Index: python/aubio/bench/node.py
===================================================================
--- python/aubio/bench/node.py	(revision ea9817996f6ee0d056a82a28c44bd2f53242b869)
+++ python/aubio/bench/node.py	(revision 43938deb94e79f59bff176d423d100ed29f5a6c3)
@@ -90,5 +90,5 @@
 	""" 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
Index: python/aubio/bench/onset.py
===================================================================
--- python/aubio/bench/onset.py	(revision 43938deb94e79f59bff176d423d100ed29f5a6c3)
+++ python/aubio/bench/onset.py	(revision 43938deb94e79f59bff176d423d100ed29f5a6c3)
@@ -0,0 +1,302 @@
+#! /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)
+
+
