issue_comments: 263751396

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https://github.com/pydata/xarray/issues/1142#issuecomment-263751396 https://api.github.com/repos/pydata/xarray/issues/1142 263751396 MDEyOklzc3VlQ29tbWVudDI2Mzc1MTM5Ng== 2443309 2016-11-30T01:04:21Z 2016-11-30T01:10:24Z MEMBER

Certainly open to adding this functionality. Bottleneck isn't going to help so the code will all live in xarray. I think it makes sense to have a bit of a design discussion here prior to getting started. Questions:

1. What window types are you interested in adding? Pandas includes:

  • boxcar
  • triang
  • blackman
  • hamming
  • bartlett
  • parzen
  • bohman
  • blackmanharris
  • nuttall
  • barthann
  • kaiser (needs beta)
  • gaussian (needs std)
  • general_gaussian (needs power, width)
  • slepian (needs width)

2. Can we maintain compatibility with pandas and bottleneck.

We have tried to maintain compatibility with both pandas and bottleneck in our rolling implementation. This is proving somewhat difficult (e.g. #1046) but is a design consideration that we should keep in mind.

Also, our current implementation falls back to operating on individual slices of the DataArray when bottleneck cannot be utilized. We should think a bit about the applicability of other windows when using other window types. Presumably, each win_type listed above would just provide a different set of weights to be associated with the members of each window.

3. What about nd windows?

Our current implementation left open the possibility of n-dimensional windows (see #819). While we haven't implemented it yet, the utility of the rolling object for a 2+ dimensional smoother would be quite a nice feature. That said, I'd be hesitant to implement anything on the rolling object that would not allow us to make this addition in the future.

 
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