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adding conversion to tensorstore #242
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Seems like the new pydantic release is breaking. |
also removed non-standard axis
@edyoshikun Did you cherry-pick the commit from main? The history is now weird. I would rebase it manually. |
except ValueError as e: | ||
print(f"Error opening Zarr store: {e}") | ||
raise |
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What's the purpose of this?
"path": str((Path(self._store.path) / self.path).resolve()), | ||
}, | ||
"metadata": metadata, | ||
} |
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There could be a **ts_kwargs
here to allow passing in additional configuration, for example a global cache context.
) | ||
def test_ome_zarr_to_tensorstore(channels_and_random_5d, arr_name): | ||
"""Test `iohub.ngff.Position.data` to tensortore""" | ||
pytest.importorskip("tensorstore") |
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Maybe add tensorstore to dev requirements and not skip this?
@@ -344,7 +345,27 @@ def downscale(self): | |||
raise NotImplementedError | |||
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def tensorstore(self): | |||
raise NotImplementedError | |||
import tensorstore as ts |
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Needs a docstring.
with _temp_ome_zarr(random_5d, channel_names, "0") as dataset: | ||
assert_array_almost_equal(dataset.data.numpy(), random_5d) |
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Is this redundant with another test case?
This PR makes a zarray into tensorstore object