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  • markelg · 1 ✖

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  • passing unlimited_dims to to_netcdf triggers RuntimeError: NetCDF: Invalid argument · 1 ✖

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  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
366255764 https://github.com/pydata/xarray/issues/1849#issuecomment-366255764 https://api.github.com/repos/pydata/xarray/issues/1849 MDEyOklzc3VlQ29tbWVudDM2NjI1NTc2NA== markelg 6883049 2018-02-16T14:50:21Z 2018-02-16T15:10:40Z CONTRIBUTOR

This happened to me today after introducing some modifications in a code that was working fine. I have tried to trace it without success. Finally, I found a workaround which consist on removing the "contiguous" entry from the .encoding attributes. This works with gerritholl's file:

import xarray as xr ds = xr.open_dataset("sample.nc") del ds.x.encoding["contiguous"] del ds.y.encoding["contiguous"] ds.to_netcdf("sample2.nc", unlimited_dims=["y"])

So it seems that this entry in the encoding dictionaries is triggering the error.

OK, so I guess that this explains it, from the netCDF4 documentation:

"contiguous: if True (default False), the variable data is stored contiguously on disk. Default False. Setting to True for a variable with an unlimited dimension will trigger an error."

This is quite an obscure error right now, so maybe we could force contiguous to be False when unlimited_dims is being used, or either raise a more informative error.

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  passing unlimited_dims to to_netcdf triggers RuntimeError: NetCDF: Invalid argument 290572700

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