source: trunk/EventBenchConsole/src/de/ugoe/cs/eventbench/commands/CMDtrainPPM.java

package de.ugoe.cs.eventbench.commands;

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

import de.ugoe.cs.eventbench.models.PredictionByPartialMatch;
import de.ugoe.cs.eventbench.models.TrieBasedModel;
import de.ugoe.cs.util.console.Console;

/**
 * <p>
 * Command that trains Prediction by Partial Match (PPM) models.
 * </p>
 * 
 * @author Steffen Herbold
 * @version 2.0
 */
public class CMDtrainPPM extends AbstractTrainCommand {

        /**
         * <p>
         * Escape probability of the PPM model.
         * </p>
         */
        double probEscape;

        /**
         * <p>
         * Maximal Markov order of the PPM model.
         * </p>
         */
        int maxOrder;

        /**
         * <p>
         * Minimal Markov order of the PPM model. Default: 0
         * </p>
         */
        int minOrder = 0;

        /*
         * (non-Javadoc)
         * 
         * @see de.ugoe.cs.util.console.Command#help()
         */
        @Override
        public void help() {
                Console.println("Usage: trainPPM <modelName> <sequencesName> <probEscape> <maxOrder> {<minOrder>}");
        }

        /**
         * <p>
         * Handles the parameters probEscape, maxOrder, and minOrder.
         * </p>
         * 
         * @see de.ugoe.cs.eventbench.commands.AbstractTrainCommand#handleOptionalParameters(java.util.List)
         */
        @Override
        void handleAdditionalParameters(List<Object> parameters) throws Exception {
                probEscape = Double.parseDouble((String) parameters.get(2));
                maxOrder = Integer.parseInt((String) parameters.get(3));
                if (parameters.size() == 5) {
                        minOrder = Integer.parseInt((String) parameters.get(4));
                }
        }

        /*
         * (non-Javadoc)
         * 
         * @see de.ugoe.cs.eventbench.commands.AbstractTrainCommand#createModel()
         */
        @Override
        TrieBasedModel createModel() {
                return new PredictionByPartialMatch(maxOrder, minOrder, new Random(),
                                probEscape);
        }

}