TICL/python/CLUE3DHighStep_cff.py

0001 import FWCore.ParameterSet.Config as cms
0002
0003 from RecoHGCal.TICL.TICLSeedingRegions_cff import ticlSeedingGlobal, ticlSeedingGlobalHFNose
0004 from RecoHGCal.TICL.trackstersProducer_cfi import trackstersProducer as _trackstersProducer
0005 from RecoHGCal.TICL.filteredLayerClustersProducer_cfi import filteredLayerClustersProducer as _filteredLayerClustersProducer
0006
0007 # CLUSTER FILTERING/MASKING
0008
0009 filteredLayerClustersCLUE3DHigh = _filteredLayerClustersProducer.clone(
0010     clusterFilter = "ClusterFilterByAlgoAndSize",
0011     min_cluster_size = 2, # inclusive
0012     iteration_label = "CLUE3DHigh"
0013 )
0014
0015 # PATTERN RECOGNITION
0016
0017 ticlTrackstersCLUE3DHigh = _trackstersProducer.clone(
0018     filtered_mask = "filteredLayerClustersCLUE3DHigh:CLUE3DHigh",
0019     seeding_regions = "ticlSeedingGlobal",
0020     itername = "CLUE3DHigh",
0021     patternRecognitionBy = "CLUE3D",
0022     pluginPatternRecognitionByCLUE3D = dict (
0023         criticalDensity = [0.6, 0.6, 0.6],
0024         criticalEtaPhiDistance = [0.025, 0.025, 0.025],
0025         kernelDensityFactor = [0.2, 0.2, 0.2],
0026         algo_verbosity = 0,
0027         doPidCut = True,
0028         cutHadProb = 999
0029     ),
0030     inferenceAlgo = cms.string('TracksterInferenceByCNNv4'),
0031     pluginInferenceAlgoTracksterInferenceByCNNv4 = cms.PSet(
0032         algo_verbosity = cms.int32(0),
0033         onnxModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv4/onnx_models/energy_id_v0.onnx'),
0034         inputNames  = cms.vstring('input:0'),
0035         outputNames = cms.vstring("output/regressed_energy:0", "output/id_probabilities:0"),
0036         eid_min_cluster_energy = cms.double(1),
0037         eid_n_layers = cms.int32(50),
0038         eid_n_clusters = cms.int32(10),
0039         doPID = cms.int32(1),
0040         doRegression = cms.int32(0),
0041         type = cms.string('TracksterInferenceByCNNv4')
0042     ),
0043     pluginInferenceAlgoTracksterInferenceByDNN = cms.PSet(
0044         algo_verbosity = cms.int32(0),
0045         onnxPIDModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/patternrecognition/id_v0.onnx'),
0046         onnxEnergyModelPath = cms.FileInPath('RecoHGCal/TICL/data/ticlv5/onnx_models/patternrecognition/energy_v0.onnx'),
0047         inputNames  = cms.vstring('input'),
0048         output_en   = cms.vstring('enreg_output'),
0049         output_id   = cms.vstring('pid_output'),
0050         eid_min_cluster_energy = cms.double(1),
0051         eid_n_layers = cms.int32(50),
0052         eid_n_clusters = cms.int32(10),
0053         doPID = cms.int32(1),
0054         doRegression = cms.int32(0),
0055         type = cms.string('TracksterInferenceByDNN')
0056     ),
0057     pluginInferenceAlgoTracksterInferenceByANN = cms.PSet(
0058       algo_verbosity = cms.int32(0),
0059       type = cms.string('TracksterInferenceByANN')
0060
0061     ),
0062
0063
0064 )
0065
0066 from Configuration.ProcessModifiers.ticl_v5_cff import ticl_v5
0067 ticl_v5.toModify(ticlTrackstersCLUE3DHigh.pluginPatternRecognitionByCLUE3D, computeLocalTime = cms.bool(True))
0068 ticl_v5.toModify(ticlTrackstersCLUE3DHigh.pluginPatternRecognitionByCLUE3D, usePCACleaning = cms.bool(True))
0069 ticl_v5.toModify(ticlTrackstersCLUE3DHigh.inferenceAlgo, type = cms.string('TracksterInferenceByDNN'))
0070
0071 ticlCLUE3DHighStepTask = cms.Task(ticlSeedingGlobal
0072     ,filteredLayerClustersCLUE3DHigh
0073     ,ticlTrackstersCLUE3DHigh)
0074