1 | from aubioclass import * |
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2 | |
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3 | def get_onset_mode(nvalue): |
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4 | """ utility function to convert a string to aubio_onsetdetection_type """ |
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5 | if nvalue == 'complexdomain' or nvalue == 'complex' : |
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6 | return aubio_onset_complex |
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7 | elif nvalue == 'hfc' : |
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8 | return aubio_onset_hfc |
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9 | elif nvalue == 'phase' : |
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10 | return aubio_onset_phase |
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11 | elif nvalue == 'specdiff' : |
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12 | return aubio_onset_specdiff |
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13 | elif nvalue == 'energy' : |
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14 | return aubio_onset_energy |
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15 | elif nvalue == 'kl' : |
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16 | return aubio_onset_kl |
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17 | elif nvalue == 'mkl' : |
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18 | return aubio_onset_mkl |
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19 | elif nvalue == 'dual' : |
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20 | return 'dual' |
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21 | else: |
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22 | import sys |
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23 | print "unknown onset detection function selected" |
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24 | sys.exit(1) |
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25 | |
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26 | def get_pitch_mode(nvalue): |
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27 | """ utility function to convert a string to aubio_pitchdetection_type """ |
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28 | if nvalue == 'mcomb' : |
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29 | return aubio_pitch_mcomb |
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30 | elif nvalue == 'yin' : |
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31 | return aubio_pitch_yin |
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32 | elif nvalue == 'fcomb' : |
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33 | return aubio_pitch_fcomb |
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34 | elif nvalue == 'schmitt': |
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35 | return aubio_pitch_schmitt |
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36 | else: |
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37 | import sys |
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38 | print "error: unknown pitch detection function selected" |
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39 | sys.exit(1) |
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40 | |
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41 | def check_onset_mode(option, opt, value, parser): |
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42 | """ wrapper function to convert a list of modes to |
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43 | aubio_onsetdetection_type """ |
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44 | nvalues = parser.rargs[0].split(',') |
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45 | val = [] |
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46 | for nvalue in nvalues: |
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47 | val.append(get_onset_mode(nvalue)) |
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48 | setattr(parser.values, option.dest, val) |
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49 | |
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50 | def check_pitch_mode(option, opt, value, parser): |
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51 | """ utility function to convert a string to aubio_pitchdetection_type""" |
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52 | nvalues = parser.rargs[0].split(',') |
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53 | val = [] |
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54 | for nvalue in nvalues: |
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55 | val.append(get_pitch_mode(nvalue)) |
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56 | setattr(parser.values, option.dest, val) |
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57 | |
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58 | def check_pitchm_mode(option, opt, value, parser): |
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59 | """ utility function to convert a string to aubio_pitchdetection_mode """ |
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60 | nvalue = parser.rargs[0] |
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61 | if nvalue == 'freq' : |
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62 | setattr(parser.values, option.dest, aubio_pitchm_freq) |
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63 | elif nvalue == 'midi' : |
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64 | setattr(parser.values, option.dest, aubio_pitchm_midi) |
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65 | elif nvalue == 'cent' : |
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66 | setattr(parser.values, option.dest, aubio_pitchm_cent) |
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67 | elif nvalue == 'bin' : |
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68 | setattr(parser.values, option.dest, aubio_pitchm_bin) |
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69 | else: |
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70 | import sys |
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71 | print "error: unknown pitch detection output selected" |
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72 | sys.exit(1) |
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73 | |
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74 | |
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75 | #def getonsets(filein,threshold=0.2,silence=-70.,bufsize=1024,hopsize=512, |
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76 | # mode='dual',localmin=False,storefunc=False,derivate=False): |
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77 | # frameread = 0 |
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78 | # filei = sndfile(filein) |
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79 | # channels = filei.channels() |
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80 | # myvec = fvec(hopsize,channels) |
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81 | # readsize = filei.read(hopsize,myvec) |
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82 | # opick = onsetpick(bufsize,hopsize,channels,myvec,threshold, |
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83 | # mode=mode,derivate=derivate) |
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84 | # mylist = list() |
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85 | # if localmin: |
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86 | # ovalist = [0., 0., 0., 0., 0.] |
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87 | # ofunclist = [] |
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88 | # while(readsize): |
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89 | # readsize = filei.read(hopsize,myvec) |
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90 | # isonset,val = opick.do(myvec) |
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91 | # if (aubio_silence_detection(myvec(),silence)): |
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92 | # isonset=0 |
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93 | # if localmin: |
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94 | # if val > 0: ovalist.append(val) |
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95 | # else: ovalist.append(0) |
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96 | # ovalist.pop(0) |
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97 | # if storefunc: |
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98 | # ofunclist.append(val) |
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99 | # if (isonset == 1): |
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100 | # if localmin: |
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101 | # i=len(ovalist)-1 |
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102 | # # find local minima before peak |
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103 | # while ovalist[i-1] < ovalist[i] and i > 0: |
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104 | # i -= 1 |
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105 | # now = (frameread+1-i) |
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106 | # else: |
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107 | # now = frameread |
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108 | # if now > 0 : |
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109 | # mylist.append(now) |
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110 | # else: |
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111 | # now = 0 |
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112 | # mylist.append(now) |
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113 | # frameread += 1 |
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114 | # return mylist, ofunclist |
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115 | # |
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116 | #def cutfile(filein,slicetimes,zerothres=0.008,bufsize=1024,hopsize=512): |
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117 | # frameread = 0 |
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118 | # readsize = hopsize |
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119 | # filei = sndfile(filein) |
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120 | # framestep = hopsize/(filei.samplerate()+0.) |
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121 | # channels = filei.channels() |
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122 | # newname = "%s%s%09.5f%s%s" % (filein.split(".")[0].split("/")[-1],".", |
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123 | # frameread*framestep,".",filein.split(".")[-1]) |
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124 | # fileo = sndfile(newname,model=filei) |
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125 | # myvec = fvec(hopsize,channels) |
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126 | # mycopy = fvec(hopsize,channels) |
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127 | # while(readsize==hopsize): |
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128 | # readsize = filei.read(hopsize,myvec) |
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129 | # # write to current file |
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130 | # if len(slicetimes) and frameread >= slicetimes[0]: |
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131 | # slicetimes.pop(0) |
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132 | # # write up to 1st zero crossing |
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133 | # zerocross = 0 |
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134 | # while ( abs( myvec.get(zerocross,0) ) > zerothres ): |
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135 | # zerocross += 1 |
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136 | # writesize = fileo.write(zerocross,myvec) |
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137 | # fromcross = 0 |
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138 | # while (zerocross < readsize): |
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139 | # for i in range(channels): |
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140 | # mycopy.set(myvec.get(zerocross,i),fromcross,i) |
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141 | # fromcross += 1 |
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142 | # zerocross += 1 |
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143 | # del fileo |
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144 | # fileo = sndfile("%s%s%09.5f%s%s" % |
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145 | # (filein.split(".")[0].split("/")[-1],".", |
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146 | # frameread*framestep,".",filein.split(".")[-1]),model=filei) |
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147 | # writesize = fileo.write(fromcross,mycopy) |
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148 | # else: |
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149 | # writesize = fileo.write(readsize,myvec) |
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150 | # frameread += 1 |
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151 | # del fileo |
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152 | # |
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153 | # |
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154 | #def getsilences(filein,hopsize=512,silence=-70): |
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155 | # frameread = 0 |
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156 | # filei = sndfile(filein) |
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157 | # srate = filei.samplerate() |
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158 | # channels = filei.channels() |
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159 | # myvec = fvec(hopsize,channels) |
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160 | # readsize = filei.read(hopsize,myvec) |
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161 | # mylist = [] |
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162 | # wassilence = 0 |
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163 | # while(readsize==hopsize): |
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164 | # readsize = filei.read(hopsize,myvec) |
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165 | # if (aubio_silence_detection(myvec(),silence)==1): |
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166 | # if wassilence == 0: |
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167 | # mylist.append(frameread) |
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168 | # wassilence == 1 |
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169 | # else: wassilence = 0 |
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170 | # frameread += 1 |
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171 | # return mylist |
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172 | # |
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173 | # |
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174 | #def getpitch(filein,mode=aubio_pitch_mcomb,bufsize=1024,hopsize=512,omode=aubio_pitchm_freq, |
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175 | # samplerate=44100.,silence=-70): |
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176 | # frameread = 0 |
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177 | # filei = sndfile(filein) |
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178 | # srate = filei.samplerate() |
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179 | # channels = filei.channels() |
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180 | # myvec = fvec(hopsize,channels) |
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181 | # readsize = filei.read(hopsize,myvec) |
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182 | # pitchdet = pitchdetection(mode=mode,bufsize=bufsize,hopsize=hopsize, |
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183 | # channels=channels,samplerate=srate,omode=omode) |
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184 | # mylist = [] |
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185 | # while(readsize==hopsize): |
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186 | # readsize = filei.read(hopsize,myvec) |
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187 | # freq = pitchdet(myvec) |
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188 | # #print "%.3f %.2f" % (now,freq) |
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189 | # if (aubio_silence_detection(myvec(),silence)!=1): |
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190 | # mylist.append(freq) |
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191 | # else: |
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192 | # mylist.append(-1.) |
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193 | # frameread += 1 |
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194 | # return mylist |
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195 | |
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196 | |
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197 | class taskparams(object): |
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198 | """ default parameters for task classes """ |
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199 | def __init__(self,input=None,output=None): |
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200 | self.silence = -70 |
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201 | self.derivate = False |
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202 | self.localmin = False |
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203 | self.delay = 4. |
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204 | self.storefunc = False |
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205 | self.bufsize = 512 |
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206 | self.hopsize = 256 |
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207 | self.samplerate = 44100 |
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208 | self.tol = 0.05 |
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209 | self.mintol = 0.0 |
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210 | self.step = float(self.hopsize)/float(self.samplerate) |
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211 | self.threshold = 0.1 |
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212 | self.onsetmode = 'dual' |
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213 | self.pitchmode = 'yin' |
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214 | self.dcthreshold = -1. |
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215 | self.omode = aubio_pitchm_freq |
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216 | self.verbose = False |
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217 | |
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218 | class task(taskparams): |
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219 | """ default template class to apply tasks on a stream """ |
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220 | def __init__(self,input,output=None,params=None): |
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221 | """ open the input file and initialize default argument |
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222 | parameters should be set *before* calling this method. |
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223 | """ |
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224 | import time |
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225 | self.tic = time.time() |
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226 | if params == None: self.params = taskparams() |
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227 | else: self.params = params |
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228 | self.frameread = 0 |
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229 | self.readsize = self.params.hopsize |
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230 | self.input = input |
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231 | self.filei = sndfile(self.input) |
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232 | self.srate = self.filei.samplerate() |
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233 | self.channels = self.filei.channels() |
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234 | self.params.step = float(self.params.hopsize)/float(self.srate) |
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235 | self.myvec = fvec(self.params.hopsize,self.channels) |
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236 | self.output = output |
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237 | |
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238 | def __call__(self): |
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239 | self.readsize = self.filei.read(self.params.hopsize,self.myvec) |
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240 | self.frameread += 1 |
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241 | |
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242 | def compute_all(self): |
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243 | """ Compute data """ |
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244 | mylist = [] |
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245 | while(self.readsize==self.params.hopsize): |
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246 | tmp = self() |
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247 | if tmp: |
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248 | mylist.append(tmp) |
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249 | if self.params.verbose: |
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250 | self.fprint(tmp) |
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251 | return mylist |
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252 | |
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253 | def fprint(self,foo): |
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254 | print foo |
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255 | |
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256 | def eval(self,results): |
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257 | """ Eval data """ |
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258 | pass |
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259 | |
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260 | def plot(self): |
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261 | """ Plot data """ |
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262 | pass |
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263 | |
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264 | def time(self): |
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265 | import time |
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266 | print "CPU time is now %f seconds," % time.clock(), |
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267 | print "task execution took %f seconds" % (time.time() - self.tic) |
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268 | |
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269 | class tasksilence(task): |
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270 | wassilence = 1 |
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271 | issilence = 1 |
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272 | def __call__(self): |
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273 | task.__call__(self) |
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274 | if (aubio_silence_detection(self.myvec(),self.params.silence)==1): |
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275 | if self.wassilence == 1: self.issilence = 1 |
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276 | else: self.issilence = 2 |
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277 | self.wassilence = 1 |
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278 | else: |
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279 | if self.wassilence <= 0: self.issilence = 0 |
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280 | else: self.issilence = -1 |
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281 | self.wassilence = 0 |
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282 | if self.issilence == -1: |
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283 | return max(self.frameread-self.params.delay,0.), -1 |
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284 | elif self.issilence == 2: |
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285 | return max(self.frameread+self.params.delay,0.), 2 |
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286 | |
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287 | def fprint(self,foo): |
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288 | print self.params.step*foo[0], |
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289 | if foo[1] == 2: print "OFF" |
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290 | else: print "ON" |
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291 | |
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292 | class taskpitch(task): |
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293 | def __init__(self,input,params=None): |
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294 | task.__init__(self,input,params=params) |
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295 | self.pitchdet = pitchdetection(mode=get_pitch_mode(self.params.pitchmode), |
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296 | bufsize=self.params.bufsize, |
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297 | hopsize=self.params.hopsize, |
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298 | channels=self.channels, |
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299 | samplerate=self.srate, |
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300 | omode=self.params.omode) |
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301 | |
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302 | def __call__(self): |
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303 | #print "%.3f %.2f" % (now,freq) |
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304 | task.__call__(self) |
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305 | freq = self.pitchdet(self.myvec) |
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306 | if (aubio_silence_detection(self.myvec(),self.params.silence)!=1): |
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307 | return freq |
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308 | else: |
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309 | return -1. |
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310 | |
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311 | def gettruth(self): |
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312 | """ big hack to extract midi note from /path/to/file.<midinote>.wav """ |
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313 | floatpit = self.input.split('.')[-2] |
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314 | try: |
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315 | return aubio_miditofreq(float(floatpit)) |
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316 | except ValueError: |
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317 | print "ERR: no truth file found" |
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318 | return 0 |
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319 | |
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320 | def eval(self,results): |
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321 | def mmean(l): |
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322 | return sum(l)/max(float(len(l)),1) |
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323 | |
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324 | from median import short_find |
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325 | self.truth = self.gettruth() |
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326 | res = [] |
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327 | for i in results: |
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328 | if i == -1: pass |
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329 | else: |
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330 | res.append(self.truth-i) |
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331 | if not res: |
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332 | avg = self.truth; med = self.truth |
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333 | else: |
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334 | avg = mmean(res) |
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335 | med = short_find(res,len(res)/2) |
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336 | return self.truth, self.truth-med, self.truth-avg |
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337 | |
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338 | def plot(self,pitch,outplot=None): |
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339 | from aubio.gnuplot import plot_pitch |
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340 | plot_pitch(self.input, |
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341 | pitch, |
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342 | samplerate=float(self.srate), |
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343 | hopsize=self.params.hopsize, |
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344 | outplot=outplot) |
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345 | |
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346 | |
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347 | class taskonset(task): |
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348 | def __init__(self,input,output=None,params=None): |
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349 | """ open the input file and initialize arguments |
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350 | parameters should be set *before* calling this method. |
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351 | """ |
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352 | task.__init__(self,input,params=params) |
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353 | self.opick = onsetpick(self.params.bufsize, |
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354 | self.params.hopsize, |
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355 | self.channels, |
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356 | self.myvec, |
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357 | self.params.threshold, |
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358 | mode=get_onset_mode(self.params.onsetmode), |
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359 | dcthreshold=self.params.dcthreshold, |
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360 | derivate=self.params.derivate) |
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361 | self.olist = [] |
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362 | self.ofunc = [] |
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363 | self.maxofunc = 0 |
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364 | self.last = 0 |
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365 | if self.params.localmin: |
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366 | self.ovalist = [0., 0., 0., 0., 0.] |
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367 | |
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368 | def __call__(self): |
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369 | task.__call__(self) |
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370 | isonset,val = self.opick.do(self.myvec) |
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371 | if (aubio_silence_detection(self.myvec(),self.params.silence)): |
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372 | isonset=0 |
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373 | if self.params.storefunc: |
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374 | self.ofunc.append(val) |
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375 | if self.params.localmin: |
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376 | if val > 0: self.ovalist.append(val) |
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377 | else: self.ovalist.append(0) |
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378 | self.ovalist.pop(0) |
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379 | if (isonset == 1): |
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380 | if self.params.localmin: |
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381 | # find local minima before peak |
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382 | i=len(self.ovalist)-1 |
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383 | while self.ovalist[i-1] < self.ovalist[i] and i > 0: |
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384 | i -= 1 |
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385 | now = (self.frameread+1-i) |
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386 | else: |
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387 | now = self.frameread |
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388 | # take back delay |
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389 | if self.params.delay != 0.: now -= self.params.delay |
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390 | if now < 0 : |
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391 | now = 0 |
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392 | if self.params.mintol: |
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393 | # prune doubled |
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394 | if (now - self.last) > self.params.mintol: |
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395 | self.last = now |
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396 | return now, val |
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397 | else: |
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398 | return now, val |
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399 | |
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400 | |
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401 | def fprint(self,foo): |
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402 | print self.params.step*foo[0] |
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403 | |
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404 | def eval(self,inputdata,ftru,mode='roc',vmode=''): |
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405 | from txtfile import read_datafile |
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406 | from onsetcompare import onset_roc, onset_diffs, onset_rocloc |
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407 | ltru = read_datafile(ftru,depth=0) |
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408 | lres = [] |
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409 | for i in range(len(inputdata)): lres.append(inputdata[i][0]*self.params.step) |
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410 | if vmode=='verbose': |
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411 | print "Running with mode %s" % self.params.onsetmode, |
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412 | print " and threshold %f" % self.params.threshold, |
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413 | print " on file", self.input |
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414 | #print ltru; print lres |
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415 | if mode == 'local': |
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416 | l = onset_diffs(ltru,lres,self.params.tol) |
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417 | mean = 0 |
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418 | for i in l: mean += i |
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419 | if len(l): mean = "%.3f" % (mean/len(l)) |
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420 | else: mean = "?0" |
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421 | return l, mean |
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422 | elif mode == 'roc': |
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423 | self.orig, self.missed, self.merged, \ |
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424 | self.expc, self.bad, self.doubled = \ |
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425 | onset_roc(ltru,lres,self.params.tol) |
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426 | elif mode == 'rocloc': |
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427 | self.v = {} |
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428 | self.v['orig'], self.v['missed'], self.v['Tm'], \ |
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429 | self.v['expc'], self.v['bad'], self.v['Td'], \ |
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430 | self.v['l'], self.v['labs'] = \ |
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431 | onset_rocloc(ltru,lres,self.params.tol) |
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432 | |
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433 | def plot(self,onsets,ofunc,wplot,oplots,nplot=False): |
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434 | import Gnuplot, Gnuplot.funcutils |
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435 | import aubio.txtfile |
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436 | import os.path |
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437 | import numarray |
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438 | from aubio.onsetcompare import onset_roc |
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439 | |
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440 | x1,y1,y1p = [],[],[] |
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441 | oplot = [] |
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442 | |
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443 | self.lenofunc = len(ofunc) |
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444 | self.maxofunc = max(ofunc) |
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445 | # onset detection function |
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446 | downtime = numarray.arange(len(ofunc))*self.params.step |
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447 | oplot.append(Gnuplot.Data(downtime,ofunc,with='lines',title=self.params.onsetmode)) |
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448 | |
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449 | # detected onsets |
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450 | if not nplot: |
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451 | for i in onsets: |
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452 | x1.append(i[0]*self.params.step) |
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453 | y1.append(self.maxofunc) |
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454 | y1p.append(-self.maxofunc) |
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455 | #x1 = numarray.array(onsets)*self.params.step |
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456 | #y1 = self.maxofunc*numarray.ones(len(onsets)) |
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457 | if x1: |
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458 | oplot.append(Gnuplot.Data(x1,y1,with='impulses')) |
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459 | wplot.append(Gnuplot.Data(x1,y1p,with='impulses')) |
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460 | |
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461 | oplots.append(oplot) |
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462 | |
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463 | # check if datafile exists truth |
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464 | datafile = self.input.replace('.wav','.txt') |
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465 | if datafile == self.input: datafile = "" |
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466 | if not os.path.isfile(datafile): |
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467 | self.title = "" #"(no ground truth)" |
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468 | t = Gnuplot.Data(0,0,with='impulses') |
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469 | else: |
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470 | t_onsets = aubio.txtfile.read_datafile(datafile) |
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471 | x2 = numarray.array(t_onsets).resize(len(t_onsets)) |
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472 | y2 = self.maxofunc*numarray.ones(len(t_onsets)) |
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473 | wplot.append(Gnuplot.Data(x2,y2,with='impulses')) |
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474 | |
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475 | tol = 0.050 |
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476 | |
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477 | orig, missed, merged, expc, bad, doubled = \ |
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478 | onset_roc(x2,x1,tol) |
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479 | self.title = "GD %2.3f%% FP %2.3f%%" % \ |
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480 | ((100*float(orig-missed-merged)/(orig)), |
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481 | (100*float(bad+doubled)/(orig))) |
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482 | |
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483 | |
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484 | def plotplot(self,wplot,oplot,outplot=None): |
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485 | from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot |
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486 | import re |
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487 | # audio data |
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488 | time,data = audio_to_array(self.input) |
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489 | wplot = [make_audio_plot(time,data)] + wplot |
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490 | # prepare the plot |
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491 | g = gnuplot_init(outplot) |
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492 | |
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493 | g('set multiplot') |
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494 | |
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495 | # hack to align left axis |
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496 | g('set lmargin 6') |
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497 | g('set tmargin 0') |
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498 | g('set format x ""') |
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499 | g('set format y ""') |
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500 | g('set noytics') |
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501 | |
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502 | for i in range(len(oplot)): |
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503 | # plot onset detection functions |
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504 | g('set size 1,%f' % (0.7/(len(oplot)))) |
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505 | g('set origin 0,%f' % (float(i)*0.7/(len(oplot)))) |
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506 | g('set xrange [0:%f]' % (self.lenofunc*self.params.step)) |
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507 | g.plot(*oplot[i]) |
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508 | |
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509 | g('set tmargin 3') |
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510 | g('set format x "%10.1f"') |
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511 | |
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512 | g('set title \'%s %s\'' % (re.sub('.*/','',self.input),self.title)) |
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513 | |
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514 | # plot waveform and onsets |
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515 | g('set size 1,0.3') |
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516 | g('set origin 0,0.7') |
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517 | g('set xrange [0:%f]' % max(time)) |
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518 | g('set yrange [-1:1]') |
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519 | g.ylabel('amplitude') |
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520 | g.plot(*wplot) |
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521 | |
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522 | g('unset multiplot') |
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523 | |
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524 | class taskcut(task): |
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525 | def __init__(self,input,slicetimes,params=None,output=None): |
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526 | """ open the input file and initialize arguments |
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527 | parameters should be set *before* calling this method. |
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528 | """ |
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529 | task.__init__(self,input,output=None,params=params) |
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530 | self.newname = "%s%s%09.5f%s%s" % (self.input.split(".")[0].split("/")[-1],".", |
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531 | self.frameread*self.params.step,".",self.input.split(".")[-1]) |
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532 | self.fileo = sndfile(self.newname,model=self.filei) |
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533 | self.myvec = fvec(self.params.hopsize,self.channels) |
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534 | self.mycopy = fvec(self.params.hopsize,self.channels) |
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535 | self.slicetimes = slicetimes |
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536 | |
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537 | def __call__(self): |
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538 | task.__call__(self) |
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539 | # write to current file |
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540 | if len(self.slicetimes) and self.frameread >= self.slicetimes[0][0]: |
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541 | self.slicetimes.pop(0) |
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542 | # write up to 1st zero crossing |
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543 | zerocross = 0 |
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544 | while ( abs( self.myvec.get(zerocross,0) ) > self.params.zerothres ): |
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545 | zerocross += 1 |
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546 | writesize = self.fileo.write(zerocross,self.myvec) |
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547 | fromcross = 0 |
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548 | while (zerocross < self.readsize): |
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549 | for i in range(self.channels): |
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550 | self.mycopy.set(self.myvec.get(zerocross,i),fromcross,i) |
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551 | fromcross += 1 |
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552 | zerocross += 1 |
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553 | del self.fileo |
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554 | self.fileo = sndfile("%s%s%09.5f%s%s" % |
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555 | (self.input.split(".")[0].split("/")[-1],".", |
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556 | self.frameread*self.params.step,".",self.input.split(".")[-1]),model=self.filei) |
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557 | writesize = self.fileo.write(fromcross,self.mycopy) |
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558 | else: |
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559 | writesize = self.fileo.write(self.readsize,self.myvec) |
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560 | |
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561 | class taskbeat(taskonset): |
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562 | def __init__(self,input,params=None,output=None): |
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563 | """ open the input file and initialize arguments |
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564 | parameters should be set *before* calling this method. |
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565 | """ |
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566 | taskonset.__init__(self,input,output=None,params=params) |
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567 | self.btwinlen = 512**2/self.params.hopsize |
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568 | self.btstep = self.btwinlen/4 |
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569 | self.btoutput = fvec(self.btstep,self.channels) |
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570 | self.dfframe = fvec(self.btwinlen,self.channels) |
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571 | self.bt = beattracking(self.btwinlen,self.channels) |
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572 | self.pos2 = 0 |
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573 | |
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574 | def __call__(self): |
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575 | taskonset.__call__(self) |
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576 | # write to current file |
---|
577 | if self.pos2 == self.btstep - 1 : |
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578 | self.bt.do(self.dfframe,self.btoutput) |
---|
579 | for i in range (self.btwinlen - self.btstep): |
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580 | self.dfframe.set(self.dfframe.get(i+self.btstep,0),i,0) |
---|
581 | for i in range(self.btwinlen - self.btstep, self.btwinlen): |
---|
582 | self.dfframe.set(0,i,0) |
---|
583 | self.pos2 = -1; |
---|
584 | self.pos2 += 1 |
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585 | val = self.opick.pp.getval() |
---|
586 | self.dfframe.set(val,self.btwinlen - self.btstep + self.pos2,0) |
---|
587 | i=0 |
---|
588 | for i in range(1,int( self.btoutput.get(0,0) ) ): |
---|
589 | if self.pos2 == self.btoutput.get(i,0) and \ |
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590 | aubio_silence_detection(self.myvec(), |
---|
591 | self.params.silence)!=1: |
---|
592 | return self.frameread, 0 |
---|
593 | |
---|
594 | def eval(self,results): |
---|
595 | pass |
---|