Add support for Array API in NamedArray #13899
GitHub Actions / Test Results
failed
Aug 22, 2024 in 0s
143 errors, 2 128 fail, 7 919 skipped, 3 502 pass in 5m 53s
Annotations
github-actions / Test Results
1 out of 2 runs with error: xarray.tests.test_dask
artifacts/Test results for Linux-3.12 flaky/pytest.xml [took 0s]
Raw output
collection failure
#x1B[31mImportError while importing test module '/home/runner/work/xarray/xarray/xarray/tests/test_dask.py'.
Hint: make sure your test modules/packages have valid Python names.
Traceback:
#x1B[1m#x1B[31m../../../micromamba/envs/xarray-tests/lib/python3.12/importlib/__init__.py#x1B[0m:90: in import_module
return _bootstrap._gcd_import(name[level:], package, level)
#x1B[1m#x1B[31mxarray/tests/test_dask.py#x1B[0m:1127: in <module>
@pytest.mark.parametrize("obj", [make_ds(), make_da()])
#x1B[1m#x1B[31mxarray/tests/test_dask.py#x1B[0m:1067: in make_ds
map_ds["a"] = make_da()
#x1B[1m#x1B[31mxarray/tests/test_dask.py#x1B[0m:1059: in make_da
da.coords["ndcoord"] = da.x * 2
#x1B[1m#x1B[31mxarray/core/_typed_ops.py#x1B[0m:253: in __mul__
return self._binary_op(other, operator.mul)
#x1B[1m#x1B[31mxarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31mxarray/namedarray/core.py#x1B[0m:543: in __mul__
from xarray.namedarray._array_api import asarray, multiply
#x1B[1m#x1B[31mxarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31mxarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
#x1B[1m#x1B[31mxarray/namedarray/_array_api/_utils.py#x1B[0m:28: in _maybe_default_namespace
import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m#x1B[0m
github-actions / Test Results
1 out of 2 runs with error: xarray.tests.test_sparse
artifacts/Test results for Linux-3.12 flaky/pytest.xml [took 0s]
Raw output
collection failure
#x1B[31mImportError while importing test module '/home/runner/work/xarray/xarray/xarray/tests/test_sparse.py'.
Hint: make sure your test modules/packages have valid Python names.
Traceback:
#x1B[1m#x1B[31m../../../micromamba/envs/xarray-tests/lib/python3.12/importlib/__init__.py#x1B[0m:90: in import_module
return _bootstrap._gcd_import(name[level:], package, level)
#x1B[1m#x1B[31mxarray/tests/test_sparse.py#x1B[0m:220: in <module>
(do("where", cond=make_xrvar({"x": 10, "y": 5}) > 0.5), True),
#x1B[1m#x1B[31mxarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31mxarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31mxarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
#x1B[1m#x1B[31mxarray/namedarray/_array_api/_utils.py#x1B[0m:28: in _maybe_default_namespace
import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m#x1B[0m
Check warning on line 0 in xarray.tests.test_accessor_dt.TestDatetimeAccessor
github-actions / Test Results
test_total_seconds (xarray.tests.test_accessor_dt.TestDatetimeAccessor) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_accessor_dt.TestDatetimeAccessor object at 0x7ffb894213c0>
def test_total_seconds(self) -> None:
# Subtract a value in the middle of the range to ensure that some values
# are negative
> delta = self.data.time - np.datetime64("2000-01-03")
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_accessor_dt.py#x1B[0m:107:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:250: in __sub__
return self._binary_op(other, operator.sub)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:590: in __sub__
from xarray.namedarray._array_api import asarray, subtract
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_accessor_dt.TestDatetimeAccessor
github-actions / Test Results
test_strftime (xarray.tests.test_accessor_dt.TestDatetimeAccessor) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_accessor_dt.TestDatetimeAccessor object at 0x7ffb89139d50>
def test_strftime(self) -> None:
> assert (
"2000-01-01 01:00:00" == self.data.time.dt.strftime("%Y-%m-%d %H:%M:%S")[1]
)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_accessor_dt.py#x1B[0m:140:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:295: in __eq__
return self._binary_op(other, nputils.array_eq)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/nputils.py#x1B[0m:113: in array_eq
return _ensure_bool_is_ndarray(self == other, self, other)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:467: in __eq__
from xarray.namedarray._array_api import asarray, equal
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-1-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 1, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-1-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 1, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-2-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 2, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-2-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 2, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_assertions
github-actions / Test Results
test_ensure_warnings_not_elevated[assert_duckarray_equal] (xarray.tests.test_assertions) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
func = 'assert_duckarray_equal'
@pytest.mark.parametrize(
"func",
[
"assert_equal",
"assert_identical",
"assert_allclose",
"assert_duckarray_equal",
"assert_duckarray_allclose",
],
)
def test_ensure_warnings_not_elevated(func) -> None:
# make sure warnings are not elevated to errors in the assertion functions
# e.g. by @pytest.mark.filterwarnings("error")
# see https://github.com/pydata/xarray/pull/4760#issuecomment-774101639
# define a custom Variable class that raises a warning in assert_*
class WarningVariable(xr.Variable):
@property # type: ignore[misc]
def dims(self):
warnings.warn("warning in test")
return super().dims
def __array__(self, dtype=None, copy=None):
warnings.warn("warning in test")
return super().__array__()
a = WarningVariable("x", [1])
b = WarningVariable("x", [2])
with warnings.catch_warnings(record=True) as w:
# elevate warnings to errors
warnings.filterwarnings("error")
with pytest.raises(AssertionError):
> getattr(xr.testing, func)(a, b)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_assertions.py#x1B[0m:187:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/duck_array_ops.py#x1B[0m:314: in array_equiv
flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2))
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:467: in __eq__
from xarray.namedarray._array_api import asarray, equal
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-3-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 3, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_assertions
github-actions / Test Results
test_ensure_warnings_not_elevated[assert_duckarray_allclose] (xarray.tests.test_assertions) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
func = 'assert_duckarray_allclose'
@pytest.mark.parametrize(
"func",
[
"assert_equal",
"assert_identical",
"assert_allclose",
"assert_duckarray_equal",
"assert_duckarray_allclose",
],
)
def test_ensure_warnings_not_elevated(func) -> None:
# make sure warnings are not elevated to errors in the assertion functions
# e.g. by @pytest.mark.filterwarnings("error")
# see https://github.com/pydata/xarray/pull/4760#issuecomment-774101639
# define a custom Variable class that raises a warning in assert_*
class WarningVariable(xr.Variable):
@property # type: ignore[misc]
def dims(self):
warnings.warn("warning in test")
return super().dims
def __array__(self, dtype=None, copy=None):
warnings.warn("warning in test")
return super().__array__()
a = WarningVariable("x", [1])
b = WarningVariable("x", [2])
with warnings.catch_warnings(record=True) as w:
# elevate warnings to errors
warnings.filterwarnings("error")
with pytest.raises(AssertionError):
> getattr(xr.testing, func)(a, b)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_assertions.py#x1B[0m:187:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/testing/assertions.py#x1B[0m:294: in _format_message
diff = x - y
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:590: in __sub__
from xarray.namedarray._array_api import asarray, subtract
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-3-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 3, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-4-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 4, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_dataset.TestDataset
github-actions / Test Results
test_variable_indexing (xarray.tests.test_dataset.TestDataset) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_dataset.TestDataset object at 0x7f638c353070>
def test_variable_indexing(self) -> None:
data = create_test_data()
v = data["var1"]
d1 = data["dim1"]
d2 = data["dim2"]
assert_equal(v, v[d1.values])
assert_equal(v, v[d1])
> assert_equal(v[:3], v[d1 < 3])
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_dataset.py#x1B[0m:2692:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:283: in __lt__
return self._binary_op(other, operator.lt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:528: in __lt__
from xarray.namedarray._array_api import asarray, less
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-sum-4-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 4, name = 'sum'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-1-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 1, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-1-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 1, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_datatree_mapping.TestMapOverSubTree
github-actions / Test Results
test_single_dt_arg (xarray.tests.test_datatree_mapping.TestMapOverSubTree) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_datatree_mapping.TestMapOverSubTree object at 0x7ffb869b0f40>
create_test_datatree = <function create_test_datatree.<locals>._create_test_datatree at 0x7ffb85ef7a30>
def test_single_dt_arg(self, create_test_datatree):
dt = create_test_datatree()
@map_over_subtree
def times_ten(ds):
return 10.0 * ds
> expected = create_test_datatree(modify=lambda ds: 10.0 * ds)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_datatree_mapping.py#x1B[0m:122:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/conftest.py#x1B[0m:175: in _create_test_datatree
set1_data = modify(xr.Dataset({"a": 0, "b": 1}))
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_datatree_mapping.py#x1B[0m:122: in <lambda>
expected = create_test_datatree(modify=lambda ds: 10.0 * ds)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:99: in __rmul__
return self._binary_op(other, operator.mul, reflexive=True)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7778: in _binary_op
ds = self._calculate_binary_op(g, other, join=align_type)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7847: in _calculate_binary_op
new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars}
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7847: in <dictcomp>
new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars}
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7777: in <lambda>
g = f if not reflexive else lambda x, y: f(y, x)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:663: in __rmul__
from xarray.namedarray._array_api import asarray, multiply
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-2-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 2, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-2-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 2, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-3-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 3, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_datatree_mapping.TestMapOverSubTree
github-actions / Test Results
test_single_dt_arg_plus_args_and_kwargs (xarray.tests.test_datatree_mapping.TestMapOverSubTree) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_datatree_mapping.TestMapOverSubTree object at 0x7ffb869b0c10>
create_test_datatree = <function create_test_datatree.<locals>._create_test_datatree at 0x7ffb85ef7a30>
def test_single_dt_arg_plus_args_and_kwargs(self, create_test_datatree):
dt = create_test_datatree()
@map_over_subtree
def multiply_then_add(ds, times, add=0.0):
return (times * ds) + add
> expected = create_test_datatree(modify=lambda ds: (10.0 * ds) + 2.0)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_datatree_mapping.py#x1B[0m:133:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/conftest.py#x1B[0m:175: in _create_test_datatree
set1_data = modify(xr.Dataset({"a": 0, "b": 1}))
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_datatree_mapping.py#x1B[0m:133: in <lambda>
expected = create_test_datatree(modify=lambda ds: (10.0 * ds) + 2.0)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:99: in __rmul__
return self._binary_op(other, operator.mul, reflexive=True)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7778: in _binary_op
ds = self._calculate_binary_op(g, other, join=align_type)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7847: in _calculate_binary_op
new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars}
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7847: in <dictcomp>
new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars}
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7777: in <lambda>
g = f if not reflexive else lambda x, y: f(y, x)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:663: in __rmul__
from xarray.namedarray._array_api import asarray, multiply
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-3-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 3, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-4-1] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (a: 3, time: 21, x: 4)> Size: 2kB
array([[[0.5488135 , 0.71518937, 0.60276338, 0.54488318],
...ates:
* time (time) datetime64[ns] 168B 2000-01-01 2000-01-02 ... 2000-01-21
Dimensions without coordinates: a, x
window = 4, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Check warning on line 0 in xarray.tests.test_coarsen
github-actions / Test Results
test_coarsen_da_reduce[numpy-mean-4-2] (xarray.tests.test_coarsen) failed
artifacts/Test results for Linux-3.10 bare-minimum/pytest.xml [took 0s]
Raw output
ModuleNotFoundError: No module named 'array_api_compat'
da = <xarray.DataArray (time: 11)> Size: 88B
array([ 0., nan, 1., 2., nan, 3., 4., 5., nan, 6., 7.])
Dimensions without coordinates: time
window = 4, name = 'mean'
@pytest.mark.parametrize("da", (1, 2), indirect=True)
@pytest.mark.parametrize("window", (1, 2, 3, 4))
@pytest.mark.parametrize("name", ("sum", "mean", "std", "max"))
def test_coarsen_da_reduce(da, window, name) -> None:
> if da.isnull().sum() > 1 and window == 1:
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/tests/test_coarsen.py#x1B[0m:244:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:289: in __gt__
return self._binary_op(other, operator.gt)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:496: in __gt__
from xarray.namedarray._array_api import asarray, greater
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
_xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xp = None
def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
if xp is None:
# import array_api_strict as xpd
> import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m
#x1B[1m#x1B[31m/home/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:28: ModuleNotFoundError
Loading