diff options
author | skachano <skachano@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2016-09-28 12:33:22 +0000 |
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committer | skachano <skachano@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2016-09-28 12:33:22 +0000 |
commit | d16822ea1d3cedea66dcddd390becdd4cbb557bb (patch) | |
tree | b1c592e415f43c1be425608db861e5348e61dcf3 /src/Witness_complex/include | |
parent | 1c09c91ddf4d38196a91bbff5ae432fb13be6762 (diff) | |
parent | a138c9ed4fb9770a3612ff4ee0f914942bbe9724 (diff) |
Merged trunk into relaxed witness branch
git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/relaxed-witness@1579 636b058d-ea47-450e-bf9e-a15bfbe3eedb
Former-commit-id: a9ca2e7a968ebf4bb80cfa795965ae78511e8dd4
Diffstat (limited to 'src/Witness_complex/include')
4 files changed, 87 insertions, 88 deletions
diff --git a/src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h b/src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h index 47cd888d..df93155b 100644 --- a/src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h +++ b/src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h @@ -23,7 +23,10 @@ #ifndef LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ #define LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ +#include <boost/range/size.hpp> + #include <limits> // for numeric_limits<> +#include <iterator> #include <algorithm> // for sort #include <vector> @@ -31,13 +34,19 @@ namespace Gudhi { namespace witness_complex { - typedef std::vector<int> typeVectorVertex; + typedef std::vector<int> typeVectorVertex; /** + * \ingroup witness_complex * \brief Landmark choice strategy by iteratively adding the furthest witness from the * current landmark set as the new landmark. * \details It chooses nbL landmarks from a random access range `points` and * writes {witness}*{closest landmarks} matrix in `knn`. + * + * The type KNearestNeighbors can be seen as + * Witness_range<Closest_landmark_range<Vertex_handle>>, where + * Witness_range and Closest_landmark_range are random access ranges + * */ template <typename KNearestNeighbours, @@ -45,7 +54,7 @@ namespace witness_complex { void landmark_choice_by_furthest_point(Point_random_access_range const &points, int nbL, KNearestNeighbours &knn) { - int nb_points = points.end() - points.begin(); + int nb_points = boost::size(points); assert(nb_points >= nbL); // distance matrix witness x landmarks std::vector<std::vector<double>> wit_land_dist(nb_points, std::vector<double>()); @@ -59,6 +68,7 @@ namespace witness_complex { std::vector< double > dist_to_L(nb_points, infty); // vector of current distances to L from points // TODO(SK) Consider using rand_r(...) instead of rand(...) for improved thread safety + // or better yet std::uniform_int_distribution int rand_int = rand() % nb_points; int curr_max_w = rand_int; // For testing purposes a pseudo-random number is used here @@ -67,7 +77,7 @@ namespace witness_complex { chosen_landmarks.push_back(curr_max_w); unsigned i = 0; for (auto& p : points) { - double curr_dist = euclidean_distance(p, *(points.begin() + chosen_landmarks[current_number_of_landmarks])); + double curr_dist = euclidean_distance(p, *(std::begin(points) + chosen_landmarks[current_number_of_landmarks])); wit_land_dist[i].push_back(curr_dist); knn[i].push_back(current_number_of_landmarks); if (curr_dist < dist_to_L[i]) @@ -81,9 +91,9 @@ namespace witness_complex { curr_max_w = i; } } - for (unsigned i = 0; i < points.size(); ++i) - std::sort(knn[i].begin(), - knn[i].end(), + for (int i = 0; i < nb_points; ++i) + std::sort(std::begin(knn[i]), + std::end(knn[i]), [&wit_land_dist, i](int a, int b) { return wit_land_dist[i][a] < wit_land_dist[i][b]; }); } diff --git a/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h b/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h index dc364007..ebf6aad1 100644 --- a/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h +++ b/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h @@ -23,8 +23,11 @@ #ifndef LANDMARK_CHOICE_BY_RANDOM_POINT_H_ #define LANDMARK_CHOICE_BY_RANDOM_POINT_H_ +#include <boost/range/size.hpp> + #include <queue> // for priority_queue<> #include <utility> // for pair<> +#include <iterator> #include <vector> #include <set> @@ -32,9 +35,17 @@ namespace Gudhi { namespace witness_complex { - /** \brief Landmark choice strategy by taking random vertices for landmarks. + /** + * \ingroup witness_complex + * \brief Landmark choice strategy by taking random vertices for landmarks. * \details It chooses nbL distinct landmarks from a random access range `points` * and outputs a matrix {witness}*{closest landmarks} in knn. + * + * The type KNearestNeighbors can be seen as + * Witness_range<Closest_landmark_range<Vertex_handle>>, where + * Witness_range and Closest_landmark_range are random access ranges and + * Vertex_handle is the label type of a vertex in a simplicial complex. + * Closest_landmark_range needs to have push_back operation. */ template <typename KNearestNeighbours, @@ -42,7 +53,7 @@ namespace witness_complex { void landmark_choice_by_random_point(Point_random_access_range const &points, int nbL, KNearestNeighbours &knn) { - int nbP = points.end() - points.begin(); + int nbP = boost::size(points); assert(nbP >= nbL); std::set<int> landmarks; int current_number_of_landmarks = 0; // counter for landmarks @@ -55,12 +66,12 @@ namespace witness_complex { landmarks.insert(chosen_landmark); } - int dim = points.begin()->size(); + int dim = boost::size(*std::begin(points)); typedef std::pair<double, int> dist_i; typedef bool (*comp)(dist_i, dist_i); knn = KNearestNeighbours(nbP); for (int points_i = 0; points_i < nbP; points_i++) { - std::priority_queue<dist_i, std::vector<dist_i>, comp> l_heap([&](dist_i j1, dist_i j2) { + std::priority_queue<dist_i, std::vector<dist_i>, comp> l_heap([](dist_i j1, dist_i j2) { return j1.first > j2.first; }); std::set<int>::iterator landmarks_it; diff --git a/src/Witness_complex/include/gudhi/Witness_complex.h b/src/Witness_complex/include/gudhi/Witness_complex.h index 34cbc882..489cdf11 100644 --- a/src/Witness_complex/include/gudhi/Witness_complex.h +++ b/src/Witness_complex/include/gudhi/Witness_complex.h @@ -28,8 +28,7 @@ #include <boost/graph/adjacency_list.hpp> #include <boost/graph/connected_components.hpp> -#include <boost/container/flat_map.hpp> -#include <boost/iterator/transform_iterator.hpp> +#include <boost/range/size.hpp> #include <gudhi/distance_functions.h> @@ -47,12 +46,13 @@ namespace Gudhi { namespace witness_complex { -/** - \class Witness_complex - \brief Constructs the witness complex for the given set of witnesses and landmarks. - \ingroup witness_complex - */ -template< class Simplicial_complex> +// /* +// * \private +// \class Witness_complex +// \brief Constructs the witness complex for the given set of witnesses and landmarks. +// \ingroup witness_complex +// */ +template< class SimplicialComplex> class Witness_complex { private: struct Active_witness { @@ -65,13 +65,12 @@ class Witness_complex { }; private: - typedef typename Simplicial_complex::Simplex_handle Simplex_handle; - typedef typename Simplicial_complex::Vertex_handle Vertex_handle; + typedef typename SimplicialComplex::Simplex_handle Simplex_handle; + typedef typename SimplicialComplex::Vertex_handle Vertex_handle; typedef std::vector< double > Point_t; typedef std::vector< Point_t > Point_Vector; - // typedef typename Simplicial_complex::Filtration_value Filtration_value; typedef std::vector< Vertex_handle > typeVectorVertex; typedef std::pair< typeVectorVertex, Filtration_value> typeSimplex; typedef std::pair< Simplex_handle, bool > typePairSimplexBool; @@ -81,19 +80,19 @@ class Witness_complex { typedef std::list< Vertex_handle > ActiveWitnessList; private: - int nbL; // Number of landmarks - Simplicial_complex& sc; // Simplicial complex + int nbL_; // Number of landmarks + SimplicialComplex& sc_; // Simplicial complex public: ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////// - /** @name Constructor + /* @name Constructor */ //@{ // Witness_range<Closest_landmark_range<Vertex_handle>> - /** + /* * \brief Iterative construction of the witness complex. * \details The witness complex is written in sc_ basing on a matrix knn of * nearest neighbours of the form {witnesses}x{landmarks}. @@ -109,31 +108,29 @@ class Witness_complex { */ template< typename KNearestNeighbors > Witness_complex(KNearestNeighbors const & knn, - Simplicial_complex & sc_, - int nbL_, - int dim) : nbL(nbL_), sc(sc_) { + int nbL, + int dim, + SimplicialComplex & sc) : nbL_(nbL), sc_(sc) { // Construction of the active witness list - int nbW = knn.size(); + int nbW = boost::size(knn); typeVectorVertex vv; int counter = 0; /* The list of still useful witnesses * it will diminuish in the course of iterations */ ActiveWitnessList active_w; // = new ActiveWitnessList(); - for (int i = 0; i != nbL; ++i) { + for (Vertex_handle i = 0; i != nbL_; ++i) { // initial fill of 0-dimensional simplices // by doing it we don't assume that landmarks are necessarily witnesses themselves anymore counter++; vv = {i}; - sc.insert_simplex(vv); + sc_.insert_simplex(vv); // TODO(SK) Error if not inserted : normally no need here though } int k = 1; /* current dimension in iterative construction */ for (int i = 0; i != nbW; ++i) active_w.push_back(i); - // std::cout << "Successfully added edges" << std::endl; while (!active_w.empty() && k < dim) { - // std::cout << "Started the step k=" << k << std::endl; typename ActiveWitnessList::iterator it = active_w.begin(); while (it != active_w.end()) { typeVectorVertex simplex_vector; @@ -142,9 +139,9 @@ class Witness_complex { if (ok) { for (int i = 0; i != k + 1; ++i) simplex_vector.push_back(knn[*it][i]); - sc.insert_simplex(simplex_vector, 0.0); + sc_.insert_simplex(simplex_vector); // TODO(SK) Error if not inserted : normally no need here though - it++; + ++it; } else { active_w.erase(it++); // First increase the iterator and then erase the previous element } @@ -156,15 +153,13 @@ class Witness_complex { //@} private: - /** \brief Check if the facets of the k-dimensional simplex witnessed + /* \brief Check if the facets of the k-dimensional simplex witnessed * by witness witness_id are already in the complex. * inserted_vertex is the handle of the (k+1)-th vertex witnessed by witness_id */ template <typename KNearestNeighbors> bool all_faces_in(KNearestNeighbors const &knn, int witness_id, int k) { - // std::cout << "All face in with the landmark " << inserted_vertex << std::endl; std::vector< Vertex_handle > facet; - // Vertex_handle curr_vh = curr_sh->first; // CHECK ALL THE FACETS for (int i = 0; i != k + 1; ++i) { facet = {}; @@ -173,9 +168,8 @@ class Witness_complex { facet.push_back(knn[witness_id][j]); } } // endfor - if (sc.find(facet) == sc.null_simplex()) + if (sc_.find(facet) == sc_.null_simplex()) return false; - // std::cout << "++++ finished loop safely\n"; } // endfor return true; } @@ -194,27 +188,25 @@ class Witness_complex { } public: - /** - * \brief Verification if every simplex in the complex is witnessed by witnesses in knn. - * \param print_output =true will print the witnesses for each simplex - * \remark Added for debugging purposes. - */ + // /* + // * \brief Verification if every simplex in the complex is witnessed by witnesses in knn. + // * \param print_output =true will print the witnesses for each simplex + // * \remark Added for debugging purposes. + // */ template< class KNearestNeighbors > bool is_witness_complex(KNearestNeighbors const & knn, bool print_output) { - // bool final_result = true; - for (Simplex_handle sh : sc.complex_simplex_range()) { + for (Simplex_handle sh : sc_.complex_simplex_range()) { bool is_witnessed = false; typeVectorVertex simplex; int nbV = 0; // number of verticed in the simplex - for (int v : sc.simplex_vertex_range(sh)) + for (Vertex_handle v : sc_.simplex_vertex_range(sh)) simplex.push_back(v); nbV = simplex.size(); for (typeVectorVertex w : knn) { bool has_vertices = true; - for (int v : simplex) + for (Vertex_handle v : simplex) if (std::find(w.begin(), w.begin() + nbV, v) == w.begin() + nbV) { has_vertices = false; - // break; } if (has_vertices) { is_witnessed = true; @@ -242,6 +234,30 @@ class Witness_complex { } }; + /** + * \ingroup witness_complex + * \brief Iterative construction of the witness complex. + * \details The witness complex is written in simplicial complex sc_ + * basing on a matrix knn of + * nearest neighbours of the form {witnesses}x{landmarks}. + * + * The type KNearestNeighbors can be seen as + * Witness_range<Closest_landmark_range<Vertex_handle>>, where + * Witness_range and Closest_landmark_range are random access ranges. + * + * Procedure takes into account at most (dim+1) + * first landmarks from each landmark range to construct simplices. + * + * Landmarks are supposed to be in [0,nbL_-1] + */ + template <class KNearestNeighbors, class SimplicialComplexForWitness> + void witness_complex(KNearestNeighbors const & knn, + int nbL, + int dim, + SimplicialComplexForWitness & sc) { + Witness_complex<SimplicialComplexForWitness>(knn, nbL, dim, sc); + } + } // namespace witness_complex } // namespace Gudhi diff --git a/src/Witness_complex/include/gudhi/Witness_complex_doc.h b/src/Witness_complex/include/gudhi/Witness_complex_doc.h deleted file mode 100644 index e9f78170..00000000 --- a/src/Witness_complex/include/gudhi/Witness_complex_doc.h +++ /dev/null @@ -1,38 +0,0 @@ -#ifndef WITNESS_COMPLEX_DOC_H_ -#define WITNESS_COMPLEX_DOC_H_ - -/** - \defgroup witness_complex Witness complex - - \author Siargey Kachanovich - - \section Definitions - - Witness complex \f$ Wit(W,L) \f$ is a simplicial complex defined on two sets of points in \f$\mathbb{R}^D\f$: - - \li \f$W\f$ set of **witnesses** and - \li \f$L \subseteq W\f$ set of **landmarks**. - - The simplices are based on landmarks - and a simplex belongs to the witness complex if and only if it is witnessed, that is: - - \f$ \sigma \subset L \f$ is witnessed if there exists a point \f$w \in W\f$ such that - w is closer to the vertices of \f$ \sigma \f$ than other points in \f$ L \f$ and all of its faces are witnessed as well. - - \section Implementation - - The principal class of this module is Gudhi::Witness_complex. - - In both cases, the constructor for this class takes a {witness}x{closest_landmarks} table, where each row represents a witness and consists of landmarks sorted by distance to this witness. - This table can be constructed by two additional classes Landmark_choice_by_furthest_point and Landmark_choice_by_random_point also included in the module. - - *\image html "bench_Cy8.png" "Running time as function on number of landmarks" width=10cm - *\image html "bench_sphere.png" "Running time as function on number of witnesses for |L|=300" width=10cm - - - \copyright GNU General Public License v3. - - - */ - -#endif // WITNESS_COMPLEX_DOC_H_ |