de.unimannheim.dws.algorithms.CustomPairWiseDistance.java Source code

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Here is the source code for de.unimannheim.dws.algorithms.CustomPairWiseDistance.java

Source

package de.unimannheim.dws.algorithms;

import weka.core.Instance;
import weka.core.Instances;
import weka.core.NormalizableDistance;
import weka.core.RevisionUtils;
import weka.core.TechnicalInformation;
import weka.core.TechnicalInformation.Field;
import weka.core.TechnicalInformation.Type;
import weka.core.neighboursearch.PerformanceStats;
import weka.core.TechnicalInformationHandler;

/*
 *    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 2 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, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/**
 * <!-- options-start --> Valid options are:
 * <p/>
 * 
 * <pre>
 * -D
 *  Turns off the normalization of attribute 
 *  values in distance calculation.
 * </pre>
 * 
 * <pre>
 * -R &lt;col1,col2-col4,...&gt;
 *  Specifies list of columns to used in the calculation of the 
 *  distance. 'first' and 'last' are valid indices.
 *  (default: first-last)
 * </pre>
 * 
 * <pre>
 * -V
 *  Invert matching sense of column indices.
 * </pre>
 * 
 * <!-- options-end -->
 * 
 * @author Jochen Huelss
 * @version $Revision: 1.2 $
 */

public class CustomPairWiseDistance extends NormalizableDistance implements TechnicalInformationHandler {

    /** for serialization. */
    private static final long serialVersionUID = 6783782554224000243L;

    /**
     * Constructs an Manhattan Distance object, Instances must be still set.
     */
    public CustomPairWiseDistance() {
        super();
    }

    /**
     * Constructs an Manhattan Distance object and automatically initializes the
     * ranges.
     * 
     * @param data
     *            the instances the distance function should work on
     */
    public CustomPairWiseDistance(Instances data) {
        super(data);
    }

    /**
     * Returns a string describing this object.
     * 
     * @return a description of the evaluator suitable for displaying in the
     *         explorer/experimenter gui
     */
    public String globalInfo() {
        return "Implements the distance of two semantic web properties based on their pair count "
                + "in the USEWOD 2014 dataset. The distance between two properties is the inverse "
                + "of their count.\n\n" + "For more information, see:\n\n" + getTechnicalInformation().toString();
    }

    /**
     * Returns an instance of a TechnicalInformation object, containing detailed
     * information about the technical background of this class, e.g., paper
     * reference or book this class is based on.
     * 
     * @return the technical information about this class
     */
    public TechnicalInformation getTechnicalInformation() {
        TechnicalInformation result;

        result = new TechnicalInformation(Type.MISC);
        result.setValue(Field.AUTHOR, "Jochen");
        result.setValue(Field.TITLE, "Pair-wise Property Distances");
        result.setValue(Field.URL, "");

        return result;
    }

    /**
     * Updates the current distance calculated so far with the new difference
     * between two attributes. The difference between the attributes was
     * calculated with the difference(int,double,double) method.
     * 
     * @param currDist
     *            the current distance calculated so far
     * @param diff
     *            the difference between two new attributes
     * @return the update distance
     * @see #difference(int, double, double)
     */
    protected double updateDistance(double currDist, double diff) {
        double result;

        result = currDist;
        result += Math.abs(diff);

        return result;
    }

    /**
     * Returns the revision string.
     * 
     * @return the revision
     */
    public String getRevision() {
        return RevisionUtils.extract("$Revision: 1.2 $");
    }

    /**
     * Calculates the distance between two instances. Offers speed up (if the
     * distance function class in use supports it) in nearest neighbour search
     * by taking into account the cutOff or maximum distance. Depending on the
     * distance function class, post processing of the distances by
     * postProcessDistances(double []) may be required if this function is used.
     * 
     * @param first
     *            the first instance
     * @param second
     *            the second instance
     * @param cutOffValue
     *            If the distance being calculated becomes larger than
     *            cutOffValue then the rest of the calculation is discarded.
     * @param stats
     *            the performance stats object
     * @return the distance between the two given instances or
     *         Double.POSITIVE_INFINITY if the distance being calculated becomes
     *         larger than cutOffValue.
     */
    @Override
    public double distance(Instance first, Instance second, double cutOffValue, PerformanceStats stats) {
        double distance = 0;

        Integer value1 = (new Double(first.valueSparse(0))).intValue();
        Integer value2 = (new Double(second.valueSparse(0))).intValue();

        validate();

        if (value1 > value2) {
            Integer helper = value1;
            value1 = value2;
            value2 = helper;
        }
        distance = DistanceMatrix$.MODULE$.getDistance(value1, value2).doubleValue();

        if (distance > cutOffValue) {
            return Double.POSITIVE_INFINITY;
        }

        if (stats != null) {
            stats.incrCoordCount();
        }

        return distance;
    }

}