Class RosenbrockFunction

JSAT/src/jsat/math/optimization/RosenbrockFunction.java:17–101

The Rosenbrock function is a function with at least one minima with the value zero. It is often used as a benchmark for optimization problems. The minima is the vector of all ones. Once N %gt; 3, more then one minima can occur. @author Edward Raff

 * @author Edward Raff
 */
public class RosenbrockFunction implements Function
{

	private static final long serialVersionUID = -5573482950045304948L;

	@Override
    public double f(double... x)
    {
        return f(DenseVector.toDenseVec(x));
    }

    @Override
    public double f(Vec x)
    {
        int N = x.length();
        double f = 0.0;
        for(int i = 1; i < N; i++)
        {
            double x_p = x.get(i-1);
            double xi = x.get(i);
            f += pow(1.0-x_p, 2)+100.0*pow(xi-x_p*x_p, 2);
        }
        
        return f;
    }
    
    /**
     * Returns the gradient of the Rosenbrock function
     * @return the gradient of the Rosenbrock function
     */
    public FunctionVec getDerivative()
    {
        return GRADIENT;
    }
    
    /**
     * The gradient of the Rosenbrock function
     */
    public static final FunctionVec GRADIENT = new FunctionVec()
    {
        @Override
        public Vec f(double... x)
        {
            return f(DenseVector.toDenseVec(x));
        }

        @Override
        public Vec f(Vec x)
        {
            Vec s = x.clone();
            f(x, s);
            return s;
        }

        @Override
        public Vec f(Vec x, Vec drv)
        {
            int N = x.length();