basic Priors (#2)

* add Distributions and Random
* add Factored Distribution
* add tests
* remove test dependencies
* specialization for faster code
* add tests for mixed value support

.gitignore

@@ -3,3 +3,4 @@
 *.jl.mem
 /deps/deps.jl
 /docs/build
+Manifest.toml

Project.toml

@@ -4,12 +4,14 @@ authors = ["Johanni Brea <[email protected]>"]
 version = "0.1.0"
 
 [deps]
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+
+[compat]
+julia = "^1"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
 test = ["Test"]
-
-[compat]
-julia = "^1"

src/ApproxInferenceBase.jl

@@ -1,3 +1,5 @@
 module ApproxInferenceBase
-
+    using Distributions
+    using Random
+    include("priors.jl")
 end # module

src/priors.jl

@@ -0,0 +1,56 @@
+import Distributions.pdf, Distributions.logpdf, Random.rand, Base.length
+
+struct MixedSupport <: ValueSupport; end
+
+"""
+    Factored{N} <: Distribution{Multivariate, MixedSupport}
+
+a `Distribution` type that can be used to combine multiple `UnivariateDistribution`'s and sample from them.
+
+Example: it can be used as `prior = Factored(Normal(0,1), Uniform(-1,1))`
+"""
+struct Factored{N}<:Distribution{Multivariate,MixedSupport}
+    p::NTuple{N,UnivariateDistribution}
+    Factored(args::UnivariateDistribution...) = new{length(args)}(args)
+end
+"""
+    pdf(d::Factored, x) = begin
+
+Function to evaluate the pdf of a `Factored` distribution object
+"""
+function pdf(d::Factored{N},x) where N
+    s=pdf(d.p[1],x[1])
+    for i in 2:N
+        s*=pdf(d.p[i],x[i])
+    end
+    s
+end
+
+"""
+    logpdf(d::Factored, x) = begin
+
+Function to evaluate the logpdf of a `Factored` distribution object
+"""
+function logpdf(d::Factored{N},x) where N
+    s=logpdf(d.p[1],x[1])
+    for i in 2:N
+        s+=logpdf(d.p[i],x[i])
+    end
+    s
+end
+
+"""
+    rand(rng::AbstractRNG, factoreddist::Factored)
+
+function to sample one element from a `Factored` object
+"""
+rand(rng::AbstractRNG,factoreddist::Factored{N}) where N = ntuple(i->rand(rng,factoreddist.p[i]),Val(N))
+
+"""
+    length(p::Factored) = begin
+
+returns the number of distributions contained in `p`.
+"""
+length(p::Factored{N}) where N = N
+
+export Factored

test/runtests.jl

@@ -1,2 +1,20 @@
 using ApproxInferenceBase
 using Test
+using Distributions
+using Random
+
+@testset "Factored" begin
+    d=Factored(Uniform(0,1),Uniform(100,101))
+    @test all((0,100) .<= rand(d) .<= (1,101))
+    @test pdf(d,(0.0,0.0)) == 0.0
+    @test pdf(d,(0.5,100.5)) == 1.0
+    @test logpdf(d,(0.5,100.5)) == 0.0
+    @test logpdf(d,(0.0,0.0)) == -Inf
+    @test length(d) == 2
+    m=Factored(Uniform(0.00,1.0),DiscreteUniform(1,2))
+    sample=rand(m)
+    @test 0<sample[1]<1
+    @test sample[2] == 1 || sample[2] == 2
+    @test pdf(m,sample) == 0.5
+    @test logpdf(m,sample) ≈ log(0.5)
+end