de.unibi.techfak.jpredictor.clustering
Class EuclideanDistance

java.lang.Object
  de.unibi.techfak.jpredictor.clustering.RelationMeasure
      de.unibi.techfak.jpredictor.clustering.VectorRelationMeasure
          de.unibi.techfak.jpredictor.clustering.MinkowskiDistance
              de.unibi.techfak.jpredictor.clustering.EuclideanDistance

All Implemented Interfaces:

Computable, java.lang.Comparable

public class EuclideanDistance
extends MinkowskiDistance

The Minkowski distance for the special case p=2.

Field Summary

Fields inherited from class de.unibi.techfak.jpredictor.clustering.MinkowskiDistance

p

Fields inherited from class de.unibi.techfak.jpredictor.clustering.VectorRelationMeasure

vectorList

Fields inherited from class de.unibi.techfak.jpredictor.clustering.RelationMeasure

computationResult

Fields inherited from interface de.unibi.techfak.jpredictor.clustering.Computable

COMPUTATION_FAILED, COMPUTATION_PENDING, COMPUTATION_SUCCESS, COMPUTATION_WAITING

Constructor Summary

EuclideanDistance()
Generates the distance measure and sets the exponent to 1.

Method Summary

static double	calculate(double[] x, double[] y) Calculates the Euclidean distance between two given arrays.
java.lang.String	toString() Creates a short string of this relation measure and maybe some results if available.

Methods inherited from class de.unibi.techfak.jpredictor.clustering.MinkowskiDistance

atomicCombine, atomicNormalize, calculate, compute, getP, newInstance, optimum, setP

Methods inherited from class de.unibi.techfak.jpredictor.clustering.VectorRelationMeasure

add, add, add, clear, length

Methods inherited from class de.unibi.techfak.jpredictor.clustering.RelationMeasure

atomicCombine, compareTo, optimum, result

Methods inherited from class java.lang.Object

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

Constructor Detail

EuclideanDistance

public EuclideanDistance()

Generates the distance measure and sets the exponent to 1.

Method Detail

calculate

public static double calculate(double[] x,
                               double[] y)

Calculates the Euclidean distance between two given arrays. Returns Double.NaN in case of any error, e.g. x or y are null or of inequal length.

Parameters:

x - The first array.

y - The second array

Returns:

The Euclidean distance between the two arrays.

toString

public java.lang.String toString()

Description copied from class: RelationMeasure

Creates a short string of this relation measure and maybe some results if available.

Overrides:

toString in class MinkowskiDistance

Returns:

A string with a short description of the class.