diff options
Diffstat (limited to 'src/Subsampling/test/test_choose_n_farthest_points.cpp')
-rw-r--r-- | src/Subsampling/test/test_choose_n_farthest_points.cpp | 55 |
1 files changed, 4 insertions, 51 deletions
diff --git a/src/Subsampling/test/test_choose_n_farthest_points.cpp b/src/Subsampling/test/test_choose_n_farthest_points.cpp index 0bc0dff4..d064899a 100644 --- a/src/Subsampling/test/test_choose_n_farthest_points.cpp +++ b/src/Subsampling/test/test_choose_n_farthest_points.cpp @@ -39,65 +39,18 @@ typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K; typedef typename K::FT FT; typedef typename K::Point_d Point_d; -typedef boost::mpl::list<CGAL::Epick_d<CGAL::Dynamic_dimension_tag>, CGAL::Epick_d<CGAL::Dimension_tag<4>>> list_of_tested_kernels; - -BOOST_AUTO_TEST_CASE_TEMPLATE(test_choose_farthest_point, Kernel, list_of_tested_kernels) { - typedef typename Kernel::FT FT; - typedef typename Kernel::Point_d Point_d; +BOOST_AUTO_TEST_CASE(test_choose_farthest_point) { std::vector< Point_d > points, landmarks; // Add grid points (625 points) for (FT i = 0; i < 5; i += 1.0) for (FT j = 0; j < 5; j += 1.0) for (FT k = 0; k < 5; k += 1.0) - for (FT l = 0; l < 5; l += 1.0) { - std::vector<FT> point({i, j, k, l}); - points.push_back(Point_d(point.begin(), point.end())); - } + for (FT l = 0; l < 5; l += 1.0) + points.push_back(Point_d(std::vector<FT>({i, j, k, l}))); landmarks.clear(); - Kernel k; + K k; Gudhi::subsampling::choose_n_farthest_points(k, points, 100, std::back_inserter(landmarks)); BOOST_CHECK(landmarks.size() == 100); - for (auto landmark : landmarks) - { - // Check all landmarks are in points - BOOST_CHECK(std::find (points.begin(), points.end(), landmark) != points.end()); - } -} - -BOOST_AUTO_TEST_CASE_TEMPLATE(test_choose_farthest_point_limits, Kernel, list_of_tested_kernels) { - typedef typename Kernel::FT FT; - typedef typename Kernel::Point_d Point_d; - std::vector< Point_d > points, landmarks; - landmarks.clear(); - Kernel k; - // Choose -1 farthest points in an empty point cloud - Gudhi::subsampling::choose_n_farthest_points(k, points, -1, std::back_inserter(landmarks)); - BOOST_CHECK(landmarks.size() == 0); - landmarks.clear(); - // Choose 0 farthest points in an empty point cloud - Gudhi::subsampling::choose_n_farthest_points(k, points, 0, std::back_inserter(landmarks)); - BOOST_CHECK(landmarks.size() == 0); - landmarks.clear(); - // Choose 1 farthest points in an empty point cloud - Gudhi::subsampling::choose_n_farthest_points(k, points, 1, std::back_inserter(landmarks)); - BOOST_CHECK(landmarks.size() == 0); - landmarks.clear(); - - std::vector<FT> point({0.0, 0.0, 0.0, 0.0}); - points.push_back(Point_d(point.begin(), point.end())); - // Choose -1 farthest points in an empty point cloud - Gudhi::subsampling::choose_n_farthest_points(k, points, -1, std::back_inserter(landmarks)); - BOOST_CHECK(landmarks.size() == 1); - landmarks.clear(); - // Choose 0 farthest points in a one point cloud - Gudhi::subsampling::choose_n_farthest_points(k, points, 0, std::back_inserter(landmarks)); - BOOST_CHECK(landmarks.size() == 0); - landmarks.clear(); - // Choose 1 farthest points in a one point cloud - Gudhi::subsampling::choose_n_farthest_points(k, points, 1, std::back_inserter(landmarks)); - BOOST_CHECK(landmarks.size() == 1); - landmarks.clear(); - } |