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  • `where` grows new dimensions for unrelated variables · 2 ✖

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457209817 https://github.com/pydata/xarray/issues/1234#issuecomment-457209817 https://api.github.com/repos/pydata/xarray/issues/1234 MDEyOklzc3VlQ29tbWVudDQ1NzIwOTgxNw== max-sixty 5635139 2019-01-24T14:11:12Z 2019-01-24T15:38:36Z MEMBER

Alternatively, we might simply skip variables in Dataset.where if they don't have overlapping dimensions. The logic gets a good deal more complex, though. Currently where is a thin wrapper around np.where.

Would skipping variables without the dimension be preferable? Or do people expect the broadcast?

We recently had a discussion re skipping variables that don't have the dimension supplied using .reduce, although that was for a clearer example, where broadcasting would be less relevant - e.g. rolling along a dimension

 
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   `where` grows new dimensions for unrelated variables 203630267
275721597 https://github.com/pydata/xarray/issues/1234#issuecomment-275721597 https://api.github.com/repos/pydata/xarray/issues/1234 MDEyOklzc3VlQ29tbWVudDI3NTcyMTU5Nw== shoyer 1217238 2017-01-27T17:23:03Z 2017-01-27T17:23:03Z MEMBER

You're not the first person to be confused about this (see https://github.com/pydata/xarray/issues/1217). This is indeed working as expected, though maybe not in the most useful way.

where works by broadcasting its arguments, and when ds.c (along the a dimension) gets broadcasted with ds.y (along the b dimension), the result gets the union of both dimensions.

Alternatively, we might simply skip variables in Dataset.where if they don't have overlapping dimensions. The logic gets a good deal more complex, though. Currently where is a thin wrapper around np.where.

 
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   `where` grows new dimensions for unrelated variables 203630267

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