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author | Marc Glisse <marc.glisse@inria.fr> | 2020-10-31 23:39:01 +0100 |
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committer | Marc Glisse <marc.glisse@inria.fr> | 2020-10-31 23:39:01 +0100 |
commit | 2bbba93e7f0837b42def9bed13a6fa790c0eabda (patch) | |
tree | edb3cd03abdb956117b25413f7c6eb9bbb0b28a9 /src/Subsampling/example/example_custom_distance.cpp | |
parent | 6b995c03793096459a333c907b606770113b96d7 (diff) |
s/kernel/distance/ for choose_n_farthest_points argument
Diffstat (limited to 'src/Subsampling/example/example_custom_distance.cpp')
-rw-r--r-- | src/Subsampling/example/example_custom_distance.cpp | 44 |
1 files changed, 44 insertions, 0 deletions
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"; +} |