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:
format:
type: ASpecD recipe
version: '0.2'
settings:
default_package: cwepr
datasets:
- /path/to/first/dataset
- /path/to/second/dataset
tasks:
- kind: processing
type: FrequencyCorrection
properties:
parameters:
frequency: 9.8
- kind: processing
type: BaselineCorrection
properties:
parameters:
order: 0
- kind: singleplot
type: SinglePlotter1D
properties:
filename:
- first-dataset.pdf
- second-dataset.pdf
For more general information on the cwepr package and for how to use it, see its documentation.
Features
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:
Mirjam Schröder, Till Biskup. cwepr – a Python package for analysing cw-EPR data focussing on reproducibility and simple usage. Journal of Magnetic Resonance 335:107140, 2022. doi:10.1016/j.jmr.2021.107140 | PDF | SI
Mirjam Schröder, Till Biskup. cwepr (2021). doi:10.5281/zenodo.4896687
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.
Installation
Install the package by running:
pip install cwepr
License
This program is free software: you can redistribute it and/or modify it under the terms of the BSD License.
2 maintainers
Metadata
2 maintainers
Release files for cwepr 0.5.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| cwepr-0.5.1.tar.gz | 3.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cwepr-0.5.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.8 MB
Release files / cwepr-0.5.1.tar.gz
| Download URL | cwepr-0.5.1.tar.gz |
|---|---|
| Size | 3.7 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/5.0.0 CPython/3.9.2
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Release files / cwepr-0.5.1-py3-none-any.whl
| Download URL | cwepr-0.5.1-py3-none-any.whl |
|---|---|
| Size | 88.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.2
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