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1 /* -*- c-basic-offset: 4 -*- vi:set ts=8 sts=4 sw=4: */
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2
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3 /*
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4 A waveform viewer and audio annotation editor.
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5 Chris Cannam, Queen Mary University of London, 2005
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6
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7 This is experimental software. Not for distribution.
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8 */
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9
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10 #include "BeatDetectTransform.h"
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11
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12 #include "model/DenseTimeValueModel.h"
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13 #include "model/SparseOneDimensionalModel.h"
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14
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15 #include <iostream>
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16 #include "dsp/onsets/DetectionFunction.h"
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17 #include "dsp/tempotracking/TempoTrack.h"
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18
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19
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20 BeatDetectTransform::BeatDetectTransform(Model *inputModel) :
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21 Transform(inputModel)
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22 {
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23 // Step resolution for the detection function in seconds
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24 double stepSecs = 0.01161;
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25
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26 // Step resolution for the detection function in samples
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27 size_t stepSize = (size_t)floor((double)inputModel->getSampleRate() *
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28 stepSecs);
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29
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30
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31 // m_w->m_bdf->setResolution(stepSize);
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32 // output->setResolution(stepSize);
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33
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34 std::cerr << "BeatDetectTransform::BeatDetectTransform: input sample rate " << inputModel->getSampleRate() << ", stepSecs " << stepSecs << ", stepSize " << stepSize << ", unrounded stepSize " << double(inputModel->getSampleRate()) * stepSecs << ", output sample rate " << inputModel->getSampleRate() / stepSize << ", unrounded output sample rate " << double(inputModel->getSampleRate()) / double(stepSize) << std::endl;
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35
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36 m_output = new SparseOneDimensionalModel(inputModel->getSampleRate(), 1);
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37 }
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38
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39 BeatDetectTransform::~BeatDetectTransform()
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40 {
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41 // parent does it all
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42 }
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43
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44 TransformName
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45 BeatDetectTransform::getName()
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46 {
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47 return tr("Beats");
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48 }
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49
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50 void
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51 BeatDetectTransform::run()
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52 {
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53 SparseOneDimensionalModel *output = getOutput();
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54 DenseTimeValueModel *input = getInput();
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55 if (!input) return;
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56
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57 DFConfig config;
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58
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59 config.DFType = DF_COMPLEXSD;
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60
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61 // Step resolution for the detection function in seconds
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62 config.stepSecs = 0.01161;
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63
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64 // Step resolution for the detection function in samples
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65 config.stepSize = (unsigned int)floor((double)input->getSampleRate() *
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66 config.stepSecs );
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67
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68 config.frameLength = 2 * config.stepSize;
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69
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70 unsigned int stepSize = config.stepSize;
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71 unsigned int frameLength = config.frameLength;
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72
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73 // m_w->m_bdf->setResolution(stepSize);
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74 output->setResolution(stepSize);
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75
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76 //Tempo Tracking Configuration Parameters
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77 TTParams ttparams;
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78
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79 // Low Pass filter coefficients for detection function smoothing
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80 double* aCoeffs = new double[3];
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81 double* bCoeffs = new double[3];
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82
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83 aCoeffs[ 0 ] = 1;
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84 aCoeffs[ 1 ] = -0.5949;
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85 aCoeffs[ 2 ] = 0.2348;
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86 bCoeffs[ 0 ] = 0.1600;
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87 bCoeffs[ 1 ] = 0.3200;
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88 bCoeffs[ 2 ] = 0.1600;
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89
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90 ttparams.winLength = 512;
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91 ttparams.lagLength = 128;
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92 ttparams.LPOrd = 2;
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93 ttparams.LPACoeffs = aCoeffs;
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94 ttparams.LPBCoeffs = bCoeffs;
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95 ttparams.alpha = 9;
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96 ttparams.WinT.post = 8;
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97 ttparams.WinT.pre = 7;
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98
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99 ////////////////////////////////////////////////////////////
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100 // DetectionFunction
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101 ////////////////////////////////////////////////////////////
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102 // Instantiate and configure detection function object
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103
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104 DetectionFunction df(config);
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105
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106 size_t origin = input->getStartFrame();
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107 size_t frameCount = input->getEndFrame() - origin;
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108 size_t blocks = (frameCount / stepSize);
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109 if (blocks * stepSize < frameCount) ++blocks;
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110
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111 double *buffer = new double[frameLength];
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112
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113 // DF output with causal extension
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114 unsigned int clen = blocks + ttparams.winLength;
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115 double *dfOutput = new double[clen];
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116
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117 std::cerr << "Detecting beats at step size " << stepSize << "..." << std::endl;
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118
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119 for (size_t i = 0; i < clen; ++i) {
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120
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121 // std::cerr << "block " << i << "/" << clen << std::endl;
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122 // std::cerr << ".";
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123
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124 if (i < blocks) {
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125 size_t got = input->getValues(-1, //!!! needs to come from parent layer -- which is not supposed to be in scope at this point
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126 origin + i * stepSize,
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127 origin + i * stepSize + frameLength,
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128 buffer);
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129 while (got < frameLength) buffer[got++] = 0.0;
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130 dfOutput[i] = df.process(buffer);
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131 } else {
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132 dfOutput[i] = 0.0;
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133 }
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134
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135 // m_w->m_bdf->addPoint(SparseTimeValueModel::Point
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136 // (i * stepSize, dfOutput[i],
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137 // QString("%1").arg(dfOutput[i])));
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138 // m_w->m_bdf->setCompletion(i * 99 / clen);
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139 output->setCompletion(i * 99 / clen);
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140
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141 if (m_deleting) {
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142 delete [] buffer;
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143 delete [] dfOutput;
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144 delete [] aCoeffs;
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145 delete [] bCoeffs;
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146 return;
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147 }
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148 }
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149
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150 // m_w->m_bdf->setCompletion(100);
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151
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152 // Tempo Track Object instantiation and configuration
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153 TempoTrack tempoTracker(ttparams);
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154
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155 // Vector of detected onsets
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156 vector<int> beats;
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157
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158 std::cerr << "Running tempo tracker..." << std::endl;
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159
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160 beats = tempoTracker.process(dfOutput, blocks);
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161
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162 delete [] buffer;
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163 delete [] dfOutput;
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164 delete [] aCoeffs;
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165 delete [] bCoeffs;
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166
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167 for (size_t i = 0; i < beats.size(); ++i) {
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168 // std::cerr << "Beat value " << beats[i] << ", multiplying out to " << beats[i] * stepSize << std::endl;
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169 float bpm = 0.0;
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170 int fdiff = 0;
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171 if (i < beats.size() - 1) {
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172 fdiff = (beats[i+1] - beats[i]) * stepSize;
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173 // one beat is fdiff frames, so there are samplerate/fdiff bps,
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174 // so 60*samplerate/fdiff bpm
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175 if (fdiff > 0) {
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176 bpm = (60.0 * input->getSampleRate()) / fdiff;
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177 }
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178 }
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179 output->addPoint(SparseOneDimensionalModel::Point
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180 (origin + beats[i] * stepSize, QString("%1").arg(bpm)));
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181 if (m_deleting) return;
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182 }
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183
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184 output->setCompletion(100);
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185 }
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186
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187 DenseTimeValueModel *
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188 BeatDetectTransform::getInput()
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189 {
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190 DenseTimeValueModel *dtvm =
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191 dynamic_cast<DenseTimeValueModel *>(getInputModel());
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192 if (!dtvm) {
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193 std::cerr << "BeatDetectTransform::getInput: WARNING: Input model is not conformable to DenseTimeValueModel" << std::endl;
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194 }
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195 return dtvm;
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196 }
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197
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198 SparseOneDimensionalModel *
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199 BeatDetectTransform::getOutput()
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200 {
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201 return static_cast<SparseOneDimensionalModel *>(getOutputModel());
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202 }
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203
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