class bench:
""" class to run benchmarks on directories """
def __init__(self,datadir,resdir=None,checkres=False,checkanno=False,params=[]):
- from aubio.tasks import taskparams
+ from aubio.task.params import taskparams
self.datadir = datadir
# path to write results path to
self.resdir = resdir
--- /dev/null
+#! /usr/bin/python
+
+from aubio.bench.node import *
+from os.path import dirname,basename
+
+def mmean(l):
+ return sum(l)/max(float(len(l)),1)
+
+def stdev(l):
+ smean = 0
+ if not len(l): return smean
+ lmean = mmean(l)
+ for i in l:
+ smean += (i-lmean)**2
+ smean *= 1. / len(l)
+ return smean**.5
+
+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']
+ """ list of values to print per dir """
+ printnames = [ 'mode', 'thres', 'dist', 'prec', 'recl',
+ 'GD', 'FP',
+ 'Torig', 'Ttrue', 'Tfp', 'Tfn', 'TTm', 'TTd',
+ '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",
+ 'Torig': "%5.4s", 'Ttrue': "%5.4s", 'Tfp': "%5.4s", 'Tfn': "%5.4s",
+ 'TTm': "%5.4s", 'TTd': "%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",
+ "GD": "%5.4s", "FP": "%5.4s",
+ "GDm": "%5.4s", "FPd": "%5.4s"}
+
+ def dir_eval(self):
+ """ evaluate statistical data over the directory """
+ v = self.v
+
+ v['mode'] = self.params.onsetmode
+ v['thres'] = self.params.threshold
+ v['bufsize'] = self.params.bufsize
+ v['hopsize'] = self.params.hopsize
+ v['silence'] = self.params.silence
+ v['mintol'] = self.params.mintol
+
+ v['Torig'] = sum(v['orig'])
+ v['TTm'] = sum(v['Tm'])
+ v['TTd'] = sum(v['Td'])
+ v['Texpc'] = sum(v['expc'])
+ v['Tbad'] = sum(v['bad'])
+ v['Tmissed'] = sum(v['missed'])
+ v['aTm'] = mmean(v['Tm'])
+ v['aTd'] = mmean(v['Td'])
+
+ v['mean'] = mmean(v['l'])
+ v['smean'] = stdev(v['l'])
+
+ v['amean'] = mmean(v['labs'])
+ v['samean'] = stdev(v['labs'])
+
+ # old type calculations
+ # good detection rate
+ v['GD'] = 100.*(v['Torig']-v['Tmissed']-v['TTm'])/v['Torig']
+ # false positive rate
+ v['FP'] = 100.*(v['Tbad']+v['TTd'])/v['Torig']
+ # good detection counting merged detections as good
+ v['GDm'] = 100.*(v['Torig']-v['Tmissed'])/v['Torig']
+ # false positives counting doubled as good
+ v['FPd'] = 100.*v['Tbad']/v['Torig']
+
+ # mirex type annotations
+ totaltrue = v['Texpc']-v['Tbad']-v['TTd']
+ totalfp = v['Tbad']+v['TTd']
+ totalfn = v['Tmissed']+v['TTm']
+ self.v['Ttrue'] = totaltrue
+ self.v['Tfp'] = totalfp
+ self.v['Tfn'] = totalfn
+ # average over the number of annotation files
+ N = float(len(self.reslist))
+ self.v['aTtrue'] = totaltrue/N
+ self.v['aTfp'] = totalfp/N
+ self.v['aTfn'] = totalfn/N
+
+ # F-measure
+ 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)
+ self.v['dist'] = self.F
+ self.v['prec'] = self.P
+ self.v['recl'] = self.R
+
+
+ """
+ Plot functions
+ """
+
+ def plotroc(self,d,plottitle=""):
+ import Gnuplot, Gnuplot.funcutils
+ gd = []
+ fp = []
+ for i in self.vlist:
+ gd.append(i['GD'])
+ fp.append(i['FP'])
+ d.append(Gnuplot.Data(fp, gd, with='linespoints',
+ title="%s %s" % (plottitle,i['mode']) ))
+
+ def plotplotroc(self,d,outplot=0,extension='ps'):
+ import Gnuplot, Gnuplot.funcutils
+ from sys import exit
+ g = Gnuplot.Gnuplot(debug=0, persist=1)
+ if outplot:
+ if extension == 'ps': ext, extension = '.ps' , 'postscript'
+ elif extension == 'png': ext, extension = '.png', 'png'
+ elif extension == 'svg': ext, extension = '.svg', 'svg'
+ else: exit("ERR: unknown plot extension")
+ g('set terminal %s' % extension)
+ g('set output \'roc-%s%s\'' % (outplot,ext))
+ xmax = 30 #max(fp)
+ ymin = 50
+ g('set xrange [0:%f]' % xmax)
+ g('set yrange [%f:100]' % ymin)
+ # grid set
+ g('set grid')
+ g('set xtics 0,5,%f' % xmax)
+ g('set ytics %f,5,100' % ymin)
+ g('set key 27,65')
+ #g('set format \"%g\"')
+ g.title(basename(self.datadir))
+ g.xlabel('false positives (%)')
+ g.ylabel('correct detections (%)')
+ g.plot(*d)
+
+ def plotpr(self,d,plottitle=""):
+ import Gnuplot, Gnuplot.funcutils
+ x = []
+ y = []
+ for i in self.vlist:
+ x.append(i['prec'])
+ y.append(i['recl'])
+ d.append(Gnuplot.Data(x, y, with='linespoints',
+ title="%s %s" % (plottitle,i['mode']) ))
+
+ def plotplotpr(self,d,outplot=0,extension='ps'):
+ import Gnuplot, Gnuplot.funcutils
+ from sys import exit
+ g = Gnuplot.Gnuplot(debug=0, persist=1)
+ if outplot:
+ if extension == 'ps': ext, extension = '.ps' , 'postscript'
+ elif extension == 'png': ext, extension = '.png', 'png'
+ elif extension == 'svg': ext, extension = '.svg', 'svg'
+ else: exit("ERR: unknown plot extension")
+ g('set terminal %s' % extension)
+ g('set output \'pr-%s%s\'' % (outplot,ext))
+ g.title(basename(self.datadir))
+ g.xlabel('Recall (%)')
+ g.ylabel('Precision (%)')
+ g.plot(*d)
+
+ def plotfmeas(self,d,plottitle=""):
+ import Gnuplot, Gnuplot.funcutils
+ x,y = [],[]
+ for i in self.vlist:
+ x.append(i['thres'])
+ y.append(i['dist'])
+ d.append(Gnuplot.Data(x, y, with='linespoints',
+ title="%s %s" % (plottitle,i['mode']) ))
+
+ def plotplotfmeas(self,d,outplot="",extension='ps', title="F-measure"):
+ import Gnuplot, Gnuplot.funcutils
+ from sys import exit
+ g = Gnuplot.Gnuplot(debug=0, persist=1)
+ if outplot:
+ if extension == 'ps': terminal = 'postscript'
+ elif extension == 'png': terminal = 'png'
+ elif extension == 'svg': terminal = 'svg'
+ else: exit("ERR: unknown plot extension")
+ g('set terminal %s' % terminal)
+ g('set output \'fmeas-%s.%s\'' % (outplot,extension))
+ g.xlabel('threshold \\delta')
+ g.ylabel('F-measure (%)')
+ g('set xrange [0:1.2]')
+ g('set yrange [0:100]')
+ g.title(basename(self.datadir))
+ # grid set
+ #g('set grid')
+ #g('set xtics 0,5,%f' % xmax)
+ #g('set ytics %f,5,100' % ymin)
+ #g('set key 27,65')
+ #g('set format \"%g\"')
+ g.plot(*d)
+
+ def plotfmeasvar(self,d,var,plottitle=""):
+ import Gnuplot, Gnuplot.funcutils
+ x,y = [],[]
+ for i in self.vlist:
+ x.append(i[var])
+ y.append(i['dist'])
+ d.append(Gnuplot.Data(x, y, with='linespoints',
+ title="%s %s" % (plottitle,i['mode']) ))
+
+ def plotplotfmeasvar(self,d,var,outplot="",extension='ps', title="F-measure"):
+ import Gnuplot, Gnuplot.funcutils
+ from sys import exit
+ g = Gnuplot.Gnuplot(debug=0, persist=1)
+ if outplot:
+ if extension == 'ps': terminal = 'postscript'
+ elif extension == 'png': terminal = 'png'
+ elif extension == 'svg': terminal = 'svg'
+ else: exit("ERR: unknown plot extension")
+ g('set terminal %s' % terminal)
+ g('set output \'fmeas-%s.%s\'' % (outplot,extension))
+ g.xlabel(var)
+ g.ylabel('F-measure (%)')
+ #g('set xrange [0:1.2]')
+ g('set yrange [0:100]')
+ g.title(basename(self.datadir))
+ g.plot(*d)
+
+ def plotdiffs(self,d,plottitle=""):
+ import Gnuplot, Gnuplot.funcutils
+ v = self.v
+ l = v['l']
+ mean = v['mean']
+ smean = v['smean']
+ amean = v['amean']
+ samean = v['samean']
+ val = []
+ per = [0] * 100
+ for i in range(0,100):
+ val.append(i*.001-.05)
+ for j in l:
+ if abs(j-val[i]) <= 0.001:
+ per[i] += 1
+ total = v['Torig']
+ for i in range(len(per)): per[i] /= total/100.
+
+ d.append(Gnuplot.Data(val, per, with='fsteps',
+ title="%s %s" % (plottitle,v['mode']) ))
+ #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (mean,smean))
+ #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (amean,samean))
+
+
+ def plotplotdiffs(self,d,outplot=0,extension='ps'):
+ import Gnuplot, Gnuplot.funcutils
+ from sys import exit
+ g = Gnuplot.Gnuplot(debug=0, persist=1)
+ if outplot:
+ if extension == 'ps': ext, extension = '.ps' , 'postscript'
+ elif extension == 'png': ext, extension = '.png', 'png'
+ elif extension == 'svg': ext, extension = '.svg', 'svg'
+ else: exit("ERR: unknown plot extension")
+ g('set terminal %s' % extension)
+ g('set output \'diffhist-%s%s\'' % (outplot,ext))
+ g('eps(x) = 1./(sigma*(2.*3.14159)**.5) * exp ( - ( x - mean ) ** 2. / ( 2. * sigma ** 2. ))')
+ g.title(basename(self.datadir))
+ g.xlabel('delay to hand-labelled onset (s)')
+ g.ylabel('% number of correct detections / ms ')
+ g('set xrange [-0.05:0.05]')
+ g('set yrange [0:20]')
+ g.plot(*d)
+
+
+ def plothistcat(self,d,plottitle=""):
+ import Gnuplot, Gnuplot.funcutils
+ total = v['Torig']
+ for i in range(len(per)): per[i] /= total/100.
+
+ d.append(Gnuplot.Data(val, per, with='fsteps',
+ title="%s %s" % (plottitle,v['mode']) ))
+ #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (mean,smean))
+ #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (amean,samean))
+
+
+ def plotplothistcat(self,d,outplot=0,extension='ps'):
+ import Gnuplot, Gnuplot.funcutils
+ from sys import exit
+ g = Gnuplot.Gnuplot(debug=0, persist=1)
+ if outplot:
+ if extension == 'ps': ext, extension = '.ps' , 'postscript'
+ elif extension == 'png': ext, extension = '.png', 'png'
+ elif extension == 'svg': ext, extension = '.svg', 'svg'
+ else: exit("ERR: unknown plot extension")
+ g('set terminal %s' % extension)
+ g('set output \'diffhist-%s%s\'' % (outplot,ext))
+ g('eps(x) = 1./(sigma*(2.*3.14159)**.5) * exp ( - ( x - mean ) ** 2. / ( 2. * sigma ** 2. ))')
+ g.title(basename(self.datadir))
+ g.xlabel('delay to hand-labelled onset (s)')
+ g.ylabel('% number of correct detections / ms ')
+ g('set xrange [-0.05:0.05]')
+ g('set yrange [0:20]')
+ g.plot(*d)
+
+
print self.params.step*foo[0]
def eval(self,inputdata,ftru,mode='roc',vmode=''):
- from txtfile import read_datafile
- from onsetcompare import onset_roc, onset_diffs, onset_rocloc
+ from aubio.txtfile import read_datafile
+ from aubio.onsetcompare import onset_roc, onset_diffs, onset_rocloc
ltru = read_datafile(ftru,depth=0)
lres = []
for i in range(len(inputdata)): lres.append(inputdata[i][0]*self.params.step)
#! /usr/bin/python
-from aubio.tasks import *
+from aubio.task import *
-from benchonset import mmean, stdev, benchonset
+from aubio.bench.onset import mmean, stdev, benchonset
class mybenchonset(benchonset):
+++ /dev/null
-#! /usr/bin/python
-
-from aubio.bench.node import *
-from os.path import dirname,basename
-
-def mmean(l):
- return sum(l)/max(float(len(l)),1)
-
-def stdev(l):
- smean = 0
- if not len(l): return smean
- lmean = mmean(l)
- for i in l:
- smean += (i-lmean)**2
- smean *= 1. / len(l)
- return smean**.5
-
-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']
- """ list of values to print per dir """
- printnames = [ 'mode', 'thres', 'dist', 'prec', 'recl',
- 'GD', 'FP',
- 'Torig', 'Ttrue', 'Tfp', 'Tfn', 'TTm', 'TTd',
- '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",
- 'Torig': "%5.4s", 'Ttrue': "%5.4s", 'Tfp': "%5.4s", 'Tfn': "%5.4s",
- 'TTm': "%5.4s", 'TTd': "%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",
- "GD": "%5.4s", "FP": "%5.4s",
- "GDm": "%5.4s", "FPd": "%5.4s"}
-
- def dir_eval(self):
- """ evaluate statistical data over the directory """
- v = self.v
-
- v['mode'] = self.params.onsetmode
- v['thres'] = self.params.threshold
- v['bufsize'] = self.params.bufsize
- v['hopsize'] = self.params.hopsize
- v['silence'] = self.params.silence
- v['mintol'] = self.params.mintol
-
- v['Torig'] = sum(v['orig'])
- v['TTm'] = sum(v['Tm'])
- v['TTd'] = sum(v['Td'])
- v['Texpc'] = sum(v['expc'])
- v['Tbad'] = sum(v['bad'])
- v['Tmissed'] = sum(v['missed'])
- v['aTm'] = mmean(v['Tm'])
- v['aTd'] = mmean(v['Td'])
-
- v['mean'] = mmean(v['l'])
- v['smean'] = stdev(v['l'])
-
- v['amean'] = mmean(v['labs'])
- v['samean'] = stdev(v['labs'])
-
- # old type calculations
- # good detection rate
- v['GD'] = 100.*(v['Torig']-v['Tmissed']-v['TTm'])/v['Torig']
- # false positive rate
- v['FP'] = 100.*(v['Tbad']+v['TTd'])/v['Torig']
- # good detection counting merged detections as good
- v['GDm'] = 100.*(v['Torig']-v['Tmissed'])/v['Torig']
- # false positives counting doubled as good
- v['FPd'] = 100.*v['Tbad']/v['Torig']
-
- # mirex type annotations
- totaltrue = v['Texpc']-v['Tbad']-v['TTd']
- totalfp = v['Tbad']+v['TTd']
- totalfn = v['Tmissed']+v['TTm']
- self.v['Ttrue'] = totaltrue
- self.v['Tfp'] = totalfp
- self.v['Tfn'] = totalfn
- # average over the number of annotation files
- N = float(len(self.reslist))
- self.v['aTtrue'] = totaltrue/N
- self.v['aTfp'] = totalfp/N
- self.v['aTfn'] = totalfn/N
-
- # F-measure
- 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)
- self.v['dist'] = self.F
- self.v['prec'] = self.P
- self.v['recl'] = self.R
-
-
- """
- Plot functions
- """
-
- def plotroc(self,d,plottitle=""):
- import Gnuplot, Gnuplot.funcutils
- gd = []
- fp = []
- for i in self.vlist:
- gd.append(i['GD'])
- fp.append(i['FP'])
- d.append(Gnuplot.Data(fp, gd, with='linespoints',
- title="%s %s" % (plottitle,i['mode']) ))
-
- def plotplotroc(self,d,outplot=0,extension='ps'):
- import Gnuplot, Gnuplot.funcutils
- from sys import exit
- g = Gnuplot.Gnuplot(debug=0, persist=1)
- if outplot:
- if extension == 'ps': ext, extension = '.ps' , 'postscript'
- elif extension == 'png': ext, extension = '.png', 'png'
- elif extension == 'svg': ext, extension = '.svg', 'svg'
- else: exit("ERR: unknown plot extension")
- g('set terminal %s' % extension)
- g('set output \'roc-%s%s\'' % (outplot,ext))
- xmax = 30 #max(fp)
- ymin = 50
- g('set xrange [0:%f]' % xmax)
- g('set yrange [%f:100]' % ymin)
- # grid set
- g('set grid')
- g('set xtics 0,5,%f' % xmax)
- g('set ytics %f,5,100' % ymin)
- g('set key 27,65')
- #g('set format \"%g\"')
- g.title(basename(self.datadir))
- g.xlabel('false positives (%)')
- g.ylabel('correct detections (%)')
- g.plot(*d)
-
- def plotpr(self,d,plottitle=""):
- import Gnuplot, Gnuplot.funcutils
- x = []
- y = []
- for i in self.vlist:
- x.append(i['prec'])
- y.append(i['recl'])
- d.append(Gnuplot.Data(x, y, with='linespoints',
- title="%s %s" % (plottitle,i['mode']) ))
-
- def plotplotpr(self,d,outplot=0,extension='ps'):
- import Gnuplot, Gnuplot.funcutils
- from sys import exit
- g = Gnuplot.Gnuplot(debug=0, persist=1)
- if outplot:
- if extension == 'ps': ext, extension = '.ps' , 'postscript'
- elif extension == 'png': ext, extension = '.png', 'png'
- elif extension == 'svg': ext, extension = '.svg', 'svg'
- else: exit("ERR: unknown plot extension")
- g('set terminal %s' % extension)
- g('set output \'pr-%s%s\'' % (outplot,ext))
- g.title(basename(self.datadir))
- g.xlabel('Recall (%)')
- g.ylabel('Precision (%)')
- g.plot(*d)
-
- def plotfmeas(self,d,plottitle=""):
- import Gnuplot, Gnuplot.funcutils
- x,y = [],[]
- for i in self.vlist:
- x.append(i['thres'])
- y.append(i['dist'])
- d.append(Gnuplot.Data(x, y, with='linespoints',
- title="%s %s" % (plottitle,i['mode']) ))
-
- def plotplotfmeas(self,d,outplot="",extension='ps', title="F-measure"):
- import Gnuplot, Gnuplot.funcutils
- from sys import exit
- g = Gnuplot.Gnuplot(debug=0, persist=1)
- if outplot:
- if extension == 'ps': terminal = 'postscript'
- elif extension == 'png': terminal = 'png'
- elif extension == 'svg': terminal = 'svg'
- else: exit("ERR: unknown plot extension")
- g('set terminal %s' % terminal)
- g('set output \'fmeas-%s.%s\'' % (outplot,extension))
- g.xlabel('threshold \\delta')
- g.ylabel('F-measure (%)')
- g('set xrange [0:1.2]')
- g('set yrange [0:100]')
- g.title(basename(self.datadir))
- # grid set
- #g('set grid')
- #g('set xtics 0,5,%f' % xmax)
- #g('set ytics %f,5,100' % ymin)
- #g('set key 27,65')
- #g('set format \"%g\"')
- g.plot(*d)
-
- def plotfmeasvar(self,d,var,plottitle=""):
- import Gnuplot, Gnuplot.funcutils
- x,y = [],[]
- for i in self.vlist:
- x.append(i[var])
- y.append(i['dist'])
- d.append(Gnuplot.Data(x, y, with='linespoints',
- title="%s %s" % (plottitle,i['mode']) ))
-
- def plotplotfmeasvar(self,d,var,outplot="",extension='ps', title="F-measure"):
- import Gnuplot, Gnuplot.funcutils
- from sys import exit
- g = Gnuplot.Gnuplot(debug=0, persist=1)
- if outplot:
- if extension == 'ps': terminal = 'postscript'
- elif extension == 'png': terminal = 'png'
- elif extension == 'svg': terminal = 'svg'
- else: exit("ERR: unknown plot extension")
- g('set terminal %s' % terminal)
- g('set output \'fmeas-%s.%s\'' % (outplot,extension))
- g.xlabel(var)
- g.ylabel('F-measure (%)')
- #g('set xrange [0:1.2]')
- g('set yrange [0:100]')
- g.title(basename(self.datadir))
- g.plot(*d)
-
- def plotdiffs(self,d,plottitle=""):
- import Gnuplot, Gnuplot.funcutils
- v = self.v
- l = v['l']
- mean = v['mean']
- smean = v['smean']
- amean = v['amean']
- samean = v['samean']
- val = []
- per = [0] * 100
- for i in range(0,100):
- val.append(i*.001-.05)
- for j in l:
- if abs(j-val[i]) <= 0.001:
- per[i] += 1
- total = v['Torig']
- for i in range(len(per)): per[i] /= total/100.
-
- d.append(Gnuplot.Data(val, per, with='fsteps',
- title="%s %s" % (plottitle,v['mode']) ))
- #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (mean,smean))
- #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (amean,samean))
-
-
- def plotplotdiffs(self,d,outplot=0,extension='ps'):
- import Gnuplot, Gnuplot.funcutils
- from sys import exit
- g = Gnuplot.Gnuplot(debug=0, persist=1)
- if outplot:
- if extension == 'ps': ext, extension = '.ps' , 'postscript'
- elif extension == 'png': ext, extension = '.png', 'png'
- elif extension == 'svg': ext, extension = '.svg', 'svg'
- else: exit("ERR: unknown plot extension")
- g('set terminal %s' % extension)
- g('set output \'diffhist-%s%s\'' % (outplot,ext))
- g('eps(x) = 1./(sigma*(2.*3.14159)**.5) * exp ( - ( x - mean ) ** 2. / ( 2. * sigma ** 2. ))')
- g.title(basename(self.datadir))
- g.xlabel('delay to hand-labelled onset (s)')
- g.ylabel('% number of correct detections / ms ')
- g('set xrange [-0.05:0.05]')
- g('set yrange [0:20]')
- g.plot(*d)
-
-
- def plothistcat(self,d,plottitle=""):
- import Gnuplot, Gnuplot.funcutils
- total = v['Torig']
- for i in range(len(per)): per[i] /= total/100.
-
- d.append(Gnuplot.Data(val, per, with='fsteps',
- title="%s %s" % (plottitle,v['mode']) ))
- #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (mean,smean))
- #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (amean,samean))
-
-
- def plotplothistcat(self,d,outplot=0,extension='ps'):
- import Gnuplot, Gnuplot.funcutils
- from sys import exit
- g = Gnuplot.Gnuplot(debug=0, persist=1)
- if outplot:
- if extension == 'ps': ext, extension = '.ps' , 'postscript'
- elif extension == 'png': ext, extension = '.png', 'png'
- elif extension == 'svg': ext, extension = '.svg', 'svg'
- else: exit("ERR: unknown plot extension")
- g('set terminal %s' % extension)
- g('set output \'diffhist-%s%s\'' % (outplot,ext))
- g('eps(x) = 1./(sigma*(2.*3.14159)**.5) * exp ( - ( x - mean ) ** 2. / ( 2. * sigma ** 2. ))')
- g.title(basename(self.datadir))
- g.xlabel('delay to hand-labelled onset (s)')
- g.ylabel('% number of correct detections / ms ')
- g('set xrange [-0.05:0.05]')
- g('set yrange [0:20]')
- g.plot(*d)
-
-
#! /usr/bin/python
from aubio.bench.node import *
-from aubio.tasks import *
+from aubio.task import *
class benchpitch(bench):
projects / aubio.git / commitdiff