From 4e0717c3cfb336aa86f6720f2f49adf58f0e95d7 Mon Sep 17 00:00:00 2001 From: Stephen Gemin <45926479+StephenGemin@users.noreply.github.com> Date: Fri, 19 Jul 2019 23:06:29 -0400 Subject: [PATCH] Add error & test checks for matrix_operations.py (#925) * Update matrix_operation.py 1. Adding error checks for integer inputs 2. Adding error checks for matrix operations where size requirements do not match up 3. Added matrix subtraction function 4. included error check so only integer is passed into identity function * Create test_matrix_operation.py * Update matrix_ops and Add Test Cases 1. Included error checks in matrix operation. There were some cases where the functions would not work correctly. 2. PEP8 changes to matrix_operations.py 3. added test cases for matrix operations using pytest. * Update pytest.ini Add carriage return to end of file --- matrix/matrix_operation.py | 136 +++++++++++++++++++------- matrix/tests/pytest.ini | 3 + matrix/tests/test_matrix_operation.py | 112 +++++++++++++++++++++ 3 files changed, 217 insertions(+), 34 deletions(-) create mode 100644 matrix/tests/pytest.ini create mode 100644 matrix/tests/test_matrix_operation.py 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