### 34.10 Examples

For any root finding algorithm we need to prepare the function to be solved. For this example we will use the general quadratic equation described earlier. We first need a header file (`demo_fn.h`) to define the function parameters,

    struct quadratic_params
      {
        double a, b, c;
      };

    double quadratic (double x, void *params);
    double quadratic_deriv (double x, void *params);
    void quadratic_fdf (double x, void *params,
                        double *y, double *dy);

We place the function definitions in a separate file (`demo_fn.c`),

    double
    quadratic (double x, void *params)
    {
      struct quadratic_params *p
        = (struct quadratic_params *) params;

      double a = p->a;
      double b = p->b;
      double c = p->c;

      return (a * x + b) * x + c;
    }

    double
    quadratic_deriv (double x, void *params)
    {
      struct quadratic_params *p
        = (struct quadratic_params *) params;

      double a = p->a;
      double b = p->b;

      return 2.0 * a * x + b;
    }

    void
    quadratic_fdf (double x, void *params,
                   double *y, double *dy)
    {
      struct quadratic_params *p
        = (struct quadratic_params *) params;

      double a = p->a;
      double b = p->b;
      double c = p->c;

      *y = (a * x + b) * x + c;
      *dy = 2.0 * a * x + b;
    }

The first program uses the function solver `gsl_root_fsolver_brent` for Brent’s method and the general quadratic defined above to solve the following equation,

    x^2 - 5 = 0

with solution x = \sqrt 5 = 2.236068...

    #include <stdio.h>
    #include <gsl/gsl_errno.h>
    #include <gsl/gsl_math.h>
    #include <gsl/gsl_roots.h>

    #include "demo_fn.h"
    #include "demo_fn.c"

    int
    main (void)
    {
      int status;
      int iter = 0, max_iter = 100;
      const gsl_root_fsolver_type *T;
      gsl_root_fsolver *s;
      double r = 0, r_expected = sqrt (5.0);
      double x_lo = 0.0, x_hi = 5.0;
      gsl_function F;
      struct quadratic_params params = {1.0, 0.0, -5.0};

      F.function = &quadratic;
      F.params = &params;

      T = gsl_root_fsolver_brent;
      s = gsl_root_fsolver_alloc (T);
      gsl_root_fsolver_set (s, &F, x_lo, x_hi);

      printf ("using %s method\n",
              gsl_root_fsolver_name (s));

      printf ("%5s [%9s, %9s] %9s %10s %9s\n",
              "iter", "lower", "upper", "root",
              "err", "err(est)");

      do
        {
          iter++;
          status = gsl_root_fsolver_iterate (s);
          r = gsl_root_fsolver_root (s);
          x_lo = gsl_root_fsolver_x_lower (s);
          x_hi = gsl_root_fsolver_x_upper (s);
          status = gsl_root_test_interval (x_lo, x_hi,
                                           0, 0.001);

          if (status == GSL_SUCCESS)
            printf ("Converged:\n");

          printf ("%5d [%.7f, %.7f] %.7f %+.7f %.7f\n",
                  iter, x_lo, x_hi,
                  r, r - r_expected,
                  x_hi - x_lo);
        }
      while (status == GSL_CONTINUE && iter < max_iter);

      gsl_root_fsolver_free (s);

      return status;
    }

Here are the results of the iterations,

    $ ./a.out
    using brent method
     iter [    lower,     upper]      root        err  err(est)
        1 [1.0000000, 5.0000000] 1.0000000 -1.2360680 4.0000000
        2 [1.0000000, 3.0000000] 3.0000000 +0.7639320 2.0000000
        3 [2.0000000, 3.0000000] 2.0000000 -0.2360680 1.0000000
        4 [2.2000000, 3.0000000] 2.2000000 -0.0360680 0.8000000
        5 [2.2000000, 2.2366300] 2.2366300 +0.0005621 0.0366300
    Converged:
        6 [2.2360634, 2.2366300] 2.2360634 -0.0000046 0.0005666

If the program is modified to use the bisection solver instead of Brent’s method, by changing `gsl_root_fsolver_brent` to `gsl_root_fsolver_bisection` the slower convergence of the Bisection method can be observed,

    $ ./a.out
    using bisection method
     iter [    lower,     upper]      root        err  err(est)
        1 [0.0000000, 2.5000000] 1.2500000 -0.9860680 2.5000000
        2 [1.2500000, 2.5000000] 1.8750000 -0.3610680 1.2500000
        3 [1.8750000, 2.5000000] 2.1875000 -0.0485680 0.6250000
        4 [2.1875000, 2.5000000] 2.3437500 +0.1076820 0.3125000
        5 [2.1875000, 2.3437500] 2.2656250 +0.0295570 0.1562500
        6 [2.1875000, 2.2656250] 2.2265625 -0.0095055 0.0781250
        7 [2.2265625, 2.2656250] 2.2460938 +0.0100258 0.0390625
        8 [2.2265625, 2.2460938] 2.2363281 +0.0002601 0.0195312
        9 [2.2265625, 2.2363281] 2.2314453 -0.0046227 0.0097656
       10 [2.2314453, 2.2363281] 2.2338867 -0.0021813 0.0048828
       11 [2.2338867, 2.2363281] 2.2351074 -0.0009606 0.0024414
    Converged:
       12 [2.2351074, 2.2363281] 2.2357178 -0.0003502 0.0012207

The next program solves the same function using a derivative solver instead.

    #include <stdio.h>
    #include <gsl/gsl_errno.h>
    #include <gsl/gsl_math.h>
    #include <gsl/gsl_roots.h>

    #include "demo_fn.h"
    #include "demo_fn.c"

    int
    main (void)
    {
      int status;
      int iter = 0, max_iter = 100;
      const gsl_root_fdfsolver_type *T;
      gsl_root_fdfsolver *s;
      double x0, x = 5.0, r_expected = sqrt (5.0);
      gsl_function_fdf FDF;
      struct quadratic_params params = {1.0, 0.0, -5.0};

      FDF.f = &quadratic;
      FDF.df = &quadratic_deriv;
      FDF.fdf = &quadratic_fdf;
      FDF.params = &params;

      T = gsl_root_fdfsolver_newton;
      s = gsl_root_fdfsolver_alloc (T);
      gsl_root_fdfsolver_set (s, &FDF, x);

      printf ("using %s method\n",
              gsl_root_fdfsolver_name (s));

      printf ("%-5s %10s %10s %10s\n",
              "iter", "root", "err", "err(est)");
      do
        {
          iter++;
          status = gsl_root_fdfsolver_iterate (s);
          x0 = x;
          x = gsl_root_fdfsolver_root (s);
          status = gsl_root_test_delta (x, x0, 0, 1e-3);

          if (status == GSL_SUCCESS)
            printf ("Converged:\n");

          printf ("%5d %10.7f %+10.7f %10.7f\n",
                  iter, x, x - r_expected, x - x0);
        }
      while (status == GSL_CONTINUE && iter < max_iter);

      gsl_root_fdfsolver_free (s);
      return status;
    }

Here are the results for Newton’s method,

    $ ./a.out
    using newton method
    iter        root        err   err(est)
        1  3.0000000 +0.7639320 -2.0000000
        2  2.3333333 +0.0972654 -0.6666667
        3  2.2380952 +0.0020273 -0.0952381
    Converged:
        4  2.2360689 +0.0000009 -0.0020263

Note that the error can be estimated more accurately by taking the difference between the current iterate and next iterate rather than the previous iterate. The other derivative solvers can be investigated by changing `gsl_root_fdfsolver_newton` to `gsl_root_fdfsolver_secant` or `gsl_root_fdfsolver_steffenson`.