From: Paul Brossier Date: Fri, 17 Feb 2006 17:17:10 +0000 (+0000) Subject: merge some benchonset code into node X-Git-Tag: bzr2git~773 X-Git-Url: http://git.tremily.us/?a=commitdiff_plain;h=c912c67ccd0dd420833c8e063fe084f3e59bb85a;p=aubio.git merge some benchonset code into node merge some benchonset code into node --- diff --git a/python/aubio/bench/node.py b/python/aubio/bench/node.py index 9ab753ba..22e231a6 100644 --- a/python/aubio/bench/node.py +++ b/python/aubio/bench/node.py @@ -143,20 +143,62 @@ class bench: print "Creating results directory" act_on_results(mkdir,self.datadir,self.resdir,filter='d') - def pretty_print(self,values,sep='|'): - for i in range(len(values)): - print self.formats[i] % values[i], sep, + def pretty_print(self,sep='|'): + for i in self.printnames: + print self.formats[i] % self.v[i], sep, + print + + def pretty_titles(self,sep='|'): + for i in self.printnames: + print self.formats[i] % i, sep, print def dir_exec(self): """ run file_exec on every input file """ - pass + self.l , self.labs = [], [] + self.v = {} + for i in self.valuenames: + self.v[i] = [] + for i in self.valuelists: + self.v[i] = [] + act_on_files(self.file_exec,self.sndlist,self.reslist, \ + suffix='',filter=sndfile_filter) def dir_eval(self): pass - def file_exec(self): - pass + def file_gettruth(self,input): + """ get ground truth filenames """ + from os.path import isfile + ftrulist = [] + # search for match as filetask.input,".txt" + ftru = '.'.join(input.split('.')[:-1]) + ftru = '.'.join((ftru,'txt')) + if isfile(ftru): + ftrulist.append(ftru) + else: + # search for matches for filetask.input in the list of results + for i in range(len(self.reslist)): + check = '.'.join(self.reslist[i].split('.')[:-1]) + check = '_'.join(check.split('_')[:-1]) + if check == '.'.join(input.split('.')[:-1]): + ftrulist.append(self.reslist[i]) + return ftrulist + + def file_exec(self,input,output): + """ create filetask, extract data, evaluate """ + filetask = self.task(input,params=self.params) + computed_data = filetask.compute_all() + ftrulist = self.file_gettruth(filetask.input) + for i in ftrulist: + filetask.eval(computed_data,i,mode='rocloc',vmode='') + """ append filetask.v to self.v """ + for i in self.valuenames: + self.v[i].append(filetask.v[i]) + for j in self.valuelists: + if filetask.v[j]: + for i in range(len(filetask.v[j])): + self.v[j].append(filetask.v[j][i]) def file_eval(self): pass diff --git a/python/test/bench/onset/bench-onset b/python/test/bench/onset/bench-onset index 9b3ee436..a3b1b7cd 100755 --- a/python/test/bench/onset/bench-onset +++ b/python/test/bench/onset/bench-onset @@ -19,89 +19,38 @@ def stdev(l): class benchonset(bench): + """ list of values to store per file """ valuenames = ['orig','missed','Tm','expc','bad','Td'] + """ list of lists to store per file """ valuelists = ['l','labs'] - printnames = [ 'mode', 'thres', 'dist', 'prec', 'recl', 'Ttrue', 'Tfp', 'Tfn', 'Tm', 'Td', - 'aTtrue', 'aTfp', 'aTfn', 'aTm', 'aTd', 'mean', 'smean', 'amean', 'samean'] - - formats = {'mode': "%12s" , - 'thres': "%5.4s", - 'dist': "%5.4s", - 'prec': "%5.4s", - 'recl': "%5.4s", - - 'Ttrue': "%5.4s", - 'Tfp': "%5.4s", - 'Tfn': "%5.4s", - 'Tm': "%5.4s", - 'Td': "%5.4s", - - 'aTtrue':"%5.4s", - 'aTfp': "%5.4s", - 'aTfn': "%5.4s", - 'aTm': "%5.4s", - 'aTd': "%5.4s", - - 'mean': "%5.40s", - 'smean': "%5.40s", - 'amean': "%5.40s", - 'samean': "%5.40s"} - - def file_gettruth(self,input): - from os.path import isfile - ftrulist = [] - # search for match as filetask.input,".txt" - ftru = '.'.join(input.split('.')[:-1]) - ftru = '.'.join((ftru,'txt')) - if isfile(ftru): - ftrulist.append(ftru) - else: - # search for matches for filetask.input in the list of results - for i in range(len(self.reslist)): - check = '.'.join(self.reslist[i].split('.')[:-1]) - check = '_'.join(check.split('_')[:-1]) - if check == '.'.join(input.split('.')[:-1]): - ftrulist.append(self.reslist[i]) - return ftrulist - - def file_exec(self,input,output): - filetask = self.task(input,params=self.params) - computed_data = filetask.compute_all() - ftrulist = self.file_gettruth(filetask.input) - for i in ftrulist: - #print i - filetask.eval(computed_data,i,mode='rocloc',vmode='') - for i in self.valuenames: - self.v[i] += filetask.v[i] - for i in filetask.v['l']: - self.v['l'].append(i) - for i in filetask.v['labs']: - self.v['labs'].append(i) - - def dir_exec(self): - """ run file_exec on every input file """ - self.l , self.labs = [], [] - self.v = {} - for i in self.valuenames: - self.v[i] = 0. - for i in self.valuelists: - self.v[i] = [] - self.v['thres'] = self.params.threshold - act_on_files(self.file_exec,self.sndlist,self.reslist, \ - suffix='',filter=sndfile_filter) + """ list of values to print per dir """ + printnames = [ 'mode', 'thres', 'dist', 'prec', 'recl', + 'Ttrue', 'Tfp', 'Tfn', 'Tm', 'Td', + 'aTtrue', 'aTfp', 'aTfn', 'aTm', 'aTd', + 'mean', 'smean', 'amean', 'samean'] + + """ per dir """ + formats = {'mode': "%12s" , 'thres': "%5.4s", + 'dist': "%5.4s", 'prec': "%5.4s", 'recl': "%5.4s", + 'Ttrue': "%5.4s", 'Tfp': "%5.4s", 'Tfn': "%5.4s", + 'Tm': "%5.4s", 'Td': "%5.4s", + 'aTtrue':"%5.4s", 'aTfp': "%5.4s", 'aTfn': "%5.4s", + 'aTm': "%5.4s", 'aTd': "%5.4s", + 'mean': "%5.40s", 'smean': "%5.40s", + 'amean': "%5.40s", 'samean': "%5.40s"} def dir_eval(self): - totaltrue = self.v['expc']-self.v['bad']-self.v['Td'] - totalfp = self.v['bad']+self.v['Td'] - totalfn = self.v['missed']+self.v['Tm'] + """ evaluate statistical data over the directory """ + totaltrue = sum(self.v['expc'])-sum(self.v['bad'])-sum(self.v['Td']) + totalfp = sum(self.v['bad'])+sum(self.v['Td']) + totalfn = sum(self.v['missed'])+sum(self.v['Tm']) self.P = 100*float(totaltrue)/max(totaltrue + totalfp,1) self.R = 100*float(totaltrue)/max(totaltrue + totalfn,1) if self.R < 0: self.R = 0 self.F = 2.* self.P*self.R / max(float(self.P+self.R),1) - N = float(len(self.reslist)) - self.v['mode'] = self.params.onsetmode + self.v['thres'] = self.params.threshold self.v['thres'] = "%2.3f" % self.params.threshold self.v['dist'] = "%2.3f" % self.F self.v['prec'] = "%2.3f" % self.P @@ -112,8 +61,8 @@ class benchonset(bench): self.v['aTtrue'] = totaltrue/N self.v['aTfp'] = totalfp/N self.v['aTfn'] = totalfn/N - self.v['aTm'] = self.v['Tm']/N - self.v['aTd'] = self.v['Td']/N + self.v['aTm'] = sum(self.v['Tm'])/N + self.v['aTd'] = sum(self.v['Td'])/N self.v['mean'] = mmean(self.v['l']) self.v['smean'] = stdev(self.v['l']) self.v['amean'] = mmean(self.v['labs']) @@ -122,7 +71,6 @@ class benchonset(bench): def run_bench(self,modes=['dual'],thresholds=[0.5]): self.modes = modes self.thresholds = thresholds - self.pretty_titles() for mode in self.modes: self.params.onsetmode = mode @@ -133,22 +81,12 @@ class benchonset(bench): self.pretty_print() #print self.v - def pretty_print(self,sep='|'): - for i in self.printnames: - print self.formats[i] % self.v[i], sep, - print - - def pretty_titles(self,sep='|'): - for i in self.printnames: - print self.formats[i] % i, sep, - print - def auto_learn(self,modes=['dual'],thresholds=[0.1,1.5]): """ simple dichotomia like algorithm to optimise threshold """ self.modes = modes self.pretty_titles() for mode in self.modes: - steps = 10 + steps = 11 lesst = thresholds[0] topt = thresholds[1] self.params.onsetmode = mode @@ -230,7 +168,7 @@ if __name__ == "__main__": if len(sys.argv) > 1: datapath = sys.argv[1] else: print "ERR: a path is required"; sys.exit(1) modes = ['complex', 'energy', 'phase', 'specdiff', 'kl', 'mkl', 'dual'] - #modes = [ 'phase' ] + #modes = [ 'mkl' ] thresholds = [ 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2] #thresholds = [1.5] @@ -242,7 +180,6 @@ if __name__ == "__main__": benchonset.task = taskonset benchonset.valuesdict = {} - try: #benchonset.auto_learn2(modes=modes) benchonset.run_bench(modes=modes,thresholds=thresholds)