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// Copyright (c) 2002 Utrecht University (The Netherlands).
// All rights reserved.
//
// This file is part of CGAL (www.cgal.org); you may redistribute it under
// the terms of the Q Public License version 1.0.
// See the file LICENSE.QPL distributed with CGAL.
//
// Licensees holding a valid commercial license may use this file in
// accordance with the commercial license agreement provided with the software.
//
// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
//
// $URL: svn+ssh://scm.gforge.inria.fr/svn/cgal/branches/CGAL-3.2-branch/Spatial_searching/include/CGAL/Orthogonal_k_neighbor_search.h $
// $Id: Orthogonal_k_neighbor_search.h 28567 2006-02-16 14:30:13Z lsaboret $
//
//
// Author(s) : Hans Tangelder (<hanst@cs.uu.nl>)
#ifndef ORTHOGONAL_K_NEIGHBOR_SEARCH_H
#define ORTHOGONAL_K_NEIGHBOR_SEARCH_H
#include <cstring>
#include <list>
#include <queue>
#include <memory>
#include <CGAL/Kd_tree_node.h>
#include <CGAL/Kd_tree.h>
#include <CGAL/Euclidean_distance.h>
#include <CGAL/Splitters.h>
namespace CGAL {
template <class SearchTraits,
class Distance_= Euclidean_distance<SearchTraits>,
class Splitter_= Sliding_midpoint<SearchTraits> ,
class Tree_= Kd_tree<SearchTraits, Splitter_, Tag_true> >
class Orthogonal_k_neighbor_search {
public:
typedef Splitter_ Splitter;
typedef Tree_ Tree;
typedef Distance_ Distance;
typedef typename SearchTraits::Point_d Point_d;
typedef typename Distance::Query_item Query_item;
typedef typename SearchTraits::FT FT;
typedef std::pair<Point_d,FT> Point_with_transformed_distance;
typedef typename Tree::Node_handle Node_handle;
typedef typename Tree::Point_d_iterator Point_d_iterator;
private:
int number_of_internal_nodes_visited;
int number_of_leaf_nodes_visited;
int number_of_items_visited;
bool search_nearest;
FT multiplication_factor;
Query_item query_object;
int total_item_number;
FT distance_to_root;
typedef std::list<Point_with_transformed_distance> NN_list;
public:
typedef typename NN_list::const_iterator iterator;
private:
NN_list l;
int max_k;
int actual_k;
Distance distance_instance;
bool
branch(FT distance)
{
if (actual_k<max_k) return true;
else
if (search_nearest) return
( distance * multiplication_factor < l.rbegin()->second);
else return
( distance >
l.begin()->second * multiplication_factor);
}
void
insert(Point_d* I, FT dist)
{
bool insert;
if (actual_k<max_k) insert=true;
else
if (search_nearest) insert=
( dist < l.rbegin()->second );
else insert=(dist > l.rbegin()->second);
if (insert) {
actual_k++;
typename NN_list::iterator it=l.begin();
if (search_nearest)
for (; (it != l.end()); ++it)
{ if (dist < it->second) break;}
else
for (; (it != l.end()); ++it)
{ if (dist > it->second) break;}
Point_with_transformed_distance NN_Candidate(*I,dist);
l.insert(it,NN_Candidate);
if (actual_k > max_k) {
actual_k--;
l.pop_back();
}
}
}
public:
iterator
begin() const
{
return l.begin();
}
iterator
end() const
{
return l.end();
}
// constructor
Orthogonal_k_neighbor_search(Tree& tree, const Query_item& q,
int k=1, FT Eps=FT(0.0), bool Search_nearest=true, const Distance& d=Distance())
: number_of_internal_nodes_visited(0), number_of_leaf_nodes_visited(0), number_of_items_visited(0),
search_nearest(Search_nearest), multiplication_factor(d.transformed_distance(1.0+Eps)), query_object(q),
total_item_number(tree.size()), max_k(k), actual_k(0), distance_instance(d)
{
if (search_nearest)
distance_to_root = d.min_distance_to_rectangle(q, tree.bounding_box());
else
distance_to_root = d.max_distance_to_rectangle(q, tree.bounding_box());
compute_neighbors_orthogonally(tree.root(), distance_to_root);
}
// Print statistics of the k_neighbor search process.
std::ostream&
statistics (std::ostream& s)
{
s << "K_Neighbor search statistics:" << std::endl;
s << "Number of internal nodes visited:"
<< number_of_internal_nodes_visited << std::endl;
s << "Number of leaf nodes visited:"
<< number_of_leaf_nodes_visited << std::endl;
s << "Number of items visited:"
<< number_of_items_visited << std::endl;
return s;
}
private:
void
compute_neighbors_orthogonally(Node_handle N, FT rd)
{
typename SearchTraits::Construct_cartesian_const_iterator_d construct_it;
typename SearchTraits::Cartesian_const_iterator_d query_object_it = construct_it(query_object);
if (!(N->is_leaf())) {
number_of_internal_nodes_visited++;
int new_cut_dim=N->cutting_dimension();
FT old_off, new_rd;
FT new_off =
*(query_object_it + new_cut_dim) -
N->cutting_value();
if ( ((new_off < FT(0.0)) && (search_nearest)) ||
(( new_off >= FT(0.0)) && (!search_nearest)) ) {
compute_neighbors_orthogonally(N->lower(),rd);
if (search_nearest) {
old_off= *(query_object_it + new_cut_dim)-
N->low_value();
if (old_off>FT(0.0)) old_off=FT(0.0);
}
else
{
old_off= *(query_object_it + new_cut_dim)
- N->high_value();
if (old_off<FT(0.0)) old_off=FT(0.0);
}
new_rd=
distance_instance.new_distance(rd,old_off,
new_off,
new_cut_dim);
if (branch(new_rd))
compute_neighbors_orthogonally(N->upper(),
new_rd);
}
else { // compute new distance
compute_neighbors_orthogonally(N->upper(),rd);
if (search_nearest) {
old_off= N->high_value() -
*(query_object_it + new_cut_dim);
if (old_off>FT(0.0)) old_off=FT(0.0);
}
else
{
old_off= N->low_value() -
*(query_object_it + new_cut_dim);
if (old_off<FT(0.0)) old_off=FT(0.0);
}
new_rd=
distance_instance. new_distance(rd,old_off,
new_off,
new_cut_dim);
if (branch(new_rd))
compute_neighbors_orthogonally(N->lower(),
new_rd);
}
}
else
{
// n is a leaf
number_of_leaf_nodes_visited++;
if (N->size() > 0)
for (Point_d_iterator it=N->begin(); it != N->end(); it++) {
number_of_items_visited++;
FT distance_to_query_object=
distance_instance.transformed_distance(query_object,**it);
insert(*it,distance_to_query_object);
}
}
}
}; // class
} // namespace CGAL
#endif // ORTHOGONAL_K_NEIGHBOR_SEARCH
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