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1 /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
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2 /*
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3 QM DSP Library
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4
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5 Centre for Digital Music, Queen Mary, University of London.
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6 This file 2005-2006 Christian Landone.
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7
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8 This program is free software; you can redistribute it and/or
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9 modify it under the terms of the GNU General Public License as
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10 published by the Free Software Foundation; either version 2 of the
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11 License, or (at your option) any later version. See the file
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12 COPYING included with this distribution for more information.
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13 */
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14
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15 #include "ConstantQ.h"
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16 #include "dsp/transforms/FFT.h"
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17
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18 #include <iostream>
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19
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20 #ifdef NOT_DEFINED
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21 // see note in CQprecalc
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22
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23 #include "CQprecalc.cpp"
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24
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25 static bool push_precalculated(int uk, int fftlength,
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26 std::vector<unsigned> &is,
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27 std::vector<unsigned> &js,
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28 std::vector<double> &real,
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29 std::vector<double> &imag)
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30 {
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31 if (uk == 76 && fftlength == 16384) {
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32 push_76_16384(is, js, real, imag);
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33 return true;
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34 }
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35 if (uk == 144 && fftlength == 4096) {
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36 push_144_4096(is, js, real, imag);
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37 return true;
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38 }
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39 if (uk == 65 && fftlength == 2048) {
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40 push_65_2048(is, js, real, imag);
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41 return true;
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42 }
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43 if (uk == 84 && fftlength == 65536) {
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44 push_84_65536(is, js, real, imag);
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45 return true;
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46 }
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47 return false;
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48 }
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49 #endif
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50
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51 //---------------------------------------------------------------------------
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52 // nextpow2 returns the smallest integer n such that 2^n >= x.
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53 static double nextpow2(double x) {
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54 double y = ceil(log(x)/log(2.0));
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55 return(y);
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56 }
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57
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58 static double squaredModule(const double & xx, const double & yy) {
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59 return xx*xx + yy*yy;
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60 }
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61
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62 //----------------------------------------------------------------------------
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63
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64 ConstantQ::ConstantQ( CQConfig Config ) :
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65 m_sparseKernel(0)
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66 {
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67 initialise( Config );
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68 }
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69
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70 ConstantQ::~ConstantQ()
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71 {
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72 deInitialise();
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73 }
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74
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75 //----------------------------------------------------------------------------
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76 void ConstantQ::sparsekernel()
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77 {
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78 // std::cerr << "ConstantQ: initialising sparse kernel, uK = " << m_uK << ", FFTLength = " << m_FFTLength << "...";
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79
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80 SparseKernel *sk = new SparseKernel();
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81
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82 #ifdef NOT_DEFINED
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83 if (push_precalculated(m_uK, m_FFTLength,
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84 sk->is, sk->js, sk->real, sk->imag)) {
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85 // std::cerr << "using precalculated kernel" << std::endl;
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86 m_sparseKernel = sk;
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87 return;
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88 }
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89 #endif
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90
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91 //generates spectral kernel matrix (upside down?)
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92 // initialise temporal kernel with zeros, twice length to deal w. complex numbers
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93
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94 double* hammingWindowRe = new double [ m_FFTLength ];
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95 double* hammingWindowIm = new double [ m_FFTLength ];
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96 double* transfHammingWindowRe = new double [ m_FFTLength ];
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97 double* transfHammingWindowIm = new double [ m_FFTLength ];
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98
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99 for (unsigned u=0; u < m_FFTLength; u++)
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100 {
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101 hammingWindowRe[u] = 0;
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102 hammingWindowIm[u] = 0;
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103 }
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104
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105 // Here, fftleng*2 is a guess of the number of sparse cells in the matrix
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106 // The matrix K x fftlength but the non-zero cells are an antialiased
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107 // square root function. So mostly is a line, with some grey point.
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108 sk->is.reserve( m_FFTLength*2 );
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109 sk->js.reserve( m_FFTLength*2 );
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110 sk->real.reserve( m_FFTLength*2 );
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111 sk->imag.reserve( m_FFTLength*2 );
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112
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113 // for each bin value K, calculate temporal kernel, take its fft to
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114 //calculate the spectral kernel then threshold it to make it sparse and
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115 //add it to the sparse kernels matrix
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116 double squareThreshold = m_CQThresh * m_CQThresh;
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117
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118 FFT m_FFT(m_FFTLength);
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119
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120 for (unsigned k = m_uK; k--; )
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121 {
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122 for (unsigned u=0; u < m_FFTLength; u++)
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123 {
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124 hammingWindowRe[u] = 0;
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125 hammingWindowIm[u] = 0;
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126 }
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127
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128 // Computing a hamming window
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129 const unsigned hammingLength = (int) ceil( m_dQ * m_FS / ( m_FMin * pow(2,((double)(k))/(double)m_BPO)));
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130
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131 unsigned origin = m_FFTLength/2 - hammingLength/2;
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132
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133 for (unsigned i=0; i<hammingLength; i++)
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134 {
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135 const double angle = 2*PI*m_dQ*i/hammingLength;
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136 const double real = cos(angle);
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137 const double imag = sin(angle);
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138 const double absol = hamming(hammingLength, i)/hammingLength;
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139 hammingWindowRe[ origin + i ] = absol*real;
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140 hammingWindowIm[ origin + i ] = absol*imag;
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141 }
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142
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143 for (unsigned i = 0; i < m_FFTLength/2; ++i) {
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144 double temp = hammingWindowRe[i];
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145 hammingWindowRe[i] = hammingWindowRe[i + m_FFTLength/2];
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146 hammingWindowRe[i + m_FFTLength/2] = temp;
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147 temp = hammingWindowIm[i];
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148 hammingWindowIm[i] = hammingWindowIm[i + m_FFTLength/2];
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149 hammingWindowIm[i + m_FFTLength/2] = temp;
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150 }
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151
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152 //do fft of hammingWindow
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153 m_FFT.process( 0, hammingWindowRe, hammingWindowIm, transfHammingWindowRe, transfHammingWindowIm );
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154
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155
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156 for (unsigned j=0; j<( m_FFTLength ); j++)
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157 {
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158 // perform thresholding
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159 const double squaredBin = squaredModule( transfHammingWindowRe[ j ], transfHammingWindowIm[ j ]);
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160 if (squaredBin <= squareThreshold) continue;
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161
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162 // Insert non-zero position indexes, doubled because they are floats
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163 sk->is.push_back(j);
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164 sk->js.push_back(k);
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165
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166 // take conjugate, normalise and add to array sparkernel
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167 sk->real.push_back( transfHammingWindowRe[ j ]/m_FFTLength);
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168 sk->imag.push_back(-transfHammingWindowIm[ j ]/m_FFTLength);
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169 }
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170
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171 }
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172
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173 delete [] hammingWindowRe;
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174 delete [] hammingWindowIm;
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175 delete [] transfHammingWindowRe;
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176 delete [] transfHammingWindowIm;
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177
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178 /*
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179 using std::cout;
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180 using std::endl;
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181
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182 cout.precision(28);
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183
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184 int n = sk->is.size();
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185 int w = 8;
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186 cout << "static unsigned int sk_i_" << m_uK << "_" << m_FFTLength << "[" << n << "] = {" << endl;
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187 for (int i = 0; i < n; ++i) {
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188 if (i % w == 0) cout << " ";
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189 cout << sk->is[i];
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190 if (i + 1 < n) cout << ", ";
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191 if (i % w == w-1) cout << endl;
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192 };
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193 if (n % w != 0) cout << endl;
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194 cout << "};" << endl;
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195
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196 n = sk->js.size();
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197 cout << "static unsigned int sk_j_" << m_uK << "_" << m_FFTLength << "[" << n << "] = {" << endl;
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198 for (int i = 0; i < n; ++i) {
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199 if (i % w == 0) cout << " ";
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200 cout << sk->js[i];
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201 if (i + 1 < n) cout << ", ";
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202 if (i % w == w-1) cout << endl;
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203 };
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204 if (n % w != 0) cout << endl;
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205 cout << "};" << endl;
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206
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207 w = 2;
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208 n = sk->real.size();
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209 cout << "static double sk_real_" << m_uK << "_" << m_FFTLength << "[" << n << "] = {" << endl;
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210 for (int i = 0; i < n; ++i) {
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211 if (i % w == 0) cout << " ";
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212 cout << sk->real[i];
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213 if (i + 1 < n) cout << ", ";
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214 if (i % w == w-1) cout << endl;
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215 };
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216 if (n % w != 0) cout << endl;
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217 cout << "};" << endl;
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218
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219 n = sk->imag.size();
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220 cout << "static double sk_imag_" << m_uK << "_" << m_FFTLength << "[" << n << "] = {" << endl;
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221 for (int i = 0; i < n; ++i) {
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222 if (i % w == 0) cout << " ";
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223 cout << sk->imag[i];
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224 if (i + 1 < n) cout << ", ";
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225 if (i % w == w-1) cout << endl;
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226 };
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227 if (n % w != 0) cout << endl;
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228 cout << "};" << endl;
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229
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230 cout << "static void push_" << m_uK << "_" << m_FFTLength << "(vector<unsigned int> &is, vector<unsigned int> &js, vector<double> &real, vector<double> &imag)" << endl;
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231 cout << "{\n is.reserve(" << n << ");\n";
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232 cout << " js.reserve(" << n << ");\n";
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233 cout << " real.reserve(" << n << ");\n";
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234 cout << " imag.reserve(" << n << ");\n";
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235 cout << " for (int i = 0; i < " << n << "; ++i) {" << endl;
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236 cout << " is.push_back(sk_i_" << m_uK << "_" << m_FFTLength << "[i]);" << endl;
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237 cout << " js.push_back(sk_j_" << m_uK << "_" << m_FFTLength << "[i]);" << endl;
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238 cout << " real.push_back(sk_real_" << m_uK << "_" << m_FFTLength << "[i]);" << endl;
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239 cout << " imag.push_back(sk_imag_" << m_uK << "_" << m_FFTLength << "[i]);" << endl;
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240 cout << " }" << endl;
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241 cout << "}" << endl;
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242 */
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243 // std::cerr << "done\n -> is: " << sk->is.size() << ", js: " << sk->js.size() << ", reals: " << sk->real.size() << ", imags: " << sk->imag.size() << std::endl;
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244
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245 m_sparseKernel = sk;
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246 return;
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247 }
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248
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249 //-----------------------------------------------------------------------------
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250 double* ConstantQ::process( const double* fftdata )
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251 {
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252 if (!m_sparseKernel) {
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253 std::cerr << "ERROR: ConstantQ::process: Sparse kernel has not been initialised" << std::endl;
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254 return m_CQdata;
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255 }
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256
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257 SparseKernel *sk = m_sparseKernel;
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258
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259 for (unsigned row=0; row<2*m_uK; row++)
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260 {
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261 m_CQdata[ row ] = 0;
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262 m_CQdata[ row+1 ] = 0;
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263 }
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264 const unsigned *fftbin = &(sk->is[0]);
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265 const unsigned *cqbin = &(sk->js[0]);
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266 const double *real = &(sk->real[0]);
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267 const double *imag = &(sk->imag[0]);
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268 const unsigned int sparseCells = sk->real.size();
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269
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270 for (unsigned i = 0; i<sparseCells; i++)
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271 {
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272 const unsigned row = cqbin[i];
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273 const unsigned col = fftbin[i];
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274 const double & r1 = real[i];
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275 const double & i1 = imag[i];
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276 const double & r2 = fftdata[ (2*m_FFTLength) - 2*col - 2 ];
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277 const double & i2 = fftdata[ (2*m_FFTLength) - 2*col - 2 + 1 ];
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278 // add the multiplication
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279 m_CQdata[ 2*row ] += (r1*r2 - i1*i2);
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280 m_CQdata[ 2*row+1] += (r1*i2 + i1*r2);
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281 }
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282
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283 return m_CQdata;
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284 }
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285
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286
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287 void ConstantQ::initialise( CQConfig Config )
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288 {
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289 m_FS = Config.FS;
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290 m_FMin = Config.min; // min freq
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291 m_FMax = Config.max; // max freq
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292 m_BPO = Config.BPO; // bins per octave
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293 m_CQThresh = Config.CQThresh;// ConstantQ threshold for kernel generation
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294
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295 m_dQ = 1/(pow(2,(1/(double)m_BPO))-1); // Work out Q value for Filter bank
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296 m_uK = (unsigned int) ceil(m_BPO * log(m_FMax/m_FMin)/log(2.0)); // No. of constant Q bins
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297
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298 // std::cerr << "ConstantQ::initialise: rate = " << m_FS << ", fmin = " << m_FMin << ", fmax = " << m_FMax << ", bpo = " << m_BPO << ", K = " << m_uK << ", Q = " << m_dQ << std::endl;
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299
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300 // work out length of fft required for this constant Q Filter bank
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301 m_FFTLength = (int) pow(2, nextpow2(ceil( m_dQ*m_FS/m_FMin )));
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302
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303 m_hop = m_FFTLength/8; // <------ hop size is window length divided by 32
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304
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c@249
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305 // std::cerr << "ConstantQ::initialise: -> fft length = " << m_FFTLength << ", hop = " << m_hop << std::endl;
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306
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307 // allocate memory for cqdata
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308 m_CQdata = new double [2*m_uK];
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309 }
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310
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311 void ConstantQ::deInitialise()
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312 {
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313 delete [] m_CQdata;
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314 delete m_sparseKernel;
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c@225
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315 }
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316
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c@257
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317 void ConstantQ::process(const double *FFTRe, const double* FFTIm,
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c@257
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318 double *CQRe, double *CQIm)
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c@225
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319 {
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320 if (!m_sparseKernel) {
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321 std::cerr << "ERROR: ConstantQ::process: Sparse kernel has not been initialised" << std::endl;
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c@276
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322 return;
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c@276
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323 }
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324
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325 SparseKernel *sk = m_sparseKernel;
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326
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327 for (unsigned row=0; row<m_uK; row++)
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328 {
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329 CQRe[ row ] = 0;
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330 CQIm[ row ] = 0;
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c@225
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331 }
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332
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c@276
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333 const unsigned *fftbin = &(sk->is[0]);
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c@276
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334 const unsigned *cqbin = &(sk->js[0]);
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c@276
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335 const double *real = &(sk->real[0]);
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c@276
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336 const double *imag = &(sk->imag[0]);
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c@276
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337 const unsigned int sparseCells = sk->real.size();
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c@225
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338
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c@225
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339 for (unsigned i = 0; i<sparseCells; i++)
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c@225
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340 {
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341 const unsigned row = cqbin[i];
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c@225
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342 const unsigned col = fftbin[i];
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c@225
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343 const double & r1 = real[i];
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c@225
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344 const double & i1 = imag[i];
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c@263
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345 const double & r2 = FFTRe[ m_FFTLength - col - 1 ];
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c@263
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346 const double & i2 = FFTIm[ m_FFTLength - col - 1 ];
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c@225
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347 // add the multiplication
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c@225
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348 CQRe[ row ] += (r1*r2 - i1*i2);
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c@225
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349 CQIm[ row ] += (r1*i2 + i1*r2);
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c@225
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350 }
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c@225
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351 }
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