issue_comments: 662547659

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https://github.com/pydata/xarray/issues/3245#issuecomment-662547659 https://api.github.com/repos/pydata/xarray/issues/3245 662547659 MDEyOklzc3VlQ29tbWVudDY2MjU0NzY1OQ== 2448579 2020-07-22T16:17:02Z 2020-07-22T16:17:02Z MEMBER

It seems like general consensus was (please correct me if any of this is wrong):

  1. .values will return np.asarray(obj.data) and respect the underlying library's choices: this will raise an error with cupy and that's OK.
  2. .plot() is a special case and should always coerce to numpy before passing data to matplotlib. plot currently uses .values so we should add a new function that always returns xarray objects with numpy arrays (with cupy as special case) and use that in plot.
  3. for now we are OK with special as_sparse, as_cupy, as_pint methods in xarray as long as all that logic is contained in one place: as_duck_array.py?
 
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