kdtreenode.hpp

dysii是一款非常出色的滤波函数库

#ifndef INDII_ML_AUX_KDTREENODE_HPP
#define INDII_ML_AUX_KDTREENODE_HPP

#include "PartitionTreeNode.hpp"
#include "Norm.hpp"
#include "Kernel.hpp"
#include "vector.hpp"

namespace indii {
  namespace ml {
    namespace aux {
/**
 * Node of a KD-tree.
 *
 * @author Lawrence Murray <[e-mail]>
 * @version $Rev: 404 $
 * @date $Date: 2008-03-05 14:52:55 +0000 (Wed, 05 Mar 2008) $
 *
 * @param P Degree of the normed vector space (as in \f$\|\cdot\|_p\f$) on
 * which the tree is defined.
 *
 * @section PartitionTreeInternal_serialization Serialization
 *
 * This class supports serialization through the Boost.Serialization
 * library.
 */
class KDTreeNode : public PartitionTreeNode {
public:
  /**
   * Default constructor.
   *
   * This should generally only be used when the object is to be
   * restored from a serialization.
   */
  KDTreeNode();

  /**
   * Destructor.
   */
  virtual ~KDTreeNode();

  /**
   * Get lower bound on the node.
   */
  virtual vector& getLower() = 0;
  
  /**
   * Get upper bound on the node.
   */
  virtual vector& getUpper() = 0;

  /**
   * Find nearest point on hyperrectangle bounary to given point.
   *
   * @param x Query point.
   *
   * @return Nearest point to x on the boundary of the hyperrectangle
   * enclosed by the node.
   */
  virtual vector nearestTo(const vector& x) = 0;

  /**
   * Calculate density at a single point.
   *
   * @param x \f$\mathbf{x}\f$; vector.
   * @param N \f$\|\mathbf{x}\|_p\f$; a norm.
   * @param K \f$K(\|\mathbf{x}\|_p)\f$; a density kernel.
   *
   * @return Density at \f$\mathbf{x}\f$ using the given norm and kernel.
   */
  virtual double densityAt(const vector& x, Norm& N, Kernel& K) = 0;

  /**
   * Sample from the density.
   *
   * @param u Weight between zero and the total weight at the node.
   * @param N \f$\|\mathbf{x}\|_p\f$; a norm.
   * @param K \f$K(\|\mathbf{x}\|_p)\f$; density kernel from which to
   * sample.
   *
   * @return Sample from the distribution defined by the tree, norm and
   * kernel.
   */
  virtual vector sample(const double u, Norm& N, Kernel& K) = 0;

private:
  /**
   * Serialize, or restore from serialization.
   */
  template<class Archive>
  void serialize(Archive& ar, const unsigned int version);

  /*
   * Boost.Serialization requirements.
   */
  friend class boost::serialization::access;

};

    }
  }
}

#include "boost/serialization/base_object.hpp"

template<class Archive>
void indii::ml::aux::KDTreeNode::serialize(Archive& ar,
    const unsigned int version) {
  ar & boost::serialization::base_object<PartitionTreeNode>(*this);
}

#endif