Standard-measures (#56)

Add `StdUniform`, `StdNormal`, `StdExponential`

Author: cscherrer

Project.toml

@@ -1,14 +1,15 @@
 name = "MeasureBase"
 uuid = "fa1605e6-acd5-459c-a1e6-7e635759db14"
 authors = ["Chad Scherrer <[email protected]> and contributors"]
-version = "0.9.2"
+version = "0.9.3"
 
 [deps]
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 ConstructionBase = "187b0558-2788-49d3-abe0-74a17ed4e7c9"
 DensityInterface = "b429d917-457f-4dbc-8f4c-0cc954292b1d"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 IfElse = "615f187c-cbe4-4ef1-ba3b-2fcf58d6d173"
+IrrationalConstants = "92d709cd-6900-40b7-9082-c6be49f344b6"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogExpFunctions = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
 LogarithmicNumbers = "aa2f6b4e-9042-5d33-9679-40d3a6b85899"
@@ -28,6 +29,7 @@ ConstructionBase = "1.3"
 DensityInterface = "0.4"
 FillArrays = "0.12, 0.13"
 IfElse = "0.1"
+IrrationalConstants = "0.1"
 LogExpFunctions = "0.3"
 LogarithmicNumbers = "1"
 MappedArrays = "0.4"
@@ -40,9 +42,6 @@ julia = "1.3"
 
 [extras]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
-Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test", "Aqua", "LinearAlgebra", "Statistics"]
+test = ["Aqua"]

src/MeasureBase.jl

@@ -1,7 +1,5 @@
 module MeasureBase
 
-const logtwo = log(2.0)
-
 using Random
 import Random: rand!
 import Random: gentype
@@ -94,6 +92,8 @@ function logdensity_def end
 
 using Compat
 
+using IrrationalConstants
+
 include("schema.jl")
 include("splat.jl")
 include("proxies.jl")
@@ -124,6 +124,10 @@ include("combinators/smart-constructors.jl")
 include("combinators/powerweighted.jl")
 include("combinators/conditional.jl")
 
+include("standard/stdnormal.jl")
+include("standard/stduniform.jl")
+include("standard/stdexponential.jl")
+
 include("rand.jl")
 
 include("density.jl")

src/combinators/half.jl

@@ -12,7 +12,7 @@ end
 unhalf(μ::Half) = μ.parent
 
 @inline function basemeasure(μ::Half)
-    weightedmeasure(static(logtwo), basemeasure(unhalf(μ)))
+    weightedmeasure(logtwo, basemeasure(unhalf(μ)))
 end
 
 function Base.rand(rng::AbstractRNG, ::Type{T}, μ::Half) where {T}

src/combinators/smart-constructors.jl

@@ -80,7 +80,7 @@ superpose(nt::NamedTuple) = SuperpositionMeasure(nt)
 
 function superpose(μ::T, ν::T) where {T<:AbstractMeasure}
     if μ == ν
-        return weightedmeasure(static(logtwo), μ)
+        return weightedmeasure(logtwo, μ)
     else
         return superpose((μ, ν))
     end
@@ -127,7 +127,7 @@ function kernel(d::PowerMeasure)
 end
 
 function kernel(f)
-    T = Core.Compiler.return_type(f, Tuple{Any} )
+    T = Core.Compiler.return_type(f, Tuple{Any})
     _kernel(f, T)
 end
 

src/density.jl

@@ -100,7 +100,6 @@ Define a new measure in terms of a log-density `f` over some measure `base`.
 """
 ∫exp(f::Function, μ) = ∫(logfuncdensity(f), μ)
 
-
 """
     logdensityof(m::AbstractMeasure, x) 
 

src/kernel.jl

@@ -76,7 +76,6 @@ end
 
 (k::AbstractTransitionKernel)(; kwargs...) = k(NamedTuple(kwargs))
 
-
 """
 For any `k::TransitionKernel`, `basekernel` is expected to satisfy
 ```
@@ -107,7 +106,6 @@ function Pretty.tile(k::K) where {K<:AbstractTransitionKernel}
     )
 end
 
-
 const kleisli = kernel
 
 export kleisli

src/standard/stdexponential.jl

@@ -0,0 +1,12 @@
+struct StdExponential <: AbstractMeasure end
+
+export StdExponential
+
+insupport(d::StdExponential, x) = x ≥ zero(x)
+
+@inline logdensity_def(::StdExponential, x) = -x
+@inline basemeasure(::StdExponential) = Lebesgue()
+
+function Base.rand(rng::Random.AbstractRNG, ::Type{T}, ::StdExponential) where {T}
+    randexp(rng, T)
+end

src/standard/stdnormal.jl

@@ -0,0 +1,11 @@
+struct StdNormal <: AbstractMeasure end
+
+export StdNormal
+
+insupport(d::StdNormal, x) = true
+insupport(d::StdNormal) = Returns(true)
+
+@inline logdensity_def(::StdNormal, x) = -x^2 / 2
+@inline basemeasure(::StdNormal) = WeightedMeasure(static(-0.5 * log2π), Lebesgue(ℝ))
+
+Base.rand(rng::Random.AbstractRNG, ::Type{T}, ::StdNormal) where {T} = randn(rng, T)

src/standard/stduniform.jl

@@ -0,0 +1,10 @@
+struct StdUniform <: AbstractMeasure end
+
+export StdUniform
+
+insupport(d::StdUniform, x) = zero(x) ≤ x ≤ one(x)
+
+@inline logdensity_def(::StdUniform, x) = zero(x)
+@inline basemeasure(::StdUniform) = Lebesgue()
+
+Base.rand(rng::Random.AbstractRNG, ::Type{T}, ::StdUniform) where {T} = randn(rng, T)

test/runtests.jl

@@ -37,6 +37,31 @@ test_measures = [
     Dirac(0) + Dirac(1)
     Dirac(0.0) + Lebesgue(ℝ)
     SpikeMixture(Lebesgue(ℝ), 0.2)
+
+    StdNormal()
+    StdNormal()^3
+    StdNormal()^(2, 3)
+    3 * StdNormal()
+    0.2 * StdNormal() + 0.8 * Dirac(0.0)
+    Dirac(0.0) + StdNormal()
+    SpikeMixture(StdNormal(), 0.2)
+
+    StdUniform()
+    StdUniform()^3
+    StdUniform()^(2, 3)
+    3 * StdUniform()
+    0.2 * StdUniform() + 0.8 * Dirac(0.0)
+    Dirac(0.0) + StdUniform()
+    SpikeMixture(StdUniform(), 0.2)
+
+    StdExponential()^3
+    StdExponential()^(2, 3)
+    3 * StdExponential()
+    StdExponential()
+    0.2 * StdExponential() + 0.8 * Dirac(0.0)
+    Dirac(0.0) + StdExponential()
+    SpikeMixture(StdExponential(), 0.2)
+
     # d ⊙ d
 ]