def test_difference_of_gaussians(s, s2):
image = np.random.rand(10, 10)
im1 = gaussian(image, s, preserve_range=True)
im2 = gaussian(image, s2, preserve_range=True)
dog = im1 - im2
dog2 = difference_of_gaussians(image, s, s2)
assert np.allclose(dog, dog2)
def test_auto_sigma2(s):
image = np.random.rand(10, 10)
im1 = gaussian(image, s, preserve_range=True)
s2 = 1.6 * np.array(s)
im2 = gaussian(image, s2, preserve_range=True)
dog = im1 - im2
dog2 = difference_of_gaussians(image, s, s2)
assert np.allclose(dog, dog2)
def test_dog_invalid_sigma_dims():
image = np.ones((5, 5, 3))
with pytest.raises(ValueError):
difference_of_gaussians(image, (1, 2))
with pytest.raises(ValueError):
difference_of_gaussians(image, 1, (3, 4))
with pytest.raises(ValueError):
with expected_warnings(["`multichannel` is a deprecated argument"]):
difference_of_gaussians(image, (1, 2, 3), multichannel=True)
with pytest.raises(ValueError):
difference_of_gaussians(image, (1, 2, 3), channel_axis=-1)
def test_dog_invalid_sigma_dims():
image = np.ones((5, 5, 3))
with testing.raises(ValueError):
difference_of_gaussians(image, (1, 2))
with testing.raises(ValueError):
difference_of_gaussians(image, 1, (3, 4))
with testing.raises(ValueError):
difference_of_gaussians(image, (1, 2, 3), multichannel=True)
def test_dog_invalid_sigma2():
image = np.ones((3, 3))
with pytest.raises(ValueError):
difference_of_gaussians(image, 3, 2)
with pytest.raises(ValueError):
difference_of_gaussians(image, (1, 5), (2, 4))
