public void AlphaOfMinimizerIsFound()
{
var theta = Vector<double>.Build.DenseOfArray(new[] {1.0D, 100.0D});
var x0 = Vector<double>.Build.DenseOfArray(new[] {-1.5D, 0.6D});
var rosenbrock = new RosenbrockHypothesis();
// evaluate at the point
var value = rosenbrock.Evaluate(theta, x0);
var gradient = rosenbrock.Jacobian(theta, x0);
// determine the initial search direction
var direction = -gradient.Normalize(2);
// create a wrapper cost function
var wrapper = new FunctionValueOptimization<double>(rosenbrock, theta);
// perform a line search
var lineSearch = new HagerZhangLineSearch();
var alpha = lineSearch.Minimize(wrapper, x0, direction, 0.0D);
alpha.Should().BeApproximately(0.235552763819095D, 1E-5D, "because that is the alpha value of the minimum along the search direction");
}
public void AlphaOfMinimizerIsFound()
{
var theta = Vector <double> .Build.DenseOfArray(new[] { 1.0D, 100.0D });
var x0 = Vector <double> .Build.DenseOfArray(new[] { -1.5D, 0.6D });
var rosenbrock = new RosenbrockHypothesis();
// evaluate at the point
var value = rosenbrock.Evaluate(theta, x0);
var gradient = rosenbrock.Jacobian(theta, x0);
// determine the initial search direction
var direction = -gradient.Normalize(2);
// create a wrapper cost function
var wrapper = new FunctionValueOptimization <double>(rosenbrock, theta);
// perform a line search
var lineSearch = new HagerZhangLineSearch();
var alpha = lineSearch.Minimize(wrapper, x0, direction, 0.0D);
alpha.Should().BeApproximately(0.235552763819095D, 1E-5D, "because that is the alpha value of the minimum along the search direction");
}
