API Reference

This page provides an auto-generated summary of xbitinfo’s API. For more details and examples, refer to the relevant chapters in the main part of the documentation.

xbitinfo

get_bitinformation(ds[, dim, axis, label, ...])	Wrap BitInformation.jl.bitinformation().
get_keepbits(info_per_bit[, inflevel, ...])	Get the number of mantissa bits to keep.
get_prefect_flow([paths])	Create prefect.Flow for paths to be:

Bitrounding

xr_bitround(da, keepbits)	Apply bitrounding based on keepbits from xbitinfo.xbitinfo.get_keepbits() for xarray.Dataset or xarray.DataArray wrapping numcodecs.bitround
jl_bitround(da, keepbits)	Apply bitrounding based on keepbits from xbitinfo.xbitinfo.get_keepbits() for xarray.Dataset or xarray.DataArray wrapping BitInformation.jl.round.
bitround_along_dim(ds, info_per_bit, dim[, ...])	Apply bitrounding on slices along dim based on inflevels.

Save compressed

get_chunksizes(da[, for_cdo, time_dim, chunks])	Get chunksizes for xarray.DataArray for to_netcdf(encoding) from original file.
ToCompressed_Netcdf(xarray_obj)	Save to compressed netcdf wrapping xarray.Dataset.to_netcdf() with xbitinfo.save_compressed.get_compress_encoding_nc().
get_compress_encoding_nc(ds[, compression, ...])	Generate encoding for xarray.Dataset.to_netcdf().
ToCompressed_Zarr(xarray_obj)	Save to compressed zarr wrapping xarray.Dataset.to_zarr() with xbitinfo.save_compressed.get_compress_encoding_zarr().
get_compress_encoding_zarr(ds[, compressor])	Generate encoding for xarray.Dataset.to_zarr().

Graphics

plot_bitinformation(bitinfo[, ...])	Plot bitwise information content as in Klöwer et al. 2021 Figure 2.
plot_distribution(ds[, nbins, cmap, offset, ...])	Plot statistical distributions of all variables as in Klöwer et al. 2021 Figure SI 1.
add_bitinfo_labels(da, info_per_bit[, ...])	Helper function for visualization of Figure 3 in Klöwer et al. 2021.