import numpy as np num_addorsub=0 num_mul=0 num_assign=0 def matrix_add(matrix_a, matrix_b): ''' :param matrix_a: :param matrix_b: :return:matrix_c=matrix_a+matrix_b ''' rows = len(matrix_a) # get numbers of rows columns = len(matrix_a[0]) # get numbers of cols matrix_c = [list() for i in range(rows)] # build matrix 2d list for i in range(rows): for j in range(columns): matrix_c_temp = matrix_a[i][j] + matrix_b[i][j] global num_addorsub,num_assign num_addorsub = num_addorsub + 1 num_assign = num_assign + 1 matrix_c[i].append(matrix_c_temp) return matrix_c def matrix_minus(matrix_a, matrix_b): ''' :param matrix_a: :param matrix_b: :return:matrix_c=matrix_a-matrix_b ''' rows = len(matrix_a) columns = len(matrix_a[0]) matrix_c = [list() for i in range(rows)] for i in range(rows): for j in range(columns): matrix_c_temp = matrix_a[i][j] - matrix_b[i][j] global num_addorsub,num_assign num_addorsub = num_addorsub + 1 num_assign=num_assign + 1 matrix_c[i].append(matrix_c_temp) return matrix_c def matrix_divide(matrix_a, row, column): ''' :param matrix_a: :param row: :param column: :return: matrix_b=matrix_a(row,column) to divide matrix_a ''' rows = len(matrix_a) columns = len(matrix_a[0]) matrix_b = [list() for i in range(rows // 2)] k = 0 for i in range((row - 1) * rows // 2, row * rows // 2): for j in range((column - 1) * columns // 2, column * columns // 2): matrix_c_temp = matrix_a[i][j] matrix_b[k].append(matrix_c_temp) k += 1 return matrix_b def matrix_merge(matrix_11, matrix_12, matrix_21, matrix_22): ''' :param matrix_11: :param matrix_12: :param matrix_21: :param matrix_22: :return:mariix merged by 4 parts above ''' length = len(matrix_11) matrix_all = [list() for i in range(length * 2)] # build a matrix of double rows for i in range(length): # for each row. matrix_all list contain row of matrix_11 and matrix_12 matrix_all[i] = matrix_11[i] + matrix_12[i] for j in range(length): # for each row. matrix_all list contain row of matrix_21 and matrix_22 matrix_all[length + j] = matrix_21[j] + matrix_22[j] return matrix_all def strassen(matrix_a, matrix_b): ''' :param matrix_a: :param matrix_b: :return:matrix_a * matrix_b ''' row_a = len(matrix_a) col_a = len(matrix_a[0]) row_b = len(matrix_b) col_b = len(matrix_b[0]) if col_a != row_b: print('matrix_a and matrix_b can not be multiplied') return global num_mul,num_addorsub if row_a == 1 or col_a == 1 or row_b == 1 or col_b == 1: matrix_all = [list() for i in range(row_a)] for i in range(row_a): for j in range(col_b): matrix_all_temp = 0 for k in range(col_a): matrix_all_temp += matrix_a[i][k] * matrix_b[k][j] num_mul = num_mul + 1 num_addorsub = num_addorsub + 1 matrix_all[i].append(matrix_all_temp) else: # 10 first parts of computing s1 = matrix_minus((matrix_divide(matrix_b, 1, 2)), (matrix_divide(matrix_b, 2, 2))) s2 = matrix_add((matrix_divide(matrix_a, 1, 1)), (matrix_divide(matrix_a, 1, 2))) s3 = matrix_add((matrix_divide(matrix_a, 2, 1)), (matrix_divide(matrix_a, 2, 2))) s4 = matrix_minus((matrix_divide(matrix_b, 2, 1)), (matrix_divide(matrix_b, 1, 1))) s5 = matrix_add((matrix_divide(matrix_a, 1, 1)), (matrix_divide(matrix_a, 2, 2))) s6 = matrix_add((matrix_divide(matrix_b, 1, 1)), (matrix_divide(matrix_b, 2, 2))) s7 = matrix_minus((matrix_divide(matrix_a, 1, 2)), (matrix_divide(matrix_a, 2, 2))) s8 = matrix_add((matrix_divide(matrix_b, 2, 1)), (matrix_divide(matrix_b, 2, 2))) s9 = matrix_minus((matrix_divide(matrix_a, 1, 1)), (matrix_divide(matrix_a, 2, 1))) s10 = matrix_add((matrix_divide(matrix_b, 1, 1)), (matrix_divide(matrix_b, 1, 2))) # 7 second parts of computing p1 = strassen(matrix_divide(matrix_a, 1, 1), s1) p2 = strassen(s2, matrix_divide(matrix_b, 2, 2)) p3 = strassen(s3, matrix_divide(matrix_b, 1, 1)) p4 = strassen(matrix_divide(matrix_a, 2, 2), s4) p5 = strassen(s5, s6) p6 = strassen(s7, s8) p7 = strassen(s9, s10) # 4 final parts of result c11 = matrix_add(matrix_add(p5, p4), matrix_minus(p6, p2)) c12 = matrix_add(p1, p2) c21 = matrix_add(p3, p4) c22 = matrix_minus(matrix_add(p5, p1), matrix_add(p3, p7)) matrix_all = matrix_merge(c11, c12, c21, c22) global num_assign num_assign =num_assign+22 return matrix_all def main(): # statistical data A = np.random.random_integers(-5, 5, size=(256, 64)) print("\nRandom Matrix A:\n", A) B = np.random.random_integers(-5, 5, size=(64, 128)) print("\nRandom Matrix B:\n", B) C_verification=np.dot(A,B) result = strassen(A, B) print("\n A*B Result of matrixs by generate randomly\n",np.array(result)) print("\nfrequency of add/sub",num_addorsub) print("frequency of assign", num_assign) print("frequency of mul", num_mul) if (C_verification==result).all(): print("\nCorrect") else: print("\nWrong") if __name__ == '__main__': main() # frequency of add/sub 4499186 # frequency of assign 3989370 # frequency of mul 941192 # 2097152