text: /*
   * 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 PROXIMALPENALTY_H
  #define PROXIMALPENALTY_H
  #include <shogun/optimization/Penalty.h>
  namespace shogun
  {
  /** @brief The base class for sparse penalty/regularization used in minimization.
   *
   * This is the interface of regularizers used in minimizers.
   * (eg,
   * FirstOrderMinimizer::update_gradient(SGVector<float64_t> gradient, SGVector<float64_t> var)
   * FirstOrderMinimizer::get_penalty(SGVector<float64_t> var)
   * ) 
   *
   * Reference:
   * Proximal gradient method
   * www.eecs.berkeley.edu/~elghaoui/Teaching/EE227A/lecture18.pdf
   *
   */
  class ProximalPenalty: public Penalty
  {
  public:
  	~ProximalPenalty() override {}; 
  
  	/** Do proximal projection/operation in place
  	 * @param variable the raw variable
  	 * @param proximal_weight weight of the penalty
  	 */
  	virtual void update_variable_for_proximity(SGVector<float64_t> variable,
  		float64_t proximal_weight)=0;
  
  };
  
  }
  #endif
  