scikit-image

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from numpy.testing import assert_array_equal
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from skimage.color import rgb2gray
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from skimage.data import astronaut, cells3d
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from skimage.filters import gaussian
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from skimage.measure import blur_effect
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def test_blur_effect():
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    """Test that the blur metric increases with more blurring."""
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    image = astronaut()
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    B0 = blur_effect(image, channel_axis=-1)
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    B1 = blur_effect(gaussian(image, sigma=1, channel_axis=-1), channel_axis=-1)
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    B2 = blur_effect(gaussian(image, sigma=4, channel_axis=-1), channel_axis=-1)
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    assert 0 <= B0 < 1
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    assert B0 < B1 < B2
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def test_blur_effect_h_size():
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    """Test that the blur metric decreases with increasing size of the
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    re-blurring filter.
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    """
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    image = astronaut()
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    B0 = blur_effect(image, h_size=3, channel_axis=-1)
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    B1 = blur_effect(image, channel_axis=-1)  # default h_size is 11
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    B2 = blur_effect(image, h_size=30, channel_axis=-1)
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    assert 0 <= B0 < 1
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    assert B0 > B1 > B2
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def test_blur_effect_channel_axis():
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    """Test that passing an RGB image is equivalent to passing its grayscale
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    version.
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    """
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    image = astronaut()
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    B0 = blur_effect(image, channel_axis=-1)
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    B1 = blur_effect(rgb2gray(image))
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    B0_arr = blur_effect(image, channel_axis=-1, reduce_func=None)
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    B1_arr = blur_effect(rgb2gray(image), reduce_func=None)
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    assert 0 <= B0 < 1
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    assert B0 == B1
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    assert_array_equal(B0_arr, B1_arr)
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def test_blur_effect_3d():
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    """Test that the blur metric works on a 3D image."""
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    image_3d = cells3d()[:, 1, :, :]  # grab just the nuclei
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    B0 = blur_effect(image_3d)
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    B1 = blur_effect(gaussian(image_3d, sigma=1))
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    B2 = blur_effect(gaussian(image_3d, sigma=4))
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    assert 0 <= B0 < 1
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    assert B0 < B1 < B2
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