Class KNearestNeighborSearchOnKDTree<T>

java.lang.Object

net.imglib2.neighborsearch.KNearestNeighborSearchOnKDTree<T>

All Implemented Interfaces:

EuclideanSpace, KNearestNeighborSearch<T>, NearestNeighborSearch<T>

public class KNearestNeighborSearchOnKDTree<T>
extends Object
implements KNearestNeighborSearch<T>

Implementation of KNearestNeighborSearch search for kd-trees.

Field Summary

Fields

Modifier and Type	Field	Description
private final KNearestNeighborSearchImpl	impl
private final int	k
private final KDTreeNode<T>[]	matches
private final KDTree<T>	tree

Constructor Summary

Constructors

Modifier	Constructor	Description
	KNearestNeighborSearchOnKDTree(KDTree<T> tree, int k)
private	KNearestNeighborSearchOnKDTree(KNearestNeighborSearchOnKDTree<T> knn)

Method Summary

Modifier and Type	Method	Description
KNearestNeighborSearchOnKDTree<T>	copy()	Create a copy.
double	getDistance()	Access the Euclidean distance between the reference location as used for the last search and the nearest neighbor, ordered by square Euclidean distance.
int	getK()	Get the of k nearest neighbor points used in this search
RealLocalizable	getPosition()	Access the position of the nearest neighbor, ordered by square Euclidean distance.
RealLocalizable	getPosition(int i)	Access the position of the ith nearest neighbor, ordered by square Euclidean distance.
Sampler<T>	getSampler()	Access the data of the nearest neighbor.
Sampler<T>	getSampler(int i)	Access the data of the ith nearest neighbor, ordered by square Euclidean distance.
double	getSquareDistance()	Access the square Euclidean distance between the reference location as used for the last search and the nearest neighbor, ordered by square Euclidean distance.
double	getSquareDistance(int i)	Access the square Euclidean distance between the reference location as used for the last search and the ith nearest neighbor, ordered by square Euclidean distance.
int	numDimensions()	Gets the space's number of dimensions.
void	search(RealLocalizable p)	Perform k-nearest-neighbor search for a reference coordinate.

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface KNearestNeighborSearch

getDistance

Field Details

tree

private final KDTree<T> tree

k

private final int k

impl

private final KNearestNeighborSearchImpl impl

matches

private final KDTreeNode<T>[] matches

Constructor Details

KNearestNeighborSearchOnKDTree

public KNearestNeighborSearchOnKDTree(KDTree<T> tree,
 int k)

KNearestNeighborSearchOnKDTree

private KNearestNeighborSearchOnKDTree(KNearestNeighborSearchOnKDTree<T> knn)

Method Details

numDimensions

public int numDimensions()

Description copied from interface: EuclideanSpace

Gets the space's number of dimensions.

Specified by:

numDimensions in interface EuclideanSpace

getK

public int getK()

Description copied from interface: KNearestNeighborSearch

Get the of k nearest neighbor points used in this search

Specified by:

getK in interface KNearestNeighborSearch<T>

Returns:

the number of nearest neighbor points k used for this search

search

public void search(RealLocalizable p)

Description copied from interface: KNearestNeighborSearch

Perform k-nearest-neighbor search for a reference coordinate.

Specified by:

search in interface KNearestNeighborSearch<T>

Specified by:

search in interface NearestNeighborSearch<T>

Parameters:

p -

getSampler

public Sampler<T> getSampler(int i)

Description copied from interface: KNearestNeighborSearch

Access the data of the i^th nearest neighbor, ordered by square Euclidean distance. Data is accessed through a Sampler that guarantees write access if the underlying data set is writable.

Specified by:

getSampler in interface KNearestNeighborSearch<T>

getPosition

public RealLocalizable getPosition(int i)

Description copied from interface: KNearestNeighborSearch

Access the position of the i^th nearest neighbor, ordered by square Euclidean distance.

Specified by:

getPosition in interface KNearestNeighborSearch<T>

getSquareDistance

public double getSquareDistance(int i)

Description copied from interface: KNearestNeighborSearch

Access the square Euclidean distance between the reference location as used for the last search and the i^th nearest neighbor, ordered by square Euclidean distance.

Specified by:

getSquareDistance in interface KNearestNeighborSearch<T>

copy

public KNearestNeighborSearchOnKDTree<T> copy()

Description copied from interface: KNearestNeighborSearch

Create a copy.

Specified by:

copy in interface KNearestNeighborSearch<T>

Specified by:

copy in interface NearestNeighborSearch<T>

getPosition

public RealLocalizable getPosition()

Description copied from interface: NearestNeighborSearch

Access the position of the nearest neighbor, ordered by square Euclidean distance.

Specified by:

getPosition in interface NearestNeighborSearch<T>

getSampler

public Sampler<T> getSampler()

Description copied from interface: NearestNeighborSearch

Access the data of the nearest neighbor. Data is accessed through a Sampler that guarantees write access if the underlying data set is writable.

Specified by:

getSampler in interface NearestNeighborSearch<T>

getSquareDistance

public double getSquareDistance()

Description copied from interface: NearestNeighborSearch

Access the square Euclidean distance between the reference location as used for the last search and the nearest neighbor, ordered by square Euclidean distance.

Specified by:

getSquareDistance in interface NearestNeighborSearch<T>

getDistance

public double getDistance()

Description copied from interface: NearestNeighborSearch

Access the Euclidean distance between the reference location as used for the last search and the nearest neighbor, ordered by square Euclidean distance.

Specified by:

getDistance in interface NearestNeighborSearch<T>