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Package for handling cw-EPR data.

Project description

The cwEPR package provides tools for handling experimental data obtained using continuous-wave EPR (cwEPR) spectroscopy and is derived from the ASpecD framework. Due to inheriting from the ASpecD superclasses, all data generated with the cwepr package are completely reproducible and have a complete history.

What is even better: Actual data processing and analysis no longer requires programming skills, but is as simple as writing a text file summarising all the steps you want to have been performed on your dataset(s) in an organised way. Curious? Have a look at the following example:

  type: ASpecD recipe
  version: '0.2'

  default_package: cwepr

  - /path/to/first/dataset
  - /path/to/second/dataset

  - kind: processing
    type: FrequencyCorrection
        frequency: 9.8
  - kind: processing
    type: BaselineCorrection
        order: 0
  - kind: singleplot
    type: SinglePlotter1D
        - first-dataset.pdf
        - second-dataset.pdf

For more general information on the cwepr package and for how to use it, see its documentation.


A list of features:

  • Fully reproducible processing of cw-EPR data

  • Import of EPR data from diverse sources (Bruker ESP, EMX, Elexsys; Magnettech)

  • Generic plotting capabilities, easily extendable

  • Report generation using pre-defined templates

  • Recipe-driven data analysis, allowing tasks to be performed fully unattended in the background

And to make it even more convenient for users and future-proof:

  • Open source project written in Python (>= 3.7)

  • Extensive user and API documentation

Target audience

The cwepr package addresses scientists working with cwEPR data (both, measured and calculated) on a daily base and concerned with reproducibility. Due to being based on the ASpecD framework, the cwepr package ensures reproducibility and—as much as possible—replicability of data processing, starting from recording data and ending with their final (graphical) representation, e.g., in a peer-reviewed publication. This is achieved by automatically creating a gap-less record of each operation performed on your data. If you do care about reproducibility and are looking for a system that helps you to achieve this goal, the cwepr package may well be interesting for you.

How to cite

cwepr is free software. However, if you use cwepr for your own research, please cite both, the article describing it and the software itself:

To make things easier, cwepr has a DOI provided by Zenodo, and you may click on the badge below to directly access the record associated with it. Note that this DOI refers to the package as such and always forwards to the most current version.


Install the package by running:

pip install cwepr


This program is free software: you can redistribute it and/or modify it under the terms of the BSD License.

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