issues: 936305081

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936305081 MDU6SXNzdWU5MzYzMDUwODE= 5570 assert_equal does not handle wrapped duck arrays well 35968931 open 0     0 2021-07-03T18:27:11Z 2021-07-03T18:49:57Z   MEMBER      

Whilst trying to fix #5559 I noticed that xarray.testing.assert_equal (and xarray.testing.assert_equal) don't behave well with wrapped duck-typed arrays.

Firstly, they can give unhelpful AssertionError messages:

```python In [5]: a = np.array([1,2,3])

In [6]: q = pint.Quantity([1,2,3], units='m')

In [7]: da_np = xr.DataArray(a, dims='x')

In [8]: da_p = xr.DataArray(q, dims='x')

In [9]: da_np Out[9]: <xarray.DataArray (x: 3)> array([1, 2, 3]) Dimensions without coordinates: x

In [10]: da_p Out[10]: <xarray.DataArray (x: 3)> <Quantity([1 2 3], 'meter')> Dimensions without coordinates: x

In [11]: from xarray.testing import assert_equal

In [12]: assert_equal(da_np, da_p) /home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/xarray/core/duck_array_ops.py:265: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2)) /home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/xarray/core/duck_array_ops.py:265: DeprecationWarning: elementwise comparison failed; this will raise an error in the future. flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2)) /home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/xarray/core/duck_array_ops.py:265: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2)) /home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/xarray/core/duck_array_ops.py:265: DeprecationWarning: elementwise comparison failed; this will raise an error in the future. flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2)) /home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/numpy/core/_asarray.py:102: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray. return array(a, dtype, copy=False, order=order)

AssertionError Traceback (most recent call last) <ipython-input-12-33b16d6b79ed> in <module> ----> 1 assert_equal(da_np, da_p)

[... skipping hidden 1 frame]

~/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/xarray/testing.py in assert_equal(a, b) 79 assert type(a) == type(b) 80 if isinstance(a, (Variable, DataArray)): ---> 81 assert a.equals(b), formatting.diff_array_repr(a, b, "equals") 82 elif isinstance(a, Dataset): 83 assert a.equals(b), formatting.diff_dataset_repr(a, b, "equals")

AssertionError: Left and right DataArray objects are not equal

Differing values: L array([1, 2, 3]) R array([1, 2, 3]) `` These are different, but not because the array values are different. At the moment.valuesis converting the wrapped array type by stripping the units too - it might be better to check the type of the wrapped array first, then use.valuesto compare. Or could we even do duck-typed testing by delegating viaexpected.data.equals(actual.data)? (EDIT: I don't think a.equals()method exists in the numpy API, but you could do the equivalent ofassert all(expected.data == actual.data)`

Secondly, given that we coerce before comparison, I think it's possible that assert_equal could say two different wrapped duck-type arrays are equal when they are not, just because np.asarray() coerces them to the same values.

EDIT2: Looks like there is some discussion here

 
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