Function test_bound_solver_brown

dlib/test/optimization.cpp:1091–1141

    template <typename search_strategy_type>
    double test_bound_solver_brown (dlib::rand& rnd, search_strategy_type search_strategy)
    {
        using namespace dlib::test_functions;
        print_spinner();
        matrix<double,4,1> starting_point(4), lower(4), upper(4), x;

        const matrix<double,0,1> solution = brown_solution();

        // pick random bounds
        lower = rnd.get_random_gaussian(), rnd.get_random_gaussian(), rnd.get_random_gaussian(), rnd.get_random_gaussian();
        lower = lower*10 + solution;
        upper = rnd.get_random_gaussian(), rnd.get_random_gaussian(), rnd.get_random_gaussian(), rnd.get_random_gaussian();
        upper = upper*10 + solution;
        for (int i = 0; i < lower.size(); ++i)
        {
            if (upper(i) < lower(i)) 
                swap(upper(i),lower(i));
        }

        starting_point = rnd.get_random_double()*(upper(0)-lower(0))+lower(0), 
                       rnd.get_random_double()*(upper(1)-lower(1))+lower(1),
                       rnd.get_random_double()*(upper(2)-lower(2))+lower(2),
                       rnd.get_random_double()*(upper(3)-lower(3))+lower(3);

        dlog << LINFO << "lower: "<< trans(lower);
        dlog << LINFO << "upper: "<< trans(upper);
        dlog << LINFO << "starting: "<< trans(starting_point);

        // The contract for find_min_box_constrained() says we always call obj() before der().  So
        // these lambdas verify that this is so.
        dlib::matrix<double,0,1> last_x;
        auto obj = [&](const dlib::matrix<double,0,1> &x) { last_x = x; return brown(x); };
        auto der = [&](const dlib::matrix<double,0,1> &x) { 
            // check that obj(x) was called before der(x).
            DLIB_TEST_MSG(max(abs(x - last_x)) == 0, max(abs(x - last_x)));
            return brown_derivative(x); 
        };

        x = starting_point;
        double val = find_min_box_constrained( 
            search_strategy,
            objective_delta_stop_strategy(1e-16, 500), 
            obj, der, x,
            lower,  
            upper   
        );

        DLIB_TEST(std::abs(val - brown(x)) < 1e-14);
        dlog << LINFO << "brown solution:\n" << x;
        return unconstrained_gradient_magnitude(brown_derivative, x, lower, upper);
    }

    template <typename search_strategy_type>
    void test_box_constrained_optimizers(search_strategy_type search_strategy)