weka.clusterers.RandomizableDensityBasedClusterer.java Source code

Introduction

Here is the source code for weka.clusterers.RandomizableDensityBasedClusterer.java

Source

/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

/*
 * RandomizableDensityBasedClusterer.java
 * Copyright (C) 2006-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.clusterers;

import java.util.Collections;
import java.util.Enumeration;
import java.util.Vector;

import weka.core.Option;
import weka.core.OptionHandler;
import weka.core.Randomizable;
import weka.core.Utils;

/**
 * Abstract utility class for handling settings common to randomizable
 * clusterers.
 * 
 * @author FracPete (fracpete at waikato dot ac dot nz)
 * @version $Revision$
 */
public abstract class RandomizableDensityBasedClusterer extends AbstractDensityBasedClusterer
        implements OptionHandler, Randomizable {

    /** for serialization */
    private static final long serialVersionUID = -5325270357918932849L;

    /** the default seed value */
    protected int m_SeedDefault = 1;

    /** The random number seed. */
    protected int m_Seed = m_SeedDefault;

    /**
     * Returns an enumeration describing the available options.
     * 
     * @return an enumeration of all the available options.
     */
    @Override
    public Enumeration<Option> listOptions() {
        Vector<Option> result = new Vector<Option>();

        result.addElement(
                new Option("\tRandom number seed.\n" + "\t(default " + m_SeedDefault + ")", "S", 1, "-S <num>"));

        result.addAll(Collections.list(super.listOptions()));

        return result.elements();
    }

    /**
     * Parses a given list of options. Valid options are:
     * <p>
     * 
     * @param options the list of options as an array of strings
     * @throws Exception if an option is not supported
     */
    @Override
    public void setOptions(String[] options) throws Exception {
        String tmpStr;

        tmpStr = Utils.getOption('S', options);
        if (tmpStr.length() != 0) {
            setSeed(Integer.parseInt(tmpStr));
        } else {
            setSeed(m_SeedDefault);
        }

        super.setOptions(options);
    }

    /**
     * Gets the current settings of the classifier.
     * 
     * @return an array of strings suitable for passing to setOptions
     */
    @Override
    public String[] getOptions() {

        Vector<String> result = new Vector<String>();

        result.add("-S");
        result.add("" + getSeed());

        Collections.addAll(result, super.getOptions());

        return result.toArray(new String[result.size()]);
    }

    /**
     * Returns the tip text for this property
     * 
     * @return tip text for this property suitable for displaying in the
     *         explorer/experimenter gui
     */
    public String seedTipText() {
        return "The random number seed to be used.";
    }

    /**
     * Set the seed for random number generation.
     * 
     * @param value the seed to use
     */
    @Override
    public void setSeed(int value) {
        m_Seed = value;
    }

    /**
     * Gets the seed for the random number generations
     * 
     * @return the seed for the random number generation
     */
    @Override
    public int getSeed() {
        return m_Seed;
    }
}