issue_comments: 565608876

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https://github.com/pydata/xarray/issues/3349#issuecomment-565608876 https://api.github.com/repos/pydata/xarray/issues/3349 565608876 MDEyOklzc3VlQ29tbWVudDU2NTYwODg3Ng== 81219 2019-12-13T21:07:39Z 2019-12-13T21:07:39Z CONTRIBUTOR

My current implementation is pretty naive. It's just calling numpy.polyfit using dask.array.apply_along_axis. Happy to put that in a PR as a starting point, but there are a couple of questions I had: * How to return the full output (residuals, rank, singular_values, rcond) ? A tuple of dataarrays or a dataset ? * Do we want to use the dask least square functionality to allow for chunking within the x dimension ? Then it's not just a simple wrapper around polyfit. * Should we use np.polyfit or np.polynomial.polynomial.polyfit ?

 
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