html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/7707#issuecomment-1555902158,https://api.github.com/repos/pydata/xarray/issues/7707,1555902158,IC_kwDOAMm_X85cvS7O,14808389,2023-05-20T12:32:47Z,2023-05-20T15:26:43Z,MEMBER,"with #7855 and the recent change to `pint` we're finally down to just two test failures (and a whole lot of warnings):
```
xarray/tests/test_dataarray.py::TestDataArray::test_to_and_from_cdms2_sgrid: ValueError: operands could not be broadcast together with shapes (3,) (4,)
xarray/tests/test_ufuncs.py::test_unary: AssertionError: assert ( is or 1.0 == 0.9999999999999999)
```
The first one looks like `cdms2` is incompatible with a change in `numpy>=1.25`. Not sure if we can do anything about that, especially since there's a big warning on the [cdms2 repo](https://github.com/CDAT/cdms) stating that the package is going to be retired / archived by the end of this year... I guess we should start thinking about removing `cdms2` support?
The second looks like a precision issue, which we should be able to resolve by using `assert_allclose` instead... not sure, though, especially given numpy/numpy#23773. Otherwise we could just defer to whatever `numpy` is doing (of course, that assumes that `full_like` works properly, which might not be a good idea for a unit test):
```python
@pytest.mark.parametrize(
""a"",
[
xr.Variable([""x""], [0, 0]),
xr.DataArray([0, 0], dims=""x""),
xr.Dataset({""y"": (""x"", [0, 0])}),
],
)
def test_unary(a):
fill_value = np.cos(0)
expected = xr.full_like(a, fill_value=fill_value, dtype=fill_value.dtype)
actual = np.cos(a)
assert_identical(actual, expected)
```
Edit: if relying on `full_like` turns out to be a concern, maybe we could use ""copy + assign"" instead?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625
https://github.com/pydata/xarray/issues/7707#issuecomment-1537490801,https://api.github.com/repos/pydata/xarray/issues/7707,1537490801,IC_kwDOAMm_X85bpD9x,2443309,2023-05-07T16:50:35Z,2023-05-07T16:50:35Z,MEMBER,See https://github.com/pydata/xarray/pull/7825 for a PR fixing the outstanding Zarr V3 failures.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625
https://github.com/pydata/xarray/issues/7707#issuecomment-1536641744,https://api.github.com/repos/pydata/xarray/issues/7707,1536641744,IC_kwDOAMm_X85bl0rQ,14808389,2023-05-05T18:48:42Z,2023-05-05T18:48:42Z,MEMBER,"`pint<0.21` should work, and I'm looking into how this could be fixed, see hgrecco/pint#1660 and hgrecco/pint#1749. For the latter we might have to mark the ""pint wrapping dask"" test as requiring `pint>=0.21` and make it use an explicit registry.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625
https://github.com/pydata/xarray/issues/7707#issuecomment-1534920140,https://api.github.com/repos/pydata/xarray/issues/7707,1534920140,IC_kwDOAMm_X85bfQXM,14371165,2023-05-04T14:50:01Z,2023-05-04T14:50:01Z,MEMBER,"Lots of pint errors with version 0.21, @keewis. I think pint 0.20.1 worked well?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625
https://github.com/pydata/xarray/issues/7707#issuecomment-1510443977,https://api.github.com/repos/pydata/xarray/issues/7707,1510443977,IC_kwDOAMm_X85aB4vJ,14808389,2023-04-16T17:55:12Z,2023-04-16T17:57:23Z,MEMBER,"flaky segfaults aside, we're down to just the zarr v3 tests, a flaky `cdms2` test, and a test related to `pint` (though that one appears to be an upstream issue – not entirely sure, though).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625
https://github.com/pydata/xarray/issues/7707#issuecomment-1498209121,https://api.github.com/repos/pydata/xarray/issues/7707,1498209121,IC_kwDOAMm_X85ZTNth,6628425,2023-04-05T21:58:06Z,2023-04-06T00:11:46Z,MEMBER,"I think it is fine that `CFTimeIndex.to_datetimeindex()` no longer raises an error for out-of-nanosecond-precision range dates, so we can simply relax that test for pandas versions greater than or equal to 2 and update its docstring.
In practice I don't think this will come up very often (we can address later if we want probably), but one subtle issue there is that prior to October 15th, 1582, the proleptic Gregorian calendar and the ""standard"" calendar are not equivalent, so we may want to update [how we warn when converting between calendars](https://github.com/pydata/xarray/blob/84607c3b1d61e3bc2d4b07b4f12f41a40b027f6f/xarray/coding/cftimeindex.py#L640-L649). The ""standard"" calendar [according to the CF Conventions](https://cfconventions.org/Data/cf-conventions/cf-conventions-1.10/cf-conventions.html#calendar) is a mixed Julian/Gregorian calendar, which uses a Julian calendar prior to 1582-10-15 and a Gregorian calendar after.
In cftime the `DatetimeGregorian` object conforms to this definition, and is what is created if you provide `""standard""` as the `calendar` argument to `num2date`:
```
>>> cftime.num2date([0, 1], units=""days since 1582-10-04"", calendar=""standard"")
array([cftime.DatetimeGregorian(1582, 10, 4, 0, 0, 0, 0, has_year_zero=False),
cftime.DatetimeGregorian(1582, 10, 15, 0, 0, 0, 0, has_year_zero=False)],
dtype=object)
>>> cftime.num2date([0, 1], units=""days since 1582-10-04"", calendar=""proleptic_gregorian"")
array([cftime.DatetimeProlepticGregorian(1582, 10, 4, 0, 0, 0, 0, has_year_zero=True),
cftime.DatetimeProlepticGregorian(1582, 10, 5, 0, 0, 0, 0, has_year_zero=True)],
dtype=object)
```
I'll need to think more about how to handle the `test_should_cftime_be_used_source_outside_range` failure; I'm not sure if we're ready to handle changing the behavior of this until we fully address #7493.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625
https://github.com/pydata/xarray/issues/7707#issuecomment-1496211311,https://api.github.com/repos/pydata/xarray/issues/7707,1496211311,IC_kwDOAMm_X85ZLl9v,14808389,2023-04-04T15:47:28Z,2023-04-04T15:47:28Z,MEMBER,"it seems the tests segfaulted again. Not sure which test exactly is causing that, though.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625
https://github.com/pydata/xarray/issues/7707#issuecomment-1496083800,https://api.github.com/repos/pydata/xarray/issues/7707,1496083800,IC_kwDOAMm_X85ZLG1Y,2448579,2023-04-04T14:34:27Z,2023-04-04T14:34:27Z,MEMBER,"Oh wow, we're down to mostly Zarr failures!
cc @jhamman ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625