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

#include <itkKdTreeBasedKmeansEstimator.h>

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

Detailed Description

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

Candidate Vector.

Definition at line 179 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 ()
void	SetCentroids (InternalParametersType &centroids)

Private Attributes
std::vector< Candidate >	m_Candidates
MeasurementVectorSizeType	m_MeasurementVectorSize

Constructor & Destructor Documentation

template<class TKdTree >

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

inline

Definition at line 182 of file itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

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

inlinevirtual

Definition at line 190 of file itkKdTreeBasedKmeansEstimator.h.

Member Function Documentation

template<class TKdTree >

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

inline

gets the centroids (k-means)

Definition at line 218 of file itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Centroid.

template<class TKdTree >

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

inline

gets the index-th candidates

Definition at line 250 of file itkKdTreeBasedKmeansEstimator.h.

template<class 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 200 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.

template<class TKdTree >

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

inline

returns the number of candidate = k

Definition at line 193 of file itkKdTreeBasedKmeansEstimator.h.

template<class 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 231 of file itkKdTreeBasedKmeansEstimator.h.

Member Data Documentation

template<class TKdTree >

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

private

internal storage for the candidates

Definition at line 257 of file itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

MeasurementVectorSizeType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::m_MeasurementVectorSize

private

Length of each measurement vector

Definition at line 260 of file itkKdTreeBasedKmeansEstimator.h.

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

• itkKdTreeBasedKmeansEstimator.h