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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 /*
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4 Vamp
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5
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6 An API for audio analysis and feature extraction plugins.
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7
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8 Centre for Digital Music, Queen Mary, University of London.
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9 Copyright 2006 Chris Cannam.
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10
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11 Permission is hereby granted, free of charge, to any person
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12 obtaining a copy of this software and associated documentation
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13 files (the "Software"), to deal in the Software without
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14 restriction, including without limitation the rights to use, copy,
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15 modify, merge, publish, distribute, sublicense, and/or sell copies
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16 of the Software, and to permit persons to whom the Software is
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17 furnished to do so, subject to the following conditions:
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18
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19 The above copyright notice and this permission notice shall be
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20 included in all copies or substantial portions of the Software.
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21
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22 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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23 EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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24 MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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25 NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR
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26 ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
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27 CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
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28 WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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29
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30 Except as contained in this notice, the names of the Centre for
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31 Digital Music; Queen Mary, University of London; and Chris Cannam
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32 shall not be used in advertising or otherwise to promote the sale,
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33 use or other dealings in this Software without prior written
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34 authorization.
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35 */
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36
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37 #include "SpectralCentroid.h"
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38
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39 using std::string;
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40 using std::vector;
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41 using std::cerr;
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42 using std::endl;
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43
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44 #include <cmath>
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45
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46
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47 SpectralCentroid::SpectralCentroid(float inputSampleRate) :
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48 Plugin(inputSampleRate),
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49 m_stepSize(0),
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50 m_blockSize(0),
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51 m_workBuffer(0)
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52 {
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53 }
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54
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55 SpectralCentroid::~SpectralCentroid()
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56 {
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57 delete m_workBuffer;
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58 }
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59
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60 string
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61 SpectralCentroid::getName() const
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62 {
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63 return "spectralcentroid";
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64 }
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65
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66 string
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67 SpectralCentroid::getDescription() const
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68 {
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69 return "Spectral Centroid";
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70 }
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71
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72 string
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73 SpectralCentroid::getMaker() const
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74 {
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75 return "Queen Mary, University of London";
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76 }
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77
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78 int
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79 SpectralCentroid::getPluginVersion() const
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80 {
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81 return 2;
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82 }
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83
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84 string
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85 SpectralCentroid::getCopyright() const
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86 {
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87 return "Freely redistributable (BSD license)";
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88 }
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89
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90 bool
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91 SpectralCentroid::initialise(size_t channels, size_t stepSize, size_t blockSize)
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92 {
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93 if (channels < getMinChannelCount() ||
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94 channels > getMaxChannelCount()) return false;
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95
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96 m_stepSize = stepSize;
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97 m_blockSize = blockSize;
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98
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99 delete m_workBuffer;
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100 m_workBuffer = new double[m_blockSize * 4];
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101
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102 return true;
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103 }
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104
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105 void
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106 SpectralCentroid::reset()
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107 {
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108 delete m_workBuffer;
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109 m_workBuffer = new double[m_blockSize * 4];
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110 }
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111
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112 size_t
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113 SpectralCentroid::getPreferredStepSize() const
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114 {
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115 return 2048; // or whatever -- parameter?
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116 }
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117
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118 size_t
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119 SpectralCentroid::getPreferredBlockSize() const
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120 {
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121 return getPreferredStepSize();
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122 }
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123
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124 SpectralCentroid::OutputList
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125 SpectralCentroid::getOutputDescriptors() const
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126 {
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127 OutputList list;
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128
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129 OutputDescriptor d;
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130 d.name = "logcentroid";
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131 d.unit = "Hz";
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132 d.description = "Log Frequency Centroid";
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133 d.hasFixedValueCount = true;
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134 d.valueCount = 1;
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135 d.hasKnownExtents = false;
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136 d.isQuantized = false;
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137 d.sampleType = OutputDescriptor::OneSamplePerStep;
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138 list.push_back(d);
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139
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140 d.name = "linearcentroid";
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141 d.description = "Linear Frequency Centroid";
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142 list.push_back(d);
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143
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144 return list;
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145 }
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146
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147 SpectralCentroid::FeatureSet
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148 SpectralCentroid::process(float **inputBuffers, Vamp::RealTime)
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149 {
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150 if (m_stepSize == 0) {
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151 cerr << "ERROR: SpectralCentroid::process: "
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152 << "SpectralCentroid has not been initialised"
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153 << endl;
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154 return FeatureSet();
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155 }
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156
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157 double numLin = 0.0, numLog = 0.0, denom = 0.0;
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158
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159 for (size_t i = 1; i < m_blockSize/2; ++i) {
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160 double freq = (double(i) * m_inputSampleRate) / m_blockSize;
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161 double real = inputBuffers[0][i*2];
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162 double imag = inputBuffers[0][i*2 + 1];
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163 double power = sqrt(real * real + imag * imag) / (m_blockSize/2);
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164 numLin += freq * power;
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165 numLog += log10f(freq) * power;
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166 denom += power;
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167 }
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168
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169 FeatureSet returnFeatures;
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170
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171 std::cerr << "power " << denom << ", block size " << m_blockSize << std::endl;
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172
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173 if (denom != 0.0) {
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174 float centroidLin = float(numLin / denom);
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175 float centroidLog = exp10f(float(numLog / denom));
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176 Feature feature;
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177 feature.hasTimestamp = false;
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178 feature.values.push_back(centroidLog);
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179 returnFeatures[0].push_back(feature);
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180 feature.values.clear();
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181 feature.values.push_back(centroidLin);
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182 returnFeatures[1].push_back(feature);
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183 }
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184
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185 return returnFeatures;
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186 }
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187
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188 SpectralCentroid::FeatureSet
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189 SpectralCentroid::getRemainingFeatures()
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190 {
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191 return FeatureSet();
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192 }
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193
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