lar_content::LArPcaHelper Class Reference

LArPcaHelper class. More...

#include <LArPcaHelper.h>

Public Types
typedef pandora::CartesianVector	EigenValues
typedef std::vector< pandora::CartesianVector >	EigenVectors
typedef std::pair< const pandora::CartesianVector, double >	WeightedPoint
typedef std::vector< WeightedPoint >	WeightedPointVector

Public Member Functions
template<typename T >
void	RunPca (const T &t, CartesianVector &centroid, EigenValues &outputEigenValues, EigenVectors &outputEigenVectors)

Static Public Member Functions
template<typename T >
static void	RunPca (const T &t, pandora::CartesianVector &centroid, EigenValues &outputEigenValues, EigenVectors &outputEigenVectors)
	Run principal component analysis using input calo hits (TPC_VIEW_U,V,W or TPC_3D; all treated as 3D points) More...
static void	RunPca (const WeightedPointVector &pointVector, pandora::CartesianVector &centroid, EigenValues &outputEigenValues, EigenVectors &outputEigenVectors)
	Run principal component analysis using weighted input Cartesian vectors (TPC_VIEW_U,V,W or TPC_3D; all treated as 3D points) More...

Detailed Description

LArPcaHelper class.

Definition at line 21 of file LArPcaHelper.h.

Member Typedef Documentation

typedef pandora::CartesianVector lar_content::LArPcaHelper::EigenValues

Definition at line 24 of file LArPcaHelper.h.

typedef std::vector<pandora::CartesianVector> lar_content::LArPcaHelper::EigenVectors

Definition at line 25 of file LArPcaHelper.h.

typedef std::pair<const pandora::CartesianVector, double> lar_content::LArPcaHelper::WeightedPoint

Definition at line 26 of file LArPcaHelper.h.

typedef std::vector<WeightedPoint> lar_content::LArPcaHelper::WeightedPointVector

Definition at line 27 of file LArPcaHelper.h.

Member Function Documentation

template<typename T >

void lar_content::LArPcaHelper::RunPca	(	const T &	t,
		CartesianVector &	centroid,
		EigenValues &	outputEigenValues,
		EigenVectors &	outputEigenVectors
	)

Definition at line 21 of file LArPcaHelper.cc.

{
    WeightedPointVector weightedPointVector;

    for (const auto &point : t)
        weightedPointVector.push_back(std::make_pair(LArObjectHelper::TypeAdaptor::GetPosition(point), 1.));

    return LArPcaHelper::RunPca(weightedPointVector, centroid, outputEigenValues, outputEigenVectors);
}

template<typename T >

static void lar_content::LArPcaHelper::RunPca ( const T &  t, pandora::CartesianVector &  centroid, EigenValues &  outputEigenValues, EigenVectors &  outputEigenVectors  )

static

Run principal component analysis using input calo hits (TPC_VIEW_U,V,W or TPC_3D; all treated as 3D points)

Parameters

t	the input information
centroid	to receive the centroid position
outputEigenValues	to receive the eigen values
outputEigenVectors	to receive the eigen vectors

static void lar_content::LArPcaHelper::RunPca ( const WeightedPointVector &  pointVector, pandora::CartesianVector &  centroid, EigenValues &  outputEigenValues, EigenVectors &  outputEigenVectors  )

static

Run principal component analysis using weighted input Cartesian vectors (TPC_VIEW_U,V,W or TPC_3D; all treated as 3D points)

Parameters

pointVector	a vector of pairs of positions and weights
centroid	to receive the centroid position
outputEigenValues	to receive the eigen values
outputEigenVectors	to receive the eigen vectors

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

• larpandoracontent/larpandoracontent/LArHelpers/LArPcaHelper.h
• larpandoracontent/larpandoracontent/LArHelpers/LArPcaHelper.cc