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-rw-r--r-- | src/Witness_complex/example/example_strong_witness_complex_fvecs.cpp | 79 |
1 files changed, 79 insertions, 0 deletions
diff --git a/src/Witness_complex/example/example_strong_witness_complex_fvecs.cpp b/src/Witness_complex/example/example_strong_witness_complex_fvecs.cpp new file mode 100644 index 00000000..a8e16fb0 --- /dev/null +++ b/src/Witness_complex/example/example_strong_witness_complex_fvecs.cpp @@ -0,0 +1,79 @@ +/* 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/Points_fvecs_reader.h> + +#include <CGAL/Epick_d.h> + +#include <iostream> +#include <fstream> +#include <ctime> +#include <string> +#include <vector> + +using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>; +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[]) { + if (argc != 5) { + std::cerr << "Usage: " << argv[0] + << " path_to_point_file number_of_landmarks max_squared_alpha limit_dimension\n"; + return 0; + } + + std::string file_name = argv[1]; + int nbL = atoi(argv[2]), lim_dim = atoi(argv[4]); + 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::load_points_from_fvecs_file<K>(file_name, std::back_insert_iterator< Point_vector >(point_vector)); + + + 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)); + + // Compute witness complex + start = clock(); + 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 << "Number of simplices is: " << simplex_tree.num_simplices() << std::endl; + std::cout << "Max dimension is : " << simplex_tree.dimension() << std::endl; + +} |