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  • AlxLhrNc · 1 ✖

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  • Rolling.argmin() and Rolling.argmax() over multiple dimensions does not work · 1 ✖

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  • NONE · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1158434252 https://github.com/pydata/xarray/issues/6691#issuecomment-1158434252 https://api.github.com/repos/pydata/xarray/issues/6691 IC_kwDOAMm_X85FDE3M AlxLhrNc 90059220 2022-06-17T02:54:27Z 2022-06-17T02:54:27Z NONE

Thank you for upgrading this question. Using keewis suggestion:

We could try to work around this by wrapping argmin and argmax in a function that ravels / unravels the reduce dimensions.

I had a look into numpy documentation and came up with a work around like so: ```python import numpy as np, xarray as xr

arr = xr.DataArray(np.ones((5,6,7))) arr[1,3,2], arr[3,1,4] = 0, 2

print('Values:',arr.min(), arr.max())

min_pos = np.concatenate(np.where(arr == arr.min())) max_pos = np.concatenate(np.where(arr == arr.max())) print('Indexes on nD:', min_pos, max_pos) ``` It is not perfect I suppose but it is doing the job for now.

 
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   Rolling.argmin() and Rolling.argmax() over multiple dimensions does not work 1268821199

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