ineb2weight.cc

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/* Copyright (C) 2013,2014 Aarsh Shah
 *
 * 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 2 of the
 * License, or (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
 */

#include <config.h>

#include "xapian/weight.h"
#include "common/log2.h"

#include "serialise-double.h"

#include "xapian/error.h"

using namespace std;

namespace Xapian {

IneB2Weight::IneB2Weight(double c) : param_c(c) {
    if (param_c <= 0)
        throw Xapian::InvalidArgumentError("Parameter c is invalid");
    need_stat(AVERAGE_LENGTH);
    need_stat(DOC_LENGTH);
    need_stat(DOC_LENGTH_MIN);
    need_stat(COLLECTION_SIZE);
    need_stat(WDF);
    need_stat(WDF_MAX);
    need_stat(WQF);
    need_stat(COLLECTION_FREQ);
    need_stat(TERMFREQ);
}

IneB2Weight *
IneB2Weight::clone() const
{
    return new IneB2Weight(param_c);
}

void
IneB2Weight::init(double factor)
{
    if (factor == 0.0) {
        // This object is for the term-independent contribution, and that's
        // always zero for this scheme.
        return;
    }

    double wdfn_upper = get_wdf_upper_bound();
    if (wdfn_upper == 0) {
        upper_bound = 0.0;
        return;
    }

    wdfn_upper *= log2(1 + (param_c * get_average_length()) /
                    get_doclength_lower_bound());

    double N = get_collection_size();
    double F = get_collection_freq();
    double termfreq = get_termfreq();

    double max_wdfn_product_B = (F + 1.0) / (termfreq + (termfreq / wdfn_upper));

    double mean = F / N;

    double expected_max = N * (1.0 - exp(-mean));

    double idf_max = log2((N + 1.0) / (expected_max + 0.5));

    /* Calculate constant values used in get_sumpart(). */
    wqf_product_idf = get_wqf() * idf_max * factor;
    c_product_avlen = param_c * get_average_length();
    B_constant = (F + 1.0) / termfreq;

    upper_bound = max_wdfn_product_B * idf_max * get_wqf() * factor;
}

string
IneB2Weight::name() const
{
    return "Xapian::IneB2Weight";
}

string
IneB2Weight::serialise() const
{
    return serialise_double(param_c);
}

IneB2Weight *
IneB2Weight::unserialise(const string & s) const
{
    const char *ptr = s.data();
    const char *end = ptr + s.size();
    double c = unserialise_double(&ptr, end);
    if (rare(ptr != end))
        throw Xapian::SerialisationError("Extra data in IneB2Weight::unserialise()");
    return new IneB2Weight(c);
}

double
IneB2Weight::get_sumpart(Xapian::termcount wdf, Xapian::termcount len,
                         Xapian::termcount) const
{
    if (wdf == 0) return 0.0;
    double wdfn = wdf;

    wdfn *= log2(1 + c_product_avlen / len);

    double wdfn_product_B = wdfn * B_constant / (wdfn + 1.0);

    return (wdfn_product_B * wqf_product_idf);
}

double
IneB2Weight::get_maxpart() const
{
    return upper_bound;
}

double
IneB2Weight::get_sumextra(Xapian::termcount, Xapian::termcount) const
{
    return 0;
}

double
IneB2Weight::get_maxextra() const
{
    return 0;
}

}