issue_comments: 282968309

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https://github.com/pydata/xarray/issues/1288#issuecomment-282968309 https://api.github.com/repos/pydata/xarray/issues/1288 282968309 MDEyOklzc3VlQ29tbWVudDI4Mjk2ODMwOQ== 1217238 2017-02-28T07:55:14Z 2017-02-28T08:09:23Z MEMBER

I agree that the API should mostly copy the mean/sum reduce methods (and in fact the implementation could probably share much of the logic). But there's still a question of whether the API should expose multiple methods like DataArray.trapz/DataArray.simps or a single method like DataArray.integrate (with method='simps'/method='trapz').

As long as there isn't something else we'd want to reserve the name for, I like the sound of integrate a little better, because it's more self-descriptive. trapz is only obvious if you know the name of the NumPy method. In contrast, integrate is the obvious way to approximate an integral. I would only hold off on using integrate if there is different functionality that comes to mind with the same.

It looks like SciPy implements Simpson's rule with the same API (see scipy.integrate.simps), so that would be easy to support, too. Given how prevalent SciPy is these days, I would have no compunctions about making scipy required for this method and defaulting to method='simps' for DataArray.integrate.

It would be useful to have dask.array versions of these functions, too, but that's not essential for a first pass. The implementation of trapz is very simple, so this would be quite easy to add to dask.

CC @spencerahill @rabernat @lesommer in case any of you have opinions about this

 
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