def test_nan_const():
img = 123 * np.ones((100, 100), dtype=float)
img[20, 20] = np.nan
img[50, 53] = np.nan
kernel_shape = (10, 10)
x = np.arange(-kernel_shape[1] // 2,
kernel_shape[1] // 2 + 1)[np.newaxis, :]
y = np.arange(-kernel_shape[0] // 2, kernel_shape[0] // 2 + 1)[:,
np.newaxis]
expected_img = np.zeros_like(img)
expected_img[y + 20, x + 20] = np.nan
expected_img[y + 50, x + 53] = np.nan
kernel = ellipsoid_kernel(kernel_shape, 100)
background = rolling_ball(img, kernel=kernel, nansafe=True)
assert np.allclose(img - background, expected_img, equal_nan=True)
def test_ndim():
image = data.cells3d()[:5, 1, ...]
kernel = ellipsoid_kernel((3, 100, 100), 100)
rolling_ball(image, kernel=kernel)
def test_ellipsoid_const(dtype):
img = 155 * np.ones((100, 100), dtype=dtype)
kernel = ellipsoid_kernel((25, 53), 50)
background = rolling_ball(img, kernel=kernel)
assert np.allclose(img - background, np.zeros_like(img))
assert background.dtype == img.dtype
def time_rollingball_ndim(self):
from skimage.restoration.rolling_ball import ellipsoid_kernel
image = data.cells3d()[:, 1, ...]
kernel = ellipsoid_kernel((1, 100, 100), 100)
restoration.rolling_ball(image, kernel=kernel)
