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/** \file
* Defines the interface for the KDTree class.
*
* \author Martin F. Krafft <libkdtree@pobox.madduck.net>
*
* Paul Harris figured this stuff out (below)
* Notes:
* This is similar to a binary tree, but its not the same.
* There are a few important differences:
*
* * Each level is sorted by a different criteria (this is fundamental to the design).
*
* * It is possible to have children IDENTICAL to its parent in BOTH branches
* This is different to a binary tree, where identical children are always to the right
* So, KDTree has the relationships:
* * The left branch is <= its parent (in binary tree, this relationship is a plain < )
* * The right branch is <= its parent (same as binary tree)
*
* This is done for mostly for performance.
* Its a LOT easier to maintain a consistent tree if we use the <= relationship.
* Note that this relationship only makes a difference when searching for an exact
* item with find() or find_exact, other search, erase and insert functions don't notice
* the difference.
*
* In the case of binary trees, you can safely assume that the next identical item
* will be the child leaf,
* but in the case of KDTree, the next identical item might
* be a long way down a subtree, because of the various different sort criteria.
*
* So erase()ing a node from a KDTree could require serious and complicated
* tree rebalancing to maintain consistency... IF we required binary-tree-like relationships.
*
* This has no effect on insert()s, a < test is good enough to keep consistency.
*
* It has an effect on find() searches:
* * Instead of using compare(child,node) for a < relationship and following 1 branch,
* we must use !compare(node,child) for a <= relationship, and test BOTH branches, as
* we could potentially go down both branches.
*
* It has no real effect on bounds-based searches (like find_nearest, find_within_range)
* as it compares vs a boundary and would follow both branches if required.
*
* This has no real effect on erase()s, a < test is good enough to keep consistency.
*/
#ifndef INCLUDE_KDTREE_KDTREE_HPP
#define INCLUDE_KDTREE_KDTREE_HPP
//
// This number is guarenteed to change with every release.
//
// KDTREE_VERSION % 100 is the patch level
// KDTREE_VERSION / 100 % 1000 is the minor version
// KDTREE_VERSION / 100000 is the major version
#define KDTREE_VERSION 703
//
// KDTREE_LIB_VERSION must be defined to be the same as KDTREE_VERSION
// but as a *string* in the form "x_y[_z]" where x is the major version
// number, y is the minor version number, and z is the patch level if not 0.
#define KDTREE_LIB_VERSION "0_7_3"
#include <vector>
#ifdef KDTREE_CHECK_PERFORMANCE_COUNTERS
# include <map>
#endif
#include <algorithm>
#include <functional>
#ifdef KDTREE_DEFINE_OSTREAM_OPERATORS
# include <ostream>
# include <stack>
#endif
#include <cmath>
#include <cstddef>
#include <cassert>
#include "function.hpp"
#include "allocator.hpp"
#include "iterator.hpp"
#include "node.hpp"
#include "region.hpp"
namespace KDTree
{
#ifdef KDTREE_CHECK_PERFORMANCE
unsigned long long num_dist_calcs = 0;
#endif
template <size_t const __K, typename _Val,
typename _Acc = _Bracket_accessor<_Val>,
typename _Dist = squared_difference<typename _Acc::result_type,
typename _Acc::result_type>,
typename _Cmp = std::less<typename _Acc::result_type>,
typename _Alloc = std::allocator<_Node<_Val> > >
class KDTree : protected _Alloc_base<_Val, _Alloc>
{
protected:
typedef _Alloc_base<_Val, _Alloc> _Base;
typedef typename _Base::allocator_type allocator_type;
typedef _Node_base* _Base_ptr;
typedef _Node_base const* _Base_const_ptr;
typedef _Node<_Val>* _Link_type;
typedef _Node<_Val> const* _Link_const_type;
typedef _Node_compare<_Val, _Acc, _Cmp> _Node_compare_;
public:
typedef _Region<__K, _Val, typename _Acc::result_type, _Acc, _Cmp>
_Region_;
typedef _Val value_type;
typedef value_type* pointer;
typedef value_type const* const_pointer;
typedef value_type& reference;
typedef value_type const& const_reference;
typedef typename _Acc::result_type subvalue_type;
typedef typename _Dist::distance_type distance_type;
typedef size_t size_type;
typedef ptrdiff_t difference_type;
KDTree(_Acc const& __acc = _Acc(), _Dist const& __dist = _Dist(),
_Cmp const& __cmp = _Cmp(), const allocator_type& __a = allocator_type())
: _Base(__a), _M_header(),
_M_count(0), _M_acc(__acc), _M_cmp(__cmp), _M_dist(__dist)
{
_M_empty_initialise();
}
KDTree(const KDTree& __x)
: _Base(__x.get_allocator()), _M_header(), _M_count(0),
_M_acc(__x._M_acc), _M_cmp(__x._M_cmp), _M_dist(__x._M_dist)
{
_M_empty_initialise();
// this is slow:
// this->insert(begin(), __x.begin(), __x.end());
// this->optimise();
// this is much faster, as it skips a lot of useless work
// do the optimisation before inserting
// Needs to be stored in a vector first as _M_optimise()
// sorts the data in the passed iterators directly.
std::vector<value_type> temp;
temp.reserve(__x.size());
std::copy(__x.begin(),__x.end(),std::back_inserter(temp));
_M_optimise(temp.begin(), temp.end(), 0);
}
template<typename _InputIterator>
KDTree(_InputIterator __first, _InputIterator __last,
_Acc const& acc = _Acc(), _Dist const& __dist = _Dist(),
_Cmp const& __cmp = _Cmp(), const allocator_type& __a = allocator_type())
: _Base(__a), _M_header(), _M_count(0),
_M_acc(acc), _M_cmp(__cmp), _M_dist(__dist)
{
_M_empty_initialise();
// this is slow:
// this->insert(begin(), __first, __last);
// this->optimise();
// this is much faster, as it skips a lot of useless work
// do the optimisation before inserting
// Needs to be stored in a vector first as _M_optimise()
// sorts the data in the passed iterators directly.
std::vector<value_type> temp;
temp.reserve(std::distance(__first,__last));
std::copy(__first,__last,std::back_inserter(temp));
_M_optimise(temp.begin(), temp.end(), 0);
// NOTE: this will BREAK users that are passing in
// read-once data via the iterator...
// We increment __first all the way to __last once within
// the distance() call, and again within the copy() call.
//
// This should end up using some funky C++ concepts or
// type traits to check that the iterators can be used in this way...
}
// this will CLEAR the tree and fill it with the contents
// of 'writable_vector'. it will use the passed vector directly,
// and will basically resort the vector many times over while
// optimising the tree.
//
// Paul: I use this when I have already built up a vector of data
// that I want to add, and I don't mind if its contents get shuffled
// by the kdtree optimise routine.
void efficient_replace_and_optimise( std::vector<value_type> & writable_vector )
{
this->clear();
_M_optimise(writable_vector.begin(), writable_vector.end(), 0);
}
KDTree&
operator=(const KDTree& __x)
{
if (this != &__x)
{
_M_acc = __x._M_acc;
_M_dist = __x._M_dist;
_M_cmp = __x._M_cmp;
// this is slow:
// this->insert(begin(), __x.begin(), __x.end());
// this->optimise();
// this is much faster, as it skips a lot of useless work
// do the optimisation before inserting
// Needs to be stored in a vector first as _M_optimise()
// sorts the data in the passed iterators directly.
std::vector<value_type> temp;
temp.reserve(__x.size());
std::copy(__x.begin(),__x.end(),std::back_inserter(temp));
efficient_replace_and_optimise(temp);
}
return *this;
}
~KDTree()
{
this->clear();
}
allocator_type
get_allocator() const
{
return _Base::get_allocator();
}
size_type
size() const
{
return _M_count;
}
size_type
max_size() const
{
return size_type(-1);
}
bool
empty() const
{
return this->size() == 0;
}
void
clear()
{
_M_erase_subtree(_M_get_root());
_M_set_leftmost(&_M_header);
_M_set_rightmost(&_M_header);
_M_set_root(NULL);
_M_count = 0;
}
/*! \brief Comparator for the values in the KDTree.
The comparator shall not be modified, it could invalidate the tree.
\return a copy of the comparator used by the KDTree.
*/
_Cmp
value_comp() const
{ return _M_cmp; }
/*! \brief Accessor to the value's elements.
This accessor shall not be modified, it could invalidate the tree.
\return a copy of the accessor used by the KDTree.
*/
_Acc
value_acc() const
{ return _M_acc; }
/*! \brief Distance calculator between 2 value's element.
This functor can be modified. It's modification will only affect the
behavior of the find and find_nearest functions.
\return a reference to the distance calculator used by the KDTree.
*/
const _Dist&
value_distance() const
{ return _M_dist; }
_Dist&
value_distance()
{ return _M_dist; }
// typedef _Iterator<_Val, reference, pointer> iterator;
typedef _Iterator<_Val, const_reference, const_pointer> const_iterator;
// No mutable iterator at this stage
typedef const_iterator iterator;
typedef std::reverse_iterator<const_iterator> const_reverse_iterator;
typedef std::reverse_iterator<iterator> reverse_iterator;
// Note: the static_cast in end() is invalid (_M_header is not convertable to a _Link_type), but
// thats ok as it just means undefined behaviour if the user dereferences the end() iterator.
const_iterator begin() const { return const_iterator(_M_get_leftmost()); }
const_iterator end() const { return const_iterator(static_cast<_Link_const_type>(&_M_header)); }
const_reverse_iterator rbegin() const { return const_reverse_iterator(end()); }
const_reverse_iterator rend() const { return const_reverse_iterator(begin()); }
iterator
insert(iterator /* ignored */, const_reference __V)
{
return this->insert(__V);
}
iterator
insert(const_reference __V)
{
if (!_M_get_root())
{
_Link_type __n = _M_new_node(__V, &_M_header);
++_M_count;
_M_set_root(__n);
_M_set_leftmost(__n);
_M_set_rightmost(__n);
return iterator(__n);
}
return _M_insert(_M_get_root(), __V, 0);
}
template <class _InputIterator>
void insert(_InputIterator __first, _InputIterator __last) {
for (; __first != __last; ++__first)
this->insert(*__first);
}
void
insert(iterator __pos, size_type __n, const value_type& __x)
{
for (; __n > 0; --__n)
this->insert(__pos, __x);
}
template<typename _InputIterator>
void
insert(iterator __pos, _InputIterator __first, _InputIterator __last) {
for (; __first != __last; ++__first)
this->insert(__pos, *__first);
}
// Note: this uses the find() to location the item you want to erase.
// find() compares by equivalence of location ONLY. See the comments
// above find_exact() for why you may not want this.
//
// If you want to erase ANY item that has the same location as __V,
// then use this function.
//
// If you want to erase a PARTICULAR item, and not any other item
// that might happen to have the same location, then you should use
// erase_exact().
void
erase(const_reference __V) {
const_iterator b = this->find(__V);
this->erase(b);
}
void
erase_exact(const_reference __V) {
this->erase(this->find_exact(__V));
}
// note: kept as const because its easier to const-cast it away
void
erase(const_iterator const& __IT)
{
assert(__IT != this->end());
_Link_const_type target = __IT.get_raw_node();
_Link_const_type n = target;
size_type level = 0;
while ((n = _S_parent(n)) != &_M_header)
++level;
_M_erase( const_cast<_Link_type>(target), level );
_M_delete_node( const_cast<_Link_type>(target) );
--_M_count;
}
/* this does not work since erasure changes sort order
void
erase(const_iterator __A, const_iterator const& __B)
{
if (0 && __A == this->begin() && __B == this->end())
{
this->clear();
}
else
{
while (__A != __B)
this->erase(__A++);
}
}
*/
// compares via equivalence
// so if you are looking for any item with the same location,
// according to the standard accessor comparisions,
// then this is the function for you.
template <class SearchVal>
const_iterator
find(SearchVal const& __V) const
{
if (!_M_get_root()) return this->end();
return _M_find(_M_get_root(), __V, 0);
}
// compares via equality
// if you are looking for a particular item in the tree,
// and (for example) it has an ID that is checked via an == comparison
// eg
// struct Item
// {
// size_type unique_id;
// bool operator==(Item const& a, Item const& b) { return a.unique_id == b.unique_id; }
// Location location;
// };
// Two items may be equivalent in location. find() would return
// either one of them. But no two items have the same ID, so
// find_exact() would always return the item with the same location AND id.
//
template <class SearchVal>
const_iterator
find_exact(SearchVal const& __V) const
{
if (!_M_get_root()) return this->end();
return _M_find_exact(_M_get_root(), __V, 0);
}
// NOTE: see notes on find_within_range().
size_type
count_within_range(const_reference __V, subvalue_type const __R) const
{
if (!_M_get_root()) return 0;
_Region_ __region(__V, __R, _M_acc, _M_cmp);
return this->count_within_range(__region);
}
size_type
count_within_range(_Region_ const& __REGION) const
{
if (!_M_get_root()) return 0;
_Region_ __bounds(__REGION);
return _M_count_within_range(_M_get_root(),
__REGION, __bounds, 0);
}
// NOTE: see notes on find_within_range().
template <typename SearchVal, class Visitor>
Visitor
visit_within_range(SearchVal const& V, subvalue_type const R, Visitor visitor) const
{
if (!_M_get_root()) return visitor;
_Region_ region(V, R, _M_acc, _M_cmp);
return this->visit_within_range(region, visitor);
}
template <class Visitor>
Visitor
visit_within_range(_Region_ const& REGION, Visitor visitor) const
{
if (_M_get_root())
{
_Region_ bounds(REGION);
return _M_visit_within_range(visitor, _M_get_root(), REGION, bounds, 0);
}
return visitor;
}
// NOTE: this will visit points based on 'Manhattan distance' aka city-block distance
// aka taxicab metric. Meaning it will find all points within:
// max(x_dist,max(y_dist,z_dist));
// AND NOT than what you would expect: sqrt(x_dist*x_dist + y_dist*y_dist + z_dist*z_dist)
//
// This is because it converts the distance into a bounding-box 'region' and compares
// against that.
//
// If you want the sqrt() behaviour, ask on the mailing list for different options.
//
template <typename SearchVal, typename _OutputIterator>
_OutputIterator
find_within_range(SearchVal const& val, subvalue_type const range,
_OutputIterator out) const
{
if (!_M_get_root()) return out;
_Region_ region(val, range, _M_acc, _M_cmp);
return this->find_within_range(region, out);
}
template <typename _OutputIterator>
_OutputIterator
find_within_range(_Region_ const& region,
_OutputIterator out) const
{
if (_M_get_root())
{
_Region_ bounds(region);
out = _M_find_within_range(out, _M_get_root(),
region, bounds, 0);
}
return out;
}
template <class SearchVal>
std::pair<const_iterator, distance_type>
find_nearest (SearchVal const& __val) const
{
if (_M_get_root())
{
std::pair<const _Node<_Val>*,
std::pair<size_type, typename _Acc::result_type> >
best = _S_node_nearest (__K, 0, __val,
_M_get_root(), &_M_header, _M_get_root(),
std::sqrt(_S_accumulate_node_distance
(__K, _M_dist, _M_acc, _M_get_root()->_M_value, __val)),
_M_cmp, _M_acc, _M_dist,
always_true<value_type>());
return std::pair<const_iterator, distance_type>
(best.first, best.second.second);
}
return std::pair<const_iterator, distance_type>(end(), 0);
}
template <class SearchVal>
std::pair<const_iterator, distance_type>
find_nearest (SearchVal const& __val, distance_type __max) const
{
if (_M_get_root())
{
bool root_is_candidate = false;
const _Node<_Val>* node = _M_get_root();
{ // scope to ensure we don't use 'root_dist' anywhere else
distance_type root_dist = std::sqrt(_S_accumulate_node_distance
(__K, _M_dist, _M_acc, _M_get_root()->_M_value, __val));
if (root_dist <= __max)
{
root_is_candidate = true;
__max = root_dist;
}
}
std::pair<const _Node<_Val>*,
std::pair<size_type, typename _Acc::result_type> >
best = _S_node_nearest (__K, 0, __val, _M_get_root(), &_M_header,
node, __max, _M_cmp, _M_acc, _M_dist,
always_true<value_type>());
// make sure we didn't just get stuck with the root node...
if (root_is_candidate || best.first != _M_get_root())
return std::pair<const_iterator, distance_type>
(best.first, best.second.second);
}
return std::pair<const_iterator, distance_type>(end(), __max);
}
template <class SearchVal, class _Predicate>
std::pair<const_iterator, distance_type>
find_nearest_if (SearchVal const& __val, distance_type __max,
_Predicate __p) const
{
if (_M_get_root())
{
bool root_is_candidate = false;
const _Node<_Val>* node = _M_get_root();
if (__p(_M_get_root()->_M_value))
{
{ // scope to ensure we don't use root_dist anywhere else
distance_type root_dist = std::sqrt(_S_accumulate_node_distance
(__K, _M_dist, _M_acc, _M_get_root()->_M_value, __val));
if (root_dist <= __max)
{
root_is_candidate = true;
root_dist = __max;
}
}
}
std::pair<const _Node<_Val>*,
std::pair<size_type, typename _Acc::result_type> >
best = _S_node_nearest (__K, 0, __val, _M_get_root(), &_M_header,
node, __max, _M_cmp, _M_acc, _M_dist, __p);
// make sure we didn't just get stuck with the root node...
if (root_is_candidate || best.first != _M_get_root())
return std::pair<const_iterator, distance_type>
(best.first, best.second.second);
}
return std::pair<const_iterator, distance_type>(end(), __max);
}
void
optimise()
{
std::vector<value_type> __v(this->begin(),this->end());
this->clear();
_M_optimise(__v.begin(), __v.end(), 0);
}
void
optimize()
{ // cater for people who cannot spell :)
this->optimise();
}
void check_tree()
{
_M_check_node(_M_get_root(),0);
}
protected:
void _M_check_children( _Link_const_type child, _Link_const_type parent, size_type const level, bool to_the_left )
{
assert(parent);
if (child)
{
_Node_compare_ compare(level % __K, _M_acc, _M_cmp);
// REMEMBER! its a <= relationship for BOTH branches
// for left-case (true), child<=node --> !(node<child)
// for right-case (false), node<=child --> !(child<node)
assert(!to_the_left || !compare(parent->_M_value,child->_M_value)); // check the left
assert(to_the_left || !compare(child->_M_value,parent->_M_value)); // check the right
// and recurse down the tree, checking everything
_M_check_children(_S_left(child),parent,level,to_the_left);
_M_check_children(_S_right(child),parent,level,to_the_left);
}
}
void _M_check_node( _Link_const_type node, size_type const level )
{
if (node)
{
// (comparing on this level)
// everything to the left of this node must be smaller than this
_M_check_children( _S_left(node), node, level, true );
// everything to the right of this node must be larger than this
_M_check_children( _S_right(node), node, level, false );
_M_check_node( _S_left(node), level+1 );
_M_check_node( _S_right(node), level+1 );
}
}
void _M_empty_initialise()
{
_M_set_leftmost(&_M_header);
_M_set_rightmost(&_M_header);
_M_header._M_parent = NULL;
_M_set_root(NULL);
}
iterator
_M_insert_left(_Link_type __N, const_reference __V)
{
_S_set_left(__N, _M_new_node(__V)); ++_M_count;
_S_set_parent( _S_left(__N), __N );
if (__N == _M_get_leftmost())
_M_set_leftmost( _S_left(__N) );
return iterator(_S_left(__N));
}
iterator
_M_insert_right(_Link_type __N, const_reference __V)
{
_S_set_right(__N, _M_new_node(__V)); ++_M_count;
_S_set_parent( _S_right(__N), __N );
if (__N == _M_get_rightmost())
_M_set_rightmost( _S_right(__N) );
return iterator(_S_right(__N));
}
iterator
_M_insert(_Link_type __N, const_reference __V,
size_type const __L)
{
if (_Node_compare_(__L % __K, _M_acc, _M_cmp)(__V, __N->_M_value))
{
if (!_S_left(__N))
return _M_insert_left(__N, __V);
return _M_insert(_S_left(__N), __V, __L+1);
}
else
{
if (!_S_right(__N) || __N == _M_get_rightmost())
return _M_insert_right(__N, __V);
return _M_insert(_S_right(__N), __V, __L+1);
}
}
_Link_type
_M_erase(_Link_type dead_dad, size_type const level)
{
// find a new step_dad, he will become a drop-in replacement.
_Link_type step_dad = _M_get_erase_replacement(dead_dad, level);
// tell dead_dad's parent that his new child is step_dad
if (dead_dad == _M_get_root())
_M_set_root(step_dad);
else if (_S_left(_S_parent(dead_dad)) == dead_dad)
_S_set_left(_S_parent(dead_dad), step_dad);
else
_S_set_right(_S_parent(dead_dad), step_dad);
// deal with the left and right edges of the tree...
// if the dead_dad was at the edge, then substitude...
// but if there IS no new dead, then left_most is the dead_dad's parent
if (dead_dad == _M_get_leftmost())
_M_set_leftmost( (step_dad ? step_dad : _S_parent(dead_dad)) );
if (dead_dad == _M_get_rightmost())
_M_set_rightmost( (step_dad ? step_dad : _S_parent(dead_dad)) );
if (step_dad)
{
// step_dad gets dead_dad's parent
_S_set_parent(step_dad, _S_parent(dead_dad));
// first tell the children that step_dad is their new dad
if (_S_left(dead_dad))
_S_set_parent(_S_left(dead_dad), step_dad);
if (_S_right(dead_dad))
_S_set_parent(_S_right(dead_dad), step_dad);
// step_dad gets dead_dad's children
_S_set_left(step_dad, _S_left(dead_dad));
_S_set_right(step_dad, _S_right(dead_dad));
}
return step_dad;
}
_Link_type
_M_get_erase_replacement(_Link_type node, size_type const level)
{
// if 'node' is null, then we can't do any better
if (_S_is_leaf(node))
return NULL;
std::pair<_Link_type,size_type> candidate;
// if there is nothing to the left, find a candidate on the right tree
if (!_S_left(node))
candidate = _M_get_j_min( std::pair<_Link_type,size_type>(_S_right(node),level), level+1);
// ditto for the right
else if ((!_S_right(node)))
candidate = _M_get_j_max( std::pair<_Link_type,size_type>(_S_left(node),level), level+1);
// we have both children ...
else
{
// we need to do a little more work in order to find a good candidate
// this is actually a technique used to choose a node from either the
// left or right branch RANDOMLY, so that the tree has a greater change of
// staying balanced.
// If this were a true binary tree, we would always hunt down the right branch.
// See top for notes.
_Node_compare_ compare(level % __K, _M_acc, _M_cmp);
// compare the children based on this level's criteria...
// (this gives virtually random results)
if (compare(_S_right(node)->_M_value, _S_left(node)->_M_value))
// the right is smaller, get our replacement from the SMALLEST on the right
candidate = _M_get_j_min(std::pair<_Link_type,size_type>(_S_right(node),level), level+1);
else
candidate = _M_get_j_max( std::pair<_Link_type,size_type>(_S_left(node),level), level+1);
}
// we have a candidate replacement by now.
// remove it from the tree, but don't delete it.
// it must be disconnected before it can be reconnected.
_Link_type parent = _S_parent(candidate.first);
if (_S_left(parent) == candidate.first)
_S_set_left(parent, _M_erase(candidate.first, candidate.second));
else
_S_set_right(parent, _M_erase(candidate.first, candidate.second));
return candidate.first;
}
std::pair<_Link_type,size_type>
_M_get_j_min( std::pair<_Link_type,size_type> const node, size_type const level)
{
typedef std::pair<_Link_type,size_type> Result;
if (_S_is_leaf(node.first))
return Result(node.first,level);
_Node_compare_ compare(node.second % __K, _M_acc, _M_cmp);
Result candidate = node;
if (_S_left(node.first))
{
Result left = _M_get_j_min(Result(_S_left(node.first), node.second), level+1);
if (compare(left.first->_M_value, candidate.first->_M_value))
candidate = left;
}
if (_S_right(node.first))
{
Result right = _M_get_j_min( Result(_S_right(node.first),node.second), level+1);
if (compare(right.first->_M_value, candidate.first->_M_value))
candidate = right;
}
if (candidate.first == node.first)
return Result(candidate.first,level);
return candidate;
}
std::pair<_Link_type,size_type>
_M_get_j_max( std::pair<_Link_type,size_type> const node, size_type const level)
{
typedef std::pair<_Link_type,size_type> Result;
if (_S_is_leaf(node.first))
return Result(node.first,level);
_Node_compare_ compare(node.second % __K, _M_acc, _M_cmp);
Result candidate = node;
if (_S_left(node.first))
{
Result left = _M_get_j_max( Result(_S_left(node.first),node.second), level+1);
if (compare(candidate.first->_M_value, left.first->_M_value))
candidate = left;
}
if (_S_right(node.first))
{
Result right = _M_get_j_max(Result(_S_right(node.first),node.second), level+1);
if (compare(candidate.first->_M_value, right.first->_M_value))
candidate = right;
}
if (candidate.first == node.first)
return Result(candidate.first,level);
return candidate;
}
void
_M_erase_subtree(_Link_type __n)
{
while (__n)
{
_M_erase_subtree(_S_right(__n));
_Link_type __t = _S_left(__n);
_M_delete_node(__n);
__n = __t;
}
}
const_iterator
_M_find(_Link_const_type node, const_reference value, size_type const level) const
{
// be aware! This is very different to normal binary searches, because of the <=
// relationship used. See top for notes.
// Basically we have to check ALL branches, as we may have an identical node
// in different branches.
const_iterator found = this->end();
_Node_compare_ compare(level % __K, _M_acc, _M_cmp);
if (!compare(node->_M_value,value)) // note, this is a <= test
{
// this line is the only difference between _M_find_exact() and _M_find()
if (_M_matches_node(node, value, level))
return const_iterator(node); // return right away
if (_S_left(node))
found = _M_find(_S_left(node), value, level+1);
}
if ( _S_right(node) && found == this->end() && !compare(value,node->_M_value)) // note, this is a <= test
found = _M_find(_S_right(node), value, level+1);
return found;
}
const_iterator
_M_find_exact(_Link_const_type node, const_reference value, size_type const level) const
{
// be aware! This is very different to normal binary searches, because of the <=
// relationship used. See top for notes.
// Basically we have to check ALL branches, as we may have an identical node
// in different branches.
const_iterator found = this->end();
_Node_compare_ compare(level % __K, _M_acc, _M_cmp);
if (!compare(node->_M_value,value)) // note, this is a <= test
{
// this line is the only difference between _M_find_exact() and _M_find()
if (value == *const_iterator(node))
return const_iterator(node); // return right away
if (_S_left(node))
found = _M_find_exact(_S_left(node), value, level+1);
}
// note: no else! items that are identical can be down both branches
if ( _S_right(node) && found == this->end() && !compare(value,node->_M_value)) // note, this is a <= test
found = _M_find_exact(_S_right(node), value, level+1);
return found;
}
bool
_M_matches_node_in_d(_Link_const_type __N, const_reference __V,
size_type const __L) const
{
_Node_compare_ compare(__L % __K, _M_acc, _M_cmp);
return !(compare(__N->_M_value, __V) || compare(__V, __N->_M_value));
}
bool
_M_matches_node_in_other_ds(_Link_const_type __N, const_reference __V,
size_type const __L = 0) const
{
size_type __i = __L;
while ((__i = (__i + 1) % __K) != __L % __K)
if (!_M_matches_node_in_d(__N, __V, __i)) return false;
return true;
}
bool
_M_matches_node(_Link_const_type __N, const_reference __V,
size_type __L = 0) const
{
return _M_matches_node_in_d(__N, __V, __L)
&& _M_matches_node_in_other_ds(__N, __V, __L);
}
size_type
_M_count_within_range(_Link_const_type __N, _Region_ const& __REGION,
_Region_ const& __BOUNDS,
size_type const __L) const
{
size_type count = 0;
if (__REGION.encloses(_S_value(__N)))
{
++count;
}
if (_S_left(__N))
{
_Region_ __bounds(__BOUNDS);
__bounds.set_high_bound(_S_value(__N), __L);
if (__REGION.intersects_with(__bounds))
count += _M_count_within_range(_S_left(__N),
__REGION, __bounds, __L+1);
}
if (_S_right(__N))
{
_Region_ __bounds(__BOUNDS);
__bounds.set_low_bound(_S_value(__N), __L);
if (__REGION.intersects_with(__bounds))
count += _M_count_within_range(_S_right(__N),
__REGION, __bounds, __L+1);
}
return count;
}
template <class Visitor>
Visitor
_M_visit_within_range(Visitor visitor,
_Link_const_type N, _Region_ const& REGION,
_Region_ const& BOUNDS,
size_type const L) const
{
if (REGION.encloses(_S_value(N)))
{
visitor(_S_value(N));
}
if (_S_left(N))
{
_Region_ bounds(BOUNDS);
bounds.set_high_bound(_S_value(N), L);
if (REGION.intersects_with(bounds))
visitor = _M_visit_within_range(visitor, _S_left(N),
REGION, bounds, L+1);
}
if (_S_right(N))
{
_Region_ bounds(BOUNDS);
bounds.set_low_bound(_S_value(N), L);
if (REGION.intersects_with(bounds))
visitor = _M_visit_within_range(visitor, _S_right(N),
REGION, bounds, L+1);
}
return visitor;
}
template <typename _OutputIterator>
_OutputIterator
_M_find_within_range(_OutputIterator out,
_Link_const_type __N, _Region_ const& __REGION,
_Region_ const& __BOUNDS,
size_type const __L) const
{
if (__REGION.encloses(_S_value(__N)))
{
*out++ = _S_value(__N);
}
if (_S_left(__N))
{
_Region_ __bounds(__BOUNDS);
__bounds.set_high_bound(_S_value(__N), __L);
if (__REGION.intersects_with(__bounds))
out = _M_find_within_range(out, _S_left(__N),
__REGION, __bounds, __L+1);
}
if (_S_right(__N))
{
_Region_ __bounds(__BOUNDS);
__bounds.set_low_bound(_S_value(__N), __L);
if (__REGION.intersects_with(__bounds))
out = _M_find_within_range(out, _S_right(__N),
__REGION, __bounds, __L+1);
}
return out;
}
template <typename _Iter>
void
_M_optimise(_Iter const& __A, _Iter const& __B,
size_type const __L)
{
if (__A == __B) return;
_Node_compare_ compare(__L % __K, _M_acc, _M_cmp);
_Iter __m = __A + (__B - __A) / 2;
std::nth_element(__A, __m, __B, compare);
this->insert(*__m);
if (__m != __A) _M_optimise(__A, __m, __L+1);
if (++__m != __B) _M_optimise(__m, __B, __L+1);
}
_Link_const_type
_M_get_root() const
{
return const_cast<_Link_const_type>(_M_root);
}
_Link_type
_M_get_root()
{
return _M_root;
}
void _M_set_root(_Link_type n)
{
_M_root = n;
}
_Link_const_type
_M_get_leftmost() const
{
return static_cast<_Link_type>(_M_header._M_left);
}
void
_M_set_leftmost( _Node_base * a )
{
_M_header._M_left = a;
}
_Link_const_type
_M_get_rightmost() const
{
return static_cast<_Link_type>( _M_header._M_right );
}
void
_M_set_rightmost( _Node_base * a )
{
_M_header._M_right = a;
}
static _Link_type
_S_parent(_Base_ptr N)
{
return static_cast<_Link_type>( N->_M_parent );
}
static _Link_const_type
_S_parent(_Base_const_ptr N)
{
return static_cast<_Link_const_type>( N->_M_parent );
}
static void
_S_set_parent(_Base_ptr N, _Base_ptr p)
{
N->_M_parent = p;
}
static void
_S_set_left(_Base_ptr N, _Base_ptr l)
{
N->_M_left = l;
}
static _Link_type
_S_left(_Base_ptr N)
{
return static_cast<_Link_type>( N->_M_left );
}
static _Link_const_type
_S_left(_Base_const_ptr N)
{
return static_cast<_Link_const_type>( N->_M_left );
}
static void
_S_set_right(_Base_ptr N, _Base_ptr r)
{
N->_M_right = r;
}
static _Link_type
_S_right(_Base_ptr N)
{
return static_cast<_Link_type>( N->_M_right );
}
static _Link_const_type
_S_right(_Base_const_ptr N)
{
return static_cast<_Link_const_type>( N->_M_right );
}
static bool
_S_is_leaf(_Base_const_ptr N)
{
return !_S_left(N) && !_S_right(N);
}
static const_reference
_S_value(_Link_const_type N)
{
return N->_M_value;
}
static const_reference
_S_value(_Base_const_ptr N)
{
return static_cast<_Link_const_type>(N)->_M_value;
}
static _Link_const_type
_S_minimum(_Link_const_type __X)
{
return static_cast<_Link_const_type> ( _Node_base::_S_minimum(__X) );
}
static _Link_const_type
_S_maximum(_Link_const_type __X)
{
return static_cast<_Link_const_type>( _Node_base::_S_maximum(__X) );
}
_Link_type
_M_new_node(const_reference __V, // = value_type(),
_Base_ptr const __PARENT = NULL,
_Base_ptr const __LEFT = NULL,
_Base_ptr const __RIGHT = NULL)
{
typename _Base::NoLeakAlloc noleak(this);
_Link_type new_node = noleak.get();
_Base::_M_construct_node(new_node, __V, __PARENT, __LEFT, __RIGHT);
noleak.disconnect();
return new_node;
}
/* WHAT was this for?
_Link_type
_M_clone_node(_Link_const_type __X)
{
_Link_type __ret = _M_allocate_node(__X->_M_value);
// TODO
return __ret;
}
*/
void
_M_delete_node(_Link_type __p)
{
_Base::_M_destroy_node(__p);
_Base::_M_deallocate_node(__p);
}
_Link_type _M_root;
_Node_base _M_header;
size_type _M_count;
_Acc _M_acc;
_Cmp _M_cmp;
_Dist _M_dist;
#ifdef KDTREE_DEFINE_OSTREAM_OPERATORS
friend std::ostream&
operator<<(std::ostream& o,
KDTree<__K, _Val, _Acc, _Dist, _Cmp, _Alloc> const& tree)
{
o << "meta node: " << tree._M_header << std::endl;
o << "root node: " << tree._M_root << std::endl;
if (tree.empty())
return o << "[empty " << __K << "d-tree " << &tree << "]";
o << "nodes total: " << tree.size() << std::endl;
o << "dimensions: " << __K << std::endl;
typedef KDTree<__K, _Val, _Acc, _Dist, _Cmp, _Alloc> _Tree;
std::stack<_Link_const_type> s;
s.push(tree._M_get_root());
while (!s.empty())
{
_Link_const_type n = s.top();
s.pop();
o << *n << std::endl;
if (_Tree::_S_left(n)) s.push(_Tree::_S_left(n));
if (_Tree::_S_right(n)) s.push(_Tree::_S_right(n));
}
return o;
}
#endif
}; // class KDTree
} // namespace KDTree
#endif // include guard
/* COPYRIGHT --
*
* This file is part of libkdtree++, a C++ template KD-Tree sorting container.
* libkdtree++ is (c) 2004-2007 Martin F. Krafft <libkdtree@pobox.madduck.net>
* and Sylvain Bougerel <sylvain.bougerel.devel@gmail.com> distributed under the
* terms of the Artistic License 2.0. See the ./COPYING file in the source tree
* root for more information.
* Parts of this file are (c) 2004-2007 Paul Harris <paulharris@computer.org>.
*
* THIS PACKAGE IS PROVIDED "AS IS" AND WITHOUT ANY EXPRESS OR IMPLIED
* WARRANTIES, INCLUDING, WITHOUT LIMITATION, THE IMPLIED WARRANTIES
* OF MERCHANTIBILITY AND FITNESS FOR A PARTICULAR PURPOSE.
*/
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