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  • rabernat · 1 ✖

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  • New function for applying vectorized functions for unlabeled arrays to xarray objects · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
248938413 https://github.com/pydata/xarray/pull/964#issuecomment-248938413 https://api.github.com/repos/pydata/xarray/issues/964 MDEyOklzc3VlQ29tbWVudDI0ODkzODQxMw== rabernat 1197350 2016-09-22T15:30:35Z 2016-09-22T15:30:35Z MEMBER

Of course I think this is a fantastic feature which will change the way use use xarray.

I gave it a test run for a problem we come across a lot on the mailing list: estimating a linear trend along one dimension of a dataarray. A short example notebook is here: https://gist.github.com/rabernat/a0ec6a7e947f2d928615a30f5cb91ee9

Overall it worked as I hoped, but there were a few bumps I had to overcome. My feedback is from a user perspective, regarding the api and documentation - In the documentation, I would not assume that the user is familiar with Numpy generalized universal functions. A more explicit explanation of the syntax and meaning of the signature in the docstring would be very helpful. It took me lots of trial an error to find the signature that worked. - The function I wanted to apply, np.polyfit, works on the first axis of the array, not the last. This required an extra swap-axis step inside a wrapper function. - This would not work if the data ndim were > 2, because np.polyfit expects a 2D array. So an additional stacking step would also be required.

Perhaps I am not using this as designed, but this was the most obvious example application I could think of.

 
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   New function for applying vectorized functions for unlabeled arrays to xarray objects 170779798

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