Merge branch 'cs-mb-0.14' into dev

JuliaMath · Aug 22, 2023 · 744c4a4 · 744c4a4
2 parents 5a25a51 + 07074d6
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diff --git a/.github/workflows/Breakage.yml b/.github/workflows/Breakage.yml
@@ -15,8 +15,8 @@ jobs:
       fail-fast: false
       matrix:
         pkg: [
-          "cscherrer/Soss.jl",
-          "mschauer/Mitosis.jl"
+          # "cscherrer/Soss.jl",
+          # "mschauer/Mitosis.jl"
         ]
         pkgversion: [latest, stable]
 

diff --git a/CITATION.bib b/CITATION.bib
@@ -1,7 +1,7 @@
 @misc{MeasureTheory.jl,
 	author  = {Chad Scherrer <chad.scherrer@gmail.com> and contributors},
 	title   = {MeasureTheory.jl},
-	url     = {https://github.com/cscherrer/MeasureTheory.jl},
+	url     = {https://github.com/JuliaMath/MeasureTheory.jl},
 	version = {v0.2.2},
 	year    = {2021},
 	month   = {1}

diff --git a/Project.toml b/Project.toml
@@ -47,7 +47,8 @@ ConcreteStructs = "0.2"
 ConstructionBase = "1.3"
 DensityInterface = "0.4"
 Distributions = "0.25"
-FillArrays = "0.12, 0.13"
+DynamicIterators = "0.4"
+FillArrays = "1"
 ForwardDiff = "0.10"
 IfElse = "0.1"
 Infinities = "0.1"
@@ -63,11 +64,11 @@ PositiveFactorizations = "0.2"
 PrettyPrinting = "0.3, 0.4"
 Reexport = "1"
 SpecialFunctions = "1, 2"
-Static = "0.5, 0.6"
+Static = "0.8"
 StaticArraysCore = "1"
-StatsBase = "0.32, 0.33"
+StatsBase = "0.34"
 StatsFuns = "0.9, 1"
-TransformVariables = "0.5, 0.6, 0.7"
+TransformVariables = "0.8"
 Tricks = "0.1"
 julia = "1.6"
 

diff --git a/README.md b/README.md
@@ -1,9 +1,9 @@
 # MeasureTheory
 
-[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://cscherrer.github.io/MeasureTheory.jl/stable)
-[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://cscherrer.github.io/MeasureTheory.jl/dev)
-[![Build Status](https://github.com/cscherrer/MeasureTheory.jl/workflows/CI/badge.svg)](https://github.com/cscherrer/MeasureTheory.jl/actions)
-[![Coverage](https://codecov.io/gh/cscherrer/MeasureTheory.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/cscherrer/MeasureTheory.jl)
+[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaMath.github.io/MeasureTheory.jl/stable)
+[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://JuliaMath.github.io/MeasureTheory.jl/dev)
+[![Build Status](https://github.com/JuliaMath/MeasureTheory.jl/workflows/CI/badge.svg)](https://github.com/JuliaMath/MeasureTheory.jl/actions)
+[![Coverage](https://codecov.io/gh/JuliaMath/MeasureTheory.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaMath/MeasureTheory.jl)
 [![DOI](https://proceedings.juliacon.org/papers/10.21105/jcon.00092/status.svg)](https://doi.org/10.21105/jcon.00092)
 
 `MeasureTheory.jl` is a package for building and reasoning about measures.
@@ -21,15 +21,15 @@ To install `MeasureTheory.jl`, open the Julia Pkg REPL (by typing `]` in the sta
 pkg> add MeasureTheory
 ```
 
-To get an idea of the possibilities offered by this package, go to the [documentation](https://cscherrer.github.io/MeasureTheory.jl/stable).
+To get an idea of the possibilities offered by this package, go to the [documentation](https://JuliaMath.github.io/MeasureTheory.jl/stable).
 
 
 
 ## Coordination and support
 
 For interaction and shorter usage questions, there is the dedicated channel [#measuretheory on Julia's Zulip chat julialang.zulipchat.com](https://julialang.zulipchat.com/#narrow/stream/259730-measuretheory.2Ejl) and the #measuretheory channel on the [Julia language Slack chat](https://julialang.org/slack/) and for broader discussions [Julia's discourse forum](https://discourse.julialang.org).
 
-Development takes place on Github with [Github's issue ticker](https://github.com/cscherrer/MeasureTheory.jl/issues) for bug reports and coordination.
+Development takes place on Github with [Github's issue ticker](https://github.com/JuliaMath/MeasureTheory.jl/issues) for bug reports and coordination.
 
 We adhere to the [community standards set forward by the Julia community.](https://julialang.org/community/standards/)
 
@@ -39,4 +39,4 @@ We adhere to the [community standards set forward by the Julia community.](https
 
 ## Stargazers over time
 
-[![Stargazers over time](https://starchart.cc/cscherrer/MeasureTheory.jl.svg)](https://starchart.cc/cscherrer/MeasureTheory.jl)
+[![Stargazers over time](https://starchart.cc/JuliaMath/MeasureTheory.jl.svg)](https://starchart.cc/JuliaMath/MeasureTheory.jl)
diff --git a/docs/make.jl b/docs/make.jl
@@ -20,7 +20,7 @@ pages = [
 makedocs(;
     modules = [MeasureBase, MeasureTheory],
     authors = "Chad Scherrer <[email protected]> and contributors",
-    repo = "https://github.com/cscherrer/MeasureTheory.jl/blob/{commit}{path}#L{line}",
+    repo = "https://github.com/JuliaMath/MeasureTheory.jl/blob/{commit}{path}#L{line}",
     sitename = "MeasureTheory.jl",
     format = Documenter.HTML(;
         prettyurls = get(ENV, "CI", "false") == "true",
@@ -30,4 +30,4 @@ makedocs(;
     pages = pages,
 )
 
-deploydocs(; repo = "github.com/cscherrer/MeasureTheory.jl")
+deploydocs(; repo = "github.com/JuliaMath/MeasureTheory.jl")
diff --git a/docs/src/old_readme.md b/docs/src/old_readme.md
@@ -2,10 +2,10 @@
 
 [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://cscherrer.github.io/MeasureTheory.jl/stable)
 [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://cscherrer.github.io/MeasureTheory.jl/dev)
-[![Build Status](https://github.com/cscherrer/MeasureTheory.jl/workflows/CI/badge.svg)](https://github.com/cscherrer/MeasureTheory.jl/actions)
-[![Coverage](https://codecov.io/gh/cscherrer/MeasureTheory.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/cscherrer/MeasureTheory.jl)
+[![Build Status](https://github.com/JuliaMath/MeasureTheory.jl/workflows/CI/badge.svg)](https://github.com/JuliaMath/MeasureTheory.jl/actions)
+[![Coverage](https://codecov.io/gh/JuliaMath/MeasureTheory.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaMath/MeasureTheory.jl)
 
-Check out our [JuliaCon submission](https://github.com/cscherrer/MeasureTheory.jl/blob/paper/paper/paper.pdf)
+Check out our [JuliaCon submission](https://github.com/JuliaMath/MeasureTheory.jl/blob/paper/paper/paper.pdf)
 
 `MeasureTheory.jl` is a package for building and reasoning about measures.
 

diff --git a/src/MeasureTheory.jl b/src/MeasureTheory.jl
@@ -8,7 +8,6 @@ using MLStyle
 import TransformVariables
 const TV = TransformVariables
 
-# using DistributionMeasures
 using TransformVariables: asℝ₊, as𝕀, asℝ, transform
 
 import Base
@@ -122,6 +121,10 @@ xlog1py(x::Number, y::Number) = LogExpFunctions.xlog1py(x, y)
 xlog1py(x, y) = x * log(1 + y)
 
 using MeasureBase: Φ, Φinv
+as(args...; kwargs...) = TV.as(args...; kwargs...)
+
+# Type piracy until https://github.com/JuliaMath/MeasureBase.jl/issues/127 is fixed
+MeasureBase.rand(::FixedRNG, ::Type{Bool}) = true
 
 include("utils.jl")
 include("const.jl")

diff --git a/src/distributions.jl b/src/distributions.jl
@@ -39,4 +39,3 @@ function as(d::Dists.Product, _data::NamedTuple = NamedTuple())
     as(Vector, as(v[1]), n)
 end
 
-# as(m::DistributionMeasures.DistributionMeasure) = as(m.d)
diff --git a/src/parameterized.jl b/src/parameterized.jl
@@ -162,8 +162,6 @@ function as(d::ProductMeasure{<:Base.Generator})
     as(Array, as(d1), size(marginals(d))...)
 end
 
-as(args...; kwargs...) = TV.as(args...; kwargs...)
-
 as(::Beta) = as𝕀
 as(::Cauchy) = asℝ
 as(d::Dirichlet{(:α,)}) = TV.UnitSimplex(length(d.α))

diff --git a/src/parameterized/binomial.jl b/src/parameterized/binomial.jl
@@ -22,8 +22,8 @@ end
     x ∈ (0, 1)
 end
 
-function Base.rand(rng::AbstractRNG, ::Type, d::Binomial{(:n, :p)})
-    rand(rng, Dists.Binomial(d.n, d.p))
+function Base.rand(rng::AbstractRNG, ::Type{T}, d::Binomial{(:n, :p)}) where {T}
+    rand(rng, T, Dists.Binomial(d.n, d.p))
 end
 
 Binomial(n) = Binomial(n, 0.5)

diff --git a/src/parameterized/cauchy.jl b/src/parameterized/cauchy.jl
@@ -27,6 +27,7 @@ function density_def(d::Cauchy{()}, x)
 end
 
 Base.rand(rng::AbstractRNG, T::Type, μ::Cauchy{()}) = randn(rng, T) / randn(rng, T)
+
 Base.rand(::FixedRNG, ::Type{T}, ::Cauchy{()}) where {T} = zero(T)
 
 for N in AFFINEPARS
@@ -45,6 +46,8 @@ end
 
 HalfCauchy(σ) = HalfCauchy(σ = σ)
 
+Base.rand(::FixedRNG, ::Type{T}, μ::Half{<:Cauchy}) where {T} = one(T)
+
 insupport(::Cauchy, x) = true
 
 function smf(::Cauchy{()}, x)

diff --git a/src/parameterized/gumbel.jl b/src/parameterized/gumbel.jl
@@ -29,7 +29,7 @@ end
 import Base
 
 function Base.rand(rng::AbstractRNG, ::Type{T}, d::Gumbel{()}) where {T}
-    u = rand(rng)
+    u = rand(rng, T)
     -log(-log(u))
 end
 

diff --git a/src/parameterized/lkj-cholesky.jl b/src/parameterized/lkj-cholesky.jl
@@ -53,7 +53,7 @@ logdensity_def(d::LKJCholesky, C::Cholesky) = logdensity_def(d, C.UL)
     # z = diag(L)
     # sum(log.(z) .* ((k:-1:1) .+ 2*(η-1)))
 
-    # Note: https://github.com/cscherrer/MeasureTheory.jl/issues/100#issuecomment-852428192
+    # Note: https://github.com/JuliaMath/MeasureTheory.jl/issues/100#issuecomment-852428192
     c = d.k + 2(η - 1)
     n = size(L, 1)
     s = sum(1:n) do i

diff --git a/src/resettable-rng.jl b/src/resettable-rng.jl
@@ -57,6 +57,14 @@ for T in vcat(subtypes(Signed), subtypes(Unsigned), subtypes(AbstractFloat))
     end
 end
 
+function Base.rand(r::ResettableRNG, d::AbstractMeasure)
+    rand(r.rng, d)
+end
+
+function Base.rand(r::ResettableRNG, ::Type{T}, d::AbstractMeasure) where {T}
+    rand(r.rng, T, d)
+end
+
 Base.iterate(r::ResettableRNG) = iterate(r, nothing)
 
 function Base.iterate(r::ResettableRNG, ::Nothing)

diff --git a/src/transforms/corrcholesky.jl b/src/transforms/corrcholesky.jl
@@ -30,9 +30,9 @@ function TV.transform_with(flag::TV.LogJacFlag, t::CorrCholesky, x::AbstractVect
     return Cholesky(U, 'U', 0), ℓ, index
 end
 
-TV.inverse_eltype(t::CorrCholesky, x::AbstractMatrix) = TV.extended_eltype(x)
+TV.inverse_eltype(t::CorrCholesky, x::AbstractMatrix) = eltype(x)
 
-TV.inverse_eltype(t::CorrCholesky, x::Cholesky) = TV.extended_eltype(x)
+TV.inverse_eltype(t::CorrCholesky, x::Cholesky) = eltype(x)
 
 function TV.inverse_at!(x::AbstractVector, index, t::CorrCholesky, L::LowerTriangular)
     return TV.inverse_at!(x, index, CorrCholeskyUpper(t.n), L')

diff --git a/src/transforms/corrcholeskylower.jl b/src/transforms/corrcholeskylower.jl
@@ -38,7 +38,7 @@ function TV.transform_with(
     return U', ℓ, index
 end
 
-TV.inverse_eltype(t::CorrCholeskyLower, L::LowerTriangular) = TV.extended_eltype(L)
+TV.inverse_eltype(t::CorrCholeskyLower, L::LowerTriangular) = eltype(L)
 
 function TV.inverse_at!(x::AbstractVector, index, t::CorrCholeskyLower, L::LowerTriangular)
     return TV.inverse_at!(x, index, CorrCholeskyUpper(t.n), L')

diff --git a/src/transforms/ordered.jl b/src/transforms/ordered.jl
@@ -49,7 +49,7 @@ function TV.transform_with(flag::TV.LogJacFlag, t::Ordered, x, index::T) where {
     return (y, ℓ, index)
 end
 
-TV.inverse_eltype(t::Ordered, y::AbstractVector) = TV.extended_eltype(y)
+TV.inverse_eltype(t::Ordered, y::AbstractVector) = eltype(y)
 
 Ordered(n::Int) = Ordered(asℝ, n)
 

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -73,7 +73,6 @@ test_measures = Any[
     MvNormal(σ = σ)
     MvNormal(λ = λ)
     Uniform()
-    # Counting(Float64)
     Dirac(0.0) + Normal()
 ]
 
@@ -104,6 +103,10 @@ end
         @test ℓ ≈ logdensity_def(Binomial(; n, logitp), y)
         @test ℓ ≈ logdensity_def(Binomial(; n, probitp), y)
 
+        rng = ResettableRNG(Random.MersenneTwister())
+        @test rand(rng, Binomial(n=0, p=1.0)) == 0
+        @test rand(rng, Binomial(n=10, p=1.0)) == 10
+
         @test_broken logdensity_def(Binomial(n, p), CountingBase(ℤ[0:n]), x) ≈
                      binomlogpdf(n, p, x)
     end
@@ -298,7 +301,7 @@ using DynamicIterators: trace, TimeLift
 
 @testset "rootmeasure/logpdf" begin
     x = rand(Normal())
-    @test log𝒹(Normal(), rootmeasure(Normal()))(x) ≈ logdensityof(Normal(), x)
+    @test logdensity_rel(Normal(), rootmeasure(Normal()), x) ≈ logdensityof(Normal(), x)
 end
 
 @testset "Transforms" begin
@@ -465,45 +468,26 @@ end
     end
 end
 
-@testset "Density measures and Radon-Nikodym" begin
-    x = randn()
-    # let d = ∫(𝒹(Cauchy(), Normal()), Normal())
-    #     @test logdensity_rel(𝒹(d, Cauchy()), x) ≈ 0 atol = 1e-12
-    # end
-
-    let f = 𝒹(∫(x -> x^2, Normal()), Normal())
-        @test f(x) ≈ x^2
-    end
-
-    # let d = ∫exp(log𝒹(Cauchy(), Normal()), Normal())
-    #     @test logdensity_rel(d, Cauchy(), x) ≈ 0 atol=1e-12
-    # end
-
-    let f = log𝒹(∫exp(x -> x^2, Normal()), Normal())
-        @test f(x) ≈ x^2
-    end
-end
-
 @testset "Half measures" begin
     @testset "HalfNormal" begin
         d = Normal(σ = 3)
         h = HalfNormal(3)
         x = rand(h)
-        @test density_rel(h, Lebesgue(ℝ), x) ≈ 2 * density_rel(d, Lebesgue(ℝ), x)
+        @test densityof(h, x) ≈ 2 * densityof(d, x)
     end
 
     @testset "HalfCauchy" begin
         d = Cauchy(σ = 3)
         h = HalfCauchy(3)
         x = rand(h)
-        @test density_rel(h, Lebesgue(ℝ), x) ≈ 2 * density_rel(d, Lebesgue(ℝ), x)
+        @test densityof(h, x) ≈ 2 * densityof(d, x)
     end
 
     @testset "HalfStudentT" begin
         d = StudentT(ν = 2, σ = 3)
         h = HalfStudentT(2, 3)
         x = rand(h)
-        @test density_rel(h, Lebesgue(ℝ), x) ≈ 2 * density_rel(d, Lebesgue(ℝ), x)
+        @test densityof(h, x) ≈ 2 * densityof(d, x)
     end
 end
 
@@ -642,7 +626,7 @@ end
     end
 end
 
-@testset "https://github.com/cscherrer/MeasureTheory.jl/issues/217" begin
+@testset "https://github.com/JuliaMath/MeasureTheory.jl/issues/217" begin
     d = For(rand(3), rand(3)) do x, y
         Normal(x, y)
     end
Original file line number	Diff line number	Diff line change
Expand Up		@@ -39,4 +39,3 @@ function as(d::Dists.Product, _data::NamedTuple = NamedTuple())
		as(Vector, as(v[1]), n)
		end

		# as(m::DistributionMeasures.DistributionMeasure) = as(m.d)