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

Area of Science:

• Spectroscopy
• Computational Science
• Data Analysis

Background:

• Reproducibility in science is challenged by complex computer-based data processing.
• Current analysis methods often hinder the ability to trace steps from raw data to final figures.
• This lack of traceability can compromise the scientific integrity of published work.

Purpose of the Study:

• To develop user-friendly, modular, and extendible analysis tools for reproducible spectroscopic data processing.
• To introduce the open-source Python package cwepr, built upon the ASpecD framework.
• To address the reproducibility crisis in spectroscopy through improved data analysis practices.

Main Methods:

• Development of the open-source Python package cwepr.
• Utilizing the ASpecD framework for data analysis.
• Implementation of a gap-less record of all processing and analysis steps.
• Creation of a user-friendly interface requiring no programming skills.

Main Results:

• cwepr provides an automatically generated, gap-less record of data processing and analysis.
• The package offers a powerful user interface accessible to users without programming expertise.
• cwepr adheres to best practices in both scientific and software development.

Conclusions:

• The cwepr package facilitates reproducible analysis of spectroscopic data.
• It offers a solution to the challenges in reproducing figures from raw data.
• The tool is expected to significantly impact the field and mitigate the reproducibility crisis in spectroscopy.