def _check_field(
cls,
xr_dataset: xr.Dataset,
field_spec: Spec,
field: Hashable,
add_comment_attr: bool = False,
) -> None:
from sgkit.utils import check_array_like
assert isinstance(
field_spec, ArrayLikeSpec
), "ArrayLikeSpec is the only currently supported variable spec"
try:
arr = xr_dataset[field]
try:
check_array_like(arr,
kind=field_spec.kind,
ndim=field_spec.ndim)
if add_comment_attr and field_spec.__doc__ is not None:
arr.attrs["comment"] = field_spec.__doc__.strip()
except (TypeError, ValueError) as e:
raise ValueError(
f"{field} does not match the spec, see the error above for more detail"
) from e
except KeyError:
raise ValueError(f"{field} not present in {xr_dataset}")
def _check_field(cls, xr_dataset: xr.Dataset, field_spec: Spec,
field: Hashable) -> None:
from sgkit.utils import check_array_like
assert isinstance(
field_spec, ArrayLikeSpec
), "ArrayLikeSpec is the only currently supported variable spec"
if field not in xr_dataset:
raise ValueError(f"{field} not present in {xr_dataset}")
try:
check_array_like(xr_dataset[field],
kind=field_spec.kind,
ndim=field_spec.ndim)
except (TypeError, ValueError) as e:
raise ValueError(
f"{field} does not match the spec, see the error above for more detail"
) from e
def test_check_array_like():
with pytest.raises(TypeError,
match=r"Not an array. Missing attribute 'ndim'"):
check_array_like("foo")
a = np.arange(100, dtype="i4")
with pytest.raises(TypeError,
match=r"Array dtype \(int32\) does not match int64"):
check_array_like(a, dtype="i8")
with pytest.raises(
TypeError,
match=
r"Array dtype \(int32\) does not match one of (\{dtype\('int8'\), dtype\('int16'\)\}|\{dtype\('int16'\), dtype\('int8'\)\})",
):
check_array_like(a, dtype={"i1", "i2"})
with pytest.raises(TypeError,
match=r"Array dtype kind \(i\) does not match f"):
check_array_like(a, kind="f")
with pytest.raises(
TypeError,
match=
r"Array dtype kind \(i\) does not match one of (\{'f', 'S'\}|\{'S', 'f'\})",
):
check_array_like(a, kind={"f", "S"})
with pytest.raises(ValueError,
match=r"Number of dimensions \(1\) does not match 2"):
check_array_like(a, ndim=2)
with pytest.raises(
ValueError,
match=
r"Number of dimensions \(1\) does not match one of (\{2, 3\}|\{3, 2\})",
):
check_array_like(a, ndim={2, 3})
def test_check_array_like():
with pytest.raises(TypeError):
check_array_like("foo")
a = np.arange(100, dtype="i4")
with pytest.raises(TypeError):
check_array_like(a, dtype="i8")
with pytest.raises(TypeError):
check_array_like(a, dtype={"i1", "i2"})
with pytest.raises(TypeError):
check_array_like(a, kind="f")
with pytest.raises(ValueError):
check_array_like(a, ndim=2)
with pytest.raises(ValueError):
check_array_like(a, ndim={2, 3})