def test_dask_array_creates_cache():
"""Test that dask arrays create cache but turns off fusion."""
resize_dask_cache(1)
assert _dask_utils._DASK_CACHE.cache.available_bytes == 1
# by default we have no dask_cache and task fusion is active
original = dask.config.get("optimization.fuse.active", None)
def mock_set_view_slice():
assert dask.config.get("optimization.fuse.active") is False
layer = layers.Image(da.ones((100, 100)))
layer._set_view_slice = mock_set_view_slice
layer.set_view_slice()
# adding a dask array will reate cache and turn off task fusion,
# *but only* during slicing (see "mock_set_view_slice" above)
assert _dask_utils._DASK_CACHE.cache.available_bytes > 100
assert not _dask_utils._DASK_CACHE.active
assert dask.config.get("optimization.fuse.active", None) == original
# make sure we can resize the cache
resize_dask_cache(10000)
assert _dask_utils._DASK_CACHE.cache.available_bytes == 10000
# This should only affect dask arrays, and not numpy data
def mock_set_view_slice2():
assert dask.config.get("optimization.fuse.active", None) == original
layer2 = layers.Image(np.ones((100, 100)))
layer2._set_view_slice = mock_set_view_slice2
layer2.set_view_slice()
def test_link_image_layers_all_attributes(key, value):
"""Test linking common attributes across layers of similar types."""
l1 = layers.Image(np.random.rand(10, 10), contrast_limits=(0, 0.8))
l2 = layers.Image(np.random.rand(10, 10), contrast_limits=(0.1, 0.9))
link_layers([l1, l2])
# linking does (currently) apply to things that were unequal before linking
assert l1.contrast_limits != l2.contrast_limits
# once we set either... they will both be changed
assert getattr(l1, key) != value
setattr(l2, key, value)
assert getattr(l1, key) == getattr(l2, key) == value
def iter_layer_events() -> Iterator[Ev]:
basenames = base_event_names()
docs = class_doc_attrs(layers.Layer)
for name in basenames:
yield Ev(name, layers.Layer, description=docs.get(name))
EXAMPLE_LAYERS: List[layers.Layer] = [
layers.Image(np.random.random((2, 2))),
layers.Labels(np.random.randint(20, size=(10, 15))),
layers.Points(10 * np.random.random((10, 2))),
layers.Vectors(20 * np.random.random((10, 2, 2))),
layers.Shapes(20 * np.random.random((10, 4, 2))),
layers.Surface((
20 * np.random.random((10, 3)),
np.random.randint(10, size=(6, 3)),
np.random.random(10),
)),
layers.Tracks(
np.column_stack((np.ones(20), np.arange(20), 20 * np.random.random(
(20, 2))))),
]
for lay in EXAMPLE_LAYERS:
docs = class_doc_attrs(type(lay))
for name in [i for i in lay.events.emitters if i not in basenames]:
yield Ev(name, lay.__class__, description=docs.get(name))
def test_link_invalid_param():
"""Test that linking non-shared attributes raises."""
l1 = layers.Image(np.random.rand(10, 10))
l2 = layers.Points(None)
with pytest.raises(ValueError) as e:
link_layers([l1, l2], ('rendering', ))
assert "Cannot link attributes that are not shared by all layers" in str(e)
def test_dask_not_greedy(dtype):
"""Make sure that we don't immediately calculate dask arrays."""
FETCH_COUNT = 0
def get_plane(block_id):
if isinstance(block_id, tuple):
nonlocal FETCH_COUNT
FETCH_COUNT += 1
return np.random.rand(1, 1, 1, 10, 10)
arr = da.map_blocks(
get_plane,
chunks=((1, ) * 4, (1, ) * 2, (1, ) * 8, (10, ), (10, )),
dtype=dtype,
)
layer = layers.Image(arr)
# the <= is because before dask-2021.12.0, the above code resulted in NO
# fetches for uint8 data, and afterwards, results in a single fetch.
# the single fetch is actually the more "expected" behavior. And all we
# are really trying to assert here is that we didn't fetch all the planes
# in the first index... so we allow 0-1 fetches.
assert FETCH_COUNT <= 1
if dtype == 'uint8':
assert tuple(layer.contrast_limits) == (0, 255)
def test_list_of_dask_arrays_doesnt_create_cache():
"""Test that adding a list of dask array also creates a dask cache."""
utils.dask_cache = None # in case other tests created it
original = dask.config.get("optimization.fuse.active", None)
_ = layers.Image([da.ones((100, 100)), da.ones((20, 20))])
assert utils.dask_cache is None
assert dask.config.get("optimization.fuse.active", None) == original
def test_list_of_dask_arrays_doesnt_create_cache():
"""Test that adding a list of dask array also creates a dask cache."""
resize_dask_cache(1) # in case other tests created it
assert _dask_utils._DASK_CACHE.cache.available_bytes == 1
original = dask.config.get("optimization.fuse.active", None)
_ = layers.Image([da.ones((100, 100)), da.ones((20, 20))])
assert _dask_utils._DASK_CACHE.cache.available_bytes > 100
assert not _dask_utils._DASK_CACHE.active
assert dask.config.get("optimization.fuse.active", None) == original
def test_link_different_type_layers_all_attributes(key, value):
"""Test linking common attributes across layers of different types."""
l1 = layers.Image(np.random.rand(10, 10))
l2 = layers.Points(None)
link_layers([l1, l2])
# once we set either... they will both be changed
assert getattr(l1, key) != value
setattr(l2, key, value)
assert getattr(l1, key) == getattr(l2, key) == value
def test_dask_array_creates_cache():
"""Test that adding a dask array creates a dask cache and turns of fusion.
"""
# by default we have no dask_cache and task fusion is active
original = dask.config.get("optimization.fuse.active", None)
def mock_set_view_slice():
assert dask.config.get("optimization.fuse.active") is False
layer = layers.Image(da.ones((100, 100)))
layer._set_view_slice = mock_set_view_slice
layer.set_view_slice()
# adding a dask array will turn on the cache, and turn off task fusion.
assert isinstance(utils.dask_cache, dask.cache.Cache)
assert dask.config.get("optimization.fuse.active", None) == original
# if the dask version is too low to remove task fusion, emit a warning
_dask_ver = dask.__version__
dask.__version__ = '2.14.0'
with pytest.warns(UserWarning) as record:
_ = layers.Image(da.ones((100, 100)))
assert 'upgrade Dask to v2.15.0 or later' in record[0].message.args[0]
dask.__version__ = _dask_ver
# make sure we can resize the cache
assert utils.dask_cache.cache.total_bytes > 1000
utils.resize_dask_cache(1000)
assert utils.dask_cache.cache.total_bytes <= 1000
# This should only affect dask arrays, and not numpy data
def mock_set_view_slice2():
assert dask.config.get("optimization.fuse.active", None) == original
layer2 = layers.Image(np.ones((100, 100)))
layer2._set_view_slice = mock_set_view_slice2
layer2.set_view_slice()
# clean up cache
utils.dask_cache = None
def test_dask_array_doesnt_create_cache():
"""Test that dask arrays don't create cache but turns off fusion."""
# by default we have no dask_cache and task fusion is active
original = dask.config.get("optimization.fuse.active", None)
def mock_set_view_slice():
assert dask.config.get("optimization.fuse.active") is False
layer = layers.Image(da.ones((100, 100)))
layer._set_view_slice = mock_set_view_slice
layer.set_view_slice()
# adding a dask array won't create cache, but will turn off task fusion,
# *but only* during slicing (see "mock_set_view_slice" above)
assert utils.dask_cache is None
assert dask.config.get("optimization.fuse.active", None) == original
# if the dask version is too low to remove task fusion, emit a warning
_dask_ver = dask.__version__
dask.__version__ = '2.14.0'
with pytest.warns(UserWarning) as record:
_ = layers.Image(da.ones((100, 100)))
assert 'upgrade Dask to v2.15.0 or later' in record[0].message.args[0]
dask.__version__ = _dask_ver
# make sure we can resize the cache
utils.resize_dask_cache(10000)
assert utils.dask_cache.cache.available_bytes == 10000
# This should only affect dask arrays, and not numpy data
def mock_set_view_slice2():
assert dask.config.get("optimization.fuse.active", None) == original
layer2 = layers.Image(np.ones((100, 100)))
layer2._set_view_slice = mock_set_view_slice2
layer2.set_view_slice()
# clean up cache
utils.dask_cache = None
def test_list_of_dask_arrays_creates_cache():
"""Test that adding a list of dask array also creates a dask cache."""
original = dask.config.get("optimization.fuse.active", None)
_ = layers.Image([da.ones((100, 100)), da.ones((20, 20))])
assert isinstance(utils.dask_cache, dask.cache.Cache)
assert dask.config.get("optimization.fuse.active", None) == original