gumpy is a Python 3 toolbox to develop Brain-Computer Interfaces (BCI).

gumpy contains implementations of several functions that are commonly used during EEG and EMG decoding. For this purpose it heavily relies on other numerical and scientific libraries, for instance numpy, scipy, or scikit-learn, to name just a few. In fact, gumpy mostly wraps existing functions in such a way that researchers working in the field can quickly perform data analysis and implement novel classifiers. Moreover, one of gumpy's design principles was to make it easily extendable.

license

MIT License

contributions

Please use github (www.github.com/gumpy-bci/gumpy) and see below

issues

Please use the issue tracker on github (www.github.com/gumpy-bci/gumpy/issues)

You can find documentation for gumpy either on www.gumpy.org or in subfolder doc. For examples, see the folder examples.

If you wish to contribute to gumpy's development clone the main repository from github and start coding, test if everything works as expected, and finally submit patches or open merge requests. Preferrably in this order.

Please make sure that you follow PEP8, or have a look at the formatting of gumpy's code, and include proper documentation both in your commit messages as well as the source code. We use Google docstrings for formatting, and auto-generate parts of the documentation with sphinx.

• Zied Tayeb
• Nicolai Waniek, www.github.com/rochus
• Juri Fedjaev
• Nejla Ghaboosi
• Leonard Rychly

Zied Tayeb, Nicolai Waniek, Juri Fedjaev, Nejla Ghaboosi, Leonard Rychly, Christian Widderich, Christoph Richter, Jonas Braun, Matteo Saveriano, Gordon Cheng, and Jörg Conradt. "gumpy: A Python Toolbox Suitable for Hybrid Brain-Computer Interfaces"

@Article{gumpy2018,
    Title = {gumpy: A Python Toolbox Suitable for Hybrid Brain-Computer Interfaces},
    Author = {Tayeb, Zied and Waniek, Nicolai and Fedjaev, Juri and Ghaboosi, Nejla and Rychly, Leonard and Widderich, Christian and Richter, Christoph and Braun, Jonas and Saveriano, Matteo and Cheng, Gordon and Conradt, Jorg},
    Year = {2018},
    Journal = {}
}

• www.gumpy.org: gumpy's main website. You can find links to datasets here
• www.github.com/gumpy-bci/gumpy: gumpy's main github repository
• www.github.com/gumpy-bci/gumpy-deeplearning: gumpy's deep learning models for BCI
• https://github.com/gumpy-bci/gumpy-realtime : gumpy's real-time BCI module with several online demos
• https://www.youtube.com/channel/UCdarvfot4Ustk2UCmCp62sw : gumpy's Youtube channel
• https://www.youtube.com/watch?v=M68GeL8PafE

• All code in this repository is published under the MIT License. For more details see the LICENSE file.