frites 0.4.2

Framework of Information Theory for Electrophysiological data and Statistics

Frites

Description

Frites is a Python toolbox for assessing information-theorical measures on human and animal neurophysiological data (M/EEG, Intracranial). The aim of Frites is to extract task-related cognitive brain networks (i.e modulated by the task). The toolbox also includes directed and undirected connectivity metrics such as group-level statistics.

Documentation

Frites documentation is available online at https://brainets.github.io/frites/

Installation

Run the following command into your terminal to get the latest stable version :

pip install -U frites

You can also install the latest version of the software directly from Github :

pip install git+https://github.com/brainets/frites.git

For developers, you can install it in develop mode with the following commands :

git clone https://github.com/brainets/frites.git
cd frites
python setup.py develop
# or : pip install -e .

Dependencies

The main dependencies of Frites are :

• Numpy
• Scipy
• MNE Python
• Xarray
• Joblib

In addition to the main dependencies, here’s the list of additional packages that you might need :

• Numba : speed up the computations of some functions
• Dcor for fast implementation of distance correlation
• Matplotlib, Seaborn and Networkx for plotting the examples
• Some example are using scikit learn estimators