Fix KMM coefficient and add tests

src/kmm.jl

@@ -29,4 +29,4 @@ Kernel Mean Matching (KMM).
   λ::T=0.0
 end
 
-default_optlib(dre::Type{<:KMM}) = JuMPLib
+default_optlib(dre::Type{<:KMM}) = JuliaLib

src/kmm/julia.jl

@@ -19,5 +19,5 @@ function _densratio(x_nu, x_de, dre::KMM, optlib::Type{JuliaLib})
   Kdenu = gaussian_gramian(x_de, x_nu, σ=σ)
 
   # closed-form solution (without constraints)
-  (n_de / n_nu) * (Kdede + λ*I) \ vec(sum(Kdenu, dims=2))
+  (n_de / n_nu) * ((Kdede + λ*I) \ vec(sum(Kdenu, dims=2)))
 end

test/basic.jl

@@ -8,26 +8,5 @@
     G = DensityRatioEstimation.gaussian_gramian(x_nu, x_nu, σ=2.0)
     @test issymmetric(G)
     @test all(G .> 0)
-
-    # features can be any indexable
-    x_nu = [(a=1.,b=2.),(a=3.,b=4.)]
-    x_de = [(a=1.,b=2.),(a=3.,b=4.),(a=5.,b=6.)]
-    G = DensityRatioEstimation.gaussian_gramian(x_nu, x_de)
-    @test size(G) == (2, 3)
-    @test all(G .> 0)
-  end
-
-  for (d_nu, d_de) in [pair₁, pair₂]
-    Random.seed!(123)
-    x_nu, x_de = rand(d_nu, 100), rand(d_de, 200)
-    @testset "$dre -- $optlib" for (dre, optlib) in [(KMM(),   JuMPLib),
-                                                     (KLIEP(), OptimLib),
-                                                     (KLIEP(), ConvexLib)]
-
-      r = densratio(x_nu, x_de, dre, optlib=optlib)
-
-      # density ratios must be positive
-      @test all(r .> 0)
-    end
   end
 end

test/kliep.jl

@@ -1,15 +1,26 @@
-@testset "KLIEP" begin
-  for (i, pair) in enumerate([pair₁, pair₂])
+@testset "KLIEP -- $optlib" for optlib in [OptimLib, ConvexLib]
+  for (i, pair, rtol_correctness) in zip(1:2, [pair₁, pair₂], (2e-1, 4e-1))
     d_nu, d_de = pair
     Random.seed!(123)
-    x_nu, x_de = rand(d_nu, 1000), rand(d_de, 500)
+    x_nu, x_de = rand(d_nu, 1_000), rand(d_de, 500)
 
     # estimated density ratio
-    r̂ = densratio(x_nu, x_de, KLIEP(σ=1.0, b=100))
+    σ, b = 1.0, 100
+    r̂ = densratio(x_nu, x_de, KLIEP(σ=σ, b=b), optlib=optlib)
+
+    # density ratios must be positive
+    @test all(r̂ .> 0)
+
+    # simplex constraints
+    @test abs(mean(r̂) - 1) ≤ 1e-2
+    @test all(r̂ .≤ Inf)
+
+    r = pdf.(d_nu, x_de) ./ pdf.(d_de, x_de)
+    @test r ≈ r̂ rtol=rtol_correctness
 
     if visualtests
-      gr(size=(800,800))
-      @plottest plot_d_nu(pair,x_de,r̂) joinpath(datadir,"KLIEP-$i.png") !istravis
+      gr(size=(800, 800))
+      @plottest plot_d_nu(pair, x_de, r̂) joinpath(datadir, "KLIEP-$optlib-$i.png") !istravis
     end
   end
 end

test/kmm.jl

@@ -1,19 +1,29 @@
-@testset "KMM" begin
-  d_nu, d_de = pair₁
+@testset "KMM -- $optlib" for optlib in [JuliaLib, JuMPLib]
+  for (i, pair) in enumerate([pair₁, pair₂])
+    d_nu, d_de = pair
+    Random.seed!(123)
+    x_nu, x_de = rand(d_nu, 2_000), rand(d_de, 1_000)
 
-  Random.seed!(123)
-  x_nu, x_de = rand(d_nu, 2000), rand(d_de, 1000)
+    # estimated density ratio
+    σ, B, ϵ, λ = 1.5, Inf, 0.01, 0.001
+    r̂ = densratio(x_nu, x_de, KMM(σ=σ, B=B, ϵ=ϵ,  λ=λ), optlib=optlib)
 
-  # estimated density ratio
-  σ, B, ϵ = 1.0, Inf, 0.01
-  r̂ = densratio(x_nu, x_de, KMM(σ=σ, B=B, ϵ=ϵ))
+    # density ratios must be positive
+    optlib == JuMPLib && @test all(r̂ .> 0)
 
-  # simplex constraints
-  @test abs(mean(r̂) - 1) ≤ ϵ
-  @test all(r̂ .≤ B)
+    # simplex constraints
+    @test abs(mean(r̂) - 1) ≤ 1e-2
+    @test all(r̂ .≤ B)
 
-  if visualtests
-    gr(size=(800,800))
-    @plottest plot_d_nu(pair₁,x_de,r̂) joinpath(datadir,"KMM.png") !istravis
+    if i == 1 # FIXME: only check correctness for the Gaussian case now
+      # compare against true ratio
+      r = pdf.(d_nu, x_de) ./ pdf.(d_de, x_de)
+      @test r ≈ r̂ rtol=2e-1
+    end
+
+    if visualtests
+      gr(size=(800, 800))
+      @plottest plot_d_nu(pair, x_de, r̂) joinpath(datadir, "KMM-$optlib-$i.png") !istravis
+    end
   end
 end