/
test_testing.py
164 lines (138 loc) · 4.14 KB
/
test_testing.py
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import warnings
import numpy as np
import pytest
import xarray as xr
from . import has_dask
try:
from dask.array import from_array as dask_from_array
except ImportError:
dask_from_array = lambda x: x
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",
),
),
)
def test_assert_allclose(obj1, obj2) -> None:
with pytest.raises(AssertionError):
xr.testing.assert_allclose(obj1, obj2)
@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")
return super().dims
def __array__(self):
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)
assert len(w) > 0