diff options
Diffstat (limited to 'src/Subsampling/include/gudhi/sparsify_point_set.h')
| -rw-r--r-- | src/Subsampling/include/gudhi/sparsify_point_set.h | 6 |
1 files changed, 4 insertions, 2 deletions
diff --git a/src/Subsampling/include/gudhi/sparsify_point_set.h b/src/Subsampling/include/gudhi/sparsify_point_set.h index 78e0da4a..afa6d45a 100644 --- a/src/Subsampling/include/gudhi/sparsify_point_set.h +++ b/src/Subsampling/include/gudhi/sparsify_point_set.h @@ -29,7 +29,7 @@ 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`. + * is greater than `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> @@ -53,6 +53,7 @@ sparsify_point_set( OutputIterator output_it) { typedef typename Gudhi::spatial_searching::Kd_tree_search< Kernel, Point_range> Points_ds; + using std::sqrt; #ifdef GUDHI_SUBSAMPLING_PROFILING Gudhi::Clock t; @@ -73,7 +74,8 @@ sparsify_point_set( // If another point Q is closer that min_squared_dist, mark Q to be dropped auto drop = [&dropped_points] (std::ptrdiff_t neighbor_point_idx) { dropped_points[neighbor_point_idx] = true; }; - points_ds.all_near_neighbors(pt, min_squared_dist, boost::make_function_output_iterator(std::ref(drop))); + // FIXME: what if FT does not support sqrt? + points_ds.all_near_neighbors(pt, sqrt(min_squared_dist), boost::make_function_output_iterator(std::ref(drop))); } #ifdef GUDHI_SUBSAMPLING_PROFILING |