def test_block_get_bcube():
bcube = BoundingCube(0, 1, 0, 1, 0, 1, mip=0)
start, stop = 10, 11
block = Block(start=start,
stop=stop,
src_stack=Stack(),
dst_stack=Stack(),
previous=None)
adj_bcube = bcube.reset_coords(zs=start, ze=stop, in_place=False)
assert adj_bcube == block.get_bcube(bcube)
assert bcube.z != (start, stop)
def break_bcube_into_chunks(self,
bcube,
chunk_xy,
chunk_z,
mip,
flatten=True,
chunk_xy_step=None,
chunk_z_step=None,
**kwargs):
"""Default breaking up of a bcube into smaller bcubes (chunks).
Returns a list of chunks
Args:
bcube: BoundingBox for region to be broken into chunks
chunk_size: tuple for dimensions of chunk that bbox will be broken into
mip: int for MIP level at which chunk_xy is dspecified
"""
indexed_bcube = self.indexing_scheme(bcube, mip, kwargs)
x_range = indexed_bcube.x_range(mip=mip)
y_range = indexed_bcube.y_range(mip=mip)
z_range = indexed_bcube.z_range()
if chunk_xy_step is None:
chunk_xy_step = chunk_xy
if chunk_z_step is None:
chunk_z_step = chunk_z
xy_chunks = []
flat_chunks = []
for zs in range(z_range[0], z_range[1], chunk_z_step):
xy_chunks.append([])
for xs in range(x_range[0], x_range[1], chunk_xy_step):
xy_chunks[-1].append([])
for ys in range(y_range[0], y_range[1], chunk_xy_step):
chunk = BoundingCube(xs,
xs + chunk_xy,
ys,
ys + chunk_xy,
zs,
zs + chunk_z,
mip=mip)
xy_chunks[-1][-1].append(chunk)
flat_chunks.append(chunk)
if flatten:
return flat_chunks
else:
return xy_chunks
def __init__(self, data_mip_ranges=None, **kwargs):
super().__init__(**kwargs)
self.declared_write_mips = []
self.declared_write_bcube = BoundingCube(0, 0, 0, 0, 0, 0, 0)
def test_combine_masks():
src_path = "file:///tmp/cloudvolume/combine_mask_test/src"
dst_path = "file:///tmp/cloudvolume/combine_mask_test/mask/dst"
make_test_dataset(path=src_path)
src_stack = Stack()
backend = str_to_backend("cv")
layer = backend.create_layer(
path=src_path,
layer_type="mask",
name="M",
reference=None,
)
src_stack.add_layer(layer)
dst_layer = src_stack.create_unattached_sublayer(
name="dst",
layer_type="mask",
custom_folder="file:///tmp/cloudvolume/combine_mask_test",
)
exp = {
"inputs": [
{
"inputs": [
{
"weight": 1,
"key": "M",
"offset": -1
},
{
"weight": 1,
"key": "M",
"offset": 0
},
],
"threshold":
1,
},
{
"inputs": [
{
"weight": 1,
"key": "M",
"offset": 0
},
{
"weight": 1,
"key": "M",
"offset": 1
},
],
"threshold":
1,
},
],
"threshold":
0,
}
bcube = BoundingCube(0, 1, 0, 1, 0, 16, mip=0)
task = CombineMasksTask(src_stack=src_stack,
exp=exp,
dst_layer=dst_layer,
mip=0,
bcube=bcube,
pad=0)
task.execute()
D = MiplessCloudVolume(path=dst_path)
O = np.zeros((1, 1, 6), dtype=np.uint8)
O[:, :, 1] = 1
O[:, :, 2] = 1
assert np.all(D[0][:][:, :, :, 0] == O)
delete_layer(dst_path[7:])
delete_layer(src_path[7:])