diff options
| -rw-r--r-- | src/Subsampling/include/gudhi/sparsify_point_set.h | 97 |
1 files changed, 48 insertions, 49 deletions
diff --git a/src/Subsampling/include/gudhi/sparsify_point_set.h b/src/Subsampling/include/gudhi/sparsify_point_set.h index 89770886..a6844919 100644 --- a/src/Subsampling/include/gudhi/sparsify_point_set.h +++ b/src/Subsampling/include/gudhi/sparsify_point_set.h @@ -33,66 +33,65 @@ namespace Gudhi { - template <typename Kernel, typename Point_container, typename OutputIterator> - bool - sparsify_point_set( - const Kernel &k, Point_container const& input_pts, - typename Kernel::FT min_squared_dist, - OutputIterator output_it) - { - typedef typename Gudhi::Spatial_tree_data_structure< - Kernel, Point_container> Points_ds; - - typename Kernel::Squared_distance_d sqdist = k.squared_distance_d_object(); +template <typename Kernel, typename Point_container, typename OutputIterator> +bool +sparsify_point_set( + const Kernel &k, Point_container const& input_pts, + typename Kernel::FT min_squared_dist, + OutputIterator output_it) +{ + typedef typename Gudhi::Spatial_tree_data_structure< + Kernel, Point_container> Points_ds; + + typename Kernel::Squared_distance_d sqdist = k.squared_distance_d_object(); #ifdef GUDHI_TC_PROFILING - Gudhi::Clock t; + Gudhi::Clock t; #endif - Points_ds points_ds(input_pts); + Points_ds points_ds(input_pts); + + std::vector<bool> dropped_points(input_pts.size(), false); + + // Parse the input points, and add them if they are not too close to + // the other points + std::size_t pt_idx = 0; + for (typename Point_container::const_iterator it_pt = input_pts.begin() ; + it_pt != input_pts.end(); + ++it_pt, ++pt_idx) + { + if (dropped_points[pt_idx]) + continue; - std::vector<bool> dropped_points(input_pts.size(), false); + *output_it++ = *it_pt; - // Parse the input points, and add them if they are not too close to - // the other points - std::size_t pt_idx = 0; - for (typename Point_container::const_iterator it_pt = input_pts.begin() ; - it_pt != input_pts.end(); - ++it_pt, ++pt_idx) + auto ins_range = points_ds.query_incremental_ANN(*it_pt); + + // If another point Q is closer that min_squared_dist, mark Q to be dropped + for (auto const& neighbor : ins_range) + { + std::size_t neighbor_point_idx = neighbor.first; + // If the neighbor is too close, we drop the neighbor + if (neighbor.second < min_squared_dist) + //if (neighbor.second < 0.2*((*it_pt)[0] + 1.)*0.5 + 0.00005) + //if (neighbor.second < ((*it_pt)[0] < 0 ? 0.2 : 0.00001)) { - if (dropped_points[pt_idx]) - continue; - - *output_it++ = *it_pt; - - auto ins_range = points_ds.query_incremental_ANN(*it_pt); - - // If another point Q is closer that min_squared_dist, mark Q to be dropped - for (auto const& neighbor : ins_range) - { - std::size_t neighbor_point_idx = neighbor.first; - // If the neighbor is too close, we drop the neighbor - if (neighbor.second < min_squared_dist) - //if (neighbor.second < 0.2*((*it_pt)[0] + 1.)*0.5 + 0.00005) - //if (neighbor.second < ((*it_pt)[0] < 0 ? 0.2 : 0.00001)) - { - // N.B.: If neighbor_point_idx < pt_idx, - // dropped_points[neighbor_point_idx] is already true but adding a - // test doesn't make things faster, so why bother? - dropped_points[neighbor_point_idx] = true; - } - else - break; - } + // N.B.: If neighbor_point_idx < pt_idx, + // dropped_points[neighbor_point_idx] is already true but adding a + // test doesn't make things faster, so why bother? + dropped_points[neighbor_point_idx] = true; } + else + break; + } + } #ifdef GUDHI_TC_PROFILING - t.end(); - std::cerr << "Point set sparsified in " << t.num_seconds() - << " seconds." << std::endl; + t.end(); + std::cerr << "Point set sparsified in " << t.num_seconds() + << " seconds." << std::endl; #endif - } - +} } //namespace Gudhi |