From e4385e5f8d43560a51c0d24a0b85bad878c2e9b5 Mon Sep 17 00:00:00 2001 From: doloresgarcia Date: Wed, 26 Jun 2024 17:09:42 +0200 Subject: [PATCH] broken evaluation for debug --- Tracking/include/GenFitter_evaluation.h | 94 +++++++ Tracking/model_multivector_1_input.onnx | Bin 0 -> 7828198 bytes Tracking/src/GenFitter_evaluation.cpp | 319 ++++++++++++++++++++++++ Tracking/test/runIDEAtracker_eval.py | 67 +++++ 4 files changed, 480 insertions(+) create mode 100644 Tracking/include/GenFitter_evaluation.h create mode 100644 Tracking/model_multivector_1_input.onnx create mode 100644 Tracking/src/GenFitter_evaluation.cpp create mode 100644 Tracking/test/runIDEAtracker_eval.py diff --git a/Tracking/include/GenFitter_evaluation.h b/Tracking/include/GenFitter_evaluation.h new file mode 100644 index 0000000..0f2597f --- /dev/null +++ b/Tracking/include/GenFitter_evaluation.h @@ -0,0 +1,94 @@ +#pragma once + +// GAUDI +#include "Gaudi/Property.h" +// #include "GaudiAlg/GaudiAlgorithm.h" +#include "Gaudi/Algorithm.h" +// K4FWCORE +#include "k4FWCore/DataHandle.h" + +// EDM4HEP +#include "edm4hep/SimTrackerHitCollection.h" +#if __has_include("edm4hep/TrackerHit3DCollection.h") +#include "edm4hep/TrackerHit3DCollection.h" +#else +#include "edm4hep/TrackerHit3D.h" +#include "extension/TrackerHit3D.h" +namespace edm4hep { + using TrackerHit3DCollection = edm4hep::TrackerHitCollection; +} // namespace edm4hep +#endif + +#include "extension/TrackCollection.h" +#include "extension/TrackCollection.h" +#include "extension/TrackerHit3DCollection.h" +// EDM4HEP extension +#include "extension/DriftChamberDigiCollection.h" +#include "extension/DriftChamberDigiLocalCollection.h" +#include "extension/MCRecoDriftChamberDigiAssociationCollection.h" + +#include "onnxruntime_cxx_api.h" +#include +#include +#include +// GENFIT +//#include "WireMeasurement.h" + +/** @class GenFitter_eval + * + * + * + * @author Maria Dolores Garcia, Brieuc Francois + * @date 2023-03 + * + */ + +class GenFitter_eval : public Gaudi::Algorithm { +public: + explicit GenFitter_eval(const std::string&, ISvcLocator*); + virtual ~GenFitter_eval(); + /** Initialize. + * @return status code + */ + virtual StatusCode initialize() final; + /** Execute. + * @return status code + */ + virtual StatusCode execute(const EventContext&) const final; + /** Finalize. + * @return status code + */ + virtual StatusCode finalize() final; + +private: + /// Pointer to the ONNX enviroment + std::unique_ptr fEnv; + /// Pointer to the ONNX inference session + std::unique_ptr fSession; + /// ONNX settings + Ort::SessionOptions fSessionOptions; + /// ONNX memory info + const OrtMemoryInfo* fInfo; + struct MemoryInfo; + /// the input names represent the names given to the model + /// when defining the model's architecture (if applicable) + /// they can also be retrieved from model.summary() + std::vector fInames; + std::vector fOnames; + + std::string modelPath={}; + // Input tracker hit collection name + mutable DataHandle m_input_hits_CDC{"inputHits_CDC", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_hits_VTXIB{"inputHits_VTXIB", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_hits_VTXD{"inputHits_VTXD", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_hits_VTXOB{"inputHits_VTXOB", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_Association_CDC{"inputAssociation_CDC_sim", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_hits_CDC_sim{"inputHits_CDC_sim", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_hits_VTXIB_sim{"inputHits_VTXIB_sim", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_hits_VTXD_sim{"inputHits_VTXD_sim", Gaudi::DataHandle::Reader, this}; + mutable DataHandle m_input_hits_VTXOB_sim{"inputHits_VTXOB_sim", Gaudi::DataHandle::Reader, this}; + + // Output track collection name + mutable DataHandle m_output_tracks{"outputTracks", Gaudi::DataHandle::Writer, this}; + mutable DataHandle m_output_hits{"outputHits", Gaudi::DataHandle::Writer, this}; +}; diff --git a/Tracking/model_multivector_1_input.onnx b/Tracking/model_multivector_1_input.onnx new file mode 100644 index 0000000000000000000000000000000000000000..daceb22a8ffe16aca145f28cc5e63cfd0a0d6745 GIT binary patch literal 7828198 zcmeEvcVJXS@P86QJ6Z@mNbdn+u3yOQUT6ZLNR@5~A%swpkc28F^j<`&6zPb90@8E4 z2Z%HQsUnJ0rB?x^%5QSHxA*q)?%lh9e*ONw=pWo&c6N4VXJ=>kGxJ`aJb}5BhNLDY z$Mg!ysR_}9sOv1=dd*K|4$KubFuHG)Iw*hr#DtX8=!DcLwa!p6kMJ$Hq$(#g7!Vtr zKOlEx9v{blOMU${KC0R(2eqRYO;Dct(J2`{7%Tc`dGRGhYtQU_#A1WFHFR)_>BYA=K4$cNaV7*#SU?ay&BVwjZV1q+o zql2wUB(PqqOyDqX3_8&mc!BvD4smb}3(TEqC!tJYy_Ccjp&e&Xda*&ti`-BpFcLnf zg)TK>sg3edBY}vsHNDu@c(Hvs!+uv_t`+*xF}cHJ<>u_lAhs)oa_a=vdV#e;B)35= zFLx7Fp1!bnk_MzkIc84h_}3)#s}VjJ0&}PIjgNsv6O^}2<_CkOVov)z+B7ZHp$AZ z3UV7YvT}3wWfa?&Lb;8C+=8iT!o+gxl*z5-?9M2*J0)^!1!L2yncN0BxwV{q8O8Rc zOm3~(A-7gAHLX@Gw@F^^NR_bs1@#I2Y4pM`!b;MDAI$U>8s;mEVOf2JmUDk5vHRn7 z$nP?Ouh0rUPs=t|ljO!KY%^MJXEiC`S%qyzYY=p3beOGHyt$e@Y_5W@&~m%0$^Gui 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"onnxruntime_cxx_api.h" +#include +#include "edm4hep/TrackerHit3D.h" +#include "extension/MutableTrackerHit3D.h" + +torch::Tensor find_condpoints1(torch::Tensor betas, torch::Tensor unassigned, float tbeta) { + int n_points = unassigned.size(0); + int size_b = betas.size(0); + auto select_condpoints = betas.gt(tbeta); + auto mask_unassigned = torch::zeros({size_b}, torch::dtype(torch::kBool)); + for (int i = 0; i < n_points-1; ++i) { + auto ii = unassigned.index({i}); + mask_unassigned.index_put_({ii.squeeze()}, true); + } + select_condpoints = mask_unassigned * select_condpoints; + auto indices_condpoints = select_condpoints.nonzero(); + auto betas_condpoints = -betas.index({indices_condpoints}); + auto sorted_indices = torch::argsort(betas_condpoints, /*dim=*/0, /*descending=*/false); + indices_condpoints = indices_condpoints.index({sorted_indices}); + return indices_condpoints; +} + +// Main clustering function +torch::Tensor get_clustering1(std::vector output_vector, int64_t num_rows, float tbeta=0.6, float td=0.05) { + + torch::Tensor output_model_tensor = torch::from_blob(output_vector.data(), {num_rows,4}, torch::kFloat32); + auto rows_output_model = torch::arange(0, output_model_tensor.size(0), torch::kLong); + auto coord_ind_output_model = torch::arange(0, 3, torch::kLong); + auto betas = output_model_tensor.index({rows_output_model,3}); + auto X = output_model_tensor.index({torch::indexing::Slice(), torch::indexing::Slice(0, 3)}); + int n_points = betas.size(0); + auto select_condpoints = betas.gt(tbeta); + auto indices_condpoints = find_condpoints1(betas, torch::arange(n_points), tbeta); + auto clustering = -1 * torch::ones({n_points}, torch::kLong); + int index_assignation = 0; + auto unassigned = torch::arange(n_points); + while (indices_condpoints.size(0) > 0 && unassigned.size(0) > 0) { + auto index_condpoint = indices_condpoints.index({0}); + auto d = (X.index({unassigned}) - X.index({index_condpoint})).norm(2, -1).squeeze(); + auto mask_distance = d.lt(td); + auto mask_distance_ind = mask_distance.nonzero(); + auto assigned_to_this_condpoint = unassigned.index({mask_distance_ind}); + clustering.index_put_({assigned_to_this_condpoint}, index_assignation); + auto mask_distance_out = d.ge(td); + auto mask_distance_ind_out = mask_distance_out.squeeze(0).nonzero(); + unassigned = unassigned.index({mask_distance_ind_out}); + indices_condpoints = find_condpoints1(betas, unassigned, tbeta); + index_assignation += 1; + } + return clustering; +} + +std::string print_shape1(const std::vector& v) { +std::stringstream ss(""); +for (std::size_t i = 0; i < v.size() - 1; i++) ss << v[i] << "x"; +ss << v[v.size() - 1]; +return ss.str(); +} + +DECLARE_COMPONENT(GenFitter_eval) + +GenFitter_eval::GenFitter_eval(const std::string& aName, ISvcLocator* aSvcLoc) : Gaudi::Algorithm(aName, aSvcLoc) { + declareProperty("modelPath", modelPath, "Path to the model"); + declareProperty("inputHits_CDC", m_input_hits_CDC, "Input CDC tracker hit collection name"); + declareProperty("inputHits_VTXIB", m_input_hits_VTXIB, "Input VTXIB tracker hit collection name"); + declareProperty("inputHits_VTXD", m_input_hits_VTXD, "Input VTXD tracker hit collection name"); + declareProperty("inputHits_VTXOB", m_input_hits_VTXOB, "Input VTXOB tracker hit collection name"); + declareProperty("inputAssociation_CDC_sim", m_input_Association_CDC, "Input CDC association collection name"); + declareProperty("inputHits_CDC_sim", m_input_hits_CDC_sim, "Input CDC sim hit collection name"); + declareProperty("inputHits_VTXIB_sim", m_input_hits_VTXIB_sim, "Input VTXIB sim hit collection name"); + declareProperty("inputHits_VTXD_sim", m_input_hits_VTXD_sim, "Input VTXD sim hit collection name"); + declareProperty("inputHits_VTXOB_sim", m_input_hits_VTXOB_sim, "Input VTXOB sim hit collection name"); + declareProperty("outputTracks", m_output_tracks, "Output track collection name"); + declareProperty("outputHits", m_output_hits, "Output hits collection name"); +} + +GenFitter_eval::~GenFitter_eval() {} + +StatusCode GenFitter_eval::initialize() { + fInfo = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault); + auto envLocal = std::make_unique(ORT_LOGGING_LEVEL_WARNING, "ONNX_Runtime"); + fEnv = std::move(envLocal); + // std::cout << "Environment created" << std::endl; + // std::string model_path = "/afs/cern.ch/work/m/mgarciam/private/k4RecTracker_dev_0/Tracking/model_multivector_1_input.onnx"; + fSessionOptions.SetIntraOpNumThreads(1); + fSessionOptions.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_DISABLE_ALL); + // printf("Using Onnxruntime C++ API\n"); + auto sessionLocal = std::make_unique(*fEnv, modelPath.c_str(), fSessionOptions); + fSession = std::move(sessionLocal); + // printf("Starting to run inference\n"); + Ort::AllocatorWithDefaultOptions allocator; + std::size_t i = 0; + const auto input_name = fSession->GetInputNameAllocated(i, allocator).release(); + + const auto output_names = fSession->GetOutputNameAllocated(i, allocator).release(); + + fInames.push_back(input_name); + fOnames.push_back(output_names); + return StatusCode::SUCCESS;} + + +StatusCode GenFitter_eval::execute(const EventContext&) const { + // Get the input collection with tracker hits + const extension::DriftChamberDigiCollection* input_hits_CDC = m_input_hits_CDC.get(); + // std::cout << "Input Hit collection size CDC: " << input_hits_CDC->size() << std::endl; + const edm4hep::TrackerHit3DCollection* inputHits_VTXD = m_input_hits_VTXD.get(); + const edm4hep::TrackerHit3DCollection* inputHits_VTXIB = m_input_hits_VTXIB.get(); + const edm4hep::TrackerHit3DCollection* inputHits_VTXOB = m_input_hits_VTXOB.get(); + + const edm4hep::SimTrackerHitCollection* inputHits_VTXD_sim = m_input_hits_VTXD_sim.get(); + const edm4hep::SimTrackerHitCollection* inputHits_VTXIB_sim = m_input_hits_VTXOB_sim.get(); + const edm4hep::SimTrackerHitCollection* inputHits_VTXOB_sim = m_input_hits_VTXOB_sim.get(); + const edm4hep::SimTrackerHitCollection* inputHits_CDC_sim = m_input_hits_CDC_sim.get(); + const extension::MCRecoDriftChamberDigiAssociation* inputAssociation_CDC_sim = m_input_Association_CDC.get(); + std::cout << "Input Hit collection size VTXD: " << inputHits_VTXD_sim->size() << std::endl; + // std::cout << "Input Hit collection size VTXIB: " << inputHits_VTXIB->size() << std::endl; + // std::cout << "Input Hit collection size VTXOB: " << inputHits_VTXOB->size() << std::endl; + + // For now there is a 1to1 correspondence between sim and digi so we can get the list of mc for each hit + std::vector ListHitMC_VTXD; + for (const auto& input_sim_hit : *inputHits_VTXD_sim) { + auto MC_particle = input_sim_hit.getParticle(); + auto object_id_MC = MC_particle.getObjectID(); + auto index_MC = object_id_MC.index; + ListHitMC_VTXD.push_back(index_MC); + } + std::vector ListHitMC_VTXIB; + for (const auto& input_sim_hit : *inputHits_VTXIB_sim) { + auto MC_particle = input_sim_hit.getParticle(); + auto object_id_MC = MC_particle.getObjectID(); + auto index_MC = object_id_MC.index; + ListHitMC_VTXIB.push_back(index_MC); + } + std::vector ListHitMC_VTXOB; + for (const auto& input_sim_hit : *inputHits_VTXOB_sim) { + auto MC_particle = input_sim_hit.getParticle(); + auto object_id_MC = MC_particle.getObjectID(); + auto index_MC = object_id_MC.index; + ListHitMC_VTXOB.push_back(index_MC); + } + + // size_t size_total = size_CDC+size_VTXD+size_VTXIB+size_VTXOB; + std::vector ListGlobalInputs; + std::vector ListHitType_VTXD; + int it = 0; + int it_0 = 0; + for (const auto& input_sim_hit : *inputHits_VTXD) { + ListGlobalInputs.push_back(input_sim_hit.getPosition().x); + ListGlobalInputs.push_back(input_sim_hit.getPosition().y); + ListGlobalInputs.push_back(input_sim_hit.getPosition().z); + ListGlobalInputs.push_back(1.0); + ListGlobalInputs.push_back(0.0); + ListGlobalInputs.push_back(0.0); + ListGlobalInputs.push_back(0.0); + ListHitType_VTXD.push_back(it); + it += 1; + it_0 += 1; + } + torch::Tensor ListHitType_VTXD_tensor = torch::from_blob(ListHitType_VTXD.data(), {it_0}, torch::kFloat32); + std::cout << "Here1" << std::endl; + std::vector ListHitType_VTXIB; + int it_1 = 0; + for (const auto& input_sim_hit : *inputHits_VTXIB) { + ListGlobalInputs.push_back(input_sim_hit.getPosition().x); + ListGlobalInputs.push_back(input_sim_hit.getPosition().y); + ListGlobalInputs.push_back(input_sim_hit.getPosition().z); + ListGlobalInputs.push_back(1.0); + ListGlobalInputs.push_back(0.0); + ListGlobalInputs.push_back(0.0); + ListGlobalInputs.push_back(0.0); + ListHitType_VTXIB.push_back(it); + it += 1; + it_1 += 1; + } + torch::Tensor ListHitType_VTXIB_tensor = torch::from_blob(ListHitType_VTXIB.data(), {it_1}, torch::kFloat32); + // std::cout << "Input Hit collection size inputHits_VTXIB: " << it < ListHitType_VTXOB; + int it_2 = 0; + for (const auto& input_sim_hit : *inputHits_VTXOB) { + ListGlobalInputs.push_back(input_sim_hit.getPosition().x); + ListGlobalInputs.push_back(input_sim_hit.getPosition().y); + ListGlobalInputs.push_back(input_sim_hit.getPosition().z); + ListGlobalInputs.push_back(1.0); + ListGlobalInputs.push_back(0.0); + ListGlobalInputs.push_back(0.0); + ListGlobalInputs.push_back(0.0); + ListHitType_VTXOB.push_back(it); + it += 1; + it_2 += 1; + } + torch::Tensor ListHitType_VTXOB_tensor = torch::from_blob(ListHitType_VTXOB.data(), {it_2}, torch::kFloat32); + // std::cout << "Input Hit collection size inputHits_VTXOB: " << it < ListHitMC_CDC; + std::vector ListHitType_CDC; + for (const auto& input_sim_hit : *input_hits_CDC) { + ListGlobalInputs.push_back(input_sim_hit.getLeftPosition().x); + ListGlobalInputs.push_back(input_sim_hit.getLeftPosition().y); + ListGlobalInputs.push_back(input_sim_hit.getLeftPosition().z); + ListGlobalInputs.push_back(0.0); + ListGlobalInputs.push_back(input_sim_hit.getRightPosition().x - input_sim_hit.getLeftPosition().x); + ListGlobalInputs.push_back(input_sim_hit.getRightPosition().y - input_sim_hit.getLeftPosition().y); + ListGlobalInputs.push_back(input_sim_hit.getRightPosition().z - input_sim_hit.getLeftPosition().z); + ListHitType_CDC.push_back(it); + + // auto association_cdc = inputAssociation_CDC_sim[it_3]; + // auto hit_reference = association_cdc.getSim(); + // auto corresponding_sim_hit_CDC = hit_reference; + // auto corresponding_sim_hit_CDC_id = corresponding_sim_hit_CDC.getObjectID(); + // std::cout << "Input Hit association CDC: " << corresponding_sim_hit_CDC_id.index <at(index_hit); + // auto MC_particle = corresponding_sim_hit_CDC.getParticle(); + // auto object_id_MC = MC_particle.getObjectID(); + // auto index_MC = object_id_MC.index; + // ListHitMC_CDC.push_back(index_MC); + it += 1; + it_3 += 1; + } + torch::Tensor ListHitType_CDC_tensor = torch::from_blob(ListHitType_CDC.data(), {it_3}, torch::kFloat32); + // std::cout << "Input Hit collection size CDC: " << it < tensor_shape = {it, 7}; + std::vector input_tensors; + input_tensors.emplace_back( Ort::Value::CreateTensor(fInfo, ListGlobalInputs.data(), total_size, tensor_shape.data(), tensor_shape.size())); + + auto output_tensors = fSession->Run(Ort::RunOptions{nullptr}, fInames.data(), input_tensors.data(), + fInames.size(), fOnames.data(), fOnames.size()); + // std::cout << "Done!" << std::endl; + // Get the outputs and covert to vector + float* floatarr = output_tensors.front().GetTensorMutableData(); + std::vector output_vector(floatarr, floatarr + it*4); + auto clustering = get_clustering1(output_vector, it); + torch::Tensor unique_tensor; + torch::Tensor inverse_indices; + std::tie(unique_tensor, inverse_indices) = at::_unique(clustering, true, true); + + // std::cout << "Clustering: " << clustering << std::endl; + // std::cout << "inverse_indices: " << inverse_indices << std::endl; + + + // std::cout << "indices: " << clustering.index({indices}) << std::endl; + extension::TrackCollection* output_tracks = m_output_tracks.createAndPut(); + extension::TrackerHit3DCollection* output_hits= m_output_hits.createAndPut(); + int64_t number_of_tracks = unique_tensor.numel(); + std::cout << "number_of_tracks: " << number_of_tracks << std::endl; + std::cout << "Writing data" << std::endl; + for (int i = 0; i < number_of_tracks; ++i) { + auto id_of_track = unique_tensor.index({i}); + auto output_track = output_tracks->create(); + // set global properties + output_track.setChi2(1.); + output_track.setNdf(1); + output_track.setDEdx(1.); + torch::Tensor mask = (clustering == id_of_track); + torch::Tensor indices = torch::nonzero(mask); + int64_t number_of_hits = indices.numel(); + for (int j = 0; j < number_of_hits; ++j) { + auto index_id = indices.index({j}); + torch::Tensor mask_VTXD = (ListHitType_VTXD_tensor == index_id); + torch::Tensor mask_VTXIB = (ListHitType_VTXIB_tensor == index_id); + torch::Tensor mask_VTOB = (ListHitType_VTXOB_tensor == index_id); + torch::Tensor mask_CDC = (ListHitType_CDC_tensor == index_id); + if ((torch::sum(mask_VTXD)>0).item()){ + // The hit belong to vtxd + auto hit = inputHits_VTXD->at(index_id.item()); + auto hit_extension = output_hits->create(); + hit_extension.setCellID(hit.getCellID()); + hit_extension.setType(1); + hit_extension.setEDep(ListHitMC_VTXD[index_id.item()]); + hit_extension.setPosition(hit.getPosition()); + // output_track.addToTrackerHits(hit_extension); + + // add this hit to some collection + } else if ((torch::sum(mask_VTXIB)>0).item()){ + index_id = index_id-it_0; + auto hit = inputHits_VTXIB->at(index_id.item()); + auto hit_extension = output_hits->create(); + hit_extension.setCellID(hit.getCellID()); + hit_extension.setType(1); + // hit_extension.setEDep(ListHitMC_VTXIB[index_id.item()]); + hit_extension.setPosition(hit.getPosition()); + // output_track.addToTrackerHits(hit_extension); + } else if ((torch::sum(mask_VTOB)>0).item()){ + index_id = index_id-(it_1+it_0); + auto hit = inputHits_VTXOB->at(index_id.item()); + auto hit_extension = output_hits->create(); + hit_extension.setCellID(hit.getCellID()); + hit_extension.setType(1); + // hit_extension.setEDep(ListHitMC_VTXOB[index_id.item()]); + hit_extension.setPosition(hit.getPosition()); + output_track.addToTrackerHits(hit_extension); + } else if ((torch::sum(mask_CDC)>0).item()){ + index_id = index_id-(it_1+it_2 +it_0); + auto hit = input_hits_CDC->at(index_id.item()); + auto hit_extension = output_hits->create(); + hit_extension.setCellID(hit.getCellID()); + hit_extension.setType(0); + //hit_extension.setEDep(ListHitMC_CDC[index_id.item()]); + // hit_extension.setEDep(0); + hit_extension.setPosition(hit.getLeftPosition()); + output_track.addToTrackerHits(hit_extension); + } + } + } + + + return StatusCode::SUCCESS; +} + +StatusCode GenFitter_eval::finalize() { return StatusCode::SUCCESS; } + diff --git a/Tracking/test/runIDEAtracker_eval.py b/Tracking/test/runIDEAtracker_eval.py new file mode 100644 index 0000000..2eb9bac --- /dev/null +++ b/Tracking/test/runIDEAtracker_eval.py @@ -0,0 +1,67 @@ +import os + +from Gaudi.Configuration import * + +# Loading the input SIM file +from Configurables import k4DataSvc, PodioInput + +evtsvc = k4DataSvc("EventDataSvc") +evtsvc.input = "output_IDEA_DIGI.root" +inp = PodioInput("InputReader") + + +# pattern recognition over digitized hits +from Configurables import GenFitter_eval + +dch_tracking = GenFitter_eval( + "GenFitter", + modelPath="/afs/cern.ch/work/m/mgarciam/private/k4RecTracker_dev_0/Tracking/model_multivector_1_input.onnx", + inputHits_CDC="CDCHDigis", + inputHits_VTXD="VTXDDigis", + inputHits_VTXIB="VTXIBDigis", + inputHits_VTXOB="VTXOBDigis", + inputHits_CDC_sim="CDCHHits", + inputHits_VTXD_sim="VTXDCollection", + inputHits_VTXIB_sim="VTXIBCollection", + inputHits_VTXOB_sim="VTXOBCollection", + inputAssociation_CDC_sim="CDCHDigisAssociation", + outputTracks="CDCHTracks", + outputHits="Hits", + OutputLevel=INFO, +) + +################ Output +from Configurables import PodioOutput + +out = PodioOutput("out", OutputLevel=INFO) +out.outputCommands = ["keep *"] + +out.filename = "output_tracking.root" + +# CPU information +from Configurables import AuditorSvc, ChronoAuditor + +chra = ChronoAuditor() +audsvc = AuditorSvc() +audsvc.Auditors = [chra] +out.AuditExecute = True + +from Configurables import EventCounter + +event_counter = EventCounter("event_counter") +event_counter.Frequency = 1 + +from Configurables import ApplicationMgr + +ApplicationMgr( + TopAlg=[ + inp, + event_counter, + dch_tracking, + out, + ], + EvtSel="NONE", + EvtMax=1, + ExtSvc=[evtsvc, audsvc], + StopOnSignal=True, +)

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