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35.4 Providing a function to minimize

You must provide a parametric function of n variables for the minimizers to operate on. You may also need to provide a routine which calculates the gradient of the function and a third routine which calculates both the function value and the gradient together. In order to allow for general parameters the functions are defined by the following data types:

Data Type: gsl_multimin_function_fdf

This data type defines a general function of n variables with parameters and the corresponding gradient vector of derivatives,

double (* f) (const gsl_vector * x, void * params)

this function should return the result f(x,params) for argument x and parameters params. If the function cannot be computed, an error value of GSL_NAN should be returned.

void (* df) (const gsl_vector * x, void * params, gsl_vector * g)

this function should store the n-dimensional gradient result g_i = d f(x,params) / d x_i in the vector g for argument x and parameters params, returning an appropriate error code if the function cannot be computed.

void (* fdf) (const gsl_vector * x, void * params, double * f, gsl_vector * g)

This function should set the values of the f and g as above, for arguments x and parameters params. This function provides an optimization of the separate functions for f(x) and g(x)---it is always faster to compute the function and its derivative at the same time.

size_t n

the dimension of the system, i.e. the number of components of the vectors x.

void * params

a pointer to the parameters of the function.

Data Type: gsl_multimin_function

This data type defines a general function of n variables with parameters,

double (* f) (const gsl_vector * x, void * params)

this function should return the result f(x,params) for argument x and parameters params. If the function cannot be computed, an error value of GSL_NAN should be returned.

size_t n

the dimension of the system, i.e. the number of components of the vectors x.

void * params

a pointer to the parameters of the function.

The following example function defines a simple two-dimensional paraboloid with five parameters,

/* Paraboloid centered on (p[0],p[1]), with  
   scale factors (p[2],p[3]) and minimum p[4] */

double
my_f (const gsl_vector *v, void *params)
{
  double x, y;
  double *p = (double *)params;
  
  x = gsl_vector_get(v, 0);
  y = gsl_vector_get(v, 1);
 
  return p[2] * (x - p[0]) * (x - p[0]) +
           p[3] * (y - p[1]) * (y - p[1]) + p[4]; 
}

/* The gradient of f, df = (df/dx, df/dy). */
void 
my_df (const gsl_vector *v, void *params, 
       gsl_vector *df)
{
  double x, y;
  double *p = (double *)params;
  
  x = gsl_vector_get(v, 0);
  y = gsl_vector_get(v, 1);
 
  gsl_vector_set(df, 0, 2.0 * p[2] * (x - p[0]));
  gsl_vector_set(df, 1, 2.0 * p[3] * (y - p[1]));
}

/* Compute both f and df together. */
void 
my_fdf (const gsl_vector *x, void *params, 
        double *f, gsl_vector *df) 
{
  *f = my_f(x, params); 
  my_df(x, params, df);
}

The function can be initialized using the following code,

gsl_multimin_function_fdf my_func;

/* Paraboloid center at (1,2), scale factors (10, 20), 
   minimum value 30 */
double p[5] = { 1.0, 2.0, 10.0, 20.0, 30.0 }; 

my_func.n = 2;  /* number of function components */
my_func.f = &my_f;
my_func.df = &my_df;
my_func.fdf = &my_fdf;
my_func.params = (void *)p;