def create_n5(array: Array5D, axiskeys: str = "xyztc", chunk_size: Optional[Shape5D] = None):
data_slice = DataSourceSlice(ArrayDataSource.from_array5d(array))
chunk_size = chunk_size or Shape5D.hypercube(10)
path = Path(tempfile.mkstemp()[1] + ".n5/data")
sink = N5DataSink(path=path, data_slice=data_slice, axiskeys=axiskeys, tile_shape=chunk_size)
sink.process()
return path.as_posix()
def __init__(
self,
*,
data: np.ndarray,
axiskeys: str,
tile_shape: Optional[Shape5D] = None,
location: Point5D = Point5D.zero(),
):
self._data = Array5D(data, axiskeys=axiskeys, location=location)
if tile_shape is None:
tile_shape = Shape5D.hypercube(256).to_interval5d().clamped(
self._data.shape).shape
super().__init__(
dtype=self._data.dtype,
tile_shape=tile_shape,
interval=self._data.interval,
axiskeys=axiskeys,
)
def __init__(
self,
url: str,
*,
tile_shape: Optional[Shape5D] = None,
dtype: np.dtype,
name: str = "",
shape: Shape5D,
location: Point5D = Point5D.zero(),
axiskeys: str,
):
self.url = url
self.tile_shape = (tile_shape or Shape5D.hypercube(256)).to_slice_5d().clamped(shape.to_slice_5d()).shape
self.dtype = dtype
self.name = name or self.url.split("/")[-1]
self.shape = shape
self.roi = shape.to_slice_5d(offset=location)
self.location = location
self.axiskeys = axiskeys