adams.data.featureconverter.Weka.java Source code

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Here is the source code for adams.data.featureconverter.Weka.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 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/>.
 */

/**
 * WekaFeatureConverter.java
 * Copyright (C) 2014 University of Waikato, Hamilton, New Zealand
 */
package adams.data.featureconverter;

import java.util.ArrayList;
import java.util.List;

import weka.core.Attribute;
import weka.core.DenseInstance;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.Utils;

/**
 * Generates features in spreadsheet format.
 * 
 * @author  fracpete (fracpete at waikato dot ac dot nz)
 * @version $Revision$
 */
public class Weka extends AbstractFeatureConverter<Instances, Instance> {

    /** for serialization. */
    private static final long serialVersionUID = 2019318091828718405L;

    /**
     * Returns a string describing the object.
     *
     * @return          a description suitable for displaying in the gui
     */
    @Override
    public String globalInfo() {
        return "Turns the features into Weka format.";
    }

    /**
     * Returns the class of the dataset that the converter generates.
     * 
     * @return      the format
     */
    @Override
    public Class getDatasetFormat() {
        return Instances.class;
    }

    /**
     * Returns the class of the row that the converter generates.
     * 
     * @return      the format
     */
    @Override
    public Class getRowFormat() {
        return Instance.class;
    }

    /**
     * Performs the actual generation of a row from the raw data.
     * 
     * @param data   the data of the row, elements can be null (= missing)
     * @return      the dataset structure
     */
    @Override
    protected Instances doGenerateHeader(HeaderDefinition header) {
        Instances result;
        ArrayList<Attribute> atts;
        ArrayList<String> values;
        int i;

        atts = new ArrayList<Attribute>();
        for (i = 0; i < header.size(); i++) {
            switch (header.getType(i)) {
            case BOOLEAN:
                values = new ArrayList<String>();
                values.add("yes");
                values.add("no");
                atts.add(new Attribute(header.getName(i), values));
                break;
            case NUMERIC:
                atts.add(new Attribute(header.getName(i)));
                break;
            case STRING:
            case UNKNOWN:
                atts.add(new Attribute(header.getName(i), (List<String>) null));
                break;
            }
        }

        result = new Instances(header.getDataset(), atts, 0);

        return result;
    }

    /**
     * Performs the actual generation of a row from the raw data.
     * 
     * @param data   the data of the row, elements can be null (= missing)
     * @return      the dataset structure
     */
    @Override
    protected Instance doGenerateRow(List<Object> data) {
        Instance result;
        int i;
        Object obj;
        double[] values;

        values = new double[m_Header.numAttributes()];

        for (i = 0; i < data.size(); i++) {
            obj = data.get(i);
            if (obj == null) {
                values[i] = Utils.missingValue();
                continue;
            }
            switch (m_HeaderDefinition.getType(i)) {
            case BOOLEAN:
                values[i] = ((Boolean) obj) ? 0.0 : 1.0;
                break;
            case NUMERIC:
                values[i] = ((Number) obj).doubleValue();
                break;
            case STRING:
            case UNKNOWN:
                values[i] = m_Header.attribute(i).addStringValue(obj.toString());
                break;
            }
        }

        result = new DenseInstance(1.0, values);
        result.setDataset(m_Header);

        return result;
    }
}