ompl/datastructures/NearestNeighborsLinear.h
00001 /********************************************************************* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Copyright (c) 2008, Willow Garage, Inc. 00005 * All rights reserved. 00006 * 00007 * Redistribution and use in source and binary forms, with or without 00008 * modification, are permitted provided that the following conditions 00009 * are met: 00010 * 00011 * * Redistributions of source code must retain the above copyright 00012 * notice, this list of conditions and the following disclaimer. 00013 * * Redistributions in binary form must reproduce the above 00014 * copyright notice, this list of conditions and the following 00015 * disclaimer in the documentation and/or other materials provided 00016 * with the distribution. 00017 * * Neither the name of the Willow Garage nor the names of its 00018 * contributors may be used to endorse or promote products derived 00019 * from this software without specific prior written permission. 00020 * 00021 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00022 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00023 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00024 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00025 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00026 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00027 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00028 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00029 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00030 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00031 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00032 * POSSIBILITY OF SUCH DAMAGE. 00033 *********************************************************************/ 00034 00035 /* Author: Ioan Sucan */ 00036 00037 #ifndef OMPL_DATASTRUCTURES_NEAREST_NEIGHBORS_LINEAR_ 00038 #define OMPL_DATASTRUCTURES_NEAREST_NEIGHBORS_LINEAR_ 00039 00040 #include "ompl/datastructures/NearestNeighbors.h" 00041 #include "ompl/util/Exception.h" 00042 #include <algorithm> 00043 00044 namespace ompl 00045 { 00046 00056 template<typename _T> 00057 class NearestNeighborsLinear : public NearestNeighbors<_T> 00058 { 00059 public: 00060 NearestNeighborsLinear() : NearestNeighbors<_T>() 00061 { 00062 } 00063 00064 virtual ~NearestNeighborsLinear() 00065 { 00066 } 00067 00068 virtual void clear() 00069 { 00070 data_.clear(); 00071 } 00072 00073 virtual bool reportsSortedResults() const 00074 { 00075 return true; 00076 } 00077 00078 virtual void add(const _T &data) 00079 { 00080 data_.push_back(data); 00081 } 00082 00083 virtual void add(const std::vector<_T> &data) 00084 { 00085 data_.reserve(data_.size() + data.size()); 00086 data_.insert(data_.end(), data.begin(), data.end()); 00087 } 00088 00089 virtual bool remove(const _T &data) 00090 { 00091 if (!data_.empty()) 00092 for (int i = data_.size() - 1 ; i >= 0 ; --i) 00093 if (data_[i] == data) 00094 { 00095 data_.erase(data_.begin() + i); 00096 return true; 00097 } 00098 return false; 00099 } 00100 00101 virtual _T nearest(const _T &data) const 00102 { 00103 const std::size_t sz = data_.size(); 00104 std::size_t pos = sz; 00105 double dmin = 0.0; 00106 for (std::size_t i = 0 ; i < sz ; ++i) 00107 { 00108 double distance = NearestNeighbors<_T>::distFun_(data_[i], data); 00109 if (pos == sz || dmin > distance) 00110 { 00111 pos = i; 00112 dmin = distance; 00113 } 00114 } 00115 if (pos != sz) 00116 return data_[pos]; 00117 00118 throw Exception("No elements found in nearest neighbors data structure"); 00119 } 00120 00122 virtual void nearestK(const _T &data, std::size_t k, std::vector<_T> &nbh) const 00123 { 00124 nbh = data_; 00125 if (nbh.size() > k) 00126 { 00127 std::partial_sort(nbh.begin(), nbh.begin() + k, nbh.end(), 00128 ElemSort(data, NearestNeighbors<_T>::distFun_)); 00129 nbh.resize(k); 00130 } 00131 else 00132 { 00133 std::sort(nbh.begin(), nbh.end(), ElemSort(data, NearestNeighbors<_T>::distFun_)); 00134 } 00135 } 00136 00138 virtual void nearestR(const _T &data, double radius, std::vector<_T> &nbh) const 00139 { 00140 nbh.clear(); 00141 for (std::size_t i = 0 ; i < data_.size() ; ++i) 00142 if (NearestNeighbors<_T>::distFun_(data_[i], data) <= radius) 00143 nbh.push_back(data_[i]); 00144 std::sort(nbh.begin(), nbh.end(), ElemSort(data, NearestNeighbors<_T>::distFun_)); 00145 } 00146 00147 virtual std::size_t size() const 00148 { 00149 return data_.size(); 00150 } 00151 00152 virtual void list(std::vector<_T> &data) const 00153 { 00154 data = data_; 00155 } 00156 00157 protected: 00158 00160 std::vector<_T> data_; 00161 00162 private: 00163 00164 struct ElemSort 00165 { 00166 ElemSort(const _T &e, const typename NearestNeighbors<_T>::DistanceFunction &df) : e_(e), df_(df) 00167 { 00168 } 00169 00170 bool operator()(const _T &a, const _T &b) const 00171 { 00172 return df_(a, e_) < df_(b, e_); 00173 } 00174 00175 const _T &e_; 00176 const typename NearestNeighbors<_T>::DistanceFunction &df_; 00177 }; 00178 00179 }; 00180 00181 00182 } 00183 00184 #endif