issue_comments: 514452182

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https://github.com/pydata/xarray/issues/525#issuecomment-514452182 https://api.github.com/repos/pydata/xarray/issues/525 514452182 MDEyOklzc3VlQ29tbWVudDUxNDQ1MjE4Mg== 3460034 2019-07-24T02:19:08Z 2019-07-24T02:19:08Z CONTRIBUTOR

In light of the recent activity with __array_function__ in #3117, I took a quick look to see if it worked with Pint as modified in https://github.com/hgrecco/pint/pull/764. The basics of sticking a Pint Quantity in a DataArray seem to work well, and the perhaps the greatest issues are on Pint's end...right now https://github.com/hgrecco/pint/pull/764 is limited in the functions it handles through __array_function__, and there are some quirks with operator precedence.

However, the other main problem was that coordinates did not work with Quantity's. Looking again at https://github.com/pydata/xarray/issues/1938#issuecomment-510953379 and #2956, this is not surprising. I'm curious though about what it would take to let indexing work with Pint (or other unit arrays)? For most of my use cases (meteorological analysis as in MetPy), having units with coordinates is just as important as having units with the data itself. I'd be interested in helping implement it, but I would greatly appreciate some initial direction, since I'm new to that part of the xarray codebase.

Also, cc @keewis, since I saw in #2956 you have a unit-support branch that looks like it attempts to extend NumpyIndexingAdapter to work with unit arrays, but still has the coordinates-with-units tests marked as xfail.

 
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