This is an xarray-wrapper around BitInformation.jl to retrieve and apply bitrounding from within python.
The package intends to present an easy pipeline to compress (climate) datasets based on the real information content.
Klöwer, M., Razinger, M., Dominguez, J. J., Düben, P. D., & Palmer, T. N. (2021). Compressing atmospheric data into its real information content. Nature Computational Science, 1(11), 713–724. doi: 10/gnm4jj
conda install -c conda-forge xbitinfo
pip install xbitinfo # ensure to install julia manually
import xarray as xr
import xbitinfo as xb
example_dataset = 'eraint_uvz'
ds = xr.tutorial.load_dataset(example_dataset)
bitinfo = xb.get_bitinformation(ds, dim="longitude") # calling bitinformation.jl.bitinformation
keepbits = xb.get_keepbits(bitinfo, inflevel=0.99) # get number of mantissa bits to keep for 99% real information
ds_bitrounded = xb.xr_bitround(ds, keepbits) # bitrounding keeping only keepbits mantissa bits
ds_bitrounded.to_compressed_netcdf(outpath) # save to netcdf with compression