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/pull/4760#issuecomment-945825537,https://api.github.com/repos/pydata/xarray/issues/4760,945825537,IC_kwDOAMm_X844YCcB,10194086,2021-10-18T14:21:56Z,2021-10-18T14:21:56Z,MEMBER,"I closed the PR by accident but I think I'll keep it closed, unless there is interest to get this in. Testing dtypes could be an interesting option, however,

- there are O(1000) tests that do not preserve dtype - so this would be an enormous cleanup required if we ever seriously wanted to do this
- some elements cannot preserve dtypes (str types in pandas index (not sure what the index refactor does here) and [empty str arrays](https://github.com/pydata/xarray/blob/07de257c5884df49335496ee6347fb633a7c302c/xarray/tests/test_accessor_str.py#L1571))","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594
https://github.com/pydata/xarray/pull/4760#issuecomment-774112777,https://api.github.com/repos/pydata/xarray/issues/4760,774112777,MDEyOklzc3VlQ29tbWVudDc3NDExMjc3Nw==,10194086,2021-02-05T15:44:58Z,2021-02-05T16:14:22Z,MEMBER,"True, but for the problem that the diff repr is not shown I think it makes sense to go for this, e.g. the following works fine:

```python
def test_x():

    data_array1 = xr.DataArray(data=1 * unit_registry.m)
    data_array2 = xr.DataArray(data=2 * unit_registry.m)

    with warnings.catch_warnings():
        warnings.simplefilter(""always"")

        xr.testing.assert_allclose(data_array1, data_array2)
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594
https://github.com/pydata/xarray/pull/4760#issuecomment-774106999,https://api.github.com/repos/pydata/xarray/issues/4760,774106999,MDEyOklzc3VlQ29tbWVudDc3NDEwNjk5OQ==,14808389,2021-02-05T15:35:18Z,2021-02-05T16:00:17Z,MEMBER,"to really fix this we need some way to say ""I really want to convert to a `numpy.ndarray`"" (unfortunately, `np.asarray` seems to be commonly used as ""ensure that this is a `numpy.ndarray`""). That's the same issue as with `cupy.Array`, which will raise in `__array__`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594
https://github.com/pydata/xarray/pull/4760#issuecomment-774115528,https://api.github.com/repos/pydata/xarray/issues/4760,774115528,MDEyOklzc3VlQ29tbWVudDc3NDExNTUyOA==,14808389,2021-02-05T15:49:32Z,2021-02-05T15:59:52Z,MEMBER,"yes, I agree that it makes sense to set warnings to `""always""` in the `assert_*` functions.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594
https://github.com/pydata/xarray/pull/4760#issuecomment-774101639,https://api.github.com/repos/pydata/xarray/issues/4760,774101639,MDEyOklzc3VlQ29tbWVudDc3NDEwMTYzOQ==,10194086,2021-02-05T15:27:27Z,2021-02-05T15:27:27Z,MEMBER,"Thanks! That drove me nuts but I finally figured out the problem:

https://github.com/pydata/xarray/blob/5735e163bea43ec9bc3c2e640fbf25a1d4a9d0c0/xarray/tests/test_units.py#L29

promotes the warning to an error so `diff_array_repr` fails (because the units are stripped...) and that is what we see. That also fails on master - run the following in with pytest:

```python
import pint
import pytest
import xarray as xr

pytestmark = [
    pytest.mark.filterwarnings(""error::pint.UnitStrippedWarning""),
]

unit_registry = pint.UnitRegistry(force_ndarray=True)


def test_y():

    data_array1 = xr.DataArray(data=1 * unit_registry.m)
    data_array2 = xr.DataArray(data=2 * unit_registry.m)

    xr.testing.assert_allclose(data_array1, data_array2)
```

@keewis do you have an idea how to fix this? One idea is to supress warnings in `diff_array_repr` and `diff_dataset_repr`. Do we need to strip the units before sending them to these functions?



","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594
https://github.com/pydata/xarray/pull/4760#issuecomment-774024142,https://api.github.com/repos/pydata/xarray/issues/4760,774024142,MDEyOklzc3VlQ29tbWVudDc3NDAyNDE0Mg==,14808389,2021-02-05T13:10:27Z,2021-02-05T14:14:20Z,MEMBER,"the difference is that the unit registry has `force_ndarray_like` enabled. This is important because a `pint.Quantity` wrapping a python scalar is not a duck array, so the unit gets stripped.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594
https://github.com/pydata/xarray/pull/4760#issuecomment-774001075,https://api.github.com/repos/pydata/xarray/issues/4760,774001075,MDEyOklzc3VlQ29tbWVudDc3NDAwMTA3NQ==,10194086,2021-02-05T12:22:41Z,2021-02-05T12:22:41Z,MEMBER,"@keewis The following test is giving me trouble: `pytest xarray/tests/test_units.py::test_align_dataarray[int64-10-data-compatible_unit]`

https://github.com/pydata/xarray/blob/5735e163bea43ec9bc3c2e640fbf25a1d4a9d0c0/xarray/tests/test_units.py#L461

I now try to reproduce what it does but I cannot even manage that... I think the following is what the test does but it fails with `DimensionalityError: Cannot convert from 'dimensionless' to 'meter'` - can you see what I do wrong/ different from the test?

```python
import numpy as np
import pint
import xarray as xr

unit_registry = pint.UnitRegistry()

dtype = np.int64

data_unit1 = unit_registry.m
data_unit2 = unit_registry.mm

array1 = np.linspace(0, 10, 2 * 5).reshape(2, 5).astype(dtype)
array2 = np.linspace(0, 8, 2 * 5).reshape(2, 5).astype(dtype)

x = np.arange(2) # * dim_unit1
y1 = np.arange(5) # * dim_unit1
y2 = np.arange(2, 7) # * dim_unit2

u1 = np.array([3, 5, 7, 8, 9]) # * coord_unit1
u2 = np.array([7, 8, 9, 11, 13])  # * coord_unit2

coords1 = {""x"": x, ""y"": y1}
coords2 = {""x"": x, ""y"": y2}

data_array1 = xr.DataArray(data=array1 * data_unit1, coords=coords1, dims=(""x"", ""y""))
data_array2 = xr.DataArray(data=array2 * data_unit2, coords=coords2, dims=(""x"", ""y""))

fill_value = 10

actual_a, actual_b = xr.align(data_array1, data_array2, join=""outer"", fill_value=fill_value * data_unit1)

```


---

The underlying problem is that when I run this test with `check_dtype=True` it raises an error (which is fine) but instead of a nice `diff_repr` it elevates the `UnitStrippedWarning` to an error and I have not the slightest clue why... 

<details>

```python-traceback

>       assert_allclose(expected_b, actual_b)

/home/mathause/code/xarray/xarray/tests/test_units.py:542: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/home/mathause/code/xarray/xarray/tests/__init__.py:208: in assert_allclose
    xarray.testing.assert_allclose(a, b, check_dtype=check_dtype, **kwargs)
/home/mathause/code/xarray/xarray/testing.py:178: in assert_allclose
    assert allclose, formatting.diff_array_repr(
/home/mathause/code/xarray/xarray/core/formatting.py:667: in diff_array_repr
    if not equiv(a, b, check_dtype=check_dtype):
/home/mathause/code/xarray/xarray/testing.py:40: in _data_allclose_or_equiv
    return duck_array_ops.allclose_or_equiv(
/home/mathause/code/xarray/xarray/core/duck_array_ops.py:249: in allclose_or_equiv
    arr1 = asarray(arr1)
/home/mathause/code/xarray/xarray/core/duck_array_ops.py:184: in asarray
    return data if is_duck_array(data) else xp.asarray(data)
/home/mathause/conda/envs/xarray_dev/lib/python3.8/site-packages/numpy/core/_asarray.py:102: in asarray
    return array(a, dtype, copy=False, order=order)
/home/mathause/code/xarray/xarray/core/common.py:139: in __array__
    return np.asarray(self.values, dtype=dtype)
/home/mathause/code/xarray/xarray/core/dataarray.py:634: in values
    return self.variable.values
/home/mathause/code/xarray/xarray/core/variable.py:544: in values
    return _as_array_or_item(self._data)
/home/mathause/code/xarray/xarray/core/variable.py:276: in _as_array_or_item
    data = np.asarray(data)
/home/mathause/conda/envs/xarray_dev/lib/python3.8/site-packages/numpy/core/_asarray.py:102: in asarray
    return array(a, dtype, copy=False, order=order)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <Quantity([[10. 10.  0.  0.  1.  2.  3.]
 [10. 10.  4.  5.  6.  7.  8.]], 'millimeter')>, t = None

    def __array__(self, t=None):
>       warnings.warn(
            ""The unit of the quantity is stripped when downcasting to ndarray."",
            UnitStrippedWarning,
            stacklevel=2,
        )
E       pint.errors.UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.

/home/mathause/conda/envs/xarray_dev/lib/python3.8/site-packages/pint/quantity.py:1683: UnitStrippedWarning
```
</details>







","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594
https://github.com/pydata/xarray/pull/4760#issuecomment-754142883,https://api.github.com/repos/pydata/xarray/issues/4760,754142883,MDEyOklzc3VlQ29tbWVudDc1NDE0Mjg4Mw==,2448579,2021-01-04T18:36:52Z,2021-01-04T18:36:52Z,MEMBER,"> sometimes dask can get the dtype wrong before the compute (see below)

I suspect this is only for object arrays since you need not get back an object array? Maybe check in `lazy_array_equiv` only if all dtypes are not `object`","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,778069594