def test_normalize_order():
eq('F', normalize_order('F'))
eq('C', normalize_order('C'))
eq('F', normalize_order('f'))
eq('C', normalize_order('c'))
with assert_raises(ValueError):
normalize_order('foo')
def test_normalize_order():
assert 'F' == normalize_order('F')
assert 'C' == normalize_order('C')
assert 'F' == normalize_order('f')
assert 'C' == normalize_order('c')
with pytest.raises(ValueError):
normalize_order('foo')
def test_normalize_order():
eq('F', normalize_order('F'))
eq('C', normalize_order('C'))
eq('F', normalize_order('f'))
eq('C', normalize_order('c'))
with assert_raises(ValueError):
normalize_order('foo')
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 and chunk_store != store:
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)
chunks = normalize_chunks(chunks, shape, dtype.itemsize)
order = normalize_order(order)
# obtain compressor config
if compressor == 'none':
# compatibility
compressor = None
elif compressor == 'default':
compressor = default_compressor
if compressor:
try:
compressor_config = compressor.get_config()
except AttributeError:
err_bad_compressor(compressor)
else:
compressor_config = None
# 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')
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 and chunk_store != store:
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)
chunks = normalize_chunks(chunks, shape, dtype.itemsize)
order = normalize_order(order)
# obtain compressor config
if compressor == 'none':
# compatibility
compressor = None
elif compressor == 'default':
compressor = default_compressor
if compressor:
try:
compressor_config = compressor.get_config()
except AttributeError:
err_bad_compressor(compressor)
else:
compressor_config = None
# 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')
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')
