145 lines
3.6 KiB
C++
145 lines
3.6 KiB
C++
/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
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/*
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QM DSP Library
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Centre for Digital Music, Queen Mary, University of London.
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This file copyright 2006 Martin Gasser.
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This program is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License as
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published by the Free Software Foundation; either version 2 of the
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License, or (at your option) any later version. See the file
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COPYING included with this distribution for more information.
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*/
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#include "ChangeDetectionFunction.h"
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#ifndef PI
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#define PI (3.14159265358979232846)
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#endif
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ChangeDetectionFunction::ChangeDetectionFunction(ChangeDFConfig config) :
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m_dFilterSigma(0.0), m_iFilterWidth(0)
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{
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setFilterWidth(config.smoothingWidth);
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}
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ChangeDetectionFunction::~ChangeDetectionFunction()
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{
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}
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void ChangeDetectionFunction::setFilterWidth(const int iWidth)
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{
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m_iFilterWidth = iWidth*2+1;
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// it is assumed that the gaussian is 0 outside of +/- FWHM
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// => filter width = 2*FWHM = 2*2.3548*sigma
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m_dFilterSigma = double(m_iFilterWidth) / double(2*2.3548);
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m_vaGaussian.resize(m_iFilterWidth);
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double dScale = 1.0 / (m_dFilterSigma*sqrt(2*PI));
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for (int x = -(m_iFilterWidth-1)/2; x <= (m_iFilterWidth-1)/2; x++)
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{
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double w = dScale * std::exp ( -(x*x)/(2*m_dFilterSigma*m_dFilterSigma) );
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m_vaGaussian[x + (m_iFilterWidth-1)/2] = w;
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}
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#ifdef DEBUG_CHANGE_DETECTION_FUNCTION
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std::cerr << "Filter sigma: " << m_dFilterSigma << std::endl;
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std::cerr << "Filter width: " << m_iFilterWidth << std::endl;
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#endif
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}
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ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
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{
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ChangeDistance retVal;
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retVal.resize(rTCSGram.getSize(), 0.0);
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TCSGram smoothedTCSGram;
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for (int iPosition = 0; iPosition < rTCSGram.getSize(); iPosition++)
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{
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int iSkipLower = 0;
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int iLowerPos = iPosition - (m_iFilterWidth-1)/2;
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int iUpperPos = iPosition + (m_iFilterWidth-1)/2;
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if (iLowerPos < 0)
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{
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iSkipLower = -iLowerPos;
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iLowerPos = 0;
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}
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if (iUpperPos >= rTCSGram.getSize())
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{
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int iMaxIndex = rTCSGram.getSize() - 1;
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iUpperPos = iMaxIndex;
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}
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TCSVector smoothedVector;
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// for every bin of the vector, calculate the smoothed value
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for (int iPC = 0; iPC < 6; iPC++)
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{
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size_t j = 0;
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double dSmoothedValue = 0.0;
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TCSVector rCV;
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for (int i = iLowerPos; i <= iUpperPos; i++)
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{
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rTCSGram.getTCSVector(i, rCV);
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dSmoothedValue += m_vaGaussian[iSkipLower + j++] * rCV[iPC];
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}
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smoothedVector[iPC] = dSmoothedValue;
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}
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smoothedTCSGram.addTCSVector(smoothedVector);
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}
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for (int iPosition = 0; iPosition < rTCSGram.getSize(); iPosition++)
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{
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/*
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TODO: calculate a confidence measure for the current estimation
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if the current estimate is not confident enough, look further into the future/the past
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e.g., High frequency content, zero crossing rate, spectral flatness
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*/
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TCSVector nextTCS;
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TCSVector previousTCS;
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int iWindow = 1;
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// while (previousTCS.magnitude() < 0.1 && (iPosition-iWindow) > 0)
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{
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smoothedTCSGram.getTCSVector(iPosition-iWindow, previousTCS);
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// std::cout << previousTCS.magnitude() << std::endl;
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iWindow++;
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}
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iWindow = 1;
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// while (nextTCS.magnitude() < 0.1 && (iPosition+iWindow) < (rTCSGram.getSize()-1) )
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{
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smoothedTCSGram.getTCSVector(iPosition+iWindow, nextTCS);
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iWindow++;
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}
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double distance = 0.0;
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// Euclidean distance
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for (size_t j = 0; j < 6; j++)
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{
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distance += std::pow(nextTCS[j] - previousTCS[j], 2.0);
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}
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retVal[iPosition] = std::pow(distance, 0.5);
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}
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return retVal;
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}
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