PluginEstimate.h

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/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 1999-2009 Soeren Sonnenburg
 * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
 */

#ifndef _PLUGINESTIMATE_H___
#define _PLUGINESTIMATE_H___

#include <shogun/lib/config.h>

#include <shogun/machine/Machine.h>
#include <shogun/features/StringFeatures.h>
#include <shogun/labels/BinaryLabels.h>
#include <shogun/distributions/LinearHMM.h>

namespace shogun
{
class CPluginEstimate: public CMachine
{
    public:

        MACHINE_PROBLEM_TYPE(PT_BINARY);

        CPluginEstimate(float64_t pos_pseudo=1e-10, float64_t neg_pseudo=1e-10);
        virtual ~CPluginEstimate();

        virtual CBinaryLabels* apply_binary(CFeatures* data=NULL);

        virtual void set_features(CStringFeatures<uint16_t>* feat)
        {
            SG_REF(feat);
            SG_UNREF(features);
            features=feat;
        }

        virtual CStringFeatures<uint16_t>* get_features() { SG_REF(features); return features; }

        float64_t apply_one(int32_t vec_idx);

        inline float64_t posterior_log_odds_obsolete(
            uint16_t* vector, int32_t len)
        {
            return pos_model->get_log_likelihood_example(vector, len) - neg_model->get_log_likelihood_example(vector, len);
        }

        inline float64_t get_parameterwise_log_odds(
            uint16_t obs, int32_t position)
        {
            return pos_model->get_positional_log_parameter(obs, position) - neg_model->get_positional_log_parameter(obs, position);
        }

        inline float64_t log_derivative_pos_obsolete(uint16_t obs, int32_t pos)
        {
            return pos_model->get_log_derivative_obsolete(obs, pos);
        }

        inline float64_t log_derivative_neg_obsolete(uint16_t obs, int32_t pos)
        {
            return neg_model->get_log_derivative_obsolete(obs, pos);
        }

        inline bool get_model_params(
            float64_t*& pos_params, float64_t*& neg_params,
            int32_t &seq_length, int32_t &num_symbols)
        {
            if ((!pos_model) || (!neg_model))
            {
                SG_ERROR("no model available\n")
                return false;
            }

            SGVector<float64_t> log_pos_trans = pos_model->get_log_transition_probs();
            pos_params = log_pos_trans.vector;
            SGVector<float64_t> log_neg_trans = neg_model->get_log_transition_probs();
            neg_params = log_neg_trans.vector;

            seq_length = pos_model->get_sequence_length();
            num_symbols = pos_model->get_num_symbols();
            ASSERT(pos_model->get_num_model_parameters()==neg_model->get_num_model_parameters())
            ASSERT(pos_model->get_num_symbols()==neg_model->get_num_symbols())
            return true;
        }

        inline void set_model_params(
            float64_t* pos_params, float64_t* neg_params,
            int32_t seq_length, int32_t num_symbols)
        {
            int32_t num_params;

            SG_UNREF(pos_model);
            pos_model=new CLinearHMM(seq_length, num_symbols);
            SG_REF(pos_model);


            SG_UNREF(neg_model);
            neg_model=new CLinearHMM(seq_length, num_symbols);
            SG_REF(neg_model);

            num_params=pos_model->get_num_model_parameters();
            ASSERT(seq_length*num_symbols==num_params)
            ASSERT(num_params==neg_model->get_num_model_parameters())

            pos_model->set_log_transition_probs(SGVector<float64_t>(pos_params, num_params));
            neg_model->set_log_transition_probs(SGVector<float64_t>(neg_params, num_params));
        }

        inline int32_t get_num_params()
        {
            return pos_model->get_num_model_parameters()+neg_model->get_num_model_parameters();
        }

        inline bool check_models()
        {
            return ( (pos_model!=NULL) && (neg_model!=NULL) );
        }

        virtual const char* get_name() const { return "PluginEstimate"; }

    protected:
        virtual bool train_machine(CFeatures* data=NULL);

    protected:
        float64_t m_pos_pseudo;
        float64_t m_neg_pseudo;

        CLinearHMM* pos_model;
        CLinearHMM* neg_model;

        CStringFeatures<uint16_t>* features;
};
}
#endif