Generador de conjuntos de puntos 2D para pruebas de clusterización

GenerateGaussianClusters.java

package edu.upb.estalg.Estructuras.UnionFind;

import edu.princeton.cs.algs4.StdDraw;
import edu.princeton.cs.algs4.StdOut;
import edu.princeton.cs.algs4.StdRandom;

import java.awt.*;
import java.util.Arrays;

public class GenerateGaussianClusters {



    public static double[][] clusters(int k, int n, int d) {
        double[][] datapoints = new double[k*n][];
        int pos=0;
        double[] mu = new double[d];
        double[] sigma = new double[d];
        double min=Double.POSITIVE_INFINITY, max=Double.NEGATIVE_INFINITY;
        for(int i=0; i<k; i++) {
            for(int l=0; l<d; l++) {
                mu[l] = 2*(StdRandom.uniform() - 0.5);
                sigma[l] = StdRandom.uniform() / 3;
            }
            for(int j=0; j<n; j++) {
                double[] sample = new double[d];
                for(int l=0; l<d; l++) {
                    sample[l] = StdRandom.gaussian(mu[l], sigma[l]);
                    min = sample[l]<min ? sample[l] : min;
                    max = sample[l]>max ? sample[l] : max;
                }
                datapoints[pos++] = sample;
                StdOut.println(Arrays.toString(sample));
            }
        }
        StdOut.println("min = "+min+", max="+max);
        return datapoints;
    }


    public static void plotDataPoints(double[][] datapoints) {
        Color[] colors = { StdDraw.CYAN, StdDraw.RED, StdDraw.GREEN };
        StdDraw.setScale(-2,2);
        StdDraw.setPenRadius(0.004);
        for(int i=0; i<datapoints.length; i++) {
            StdDraw.point(datapoints[i][0], datapoints[i][1]);
        }
    }


    public static void main(String[] args) {
        StdRandom.setSeed(454);
        double[][] datapoints = clusters(3, 50, 2);
        plotDataPoints(datapoints);
    }


}