package com.imsl.test.example.math;

import com.imsl.math.*;

/**
 * <p>
 * Solves a small linear system with the Generalized Minimum Residual (GMRES)
 * method.
 * </p>
 *
 * A solution to a small linear system is found. The coefficient matrix is
 * stored as a full matrix and no preconditioning is used. Typically,
 * preconditioning is required to achieve convergence in a reasonable number of
 * iterations.
 *
 * @see <a href="GenMinResEx1.java">Code</a>
 * @see <a href="doc-files/GenMinResEx1.out">Output</a>
 */
public class GenMinResEx1 implements GenMinRes.Function {

    // If A were to be read in from some outside source the
    // code to read the matrix could reside in a constructor.
    static private double a[][] = {
        {33.0, 16.0, 72.0},
        {-24.0, -10.0, -57.0},
        {18.0, -11.0, 7.0}
    };
    static private double b[] = {129.0, -96.0, 8.5};

    /**
     * Obtains the multiplication of the matrix <code>a</code> and the input
     * <code>p</code>. The result is returned in <code>z</code>.
     *
     * @param p a <code>double</code> array with
     * <code>p.length</code>=<code>a[0].length</code>
     * @param z a <code>double</code> array
     */
    @Override
    public void amultp(double p[], double z[]) {
        double[] result;
        result = Matrix.multiply(a, p);
        System.arraycopy(result, 0, z, 0, z.length);
    }

    public static void main(String args[]) throws Exception {
        int n = 3;

        GenMinResEx1 atp = new GenMinResEx1();

        // Construct a GenMinRes object
        GenMinRes gnmnrs = new GenMinRes(n, atp);

        // Solve Ax = b
        new PrintMatrix("x").print(gnmnrs.solve(b));
    }
}