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4.37 kB
| /*********************************************************************** | |
| * 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 | |
| * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF | |
| * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | |
| *************************************************************************/ | |
| namespace flann | |
| { | |
| struct LinearIndexParams : public IndexParams | |
| { | |
| LinearIndexParams() | |
| { | |
| (* this)["algorithm"] = FLANN_INDEX_LINEAR; | |
| } | |
| }; | |
| template <typename Distance> | |
| class LinearIndex : public NNIndex<Distance> | |
| { | |
| public: | |
| typedef typename Distance::ElementType ElementType; | |
| typedef typename Distance::ResultType DistanceType; | |
| typedef NNIndex<Distance> BaseClass; | |
| LinearIndex(const IndexParams& params = LinearIndexParams(), Distance d = Distance()) : | |
| BaseClass(params, d) | |
| { | |
| } | |
| LinearIndex(const Matrix<ElementType>& input_data, const IndexParams& params = LinearIndexParams(), Distance d = Distance()) : | |
| BaseClass(params, d) | |
| { | |
| setDataset(input_data); | |
| } | |
| LinearIndex(const LinearIndex& other) : BaseClass(other) | |
| { | |
| } | |
| LinearIndex& operator=(LinearIndex other) | |
| { | |
| this->swap(other); | |
| return *this; | |
| } | |
| virtual ~LinearIndex() | |
| { | |
| } | |
| BaseClass* clone() const | |
| { | |
| return new LinearIndex(*this); | |
| } | |
| void addPoints(const Matrix<ElementType>& points, float rebuild_threshold = 2) | |
| { | |
| assert(points.cols==veclen_); | |
| extendDataset(points); | |
| } | |
| flann_algorithm_t getType() const | |
| { | |
| return FLANN_INDEX_LINEAR; | |
| } | |
| int usedMemory() const | |
| { | |
| return 0; | |
| } | |
| template<typename Archive> | |
| void serialize(Archive& ar) | |
| { | |
| ar.setObject(this); | |
| ar & *static_cast<NNIndex<Distance>*>(this); | |
| if (Archive::is_loading::value) { | |
| index_params_["algorithm"] = getType(); | |
| } | |
| } | |
| void saveIndex(FILE* stream) | |
| { | |
| serialization::SaveArchive sa(stream); | |
| sa & *this; | |
| } | |
| void loadIndex(FILE* stream) | |
| { | |
| serialization::LoadArchive la(stream); | |
| la & *this; | |
| } | |
| void findNeighbors(ResultSet<DistanceType>& resultSet, const ElementType* vec, const SearchParams& /*searchParams*/) const | |
| { | |
| if (removed_) { | |
| for (size_t i = 0; i < points_.size(); ++i) { | |
| if (removed_points_.test(i)) continue; | |
| DistanceType dist = distance_(points_[i], vec, veclen_); | |
| resultSet.addPoint(dist, i); | |
| } | |
| } | |
| else { | |
| for (size_t i = 0; i < points_.size(); ++i) { | |
| DistanceType dist = distance_(points_[i], vec, veclen_); | |
| resultSet.addPoint(dist, i); | |
| } | |
| } | |
| } | |
| protected: | |
| void buildIndexImpl() | |
| { | |
| /* nothing to do here for linear search */ | |
| } | |
| void freeIndex() | |
| { | |
| /* nothing to do here for linear search */ | |
| } | |
| private: | |
| USING_BASECLASS_SYMBOLS | |
| }; | |
| } | |