mirror of https://github.com/CGAL/cgal
559 lines
17 KiB
C++
559 lines
17 KiB
C++
// Copyright (c) 2007-2008 INRIA (France).
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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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// You can redistribute it and/or modify it under the terms of the GNU
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// General Public License as published by the Free Software Foundation,
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// either version 3 of the License, or (at your option) any later version.
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//
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// Licensees holding a valid commercial license may use this file in
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// accordance with the commercial license agreement provided with the software.
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//
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// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
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// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
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//
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// $URL$
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// $Id$
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// SPDX-License-Identifier: GPL-3.0+
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//
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//
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// Author(s) : Tong Zhao, Cédric Portaneri
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#ifndef CGAL_OCTREE_3_H
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#define CGAL_OCTREE_3_H
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#include <CGAL/Octree/Node.h>
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#include <CGAL/Octree/Split_criterion.h>
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#include <CGAL/Octree/Walker_criterion.h>
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#include <CGAL/Octree/Walker_iterator.h>
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#include <CGAL/bounding_box.h>
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#include <CGAL/Aff_transformation_3.h>
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#include <CGAL/aff_transformation_tags.h>
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#include <CGAL/Orthogonal_k_neighbor_search.h>
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#include <CGAL/Search_traits_3.h>
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#include <CGAL/Search_traits_adapter.h>
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#include <CGAL/intersections.h>
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#include <boost/function.hpp>
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#include <boost/iterator/iterator_facade.hpp>
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#include <boost/range/iterator_range.hpp>
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#include <iostream>
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#include <fstream>
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#include <ostream>
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#include <functional>
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#include <stack>
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#include <queue>
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#include <vector>
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#include <math.h>
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#include <CGAL/squared_distance_3.h>
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namespace CGAL {
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namespace Octree {
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/*!
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* \ingroup PkgOctreeClasses
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*
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* \brief Class Octree is a data structure for efficient computations in 3D space.
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*
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* \details It builds a heirarchy of nodes which subdivide the space based on a collection of points.
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* Each node represents an axis aligned cubic region of space.
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* A node contains the range of points that are present in the region it defines,
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* and it may contain eight other nodes which further subdivide the region.
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*
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* \tparam PointRange is a range type that provides random access iterators over the indices of a set of points.
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* \tparam PointMap is a type that maps items in the PointRange to Point data
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*/
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template<class PointRange, class PointMap>
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class Octree {
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public:
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/// \name Public Types
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/// @{
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/*!
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* \brief The point type is deduced from the type of the property map used
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*/
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typedef typename boost::property_traits<PointMap>::value_type Point;
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/*!
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* \brief The Kernel used is deduced from the point type
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*/
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typedef typename CGAL::Kernel_traits<Point>::Kernel Kernel;
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/*!
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* \brief The floating point type is decided by the Kernel
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*/
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typedef typename Kernel::FT FT;
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/*!
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* \brief
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*/
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typedef boost::iterator_range<typename PointRange::iterator> Points_iterator_range;
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/*!
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* \brief The Sub-tree / Octant type
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*/
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typedef Node::Node<Points_iterator_range> Node;
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/*!
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* \brief A function that determines whether a node needs to be split when refining a tree
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*/
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typedef std::function<bool(const Node &)> Split_criterion;
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/*!
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* \brief A range that provides input-iterator access to the nodes of a tree
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*/
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typedef boost::iterator_range<Walker_iterator<const Node>> Node_range;
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/*!
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* \brief A function that determines the next node in a traversal given the current one
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*/
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typedef std::function<const Node *(const Node *)> Node_walker;
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/// @}
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private: // Private types
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typedef typename Kernel::Vector_3 Vector;
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typedef typename Kernel::Iso_cuboid_3 Iso_cuboid;
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typedef typename Kernel::Sphere_3 Sphere;
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typedef typename CGAL::Bbox_3 Bbox;
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typedef typename PointRange::iterator Range_iterator;
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typedef typename std::iterator_traits<Range_iterator>::value_type Range_type;
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private: // data members :
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Node m_root; /* root node of the octree */
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uint8_t m_max_depth_reached = 0; /* octree actual highest depth reached */
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PointRange &m_ranges; /* input point range */
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PointMap m_points_map; /* property map: `value_type of InputIterator` -> `Point` (Position) */
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Point m_bbox_min; /* input bounding box min value */
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FT m_bbox_side; /* input bounding box side length (cube) */
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std::vector<FT> m_side_per_depth; /* side length per node's depth */
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std::vector<size_t> m_unit_per_depth; /* number of unit node (smallest) inside one node for each depth for one axis */
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public:
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/// \name Construction, Destruction
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/// @{
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/*!
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* \brief Create an octree from a collection of points
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*
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* The resulting octree will have a root node with no children that contains the points passed.
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* That root node will have a bounding box that encloses all of the points passed,
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* with padding according to the enlarge_ratio
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*
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* \param point_range random access iterator over the indices of the points
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* \param point_map maps the point indices to their coordinate locations
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* \param enlarge_ratio the degree to which the bounding box should be enlarged
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*/
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Octree(
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PointRange &point_range,
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PointMap &point_map,
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const FT enlarge_ratio = 1.2) :
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m_ranges(point_range),
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m_points_map(point_map) {
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// compute bounding box that encloses all points
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Iso_cuboid bbox = CGAL::bounding_box(boost::make_transform_iterator
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(m_ranges.begin(),
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CGAL::Property_map_to_unary_function<PointMap>(
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m_points_map)),
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boost::make_transform_iterator
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(m_ranges.end(),
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CGAL::Property_map_to_unary_function<PointMap>(
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m_points_map)));
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// Find the center point of the box
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Point bbox_centroid = midpoint(bbox.min(), bbox.max());
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// scale bounding box to add padding
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bbox = bbox.transform(Aff_transformation_3<Kernel>(SCALING, enlarge_ratio));
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// Convert the bounding box into a cube
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FT x_len = bbox.xmax() - bbox.xmin();
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FT y_len = bbox.ymax() - bbox.ymin();
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FT z_len = bbox.zmax() - bbox.zmin();
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FT max_len = std::max({x_len, y_len, z_len});
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bbox = Iso_cuboid(bbox.min(), bbox.min() + max_len * Vector(1.0, 1.0, 1.0));
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// Shift the squared box to make sure it's centered in the original place
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Point bbox_transformed_centroid = midpoint(bbox.min(), bbox.max());
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Vector diff_centroid = bbox_centroid - bbox_transformed_centroid;
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bbox = bbox.transform(Aff_transformation_3<Kernel>(TRANSLATION, diff_centroid));
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// save octree attributes
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m_bbox_min = bbox.min();
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m_bbox_side = bbox.max()[0] - m_bbox_min[0];
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m_root.value() = {point_range.begin(), point_range.end()};
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}
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/// @}
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/// \name Tree Building
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/// @{
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/*!
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* \brief Subdivide an octree's nodes and sub-nodes until it meets the given criteria
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*
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* \todo
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*
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* \param split_criterion rule to use when determining whether or not a node needs to be subdivided
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*/
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void refine(const Split_criterion &split_criterion) {
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// create a side length map
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for (int i = 0; i <= (int) 32; i++)
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m_side_per_depth.push_back(m_bbox_side / (FT) (1 << i));
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// Initialize a queue of nodes that need to be refined
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std::queue<Node *> todo;
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todo.push(&m_root);
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// Process items in the queue until it's consumed fully
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while (!todo.empty()) {
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// Get the next element
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auto current = todo.front();
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todo.pop();
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int depth = current->depth();
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// Check if this node needs to be processed
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if (split_criterion(*current)) {
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// Split this node
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current->split();
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// Redistribute its points
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reassign_points((*current));
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// Process each of its children
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for (int i = 0; i < 8; ++i)
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todo.push(&(*current)[i]);
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}
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}
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}
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/*!
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* \brief Refine an octree using a max depth and max number of points in a node as split criterion
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*
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* \todo
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*
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* \param max_depth deepest a tree is allowed to be (nodes at this depth will not be split)
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* \param bucket_size maximum points a node is allowed to contain
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*/
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void refine(size_t max_depth, size_t bucket_size) {
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refine(Split_to_max_depth_or_bucket_size(max_depth, bucket_size));
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}
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/// @}
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/// \name Accessors
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/// @{
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/*!
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* \brief Provides read and write access to the root node, and by extension the rest of the tree
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*
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* \todo
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*
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* \return a reference to the root node of the tree
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*/
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Node &root() { return m_root; }
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/*!
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* \brief Provides read-only access to the root node, and by extension the rest of the tree
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*
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* \todo
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*
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* \return a const reference to the root node of the tree
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*/
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const Node &root() const { return m_root; }
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/*!
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* \brief Constructs an input range of nodes using a tree walker function
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*
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* \todo
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*
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* \tparam Walker type of the walker rule
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* \param walker the rule to use when determining the order of the sequence of points produced
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* \return a forward input iterator over the nodes of the tree
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*/
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template<class Walker>
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Node_range walk(const Walker &walker = Walker()) const {
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const Node *first = walker.first(&m_root);
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Node_walker next = std::bind(&Walker::template next<Points_iterator_range>,
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walker, std::placeholders::_1);
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return boost::make_iterator_range(Walker_iterator<const Node>(first, next),
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Walker_iterator<const Node>());
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}
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/*!
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* \brief Find the leaf node which would contain a point
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*
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* Traverses the octree and finds the deepest cell that has a domain enclosing the point passed.
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*
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* \param p The point to find a node for
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* \return A reference to the node which would contain the point
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*/
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const Node &locate(const Point &p) const {
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// Start at the root node
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auto *node_for_point = &m_root;
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// Descend the tree until reaching a leaf node
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while (!node_for_point->is_leaf()) {
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// Find the point to split around
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Point center = compute_barycenter_position(*node_for_point);
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// Find the index of the correct sub-node
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typename Node::Index index;
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for (int dimension = 0; dimension < 3; ++dimension) {
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index[dimension] = center[dimension] < p[dimension];
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}
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// Find the correct sub-node of the current node
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node_for_point = &(*node_for_point)[index.to_ulong()];
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}
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// Return the result
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return *node_for_point;
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}
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/*!
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* \brief Find the bounding box of a node
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*
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* \todo
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*
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* \param node the node to determine the bounding box of
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* \return the bounding box defined by that node's relationship to the tree
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*/
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Bbox bbox(const Node &node) const {
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// Determine the side length of this node
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FT size = m_side_per_depth[node.depth()];
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// Determine the location this node should be split
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FT min_corner[3];
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FT max_corner[3];
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for (int i = 0; i < 3; i++) {
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min_corner[i] = m_bbox_min[i] + (node.location()[i] * size);
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max_corner[i] = min_corner[i] + size;
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}
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// Create the cube
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return {min_corner[0], min_corner[1], min_corner[2],
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max_corner[0], max_corner[1], max_corner[2]};
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}
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/*!
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* \brief Find the K points in a tree that are nearest to the search point
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*
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* \todo
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*
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* \tparam Point_output_iterator an output iterator type that will accept points
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* \param search_point the location to find points near
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* \param k the number of points to find
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* \param output the output iterator to add the found points to
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*/
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template<typename Point_output_iterator>
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void nearest_k_neighbours(const Point &search_point, std::size_t k, Point_output_iterator output) const {
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// Create an empty list of points
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std::vector<std::pair<Point, FT>> points_list;
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points_list.reserve(k);
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// Invoking the recursive function adds those points to the vector (passed by reference)
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nearest_k_neighbours_recursive(search_point, points_list, m_root, std::numeric_limits<FT>::max());
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// Add all the points found to the output
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for (auto &item : points_list)
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*output++ = item.first;
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}
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/// @}
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/// \name Operators
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/// @{
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/*!
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* \brief Compares the topology of a pair of Octrees
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*
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* \todo
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*
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* \param rhs tree to compare with
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* \return whether the trees have the same topology
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*/
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bool operator==(Octree<PointRange, PointMap> &rhs) {
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// Identical trees should have the same bounding box
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if (rhs.m_bbox_min != m_bbox_min || rhs.m_bbox_side != m_bbox_side)
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return false;
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// Identical trees should have the same depth
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if (rhs.m_max_depth_reached != m_max_depth_reached)
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return false;
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// If all else is equal, recursively compare the trees themselves
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return rhs.m_root == m_root;
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}
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/// @}
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private: // functions :
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Point compute_barycenter_position(const Node &node) const {
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// Determine the side length of this node
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FT size = m_side_per_depth[node.depth()];
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// Determine the location this node should be split
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FT bary[3];
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for (int i = 0; i < 3; i++)
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bary[i] = node.location()[i] * size + (size / 2.0) + m_bbox_min[i];
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// Convert that location into a point
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return {bary[0], bary[1], bary[2]};
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}
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void reassign_points(Node &node, Range_iterator begin, Range_iterator end, const Point ¢er,
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std::bitset<3> coord = {},
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std::size_t dimension = 0) {
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// Root case: reached the last dimension
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if (dimension == 3) {
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node[coord.to_ulong()].value() = {begin, end};
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return;
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}
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// Split the point collection around the center point on this dimension
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Range_iterator split_point = std::partition(begin, end,
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[&](const Range_type &a) -> bool {
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return (get(m_points_map, a)[dimension] < center[dimension]);
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});
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// Further subdivide the first side of the split
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std::bitset<3> coord_left = coord;
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coord_left[dimension] = false;
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reassign_points(node, begin, split_point, center, coord_left, dimension + 1);
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// Further subdivide the second side of the split
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std::bitset<3> coord_right = coord;
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coord_right[dimension] = true;
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reassign_points(node, split_point, end, center, coord_right, dimension + 1);
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}
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void reassign_points(Node &node) {
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Point center = compute_barycenter_position(node);
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reassign_points(node, node.value().begin(), node.value().end(), center);
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}
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bool do_intersect(const Node &node, const Sphere &sphere) const {
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// Create a cubic bounding box from the node
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Bbox node_cube = bbox(node);
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// Check for overlap between the node's box and the sphere as a box, to quickly catch some cases
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// FIXME: Activating this causes slower times!
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// if (!do_overlap(node_cube, sphere.bbox()))
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// return false;
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// Check for intersection between the node and the sphere
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return CGAL::do_intersect(node_cube, sphere);
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}
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FT nearest_k_neighbours_recursive(const Point &p, std::vector<std::pair<Point, FT>> &out, const Node &node,
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FT search_bounds_radius_squared) const {
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FT largest_radius_squared_found = search_bounds_radius_squared;
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// Check whether we've reached the bottom of the tree
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if (node.is_leaf()) {
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// Base case: the node has no children
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// Check if the node contains any points
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if (0 < std::distance(node.value().begin(), node.value().end())) {
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// If it does, loop through each point
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for (auto i : node.value()) {
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auto point = get(m_points_map, i);
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// Find the distance of the point
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FT new_distance_squared = CGAL::squared_distance(point, p);
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// Check whether the new distance is an improvement
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if (new_distance_squared < largest_radius_squared_found) {
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// Make room for the new point if necessary
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if (out.size() == out.capacity())
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// The list is already sorted, so the last item is the furthest
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out.pop_back();
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// Add the point to the list
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out.push_back({point, new_distance_squared});
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// Sort the list
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std::sort(out.begin(), out.end(), [=](auto &left, auto &right) {
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return left.second < right.second;
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});
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// Update the distance
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largest_radius_squared_found = out.back().second;
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}
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}
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}
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} else {
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// If the node has children
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// Search each of them
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for (int index = 0; index < 8; ++index) {
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auto &n = node[index];
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// Check whether this node is capable of containing closer points
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if (do_intersect(n, Sphere{p, largest_radius_squared_found + 0.1 /*TODO: This is my epsilon*/})) {
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// Recursive case
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largest_radius_squared_found =
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nearest_k_neighbours_recursive(p, out, n, largest_radius_squared_found);
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}
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}
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}
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//out.push_back(p);
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return largest_radius_squared_found;
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}
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}; // end class Octree
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} // namespace Octree
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} // namespace CGAL
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#endif // CGAL_OCTREE_3_H
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