guineu.modules.dataanalysis.clustering.simplekmeans.SimpleKMeansClusterer.java Source code

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Here is the source code for guineu.modules.dataanalysis.clustering.simplekmeans.SimpleKMeansClusterer.java

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/*
 * Copyright 2007-2013 VTT Biotechnology
 * This file is part of Guineu.
 *
 * Guineu 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 2 of the License, or (at your option) any later
 * version.
 *
 * Guineu 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
 * Guineu; if not, write to the Free Software Foundation, Inc., 51 Franklin St,
 * Fifth Floor, Boston, MA 02110-1301 USA
 */
/**
 * @author Taken from MZmine2
 * http://mzmine.sourceforge.net/
 */

package guineu.modules.dataanalysis.clustering.simplekmeans;

import guineu.modules.dataanalysis.clustering.ClusteringAlgorithm;
import guineu.modules.dataanalysis.clustering.VisualizationType;
import guineu.parameters.ParameterSet;
import java.util.ArrayList;
import java.util.Enumeration;
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;
import weka.clusterers.Clusterer;
import weka.clusterers.SimpleKMeans;
import weka.core.Instance;
import weka.core.Instances;

public class SimpleKMeansClusterer implements ClusteringAlgorithm {

    private ParameterSet parameters;
    private int numberOfGroups = 0;

    public SimpleKMeansClusterer() {
        parameters = new SimpleKMeansClustererParameters();
    }

    public String toString() {
        return "Simple KMeans";
    }

    public ParameterSet getParameterSet() {
        return parameters;
    }

    public List<Integer> getClusterGroups(Instances dataset) {
        List<Integer> clusters = new ArrayList<Integer>();
        String[] options = new String[2];
        Clusterer clusterer = new SimpleKMeans();

        int numberOfGroups = parameters.getParameter(SimpleKMeansClustererParameters.numberOfGroups).getValue();
        options[0] = "-N";
        options[1] = String.valueOf(numberOfGroups);

        try {
            ((SimpleKMeans) clusterer).setOptions(options);
            clusterer.buildClusterer(dataset);
            Enumeration e = dataset.enumerateInstances();
            while (e.hasMoreElements()) {
                clusters.add(clusterer.clusterInstance((Instance) e.nextElement()));
            }
            this.numberOfGroups = clusterer.numberOfClusters();
        } catch (Exception ex) {
            Logger.getLogger(SimpleKMeansClusterer.class.getName()).log(Level.SEVERE, null, ex);
        }
        return clusters;
    }

    public String getHierarchicalCluster(Instances dataset) {
        return null;
    }

    public VisualizationType getVisualizationType() {
        return parameters.getParameter(SimpleKMeansClustererParameters.visualization).getValue();
    }

    public int getNumberOfGroups() {
        return this.numberOfGroups;
    }
}