VariationalLikelihood.cpp

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2014 Wu Lin
 * All rights reserved.
 *
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 * modification, are permitted provided that the following conditions are met:
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 *    list of conditions and the following disclaimer.
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#include <shogun/lib/config.h>
#include <shogun/machine/gp/VariationalLikelihood.h>

namespace shogun
{

CVariationalLikelihood::CVariationalLikelihood()
    : CLikelihoodModel()
{
    init();
}

CVariationalLikelihood::~CVariationalLikelihood()
{
    SG_UNREF(m_likelihood);
}

void CVariationalLikelihood::set_likelihood(CLikelihoodModel * lik)
{
    SG_UNREF(m_likelihood);
    m_likelihood=lik;
    SG_REF(m_likelihood);
}

void CVariationalLikelihood::init()
{
    //m_likelihood will be specified by its subclass
    //via the init_likelihood method
    m_likelihood = NULL;
    SG_REF(m_likelihood);

    SG_ADD(&m_lab, "labels",
        "The label of the data\n",
        MS_NOT_AVAILABLE);

    SG_ADD((CSGObject**)&m_likelihood, "likelihood",
        "The distribution used to model the data\n",
        MS_NOT_AVAILABLE);
}

SGVector<float64_t> CVariationalLikelihood::get_predictive_means(
    SGVector<float64_t> mu, SGVector<float64_t> s2,
    const CLabels* lab) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_predictive_means(mu, s2, lab);
}

SGVector<float64_t> CVariationalLikelihood::get_predictive_variances(
    SGVector<float64_t> mu, SGVector<float64_t> s2,
    const CLabels* lab) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_predictive_variances(mu, s2, lab);
}

SGVector<float64_t> CVariationalLikelihood::get_first_derivative(
    const CLabels* lab, SGVector<float64_t> func,
    const TParameter* param) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_first_derivative(lab, func, param);
}

SGVector<float64_t> CVariationalLikelihood::get_second_derivative(
    const CLabels* lab, SGVector<float64_t> func,
    const TParameter* param) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_second_derivative(lab, func, param);
}

SGVector<float64_t> CVariationalLikelihood::get_third_derivative(
    const CLabels* lab, SGVector<float64_t> func,
    const TParameter* param) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_third_derivative(lab, func, param);
}

ELikelihoodModelType CVariationalLikelihood::get_model_type() const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_model_type();
}

SGVector<float64_t> CVariationalLikelihood::get_log_probability_f(
    const CLabels* lab, SGVector<float64_t> func) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_log_probability_f(lab, func);
}

SGVector<float64_t> CVariationalLikelihood::get_log_probability_derivative_f(
    const CLabels* lab, SGVector<float64_t> func, index_t i) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_log_probability_derivative_f(lab, func, i);
}

SGVector<float64_t> CVariationalLikelihood::get_log_zeroth_moments(
    SGVector<float64_t> mu, SGVector<float64_t> s2,
    const CLabels* lab) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_log_zeroth_moments(mu, s2, lab);
}

float64_t CVariationalLikelihood::get_first_moment(
    SGVector<float64_t> mu, SGVector<float64_t> s2,
    const CLabels* lab, index_t i) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_first_moment(mu, s2, lab, i);
}

float64_t CVariationalLikelihood::get_second_moment(
    SGVector<float64_t> mu, SGVector<float64_t> s2,
    const CLabels* lab, index_t i) const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->get_second_moment(mu, s2, lab, i);
}

bool CVariationalLikelihood::supports_regression() const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->supports_regression();
}

bool CVariationalLikelihood::supports_binary() const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->supports_binary();
}

bool CVariationalLikelihood::supports_multiclass() const
{
    REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
    return m_likelihood->supports_multiclass();
}

}