def test_segmentation_centroid(self, small_cont_seg: ImageContainer):
features = small_cont_seg.features_segmentation(
label_layer="segmented", intensity_layer=None, feature_name="foo", props=["centroid"]
)
assert isinstance(features, dict)
assert "foo_centroid" in features
assert isinstance(features["foo_centroid"], np.ndarray)
assert features["foo_centroid"].ndim == 2
def test_segmentation_props(self, small_cont_seg: ImageContainer, props: Sequence[str]):
if not len(props):
with pytest.raises(ValueError, match=r"No properties have been selected."):
small_cont_seg.features_segmentation(
label_layer="segmented", intensity_layer="image", feature_name="foo", props=props
)
else:
features = small_cont_seg.features_segmentation(
label_layer="segmented", intensity_layer="image", feature_name="foo", props=props, channels=[0]
)
haystack = features.keys()
int_props = [p for p in props if "intensity" in props]
no_int_props = [p for p in props if "intensity" not in props]
for p in no_int_props:
assert any(f"{p}_mean" in h for h in haystack), haystack
assert any(f"{p}_std" in h for h in haystack), haystack
for p in int_props:
assert any(f"ch-0_{p}_mean" in h for h in haystack), haystack
assert any(f"ch-0_{p}_std" in h for h in haystack), haystack
def test_segmentation_label(self, small_cont_seg: ImageContainer):
features = small_cont_seg.features_segmentation("image", feature_name="foo", props=["label"])
assert isinstance(features, dict)
assert "foo_label" in features
assert features["foo_label"] == 254
def test_segmentation_invalid_props(self, small_cont: ImageContainer):
with pytest.raises(ValueError, match=r"Invalid property `foobar`. Valid properties are"):
small_cont.features_segmentation("image", feature_name="foo", props=["foobar"])