34.8 Examples

The following program uses the Brent algorithm to find the minimum of the function f(x) = \cos(x) + 1, which occurs at x = \pi. The starting interval is (0,6), with an initial guess for the minimum of 2.

     #include <stdio.h>
     #include <gsl/gsl_errno.h>
     #include <gsl/gsl_math.h>
     #include <gsl/gsl_min.h>
     
     double fn1 (double x, void * params)
     {
       return cos(x) + 1.0;
     }
     
     int
     main (void)
     {
       int status;
       int iter = 0, max_iter = 100;
       const gsl_min_fminimizer_type *T;
       gsl_min_fminimizer *s;
       double m = 2.0, m_expected = M_PI;
       double a = 0.0, b = 6.0;
       gsl_function F;
     
       F.function = &fn1;
       F.params = 0;
     
       T = gsl_min_fminimizer_brent;
       s = gsl_min_fminimizer_alloc (T);
       gsl_min_fminimizer_set (s, &F, m, a, b);
     
       printf ("using %s method\n",
               gsl_min_fminimizer_name (s));
     
       printf ("%5s [%9s, %9s] %9s %10s %9s\n",
               "iter", "lower", "upper", "min",
               "err", "err(est)");
     
       printf ("%5d [%.7f, %.7f] %.7f %+.7f %.7f\n",
               iter, a, b,
               m, m - m_expected, b - a);
     
       do
         {
           iter++;
           status = gsl_min_fminimizer_iterate (s);
     
           m = gsl_min_fminimizer_x_minimum (s);
           a = gsl_min_fminimizer_x_lower (s);
           b = gsl_min_fminimizer_x_upper (s);
     
           status 
             = gsl_min_test_interval (a, b, 0.001, 0.0);
     
           if (status == GSL_SUCCESS)
             printf ("Converged:\n");
     
           printf ("%5d [%.7f, %.7f] "
                   "%.7f %+.7f %.7f\n",
                   iter, a, b,
                   m, m - m_expected, b - a);
         }
       while (status == GSL_CONTINUE && iter < max_iter);
     
       gsl_min_fminimizer_free (s);
     
       return status;
     }

Here are the results of the minimization procedure.

     $ ./a.out
         0 [0.0000000, 6.0000000] 2.0000000 -1.1415927 6.0000000
         1 [2.0000000, 6.0000000] 3.2758640 +0.1342713 4.0000000
         2 [2.0000000, 3.2831929] 3.2758640 +0.1342713 1.2831929
         3 [2.8689068, 3.2831929] 3.2758640 +0.1342713 0.4142862
         4 [2.8689068, 3.2831929] 3.2758640 +0.1342713 0.4142862
         5 [2.8689068, 3.2758640] 3.1460585 +0.0044658 0.4069572
         6 [3.1346075, 3.2758640] 3.1460585 +0.0044658 0.1412565
         7 [3.1346075, 3.1874620] 3.1460585 +0.0044658 0.0528545
         8 [3.1346075, 3.1460585] 3.1460585 +0.0044658 0.0114510
         9 [3.1346075, 3.1460585] 3.1424060 +0.0008133 0.0114510
        10 [3.1346075, 3.1424060] 3.1415885 -0.0000041 0.0077985
     Converged:                            
        11 [3.1415885, 3.1424060] 3.1415927 -0.0000000 0.0008175