Changelog¶

All notable changes to Syntropy are documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased¶

syntropy.knn gained sample entropy (sample_entropy) and cross-sample entropy (cross_sample_entropy): non-parametric, distance-based measures of complexity and dynamical similarity for continuous time series.
syntropy.mixed.mutual_information now accepts a continuous_estimator argument ("gaussian" or "knn", with a k parameter for the KNN option), matching the mixed entropy functions. The KNN estimator recovers the true mutual information for non-Gaussian continuous marginals, where the Gaussian plug-in is only an approximation.

syntropy.mixed estimators no longer raise an IndexError when given a single continuous variable (the covariance is now treated as a 1x1 matrix).

Initial alpha release.
Discrete, Gaussian, KNN (Kraskov), neural (normalizing-flow), and mixed estimators.
Pointwise (local) values alongside expected values across estimators.
Higher-order measures: total correlation, dual total correlation, O-information, and S-information.
Partial information decomposition, partial entropy decomposition, generalized information decomposition, and integrated information decomposition.
Information rates and Lempel-Ziv complexity measures for time series.