/usr/include/CGAL/Kd_tree.h is in libcgal-dev 4.11-2build1.
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// All rights reserved.
//
// This file is part of CGAL (www.cgal.org).
// You can redistribute it and/or modify it under the terms of the GNU
// General Public License as published by the Free Software Foundation,
// either version 3 of the License, or (at your option) any later version.
//
// 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.
//
// $URL$
// $Id$
//
// Author(s) : Hans Tangelder (<hanst@cs.uu.nl>),
// : Waqar Khan <wkhan@mpi-inf.mpg.de>
#ifndef CGAL_KD_TREE_H
#define CGAL_KD_TREE_H
#include <CGAL/license/Spatial_searching.h>
#include <CGAL/basic.h>
#include <CGAL/assertions.h>
#include <vector>
#include <CGAL/algorithm.h>
#include <CGAL/Kd_tree_node.h>
#include <CGAL/Splitters.h>
#include <CGAL/internal/Get_dimension_tag.h>
#include <deque>
#include <boost/container/deque.hpp>
#include <boost/optional.hpp>
#ifdef CGAL_HAS_THREADS
#include <CGAL/mutex.h>
#endif
namespace CGAL {
//template <class SearchTraits, class Splitter_=Median_of_rectangle<SearchTraits>, class UseExtendedNode = Tag_true >
template <class SearchTraits, class Splitter_=Sliding_midpoint<SearchTraits>, class UseExtendedNode = Tag_true >
class Kd_tree {
public:
typedef SearchTraits Traits;
typedef Splitter_ Splitter;
typedef typename SearchTraits::Point_d Point_d;
typedef typename Splitter::Container Point_container;
typedef typename SearchTraits::FT FT;
typedef Kd_tree_node<SearchTraits, Splitter, UseExtendedNode > Node;
typedef Kd_tree_leaf_node<SearchTraits, Splitter, UseExtendedNode > Leaf_node;
typedef Kd_tree_internal_node<SearchTraits, Splitter, UseExtendedNode > Internal_node;
typedef Kd_tree<SearchTraits, Splitter> Tree;
typedef Kd_tree<SearchTraits, Splitter,UseExtendedNode> Self;
typedef Node* Node_handle;
typedef const Node* Node_const_handle;
typedef Leaf_node* Leaf_node_handle;
typedef const Leaf_node* Leaf_node_const_handle;
typedef Internal_node* Internal_node_handle;
typedef const Internal_node* Internal_node_const_handle;
typedef typename std::vector<const Point_d*>::const_iterator Point_d_iterator;
typedef typename std::vector<const Point_d*>::const_iterator Point_d_const_iterator;
typedef typename Splitter::Separator Separator;
typedef typename std::vector<Point_d>::const_iterator iterator;
typedef typename std::vector<Point_d>::const_iterator const_iterator;
typedef typename std::vector<Point_d>::size_type size_type;
typedef typename internal::Get_dimension_tag<SearchTraits>::Dimension D;
private:
SearchTraits traits_;
Splitter split;
// wokaround for https://svn.boost.org/trac/boost/ticket/9332
#if (_MSC_VER == 1800) && (BOOST_VERSION == 105500)
std::deque<Internal_node> internal_nodes;
std::deque<Leaf_node> leaf_nodes;
#else
boost::container::deque<Internal_node> internal_nodes;
boost::container::deque<Leaf_node> leaf_nodes;
#endif
Node_handle tree_root;
Kd_tree_rectangle<FT,D>* bbox;
std::vector<Point_d> pts;
// Instead of storing the points in arrays in the Kd_tree_node
// we put all the data in a vector in the Kd_tree.
// and we only store an iterator range in the Kd_tree_node.
//
std::vector<const Point_d*> data;
#ifdef CGAL_HAS_THREADS
mutable CGAL_MUTEX building_mutex;//mutex used to protect const calls inducing build()
#endif
bool built_;
bool removed_;
// protected copy constructor
Kd_tree(const Tree& tree)
: traits_(tree.traits_),built_(tree.built_)
{};
// Instead of the recursive construction of the tree in the class Kd_tree_node
// we do this in the tree class. The advantage is that we then can optimize
// the allocation of the nodes.
// The leaf node
Node_handle
create_leaf_node(Point_container& c)
{
Leaf_node node(true , static_cast<unsigned int>(c.size()));
std::ptrdiff_t tmp = c.begin() - data.begin();
node.data = pts.begin() + tmp;
leaf_nodes.push_back(node);
Leaf_node_handle nh = &leaf_nodes.back();
return nh;
}
// The internal node
Node_handle
create_internal_node(Point_container& c, const Tag_true&)
{
return create_internal_node_use_extension(c);
}
Node_handle
create_internal_node(Point_container& c, const Tag_false&)
{
return create_internal_node(c);
}
// TODO: Similiar to the leaf_init function above, a part of the code should be
// moved to a the class Kd_tree_node.
// It is not proper yet, but the goal was to see if there is
// a potential performance gain through the Compact_container
Node_handle
create_internal_node_use_extension(Point_container& c)
{
Internal_node node(false);
internal_nodes.push_back(node);
Internal_node_handle nh = &internal_nodes.back();
Separator sep;
Point_container c_low(c.dimension(),traits_);
split(sep, c, c_low);
nh->set_separator(sep);
int cd = nh->cutting_dimension();
if(!c_low.empty()){
nh->lower_low_val = c_low.tight_bounding_box().min_coord(cd);
nh->lower_high_val = c_low.tight_bounding_box().max_coord(cd);
}
else{
nh->lower_low_val = nh->cutting_value();
nh->lower_high_val = nh->cutting_value();
}
if(!c.empty()){
nh->upper_low_val = c.tight_bounding_box().min_coord(cd);
nh->upper_high_val = c.tight_bounding_box().max_coord(cd);
}
else{
nh->upper_low_val = nh->cutting_value();
nh->upper_high_val = nh->cutting_value();
}
CGAL_assertion(nh->cutting_value() >= nh->lower_low_val);
CGAL_assertion(nh->cutting_value() <= nh->upper_high_val);
if (c_low.size() > split.bucket_size()){
nh->lower_ch = create_internal_node_use_extension(c_low);
}else{
nh->lower_ch = create_leaf_node(c_low);
}
if (c.size() > split.bucket_size()){
nh->upper_ch = create_internal_node_use_extension(c);
}else{
nh->upper_ch = create_leaf_node(c);
}
return nh;
}
// Note also that I duplicated the code to get rid if the if's for
// the boolean use_extension which was constant over the construction
Node_handle
create_internal_node(Point_container& c)
{
Internal_node node(false);
internal_nodes.push_back(node);
Internal_node_handle nh = &internal_nodes.back();
Separator sep;
Point_container c_low(c.dimension(),traits_);
split(sep, c, c_low);
nh->set_separator(sep);
if (c_low.size() > split.bucket_size()){
nh->lower_ch = create_internal_node(c_low);
}else{
nh->lower_ch = create_leaf_node(c_low);
}
if (c.size() > split.bucket_size()){
nh->upper_ch = create_internal_node(c);
}else{
nh->upper_ch = create_leaf_node(c);
}
return nh;
}
public:
Kd_tree(Splitter s = Splitter(),const SearchTraits traits=SearchTraits())
: traits_(traits),split(s), built_(false), removed_(false)
{}
template <class InputIterator>
Kd_tree(InputIterator first, InputIterator beyond,
Splitter s = Splitter(),const SearchTraits traits=SearchTraits())
: traits_(traits),split(s), built_(false), removed_(false)
{
pts.insert(pts.end(), first, beyond);
}
bool empty() const {
return pts.empty();
}
void
build()
{
// This function is not ready to be called when a tree already exists, one
// must call invalidate_build() first.
CGAL_assertion(!is_built());
CGAL_assertion(!pts.empty());
CGAL_assertion(!removed_);
const Point_d& p = *pts.begin();
typename SearchTraits::Construct_cartesian_const_iterator_d ccci=traits_.construct_cartesian_const_iterator_d_object();
int dim = static_cast<int>(std::distance(ccci(p), ccci(p,0)));
data.reserve(pts.size());
for(unsigned int i = 0; i < pts.size(); i++){
data.push_back(&pts[i]);
}
Point_container c(dim, data.begin(), data.end(),traits_);
bbox = new Kd_tree_rectangle<FT,D>(c.bounding_box());
if (c.size() <= split.bucket_size()){
tree_root = create_leaf_node(c);
}else {
tree_root = create_internal_node(c, UseExtendedNode());
}
//Reorder vector for spatial locality
std::vector<Point_d> ptstmp;
ptstmp.resize(pts.size());
for (std::size_t i = 0; i < pts.size(); ++i){
ptstmp[i] = *data[i];
}
for(std::size_t i = 0; i < leaf_nodes.size(); ++i){
std::ptrdiff_t tmp = leaf_nodes[i].begin() - pts.begin();
leaf_nodes[i].data = ptstmp.begin() + tmp;
}
pts.swap(ptstmp);
data.clear();
built_ = true;
}
private:
//any call to this function is for the moment not threadsafe
void const_build() const {
#ifdef CGAL_HAS_THREADS
//this ensure that build() will be called once
CGAL_SCOPED_LOCK(building_mutex);
if(!is_built())
#endif
const_cast<Self*>(this)->build(); //THIS IS NOT THREADSAFE
}
public:
bool is_built() const
{
return built_;
}
void invalidate_build()
{
if(removed_){
// Walk the tree to collect the remaining points.
// Writing directly to pts would likely work, but better be safe.
std::vector<Point_d> ptstmp;
//ptstmp.resize(root()->num_items());
root()->tree_items(std::back_inserter(ptstmp));
pts.swap(ptstmp);
removed_=false;
CGAL_assertion(is_built()); // the rest of the cleanup must happen
}
if(is_built()){
internal_nodes.clear();
leaf_nodes.clear();
data.clear();
delete bbox;
built_ = false;
}
}
void clear()
{
invalidate_build();
pts.clear();
removed_ = false;
}
void
insert(const Point_d& p)
{
invalidate_build();
pts.push_back(p);
}
template <class InputIterator>
void
insert(InputIterator first, InputIterator beyond)
{
invalidate_build();
pts.insert(pts.end(),first, beyond);
}
private:
struct Equal_by_coordinates {
SearchTraits const* traits;
Point_d const* pp;
bool operator()(Point_d const&q) const {
typename SearchTraits::Construct_cartesian_const_iterator_d ccci=traits->construct_cartesian_const_iterator_d_object();
return std::equal(ccci(*pp), ccci(*pp,0), ccci(q));
}
};
Equal_by_coordinates equal_by_coordinates(Point_d const&p){
Equal_by_coordinates ret = { &traits(), &p };
return ret;
}
public:
void
remove(const Point_d& p)
{
remove(p, equal_by_coordinates(p));
}
template<class Equal>
void
remove(const Point_d& p, Equal const& equal_to_p)
{
#if 0
// This code could have quadratic runtime.
if (!is_built()) {
std::vector<Point_d>::iterator pi = std::find_if(pts.begin(), pts.end(), equal_to_p);
// Precondition: the point must be there.
CGAL_assertion (pi != pts.end());
pts.erase(pi);
return;
}
#endif
bool success = remove_(p, 0, false, 0, false, root(), equal_to_p);
CGAL_assertion(success);
// Do not set the flag is the tree has been cleared.
if(is_built())
removed_ |= success;
}
private:
template<class Equal>
bool remove_(const Point_d& p,
Internal_node_handle grandparent, bool parent_islower,
Internal_node_handle parent, bool islower,
Node_handle node, Equal const& equal_to_p) {
// Recurse to locate the point
if (!node->is_leaf()) {
Internal_node_handle newparent = static_cast<Internal_node_handle>(node);
// FIXME: This should be if(x<y) remove low; else remove up;
if (traits().construct_cartesian_const_iterator_d_object()(p)[newparent->cutting_dimension()] <= newparent->cutting_value()) {
if (remove_(p, parent, islower, newparent, true, newparent->lower(), equal_to_p))
return true;
}
//if (traits().construct_cartesian_const_iterator_d_object()(p)[newparent->cutting_dimension()] >= newparent->cutting_value())
return remove_(p, parent, islower, newparent, false, newparent->upper(), equal_to_p);
CGAL_assertion(false); // Point was not found
}
// Actual removal
Leaf_node_handle lnode = static_cast<Leaf_node_handle>(node);
if (lnode->size() > 1) {
iterator pi = std::find_if(lnode->begin(), lnode->end(), equal_to_p);
// FIXME: we should ensure this never happens
if (pi == lnode->end()) return false;
iterator lasti = lnode->end() - 1;
if (pi != lasti) {
// Hack to get a non-const iterator
std::iter_swap(pts.begin()+(pi-pts.begin()), pts.begin()+(lasti-pts.begin()));
}
lnode->drop_last_point();
} else if (!equal_to_p(*lnode->begin())) {
// FIXME: we should ensure this never happens
return false;
} else if (grandparent) {
Node_handle brother = islower ? parent->upper() : parent->lower();
if (parent_islower)
grandparent->set_lower(brother);
else
grandparent->set_upper(brother);
} else if (parent) {
tree_root = islower ? parent->upper() : parent->lower();
} else {
clear();
}
return true;
}
public:
//For efficiency; reserve the size of the points vectors in advance (if the number of points is already known).
void reserve(size_t size)
{
pts.reserve(size);
}
//Get the capacity of the underlying points vector.
size_t capacity()
{
return pts.capacity();
}
template <class OutputIterator, class FuzzyQueryItem>
OutputIterator
search(OutputIterator it, const FuzzyQueryItem& q) const
{
if(! pts.empty()){
if(! is_built()){
const_build();
}
Kd_tree_rectangle<FT,D> b(*bbox);
return tree_root->search(it,q,b);
}
return it;
}
template <class FuzzyQueryItem>
boost::optional<Point_d>
search_any_point(const FuzzyQueryItem& q) const
{
if(! pts.empty()){
if(! is_built()){
const_build();
}
Kd_tree_rectangle<FT,D> b(*bbox);
return tree_root->search_any_point(q,b);
}
return boost::none;
}
~Kd_tree() {
if(is_built()){
delete bbox;
}
}
const SearchTraits&
traits() const
{
return traits_;
}
Node_const_handle
root() const
{
if(! is_built()){
const_build();
}
return tree_root;
}
Node_handle
root()
{
if(! is_built()){
build();
}
return tree_root;
}
void
print() const
{
if(! pts.empty()){
if(! is_built()){
const_build();
}
root()->print();
}else{
std::cout << "empty tree\n";
}
}
const Kd_tree_rectangle<FT,D>&
bounding_box() const
{
if(! is_built()){
const_build();
}
return *bbox;
}
const_iterator
begin() const
{
return pts.begin();
}
const_iterator
end() const
{
return pts.end();
}
size_type
size() const
{
return pts.size();
}
// Print statistics of the tree.
std::ostream&
statistics(std::ostream& s) const
{
if(! is_built()){
const_build();
}
s << "Tree statistics:" << std::endl;
s << "Number of items stored: "
<< root()->num_items() << std::endl;
s << "Number of nodes: "
<< root()->num_nodes() << std::endl;
s << " Tree depth: " << root()->depth() << std::endl;
return s;
}
};
} // namespace CGAL
#endif // CGAL_KD_TREE_H
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