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Java Information Dynamics Toolkit (JIDT)

Copyright (C) 2012-2014 Joseph T. Lizier; 2014-2015 Joseph T. Lizier and Ipek Özdemir

JIDT provides a stand-alone, open-source code Java implementation (also usable in Matlab, Octave, Python, R, Julia and Clojure) of information-theoretic measures of distributed computation in complex systems: i.e. information storage, transfer and modification.

JIDT includes implementations:

• principally for the measures transfer entropy, mutual information, and their conditional variants, as well as active information storage, entropy, etc;
• for both discrete and continuous-valued data;
• using various types of estimators (e.g. Kraskov-Stögbauer-Grassberger estimators, box-kernel estimation, linear-Gaussian), as described in full at ImplementedMeasures.

JIDT is distributed under the GNU GPL v3 license (or later).

Getting started

1. Download and Installation is very easy!
2. Quick start: download the latest v1.3 full distribution (suitable for all platforms) and see the readme.txt file therein.
3. Documentation including: the paper describing JIDT at arXiv:1408.3270 (distributed with the toolkit), a Tutorial, and Javadocs (v1.3 here);
4. Demos are included with the full distribution, including a GUI app for automatic analysis and code generation, simple java demos and cellular automata (CA) demos.
5. These Java tools can easily be used in Matlab/Octave, Python, R, Julia and Clojure! (click on each language here for examples)

For further information or announcements:

• Join our discussion group: http://groups.google.com/d/forum/jidt-discuss
• See also the FAQs
• Follow @infodynamicstkt on twitter

Citation

Please cite your use of this toolkit as:

Joseph T. Lizier, "JIDT: An information-theoretic toolkit for studying the dynamics of complex systems", Frontiers in Robotics and AI 1:11, 2014; doi:10.3389/frobt.2014.00011 (pre-print: arXiv:1408.3270)

And please let me know about any publications resulting from its use!

See other PublicationsUsingThisToolkit.

News

19/7/2015 - New jar and full distribution files available for release v1.3; Changes for v1.3 include: Added AutoAnalyser (Code Generator) GUI demo for MI and TE; Added auto-embedding capability via Ragwitz criteria for AIS and TE calculators (KSG estimators); Added Java demo 9 for showcasing use of Ragwitz auto-embedding; Adding small amount of noise to data in all KSG estimators now by default (may be disabled via setProperty()); Added getProperty() methods for all conditional MI and TE calculators; Upgraded Python demos for Python 3 compatibility; Fixed bias correction on mixed discrete-continuous KSG calculators; Updated the tutorial slides to those in use for ECAL 2015 JIDT tutorial.

12/2/2015 - New jar and full distribution files available for release v1.2.1; Changes for v1.2.1 include: Added tutorial slides, description of exercises and sample exercise solutions; Made jar target Java 1.6; Added Schreiber TE heart-breath rate with KSG estimator demo code for Python.

28/1/2015 - New jar and full distribution files available for release v1.2; Changes for v1.2 include: Dynamic correlation exclusion, or Theiler window, added to all Kraskov estimators; Added univariate MI calculation to simple demo 6; Added Java code for Schreiber TE heart-breath rate with KSG estimator, ready for use as a template in Tutorial; Patch for crashes in KSG conditional MI algorithm 2.

20/11/2014 - New jar and full distribution files available for release v1.1; Changes for v1.1 include: Implemented Fast Nearest Neighbour Search for Kraskov-Stögbauer-Grassberger (KSG) estimators for MI, conditional MI, TE, conditional TE, AIS, Predictive info, and multi-information. This includes a general (multivariate) k-d tree implementation; Added multi-threading (using all available processors by default) for the KSG estimators -- code contributed by Ipek Özdemir; Added Predictive information / Excess entropy implementations for KSG, kernel and Gaussian estimators; Added R, Julia, and Clojure demos; Added Windows batch files for the Simple Java Demos; Added property for adding a small amount of noise to data in all KSG estimators;

15/8/2014 JIDT paper finalised and uploaded to the website and arXiv:1408.3270

14/8/2014 - New jar and full distribution files available for our first official release, v1.0; Changes for v1.0 include: Added the draft of the paper on the toolkit to the release; Javadocs made ready for release; Switched source->destination arguments for discrete TE calculators to be with source first in line with continuous calculators; Renamed all discrete calculators to have Discrete suffix -- TE and conditional TE calculators also renamed to remove "Apparent" prefix and change "Complete" to "Conditional"; Kraskov estimators now using 4 nearest neighbours by default; Unit test for Gaussian TE against ChaLearn Granger causality measurement; Added Schreiber TE demos; Interregional transfer demos; documentation for Interaction lag demos; added examples 7 and 8 to Simple Java demos; Added property to add noise to data for Kraskov MI; Added derivation of Apache Commons Math code for chi square distribution, and included relevant notices in our release; Inserted translation class for arrays between Octave and Java; Added analytic statistical significance calculation to Gaussian calculators and discrete TE; Corrected Kraskov algorithm 2 for conditional MI to follow equation in Wibral et al. 2014.

20/4/2014 - New jar and full distribution files available for v0.2.0; Moved downloads to http://lizier.me/joseph/ since google code has stopped the download facility here :(. Changes for v0.2.0 include: Rearchitected (most) Transfer Entropy and Multivariate TE calculators to use an underlying conditional mutual information calculator, and have arbitrary embedding delay, source-dest delay; this includes moving Kraskov-Grassberger Transfer Entropy calculator to use a single conditional mutual information estimator instead of two mutual information estimators; Rearchitected (most) Active Information Storage calculators to use an underlying mutual information calculator; Added Conditional Transfer Entropy calculators using underlying conditional mutual information calculators; Moved mixed discrete-continuous calculators to a new "mixed" package; bug fixes.

11/9/2013 - New jar and full distribution files available for v0.1.4; added scripts to generate CA figures for 2013 book chapters; added general Java demo code; added Python demo code; made Octave/Matlab demos and CA demos properly compatible for Matlab; added extra Octave/Matlab general demos; added more unit tests for MI and conditional MI calculators, including against results from Wibral's TRENTOOL; bug fixes.

11/9/2013 - New CA demo scripts for several review book chapters we're preparing in 2013 have been uploaded - see CellularAutomataDemos.

4/6/2013 - Added instructions on how to use in python and several PythonExamples.

13/01/2013 - New jar and full distribution files available for v0.1.3; existing Octave/Matlab demo code made compatible with Matlab; several bug fixes, including using max norm by default in Kraskov calculator (instead of requiring this to be set explicitly); more unit tests (including against results from Kraskov's own MI implementation)

19/11/2012 - New jar and full distribution files available for v0.1.2, including demo code for two newly submitted papers

31/10/2012 - Jar and full distribution files available for v0.1.1 (first distribution)

7/5/2012 - JIDT project created and code uploaded