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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 2006-2008 Chris Cannam and QMUL.
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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 "PluginSummarisingAdapter.h"
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38
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39 #include <map>
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40 #include <cmath>
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41 #include <climits>
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42
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43 namespace Vamp {
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44
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45 namespace HostExt {
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46
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47 class PluginSummarisingAdapter::Impl
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48 {
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49 public:
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50 Impl(Plugin *plugin, float inputSampleRate);
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51 ~Impl();
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52
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53 FeatureSet process(const float *const *inputBuffers, RealTime timestamp);
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54 FeatureSet getRemainingFeatures();
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55
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56 void setSummarySegmentBoundaries(const SegmentBoundaries &);
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57
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58 FeatureList getSummaryForOutput(int output,
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59 SummaryType type,
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60 AveragingMethod avg);
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61
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62 FeatureSet getSummaryForAllOutputs(SummaryType type,
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63 AveragingMethod avg);
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64
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65 protected:
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66 Plugin *m_plugin;
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67 float m_inputSampleRate;
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68
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69 SegmentBoundaries m_boundaries;
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70
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71 typedef std::vector<float> ValueList;
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72
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73 struct Result { // smaller than Feature
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74 RealTime time;
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75 RealTime duration;
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76 ValueList values; // bin number -> value
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77 };
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78
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79 typedef std::vector<Result> ResultList;
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80
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81 struct OutputAccumulator {
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82 int bins;
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83 ResultList results;
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84 OutputAccumulator() : bins(0) { }
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85 };
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86
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87 typedef std::map<int, OutputAccumulator> OutputAccumulatorMap;
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88 OutputAccumulatorMap m_accumulators; // output number -> accumulator
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89
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90 typedef std::map<RealTime, OutputAccumulator> SegmentAccumulatorMap;
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91 typedef std::map<int, SegmentAccumulatorMap> OutputSegmentAccumulatorMap;
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92 OutputSegmentAccumulatorMap m_segmentedAccumulators;
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93
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94 typedef std::map<int, RealTime> OutputTimestampMap;
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95 OutputTimestampMap m_prevTimestamps; // output number -> timestamp
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96 OutputTimestampMap m_prevDurations; // output number -> durations
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97
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98 struct OutputBinSummary {
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99
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100 int count;
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101
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102 // extents
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103 float minimum;
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104 float maximum;
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105 float sum;
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106
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107 // sample-average results
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108 float median;
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109 float mode;
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110 float variance;
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111
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112 // continuous-time average results
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113 float median_c;
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114 float mode_c;
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115 float mean_c;
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116 float variance_c;
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117 };
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118
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119 typedef std::map<int, OutputBinSummary> OutputSummary;
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120 typedef std::map<RealTime, OutputSummary> SummarySegmentMap;
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121 typedef std::map<int, SummarySegmentMap> OutputSummarySegmentMap;
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122
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123 OutputSummarySegmentMap m_summaries;
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124
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125 bool m_reduced;
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126 RealTime m_lastTimestamp;
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127
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128 void accumulate(const FeatureSet &fs, RealTime, bool final);
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129 void accumulate(int output, const Feature &f, RealTime, bool final);
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130 void accumulateFinalDurations();
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131 void findSegmentBounds(RealTime t, RealTime &start, RealTime &end);
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132 void segment();
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133 void reduce();
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134 };
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135
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136 static RealTime INVALID_DURATION(INT_MIN, INT_MIN);
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137
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138 PluginSummarisingAdapter::PluginSummarisingAdapter(Plugin *plugin) :
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139 PluginWrapper(plugin)
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140 {
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141 m_impl = new Impl(plugin, m_inputSampleRate);
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142 }
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143
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144 PluginSummarisingAdapter::~PluginSummarisingAdapter()
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145 {
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146 delete m_impl;
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147 }
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148
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149 Plugin::FeatureSet
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150 PluginSummarisingAdapter::process(const float *const *inputBuffers, RealTime timestamp)
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151 {
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152 return m_impl->process(inputBuffers, timestamp);
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153 }
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154
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155 Plugin::FeatureSet
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156 PluginSummarisingAdapter::getRemainingFeatures()
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157 {
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158 return m_impl->getRemainingFeatures();
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159 }
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160
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161 Plugin::FeatureList
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162 PluginSummarisingAdapter::getSummaryForOutput(int output,
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163 SummaryType type,
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164 AveragingMethod avg)
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165 {
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166 return m_impl->getSummaryForOutput(output, type, avg);
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167 }
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168
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169 Plugin::FeatureSet
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170 PluginSummarisingAdapter::getSummaryForAllOutputs(SummaryType type,
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171 AveragingMethod avg)
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172 {
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173 return m_impl->getSummaryForAllOutputs(type, avg);
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174 }
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175
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176 PluginSummarisingAdapter::Impl::Impl(Plugin *plugin, float inputSampleRate) :
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177 m_plugin(plugin),
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178 m_inputSampleRate(inputSampleRate),
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179 m_reduced(false)
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180 {
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181 }
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182
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183 PluginSummarisingAdapter::Impl::~Impl()
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184 {
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185 }
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186
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187 Plugin::FeatureSet
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188 PluginSummarisingAdapter::Impl::process(const float *const *inputBuffers, RealTime timestamp)
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189 {
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190 if (m_reduced) {
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191 std::cerr << "WARNING: Cannot call PluginSummarisingAdapter::process() or getRemainingFeatures() after one of the getSummary methods" << std::endl;
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192 }
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193 FeatureSet fs = m_plugin->process(inputBuffers, timestamp);
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194 accumulate(fs, timestamp, false);
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195 //!!! should really be "timestamp plus step size"
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196 m_lastTimestamp = timestamp;
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197 return fs;
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198 }
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199
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200 Plugin::FeatureSet
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201 PluginSummarisingAdapter::Impl::getRemainingFeatures()
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202 {
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203 if (m_reduced) {
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204 std::cerr << "WARNING: Cannot call PluginSummarisingAdapter::process() or getRemainingFeatures() after one of the getSummary methods" << std::endl;
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205 }
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206 FeatureSet fs = m_plugin->getRemainingFeatures();
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207 accumulate(fs, m_lastTimestamp, true);
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208 return fs;
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209 }
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210
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211 Plugin::FeatureList
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212 PluginSummarisingAdapter::Impl::getSummaryForOutput(int output,
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213 SummaryType type,
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214 AveragingMethod avg)
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215 {
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216 if (!m_reduced) {
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217 segment();
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218 reduce();
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219 m_reduced = true;
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220 }
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221
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222 bool continuous = (avg == ContinuousTimeAverage);
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223
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224 FeatureList fl;
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225 for (SummarySegmentMap::const_iterator i = m_summaries[output].begin();
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226 i != m_summaries[output].end(); ++i) {
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227
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228 Feature f;
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229 f.hasTimestamp = true;
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230 f.timestamp = i->first;
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231 f.hasDuration = false;
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232
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233 for (OutputSummary::const_iterator j = i->second.begin();
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234 j != i->second.end(); ++j) {
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235
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236 // these will be ordered by bin number, and no bin numbers
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237 // will be missing except at the end (because of the way
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238 // the accumulators were initially filled in accumulate())
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239
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240 const OutputBinSummary &summary = j->second;
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241 float result = 0.f;
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242
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243 switch (type) {
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244
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245 case Minimum:
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246 result = summary.minimum;
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247 break;
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248
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249 case Maximum:
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250 result = summary.maximum;
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251 break;
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252
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253 case Mean:
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254 if (continuous) {
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255 result = summary.mean_c;
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256 } else if (summary.count) {
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257 result = summary.sum / summary.count;
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258 }
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259 break;
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260
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261 case Median:
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262 if (continuous) result = summary.median_c;
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263 else result = summary.median;
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264 break;
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265
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266 case Mode:
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267 if (continuous) result = summary.mode_c;
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268 else result = summary.mode;
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269 break;
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270
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271 case Sum:
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272 result = summary.sum;
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273 break;
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274
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275 case Variance:
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276 if (continuous) result = summary.variance_c;
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277 else result = summary.variance;
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278 break;
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279
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280 case StandardDeviation:
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281 if (continuous) result = sqrtf(summary.variance_c);
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282 else result = sqrtf(summary.variance);
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283 break;
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284
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285 case Count:
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286 result = summary.count;
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287 break;
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288
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289 default:
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290 break;
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291 }
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292
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293 f.values.push_back(result);
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294 }
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295
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296 fl.push_back(f);
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297 }
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298 return fl;
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299 }
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300
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301 Plugin::FeatureSet
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302 PluginSummarisingAdapter::Impl::getSummaryForAllOutputs(SummaryType type,
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303 AveragingMethod avg)
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304 {
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305 if (!m_reduced) {
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306 segment();
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307 reduce();
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308 m_reduced = true;
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309 }
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310
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311 FeatureSet fs;
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312 for (OutputSummarySegmentMap::const_iterator i = m_summaries.begin();
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313 i != m_summaries.end(); ++i) {
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314 fs[i->first] = getSummaryForOutput(i->first, type, avg);
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315 }
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316 return fs;
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317 }
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318
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319 void
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320 PluginSummarisingAdapter::Impl::accumulate(const FeatureSet &fs,
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321 RealTime timestamp,
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322 bool final)
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323 {
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cannam@174
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324 for (FeatureSet::const_iterator i = fs.begin(); i != fs.end(); ++i) {
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325 for (FeatureList::const_iterator j = i->second.begin();
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326 j != i->second.end(); ++j) {
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cannam@182
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327 if (j->hasTimestamp) {
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328 accumulate(i->first, *j, j->timestamp, final);
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329 } else {
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cannam@182
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330 //!!! is this correct?
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331 accumulate(i->first, *j, timestamp, final);
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332 }
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333 }
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334 }
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335 }
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336
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cannam@174
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337 void
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338 PluginSummarisingAdapter::Impl::accumulate(int output,
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339 const Feature &f,
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340 RealTime timestamp,
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341 bool final)
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342 {
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cannam@180
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343 //!!! to do: use timestamp to determine which segment we're on
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344
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cannam@185
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345 //!!! What should happen if a feature's duration spans a segment
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346 // boundary? I think we probably want to chop it, and pretend that it
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347 // appears in both -- don't we? do we? A very long feature (e.g. key,
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348 // if the whole audio is in a single key) might span many or all
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349 // segments, and we want that to be reflected in the results (e.g. it
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350 // is the modal key in all of those segments, not just the first).
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cannam@185
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351 // That is actually quite complicated to do!
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352
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cannam@185
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353 //!!! This affects how we record things. If features spanning a
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354 // boundary should be chopped, then we need to have per-segment
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355 // accumulators (and the feature value goes into both -- perhaps we
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356 // need a separate phase to split the accumulator up into segments).
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357 // If features spanning a boundary should be counted only in the first
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358 // segment, with their full duration, then we should store them in a
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359 // single accumulator and distribute into segments only on reduce.
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360
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cannam@184
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361 std::cerr << "output " << output << ": timestamp " << timestamp << ", prev timestamp " << m_prevTimestamps[output] << ", final " << final << std::endl;
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cannam@182
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362
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cannam@184
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363 // At each process step, accumulate() is called once for each
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cannam@184
|
364 // feature on each output within that process's returned feature
|
cannam@184
|
365 // list, and with the timestamp passed in being that of the start
|
cannam@184
|
366 // of the process block.
|
cannam@182
|
367
|
cannam@184
|
368 // At the end (in getRemainingFeatures), accumulate() is called
|
cannam@184
|
369 // once for each feature on each output within the feature list
|
cannam@184
|
370 // returned by getRemainingFeatures, and with the timestamp being
|
cannam@184
|
371 // the same as the last process block and final set to true.
|
cannam@184
|
372
|
cannam@184
|
373 // (What if getRemainingFeatures doesn't return any features? We
|
cannam@184
|
374 // still need to ensure that the final duration is written. Need
|
cannam@184
|
375 // a separate function to close the durations.)
|
cannam@184
|
376
|
cannam@184
|
377 // At each call, we pull out the value for the feature and stuff
|
cannam@184
|
378 // it into the accumulator's appropriate values array; and we
|
cannam@184
|
379 // calculate the duration for the _previous_ feature, or pull it
|
cannam@184
|
380 // from the prevDurations array if the previous feature had a
|
cannam@184
|
381 // duration in its structure, and stuff that into the
|
cannam@184
|
382 // accumulator's appropriate durations array.
|
cannam@184
|
383
|
cannam@184
|
384 if (m_prevDurations.find(output) != m_prevDurations.end()) {
|
cannam@184
|
385
|
cannam@184
|
386 // Not the first time accumulate has been called for this
|
cannam@184
|
387 // output -- there has been a previous feature
|
cannam@184
|
388
|
cannam@184
|
389 RealTime prevDuration;
|
cannam@184
|
390
|
cannam@184
|
391 // Note that m_prevDurations[output] only contains the
|
cannam@184
|
392 // duration field that was contained in the previous feature.
|
cannam@184
|
393 // If it didn't have an explicit duration,
|
cannam@184
|
394 // m_prevDurations[output] should be INVALID_DURATION and we
|
cannam@184
|
395 // will have to calculate the duration from the previous and
|
cannam@184
|
396 // current timestamps.
|
cannam@184
|
397
|
cannam@184
|
398 if (m_prevDurations[output] != INVALID_DURATION) {
|
cannam@184
|
399 prevDuration = m_prevDurations[output];
|
cannam@184
|
400 std::cerr << "Previous duration from previous feature: " << prevDuration << std::endl;
|
cannam@184
|
401 } else {
|
cannam@184
|
402 prevDuration = timestamp - m_prevTimestamps[output];
|
cannam@184
|
403 std::cerr << "Previous duration from diff: " << timestamp << " - "
|
cannam@184
|
404 << m_prevTimestamps[output] << std::endl;
|
cannam@180
|
405 }
|
cannam@184
|
406
|
cannam@184
|
407 std::cerr << "output " << output << ": ";
|
cannam@184
|
408
|
cannam@184
|
409 std::cerr << "Pushing previous duration as " << prevDuration << std::endl;
|
cannam@185
|
410
|
cannam@185
|
411 m_accumulators[output].results
|
cannam@185
|
412 [m_accumulators[output].results.size() - 1]
|
cannam@185
|
413 .duration = prevDuration;
|
cannam@180
|
414 }
|
cannam@180
|
415
|
cannam@184
|
416 if (f.hasDuration) m_prevDurations[output] = f.duration;
|
cannam@184
|
417 else m_prevDurations[output] = INVALID_DURATION;
|
cannam@184
|
418
|
cannam@180
|
419 m_prevTimestamps[output] = timestamp;
|
cannam@185
|
420
|
cannam@185
|
421 //!!! should really be "timestamp plus duration" or "timestamp plus output resolution"
|
cannam@184
|
422 if (timestamp > m_lastTimestamp) m_lastTimestamp = timestamp;
|
cannam@180
|
423
|
cannam@185
|
424 Result result;
|
cannam@185
|
425 result.time = timestamp;
|
cannam@185
|
426 result.duration = INVALID_DURATION;
|
cannam@185
|
427
|
cannam@185
|
428 if (f.values.size() > m_accumulators[output].bins) {
|
cannam@185
|
429 m_accumulators[output].bins = f.values.size();
|
cannam@185
|
430 }
|
cannam@185
|
431
|
cannam@174
|
432 for (int i = 0; i < int(f.values.size()); ++i) {
|
cannam@185
|
433 result.values.push_back(f.values[i]);
|
cannam@174
|
434 }
|
cannam@185
|
435
|
cannam@185
|
436 m_accumulators[output].results.push_back(result);
|
cannam@184
|
437 }
|
cannam@180
|
438
|
cannam@184
|
439 void
|
cannam@184
|
440 PluginSummarisingAdapter::Impl::accumulateFinalDurations()
|
cannam@184
|
441 {
|
cannam@184
|
442 for (OutputTimestampMap::iterator i = m_prevTimestamps.begin();
|
cannam@184
|
443 i != m_prevTimestamps.end(); ++i) {
|
cannam@184
|
444
|
cannam@184
|
445 int output = i->first;
|
cannam@185
|
446
|
cannam@185
|
447 int acount = m_accumulators[output].results.size();
|
cannam@185
|
448
|
cannam@185
|
449 if (acount == 0) continue;
|
cannam@185
|
450
|
cannam@184
|
451 RealTime prevTimestamp = i->second;
|
cannam@184
|
452
|
cannam@184
|
453 std::cerr << "output " << output << ": ";
|
cannam@184
|
454
|
cannam@184
|
455 if (m_prevDurations.find(output) != m_prevDurations.end() &&
|
cannam@184
|
456 m_prevDurations[output] != INVALID_DURATION) {
|
cannam@184
|
457
|
cannam@184
|
458 std::cerr << "Pushing final duration from feature as " << m_prevDurations[output] << std::endl;
|
cannam@184
|
459
|
cannam@185
|
460 m_accumulators[output].results[acount - 1].duration =
|
cannam@185
|
461 m_prevDurations[output];
|
cannam@184
|
462
|
cannam@184
|
463 } else {
|
cannam@184
|
464
|
cannam@184
|
465 std::cerr << "Pushing final duration from diff as " << m_lastTimestamp << " - " << m_prevTimestamps[output] << std::endl;
|
cannam@184
|
466
|
cannam@185
|
467 m_accumulators[output].results[acount - 1].duration =
|
cannam@185
|
468 m_lastTimestamp - m_prevTimestamps[output];
|
cannam@184
|
469 }
|
cannam@180
|
470 }
|
cannam@174
|
471 }
|
cannam@174
|
472
|
cannam@185
|
473 void
|
cannam@186
|
474 PluginSummarisingAdapter::Impl::findSegmentBounds(RealTime t,
|
cannam@186
|
475 RealTime &start,
|
cannam@186
|
476 RealTime &end)
|
cannam@186
|
477 {
|
cannam@186
|
478 std::cerr << "findSegmentBounds: t = " << t << std::endl;
|
cannam@186
|
479
|
cannam@186
|
480 SegmentBoundaries::const_iterator i = std::lower_bound
|
cannam@186
|
481 (m_boundaries.begin(), m_boundaries.end(), t);
|
cannam@186
|
482
|
cannam@186
|
483 start = RealTime::zeroTime;
|
cannam@186
|
484 end = m_lastTimestamp;
|
cannam@186
|
485
|
cannam@186
|
486 if (i != m_boundaries.end()) {
|
cannam@186
|
487
|
cannam@186
|
488 start = *i;
|
cannam@186
|
489
|
cannam@186
|
490 if (++i != m_boundaries.end()) {
|
cannam@186
|
491 end = *i;
|
cannam@186
|
492 }
|
cannam@186
|
493 }
|
cannam@186
|
494
|
cannam@186
|
495 std::cerr << "findSegmentBounds: " << t << " is in segment " << start << " -> " << end << std::endl;
|
cannam@186
|
496 }
|
cannam@186
|
497
|
cannam@186
|
498 void
|
cannam@185
|
499 PluginSummarisingAdapter::Impl::segment()
|
cannam@185
|
500 {
|
cannam@185
|
501 SegmentBoundaries::iterator boundaryitr = m_boundaries.begin();
|
cannam@185
|
502 RealTime segmentStart = RealTime::zeroTime;
|
cannam@186
|
503
|
cannam@185
|
504 for (OutputAccumulatorMap::iterator i = m_accumulators.begin();
|
cannam@185
|
505 i != m_accumulators.end(); ++i) {
|
cannam@185
|
506
|
cannam@185
|
507 int output = i->first;
|
cannam@185
|
508 OutputAccumulator &source = i->second;
|
cannam@185
|
509
|
cannam@186
|
510 for (int n = 0; n < source.results.size(); ++n) {
|
cannam@186
|
511
|
cannam@186
|
512 // This result spans source.results[n].time to
|
cannam@186
|
513 // source.results[n].time + source.results[n].duration.
|
cannam@186
|
514 // We need to dispose it into segments appropriately
|
cannam@186
|
515
|
cannam@186
|
516 RealTime resultStart = source.results[n].time;
|
cannam@186
|
517 RealTime resultEnd = resultStart + source.results[n].duration;
|
cannam@186
|
518
|
cannam@186
|
519 RealTime segmentStart = RealTime::zeroTime;
|
cannam@186
|
520 RealTime segmentEnd = resultEnd - RealTime(1, 0);
|
cannam@186
|
521
|
cannam@186
|
522 while (segmentEnd < resultEnd) {
|
cannam@186
|
523
|
cannam@186
|
524 findSegmentBounds(resultStart, segmentStart, segmentEnd);
|
cannam@186
|
525
|
cannam@186
|
526 RealTime chunkStart = resultStart;
|
cannam@186
|
527 if (chunkStart < segmentStart) chunkStart = segmentStart;
|
cannam@186
|
528
|
cannam@186
|
529 RealTime chunkEnd = resultEnd;
|
cannam@186
|
530 if (chunkEnd > segmentEnd) chunkEnd = segmentEnd;
|
cannam@186
|
531
|
cannam@186
|
532 m_segmentedAccumulators[output][segmentStart].bins = source.bins;
|
cannam@186
|
533
|
cannam@186
|
534 Result chunk;
|
cannam@186
|
535 chunk.time = chunkStart;
|
cannam@186
|
536 chunk.duration = chunkEnd - chunkStart;
|
cannam@186
|
537 chunk.values = source.results[n].values;
|
cannam@186
|
538
|
cannam@186
|
539 std::cerr << "chunk for segment " << segmentStart << ": from " << chunk.time << ", duration " << chunk.duration << std::endl;
|
cannam@186
|
540
|
cannam@186
|
541 m_segmentedAccumulators[output][segmentStart].results
|
cannam@186
|
542 .push_back(chunk);
|
cannam@186
|
543
|
cannam@186
|
544 resultStart = chunkEnd;
|
cannam@186
|
545 }
|
cannam@186
|
546 }
|
cannam@186
|
547 }
|
cannam@186
|
548
|
cannam@185
|
549
|
cannam@185
|
550
|
cannam@185
|
551 /*
|
cannam@185
|
552 if (boundaryitr == m_boundaries.end()) {
|
cannam@185
|
553 m_segmentedAccumulators[output][segmentStart] = source;
|
cannam@185
|
554 source.clear();
|
cannam@185
|
555 continue;
|
cannam@185
|
556 }
|
cannam@185
|
557 */
|
cannam@185
|
558
|
cannam@185
|
559
|
cannam@185
|
560
|
cannam@185
|
561
|
cannam@185
|
562 }
|
cannam@185
|
563
|
cannam@181
|
564 struct ValueDurationFloatPair
|
cannam@181
|
565 {
|
cannam@181
|
566 float value;
|
cannam@181
|
567 float duration;
|
cannam@181
|
568
|
cannam@181
|
569 ValueDurationFloatPair() : value(0), duration(0) { }
|
cannam@181
|
570 ValueDurationFloatPair(float v, float d) : value(v), duration(d) { }
|
cannam@181
|
571 ValueDurationFloatPair &operator=(const ValueDurationFloatPair &p) {
|
cannam@181
|
572 value = p.value;
|
cannam@181
|
573 duration = p.duration;
|
cannam@181
|
574 return *this;
|
cannam@181
|
575 }
|
cannam@181
|
576 bool operator<(const ValueDurationFloatPair &p) const {
|
cannam@181
|
577 return value < p.value;
|
cannam@181
|
578 }
|
cannam@181
|
579 };
|
cannam@181
|
580
|
cannam@181
|
581 static double toSec(const RealTime &r)
|
cannam@181
|
582 {
|
cannam@181
|
583 return r.sec + double(r.nsec) / 1000000000.0;
|
cannam@181
|
584 }
|
cannam@181
|
585
|
cannam@174
|
586 void
|
cannam@174
|
587 PluginSummarisingAdapter::Impl::reduce()
|
cannam@174
|
588 {
|
cannam@184
|
589 accumulateFinalDurations();
|
cannam@184
|
590
|
cannam@174
|
591 RealTime segmentStart = RealTime::zeroTime; //!!!
|
cannam@174
|
592
|
cannam@174
|
593 for (OutputAccumulatorMap::iterator i = m_accumulators.begin();
|
cannam@174
|
594 i != m_accumulators.end(); ++i) {
|
cannam@174
|
595
|
cannam@174
|
596 int output = i->first;
|
cannam@174
|
597 OutputAccumulator &accumulator = i->second;
|
cannam@174
|
598
|
cannam@185
|
599 int sz = accumulator.results.size();
|
cannam@185
|
600
|
cannam@182
|
601 double totalDuration = 0.0;
|
cannam@185
|
602 //!!! is this right?
|
cannam@185
|
603 if (sz > 0) {
|
cannam@185
|
604 totalDuration = toSec(accumulator.results[sz-1].time +
|
cannam@185
|
605 accumulator.results[sz-1].duration);
|
cannam@180
|
606 }
|
cannam@180
|
607
|
cannam@185
|
608 for (int bin = 0; bin < accumulator.bins; ++bin) {
|
cannam@174
|
609
|
cannam@180
|
610 // work on all values over time for a single bin
|
cannam@180
|
611
|
cannam@174
|
612 OutputBinSummary summary;
|
cannam@180
|
613
|
cannam@185
|
614 summary.count = sz;
|
cannam@180
|
615
|
cannam@174
|
616 summary.minimum = 0.f;
|
cannam@174
|
617 summary.maximum = 0.f;
|
cannam@180
|
618
|
cannam@174
|
619 summary.median = 0.f;
|
cannam@174
|
620 summary.mode = 0.f;
|
cannam@174
|
621 summary.sum = 0.f;
|
cannam@174
|
622 summary.variance = 0.f;
|
cannam@180
|
623
|
cannam@180
|
624 summary.median_c = 0.f;
|
cannam@180
|
625 summary.mode_c = 0.f;
|
cannam@180
|
626 summary.mean_c = 0.f;
|
cannam@180
|
627 summary.variance_c = 0.f;
|
cannam@180
|
628
|
cannam@185
|
629 if (sz == 0) continue;
|
cannam@180
|
630
|
cannam@181
|
631 std::vector<ValueDurationFloatPair> valvec;
|
cannam@181
|
632
|
cannam@181
|
633 for (int k = 0; k < sz; ++k) {
|
cannam@185
|
634 while (accumulator.results[k].values.size() <
|
cannam@185
|
635 accumulator.bins) {
|
cannam@185
|
636 accumulator.results[k].values.push_back(0.f);
|
cannam@185
|
637 }
|
cannam@185
|
638 }
|
cannam@185
|
639
|
cannam@185
|
640 for (int k = 0; k < sz; ++k) {
|
cannam@185
|
641 float value = accumulator.results[k].values[bin];
|
cannam@185
|
642 valvec.push_back(ValueDurationFloatPair
|
cannam@185
|
643 (value,
|
cannam@185
|
644 toSec(accumulator.results[k].duration)));
|
cannam@181
|
645 }
|
cannam@181
|
646
|
cannam@181
|
647 std::sort(valvec.begin(), valvec.end());
|
cannam@181
|
648
|
cannam@181
|
649 summary.minimum = valvec[0].value;
|
cannam@181
|
650 summary.maximum = valvec[sz-1].value;
|
cannam@174
|
651
|
cannam@174
|
652 if (sz % 2 == 1) {
|
cannam@181
|
653 summary.median = valvec[sz/2].value;
|
cannam@174
|
654 } else {
|
cannam@181
|
655 summary.median = (valvec[sz/2].value + valvec[sz/2 + 1].value) / 2;
|
cannam@174
|
656 }
|
cannam@181
|
657
|
cannam@181
|
658 double duracc = 0.0;
|
cannam@181
|
659 summary.median_c = valvec[sz-1].value;
|
cannam@174
|
660
|
cannam@181
|
661 for (int k = 0; k < sz; ++k) {
|
cannam@181
|
662 duracc += valvec[k].duration;
|
cannam@181
|
663 if (duracc > totalDuration/2) {
|
cannam@181
|
664 summary.median_c = valvec[k].value;
|
cannam@181
|
665 break;
|
cannam@181
|
666 }
|
cannam@181
|
667 }
|
cannam@185
|
668
|
cannam@185
|
669 std::cerr << "median_c = " << summary.median_c << std::endl;
|
cannam@185
|
670 std::cerr << "median = " << summary.median << std::endl;
|
cannam@181
|
671
|
cannam@174
|
672 std::map<float, int> distribution;
|
cannam@174
|
673
|
cannam@174
|
674 for (int k = 0; k < sz; ++k) {
|
cannam@185
|
675 summary.sum += accumulator.results[k].values[bin];
|
cannam@185
|
676 distribution[accumulator.results[k].values[bin]] += 1;
|
cannam@174
|
677 }
|
cannam@174
|
678
|
cannam@174
|
679 int md = 0;
|
cannam@174
|
680
|
cannam@174
|
681 for (std::map<float, int>::iterator di = distribution.begin();
|
cannam@174
|
682 di != distribution.end(); ++di) {
|
cannam@174
|
683 if (di->second > md) {
|
cannam@174
|
684 md = di->second;
|
cannam@174
|
685 summary.mode = di->first;
|
cannam@174
|
686 }
|
cannam@174
|
687 }
|
cannam@174
|
688
|
cannam@174
|
689 distribution.clear();
|
cannam@174
|
690
|
cannam@181
|
691 std::map<float, double> distribution_c;
|
cannam@180
|
692
|
cannam@180
|
693 for (int k = 0; k < sz; ++k) {
|
cannam@185
|
694 distribution_c[accumulator.results[k].values[bin]]
|
cannam@185
|
695 += toSec(accumulator.results[k].duration);
|
cannam@180
|
696 }
|
cannam@180
|
697
|
cannam@181
|
698 double mrd = 0.0;
|
cannam@180
|
699
|
cannam@181
|
700 for (std::map<float, double>::iterator di = distribution_c.begin();
|
cannam@180
|
701 di != distribution_c.end(); ++di) {
|
cannam@180
|
702 if (di->second > mrd) {
|
cannam@180
|
703 mrd = di->second;
|
cannam@180
|
704 summary.mode_c = di->first;
|
cannam@180
|
705 }
|
cannam@180
|
706 }
|
cannam@180
|
707
|
cannam@180
|
708 distribution_c.clear();
|
cannam@180
|
709
|
cannam@181
|
710 if (totalDuration > 0.0) {
|
cannam@181
|
711
|
cannam@181
|
712 double sum_c = 0.0;
|
cannam@181
|
713
|
cannam@181
|
714 for (int k = 0; k < sz; ++k) {
|
cannam@185
|
715 double value = accumulator.results[k].values[bin]
|
cannam@185
|
716 * toSec(accumulator.results[k].duration);
|
cannam@181
|
717 sum_c += value;
|
cannam@181
|
718 }
|
cannam@182
|
719
|
cannam@182
|
720 std::cerr << "mean_c = " << sum_c << " / " << totalDuration << " = "
|
cannam@184
|
721 << sum_c / totalDuration << " (sz = " << sz << ")" << std::endl;
|
cannam@181
|
722
|
cannam@181
|
723 summary.mean_c = sum_c / totalDuration;
|
cannam@181
|
724
|
cannam@181
|
725 for (int k = 0; k < sz; ++k) {
|
cannam@185
|
726 double value = accumulator.results[k].values[bin]
|
cannam@185
|
727 * toSec(accumulator.results[k].duration);
|
cannam@181
|
728 summary.variance_c +=
|
cannam@181
|
729 (value - summary.mean_c) * (value - summary.mean_c);
|
cannam@181
|
730 }
|
cannam@181
|
731
|
cannam@181
|
732 summary.variance_c /= summary.count;
|
cannam@181
|
733 }
|
cannam@181
|
734
|
cannam@174
|
735 float mean = summary.sum / summary.count;
|
cannam@174
|
736
|
cannam@182
|
737 std::cerr << "mean = " << summary.sum << " / " << summary.count << " = "
|
cannam@182
|
738 << summary.sum / summary.count << std::endl;
|
cannam@182
|
739
|
cannam@174
|
740 for (int k = 0; k < sz; ++k) {
|
cannam@185
|
741 float value = accumulator.results[k].values[bin];
|
cannam@185
|
742 summary.variance += (value - mean) * (value - mean);
|
cannam@174
|
743 }
|
cannam@174
|
744 summary.variance /= summary.count;
|
cannam@174
|
745
|
cannam@174
|
746 m_summaries[output][segmentStart][bin] = summary;
|
cannam@174
|
747 }
|
cannam@174
|
748 }
|
cannam@175
|
749
|
cannam@175
|
750 m_accumulators.clear();
|
cannam@174
|
751 }
|
cannam@174
|
752
|
cannam@174
|
753
|
cannam@174
|
754 }
|
cannam@174
|
755
|
cannam@174
|
756 }
|
cannam@174
|
757
|