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"""

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

"""

import logging

# standard libraries

import sys

import numpy as np

import pytest # type: ignore

# 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

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