#include <HoughSeedFinderAlg.h>

Inheritance diagram for lar_cluster3d::HoughSeedFinderAlg:

Classes
class	AccumulatorBin

struct	SortBinIndexList

class	SortHoughClusterList

Public Member Functions
	HoughSeedFinderAlg (fhicl::ParameterSet const &pset)
	Constructor. More...

virtual	~HoughSeedFinderAlg ()
	Destructor. More...

virtual void	reconfigure (fhicl::ParameterSet const &pset)
	a handler for the case where the algorithm control parameters are to be reset More...

virtual bool	findTrackSeeds (reco::HitPairListPtr &hitPairListPtr, reco::PrincipalComponents &inputPCA, SeedHitPairListPairVec &seedHitPairVec) const
	Given the list of hits this will search for candidate Seed objects and return them. More...

virtual bool	findTrackHits (reco::HitPairListPtr &hitPairListPtr, reco::PrincipalComponents &inputPCA, reco::HitPairListPtrList &hitPairListPtrList) const
	Given the list of hits this will return the sets of hits which belong on the same line. More...

	HoughSeedFinderAlg (fhicl::ParameterSet const &pset)
	Constructor. More...

bool	findTrackSeeds (reco::HitPairListPtr &hitPairListPtr, reco::PrincipalComponents &inputPCA, SeedHitPairListPairVec &seedHitPairVec) const override
	Given the list of hits this will search for candidate Seed objects and return them. More...

bool	findTrackHits (reco::HitPairListPtr &hitPairListPtr, reco::PrincipalComponents &inputPCA, reco::HitPairListPtrList &hitPairListPtrList) const
	Given the list of hits this will return the sets of hits which belong on the same line. More...

Private Types
typedef std::pair< int, int >	BinIndex

typedef std::map< BinIndex, AccumulatorBin >	RhoThetaAccumulatorBinMap

typedef std::list< BinIndex >	HoughCluster

typedef std::list< HoughCluster >	HoughClusterList

typedef std::pair< int, int >	BinIndex

typedef std::map< BinIndex, AccumulatorBin >	RhoThetaAccumulatorBinMap

typedef std::list< BinIndex >	HoughCluster

typedef std::list< HoughCluster >	HoughClusterList

Private Member Functions
void	findHitGaps (reco::HitPairListPtr &inputHitList, reco::HitPairListPtr &outputList) const
	Using Principal Components Axis, look for gaps in a list of 3D hits. More...

void	HoughRegionQuery (BinIndex &curBin, RhoThetaAccumulatorBinMap &rhoThetaAccumulatorBinMap, HoughCluster &neighborPts, size_t threshold) const

void	expandHoughCluster (BinIndex &curBin, HoughCluster &neighborPts, HoughCluster &houghCluster, RhoThetaAccumulatorBinMap &rhoThetaAccumulatorBinMap, size_t threshold) const

void	findHoughClusters (const reco::HitPairListPtr &inputHits, reco::PrincipalComponents &pca, int &nLoops, RhoThetaAccumulatorBinMap &rhoThetaMap, HoughClusterList &clusterList) const

bool	buildSeed (reco::HitPairListPtr &seed3DHits, SeedHitPairListPair &seedHitPair) const
	Given a list of candidate "seed" 3D hits, build the seed and get associated unique 2D hits. More...

void	LineFit2DHits (std::set< const reco::ClusterHit2D * > &hitList, double XOrigin, TVector3 &Pos, TVector3 &Dir, double &ChiDOF) const

void	findHitGaps (reco::HitPairListPtr &inputHitList, reco::HitPairListPtr &outputList) const
	Using Principal Components Axis, look for gaps in a list of 3D hits. More...

void	HoughRegionQuery (BinIndex &curBin, RhoThetaAccumulatorBinMap &rhoThetaAccumulatorBinMap, HoughCluster &neighborPts, size_t threshold) const

void	expandHoughCluster (BinIndex &curBin, HoughCluster &neighborPts, HoughCluster &houghCluster, RhoThetaAccumulatorBinMap &rhoThetaAccumulatorBinMap, size_t threshold) const

void	findHoughClusters (const reco::HitPairListPtr &inputHits, reco::PrincipalComponents &pca, int &nLoops, RhoThetaAccumulatorBinMap &rhoThetaMap, HoughClusterList &clusterList) const

bool	buildSeed (reco::HitPairListPtr &seed3DHits, SeedHitPairListPair &seedHitPair) const
	Given a list of candidate "seed" 3D hits, build the seed and get associated unique 2D hits. More...

void	LineFit2DHits (std::set< const reco::ClusterHit2D * > &hitList, double XOrigin, TVector3 &Pos, TVector3 &Dir, double &ChiDOF) const

Private Attributes
size_t	m_minimum3DHits

int	m_thetaBins

int	m_rhoBins

size_t	m_hiThresholdMin

double	m_hiThresholdFrac

double	m_loThresholdFrac

size_t	m_numSeed2DHits

double	m_numAveDocas

int	m_numSkippedHits

int	m_maxLoopsPerCluster

double	m_maximumGap

geo::Geometry *	m_geometry

PrincipalComponentsAlg	m_pcaAlg

bool	m_displayHist

std::vector< std::unique_ptr< TCanvas > >	m_Canvases
	Graphical trace canvases. More...

std::vector< TVirtualPad * >	m_Pads
	View pads in current canvas. More...

geo::Geometry const *	m_geometry

Detailed Description

HoughSeedFinderAlg class.

Definition at line 31 of file HoughSeedFinderAlg.h.

Member Typedef Documentation

typedef std::pair<int, int> lar_cluster3d::HoughSeedFinderAlg::BinIndex

private

Definition at line 73 of file HoughSeedFinderAlg.h.

typedef std::pair<int, int> lar_cluster3d::HoughSeedFinderAlg::BinIndex

private

Definition at line 82 of file HoughSeedFinderAlg.h.

typedef std::list<BinIndex> lar_cluster3d::HoughSeedFinderAlg::HoughCluster

private

Definition at line 79 of file HoughSeedFinderAlg.h.

typedef std::list<BinIndex> lar_cluster3d::HoughSeedFinderAlg::HoughCluster

private

Definition at line 88 of file HoughSeedFinderAlg.h.

typedef std::list<HoughCluster> lar_cluster3d::HoughSeedFinderAlg::HoughClusterList

private

Definition at line 80 of file HoughSeedFinderAlg.h.

typedef std::list<HoughCluster > lar_cluster3d::HoughSeedFinderAlg::HoughClusterList

private

Definition at line 89 of file HoughSeedFinderAlg.h.

typedef std::map<BinIndex, AccumulatorBin> lar_cluster3d::HoughSeedFinderAlg::RhoThetaAccumulatorBinMap

private

Definition at line 78 of file HoughSeedFinderAlg.h.

typedef std::map<BinIndex, AccumulatorBin> lar_cluster3d::HoughSeedFinderAlg::RhoThetaAccumulatorBinMap

private

Definition at line 87 of file HoughSeedFinderAlg.h.

Constructor & Destructor Documentation

lar_cluster3d::HoughSeedFinderAlg::HoughSeedFinderAlg ( fhicl::ParameterSet const & pset )

Constructor.

Parameters

pset

Definition at line 49 of file HoughSeedFinderAlg.cxx.

                                                                     :
      m_minimum3DHits(5),
      m_thetaBins(360),
      m_rhoBins(75),
      m_hiThresholdMin(5),
      m_hiThresholdFrac(.05),
      m_loThresholdFrac(0.85),
      m_numSeed2DHits(80),
      m_numAveDocas(6.),
      m_numSkippedHits(10),
      m_maxLoopsPerCluster(3),
      m_maximumGap(5.),
      m_pcaAlg(pset.get<fhicl::ParameterSet>("PrincipalComponentsAlg")),
      m_displayHist(false)
 {
     this->reconfigure(pset);
     
     art::ServiceHandle<geo::Geometry>            geometry;
     
     m_geometry = &*geometry;
     //    m_detector = detectorProperties->provider();
 }

lar_cluster3d::HoughSeedFinderAlg::~HoughSeedFinderAlg ( )

virtual

Destructor.

Definition at line 74 of file HoughSeedFinderAlg.cxx.

75 {

76 }

lar_cluster3d::HoughSeedFinderAlg::HoughSeedFinderAlg ( fhicl::ParameterSet const & pset )

Constructor.

Parameters

pset

Member Function Documentation

bool lar_cluster3d::HoughSeedFinderAlg::buildSeed	(	reco::HitPairListPtr &	seed3DHits,
		SeedHitPairListPair &	seedHitPair
	)		const

private

Given a list of candidate "seed" 3D hits, build the seed and get associated unique 2D hits.

bool lar_cluster3d::HoughSeedFinderAlg::buildSeed	(	reco::HitPairListPtr &	seed3DHits,
		SeedHitPairListPair &	seedHitPair
	)		const

private

Given a list of candidate "seed" 3D hits, build the seed and get associated unique 2D hits.

Definition at line 552 of file HoughSeedFinderAlg.cxx.

 {
     if (seed3DHits.size() < m_minimum3DHits) return false;
     
     reco::PrincipalComponents seedFullPca;
     
     m_pcaAlg.PCAAnalysis_3D(seed3DHits, seedFullPca, true);
     
     if (!seedFullPca.getSvdOK()) return false;
 
     // Use the following to set the 3D doca and arclength for each hit
     m_pcaAlg.PCAAnalysis_calc3DDocas(seed3DHits, seedFullPca);
     
     // Use this info to sort the hits along the principle axis
     //seed3DHits.sort(SeedFinderAlgBase::Sort3DHitsByArcLen3D());
     seed3DHits.sort(SeedFinderAlgBase::Sort3DHitsByAbsArcLen3D());
     
     // The idea here is to search for the first hit that lies "close" to the principle axis
     // At that point we count out n hits to use as the seed
     reco::HitPairListPtr                seedHit3DList;
     std::set<const reco::ClusterHit2D*> seedHitSet;
     double                              aveDocaToAxis = seedFullPca.getAveHitDoca();
     int                                 gapCount(0);
     
     // Now loop through hits to search for a "continuous" block of at least m_numSeed2DHits
     // We'll arrive at that number by collecting 2D hits in an stl set which will keep track of unique occurances
     for(reco::HitPairListPtr::iterator peakBinItr = seed3DHits.begin(); peakBinItr != seed3DHits.end(); peakBinItr++)
     {
         const reco::ClusterHit3D* hit3D = *peakBinItr;
         
         if (hit3D->getDocaToAxis() < m_numAveDocas*aveDocaToAxis)
         {
             // Check if we need to reset because of gap count
             if (gapCount > m_numSkippedHits)
             {
                 seedHit3DList.clear();
                 seedHitSet.clear();
             }
             
             seedHit3DList.push_back(hit3D);
             
             for(const auto& hit : hit3D->getHits()) seedHitSet.insert(hit);
             
             gapCount = 0;
         }
         else gapCount++;
         
         if (seedHitSet.size() > m_numSeed2DHits) break;
     }
     
     // If not enough hits then we are done
     if (seedHit3DList.size() < m_minimum3DHits) return false;
     
     reco::PrincipalComponents seedPca;
 
     // Use only the "seed" 3D hits to get new PCA axes
     m_pcaAlg.PCAAnalysis_3D(seedHit3DList, seedPca, true);
     
     if (!seedPca.getSvdOK()) return false;
     
     m_pcaAlg.PCAAnalysis_calc3DDocas(seedHit3DList, seedPca);
     //seedHit3DList.sort(SeedFinderAlgBase::Sort3DHitsByAbsArcLen3D());
     seedHit3DList.sort(SeedFinderAlgBase::Sort3DHitsByArcLen3D());
     
     // Now translate the seedCenter by the arc len to the first hit
     double seedCenter[3] = {seedPca.getAvePosition()[0],     seedPca.getAvePosition()[1],     seedPca.getAvePosition()[2]};
     double seedDir[3]    = {seedPca.getEigenVectors()[0][0], seedPca.getEigenVectors()[0][1], seedPca.getEigenVectors()[0][2]};
     
     double arcLen       = seedHit3DList.front()->getArclenToPoca();
     double seedStart[3] = {seedCenter[0]+arcLen*seedDir[0], seedCenter[1]+arcLen*seedDir[1], seedCenter[2]+arcLen*seedDir[2]};
     
     //seedStart[0] = seedHit3DList.front()->getX();
     //seedStart[1] = seedHit3DList.front()->getY();
     //seedStart[2] = seedHit3DList.front()->getZ();
     
     if (seedHitSet.size() >= 10)
     {
         TVector3 newSeedPos;
         TVector3 newSeedDir;
         double   chiDOF;
     
         LineFit2DHits(seedHitSet, seedStart[0], newSeedPos, newSeedDir, chiDOF);
     
         if (chiDOF > 0.)
         {
             // check angles between new/old directions
             double cosAng = seedDir[0]*newSeedDir[0]+seedDir[1]*newSeedDir[1]+seedDir[2]*newSeedDir[2];
             
             if (cosAng < 0.) newSeedDir *= -1.;
             
             seedStart[0] = newSeedPos[0];
             seedStart[1] = newSeedPos[1];
             seedStart[2] = newSeedPos[2];
             seedDir[0]   = newSeedDir[0];
             seedDir[1]   = newSeedDir[1];
             seedDir[2]   = newSeedDir[2];
         }
     }
 
     // Keep track of this seed and the 3D hits that make it up
     seedHitPair = SeedHitPairListPair(recob::Seed(seedStart, seedDir), seedHit3DList);
     
     // We are going to drop a few hits off the ends in the hope this facilitates finding more track like objects, provided there are enough hits
     if (seed3DHits.size() > 100)
     {
         // Need to reset the doca/arclen first
         m_pcaAlg.PCAAnalysis_calc3DDocas(seed3DHits, seedFullPca);
         
         // Now resort the hits
         seed3DHits.sort(SeedFinderAlgBase::Sort3DHitsByAbsArcLen3D());
         
         size_t numToKeep = seed3DHits.size() - 10;
         
         reco::HitPairListPtr::iterator endItr = seed3DHits.begin();
         
         std::advance(endItr, numToKeep);
         
         seed3DHits.erase(endItr, seed3DHits.end());
     }
     
     return true;
 }

void lar_cluster3d::HoughSeedFinderAlg::expandHoughCluster	(	BinIndex &	curBin,
		HoughCluster &	neighborPts,
		HoughCluster &	houghCluster,
		RhoThetaAccumulatorBinMap &	rhoThetaAccumulatorBinMap,
		size_t	threshold
	)		const

private

void lar_cluster3d::HoughSeedFinderAlg::expandHoughCluster	(	BinIndex &	curBin,
		HoughCluster &	neighborPts,
		HoughCluster &	houghCluster,
		RhoThetaAccumulatorBinMap &	rhoThetaAccumulatorBinMap,
		size_t	threshold
	)		const

private

The workhorse routine for a DBScan like clustering routine to identify peak bins in Hough Space

Definition at line 228 of file HoughSeedFinderAlg.cxx.

 {
     /** 
      *  @brief The workhorse routine for a DBScan like clustering routine to identify peak bins in Hough Space
      */
     
     // Start by adding the input point to our Hough Cluster
     houghCluster.push_back(curBin);
     
     for(auto& binIndex : neighborPts)
     {
         AccumulatorBin& accBin = rhoThetaAccumulatorBinMap[binIndex];
         
         if (!accBin.isVisited())
         {
             accBin.setVisited();
             
             HoughCluster nextNeighborPts;
             
             HoughRegionQuery(binIndex, rhoThetaAccumulatorBinMap, nextNeighborPts, threshold);
             
             if(!nextNeighborPts.empty())
             {
                 for(auto& neighborIdx : nextNeighborPts)
                 {
                     neighborPts.push_back(neighborIdx);
                 }
             }
         }
         
         if (!accBin.isInCluster())
         {
             houghCluster.push_back(binIndex);
             accBin.setInCluster();
         }
     }
     
     return;
 }

void lar_cluster3d::HoughSeedFinderAlg::findHitGaps	(	reco::HitPairListPtr &	inputHitList,
		reco::HitPairListPtr &	outputList
	)		const

private

Using Principal Components Axis, look for gaps in a list of 3D hits.

Parameters

inputHitList	- input list of 3D hits to check
pca	- Principal Components Axis to use
hitListList	- output list of hit lists which are gap free

void lar_cluster3d::HoughSeedFinderAlg::findHitGaps	(	reco::HitPairListPtr &	inputHitList,
		reco::HitPairListPtr &	outputList
	)		const

private

Using Principal Components Axis, look for gaps in a list of 3D hits.

Parameters

inputHitList	- input list of 3D hits to check
pca	- Principal Components Axis to use
hitListList	- output list of hit lists which are gap free

Definition at line 306 of file HoughSeedFinderAlg.cxx.

 {
     // Intention is to try to find the largest "contiguous" block of hits in the input list
     // In a nutshell, the idea is to order input hits according to the pca, then
     // loop through the hits and store them in a new hit list. If a gap is detected then
     // we terminate the previous list, create a new one and continue. After the loop over
     // hits is complete then simply pick the biggest list.
     // Step I is to run the pca and order the hits
     reco::PrincipalComponents pca;
     
     m_pcaAlg.PCAAnalysis_3D(inputHitList, pca, true);
     
     // It would seem that the analysis can fail!
     if (!pca.getSvdOK())
     {
         outputList = inputHitList;
         return;
     }
     
     m_pcaAlg.PCAAnalysis_calc3DDocas(inputHitList, pca);
     
     inputHitList.sort(SeedFinderAlgBase::Sort3DHitsByArcLen3D());
     outputList.clear();
     
     // Create containers to hold our hit lists
     reco::HitPairListPtr continuousHitList;
     
     std::map<size_t, reco::HitPairListPtr > gapHitListMap;
     
     // Remember the distance arc length of the last hit
     double arcLenLastHit = inputHitList.front()->getArclenToPoca();
     
     // Loop through the input hits
     for(const auto& hit3D : inputHitList)
     {
         // Hits in order, delta arclength should always be positive
         double arcLen      = hit3D->getArclenToPoca();
         double deltaArcLen = arcLen - arcLenLastHit;
         
         if (deltaArcLen > m_maximumGap)
         {
             gapHitListMap[continuousHitList.size()] = continuousHitList;
             continuousHitList.clear();
         }
         
         continuousHitList.emplace_back(hit3D);
         
         arcLenLastHit = arcLen;
     }
     
     if (!continuousHitList.empty()) gapHitListMap[continuousHitList.size()] = continuousHitList;
     
     // Get the largest list of hits
     std::map<size_t, reco::HitPairListPtr >::reverse_iterator longestListItr = gapHitListMap.rbegin();
     
     if (longestListItr != gapHitListMap.rend())
     {
         size_t               nContinuousHits = longestListItr->first;
         reco::HitPairListPtr longestList     = longestListItr->second;
     
         outputList.resize(nContinuousHits);
         std::copy(longestList.begin(), longestList.end(), outputList.begin());
     }
 
     return;
 }

void lar_cluster3d::HoughSeedFinderAlg::findHoughClusters	(	const reco::HitPairListPtr &	inputHits,
		reco::PrincipalComponents &	pca,
		int &	nLoops,
		RhoThetaAccumulatorBinMap &	rhoThetaMap,
		HoughClusterList &	clusterList
	)		const

private

void lar_cluster3d::HoughSeedFinderAlg::findHoughClusters	(	const reco::HitPairListPtr &	inputHits,
		reco::PrincipalComponents &	pca,
		int &	nLoops,
		RhoThetaAccumulatorBinMap &	rhoThetaMap,
		HoughClusterList &	clusterList
	)		const

private

Definition at line 374 of file HoughSeedFinderAlg.cxx.

 {
     // The goal of this function is to do a basic Hough Transform on the input list of 3D hits.
     // In order to transform this to a 2D problem, the 3D hits are projected to the plane of the two
     // largest eigen values from the input principal components analysis axis.
     // There are two basic steps to the job here:
     // 1) Build and accumlate a rho-theta map
     // 2) Go through that rho-theta map and find candidate Hough "clusters"
     // Unfortunately, the following may not be suitable viewing for those who may be feint of heart
     //
     // Define some constants
     static int   histCount(0);
     const double maxTheta(M_PI);                               // Obviously, 180 degrees
     const double thetaBinSize(maxTheta/double(m_thetaBins));    // around 4 degrees (45 bins)
     const double rhoBinSizeMin(m_geometry->WirePitch());       // Wire spacing gives a natural bin size?
     
     // Recover the parameters from the Principal Components Analysis that we need to project and accumulate
     TVector3 pcaCenter(pca.getAvePosition()[0],pca.getAvePosition()[1],pca.getAvePosition()[2]);
     TVector3 planeVec0(pca.getEigenVectors()[0][0],pca.getEigenVectors()[0][1],pca.getEigenVectors()[0][2]);
     TVector3 planeVec1(pca.getEigenVectors()[1][0],pca.getEigenVectors()[1][1],pca.getEigenVectors()[1][2]);
     TVector3 pcaPlaneNrml(pca.getEigenVectors()[2][0],pca.getEigenVectors()[2][1],pca.getEigenVectors()[2][2]);
     double   eigenVal0  = 3. * sqrt(pca.getEigenValues()[0]);
     double   eigenVal1  = 3. * sqrt(pca.getEigenValues()[1]);
     double   maxRho     = std::sqrt(eigenVal0*eigenVal0 + eigenVal1*eigenVal1) * 2. / 3.;
     double   rhoBinSize = maxRho / double(m_rhoBins);
     
     if (rhoBinSize < rhoBinSizeMin) rhoBinSize = rhoBinSizeMin;
     
     // **********************************************************************
     // Part I: Accumulate values in the rho-theta map
     // **********************************************************************
     
     size_t maxBinCount(0);
     int    nAccepted3DHits(0);
     
     // Commence looping over the input 3D hits and fill our accumulator bins
     for(reco::HitPairListPtr::const_iterator hit3DItr  = hitPairListPtr.begin();
                                              hit3DItr != hitPairListPtr.end();
                                              hit3DItr++)
     {
         // Recover the hit
         const reco::ClusterHit3D* hit3D(*hit3DItr);
         
         // Skip hits which are not skeleton points
         if (!(hit3D->getStatusBits() & 0x10000000)) continue;
         
         nAccepted3DHits++;
         
         TVector3 hit3DPosition(hit3D->getPosition()[0], hit3D->getPosition()[1], hit3D->getPosition()[2]);
         TVector3 pcaToHitVec = hit3DPosition - pcaCenter;
         TVector3 pcaToHitPlaneVec(pcaToHitVec.Dot(planeVec0), pcaToHitVec.Dot(planeVec1), 0.);
         
         double   xPcaToHit = pcaToHitPlaneVec[0];
         double   yPcaToHit = pcaToHitPlaneVec[1];
         
         // Create an accumulator value
         AccumulatorValues accValue(pcaToHitPlaneVec, hit3DItr);
         
         // Commence loop over theta to fill accumulator bins
         // Note that with theta in the range 0-pi then we can have negative values for rho
         for(int thetaIdx  = 0; thetaIdx < m_thetaBins; thetaIdx++)
         {
             // We need to convert our theta index to an angle
             double theta  = thetaBinSize * double(thetaIdx);
             
             // calculate rho for this angle
             double rho    = xPcaToHit * std::cos(theta) + yPcaToHit * std::sin(theta);
             
             // Get the rho index
             int    rhoIdx = std::round(rho / rhoBinSize);
             
             // Accumulate
             BinIndex binIndex(rhoIdx, thetaIdx);
             
             rhoThetaAccumulatorBinMap[binIndex].addAccumulatorValue(accValue);
             
             if (rhoThetaAccumulatorBinMap[binIndex].getAccumulatorValues().size() > maxBinCount)
                 maxBinCount = rhoThetaAccumulatorBinMap[binIndex].getAccumulatorValues().size();
         }
     }
     
     // Accumulation done, if asked now display the hist
     if (m_displayHist)
     {
         std::ostringstream ostr;
         ostr << "Hough Histogram " << histCount++;
         m_Canvases.emplace_back(new TCanvas(ostr.str().c_str(), ostr.str().c_str(), 1000, 1000));
         
         std::ostringstream ostr2;
         ostr2 << "Plane";
         
         m_Canvases.back()->GetFrame()->SetFillColor(46);
         m_Canvases.back()->SetFillColor(19);
         m_Canvases.back()->SetBorderMode(19);
         m_Canvases.back()->cd(1);
         
         double zmin = 0.06;
         double zmax = 0.94;
         double xmin = 0.04;
         double xmax = 0.95;
         TPad* p = new TPad(ostr2.str().c_str(), ostr2.str().c_str(), zmin, xmin, zmax, xmax);
         p->SetBit(kCanDelete);   // Give away ownership.
         p->Range(zmin, xmin, zmax, xmax);
         p->SetFillStyle(4000);   // Transparent.
         p->Draw();
         m_Pads.push_back(p);
         
         TH2D* houghHist = new TH2D("HoughHist", "Hough Space", 2*m_rhoBins, -m_rhoBins+0.5, m_rhoBins+0.5, m_thetaBins, 0., m_thetaBins);
         
         for(const auto& rhoThetaMap : rhoThetaAccumulatorBinMap)
         {
             houghHist->Fill(rhoThetaMap.first.first, rhoThetaMap.first.second+0.5, rhoThetaMap.second.getAccumulatorValues().size());
         }
         
         houghHist->SetBit(kCanDelete);
         houghHist->Draw();
         m_Canvases.back()->Update();
     }
     
     // **********************************************************************
     // Part II: Use DBScan (or a slight variation) to find clusters of bins
     // **********************************************************************
     
     size_t thresholdLo = std::max(size_t(m_hiThresholdFrac*nAccepted3DHits), m_hiThresholdMin);
     size_t thresholdHi = m_loThresholdFrac * maxBinCount;
     
     std::list<RhoThetaAccumulatorBinMap::iterator> binIndexList;
     
     for(RhoThetaAccumulatorBinMap::iterator mapItr  = rhoThetaAccumulatorBinMap.begin();
         mapItr != rhoThetaAccumulatorBinMap.end();
         mapItr++)
         binIndexList.push_back(mapItr);
     
     binIndexList.sort(SortBinIndexList());
     
     for(auto& mapItr : binIndexList)
     {
         // If we have been here before we skip
         //if (mapItr.second.isVisited()) continue;
         if (mapItr->second.isInCluster()) continue;
         
         // Mark this bin as visited
         // Actually, don't mark it since we are double thresholding and don't want it missed
         //mapItr.second.setVisited();
         
         // Make sure over threshold
         if (mapItr->second.getAccumulatorValues().size() < thresholdLo)
         {
             mapItr->second.setNoise();
             continue;
         }
         
         // Set the low threshold to make sure we merge bins that might be either side of a boundary trajectory
         thresholdHi = std::max(size_t(m_loThresholdFrac * mapItr->second.getAccumulatorValues().size()), m_hiThresholdMin);
         
         // Recover our neighborhood
         HoughCluster neighborhood;
         BinIndex     curBin(mapItr->first);
         
         HoughRegionQuery(curBin, rhoThetaAccumulatorBinMap, neighborhood, thresholdHi);
         
         houghClusters.push_back(HoughCluster());
         
         HoughCluster& houghCluster = houghClusters.back();
         
         expandHoughCluster(curBin, neighborhood, houghCluster, rhoThetaAccumulatorBinMap, thresholdHi);
     }
     
     // Sort the clusters using the SortHoughClusterList metric
     if (!houghClusters.empty()) houghClusters.sort(SortHoughClusterList(rhoThetaAccumulatorBinMap));
     
     return;
 }

bool lar_cluster3d::HoughSeedFinderAlg::findTrackHits	(	reco::HitPairListPtr &	hitPairListPtr,
		reco::PrincipalComponents &	inputPCA,
		reco::HitPairListPtrList &	hitPairListPtrList
	)		const

Given the list of hits this will return the sets of hits which belong on the same line.

bool lar_cluster3d::HoughSeedFinderAlg::findTrackHits	(	reco::HitPairListPtr &	hitPairListPtr,
		reco::PrincipalComponents &	inputPCA,
		reco::HitPairListPtrList &	hitPairListPtrList
	)		const

virtual

Given the list of hits this will return the sets of hits which belong on the same line.

Definition at line 872 of file HoughSeedFinderAlg.cxx.

 {
     // The goal of this routine is run the Hough Transform on the input set of hits
     // and then to return a list of lists of hits which are associated to a given line
     
     // Make sure we are using the right pca
     reco::HitPairListPtr hitPairListPtr = inputHitPairListPtr;
     
     int nLoops(0);
     
     // Make a local copy of the input PCA
     reco::PrincipalComponents pca = inputPCA;
     
     // We also require that there be some spread in the data, otherwise not worth running?
     double eigenVal0 = 3. * sqrt(pca.getEigenValues()[0]);
     double eigenVal1 = 3. * sqrt(pca.getEigenValues()[1]);
     
     if (eigenVal0 > 5. && eigenVal1 > 0.001)
     {
         // **********************************************************************
         // Part I: Build Hough space and find Hough clusters
         // **********************************************************************
         RhoThetaAccumulatorBinMap rhoThetaAccumulatorBinMap;
         HoughClusterList          houghClusters;
         
         findHoughClusters(hitPairListPtr, pca, nLoops, rhoThetaAccumulatorBinMap, houghClusters);
         
         // **********************************************************************
         // Part II: Go through the clusters to find the peak bins
         // **********************************************************************
         
         // We need to use a set so we can be sure to have unique hits
         reco::HitPairListPtr                clusterHitsList;
         std::set<const reco::ClusterHit3D*> masterHitPtrList;
         std::set<const reco::ClusterHit3D*> peakBinPtrList;
         
         size_t firstPeakCount(0);
         
         // Loop through the list of all clusters found above
         for(auto& houghCluster : houghClusters)
         {
             BinIndex peakBin   = houghCluster.front();
             size_t   peakCount = 0;
             size_t   totalHits = 0;
             
             // Make a local (to this cluster) set of of hits
             std::set<const reco::ClusterHit3D*> localHitPtrList;
             
             // Now loop through the bins that were attached to this cluster
             for(auto& binIndex : houghCluster)
             {
                 // An even more local list so we can keep track of peak values
                 std::set<const reco::ClusterHit3D*> tempHitPtrList;
                 
                 // Recover the hits associated to this cluster
                 for(auto& hitItr : rhoThetaAccumulatorBinMap[binIndex].getAccumulatorValues())
                 {
                     reco::HitPairListPtr::const_iterator hit3DItr = hitItr.getHitIterator();
                     
                     tempHitPtrList.insert(*hit3DItr);
                 }
                 
                 // count hits before we remove any
                 totalHits += tempHitPtrList.size();
                 
                 // Trim out any hits already used by a bigger/better cluster
                 std::set<const reco::ClusterHit3D*> tempHit3DSet;
                 
                 std::set_difference(tempHitPtrList.begin(),   tempHitPtrList.end(),
                                     masterHitPtrList.begin(), masterHitPtrList.end(),
                                     std::inserter(tempHit3DSet, tempHit3DSet.end()) );
                 
                 tempHitPtrList = tempHit3DSet;
                 
                 size_t binCount = tempHitPtrList.size();
                 
                 if (peakCount < binCount)
                 {
                     peakCount      = binCount;
                     peakBin        = binIndex;
                     peakBinPtrList = tempHitPtrList;
                 }
                 
                 // Add this to our local list
                 localHitPtrList.insert(tempHitPtrList.begin(),tempHitPtrList.end());
             }
             
             if (localHitPtrList.size() < m_minimum3DHits) continue;
             
             if (!firstPeakCount) firstPeakCount = peakCount;
             
             // If the peak counts are significantly less than the first cluster's peak then skip
             if (peakCount < firstPeakCount / 10) continue;
             
             // **********************************************************************
             // Part III: Make a list of hits from the total number associated
             // **********************************************************************
             
             hitPairListPtrList.push_back(reco::HitPairListPtr());
             
             hitPairListPtrList.back().resize(localHitPtrList.size());
             std::copy(localHitPtrList.begin(), localHitPtrList.end(), hitPairListPtrList.back().begin());
             
             // We want to remove the hits which have been used from further contention
             masterHitPtrList.insert(localHitPtrList.begin(),localHitPtrList.end());
             
             if (hitPairListPtr.size() - masterHitPtrList.size() < m_minimum3DHits) break;
         } // end loop over hough clusters
     }
     
     return true;
 }

bool lar_cluster3d::HoughSeedFinderAlg::findTrackSeeds	(	reco::HitPairListPtr &	hitPairListPtr,
		reco::PrincipalComponents &	inputPCA,
		SeedHitPairListPairVec &	seedHitPairVec
	)		const

overridevirtual

Given the list of hits this will search for candidate Seed objects and return them.

Implements lar_cluster3d::SeedFinderAlgBase.

bool lar_cluster3d::HoughSeedFinderAlg::findTrackSeeds	(	reco::HitPairListPtr &	hitPairListPtr,
		reco::PrincipalComponents &	inputPCA,
		SeedHitPairListPairVec &	seedHitPairVec
	)		const

virtual

Given the list of hits this will search for candidate Seed objects and return them.

Implements lar_cluster3d::SeedFinderAlgBase.

Definition at line 676 of file HoughSeedFinderAlg.cxx.

 {
     // This will be a busy routine... the basic tasks are:
     // 1) loop through hits and project to the plane defined by the two largest eigen values, accumulate in Hough space
     // 2) "Cluster" the Hough space to associate hits which are common to a line
     // 3) Process these clusters (still to be defined exactly)
     
     // Create an interim data structure which will allow us to sort our seeds by "best"
     // before we return them in the seedHitPairVec
     typedef std::map<size_t, SeedHitPairListPairVec > SizeToSeedToHitMap;
 
     SizeToSeedToHitMap  seedHitPairMap;
     SeedHitPairListPair seedHitPair;
     
     // Make sure we are using the right pca
     reco::HitPairListPtr hitPairListPtr = inputHitPairListPtr;
     
     int nLoops(0);
     
     // Make a local copy of the input PCA
     reco::PrincipalComponents pca = inputPCA;
     
     // We loop over hits in our list until there are no more
     while(!hitPairListPtr.empty())
     {
         // We also require that there be some spread in the data, otherwise not worth running?
         double eigenVal0 = 3. * sqrt(pca.getEigenValues()[0]);
         double eigenVal1 = 3. * sqrt(pca.getEigenValues()[1]);
         
         if (eigenVal0 > 5. && eigenVal1 > 0.001)
         {
             // **********************************************************************
             // Part I: Build Hough space and find Hough clusters
             // **********************************************************************
             RhoThetaAccumulatorBinMap rhoThetaAccumulatorBinMap;
             HoughClusterList          houghClusters;
             
             findHoughClusters(hitPairListPtr, pca, nLoops, rhoThetaAccumulatorBinMap, houghClusters);
             
             // If no clusters then done
             if (houghClusters.empty()) break;
             
             // **********************************************************************
             // Part II: Go through the clusters to find the peak bins
             // **********************************************************************
             
             // We need to use a set so we can be sure to have unique hits
             reco::HitPairListPtr                clusterHitsList;
             std::set<const reco::ClusterHit3D*> masterHitPtrList;
             std::set<const reco::ClusterHit3D*> peakBinPtrList;
             
             size_t firstPeakCount(0);
         
             // Loop through the list of all clusters found above
             for(auto& houghCluster : houghClusters)
             {
                 BinIndex peakBin   = houghCluster.front();
                 size_t   peakCount = 0;
                 size_t   totalHits = 0;
                 
                 // Make a local (to this cluster) set of of hits
                 std::set<const reco::ClusterHit3D*> localHitPtrList;
             
                 // Now loop through the bins that were attached to this cluster
                 for(auto& binIndex : houghCluster)
                 {
                     // An even more local list so we can keep track of peak values
                     std::set<const reco::ClusterHit3D*> tempHitPtrList;
                     
                     // Recover the hits associated to this cluster
                     for(auto& hitItr : rhoThetaAccumulatorBinMap[binIndex].getAccumulatorValues())
                     {
                         reco::HitPairListPtr::const_iterator hit3DItr = hitItr.getHitIterator();
                         
                         tempHitPtrList.insert(*hit3DItr);
                     }
                     
                     // count hits before we remove any
                     totalHits += tempHitPtrList.size();
                     
                     // Trim out any hits already used by a bigger/better cluster
                     std::set<const reco::ClusterHit3D*> tempHit3DSet;
                     
                     std::set_difference(tempHitPtrList.begin(),   tempHitPtrList.end(),
                                         masterHitPtrList.begin(), masterHitPtrList.end(),
                                         std::inserter(tempHit3DSet, tempHit3DSet.end()) );
                     
                     tempHitPtrList = tempHit3DSet;
                     
                     size_t binCount = tempHitPtrList.size();
                 
                     if (peakCount < binCount)
                     {
                         peakCount      = binCount;
                         peakBin        = binIndex;
                         peakBinPtrList = tempHitPtrList;
                     }
                     
                     // Add this to our local list
                     localHitPtrList.insert(tempHitPtrList.begin(),tempHitPtrList.end());
                 }
                 
                 if (localHitPtrList.size() < m_minimum3DHits) continue;
                 
                 if (!firstPeakCount) firstPeakCount = peakCount;
                 
                 // If the peak counts are significantly less than the first cluster's peak then skip
                 if (peakCount < firstPeakCount / 10) continue;
             
                 // **********************************************************************
                 // Part III: Make a Seed from the peak bin hits
                 // **********************************************************************
             
                 reco::HitPairListPtr allPeakBinHits;
             
                 for(const auto& hit3D : localHitPtrList) allPeakBinHits.push_back(hit3D);
                 
                 reco::HitPairListPtr peakBinHits;
                 
                 // Find longest "continuous" set of hits and use these for the seed
                 findHitGaps(allPeakBinHits, peakBinHits);
                 
                 if (peakBinHits.size() < m_minimum3DHits) continue;
                 
                 // We now build the actual seed.
                 if (buildSeed(peakBinHits, seedHitPair))
                 {
                     // Keep track of this in our map (which will do ordering for us)
                     seedHitPairMap[peakBinHits.size()].push_back(seedHitPair);
                 
                     // For visual testing in event display, mark all the hits in the first seed so we can see them
                     if (seedHitPairMap.size() == 1)
                     {
                         for(const auto& hit3D : peakBinHits) hit3D->setStatusBit(0x40000000);
                     }
                     
 //                    for(const auto& hit3D : seedHitPair.second) hit3D->setStatusBit(0x40000000);
                 }
                 
                 // Our peakBinHits collection will most likely be a subset of the localHitPtrList collection
                 // We want to remove only the "pure" hits which are those in the peakBinHits collection
                 // So, sort them and then add to our master list
                 peakBinHits.sort();
                 
                 masterHitPtrList.insert(peakBinHits.begin(),peakBinHits.end());
                 
                 if (hitPairListPtr.size() - masterHitPtrList.size() < m_minimum3DHits) break;
             } // end loop over hough clusters
             
             // If the masterHitPtrList is empty then nothing happened and we're done
             if (masterHitPtrList.empty()) break;
             
             // **********************************************************************
             // Part IV: Remove remaining peak bin hits from HitPairPtrList
             // **********************************************************************
 
             hitPairListPtr.sort();
             
             reco::HitPairListPtr::iterator newListEnd =
                 std::set_difference(hitPairListPtr.begin(),   hitPairListPtr.end(),
                                     masterHitPtrList.begin(), masterHitPtrList.end(),
                                     hitPairListPtr.begin() );
 
             hitPairListPtr.erase(newListEnd, hitPairListPtr.end());
             
             if (hitPairListPtr.size() < m_minimum3DHits) break;
             
             if (nLoops++ > m_maxLoopsPerCluster) break;
             
             // ********************************************************
         }
         else break; // eigen values not in range
         
         // At this point run the PCA on the remaining hits
         m_pcaAlg.PCAAnalysis_3D(hitPairListPtr, pca, true);
         
         if (!pca.getSvdOK()) break;
     }
     
     // The final task before returning is to transfer the stored seeds into the output seed vector
     // What we want to do is make sure the first seeds are the "best" seeds which is defined as the
     // seeds which were associated to the most hits by the Hough Transform. Our seed map will have
     // the reverse of this ordering so we simply iterate through it "backwards"
     for(SizeToSeedToHitMap::reverse_iterator seedMapItr = seedHitPairMap.rbegin(); seedMapItr != seedHitPairMap.rend(); seedMapItr++)
     {
         for(const auto& seedHitPair : seedMapItr->second)
         {
             seedHitPairVec.emplace_back(seedHitPair);
         }
     }
     
     return true;
 }

void lar_cluster3d::HoughSeedFinderAlg::HoughRegionQuery	(	BinIndex &	curBin,
		RhoThetaAccumulatorBinMap &	rhoThetaAccumulatorBinMap,
		HoughCluster &	neighborPts,
		size_t	threshold
	)		const

private

void lar_cluster3d::HoughSeedFinderAlg::HoughRegionQuery	(	BinIndex &	curBin,
		RhoThetaAccumulatorBinMap &	rhoThetaAccumulatorBinMap,
		HoughCluster &	neighborPts,
		size_t	threshold
	)		const

private

Does a query of nearest neighbors to look for matching bins

Definition at line 192 of file HoughSeedFinderAlg.cxx.

 {
     /**
      *   @brief Does a query of nearest neighbors to look for matching bins
      */
     
     // We simply loop over the nearest indices and see if we have any friends over threshold
     for(int rhoIdx = curBin.first - 1; rhoIdx <= curBin.first + 1; rhoIdx++)
     {
         for(int jdx = curBin.second - 1; jdx <= curBin.second + 1; jdx++)
         {
             // Skip the self reference
             if (rhoIdx == curBin.first && jdx == curBin.second) continue;
             
             // Theta bin needs to handle the wrap.
             int thetaIdx(jdx);
             
             if      (thetaIdx < 0)             thetaIdx = m_thetaBins - 1;
             else if (thetaIdx > m_thetaBins -1) thetaIdx = 0;
             
             BinIndex                            binIndex(rhoIdx,thetaIdx);
             RhoThetaAccumulatorBinMap::iterator mapItr = rhoThetaAccumulatorBinMap.find(binIndex);
             
             if (mapItr != rhoThetaAccumulatorBinMap.end())
             {
                 if (mapItr->second.getAccumulatorValues().size() >= threshold) neighborPts.push_back(binIndex);
             }
         }
     }
     
     return;
 }

void lar_cluster3d::HoughSeedFinderAlg::LineFit2DHits	(	std::set< const reco::ClusterHit2D * > &	hitList,
		double	XOrigin,
		TVector3 &	Pos,
		TVector3 &	Dir,
		double &	ChiDOF
	)		const

private

void lar_cluster3d::HoughSeedFinderAlg::LineFit2DHits	(	std::set< const reco::ClusterHit2D * > &	hitList,
		double	XOrigin,
		TVector3 &	Pos,
		TVector3 &	Dir,
		double &	ChiDOF
	)		const

private

Definition at line 989 of file HoughSeedFinderAlg.cxx.

 {
     // The following is lifted from Bruce Baller to try to get better
     // initial parameters for a candidate Seed. It is slightly reworked
     // which is why it is included here instead of used as is.
     //
     // Linear fit using X as the independent variable. Hits to be fitted
     // are passed in the hits vector in a pair form (X, WireID). The
     // fitted track position at XOrigin is returned in the Pos vector.
     // The direction cosines are returned in the Dir vector.
     //
     // SVD fit adapted from $ROOTSYS/tutorials/matrix/solveLinear.C
     // Fit equation is w = A(X)v, where w is a vector of hit wires, A is
     // a matrix to calculate a track projected to a point at X, and v is
     // a vector (Yo, Zo, dY/dX, dZ/dX).
     //
     // Note: The covariance matrix should also be returned
     // B. Baller August 2014
     
     // assume failure
     ChiDOF = -1;
     
     if(hit2DSet.size() < 4) return;
     
     const unsigned int nvars = 4;
     unsigned int       npts  = hit2DSet.size();
     
     TMatrixD A(npts, nvars);
     // vector holding the Wire number
     TVectorD w(npts);
     unsigned short ninpl[3] = {0};
     unsigned short nok = 0;
     unsigned short iht(0), cstat, tpc, ipl;
     double x, cw, sw, off;
     
     // Loop over unique 2D hits from the input list of 3D hits
     for (const auto& hit : hit2DSet)
     {
         geo::WireID wireID = hit->getHit().WireID();
     
         cstat = wireID.Cryostat;
         tpc   = wireID.TPC;
         ipl   = wireID.Plane;
     
         // get the wire plane offset
         off = m_geometry->WireCoordinate(0, 0, ipl, tpc, cstat);
     
         // get the "cosine-like" component
         cw  = m_geometry->WireCoordinate(1, 0, ipl, tpc, cstat) - off;
     
         // the "sine-like" component
         sw  = m_geometry->WireCoordinate(0, 1, ipl, tpc, cstat) - off;
     
         x = hit->getXPosition() - XOrigin;
         
         A[iht][0] = cw;
         A[iht][1] = sw;
         A[iht][2] = cw * x;
         A[iht][3] = sw * x;
         w[iht]    = wireID.Wire - off;
         
         ++ninpl[ipl];
         
         // need at least two points in a plane
         if(ninpl[ipl] == 2) ++nok;
     
         iht++;
     }
     
     // need at least 2 planes with at least two points
     if(nok < 2) return;
     
     TDecompSVD svd(A);
     bool ok;
     TVectorD tVec = svd.Solve(w, ok);
     
     ChiDOF = 0;
     
     // not enough points to calculate Chisq
     if(npts <= 4) return;
     
     double ypr, zpr, diff;
     
     for (const auto& hit : hit2DSet)
     {
         geo::WireID wireID = hit->getHit().WireID();
         
         cstat = wireID.Cryostat;
         tpc   = wireID.TPC;
         ipl   = wireID.Plane;
         off   = m_geometry->WireCoordinate(0, 0, ipl, tpc, cstat);
         cw    = m_geometry->WireCoordinate(1, 0, ipl, tpc, cstat) - off;
         sw    = m_geometry->WireCoordinate(0, 1, ipl, tpc, cstat) - off;
         x     = hit->getXPosition() - XOrigin;
         ypr   = tVec[0] + tVec[2] * x;
         zpr   = tVec[1] + tVec[3] * x;
         diff  = ypr * cw + zpr * sw - (wireID.Wire - off);
         ChiDOF += diff * diff;
     }
 
     
     float werr2 = m_geometry->WirePitch() * m_geometry->WirePitch();
     ChiDOF /= werr2;
     ChiDOF /= (float)(npts - 4);
     
     double norm = sqrt(1 + tVec[2] * tVec[2] + tVec[3] * tVec[3]);
     Dir[0] = 1 / norm;
     Dir[1] = tVec[2] / norm;
     Dir[2] = tVec[3] / norm;
     
     Pos[0] = XOrigin;
     Pos[1] = tVec[0];
     Pos[2] = tVec[1];
     
 } // TrkLineFit()

void lar_cluster3d::HoughSeedFinderAlg::reconfigure ( fhicl::ParameterSet const & pset )

virtual

a handler for the case where the algorithm control parameters are to be reset

Implements lar_cluster3d::SeedFinderAlgBase.

Definition at line 78 of file HoughSeedFinderAlg.cxx.

 {
     m_minimum3DHits      = pset.get<size_t>("Minimum3DHits",           5);
     m_thetaBins          = pset.get<int>   ("ThetaBins",             360);
     m_rhoBins            = pset.get<int>   ("HalfRhoBins",            75);
     m_hiThresholdMin     = pset.get<size_t>("HiThresholdMin",          5);
     m_hiThresholdFrac    = pset.get<double>("HiThresholdFrac",      0.05);
     m_loThresholdFrac    = pset.get<double>("LoThresholdFrac",      0.85);
     m_numSeed2DHits      = pset.get<size_t>("NumSeed2DHits",          80);
     m_numAveDocas        = pset.get<double>("NumAveDocas",            6.);
     m_numSkippedHits     = pset.get<int>   ("NumSkippedHits",         10);
     m_maxLoopsPerCluster = pset.get<int>("MaxLoopsPerCluster",         3);
     m_maximumGap         = pset.get<double>("MaximumGap",             5.);
     m_displayHist        = pset.get<bool>  ("DisplayHoughHist",    false);
     
     m_pcaAlg.reconfigure(pset.get<fhicl::ParameterSet>("PrincipalComponentsAlg"));
 }

Member Data Documentation

std::vector< std::unique_ptr< TCanvas > > lar_cluster3d::HoughSeedFinderAlg::m_Canvases

mutableprivate

Graphical trace canvases.

Definition at line 130 of file HoughSeedFinderAlg.h.

bool lar_cluster3d::HoughSeedFinderAlg::m_displayHist

private

Definition at line 129 of file HoughSeedFinderAlg.h.

geo::Geometry const* lar_cluster3d::HoughSeedFinderAlg::m_geometry

private

Definition at line 122 of file HoughSeedFinderAlg.h.

geo::Geometry* lar_cluster3d::HoughSeedFinderAlg::m_geometry

private

Definition at line 124 of file HoughSeedFinderAlg.h.

double lar_cluster3d::HoughSeedFinderAlg::m_hiThresholdFrac

private

Definition at line 116 of file HoughSeedFinderAlg.h.

size_t lar_cluster3d::HoughSeedFinderAlg::m_hiThresholdMin

private

Definition at line 115 of file HoughSeedFinderAlg.h.

double lar_cluster3d::HoughSeedFinderAlg::m_loThresholdFrac

private

Definition at line 117 of file HoughSeedFinderAlg.h.

double lar_cluster3d::HoughSeedFinderAlg::m_maximumGap

private

Definition at line 122 of file HoughSeedFinderAlg.h.

int lar_cluster3d::HoughSeedFinderAlg::m_maxLoopsPerCluster

private

Definition at line 121 of file HoughSeedFinderAlg.h.

size_t lar_cluster3d::HoughSeedFinderAlg::m_minimum3DHits

private

Definition at line 112 of file HoughSeedFinderAlg.h.

double lar_cluster3d::HoughSeedFinderAlg::m_numAveDocas

private

Definition at line 119 of file HoughSeedFinderAlg.h.

size_t lar_cluster3d::HoughSeedFinderAlg::m_numSeed2DHits

private

Definition at line 118 of file HoughSeedFinderAlg.h.

int lar_cluster3d::HoughSeedFinderAlg::m_numSkippedHits

private

Definition at line 120 of file HoughSeedFinderAlg.h.

std::vector< TVirtualPad * > lar_cluster3d::HoughSeedFinderAlg::m_Pads

mutableprivate

View pads in current canvas.

Definition at line 131 of file HoughSeedFinderAlg.h.

PrincipalComponentsAlg lar_cluster3d::HoughSeedFinderAlg::m_pcaAlg

private

Definition at line 127 of file HoughSeedFinderAlg.h.

int lar_cluster3d::HoughSeedFinderAlg::m_rhoBins

private

Definition at line 114 of file HoughSeedFinderAlg.h.

int lar_cluster3d::HoughSeedFinderAlg::m_thetaBins

private

Definition at line 113 of file HoughSeedFinderAlg.h.

The documentation for this class was generated from the following files:

dunereco/dunereco/RecoAlgDUNE/Cluster3DAlgs/HoughSeedFinderAlg.h
dunereco/dunereco/RecoAlgDUNE/Cluster3DAlgs/HoughSeedFinderAlg.cxx

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