def test_downsampling_image_produces_correct_resolution_and_data_shape(scale):
image = ImageData(channels=np.arange(24).reshape(1, 6, 4), pixel_resolution_um=12)
image2 = image.resample(scale)
assert image2.pixel_resolution_um == (image.pixel_resolution_um / scale)
assert image2.num_channels == image.num_channels
assert approx(image.width * scale == image2.width, abs=1)
assert approx(image.height * scale == image2.height, abs=1)
def test_downsampling_image_produces_correct_resolution_and_data_shape(
to_resolution):
from_resolution = 12
image = ImageData(channels=np.arange(24).reshape(1, 6, 4),
pixel_resolution_um=from_resolution)
image2 = image.resample(resolution_um=to_resolution)
assert image2.pixel_resolution_um == to_resolution
assert image2.num_channels == image.num_channels
scale_ratio = from_resolution / to_resolution
assert approx(image.width * scale_ratio == image2.width, abs=1)
assert approx(image.height * scale_ratio == image2.height, abs=1)
def repo():
repo = Mock(BaseSectionRepo)
repo.sections = [
Section(image=ImageData(channels=np.arange(12).reshape(2, 3, 2),
pixel_resolution_um=12), )
]
return repo
def repo():
repo = Mock(BaseSectionRepo)
repo.sections = [
Section(image=ImageData(channels=np.random.random((2, 3, 4)),
pixel_resolution_um=20.))
]
return repo
def test_nonexistent_image_coords_raise_error_and_doesnt_if_exists(i, j):
section = Section(image=ImageData(channels=arange(180).reshape(2, 3, 30),
pixel_resolution_um=1), )
if i < 0 or i >= section.image.height or j < 0 or j >= section.image.width:
with pytest.raises(ValueError):
section.pos_from_coord(i=i, j=j)
else:
assert section.pos_from_coord(i=i, j=j)
def test_section_recenter_sets_shift_to_half_the_width_and_height(
width, height):
section = Section(image=ImageData(channels=np.random.random((3, height,
width)),
pixel_resolution_um=123))
assert section.plane_2d.x == 0 and section.plane_2d.y == 0
section2 = section.recenter()
assert section2.plane_2d.x == approx(
-width / 2) and section2.plane_2d.y == approx(-height / 2)
def repo():
repo = Mock(BaseSectionRepo)
repo.sections = [
Section(
image=ImageData(channels=np.random.random((2, 3, 4)), pixel_resolution_um=12.),
plane_3d=AtlasTransform(right=5, superior=2, anterior=20),
)
]
return repo
def test_image_scale_matrix_converts_pixel_resolution_to_um_space(width, height, channels, res):
image = ImageData(channels=np.random.random(size=(channels, height, width)), pixel_resolution_um=res)
r = res
expected = np.array([
[1/r, 0, 0, 0],
[0, 1/r, 0, 0],
[0, 0, 1, 0],
[0, 0, 0, 1],
])
assert np.all(np.isclose(image.scale_matrix, expected))
def test_image_shape_matrix_calculation(width, height):
image = ImageData(channels=np.random.random((2, height, width)),
pixel_resolution_um=10)
expected = np.array([
[1, 0, 0, image.height],
[0, 1, 0, image.width],
[0, 0, 1, 0],
[0, 0, 0, 1],
])
assert approx(image.shape_matrix == expected)
def slice(self, plane: AtlasTransform) -> Section:
new_volume = affine_transform(self.volume,
matrix=plane.affine_transform,
cval=0.)
slice_image = new_volume[:, :, 0][np.newaxis, :, :]
return Section(image=ImageData(channels=slice_image,
pixel_resolution_um=self.resolution_um),
plane_3d=plane,
thickness_um=self.resolution_um)
def test_can_get_3d_position_from_2d_pixel_coordinate_in_section(
i, j, dx, dy, dz, pixel_resolution):
section = Section(
image=ImageData(
channels=arange(24).reshape(2, 3, 4),
pixel_resolution_um=pixel_resolution,
),
plane_3d=Plane3D(x=dx, y=dy, z=dz),
)
x, y, z = section.pos_from_coord(i=i, j=j) # observed 3D positions
assert x == approx((j * 1 / pixel_resolution) + dx)
assert y == approx((-i * 1 / pixel_resolution) + dy)
assert z == approx(dz)
def read(self, filename: str) -> ImageData:
f = tifffile.TiffFile(filename)
image = f.asarray()
assert image.ndim == 3
assert image.dtype == uint16
metadata = xmltodict.parse(f.ome_metadata)
pix_mdata = metadata['OME']['Image']['Pixels']
res_x, res_y = pix_mdata['@PhysicalSizeX'], pix_mdata['@PhysicalSizeY']
assert res_x == res_y, \
"Pixels are not square"
return ImageData(channels=image, pixel_resolution_um=1 / float(res_x))
def test_can_get_correct_3d_position_with_image_shifts_and_planar_rotations(
j, pixel_resolution, x_shift, y_shift, theta):
section = Section(
image=ImageData(channels=arange(2400).reshape(2, 30, 40),
pixel_resolution_um=pixel_resolution),
plane_2d=Image2DTransform(i=x_shift, j=y_shift, theta=theta),
)
x, y, z = section.pos_from_coord(i=0, j=j)
assert x == approx(
(pixel_resolution) * (j * cos(radians(theta)) + x_shift))
assert y == approx(
(pixel_resolution) * (j * sin(radians(theta)) + y_shift))
assert z == 0
def test_downsampling_beyond_dimensions_produces_valueerror(scale):
image = ImageData(channels=np.arange(24).reshape(1, 4, 6), pixel_resolution_um=12)
if scale <= 0:
with pytest.raises(ValueError, match=r".* positive.*"):
image.resample(scale)
elif scale < 0.25:
with pytest.raises(ValueError, match=r".* small.*"):
image.resample(scale)
def test_can_get_3d_position_from_2d_pixel_coordinate_in_section(
i, j, right, superior, anterior, pixel_resolution):
section = Section(
image=ImageData(
channels=arange(24).reshape(2, 3, 4),
pixel_resolution_um=pixel_resolution,
),
plane_3d=AtlasTransform(right=right,
superior=superior,
anterior=anterior),
)
x, y, z = section.pos_from_coord(i=i, j=j) # observed 3D positions
assert x == approx((j * pixel_resolution) + right)
assert y == approx((-i * pixel_resolution) + superior)
assert z == approx(anterior)
def test_section_origin_set_sets_shift_to_half_half_and_shift_matrix_to_half_width_height(
width, height):
section = Section(image=ImageData(channels=np.random.random((3, height,
width)),
pixel_resolution_um=120))
assert section.plane_2d.i == 0 and section.plane_2d.j == 0
section2 = section.set_image_origin_to_center()
res = section2.image.pixel_resolution_um
height, width = section2.image.height, section2.image.width
assert section2.plane_2d.i == -0.5 and section2.plane_2d.j == -0.5
expected_shift_matrix = np.array([
[res, 0, 0, -res * height / 2],
[0, res, 0, -res * width / 2],
[0, 0, 1, 0],
[0, 0, 0, 1],
])
assert np.all(np.isclose(section2.shift_matrix, expected_shift_matrix))
def reader(image_data):
reader = Mock(BaseSectionReader)
reader.read.return_value = ImageData(channels=image_data,
pixel_resolution_um=10)
return reader
def test_downsampling_beyond_dimensions_produces_valueerror(to_resolution):
image = ImageData(channels=np.arange(24).reshape(1, 4, 6),
pixel_resolution_um=12)
with pytest.raises(ValueError, match=r".* positive.*"):
image.resample(resolution_um=to_resolution)
def test_resample_section_gets_new_section_with_resampled_image():
section = Section(image=ImageData(channels=np.random.random((3, 4, 4)),
pixel_resolution_um=12))
section2 = section.resample(resolution_um=24)
assert isinstance(section2, Section)
assert section2.image.pixel_resolution_um == 24
def test_image_aspect_ratio_calculation(width, height):
image = ImageData(channels=np.random.random((2, height, width)),
pixel_resolution_um=10)
assert approx(image.aspect_ratio == width / height)
def section2():
return Section(image=ImageData(
channels=np.arange(12).reshape(2, 3, 2),
pixel_resolution_um=12,
), )
def test_image_reports_correct_number_of_channels(shape, num_channels):
image = ImageData(channels=np.random.random(size=shape), pixel_resolution_um=12)
assert image.num_channels == num_channels
def test_downsampling_image_produces_im_with_similar_statistical_properties_as_original(scale):
image = ImageData(channels=np.random.random((2, 120, 120)), pixel_resolution_um=12)
im2 = image.resample(scale)
assert np.all(np.isclose(image.channels.mean(), im2.channels.mean(), rtol=3e-2))
assert np.all(np.isclose(image.channels.std(), im2.channels.std(), rtol=3e-2))
def test_image_width(shape, width):
image = ImageData(channels=np.random.random(size=shape), pixel_resolution_um=12)
assert image.width == width
def test_image_height(shape, height):
image = ImageData(channels=np.random.random(size=shape), pixel_resolution_um=12)
assert image.height == height