org.openimaj.ml.clustering.assignment.hard

Class ExactDoubleAssigner

java.lang.Object

org.openimaj.ml.clustering.assignment.hard.ExactDoubleAssigner

All Implemented Interfaces:

Assigner<double[]>, HardAssigner<double[],double[],IntDoublePair>

public class ExactDoubleAssigner
extends Object
implements HardAssigner<double[],double[],IntDoublePair>

A HardAssigner that assigns points to the closest cluster based on the distance to the centroid.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Field Summary

Fields

Modifier and Type	Field and Description
protected DoubleNearestNeighboursExact	nn

Constructor Summary

Constructors

Constructor and Description
ExactDoubleAssigner(CentroidsProvider<double[]> provider) Construct the assigner using the given cluster data.
ExactDoubleAssigner(CentroidsProvider<double[]> provider, DoubleFVComparator comparison) Construct the assigner using the given cluster data and distance function.
ExactDoubleAssigner(double[][] data, DoubleFVComparator comparison) Construct the assigner using the given cluster data and distance function.

Method Summary

Modifier and Type	Method and Description
int	assign(double[] data) Assign a single point to a cluster.
int[]	assign(double[][] data) Assign data to a cluster.
IntDoublePair	assignDistance(double[] data) Assign a single point to a cluster.
void	assignDistance(double[][] data, int[] indices, double[] distances) Assign data to clusters.
DoubleNearestNeighboursExact	getNN() Get the underlying nearest-neighbour implementation.
int	numDimensions() Get the number of dimensions of the input vectors.
int	size() The number of centroids or unique ids that can be generated.

Methods inherited from class java.lang.Object

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

Field Detail

nn

protected DoubleNearestNeighboursExact nn

Constructor Detail

ExactDoubleAssigner

public ExactDoubleAssigner(CentroidsProvider<double[]> provider)

Construct the assigner using the given cluster data. The distance function defaults to Euclidean.

Parameters:

provider - the cluster data provider

ExactDoubleAssigner

public ExactDoubleAssigner(CentroidsProvider<double[]> provider,
                           DoubleFVComparator comparison)

Construct the assigner using the given cluster data and distance function.

Parameters:

provider - the cluster data provider

comparison - the distance function

ExactDoubleAssigner

public ExactDoubleAssigner(double[][] data,
                           DoubleFVComparator comparison)

Construct the assigner using the given cluster data and distance function.

Parameters:

data - the cluster data

comparison - the distance function

Method Detail

assign

public int[] assign(double[][] data)

Description copied from interface: HardAssigner

Assign data to a cluster.

Specified by:

assign in interface HardAssigner<double[],double[],IntDoublePair>

Parameters:

data - the data.

Returns:

The cluster indices which the data was assigned to.

assign

public int assign(double[] data)

Description copied from interface: HardAssigner

Assign a single point to a cluster.

Specified by:

assign in interface HardAssigner<double[],double[],IntDoublePair>

Parameters:

data - datum to assign.

Returns:

the cluster index.

assignDistance

public void assignDistance(double[][] data,
                           int[] indices,
                           double[] distances)

Description copied from interface: HardAssigner

Assign data to clusters. The results are returned in the indices and distances arrays. The return arrays must have the same length as the data array.

Specified by:

assignDistance in interface HardAssigner<double[],double[],IntDoublePair>

Parameters:

data - the data.

indices - the cluster index for each data point.

distances - the distance to the closest cluster for each data point.

assignDistance

public IntDoublePair assignDistance(double[] data)

Description copied from interface: HardAssigner

Assign a single point to a cluster.

Specified by:

assignDistance in interface HardAssigner<double[],double[],IntDoublePair>

Parameters:

data - point to assign.

Returns:

the cluster index and distance.

size

public int size()

Description copied from interface: HardAssigner

The number of centroids or unique ids that can be generated.

Specified by:

size in interface HardAssigner<double[],double[],IntDoublePair>

Returns:

The number of centroids or unique ids that can be generated.

numDimensions

public int numDimensions()

Description copied from interface: Assigner

Get the number of dimensions of the input vectors.

Specified by:

numDimensions in interface Assigner<double[]>

Returns:

the number of dimensions

getNN

public DoubleNearestNeighboursExact getNN()

Get the underlying nearest-neighbour implementation.

Returns:

the underlying nearest-neighbour implementation.