lar_cluster3d::ClusterMergeAlg Class Reference

Inheritance diagram for lar_cluster3d::ClusterMergeAlg:

Public Member Functions
	ClusterMergeAlg (const fhicl::ParameterSet &)
	Constructor. More...
	~ClusterMergeAlg ()
	Destructor. More...
void	configure (fhicl::ParameterSet const &pset) override
void	initializeHistograms (art::TFileDirectory &) override
	Interface for initializing histograms if they are desired Note that the idea is to put hisgtograms in a subfolder. More...
void	ModifyClusters (reco::ClusterParametersList &) const override
	Scan an input collection of clusters and modify those according to the specific implementing algorithm. More...
float	getTimeToExecute () const override
	If monitoring, recover the time to execute a particular function. More...
virtual void	configure (const fhicl::ParameterSet &)=0
	Interface for configuring the particular algorithm tool. More...

Private Member Functions
bool	consistentClusters (const reco::PrincipalComponents &, const reco::PrincipalComponents &) const
bool	mergeClusters (reco::ClusterParameters &, reco::ClusterParameters &) const
float	closestApproach (const TVector3 &, const TVector3 &, const TVector3 &, const TVector3 &, TVector3 &, TVector3 &) const

Private Attributes
bool	m_enableMonitoring
	Data members to follow. More...
double	m_minCosAxisAng
	minimum Cos(angle) cut value More...
double	m_minEigenToProcess
	Don't look anymore at clusters below this size. More...
float	m_timeToProcess
geo::Geometry *	m_geometry
PrincipalComponentsAlg	m_pcaAlg

Detailed Description

Definition at line 38 of file ClusterMergeAlg_tool.cc.

Constructor & Destructor Documentation

lar_cluster3d::ClusterMergeAlg::ClusterMergeAlg ( const fhicl::ParameterSet &  )

explicit

Constructor.

Parameters

pset

lar_cluster3d::ClusterMergeAlg::~ClusterMergeAlg

(

)

Destructor.

Definition at line 105 of file ClusterMergeAlg_tool.cc.

{
}

Member Function Documentation

float lar_cluster3d::ClusterMergeAlg::closestApproach ( const TVector3 &  P0, const TVector3 &  u0, const TVector3 &  P1, const TVector3 &  u1, TVector3 &  poca0, TVector3 &  poca1  ) const

private

Definition at line 438 of file ClusterMergeAlg_tool.cc.

References d, DEFINE_ART_CLASS_TOOL, den, and e.

Referenced by consistentClusters(), and getTimeToExecute().

{
    // Technique is to compute the arclength to each point of closest approach
    TVector3 w0 = P0 - P1;
    float a(1.);
    float b(u0.Dot(u1));
    float c(1.);
    float d(u0.Dot(w0));
    float e(u1.Dot(w0));
    float den(a * c - b * b);
    
    float arcLen0 = (b * e - c * d) / den;
    float arcLen1 = (a * e - b * d) / den;
    
    poca0 = P0 + arcLen0 * u0;
    poca1 = P1 + arcLen1 * u1;
    
    return (poca0 - poca1).Mag();
}

virtual void lar_cluster3d::IClusterModAlg::configure ( const fhicl::ParameterSet &  )

pure virtualinherited

Interface for configuring the particular algorithm tool.

Parameters

ParameterSet

The input set of parameters for configuration

void lar_cluster3d::ClusterMergeAlg::configure ( fhicl::ParameterSet const &  pset )

override

Definition at line 111 of file ClusterMergeAlg_tool.cc.

References fhicl::ParameterSet::get(), m_enableMonitoring, m_geometry, m_minCosAxisAng, m_minEigenToProcess, and m_timeToProcess.

{
    m_enableMonitoring  = pset.get<bool>  ("EnableMonitoring",  true  );
    m_minCosAxisAng     = pset.get<double>("MinCosAxisAng",     0.975 );
    m_minEigenToProcess = pset.get<double>("MinEigenToProcess", 2.0   );
    
    art::ServiceHandle<geo::Geometry> geometry;
    
    m_geometry = &*geometry;
    
    m_timeToProcess = 0.;
    
    return;
}

bool lar_cluster3d::ClusterMergeAlg::consistentClusters ( const reco::PrincipalComponents &  firstPCA, const reco::PrincipalComponents &  nextPCA  ) const

private

Definition at line 204 of file ClusterMergeAlg_tool.cc.

References closestApproach(), reco::PrincipalComponents::getAvePosition(), reco::PrincipalComponents::getEigenValues(), reco::PrincipalComponents::getEigenVectors(), and max.

Referenced by getTimeToExecute(), and ModifyClusters().

{
    // Assume failure
    bool consistent(false);
    
    // Two types of conditions to decide between to start:
    // 1) the cluster to merge lies along the trajectory of the primary cluster, in which case merge it
    //    - note that this should take care of relatively colinear trajectories
    // 2) the trajectories of the two clusters are consistent
    //    - their doca is small
    //    - the vectors to their centers are not inconsistent with the trajectory of the first,
    //    - etc.
    //
    // Initial set up to check if the merge candidate is within the trajectory of the primary cluster
    
    // Recover the positions of the centers of the two clusters
    TVector3 firstCenter(firstPCA.getAvePosition()[0],firstPCA.getAvePosition()[1],firstPCA.getAvePosition()[2]);
    TVector3 nextCenter(nextPCA.getAvePosition()[0],nextPCA.getAvePosition()[1],nextPCA.getAvePosition()[2]);
    
    // And form a vector between the two centers
    TVector3 firstPosToNextPos = nextCenter - firstCenter;
    
    // Now get the first PCA's primary axis and since we'll use them get all of them at once...
    TVector3 firstAxis0(firstPCA.getEigenVectors()[0][0],firstPCA.getEigenVectors()[0][1],firstPCA.getEigenVectors()[0][2]);
    TVector3 firstAxis1(firstPCA.getEigenVectors()[1][0],firstPCA.getEigenVectors()[1][1],firstPCA.getEigenVectors()[1][2]);
    TVector3 firstAxis2(firstPCA.getEigenVectors()[2][0],firstPCA.getEigenVectors()[2][1],firstPCA.getEigenVectors()[2][2]);
    
    // Adopt the convention that the cluster axis is in same direction as vector from first to next centers
    if (firstPosToNextPos.Dot(firstAxis0) < 0.) firstAxis0 = -firstAxis0;

    // Want the distance of closest approach of the next cluser's center to the primary, start by finding arc length
    double arcLenToNextDoca = firstPosToNextPos.Dot(firstAxis0);
    
    // Position on the first cluster's axis of doca to next center
    TVector3 firstAxisDocaPos = firstCenter + arcLenToNextDoca * firstAxis0;
    
    // Doca vector
    TVector3 nextDocaVec = nextCenter - firstAxisDocaPos;
    
    // Need the projection of the doca vector onto the two transverse axes of the first cluster
    double docaVecProj1 = std::fabs(firstAxis1.Dot(nextDocaVec));
    double docaVecProj2 = std::fabs(firstAxis2.Dot(nextDocaVec));
    
    // We will now compare these to the eigen values of the first cluster, so recover all of them
    TVector3 firstEigenVals(3. * sqrt(firstPCA.getEigenValues()[0]),
                            3. * sqrt(firstPCA.getEigenValues()[1]),
                            3. * sqrt(firstPCA.getEigenValues()[2]));
    
    // Use the angle between the vector between cluster centers and the first axis to moderate the selection cut
    double firstToNextDist  = firstPosToNextPos.Mag();
    double cosAngFTNtoAxis0 = arcLenToNextDoca / firstToNextDist;
    double docaVecProj1Cut  = std::max( 1., (1. + 2. * cosAngFTNtoAxis0) * firstEigenVals[1]);
    double docaVecProj2Cut  = std::max(0.5, (1. + 2. * cosAngFTNtoAxis0) * firstEigenVals[2]);
    
//    std::cout << "   ==> Check in tube, doca: " << nextDocaVec.Mag() << ", proj: " << docaVecProj1 << "/" << docaVecProj2 << ", cut: " << docaVecProj1Cut << "/" << docaVecProj2Cut << ", eigen: " << firstEigenVals[0] << "/" << firstEigenVals[1] << "/" << firstEigenVals[2] << ", arcLenToNextDoca: " << arcLenToNextDoca << ", cos(ang): " << cosAngFTNtoAxis0 << std::endl;

    // Ok, the first selection is that the cluster to merge lies within an (elliptical) tube of the first cluster's axis
    if (docaVecProj1 < docaVecProj1Cut && docaVecProj2 < docaVecProj2Cut) consistent = true;
    
    // Otherwise we need to decide if the two clusters are consistent because they are "similar"...
    else
    {
        // Set up to find the distance of closeset approach of the two primary axes.
        // Results vectors
        TVector3 firstPoca;
        TVector3 nextPoca;
        
        // Get the primary axis for the next point
        TVector3 nextAxis0(nextPCA.getEigenVectors()[0][0],nextPCA.getEigenVectors()[0][1],nextPCA.getEigenVectors()[0][2]);
        
        // Convention on axis direction applied again
        if (firstPosToNextPos.Dot(nextAxis0) < 0.) nextAxis0 = -nextAxis0;
        
        // Recover the doca of the two axes and their points of closest approach
        float lineDoca = closestApproach(firstCenter, firstAxis0, nextCenter, nextAxis0, firstPoca, nextPoca);
        
        // Determine the arc lengths to the two pocas
        double arcLenToFirstPoca = (firstPoca - firstCenter).Dot(firstAxis0);  // is this faster than "Mag"?
        double arcLenToNextPoca  = (nextPoca  - nextCenter ).Dot(nextAxis0);
        
 //       std::cout << "       - arcLenToFirstPoca: " << arcLenToFirstPoca << ", arcLenToNextPoca: " << arcLenToNextPoca << ", first/Next dist: " << firstToNextDist << std::endl;
        
        // Require both of these to be less than length from first to next and to have the "right" sign where for the arc length
        // to the first axis poca this will be positive and for the next poca it will be negative
        // This prevents really long clusters that are not consistent from getting attached at their end points
        if (arcLenToFirstPoca >= 0. && arcLenToFirstPoca < firstToNextDist && arcLenToNextPoca <= 0. && arcLenToNextPoca > -firstToNextDist)
        {
            // Don't let clusters that are really far apart get joined together and really try to suppress clusters which
            // are not colinear but which have a small doca
            double nextEigenVal0     = std::max(1.,3. * sqrt(nextPCA.getEigenValues()[0]));
            double nextArcLenCut     = (1. + 5. * cosAngFTNtoAxis0) * nextEigenVal0;
            
//            std::cout << "       - linedoca: " << lineDoca << ", cosAngFTNtoAxis0: " << cosAngFTNtoAxis0 << ", nextEigenVal0: " << nextEigenVal0 << ", nextArcLenCut: " << nextArcLenCut << std::endl;
            
            // Check the actual doca with a simple cut on the first eigen value, make sure "in range"
            if (lineDoca < firstEigenVals[1] && -arcLenToNextPoca < nextArcLenCut) consistent = true;
        }
    }
    
    return consistent;
    
    // hide all of this down here for now
/*
    // We need the next cluster's principal eigenvalue
    double nextEigenVal0 = 3. * std::sqrt(nextPCA.getEigenValues()[0]);
    
    // Now get position of endpoint of next cluster
    TVector3 nextEndPoint = nextCenter - nextEigenVal0 * nextAxis0;
    
    // Ok, now reset the firstPosToNextPos vector
    firstPosToNextPos = nextEndPoint - firstCenter;
    
    // Get the arclength to the point on the first axis which is the poca to the next point
    double arcLenToNextDoca = firstPosToNextPos.Dot(firstAxis0);
    
    // And recover that point
    TVector3 firstAxisPoca = firstCenter + arcLenToNextDoca * firstAxis0;
    
    // And then the vector for poca
    TVector3 nextToFirstDocaVec = nextEndPoint - firstAxisPoca;
    
    // Projections of the doca vec on the first and second eigen axes
    double docaVecProjMajor = std::fabs(nextToFirstDocaVec.Dot(firstAxis1));
    double docaVecProjMinor = std::fabs(nextToFirstDocaVec.Dot(firstAxis2));
    
    // Get the eigen values
    
    // Get the ratio of the first eigen value to the arc length
    double scaleFactor   = std::max(3.,arcLenToNextDoca / firstEigenVals[0]);
    double cutValueMajor = scaleFactor * firstEigenVals[1];
    double cutValueMinor = scaleFactor * firstEigenVals[2];
    
    
    // Ok, the first selection is that the doca of the next point to the first PCA primary axis is within
    // the allowed maximum spread
    if (docaVecProjMajor < cutValueMajor && docaVecProjMinor < cutValueMinor)
    {
        
        // Effectively the same cut as above but now with the point of closest approach
        float arcLenToPoca0 = (firstPoca - firstCenter).Dot(firstAxis0);
        float docaCutValue  = arcLenToPoca0 * firstEigenVals[1] / firstEigenVals[0];
        
        std::cout << "   --> arcLenToPoca0: " << arcLenToPoca0 << ", firstToNext: " << firstPosToNextPos.Mag() << ", docaCutValue: " << docaCutValue << ", lineDoca: " << lineDoca << std::endl;
        
        // Require that the doca of the two lines be within range
        if (lineDoca < 3. * docaCutValue)
        {
            // Final check, look at arc lengths to pocas
            double arcLenToPocaFirst     = (firstPoca - firstCenter).Dot(firstAxis0);
            double arcLenToPocaNext      = (nextPoca  - nextEndPoint).Dot(nextAxis0);
            double firstPosToNextPosDist = firstPosToNextPos.Mag();
            double totalArcLen           = arcLenToPocaFirst - arcLenToPocaNext;  // arcLenToPocaNext should be negative
            
            std::cout << "   >>> arcLenToPocaFirst: " << arcLenToPocaFirst << ", arcLenToPocaNext: " << arcLenToPocaNext << ", totalArcLen: " << totalArcLen << ", 2nd cut: " << firstPosToNextPos.Mag() / m_minCosAxisAng << std::endl;
            
            // It can be that that the lines are nearly parallel so the poca can be past the center of the two clusters
            // If that is the case then it should be that a simple angle check is sufficient
            if (arcLenToPocaFirst > firstPosToNextPosDist || arcLenToPocaNext > firstPosToNextPosDist)
            {
                if (firstPosToNextPos.Unit().Dot(firstAxis0) > m_minCosAxisAng) consistent = true;
            }
            // Otherwise the poca's are both "between" the cluster centers so require the sum of arc lengths to be within range
            else if (2. * totalArcLen >firstPosToNextPos.Mag() && totalArcLen < firstPosToNextPos.Mag() / m_minCosAxisAng) consistent = true;
        }
    }
*/
}

float lar_cluster3d::ClusterMergeAlg::getTimeToExecute ( ) const

inlineoverridevirtual

If monitoring, recover the time to execute a particular function.

Implements lar_cluster3d::IClusterModAlg.

Definition at line 74 of file ClusterMergeAlg_tool.cc.

References closestApproach(), consistentClusters(), m_timeToProcess, and mergeClusters().

{return m_timeToProcess;}

void lar_cluster3d::ClusterMergeAlg::initializeHistograms ( art::TFileDirectory &  )

overridevirtual

Interface for initializing histograms if they are desired Note that the idea is to put hisgtograms in a subfolder.

Parameters

TFileDirectory

- the folder to store the hists in

Implements lar_cluster3d::IClusterModAlg.

Definition at line 126 of file ClusterMergeAlg_tool.cc.

{
    return;
}

bool lar_cluster3d::ClusterMergeAlg::mergeClusters ( reco::ClusterParameters &  firstClusterParams, reco::ClusterParameters &  nextClusterParams  ) const

private

Definition at line 372 of file ClusterMergeAlg_tool.cc.

References reco::PrincipalComponents::getAvePosition(), reco::PrincipalComponents::getEigenValues(), reco::PrincipalComponents::getEigenVectors(), reco::ClusterParameters::getFullPCA(), reco::ClusterParameters::getHit3DToEdgeMap(), reco::ClusterParameters::getHitPairListPtr(), reco::ClusterParameters::getSkeletonPCA(), reco::PrincipalComponents::getSvdOK(), m_pcaAlg, lar_cluster3d::PrincipalComponentsAlg::PCAAnalysis_3D(), and reco::ClusterParameters::UpdateParameters().

Referenced by getTimeToExecute(), and ModifyClusters().

{
    bool merged(false);
    
    // Merge the next cluster into the first one
    // Do this by making a local copy of the input cluster parameters
    reco::ClusterParameters clusterParams = firstClusterParams;
    
    // Get the hits
    reco::HitPairListPtr& hitPairListPtr = clusterParams.getHitPairListPtr();
    
    for(const auto* hit : nextClusterParams.getHitPairListPtr())
    {
        hitPairListPtr.push_back(hit);
        
        for(const auto* hit2D : hit->getHits())
            if (hit2D) clusterParams.UpdateParameters(hit2D);
    }
    
    
    TVector3 origCenter(clusterParams.getFullPCA().getAvePosition()[0],clusterParams.getFullPCA().getAvePosition()[1],clusterParams.getFullPCA().getAvePosition()[2]);
    TVector3 origAxis0(clusterParams.getFullPCA().getEigenVectors()[0][0],clusterParams.getFullPCA().getEigenVectors()[0][1],clusterParams.getFullPCA().getEigenVectors()[0][2]);
    TVector3 origEigen(clusterParams.getFullPCA().getEigenValues()[0],clusterParams.getFullPCA().getEigenValues()[1],clusterParams.getFullPCA().getEigenValues()[2]);

//    std::cout << "      **>> orig center: " << origCenter[0] << "/" << origCenter[1] << "/" << origCenter[2] << std::endl;
//    std::cout << "           orig vector: " << origAxis0[0] << "/" << origAxis0[1] << "/" << origAxis0[2] << std::endl;
//    std::cout << "           orig eigen:  " << origEigen[0] << "/" << origEigen[1] << "/" << origEigen[2] << std::endl;

    
    // Recalculate the PCA
    m_pcaAlg.PCAAnalysis_3D(clusterParams.getHitPairListPtr(), clusterParams.getFullPCA());
    
    
    TVector3 newCenter(clusterParams.getFullPCA().getAvePosition()[0],clusterParams.getFullPCA().getAvePosition()[1],clusterParams.getFullPCA().getAvePosition()[2]);
    TVector3 newAxis0(clusterParams.getFullPCA().getEigenVectors()[0][0],clusterParams.getFullPCA().getEigenVectors()[0][1],clusterParams.getFullPCA().getEigenVectors()[0][2]);
    TVector3 newEigen(clusterParams.getFullPCA().getEigenValues()[0],clusterParams.getFullPCA().getEigenValues()[1],clusterParams.getFullPCA().getEigenValues()[2]);
    
//    std::cout << "      >>>> new center:  " << newCenter[0] << "/" << newCenter[1] << "/" << newCenter[2] << std::endl;
//    std::cout << "           new vector:  " << newAxis0[0] << "/" << newAxis0[1] << "/" << newAxis0[2] << std::endl;
//    std::cout << "           new eigen:   " << newEigen[0] << "/" << newEigen[1] << "/" << newEigen[2] << ", cos orig to new: " << origAxis0.Dot(newAxis0) << std::endl;
    

//    if (newEigen[0] > 0.8 * origEigen[0] && newEigen[1] * origEigen[0] < 5. * newEigen[0] * origEigen[1])
    {
        // Must have a valid pca
        if (clusterParams.getFullPCA().getSvdOK())
        {
            // Finish out the merging here
            reco::Hit3DToEdgeMap& firstEdgeMap = clusterParams.getHit3DToEdgeMap();
            reco::Hit3DToEdgeMap& nextEdgeMap  = nextClusterParams.getHit3DToEdgeMap();
            
            for(const auto& pair : nextEdgeMap) firstEdgeMap[pair.first] = pair.second;
            
            // Set the skeleton PCA to make sure it has some value
            clusterParams.getSkeletonPCA() = clusterParams.getFullPCA();
            
            // Copy back to the input
            firstClusterParams = clusterParams;
            
            merged = true;
        }
    }
    
    return merged;
}

void lar_cluster3d::ClusterMergeAlg::ModifyClusters ( reco::ClusterParametersList &  clusterParametersList ) const

overridevirtual

Scan an input collection of clusters and modify those according to the specific implementing algorithm.

Parameters

clusterParametersList

A list of cluster objects (parameters from associated hits)

Top level interface for algorithm to consider pairs of clusters from the input list and determine if they are consistent with each other and, therefore, should be merged. This is done by looking at the PCA for each cluster and looking at the projection of the primary axis along the vector connecting their centers.

Implements lar_cluster3d::IClusterModAlg.

Definition at line 131 of file ClusterMergeAlg_tool.cc.

References consistentClusters(), reco::PrincipalComponents::getEigenValues(), reco::ClusterParameters::getFullPCA(), art::left(), m_enableMonitoring, m_minEigenToProcess, m_timeToProcess, mergeClusters(), and art::right().

{
    // Initial clustering is done, now trim the list and get output parameters
    cet::cpu_timer theClockBuildClusters;
    
    // Start clocks if requested
    if (m_enableMonitoring) theClockBuildClusters.start();
    
    // Resort by the largest first eigen value (so the "longest" cluster)
    clusterParametersList.sort([](auto& left, auto& right){return left.getFullPCA().getEigenValues()[0] > right.getFullPCA().getEigenValues()[0];});
    
    reco::ClusterParametersList::iterator firstClusterItr = clusterParametersList.begin();
    
//    int clusCntr(0);
    
    while(firstClusterItr != clusterParametersList.end())
    {
        reco::ClusterParameters&              firstClusterParams = *firstClusterItr;
        reco::ClusterParametersList::iterator nextClusterItr     = firstClusterItr;
        
        // Once you get down to the smallest clusters if they haven't already been absorbed there is no need to check them
        if (firstClusterParams.getFullPCA().getEigenValues()[0] < m_minEigenToProcess) break;
        
//        std::cout << "+++++++++++++++++++++++++++++++ Checking PCA for cluster # " << clusCntr++ << " +++++++++++++++++++++++++++" << std::endl;
//        std::cout << "+++++++ eigen values: " << firstClusterParams.getFullPCA().getEigenValues()[0] << "/" << firstClusterParams.getFullPCA().getEigenValues()[1] << "/" << firstClusterParams.getFullPCA().getEigenValues()[2] << " +++++++++" << std::endl;
        
        // want the next one...
        nextClusterItr++;
    
        while(nextClusterItr != clusterParametersList.end())
        {
            reco::ClusterParameters& nextClusterParams = *nextClusterItr;
            
            // On any given loop through here it **might** be that the first cluster has been modified. So can't cache
            // the parameters, need the curret ones
            if (consistentClusters(firstClusterParams.getFullPCA(),nextClusterParams.getFullPCA()))
            {
                if (mergeClusters(firstClusterParams, nextClusterParams))
                {
                    // Now remove the "next" cluster
                    nextClusterItr = clusterParametersList.erase(nextClusterItr);
                
                    // Restart loop?
                    nextClusterItr = firstClusterItr;
                }
            }
            
            nextClusterItr++;
        }
        
        firstClusterItr++;
    }
    
    
    if (m_enableMonitoring)
    {
        theClockBuildClusters.stop();
        
        m_timeToProcess = theClockBuildClusters.accumulated_real_time();
    }
    
    mf::LogDebug("Cluster3D") << ">>>>> Merge clusters done, found " << clusterParametersList.size() << " clusters" << std::endl;
    
    return;
}

Member Data Documentation

bool lar_cluster3d::ClusterMergeAlg::m_enableMonitoring

private

Data members to follow.

Definition at line 87 of file ClusterMergeAlg_tool.cc.

Referenced by configure(), and ModifyClusters().

geo::Geometry* lar_cluster3d::ClusterMergeAlg::m_geometry

private

Definition at line 92 of file ClusterMergeAlg_tool.cc.

Referenced by configure().

double lar_cluster3d::ClusterMergeAlg::m_minCosAxisAng

private

minimum Cos(angle) cut value

Definition at line 88 of file ClusterMergeAlg_tool.cc.

Referenced by configure().

double lar_cluster3d::ClusterMergeAlg::m_minEigenToProcess

private

Don't look anymore at clusters below this size.

Definition at line 89 of file ClusterMergeAlg_tool.cc.

Referenced by configure(), and ModifyClusters().

PrincipalComponentsAlg lar_cluster3d::ClusterMergeAlg::m_pcaAlg

private

Definition at line 94 of file ClusterMergeAlg_tool.cc.

Referenced by mergeClusters().

float lar_cluster3d::ClusterMergeAlg::m_timeToProcess

mutableprivate

Definition at line 90 of file ClusterMergeAlg_tool.cc.

Referenced by configure(), getTimeToExecute(), and ModifyClusters().

---

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

• /cvmfs/larsoft.opensciencegrid.org/products/larreco/v07_10_02/source/larreco/RecoAlg/Cluster3DAlgs/ClusterMergeAlg_tool.cc