Clustering.WekaHierarchicalClustererWrapper.java Source code

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Here is the source code for Clustering.WekaHierarchicalClustererWrapper.java

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package Clustering;

import java.io.File;
import java.io.FileInputStream;
import java.util.HashMap;
import java.util.List;
import weka.clusterers.HierarchicalClusterer;
import weka.core.Instances;
import weka.core.converters.ConverterUtils;

/**
 * 
 *
 * @author SHKim12
 */
public class WekaHierarchicalClustererWrapper implements ITagListClusterer {

    protected String m_LastErrorMessage;

    public String getLastErrorMessage() {
        return m_LastErrorMessage;
    }

    protected String m_LinkType;
    protected String m_DistanceFunction;
    protected IArffExporter m_ArffExporter;

    private String getLinkTypeOptionString(String linkType) {
        switch (linkType) {
        case "Single":
            return "SINGLE";
        case "Complete":
            return "COMPLETE";
        case "Average":
            return "AVERAGE";
        case "Mean":
            return "MEAN";
        case "Centroid":
            return "CENTROID";
        case "Ward":
            return "WARD";
        case "Adjusted Complete":
            return "ADJCOMPLETE";
        case "Neighbor Joining":
            return "NEIGHBOR_JOINING";
        default:
            return null;
        }
    }

    private String getDistanceFunctionOptionString(String linkType) {
        switch (linkType) {
        case "Manhattan":
            return "weka.core.ManhattanDistance";
        case "Euclidean":
            return "weka.core.EuclideanDistance";
        case "Chebyshev":
            return "weka.core.ChebyshevDistance";
        default:
            return null;
        }
    }

    public WekaHierarchicalClustererWrapper(String linkType, String distanceFunction, IArffExporter arffExporter) {
        m_LinkType = getLinkTypeOptionString(linkType);
        m_DistanceFunction = getDistanceFunctionOptionString(distanceFunction);
        m_ArffExporter = arffExporter;
    }

    public static WekaFeatureWiseHierarchicalClustererWrapper getFeaturewiseClusterer(String linkType,
            String distanceFunction) {
        return new WekaFeatureWiseHierarchicalClustererWrapper(linkType, distanceFunction);
    }

    public static WekaSeriesWiseHierarchicalClustererWrapper getSerieswiseClusterer(String linkType,
            String distanceFunction) {
        return new WekaSeriesWiseHierarchicalClustererWrapper(linkType, distanceFunction);
    }

    @Override
    public String cluster(HashMap<String, List> data) {

        try {
            File arff = m_ArffExporter.getArff(data);
            if (arff == null)
                return null;

            FileInputStream is = new FileInputStream(arff.getAbsolutePath());
            Instances instances = ConverterUtils.DataSource.read(is);
            is.close();

            HierarchicalClusterer cl = new HierarchicalClusterer();

            String[] options = new String[6];
            options[0] = "-N"; // number of clusters should be "1"
            options[1] = "1";
            options[2] = "-L"; // linking type
            options[3] = m_LinkType;
            options[4] = "-A";
            options[5] = m_DistanceFunction;

            cl.setOptions(options);

            cl.buildClusterer(instances);

            String newickString = cl.graph();

            if (!arff.delete())
                arff.deleteOnExit();

            return newickString;

        } catch (Exception ex) {
            //System.out.println( "[EXCEPTION] " + ex.toString() );
            m_LastErrorMessage = ex.getMessage();
            return null;
        }
    }
}