def test_encode_fill_value(fill_value, dtype, object_codec, result):
# normalize metadata (copied from _init_array_metadata)
dtype, object_codec = normalize_dtype(dtype, object_codec)
dtype = dtype.base
fill_value = normalize_fill_value(fill_value, dtype)
# test
if result:
encode_fill_value(fill_value, dtype, object_codec)
else:
with pytest.raises(ValueError):
encode_fill_value(fill_value, dtype, object_codec)
def transfer_attrs(self, h5obj, zobj):
"""Transfer attributes from an HDF5 object to its equivalent Zarr object.
Parameters
----------
h5obj : h5py.Group or h5py.Dataset
An HDF5 group or dataset.
zobj : zarr.hierarchy.Group or zarr.core.Array
An equivalent Zarr group or array to the HDF5 group or dataset with
attributes.
"""
for n, v in h5obj.attrs.items():
if n in ('REFERENCE_LIST', 'DIMENSION_LIST'):
continue
# Fix some attribute values to avoid JSON encoding exceptions...
if isinstance(v, bytes):
v = v.decode('utf-8')
elif isinstance(v, (np.ndarray, np.number)):
if n == '_FillValue':
v = encode_fill_value(v, v.dtype)
elif v.size == 1:
v = v.flatten()[0].tolist()
else:
v = v.tolist()
if self._xr and v == 'DIMENSION_SCALE':
continue
try:
zobj.attrs[n] = v
except TypeError:
print(f'Caught TypeError: {n}@{h5obj.name} = {v} ({type(v)})')
def _transfer_attrs(self, h5obj: Union[h5py.Dataset, h5py.Group],
zobj: Union[zarr.Array, zarr.Group]):
"""Transfer attributes from an HDF5 object to its equivalent Zarr object.
Parameters
----------
h5obj : h5py.Group or h5py.Dataset
An HDF5 group or dataset.
zobj : zarr.hierarchy.Group or zarr.core.Array
An equivalent Zarr group or array to the HDF5 group or dataset with
attributes.
"""
for n, v in h5obj.attrs.items():
if n in _HIDDEN_ATTRS:
continue
# Fix some attribute values to avoid JSON encoding exceptions...
if isinstance(v, bytes):
v = v.decode('utf-8')
elif isinstance(v, (np.ndarray, np.number, np.bool_)):
if v.dtype.kind == 'S':
v = v.astype(str)
if n == '_FillValue':
v = encode_fill_value(v, v.dtype)
elif v.size == 1:
v = v.flatten()[0]
if isinstance(v, (np.ndarray, np.number, np.bool_)):
v = v.tolist()
else:
v = v.tolist()
elif isinstance(v, h5py._hl.base.Empty):
v = ""
if v == 'DIMENSION_SCALE':
continue
try:
zobj.attrs[n] = v
except TypeError:
lggr.exception(
f'Caught TypeError: {n}@{h5obj.name} = {v} ({type(v)})')
def _extract_fill_value(da, dtype):
""" helper function to extract fill value from DataArray. """
fill_value = da.attrs.pop('_FillValue', None)
return encode_fill_value(fill_value, dtype)