diff options
Diffstat (limited to 'example/Persistent_cohomology/rips_persistence_step_by_step.cpp')
| -rw-r--r-- | example/Persistent_cohomology/rips_persistence_step_by_step.cpp | 217 |
1 files changed, 217 insertions, 0 deletions
diff --git a/example/Persistent_cohomology/rips_persistence_step_by_step.cpp b/example/Persistent_cohomology/rips_persistence_step_by_step.cpp new file mode 100644 index 00000000..554eeba6 --- /dev/null +++ b/example/Persistent_cohomology/rips_persistence_step_by_step.cpp @@ -0,0 +1,217 @@ +/* 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 + * + * Copyright (C) 2014 INRIA Sophia Antipolis-Méditerranée (France) + * + * 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/>. + */ + +#include <gudhi/graph_simplicial_complex.h> +#include <gudhi/distance_functions.h> +#include <gudhi/Simplex_tree.h> +#include <gudhi/Persistent_cohomology.h> +#include <gudhi/Points_off_io.h> + +#include <boost/program_options.hpp> + +#include <string> +#include <vector> +#include <limits> // infinity +#include <utility> // for pair +#include <map> + +// ---------------------------------------------------------------------------- +// rips_persistence_step_by_step is an example of each step that is required to +// build a Rips over a Simplex_tree. Please refer to rips_persistence to see +// how to do the same thing with the Rips_complex wrapper for less detailed +// steps. +// ---------------------------------------------------------------------------- + +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; +using Vertex_handle = Simplex_tree::Vertex_handle; +using Filtration_value = Simplex_tree::Filtration_value; +using Graph_t = boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS +, boost::property < vertex_filtration_t, Filtration_value > +, boost::property < edge_filtration_t, Filtration_value > +>; +using Edge_t = std::pair< Vertex_handle, Vertex_handle >; + +template< typename InputPointRange, typename Distance > +Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold, Distance distance); + +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >; +using Point = std::vector<double>; +using Points_off_reader = Gudhi::Points_off_reader<Point>; + +void program_options(int argc, char * argv[] + , std::string & off_file_points + , std::string & filediag + , Filtration_value & threshold + , int & dim_max + , int & p + , Filtration_value & min_persistence); + +int main(int argc, char * argv[]) { + std::string off_file_points; + std::string filediag; + Filtration_value threshold; + int dim_max; + int p; + Filtration_value min_persistence; + + program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); + + // Extract the points from the file filepoints + Points_off_reader off_reader(off_file_points); + + // Compute the proximity graph of the points + Graph_t prox_graph = compute_proximity_graph(off_reader.get_point_cloud(), threshold + , Gudhi::Euclidean_distance()); + + // Construct the Rips complex in a Simplex Tree + Simplex_tree st; + // insert the proximity graph in the simplex tree + st.insert_graph(prox_graph); + // expand the graph until dimension dim_max + st.expansion(dim_max); + + std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; + std::cout << " and has dimension " << st.dimension() << " \n"; + + // Sort the simplices in the order of the filtration + st.initialize_filtration(); + + // Compute the persistence diagram of the complex + Persistent_cohomology pcoh(st); + // initializes the coefficient field for homology + pcoh.init_coefficients(p); + + pcoh.compute_persistent_cohomology(min_persistence); + + // Output the diagram in filediag + if (filediag.empty()) { + pcoh.output_diagram(); + } else { + std::ofstream out(filediag); + pcoh.output_diagram(out); + out.close(); + } + + return 0; +} + +void program_options(int argc, char * argv[] + , std::string & off_file_points + , std::string & filediag + , Filtration_value & threshold + , int & dim_max + , int & p + , Filtration_value & min_persistence) { + namespace po = boost::program_options; + po::options_description hidden("Hidden options"); + hidden.add_options() + ("input-file", po::value<std::string>(&off_file_points), + "Name of an OFF file containing a point set.\n"); + + po::options_description visible("Allowed options", 100); + visible.add_options() + ("help,h", "produce help message") + ("output-file,o", po::value<std::string>(&filediag)->default_value(std::string()), + "Name of file in which the persistence diagram is written. Default print in std::cout") + ("max-edge-length,r", + po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), + "Maximal length of an edge for the Rips complex construction.") + ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1), + "Maximal dimension of the Rips complex we want to compute.") + ("field-charac,p", po::value<int>(&p)->default_value(11), + "Characteristic p of the coefficient field Z/pZ for computing homology.") + ("min-persistence,m", po::value<Filtration_value>(&min_persistence), + "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length intervals"); + + po::positional_options_description pos; + pos.add("input-file", 1); + + po::options_description all; + all.add(visible).add(hidden); + + po::variables_map vm; + po::store(po::command_line_parser(argc, argv). + options(all).positional(pos).run(), vm); + po::notify(vm); + + if (vm.count("help") || !vm.count("input-file")) { + std::cout << std::endl; + std::cout << "Compute the persistent homology with coefficient field Z/pZ \n"; + std::cout << "of a Rips complex defined on a set of input points.\n \n"; + std::cout << "The output diagram contains one bar per line, written with the convention: \n"; + std::cout << " p dim b d \n"; + std::cout << "where dim is the dimension of the homological feature,\n"; + std::cout << "b and d are respectively the birth and death of the feature and \n"; + std::cout << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl; + + std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; + std::cout << visible << std::endl; + std::abort(); + } +} + +/** Output 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. + * + * The type PointCloud furnishes .begin() and .end() methods, that return + * iterators with value_type Point. + */ +template< typename InputPointRange, typename Distance > +Graph_t compute_proximity_graph(InputPointRange &points, Filtration_value threshold, Distance distance) { + std::vector< Edge_t > edges; + std::vector< Filtration_value > edges_fil; + + Vertex_handle idx_u, idx_v; + Filtration_value fil; + idx_u = 0; + for (auto it_u = points.begin(); it_u != points.end(); ++it_u) { + idx_v = idx_u + 1; + for (auto it_v = it_u + 1; it_v != points.end(); ++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; + } + + Graph_t skel_graph(edges.begin() + , edges.end() + , edges_fil.begin() + , idx_u); // number of points labeled from 0 to idx_u-1 + + auto vertex_prop = boost::get(vertex_filtration_t(), skel_graph); + + boost::graph_traits<Graph_t>::vertex_iterator vi, vi_end; + for (std::tie(vi, vi_end) = boost::vertices(skel_graph); + vi != vi_end; ++vi) { + boost::put(vertex_prop, *vi, 0.); + } + + return skel_graph; +} |