view maths/KLDivergence.cpp @ 321:f1e6be2de9a5

A threshold (delta) is added in the peak picking parameters structure (PPickParams). It is used as an offset when computing the smoothed detection function. A constructor for the structure PPickParams is also added to set the parameters to 0 when a structure instance is created. Hence programmes using the peak picking parameter structure and which do not set the delta parameter (e.g. QM Vamp note onset detector) won't be affected by the modifications.

Functions modified:
- dsp/onsets/PeakPicking.cpp
- dsp/onsets/PeakPicking.h
- dsp/signalconditioning/DFProcess.cpp
- dsp/signalconditioning/DFProcess.h

/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */

/*
    QM DSP Library

    Centre for Digital Music, Queen Mary, University of London.
    This file copyright 2008 QMUL

    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.  See the file
    COPYING included with this distribution for more information.
*/

#include "KLDivergence.h"

#include <cmath>

double KLDivergence::distanceGaussian(const vector<double> &m1,
                                      const vector<double> &v1,
                                      const vector<double> &m2,
                                      const vector<double> &v2)
{
    int sz = m1.size();

    double d = -2.0 * sz;
    double small = 1e-20;

    for (int k = 0; k < sz; ++k) {

        double kv1 = v1[k] + small;
        double kv2 = v2[k] + small;
        double km = (m1[k] - m2[k]) + small;

        d += kv1 / kv2 + kv2 / kv1;
        d += km * (1.0 / kv1 + 1.0 / kv2) * km;
    }

    d /= 2.0;

    return d;
}

double KLDivergence::distanceDistribution(const vector<double> &d1,
                                          const vector<double> &d2,
                                          bool symmetrised)
{
    int sz = d1.size();

    double d = 0;
    double small = 1e-20;
    
    for (int i = 0; i < sz; ++i) {
        d += d1[i] * log10((d1[i] + small) / (d2[i] + small));
    }

    if (symmetrised) {
        d += distanceDistribution(d2, d1, false);
    }

    return d;
}