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SETPatternRecognition Class Reference

#include <SETPatternRecognition.h>

Inheritance diagram for SETPatternRecognition:
MuonSeedVPatternRecognition

Public Member Functions

virtual void produce (const edm::Event &event, const edm::EventSetup &eSetup, std::vector< MuonRecHitContainer > &result)
 
bool segmentCleaning (const DetId &detId, const LocalPoint &localPosition, const LocalError &localError, const LocalVector &localDirection, const LocalError &localDirectionError, const double &chi2, const int &ndf)
 
 SETPatternRecognition (const edm::ParameterSet &pset, edm::ConsumesCollector &iC)
 
void setServiceProxy (MuonServiceProxy *service)
 
virtual ~SETPatternRecognition ()
 
- Public Member Functions inherited from MuonSeedVPatternRecognition
 MuonSeedVPatternRecognition (const edm::ParameterSet &pset)
 
virtual ~MuonSeedVPatternRecognition ()
 

Private Attributes

edm::InputTag CSCRecSegmentLabel
 
edm::EDGetTokenT
< CSCSegmentCollection
cscToken
 
edm::InputTag DTRecSegmentLabel
 
edm::EDGetTokenT
< DTRecSegment4DCollection
dtToken
 
int maxActiveChambers
 
double minLocalSegmentAngle
 
double outsideChamberErrorScale
 
edm::InputTag RPCRecSegmentLabel
 
edm::EDGetTokenT
< RPCRecHitCollection
rpcToken
 
MuonServiceProxytheService
 
bool useRPCs
 

Additional Inherited Members

- Public Types inherited from MuonSeedVPatternRecognition
typedef
MuonTransientTrackingRecHit::ConstMuonRecHitPointer 
ConstMuonRecHitPointer
 
typedef
MuonTransientTrackingRecHit::MuonRecHitContainer 
MuonRecHitContainer
 
typedef
MuonTransientTrackingRecHit::MuonRecHitPointer 
MuonRecHitPointer
 
- Protected Attributes inherited from MuonSeedVPatternRecognition
bool enableCSCMeasurement
 Enable the CSC measurement. More...
 
bool enableDTMeasurement
 Enable the DT measurement. More...
 
edm::InputTag theCSCRecSegmentLabel
 the name of the CSC rec hits collection More...
 
edm::InputTag theDTRecSegmentLabel
 the name of the DT rec hits collection More...
 

Detailed Description

I. Bloch, E. James, S. Stoynev

Definition at line 14 of file SETPatternRecognition.h.

Constructor & Destructor Documentation

SETPatternRecognition::SETPatternRecognition ( const edm::ParameterSet pset,
edm::ConsumesCollector iC 
)
explicit

Definition at line 18 of file SETPatternRecognition.cc.

References edm::ConsumesCollector::consumes(), CSCRecSegmentLabel, cscToken, DTRecSegmentLabel, dtToken, edm::ParameterSet::getParameter(), maxActiveChambers, metname, minLocalSegmentAngle, outsideChamberErrorScale, RPCRecSegmentLabel, rpcToken, and useRPCs.

19 : MuonSeedVPatternRecognition(parameterSet.getParameter<ParameterSet>("SETTrajBuilderParameters").getParameter<ParameterSet>("FilterParameters"))
20 {
21  const string metname = "Muon|RecoMuon|SETPatternRecognition";
22  // Parameter set for the Builder
23  ParameterSet trajectoryBuilderParameters = parameterSet.getParameter<ParameterSet>("SETTrajBuilderParameters");
24  // The inward-outward fitter (starts from seed state)
25  ParameterSet filterPSet = trajectoryBuilderParameters.getParameter<ParameterSet>("FilterParameters");
26  maxActiveChambers = filterPSet.getParameter<int>("maxActiveChambers");
27  useRPCs = filterPSet.getParameter<bool>("EnableRPCMeasurement");
28  DTRecSegmentLabel = filterPSet.getParameter<edm::InputTag>("DTRecSegmentLabel");
29  CSCRecSegmentLabel = filterPSet.getParameter<edm::InputTag>("CSCRecSegmentLabel");
30  RPCRecSegmentLabel = filterPSet.getParameter<edm::InputTag>("RPCRecSegmentLabel");
31 
32  outsideChamberErrorScale = filterPSet.getParameter<double>("OutsideChamberErrorScale");
33  minLocalSegmentAngle = filterPSet.getParameter<double>("MinLocalSegmentAngle");
34  //----
38 
39 }
EDGetTokenT< ProductType > consumes(edm::InputTag const &tag)
T getParameter(std::string const &) const
edm::EDGetTokenT< DTRecSegment4DCollection > dtToken
edm::EDGetTokenT< RPCRecHitCollection > rpcToken
edm::EDGetTokenT< CSCSegmentCollection > cscToken
const std::string metname
MuonSeedVPatternRecognition(const edm::ParameterSet &pset)
ParameterSet const & parameterSet(Provenance const &provenance)
Definition: Provenance.cc:11
virtual SETPatternRecognition::~SETPatternRecognition ( )
inlinevirtual

Definition at line 18 of file SETPatternRecognition.h.

18 {}

Member Function Documentation

void SETPatternRecognition::produce ( const edm::Event event,
const edm::EventSetup eSetup,
std::vector< MuonRecHitContainer > &  result 
)
virtual

Output is a cluster, with possibly more than one hit per layer

Implements MuonSeedVPatternRecognition.

Definition at line 42 of file SETPatternRecognition.cc.

References begin, HLT_25ns14e33_v1_cff::cscSegments, cscToken, dtToken, end, edm::eventsetup::heterocontainer::insert(), maxActiveChambers, metname, Pi, HLT_25ns14e33_v1_cff::rpcRecHits, rpcToken, segmentCleaning(), findQualityFiles::size, MuonTransientTrackingRecHit::specificBuild(), groupFilesInBlocks::temp, theService, and useRPCs.

Referenced by SETMuonSeedProducer::produce().

44 {
45  const string metname = "Muon|RecoMuon|SETMuonSeedSeed";
46 
47  //---- Build collection of all segments
48  MuonRecHitContainer muonRecHits;
49  MuonRecHitContainer muonRecHits_DT2D_hasPhi;
50  MuonRecHitContainer muonRecHits_DT2D_hasZed;
51  MuonRecHitContainer muonRecHits_RPC;
52 
53  // ********************************************;
54  // Get the DT-Segment collection from the Event
55  // ********************************************;
56 
58  event.getByToken(dtToken, dtRecHits);
59  std::vector<DTChamberId> chambers_DT;
60  std::vector<DTChamberId>::const_iterator chIt_DT;
61  for (DTRecSegment4DCollection::const_iterator rechit = dtRecHits->begin(); rechit!=dtRecHits->end();++rechit) {
62  bool insert = true;
63  for(chIt_DT=chambers_DT.begin(); chIt_DT != chambers_DT.end(); ++chIt_DT){
64  if (
65  ((*rechit).chamberId().wheel()) == ((*chIt_DT).wheel()) &&
66  ((*rechit).chamberId().station() == (*chIt_DT).station()) &&
67  ((*rechit).chamberId().sector() == (*chIt_DT).sector())){
68  insert = false;
69  }
70  }
71  if (insert){
72  chambers_DT.push_back((*rechit).chamberId());
73  }
74  if(segmentCleaning((*rechit).geographicalId(),
75  rechit->localPosition(), rechit->localPositionError(),
76  rechit->localDirection(), rechit->localDirectionError(),
77  rechit->chi2(), rechit->degreesOfFreedom())){
78  continue;
79  }
80  if( (rechit->hasZed() && rechit->hasPhi()) ) {
81  muonRecHits.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
82  }
83  else if(rechit->hasZed()) {
84  muonRecHits_DT2D_hasZed.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
85  }
86  else if(rechit->hasPhi()) { // safeguard
87  muonRecHits_DT2D_hasPhi.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
88  }
89  else {
90  //std::cout<<"Warning in "<<metname<<": DT segment which claims to have neither phi nor Z."<<std::endl;
91  }
92  }
93  //std::cout<<"DT done"<<std::endl;
94 
95  // ********************************************;
96  // Get the CSC-Segment collection from the event
97  // ********************************************;
98 
100  event.getByToken(cscToken, cscSegments);
101  std::vector<CSCDetId> chambers_CSC;
102  std::vector<CSCDetId>::const_iterator chIt_CSC;
103  for(CSCSegmentCollection::const_iterator rechit=cscSegments->begin(); rechit != cscSegments->end(); ++rechit) {
104  bool insert = true;
105  for(chIt_CSC=chambers_CSC.begin(); chIt_CSC != chambers_CSC.end(); ++chIt_CSC){
106  if (((*rechit).cscDetId().chamber() == (*chIt_CSC).chamber()) &&
107  ((*rechit).cscDetId().station() == (*chIt_CSC).station()) &&
108  ((*rechit).cscDetId().ring() == (*chIt_CSC).ring()) &&
109  ((*rechit).cscDetId().endcap() == (*chIt_CSC).endcap())){
110  insert = false;
111  }
112  }
113  if (insert){
114  chambers_CSC.push_back((*rechit).cscDetId().chamberId());
115  }
116  if(segmentCleaning((*rechit).geographicalId(),
117  rechit->localPosition(), rechit->localPositionError(),
118  rechit->localDirection(), rechit->localDirectionError(),
119  rechit->chi2(), rechit->degreesOfFreedom())){
120  continue;
121  }
122  muonRecHits.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
123  }
124  //std::cout<<"CSC done"<<std::endl;
125 
126  // ********************************************;
127  // Get the RPC-Hit collection from the event
128  // ********************************************;
129 
131  event.getByToken(rpcToken, rpcRecHits);
132  if(useRPCs){
133  for(RPCRecHitCollection::const_iterator rechit=rpcRecHits->begin(); rechit != rpcRecHits->end(); ++rechit) {
134  // RPCs are special
135  const LocalVector localDirection(0.,0.,1.);
136  const LocalError localDirectionError (0.,0.,0.);
137  const double chi2 = 1.;
138  const int ndf = 1;
139  if(segmentCleaning((*rechit).geographicalId(),
140  rechit->localPosition(), rechit->localPositionError(),
141  localDirection, localDirectionError,
142  chi2, ndf)){
143  continue;
144  }
145  muonRecHits_RPC.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
146  }
147  }
148  //std::cout<<"RPC done"<<std::endl;
149  //
150  if(int(chambers_DT.size() + chambers_CSC.size()) > maxActiveChambers){
151  // std::cout <<" Too many active chambers : nDT = "<<chambers_DT.size()<<
152  // " nCSC = "<<chambers_CSC.size()<<" Skip them all."<<std::endl;
153  edm::LogWarning("tooManyActiveChambers")<<" Too many active chambers : nDT = "<<chambers_DT.size()
154  <<" nCSC = "<<chambers_CSC.size()<<" Skip them all.";
155  muonRecHits.clear();
156  muonRecHits_DT2D_hasPhi.clear();
157  muonRecHits_DT2D_hasZed.clear();
158  muonRecHits_RPC.clear();
159  }
160  //---- Find "pre-clusters" from all segments; these contain potential muon candidates
161 
162  //---- From all the hits (i.e. segments; sometimes "rechits" is also used with the same meaning;
163  //---- this convention has meaning in the global reconstruction though could be misleading
164  //---- from a local reconstruction point of view; "local rechits" are used in the backward fit only)
165  //---- make clusters of hits; a trajectory could contain hits from one cluster only
166 
167  // the clustering procedure is very similar to the one used in the segment reconstruction
168 
169  bool useDT2D_hasPhi = true;
170  bool useDT2D_hasZed = true;
171  double dXclusBoxMax = 0.60; // phi - can be as large as 15 - 20 degrees for 6 GeV muons
172  double dYclusBoxMax = 0.;
173 
174  // this is the main selection criteria; the value of 0.02 rad seems wide enough to
175  // contain any hit from a passing muon and still narrow enough to remove good part of
176  // possible "junk" hits
177  // (Comment: it may be better to allow maximum difference between any two hits in a trajectory
178  // to be 0.02 or 0.04 or ...; currently the requirement below is imposed on two consecutive hits)
179 
180  dYclusBoxMax = 0.02; // theta // hardoded - remove it!
181 
182  // X and Y are distance variables - we use eta and phi here
183 
184  float dXclus = 0.0;
185  float dXclus_box = 0.0;
186  float dYclus_box = 0.0;
187 
189 
190  std::vector< MuonRecHitContainer > seeds;
191 
192  std::vector<float> running_meanX;
193  std::vector<float> running_meanY;
194 
195  std::vector<float> seed_minX;
196  std::vector<float> seed_maxX;
197  std::vector<float> seed_minY;
198  std::vector<float> seed_maxY;
199 
200  // split rechits into subvectors and return vector of vectors:
201  // Loop over rechits
202  // Create one seed per hit
203  for (MuonRecHitContainer::const_iterator it = muonRecHits.begin(); it != muonRecHits.end(); ++it ) {
204 
205  // try to avoid using 2D DT segments. We will add them later to the
206  // clusters they are most likely to belong to. Might need to add them
207  // to more than just one cluster, if we find them to be consistent with
208  // more than one. This would lead to an implicit sharing of hits between
209  // SA muon candidates.
210 
211  temp.clear();
212 
213  temp.push_back((*it));
214 
215  seeds.push_back(temp);
216 
217  // First added hit in seed defines the mean to which the next hit is compared
218  // for this seed.
219 
220  running_meanX.push_back( (*it)->globalPosition().phi() );
221  running_meanY.push_back( (*it)->globalPosition().theta() );
222 
223  // set min/max X and Y for box containing the hits in the precluster:
224  seed_minX.push_back( (*it)->globalPosition().phi() );
225  seed_maxX.push_back( (*it)->globalPosition().phi() );
226  seed_minY.push_back( (*it)->globalPosition().theta() );
227  seed_maxY.push_back( (*it)->globalPosition().theta() );
228  }
229 
230  // merge clusters that are too close
231  // measure distance between final "running mean"
232  for(unsigned int NNN = 0; NNN < seeds.size(); ++NNN) {
233 
234  for(unsigned int MMM = NNN+1; MMM < seeds.size(); ++MMM) {
235  if(running_meanX[MMM] == 999999. || running_meanX[NNN] == 999999. ) {
236  // LogDebug("CSC") << "CSCSegmentST::clusterHits: Warning: Skipping used seeds, this should happen - inform developers!\n";
237  //std::cout<<"We should never see this line now!!!"<<std::endl;
238  continue; //skip seeds that have been used
239  }
240 
241  // Some complications for using phi as a clustering variable due to wrap-around (-pi = pi)
242  // Define temporary mean, min, and max variables for the cluster which could be merged (NNN)
243  double temp_meanX = running_meanX[NNN];
244  double temp_minX = seed_minX[NNN];
245  double temp_maxX = seed_maxX[NNN];
246 
247  // check if the difference between the two phi values is greater than pi
248  // if so, need to shift temporary values by 2*pi to make a valid comparison
249  dXclus = running_meanX[NNN] - running_meanX[MMM];
250  if (dXclus > TMath::Pi()) {
251  temp_meanX = temp_meanX - 2.*TMath::Pi();
252  temp_minX = temp_minX - 2.*TMath::Pi();
253  temp_maxX = temp_maxX - 2.*TMath::Pi();
254  }
255  if (dXclus < -TMath::Pi()) {
256  temp_meanX = temp_meanX + 2.*TMath::Pi();
257  temp_minX = temp_minX + 2.*TMath::Pi();
258  temp_maxX = temp_maxX + 2.*TMath::Pi();
259  }
260 
261  // // calculate cut criteria for simple running mean distance cut:
262  // // not sure that these values are really used anywhere
263 
264  // calculate minmal distance between precluster boxes containing the hits:
265  // use the temp variables from above for phi of the NNN cluster
266  if ( temp_meanX > running_meanX[MMM] ) dXclus_box = temp_minX - seed_maxX[MMM];
267  else dXclus_box = seed_minX[MMM] - temp_maxX;
268  if ( running_meanY[NNN] > running_meanY[MMM] ) dYclus_box = seed_minY[NNN] - seed_maxY[MMM];
269  else dYclus_box = seed_minY[MMM] - seed_maxY[NNN];
270 
271 
272  if( dXclus_box < dXclusBoxMax && dYclus_box < dYclusBoxMax ) {
273  // merge clusters!
274  // merge by adding seed NNN to seed MMM and erasing seed NNN
275 
276  // calculate running mean for the merged seed:
277  // use the temp variables from above for phi of the NNN cluster
278  running_meanX[MMM] = (temp_meanX*seeds[NNN].size() + running_meanX[MMM]*seeds[MMM].size()) / (seeds[NNN].size()+seeds[MMM].size());
279  running_meanY[MMM] = (running_meanY[NNN]*seeds[NNN].size() + running_meanY[MMM]*seeds[MMM].size()) / (seeds[NNN].size()+seeds[MMM].size());
280 
281  // update min/max X and Y for box containing the hits in the merged cluster:
282  // use the temp variables from above for phi of the NNN cluster
283  if ( temp_minX <= seed_minX[MMM] ) seed_minX[MMM] = temp_minX;
284  if ( temp_maxX > seed_maxX[MMM] ) seed_maxX[MMM] = temp_maxX;
285  if ( seed_minY[NNN] <= seed_minY[MMM] ) seed_minY[MMM] = seed_minY[NNN];
286  if ( seed_maxY[NNN] > seed_maxY[MMM] ) seed_maxY[MMM] = seed_maxY[NNN];
287 
288  // now check to see if the running mean has moved outside of the allowed -pi to pi region
289  // if so, then adjust shift all values up or down by 2 * pi
290  if (running_meanX[MMM] > TMath::Pi()) {
291  running_meanX[MMM] = running_meanX[MMM] - 2.*TMath::Pi();
292  seed_minX[MMM] = seed_minX[MMM] - 2.*TMath::Pi();
293  seed_maxX[MMM] = seed_maxX[MMM] - 2.*TMath::Pi();
294  }
295  if (running_meanX[MMM] < -TMath::Pi()) {
296  running_meanX[MMM] = running_meanX[MMM] + 2.*TMath::Pi();
297  seed_minX[MMM] = seed_minX[MMM] + 2.*TMath::Pi();
298  seed_maxX[MMM] = seed_maxX[MMM] + 2.*TMath::Pi();
299  }
300 
301  // add seed NNN to MMM (lower to larger number)
302  seeds[MMM].insert(seeds[MMM].end(),seeds[NNN].begin(),seeds[NNN].end());
303 
304  // mark seed NNN as used (at the moment just set running mean to 999999.)
305  running_meanX[NNN] = 999999.;
306  running_meanY[NNN] = 999999.;
307  // we have merged a seed (NNN) to the highter seed (MMM) - need to contimue to
308  // next seed (NNN+1)
309  break;
310  }
311 
312  }
313  }
314  bool tooCloseClusters = false;
315  if(seeds.size()>1){
316  std::vector <double> seedTheta(seeds.size());
317  for(unsigned int iSeed = 0;iSeed<seeds.size();++iSeed){
318  seedTheta[iSeed] = seeds[iSeed][0]->globalPosition().theta();
319  if(iSeed){
320  double dTheta = fabs(seedTheta[iSeed] - seedTheta[iSeed-1]);
321  if (dTheta < 0.5){ //? should be something more clever
322  tooCloseClusters = true;
323  break;
324  }
325  }
326  }
327 
328  }
329 
330  // have formed clusters from all hits except for 2D DT segments. Now add the 2D segments to the
331  // compatible clusters. For this we compare the mean cluster postition with the
332  // 2D segment position. We should use the valid coordinate only and use the bad coordinate
333  // as a cross check.
334  for(unsigned int NNN = 0; NNN < seeds.size(); ++NNN) {
335  if(running_meanX[NNN] == 999999.) continue; //skip seeds that have been marked as used up in merging
336 
337  // We have a valid cluster - loop over all 2D segments.
338  if(useDT2D_hasZed) {
339  for (MuonRecHitContainer::const_iterator it2 = muonRecHits_DT2D_hasZed.begin(); it2 != muonRecHits_DT2D_hasZed.end(); ++it2 ) {
340  // check that global theta of 2-D segment lies within cluster box plus or minus allowed slop
341  if (((*it2)->globalPosition().theta() < seed_maxY[NNN] + dYclusBoxMax) && ((*it2)->globalPosition().theta() > seed_minY[NNN] - dYclusBoxMax)) {
342  // check that global phi of 2-D segment (assumed to be center of chamber since no phi hit info)
343  // matches with cluster box plus or minus allowed slop given that the true phi value could be
344  // anywhere within a given chamber (+/- 5 degrees ~ 0.09 radians from center)
345  if(
346  !(
347  (
348  ((*it2)->globalPosition().phi() + 0.09) < (seed_minX[NNN] - dXclusBoxMax)
349  &&
350  ((*it2)->globalPosition().phi() - 0.09) < (seed_minX[NNN] - dXclusBoxMax)
351  )
352  ||
353  (
354  ((*it2)->globalPosition().phi() + 0.09) > (seed_maxX[NNN] + dXclusBoxMax)
355  &&
356  ((*it2)->globalPosition().phi() - 0.09) > (seed_maxX[NNN] + dXclusBoxMax)
357  )
358  )
359  ) { // we have checked that the 2Dsegment is within tight theta boundaries and loose phi boundaries of the current cluster -> add it
360  seeds[NNN].push_back((*it2));
361 
362  }
363  }
364  }
365 
366  }
367 
368  // put DT hasphi loop here
369  if (useDT2D_hasPhi) {
370 
371  for (MuonRecHitContainer::const_iterator it2 = muonRecHits_DT2D_hasPhi.begin(); it2 != muonRecHits_DT2D_hasPhi.end(); ++it2 ) {
372  if (((*it2)->globalPosition().phi() < seed_maxX[NNN] + dXclusBoxMax) && ((*it2)->globalPosition().phi() > seed_minX[NNN] - dXclusBoxMax)) {
373  if(
374  !(
375  (
376  ((*it2)->globalPosition().theta() + 0.3) < (seed_minY[NNN] - dYclusBoxMax)
377  &&
378  ((*it2)->globalPosition().theta() - 0.3) < (seed_minY[NNN] - dYclusBoxMax)
379  )
380  ||
381  (
382  ((*it2)->globalPosition().theta() + 0.3) > (seed_maxY[NNN] + dYclusBoxMax)
383  &&
384  ((*it2)->globalPosition().theta() - 0.3) > (seed_maxY[NNN] + dYclusBoxMax)
385  )
386  )
387  ) { // we have checked that the 2Dsegment is within tight phi boundaries and loose theta boundaries of the current cluster -> add it
388  seeds[NNN].push_back((*it2)); // warning - neeed eta/theta switch here
389 
390  }
391  }
392  }
393  } // DT2D_hastPhi loop
394 
395  // put RPC loop here
396  int secondCh = 0;
397  DetId detId_prev;
398  if(seeds[NNN].size()>1){// actually we should check how many chambers with measurements are present
399  for(unsigned int iRH = 0 ;iRH<seeds[NNN].size() ;++iRH){
400  if( iRH && detId_prev != seeds[NNN][iRH]->hit()->geographicalId()){
401  ++secondCh;
402  break;
403  }
404  detId_prev = seeds[NNN][iRH]->hit()->geographicalId();
405  }
406  }
407 
408  if (useRPCs && !secondCh && !tooCloseClusters) {
409  for (MuonRecHitContainer::const_iterator it2 = muonRecHits_RPC.begin(); it2 != muonRecHits_RPC.end(); ++it2 ) {
410  if (((*it2)->globalPosition().phi() < seed_maxX[NNN] + dXclusBoxMax) && ((*it2)->globalPosition().phi() > seed_minX[NNN] - dXclusBoxMax)) {
411  if(
412  !(
413  (
414  ((*it2)->globalPosition().theta() + 0.3) < (seed_minY[NNN] - dYclusBoxMax)
415  &&
416  ((*it2)->globalPosition().theta() - 0.3) < (seed_minY[NNN] - dYclusBoxMax)
417  )
418  ||
419  (
420  ((*it2)->globalPosition().theta() + 0.3) > (seed_maxY[NNN] + dYclusBoxMax)
421  &&
422  ((*it2)->globalPosition().theta() - 0.3) > (seed_maxY[NNN] + dYclusBoxMax)
423  )
424  )
425  ) { // we have checked that the 2Dsegment is within tight phi boundaries and loose theta boundaries of the current cluster -> add it
426  seeds[NNN].push_back((*it2)); // warning - neeed eta/theta switch here
427 
428  }
429  }
430  }
431  } // RPC loop
432  }
433 
434  // hand over the final seeds to the output
435  // would be more elegant if we could do the above step with
436  // erasing the merged ones, rather than the
437  for(unsigned int NNN = 0; NNN < seeds.size(); ++NNN) {
438  if(running_meanX[NNN] == 999999.) continue; //skip seeds that have been marked as used up in merging
439  //std::cout<<"Next Cluster..."<<std::endl;
440  segments_clusters.push_back(seeds[NNN]);
441  }
442 }
const double Pi
edm::EDGetTokenT< DTRecSegment4DCollection > dtToken
edm::EDGetTokenT< RPCRecHitCollection > rpcToken
edm::EDGetTokenT< CSCSegmentCollection > cscToken
const std::string metname
bool segmentCleaning(const DetId &detId, const LocalPoint &localPosition, const LocalError &localError, const LocalVector &localDirection, const LocalError &localDirectionError, const double &chi2, const int &ndf)
#define end
Definition: vmac.h:37
bool insert(Storage &iStorage, ItemType *iItem, const IdTag &iIdTag)
Definition: HCMethods.h:49
MuonServiceProxy * theService
Definition: DetId.h:18
#define begin
Definition: vmac.h:30
MuonTransientTrackingRecHit::MuonRecHitContainer MuonRecHitContainer
static MuonRecHitPointer specificBuild(const GeomDet *geom, const TrackingRecHit *rh)
tuple size
Write out results.
bool SETPatternRecognition::segmentCleaning ( const DetId detId,
const LocalPoint localPosition,
const LocalError localError,
const LocalVector localDirection,
const LocalError localDirectionError,
const double &  chi2,
const int &  ndf 
)

Definition at line 445 of file SETPatternRecognition.cc.

References Surface::bounds(), Bounds::inside(), minLocalSegmentAngle, outsideChamberErrorScale, GeomDet::surface(), theService, and PV3DBase< T, PVType, FrameType >::z().

Referenced by produce().

448  {
449  // drop segments which are "bad"
450  bool dropTheSegment = true;
451  const GeomDet* geomDet = theService->trackingGeometry()->idToDet( detId );
452  // only segments whithin the boundaries of the chamber
453  bool insideCh = geomDet->surface().bounds().inside(localPosition, localError,outsideChamberErrorScale);
454 
455  // Don't use segments (nearly) parallel to the chamberi;
456  // the direction vector is normalized (R=1)
457  bool parallelSegment = fabs(localDirection.z())>minLocalSegmentAngle? false: true;
458 
459  if(insideCh && !parallelSegment){
460  dropTheSegment = false;
461  }
462  // use chi2 too? (DT, CSCs, RPCs; 2D, 4D;...)
463 
464 
465  return dropTheSegment;
466 }
virtual bool inside(const Local3DPoint &) const =0
Determine if the point is inside the bounds.
const Bounds & bounds() const
Definition: Surface.h:128
const Plane & surface() const
The nominal surface of the GeomDet.
Definition: GeomDet.h:40
T z() const
Definition: PV3DBase.h:64
MuonServiceProxy * theService
void SETPatternRecognition::setServiceProxy ( MuonServiceProxy service)
inline

Definition at line 23 of file SETPatternRecognition.h.

References theService.

Referenced by SETMuonSeedProducer::SETMuonSeedProducer().

23 {theService = service;}
MuonServiceProxy * theService

Member Data Documentation

edm::InputTag SETPatternRecognition::CSCRecSegmentLabel
private

Definition at line 35 of file SETPatternRecognition.h.

Referenced by SETPatternRecognition().

edm::EDGetTokenT<CSCSegmentCollection> SETPatternRecognition::cscToken
private

Definition at line 39 of file SETPatternRecognition.h.

Referenced by produce(), and SETPatternRecognition().

edm::InputTag SETPatternRecognition::DTRecSegmentLabel
private

Definition at line 34 of file SETPatternRecognition.h.

Referenced by SETPatternRecognition().

edm::EDGetTokenT<DTRecSegment4DCollection> SETPatternRecognition::dtToken
private

Definition at line 38 of file SETPatternRecognition.h.

Referenced by produce(), and SETPatternRecognition().

int SETPatternRecognition::maxActiveChambers
private

Definition at line 31 of file SETPatternRecognition.h.

Referenced by produce(), and SETPatternRecognition().

double SETPatternRecognition::minLocalSegmentAngle
private

Definition at line 44 of file SETPatternRecognition.h.

Referenced by segmentCleaning(), and SETPatternRecognition().

double SETPatternRecognition::outsideChamberErrorScale
private

Definition at line 43 of file SETPatternRecognition.h.

Referenced by segmentCleaning(), and SETPatternRecognition().

edm::InputTag SETPatternRecognition::RPCRecSegmentLabel
private

Definition at line 36 of file SETPatternRecognition.h.

Referenced by SETPatternRecognition().

edm::EDGetTokenT<RPCRecHitCollection> SETPatternRecognition::rpcToken
private

Definition at line 40 of file SETPatternRecognition.h.

Referenced by produce(), and SETPatternRecognition().

MuonServiceProxy* SETPatternRecognition::theService
private

Definition at line 47 of file SETPatternRecognition.h.

Referenced by produce(), segmentCleaning(), and setServiceProxy().

bool SETPatternRecognition::useRPCs
private

Definition at line 32 of file SETPatternRecognition.h.

Referenced by produce(), and SETPatternRecognition().