KNNHeap.cpp

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2014 Parijat Mazumdar
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 * list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 * this list of conditions and the following disclaimer in the documentation
 * and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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#include <shogun/multiclass/tree/KNNHeap.h>
#include <shogun/mathematics/Math.h>
#include <shogun/lib/SGVector.h>

using namespace shogun;

CKNNHeap::CKNNHeap(int32_t k)
{
    m_capacity=k;
    m_dists=SGVector<float64_t>(m_capacity);
    m_inds=SGVector<index_t>(m_capacity);
    m_sorted=false;

    for (int32_t i=0;i<m_capacity;i++)
    {
        m_dists[i]=CMath::MAX_REAL_NUMBER;
        m_inds[i]=0;
    }
}

void CKNNHeap::push(index_t index, float64_t dist)
{
    if (dist>m_dists[0])
        return;

    m_dists[0]=dist;
    m_inds[0]=index;

    index_t i_swap;
    index_t i=0;
    while (true)
    {
        index_t l=2*i+1;
        index_t r=l+1;
        if (l>=m_capacity)
        {
            break;
        }
        else if (r>=m_capacity)
        {
            if (m_dists[l]>dist)
                i_swap=l;
            else
                break;
        }
        else if (m_dists[l]>=m_dists[r])
        {
            if (m_dists[l]>dist)
                i_swap=l;
            else
                break;
        }
        else
        {
            if (m_dists[r]>dist)
                i_swap=r;
            else
                break;
        }

        m_dists[i]=m_dists[i_swap];
        m_inds[i]=m_inds[i_swap];

        m_dists[i_swap]=dist;
        m_inds[i_swap]=index;
        i=i_swap;
    }
}

SGVector<float64_t> CKNNHeap::get_dists()
{
    if (m_sorted)
        return m_dists;

    m_sorted=true;
    SGVector<float64_t> new_dists(m_capacity);
    SGVector<index_t> new_inds(m_capacity);

    // O(nlogn) heap-sort
    for (int32_t i=m_capacity-1;i>-1;i--)
    {
        new_dists[i]=m_dists[0];
        new_inds[i]=m_inds[0];
        push(0,-1);
    }

    m_dists=new_dists;
    m_inds=new_inds;

    return m_dists;
}

SGVector<index_t> CKNNHeap::get_indices()
{
    if (m_sorted)
        return m_inds;

    m_sorted=true;
    SGVector<float64_t> new_dists(m_capacity);
    SGVector<index_t> new_inds(m_capacity);

    // O(nlogn) heap-sort
    for (int32_t i=m_capacity-1;i>-1;i--)
    {
        new_dists[i]=m_dists[0];
        new_inds[i]=m_inds[0];
        push(0,-1);
    }

    m_dists=new_dists;
    m_inds=new_inds;

    return m_inds;
}