lar_cluster3d::MinSpanTreeAlg Class Reference

Inheritance diagram for lar_cluster3d::MinSpanTreeAlg:

Public Member Functions
	MinSpanTreeAlg (const fhicl::ParameterSet &)
	Constructor. More...
	~MinSpanTreeAlg ()
	Destructor. More...
void	configure (fhicl::ParameterSet const &pset) override
void	Cluster3DHits (reco::HitPairList &hitPairList, reco::ClusterParametersList &clusterParametersList) const override
	Given a set of recob hits, run DBscan to form 3D clusters. More...
void	Cluster3DHits (reco::HitPairListPtr &hitPairList, reco::ClusterParametersList &clusterParametersList) const override
	Given a set of recob hits, run DBscan to form 3D clusters. More...
float	getTimeToExecute (TimeValues index) const override
	If monitoring, recover the time to execute a particular function. More...
Public Member Functions inherited from lar_cluster3d::IClusterAlg
virtual	~IClusterAlg () noexcept=default
	Virtual Destructor. More...
virtual void	configure (const fhicl::ParameterSet &)=0
	Interface for configuring the particular algorithm tool. More...

Private Types
using	BestNodeTuple = std::tuple< const reco::ClusterHit3D *, float, float >
using	BestNodeMap = std::unordered_map< const reco::ClusterHit3D *, BestNodeTuple >
using	ChannelStatusVec = std::vector< size_t >
	define data structure for keeping track of channel status More...
using	ChannelStatusByPlaneVec = std::vector< ChannelStatusVec >

Private Member Functions
void	RunPrimsAlgorithm (reco::HitPairList &, kdTree::KdTreeNode &, reco::ClusterParametersList &) const
	Driver for Prim's algorithm. More...
void	PruneAmbiguousHits (reco::ClusterParameters &, reco::Hit2DToClusterMap &) const
	Prune the obvious ambiguous hits. More...
void	FindBestPathInCluster (reco::ClusterParameters &) const
	Algorithm to find the best path through the given cluster. More...
reco::HitPairListPtr	DepthFirstSearch (const reco::EdgeTuple &, const reco::Hit3DToEdgeMap &, float &) const
	a depth first search to find longest branches More...
void	FindBestPathInCluster (reco::ClusterParameters &, kdTree::KdTreeNode &) const
	Alternative version of FindBestPathInCluster utilizing an A* algorithm. More...
void	AStar (const reco::ClusterHit3D *, const reco::ClusterHit3D *, float alpha, kdTree::KdTreeNode &, reco::ClusterParameters &) const
	Algorithm to find shortest path between two 3D hits. More...
void	ReconstructBestPath (const reco::ClusterHit3D *, BestNodeMap &, reco::HitPairListPtr &, reco::EdgeList &) const
float	DistanceBetweenNodes (const reco::ClusterHit3D *, const reco::ClusterHit3D *) const
void	LeastCostPath (const reco::EdgeTuple &, const reco::ClusterHit3D *, reco::ClusterParameters &, float &) const
	Find the lowest cost path between two nodes using MST edges. More...
void	CheckHitSorting (reco::ClusterParameters &clusterParams) const

Private Attributes
bool	m_enableMonitoring
	Data members to follow. More...
std::vector< float >	m_timeVector
std::vector< std::vector< float > >	m_wireDir
geo::Geometry const *	m_geometry
PrincipalComponentsAlg	m_pcaAlg
kdTree	m_kdTree
std::unique_ptr< lar_cluster3d::IClusterParametersBuilder >	m_clusterBuilder
	Common cluster builder tool. More...

Additional Inherited Members
Public Types inherited from lar_cluster3d::IClusterAlg
enum	TimeValues {   BUILDTHREEDHITS = 0, BUILDHITTOHITMAP = 1, RUNDBSCAN = 2, BUILDCLUSTERINFO = 3,   PATHFINDING = 4, NUMTIMEVALUES }
	enumerate the possible values for time checking if monitoring timing More...

Detailed Description

Definition at line 43 of file MinSpanTreeAlg_tool.cc.

Member Typedef Documentation

using lar_cluster3d::MinSpanTreeAlg::BestNodeMap = std::unordered_map<const reco::ClusterHit3D*,BestNodeTuple>

private

Definition at line 111 of file MinSpanTreeAlg_tool.cc.

using lar_cluster3d::MinSpanTreeAlg::BestNodeTuple = std::tuple<const reco::ClusterHit3D*,float,float>

private

Definition at line 110 of file MinSpanTreeAlg_tool.cc.

using lar_cluster3d::MinSpanTreeAlg::ChannelStatusByPlaneVec = std::vector<ChannelStatusVec>

private

Definition at line 131 of file MinSpanTreeAlg_tool.cc.

using lar_cluster3d::MinSpanTreeAlg::ChannelStatusVec = std::vector<size_t>

private

define data structure for keeping track of channel status

Definition at line 130 of file MinSpanTreeAlg_tool.cc.

Constructor & Destructor Documentation

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

explicit

Constructor.

Parameters

pset

Definition at line 148 of file MinSpanTreeAlg_tool.cc.

                                                            :
    m_pcaAlg(pset.get<fhicl::ParameterSet>("PrincipalComponentsAlg")),
    m_kdTree(pset.get<fhicl::ParameterSet>("kdTree"))
{
    this->configure(pset);
}

lar_cluster3d::MinSpanTreeAlg::~MinSpanTreeAlg

(

)

Destructor.

Definition at line 157 of file MinSpanTreeAlg_tool.cc.

{
}

Member Function Documentation

void lar_cluster3d::MinSpanTreeAlg::AStar ( const reco::ClusterHit3D *  startNode, const reco::ClusterHit3D *  goalNode, float  alpha, kdTree::KdTreeNode &  topNode, reco::ClusterParameters &  clusterParams  ) const

private

Algorithm to find shortest path between two 3D hits.

Definition at line 533 of file MinSpanTreeAlg_tool.cc.

{
    // Recover the list of hits and edges
    reco::HitPairListPtr& pathNodeList = clusterParams.getBestHitPairListPtr();
    reco::EdgeList&       bestEdgeList = clusterParams.getBestEdgeList();
    reco::Hit3DToEdgeMap& curEdgeMap   = clusterParams.getHit3DToEdgeMap();

    // Find the shortest path from start to goal using an A* algorithm
    // Keep track of the nodes which have already been evaluated
    reco::HitPairListPtr closedList;

    // Keep track of the nodes that have been "discovered" but yet to be evaluated
    reco::HitPairListPtr openList = {startNode};

    // Create a map which, for each node, will tell us the node it can be most efficiencly reached from.
    BestNodeMap bestNodeMap;

    bestNodeMap[startNode] = BestNodeTuple(startNode,0.,DistanceBetweenNodes(startNode,goalNode));

    alpha = 1.; //std::max(0.5,alpha);

    while(!openList.empty())
    {
        // The list is not empty so by def we will return something
        reco::HitPairListPtr::iterator currentNodeItr = openList.begin();

        // If the list contains more than one element then we need to find the one with the smallest total estimated cost to the end
        if (openList.size() > 1)
            currentNodeItr = std::min_element(openList.begin(),openList.end(),[bestNodeMap](const auto& next, const auto& best){return std::get<2>(bestNodeMap.at(next)) < std::get<2>(bestNodeMap.at(best));});

        // Easier to deal directly with the pointer to the node
        const reco::ClusterHit3D* currentNode = *currentNodeItr;

        // Check to see if we have reached the goal and need to evaluate the path
        if (currentNode == goalNode)
        {
            // The path reconstruction will
            ReconstructBestPath(goalNode, bestNodeMap, pathNodeList, bestEdgeList);

            break;
        }

        // Otherwise need to keep evaluating
        else
        {
            openList.erase(currentNodeItr);
            currentNode->setStatusBit(reco::ClusterHit3D::PATHCHECKED);

            // Get tuple values for the current node
            const BestNodeTuple& currentNodeTuple = bestNodeMap.at(currentNode);
            float                currentNodeScore = std::get<1>(currentNodeTuple);

            // Recover the edges associated to the current point
            const reco::EdgeList& curEdgeList = curEdgeMap[currentNode];
            
            for(const auto& curEdge : curEdgeList)
            {
                const reco::ClusterHit3D* candHit3D = std::get<1>(curEdge);
                
                if (candHit3D->getStatusBits() & reco::ClusterHit3D::PATHCHECKED) continue;
                
                float tentative_gScore = currentNodeScore + std::get<2>(curEdge);

                // Have we seen the candidate node before?
                BestNodeMap::iterator candNodeItr = bestNodeMap.find(candHit3D);
                
                if (candNodeItr == bestNodeMap.end())
                {
                    openList.push_back(candHit3D);
                }
                else if (tentative_gScore > std::get<1>(candNodeItr->second)) continue;
                
                // Make a guess at score to get to target...
                float guessToTarget = DistanceBetweenNodes(candHit3D,goalNode) / 0.3;
                
                bestNodeMap[candHit3D] = BestNodeTuple(currentNode,tentative_gScore, tentative_gScore + guessToTarget);
            }
        }
    }

    return;
}

void lar_cluster3d::MinSpanTreeAlg::CheckHitSorting ( reco::ClusterParameters &  clusterParams ) const

private

Definition at line 901 of file MinSpanTreeAlg_tool.cc.

{
    reco::HitPairListPtr& curCluster = clusterParams.getHitPairListPtr();

    // Trial A* here
    if (curCluster.size() > 2)
    {
        // Do a quick PCA to determine our parameter "alpha"
        reco::PrincipalComponents pca;
        m_pcaAlg.PCAAnalysis_3D(curCluster, pca);

        if (pca.getSvdOK())
        {
            const Eigen::Vector3f& pcaAxis  = pca.getEigenVectors().row(2);

            std::vector<size_t> closestPlane = {0, 0, 0 };
            std::vector<float>  bestAngle    = {0.,0.,0.};

            for(size_t plane = 0; plane < 3; plane++)
            {
                const std::vector<float>& wireDir = m_wireDir[plane];

                float dotProd = std::fabs(pcaAxis[0]*wireDir[0] + pcaAxis[1]*wireDir[1] + pcaAxis[2]*wireDir[2]);

                if (dotProd > bestAngle[0])
                {
                    bestAngle[2]    = bestAngle[1];
                    closestPlane[2] = closestPlane[1];
                    bestAngle[1]    = bestAngle[0];
                    closestPlane[1] = closestPlane[0];
                    closestPlane[0] = plane;
                    bestAngle[0]    = dotProd;
                }
                else if (dotProd > bestAngle[1])
                {
                    bestAngle[2]    = bestAngle[1];
                    closestPlane[2] = closestPlane[1];
                    closestPlane[1] = plane;
                    bestAngle[1]    = dotProd;
                }
                else
                {
                    closestPlane[2] = plane;
                    bestAngle[2]    = dotProd;
                }
            }

            // Get a copy of our 3D hits
            reco::HitPairListPtr localHitList = curCluster;

            // Sort the hits
            localHitList.sort(SetCheckHitOrder(closestPlane));

            // Ok, let's print it all and take a look
            std::cout << "********************************************************************************************" << std::endl;
            std::cout << "**>>>>> longest axis: " << closestPlane[0] << ", best angle: " << bestAngle[0] << std::endl;
            std::cout << "**>>>>> second  axis: " << closestPlane[1] << ", best angle: " << bestAngle[1] << std::endl;
            std::cout << " " << std::endl;

            reco::HitPairListPtr::iterator firstHitItr = localHitList.begin();
            reco::HitPairListPtr::iterator lastHitItr  = localHitList.begin();

            size_t bestPlane = closestPlane[0];

            reco::HitPairListPtr testList;

            while(firstHitItr != localHitList.end())
            {
                const reco::ClusterHit3D* currentHit = *firstHitItr;

                // Search for the last matching best view hit
                while(lastHitItr != localHitList.end())
                {
                    // If a different wire on the best view then we're certainly done
                    if (currentHit->getWireIDs()[bestPlane] != (*lastHitItr)->getWireIDs()[bestPlane]) break;

                    // More subtle test to see if same wire but different hit (being careful of case of no hit)
                    if (currentHit->getHits()[bestPlane] && (*lastHitItr)->getHits()[bestPlane] && currentHit->getHits()[bestPlane] != (*lastHitItr)->getHits()[bestPlane]) break;

                    // Yet event more subtle test...
                    if ((!(currentHit->getHits()[bestPlane]) && (*lastHitItr)->getHits()[bestPlane]) || (currentHit->getHits()[bestPlane] && !((*lastHitItr)->getHits()[bestPlane]))) break;

                    // Not there yet...
                    lastHitItr++;
                }

                // How many hits in this chain?
//                size_t numHits(std::distance(firstHitItr,lastHitItr));
//                float  minOverlapFraction(0.);

//                if (numHits > 1)
//                {
//                    reco::HitPairListPtr::iterator bestMinOverlapItr = std::max_element(firstHitItr,lastHitItr,[](const auto& left, const auto& right){return left->getMinOverlapFraction() < right->getMinOverlapFraction();});
//
//                    minOverlapFraction = std::min(0.999*(*bestMinOverlapItr)->getMinOverlapFraction(),0.90);
//                }

                while(firstHitItr != lastHitItr)
                {
//                    if (currentHit->getMinOverlapFraction() > minOverlapFraction) testList.push_back(currentHit); //currentHit->setStatusBit(reco::ClusterHit3D::SKELETONHIT);

                    currentHit = *++firstHitItr;
                }

                firstHitItr = lastHitItr;
            }
/*
            for(const auto& hit : localHitList)
            {
                std::cout << "- wires: ";

                for(size_t idx = 0; idx < 3; idx++)
                {
                    float viewTime = -1.;

                    if (hit->getHits()[closestView[idx]]) viewTime = hit->getHits()[closestView[idx]]->getTimeTicks();

                    std::cout << closestView[idx] << ":" << hit->getWireIDs()[closestView[idx]].Wire << " - " << viewTime << ", ";
                }

                bool isSkeleton = hit->getStatusBits() & reco::ClusterHit3D::SKELETONHIT;

                std::cout << "ave time: " << hit->getAvePeakTime() << ", min/max overlap: " << hit->getMinOverlapFraction() << "/" << hit->getMaxOverlapFraction() << ", tagged: " << isSkeleton << std::endl;

                if (isSkeleton) testList.push_back(hit);
            }
*/
            curCluster = testList;
        }
    }

    return;
}

void lar_cluster3d::MinSpanTreeAlg::Cluster3DHits ( reco::HitPairList &  hitPairList, reco::ClusterParametersList &  clusterParametersList  ) const

overridevirtual

Given a set of recob hits, run DBscan to form 3D clusters.

Parameters

hitPairList	The input list of 3D hits to run clustering on
hitPairClusterMap	A map of hits that have been clustered
clusterParametersList	A list of cluster objects (parameters from associated hits)

Driver for processing input 2D hits, transforming to 3D hits and building lists of associated 3D hits (candidate 3D clusters)

Implements lar_cluster3d::IClusterAlg.

Definition at line 208 of file MinSpanTreeAlg_tool.cc.

{
    /**
     *  @brief Driver for processing input 2D hits, transforming to 3D hits and building lists
     *         of associated 3D hits (candidate 3D clusters)
     */

    // Zero the time vector
    if (m_enableMonitoring) std::fill(m_timeVector.begin(),m_timeVector.end(),0.);

    // DBScan is driven of its "epsilon neighborhood". Computing adjacency within DBScan can be time
    // consuming so the idea is the prebuild the adjaceny map and then run DBScan.
    // The following call does this work
    kdTree::KdTreeNodeList kdTreeNodeContainer;
    kdTree::KdTreeNode     topNode = m_kdTree.BuildKdTree(hitPairList, kdTreeNodeContainer);

    if (m_enableMonitoring) m_timeVector.at(BUILDHITTOHITMAP) = m_kdTree.getTimeToExecute();

    // Run DBScan to get candidate clusters
    RunPrimsAlgorithm(hitPairList, topNode, clusterParametersList);

    // 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();

    m_clusterBuilder->BuildClusterInfo(clusterParametersList);

    if (m_enableMonitoring)
    {
        theClockBuildClusters.stop();

        m_timeVector[BUILDCLUSTERINFO] = theClockBuildClusters.accumulated_real_time();
    }

    // Test run the path finding algorithm
    for (auto& clusterParams : clusterParametersList) FindBestPathInCluster(clusterParams, topNode);

    mf::LogDebug("MinSpanTreeAlg") << ">>>>> Cluster3DHits done, found " << clusterParametersList.size() << " clusters" << std::endl;

    return;
}

void lar_cluster3d::MinSpanTreeAlg::Cluster3DHits ( reco::HitPairListPtr &  hitPairList, reco::ClusterParametersList &  clusterParametersList  ) const

inlineoverridevirtual

Given a set of recob hits, run DBscan to form 3D clusters.

Parameters

hitPairListPtr	The input list of 3D hits to run clustering on
clusterParametersList	A list of cluster objects (parameters from associated hits)

Implements lar_cluster3d::IClusterAlg.

Definition at line 70 of file MinSpanTreeAlg_tool.cc.

                                                                                        {return;}

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

override

Definition at line 163 of file MinSpanTreeAlg_tool.cc.

{
    m_enableMonitoring         = pset.get<bool>  ("EnableMonitoring",  true  );

    art::ServiceHandle<geo::Geometry const> geometry;

    m_geometry = &*geometry;

    m_timeVector.resize(NUMTIMEVALUES, 0.);

    // Determine the unit directon and normal vectors to the wires
    m_wireDir.resize(3);

    raw::ChannelID_t uChannel(0);
    std::vector<geo::WireID> uWireID  = m_geometry->ChannelToWire(uChannel);
    const geo::WireGeo*      uWireGeo = m_geometry->WirePtr(uWireID[0]);

    TVector3 uWireDir = uWireGeo->Direction();

    m_wireDir[0].resize(3);
    m_wireDir[0][0] =  uWireDir[0];
    m_wireDir[0][1] = -uWireDir[2];
    m_wireDir[0][2] =  uWireDir[1];

    raw::ChannelID_t vChannel(2400);
    std::vector<geo::WireID> vWireID = m_geometry->ChannelToWire(vChannel);
    const geo::WireGeo* vWireGeo = m_geometry->WirePtr(vWireID[0]);

    TVector3 vWireDir = vWireGeo->Direction();

    m_wireDir[1].resize(3);
    m_wireDir[1][0] =  vWireDir[0];
    m_wireDir[1][1] = -vWireDir[2];
    m_wireDir[1][2] =  vWireDir[1];

    m_wireDir[2].resize(3);
    m_wireDir[2][0] = 0.;
    m_wireDir[2][1] = 0.;
    m_wireDir[2][2] = 1.;

    m_clusterBuilder = art::make_tool<lar_cluster3d::IClusterParametersBuilder>(pset.get<fhicl::ParameterSet>("ClusterParamsBuilder"));

    return;
}

reco::HitPairListPtr lar_cluster3d::MinSpanTreeAlg::DepthFirstSearch ( const reco::EdgeTuple &  curEdge, const reco::Hit3DToEdgeMap &  hitToEdgeMap, float &  bestTreeQuality  ) const

private

a depth first search to find longest branches

Definition at line 722 of file MinSpanTreeAlg_tool.cc.

{
    reco::HitPairListPtr hitPairListPtr;
    float               bestQuality(0.);
    float               curEdgeWeight = std::max(0.3,std::get<2>(curEdge));
    float               curEdgeProj(1./curEdgeWeight);

    reco::Hit3DToEdgeMap::const_iterator edgeListItr = hitToEdgeMap.find(std::get<1>(curEdge));

    if (edgeListItr != hitToEdgeMap.end())
    {
        // The input edge weight has quality factors applied, recalculate just the position difference
        const Eigen::Vector3f& firstHitPos  = std::get<0>(curEdge)->getPosition();
        const Eigen::Vector3f& secondHitPos = std::get<1>(curEdge)->getPosition();
        float                  curEdgeVec[] = {secondHitPos[0]-firstHitPos[0],secondHitPos[1]-firstHitPos[1],secondHitPos[2]-firstHitPos[2]};
        float                  curEdgeMag   = std::sqrt(curEdgeVec[0]*curEdgeVec[0]+curEdgeVec[1]*curEdgeVec[1]+curEdgeVec[2]*curEdgeVec[2]);

        curEdgeMag = std::max(float(0.1),curEdgeMag);

        for(const auto& edge : edgeListItr->second)
        {
            // skip the self reference
            if (std::get<1>(edge) == std::get<0>(curEdge)) continue;

            float quality(0.);

            reco::HitPairListPtr tempList = DepthFirstSearch(edge,hitToEdgeMap,quality);

            if (quality > bestQuality)
            {
                hitPairListPtr = tempList;
                bestQuality    = quality;
                curEdgeProj    = 1./curEdgeMag;
            }
        }
    }

    hitPairListPtr.push_front(std::get<1>(curEdge));

    bestTreeQuality += bestQuality + curEdgeProj;

    return hitPairListPtr;
}

float lar_cluster3d::MinSpanTreeAlg::DistanceBetweenNodes ( const reco::ClusterHit3D *  node1, const reco::ClusterHit3D *  node2  ) const

private

Definition at line 694 of file MinSpanTreeAlg_tool.cc.

{
    const Eigen::Vector3f& node1Pos    = node1->getPosition();
    const Eigen::Vector3f& node2Pos    = node2->getPosition();
    float                  deltaNode[] = {node1Pos[0]-node2Pos[0], node1Pos[1]-node2Pos[1], node1Pos[2]-node2Pos[2]};

    // Standard euclidean distance
    return std::sqrt(deltaNode[0]*deltaNode[0]+deltaNode[1]*deltaNode[1]+deltaNode[2]*deltaNode[2]);

    // Manhatten distance
    //return std::fabs(deltaNode[0]) + std::fabs(deltaNode[1]) + std::fabs(deltaNode[2]);
/*
    // Chebyshev distance
    // We look for maximum distance by wires...

    // Now go through the hits and compare view by view to look for delta wire and tigher constraint on delta t
    int wireDeltas[] = {0,0,0};

    for(size_t idx = 0; idx < 3; idx++)
        wireDeltas[idx] = std::abs(int(node1->getWireIDs()[idx].Wire) - int(node2->getWireIDs()[idx].Wire));

    // put wire deltas in order...
    std::sort(wireDeltas, wireDeltas + 3);

    return std::sqrt(deltaNode[0]*deltaNode[0] + 0.09 * float(wireDeltas[2]*wireDeltas[2]));
 */
}

void lar_cluster3d::MinSpanTreeAlg::FindBestPathInCluster ( reco::ClusterParameters &  curCluster ) const

private

Algorithm to find the best path through the given cluster.

Definition at line 376 of file MinSpanTreeAlg_tool.cc.

{
    reco::HitPairListPtr longestCluster;
    float                bestQuality(0.);
    float                aveNumEdges(0.);
    size_t               maxNumEdges(0);
    size_t               nIsolatedHits(0);

    // Now proceed with building the clusters
    cet::cpu_timer theClockPathFinding;

    // Start clocks if requested
    if (m_enableMonitoring) theClockPathFinding.start();

    reco::HitPairListPtr& hitPairList  = curCluster.getHitPairListPtr();
    reco::Hit3DToEdgeMap& curEdgeMap   = curCluster.getHit3DToEdgeMap();
    reco::EdgeList&       bestEdgeList = curCluster.getBestEdgeList();

    // Do some spelunking...
    for(const auto& hit : hitPairList)
    {
        if (!curEdgeMap[hit].empty() && curEdgeMap[hit].size() == 1)
        {
            float quality(0.);

            reco::HitPairListPtr tempList = DepthFirstSearch(curEdgeMap[hit].front(), curEdgeMap, quality);

            tempList.push_front(std::get<0>(curEdgeMap[hit].front()));

            if (quality > bestQuality)
            {
                longestCluster = tempList;
                bestQuality    = quality;
            }

            nIsolatedHits++;
        }

        aveNumEdges += float(curEdgeMap[hit].size());
        maxNumEdges  = std::max(maxNumEdges,curEdgeMap[hit].size());
    }

    aveNumEdges /= float(hitPairList.size());
    std::cout << "----> # isolated hits: " << nIsolatedHits << ", longest branch: " << longestCluster.size() << ", cluster size: " << hitPairList.size() << ", ave # edges: " << aveNumEdges << ", max: " << maxNumEdges << std::endl;

    if (!longestCluster.empty())
    {
        hitPairList = longestCluster;
        for(const auto& hit : hitPairList)
        {
            for(const auto& edge : curEdgeMap[hit]) bestEdgeList.emplace_back(edge);
        }

        std::cout << "        ====> new cluster size: " << hitPairList.size() << std::endl;
    }

    if (m_enableMonitoring)
    {
        theClockPathFinding.stop();

        m_timeVector[PATHFINDING] += theClockPathFinding.accumulated_real_time();
    }

    return;
}

void lar_cluster3d::MinSpanTreeAlg::FindBestPathInCluster ( reco::ClusterParameters &  clusterParams, kdTree::KdTreeNode &  topNode  ) const

private

Alternative version of FindBestPathInCluster utilizing an A* algorithm.

Definition at line 442 of file MinSpanTreeAlg_tool.cc.

{
    // Set up for timing the function
    cet::cpu_timer theClockPathFinding;

    // Start clocks if requested
    if (m_enableMonitoring) theClockPathFinding.start();

    // Trial A* here
    if (clusterParams.getHitPairListPtr().size() > 2)
    {
        // Get references to what we need....
        reco::HitPairListPtr& curCluster = clusterParams.getHitPairListPtr();
        reco::Hit3DToEdgeMap& curEdgeMap = clusterParams.getHit3DToEdgeMap();
        
        // Do a quick PCA to determine our parameter "alpha"
        reco::PrincipalComponents pca;
        m_pcaAlg.PCAAnalysis_3D(curCluster, pca);

        // The chances of a failure are remote, still we should check
        if (pca.getSvdOK())
        {
            float                     pcaLen    = 3.0*sqrt(pca.getEigenValues()[2]);
            float                     pcaWidth  = 3.0*sqrt(pca.getEigenValues()[1]);
            float                     pcaHeight = 3.0*sqrt(pca.getEigenValues()[0]);
            const Eigen::Vector3f&    pcaCenter = pca.getAvePosition();
            float                     alpha     = std::min(float(1.),std::max(float(0.001),pcaWidth/pcaLen));
            
            // Create a temporary container for the isolated points
            reco::ProjectedPointList  isolatedPointList;
            
            // Go through and find the isolated points, for those get the projection to the plane of maximum spread
            for(const auto& hit3D : curCluster)
            {
                // the definition of an isolated hit is that it only has one associated edge
                if (!curEdgeMap[hit3D].empty() && curEdgeMap[hit3D].size() == 1)
                {
                    Eigen::Vector3f pcaToHitVec(hit3D->getPosition()[0] - pcaCenter(0),
                                                hit3D->getPosition()[1] - pcaCenter(1),
                                                hit3D->getPosition()[2] - pcaCenter(2));
                    Eigen::Vector3f pcaToHit = pca.getEigenVectors() * pcaToHitVec;
                    
                    // This sets x,y where x is the longer spread, y the shorter
                    isolatedPointList.emplace_back(pcaToHit(2),pcaToHit(1),hit3D);
                }
            }

            std::cout << "************* Finding best path with A* in cluster *****************" << std::endl;
            std::cout << "**> There are " << curCluster.size() << " hits, " << isolatedPointList.size() << " isolated hits, the alpha parameter is " << alpha << std::endl;
            std::cout << "**> PCA len: " << pcaLen << ", wid: " << pcaWidth << ", height: " << pcaHeight << ", ratio: " << pcaHeight/pcaWidth << std::endl;
            
            // If no isolated points then nothing to do...
            if (isolatedPointList.size() > 1)
            {
                // Sort the point vec by increasing x, if same then by increasing y.
                isolatedPointList.sort([](const auto& left, const auto& right){return (std::abs(std::get<0>(left) - std::get<0>(right)) > std::numeric_limits<float>::epsilon()) ? std::get<0>(left) < std::get<0>(right) : std::get<1>(left) <     std::get<1>(right);});
                
                // Ok, get the two most distance points...
                const reco::ClusterHit3D* startHit = std::get<2>(isolatedPointList.front());
                const reco::ClusterHit3D* stopHit  = std::get<2>(isolatedPointList.back());
    
                std::cout << "**> Sorted " << isolatedPointList.size() << " hits, longest distance: " << DistanceBetweenNodes(startHit,stopHit) << std::endl;
    
                // Call the AStar function to try to find the best path...
//                AStar(startHit,stopHit,alpha,topNode,clusterParams);
    
                float cost(std::numeric_limits<float>::max());
    
                LeastCostPath(curEdgeMap[startHit].front(),stopHit,clusterParams,cost);
    
                clusterParams.getBestHitPairListPtr().push_front(startHit);
    
                std::cout << "**> Best path has " << clusterParams.getBestHitPairListPtr().size() << " hits, " << clusterParams.getBestEdgeList().size() << " edges" << std::endl;
            }
        }
        else
        {
            std::cout << "++++++>>> PCA failure! # hits: " << curCluster.size() << std::endl;
        }
    }

    if (m_enableMonitoring)
    {
        theClockPathFinding.stop();

        m_timeVector[PATHFINDING] += theClockPathFinding.accumulated_real_time();
    }

    return;
}

float lar_cluster3d::MinSpanTreeAlg::getTimeToExecute ( TimeValues  index ) const

inlineoverridevirtual

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

Implements lar_cluster3d::IClusterAlg.

Definition at line 76 of file MinSpanTreeAlg_tool.cc.

{return m_timeVector.at(index);}

void lar_cluster3d::MinSpanTreeAlg::LeastCostPath ( const reco::EdgeTuple &  curEdge, const reco::ClusterHit3D *  goalNode, reco::ClusterParameters &  clusterParams, float &  showMeTheMoney  ) const

private

Find the lowest cost path between two nodes using MST edges.

Definition at line 641 of file MinSpanTreeAlg_tool.cc.

{
    // Recover the mapping between hits and edges
    reco::Hit3DToEdgeMap& curEdgeMap = clusterParams.getHit3DToEdgeMap();
    
    reco::Hit3DToEdgeMap::const_iterator edgeListItr = curEdgeMap.find(std::get<1>(curEdge));

    showMeTheMoney = std::numeric_limits<float>::max();

    if (edgeListItr != curEdgeMap.end() && !edgeListItr->second.empty())
    {
        reco::HitPairListPtr& bestNodeList = clusterParams.getBestHitPairListPtr();
        reco::EdgeList&       bestEdgeList = clusterParams.getBestEdgeList();
        
        for(const auto& edge : edgeListItr->second)
        {
            // skip the self reference
            if (std::get<1>(edge) == std::get<0>(curEdge)) continue;

            // Have we found the droid we are looking for?
            if (std::get<1>(edge) == goalNode)
            {
                bestNodeList.push_back(goalNode);
                bestEdgeList.push_back(edge);
                showMeTheMoney = std::get<2>(edge);
                break;
            }

            // Keep searching, it is out there somewhere...
            float currentCost(0.);

            LeastCostPath(edge,goalNode,clusterParams,currentCost);

            if (currentCost < std::numeric_limits<float>::max())
            {
                showMeTheMoney = std::get<2>(edge) + currentCost;
                break;
            }
        }
    }

    if (showMeTheMoney < std::numeric_limits<float>::max())
    {
        clusterParams.getBestHitPairListPtr().push_front(std::get<1>(curEdge));
        clusterParams.getBestEdgeList().push_front(curEdge);
    }

    return;
}

void lar_cluster3d::MinSpanTreeAlg::PruneAmbiguousHits ( reco::ClusterParameters &  clusterParams, reco::Hit2DToClusterMap &  hit2DToClusterMap  ) const

private

Prune the obvious ambiguous hits.

Definition at line 768 of file MinSpanTreeAlg_tool.cc.

{

    // Recover the HitPairListPtr from the input clusterParams (which will be the
    // only thing that has been provided)
    reco::HitPairListPtr& hitPairVector = clusterParams.getHitPairListPtr();

    size_t nStartedWith(hitPairVector.size());
    size_t nRejectedHits(0);

    reco::HitPairListPtr goodHits;

    // Loop through the hits and try to week out the clearly ambiguous ones
    for(const auto& hit3D : hitPairVector)
    {
        // Loop to try to remove ambiguous hits
        size_t n2DHitsIn3DHit(0);
        size_t nThisClusterOnly(0);
        size_t nOtherCluster(0);

        //        reco::ClusterParameters* otherCluster;
        const std::set<const reco::ClusterHit3D*>* otherClusterHits = 0;

        for(const auto& hit2D : hit3D->getHits())
        {
            if (!hit2D) continue;

            n2DHitsIn3DHit++;

            if (hit2DToClusterMap[hit2D].size() < 2) nThisClusterOnly = hit2DToClusterMap[hit2D][&clusterParams].size();
            else
            {
                for(const auto& clusterHitMap : hit2DToClusterMap[hit2D])
                {
                    if (clusterHitMap.first == &clusterParams) continue;

                    if (clusterHitMap.second.size() > nOtherCluster)
                    {
                        nOtherCluster    = clusterHitMap.second.size();
                        //                        otherCluster     = clusterHitMap.first;
                        otherClusterHits = &clusterHitMap.second;
                    }
                }
            }
        }

        if (n2DHitsIn3DHit < 3 && nThisClusterOnly > 1 && nOtherCluster > 0)
        {
            bool skip3DHit(false);

            for(const auto& otherHit3D : *otherClusterHits)
            {
                size_t nOther2DHits(0);

                for(const auto& otherHit2D : otherHit3D->getHits())
                {
                    if (!otherHit2D) continue;

                    nOther2DHits++;
                }

                if (nOther2DHits > 2)
                {
                    skip3DHit = true;
                    nRejectedHits++;
                    break;
                }
            }

            if (skip3DHit) continue;

        }

        goodHits.emplace_back(hit3D);
    }

    std::cout << "###>> Input " << nStartedWith << " hits, rejected: " << nRejectedHits << std::endl;

    hitPairVector.resize(goodHits.size());
    std::copy(goodHits.begin(),goodHits.end(),hitPairVector.begin());

    return;
}

void lar_cluster3d::MinSpanTreeAlg::ReconstructBestPath ( const reco::ClusterHit3D *  goalNode, BestNodeMap &  bestNodeMap, reco::HitPairListPtr &  pathNodeList, reco::EdgeList &  bestEdgeList  ) const

private

Definition at line 620 of file MinSpanTreeAlg_tool.cc.

{
    while(std::get<0>(bestNodeMap.at(goalNode)) != goalNode)
    {
        const reco::ClusterHit3D* nextNode = std::get<0>(bestNodeMap[goalNode]);
        reco::EdgeTuple           bestEdge = reco::EdgeTuple(goalNode,nextNode,DistanceBetweenNodes(goalNode,nextNode));

        pathNodeList.push_front(goalNode);
        bestEdgeList.push_front(bestEdge);

        goalNode = nextNode;
    }

    pathNodeList.push_front(goalNode);

    return;
}

void lar_cluster3d::MinSpanTreeAlg::RunPrimsAlgorithm ( reco::HitPairList &  hitPairList, kdTree::KdTreeNode &  topNode, reco::ClusterParametersList &  clusterParametersList  ) const

private

Driver for Prim's algorithm.

Definition at line 254 of file MinSpanTreeAlg_tool.cc.

{
    // If no hits then no work
    if (hitPairList.empty()) return;

    // Now proceed with building the clusters
    cet::cpu_timer theClockDBScan;

    // Start clocks if requested
    if (m_enableMonitoring) theClockDBScan.start();

    // Initialization
    size_t clusterIdx(0);

    // This will contain our list of edges
    reco::EdgeList curEdgeList;

    // Get the first point
    reco::HitPairList::iterator freeHitItr   = hitPairList.begin();
    const reco::ClusterHit3D*   lastAddedHit = &(*freeHitItr++);

    lastAddedHit->setStatusBit(reco::ClusterHit3D::CLUSTERATTACHED);

    // Make a cluster...
    clusterParametersList.push_back(reco::ClusterParameters());

    // Get an iterator to the first cluster
    reco::ClusterParametersList::iterator curClusterItr = --clusterParametersList.end();

    // We use pointers here because the objects they point to will change in the loop below
    reco::Hit3DToEdgeMap* curEdgeMap = &(*curClusterItr).getHit3DToEdgeMap();
    reco::HitPairListPtr* curCluster = &(*curClusterItr).getHitPairListPtr();

    // Loop until all hits have been associated to a cluster
    while(1)
    {
        // and the 3D hit status bits
        lastAddedHit->setStatusBit(reco::ClusterHit3D::CLUSTERATTACHED);

        // Purge the current list to get rid of edges which point to hits already in the cluster
        for(reco::EdgeList::iterator curEdgeItr = curEdgeList.begin(); curEdgeItr != curEdgeList.end();)
        {
            if (std::get<1>(*curEdgeItr)->getStatusBits() & reco::ClusterHit3D::CLUSTERATTACHED)
                curEdgeItr = curEdgeList.erase(curEdgeItr);
            else curEdgeItr++;
        }

        // Add the lastUsedHit to the current cluster
        curCluster->push_back(lastAddedHit);

        // Set up to find the list of nearest neighbors to the last used hit...
        kdTree::CandPairList CandPairList;
        float                bestDistance(1.5); //std::numeric_limits<float>::max());

        // And find them... result will be an unordered list of neigbors
        m_kdTree.FindNearestNeighbors(lastAddedHit, topNode, CandPairList, bestDistance);

        // Copy edges to the current list (but only for hits not already in a cluster)
//        for(auto& pair : CandPairList)
//            if (!(pair.second->getStatusBits() & reco::ClusterHit3D::CLUSTERATTACHED)) curEdgeList.push_back(reco::EdgeTuple(lastAddedHit,pair.second,pair.first));
        for(auto& pair : CandPairList)
        {
            if (!(pair.second->getStatusBits() & reco::ClusterHit3D::CLUSTERATTACHED))
            {
                double edgeWeight = lastAddedHit->getHitChiSquare() * pair.second->getHitChiSquare();
                
                curEdgeList.push_back(reco::EdgeTuple(lastAddedHit,pair.second,edgeWeight));
            }
        }

        // If the edge list is empty then we have a complete cluster
        if (curEdgeList.empty())
        {
            std::cout << "-----------------------------------------------------------------------------------------" << std::endl;
            std::cout << "**> Cluster idx: " << clusterIdx++ << " has " << curCluster->size() << " hits" << std::endl;

            // Look for the next "free" hit
            freeHitItr = std::find_if(freeHitItr,hitPairList.end(),[](const auto& hit){return !(hit.getStatusBits() & reco::ClusterHit3D::CLUSTERATTACHED);});

            // If at end of input list we are done with all hits
            if (freeHitItr == hitPairList.end()) break;

            std::cout << "##################################################################>Processing another cluster" << std::endl;

            // Otherwise, get a new cluster and set up
            clusterParametersList.push_back(reco::ClusterParameters());

            curClusterItr = --clusterParametersList.end();

            curEdgeMap   = &(*curClusterItr).getHit3DToEdgeMap();
            curCluster   = &(*curClusterItr).getHitPairListPtr();
            lastAddedHit = &(*freeHitItr++);
        }
        // Otherwise we are still processing the current cluster
        else
        {
            // Sort the list of edges by distance
            curEdgeList.sort([](const auto& left,const auto& right){return std::get<2>(left) < std::get<2>(right);});

            // Populate the map with the edges...
            reco::EdgeTuple& curEdge = curEdgeList.front();

            (*curEdgeMap)[std::get<0>(curEdge)].push_back(curEdge);
            (*curEdgeMap)[std::get<1>(curEdge)].push_back(reco::EdgeTuple(std::get<1>(curEdge),std::get<0>(curEdge),std::get<2>(curEdge)));

            // Update the last hit to be added to the collection
            lastAddedHit = std::get<1>(curEdge);
        }
    }

    if (m_enableMonitoring)
    {
        theClockDBScan.stop();

        m_timeVector[RUNDBSCAN] = theClockDBScan.accumulated_real_time();
    }

    return;
}

Member Data Documentation

std::unique_ptr<lar_cluster3d::IClusterParametersBuilder> lar_cluster3d::MinSpanTreeAlg::m_clusterBuilder

private

Common cluster builder tool.

Definition at line 145 of file MinSpanTreeAlg_tool.cc.

bool lar_cluster3d::MinSpanTreeAlg::m_enableMonitoring

private

Data members to follow.

Definition at line 136 of file MinSpanTreeAlg_tool.cc.

geo::Geometry const* lar_cluster3d::MinSpanTreeAlg::m_geometry

private

Definition at line 140 of file MinSpanTreeAlg_tool.cc.

kdTree lar_cluster3d::MinSpanTreeAlg::m_kdTree

private

Definition at line 143 of file MinSpanTreeAlg_tool.cc.

PrincipalComponentsAlg lar_cluster3d::MinSpanTreeAlg::m_pcaAlg

private

Definition at line 142 of file MinSpanTreeAlg_tool.cc.

std::vector<float> lar_cluster3d::MinSpanTreeAlg::m_timeVector

mutableprivate

Definition at line 137 of file MinSpanTreeAlg_tool.cc.

std::vector<std::vector<float> > lar_cluster3d::MinSpanTreeAlg::m_wireDir

private

Definition at line 138 of file MinSpanTreeAlg_tool.cc.

---

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

• larreco/larreco/RecoAlg/Cluster3DAlgs/MinSpanTreeAlg_tool.cc