1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
|
from __future__ import annotations
import re
from typing import TYPE_CHECKING
import h5py
import zarr
import anndata as ad
from anndata._io.zarr import open_write_group
from anndata.compat import CSArray, CSMatrix, ZarrGroup, is_zarr_v2
from anndata.experimental import read_dispatched, write_dispatched
from anndata.tests.helpers import assert_equal, gen_adata
if TYPE_CHECKING:
from collections.abc import Callable
from pathlib import Path
def test_read_dispatched_w_regex(tmp_path: Path):
def read_only_axis_dfs(func, elem_name: str, elem, iospec):
if iospec.encoding_type == "anndata":
return func(elem)
elif re.match(r"^/((obs)|(var))?(/.*)?$", elem_name):
return func(elem)
else:
return None
adata = gen_adata((1000, 100))
z = open_write_group(tmp_path)
ad.io.write_elem(z, "/", adata)
# TODO: see https://github.com/zarr-developers/zarr-python/issues/2716
if not is_zarr_v2() and isinstance(z, ZarrGroup):
z = zarr.open(z.store)
expected = ad.AnnData(obs=adata.obs, var=adata.var)
actual = read_dispatched(z, read_only_axis_dfs)
assert_equal(expected, actual)
def test_read_dispatched_dask(tmp_path: Path):
import dask.array as da
def read_as_dask_array(func, elem_name: str, elem, iospec):
if iospec.encoding_type in {
"dataframe",
"csr_matrix",
"csc_matrix",
"awkward-array",
}:
# Preventing recursing inside of these types
return ad.io.read_elem(elem)
elif iospec.encoding_type == "array":
return da.from_zarr(elem)
else:
return func(elem)
adata = gen_adata((1000, 100))
z = open_write_group(tmp_path)
ad.io.write_elem(z, "/", adata)
# TODO: see https://github.com/zarr-developers/zarr-python/issues/2716
if not is_zarr_v2() and isinstance(z, ZarrGroup):
z = zarr.open(z.store)
dask_adata = read_dispatched(z, read_as_dask_array)
assert isinstance(dask_adata.layers["array"], da.Array)
assert isinstance(dask_adata.obsm["array"], da.Array)
assert isinstance(dask_adata.uns["nested"]["nested_further"]["array"], da.Array)
expected = ad.io.read_elem(z)
actual = dask_adata.to_memory(copy=False)
assert_equal(expected, actual)
def test_read_dispatched_null_case(tmp_path: Path):
adata = gen_adata((100, 100))
z = open_write_group(tmp_path)
ad.io.write_elem(z, "/", adata)
# TODO: see https://github.com/zarr-developers/zarr-python/issues/2716
if not is_zarr_v2() and isinstance(z, ZarrGroup):
z = zarr.open(z.store)
expected = ad.io.read_elem(z)
actual = read_dispatched(z, lambda _, __, x, **___: ad.io.read_elem(x))
assert_equal(expected, actual)
def test_write_dispatched_chunks(tmp_path: Path):
from itertools import chain, repeat
def determine_chunks(elem_shape, specified_chunks):
chunk_iterator = chain(specified_chunks, repeat(None))
return tuple(e if c is None else c for e, c in zip(elem_shape, chunk_iterator))
adata = gen_adata((1000, 100))
def write_chunked(func, store, k, elem, dataset_kwargs, iospec):
M, N = 13, 42
def set_copy(d, **kwargs):
d = dict(d)
d.update(kwargs)
return d
# TODO: Should the passed path be absolute?
path = "/" + store.path + "/" + k
if hasattr(elem, "shape") and not isinstance(
elem, CSMatrix | CSArray | ad.AnnData
):
if re.match(r"^/((X)|(layers)).*", path):
chunks = (M, N)
elif path.startswith("/obsp"):
chunks = (M, M)
elif path.startswith("/obs"):
chunks = (M,)
elif path.startswith("/varp"):
chunks = (N, N)
elif path.startswith("/var"):
chunks = (N,)
else:
chunks = dataset_kwargs.get("chunks", ())
func(
store,
k,
elem,
dataset_kwargs=set_copy(
dataset_kwargs, chunks=determine_chunks(elem.shape, chunks)
),
)
else:
func(store, k, elem, dataset_kwargs=dataset_kwargs)
z = open_write_group(tmp_path)
write_dispatched(z, "/", adata, callback=write_chunked)
def check_chunking(k: str, v: ZarrGroup | zarr.Array):
if (
not isinstance(v, zarr.Array)
or v.shape == ()
or any(k.endswith(x) for x in ("data", "indices", "indptr"))
):
return
if re.match(r"obs[mp]?/\w+", k):
assert v.chunks[0] == 13
elif re.match(r"var[mp]?/\w+", k):
assert v.chunks[0] == 42
if is_zarr_v2():
z.visititems(check_chunking)
else:
def visititems(
z: ZarrGroup, visitor: Callable[[str, ZarrGroup | zarr.Array], None]
) -> None:
for key in z:
maybe_group = z[key]
if isinstance(maybe_group, ZarrGroup):
visititems(maybe_group, visitor)
else:
visitor(key, maybe_group)
visititems(z, check_chunking)
def test_io_dispatched_keys(tmp_path: Path):
h5ad_write_keys = []
zarr_write_keys = []
h5ad_read_keys = []
zarr_read_keys = []
h5ad_path = tmp_path / "test.h5ad"
zarr_path = tmp_path / "test.zarr"
def h5ad_writer(func, store, k, elem, dataset_kwargs, iospec):
h5ad_write_keys.append(k if is_zarr_v2() else k.strip("/"))
func(store, k, elem, dataset_kwargs=dataset_kwargs)
def zarr_writer(func, store, k, elem, dataset_kwargs, iospec):
zarr_write_keys.append(
k if is_zarr_v2() else f"{store.name.strip('/')}/{k.strip('/')}".strip("/")
)
func(store, k, elem, dataset_kwargs=dataset_kwargs)
def h5ad_reader(func, elem_name: str, elem, iospec):
h5ad_read_keys.append(elem_name if is_zarr_v2() else elem_name.strip("/"))
return func(elem)
def zarr_reader(func, elem_name: str, elem, iospec):
zarr_read_keys.append(elem_name if is_zarr_v2() else elem_name.strip("/"))
return func(elem)
adata = gen_adata((50, 100))
with h5py.File(h5ad_path, "w") as f:
write_dispatched(f, "/", adata, callback=h5ad_writer)
_ = read_dispatched(f, h5ad_reader)
f = open_write_group(zarr_path)
write_dispatched(f, "/", adata, callback=zarr_writer)
_ = read_dispatched(f, zarr_reader)
assert sorted(h5ad_read_keys) == sorted(zarr_read_keys)
assert sorted(h5ad_write_keys) == sorted(zarr_write_keys)
for sub_sparse_key in ["data", "indices", "indptr"]:
assert f"/X/{sub_sparse_key}" not in h5ad_read_keys
assert f"/X/{sub_sparse_key}" not in h5ad_write_keys
|
