import java.io.*;

import java.util.*;

import java.lang.*;

import java.text.*;

public class Centroid

{

// finds the mean of the dataset for grouping

public void Grouping(double[] Cordx, double[] Cordy, int clustNumber)

{

int clusterNumber = clustNumber;

double[] ClustCordX = new double[clustNumber];

double[] ClustCordY = new double[clustNumber];

this.getMeansetCentroid(Cordx, Cordy, clustNumber);

DecimalFormat dec = new DecimalFormat("0.00");

for(int i = 0;i<Cordx.length;i++)

{

String result1 = dec.format(Cordx[i]);

String result2 = dec.format(Cordy[i]);

System.out.println("\n Cords are ( " + result1 + " , " + result2 + ")");

}

//setting random datasets as centroids

for(int i = 0; i<clustNumber;i++)

{

ClustCordX[i] = Cordx[i];

ClustCordY[i] = Cordy[i];

}

this.groupCordtoCluster(Cordx,Cordy,ClustCordX,ClustCordY);

}

public void groupCordtoCluster(double[] Cordx, double[] Cordy, double[] ClustCordX, double[] ClustCordY)

{

double temp ;

int size = Cordx.length;

int clustsize = ClustCordX.length;

int clusterComparison = clustsize;

int[] grouping = new int[size - clustsize];

double[] ClustgroupX = new double[size - clustsize];

double[] ClustgroupY = new double[size - clustsize];

int tempint = -1;

//grouping the dataset to respective clusters by comparing the distance

for(int i = clusterComparison; i < size;i++)

{

temp = 0;

for(int j = 0;j<clustsize;j++)

{

if (j == 0)

tempint++;

if(temp == 0)

{

temp = Math.sqrt(Math.pow((Cordx[i]-ClustCordX[j]),2) + Math.pow((Cordy[i]-ClustCordY[j]),2));

grouping[tempint] = j;

ClustgroupX[tempint] = Cordx[i];

ClustgroupY[tempint] = Cordy[i];

}

else if (temp > Math.sqrt(Math.pow((Cordx[i]-ClustCordX[j]),2) + Math.pow((Cordy[i]-ClustCordY[j]),2)))

{

temp = Math.sqrt(Math.pow((Cordx[i]-ClustCordX[j]),2) + Math.pow((Cordy[i]-ClustCordY[j]),2));

grouping[tempint] = j;

ClustgroupX[tempint] = Cordx[i];

ClustgroupY[tempint] = Cordy[i];

}

}

}

DecimalFormat dec = new DecimalFormat("0.00");

String result1, result2, result3, result4;

for(int i = 0; i<grouping.length;i++)

{

//for(int i = 1; i< clustNumber;i++) {

System.out.println("------------------------");

System.out.println("Clusters for group " + grouping[i]);

result1 = dec.format(Cordx[grouping[i]]);

result2 = dec.format(Cordy[grouping[i]]);

result3 = dec.format(ClustgroupX[i]);

result4 = dec.format(ClustgroupY[i]);

System.out.println("Cordinates are (" + result1 + " , " + result2 + ")");

System.out.println("------------------------");

System.out.println("Clusters for group " + grouping[i]);

System.out.println("Cordinates are (" + result3 + " , " + result4 + ")");

}

}

public void getMeansetCentroid(double[] Cordx, double[] Cordy, int ClustNumber)

{

double xCord, yCord;

double MAX=0,distance, tempd1, tempd2;

double[] Distances = new double[Cordx.length];

int reference, i, j, temp1, temp2, point, length;

reference = i = j = temp1 = temp2 = point =0;

int[] centroids;

for(j = 1; j < Cordx.length;j++)

{

Distances[j-1] = Math.sqrt(Math.pow((Cordx[j]-Cordx[0]),2) + Math.pow((Cordy[j]-Cordy[0]),2));

}

for(i=0;i<Cordx.length-1;i++)

{

for(j=0;j<Cordx.length-1-i;j++)

{

if(Distances[j+1] < Distances[j])

{

distance = Distances[j];

tempd1 = Cordx[j];

tempd2 = Cordy[j];

Distances[j] = Distances[j+1];

Cordx[j] = Cordx[j+1];

Cordy[j] = Cordy[j+1];

Distances[j+1] = distance;

Cordx[j+1] = tempd1;

Cordy[j+1] = tempd2;

}

}

}

//recalculation of centroids

point = Cordx.length;

do

{

if(Cordx.length % ClustNumber != 0)

point--;

}while(point % ClustNumber != 0);

length = point/ClustNumber;

for(i=0;i<Cordx.length;i=length+i)

{

if((i+length-1) > point)

break;

tempd1 = Cordx[i];

tempd2 = Cordy[i];

Cordx[i] = Cordx[i+length-1];

Cordy[i] = Cordy[i+length-1];

Cordx[i+length-1] = tempd1;

Cordy[i+length-1] = tempd2;

}

}

}