#include <itkKdTreeGenerator.h>

Inheritance diagram for itk::Statistics::KdTreeGenerator< TSample >:

Collaboration diagram for itk::Statistics::KdTreeGenerator< TSample >:

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef KdTreeType::KdTreeNodeType	KdTreeNodeType
typedef KdTree< TSample >	KdTreeType
typedef TSample::MeasurementType	MeasurementType
typedef unsigned int	MeasurementVectorSizeType
typedef TSample::MeasurementVectorType	MeasurementVectorType
typedef KdTreeType::Pointer	OutputPointer
typedef KdTreeType	OutputType
typedef SmartPointer< Self >	Pointer
typedef KdTreeGenerator	Self
typedef SubsampleType::Pointer	SubsamplePointer
typedef Subsample< TSample >	SubsampleType
typedef Object	Superclass
Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
void	GenerateData ()
virtual unsigned int	GetMeasurementVectorSize () const
virtual const char *	GetNameOfClass () const
OutputPointer	GetOutput ()
void	SetBucketSize (unsigned int size)
void	SetSample (TSample *sample)
void	Update ()
Static Public Member Functions
static Pointer	New ()
Protected Member Functions
virtual KdTreeNodeType *	GenerateNonterminalNode (unsigned int beginIndex, unsigned int endIndex, MeasurementVectorType &lowerBound, MeasurementVectorType &upperBound, unsigned int level)
KdTreeNodeType *	GenerateTreeLoop (unsigned int beginIndex, unsigned int endIndex, MeasurementVectorType &lowerBound, MeasurementVectorType &upperBound, unsigned int level)
SubsamplePointer	GetSubsample ()
	KdTreeGenerator ()
void	PrintSelf (std::ostream &os, Indent indent) const
virtual	~KdTreeGenerator ()
Private Member Functions
	KdTreeGenerator (const Self &)
void	operator= (const Self &)
Private Attributes
unsigned int	m_BucketSize
MeasurementVectorSizeType	m_MeasurementVectorSize
TSample *	m_SourceSample
SubsamplePointer	m_Subsample
MeasurementVectorType	m_TempLowerBound
MeasurementVectorType	m_TempMean
MeasurementVectorType	m_TempUpperBound
OutputPointer	m_Tree

Detailed Description

template<class TSample>
class itk::Statistics::KdTreeGenerator< TSample >

This class generates a KdTree object without centroid information.

The KdTree object stores measurment vectors in a k-d tree structure that is a binary tree. The partition value is the median value of one of the k dimension (partition dimension). The partition dimension is determined by the spread of measurement values in each dimension. The partition dimension is the dimension has the widest spread. Our implementation of k-d tree doesn't have any construction or insertion logic. Users should use this class or the WeightedCentroidKdTreeGenerator class.

The number of the measurement vectors in a terminal node is set by the SetBucketSize method. If we use too small number for this, it might cause computational overhead to calculate bound conditions. However, too large number will cause more distance calculation between the measurement vectors in a terminal node and the query point.

To run this generator, users should provides the bucket size (SetBucketSize method) and the input sample (SetSample method). The Update method will run this generator. To get the resulting KdTree object, call the GetOutput method.

Recent API changes: The static const macro to get the length of a measurement vector, 'MeasurementVectorSize' has been removed to allow the length of a measurement vector to be specified at run time. It is now obtained from the sample set as input. You may query this length using the function GetMeasurementVectorSize().

See also:: KdTree, KdTreeNode, KdTreeNonterminalNode, KdTreeTerminalNode, WeightedCentroidKdTreeGenerator

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Definition at line 70 of file itkKdTreeGenerator.h.

Member Typedef Documentation

template<class TSample >

typedef SmartPointer< const Self > itk::Statistics::KdTreeGenerator< TSample >::ConstPointer

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 77 of file itkKdTreeGenerator.h.

template<class TSample >

typedef KdTreeType::KdTreeNodeType itk::Statistics::KdTreeGenerator< TSample >::KdTreeNodeType

Typedef for the k-d tree node type

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 102 of file itkKdTreeGenerator.h.

template<class TSample >

typedef KdTree< TSample > itk::Statistics::KdTreeGenerator< TSample >::KdTreeType

Typedef for the k-d tree

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 93 of file itkKdTreeGenerator.h.

template<class TSample >

typedef TSample::MeasurementType itk::Statistics::KdTreeGenerator< TSample >::MeasurementType

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 87 of file itkKdTreeGenerator.h.

template<class TSample >

typedef unsigned int itk::Statistics::KdTreeGenerator< TSample >::MeasurementVectorSizeType

Typedef for the length of each measurement vector

Definition at line 90 of file itkKdTreeGenerator.h.

template<class TSample >

typedef TSample::MeasurementVectorType itk::Statistics::KdTreeGenerator< TSample >::MeasurementVectorType

typedef alias for the source data container

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 83 of file itkKdTreeGenerator.h.

template<class TSample >

typedef KdTreeType::Pointer itk::Statistics::KdTreeGenerator< TSample >::OutputPointer

Typedef for the smart pointer to the k-d tree

Definition at line 99 of file itkKdTreeGenerator.h.

template<class TSample >

typedef KdTreeType itk::Statistics::KdTreeGenerator< TSample >::OutputType

Type alias for the k-d tree type

Definition at line 96 of file itkKdTreeGenerator.h.

template<class TSample >

typedef SmartPointer< Self > itk::Statistics::KdTreeGenerator< TSample >::Pointer

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 76 of file itkKdTreeGenerator.h.

template<class TSample >

typedef KdTreeGenerator itk::Statistics::KdTreeGenerator< TSample >::Self

Standard class typedefs

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 74 of file itkKdTreeGenerator.h.

template<class TSample >

typedef SubsampleType::Pointer itk::Statistics::KdTreeGenerator< TSample >::SubsamplePointer

Typedef for the smart pointer to the Subsample

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 108 of file itkKdTreeGenerator.h.

template<class TSample >

typedef Subsample< TSample > itk::Statistics::KdTreeGenerator< TSample >::SubsampleType

Typedef for the internal Subsample

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 105 of file itkKdTreeGenerator.h.

template<class TSample >

typedef Object itk::Statistics::KdTreeGenerator< TSample >::Superclass

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

Definition at line 75 of file itkKdTreeGenerator.h.

Constructor & Destructor Documentation

template<class TSample >

itk::Statistics::KdTreeGenerator< TSample >::KdTreeGenerator ( ) [protected]

Constructor

template<class TSample >

virtual itk::Statistics::KdTreeGenerator< TSample >::~KdTreeGenerator ( ) [inline, protected, virtual]

Destructor

Definition at line 141 of file itkKdTreeGenerator.h.

template<class TSample >

itk::Statistics::KdTreeGenerator< TSample >::KdTreeGenerator ( const Self & ) [private]

Member Function Documentation

template<class TSample >

virtual::itk::LightObject::Pointer itk::Statistics::KdTreeGenerator< TSample >::CreateAnother ( void ) const [virtual]

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample >

void itk::Statistics::KdTreeGenerator< TSample >::GenerateData ( )

Runs this k-d tree construction algorithm.

template<class TSample >

virtual KdTreeNodeType* itk::Statistics::KdTreeGenerator< TSample >::GenerateNonterminalNode	(	unsigned int	beginIndex,
		unsigned int	endIndex,
		MeasurementVectorType &	lowerBound,
		MeasurementVectorType &	upperBound,
		unsigned int	level
	)		`[protected, virtual]`

Nonterminal node generation routine

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample >

KdTreeNodeType* itk::Statistics::KdTreeGenerator< TSample >::GenerateTreeLoop	(	unsigned int	beginIndex,
		unsigned int	endIndex,
		MeasurementVectorType &	lowerBound,
		MeasurementVectorType &	upperBound,
		unsigned int	level
	)		`[protected]`

Tree generation loop

template<class TSample >

virtual unsigned int itk::Statistics::KdTreeGenerator< TSample >::GetMeasurementVectorSize ( ) const [virtual]

Get macro to get the length of the measurement vectors that are being held in the 'sample' that is passed to this class

template<class TSample >

virtual const char* itk::Statistics::KdTreeGenerator< TSample >::GetNameOfClass ( ) const [virtual]

Run-time type information (and related methods)

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample >

OutputPointer itk::Statistics::KdTreeGenerator< TSample >::GetOutput ( void ) [inline]

Returns the pointer to the generated k-d tree.

Definition at line 118 of file itkKdTreeGenerator.h.

template<class TSample >

SubsamplePointer itk::Statistics::KdTreeGenerator< TSample >::GetSubsample ( ) [inline, protected]

Returns the smart pointer to the internal Subsample object.

Definition at line 146 of file itkKdTreeGenerator.h.

template<class TSample >

static Pointer itk::Statistics::KdTreeGenerator< TSample >::New ( ) [static]

Method for creation through the object factory.

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample >

void itk::Statistics::KdTreeGenerator< TSample >::operator= ( const Self & ) [private]

Mutex lock to protect modification to the reference count

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample >

void itk::Statistics::KdTreeGenerator< TSample >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const `[protected, virtual]`

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::Object.

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample >

void itk::Statistics::KdTreeGenerator< TSample >::SetBucketSize ( unsigned int size )

Sets the number of measurement vectors that can be stored in a terminal node.

template<class TSample >

void itk::Statistics::KdTreeGenerator< TSample >::SetSample ( TSample * sample )

Sets the input sample that provides the measurement vectors.

template<class TSample >

void itk::Statistics::KdTreeGenerator< TSample >::Update ( void ) [inline]

Runs this k-d tree construction algorithm.

Definition at line 124 of file itkKdTreeGenerator.h.