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A Python3 package for eeg (pre)processing from Automagic.

Project description


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A Python3 version of the automagic EEG processing pipeline. Development in progress. This is all temporary.


  1. Paper:
  2. Paper:
  3. Matlab github repo:

Project Organization

├── Makefile           <- Makefile with commands like `make data` or `make train`
├──          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
├── docs               <- A default Sphinx project; see for details
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
├──           <- makes project pip installable (pip install -e .) so src can be imported
├── pyautomagic
|   ├── src            <- Src/ from automagic (matlab)
│   ├──    <- Makes src a Python module
│   │
│   ├── base           <- Scripts that are configuration files, or other code used by the entire pyautomagic repo.
│   │
│   ├── gui             <- Scripts for the gui
│   │
│   ├── preprocessing   <- Scripts for running EEG preprocessing
│   │
│   └── visualization  <- Scripts to visualize results, etc.
└── tox.ini            <- tox file with settings for running tox; see

Intended Users / Usage

Researchers dealing with EEG data. The main (default) workflow is summarized in:

Installation Guide

For installation instructions, see installation guide.

Setup Jupyter Kernel To Test

You need to install ipykernel to expose your conda environment to jupyter notebooks.

conda install ipykernel
python -m ipykernel install --name pyautomagic --user
# now you can run jupyter lab and select a kernel
jupyter lab 

Testing and Documentation

For contributing, please see contribution guide.

For running tests, please see testing guide.

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