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  • `Dataset.where()` incorrectly applies mask and creates new dimensions · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1206374954 https://github.com/pydata/xarray/issues/6879#issuecomment-1206374954 https://api.github.com/repos/pydata/xarray/issues/6879 IC_kwDOAMm_X85H59Iq headtr1ck 43316012 2022-08-05T12:09:59Z 2022-08-05T12:09:59Z COLLABORATOR

What is the use case in enlarging the 1-D array to a 3-D array with coordinates that it didn't have before?

It just follows the normal broadcasting behavior of xarray where any operation that involves two or more Datasets/DataArrays will broadcast all their dimensions.

 
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   `Dataset.where()` incorrectly applies mask and creates new dimensions 1329754426
1206361835 https://github.com/pydata/xarray/issues/6879#issuecomment-1206361835 https://api.github.com/repos/pydata/xarray/issues/6879 IC_kwDOAMm_X85H557r guidocioni 12760310 2022-08-05T11:53:15Z 2022-08-05T11:53:30Z NONE

Thanks for the issue.

I would claim that this is the correct broadcasting behavior.

You could obtain your required result using

python ds_mask = xr.Dataset({"t_2m_min_anom": mask, "t_2m_min_anom_stations": True}) data.where(ds_mask)

Hey, thanks for the workaround. However, I'm still not convinced that this is the "correct" behaviour. If mask has as explicit coodinates lat and lon it should only be applied to variables that have these coordinates.

What is the use case in enlarging the 1-D array to a 3-D array with coordinates that it didn't have before?

 
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   `Dataset.where()` incorrectly applies mask and creates new dimensions 1329754426
1206358216 https://github.com/pydata/xarray/issues/6879#issuecomment-1206358216 https://api.github.com/repos/pydata/xarray/issues/6879 IC_kwDOAMm_X85H55DI headtr1ck 43316012 2022-08-05T11:48:49Z 2022-08-05T11:48:49Z COLLABORATOR

Thanks for the issue.

I would claim that this is the correct broadcasting behavior.

You could obtain your required result using python ds_mask = xr.Dataset({"t_2m_min_anom": mask, "t_2m_min_anom_stations": True}) data.where(ds_mask)

 
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   `Dataset.where()` incorrectly applies mask and creates new dimensions 1329754426

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