No Matches
/* 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): Clément Maria
* Copyright (C) 2014 Inria
* Modification(s):
* - YYYY/MM Author: Description of the modification
#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 Proximity_graph = Gudhi::Proximity_graph<Simplex_tree>;
using Point = std::vector<double>;
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
Proximity_graph prox_graph = Gudhi::compute_proximity_graph<Simplex_tree>(off_reader.get_point_cloud(),
// Construct the Rips complex in a Simplex Tree
// insert the proximity graph in the simplex tree
// expand the graph until dimension dim_max
std::clog << "The complex contains " << st.num_simplices() << " simplices \n";
std::clog << " and has dimension " << st.dimension() << " \n";
// Compute the persistence diagram of the complex
// initializes the coefficient field for homology
// Output the diagram in filediag
if (filediag.empty()) {
} else {
std::ofstream out(filediag);
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");
("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);
("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 standard output")
"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;
po::variables_map vm;
po::store(po::command_line_parser(argc, argv).
options(all).positional(pos).run(), vm);
if (vm.count("help") || !vm.count("input-file")) {
std::clog << std::endl;
std::clog << "Compute the persistent homology with coefficient field Z/pZ \n";
std::clog << "of a Rips complex defined on a set of input points.\n \n";
std::clog << "The output diagram contains one bar per line, written with the convention: \n";
std::clog << " p dim b d \n";
std::clog << "where dim is the dimension of the homological feature,\n";
std::clog << "b and d are respectively the birth and death of the feature and \n";
std::clog << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl;
std::clog << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl;
std::clog << visible << std::endl;
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:102
Options::Vertex_handle Vertex_handle
Type for the vertex handle.
Definition: Simplex_tree.h:110
void expansion(int max_dim)
Expands the Simplex_tree containing only its one skeleton until dimension max_dim.
Definition: Simplex_tree.h:1360
size_t num_simplices()
Returns the number of simplices in the simplex_tree.
Definition: Simplex_tree.h:664
void insert_graph(const OneSkeletonGraph &skel_graph)
Inserts a 1-skeleton in an empty Simplex_tree.
Definition: Simplex_tree.h:1272
Structure representing the coefficient field .
Definition: Field_Zp.h:27
Computes the persistent cohomology of a filtered complex.
Definition: Persistent_cohomology.h:54
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
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