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/1192#issuecomment-434478590,https://api.github.com/repos/pydata/xarray/issues/1192,434478590,MDEyOklzc3VlQ29tbWVudDQzNDQ3ODU5MA==,1217238,2018-10-30T21:34:54Z,2018-10-30T21:34:54Z,MEMBER,"see also https://github.com/pydata/xarray/issues/2525
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,198742089
https://github.com/pydata/xarray/issues/1192#issuecomment-305538498,https://api.github.com/repos/pydata/xarray/issues/1192,305538498,MDEyOklzc3VlQ29tbWVudDMwNTUzODQ5OA==,1217238,2017-06-01T15:57:31Z,2017-06-01T15:57:31Z,MEMBER,"The dask implementation is short enough that I would certainly reimplement/vendor the pure numpy version for xarray. It might also be worth considering using the related utility [`skimage.util.view_as_blocks`](http://scikit-image.org/docs/dev/api/skimage.util.html#skimage.util.view_as_blocks) from skimage, which does the necessary reshaping using views (which should be much faster).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,198742089
https://github.com/pydata/xarray/issues/1192#issuecomment-305209648,https://api.github.com/repos/pydata/xarray/issues/1192,305209648,MDEyOklzc3VlQ29tbWVudDMwNTIwOTY0OA==,1217238,2017-05-31T14:46:55Z,2017-05-31T14:46:55Z,MEMBER,"Currently dask is an optional dependency for carry, which I would like to
preserve if possible. I'll take a glance at the implementation shortly, but
my guess is that we will indeed want to vendor the numpy version into
xarray.
On Wed, May 31, 2017 at 6:38 AM Peter Steinberg <notifications@github.com>
wrote:

> Hi @darothen <https://github.com/darothen> earthio is a recent
> experimental refactor of what was the elm.readers subpackage. elm -
> Ensemble Learning Models was developed with a Phase I NASA SBIR in 2016 and
> in part reflects our thinking in late 2015 when xarray was newer and we
> were planning the proposal. In the last ca. month we have started a Phase
> II of development on multi-model dask/xarray ML algorithms based on xarray,
> dask, scikit-learn and a Bokeh maps UI for tasks like land cover
> classification. I'll add you to elm and feel free to contact me at
> psteinberg [at] continuum [dot] io. We will do more promotion / blogs in
> the near term and also in about 12 months we will release a free/open
> collection of notebooks that form a ""Machine Learning with Environmental
> Data"" 3-day course.
>
> Back to the subject matter of the thread.... I assigned this issue to
> myself. I'll wait to get started until after @shoyer
> <https://github.com/shoyer> comments on @laliberte
> <https://github.com/laliberte> 's question:
>
> (1) replicate serial coarsen into xarray or (2) point to dask coarsen
> methods?
>
> —
>
>
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
> <https://github.com/pydata/xarray/issues/1192#issuecomment-305189172>, or mute
> the thread
> <https://github.com/notifications/unsubscribe-auth/ABKS1hU-F507Wp1-MMa_JXzyaNtxXYQvks5r_W1hgaJpZM4LaxU4>
> .
>
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,198742089
https://github.com/pydata/xarray/issues/1192#issuecomment-270427209,https://api.github.com/repos/pydata/xarray/issues/1192,270427209,MDEyOklzc3VlQ29tbWVudDI3MDQyNzIwOQ==,1217238,2017-01-04T17:12:04Z,2017-01-04T17:12:15Z,MEMBER,"This has the feel of a multi-dimensional resampling operation operation. I could potentially see this as part of that interface (e.g., `array.resample(x=3, y=3).mean()`), but that may be a slightly different operations because `resample`'s window size is in label rather than integer coordinates.

That said, this seems useful and I wouldn't get too hung up about the optimal interface. I would be happy with a `coarsen` method, though I'd prefer to have an non-dask implementation, too. Potentially we could simply copy in skimage's [`block_reduce` function](http://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.block_reduce) for the non-dask implementation, which if I recall correctly does some clever tricks with reshaping to do the calculation efficiently.

cc @jhamman who has been thinking about regridding/resampling.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,198742089