tdd-sc-example-02.py

import numpy as np
import pytest


# Test multiple dtypes at once
@pytest.mark.parametrize(
    "dtype", ["int8", "int16", "float16", "float32", "float64", "float128"]
)
def test_zero(dtype):
    # Set random seed
    seed = int(np.random.rand() * (2**32 - 1))
    np.random.seed(seed)

    # Create a 2D array of random shape and fill with zeros
    nx, ny = np.random.randint(3, 100, size=(2,))
    arr = np.zeros((nx, ny), dtype=dtype)

    # Apply sobel function
    arr_sob = sobel(arr)

    # `assert_array_equal` should fail most of the times.
    # It will only work when `arr_sob` is identically zero,
    # which is usually not the case. Don't use it!
    # np.testing.assert_array_equal(arr_sob, 0.0, err_msg=f"{seed=} {nx=}, {ny=}")

    # `assert_almost_equal` can fail when used with high decimals.
    # It also relies on float64 checking, which might fail for
    # float 128 types. I would avoid using it.
    # np.testing.assert_almost_equal(
    #     arr_sob, np.zeros_like(arr), err_msg=f"{seed=} {nx=}, {ny=}", decimal=40
    # )

    # `assert_allclose` with custom tolerance is my preferred method
    # The 10 is arbitrary and depends on the problem. If a method
    # which you know to be correct does not pass, increase to 100, etc.
    # If the tolerance needed to make the tests pass is too high, make
    # sure the method is actually correct.
    tol = 10 * np.finfo(arr.dtype).eps
    err_msg = f"{seed=} {nx=}, {ny=} {tol=}"  # Log seeds and other info
    np.testing.assert_allclose(
        arr_sob,
        np.zeros_like(arr),
        err_msg=err_msg,
        atol=tol,  # rtol is useless for desired=zeros
    )

@pytest.mark.parametrize(
    "dtype", ["int8", "int16", "float16", "float32", "float64", "float128"]
)
def test_constant(dtype):
    seed = int(np.random.rand() * (2**32 - 1))
    np.random.seed(seed)

    nx, ny = np.random.randint(3, 100, size=(2,))
    constant = np.random.randn(1).item()
    arr = np.full((nx, ny), fill_value=constant, dtype=dtype)
    arr_sob = sobel(arr)


    tol = 10 * np.finfo(arr.dtype).eps
    err_msg = f"{seed=} {nx=}, {ny=} {tol=}"
    np.testing.assert_allclose(
        arr_sob,
        np.zeros_like(arr),
        err_msg=err_msg,
        atol=tol,  # rtol is useless for desired=zeros
    )