RandomFourierGaussPreproc.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) 2010-2011 Alexander Binder
 * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
 * Copyright (C) 2010-2011 Berlin Institute of Technology
 */

#include <shogun/preprocessor/RandomFourierGaussPreproc.h>
#include <cmath>

using namespace shogun;

void CRandomFourierGaussPreproc::copy(const CRandomFourierGaussPreproc & feats) {

    dim_input_space = feats.dim_input_space;
    cur_dim_input_space = feats.cur_dim_input_space;

    dim_feature_space = feats.dim_feature_space;
    cur_dim_feature_space=feats.cur_dim_feature_space;

    kernelwidth=feats.kernelwidth;
    cur_kernelwidth=feats.cur_kernelwidth;

    if(cur_dim_feature_space>0)
    {
        if(feats.randomcoeff_additive==NULL)
        {
            throw ShogunException(
                            "void CRandomFourierGaussPreproc::copy(...): feats.randomcoeff_additive==NULL && cur_dim_feature_space>0 \n");
        }

        randomcoeff_additive = SG_MALLOC(float64_t, cur_dim_feature_space);
        std::copy(feats.randomcoeff_additive,feats.randomcoeff_additive+cur_dim_feature_space,randomcoeff_additive);
    }
    else
    {
        randomcoeff_additive = NULL;
    }

    if((cur_dim_feature_space>0)&&(cur_dim_input_space>0))
    {
        if(feats.randomcoeff_multiplicative==NULL)
        {
            throw ShogunException(
                            "void CRandomFourierGaussPreproc::copy(...): feats.randomcoeff_multiplicative==NULL && cur_dim_feature_space>0 &&(cur_dim_input_space>0)  \n");
        }

        randomcoeff_multiplicative=SG_MALLOC(float64_t, cur_dim_feature_space*cur_dim_input_space);
        std::copy(feats.randomcoeff_multiplicative,feats.randomcoeff_multiplicative+cur_dim_feature_space*cur_dim_input_space,randomcoeff_multiplicative);
    }
    else
    {
        randomcoeff_multiplicative = NULL;
    }

}

CRandomFourierGaussPreproc::CRandomFourierGaussPreproc() :
    CDensePreprocessor<float64_t> () {
    dim_feature_space = 1000;
    dim_input_space = 0;
    cur_dim_input_space = 0;
    cur_dim_feature_space=0;

    randomcoeff_multiplicative=NULL;
    randomcoeff_additive=NULL;

    kernelwidth=1;
    cur_kernelwidth=kernelwidth;

    //m_parameter is inherited from CSGObject,
    //serialization initialization
    if(m_parameters)
    {
        SG_ADD(&dim_input_space, "dim_input_space",
            "Dimensionality of the input space.", MS_NOT_AVAILABLE);
        SG_ADD(&cur_dim_input_space, "cur_dim_input_space",
            "Dimensionality of the input space.", MS_NOT_AVAILABLE);
        SG_ADD(&dim_feature_space, "dim_feature_space",
            "Dimensionality of the feature space.", MS_NOT_AVAILABLE);
        SG_ADD(&cur_dim_feature_space, "cur_dim_feature_space",
            "Dimensionality of the feature space.", MS_NOT_AVAILABLE);

        SG_ADD(&kernelwidth, "kernelwidth", "Kernel width.", MS_AVAILABLE);
        SG_ADD(&cur_kernelwidth, "cur_kernelwidth", "Kernel width.", MS_AVAILABLE);

        m_parameters->add_vector(&randomcoeff_additive,&cur_dim_feature_space,"randomcoeff_additive");
        m_parameters->add_matrix(&randomcoeff_multiplicative,&cur_dim_feature_space,&cur_dim_input_space,"randomcoeff_multiplicative");
    }

}

CRandomFourierGaussPreproc::CRandomFourierGaussPreproc(
        const CRandomFourierGaussPreproc & feats) :
    CDensePreprocessor<float64_t> () {

    randomcoeff_multiplicative=NULL;
    randomcoeff_additive=NULL;

    //m_parameter is inherited from CSGObject,
    //serialization initialization
    if(m_parameters)
    {
        SG_ADD(&dim_input_space, "dim_input_space",
            "Dimensionality of the input space.", MS_NOT_AVAILABLE);
        SG_ADD(&cur_dim_input_space, "cur_dim_input_space",
            "Dimensionality of the input space.", MS_NOT_AVAILABLE);
        SG_ADD(&dim_feature_space, "dim_feature_space",
            "Dimensionality of the feature space.", MS_NOT_AVAILABLE);
        SG_ADD(&cur_dim_feature_space, "cur_dim_feature_space",
            "Dimensionality of the feature space.", MS_NOT_AVAILABLE);

        SG_ADD(&kernelwidth, "kernelwidth", "Kernel width.", MS_AVAILABLE);
        SG_ADD(&cur_kernelwidth, "cur_kernelwidth", "Kernel width.", MS_AVAILABLE);

        m_parameters->add_vector(&randomcoeff_additive,&cur_dim_feature_space,"randomcoeff_additive");
        m_parameters->add_matrix(&randomcoeff_multiplicative,&cur_dim_feature_space,&cur_dim_input_space,"randomcoeff_multiplicative");
    }

    copy(feats);
}

CRandomFourierGaussPreproc::~CRandomFourierGaussPreproc() {

    SG_FREE(randomcoeff_multiplicative);
    SG_FREE(randomcoeff_additive);

}

EFeatureClass CRandomFourierGaussPreproc::get_feature_class() {
    return C_DENSE;
}

EFeatureType CRandomFourierGaussPreproc::get_feature_type() {
    return F_DREAL;
}

int32_t CRandomFourierGaussPreproc::get_dim_feature_space() const {
    return ((int32_t) dim_feature_space);
}

void CRandomFourierGaussPreproc::set_dim_feature_space(const int32_t dim) {
    if (dim <= 0) {
        throw ShogunException(
                "void CRandomFourierGaussPreproc::set_dim_feature_space(const int32 dim): dim<=0 is not allowed");
    }

    dim_feature_space = dim;

}

int32_t CRandomFourierGaussPreproc::get_dim_input_space() const {
    return ((int32_t) dim_input_space);
}

void CRandomFourierGaussPreproc::set_kernelwidth(const float64_t kernelwidth2 ) {
    if (kernelwidth2 <= 0) {
        throw ShogunException(
                "void CRandomFourierGaussPreproc::set_kernelwidth(const float64_t kernelwidth2 ): kernelwidth2 <= 0 is not allowed");
    }
    kernelwidth=kernelwidth2;
}

float64_t CRandomFourierGaussPreproc::get_kernelwidth( ) const {
    return (kernelwidth);
}

void CRandomFourierGaussPreproc::set_dim_input_space(const int32_t dim) {
    if (dim <= 0) {
        throw ShogunException(
                "void CRandomFourierGaussPreproc::set_dim_input_space(const int32 dim): dim<=0 is not allowed");
    }

    dim_input_space = dim;

}

bool CRandomFourierGaussPreproc::test_rfinited() const {

    if ((dim_feature_space ==  cur_dim_feature_space)
            && (dim_input_space > 0) && (dim_feature_space > 0)) {
        if ((dim_input_space == cur_dim_input_space)&&(CMath::abs(kernelwidth-cur_kernelwidth)<1e-5)) {

            // already inited
            return true;
        } else {
            return false;
        }
    }

    return false;
}

bool CRandomFourierGaussPreproc::init_randomcoefficients() {
    if (dim_feature_space <= 0) {
        throw ShogunException(
                "bool CRandomFourierGaussPreproc::init_randomcoefficients(): dim_feature_space<=0 is not allowed\n");
    }
    if (dim_input_space <= 0) {
        throw ShogunException(
                "bool CRandomFourierGaussPreproc::init_randomcoefficients(): dim_input_space<=0 is not allowed\n");
    }

    if (test_rfinited()) {
        return false;
    }


    SG_INFO("initializing randomcoefficients \n") 

    float64_t pi = 3.14159265;


    SG_FREE(randomcoeff_multiplicative);
    randomcoeff_multiplicative=NULL;
    SG_FREE(randomcoeff_additive);
    randomcoeff_additive=NULL;


    cur_dim_feature_space=dim_feature_space;
    randomcoeff_additive=SG_MALLOC(float64_t, cur_dim_feature_space);
    cur_dim_input_space = dim_input_space;
    randomcoeff_multiplicative=SG_MALLOC(float64_t, cur_dim_feature_space*cur_dim_input_space);

    cur_kernelwidth=kernelwidth;

    for (int32_t  i = 0; i < cur_dim_feature_space; ++i) {
        randomcoeff_additive[i] = CMath::random((float64_t) 0.0, 2 * pi);
    }

    for (int32_t  i = 0; i < cur_dim_feature_space; ++i) {
        for (int32_t k = 0; k < cur_dim_input_space; ++k) {
            float64_t x1,x2;
            float64_t s = 2;
            while ((s >= 1) ) {
                // Marsaglia polar for gaussian
                x1 = CMath::random((float64_t) -1.0, (float64_t) 1.0);
                x2 = CMath::random((float64_t) -1.0, (float64_t) 1.0);
                s=x1*x1+x2*x2;
            }

            // =  x1/CMath::sqrt(val)* CMath::sqrt(-2*CMath::log(val));
            randomcoeff_multiplicative[i*cur_dim_input_space+k] =  x1*CMath::sqrt(-2*CMath::log(s)/s )/kernelwidth;
        }
    }

    SG_INFO("finished: initializing randomcoefficients \n") 

    return true;
}

void CRandomFourierGaussPreproc::get_randomcoefficients(
        float64_t ** randomcoeff_additive2,
        float64_t ** randomcoeff_multiplicative2, int32_t *dim_feature_space2,
        int32_t *dim_input_space2, float64_t* kernelwidth2) const {

    ASSERT(randomcoeff_additive2)
    ASSERT(randomcoeff_multiplicative2)

    if (!test_rfinited()) {
        *dim_feature_space2 = 0;
        *dim_input_space2 = 0;
        *kernelwidth2=1;
        *randomcoeff_additive2 = NULL;
        *randomcoeff_multiplicative2 = NULL;
        return;
    }

    *dim_feature_space2 = cur_dim_feature_space;
    *dim_input_space2 = cur_dim_input_space;
    *kernelwidth2=cur_kernelwidth;

    *randomcoeff_additive2 = SG_MALLOC(float64_t, cur_dim_feature_space);
    *randomcoeff_multiplicative2 = SG_MALLOC(float64_t, cur_dim_feature_space*cur_dim_input_space);

    std::copy(randomcoeff_additive, randomcoeff_additive+cur_dim_feature_space,
            *randomcoeff_additive2);
    std::copy(randomcoeff_multiplicative, randomcoeff_multiplicative+cur_dim_feature_space*cur_dim_input_space,
            *randomcoeff_multiplicative2);


}

void CRandomFourierGaussPreproc::set_randomcoefficients(
        float64_t *randomcoeff_additive2,
        float64_t * randomcoeff_multiplicative2,
        const int32_t dim_feature_space2, const int32_t dim_input_space2, const float64_t kernelwidth2) {
    dim_feature_space = dim_feature_space2;
    dim_input_space = dim_input_space2;
    kernelwidth=kernelwidth2;

    SG_FREE(randomcoeff_multiplicative);
    randomcoeff_multiplicative=NULL;
    SG_FREE(randomcoeff_additive);
    randomcoeff_additive=NULL;

    cur_dim_feature_space=dim_feature_space;
    cur_dim_input_space = dim_input_space;
    cur_kernelwidth=kernelwidth;

    if( (dim_feature_space>0) && (dim_input_space>0) )
    {
    randomcoeff_additive=SG_MALLOC(float64_t, cur_dim_feature_space);
    randomcoeff_multiplicative=SG_MALLOC(float64_t, cur_dim_feature_space*cur_dim_input_space);

    std::copy(randomcoeff_additive2, randomcoeff_additive2
            + dim_feature_space, randomcoeff_additive);
    std::copy(randomcoeff_multiplicative2, randomcoeff_multiplicative2
            + cur_dim_feature_space*cur_dim_input_space, randomcoeff_multiplicative);
    }

}

bool CRandomFourierGaussPreproc::init(CFeatures *f) {
    if (f->get_feature_class() != get_feature_class()) {
        throw ShogunException(
                "CRandomFourierGaussPreproc::init (CFeatures *f) requires CDenseFeatures<float64_t> as features\n");
    }
    if (f->get_feature_type() != get_feature_type()) {
        throw ShogunException(
                "CRandomFourierGaussPreproc::init (CFeatures *f) requires CDenseFeatures<float64_t> as features\n");
    }
    if (dim_feature_space <= 0) {
        throw ShogunException(
                "CRandomFourierGaussPreproc::init (CFeatures *f): dim_feature_space<=0 is not allowed, use void set_dim_feature_space(const int32 dim) before!\n");
    }

    SG_INFO("calling CRandomFourierGaussPreproc::init(...)\n")
    int32_t num_features =
            ((CDenseFeatures<float64_t>*) f)->get_num_features();

    if (!test_rfinited()) {
        dim_input_space = num_features;
        init_randomcoefficients();
        ASSERT( test_rfinited())
        return true;
    } else {
        dim_input_space = num_features;
        // does not reinit if dimension is the same to avoid overriding a previous call of set_randomcoefficients(...)
        bool inited = init_randomcoefficients();
        return inited;
    }

}

SGVector<float64_t> CRandomFourierGaussPreproc::apply_to_feature_vector(SGVector<float64_t> vector)
{
    if (!test_rfinited()) {
        throw ShogunException(
                "float64_t * CRandomFourierGaussPreproc::apply_to_feature_vector(...): test_rfinited()==false: you need to call before CRandomFourierGaussPreproc::init (CFeatures *f) OR   1. set_dim_feature_space(const int32 dim), 2. set_dim_input_space(const int32 dim), 3. init_randomcoefficients() or set_randomcoefficients(...) \n");
    }

    float64_t val = CMath::sqrt(2.0 / cur_dim_feature_space);
    float64_t *res = SG_MALLOC(float64_t, cur_dim_feature_space);

    for (int32_t od = 0; od < cur_dim_feature_space; ++od) {
        res[od] = val * cos(randomcoeff_additive[od] + SGVector<float64_t>::dot(vector.vector,
                randomcoeff_multiplicative+od*cur_dim_input_space, cur_dim_input_space));
    }

    return SGVector<float64_t>(res,cur_dim_feature_space);
}

SGMatrix<float64_t> CRandomFourierGaussPreproc::apply_to_feature_matrix(CFeatures* features)
{
    init(features);

    // version for case dim_feature_space < dim_input space with direct transformation on feature matrix ??

    int32_t num_vectors = 0;
    int32_t num_features = 0;
    float64_t* m = ((CDenseFeatures<float64_t>*) features)->get_feature_matrix(
            num_features, num_vectors);
    SG_INFO("get Feature matrix: %ix%i\n", num_vectors, num_features)

    if (num_features!=cur_dim_input_space)
    {
        throw ShogunException(
                        "float64_t * CRandomFourierGaussPreproc::apply_to_feature_matrix(CFeatures *f): num_features!=cur_dim_input_space is not allowed\n");
    }

    if (m)
    {
        SGMatrix<float64_t> res(cur_dim_feature_space,num_vectors);

        float64_t val = CMath::sqrt(2.0 / cur_dim_feature_space);

        for (int32_t vec = 0; vec < num_vectors; vec++)
        {
            for (int32_t od = 0; od < cur_dim_feature_space; ++od)
            {
                res.matrix[od + vec * cur_dim_feature_space] = val * cos(
                        randomcoeff_additive[od]
                                + SGVector<float64_t>::dot(m+vec * num_features,
                                        randomcoeff_multiplicative+od*cur_dim_input_space,
                                        cur_dim_input_space));
            }
        }
        ((CDenseFeatures<float64_t>*) features)->set_feature_matrix(res);

        return res;
    }
    else
        return SGMatrix<float64_t>();
}

void CRandomFourierGaussPreproc::cleanup()
{

}