BinnedDotFeatures.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.
 *
 * Copyright (C) 2012 Soeren Sonnenburg
 */

#include <shogun/features/BinnedDotFeatures.h>
#include <shogun/base/Parameter.h>

using namespace shogun;

CBinnedDotFeatures::CBinnedDotFeatures(int32_t size)
    : CDotFeatures(size)
{
    init();
}


CBinnedDotFeatures::CBinnedDotFeatures(const CBinnedDotFeatures & orig)
    : CDotFeatures(orig), m_bins(orig.m_bins), m_fill(orig.m_fill),
    m_norm_one(orig.m_norm_one)
{
    init();
}

CBinnedDotFeatures::CBinnedDotFeatures(CDenseFeatures<float64_t>* sf, SGMatrix<float64_t> bins)
{
    init();
    set_simple_features(sf);
    set_bins(bins);

}

CBinnedDotFeatures::~CBinnedDotFeatures()
{
    SG_UNREF(m_features);
}

int32_t CBinnedDotFeatures::get_dim_feature_space() const
{
    return m_bins.num_rows*m_bins.num_cols;
}

float64_t CBinnedDotFeatures::dot(int32_t vec_idx1, CDotFeatures* df, int32_t vec_idx2)
{
    ASSERT(df)
    ASSERT(df->get_feature_type() == get_feature_type())
    ASSERT(df->get_feature_class() == get_feature_class())

    float64_t result=0;
    double sum1=0;
    double sum2=0;

    SGVector<float64_t> vec1=m_features->get_feature_vector(vec_idx1);
    SGVector<float64_t> vec2=((CBinnedDotFeatures*) df)->m_features->get_feature_vector(vec_idx2);

    for (int32_t i=0; i<m_bins.num_cols; i++)
    {
        float64_t v1=vec1.vector[i];
        float64_t v2=vec2.vector[i];
        float64_t* col=m_bins.get_column_vector(i);

        for (int32_t j=0; j<m_bins.num_rows; j++)
        {
            if (m_fill)
            {
                if (col[j]<=v1)
                {
                    sum1+=1.0;

                    if (col[j]<=v2)
                    {
                        sum2+=1.0;
                        result+=1.0;
                    }
                }
                else
                {
                    if (col[j]<=v2)
                        sum2+=1.0;
                    else
                        break;
                }

                /* the above is the fast version of
                if (col[j]<=v1 && col[j]<=v2)
                    result+=1.0;

                if (col[j]<=v1)
                    sum1+=1.0;

                if (col[j]<=v2)
                    sum2+=1.0;
                */
            }
            else
            {
                if (col[j]<=v1 && (j+1)<m_bins.num_rows && col[j+1]>v1 &&
                        col[j]<=v2 && (j+1)<m_bins.num_rows && col[j+1]>v2)
                {
                    result+=1;
                    break;
                }
            }
        }
    }
    m_features->free_feature_vector(vec1, vec_idx1);
    ((CBinnedDotFeatures*) df)->m_features->free_feature_vector(vec2, vec_idx2);

    if (m_fill && m_norm_one && sum1!=0 && sum2!=0)
        result/=CMath::sqrt(sum1*sum2);

    return result;

}

float64_t CBinnedDotFeatures::dense_dot(int32_t vec_idx1, const float64_t* vec2, int32_t vec2_len)
{
    assert_shape(vec2_len);

    float64_t result=0;
    double sum=0;

    SGVector<float64_t> vec1=m_features->get_feature_vector(vec_idx1);


    for (int32_t i=0; i<m_bins.num_cols; i++)
    {
        float64_t v=vec1.vector[i];
        float64_t* col=m_bins.get_column_vector(i);
        int32_t offs=i*m_bins.num_rows;

        for (int32_t j=0; j<m_bins.num_rows; j++)
        {
            if (m_fill)
            {
                if (col[j]<=v)
                {
                    result+=vec2[offs+j];
                    sum+=1.0;
                }
            }
            else
            {
                if (col[j]<=v && (j+1)<m_bins.num_rows && col[j+1]>v)
                {
                    result+=vec2[offs+j];
                    break;
                }
            }
        }
    }
    m_features->free_feature_vector(vec1, vec_idx1);

    if (m_fill && m_norm_one && sum!=0)
        result/=CMath::sqrt(sum);

    return result;
}

void CBinnedDotFeatures::add_to_dense_vec(float64_t alpha, int32_t vec_idx1, float64_t* vec2, int32_t vec2_len, bool abs_val)
{
    assert_shape(vec2_len);
    SGVector<float64_t> vec1=m_features->get_feature_vector(vec_idx1);

    if (m_fill && m_norm_one)
    {
        float64_t alpha_correction=0;
        for (int32_t i=0; i<m_bins.num_cols; i++)
        {
            float64_t v=vec1.vector[i];
            float64_t* col=m_bins.get_column_vector(i);

            for (int32_t j=0; j<m_bins.num_rows; j++)
            {
                if (col[j]<=v)
                    alpha_correction+=1.0;
            }
        }

        if (alpha_correction==0.0)
            return;

        alpha/=CMath::sqrt(alpha_correction);
    }

    for (int32_t i=0; i<m_bins.num_cols; i++)
    {
        float64_t v=vec1.vector[i];
        float64_t* col=m_bins.get_column_vector(i);
        int32_t offs=i*m_bins.num_rows;

        for (int32_t j=0; j<m_bins.num_rows; j++)
        {
            if (m_fill)
            {
                if (col[j]<=v)
                    vec2[offs+j]+=alpha;
            }
            else
            {
                if (col[j]<=v && (j+1)<m_bins.num_rows && col[j+1]>v)
                {
                    vec2[offs+j]+=alpha;
                    break;
                }
            }
        }
    }
    m_features->free_feature_vector(vec1, vec_idx1);
}

void CBinnedDotFeatures::assert_shape(int32_t vec2_len)
{
    if (m_bins.num_cols*m_bins.num_rows != vec2_len)
    {
        SG_ERROR("Bin matrix has shape (%d,%d) = %d entries, not matching vector"
                " length %d\n", m_bins.num_cols,m_bins.num_rows,
                m_bins.num_cols*m_bins.num_rows,vec2_len);
    }

    if (m_features && m_bins.num_cols != m_features->get_num_features())
    {
        SG_ERROR("Number of colums (%d) doesn't match number of features "
                "(%d)\n", m_bins.num_cols, m_features->get_num_features());
    }

}

int32_t CBinnedDotFeatures::get_nnz_features_for_vector(int32_t num)
{
    if (m_fill)
        return m_bins.num_rows;
    else
        return 1;
}

void* CBinnedDotFeatures::get_feature_iterator(int32_t vector_index)
{
    SG_NOTIMPLEMENTED
    return NULL;
}

bool CBinnedDotFeatures::get_next_feature(int32_t& index, float64_t& value, void* iterator)
{
    SG_NOTIMPLEMENTED
    return false;
}

void CBinnedDotFeatures::free_feature_iterator(void* iterator)
{
    SG_NOTIMPLEMENTED
}

bool CBinnedDotFeatures::get_fill()
{
    return m_fill;
}

void CBinnedDotFeatures::set_fill(bool fill)
{
    m_fill=fill;
}

bool CBinnedDotFeatures::get_norm_one()
{
    return m_fill;
}

void CBinnedDotFeatures::set_norm_one(bool norm_one)
{
    m_norm_one=norm_one;
}

void CBinnedDotFeatures::set_bins(SGMatrix<float64_t> bins)
{
    m_bins=bins;
}

SGMatrix<float64_t> CBinnedDotFeatures::get_bins()
{
    return m_bins;
}

void CBinnedDotFeatures::set_simple_features(CDenseFeatures<float64_t>* features)
{
    SG_REF(features);
    m_features=features;
}

CDenseFeatures<float64_t>* CBinnedDotFeatures::get_simple_features()
{
    SG_REF(m_features);
    return m_features;
}

void CBinnedDotFeatures::init()
{
    m_features=NULL;
    m_fill=true;
    m_norm_one=false;
}

const char* CBinnedDotFeatures::get_name() const
{
    return "BinnedDotFeatures";
}

CFeatures* CBinnedDotFeatures::duplicate() const
{
    return new CBinnedDotFeatures(*this);
}

EFeatureType CBinnedDotFeatures::get_feature_type() const
{
    return F_DREAL;
}


EFeatureClass CBinnedDotFeatures::get_feature_class() const
{
    return C_BINNED_DOT;
}

int32_t CBinnedDotFeatures::get_num_vectors() const
{
    ASSERT(m_features)
    return m_features->get_num_vectors();
}