/* 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): Siargey Kachanovich
* 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
* 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/Simplex_tree.h>
#include <gudhi/Euclidean_strong_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>;
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::cout << "Successfully read " << witnesses.size() << " points.\n";
std::cout << "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));
// Compute witness complex
Strong_witness_complex strong_witness_complex(landmarks, witnesses);
strong_witness_complex.create_complex(simplex_tree, max_squared_alpha, lim_d);
std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices \n";
std::cout << " and has dimension " << simplex_tree.dimension() << " \n";
// Sort the simplices in the order of the filtration
// Compute the persistence diagram of the complex
Persistent_cohomology pcoh(simplex_tree);
// 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[], 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.");
po::options_description visible("Allowed options", 100);
Filtration_value default_alpha = std::numeric_limits<Filtration_value>::infinity();
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 std::cout")(
"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 strong witness complex we want to compute.");
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::cout << std::endl;
std::cout << "Compute the persistent homology with coefficient field Z/pZ \n";
std::cout << "of a Strong witness 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;
GUDHI  Version 2.3.0  - C++ library for Topological Data Analysis (TDA) and Higher Dimensional Geometry Understanding.  - Copyright : GPL v3 Generated on Tue Sep 4 2018 14:32:59 for GUDHI by Doxygen 1.8.13