issues: 1150251120

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1150251120 I_kwDOAMm_X85Ej3Bw 6304 add join argument to xr.broadcast? 10194086 open 0     1 2022-02-25T09:52:14Z 2022-02-25T21:50:16Z   MEMBER      

Is your feature request related to a problem?

xr.broadcast always does an outer join:

https://github.com/pydata/xarray/blob/de965f342e1c9c5de92ab135fbc4062e21e72453/xarray/core/alignment.py#L702

https://github.com/pydata/xarray/blob/de965f342e1c9c5de92ab135fbc4062e21e72453/xarray/core/alignment.py#L768

This is not how the (default) broadcasting (arithmetic join) works, e.g. the following first does an inner join and then broadcasts:

```python import xarray as xr

da1 = xr.DataArray([[0, 1, 2]], dims=("y", "x"), coords={"x": [0, 1, 2]}) da2 = xr.DataArray([0, 1, 2, 3, 4], dims="x", coords={"x": [0, 1, 2, 3, 4]}) da1 + da2 ```

<xarray.DataArray (y: 1, x: 3)> array([[0, 2, 4]]) Coordinates: * x (x) int64 0 1 2 Dimensions without coordinates: y

Describe the solution you'd like

Add a join argument to xr.broadcast. I would propose to leave the default as is

python def broadcast(*args, exclude=None, join="outer"): args = align(*args, join=join, copy=False, exclude=exclude)

Describe alternatives you've considered

  • We could make broadcast respect options -> arithmetic_join but that would be a breaking change and I am not sure how the deprecation should/ would be handled...
  • We could leave it as is.

Additional context

  • xr.broadcast should not be used often because this is should happen automatically in most cases
  • in #6059 I use broadcast because I couldn't get it to work otherwise (maybe there is a better way?). However, the "outer elements" are immediately discarded again - so it's kind of pointless to do an outer join.

```python import numpy as np import xarray as xr

da = xr.DataArray(np.arange(6).reshape(3, 2), coords={"dim_0": [0, 1, 2]}) w = xr.DataArray([1, 1, 1, 1, 1, 1], coords={"dim_0": [0, 1, 2, 4, 5, 6]}) da.weighted(w).quantile(0.5) ```

 
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     13221727 issue

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