def create_h5(array: Array5D,
axiskeys_style: str,
chunk_shape: Optional[Shape5D] = None,
axiskeys: str = "xyztc"):
raw_chunk_shape = (chunk_shape or Shape5D() * 2).clamped(
maximum=array.shape).to_tuple(axiskeys)
path = tempfile.mkstemp()[1] + ".h5"
f = h5py.File(path, "w")
ds = f.create_dataset("data",
chunks=raw_chunk_shape,
data=array.raw(axiskeys))
if axiskeys_style == "dims":
for key, dim in zip(axiskeys, ds.dims): # type: ignore
dim.label = key
elif axiskeys_style == "vigra":
type_flags = {"x": 2, "y": 2, "z": 2, "t": 2, "c": 1}
axistags = [{
"key": key,
"typeflags": type_flags[key],
"resolution": 0,
"description": ""
} for key in axiskeys]
ds.attrs["axistags"] = json.dumps({"axes": axistags})
else:
raise Exception(f"Bad axiskeys_style: {axiskeys_style}")
return Path(path)
def test_writing_to_offset_precomputed_chunks(tmp_path: Path, data: Array5D):
datasource = ArrayDataSource.from_array5d(data,
tile_shape=Shape5D(x=10, y=10),
location=Point5D(x=1000, y=1000))
scale = PrecomputedChunksScale.from_datasource(datasource=datasource,
key=Path("my_test_data"),
encoding=RawEncoder())
sink_path = Path("mytest.precomputed")
filesystem = OsFs(tmp_path.as_posix())
info = PrecomputedChunksInfo(
data_type=datasource.dtype,
type_="image",
num_channels=datasource.shape.c,
scales=tuple([scale]),
)
datasink = PrecomputedChunksSink.create(
filesystem=filesystem,
base_path=sink_path,
info=info,
).scale_sinks[0]
for tile in datasource.roi.get_datasource_tiles():
datasink.write(tile.retrieve())
precomp_datasource = PrecomputedChunksDataSource(
path=sink_path, filesystem=filesystem, resolution=scale.resolution)
reloaded_data = precomp_datasource.retrieve()
assert (reloaded_data.raw("xyz") == data.raw("xyz")).all() # type: ignore
def from_array5d(cls,
arr: Array5D,
*,
tile_shape: Optional[Shape5D] = None,
location: Point5D = Point5D.zero()):
return cls(data=arr.raw(Point5D.LABELS),
axiskeys=Point5D.LABELS,
location=location,
tile_shape=tile_shape)
def create_png(array: Array5D) -> Path:
png_path = tempfile.mkstemp()[1] + ".png"
skimage.io.imsave(png_path, array.raw("yxc")) # type: ignore
return Path(png_path)
def from_array5d(data: Array5D, labels: Optional[Set[int]] = None) -> "ConnectedComponents":
return ConnectedComponents(
data.raw(Point5D.LABELS), axiskeys=Point5D.LABELS, location=data.location, labels=labels
)
def array5d_to_vigra(arr: Array5D, axiskeys: str):
return vigra.taggedView(arr.raw(axiskeys), axistags=axiskeys)