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import FWCore.ParameterSet.Config as cms
hltTiclTrackstersCLUE3DHigh = cms.EDProducer("TrackstersProducer",
detector = cms.string('HGCAL'),
filtered_mask = cms.InputTag("hltFilteredLayerClustersCLUE3DHigh","CLUE3DHigh"),
itername = cms.string('CLUE3DHigh'),
layer_clusters = cms.InputTag("hltHgcalMergeLayerClusters"),
layer_clusters_hfnose_tiles = cms.InputTag("ticlLayerTileHFNose"),
layer_clusters_tiles = cms.InputTag("hltTiclLayerTileProducer"),
mightGet = cms.optional.untracked.vstring,
original_mask = cms.InputTag("hltHgcalMergeLayerClusters","InitialLayerClustersMask"),
patternRecognitionBy = cms.string('CLUE3D'),
inferenceAlgo = cms.string('TracksterInferenceByCNNv4'),
pluginPatternRecognitionByCA = cms.PSet(
algo_verbosity = cms.int32(0),
energy_em_over_total_threshold = cms.double(-1),
etaLimitIncreaseWindow = cms.double(2.1),
filter_on_categories = cms.vint32(0),
max_delta_time = cms.double(3),
max_longitudinal_sigmaPCA = cms.double(9999),
max_missing_layers_in_trackster = cms.int32(9999),
max_out_in_hops = cms.int32(10),
min_cos_pointing = cms.double(-1),
min_cos_theta = cms.double(0.915),
min_layers_per_trackster = cms.int32(10),
oneTracksterPerTrackSeed = cms.bool(False),
out_in_dfs = cms.bool(True),
pid_threshold = cms.double(0),
promoteEmptyRegionToTrackster = cms.bool(False),
root_doublet_max_distance_from_seed_squared = cms.double(9999),
shower_start_max_layer = cms.int32(9999),
siblings_maxRSquared = cms.vdouble(0.0006, 0.0006, 0.0006),
skip_layers = cms.int32(0),
type = cms.string('CA')
),
pluginPatternRecognitionByCLUE3D = cms.PSet(
algo_verbosity = cms.int32(0),
criticalDensity = cms.vdouble(
0.6,
0.6,
0.6
),
criticalSelfDensity = cms.vdouble(
0.15,
0.15,
0.15
),
densitySiblingLayers = cms.vint32(
3,
3,
3
),
densityEtaPhiDistanceSqr = cms.vdouble(
0.0008,
0.0008,
0.0008
),
densityXYDistanceSqr = cms.vdouble(
3.24,
3.24,
3.24
),
kernelDensityFactor = cms.vdouble(
0.2,
0.2,
0.2
),
densityOnSameLayer = cms.bool(False),
nearestHigherOnSameLayer = cms.bool(False),
useAbsoluteProjectiveScale = cms.bool(True),
useClusterDimensionXY = cms.bool(False),
rescaleDensityByZ = cms.bool(False),
criticalEtaPhiDistance = cms.vdouble(
0.025,
0.025,
0.025
),
criticalXYDistance = cms.vdouble(
1.8,
1.8,
1.8
),
criticalZDistanceLyr = cms.vint32(
5,
5,
5
),
outlierMultiplier = cms.vdouble(
2,
2,
2
),
minNumLayerCluster = cms.vint32(
2,
2,
2
),
computeLocalTime = cms.bool(False),
doPidCut = cms.bool(True),
cutHadProb = cms.double(999.),
type = cms.string('CLUE3D')
),
pluginPatternRecognitionByFastJet = cms.PSet(
algo_verbosity = cms.int32(0),
antikt_radius = cms.double(0.09),
minNumLayerCluster = cms.int32(5),
type = cms.string('FastJet')
),
pluginInferenceAlgoTracksterInferenceByCNNv4 = cms.PSet(
algo_verbosity = cms.int32(0),
onnxModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv4/onnx_models/energy_id_v0.onnx'),
inputNames = cms.vstring('input:0'),
outputNames = cms.vstring("output/regressed_energy:0", "output/id_probabilities:0"),
eid_min_cluster_energy = cms.double(1),
eid_n_layers = cms.int32(50),
eid_n_clusters = cms.int32(10),
doPID = cms.int32(1),
doRegression = cms.int32(0),
type = cms.string('TracksterInferenceByCNNv4')
),
pluginInferenceAlgoTracksterInferenceByDNN = cms.PSet(
algo_verbosity = cms.int32(0),
onnxPIDModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/DNN/patternrecognition/id_v0.onnx'),
onnxEnergyModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/DNN/patternrecognition/energy_v0.onnx'),
inputNames = cms.vstring('input'),
output_en = cms.vstring('enreg_output'),
output_id = cms.vstring('pid_output'),
eid_n_layers = cms.int32(50),
eid_n_clusters = cms.int32(10),
doPID = cms.int32(1),
doRegression = cms.int32(0),
type = cms.string('TracksterInferenceByDNN')
),
pluginInferenceAlgoTracksterInferenceByPFN = cms.PSet(
algo_verbosity = cms.int32(0),
onnxPIDModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/PFN/patternrecognition/id_v0.onnx'),
onnxEnergyModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/PFN/patternrecognition/energy_v0.onnx'),
inputNames = cms.vstring('input','input_tr_features'),
output_en = cms.vstring('enreg_output'),
output_id = cms.vstring('pid_output'),
eid_n_layers = cms.int32(50),
eid_n_clusters = cms.int32(10),
doPID = cms.int32(1),
doRegression = cms.int32(0),
type = cms.string('TracksterInferenceByPFN')
),
pluginInferenceAlgoTracksterInferenceByANN = cms.PSet(
algo_verbosity = cms.int32(0),
type = cms.string('TracksterInferenceByANN')
),
seeding_regions = cms.InputTag("hltTiclSeedingGlobal"),
time_layerclusters = cms.InputTag("hltHgcalMergeLayerClusters","timeLayerCluster")
)
from Configuration.ProcessModifiers.ticl_v5_cff import ticl_v5
ticl_v5.toModify(hltTiclTrackstersCLUE3DHigh.pluginPatternRecognitionByCLUE3D, computeLocalTime = cms.bool(True))
ticl_v5.toModify(hltTiclTrackstersCLUE3DHigh, inferenceAlgo = cms.string('TracksterInferenceByPFN'))
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