ref: c912c67ccd0dd420833c8e063fe084f3e59bb85a
parent: e968939e0135dcc1d09d611d875dc07b0605e862
author: Paul Brossier <piem@altern.org>
date: Fri Feb 17 12:17:10 EST 2006
merge some benchonset code into node merge some benchonset code into node
--- a/python/aubio/bench/node.py
+++ b/python/aubio/bench/node.py
@@ -143,20 +143,62 @@
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,
+ def pretty_titles(self,sep='|'):
+ for i in self.printnames:
+ print self.formats[i] % i, sep,
+
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
--- a/python/test/bench/onset/bench-onset
+++ b/python/test/bench/onset/bench-onset
@@ -19,89 +19,38 @@
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']
+ """ 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']
- 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
+ """ 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 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)
-
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 @@
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 @@
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 @@
self.pretty_print()
#print self.v
- def pretty_print(self,sep='|'):
- for i in self.printnames:
- print self.formats[i] % self.v[i], sep,
-
- def pretty_titles(self,sep='|'):
- for i in self.printnames:
- print self.formats[i] % i, sep,
-
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 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]
@@ -241,7 +179,6 @@
benchonset.params = taskparams()
benchonset.task = taskonset
benchonset.valuesdict = {}-
try:
#benchonset.auto_learn2(modes=modes)