feat(metrics/similarity): create jaccard_index

src/metrics/similarity.rs

@@ -18,3 +18,25 @@ pub fn cosine_similarity(a: &[f64], b: &[f64]) -> f64 {
     let norm_b = norm_l2(b);
     dot / (norm_a * norm_b)
 }
+
+/// Compute the Jaccard index between two sets.
+///
+/// # Examples
+///
+/// ```
+/// # use engram::metrics::jaccard_index;
+/// let a = [true, true, false, false];
+/// let b = [true, false, true, false];
+/// let c = [false, false, false, false];
+/// assert_eq!(jaccard_index(&a, &b), 0.3333333333333333);
+/// assert_eq!(jaccard_index(&a, &c), 0.0);
+/// ```
+pub fn jaccard_index(a: &[bool], b: &[bool]) -> f64 {
+    let intersection = a.iter().zip(b.iter()).filter(|(&a, &b)| a && b).count();
+    let union = a.iter().zip(b.iter()).filter(|(&a, &b)| a || b).count();
+    if union == 0 {
+        0.0
+    } else {
+        intersection as f64 / union as f64
+    }
+}