org.openimaj.knn

Class LongNearestNeighbours

java.lang.Object

org.openimaj.knn.LongNearestNeighbours

All Implemented Interfaces:

NearestNeighbours<long[],double[],IntDoublePair>

Direct Known Subclasses:

IncrementalLongADCNearestNeighbours, LongADCNearestNeighbours, LongNearestNeighboursExact, LongNearestNeighboursKDTree

public abstract class LongNearestNeighbours
extends Object
implements NearestNeighbours<long[],double[],IntDoublePair>

Abstract base class for k-nearest-neighbour calculations with long[] data.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk), Sina Samangooei (ss@ecs.soton.ac.uk)

Constructor Summary

Constructors

Constructor and Description
LongNearestNeighbours()

Method Summary

Modifier and Type	Method and Description
static double	distanceFunc(long[] qu, long[] pnt) Static method to find the sum-squared distance between a query vector and a point.
static void	distanceFunc(long[] qu, long[][] pnts, double[] dsq_out) Static method to find the sum-squared distance between a query vector and each of a set of points.
static double	distanceFunc(LongFVComparator distance, long[] qu, long[] pnt) Static method to find a distance between a query vector and a point.
static void	distanceFunc(LongFVComparator distance, long[] qu, long[][] pnts, double[] dsq_out) Static method to find a distance between a query vector and each of a set of points.
abstract int	numDimensions() Get the number of dimensions of each vector in the dataset

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.openimaj.knn.NearestNeighbours

searchKNN, searchKNN, searchKNN, searchNN, searchNN, searchNN, size

Constructor Detail

LongNearestNeighbours

public LongNearestNeighbours()

Method Detail

distanceFunc

public static void distanceFunc(long[] qu,
                                long[][] pnts,
                                double[] dsq_out)

Static method to find the sum-squared distance between a query vector and each of a set of points. Results are stored in the dsq_out array, much must have the same length as the number of points.

Parameters:

qu - The query vector.

pnts - The points to compare against.

dsq_out - The resultant distances.

distanceFunc

public static double distanceFunc(long[] qu,
                                  long[] pnt)

Static method to find the sum-squared distance between a query vector and a point.

Parameters:

qu - The query vector.

pnt - The point to compare against.

Returns:

The resultant distance.

distanceFunc

public static double distanceFunc(LongFVComparator distance,
                                  long[] qu,
                                  long[] pnt)

Static method to find a distance between a query vector and a point.

Parameters:

distance - the distance measure

qu - The query vector.

pnt - The point to compare against.

Returns:

The resultant distance.

distanceFunc

public static void distanceFunc(LongFVComparator distance,
                                long[] qu,
                                long[][] pnts,
                                double[] dsq_out)

Static method to find a distance between a query vector and each of a set of points. Results are stored in the dsq_out array, much must have the same length as the number of points.

Parameters:

distance - the distance measure

qu - The query vector.

pnts - The points to compare against.

dsq_out - The resultant distances.

numDimensions

public abstract int numDimensions()

Get the number of dimensions of each vector in the dataset

Returns:

the number of dimensions