issue_comments: 276235524

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https://github.com/pydata/xarray/issues/60#issuecomment-276235524 https://api.github.com/repos/pydata/xarray/issues/60 276235524 MDEyOklzc3VlQ29tbWVudDI3NjIzNTUyNA== 1217238 2017-01-31T00:21:35Z 2017-01-31T00:21:35Z MEMBER

take is numpy function that only handles scalar or 1d arguments: https://docs.scipy.org/doc/numpy/reference/generated/numpy.take.html#numpy.take

I just merged #1237 -- see if it works with that.

multiple maxes is presumably fine as long as user is aware it just takes the first.

Yeah, that's not a problem here, only for the where based implementation.

However, nanargmax is probably the actual desired function here, but looks like it will raise on all-nan slices. Would dropping these and then re-aligning be too much overhead?

This behavior for nanargmax is unfortunate. The "right" behavior for xarray is probably to use NaN or NaT to mark the index in such locations but numpy makes this tricky. I think this could be achieved, though, with some mix of where, isnull and other vectorized operations. Basically you need to replace all NaN slices with some placeholder value before calculating nanargmax, and then use the locations of all NaN slices again to replace the results of nanargmax with the appropriate fill value.

 
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