Metadata-Version: 2.1
Name: Orange3-MNE
Version: 1.0.3
Summary: Electrophysiological data processing widgets for Orange 3 based on the MNE for Python library.
Home-page: https://gitlab.com/fifal/orange-mne-library
Author: Filip Jani
Author-email: jsem@filek.cz
License: UNKNOWN
Description: MNE Widgets for Orange 3 is a python package, that provides methods from MNE for Python for Orange 3 in a form of widgets, 
        to allow for electrophysiological data processing.
        
        > *Note: This library was created as a part of the master's thesis to show that it is possible to use Orange 3 as a workflow management system for electrophysiological data processing. The widgets' functionality was verified on three existing experiments. Nevertheless, the library requires further development.* 
        
        ### Installation
        1. The installation process is quite straightforward, first we need to install the Orange 3 tool:
            > *Note: If you have Orange 3 already installed, you can skip this step and continue to step 2.*
            ```bash
            virtualenv orange          # Create a virtual environment
            ./orange/Scripts/activate  # Activate the environment (source ./orange/Scripts/activate for linux)
            pip install Orange3 PyQt5  # Install Orange 3 and PyQt library
            ```
        2. Then run Orange: `python -m Orange.canvas`
        3. In Orange navigate to Options -> Add-ons
        4. Click on `Add more...` and enter the package name: `Orange3-MNE`
        5. Confirm the settings and Orange will install the library
        6. Restart Orange and the electrophysiological data processing library will be available
        
        ### User's guide
        The documentation on how to use Orange 3 is available on its [homepage](https://orange.biolab.si/docs/).
        
        The documentation to widgets in this library can be found [here](https://gitlab.com/fifal/orange-mne-library/-/blob/master/docs/widgets.md).
Keywords: orange3 add-on mne eeg electrophysiology
Platform: UNKNOWN
Description-Content-Type: text/markdown
