Generalize Contingency

src/densities/contingency.jl

@@ -22,25 +22,25 @@ A `Contingency` distribution over more than two variables requires higher-order
 - `renormalize`, optional, supports either `Val(true)` or `Val(false)`, specifies whether matrix `P` must be automatically renormalized. Does not modify the original `P` and allocates a new one for the renormalized version. If set to `false` the contingency matrix `P` **must** be normalized by hand, otherwise the result of related calculations might be wrong
 
 """
-struct Contingency{T,P<:AbstractMatrix{T}}
+struct Contingency{T,P<:AbstractArray{T}}
  p::P
 
- Contingency{T,P}(A::AbstractMatrix) where {T,P<:AbstractMatrix{T}} = new(A)
+ Contingency{T,P}(A::AbstractArray) where {T,P<:AbstractArray{T}} = new(A)
 end
 
-Contingency(P::AbstractMatrix) = Contingency(P, Val(true))
+Contingency(P::AbstractArray) = Contingency(P, Val(true))
 
-function Contingency(P::M, ::Val{true}) where {T,M<:AbstractMatrix{T}}
+function Contingency(P::M, ::Val{true}) where {T,M<:AbstractArray{T}}
  return Contingency{T,M}(P ./ sum(P))
 end
 
-Contingency(P::M, ::Val{false}) where {T,M<:AbstractMatrix{T}} = Contingency{T,M}(P)
+Contingency(P::M, ::Val{false}) where {T,M<:AbstractArray{T}} = Contingency{T,M}(P)
 
 BayesBase.components(distribution::Contingency) = distribution.p
 BayesBase.component(distribution::Contingency, k) = distribution.p[:, k]
 
-function BayesBase.vague(::Type{<:Contingency}, dims::Int)
- return Contingency(ones(dims, dims) ./ abs2(dims))
+function BayesBase.vague(::Type{<:Contingency}, dims::Int, nvars::Int=2)
+ return Contingency(ones([dims for _ in 1:nvars]...))
 end
 
 BayesBase.paramfloattype(distribution::Contingency) = deep_eltype(components(distribution))

test/densities/contingency_tests.jl

@@ -20,6 +20,10 @@ end
 
  @test typeof(d2) <: Contingency
  @test components(d2) ≈ ones(4, 4) ./ 16
+
+ d3 = vague(Contingency, 5, 3)
+ @test typeof(d3) <: Contingency
+ @test components(d3) ≈ ones(5, 5, 5) ./ 125
 end
 
 @testitem "Contingency: entropy" begin
@@ -31,6 +35,17 @@ end
  @test entropy(Contingency(10.0 * [0.09 0.00; 0.00 0.91])) ≈ 0.30253782309749805
  @test !isnan(entropy(Contingency([0.0 1.0; 1.0 0.0])))
  @test !isinf(entropy(Contingency([0.0 1.0; 1.0 0.0])))
+
+ @test entropy(
+ Contingency(
+ stack([
+ 0.3 * [0.2 0.1 0.7; 0.4 0.3 0.3; 0.1 0.6 0.3],
+ 0.7 * [0.2 0.1 0.7; 0.4 0.3 0.3; 0.1 0.6 0.3],
+ ],),
+ ),
+ ) ≈ 2.6390313416381166
+
+ @test entropy(Contingency(ones(2, 2, 2))) == 2.0794415416798357
 end
 
 @testitem "Contingency: isapprox" begin