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 test_normalize_fill_value():
eq(b'', normalize_fill_value(0, dtype=np.dtype('S1')))
eq(b'',
normalize_fill_value(0, dtype=np.dtype([('foo', 'i4'), ('bar', 'f8')])))
eq('', normalize_fill_value(0, dtype=np.dtype('U1')))
def test_normalize_fill_value():
assert b'' == normalize_fill_value(0, dtype=np.dtype('S1'))
structured_dtype = np.dtype([('foo', 'S3'), ('bar', 'i4'), ('baz', 'f8')])
expect = np.array((b'', 0, 0.), dtype=structured_dtype)[()]
assert expect == normalize_fill_value(0, dtype=structured_dtype)
assert '' == normalize_fill_value(0, dtype=np.dtype('U1'))
def _init_array_metadata(store,
shape,
chunks=None,
dtype=None,
compressor='default',
fill_value=None,
order='C',
overwrite=False,
path=None,
chunk_store=None,
filters=None):
# guard conditions
if overwrite:
# attempt to delete any pre-existing items in store
rmdir(store, path)
if chunk_store is not None:
rmdir(chunk_store, path)
elif contains_array(store, path):
err_contains_array(path)
elif contains_group(store, path):
err_contains_group(path)
# normalize metadata
shape = normalize_shape(shape)
dtype = np.dtype(dtype)
if dtype.kind in 'mM':
raise ValueError(
'datetime64 and timedelta64 dtypes are not currently supported; '
'please store the data using int64 instead')
chunks = normalize_chunks(chunks, shape, dtype.itemsize)
order = normalize_order(order)
fill_value = normalize_fill_value(fill_value, dtype)
# compressor prep
if shape == ():
# no point in compressing a 0-dimensional array, only a single value
compressor = None
elif compressor == 'none':
# compatibility
compressor = None
elif compressor == 'default':
compressor = default_compressor
# obtain compressor config
compressor_config = None
if compressor:
try:
compressor_config = compressor.get_config()
except AttributeError:
err_bad_compressor(compressor)
# obtain filters config
if filters:
filters_config = [f.get_config() for f in filters]
else:
filters_config = None
# initialize metadata
meta = dict(shape=shape,
chunks=chunks,
dtype=dtype,
compressor=compressor_config,
fill_value=fill_value,
order=order,
filters=filters_config)
key = _path_to_prefix(path) + array_meta_key
store[key] = encode_array_metadata(meta)
# initialize attributes
key = _path_to_prefix(path) + attrs_key
store[key] = json.dumps(dict()).encode('ascii')