#include <SETPatternRecognition.h>

Inheritance diagram for SETPatternRecognition:

Public Member Functions
void	produce (const edm::Event &event, const edm::EventSetup &eSetup, std::vector< MuonRecHitContainer > &result) override

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)

	~SETPatternRecognition () override

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

MuonServiceProxy *	theService

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...

bool	enableME0Measurement
	Enable the ME0 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...

edm::InputTag	theME0RecSegmentLabel
	the name of the ME0 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.

 : MuonSeedVPatternRecognition(parameterSet.getParameter<ParameterSet>("SETTrajBuilderParameters").getParameter<ParameterSet>("FilterParameters"))
 {
   const string metname = "Muon|RecoMuon|SETPatternRecognition";  
   // Parameter set for the Builder
   ParameterSet trajectoryBuilderParameters = parameterSet.getParameter<ParameterSet>("SETTrajBuilderParameters");
   // The inward-outward fitter (starts from seed state)
   ParameterSet filterPSet = trajectoryBuilderParameters.getParameter<ParameterSet>("FilterParameters");
   maxActiveChambers = filterPSet.getParameter<int>("maxActiveChambers"); 
   useRPCs = filterPSet.getParameter<bool>("EnableRPCMeasurement");
   DTRecSegmentLabel  = filterPSet.getParameter<edm::InputTag>("DTRecSegmentLabel");
   CSCRecSegmentLabel  = filterPSet.getParameter<edm::InputTag>("CSCRecSegmentLabel");
   RPCRecSegmentLabel  = filterPSet.getParameter<edm::InputTag>("RPCRecSegmentLabel");
 
   outsideChamberErrorScale = filterPSet.getParameter<double>("OutsideChamberErrorScale");
   minLocalSegmentAngle = filterPSet.getParameter<double>("MinLocalSegmentAngle");
   //----
   dtToken  = iC.consumes<DTRecSegment4DCollection>(DTRecSegmentLabel);
   cscToken = iC.consumes<CSCSegmentCollection>(CSCRecSegmentLabel);
   rpcToken = iC.consumes<RPCRecHitCollection> (RPCRecSegmentLabel);
 
 } 

SETPatternRecognition::~SETPatternRecognition ( )

inlineoverride

Definition at line 18 of file SETPatternRecognition.h.

References produce(), and mps_fire::result.

18 {}

Member Function Documentation

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

overridevirtual

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

Implements MuonSeedVPatternRecognition.

Definition at line 42 of file SETPatternRecognition.cc.

References begin, vertices_cff::chi2, cscSegments_cfi::cscSegments, cscToken, dtToken, CSCSegmentAlgorithmDF_cfi::dXclusBoxMax, CSCSegmentAlgorithmDF_cfi::dYclusBoxMax, end, edm::eventsetup::heterocontainer::insert(), maxActiveChambers, metname, Pi, JetIDParams_cfi::rpcRecHits, rpcToken, segmentCleaning(), findQualityFiles::size, MuonTransientTrackingRecHit::specificBuild(), groupFilesInBlocks::temp, theService, and useRPCs.

Referenced by SETMuonSeedProducer::produce(), and ~SETPatternRecognition().

 {
   const string metname = "Muon|RecoMuon|SETMuonSeedSeed";  
 
   //---- Build collection of all segments
   MuonRecHitContainer muonRecHits;
   MuonRecHitContainer muonRecHits_DT2D_hasPhi;
   MuonRecHitContainer muonRecHits_DT2D_hasZed;
   MuonRecHitContainer muonRecHits_RPC;
 
   // ********************************************;
   // Get the DT-Segment collection from the Event
   // ********************************************;
 
   edm::Handle<DTRecSegment4DCollection> dtRecHits;
   event.getByToken(dtToken, dtRecHits);
   std::vector<DTChamberId> chambers_DT;
   std::vector<DTChamberId>::const_iterator chIt_DT;
   for (DTRecSegment4DCollection::const_iterator rechit = dtRecHits->begin(); rechit!=dtRecHits->end();++rechit) {
     bool insert = true;
     for(chIt_DT=chambers_DT.begin(); chIt_DT != chambers_DT.end(); ++chIt_DT){
       if (
       ((*rechit).chamberId().wheel()) == ((*chIt_DT).wheel()) &&
       ((*rechit).chamberId().station() == (*chIt_DT).station()) &&
       ((*rechit).chamberId().sector() == (*chIt_DT).sector())){
     insert = false;
       }
     }
     if (insert){
       chambers_DT.push_back((*rechit).chamberId());
     }
     if(segmentCleaning((*rechit).geographicalId(), 
                rechit->localPosition(), rechit->localPositionError(),
                rechit->localDirection(), rechit->localDirectionError(),
                rechit->chi2(), rechit->degreesOfFreedom())){
       continue;
     }
     if( (rechit->hasZed() && rechit->hasPhi()) ) {
     muonRecHits.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
     }
     else if(rechit->hasZed()) {
     muonRecHits_DT2D_hasZed.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
     }
     else if(rechit->hasPhi()) { // safeguard
     muonRecHits_DT2D_hasPhi.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
     }
     else {
       //std::cout<<"Warning in "<<metname<<": DT segment which claims to have neither phi nor Z."<<std::endl;
     }
   }
   //std::cout<<"DT done"<<std::endl;
 
   // ********************************************;
   // Get the CSC-Segment collection from the event
   // ********************************************;
 
   edm::Handle<CSCSegmentCollection> cscSegments;
   event.getByToken(cscToken, cscSegments);
   std::vector<CSCDetId> chambers_CSC;
   std::vector<CSCDetId>::const_iterator chIt_CSC;
   for(CSCSegmentCollection::const_iterator rechit=cscSegments->begin(); rechit != cscSegments->end(); ++rechit) {
     bool insert = true;
     for(chIt_CSC=chambers_CSC.begin(); chIt_CSC != chambers_CSC.end(); ++chIt_CSC){
       if (((*rechit).cscDetId().chamber() == (*chIt_CSC).chamber()) &&
       ((*rechit).cscDetId().station() == (*chIt_CSC).station()) &&
       ((*rechit).cscDetId().ring() == (*chIt_CSC).ring()) &&
       ((*rechit).cscDetId().endcap() == (*chIt_CSC).endcap())){
     insert = false;
       }
     }
     if (insert){
       chambers_CSC.push_back((*rechit).cscDetId().chamberId());
     }
     if(segmentCleaning((*rechit).geographicalId(), 
                rechit->localPosition(), rechit->localPositionError(),
                rechit->localDirection(), rechit->localDirectionError(),
                rechit->chi2(), rechit->degreesOfFreedom())){
       continue;
     }
     muonRecHits.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
   }
   //std::cout<<"CSC done"<<std::endl;
 
   // ********************************************;
   // Get the RPC-Hit collection from the event
   // ********************************************;
 
   edm::Handle<RPCRecHitCollection> rpcRecHits;
   event.getByToken(rpcToken, rpcRecHits);
   if(useRPCs){
     for(RPCRecHitCollection::const_iterator rechit=rpcRecHits->begin(); rechit != rpcRecHits->end(); ++rechit) {
       // RPCs are special
       const LocalVector  localDirection(0.,0.,1.);
       const LocalError localDirectionError (0.,0.,0.); 
       const double chi2 = 1.;
       const int ndf = 1;
       if(segmentCleaning((*rechit).geographicalId(), 
              rechit->localPosition(), rechit->localPositionError(),
              localDirection, localDirectionError,
              chi2, ndf)){
     continue;
       }
       muonRecHits_RPC.push_back(MuonTransientTrackingRecHit::specificBuild(theService->trackingGeometry()->idToDet((*rechit).geographicalId()),&*rechit));
     }
   }
   //std::cout<<"RPC done"<<std::endl;
   //
   if(int(chambers_DT.size() + chambers_CSC.size()) > maxActiveChambers){
     // std::cout <<" Too many active chambers : nDT = "<<chambers_DT.size()<<
     // " nCSC = "<<chambers_CSC.size()<<"  Skip them all."<<std::endl;
     edm::LogWarning("tooManyActiveChambers")<<" Too many active chambers : nDT = "<<chambers_DT.size()
              <<" nCSC = "<<chambers_CSC.size()<<"  Skip them all.";
     muonRecHits.clear();                                
     muonRecHits_DT2D_hasPhi.clear();    
     muonRecHits_DT2D_hasZed.clear();
     muonRecHits_RPC.clear();
   }
   //---- Find "pre-clusters" from all segments; these contain potential muon candidates
 
   //---- From all the hits (i.e. segments; sometimes "rechits" is also used with the same meaning;
   //---- this convention has meaning in the global reconstruction though could be misleading 
   //---- from a local reconstruction point of view; "local rechits" are used in the backward fit only) 
   //---- make clusters of hits; a trajectory could contain hits from one cluster only   
 
   // the clustering procedure is very similar to the one used in the segment reconstruction 
 
   bool useDT2D_hasPhi = true;
   bool useDT2D_hasZed = true;
   double dXclusBoxMax         = 0.60; // phi - can be as large as 15 - 20 degrees for 6 GeV muons
   double dYclusBoxMax = 0.;
 
   // this is the main selection criteria; the value of 0.02 rad seems wide enough to 
   // contain any hit from a passing muon and still narrow enough to remove good part of
   // possible "junk" hits
   // (Comment: it may be better to allow maximum difference between any two hits in a trajectory
   // to be 0.02 or 0.04 or ...; currently the requirement below is imposed on two consecutive hits)  
 
   dYclusBoxMax              = 0.02; // theta // hardoded - remove it!
   
   // X and Y are distance variables - we use eta and phi here
 
   float dXclus = 0.0;
   float dXclus_box = 0.0;
   float dYclus_box = 0.0;
 
   MuonRecHitContainer temp;
 
   std::vector< MuonRecHitContainer > seeds;
 
   std::vector<float> running_meanX;
   std::vector<float> running_meanY;
 
   std::vector<float> seed_minX;
   std::vector<float> seed_maxX;
   std::vector<float> seed_minY;
   std::vector<float> seed_maxY;
 
   // split rechits into subvectors and return vector of vectors:
   // Loop over rechits 
   // Create one seed per hit
   for (MuonRecHitContainer::const_iterator it = muonRecHits.begin(); it != muonRecHits.end(); ++it ) {
 
     // try to avoid using 2D DT segments. We will add them later to the 
     // clusters they are most likely to belong to. Might need to add them 
     // to more than just one cluster, if we find them to be consistent with 
     // more than one. This would lead to an implicit sharing of hits between 
     // SA muon candidates. 
 
     temp.clear();
 
     temp.push_back((*it));
 
     seeds.push_back(temp);
 
     // First added hit in seed defines the mean to which the next hit is compared
     // for this seed.
 
     running_meanX.push_back( (*it)->globalPosition().phi() );
     running_meanY.push_back( (*it)->globalPosition().theta() );
 
     // set min/max X and Y for box containing the hits in the precluster:
     seed_minX.push_back( (*it)->globalPosition().phi() );
     seed_maxX.push_back( (*it)->globalPosition().phi() );
     seed_minY.push_back( (*it)->globalPosition().theta() );
     seed_maxY.push_back( (*it)->globalPosition().theta() );
   }
 
   // merge clusters that are too close
   // measure distance between final "running mean"
   for(unsigned int NNN = 0; NNN < seeds.size(); ++NNN) {
 
     for(unsigned int MMM = NNN+1; MMM < seeds.size(); ++MMM) {
       if(running_meanX[MMM] == 999999. || running_meanX[NNN] == 999999. ) {
     //        LogDebug("CSC") << "CSCSegmentST::clusterHits: Warning: Skipping used seeds, this should happen - inform developers!\n";
     //std::cout<<"We should never see this line now!!!"<<std::endl;
         continue; //skip seeds that have been used 
       }
 
       // Some complications for using phi as a clustering variable due to wrap-around (-pi = pi)
       // Define temporary mean, min, and max variables for the cluster which could be merged (NNN)
       double temp_meanX = running_meanX[NNN];
       double temp_minX = seed_minX[NNN];
       double temp_maxX = seed_maxX[NNN];
 
       // check if the difference between the two phi values is greater than pi
       // if so, need to shift temporary values by 2*pi to make a valid comparison
       dXclus = running_meanX[NNN] - running_meanX[MMM];
       if (dXclus > TMath::Pi()) {
         temp_meanX = temp_meanX - 2.*TMath::Pi();
         temp_minX = temp_minX - 2.*TMath::Pi();
         temp_maxX = temp_maxX - 2.*TMath::Pi();
       }
       if (dXclus < -TMath::Pi()) {
         temp_meanX = temp_meanX + 2.*TMath::Pi();
         temp_minX = temp_minX + 2.*TMath::Pi();
         temp_maxX = temp_maxX + 2.*TMath::Pi();
       }
 
       //       // calculate cut criteria for simple running mean distance cut:
       //       // not sure that these values are really used anywhere
 
       // calculate minmal distance between precluster boxes containing the hits:
       // use the temp variables from above for phi of the NNN cluster 
       if ( temp_meanX > running_meanX[MMM] )         dXclus_box = temp_minX - seed_maxX[MMM];
       else                                           dXclus_box = seed_minX[MMM] - temp_maxX;
       if ( running_meanY[NNN] > running_meanY[MMM] ) dYclus_box = seed_minY[NNN] - seed_maxY[MMM];
       else                                           dYclus_box = seed_minY[MMM] - seed_maxY[NNN];
 
 
       if( dXclus_box < dXclusBoxMax && dYclus_box < dYclusBoxMax ) {
         // merge clusters!
         // merge by adding seed NNN to seed MMM and erasing seed NNN
 
         // calculate running mean for the merged seed:
         // use the temp variables from above for phi of the NNN cluster 
         running_meanX[MMM] = (temp_meanX*seeds[NNN].size() + running_meanX[MMM]*seeds[MMM].size()) / (seeds[NNN].size()+seeds[MMM].size());
         running_meanY[MMM] = (running_meanY[NNN]*seeds[NNN].size() + running_meanY[MMM]*seeds[MMM].size()) / (seeds[NNN].size()+seeds[MMM].size());
 
         // update min/max X and Y for box containing the hits in the merged cluster:
         // use the temp variables from above for phi of the NNN cluster 
         if ( temp_minX <= seed_minX[MMM] ) seed_minX[MMM] = temp_minX;
         if ( temp_maxX >  seed_maxX[MMM] ) seed_maxX[MMM] = temp_maxX;
         if ( seed_minY[NNN] <= seed_minY[MMM] ) seed_minY[MMM] = seed_minY[NNN];
         if ( seed_maxY[NNN] >  seed_maxY[MMM] ) seed_maxY[MMM] = seed_maxY[NNN];
 
         // now check to see if the running mean has moved outside of the allowed -pi to pi region
         // if so, then adjust shift all values up or down by 2 * pi
         if (running_meanX[MMM] > TMath::Pi()) {
           running_meanX[MMM] = running_meanX[MMM] - 2.*TMath::Pi();
           seed_minX[MMM] = seed_minX[MMM] - 2.*TMath::Pi();
           seed_maxX[MMM] = seed_maxX[MMM] - 2.*TMath::Pi();
         }
         if (running_meanX[MMM] < -TMath::Pi()) {
           running_meanX[MMM] = running_meanX[MMM] + 2.*TMath::Pi();
           seed_minX[MMM] = seed_minX[MMM] + 2.*TMath::Pi();
           seed_maxX[MMM] = seed_maxX[MMM] + 2.*TMath::Pi();
         }
 
         // add seed NNN to MMM (lower to larger number)
         seeds[MMM].insert(seeds[MMM].end(),seeds[NNN].begin(),seeds[NNN].end());
 
         // mark seed NNN as used (at the moment just set running mean to 999999.)
         running_meanX[NNN] = 999999.;
         running_meanY[NNN] = 999999.;
         // we have merged a seed (NNN) to the highter seed (MMM) - need to contimue to 
         // next seed (NNN+1)
         break;
       }
 
     }
   }
   bool tooCloseClusters = false;
   if(seeds.size()>1){
     std::vector <double> seedTheta(seeds.size());
     for(unsigned int iSeed = 0;iSeed<seeds.size();++iSeed){
       seedTheta[iSeed] = seeds[iSeed][0]->globalPosition().theta(); 
       if(iSeed){
     double dTheta = fabs(seedTheta[iSeed] - seedTheta[iSeed-1]);
     if (dTheta < 0.5){ //? should be something more clever
       tooCloseClusters = true;
       break;
     }
       }
     }
     
   }
 
   // have formed clusters from all hits except for 2D DT segments. Now add the 2D segments to the 
   // compatible clusters. For this we compare the mean cluster postition with the 
   // 2D segment position. We should use the valid coordinate only and use the bad coordinate 
   // as a cross check.
   for(unsigned int NNN = 0; NNN < seeds.size(); ++NNN) {
     if(running_meanX[NNN] == 999999.) continue; //skip seeds that have been marked as used up in merging
 
     // We have a valid cluster - loop over all 2D segments.
     if(useDT2D_hasZed) {
       for (MuonRecHitContainer::const_iterator it2 = muonRecHits_DT2D_hasZed.begin(); it2 != muonRecHits_DT2D_hasZed.end(); ++it2 ) {
     // check that global theta of 2-D segment lies within cluster box plus or minus allowed slop
     if (((*it2)->globalPosition().theta() < seed_maxY[NNN] + dYclusBoxMax) && ((*it2)->globalPosition().theta() > seed_minY[NNN] - dYclusBoxMax)) {
       // check that global phi of 2-D segment (assumed to be center of chamber since no phi hit info)
       // matches with cluster box plus or minus allowed slop given that the true phi value could be 
       // anywhere within a given chamber (+/- 5 degrees ~ 0.09 radians from center) 
       if(
          !( 
            (
         ((*it2)->globalPosition().phi() + 0.09) < (seed_minX[NNN] - dXclusBoxMax) 
         && 
         ((*it2)->globalPosition().phi() - 0.09) < (seed_minX[NNN] - dXclusBoxMax)
         )
            ||
            (
         ((*it2)->globalPosition().phi() + 0.09) > (seed_maxX[NNN] + dXclusBoxMax) 
         && 
         ((*it2)->globalPosition().phi() - 0.09) > (seed_maxX[NNN] + dXclusBoxMax)
         )
            )
          ) { // we have checked that the 2Dsegment is within tight theta boundaries and loose phi boundaries of the current cluster -> add it
         seeds[NNN].push_back((*it2));
         
       }
     }                 
       }
       
     }
     
     // put DT hasphi loop here
     if (useDT2D_hasPhi) {
       
       for (MuonRecHitContainer::const_iterator it2 = muonRecHits_DT2D_hasPhi.begin(); it2 != muonRecHits_DT2D_hasPhi.end(); ++it2 ) {
     if (((*it2)->globalPosition().phi() < seed_maxX[NNN] + dXclusBoxMax) && ((*it2)->globalPosition().phi() > seed_minX[NNN] - dXclusBoxMax)) {
       if(
          !( 
            (
         ((*it2)->globalPosition().theta() + 0.3) < (seed_minY[NNN] - dYclusBoxMax) 
         && 
         ((*it2)->globalPosition().theta() - 0.3) < (seed_minY[NNN] - dYclusBoxMax)
         )
            ||
            (
         ((*it2)->globalPosition().theta() + 0.3) > (seed_maxY[NNN] + dYclusBoxMax) 
         && 
         ((*it2)->globalPosition().theta() - 0.3) > (seed_maxY[NNN] + dYclusBoxMax)
         )
            )
          ) { // we have checked that the 2Dsegment is within tight phi boundaries and loose theta boundaries of the current cluster -> add it
         seeds[NNN].push_back((*it2)); // warning - neeed eta/theta switch here
         
       }
     }
       }
     } // DT2D_hastPhi loop
     
     // put RPC loop here
     int secondCh = 0;
     DetId detId_prev;
     if(seeds[NNN].size()>1){// actually we should check how many chambers with measurements are present
       for(unsigned int iRH = 0 ;iRH<seeds[NNN].size() ;++iRH){
         if( iRH && detId_prev != seeds[NNN][iRH]->hit()->geographicalId()){
       ++secondCh;
       break;
     }
     detId_prev = seeds[NNN][iRH]->hit()->geographicalId();
       }
     }
 
     if (useRPCs && !secondCh && !tooCloseClusters) {
       for (MuonRecHitContainer::const_iterator it2 = muonRecHits_RPC.begin(); it2 != muonRecHits_RPC.end(); ++it2 ) {
     if (((*it2)->globalPosition().phi() < seed_maxX[NNN] + dXclusBoxMax) && ((*it2)->globalPosition().phi() > seed_minX[NNN] - dXclusBoxMax)) {
       if(
          !( 
            (
         ((*it2)->globalPosition().theta() + 0.3) < (seed_minY[NNN] - dYclusBoxMax) 
         && 
         ((*it2)->globalPosition().theta() - 0.3) < (seed_minY[NNN] - dYclusBoxMax)
         )
            ||
            (
         ((*it2)->globalPosition().theta() + 0.3) > (seed_maxY[NNN] + dYclusBoxMax) 
         && 
         ((*it2)->globalPosition().theta() - 0.3) > (seed_maxY[NNN] + dYclusBoxMax)
         )
            )
          ) { // we have checked that the 2Dsegment is within tight phi boundaries and loose theta boundaries of the current cluster -> add it
         seeds[NNN].push_back((*it2)); // warning - neeed eta/theta switch here
         
       }
     }
       }
     } // RPC loop
   }
   
   // hand over the final seeds to the output
   // would be more elegant if we could do the above step with 
   // erasing the merged ones, rather than the 
   for(unsigned int NNN = 0; NNN < seeds.size(); ++NNN) {
     if(running_meanX[NNN] == 999999.) continue; //skip seeds that have been marked as used up in merging
     //std::cout<<"Next Cluster..."<<std::endl;
     segments_clusters.push_back(seeds[NNN]);
   }
 }

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(), and setServiceProxy().

                                                            {
   // drop segments which are "bad"
   bool dropTheSegment = true;
   const GeomDet* geomDet = theService->trackingGeometry()->idToDet( detId );
   // only segments whithin the boundaries of the chamber
   bool insideCh = geomDet->surface().bounds().inside(localPosition, localError,outsideChamberErrorScale);
 
   // Don't use segments (nearly) parallel to the chamberi;
   // the direction vector is normalized (R=1)  
   bool parallelSegment = fabs(localDirection.z())>minLocalSegmentAngle? false: true;
 
   if(insideCh && !parallelSegment){
     dropTheSegment = false;
   }
   // use chi2 too? (DT, CSCs, RPCs; 2D, 4D;...)
 
 
   return dropTheSegment;
 }