def test_stack_to_images_1_channel():
"""Split when only one channel"""
data = np.random.randint(0, 100, (10, 1, 128, 128))
stack = Image(data)
images = stack_to_images(stack, 1, colormap=['magma'])
assert isinstance(images, list)
assert len(images) == 1
for i in images:
assert i.rgb is False
assert type(stack) == type(i)
assert i.data.shape == (10, 128, 128)
def test_stack_to_images_0_rgb():
"""Split RGB along the first axis (z or t) so the images remain rgb"""
data = np.random.randint(0, 100, (10, 128, 128, 3))
stack = Image(data)
images = stack_to_images(stack, 0, colormap=None)
assert isinstance(images, list)
assert len(images) == 10
for i in images:
assert i.rgb
assert type(stack) == type(i)
assert i.data.shape == (128, 128, 3)
def test_stack_to_images_4_channels():
"""Test 4x128x128 stack is split into 4 channels w/ colormap keyword"""
data = np.random.randint(0, 100, (4, 128, 128))
stack = Image(data)
images = stack_to_images(stack, 0, colormap=['red', 'blue'])
assert isinstance(images, list)
assert len(images) == 4
assert images[-2].colormap.name == 'red'
for i in images:
assert type(stack) == type(i)
assert i.data.shape == (128, 128)
def test_stack_to_images_basic():
"""Test that a 2 channel zcyx stack is split into 2 image layers"""
data = np.random.randint(0, 100, (10, 2, 128, 128))
stack = Image(data)
images = stack_to_images(stack, 1, colormap=None)
assert isinstance(images, list)
assert images[0].colormap.name == 'magenta'
assert len(images) == 2
for i in images:
assert type(stack) == type(i)
assert i.data.shape == (10, 128, 128)
def test_stack_to_images_rgb():
"""Test 3 channel RGB image (channel axis = -1) into single channels."""
data = np.random.randint(0, 100, (10, 128, 128, 3))
stack = Image(data)
images = stack_to_images(stack, -1, colormap=None)
assert isinstance(images, list)
assert len(images) == 3
for i in images:
assert type(stack) == type(i)
assert i.data.shape == (10, 128, 128)
assert i.scale.shape == (3, )
assert i.rgb is False
def test_stack_to_images_multiscale():
"""Test that a 3 channel multiscale image returns 3 multiscale images."""
data = list()
data.append(np.random.randint(0, 200, (3, 128, 128)))
data.append(np.random.randint(0, 200, (3, 64, 64)))
data.append(np.random.randint(0, 200, (3, 32, 32)))
data.append(np.random.randint(0, 200, (3, 16, 16)))
stack = Image(data)
images = stack_to_images(stack, 0)
assert len(images) == 3
assert len(images[0].data) == 4
assert images[0].data[-1].shape[-1] == 16
assert images[1].data[-1].shape[-1] == 16
assert images[2].data[-1].shape[-1] == 16
