diff options
Diffstat (limited to 'src/Witness_complex/example/example_strong_witness_complex_off.cpp')
-rw-r--r-- | src/Witness_complex/example/example_strong_witness_complex_off.cpp | 48 |
1 files changed, 12 insertions, 36 deletions
diff --git a/src/Witness_complex/example/example_strong_witness_complex_off.cpp b/src/Witness_complex/example/example_strong_witness_complex_off.cpp index f195953b..19f73836 100644 --- a/src/Witness_complex/example/example_strong_witness_complex_off.cpp +++ b/src/Witness_complex/example/example_strong_witness_complex_off.cpp @@ -1,29 +1,7 @@ -/* 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 (France) - * - * 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 - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * 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/Fake_simplex_tree.h> #include <gudhi/Euclidean_strong_witness_complex.h> #include <gudhi/pick_n_random_points.h> +#include <gudhi/choose_n_farthest_points.h> #include <gudhi/Points_off_io.h> #include <CGAL/Epick_d.h> @@ -39,10 +17,9 @@ using Point_d = typename K::Point_d; using Witness_complex = Gudhi::witness_complex::Euclidean_strong_witness_complex<K>; using Point_vector = std::vector<Point_d>; -int main(int argc, char * const argv[]) { +int main(int argc, char* const argv[]) { if (argc != 5) { - std::cerr << "Usage: " << argv[0] - << " path_to_point_file number_of_landmarks max_squared_alpha limit_dimension\n"; + std::cerr << "Usage: " << argv[0] << " path_to_point_file number_of_landmarks max_squared_alpha limit_dimension\n"; return 0; } @@ -51,31 +28,30 @@ int main(int argc, char * const argv[]) { double alpha2 = atof(argv[3]); clock_t start, end; Gudhi::Simplex_tree<> simplex_tree; - //Gudhi::Fake_simplex_tree simplex_tree; // Read the point file Point_vector point_vector, landmarks; Gudhi::Points_off_reader<Point_d> off_reader(file_name); if (!off_reader.is_valid()) { - std::cerr << "Strong witness complex - Unable to read file " << file_name << "\n"; - exit(-1); // ----- >> - } + std::cerr << "Strong witness complex - Unable to read file " << file_name << "\n"; + exit(-1); // ----- >> + } point_vector = Point_vector(off_reader.get_point_cloud()); std::cout << "Successfully read " << point_vector.size() << " points.\n"; std::cout << "Ambient dimension is " << point_vector[0].dimension() << ".\n"; - // Choose landmarks - Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks)); + // 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(), point_vector, nbL, Gudhi::subsampling::random_starting_point, + std::back_inserter(landmarks)); // Compute witness complex start = clock(); - Witness_complex witness_complex(landmarks, - point_vector); + Witness_complex witness_complex(landmarks, point_vector); witness_complex.create_complex(simplex_tree, alpha2, lim_dim); end = clock(); - std::cout << "Strong witness complex took " - << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n"; + std::cout << "Strong witness complex took " << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n"; std::cout << "Number of simplices is: " << simplex_tree.num_simplices() << "\n"; } |