promote package based on paper proof (#417)

* promote quality based on paper proof

* Apply suggestions from code review

Co-authored-by: Kristian Agasøster Haaga <[email protected]>

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Co-authored-by: Kristian Agasøster Haaga <[email protected]>

Project.toml

@@ -2,7 +2,7 @@ name = "ComplexityMeasures"
 uuid = "ab4b797d-85ee-42ba-b621-05d793b346a2"
 authors = "Kristian Agasøster Haaga <[email protected]>, George Datseries <[email protected]>"
 repo = "https://github.com/juliadynamics/ComplexityMeasures.jl.git"
-version = "3.6.3"
+version = "3.6.4"
 
 [deps]
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"

README.md

@@ -6,10 +6,15 @@
 [![codecov](https://codecov.io/gh/JuliaDynamics/ComplexityMeasures.jl/branch/main/graph/badge.svg?token=6XlPGg5nRG)](https://codecov.io/gh/JuliaDynamics/ComplexityMeasures.jl)
 [![Package Downloads](https://img.shields.io/badge/dynamic/json?url=http%3A%2F%2Fjuliapkgstats.com%2Fapi%2Fv1%2Ftotal_downloads%2FComplexityMeasures&query=total_requests&label=Downloads)](http://juliapkgstats.com/pkg/ComplexityMeasures)
 [![Package Downloads](https://img.shields.io/badge/dynamic/json?url=http%3A%2F%2Fjuliapkgstats.com%2Fapi%2Fv1%2Ftotal_downloads%2FEntropies&query=total_requests&label=Downloads%20(Entropies))](http://juliapkgstats.com/pkg/Entropies)
-[![DOI](https://img.shields.io/badge/DOI:-arXiv.2406.05011-blueviolet.svg)](https://doi.org/10.48550/arXiv.2406.05011)
+[![publication](https://img.shields.io/badge/publication-arXiv.2406.05011-blueviolet.svg)](https://doi.org/10.48550/arXiv.2406.05011)
 
-ComplexityMeasures.jl is a software for calculating 1000s of various kinds of
-probabilities, entropies, and other so-called _complexity measures_ from a single input dataset. For relational measures across many input datasets see its extension [CausalityTools.jl](https://juliadynamics.github.io/CausalityTools.jl/dev/).
+ComplexityMeasures.jl is a Julia-based software for calculating 1000s of various kinds of
+probabilities, entropies, and other so-called _complexity measures_ from a single-variable input datasets. For relational measures across many input datasets see its extension [CausalityTools.jl](https://juliadynamics.github.io/CausalityTools.jl/dev/).
+If you are a user of other programming languages (Python, R, MATLAB, ...),
+you can still use ComplexityMeasures.jl due to Julia's interoperability.
+For example, for Python use [`juliacall`](https://pypi.org/project/juliacall/).
+
+A careful comparison with alternative widely used software shows that ComplexityMeasures.jl outclasses the alternatives in several objective aspects of comparison, such as computational performance, overall amount of measures, reliability, and extendability. See the associated publication for more details.
 
 The key features that it provides can be summarized as: