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* Software License Agreement (BSD License)
*
* Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
* Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
*
* THE BSD LICENSE
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
* IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
* NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*************************************************************************/
#ifndef FLANN_RESULTSET_H
#define FLANN_RESULTSET_H
#include <algorithm>
#include <cstring>
#include <iostream>
#include <limits>
#include <set>
#include <vector>
namespace flann
{
/* This record represents a branch point when finding neighbors in
the tree. It contains a record of the minimum distance to the query
point, as well as the node at which the search resumes.
*/
template <typename T, typename DistanceType>
struct BranchStruct
{
T node; /* Tree node at which search resumes */
DistanceType mindist; /* Minimum distance to query for all nodes below. */
BranchStruct() {}
BranchStruct(const T& aNode, DistanceType dist) : node(aNode), mindist(dist) {}
bool operator<(const BranchStruct<T, DistanceType>& rhs) const
{
return mindist<rhs.mindist;
}
};
template <typename DistanceType>
struct DistanceIndex
{
DistanceIndex(DistanceType dist, size_t index) :
dist_(dist), index_(index)
{
}
bool operator<(const DistanceIndex& dist_index) const
{
return (dist_ < dist_index.dist_) || ((dist_ == dist_index.dist_) && index_ < dist_index.index_);
}
DistanceType dist_;
size_t index_;
};
template <typename DistanceType>
class ResultSet
{
public:
virtual ~ResultSet() {}
virtual bool full() const = 0;
virtual void addPoint(DistanceType dist, size_t index) = 0;
virtual DistanceType worstDist() const = 0;
};
/**
* KNNSimpleResultSet does not ensure that the element it holds are unique.
* Is used in those cases where the nearest neighbour algorithm used does not
* attempt to insert the same element multiple times.
*/
template <typename DistanceType>
class KNNSimpleResultSet : public ResultSet<DistanceType>
{
public:
typedef DistanceIndex<DistanceType> DistIndex;
KNNSimpleResultSet(size_t capacity_) :
capacity_(capacity_)
{
// reserving capacity to prevent memory re-allocations
dist_index_.resize(capacity_, DistIndex(std::numeric_limits<DistanceType>::max(),-1));
clear();
}
~KNNSimpleResultSet()
{
}
/**
* Clears the result set
*/
void clear()
{
worst_distance_ = std::numeric_limits<DistanceType>::max();
dist_index_[capacity_-1].dist_ = worst_distance_;
count_ = 0;
}
/**
*
* @return Number of elements in the result set
*/
size_t size() const
{
return count_;
}
/**
* Radius search result set always reports full
* @return
*/
bool full() const
{
return count_==capacity_;
}
/**
* Add a point to result set
* @param dist distance to point
* @param index index of point
*/
void addPoint(DistanceType dist, size_t index)
{
if (dist>=worst_distance_) return;
if (count_ < capacity_) ++count_;
size_t i;
for (i=count_-1; i>0; --i) {
#ifdef FLANN_FIRST_MATCH
if ( (dist_index_[i-1].dist_>dist) || ((dist==dist_index_[i-1].dist_)&&(dist_index_[i-1].index_>index)) )
#else
if (dist_index_[i-1].dist_>dist)
#endif
{
dist_index_[i] = dist_index_[i-1];
}
else break;
}
dist_index_[i].dist_ = dist;
dist_index_[i].index_ = index;
worst_distance_ = dist_index_[capacity_-1].dist_;
}
/**
* Copy indices and distances to output buffers
* @param indices
* @param dists
* @param num_elements Number of elements to copy
* @param sorted Indicates if results should be sorted
*/
void copy(size_t* indices, DistanceType* dists, size_t num_elements, bool sorted = true)
{
size_t n = std::min(count_, num_elements);
for (size_t i=0; i<n; ++i) {
*indices++ = dist_index_[i].index_;
*dists++ = dist_index_[i].dist_;
}
}
DistanceType worstDist() const
{
return worst_distance_;
}
private:
size_t capacity_;
size_t count_;
DistanceType worst_distance_;
std::vector<DistIndex> dist_index_;
};
/**
* K-Nearest neighbour result set. Ensures that the elements inserted are unique
*/
template <typename DistanceType>
class KNNResultSet : public ResultSet<DistanceType>
{
public:
typedef DistanceIndex<DistanceType> DistIndex;
KNNResultSet(int capacity) : capacity_(capacity)
{
// reserving capacity to prevent memory re-allocations
dist_index_.resize(capacity_, DistIndex(std::numeric_limits<DistanceType>::max(),-1));
clear();
}
~KNNResultSet()
{
}
/**
* Clears the result set
*/
void clear()
{
worst_distance_ = std::numeric_limits<DistanceType>::max();
dist_index_[capacity_-1].dist_ = worst_distance_;
count_ = 0;
}
size_t size() const
{
return count_;
}
bool full() const
{
return count_ == capacity_;
}
void addPoint(DistanceType dist, size_t index)
{
if (dist >= worst_distance_) return;
size_t i;
for (i = count_; i > 0; --i) {
#ifdef FLANN_FIRST_MATCH
if ( (dist_index_[i-1].dist_<=dist) && ((dist!=dist_index_[i-1].dist_)||(dist_index_[i-1].index_<=index)) )
#else
if (dist_index_[i-1].dist_<=dist)
#endif
{
// Check for duplicate indices
size_t j = i - 1;
while (dist_index_[j].dist_ == dist) {
if (dist_index_[j].index_ == index) {
return;
}
--j;
}
break;
}
}
if (count_ < capacity_) ++count_;
for (size_t j = count_-1; j > i; --j) {
dist_index_[j] = dist_index_[j-1];
}
dist_index_[i].dist_ = dist;
dist_index_[i].index_ = index;
worst_distance_ = dist_index_[capacity_-1].dist_;
}
/**
* Copy indices and distances to output buffers
* @param indices
* @param dists
* @param num_elements Number of elements to copy
* @param sorted Indicates if results should be sorted
*/
void copy(size_t* indices, DistanceType* dists, size_t num_elements, bool sorted = true)
{
size_t n = std::min(count_, num_elements);
for (size_t i=0; i<n; ++i) {
*indices++ = dist_index_[i].index_;
*dists++ = dist_index_[i].dist_;
}
}
DistanceType worstDist() const
{
return worst_distance_;
}
private:
size_t capacity_;
size_t count_;
DistanceType worst_distance_;
std::vector<DistIndex> dist_index_;
};
template <typename DistanceType>
class KNNResultSet2 : public ResultSet<DistanceType>
{
public:
typedef DistanceIndex<DistanceType> DistIndex;
KNNResultSet2(size_t capacity_) :
capacity_(capacity_)
{
// reserving capacity to prevent memory re-allocations
dist_index_.reserve(capacity_);
clear();
}
~KNNResultSet2()
{
}
/**
* Clears the result set
*/
void clear()
{
dist_index_.clear();
worst_dist_ = std::numeric_limits<DistanceType>::max();
is_full_ = false;
}
/**
*
* @return Number of elements in the result set
*/
size_t size() const
{
return dist_index_.size();
}
/**
* Radius search result set always reports full
* @return
*/
bool full() const
{
return is_full_;
}
/**
* Add another point to result set
* @param dist distance to point
* @param index index of point
* Pre-conditions: capacity_>0
*/
void addPoint(DistanceType dist, size_t index)
{
if (dist>=worst_dist_) return;
if (dist_index_.size()==capacity_) {
// if result set if filled to capacity, remove farthest element
std::pop_heap(dist_index_.begin(), dist_index_.end());
dist_index_.pop_back();
}
// add new element
dist_index_.push_back(DistIndex(dist,index));
if (is_full_) { // when is_full_==true, we have a heap
std::push_heap(dist_index_.begin(), dist_index_.end());
}
if (dist_index_.size()==capacity_) {
if (!is_full_) {
std::make_heap(dist_index_.begin(), dist_index_.end());
is_full_ = true;
}
// we replaced the farthest element, update worst distance
worst_dist_ = dist_index_[0].dist_;
}
}
/**
* Copy indices and distances to output buffers
* @param indices
* @param dists
* @param num_elements Number of elements to copy
* @param sorted Indicates if results should be sorted
*/
void copy(size_t* indices, DistanceType* dists, size_t num_elements, bool sorted = true)
{
if (sorted) {
// std::sort_heap(dist_index_.begin(), dist_index_.end());
// sort seems faster here, even though dist_index_ is a heap
std::sort(dist_index_.begin(), dist_index_.end());
}
else {
if (num_elements<size()) {
std::nth_element(dist_index_.begin(), dist_index_.begin()+num_elements, dist_index_.end());
}
}
size_t n = std::min(dist_index_.size(), num_elements);
for (size_t i=0; i<n; ++i) {
*indices++ = dist_index_[i].index_;
*dists++ = dist_index_[i].dist_;
}
}
DistanceType worstDist() const
{
return worst_dist_;
}
private:
size_t capacity_;
DistanceType worst_dist_;
std::vector<DistIndex> dist_index_;
bool is_full_;
};
/**
* Unbounded radius result set. It will hold as many elements as
* are added to it.
*/
template <typename DistanceType>
class RadiusResultSet : public ResultSet<DistanceType>
{
public:
typedef DistanceIndex<DistanceType> DistIndex;
RadiusResultSet(DistanceType radius_) :
radius_(radius_)
{
// reserving some memory to limit number of re-allocations
dist_index_.reserve(1024);
clear();
}
~RadiusResultSet()
{
}
/**
* Clears the result set
*/
void clear()
{
dist_index_.clear();
}
/**
*
* @return Number of elements in the result set
*/
size_t size() const
{
return dist_index_.size();
}
/**
* Radius search result set always reports full
* @return
*/
bool full() const
{
return true;
}
/**
* Add another point to result set
* @param dist distance to point
* @param index index of point
* Pre-conditions: capacity_>0
*/
void addPoint(DistanceType dist, size_t index)
{
if (dist<radius_) {
// add new element
dist_index_.push_back(DistIndex(dist,index));
}
}
/**
* Copy indices and distances to output buffers
* @param indices
* @param dists
* @param num_elements Number of elements to copy
* @param sorted Indicates if results should be sorted
*/
void copy(size_t* indices, DistanceType* dists, size_t num_elements, bool sorted = true)
{
if (sorted) {
// std::sort_heap(dist_index_.begin(), dist_index_.end());
// sort seems faster here, even though dist_index_ is a heap
std::sort(dist_index_.begin(), dist_index_.end());
}
else {
if (num_elements<size()) {
std::nth_element(dist_index_.begin(), dist_index_.begin()+num_elements, dist_index_.end());
}
}
size_t n = std::min(dist_index_.size(), num_elements);
for (size_t i=0; i<n; ++i) {
*indices++ = dist_index_[i].index_;
*dists++ = dist_index_[i].dist_;
}
}
DistanceType worstDist() const
{
return radius_;
}
private:
DistanceType radius_;
std::vector<DistIndex> dist_index_;
};
/**
* Bounded radius result set. It limits the number of elements
* it can hold to a preset capacity.
*/
template <typename DistanceType>
class KNNRadiusResultSet : public ResultSet<DistanceType>
{
public:
typedef DistanceIndex<DistanceType> DistIndex;
KNNRadiusResultSet(DistanceType radius_, size_t capacity_) :
radius_(radius_), capacity_(capacity_)
{
// reserving capacity to prevent memory re-allocations
dist_index_.reserve(capacity_);
clear();
}
~KNNRadiusResultSet()
{
}
/**
* Clears the result set
*/
void clear()
{
dist_index_.clear();
worst_dist_ = radius_;
is_heap_ = false;
}
/**
*
* @return Number of elements in the result set
*/
size_t size() const
{
return dist_index_.size();
}
/**
* Radius search result set always reports full
* @return
*/
bool full() const
{
return true;
}
/**
* Add another point to result set
* @param dist distance to point
* @param index index of point
* Pre-conditions: capacity_>0
*/
void addPoint(DistanceType dist, size_t index)
{
if (dist>=worst_dist_) return;
if (dist_index_.size()==capacity_) {
// if result set is filled to capacity, remove farthest element
std::pop_heap(dist_index_.begin(), dist_index_.end());
dist_index_.pop_back();
}
// add new element
dist_index_.push_back(DistIndex(dist,index));
if (is_heap_) {
std::push_heap(dist_index_.begin(), dist_index_.end());
}
if (dist_index_.size()==capacity_) {
// when got to full capacity, make it a heap
if (!is_heap_) {
std::make_heap(dist_index_.begin(), dist_index_.end());
is_heap_ = true;
}
// we replaced the farthest element, update worst distance
worst_dist_ = dist_index_[0].dist_;
}
}
/**
* Copy indices and distances to output buffers
* @param indices
* @param dists
* @param num_elements Number of elements to copy
* @param sorted Indicates if results should be sorted
*/
void copy(size_t* indices, DistanceType* dists, size_t num_elements, bool sorted = true)
{
if (sorted) {
// std::sort_heap(dist_index_.begin(), dist_index_.end());
// sort seems faster here, even though dist_index_ is a heap
std::sort(dist_index_.begin(), dist_index_.end());
}
else {
if (num_elements<size()) {
std::nth_element(dist_index_.begin(), dist_index_.begin()+num_elements, dist_index_.end());
}
}
size_t n = std::min(dist_index_.size(), num_elements);
for (size_t i=0; i<n; ++i) {
*indices++ = dist_index_[i].index_;
*dists++ = dist_index_[i].dist_;
}
}
DistanceType worstDist() const
{
return worst_dist_;
}
private:
bool is_heap_;
DistanceType radius_;
size_t capacity_;
DistanceType worst_dist_;
std::vector<DistIndex> dist_index_;
};
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/**
* This is a result set that only counts the neighbors within a radius.
*/
template <typename DistanceType>
class CountRadiusResultSet : public ResultSet<DistanceType>
{
DistanceType radius;
size_t count;
public:
CountRadiusResultSet(DistanceType radius_ ) :
radius(radius_)
{
clear();
}
~CountRadiusResultSet()
{
}
void clear()
{
count = 0;
}
size_t size() const
{
return count;
}
bool full() const
{
return true;
}
void addPoint(DistanceType dist, size_t index)
{
if (dist<radius) {
count++;
}
}
DistanceType worstDist() const
{
return radius;
}
};
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/** Class that holds the k NN neighbors
*/
template<typename DistanceType>
class UniqueResultSet : public ResultSet<DistanceType>
{
public:
struct DistIndex
{
DistIndex(DistanceType dist, unsigned int index) :
dist_(dist), index_(index)
{
}
bool operator<(const DistIndex dist_index) const
{
return (dist_ < dist_index.dist_) || ((dist_ == dist_index.dist_) && index_ < dist_index.index_);
}
DistanceType dist_;
unsigned int index_;
};
/** Default cosntructor */
UniqueResultSet() :
worst_distance_(std::numeric_limits<DistanceType>::max())
{
}
/** Check the status of the set
* @return true if we have k NN
*/
inline bool full() const
{
return is_full_;
}
/** Copy the set to two C arrays
* @param indices pointer to a C array of indices
* @param dist pointer to a C array of distances
* @param n_neighbors the number of neighbors to copy
*/
void copy(size_t* indices, DistanceType* dist, int n_neighbors, bool sorted = true)
{
if (n_neighbors<0) n_neighbors = dist_indices_.size();
int i = 0;
typedef typename std::set<DistIndex>::const_iterator Iterator;
for (Iterator dist_index = dist_indices_.begin(), dist_index_end =
dist_indices_.end(); (dist_index != dist_index_end) && (i < n_neighbors); ++dist_index, ++indices, ++dist, ++i) {
*indices = dist_index->index_;
*dist = dist_index->dist_;
}
}
/** The number of neighbors in the set
* @return
*/
size_t size() const
{
return dist_indices_.size();
}
/** The distance of the furthest neighbor
* If we don't have enough neighbors, it returns the max possible value
* @return
*/
inline DistanceType worstDist() const
{
return worst_distance_;
}
protected:
/** Flag to say if the set is full */
bool is_full_;
/** The worst distance found so far */
DistanceType worst_distance_;
/** The best candidates so far */
std::set<DistIndex> dist_indices_;
};
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/** Class that holds the k NN neighbors
* Faster than KNNResultSet as it uses a binary heap and does not maintain two arrays
*/
template<typename DistanceType>
class KNNUniqueResultSet : public UniqueResultSet<DistanceType>
{
public:
/** Constructor
* @param capacity the number of neighbors to store at max
*/
KNNUniqueResultSet(unsigned int capacity) : capacity_(capacity)
{
this->is_full_ = false;
this->clear();
}
/** Add a possible candidate to the best neighbors
* @param dist distance for that neighbor
* @param index index of that neighbor
*/
inline void addPoint(DistanceType dist, size_t index)
{
// Don't do anything if we are worse than the worst
if (dist >= worst_distance_) return;
dist_indices_.insert(DistIndex(dist, index));
if (is_full_) {
if (dist_indices_.size() > capacity_) {
dist_indices_.erase(*dist_indices_.rbegin());
worst_distance_ = dist_indices_.rbegin()->dist_;
}
}
else if (dist_indices_.size() == capacity_) {
is_full_ = true;
worst_distance_ = dist_indices_.rbegin()->dist_;
}
}
/** Remove all elements in the set
*/
void clear()
{
dist_indices_.clear();
worst_distance_ = std::numeric_limits<DistanceType>::max();
is_full_ = false;
}
protected:
typedef typename UniqueResultSet<DistanceType>::DistIndex DistIndex;
using UniqueResultSet<DistanceType>::is_full_;
using UniqueResultSet<DistanceType>::worst_distance_;
using UniqueResultSet<DistanceType>::dist_indices_;
/** The number of neighbors to keep */
unsigned int capacity_;
};
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/** Class that holds the radius nearest neighbors
* It is more accurate than RadiusResult as it is not limited in the number of neighbors
*/
template<typename DistanceType>
class RadiusUniqueResultSet : public UniqueResultSet<DistanceType>
{
public:
/** Constructor
* @param capacity the number of neighbors to store at max
*/
RadiusUniqueResultSet(DistanceType radius) :
radius_(radius)
{
is_full_ = true;
}
/** Add a possible candidate to the best neighbors
* @param dist distance for that neighbor
* @param index index of that neighbor
*/
void addPoint(DistanceType dist, size_t index)
{
if (dist < radius_) dist_indices_.insert(DistIndex(dist, index));
}
/** Remove all elements in the set
*/
inline void clear()
{
dist_indices_.clear();
}
/** Check the status of the set
* @return alwys false
*/
inline bool full() const
{
return true;
}
/** The distance of the furthest neighbor
* If we don't have enough neighbors, it returns the max possible value
* @return
*/
inline DistanceType worstDist() const
{
return radius_;
}
private:
typedef typename UniqueResultSet<DistanceType>::DistIndex DistIndex;
using UniqueResultSet<DistanceType>::dist_indices_;
using UniqueResultSet<DistanceType>::is_full_;
/** The furthest distance a neighbor can be */
DistanceType radius_;
};
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
/** Class that holds the k NN neighbors within a radius distance
*/
template<typename DistanceType>
class KNNRadiusUniqueResultSet : public KNNUniqueResultSet<DistanceType>
{
public:
/** Constructor
* @param capacity the number of neighbors to store at max
*/
KNNRadiusUniqueResultSet(DistanceType radius, size_t capacity) : KNNUniqueResultSet<DistanceType>(capacity)
{
this->radius_ = radius;
this->clear();
}
/** Remove all elements in the set
*/
void clear()
{
dist_indices_.clear();
worst_distance_ = radius_;
is_full_ = true;
}
private:
using KNNUniqueResultSet<DistanceType>::dist_indices_;
using KNNUniqueResultSet<DistanceType>::is_full_;
using KNNUniqueResultSet<DistanceType>::worst_distance_;
/** The maximum distance of a neighbor */
DistanceType radius_;
};
}
#endif //FLANN_RESULTSET_H
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