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test_array.py
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704 lines (592 loc) · 23.7 KB
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import json
import math
import pickle
from itertools import accumulate
from typing import Any, Literal
import numcodecs
import numpy as np
import pytest
import zarr.api.asynchronous
from zarr import Array, AsyncArray, Group
from zarr.codecs import BytesCodec, VLenBytesCodec
from zarr.core._info import ArrayInfo
from zarr.core.array import chunks_initialized
from zarr.core.buffer import default_buffer_prototype
from zarr.core.buffer.cpu import NDBuffer
from zarr.core.common import JSON, MemoryOrder, ZarrFormat
from zarr.core.group import AsyncGroup
from zarr.core.indexing import ceildiv
from zarr.core.metadata.v3 import DataType
from zarr.core.sync import sync
from zarr.errors import ContainsArrayError, ContainsGroupError
from zarr.storage import LocalStore, MemoryStore
from zarr.storage.common import StorePath
@pytest.mark.parametrize("store", ["local", "memory", "zip"], indirect=["store"])
@pytest.mark.parametrize("zarr_format", [2, 3])
@pytest.mark.parametrize("exists_ok", [True, False])
@pytest.mark.parametrize("extant_node", ["array", "group"])
def test_array_creation_existing_node(
store: LocalStore | MemoryStore,
zarr_format: ZarrFormat,
exists_ok: bool,
extant_node: Literal["array", "group"],
) -> None:
"""
Check that an existing array or group is handled as expected during array creation.
"""
spath = StorePath(store)
group = Group.from_store(spath, zarr_format=zarr_format)
expected_exception: type[ContainsArrayError | ContainsGroupError]
if extant_node == "array":
expected_exception = ContainsArrayError
_ = group.create_array("extant", shape=(10,), dtype="uint8")
elif extant_node == "group":
expected_exception = ContainsGroupError
_ = group.create_group("extant")
else:
raise AssertionError
new_shape = (2, 2)
new_dtype = "float32"
if exists_ok:
if not store.supports_deletes:
pytest.skip("store does not support deletes")
arr_new = Array.create(
spath / "extant",
shape=new_shape,
dtype=new_dtype,
exists_ok=exists_ok,
zarr_format=zarr_format,
)
assert arr_new.shape == new_shape
assert arr_new.dtype == new_dtype
else:
with pytest.raises(expected_exception):
arr_new = Array.create(
spath / "extant",
shape=new_shape,
dtype=new_dtype,
exists_ok=exists_ok,
zarr_format=zarr_format,
)
@pytest.mark.parametrize("store", ["local", "memory", "zip"], indirect=["store"])
@pytest.mark.parametrize("zarr_format", [2, 3])
async def test_create_creates_parents(
store: LocalStore | MemoryStore, zarr_format: ZarrFormat
) -> None:
# prepare a root node, with some data set
await zarr.api.asynchronous.open_group(
store=store, path="a", zarr_format=zarr_format, attributes={"key": "value"}
)
# create a child node with a couple intermediates
await zarr.api.asynchronous.create(
shape=(2, 2), store=store, path="a/b/c/d", zarr_format=zarr_format
)
parts = ["a", "a/b", "a/b/c"]
if zarr_format == 2:
files = [".zattrs", ".zgroup"]
else:
files = ["zarr.json"]
expected = [f"{part}/{file}" for file in files for part in parts]
if zarr_format == 2:
expected.extend([".zattrs", ".zgroup", "a/b/c/d/.zarray", "a/b/c/d/.zattrs"])
else:
expected.extend(["zarr.json", "a/b/c/d/zarr.json"])
expected = sorted(expected)
result = sorted([x async for x in store.list_prefix("")])
assert result == expected
paths = ["a", "a/b", "a/b/c"]
for path in paths:
g = await zarr.api.asynchronous.open_group(store=store, path=path)
assert isinstance(g, AsyncGroup)
@pytest.mark.parametrize("store", ["local", "memory", "zip"], indirect=["store"])
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_array_name_properties_no_group(
store: LocalStore | MemoryStore, zarr_format: ZarrFormat
) -> None:
arr = Array.create(store=store, shape=(100,), chunks=(10,), zarr_format=zarr_format, dtype="i4")
assert arr.path == ""
assert arr.name is None
assert arr.basename is None
@pytest.mark.parametrize("store", ["local", "memory", "zip"], indirect=["store"])
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_array_name_properties_with_group(
store: LocalStore | MemoryStore, zarr_format: ZarrFormat
) -> None:
root = Group.from_store(store=store, zarr_format=zarr_format)
foo = root.create_array("foo", shape=(100,), chunks=(10,), dtype="i4")
assert foo.path == "foo"
assert foo.name == "/foo"
assert foo.basename == "foo"
bar = root.create_group("bar")
spam = bar.create_array("spam", shape=(100,), chunks=(10,), dtype="i4")
assert spam.path == "bar/spam"
assert spam.name == "/bar/spam"
assert spam.basename == "spam"
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize("specifiy_fill_value", [True, False])
@pytest.mark.parametrize("dtype_str", ["bool", "uint8", "complex64"])
def test_array_v3_fill_value_default(
store: MemoryStore, specifiy_fill_value: bool, dtype_str: str
) -> None:
"""
Test that creating an array with the fill_value parameter set to None, or unspecified,
results in the expected fill_value attribute of the array, i.e. 0 cast to the array's dtype.
"""
shape = (10,)
default_fill_value = 0
if specifiy_fill_value:
arr = Array.create(
store=store,
shape=shape,
dtype=dtype_str,
zarr_format=3,
chunk_shape=shape,
fill_value=None,
)
else:
arr = Array.create(
store=store, shape=shape, dtype=dtype_str, zarr_format=3, chunk_shape=shape
)
assert arr.fill_value == np.dtype(dtype_str).type(default_fill_value)
assert arr.fill_value.dtype == arr.dtype
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize(
("dtype_str", "fill_value"),
[("bool", True), ("uint8", 99), ("float32", -99.9), ("complex64", 3 + 4j)],
)
def test_array_v3_fill_value(store: MemoryStore, fill_value: int, dtype_str: str) -> None:
shape = (10,)
arr = Array.create(
store=store,
shape=shape,
dtype=dtype_str,
zarr_format=3,
chunk_shape=shape,
fill_value=fill_value,
)
assert arr.fill_value == np.dtype(dtype_str).type(fill_value)
assert arr.fill_value.dtype == arr.dtype
def test_create_positional_args_deprecated() -> None:
store = MemoryStore()
with pytest.warns(FutureWarning, match="Pass"):
Array.create(store, (2, 2), dtype="f8")
def test_selection_positional_args_deprecated() -> None:
store = MemoryStore()
arr = Array.create(store, shape=(2, 2), dtype="f8")
with pytest.warns(FutureWarning, match="Pass out"):
arr.get_basic_selection(..., NDBuffer(array=np.empty((2, 2))))
with pytest.warns(FutureWarning, match="Pass fields"):
arr.set_basic_selection(..., 1, None)
with pytest.warns(FutureWarning, match="Pass out"):
arr.get_orthogonal_selection(..., NDBuffer(array=np.empty((2, 2))))
with pytest.warns(FutureWarning, match="Pass"):
arr.set_orthogonal_selection(..., 1, None)
with pytest.warns(FutureWarning, match="Pass"):
arr.get_mask_selection(np.zeros((2, 2), dtype=bool), NDBuffer(array=np.empty((0,))))
with pytest.warns(FutureWarning, match="Pass"):
arr.set_mask_selection(np.zeros((2, 2), dtype=bool), 1, None)
with pytest.warns(FutureWarning, match="Pass"):
arr.get_coordinate_selection(([0, 1], [0, 1]), NDBuffer(array=np.empty((2,))))
with pytest.warns(FutureWarning, match="Pass"):
arr.set_coordinate_selection(([0, 1], [0, 1]), 1, None)
with pytest.warns(FutureWarning, match="Pass"):
arr.get_block_selection((0, slice(None)), NDBuffer(array=np.empty((2, 2))))
with pytest.warns(FutureWarning, match="Pass"):
arr.set_block_selection((0, slice(None)), 1, None)
@pytest.mark.parametrize("store", ["memory"], indirect=True)
async def test_array_v3_nan_fill_value(store: MemoryStore) -> None:
shape = (10,)
arr = Array.create(
store=store,
shape=shape,
dtype=np.float64,
zarr_format=3,
chunk_shape=shape,
fill_value=np.nan,
)
arr[:] = np.nan
assert np.isnan(arr.fill_value)
assert arr.fill_value.dtype == arr.dtype
# all fill value chunk is an empty chunk, and should not be written
assert len([a async for a in store.list_prefix("/")]) == 0
@pytest.mark.parametrize("store", ["local"], indirect=["store"])
@pytest.mark.parametrize("zarr_format", [2, 3])
async def test_serializable_async_array(
store: LocalStore | MemoryStore, zarr_format: ZarrFormat
) -> None:
expected = await AsyncArray.create(
store=store, shape=(100,), chunks=(10,), zarr_format=zarr_format, dtype="i4"
)
# await expected.setitems(list(range(100)))
p = pickle.dumps(expected)
actual = pickle.loads(p)
assert actual == expected
# np.testing.assert_array_equal(await actual.getitem(slice(None)), await expected.getitem(slice(None)))
# TODO: uncomment the parts of this test that will be impacted by the config/prototype changes in flight
@pytest.mark.parametrize("store", ["local"], indirect=["store"])
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_serializable_sync_array(store: LocalStore, zarr_format: ZarrFormat) -> None:
expected = Array.create(
store=store, shape=(100,), chunks=(10,), zarr_format=zarr_format, dtype="i4"
)
expected[:] = list(range(100))
p = pickle.dumps(expected)
actual = pickle.loads(p)
assert actual == expected
np.testing.assert_array_equal(actual[:], expected[:])
@pytest.mark.parametrize("store", ["memory"], indirect=True)
def test_storage_transformers(store: MemoryStore) -> None:
"""
Test that providing an actual storage transformer produces a warning and otherwise passes through
"""
metadata_dict: dict[str, JSON] = {
"zarr_format": 3,
"node_type": "array",
"shape": (10,),
"chunk_grid": {"name": "regular", "configuration": {"chunk_shape": (1,)}},
"data_type": "uint8",
"chunk_key_encoding": {"name": "v2", "configuration": {"separator": "/"}},
"codecs": (BytesCodec().to_dict(),),
"fill_value": 0,
"storage_transformers": ({"test": "should_raise"}),
}
match = "Arrays with storage transformers are not supported in zarr-python at this time."
with pytest.raises(ValueError, match=match):
Array.from_dict(StorePath(store), data=metadata_dict)
@pytest.mark.parametrize("test_cls", [Array, AsyncArray[Any]])
@pytest.mark.parametrize("nchunks", [2, 5, 10])
def test_nchunks(test_cls: type[Array] | type[AsyncArray[Any]], nchunks: int) -> None:
"""
Test that nchunks returns the number of chunks defined for the array.
"""
store = MemoryStore()
shape = 100
arr = Array.create(store, shape=(shape,), chunks=(ceildiv(shape, nchunks),), dtype="i4")
expected = nchunks
if test_cls == Array:
observed = arr.nchunks
else:
observed = arr._async_array.nchunks
assert observed == expected
@pytest.mark.parametrize("test_cls", [Array, AsyncArray[Any]])
async def test_nchunks_initialized(test_cls: type[Array] | type[AsyncArray[Any]]) -> None:
"""
Test that nchunks_initialized accurately returns the number of stored chunks.
"""
store = MemoryStore()
arr = Array.create(store, shape=(100,), chunks=(10,), dtype="i4")
# write chunks one at a time
for idx, region in enumerate(arr._iter_chunk_regions()):
arr[region] = 1
expected = idx + 1
if test_cls == Array:
observed = arr.nchunks_initialized
else:
observed = await arr._async_array.nchunks_initialized()
assert observed == expected
# delete chunks
for idx, key in enumerate(arr._iter_chunk_keys()):
sync(arr.store_path.store.delete(key))
if test_cls == Array:
observed = arr.nchunks_initialized
else:
observed = await arr._async_array.nchunks_initialized()
expected = arr.nchunks - idx - 1
assert observed == expected
async def test_chunks_initialized() -> None:
"""
Test that chunks_initialized accurately returns the keys of stored chunks.
"""
store = MemoryStore()
arr = Array.create(store, shape=(100,), chunks=(10,), dtype="i4")
chunks_accumulated = tuple(
accumulate(tuple(tuple(v.split(" ")) for v in arr._iter_chunk_keys()))
)
for keys, region in zip(chunks_accumulated, arr._iter_chunk_regions(), strict=False):
arr[region] = 1
observed = sorted(await chunks_initialized(arr._async_array))
expected = sorted(keys)
assert observed == expected
def test_nbytes_stored() -> None:
arr = zarr.create(shape=(100,), chunks=(10,), dtype="i4")
result = arr.nbytes_stored()
assert result == 366 # the size of the metadata document. This is a fragile test.
arr[:50] = 1
result = arr.nbytes_stored()
assert result == 566 # the size with 5 chunks filled.
arr[50:] = 2
result = arr.nbytes_stored()
assert result == 766 # the size with all chunks filled.
async def test_nbytes_stored_async() -> None:
arr = await zarr.api.asynchronous.create(shape=(100,), chunks=(10,), dtype="i4")
result = await arr.nbytes_stored()
assert result == 366 # the size of the metadata document. This is a fragile test.
await arr.setitem(slice(50), 1)
result = await arr.nbytes_stored()
assert result == 566 # the size with 5 chunks filled.
await arr.setitem(slice(50, 100), 2)
result = await arr.nbytes_stored()
assert result == 766 # the size with all chunks filled.
def test_default_fill_values() -> None:
a = Array.create(MemoryStore(), shape=5, chunk_shape=5, dtype="<U4")
assert a.fill_value == ""
b = Array.create(MemoryStore(), shape=5, chunk_shape=5, dtype="<S4")
assert b.fill_value == b""
c = Array.create(MemoryStore(), shape=5, chunk_shape=5, dtype="i")
assert c.fill_value == 0
d = Array.create(MemoryStore(), shape=5, chunk_shape=5, dtype="f")
assert d.fill_value == 0.0
def test_vlen_errors() -> None:
with pytest.raises(ValueError, match="At least one ArrayBytesCodec is required."):
Array.create(MemoryStore(), shape=5, chunk_shape=5, dtype="<U4", codecs=[])
with pytest.raises(
ValueError,
match="For string dtype, ArrayBytesCodec must be `VLenUTF8Codec`, got `BytesCodec`.",
):
Array.create(MemoryStore(), shape=5, chunk_shape=5, dtype="<U4", codecs=[BytesCodec()])
with pytest.raises(ValueError, match="Only one ArrayBytesCodec is allowed."):
Array.create(
MemoryStore(),
shape=5,
chunk_shape=5,
dtype="<U4",
codecs=[BytesCodec(), VLenBytesCodec()],
)
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_update_attrs(zarr_format: int) -> None:
# regression test for https://github.com/zarr-developers/zarr-python/issues/2328
store = MemoryStore()
arr = Array.create(store=store, shape=5, chunk_shape=5, dtype="f8", zarr_format=zarr_format)
arr.attrs["foo"] = "bar"
assert arr.attrs["foo"] == "bar"
arr2 = zarr.open_array(store=store, zarr_format=zarr_format)
assert arr2.attrs["foo"] == "bar"
class TestInfo:
def test_info_v2(self) -> None:
arr = zarr.create(shape=(4, 4), chunks=(2, 2), zarr_format=2)
result = arr.info
expected = ArrayInfo(
_zarr_format=2,
_data_type=np.dtype("float64"),
_shape=(4, 4),
_chunk_shape=(2, 2),
_order="C",
_read_only=False,
_store_type="MemoryStore",
_count_bytes=128,
_filters=(numcodecs.Zstd(),),
)
assert result == expected
def test_info_v3(self) -> None:
arr = zarr.create(shape=(4, 4), chunks=(2, 2), zarr_format=3)
result = arr.info
expected = ArrayInfo(
_zarr_format=3,
_data_type=DataType.parse("float64"),
_shape=(4, 4),
_chunk_shape=(2, 2),
_order="C",
_read_only=False,
_store_type="MemoryStore",
_codecs=[BytesCodec()],
_count_bytes=128,
)
assert result == expected
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_resize_1d(store: MemoryStore, zarr_format: int) -> None:
z = zarr.create(
shape=105, chunks=10, dtype="i4", fill_value=0, store=store, zarr_format=zarr_format
)
a = np.arange(105, dtype="i4")
z[:] = a
assert (105,) == z.shape
assert (105,) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10,) == z.chunks
np.testing.assert_array_equal(a, z[:])
z.resize(205)
assert (205,) == z.shape
assert (205,) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10,) == z.chunks
np.testing.assert_array_equal(a, z[:105])
np.testing.assert_array_equal(np.zeros(100, dtype="i4"), z[105:])
z.resize(55)
assert (55,) == z.shape
assert (55,) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10,) == z.chunks
np.testing.assert_array_equal(a[:55], z[:])
# via shape setter
new_shape = (105,)
z.shape = new_shape
assert new_shape == z.shape
assert new_shape == z[:].shape
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_resize_2d(store: MemoryStore, zarr_format: int) -> None:
z = zarr.create(
shape=(105, 105),
chunks=(10, 10),
dtype="i4",
fill_value=0,
store=store,
zarr_format=zarr_format,
)
a = np.arange(105 * 105, dtype="i4").reshape((105, 105))
z[:] = a
assert (105, 105) == z.shape
assert (105, 105) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10, 10) == z.chunks
np.testing.assert_array_equal(a, z[:])
z.resize((205, 205))
assert (205, 205) == z.shape
assert (205, 205) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10, 10) == z.chunks
np.testing.assert_array_equal(a, z[:105, :105])
np.testing.assert_array_equal(np.zeros((100, 205), dtype="i4"), z[105:, :])
np.testing.assert_array_equal(np.zeros((205, 100), dtype="i4"), z[:, 105:])
z.resize((55, 55))
assert (55, 55) == z.shape
assert (55, 55) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10, 10) == z.chunks
np.testing.assert_array_equal(a[:55, :55], z[:])
z.resize((55, 1))
assert (55, 1) == z.shape
assert (55, 1) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10, 10) == z.chunks
np.testing.assert_array_equal(a[:55, :1], z[:])
z.resize((1, 55))
assert (1, 55) == z.shape
assert (1, 55) == z[:].shape
assert np.dtype("i4") == z.dtype
assert np.dtype("i4") == z[:].dtype
assert (10, 10) == z.chunks
np.testing.assert_array_equal(a[:1, :10], z[:, :10])
np.testing.assert_array_equal(np.zeros((1, 55 - 10), dtype="i4"), z[:, 10:55])
# via shape setter
new_shape = (105, 105)
z.shape = new_shape
assert new_shape == z.shape
assert new_shape == z[:].shape
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_append_1d(store: MemoryStore, zarr_format: int) -> None:
a = np.arange(105)
z = zarr.create(shape=a.shape, chunks=10, dtype=a.dtype, store=store, zarr_format=zarr_format)
z[:] = a
assert a.shape == z.shape
assert a.dtype == z.dtype
assert (10,) == z.chunks
np.testing.assert_array_equal(a, z[:])
b = np.arange(105, 205)
e = np.append(a, b)
assert z.shape == (105,)
z.append(b)
assert e.shape == z.shape
assert e.dtype == z.dtype
assert (10,) == z.chunks
np.testing.assert_array_equal(e, z[:])
# check append handles array-like
c = [1, 2, 3]
f = np.append(e, c)
z.append(c)
assert f.shape == z.shape
assert f.dtype == z.dtype
assert (10,) == z.chunks
np.testing.assert_array_equal(f, z[:])
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_append_2d(store: MemoryStore, zarr_format: int) -> None:
a = np.arange(105 * 105, dtype="i4").reshape((105, 105))
z = zarr.create(
shape=a.shape, chunks=(10, 10), dtype=a.dtype, store=store, zarr_format=zarr_format
)
z[:] = a
assert a.shape == z.shape
assert a.dtype == z.dtype
assert (10, 10) == z.chunks
actual = z[:]
np.testing.assert_array_equal(a, actual)
b = np.arange(105 * 105, 2 * 105 * 105, dtype="i4").reshape((105, 105))
e = np.append(a, b, axis=0)
z.append(b)
assert e.shape == z.shape
assert e.dtype == z.dtype
assert (10, 10) == z.chunks
actual = z[:]
np.testing.assert_array_equal(e, actual)
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_append_2d_axis(store: MemoryStore, zarr_format: int) -> None:
a = np.arange(105 * 105, dtype="i4").reshape((105, 105))
z = zarr.create(
shape=a.shape, chunks=(10, 10), dtype=a.dtype, store=store, zarr_format=zarr_format
)
z[:] = a
assert a.shape == z.shape
assert a.dtype == z.dtype
assert (10, 10) == z.chunks
np.testing.assert_array_equal(a, z[:])
b = np.arange(105 * 105, 2 * 105 * 105, dtype="i4").reshape((105, 105))
e = np.append(a, b, axis=1)
z.append(b, axis=1)
assert e.shape == z.shape
assert e.dtype == z.dtype
assert (10, 10) == z.chunks
np.testing.assert_array_equal(e, z[:])
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize("zarr_format", [2, 3])
def test_append_bad_shape(store: MemoryStore, zarr_format: int) -> None:
a = np.arange(100)
z = zarr.create(shape=a.shape, chunks=10, dtype=a.dtype, store=store, zarr_format=zarr_format)
z[:] = a
b = a.reshape(10, 10)
with pytest.raises(ValueError):
z.append(b)
@pytest.mark.parametrize("order", ["C", "F", None])
@pytest.mark.parametrize("zarr_format", [2, 3])
@pytest.mark.parametrize("store", ["memory"], indirect=True)
def test_array_create_order(
order: MemoryOrder | None, zarr_format: int, store: MemoryStore
) -> None:
arr = Array.create(store=store, shape=(2, 2), order=order, zarr_format=zarr_format, dtype="i4")
expected = order or zarr.config.get("array.order")
assert arr.order == expected
vals = np.asarray(arr)
if expected == "C":
assert vals.flags.c_contiguous
elif expected == "F":
assert vals.flags.f_contiguous
else:
raise AssertionError
@pytest.mark.parametrize(
("fill_value", "expected"),
[
(np.nan * 1j, ["NaN", "NaN"]),
(np.nan, ["NaN", 0.0]),
(np.inf, ["Infinity", 0.0]),
(np.inf * 1j, ["NaN", "Infinity"]),
(-np.inf, ["-Infinity", 0.0]),
(math.inf, ["Infinity", 0.0]),
],
)
async def test_special_complex_fill_values_roundtrip(fill_value: Any, expected: list[Any]) -> None:
store = MemoryStore()
Array.create(store=store, shape=(1,), dtype=np.complex64, fill_value=fill_value)
content = await store.get("zarr.json", prototype=default_buffer_prototype())
assert content is not None
actual = json.loads(content.to_bytes())
assert actual["fill_value"] == expected