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/issues/3032#issuecomment-503768609,https://api.github.com/repos/pydata/xarray/issues/3032,503768609,MDEyOklzc3VlQ29tbWVudDUwMzc2ODYwOQ==,23738400,2019-06-19T22:23:21Z,2019-06-19T22:23:21Z,CONTRIBUTOR,"@max-sixty Not at all, whatever is best. I actually opened the issue without being 100% it was one.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503747413,https://api.github.com/repos/pydata/xarray/issues/3032,503747413,MDEyOklzc3VlQ29tbWVudDUwMzc0NzQxMw==,5635139,2019-06-19T21:09:18Z,2019-06-19T21:09:18Z,MEMBER,"@shoyer thanks for the clarity
@OriolAbril would you mind if we changed this issue to ""apply_ufunc should preemptively broadcast""","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503746105,https://api.github.com/repos/pydata/xarray/issues/3032,503746105,MDEyOklzc3VlQ29tbWVudDUwMzc0NjEwNQ==,1217238,2019-06-19T21:04:56Z,2019-06-19T21:04:56Z,MEMBER,"With NumPy arrays at least, there is no cost for broadcasting, because it
can always be done with views. But even for other array types, inserting
size 1 dimensions in the correct location should be basically free, and
would be more helpful than what we currently do
On Wed, Jun 19, 2019 at 9:25 PM Oriol Abril <notifications@github.com>
wrote:
> I'm trying to think whether there would be any performance cost there -
> i.e. are there any arrays where preemptive broadcasting would be both
> expensive and unnecessary?
>
> Even if there were a performance cost (compared to the actual behaviour),
> it could be easily avoided by using all dims as input_core_dims couldn't
> it? IIUC, all dims should be broadcasted unless they are in input core
> dims, so it broadcasting could still be avoided without problem.
>
> —
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","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503675891,https://api.github.com/repos/pydata/xarray/issues/3032,503675891,MDEyOklzc3VlQ29tbWVudDUwMzY3NTg5MQ==,23738400,2019-06-19T18:25:14Z,2019-06-19T18:25:14Z,CONTRIBUTOR,"> I'm trying to think whether there would be any performance cost there - i.e. are there any arrays where preemptive broadcasting would be both expensive and unnecessary?
Even if there were a performance cost (compared to the actual behaviour), it could be easily avoided by using all dims as input_core_dims couldn't it? IIUC, all dims should be broadcasted unless they are in input core dims, so it broadcasting could still be avoided without problem.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503652824,https://api.github.com/repos/pydata/xarray/issues/3032,503652824,MDEyOklzc3VlQ29tbWVudDUwMzY1MjgyNA==,5635139,2019-06-19T17:21:34Z,2019-06-19T17:21:34Z,MEMBER,I'm trying to think whether there would be any performance cost there - i.e. are there any arrays where preemptive broadcasting would be both expensive and unnecessary?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503650578,https://api.github.com/repos/pydata/xarray/issues/3032,503650578,MDEyOklzc3VlQ29tbWVudDUwMzY1MDU3OA==,1217238,2019-06-19T17:15:32Z,2019-06-19T17:15:32Z,MEMBER,"Yes, exactly.","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503625092,https://api.github.com/repos/pydata/xarray/issues/3032,503625092,MDEyOklzc3VlQ29tbWVudDUwMzYyNTA5Mg==,5635139,2019-06-19T16:04:58Z,2019-06-19T16:04:58Z,MEMBER,"> We should probably make apply_ufunc() explicitly broadcast arrays first.
To confirm, so that we have something like this?
```python
xr.apply_ufunc(func, a, c)
# Out
# (7, 3, 5, 6)
# (7, 3, 5, 6)
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503618955,https://api.github.com/repos/pydata/xarray/issues/3032,503618955,MDEyOklzc3VlQ29tbWVudDUwMzYxODk1NQ==,1217238,2019-06-19T15:50:03Z,2019-06-19T15:50:03Z,MEMBER,"For what it's worth, I agree that this behavior is a little surprising. We should probably make `apply_ufunc()` explicitly broadcast arrays first.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503337637,https://api.github.com/repos/pydata/xarray/issues/3032,503337637,MDEyOklzc3VlQ29tbWVudDUwMzMzNzYzNw==,5635139,2019-06-18T22:37:42Z,2019-06-18T22:42:14Z,MEMBER,"Because `func` receives unlabelled arrays, `apply_ufunc` aligns the axes _order_. So if they share a dimension:
```python
In [8]: import xarray as xr
...: import numpy as np
...:
...: a = xr.DataArray(data=np.random.normal(size=(7, 3)), dims=[""dim1"", ""dim2""])
...: c = xr.DataArray(data=np.random.normal(size=(7, 6)), dims=[""dim1"", ""dim4""]) # <- change here
...:
...: def func(x,y):
...: print(x.shape)
...: print(y.shape)
...: return x
...:
In [9]: xr.apply_ufunc(func, a, c)
(7, 3, 1)
(7, 1, 6)
```
...otherwise `func` wouldn't know how to align.
Another option would be for your original example to put lengths of 1 in _all_ axes, rather than only 'forward filling', e.g.
```
xr.apply_ufunc(func, a, c)
# Out
# (7, 3, 1, 1)
# (1, 1, 5, 6) # <- change here
```
I _think_ it operates without that step because functions 'in the wild' generally will handle that themselves, but that's a guess and needs someone who knows this better to weight in","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503335417,https://api.github.com/repos/pydata/xarray/issues/3032,503335417,MDEyOklzc3VlQ29tbWVudDUwMzMzNTQxNw==,23738400,2019-06-18T22:28:20Z,2019-06-18T22:28:20Z,CONTRIBUTOR,Then shouldn't `a` in the first example keep its original shape?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471
https://github.com/pydata/xarray/issues/3032#issuecomment-503334445,https://api.github.com/repos/pydata/xarray/issues/3032,503334445,MDEyOklzc3VlQ29tbWVudDUwMzMzNDQ0NQ==,5635139,2019-06-18T22:24:16Z,2019-06-18T22:24:16Z,MEMBER,"Thanks for the issue & code sample @OriolAbril
IIUC, `func` needs to do this broadcasting itself; from the `apply_ufunc` docstring:
```
func : callable
Function to call like ``func(*args, **kwargs)`` on unlabeled arrays
(``.data``) that returns an array or tuple of arrays. If multiple
arguments with non-matching dimensions are supplied, this function is
expected to vectorize (broadcast) over axes of positional arguments in
the style of NumPy universal functions [1]_ (if this is not the case,
set ``vectorize=True``). If this function returns multiple outputs, you
must set ``output_core_dims`` as well.
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,457716471