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  • argmin / argmax behavior doesn't match documentation · 2 ✖

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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
571137508 https://github.com/pydata/xarray/issues/1388#issuecomment-571137508 https://api.github.com/repos/pydata/xarray/issues/1388 MDEyOklzc3VlQ29tbWVudDU3MTEzNzUwOA== stale[bot] 26384082 2020-01-06T13:26:42Z 2020-01-06T13:26:42Z NONE

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  argmin / argmax behavior doesn't match documentation 224878728
298253809 https://github.com/pydata/xarray/issues/1388#issuecomment-298253809 https://api.github.com/repos/pydata/xarray/issues/1388 MDEyOklzc3VlQ29tbWVudDI5ODI1MzgwOQ== lamorton 23484003 2017-04-30T20:08:25Z 2017-04-30T20:08:25Z NONE

Well, xarray at least agrees with numpy's implementation of that function, but that's not to say it is 'correct.' It would be nice if numpy.argmin worked intuitively. That aside, it seems to me that applying min() to a xr.DataArray should return a reduced array with length 1 in each dimension; then you could just query this object and find the coordinate/dimension values. Perhaps then argmin() would just get a tuple of axis indices, such that arr[*arr.argmin()] == arr.min() would hold.

The next question is, what happens if you start supplying coordinate/dimension optional arguments to argmin? It doesn't make sense to minimize over a coordinate, so only dimensions should be accepted. This should result in a tuple of lists, the way numpy.where does.

Does that seem reasonable?

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  argmin / argmax behavior doesn't match documentation 224878728

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