IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks
Information Theory
2019-02-20 v2 math.IT
Abstract
The Information Dynamics Toolkit xl (IDTxl) is a comprehensive software package for efficient inference of networks and their node dynamics from multivariate time series data using information theory. IDTxl provides functionality to estimate the following measures: 1) For network inference: multivariate transfer entropy (TE)/Granger causality (GC), multivariate mutual information (MI), bivariate TE/GC, bivariate MI 2) For analysis of node dynamics: active information storage (AIS), partial information decomposition (PID) IDTxl implements estimators for discrete and continuous data with parallel computing engines for both GPU and CPU platforms. Written for Python3.4.3+.
Cite
@article{arxiv.1807.10459,
title = {IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks},
author = {Patricia Wollstadt and Joseph T. Lizier and Raul Vicente and Conor Finn and Mario Martínez-Zarzuela and Pedro Mediano and Leonardo Novelli and Michael Wibral},
journal= {arXiv preprint arXiv:1807.10459},
year = {2019}
}
Comments
4 pages