Metadata-Version: 1.2
Name: frites
Version: 0.3.5
Summary: Framework of Information Theory for Electrophysiological data and Statistics
Home-page: https://github.com/brainets/frites
Author: BraiNets
Author-email: e.combrisson@gmail.com
Maintainer: Etienne Combrisson
License: BSD 3-Clause License
Download-URL: https://github.com/brainets/frites/archive/v0.3.5.tar.gz
Description: ======
        frites
        ======
        
        .. image:: https://github.com/brainets/frites/workflows/frites/badge.svg
            :target: https://github.com/brainets/frites/workflows/frites
        
        .. image:: https://travis-ci.org/brainets/frites.svg?branch=master
            :target: https://travis-ci.org/brainets/frites
        
        .. image:: https://circleci.com/gh/brainets/frites.svg?style=svg
            :target: https://circleci.com/gh/brainets/frites
        
        .. image:: https://codecov.io/gh/brainets/frites/branch/master/graph/badge.svg
          :target: https://codecov.io/gh/brainets/frites
        
        .. image:: https://badge.fury.io/py/frites.svg
            :target: https://badge.fury.io/py/frites
        
        .. image:: https://pepy.tech/badge/frites
            :target: https://pepy.tech/project/frites
        
        .. figure::  https://github.com/brainets/frites/blob/master/docs/source/_static/frites.png
            :align:  center
        
        
        Description
        -----------
        
        
        **FRITES = Framework for Information Theoretical analysis of Electrophysiological data and Statistics**
        
        
        Frites is a python package for analyzing neurophysiological brain data (i.e M/EEG, sEEG / iEEG / ECoG). The package is entirely based on information theoretic measures (such as mutual information (MI)) in order to perform analysis such as :
        
        * "Correlation like" (**I(c; c)** = MI between two continuous variables)
        * "Machine-learning like" (**I(c; d)** = MI between a continuous and a discrete variable)
        * "Partial correlation like" (**I(c; c | d)** = MI between two continuous variables and removing the influence of a discrete one)
        * Information-transfer about a specific feature
        
        For a comprehensive (and extensive) review, see the paper of Robin AA Ince `A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula <https://www.ncbi.nlm.nih.gov/pubmed/27860095>`_.
        
        Frites also comes with embedded statistics which support fixed and random-effect analysis in combination with inferences either at the single time-point level or at the temporal cluster level.
        
        Take a look at the online documentation and examples to start analyzing your data with Frites : https://brainets.github.io/frites/
        
        
        Installation
        ------------
        
        Dependencies
        ++++++++++++
        
        The main dependencies of Frites are :
        
        * `Numpy <https://numpy.org/>`_
        * `Scipy <https://www.scipy.org/>`_
        * `MNE <https://mne.tools/stable/index.html>`_
        * `Xarray <http://xarray.pydata.org/en/stable/>`_
        * `Joblib <https://joblib.readthedocs.io/en/latest/>`_
        
        In addition to the main dependencies, here's the list of additional packages that you might need :
        
        * `Numba <http://numba.pydata.org/>`_ : speed computations of some functions
        * `Matplotlib <https://matplotlib.org/>`_, `Seaborn <https://seaborn.pydata.org/>`_ and `Networkx <https://networkx.github.io/>`_ for plotting the examples
        
        
        User installation
        +++++++++++++++++
        
        Frites can be installed (and/or updated) via pip with the following command :
        
        .. code-block:: shell
        
            pip install -U frites
        
        
        Developer installation
        ++++++++++++++++++++++
        
        For developers, you can install frites in develop mode with the following commands :
        
        .. code-block:: shell
        
            git clone https://github.com/brainets/frites.git
            cd frites
            python setup.py develop
        
        
Keywords: information-theory statistics
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
