From 58c77ecd1c09c1cf116be44c1a7e9d18cd99970b Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Thu, 1 Dec 2016 16:42:46 +0000 Subject: Remove traces from tangential Tests the limits for choose_n_farthest_points and fix random git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/trunk@1808 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 53eec1efbc138080d1b202c2cdd4e7ff8cdde266 --- .../include/gudhi/choose_n_farthest_points.h | 20 ++++++-- .../test/test_choose_n_farthest_points.cpp | 55 ++++++++++++++++++++-- 2 files changed, 66 insertions(+), 9 deletions(-) (limited to 'src/Subsampling') diff --git a/src/Subsampling/include/gudhi/choose_n_farthest_points.h b/src/Subsampling/include/gudhi/choose_n_farthest_points.h index 40c7808d..9b45c640 100644 --- a/src/Subsampling/include/gudhi/choose_n_farthest_points.h +++ b/src/Subsampling/include/gudhi/choose_n_farthest_points.h @@ -60,10 +60,15 @@ void choose_n_farthest_points(Kernel const &k, std::size_t final_size, std::size_t starting_point, OutputIterator output_it) { - typename Kernel::Squared_distance_d sqdist = k.squared_distance_d_object(); - std::size_t nb_points = boost::size(input_pts); - assert(nb_points >= final_size); + if (final_size > nb_points) + final_size = nb_points; + + // Tests to the limit + if (final_size < 1) + return; + + typename Kernel::Squared_distance_d sqdist = k.squared_distance_d_object(); std::size_t current_number_of_landmarks = 0; // counter for landmarks const double infty = std::numeric_limits::infinity(); // infinity (see next entry) @@ -107,11 +112,16 @@ void choose_n_farthest_points(Kernel const& k, Point_container const &input_pts, unsigned final_size, OutputIterator output_it) { + // Tests to the limit + if ((final_size < 1) || (input_pts.size() == 0)) + return; + // Choose randomly the first landmark std::random_device rd; std::mt19937 gen(rd()); - std::uniform_int_distribution<> dis(1, 6); - int starting_point = dis(gen); + std::uniform_int_distribution<> dis(0, (input_pts.size() - 1)); + std::size_t starting_point = dis(gen); + choose_n_farthest_points(k, input_pts, final_size, starting_point, output_it); } diff --git a/src/Subsampling/test/test_choose_n_farthest_points.cpp b/src/Subsampling/test/test_choose_n_farthest_points.cpp index d064899a..0bc0dff4 100644 --- a/src/Subsampling/test/test_choose_n_farthest_points.cpp +++ b/src/Subsampling/test/test_choose_n_farthest_points.cpp @@ -39,18 +39,65 @@ typedef CGAL::Epick_d K; typedef typename K::FT FT; typedef typename K::Point_d Point_d; -BOOST_AUTO_TEST_CASE(test_choose_farthest_point) { +typedef boost::mpl::list, CGAL::Epick_d>> 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; 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) - points.push_back(Point_d(std::vector({i, j, k, l}))); + for (FT l = 0; l < 5; l += 1.0) { + std::vector point({i, j, k, l}); + points.push_back(Point_d(point.begin(), point.end())); + } landmarks.clear(); - K k; + Kernel 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 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(); + } -- cgit v1.2.3