Loading...
Searching...
No Matches
weak_witness_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): Siargey Kachanovich
*
* Copyright (C) 2016 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#include <gudhi/Simplex_tree.h>
#include <gudhi/Euclidean_witness_complex.h>
#include <gudhi/Persistent_cohomology.h>
#include <gudhi/Points_off_io.h>
#include <gudhi/pick_n_random_points.h>
#include <gudhi/choose_n_farthest_points.h>
#include <boost/program_options.hpp>
#include <CGAL/Epick_d.h>
#include <string>
#include <vector>
#include <limits> // infinity
using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>;
using Point_d = K::Point_d;
using Point_vector = std::vector<Point_d>;
using Witness_complex = Gudhi::witness_complex::Euclidean_witness_complex<K>;
using SimplexTree = Gudhi::Simplex_tree<>;
using Filtration_value = SimplexTree::Filtration_value;
using Field_Zp = Gudhi::persistent_cohomology::Field_Zp;
using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<SimplexTree, Field_Zp>;
void program_options(int argc, char* argv[], int& nbL, std::string& file_name, std::string& filediag,
Filtration_value& max_squared_alpha, int& p, int& dim_max, Filtration_value& min_persistence);
int main(int argc, char* argv[]) {
std::string file_name;
std::string filediag;
Filtration_value max_squared_alpha;
int p, nbL, lim_d;
Filtration_value min_persistence;
SimplexTree simplex_tree;
program_options(argc, argv, nbL, file_name, filediag, max_squared_alpha, p, lim_d, min_persistence);
// Extract the points from the file file_name
Point_vector witnesses, landmarks;
Gudhi::Points_off_reader<Point_d> off_reader(file_name);
if (!off_reader.is_valid()) {
std::cerr << "Witness complex - Unable to read file " << file_name << "\n";
exit(-1); // ----- >>
}
witnesses = Point_vector(off_reader.get_point_cloud());
std::clog << "Successfully read " << witnesses.size() << " points.\n";
std::clog << "Ambient dimension is " << witnesses[0].dimension() << ".\n";
// Choose landmarks (decomment one of the following two lines)
// Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks));
Gudhi::subsampling::choose_n_farthest_points(K().squared_distance_d_object(), witnesses, nbL,
Gudhi::subsampling::random_starting_point,
std::back_inserter(landmarks));
// Compute witness complex
Witness_complex witness_complex(landmarks, witnesses);
witness_complex.create_complex(simplex_tree, max_squared_alpha, lim_d);
std::clog << "The complex contains " << simplex_tree.num_simplices() << " simplices \n";
std::clog << " and has dimension " << simplex_tree.dimension() << " \n";
// Sort the simplices in the order of the filtration
simplex_tree.initialize_filtration();
// Compute the persistence diagram of the complex
Persistent_cohomology pcoh(simplex_tree);
// 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[], int& nbL, std::string& file_name, std::string& filediag,
Filtration_value& max_squared_alpha, int& p, int& dim_max, Filtration_value& min_persistence) {
namespace po = boost::program_options;
po::options_description hidden("Hidden options");
hidden.add_options()("input-file", po::value<std::string>(&file_name),
"Name of file containing a point set in off format.");
Filtration_value default_alpha = std::numeric_limits<Filtration_value>::infinity();
po::options_description visible("Allowed options", 100);
visible.add_options()("help,h", "produce help message")("landmarks,l", po::value<int>(&nbL),
"Number of landmarks to choose from the point cloud.")(
"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")(
"max-sq-alpha,a", po::value<Filtration_value>(&max_squared_alpha)->default_value(default_alpha),
"Maximal squared relaxation parameter.")(
"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)->default_value(0),
"Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length "
"intervals")("cpx-dimension,d", po::value<int>(&dim_max)->default_value(std::numeric_limits<int>::max()),
"Maximal dimension of the weak witness complex we want to compute.");
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::clog << std::endl;
std::clog << "Compute the persistent homology with coefficient field Z/pZ \n";
std::clog << "of a Weak witness 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;
exit(-1);
}
}
Gudhi::Points_off_reader
OFF file reader implementation in order to read points from an OFF file.
Definition Points_off_io.h:122
Gudhi::Simplex_tree
Simplex Tree data structure for representing simplicial complexes.
Definition Simplex_tree.h:98
Gudhi::Simplex_tree::Filtration_value
Options::Filtration_value Filtration_value
Type for the value of the filtration function.
Definition Simplex_tree.h:105
Gudhi::Simplex_tree::initialize_filtration
void initialize_filtration(bool ignore_infinite_values=false) const
Initializes the filtration cache, i.e. sorts the simplices according to their order in the filtration...
Definition Simplex_tree.h:1200
Gudhi::Simplex_tree::num_simplices
size_t num_simplices() const
Returns the number of simplices in the simplex_tree.
Definition Simplex_tree.h:791
Gudhi::persistent_cohomology::Field_Zp
Structure representing the coefficient field .
Definition Field_Zp.h:27
Gudhi::persistent_cohomology::Persistent_cohomology
Computes the persistent cohomology of a filtered complex.
Definition Persistent_cohomology.h:54
Gudhi::witness_complex::Euclidean_witness_complex
Constructs (weak) witness complex for given sets of witnesses and landmarks in Euclidean space.
Definition Euclidean_witness_complex.h:53
Gudhi::subsampling::choose_n_farthest_points
void choose_n_farthest_points(Distance dist, Point_range const &input_pts, std::size_t final_size, std::size_t starting_point, PointOutputIterator output_it, DistanceOutputIterator dist_it={})
Subsample by an iterative, greedy strategy.
Definition choose_n_farthest_points.h:75
Gudhi::subsampling::random_starting_point
@ random_starting_point
Definition choose_n_farthest_points.h:43