ATLAS Offline Software
MvaTESEvaluator.cxx
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1 /*
2  Copyright (C) 2002-2025 CERN for the benefit of the ATLAS collaboration
3 */
4 
5 // local include(s)
6 #include "tauRecTools/MvaTESEvaluator.h"
7 #include "tauRecTools/HelperFunctions.h"
8 
9 
10 MvaTESEvaluator::MvaTESEvaluator(const std::string& name)
11  : TauRecToolBase(name) {
12 }
13 
14 
15 StatusCode MvaTESEvaluator::initialize(){
16 
17  const std::string weightFile = find_file(m_sWeightFileName);
18  m_bdtHelper = std::make_unique<tauRecTools::BDTHelper>();
19  ATH_CHECK(m_bdtHelper->initialize(weightFile));
20 
21  if (!m_sWeightFileName0p.empty()) {
22  const std::string weightFile0p = find_file(m_sWeightFileName0p);
23  m_bdtHelper0p = std::make_unique<tauRecTools::BDTHelper>();
24  ATH_CHECK(m_bdtHelper0p->initialize(weightFile0p));
25  }
26 
27  return StatusCode::SUCCESS;
28 }
29 
30 
31 StatusCode MvaTESEvaluator::execute(xAOD::TauJet& xTau) const {
32 
33  std::map<TString, float*> availableVars;
34  MvaInputVariables vars;
35 
36  // Declare input variables to the reader
37  if (!inTrigger()) {
38  availableVars.insert( std::make_pair("TauJetsAuxDyn.mu", &vars.mu) );
39  availableVars.insert( std::make_pair("TauJetsAuxDyn.nVtxPU", &vars.nVtxPU) );
40  availableVars.insert( std::make_pair("TauJetsAuxDyn.rho", &vars.rho) );
41  availableVars.insert( std::make_pair("TauJetsAuxDyn.ClustersMeanCenterLambda", &vars.center_lambda) );
42  availableVars.insert( std::make_pair("TauJetsAuxDyn.ClustersMeanFirstEngDens", &vars.first_eng_dens) );
43  availableVars.insert( std::make_pair("TauJetsAuxDyn.ClustersMeanSecondLambda", &vars.second_lambda) );
44  availableVars.insert( std::make_pair("TauJetsAuxDyn.ClustersMeanPresamplerFrac", &vars.presampler_frac) );
45  availableVars.insert( std::make_pair("TauJetsAuxDyn.ClustersMeanEMProbability", &vars.eprobability) );
46  availableVars.insert( std::make_pair("TauJetsAuxDyn.ptIntermediateAxisEM/TauJetsAuxDyn.ptIntermediateAxis", &vars.ptEM_D_ptLC) );
47  availableVars.insert( std::make_pair("TauJetsAuxDyn.ptIntermediateAxis/TauJetsAuxDyn.ptCombined", &vars.ptLC_D_ptCombined) );
48  availableVars.insert( std::make_pair("TauJetsAuxDyn.etaPanTauCellBased", &vars.etaConstituent) );
49  if (m_bdtHelper0p && xTau.nTracks()==0) {
50  availableVars.insert( std::make_pair("log(TauJetsAuxDyn.ptCombined)", &vars.logPtCombined) );
51  availableVars.insert( std::make_pair("TauJetsAuxDyn.LeadClusterFrac", &vars.lead_cluster_frac) );
52  availableVars.insert( std::make_pair("TauJetsAuxDyn.centFrac", &vars.centFrac) );
53  availableVars.insert( std::make_pair("TauJetsAuxDyn.UpsilonCluster", &vars.upsilon_cluster) );
54  availableVars.insert( std::make_pair("TauJetsAuxDyn.ptJetSeed/TauJetsAuxDyn.ptCombined", &vars.ptSeed_D_ptCombined) );
55  }
56  else {
57  availableVars.insert( std::make_pair("TauJetsAuxDyn.ptPanTauCellBased/TauJetsAuxDyn.ptCombined", &vars.ptConstituent_D_ptCombined) );
58  availableVars.insert( std::make_pair("TauJetsAuxDyn.ptCombined", &vars.ptCombined) );
59  availableVars.insert( std::make_pair("TauJetsAuxDyn.PanTau_BDTValue_1p0n_vs_1p1n", &vars.PanTauBDT_1p0n_vs_1p1n) );
60  availableVars.insert( std::make_pair("TauJetsAuxDyn.PanTau_BDTValue_1p1n_vs_1pXn", &vars.PanTauBDT_1p1n_vs_1pXn) );
61  availableVars.insert( std::make_pair("TauJetsAuxDyn.PanTau_BDTValue_3p0n_vs_3pXn", &vars.PanTauBDT_3p0n_vs_3pXn) );
62  availableVars.insert( std::make_pair("TauJetsAuxDyn.nTracks", &vars.nTracks) );
63  availableVars.insert( std::make_pair("TauJetsAuxDyn.PFOEngRelDiff", &vars.PFOEngRelDiff) );
64  }
65  }
66  else {
67  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.mu", &vars.mu) );
68  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ClustersMeanCenterLambda", &vars.center_lambda) );
69  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ClustersMeanFirstEngDens", &vars.first_eng_dens) );
70  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ClustersMeanSecondLambda", &vars.second_lambda) );
71  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ClustersMeanPresamplerFrac", &vars.presampler_frac) );
72  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ClustersMeanEMProbability", &vars.eprobability) );
73  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.LeadClusterFrac", &vars.lead_cluster_frac) );
74  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.SecondClusterFrac", &vars.second_cluster_frac) );
75  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ThirdClusterFrac", &vars.third_cluster_frac) );
76  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.UpsilonCluster", &vars.upsilon_cluster) );
77  availableVars.insert( std::make_pair("log(TrigTauJetsAuxDyn.ptDetectorAxis)", &vars.logPtDetectorAxis) );
78  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.etaDetectorAxis", &vars.etaDetectorAxis) );
79  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ptIntermediateAxisEM/TrigTauJetsAuxDyn.ptDetectorAxis", &vars.ptEM_D_ptLC) );
80  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.ptDetectorAxis/TrigTauJetsAuxDyn.ptJetSeed", &vars.ptDetectorAxis_D_ptJetSeed) );
81  availableVars.insert( std::make_pair("TrigTauJetsAuxDyn.centFrac", &vars.centFrac) );
82  }
83 
84  // Retrieve average pileup
85  static const SG::ConstAccessor<float> acc_mu("mu");
86  vars.mu = acc_mu(xTau);
87 
88  // Retrieve cluster moments
89  xTau.detail(xAOD::TauJetParameters::ClustersMeanCenterLambda, vars.center_lambda);
90  xTau.detail(xAOD::TauJetParameters::ClustersMeanFirstEngDens, vars.first_eng_dens);
91  xTau.detail(xAOD::TauJetParameters::ClustersMeanEMProbability,vars.eprobability);
92  xTau.detail(xAOD::TauJetParameters::ClustersMeanSecondLambda, vars.second_lambda);
93  xTau.detail(xAOD::TauJetParameters::ClustersMeanPresamplerFrac, vars.presampler_frac);
94 
95  static const SG::ConstAccessor<float> acc_ptIntermediateAxisEM("ptIntermediateAxisEM");
96  float ptEM = acc_ptIntermediateAxisEM(xTau);
97 
98  if (!inTrigger()) {
99  static const SG::ConstAccessor<float> acc_ptCombined("ptCombined");
100  float ptCombined = acc_ptCombined(xTau);
101 
102  if (ptCombined==0.) {
103  xTau.setP4(xAOD::TauJetParameters::FinalCalib, 1., xTau.etaPanTauCellBased(), xTau.phiPanTauCellBased(), 0.);
104  // apply MVA calibration as default
105  xTau.setP4(1., xTau.etaPanTauCellBased(), xTau.phiPanTauCellBased(), 0.);
106  return StatusCode::SUCCESS;
107  }
108 
109  static const SG::ConstAccessor<int> acc_nVtxPU("nVtxPU");
110  vars.nVtxPU = acc_nVtxPU(xTau);
111 
112  static const SG::ConstAccessor<float> acc_rho("rho");
113  vars.rho = acc_rho(xTau);
114 
115  float ptLC = xTau.ptIntermediateAxis();
116 
117  float ptConstituent = xTau.ptPanTauCellBased();
118  vars.etaConstituent = xTau.etaPanTauCellBased();
119 
120  vars.ptEM_D_ptLC = (ptLC != 0.) ? ptEM / ptLC : 0.;
121  vars.ptLC_D_ptCombined = ptLC / ptCombined;
122 
123  float ptMVA = 0.;
124 
125  if (m_bdtHelper0p && xTau.nTracks()==0) {
126  vars.logPtCombined = std::log(ptCombined);
127  vars.ptSeed_D_ptCombined = xTau.ptJetSeed() / ptCombined;
128 
129  static const SG::ConstAccessor<float> acc_UpsilonCluster("UpsilonCluster");
130  vars.upsilon_cluster = acc_UpsilonCluster(xTau);
131 
132  static const SG::ConstAccessor<float> acc_LeadClusterFrac("LeadClusterFrac");
133  vars.lead_cluster_frac = acc_LeadClusterFrac(xTau);
134 
135  xTau.detail(xAOD::TauJetParameters::centFrac, vars.centFrac);
136 
137  ptMVA = float( ptCombined * m_bdtHelper0p->getResponse(availableVars) );
138  }
139  else {
140  vars.ptCombined = ptCombined;
141  vars.ptConstituent_D_ptCombined = ptConstituent / ptCombined;
142 
143  // Retrieve substructure info
144  static const SG::ConstAccessor<float> acc_PanTauBDT_1p0n_vs_1p1n("PanTau_BDTValue_1p0n_vs_1p1n");
145  static const SG::ConstAccessor<float> acc_PanTauBDT_1p1n_vs_1pXn("PanTau_BDTValue_1p1n_vs_1pXn");
146  static const SG::ConstAccessor<float> acc_PanTauBDT_3p0n_vs_3pXn("PanTau_BDTValue_3p0n_vs_3pXn");
147  // BDT values are initialised to -1111, while actual scores (when evaluated) are within [-5,1], so take max between BDT score and -5-epsilon
148  vars.PanTauBDT_1p0n_vs_1p1n = std::max(acc_PanTauBDT_1p0n_vs_1p1n(xTau), -5.1f);
149  vars.PanTauBDT_1p1n_vs_1pXn = std::max(acc_PanTauBDT_1p1n_vs_1pXn(xTau), -5.1f);
150  vars.PanTauBDT_3p0n_vs_3pXn = std::max(acc_PanTauBDT_3p0n_vs_3pXn(xTau), -5.1f);
151  vars.nTracks = static_cast<float>(xTau.nTracks());
152  xTau.detail(xAOD::TauJetParameters::PFOEngRelDiff, vars.PFOEngRelDiff);
153 
154  ptMVA = float( ptCombined * m_bdtHelper->getResponse(availableVars) );
155  }
156 
157  if (ptMVA<1.) ptMVA=1.;
158  xTau.setP4(xAOD::TauJetParameters::FinalCalib, ptMVA, vars.etaConstituent, xTau.phiPanTauCellBased(), 0.);
159  // apply MVA calibration as default
160  xTau.setP4(ptMVA, vars.etaConstituent, xTau.phiPanTauCellBased(), 0.);
161  }
162  else {
163  // protection but should never happen
164  if (xTau.ptDetectorAxis()==0. || xTau.ptJetSeed()==0.) {
165  xTau.setP4(xAOD::TauJetParameters::FinalCalib, 1., xTau.etaDetectorAxis(), xTau.phiDetectorAxis(), 0.);
166  xTau.setP4(1., xTau.etaDetectorAxis(), xTau.phiDetectorAxis(), 0.);
167  return StatusCode::SUCCESS;
168  }
169 
170  vars.logPtDetectorAxis = std::log(xTau.ptDetectorAxis());
171  vars.etaDetectorAxis = xTau.etaDetectorAxis();
172  vars.ptEM_D_ptLC = ptEM / xTau.ptDetectorAxis();
173  vars.ptDetectorAxis_D_ptJetSeed = xTau.ptDetectorAxis() / xTau.ptJetSeed();
174 
175  static const SG::ConstAccessor<float> acc_UpsilonCluster("UpsilonCluster");
176  static const SG::ConstAccessor<float> acc_LeadClusterFrac("LeadClusterFrac");
177  static const SG::ConstAccessor<float> acc_SecondClusterFrac("SecondClusterFrac");
178  static const SG::ConstAccessor<float> acc_ThirdClusterFrac("ThirdClusterFrac");
179 
180  vars.upsilon_cluster = acc_UpsilonCluster(xTau);
181  vars.lead_cluster_frac = acc_LeadClusterFrac(xTau);
182  vars.second_cluster_frac = acc_SecondClusterFrac(xTau);
183  vars.third_cluster_frac = acc_ThirdClusterFrac(xTau);
184 
185  xTau.detail(xAOD::TauJetParameters::centFrac, vars.centFrac);
186 
187  float ptMVA = float( xTau.ptDetectorAxis() * m_bdtHelper->getResponse(availableVars) );
188  if (ptMVA<1.) ptMVA=1.;
189 
190  xTau.setP4(xAOD::TauJetParameters::FinalCalib, ptMVA, vars.etaDetectorAxis, xTau.phiDetectorAxis(), 0.);
191  // apply MVA calibration
192  xTau.setP4(ptMVA, vars.etaDetectorAxis, xTau.phiDetectorAxis(), 0.);
193  }
194 
195  ATH_MSG_DEBUG("final calib:" << xTau.pt() << " " << xTau.eta() << " " << xTau.phi() << " " << xTau.e());
196 
197  return StatusCode::SUCCESS;
198 }
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Definition: MvaTESEvaluator.h:37
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