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

#include <itkKdTreeBasedKmeansEstimator.h>

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

Classes
struct	Candidate

Public Member Functions
	CandidateVector ()=default
int	Size () const
virtual	~CandidateVector ()=default
std::vector< Candidate >	m_Candidates
MeasurementVectorSizeType	m_MeasurementVectorSize { 0 }
void	SetCentroids (InternalParametersType &centroids)
void	GetCentroids (InternalParametersType &centroids)
void	UpdateCentroids ()
Candidate &	operator[] (int index)

Detailed Description

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

Candidate Vector.

Definition at line 178 of file itkKdTreeBasedKmeansEstimator.h.

Constructor & Destructor Documentation

CandidateVector()

template<typename TKdTree >

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

default

~CandidateVector()

template<typename TKdTree >

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

virtualdefault

Member Function Documentation

GetCentroids()

template<typename TKdTree >

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

inline

gets the centroids (k-means)

Definition at line 220 of file itkKdTreeBasedKmeansEstimator.h.

operator[]()

template<typename TKdTree >

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

inline

gets the index-th candidates

Definition at line 251 of file itkKdTreeBasedKmeansEstimator.h.

SetCentroids()

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 202 of file itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Centroid, itk::NumericTraits< T >::GetLength(), itk::NumericTraits< T >::SetLength(), itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Size, and itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::WeightedCentroid.

Size()

template<typename TKdTree >

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

inline

returns the number of candidate = k

Definition at line 194 of file itkKdTreeBasedKmeansEstimator.h.

UpdateCentroids()

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 234 of file itkKdTreeBasedKmeansEstimator.h.

Member Data Documentation

m_Candidates

template<typename TKdTree >

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

private

internal storage for the candidates

Definition at line 255 of file itkKdTreeBasedKmeansEstimator.h.

m_MeasurementVectorSize

template<typename TKdTree >

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

private

Length of each measurement vector

Definition at line 258 of file itkKdTreeBasedKmeansEstimator.h.

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

• itkKdTreeBasedKmeansEstimator.h