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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This is the stable version. Apart from bugfixes, this version does not receive any other updates.

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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 .
 */

/*
 *   RemoteResult.java
 *   Copyright (C) 2003-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.gui.boundaryvisualizer;

import java.io.Serializable;

/**
 * Class that encapsulates a result (and progress info) for part of a
 * distributed boundary visualization. The result of a sub-task is the
 * probabilities necessary to display one row of the final visualization.
 * 
 * @author Mark Hall
 * @version $Revision: 10222 $
 * @since 1.0
 * @see Serializable
 */
public class RemoteResult implements Serializable {

  /** for serialization */
  private static final long serialVersionUID = 1873271280044633808L;

  /** the row number that this result corresponds to */
  // private int m_rowNumber; NOT USED

  /** how many pixels in a row */
  // private int m_rowLength; NOT USED

  /**
   * the result - ie. the probability distributions produced by the classifier
   * for this row in the visualization
   */
  private final double[][] m_probabilities;

  /** progress on computing this row */
  private int m_percentCompleted;

  /**
   * Creates a new RemoteResult instance.
   * 
   * @param rowNum the row number
   * @param rowLength the number of pixels in the row
   */
  public RemoteResult(int rowNum, int rowLength) {
    m_probabilities = new double[rowLength][0];
  }

  /**
   * Store the classifier's distribution for a particular pixel in the
   * visualization
   * 
   * @param index the pixel
   * @param distribution the probability distribution from the classifier
   */
  public void setLocationProbs(int index, double[] distribution) {
    m_probabilities[index] = distribution;
  }

  /**
   * Return the probability distributions for this row in the visualization
   * 
   * @return the probability distributions
   */
  public double[][] getProbabilities() {
    return m_probabilities;
  }

  /**
   * Set the progress for this row so far
   * 
   * @param pc a percent completed value
   */
  public void setPercentCompleted(int pc) {
    m_percentCompleted = pc;
  }

  /**
   * Return the progress for this row
   * 
   * @return a percent completed value
   */
  public int getPercentCompleted() {
    return m_percentCompleted;
  }
}