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DeerLab is a Python package for the analysis of dipolar EPR (electron paramagnetic resonance) spectroscopy data. Dipolar EPR spectroscopy techniques include DEER (double electron-electron resonance), RIDME (relaxation-induced dipolar modulation enhancement), and others. The documentation can be found here.

DeerLab consists of a collection of functions for modelling, data processing, and least-squares fitting. They can be combined in scripts to build custom data analysis workflows. DeerLab supports both classes of distance distribution models: non-parametric (Tikhonov regularization and related) and parametric (multi-Gaussians etc). It also provides a selection of background and experiment models.

The early versions of DeerLab (up to version 0.9) are written in MATLAB. The old MATLAB codebase is archived and can be found here.

DeerLab is available for Windows, Mac and Linux systems and requires Python 3.6, 3.7, or 3.8.

All additional dependencies are automatically downloaded and installed during the setup.

A pre-built distribution can be installed using pip.

First, ensure that pip is up-to-date. From a terminal (preferably with administrative privileges) use the following command:

python -m pip install --upgrade pip

Next, install DeerLab with

python -m pip install deerlab

More details on the installation of DeerLab can be found here.

A paper about DeerLab is currently submitted for publication. When you use DeerLab in your work, for now, please cite the preprint

Fábregas Ibáñez, L., Jeschke, G., and Stoll, S.: DeerLab: A comprehensive software package for analyzing dipolar EPR spectroscopy data, Magn. Reson. Discuss., https://doi.org/10.5194/mr-2020-13, 2020

Please check back frequently for updated publication information.

The DeerLab toolbox is licensed under the MIT License.

Copyright (c) 2019-2020: Luis Fábregas Ibáñez, Stefan Stoll, Gunnar Jeschke, and other contributors.