def test_slow_warp_nonint_oshape():
image = cp.random.rand(5, 5)
with pytest.raises(ValueError):
warp(image, lambda xy: xy, output_shape=(13.1, 19.5))
warp(image, lambda xy: xy, output_shape=(13.0001, 19.9999))
def test_warp_matrix():
x = cp.zeros((5, 5), dtype=np.double)
x[2, 2] = 1
refx = cp.zeros((5, 5), dtype=np.double)
refx[1, 1] = 1
matrix = cp.asarray([[1, 0, 1], [0, 1, 1], [0, 0, 1]])
# _warp_fast
outx = warp(x, matrix, order=1)
assert_array_almost_equal(outx, refx)
# check for ndimage.map_coordinates
outx = warp(x, matrix, order=5)
def test_warp_identity():
img = img_as_float(cp.array(rgb2gray(astronaut())))
assert len(img.shape) == 2
assert cp.allclose(img, warp(img, AffineTransform(rotation=0)))
assert not cp.allclose(img, warp(img, AffineTransform(rotation=0.1)))
img = cp.asnumpy(img)
rgb_img = cp.transpose(
cp.asarray(np.array([img, np.zeros_like(img), img])), (1, 2, 0))
warped_rgb_img = warp(rgb_img, AffineTransform(rotation=0.1))
assert cp.allclose(rgb_img, warp(rgb_img, AffineTransform(rotation=0)))
assert not cp.allclose(rgb_img, warped_rgb_img)
# assert no cross-talk between bands
assert cp.all(0 == warped_rgb_img[:, :, 1])
def test_warp_tform():
x = cp.zeros((5, 5), dtype=np.double)
x[2, 2] = 1
theta = -np.pi / 2
tform = SimilarityTransform(scale=1,
rotation=theta,
translation=(0, 4),
xp=cp)
x90 = warp(x, tform, order=1)
assert_array_almost_equal(x90, cp.rot90(x))
x90 = warp(x, tform.inverse, order=1)
assert_array_almost_equal(x90, cp.rot90(x))
def test_zero_image_size():
with pytest.raises(ValueError):
warp(cp.zeros(0), SimilarityTransform())
with pytest.raises(ValueError):
warp(cp.zeros((0, 10)), SimilarityTransform())
with pytest.raises(ValueError):
warp(cp.zeros((10, 0)), SimilarityTransform())
with pytest.raises(ValueError):
warp(cp.zeros((10, 10, 0)), SimilarityTransform())
def test_bool_array_warnings():
img = cp.zeros((10, 10), dtype=bool)
with expected_warnings(['Input image dtype is bool']):
rescale(img, 0.5, anti_aliasing=True)
with expected_warnings(['Input image dtype is bool']):
resize(img, (5, 5), anti_aliasing=True)
with expected_warnings(['Input image dtype is bool']):
rescale(img, 0.5, order=1)
with expected_warnings(['Input image dtype is bool']):
resize(img, (5, 5), order=1)
with expected_warnings(['Input image dtype is bool']):
warp(img, cp.eye(3), order=1)
def test_warp_callable():
x = cp.zeros((5, 5), dtype=np.double)
x[2, 2] = 1
refx = cp.zeros((5, 5), dtype=np.double)
refx[1, 1] = 1
def shift(xy):
return xy + 1
outx = warp(x, shift, order=1)
assert_array_almost_equal(outx, refx)
def test_homography():
x = cp.zeros((5, 5), dtype=np.double)
x[1, 1] = 1
theta = -np.pi / 2
# fmt: off
M = cp.array([[np.cos(theta), -np.sin(theta), 0],
[np.sin(theta), np.cos(theta), 4], [0, 0, 1]])
# fmt: on
x90 = warp(x, inverse_map=ProjectiveTransform(M).inverse, order=1)
assert_array_almost_equal(x90, cp.rot90(x))
def test_warp_nd():
for dim in range(2, 8):
shape = dim * (5, )
x = cp.zeros(shape, dtype=np.double)
x_c = dim * (2, )
x[x_c] = 1
refx = cp.zeros(shape, dtype=np.double)
refx_c = dim * (1, )
refx[refx_c] = 1
coord_grid = dim * (slice(0, 5, 1), )
coords = cp.array(cp.mgrid[coord_grid]) + 1
outx = warp(x, coords, order=0, cval=0)
assert_array_almost_equal(outx, refx)
def test_inverse():
tform = SimilarityTransform(scale=0.5, rotation=0.1)
inverse_tform = SimilarityTransform(matrix=cp.linalg.inv(tform.params))
image = cp.arange(10 * 10).reshape(10, 10).astype(cp.double)
assert_array_equal(warp(image, inverse_tform), warp(image, tform.inverse))
def test_invalid():
with pytest.raises(ValueError):
warp(cp.ones((4, 3, 3, 3)), SimilarityTransform())
def test_const_cval_out_of_range():
img = cp.random.randn(100, 100)
cval = -10
warped = warp(img, AffineTransform(translation=(10, 10)), cval=cval)
assert cp.sum(warped == cval) == (2 * 100 * 10 - 10 * 10)
