v1.6.1-dist

Full distribution release v1.6.1 (including source code, jar, demos, documentation, etc.)

Release notes:

v1.6.1 22/08/2023

(after 909 commits recorded by github)
Minor release to capture latest before using JIDT in class.
Minor updates to supporting use in Python, including virtual environments;
Minor tweaks to fish schooling examples (mostly comments).

v1.6-dist

Full distribution release v1.5 (including source code, jar, demos, documentation, etc.)

Release notes:

v1.6 5/09/2022

(after 892 commits recorded by github)
Adding Flocking/Schooling/Swarming demo;
Included Pedro's code on IIT and O-/S-Information measures;
Spiking TE estimator added from David;
Fixed up AutoAnalyser to work well for Python3 and numpy;
Links to lecture videos included in the beta wiki for the course;
Added rudimentary effective network inference (simplified version of the IDTxl full algorithm) in demos/octave/EffectiveNetworkInference;

v1.5-dist

Full distribution release v1.5 (including source code, jar, demos, documentation, etc.)

Release notes:

v1.5 26/11/2018

(after 753 commits recorded by github)
Added GPU (cuda) capability for KSG Conditional Mutual Information calculator (proper documentation to come), including unit tests and brief wiki page;
Added auto-embedding for TE/AIS with multivariate KSG, and univariate and multivariate Gaussian estimator (plus unit tests), for Ragwitz criteria and Maximum bias-corrected AIS, and also added Maximum bias corrected AIS and TE to handle source embedding as well;
Kozachenko entropy estimator adds noise to data by default;
Added bias-correction property to Gaussian and Kernel estimators for MI and conditional MI, including with surrogates (only option for kernel);
Enabled use of different bases for different variables in MI discrete estimator;
All new above features enabled in AutoAnalyser;
Added drop-down menus for parameters in AutoAnalyser;
Included long-form lecture slides in course folder.

v1.4-dist

Full distribution release v1.4 (including source code, jar, demos, documentation, etc.)

Release notes:

v1.4 26/11/2016

(after 638 commits recorded by github)
Major expansion of functionality for AutoAnalysers: adding Launcher applet and capability to double click jar to launch, added Entropy, CMI, CTE and AIS AutoAnalysers, also added binned estimator type, added all variables/pairs analysis, added statistical significance analysis, and ensured functionality of generated Python code with Python3;
Added GPU (cuda) capability for KSG Mutual Information calculator (proper documentation and wiki page to come), including unit tests;
Added fast neighbour search implementations for mixed discrete-continuous KSG MI estimators;
Expanded Gaussian estimator for multi-information (integration);
Made all demo/data files readable by Matlab.

v1.3.1-dist

Full distribution release v1.3.1 (including source code, jar, demos, documentation, etc.)

This was the first new distribution generated while the project was hosted on github.

Release notes:

v1.3.1 21/10/2016

(after 386 commits recorded by github)
Major update to TransferEntropyCalculatorDiscrete so as to implement arbitrary source and dest embeddings and source-dest delay;
Conditional TE calculators (continuous) handle empty conditional variables;
Added auto-embedding method for AIS and TE which maximises bias corrected AIS;
Added getSeparateNumObservations() method to TE calculators to make reconstructing/separating local values easier after multiple addObservations() calls;
Fixed kernel estimator classes to return proper densities, not probabilities;
Bug fix in mixed discrete-continuous MI (Kraskov) implementation;
Added simple interface for adding joint observations for MultiInfoCalculatorDiscrete
Including compiled class files for the AutoAnalyser demo in distribution;
Updated Python demo 1 to show use of numpy arrays with ints;
Added Python demo 7 and 9 for TE Kraskov with ensemble method and auto-embedding respectively;
Added Matlab/Octave example 10 for conditional TE via Kraskov (KSG) algorithm;
Added utilities to prepare for enhancing surrogate calculations with fast nearest neighbour search;
Minor bug patch to Python readFloatsFile utility;

v1.3-dist

Full distribution release v1.3 (including source code, jar, demos, documentation, etc.)

This was the last distribution generated while the project was hosted on google code; copied here.

Release notes:

v1.3 10/7/2015 at r691 (revision number on google code)

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;