diff options
Diffstat (limited to 'src/Subsampling/example')
4 files changed, 47 insertions, 66 deletions
diff --git a/src/Subsampling/example/CMakeLists.txt b/src/Subsampling/example/CMakeLists.txt index dfac055c..f4a23d22 100644 --- a/src/Subsampling/example/CMakeLists.txt +++ b/src/Subsampling/example/CMakeLists.txt @@ -3,7 +3,6 @@ project(Subsampling_examples) if(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) 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}) @@ -13,5 +12,6 @@ if(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) COMMAND $<TARGET_FILE:Subsampling_example_choose_n_farthest_points>) add_test(NAME Subsampling_example_sparsify_point_set COMMAND $<TARGET_FILE:Subsampling_example_sparsify_point_set>) - endif(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) + +add_executable(Subsampling_example_custom_distance example_custom_distance.cpp) diff --git a/src/Subsampling/example/example_choose_n_farthest_points.cpp b/src/Subsampling/example/example_choose_n_farthest_points.cpp index 27cf5d4e..e8b3ce2d 100644 --- a/src/Subsampling/example/example_choose_n_farthest_points.cpp +++ b/src/Subsampling/example/example_choose_n_farthest_points.cpp @@ -20,7 +20,7 @@ int main(void) { K k; std::vector<Point_d> results; - Gudhi::subsampling::choose_n_farthest_points(k, points, 100, + Gudhi::subsampling::choose_n_farthest_points(k.squared_distance_d_object(), points, 100, Gudhi::subsampling::random_starting_point, std::back_inserter(results)); std::clog << "Before sparsification: " << points.size() << " points.\n"; diff --git a/src/Subsampling/example/example_custom_distance.cpp b/src/Subsampling/example/example_custom_distance.cpp new file mode 100644 index 00000000..3325b12d --- /dev/null +++ b/src/Subsampling/example/example_custom_distance.cpp @@ -0,0 +1,44 @@ +#include <gudhi/choose_n_farthest_points.h> + +#include <iostream> +#include <vector> +#include <iterator> + + +typedef unsigned Point; + +/* The class Distance 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 Distance { + private: + std::vector<std::vector<double>> matrix_; + + public: + Distance() { + matrix_.push_back({0, 1, 2, 4}); + matrix_.push_back({1, 0, 4, 2}); + matrix_.push_back({2, 4, 0, 1}); + matrix_.push_back({4, 2, 1, 0}); + } + + double operator()(Point p1, Point p2) const { + return matrix_[p1][p2]; + } +}; + +int main(void) { + std::vector<Point> points = {0, 1, 2, 3}; + std::vector<Point> results; + + Gudhi::subsampling::choose_n_farthest_points(Distance(), points, 2, + Gudhi::subsampling::random_starting_point, + std::back_inserter(results)); + std::clog << "Before sparsification: " << points.size() << " points.\n"; + std::clog << "After sparsification: " << results.size() << " points.\n"; + std::clog << "Result table: {" << results[0] << "," << results[1] << "}\n"; +} diff --git a/src/Subsampling/example/example_custom_kernel.cpp b/src/Subsampling/example/example_custom_kernel.cpp deleted file mode 100644 index 535bf42a..00000000 --- a/src/Subsampling/example/example_custom_kernel.cpp +++ /dev/null @@ -1,63 +0,0 @@ -#include <gudhi/choose_n_farthest_points.h> - -#include <iostream> -#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, - Gudhi::subsampling::random_starting_point, - std::back_inserter(results)); - std::clog << "Before sparsification: " << points.size() << " points.\n"; - std::clog << "After sparsification: " << results.size() << " points.\n"; - std::clog << "Result table: {" << results[0] << "," << results[1] << "}\n"; - - return 0; -} |