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

#include <itkKdTreeBasedKmeansEstimator.h>

Detailed Description

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

Candidate Vector.

Definition at line 181 of file itkKdTreeBasedKmeansEstimator.h.

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

Classes
struct	Candidate

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

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

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 222 of file itkKdTreeBasedKmeansEstimator.h.

References m_Candidates, and Size().

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.

References m_Candidates.

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 205 of file itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Centroid, itk::NumericTraits< T >::GetLength(), m_Candidates, m_MeasurementVectorSize, 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 197 of file itkKdTreeBasedKmeansEstimator.h.

References m_Candidates.

Referenced by GetCentroids(), and UpdateCentroids().

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.

References m_Candidates, m_MeasurementVectorSize, and Size().

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 258 of file itkKdTreeBasedKmeansEstimator.h.

Referenced by GetCentroids(), operator[](), SetCentroids(), Size(), and UpdateCentroids().

m_MeasurementVectorSize

template<typename TKdTree>

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

private

Length of each measurement vector

Definition at line 261 of file itkKdTreeBasedKmeansEstimator.h.

Referenced by SetCentroids(), and UpdateCentroids().

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

• itkKdTreeBasedKmeansEstimator.h