Created
January 13, 2026 20:39
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| import math | |
| from collections.abc import Sequence | |
| def dot_product(vec_a: Sequence[float],vec_b: Sequence[float]) -> float: | |
| if len(vec_a) != len(vec_b): | |
| raise ValueError("Vectors must be of the same length") | |
| return sum(a * b for a, b in zip(vec_a, vec_b)) | |
| def magnitude(vec: Sequence[float]) -> float: | |
| return math.sqrt(sum(x ** 2 for x in vec)) | |
| def normalize(vec: list[float]) -> list[float]: | |
| mag = magnitude(vec) | |
| if mag == 0: | |
| raise ValueError("Cannot normalize a zero-length vector") | |
| return [x / mag for x in vec] | |
| def cosine_similarity(vec_a: Sequence[float], vec_b: Sequence[float]) -> float: | |
| if len(vec_a) != len(vec_b): | |
| raise ValueError("Vectors must be of the same length") | |
| mag_a, mag_b = magnitude(vec_a), magnitude(vec_b) | |
| if mag_a == 0 or mag_b == 0: | |
| raise ValueError("Cannot compute cosine similarity for zero-length vectors") | |
| return dot_product(vec_a, vec_b) / (mag_a * mag_b) | |
| def matmul(matrix:Sequence[Sequence[float]], vector:Sequence[float]) -> list[float]: | |
| results: list[float] = [] | |
| for row in matrix: | |
| result = dot_product(row, vector) | |
| results.append(result) | |
| return results |
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