public MinimizationResult FindMinimum(Func <Vector <double>, double> objectiveFunction, Vector <double> initialGuess)
{
var lowerBound = Vector <double> .Build.Dense(initialGuess.Count, Double.NegativeInfinity);
var upperBound = Vector <double> .Build.Dense(initialGuess.Count, Double.PositiveInfinity);
var objective = ObjectiveFunction.Value(objectiveFunction);
var objectiveFunctionWithGradient = new ForwardDifferenceGradientObjectiveFunction(objective, lowerBound, upperBound, RelativeIncrement, MinimumIncrement);
var bfgsMinimizer = new BfgsMinimizer(GradientTolerance, ParameterTolerance, FunctionProgressTolerance, MaximumIterations);
return(bfgsMinimizer.FindMinimum(objectiveFunctionWithGradient, initialGuess));
}
public void Mgh_FiniteDifference_Tests(TestFunctions.TestCase test_case)
{
var obj1 = new MghObjectiveFunction(test_case.Function, true, true);
var obj = new ForwardDifferenceGradientObjectiveFunction(obj1, test_case.LowerBound, test_case.UpperBound, 1e-10, 1e-10);
var solver = new BfgsBMinimizer(1e-8, 1e-8, 1e-8, 10000);
var result = solver.FindMinimum(obj, test_case.LowerBound, test_case.UpperBound, test_case.InitialGuess);
if (test_case.MinimizingPoint != null)
{
Assert.That((result.MinimizingPoint - test_case.MinimizingPoint).L2Norm(), Is.LessThan(1e-3));
}
var val1 = result.FunctionInfoAtMinimum.Value;
var val2 = test_case.MinimalValue;
var abs_min = Math.Min(Math.Abs(val1), Math.Abs(val2));
var abs_err = Math.Abs(val1 - val2);
var rel_err = abs_err / abs_min;
var success = (abs_min <= 1 && abs_err < 1e-3) || (abs_min > 1 && rel_err < 1e-3);
Assert.That(success, "Minimal function value is not as expected.");
}
public void BfgsMinimizer_MinimizesProperlyWhenConstrainedInOneVariable()
{
// Test comes from github issue 510
// https://github.com/mathnet/mathnet-numerics/issues/510
Func <Vector <double>, double> function = (Vector <double> vectorArg) =>
{
double x = vectorArg[0];
double y = -1.0 * Math.Exp(-x * x);
return(y);
};
double gradientTolerance = 1e-10;
double parameterTolerance = 1e-10;
double functionProgressTolerance = 1e-10;
int maxIterations = 1000;
var initialGuess = new DenseVector(new[] { -1.0 });
// Bad Bound
var lowerBound = new DenseVector(new[] { -2.0 });
var upperBound = new DenseVector(new[] { 2.0 });
var objective = ObjectiveFunction.Value(function);
var objectiveWithGradient = new ForwardDifferenceGradientObjectiveFunction(objective, lowerBound, upperBound);
var algorithm = new BfgsBMinimizer(gradientTolerance, parameterTolerance, functionProgressTolerance, maxIterations);
var result = algorithm.FindMinimum(objectiveWithGradient, lowerBound, upperBound, initialGuess);
var resultVector = result.MinimizingPoint;
double xResult = resultVector[0];
// (actual minimum at zero)
var abs_err = Math.Abs(xResult);
var success = abs_err < 1e-6;
Assert.That(success, "Minimal function value is not as expected.");
}
