mirror of
https://github.com/TheAlgorithms/Python.git
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4c76e3cba0
* [mypy] Added/fixed type annotations for "rotate_matrix.py" * [mypy] Added/fixed type annotations for "test_matrix_operation.py"
121 lines
3.9 KiB
Python
121 lines
3.9 KiB
Python
"""
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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
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the pytest run configuration
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-vv -m mat_ops -p no:cacheprovider
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"""
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import logging
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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 # type: ignore
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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(
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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)
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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(
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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)
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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(
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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)
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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(
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f"\n\t{test_multiplication.__name__} does not meet dim requirements"
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)
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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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