Create runtests.jl

Added basic tests for the gradient descent code in OptimizationODE.jl

Author: ParasPuneetSingh

lib/OptimizationODE/test/runtests.jl

@@ -0,0 +1,45 @@
+using Test
+using Optimization
+using Optimization.SciMLBase
+using OptimizationODE
+
+@testset "ODEGradientDescent Tests" begin
+
+    # Define the Rosenbrock objective and its gradient
+    function rosen(u, p)
+        return (p[1] - u[1])^2 + p[2] * (u[2] - u[1]^2)^2
+    end
+
+    function rosen_grad!(g, u, p, data)
+        g[1] = -2 * (p[1] - u[1]) - 4 * p[2] * u[1] * (u[2] - u[1]^2)
+        g[2] =  2 * p[2] * (u[2] - u[1]^2)
+        return g
+    end
+
+    # Set up the problem
+    u0 = [0.0, 0.0]
+    p  = [1.0, 100.0]
+
+    # Wrap into an OptimizationFunction without AD, providing our gradient
+    f = OptimizationFunction(
+        rosen,
+        Optimization.SciMLBase.NoAD();
+        grad = rosen_grad!
+    )
+
+    prob = OptimizationProblem(f, u0, p)
+
+    # Solve with ODEGradientDescent 
+    sol = solve(
+        prob,
+        ODEGradientDescent();
+        η    = 0.001,
+        tmax = 1_000.0,
+        dt   = 0.01
+    )
+
+    # Assertions 
+    @test isapprox(sol.u[1], 1.0; atol = 1e-2)
+    @test isapprox(sol.u[2], 1.0; atol = 1e-2)
+
+end