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CHANGELOG

Changelog is kept with respect to version 0.11 of Entropies.jl. From version v2.0 onwards, this package has been renamed to ComplexityMeasures.jl.

3 (to be released)

This release does not contain strictly breaking changes, because deprecations have been put in place everywhere. The major change that facilitated v2 -> v3 is the large renaming overhaul that we performed: we renamed the concept of "entropy" to "information measure", and entropy has been renamed to information. Similarly, we now have DiscreteInfoEstimator and DifferentialInfoEstimator. We consider as "information measures" anything that is a functional of probability mass/density functions.

Further additions to the library in v3:

  • New function allprobabilities that is like probabilities but also includes 0 entries for possible outcomes that were not present in the data.
  • New extropy definitions that count as information measures (and thus can be given to information): ShannonExtropy, RenyiExtropy, TsallisExtropy.
  • StatisticalComplexity is now compatible with any normalizable EntropyDefinition.
  • StatisticalComplexity can now estimate probabilities using any combination of ProbabilitiesEstimator and OutcomeSpace.
  • Add the 1976 Lempel-Ziv complexity measure (LempelZiv76).
  • New entropy definition: identification entropy (Identification).
  • Minor documentation fixes.
  • GaussianCDFEncoding now can be used with vector-valued inputs.
  • New LeonenkoProzantoSavani differential entropy estimator. Works with Shannon, Renyi and Tsallis entropies.

Bug fixes

  • outcome_space for Dispersion now correctly returns the all possible sorted outcomes (as promised by the outcome_space docstring).
  • decode with GaussianCDFEncoding now correctly returns only the left-sides of the [0, 1] subintervals, and always returns the decoded symbol as a Vector{SVector} (consistent with RectangularBinEncoding), regardless of whether the input is a scalar or a vector.

Renaming

  • SymbolicPermutation is now OrdinalPatterns.
  • SymbolicWeightedPermutation is now WeightedOrdinalPatterns.
  • SymbolicAmplitudeAwarePermutation is now AmplitudeAwareOrdinalPatterns.
  • SpatialSymbolicPermutation is now SpatialOrdinalPatterns.

2.7.1

  • Fix bug in calculation of statistical complexity

2.7

  • Add generalized statistical complexity as complexity measure.

2.6

  • Fixed differential entropy "unit" bug caused by erroneous conversion between logarithm bases and introduced the convert_logunit function to convert between entropies computed with different logarithm bases.

2.5

  • Moved to StateSpaceSets.jl v1 (only renames of Dataset to StateSpaceSet).

2.4

  • Rectangular binnings have been reformed to operate based on ranges. This leads to much more intuitive bin sizes and edges. For RectangularBinning nothing changes, while for FixedRectangularBinning the ranges should be given explicitly. Backwards compatible deprecations have been added.
  • This also allows for a new precise option that utilizes Base Julia TwinPrecision to make more accurate mapping of points to bins at the cost of performance.

2.3

  • Like differential entropies, discrete entropies now also have their own estimator type.
  • The approach of giving both an entropy definition, and an entropy estimator to entropy has been dropped. Now the entropy estimators know what definitions they are applied for. This change is a deprecation, i.e., backwards compatible.
  • Added PlugInEntropy discrete entropy estimator.

2.2

  • Corrected documentation for SymbolicPermutation, SymbolicAmplitudeAwarePermutation, and SymbolicWeightedPermutation, indicating that the outcome space is the set of factorial(m) permutations of the integers 1:m, not the rank orderings, as was stated before.

2.1

  • Added Gao estimator for differential Shannon entropy.
  • Added Lord estimator for differential Shannon entropy.
  • Probabilities now wraps AbstractArray{T, N} instead of AbstractVector{T}, so that it can also represent multidimensional probability mass functions. For vectors, it behaves as before.

2.0

The API for Entropies.jl has been completely overhauled, and the package has been renamed to ComplexityMeasures.jl. Along with the overhaul comes a massive amount of new features, an entirely new API, extendable and educative code, dedicated documentation pages, and more!

We believe it is best to learn all of this by visiting the online documentation.

We tried our best to keep pre-2.0 functions working and throw deprecation warnings. If we missed code that should be working, let us know by opening an issue.

Major changes

  • Common generic interface function entropy, entropy_normalized and maximum (maximum entropy) that dispatches on different definitions of entropies (e.g Renyi() Shannon(), Tsallis()) and estimated probabilities.
  • Convenience functions for common entropies, such as permutation entropy and dispersion entropy still exist.
  • New interface DifferentialEntropyEstimator that is also used in entropy.
  • The base of the entropy is now a field of the EntropyDefinition type, not the estimator.
  • An entirely new section of entropy-like complexity measures, such as the reverse dispersion entropy.
  • Many new estimators, such as SpatialPermutation and PowerSpectrum.
  • Check the online documentation for a comprehensive overview of the changes.

Minor changes

  • No more deprecation warnings for using the old keyword α for Renyi entropy.
  • The KozachenkoLeonenko estimator now correctly fixes its neighbor search to the closest neighbor only, and its constructor does no longer accept k as an input. It also uses correct scaling factor and adapts to dimension.
  • Using a logarithm base different from MathConstants.e now yields correct results for Kraskov and KozachenkoLeonenko.

main

  • New probability estimator SpatialSymbolicPermutation suitable for computing spatial permutation entropies
  • Introduce Tsallis entropy.

1.2

  • Added dispersion entropy.

1.1

  • Introduce convenience function permentropy.
  • Several type instabilities fixed.

1.0

No actual changes, just first major version release.

0.12

  • Nearest neighbor searches now use Neighborhood.jl and the Theiler window properly.

0.11.1

  • probabilities(data, n::Int) now uses a rectangular binning of n bins for each dimension. Before, while not documented as possible in the public API, using integer n would take it as the bin size.