Metadata-Version: 2.1
Name: pyautomagic
Version: 0.1.0
Summary: A Python3 package for eeg (pre)processing from Automagic.
Home-page: https://github.com/NeuroDataDesign/pyautomagic
Author: NDD19
Maintainer: Adam Li
Maintainer-email: adam2392@gmail.com
License: MIT
Project-URL: Documentation, https://github.com/NeuroDataDesign/pyautomagic/docs/
Project-URL: Source, https://github.com/NeuroDataDesign/pyautomagic
Project-URL: Tracker, https://github.com/NeuroDataDesign/pyautomagic/issues
Keywords: EEG,research tools,automated processing
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation
Classifier: Natural Language :: English
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.14.5)
Requires-Dist: scipy (>=1.1.0)
Requires-Dist: scikit-learn (>=0.19.2)
Requires-Dist: pandas (>=0.23.4)
Requires-Dist: mne (>=0.19.2)
Requires-Dist: mne-bids (>=0.3)

pyautomagic
===========

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

References
----------
1. Paper: https://www.biorxiv.org/content/10.1101/460469v1
2. Paper: https://www.ncbi.nlm.nih.gov/pubmed/31233907
3. Matlab github repo: https://github.com/methlabUZH/automagic


Project Organization
--------------------

    ├── 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


--------


Intended Users / Usage
----------------------

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

Installation Guide
------------------

For installation instructions, see [installation guide](./INSTALLATION.md).

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](./CONTRIBUTING.md).

For running tests, please see [testing guide](./TESTING_SETUP.md).

