Joshua Charkow

@singjc Can you please test that this works as expected with UIS? (e.g. no data is missing from the .osw file)?

@timosachsenberg I think this is ready for merging? I have not had a chance to review with @hroest but this does not change any functionality just outputs more information so...

Thanks for looping me into the discussion. Results look promising, especially because the file is both smaller and runtime is reduced as well! Just a few requests: It would be...

> [@jcharkow](https://github.com/jcharkow) I have read the `mspack` paper (10.1093/bioinformatics/btab636). This appears to combine out-of-band data that is compressed and standard `gzip` compression of the XML metadata. This is pretty much...

I've done a benchmark with msnumpress on my end for the same file that you benchmarked with above. m/z array is 64-bit float with MS-Numpress linear prediction compression followed by...

Thanks for doing these benchmarks. The dictionary encoding for ion mobility sounds like a good idea that would be beneficial.

Interestingly, it seems that the improvements in terms of timing for Numpress+Zstd over Numpress+zLib is much more pronounced for thermo data than bruker data. @mobiusklein when summarizing everything it might...

Just clarrifying the `ion mobility` graph for the thermo data is actually `m/z`? Interesting how we see different trends. Interesting how we see different trends based on different datatypes however...

Doing eFDR / FDR identification curves with different workflows we can se that LDA_XGBoost is quite similar to XGBoost in terms of overfitting and actually overfits slightly less than XGBoost...

Currently, this method only supports a combined output file (no split based on runs) and no IPF