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