basic.java

java实现的隐马尔科夫模型

package be.ac.ulg.montefiore.run.jahmm.test;

import be.ac.ulg.montefiore.run.jahmm.*;
import java.util.*;


public class Basic {
    static public void main(String[] argv) {
	Hmm hmm = new Hmm(5, new OpdfIntegerFactory(10));
	
	hmm.setOpdf(1, new OpdfInteger(6));
	
	Vector oseq = new Vector();
	for (int i = 0; i < 5; i++)
	    oseq.add(new ObservationInteger(i));
	
	
	ForwardBackwardCalculator fbc = 
	    new ForwardBackwardCalculator(oseq, hmm);
	System.out.println("Sequence probability " + fbc.probability());

	ForwardBackwardScaledCalculator fbsc = 
	    new ForwardBackwardScaledCalculator(oseq, hmm);
	System.out.println("Sequence probability (using scaling): " +
			   Math.exp(fbsc.lnProbability()));
	
	
	ViterbiCalculator vc = new ViterbiCalculator(oseq, hmm);
	System.out.println("Most likely state sequence: " +
			   toString(vc.stateSequence()));
	System.out.println("Probability on best sequence path: " + 
			   Math.exp(vc.lnProbability()));
	
	
	Vector oseq2 = new Vector();
	for (int i = 0; i < 30000; i++)
	    oseq2.add(new ObservationInteger((int) (Math.random() * 10.)));

	KMeansCalculator kmc = new KMeansCalculator(20, oseq2);
    }

    static private String toString(int[] sseq) {
	String s = "[ ";
	
	for (int i = 0; i < sseq.length; i++)
	    s += sseq[i] + " ";

	return s + "]";
    }

    static private String toString(Vector cluster) {
	String s = "[ ";
	
	for (int i = 0; i < cluster.size(); i++) {
	    s += cluster.elementAt(i).toString() + " ";
	}

	return s + "]";
    }
}