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-670819822,https://api.github.com/repos/pydata/xarray/issues/4219,670819822,MDEyOklzc3VlQ29tbWVudDY3MDgxOTgyMg==,5635139,2020-08-08T04:02:09Z,2020-08-08T04:02:09Z,MEMBER,"Great! Thanks @fujiisoup !
Ready to go from my POV ","{""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-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-670625085,https://api.github.com/repos/pydata/xarray/issues/4219,670625085,MDEyOklzc3VlQ29tbWVudDY3MDYyNTA4NQ==,2448579,2020-08-07T17:26:06Z,2020-08-07T17:26:06Z,MEMBER,"I think it's more like
```
da.rolling(x=2).construct(""xr"").rolling(y=2).construct(""yr"").std([""xr"", ""yr""])
```
but that gives
```
array([[0., 5., 5.],
[0., 5., 5.],
[0., 5., 5.]])
```","{""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-670594286,https://api.github.com/repos/pydata/xarray/issues/4219,670594286,MDEyOklzc3VlQ29tbWVudDY3MDU5NDI4Ng==,5635139,2020-08-07T16:13:28Z,2020-08-07T16:13:28Z,MEMBER,"I'm still a bit confused. How does the ""roll over each dimension in turn"" approach equal the ""roll over both dimension together"" approach with a function like std? Here's a proposed counter example:
```python
import xarray as xr
import numpy as np
da = xr.DataArray(np.asarray([[0,10,0],[0,10,0], [0,10,0]]), dims=list('xy'))
print(da)
array([[ 0, 10, 0],
[ 0, 10, 0],
[ 0, 10, 0]])
Dimensions without coordinates: x, y
x_std = da.rolling(dict(x=2)).std()
print(x_std)
array([[nan, nan, nan],
[ 0., 0., 0.],
[ 0., 0., 0.]])
Dimensions without coordinates: x, y
x_then_y_std = x_std.rolling(dict(y=2)).std()
print(x_then_y_std)
array([[nan, nan, nan],
[nan, 0., 0.],
[nan, 0., 0.]])
Dimensions without coordinates: x, y
combined_std = da.rolling(dict(x=2, y=2)).std()
print(combined_std)
array([[nan, nan, nan],
[nan, 5., 5.],
[nan, 5., 5.]])
Dimensions without coordinates: x, y
```","{""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-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-657614995,https://api.github.com/repos/pydata/xarray/issues/4219,657614995,MDEyOklzc3VlQ29tbWVudDY1NzYxNDk5NQ==,2448579,2020-07-13T15:05:26Z,2020-07-13T15:05:26Z,MEMBER,"I think the dictionary is OK. We can allow scalars for `center`, `stride` etc. in which case the scalar applies to all dimensions. This would preserve backward compatibility.
scalar for `min_counts` also seems OK to me. We can update it if someone requests it.","{""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-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
https://github.com/pydata/xarray/pull/4219#issuecomment-657257847,https://api.github.com/repos/pydata/xarray/issues/4219,657257847,MDEyOklzc3VlQ29tbWVudDY1NzI1Nzg0Nw==,5635139,2020-07-12T18:23:19Z,2020-07-12T18:23:28Z,MEMBER,"Re the API, I think the dict is probably the best option, although it does complicate as the arguments become differently typed depending on one vs multiple dimensions.
One alternative is to allow fluent args, like:
```python
(
da
.rolling(x=3, center=True)
.rolling(y=5, min_periods=2)
.mean()
)
```
...but does that then seem like the second `rolling` is operating on the _result_ of the first?","{""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-657257600,https://api.github.com/repos/pydata/xarray/issues/4219,657257600,MDEyOklzc3VlQ29tbWVudDY1NzI1NzYwMA==,5635139,2020-07-12T18:20:38Z,2020-07-12T18:20:38Z,MEMBER,"This looks very promising; I'm surprised it was possible without more code. I'm being slow, but where is the nd-rolling algo? I had thought bottleneck didn't support more than one dimension? https://bottleneck.readthedocs.io/en/latest/bottleneck.move.html, and that we'd have to implement our own in numbagg (which would be very possible)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,655389649