Framework of Information Theory for Electrophysiological data and Statistics
Project description
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 :
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
Project details
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