Metadata-Version: 2.1
Name: DeerLab
Version: 0.12.1
Summary: Comprehensive package for data analysis of dipolar EPR spectroscopy
Home-page: https://github.com/JeschkeLab/DeerLab
Author: Luis Fábregas Ibáñez , Stefan Stoll and other contributors
License: LICENSE.txt
Project-URL: Documentation, https://jeschkelab.github.io/DeerLab/
Project-URL: Source, https://github.com/JeschkeLab/DeerLab
Description: <p align="center">
        <img src="https://raw.githubusercontent.com/JeschkeLab/DeerLab/main/docsrc/source/_static/logo_dark.png" alt="DeerLab Logo" width="40%"></img>
        </p>
        </div>
        
        ### About
        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](https://jeschkelab.github.io/DeerLab/index.html).
        
        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](https://github.com/JeschkeLab/DeerLab-Matlab).
        
        ### Requirements
        
        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.
         
        ### 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](https://jeschkelab.github.io/DeerLab/installation.html).
        
        ### Citation
        
        When you use DeerLab in your work, please cite the following publication:
        
        <div style="height:6%px; width:100%; display:flex; flex-wrap:wrap; align-items:center; border-style:solid">
            <div style="margin-left:2%; margin-bottom:2%; font-size:14px">
                <h3 style="font-size:110%">  DeerLab: a comprehensive software package for analyzing dipolar electron paramagnetic resonance spectroscopy data </h3> 
                Luis FÃ¡bregas IbÃ¡Ã±ez, Gunnar Jeschke, Stefan Stoll <br>
                Magn. Reson., 1, 209â€“224, 2020 <br>
                <a href="https://doi.org/10.5194/mr-1-209-2020"> doi.org/10.5194/mr-1-209-2020</a>
            </div>
        </div>
        
        ### License
        
        The DeerLab toolbox is licensed under the [MIT License](LICENSE).
        
        Copyright (c) 2019-2020: Luis FÃ¡bregas IbÃ¡Ã±ez, Stefan Stoll, Gunnar Jeschke, and [other contributors](https://github.com/JeschkeLab/DeerLab/contributors).
        
Keywords: data analysis EPR spectroscopy DEER PELDOR
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/markdown
