diff options
Diffstat (limited to 'src/Subsampling/example')
4 files changed, 109 insertions, 0 deletions
diff --git a/src/Subsampling/example/CMakeLists.txt b/src/Subsampling/example/CMakeLists.txt new file mode 100644 index 00000000..81b39d6e --- /dev/null +++ b/src/Subsampling/example/CMakeLists.txt @@ -0,0 +1,22 @@ +cmake_minimum_required(VERSION 2.6) +project(Subsampling_examples) + +if(CGAL_FOUND) + if (NOT CGAL_VERSION VERSION_LESS 4.8.1) + message(STATUS "CGAL version: ${CGAL_VERSION}.") + + 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_sparsify_point_set example_sparsify_point_set.cpp) + target_link_libraries(Subsampling_example_sparsify_point_set ${CGAL_LIBRARY}) + else() + message(WARNING "Eigen3 not found. Version 3.1.0 is required for Subsampling feature.") + endif() + else() + message(WARNING "CGAL version: ${CGAL_VERSION} is too old to compile Subsampling examples. Version 4.8.1 is required.") + endif () +else() + message(WARNING "CGAL not found. It is required for the Subsampling examples.") +endif() diff --git a/src/Subsampling/example/example_choose_n_farthest_points.cpp b/src/Subsampling/example/example_choose_n_farthest_points.cpp new file mode 100644 index 00000000..9955d0ec --- /dev/null +++ b/src/Subsampling/example/example_choose_n_farthest_points.cpp @@ -0,0 +1,29 @@ +#include <gudhi/choose_n_farthest_points.h> + +#include <CGAL/Epick_d.h> +#include <CGAL/Random.h> + +#include <array> +#include <vector> +#include <iterator> + +int main (void) +{ + typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K; + typedef typename K::FT FT; + typedef typename K::Point_d Point_d; + + CGAL::Random rd; + + std::vector<Point_d> points; + for (int i = 0 ; i < 500 ; ++i) + points.push_back(Point_d(std::array<FT,4>({rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1)}))); + + K k; + std::vector<Point_d> results; + Gudhi::subsampling::choose_n_farthest_points(k, points, 100, std::back_inserter(results)); + std::cout << "Before sparsification: " << points.size() << " points.\n"; + std::cout << "After sparsification: " << results.size() << " points.\n"; + + return 0; +} diff --git a/src/Subsampling/example/example_pick_n_random_points.cpp b/src/Subsampling/example/example_pick_n_random_points.cpp new file mode 100644 index 00000000..d2f063ba --- /dev/null +++ b/src/Subsampling/example/example_pick_n_random_points.cpp @@ -0,0 +1,29 @@ +#include <gudhi/pick_n_random_points.h> + +#include <CGAL/Epick_d.h> +#include <CGAL/Random.h> + +#include <array> +#include <vector> +#include <iterator> + +int main (void) +{ + typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K; + typedef typename K::FT FT; + typedef typename K::Point_d Point_d; + + CGAL::Random rd; + + std::vector<Point_d> points; + for (int i = 0 ; i < 500 ; ++i) + points.push_back(Point_d(std::array<FT,4>({rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1)}))); + + K k; + std::vector<Point_d> results; + Gudhi::subsampling::pick_n_random_points(points, 100, std::back_inserter(results)); + std::cout << "Before sparsification: " << points.size() << " points.\n"; + std::cout << "After sparsification: " << results.size() << " points.\n"; + + return 0; +} diff --git a/src/Subsampling/example/example_sparsify_point_set.cpp b/src/Subsampling/example/example_sparsify_point_set.cpp new file mode 100644 index 00000000..cb5ccf0b --- /dev/null +++ b/src/Subsampling/example/example_sparsify_point_set.cpp @@ -0,0 +1,29 @@ +#include <gudhi/sparsify_point_set.h> + +#include <CGAL/Epick_d.h> +#include <CGAL/Random.h> + +#include <array> +#include <vector> +#include <iterator> + +int main (void) +{ + typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K; + typedef typename K::FT FT; + typedef typename K::Point_d Point_d; + + CGAL::Random rd; + + std::vector<Point_d> points; + for (int i = 0 ; i < 500 ; ++i) + points.push_back(Point_d(std::array<FT,4>({rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1)}))); + + K k; + std::vector<Point_d> results; + Gudhi::subsampling::sparsify_point_set(k, points, 0.4, std::back_inserter(results)); + std::cout << "Before sparsification: " << points.size() << " points.\n"; + std::cout << "After sparsification: " << results.size() << " points.\n"; + + return 0; +} |