A Python3 version of the automagic EEG processing pipeline. Development in progress. This is all temporary.
- Paper: https://www.biorxiv.org/content/10.1101/460469v1
- Paper: https://www.ncbi.nlm.nih.gov/pubmed/31233907
- Matlab github repo: https://github.com/methlabUZH/automagic
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- 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 sphinx-doc.org 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`
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── pyautomagic
| ├── src <- Src/ from automagic (matlab)
│ ├── __init__.py <- 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 tox.testrun.org
Researchers dealing with EEG data. The main (default) workflow is summarized in:
For installation instructions, see installation guide.
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
For contributing, please see contribution guide.
For running tests, please see testing guide.