mirror of https://github.com/CGAL/cgal
664 lines
21 KiB
C++
664 lines
21 KiB
C++
// Copyright (c) 2002,2011 Utrecht University (The Netherlands).
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// All rights reserved.
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//
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// This file is part of CGAL (www.cgal.org).
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//
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// $URL$
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// $Id$
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// SPDX-License-Identifier: GPL-3.0-or-later OR LicenseRef-Commercial
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//
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//
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// Author(s) : Hans Tangelder (<hanst@cs.uu.nl>)
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// Clement Jamin (clement.jamin.pro@gmail.com)
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#ifndef CGAL_ORTHOGONAL_INCREMENTAL_NEIGHBOR_SEARCH
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#define CGAL_ORTHOGONAL_INCREMENTAL_NEIGHBOR_SEARCH
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#include <CGAL/license/Spatial_searching.h>
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#include <CGAL/disable_warnings.h>
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#include <CGAL/Kd_tree.h>
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#include <CGAL/Euclidean_distance.h>
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#include <CGAL/tuple.h>
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#include <CGAL/Spatial_searching/internal/Search_helpers.h>
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#include <cstring>
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#include <list>
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#include <queue>
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#include <memory>
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#include <iterator> // for std::distance
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#include <tuple> // std::get for tuple
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namespace CGAL {
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template <class SearchTraits,
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class Distance_= typename internal::Spatial_searching_default_distance<SearchTraits>::type,
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class Splitter_ = Sliding_midpoint<SearchTraits>,
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class Tree_= Kd_tree<SearchTraits, Splitter_, Tag_true, Tag_false> >
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class Orthogonal_incremental_neighbor_search {
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public:
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typedef Splitter_ Splitter;
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typedef Tree_ Tree;
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typedef Distance_ Distance;
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typedef typename SearchTraits::Point_d Point_d;
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typedef typename Distance::Query_item Query_item;
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typedef typename SearchTraits::FT FT;
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typedef typename Tree::Point_d_iterator Point_d_iterator;
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typedef typename Tree::Node_const_handle Node_const_handle;
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typedef std::pair<Point_d,FT> Point_with_transformed_distance;
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typedef std::tuple<Node_const_handle,FT,std::vector<FT> > Node_with_distance;
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typedef std::vector<Node_with_distance*> Node_with_distance_vector;
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typedef std::vector<Point_with_transformed_distance*> Point_with_transformed_distance_vector;
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template<class T>
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struct Object_wrapper
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{
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T object;
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Object_wrapper(const T& t):object(t){}
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const T& operator* () const { return object; }
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const T* operator-> () const { return &object; }
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};
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class Iterator_implementation {
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SearchTraits traits;
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public:
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int number_of_neighbours_computed;
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int number_of_internal_nodes_visited;
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int number_of_leaf_nodes_visited;
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int number_of_items_visited;
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private:
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typedef std::vector<FT> Distance_vector;
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Distance_vector dists;
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Distance orthogonal_distance_instance;
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internal::Distance_helper<Distance, SearchTraits> m_distance_helper;
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FT multiplication_factor;
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Query_item query_point;
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FT distance_to_root;
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bool search_nearest_neighbour;
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FT rd;
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int m_dim;
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Tree const& m_tree;
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class Priority_higher {
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public:
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bool search_nearest;
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Priority_higher(bool search_the_nearest_neighbour)
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: search_nearest(search_the_nearest_neighbour)
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{}
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//highest priority is smallest distance
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bool
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operator() (Node_with_distance* n1, Node_with_distance* n2) const
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{
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return (search_nearest) ? (std::get<1>(*n1) > std::get<1>(*n2)) : (std::get<1>(*n2) > std::get<1>(*n1));
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}
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};
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class Distance_smaller {
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public:
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bool search_nearest;
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Distance_smaller(bool search_the_nearest_neighbour)
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: search_nearest(search_the_nearest_neighbour)
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{}
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//highest priority is smallest distance
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bool operator() (Point_with_transformed_distance* p1, Point_with_transformed_distance* p2) const
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{
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return (search_nearest) ? (p1->second > p2->second) : (p2->second > p1->second);
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}
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};
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std::priority_queue<Node_with_distance*, Node_with_distance_vector,
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Priority_higher> PriorityQueue;
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public:
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std::priority_queue<Point_with_transformed_distance*, Point_with_transformed_distance_vector,
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Distance_smaller> Item_PriorityQueue;
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public:
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int reference_count;
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// constructor
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Iterator_implementation(const Tree& tree,const Query_item& q, const Distance& tr,
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FT Eps=FT(0.0), bool search_nearest=true)
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: traits(tree.traits()),number_of_neighbours_computed(0), number_of_internal_nodes_visited(0),
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number_of_leaf_nodes_visited(0), number_of_items_visited(0),
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orthogonal_distance_instance(tr),
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m_distance_helper(orthogonal_distance_instance, traits),
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multiplication_factor(orthogonal_distance_instance.transformed_distance(FT(1.0)+Eps)),
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query_point(q), search_nearest_neighbour(search_nearest),
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m_tree(tree),
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PriorityQueue(Priority_higher(search_nearest)), Item_PriorityQueue(Distance_smaller(search_nearest)),
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reference_count(1)
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{
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if (m_tree.empty()) return;
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typename SearchTraits::Construct_cartesian_const_iterator_d ccci=traits.construct_cartesian_const_iterator_d_object();
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m_dim = static_cast<int>(std::distance(ccci(q), ccci(q,0)));
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dists.resize(m_dim);
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for(int i=0 ; i<m_dim ; ++i){
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dists[i] = 0;
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}
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if (search_nearest){
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distance_to_root=
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orthogonal_distance_instance.min_distance_to_rectangle(q, m_tree.bounding_box(),dists);
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Node_with_distance *The_Root = new Node_with_distance(m_tree.root(),
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distance_to_root, dists);
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PriorityQueue.push(The_Root);
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// rd is the distance of the top of the priority queue to q
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rd=std::get<1>(*The_Root);
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Compute_the_next_nearest_neighbour();
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}
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else{
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distance_to_root=
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orthogonal_distance_instance.max_distance_to_rectangle(q,
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m_tree.bounding_box(), dists);
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Node_with_distance *The_Root = new Node_with_distance(m_tree.root(),
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distance_to_root, dists);
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PriorityQueue.push(The_Root);
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// rd is the distance of the top of the priority queue to q
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rd=std::get<1>(*The_Root);
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Compute_the_next_furthest_neighbour();
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}
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}
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// * operator
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const Point_with_transformed_distance&
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operator* () const
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{
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return *(Item_PriorityQueue.top());
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}
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// prefix operator
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Iterator_implementation&
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operator++()
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{
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Delete_the_current_item_top();
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if(search_nearest_neighbour)
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Compute_the_next_nearest_neighbour();
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else
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Compute_the_next_furthest_neighbour();
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return *this;
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}
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// postfix operator
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Object_wrapper<Point_with_transformed_distance>
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operator++(int)
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{
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Object_wrapper<Point_with_transformed_distance> result( *(Item_PriorityQueue.top()) );
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++*this;
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return result;
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}
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// Print statistics of the general priority search process.
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std::ostream&
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statistics (std::ostream& s) const {
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s << "Orthogonal priority search statistics:"
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<< std::endl;
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s << "Number of internal nodes visited:"
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<< number_of_internal_nodes_visited << std::endl;
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s << "Number of leaf nodes visited:"
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<< number_of_leaf_nodes_visited << std::endl;
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s << "Number of items visited:"
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<< number_of_items_visited << std::endl;
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s << "Number of neighbours computed:"
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<< number_of_neighbours_computed << std::endl;
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return s;
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}
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//destructor
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~Iterator_implementation()
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{
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while (!PriorityQueue.empty()) {
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Node_with_distance* The_top=PriorityQueue.top();
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PriorityQueue.pop();
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delete The_top;
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}
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while (!Item_PriorityQueue.empty()) {
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Point_with_transformed_distance* The_top=Item_PriorityQueue.top();
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Item_PriorityQueue.pop();
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delete The_top;
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}
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}
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private:
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void
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Delete_the_current_item_top()
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{
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Point_with_transformed_distance* The_item_top=Item_PriorityQueue.top();
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Item_PriorityQueue.pop();
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delete The_item_top;
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}
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// With cache
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bool search_in_leaf(typename Tree::Leaf_node_const_handle node, Tag_true, bool search_furthest)
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{
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typename Tree::iterator it_node_point = node->begin(), it_node_point_end = node->end();
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typename std::vector<FT>::const_iterator cache_point_begin = m_tree.cache_begin() + m_dim*(it_node_point - m_tree.begin());
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for (; it_node_point != it_node_point_end; ++it_node_point)
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{
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number_of_items_visited++;
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FT distance_to_query_point =
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m_distance_helper.transformed_distance_from_coordinates(
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query_point, *it_node_point, cache_point_begin, cache_point_begin + m_dim);
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Point_with_transformed_distance *NN_Candidate =
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new Point_with_transformed_distance(*it_node_point, distance_to_query_point);
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Item_PriorityQueue.push(NN_Candidate);
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cache_point_begin += m_dim;
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}
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// old top of PriorityQueue has been processed,
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// hence update rd
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bool next_neighbour_found;
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if (!(PriorityQueue.empty()))
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{
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rd = std::get<1>(*PriorityQueue.top());
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next_neighbour_found = (search_furthest ?
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multiplication_factor*rd < Item_PriorityQueue.top()->second
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: multiplication_factor*rd > Item_PriorityQueue.top()->second);
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}
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else // priority queue empty => last neighbour found
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{
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next_neighbour_found = true;
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}
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number_of_neighbours_computed++;
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return next_neighbour_found;
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}
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// Without cache
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bool search_in_leaf(typename Tree::Leaf_node_const_handle node, Tag_false, bool search_furthest)
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{
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typename Tree::iterator it_node_point = node->begin(), it_node_point_end = node->end();
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for (; it_node_point != it_node_point_end; ++it_node_point)
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{
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number_of_items_visited++;
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FT distance_to_query_point=
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orthogonal_distance_instance.transformed_distance(query_point, *it_node_point);
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Point_with_transformed_distance *NN_Candidate =
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new Point_with_transformed_distance(*it_node_point, distance_to_query_point);
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Item_PriorityQueue.push(NN_Candidate);
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}
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// old top of PriorityQueue has been processed,
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// hence update rd
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bool next_neighbour_found;
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if (!(PriorityQueue.empty()))
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{
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rd = std::get<1>(*PriorityQueue.top());
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next_neighbour_found = (search_furthest ?
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multiplication_factor*rd < Item_PriorityQueue.top()->second
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: multiplication_factor*rd > Item_PriorityQueue.top()->second);
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}
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else // priority queue empty => last neighbour found
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{
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next_neighbour_found=true;
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}
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number_of_neighbours_computed++;
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return next_neighbour_found;
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}
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void
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Compute_the_next_nearest_neighbour()
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{
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// compute the next item
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bool next_neighbour_found=false;
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if (!(Item_PriorityQueue.empty())) {
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next_neighbour_found=
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(multiplication_factor*rd > Item_PriorityQueue.top()->second);
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}
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object();
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typename SearchTraits::Cartesian_const_iterator_d query_point_it = construct_it(query_point);
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// otherwise browse the tree further
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while ((!next_neighbour_found) && (!PriorityQueue.empty())) {
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Node_with_distance* The_node_top=PriorityQueue.top();
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Node_const_handle N= std::get<0>(*The_node_top);
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dists = std::get<2>(*The_node_top);
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PriorityQueue.pop();
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delete The_node_top;
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FT copy_rd=rd;
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while (!(N->is_leaf())) { // compute new distance
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typename Tree::Internal_node_const_handle node =
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static_cast<typename Tree::Internal_node_const_handle>(N);
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number_of_internal_nodes_visited++;
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int new_cut_dim=node->cutting_dimension();
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FT new_rd,dst = dists[new_cut_dim];
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FT val = *(query_point_it + new_cut_dim);
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FT diff1 = val - node->upper_low_value();
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FT diff2 = val - node->lower_high_value();
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if (diff1 + diff2 < FT(0.0)) {
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new_rd=
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orthogonal_distance_instance.new_distance(copy_rd,dst,diff1,new_cut_dim);
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CGAL_assertion(new_rd >= copy_rd);
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dists[new_cut_dim] = diff1;
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Node_with_distance *Upper_Child =
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new Node_with_distance(node->upper(), new_rd, dists);
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PriorityQueue.push(Upper_Child);
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dists[new_cut_dim] = dst;
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N=node->lower();
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}
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else { // compute new distance
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new_rd=orthogonal_distance_instance.new_distance(copy_rd,dst,diff2,new_cut_dim);
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CGAL_assertion(new_rd >= copy_rd);
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dists[new_cut_dim] = diff2;
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Node_with_distance *Lower_Child =
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new Node_with_distance(node->lower(), new_rd, dists);
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PriorityQueue.push(Lower_Child);
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dists[new_cut_dim] = dst;
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N=node->upper();
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}
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}
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// n is a leaf
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typename Tree::Leaf_node_const_handle node =
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static_cast<typename Tree::Leaf_node_const_handle>(N);
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number_of_leaf_nodes_visited++;
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if (node->size() > 0) {
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typename internal::Has_points_cache<Tree, internal::has_Enable_points_cache<Tree>::type::value>::type dummy;
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next_neighbour_found = search_in_leaf(node, dummy, false);
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}
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} // next_neighbour_found or priority queue is empty
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// in the latter case also the item priority quee is empty
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}
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void
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Compute_the_next_furthest_neighbour()
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{
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// compute the next item
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bool next_neighbour_found=false;
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if (!(Item_PriorityQueue.empty())) {
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next_neighbour_found=
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(rd < multiplication_factor*Item_PriorityQueue.top()->second);
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}
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typename SearchTraits::Construct_cartesian_const_iterator_d construct_it=traits.construct_cartesian_const_iterator_d_object();
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typename SearchTraits::Cartesian_const_iterator_d query_point_it = construct_it(query_point);
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// otherwise browse the tree further
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while ((!next_neighbour_found) && (!PriorityQueue.empty())) {
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Node_with_distance* The_node_top=PriorityQueue.top();
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Node_const_handle N= std::get<0>(*The_node_top);
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dists = std::get<2>(*The_node_top);
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PriorityQueue.pop();
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delete The_node_top;
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FT copy_rd=rd;
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while (!(N->is_leaf())) { // compute new distance
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typename Tree::Internal_node_const_handle node =
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static_cast<typename Tree::Internal_node_const_handle>(N);
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number_of_internal_nodes_visited++;
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int new_cut_dim=node->cutting_dimension();
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FT new_rd,dst = dists[new_cut_dim];
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FT val = *(query_point_it + new_cut_dim);
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FT diff1 = val - node->upper_low_value();
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FT diff2 = val - node->lower_high_value();
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if (diff1 + diff2 < FT(0.0)) {
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diff1 = val - node->upper_high_value();
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new_rd=
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orthogonal_distance_instance.new_distance(copy_rd,dst,diff1,new_cut_dim);
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Node_with_distance *Lower_Child =
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new Node_with_distance(node->lower(), copy_rd, dists);
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PriorityQueue.push(Lower_Child);
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N=node->upper();
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dists[new_cut_dim] = diff1;
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copy_rd=new_rd;
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}
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else { // compute new distance
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diff2 = val - node->lower_low_value();
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new_rd=orthogonal_distance_instance.new_distance(copy_rd,dst,diff2,new_cut_dim);
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Node_with_distance *Upper_Child =
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new Node_with_distance(node->upper(), copy_rd, dists);
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PriorityQueue.push(Upper_Child);
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N=node->lower();
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dists[new_cut_dim] = diff2;
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copy_rd=new_rd;
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}
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}
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// n is a leaf
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typename Tree::Leaf_node_const_handle node =
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static_cast<typename Tree::Leaf_node_const_handle>(N);
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number_of_leaf_nodes_visited++;
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if (node->size() > 0) {
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typename internal::Has_points_cache<Tree, internal::has_Enable_points_cache<Tree>::type::value>::type dummy;
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next_neighbour_found = search_in_leaf(node, dummy, true);
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}
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} // next_neighbour_found or priority queue is empty
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// in the latter case also the item priority quee is empty
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}
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}; // class Iterator_implementaion
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public:
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class iterator;
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typedef iterator const_iterator;
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// constructor
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Orthogonal_incremental_neighbor_search(const Tree& tree,
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const Query_item& q, FT Eps = FT(0.0),
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bool search_nearest=true, const Distance& tr=Distance())
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: m_tree(tree),m_query(q),m_dist(tr),m_Eps(Eps),m_search_nearest(search_nearest)
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{}
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iterator
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begin() const
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{
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return iterator(m_tree,m_query,m_dist,m_Eps,m_search_nearest);
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}
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iterator
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end() const
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{
|
|
return iterator();
|
|
}
|
|
|
|
std::ostream&
|
|
statistics(std::ostream& s)
|
|
{
|
|
begin()->statistics(s);
|
|
return s;
|
|
}
|
|
|
|
|
|
|
|
|
|
class iterator {
|
|
|
|
public:
|
|
|
|
typedef std::input_iterator_tag iterator_category;
|
|
typedef Point_with_transformed_distance value_type;
|
|
typedef const Point_with_transformed_distance* pointer;
|
|
typedef const Point_with_transformed_distance& reference;
|
|
typedef std::size_t size_type;
|
|
typedef std::ptrdiff_t difference_type;
|
|
typedef int distance_type;
|
|
|
|
//class Iterator_implementation;
|
|
Iterator_implementation *Ptr_implementation;
|
|
|
|
|
|
public:
|
|
|
|
// default constructor
|
|
iterator()
|
|
: Ptr_implementation(0)
|
|
{}
|
|
|
|
int
|
|
the_number_of_items_visited()
|
|
{
|
|
return Ptr_implementation->number_of_items_visited;
|
|
}
|
|
|
|
// constructor
|
|
iterator(const Tree& tree,const Query_item& q, const Distance& tr=Distance(), FT eps=FT(0.0),
|
|
bool search_nearest=true)
|
|
: Ptr_implementation(new Iterator_implementation(tree, q, tr, eps, search_nearest))
|
|
{}
|
|
|
|
// copy constructor
|
|
iterator(const iterator& Iter)
|
|
{
|
|
Ptr_implementation = Iter.Ptr_implementation;
|
|
if (Ptr_implementation != 0) Ptr_implementation->reference_count++;
|
|
}
|
|
|
|
iterator& operator=(const iterator& Iter)
|
|
{
|
|
if (Ptr_implementation != Iter.Ptr_implementation){
|
|
if (Ptr_implementation != 0 && --(Ptr_implementation->reference_count)==0) {
|
|
delete Ptr_implementation;
|
|
}
|
|
Ptr_implementation = Iter.Ptr_implementation;
|
|
if (Ptr_implementation != 0) Ptr_implementation->reference_count++;
|
|
}
|
|
return *this;
|
|
}
|
|
|
|
|
|
const Point_with_transformed_distance&
|
|
operator* () const
|
|
{
|
|
return *(*Ptr_implementation);
|
|
}
|
|
|
|
// -> operator
|
|
const Point_with_transformed_distance*
|
|
operator-> () const
|
|
{
|
|
return &*(*Ptr_implementation);
|
|
}
|
|
|
|
// prefix operator
|
|
iterator&
|
|
operator++()
|
|
{
|
|
++(*Ptr_implementation);
|
|
return *this;
|
|
}
|
|
|
|
// postfix operator
|
|
Object_wrapper<Point_with_transformed_distance>
|
|
operator++(int)
|
|
{
|
|
return (*Ptr_implementation)++;
|
|
}
|
|
|
|
|
|
bool
|
|
operator==(const iterator& It) const
|
|
{
|
|
if (
|
|
((Ptr_implementation == 0) ||
|
|
Ptr_implementation->Item_PriorityQueue.empty()) &&
|
|
((It.Ptr_implementation == 0) ||
|
|
It.Ptr_implementation->Item_PriorityQueue.empty())
|
|
)
|
|
return true;
|
|
// else
|
|
return (Ptr_implementation == It.Ptr_implementation);
|
|
}
|
|
|
|
bool
|
|
operator!=(const iterator& It) const
|
|
{
|
|
return !(*this == It);
|
|
}
|
|
|
|
std::ostream&
|
|
statistics (std::ostream& s)
|
|
{
|
|
Ptr_implementation->statistics(s);
|
|
return s;
|
|
}
|
|
|
|
~iterator()
|
|
{
|
|
if (Ptr_implementation != 0) {
|
|
Ptr_implementation->reference_count--;
|
|
if (Ptr_implementation->reference_count==0) {
|
|
delete Ptr_implementation;
|
|
Ptr_implementation = 0;
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
}; // class iterator
|
|
|
|
//data members
|
|
const Tree& m_tree;
|
|
Query_item m_query;
|
|
Distance m_dist;
|
|
FT m_Eps;
|
|
bool m_search_nearest;
|
|
}; // class
|
|
|
|
template <class Traits, class Query_item, class Distance>
|
|
void swap (typename Orthogonal_incremental_neighbor_search<Traits,
|
|
Query_item, Distance>::iterator& x,
|
|
typename Orthogonal_incremental_neighbor_search<Traits,
|
|
Query_item, Distance>::iterator& y)
|
|
{
|
|
typename Orthogonal_incremental_neighbor_search<Traits,
|
|
Query_item, Distance>::iterator::Iterator_implementation
|
|
*tmp = x.Ptr_implementation;
|
|
x.Ptr_implementation = y.Ptr_implementation;
|
|
y.Ptr_implementation = tmp;
|
|
}
|
|
|
|
} // namespace CGAL
|
|
|
|
#include <CGAL/enable_warnings.h>
|
|
|
|
#endif // CGAL_ORTHOGONAL_INCREMENTAL_NEIGHBOR_SEARCH_H
|