from __future__ import annotations import math def default_matrix_multiplication(a: list, b: list) -> list: """ Multiplication only for 2x2 matrices """ if len(a) != 2 or len(a[0]) != 2 or len(b) != 2 or len(b[0]) != 2: raise Exception("Matrices are not 2x2") new_matrix = [ [a[0][0] * b[0][0] + a[0][1] * b[1][0], a[0][0] * b[0][1] + a[0][1] * b[1][1]], [a[1][0] * b[0][0] + a[1][1] * b[1][0], a[1][0] * b[0][1] + a[1][1] * b[1][1]], ] return new_matrix def matrix_addition(matrix_a: list, matrix_b: list): return [ [matrix_a[row][col] + matrix_b[row][col] for col in range(len(matrix_a[row]))] for row in range(len(matrix_a)) ] def matrix_subtraction(matrix_a: list, matrix_b: list): return [ [matrix_a[row][col] - matrix_b[row][col] for col in range(len(matrix_a[row]))] for row in range(len(matrix_a)) ] def split_matrix(a: list) -> tuple[list, list, list, list]: """ Given an even length matrix, returns the top_left, top_right, bot_left, bot_right quadrant. >>> split_matrix([[4,3,2,4],[2,3,1,1],[6,5,4,3],[8,4,1,6]]) ([[4, 3], [2, 3]], [[2, 4], [1, 1]], [[6, 5], [8, 4]], [[4, 3], [1, 6]]) >>> split_matrix([ ... [4,3,2,4,4,3,2,4],[2,3,1,1,2,3,1,1],[6,5,4,3,6,5,4,3],[8,4,1,6,8,4,1,6], ... [4,3,2,4,4,3,2,4],[2,3,1,1,2,3,1,1],[6,5,4,3,6,5,4,3],[8,4,1,6,8,4,1,6] ... ]) # doctest: +NORMALIZE_WHITESPACE ([[4, 3, 2, 4], [2, 3, 1, 1], [6, 5, 4, 3], [8, 4, 1, 6]], [[4, 3, 2, 4], [2, 3, 1, 1], [6, 5, 4, 3], [8, 4, 1, 6]], [[4, 3, 2, 4], [2, 3, 1, 1], [6, 5, 4, 3], [8, 4, 1, 6]], [[4, 3, 2, 4], [2, 3, 1, 1], [6, 5, 4, 3], [8, 4, 1, 6]]) """ if len(a) % 2 != 0 or len(a[0]) % 2 != 0: raise Exception("Odd matrices are not supported!") matrix_length = len(a) mid = matrix_length // 2 top_right = [[a[i][j] for j in range(mid, matrix_length)] for i in range(mid)] bot_right = [ [a[i][j] for j in range(mid, matrix_length)] for i in range(mid, matrix_length) ] top_left = [[a[i][j] for j in range(mid)] for i in range(mid)] bot_left = [[a[i][j] for j in range(mid)] for i in range(mid, matrix_length)] return top_left, top_right, bot_left, bot_right def matrix_dimensions(matrix: list) -> tuple[int, int]: return len(matrix), len(matrix[0]) def print_matrix(matrix: list) -> None: for i in range(len(matrix)): print(matrix[i]) def actual_strassen(matrix_a: list, matrix_b: list) -> list: """ Recursive function to calculate the product of two matrices, using the Strassen Algorithm. It only supports even length matrices. """ if matrix_dimensions(matrix_a) == (2, 2): return default_matrix_multiplication(matrix_a, matrix_b) a, b, c, d = split_matrix(matrix_a) e, f, g, h = split_matrix(matrix_b) t1 = actual_strassen(a, matrix_subtraction(f, h)) t2 = actual_strassen(matrix_addition(a, b), h) t3 = actual_strassen(matrix_addition(c, d), e) t4 = actual_strassen(d, matrix_subtraction(g, e)) t5 = actual_strassen(matrix_addition(a, d), matrix_addition(e, h)) t6 = actual_strassen(matrix_subtraction(b, d), matrix_addition(g, h)) t7 = actual_strassen(matrix_subtraction(a, c), matrix_addition(e, f)) top_left = matrix_addition(matrix_subtraction(matrix_addition(t5, t4), t2), t6) top_right = matrix_addition(t1, t2) bot_left = matrix_addition(t3, t4) bot_right = matrix_subtraction(matrix_subtraction(matrix_addition(t1, t5), t3), t7) # construct the new matrix from our 4 quadrants new_matrix = [] for i in range(len(top_right)): new_matrix.append(top_left[i] + top_right[i]) for i in range(len(bot_right)): new_matrix.append(bot_left[i] + bot_right[i]) return new_matrix def strassen(matrix1: list, matrix2: list) -> list: """ >>> strassen([[2,1,3],[3,4,6],[1,4,2],[7,6,7]], [[4,2,3,4],[2,1,1,1],[8,6,4,2]]) [[34, 23, 19, 15], [68, 46, 37, 28], [28, 18, 15, 12], [96, 62, 55, 48]] >>> strassen([[3,7,5,6,9],[1,5,3,7,8],[1,4,4,5,7]], [[2,4],[5,2],[1,7],[5,5],[7,8]]) [[139, 163], [121, 134], [100, 121]] """ if matrix_dimensions(matrix1)[1] != matrix_dimensions(matrix2)[0]: raise Exception( "Unable to multiply these matrices, please check the dimensions. \n" f"Matrix A:{matrix1} \nMatrix B:{matrix2}" ) dimension1 = matrix_dimensions(matrix1) dimension2 = matrix_dimensions(matrix2) if dimension1[0] == dimension1[1] and dimension2[0] == dimension2[1]: return [matrix1, matrix2] maximum = max(max(dimension1), max(dimension2)) maxim = int(math.pow(2, math.ceil(math.log2(maximum)))) new_matrix1 = matrix1 new_matrix2 = matrix2 # Adding zeros to the matrices so that the arrays dimensions are the same and also # power of 2 for i in range(0, maxim): if i < dimension1[0]: for j in range(dimension1[1], maxim): new_matrix1[i].append(0) else: new_matrix1.append([0] * maxim) if i < dimension2[0]: for j in range(dimension2[1], maxim): new_matrix2[i].append(0) else: new_matrix2.append([0] * maxim) final_matrix = actual_strassen(new_matrix1, new_matrix2) # Removing the additional zeros for i in range(0, maxim): if i < dimension1[0]: for j in range(dimension2[1], maxim): final_matrix[i].pop() else: final_matrix.pop() return final_matrix if __name__ == "__main__": matrix1 = [ [2, 3, 4, 5], [6, 4, 3, 1], [2, 3, 6, 7], [3, 1, 2, 4], [2, 3, 4, 5], [6, 4, 3, 1], [2, 3, 6, 7], [3, 1, 2, 4], [2, 3, 4, 5], [6, 2, 3, 1], ] matrix2 = [[0, 2, 1, 1], [16, 2, 3, 3], [2, 2, 7, 7], [13, 11, 22, 4]] print(strassen(matrix1, matrix2))