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| 1 | #! /usr/bin/python | ||
| 2 | |||
| 3 | from aubio.bench.node import * | ||
| 4 | from aubio.tasks import * | ||
| 5 | |||
| 6 | class benchonset(bench): | ||
| 7 | |||
| 8 | def dir_eval(self): | ||
| 9 | self.P = 100*float(self.expc-self.missed-self.merged)/(self.expc-self.missed-self.merged + self.bad+self.doubled) | ||
| 10 | self.R = 100*float(self.expc-self.missed-self.merged)/(self.expc-self.missed-self.merged + self.missed+self.merged) | ||
| 11 | if self.R < 0: self.R = 0 | ||
| 12 | self.F = 2* self.P*self.R / (self.P+self.R) | ||
| 13 | |||
| 14 | self.values = [self.params.onsetmode, | ||
| 15 | "%2.3f" % self.params.threshold, | ||
| 16 | self.orig, | ||
| 17 | self.expc, | ||
| 18 | self.missed, | ||
| 19 | self.merged, | ||
| 20 | self.bad, | ||
| 21 | self.doubled, | ||
| 22 | (self.orig-self.missed-self.merged), | ||
| 23 | "%2.3f" % (100*float(self.orig-self.missed-self.merged)/(self.orig)), | ||
| 24 | "%2.3f" % (100*float(self.bad+self.doubled)/(self.orig)), | ||
| 25 | "%2.3f" % (100*float(self.orig-self.missed)/(self.orig)), | ||
| 26 | "%2.3f" % (100*float(self.bad)/(self.orig)), | ||
| 27 | "%2.3f" % self.P, | ||
| 28 | "%2.3f" % self.R, | ||
| 29 | "%2.3f" % self.F ] | ||
| 30 | |||
| 31 | def file_exec(self,input,output): | ||
| 32 | filetask = self.task(input,params=self.params) | ||
| 33 | computed_data = filetask.compute_all() | ||
| 34 | results = filetask.eval(computed_data) | ||
| 35 | self.orig += filetask.orig | ||
| 36 | self.missed += filetask.missed | ||
| 37 | self.merged += filetask.merged | ||
| 38 | self.expc += filetask.expc | ||
| 39 | self.bad += filetask.bad | ||
| 40 | self.doubled += filetask.doubled | ||
| 41 | |||
| 42 | |||
| 43 | def run_bench(self,modes=['dual'],thresholds=[0.5]): | ||
| 44 | self.modes = modes | ||
| 45 | self.thresholds = thresholds | ||
| 46 | |||
| 47 | self.pretty_print(self.titles) | ||
| 48 | for mode in self.modes: | ||
| 49 | self.params.onsetmode = mode | ||
| 50 | for threshold in self.thresholds: | ||
| 51 | self.params.threshold = threshold | ||
| 52 | self.dir_exec() | ||
| 53 | self.dir_eval() | ||
| 54 | self.pretty_print(self.values) | ||
| 55 | |||
| 56 | def auto_learn(self,modes=['dual'],thresholds=[0.1,1.5]): | ||
| 57 | """ simple dichotomia like algorithm to optimise threshold """ | ||
| 58 | self.modes = modes | ||
| 59 | self.pretty_print(self.titles) | ||
| 60 | for mode in self.modes: | ||
| 61 | steps = 10 | ||
| 62 | lesst = thresholds[0] | ||
| 63 | topt = thresholds[1] | ||
| 64 | self.params.onsetmode = mode | ||
| 65 | |||
| 66 | self.params.threshold = topt | ||
| 67 | self.dir_exec() | ||
| 68 | self.dir_eval() | ||
| 69 | self.pretty_print(self.values) | ||
| 70 | topF = self.F | ||
| 71 | |||
| 72 | self.params.threshold = lesst | ||
| 73 | self.dir_exec() | ||
| 74 | self.dir_eval() | ||
| 75 | self.pretty_print(self.values) | ||
| 76 | lessF = self.F | ||
| 77 | |||
| 78 | for i in range(steps): | ||
| 79 | self.params.threshold = ( lesst + topt ) * .5 | ||
| 80 | self.dir_exec() | ||
| 81 | self.dir_eval() | ||
| 82 | self.pretty_print(self.values) | ||
| 83 | if self.F == 100.0 or self.F == topF: | ||
| 84 | print "assuming we converged, stopping" | ||
| 85 | break | ||
| 86 | #elif abs(self.F - topF) < 0.01 : | ||
| 87 | # print "done converging" | ||
| 88 | # break | ||
| 89 | if topF < self.F: | ||
| 90 | #lessF = topF | ||
| 91 | #lesst = topt | ||
| 92 | topF = self.F | ||
| 93 | topt = self.params.threshold | ||
| 94 | elif lessF < self.F: | ||
| 95 | lessF = self.F | ||
| 96 | lesst = self.params.threshold | ||
| 97 | if topt == lesst: | ||
| 98 | lesst /= 2. | ||
| 99 | |||
| 100 | def auto_learn2(self,modes=['dual'],thresholds=[0.1,1.0]): | ||
| 101 | """ simple dichotomia like algorithm to optimise threshold """ | ||
| 102 | self.modes = modes | ||
| 103 | self.pretty_print(self.titles) | ||
| 104 | for mode in self.modes: | ||
| 105 | steps = 10 | ||
| 106 | step = thresholds[1] | ||
| 107 | curt = thresholds[0] | ||
| 108 | self.params.onsetmode = mode | ||
| 109 | |||
| 110 | self.params.threshold = curt | ||
| 111 | self.dir_exec() | ||
| 112 | self.dir_eval() | ||
| 113 | self.pretty_print(self.values) | ||
| 114 | curexp = self.expc | ||
| 115 | |||
| 116 | for i in range(steps): | ||
| 117 | if curexp < self.orig: | ||
| 118 | #print "we found at most less onsets than annotated" | ||
| 119 | self.params.threshold -= step | ||
| 120 | step /= 2 | ||
| 121 | elif curexp > self.orig: | ||
| 122 | #print "we found more onsets than annotated" | ||
| 123 | self.params.threshold += step | ||
| 124 | step /= 2 | ||
| 125 | self.dir_exec() | ||
| 126 | self.dir_eval() | ||
| 127 | curexp = self.expc | ||
| 128 | self.pretty_print(self.values) | ||
| 129 | if self.orig == 100.0 or self.orig == self.expc: | ||
| 130 | print "assuming we converged, stopping" | ||
| 131 | break | ||
| 132 | |||
| 133 | if __name__ == "__main__": | ||
| 134 | import sys | ||
| 135 | if len(sys.argv) > 1: datapath = sys.argv[1] | ||
| 136 | else: print "ERR: a path is required"; sys.exit(1) | ||
| 137 | modes = ['complex', 'energy', 'phase', 'specdiff', 'kl', 'mkl', 'dual'] | ||
| 138 | #modes = [ 'complex' ] | ||
| 139 | thresholds = [ 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5] | ||
| 140 | #thresholds = [1.5] | ||
| 141 | |||
| 142 | #datapath = "%s%s" % (DATADIR,'/onset/DB/*/') | ||
| 143 | respath = '/var/tmp/DB-testings' | ||
| 144 | |||
| 145 | benchonset = benchonset(datapath,respath,checkres=True,checkanno=True) | ||
| 146 | benchonset.params = taskparams() | ||
| 147 | benchonset.task = taskonset | ||
| 148 | |||
| 149 | benchonset.titles = [ 'mode', 'thres', 'orig', 'expc', 'missd', 'mergd', | ||
| 150 | 'bad', 'doubl', 'corrt', 'GD', 'FP', 'GD-merged', 'FP-pruned', | ||
| 151 | 'prec', 'recl', 'dist' ] | ||
| 152 | benchonset.formats = ["%12s" , "| %6s", "| %6s", "| %6s", "| %6s", "| %6s", | ||
| 153 | "| %6s", "| %6s", "| %6s", "| %8s", "| %8s", "| %8s", "| %8s", | ||
| 154 | "| %6s", "| %6s", "| %6s"] | ||
| 155 | |||
| 156 | try: | ||
| 157 | benchonset.auto_learn2(modes=modes) | ||
| 158 | #benchonset.run_bench(modes=modes) | ||
| 159 | except KeyboardInterrupt: | ||
| 160 | sys.exit(1) | ||