mathnet-numerics/src/UnitTests/OptimizationTests/BfgsTest.cs

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using MathNet.Numerics.LinearAlgebra;
using MathNet.Numerics.LinearAlgebra.Double;
using MathNet.Numerics.Optimization;
using NUnit.Framework;

namespace MathNet.Numerics.UnitTests.OptimizationTests
{
    [TestFixture, Category("RootFinding")]
    internal class BfgsTest
    {
        private const double Precision = 1e-4;

        [Test]
        public void MinimizeRosenbrock()
        {
            CheckRosenbrock(15.0, 8.0, expectedMin: 0.0);
            CheckRosenbrock(-1.2, 1.0, expectedMin: 0.0);
            CheckRosenbrock(-1.2, 100.0, expectedMin: 0.0);
        }

        private static void CheckRosenbrock(double a, double b, double expectedMin)
        {
            var x = BfgsSolver.Solve(new DenseVector(new[] { a, b }), Rosenbrock, RosenbrockGradient);
            Numerics.Precision.AlmostEqual(expectedMin, Rosenbrock(x), Precision);
        }

        private static double Rosenbrock(Vector<double> x)
        {
            double t1 = (1 - x[0]);
            double t2 = (x[1] - x[0] * x[0]);
            return t1 * t1 + 100 * t2 * t2;
        }

        private static Vector<double> RosenbrockGradient(Vector<double> x)
        {
            var grad = new DenseVector(2);
            grad[0]  = -2 * (1 - x[0]) + 200 * (x[1] - x[0] * x[0]) * (-2 * x[0]);
            grad[1]  = 200 * (x[1] - x[0] * x[0]);
            return grad;
        }
    }
}