Enable tests with ome-zarr-py (#297)

* wip

* wip: 2025-02-27

* Undo reformatting

* Remove unused imports

* Fix miscellaneous failing tests.

* Get rename_well working.

* sort import

* Read MMStack with Zarr v3 (#293)

* use fsspec as a wrapper for ZarrTiffStore

* update deprecated readers and tests

* document the helper function

* add back the binary check after a flag

* use kwarg for file mode in reader

* restore dtype attribute

* restore opening zarr with dask

* stringify path name

* remove redundant dtype

* add rich for zarr v3 print tree

* skip tests that require ome-zarr-py

* fix file list checking
it doesn't matter what the order is

* fix commas

* stringify path names

* `test_rename_well` no longer broken, remove mark

* from_positions is actually broken
this is not related to ome-zarr-py

* enable tests against ome-zarr-py

* from_positions is actually broken
this is not related to ome-zarr-py

* replace almost equal assertion in the ngff-zarr test

* unskip ome-zarr-py tests

* consolidate import paths

* bump test requirement

---------

Co-authored-by: Alan Liddell <alan.c.liddell@gmail.com>
Co-authored-by: Alan Liddell <aliddell@chanzuckerberg.com>

Author: ziw-liu

setup.cfg

@@ -61,7 +61,7 @@ dev =
     hypothesis>=6.61.0
     requests>=2.22.0
     wget>=3.2
-    ome-zarr>=0.9.0
+    ome-zarr>=0.12.0
 
 doc =
     matplotlib

tests/ngff/test_ngff.py

@@ -13,11 +13,13 @@
 import hypothesis.extra.numpy as npst
 import hypothesis.strategies as st
 import numpy as np
+import ome_zarr.io
+import ome_zarr.reader
 import pytest
 import zarr.storage
 from hypothesis import HealthCheck, assume, given, settings
 from ngff_zarr import from_ngff_zarr
-from numpy.testing import assert_array_almost_equal, assert_array_equal
+from numpy.testing import assert_allclose, assert_array_equal
 from numpy.typing import NDArray
 
 if TYPE_CHECKING:
@@ -308,7 +310,6 @@ def _temp_ome_zarr_plate(
         temp_dir.cleanup()
 
 
-@pytest.mark.skip(reason="zarr-python / ome_zarr incompatibility")
 @given(
     channels_and_random_5d=_channels_and_random_5d(),
     arr_name=short_alpha_numeric,
@@ -321,21 +322,19 @@ def _temp_ome_zarr_plate(
 )
 def test_write_ome_zarr(channels_and_random_5d, arr_name, version):
     """Test `iohub.ngff.Position.__setitem__()`"""
-    from ome_zarr.io import parse_url
-    from ome_zarr.reader import Reader
-
     channel_names, random_5d = channels_and_random_5d
     with _temp_ome_zarr(
         random_5d, channel_names, arr_name, version=version
     ) as dataset:
-        assert_array_almost_equal(dataset[arr_name][:], random_5d)
+        assert_allclose(dataset[arr_name][:], random_5d)
         # round-trip test with the offical reader implementation
-        ext_reader = Reader(parse_url(dataset.zgroup.store.path))
+        ext_reader = ome_zarr.reader.Reader(
+            ome_zarr.io.parse_url(dataset.zgroup.store.root)
+        )
         node = list(ext_reader())[0]
         assert node.metadata["channel_names"] == channel_names
         assert node.specs[0].datasets == [arr_name]
-        assert node.data[0].shape == random_5d.shape
-        assert node.data[0].dtype == random_5d.dtype
+        assert_allclose(node.data[0], random_5d)
 
 
 @given(
@@ -397,15 +396,11 @@ def test_ome_zarr_to_dask(channels_and_random_5d, arr_name, version):
     with _temp_ome_zarr(
         random_5d, channel_names, "0", version=version
     ) as dataset:
-        assert_array_almost_equal(
-            dataset.data.dask_array().compute(), random_5d
-        )
+        assert_allclose(dataset.data.dask_array().compute(), random_5d)
     with _temp_ome_zarr(
         random_5d, channel_names, arr_name, version=version
     ) as dataset:
-        assert_array_almost_equal(
-            dataset[arr_name].dask_array().compute(), random_5d
-        )
+        assert_allclose(dataset[arr_name].dask_array().compute(), random_5d)
 
 
 @given(channels_and_random_5d=_channels_and_random_5d())
@@ -457,7 +452,7 @@ def test_position_data(channels_and_random_5d, arr_name, version):
     with _temp_ome_zarr(
         random_5d, channel_names, "0", version=version
     ) as dataset:
-        assert_array_almost_equal(dataset.data.numpy(), random_5d)
+        assert_allclose(dataset.data.numpy(), random_5d)
     with pytest.raises(KeyError):
         with _temp_ome_zarr(
             random_5d, channel_names, arr_name, version=version
@@ -513,7 +508,7 @@ def test_append_channel(channels_and_random_5d, arr_name, version):
     ) as dataset:
         dataset.append_channel(channel_names[-1], resize_arrays=True)
         dataset[arr_name][:, -1] = random_5d[:, -1]
-        assert_array_almost_equal(dataset[arr_name][:], random_5d)
+        assert_allclose(dataset[arr_name][:], random_5d)
 
 
 @given(
@@ -617,9 +612,7 @@ def test_update_channel(channels_and_random_5d, arr_name, version):
             dataset.update_channel(
                 chan_name=ch, target=arr_name, data=random_5d[:, -1]
             )
-            assert_array_almost_equal(
-                dataset[arr_name][:, i], random_5d[:, -1]
-            )
+            assert_allclose(dataset[arr_name][:, i], random_5d[:, -1])
 
 
 @given(
@@ -643,16 +636,12 @@ def test_write_more_channels(channels_and_random_5d, arr_name, version):
             pass
 
 
-@pytest.mark.skip(reason="zarr-python / ome_zarr incompatibility")
 @given(
     ch_shape_dtype=_channels_and_random_5d_shape_and_dtype(),
     arr_name=short_alpha_numeric,
 )
 def test_set_transform_image(ch_shape_dtype, arr_name):
     """Test `iohub.ngff.Position.set_transform()`"""
-    from ome_zarr.io import parse_url
-    from ome_zarr.reader import Reader
-
     channel_names, shape, dtype = ch_shape_dtype
     transform = [
         TransformationMeta(type="translation", translation=(1, 2, 3, 4, 5))
@@ -678,7 +667,9 @@ def test_set_transform_image(ch_shape_dtype, arr_name):
                 == transform
             )
         # read data with an external reader
-        ext_reader = Reader(parse_url(dataset.zgroup.store.path))
+        ext_reader = ome_zarr.reader.Reader(
+            ome_zarr.io.parse_url(dataset.zgroup.store.root)
+        )
         node = list(ext_reader())[0]
         assert node.metadata["coordinateTransformations"][0] == [
             translate.model_dump(**TO_DICT_SETTINGS) for translate in transform
@@ -1049,7 +1040,7 @@ def _tile_data(tiles):
         ) as dataset:
             for data, row, column in _tile_data(tiles):
                 read = tiles.get_tile(row, column)
-                assert_array_almost_equal(data, read)
+                assert_allclose(data, read)
 
 
 @given(channel_names=channel_names_st)
@@ -1258,9 +1249,6 @@ def test_position_scale(channels_and_random_5d, version):
     reason="https://github.com/zarr-developers/zarr-python/issues/2407"
 )
 def test_combine_fovs_to_hcs():
-    from ome_zarr.io import parse_url
-    from ome_zarr.reader import Reader
-
     fovs = {}
     fov_paths = ("A/1/0", "B/1/0", "H/12/9")
     with open_ome_zarr(hcs_ref) as hcs_store:
@@ -1285,7 +1273,6 @@ def test_combine_fovs_to_hcs():
                 assert_array_equal(dataset[fov_path]["0"].numpy(), array)
 
 
-@pytest.mark.skip(reason="zarr-python / ome_zarr incompatibility")
 def test_hcs_external_reader(tmp_path):
     store_path = tmp_path / "hcs.zarr"
     fov_name_parts = (("A", "1", "7"), ("B", "1", "7"), ("H", "12", "7"))
@@ -1298,7 +1285,9 @@ def test_hcs_external_reader(tmp_path):
             fov.create_zeros("0", shape=(1, 2, 3, y_size, x_size), dtype=int)
         n_rows = len(dataset.metadata.rows)
         n_cols = len(dataset.metadata.columns)
-    plate = list(Reader(parse_url(store_path))())[0]
+    plate = list(
+        ome_zarr.reader.Reader(ome_zarr.io.parse_url(store_path))()
+    )[0]
     assert plate.data[0].shape == (1, 2, 3, y_size * n_rows, x_size * n_cols)
     assert plate.data[0].dtype == int
     assert not plate.data[0].any()
@@ -1368,7 +1357,7 @@ def test_ngff_zarr_read(channels_and_random_5d, arr_name, version):
         nz_multiscales = from_ngff_zarr(
             dataset.zgroup.store.root, validate=True
         )
-        assert_array_almost_equal(
+        assert_allclose(
             dataset[arr_name].dask_array().compute(),
             nz_multiscales.images[0].data,
         )