def test_from_numpy_array_raises_error_when_incorrect_dims_passed():
array = np.ones((2, 2))
# verify this method works with the correct shape
image = ImageStack.from_numpy_array(array.reshape((1, 1, 1, 2, 2)))
assert isinstance(image, ImageStack)
with pytest.raises(ValueError):
ImageStack.from_numpy_array(array.reshape((1, 1, 2, 2)))
ImageStack.from_numpy_array(array.reshape((1, 2, 2)))
ImageStack.from_numpy_array(array)
ImageStack.from_numpy_array(array.reshape((1, 1, 1, 1, 2, 2)))
def test_max_projection_preserves_dtype():
original_dtype = np.uint16
array = np.ones((2, 2, 2), dtype=original_dtype)
image = ImageStack.from_numpy_array(array.reshape((1, 1, 2, 2, 2)))
max_projection = image.max_proj(Indices.CH, Indices.HYB, Indices.Z)
assert max_projection.dtype == original_dtype
def test_iss_pipeline():
np.random.seed(2)
synthesizer = SyntheticData(n_spots=5)
codebook = synthesizer.codebook()
true_intensities = synthesizer.intensities(codebook=codebook)
image = synthesizer.spots(intensities=true_intensities)
dots_data = image.max_proj(Indices.HYB, Indices.CH, Indices.Z)
dots = ImageStack.from_numpy_array(
dots_data.reshape((1, 1, 1, *dots_data.shape)))
wth = WhiteTophat(disk_size=15)
wth.filter(image)
wth.filter(dots)
fsr = FourierShiftRegistration(upsampling=1000, reference_stack=dots)
fsr.register(image)
min_sigma = 1.5
max_sigma = 5
num_sigma = 10
threshold = 1e-4
gsd = GaussianSpotDetector(
min_sigma=min_sigma,
max_sigma=max_sigma,
num_sigma=num_sigma,
threshold=threshold,
blobs_stack=dots,
measurement_type='max',
)
intensities = gsd.find(hybridization_image=image)
assert intensities.shape[0] == 5
codebook.decode_euclidean(intensities)
def labeled_synthetic_dataset():
stp = synthesize.SyntheticSpotTileProvider()
image = ImageStack.synthetic_stack(tile_data_provider=stp.tile)
max_proj = image.max_proj(Indices.HYB, Indices.CH, Indices.Z)
view = max_proj.reshape((1, 1, 1) + max_proj.shape)
dots = ImageStack.from_numpy_array(view)
def labeled_synthetic_dataset_factory():
return deepcopy(image), deepcopy(dots), deepcopy(stp.codebook)
return labeled_synthetic_dataset_factory
def test_from_numpy_array_preserves_dtype():
original_dtype = np.uint16
array = np.ones((2, 2, 2), dtype=original_dtype)
image = ImageStack.from_numpy_array(array.reshape((1, 1, 2, 2, 2)))
assert image.numpy_array.dtype == original_dtype
def test_from_numpy_array_preserves_data():
array = np.random.random((1, 1, 1, 2, 2))
image_stack = ImageStack.from_numpy_array(array)
assert np.array_equal(array, image_stack.numpy_array)
def synthetic_two_spot_imagestack_3d(synthetic_two_spot_3d):
data = synthetic_two_spot_3d
return ImageStack.from_numpy_array(data.reshape(1, 1, *data.shape))
def synthetic_single_spot_imagestack_2d(synthetic_single_spot_2d):
data = synthetic_single_spot_2d
return ImageStack.from_numpy_array(data.reshape(1, 1, 1, *data.shape))