RandomPointsUtil.java

package mia.clustering.ch09;

import java.util.ArrayList;
import java.util.List;
import java.util.Random;

import org.apache.mahout.clustering.dirichlet.UncommonDistributions;
import org.apache.mahout.common.RandomUtils;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.Vector;

public class RandomPointsUtil {
	public static void generateSamples(List<Vector> vectors, int num,
			double mx, double my, double sd) {
		for (int i = 0; i < num; i++) {
			vectors.add(new DenseVector(new double[] {
					UncommonDistributions.rNorm(mx, sd),
					UncommonDistributions.rNorm(my, sd) }));
		}
	}	
	
  public static List<Vector> chooseRandomPoints(Iterable<Vector> vectors, int k) {
    List<Vector> chosenPoints = new ArrayList<Vector>(k);
    Random random = RandomUtils.getRandom();
    for (Vector value : vectors) {
      int currentSize = chosenPoints.size();
      if (currentSize < k) {
        chosenPoints.add(value);
      } else if (random.nextInt(currentSize + 1) == 0) { // with chance 1/(currentSize+1) pick new element
        int indexToRemove = random.nextInt(currentSize); // evict one chosen randomly
        chosenPoints.remove(indexToRemove);
        chosenPoints.add(value);
      }
    }
    return chosenPoints;
  }
}