html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/7152#issuecomment-1287253517,https://api.github.com/repos/pydata/xarray/issues/7152,1287253517,IC_kwDOAMm_X85Mue4N,2448579,2022-10-21T17:35:03Z,2022-10-21T17:35:03Z,MEMBER,"> o you think it would be better to finish this PR as the creation of _aggregations.py to give the cum methods better documentation? Then start a new one to fix https://github.com/pydata/xarray/issues/6528?
Sure that would be a good intermediate step. Let us know if you need help.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1403614394
https://github.com/pydata/xarray/pull/7152#issuecomment-1287138940,https://api.github.com/repos/pydata/xarray/issues/7152,1287138940,IC_kwDOAMm_X85MuC58,2448579,2022-10-21T15:42:12Z,2022-10-21T15:42:12Z,MEMBER,"Thanks for taking this on @patrick-naylor ! This is a decent-sized project!
> Using apply_ufunc and np.cumsum/cumprod has some issues as it only finds the cumulative across one axis which makes iterating through each dimension necessary.
`np.cumsum` only supports an integer axis so this is OK?
`flox` doesn't support `cumsum` at the moment (https://github.com/xarray-contrib/flox/issues/91) so we can delete that bit and just have one code path.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1403614394
https://github.com/pydata/xarray/pull/7152#issuecomment-1275131950,https://api.github.com/repos/pydata/xarray/issues/7152,1275131950,IC_kwDOAMm_X85MAPgu,2448579,2022-10-11T18:51:26Z,2022-10-11T18:51:26Z,MEMBER,"> Is there a particular reason why there is no cumprod for GroupBy objects?
Nope. Just wasn't added in :)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1403614394
https://github.com/pydata/xarray/pull/7152#issuecomment-1274963421,https://api.github.com/repos/pydata/xarray/issues/7152,1274963421,IC_kwDOAMm_X85L_mXd,2448579,2022-10-11T16:27:15Z,2022-10-11T16:30:32Z,MEMBER,"Thanks @patrick-naylor !
Instead of using `Dataset.reduce` I think we want something like
``` python
def cumsum(..., dim):
return xr.apply_ufunc(
np.cumsum if skipna else np.nancumsum,
obj,
input_core_dims=[dim],
output_core_dims=[dim],
kwargs={""axis"": -1},
)
# now transpose dimensions back to input order
```
to fix #6528.
At the moment, this should also work on GroupBy objects quite nicely.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1403614394