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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
This commit is contained in:
Stephen Gemin
Christian Clauss
parent
dc1de946ea
commit
4e0717c3cf
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@ -1,64 +1,131 @@
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from __future__ import print_function
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"""
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function based version of matrix operations, which are just 2D arrays
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"""
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def add(matrix_a, matrix_b):
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rows = len(matrix_a)
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columns = len(matrix_a[0])
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matrix_c = []
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for i in range(rows):
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list_1 = []
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for j in range(columns):
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val = matrix_a[i][j] + matrix_b[i][j]
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list_1.append(val)
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matrix_c.append(list_1)
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return matrix_c
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if _check_not_integer(matrix_a) and _check_not_integer(matrix_b):
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rows, cols = _verify_matrix_sizes(matrix_a, matrix_b)
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matrix_c = []
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for i in range(rows[0]):
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list_1 = []
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for j in range(cols[0]):
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val = matrix_a[i][j] + matrix_b[i][j]
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list_1.append(val)
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matrix_c.append(list_1)
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return matrix_c
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def scalarMultiply(matrix , n):
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def subtract(matrix_a, matrix_b):
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if _check_not_integer(matrix_a) and _check_not_integer(matrix_b):
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rows, cols = _verify_matrix_sizes(matrix_a, matrix_b)
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matrix_c = []
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for i in range(rows[0]):
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list_1 = []
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for j in range(cols[0]):
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val = matrix_a[i][j] - matrix_b[i][j]
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list_1.append(val)
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matrix_c.append(list_1)
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return matrix_c
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def scalar_multiply(matrix, n):
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return [[x * n for x in row] for row in matrix]
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def multiply(matrix_a, matrix_b):
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matrix_c = []
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n = len(matrix_a)
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for i in range(n):
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list_1 = []
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for j in range(n):
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val = 0
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for k in range(n):
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val = val + matrix_a[i][k] * matrix_b[k][j]
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list_1.append(val)
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matrix_c.append(list_1)
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return matrix_c
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if _check_not_integer(matrix_a) and _check_not_integer(matrix_b):
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matrix_c = []
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rows, cols = _verify_matrix_sizes(matrix_a, matrix_b)
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if cols[0] != rows[1]:
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raise ValueError(f'Cannot multiply matrix of dimensions ({rows[0]},{cols[0]}) '
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f'and ({rows[1]},{cols[1]})')
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for i in range(rows[0]):
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list_1 = []
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for j in range(cols[1]):
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val = 0
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for k in range(cols[1]):
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val = val + matrix_a[i][k] * matrix_b[k][j]
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list_1.append(val)
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matrix_c.append(list_1)
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return matrix_c
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def identity(n):
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"""
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:param n: dimension for nxn matrix
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:type n: int
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:return: Identity matrix of shape [n, n]
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"""
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n = int(n)
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return [[int(row == column) for column in range(n)] for row in range(n)]
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def transpose(matrix):
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return map(list , zip(*matrix))
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def transpose(matrix, return_map=True):
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if _check_not_integer(matrix):
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if return_map:
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return map(list, zip(*matrix))
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else:
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# mt = []
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# for i in range(len(matrix[0])):
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# mt.append([row[i] for row in matrix])
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# return mt
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return [[row[i] for row in matrix] for i in range(len(matrix[0]))]
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def minor(matrix, row, column):
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minor = matrix[:row] + matrix[row + 1:]
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minor = [row[:column] + row[column + 1:] for row in minor]
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return minor
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def determinant(matrix):
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if len(matrix) == 1: return matrix[0][0]
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if len(matrix) == 1:
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return matrix[0][0]
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res = 0
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for x in range(len(matrix)):
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res += matrix[0][x] * determinant(minor(matrix , 0 , x)) * (-1) ** x
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res += matrix[0][x] * determinant(minor(matrix, 0, x)) * (-1) ** x
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return res
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def inverse(matrix):
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det = determinant(matrix)
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if det == 0: return None
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if det == 0:
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return None
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matrixMinor = [[] for _ in range(len(matrix))]
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matrix_minor = [[] for _ in range(len(matrix))]
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for i in range(len(matrix)):
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for j in range(len(matrix)):
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matrixMinor[i].append(determinant(minor(matrix , i , j)))
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matrix_minor[i].append(determinant(minor(matrix, i, j)))
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cofactors = [[x * (-1) ** (row + col) for col, x in enumerate(matrixMinor[row])] for row in range(len(matrix))]
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cofactors = [[x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row])] for row in range(len(matrix))]
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adjugate = transpose(cofactors)
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return scalarMultiply(adjugate , 1/det)
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return scalar_multiply(adjugate, 1/det)
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def _check_not_integer(matrix):
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try:
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rows = len(matrix)
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cols = len(matrix[0])
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return True
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except TypeError:
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raise TypeError("Cannot input an integer value, it must be a matrix")
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def _shape(matrix):
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return list((len(matrix), len(matrix[0])))
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def _verify_matrix_sizes(matrix_a, matrix_b):
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shape = _shape(matrix_a)
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shape += _shape(matrix_b)
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if shape[0] != shape[2] or shape[1] != shape[3]:
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raise ValueError(f"operands could not be broadcast together with shape "
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f"({shape[0], shape[1]}), ({shape[2], shape[3]})")
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return [shape[0], shape[2]], [shape[1], shape[3]]
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def main():
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matrix_a = [[12, 10], [3, 9]]
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@ -68,9 +135,10 @@ def main():
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print('Add Operation, %s + %s = %s \n' %(matrix_a, matrix_b, (add(matrix_a, matrix_b))))
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print('Multiply Operation, %s * %s = %s \n' %(matrix_a, matrix_b, multiply(matrix_a, matrix_b)))
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print('Identity: %s \n' %identity(5))
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print('Minor of %s = %s \n' %(matrix_c, minor(matrix_c , 1 , 2)))
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print('Minor of %s = %s \n' %(matrix_c, minor(matrix_c, 1, 2)))
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print('Determinant of %s = %s \n' %(matrix_b, determinant(matrix_b)))
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print('Inverse of %s = %s\n'%(matrix_d, inverse(matrix_d)))
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if __name__ == '__main__':
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main()
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3
matrix/tests/pytest.ini
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3
matrix/tests/pytest.ini
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@ -0,0 +1,3 @@
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[pytest]
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markers =
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mat_ops: tests for matrix operations
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112
matrix/tests/test_matrix_operation.py
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112
matrix/tests/test_matrix_operation.py
Normal file
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@ -0,0 +1,112 @@
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"""
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Testing here assumes that numpy and linalg is ALWAYS correct!!!!
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If running from PyCharm you can place the following line in "Additional Arguments" for the pytest run configuration
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-vv -m mat_ops -p no:cacheprovider
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"""
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# standard libraries
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import sys
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import numpy as np
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import pytest
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import logging
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# Custom/local libraries
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from matrix import matrix_operation as matop
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mat_a = [[12, 10], [3, 9]]
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mat_b = [[3, 4], [7, 4]]
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mat_c = [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
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mat_d = [[3, 0, -2], [2, 0, 2], [0, 1, 1]]
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mat_e = [[3, 0, 2], [2, 0, -2], [0, 1, 1], [2, 0, -2]]
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mat_f = [1]
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mat_h = [2]
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logger = logging.getLogger()
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logger.level = logging.DEBUG
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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@pytest.mark.mat_ops
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@pytest.mark.parametrize(('mat1', 'mat2'), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e),
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(mat_f, mat_h)])
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def test_addition(mat1, mat2):
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if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2):
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with pytest.raises(TypeError):
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logger.info(f"\n\t{test_addition.__name__} returned integer")
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matop.add(mat1, mat2)
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elif (np.array(mat1)).shape == (np.array(mat2)).shape:
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logger.info(f"\n\t{test_addition.__name__} with same matrix dims")
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act = (np.array(mat1) + np.array(mat2)).tolist()
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theo = matop.add(mat1, mat2)
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assert theo == act
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else:
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with pytest.raises(ValueError):
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logger.info(f"\n\t{test_addition.__name__} with different matrix dims")
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matop.add(mat1, mat2)
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@pytest.mark.mat_ops
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@pytest.mark.parametrize(('mat1', 'mat2'), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e),
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(mat_f, mat_h)])
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def test_subtraction(mat1, mat2):
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if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2):
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with pytest.raises(TypeError):
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logger.info(f"\n\t{test_subtraction.__name__} returned integer")
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matop.subtract(mat1, mat2)
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elif (np.array(mat1)).shape == (np.array(mat2)).shape:
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logger.info(f"\n\t{test_subtraction.__name__} with same matrix dims")
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act = (np.array(mat1) - np.array(mat2)).tolist()
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theo = matop.subtract(mat1, mat2)
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assert theo == act
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else:
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with pytest.raises(ValueError):
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logger.info(f"\n\t{test_subtraction.__name__} with different matrix dims")
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assert matop.subtract(mat1, mat2)
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@pytest.mark.mat_ops
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@pytest.mark.parametrize(('mat1', 'mat2'), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e),
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(mat_f, mat_h)])
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def test_multiplication(mat1, mat2):
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if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2):
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logger.info(f"\n\t{test_multiplication.__name__} returned integer")
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with pytest.raises(TypeError):
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matop.add(mat1, mat2)
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elif (np.array(mat1)).shape == (np.array(mat2)).shape:
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logger.info(f"\n\t{test_multiplication.__name__} meets dim requirements")
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act = (np.matmul(mat1, mat2)).tolist()
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theo = matop.multiply(mat1, mat2)
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assert theo == act
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else:
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with pytest.raises(ValueError):
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logger.info(f"\n\t{test_multiplication.__name__} does not meet dim requirements")
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assert matop.subtract(mat1, mat2)
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@pytest.mark.mat_ops
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def test_scalar_multiply():
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act = (3.5 * np.array(mat_a)).tolist()
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theo = matop.scalar_multiply(mat_a, 3.5)
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assert theo == act
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@pytest.mark.mat_ops
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def test_identity():
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act = (np.identity(5)).tolist()
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theo = matop.identity(5)
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assert theo == act
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@pytest.mark.mat_ops
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@pytest.mark.parametrize('mat', [mat_a, mat_b, mat_c, mat_d, mat_e, mat_f])
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def test_transpose(mat):
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if (np.array(mat)).shape < (2, 2):
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with pytest.raises(TypeError):
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logger.info(f"\n\t{test_transpose.__name__} returned integer")
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matop.transpose(mat)
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else:
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act = (np.transpose(mat)).tolist()
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theo = matop.transpose(mat, return_map=False)
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assert theo == act
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