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@pwollstadt pwollstadt released this 24 Aug 15:42
· 402 commits to master since this release
v0.3.0
4b1b4a4

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)

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