source: trunk/EventBenchCore/src/de/ugoe/cs/eventbench/models/DeterministicFiniteAutomaton.java @ 102

package de.ugoe.cs.eventbench.models;

import java.util.Collection;
import java.util.LinkedList;
import java.util.List;
import java.util.Random;

import de.ugoe.cs.eventbench.data.Event;

/**
 * <p>
 * Implements a Deterministic Finite Automata (DFA) capable of random session
 * generation. It is a special case of a first-order Markov model, where the
 * transition probability is equally high for all following states.
 * </p>
 * 
 * @author Steffen Herbold
 * @version 1.0
 */
public class DeterministicFiniteAutomaton extends FirstOrderMarkovModel {

        /**
         * <p>
         * Id for object serialization.
         * </p>
         */
        private static final long serialVersionUID = 1L;

        /**
         * <p>
         * Constructor. Creates a new DeterministicFiniteAutomaton.
         * </p>
         * 
         * @param r
         *            random number generator used by probabilistic methods of the
         *            class
         */
        public DeterministicFiniteAutomaton(Random r) {
                super(r);
        }

        /**
         * <p>
         * Calculates the proability of the next state. Each of the following states
         * in the automaton is equally probable.
         * </p>
         * 
         * @see de.ugoe.cs.eventbench.models.IStochasticProcess#getProbability(java.util.List,
         *      de.ugoe.cs.eventbench.data.Event)
         */
        @Override
        public double getProbability(List<? extends Event<?>> context,
                        Event<?> symbol) {
                double result = 0.0d;

                List<Event<?>> contextCopy;
                if (context.size() >= trieOrder) {
                        contextCopy = new LinkedList<Event<?>>(context.subList(
                                        context.size() - trieOrder + 1, context.size()));
                } else {
                        contextCopy = new LinkedList<Event<?>>(context);
                }

                Collection<Event<?>> followers = trie.getFollowingSymbols(contextCopy);

                if (followers.size() != 0 && followers.contains(symbol)) {
                        result = 1.0d / followers.size();
                }

                return result;
        }

}