Histogram.cpp

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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
 * Written (W) 1999-2008 Gunnar Raetsch
 * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
 */

#include <shogun/distributions/Histogram.h>
#include <shogun/lib/common.h>
#include <shogun/features/StringFeatures.h>
#include <shogun/io/SGIO.h>
#include <shogun/mathematics/Math.h>

using namespace shogun;

CHistogram::CHistogram()
: CDistribution()
{
    hist=SG_CALLOC(float64_t, 1<<16);
}

CHistogram::CHistogram(CStringFeatures<uint16_t> *f)
: CDistribution()
{
    hist=SG_CALLOC(float64_t, 1<<16);
    features=f;
}

CHistogram::~CHistogram()
{
    SG_FREE(hist);
}

bool CHistogram::train(CFeatures* data)
{
    int32_t vec;
    int32_t feat;
    int32_t i;

    if (data)
    {
        if (data->get_feature_class() != C_STRING ||
                data->get_feature_type() != F_WORD)
        {
            SG_ERROR("Expected features of class string type word\n");
        }
        set_features(data);
    }

    ASSERT(features);
    ASSERT(features->get_feature_class()==C_STRING);
    ASSERT(features->get_feature_type()==F_WORD);

    for (i=0; i< (int32_t) (1<<16); i++)
        hist[i]=0;

    for (vec=0; vec<features->get_num_vectors(); vec++)
    {
        int32_t len;
        bool free_vec;

        uint16_t* vector=((CStringFeatures<uint16_t>*) features)->
            get_feature_vector(vec, len, free_vec);

        for (feat=0; feat<len ; feat++)
            hist[vector[feat]]++;

        ((CStringFeatures<uint16_t>*) features)->
            free_feature_vector(vector, vec, free_vec);
    }

    for (i=0; i< (int32_t) (1<<16); i++)
        hist[i]=log(hist[i]);

    return true;
}

float64_t CHistogram::get_log_likelihood_example(int32_t num_example)
{
    ASSERT(features);
    ASSERT(features->get_feature_class()==C_STRING);
    ASSERT(features->get_feature_type()==F_WORD);

    int32_t len;
    bool free_vec;
    float64_t loglik=0;

    uint16_t* vector=((CStringFeatures<uint16_t>*) features)->
        get_feature_vector(num_example, len, free_vec);

    for (int32_t i=0; i<len; i++)
        loglik+=hist[vector[i]];

    ((CStringFeatures<uint16_t>*) features)->
        free_feature_vector(vector, num_example, free_vec);

    return loglik;
}

float64_t CHistogram::get_log_derivative(int32_t num_param, int32_t num_example)
{
    if (hist[num_param] < CMath::ALMOST_NEG_INFTY)
        return -CMath::INFTY;
    else
    {
        ASSERT(features);
        ASSERT(features->get_feature_class()==C_STRING);
        ASSERT(features->get_feature_type()==F_WORD);

        int32_t len;
        bool free_vec;
        float64_t deriv=0;

        uint16_t* vector=((CStringFeatures<uint16_t>*) features)->
            get_feature_vector(num_example, len, free_vec);

        int32_t num_occurences=0;

        for (int32_t i=0; i<len; i++)
        {
            deriv+=hist[vector[i]];

            if (vector[i]==num_param)
                num_occurences++;
        }

        ((CStringFeatures<uint16_t>*) features)->
            free_feature_vector(vector, num_example, free_vec);

        if (num_occurences>0)
            deriv+=CMath::log((float64_t) num_occurences)-hist[num_param];
        else
            deriv=-CMath::INFTY;

        return deriv;
    }
}

float64_t CHistogram::get_log_model_parameter(int32_t num_param)
{
    return hist[num_param];
}

bool CHistogram::set_histogram(const SGVector<float64_t> histogram)
{
    ASSERT(histogram.vlen==get_num_model_parameters());

    SG_FREE(hist);
    hist=SG_MALLOC(float64_t, histogram.vlen);
    for (int32_t i=0; i<histogram.vlen; i++)
        hist[i]=histogram.vector[i];

    return true;
}

SGVector<float64_t> CHistogram::get_histogram()
{
    return SGVector<float64_t>(hist,get_num_model_parameters(),false);
}