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<title>Providing a function to minimize - GNU Scientific Library -- Reference Manual</title>
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<h3 class="section">35.4 Providing a function to minimize</h3>

<p>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:

<div class="defun">
&mdash; Data Type: <b>gsl_multimin_function_fdf</b><var><a name="index-gsl_005fmultimin_005ffunction_005ffdf-2335"></a></var><br>
<blockquote><p>This data type defines a general function of n variables with
parameters and the corresponding gradient vector of derivatives,

          <dl>
<dt><code>double (* f) (const gsl_vector * </code><var>x</var><code>, void * </code><var>params</var><code>)</code><dd>this function should return the result
<!-- {$f(x,\hbox{\it params})$} -->
f(x,params) for argument <var>x</var> and parameters <var>params</var>.

          <br><dt><code>void (* df) (const gsl_vector * </code><var>x</var><code>, void * </code><var>params</var><code>, gsl_vector * </code><var>g</var><code>)</code><dd>this function should store the <var>n</var>-dimensional gradient
<!-- {$g_i = \partial f(x,\hbox{\it params}) / \partial x_i$} -->
g_i = d f(x,params) / d x_i in the vector <var>g</var> for argument <var>x</var>
and parameters <var>params</var>, returning an appropriate error code if the
function cannot be computed.

          <br><dt><code>void (* fdf) (const gsl_vector * </code><var>x</var><code>, void * </code><var>params</var><code>, double * f, gsl_vector * </code><var>g</var><code>)</code><dd>This function should set the values of the <var>f</var> and <var>g</var> as above,
for arguments <var>x</var> and parameters <var>params</var>.  This function
provides an optimization of the separate functions for f(x) and
g(x)&mdash;it is always faster to compute the function and its
derivative at the same time.

          <br><dt><code>size_t n</code><dd>the dimension of the system, i.e. the number of components of the
vectors <var>x</var>.

          <br><dt><code>void * params</code><dd>a pointer to the parameters of the function. 
</dl>
        </p></blockquote></div>

<div class="defun">
&mdash; Data Type: <b>gsl_multimin_function</b><var><a name="index-gsl_005fmultimin_005ffunction-2336"></a></var><br>
<blockquote><p>This data type defines a general function of n variables with
parameters,

          <dl>
<dt><code>double (* f) (const gsl_vector * </code><var>x</var><code>, void * </code><var>params</var><code>)</code><dd>this function should return the result
<!-- {$f(x,\hbox{\it params})$} -->
f(x,params) for argument <var>x</var> and parameters <var>params</var>.

          <br><dt><code>size_t n</code><dd>the dimension of the system, i.e. the number of components of the
vectors <var>x</var>.

          <br><dt><code>void * params</code><dd>a pointer to the parameters of the function. 
</dl>
        </p></blockquote></div>

<p class="noindent">The following example function defines a simple two-dimensional
paraboloid with five parameters,

<pre class="example"><pre class="verbatim">     /* 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);
     }
</pre></pre>
   <p class="noindent">The function can be initialized using the following code,

<pre class="example">     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 = &amp;my_f;
     my_func.df = &amp;my_df;
     my_func.fdf = &amp;my_fdf;
     my_func.params = (void *)p;
</pre>
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