ThreeDLinearFitFeatureTool class for the calculation of variables related to 3d sliding linear fit. More...

#include <TrackShowerIdFeatureTool.h>

Inheritance diagram for lar_content::ThreeDLinearFitFeatureTool:

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

void	Run (LArMvaHelper::MvaFeatureVector &featureVector, const pandora::Algorithm const pAlgorithm, const pandora::ParticleFlowObject const pInputPfo)

Public Member Functions inherited from lar_content::MvaFeatureTool< Ts >
	MvaFeatureTool ()=default
	Default constructor. More...

virtual void	Run (MvaTypes::MvaFeatureVector &featureVector, Ts...args)=0
	Run the algorithm tool. More...

Private Member Functions
pandora::StatusCode	ReadSettings (const pandora::TiXmlHandle xmlHandle)

void	CalculateVariablesSlidingLinearFit (const pandora::Cluster *const pCluster, float &straightLineLengthLarge, float &diffWithStraigthLineMean, float &maxFitGapLength, float &rmsSlidingLinearFit) const
	Calculation of several variables related to sliding linear fit. More...

Private Attributes
unsigned int	m_slidingLinearFitWindow
	The sliding linear fit window. More...

unsigned int	m_slidingLinearFitWindowLarge
	The sliding linear fit window - should be large, providing a simple linear fit. More...

Additional Inherited Members
Public Types inherited from lar_content::MvaFeatureTool< Ts >
typedef std::vector< MvaFeatureTool< Ts... > * >	FeatureToolVector

Detailed Description

ThreeDLinearFitFeatureTool class for the calculation of variables related to 3d sliding linear fit.

Definition at line 141 of file TrackShowerIdFeatureTool.h.

Constructor & Destructor Documentation

lar_content::ThreeDLinearFitFeatureTool::ThreeDLinearFitFeatureTool ( )

Default constructor.

Definition at line 301 of file TrackShowerIdFeatureTool.cc.

                                                        : m_slidingLinearFitWindow(3), m_slidingLinearFitWindowLarge(10000)
 {
 }

Member Function Documentation

void lar_content::ThreeDLinearFitFeatureTool::CalculateVariablesSlidingLinearFit	(	const pandora::Cluster *const	pCluster,
		float &	straightLineLengthLarge,
		float &	diffWithStraigthLineMean,
		float &	maxFitGapLength,
		float &	rmsSlidingLinearFit
	)		const

private

Calculation of several variables related to sliding linear fit.

Parameters

pCluster	the cluster we are characterizing
straightLineLengthLarge	to receive to length reported by the straight line fit
diffWithStraigthLineMean	to receive the difference with straight line mean variable
diffWithStraightLineSigma	to receive the difference with straight line sigma variable
dTdLWidth	to receive the dTdL width variable
maxFitGapLength	to receive the max fit gap length variable
rmsSlidingLinearFit	to receive the RMS from the linear fit

Definition at line 358 of file TrackShowerIdFeatureTool.cc.

 {
     try
     {
         const TwoDSlidingFitResult slidingFitResult(pCluster, m_slidingLinearFitWindow, LArGeometryHelper::GetWireZPitch(this->GetPandora()));
         const TwoDSlidingFitResult slidingFitResultLarge(
             pCluster, m_slidingLinearFitWindowLarge, LArGeometryHelper::GetWireZPitch(this->GetPandora()));
 
         if (slidingFitResult.GetLayerFitResultMap().empty())
             throw StatusCodeException(STATUS_CODE_NOT_INITIALIZED);
 
         straightLineLengthLarge =
             (slidingFitResultLarge.GetGlobalMaxLayerPosition() - slidingFitResultLarge.GetGlobalMinLayerPosition()).GetMagnitude();
         rmsSlidingLinearFit = 0.f;
 
         FloatVector diffWithStraightLineVector;
         const HitType hitType(LArClusterHelper::GetClusterHitType(pCluster));
         CartesianVector previousFitPosition(slidingFitResult.GetGlobalMinLayerPosition());
         float dTdLMin(+std::numeric_limits<float>::max()), dTdLMax(-std::numeric_limits<float>::max());
 
         for (const auto &mapEntry : slidingFitResult.GetLayerFitResultMap())
         {
             const LayerFitResult &layerFitResult(mapEntry.second);
             rmsSlidingLinearFit += layerFitResult.GetRms();
 
             CartesianVector thisFitPosition(0.f, 0.f, 0.f);
             slidingFitResult.GetGlobalPosition(layerFitResult.GetL(), layerFitResult.GetFitT(), thisFitPosition);
 
             LayerFitResultMap::const_iterator iterLarge =
                 slidingFitResultLarge.GetLayerFitResultMap().find(slidingFitResultLarge.GetLayer(layerFitResult.GetL()));
 
             if (slidingFitResultLarge.GetLayerFitResultMap().end() == iterLarge)
                 throw StatusCodeException(STATUS_CODE_FAILURE);
 
             diffWithStraightLineVector.push_back(static_cast<float>(std::fabs(layerFitResult.GetFitT() - iterLarge->second.GetFitT())));
 
             const float thisGapLength((thisFitPosition - previousFitPosition).GetMagnitude());
             const float minZ(std::min(thisFitPosition.GetZ(), previousFitPosition.GetZ()));
             const float maxZ(std::max(thisFitPosition.GetZ(), previousFitPosition.GetZ()));
 
             if ((maxZ - minZ) > std::numeric_limits<float>::epsilon())
             {
                 const float gapZ(LArGeometryHelper::CalculateGapDeltaZ(this->GetPandora(), minZ, maxZ, hitType));
                 const float correctedGapLength(thisGapLength * (1.f - gapZ / (maxZ - minZ)));
 
                 if (correctedGapLength > maxFitGapLength)
                     maxFitGapLength = correctedGapLength;
             }
             else
             {
                 maxFitGapLength = 0.f;
             }
 
             dTdLMin = std::min(dTdLMin, static_cast<float>(layerFitResult.GetGradient()));
             dTdLMax = std::max(dTdLMax, static_cast<float>(layerFitResult.GetGradient()));
             previousFitPosition = thisFitPosition;
         }
 
         if (diffWithStraightLineVector.empty())
             throw StatusCodeException(STATUS_CODE_FAILURE);
 
         diffWithStraightLineMean = 0.f;
 
         for (const float diffWithStraightLine : diffWithStraightLineVector)
             diffWithStraightLineMean += diffWithStraightLine;
 
         diffWithStraightLineMean /= static_cast<float>(diffWithStraightLineVector.size());
     }
     catch (const StatusCodeException &)
     {
         straightLineLengthLarge = -1.f;
         diffWithStraightLineMean = -1.f;
         maxFitGapLength = -1.f;
         rmsSlidingLinearFit = -1.f;
     }
 }

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

private

Definition at line 438 of file TrackShowerIdFeatureTool.cc.

 {
     PANDORA_RETURN_RESULT_IF_AND_IF(
         STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle, "SlidingLinearFitWindow", m_slidingLinearFitWindow));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=,
         XmlHelper::ReadValue(xmlHandle, "SlidingLinearFitWindowLarge", m_slidingLinearFitWindowLarge));
 
     return STATUS_CODE_SUCCESS;
 }

void lar_content::ThreeDLinearFitFeatureTool::Run	(	LArMvaHelper::MvaFeatureVector &	featureVector,
		const pandora::Algorithm *const	pAlgorithm,
		const pandora::ParticleFlowObject *const	pInputPfo
	)

Definition at line 307 of file TrackShowerIdFeatureTool.cc.

 {
     if (PandoraContentApi::GetSettings(*pAlgorithm)->ShouldDisplayAlgorithmInfo())
         std::cout << "----> Running Algorithm Tool: " << this->GetInstanceName() << ", " << this->GetType() << std::endl;
 
     ClusterList clusterList;
     LArPfoHelper::GetTwoDClusterList(pInputPfo, clusterList);
     float diffWithStraightLineMean(0.f), maxFitGapLength(0.f), rmsSlidingLinearFit(0.f);
     LArMvaHelper::MvaFeature length, diff, gap, rms;
     unsigned int nClustersUsed(0);
 
     for (const Cluster *const pCluster : clusterList)
     {
         float straightLineLengthLargeCluster(-1.f), diffWithStraightLineMeanCluster(-1.f), maxFitGapLengthCluster(-1.f),
             rmsSlidingLinearFitCluster(-1.f);
 
         this->CalculateVariablesSlidingLinearFit(
             pCluster, straightLineLengthLargeCluster, diffWithStraightLineMeanCluster, maxFitGapLengthCluster, rmsSlidingLinearFitCluster);
 
         if (straightLineLengthLargeCluster > std::numeric_limits<float>::epsilon())
         {
             diffWithStraightLineMeanCluster /= straightLineLengthLargeCluster;
             maxFitGapLengthCluster /= straightLineLengthLargeCluster;
             rmsSlidingLinearFitCluster /= straightLineLengthLargeCluster;
 
             diffWithStraightLineMean += diffWithStraightLineMeanCluster;
             maxFitGapLength += maxFitGapLengthCluster;
             rmsSlidingLinearFit += rmsSlidingLinearFitCluster;
 
             ++nClustersUsed;
         }
     }
 
     if (nClustersUsed > 0)
     {
         const float nClusters(static_cast<float>(nClustersUsed));
         length = std::sqrt(LArPfoHelper::GetThreeDLengthSquared(pInputPfo));
         diff = diffWithStraightLineMean / nClusters;
         gap = maxFitGapLength / nClusters;
         rms = rmsSlidingLinearFit / nClusters;
     }
 
     featureVector.push_back(length);
     featureVector.push_back(diff);
     featureVector.push_back(gap);
     featureVector.push_back(rms);
 }

Member Data Documentation

unsigned int lar_content::ThreeDLinearFitFeatureTool::m_slidingLinearFitWindow

private

The sliding linear fit window.

Definition at line 168 of file TrackShowerIdFeatureTool.h.

unsigned int lar_content::ThreeDLinearFitFeatureTool::m_slidingLinearFitWindowLarge

private

The sliding linear fit window - should be large, providing a simple linear fit.

Definition at line 169 of file TrackShowerIdFeatureTool.h.

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

larpandoracontent/larpandoracontent/LArTrackShowerId/TrackShowerIdFeatureTool.h
larpandoracontent/larpandoracontent/LArTrackShowerId/TrackShowerIdFeatureTool.cc

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation