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Reinstate tests that now pass due to changes in Cubed #45

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Merged
tomwhite merged 1 commit into from
May 25, 2026
Merged

Reinstate tests that now pass due to changes in Cubed #45

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36 changes: 18 additions & 18 deletions cubed_xarray/tests/test_xarray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
import xarray as xr
from cubed import raise_if_computes as raise_if_cubed_computes
from xarray import DataArray, Dataset, Variable
from xarray.core import duck_array_ops
from xarray.tests import (
assert_allclose,
assert_array_equal,
Expand Down Expand Up @@ -132,7 +133,7 @@ def test_roll(self):
u = self.eager_var
v = self.lazy_var
self.assertLazyAndIdentical(u.roll(x=2), v.roll(x=2))
# assert v.data.chunks == v.roll(x=1).data.chunks # TODO: fails
assert v.data.chunks == v.roll(x=1).data.chunks

def test_unary_op(self):
u = self.eager_var
Expand All @@ -146,7 +147,7 @@ def test_binary_op(self):
v = self.lazy_var
self.assertLazyAndIdentical(2 * u, 2 * v)
self.assertLazyAndIdentical(u + u, v + v)
# self.assertLazyAndIdentical(u[0] + u, v[0] + v) # TODO: fails
self.assertLazyAndIdentical(u[0] + u, v[0] + v)

def test_binary_op_bitshift(self) -> None:
# bit shifts only work on ints so we need to generate
Expand Down Expand Up @@ -185,22 +186,23 @@ def test_reduce(self):
u = self.eager_var
v = self.lazy_var
self.assertLazyAndAllClose(u.mean(), v.mean())
# TODO: other reduce functions need work
self.assertLazyAndAllClose((u > 1).any(), (v > 1).any())
self.assertLazyAndAllClose((u < 1).all("x"), (v < 1).all("x"))
with raise_if_cubed_computes():
v.reduce(duck_array_ops.mean)
# TODO: std, argmax, argmin compute eagerly (not lazy) in cubed
# self.assertLazyAndAllClose(u.std(), v.std())
# with raise_if_cubed_computes():
# actual = v.argmax(dim="x")
# self.assertLazyAndAllClose(u.argmax(dim="x"), actual)
# with raise_if_cubed_computes():
# actual = v.argmin(dim="x")
# self.assertLazyAndAllClose(u.argmin(dim="x"), actual)
# self.assertLazyAndAllClose((u > 1).any(), (v > 1).any())
# self.assertLazyAndAllClose((u < 1).all("x"), (v < 1).all("x"))
# TODO: median no longer raises NotImplementedError in xarray
# with pytest.raises(NotImplementedError, match=r"only works along an axis"):
# v.median()
# with pytest.raises(NotImplementedError, match=r"only works along an axis"):
# v.median(v.dims)
# with raise_if_cubed_computes():
# v.reduce(duck_array_ops.mean)

def test_missing_values(self):
values = np.array([0, 1, np.nan, 3])
Expand All @@ -210,7 +212,7 @@ def test_missing_values(self):
lazy_var = Variable("x", data)
self.assertLazyAndIdentical(eager_var, lazy_var.fillna(lazy_var))
self.assertLazyAndIdentical(Variable("x", range(4)), lazy_var.fillna(2))
# self.assertLazyAndIdentical(eager_var.count(), lazy_var.count()) # TODO: doesn't use array API
self.assertLazyAndIdentical(eager_var.count(), lazy_var.count())

def test_concat(self):
u = self.eager_var
Expand Down Expand Up @@ -423,7 +425,6 @@ def test_ufuncs(self):
v = self.lazy_array
self.assertLazyAndAllClose(np.sin(u), np.sin(v))

@pytest.mark.xfail(reason="failure in cubed")
def test_where_dispatching(self):
a = np.arange(10)
b = a > 3
Expand Down Expand Up @@ -665,16 +666,15 @@ def test_unify_chunks(map_ds):
assert out_a.chunks == ((4, 4, 2), (5, 5, 5, 5))
assert out_b.chunks == expected_chunks

# TODO: following fails
# # Test unordered dims
# da = ds_copy["cxy"]
# out_a, out_b = xr.unify_chunks(da.chunk({"x": -1}), da.T.chunk({"y": -1}))
# assert out_a.chunks == ((4, 4, 2), (5, 5, 5, 5))
# assert out_b.chunks == ((5, 5, 5, 5), (4, 4, 2))
# Test unordered dims
da = ds_copy["cxy"]
out_a, out_b = xr.unify_chunks(da.chunk({"x": -1}), da.T.chunk({"y": -1}))
assert out_a.chunks == ((4, 4, 2), (10, 10))
assert out_b.chunks == ((10, 10), (4, 4, 2))

# # Test mismatch
# with pytest.raises(ValueError, match=r"Dimension 'x' size mismatch: 10 != 2"):
# xr.unify_chunks(da, da.isel(x=slice(2)))
# Test mismatch
with pytest.raises(ValueError, match=r"Dimension 'x' size mismatch: 10 != 2"):
xr.unify_chunks(da, da.isel(x=slice(2)))


@pytest.mark.parametrize("obj", [make_ds(), make_da()])
Expand Down
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