def test_crop_corner_scale(self, scale: float):
shape_img = (50, 50)
img = ImageContainer(np.zeros(shape_img))
if scale <= 0:
with pytest.raises(
ValueError,
match=r"Expected `scale` to be positive, found `0`."):
img.crop_corner(10, 10, size=20, scale=scale)
else:
crop = img.crop_corner(10, 10, size=20, scale=scale)
assert crop.shape == tuple(int(i * scale) for i in (20, 20))
def test_plot_crop_center(self, qtbot, adata: AnnData, napari_cont: ImageContainer):
viewer = napari_cont.crop_corner(0, 0, size=500).interactive(adata)
bdata = viewer.adata
cnt = viewer._controller
cnt.add_points(bdata.obs_vector(bdata.var_names[42]), layer_name="foo")
viewer.screenshot(dpi=DPI)
def test_crop_metadata(self, small_cont_1c: ImageContainer, dy: int):
crop = small_cont_1c.crop_corner(dy, 0, 50, mask_circle=True)
assert small_cont_1c.data.attrs[Key.img.coords] is _NULL_COORDS
assert crop.data.attrs[Key.img.coords] == CropCoords(0, 0, 50, 50 + dy)
assert crop.data.attrs[Key.img.padding] == CropPadding(x_pre=0,
y_pre=abs(dy),
x_post=0,
y_post=0)
assert crop.data.attrs[Key.img.mask_circle]
def test_crop_corner_mask_circle(self, small_cont_1c: ImageContainer,
size: Tuple[int, int]):
if size[0] != size[1]:
with pytest.raises(ValueError, match=r"Masking circle is only"):
small_cont_1c.crop_corner(0,
0,
size=size,
mask_circle=True,
cval=np.nan)
else:
crop = small_cont_1c.crop_corner(0,
0,
size=20,
mask_circle=True,
cval=np.nan)
mask = (crop.data.x - 10)**2 + (crop.data.y - 10)**2 <= 10**2
assert crop.shape == (20, 20)
np.testing.assert_array_equal(
crop["image"].values[..., 0][~mask.values], np.nan)
def test_preserve_dtypes(self, cont: ImageContainer, preserve: bool):
assert np.issubdtype(cont["image"].dtype, np.uint8)
crop = cont.crop_corner(-10,
-10,
20,
cval=-5,
preserve_dtypes=preserve)
if preserve:
assert np.issubdtype(crop["image"].dtype, np.uint8)
# we specifically use 0, otherwise overflow would happend and the value would be 256 - 5
np.testing.assert_array_equal(crop["image"][:10, :10], 0)
else:
assert np.issubdtype(crop["image"].dtype, np.signedinteger)
np.testing.assert_array_equal(crop["image"][:10, :10], -5)
def test_big_crop(self, cont_dot: ImageContainer):
crop = cont_dot.crop_center(
y=50,
x=20,
radius=150,
cval=5,
)
np.testing.assert_array_equal(crop.data["image_0"].shape,
(301, 301, 10))
# check that values outside of img are padded with 5
np.testing.assert_array_equal(crop.data["image_0"][0, 0, 0], 5)
np.testing.assert_array_equal(crop.data["image_0"][-1, -1, 0], 5)
assert crop.data["image_0"].dtype == np.uint8
# compare with crop_corner
crop2 = cont_dot.crop_corner(y=-100, x=-130, size=301, cval=5)
np.testing.assert_array_equal(crop2.data["image_0"],
crop.data["image_0"])
def test_crop_corner_size(self, small_cont_1c: ImageContainer,
dy: Optional[Union[int, float]],
dx: Optional[Union[int, float]]):
crop = small_cont_1c.crop_corner(dy, dx, size=20)
# original coordinates
ody, odx = max(dy, 0), max(dx, 0)
ody = int(ody *
small_cont_1c.shape[0]) if isinstance(ody, float) else ody
odx = int(odx *
small_cont_1c.shape[1]) if isinstance(odx, float) else odx
# crop coordinates
cdy = 0 if isinstance(dy, float) or dy > 0 else dy
cdx = 0 if isinstance(dx, float) or dx > 0 else dx
cdy, cdx = abs(cdy), abs(cdx)
assert crop.shape == (20, 20)
cdata, odata = crop["image"].data, small_cont_1c["image"].data
cdata = cdata[cdy:, cdx:]
np.testing.assert_array_equal(
cdata, odata[ody:ody + cdata.shape[0], odx:odx + cdata.shape[1]])
def test_test_crop_corner_cval(self, cval: float):
shape_img = (50, 50)
img = ImageContainer(np.zeros(shape_img))
crop = img.crop_corner(10, 10, cval=cval)
np.testing.assert_array_equal(crop["image"].data[-10:, -10:], cval)
