diff --git a/matrix/matrix_operation.py b/matrix/matrix_operation.py index dd7c01582681..b32a4dcf7af3 100644 --- a/matrix/matrix_operation.py +++ b/matrix/matrix_operation.py @@ -1,64 +1,131 @@ -from __future__ import print_function +""" +function based version of matrix operations, which are just 2D arrays +""" + def add(matrix_a, matrix_b): - rows = len(matrix_a) - columns = len(matrix_a[0]) - matrix_c = [] - for i in range(rows): - list_1 = [] - for j in range(columns): - val = matrix_a[i][j] + matrix_b[i][j] - list_1.append(val) - matrix_c.append(list_1) - return matrix_c - -def scalarMultiply(matrix , n): + 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): - matrix_c = [] - n = len(matrix_a) - for i in range(n): - list_1 = [] - for j in range(n): - val = 0 - for k in range(n): - val = val + matrix_a[i][k] * matrix_b[k][j] - list_1.append(val) - matrix_c.append(list_1) - return matrix_c + 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(list , zip(*matrix)) + +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] + 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 + res += matrix[0][x] * determinant(minor(matrix, 0, x)) * (-1) ** x return res + def inverse(matrix): det = determinant(matrix) - if det == 0: return None + if det == 0: + return None - matrixMinor = [[] for _ in range(len(matrix))] + matrix_minor = [[] for _ in range(len(matrix))] for i in range(len(matrix)): for j in range(len(matrix)): - matrixMinor[i].append(determinant(minor(matrix , i , j))) + matrix_minor[i].append(determinant(minor(matrix, i, j))) - cofactors = [[x * (-1) ** (row + col) for col, x in enumerate(matrixMinor[row])] for row in range(len(matrix))] + cofactors = [[x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row])] for row in range(len(matrix))] adjugate = transpose(cofactors) - return scalarMultiply(adjugate , 1/det) + 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]] @@ -68,9 +135,10 @@ def main(): 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('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() diff --git a/matrix/tests/pytest.ini b/matrix/tests/pytest.ini new file mode 100644 index 000000000000..8a978b56ef8b --- /dev/null +++ b/matrix/tests/pytest.ini @@ -0,0 +1,3 @@ +[pytest] +markers = + mat_ops: tests for matrix operations diff --git a/matrix/tests/test_matrix_operation.py b/matrix/tests/test_matrix_operation.py new file mode 100644 index 000000000000..8b81b65d0fc8 --- /dev/null +++ b/matrix/tests/test_matrix_operation.py @@ -0,0 +1,112 @@ +""" +Testing here assumes that numpy and linalg is ALWAYS correct!!!! + +If running from PyCharm you can place the following line in "Additional Arguments" for the pytest run configuration +-vv -m mat_ops -p no:cacheprovider +""" + +# standard libraries +import sys +import numpy as np +import pytest +import logging + +# Custom/local libraries +from matrix import matrix_operation as matop + +mat_a = [[12, 10], [3, 9]] +mat_b = [[3, 4], [7, 4]] +mat_c = [[3, 0, 2], [2, 0, -2], [0, 1, 1]] +mat_d = [[3, 0, -2], [2, 0, 2], [0, 1, 1]] +mat_e = [[3, 0, 2], [2, 0, -2], [0, 1, 1], [2, 0, -2]] +mat_f = [1] +mat_h = [2] + +logger = logging.getLogger() +logger.level = logging.DEBUG +stream_handler = logging.StreamHandler(sys.stdout) +logger.addHandler(stream_handler) + + +@pytest.mark.mat_ops +@pytest.mark.parametrize(('mat1', 'mat2'), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), + (mat_f, mat_h)]) +def test_addition(mat1, mat2): + if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2): + with pytest.raises(TypeError): + logger.info(f"\n\t{test_addition.__name__} returned integer") + matop.add(mat1, mat2) + elif (np.array(mat1)).shape == (np.array(mat2)).shape: + logger.info(f"\n\t{test_addition.__name__} with same matrix dims") + act = (np.array(mat1) + np.array(mat2)).tolist() + theo = matop.add(mat1, mat2) + assert theo == act + else: + with pytest.raises(ValueError): + logger.info(f"\n\t{test_addition.__name__} with different matrix dims") + matop.add(mat1, mat2) + + +@pytest.mark.mat_ops +@pytest.mark.parametrize(('mat1', 'mat2'), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), + (mat_f, mat_h)]) +def test_subtraction(mat1, mat2): + if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2): + with pytest.raises(TypeError): + logger.info(f"\n\t{test_subtraction.__name__} returned integer") + matop.subtract(mat1, mat2) + elif (np.array(mat1)).shape == (np.array(mat2)).shape: + logger.info(f"\n\t{test_subtraction.__name__} with same matrix dims") + act = (np.array(mat1) - np.array(mat2)).tolist() + theo = matop.subtract(mat1, mat2) + assert theo == act + else: + with pytest.raises(ValueError): + logger.info(f"\n\t{test_subtraction.__name__} with different matrix dims") + assert matop.subtract(mat1, mat2) + + +@pytest.mark.mat_ops +@pytest.mark.parametrize(('mat1', 'mat2'), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), + (mat_f, mat_h)]) +def test_multiplication(mat1, mat2): + if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2): + logger.info(f"\n\t{test_multiplication.__name__} returned integer") + with pytest.raises(TypeError): + matop.add(mat1, mat2) + elif (np.array(mat1)).shape == (np.array(mat2)).shape: + logger.info(f"\n\t{test_multiplication.__name__} meets dim requirements") + act = (np.matmul(mat1, mat2)).tolist() + theo = matop.multiply(mat1, mat2) + assert theo == act + else: + with pytest.raises(ValueError): + logger.info(f"\n\t{test_multiplication.__name__} does not meet dim requirements") + assert matop.subtract(mat1, mat2) + + +@pytest.mark.mat_ops +def test_scalar_multiply(): + act = (3.5 * np.array(mat_a)).tolist() + theo = matop.scalar_multiply(mat_a, 3.5) + assert theo == act + + +@pytest.mark.mat_ops +def test_identity(): + act = (np.identity(5)).tolist() + theo = matop.identity(5) + assert theo == act + + +@pytest.mark.mat_ops +@pytest.mark.parametrize('mat', [mat_a, mat_b, mat_c, mat_d, mat_e, mat_f]) +def test_transpose(mat): + if (np.array(mat)).shape < (2, 2): + with pytest.raises(TypeError): + logger.info(f"\n\t{test_transpose.__name__} returned integer") + matop.transpose(mat) + else: + act = (np.transpose(mat)).tolist() + theo = matop.transpose(mat, return_map=False) + assert theo == act