IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks
July 27, 2018 Β· Declared Dead Β· π Journal of Open Source Software
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Authors
Patricia Wollstadt, Joseph T. Lizier, Raul Vicente, Conor Finn, Mario MartΓnez-Zarzuela, Pedro Mediano, Leonardo Novelli, Michael Wibral
arXiv ID
1807.10459
Category
cs.IT: Information Theory
Citations
113
Venue
Journal of Open Source Software
Last Checked
4 months ago
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+.
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