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/4219#issuecomment-670821295,https://api.github.com/repos/pydata/xarray/issues/4219,670821295,MDEyOklzc3VlQ29tbWVudDY3MDgyMTI5NQ==,6815844,2020-08-08T04:18:08Z,2020-08-08T04:18:08Z,MEMBER,"@max-sixty
thanks for the review.
merged","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-670705764,https://api.github.com/repos/pydata/xarray/issues/4219,670705764,MDEyOklzc3VlQ29tbWVudDY3MDcwNTc2NA==,6815844,2020-08-07T20:45:01Z,2020-08-07T20:45:01Z,MEMBER,"Thanks @max-sixty .
You are completely correct.
As the test pass, I was fooling myself.
The reason was that the dataset I was using for the test does not have `time` and `x` simultaneously.
So I was not testing the 2d-rolling but just 1d-rolling.
Fixed. Now it correctly fails for `mean` and `std`, but passes with `max` and `sum`
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-667411555,https://api.github.com/repos/pydata/xarray/issues/4219,667411555,MDEyOklzc3VlQ29tbWVudDY2NzQxMTU1NQ==,6815844,2020-07-31T22:25:25Z,2020-07-31T22:25:25Z,MEMBER,"Thanks @max-sixty for the review ;)
I'll work for the update in a few days.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-666841275,https://api.github.com/repos/pydata/xarray/issues/4219,666841275,MDEyOklzc3VlQ29tbWVudDY2Njg0MTI3NQ==,6815844,2020-07-31T00:42:23Z,2020-07-31T00:42:23Z,MEMBER,Could anyone kindly review this?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-658403527,https://api.github.com/repos/pydata/xarray/issues/4219,658403527,MDEyOklzc3VlQ29tbWVudDY1ODQwMzUyNw==,6815844,2020-07-14T20:44:12Z,2020-07-14T20:44:12Z,MEMBER,"I got an error for typechecking, only in CI but not in local, from the code that I didn't change.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-657902895,https://api.github.com/repos/pydata/xarray/issues/4219,657902895,MDEyOklzc3VlQ29tbWVudDY1NzkwMjg5NQ==,6815844,2020-07-14T00:49:38Z,2020-07-14T00:49:38Z,MEMBER,"A possible improvement will be nan-reduction methods for nd-rolling.
Currently, we just use numpy nan-reductions, which is memory consuming for strided arrays.
This issue can be solved by replacing nan by appropriate values and applying nonnan-reduction methods,
e.g.,
```python
da.rolling(x=2, y=3).construct(x='xw', y='yw').sum(['xw', 'yw'])
```
should be the same with
```python
da.rolling(x=2, y=3).construct(x='xw', y='yw', fill_value=0).sum(['xw', 'yw'], skipna=False)
```
and the latter is much more memory efficient.
I'd like to leave this improvement to future PR.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-657897529,https://api.github.com/repos/pydata/xarray/issues/4219,657897529,MDEyOklzc3VlQ29tbWVudDY1Nzg5NzUyOQ==,6815844,2020-07-14T00:27:51Z,2020-07-14T00:27:51Z,MEMBER,"I think now it is ready for review, though I'm sure tests miss a lot of edge cases.
Maybe we can fix them if pointed out.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-657270068,https://api.github.com/repos/pydata/xarray/issues/4219,657270068,MDEyOklzc3VlQ29tbWVudDY1NzI3MDA2OA==,6815844,2020-07-12T20:18:28Z,2020-07-12T20:18:28Z,MEMBER,"Another API concern. We now use `min_periods`, in which we implicitly assume one-dimension cases.
With nd-dimension, I think `min_counts` argument is more appropriate like bottleneck, which will limit the lower bound of the number of missing entries in the n-dimensional window.
Even if we leave it, we may disallow nd-argument of `min_periods` but keep it a scalar.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649
https://github.com/pydata/xarray/pull/4219#issuecomment-657269189,https://api.github.com/repos/pydata/xarray/issues/4219,657269189,MDEyOklzc3VlQ29tbWVudDY1NzI2OTE4OQ==,6815844,2020-07-12T20:09:34Z,2020-07-12T20:09:34Z,MEMBER,"Hi @max-sixty
> One alternative is to allow fluent args, like:
> ...but does that then seem like the second rolling is operating on the result of the first?
I couldn't think of it until just now. But yes, it sounds to me like a repeated rolling operation.
> I'm being slow, but where is the nd-rolling algo? I had thought bottleneck didn't support more than one dimension?
No. With nd-rolling, we need to use numpy reductions.
Its `skipna=True` operation is currently slow, but it can be improved replacing nan *before* the stride-trick.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649