#! /usr/bin/python
-from aubio.bench.node import *
from aubio.tasks import *
from benchonset import mmean, stdev, benchonset
def run_bench(self,modes=['dual'],thresholds=[0.5]):
from os.path import dirname,basename
- self.modes = modes
self.thresholds = thresholds
self.pretty_titles()
- for mode in self.modes:
- d = []
- outplot = "_-_".join(("delay",mode,
- basename(self.datadir) ))
+ for mode in modes:
+ d = []
self.params.onsetmode = mode
+ self.params.localmin = True
+ self.params.delay = 1.
self.params.threshold = thresholds[0]
-
+ #
self.params.localmin = False
self.params.delay = 0.
-
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
+ self.dir_eval_print()
self.plotdiffs(d,plottitle="Causal")
-
+ #
self.params.localmin = True
self.params.delay = 0.
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
+ self.dir_eval_print()
self.plotdiffs(d,plottitle="Local min")
self.params.localmin = False
self.params.delay = 6.
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
+ self.dir_eval_print()
self.plotdiffs(d,plottitle="Fixed delay")
- self.plotplotdiffs(d)
- self.plotplotdiffs(d,outplot=outplot,extension="png")
- self.plotplotdiffs(d,outplot=outplot,extension="ps")
- self.plotplotdiffs(d,outplot=outplot,extension="svg")
-
+ #self.plotplotdiffs(d)
+ outplot = "_-_".join(("delay",mode,basename(self.datadir) ))
+ for ext in ("png","svg","ps"):
+ self.plotplotdiffs(d,outplot=outplot,extension=ext)
if __name__ == "__main__":
import sys
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 = [ 'complex' ]
- thresholds = [ 0.5]
- #thresholds = [1.5]
+ modes = ['complex', 'energy', 'phase', 'hfc', 'specdiff', 'kl', 'mkl', 'dual']
+ #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]
+ #modes = [ 'hfc' ]
+ thresholds = [0.5]
#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
respath = '/var/tmp/DB-testings'
from os.path import dirname,basename
self.thresholds = thresholds
self.pretty_titles()
- d,e,f = [],[],[]
+ d,e,f,g = [],[],[],[]
for mode in modes:
self.vlist = []
self.params.onsetmode = mode
+ #self.params.localmin = True
+ self.params.delay = 2.
+ self.params.bufsize = 1024
+ self.params.hopsize = 256
+ self.params.step = float(self.params.hopsize)/float(self.params.samplerate)
+ #self.params.mintol = 8.
+
for threshold in self.thresholds:
self.params.threshold = threshold
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
- #print self.v
+ self.dir_eval_print()
self.vlist.append(self.v)
self.plotroc(d)
self.plotfmeas(e)
self.plotpr(f)
- #print vlist
+ #self.plothistcat(g)
+
+
+
#self.plotplotroc(d)
#self.plotplotfmeas(e)
#self.plotplotpr(f)
self.plotplotroc(d,outplot=outplot,extension=ext)
self.plotplotfmeas(e,outplot=outplot,extension=ext)
self.plotplotpr(f,outplot=outplot,extension=ext)
-
-
- 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 = 11
- lesst = thresholds[0]
- topt = thresholds[1]
- self.params.onsetmode = mode
-
- self.params.threshold = topt
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
- topF = self.F
-
- self.params.threshold = lesst
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
- lessF = self.F
-
- for i in range(steps):
- self.params.localmin = True
- self.params.delay = 1.
- self.dir_exec()
- self.dir_eval()
- self.params.threshold = ( lesst + topt ) * .5
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
- if self.F == 100.0 or self.F == topF:
- print "assuming we converged, stopping"
- break
- #elif abs(self.F - topF) < 0.01 :
- # print "done converging"
- # break
- if topF < self.F:
- #lessF = topF
- #lesst = topt
- topF = self.F
- topt = self.params.threshold
- elif lessF < self.F:
- lessF = self.F
- lesst = self.params.threshold
- if topt == lesst:
- lesst /= 2.
-
- def auto_learn2(self,modes=['dual'],thresholds=[0.00001,1.0]):
- """ simple dichotomia like algorithm to optimise threshold """
- self.modes = modes
- self.pretty_titles([])
- for mode in self.modes:
- steps = 10
- step = 0.4
- self.params.onsetmode = mode
- self.params.threshold = thresholds[0]
- cur = 0
-
- for i in range(steps):
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
- new = self.P
- if self.R == 0.0:
- #print "Found maximum, highering"
- step /= 2.
- self.params.threshold -= step
- elif new == 100.0:
- #print "Found maximum, highering"
- step *= .99
- self.params.threshold += step
- elif cur > new:
- #print "lower"
- step /= 2.
- self.params.threshold -= step
- elif cur < new:
- #print "higher"
- step *= .99
- self.params.threshold += step
- else:
- print "Assuming we converged"
- break
- cur = new
-
+ #self.plotplothistcat(g,outplot=outplot,extension=ext)
if __name__ == "__main__":
import sys
modes = ['complex', 'energy', 'phase', 'hfc', 'specdiff', 'kl', 'mkl', 'dual']
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]
#modes = [ 'hfc' ]
- #thresholds = [0.1, 1.5]
+ #thresholds = [0.5]
#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
respath = '/var/tmp/DB-testings'
from aubio.tasks import *
-from benchonset import mmean, stdev, plotdiffs, plotplotdiffs, benchonset
+from benchonset import mmean, stdev, benchonset
class mybenchonset(benchonset):
from os.path import dirname,basename
self.thresholds = thresholds
self.pretty_titles()
+
for mode in modes:
self.params.onsetmode = mode
+ self.params.localmin = True
+ self.params.delay = 1.
self.params.threshold = thresholds[0]
self.params.localmin = False
-
+ #
for delay in (0., 4.):
d = []
- outplot = "_-_".join(("window",mode,"delay-%s" % delay,
- basename(self.datadir) ))
self.params.delay = delay
-
for buf in (2048, 1024, 512):
for hop in (buf/2, buf/4):
self.params.bufsize = buf
self.params.hopsize = hop
self.params.step = float(self.params.hopsize)/float(self.params.samplerate)
-
- self.dir_exec()
- self.dir_eval()
- self.pretty_print()
- plotdiffs(self.v,d,plottitle="%s %s" % (buf,hop))
-
- plotplotdiffs(d)
- plotplotdiffs(d,outplot=outplot,extension="png")
- plotplotdiffs(d,outplot=outplot,extension="ps")
- plotplotdiffs(d,outplot=outplot,extension="svg")
-
+ self.dir_eval_print()
+ self.plotdiffs(d,plottitle="%s %s" % (buf,hop))
+ #plotplotdiffs(d)
+ outplot = "_-_".join(("window",mode,"delay-%s" % int(delay),
+ basename(self.datadir) ))
+ for ext in ("png","svg","ps"):
+ self.plotplotdiffs(d,outplot=outplot,extension=ext)
if __name__ == "__main__":
import sys
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 = [ 'complex' ]
- thresholds = [ 0.5]
- #thresholds = [1.5]
+ modes = ['complex', 'energy', 'phase', 'hfc', 'specdiff', 'kl', 'mkl', 'dual']
+ #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]
+ #modes = [ 'hfc' ]
+ thresholds = [0.5]
#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
respath = '/var/tmp/DB-testings'
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'])
self.v['prec'] = self.P
self.v['recl'] = self.R
+
+ """
+ Plot functions
+ """
+
def plotroc(self,d,plottitle=""):
import Gnuplot, Gnuplot.funcutils
gd = []
#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
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 [0:50]')
+ 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)
projects / aubio.git / commitdiff