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author | Tavian Barnes <tavianator@tavianator.com> | 2020-07-06 22:24:02 -0400 |
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committer | Tavian Barnes <tavianator@tavianator.com> | 2020-07-06 22:33:10 -0400 |
commit | 5f85a59d4be37d350bcf1ee62c25ac1f84d71770 (patch) | |
tree | 8fc7ea8e59226c5e677d7b9aef39b0b2be5f28b7 /src/lib.rs | |
parent | ed4d7b7143f1a8a9602698ca3e60e18bbb4dd226 (diff) | |
download | acap-5f85a59d4be37d350bcf1ee62c25ac1f84d71770.tar.xz |
kd: Use a more traditional k-d tree implementation
The slight extra pruning possible in the previous implementation didn't
seem to be worth it. The new, simpler implementation is also about 30%
faster in most of the benchmarks.
This gets rid of Coordinate{Proximity,Metric} as they're not necessary
any more (and the old ExactNeighbors impl was too restrictive anyway).
Diffstat (limited to 'src/lib.rs')
-rw-r--r-- | src/lib.rs | 6 |
1 files changed, 3 insertions, 3 deletions
@@ -464,10 +464,10 @@ pub mod tests { type Point = Euclidean<[f32; 3]>; - /// Test a [NearestNeighbors] implementation. - pub fn test_nearest_neighbors<T, F>(from_iter: F) + /// Test an [ExactNeighbors] implementation. + pub fn test_exact_neighbors<T, F>(from_iter: F) where - T: NearestNeighbors<Point>, + T: ExactNeighbors<Point>, F: Fn(Vec<Point>) -> T, { test_empty(&from_iter); |