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PFRecoTauDiscriminationByIsolation.cc
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1 #include <functional>
10 
11 #include "TMath.h"
12 #include "TFormula.h"
13 
14 /* class PFRecoTauDiscriminationByIsolation
15  * created : Jul 23 2007,
16  * revised : Thu Aug 13 14:44:40 PDT 2009
17  * contributors : Ludovic Houchu (IPHC, Strasbourg),
18  * Christian Veelken (UC Davis),
19  * Evan K. Friis (UC Davis)
20  * Michalis Bachtis (UW Madison)
21  */
22 
23 using namespace reco;
24 using namespace std;
25 
27 {
28  public:
31  moduleLabel_(pset.getParameter<std::string>("@module_label")),
32  qualityCutsPSet_(pset.getParameter<edm::ParameterSet>("qualityCuts"))
33  {
34  includeTracks_ = pset.getParameter<bool>(
35  "ApplyDiscriminationByTrackerIsolation");
36  includeGammas_ = pset.getParameter<bool>(
37  "ApplyDiscriminationByECALIsolation");
38 
39  calculateWeights_ = pset.exists("ApplyDiscriminationByWeightedECALIsolation") ?
40  pset.getParameter<bool>("ApplyDiscriminationByWeightedECALIsolation") : false;
41 
42  // RIC: multiply neutral isolation by a flat factor.
43  // Useful, for instance, to combine charged and neutral isolations
44  // with different relative weights
45  weightGammas_ = pset.exists("WeightECALIsolation") ?
46  pset.getParameter<double>("WeightECALIsolation") : 1.0;
47 
48  // RIC: allow to relax the isolation completely beyond a given tau pt
49  minPtForNoIso_ = pset.exists("minTauPtForNoIso") ?
50  pset.getParameter<double>("minTauPtForNoIso") : -99.;
51 
52  applyOccupancyCut_ = pset.getParameter<bool>("applyOccupancyCut");
53  maximumOccupancy_ = pset.getParameter<uint32_t>("maximumOccupancy");
54 
55  applySumPtCut_ = pset.getParameter<bool>("applySumPtCut");
56  maximumSumPt_ = pset.getParameter<double>("maximumSumPtCut");
57 
58  applyRelativeSumPtCut_ = pset.getParameter<bool>(
59  "applyRelativeSumPtCut");
60  maximumRelativeSumPt_ = pset.getParameter<double>(
61  "relativeSumPtCut");
62  offsetRelativeSumPt_ = pset.exists("relativeSumPtOffset") ?
63  pset.getParameter<double>("relativeSumPtOffset") : 0.0;
64 
65  storeRawOccupancy_ = pset.exists("storeRawOccupancy") ?
66  pset.getParameter<bool>("storeRawOccupancy") : false;
67  storeRawSumPt_ = pset.exists("storeRawSumPt") ?
68  pset.getParameter<bool>("storeRawSumPt") : false;
69  storeRawPUsumPt_ = pset.exists("storeRawPUsumPt") ?
70  pset.getParameter<bool>("storeRawPUsumPt") : false;
71  storeRawFootprintCorrection_ = pset.exists("storeRawFootprintCorrection") ?
72  pset.getParameter<bool>("storeRawFootprintCorrection") : false;
73  storeRawPhotonSumPt_outsideSignalCone_ = pset.exists("storeRawPhotonSumPt_outsideSignalCone") ?
74  pset.getParameter<bool>("storeRawPhotonSumPt_outsideSignalCone") : false;
75 
76  // Sanity check on requested options. We can't apply cuts and store the
77  // raw output at the same time
78  if ( applySumPtCut_ || applyOccupancyCut_ || applyRelativeSumPtCut_ ) {
79  if ( storeRawSumPt_ || storeRawOccupancy_ || storeRawPUsumPt_ ) {
80  throw cms::Exception("BadIsoConfig")
81  << "A 'store raw' and a 'apply cut' option have been set to true "
82  << "simultaneously. These options are mutually exclusive.";
83  }
84  }
85 
86  // sanity check2 - can't use weighted and unweighted iso at the same time
87  if ( includeGammas_ && calculateWeights_ ) {
88  throw cms::Exception("BasIsoConfig")
89  << "Both 'ApplyDiscriminationByECALIsolation' and 'ApplyDiscriminationByWeightedECALIsolation' "
90  << "have been set to true. These options are mutually exclusive.";
91  }
92 
93  // Can only store one type
94  int numStoreOptions = 0;
95  if ( storeRawSumPt_ ) ++numStoreOptions;
96  if ( storeRawOccupancy_ ) ++numStoreOptions;
97  if ( storeRawPUsumPt_ ) ++numStoreOptions;
98  if ( storeRawFootprintCorrection_ ) ++numStoreOptions;
99  if ( storeRawPhotonSumPt_outsideSignalCone_ ) ++numStoreOptions;
100  if ( numStoreOptions > 1 ) {
101  throw cms::Exception("BadIsoConfig")
102  << "Multiple 'store sum pt' and/or 'store occupancy' options are set."
103  << " These options are mutually exclusive.";
104  }
105 
106  if ( pset.exists("customOuterCone") ) {
107  customIsoCone_ = pset.getParameter<double>("customOuterCone");
108  } else {
109  customIsoCone_ = -1;
110  }
111 
112  applyPhotonPtSumOutsideSignalConeCut_ = ( pset.exists("applyPhotonPtSumOutsideSignalConeCut") ) ?
113  pset.getParameter<bool>("applyPhotonPtSumOutsideSignalConeCut") : false;
114  if ( applyPhotonPtSumOutsideSignalConeCut_ ) {
115  maxAbsPhotonSumPt_outsideSignalCone_ = pset.getParameter<double>("maxAbsPhotonSumPt_outsideSignalCone");
116  maxRelPhotonSumPt_outsideSignalCone_ = pset.getParameter<double>("maxRelPhotonSumPt_outsideSignalCone");
117  }
118 
119  applyFootprintCorrection_ = ( pset.exists("applyFootprintCorrection") ) ?
120  pset.getParameter<bool>("applyFootprintCorrection") : false;
121  if ( applyFootprintCorrection_ || storeRawFootprintCorrection_ ) {
122  edm::VParameterSet cfgFootprintCorrections = pset.getParameter<edm::VParameterSet>("footprintCorrections");
123  for ( edm::VParameterSet::const_iterator cfgFootprintCorrection = cfgFootprintCorrections.begin();
124  cfgFootprintCorrection != cfgFootprintCorrections.end(); ++cfgFootprintCorrection ) {
125  std::string selection = cfgFootprintCorrection->getParameter<std::string>("selection");
126  std::string offset = cfgFootprintCorrection->getParameter<std::string>("offset");
127  std::unique_ptr<FootprintCorrection> footprintCorrection(new FootprintCorrection(selection, offset));
128  footprintCorrections_.push_back(std::move(footprintCorrection));
129  }
130  }
131 
132  // Get the quality cuts specific to the isolation region
133  edm::ParameterSet isolationQCuts = qualityCutsPSet_.getParameterSet(
134  "isolationQualityCuts");
135 
136  qcuts_.reset(new tau::RecoTauQualityCuts(isolationQCuts));
137 
138  vertexAssociator_.reset(
139  new tau::RecoTauVertexAssociator(qualityCutsPSet_,consumesCollector()));
140 
141  applyDeltaBeta_ = pset.exists("applyDeltaBetaCorrection") ?
142  pset.getParameter<bool>("applyDeltaBetaCorrection") : false;
143 
144  if ( applyDeltaBeta_ || calculateWeights_ ) {
145  // Factorize the isolation QCuts into those that are used to
146  // select PU and those that are not.
147  std::pair<edm::ParameterSet, edm::ParameterSet> puFactorizedIsoQCuts =
148  reco::tau::factorizePUQCuts(isolationQCuts);
149 
150  // Determine the pt threshold for the PU tracks
151  // First check if the user specifies explicitly the cut.
152  if ( pset.exists("deltaBetaPUTrackPtCutOverride") ) {
153  puFactorizedIsoQCuts.second.addParameter<double>(
154  "minTrackPt",
155  pset.getParameter<double>("deltaBetaPUTrackPtCutOverride"));
156  } else {
157  // Secondly take it from the minGammaEt
158  puFactorizedIsoQCuts.second.addParameter<double>(
159  "minTrackPt",
160  isolationQCuts.getParameter<double>("minGammaEt"));
161  }
162 
163  pileupQcutsPUTrackSelection_.reset(new tau::RecoTauQualityCuts(
164  puFactorizedIsoQCuts.first));
165 
166  pileupQcutsGeneralQCuts_.reset(new tau::RecoTauQualityCuts(
167  puFactorizedIsoQCuts.second));
168 
169  pfCandSrc_ = pset.getParameter<edm::InputTag>("particleFlowSrc");
170  pfCand_token = consumes<reco::PFCandidateCollection>(pfCandSrc_);
171  vertexSrc_ = pset.getParameter<edm::InputTag>("vertexSrc");
172  vertex_token = consumes<reco::VertexCollection>(vertexSrc_);
173  deltaBetaCollectionCone_ = pset.getParameter<double>(
174  "isoConeSizeForDeltaBeta");
175  std::string deltaBetaFactorFormula =
176  pset.getParameter<string>("deltaBetaFactor");
177  deltaBetaFormula_.reset(
178  new TFormula("DB_corr", deltaBetaFactorFormula.c_str()));
179  }
180 
181  applyRhoCorrection_ = pset.exists("applyRhoCorrection") ?
182  pset.getParameter<bool>("applyRhoCorrection") : false;
183  if ( applyRhoCorrection_ ) {
184  rhoProducer_ = pset.getParameter<edm::InputTag>("rhoProducer");
185  rho_token=consumes<double>(rhoProducer_);
186  rhoConeSize_ = pset.getParameter<double>("rhoConeSize");
187  rhoUEOffsetCorrection_ =
188  pset.getParameter<double>("rhoUEOffsetCorrection");
189  }
190  useAllPFCands_ = pset.exists("UseAllPFCandsForWeights") ?
191  pset.getParameter<bool>("UseAllPFCandsForWeights") : false;
192 
193  verbosity_ = ( pset.exists("verbosity") ) ?
194  pset.getParameter<int>("verbosity") : 0;
195  }
196 
198  {
199  }
200 
201  void beginEvent(const edm::Event& evt, const edm::EventSetup& evtSetup) override;
202  double discriminate(const PFTauRef& pfTau) const override;
203 
204  inline double weightedSum(const std::vector<PFCandidatePtr>& inColl_, double eta, double phi) const {
205  double out = 1.0;
206  for (auto const & inObj_ : inColl_){
207  double sum = (inObj_->pt()*inObj_->pt())/(deltaR2(eta,phi,inObj_->eta(),inObj_->phi()));
208  if(sum > 1.0) out *= sum;
209  }
210  return out;
211  }
212 
213  private:
215 
217  std::auto_ptr<tau::RecoTauQualityCuts> qcuts_;
218 
219  // Inverted QCut which selects tracks with bad DZ/trackWeight
220  std::auto_ptr<tau::RecoTauQualityCuts> pileupQcutsPUTrackSelection_;
221  std::auto_ptr<tau::RecoTauQualityCuts> pileupQcutsGeneralQCuts_;
222 
223  std::auto_ptr<tau::RecoTauVertexAssociator> vertexAssociator_;
224 
237  // RIC:
239 
243 
246  {
248  : selection_(selection),
249  offset_(offset)
250  {}
254  };
255  std::vector<std::unique_ptr<FootprintCorrection> > footprintCorrections_;
256 
257  // Options to store the raw value in the discriminator instead of boolean pass/fail flag
263 
264  /* **********************************************************************
265  **** Pileup Subtraction Parameters ***********************************
266  **********************************************************************/
267 
268  // Delta Beta correction
272  // Keep track of how many vertices are in the event
275  std::vector<reco::PFCandidatePtr> chargedPFCandidatesInEvent_;
276  // Size of cone used to collect PU tracks
278  std::auto_ptr<TFormula> deltaBetaFormula_;
280 
281  // Rho correction
286  double rhoConeSize_;
290 
291  // Flag to enable/disable debug output
293 };
294 
296 {
297  // NB: The use of the PV in this context is necessitated by its use in
298  // applying quality cuts to the different objects in the isolation cone
299  // The vertex associator contains the logic to select the appropriate vertex
300  // We need to pass it the event so it can load the vertices.
301  vertexAssociator_->setEvent(event);
302 
303  // If we are applying the delta beta correction, we need to get the PF
304  // candidates from the event so we can find the PU tracks.
305  if ( applyDeltaBeta_ || calculateWeights_ ) {
306  // Collect all the PF pile up tracks
308  event.getByToken(pfCand_token, pfCandidates);
309  chargedPFCandidatesInEvent_.clear();
310  chargedPFCandidatesInEvent_.reserve(pfCandidates->size());
311  size_t numPFCandidates = pfCandidates->size();
312  for ( size_t i = 0; i < numPFCandidates; ++i ) {
313  reco::PFCandidatePtr pfCandidate(pfCandidates, i);
314  if ( pfCandidate->charge() != 0 ) {
315  chargedPFCandidatesInEvent_.push_back(pfCandidate);
316  }
317  }
318  // Count all the vertices in the event, to parameterize the DB
319  // correction factor
321  event.getByToken(vertex_token, vertices);
322  size_t nVtxThisEvent = vertices->size();
323  deltaBetaFactorThisEvent_ = deltaBetaFormula_->Eval(nVtxThisEvent);
324  }
325 
326  if ( applyRhoCorrection_ ) {
327  edm::Handle<double> rhoHandle_;
328  event.getByToken(rho_token, rhoHandle_);
329  rhoThisEvent_ = (*rhoHandle_ - rhoUEOffsetCorrection_)*
330  (3.14159)*rhoConeSize_*rhoConeSize_;
331  }
332 }
333 
334 double
336 {
337  LogDebug("discriminate") << " tau: Pt = " << pfTau->pt() << ", eta = " << pfTau->eta() << ", phi = " << pfTau->phi();
338  LogDebug("discriminate") << *pfTau ;
339 
340  // collect the objects we are working with (ie tracks, tracks+gammas, etc)
341  std::vector<PFCandidatePtr> isoCharged_;
342  std::vector<PFCandidatePtr> isoNeutral_;
343  std::vector<PFCandidatePtr> isoPU_;
344  PFCandidateCollection isoNeutralWeight_;
345  std::vector<PFCandidatePtr> chPV_;
346  isoCharged_.reserve(pfTau->isolationPFChargedHadrCands().size());
347  isoNeutral_.reserve(pfTau->isolationPFGammaCands().size());
348  isoPU_.reserve(std::min(100UL, chargedPFCandidatesInEvent_.size()));
349  isoNeutralWeight_.reserve(pfTau->isolationPFGammaCands().size());
350 
351  chPV_.reserve(std::min(50UL, chargedPFCandidatesInEvent_.size()));
352 
353  // Get the primary vertex associated to this tau
354  reco::VertexRef pv = vertexAssociator_->associatedVertex(*pfTau);
355  // Let the quality cuts know which the vertex to use when applying selections
356  // on dz, etc.
357  if ( verbosity_ ) {
358  if ( pv.isNonnull() ) {
359  LogTrace("discriminate") << "pv: x = " << pv->position().x() << ", y = " << pv->position().y() << ", z = " << pv->position().z() ;
360  } else {
361  LogTrace("discriminate") << "pv: N/A" ;
362  }
363  if ( pfTau->leadPFChargedHadrCand().isNonnull() ) {
364  LogTrace("discriminate") << "leadPFChargedHadron:"
365  << " Pt = " << pfTau->leadPFChargedHadrCand()->pt() << ","
366  << " eta = " << pfTau->leadPFChargedHadrCand()->eta() << ","
367  << " phi = " << pfTau->leadPFChargedHadrCand()->phi() ;
368  } else {
369  LogTrace("discriminate") << "leadPFChargedHadron: N/A" ;
370  }
371  }
372 
373  // CV: isolation is not well defined in case primary vertex or leading charged hadron do not exist
374  if ( !(pv.isNonnull() && pfTau->leadPFChargedHadrCand().isNonnull()) ) return 0.;
375 
376  qcuts_->setPV(pv);
377  qcuts_->setLeadTrack(pfTau->leadPFChargedHadrCand());
378 
379  if ( applyDeltaBeta_ || calculateWeights_) {
380  pileupQcutsGeneralQCuts_->setPV(pv);
381  pileupQcutsGeneralQCuts_->setLeadTrack(pfTau->leadPFChargedHadrCand());
382  pileupQcutsPUTrackSelection_->setPV(pv);
383  pileupQcutsPUTrackSelection_->setLeadTrack(pfTau->leadPFChargedHadrCand());
384  }
385 
386  // Load the tracks if they are being used.
387  if ( includeTracks_ ) {
388  for( auto const & cand : pfTau->isolationPFChargedHadrCands() ) {
389  if ( qcuts_->filterCandRef(cand) ) {
390  LogTrace("discriminate") << "adding charged iso cand with pt " << cand->pt() ;
391  isoCharged_.push_back(cand);
392  }
393  }
394  }
395  if ( includeGammas_ || calculateWeights_ ) {
396  for( auto const & cand : pfTau->isolationPFGammaCands() ) {
397  if ( qcuts_->filterCandRef(cand) ) {
398  LogTrace("discriminate") << "adding neutral iso cand with pt " << cand->pt() ;
399  isoNeutral_.push_back(cand);
400  }
401  }
402  }
403 
406 
407  // If desired, get PU tracks.
408  if ( applyDeltaBeta_ || calculateWeights_) {
409  // First select by inverted the DZ/track weight cuts. True = invert
410  if ( verbosity_ ) {
411  std::cout << "Initial PFCands: " << chargedPFCandidatesInEvent_.size() << std::endl;
412  }
413 
414  std::vector<PFCandidatePtr> allPU =
415  pileupQcutsPUTrackSelection_->filterCandRefs(
416  chargedPFCandidatesInEvent_, true);
417 
418  std::vector<PFCandidatePtr> allNPU =
419  pileupQcutsPUTrackSelection_->filterCandRefs(
420  chargedPFCandidatesInEvent_);
421  LogTrace("discriminate") << "After track cuts: " << allPU.size() ;
422 
423  // Now apply the rest of the cuts, like pt, and TIP, tracker hits, etc
424  if ( !useAllPFCands_ ) {
425  std::vector<PFCandidatePtr> cleanPU =
426  pileupQcutsGeneralQCuts_->filterCandRefs(allPU);
427 
428  std::vector<PFCandidatePtr> cleanNPU =
429  pileupQcutsGeneralQCuts_->filterCandRefs(allNPU);
430 
431  LogTrace("discriminate") << "After cleaning cuts: " << cleanPU.size() ;
432 
433  // Only select PU tracks inside the isolation cone.
434  DRFilter deltaBetaFilter(pfTau->p4(), 0, deltaBetaCollectionCone_);
435  for ( auto const & cand : cleanPU ) {
436  if ( deltaBetaFilter(cand) ) isoPU_.push_back(cand);
437  }
438 
439  for ( auto const & cand : cleanNPU ) {
440  if ( deltaBetaFilter(cand) ) chPV_.push_back(cand);
441  }
442  LogTrace("discriminate") << "After cone cuts: " << isoPU_.size() << " " << chPV_.size() ;
443  } else {
444  isoPU_ = std::move(allPU);
445  chPV_ = std::move(allNPU);
446  }
447  }
448 
449  if ( calculateWeights_ ) {
450  for ( auto const & isoObject : isoNeutral_ ) {
451  if ( isoObject->charge() != 0 ) {
452  // weight only neutral objects
453  isoNeutralWeight_.push_back(*isoObject);
454  continue;
455  }
456 
457  double eta = isoObject->eta();
458  double phi = isoObject->phi();
459  double sumNPU = 0.5*log(weightedSum(chPV_, eta, phi));
460 
461  double sumPU = 0.5*log(weightedSum(isoPU_, eta, phi));
462  PFCandidate neutral = (*isoObject);
463  if ( (sumNPU + sumPU) > 0 ) neutral.setP4(((sumNPU)/(sumNPU + sumPU))*neutral.p4());
464 
465  isoNeutralWeight_.push_back(neutral);
466  }
467  }
468 
469  // Check if we want a custom iso cone
470  if ( customIsoCone_ >= 0. ) {
471  DRFilter filter(pfTau->p4(), 0, customIsoCone_);
472  DRFilter2 filter2(pfTau->p4(), 0, customIsoCone_);
473  std::vector<PFCandidatePtr> isoCharged_filter;
474  std::vector<PFCandidatePtr> isoNeutral_filter;
475  PFCandidateCollection isoNeutralWeight_filter;
476  // Remove all the objects not in our iso cone
477  for( auto const & isoObject : isoCharged_ ) {
478  if ( filter(isoObject) ) isoCharged_filter.push_back(isoObject);
479  }
480  if(!calculateWeights_){
481  for( auto const & isoObject : isoNeutral_ ) {
482  if ( filter(isoObject) ) isoNeutral_filter.push_back(isoObject);
483  }
484  isoNeutral_ = isoNeutral_filter;
485  }else{
486  for( auto const & isoObject : isoNeutralWeight_){
487  if ( filter2(isoObject) ) isoNeutralWeight_filter.push_back(isoObject);
488  }
489  isoNeutralWeight_ = isoNeutralWeight_filter;
490  }
491  isoCharged_ = isoCharged_filter;
492  }
493 
494  bool failsOccupancyCut = false;
495  bool failsSumPtCut = false;
496  bool failsRelativeSumPtCut = false;
497 
498 //--- nObjects requirement
499  int neutrals = isoNeutral_.size();
500 
501  if ( applyDeltaBeta_ ) {
502  neutrals -= TMath::Nint(deltaBetaFactorThisEvent_*isoPU_.size());
503  }
504  if ( neutrals < 0 ) {
505  neutrals = 0;
506  }
507 
508  size_t nOccupants = isoCharged_.size() + neutrals;
509 
510  failsOccupancyCut = ( nOccupants > maximumOccupancy_ );
511 
512  double footprintCorrection_value = 0.;
513  if ( applyFootprintCorrection_ || storeRawFootprintCorrection_ ) {
514  for ( std::vector<std::unique_ptr<FootprintCorrection> >::const_iterator footprintCorrection = footprintCorrections_.begin();
515  footprintCorrection != footprintCorrections_.end(); ++footprintCorrection ) {
516  if ( (*footprintCorrection)->selection_(*pfTau) ) {
517  footprintCorrection_value = (*footprintCorrection)->offset_(*pfTau);
518  }
519  }
520  }
521 
522  double totalPt = 0.;
523  double puPt = 0.;
524 //--- Sum PT requirement
525  if ( applySumPtCut_ || applyRelativeSumPtCut_ || storeRawSumPt_ || storeRawPUsumPt_ ) {
526  double chargedPt = 0.;
527  double neutralPt = 0.;
528  double weightedNeutralPt = 0.;
529  for ( auto const & isoObject : isoCharged_ ) {
530  chargedPt += isoObject->pt();
531  }
532  if ( !calculateWeights_ ) {
533  for ( auto const & isoObject : isoNeutral_ ) {
534  neutralPt += isoObject->pt();
535  }
536  } else {
537  for ( auto const & isoObject : isoNeutralWeight_ ) {
538  weightedNeutralPt += isoObject.pt();
539  }
540  }
541  for ( auto const & isoObject : isoPU_ ) {
542  puPt += isoObject->pt();
543  }
544  LogTrace("discriminate") << "chargedPt = " << chargedPt ;
545  LogTrace("discriminate") << "neutralPt = " << neutralPt ;
546  LogTrace("discriminate") << "weighted neutral Pt = " << weightedNeutralPt ;
547  LogTrace("discriminate") << "puPt = " << puPt << " (delta-beta corr. = " << (deltaBetaFactorThisEvent_*puPt) << ")" ;
548 
549  if ( calculateWeights_ ) {
550  neutralPt = weightedNeutralPt;
551  }
552 
553  if ( applyDeltaBeta_ ) {
554  neutralPt -= (deltaBetaFactorThisEvent_*puPt);
555  }
556 
557  if ( applyFootprintCorrection_ ) {
558  neutralPt -= footprintCorrection_value;
559  }
560 
561  if ( applyRhoCorrection_ ) {
562  neutralPt -= rhoThisEvent_;
563  }
564 
565  if ( neutralPt < 0. ) {
566  neutralPt = 0.;
567  }
568 
569  totalPt = chargedPt + weightGammas_ * neutralPt;
570  LogTrace("discriminate") << "totalPt = " << totalPt << " (cut = " << maximumSumPt_ << ")" ;
571 
572  failsSumPtCut = (totalPt > maximumSumPt_);
573 
574 //--- Relative Sum PT requirement
575  failsRelativeSumPtCut = (totalPt > ((pfTau->pt() - offsetRelativeSumPt_)*maximumRelativeSumPt_));
576  }
577 
578  bool failsPhotonPtSumOutsideSignalConeCut = false;
579  double photonSumPt_outsideSignalCone = 0.;
580  if ( applyPhotonPtSumOutsideSignalConeCut_ || storeRawPhotonSumPt_outsideSignalCone_ ) {
581  const std::vector<reco::PFCandidatePtr>& signalPFGammas = pfTau->signalPFGammaCands();
582  for ( std::vector<reco::PFCandidatePtr>::const_iterator signalPFGamma = signalPFGammas.begin();
583  signalPFGamma != signalPFGammas.end(); ++signalPFGamma ) {
584  double dR = deltaR(pfTau->eta(), pfTau->phi(), (*signalPFGamma)->eta(), (*signalPFGamma)->phi());
585  if ( dR > pfTau->signalConeSize() ) photonSumPt_outsideSignalCone += (*signalPFGamma)->pt();
586  }
587  if ( photonSumPt_outsideSignalCone > maxAbsPhotonSumPt_outsideSignalCone_ || photonSumPt_outsideSignalCone > (maxRelPhotonSumPt_outsideSignalCone_*pfTau->pt()) ) {
588  failsPhotonPtSumOutsideSignalConeCut = true;
589  }
590  }
591 
592  bool fails = (applyOccupancyCut_ && failsOccupancyCut) ||
593  (applySumPtCut_ && failsSumPtCut) ||
594  (applyRelativeSumPtCut_ && failsRelativeSumPtCut) ||
595  (applyPhotonPtSumOutsideSignalConeCut_ && failsPhotonPtSumOutsideSignalConeCut);
596 
597 
598  if (pfTau->pt() > minPtForNoIso_ && minPtForNoIso_ > 0.){
599  return 1.;
600  LogDebug("discriminate") << "tau pt = " << pfTau->pt() << "\t min cutoff pt = " << minPtForNoIso_ ;
601  }
602 
603  // We did error checking in the constructor, so this is safe.
604  if ( storeRawSumPt_ ) {
605  return totalPt;
606  } else if ( storeRawPUsumPt_ ) {
607  if ( applyDeltaBeta_ ) return puPt;
608  else if ( applyRhoCorrection_ ) return rhoThisEvent_;
609  else return 0.;
610  } else if ( storeRawOccupancy_ ) {
611  return nOccupants;
612  } else if ( storeRawFootprintCorrection_ ) {
613  return footprintCorrection_value;
614  } else if ( storeRawPhotonSumPt_outsideSignalCone_ ) {
615  return photonSumPt_outsideSignalCone;
616  } else {
617  return (fails ? 0. : 1.);
618  }
619 }
620 
#define LogDebug(id)
PFRecoTauDiscriminationByIsolation(const edm::ParameterSet &pset)
T getParameter(std::string const &) const
int i
Definition: DBlmapReader.cc:9
bool isNonnull() const
Checks for non-null.
Definition: Ref.h:252
std::auto_ptr< tau::RecoTauQualityCuts > pileupQcutsGeneralQCuts_
#define DEFINE_FWK_MODULE(type)
Definition: MakerMacros.h:17
std::vector< ParameterSet > VParameterSet
Definition: ParameterSet.h:33
selection
main part
Definition: corrVsCorr.py:98
void beginEvent(const edm::Event &evt, const edm::EventSetup &evtSetup) override
bool exists(std::string const &parameterName) const
checks if a parameter exists
double weightedSum(const std::vector< PFCandidatePtr > &inColl_, double eta, double phi) const
std::vector< PFCandidatePtr > pfCandidates(const PFJet &jet, int particleId, bool sort=true)
std::vector< std::unique_ptr< FootprintCorrection > > footprintCorrections_
edm::EDGetTokenT< reco::PFCandidateCollection > pfCand_token
FootprintCorrection(const std::string &selection, const std::string &offset)
def move
Definition: eostools.py:510
auto deltaR(const T1 &t1, const T2 &t2) -> decltype(t1.eta())
Definition: deltaR.h:28
std::vector< reco::PFCandidatePtr > chargedPFCandidatesInEvent_
std::pair< edm::ParameterSet, edm::ParameterSet > factorizePUQCuts(const edm::ParameterSet &inputSet)
T min(T a, T b)
Definition: MathUtil.h:58
How EventSelector::AcceptEvent() decides whether to accept an event for output otherwise it is excluding the probing of A single or multiple positive and the trigger will pass if any such matching triggers are PASS or EXCEPTION[A criterion thatmatches no triggers at all is detected and causes a throw.] A single negative with an expectation of appropriate bit checking in the decision and the trigger will pass if any such matching triggers are FAIL or EXCEPTION A wildcarded negative criterion that matches more than one trigger in the trigger but the state exists so we define the behavior If all triggers are the negative crieriion will lead to accepting the event(this again matches the behavior of"!*"before the partial wildcard feature was incorporated).The per-event"cost"of each negative criterion with multiple relevant triggers is about the same as!*was in the past
double discriminate(const PFTauRef &pfTau) const override
#define LogTrace(id)
std::auto_ptr< tau::RecoTauQualityCuts > qcuts_
std::auto_ptr< tau::RecoTauQualityCuts > pileupQcutsPUTrackSelection_
std::vector< reco::PFCandidate > PFCandidateCollection
collection of PFCandidates
ParameterSet const & getParameterSet(std::string const &) const
virtual void setP4(const LorentzVector &p4) final
set 4-momentum
Geom::Phi< T > phi() const
T1 deltaR2(T1 eta1, T2 phi1, T3 eta2, T4 phi2)
Definition: deltaR.h:36
Particle reconstructed by the particle flow algorithm.
Definition: PFCandidate.h:39
std::auto_ptr< tau::RecoTauVertexAssociator > vertexAssociator_
tuple cout
Definition: gather_cfg.py:145
moduleLabel_(iConfig.getParameter< string >("@module_label"))
virtual const LorentzVector & p4() const final
four-momentum Lorentz vector
Definition: LeafCandidate.h:99
edm::EDGetTokenT< reco::VertexCollection > vertex_token