dual_tree_traverser.hpp

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#ifndef MLPACK_CORE_TREE_RECTANGLE_TREE_DUAL_TREE_TRAVERSER_HPP
#define MLPACK_CORE_TREE_RECTANGLE_TREE_DUAL_TREE_TRAVERSER_HPP

#include <mlpack/prereqs.hpp>

#include "rectangle_tree.hpp"

namespace mlpack {
namespace tree {

template<typename MetricType,
         typename StatisticType,
         typename MatType,
         typename SplitType,
         typename DescentType,
         template<typename> class AuxiliaryInformationType>
template<typename RuleType>
class RectangleTree<MetricType, StatisticType, MatType, SplitType,
                    DescentType, AuxiliaryInformationType>::DualTreeTraverser
{
 public:
  DualTreeTraverser(RuleType& rule);

  void Traverse(RectangleTree& queryNode, RectangleTree& referenceNode);

  size_t NumPrunes() const { return numPrunes; }
  size_t& NumPrunes() { return numPrunes; }

  size_t NumVisited() const { return numVisited; }
  size_t& NumVisited() { return numVisited; }

  size_t NumScores() const { return numScores; }
  size_t& NumScores() { return numScores; }

  size_t NumBaseCases() const { return numBaseCases; }
  size_t& NumBaseCases() { return numBaseCases; }

 private:

  // We use this struct and this function to make the sorting and scoring easy
  // and efficient:
  struct NodeAndScore
  {
    RectangleTree* node;
    double score;
    typename RuleType::TraversalInfoType travInfo;
  };

  static bool nodeComparator(const NodeAndScore& obj1,
                             const NodeAndScore& obj2)
  {
    return obj1.score < obj2.score;
  }

  RuleType& rule;

  size_t numPrunes;

  size_t numVisited;

  size_t numScores;

  size_t numBaseCases;

  typename RuleType::TraversalInfoType traversalInfo;
};

} // namespace tree
} // namespace mlpack

// Include implementation.
#include "dual_tree_traverser_impl.hpp"

#endif