Merge 1d5b4fe into 2d846fe

Project.toml

@@ -7,6 +7,7 @@ Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
@@ -16,6 +17,7 @@ ZygoteRules = "700de1a5-db45-46bc-99cf-38207098b444"
 [compat]
 Compat = "2.2, 3"
 Distances = "0.8"
+MacroTools = "0.5"
 Requires = "1.0.1"
 SpecialFunctions = "0.8, 0.9, 0.10"
 StatsBase = "0.32"

src/KernelFunctions.jl

@@ -4,7 +4,7 @@ export kernelmatrix, kernelmatrix!, kerneldiagmatrix, kerneldiagmatrix!, kappa
 export transform
 export params, duplicate, set! # Helpers
 
-export Kernel
+export Kernel, BaseKernel, @kernel
 export ConstantKernel, WhiteKernel, ZeroKernel
 export SqExponentialKernel, ExponentialKernel, GammaExponentialKernel
 export ExponentiatedKernel
@@ -46,6 +46,7 @@ for k in ["exponential","matern","polynomial","constant","rationalquad","exponen
 end
 include("kernels/transformedkernel.jl")
 include("kernels/scaledkernel.jl")
+include("kernels/kernel_macro.jl")
 include("matrix/kernelmatrix.jl")
 include("kernels/kernelsum.jl")
 include("kernels/kernelproduct.jl")

src/generic.jl

@@ -11,8 +11,8 @@ _scale(t::ScaleTransform, metric::Euclidean, x, y) =  first(t.s) * evaluate(metr
 _scale(t::ScaleTransform, metric::Union{SqEuclidean,DotProduct}, x, y) =  first(t.s)^2 * evaluate(metric, x, y)
 _scale(t::ScaleTransform, metric, x, y) = evaluate(metric, apply(t, x), apply(t, y))
 
-printshifted(io::IO,κ::Kernel,shift::Int) = print(io,"$κ")
-Base.show(io::IO,κ::Kernel) = print(io,nameof(typeof(κ)))
+printshifted(io::IO, κ::Kernel, shift::Int) = print(io, "$κ")
+Base.show(io::IO, κ::Kernel) = print(io, nameof(typeof(κ)))
 
 ### Syntactic sugar for creating matrices and using kernel functions
 for k in subtypes(BaseKernel)

src/kernels/kernel_macro.jl

@@ -0,0 +1,24 @@
+using MacroTools: @capture
+
+"""
+
+"""
+macro kernel(expr::Expr,arg=nothing)
+    @capture(expr,(scale_*k_ | k_)) || throw(error("@kernel first arguments should be of the form `σ*Kernel()` or `Kernel()`"))
+    t = if @capture(arg,kw_=val_)
+        if kw == :l
+            val
+        elseif kw == :t
+            val
+        else
+            throw(error("The additional argument could not be intepreted. Please see documentation of `@kernel`"))
+        end
+    else
+        arg
+    end
+    if isnothing(scale)
+        return esc(:(transform($k,$t)))
+    else
+        return esc(:($scale*transform($k,$t)))
+    end
+end

src/kernels/transformedkernel.jl

@@ -3,6 +3,9 @@ struct TransformedKernel{Tk<:Kernel,Tr<:Transform} <: Kernel
     transform::Tr
 end
 
+function TransformedKernel(k::TransformedKernel,t::Transform)
+    TransformedKernel(kernel(k),t∘k.transform)
+end
 """
 ```julia
     transform(k::BaseKernel, t::Transform) (1)
@@ -15,11 +18,13 @@ end
 """
 transform
 
-transform(k::BaseKernel, t::Transform) = TransformedKernel(k, t)
+transform(k::Kernel, t::Transform) = TransformedKernel(k, t)
+
+transform(k::Kernel, ρ::Real) = TransformedKernel(k, ScaleTransform(ρ))
 
-transform(k::BaseKernel, ρ::Real) = TransformedKernel(k, ScaleTransform(ρ))
+transform(k::Kernel,ρ::AbstractVector) = TransformedKernel(k, ARDTransform(ρ))
 
-transform(k::BaseKernel,ρ::AbstractVector) = TransformedKernel(k, ARDTransform(ρ))
+transform(k::BaseKernel,::Nothing) = k
 
 kernel(κ) = κ.kernel
 

src/transform/ardtransform.jl

@@ -38,3 +38,5 @@ apply(t::ARDTransform,x::AbstractVector{<:Real};obsdim::Int=defaultobs) = t.v .*
 _transform(t::ARDTransform,X::AbstractMatrix{<:Real},obsdim::Int=defaultobs) = obsdim == 1 ? t.v'.*X : t.v .* X
 
 Base.isequal(t::ARDTransform,t2::ARDTransform) = isequal(t.v,t2.v)
+
+Base.show(io::IO, t::ARDTransform) = print(io,"ARD Transform, ρ = $(t.v)")

src/transform/chaintransform.jl

@@ -36,6 +36,13 @@ params(t::ChainTransform) = (params.(t.transforms))
 duplicate(t::ChainTransform,θ) = ChainTransform(duplicate.(t.transforms,θ))
 
 
-Base.:∘(t₁::Transform,t₂::Transform) = ChainTransform([t₂,t₁])
-Base.:∘(t::Transform,tc::ChainTransform) = ChainTransform(vcat(tc.transforms,t)) #TODO add test
-Base.:∘(tc::ChainTransform,t::Transform) = ChainTransform(vcat(t,tc.transforms))
+Base.:∘(t₁::Transform, t₂::Transform) = ChainTransform([t₂, t₁])
+Base.:∘(t::Transform, tc::ChainTransform) = ChainTransform(vcat(tc.transforms, t)) #TODO add test
+Base.:∘(tc::ChainTransform, t::Transform) = ChainTransform(vcat(t, tc.transforms))
+
+function Base.show(io::IO, tc::ChainTransform)
+    print(io,"Chain Transform : $(first(tc.transforms))")
+    for t in tc.transforms[2:end]
+        print(io, " |> $t")
+    end
+end

src/transform/scaletransform.jl

@@ -23,4 +23,4 @@ apply(t::ScaleTransform,x::AbstractVecOrMat;obsdim::Int=defaultobs) = first(t.s)
 
 Base.isequal(t::ScaleTransform,t2::ScaleTransform) = isequal(first(t.s),first(t2.s))
 
-Base.show(io::IO,t::ScaleTransform) = print(io,"Scale Transform s=$(first(t.s))")
+Base.show(io::IO,t::ScaleTransform) = print(io,"Scale Transform, s = $(first(t.s))")

src/transform/selecttransform.jl

@@ -41,3 +41,5 @@ function apply(t::SelectTransform, x::AbstractVector{<:Real}; obsdim::Int = defa
 end
 
 _transform(t::SelectTransform,X::AbstractMatrix{<:Real},obsdim::Int=defaultobs) = obsdim == 2 ? view(X,t.select,:) : view(X,:,t.select)
+
+Base.show(io::IO, t::SelectTransform) = print(io, "Selected Dimensions : $(t.select)")

src/transform/transform.jl

@@ -17,6 +17,10 @@ params(t::IdentityTransform) = nothing
 
 apply(t::IdentityTransform, x; obsdim::Int=defaultobs) = x #TODO add test
 
+Transform(ρ::Real) = ScaleTransform(ρ)
+Transform(ρ::AbstractVector) = ARDTransform(ρ)
+Transform(t::Transform) = t
+
 ### TODO Maybe defining adjoints could help but so far it's not working
 
 

test/runtests.jl

@@ -7,6 +7,7 @@ using Random
 include("test_kernelmatrix.jl")
 include("test_approximations.jl")
 include("test_constructors.jl")
+include("test_macro.jl")
 # include("test_AD.jl")
 include("test_transform.jl")
 include("test_distances.jl")

test/test_macro.jl

@@ -0,0 +1,12 @@
+using KernelFunctions
+using Test
+
+@testset "Kernel Macro" begin
+    @test (@kernel SqExponentialKernel()) isa SqExponentialKernel
+    @test (@kernel 3.0*SqExponentialKernel()) isa ScaledKernel{SqExponentialKernel,Float64}
+    @test (@kernel 3.0*SqExponentialKernel() l=3.0) isa ScaledKernel{TransformedKernel{SqExponentialKernel,ScaleTransform{Float64}},Float64}
+    @test (@kernel 3.0*SqExponentialKernel() 3.0) isa ScaledKernel{TransformedKernel{SqExponentialKernel,ScaleTransform{Float64}},Float64}
+    @test (@kernel 3.0*SqExponentialKernel() l=[3.0]) isa ScaledKernel{TransformedKernel{SqExponentialKernel,ARDTransform{Float64,1}},Float64}
+    @test (@kernel 3.0*SqExponentialKernel() LowRankTransform(rand(3,2))) isa ScaledKernel{TransformedKernel{SqExponentialKernel,LowRankTransform{Array{Float64,2}}},Float64}
+    @test (@kernel (3.0*SqExponentialKernel()+5.0*Matern32Kernel()) 3.0) isa TransformedKernel{KernelSum,ScaleTransform{Float64}}
+end