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| author | Tavian Barnes <tavianator@tavianator.com> | 2020-05-26 12:54:26 -0400 |
|---|---|---|
| committer | Tavian Barnes <tavianator@tavianator.com> | 2020-06-24 10:02:23 -0400 |
| commit | e272ede323d74d1dd30d28fd862099376b49265b (patch) | |
| tree | fb1dec1894b09677e12a348372777688c3ad272d /benches | |
| parent | b6b5a0ad79b49387ca2e07331b7cb9810b832db2 (diff) | |
| download | acap-e272ede323d74d1dd30d28fd862099376b49265b.tar.xz | |
vp: Implement flat VP trees
Diffstat (limited to 'benches')
| -rw-r--r-- | benches/benches.rs | 8 |
1 files changed, 7 insertions, 1 deletions
diff --git a/benches/benches.rs b/benches/benches.rs index 8791845..a8676ba 100644 --- a/benches/benches.rs +++ b/benches/benches.rs @@ -2,7 +2,7 @@ use acap::euclid::Euclidean; use acap::exhaustive::ExhaustiveSearch; -use acap::vp::VpTree; +use acap::vp::{FlatVpTree, VpTree}; use acap::NearestNeighbors; use criterion::{black_box, criterion_group, criterion_main, Criterion}; @@ -36,6 +36,7 @@ fn bench_from_iter(c: &mut Criterion) { let mut group = c.benchmark_group("from_iter"); group.bench_function("ExhaustiveSearch", |b| b.iter(|| ExhaustiveSearch::from_iter(points.clone()))); group.bench_function("VpTree", |b| b.iter(|| VpTree::from_iter(points.clone()))); + group.bench_function("FlatVpTree", |b| b.iter(|| FlatVpTree::from_iter(points.clone()))); group.finish(); } @@ -45,25 +46,30 @@ fn bench_nearest_neighbors(c: &mut Criterion) { let exhaustive = ExhaustiveSearch::from_iter(points.clone()); let vp_tree = VpTree::from_iter(points.clone()); + let flat_vp_tree = FlatVpTree::from_iter(points.clone()); let mut nearest = c.benchmark_group("NearestNeighbors::nearest"); nearest.bench_function("ExhaustiveSearch", |b| b.iter(|| exhaustive.nearest(&target))); nearest.bench_function("VpTree", |b| b.iter(|| vp_tree.nearest(&target))); + nearest.bench_function("FlatVpTree", |b| b.iter(|| flat_vp_tree.nearest(&target))); nearest.finish(); let mut nearest_within = c.benchmark_group("NearestNeighbors::nearest_within"); nearest_within.bench_function("ExhaustiveSearch", |b| b.iter(|| exhaustive.nearest_within(&target, 0.1))); nearest_within.bench_function("VpTree", |b| b.iter(|| vp_tree.nearest_within(&target, 0.1))); + nearest_within.bench_function("FlatVpTree", |b| b.iter(|| flat_vp_tree.nearest_within(&target, 0.1))); nearest_within.finish(); let mut k_nearest = c.benchmark_group("NearestNeighbors::k_nearest"); k_nearest.bench_function("ExhaustiveSearch", |b| b.iter(|| exhaustive.k_nearest(&target, 3))); k_nearest.bench_function("VpTree", |b| b.iter(|| vp_tree.k_nearest(&target, 3))); + k_nearest.bench_function("FlatVpTree", |b| b.iter(|| flat_vp_tree.k_nearest(&target, 3))); k_nearest.finish(); let mut k_nearest_within = c.benchmark_group("NearestNeighbors::k_nearest_within"); k_nearest_within.bench_function("ExhaustiveSearch", |b| b.iter(|| exhaustive.k_nearest_within(&target, 3, 0.1))); k_nearest_within.bench_function("VpTree", |b| b.iter(|| vp_tree.k_nearest_within(&target, 3, 0.1))); + k_nearest_within.bench_function("FlatVpTree", |b| b.iter(|| flat_vp_tree.k_nearest_within(&target, 3, 0.1))); k_nearest_within.finish(); } |