Update optimizationsystem.jl

Author: ChrisRackauckas

test/optimizationsystem.jl

@@ -63,18 +63,22 @@ sol = solve(prob, AmplNLWriter.Optimizer(Ipopt_jll.amplexe))
 
 #equality constraint, lcons == ucons
 cons2 = [0.0 ~ x^2 + y^2]
+out = zeros(1)
 sys2 = OptimizationSystem(loss, [x, y], [a, b], name = :sys2, constraints = cons2)
 prob = OptimizationProblem(sys2, [x => 0.0, y => 0.0], [a => 1.0, b => 1.0], lcons = [1.0],
                            ucons = [1.0], grad = true, hess = true)
 sol = solve(prob, IPNewton())
 @test sol.minimum < 1.0
-@test prob.f.cons(sol.minimizer, [1.0, 1.0]) ≈ [1.0]
+prob.f.cons(out, sol.minimizer, [1.0, 1.0])
+@test out ≈ [1.0]
 sol = solve(prob, Ipopt.Optimizer())
 @test sol.minimum < 1.0
-@test prob.f.cons(sol.minimizer, [1.0, 1.0]) ≈ [1.0]
+prob.f.cons(out, sol.minimizer, [1.0, 1.0])
+@test out ≈ [1.0]
 sol = solve(prob, AmplNLWriter.Optimizer(Ipopt_jll.amplexe))
 @test sol.minimum < 1.0
-@test prob.f.cons(sol.minimizer, [1.0, 1.0]) ≈ [1.0]
+prob.f.cons(out, sol.minimizer, [1.0, 1.0])
+@test out ≈ [1.0]
 
 rosenbrock(x, p) = (p[1] - x[1])^2 + p[2] * (x[2] - x[1]^2)^2
 x0 = zeros(2)