Squashed 'vendor/ruvector/' content from commit b64c2172

git-subtree-dir: vendor/ruvector
git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900

crates/ruvector-nervous-system/benches/pattern_separation.rs

@@ -0,0 +1,64 @@
+use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
+use ruvector_nervous_system::DentateGyrus;
+
+fn bench_encoding(c: &mut Criterion) {
+    let mut group = c.benchmark_group("dentate_gyrus_encoding");
+
+    // Benchmark different input dimensions
+    for input_dim in [128, 256, 512].iter() {
+        let dg = DentateGyrus::new(*input_dim, 10000, 200, 42);
+        let input: Vec<f32> = (0..*input_dim).map(|i| (i as f32).sin()).collect();
+
+        group.bench_with_input(BenchmarkId::from_parameter(input_dim), input_dim, |b, _| {
+            b.iter(|| black_box(dg.encode(black_box(&input))));
+        });
+    }
+
+    group.finish();
+}
+
+fn bench_similarity(c: &mut Criterion) {
+    let dg = DentateGyrus::new(512, 10000, 200, 42);
+
+    let input1: Vec<f32> = (0..512).map(|i| (i as f32).sin()).collect();
+    let input2: Vec<f32> = (0..512).map(|i| (i as f32).cos()).collect();
+
+    let sparse1 = dg.encode(&input1);
+    let sparse2 = dg.encode(&input2);
+
+    c.bench_function("jaccard_similarity", |b| {
+        b.iter(|| black_box(sparse1.jaccard_similarity(black_box(&sparse2))));
+    });
+
+    c.bench_function("hamming_distance", |b| {
+        b.iter(|| black_box(sparse1.hamming_distance(black_box(&sparse2))));
+    });
+}
+
+fn bench_sparsity_levels(c: &mut Criterion) {
+    let mut group = c.benchmark_group("sparsity_levels");
+
+    for sparsity_pct in [2, 3, 5].iter() {
+        let k = (10000 * sparsity_pct) / 100;
+        let dg = DentateGyrus::new(512, 10000, k, 42);
+        let input: Vec<f32> = (0..512).map(|i| (i as f32).sin()).collect();
+
+        group.bench_with_input(
+            BenchmarkId::from_parameter(format!("{}%", sparsity_pct)),
+            sparsity_pct,
+            |b, _| {
+                b.iter(|| black_box(dg.encode(black_box(&input))));
+            },
+        );
+    }
+
+    group.finish();
+}
+
+criterion_group!(
+    benches,
+    bench_encoding,
+    bench_similarity,
+    bench_sparsity_levels
+);
+criterion_main!(benches);