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However, in practice the decision on how much information shall be kept needs testing with the downstream tools and is often an iterative process to ensure consistent behaviour with the original dataset. The gathering of the bitinformation and the decision on the bitrounding parameters are therefore often not immediately following each other and are interrupted by visual inspection and testing (see Fig. \autoref{fig:xbitinfo_workflow}) + +![Xbitinfo workflow with the addition of storing the computational expensive retrieval of the bitinformation content in a JSON file for later reference and the ability to evaluate and adjust the keepbits on subsets of the original dataset.\label{fig:xbitinfo_workflow}](xbitinfo_workflow.png){ width=40% } + +Xbitinfo therefore provides additional convience functions over `klower_compressing_2021:2021` to analyse, filter and visualize the information content. Because Xbitinfo operates on xarray `Datasets` it can also handle a large variety of input and output formats, like netCDF and Zarr and naturally fit into several current scientific workflows. Thanks to the xarray-compatibility it can also make use of a wide range of modern compression algorithms that are implemented for the specific output data formats to utilize the additional compression gains due to reduced information. + +Xbitinfo provides two backends for the calculation of the bitinformation content, one wraps the latest Julia implementation provided with `klower_compressing_2021:2021` for consistency and the other uses numpy to be dask compatible and more performant. + + +# Example + +To compress a dataset based on its bitinformation content with xbitinfo follows the following steps: + +```python +import xarray as xr +import xbitinfo as xb + +ds = xr.open_dataset("/path/to/input/file") +bitinfo = xb.get_bitinformation(ds) +keepbits = xb.get_keepbits(bitinfo, inflevel=0.95) +ds = xb.xr_bitround(ds, keepbits) +ds.to_compressed_zarr("/path/to/output/file") +``` + + +# Remarks + +It should be noted that the BitInformation algorithm relies on uncompressed data that hasn't been manipulated beforehand. A common issue is that climate model output has been linearily quantized during its generation, e.g. because it has been written to the GRIB format. Such datasets should be handeled with care as the bitinformation often contains artificial information resulting in too many keepbits. Filters to capture those cases are currently developed within xbitinfo to warn the user. + + + # Acknowledgements diff --git a/xbitinfo_workflow.png b/xbitinfo_workflow.png new file mode 100644 index 0000000000000000000000000000000000000000..9d1a6b9cdfbd75adbea23b5201729c8f9857adf6 GIT binary patch literal 185545 zcmeFZbyQSs_cu-p2vQ;;5+WcWAV^Az0)lkM5YpYv00RmJB`qyT!;pgHjG}Z(ODZKD zL+9@h13vfj{r>l^-+JG*?muqV+{2vf>}$to@BO*f`TIbIy&}>YUB{H-^y_opA7MB zT80fqX(qoYLTwbxIRpATsE=^&6N*{;u|eT)Zr}DN1!dg*d_%1N&E4`RU-Za~i4^<4 z`{PG%qX$haKU}FrFq(CEzi(?x^6K<;nz`ba_AOF6!jJ()`PY}6(ON7#gV~Sk@r7*p?WcgGSMuQ{D2yTi)4+P zduL7hR>{M!G0!2=!9^H`15r_`s9&WBc_p6{(s-naux?cguKDIsuogB?esA@#a zESNF9kbLG8c-Q;OgDi%ZJDuO`r+jkQG{<0yi<9?Dp%vaM%ogKI8sDO4GnroOwQP4J z%<11X?d*N_Hfo!Z(9^U1+l%H&hB@l>Pj{Nd*WC?E!bVbJh;DbvNl`bwAEDi)U|c`& z&!n&yW096r#f_sy*`2`=tKwt@Kc`PrZN|;HD?*plENL4T-b{+PH^W(QufPU1?sK6^ zSiMfel<*634Kr_#Hz;lU4@5+KEE~uSP~dB5D6cxryc_yZ?oOfESH9wiG<~+qxI&CY z`0f~0P!U~QjDQ^7$pC*5!fk&=4^DvLuSkd)gC-)4!Yn=e-hi|T6EhXt8cj!>VGw@{ 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