def test_load_hdf5_from_file(hdf5_path: Union[str, Path], patient_id: str,
acquisition_date: datetime,
array_shape: np.ndarray,
load_segmentation: bool) -> None:
"""
Assert that the HDF5 object is loaded with the expected attributes.
"""
hdf5_path = Path(hdf5_path)
act_hdf5 = HDF5Object.from_file(hdf5_path,
load_segmentation=load_segmentation)
assert act_hdf5.patient_id == patient_id
assert act_hdf5.acquisition_date.isoformat(
) == acquisition_date # type: ignore
assert np.array_equal(act_hdf5.volume.shape, array_shape)
if load_segmentation:
assert act_hdf5.segmentation is not None
assert np.array_equal(act_hdf5.segmentation.shape, array_shape)
else:
assert act_hdf5.segmentation is None
def load_hdf5_file(path_str: Union[str, Path],
load_segmentation: bool = False) -> HDF5Object:
"""
Loads a single HDF5 file.
:param path_str: The path of the HDF5 file that should be loaded.
:param load_segmentation: If True, the `segmentation` field of the result object will be populated. If
False, the field will be set to None.
:return: HDF5Object
"""
def _is_valid_hdf5_path(_path: Path) -> bool:
"""
Validates a path for an image
:param _path:
:return:
"""
return _path.is_file() and is_hdf5_file_path(_path)
path = Path(path_str)
if path is None or not _is_valid_hdf5_path(path):
raise ValueError(f"Invalid path: {path}")
return HDF5Object.from_file(path, load_segmentation=load_segmentation)