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Dispatch to Dask if nanquantile is available #9719

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merged 4 commits into from
Nov 9, 2024
Merged

Dispatch to Dask if nanquantile is available #9719

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9569bdd
Dispatch to Dask is nanquantile is available
phofl Nov 5, 2024
d4a5011
Fixup
phofl Nov 5, 2024
61b7edf
Change test
phofl Nov 5, 2024
15354f8
Merge remote-tracking branch 'refs/remotes/upstream/main' into quanti…
phofl Nov 9, 2024
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3 changes: 2 additions & 1 deletion xarray/core/variable.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,7 @@
)
from xarray.namedarray.core import NamedArray, _raise_if_any_duplicate_dimensions
from xarray.namedarray.pycompat import integer_types, is_0d_dask_array, to_duck_array
from xarray.namedarray.utils import module_available
from xarray.util.deprecation_helpers import deprecate_dims

NON_NUMPY_SUPPORTED_ARRAY_TYPES = (
Expand Down Expand Up @@ -1948,7 +1949,7 @@ def _wrapper(npa, **kwargs):
output_core_dims=[["quantile"]],
output_dtypes=[np.float64],
dask_gufunc_kwargs=dict(output_sizes={"quantile": len(q)}),
dask="parallelized",
dask="allowed" if module_available("dask", "2024.11.0") else "parallelized",
kwargs=kwargs,
)

Expand Down
14 changes: 11 additions & 3 deletions xarray/tests/test_variable.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,7 @@
from xarray.core.utils import NDArrayMixin
from xarray.core.variable import as_compatible_data, as_variable
from xarray.namedarray.pycompat import array_type
from xarray.namedarray.utils import module_available
from xarray.tests import (
assert_allclose,
assert_array_equal,
Expand Down Expand Up @@ -1871,9 +1872,16 @@ def test_quantile_interpolation_deprecation(self, method) -> None:
def test_quantile_chunked_dim_error(self):
v = Variable(["x", "y"], self.d).chunk({"x": 2})

# this checks for ValueError in dask.array.apply_gufunc
with pytest.raises(ValueError, match=r"consists of multiple chunks"):
v.quantile(0.5, dim="x")
if module_available("dask", "2024.11.0"):
# Dask rechunks
np.testing.assert_allclose(
v.compute().quantile(0.5, dim="x"), v.quantile(0.5, dim="x")
)

else:
# this checks for ValueError in dask.array.apply_gufunc
with pytest.raises(ValueError, match=r"consists of multiple chunks"):
v.quantile(0.5, dim="x")

@pytest.mark.parametrize("compute_backend", ["numbagg", None], indirect=True)
@pytest.mark.parametrize("q", [-0.1, 1.1, [2], [0.25, 2]])
Expand Down
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