balltree.java

矩阵的QR分解算法

        if (leftPivotDist < rightPivotDist) {
          nearestNeighbours(heap, node.m_Left, target, k);
          nearestNeighbours(heap, node.m_Right, target, k);
        } else {
          nearestNeighbours(heap, node.m_Right, target, k);
          nearestNeighbours(heap, node.m_Left, target, k);
        }
      }
      // else see which ball is closer (if dist < 0 target is inside a ball, and
      // hence the ball is closer).
      else {
        if (leftBallDist < rightBallDist) {
          nearestNeighbours(heap, node.m_Left, target, k);
          nearestNeighbours(heap, node.m_Right, target, k);
        } else {
          nearestNeighbours(heap, node.m_Right, target, k);
          nearestNeighbours(heap, node.m_Left, target, k);
        }
      }
    } else if (node.m_Left != null || node.m_Right != null) { // invalid leaves
                                                              // assignment
      throw new Exception("Error: Only one leaf of the built ball tree is " + 
                          "assigned. Please check code.");
    } else if (node.m_Left == null && node.m_Right == null) { // if node is a
                                                              // leaf
      if (m_TreeStats != null) {
        m_TreeStats.updatePointCount(node.numInstances());
        m_TreeStats.incrLeafCount();
      }
      for (int i = node.m_Start; i <= node.m_End; i++) {
        if (target == m_Instances.instance(m_InstList[i])) //for hold-one-out cross-validation
          continue;
        if (heap.totalSize() < k) {
          distance = m_DistanceFunction.distance(target, m_Instances
              .instance(m_InstList[i]), Double.POSITIVE_INFINITY, m_Stats);
          heap.put(m_InstList[i], distance);
        } else {
          MyHeapElement head = heap.peek();
          distance = m_DistanceFunction.distance(target, 
              m_Instances.instance(m_InstList[i]), head.distance, m_Stats);
          if (distance < head.distance) {
            heap.putBySubstitute(m_InstList[i], distance);
          } else if (distance == head.distance) {
            heap.putKthNearest(m_InstList[i], distance);
          }
        }//end else(heap.totalSize())
      }
    }//end else if node is a leaf
  }
  
  /**
   * Returns the nearest instance in the current neighbourhood to the supplied
   * instance.
   * 
   * @param target 	The instance to find the nearest neighbour for.
   * @throws Exception 	if the nearest neighbour could not be found.
   * @return The nearest neighbour of the given target instance.
   */
  public Instance nearestNeighbour(Instance target) throws Exception {
    return kNearestNeighbours(target, 1).instance(0);
  }

 /** 
   * Returns the distances of the k nearest neighbours. The kNearestNeighbours
   * or nearestNeighbour must always be called before calling this function. If
   * this function is called before calling either the kNearestNeighbours or 
   * the nearestNeighbour, then it throws an exception. If, however, any 
   * one of the two functions is called at any point in the past, then no   
   * exception is thrown and the distances of NN(s) from the training set for 
   * the last supplied target instance (to either one of the nearestNeighbour 
   * functions) is/are returned.
   *
   * @return 		array containing the distances of the 
   *            	nearestNeighbours. The length and ordering of the 
   *            	array is the same as that of the instances returned 
   *            	by nearestNeighbour functions.
   * @throws Exception 	if called before calling kNearestNeighbours
   *            	or nearestNeighbours.
   */
  public double[] getDistances() throws Exception {
    if(m_Distances==null)
      throw new Exception("No distances available. Please call either "+
                          "kNearestNeighbours or nearestNeighbours first.");
    return m_Distances;    
  }

  /**
   * Adds one instance to the BallTree. This involves creating/updating the 
   * structure to reflect the newly added training instance 
   * 
   * @param ins The instance to be added. Usually the newly added instance in the
   *            training set.
   * @throws Exception If the instance cannot be added to the tree.
   */
  public void update(Instance ins) throws Exception {
    addInstanceInfo(ins);
    m_InstList = m_TreeConstructor.addInstance(m_Root, ins);    
  }
  
  /** 
   * Adds the given instance's info. This implementation updates the attributes' 
   * range datastructures of EuclideanDistance class.
   * 
   * @param ins		The instance to add the information of. Usually this is
   * 			the test instance supplied to update the range of 
   * 			attributes in the distance function.
   */
  public void addInstanceInfo(Instance ins) {
    if(m_Instances!=null)
      m_DistanceFunction.update(ins);
  }  

  /**
   * Builds the BallTree based on the given set of instances.
   * @param insts The insts for which the BallTree is to be 
   * built. 
   * @throws Exception If some error occurs while 
   * building the BallTree
   */
  public void setInstances(Instances insts) throws Exception {
    super.setInstances(insts);
    buildTree();
  }
  
  /**
   * Returns the tip text for this property.
   * 
   * @return 		tip text for this property suitable for
   * 			displaying in the explorer/experimenter gui
   */
  public String ballTreeConstructorTipText() {
    return "The tree constructor being used.";
  }
      
  /**
   * Returns the BallTreeConstructor currently in use.
   * @return The BallTreeConstructor currently in use.
   */
  public BallTreeConstructor getBallTreeConstructor() {
    return m_TreeConstructor;
  }
  
  /**
   * Sets the BallTreeConstructor for building the BallTree 
   * (default TopDownConstructor).
   * @param constructor The new BallTreeConstructor. 
   */
  public void setBallTreeConstructor(BallTreeConstructor constructor) {
    m_TreeConstructor = constructor;
  }
  
  /**
   * Returns the size of the tree.
   * 
   * @return 		the size of the tree
   */
  public double measureTreeSize() {
    return m_TreeConstructor.getNumNodes();
  }
  
  /**
   * Returns the number of leaves.
   * 
   * @return 		the number of leaves
   */
  public double measureNumLeaves() {
    return m_TreeConstructor.getNumLeaves();
  }
  
  /**
   * Returns the depth of the tree. 
   * 
   * @return 		the number of rules
   */
  public double measureMaxDepth() {
    return m_TreeConstructor.getMaxDepth();
  }
    
  /**
   * Returns an enumeration of the additional measure names.
   * 
   * @return 		an enumeration of the measure names
   */
  public Enumeration enumerateMeasures() {
    Vector newVector = new Vector();
    newVector.addElement("measureTreeSize");
    newVector.addElement("measureNumLeaves");
    newVector.addElement("measureMaxDepth");
    if (m_Stats != null) {
      for (Enumeration e = m_Stats.enumerateMeasures(); e.hasMoreElements();) {
        newVector.addElement(e.nextElement());
      }
    }
    return newVector.elements();
  }
  
  /**
   * Returns the value of the named measure.
   * 
   * @param additionalMeasureName 	the name of the measure to query for 
   * 					its value.
   * @return 				the value of the named measure.
   * @throws IllegalArgumentException 	if the named measure is not supported.
   */
  public double getMeasure(String additionalMeasureName) {
    if (additionalMeasureName.compareToIgnoreCase("measureMaxDepth") == 0) {
      return measureMaxDepth();
    } else if (additionalMeasureName.compareToIgnoreCase("measureTreeSize") == 0) {
      return measureTreeSize();
    } else if (additionalMeasureName.compareToIgnoreCase("measureNumLeaves") == 0) {
      return measureNumLeaves();
    } else if(m_Stats!=null) {
      return m_Stats.getMeasure(additionalMeasureName);
    } else {
      throw new IllegalArgumentException(additionalMeasureName 
			  + " not supported (BallTree)");
    }
  }
  	
  /**
   * Sets whether to calculate the performance statistics or not.
   * @param measurePerformance This should be true if performance
   * statistics are to be calculated.
   */
  public void setMeasurePerformance(boolean measurePerformance) {
    m_MeasurePerformance = measurePerformance;
    if (m_MeasurePerformance) {
      if (m_Stats == null)
        m_Stats = m_TreeStats = new TreePerformanceStats();
    } else
      m_Stats = m_TreeStats = null;
  }
  
  /**
   * Returns an enumeration describing the available options.
   * 
   * @return 		an enumeration of all the available options.
   */
  public Enumeration listOptions() {
    Vector newVector = new Vector();
    
    newVector.addElement(new Option(
	"\tThe construction method to employ. Either TopDown or BottomUp\n"
	+ "\t(default: weka.core.TopDownConstructor)",
	"C", 1, "-C <classname and options>"));

    return newVector.elements();
  }

  /**
   * Parses a given list of options.
   * 
   <!-- options-start -->
   * Valid options are: <p/>
   * 
   * <pre> -C &lt;classname and options&gt;
   *  The construction method to employ. Either TopDown or BottomUp
   *  (default: weka.core.TopDownConstructor)</pre>
   * 
   <!-- options-end --> 
   * 
   * @param options 	the list of options as an array of strings
   * @throws Exception 	if an option is not supported
   */
  public void setOptions(String[] options)
    throws Exception {

    super.setOptions(options);

    String optionString = Utils.getOption('C', options);
    if(optionString.length() != 0) {
      String constructorSpec[] = Utils.splitOptions(optionString);
      if(constructorSpec.length == 0) { 
        throw new Exception("Invalid BallTreeConstructor specification string."); 
      }
      String className = constructorSpec[0];
      constructorSpec[0] = "";

      setBallTreeConstructor( (BallTreeConstructor)
                            Utils.forName( BallTreeConstructor.class, 
                                           className, constructorSpec) );
    }
    else {
      setBallTreeConstructor(new TopDownConstructor());  
    }
  }

  /**
   * Gets the current settings of KDtree.
   * 
   * @return 		an array of strings suitable for passing to setOptions
   */
  public String[] getOptions() {
    Vector<String>	result;
    String[]		options;
    int			i;
    
    result = new Vector<String>();
    
    options = super.getOptions();
    for (i = 0; i < options.length; i++)
      result.add(options[i]);
    
    result.add("-C");
    result.add(
	(m_TreeConstructor.getClass().getName() + " " +
	 Utils.joinOptions(m_TreeConstructor.getOptions())).trim());

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