def test_stackio_list_iterator():
metadata = {
'SizeC': 1,
'TimeIncrement': 10.0,
'DimensionOrder': ['C', 'T', 'Z', 'Y', 'X'],
'SizeT': 4,
'AcquisitionDate': '2014-03-24T11:25:14',
'SizeX': 56,
'SizeY': 48,
'SizeZ': 4,
'PhysicalSizeY': 0.065,
'PhysicalSizeX': 0.065,
'Shape': (1, 4, 4, 48, 56),
'PhysicalSizeZ': 1.0
}
file_list = data.stack_list()
stackio = StackIO(image_path_list=file_list, metadata=metadata)
stack_iter = stackio.list_iterator()
for n, stack in enumerate(stack_iter()):
assert stack.shape == (5, 172, 165)
assert n == 3
file_list = data.stack_list()
stackio = StackIO(image_path_list=file_list,
metadata=metadata,
base_dir=os.path.dirname(file_list[0]))
assert len(stackio.image_path_list) == 4
def test_cell_boundaries_detector():
# Fake to only detect the first time stamp
# to make tests faster
st = StackIO(data.TC_BF_cells())
data_iterator = [list(st.image_iterator(position=-3)())[0]]
metadata = st.metadata
metadata['SizeT'] = 1
parameters = {'object_height': 3, 'minimal_area': 160}
shapes = cell_boundaries_detector(data_iterator,
st.metadata,
show_progress=True,
parameters=parameters)
real_shapes = np.array([[
5.529290429042903909e+00, 7.725527184297377836e+00,
-1.109566958016608318e+00, 1.057975329135689790e+01,
7.965464600887037783e+00, 0.000000000000000000e+00
]])
assert_array_almost_equal(shapes, real_shapes)
def setup():
global stack_iter
global metadata
image_path_list = data.stack_list()
metadata = {"PhysicalSizeX": 0.42,
"PhysicalSizeY": 0.42,
"PhysicalSizeZ": 1.5,
"TimeIncrement": 3,
"FileName": '',
"Shape": [1, 1, 512, 512],
"DimensionOrder": "TZYX"}
metadata['FileName'] = image_path_list[0]
stack_io = StackIO(image_path_list=image_path_list,
metadata=metadata)
im0 = stack_io.get_tif().asarray()
correct_metadata = {'FileName': os.path.basename(image_path_list[0]),
'SizeX': im0.shape[2],
'SizeY': im0.shape[1],
'SizeZ': im0.shape[0],
'SizeT': len(image_path_list),
'Shape': (len(image_path_list),
im0.shape[2],
im0.shape[1],
im0.shape[0])}
stack_io.metadata.update(correct_metadata)
metadata = stack_io.metadata
stack_iter = stack_io.list_iterator()
def setup():
global stack_iter
global metadata
image_path_list = data.stack_list()
metadata = {
"PhysicalSizeX": 0.42,
"PhysicalSizeY": 0.42,
"PhysicalSizeZ": 1.5,
"TimeIncrement": 3,
"FileName": '',
"Shape": [1, 1, 512, 512],
"DimensionOrder": "TZYX"
}
metadata['FileName'] = image_path_list[0]
stack_io = StackIO(image_path_list=image_path_list, metadata=metadata)
im0 = stack_io.get_tif().asarray()
correct_metadata = {
'FileName': os.path.basename(image_path_list[0]),
'SizeX': im0.shape[2],
'SizeY': im0.shape[1],
'SizeZ': im0.shape[0],
'SizeT': len(image_path_list),
'Shape':
(len(image_path_list), im0.shape[2], im0.shape[1], im0.shape[0])
}
stack_io.metadata.update(correct_metadata)
metadata = stack_io.metadata
stack_iter = stack_io.list_iterator()
def test_stackio_get_tif():
fname = data.CZT_peaks()
st = StackIO(fname, json_discovery=False, base_dir=os.path.dirname(fname))
assert st.image_path == fname
fname = data.CZT_peaks()
st = StackIO(fname, json_discovery=False)
assert st.image_path == fname
def test_stackio_image_iterator():
fname = data.CZT_peaks()
st = StackIO(fname, json_discovery=False)
arr = st.get_tif().asarray(memmap=True)
iterator = st.image_iterator(channel_index=0, memmap=True)
for a in iterator():
assert a.shape == arr.shape[-2:]
# Test with channels index
fname = data.CZT_peaks()
st = StackIO(fname, json_discovery=False)
assert_raises(TypeError,
st.image_iterator,
hannel_index='GFP',
memmap=True)
st.metadata['Channels'] = ['GFP']
it = st.image_iterator(channel_index='GFP',
memmap=False,
z_projection=True)
assert list(it())[0].shape == arr.shape[-2:]
def test_peak_detector_no_peaks():
fname = data.CZT_peaks()
st = StackIO(fname, json_discovery=False)
data_iterator = st.image_iterator(channel_index=0)
parameters = {'w_s': 0.7,
'peak_radius': 0.2,
'threshold': 300,
'max_peaks': 4}
peaks = peak_detector(data_iterator(),
st.metadata,
parallel=True,
show_progress=False,
parameters=parameters)
assert peaks.empty is True
def test_cell_boundaries_detector_no_shapes():
# Fake to only detect the first time stamp
# to make tests faster
st = StackIO(data.CZT_peaks())
data_iterator = [list(st.image_iterator(position=-3, channel_index=0)())[0]]
metadata = st.metadata
metadata['SizeT'] = 1
parameters = {'object_height': 1e-6,
'minimal_area': 160}
shapes = cell_boundaries_detector(data_iterator, metadata,
show_progress=True,
parameters=parameters)
assert shapes.empty is True
def test_cell_boundaries_detector_no_shapes():
# Fake to only detect the first time stamp
# to make tests faster
st = StackIO(data.CZT_peaks())
data_iterator = [
list(st.image_iterator(position=-3, channel_index=0)())[0]
]
metadata = st.metadata
metadata['SizeT'] = 1
parameters = {'object_height': 1e-6, 'minimal_area': 160}
shapes = cell_boundaries_detector(data_iterator,
metadata,
show_progress=True,
parameters=parameters)
assert shapes.empty is True
def test_cell_boundaries_detector():
# Fake to only detect the first time stamp
# to make tests faster
st = StackIO(data.TC_BF_cells())
data_iterator = [list(st.image_iterator(position=-3)())[0]]
metadata = st.metadata
metadata['SizeT'] = 1
parameters = {'object_height': 3,
'minimal_area': 160}
shapes = cell_boundaries_detector(data_iterator, st.metadata,
show_progress=True,
parameters=parameters)
real_shapes = np.array([[5.529290429042903909e+00, 7.725527184297377836e+00,
-1.109566958016608318e+00, 1.057975329135689790e+01,
7.965464600887037783e+00, 0.000000000000000000e+00]])
assert_array_almost_equal(shapes, real_shapes)
def test_stackio_from_objectsio():
oio = ObjectsIO.from_h5(data.sample_h5_temp())
st = StackIO.from_objectsio(oio)
true_metadata = {
'PysicalSizeY': 0.43,
'PysicalSizeX': 0.43,
'PysicalSizeZ': 1.5,
'TimeIncrement': 3.0,
'Shape': (512, 512, 23, 5),
'SizeT': 5,
'Type': 'unint16',
'FileName': 'sample.ome.tif',
'DimensionOrder': 'TZYX',
'SizeZ': 23,
'SizeY': 512,
'SizeX': 512
}
guessed_metadata = st.metadata
assert guessed_metadata == true_metadata
def test_stackio_from_tif_file():
st = StackIO(data.CZT_peaks(), json_discovery=False)
true_metadata = {
'SizeC': 1,
'TimeIncrement': 10.0,
'DimensionOrder': ['C', 'T', 'Z', 'Y', 'X'],
'SizeT': 4,
'AcquisitionDate': '2014-03-24T11:25:14',
'SizeX': 56,
'SizeY': 48,
'SizeZ': 4,
'PhysicalSizeY': 0.065,
'PhysicalSizeX': 0.065,
'Shape': (1, 4, 4, 48, 56),
'PhysicalSizeZ': 1.0
}
guessed_metadata = st.metadata
guessed_metadata.pop("FileName")
assert guessed_metadata == true_metadata
def test_stackio_get_tif_from_list():
images_list = data.stack_list()
st = StackIO(image_path_list=images_list)
assert st.get_tif_from_list(3).asarray().shape == (5, 172, 165)