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package kmean348;

import java.awt.geom.Point2D;

import java.util.ArrayList;

import java.util.List;

import java.util.Scanner;

/**

*

* @author Tak

*/

public class Main {

private static final Scanner scannerObject = new Scanner(System.in);

private static int k;

private static int noOfInputPoints;

private static List<Point2D.Double> inputPoints;

private static int noOfClusterPoints;

private static List<Point2D.Double> clusterPoints;

private static int[] groupOfElement;

/**

* @param args the command line arguments

*/

public static void main(String[] args) {

System.out.print("Enter the value of k: ");

k = scannerObject.nextInt();

System.out.print("Enter the number of inputs: ");

noOfInputPoints = scannerObject.nextInt();

groupOfElement = new int[noOfInputPoints];

inputPoints = new ArrayList<Point2D.Double>();

//get the input points

for (int i=0; i<noOfInputPoints; i++) {

System.out.printf("for Point: %d\n" , i);

System.out.print("Enter x: ");

double x = scannerObject.nextDouble();

System.out.print("Enter y: ");

double y = scannerObject.nextDouble();

Point2D.Double point = new Point2D.Double(x,y);

inputPoints.add(point);

}

//instanstiate the initial cluster points i.e initial mean values

//Assuming a value of 2

//System.out.print("Enter the no. of cluster points: ");

//noOfClusterPoints = scannerObject.nextInt();

noOfClusterPoints= 2;

clusterPoints = new ArrayList<Point2D.Double>();

for (int i=0; i<noOfClusterPoints; i++) {

clusterPoints.add(inputPoints.get(i));

}

for (int i=0; i<k; i++) {

//for each instance of k

for (int j=0; j<noOfInputPoints; j++) {

int index = 0;

//calculate the euclidean distance of the point with each group

double group1 = findEuclideanDistance(inputPoints.get(j), clusterPoints.get(0));

double group2 = findEuclideanDistance(inputPoints.get(j), clusterPoints.get(1));

if(Double.compare(group2, group1) < 0 ) {

index = 1;

}

groupOfElement[j] = index;

System.out.printf("Logging===k = %d, j= %d, index= %d\n", k, j, index);

Point2D.Double newMeanPoint = findMean(inputPoints.get(j), clusterPoints.get(index));

clusterPoints.set(index, newMeanPoint);

}

}

for (int i=0;i<noOfClusterPoints; i++){

System.out.printf("Group %d\n", noOfClusterPoints);

System.out.println(clusterPoints.get(i).toString());

}

for (int i=0; i<noOfInputPoints; i++) {

System.out.printf("cluster of point %d = %d\n", i, groupOfElement[i]);

}

}

for(int)