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DPFIsolation.cc
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1 /*
2  * \class DPFIsolation
3  *
4  * Deep ParticleFlow tau isolation using Deep NN.
5  *
6  * \author Owen Colegrove, UCSB
7  */
8 
9 #include "RecoTauTag/RecoTau/interface/DeepTauBase.h"
10 
11 namespace {
12 
13 inline int getPFCandidateIndex(const edm::Handle<pat::PackedCandidateCollection>& pfcands,
14  const reco::CandidatePtr& cptr)
15 {
16  for(unsigned int i = 0; i < pfcands->size(); ++i) {
17  if(reco::CandidatePtr(pfcands,i) == cptr)
18  return i;
19  }
20  return -1;
21 }
22 } // anonymous namespace
23 
24 #if __cplusplus < 201703L
25 namespace std {
26  template<class T>
27  inline constexpr const T& clamp( const T& v, const T& lo, const T& hi )
28  {
29  return (v < lo) ? lo : (v > hi)? hi : v;
30  }
31 }
32 #endif
33 
34 class DPFIsolation : public deep_tau::DeepTauBase {
35 public:
36  static const OutputCollection& GetOutputs()
37  {
38  const size_t tau_index = 0;
39  static const OutputCollection outputs_ = { { "VSall", Output({tau_index}, {}) } };
40  return outputs_;
41  };
42 
43  static unsigned getNumberOfParticles(unsigned graphVersion)
44  {
45  static const std::map<unsigned, unsigned> nparticles { { 0, 60 }, { 1, 36 } };
46  return nparticles.at(graphVersion);
47  }
48 
49  static unsigned GetNumberOfFeatures(unsigned graphVersion)
50  {
51  static const std::map<unsigned, unsigned> nfeatures { { 0, 47 }, { 1, 51 } };
52  return nfeatures.at(graphVersion);
53  }
54 
55  static void fillDescriptions(edm::ConfigurationDescriptions& descriptions)
56  {
57  edm::ParameterSetDescription desc;
58  desc.add<edm::InputTag>("pfcands", edm::InputTag("packedPFCandidates"));
59  desc.add<edm::InputTag>("taus", edm::InputTag("slimmedTaus"));
60  desc.add<edm::InputTag>("vertices", edm::InputTag("offlineSlimmedPrimaryVertices"));
61  desc.add<std::string>("graph_file", "RecoTauTag/TrainingFiles/data/DPFTauId/DPFIsolation_2017v0_quantized.pb");
62  desc.add<unsigned>("version", 0);
63  desc.add<bool>("mem_mapped", false);
64 
65  edm::ParameterSetDescription descWP;
66  descWP.add<std::string>("VVVLoose", "0");
67  descWP.add<std::string>("VVLoose", "0");
68  descWP.add<std::string>("VLoose", "0");
69  descWP.add<std::string>("Loose", "0");
70  descWP.add<std::string>("Medium", "0");
71  descWP.add<std::string>("Tight", "0");
72  descWP.add<std::string>("VTight", "0");
73  descWP.add<std::string>("VVTight", "0");
74  descWP.add<std::string>("VVVTight", "0");
75  desc.add<edm::ParameterSetDescription>("VSallWP", descWP);
76  descriptions.add("DPFTau2016v0", desc);
77  }
78 
79  explicit DPFIsolation(const edm::ParameterSet& cfg,const deep_tau::DeepTauCache* cache) :
80  DeepTauBase(cfg, GetOutputs(), cache),
81  pfcand_token(consumes<pat::PackedCandidateCollection>(cfg.getParameter<edm::InputTag>("pfcands"))),
82  vtx_token(consumes<reco::VertexCollection>(cfg.getParameter<edm::InputTag>("vertices"))),
83  graphVersion(cfg.getParameter<unsigned>("version"))
84  {
85  const auto& shape = cache_->getGraph().node(0).attr().at("shape").shape();
86 
87  if(!(graphVersion == 1 || graphVersion == 0 ))
88  throw cms::Exception("DPFIsolation") << "unknown version of the graph_ file.";
89 
90  if(!(shape.dim(1).size() == getNumberOfParticles(graphVersion) && shape.dim(2).size() == GetNumberOfFeatures(graphVersion)))
91  throw cms::Exception("DPFIsolation") << "number of inputs does not match the expected inputs for the given version";
92 
93  }
94 
95 private:
96  tensorflow::Tensor getPredictions(edm::Event& event, const edm::EventSetup& es,
97  edm::Handle<TauCollection> taus) override
98  {
99  edm::Handle<pat::PackedCandidateCollection> pfcands;
100  event.getByToken(pfcand_token, pfcands);
101 
102  edm::Handle<reco::VertexCollection> vertices;
103  event.getByToken(vtx_token, vertices);
104 
105  tensorflow::Tensor tensor(tensorflow::DT_FLOAT, {1,
106  static_cast<int>(getNumberOfParticles(graphVersion)), static_cast<int>(GetNumberOfFeatures(graphVersion))});
107 
108  tensorflow::Tensor predictions(tensorflow::DT_FLOAT, { static_cast<int>(taus->size()), 1});
109 
110  std::vector<tensorflow::Tensor> outputs_;
111 
112  float pfCandPt, pfCandPz, pfCandPtRel, pfCandPzRel, pfCandDr, pfCandDEta, pfCandDPhi, pfCandEta, pfCandDz,
113  pfCandDzErr, pfCandD0, pfCandD0D0, pfCandD0Dz, pfCandD0Dphi, pfCandPuppiWeight,
114  pfCandPixHits, pfCandHits, pfCandLostInnerHits, pfCandPdgID, pfCandCharge, pfCandFromPV,
115  pfCandVtxQuality, pfCandHighPurityTrk, pfCandTauIndMatch, pfCandDzSig, pfCandD0Sig, pfCandD0Err,
116  pfCandPtRelPtRel, pfCandDzDz, pfCandDVx_1, pfCandDVy_1, pfCandDVz_1, pfCandD_1;
117  float pvx = !vertices->empty() ? (*vertices)[0].x() : -1;
118  float pvy = !vertices->empty() ? (*vertices)[0].y() : -1;
119  float pvz = !vertices->empty() ? (*vertices)[0].z() : -1;
120 
121  bool pfCandIsBarrel;
122 
123  // These variables define ranges further used for standardization
124  static constexpr float pfCandPt_max = 500.f;
125  static constexpr float pfCandPz_max = 1000.f;
126  static constexpr float pfCandPtRel_max = 1.f;
127  static constexpr float pfCandPzRel_max = 100.f;
128  static constexpr float pfCandPtRelPtRel_max = 1.f;
129  static constexpr float pfCandD0_max = 5.f;
130  static constexpr float pfCandDz_max = 5.f;
131  static constexpr float pfCandDVx_y_z_1_max = 0.05f;
132  static constexpr float pfCandD_1_max = 0.1f;
133  static constexpr float pfCandD0_z_Err_max = 1.f;
134  static constexpr float pfCandDzSig_max = 3.f;
135  static constexpr float pfCandD0Sig_max = 1.f;
136  static constexpr float pfCandDr_max = 0.5f;
137  static constexpr float pfCandEta_max = 2.75f;
138  static constexpr float pfCandDEta_max = 0.5f;
139  static constexpr float pfCandDPhi_max = 0.5f;
140  static constexpr float pfCandPixHits_max = 7.f;
141  static constexpr float pfCandHits_max = 30.f;
142 
143  for(size_t tau_index = 0; tau_index < taus->size(); tau_index++) {
144  pat::Tau tau = taus->at(tau_index);
145  bool isGoodTau = false;
146  const float lepRecoPt = tau.pt();
147  const float lepRecoPz = std::abs(tau.pz());
148  const float lepRecoEta = tau.eta();
149  const float lepRecoPhi = tau.phi();
150 
151  if(lepRecoPt >= 30 && std::abs(lepRecoEta) < 2.3 && tau.isTauIDAvailable("againstMuonLoose3") &&
152  tau.isTauIDAvailable("againstElectronVLooseMVA6")) {
153  isGoodTau = (tau.tauID("againstElectronVLooseMVA6") && tau.tauID("againstMuonLoose3") );
154  }
155 
156  if (!isGoodTau) {
157  predictions.matrix<float>()(tau_index, 0) = -1;
158  continue;
159  }
160 
161  std::vector<unsigned int> signalCandidateInds;
162 
163  for(const auto c : tau.signalCands())
164  signalCandidateInds.push_back(getPFCandidateIndex(pfcands,c));
165 
166  // Use of setZero results in warnings in eigen library during compilation.
167  //tensor.flat<float>().setZero();
168  const unsigned n_inputs = getNumberOfParticles(graphVersion) * GetNumberOfFeatures(graphVersion);
169  for(unsigned input_idx = 0; input_idx < n_inputs; ++input_idx)
170  tensor.flat<float>()(input_idx) = 0;
171 
172  unsigned int iPF = 0;
173  const unsigned max_iPF = getNumberOfParticles(graphVersion);
174 
175  std::vector<unsigned int> sorted_inds(pfcands->size());
176  std::size_t n = 0;
177  std::generate(std::begin(sorted_inds), std::end(sorted_inds), [&]{ return n++; });
178 
179  std::sort(std::begin(sorted_inds), std::end(sorted_inds),
180  [&](int i1, int i2) { return pfcands->at(i1).pt() > pfcands->at(i2).pt(); } );
181 
182  for(size_t pf_index = 0; pf_index < pfcands->size() && iPF < max_iPF; pf_index++) {
183  pat::PackedCandidate p = pfcands->at(sorted_inds.at(pf_index));
184  float deltaR_tau_p = deltaR(p.p4(),tau.p4());
185 
186  if (p.pt() < 0.5) continue;
187  if (p.fromPV() < 0) continue;
188  if (deltaR_tau_p > 0.5) continue;
189  if (p.fromPV() < 1 && p.charge() != 0) continue;
190  pfCandPt = p.pt();
191  pfCandPtRel = p.pt()/lepRecoPt;
192 
193  pfCandDr = deltaR_tau_p;
194  pfCandDEta = std::abs(lepRecoEta - p.eta());
195  pfCandDPhi = std::abs(deltaPhi(lepRecoPhi, p.phi()));
196  pfCandEta = p.eta();
197  pfCandIsBarrel = (std::abs(pfCandEta) < 1.4);
198  pfCandPz = std::abs(std::sinh(pfCandEta)*pfCandPt);
199  pfCandPzRel = pfCandPz/lepRecoPz;
200  pfCandPdgID = std::abs(p.pdgId());
201  pfCandCharge = p.charge();
202  pfCandDVx_1 = p.vx() - pvx;
203  pfCandDVy_1 = p.vy() - pvy;
204  pfCandDVz_1 = p.vz() - pvz;
205 
206  pfCandD_1 = std::sqrt(pfCandDVx_1*pfCandDVx_1 + pfCandDVy_1*pfCandDVy_1 + pfCandDVz_1*pfCandDVz_1);
207 
208  if (pfCandCharge != 0 and p.hasTrackDetails()){
209  pfCandDz = p.dz();
210  pfCandDzErr = p.dzError();
211  pfCandDzSig = (std::abs(p.dz()) + 0.000001)/(p.dzError() + 0.00001);
212  pfCandD0 = p.dxy();
213  pfCandD0Err = p.dxyError();
214  pfCandD0Sig = (std::abs(p.dxy()) + 0.000001)/ (p.dxyError() + 0.00001);
215  pfCandPixHits = p.numberOfPixelHits();
216  pfCandHits = p.numberOfHits();
217  pfCandLostInnerHits = p.lostInnerHits();
218  } else {
219  float disp = 1;
220  int psudorand = p.pt()*1000000;
221  if (psudorand%2 == 0) disp = -1;
222  pfCandDz = 5*disp;
223  pfCandDzErr = 0;
224  pfCandDzSig = 0;
225  pfCandD0 = 5*disp;
226  pfCandD0Err = 0;
227  pfCandD0Sig = 0;
228  pfCandPixHits = 0;
229  pfCandHits = 0;
230  pfCandLostInnerHits = 2.;
231  pfCandDVx_1 = 1;
232  pfCandDVy_1 = 1;
233  pfCandDVz_1 = 1;
234  pfCandD_1 = 1;
235  }
236 
237  pfCandPuppiWeight = p.puppiWeight();
238  pfCandFromPV = p.fromPV();
239  pfCandVtxQuality = p.pvAssociationQuality();
240  pfCandHighPurityTrk = p.trackHighPurity();
241  float pfCandTauIndMatch_temp = 0;
242 
243  for (auto i : signalCandidateInds) {
244  if (i == sorted_inds.at(pf_index)) pfCandTauIndMatch_temp = 1;
245  }
246 
247  pfCandTauIndMatch = pfCandTauIndMatch_temp;
248  pfCandPtRelPtRel = pfCandPtRel*pfCandPtRel;
249  pfCandPt = std::min(pfCandPt, pfCandPt_max);
250  pfCandPt = pfCandPt/pfCandPt_max;
251 
252  pfCandPz = std::min(pfCandPz, pfCandPz_max);
253  pfCandPz = pfCandPz/pfCandPz_max;
254 
255  pfCandPtRel = std::min(pfCandPtRel, pfCandPtRel_max);
256  pfCandPzRel = std::min(pfCandPzRel, pfCandPzRel_max);
257  pfCandPzRel = pfCandPzRel/pfCandPzRel_max;
258  pfCandDr = pfCandDr/pfCandDr_max;
259  pfCandEta = pfCandEta/pfCandEta_max;
260  pfCandDEta = pfCandDEta/pfCandDEta_max;
261  pfCandDPhi = pfCandDPhi/pfCandDPhi_max;
262  pfCandPixHits = pfCandPixHits/pfCandPixHits_max;
263  pfCandHits = pfCandHits/pfCandHits_max;
264 
265  pfCandPtRelPtRel = std::min(pfCandPtRelPtRel, pfCandPtRelPtRel_max);
266 
267  pfCandD0 = std::clamp(pfCandD0, -pfCandD0_max, pfCandD0_max);
268  pfCandD0 = pfCandD0/pfCandD0_max;
269 
270  pfCandDz = std::clamp(pfCandDz, -pfCandDz_max, pfCandDz_max);
271  pfCandDz = pfCandDz/pfCandDz_max;
272 
273  pfCandD0Err = std::min(pfCandD0Err, pfCandD0_z_Err_max);
274  pfCandDzErr = std::min(pfCandDzErr, pfCandD0_z_Err_max);
275  pfCandDzSig = std::min(pfCandDzSig, pfCandDzSig_max);
276  pfCandDzSig = pfCandDzSig/pfCandDzSig_max;
277 
278  pfCandD0Sig = std::min(pfCandD0Sig, pfCandD0Sig_max);
279  pfCandD0D0 = pfCandD0*pfCandD0;
280  pfCandDzDz = pfCandDz*pfCandDz;
281  pfCandD0Dz = pfCandD0*pfCandDz;
282  pfCandD0Dphi = pfCandD0*pfCandDPhi;
283 
284  pfCandDVx_1 = std::clamp(pfCandDVx_1, -pfCandDVx_y_z_1_max, pfCandDVx_y_z_1_max);
285  pfCandDVx_1 = pfCandDVx_1/pfCandDVx_y_z_1_max;
286 
287  pfCandDVy_1 = std::clamp(pfCandDVy_1, -pfCandDVx_y_z_1_max, pfCandDVx_y_z_1_max);
288  pfCandDVy_1 = pfCandDVy_1/pfCandDVx_y_z_1_max;
289 
290  pfCandDVz_1 = std::clamp(pfCandDVz_1, -pfCandDVx_y_z_1_max, pfCandDVx_y_z_1_max);
291  pfCandDVz_1 = pfCandDVz_1/pfCandDVx_y_z_1_max;
292 
293  pfCandD_1 = std::clamp(pfCandD_1, -pfCandD_1_max, pfCandD_1_max);
294  pfCandD_1 = pfCandD_1/ pfCandD_1_max;
295 
296  if (graphVersion == 0) {
297  tensor.tensor<float,3>()( 0, 60-1-iPF, 0) = pfCandPt;
298  tensor.tensor<float,3>()( 0, 60-1-iPF, 1) = pfCandPz;
299  tensor.tensor<float,3>()( 0, 60-1-iPF, 2) = pfCandPtRel;
300  tensor.tensor<float,3>()( 0, 60-1-iPF, 3) = pfCandPzRel;
301  tensor.tensor<float,3>()( 0, 60-1-iPF, 4) = pfCandDr;
302  tensor.tensor<float,3>()( 0, 60-1-iPF, 5) = pfCandDEta;
303  tensor.tensor<float,3>()( 0, 60-1-iPF, 6) = pfCandDPhi;
304  tensor.tensor<float,3>()( 0, 60-1-iPF, 7) = pfCandEta;
305  tensor.tensor<float,3>()( 0, 60-1-iPF, 8) = pfCandDz;
306  tensor.tensor<float,3>()( 0, 60-1-iPF, 9) = pfCandDzSig;
307  tensor.tensor<float,3>()( 0, 60-1-iPF, 10) = pfCandD0;
308  tensor.tensor<float,3>()( 0, 60-1-iPF, 11) = pfCandD0Sig;
309  tensor.tensor<float,3>()( 0, 60-1-iPF, 12) = pfCandDzErr;
310  tensor.tensor<float,3>()( 0, 60-1-iPF, 13) = pfCandD0Err;
311  tensor.tensor<float,3>()( 0, 60-1-iPF, 14) = pfCandD0D0;
312  tensor.tensor<float,3>()( 0, 60-1-iPF, 15) = pfCandCharge==0;
313  tensor.tensor<float,3>()( 0, 60-1-iPF, 16) = pfCandCharge==1;
314  tensor.tensor<float,3>()( 0, 60-1-iPF, 17) = pfCandCharge==-1;
315  tensor.tensor<float,3>()( 0, 60-1-iPF, 18) = pfCandPdgID>22;
316  tensor.tensor<float,3>()( 0, 60-1-iPF, 19) = pfCandPdgID==22;
317  tensor.tensor<float,3>()( 0, 60-1-iPF, 20) = pfCandDzDz;
318  tensor.tensor<float,3>()( 0, 60-1-iPF, 21) = pfCandD0Dz;
319  tensor.tensor<float,3>()( 0, 60-1-iPF, 22) = pfCandD0Dphi;
320  tensor.tensor<float,3>()( 0, 60-1-iPF, 23) = pfCandPtRelPtRel;
321  tensor.tensor<float,3>()( 0, 60-1-iPF, 24) = pfCandPixHits;
322  tensor.tensor<float,3>()( 0, 60-1-iPF, 25) = pfCandHits;
323  tensor.tensor<float,3>()( 0, 60-1-iPF, 26) = pfCandLostInnerHits==-1;
324  tensor.tensor<float,3>()( 0, 60-1-iPF, 27) = pfCandLostInnerHits==0;
325  tensor.tensor<float,3>()( 0, 60-1-iPF, 28) = pfCandLostInnerHits==1;
326  tensor.tensor<float,3>()( 0, 60-1-iPF, 29) = pfCandLostInnerHits==2;
327  tensor.tensor<float,3>()( 0, 60-1-iPF, 30) = pfCandPuppiWeight;
328  tensor.tensor<float,3>()( 0, 60-1-iPF, 31) = (pfCandVtxQuality == 1);
329  tensor.tensor<float,3>()( 0, 60-1-iPF, 32) = (pfCandVtxQuality == 5);
330  tensor.tensor<float,3>()( 0, 60-1-iPF, 33) = (pfCandVtxQuality == 6);
331  tensor.tensor<float,3>()( 0, 60-1-iPF, 34) = (pfCandVtxQuality == 7);
332  tensor.tensor<float,3>()( 0, 60-1-iPF, 35) = (pfCandFromPV == 1);
333  tensor.tensor<float,3>()( 0, 60-1-iPF, 36) = (pfCandFromPV == 2);
334  tensor.tensor<float,3>()( 0, 60-1-iPF, 37) = (pfCandFromPV == 3);
335  tensor.tensor<float,3>()( 0, 60-1-iPF, 38) = pfCandIsBarrel;
336  tensor.tensor<float,3>()( 0, 60-1-iPF, 39) = pfCandHighPurityTrk;
337  tensor.tensor<float,3>()( 0, 60-1-iPF, 40) = pfCandPdgID==1;
338  tensor.tensor<float,3>()( 0, 60-1-iPF, 41) = pfCandPdgID==2;
339  tensor.tensor<float,3>()( 0, 60-1-iPF, 42) = pfCandPdgID==11;
340  tensor.tensor<float,3>()( 0, 60-1-iPF, 43) = pfCandPdgID==13;
341  tensor.tensor<float,3>()( 0, 60-1-iPF, 44) = pfCandPdgID==130;
342  tensor.tensor<float,3>()( 0, 60-1-iPF, 45) = pfCandPdgID==211;
343  tensor.tensor<float,3>()( 0, 60-1-iPF, 46) = pfCandTauIndMatch;
344  }
345 
346  if (graphVersion == 1) {
347  tensor.tensor<float,3>()( 0, 36-1-iPF, 0) = pfCandPt;
348  tensor.tensor<float,3>()( 0, 36-1-iPF, 1) = pfCandPz;
349  tensor.tensor<float,3>()( 0, 36-1-iPF, 2) = pfCandPtRel;
350  tensor.tensor<float,3>()( 0, 36-1-iPF, 3) = pfCandPzRel;
351  tensor.tensor<float,3>()( 0, 36-1-iPF, 4) = pfCandDr;
352  tensor.tensor<float,3>()( 0, 36-1-iPF, 5) = pfCandDEta;
353  tensor.tensor<float,3>()( 0, 36-1-iPF, 6) = pfCandDPhi;
354  tensor.tensor<float,3>()( 0, 36-1-iPF, 7) = pfCandEta;
355  tensor.tensor<float,3>()( 0, 36-1-iPF, 8) = pfCandDz;
356  tensor.tensor<float,3>()( 0, 36-1-iPF, 9) = pfCandDzSig;
357  tensor.tensor<float,3>()( 0, 36-1-iPF, 10) = pfCandD0;
358  tensor.tensor<float,3>()( 0, 36-1-iPF, 11) = pfCandD0Sig;
359  tensor.tensor<float,3>()( 0, 36-1-iPF, 12) = pfCandDzErr;
360  tensor.tensor<float,3>()( 0, 36-1-iPF, 13) = pfCandD0Err;
361  tensor.tensor<float,3>()( 0, 36-1-iPF, 14) = pfCandD0D0;
362  tensor.tensor<float,3>()( 0, 36-1-iPF, 15) = pfCandCharge==0;
363  tensor.tensor<float,3>()( 0, 36-1-iPF, 16) = pfCandCharge==1;
364  tensor.tensor<float,3>()( 0, 36-1-iPF, 17) = pfCandCharge==-1;
365  tensor.tensor<float,3>()( 0, 36-1-iPF, 18) = pfCandPdgID>22;
366  tensor.tensor<float,3>()( 0, 36-1-iPF, 19) = pfCandPdgID==22;
367  tensor.tensor<float,3>()( 0, 36-1-iPF, 20) = pfCandDVx_1;
368  tensor.tensor<float,3>()( 0, 36-1-iPF, 21) = pfCandDVy_1;
369  tensor.tensor<float,3>()( 0, 36-1-iPF, 22) = pfCandDVz_1;
370  tensor.tensor<float,3>()( 0, 36-1-iPF, 23) = pfCandD_1;
371  tensor.tensor<float,3>()( 0, 36-1-iPF, 24) = pfCandDzDz;
372  tensor.tensor<float,3>()( 0, 36-1-iPF, 25) = pfCandD0Dz;
373  tensor.tensor<float,3>()( 0, 36-1-iPF, 26) = pfCandD0Dphi;
374  tensor.tensor<float,3>()( 0, 36-1-iPF, 27) = pfCandPtRelPtRel;
375  tensor.tensor<float,3>()( 0, 36-1-iPF, 28) = pfCandPixHits;
376  tensor.tensor<float,3>()( 0, 36-1-iPF, 29) = pfCandHits;
377  tensor.tensor<float,3>()( 0, 36-1-iPF, 30) = pfCandLostInnerHits==-1;
378  tensor.tensor<float,3>()( 0, 36-1-iPF, 31) = pfCandLostInnerHits==0;
379  tensor.tensor<float,3>()( 0, 36-1-iPF, 32) = pfCandLostInnerHits==1;
380  tensor.tensor<float,3>()( 0, 36-1-iPF, 33) = pfCandLostInnerHits==2;
381  tensor.tensor<float,3>()( 0, 36-1-iPF, 34) = pfCandPuppiWeight;
382  tensor.tensor<float,3>()( 0, 36-1-iPF, 35) = (pfCandVtxQuality == 1);
383  tensor.tensor<float,3>()( 0, 36-1-iPF, 36) = (pfCandVtxQuality == 5);
384  tensor.tensor<float,3>()( 0, 36-1-iPF, 37) = (pfCandVtxQuality == 6);
385  tensor.tensor<float,3>()( 0, 36-1-iPF, 38) = (pfCandVtxQuality == 7);
386  tensor.tensor<float,3>()( 0, 36-1-iPF, 39) = (pfCandFromPV == 1);
387  tensor.tensor<float,3>()( 0, 36-1-iPF, 40) = (pfCandFromPV == 2);
388  tensor.tensor<float,3>()( 0, 36-1-iPF, 41) = (pfCandFromPV == 3);
389  tensor.tensor<float,3>()( 0, 36-1-iPF, 42) = pfCandIsBarrel;
390  tensor.tensor<float,3>()( 0, 36-1-iPF, 43) = pfCandHighPurityTrk;
391  tensor.tensor<float,3>()( 0, 36-1-iPF, 44) = pfCandPdgID==1;
392  tensor.tensor<float,3>()( 0, 36-1-iPF, 45) = pfCandPdgID==2;
393  tensor.tensor<float,3>()( 0, 36-1-iPF, 46) = pfCandPdgID==11;
394  tensor.tensor<float,3>()( 0, 36-1-iPF, 47) = pfCandPdgID==13;
395  tensor.tensor<float,3>()( 0, 36-1-iPF, 48) = pfCandPdgID==130;
396  tensor.tensor<float,3>()( 0, 36-1-iPF, 49) = pfCandPdgID==211;
397  tensor.tensor<float,3>()( 0, 36-1-iPF, 50) = pfCandTauIndMatch;
398  }
399  iPF++;
400  }
401  tensorflow::run(&(cache_->getSession()), { { "input_1", tensor } }, { "output_node0" }, {}, &outputs_);
402  predictions.matrix<float>()(tau_index, 0) = outputs_[0].flat<float>()(0);
403  }
404  return predictions;
405  }
406 
407 private:
408  edm::EDGetTokenT<pat::PackedCandidateCollection> pfcand_token;
409  edm::EDGetTokenT<reco::VertexCollection> vtx_token;
410  unsigned graphVersion;
411 };
412 
413 #include "FWCore/Framework/interface/MakerMacros.h"
414 DEFINE_FWK_MODULE(DPFIsolation);
pat::PackedCandidate::puppiWeight
float puppiWeight() const
Set both weights at once (with option for only full PUPPI)
Definition: PackedCandidate.cc:361
pat::PackedCandidate::dz
virtual float dz(size_t ipv=0) const
dz with respect to the PV[ipv]
Definition: PackedCandidate.h:496
DPFIsolation::pfcand_token
edm::EDGetTokenT< pat::PackedCandidateCollection > pfcand_token
Definition: DPFIsolation.cc:408
pat::PackedCandidate::dxyError
float dxyError() const override
uncertainty on dxy
Definition: PackedCandidate.h:507
mps_fire.i
i
Definition: mps_fire.py:269
reco::LeafCandidate::eta
double eta() const final
momentum pseudorapidity
Definition: LeafCandidate.h:137
DPFIsolation::fillDescriptions
static void fillDescriptions(edm::ConfigurationDescriptions &descriptions)
Definition: DPFIsolation.cc:55
AlCaHLTBitMon_ParallelJobs.p
p
Definition: AlCaHLTBitMon_ParallelJobs.py:152
pat::PackedCandidate::numberOfHits
int numberOfHits() const
Definition: PackedCandidate.h:454
pat::PackedCandidate::pdgId
int pdgId() const override
PDG identifier.
Definition: PackedCandidate.h:565
DPFIsolation::getNumberOfParticles
static unsigned getNumberOfParticles(unsigned graphVersion)
Definition: DPFIsolation.cc:43
AlCaHLTBitMon_QueryRunRegistry.string
string
Definition: AlCaHLTBitMon_QueryRunRegistry.py:255
DEFINE_FWK_MODULE
#define DEFINE_FWK_MODULE(type)
Definition: MakerMacros.h:17
pat::PackedCandidateCollection
std::vector< pat::PackedCandidate > PackedCandidateCollection
Definition: PackedCandidate.h:791
pat::PackedCandidate::p4
const LorentzVector & p4() const override
four-momentum Lorentz vecto r
Definition: PackedCandidate.h:318
pat::PackedCandidate::dzError
float dzError() const override
uncertainty on dz
Definition: PackedCandidate.h:505
electrons_cff.vertices
vertices
Definition: electrons_cff.py:14
reco::LeafCandidate::pt
double pt() const final
transverse momentum
Definition: LeafCandidate.h:131
reco::VertexCollection
std::vector< Vertex > VertexCollection
collection of Vertex objects
Definition: VertexFwd.h:9
pat::Tau::tauID
float tauID(const std::string &name) const
pat::Tau::signalCands
reco::CandidatePtrVector signalCands() const
pat::PackedCandidate::vz
double vz() const override
z coordinate of vertex position
Definition: PackedCandidate.h:470
deep_tau::DeepTauBase::OutputCollection
std::map< std::string, Output > OutputCollection
Definition: DeepTauBase.h:82
constexpr
#define constexpr
pat
Definition: HeavyIon.h:7
models.generate
def generate(map_blobs=False, class_name=None)
Definition: models.py:187
deep_tau::DeepTauBase
Definition: DeepTauBase.h:58
deep_tau::DeepTauCache
Definition: DeepTauBase.h:40
pat::PackedCandidate::charge
int charge() const override
electric charge
Definition: PackedCandidate.h:301
pat::PackedCandidate::vy
double vy() const override
y coordinate of vertex position
Definition: PackedCandidate.h:468
DPFIsolation::GetNumberOfFeatures
static unsigned GetNumberOfFeatures(unsigned graphVersion)
Definition: DPFIsolation.cc:49
pat::PackedCandidate::pvAssociationQuality
const PVAssociationQuality pvAssociationQuality() const
Definition: PackedCandidate.h:488
reco::LeafCandidate::pz
double pz() const final
z coordinate of momentum vector
Definition: LeafCandidate.h:129
pat::PackedCandidate::fromPV
const PVAssoc fromPV(size_t ipv=0) const
Definition: PackedCandidate.h:476
mathSSE::sqrt
T sqrt(T t)
Definition: SSEVec.h:18
pat::PackedCandidate::trackHighPurity
bool trackHighPurity() const
true if the track had the highPurity quality bit
Definition: PackedCandidate.h:527
pat::PackedCandidate::lostInnerHits
LostInnerHits lostInnerHits() const
Definition: PackedCandidate.h:538
funct::abs
Abs< T >::type abs(const T &t)
Definition: Abs.h:22
reco::LeafCandidate::p4
const LorentzVector & p4() const final
four-momentum Lorentz vector
Definition: LeafCandidate.h:99
pat::PackedCandidate::pt
double pt() const override
transverse momentum
Definition: PackedCandidate.h:350
end
#define end
Definition: vmac.h:37
min
T min(T a, T b)
Definition: MathUtil.h:58
edm::ParameterSetDescription::add
ParameterDescriptionBase * add(U const &iLabel, T const &value)
Definition: ParameterSetDescription.h:89
pat::PackedCandidate::numberOfPixelHits
int numberOfPixelHits() const
Definition: PackedCandidate.h:453
pat::Tau
Analysis-level tau class.
Definition: Tau.h:55
DPFIsolation::getPredictions
tensorflow::Tensor getPredictions(edm::Event &event, const edm::EventSetup &es, edm::Handle< TauCollection > taus) override
Definition: DPFIsolation.cc:96
helperFunctions.cache
def cache(function)
Definition: helperFunctions.py:151
pat::PackedCandidate::hasTrackDetails
bool hasTrackDetails() const
Return true if a bestTrack can be extracted from this Candidate.
Definition: PackedCandidate.h:523
deltaR
double deltaR(double eta1, double eta2, double phi1, double phi2)
Definition: TreeUtility.cc:17
pat::Tau::isTauIDAvailable
bool isTauIDAvailable(const std::string &name) const
Returns true if a specific ID is available in this pat::Tau.
pat::PackedCandidate::eta
double eta() const override
momentum pseudorapidity
Definition: PackedCandidate.h:376
pat::PackedCandidate::phi
double phi() const override
momentum azimuthal angle
Definition: PackedCandidate.h:352
DPFIsolation::vtx_token
edm::EDGetTokenT< reco::VertexCollection > vtx_token
Definition: DPFIsolation.cc:409
std::clamp
const T & clamp(const T &v, const T &lo, const T &hi)
Definition: DPFIsolation.cc:27
DPFIsolation::DPFIsolation
DPFIsolation(const edm::ParameterSet &cfg, const deep_tau::DeepTauCache *cache)
Definition: DPFIsolation.cc:79
edm::ConfigurationDescriptions::add
void add(std::string const &label, ParameterSetDescription const &psetDescription)
Definition: ConfigurationDescriptions.cc:63
reco
fixed size matrix
Definition: AlignmentAlgorithmBase.h:43
begin
#define begin
Definition: vmac.h:30
edm
HLT enums.
Definition: AlignableModifier.h:17
Output
#define Output(cl)
Definition: vmac.h:192
DPFIsolation::graphVersion
unsigned graphVersion
Definition: DPFIsolation.cc:410
tensorflow::run
void run(Session *session, const NamedTensorList &inputs, const std::vector< std::string > &outputNames, const std::vector< std::string > &targetNodes, std::vector< Tensor > *outputs)
Definition: TensorFlow.cc:210
hiPixelPairStep_cff.deltaPhi
deltaPhi
Definition: hiPixelPairStep_cff.py:87
DPFIsolation::GetOutputs
static const OutputCollection & GetOutputs()
Definition: DPFIsolation.cc:36
pat::PackedCandidate::dxy
virtual float dxy() const
dxy with respect to the PV ref
Definition: PackedCandidate.h:494
T
long double T
Definition: Basic3DVectorLD.h:57
reco::LeafCandidate::phi
double phi() const final
momentum azimuthal angle
Definition: LeafCandidate.h:133
nano_cff.taus
taus
Definition: nano_cff.py:33
pat::PackedCandidate::vx
double vx() const override
x coordinate of vertex position
Definition: PackedCandidate.h:466
event
Definition: event.py:1
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