| [83c6734] | 1 | |
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| 2 | from aubio.bench.node import * |
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| 3 | from os.path import dirname,basename |
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| 4 | |
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| 5 | def mmean(l): |
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| 6 | return sum(l)/max(float(len(l)),1) |
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| 7 | |
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| 8 | def stdev(l): |
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| 9 | smean = 0 |
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| 10 | if not len(l): return smean |
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| 11 | lmean = mmean(l) |
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| 12 | for i in l: |
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| 13 | smean += (i-lmean)**2 |
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| 14 | smean *= 1. / len(l) |
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| 15 | return smean**.5 |
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| 16 | |
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| 17 | class benchonset(bench): |
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| 18 | |
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| 19 | """ list of values to store per file """ |
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| 20 | valuenames = ['orig','missed','Tm','expc','bad','Td'] |
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| 21 | """ list of lists to store per file """ |
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| 22 | valuelists = ['l','labs'] |
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| 23 | """ list of values to print per dir """ |
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| 24 | printnames = [ 'mode', 'thres', 'dist', 'prec', 'recl', |
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| 25 | 'GD', 'FP', |
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| 26 | 'Torig', 'Ttrue', 'Tfp', 'Tfn', 'TTm', 'TTd', |
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| 27 | 'aTtrue', 'aTfp', 'aTfn', 'aTm', 'aTd', |
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| 28 | 'mean', 'smean', 'amean', 'samean'] |
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| 29 | |
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| 30 | """ per dir """ |
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| 31 | formats = {'mode': "%12s" , 'thres': "%5.4s", |
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| 32 | 'dist': "%5.4s", 'prec': "%5.4s", 'recl': "%5.4s", |
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| 33 | 'Torig': "%5.4s", 'Ttrue': "%5.4s", 'Tfp': "%5.4s", 'Tfn': "%5.4s", |
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| 34 | 'TTm': "%5.4s", 'TTd': "%5.4s", |
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| 35 | 'aTtrue':"%5.4s", 'aTfp': "%5.4s", 'aTfn': "%5.4s", |
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| 36 | 'aTm': "%5.4s", 'aTd': "%5.4s", |
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| [ac4f38e] | 37 | 'mean': "%5.6s", 'smean': "%5.6s", |
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| 38 | 'amean': "%5.6s", 'samean': "%5.6s", |
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| [83c6734] | 39 | "GD": "%5.4s", "FP": "%5.4s", |
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| [ac4f38e] | 40 | "GDm": "%5.4s", "FPd": "%5.4s", |
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| 41 | "bufsize": "%5.4s", "hopsize": "%5.4s", |
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| 42 | "time": "%5.4s"} |
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| [83c6734] | 43 | |
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| 44 | def dir_eval(self): |
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| 45 | """ evaluate statistical data over the directory """ |
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| 46 | v = self.v |
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| 47 | |
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| 48 | v['mode'] = self.params.onsetmode |
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| 49 | v['thres'] = self.params.threshold |
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| [6ae3a77] | 50 | v['bufsize'] = self.params.bufsize |
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| 51 | v['hopsize'] = self.params.hopsize |
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| 52 | v['silence'] = self.params.silence |
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| 53 | v['mintol'] = self.params.mintol |
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| [83c6734] | 54 | |
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| 55 | v['Torig'] = sum(v['orig']) |
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| 56 | v['TTm'] = sum(v['Tm']) |
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| 57 | v['TTd'] = sum(v['Td']) |
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| 58 | v['Texpc'] = sum(v['expc']) |
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| 59 | v['Tbad'] = sum(v['bad']) |
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| 60 | v['Tmissed'] = sum(v['missed']) |
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| 61 | v['aTm'] = mmean(v['Tm']) |
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| 62 | v['aTd'] = mmean(v['Td']) |
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| 63 | |
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| 64 | v['mean'] = mmean(v['l']) |
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| 65 | v['smean'] = stdev(v['l']) |
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| 66 | |
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| 67 | v['amean'] = mmean(v['labs']) |
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| 68 | v['samean'] = stdev(v['labs']) |
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| 69 | |
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| 70 | # old type calculations |
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| 71 | # good detection rate |
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| 72 | v['GD'] = 100.*(v['Torig']-v['Tmissed']-v['TTm'])/v['Torig'] |
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| 73 | # false positive rate |
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| 74 | v['FP'] = 100.*(v['Tbad']+v['TTd'])/v['Torig'] |
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| 75 | # good detection counting merged detections as good |
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| 76 | v['GDm'] = 100.*(v['Torig']-v['Tmissed'])/v['Torig'] |
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| 77 | # false positives counting doubled as good |
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| 78 | v['FPd'] = 100.*v['Tbad']/v['Torig'] |
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| 79 | |
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| 80 | # mirex type annotations |
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| 81 | totaltrue = v['Texpc']-v['Tbad']-v['TTd'] |
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| 82 | totalfp = v['Tbad']+v['TTd'] |
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| 83 | totalfn = v['Tmissed']+v['TTm'] |
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| 84 | self.v['Ttrue'] = totaltrue |
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| 85 | self.v['Tfp'] = totalfp |
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| 86 | self.v['Tfn'] = totalfn |
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| 87 | # average over the number of annotation files |
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| 88 | N = float(len(self.reslist)) |
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| 89 | self.v['aTtrue'] = totaltrue/N |
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| 90 | self.v['aTfp'] = totalfp/N |
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| 91 | self.v['aTfn'] = totalfn/N |
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| 92 | |
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| 93 | # F-measure |
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| 94 | self.P = 100.*float(totaltrue)/max(totaltrue + totalfp,1) |
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| 95 | self.R = 100.*float(totaltrue)/max(totaltrue + totalfn,1) |
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| 96 | #if self.R < 0: self.R = 0 |
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| 97 | self.F = 2.* self.P*self.R / max(float(self.P+self.R),1) |
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| 98 | self.v['dist'] = self.F |
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| 99 | self.v['prec'] = self.P |
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| 100 | self.v['recl'] = self.R |
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| 101 | |
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| [6ae3a77] | 102 | |
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| 103 | """ |
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| 104 | Plot functions |
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| 105 | """ |
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| 106 | |
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| [83c6734] | 107 | def plotroc(self,d,plottitle=""): |
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| 108 | import Gnuplot, Gnuplot.funcutils |
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| 109 | gd = [] |
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| 110 | fp = [] |
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| 111 | for i in self.vlist: |
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| 112 | gd.append(i['GD']) |
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| 113 | fp.append(i['FP']) |
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| [5f23f66] | 114 | d.append(Gnuplot.Data(fp, gd, with_='linespoints', |
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| [83c6734] | 115 | title="%s %s" % (plottitle,i['mode']) )) |
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| 116 | |
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| 117 | def plotplotroc(self,d,outplot=0,extension='ps'): |
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| 118 | import Gnuplot, Gnuplot.funcutils |
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| 119 | from sys import exit |
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| 120 | g = Gnuplot.Gnuplot(debug=0, persist=1) |
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| 121 | if outplot: |
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| 122 | if extension == 'ps': ext, extension = '.ps' , 'postscript' |
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| 123 | elif extension == 'png': ext, extension = '.png', 'png' |
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| 124 | elif extension == 'svg': ext, extension = '.svg', 'svg' |
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| 125 | else: exit("ERR: unknown plot extension") |
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| 126 | g('set terminal %s' % extension) |
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| 127 | g('set output \'roc-%s%s\'' % (outplot,ext)) |
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| 128 | xmax = 30 #max(fp) |
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| 129 | ymin = 50 |
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| 130 | g('set xrange [0:%f]' % xmax) |
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| 131 | g('set yrange [%f:100]' % ymin) |
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| 132 | # grid set |
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| 133 | g('set grid') |
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| 134 | g('set xtics 0,5,%f' % xmax) |
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| 135 | g('set ytics %f,5,100' % ymin) |
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| 136 | g('set key 27,65') |
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| 137 | #g('set format \"%g\"') |
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| 138 | g.title(basename(self.datadir)) |
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| 139 | g.xlabel('false positives (%)') |
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| 140 | g.ylabel('correct detections (%)') |
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| 141 | g.plot(*d) |
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| 142 | |
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| 143 | def plotpr(self,d,plottitle=""): |
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| 144 | import Gnuplot, Gnuplot.funcutils |
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| 145 | x = [] |
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| 146 | y = [] |
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| 147 | for i in self.vlist: |
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| 148 | x.append(i['prec']) |
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| 149 | y.append(i['recl']) |
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| [5f23f66] | 150 | d.append(Gnuplot.Data(x, y, with_='linespoints', |
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| [83c6734] | 151 | title="%s %s" % (plottitle,i['mode']) )) |
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| 152 | |
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| 153 | def plotplotpr(self,d,outplot=0,extension='ps'): |
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| 154 | import Gnuplot, Gnuplot.funcutils |
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| 155 | from sys import exit |
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| 156 | g = Gnuplot.Gnuplot(debug=0, persist=1) |
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| 157 | if outplot: |
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| 158 | if extension == 'ps': ext, extension = '.ps' , 'postscript' |
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| 159 | elif extension == 'png': ext, extension = '.png', 'png' |
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| 160 | elif extension == 'svg': ext, extension = '.svg', 'svg' |
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| 161 | else: exit("ERR: unknown plot extension") |
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| 162 | g('set terminal %s' % extension) |
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| 163 | g('set output \'pr-%s%s\'' % (outplot,ext)) |
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| 164 | g.title(basename(self.datadir)) |
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| 165 | g.xlabel('Recall (%)') |
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| 166 | g.ylabel('Precision (%)') |
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| 167 | g.plot(*d) |
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| 168 | |
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| 169 | def plotfmeas(self,d,plottitle=""): |
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| 170 | import Gnuplot, Gnuplot.funcutils |
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| 171 | x,y = [],[] |
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| 172 | for i in self.vlist: |
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| 173 | x.append(i['thres']) |
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| 174 | y.append(i['dist']) |
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| [5f23f66] | 175 | d.append(Gnuplot.Data(x, y, with_='linespoints', |
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| [83c6734] | 176 | title="%s %s" % (plottitle,i['mode']) )) |
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| 177 | |
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| 178 | def plotplotfmeas(self,d,outplot="",extension='ps', title="F-measure"): |
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| 179 | import Gnuplot, Gnuplot.funcutils |
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| 180 | from sys import exit |
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| 181 | g = Gnuplot.Gnuplot(debug=0, persist=1) |
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| 182 | if outplot: |
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| 183 | if extension == 'ps': terminal = 'postscript' |
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| 184 | elif extension == 'png': terminal = 'png' |
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| 185 | elif extension == 'svg': terminal = 'svg' |
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| 186 | else: exit("ERR: unknown plot extension") |
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| 187 | g('set terminal %s' % terminal) |
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| 188 | g('set output \'fmeas-%s.%s\'' % (outplot,extension)) |
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| 189 | g.xlabel('threshold \\delta') |
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| 190 | g.ylabel('F-measure (%)') |
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| 191 | g('set xrange [0:1.2]') |
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| 192 | g('set yrange [0:100]') |
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| 193 | g.title(basename(self.datadir)) |
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| 194 | # grid set |
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| 195 | #g('set grid') |
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| 196 | #g('set xtics 0,5,%f' % xmax) |
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| 197 | #g('set ytics %f,5,100' % ymin) |
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| 198 | #g('set key 27,65') |
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| 199 | #g('set format \"%g\"') |
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| 200 | g.plot(*d) |
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| 201 | |
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| [6ae3a77] | 202 | def plotfmeasvar(self,d,var,plottitle=""): |
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| 203 | import Gnuplot, Gnuplot.funcutils |
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| 204 | x,y = [],[] |
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| 205 | for i in self.vlist: |
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| 206 | x.append(i[var]) |
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| 207 | y.append(i['dist']) |
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| [5f23f66] | 208 | d.append(Gnuplot.Data(x, y, with_='linespoints', |
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| [6ae3a77] | 209 | title="%s %s" % (plottitle,i['mode']) )) |
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| 210 | |
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| 211 | def plotplotfmeasvar(self,d,var,outplot="",extension='ps', title="F-measure"): |
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| 212 | import Gnuplot, Gnuplot.funcutils |
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| 213 | from sys import exit |
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| 214 | g = Gnuplot.Gnuplot(debug=0, persist=1) |
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| 215 | if outplot: |
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| 216 | if extension == 'ps': terminal = 'postscript' |
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| 217 | elif extension == 'png': terminal = 'png' |
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| 218 | elif extension == 'svg': terminal = 'svg' |
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| 219 | else: exit("ERR: unknown plot extension") |
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| 220 | g('set terminal %s' % terminal) |
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| 221 | g('set output \'fmeas-%s.%s\'' % (outplot,extension)) |
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| 222 | g.xlabel(var) |
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| 223 | g.ylabel('F-measure (%)') |
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| 224 | #g('set xrange [0:1.2]') |
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| 225 | g('set yrange [0:100]') |
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| 226 | g.title(basename(self.datadir)) |
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| 227 | g.plot(*d) |
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| 228 | |
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| [83c6734] | 229 | def plotdiffs(self,d,plottitle=""): |
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| 230 | import Gnuplot, Gnuplot.funcutils |
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| 231 | v = self.v |
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| 232 | l = v['l'] |
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| 233 | mean = v['mean'] |
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| 234 | smean = v['smean'] |
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| 235 | amean = v['amean'] |
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| 236 | samean = v['samean'] |
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| 237 | val = [] |
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| 238 | per = [0] * 100 |
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| 239 | for i in range(0,100): |
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| 240 | val.append(i*.001-.05) |
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| 241 | for j in l: |
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| 242 | if abs(j-val[i]) <= 0.001: |
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| 243 | per[i] += 1 |
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| 244 | total = v['Torig'] |
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| 245 | for i in range(len(per)): per[i] /= total/100. |
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| 246 | |
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| [5f23f66] | 247 | d.append(Gnuplot.Data(val, per, with_='fsteps', |
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| [83c6734] | 248 | title="%s %s" % (plottitle,v['mode']) )) |
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| 249 | #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (mean,smean)) |
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| 250 | #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (amean,samean)) |
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| 251 | |
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| 252 | |
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| 253 | def plotplotdiffs(self,d,outplot=0,extension='ps'): |
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| 254 | import Gnuplot, Gnuplot.funcutils |
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| 255 | from sys import exit |
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| 256 | g = Gnuplot.Gnuplot(debug=0, persist=1) |
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| 257 | if outplot: |
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| 258 | if extension == 'ps': ext, extension = '.ps' , 'postscript' |
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| 259 | elif extension == 'png': ext, extension = '.png', 'png' |
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| 260 | elif extension == 'svg': ext, extension = '.svg', 'svg' |
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| 261 | else: exit("ERR: unknown plot extension") |
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| 262 | g('set terminal %s' % extension) |
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| 263 | g('set output \'diffhist-%s%s\'' % (outplot,ext)) |
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| 264 | g('eps(x) = 1./(sigma*(2.*3.14159)**.5) * exp ( - ( x - mean ) ** 2. / ( 2. * sigma ** 2. ))') |
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| 265 | g.title(basename(self.datadir)) |
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| 266 | g.xlabel('delay to hand-labelled onset (s)') |
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| 267 | g.ylabel('% number of correct detections / ms ') |
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| 268 | g('set xrange [-0.05:0.05]') |
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| [6ae3a77] | 269 | g('set yrange [0:20]') |
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| 270 | g.plot(*d) |
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| 271 | |
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| 272 | |
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| 273 | def plothistcat(self,d,plottitle=""): |
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| 274 | import Gnuplot, Gnuplot.funcutils |
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| 275 | total = v['Torig'] |
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| 276 | for i in range(len(per)): per[i] /= total/100. |
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| 277 | |
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| [5f23f66] | 278 | d.append(Gnuplot.Data(val, per, with_='fsteps', |
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| [6ae3a77] | 279 | title="%s %s" % (plottitle,v['mode']) )) |
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| 280 | #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (mean,smean)) |
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| 281 | #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (amean,samean)) |
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| 282 | |
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| 283 | |
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| 284 | def plotplothistcat(self,d,outplot=0,extension='ps'): |
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| 285 | import Gnuplot, Gnuplot.funcutils |
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| 286 | from sys import exit |
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| 287 | g = Gnuplot.Gnuplot(debug=0, persist=1) |
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| 288 | if outplot: |
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| 289 | if extension == 'ps': ext, extension = '.ps' , 'postscript' |
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| 290 | elif extension == 'png': ext, extension = '.png', 'png' |
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| 291 | elif extension == 'svg': ext, extension = '.svg', 'svg' |
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| 292 | else: exit("ERR: unknown plot extension") |
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| 293 | g('set terminal %s' % extension) |
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| 294 | g('set output \'diffhist-%s%s\'' % (outplot,ext)) |
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| 295 | g('eps(x) = 1./(sigma*(2.*3.14159)**.5) * exp ( - ( x - mean ) ** 2. / ( 2. * sigma ** 2. ))') |
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| 296 | g.title(basename(self.datadir)) |
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| 297 | g.xlabel('delay to hand-labelled onset (s)') |
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| 298 | g.ylabel('% number of correct detections / ms ') |
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| 299 | g('set xrange [-0.05:0.05]') |
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| 300 | g('set yrange [0:20]') |
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| [83c6734] | 301 | g.plot(*d) |
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| 302 | |
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| 303 | |
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