add unit test for beam hardening

logger = logging.getLogger(__name__)

class beam_hardening_correction(param.Parameterized):

class beam_hardening_correction(param.ParameterizedFunction):

    """Imaging correction for beam hardening.

    Parameters

"""Unit test for beam hardening correction"""

#!/usr/bin/env python

import numpy as np

import pytest

from imars3d.backend.corrections.beam_hardening import beam_hardening_correction

@pytest.fixture(scope="module")

def fake_beam_hardening_image() -> np.ndarray:

    """Use a checker board image as the fake beam hardening image

    Returns

    -------

    np.ndarray

        A checker board image stack

    NOTE

    ----

    As of 02-15-2024, the dev team did not receive needed testing data

    for beam hardening correction, a synthetic image is used for testing.

    """

    np.random.seed(42)

    image_stack = []

    image_size = 255

    image = np.zeros((image_size, image_size))

    for i in range(image_size):

        for j in range(image_size):

            if (i + j) % 2 == 0:

                image[i, j] = 1

    # flip the image to create a stack

    for _ in range(10):

        if np.random.rand() > 0.5:

            image = np.flip(image, axis=0)

        else:

            image = np.flip(image, axis=1)

        image_stack.append(image)

    return np.stack(image_stack, axis=0)

def test_beam_hardening_correction(fake_beam_hardening_image):

    """Test beam hardening correction"""

    # test the correction

    corrected_image = beam_hardening_correction(

        arrays=fake_beam_hardening_image,

        q=0.005,

        n=20.0,

        opt=True,

    )

    assert corrected_image.shape == (10, 255, 255)

    assert corrected_image.dtype == np.float64

    assert np.all(corrected_image >= 0)

if __name__ == "__main__":

    pytest.main([__file__])