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18 changes: 18 additions & 0 deletions la/vector.v
Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
module la

import math
import vsl.errors

// vector_apply sets this []T with the scaled components of another []T
// this := a * another ⇒ this[i] := a * another[i]
Expand Down Expand Up @@ -80,3 +81,20 @@ pub fn vector_largest[T](o []T, den T) T {
}
return largest / den
}

// vector_cosine_similarity calculates the cosine similarity between two vectors
pub fn vector_cosine_similarity(a []f64, b []f64) f64 {
if a.len != b.len {
errors.vsl_panic('Vectors must have the same length', .efailed)
}

dot_product := vector_dot(a, b)
norm_a := vector_norm(a)
norm_b := vector_norm(b)

if norm_a == 0 || norm_b == 0 {
return 0
}

return dot_product / (norm_a * norm_b)
}
20 changes: 20 additions & 0 deletions la/vector_test.v
Original file line number Diff line number Diff line change
Expand Up @@ -70,3 +70,23 @@ fn test_vector_largest() {
l := 2.0
assert float64.close(vector_largest(a, 2), l)
}

fn test_vector_cosine_similarity() {
a := [1.0, 2.0, 3.0]
b := [4.0, 5.0, 6.0]
c := [1.0, 0.0, 0.0]
d := [0.0, 1.0, 0.0]

// Cosine similarity of a and b (should be close to 0.974631846)
assert float64.tolerance(vector_cosine_similarity(a, b), 0.974631846, 1e-8)

// Cosine similarity of a with itself (should be exactly 1)
assert float64.close(vector_cosine_similarity(a, a), 1.0)

// Cosine similarity of perpendicular vectors (should be 0)
assert float64.close(vector_cosine_similarity(c, d), 0.0)

// Cosine similarity of a zero vector with another vector (should be 0)
zero_vector := [0.0, 0.0, 0.0]
assert float64.close(vector_cosine_similarity(zero_vector, a), 0.0)
}