def __init__(self,
path: Path,
*,
location: Point5D = Point5D.zero(),
filesystem: FS):
url = filesystem.geturl(path.as_posix())
match = re.search(r"[^/]+\.n5/.*$", url, re.IGNORECASE)
if not match:
raise UnsupportedUrlException(url)
name = match.group(0)
self.filesystem = filesystem.opendir(path.as_posix())
with self.filesystem.openbin("attributes.json", "r") as f:
attributes_json_bytes = f.read()
attributes = json.loads(attributes_json_bytes.decode("utf8"))
dimensions = attributes["dimensions"][::-1]
blockSize = attributes["blockSize"][::-1]
axiskeys = "".join(attributes["axes"]).lower(
)[::-1] if "axes" in attributes else guess_axiskeys(dimensions)
super().__init__(
url=url,
name=name,
tile_shape=Shape5D.create(raw_shape=blockSize, axiskeys=axiskeys),
shape=Shape5D.create(raw_shape=dimensions, axiskeys=axiskeys),
dtype=np.dtype(attributes["dataType"]).newbyteorder(">"),
location=location,
axiskeys=axiskeys,
)
self.compression_type = attributes["compression"]["type"]
if self.compression_type not in N5Block.DECOMPRESSORS.keys():
raise NotImplementedError(
f"Don't know how to decompress from {self.compression_type}")
def __init__(self,
path: Path,
*,
location: Point5D = Point5D.zero(),
chunk_size: Optional[Shape5D] = None,
filesystem: FS):
"""A DataSource that handles Neurogancer's precomputed chunks
path: a path all the pay down to the scale, i.e., if some scale has
"key": "my_scale"
then your path should end in "my_scale"
chunk_size: a valid chunk_size for the scale selected by 'path'
"""
self.filesystem = filesystem.opendir(path.parent.as_posix())
self.info = PrecomputedChunksInfo.load(path=Path("info"),
filesystem=self.filesystem)
self.scale = self.info.get_scale(key=path.name)
super().__init__(
url="precomputed://" + filesystem.desc(path.as_posix()),
tile_shape=self.scale.get_tile_shape_5d(
self.info.num_channels, tile_shape_hint=chunk_size),
shape=self.scale.get_shape_5d(self.info.num_channels),
dtype=self.info.data_type,
name=path.name,
location=location,
axiskeys=self.scale.
axiskeys[::
-1], # externally reported axiskeys are always c-ordered
)
encoding_type = self.scale.encoding
if encoding_type == "raw":
noop = lambda data: data
self.decompressor = noop
self.compressor = noop
else:
raise NotImplementedError(
f"Don't know how to decompress {compression_type}")
def __init__(self, root_fs: FS, config: Config):
super(DryRunSideEffects, self).__init__(root_fs)
self.fragments_fs = read_only(
root_fs.opendir(config.change_fragments_path))
def __init__(self, base_fs: FS, ds_name="train"):
self.split = ds_name
self.base_fs = base_fs.opendir("images/{}".format(ds_name))
self.length = len(self.base_fs.listdir(""))
