Metadata-Version: 2.1
Name: mnelab
Version: 0.2.0
Summary: A graphical user interface for MNE
Home-page: https://github.com/cbrnr/mnelab
Author: Clemens Brunner
Author-email: clemens.brunner@gmail.com
License: BSD-3-Clause
Keywords: EEG MEG MNE GUI electrophysiology
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.5, <4
Description-Content-Type: text/markdown
Requires-Dist: mne
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: PyQt5
Provides-Extra: edf_export
Requires-Dist: pyedflib ; extra == 'edf_export'
Provides-Extra: fastica
Requires-Dist: scikit-learn ; extra == 'fastica'
Provides-Extra: picard
Requires-Dist: python-picard ; extra == 'picard'
Provides-Extra: xdf_import
Requires-Dist: pyxdf ; extra == 'xdf_import'

[![Latest PyPI Release](https://img.shields.io/pypi/v/mnelab.svg)](https://pypi.org/project/mnelab/)
[![Conda Version](https://img.shields.io/conda/vn/conda-forge/mnelab.svg)](https://anaconda.org/conda-forge/mnelab)
![Python 3.6](https://img.shields.io/badge/python-3.6-green.svg)
![Python 3.7](https://img.shields.io/badge/python-3.7-green.svg)
![License](https://img.shields.io/badge/license-BSD-green.svg)

MNELAB
======

Graphical user interface (GUI) for [MNE](https://github.com/mne-tools/mne-python), a Python-based toolbox for EEG/MEG analysis.

### Screenshots

![](https://raw.githubusercontent.com/cbrnr/mnelab/master/mnelab.png)

### Dependencies
MNELAB requires Python >= 3.6. In addition, the following Python packages are required:
- [PyQt5](https://www.riverbankcomputing.com/software/pyqt/download5) >= 5.6.0
- [numpy](http://www.numpy.org/) >= 1.8.1
- [scipy](https://www.scipy.org/scipylib/index.html) >= 0.17.1
- [matplotlib](https://matplotlib.org/) >= 2.0.0
- [mne](https://github.com/mne-tools/mne-python) >= 0.17

Optional dependencies provide additional features if installed:
- [scikit-learn]() (ICA computation via FastICA)
- [python-picard](https://pierreablin.github.io/picard/) (ICA computation via PICARD)
- [pyEDFlib](https://github.com/holgern/pyedflib) (export raw to EDF/BDF)
- [pyxdf](https://github.com/xdf-modules/xdf-Python) (import XDF files)

In general, I recommended to always use the latest package versions.

### Additional features
MNELAB comes with the following features that are not (yet) available in MNE:
- Export raw to EDF/BDF (requires [pyEDFlib](https://github.com/holgern/pyedflib))
- Export raw to EEGLAB SET
- Import [XDF](https://github.com/sccn/xdf/wiki/Specifications) files (requires [pyxdf](https://github.com/xdf-modules/xdf-Python))

### Installation
#### Via pip
The latest release is available on [PyPI](https://pypi.python.org/pypi) and can be installed with:
```
pip install mnelab
mnelab
```
The `mnelab` command in the last line starts the application.

#### Via conda
An (unofficial, but regularly updated) conda package can be installed from [conda-forge](https://conda-forge.org/).
We **strongly** suggest to install MNELAB into its own dedicated environment to ensure smooth installation
and operation:
```
conda create -y --name mnelab -c conda-forge mnelab
conda activate mnelab
mnelab
```
The `mnelab` command in the last line starts the application.
Any issues with this conda package should be reported to the respective
[issue tracker](https://github.com/conda-forge/mnelab-feedstock/issues).

#### Standalone installer
A stand-alone installer will be available soon.


#### Development version
Follow these steps to use the latest development version of MNELAB:

1. [Download the source code](https://github.com/cbrnr/mnelab/archive/master.zip) and unpack it into a folder of your choice.
2. Open a terminal, change to the folder where you unpacked the MNELAB source.
    - If you use [Anaconda](https://www.anaconda.com/distribution/) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html), install all dependencies with `conda install numpy scipy matplotlib pyqt` followed by `pip install mne`.
    - Otherwise, install all dependencies with `pip install -r requirements.txt`.
3. Finally, run `python3 -m mnelab` to start MNELAB (if this does not work try `python -m mnelab`, just make sure to use Python 3 because Python 2 is not supported).


