From 9da5b3b91863ad56459c4af2dc3fc727c91f9e1a Mon Sep 17 00:00:00 2001 From: "k.koide" Date: Wed, 5 Jun 2024 11:15:10 +0900 Subject: [PATCH 1/3] purge deprecated --- include/small_gicp/ann/deprecated/kdtree.hpp | 105 - .../small_gicp/ann/deprecated/kdtree_omp.hpp | 22 - .../small_gicp/ann/deprecated/kdtree_tbb.hpp | 22 - .../small_gicp/ann/deprecated/nanoflann.hpp | 2048 ----------------- .../ann/deprecated/nanoflann_omp.hpp | 657 ------ .../ann/deprecated/nanoflann_tbb.hpp | 639 ----- 6 files changed, 3493 deletions(-) delete mode 100644 include/small_gicp/ann/deprecated/kdtree.hpp delete mode 100644 include/small_gicp/ann/deprecated/kdtree_omp.hpp delete mode 100644 include/small_gicp/ann/deprecated/kdtree_tbb.hpp delete mode 100644 include/small_gicp/ann/deprecated/nanoflann.hpp delete mode 100644 include/small_gicp/ann/deprecated/nanoflann_omp.hpp delete mode 100644 include/small_gicp/ann/deprecated/nanoflann_tbb.hpp diff --git a/include/small_gicp/ann/deprecated/kdtree.hpp b/include/small_gicp/ann/deprecated/kdtree.hpp deleted file mode 100644 index 5b1c611..0000000 --- a/include/small_gicp/ann/deprecated/kdtree.hpp +++ /dev/null @@ -1,105 +0,0 @@ -// SPDX-FileCopyrightText: Copyright 2024 Kenji Koide -// SPDX-License-Identifier: MIT -#pragma once - -#include -#include -#include -#include -#include - -namespace small_gicp { - -/// @brief Unsafe KdTree with arbitrary nanoflann Adaptor. -/// @note This class does not hold the ownership of the input points. -/// You must keep the input points along with this class. -template class Adaptor> -class UnsafeKdTreeGeneric { -public: - using Ptr = std::shared_ptr; - using ConstPtr = std::shared_ptr; - using ThisClass = UnsafeKdTreeGeneric; - using Index = Adaptor, ThisClass, 3, size_t>; - - /// @brief Constructor - /// @param points Input points - explicit UnsafeKdTreeGeneric(const PointCloud& points) : points(points), index(3, *this, nanoflann::KDTreeSingleIndexAdaptorParams(10)) { index.buildIndex(); } - - /// @brief Constructor - /// @param points Input points - /// @params num_threads Number of threads used for building the index (This argument is only valid for OMP implementation) - explicit UnsafeKdTreeGeneric(const PointCloud& points, int num_threads) : points(points), index(3, *this, nanoflann::KDTreeSingleIndexAdaptorParams(10)) { - index.buildIndex(num_threads); - } - - ~UnsafeKdTreeGeneric() {} - - // Interfaces for nanoflann - size_t kdtree_get_point_count() const { return traits::size(points); } - double kdtree_get_pt(const size_t idx, const size_t dim) const { return traits::point(points, idx)[dim]; } - - template - bool kdtree_get_bbox(BBox&) const { - return false; - } - - /// @brief Find k-nearest neighbors - size_t knn_search(const Eigen::Vector4d& pt, size_t k, size_t* k_indices, double* k_sq_dists) const { return index.knnSearch(pt.data(), k, k_indices, k_sq_dists); } - -private: - const PointCloud& points; ///< Input points - Index index; ///< KdTree index -}; - -/// @brief KdTree with arbitrary nanoflann Adaptor -template class Adaptor> -class KdTreeGeneric { -public: - using Ptr = std::shared_ptr; - using ConstPtr = std::shared_ptr; - - /// @brief Constructor - /// @param points Input points - explicit KdTreeGeneric(const std::shared_ptr& points) : points(points), tree(*points) {} - - /// @brief Constructor - /// @param points Input points - explicit KdTreeGeneric(const std::shared_ptr& points, int num_threads) : points(points), tree(*points, num_threads) {} - - ~KdTreeGeneric() {} - - /// @brief Find k-nearest neighbors - size_t knn_search(const Eigen::Vector4d& pt, size_t k, size_t* k_indices, double* k_sq_dists) const { return tree.knn_search(pt, k, k_indices, k_sq_dists); } - -private: - const std::shared_ptr points; ///< Input points - const UnsafeKdTreeGeneric tree; ///< KdTree -}; - -/// @brief Standard KdTree (unsafe) -template -using UnsafeKdTree = UnsafeKdTreeGeneric; - -/// @brief Standard KdTree -template -using KdTree = KdTreeGeneric; - -namespace traits { - -template class Adaptor> -struct Traits> { - static size_t knn_search(const UnsafeKdTreeGeneric& tree, const Eigen::Vector4d& point, size_t k, size_t* k_indices, double* k_sq_dists) { - return tree.knn_search(point, k, k_indices, k_sq_dists); - } -}; - -template class Adaptor> -struct Traits> { - static size_t knn_search(const KdTreeGeneric& tree, const Eigen::Vector4d& point, size_t k, size_t* k_indices, double* k_sq_dists) { - return tree.knn_search(point, k, k_indices, k_sq_dists); - } -}; - -} // namespace traits - -} // namespace small_gicp diff --git a/include/small_gicp/ann/deprecated/kdtree_omp.hpp b/include/small_gicp/ann/deprecated/kdtree_omp.hpp deleted file mode 100644 index b958b8e..0000000 --- a/include/small_gicp/ann/deprecated/kdtree_omp.hpp +++ /dev/null @@ -1,22 +0,0 @@ -// SPDX-FileCopyrightText: Copyright 2024 Kenji Koide -// SPDX-License-Identifier: MIT -#pragma once - -#include -#include -#include -#include - -namespace small_gicp { - -/// @brief Unsafe KdTree with multi-thread tree construction with OpenMP backend. -/// @note This class only parallelizes the tree construction. The search is still single-threaded as in the normal KdTree. -template -using UnsafeKdTreeOMP = UnsafeKdTreeGeneric; - -/// @brief KdTree with multi-thread tree construction with OpenMP backend. -/// @note This class only parallelizes the tree construction. The search is still single-threaded as in the normal KdTree. -template -using KdTreeOMP = KdTreeGeneric; - -} // namespace small_gicp diff --git a/include/small_gicp/ann/deprecated/kdtree_tbb.hpp b/include/small_gicp/ann/deprecated/kdtree_tbb.hpp deleted file mode 100644 index fe3be81..0000000 --- a/include/small_gicp/ann/deprecated/kdtree_tbb.hpp +++ /dev/null @@ -1,22 +0,0 @@ -// SPDX-FileCopyrightText: Copyright 2024 Kenji Koide -// SPDX-License-Identifier: MIT -#pragma once - -#include -#include -#include -#include - -namespace small_gicp { - -/// @brief Unsafe KdTree with multi-thread tree construction with TBB backend. -/// @note This class only parallelizes the tree construction. The search is still single-threaded as in the normal KdTree. -template -using UnsafeKdTreeTBB = UnsafeKdTreeGeneric; - -/// @brief KdTree with multi-thread tree construction with TBB backend. -/// @note This class only parallelizes the tree construction. The search is still single-threaded as in the normal KdTree. -template -using KdTreeTBB = KdTreeGeneric; - -} // namespace small_gicp diff --git a/include/small_gicp/ann/deprecated/nanoflann.hpp b/include/small_gicp/ann/deprecated/nanoflann.hpp deleted file mode 100644 index aefdaee..0000000 --- a/include/small_gicp/ann/deprecated/nanoflann.hpp +++ /dev/null @@ -1,2048 +0,0 @@ -/*********************************************************************** - * 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. - * Copyright 2011-2021 Jose Luis Blanco (joseluisblancoc@gmail.com). - * 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. - *************************************************************************/ - -/** \mainpage nanoflann C++ API documentation - * nanoflann is a C++ header-only library for building KD-Trees, mostly - * optimized for 2D or 3D point clouds. - * - * nanoflann does not require compiling or installing, just an - * #include in your code. - * - * See: - * - C++ API organized by modules - * - Online README - * - Doxygen - * documentation - */ - -#ifndef NANOFLANN_HPP_ -#define NANOFLANN_HPP_ - -#include -#include -#include -#include // for abs() -#include // for fwrite() -#include // for abs() -#include -#include // std::reference_wrapper -#include -#include - -/** Library version: 0xMmP (M=Major,m=minor,P=patch) */ -#define NANOFLANN_VERSION 0x132 - -// Avoid conflicting declaration of min/max macros in windows headers -#if !defined(NOMINMAX) && \ - (defined(_WIN32) || defined(_WIN32_) || defined(WIN32) || defined(_WIN64)) -#define NOMINMAX -#ifdef max -#undef max -#undef min -#endif -#endif - -namespace nanoflann { -/** @addtogroup nanoflann_grp nanoflann C++ library for ANN - * @{ */ - -/** the PI constant (required to avoid MSVC missing symbols) */ -template T pi_const() { - return static_cast(3.14159265358979323846); -} - -/** - * Traits if object is resizable and assignable (typically has a resize | assign - * method) - */ -template struct has_resize : std::false_type {}; - -template -struct has_resize().resize(1), 0)> - : std::true_type {}; - -template struct has_assign : std::false_type {}; - -template -struct has_assign().assign(1, 0), 0)> - : std::true_type {}; - -/** - * Free function to resize a resizable object - */ -template -inline typename std::enable_if::value, void>::type -resize(Container &c, const size_t nElements) { - c.resize(nElements); -} - -/** - * Free function that has no effects on non resizable containers (e.g. - * std::array) It raises an exception if the expected size does not match - */ -template -inline typename std::enable_if::value, void>::type -resize(Container &c, const size_t nElements) { - if (nElements != c.size()) - throw std::logic_error("Try to change the size of a std::array."); -} - -/** - * Free function to assign to a container - */ -template -inline typename std::enable_if::value, void>::type -assign(Container &c, const size_t nElements, const T &value) { - c.assign(nElements, value); -} - -/** - * Free function to assign to a std::array - */ -template -inline typename std::enable_if::value, void>::type -assign(Container &c, const size_t nElements, const T &value) { - for (size_t i = 0; i < nElements; i++) - c[i] = value; -} - -/** @addtogroup result_sets_grp Result set classes - * @{ */ -template -class KNNResultSet { -public: - typedef _DistanceType DistanceType; - typedef _IndexType IndexType; - typedef _CountType CountType; - -private: - IndexType *indices; - DistanceType *dists; - CountType capacity; - CountType count; - -public: - inline KNNResultSet(CountType capacity_) - : indices(0), dists(0), capacity(capacity_), count(0) {} - - inline void init(IndexType *indices_, DistanceType *dists_) { - indices = indices_; - dists = dists_; - count = 0; - if (capacity) - dists[capacity - 1] = (std::numeric_limits::max)(); - } - - inline CountType size() const { return count; } - - inline bool full() const { return count == capacity; } - - /** - * Called during search to add an element matching the criteria. - * @return true if the search should be continued, false if the results are - * sufficient - */ - inline bool addPoint(DistanceType dist, IndexType index) { - CountType i; - for (i = count; i > 0; --i) { -#ifdef NANOFLANN_FIRST_MATCH // If defined and two points have the same - // distance, the one with the lowest-index will be - // returned first. - if ((dists[i - 1] > dist) || - ((dist == dists[i - 1]) && (indices[i - 1] > index))) { -#else - if (dists[i - 1] > dist) { -#endif - if (i < capacity) { - dists[i] = dists[i - 1]; - indices[i] = indices[i - 1]; - } - } else - break; - } - if (i < capacity) { - dists[i] = dist; - indices[i] = index; - } - if (count < capacity) - count++; - - // tell caller that the search shall continue - return true; - } - - inline DistanceType worstDist() const { return dists[capacity - 1]; } -}; - -/** operator "<" for std::sort() */ -struct IndexDist_Sorter { - /** PairType will be typically: std::pair */ - template - inline bool operator()(const PairType &p1, const PairType &p2) const { - return p1.second < p2.second; - } -}; - -/** - * A result-set class used when performing a radius based search. - */ -template -class RadiusResultSet { -public: - typedef _DistanceType DistanceType; - typedef _IndexType IndexType; - -public: - const DistanceType radius; - - std::vector> &m_indices_dists; - - inline RadiusResultSet( - DistanceType radius_, - std::vector> &indices_dists) - : radius(radius_), m_indices_dists(indices_dists) { - init(); - } - - inline void init() { clear(); } - inline void clear() { m_indices_dists.clear(); } - - inline size_t size() const { return m_indices_dists.size(); } - - inline bool full() const { return true; } - - /** - * Called during search to add an element matching the criteria. - * @return true if the search should be continued, false if the results are - * sufficient - */ - inline bool addPoint(DistanceType dist, IndexType index) { - if (dist < radius) - m_indices_dists.push_back(std::make_pair(index, dist)); - return true; - } - - inline DistanceType worstDist() const { return radius; } - - /** - * Find the worst result (furtherest neighbor) without copying or sorting - * Pre-conditions: size() > 0 - */ - std::pair worst_item() const { - if (m_indices_dists.empty()) - throw std::runtime_error("Cannot invoke RadiusResultSet::worst_item() on " - "an empty list of results."); - typedef - typename std::vector>::const_iterator - DistIt; - DistIt it = std::max_element(m_indices_dists.begin(), m_indices_dists.end(), - IndexDist_Sorter()); - return *it; - } -}; - -/** @} */ - -/** @addtogroup loadsave_grp Load/save auxiliary functions - * @{ */ -template -void save_value(FILE *stream, const T &value, size_t count = 1) { - fwrite(&value, sizeof(value), count, stream); -} - -template -void save_value(FILE *stream, const std::vector &value) { - size_t size = value.size(); - fwrite(&size, sizeof(size_t), 1, stream); - fwrite(&value[0], sizeof(T), size, stream); -} - -template -void load_value(FILE *stream, T &value, size_t count = 1) { - size_t read_cnt = fread(&value, sizeof(value), count, stream); - if (read_cnt != count) { - throw std::runtime_error("Cannot read from file"); - } -} - -template void load_value(FILE *stream, std::vector &value) { - size_t size; - size_t read_cnt = fread(&size, sizeof(size_t), 1, stream); - if (read_cnt != 1) { - throw std::runtime_error("Cannot read from file"); - } - value.resize(size); - read_cnt = fread(&value[0], sizeof(T), size, stream); - if (read_cnt != size) { - throw std::runtime_error("Cannot read from file"); - } -} -/** @} */ - -/** @addtogroup metric_grp Metric (distance) classes - * @{ */ - -struct Metric {}; - -/** Manhattan distance functor (generic version, optimized for - * high-dimensionality data sets). Corresponding distance traits: - * nanoflann::metric_L1 \tparam T Type of the elements (e.g. double, float, - * uint8_t) \tparam _DistanceType Type of distance variables (must be signed) - * (e.g. float, double, int64_t) - */ -template -struct L1_Adaptor { - typedef T ElementType; - typedef _DistanceType DistanceType; - - const DataSource &data_source; - - L1_Adaptor(const DataSource &_data_source) : data_source(_data_source) {} - - inline DistanceType evalMetric(const T *a, const size_t b_idx, size_t size, - DistanceType worst_dist = -1) const { - DistanceType result = DistanceType(); - const T *last = a + size; - const T *lastgroup = last - 3; - size_t d = 0; - - /* Process 4 items with each loop for efficiency. */ - while (a < lastgroup) { - const DistanceType diff0 = - std::abs(a[0] - data_source.kdtree_get_pt(b_idx, d++)); - const DistanceType diff1 = - std::abs(a[1] - data_source.kdtree_get_pt(b_idx, d++)); - const DistanceType diff2 = - std::abs(a[2] - data_source.kdtree_get_pt(b_idx, d++)); - const DistanceType diff3 = - std::abs(a[3] - data_source.kdtree_get_pt(b_idx, d++)); - result += diff0 + diff1 + diff2 + diff3; - a += 4; - if ((worst_dist > 0) && (result > worst_dist)) { - return result; - } - } - /* Process last 0-3 components. Not needed for standard vector lengths. */ - while (a < last) { - result += std::abs(*a++ - data_source.kdtree_get_pt(b_idx, d++)); - } - return result; - } - - template - inline DistanceType accum_dist(const U a, const V b, const size_t) const { - return std::abs(a - b); - } -}; - -/** Squared Euclidean distance functor (generic version, optimized for - * high-dimensionality data sets). Corresponding distance traits: - * nanoflann::metric_L2 \tparam T Type of the elements (e.g. double, float, - * uint8_t) \tparam _DistanceType Type of distance variables (must be signed) - * (e.g. float, double, int64_t) - */ -template -struct L2_Adaptor { - typedef T ElementType; - typedef _DistanceType DistanceType; - - const DataSource &data_source; - - L2_Adaptor(const DataSource &_data_source) : data_source(_data_source) {} - - inline DistanceType evalMetric(const T *a, const size_t b_idx, size_t size, - DistanceType worst_dist = -1) const { - DistanceType result = DistanceType(); - const T *last = a + size; - const T *lastgroup = last - 3; - size_t d = 0; - - /* Process 4 items with each loop for efficiency. */ - while (a < lastgroup) { - const DistanceType diff0 = a[0] - data_source.kdtree_get_pt(b_idx, d++); - const DistanceType diff1 = a[1] - data_source.kdtree_get_pt(b_idx, d++); - const DistanceType diff2 = a[2] - data_source.kdtree_get_pt(b_idx, d++); - const DistanceType diff3 = a[3] - data_source.kdtree_get_pt(b_idx, d++); - result += diff0 * diff0 + diff1 * diff1 + diff2 * diff2 + diff3 * diff3; - a += 4; - if ((worst_dist > 0) && (result > worst_dist)) { - return result; - } - } - /* Process last 0-3 components. Not needed for standard vector lengths. */ - while (a < last) { - const DistanceType diff0 = *a++ - data_source.kdtree_get_pt(b_idx, d++); - result += diff0 * diff0; - } - return result; - } - - template - inline DistanceType accum_dist(const U a, const V b, const size_t) const { - return (a - b) * (a - b); - } -}; - -/** Squared Euclidean (L2) distance functor (suitable for low-dimensionality - * datasets, like 2D or 3D point clouds) Corresponding distance traits: - * nanoflann::metric_L2_Simple \tparam T Type of the elements (e.g. double, - * float, uint8_t) \tparam _DistanceType Type of distance variables (must be - * signed) (e.g. float, double, int64_t) - */ -template -struct L2_Simple_Adaptor { - typedef T ElementType; - typedef _DistanceType DistanceType; - - const DataSource &data_source; - - L2_Simple_Adaptor(const DataSource &_data_source) - : data_source(_data_source) {} - - inline DistanceType evalMetric(const T *a, const size_t b_idx, - size_t size) const { - DistanceType result = DistanceType(); - for (size_t i = 0; i < size; ++i) { - const DistanceType diff = a[i] - data_source.kdtree_get_pt(b_idx, i); - result += diff * diff; - } - return result; - } - - template - inline DistanceType accum_dist(const U a, const V b, const size_t) const { - return (a - b) * (a - b); - } -}; - -/** SO2 distance functor - * Corresponding distance traits: nanoflann::metric_SO2 - * \tparam T Type of the elements (e.g. double, float) - * \tparam _DistanceType Type of distance variables (must be signed) (e.g. - * float, double) orientation is constrained to be in [-pi, pi] - */ -template -struct SO2_Adaptor { - typedef T ElementType; - typedef _DistanceType DistanceType; - - const DataSource &data_source; - - SO2_Adaptor(const DataSource &_data_source) : data_source(_data_source) {} - - inline DistanceType evalMetric(const T *a, const size_t b_idx, - size_t size) const { - return accum_dist(a[size - 1], data_source.kdtree_get_pt(b_idx, size - 1), - size - 1); - } - - /** Note: this assumes that input angles are already in the range [-pi,pi] */ - template - inline DistanceType accum_dist(const U a, const V b, const size_t) const { - DistanceType result = DistanceType(); - DistanceType PI = pi_const(); - result = b - a; - if (result > PI) - result -= 2 * PI; - else if (result < -PI) - result += 2 * PI; - return result; - } -}; - -/** SO3 distance functor (Uses L2_Simple) - * Corresponding distance traits: nanoflann::metric_SO3 - * \tparam T Type of the elements (e.g. double, float) - * \tparam _DistanceType Type of distance variables (must be signed) (e.g. - * float, double) - */ -template -struct SO3_Adaptor { - typedef T ElementType; - typedef _DistanceType DistanceType; - - L2_Simple_Adaptor distance_L2_Simple; - - SO3_Adaptor(const DataSource &_data_source) - : distance_L2_Simple(_data_source) {} - - inline DistanceType evalMetric(const T *a, const size_t b_idx, - size_t size) const { - return distance_L2_Simple.evalMetric(a, b_idx, size); - } - - template - inline DistanceType accum_dist(const U a, const V b, const size_t idx) const { - return distance_L2_Simple.accum_dist(a, b, idx); - } -}; - -/** Metaprogramming helper traits class for the L1 (Manhattan) metric */ -struct metric_L1 : public Metric { - template struct traits { - typedef L1_Adaptor distance_t; - }; -}; -/** Metaprogramming helper traits class for the L2 (Euclidean) metric */ -struct metric_L2 : public Metric { - template struct traits { - typedef L2_Adaptor distance_t; - }; -}; -/** Metaprogramming helper traits class for the L2_simple (Euclidean) metric */ -struct metric_L2_Simple : public Metric { - template struct traits { - typedef L2_Simple_Adaptor distance_t; - }; -}; -/** Metaprogramming helper traits class for the SO3_InnerProdQuat metric */ -struct metric_SO2 : public Metric { - template struct traits { - typedef SO2_Adaptor distance_t; - }; -}; -/** Metaprogramming helper traits class for the SO3_InnerProdQuat metric */ -struct metric_SO3 : public Metric { - template struct traits { - typedef SO3_Adaptor distance_t; - }; -}; - -/** @} */ - -/** @addtogroup param_grp Parameter structs - * @{ */ - -/** Parameters (see README.md) */ -struct KDTreeSingleIndexAdaptorParams { - KDTreeSingleIndexAdaptorParams(size_t _leaf_max_size = 10) - : leaf_max_size(_leaf_max_size) {} - - size_t leaf_max_size; -}; - -/** Search options for KDTreeSingleIndexAdaptor::findNeighbors() */ -struct SearchParams { - /** Note: The first argument (checks_IGNORED_) is ignored, but kept for - * compatibility with the FLANN interface */ - SearchParams(int checks_IGNORED_ = 32, float eps_ = 0, bool sorted_ = true) - : checks(checks_IGNORED_), eps(eps_), sorted(sorted_) {} - - int checks; //!< Ignored parameter (Kept for compatibility with the FLANN - //!< interface). - float eps; //!< search for eps-approximate neighbours (default: 0) - bool sorted; //!< only for radius search, require neighbours sorted by - //!< distance (default: true) -}; -/** @} */ - -/** @addtogroup memalloc_grp Memory allocation - * @{ */ - -/** - * Allocates (using C's malloc) a generic type T. - * - * Params: - * count = number of instances to allocate. - * Returns: pointer (of type T*) to memory buffer - */ -template inline T *allocate(size_t count = 1) { - T *mem = static_cast(::malloc(sizeof(T) * count)); - return mem; -} - -/** - * Pooled storage allocator - * - * The following routines allow for the efficient allocation of storage in - * small chunks from a specified pool. Rather than allowing each structure - * to be freed individually, an entire pool of storage is freed at once. - * This method has two advantages over just using malloc() and free(). First, - * it is far more efficient for allocating small objects, as there is - * no overhead for remembering all the information needed to free each - * object or consolidating fragmented memory. Second, the decision about - * how long to keep an object is made at the time of allocation, and there - * is no need to track down all the objects to free them. - * - */ - -const size_t WORDSIZE = 16; -const size_t BLOCKSIZE = 8192; - -class PooledAllocator { - /* We maintain memory alignment to word boundaries by requiring that all - allocations be in multiples of the machine wordsize. */ - /* Size of machine word in bytes. Must be power of 2. */ - /* Minimum number of bytes requested at a time from the system. Must be - * multiple of WORDSIZE. */ - - size_t remaining; /* Number of bytes left in current block of storage. */ - void *base; /* Pointer to base of current block of storage. */ - void *loc; /* Current location in block to next allocate memory. */ - - void internal_init() { - remaining = 0; - base = NULL; - usedMemory = 0; - wastedMemory = 0; - } - -public: - size_t usedMemory; - size_t wastedMemory; - - /** - Default constructor. Initializes a new pool. - */ - PooledAllocator() { internal_init(); } - - /** - * Destructor. Frees all the memory allocated in this pool. - */ - ~PooledAllocator() { free_all(); } - - /** Frees all allocated memory chunks */ - void free_all() { - while (base != NULL) { - void *prev = - *(static_cast(base)); /* Get pointer to prev block. */ - ::free(base); - base = prev; - } - internal_init(); - } - - /** - * Returns a pointer to a piece of new memory of the given size in bytes - * allocated from the pool. - */ - void *malloc(const size_t req_size) { - /* Round size up to a multiple of wordsize. The following expression - only works for WORDSIZE that is a power of 2, by masking last bits of - incremented size to zero. - */ - const size_t size = (req_size + (WORDSIZE - 1)) & ~(WORDSIZE - 1); - - /* Check whether a new block must be allocated. Note that the first word - of a block is reserved for a pointer to the previous block. - */ - if (size > remaining) { - - wastedMemory += remaining; - - /* Allocate new storage. */ - const size_t blocksize = - (size + sizeof(void *) + (WORDSIZE - 1) > BLOCKSIZE) - ? size + sizeof(void *) + (WORDSIZE - 1) - : BLOCKSIZE; - - // use the standard C malloc to allocate memory - void *m = ::malloc(blocksize); - if (!m) { - fprintf(stderr, "Failed to allocate memory.\n"); - throw std::bad_alloc(); - } - - /* Fill first word of new block with pointer to previous block. */ - static_cast(m)[0] = base; - base = m; - - size_t shift = 0; - // int size_t = (WORDSIZE - ( (((size_t)m) + sizeof(void*)) & - // (WORDSIZE-1))) & (WORDSIZE-1); - - remaining = blocksize - sizeof(void *) - shift; - loc = (static_cast(m) + sizeof(void *) + shift); - } - void *rloc = loc; - loc = static_cast(loc) + size; - remaining -= size; - - usedMemory += size; - - return rloc; - } - - /** - * Allocates (using this pool) a generic type T. - * - * Params: - * count = number of instances to allocate. - * Returns: pointer (of type T*) to memory buffer - */ - template T *allocate(const size_t count = 1) { - T *mem = static_cast(this->malloc(sizeof(T) * count)); - return mem; - } -}; -/** @} */ - -/** @addtogroup nanoflann_metaprog_grp Auxiliary metaprogramming stuff - * @{ */ - -/** Used to declare fixed-size arrays when DIM>0, dynamically-allocated vectors - * when DIM=-1. Fixed size version for a generic DIM: - */ -template struct array_or_vector_selector { - typedef std::array container_t; -}; -/** Dynamic size version */ -template struct array_or_vector_selector<-1, T> { - typedef std::vector container_t; -}; - -/** @} */ - -/** kd-tree base-class - * - * Contains the member functions common to the classes KDTreeSingleIndexAdaptor - * and KDTreeSingleIndexDynamicAdaptor_. - * - * \tparam Derived The name of the class which inherits this class. - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use, these are all classes derived - * from nanoflann::Metric \tparam DIM Dimensionality of data points (e.g. 3 for - * 3D points) \tparam IndexType Will be typically size_t or int - */ - -template -class KDTreeBaseClass { - -public: - /** Frees the previously-built index. Automatically called within - * buildIndex(). */ - void freeIndex(Derived &obj) { - obj.pool.free_all(); - obj.root_node = NULL; - obj.m_size_at_index_build = 0; - } - - typedef typename Distance::ElementType ElementType; - typedef typename Distance::DistanceType DistanceType; - - /*--------------------- Internal Data Structures --------------------------*/ - struct Node { - /** Union used because a node can be either a LEAF node or a non-leaf node, - * so both data fields are never used simultaneously */ - union { - struct leaf { - IndexType left, right; //!< Indices of points in leaf node - } lr; - struct nonleaf { - int divfeat; //!< Dimension used for subdivision. - DistanceType divlow, divhigh; //!< The values used for subdivision. - } sub; - } node_type; - Node *child1, *child2; //!< Child nodes (both=NULL mean its a leaf node) - }; - - typedef Node *NodePtr; - - struct Interval { - ElementType low, high; - }; - - /** - * Array of indices to vectors in the dataset. - */ - std::vector vind; - - NodePtr root_node; - - size_t m_leaf_max_size; - - size_t m_size; //!< Number of current points in the dataset - size_t m_size_at_index_build; //!< Number of points in the dataset when the - //!< index was built - int dim; //!< Dimensionality of each data point - - /** Define "BoundingBox" as a fixed-size or variable-size container depending - * on "DIM" */ - typedef - typename array_or_vector_selector::container_t BoundingBox; - - /** Define "distance_vector_t" as a fixed-size or variable-size container - * depending on "DIM" */ - typedef typename array_or_vector_selector::container_t - distance_vector_t; - - /** The KD-tree used to find neighbours */ - - BoundingBox root_bbox; - - /** - * Pooled memory allocator. - * - * Using a pooled memory allocator is more efficient - * than allocating memory directly when there is a large - * number small of memory allocations. - */ - PooledAllocator pool; - - /** Returns number of points in dataset */ - size_t size(const Derived &obj) const { return obj.m_size; } - - /** Returns the length of each point in the dataset */ - size_t veclen(const Derived &obj) { - return static_cast(DIM > 0 ? DIM : obj.dim); - } - - /// Helper accessor to the dataset points: - inline ElementType dataset_get(const Derived &obj, size_t idx, - int component) const { - return obj.dataset.kdtree_get_pt(idx, component); - } - - /** - * Computes the inde memory usage - * Returns: memory used by the index - */ - size_t usedMemory(Derived &obj) { - return obj.pool.usedMemory + obj.pool.wastedMemory + - obj.dataset.kdtree_get_point_count() * - sizeof(IndexType); // pool memory and vind array memory - } - - void computeMinMax(const Derived &obj, IndexType *ind, IndexType count, - int element, ElementType &min_elem, - ElementType &max_elem) { - min_elem = dataset_get(obj, ind[0], element); - max_elem = dataset_get(obj, ind[0], element); - for (IndexType i = 1; i < count; ++i) { - ElementType val = dataset_get(obj, ind[i], element); - if (val < min_elem) - min_elem = val; - if (val > max_elem) - max_elem = val; - } - } - - /** - * Create a tree node that subdivides the list of vecs from vind[first] - * to vind[last]. The routine is called recursively on each sublist. - * - * @param left index of the first vector - * @param right index of the last vector - */ - NodePtr divideTree(Derived &obj, const IndexType left, const IndexType right, - BoundingBox &bbox) { - NodePtr node = obj.pool.template allocate(); // allocate memory - - /* If too few exemplars remain, then make this a leaf node. */ - if ((right - left) <= static_cast(obj.m_leaf_max_size)) { - node->child1 = node->child2 = NULL; /* Mark as leaf node. */ - node->node_type.lr.left = left; - node->node_type.lr.right = right; - - // compute bounding-box of leaf points - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - bbox[i].low = dataset_get(obj, obj.vind[left], i); - bbox[i].high = dataset_get(obj, obj.vind[left], i); - } - for (IndexType k = left + 1; k < right; ++k) { - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - if (bbox[i].low > dataset_get(obj, obj.vind[k], i)) - bbox[i].low = dataset_get(obj, obj.vind[k], i); - if (bbox[i].high < dataset_get(obj, obj.vind[k], i)) - bbox[i].high = dataset_get(obj, obj.vind[k], i); - } - } - } else { - IndexType idx; - int cutfeat; - DistanceType cutval; - middleSplit_(obj, &obj.vind[0] + left, right - left, idx, cutfeat, cutval, - bbox); - - node->node_type.sub.divfeat = cutfeat; - - BoundingBox left_bbox(bbox); - left_bbox[cutfeat].high = cutval; - node->child1 = divideTree(obj, left, left + idx, left_bbox); - - BoundingBox right_bbox(bbox); - right_bbox[cutfeat].low = cutval; - node->child2 = divideTree(obj, left + idx, right, right_bbox); - - node->node_type.sub.divlow = left_bbox[cutfeat].high; - node->node_type.sub.divhigh = right_bbox[cutfeat].low; - - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - bbox[i].low = std::min(left_bbox[i].low, right_bbox[i].low); - bbox[i].high = std::max(left_bbox[i].high, right_bbox[i].high); - } - } - - return node; - } - - void middleSplit_(Derived &obj, IndexType *ind, IndexType count, - IndexType &index, int &cutfeat, DistanceType &cutval, - const BoundingBox &bbox) { - const DistanceType EPS = static_cast(0.00001); - ElementType max_span = bbox[0].high - bbox[0].low; - for (int i = 1; i < (DIM > 0 ? DIM : obj.dim); ++i) { - ElementType span = bbox[i].high - bbox[i].low; - if (span > max_span) { - max_span = span; - } - } - ElementType max_spread = -1; - cutfeat = 0; - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - ElementType span = bbox[i].high - bbox[i].low; - if (span > (1 - EPS) * max_span) { - ElementType min_elem, max_elem; - computeMinMax(obj, ind, count, i, min_elem, max_elem); - ElementType spread = max_elem - min_elem; - if (spread > max_spread) { - cutfeat = i; - max_spread = spread; - } - } - } - // split in the middle - DistanceType split_val = (bbox[cutfeat].low + bbox[cutfeat].high) / 2; - ElementType min_elem, max_elem; - computeMinMax(obj, ind, count, cutfeat, min_elem, max_elem); - - if (split_val < min_elem) - cutval = min_elem; - else if (split_val > max_elem) - cutval = max_elem; - else - cutval = split_val; - - IndexType lim1, lim2; - planeSplit(obj, ind, count, cutfeat, cutval, lim1, lim2); - - if (lim1 > count / 2) - index = lim1; - else if (lim2 < count / 2) - index = lim2; - else - index = count / 2; - } - - /** - * Subdivide the list of points by a plane perpendicular on axe corresponding - * to the 'cutfeat' dimension at 'cutval' position. - * - * On return: - * dataset[ind[0..lim1-1]][cutfeat]cutval - */ - void planeSplit(Derived &obj, IndexType *ind, const IndexType count, - int cutfeat, DistanceType &cutval, IndexType &lim1, - IndexType &lim2) { - /* Move vector indices for left subtree to front of list. */ - IndexType left = 0; - IndexType right = count - 1; - for (;;) { - while (left <= right && dataset_get(obj, ind[left], cutfeat) < cutval) - ++left; - while (right && left <= right && - dataset_get(obj, ind[right], cutfeat) >= cutval) - --right; - if (left > right || !right) - break; // "!right" was added to support unsigned Index types - std::swap(ind[left], ind[right]); - ++left; - --right; - } - /* If either list is empty, it means that all remaining features - * are identical. Split in the middle to maintain a balanced tree. - */ - lim1 = left; - right = count - 1; - for (;;) { - while (left <= right && dataset_get(obj, ind[left], cutfeat) <= cutval) - ++left; - while (right && left <= right && - dataset_get(obj, ind[right], cutfeat) > cutval) - --right; - if (left > right || !right) - break; // "!right" was added to support unsigned Index types - std::swap(ind[left], ind[right]); - ++left; - --right; - } - lim2 = left; - } - - DistanceType computeInitialDistances(const Derived &obj, - const ElementType *vec, - distance_vector_t &dists) const { - assert(vec); - DistanceType distsq = DistanceType(); - - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - if (vec[i] < obj.root_bbox[i].low) { - dists[i] = obj.distance.accum_dist(vec[i], obj.root_bbox[i].low, i); - distsq += dists[i]; - } - if (vec[i] > obj.root_bbox[i].high) { - dists[i] = obj.distance.accum_dist(vec[i], obj.root_bbox[i].high, i); - distsq += dists[i]; - } - } - return distsq; - } - - void save_tree(Derived &obj, FILE *stream, NodePtr tree) { - save_value(stream, *tree); - if (tree->child1 != NULL) { - save_tree(obj, stream, tree->child1); - } - if (tree->child2 != NULL) { - save_tree(obj, stream, tree->child2); - } - } - - void load_tree(Derived &obj, FILE *stream, NodePtr &tree) { - tree = obj.pool.template allocate(); - load_value(stream, *tree); - if (tree->child1 != NULL) { - load_tree(obj, stream, tree->child1); - } - if (tree->child2 != NULL) { - load_tree(obj, stream, tree->child2); - } - } - - /** Stores the index in a binary file. - * IMPORTANT NOTE: The set of data points is NOT stored in the file, so when - * loading the index object it must be constructed associated to the same - * source of data points used while building it. See the example: - * examples/saveload_example.cpp \sa loadIndex */ - void saveIndex_(Derived &obj, FILE *stream) { - save_value(stream, obj.m_size); - save_value(stream, obj.dim); - save_value(stream, obj.root_bbox); - save_value(stream, obj.m_leaf_max_size); - save_value(stream, obj.vind); - save_tree(obj, stream, obj.root_node); - } - - /** Loads a previous index from a binary file. - * IMPORTANT NOTE: The set of data points is NOT stored in the file, so the - * index object must be constructed associated to the same source of data - * points used while building the index. See the example: - * examples/saveload_example.cpp \sa loadIndex */ - void loadIndex_(Derived &obj, FILE *stream) { - load_value(stream, obj.m_size); - load_value(stream, obj.dim); - load_value(stream, obj.root_bbox); - load_value(stream, obj.m_leaf_max_size); - load_value(stream, obj.vind); - load_tree(obj, stream, obj.root_node); - } -}; - -/** @addtogroup kdtrees_grp KD-tree classes and adaptors - * @{ */ - -/** kd-tree static index - * - * Contains the k-d trees and other information for indexing a set of points - * for nearest-neighbor matching. - * - * The class "DatasetAdaptor" must provide the following interface (can be - * non-virtual, inlined methods): - * - * \code - * // Must return the number of data poins - * inline size_t kdtree_get_point_count() const { ... } - * - * - * // Must return the dim'th component of the idx'th point in the class: - * inline T kdtree_get_pt(const size_t idx, const size_t dim) const { ... } - * - * // Optional bounding-box computation: return false to default to a standard - * bbox computation loop. - * // Return true if the BBOX was already computed by the class and returned - * in "bb" so it can be avoided to redo it again. - * // Look at bb.size() to find out the expected dimensionality (e.g. 2 or 3 - * for point clouds) template bool kdtree_get_bbox(BBOX &bb) const - * { - * bb[0].low = ...; bb[0].high = ...; // 0th dimension limits - * bb[1].low = ...; bb[1].high = ...; // 1st dimension limits - * ... - * return true; - * } - * - * \endcode - * - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use: nanoflann::metric_L1, - * nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc. \tparam DIM - * Dimensionality of data points (e.g. 3 for 3D points) \tparam IndexType Will - * be typically size_t or int - */ -template -class KDTreeSingleIndexAdaptor - : public KDTreeBaseClass< - KDTreeSingleIndexAdaptor, - Distance, DatasetAdaptor, DIM, IndexType> { -public: - /** Deleted copy constructor*/ - KDTreeSingleIndexAdaptor( - const KDTreeSingleIndexAdaptor - &) = delete; - - /** - * The dataset used by this index - */ - const DatasetAdaptor &dataset; //!< The source of our data - - const KDTreeSingleIndexAdaptorParams index_params; - - Distance distance; - - typedef typename nanoflann::KDTreeBaseClass< - nanoflann::KDTreeSingleIndexAdaptor, - Distance, DatasetAdaptor, DIM, IndexType> - BaseClassRef; - - typedef typename BaseClassRef::ElementType ElementType; - typedef typename BaseClassRef::DistanceType DistanceType; - - typedef typename BaseClassRef::Node Node; - typedef Node *NodePtr; - - typedef typename BaseClassRef::Interval Interval; - /** Define "BoundingBox" as a fixed-size or variable-size container depending - * on "DIM" */ - typedef typename BaseClassRef::BoundingBox BoundingBox; - - /** Define "distance_vector_t" as a fixed-size or variable-size container - * depending on "DIM" */ - typedef typename BaseClassRef::distance_vector_t distance_vector_t; - - /** - * KDTree constructor - * - * Refer to docs in README.md or online in - * https://github.com/jlblancoc/nanoflann - * - * The KD-Tree point dimension (the length of each point in the datase, e.g. 3 - * for 3D points) is determined by means of: - * - The \a DIM template parameter if >0 (highest priority) - * - Otherwise, the \a dimensionality parameter of this constructor. - * - * @param inputData Dataset with the input features - * @param params Basically, the maximum leaf node size - */ - KDTreeSingleIndexAdaptor(const int dimensionality, - const DatasetAdaptor &inputData, - const KDTreeSingleIndexAdaptorParams ¶ms = - KDTreeSingleIndexAdaptorParams()) - : dataset(inputData), index_params(params), distance(inputData) { - BaseClassRef::root_node = NULL; - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - BaseClassRef::dim = dimensionality; - if (DIM > 0) - BaseClassRef::dim = DIM; - BaseClassRef::m_leaf_max_size = params.leaf_max_size; - - // Create a permutable array of indices to the input vectors. - init_vind(); - } - - /** - * Builds the index - */ - void buildIndex() { - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - init_vind(); - this->freeIndex(*this); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - if (BaseClassRef::m_size == 0) - return; - computeBoundingBox(BaseClassRef::root_bbox); - BaseClassRef::root_node = - this->divideTree(*this, 0, BaseClassRef::m_size, - BaseClassRef::root_bbox); // construct the tree - } - - /** \name Query methods - * @{ */ - - /** - * Find set of nearest neighbors to vec[0:dim-1]. Their indices are stored - * inside the result object. - * - * Params: - * result = the result object in which the indices of the - * nearest-neighbors are stored vec = the vector for which to search the - * nearest neighbors - * - * \tparam RESULTSET Should be any ResultSet - * \return True if the requested neighbors could be found. - * \sa knnSearch, radiusSearch - */ - template - bool findNeighbors(RESULTSET &result, const ElementType *vec, - const SearchParams &searchParams) const { - assert(vec); - if (this->size(*this) == 0) - return false; - if (!BaseClassRef::root_node) - throw std::runtime_error( - "[nanoflann] findNeighbors() called before building the index."); - float epsError = 1 + searchParams.eps; - - distance_vector_t - dists; // fixed or variable-sized container (depending on DIM) - auto zero = static_cast(0); - assign(dists, (DIM > 0 ? DIM : BaseClassRef::dim), - zero); // Fill it with zeros. - DistanceType distsq = this->computeInitialDistances(*this, vec, dists); - searchLevel(result, vec, BaseClassRef::root_node, distsq, dists, - epsError); // "count_leaf" parameter removed since was neither - // used nor returned to the user. - return result.full(); - } - - /** - * Find the "num_closest" nearest neighbors to the \a query_point[0:dim-1]. - * Their indices are stored inside the result object. \sa radiusSearch, - * findNeighbors \note nChecks_IGNORED is ignored but kept for compatibility - * with the original FLANN interface. \return Number `N` of valid points in - * the result set. Only the first `N` entries in `out_indices` and - * `out_distances_sq` will be valid. Return may be less than `num_closest` - * only if the number of elements in the tree is less than `num_closest`. - */ - size_t knnSearch(const ElementType *query_point, const size_t num_closest, - IndexType *out_indices, DistanceType *out_distances_sq, - const int /* nChecks_IGNORED */ = 10) const { - nanoflann::KNNResultSet resultSet(num_closest); - resultSet.init(out_indices, out_distances_sq); - this->findNeighbors(resultSet, query_point, nanoflann::SearchParams()); - return resultSet.size(); - } - - /** - * Find all the neighbors to \a query_point[0:dim-1] within a maximum radius. - * The output is given as a vector of pairs, of which the first element is a - * point index and the second the corresponding distance. Previous contents of - * \a IndicesDists are cleared. - * - * If searchParams.sorted==true, the output list is sorted by ascending - * distances. - * - * For a better performance, it is advisable to do a .reserve() on the vector - * if you have any wild guess about the number of expected matches. - * - * \sa knnSearch, findNeighbors, radiusSearchCustomCallback - * \return The number of points within the given radius (i.e. indices.size() - * or dists.size() ) - */ - size_t - radiusSearch(const ElementType *query_point, const DistanceType &radius, - std::vector> &IndicesDists, - const SearchParams &searchParams) const { - RadiusResultSet resultSet(radius, IndicesDists); - const size_t nFound = - radiusSearchCustomCallback(query_point, resultSet, searchParams); - if (searchParams.sorted) - std::sort(IndicesDists.begin(), IndicesDists.end(), IndexDist_Sorter()); - return nFound; - } - - /** - * Just like radiusSearch() but with a custom callback class for each point - * found in the radius of the query. See the source of RadiusResultSet<> as a - * start point for your own classes. \sa radiusSearch - */ - template - size_t radiusSearchCustomCallback( - const ElementType *query_point, SEARCH_CALLBACK &resultSet, - const SearchParams &searchParams = SearchParams()) const { - this->findNeighbors(resultSet, query_point, searchParams); - return resultSet.size(); - } - - /** @} */ - -public: - /** Make sure the auxiliary list \a vind has the same size than the current - * dataset, and re-generate if size has changed. */ - void init_vind() { - // Create a permutable array of indices to the input vectors. - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - if (BaseClassRef::vind.size() != BaseClassRef::m_size) - BaseClassRef::vind.resize(BaseClassRef::m_size); - for (size_t i = 0; i < BaseClassRef::m_size; i++) - BaseClassRef::vind[i] = i; - } - - void computeBoundingBox(BoundingBox &bbox) { - resize(bbox, (DIM > 0 ? DIM : BaseClassRef::dim)); - if (dataset.kdtree_get_bbox(bbox)) { - // Done! It was implemented in derived class - } else { - const size_t N = dataset.kdtree_get_point_count(); - if (!N) - throw std::runtime_error("[nanoflann] computeBoundingBox() called but " - "no data points found."); - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - bbox[i].low = bbox[i].high = this->dataset_get(*this, 0, i); - } - for (size_t k = 1; k < N; ++k) { - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - if (this->dataset_get(*this, k, i) < bbox[i].low) - bbox[i].low = this->dataset_get(*this, k, i); - if (this->dataset_get(*this, k, i) > bbox[i].high) - bbox[i].high = this->dataset_get(*this, k, i); - } - } - } - } - - /** - * Performs an exact search in the tree starting from a node. - * \tparam RESULTSET Should be any ResultSet - * \return true if the search should be continued, false if the results are - * sufficient - */ - template - bool searchLevel(RESULTSET &result_set, const ElementType *vec, - const NodePtr node, DistanceType mindistsq, - distance_vector_t &dists, const float epsError) const { - /* If this is a leaf node, then do check and return. */ - if ((node->child1 == NULL) && (node->child2 == NULL)) { - // count_leaf += (node->lr.right-node->lr.left); // Removed since was - // neither used nor returned to the user. - DistanceType worst_dist = result_set.worstDist(); - for (IndexType i = node->node_type.lr.left; i < node->node_type.lr.right; - ++i) { - const IndexType index = BaseClassRef::vind[i]; // reorder... : i; - DistanceType dist = distance.evalMetric( - vec, index, (DIM > 0 ? DIM : BaseClassRef::dim)); - if (dist < worst_dist) { - if (!result_set.addPoint(dist, BaseClassRef::vind[i])) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - } - } - return true; - } - - /* Which child branch should be taken first? */ - int idx = node->node_type.sub.divfeat; - ElementType val = vec[idx]; - DistanceType diff1 = val - node->node_type.sub.divlow; - DistanceType diff2 = val - node->node_type.sub.divhigh; - - NodePtr bestChild; - NodePtr otherChild; - DistanceType cut_dist; - if ((diff1 + diff2) < 0) { - bestChild = node->child1; - otherChild = node->child2; - cut_dist = distance.accum_dist(val, node->node_type.sub.divhigh, idx); - } else { - bestChild = node->child2; - otherChild = node->child1; - cut_dist = distance.accum_dist(val, node->node_type.sub.divlow, idx); - } - - /* Call recursively to search next level down. */ - if (!searchLevel(result_set, vec, bestChild, mindistsq, dists, epsError)) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - - DistanceType dst = dists[idx]; - mindistsq = mindistsq + cut_dist - dst; - dists[idx] = cut_dist; - if (mindistsq * epsError <= result_set.worstDist()) { - if (!searchLevel(result_set, vec, otherChild, mindistsq, dists, - epsError)) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - } - dists[idx] = dst; - return true; - } - -public: - /** Stores the index in a binary file. - * IMPORTANT NOTE: The set of data points is NOT stored in the file, so when - * loading the index object it must be constructed associated to the same - * source of data points used while building it. See the example: - * examples/saveload_example.cpp \sa loadIndex */ - void saveIndex(FILE *stream) { this->saveIndex_(*this, stream); } - - /** Loads a previous index from a binary file. - * IMPORTANT NOTE: The set of data points is NOT stored in the file, so the - * index object must be constructed associated to the same source of data - * points used while building the index. See the example: - * examples/saveload_example.cpp \sa loadIndex */ - void loadIndex(FILE *stream) { this->loadIndex_(*this, stream); } - -}; // class KDTree - -/** kd-tree dynamic index - * - * Contains the k-d trees and other information for indexing a set of points - * for nearest-neighbor matching. - * - * The class "DatasetAdaptor" must provide the following interface (can be - * non-virtual, inlined methods): - * - * \code - * // Must return the number of data poins - * inline size_t kdtree_get_point_count() const { ... } - * - * // Must return the dim'th component of the idx'th point in the class: - * inline T kdtree_get_pt(const size_t idx, const size_t dim) const { ... } - * - * // Optional bounding-box computation: return false to default to a standard - * bbox computation loop. - * // Return true if the BBOX was already computed by the class and returned - * in "bb" so it can be avoided to redo it again. - * // Look at bb.size() to find out the expected dimensionality (e.g. 2 or 3 - * for point clouds) template bool kdtree_get_bbox(BBOX &bb) const - * { - * bb[0].low = ...; bb[0].high = ...; // 0th dimension limits - * bb[1].low = ...; bb[1].high = ...; // 1st dimension limits - * ... - * return true; - * } - * - * \endcode - * - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use: nanoflann::metric_L1, - * nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc. \tparam DIM - * Dimensionality of data points (e.g. 3 for 3D points) \tparam IndexType Will - * be typically size_t or int - */ -template -class KDTreeSingleIndexDynamicAdaptor_ - : public KDTreeBaseClass, - Distance, DatasetAdaptor, DIM, IndexType> { -public: - /** - * The dataset used by this index - */ - const DatasetAdaptor &dataset; //!< The source of our data - - KDTreeSingleIndexAdaptorParams index_params; - - std::vector &treeIndex; - - Distance distance; - - typedef typename nanoflann::KDTreeBaseClass< - nanoflann::KDTreeSingleIndexDynamicAdaptor_, - Distance, DatasetAdaptor, DIM, IndexType> - BaseClassRef; - - typedef typename BaseClassRef::ElementType ElementType; - typedef typename BaseClassRef::DistanceType DistanceType; - - typedef typename BaseClassRef::Node Node; - typedef Node *NodePtr; - - typedef typename BaseClassRef::Interval Interval; - /** Define "BoundingBox" as a fixed-size or variable-size container depending - * on "DIM" */ - typedef typename BaseClassRef::BoundingBox BoundingBox; - - /** Define "distance_vector_t" as a fixed-size or variable-size container - * depending on "DIM" */ - typedef typename BaseClassRef::distance_vector_t distance_vector_t; - - /** - * KDTree constructor - * - * Refer to docs in README.md or online in - * https://github.com/jlblancoc/nanoflann - * - * The KD-Tree point dimension (the length of each point in the datase, e.g. 3 - * for 3D points) is determined by means of: - * - The \a DIM template parameter if >0 (highest priority) - * - Otherwise, the \a dimensionality parameter of this constructor. - * - * @param inputData Dataset with the input features - * @param params Basically, the maximum leaf node size - */ - KDTreeSingleIndexDynamicAdaptor_( - const int dimensionality, const DatasetAdaptor &inputData, - std::vector &treeIndex_, - const KDTreeSingleIndexAdaptorParams ¶ms = - KDTreeSingleIndexAdaptorParams()) - : dataset(inputData), index_params(params), treeIndex(treeIndex_), - distance(inputData) { - BaseClassRef::root_node = NULL; - BaseClassRef::m_size = 0; - BaseClassRef::m_size_at_index_build = 0; - BaseClassRef::dim = dimensionality; - if (DIM > 0) - BaseClassRef::dim = DIM; - BaseClassRef::m_leaf_max_size = params.leaf_max_size; - } - - /** Assignment operator definiton */ - KDTreeSingleIndexDynamicAdaptor_ - operator=(const KDTreeSingleIndexDynamicAdaptor_ &rhs) { - KDTreeSingleIndexDynamicAdaptor_ tmp(rhs); - std::swap(BaseClassRef::vind, tmp.BaseClassRef::vind); - std::swap(BaseClassRef::m_leaf_max_size, tmp.BaseClassRef::m_leaf_max_size); - std::swap(index_params, tmp.index_params); - std::swap(treeIndex, tmp.treeIndex); - std::swap(BaseClassRef::m_size, tmp.BaseClassRef::m_size); - std::swap(BaseClassRef::m_size_at_index_build, - tmp.BaseClassRef::m_size_at_index_build); - std::swap(BaseClassRef::root_node, tmp.BaseClassRef::root_node); - std::swap(BaseClassRef::root_bbox, tmp.BaseClassRef::root_bbox); - std::swap(BaseClassRef::pool, tmp.BaseClassRef::pool); - return *this; - } - - /** - * Builds the index - */ - void buildIndex() { - BaseClassRef::m_size = BaseClassRef::vind.size(); - this->freeIndex(*this); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - if (BaseClassRef::m_size == 0) - return; - computeBoundingBox(BaseClassRef::root_bbox); - BaseClassRef::root_node = - this->divideTree(*this, 0, BaseClassRef::m_size, - BaseClassRef::root_bbox); // construct the tree - } - - /** \name Query methods - * @{ */ - - /** - * Find set of nearest neighbors to vec[0:dim-1]. Their indices are stored - * inside the result object. - * - * Params: - * result = the result object in which the indices of the - * nearest-neighbors are stored vec = the vector for which to search the - * nearest neighbors - * - * \tparam RESULTSET Should be any ResultSet - * \return True if the requested neighbors could be found. - * \sa knnSearch, radiusSearch - */ - template - bool findNeighbors(RESULTSET &result, const ElementType *vec, - const SearchParams &searchParams) const { - assert(vec); - if (this->size(*this) == 0) - return false; - if (!BaseClassRef::root_node) - return false; - float epsError = 1 + searchParams.eps; - - // fixed or variable-sized container (depending on DIM) - distance_vector_t dists; - // Fill it with zeros. - assign(dists, (DIM > 0 ? DIM : BaseClassRef::dim), - static_cast(0)); - DistanceType distsq = this->computeInitialDistances(*this, vec, dists); - searchLevel(result, vec, BaseClassRef::root_node, distsq, dists, - epsError); // "count_leaf" parameter removed since was neither - // used nor returned to the user. - return result.full(); - } - - /** - * Find the "num_closest" nearest neighbors to the \a query_point[0:dim-1]. - * Their indices are stored inside the result object. \sa radiusSearch, - * findNeighbors \note nChecks_IGNORED is ignored but kept for compatibility - * with the original FLANN interface. \return Number `N` of valid points in - * the result set. Only the first `N` entries in `out_indices` and - * `out_distances_sq` will be valid. Return may be less than `num_closest` - * only if the number of elements in the tree is less than `num_closest`. - */ - size_t knnSearch(const ElementType *query_point, const size_t num_closest, - IndexType *out_indices, DistanceType *out_distances_sq, - const int /* nChecks_IGNORED */ = 10) const { - nanoflann::KNNResultSet resultSet(num_closest); - resultSet.init(out_indices, out_distances_sq); - this->findNeighbors(resultSet, query_point, nanoflann::SearchParams()); - return resultSet.size(); - } - - /** - * Find all the neighbors to \a query_point[0:dim-1] within a maximum radius. - * The output is given as a vector of pairs, of which the first element is a - * point index and the second the corresponding distance. Previous contents of - * \a IndicesDists are cleared. - * - * If searchParams.sorted==true, the output list is sorted by ascending - * distances. - * - * For a better performance, it is advisable to do a .reserve() on the vector - * if you have any wild guess about the number of expected matches. - * - * \sa knnSearch, findNeighbors, radiusSearchCustomCallback - * \return The number of points within the given radius (i.e. indices.size() - * or dists.size() ) - */ - size_t - radiusSearch(const ElementType *query_point, const DistanceType &radius, - std::vector> &IndicesDists, - const SearchParams &searchParams) const { - RadiusResultSet resultSet(radius, IndicesDists); - const size_t nFound = - radiusSearchCustomCallback(query_point, resultSet, searchParams); - if (searchParams.sorted) - std::sort(IndicesDists.begin(), IndicesDists.end(), IndexDist_Sorter()); - return nFound; - } - - /** - * Just like radiusSearch() but with a custom callback class for each point - * found in the radius of the query. See the source of RadiusResultSet<> as a - * start point for your own classes. \sa radiusSearch - */ - template - size_t radiusSearchCustomCallback( - const ElementType *query_point, SEARCH_CALLBACK &resultSet, - const SearchParams &searchParams = SearchParams()) const { - this->findNeighbors(resultSet, query_point, searchParams); - return resultSet.size(); - } - - /** @} */ - -public: - void computeBoundingBox(BoundingBox &bbox) { - resize(bbox, (DIM > 0 ? DIM : BaseClassRef::dim)); - - if (dataset.kdtree_get_bbox(bbox)) { - // Done! It was implemented in derived class - } else { - const size_t N = BaseClassRef::m_size; - if (!N) - throw std::runtime_error("[nanoflann] computeBoundingBox() called but " - "no data points found."); - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - bbox[i].low = bbox[i].high = - this->dataset_get(*this, BaseClassRef::vind[0], i); - } - for (size_t k = 1; k < N; ++k) { - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - if (this->dataset_get(*this, BaseClassRef::vind[k], i) < bbox[i].low) - bbox[i].low = this->dataset_get(*this, BaseClassRef::vind[k], i); - if (this->dataset_get(*this, BaseClassRef::vind[k], i) > bbox[i].high) - bbox[i].high = this->dataset_get(*this, BaseClassRef::vind[k], i); - } - } - } - } - - /** - * Performs an exact search in the tree starting from a node. - * \tparam RESULTSET Should be any ResultSet - */ - template - void searchLevel(RESULTSET &result_set, const ElementType *vec, - const NodePtr node, DistanceType mindistsq, - distance_vector_t &dists, const float epsError) const { - /* If this is a leaf node, then do check and return. */ - if ((node->child1 == NULL) && (node->child2 == NULL)) { - // count_leaf += (node->lr.right-node->lr.left); // Removed since was - // neither used nor returned to the user. - DistanceType worst_dist = result_set.worstDist(); - for (IndexType i = node->node_type.lr.left; i < node->node_type.lr.right; - ++i) { - const IndexType index = BaseClassRef::vind[i]; // reorder... : i; - if (treeIndex[index] == -1) - continue; - DistanceType dist = distance.evalMetric( - vec, index, (DIM > 0 ? DIM : BaseClassRef::dim)); - if (dist < worst_dist) { - if (!result_set.addPoint( - static_cast(dist), - static_cast( - BaseClassRef::vind[i]))) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return; // false; - } - } - } - return; - } - - /* Which child branch should be taken first? */ - int idx = node->node_type.sub.divfeat; - ElementType val = vec[idx]; - DistanceType diff1 = val - node->node_type.sub.divlow; - DistanceType diff2 = val - node->node_type.sub.divhigh; - - NodePtr bestChild; - NodePtr otherChild; - DistanceType cut_dist; - if ((diff1 + diff2) < 0) { - bestChild = node->child1; - otherChild = node->child2; - cut_dist = distance.accum_dist(val, node->node_type.sub.divhigh, idx); - } else { - bestChild = node->child2; - otherChild = node->child1; - cut_dist = distance.accum_dist(val, node->node_type.sub.divlow, idx); - } - - /* Call recursively to search next level down. */ - searchLevel(result_set, vec, bestChild, mindistsq, dists, epsError); - - DistanceType dst = dists[idx]; - mindistsq = mindistsq + cut_dist - dst; - dists[idx] = cut_dist; - if (mindistsq * epsError <= result_set.worstDist()) { - searchLevel(result_set, vec, otherChild, mindistsq, dists, epsError); - } - dists[idx] = dst; - } - -public: - /** Stores the index in a binary file. - * IMPORTANT NOTE: The set of data points is NOT stored in the file, so when - * loading the index object it must be constructed associated to the same - * source of data points used while building it. See the example: - * examples/saveload_example.cpp \sa loadIndex */ - void saveIndex(FILE *stream) { this->saveIndex_(*this, stream); } - - /** Loads a previous index from a binary file. - * IMPORTANT NOTE: The set of data points is NOT stored in the file, so the - * index object must be constructed associated to the same source of data - * points used while building the index. See the example: - * examples/saveload_example.cpp \sa loadIndex */ - void loadIndex(FILE *stream) { this->loadIndex_(*this, stream); } -}; - -/** kd-tree dynaimic index - * - * class to create multiple static index and merge their results to behave as - * single dynamic index as proposed in Logarithmic Approach. - * - * Example of usage: - * examples/dynamic_pointcloud_example.cpp - * - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use: nanoflann::metric_L1, - * nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc. \tparam DIM - * Dimensionality of data points (e.g. 3 for 3D points) \tparam IndexType Will - * be typically size_t or int - */ -template -class KDTreeSingleIndexDynamicAdaptor { -public: - typedef typename Distance::ElementType ElementType; - typedef typename Distance::DistanceType DistanceType; - -protected: - size_t m_leaf_max_size; - size_t treeCount; - size_t pointCount; - - /** - * The dataset used by this index - */ - const DatasetAdaptor &dataset; //!< The source of our data - - std::vector treeIndex; //!< treeIndex[idx] is the index of tree in which - //!< point at idx is stored. treeIndex[idx]=-1 - //!< means that point has been removed. - - KDTreeSingleIndexAdaptorParams index_params; - - int dim; //!< Dimensionality of each data point - - typedef KDTreeSingleIndexDynamicAdaptor_ - index_container_t; - std::vector index; - -public: - /** Get a const ref to the internal list of indices; the number of indices is - * adapted dynamically as the dataset grows in size. */ - const std::vector &getAllIndices() const { return index; } - -private: - /** finds position of least significant unset bit */ - int First0Bit(IndexType num) { - int pos = 0; - while (num & 1) { - num = num >> 1; - pos++; - } - return pos; - } - - /** Creates multiple empty trees to handle dynamic support */ - void init() { - typedef KDTreeSingleIndexDynamicAdaptor_ - my_kd_tree_t; - std::vector index_( - treeCount, my_kd_tree_t(dim /*dim*/, dataset, treeIndex, index_params)); - index = index_; - } - -public: - Distance distance; - - /** - * KDTree constructor - * - * Refer to docs in README.md or online in - * https://github.com/jlblancoc/nanoflann - * - * The KD-Tree point dimension (the length of each point in the datase, e.g. 3 - * for 3D points) is determined by means of: - * - The \a DIM template parameter if >0 (highest priority) - * - Otherwise, the \a dimensionality parameter of this constructor. - * - * @param inputData Dataset with the input features - * @param params Basically, the maximum leaf node size - */ - KDTreeSingleIndexDynamicAdaptor(const int dimensionality, - const DatasetAdaptor &inputData, - const KDTreeSingleIndexAdaptorParams ¶ms = - KDTreeSingleIndexAdaptorParams(), - const size_t maximumPointCount = 1000000000U) - : dataset(inputData), index_params(params), distance(inputData) { - treeCount = static_cast(std::log2(maximumPointCount)); - pointCount = 0U; - dim = dimensionality; - treeIndex.clear(); - if (DIM > 0) - dim = DIM; - m_leaf_max_size = params.leaf_max_size; - init(); - const size_t num_initial_points = dataset.kdtree_get_point_count(); - if (num_initial_points > 0) { - addPoints(0, num_initial_points - 1); - } - } - - /** Deleted copy constructor*/ - KDTreeSingleIndexDynamicAdaptor( - const KDTreeSingleIndexDynamicAdaptor &) = delete; - - /** Add points to the set, Inserts all points from [start, end] */ - void addPoints(IndexType start, IndexType end) { - size_t count = end - start + 1; - treeIndex.resize(treeIndex.size() + count); - for (IndexType idx = start; idx <= end; idx++) { - int pos = First0Bit(pointCount); - index[pos].vind.clear(); - treeIndex[pointCount] = pos; - for (int i = 0; i < pos; i++) { - for (int j = 0; j < static_cast(index[i].vind.size()); j++) { - index[pos].vind.push_back(index[i].vind[j]); - if (treeIndex[index[i].vind[j]] != -1) - treeIndex[index[i].vind[j]] = pos; - } - index[i].vind.clear(); - index[i].freeIndex(index[i]); - } - index[pos].vind.push_back(idx); - index[pos].buildIndex(); - pointCount++; - } - } - - /** Remove a point from the set (Lazy Deletion) */ - void removePoint(size_t idx) { - if (idx >= pointCount) - return; - treeIndex[idx] = -1; - } - - /** - * Find set of nearest neighbors to vec[0:dim-1]. Their indices are stored - * inside the result object. - * - * Params: - * result = the result object in which the indices of the - * nearest-neighbors are stored vec = the vector for which to search the - * nearest neighbors - * - * \tparam RESULTSET Should be any ResultSet - * \return True if the requested neighbors could be found. - * \sa knnSearch, radiusSearch - */ - template - bool findNeighbors(RESULTSET &result, const ElementType *vec, - const SearchParams &searchParams) const { - for (size_t i = 0; i < treeCount; i++) { - index[i].findNeighbors(result, &vec[0], searchParams); - } - return result.full(); - } -}; - -/** An L2-metric KD-tree adaptor for working with data directly stored in an - * Eigen Matrix, without duplicating the data storage. You can select whether a - * row or column in the matrix represents a point in the state space. - * - * Example of usage: - * \code - * Eigen::Matrix mat; - * // Fill out "mat"... - * - * typedef KDTreeEigenMatrixAdaptor< Eigen::Matrix > - * my_kd_tree_t; const int max_leaf = 10; my_kd_tree_t mat_index(mat, max_leaf - * ); mat_index.index->buildIndex(); mat_index.index->... \endcode - * - * \tparam DIM If set to >0, it specifies a compile-time fixed dimensionality - * for the points in the data set, allowing more compiler optimizations. \tparam - * Distance The distance metric to use: nanoflann::metric_L1, - * nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc. \tparam row_major - * If set to true the rows of the matrix are used as the points, if set to false - * the columns of the matrix are used as the points. - */ -template -struct KDTreeEigenMatrixAdaptor { - typedef KDTreeEigenMatrixAdaptor self_t; - typedef typename MatrixType::Scalar num_t; - typedef typename MatrixType::Index IndexType; - typedef - typename Distance::template traits::distance_t metric_t; - typedef KDTreeSingleIndexAdaptor - index_t; - - index_t *index; //! The kd-tree index for the user to call its methods as - //! usual with any other FLANN index. - - /// Constructor: takes a const ref to the matrix object with the data points - KDTreeEigenMatrixAdaptor(const size_t dimensionality, - const std::reference_wrapper &mat, - const int leaf_max_size = 10) - : m_data_matrix(mat) { - const auto dims = row_major ? mat.get().cols() : mat.get().rows(); - if (size_t(dims) != dimensionality) - throw std::runtime_error( - "Error: 'dimensionality' must match column count in data matrix"); - if (DIM > 0 && int(dims) != DIM) - throw std::runtime_error( - "Data set dimensionality does not match the 'DIM' template argument"); - index = - new index_t(static_cast(dims), *this /* adaptor */, - nanoflann::KDTreeSingleIndexAdaptorParams(leaf_max_size)); - index->buildIndex(); - } - -public: - /** Deleted copy constructor */ - KDTreeEigenMatrixAdaptor(const self_t &) = delete; - - ~KDTreeEigenMatrixAdaptor() { delete index; } - - const std::reference_wrapper m_data_matrix; - - /** Query for the \a num_closest closest points to a given point (entered as - * query_point[0:dim-1]). Note that this is a short-cut method for - * index->findNeighbors(). The user can also call index->... methods as - * desired. \note nChecks_IGNORED is ignored but kept for compatibility with - * the original FLANN interface. - */ - inline void query(const num_t *query_point, const size_t num_closest, - IndexType *out_indices, num_t *out_distances_sq, - const int /* nChecks_IGNORED */ = 10) const { - nanoflann::KNNResultSet resultSet(num_closest); - resultSet.init(out_indices, out_distances_sq); - index->findNeighbors(resultSet, query_point, nanoflann::SearchParams()); - } - - /** @name Interface expected by KDTreeSingleIndexAdaptor - * @{ */ - - const self_t &derived() const { return *this; } - self_t &derived() { return *this; } - - // Must return the number of data points - inline size_t kdtree_get_point_count() const { - if(row_major) - return m_data_matrix.get().rows(); - else - return m_data_matrix.get().cols(); - } - - // Returns the dim'th component of the idx'th point in the class: - inline num_t kdtree_get_pt(const IndexType idx, size_t dim) const { - if(row_major) - return m_data_matrix.get().coeff(idx, IndexType(dim)); - else - return m_data_matrix.get().coeff(IndexType(dim), idx); - } - - // Optional bounding-box computation: return false to default to a standard - // bbox computation loop. - // Return true if the BBOX was already computed by the class and returned in - // "bb" so it can be avoided to redo it again. Look at bb.size() to find out - // the expected dimensionality (e.g. 2 or 3 for point clouds) - template bool kdtree_get_bbox(BBOX & /*bb*/) const { - return false; - } - - /** @} */ - -}; // end of KDTreeEigenMatrixAdaptor - /** @} */ - -/** @} */ // end of grouping -} // namespace nanoflann - -#endif /* NANOFLANN_HPP_ */ diff --git a/include/small_gicp/ann/deprecated/nanoflann_omp.hpp b/include/small_gicp/ann/deprecated/nanoflann_omp.hpp deleted file mode 100644 index c437276..0000000 --- a/include/small_gicp/ann/deprecated/nanoflann_omp.hpp +++ /dev/null @@ -1,657 +0,0 @@ -/*********************************************************************** - * 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. - * Copyright 2011-2021 Jose Luis Blanco (joseluisblancoc@gmail.com). - * 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. - *************************************************************************/ - -/** - * This nanoflann_mt.hpp is derived from nanoflann.hpp to parallelize the tree construction with OpenMP. - */ - -/** \mainpage nanoflann C++ API documentation - * nanoflann is a C++ header-only library for building KD-Trees, mostly - * optimized for 2D or 3D point clouds. - * - * nanoflann does not require compiling or installing, just an - * #include in your code. - * - * See: - * - C++ API organized by modules - * - Online README - * - Doxygen - * documentation - */ - -#ifndef NANOFLANN_OMP_HPP_ -#define NANOFLANN_OMP_HPP_ - -#include -#include -#include - -namespace nanoflann { - -/** kd-tree base-class - * - * Contains the member functions common to the classes KDTreeSingleIndexAdaptor - * and KDTreeSingleIndexDynamicAdaptor_. - * - * \tparam Derived The name of the class which inherits this class. - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use, these are all classes derived - * from nanoflann::Metric \tparam DIM Dimensionality of data points (e.g. 3 for - * 3D points) \tparam IndexType Will be typically size_t or int - */ - -template -class KDTreeBaseClassOMP { -public: - /** Frees the previously-built index. Automatically called within - * buildIndex(). */ - void freeIndex(Derived& obj) { - obj.root_node = NULL; - obj.m_size_at_index_build = 0; - } - - typedef typename Distance::ElementType ElementType; - typedef typename Distance::DistanceType DistanceType; - - /*--------------------- Internal Data Structures --------------------------*/ - struct Node { - /** Union used because a node can be either a LEAF node or a non-leaf node, - * so both data fields are never used simultaneously */ - union { - struct leaf { - IndexType left, right; //!< Indices of points in leaf node - } lr; - struct nonleaf { - int divfeat; //!< Dimension used for subdivision. - DistanceType divlow, divhigh; //!< The values used for subdivision. - } sub; - } node_type; - Node *child1, *child2; //!< Child nodes (both=NULL mean its a leaf node) - }; - - typedef Node* NodePtr; - - struct Interval { - ElementType low, high; - }; - - /** - * Array of indices to vectors in the dataset. - */ - std::vector vind; - - NodePtr root_node; - - size_t m_leaf_max_size; - - size_t m_size; //!< Number of current points in the dataset - size_t m_size_at_index_build; //!< Number of points in the dataset when the - //!< index was built - int dim; //!< Dimensionality of each data point - - /** Define "BoundingBox" as a fixed-size or variable-size container depending - * on "DIM" */ - typedef typename array_or_vector_selector::container_t BoundingBox; - - /** Define "distance_vector_t" as a fixed-size or variable-size container - * depending on "DIM" */ - typedef typename array_or_vector_selector::container_t distance_vector_t; - - /** The KD-tree used to find neighbours */ - - BoundingBox root_bbox; - - /** - * Pooled memory allocator. - * - * Using a pooled memory allocator is more efficient - * than allocating memory directly when there is a large - * number small of memory allocations. - */ - std::atomic_uint64_t pool_count; - std::vector pool; - - /** Returns number of points in dataset */ - size_t size(const Derived& obj) const { return obj.m_size; } - - /** Returns the length of each point in the dataset */ - size_t veclen(const Derived& obj) { return static_cast(DIM > 0 ? DIM : obj.dim); } - - /// Helper accessor to the dataset points: - inline ElementType dataset_get(const Derived& obj, size_t idx, int component) const { return obj.dataset.kdtree_get_pt(idx, component); } - - void computeMinMax(const Derived& obj, IndexType* ind, IndexType count, int element, ElementType& min_elem, ElementType& max_elem) { - min_elem = dataset_get(obj, ind[0], element); - max_elem = dataset_get(obj, ind[0], element); - for (IndexType i = 1; i < count; ++i) { - ElementType val = dataset_get(obj, ind[i], element); - if (val < min_elem) min_elem = val; - if (val > max_elem) max_elem = val; - } - } - - /** - * Create a tree node that subdivides the list of vecs from vind[first] - * to vind[last]. The routine is called recursively on each sublist. - * - * @param left index of the first vector - * @param right index of the last vector - */ - NodePtr divideTree(Derived& obj, const IndexType left, const IndexType right, BoundingBox& bbox) { - const size_t pool_loc = pool_count++; - if (pool_loc >= pool.size()) { - std::cerr << "error: pool_loc=" << pool_loc << " >= pool.size()=" << pool.size() << std::endl; - abort(); - } - NodePtr node = pool.data() + pool_loc; - - /* If too few exemplars remain, then make this a leaf node. */ - if ((right - left) <= static_cast(obj.m_leaf_max_size)) { - node->child1 = node->child2 = NULL; /* Mark as leaf node. */ - node->node_type.lr.left = left; - node->node_type.lr.right = right; - - // compute bounding-box of leaf points - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - bbox[i].low = dataset_get(obj, obj.vind[left], i); - bbox[i].high = dataset_get(obj, obj.vind[left], i); - } - for (IndexType k = left + 1; k < right; ++k) { - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - if (bbox[i].low > dataset_get(obj, obj.vind[k], i)) bbox[i].low = dataset_get(obj, obj.vind[k], i); - if (bbox[i].high < dataset_get(obj, obj.vind[k], i)) bbox[i].high = dataset_get(obj, obj.vind[k], i); - } - } - } else { - IndexType idx; - int cutfeat; - DistanceType cutval; - middleSplit_(obj, &obj.vind[0] + left, right - left, idx, cutfeat, cutval, bbox); - - node->node_type.sub.divfeat = cutfeat; - - BoundingBox left_bbox(bbox); - left_bbox[cutfeat].high = cutval; - - BoundingBox right_bbox(bbox); - right_bbox[cutfeat].low = cutval; - - if ((right - left) <= 512) { - // Do not parallelize if there are less than 512 points - node->child1 = divideTree(obj, left, left + idx, left_bbox); - node->child2 = divideTree(obj, left + idx, right, right_bbox); - } else { - // I did my best to check that the following parallelization does not cause race conditions. - // But, still not 100% sure if it is correct. - -#pragma omp task shared(obj, left_bbox) - node->child1 = divideTree(obj, left, left + idx, left_bbox); -#pragma omp task shared(obj, right_bbox) - node->child2 = divideTree(obj, left + idx, right, right_bbox); -#pragma omp taskwait - } - - node->node_type.sub.divlow = left_bbox[cutfeat].high; - node->node_type.sub.divhigh = right_bbox[cutfeat].low; - - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - bbox[i].low = std::min(left_bbox[i].low, right_bbox[i].low); - bbox[i].high = std::max(left_bbox[i].high, right_bbox[i].high); - } - } - - return node; - } - - void middleSplit_(Derived& obj, IndexType* ind, IndexType count, IndexType& index, int& cutfeat, DistanceType& cutval, const BoundingBox& bbox) { - const DistanceType EPS = static_cast(0.00001); - ElementType max_span = bbox[0].high - bbox[0].low; - for (int i = 1; i < (DIM > 0 ? DIM : obj.dim); ++i) { - ElementType span = bbox[i].high - bbox[i].low; - if (span > max_span) { - max_span = span; - } - } - ElementType max_spread = -1; - cutfeat = 0; - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - ElementType span = bbox[i].high - bbox[i].low; - if (span > (1 - EPS) * max_span) { - ElementType min_elem, max_elem; - computeMinMax(obj, ind, count, i, min_elem, max_elem); - ElementType spread = max_elem - min_elem; - if (spread > max_spread) { - cutfeat = i; - max_spread = spread; - } - } - } - // split in the middle - DistanceType split_val = (bbox[cutfeat].low + bbox[cutfeat].high) / 2; - ElementType min_elem, max_elem; - computeMinMax(obj, ind, count, cutfeat, min_elem, max_elem); - - if (split_val < min_elem) - cutval = min_elem; - else if (split_val > max_elem) - cutval = max_elem; - else - cutval = split_val; - - IndexType lim1, lim2; - planeSplit(obj, ind, count, cutfeat, cutval, lim1, lim2); - - if (lim1 > count / 2) - index = lim1; - else if (lim2 < count / 2) - index = lim2; - else - index = count / 2; - } - - /** - * Subdivide the list of points by a plane perpendicular on axe corresponding - * to the 'cutfeat' dimension at 'cutval' position. - * - * On return: - * dataset[ind[0..lim1-1]][cutfeat]cutval - */ - void planeSplit(Derived& obj, IndexType* ind, const IndexType count, int cutfeat, DistanceType& cutval, IndexType& lim1, IndexType& lim2) { - /* Move vector indices for left subtree to front of list. */ - IndexType left = 0; - IndexType right = count - 1; - for (;;) { - while (left <= right && dataset_get(obj, ind[left], cutfeat) < cutval) ++left; - while (right && left <= right && dataset_get(obj, ind[right], cutfeat) >= cutval) --right; - if (left > right || !right) break; // "!right" was added to support unsigned Index types - std::swap(ind[left], ind[right]); - ++left; - --right; - } - /* If either list is empty, it means that all remaining features - * are identical. Split in the middle to maintain a balanced tree. - */ - lim1 = left; - right = count - 1; - for (;;) { - while (left <= right && dataset_get(obj, ind[left], cutfeat) <= cutval) ++left; - while (right && left <= right && dataset_get(obj, ind[right], cutfeat) > cutval) --right; - if (left > right || !right) break; // "!right" was added to support unsigned Index types - std::swap(ind[left], ind[right]); - ++left; - --right; - } - lim2 = left; - } - - DistanceType computeInitialDistances(const Derived& obj, const ElementType* vec, distance_vector_t& dists) const { - assert(vec); - DistanceType distsq = DistanceType(); - - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - if (vec[i] < obj.root_bbox[i].low) { - dists[i] = obj.distance.accum_dist(vec[i], obj.root_bbox[i].low, i); - distsq += dists[i]; - } - if (vec[i] > obj.root_bbox[i].high) { - dists[i] = obj.distance.accum_dist(vec[i], obj.root_bbox[i].high, i); - distsq += dists[i]; - } - } - return distsq; - } -}; - -/** @addtogroup kdtrees_grp KD-tree classes and adaptors - * @{ */ - -/** kd-tree static index - * - * Contains the k-d trees and other information for indexing a set of points - * for nearest-neighbor matching. - * - * The class "DatasetAdaptor" must provide the following interface (can be - * non-virtual, inlined methods): - * - * \code - * // Must return the number of data poins - * inline size_t kdtree_get_point_count() const { ... } - * - * - * // Must return the dim'th component of the idx'th point in the class: - * inline T kdtree_get_pt(const size_t idx, const size_t dim) const { ... } - * - * // Optional bounding-box computation: return false to default to a standard - * bbox computation loop. - * // Return true if the BBOX was already computed by the class and returned - * in "bb" so it can be avoided to redo it again. - * // Look at bb.size() to find out the expected dimensionality (e.g. 2 or 3 - * for point clouds) template bool kdtree_get_bbox(BBOX &bb) const - * { - * bb[0].low = ...; bb[0].high = ...; // 0th dimension limits - * bb[1].low = ...; bb[1].high = ...; // 1st dimension limits - * ... - * return true; - * } - * - * \endcode - * - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use: nanoflann::metric_L1, - * nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc. \tparam DIM - * Dimensionality of data points (e.g. 3 for 3D points) \tparam IndexType Will - * be typically size_t or int - */ -template -class KDTreeSingleIndexAdaptorOMP : public KDTreeBaseClassOMP, Distance, DatasetAdaptor, DIM, IndexType> { -public: - /** Deleted copy constructor*/ - KDTreeSingleIndexAdaptorOMP(const KDTreeSingleIndexAdaptorOMP&) = delete; - - /** - * The dataset used by this index - */ - const DatasetAdaptor& dataset; //!< The source of our data - - const KDTreeSingleIndexAdaptorParams index_params; - - Distance distance; - - typedef typename nanoflann::KDTreeBaseClassOMP, Distance, DatasetAdaptor, DIM, IndexType> - BaseClassRef; - - typedef typename BaseClassRef::ElementType ElementType; - typedef typename BaseClassRef::DistanceType DistanceType; - - typedef typename BaseClassRef::Node Node; - typedef Node* NodePtr; - - typedef typename BaseClassRef::Interval Interval; - /** Define "BoundingBox" as a fixed-size or variable-size container depending - * on "DIM" */ - typedef typename BaseClassRef::BoundingBox BoundingBox; - - /** Define "distance_vector_t" as a fixed-size or variable-size container - * depending on "DIM" */ - typedef typename BaseClassRef::distance_vector_t distance_vector_t; - - /** - * KDTree constructor - * - * Refer to docs in README.md or online in - * https://github.com/jlblancoc/nanoflann - * - * The KD-Tree point dimension (the length of each point in the datase, e.g. 3 - * for 3D points) is determined by means of: - * - The \a DIM template parameter if >0 (highest priority) - * - Otherwise, the \a dimensionality parameter of this constructor. - * - * @param inputData Dataset with the input features - * @param params Basically, the maximum leaf node size - */ - KDTreeSingleIndexAdaptorOMP(const int dimensionality, const DatasetAdaptor& inputData, const KDTreeSingleIndexAdaptorParams& params = KDTreeSingleIndexAdaptorParams()) - : dataset(inputData), - index_params(params), - distance(inputData) { - BaseClassRef::root_node = NULL; - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - BaseClassRef::dim = dimensionality; - if (DIM > 0) BaseClassRef::dim = DIM; - BaseClassRef::m_leaf_max_size = params.leaf_max_size; - - // Create a permutable array of indices to the input vectors. - init_vind(); - } - - /** - * Builds the index - */ - void buildIndex(int num_threads) { - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - init_vind(); - this->freeIndex(*this); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - if (BaseClassRef::m_size == 0) return; - computeBoundingBox(BaseClassRef::root_bbox); - - BaseClassRef::pool_count = 0; - BaseClassRef::pool.resize(BaseClassRef::m_size); - -#pragma omp parallel num_threads(num_threads) - { -#pragma omp single nowait - { - BaseClassRef::root_node = this->divideTree(*this, 0, BaseClassRef::m_size, - BaseClassRef::root_bbox); // construct the tree - } - } - } - - /** \name Query methods - * @{ */ - - /** - * Find set of nearest neighbors to vec[0:dim-1]. Their indices are stored - * inside the result object. - * - * Params: - * result = the result object in which the indices of the - * nearest-neighbors are stored vec = the vector for which to search the - * nearest neighbors - * - * \tparam RESULTSET Should be any ResultSet - * \return True if the requested neighbors could be found. - * \sa knnSearch, radiusSearch - */ - template - bool findNeighbors(RESULTSET& result, const ElementType* vec, const SearchParams& searchParams) const { - assert(vec); - if (this->size(*this) == 0) return false; - if (!BaseClassRef::root_node) throw std::runtime_error("[nanoflann] findNeighbors() called before building the index."); - float epsError = 1 + searchParams.eps; - - distance_vector_t dists; // fixed or variable-sized container (depending on DIM) - auto zero = static_cast(0); - assign(dists, (DIM > 0 ? DIM : BaseClassRef::dim), - zero); // Fill it with zeros. - DistanceType distsq = this->computeInitialDistances(*this, vec, dists); - searchLevel( - result, - vec, - BaseClassRef::root_node, - distsq, - dists, - epsError); // "count_leaf" parameter removed since was neither - // used nor returned to the user. - return result.full(); - } - - /** - * Find the "num_closest" nearest neighbors to the \a query_point[0:dim-1]. - * Their indices are stored inside the result object. \sa radiusSearch, - * findNeighbors \note nChecks_IGNORED is ignored but kept for compatibility - * with the original FLANN interface. \return Number `N` of valid points in - * the result set. Only the first `N` entries in `out_indices` and - * `out_distances_sq` will be valid. Return may be less than `num_closest` - * only if the number of elements in the tree is less than `num_closest`. - */ - size_t knnSearch(const ElementType* query_point, const size_t num_closest, IndexType* out_indices, DistanceType* out_distances_sq, const int /* nChecks_IGNORED */ = 10) const { - nanoflann::KNNResultSet resultSet(num_closest); - resultSet.init(out_indices, out_distances_sq); - this->findNeighbors(resultSet, query_point, nanoflann::SearchParams()); - return resultSet.size(); - } - - /** - * Find all the neighbors to \a query_point[0:dim-1] within a maximum radius. - * The output is given as a vector of pairs, of which the first element is a - * point index and the second the corresponding distance. Previous contents of - * \a IndicesDists are cleared. - * - * If searchParams.sorted==true, the output list is sorted by ascending - * distances. - * - * For a better performance, it is advisable to do a .reserve() on the vector - * if you have any wild guess about the number of expected matches. - * - * \sa knnSearch, findNeighbors, radiusSearchCustomCallback - * \return The number of points within the given radius (i.e. indices.size() - * or dists.size() ) - */ - size_t radiusSearch(const ElementType* query_point, const DistanceType& radius, std::vector>& IndicesDists, const SearchParams& searchParams) - const { - RadiusResultSet resultSet(radius, IndicesDists); - const size_t nFound = radiusSearchCustomCallback(query_point, resultSet, searchParams); - if (searchParams.sorted) std::sort(IndicesDists.begin(), IndicesDists.end(), IndexDist_Sorter()); - return nFound; - } - - /** - * Just like radiusSearch() but with a custom callback class for each point - * found in the radius of the query. See the source of RadiusResultSet<> as a - * start point for your own classes. \sa radiusSearch - */ - template - size_t radiusSearchCustomCallback(const ElementType* query_point, SEARCH_CALLBACK& resultSet, const SearchParams& searchParams = SearchParams()) const { - this->findNeighbors(resultSet, query_point, searchParams); - return resultSet.size(); - } - - /** @} */ - -public: - /** Make sure the auxiliary list \a vind has the same size than the current - * dataset, and re-generate if size has changed. */ - void init_vind() { - // Create a permutable array of indices to the input vectors. - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - if (BaseClassRef::vind.size() != BaseClassRef::m_size) BaseClassRef::vind.resize(BaseClassRef::m_size); - for (size_t i = 0; i < BaseClassRef::m_size; i++) BaseClassRef::vind[i] = i; - } - - void computeBoundingBox(BoundingBox& bbox) { - resize(bbox, (DIM > 0 ? DIM : BaseClassRef::dim)); - if (dataset.kdtree_get_bbox(bbox)) { - // Done! It was implemented in derived class - } else { - const size_t N = dataset.kdtree_get_point_count(); - if (!N) - throw std::runtime_error( - "[nanoflann] computeBoundingBox() called but " - "no data points found."); - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - bbox[i].low = bbox[i].high = this->dataset_get(*this, 0, i); - } - for (size_t k = 1; k < N; ++k) { - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - if (this->dataset_get(*this, k, i) < bbox[i].low) bbox[i].low = this->dataset_get(*this, k, i); - if (this->dataset_get(*this, k, i) > bbox[i].high) bbox[i].high = this->dataset_get(*this, k, i); - } - } - } - } - - /** - * Performs an exact search in the tree starting from a node. - * \tparam RESULTSET Should be any ResultSet - * \return true if the search should be continued, false if the results are - * sufficient - */ - template - bool searchLevel(RESULTSET& result_set, const ElementType* vec, const NodePtr node, DistanceType mindistsq, distance_vector_t& dists, const float epsError) const { - /* If this is a leaf node, then do check and return. */ - if ((node->child1 == NULL) && (node->child2 == NULL)) { - // count_leaf += (node->lr.right-node->lr.left); // Removed since was - // neither used nor returned to the user. - DistanceType worst_dist = result_set.worstDist(); - for (IndexType i = node->node_type.lr.left; i < node->node_type.lr.right; ++i) { - const IndexType index = BaseClassRef::vind[i]; // reorder... : i; - DistanceType dist = distance.evalMetric(vec, index, (DIM > 0 ? DIM : BaseClassRef::dim)); - if (dist < worst_dist) { - if (!result_set.addPoint(dist, BaseClassRef::vind[i])) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - } - } - return true; - } - - /* Which child branch should be taken first? */ - int idx = node->node_type.sub.divfeat; - ElementType val = vec[idx]; - DistanceType diff1 = val - node->node_type.sub.divlow; - DistanceType diff2 = val - node->node_type.sub.divhigh; - - NodePtr bestChild; - NodePtr otherChild; - DistanceType cut_dist; - if ((diff1 + diff2) < 0) { - bestChild = node->child1; - otherChild = node->child2; - cut_dist = distance.accum_dist(val, node->node_type.sub.divhigh, idx); - } else { - bestChild = node->child2; - otherChild = node->child1; - cut_dist = distance.accum_dist(val, node->node_type.sub.divlow, idx); - } - - /* Call recursively to search next level down. */ - if (!searchLevel(result_set, vec, bestChild, mindistsq, dists, epsError)) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - - DistanceType dst = dists[idx]; - mindistsq = mindistsq + cut_dist - dst; - dists[idx] = cut_dist; - if (mindistsq * epsError <= result_set.worstDist()) { - if (!searchLevel(result_set, vec, otherChild, mindistsq, dists, epsError)) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - } - dists[idx] = dst; - return true; - } -}; - -} // namespace nanoflann - -#endif /* NANOFLANN_HPP_ */ diff --git a/include/small_gicp/ann/deprecated/nanoflann_tbb.hpp b/include/small_gicp/ann/deprecated/nanoflann_tbb.hpp deleted file mode 100644 index be51b13..0000000 --- a/include/small_gicp/ann/deprecated/nanoflann_tbb.hpp +++ /dev/null @@ -1,639 +0,0 @@ -/*********************************************************************** - * 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. - * Copyright 2011-2021 Jose Luis Blanco (joseluisblancoc@gmail.com). - * 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. - *************************************************************************/ - -/** - * This nanoflann_mt.hpp is derived from nanoflann.hpp to parallelize the tree construction with TBB - */ - -/** \mainpage nanoflann C++ API documentation - * nanoflann is a C++ header-only library for building KD-Trees, mostly - * optimized for 2D or 3D point clouds. - * - * nanoflann does not require compiling or installing, just an - * #include in your code. - * - * See: - * - C++ API organized by modules - * - Online README - * - Doxygen - * documentation - */ - -#ifndef NANOFLANN_TBB_HPP_ -#define NANOFLANN_TBB_HPP_ - -#include -#include - -namespace nanoflann { - -/** kd-tree base-class - * - * Contains the member functions common to the classes KDTreeSingleIndexAdaptor - * and KDTreeSingleIndexDynamicAdaptor_. - * - * \tparam Derived The name of the class which inherits this class. - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use, these are all classes derived - * from nanoflann::Metric \tparam DIM Dimensionality of data points (e.g. 3 for - * 3D points) \tparam IndexType Will be typically size_t or int - */ - -template -class KDTreeBaseClassTBB { -public: - /** Frees the previously-built index. Automatically called within - * buildIndex(). */ - void freeIndex(Derived& obj) { - obj.root_node = NULL; - obj.m_size_at_index_build = 0; - } - - typedef typename Distance::ElementType ElementType; - typedef typename Distance::DistanceType DistanceType; - - /*--------------------- Internal Data Structures --------------------------*/ - struct Node { - /** Union used because a node can be either a LEAF node or a non-leaf node, - * so both data fields are never used simultaneously */ - union { - struct leaf { - IndexType left, right; //!< Indices of points in leaf node - } lr; - struct nonleaf { - int divfeat; //!< Dimension used for subdivision. - DistanceType divlow, divhigh; //!< The values used for subdivision. - } sub; - } node_type; - Node *child1, *child2; //!< Child nodes (both=NULL mean its a leaf node) - }; - - typedef Node* NodePtr; - - struct Interval { - ElementType low, high; - }; - - /** - * Array of indices to vectors in the dataset. - */ - std::vector vind; - - NodePtr root_node; - - size_t m_leaf_max_size; - - size_t m_size; //!< Number of current points in the dataset - size_t m_size_at_index_build; //!< Number of points in the dataset when the - //!< index was built - int dim; //!< Dimensionality of each data point - - /** Define "BoundingBox" as a fixed-size or variable-size container depending - * on "DIM" */ - typedef typename array_or_vector_selector::container_t BoundingBox; - - /** Define "distance_vector_t" as a fixed-size or variable-size container - * depending on "DIM" */ - typedef typename array_or_vector_selector::container_t distance_vector_t; - - /** The KD-tree used to find neighbours */ - - BoundingBox root_bbox; - - /** - * Pooled memory allocator. - * - * Using a pooled memory allocator is more efficient - * than allocating memory directly when there is a large - * number small of memory allocations. - */ - tbb::concurrent_vector pool; - - /** Returns number of points in dataset */ - size_t size(const Derived& obj) const { return obj.m_size; } - - /** Returns the length of each point in the dataset */ - size_t veclen(const Derived& obj) { return static_cast(DIM > 0 ? DIM : obj.dim); } - - /// Helper accessor to the dataset points: - inline ElementType dataset_get(const Derived& obj, size_t idx, int component) const { return obj.dataset.kdtree_get_pt(idx, component); } - - void computeMinMax(const Derived& obj, IndexType* ind, IndexType count, int element, ElementType& min_elem, ElementType& max_elem) { - min_elem = dataset_get(obj, ind[0], element); - max_elem = dataset_get(obj, ind[0], element); - for (IndexType i = 1; i < count; ++i) { - ElementType val = dataset_get(obj, ind[i], element); - if (val < min_elem) min_elem = val; - if (val > max_elem) max_elem = val; - } - } - - /** - * Create a tree node that subdivides the list of vecs from vind[first] - * to vind[last]. The routine is called recursively on each sublist. - * - * @param left index of the first vector - * @param right index of the last vector - */ - NodePtr divideTree(Derived& obj, const IndexType left, const IndexType right, BoundingBox& bbox) { - NodePtr node = &(*pool.emplace_back()); - - /* If too few exemplars remain, then make this a leaf node. */ - if ((right - left) <= static_cast(obj.m_leaf_max_size)) { - node->child1 = node->child2 = NULL; /* Mark as leaf node. */ - node->node_type.lr.left = left; - node->node_type.lr.right = right; - - // compute bounding-box of leaf points - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - bbox[i].low = dataset_get(obj, obj.vind[left], i); - bbox[i].high = dataset_get(obj, obj.vind[left], i); - } - for (IndexType k = left + 1; k < right; ++k) { - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - if (bbox[i].low > dataset_get(obj, obj.vind[k], i)) bbox[i].low = dataset_get(obj, obj.vind[k], i); - if (bbox[i].high < dataset_get(obj, obj.vind[k], i)) bbox[i].high = dataset_get(obj, obj.vind[k], i); - } - } - } else { - IndexType idx; - int cutfeat; - DistanceType cutval; - middleSplit_(obj, &obj.vind[0] + left, right - left, idx, cutfeat, cutval, bbox); - - node->node_type.sub.divfeat = cutfeat; - - BoundingBox left_bbox(bbox); - left_bbox[cutfeat].high = cutval; - - BoundingBox right_bbox(bbox); - right_bbox[cutfeat].low = cutval; - - if ((right - left) <= 512) { - // Do not parallelize if there are less than 512 points - node->child1 = divideTree(obj, left, left + idx, left_bbox); - node->child2 = divideTree(obj, left + idx, right, right_bbox); - } else { - // I did my best to check that the following parallelization does not cause race conditions. - // But, still not 100% sure if it is correct. - - tbb::parallel_invoke([&] { node->child1 = divideTree(obj, left, left + idx, left_bbox); }, [&] { node->child2 = divideTree(obj, left + idx, right, right_bbox); }); - } - - node->node_type.sub.divlow = left_bbox[cutfeat].high; - node->node_type.sub.divhigh = right_bbox[cutfeat].low; - - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - bbox[i].low = std::min(left_bbox[i].low, right_bbox[i].low); - bbox[i].high = std::max(left_bbox[i].high, right_bbox[i].high); - } - } - - return node; - } - - void middleSplit_(Derived& obj, IndexType* ind, IndexType count, IndexType& index, int& cutfeat, DistanceType& cutval, const BoundingBox& bbox) { - const DistanceType EPS = static_cast(0.00001); - ElementType max_span = bbox[0].high - bbox[0].low; - for (int i = 1; i < (DIM > 0 ? DIM : obj.dim); ++i) { - ElementType span = bbox[i].high - bbox[i].low; - if (span > max_span) { - max_span = span; - } - } - ElementType max_spread = -1; - cutfeat = 0; - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - ElementType span = bbox[i].high - bbox[i].low; - if (span > (1 - EPS) * max_span) { - ElementType min_elem, max_elem; - computeMinMax(obj, ind, count, i, min_elem, max_elem); - ElementType spread = max_elem - min_elem; - if (spread > max_spread) { - cutfeat = i; - max_spread = spread; - } - } - } - // split in the middle - DistanceType split_val = (bbox[cutfeat].low + bbox[cutfeat].high) / 2; - ElementType min_elem, max_elem; - computeMinMax(obj, ind, count, cutfeat, min_elem, max_elem); - - if (split_val < min_elem) - cutval = min_elem; - else if (split_val > max_elem) - cutval = max_elem; - else - cutval = split_val; - - IndexType lim1, lim2; - planeSplit(obj, ind, count, cutfeat, cutval, lim1, lim2); - - if (lim1 > count / 2) - index = lim1; - else if (lim2 < count / 2) - index = lim2; - else - index = count / 2; - } - - /** - * Subdivide the list of points by a plane perpendicular on axe corresponding - * to the 'cutfeat' dimension at 'cutval' position. - * - * On return: - * dataset[ind[0..lim1-1]][cutfeat]cutval - */ - void planeSplit(Derived& obj, IndexType* ind, const IndexType count, int cutfeat, DistanceType& cutval, IndexType& lim1, IndexType& lim2) { - /* Move vector indices for left subtree to front of list. */ - IndexType left = 0; - IndexType right = count - 1; - for (;;) { - while (left <= right && dataset_get(obj, ind[left], cutfeat) < cutval) ++left; - while (right && left <= right && dataset_get(obj, ind[right], cutfeat) >= cutval) --right; - if (left > right || !right) break; // "!right" was added to support unsigned Index types - std::swap(ind[left], ind[right]); - ++left; - --right; - } - /* If either list is empty, it means that all remaining features - * are identical. Split in the middle to maintain a balanced tree. - */ - lim1 = left; - right = count - 1; - for (;;) { - while (left <= right && dataset_get(obj, ind[left], cutfeat) <= cutval) ++left; - while (right && left <= right && dataset_get(obj, ind[right], cutfeat) > cutval) --right; - if (left > right || !right) break; // "!right" was added to support unsigned Index types - std::swap(ind[left], ind[right]); - ++left; - --right; - } - lim2 = left; - } - - DistanceType computeInitialDistances(const Derived& obj, const ElementType* vec, distance_vector_t& dists) const { - assert(vec); - DistanceType distsq = DistanceType(); - - for (int i = 0; i < (DIM > 0 ? DIM : obj.dim); ++i) { - if (vec[i] < obj.root_bbox[i].low) { - dists[i] = obj.distance.accum_dist(vec[i], obj.root_bbox[i].low, i); - distsq += dists[i]; - } - if (vec[i] > obj.root_bbox[i].high) { - dists[i] = obj.distance.accum_dist(vec[i], obj.root_bbox[i].high, i); - distsq += dists[i]; - } - } - return distsq; - } -}; - -/** @addtogroup kdtrees_grp KD-tree classes and adaptors - * @{ */ - -/** kd-tree static index - * - * Contains the k-d trees and other information for indexing a set of points - * for nearest-neighbor matching. - * - * The class "DatasetAdaptor" must provide the following interface (can be - * non-virtual, inlined methods): - * - * \code - * // Must return the number of data poins - * inline size_t kdtree_get_point_count() const { ... } - * - * - * // Must return the dim'th component of the idx'th point in the class: - * inline T kdtree_get_pt(const size_t idx, const size_t dim) const { ... } - * - * // Optional bounding-box computation: return false to default to a standard - * bbox computation loop. - * // Return true if the BBOX was already computed by the class and returned - * in "bb" so it can be avoided to redo it again. - * // Look at bb.size() to find out the expected dimensionality (e.g. 2 or 3 - * for point clouds) template bool kdtree_get_bbox(BBOX &bb) const - * { - * bb[0].low = ...; bb[0].high = ...; // 0th dimension limits - * bb[1].low = ...; bb[1].high = ...; // 1st dimension limits - * ... - * return true; - * } - * - * \endcode - * - * \tparam DatasetAdaptor The user-provided adaptor (see comments above). - * \tparam Distance The distance metric to use: nanoflann::metric_L1, - * nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc. \tparam DIM - * Dimensionality of data points (e.g. 3 for 3D points) \tparam IndexType Will - * be typically size_t or int - */ -template -class KDTreeSingleIndexAdaptorTBB : public KDTreeBaseClassTBB, Distance, DatasetAdaptor, DIM, IndexType> { -public: - /** Deleted copy constructor*/ - KDTreeSingleIndexAdaptorTBB(const KDTreeSingleIndexAdaptorTBB&) = delete; - - /** - * The dataset used by this index - */ - const DatasetAdaptor& dataset; //!< The source of our data - - const KDTreeSingleIndexAdaptorParams index_params; - - Distance distance; - - typedef typename nanoflann::KDTreeBaseClassTBB, Distance, DatasetAdaptor, DIM, IndexType> - BaseClassRef; - - typedef typename BaseClassRef::ElementType ElementType; - typedef typename BaseClassRef::DistanceType DistanceType; - - typedef typename BaseClassRef::Node Node; - typedef Node* NodePtr; - - typedef typename BaseClassRef::Interval Interval; - /** Define "BoundingBox" as a fixed-size or variable-size container depending - * on "DIM" */ - typedef typename BaseClassRef::BoundingBox BoundingBox; - - /** Define "distance_vector_t" as a fixed-size or variable-size container - * depending on "DIM" */ - typedef typename BaseClassRef::distance_vector_t distance_vector_t; - - /** - * KDTree constructor - * - * Refer to docs in README.md or online in - * https://github.com/jlblancoc/nanoflann - * - * The KD-Tree point dimension (the length of each point in the datase, e.g. 3 - * for 3D points) is determined by means of: - * - The \a DIM template parameter if >0 (highest priority) - * - Otherwise, the \a dimensionality parameter of this constructor. - * - * @param inputData Dataset with the input features - * @param params Basically, the maximum leaf node size - */ - KDTreeSingleIndexAdaptorTBB(const int dimensionality, const DatasetAdaptor& inputData, const KDTreeSingleIndexAdaptorParams& params = KDTreeSingleIndexAdaptorParams()) - : dataset(inputData), - index_params(params), - distance(inputData) { - BaseClassRef::root_node = NULL; - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - BaseClassRef::dim = dimensionality; - if (DIM > 0) BaseClassRef::dim = DIM; - BaseClassRef::m_leaf_max_size = params.leaf_max_size; - - // Create a permutable array of indices to the input vectors. - init_vind(); - } - - /** - * Builds the index - */ - void buildIndex() { - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - init_vind(); - this->freeIndex(*this); - BaseClassRef::m_size_at_index_build = BaseClassRef::m_size; - if (BaseClassRef::m_size == 0) return; - computeBoundingBox(BaseClassRef::root_bbox); - - BaseClassRef::pool.reserve(BaseClassRef::m_size); - - BaseClassRef::root_node = this->divideTree(*this, 0, BaseClassRef::m_size, - BaseClassRef::root_bbox); // construct the tree - } - - /** \name Query methods - * @{ */ - - /** - * Find set of nearest neighbors to vec[0:dim-1]. Their indices are stored - * inside the result object. - * - * Params: - * result = the result object in which the indices of the - * nearest-neighbors are stored vec = the vector for which to search the - * nearest neighbors - * - * \tparam RESULTSET Should be any ResultSet - * \return True if the requested neighbors could be found. - * \sa knnSearch, radiusSearch - */ - template - bool findNeighbors(RESULTSET& result, const ElementType* vec, const SearchParams& searchParams) const { - assert(vec); - if (this->size(*this) == 0) return false; - if (!BaseClassRef::root_node) throw std::runtime_error("[nanoflann] findNeighbors() called before building the index."); - float epsError = 1 + searchParams.eps; - - distance_vector_t dists; // fixed or variable-sized container (depending on DIM) - auto zero = static_cast(0); - assign(dists, (DIM > 0 ? DIM : BaseClassRef::dim), - zero); // Fill it with zeros. - DistanceType distsq = this->computeInitialDistances(*this, vec, dists); - searchLevel( - result, - vec, - BaseClassRef::root_node, - distsq, - dists, - epsError); // "count_leaf" parameter removed since was neither - // used nor returned to the user. - return result.full(); - } - - /** - * Find the "num_closest" nearest neighbors to the \a query_point[0:dim-1]. - * Their indices are stored inside the result object. \sa radiusSearch, - * findNeighbors \note nChecks_IGNORED is ignored but kept for compatibility - * with the original FLANN interface. \return Number `N` of valid points in - * the result set. Only the first `N` entries in `out_indices` and - * `out_distances_sq` will be valid. Return may be less than `num_closest` - * only if the number of elements in the tree is less than `num_closest`. - */ - size_t knnSearch(const ElementType* query_point, const size_t num_closest, IndexType* out_indices, DistanceType* out_distances_sq, const int /* nChecks_IGNORED */ = 10) const { - nanoflann::KNNResultSet resultSet(num_closest); - resultSet.init(out_indices, out_distances_sq); - this->findNeighbors(resultSet, query_point, nanoflann::SearchParams()); - return resultSet.size(); - } - - /** - * Find all the neighbors to \a query_point[0:dim-1] within a maximum radius. - * The output is given as a vector of pairs, of which the first element is a - * point index and the second the corresponding distance. Previous contents of - * \a IndicesDists are cleared. - * - * If searchParams.sorted==true, the output list is sorted by ascending - * distances. - * - * For a better performance, it is advisable to do a .reserve() on the vector - * if you have any wild guess about the number of expected matches. - * - * \sa knnSearch, findNeighbors, radiusSearchCustomCallback - * \return The number of points within the given radius (i.e. indices.size() - * or dists.size() ) - */ - size_t radiusSearch(const ElementType* query_point, const DistanceType& radius, std::vector>& IndicesDists, const SearchParams& searchParams) - const { - RadiusResultSet resultSet(radius, IndicesDists); - const size_t nFound = radiusSearchCustomCallback(query_point, resultSet, searchParams); - if (searchParams.sorted) std::sort(IndicesDists.begin(), IndicesDists.end(), IndexDist_Sorter()); - return nFound; - } - - /** - * Just like radiusSearch() but with a custom callback class for each point - * found in the radius of the query. See the source of RadiusResultSet<> as a - * start point for your own classes. \sa radiusSearch - */ - template - size_t radiusSearchCustomCallback(const ElementType* query_point, SEARCH_CALLBACK& resultSet, const SearchParams& searchParams = SearchParams()) const { - this->findNeighbors(resultSet, query_point, searchParams); - return resultSet.size(); - } - - /** @} */ - -public: - /** Make sure the auxiliary list \a vind has the same size than the current - * dataset, and re-generate if size has changed. */ - void init_vind() { - // Create a permutable array of indices to the input vectors. - BaseClassRef::m_size = dataset.kdtree_get_point_count(); - if (BaseClassRef::vind.size() != BaseClassRef::m_size) BaseClassRef::vind.resize(BaseClassRef::m_size); - for (size_t i = 0; i < BaseClassRef::m_size; i++) BaseClassRef::vind[i] = i; - } - - void computeBoundingBox(BoundingBox& bbox) { - resize(bbox, (DIM > 0 ? DIM : BaseClassRef::dim)); - if (dataset.kdtree_get_bbox(bbox)) { - // Done! It was implemented in derived class - } else { - const size_t N = dataset.kdtree_get_point_count(); - if (!N) - throw std::runtime_error( - "[nanoflann] computeBoundingBox() called but " - "no data points found."); - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - bbox[i].low = bbox[i].high = this->dataset_get(*this, 0, i); - } - for (size_t k = 1; k < N; ++k) { - for (int i = 0; i < (DIM > 0 ? DIM : BaseClassRef::dim); ++i) { - if (this->dataset_get(*this, k, i) < bbox[i].low) bbox[i].low = this->dataset_get(*this, k, i); - if (this->dataset_get(*this, k, i) > bbox[i].high) bbox[i].high = this->dataset_get(*this, k, i); - } - } - } - } - - /** - * Performs an exact search in the tree starting from a node. - * \tparam RESULTSET Should be any ResultSet - * \return true if the search should be continued, false if the results are - * sufficient - */ - template - bool searchLevel(RESULTSET& result_set, const ElementType* vec, const NodePtr node, DistanceType mindistsq, distance_vector_t& dists, const float epsError) const { - /* If this is a leaf node, then do check and return. */ - if ((node->child1 == NULL) && (node->child2 == NULL)) { - // count_leaf += (node->lr.right-node->lr.left); // Removed since was - // neither used nor returned to the user. - DistanceType worst_dist = result_set.worstDist(); - for (IndexType i = node->node_type.lr.left; i < node->node_type.lr.right; ++i) { - const IndexType index = BaseClassRef::vind[i]; // reorder... : i; - DistanceType dist = distance.evalMetric(vec, index, (DIM > 0 ? DIM : BaseClassRef::dim)); - if (dist < worst_dist) { - if (!result_set.addPoint(dist, BaseClassRef::vind[i])) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - } - } - return true; - } - - /* Which child branch should be taken first? */ - int idx = node->node_type.sub.divfeat; - ElementType val = vec[idx]; - DistanceType diff1 = val - node->node_type.sub.divlow; - DistanceType diff2 = val - node->node_type.sub.divhigh; - - NodePtr bestChild; - NodePtr otherChild; - DistanceType cut_dist; - if ((diff1 + diff2) < 0) { - bestChild = node->child1; - otherChild = node->child2; - cut_dist = distance.accum_dist(val, node->node_type.sub.divhigh, idx); - } else { - bestChild = node->child2; - otherChild = node->child1; - cut_dist = distance.accum_dist(val, node->node_type.sub.divlow, idx); - } - - /* Call recursively to search next level down. */ - if (!searchLevel(result_set, vec, bestChild, mindistsq, dists, epsError)) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - - DistanceType dst = dists[idx]; - mindistsq = mindistsq + cut_dist - dst; - dists[idx] = cut_dist; - if (mindistsq * epsError <= result_set.worstDist()) { - if (!searchLevel(result_set, vec, otherChild, mindistsq, dists, epsError)) { - // the resultset doesn't want to receive any more points, we're done - // searching! - return false; - } - } - dists[idx] = dst; - return true; - } -}; - -} // namespace nanoflann - -#endif /* NANOFLANN_HPP_ */ From a5def4222235cdb3aa4f111a963d208d28f93e25 Mon Sep 17 00:00:00 2001 From: "k.koide" Date: Wed, 5 Jun 2024 11:43:34 +0900 Subject: [PATCH 2/3] Doxyfile --- docs/Doxyfile | 2579 +++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 2579 insertions(+) create mode 100644 docs/Doxyfile diff --git a/docs/Doxyfile b/docs/Doxyfile new file mode 100644 index 0000000..eead51a --- /dev/null +++ b/docs/Doxyfile @@ -0,0 +1,2579 @@ +# Doxyfile 1.8.17 + +# This file describes the settings to be used by the documentation system +# doxygen (www.doxygen.org) for a project. +# +# All text after a double hash (##) is considered a comment and is placed in +# front of the TAG it is preceding. +# +# All text after a single hash (#) is considered a comment and will be ignored. +# The format is: +# TAG = value [value, ...] +# For lists, items can also be appended using: +# TAG += value [value, ...] +# Values that contain spaces should be placed between quotes (\" \"). + +#--------------------------------------------------------------------------- +# Project related configuration options +#--------------------------------------------------------------------------- + +# This tag specifies the encoding used for all characters in the configuration +# file that follow. 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If +# left blank the current directory will be used. + +OUTPUT_DIRECTORY = + +# If the CREATE_SUBDIRS tag is set to YES then doxygen will create 4096 sub- +# directories (in 2 levels) under the output directory of each output format and +# will distribute the generated files over these directories. Enabling this +# option can be useful when feeding doxygen a huge amount of source files, where +# putting all generated files in the same directory would otherwise causes +# performance problems for the file system. +# The default value is: NO. + +CREATE_SUBDIRS = NO + +# If the ALLOW_UNICODE_NAMES tag is set to YES, doxygen will allow non-ASCII +# characters to appear in the names of generated files. If set to NO, non-ASCII +# characters will be escaped, for example _xE3_x81_x84 will be used for Unicode +# U+3044. +# The default value is: NO. + +ALLOW_UNICODE_NAMES = NO + +# The OUTPUT_LANGUAGE tag is used to specify the language in which all +# documentation generated by doxygen is written. Doxygen will use this +# information to generate all constant output in the proper language. +# Possible values are: Afrikaans, Arabic, Armenian, Brazilian, Catalan, Chinese, +# Chinese-Traditional, Croatian, Czech, Danish, Dutch, English (United States), +# Esperanto, Farsi (Persian), Finnish, French, German, Greek, Hungarian, +# Indonesian, Italian, Japanese, Japanese-en (Japanese with English messages), +# Korean, Korean-en (Korean with English messages), Latvian, Lithuanian, +# Macedonian, Norwegian, Persian (Farsi), Polish, Portuguese, Romanian, Russian, +# Serbian, Serbian-Cyrillic, Slovak, Slovene, Spanish, Swedish, Turkish, +# Ukrainian and Vietnamese. +# The default value is: English. + +OUTPUT_LANGUAGE = English + +# The OUTPUT_TEXT_DIRECTION tag is used to specify the direction in which all +# documentation generated by doxygen is written. Doxygen will use this +# information to generate all generated output in the proper direction. +# Possible values are: None, LTR, RTL and Context. +# The default value is: None. + +OUTPUT_TEXT_DIRECTION = None + +# If the BRIEF_MEMBER_DESC tag is set to YES, doxygen will include brief member +# descriptions after the members that are listed in the file and class +# documentation (similar to Javadoc). Set to NO to disable this. +# The default value is: YES. + +BRIEF_MEMBER_DESC = YES + +# If the REPEAT_BRIEF tag is set to YES, doxygen will prepend the brief +# description of a member or function before the detailed description +# +# Note: If both HIDE_UNDOC_MEMBERS and BRIEF_MEMBER_DESC are set to NO, the +# brief descriptions will be completely suppressed. +# The default value is: YES. + +REPEAT_BRIEF = YES + +# This tag implements a quasi-intelligent brief description abbreviator that is +# used to form the text in various listings. Each string in this list, if found +# as the leading text of the brief description, will be stripped from the text +# and the result, after processing the whole list, is used as the annotated +# text. Otherwise, the brief description is used as-is. If left blank, the +# following values are used ($name is automatically replaced with the name of +# the entity):The $name class, The $name widget, The $name file, is, provides, +# specifies, contains, represents, a, an and the. + +ABBREVIATE_BRIEF = "The $name class" \ + "The $name widget" \ + "The $name file" \ + is \ + provides \ + specifies \ + contains \ + represents \ + a \ + an \ + the + +# If the ALWAYS_DETAILED_SEC and REPEAT_BRIEF tags are both set to YES then +# doxygen will generate a detailed section even if there is only a brief +# description. +# The default value is: NO. + +ALWAYS_DETAILED_SEC = NO + +# If the INLINE_INHERITED_MEMB tag is set to YES, doxygen will show all +# inherited members of a class in the documentation of that class as if those +# members were ordinary class members. Constructors, destructors and assignment +# operators of the base classes will not be shown. +# The default value is: NO. + +INLINE_INHERITED_MEMB = NO + +# If the FULL_PATH_NAMES tag is set to YES, doxygen will prepend the full path +# before files name in the file list and in the header files. If set to NO the +# shortest path that makes the file name unique will be used +# The default value is: YES. + +FULL_PATH_NAMES = YES + +# The STRIP_FROM_PATH tag can be used to strip a user-defined part of the path. +# Stripping is only done if one of the specified strings matches the left-hand +# part of the path. The tag can be used to show relative paths in the file list. +# If left blank the directory from which doxygen is run is used as the path to +# strip. +# +# Note that you can specify absolute paths here, but also relative paths, which +# will be relative from the directory where doxygen is started. +# This tag requires that the tag FULL_PATH_NAMES is set to YES. + +STRIP_FROM_PATH = + +# The STRIP_FROM_INC_PATH tag can be used to strip a user-defined part of the +# path mentioned in the documentation of a class, which tells the reader which +# header file to include in order to use a class. If left blank only the name of +# the header file containing the class definition is used. Otherwise one should +# specify the list of include paths that are normally passed to the compiler +# using the -I flag. + +STRIP_FROM_INC_PATH = + +# If the SHORT_NAMES tag is set to YES, doxygen will generate much shorter (but +# less readable) file names. This can be useful is your file systems doesn't +# support long names like on DOS, Mac, or CD-ROM. +# The default value is: NO. + +SHORT_NAMES = NO + +# If the JAVADOC_AUTOBRIEF tag is set to YES then doxygen will interpret the +# first line (until the first dot) of a Javadoc-style comment as the brief +# description. If set to NO, the Javadoc-style will behave just like regular Qt- +# style comments (thus requiring an explicit @brief command for a brief +# description.) +# The default value is: NO. + +JAVADOC_AUTOBRIEF = NO + +# If the JAVADOC_BANNER tag is set to YES then doxygen will interpret a line +# such as +# /*************** +# as being the beginning of a Javadoc-style comment "banner". If set to NO, the +# Javadoc-style will behave just like regular comments and it will not be +# interpreted by doxygen. +# The default value is: NO. + +JAVADOC_BANNER = NO + +# If the QT_AUTOBRIEF tag is set to YES then doxygen will interpret the first +# line (until the first dot) of a Qt-style comment as the brief description. If +# set to NO, the Qt-style will behave just like regular Qt-style comments (thus +# requiring an explicit \brief command for a brief description.) +# The default value is: NO. + +QT_AUTOBRIEF = NO + +# The MULTILINE_CPP_IS_BRIEF tag can be set to YES to make doxygen treat a +# multi-line C++ special comment block (i.e. a block of //! or /// comments) as +# a brief description. This used to be the default behavior. The new default is +# to treat a multi-line C++ comment block as a detailed description. Set this +# tag to YES if you prefer the old behavior instead. +# +# Note that setting this tag to YES also means that rational rose comments are +# not recognized any more. +# The default value is: NO. + +MULTILINE_CPP_IS_BRIEF = NO + +# If the INHERIT_DOCS tag is set to YES then an undocumented member inherits the +# documentation from any documented member that it re-implements. +# The default value is: YES. + +INHERIT_DOCS = YES + +# If the SEPARATE_MEMBER_PAGES tag is set to YES then doxygen will produce a new +# page for each member. If set to NO, the documentation of a member will be part +# of the file/class/namespace that contains it. +# The default value is: NO. + +SEPARATE_MEMBER_PAGES = NO + +# The TAB_SIZE tag can be used to set the number of spaces in a tab. Doxygen +# uses this value to replace tabs by spaces in code fragments. +# Minimum value: 1, maximum value: 16, default value: 4. + +TAB_SIZE = 4 + +# This tag can be used to specify a number of aliases that act as commands in +# the documentation. An alias has the form: +# name=value +# For example adding +# "sideeffect=@par Side Effects:\n" +# will allow you to put the command \sideeffect (or @sideeffect) in the +# documentation, which will result in a user-defined paragraph with heading +# "Side Effects:". You can put \n's in the value part of an alias to insert +# newlines (in the resulting output). You can put ^^ in the value part of an +# alias to insert a newline as if a physical newline was in the original file. +# When you need a literal { or } or , in the value part of an alias you have to +# escape them by means of a backslash (\), this can lead to conflicts with the +# commands \{ and \} for these it is advised to use the version @{ and @} or use +# a double escape (\\{ and \\}) + +ALIASES = + +# This tag can be used to specify a number of word-keyword mappings (TCL only). +# A mapping has the form "name=value". For example adding "class=itcl::class" +# will allow you to use the command class in the itcl::class meaning. + +TCL_SUBST = + +# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C sources +# only. Doxygen will then generate output that is more tailored for C. For +# instance, some of the names that are used will be different. The list of all +# members will be omitted, etc. +# The default value is: NO. + +OPTIMIZE_OUTPUT_FOR_C = NO + +# Set the OPTIMIZE_OUTPUT_JAVA tag to YES if your project consists of Java or +# Python sources only. Doxygen will then generate output that is more tailored +# for that language. For instance, namespaces will be presented as packages, +# qualified scopes will look different, etc. +# The default value is: NO. + +OPTIMIZE_OUTPUT_JAVA = NO + +# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran +# sources. Doxygen will then generate output that is tailored for Fortran. +# The default value is: NO. + +OPTIMIZE_FOR_FORTRAN = NO + +# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL +# sources. Doxygen will then generate output that is tailored for VHDL. +# The default value is: NO. + +OPTIMIZE_OUTPUT_VHDL = NO + +# Set the OPTIMIZE_OUTPUT_SLICE tag to YES if your project consists of Slice +# sources only. Doxygen will then generate output that is more tailored for that +# language. For instance, namespaces will be presented as modules, types will be +# separated into more groups, etc. +# The default value is: NO. + +OPTIMIZE_OUTPUT_SLICE = NO + +# Doxygen selects the parser to use depending on the extension of the files it +# parses. With this tag you can assign which parser to use for a given +# extension. Doxygen has a built-in mapping, but you can override or extend it +# using this tag. The format is ext=language, where ext is a file extension, and +# language is one of the parsers supported by doxygen: IDL, Java, JavaScript, +# Csharp (C#), C, C++, D, PHP, md (Markdown), Objective-C, Python, Slice, +# Fortran (fixed format Fortran: FortranFixed, free formatted Fortran: +# FortranFree, unknown formatted Fortran: Fortran. In the later case the parser +# tries to guess whether the code is fixed or free formatted code, this is the +# default for Fortran type files), VHDL, tcl. For instance to make doxygen treat +# .inc files as Fortran files (default is PHP), and .f files as C (default is +# Fortran), use: inc=Fortran f=C. +# +# Note: For files without extension you can use no_extension as a placeholder. +# +# Note that for custom extensions you also need to set FILE_PATTERNS otherwise +# the files are not read by doxygen. + +EXTENSION_MAPPING = + +# If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments +# according to the Markdown format, which allows for more readable +# documentation. See https://daringfireball.net/projects/markdown/ for details. +# The output of markdown processing is further processed by doxygen, so you can +# mix doxygen, HTML, and XML commands with Markdown formatting. Disable only in +# case of backward compatibilities issues. +# The default value is: YES. + +MARKDOWN_SUPPORT = YES + +# When the TOC_INCLUDE_HEADINGS tag is set to a non-zero value, all headings up +# to that level are automatically included in the table of contents, even if +# they do not have an id attribute. +# Note: This feature currently applies only to Markdown headings. +# Minimum value: 0, maximum value: 99, default value: 5. +# This tag requires that the tag MARKDOWN_SUPPORT is set to YES. + +TOC_INCLUDE_HEADINGS = 5 + +# When enabled doxygen tries to link words that correspond to documented +# classes, or namespaces to their corresponding documentation. Such a link can +# be prevented in individual cases by putting a % sign in front of the word or +# globally by setting AUTOLINK_SUPPORT to NO. +# The default value is: YES. + +AUTOLINK_SUPPORT = YES + +# If you use STL classes (i.e. std::string, std::vector, etc.) but do not want +# to include (a tag file for) the STL sources as input, then you should set this +# tag to YES in order to let doxygen match functions declarations and +# definitions whose arguments contain STL classes (e.g. func(std::string); +# versus func(std::string) {}). This also make the inheritance and collaboration +# diagrams that involve STL classes more complete and accurate. +# The default value is: NO. + +BUILTIN_STL_SUPPORT = NO + +# If you use Microsoft's C++/CLI language, you should set this option to YES to +# enable parsing support. +# The default value is: NO. + +CPP_CLI_SUPPORT = NO + +# Set the SIP_SUPPORT tag to YES if your project consists of sip (see: +# https://www.riverbankcomputing.com/software/sip/intro) sources only. Doxygen +# will parse them like normal C++ but will assume all classes use public instead +# of private inheritance when no explicit protection keyword is present. +# The default value is: NO. + +SIP_SUPPORT = NO + +# For Microsoft's IDL there are propget and propput attributes to indicate +# getter and setter methods for a property. Setting this option to YES will make +# doxygen to replace the get and set methods by a property in the documentation. +# This will only work if the methods are indeed getting or setting a simple +# type. If this is not the case, or you want to show the methods anyway, you +# should set this option to NO. +# The default value is: YES. + +IDL_PROPERTY_SUPPORT = YES + +# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC +# tag is set to YES then doxygen will reuse the documentation of the first +# member in the group (if any) for the other members of the group. By default +# all members of a group must be documented explicitly. +# The default value is: NO. + +DISTRIBUTE_GROUP_DOC = NO + +# If one adds a struct or class to a group and this option is enabled, then also +# any nested class or struct is added to the same group. By default this option +# is disabled and one has to add nested compounds explicitly via \ingroup. +# The default value is: NO. + +GROUP_NESTED_COMPOUNDS = NO + +# Set the SUBGROUPING tag to YES to allow class member groups of the same type +# (for instance a group of public functions) to be put as a subgroup of that +# type (e.g. under the Public Functions section). Set it to NO to prevent +# subgrouping. Alternatively, this can be done per class using the +# \nosubgrouping command. +# The default value is: YES. + +SUBGROUPING = YES + +# When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and unions +# are shown inside the group in which they are included (e.g. using \ingroup) +# instead of on a separate page (for HTML and Man pages) or section (for LaTeX +# and RTF). +# +# Note that this feature does not work in combination with +# SEPARATE_MEMBER_PAGES. +# The default value is: NO. + +INLINE_GROUPED_CLASSES = NO + +# When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and unions +# with only public data fields or simple typedef fields will be shown inline in +# the documentation of the scope in which they are defined (i.e. file, +# namespace, or group documentation), provided this scope is documented. If set +# to NO, structs, classes, and unions are shown on a separate page (for HTML and +# Man pages) or section (for LaTeX and RTF). +# The default value is: NO. + +INLINE_SIMPLE_STRUCTS = NO + +# When TYPEDEF_HIDES_STRUCT tag is enabled, a typedef of a struct, union, or +# enum is documented as struct, union, or enum with the name of the typedef. So +# typedef struct TypeS {} TypeT, will appear in the documentation as a struct +# with name TypeT. When disabled the typedef will appear as a member of a file, +# namespace, or class. And the struct will be named TypeS. This can typically be +# useful for C code in case the coding convention dictates that all compound +# types are typedef'ed and only the typedef is referenced, never the tag name. +# The default value is: NO. + +TYPEDEF_HIDES_STRUCT = NO + +# The size of the symbol lookup cache can be set using LOOKUP_CACHE_SIZE. This +# cache is used to resolve symbols given their name and scope. Since this can be +# an expensive process and often the same symbol appears multiple times in the +# code, doxygen keeps a cache of pre-resolved symbols. If the cache is too small +# doxygen will become slower. If the cache is too large, memory is wasted. The +# cache size is given by this formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range +# is 0..9, the default is 0, corresponding to a cache size of 2^16=65536 +# symbols. At the end of a run doxygen will report the cache usage and suggest +# the optimal cache size from a speed point of view. +# Minimum value: 0, maximum value: 9, default value: 0. + +LOOKUP_CACHE_SIZE = 0 + +#--------------------------------------------------------------------------- +# Build related configuration options +#--------------------------------------------------------------------------- + +# If the EXTRACT_ALL tag is set to YES, doxygen will assume all entities in +# documentation are documented, even if no documentation was available. Private +# class members and static file members will be hidden unless the +# EXTRACT_PRIVATE respectively EXTRACT_STATIC tags are set to YES. +# Note: This will also disable the warnings about undocumented members that are +# normally produced when WARNINGS is set to YES. +# The default value is: NO. + +EXTRACT_ALL = YES + +# If the EXTRACT_PRIVATE tag is set to YES, all private members of a class will +# be included in the documentation. +# The default value is: NO. + +EXTRACT_PRIVATE = NO + +# If the EXTRACT_PRIV_VIRTUAL tag is set to YES, documented private virtual +# methods of a class will be included in the documentation. +# The default value is: NO. + +EXTRACT_PRIV_VIRTUAL = NO + +# If the EXTRACT_PACKAGE tag is set to YES, all members with package or internal +# scope will be included in the documentation. +# The default value is: NO. + +EXTRACT_PACKAGE = NO + +# If the EXTRACT_STATIC tag is set to YES, all static members of a file will be +# included in the documentation. +# The default value is: NO. + +EXTRACT_STATIC = NO + +# If the EXTRACT_LOCAL_CLASSES tag is set to YES, classes (and structs) defined +# locally in source files will be included in the documentation. If set to NO, +# only classes defined in header files are included. Does not have any effect +# for Java sources. +# The default value is: YES. + +EXTRACT_LOCAL_CLASSES = YES + +# This flag is only useful for Objective-C code. If set to YES, local methods, +# which are defined in the implementation section but not in the interface are +# included in the documentation. If set to NO, only methods in the interface are +# included. +# The default value is: NO. + +EXTRACT_LOCAL_METHODS = NO + +# If this flag is set to YES, the members of anonymous namespaces will be +# extracted and appear in the documentation as a namespace called +# 'anonymous_namespace{file}', where file will be replaced with the base name of +# the file that contains the anonymous namespace. By default anonymous namespace +# are hidden. +# The default value is: NO. + +EXTRACT_ANON_NSPACES = NO + +# If the HIDE_UNDOC_MEMBERS tag is set to YES, doxygen will hide all +# undocumented members inside documented classes or files. If set to NO these +# members will be included in the various overviews, but no documentation +# section is generated. This option has no effect if EXTRACT_ALL is enabled. +# The default value is: NO. + +HIDE_UNDOC_MEMBERS = NO + +# If the HIDE_UNDOC_CLASSES tag is set to YES, doxygen will hide all +# undocumented classes that are normally visible in the class hierarchy. If set +# to NO, these classes will be included in the various overviews. This option +# has no effect if EXTRACT_ALL is enabled. +# The default value is: NO. + +HIDE_UNDOC_CLASSES = NO + +# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, doxygen will hide all friend +# declarations. If set to NO, these declarations will be included in the +# documentation. +# The default value is: NO. + +HIDE_FRIEND_COMPOUNDS = NO + +# If the HIDE_IN_BODY_DOCS tag is set to YES, doxygen will hide any +# documentation blocks found inside the body of a function. If set to NO, these +# blocks will be appended to the function's detailed documentation block. +# The default value is: NO. + +HIDE_IN_BODY_DOCS = NO + +# The INTERNAL_DOCS tag determines if documentation that is typed after a +# \internal command is included. If the tag is set to NO then the documentation +# will be excluded. Set it to YES to include the internal documentation. +# The default value is: NO. + +INTERNAL_DOCS = NO + +# If the CASE_SENSE_NAMES tag is set to NO then doxygen will only generate file +# names in lower-case letters. If set to YES, upper-case letters are also +# allowed. This is useful if you have classes or files whose names only differ +# in case and if your file system supports case sensitive file names. Windows +# (including Cygwin) ands Mac users are advised to set this option to NO. +# The default value is: system dependent. + +CASE_SENSE_NAMES = YES + +# If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with +# their full class and namespace scopes in the documentation. If set to YES, the +# scope will be hidden. +# The default value is: NO. + +HIDE_SCOPE_NAMES = NO + +# If the HIDE_COMPOUND_REFERENCE tag is set to NO (default) then doxygen will +# append additional text to a page's title, such as Class Reference. If set to +# YES the compound reference will be hidden. +# The default value is: NO. + +HIDE_COMPOUND_REFERENCE= NO + +# If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of +# the files that are included by a file in the documentation of that file. +# The default value is: YES. + +SHOW_INCLUDE_FILES = YES + +# If the SHOW_GROUPED_MEMB_INC tag is set to YES then Doxygen will add for each +# grouped member an include statement to the documentation, telling the reader +# which file to include in order to use the member. +# The default value is: NO. + +SHOW_GROUPED_MEMB_INC = NO + +# If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include +# files with double quotes in the documentation rather than with sharp brackets. +# The default value is: NO. + +FORCE_LOCAL_INCLUDES = NO + +# If the INLINE_INFO tag is set to YES then a tag [inline] is inserted in the +# documentation for inline members. +# The default value is: YES. + +INLINE_INFO = YES + +# If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the +# (detailed) documentation of file and class members alphabetically by member +# name. If set to NO, the members will appear in declaration order. +# The default value is: YES. + +SORT_MEMBER_DOCS = YES + +# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief +# descriptions of file, namespace and class members alphabetically by member +# name. If set to NO, the members will appear in declaration order. Note that +# this will also influence the order of the classes in the class list. +# The default value is: NO. + +SORT_BRIEF_DOCS = NO + +# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the +# (brief and detailed) documentation of class members so that constructors and +# destructors are listed first. If set to NO the constructors will appear in the +# respective orders defined by SORT_BRIEF_DOCS and SORT_MEMBER_DOCS. +# Note: If SORT_BRIEF_DOCS is set to NO this option is ignored for sorting brief +# member documentation. +# Note: If SORT_MEMBER_DOCS is set to NO this option is ignored for sorting +# detailed member documentation. +# The default value is: NO. + +SORT_MEMBERS_CTORS_1ST = NO + +# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the hierarchy +# of group names into alphabetical order. If set to NO the group names will +# appear in their defined order. +# The default value is: NO. + +SORT_GROUP_NAMES = NO + +# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be sorted by +# fully-qualified names, including namespaces. If set to NO, the class list will +# be sorted only by class name, not including the namespace part. +# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES. +# Note: This option applies only to the class list, not to the alphabetical +# list. +# The default value is: NO. + +SORT_BY_SCOPE_NAME = NO + +# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper +# type resolution of all parameters of a function it will reject a match between +# the prototype and the implementation of a member function even if there is +# only one candidate or it is obvious which candidate to choose by doing a +# simple string match. By disabling STRICT_PROTO_MATCHING doxygen will still +# accept a match between prototype and implementation in such cases. +# The default value is: NO. + +STRICT_PROTO_MATCHING = NO + +# The GENERATE_TODOLIST tag can be used to enable (YES) or disable (NO) the todo +# list. This list is created by putting \todo commands in the documentation. +# The default value is: YES. + +GENERATE_TODOLIST = YES + +# The GENERATE_TESTLIST tag can be used to enable (YES) or disable (NO) the test +# list. This list is created by putting \test commands in the documentation. +# The default value is: YES. + +GENERATE_TESTLIST = YES + +# The GENERATE_BUGLIST tag can be used to enable (YES) or disable (NO) the bug +# list. This list is created by putting \bug commands in the documentation. +# The default value is: YES. + +GENERATE_BUGLIST = YES + +# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or disable (NO) +# the deprecated list. This list is created by putting \deprecated commands in +# the documentation. +# The default value is: YES. + +GENERATE_DEPRECATEDLIST= YES + +# The ENABLED_SECTIONS tag can be used to enable conditional documentation +# sections, marked by \if ... \endif and \cond +# ... \endcond blocks. + +ENABLED_SECTIONS = + +# The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the +# initial value of a variable or macro / define can have for it to appear in the +# documentation. If the initializer consists of more lines than specified here +# it will be hidden. Use a value of 0 to hide initializers completely. The +# appearance of the value of individual variables and macros / defines can be +# controlled using \showinitializer or \hideinitializer command in the +# documentation regardless of this setting. +# Minimum value: 0, maximum value: 10000, default value: 30. + +MAX_INITIALIZER_LINES = 30 + +# Set the SHOW_USED_FILES tag to NO to disable the list of files generated at +# the bottom of the documentation of classes and structs. If set to YES, the +# list will mention the files that were used to generate the documentation. +# The default value is: YES. + +SHOW_USED_FILES = YES + +# Set the SHOW_FILES tag to NO to disable the generation of the Files page. This +# will remove the Files entry from the Quick Index and from the Folder Tree View +# (if specified). +# The default value is: YES. + +SHOW_FILES = YES + +# Set the SHOW_NAMESPACES tag to NO to disable the generation of the Namespaces +# page. This will remove the Namespaces entry from the Quick Index and from the +# Folder Tree View (if specified). +# The default value is: YES. + +SHOW_NAMESPACES = YES + +# The FILE_VERSION_FILTER tag can be used to specify a program or script that +# doxygen should invoke to get the current version for each file (typically from +# the version control system). Doxygen will invoke the program by executing (via +# popen()) the command command input-file, where command is the value of the +# FILE_VERSION_FILTER tag, and input-file is the name of an input file provided +# by doxygen. Whatever the program writes to standard output is used as the file +# version. For an example see the documentation. + +FILE_VERSION_FILTER = + +# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed +# by doxygen. The layout file controls the global structure of the generated +# output files in an output format independent way. To create the layout file +# that represents doxygen's defaults, run doxygen with the -l option. You can +# optionally specify a file name after the option, if omitted DoxygenLayout.xml +# will be used as the name of the layout file. +# +# Note that if you run doxygen from a directory containing a file called +# DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE +# tag is left empty. + +LAYOUT_FILE = + +# The CITE_BIB_FILES tag can be used to specify one or more bib files containing +# the reference definitions. This must be a list of .bib files. The .bib +# extension is automatically appended if omitted. This requires the bibtex tool +# to be installed. See also https://en.wikipedia.org/wiki/BibTeX for more info. +# For LaTeX the style of the bibliography can be controlled using +# LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the +# search path. See also \cite for info how to create references. + +CITE_BIB_FILES = + +#--------------------------------------------------------------------------- +# Configuration options related to warning and progress messages +#--------------------------------------------------------------------------- + +# The QUIET tag can be used to turn on/off the messages that are generated to +# standard output by doxygen. If QUIET is set to YES this implies that the +# messages are off. +# The default value is: NO. + +QUIET = NO + +# The WARNINGS tag can be used to turn on/off the warning messages that are +# generated to standard error (stderr) by doxygen. If WARNINGS is set to YES +# this implies that the warnings are on. +# +# Tip: Turn warnings on while writing the documentation. +# The default value is: YES. + +WARNINGS = YES + +# If the WARN_IF_UNDOCUMENTED tag is set to YES then doxygen will generate +# warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag +# will automatically be disabled. +# The default value is: YES. + +WARN_IF_UNDOCUMENTED = YES + +# If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for +# potential errors in the documentation, such as not documenting some parameters +# in a documented function, or documenting parameters that don't exist or using +# markup commands wrongly. +# The default value is: YES. + +WARN_IF_DOC_ERROR = YES + +# This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that +# are documented, but have no documentation for their parameters or return +# value. If set to NO, doxygen will only warn about wrong or incomplete +# parameter documentation, but not about the absence of documentation. If +# EXTRACT_ALL is set to YES then this flag will automatically be disabled. +# The default value is: NO. + +WARN_NO_PARAMDOC = NO + +# If the WARN_AS_ERROR tag is set to YES then doxygen will immediately stop when +# a warning is encountered. +# The default value is: NO. + +WARN_AS_ERROR = NO + +# The WARN_FORMAT tag determines the format of the warning messages that doxygen +# can produce. The string should contain the $file, $line, and $text tags, which +# will be replaced by the file and line number from which the warning originated +# and the warning text. Optionally the format may contain $version, which will +# be replaced by the version of the file (if it could be obtained via +# FILE_VERSION_FILTER) +# The default value is: $file:$line: $text. + +WARN_FORMAT = "$file:$line: $text" + +# The WARN_LOGFILE tag can be used to specify a file to which warning and error +# messages should be written. If left blank the output is written to standard +# error (stderr). + +WARN_LOGFILE = + +#--------------------------------------------------------------------------- +# Configuration options related to the input files +#--------------------------------------------------------------------------- + +# The INPUT tag is used to specify the files and/or directories that contain +# documented source files. You may enter file names like myfile.cpp or +# directories like /usr/src/myproject. Separate the files or directories with +# spaces. See also FILE_PATTERNS and EXTENSION_MAPPING +# Note: If this tag is empty the current directory is searched. + +INPUT = include README.md + +# This tag can be used to specify the character encoding of the source files +# that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses +# libiconv (or the iconv built into libc) for the transcoding. See the libiconv +# documentation (see: https://www.gnu.org/software/libiconv/) for the list of +# possible encodings. +# The default value is: UTF-8. + +INPUT_ENCODING = UTF-8 + +# If the value of the INPUT tag contains directories, you can use the +# FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and +# *.h) to filter out the source-files in the directories. +# +# Note that for custom extensions or not directly supported extensions you also +# need to set EXTENSION_MAPPING for the extension otherwise the files are not +# read by doxygen. +# +# If left blank the following patterns are tested:*.c, *.cc, *.cxx, *.cpp, +# *.c++, *.java, *.ii, *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h, +# *.hh, *.hxx, *.hpp, *.h++, *.cs, *.d, *.php, *.php4, *.php5, *.phtml, *.inc, +# *.m, *.markdown, *.md, *.mm, *.dox (to be provided as doxygen C comment), +# *.doc (to be provided as doxygen C comment), *.txt (to be provided as doxygen +# C comment), *.py, *.pyw, *.f90, *.f95, *.f03, *.f08, *.f, *.for, *.tcl, *.vhd, +# *.vhdl, *.ucf, *.qsf and *.ice. + +FILE_PATTERNS = *.c \ + *.cc \ + *.cxx \ + *.cpp \ + *.c++ \ + *.java \ + *.ii \ + *.ixx \ + *.ipp \ + *.i++ \ + *.inl \ + *.idl \ + *.ddl \ + *.odl \ + *.h \ + *.hh \ + *.hxx \ + *.hpp \ + *.h++ \ + *.cs \ + *.d \ + *.php \ + *.php4 \ + *.php5 \ + *.phtml \ + *.inc \ + *.m \ + *.markdown \ + *.md \ + *.mm \ + *.dox \ + *.doc \ + *.txt \ + *.py \ + *.pyw \ + *.f90 \ + *.f95 \ + *.f03 \ + *.f08 \ + *.f \ + *.for \ + *.tcl \ + *.vhd \ + *.vhdl \ + *.ucf \ + *.qsf \ + *.ice + +# The RECURSIVE tag can be used to specify whether or not subdirectories should +# be searched for input files as well. +# The default value is: NO. + +RECURSIVE = YES + +# The EXCLUDE tag can be used to specify files and/or directories that should be +# excluded from the INPUT source files. This way you can easily exclude a +# subdirectory from a directory tree whose root is specified with the INPUT tag. +# +# Note that relative paths are relative to the directory from which doxygen is +# run. + +EXCLUDE = include/small_gicp/benchmark + +# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or +# directories that are symbolic links (a Unix file system feature) are excluded +# from the input. +# The default value is: NO. + +EXCLUDE_SYMLINKS = NO + +# If the value of the INPUT tag contains directories, you can use the +# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude +# certain files from those directories. +# +# Note that the wildcards are matched against the file with absolute path, so to +# exclude all test directories for example use the pattern */test/* + +EXCLUDE_PATTERNS = + +# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names +# (namespaces, classes, functions, etc.) that should be excluded from the +# output. The symbol name can be a fully qualified name, a word, or if the +# wildcard * is used, a substring. Examples: ANamespace, AClass, +# AClass::ANamespace, ANamespace::*Test +# +# Note that the wildcards are matched against the file with absolute path, so to +# exclude all test directories use the pattern */test/* + +EXCLUDE_SYMBOLS = + +# The EXAMPLE_PATH tag can be used to specify one or more files or directories +# that contain example code fragments that are included (see the \include +# command). + +EXAMPLE_PATH = + +# If the value of the EXAMPLE_PATH tag contains directories, you can use the +# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and +# *.h) to filter out the source-files in the directories. If left blank all +# files are included. + +EXAMPLE_PATTERNS = * + +# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be +# searched for input files to be used with the \include or \dontinclude commands +# irrespective of the value of the RECURSIVE tag. +# The default value is: NO. + +EXAMPLE_RECURSIVE = NO + +# The IMAGE_PATH tag can be used to specify one or more files or directories +# that contain images that are to be included in the documentation (see the +# \image command). + +IMAGE_PATH = + +# The INPUT_FILTER tag can be used to specify a program that doxygen should +# invoke to filter for each input file. Doxygen will invoke the filter program +# by executing (via popen()) the command: +# +# +# +# where is the value of the INPUT_FILTER tag, and is the +# name of an input file. Doxygen will then use the output that the filter +# program writes to standard output. If FILTER_PATTERNS is specified, this tag +# will be ignored. +# +# Note that the filter must not add or remove lines; it is applied before the +# code is scanned, but not when the output code is generated. If lines are added +# or removed, the anchors will not be placed correctly. +# +# Note that for custom extensions or not directly supported extensions you also +# need to set EXTENSION_MAPPING for the extension otherwise the files are not +# properly processed by doxygen. + +INPUT_FILTER = + +# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern +# basis. Doxygen will compare the file name with each pattern and apply the +# filter if there is a match. The filters are a list of the form: pattern=filter +# (like *.cpp=my_cpp_filter). See INPUT_FILTER for further information on how +# filters are used. If the FILTER_PATTERNS tag is empty or if none of the +# patterns match the file name, INPUT_FILTER is applied. +# +# Note that for custom extensions or not directly supported extensions you also +# need to set EXTENSION_MAPPING for the extension otherwise the files are not +# properly processed by doxygen. + +FILTER_PATTERNS = + +# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using +# INPUT_FILTER) will also be used to filter the input files that are used for +# producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES). +# The default value is: NO. + +FILTER_SOURCE_FILES = NO + +# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file +# pattern. A pattern will override the setting for FILTER_PATTERN (if any) and +# it is also possible to disable source filtering for a specific pattern using +# *.ext= (so without naming a filter). +# This tag requires that the tag FILTER_SOURCE_FILES is set to YES. + +FILTER_SOURCE_PATTERNS = + +# If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that +# is part of the input, its contents will be placed on the main page +# (index.html). This can be useful if you have a project on for instance GitHub +# and want to reuse the introduction page also for the doxygen output. + +USE_MDFILE_AS_MAINPAGE = README.md + +#--------------------------------------------------------------------------- +# Configuration options related to source browsing +#--------------------------------------------------------------------------- + +# If the SOURCE_BROWSER tag is set to YES then a list of source files will be +# generated. Documented entities will be cross-referenced with these sources. +# +# Note: To get rid of all source code in the generated output, make sure that +# also VERBATIM_HEADERS is set to NO. +# The default value is: NO. + +SOURCE_BROWSER = NO + +# Setting the INLINE_SOURCES tag to YES will include the body of functions, +# classes and enums directly into the documentation. +# The default value is: NO. + +INLINE_SOURCES = NO + +# Setting the STRIP_CODE_COMMENTS tag to YES will instruct doxygen to hide any +# special comment blocks from generated source code fragments. Normal C, C++ and +# Fortran comments will always remain visible. +# The default value is: YES. + +STRIP_CODE_COMMENTS = YES + +# If the REFERENCED_BY_RELATION tag is set to YES then for each documented +# entity all documented functions referencing it will be listed. +# The default value is: NO. + +REFERENCED_BY_RELATION = NO + +# If the REFERENCES_RELATION tag is set to YES then for each documented function +# all documented entities called/used by that function will be listed. +# The default value is: NO. + +REFERENCES_RELATION = NO + +# If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set +# to YES then the hyperlinks from functions in REFERENCES_RELATION and +# REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will +# link to the documentation. +# The default value is: YES. + +REFERENCES_LINK_SOURCE = YES + +# If SOURCE_TOOLTIPS is enabled (the default) then hovering a hyperlink in the +# source code will show a tooltip with additional information such as prototype, +# brief description and links to the definition and documentation. Since this +# will make the HTML file larger and loading of large files a bit slower, you +# can opt to disable this feature. +# The default value is: YES. +# This tag requires that the tag SOURCE_BROWSER is set to YES. + +SOURCE_TOOLTIPS = YES + +# If the USE_HTAGS tag is set to YES then the references to source code will +# point to the HTML generated by the htags(1) tool instead of doxygen built-in +# source browser. The htags tool is part of GNU's global source tagging system +# (see https://www.gnu.org/software/global/global.html). You will need version +# 4.8.6 or higher. +# +# To use it do the following: +# - Install the latest version of global +# - Enable SOURCE_BROWSER and USE_HTAGS in the configuration file +# - Make sure the INPUT points to the root of the source tree +# - Run doxygen as normal +# +# Doxygen will invoke htags (and that will in turn invoke gtags), so these +# tools must be available from the command line (i.e. in the search path). +# +# The result: instead of the source browser generated by doxygen, the links to +# source code will now point to the output of htags. +# The default value is: NO. +# This tag requires that the tag SOURCE_BROWSER is set to YES. + +USE_HTAGS = NO + +# If the VERBATIM_HEADERS tag is set the YES then doxygen will generate a +# verbatim copy of the header file for each class for which an include is +# specified. Set to NO to disable this. +# See also: Section \class. +# The default value is: YES. + +VERBATIM_HEADERS = YES + +# If the CLANG_ASSISTED_PARSING tag is set to YES then doxygen will use the +# clang parser (see: http://clang.llvm.org/) for more accurate parsing at the +# cost of reduced performance. This can be particularly helpful with template +# rich C++ code for which doxygen's built-in parser lacks the necessary type +# information. +# Note: The availability of this option depends on whether or not doxygen was +# generated with the -Duse_libclang=ON option for CMake. +# The default value is: NO. + +CLANG_ASSISTED_PARSING = NO + +# If clang assisted parsing is enabled you can provide the compiler with command +# line options that you would normally use when invoking the compiler. Note that +# the include paths will already be set by doxygen for the files and directories +# specified with INPUT and INCLUDE_PATH. +# This tag requires that the tag CLANG_ASSISTED_PARSING is set to YES. + +CLANG_OPTIONS = + +# If clang assisted parsing is enabled you can provide the clang parser with the +# path to the compilation database (see: +# http://clang.llvm.org/docs/HowToSetupToolingForLLVM.html) used when the files +# were built. This is equivalent to specifying the "-p" option to a clang tool, +# such as clang-check. These options will then be passed to the parser. +# Note: The availability of this option depends on whether or not doxygen was +# generated with the -Duse_libclang=ON option for CMake. + +CLANG_DATABASE_PATH = + +#--------------------------------------------------------------------------- +# Configuration options related to the alphabetical class index +#--------------------------------------------------------------------------- + +# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index of all +# compounds will be generated. Enable this if the project contains a lot of +# classes, structs, unions or interfaces. +# The default value is: YES. + +ALPHABETICAL_INDEX = YES + +# The COLS_IN_ALPHA_INDEX tag can be used to specify the number of columns in +# which the alphabetical index list will be split. +# Minimum value: 1, maximum value: 20, default value: 5. +# This tag requires that the tag ALPHABETICAL_INDEX is set to YES. + +COLS_IN_ALPHA_INDEX = 5 + +# In case all classes in a project start with a common prefix, all classes will +# be put under the same header in the alphabetical index. The IGNORE_PREFIX tag +# can be used to specify a prefix (or a list of prefixes) that should be ignored +# while generating the index headers. +# This tag requires that the tag ALPHABETICAL_INDEX is set to YES. + +IGNORE_PREFIX = + +#--------------------------------------------------------------------------- +# Configuration options related to the HTML output +#--------------------------------------------------------------------------- + +# If the GENERATE_HTML tag is set to YES, doxygen will generate HTML output +# The default value is: YES. + +GENERATE_HTML = YES + +# The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a +# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of +# it. +# The default directory is: html. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_OUTPUT = html + +# The HTML_FILE_EXTENSION tag can be used to specify the file extension for each +# generated HTML page (for example: .htm, .php, .asp). +# The default value is: .html. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_FILE_EXTENSION = .html + +# The HTML_HEADER tag can be used to specify a user-defined HTML header file for +# each generated HTML page. If the tag is left blank doxygen will generate a +# standard header. +# +# To get valid HTML the header file that includes any scripts and style sheets +# that doxygen needs, which is dependent on the configuration options used (e.g. +# the setting GENERATE_TREEVIEW). It is highly recommended to start with a +# default header using +# doxygen -w html new_header.html new_footer.html new_stylesheet.css +# YourConfigFile +# and then modify the file new_header.html. See also section "Doxygen usage" +# for information on how to generate the default header that doxygen normally +# uses. +# Note: The header is subject to change so you typically have to regenerate the +# default header when upgrading to a newer version of doxygen. For a description +# of the possible markers and block names see the documentation. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_HEADER = + +# The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each +# generated HTML page. If the tag is left blank doxygen will generate a standard +# footer. See HTML_HEADER for more information on how to generate a default +# footer and what special commands can be used inside the footer. See also +# section "Doxygen usage" for information on how to generate the default footer +# that doxygen normally uses. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_FOOTER = + +# The HTML_STYLESHEET tag can be used to specify a user-defined cascading style +# sheet that is used by each HTML page. It can be used to fine-tune the look of +# the HTML output. If left blank doxygen will generate a default style sheet. +# See also section "Doxygen usage" for information on how to generate the style +# sheet that doxygen normally uses. +# Note: It is recommended to use HTML_EXTRA_STYLESHEET instead of this tag, as +# it is more robust and this tag (HTML_STYLESHEET) will in the future become +# obsolete. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_STYLESHEET = + +# The HTML_EXTRA_STYLESHEET tag can be used to specify additional user-defined +# cascading style sheets that are included after the standard style sheets +# created by doxygen. Using this option one can overrule certain style aspects. +# This is preferred over using HTML_STYLESHEET since it does not replace the +# standard style sheet and is therefore more robust against future updates. +# Doxygen will copy the style sheet files to the output directory. +# Note: The order of the extra style sheet files is of importance (e.g. the last +# style sheet in the list overrules the setting of the previous ones in the +# list). For an example see the documentation. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_EXTRA_STYLESHEET = + +# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or +# other source files which should be copied to the HTML output directory. Note +# that these files will be copied to the base HTML output directory. Use the +# $relpath^ marker in the HTML_HEADER and/or HTML_FOOTER files to load these +# files. In the HTML_STYLESHEET file, use the file name only. Also note that the +# files will be copied as-is; there are no commands or markers available. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_EXTRA_FILES = + +# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen +# will adjust the colors in the style sheet and background images according to +# this color. Hue is specified as an angle on a colorwheel, see +# https://en.wikipedia.org/wiki/Hue for more information. For instance the value +# 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300 +# purple, and 360 is red again. +# Minimum value: 0, maximum value: 359, default value: 220. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_COLORSTYLE_HUE = 220 + +# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors +# in the HTML output. For a value of 0 the output will use grayscales only. A +# value of 255 will produce the most vivid colors. +# Minimum value: 0, maximum value: 255, default value: 100. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_COLORSTYLE_SAT = 100 + +# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the +# luminance component of the colors in the HTML output. Values below 100 +# gradually make the output lighter, whereas values above 100 make the output +# darker. The value divided by 100 is the actual gamma applied, so 80 represents +# a gamma of 0.8, The value 220 represents a gamma of 2.2, and 100 does not +# change the gamma. +# Minimum value: 40, maximum value: 240, default value: 80. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_COLORSTYLE_GAMMA = 80 + +# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML +# page will contain the date and time when the page was generated. Setting this +# to YES can help to show when doxygen was last run and thus if the +# documentation is up to date. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_TIMESTAMP = NO + +# If the HTML_DYNAMIC_MENUS tag is set to YES then the generated HTML +# documentation will contain a main index with vertical navigation menus that +# are dynamically created via JavaScript. If disabled, the navigation index will +# consists of multiple levels of tabs that are statically embedded in every HTML +# page. Disable this option to support browsers that do not have JavaScript, +# like the Qt help browser. +# The default value is: YES. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_DYNAMIC_MENUS = YES + +# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML +# documentation will contain sections that can be hidden and shown after the +# page has loaded. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_DYNAMIC_SECTIONS = NO + +# With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries +# shown in the various tree structured indices initially; the user can expand +# and collapse entries dynamically later on. Doxygen will expand the tree to +# such a level that at most the specified number of entries are visible (unless +# a fully collapsed tree already exceeds this amount). So setting the number of +# entries 1 will produce a full collapsed tree by default. 0 is a special value +# representing an infinite number of entries and will result in a full expanded +# tree by default. +# Minimum value: 0, maximum value: 9999, default value: 100. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_INDEX_NUM_ENTRIES = 100 + +# If the GENERATE_DOCSET tag is set to YES, additional index files will be +# generated that can be used as input for Apple's Xcode 3 integrated development +# environment (see: https://developer.apple.com/xcode/), introduced with OSX +# 10.5 (Leopard). To create a documentation set, doxygen will generate a +# Makefile in the HTML output directory. Running make will produce the docset in +# that directory and running make install will install the docset in +# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find it at +# startup. See https://developer.apple.com/library/archive/featuredarticles/Doxy +# genXcode/_index.html for more information. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_DOCSET = NO + +# This tag determines the name of the docset feed. A documentation feed provides +# an umbrella under which multiple documentation sets from a single provider +# (such as a company or product suite) can be grouped. +# The default value is: Doxygen generated docs. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_FEEDNAME = "Doxygen generated docs" + +# This tag specifies a string that should uniquely identify the documentation +# set bundle. This should be a reverse domain-name style string, e.g. +# com.mycompany.MyDocSet. Doxygen will append .docset to the name. +# The default value is: org.doxygen.Project. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_BUNDLE_ID = org.doxygen.Project + +# The DOCSET_PUBLISHER_ID tag specifies a string that should uniquely identify +# the documentation publisher. This should be a reverse domain-name style +# string, e.g. com.mycompany.MyDocSet.documentation. +# The default value is: org.doxygen.Publisher. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_PUBLISHER_ID = org.doxygen.Publisher + +# The DOCSET_PUBLISHER_NAME tag identifies the documentation publisher. +# The default value is: Publisher. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_PUBLISHER_NAME = Publisher + +# If the GENERATE_HTMLHELP tag is set to YES then doxygen generates three +# additional HTML index files: index.hhp, index.hhc, and index.hhk. The +# index.hhp is a project file that can be read by Microsoft's HTML Help Workshop +# (see: https://www.microsoft.com/en-us/download/details.aspx?id=21138) on +# Windows. +# +# The HTML Help Workshop contains a compiler that can convert all HTML output +# generated by doxygen into a single compiled HTML file (.chm). Compiled HTML +# files are now used as the Windows 98 help format, and will replace the old +# Windows help format (.hlp) on all Windows platforms in the future. Compressed +# HTML files also contain an index, a table of contents, and you can search for +# words in the documentation. The HTML workshop also contains a viewer for +# compressed HTML files. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_HTMLHELP = NO + +# The CHM_FILE tag can be used to specify the file name of the resulting .chm +# file. You can add a path in front of the file if the result should not be +# written to the html output directory. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +CHM_FILE = + +# The HHC_LOCATION tag can be used to specify the location (absolute path +# including file name) of the HTML help compiler (hhc.exe). If non-empty, +# doxygen will try to run the HTML help compiler on the generated index.hhp. +# The file has to be specified with full path. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +HHC_LOCATION = + +# The GENERATE_CHI flag controls if a separate .chi index file is generated +# (YES) or that it should be included in the master .chm file (NO). +# The default value is: NO. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +GENERATE_CHI = NO + +# The CHM_INDEX_ENCODING is used to encode HtmlHelp index (hhk), content (hhc) +# and project file content. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +CHM_INDEX_ENCODING = + +# The BINARY_TOC flag controls whether a binary table of contents is generated +# (YES) or a normal table of contents (NO) in the .chm file. Furthermore it +# enables the Previous and Next buttons. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +BINARY_TOC = NO + +# The TOC_EXPAND flag can be set to YES to add extra items for group members to +# the table of contents of the HTML help documentation and to the tree view. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +TOC_EXPAND = NO + +# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and +# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated that +# can be used as input for Qt's qhelpgenerator to generate a Qt Compressed Help +# (.qch) of the generated HTML documentation. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_QHP = NO + +# If the QHG_LOCATION tag is specified, the QCH_FILE tag can be used to specify +# the file name of the resulting .qch file. The path specified is relative to +# the HTML output folder. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QCH_FILE = + +# The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help +# Project output. For more information please see Qt Help Project / Namespace +# (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#namespace). +# The default value is: org.doxygen.Project. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_NAMESPACE = org.doxygen.Project + +# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating Qt +# Help Project output. For more information please see Qt Help Project / Virtual +# Folders (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#virtual- +# folders). +# The default value is: doc. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_VIRTUAL_FOLDER = doc + +# If the QHP_CUST_FILTER_NAME tag is set, it specifies the name of a custom +# filter to add. For more information please see Qt Help Project / Custom +# Filters (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom- +# filters). +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_CUST_FILTER_NAME = + +# The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the +# custom filter to add. For more information please see Qt Help Project / Custom +# Filters (see: https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom- +# filters). +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_CUST_FILTER_ATTRS = + +# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this +# project's filter section matches. Qt Help Project / Filter Attributes (see: +# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#filter-attributes). +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_SECT_FILTER_ATTRS = + +# The QHG_LOCATION tag can be used to specify the location of Qt's +# qhelpgenerator. If non-empty doxygen will try to run qhelpgenerator on the +# generated .qhp file. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHG_LOCATION = + +# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be +# generated, together with the HTML files, they form an Eclipse help plugin. To +# install this plugin and make it available under the help contents menu in +# Eclipse, the contents of the directory containing the HTML and XML files needs +# to be copied into the plugins directory of eclipse. The name of the directory +# within the plugins directory should be the same as the ECLIPSE_DOC_ID value. +# After copying Eclipse needs to be restarted before the help appears. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_ECLIPSEHELP = NO + +# A unique identifier for the Eclipse help plugin. When installing the plugin +# the directory name containing the HTML and XML files should also have this +# name. Each documentation set should have its own identifier. +# The default value is: org.doxygen.Project. +# This tag requires that the tag GENERATE_ECLIPSEHELP is set to YES. + +ECLIPSE_DOC_ID = org.doxygen.Project + +# If you want full control over the layout of the generated HTML pages it might +# be necessary to disable the index and replace it with your own. The +# DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs) at top +# of each HTML page. A value of NO enables the index and the value YES disables +# it. Since the tabs in the index contain the same information as the navigation +# tree, you can set this option to YES if you also set GENERATE_TREEVIEW to YES. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +DISABLE_INDEX = NO + +# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index +# structure should be generated to display hierarchical information. If the tag +# value is set to YES, a side panel will be generated containing a tree-like +# index structure (just like the one that is generated for HTML Help). For this +# to work a browser that supports JavaScript, DHTML, CSS and frames is required +# (i.e. any modern browser). Windows users are probably better off using the +# HTML help feature. Via custom style sheets (see HTML_EXTRA_STYLESHEET) one can +# further fine-tune the look of the index. As an example, the default style +# sheet generated by doxygen has an example that shows how to put an image at +# the root of the tree instead of the PROJECT_NAME. Since the tree basically has +# the same information as the tab index, you could consider setting +# DISABLE_INDEX to YES when enabling this option. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_TREEVIEW = NO + +# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that +# doxygen will group on one line in the generated HTML documentation. +# +# Note that a value of 0 will completely suppress the enum values from appearing +# in the overview section. +# Minimum value: 0, maximum value: 20, default value: 4. +# This tag requires that the tag GENERATE_HTML is set to YES. + +ENUM_VALUES_PER_LINE = 4 + +# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be used +# to set the initial width (in pixels) of the frame in which the tree is shown. +# Minimum value: 0, maximum value: 1500, default value: 250. +# This tag requires that the tag GENERATE_HTML is set to YES. + +TREEVIEW_WIDTH = 250 + +# If the EXT_LINKS_IN_WINDOW option is set to YES, doxygen will open links to +# external symbols imported via tag files in a separate window. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +EXT_LINKS_IN_WINDOW = NO + +# Use this tag to change the font size of LaTeX formulas included as images in +# the HTML documentation. When you change the font size after a successful +# doxygen run you need to manually remove any form_*.png images from the HTML +# output directory to force them to be regenerated. +# Minimum value: 8, maximum value: 50, default value: 10. +# This tag requires that the tag GENERATE_HTML is set to YES. + +FORMULA_FONTSIZE = 10 + +# Use the FORMULA_TRANSPARENT tag to determine whether or not the images +# generated for formulas are transparent PNGs. Transparent PNGs are not +# supported properly for IE 6.0, but are supported on all modern browsers. +# +# Note that when changing this option you need to delete any form_*.png files in +# the HTML output directory before the changes have effect. +# The default value is: YES. +# This tag requires that the tag GENERATE_HTML is set to YES. + +FORMULA_TRANSPARENT = YES + +# The FORMULA_MACROFILE can contain LaTeX \newcommand and \renewcommand commands +# to create new LaTeX commands to be used in formulas as building blocks. See +# the section "Including formulas" for details. + +FORMULA_MACROFILE = + +# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see +# https://www.mathjax.org) which uses client side JavaScript for the rendering +# instead of using pre-rendered bitmaps. Use this if you do not have LaTeX +# installed or if you want to formulas look prettier in the HTML output. When +# enabled you may also need to install MathJax separately and configure the path +# to it using the MATHJAX_RELPATH option. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +USE_MATHJAX = NO + +# When MathJax is enabled you can set the default output format to be used for +# the MathJax output. See the MathJax site (see: +# http://docs.mathjax.org/en/latest/output.html) for more details. +# Possible values are: HTML-CSS (which is slower, but has the best +# compatibility), NativeMML (i.e. MathML) and SVG. +# The default value is: HTML-CSS. +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_FORMAT = HTML-CSS + +# When MathJax is enabled you need to specify the location relative to the HTML +# output directory using the MATHJAX_RELPATH option. The destination directory +# should contain the MathJax.js script. For instance, if the mathjax directory +# is located at the same level as the HTML output directory, then +# MATHJAX_RELPATH should be ../mathjax. The default value points to the MathJax +# Content Delivery Network so you can quickly see the result without installing +# MathJax. However, it is strongly recommended to install a local copy of +# MathJax from https://www.mathjax.org before deployment. +# The default value is: https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/. +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_RELPATH = https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/ + +# The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax +# extension names that should be enabled during MathJax rendering. For example +# MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_EXTENSIONS = + +# The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces +# of code that will be used on startup of the MathJax code. See the MathJax site +# (see: http://docs.mathjax.org/en/latest/output.html) for more details. For an +# example see the documentation. +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_CODEFILE = + +# When the SEARCHENGINE tag is enabled doxygen will generate a search box for +# the HTML output. The underlying search engine uses javascript and DHTML and +# should work on any modern browser. Note that when using HTML help +# (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets (GENERATE_DOCSET) +# there is already a search function so this one should typically be disabled. +# For large projects the javascript based search engine can be slow, then +# enabling SERVER_BASED_SEARCH may provide a better solution. It is possible to +# search using the keyboard; to jump to the search box use + S +# (what the is depends on the OS and browser, but it is typically +# , /