Testvalue (#208)

* minor reformatting

* require MeasureBase 0.10

* fix OrthoLebesgue

* IfElse

* bump version

Author: cscherrer

Project.toml

@@ -1,7 +1,7 @@
 name = "MeasureTheory"
 uuid = "eadaa1a4-d27c-401d-8699-e962e1bbc33b"
 authors = ["Chad Scherrer <[email protected]> and contributors"]
-version = "0.16.2"
+version = "0.16.3"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
@@ -57,7 +57,7 @@ LogExpFunctions = "0.3.3"
 MLStyle = "0.4"
 MacroTools = "0.5"
 MappedArrays = "0.4"
-MeasureBase = "0.9"
+MeasureBase = "0.10"
 NamedTupleTools = "0.13, 0.14"
 NestedTuples = "0.3"
 PositiveFactorizations = "0.2"

src/combinators/affine.jl

@@ -137,8 +137,20 @@ struct OrthoLebesgue{N,T} <: PrimitiveMeasure
     OrthoLebesgue(nt::NamedTuple{N,T}) where {N,T} = new{N,T}(nt)
 end
 
+params(d::OrthoLebesgue) = getfield(d, :par)
+
+Base.getproperty(d::OrthoLebesgue, s::Symbol) = getproperty(params(d), s)
+Base.propertynames(d::OrthoLebesgue) = propertynames(params(d))
+
+testvalue(d::OrthoLebesgue{(:μ, :σ)}) = d.μ
+testvalue(d::OrthoLebesgue{(:μ, :λ)}) = d.μ
+testvalue(d::OrthoLebesgue{(:μ,)}) = d.μ
+
+testvalue(d::OrthoLebesgue{(:σ,)}) = zeros(size(d.σ, 1))
+testvalue(d::OrthoLebesgue{(:λ,)}) = zeros(size(d.λ, 2))
+
 function insupport(d::OrthoLebesgue, x)
-    f = AffineTransform(d.par)
+    f = AffineTransform(params(d))
     finv = inverse(f)
     z = finv(x)
     f(z) ≈ x

test/runtests.jl

@@ -10,8 +10,8 @@ using FillArrays
 using MeasureTheory
 using MeasureBase.Interface
 using MeasureTheory: kernel
-
 using Aqua
+using IfElse
 Aqua.test_all(MeasureTheory; ambiguities = false, unbound_args = false)
 
 function draw2(μ)
@@ -611,10 +611,16 @@ end
 @testset "IfElseMeasure" begin
     p = rand()
     x = randn()
-    @test logdensityof(MeasureTheory.IfElse.ifelse(Bernoulli(p), Normal(), Normal()), x) ≈
-          logdensityof(Normal(), x)
-    @test logdensityof(
-        MeasureTheory.IfElse.ifelse(Bernoulli(p), Normal(2, 3), Normal()),
-        x,
-    ) ≈ logdensityof(p * Normal(2, 3) + (1 - p) * Normal(), x)
+    
+    @test let
+        a = logdensityof(IfElse.ifelse(Bernoulli(p), Normal(), Normal()), x)
+        b = logdensityof(Normal(), x)
+        a ≈ b
+    end
+
+    @test let
+        a = logdensityof(IfElse.ifelse(Bernoulli(p), Normal(2, 3), Normal()), x)
+        b = logdensityof(p * Normal(2, 3) + (1 - p) * Normal(), x)
+        a ≈ b
+    end
 end