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Diffstat (limited to 'include/gudhi/Rips_complex.h')
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diff --git a/include/gudhi/Rips_complex.h b/include/gudhi/Rips_complex.h deleted file mode 100644 index f0fe57f4..00000000 --- a/include/gudhi/Rips_complex.h +++ /dev/null @@ -1,185 +0,0 @@ -/* This file is part of the Gudhi Library. The Gudhi library - * (Geometric Understanding in Higher Dimensions) is a generic C++ - * library for computational topology. - * - * Author(s): Clément Maria, Pawel Dlotko, Vincent Rouvreau - * - * Copyright (C) 2016 Inria - * - * This program is free software: you can redistribute it and/or modify - * it under the terms of the GNU General Public License as published by - * the Free Software Foundation, either version 3 of the License, or - * (at your option) any later version. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * GNU General Public License for more details. - * - * You should have received a copy of the GNU General Public License - * along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - -#ifndef RIPS_COMPLEX_H_ -#define RIPS_COMPLEX_H_ - -#include <gudhi/Debug_utils.h> -#include <gudhi/graph_simplicial_complex.h> - -#include <boost/graph/adjacency_list.hpp> - -#include <iostream> -#include <vector> -#include <map> -#include <string> -#include <limits> // for numeric_limits -#include <utility> // for pair<> - - -namespace Gudhi { - -namespace rips_complex { - -/** - * \class Rips_complex - * \brief Rips complex data structure. - * - * \ingroup rips_complex - * - * \details - * The data structure is a one skeleton graph, or Rips graph, containing edges when the edge length is less or equal - * to a given threshold. Edge length is computed from a user given point cloud with a given distance function, or a - * distance matrix. - * - * \tparam Filtration_value is the type used to store the filtration values of the simplicial complex. - */ -template<typename Filtration_value> -class Rips_complex { - public: - /** - * \brief Type of the one skeleton graph stored inside the Rips complex structure. - */ - typedef typename boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS - , boost::property < vertex_filtration_t, Filtration_value > - , boost::property < edge_filtration_t, Filtration_value >> OneSkeletonGraph; - - private: - typedef int Vertex_handle; - - public: - /** \brief Rips_complex constructor from a list of points. - * - * @param[in] points Range of points. - * @param[in] threshold Rips value. - * @param[in] distance distance function that returns a `Filtration_value` from 2 given points. - * - * \tparam ForwardPointRange must be a range for which `std::begin` and `std::end` return input iterators on a - * point. - * - * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where - * `Point` is a point from the `ForwardPointRange`, and that returns a `Filtration_value`. - */ - template<typename ForwardPointRange, typename Distance > - Rips_complex(const ForwardPointRange& points, Filtration_value threshold, Distance distance) { - compute_proximity_graph(points, threshold, distance); - } - - /** \brief Rips_complex constructor from a distance matrix. - * - * @param[in] distance_matrix Range of distances. - * @param[in] threshold Rips value. - * - * \tparam DistanceMatrix must have a `size()` method and on which `distance_matrix[i][j]` returns - * the distance between points \f$i\f$ and \f$j\f$ as long as \f$ 0 \leqslant i < j \leqslant - * distance\_matrix.size().\f$ - */ - template<typename DistanceMatrix> - Rips_complex(const DistanceMatrix& distance_matrix, Filtration_value threshold) { - compute_proximity_graph(boost::irange((size_t)0, distance_matrix.size()), threshold, - [&](size_t i, size_t j){return distance_matrix[j][i];}); - } - - /** \brief Initializes the simplicial complex from the Rips graph and expands it until a given maximal - * dimension. - * - * \tparam SimplicialComplexForRips must meet `SimplicialComplexForRips` concept. - * - * @param[in] complex SimplicialComplexForRips to be created. - * @param[in] dim_max graph expansion for Rips until this given maximal dimension. - * @exception std::invalid_argument In debug mode, if `complex.num_vertices()` does not return 0. - * - */ - template <typename SimplicialComplexForRips> - void create_complex(SimplicialComplexForRips& complex, int dim_max) { - GUDHI_CHECK(complex.num_vertices() == 0, - std::invalid_argument("Rips_complex::create_complex - simplicial complex is not empty")); - - // insert the proximity graph in the simplicial complex - complex.insert_graph(rips_skeleton_graph_); - // expand the graph until dimension dim_max - complex.expansion(dim_max); - } - - private: - /** \brief Computes the proximity graph of the points. - * - * If points contains n elements, the proximity graph is the graph with n vertices, and an edge [u,v] iff the - * distance function between points u and v is smaller than threshold. - * - * \tparam ForwardPointRange furnishes `.begin()` and `.end()` - * methods. - * - * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where - * `Point` is a point from the `ForwardPointRange`, and that returns a `Filtration_value`. - */ - template< typename ForwardPointRange, typename Distance > - void compute_proximity_graph(const ForwardPointRange& points, Filtration_value threshold, - Distance distance) { - std::vector< std::pair< Vertex_handle, Vertex_handle > > edges; - std::vector< Filtration_value > edges_fil; - - // Compute the proximity graph of the points. - // If points contains n elements, the proximity graph is the graph with n vertices, and an edge [u,v] iff the - // distance function between points u and v is smaller than threshold. - // -------------------------------------------------------------------------------------------- - // Creates the vector of edges and its filtration values (returned by distance function) - Vertex_handle idx_u = 0; - for (auto it_u = std::begin(points); it_u != std::end(points); ++it_u, ++idx_u) { - Vertex_handle idx_v = idx_u + 1; - for (auto it_v = it_u + 1; it_v != std::end(points); ++it_v, ++idx_v) { - Filtration_value fil = distance(*it_u, *it_v); - if (fil <= threshold) { - edges.emplace_back(idx_u, idx_v); - edges_fil.push_back(fil); - } - } - } - - // -------------------------------------------------------------------------------------------- - // Creates the proximity graph from edges and sets the property with the filtration value. - // Number of points is labeled from 0 to idx_u-1 - // -------------------------------------------------------------------------------------------- - // Do not use : rips_skeleton_graph_ = OneSkeletonGraph(...) -> deep copy of the graph (boost graph is not - // move-enabled) - rips_skeleton_graph_.~OneSkeletonGraph(); - new(&rips_skeleton_graph_)OneSkeletonGraph(edges.begin(), edges.end(), edges_fil.begin(), idx_u); - - auto vertex_prop = boost::get(vertex_filtration_t(), rips_skeleton_graph_); - - using vertex_iterator = typename boost::graph_traits<OneSkeletonGraph>::vertex_iterator; - vertex_iterator vi, vi_end; - for (std::tie(vi, vi_end) = boost::vertices(rips_skeleton_graph_); - vi != vi_end; ++vi) { - boost::put(vertex_prop, *vi, 0.); - } - } - - private: - OneSkeletonGraph rips_skeleton_graph_; -}; - -} // namespace rips_complex - -} // namespace Gudhi - -#endif // RIPS_COMPLEX_H_ |