/* 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): Vincent Rouvreau * * Copyright (C) 2014 Inria * * Modification(s): * - YYYY/MM Author: Description of the modification */ #include #include #include #include #include #include // to construct a simplex_tree from alpha complex #include #include #include #include #include // for std::ofstream #include // for std::sort using Kernel = CGAL::Epick_d< CGAL::Dimension_tag<3> >; using Point = Kernel::Point_d; using Alpha_complex = Gudhi::alpha_complex::Alpha_complex; using Simplex_tree = Gudhi::Simplex_tree<>; using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology< Simplex_tree, Gudhi::persistent_cohomology::Field_Zp >; std::vector random_points() { // Instanciate a random point generator CGAL::Random rng(0); // Generate "points_number" random points in a vector std::vector points; // Generates 1000 random 3D points on a sphere of radius 4.0 CGAL::Random_points_on_sphere_d rand_outside(3, 4.0, rng); CGAL::cpp11::copy_n(rand_outside, 1000, std::back_inserter(points)); // Generates 2000 random 3D points in a sphere of radius 3.0 CGAL::Random_points_in_ball_d rand_inside(3, 3.0, rng); CGAL::cpp11::copy_n(rand_inside, 2000, std::back_inserter(points)); return points; } /* * Compare two intervals by dimension, then by length. */ struct cmp_intervals_by_dim_then_length { explicit cmp_intervals_by_dim_then_length(Simplex_tree * sc) : sc_(sc) { } template bool operator()(const Persistent_interval & p1, const Persistent_interval & p2) { if (sc_->dimension(get < 0 > (p1)) == sc_->dimension(get < 0 > (p2))) return (sc_->filtration(get < 1 > (p1)) - sc_->filtration(get < 0 > (p1)) > sc_->filtration(get < 1 > (p2)) - sc_->filtration(get < 0 > (p2))); else return (sc_->dimension(get < 0 > (p1)) > sc_->dimension(get < 0 > (p2))); } Simplex_tree* sc_; }; int main(int argc, char **argv) { std::vector points = random_points(); std::cout << "Points size=" << points.size() << std::endl; // Alpha complex persistence computation from generated points Alpha_complex alpha_complex_from_points(points); std::cout << "alpha_complex_from_points" << std::endl; Simplex_tree simplex; std::cout << "simplex" << std::endl; if (alpha_complex_from_points.create_complex(simplex, 0.6)) { std::cout << "simplex" << std::endl; // ---------------------------------------------------------------------------- // Display information about the alpha complex // ---------------------------------------------------------------------------- std::cout << "Simplicial complex is of dimension " << simplex.dimension() << " - " << simplex.num_simplices() << " simplices - " << simplex.num_vertices() << " vertices." << std::endl; // Sort the simplices in the order of the filtration simplex.initialize_filtration(); std::cout << "Simplex_tree dim: " << simplex.dimension() << std::endl; Persistent_cohomology pcoh(simplex); // initializes the coefficient field for homology - Z/3Z pcoh.init_coefficients(3); pcoh.compute_persistent_cohomology(0.2); // Custom sort and output persistence cmp_intervals_by_dim_then_length cmp(&simplex); auto persistent_pairs = pcoh.get_persistent_pairs(); std::sort(std::begin(persistent_pairs), std::end(persistent_pairs), cmp); for (auto pair : persistent_pairs) { std::cout << simplex.dimension(get<0>(pair)) << " " << simplex.filtration(get<0>(pair)) << " " << simplex.filtration(get<1>(pair)) << std::endl; } // Persistent Betti numbers std::cout << "The persistent Betti numbers in interval [0.40, 0.41] are : "; for (int dim = 0; dim < simplex.dimension(); dim++) std::cout << "b" << dim << " = " << pcoh.persistent_betti_number(dim, 0.40, 0.41) << " ; "; std::cout << std::endl; // Betti numbers std::vector betti_numbers = pcoh.betti_numbers(); std::cout << "The Betti numbers are : "; for (std::size_t i = 0; i < betti_numbers.size(); i++) std::cout << "b" << i << " = " << betti_numbers[i] << " ; "; std::cout << std::endl; } return 0; }