diff options
-rw-r--r-- | src/Spatial_searching/include/gudhi/Spatial_tree_data_structure.h | 4 | ||||
-rw-r--r-- | src/Subsampling/include/gudhi/sparsify_point_set.h | 25 |
2 files changed, 22 insertions, 7 deletions
diff --git a/src/Spatial_searching/include/gudhi/Spatial_tree_data_structure.h b/src/Spatial_searching/include/gudhi/Spatial_tree_data_structure.h index 016975b8..ca05af57 100644 --- a/src/Spatial_searching/include/gudhi/Spatial_tree_data_structure.h +++ b/src/Spatial_searching/include/gudhi/Spatial_tree_data_structure.h @@ -54,7 +54,9 @@ namespace spatial_searching { * and the <i>incremental nearest neighbor query</i>, where no number of neighbors is provided during the call, as the * neighbors will be computed incrementally when the iterator on the range is incremented. * - * \tparam K requires a <a target="_blank" + * \tparam K requires a model of the <a target="_blank" + * href="http://doc.cgal.org/latest/Spatial_searching/classSearchTraits.html">SearchTraits</a> + * concept, such as the <a target="_blank" * href="http://doc.cgal.org/latest/Kernel_d/classCGAL_1_1Epick__d.html">CGAL::Epick_d</a> class, which * can be static if you know the ambiant dimension at compile-time, or dynamic if you don't. * \tparam Point_container_ is the type of the container where points are stored (on the user side). diff --git a/src/Subsampling/include/gudhi/sparsify_point_set.h b/src/Subsampling/include/gudhi/sparsify_point_set.h index b4536ec8..3923bf74 100644 --- a/src/Subsampling/include/gudhi/sparsify_point_set.h +++ b/src/Subsampling/include/gudhi/sparsify_point_set.h @@ -35,12 +35,25 @@ namespace Gudhi { namespace subsampling { /** -* \ingroup subsampling -* \brief Outputs a subset of the input points so that the -* squared distance between any two points -* is greater than or equal to `min_squared_dist`. -* -*/ + * \ingroup subsampling + * \brief Outputs a subset of the input points so that the + * squared distance between any two points + * is greater than or equal to `min_squared_dist`. + * + * \tparam Kernel must be a model of the <a target="_blank" + * href="http://doc.cgal.org/latest/Spatial_searching/classSearchTraits.html">SearchTraits</a> + * concept, such as the <a target="_blank" + * href="http://doc.cgal.org/latest/Kernel_d/classCGAL_1_1Epick__d.html">CGAL::Epick_d</a> class, which + * can be static if you know the ambiant dimension at compile-time, or dynamic if you don't. + * \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. + * + * @param[in] k A kernel object. + * @param[in] input_pts Const reference to the input points. + * @param[in] min_squared_dist Minimum squared distance separating the output points. + * @param[out] output_it The output iterator. + */ template <typename Kernel, typename Point_range, typename OutputIterator> void |