net.sf.jclal.activelearning.multilabel.querystrategy.AbstractMultiLabelQueryStrategy.java Source code

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Here is the source code for net.sf.jclal.activelearning.multilabel.querystrategy.AbstractMultiLabelQueryStrategy.java

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/*
 * 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., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
 */
package net.sf.jclal.activelearning.multilabel.querystrategy;

import mulan.data.LabelsMetaData;
import net.sf.jclal.activelearning.querystrategy.AbstractQueryStrategy;
import net.sf.jclal.dataset.MulanDataset;
import weka.core.Instance;

/**
 * Abstract class for multi-label query strategies
 *
 */
public abstract class AbstractMultiLabelQueryStrategy extends AbstractQueryStrategy {

    private static final long serialVersionUID = 1L;

    /**
     * The number of labels
     */
    private int numLabels = -1;

    /**
     * Array that stores the label indexes
     */
    private int[] labelIndices;

    public LabelsMetaData labelsMetaData;

    public LabelsMetaData getLabelsMetaData() {

        if (labelsMetaData == null) {
            labelsMetaData = ((MulanDataset) getLabelledData()).getLabelsMetaData();
        }

        return labelsMetaData;
    }

    public int[] getLabelIndices() {

        if (labelIndices == null) {
            labelIndices = ((MulanDataset) getLabelledData()).getLabelIndexes();
        }

        return labelIndices;
    }

    public int getNumLabels() {

        if (numLabels == -1) {
            numLabels = ((MulanDataset) getLabelledData()).getNumLabels();
        }

        return numLabels;
    }

    /**
     * Get the true labels of the instance
     * 
     * @param instance The instance to test
     * @return The true category vector
     */
    public boolean[] getTrueLabels(Instance instance) {

        boolean[] trueLabels = new boolean[getNumLabels()];

        for (int counter = 0; counter < getNumLabels(); counter++) {

            int classIdx = getLabelIndices()[counter];

            String classValue = instance.attribute(classIdx).value((int) instance.value(classIdx));

            trueLabels[counter] = classValue.equals("1");
        }

        return trueLabels;
    }

    @Override
    public void algorithmFinished() {

        labelsMetaData = null;
        labelIndices = null;
    }

}