Index: python/test/bench/onset/Makefile.am
===================================================================
--- python/test/bench/onset/Makefile.am	(revision 99d27b7be002e2ef4fde2f09e341584f1968bb48)
+++ python/test/bench/onset/Makefile.am	(revision 83c67348be306b34e1783ba44972675c9e33df30)
@@ -3,9 +3,7 @@
 export LD_LIBRARY_PATH=$(BASEDIR)/src/.libs:$(BASEDIR)/ext/.libs
 
-SOURCE = \
-	/archives/samples/DB/PercussivePhrases/CM18/Samba_Audio \
+DETAILSOURCE = \
 	/var/tmp/Onset-Mirex2005/poly_pitched \
 	/var/tmp/Onset-Mirex2005/solo_bars_and_bells \
-	/var/tmp/Onset-Mirex2005/solo_brass \
 	/var/tmp/Onset-Mirex2005/solo_drums \
 	/var/tmp/Onset-Mirex2005/solo_plucked_strings \
@@ -13,11 +11,33 @@
 	/var/tmp/Onset-Mirex2005/solo_sustained_strings \
 	/var/tmp/Onset-Mirex2005/solo_winds \
-	/var/tmp/Onset-Mirex2005/complex \
-	/var/tmp/Onset-Mirex2005
+	/var/tmp/Onset-Mirex2005/complex
 
-test-aubiocut:         $(patsubst %, %.aubiocut, $(SOURCE))
+SOURCE = /var/tmp/Onset-Mirex2005
+
+TESTSOURCE = \
+	/var/tmp/Onset-Mirex2005/solo_bars_and_bells \
+	/var/tmp/Onset-Mirex2005/solo_winds \
+	/archives/samples/DB/PercussivePhrases/CM18/Samba_Audio
+
+test-aubiocut:            $(patsubst %, %.aubiocut,    $(TESTSOURCE))
+test-aubiodelay:          $(patsubst %, %.aubiodelay,  $(TESTSOURCE))
+test-aubiowindow:         $(patsubst %, %.aubiowindow, $(TESTSOURCE))
+
+final-aubiocut:           $(patsubst %, %.aubiocut,    $(DETAILSOURCE) $(SOURCE))
+final-aubiodelay:         $(patsubst %, %.aubiodelay,  $(SOURCE))
+final-aubiowindow:        $(patsubst %, %.aubiowindow, $(SOURCE))
 
 %.aubiocut: %
 	rm -f `basename $<`.aubiocut
 	./bench-onset $< | tee `basename $<`.aubiocut
-	diff `basename $<`.aubiocut.ref `basename $<`.aubiocut
+	-diff `basename $<`.aubiocut.ref `basename $<`.aubiocut
+
+%.aubiodelay: %
+	rm -f `basename $@`
+	./bench-delay $< | tee `basename $@`
+	-diff `basename $@`.ref `basename $@`
+
+%.aubiowindow: %
+	rm -f `basename $@`
+	./bench-window $< | tee `basename $@`
+	-diff `basename $@`.ref `basename $@`
Index: python/test/bench/onset/bench-delay
===================================================================
--- python/test/bench/onset/bench-delay	(revision 83c67348be306b34e1783ba44972675c9e33df30)
+++ python/test/bench/onset/bench-delay	(revision 83c67348be306b34e1783ba44972675c9e33df30)
@@ -0,0 +1,72 @@
+#! /usr/bin/python
+
+from aubio.bench.node import *
+from aubio.tasks import *
+
+from benchonset import mmean, stdev, benchonset
+
+class mybenchonset(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) ))
+
+			self.params.onsetmode = mode
+			self.params.threshold = thresholds[0]
+
+			self.params.localmin = False 
+			self.params.delay = 0. 
+
+			self.dir_exec()
+			self.dir_eval()
+			self.pretty_print()
+			self.plotdiffs(d,plottitle="Causal")
+
+			self.params.localmin = True
+			self.params.delay = 0. 
+			self.dir_exec()
+			self.dir_eval()
+			self.pretty_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.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")
+
+
+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]
+
+	#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
+	respath = '/var/tmp/DB-testings'
+
+	benchonset = mybenchonset(datapath,respath,checkres=True,checkanno=True)
+	benchonset.params = taskparams()
+	benchonset.task = taskonset
+	benchonset.valuesdict = {}
+
+	try:
+		#benchonset.auto_learn2(modes=modes)
+		benchonset.run_bench(modes=modes,thresholds=thresholds)
+	except KeyboardInterrupt:
+		sys.exit(1)
Index: python/test/bench/onset/bench-onset
===================================================================
--- python/test/bench/onset/bench-onset	(revision 99d27b7be002e2ef4fde2f09e341584f1968bb48)
+++ python/test/bench/onset/bench-onset	(revision 83c67348be306b34e1783ba44972675c9e33df30)
@@ -1,79 +1,17 @@
 #! /usr/bin/python
 
-from aubio.bench.node import *
 from aubio.tasks import *
 
+from benchonset import mmean, stdev, benchonset
 
-
-
-def mmean(l):
-	return sum(l)/float(len(l))
-
-def stdev(l):
-	smean = 0
-	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', 
-		'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):
-		""" 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
-		self.v['recl']      = "%2.3f" % self.R
-		self.v['Ttrue']     = totaltrue
-		self.v['Tfp']       = totalfp
-		self.v['Tfn']       = totalfn
-		self.v['aTtrue']    = totaltrue/N
-		self.v['aTfp']      = totalfp/N
-		self.v['aTfn']      = totalfn/N
-		self.v['aTm']       = sum(self.v['Tm'])/N
-		self.v['aTd']       = sum(self.v['Td'])/N
-		self.v['Tm']       = sum(self.v['Tm'])
-		self.v['Td']       = sum(self.v['Td'])
-		self.v['mean']      = mmean(self.v['l'])
-		self.v['smean']     = stdev(self.v['l'])
-		self.v['amean']     = mmean(self.v['labs'])
-		self.v['samean']    = stdev(self.v['labs'])
+class mybenchonset(benchonset):
 
 	def run_bench(self,modes=['dual'],thresholds=[0.5]):
-		self.modes = modes
+		from os.path import dirname,basename
 		self.thresholds = thresholds
 		self.pretty_titles()
-		for mode in self.modes:
+		d,e,f = [],[],[]
+		for mode in modes:
+			self.vlist = []
 			self.params.onsetmode = mode
 			for threshold in self.thresholds:
@@ -83,4 +21,18 @@
 				self.pretty_print()
 				#print self.v
+				self.vlist.append(self.v)
+			self.plotroc(d)
+			self.plotfmeas(e)
+			self.plotpr(f)
+			#print vlist
+		#self.plotplotroc(d)
+		#self.plotplotfmeas(e)
+		#self.plotplotpr(f)
+		outplot = basename(self.datadir)
+		for ext in ("png","svg","ps"):
+			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]):
@@ -107,4 +59,8 @@
 
 			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()
@@ -170,13 +126,13 @@
 	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 = [ 'mkl' ]
+	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]
-	#thresholds = [1.5]
+	#modes = [ 'hfc' ]
+	#thresholds = [0.1, 1.5]
 
 	#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
 	respath = '/var/tmp/DB-testings'
 
-	benchonset = benchonset(datapath,respath,checkres=True,checkanno=True)
+	benchonset = mybenchonset(datapath,respath,checkres=True,checkanno=True)
 	benchonset.params = taskparams()
 	benchonset.task = taskonset
Index: python/test/bench/onset/bench-window
===================================================================
--- python/test/bench/onset/bench-window	(revision 83c67348be306b34e1783ba44972675c9e33df30)
+++ python/test/bench/onset/bench-window	(revision 83c67348be306b34e1783ba44972675c9e33df30)
@@ -0,0 +1,63 @@
+#! /usr/bin/python
+
+from aubio.tasks import *
+
+from benchonset import mmean, stdev, plotdiffs, plotplotdiffs, benchonset
+
+class mybenchonset(benchonset):
+
+	def run_bench(self,modes=['dual'],thresholds=[0.5]):
+		from os.path import dirname,basename
+		self.thresholds = thresholds
+		self.pretty_titles()
+		for mode in modes:
+
+			self.params.onsetmode = mode
+			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")
+
+
+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]
+
+	#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
+	respath = '/var/tmp/DB-testings'
+
+	benchonset = mybenchonset(datapath,respath,checkres=True,checkanno=True)
+	benchonset.params = taskparams()
+	benchonset.task = taskonset
+	benchonset.valuesdict = {}
+
+	try:
+		#benchonset.auto_learn2(modes=modes)
+		benchonset.run_bench(modes=modes,thresholds=thresholds)
+	except KeyboardInterrupt:
+		sys.exit(1)
Index: python/test/bench/onset/benchonset.py
===================================================================
--- python/test/bench/onset/benchonset.py	(revision 83c67348be306b34e1783ba44972675c9e33df30)
+++ python/test/bench/onset/benchonset.py	(revision 83c67348be306b34e1783ba44972675c9e33df30)
@@ -0,0 +1,235 @@
+#! /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['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
+
+	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 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 [0:50]')
+		g.plot(*d)
+
+
