/*
*	    Class MinimisationExample
*
*       An example of the use of the class Minimisation
*       and the interface MinimisationFunction
*
*       Finds the minimum of the function
*           z = a + x^2 + 3y^4
*       where a is constant
*       (an easily solved function has been chosen
*       for clarity and easy checking)
*
* 	    WRITTEN BY: Michael Thomas Flanagan
*
*	    DATE:   April 2004
*       UPDATE: June  2005
*
*       PERMISSION TO COPY:
* 	    Permission to use, copy and modify this software and its documentation
*	    for NON-COMMERCIAL purposes and without fee is hereby granted provided
*	    that an acknowledgement to the author, Michael Thomas Flanagan, and the
*	    disclaimer below, appears in all copies.
*
* 	    The author makes no representations or warranties about the suitability
*       or fitness of the software for any or for a particular purpose.
*       The author shall not be liable for any damages suffered as a result of
*       using, modifying or distributing this software or its derivatives.
*
**********************************************************/


import flanagan.math.*;

// Class to evaluate the function z = a + x^2 + 3y^4
// where a is fixed and the values of x and y
// (x[0] and x[1] in this method) are the
// current values in the minimisation method.
class MinimFunct implements MinimisationFunction{

    private double a = 0.0D;

    // evaluation function
    public double function(double[] x){
        double z = a + x[0]*x[0] +  3.0D*Math.pow(x[1], 4);
        return z;
    }

    // Method to set a
    public void setA(double a){
        this.a = a;
    }
}

// Class to demonstrate minimisation method, Minimisation nelderMead
public class MinimisationExample{

    public static void main(String[] args){

        //Create instance of Minimisation
        Minimisation min = new Minimisation();

        // Create instace of class holding function to be minimised
        MinimFunct funct = new MinimFunct();

        // Set value of the constant a to 5
        funct.setA(5.0D);

        // initial estimates
        double[] start = {1.0D, 3.0D};

        // initial step sizes
        double[] step = {0.2D, 0.6D};

        // convergence tolerance
        double ftol = 1e-15;

        // Nelder and Mead minimisation procedure
        min.nelderMead(funct, start, step, ftol);

        // get the minimum value
        double minimum = min.getMinimum();

        // get values of y and z at minimum
         double[] param = min.getParamValues();

        // Print results to a text file
        min.print("MinimExampleOutput.txt");

        // Output the results to screen
        System.out.println("Minimum = " + min.getMinimum());
        System.out.println("Value of x at the minimum = " + param[0]);
        System.out.println("Value of y at the minimum = " + param[1]);


    }
}