Inheritance diagram for lar_cluster3d::DBScanAlg:

Public Types
enum	TimeValues { BUILDTHREEDHITS = 0, BUILDHITTOHITMAP = 1, RUNDBSCAN = 2, BUILDCLUSTERINFO = 3, PATHFINDING = 4, NUMTIMEVALUES }
	enumerate the possible values for time checking if monitoring timing More...

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

	~DBScanAlg ()
	Destructor. More...

void	configure (const fhicl::ParameterSet &) override
	Interface for configuring the particular algorithm tool. More...

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 (IClusterAlg::TimeValues index) const override
	If monitoring, recover the time to execute a particular function. More...

Private Member Functions
void	expandCluster (const kdTree::KdTreeNode &, kdTree::CandPairList &, reco::ClusterParameters &, size_t) const
	the main routine for DBScan More...

Private Attributes
bool	m_enableMonitoring
	Data members to follow. More...

size_t	m_minPairPts

std::vector< float >	m_timeVector

ClusterParamsBuilder	m_clusterBuilder

kdTree	m_kdTree

Detailed Description

DBScanAlg class definiton.

Definition at line 35 of file DBScanAlg_tool.cc.

Member Enumeration Documentation

enum lar_cluster3d::IClusterAlg::TimeValues

inherited

enumerate the possible values for time checking if monitoring timing

Enumerator
BUILDTHREEDHITS
BUILDHITTOHITMAP
RUNDBSCAN
BUILDCLUSTERINFO
PATHFINDING
NUMTIMEVALUES

Definition at line 61 of file IClusterAlg.h.

                     {BUILDTHREEDHITS  = 0,
                      BUILDHITTOHITMAP = 1,
                      RUNDBSCAN        = 2,
                      BUILDCLUSTERINFO = 3,
                      PATHFINDING      = 4,
                      NUMTIMEVALUES
     };

Constructor & Destructor Documentation

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

explicit

Constructor.

Parameters

pset

Definition at line 96 of file DBScanAlg_tool.cc.

References configure().

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

lar_cluster3d::DBScanAlg::~DBScanAlg ( )

Destructor.

Definition at line 105 of file DBScanAlg_tool.cc.

106 {

107 }

Member Function Documentation

void lar_cluster3d::DBScanAlg::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
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 117 of file DBScanAlg_tool.cc.

References reco::ClusterParameters::addHit3D(), lar_cluster3d::ClusterParamsBuilder::BuildClusterInfo(), lar_cluster3d::IClusterAlg::BUILDCLUSTERINFO, lar_cluster3d::IClusterAlg::BUILDHITTOHITMAP, lar_cluster3d::kdTree::BuildKdTree(), reco::ClusterHit3D::CLUSTERATTACHED, reco::ClusterHit3D::CLUSTERNOISE, reco::ClusterHit3D::CLUSTERVISITED, expandCluster(), lar_cluster3d::kdTree::FindNearestNeighbors(), lar_cluster3d::kdTree::getTimeToExecute(), m_clusterBuilder, m_enableMonitoring, m_kdTree, m_minPairPts, m_timeVector, max, lar_cluster3d::IClusterAlg::NUMTIMEVALUES, and lar_cluster3d::IClusterAlg::RUNDBSCAN.

 {
     cet::cpu_timer theClockDBScan;
     
     m_timeVector.resize(NUMTIMEVALUES, 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.
     // We'll employ a kdTree to implement this scheme
     kdTree::KdTreeNodeList kdTreeNodeContainer;
     kdTree::KdTreeNode     topNode = m_kdTree.BuildKdTree(hitPairList, kdTreeNodeContainer);
 
     if (m_enableMonitoring) m_timeVector.at(BUILDHITTOHITMAP) = m_kdTree.getTimeToExecute();
     
     if (m_enableMonitoring) theClockDBScan.start();
     
     // Ok, here we go!
     // The idea is to loop through all of the input 3D hits and do the clustering
     for(const auto& hit : hitPairList)
     {
         // Check if the hit has already been visited
         if (hit->getStatusBits() & reco::ClusterHit3D::CLUSTERVISITED) continue;
         
         // Mark as visited
         hit->setStatusBit(reco::ClusterHit3D::CLUSTERVISITED);
         
         // Find the neighborhood for this hit
         kdTree::CandPairList candPairList;
         float                bestDistance(std::numeric_limits<float>::max());
         
         m_kdTree.FindNearestNeighbors(hit.get(), topNode, candPairList, bestDistance);
         
         if (candPairList.size() < m_minPairPts)
         {
             hit->setStatusBit(reco::ClusterHit3D::CLUSTERNOISE);
         }
         else
         {
             // "Create" a new cluster and get a reference to it
             clusterParametersList.push_back(reco::ClusterParameters());
             
             reco::ClusterParameters& curCluster = clusterParametersList.back();
             
             hit->setStatusBit(reco::ClusterHit3D::CLUSTERATTACHED);
             curCluster.addHit3D(hit.get());
             
             // expand the cluster
             expandCluster(topNode, candPairList, curCluster, m_minPairPts);
         }
     }
 
     if (m_enableMonitoring)
     {
         theClockDBScan.stop();
         
         m_timeVector[RUNDBSCAN] = theClockDBScan.accumulated_real_time();
     }
     
     // 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();
     }
     
     mf::LogDebug("Cluster3D") << ">>>>> DBScan done, found " << clusterParametersList.size() << " clusters" << std::endl;
     
     return;
 }

void lar_cluster3d::DBScanAlg::Cluster3DHits	(	reco::HitPairListPtr &	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
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 200 of file DBScanAlg_tool.cc.

References reco::ClusterParameters::addHit3D(), lar_cluster3d::ClusterParamsBuilder::BuildClusterInfo(), lar_cluster3d::IClusterAlg::BUILDCLUSTERINFO, lar_cluster3d::IClusterAlg::BUILDHITTOHITMAP, lar_cluster3d::kdTree::BuildKdTree(), reco::ClusterHit3D::CLUSTERATTACHED, reco::ClusterHit3D::CLUSTERNOISE, reco::ClusterHit3D::CLUSTERVISITED, expandCluster(), lar_cluster3d::kdTree::FindNearestNeighbors(), lar_cluster3d::kdTree::getTimeToExecute(), m_clusterBuilder, m_enableMonitoring, m_kdTree, m_minPairPts, m_timeVector, max, lar_cluster3d::IClusterAlg::NUMTIMEVALUES, and lar_cluster3d::IClusterAlg::RUNDBSCAN.

 {
     cet::cpu_timer theClockDBScan;
     
     m_timeVector.resize(NUMTIMEVALUES, 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.
     // We'll employ a kdTree to implement this scheme
     kdTree::KdTreeNodeList kdTreeNodeContainer;
     kdTree::KdTreeNode     topNode = m_kdTree.BuildKdTree(hitPairList, kdTreeNodeContainer);
     
     if (m_enableMonitoring) m_timeVector.at(BUILDHITTOHITMAP) = m_kdTree.getTimeToExecute();
     
     if (m_enableMonitoring) theClockDBScan.start();
     
     // Ok, here we go!
     // The idea is to loop through all of the input 3D hits and do the clustering
     for(const auto& hit : hitPairList)
     {
         // Check if the hit has already been visited
         if (hit->getStatusBits() & reco::ClusterHit3D::CLUSTERVISITED) continue;
         
         // Mark as visited
         hit->setStatusBit(reco::ClusterHit3D::CLUSTERVISITED);
         
         // Find the neighborhood for this hit
         kdTree::CandPairList candPairList;
         float                bestDistance(std::numeric_limits<float>::max());
         
         m_kdTree.FindNearestNeighbors(hit, topNode, candPairList, bestDistance);
         
         if (candPairList.size() < m_minPairPts)
         {
             hit->setStatusBit(reco::ClusterHit3D::CLUSTERNOISE);
         }
         else
         {
             // "Create" a new cluster and get a reference to it
             clusterParametersList.push_back(reco::ClusterParameters());
             
             reco::ClusterParameters& curCluster = clusterParametersList.back();
             
             hit->setStatusBit(reco::ClusterHit3D::CLUSTERATTACHED);
             curCluster.addHit3D(hit);
             
             // expand the cluster
             expandCluster(topNode, candPairList, curCluster, m_minPairPts);
         }
     }
     
     if (m_enableMonitoring)
     {
         theClockDBScan.stop();
         
         m_timeVector[RUNDBSCAN] = theClockDBScan.accumulated_real_time();
     }
     
     // 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();
     }
     
     mf::LogDebug("Cluster3D") << ">>>>> DBScan done, found " << clusterParametersList.size() << " clusters" << std::endl;
     
     return;
 }

void lar_cluster3d::DBScanAlg::configure ( const fhicl::ParameterSet & )

overridevirtual

Interface for configuring the particular algorithm tool.

Parameters

ParameterSet The input set of parameters for configuration

Implements lar_cluster3d::IClusterAlg.

Definition at line 111 of file DBScanAlg_tool.cc.

References fhicl::ParameterSet::get(), m_enableMonitoring, and m_minPairPts.

Referenced by DBScanAlg().

 {
     m_enableMonitoring         = pset.get<bool>  ("EnableMonitoring",  true  );
     m_minPairPts               = pset.get<size_t>("MinPairPts",        2     );
 }

void lar_cluster3d::DBScanAlg::expandCluster	(	const kdTree::KdTreeNode &	topNode,
		kdTree::CandPairList &	candPairList,
		reco::ClusterParameters &	cluster,
		size_t	minPts
	)		const

private

the main routine for DBScan

Definition at line 283 of file DBScanAlg_tool.cc.

References reco::ClusterParameters::addHit3D(), reco::ClusterHit3D::CLUSTERATTACHED, reco::ClusterHit3D::CLUSTERVISITED, DEFINE_ART_CLASS_TOOL, lar_cluster3d::kdTree::FindNearestNeighbors(), reco::ClusterHit3D::getStatusBits(), m_kdTree, max, and reco::ClusterHit3D::setStatusBit().

Referenced by Cluster3DHits(), and getTimeToExecute().

 {
     // This is the main inside loop for the DBScan based clustering algorithm
     
     // Loop over added hits until list has been exhausted
     while(!candPairList.empty())
     {
         // Dereference the point so we can see in the debugger...
         const reco::ClusterHit3D* neighborHit = candPairList.front().second;
         
         // Process if we've not been here before
         if (!(neighborHit->getStatusBits() & reco::ClusterHit3D::CLUSTERVISITED))
         {
             // set as visited
             neighborHit->setStatusBit(reco::ClusterHit3D::CLUSTERVISITED);
             
             // get the neighborhood around this point
             kdTree::CandPairList neighborCandPairList;
             float                bestDistance(std::numeric_limits<float>::max());
             
             m_kdTree.FindNearestNeighbors(neighborHit, topNode, neighborCandPairList, bestDistance);
 
             // If the epsilon neighborhood of this point is large enough then add its points to our list
             if (neighborCandPairList.size() >= minPts)
             {
                 std::copy(neighborCandPairList.begin(),neighborCandPairList.end(),std::back_inserter(candPairList));
             }
         }
         
         // If the point is not yet in a cluster then we now add
         if (!(neighborHit->getStatusBits() & reco::ClusterHit3D::CLUSTERATTACHED))
         {
             neighborHit->setStatusBit(reco::ClusterHit3D::CLUSTERATTACHED);
             cluster.addHit3D(neighborHit);
         }
         
         candPairList.pop_front();
     }
     
     return;
 }