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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,7 +1,7 @@ | ||
| import FWCore.ParameterSet.Config as cms | ||
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| from RecoMTD.TrackExtender.trackExtenderWithMTD_cfi import * | ||
| from RecoMTD.TimingIDTools.trackPUIDMVA_cfi import * | ||
| from RecoMTD.TimingIDTools.mtdTrackQualityMVA_cfi import * | ||
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| fastTimingGlobalRecoTask = cms.Task(trackExtenderWithMTD,trackPUIDMVA) | ||
| fastTimingGlobalRecoTask = cms.Task(trackExtenderWithMTD,mtdTrackQualityMVA) | ||
| fastTimingGlobalReco = cms.Sequence(fastTimingGlobalRecoTask) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,5 @@ | ||
| import FWCore.ParameterSet.Config as cms | ||
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| from RecoMTD.TimingIDTools.mtdTrackQualityMVAProducer_cfi import * | ||
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| mtdTrackQualityMVA = mtdTrackQualityMVAProducer.clone() |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,52 @@ | ||
| #include "RecoMTD/TimingIDTools/interface/MTDTrackQualityMVA.h" | ||
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| MTDTrackQualityMVA::MTDTrackQualityMVA(std::string weights_file) { | ||
| std::string options("!Color:Silent"); | ||
| std::string method("BDT"); | ||
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| std::string vars_array[] = { MTDTRACKQUALITYMVA_VARS(VAR_STRING) }; | ||
| int nvars = sizeof(vars_array) / sizeof(vars_array[0]); | ||
| vars_.assign(vars_array,vars_array+nvars); | ||
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| mva_ = std::make_unique<TMVAEvaluator>(); | ||
| mva_->initialize(options, method, weights_file, vars_, spec_vars_, true, false); //use GBR, GradBoost | ||
| } | ||
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| float MTDTrackQualityMVA::operator()(const reco::TrackRef& trk, | ||
| const reco::TrackRef& ext_trk, | ||
| const edm::ValueMap<float>& btl_chi2s, | ||
| const edm::ValueMap<float>& btl_time_chi2s, | ||
| const edm::ValueMap<float>& etl_chi2s, | ||
| const edm::ValueMap<float>& etl_time_chi2s, | ||
| const edm::ValueMap<float>& tmtds, | ||
| const edm::ValueMap<float>& trk_lengths) const { | ||
| const auto& pattern = ext_trk->hitPattern(); | ||
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| std::map<std::string, float> vars; | ||
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| //---training performed only above 0.5 GeV | ||
| constexpr float minPtForMVA = 0.5; | ||
| if (trk->pt() < minPtForMVA) | ||
| return -1; | ||
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| //---training performed only for tracks with MTD hits | ||
| if (tmtds[ext_trk] > 0) { | ||
| vars.emplace(vars_[pt], trk->pt()); | ||
| vars.emplace(vars_[eta], trk->eta()); | ||
| vars.emplace(vars_[phi], trk->phi()); | ||
| vars.emplace(vars_[chi2], trk->chi2()); | ||
| vars.emplace(vars_[ndof], trk->ndof()); | ||
| vars.emplace(vars_[numberOfValidHits], trk->numberOfValidHits()); | ||
| vars.emplace(vars_[numberOfValidPixelBarrelHits], pattern.numberOfValidPixelBarrelHits()); | ||
| vars.emplace(vars_[numberOfValidPixelEndcapHits], pattern.numberOfValidPixelEndcapHits()); | ||
| vars.emplace(vars_[btlMatchChi2], btl_chi2s.contains(ext_trk.id()) ? btl_chi2s[ext_trk] : -1); | ||
| vars.emplace(vars_[btlMatchTimeChi2], btl_time_chi2s.contains(ext_trk.id()) ? btl_time_chi2s[ext_trk] : -1); | ||
| vars.emplace(vars_[etlMatchChi2], etl_chi2s.contains(ext_trk.id()) ? etl_chi2s[ext_trk] : -1); | ||
| vars.emplace(vars_[etlMatchTimeChi2], etl_time_chi2s.contains(ext_trk.id()) ? etl_time_chi2s[ext_trk] : -1); | ||
| vars.emplace(vars_[mtdt], tmtds[ext_trk]); | ||
| vars.emplace(vars_[path_len], trk_lengths[ext_trk]); | ||
| return 1. / | ||
| (1 + sqrt(2 / (1 + mva_->evaluate(vars, false)) - 1)); //return values between 0-1 (probability) | ||
| } else | ||
| return -1; | ||
| } |
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