org.openimaj.knn

Class FloatNearestNeighbours

java.lang.Object

org.openimaj.knn.FloatNearestNeighbours

All Implemented Interfaces:

NearestNeighbours<float[],float[],IntFloatPair>

Direct Known Subclasses:

FloatADCNearestNeighbours, FloatNearestNeighboursExact, FloatNearestNeighboursKDTree, IncrementalFloatADCNearestNeighbours

public abstract class FloatNearestNeighbours
extends Object
implements NearestNeighbours<float[],float[],IntFloatPair>

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

Author:

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

Constructor Summary

Constructors

Constructor and Description
FloatNearestNeighbours()

Method Summary

Modifier and Type	Method and Description
static float	distanceFunc(float[] qu, float[] pnt) Static method to find the sum-squared distance between a query vector and a point.
static void	distanceFunc(float[] qu, float[][] pnts, float[] dsq_out) Static method to find the sum-squared distance between a query vector and each of a set of points.
static float	distanceFunc(FloatFVComparator distance, float[] qu, float[] pnt) Static method to find a distance between a query vector and a point.
static void	distanceFunc(FloatFVComparator distance, float[] qu, float[][] pnts, float[] 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

FloatNearestNeighbours

public FloatNearestNeighbours()

Method Detail

distanceFunc

public static void distanceFunc(float[] qu,
                                float[][] pnts,
                                float[] 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 float distanceFunc(float[] qu,
                                 float[] 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 float distanceFunc(FloatFVComparator distance,
                                 float[] qu,
                                 float[] 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(FloatFVComparator distance,
                                float[] qu,
                                float[][] pnts,
                                float[] 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