diff options
| -rw-r--r-- | Cargo.toml | 7 | ||||
| -rw-r--r-- | benches/benches.rs | 64 |
2 files changed, 71 insertions, 0 deletions
@@ -12,3 +12,10 @@ categories = ["algorithms", "data-structures"] [dependencies] num-traits = "0.2.11" rand = "0.7.3" + +[dev-dependencies] +criterion = "0.3" + +[[bench]] +name = "benches" +harness = false diff --git a/benches/benches.rs b/benches/benches.rs new file mode 100644 index 0000000..a43e731 --- /dev/null +++ b/benches/benches.rs @@ -0,0 +1,64 @@ +//! Benchmark for various NearestNeighbors implementations. + +use acap::euclid::Euclidean; +use acap::exhaustive::ExhaustiveSearch; +use acap::NearestNeighbors; + +use criterion::{black_box, criterion_group, criterion_main, Criterion}; + +use std::iter::FromIterator; + +type Point = Euclidean<[f32; 3]>; + +/// Generates a spiral used as the benchmark data set. +fn spiral() -> Vec<Point> { + let mut points = Vec::new(); + + let size = 1000; + let turns = 10.0; + for i in 0..size { + let y = 2.0 * (i as f32) / (size as f32) - 1.0; + let m = (1.0 - y * y).sqrt(); + let theta = turns * y * std::f32::consts::PI; + let (sin, cos) = theta.sin_cos(); + let x = m * cos * cos; + let z = m * sin * cos; + points.push(Euclidean([x, y, z])); + } + + points +} + +fn bench_from_iter(c: &mut Criterion) { + let points = black_box(spiral()); + + let mut group = c.benchmark_group("from_iter"); + group.bench_function("ExhaustiveSearch", |b| b.iter(|| ExhaustiveSearch::from_iter(points.clone()))); + group.finish(); +} + +fn bench_nearest_neighbors(c: &mut Criterion) { + let points = black_box(spiral()); + let target = black_box(Euclidean([0.0, 0.0, 0.0])); + + let exhaustive = ExhaustiveSearch::from_iter(points.clone()); + + let mut nearest = c.benchmark_group("NearestNeighbors::nearest"); + nearest.bench_function("ExhaustiveSearch", |b| b.iter(|| exhaustive.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.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.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.finish(); +} + +criterion_group!(benches, bench_from_iter, bench_nearest_neighbors); +criterion_main!(benches); |