""" function based version of matrix operations, which are just 2D arrays """ def add(matrix_a, matrix_b): if _check_not_integer(matrix_a) and _check_not_integer(matrix_b): rows, cols = _verify_matrix_sizes(matrix_a, matrix_b) matrix_c = [] for i in range(rows[0]): list_1 = [] for j in range(cols[0]): val = matrix_a[i][j] + matrix_b[i][j] list_1.append(val) matrix_c.append(list_1) return matrix_c def subtract(matrix_a, matrix_b): if _check_not_integer(matrix_a) and _check_not_integer(matrix_b): rows, cols = _verify_matrix_sizes(matrix_a, matrix_b) matrix_c = [] for i in range(rows[0]): list_1 = [] for j in range(cols[0]): val = matrix_a[i][j] - matrix_b[i][j] list_1.append(val) matrix_c.append(list_1) return matrix_c def scalar_multiply(matrix, n): return [[x * n for x in row] for row in matrix] def multiply(matrix_a, matrix_b): if _check_not_integer(matrix_a) and _check_not_integer(matrix_b): matrix_c = [] rows, cols = _verify_matrix_sizes(matrix_a, matrix_b) if cols[0] != rows[1]: raise ValueError( f"Cannot multiply matrix of dimensions ({rows[0]},{cols[0]}) " f"and ({rows[1]},{cols[1]})" ) for i in range(rows[0]): list_1 = [] for j in range(cols[1]): val = 0 for k in range(cols[1]): val = val + matrix_a[i][k] * matrix_b[k][j] list_1.append(val) matrix_c.append(list_1) return matrix_c def identity(n): """ :param n: dimension for nxn matrix :type n: int :return: Identity matrix of shape [n, n] """ n = int(n) return [[int(row == column) for column in range(n)] for row in range(n)] def transpose(matrix, return_map=True): if _check_not_integer(matrix): if return_map: return map(list, zip(*matrix)) else: # mt = [] # for i in range(len(matrix[0])): # mt.append([row[i] for row in matrix]) # return mt return [[row[i] for row in matrix] for i in range(len(matrix[0]))] def minor(matrix, row, column): minor = matrix[:row] + matrix[row + 1 :] minor = [row[:column] + row[column + 1 :] for row in minor] return minor def determinant(matrix): if len(matrix) == 1: return matrix[0][0] res = 0 for x in range(len(matrix)): res += matrix[0][x] * determinant(minor(matrix, 0, x)) * (-1) ** x return res def inverse(matrix): det = determinant(matrix) if det == 0: return None matrix_minor = [[] for _ in range(len(matrix))] for i in range(len(matrix)): for j in range(len(matrix)): matrix_minor[i].append(determinant(minor(matrix, i, j))) cofactors = [ [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row])] for row in range(len(matrix)) ] adjugate = transpose(cofactors) return scalar_multiply(adjugate, 1 / det) def _check_not_integer(matrix): try: rows = len(matrix) cols = len(matrix[0]) return True except TypeError: raise TypeError("Cannot input an integer value, it must be a matrix") def _shape(matrix): return list((len(matrix), len(matrix[0]))) def _verify_matrix_sizes(matrix_a, matrix_b): shape = _shape(matrix_a) shape += _shape(matrix_b) if shape[0] != shape[2] or shape[1] != shape[3]: raise ValueError( f"operands could not be broadcast together with shape " f"({shape[0], shape[1]}), ({shape[2], shape[3]})" ) return [shape[0], shape[2]], [shape[1], shape[3]] def main(): matrix_a = [[12, 10], [3, 9]] matrix_b = [[3, 4], [7, 4]] matrix_c = [[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]] matrix_d = [[3, 0, 2], [2, 0, -2], [0, 1, 1]] print( "Add Operation, %s + %s = %s \n" % (matrix_a, matrix_b, (add(matrix_a, matrix_b))) ) print( "Multiply Operation, %s * %s = %s \n" % (matrix_a, matrix_b, multiply(matrix_a, matrix_b)) ) print("Identity: %s \n" % identity(5)) print("Minor of %s = %s \n" % (matrix_c, minor(matrix_c, 1, 2))) print("Determinant of %s = %s \n" % (matrix_b, determinant(matrix_b))) print("Inverse of %s = %s\n" % (matrix_d, inverse(matrix_d))) if __name__ == "__main__": main()