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diff --git a/src/Collapse/include/gudhi/Rips_edge_list.h b/src/Collapse/include/gudhi/Rips_edge_list.h new file mode 100644 index 00000000..b7c4dcff --- /dev/null +++ b/src/Collapse/include/gudhi/Rips_edge_list.h @@ -0,0 +1,184 @@ +/* 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 Siddharth Pritam + * + * 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_edge_list_H_ +#define RIPS_edge_list_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_edge_list { + +/** + * \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_edge_list { + 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_edge_list(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_edge_list(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 egde list (one skeleton) complex from the Rips graph + * + * \tparam EdgeListForRips must meet `EdgeListForRips` concept. + * + * @param[in] edges EdgeListForRips to be created. + * @param[in] dim_max graph expansion for Rips until this given maximal dimension. + * @exception std::invalid_argument In debug mode, if `edges.num_vertices()` does not return 0. + * + */ + template <typename EdgeListForRips> + void create_edges(EdgeListForRips& edge_list) { + GUDHI_CHECK(edges.num_vertices() == 0, + std::invalid_argument("Rips_complex::create_complex - edge list is not empty")); + + // sort the tuple (filteration_valuem, (v1,v2){edge}) + //By default the sort is done on the first element, so here it's filteration value. + std::sort(edges.begin(),edges.end()); + for(size_t i = 0; i < edges.size(); i++ ) + edge_list.emplace_back(edges.at(i)); + + } + + 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) { + edges.clear(); + // 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(fil, idx_u, idx_v); + } + } + } + + // -------------------------------------------------------------------------------------------- + // 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_; + std::vector< std::tuple < Filtration_value, Vertex_handle, Vertex_handle > > edges; + // std::vector< Filtration_value > edges_fil; +}; + +} // namespace rips_complex + +} // namespace Gudhi + +#endif // RIPS_COMPLEX_H_ |