IDTxl - 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.

Scientific Software - Peer-reviewed - Python
Published by mwibral over 1 year ago

IDTxl - v1.5.1 01/2024

Bug fixes:

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

Scientific Software - Peer-reviewed - Python
Published by pwollstadt over 2 years ago

IDTxl - v1.5 12/2023

New features:

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

Scientific Software - Peer-reviewed - Python
Published by pwollstadt over 2 years ago

IDTxl - 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)

Scientific Software - Peer-reviewed - Python
Published by pwollstadt about 4 years ago

IDTxl - v1.3 02/2022

New features:

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

Scientific Software - Peer-reviewed - Python
Published by pwollstadt over 4 years ago

IDTxl - 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)

Scientific Software - Peer-reviewed - Python
Published by pwollstadt about 5 years ago

IDTxl - 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)

Scientific Software - Peer-reviewed - Python
Published by pwollstadt over 5 years ago

IDTxl - 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

Scientific Software - Peer-reviewed - Python
Published by pwollstadt about 6 years ago

IDTxl - Release peer reviewed and accepted for publication in JOSS

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

Scientific Software - Peer-reviewed - Python
Published by pwollstadt over 7 years ago

IDTxl - 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.

Scientific Software - Peer-reviewed - Python
Published by pwollstadt over 7 years ago

IDTxl - Updated development release

This is the second development release. Note that algorithms are still in beta stage. Also, there may be changes to the API in future releases.

To get started with using IDTxl have a look at the wiki pages describing the installation process and the example script for network inference. There are also examples in the docstrings of the algorithm classes. Further documentation: http://pwollstadt.github.io/IDTxl/ and https://github.com/pwollstadt/IDTxl/wiki.

Stable algorithms (see the demos for examples): - multivariate_transfer_entropy.py - bivariate_transfer_entropy.py - multivariate_mutual_information.py - bivariate_mutual_information.py - active_information_storage.py - partial_information_decomposition.py - network_comparison.py (group-level statistics) - visualise_graph.py - core-estimators, see the wiki page for examples

Added features: - (lagged) multivariate and bivariate MI estimation for network inference - bivariate TE estimation for network inference - Results() class: replaces results dictionary, adds functionality to generate adjacency matrices and access detailed results for individual targets - generation of synthetic test data in the Data() class (coupled logistic maps and autoregressive processes) - demo scripts for network inference algorithms and core estimators

Improvements: - add jar-file supporting JAVA v6 (fixes #9) - cleaned up console output - update of the Tartu estimator

Bug fixes: - OpenCL estimators now run on Nvidia and AMD cards (fixes #10) - Labeling of nodes in source graph - The minimum statistics did not use the correct conditioning set during the pruning step of the multivariate TE algorithm, causing a bias in the test - Non-uniform embedding was not built correctly for bivariate measures

Known issues and missing features: - OpenCL estimators fail on AMD cards in some cases due to driver settings that introduce limitations on maximum variable size - spectral multivariate transfer entropy estimation will be added in a future release - the Kraskov2 algorithm will be available for estimation in a future release (issue #15)

Scientific Software - Peer-reviewed - Python
Published by pwollstadt almost 8 years ago

IDTxl - First development release

This is the first development release.

To get started with IDTxl have a look at the wiki pages describing the installation process and the example script for network inference. There are also examples in the docstrings of the algorithm classes. Further documentation: http://pwollstadt.github.io/IDTxl/ and https://github.com/pwollstadt/IDTxl/wiki (under development).

Stable algorithms: - multivariate_transfer_entropy.py - network_comparison.py (group-level statistics) - core-estimators of basic information-theoretic quantities, see the wiki page for examples

The following algorithms and modules are in alpha stage and may still contain bugs or may change until the official release: - active_information_storage.py - partial_information_decomposition.py - bivariate_transfer_entropy.py - visualise_graph.py

Known issues and missing features:

• OpenCL estimators seem to run on Nvidia cards only (support for AMD cards will be added in the future)
• load/save functionality in idtxl_io.py is not yet working, use pickle to load and save results and data files
• the results format will change in a future release
• spectral multivariate transfer entropy estimation will be added in a future release
• (lagged) MI estimation for network inference will be added in a future release

Scientific Software - Peer-reviewed - Python
Published by pwollstadt over 8 years ago