medusa.georgios.ClusteringAlgorithms

Class KMeansPoint

java.lang.Object

medusa.georgios.ClusteringAlgorithms.KMeansPoint

public class KMeansPoint
extends java.lang.Object

Represents an abstraction for a data point in two dimensional space

Constructor Summary

Constructors

Constructor and Description
KMeansPoint(java.lang.String label, double[] coordinates)
KMeansPoint(java.lang.String label, double _x, double _y) Creates a new instance of data point

Method Summary

Modifier and Type	Method and Description
void	assignToCluster(int _clusterNumber) Assigns the data point to a cluster
static double	distance(KMeansPoint dp1, KMeansPoint dp2) Returns the distance between two data points
int	getClusterNumber() Returns the cluster to which the data point belongs
double	getCoordinate(int i)
double[]	getCoordinates()
java.lang.String	getLabel()
double	getX() Returns the value of data point in x dimension
double	getY() Returns the value of data point in y dimension
static void	main(java.lang.String[] args) Main method -- to test the kMeansPoint class
void	setCoordinates(double[] coordinates)
int	size()
java.lang.String	toDataString()
java.lang.String	toString() Returns a string representation of this kMeansPoint

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

KMeansPoint

public KMeansPoint(java.lang.String label,
                   double _x,
                   double _y)

Creates a new instance of data point

Parameters:

_x - value in dimension x

_y - value in dimension y

KMeansPoint

public KMeansPoint(java.lang.String label,
                   double[] coordinates)

Method Detail

getCoordinates

public double[] getCoordinates()

getCoordinate

public double getCoordinate(int i)

size

public int size()

setCoordinates

public void setCoordinates(double[] coordinates)

assignToCluster

public void assignToCluster(int _clusterNumber)

Assigns the data point to a cluster

Parameters:

_clusterNumber - the cluster to which this data point is to be assigned

getClusterNumber

public int getClusterNumber()

Returns the cluster to which the data point belongs

Returns:

the cluster number to which the data point belongs

getX

public double getX()

Returns the value of data point in x dimension

Returns:

the value in x dimension

getY

public double getY()

Returns the value of data point in y dimension

Returns:

the value in y dimension

distance

public static double distance(KMeansPoint dp1,
                              KMeansPoint dp2)

Returns the distance between two data points

Parameters:

dp1 - the first data point

dp2 - the second data point

Returns:

the distance between the two data points

toString

public java.lang.String toString()

Returns a string representation of this kMeansPoint

Overrides:

toString in class java.lang.Object

Returns:

a string representation of this data point

toDataString

public java.lang.String toDataString()

main

public static void main(java.lang.String[] args)

Main method -- to test the kMeansPoint class

Parameters:

args - command line arguments

getLabel

public java.lang.String getLabel()