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from __future__ import annotations
import warnings
import numpy as np
import pytest
import xarray as xr
from xarray.tests import has_dask
try:
from dask.array import from_array as dask_from_array
except ImportError:
dask_from_array = lambda x: x # type: ignore[assignment, misc]
try:
import pint
unit_registry = pint.UnitRegistry(force_ndarray_like=True)
def quantity(x):
return unit_registry.Quantity(x, "m")
has_pint = True
except ImportError:
def quantity(x):
return x
has_pint = False
def test_allclose_regression() -> None:
x = xr.DataArray(1.01)
y = xr.DataArray(1.02)
xr.testing.assert_allclose(x, y, atol=0.01)
@pytest.mark.parametrize(
"obj1,obj2",
(
pytest.param(
xr.Variable("x", [1e-17, 2]), xr.Variable("x", [0, 3]), id="Variable"
),
pytest.param(
xr.DataArray([1e-17, 2], dims="x"),
xr.DataArray([0, 3], dims="x"),
id="DataArray",
),
pytest.param(
xr.Dataset({"a": ("x", [1e-17, 2]), "b": ("y", [-2e-18, 2])}),
xr.Dataset({"a": ("x", [0, 2]), "b": ("y", [0, 1])}),
id="Dataset",
),
pytest.param(
xr.DataArray(np.array("a", dtype="|S1")),
xr.DataArray(np.array("b", dtype="|S1")),
id="DataArray_with_character_dtype",
),
pytest.param(
xr.Coordinates({"x": [1e-17, 2]}),
xr.Coordinates({"x": [0, 3]}),
id="Coordinates",
),
),
)
def test_assert_allclose(obj1, obj2) -> None:
with pytest.raises(AssertionError):
xr.testing.assert_allclose(obj1, obj2)
with pytest.raises(AssertionError):
xr.testing.assert_allclose(obj1, obj2, check_dim_order=False)
@pytest.mark.parametrize("func", ["assert_equal", "assert_allclose"])
def test_assert_allclose_equal_transpose(func) -> None:
"""Transposed DataArray raises assertion unless check_dim_order=False."""
obj1 = xr.DataArray([[0, 1, 2], [2, 3, 4]], dims=["a", "b"])
obj2 = xr.DataArray([[0, 2], [1, 3], [2, 4]], dims=["b", "a"])
with pytest.raises(AssertionError):
getattr(xr.testing, func)(obj1, obj2)
getattr(xr.testing, func)(obj1, obj2, check_dim_order=False)
ds1 = obj1.to_dataset(name="varname")
ds1["var2"] = obj1
ds2 = obj1.to_dataset(name="varname")
ds2["var2"] = obj1.transpose()
with pytest.raises(AssertionError):
getattr(xr.testing, func)(ds1, ds2)
getattr(xr.testing, func)(ds1, ds2, check_dim_order=False)
def test_assert_equal_transpose_datatree() -> None:
"""Ensure `check_dim_order=False` works for transposed DataTree"""
ds = xr.Dataset(data_vars={"data": (("x", "y"), [[1, 2]])})
a = xr.DataTree.from_dict({"node": ds})
b = xr.DataTree.from_dict({"node": ds.transpose("y", "x")})
with pytest.raises(AssertionError):
xr.testing.assert_equal(a, b)
xr.testing.assert_equal(a, b, check_dim_order=False)
@pytest.mark.filterwarnings("error")
@pytest.mark.parametrize(
"duckarray",
(
pytest.param(np.array, id="numpy"),
pytest.param(
dask_from_array,
id="dask",
marks=pytest.mark.skipif(not has_dask, reason="requires dask"),
),
pytest.param(
quantity,
id="pint",
marks=pytest.mark.skipif(not has_pint, reason="requires pint"),
),
),
)
@pytest.mark.parametrize(
["obj1", "obj2"],
(
pytest.param([1e-10, 2], [0.0, 2.0], id="both arrays"),
pytest.param([1e-17, 2], 0.0, id="second scalar"),
pytest.param(0.0, [1e-17, 2], id="first scalar"),
),
)
def test_assert_duckarray_equal_failing(duckarray, obj1, obj2) -> None:
# TODO: actually check the repr
a = duckarray(obj1)
b = duckarray(obj2)
with pytest.raises(AssertionError):
xr.testing.assert_duckarray_equal(a, b)
@pytest.mark.filterwarnings("error")
@pytest.mark.parametrize(
"duckarray",
(
pytest.param(
np.array,
id="numpy",
),
pytest.param(
dask_from_array,
id="dask",
marks=pytest.mark.skipif(not has_dask, reason="requires dask"),
),
pytest.param(
quantity,
id="pint",
marks=pytest.mark.skipif(not has_pint, reason="requires pint"),
),
),
)
@pytest.mark.parametrize(
["obj1", "obj2"],
(
pytest.param([0, 2], [0.0, 2.0], id="both arrays"),
pytest.param([0, 0], 0.0, id="second scalar"),
pytest.param(0.0, [0, 0], id="first scalar"),
),
)
def test_assert_duckarray_equal(duckarray, obj1, obj2) -> None:
a = duckarray(obj1)
b = duckarray(obj2)
xr.testing.assert_duckarray_equal(a, b)
@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", stacklevel=2)
return super().dims
def __array__(
self, dtype: np.typing.DTypeLike = None, /, *, copy: bool | None = None
) -> np.ndarray:
warnings.warn("warning in test", stacklevel=2)
return super().__array__(dtype, copy=copy)
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)
assert len(w) > 0
# ensure warnings still raise outside of assert_*
with pytest.raises(UserWarning):
warnings.warn("test", stacklevel=2)
# ensure warnings stay ignored in assert_*
with warnings.catch_warnings(record=True) as w:
# ignore warnings
warnings.filterwarnings("ignore")
with pytest.raises(AssertionError):
getattr(xr.testing, func)(a, b)
assert len(w) == 0
|
