def test_multichannel():
a = np.zeros((5, 5, 3))
a[1, 1] = np.arange(1, 4)
gaussian_rgb_a = gaussian_filter(a, sigma=1, mode='reflect',
multichannel=True)
# Check that the mean value is conserved in each channel
# (color channels are not mixed together)
assert np.allclose([a[..., i].mean() for i in range(3)],
[gaussian_rgb_a[..., i].mean() for i in range(3)])
# Test multichannel = None
gaussian_rgb_a = gaussian_filter(a, sigma=1, mode='reflect')
# Check that the mean value is conserved in each channel
# (color channels are not mixed together)
assert np.allclose([a[..., i].mean() for i in range(3)],
[gaussian_rgb_a[..., i].mean() for i in range(3)])
# Iterable sigma
gaussian_rgb_a = gaussian_filter(a, sigma=[1, 2], mode='reflect',
multichannel=True)
assert np.allclose([a[..., i].mean() for i in range(3)],
[gaussian_rgb_a[..., i].mean() for i in range(3)])
def test_null_sigma():
a = np.zeros((3, 3))
a[1, 1] = 1.
assert np.all(gaussian_filter(a, 0) == a)
def test_energy_decrease():
a = np.zeros((3, 3))
a[1, 1] = 1.
gaussian_a = gaussian_filter(a, sigma=1, mode='reflect')
assert gaussian_a.std() < a.std()
