Do we need to update AbstractArray for duck arrays?
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Description
What happened?
I'm calling cupy.round on a DataArray wrapping a cupy array and it raises an error here:
https://github.com/pydata/xarray/blob/3f7cc2da33d81e76afbfb82da57143b624b03a88/xarray/core/common.py#L155-L156
Traceback below:
--> 25 a = _core.array(a, copy=False)
26 return a.round(decimals, out=out)
27
cupy/_core/core.pyx in cupy._core.core.array()
cupy/_core/core.pyx in cupy._core.core.array()
cupy/_core/core.pyx in cupy._core.core._array_default()
~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/common.py in __array__(self, dtype)
146
147 def __array__(self: Any, dtype: DTypeLike = None) -> np.ndarray:
--> 148 return np.asarray(self.values, dtype=dtype)
149
150 def __repr__(self) -> str:
~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/dataarray.py in values(self)
644 type does not support coercion like this (e.g. cupy).
645 """
--> 646 return self.variable.values
647
648 @values.setter
~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/variable.py in values(self)
517 def values(self):
518 """The variable's data as a numpy.ndarray"""
--> 519 return _as_array_or_item(self._data)
520
521 @values.setter
~/miniconda3/envs/gpu/lib/python3.7/site-packages/xarray/core/variable.py in _as_array_or_item(data)
257 TODO: remove this (replace with np.asarray) once these issues are fixed
258 """
--> 259 data = np.asarray(data)
260 if data.ndim == 0:
261 if data.dtype.kind == "M":
cupy/_core/core.pyx in cupy._core.core.ndarray.__array__()
TypeError: Implicit conversion to a NumPy array is not allowed. Please use `.get()` to construct a NumPy array explicitly.
What did you expect to happen?
Not an error? I'm not sure what's expected
np.round(dataarray) does actually work successfully.
My question is : Do we need to update AbstractArray.__array__ to return the underlying duck array instead of always a numpy array?
Minimal Complete Verifiable Example
No response
MVCE confirmation
- Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- Complete example — the example is self-contained, including all data and the text of any traceback.
- Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- New issue — a search of GitHub Issues suggests this is not a duplicate.
Relevant log output
No response
Anything else we need to know?
No response
Environment
xarray v2022.6.0
cupy 10.6.0
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start in xarray/core/common.py at the linked array implementation and trace how DataArray values are converted before cupy.round is called. Reproduce the reported cupy and np.round behavior, then determine the expected duck-array conversion semantics and add coverage for the chosen behavior before confirming the existing NumPy path still works.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100