L1PenaltyForTG.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 L1PENALTYFORTG_H
#define L1PENALTYFORTG_H
#include <shogun/optimization/L1Penalty.h>
#include <shogun/lib/config.h>

#include <iostream>
namespace shogun
{
class L1PenaltyForTG: public L1Penalty
{
public:
    /* Constructor */
    L1PenaltyForTG():L1Penalty() { init(); }

    /* Destructor */
    virtual ~L1PenaltyForTG() {}

    virtual void update_variable_for_proximity(SGVector<float64_t> variable,
        float64_t proximal_weight)
    {
        if(m_q.vlen==0)
        {
            m_q=SGVector<float64_t>(variable.vlen);
            m_q.set_const(0.0);
        }
        else
        {
            REQUIRE(variable.vlen==m_q.vlen,
                "The length of variable (%d) is changed. Last time, the length of variable was %d", variable.vlen, m_q.vlen);
        }
        m_u+=proximal_weight;
        for(index_t idx=0; idx<variable.vlen; idx++)
        {
            float64_t z=variable[idx];
            if(z>0.0)
                variable[idx]=get_sparse_variable(z, m_u+m_q[idx]);
            else if(z<0.0)
                variable[idx]=get_sparse_variable(z, m_u-m_q[idx]);
            m_q[idx]+=variable[idx]-z;
        }
    }

    virtual void update_context(CMinimizerContext* context)
    {
        REQUIRE(context, "Context must set\n");
        L1Penalty::update_context(context);
        SGVector<float64_t> value(m_q.vlen);
        std::copy(m_q.vector,
            m_q.vector+m_q.vlen,
            value.vector);
        std::string key="L1PenaltyForTG::m_q";
        context->save_data(key, value);

        key="L1PenaltyForTG::m_u";
        context->save_data(key, m_u);
    }

    virtual void load_from_context(CMinimizerContext* context)
    {
        REQUIRE(context, "Context must set\n");
        L1Penalty::load_from_context(context);
        std::string key="L1PenaltyForTG::m_q";
        SGVector<float64_t> value=context->get_data_sgvector_float64(key);
        m_q=SGVector<float64_t>(value.vlen);
        std::copy(value.vector, value.vector+value.vlen,
            m_q.vector);

        key="L1PenaltyForTG::m_u";
        m_u=context->get_data_float64(key);
    }
protected:
    float64_t m_u;
    SGVector<float64_t> m_q;

private:
    void init()
    {
        m_u=0;
        m_q=SGVector<float64_t>();
    }

};

}

#endif