diff options
Diffstat (limited to 'src')
-rw-r--r-- | src/Subsampling/example/CMakeLists.txt | 1 | ||||
-rw-r--r-- | src/Subsampling/example/example_custom_kernel.cpp | 69 | ||||
-rw-r--r-- | src/Subsampling/include/gudhi/choose_n_farthest_points.h | 4 |
3 files changed, 73 insertions, 1 deletions
diff --git a/src/Subsampling/example/CMakeLists.txt b/src/Subsampling/example/CMakeLists.txt index 54349f0c..0fd3335c 100644 --- a/src/Subsampling/example/CMakeLists.txt +++ b/src/Subsampling/example/CMakeLists.txt @@ -6,6 +6,7 @@ if(CGAL_FOUND) if (EIGEN3_FOUND) add_executable(Subsampling_example_pick_n_random_points example_pick_n_random_points.cpp) add_executable(Subsampling_example_choose_n_farthest_points example_choose_n_farthest_points.cpp) + add_executable(Subsampling_example_custom_kernel example_custom_kernel.cpp) add_executable(Subsampling_example_sparsify_point_set example_sparsify_point_set.cpp) target_link_libraries(Subsampling_example_sparsify_point_set ${CGAL_LIBRARY}) diff --git a/src/Subsampling/example/example_custom_kernel.cpp b/src/Subsampling/example/example_custom_kernel.cpp new file mode 100644 index 00000000..05797ebe --- /dev/null +++ b/src/Subsampling/example/example_custom_kernel.cpp @@ -0,0 +1,69 @@ +#include <gudhi/choose_n_farthest_points.h> + +#include <CGAL/Epick_d.h> +#include <CGAL/Random.h> + +#include <vector> +#include <iterator> + + +/* The class Kernel contains a distance function defined on the set of points {0,1,2,3} + * and computes a distance according to the matrix: + * 0 1 2 4 + * 1 0 4 2 + * 2 4 0 1 + * 4 2 1 0 + */ +class Kernel { +public: + typedef double FT; + typedef unsigned Point_d; + + // Class Squared_distance_d + class Squared_distance_d { + private: + std::vector<std::vector<FT>> matrix_; + + public: + + Squared_distance_d() + { + matrix_.push_back(std::vector<FT>({0,1,2,4})); + matrix_.push_back(std::vector<FT>({1,0,4,2})); + matrix_.push_back(std::vector<FT>({2,4,0,1})); + matrix_.push_back(std::vector<FT>({4,2,1,0})); + } + + FT operator()(Point_d p1, Point_d p2) + { + return matrix_[p1][p2]; + } + }; + + // Constructor + Kernel() + {} + + // Object of type Squared_distance_d + Squared_distance_d squared_distance_d_object() const + { + return Squared_distance_d(); + } + +}; + +int main(void) { + typedef Kernel K; + typedef typename K::Point_d Point_d; + + K k; + std::vector<Point_d> points = {0,1,2,3}; + std::vector<Point_d> results; + + Gudhi::subsampling::choose_n_farthest_points(k, points, 2, std::back_inserter(results)); + std::cout << "Before sparsification: " << points.size() << " points.\n"; + std::cout << "After sparsification: " << results.size() << " points.\n"; + std::cout << "Result table: {" << results[0] << "," << results[1] << "}\n"; + + return 0; +} diff --git a/src/Subsampling/include/gudhi/choose_n_farthest_points.h b/src/Subsampling/include/gudhi/choose_n_farthest_points.h index 43bf6402..b6b7ace3 100644 --- a/src/Subsampling/include/gudhi/choose_n_farthest_points.h +++ b/src/Subsampling/include/gudhi/choose_n_farthest_points.h @@ -52,6 +52,7 @@ namespace subsampling { * concept <a target="_blank" * href="http://doc.cgal.org/latest/Kernel_d/classKernel__d_1_1Squared__distance__d.html">Kernel_d::Squared_distance_d</a> * concept. + * It must also contain a public member 'squared_distance_d_object' of this type. * \tparam Point_range Range whose value type is Kernel::Point_d. It must provide random-access * via `operator[]` and the points should be stored contiguously in memory. * \tparam OutputIterator Output iterator whose value type is Kernel::Point_d. @@ -112,6 +113,7 @@ void choose_n_farthest_points(Kernel const &k, * concept <a target="_blank" * href="http://doc.cgal.org/latest/Kernel_d/classKernel__d_1_1Squared__distance__d.html">Kernel_d::Squared_distance_d</a> * concept. + * It must also contain a public member 'squared_distance_d_object' of this type. * \tparam Point_range Range whose value type is Kernel::Point_d. It must provide random-access * via `operator[]` and the points should be stored contiguously in memory. * \tparam OutputIterator Output iterator whose value type is Kernel::Point_d. @@ -133,7 +135,7 @@ void choose_n_farthest_points(Kernel const& k, // Choose randomly the first landmark std::random_device rd; std::mt19937 gen(rd()); - std::uniform_int_distribution<> dis(1, 6); + std::uniform_int_distribution<> dis(0, final_size); int starting_point = dis(gen); choose_n_farthest_points(k, input_pts, final_size, starting_point, output_it); } |