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/1225#issuecomment-326146218,https://api.github.com/repos/pydata/xarray/issues/1225,326146218,MDEyOklzc3VlQ29tbWVudDMyNjE0NjIxOA==,3496314,2017-08-30T23:23:16Z,2017-08-30T23:23:16Z,NONE,"OK, thanks Joe and Stephan.
On Wed, Aug 30, 2017 at 3:36 PM, Joe Hamman
wrote:
> @tbohn - What is happening here is that xarray
> is storing the netCDF4 chunk size from the input file. For the LAI
> variable in your example, that isLAI:_ChunkSizes = 19, 1, 160, 160 ; (you
> can see this with ncdump -h -s filename.nc).
>
> $ ncdump -s -h veg_hist.0_10n.90_80w.2000_2016.mode_PFT.5dates.nc
> netcdf veg_hist.0_10n.90_80w.2000_2016.mode_PFT.5dates {
> dimensions:
> veg_class = 19 ;
> lat = 160 ;
> lon = 160 ;
> time = UNLIMITED ; // (5 currently)
> variables:
> float Cv(veg_class, lat, lon) ;
> Cv:_FillValue = -1.f ;
> Cv:units = ""-"" ;
> Cv:longname = ""Area Fraction"" ;
> Cv:missing_value = -1.f ;
> Cv:_Storage = ""contiguous"" ;
> Cv:_Endianness = ""little"" ;
> float LAI(veg_class, time, lat, lon) ;
> LAI:_FillValue = -1.f ;
> LAI:units = ""m2/m2"" ;
> LAI:longname = ""Leaf Area Index"" ;
> LAI:missing_value = -1.f ;
> LAI:_Storage = ""chunked"" ;
> LAI:_ChunkSizes = 19, 1, 160, 160 ;
> LAI:_Endianness = ""little"" ;
> ...
>
> Those integers correspond to the dimensions from LAI. When you slice your
> dataset, you end up with lat/lon dimensions that are now smaller than the
> _ChunkSizes. When writing this back to netCDF, xarray is still trying to
> use the original encoding attribute.
>
> The logical fix is to validate this encoding attribute and either 1) throw
> an informative error if something isn't going to work, or 2) change the
> ChunkSizes.
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
> , or mute
> the thread
>
> .
>
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,202964277
https://github.com/pydata/xarray/issues/1225#issuecomment-307524160,https://api.github.com/repos/pydata/xarray/issues/1225,307524160,MDEyOklzc3VlQ29tbWVudDMwNzUyNDE2MA==,3496314,2017-06-09T23:32:38Z,2017-08-30T22:26:44Z,NONE,"OK, here's my code and the file that it works (fails) on.
Code:
```Python
import os.path
import numpy as np
import xarray as xr
ds = xr.open_dataset('veg_hist.0_10n.90_80w.2000_2016.mode_PFT.5dates.nc')
ds_out = ds.isel(lat=slice(0,16),lon=slice(0,16))
#ds_out.encoding['unlimited_dims'] = 'time'
ds_out.to_netcdf('test.out.nc')
```
Note that I commented out the attempt to make 'time' unlimited - if I attempt it, I get a slightly different chunk size error ('NetCDF: Bad chunk sizes').
I realize that for now I can use 'ncks' as a workaround, but seems to me that xarray should be able to do this too.
File (attached)
[veg_hist.0_10n.90_80w.2000_2016.mode_PFT.5dates.nc.zip](https://github.com/pydata/xarray/files/1065436/veg_hist.0_10n.90_80w.2000_2016.mode_PFT.5dates.nc.zip)
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,202964277
https://github.com/pydata/xarray/issues/1225#issuecomment-307524406,https://api.github.com/repos/pydata/xarray/issues/1225,307524406,MDEyOklzc3VlQ29tbWVudDMwNzUyNDQwNg==,3496314,2017-06-09T23:34:44Z,2017-06-09T23:34:44Z,NONE,"(note also that for the example nc file I provided, the slice that my example code makes contains nothing but null values - but that's irrelevant - the error happens for other slices that do contain non-null values.)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,202964277
https://github.com/pydata/xarray/issues/1225#issuecomment-307518173,https://api.github.com/repos/pydata/xarray/issues/1225,307518173,MDEyOklzc3VlQ29tbWVudDMwNzUxODE3Mw==,3496314,2017-06-09T22:55:20Z,2017-06-09T22:55:20Z,NONE,"I've been encountering this as well, and I don't want to use the scipy engine workaround. If you can tell me what a ""self-contained"" example means, I can also try to provide one.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,202964277