issue_comments: 233472927

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https://github.com/pydata/xarray/issues/900#issuecomment-233472927 https://api.github.com/repos/pydata/xarray/issues/900 233472927 MDEyOklzc3VlQ29tbWVudDIzMzQ3MjkyNw== 1217238 2016-07-18T22:03:16Z 2016-07-18T22:03:16Z MEMBER

If you write a function that can take an xarray.Dataset as input, you can still use groupby and apply. So generally the pattern I would use is:

obs = obs.reindex_like(fcst) # possibly using tolerance if the grid isn't exactly the same combined = xarray.Dataset({'obs': obs, 'fcst': fcst}) combined.groupby('time').apply(calculate_skill)

It's hard to answer in more specifics without seeing your code/data, though.

If you need to do time shifts between reference time and (actual) time, it's pretty straightforward with xarray (we had some custom code to do that at my last job) but it isn't a one-liner.

 
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