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  • fischcheng · 5 ✖

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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
412250048 https://github.com/pydata/xarray/issues/2355#issuecomment-412250048 https://api.github.com/repos/pydata/xarray/issues/2355 MDEyOklzc3VlQ29tbWVudDQxMjI1MDA0OA== fischcheng 7747527 2018-08-11T04:31:12Z 2018-08-11T04:31:12Z NONE

I want this feature, and the way you proposed is very elegant! The last time I made an animation, I needed to output each frames to .png and packed them as a movie file using imagemagick. I would love to see this feature realized!! 

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   Animated plots - a suggestion for implementation 349026158
378128255 https://github.com/pydata/xarray/issues/2034#issuecomment-378128255 https://api.github.com/repos/pydata/xarray/issues/2034 MDEyOklzc3VlQ29tbWVudDM3ODEyODI1NQ== fischcheng 7747527 2018-04-03T04:56:26Z 2018-04-03T04:56:26Z NONE

@rabernat I like your vision. Ncview is so simple yet powerful that I totally neglect how terrible it looks. Also the examples provided @JiaweiZhuang seem perfect for such task. All parts are there, just waiting for someone to put them together! 

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   simple command line interface for xarray 310547057
378021302 https://github.com/pydata/xarray/issues/2034#issuecomment-378021302 https://api.github.com/repos/pydata/xarray/issues/2034 MDEyOklzc3VlQ29tbWVudDM3ODAyMTMwMg== fischcheng 7747527 2018-04-02T19:38:09Z 2018-04-02T19:38:09Z NONE

From my experience, there are plenty of existing tools can do the data explore/quick-view thing, including the basic ncview, ncdump, cdo or panoply. Some of them support OpenDAP. I'm not sure if Xarray needs to have such feature. 

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   simple command line interface for xarray 310547057
359025678 https://github.com/pydata/xarray/issues/1844#issuecomment-359025678 https://api.github.com/repos/pydata/xarray/issues/1844 MDEyOklzc3VlQ29tbWVudDM1OTAyNTY3OA== fischcheng 7747527 2018-01-19T16:55:25Z 2018-01-19T16:55:25Z NONE

So you got a two-year temperature field with dimension [730, 1, 481, 781], and another mean, and std data arrays of [366, 1, 481, 781] and you want to normalize the temperature field.

Sorry I'm not familiar with the Xarray's groupby functions, I'll try several things before some experts jumping in.

  • Concat two std/mean fields along dayofyear, and reindex to the time index from the temperature data. Then you can do the (dset-mean)/std
  • Separate the temperature fields into two one-year chunks, reindex time to dayofyear, then do the calculation.
  • Flatten the spatial grid then use numpy to do the trick.

I'm also interested in the right way to do it using built-in Xarray functions. I'm pretty sure there are some more clever ways to do this. 

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   How to broadcast along dayofyear 290023410
243965764 https://github.com/pydata/xarray/issues/995#issuecomment-243965764 https://api.github.com/repos/pydata/xarray/issues/995 MDEyOklzc3VlQ29tbWVudDI0Mzk2NTc2NA== fischcheng 7747527 2016-09-01T03:24:49Z 2016-09-01T03:24:49Z NONE

Thank you for answering. 

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   xarray slicing is very slow, and reading time differs a lot between variables. 174390114

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