automated runtime benchmarking (#84)

try automated benchmarking
Fix benchmark tests: fix JIT method signatures and fixture scoping
set reasonable intensity
fix ruff, fix comments
add git action right to write
fix table formating with benchmark results
make benchmark compare PR with main
add number of rounds info, warmup for jit functions and increas min amount of rounds
fix ruff
separate python processes for main and PR benchmarks, add cache clearing
fix mutation issues, make consistent number if rounds, remove unused benchmarks
make sure we time only operations and not spectra creation itself
create sample spectra before measuring time
use setup to exclude spectra creation time from measuring operations
fix to actualy measure operations without creation
use median instead of mean
remove unused file
Improve error handling for XLMOD OBO parsing failures
add workarounds for the XLMOD OBO
Fix comment new line

spectrum_utils

spectrum_utils is a Python package for efficient mass spectrometry data processing and visualization.

spectrum_utils contains the following features:

Spectrum loading from online proteomics and metabolomics data resources using the Universal Spectrum Identifier (USI) mechanism.
Common spectrum processing operations (precursor & noise peak removal, intensity filtering, intensity scaling) optimized for computational efficiency.
Annotating observed spectrum fragments using the ProForma 2.0 specification for (modified) peptidoforms.
Publication-quality, fully customizable spectrum plotting and interactive spectrum plotting.

spectrum_utils logo

Installation

spectrum_utils requires Python version 3.10+ and can be installed with pip or conda.

Using pip:

pip install spectrum_utils[iplot]

Using conda:

conda install -c bioconda spectrum_utils

Please see the documentation for detailed installation instructions, usage examples, the API reference, and more information.

spectrum_utils is freely available as open source under the Apache 2.0 license.

When using spectrum_utils, please cite the following manuscripts:

Wout Bittremieux. “spectrum_utils: A Python package for mass spectrometry data processing and visualization.” Analytical Chemistry 92, 659–661 (2020) doi:10.1021/acs.analchem.9b04884.
Wout Bittremieux, Lev Levitsky, Matteo Pilz, Timo Sachsenberg, Florian Huber, Mingxun Wang, Pieter C. Dorrestein. “Unified and standardized mass spectrometry data processing in Python using spectrum_utils” Journal of Proteome Research 22, 625–631 (2023) doi:10.1021/acs.jproteome.2c00632.