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

#include <itkKdTreeBasedKmeansEstimator.h>

List of all members.

---

Detailed Description

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

vector of k-means candidates

Definition at line 162 of file itkKdTreeBasedKmeansEstimator.h.

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

---

Constructor & Destructor Documentation

template<class TKdTree>

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

(

)

[inline]

Definition at line 165 of file itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree>

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

(

)

[inline, virtual]

Definition at line 174 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 199 of file itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree>

Candidate& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::operator[]

(

int

index

)

[inline]

gets the index-th candidates

Definition at line 231 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 182 of file itkKdTreeBasedKmeansEstimator.h.

References itk::MeasurementVectorTraits::GetLength(), and itk::MeasurementVectorTraits::SetLength().

template<class TKdTree>

int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Size

(

void

)

const [inline]

returns the number of candidate = k

Definition at line 177 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 212 of file itkKdTreeBasedKmeansEstimator.h.

---

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

• itkKdTreeBasedKmeansEstimator.h

---