issue_comments

Doing some digging, it turns out this turned up quite a while ago back in #156 where we added some code to fix this.

Looking at @tbohn's dataset, the problem variable is actually the coordinate variable 'time' corresponding to the unlimited dimension: ``` In [7]: ds.variables['time'] Out[7]: <class 'netCDF4._netCDF4.Variable'> int32 time(time) units: days since 2000-01-01 00:00:00.0 unlimited dimensions: time current shape = (5,) filling on, default _FillValue of -2147483647 used

In [8]: ds.variables['time'].chunking() Out[8]: [1048576]

In [9]: 2 ** 20 Out[9]: 1048576

In [10]: ds.dimensions Out[10]: OrderedDict([('veg_class', <class 'netCDF4._netCDF4.Dimension'>: name = 'veg_class', size = 19), ('lat', <class 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 160), ('lon', <class 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 160), ('time', <class 'netCDF4._netCDF4.Dimension'> (unlimited): name = 'time', size = 5)]) ```

For some reason netCDF4 gives it a chunking of 2 ** 20, even though it only has length 5. This leads to an error when we write a file back with the original chunking.

@chrwerner Sorry to hear about your trouble, I will take another look at this.

Right now, your best bet is probably something like: python def clean_dataset(ds): for var in ds.variables.values(): if 'chunksizes' in var.encoding: del var.encoding['chunksizes']

@tbohn "self-contained" just means something that I can run on my machine. For example, the code above plus the "somefile.nc" netCDF file that I can load to reproduce this example.

Thinking about this a little more, I think the issue is somehow related to the encoding['chunksizes'] property on the Dataset variables loaded from the original netCDF file. Something like this should work as a work-around: del myds.var.encoding['chunksizes']

The bug is somewhere in our handling of chunksize encoding for netCDF4, but it is difficult to fix it without being able to run code that reproduces it.