Detailed Description
Collaboration diagram for Metric (distance) classes:
Classes | |
| struct | nanoflann::L1_Adaptor< T, DataSource, _DistanceType > |
| Manhattan distance functor (generic version, optimized for high-dimensionality data sets). More... | |
| struct | nanoflann::L2_Adaptor< T, DataSource, _DistanceType > |
| Squared Euclidean distance functor (generic version, optimized for high-dimensionality data sets). More... | |
| struct | nanoflann::L2_Simple_Adaptor< T, DataSource, _DistanceType > |
| Squared Euclidean (L2) distance functor (suitable for low-dimensionality datasets, like 2D or 3D point clouds) Corresponding distance traits: nanoflann::metric_L2_Simple. More... | |
| struct | nanoflann::metric_L1 |
| Metaprogramming helper traits class for the L1 (Manhattan) metric. More... | |
| struct | nanoflann::metric_L2 |
| Metaprogramming helper traits class for the L2 (Euclidean) metric. More... | |
| struct | nanoflann::metric_L2_Simple |
| Metaprogramming helper traits class for the L2_simple (Euclidean) metric. More... | |