source: trunk/EventBenchCore/src/de/ugoe/cs/eventbench/models/PredictionByPartialMatch.java @ 93

package de.ugoe.cs.eventbench.models;

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

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

public class PredictionByPartialMatch extends TrieBasedModel {
        
        /**
         * Id for object serialization.
         */
        private static final long serialVersionUID = 1L;
        
        double probEscape;
        
        public PredictionByPartialMatch(int markovOrder, Random r) {
                this(markovOrder, r, 0.1);
        }
        
        public PredictionByPartialMatch(int markovOrder, Random r, double probEscape) {
                super(markovOrder, r);
                this.probEscape = probEscape;
        }
        
        public void setProbEscape(double probEscape) {
                this.probEscape = probEscape;
        }
        
        public double getProbEscape() {
                return probEscape;
        }
        
        @Override
        public double getProbability(List<? extends Event<?>> context, Event<?> symbol) {
                double result = 0.0d;
                double resultCurrentContex = 0.0d;
                double resultShorterContex = 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);
                }

        
                List<Event<?>> followers = trie.getFollowingSymbols(contextCopy); // \Sigma'
                int sumCountFollowers = 0; // N(s\sigma')
                for( Event<?> follower : followers ) {
                        sumCountFollowers += trie.getCount(contextCopy, follower);
                }
                
                int countSymbol = trie.getCount(contextCopy, symbol); // N(s\sigma)
                if( contextCopy.size()==0 ) {
                        resultCurrentContex = ((double) countSymbol) / sumCountFollowers;
                } else {
                        if( sumCountFollowers==0 ) {
                                resultCurrentContex = 0.0;
                        }
                        else {
                                resultCurrentContex = ((double) countSymbol / sumCountFollowers)*(1-probEscape);
                        }
                        contextCopy.remove(0); 
                        double probSuffix = getProbability(contextCopy, symbol);
                        if( followers.size()==0 ) {
                                resultShorterContex = probSuffix;
                        } else {
                                resultShorterContex = probEscape*probSuffix;
                        }
                }
                result = resultCurrentContex+resultShorterContex;
                
                return result;
        }
}