1 | from aubio.task.task import task |
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2 | from aubio.task.silence import tasksilence |
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3 | from aubio.task.utils import * |
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4 | from aubio.aubioclass import * |
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5 | |
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6 | class taskpitch(task): |
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7 | def __init__(self,input,params=None): |
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8 | task.__init__(self,input,params=params) |
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9 | self.shortlist = [0. for i in range(self.params.pitchsmooth)] |
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10 | self.pitchdet = pitchdetection(mode=get_pitch_mode(self.params.pitchmode), |
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11 | bufsize=self.params.bufsize, |
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12 | hopsize=self.params.hopsize, |
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13 | channels=self.channels, |
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14 | samplerate=self.srate, |
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15 | omode=self.params.omode, |
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16 | yinthresh=self.params.yinthresh) |
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17 | |
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18 | def __call__(self): |
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19 | from aubio.median import short_find |
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20 | task.__call__(self) |
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21 | if (aubio_silence_detection(self.myvec(),self.params.silence)==1): |
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22 | freq = -1. |
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23 | else: |
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24 | freq = self.pitchdet(self.myvec) |
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25 | minpitch = self.params.pitchmin |
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26 | maxpitch = self.params.pitchmax |
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27 | if maxpitch and freq > maxpitch : |
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28 | freq = -1. |
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29 | elif minpitch and freq < minpitch : |
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30 | freq = -1. |
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31 | if self.params.pitchsmooth: |
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32 | self.shortlist.append(freq) |
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33 | self.shortlist.pop(0) |
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34 | smoothfreq = short_find(self.shortlist, |
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35 | len(self.shortlist)/2) |
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36 | return smoothfreq |
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37 | else: |
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38 | return freq |
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39 | |
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40 | def compute_all(self): |
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41 | """ Compute data """ |
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42 | mylist = [] |
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43 | while(self.readsize==self.params.hopsize): |
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44 | freq = self() |
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45 | mylist.append(freq) |
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46 | if self.params.verbose: |
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47 | self.fprint("%s\t%s" % (self.frameread*self.params.step,freq)) |
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48 | return mylist |
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49 | |
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50 | def gettruth(self): |
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51 | """ extract ground truth array in frequency """ |
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52 | import os.path |
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53 | """ from wavfile.txt """ |
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54 | datafile = self.input.replace('.wav','.txt') |
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55 | if datafile == self.input: datafile = "" |
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56 | """ from file.<midinote>.wav """ |
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57 | # FIXME very weak check |
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58 | floatpit = self.input.split('.')[-2] |
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59 | if not os.path.isfile(datafile) and len(self.input.split('.')) < 3: |
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60 | print "no ground truth " |
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61 | return False,False |
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62 | elif floatpit: |
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63 | try: |
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64 | self.truth = float(floatpit) |
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65 | #print "ground truth found in filename:", self.truth |
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66 | tasksil = tasksilence(self.input,params=self.params) |
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67 | time,pitch =[],[] |
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68 | while(tasksil.readsize==tasksil.params.hopsize): |
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69 | tasksil() |
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70 | time.append(tasksil.params.step*tasksil.frameread) |
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71 | if not tasksil.issilence: |
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72 | pitch.append(self.truth) |
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73 | else: |
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74 | pitch.append(-1.) |
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75 | return time,pitch #0,aubio_miditofreq(float(floatpit)) |
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76 | except ValueError: |
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77 | # FIXME very weak check |
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78 | if not os.path.isfile(datafile): |
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79 | print "no ground truth found" |
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80 | return 0,0 |
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81 | else: |
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82 | from aubio.txtfile import read_datafile |
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83 | values = read_datafile(datafile) |
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84 | time, pitch = [], [] |
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85 | for i in range(len(values)): |
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86 | time.append(values[i][0]) |
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87 | if values[i][1] == 0.0: |
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88 | pitch.append(-1.) |
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89 | else: |
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90 | pitch.append(aubio_freqtomidi(values[i][1])) |
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91 | return time,pitch |
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92 | |
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93 | def oldeval(self,results): |
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94 | def mmean(l): |
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95 | return sum(l)/max(float(len(l)),1) |
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96 | |
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97 | from aubio.median import percental |
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98 | timet,pitcht = self.gettruth() |
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99 | res = [] |
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100 | for i in results: |
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101 | #print i,self.truth |
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102 | if i <= 0: pass |
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103 | else: res.append(self.truth-i) |
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104 | if not res or len(res) < 3: |
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105 | avg = self.truth; med = self.truth |
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106 | else: |
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107 | avg = mmean(res) |
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108 | med = percental(res,len(res)/2) |
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109 | return self.truth, self.truth-med, self.truth-avg |
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110 | |
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111 | def eval(self,pitch,tol=0.5): |
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112 | timet,pitcht = self.gettruth() |
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113 | pitch = [aubio_freqtomidi(i) for i in pitch] |
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114 | for i in range(len(pitch)): |
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115 | if pitch[i] == "nan" or pitch[i] == -1: |
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116 | pitch[i] = -1 |
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117 | time = [ i*self.params.step for i in range(len(pitch)) ] |
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118 | #print len(timet),len(pitcht) |
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119 | #print len(time),len(pitch) |
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120 | if len(timet) != len(time): |
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121 | time = time[1:len(timet)+1] |
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122 | pitch = pitch[1:len(pitcht)+1] |
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123 | #pitcht = [aubio_freqtomidi(i) for i in pitcht] |
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124 | for i in range(len(pitcht)): |
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125 | if pitcht[i] == "nan" or pitcht[i] == "-inf" or pitcht[i] == -1: |
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126 | pitcht[i] = -1 |
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127 | assert len(timet) == len(time) |
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128 | assert len(pitcht) == len(pitch) |
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129 | osil, esil, opit, epit, echr = 0, 0, 0, 0, 0 |
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130 | for i in range(len(pitcht)): |
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131 | if pitcht[i] == -1: # currently silent |
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132 | osil += 1 # count a silence |
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133 | if pitch[i] <= 0. or pitch[i] == "nan": |
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134 | esil += 1 # found a silence |
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135 | else: |
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136 | opit +=1 |
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137 | if abs(pitcht[i] - pitch[i]) < tol: |
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138 | epit += 1 |
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139 | echr += 1 |
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140 | elif abs(pitcht[i] - pitch[i]) % 12. < tol: |
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141 | echr += 1 |
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142 | #else: |
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143 | # print timet[i], pitcht[i], time[i], pitch[i] |
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144 | #print "origsilence", "foundsilence", "origpitch", "foundpitch", "orig pitchroma", "found pitchchroma" |
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145 | #print 100.*esil/float(osil), 100.*epit/float(opit), 100.*echr/float(opit) |
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146 | return osil, esil, opit, epit, echr |
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147 | |
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148 | def plot(self,pitch,wplot,oplots,outplot=None): |
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149 | import numarray |
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150 | import Gnuplot |
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151 | |
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152 | downtime = self.params.step*numarray.arange(len(pitch)) |
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153 | pitch = [aubio_freqtomidi(i) for i in pitch] |
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154 | oplots.append(Gnuplot.Data(downtime,pitch,with='lines', |
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155 | title=self.params.pitchmode)) |
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156 | |
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157 | |
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158 | def plotplot(self,wplot,oplots,outplot=None,multiplot = 1, midi = 1): |
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159 | from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot |
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160 | import re |
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161 | import Gnuplot |
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162 | # audio data |
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163 | time,data = audio_to_array(self.input) |
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164 | f = make_audio_plot(time,data) |
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165 | |
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166 | # check if ground truth exists |
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167 | timet,pitcht = self.gettruth() |
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168 | if timet and pitcht: |
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169 | oplots = [Gnuplot.Data(timet,pitcht,with='lines', |
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170 | title='ground truth')] + oplots |
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171 | |
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172 | t = Gnuplot.Data(0,0,with='impulses') |
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173 | |
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174 | g = gnuplot_init(outplot) |
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175 | g('set title \'%s\'' % (re.sub('.*/','',self.input))) |
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176 | g('set multiplot') |
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177 | # hack to align left axis |
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178 | g('set lmargin 15') |
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179 | # plot waveform and onsets |
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180 | g('set size 1,0.3') |
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181 | g('set origin 0,0.7') |
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182 | g('set xrange [0:%f]' % max(time)) |
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183 | g('set yrange [-1:1]') |
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184 | g.ylabel('amplitude') |
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185 | g.plot(f) |
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186 | g('unset title') |
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187 | # plot onset detection function |
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188 | |
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189 | |
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190 | g('set size 1,0.7') |
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191 | g('set origin 0,0') |
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192 | g('set xrange [0:%f]' % max(time)) |
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193 | if not midi: |
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194 | g('set log y') |
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195 | #g.xlabel('time (s)') |
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196 | g.ylabel('f0 (Hz)') |
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197 | g('set yrange [100:%f]' % self.params.pitchmax) |
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198 | else: |
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199 | g.ylabel('pitch (midi)') |
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200 | g('set yrange [%f:%f]' % (40, aubio_freqtomidi(self.params.pitchmax))) |
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201 | g('set key right top') |
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202 | g('set noclip one') |
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203 | g('set format x ""') |
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204 | if multiplot: |
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205 | for i in range(len(oplots)): |
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206 | # plot onset detection functions |
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207 | g('set size 1,%f' % (0.7/(len(oplots)))) |
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208 | g('set origin 0,%f' % (float(i)*0.7/(len(oplots)))) |
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209 | g('set xrange [0:%f]' % max(time)) |
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210 | g.plot(oplots[i]) |
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211 | else: |
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212 | g.plot(*oplots) |
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213 | g('unset multiplot') |
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214 | |
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