itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector Class Reference

#include <itkKdTreeBasedKmeansEstimator.h>

Collaboration diagram for itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector:

Detailed Description

template<typename TKdTree>
class itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector

Candidate Vector.

Definition at line 175 of file itkKdTreeBasedKmeansEstimator.h.

Classes
struct	Candidate

Public Member Functions
	CandidateVector ()
void	GetCentroids (InternalParametersType &centroids)
Candidate &	operator[] (int index)
int	Size () const
void	UpdateCentroids ()
virtual	~CandidateVector ()=default
void	SetCentroids (InternalParametersType &centroids)

Private Attributes
std::vector< Candidate >	m_Candidates
MeasurementVectorSizeType	m_MeasurementVectorSize {0}

Constructor & Destructor Documentation

template<typename TKdTree >

itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::CandidateVector ( )

inline

Definition at line 178 of file itkKdTreeBasedKmeansEstimator.h.

template<typename TKdTree >

virtual itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::~CandidateVector ( )

virtualdefault

Member Function Documentation

template<typename TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::GetCentroids ( InternalParametersType &  centroids )

inline

gets the centroids (k-means)

Definition at line 214 of file itkKdTreeBasedKmeansEstimator.h.

template<typename TKdTree >

Candidate& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::operator[] ( int  index )

inline

gets the index-th candidates

Definition at line 246 of file itkKdTreeBasedKmeansEstimator.h.

template<typename TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::SetCentroids ( InternalParametersType &  centroids )

inline

Initialize the centroids with the argument. At each iteration, this should be called before filtering.

Definition at line 196 of file itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Centroid, itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Size, and itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::WeightedCentroid.

template<typename TKdTree >

int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Size ( ) const

inline

returns the number of candidate = k

Definition at line 189 of file itkKdTreeBasedKmeansEstimator.h.

template<typename TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::UpdateCentroids ( )

inline

updates the centroids using the vector sum of measurement vectors that belongs to each centroid and the number of measurement vectors

Definition at line 227 of file itkKdTreeBasedKmeansEstimator.h.

Member Data Documentation

template<typename TKdTree >

std::vector< Candidate > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::m_Candidates

private

internal storage for the candidates

Definition at line 253 of file itkKdTreeBasedKmeansEstimator.h.

template<typename TKdTree >

MeasurementVectorSizeType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::m_MeasurementVectorSize {0}

private

Length of each measurement vector

Definition at line 256 of file itkKdTreeBasedKmeansEstimator.h.

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

• itkKdTreeBasedKmeansEstimator.h