CosmicRayTrackRecoveryAlgorithm class. More...

#include <CosmicRayTrackRecoveryAlgorithm.h>

Inheritance diagram for lar_content::CosmicRayTrackRecoveryAlgorithm:

Classes
class	Particle
	Particle class. More...

Public Member Functions
	CosmicRayTrackRecoveryAlgorithm ()
	Default constructor. More...

Private Types
typedef std::vector< Particle >	ParticleList

typedef std::unordered_map< const pandora::Cluster *, pandora::ClusterList >	ClusterAssociationMap

typedef std::set< unsigned int >	UIntSet

Private Member Functions
pandora::StatusCode	Run ()

pandora::StatusCode	ReadSettings (const pandora::TiXmlHandle xmlHandle)

pandora::StatusCode	GetAvailableClusters (const std::string &inputClusterListName, pandora::ClusterVector &clusterVector) const
	Get a vector of available clusters. More...

void	SelectCleanClusters (const pandora::ClusterVector &inputVector, pandora::ClusterVector &outputVector) const
	Select a set of clusters judged to be clean. More...

void	BuildSlidingFitResultMap (const pandora::ClusterVector &clusterVector, TwoDSlidingFitResultMap &slidingFitResultMap) const
	Build the map of sliding fit results. More...

void	MatchViews (const pandora::ClusterVector &clusterVector1, const pandora::ClusterVector &clusterVector2, const TwoDSlidingFitResultMap &slidingFitResultMap, ClusterAssociationMap &clusterAssociationMap) const
	Match a pair of cluster vectors and populate the cluster association map. More...

void	MatchClusters (const pandora::Cluster *const pSeedCluster, const pandora::ClusterVector &targetClusters, const TwoDSlidingFitResultMap &slidingFitResultMap, ClusterAssociationMap &clusterAssociationMap) const
	Match a seed cluster with a list of target clusters and populate the cluster association map. More...

void	MatchThreeViews (const pandora::ClusterVector &clusterVectorU, const pandora::ClusterVector &clusterVectorV, const pandora::ClusterVector &clusterVectorW, const ClusterAssociationMap &clusterAssociationMapUV, const ClusterAssociationMap &clusterAssociationMapVW, const ClusterAssociationMap &clusterAssociationMapWU, ParticleList &particleList) const
	Create candidate particles using three primary clusters. More...

void	MatchTwoViews (const pandora::ClusterVector &clusterVectorU, const pandora::ClusterVector &clusterVectorV, const pandora::ClusterVector &clusterVectorW, const ClusterAssociationMap &clusterAssociationMapUV, const ClusterAssociationMap &clusterAssociationMapVW, const ClusterAssociationMap &clusterAssociationMapWU, ParticleList &particleList) const
	Create candidate particles using two primary clusters and one pair of broken clusters. More...

void	MatchOneView (const pandora::ClusterVector &clusterVectorU, const pandora::ClusterVector &clusterVectorV, const pandora::ClusterVector &clusterVectorW, const ClusterAssociationMap &clusterAssociationMapUV, const ClusterAssociationMap &clusterAssociationMapVW, const ClusterAssociationMap &clusterAssociationMapWU, ParticleList &particleList) const
	Create candidate particles using one primary cluster and one pair of broken clusters. More...

void	BuildVetoList (const ParticleList &particleList, pandora::ClusterSet &vetoList) const
	Build the list of clusters already used to create particles. More...

void	RemoveAmbiguities (const ParticleList &inputParticleList, ParticleList &outputParticleList) const
	Remove particles with duplicate clusters. More...

void	MergeClusters (const pandora::ClusterList &inputClusterList, pandora::ClusterList &outputClusterList) const
	Merge broken clusters into a single cluster. More...

void	BuildParticles (const ParticleList &particleList)
	Build particle flow objects. More...

Private Attributes
float	m_clusterMinLength

float	m_clusterMinSpanZ

float	m_clusterMinOverlapX

float	m_clusterMaxDeltaX

unsigned int	m_clusterMinHits

std::string	m_inputClusterListNameU

std::string	m_inputClusterListNameV

std::string	m_inputClusterListNameW

std::string	m_outputPfoListName

Detailed Description

CosmicRayTrackRecoveryAlgorithm class.

Definition at line 21 of file CosmicRayTrackRecoveryAlgorithm.h.

Member Typedef Documentation

typedef std::unordered_map<const pandora::Cluster *, pandora::ClusterList> lar_content::CosmicRayTrackRecoveryAlgorithm::ClusterAssociationMap

private

Definition at line 44 of file CosmicRayTrackRecoveryAlgorithm.h.

typedef std::vector<Particle> lar_content::CosmicRayTrackRecoveryAlgorithm::ParticleList

private

Definition at line 43 of file CosmicRayTrackRecoveryAlgorithm.h.

typedef std::set<unsigned int> lar_content::CosmicRayTrackRecoveryAlgorithm::UIntSet

private

Definition at line 45 of file CosmicRayTrackRecoveryAlgorithm.h.

Constructor & Destructor Documentation

lar_content::CosmicRayTrackRecoveryAlgorithm::CosmicRayTrackRecoveryAlgorithm ( )

Default constructor.

Definition at line 22 of file CosmicRayTrackRecoveryAlgorithm.cc.

                                                                  :
     m_clusterMinLength(10.f),
     m_clusterMinSpanZ(2.f),
     m_clusterMinOverlapX(6.f),
     m_clusterMaxDeltaX(3.f),
     m_clusterMinHits(3)
 {
 }

Member Function Documentation

void lar_content::CosmicRayTrackRecoveryAlgorithm::BuildParticles ( const ParticleList & particleList )

private

Build particle flow objects.

Parameters

particleList the input list of candidate particles

Definition at line 654 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     if (particleList.empty())
         return;
 
     const PfoList *pPfoList(nullptr);
     std::string pfoListName;
     PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::CreateTemporaryListAndSetCurrent(*this, pPfoList, pfoListName));
 
     for (const Particle &particle : particleList)
     {
         if (!PandoraContentApi::IsAvailable(*this, &particle.m_clusterList))
             continue;
 
         ClusterList clusterList;
         this->MergeClusters(particle.m_clusterList, clusterList);
 
         if (clusterList.empty())
             throw StatusCodeException(STATUS_CODE_FAILURE);
 
         PandoraContentApi::ParticleFlowObject::Parameters pfoParameters;
         pfoParameters.m_particleId = MU_MINUS; // TRACK
         pfoParameters.m_charge = PdgTable::GetParticleCharge(pfoParameters.m_particleId.Get());
         pfoParameters.m_mass = PdgTable::GetParticleMass(pfoParameters.m_particleId.Get());
         pfoParameters.m_energy = 0.f;
         pfoParameters.m_momentum = CartesianVector(0.f, 0.f, 0.f);
         pfoParameters.m_clusterList = clusterList;
 
         const ParticleFlowObject *pPfo(nullptr);
         PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::ParticleFlowObject::Create(*this, pfoParameters, pPfo));
     }
 
     if (!pPfoList->empty())
         PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::SaveList<Pfo>(*this, m_outputPfoListName));
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::BuildSlidingFitResultMap	(	const pandora::ClusterVector &	clusterVector,
		TwoDSlidingFitResultMap &	slidingFitResultMap
	)		const

private

Build the map of sliding fit results.

Parameters

clusterVector	the input cluster vector
slidingFitResultMap	the output sliding fit result map

Definition at line 131 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     const unsigned int m_halfWindowLayers(25);
     const float slidingFitPitch(LArGeometryHelper::GetWireZPitch(this->GetPandora()));
 
     for (ClusterVector::const_iterator iter = clusterVector.begin(), iterEnd = clusterVector.end(); iter != iterEnd; ++iter)
     {
         if (slidingFitResultMap.end() == slidingFitResultMap.find(*iter))
         {
             try
             {
                 const TwoDSlidingFitResult slidingFitResult(*iter, m_halfWindowLayers, slidingFitPitch);
 
                 if (!slidingFitResultMap.insert(TwoDSlidingFitResultMap::value_type(*iter, slidingFitResult)).second)
                     throw StatusCodeException(STATUS_CODE_FAILURE);
             }
             catch (StatusCodeException &statusCodeException)
             {
                 if (STATUS_CODE_FAILURE == statusCodeException.GetStatusCode())
                     throw statusCodeException;
             }
         }
     }
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::BuildVetoList	(	const ParticleList &	particleList,
		pandora::ClusterSet &	vetoList
	)		const

private

Build the list of clusters already used to create particles.

Parameters

particleList	the current list of candidate particles
vetoList	the list of clusters that belong to the candidate particles

Definition at line 596 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     for (ParticleList::const_iterator pIter = particleList.begin(), pIterEnd = particleList.end(); pIter != pIterEnd; ++pIter)
     {
         const Particle &particle = *pIter;
         vetoList.insert(particle.m_clusterList.begin(), particle.m_clusterList.end());
     }
 }

StatusCode lar_content::CosmicRayTrackRecoveryAlgorithm::GetAvailableClusters	(	const std::string &	inputClusterListName,
		pandora::ClusterVector &	clusterVector
	)		const

private

Get a vector of available clusters.

Parameters

inputClusterListName	the input name of the cluster list
clusterVector	the output vector of available clusters

Definition at line 76 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     const ClusterList *pClusterList = NULL;
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_INITIALIZED, !=, PandoraContentApi::GetList(*this, inputClusterListName, pClusterList))
 
     if (!pClusterList || pClusterList->empty())
     {
         if (PandoraContentApi::GetSettings(*this)->ShouldDisplayAlgorithmInfo())
             std::cout << "CosmicRayTrackRecoveryAlgorithm: unable to find cluster list " << inputClusterListName << std::endl;
 
         return STATUS_CODE_SUCCESS;
     }
 
     for (const Cluster *const pCluster : *pClusterList)
     {
         if (PandoraContentApi::IsAvailable(*this, pCluster))
             clusterVector.push_back(pCluster);
     }
 
     std::sort(clusterVector.begin(), clusterVector.end(), LArClusterHelper::SortByNHits);
 
     return STATUS_CODE_SUCCESS;
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::MatchClusters	(	const pandora::Cluster *const	pSeedCluster,
		const pandora::ClusterVector &	targetClusters,
		const TwoDSlidingFitResultMap &	slidingFitResultMap,
		ClusterAssociationMap &	clusterAssociationMap
	)		const

private

Match a seed cluster with a list of target clusters and populate the cluster association map.

Parameters

pSeedCluster	the input seed cluster
targetClusters	the input list of target clusters
slidingFitResultMap	the input map of sliding linear fit results
clusterAssociationMap	the output map of cluster associations

Definition at line 170 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     // Match seed cluster to target clusters according to alignment in X position of start/end positions
     // Two possible matches: (a) one-to-one associations where both the track start and end positions match up
     //                       (b) one-to-two associations where the track is split into two clusters in one view
     // Require overlap in X (according to clusterMinOverlapX) and alignment in X (according to clusterMaxDeltaX)
 
     TwoDSlidingFitResultMap::const_iterator fsIter = slidingFitResultMap.find(pSeedCluster);
 
     if (slidingFitResultMap.end() == fsIter)
         throw StatusCodeException(STATUS_CODE_FAILURE);
 
     const TwoDSlidingFitResult &slidingFitResult1(fsIter->second);
     const CartesianVector &innerVertex1(slidingFitResult1.GetGlobalMinLayerPosition());
     const CartesianVector &outerVertex1(slidingFitResult1.GetGlobalMaxLayerPosition());
     const float xSpan1(std::fabs(outerVertex1.GetX() - innerVertex1.GetX()));
 
     const Cluster *pBestClusterInner(NULL);
     const Cluster *pBestClusterOuter(NULL);
     const Cluster *pBestCluster(NULL);
 
     float bestDisplacementInner(m_clusterMaxDeltaX);
     float bestDisplacementOuter(m_clusterMaxDeltaX);
     float bestDisplacement(2.f * m_clusterMaxDeltaX);
 
     for (ClusterVector::const_iterator tIter = targetClusters.begin(), tIterEnd = targetClusters.end(); tIter != tIterEnd; ++tIter)
     {
         const Cluster *const pTargetCluster = *tIter;
 
         UIntSet daughterVolumeIntersection;
         LArGeometryHelper::GetCommonDaughterVolumes(pSeedCluster, pTargetCluster, daughterVolumeIntersection);
 
         if (daughterVolumeIntersection.empty())
             continue;
 
         if (LArClusterHelper::GetClusterHitType(pSeedCluster) == LArClusterHelper::GetClusterHitType(pTargetCluster))
             throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
         TwoDSlidingFitResultMap::const_iterator ftIter = slidingFitResultMap.find(*tIter);
 
         if (slidingFitResultMap.end() == ftIter)
             throw StatusCodeException(STATUS_CODE_FAILURE);
 
         const TwoDSlidingFitResult &slidingFitResult2(ftIter->second);
         const CartesianVector &innerVertex2(slidingFitResult2.GetGlobalMinLayerPosition());
         const CartesianVector &outerVertex2(slidingFitResult2.GetGlobalMaxLayerPosition());
         const float xSpan2(std::fabs(outerVertex2.GetX() - innerVertex2.GetX()));
 
         if (xSpan2 > 1.5f * xSpan1)
             continue;
 
         const float xMin1(std::min(innerVertex1.GetX(), outerVertex1.GetX()));
         const float xMax1(std::max(innerVertex1.GetX(), outerVertex1.GetX()));
         const float xMin2(std::min(innerVertex2.GetX(), outerVertex2.GetX()));
         const float xMax2(std::max(innerVertex2.GetX(), outerVertex2.GetX()));
         const float xOverlap(std::min(xMax1, xMax2) - std::max(xMin1, xMin2));
 
         if (xOverlap < m_clusterMinOverlapX)
             continue;
 
         const float dxMin(std::fabs(xMin2 - xMin1));
         const float dxMax(std::fabs(xMax2 - xMax1));
 
         if (dxMin < bestDisplacementInner)
         {
             pBestClusterInner = pTargetCluster;
             bestDisplacementInner = dxMin;
         }
 
         if (dxMax < bestDisplacementOuter)
         {
             pBestClusterOuter = pTargetCluster;
             bestDisplacementOuter = dxMax;
         }
 
         if (dxMin + dxMax < bestDisplacement)
         {
             pBestCluster = pTargetCluster;
             bestDisplacement = dxMin + dxMax;
         }
     }
 
     if (pBestCluster)
     {
         ClusterList &seedList(clusterAssociationMap[pSeedCluster]);
 
         if (seedList.end() == std::find(seedList.begin(), seedList.end(), pBestCluster))
             seedList.push_back(pBestCluster);
 
         ClusterList &bestList(clusterAssociationMap[pBestCluster]);
 
         if (bestList.end() == std::find(bestList.begin(), bestList.end(), pSeedCluster))
             bestList.push_back(pSeedCluster);
     }
     else if (pBestClusterInner && pBestClusterOuter)
     {
         TwoDSlidingFitResultMap::const_iterator iterInner = slidingFitResultMap.find(pBestClusterInner);
         TwoDSlidingFitResultMap::const_iterator iterOuter = slidingFitResultMap.find(pBestClusterOuter);
 
         if (slidingFitResultMap.end() == iterInner || slidingFitResultMap.end() == iterOuter)
             throw StatusCodeException(STATUS_CODE_FAILURE);
 
         const LArPointingCluster pointingClusterInner(iterInner->second);
         const LArPointingCluster pointingClusterOuter(iterOuter->second);
 
         LArPointingCluster::Vertex pointingVertexInner, pointingVertexOuter;
 
         try
         {
             LArPointingClusterHelper::GetClosestVertices(pointingClusterInner, pointingClusterOuter, pointingVertexInner, pointingVertexOuter);
         }
         catch (StatusCodeException &)
         {
             return;
         }
 
         const LArPointingCluster::Vertex pointingEndInner(
             pointingVertexInner.IsInnerVertex() ? pointingClusterInner.GetOuterVertex() : pointingClusterInner.GetInnerVertex());
         const LArPointingCluster::Vertex pointingEndOuter(
             pointingVertexOuter.IsInnerVertex() ? pointingClusterOuter.GetOuterVertex() : pointingClusterOuter.GetInnerVertex());
 
         const float rSpan((pointingEndInner.GetPosition() - pointingEndOuter.GetPosition()).GetMagnitude());
 
         if (LArPointingClusterHelper::IsEmission(pointingVertexInner.GetPosition(), pointingVertexOuter, -1.f, 0.75f * rSpan, 5.f, 10.f) &&
             LArPointingClusterHelper::IsEmission(pointingVertexOuter.GetPosition(), pointingVertexInner, -1.f, 0.75f * rSpan, 5.f, 10.f))
         {
             ClusterList &bestInnerList(clusterAssociationMap[pBestClusterInner]);
 
             if (bestInnerList.end() == std::find(bestInnerList.begin(), bestInnerList.end(), pSeedCluster))
                 bestInnerList.push_back(pSeedCluster);
 
             ClusterList &bestOuterList(clusterAssociationMap[pBestClusterOuter]);
 
             if (bestOuterList.end() == std::find(bestOuterList.begin(), bestOuterList.end(), pSeedCluster))
                 bestOuterList.push_back(pSeedCluster);
         }
     }
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::MatchOneView	(	const pandora::ClusterVector &	clusterVectorU,
		const pandora::ClusterVector &	clusterVectorV,
		const pandora::ClusterVector &	clusterVectorW,
		const ClusterAssociationMap &	clusterAssociationMapUV,
		const ClusterAssociationMap &	clusterAssociationMapVW,
		const ClusterAssociationMap &	clusterAssociationMapWU,
		ParticleList &	particleList
	)		const

private

Create candidate particles using one primary cluster and one pair of broken clusters.

Parameters

clusterVectorU	input vector of clusters from the U view
clusterVectorV	input vector of clusters from the V view
clusterVectorW	input vector of clusters from the W view
clusterAssociationMapUV	map of cluster associations between the U and V views
clusterAssociationMapVW	map of cluster associations between the V and W views
clusterAssociationMapWU	map of cluster associations between the W and U views
particleList	the output list of candidate particles

Definition at line 508 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     ClusterSet vetoList;
     this->BuildVetoList(particleList, vetoList);
 
     ParticleList newParticleList;
 
     for (unsigned int iView = 0; iView < 3; ++iView)
     {
         const ClusterVector &clusterVector1((0 == iView) ? clusterVectorU : (1 == iView) ? clusterVectorV : clusterVectorW);
         const ClusterVector &clusterVector2((0 == iView) ? clusterVectorV : (1 == iView) ? clusterVectorW : clusterVectorU);
         const ClusterVector &clusterVector3((0 == iView) ? clusterVectorW : (1 == iView) ? clusterVectorU : clusterVectorV);
 
         const ClusterAssociationMap &matchedClusters12(((0 == iView) ? matchedClustersUV : (1 == iView) ? matchedClustersVW : matchedClustersWU));
         const ClusterAssociationMap &matchedClusters23(((0 == iView) ? matchedClustersVW : (1 == iView) ? matchedClustersWU : matchedClustersUV));
         const ClusterAssociationMap &matchedClusters31(((0 == iView) ? matchedClustersWU : (1 == iView) ? matchedClustersUV : matchedClustersVW));
 
         for (ClusterVector::const_iterator iter1 = clusterVector1.begin(), iterEnd1 = clusterVector1.end(); iter1 != iterEnd1; ++iter1)
         {
             const Cluster *const pCluster1 = *iter1;
 
             if (vetoList.count(pCluster1))
                 continue;
 
             const ClusterAssociationMap::const_iterator iter311 = matchedClusters31.find(pCluster1);
             const ClusterList matchedClusters31_pCluster1(iter311 != matchedClusters31.end() ? iter311->second : ClusterList());
 
             const ClusterAssociationMap::const_iterator iter121 = matchedClusters12.find(pCluster1);
             const ClusterList matchedClusters12_pCluster1(iter121 != matchedClusters12.end() ? iter121->second : ClusterList());
 
             if (matchedClusters12_pCluster1.size() + matchedClusters31_pCluster1.size() > 0)
                 continue;
 
             Particle newParticle;
             newParticle.m_clusterList.push_back(pCluster1);
 
             for (ClusterVector::const_iterator iter2 = clusterVector2.begin(), iterEnd2 = clusterVector2.end(); iter2 != iterEnd2; ++iter2)
             {
                 const Cluster *const pCluster2 = *iter2;
 
                 if (vetoList.count(pCluster2))
                     continue;
 
                 const ClusterAssociationMap::const_iterator iter122 = matchedClusters12.find(pCluster2);
                 const ClusterList matchedClusters12_pCluster2(iter122 != matchedClusters12.end() ? iter122->second : ClusterList());
 
                 const ClusterAssociationMap::const_iterator iter232 = matchedClusters23.find(pCluster2);
                 const ClusterList matchedClusters23_pCluster2(iter232 != matchedClusters23.end() ? iter232->second : ClusterList());
 
                 if (matchedClusters12_pCluster2.size() == 1 &&
                     std::find(matchedClusters12_pCluster2.begin(), matchedClusters12_pCluster2.end(), pCluster1) !=
                         matchedClusters12_pCluster2.end() &&
                     matchedClusters23_pCluster2.size() == 0)
                     newParticle.m_clusterList.push_back(pCluster2);
             }
 
             for (ClusterVector::const_iterator iter3 = clusterVector3.begin(), iterEnd3 = clusterVector3.end(); iter3 != iterEnd3; ++iter3)
             {
                 const Cluster *const pCluster3 = *iter3;
 
                 if (vetoList.count(pCluster3))
                     continue;
 
                 const ClusterAssociationMap::const_iterator iter233 = matchedClusters23.find(pCluster3);
                 const ClusterList matchedClusters23_pCluster3(iter233 != matchedClusters23.end() ? iter233->second : ClusterList());
 
                 const ClusterAssociationMap::const_iterator iter313 = matchedClusters31.find(pCluster3);
                 const ClusterList matchedClusters31_pCluster3(iter313 != matchedClusters31.end() ? iter313->second : ClusterList());
 
                 if (matchedClusters31_pCluster3.size() == 1 &&
                     std::find(matchedClusters31_pCluster3.begin(), matchedClusters31_pCluster3.end(), pCluster1) !=
                         matchedClusters31_pCluster3.end() &&
                     matchedClusters23_pCluster3.size() == 0)
                     newParticle.m_clusterList.push_back(pCluster3);
             }
 
             if (newParticle.m_clusterList.size() > 1)
                 newParticleList.push_back(newParticle);
         }
     }
 
     return this->RemoveAmbiguities(newParticleList, particleList);
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::MatchThreeViews	(	const pandora::ClusterVector &	clusterVectorU,
		const pandora::ClusterVector &	clusterVectorV,
		const pandora::ClusterVector &	clusterVectorW,
		const ClusterAssociationMap &	clusterAssociationMapUV,
		const ClusterAssociationMap &	clusterAssociationMapVW,
		const ClusterAssociationMap &	clusterAssociationMapWU,
		ParticleList &	particleList
	)		const

private

Create candidate particles using three primary clusters.

Parameters

clusterVectorU	input vector of clusters from the U view
clusterVectorV	input vector of clusters from the V view
clusterVectorW	input vector of clusters from the W view
clusterAssociationMapUV	map of cluster associations between the U and V views
clusterAssociationMapVW	map of cluster associations between the V and W views
clusterAssociationMapWU	map of cluster associations between the W and U views
particleList	the output list of candidate particles

Definition at line 312 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     ClusterSet vetoList;
     this->BuildVetoList(particleList, vetoList);
 
     ParticleList newParticleList;
 
     const ClusterVector &clusterVector1(clusterVectorU);
     const ClusterVector &clusterVector2(clusterVectorV);
     const ClusterVector &clusterVector3(clusterVectorW);
 
     const ClusterAssociationMap &matchedClusters12(matchedClustersUV);
     const ClusterAssociationMap &matchedClusters23(matchedClustersVW);
     const ClusterAssociationMap &matchedClusters31(matchedClustersWU);
 
     for (ClusterVector::const_iterator iter1 = clusterVector1.begin(), iterEnd1 = clusterVector1.end(); iter1 != iterEnd1; ++iter1)
     {
         const Cluster *const pCluster1 = *iter1;
 
         if (vetoList.count(pCluster1))
             continue;
 
         const ClusterAssociationMap::const_iterator iter311 = matchedClusters31.find(pCluster1);
         const ClusterList matchedClusters31_pCluster1(iter311 != matchedClusters31.end() ? iter311->second : ClusterList());
 
         const ClusterAssociationMap::const_iterator iter121 = matchedClusters12.find(pCluster1);
         const ClusterList matchedClusters12_pCluster1(iter121 != matchedClusters12.end() ? iter121->second : ClusterList());
 
         for (ClusterVector::const_iterator iter2 = clusterVector2.begin(), iterEndV = clusterVector2.end(); iter2 != iterEndV; ++iter2)
         {
             const Cluster *const pCluster2 = *iter2;
 
             if (vetoList.count(pCluster2))
                 continue;
 
             const ClusterAssociationMap::const_iterator iter122 = matchedClusters12.find(pCluster2);
             const ClusterList matchedClusters12_pCluster2(iter122 != matchedClusters12.end() ? iter122->second : ClusterList());
 
             const ClusterAssociationMap::const_iterator iter232 = matchedClusters23.find(pCluster2);
             const ClusterList matchedClusters23_pCluster2(iter232 != matchedClusters23.end() ? iter232->second : ClusterList());
 
             for (ClusterVector::const_iterator iter3 = clusterVector3.begin(), iterEnd3 = clusterVector3.end(); iter3 != iterEnd3; ++iter3)
             {
                 const Cluster *const pCluster3 = *iter3;
 
                 if (vetoList.count(pCluster3))
                     continue;
 
                 const ClusterAssociationMap::const_iterator iter233 = matchedClusters23.find(pCluster3);
                 const ClusterList matchedClusters23_pCluster3(iter233 != matchedClusters23.end() ? iter233->second : ClusterList());
 
                 const ClusterAssociationMap::const_iterator iter313 = matchedClusters31.find(pCluster3);
                 const ClusterList matchedClusters31_pCluster3(iter313 != matchedClusters31.end() ? iter313->second : ClusterList());
 
                 const bool match12(
                     (matchedClusters12_pCluster1.size() + matchedClusters12_pCluster2.size() > 0) &&
                     ((matchedClusters12_pCluster1.size() == 1 && std::find(matchedClusters12_pCluster1.begin(), matchedClusters12_pCluster1.end(),
                                                                      pCluster2) != matchedClusters12_pCluster1.end()) ||
                         (matchedClusters12_pCluster1.size() == 0)) &&
                     ((matchedClusters12_pCluster2.size() == 1 && std::find(matchedClusters12_pCluster2.begin(), matchedClusters12_pCluster2.end(),
                                                                      pCluster1) != matchedClusters12_pCluster2.end()) ||
                         (matchedClusters12_pCluster2.size() == 0)));
 
                 const bool match23(
                     (matchedClusters23_pCluster2.size() + matchedClusters23_pCluster3.size() > 0) &&
                     ((matchedClusters23_pCluster2.size() == 1 && std::find(matchedClusters23_pCluster2.begin(), matchedClusters23_pCluster2.end(),
                                                                      pCluster3) != matchedClusters23_pCluster2.end()) ||
                         (matchedClusters23_pCluster2.size() == 0)) &&
                     ((matchedClusters23_pCluster3.size() == 1 && std::find(matchedClusters23_pCluster3.begin(), matchedClusters23_pCluster3.end(),
                                                                      pCluster2) != matchedClusters23_pCluster3.end()) ||
                         (matchedClusters23_pCluster3.size() == 0)));
 
                 const bool match31(
                     (matchedClusters31_pCluster3.size() + matchedClusters31_pCluster1.size() > 0) &&
                     ((matchedClusters31_pCluster3.size() == 1 && std::find(matchedClusters31_pCluster3.begin(), matchedClusters31_pCluster3.end(),
                                                                      pCluster1) != matchedClusters31_pCluster3.end()) ||
                         (matchedClusters31_pCluster3.size() == 0)) &&
                     ((matchedClusters31_pCluster1.size() == 1 && std::find(matchedClusters31_pCluster1.begin(), matchedClusters31_pCluster1.end(),
                                                                      pCluster3) != matchedClusters31_pCluster1.end()) ||
                         (matchedClusters31_pCluster1.size() == 0)));
 
                 if (match12 && match23 && match31)
                 {
                     Particle newParticle;
                     newParticle.m_clusterList.push_back(pCluster1);
                     newParticle.m_clusterList.push_back(pCluster2);
                     newParticle.m_clusterList.push_back(pCluster3);
                     newParticleList.push_back(newParticle);
                 }
             }
         }
     }
 
     return this->RemoveAmbiguities(newParticleList, particleList);
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::MatchTwoViews	(	const pandora::ClusterVector &	clusterVectorU,
		const pandora::ClusterVector &	clusterVectorV,
		const pandora::ClusterVector &	clusterVectorW,
		const ClusterAssociationMap &	clusterAssociationMapUV,
		const ClusterAssociationMap &	clusterAssociationMapVW,
		const ClusterAssociationMap &	clusterAssociationMapWU,
		ParticleList &	particleList
	)		const

private

Create candidate particles using two primary clusters and one pair of broken clusters.

Parameters

clusterVectorU	input vector of clusters from the U view
clusterVectorV	input vector of clusters from the V view
clusterVectorW	input vector of clusters from the W view
clusterAssociationMapUV	map of cluster associations between the U and V views
clusterAssociationMapVW	map of cluster associations between the V and W views
clusterAssociationMapWU	map of cluster associations between the W and U views
particleList	the output list of candidate particles

Definition at line 412 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     ClusterSet vetoList;
     this->BuildVetoList(particleList, vetoList);
 
     ParticleList newParticleList;
 
     for (unsigned int iView = 0; iView < 3; ++iView)
     {
         const ClusterVector &clusterVector1((0 == iView) ? clusterVectorU : (1 == iView) ? clusterVectorV : clusterVectorW);
         const ClusterVector &clusterVector2((0 == iView) ? clusterVectorV : (1 == iView) ? clusterVectorW : clusterVectorU);
         const ClusterVector &clusterVector3((0 == iView) ? clusterVectorW : (1 == iView) ? clusterVectorU : clusterVectorV);
 
         const ClusterAssociationMap &matchedClusters12(((0 == iView) ? matchedClustersUV : (1 == iView) ? matchedClustersVW : matchedClustersWU));
         const ClusterAssociationMap &matchedClusters23(((0 == iView) ? matchedClustersVW : (1 == iView) ? matchedClustersWU : matchedClustersUV));
         const ClusterAssociationMap &matchedClusters31(((0 == iView) ? matchedClustersWU : (1 == iView) ? matchedClustersUV : matchedClustersVW));
 
         for (ClusterVector::const_iterator iter1 = clusterVector1.begin(), iterEnd1 = clusterVector1.end(); iter1 != iterEnd1; ++iter1)
         {
             const Cluster *const pCluster1 = *iter1;
 
             if (vetoList.count(pCluster1))
                 continue;
 
             const ClusterAssociationMap::const_iterator iter311 = matchedClusters31.find(pCluster1);
             const ClusterList matchedClusters31_pCluster1(iter311 != matchedClusters31.end() ? iter311->second : ClusterList());
 
             const ClusterAssociationMap::const_iterator iter121 = matchedClusters12.find(pCluster1);
             const ClusterList matchedClusters12_pCluster1(iter121 != matchedClusters12.end() ? iter121->second : ClusterList());
 
             for (ClusterVector::const_iterator iter2 = clusterVector2.begin(), iterEnd2 = clusterVector2.end(); iter2 != iterEnd2; ++iter2)
             {
                 const Cluster *const pCluster2 = *iter2;
 
                 if (vetoList.count(pCluster2))
                     continue;
 
                 const ClusterAssociationMap::const_iterator iter122 = matchedClusters12.find(pCluster2);
                 const ClusterList matchedClusters12_pCluster2(iter122 != matchedClusters12.end() ? iter122->second : ClusterList());
 
                 const ClusterAssociationMap::const_iterator iter232 = matchedClusters23.find(pCluster2);
                 const ClusterList matchedClusters23_pCluster2(iter232 != matchedClusters23.end() ? iter232->second : ClusterList());
 
                 const bool match12(
                     (matchedClusters12_pCluster1.size() == 1 && std::find(matchedClusters12_pCluster1.begin(), matchedClusters12_pCluster1.end(),
                                                                     pCluster2) != matchedClusters12_pCluster1.end()) &&
                     (matchedClusters12_pCluster2.size() == 1 && std::find(matchedClusters12_pCluster2.begin(), matchedClusters12_pCluster2.end(),
                                                                     pCluster1) != matchedClusters12_pCluster2.end()) &&
                     (matchedClusters23_pCluster2.size() == 0 && matchedClusters31_pCluster1.size() == 0));
 
                 if (!match12)
                     continue;
 
                 Particle newParticle;
                 newParticle.m_clusterList.push_back(pCluster1);
                 newParticle.m_clusterList.push_back(pCluster2);
 
                 for (ClusterVector::const_iterator iter3 = clusterVector3.begin(), iterEnd3 = clusterVector3.end(); iter3 != iterEnd3; ++iter3)
                 {
                     const Cluster *const pCluster3 = *iter3;
 
                     if (vetoList.count(pCluster3))
                         continue;
 
                     const ClusterAssociationMap::const_iterator iter233 = matchedClusters23.find(pCluster3);
                     const ClusterList matchedClusters23_pCluster3(iter233 != matchedClusters23.end() ? iter233->second : ClusterList());
 
                     const ClusterAssociationMap::const_iterator iter313 = matchedClusters31.find(pCluster3);
                     const ClusterList matchedClusters31_pCluster3(iter313 != matchedClusters31.end() ? iter313->second : ClusterList());
 
                     const bool match3((matchedClusters31_pCluster3.size() + matchedClusters23_pCluster3.size() > 0) &&
                                       ((matchedClusters31_pCluster3.size() == 1 &&
                                            std::find(matchedClusters31_pCluster3.begin(), matchedClusters31_pCluster3.end(), pCluster1) !=
                                                matchedClusters31_pCluster3.end()) ||
                                           (matchedClusters31_pCluster3.size() == 0)) &&
                                       ((matchedClusters23_pCluster3.size() == 1 &&
                                            std::find(matchedClusters23_pCluster3.begin(), matchedClusters23_pCluster3.end(), pCluster2) !=
                                                matchedClusters23_pCluster3.end()) ||
                                           (matchedClusters23_pCluster3.size() == 0)));
 
                     if (match3)
                         newParticle.m_clusterList.push_back(pCluster3);
                 }
 
                 newParticleList.push_back(newParticle);
             }
         }
     }
 
     return this->RemoveAmbiguities(newParticleList, particleList);
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::MatchViews	(	const pandora::ClusterVector &	clusterVector1,
		const pandora::ClusterVector &	clusterVector2,
		const TwoDSlidingFitResultMap &	slidingFitResultMap,
		ClusterAssociationMap &	clusterAssociationMap
	)		const

private

Match a pair of cluster vectors and populate the cluster association map.

Parameters

clusterVector1	the input vector of clusters from the first view
clusterVector2	the input vector of clusters from the second view
slidingFitResultMap	the input map of sliding linear fit results
clusterAssociationMap	the output map of cluster associations

Definition at line 158 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     for (ClusterVector::const_iterator iter1 = clusterVector1.begin(), iterEnd1 = clusterVector1.end(); iter1 != iterEnd1; ++iter1)
         this->MatchClusters(*iter1, clusterVector2, slidingFitResultMap, clusterAssociationMap);
 
     for (ClusterVector::const_iterator iter2 = clusterVector2.begin(), iterEnd2 = clusterVector2.end(); iter2 != iterEnd2; ++iter2)
         this->MatchClusters(*iter2, clusterVector1, slidingFitResultMap, clusterAssociationMap);
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::MergeClusters	(	const pandora::ClusterList &	inputClusterList,
		pandora::ClusterList &	outputClusterList
	)		const

private

Merge broken clusters into a single cluster.

Parameters

inputClusterList	the input list of broken clusters
outputClusterList	the output list of merged clusters

Definition at line 692 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     ClusterList clusterListU, clusterListV, clusterListW;
     LArClusterHelper::GetClustersByHitType(inputClusterList, TPC_VIEW_U, clusterListU);
     LArClusterHelper::GetClustersByHitType(inputClusterList, TPC_VIEW_V, clusterListV);
     LArClusterHelper::GetClustersByHitType(inputClusterList, TPC_VIEW_W, clusterListW);
 
     for (unsigned int iView = 0; iView < 3; ++iView)
     {
         const ClusterList clusterList((0 == iView) ? clusterListU : (1 == iView) ? clusterListV : clusterListW);
         const std::string inputClusterListName((0 == iView) ? m_inputClusterListNameU : (1 == iView) ? m_inputClusterListNameV : m_inputClusterListNameW);
 
         if (clusterList.empty())
             continue;
 
         const Cluster *const pSeedCluster(clusterList.front());
 
         if (!PandoraContentApi::IsAvailable(*this, pSeedCluster))
             throw StatusCodeException(STATUS_CODE_FAILURE);
 
         for (const Cluster *const pAssociatedCluster : clusterList)
         {
             if (pAssociatedCluster == pSeedCluster)
                 continue;
 
             if (!PandoraContentApi::IsAvailable(*this, pAssociatedCluster))
                 continue;
 
             PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=,
                 PandoraContentApi::MergeAndDeleteClusters(*this, pSeedCluster, pAssociatedCluster, inputClusterListName, inputClusterListName));
         }
 
         outputClusterList.push_back(pSeedCluster);
     }
 }

StatusCode lar_content::CosmicRayTrackRecoveryAlgorithm::ReadSettings ( const pandora::TiXmlHandle xmlHandle )

private

Definition at line 730 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "ClusterMinLength", m_clusterMinLength));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "ClusterMinSpanZ", m_clusterMinSpanZ));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "ClusterMinOverlapX", m_clusterMinOverlapX));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "ClusterMaxDeltaX", m_clusterMaxDeltaX));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "ClusterMinHits", m_clusterMinHits));
 
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle, "InputClusterListNameU", m_inputClusterListNameU));
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle, "InputClusterListNameV", m_inputClusterListNameV));
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle, "InputClusterListNameW", m_inputClusterListNameW));
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle, "OutputPfoListName", m_outputPfoListName));
 
     return STATUS_CODE_SUCCESS;
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::RemoveAmbiguities	(	const ParticleList &	inputParticleList,
		ParticleList &	outputParticleList
	)		const

private

Remove particles with duplicate clusters.

Parameters

inputParticleList	the input list of candidate particles
outputParticleList	the input list of candidate particles with duplications removed

Definition at line 607 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     for (ParticleList::const_iterator pIter1 = inputParticleList.begin(), pIterEnd1 = inputParticleList.end(); pIter1 != pIterEnd1; ++pIter1)
     {
         const Particle &particle1 = *pIter1;
         const ClusterList &clusterList1 = particle1.m_clusterList;
 
         try
         {
             bool isUnique(true);
 
             for (ParticleList::const_iterator pIter2 = pIter1, pIterEnd2 = inputParticleList.end(); pIter2 != pIterEnd2; ++pIter2)
             {
                 const Particle &particle2 = *pIter2;
                 const ClusterList &clusterList2 = particle2.m_clusterList;
 
                 ClusterSet duplicateSet;
 
                 for (ClusterList::const_iterator cIter1 = clusterList1.begin(), cIterEnd1 = clusterList1.end(); cIter1 != cIterEnd1; ++cIter1)
                 {
                     const Cluster *pCluster = *cIter1;
 
                     if (clusterList2.end() != std::find(clusterList2.begin(), clusterList2.end(), pCluster))
                         duplicateSet.insert(pCluster);
                 }
 
                 if (duplicateSet.size() > 0 && clusterList1.size() != clusterList2.size())
                 {
                     isUnique = false;
                     break;
                 }
             }
 
             if (!isUnique)
                 throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
             outputParticleList.push_back(particle1);
         }
         catch (StatusCodeException &)
         {
             std::cout << " Warning in CosmicRayTrackRecoveryAlgorithm: found duplicate particles in candidate list " << std::endl;
         }
     }
 }

StatusCode lar_content::CosmicRayTrackRecoveryAlgorithm::Run ( )

private

Definition at line 33 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     // Get the available clusters for each view
     ClusterVector availableClustersU, availableClustersV, availableClustersW;
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, this->GetAvailableClusters(m_inputClusterListNameU, availableClustersU));
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, this->GetAvailableClusters(m_inputClusterListNameV, availableClustersV));
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, this->GetAvailableClusters(m_inputClusterListNameW, availableClustersW));
 
     // Select clean clusters in each view
     ClusterVector cleanClustersU, cleanClustersV, cleanClustersW;
     this->SelectCleanClusters(availableClustersU, cleanClustersU);
     this->SelectCleanClusters(availableClustersV, cleanClustersV);
     this->SelectCleanClusters(availableClustersW, cleanClustersW);
 
     // Calculate sliding fit results for clean clusters
     TwoDSlidingFitResultMap slidingFitResultMap;
     this->BuildSlidingFitResultMap(cleanClustersU, slidingFitResultMap);
     this->BuildSlidingFitResultMap(cleanClustersV, slidingFitResultMap);
     this->BuildSlidingFitResultMap(cleanClustersW, slidingFitResultMap);
 
     // Match clusters between pairs of views (using start/end information)
     ClusterAssociationMap matchedClustersUV, matchedClustersVW, matchedClustersWU;
     this->MatchViews(cleanClustersU, cleanClustersV, slidingFitResultMap, matchedClustersUV);
     this->MatchViews(cleanClustersV, cleanClustersW, slidingFitResultMap, matchedClustersVW);
     this->MatchViews(cleanClustersW, cleanClustersU, slidingFitResultMap, matchedClustersWU);
 
     // Create candidate particles using one, two and three primary views
     ParticleList candidateParticles;
 
     this->MatchThreeViews(cleanClustersU, cleanClustersV, cleanClustersW, matchedClustersUV, matchedClustersVW, matchedClustersWU, candidateParticles);
 
     this->MatchTwoViews(cleanClustersU, cleanClustersV, cleanClustersW, matchedClustersUV, matchedClustersVW, matchedClustersWU, candidateParticles);
 
     this->MatchOneView(cleanClustersU, cleanClustersV, cleanClustersW, matchedClustersUV, matchedClustersVW, matchedClustersWU, candidateParticles);
 
     // Build particle flow objects from candidate particles
     this->BuildParticles(candidateParticles);
 
     return STATUS_CODE_SUCCESS;
 }

void lar_content::CosmicRayTrackRecoveryAlgorithm::SelectCleanClusters	(	const pandora::ClusterVector &	inputVector,
		pandora::ClusterVector &	outputVector
	)		const

private

Select a set of clusters judged to be clean.

Parameters

inputVector	the input vector of all available clusters
outputVector	the output vector of clean clusters

Definition at line 103 of file CosmicRayTrackRecoveryAlgorithm.cc.

 {
     for (ClusterVector::const_iterator iter = inputVector.begin(), iterEnd = inputVector.end(); iter != iterEnd; ++iter)
     {
         const Cluster *const pCluster = *iter;
 
         // Remove clusters with insufficient hits for a sliding fit
         if (pCluster->GetNCaloHits() < m_clusterMinHits)
             continue;
         // Remove clusters below a minimum length
         if (LArClusterHelper::GetLengthSquared(pCluster) < m_clusterMinLength * m_clusterMinLength)
             continue;
 
         // Remove clusters nearly parallel to Z or X
         CartesianVector minCoordinate(0.f, 0.f, 0.f);
         CartesianVector maxCoordinate(0.f, 0.f, 0.f);
         LArClusterHelper::GetClusterBoundingBox(pCluster, minCoordinate, maxCoordinate);
 
         const CartesianVector deltaCoordinate(maxCoordinate - minCoordinate);
         if (std::fabs(deltaCoordinate.GetZ()) < m_clusterMinSpanZ || std::fabs(deltaCoordinate.GetX()) < m_clusterMinOverlapX)
             continue;
 
         outputVector.push_back(pCluster);
     }
 }

Member Data Documentation

float lar_content::CosmicRayTrackRecoveryAlgorithm::m_clusterMaxDeltaX

private

Definition at line 172 of file CosmicRayTrackRecoveryAlgorithm.h.

unsigned int lar_content::CosmicRayTrackRecoveryAlgorithm::m_clusterMinHits

private

Definition at line 173 of file CosmicRayTrackRecoveryAlgorithm.h.

float lar_content::CosmicRayTrackRecoveryAlgorithm::m_clusterMinLength

private

Definition at line 169 of file CosmicRayTrackRecoveryAlgorithm.h.

float lar_content::CosmicRayTrackRecoveryAlgorithm::m_clusterMinOverlapX

private

Definition at line 171 of file CosmicRayTrackRecoveryAlgorithm.h.

float lar_content::CosmicRayTrackRecoveryAlgorithm::m_clusterMinSpanZ

private

Definition at line 170 of file CosmicRayTrackRecoveryAlgorithm.h.

std::string lar_content::CosmicRayTrackRecoveryAlgorithm::m_inputClusterListNameU

private

Definition at line 175 of file CosmicRayTrackRecoveryAlgorithm.h.

std::string lar_content::CosmicRayTrackRecoveryAlgorithm::m_inputClusterListNameV

private

Definition at line 176 of file CosmicRayTrackRecoveryAlgorithm.h.

std::string lar_content::CosmicRayTrackRecoveryAlgorithm::m_inputClusterListNameW

private

Definition at line 177 of file CosmicRayTrackRecoveryAlgorithm.h.

std::string lar_content::CosmicRayTrackRecoveryAlgorithm::m_outputPfoListName

private

Definition at line 178 of file CosmicRayTrackRecoveryAlgorithm.h.

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

larpandoracontent/larpandoracontent/LArThreeDReco/LArCosmicRay/CosmicRayTrackRecoveryAlgorithm.h
larpandoracontent/larpandoracontent/LArThreeDReco/LArCosmicRay/CosmicRayTrackRecoveryAlgorithm.cc

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