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-/* 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 Sophia Antipolis-Méditerranée (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/Relaxed_witness_complex.h>
-#include <gudhi/Dim_lists.h>
-#include <gudhi/reader_utils.h>
-#include <gudhi/Persistent_cohomology.h>
-#include "Landmark_choice_random_knn.h"
-#include "Landmark_choice_sparsification.h"
-
-#include <iostream>
-#include <fstream>
-#include <ctime>
-#include <utility>
-#include <algorithm>
-#include <set>
-#include <queue>
-#include <iterator>
-#include <string>
-
-#include <boost/tuple/tuple.hpp>
-#include <boost/iterator/zip_iterator.hpp>
-#include <boost/iterator/counting_iterator.hpp>
-#include <boost/range/iterator_range.hpp>
-
-#include <CGAL/Epick_d.h>
-#include <CGAL/Delaunay_triangulation.h>
-//#include <CGAL/Sphere_d.h>
-
-#include "generators.h"
-#include "output.h"
-
-using namespace Gudhi;
-using namespace Gudhi::witness_complex;
-using namespace Gudhi::persistent_cohomology;
-
-typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K;
-typedef K::Point_d Point_d;
-typedef K::Sphere_d Sphere_d;
-typedef CGAL::Delaunay_triangulation<K> Delaunay_triangulation;
-
-typedef std::vector<Point_d> Point_Vector;
-typedef Relaxed_witness_complex< Simplex_tree<> > RelaxedWitnessComplex;
-typedef Simplex_tree<>::Simplex_handle Simplex_handle;
-
-
-
-/**
- * \brief Customized version of read_points
- * which takes into account a possible nbP first line
- *
- */
-inline void
-read_points_cust(std::string file_name, std::vector< std::vector< double > > & points) {
- std::ifstream in_file(file_name.c_str(), std::ios::in);
- if (!in_file.is_open()) {
- std::cerr << "Unable to open file " << file_name << std::endl;
- return;
- }
- std::string line;
- double x;
- while (getline(in_file, line)) {
- std::vector< double > point;
- std::istringstream iss(line);
- while (iss >> x) {
- point.push_back(x);
- }
- if (point.size() != 1)
- points.push_back(point);
- }
- in_file.close();
-}
-
-int main (int argc, char * const argv[])
-{
- if (argc != 4) {
- std::cerr << "Usage: " << argv[0]
- << " 1 file_name alpha limD\n";
- return 0;
- }
- std::string file_name = argv[1];
- double alpha2 = atof(argv[2]);
- int limD = atoi(argv[3]);
-
- // Read points
- Point_Vector point_vector;
- read_points_cust(file_name, point_vector);
- generate_points_random_box(point_vector, 200, 2);
- write_points(file_name, point_vector);
-
- std::cout << "The file contains " << point_vector.size() << " points.\n";
- std::cout << "Ambient dimension is " << point_vector[0].size() << ".\n";
-
- // 1. Compute Delaunay centers
- Delaunay_triangulation delaunay(point_vector[0].size());
- delaunay.insert(point_vector.begin(), point_vector.end());
- Point_Vector del_centers;
- for (auto f_it = delaunay.full_cells_begin(); f_it != delaunay.full_cells_end(); ++f_it) {
- if (delaunay.is_infinite(f_it))
- continue;
- Point_Vector vertices;
- for (auto v_it = f_it->vertices_begin(); v_it != f_it->vertices_end(); ++v_it)
- vertices.push_back((*v_it)->point());
- Sphere_d sphere(vertices.begin(), vertices.end());
- del_centers.push_back(sphere.center());
- }
- std::cout << "Delaunay center count: " << del_centers.size() << ".\n";
-
- // 2. Build Relaxed Witness Complex
- std::vector<std::vector<int>> knn;
- std::vector<std::vector<double>> distances;
- Gudhi::witness_complex::build_distance_matrix(del_centers, // aka witnesses
- point_vector, // aka landmarks
- alpha2,
- limD,
- knn,
- distances);
-
- write_wl("wl_distances.txt", distances);
- Simplex_tree<> simplex_tree;
- Gudhi::witness_complex::Relaxed_witness_complex<Simplex_tree<>> rwc(distances,
- knn,
- simplex_tree,
- point_vector.size(),
- alpha2,
- limD);
- std::vector<int> dim_simplices(limD+1);
- for (auto sh: simplex_tree.complex_simplex_range()) {
- dim_simplices[simplex_tree.dimension(sh)]++;
- }
- for (unsigned i =0; i != dim_simplices.size(); ++i)
- std::cout << "dim[" << i << "]: " << dim_simplices[i] << " simplices.\n";
-
- std::vector<int> landmarks_ind;
- for (unsigned i = 0; i < point_vector.size(); ++i)
- landmarks_ind.push_back(i);
- write_witness_mesh(point_vector, landmarks_ind, simplex_tree, simplex_tree.complex_simplex_range(), true, true, "relaxed_delaunay.mesh");
-
- // 3. Check if the thing is Relaxed Delaunay
- for (auto sh: simplex_tree.complex_simplex_range()) {
- Point_Vector vertices;
- for (auto v: simplex_tree.simplex_vertex_range(sh))
- vertices.push_back(point_vector[v]);
- Sphere_d sphere(vertices.begin(), vertices.end());
- Point_d center = sphere.center();
- double r2 = sphere.squared_radius();
- typename K::Squared_distance_d dist2;
- std::vector<int> v_inds;
- for (auto v: simplex_tree.simplex_vertex_range(sh))
- v_inds.push_back(v);
- auto range_begin = std::begin(v_inds);
- auto range_end = std::end(v_inds);
- if (simplex_tree.dimension(sh) == (int)point_vector[0].size())
- for (auto v: simplex_tree.complex_vertex_range())
- if (std::find(range_begin, range_end, v) == range_end) {
- if (dist2(point_vector[v], center) < r2 - alpha2)
- std::cout << "WARNING! The vertex " << point_vector[v] << " is inside the (r2-alpha2)-ball (" << center << ", " << r2 << ") distance is " << dist2(point_vector[v], center) << "\n";
- }
- }
-}
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