import

test/gauss.jl

@@ -0,0 +1,50 @@
+  function J_gauss(p::Vector{Float64}; x::Float64=0.0)
+    λ, μ, σ = p
+    c = [1 / λ (2 * (x - μ) / σ^2) (-1 + 2 * ((x - μ) / σ)^2) / σ]
+    return c .* gauss(p; x=x)
+  end
+
+  function H_gauss(p::Vector{Float64}; x::Float64=0.0)
+    λ, μ, σ = p
+    c = zeros(3, 3)
+
+    # c[1,1] = 0
+    c[1, 2] = c[2, 1] = (2x) / (λ * σ^2) - (2 * μ) / (λ * σ^2)
+    c[1, 3] = c[3, 1] = (2 * (x - μ)^2 - σ^2) / (λ * σ^3)
+
+    c[2, 2] = (4 * (x - μ)^2 - 2 * σ^2) / σ^4
+    c[2, 3] = c[3, 2] = (2λ * (x - μ) * (2μ^2 - 3σ^2 + 2x^2 - 4μ * x)) / (λ * σ^5)
+
+    c[3, 3] = (2 * (σ^4 - 5σ^2 * (x - μ)^2 + 2 * (x - μ)^4)) / σ^6
+    return c .* gauss(p; x=x)
+  end
+
+@testset "Gauss function" begin
+  λ = 10 * (rand() - 0.5)
+  μ = 10 * (rand() - 0.5)
+  σ = 10rand()
+
+  x = σ * (2 * rand() - 0.5) + μ
+  p = [λ, μ, σ]
+
+  @test TaylorTest.check(gauss, J_gauss, p; x=x)
+  @test TaylorTest.check(J_gauss, H_gauss, p; x=x)
+end
+
+@testset "Composed Gauss function" begin
+  p = 1 .+ 5 * rand(6)
+
+  x = p[3] + p[4] + 2p[5] + sqrt(p[6]) * (2rand() - 1)
+
+  p_aux = _p -> [_p[1]/_p[2], _p[3] + _p[4] + 2_p[5], _p[6]]
+
+  J_p_aux = _p -> [1/_p[2] -_p[1]/_p[2]^2 0 0 0 0;
+                           0            0 1 1 2 0;
+                           0            0 0 0 0 1]
+
+  g = (_p; x=x) -> gauss(p_aux(_p); x=x)
+  Jg = (_p; x=x) -> J_gauss(p_aux(_p); x=x) * J_p_aux(p)
+  Hg = (_p; x=x) -> J_gauss(p_aux(_p); x=x) * J_p_aux(p)
+
+  @test TaylorTest.check(g, Jg, p; x=x)
+end