dlib C++ Library - find_optimal_parameters_abstract.h

    // Copyright (C) 2016  Davis E. King (davis@dlib.net)
    // License: Boost Software License   See LICENSE.txt for the full license.
    #undef DLIB_fIND_OPTIMAL_PARAMETERS_ABSTRACT_Hh_
    #ifdef DLIB_fIND_OPTIMAL_PARAMETERS_ABSTRACT_Hh_

    #include "../matrix.h"

    namespace dlib
    {

    // ----------------------------------------------------------------------------------------

        template <
            typename funct
            >
        double find_optimal_parameters (
            double initial_search_radius,
            double eps,
            const unsigned int max_f_evals,
            matrix<double,0,1>& x,
            const matrix<double,0,1>& x_lower,
            const matrix<double,0,1>& x_upper,
            const funct& f
        );
        /*!
            requires
                - f(x) must be a valid expression that evaluates to a double
                - x.size() == x_lower.size() == x_upper.size()
                - x.size() > 0
                - 0 < eps < initial_search_radius
                - max_f_evals > 1
                - min(x_upper - x_lower) > 0
                - min(x - x_lower) >= 0 && min(x_upper - x) >= 0
                  (i.e. the given x should be within the bounds defined by x_lower and x_upper)
            ensures
                - Performs a constrained minimization of the function f() starting from
                  the initial point x.
                - This function does not require derivatives of f().  Instead, it uses
                  derivative free methods to find the best setting of x.  In particular, it
                  will begin by searching within a sphere of radius initial_search_radius
                  around x and will continue searching until either f() has been called
                  max_f_evals times or the search area has been shrunk to less than eps radius.
                - #x == the value of x (within the bounds defined by x_lower and x_upper) that
                  was found to minimize f().  More precisely, it will always be true that:
                    - min(#x - x_lower) >= 0 && min(x_upper - #x) >= 0
                - returns f(#x).
            throws
                - No exception is thrown for executing max_f_evals iterations.  This function
                  will simply output the best x it has seen if it runs out of iterations.
        !*/

    // ----------------------------------------------------------------------------------------

    }

    #endif // DLIB_fIND_OPTIMAL_PARAMETERS_ABSTRACT_Hh_