trying the traits thing

Author: cscherrer

Project.toml

@@ -13,6 +13,7 @@ MLStyle = "d8e11817-5142-5d16-987a-aa16d5891078"
 MappedArrays = "dbb5928d-eab1-5f90-85c2-b9b0edb7c900"
 NamedTupleTools = "d9ec5142-1e00-5aa0-9d6a-321866360f50"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+SimpleTraits = "699a6c99-e7fa-54fc-8d76-47d257e15c1d"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 TransformVariables = "84d833dd-6860-57f9-a1a7-6da5db126cff"
 
@@ -23,6 +24,7 @@ KeywordCalls = "0.1.3"
 MLStyle = "0.4"
 MappedArrays = "0.4"
 NamedTupleTools = "0.13"
+SimpleTraits = "0.9"
 julia = "1.3"
 
 [extras]

src/MeasureBase.jl

@@ -6,6 +6,7 @@ using Random
 using ConcreteStructs
 using MLStyle
 using KeywordCalls
+using SimpleTraits
 using Compat
 
 export ≪

src/absolutecontinuity.jl

@@ -68,7 +68,7 @@ not, it should be a  transform (`Pushforward` or `Pullback`) of a
 function representative(μ)
     function f(μ)
         # Check if we're done
-        isprimitive(μ) && return μ
+        isprimtype(μ) && return μ
         ν = basemeasure(μ)
         return ν
     end

src/primitives.jl

@@ -1,23 +1,22 @@
-abstract type PrimitiveMeasure <: AbstractMeasure end
-
-export isprimitive
-
 """
-    isprimitive(μ)
+    isprimtype(μ)
 
 Most measures are defined in terms of other measures, for example using a
 density or a pushforward. Those that are not are considered (in this library,
 it's not a general measure theory thing) to be _primitive_. The canonical
 example of a primitive measure is `Lebesgue(X)` for some `X`.
 
 The default method is
-    isprimitive(μ) = false
+    isprimtype(μ) = false
 
 So when adding a new primitive measure, it's necessary to add a method for its type
 that returns `true`.
 """
-isprimitive(μ) = false
-isprimitive(::PrimitiveMeasure) = true
+function isprimtype end
+
+@traitdef IsPrimType{X}
+@traitdef IsPrimType{X} <- isprimtype(X)
+isprimtype(X) = false # default
 
 export basemeasure
 
@@ -31,9 +30,17 @@ For measures not defined in this way, we'll typically have `basemeasure(μ) == 
 """
 function basemeasure end
 
-basemeasure(μ::PrimitiveMeasure) = μ
+basemeasure(μ::M) where {IsPrimType{M}} = μ
 
 include("primitives/trivial.jl")
 include("primitives/lebesgue.jl")
 include("primitives/counting.jl")
 include("primitives/dirac.jl")
+
+@traitdef IsRepType{X}
+
+@traitimpl IsRepType{X} <- isreptype(X)
+isreptype(X) = false # set default
+
+# Every primitive measure is also a representative
+isreptype(μ::M) where {IsPrimType{M}} = true

src/primitives/counting.jl

@@ -1,6 +1,8 @@
 export CountingMeasure
 
-struct CountingMeasure{X} <: PrimitiveMeasure end
+struct CountingMeasure{X} <: AbstractMeasure end
+
+isprimtype(::CountingMeasure) = true
 
 function Base.show(io::IO, μ::CountingMeasure{X}) where {X}
     io = IOContext(io, :compact => true)

src/primitives/dirac.jl

@@ -1,17 +1,19 @@
 
 export Dirac
 
-struct Dirac{X} <: PrimitiveMeasure
+struct Dirac{X} <: AbstractMeasure
     x::X
 end
 
+isprimtype(::Dirac) = true
+
 sampletype(μ::Dirac{X}) where {X} = X
 
 function (μ::Dirac{X})(s) where {X}
     μ.x ∈ s && return 1
     return 0
 end
-isprimitive(::Dirac) = true
+isprimtype(::Dirac) = true
 
 logdensity(μ::Dirac, x) = (x == μ.x) ? 0.0 : -Inf
 

src/primitives/lebesgue.jl

@@ -2,7 +2,9 @@
 
 export Lebesgue
 
-struct Lebesgue{X} <: PrimitiveMeasure end
+struct Lebesgue{X} <: AbstractMeasure end
+
+isprimtype(::Lebesgue) = true
 
 function Base.show(io::IO, μ::Lebesgue{X}) where X
     io = IOContext(io, :compact => true)

src/primitives/primitives.jl

@@ -1,5 +1,7 @@
 export TrivialMeasure
 
-struct TrivialMeasure <: PrimitiveMeasure end
+struct TrivialMeasure <: AbstractMeasure end
+
+isprimtype(::TrivialMeasure) = true
 
 sampletype(::TrivialMeasure) = Nothing