NLOPTMinimizer.h

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2015 Wu Lin
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 *    list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *
 * The views and conclusions contained in the software and documentation are those
 * of the authors and should not be interpreted as representing official policies,
 * either expressed or implied, of the Shogun Development Team.
 *
 */

#ifndef NLOPTMINIMIZER_H
#define NLOPTMINIMIZER_H
#include <shogun/optimization/FirstOrderMinimizer.h>

#ifdef HAVE_NLOPT
#include <nlopt.h>
#endif 
namespace shogun
{
class NLOPTMinimizer:public FirstOrderMinimizer
{
public:
    NLOPTMinimizer();

    NLOPTMinimizer(FirstOrderCostFunction *fun);

    virtual ~NLOPTMinimizer();

    virtual float64_t minimize();

    virtual bool supports_batch_update() const {return true;}

    virtual CMinimizerContext* save_to_context() {return new CMinimizerContext();}

    virtual void load_from_context(CMinimizerContext* context) {}

#ifdef HAVE_NLOPT
    /* Set parameters used in NLOPT
     * For details please see http://ab-initio.mit.edu/wiki/index.php/NLopt_C-plus-plus_Reference
     *
     * @param algorithm provided by NLOPT for minimization
     * @param max_iterations the number of cost function evaluations 
     * @param variable_tolerance absolute tolerance on optimization parameters 
     * @param function_tolerance absolute tolerance on function value.
     */
    virtual void set_nlopt_parameters(nlopt_algorithm algorithm=NLOPT_LD_LBFGS,
        float64_t max_iterations=1000,
        float64_t variable_tolerance=1e-6,
        float64_t function_tolerance=1e-6);
private:
    /* A helper function will be called by the NLOPT library
     * Note that this function should be static and
     * private.
     * */
    static double nlopt_function(unsigned dim, const double* variable,
        double* gradient, void* func_data);

protected:

    /* Target variable */
    SGVector<float64_t> m_target_variable;

    /* Init before minimization */
    virtual void init_minimization();

    float64_t m_max_iterations;

    float64_t m_variable_tolerance;

    float64_t m_function_tolerance;

    nlopt_algorithm m_nlopt_algorithm;
#endif /* HAVE_NLOPT */

private:
    /* init */
    void init();
};

}
#endif /* NLOPTMINIMIZER_H */