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cwepr – A Python package for analysing cw-EPR data focussing on reproducibility and simple usage.

Authors :
Schröder, Mirjam
Biskup, Till
Source :
Journal of Magnetic Resonance. Feb2022, Vol. 335, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

[Display omitted] • Open-source software package for processing and analysis of cw-EPR data. • Focus on full reproducibility and simple usage. • Powerful user interface requiring no programming skills of the user. • Real-world examples of routine tasks as well as more specialised workflows. • Available open-source and free of charge, welcoming contributions from the community. Reproducibility is at the heart of science. Nevertheless, with the advent of computer-based data processing and analysis, most spectroscopists have a hard time fully reproducing a figure from last year's publication starting from the raw data. Unfortunately, this renders their work eventually unscientific. To change this, we need to develop analysis tools that relieve their users from having to trace each processing and analysis step. Furthermore, these tools need to be modular, extendible, and easy to use in order to get used. To this end, we present here the open-source Python package cwepr based on the ASpecD framework for reproducible analysis of spectroscopic data. This package follows best practices of both, science and software development. Key features include an automatically generated gap-less record of each individual processing and analysis step from the raw data to the final published figure. Additionally, it provides a powerful user interface requiring no programming skills of the user. Due to its code quality, modularity, and extensive documentation, it can be easily extended and is actively developed by spectroscopists working in the field. We expect this approach to have a high impact in the field and to help fighting the looming reproducibility crisis in spectroscopy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10907807
Volume :
335
Database :
Academic Search Index
Journal :
Journal of Magnetic Resonance
Publication Type :
Academic Journal
Accession number :
155057725
Full Text :
https://doi.org/10.1016/j.jmr.2021.107140