def test_multiotsu_more_classes_then_values():
img = cp.ones((10, 10), dtype=cp.uint8)
with testing.raises(ValueError):
threshold_multiotsu(img, classes=2)
img[:, 3:] = 2
with testing.raises(ValueError):
threshold_multiotsu(img, classes=3)
img[:, 6:] = 3
with testing.raises(ValueError):
threshold_multiotsu(img, classes=4)
def test_correlate_sparse_invalid_kernel(mode):
image = cp.array([[0, 0, 1, 3, 5], [0, 1, 4, 3, 4], [1, 2, 5, 4, 1],
[2, 4, 5, 2, 1], [4, 5, 1, 0, 0]],
dtype=float)
# invalid kernel size
invalid_kernel = cp.array([0, 1, 2, 4]).reshape((2, 2))
with testing.raises(ValueError):
correlate_sparse(image, invalid_kernel, mode=mode)
def test_bad_inputs():
# Too few dimensions
img = cp.ones(10)
labels = cp.arange(10)
with testing.raises(ValueError):
random_walker(img, labels)
with testing.raises(ValueError):
random_walker(img, labels, multichannel=True)
# Too many dimensions
np.random.seed(42)
img = cp.array(np.random.normal(size=(3, 3, 3, 3, 3)))
labels = cp.arange(3**5).reshape(img.shape)
with testing.raises(ValueError):
random_walker(img, labels)
with testing.raises(ValueError):
random_walker(img, labels, multichannel=True)
# Spacing incorrect length
img = cp.array(np.random.normal(size=(10, 10)))
labels = cp.zeros((10, 10))
labels[2, 4] = 2
labels[6, 8] = 5
with testing.raises(ValueError):
random_walker(img, labels, spacing=cp.array((1, )))
# Invalid mode
img = cp.array(np.random.normal(size=(10, 10)))
labels = cp.zeros((10, 10))
with testing.raises(ValueError):
random_walker(img, labels, mode='bad')
def test_threshold_minimum_failure():
img = cp.zeros((16 * 16), dtype=cp.uint8)
with testing.raises(RuntimeError):
threshold_minimum(img)
def test_local_even_block_size_error():
img = camerad
with testing.raises(ValueError):
threshold_local(img, block_size=4)
def test_li_negative_inital_guess():
with testing.raises(ValueError):
threshold_li(coinsd, initial_guess=-5)
def test_wrong_dtype():
rnd = cp.random.RandomState(0)
img = rnd.normal(size=(256, 256))
with testing.raises(ValueError):
u, v = optical_flow_ilk(img, img, dtype='int')
def test_incompatible_shapes():
rnd = cp.random.RandomState(0)
I0 = rnd.normal(size=(256, 256))
I1 = rnd.normal(size=(255, 256))
with testing.raises(ValueError):
u, v = optical_flow_ilk(I0, I1)