cibr-jyu / meggie

User-friendly MNE-python based graphical user interface to do MEG and EEG analysis with multiple subjects

Meggie

Documentation

• User documentation is found here: http://meggie.teekuningas.net
• Developer documentation is found here: https://cibr-jyu.github.io/meggie

Installation (from terminal)

Note that Python>=3.8 might be required to get the newest version.

From conda-forge (mamba instead of conda might install faster):

1. Install meggie to a conda environment: conda create -n meggie-env -c conda-forge meggie=1.6.3
2. Activate the environment: conda activate meggie-env
3. Run: meggie

Using this repository:

1. Clone this repository to /path/to/meggie/repo
2. Create virtual environment: python -m venv /path/to/meggie-env
3. Activate the environment: source /path/to/meggie-env/bin/activate
4. Enter the repository: cd /path/to/meggie/repo
5. Install dependencies: python -m pip install -r requirements.txt
6. Install meggie: python -m pip install .
7. Run: meggie

Debugging

• If command meggie is not found, you should ensure that you are in the correct python environment.
• If the command is found, but the software crashes during startup to an ImportError, you should ensure that you are using Python 3 and that the dependencies are installed. Individual missing dependencies can often be installed with either conda install or pip install.
• If the software crashes during analysis or startup, and the terminal window does not show you the stacktrace, you can start meggie using command meggie debug and then the next crash will come with a stacktrace.

License

This project is licensed under the BSD license.

Acknowledgements

Great thanks to the excellent MNE-python and all the people who have helped.