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/* -*- 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 2006 Martin Gasser.
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 "ChangeDetectionFunction.h"
#ifndef PI
#define PI (3.14159265358979232846)
#endif
ChangeDetectionFunction::ChangeDetectionFunction(ChangeDFConfig config) :
m_dFilterSigma(0.0), m_iFilterWidth(0)
{
setFilterWidth(config.smoothingWidth);
}
ChangeDetectionFunction::~ChangeDetectionFunction()
{
}
void ChangeDetectionFunction::setFilterWidth(const int iWidth)
{
m_iFilterWidth = iWidth*2+1;
// it is assumed that the gaussian is 0 outside of +/- FWHM
// => filter width = 2*FWHM = 2*2.3548*sigma
m_dFilterSigma = double(m_iFilterWidth) / double(2*2.3548);
m_vaGaussian.resize(m_iFilterWidth);
double dScale = 1.0 / (m_dFilterSigma*sqrt(2*PI));
for (int x = -(m_iFilterWidth-1)/2; x <= (m_iFilterWidth-1)/2; x++)
{
double w = dScale * std::exp ( -(x*x)/(2*m_dFilterSigma*m_dFilterSigma) );
m_vaGaussian[x + (m_iFilterWidth-1)/2] = w;
}
#ifdef DEBUG_CHANGE_DETECTION_FUNCTION
std::cerr << "Filter sigma: " << m_dFilterSigma << std::endl;
std::cerr << "Filter width: " << m_iFilterWidth << std::endl;
#endif
}
ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
{
ChangeDistance retVal;
retVal.resize(rTCSGram.getSize(), 0.0);
TCSGram smoothedTCSGram;
for (int iPosition = 0; iPosition < rTCSGram.getSize(); iPosition++)
{
int iSkipLower = 0;
int iLowerPos = iPosition - (m_iFilterWidth-1)/2;
int iUpperPos = iPosition + (m_iFilterWidth-1)/2;
if (iLowerPos < 0)
{
iSkipLower = -iLowerPos;
iLowerPos = 0;
}
if (iUpperPos >= rTCSGram.getSize())
{
int iMaxIndex = rTCSGram.getSize() - 1;
iUpperPos = iMaxIndex;
}
TCSVector smoothedVector;
// for every bin of the vector, calculate the smoothed value
for (int iPC = 0; iPC < 6; iPC++)
{
size_t j = 0;
double dSmoothedValue = 0.0;
TCSVector rCV;
for (int i = iLowerPos; i <= iUpperPos; i++)
{
rTCSGram.getTCSVector(i, rCV);
dSmoothedValue += m_vaGaussian[iSkipLower + j++] * rCV[iPC];
}
smoothedVector[iPC] = dSmoothedValue;
}
smoothedTCSGram.addTCSVector(smoothedVector);
}
for (int iPosition = 0; iPosition < rTCSGram.getSize(); iPosition++)
{
/*
TODO: calculate a confidence measure for the current estimation
if the current estimate is not confident enough, look further into the future/the past
e.g., High frequency content, zero crossing rate, spectral flatness
*/
TCSVector nextTCS;
TCSVector previousTCS;
int iWindow = 1;
// while (previousTCS.magnitude() < 0.1 && (iPosition-iWindow) > 0)
{
smoothedTCSGram.getTCSVector(iPosition-iWindow, previousTCS);
// std::cout << previousTCS.magnitude() << std::endl;
iWindow++;
}
iWindow = 1;
// while (nextTCS.magnitude() < 0.1 && (iPosition+iWindow) < (rTCSGram.getSize()-1) )
{
smoothedTCSGram.getTCSVector(iPosition+iWindow, nextTCS);
iWindow++;
}
double distance = 0.0;
// Euclidean distance
for (size_t j = 0; j < 6; j++)
{
distance += std::pow(nextTCS[j] - previousTCS[j], 2.0);
}
retVal[iPosition] = std::pow(distance, 0.5);
}
return retVal;
}
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