C++ RectangleTree::Child方法代码示例

RectangleTree<MetricType, StatisticType, MatType, SplitType, DescentType,
              AuxiliaryInformationType>::
RectangleTree(
    const RectangleTree& other,
    const bool deepCopy,
    RectangleTree* newParent) :
    maxNumChildren(other.MaxNumChildren()),
    minNumChildren(other.MinNumChildren()),
    numChildren(other.NumChildren()),
    children(maxNumChildren + 1, NULL),
    parent(deepCopy ? newParent : other.Parent()),
    begin(other.Begin()),
    count(other.Count()),
    numDescendants(other.numDescendants),
    maxLeafSize(other.MaxLeafSize()),
    minLeafSize(other.MinLeafSize()),
    bound(other.bound),
    parentDistance(other.ParentDistance()),
    dataset(deepCopy ?
        (parent ? parent->dataset : new MatType(*other.dataset)) :
        &other.Dataset()),
    ownsDataset(deepCopy && (!parent)),
    points(other.points),
    auxiliaryInfo(other.auxiliaryInfo, this, deepCopy)
{
  if (deepCopy)
  {
    if (numChildren > 0)
    {
      for (size_t i = 0; i < numChildren; i++)
        children[i] = new RectangleTree(other.Child(i), true, this);
    }
  }
  else
    children = other.children;
}

void RectangleTree<MetricType, StatisticType, MatType, SplitType, DescentType,
                   AuxiliaryInformationType>::
DualTreeTraverser<RuleType>::Traverse(RectangleTree& queryNode,
                                      RectangleTree& referenceNode)
{
  // Increment the visit counter.
  ++numVisited;

  // Store the current traversal info.
  traversalInfo = rule.TraversalInfo();

  // We now have four options.
  // 1)  Both nodes are leaf nodes.
  // 2)  Only the reference node is a leaf node.
  // 3)  Only the query node is a leaf node.
  // 4)  Niether node is a leaf node.
  // We go through those options in that order.

  if (queryNode.IsLeaf() && referenceNode.IsLeaf())
  {
    // Evaluate the base case.  Do the query points on the outside so we can
    // possibly prune the reference node for that particular point.
    for (size_t query = 0; query < queryNode.Count(); ++query)
    {
      // Restore the traversal information.
      rule.TraversalInfo() = traversalInfo;
      const double childScore = rule.Score(queryNode.Point(query),
          referenceNode);

      if (childScore == DBL_MAX)
        continue;  // We don't require a search in this reference node.

      for(size_t ref = 0; ref < referenceNode.Count(); ++ref)
        rule.BaseCase(queryNode.Point(query), referenceNode.Point(ref));

      numBaseCases += referenceNode.Count();
    }
  }
  else if (!queryNode.IsLeaf() && referenceNode.IsLeaf())
  {
    // We only need to traverse down the query node.  Order doesn't matter here.
    for (size_t i = 0; i < queryNode.NumChildren(); ++i)
    {
      // Before recursing, we have to set the traversal information correctly.
      rule.TraversalInfo() = traversalInfo;
      ++numScores;
      if (rule.Score(queryNode.Child(i), referenceNode) < DBL_MAX)
        Traverse(queryNode.Child(i), referenceNode);
      else
        numPrunes++;
    }
  }
  else if (queryNode.IsLeaf() && !referenceNode.IsLeaf())
  {
    // We only need to traverse down the reference node.  Order does matter
    // here.

    // We sort the children of the reference node by their scores.
    std::vector<NodeAndScore> nodesAndScores(referenceNode.NumChildren());
    for (size_t i = 0; i < referenceNode.NumChildren(); i++)
    {
      rule.TraversalInfo() = traversalInfo;
      nodesAndScores[i].node = &(referenceNode.Child(i));
      nodesAndScores[i].score = rule.Score(queryNode,
          *(nodesAndScores[i].node));
      nodesAndScores[i].travInfo = rule.TraversalInfo();
    }
    std::sort(nodesAndScores.begin(), nodesAndScores.end(), nodeComparator);
    numScores += nodesAndScores.size();

    for (size_t i = 0; i < nodesAndScores.size(); i++)
    {
      rule.TraversalInfo() = nodesAndScores[i].travInfo;
      if (rule.Rescore(queryNode, *(nodesAndScores[i].node),
          nodesAndScores[i].score) < DBL_MAX)
      {
        Traverse(queryNode, *(nodesAndScores[i].node));
      }
      else
      {
        numPrunes += nodesAndScores.size() - i;
        break;
      }
    }
  }
  else
  {
    // We need to traverse down both the reference and the query trees.
    // We loop through all of the query nodes, and for each of them, we
    // loop through the reference nodes to see where we need to descend.
    for (size_t j = 0; j < queryNode.NumChildren(); j++)
    {
      // We sort the children of the reference node by their scores.
      std::vector<NodeAndScore> nodesAndScores(referenceNode.NumChildren());
      for (size_t i = 0; i < referenceNode.NumChildren(); i++)
      {
        rule.TraversalInfo() = traversalInfo;
        nodesAndScores[i].node = &(referenceNode.Child(i));
        nodesAndScores[i].score = rule.Score(queryNode.Child(j),
            *nodesAndScores[i].node);
//.........这里部分代码省略.........