ParticleRecoveryAlgorithm class. More...

#include <ParticleRecoveryAlgorithm.h>

Inheritance diagram for lar_content::ParticleRecoveryAlgorithm:

Classes
class	SimpleOverlapTensor
	SimpleOverlapTensor class. More...

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

Private Member Functions
pandora::StatusCode	Run ()

void	GetInputClusters (pandora::ClusterList &inputClusterListU, pandora::ClusterList &inputClusterListV, pandora::ClusterList &inputClusterListW) const
	Get the input cluster lists for processing in this algorithm. More...

void	SelectInputClusters (const pandora::ClusterList &inputClusterList, pandora::ClusterList &selectedClusterList) const
	Select a subset of input clusters for processing in this algorithm. More...

void	StandardClusterSelection (const pandora::ClusterList &inputClusterList, pandora::ClusterList &selectedClusterList) const
	Select a subset of input clusters for processing in this algorithm. More...

void	VertexClusterSelection (const pandora::ClusterList &inputClusterList, pandora::ClusterList &selectedClusterList) const
	Select a subset of input clusters nodally associated with the vertices of existing particles. More...

void	FindOverlaps (const pandora::ClusterList &clusterList1, const pandora::ClusterList &clusterList2, SimpleOverlapTensor &overlapTensor) const
	Find cluster overlaps and record these in the overlap tensor. More...

bool	IsOverlap (const pandora::Cluster const pCluster1, const pandora::Cluster const pCluster2) const
	Whether two clusters overlap convincingly in x. More...

void	CalculateEffectiveOverlapFractions (const pandora::Cluster const pCluster1, const float xMin1, const float xMax1, const pandora::Cluster const pCluster2, const float xMin2, const float xMax2, float &xOverlapFraction1, float &xOverlapFraction2) const
	Calculate effective overlap fractions taking into account gaps. More...

void	CalculateEffectiveSpan (const pandora::Cluster *const pCluster, const float xMin, const float xMax, float &xMinEff, float &xMaxEff) const
	Calculate effective span for a given clsuter taking gaps into account. More...

void	ExamineTensor (const SimpleOverlapTensor &overlapTensor) const
	Identify unambiguous cluster overlaps and resolve ambiguous overlaps, creating new track particles. More...

bool	CheckConsistency (const pandora::Cluster const pClusterU, const pandora::Cluster const pClusterV, const pandora::Cluster *const pClusterW) const
	Whether a trio of clusters are consistent with representing projections of the same 3d trajectory. More...

void	CreateTrackParticle (const pandora::ClusterList &clusterList) const
	Create and save a track particle containing the provided clusters. More...

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

Private Attributes
pandora::StringVector	m_inputClusterListNames
	The list of cluster list names. More...

std::string	m_outputPfoListName
	The output pfo list name. More...

bool	m_checkGaps
	Whether to check for gaps in the calculation of the overlap. More...

unsigned int	m_minClusterCaloHits
	The min number of hits in base cluster selection method. More...

float	m_minClusterLengthSquared
	The min length (squared) in base cluster selection method. More...

float	m_minClusterXSpan
	The min x span required in order to consider a cluster. More...

bool	m_vertexClusterMode
	Whether to demand clusters are associated with vertices of existing particles. More...

float	m_minVertexLongitudinalDistance
	Vertex association check: min longitudinal distance cut. More...

float	m_maxVertexTransverseDistance
	Vertex association check: max transverse distance cut. More...

float	m_minXOverlapFraction
	The min x overlap fraction required in order to id overlapping clusters. More...

float	m_minXOverlapFractionGaps
	The min x overlap fraction when there are gaps involved. More...

float	m_sampleStepSize
	The sampling step size used in association checks, units cm. More...

unsigned int	m_slidingFitHalfWindow
	The half window for the fit sliding result constructor. More...

float	m_pseudoChi2Cut
	The selection cut on the matched chi2. More...

Detailed Description

ParticleRecoveryAlgorithm class.

Definition at line 21 of file ParticleRecoveryAlgorithm.h.

Constructor & Destructor Documentation

lar_content::ParticleRecoveryAlgorithm::ParticleRecoveryAlgorithm ( )

Default constructor.

Definition at line 26 of file ParticleRecoveryAlgorithm.cc.

                                                      :
     m_checkGaps(true),
     m_minClusterCaloHits(20),
     m_minClusterLengthSquared(5.f * 5.f),
     m_minClusterXSpan(0.25f),
     m_vertexClusterMode(false),
     m_minVertexLongitudinalDistance(-2.5f),
     m_maxVertexTransverseDistance(1.5f),
     m_minXOverlapFraction(0.75f),
     m_minXOverlapFractionGaps(0.75f),
     m_sampleStepSize(0.5f),
     m_slidingFitHalfWindow(10),
     m_pseudoChi2Cut(5.f)
 {
 }

Member Function Documentation

void lar_content::ParticleRecoveryAlgorithm::CalculateEffectiveOverlapFractions	(	const pandora::Cluster *const	pCluster1,
		const float	xMin1,
		const float	xMax1,
		const pandora::Cluster *const	pCluster2,
		const float	xMin2,
		const float	xMax2,
		float &	xOverlapFraction1,
		float &	xOverlapFraction2
	)		const

private

Calculate effective overlap fractions taking into account gaps.

Parameters

pCluster1	address of the first cluster
xMin1	min x value of the first cluster
xMax1	max x value of the first cluster
pCluster2	address of the second cluster
xMin2	min x value of the second cluster
xMax2	max x value of the second cluster
xOverlapFraction1	to receive the effective overlap fraction for the first cluster
xOverlapFraction2	to receive the effective overlap fraction for the second cluster

Definition at line 234 of file ParticleRecoveryAlgorithm.cc.

 {
     if (PandoraContentApi::GetGeometry(*this)->GetDetectorGapList().empty())
         return;
 
     const float xMin(std::min(xMin1, xMin2));
     const float xMax(std::max(xMax1, xMax2));
     float xMinEff1(xMin1), xMaxEff1(xMax1), xMinEff2(xMin2), xMaxEff2(xMax2);
 
     this->CalculateEffectiveSpan(pCluster1, xMin, xMax, xMinEff1, xMaxEff1);
     this->CalculateEffectiveSpan(pCluster2, xMin, xMax, xMinEff2, xMaxEff2);
 
     const float effectiveXSpan1(xMaxEff1 - xMinEff1), effectiveXSpan2(xMaxEff2 - xMinEff2);
     const float effectiveXOverlapSpan(std::min(xMaxEff1, xMaxEff2) - std::max(xMinEff1, xMinEff2));
 
     if ((effectiveXSpan1 > std::numeric_limits<float>::epsilon()) && (effectiveXSpan2 > std::numeric_limits<float>::epsilon()))
     {
         xOverlapFraction1 = std::min(1.f, (effectiveXOverlapSpan / effectiveXSpan1));
         xOverlapFraction2 = std::min(1.f, (effectiveXOverlapSpan / effectiveXSpan2));
     }
 }

void lar_content::ParticleRecoveryAlgorithm::CalculateEffectiveSpan	(	const pandora::Cluster *const	pCluster,
		const float	xMin,
		const float	xMax,
		float &	xMinEff,
		float &	xMaxEff
	)		const

private

Calculate effective span for a given clsuter taking gaps into account.

Parameters

pCluster	address of the cluster
xMin	the min x value above which checks for gaps will be performed
xMax	the max x value below which checks for gaps will be performed
xMinEff	to receive the effective min x value for the cluster, including adjacent gaps
xMaxEff	to receive the effective max x value for the cluster, including adjacent gaps

Definition at line 259 of file ParticleRecoveryAlgorithm.cc.

 {
     // TODO cache sliding linear fit results and optimise protection against exceptions from TwoDSlidingFitResult and IsXSamplingPointInGap
     try
     {
         const float slidingFitPitch(LArGeometryHelper::GetWireZPitch(this->GetPandora()));
 
         const TwoDSlidingFitResult slidingFitResult(pCluster, m_slidingFitHalfWindow, slidingFitPitch);
 
         const int nSamplingPointsLeft(1 + static_cast<int>((xMinEff - xMin) / m_sampleStepSize));
         const int nSamplingPointsRight(1 + static_cast<int>((xMax - xMaxEff) / m_sampleStepSize));
         float dxMin(0.f), dxMax(0.f);
 
         for (int iSample = 1; iSample <= nSamplingPointsLeft; ++iSample)
         {
             const float xSample(std::max(xMin, xMinEff - static_cast<float>(iSample) * m_sampleStepSize));
 
             if (!LArGeometryHelper::IsXSamplingPointInGap(this->GetPandora(), xSample, slidingFitResult, m_sampleStepSize))
                 break;
 
             dxMin = xMinEff - xSample;
         }
 
         for (int iSample = 1; iSample <= nSamplingPointsRight; ++iSample)
         {
             const float xSample(std::min(xMax, xMaxEff + static_cast<float>(iSample) * m_sampleStepSize));
 
             if (!LArGeometryHelper::IsXSamplingPointInGap(this->GetPandora(), xSample, slidingFitResult, m_sampleStepSize))
                 break;
 
             dxMax = xSample - xMaxEff;
         }
 
         xMinEff = xMinEff - dxMin;
         xMaxEff = xMaxEff + dxMax;
     }
     catch (StatusCodeException &)
     {
     }
 }

bool lar_content::ParticleRecoveryAlgorithm::CheckConsistency	(	const pandora::Cluster *const	pClusterU,
		const pandora::Cluster *const	pClusterV,
		const pandora::Cluster *const	pClusterW
	)		const

private

Whether a trio of clusters are consistent with representing projections of the same 3d trajectory.

Parameters

pClusterU	the address of cluster u
pClusterV	the address of cluster v
pClusterW	the address of cluster w

Returns: boolean

Definition at line 341 of file ParticleRecoveryAlgorithm.cc.

 {
     // Requirements on X matching
     float xMinU(0.f), xMinV(0.f), xMinW(0.f), xMaxU(0.f), xMaxV(0.f), xMaxW(0.f);
     pClusterU->GetClusterSpanX(xMinU, xMaxU);
     pClusterV->GetClusterSpanX(xMinV, xMaxV);
     pClusterW->GetClusterSpanX(xMinW, xMaxW);
 
     const float xMin(std::max(xMinU, std::max(xMinV, xMinW)));
     const float xMax(std::min(xMaxU, std::min(xMaxV, xMaxW)));
     const float xOverlap(xMax - xMin);
 
     if (xOverlap < std::numeric_limits<float>::epsilon())
         return false;
 
     // Requirements on 3D matching
     float u(std::numeric_limits<float>::max()), v(std::numeric_limits<float>::max()), w(std::numeric_limits<float>::max());
 
     if ((STATUS_CODE_SUCCESS != LArClusterHelper::GetAverageZ(pClusterU, xMin, xMax, u)) ||
         (STATUS_CODE_SUCCESS != LArClusterHelper::GetAverageZ(pClusterV, xMin, xMax, v)) ||
         (STATUS_CODE_SUCCESS != LArClusterHelper::GetAverageZ(pClusterW, xMin, xMax, w)))
     {
         return false;
     }
 
     const float uv2w(LArGeometryHelper::MergeTwoPositions(this->GetPandora(), TPC_VIEW_U, TPC_VIEW_V, u, v));
     const float vw2u(LArGeometryHelper::MergeTwoPositions(this->GetPandora(), TPC_VIEW_V, TPC_VIEW_W, v, w));
     const float wu2v(LArGeometryHelper::MergeTwoPositions(this->GetPandora(), TPC_VIEW_W, TPC_VIEW_U, w, u));
 
     const float pseudoChi2(((u - vw2u) * (u - vw2u) + (v - wu2v) * (v - wu2v) + (w - uv2w) * (w - uv2w)) / 3.f);
 
     if (pseudoChi2 > m_pseudoChi2Cut)
         return false;
 
     return true;
 }

void lar_content::ParticleRecoveryAlgorithm::CreateTrackParticle ( const pandora::ClusterList & clusterList ) const

private

Create and save a track particle containing the provided clusters.

Parameters

clusterList the cluster list

Definition at line 380 of file ParticleRecoveryAlgorithm.cc.

 {
     if (clusterList.size() < 2)
         throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
     const PfoList *pPfoList = NULL;
     std::string pfoListName;
     PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::CreateTemporaryListAndSetCurrent(*this, pPfoList, pfoListName));
 
     // TODO Correct these placeholder parameters
     PandoraContentApi::ParticleFlowObject::Parameters pfoParameters;
     pfoParameters.m_particleId = MU_MINUS;
     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(NULL);
     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));
         PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::ReplaceCurrentList<Pfo>(*this, m_outputPfoListName));
     }
 }

void lar_content::ParticleRecoveryAlgorithm::ExamineTensor ( const SimpleOverlapTensor & overlapTensor ) const

private

Identify unambiguous cluster overlaps and resolve ambiguous overlaps, creating new track particles.

Parameters

overlapTensor the overlap tensor

Definition at line 303 of file ParticleRecoveryAlgorithm.cc.

 {
     ClusterVector sortedKeyClusters(overlapTensor.GetKeyClusters().begin(), overlapTensor.GetKeyClusters().end());
     std::sort(sortedKeyClusters.begin(), sortedKeyClusters.end(), LArClusterHelper::SortByNHits);
 
     for (const Cluster *const pKeyCluster : sortedKeyClusters)
     {
         ClusterList clusterListU, clusterListV, clusterListW;
 
         overlapTensor.GetConnectedElements(pKeyCluster, true, clusterListU, clusterListV, clusterListW);
         const unsigned int nU(clusterListU.size()), nV(clusterListV.size()), nW(clusterListW.size());
 
         if ((0 == nU * nV) && (0 == nV * nW) && (0 == nW * nU))
             continue;
 
         ClusterList clusterListAll;
         clusterListAll.insert(clusterListAll.end(), clusterListU.begin(), clusterListU.end());
         clusterListAll.insert(clusterListAll.end(), clusterListV.begin(), clusterListV.end());
         clusterListAll.insert(clusterListAll.end(), clusterListW.begin(), clusterListW.end());
 
         if ((1 == nU * nV * nW) && this->CheckConsistency(*(clusterListU.begin()), *(clusterListV.begin()), *(clusterListW.begin())))
         {
             this->CreateTrackParticle(clusterListAll);
         }
         else if ((0 == nU * nV * nW) && ((1 == nU && 1 == nV) || (1 == nV && 1 == nW) || (1 == nW && 1 == nU)))
         {
             this->CreateTrackParticle(clusterListAll);
         }
         else
         {
             // TODO - check here whether there is a gap in the 2 in one view when 1:2:0
             // May later choose to resolve simple ambiguities, e.g. of form nU:nV:nW == 1:2:0
         }
     }
 }

void lar_content::ParticleRecoveryAlgorithm::FindOverlaps	(	const pandora::ClusterList &	clusterList1,
		const pandora::ClusterList &	clusterList2,
		SimpleOverlapTensor &	overlapTensor
	)		const

private

Find cluster overlaps and record these in the overlap tensor.

Parameters

clusterList1	the first cluster list
clusterList2	the second cluster list
overlapTensor	the overlap tensor

Definition at line 188 of file ParticleRecoveryAlgorithm.cc.

 {
     for (ClusterList::const_iterator iter1 = clusterList1.begin(), iter1End = clusterList1.end(); iter1 != iter1End; ++iter1)
     {
         for (ClusterList::const_iterator iter2 = clusterList2.begin(), iter2End = clusterList2.end(); iter2 != iter2End; ++iter2)
         {
             if (this->IsOverlap(*iter1, *iter2))
                 overlapTensor.AddAssociation(*iter1, *iter2);
         }
     }
 }

void lar_content::ParticleRecoveryAlgorithm::GetInputClusters	(	pandora::ClusterList &	inputClusterListU,
		pandora::ClusterList &	inputClusterListV,
		pandora::ClusterList &	inputClusterListW
	)		const

private

Get the input cluster lists for processing in this algorithm.

Parameters

inputClusterListU	to receive the list of clusters in the u view
inputClusterListU	to receive the list of clusters in the v view
inputClusterListU	to receive the list of clusters in the w view

Definition at line 65 of file ParticleRecoveryAlgorithm.cc.

 {
     for (StringVector::const_iterator iter = m_inputClusterListNames.begin(), iterEnd = m_inputClusterListNames.end(); iter != iterEnd; ++iter)
     {
         const ClusterList *pClusterList(NULL);
         PANDORA_THROW_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_INITIALIZED, !=, PandoraContentApi::GetList(*this, *iter, pClusterList));
 
         if (!pClusterList || pClusterList->empty())
         {
             if (PandoraContentApi::GetSettings(*this)->ShouldDisplayAlgorithmInfo())
                 std::cout << "ParticleRecoveryAlgorithm: unable to find cluster list " << *iter << std::endl;
 
             continue;
         }
 
         for (ClusterList::const_iterator cIter = pClusterList->begin(), cIterEnd = pClusterList->end(); cIter != cIterEnd; ++cIter)
         {
             const Cluster *const pCluster(*cIter);
             const HitType hitType(LArClusterHelper::GetClusterHitType(pCluster));
 
             if ((TPC_VIEW_U != hitType) && (TPC_VIEW_V != hitType) && (TPC_VIEW_W != hitType))
                 throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
             ClusterList &clusterList((TPC_VIEW_U == hitType) ? inputClusterListU : (TPC_VIEW_V == hitType) ? inputClusterListV : inputClusterListW);
             clusterList.push_back(pCluster);
         }
     }
 }

bool lar_content::ParticleRecoveryAlgorithm::IsOverlap	(	const pandora::Cluster *const	pCluster1,
		const pandora::Cluster *const	pCluster2
	)		const

private

Whether two clusters overlap convincingly in x.

Parameters

pCluster1	address of the first cluster
pCluster2	address of the second cluster

Definition at line 202 of file ParticleRecoveryAlgorithm.cc.

 {
     if (LArClusterHelper::GetClusterHitType(pCluster1) == LArClusterHelper::GetClusterHitType(pCluster2))
         throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
     if ((0 == pCluster1->GetNCaloHits()) || (0 == pCluster2->GetNCaloHits()))
         throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
     float xMin1(0.f), xMax1(0.f), xMin2(0.f), xMax2(0.f);
     pCluster1->GetClusterSpanX(xMin1, xMax1);
     pCluster2->GetClusterSpanX(xMin2, xMax2);
 
     const float xSpan1(xMax1 - xMin1), xSpan2(xMax2 - xMin2);
 
     if ((xSpan1 < std::numeric_limits<float>::epsilon()) || (xSpan2 < std::numeric_limits<float>::epsilon()))
         throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
     const float xOverlap(std::min(xMax1, xMax2) - std::max(xMin1, xMin2));
 
     float xOverlapFraction1(xOverlap / xSpan1), xOverlapFraction2(xOverlap / xSpan2);
 
     if (m_checkGaps)
         this->CalculateEffectiveOverlapFractions(pCluster1, xMin1, xMax1, pCluster2, xMin2, xMax2, xOverlapFraction1, xOverlapFraction2);
 
     if ((xOverlapFraction1 < m_minXOverlapFraction) || (xOverlapFraction2 < m_minXOverlapFraction))
         return false;
 
     return true;
 }

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

private

Definition at line 481 of file ParticleRecoveryAlgorithm.cc.

 {
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadVectorOfValues(xmlHandle, "InputClusterListNames", m_inputClusterListNames));
     PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle, "OutputPfoListName", m_outputPfoListName));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "MinClusterCaloHits", m_minClusterCaloHits));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "CheckGaps", m_checkGaps));
 
     float minClusterLength = std::sqrt(m_minClusterLengthSquared);
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "MinClusterLength", minClusterLength));
     m_minClusterLengthSquared = minClusterLength * minClusterLength;
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "MinClusterXSpan", m_minClusterXSpan));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "VertexClusterMode", m_vertexClusterMode));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=,
         XmlHelper::ReadValue(xmlHandle, "MinVertexLongitudinalDistance", m_minVertexLongitudinalDistance));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=,
         XmlHelper::ReadValue(xmlHandle, "MaxVertexTransverseDistance", m_maxVertexTransverseDistance));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "MinXOverlapFraction", m_minXOverlapFraction));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=,
         XmlHelper::ReadValue(xmlHandle, "MinXOverlapFractionGaps", m_minXOverlapFractionGaps));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "SampleStepSize", m_sampleStepSize));
 
     if (m_sampleStepSize < std::numeric_limits<float>::epsilon())
     {
         std::cout << "ParticleRecoveryAlgorithm: Invalid value for SampleStepSize " << m_sampleStepSize << std::endl;
         throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
     }
 
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "SlidingFitHalfWindow", m_slidingFitHalfWindow));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "PseudoChi2Cut", m_pseudoChi2Cut));
 
     return STATUS_CODE_SUCCESS;
 }

StatusCode lar_content::ParticleRecoveryAlgorithm::Run ( )

private

Definition at line 44 of file ParticleRecoveryAlgorithm.cc.

 {
     ClusterList inputClusterListU, inputClusterListV, inputClusterListW;
     this->GetInputClusters(inputClusterListU, inputClusterListV, inputClusterListW);
 
     ClusterList selectedClusterListU, selectedClusterListV, selectedClusterListW;
     this->SelectInputClusters(inputClusterListU, selectedClusterListU);
     this->SelectInputClusters(inputClusterListV, selectedClusterListV);
     this->SelectInputClusters(inputClusterListW, selectedClusterListW);
 
     SimpleOverlapTensor overlapTensor;
     this->FindOverlaps(selectedClusterListU, selectedClusterListV, overlapTensor);
     this->FindOverlaps(selectedClusterListV, selectedClusterListW, overlapTensor);
     this->FindOverlaps(selectedClusterListW, selectedClusterListU, overlapTensor);
     this->ExamineTensor(overlapTensor);
 
     return STATUS_CODE_SUCCESS;
 }

void lar_content::ParticleRecoveryAlgorithm::SelectInputClusters	(	const pandora::ClusterList &	inputClusterList,
		pandora::ClusterList &	selectedClusterList
	)		const

private

Select a subset of input clusters for processing in this algorithm.

Parameters

inputClusterList	the input cluster list
selectedClusterList	to receive the selected cluster list

Definition at line 96 of file ParticleRecoveryAlgorithm.cc.

 {
     if (m_vertexClusterMode)
     {
         ClusterList vertexClusterList;
         this->VertexClusterSelection(inputClusterList, vertexClusterList);
         this->StandardClusterSelection(vertexClusterList, selectedClusterList);
     }
     else
     {
         this->StandardClusterSelection(inputClusterList, selectedClusterList);
     }
 }

void lar_content::ParticleRecoveryAlgorithm::StandardClusterSelection	(	const pandora::ClusterList &	inputClusterList,
		pandora::ClusterList &	selectedClusterList
	)		const

private

Select a subset of input clusters for processing in this algorithm.

Parameters

inputClusterList	the input cluster list
selectedClusterList	to receive the selected cluster list

Definition at line 112 of file ParticleRecoveryAlgorithm.cc.

 {
     for (ClusterList::const_iterator iter = inputClusterList.begin(), iterEnd = inputClusterList.end(); iter != iterEnd; ++iter)
     {
         const Cluster *const pCluster = *iter;
 
         if (!pCluster->IsAvailable())
             continue;
 
         if (pCluster->GetNCaloHits() < m_minClusterCaloHits)
             continue;
 
         if (LArClusterHelper::GetLengthSquared(pCluster) < m_minClusterLengthSquared)
             continue;
 
         float xMin(0.f), xMax(0.f);
         pCluster->GetClusterSpanX(xMin, xMax);
 
         if ((xMax - xMin) < m_minClusterXSpan)
             continue;
 
         selectedClusterList.push_back(pCluster);
     }
 }

void lar_content::ParticleRecoveryAlgorithm::VertexClusterSelection	(	const pandora::ClusterList &	inputClusterList,
		pandora::ClusterList &	selectedClusterList
	)		const

private

Select a subset of input clusters nodally associated with the vertices of existing particles.

Parameters

inputClusterList	the input cluster list
selectedClusterList	to receive the selected cluster list

Definition at line 139 of file ParticleRecoveryAlgorithm.cc.

 {
     CartesianPointVector vertexList;
 
     for (ClusterList::const_iterator iter = inputClusterList.begin(), iterEnd = inputClusterList.end(); iter != iterEnd; ++iter)
     {
         try
         {
             if (!(*iter)->IsAvailable())
             {
                 const LArPointingCluster pointingCluster(*iter);
                 vertexList.push_back(pointingCluster.GetInnerVertex().GetPosition());
                 vertexList.push_back(pointingCluster.GetOuterVertex().GetPosition());
             }
         }
         catch (StatusCodeException &)
         {
         }
     }
 
     for (ClusterList::const_iterator iter = inputClusterList.begin(), iterEnd = inputClusterList.end(); iter != iterEnd; ++iter)
     {
         try
         {
             const Cluster *const pCluster = *iter;
 
             if (!pCluster->IsAvailable())
                 continue;
 
             const LArPointingCluster pointingCluster(pCluster);
 
             for (CartesianPointVector::const_iterator vIter = vertexList.begin(), vIterEnd = vertexList.end(); vIter != vIterEnd; ++vIter)
             {
                 if (LArPointingClusterHelper::IsNode(*vIter, pointingCluster.GetInnerVertex(), m_minVertexLongitudinalDistance, m_maxVertexTransverseDistance) ||
                     LArPointingClusterHelper::IsNode(*vIter, pointingCluster.GetOuterVertex(), m_minVertexLongitudinalDistance, m_maxVertexTransverseDistance))
                 {
                     selectedClusterList.push_back(pCluster);
                     break;
                 }
             }
         }
         catch (StatusCodeException &)
         {
         }
     }
 }