = cms.vint32(0),
0019 max_delta_time = cms.double(3),
0020 max_longitudinal_sigmaPCA = cms.double(9999),
0021 max_missing_layers_in_trackster = cms.int32(9999),
0022 max_out_in_hops = cms.int32(10),
0023 min_cos_pointing = cms.double(-1),
0024 min_cos_theta = cms.double(0.915),
0025 min_layers_per_trackster = cms.int32(10),
0026 oneTracksterPerTrackSeed = cms.bool(False),
0027 out_in_dfs = cms.bool(True),
0028 pid_threshold = cms.double(0),
0029 promoteEmptyRegionToTrackster = cms.bool(False),
0030 root_doublet_max_distance_from_seed_squared = cms.double(9999),
0031 shower_start_max_layer = cms.int32(9999),
0032 siblings_maxRSquared = cms.vdouble(0.0006, 0.0006, 0.0006),
0033 skip_layers = cms.int32(0),
0034 type = cms.string('CA')
0035 ),
0036 pluginPatternRecognitionByCLUE3D = cms.PSet(
0037 algo_verbosity = cms.int32(0),
0038 criticalDensity = cms.vdouble(
0039 0.6,
0040 0.6,
0041 0.6
0042 ),
0043 criticalSelfDensity = cms.vdouble(
0044 0.15,
0045 0.15,
0046 0.15
0047 ),
0048 densitySiblingLayers = cms.vint32(
0049 3,
0050 3,
0051 3
0052 ),
0053 densityEtaPhiDistanceSqr = cms.vdouble(
0054 0.0008,
0055 0.0008,
0056 0.0008
0057 ),
0058 densityXYDistanceSqr = cms.vdouble(
0059 3.24,
0060 3.24,
0061 3.24
0062 ),
0063 kernelDensityFactor = cms.vdouble(
0064 0.2,
0065 0.2,
0066 0.2
0067 ),
0068 densityOnSameLayer = cms.bool(False),
0069 nearestHigherOnSameLayer = cms.bool(False),
0070 useAbsoluteProjectiveScale = cms.bool(True),
0071 useClusterDimensionXY = cms.bool(False),
0072 rescaleDensityByZ = cms.bool(False),
0073 criticalEtaPhiDistance = cms.vdouble(
0074 0.025,
0075 0.025,
0076 0.025
0077 ),
0078 criticalXYDistance = cms.vdouble(
0079 1.8,
0080 1.8,
0081 1.8
0082 ),
0083 criticalZDistanceLyr = cms.vint32(
0084 5,
0085 5,
0086 5
0087 ),
0088 outlierMultiplier = cms.vdouble(
0089 2,
0090 2,
0091 2
0092 ),
0093 minNumLayerCluster = cms.vint32(
0094 2,
0095 2,
0096 2
0097 ),
0098 computeLocalTime = cms.bool(False),
0099 doPidCut = cms.bool(True),
0100 cutHadProb = cms.double(999.),
0101 type = cms.string('CLUE3D')
0102 ),
0103 pluginPatternRecognitionByFastJet = cms.PSet(
0104 algo_verbosity = cms.int32(0),
0105 antikt_radius = cms.double(0.09),
0106 minNumLayerCluster = cms.int32(5),
0107 type = cms.string('FastJet')
0108 ),
0109 pluginInferenceAlgoTracksterInferenceByCNNv4 = cms.PSet(
0110 algo_verbosity = cms.int32(0),
0111 onnxModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv4/onnx_models/energy_id_v0.onnx'),
0112 inputNames = cms.vstring('input:0'),
0113 outputNames = cms.vstring("output/regressed_energy:0", "output/id_probabilities:0"),
0114 eid_min_cluster_energy = cms.double(1),
0115 eid_n_layers = cms.int32(50),
0116 eid_n_clusters = cms.int32(10),
0117 doPID = cms.int32(1),
0118 doRegression = cms.int32(0),
0119 type = cms.string('TracksterInferenceByCNNv4')
0120 ),
0121 pluginInferenceAlgoTracksterInferenceByDNN = cms.PSet(
0122 algo_verbosity = cms.int32(0),
0123 onnxPIDModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/patternrecognition/id_v0.onnx'),
0124 onnxEnergyModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/patternrecognition/energy_v0.onnx'),
0125 inputNames = cms.vstring('input'),
0126 output_en = cms.vstring('enreg_output'),
0127 output_id = cms.vstring('pid_output'),
0128 eid_n_layers = cms.int32(50),
0129 eid_n_clusters = cms.int32(10),
0130 doPID = cms.int32(1),
0131 doRegression = cms.int32(0),
0132 type = cms.string('TracksterInferenceByDNN')
0133 ),
0134 pluginInferenceAlgoTracksterInferenceByANN = cms.PSet(
0135 algo_verbosity = cms.int32(0),
0136 type = cms.string('TracksterInferenceByANN')
0137
0138 ),
0139 seeding_regions = cms.InputTag("hltTiclSeedingL1"),
0140 time_layerclusters = cms.InputTag("hltHgcalMergeLayerClustersL1Seeded","timeLayerCluster"),
0141 )
0142
0143 from Configuration.ProcessModifiers.ticl_v5_cff import ticl_v5
0144 ticl_v5.toModify(hltTiclTrackstersCLUE3DHighL1Seeded.pluginPatternRecognitionByCLUE3D, computeLocalTime = cms.bool(True))
0145 ticl_v5.toModify(hltTiclTrackstersCLUE3DHighL1Seeded.inferenceAlgo, type = cms.string('TracksterInferenceByDNN'))
0146
