more tests

test/nested_ad_tests.jl

@@ -1,4 +1,4 @@
-using Integrals, ForwardDiff, Cubature, Test
+using Integrals, ForwardDiff, Cubature, Cuba, Test
 
 my_parameters = [1.0, 2.0]
 my_function(x, p) = x^2 + p[1]^3 * x + p[2]^2
@@ -11,3 +11,36 @@ my_solution = my_integration(my_parameters)
 @test ForwardDiff.jacobian(my_integration, my_parameters) == [0.0 8.0]
 @test ForwardDiff.jacobian(x->ForwardDiff.jacobian(my_integration, x), my_parameters) == [0.0 0.0
                                                                                           0.0 4.0]
+
+ff(x,p) = sum(sin.(x .* p))
+lb = ones(2)
+ub = 3ones(2)
+p = [1.5,2.0]
+
+function testf(p)
+    prob = IntegralProblem(ff,lb,ub,p)
+    sin(solve(prob,CubaCuhre(),reltol=1e-6,abstol=1e-6)[1])
+end
+
+hp1 = FiniteDiff.finite_difference_hessian(testf,p)
+hp2 = ForwardDiff.hessian(testf,p)
+@test hp1 ≈ hp2 atol=1e-4
+
+ff2(x,p) = x*p[1].+p[2]*p[3]
+lb =1.0
+ub = 3.0
+p = [2.0, 3.0, 4.0]
+_ff3 = BatchIntegralFunction(ff2)
+prob = IntegralProblem(_ff3,lb,ub,p)
+
+function testf3(lb,ub,p; f=_ff3)
+    prob = IntegralProblem(_ff3,lb,ub,p)
+    solve(prob, CubatureJLh(); reltol=1e-3,abstol=1e-3)[1]
+end
+
+dp1 = ForwardDiff.gradient(p->testf3(lb,ub,p),p)
+dp2 = Zygote.gradient(p->testf3(lb,ub,p),p)[1]
+dp3 = FiniteDiff.finite_difference_gradient(p->testf3(lb,ub,p),p)
+
+@test dp1 ≈ dp3
+@test dp2 ≈ dp3