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-rw-r--r--src/Subsampling/example/example_custom_distance.cpp44
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
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+++ b/src/Subsampling/example/example_custom_distance.cpp
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+#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";
+}