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diff --git a/src/Alpha_complex/test/Weighted_alpha_complex_unit_test.cpp b/src/Alpha_complex/test/Weighted_alpha_complex_unit_test.cpp
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+/* 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) 2020 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE "weighted_alpha_complex"
+#include <boost/test/unit_test.hpp>
+#include <boost/mpl/list.hpp>
+
+#include <CGAL/Epick_d.h>
+#include <CGAL/Epeck_d.h>
+
+#include <cmath> // float comparison
+#include <vector>
+#include <random>
+#include <array>
+#include <cmath> // for std::fabs
+
+#include <gudhi/Alpha_complex.h>
+#include <gudhi/Alpha_complex_3d.h>
+#include <gudhi/Simplex_tree.h>
+#include <gudhi/Unitary_tests_utils.h>
+
+using list_of_exact_kernel_variants = boost::mpl::list<CGAL::Epeck_d< CGAL::Dynamic_dimension_tag >,
+ CGAL::Epeck_d< CGAL::Dimension_tag<4> >
+ > ;
+
+BOOST_AUTO_TEST_CASE_TEMPLATE(Zero_weighted_alpha_complex, Kernel, list_of_exact_kernel_variants) {
+ // Check that in exact mode for static dimension 4 the code for dD unweighted and for dD weighted with all weights
+ // 0 give exactly the same simplex tree (simplices and filtration values).
+
+ // Random points construction
+ using Point_d = typename Kernel::Point_d;
+ std::vector<Point_d> points;
+ std::uniform_real_distribution<double> rd_pts(-10., 10.);
+ std::random_device rand_dev;
+ std::mt19937 rand_engine(rand_dev());
+ for (int idx = 0; idx < 20; idx++) {
+ std::vector<double> point {rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine)};
+ points.emplace_back(point.begin(), point.end());
+ }
+
+ // Alpha complex from points
+ Gudhi::alpha_complex::Alpha_complex<Kernel, false> alpha_complex_from_points(points);
+ Gudhi::Simplex_tree<> simplex;
+ Gudhi::Simplex_tree<>::Filtration_value infty = std::numeric_limits<Gudhi::Simplex_tree<>::Filtration_value>::infinity();
+ BOOST_CHECK(alpha_complex_from_points.create_complex(simplex, infty, true));
+ std::clog << "Iterator on alpha complex simplices in the filtration order, with [filtration value]:"
+ << std::endl;
+ for (auto f_simplex : simplex.filtration_simplex_range()) {
+ std::clog << " ( ";
+ for (auto vertex : simplex.simplex_vertex_range(f_simplex)) {
+ std::clog << vertex << " ";
+ }
+ std::clog << ") -> " << "[" << simplex.filtration(f_simplex) << "] " << std::endl;
+ }
+
+ // Alpha complex from zero weighted points
+ std::vector<typename Kernel::FT> weights(20, 0.);
+ Gudhi::alpha_complex::Alpha_complex<Kernel, true> alpha_complex_from_zero_weighted_points(points, weights);
+ Gudhi::Simplex_tree<> zw_simplex;
+ BOOST_CHECK(alpha_complex_from_zero_weighted_points.create_complex(zw_simplex, infty, true));
+
+ std::clog << "Iterator on zero weighted alpha complex simplices in the filtration order, with [filtration value]:"
+ << std::endl;
+ for (auto f_simplex : zw_simplex.filtration_simplex_range()) {
+ std::clog << " ( ";
+ for (auto vertex : zw_simplex.simplex_vertex_range(f_simplex)) {
+ std::clog << vertex << " ";
+ }
+ std::clog << ") -> " << "[" << zw_simplex.filtration(f_simplex) << "] " << std::endl;
+ }
+
+ BOOST_CHECK(zw_simplex == simplex);
+}
+
+template <typename Point_d>
+bool cgal_3d_point_sort (Point_d a,Point_d b) {
+ if (a[0] != b[0])
+ return a[0] < b[0];
+ if (a[1] != b[1])
+ return a[1] < b[1];
+ return a[2] < b[2];
+}
+
+BOOST_AUTO_TEST_CASE(Weighted_alpha_complex_3d_comparison) {
+ // check that for random weighted 3d points in safe mode the 3D and dD codes give the same result with some tolerance
+
+ // Random points construction
+ using Kernel_dD = CGAL::Epeck_d< CGAL::Dimension_tag<3> >;
+ using Bare_point_d = typename Kernel_dD::Point_d;
+ using Weighted_point_d = typename Kernel_dD::Weighted_point_d;
+ std::vector<Weighted_point_d> w_points_d;
+
+ using Exact_weighted_alpha_complex_3d =
+ Gudhi::alpha_complex::Alpha_complex_3d<Gudhi::alpha_complex::complexity::EXACT, true, false>;
+ using Bare_point_3 = typename Exact_weighted_alpha_complex_3d::Bare_point_3;
+ using Weighted_point_3 = typename Exact_weighted_alpha_complex_3d::Weighted_point_3;
+ std::vector<Weighted_point_3> w_points_3;
+
+ std::uniform_real_distribution<double> rd_pts(-10., 10.);
+ std::uniform_real_distribution<double> rd_wghts(-0.5, 0.5);
+ std::random_device rand_dev;
+ std::mt19937 rand_engine(rand_dev());
+ for (int idx = 0; idx < 20; idx++) {
+ std::vector<double> point {rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine)};
+ double weight = rd_wghts(rand_engine);
+ w_points_d.emplace_back(Bare_point_d(point.begin(), point.end()), weight);
+ w_points_3.emplace_back(Bare_point_3(point[0], point[1], point[2]), weight);
+ }
+
+ // Structures necessary for comparison
+ using Points = std::vector<std::array<double,3>>;
+ using Points_and_filtrations = std::map<Points, double>;
+ Points_and_filtrations pts_fltr_dD;
+ Points_and_filtrations pts_fltr_3d;
+
+ // Weighted alpha complex for dD version
+ Gudhi::alpha_complex::Alpha_complex<Kernel_dD, true> alpha_complex_dD_from_weighted_points(w_points_d);
+ Gudhi::Simplex_tree<> w_simplex_d;
+ BOOST_CHECK(alpha_complex_dD_from_weighted_points.create_complex(w_simplex_d));
+
+ std::clog << "Iterator on weighted alpha complex dD simplices in the filtration order, with [filtration value]:"
+ << std::endl;
+ for (auto f_simplex : w_simplex_d.filtration_simplex_range()) {
+ Points points;
+ for (auto vertex : w_simplex_d.simplex_vertex_range(f_simplex)) {
+ CGAL::NT_converter<Kernel_dD::RT, double> cgal_converter;
+ Bare_point_d pt = alpha_complex_dD_from_weighted_points.get_point(vertex).point();
+ points.push_back({cgal_converter(pt[0]), cgal_converter(pt[1]), cgal_converter(pt[2])});
+ }
+ std::clog << " ( ";
+ std::sort (points.begin(), points.end());
+ for (auto point : points) {
+ std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
+ }
+ std::clog << ") -> " << "[" << w_simplex_d.filtration(f_simplex) << "] ";
+ std::clog << std::endl;
+ pts_fltr_dD[points] = w_simplex_d.filtration(f_simplex);
+ }
+
+ // Weighted alpha complex for 3D version
+ Exact_weighted_alpha_complex_3d alpha_complex_3D_from_weighted_points(w_points_3);
+ Gudhi::Simplex_tree<> w_simplex_3;
+ BOOST_CHECK(alpha_complex_3D_from_weighted_points.create_complex(w_simplex_3));
+
+ std::clog << "Iterator on weighted alpha complex 3D simplices in the filtration order, with [filtration value]:"
+ << std::endl;
+ for (auto f_simplex : w_simplex_3.filtration_simplex_range()) {
+ Points points;
+ for (auto vertex : w_simplex_3.simplex_vertex_range(f_simplex)) {
+ Bare_point_3 pt = alpha_complex_3D_from_weighted_points.get_point(vertex).point();
+ CGAL::NT_converter<Exact_weighted_alpha_complex_3d::Kernel::RT, double> cgal_converter;
+ points.push_back({cgal_converter(pt[0]), cgal_converter(pt[1]), cgal_converter(pt[2])});
+ }
+ std::clog << " ( ";
+ std::sort (points.begin(), points.end());
+ for (auto point : points) {
+ std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
+ }
+ std::clog << ") -> " << "[" << w_simplex_3.filtration(f_simplex) << "] " << std::endl;
+ pts_fltr_3d[points] = w_simplex_d.filtration(f_simplex);
+ }
+
+ // Compares structures
+ auto d3_itr = pts_fltr_3d.begin();
+ auto dD_itr = pts_fltr_dD.begin();
+ for (; d3_itr != pts_fltr_3d.end() && dD_itr != pts_fltr_dD.end(); ++d3_itr) {
+ if (d3_itr->first != dD_itr->first) {
+ for(auto point : d3_itr->first)
+ std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
+ std::clog << " versus ";
+ for(auto point : dD_itr->first)
+ std::clog << point[0] << " " << point[1] << " " << point[2] << " | ";
+ std::clog << std::endl;
+ BOOST_CHECK(false);
+ }
+ // In safe mode, relative error is less than 1e-5 (can be changed with set_relative_precision_of_to_double)
+ if (std::fabs(d3_itr->second - dD_itr->second) > 1e-5 * (std::fabs(d3_itr->second) + std::fabs(dD_itr->second))) {
+ std::clog << d3_itr->second << " versus " << dD_itr->second << " diff "
+ << std::fabs(d3_itr->second - dD_itr->second) << std::endl;
+ BOOST_CHECK(false);
+ }
+ ++dD_itr;
+ }
+}
+
+using list_of_1d_kernel_variants = boost::mpl::list<CGAL::Epeck_d< CGAL::Dynamic_dimension_tag >,
+ CGAL::Epeck_d< CGAL::Dimension_tag<1>>,
+ CGAL::Epick_d< CGAL::Dynamic_dimension_tag >,
+ CGAL::Epick_d< CGAL::Dimension_tag<1>>
+ >;
+
+BOOST_AUTO_TEST_CASE_TEMPLATE(Weighted_alpha_complex_non_visible_points, Kernel, list_of_1d_kernel_variants) {
+ // check that for 2 closed weighted 1-d points, one with a high weight to hide the second one with a small weight,
+ // that the point with a small weight has the same high filtration value than the edge formed by the 2 points
+ using Point_d = typename Kernel::Point_d;
+ std::vector<Point_d> points;
+ std::vector<double> p1 {0.};
+ points.emplace_back(p1.begin(), p1.end());
+ // closed enough points
+ std::vector<double> p2 {0.1};
+ points.emplace_back(p2.begin(), p2.end());
+ std::vector<typename Kernel::FT> weights {100., 0.01};
+
+ Gudhi::alpha_complex::Alpha_complex<Kernel, true> alpha_complex(points, weights);
+ Gudhi::Simplex_tree<> stree;
+ BOOST_CHECK(alpha_complex.create_complex(stree));
+
+ std::clog << "Iterator on weighted alpha complex simplices in the filtration order, with [filtration value]:"
+ << std::endl;
+ for (auto f_simplex : stree.filtration_simplex_range()) {
+ std::clog << " ( ";
+ for (auto vertex : stree.simplex_vertex_range(f_simplex)) {
+ std::clog << vertex << " ";
+ }
+ std::clog << ") -> " << "[" << stree.filtration(f_simplex) << "] " << std::endl;
+ }
+
+ BOOST_CHECK(stree.filtration(stree.find({0})) == -100.);
+ BOOST_CHECK(stree.filtration(stree.find({1})) == stree.filtration(stree.find({0, 1})));
+ BOOST_CHECK(stree.filtration(stree.find({1})) > 100000);
+} \ No newline at end of file