also likelihood<->kernel

src/Mitosis.jl

@@ -38,6 +38,7 @@ include("mt.jl")
 export Gaussian, conditional, marginal, Copy, fuse, weighted
 export Traced, BFFG, left′, right′, forward, backward, backwardfilter, forwardsampler
 export BF, density, logdensity, ⊕, kernel, correct, Kernel, WGaussian, Gaussian, ConstantMap, AffineMap, LinearMap, GaussKernel
+export likelihood
 
 function independent_sum
 end

src/gauss.jl

@@ -139,4 +139,11 @@ end
 
 function marginal(p::Gaussian{(:μ, :Σ)}, A)
     Gaussian{(:μ, :Σ)}(p.μ[A], p.Σ[A,A])
+end
+
+function likelihood(k::AffineGaussianKernel, obs)
+    q = backward(BFFG(), k, obs; unfused=true)[2].y
+    F, Γ, c =  params(q)
+    c0 = Mitosis.logdensity0(Gaussian{(:F,:Γ)}(F, Γ))
+    WGaussian{(:F,:Γ, :c)}(F, Γ, c - c0)
 end

test/gauss.jl

@@ -36,4 +36,9 @@ end
     π = marginal(q, 1:d1)
     k = conditional(q, d1+1:d, 1:d1)
     @test k(π) ≈ marginal(q, d1+1:d)
+    x = rand(π)
+    obs = rand(k(x))
+
+    @test logdensity(k(x), obs) ≈ logdensity(likelihood(k, obs), x) 
+
 end