point_cloud_edge_collapse_rips_persistence.cpp
/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
* See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
* Author(s): Siddharth Pritam, Vincent Rouvreau
*
* Copyright (C) 2020 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#include <gudhi/Flag_complex_edge_collapser.h>
#include <gudhi/Simplex_tree.h>
#include <gudhi/Persistent_cohomology.h>
#include <gudhi/Points_off_io.h>
#include <boost/program_options.hpp>
#include <boost/range/adaptor/transformed.hpp>
#include<utility> // for std::pair
#include<vector>
#include<tuple>
// Types definition
using Point = std::vector<Filtration_value>;
using Vector_of_points = std::vector<Point>;
using Filtered_edge = std::tuple<Vertex_handle, Vertex_handle, Filtration_value>;
using Proximity_graph = Gudhi::Proximity_graph<Simplex_tree>;
void program_options(int argc, char* argv[], std::string& off_file_points, std::string& filediag,
Filtration_value& threshold, int& dim_max, int& p, int& edge_collapse_iter_nb,
Filtration_value& min_persistence);
int main(int argc, char* argv[]) {
std::string off_file_points;
std::string filediag;
double threshold;
int dim_max;
int p;
int edge_collapse_iter_nb;
double min_persistence;
program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, edge_collapse_iter_nb, min_persistence);
std::cout << "The current input values to run the program is: " << std::endl;
std::cout << "min_persistence, threshold, max_complex_dimension, off_file_points, filediag"
<< std::endl;
std::cout << min_persistence << ", " << threshold << ", " << dim_max
<< ", " << off_file_points << ", " << filediag << std::endl;
Gudhi::Points_off_reader<Point> off_reader(off_file_points);
if (!off_reader.is_valid()) {
std::cerr << "Unable to read file " << off_file_points << "\n";
exit(-1); // ----- >>
}
Vector_of_points point_vector = off_reader.get_point_cloud();
if (point_vector.size() <= 0) {
std::cerr << "Empty point cloud." << std::endl;
exit(-1); // ----- >>
}
std::cout << "Successfully read " << point_vector.size() << " point_vector.\n";
std::cout << "Ambient dimension is " << point_vector[0].size() << ".\n";
Proximity_graph proximity_graph = Gudhi::compute_proximity_graph<Simplex_tree>(point_vector,
threshold,
if (num_edges(proximity_graph) <= 0) {
std::cerr << "Total number of edges is zero." << std::endl;
exit(-1);
}
auto edges_from_graph = boost::adaptors::transform(edges(proximity_graph), [&](auto&&edge){
return std::make_tuple(source(edge, proximity_graph),
target(edge, proximity_graph),
get(Gudhi::edge_filtration_t(), proximity_graph, edge));
});
std::vector<Filtered_edge> edges_list(edges_from_graph.begin(), edges_from_graph.end());
std::vector<Filtered_edge> remaining_edges;
for (int iter = 0; iter < edge_collapse_iter_nb; iter++) {
auto remaining_edges = Gudhi::collapse::flag_complex_collapse_edges(edges_list);
edges_list = std::move(remaining_edges);
remaining_edges.clear();
}
Simplex_tree stree;
for (Vertex_handle vertex = 0; static_cast<std::size_t>(vertex) < point_vector.size(); vertex++) {
// insert the vertex with a 0. filtration value just like a Rips
stree.insert_simplex({vertex}, 0.);
}
for (auto filtered_edge : edges_list) {
stree.insert_simplex({std::get<0>(filtered_edge), std::get<1>(filtered_edge)}, std::get<2>(filtered_edge));
}
stree.expansion(dim_max);
std::cout << "The complex contains " << stree.num_simplices() << " simplices after collapse. \n";
std::cout << " and has dimension " << stree.dimension() << " \n";
// Sort the simplices in the order of the filtration
// Compute the persistence diagram of the complex
Persistent_cohomology pcoh(stree);
// initializes the coefficient field for homology
pcoh.init_coefficients(p);
pcoh.compute_persistent_cohomology(min_persistence);
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, int& edge_collapse_iter_nb,
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.")(
"edge-collapse-iterations,i", po::value<int>(&edge_collapse_iter_nb)->default_value(1),
"Number of iterations edge collapse is performed.")(
"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, after edge collapse, 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;
exit(-1);
}
}
Compute the Euclidean distance between two Points given by a range of coordinates....
Definition: distance_functions.h:32
OFF file reader implementation in order to read points from an OFF file.
Definition: Points_off_io.h:122
Options::Filtration_value Filtration_value
Type for the value of the filtration function.
Definition: Simplex_tree.h:86
std::pair< Simplex_handle, bool > insert_simplex(const InputVertexRange &simplex, Filtration_value filtration=0)
Insert a simplex, represented by a range of Vertex_handles, in the simplicial complex.
Definition: Simplex_tree.h:778
void initialize_filtration()
Initializes the filtration cache, i.e. sorts the simplices according to their order in the filtration...
Definition: Simplex_tree.h:912
Options::Vertex_handle Vertex_handle
Type for the vertex handle.
Definition: Simplex_tree.h:94
void expansion(int max_dim)
Expands the Simplex_tree containing only its one skeleton until dimension max_dim.
Definition: Simplex_tree.h:1170
int dimension(Simplex_handle sh)
Returns the dimension of a simplex.
Definition: Simplex_tree.h:600
size_t num_simplices()
returns the number of simplices in the simplex_tree.
Definition: Simplex_tree.h:578
Structure representing the coefficient field .
Definition: Field_Zp.h:27
Computes the persistent cohomology of a filtered complex.
Definition: Persistent_cohomology.h:52
Global distance functions.
Graph simplicial complex methods.
typename boost::adjacency_list< boost::vecS, boost::vecS, boost::directedS, boost::property< vertex_filtration_t, typename SimplicialComplexForProximityGraph::Filtration_value >, boost::property< edge_filtration_t, typename SimplicialComplexForProximityGraph::Filtration_value > > Proximity_graph
Proximity_graph contains the vertices and edges with their filtration values in order to store the re...
Definition: graph_simplicial_complex.h:45
auto flag_complex_collapse_edges(const FilteredEdgeRange &edges)
Implicitly constructs a flag complex from edges as an input, collapses edges while preserving the per...
Definition: Flag_complex_edge_collapser.h:329
Value type for a filtration function on a cell complex.
Definition: FiltrationValue.h:20
Handle type for the vertices of a cell complex.
Definition: VertexHandle.h:15