#include <itkKdTree.h>

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

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

Classes
class	NearestNeighbors
	data structure for storing k-nearest neighbor search result (k number of Neighbors) More...

Public Types
typedef TSample::AbsoluteFrequencyType	AbsoluteFrequencyType
typedef TSample::ConstIterator	ConstIterator
typedef SmartPointer< const Self >	ConstPointer
typedef EuclideanDistanceMetric < MeasurementVectorType >	DistanceMetricType
typedef TSample::InstanceIdentifier	InstanceIdentifier
typedef std::vector < InstanceIdentifier >	InstanceIdentifierVectorType
typedef TSample::Iterator	Iterator
typedef KdTreeNode< TSample >	KdTreeNodeType
typedef TSample::MeasurementType	MeasurementType
typedef unsigned int	MeasurementVectorSizeType
typedef TSample::MeasurementVectorType	MeasurementVectorType
typedef std::pair < InstanceIdentifier, double >	NeighborType
typedef SmartPointer< Self >	Pointer
typedef TSample	SampleType
typedef KdTree	Self
typedef Object	Superclass
Public Types inherited from itk::Object
Public Types inherited from itk::LightObject

Public Member Functions
bool	BallWithinBounds (const MeasurementVectorType &, MeasurementVectorType &, MeasurementVectorType &, double) const
bool	BoundsOverlapBall (const MeasurementVectorType &, MeasurementVectorType &, MeasurementVectorType &, double) const
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
void	DeleteNode (KdTreeNodeType *)
DistanceMetricType *	GetDistanceMetric ()
KdTreeNodeType *	GetEmptyTerminalNode ()
AbsoluteFrequencyType	GetFrequency (InstanceIdentifier id) const
const MeasurementVectorType &	GetMeasurementVector (InstanceIdentifier id) const
virtual MeasurementVectorSizeType	GetMeasurementVectorSize () const
virtual const char *	GetNameOfClass () const
KdTreeNodeType *	GetRoot ()
const TSample *	GetSample () const
void	PlotTree (std::ostream &os) const
void	PlotTree (KdTreeNodeType *node, std::ostream &os=std::cout) const
void	PrintTree (std::ostream &) const
void	PrintTree (KdTreeNodeType *, unsigned int, unsigned int, std::ostream &os=std::cout) const
void	Search (const MeasurementVectorType &, unsigned int, InstanceIdentifierVectorType &) const
void	Search (const MeasurementVectorType &, double, InstanceIdentifierVectorType &) const
void	SetBucketSize (unsigned int)
void	SetSample (const TSample *)
SizeValueType	Size () const

void	SetRoot (KdTreeNodeType *root)
Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)
unsigned long	AddObserver (const EventObject &event, Command *) const
virtual void	DebugOff () const
virtual void	DebugOn () const
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
MetaDataDictionary &	GetMetaDataDictionary (void)
const MetaDataDictionary &	GetMetaDataDictionary (void) const
virtual unsigned long	GetMTime () const
virtual const TimeStamp &	GetTimeStamp () const
bool	HasObserver (const EventObject &event) const
void	InvokeEvent (const EventObject &)
void	InvokeEvent (const EventObject &) const
virtual void	Modified () const
virtual void	Register () const
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
void	SetDebug (bool debugFlag) const
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
virtual void	SetReferenceCount (int)
virtual void	UnRegister () const
Public Member Functions inherited from itk::LightObject
virtual void	Delete ()
virtual int	GetReferenceCount () const
	itkCloneMacro (Self)
void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions
static Pointer	New ()
Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static void	SetGlobalWarningDisplay (bool flag)
Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

Protected Member Functions
	KdTree ()
int	NearestNeighborSearchLoop (const KdTreeNodeType *, const MeasurementVectorType &, MeasurementVectorType &, MeasurementVectorType &, NearestNeighbors &) const
void	PrintSelf (std::ostream &os, Indent indent) const
int	SearchLoop (const KdTreeNodeType *, const MeasurementVectorType &, double, MeasurementVectorType &, MeasurementVectorType &, InstanceIdentifierVectorType &) const
virtual	~KdTree ()
Protected Member Functions inherited from itk::Object
	Object ()
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	SetTimeStamp (const TimeStamp &time)
virtual	~Object ()
Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const
	LightObject ()
virtual void	PrintHeader (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
virtual	~LightObject ()

Private Member Functions
	KdTree (const Self &)
void	operator= (const Self &)

Private Attributes
int	m_BucketSize
DistanceMetricType::Pointer	m_DistanceMetric
KdTreeNodeType *	m_EmptyTerminalNode
MeasurementVectorSizeType	m_MeasurementVectorSize
KdTreeNodeType *	m_Root
const TSample *	m_Sample

Detailed Description

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

This class provides methods for k-nearest neighbor search and related data structures for a k-d tree.

An object of this class stores instance identifiers in a k-d tree that is a binary tree with childrens split along a dimension among k-dimensions. The dimension of the split (or partition) is determined for each nonterminal node that has two children. The split process is terminated when the node has no children (when the number of measurement vectors is less than or equal to the size set by the SetBucketSize. That is The split process is a recursive process in nature and in implementation. This implementation doesn't support dynamic insert and delete operations for the tree. Instead, we can use the KdTreeGenerator or WeightedCentroidKdTreeGenerator to generate a static KdTree object.

To search k-nearest neighbor, call the Search method with the query point in a k-d space and the number of nearest neighbors. The GetSearchResult method returns a pointer to a NearestNeighbors object with k-nearest neighbors.

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. Please use the function GetMeasurementVectorSize() instead.

See also:: KdTreeNode, KdTreeNonterminalNode, KdTreeWeightedCentroidNonterminalNode, KdTreeTerminalNode, KdTreeGenerator, WeightedCentroidKdTreeNode

Definition at line 482 of file itkKdTree.h.

Member Typedef Documentation

template<class TSample >

typedef TSample::AbsoluteFrequencyType itk::Statistics::KdTree< TSample >::AbsoluteFrequencyType

Definition at line 502 of file itkKdTree.h.

template<class TSample >

typedef TSample::ConstIterator itk::Statistics::KdTree< TSample >::ConstIterator

Definition at line 717 of file itkKdTree.h.

template<class TSample >

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

Reimplemented from itk::Object.

Definition at line 489 of file itkKdTree.h.

template<class TSample >

typedef EuclideanDistanceMetric< MeasurementVectorType > itk::Statistics::KdTree< TSample >::DistanceMetricType

DistanceMetric type for the distance calculation and comparison

Definition at line 508 of file itkKdTree.h.

template<class TSample >

typedef TSample::InstanceIdentifier itk::Statistics::KdTree< TSample >::InstanceIdentifier

Definition at line 501 of file itkKdTree.h.

template<class TSample >

typedef std::vector< InstanceIdentifier > itk::Statistics::KdTree< TSample >::InstanceIdentifierVectorType

Definition at line 521 of file itkKdTree.h.

template<class TSample >

typedef TSample::Iterator itk::Statistics::KdTree< TSample >::Iterator

Definition at line 716 of file itkKdTree.h.

template<class TSample >

typedef KdTreeNode<TSample> itk::Statistics::KdTree< TSample >::KdTreeNodeType

Node type of the KdTree

Definition at line 514 of file itkKdTree.h.

template<class TSample >

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

Definition at line 500 of file itkKdTree.h.

template<class TSample >

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

Definition at line 504 of file itkKdTree.h.

template<class TSample >

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

Definition at line 499 of file itkKdTree.h.

template<class TSample >

typedef std::pair< InstanceIdentifier, double > itk::Statistics::KdTree< TSample >::NeighborType

Neighbor type. The first element of the std::pair is the instance identifier and the second one is the distance between the measurement vector identified by the first element and the query point.

Definition at line 519 of file itkKdTree.h.

template<class TSample >

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

Reimplemented from itk::Object.

Definition at line 488 of file itkKdTree.h.

template<class TSample >

typedef TSample itk::Statistics::KdTree< TSample >::SampleType

typedef alias for the source data container

Definition at line 495 of file itkKdTree.h.

template<class TSample >

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

Standard class typedefs

Reimplemented from itk::Object.

Definition at line 486 of file itkKdTree.h.

template<class TSample >

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

Reimplemented from itk::Object.

Definition at line 487 of file itkKdTree.h.

Constructor & Destructor Documentation

template<class TSample >

itk::Statistics::KdTree< TSample >::KdTree ( )

protected

Constructor

template<class TSample >

virtual itk::Statistics::KdTree< TSample >::~KdTree ( )

protectedvirtual

Destructor: deletes the root node and the empty terminal node.

template<class TSample >

itk::Statistics::KdTree< TSample >::KdTree ( const Self & )

private

Member Function Documentation

template<class TSample >

bool itk::Statistics::KdTree< TSample >::BallWithinBounds	(	const MeasurementVectorType &	,
		MeasurementVectorType &	,
		MeasurementVectorType &	,
		double
	)		const

Returns true if the intermediate k-nearest neighbors exist within the the bounding box defined by the lowerBound and the upperBound. Otherwise returns false. Returns false if the ball defined by the distance between the query point and the farthest neighbor touch the surface of the bounding box.

template<class TSample >

bool itk::Statistics::KdTree< TSample >::BoundsOverlapBall	(	const MeasurementVectorType &	,
		MeasurementVectorType &	,
		MeasurementVectorType &	,
		double
	)		const

Returns true if the ball defined by the distance between the query point and the farthest neighbor overlaps with the bounding box defined by the lower and the upper bounds.

template<class TSample >

virtual::itk::LightObject::Pointer itk::Statistics::KdTree< 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.

template<class TSample >

void itk::Statistics::KdTree< TSample >::DeleteNode ( KdTreeNodeType * )

Deletes the node recursively

template<class TSample >

DistanceMetricType* itk::Statistics::KdTree< TSample >::GetDistanceMetric ( )

inline

Get the pointer to the distance metric.

Definition at line 672 of file itkKdTree.h.

template<class TSample >

KdTreeNodeType* itk::Statistics::KdTree< TSample >::GetEmptyTerminalNode ( )

inline

Returns the pointer to the empty terminal node. A KdTree object has a single empty terminal node in memory. when the split process has to create an empty terminal node, the single instance is reused for this case

Definition at line 633 of file itkKdTree.h.

template<class TSample >

AbsoluteFrequencyType itk::Statistics::KdTree< TSample >::GetFrequency ( InstanceIdentifier id ) const

inline

Returns the frequency of the measurement vector identified by the instance identifier

Definition at line 666 of file itkKdTree.h.

template<class TSample >

const MeasurementVectorType& itk::Statistics::KdTree< TSample >::GetMeasurementVector ( InstanceIdentifier id ) const

inline

Returns the measurement vector identified by the instance identifier that is an identifier defiend for the input sample

Definition at line 658 of file itkKdTree.h.

template<class TSample >

virtual MeasurementVectorSizeType itk::Statistics::KdTree< TSample >::GetMeasurementVectorSize ( ) const

virtual

Get Macro to get the length of a measurement vector in the KdTree. The length is obtained from the input sample.

template<class TSample >

virtual const char* itk::Statistics::KdTree< TSample >::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods)

Reimplemented from itk::Object.

template<class TSample >

KdTreeNodeType* itk::Statistics::KdTree< TSample >::GetRoot ( )

inline

Returns the pointer to the root node.

Definition at line 651 of file itkKdTree.h.

template<class TSample >

const TSample* itk::Statistics::KdTree< TSample >::GetSample ( ) const

inline

Returns the pointer to the input sample

Definition at line 619 of file itkKdTree.h.

template<class TSample >

int itk::Statistics::KdTree< TSample >::NearestNeighborSearchLoop	(	const KdTreeNodeType *	,
		const MeasurementVectorType &	,
		MeasurementVectorType &	,
		MeasurementVectorType &	,
		NearestNeighbors &
	)		const

protected

search loop

template<class TSample >

static Pointer itk::Statistics::KdTree< TSample >::New ( )

static

Method for creation through the object factory.

Reimplemented from itk::Object.

template<class TSample >

void itk::Statistics::KdTree< TSample >::operator= ( const Self & )

private

Mutex lock to protect modification to the reference count

Reimplemented from itk::Object.

template<class TSample >

void itk::Statistics::KdTree< TSample >::PlotTree ( std::ostream & os ) const

Draw out the tree information to a ostream using the format of the Graphviz dot tool.

template<class TSample >

void itk::Statistics::KdTree< TSample >::PlotTree	(	KdTreeNodeType *	node,
		std::ostream &	os = `std::cout`
	)		const

Prints out the tree information

template<class TSample >

void itk::Statistics::KdTree< TSample >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

protectedvirtual

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.

template<class TSample >

void itk::Statistics::KdTree< TSample >::PrintTree ( std::ostream & ) const

Prints out the tree information

template<class TSample >

void itk::Statistics::KdTree< TSample >::PrintTree	(	KdTreeNodeType *	,
		unsigned	int,
		unsigned	int,
		std::ostream &	os = `std::cout`
	)		const

Prints out the tree information

template<class TSample >

void itk::Statistics::KdTree< TSample >::Search	(	const MeasurementVectorType &	,
		unsigned	int,
		InstanceIdentifierVectorType &
	)		const

Searches the k-nearest neighbors

template<class TSample >

void itk::Statistics::KdTree< TSample >::Search	(	const MeasurementVectorType &	,
		double	,
		InstanceIdentifierVectorType &
	)		const

Searches the neighbors fallen into a hypersphere

template<class TSample >

int itk::Statistics::KdTree< TSample >::SearchLoop	(	const KdTreeNodeType *	,
		const MeasurementVectorType &	,
		double	,
		MeasurementVectorType &	,
		MeasurementVectorType &	,
		InstanceIdentifierVectorType &
	)		const

protected

search loop

template<class TSample >

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

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

template<class TSample >

void itk::Statistics::KdTree< TSample >::SetRoot ( KdTreeNodeType * root )

inline

Sets the root node of the KdTree that is a result of KdTreeGenerator or WeightedCentroidKdTreeGenerator.

Definition at line 640 of file itkKdTree.h.

template<class TSample >

void itk::Statistics::KdTree< TSample >::SetSample ( const TSample * )

Sets the input sample that provides the measurement vectors to the k-d tree

template<class TSample >

SizeValueType itk::Statistics::KdTree< TSample >::Size ( void ) const

inline

Definition at line 624 of file itkKdTree.h.

Member Data Documentation

template<class TSample >

int itk::Statistics::KdTree< TSample >::m_BucketSize

private

Number of measurement vectors can be stored in a terminal node.

Definition at line 746 of file itkKdTree.h.

template<class TSample >

DistanceMetricType::Pointer itk::Statistics::KdTree< TSample >::m_DistanceMetric

private

Distance metric smart pointer

Definition at line 755 of file itkKdTree.h.

template<class TSample >

KdTreeNodeType* itk::Statistics::KdTree< TSample >::m_EmptyTerminalNode

private

Pointer to the empty terminal node

Definition at line 752 of file itkKdTree.h.

template<class TSample >

MeasurementVectorSizeType itk::Statistics::KdTree< TSample >::m_MeasurementVectorSize

private

Measurement vector size

Definition at line 758 of file itkKdTree.h.

template<class TSample >

KdTreeNodeType* itk::Statistics::KdTree< TSample >::m_Root

private

Pointer to the root node

Definition at line 749 of file itkKdTree.h.

template<class TSample >

const TSample* itk::Statistics::KdTree< TSample >::m_Sample

private

Pointer to the input sample

Definition at line 743 of file itkKdTree.h.

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

itkKdTree.h

Classes

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

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