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install the dev version of sparse in the upstream-dev CI (#5059)
* re-enable sparse [test-upstream] * remove the comment about adding sparse back in * silence the failing test for now [test-upstream]
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ci/install-upstream-wheels.sh

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#!/usr/bin/env bash
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# TODO: add sparse back in, once Numba works with the development version of
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# NumPy again: https://github.com/pydata/xarray/issues/4146
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conda uninstall -y --force \
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numpy \
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scipy \
@@ -42,5 +39,5 @@ python -m pip install \
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git+https://github.com/Unidata/cftime \
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git+https://github.com/mapbox/rasterio \
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git+https://github.com/hgrecco/pint \
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git+https://github.com/pydata/bottleneck # \
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# git+https://github.com/pydata/sparse
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git+https://github.com/pydata/bottleneck \
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git+https://github.com/pydata/sparse

xarray/tests/test_sparse.py

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@@ -227,6 +227,10 @@ def test_variable_method(func, sparse_output):
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ret_s = func(var_s)
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ret_d = func(var_d)
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# TODO: figure out how to verify the results of each method
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if isinstance(ret_d, xr.Variable) and isinstance(ret_d.data, sparse.SparseArray):
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ret_d = ret_d.copy(data=ret_d.data.todense())
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if sparse_output:
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assert isinstance(ret_s.data, sparse.SparseArray)
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assert np.allclose(ret_s.data.todense(), ret_d.data, equal_nan=True)

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