v1.6.0 10/2024

This release provides fixes for the bugs ralted to the FDR corrections in the stats module; it introduces a new dependency on python statsmodels.

v1.5.1 01/2024

Bug fixes:

Update to JIDT version 1.6.1. Fix formatting issues and minor bugs.

v1.5 12/2023

New features:

• Implementation of purely Python-based (C)MI-estimators and MPI-support for serial (C)MI-estimators by @daehrlich

v1.4 04/2022

New features:

• Implementation of significant subgraph mining by @aarongutknecht as described in the biorXiV preprint

Bug fixes:

• Ensure that output in results classes contains only numpy and not JPype types. This eases further processing of outputs, especially loading and saving of results (if JPype types are saved, a JVM has to run when loading them again)

v1.3 02/2022

New features:

• Implementation of history-dependence estimator for neural spike data (by @DrMichaelLindner)

v1.2.2 05/2021

Fixes:

• Fix call to maximum stats in multivariate network inference (use correct conditioning set when performing statistics)

Minor fixes:

• Update PID references in README (#67)

v1.2 02/2021

New features:

• Checkpointing: allows to restart an analysis in case of a crash (by @makavelj)
• Random seed for Data class: sets seed to control generation of data permutations (by @makavelj)

Fixes:

• OpenCl estimators crash for certain problem instances (#30, #10)
• Minor fixes:
  • Compatibility with latest networkx version (#55)
  • Export of DiGraph objects for nodes without links (#50)

v1.1 05/2020

New features:

• Multivariate, differentiable Partial Information Decomposition (Makkeh et al., 2020, arXiv:2002.03356 [cs.IT])

Fixes:

• Fixing compatibility for JPype1 0.7 and improving Java memory usage
• Adds Kraskov algorithm 2 and improves memory error handling
• Minor fixes:
  • Fixes installation process, #37, #41
  • Fixes max stats for AIS and bivariate MI estimation
  • Fixes surrogate creation for maximum seq. statistics

Release peer reviewed and accepted for publication in JOSS

This release was peer-reviewed for publication in the Journal of Open Source Software.

Updated development release

Updates to documentation, gh-pages, and unit-/system-tests.

Improvements:

• Improve handling memory exhaustion for JidtDiscrete estimators. This also required including a new JIDT jar. Please note there are occasions where the OS cannot provide more memory (even though heap is large enough) where Java crashes and via jpype1 this seems to kill python. I will continue to investigate this but it may not be solveable.

Bug fixes:

• Fixes #15 by adding Kraskov algorithm 2 option for all JidtKraskov estimators. This required including a new JIDT jar. Unit test included for MI.