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  • xr.open_dataset(f1).to_netcdf(file2) is not idempotent · 2 ✖

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480624904 https://github.com/pydata/xarray/issues/2871#issuecomment-480624904 https://api.github.com/repos/pydata/xarray/issues/2871 MDEyOklzc3VlQ29tbWVudDQ4MDYyNDkwNA== shoyer 1217238 2019-04-07T20:11:05Z 2019-04-07T20:11:05Z MEMBER

Indeed it works. Thanks. My quick fix:

$ diff variables.py variables.py.orig 152,155d151 < elif encoding.get('missing_value') is not None: < fill_value = pop_to(encoding, attrs, 'missing_value', name=name) < if not pd.isnull(fill_value): < data = duck_array_ops.fillna(data, fill_value) I also figured out how to write back floating point values: encoding=None means use existing values, so specifying encoding={'tmpk': {}} in to_netcdf() did the trick. Should there be an option for this? What you see on the screen is not what you get in the file.

Yes, this is a challenging design problem and the current state of affairs is definitely not ideal. If you have ideas about how to reveal the presence of an encoding dict associated with a variable without overwhelming the user with information those would be very welcome. The alternative would be to not keep around encoding at all, but I think users do appreciate that reading/writing a netCDF file generally returns the exact same thing.

 
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   xr.open_dataset(f1).to_netcdf(file2) is not idempotent 429914958
480460266 https://github.com/pydata/xarray/issues/2871#issuecomment-480460266 https://api.github.com/repos/pydata/xarray/issues/2871 MDEyOklzc3VlQ29tbWVudDQ4MDQ2MDI2Ng== shoyer 1217238 2019-04-06T00:49:39Z 2019-04-06T00:49:39Z MEMBER

I think this could be fixed by making CFMaskCoder handle missing_value and _FillValue in a symmetric way in encoding/decoding: https://github.com/pydata/xarray/blob/23d54a890e6cfe1de420071b597c911164de4cb8/xarray/coding/variables.py#L142

Right now, it only uses missing_value in the decode() method.

 
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   xr.open_dataset(f1).to_netcdf(file2) is not idempotent 429914958

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