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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37 | 'mean': "%5.6s", 'smean': "%5.6s", |
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38 | 'amean': "%5.6s", 'samean': "%5.6s", |
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39 | "GD": "%5.4s", "FP": "%5.4s", |
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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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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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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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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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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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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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114 | d.append(Gnuplot.Data(fp, gd, with_='linespoints', |
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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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150 | d.append(Gnuplot.Data(x, y, with_='linespoints', |
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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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175 | d.append(Gnuplot.Data(x, y, with_='linespoints', |
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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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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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208 | d.append(Gnuplot.Data(x, y, with_='linespoints', |
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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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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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247 | d.append(Gnuplot.Data(val, per, with_='fsteps', |
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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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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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278 | d.append(Gnuplot.Data(val, per, with_='fsteps', |
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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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301 | g.plot(*d) |
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302 | |
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303 | |
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