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weka.core.neighboursearch.balltrees.MedianOfWidestDimension Maven / Gradle / Ivy

/*
 *   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 .
 */

/*
 * MedianOfWidestDimension.java
 * Copyright (C) 2007-2012 University of Waikato, Hamilton, New Zealand
 */

package weka.core.neighboursearch.balltrees;

import java.util.Enumeration;
import java.util.Vector;

import weka.core.EuclideanDistance;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.NormalizableDistance;
import weka.core.Option;
import weka.core.OptionHandler;
import weka.core.RevisionUtils;
import weka.core.TechnicalInformation;
import weka.core.TechnicalInformation.Field;
import weka.core.TechnicalInformation.Type;
import weka.core.TechnicalInformationHandler;
import weka.core.Utils;

/**
 *  Class that splits a BallNode of a ball tree based
 * on the median value of the widest dimension of the points in the ball. It
 * essentially implements Omohundro's KD construction algorithm.
 * 

 * 
 * 
 *  BibTeX:
 * 
 * 
 * @techreport{Omohundro1989,
 *    author = {Stephen M. Omohundro},
 *    institution = {International Computer Science Institute},
 *    month = {December},
 *    number = {TR-89-063},
 *    title = {Five Balltree Construction Algorithms},
 *    year = {1989}
 * }
 * 
 * 

 * 
 * 
 *  Valid options are:
 * 

 * 
 * 
 * -N
 *  Normalize dimensions' widths.
 * 
 * 
 * 
 * 
 * @author Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
 * @version $Revision: 10203 $
 */
public class MedianOfWidestDimension extends BallSplitter implements
  OptionHandler, TechnicalInformationHandler {

  /** for serialization. */
  private static final long serialVersionUID = 3054842574468790421L;

  /**
   * Should we normalize the widths(ranges) of the dimensions (attributes)
   * before selecting the widest one.
   */
  protected boolean m_NormalizeDimWidths = true;

  /**
   * Constructor.
   */
  public MedianOfWidestDimension() {
  }

  /**
   * Constructor.
   * 
   * @param instList The master index array.
   * @param insts The instances on which the tree is (or is to be) built.
   * @param e The Euclidean distance function to use for splitting.
   */
  public MedianOfWidestDimension(int[] instList, Instances insts,
    EuclideanDistance e) {
    super(instList, insts, e);
  }

  /**
   * Returns a string describing this nearest neighbour search algorithm.
   * 
   * @return a description of the algorithm for displaying in the
   *         explorer/experimenter gui
   */
  public String globalInfo() {
    return "Class that splits a BallNode of a ball tree based on the "
      + "median value of the widest dimension of the points in the ball. "
      + "It essentially implements Omohundro's  KD construction algorithm.";
  }

  /**
   * 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
   */
  @Override
  public TechnicalInformation getTechnicalInformation() {
    TechnicalInformation result;

    result = new TechnicalInformation(Type.TECHREPORT);
    result.setValue(Field.AUTHOR, "Stephen M. Omohundro");
    result.setValue(Field.YEAR, "1989");
    result.setValue(Field.TITLE, "Five Balltree Construction Algorithms");
    result.setValue(Field.MONTH, "December");
    result.setValue(Field.NUMBER, "TR-89-063");
    result.setValue(Field.INSTITUTION,
      "International Computer Science Institute");

    return result;
  }

  /**
   * Splits a ball into two.
   * 
   * @param node The node to split.
   * @param numNodesCreated The number of nodes that so far have been created
   *          for the tree, so that the newly created nodes are assigned
   *          correct/meaningful node numbers/ids.
   * @throws Exception If there is some problem in splitting the given node.
   */
  @Override
  public void splitNode(BallNode node, int numNodesCreated) throws Exception {
    correctlyInitialized();
    // int[] instList = getNodesInstsList(node);
    double[][] ranges = m_DistanceFunction.initializeRanges(m_Instlist,
      node.m_Start, node.m_End);

    int splitAttrib = widestDim(ranges, m_DistanceFunction.getRanges());

    // In this case median is defined to be either the middle value (in case of
    // odd number of values) or the left of the two middle values (in case of
    // even number of values).
    int medianIdxIdx = node.m_Start + (node.m_End - node.m_Start) / 2;
    // the following finds the median and also re-arranges the array so all
    // elements to the left are < median and those to the right are > median.
    int medianIdx = select(splitAttrib, m_Instlist, node.m_Start, node.m_End,
      (node.m_End - node.m_Start) / 2 + 1); // Utils.select(array, indices,
                                            // node.m_Start, node.m_End,
                                            // (node.m_End-node.m_Start)/2+1);
                                            // //(int)
                                            // (node.m_NumInstances/2D+0.5D);

    Instance pivot;

    node.m_SplitAttrib = splitAttrib;
    node.m_SplitVal = m_Instances.instance(m_Instlist[medianIdx]).value(
      splitAttrib);

    node.m_Left = new BallNode(node.m_Start, medianIdxIdx, numNodesCreated + 1,
      (pivot = BallNode.calcCentroidPivot(node.m_Start, medianIdxIdx,
        m_Instlist, m_Instances)), BallNode.calcRadius(node.m_Start,
        medianIdxIdx, m_Instlist, m_Instances, pivot, m_DistanceFunction));
    node.m_Right = new BallNode(medianIdxIdx + 1, node.m_End,
      numNodesCreated + 2, (pivot = BallNode.calcCentroidPivot(
        medianIdxIdx + 1, node.m_End, m_Instlist, m_Instances)),
      BallNode.calcRadius(medianIdxIdx + 1, node.m_End, m_Instlist,
        m_Instances, pivot, m_DistanceFunction));
  }

  /**
   * Partitions the instances around a pivot. Used by quicksort and
   * kthSmallestValue.
   * 
   * @param attIdx The attribution/dimension based on which the instances should
   *          be partitioned.
   * @param index The master index array containing indices of the instances.
   * @param l The begining index of the portion of master index array that
   *          should be partitioned.
   * @param r The end index of the portion of master index array that should be
   *          partitioned.
   * @return the index of the middle element (in the master index array, i.e.
   *         index of the index of middle element).
   */
  protected int partition(int attIdx, int[] index, int l, int r) {

    double pivot = m_Instances.instance(index[(l + r) / 2]).value(attIdx);
    int help;

    while (l < r) {
      while ((m_Instances.instance(index[l]).value(attIdx) < pivot) && (l < r)) {
        l++;
      }
      while ((m_Instances.instance(index[r]).value(attIdx) > pivot) && (l < r)) {
        r--;
      }
      if (l < r) {
        help = index[l];
        index[l] = index[r];
        index[r] = help;
        l++;
        r--;
      }
    }
    if ((l == r) && (m_Instances.instance(index[r]).value(attIdx) > pivot)) {
      r--;
    }

    return r;
  }

  /**
   * Implements computation of the kth-smallest element according to Manber's
   * "Introduction to Algorithms".
   * 
   * @param attIdx The dimension/attribute of the instances in which to find the
   *          kth-smallest element.
   * @param indices The master index array containing indices of the instances.
   * @param left The begining index of the portion of the master index array in
   *          which to find the kth-smallest element.
   * @param right The end index of the portion of the master index array in
   *          which to find the kth-smallest element.
   * @param k The value of k
   * @return The index of the kth-smallest element
   */
  public int select(int attIdx, int[] indices, int left, int right, int k) {

    if (left == right) {
      return left;
    } else {
      int middle = partition(attIdx, indices, left, right);
      if ((middle - left + 1) >= k) {
        return select(attIdx, indices, left, middle, k);
      } else {
        return select(attIdx, indices, middle + 1, right, k
          - (middle - left + 1));
      }
    }
  }

  /**
   * Returns the widest dimension. The width of each dimension (for the points
   * inside the node) is normalized, if m_NormalizeNodeWidth is set to true.
   * 
   * @param nodeRanges The attributes' range of the points inside the node that
   *          is to be split.
   * @param universe The attributes' range for the whole point-space.
   * @return The index of the attribute/dimension in which the points of the
   *         node have widest spread.
   */
  protected int widestDim(double[][] nodeRanges, double[][] universe) {
    final int classIdx = m_Instances.classIndex();
    double widest = 0.0;
    int w = -1;
    if (m_NormalizeDimWidths) {
      for (int i = 0; i < nodeRanges.length; i++) {
        double newWidest = nodeRanges[i][NormalizableDistance.R_WIDTH]
          / universe[i][NormalizableDistance.R_WIDTH];
        if (newWidest > widest) {
          if (i == classIdx) {
            continue;
          }
          widest = newWidest;
          w = i;
        }
      }
    } else {
      for (int i = 0; i < nodeRanges.length; i++) {
        if (nodeRanges[i][NormalizableDistance.R_WIDTH] > widest) {
          if (i == classIdx) {
            continue;
          }
          widest = nodeRanges[i][NormalizableDistance.R_WIDTH];
          w = i;
        }
      }
    }
    return w;
  }

  /**
   * Returns the tip text for this property.
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String normalizeDimWidthsTipText() {
    return "Whether to normalize the widths(ranges) of the dimensions "
      + "(attributes) before selecting the widest one.";
  }

  /**
   * Should we normalize the widths(ranges) of the dimensions (attributes)
   * before selecting the widest one.
   * 
   * @param normalize Should be true if the widths are to be normalized.
   */
  public void setNormalizeDimWidths(boolean normalize) {
    m_NormalizeDimWidths = normalize;
  }

  /**
   * Whether we are normalizing the widths(ranges) of the dimensions
   * (attributes) or not.
   * 
   * @return true if widths are being normalized.
   */
  public boolean getNormalizeDimWidths() {
    return m_NormalizeDimWidths;
  }

  /**
   * Returns an enumeration describing the available options.
   * 
   * @return an enumeration of all the available options.
   */
  @Override
  public Enumeration listOptions() {
    Vector newVector = new Vector();

    newVector.addElement(new Option("\tNormalize dimensions' widths.", "N", 0,
      "-N"));

    return newVector.elements();
  }

  /**
   * Parses a given list of options.
   * 
   *  Valid options are:
   * 

   * 
   * 
   * -N
   *  Normalize dimensions' widths.
   * 
   * 
   * 
   * 
   * @param options the list of options as an array of strings
   * @throws Exception if an option is not supported
   */
  @Override
  public void setOptions(String[] options) throws Exception {

    setNormalizeDimWidths(Utils.getFlag('N', options));
  }

  /**
   * Gets the current settings.
   * 
   * @return An array of strings suitable for passing to setOptions or to be
   *         displayed by a GenericObjectEditor.
   */
  @Override
  public String[] getOptions() {
    Vector result;

    result = new Vector();

    if (getNormalizeDimWidths()) {
      result.add("-N");
    }

    return result.toArray(new String[result.size()]);
  }

  /**
   * Returns the revision string.
   * 
   * @return the revision
   */
  @Override
  public String getRevision() {
    return RevisionUtils.extract("$Revision: 10203 $");
  }
}