fix incorrectly not propagated option r in sample entropy (#396)

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 = "3.4.1"
+version = "3.4.2"
 
 [deps]
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"

src/complexity_measures/sample_entropy.jl

@@ -73,10 +73,10 @@ Base.@kwdef struct SampleEntropy{R} <: ComplexityEstimator
         r > 0 || throw(ArgumentError("r must be > 0. Got r=$(r)."))
         new{R}(m, τ, r)
     end
-    function SampleEntropy(x::AbstractVector; m::Int = 2, τ::Int = 1)
-        r = 0.2 * Statistics.std(x)
-        SampleEntropy(m, τ, r)
-    end
+end
+
+function SampleEntropy(x::AbstractVector; r = 0.2Statistics.std(x), m::Int = 2, τ::Int = 1)
+    return SampleEntropy(m, τ, r)
 end
 
 # See comment in https://github.com/JuliaDynamics/ComplexityMeasures.jl/pull/71 for why

src/convenience.jl

@@ -8,7 +8,7 @@ export entropy_distribution
     entropy_distribution(x; τ = 1, m = 3, n = 3, base = 2)
 
 Compute the distribution entropy [Li2015](@cite) of `x` using embedding dimension `m`
-with delay/lag `τ`, using the Chebyshev distance metric, and using an `n`-element 
+with delay/lag `τ`, using the Chebyshev distance metric, and using an `n`-element
 equally-spaced binning over the distribution of distances to estimate probabilities.
 
 This function is just a convenience call to:
@@ -90,8 +90,8 @@ This is just a wrapper for `complexity(SampleEntropy(; r, m, τ, base), x)`.
 
 See also: [`SampleEntropy`](@ref), [`complexity`](@ref), [`complexity_normalized`](@ref)).
 """
-function entropy_sample(x; normalize = true, kwargs...)
-    c = SampleEntropy(x; kwargs...)
+function entropy_sample(x; normalize = true, r = 0.2std(x), kwargs...)
+    c = SampleEntropy(x; r, kwargs...)
     if normalize
         complexity_normalized(c, x)
     else