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Diffstat (limited to 'src/Rips_complex/include/gudhi/Rips_complex.h')
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diff --git a/src/Rips_complex/include/gudhi/Rips_complex.h b/src/Rips_complex/include/gudhi/Rips_complex.h new file mode 100644 index 00000000..10f674e5 --- /dev/null +++ b/src/Rips_complex/include/gudhi/Rips_complex.h @@ -0,0 +1,154 @@ +/* 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 & 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 1-skeleton graph constructed from a point cloud, containing edges when the edge length is + * less or equal to a given threshold. Edge length is computed from a user given function. + * + * The complex is a template class requiring a Filtration_value type. + * + * \remark When Alpha_complex is constructed with an infinite value of alpha, the complex is a Delaunay complex. + * + * \tparam Filtration_value must meet `SimplicialComplexForRips` concept. + */ +template<typename Filtration_value> +class Rips_complex { + private: + 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 >> Graph_t; + + 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. + * + * The type InputPointRange must be a range for which std::begin and std::end return input iterators on a point. + */ + template<typename InputPointRange, typename Point_d > + Rips_complex(const InputPointRange& points, Filtration_value threshold, + Filtration_value distance(const Point_d& p1,const Point_d& p2)) { + std::vector< std::pair< Vertex_handle, Vertex_handle > > edges; + std::vector< Filtration_value > edges_fil; + std::map< Vertex_handle, Filtration_value > vertices; + + // 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, idx_v; + Filtration_value fil; + idx_u = 0; + for (auto it_u = std::begin(points); it_u != std::end(points); ++it_u) { + idx_v = idx_u + 1; + for (auto it_v = it_u + 1; it_v != std::end(points); ++it_v, ++idx_v) { + fil = distance(*it_u, *it_v); + if (fil <= threshold) { + edges.emplace_back(idx_u, idx_v); + edges_fil.push_back(fil); + } + } + ++idx_u; + } + + // -------------------------------------------------------------------------------------------- + // 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 + rips_skeleton_graph_ = Graph_t(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<Graph_t>::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.); + } + + } + + /** \brief Initializes the simplicial complex from the 1-skeleton 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. + * + * @return true if creation succeeds, false otherwise. + * + */ + template <typename SimplicialComplexForRips> + bool create_complex(SimplicialComplexForRips& complex, int dim_max) { + if (complex.num_vertices() > 0) { + std::cerr << "Rips_complex create_complex - complex is not empty\n"; + return false; // ----- >> + } + + // 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); + + // -------------------------------------------------------------------------------------------- + return true; + } + private: + Graph_t rips_skeleton_graph_; +}; + +} // namespace rips_complex + +} // namespace Gudhi + +#endif // RIPS_COMPLEX_H_ |