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  • fujiisoup · 4 ✖

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  • Multi-dimensional binning/resampling/coarsening · 4 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
447545224 https://github.com/pydata/xarray/issues/2525#issuecomment-447545224 https://api.github.com/repos/pydata/xarray/issues/2525 MDEyOklzc3VlQ29tbWVudDQ0NzU0NTIyNA== fujiisoup 6815844 2018-12-15T07:28:13Z 2018-12-15T07:28:13Z MEMBER

Thinking its API. I like rolling-like API. One in my mind is python ds.coarsen(x=2, y=2, side='left', trim_excess=True).mean() To apply a customized callable other than np.mean to a particular coordinate, it would probably be python ds.coarsen(x=2, y=2, side='left', trim_excess=True).mean(coordinate_apply={'surface_area': np.sum})

 
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   Multi-dimensional binning/resampling/coarsening 375126758
435268965 https://github.com/pydata/xarray/issues/2525#issuecomment-435268965 https://api.github.com/repos/pydata/xarray/issues/2525 MDEyOklzc3VlQ29tbWVudDQzNTI2ODk2NQ== fujiisoup 6815844 2018-11-02T04:37:35Z 2018-11-02T04:37:35Z MEMBER

+1 for block

What would the coordinates look like? 1. apply func also for coordinate 2. always apply mean to coordinate

 
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   Multi-dimensional binning/resampling/coarsening 375126758
434589377 https://github.com/pydata/xarray/issues/2525#issuecomment-434589377 https://api.github.com/repos/pydata/xarray/issues/2525 MDEyOklzc3VlQ29tbWVudDQzNDU4OTM3Nw== fujiisoup 6815844 2018-10-31T07:36:41Z 2018-10-31T07:36:41Z MEMBER

block_reduce sounds nice, but I am a little hesitating to add a soft-dependence of scikit-image only for this function... It is using the strid trick, as we are doing in rolling.construct. Maybe we can implement it by ourselves.

 
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   Multi-dimensional binning/resampling/coarsening 375126758
434261896 https://github.com/pydata/xarray/issues/2525#issuecomment-434261896 https://api.github.com/repos/pydata/xarray/issues/2525 MDEyOklzc3VlQ29tbWVudDQzNDI2MTg5Ng== fujiisoup 6815844 2018-10-30T11:17:17Z 2018-10-30T11:17:17Z MEMBER

This is from a thread at SO.

Does anyone have an opinion if we add a bin (or rolling_bin) method to compute the binning? For the above example, currently we need to do python dsa.rolling(x=2).construct('tmp').isel(x=slice(1, None, 2)).mean('tmp') which is a little complex.

 
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   Multi-dimensional binning/resampling/coarsening 375126758

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