Mercurial > hg > qm-dsp
diff dsp/chromagram/ConstantQ.cpp @ 0:d7116e3183f8
* Queen Mary C++ DSP library
author | cannam |
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date | Wed, 05 Apr 2006 17:35:59 +0000 |
parents | |
children | 07ac3de1e53b |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/dsp/chromagram/ConstantQ.cpp Wed Apr 05 17:35:59 2006 +0000 @@ -0,0 +1,193 @@ +/* -*- 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 2005-2006 Christian Landone. + All rights reserved. +*/ + +#include "ConstantQ.h" +#include "dsp/transforms/FFT.h" + +//--------------------------------------------------------------------------- +// nextpow2 returns the smallest integer n such that 2^n >= x. +static double nextpow2(double x) { + double y = ceil(log(x)/log(2.0)); + return(y); +} + +static double squaredModule(const double & xx, const double & yy) { + return xx*xx + yy*yy; +} + +//---------------------------------------------------------------------------- + +ConstantQ::ConstantQ( CQConfig Config ) +{ + initialise( Config ); +} + +ConstantQ::~ConstantQ() +{ + deInitialise(); +} + +//---------------------------------------------------------------------------- +void ConstantQ::sparsekernel() +{ + //generates spectral kernel matrix (upside down?) + // initialise temporal kernel with zeros, twice length to deal w. complex numbers + + double* hammingWindowRe = new double [ m_FFTLength ]; + double* hammingWindowIm = new double [ m_FFTLength ]; + double* transfHammingWindowRe = new double [ m_FFTLength ]; + double* transfHammingWindowIm = new double [ m_FFTLength ]; + + for (unsigned u=0; u < m_FFTLength; u++) + { + hammingWindowRe[u] = 0; + hammingWindowIm[u] = 0; + } + + + // Here, fftleng*2 is a guess of the number of sparse cells in the matrix + // The matrix K x fftlength but the non-zero cells are an antialiased + // square root function. So mostly is a line, with some grey point. + m_sparseKernelIs.reserve( m_FFTLength*2 ); + m_sparseKernelJs.reserve( m_FFTLength*2 ); + m_sparseKernelRealValues.reserve( m_FFTLength*2 ); + m_sparseKernelImagValues.reserve( m_FFTLength*2 ); + + // for each bin value K, calculate temporal kernel, take its fft to + //calculate the spectral kernel then threshold it to make it sparse and + //add it to the sparse kernels matrix + double squareThreshold = m_CQThresh * m_CQThresh; + + FFT m_FFT; + + for (unsigned k = m_uK; k--; ) + { + // Computing a hamming window + const unsigned hammingLength = (int) ceil( m_dQ * m_FS / ( m_FMin * pow(2,((double)(k))/(double)m_BPO))); + for (unsigned i=0; i<hammingLength; i++) + { + const double angle = 2*PI*m_dQ*i/hammingLength; + const double real = cos(angle); + const double imag = sin(angle); + const double absol = hamming(hammingLength, i)/hammingLength; + hammingWindowRe[ i ] = absol*real; + hammingWindowIm[ i ] = absol*imag; + } + + //do fft of hammingWindow + m_FFT.process( m_FFTLength, 0, hammingWindowRe, hammingWindowIm, transfHammingWindowRe, transfHammingWindowIm ); + + + for (unsigned j=0; j<( m_FFTLength ); j++) + { + // perform thresholding + const double squaredBin = squaredModule( transfHammingWindowRe[ j ], transfHammingWindowIm[ j ]); + if (squaredBin <= squareThreshold) continue; + + // Insert non-zero position indexes, doubled because they are floats + m_sparseKernelIs.push_back(j); + m_sparseKernelJs.push_back(k); + + // take conjugate, normalise and add to array sparkernel + m_sparseKernelRealValues.push_back( transfHammingWindowRe[ j ]/m_FFTLength); + m_sparseKernelImagValues.push_back(-transfHammingWindowIm[ j ]/m_FFTLength); + } + + } + + delete [] hammingWindowRe; + delete [] hammingWindowIm; + delete [] transfHammingWindowRe; + delete [] transfHammingWindowIm; + +} + +//----------------------------------------------------------------------------- +double* ConstantQ::process( double* fftdata ) +{ + for (unsigned row=0; row<2*m_uK; row++) + { + m_CQdata[ row ] = 0; + m_CQdata[ row+1 ] = 0; + } + const unsigned *fftbin = &(m_sparseKernelIs[0]); + const unsigned *cqbin = &(m_sparseKernelJs[0]); + const double *real = &(m_sparseKernelRealValues[0]); + const double *imag = &(m_sparseKernelImagValues[0]); + const unsigned int sparseCells = m_sparseKernelRealValues.size(); + + for (unsigned i = 0; i<sparseCells; i++) + { + const unsigned row = cqbin[i]; + const unsigned col = fftbin[i]; + const double & r1 = real[i]; + const double & i1 = imag[i]; + const double & r2 = fftdata[ (2*m_FFTLength) - 2*col]; + const double & i2 = fftdata[ (2*m_FFTLength) - 2*col+1]; + // add the multiplication + m_CQdata[ 2*row ] += (r1*r2 - i1*i2); + m_CQdata[ 2*row+1] += (r1*i2 + i1*r2); + } + + return m_CQdata; +} + + +void ConstantQ::initialise( CQConfig Config ) +{ + m_FS = Config.FS; + m_FMin = Config.min; // min freq + m_FMax = Config.max; // max freq + m_BPO = Config.BPO; // bins per octave + m_CQThresh = Config.CQThresh;// ConstantQ threshold for kernel generation + + m_dQ = 1/(pow(2,(1/(double)m_BPO))-1); // Work out Q value for Filter bank + m_uK = (unsigned int) ceil(m_BPO * log(m_FMax/m_FMin)/log(2.0)); // No. of constant Q bins + + // work out length of fft required for this constant Q Filter bank + m_FFTLength = (int) pow(2, nextpow2(ceil( m_dQ*m_FS/m_FMin ))); + + m_hop = m_FFTLength/8; // <------ hop size is window length divided by 32 + + // allocate memory for cqdata + m_CQdata = new double [2*m_uK]; +} + +void ConstantQ::deInitialise() +{ + delete [] m_CQdata; +} + +void ConstantQ::process(double *FFTRe, double* FFTIm, double *CQRe, double *CQIm) +{ + for (unsigned row=0; row<m_uK; row++) + { + CQRe[ row ] = 0; + CQIm[ row ] = 0; + } + + const unsigned *fftbin = &(m_sparseKernelIs[0]); + const unsigned *cqbin = &(m_sparseKernelJs[0]); + const double *real = &(m_sparseKernelRealValues[0]); + const double *imag = &(m_sparseKernelImagValues[0]); + const unsigned int sparseCells = m_sparseKernelRealValues.size(); + + for (unsigned i = 0; i<sparseCells; i++) + { + const unsigned row = cqbin[i]; + const unsigned col = fftbin[i]; + const double & r1 = real[i]; + const double & i1 = imag[i]; + const double & r2 = FFTRe[ m_FFTLength- col]; + const double & i2 = FFTIm[ m_FFTLength - col]; + // add the multiplication + CQRe[ row ] += (r1*r2 - i1*i2); + CQIm[ row ] += (r1*i2 + i1*r2); + } +}