added bench-window, bench-delay, benchonset added bench-window, bench-delay, benchonset

Paul Brossier committed 20 years ago

Commit 83c67341 parent 79c04d85 files · +425 −79Browse files

Showing the changes to python (5 of 5 files). Show all

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5 files

python/test/bench/onset/Makefile.am +27 −7
python/test/bench/onset/bench-delay +72 −0
python/test/bench/onset/bench-onset +28 −72
python/test/bench/onset/bench-window +63 −0
python/test/bench/onset/benchonset.py +235 −0

python/test/bench/onset/Makefile.am+27−7

@@ -2,22 +2,42 @@ export BASEDIR=../../../.. · 1 unmodified line
2	2	export PYTHONPATH=$(BASEDIR)/python
3	3	export LD_LIBRARY_PATH=$(BASEDIR)/src/.libs:$(BASEDIR)/ext/.libs
4	4
5		−SOURCE = \
6		− /archives/samples/DB/PercussivePhrases/CM18/Samba_Audio \
	5	+DETAILSOURCE = \
7	6	/var/tmp/Onset-Mirex2005/poly_pitched \
8	7	/var/tmp/Onset-Mirex2005/solo_bars_and_bells \
9		− /var/tmp/Onset-Mirex2005/solo_brass \
10	8	/var/tmp/Onset-Mirex2005/solo_drums \
11	9	/var/tmp/Onset-Mirex2005/solo_plucked_strings \
12	10	/var/tmp/Onset-Mirex2005/solo_singing_voice \
13	11	/var/tmp/Onset-Mirex2005/solo_sustained_strings \
14	12	/var/tmp/Onset-Mirex2005/solo_winds \
15		− /var/tmp/Onset-Mirex2005/complex \
16		− /var/tmp/Onset-Mirex2005
	13	+ /var/tmp/Onset-Mirex2005/complex
17	14
18		−test-aubiocut: $(patsubst %, %.aubiocut, $(SOURCE))
	15	+SOURCE = /var/tmp/Onset-Mirex2005
	16	+
	17	+TESTSOURCE = \
	18	+ /var/tmp/Onset-Mirex2005/solo_bars_and_bells \
	19	+ /var/tmp/Onset-Mirex2005/solo_winds \
	20	+ /archives/samples/DB/PercussivePhrases/CM18/Samba_Audio
	21	+
	22	+test-aubiocut: $(patsubst %, %.aubiocut, $(TESTSOURCE))
	23	+test-aubiodelay: $(patsubst %, %.aubiodelay, $(TESTSOURCE))
	24	+test-aubiowindow: $(patsubst %, %.aubiowindow, $(TESTSOURCE))
	25	+
	26	+final-aubiocut: $(patsubst %, %.aubiocut, $(DETAILSOURCE) $(SOURCE))
	27	+final-aubiodelay: $(patsubst %, %.aubiodelay, $(SOURCE))
	28	+final-aubiowindow: $(patsubst %, %.aubiowindow, $(SOURCE))
19	29
20	30	%.aubiocut: %
21	31	rm -f `basename $<`.aubiocut
22	32	./bench-onset $< \| tee `basename $<`.aubiocut
23		− diff `basename $<`.aubiocut.ref `basename $<`.aubiocut
	33	+ -diff `basename $<`.aubiocut.ref `basename $<`.aubiocut
	34	+
	35	+%.aubiodelay: %
	36	+ rm -f `basename $@`
	37	+ ./bench-delay $< \| tee `basename $@`
	38	+ -diff `basename $@`.ref `basename $@`
	39	+
	40	+%.aubiowindow: %
	41	+ rm -f `basename $@`
	42	+ ./bench-window $< \| tee `basename $@`
	43	+ -diff `basename $@`.ref `basename $@`

python/test/bench/onset/bench-delay+72−0

@@ -0,0 +1,72 @@
	1	+#! /usr/bin/python
	2	+
	3	+from aubio.bench.node import *
	4	+from aubio.tasks import *
	5	+
	6	+from benchonset import mmean, stdev, benchonset
	7	+
	8	+class mybenchonset(benchonset):
	9	+
	10	+ def run_bench(self,modes=['dual'],thresholds=[0.5]):
	11	+ from os.path import dirname,basename
	12	+ self.modes = modes
	13	+ self.thresholds = thresholds
	14	+ self.pretty_titles()
	15	+ for mode in self.modes:
	16	+ d = []
	17	+ outplot = "_-_".join(("delay",mode,
	18	+ basename(self.datadir) ))
	19	+
	20	+ self.params.onsetmode = mode
	21	+ self.params.threshold = thresholds[0]
	22	+
	23	+ self.params.localmin = False
	24	+ self.params.delay = 0.
	25	+
	26	+ self.dir_exec()
	27	+ self.dir_eval()
	28	+ self.pretty_print()
	29	+ self.plotdiffs(d,plottitle="Causal")
	30	+
	31	+ self.params.localmin = True
	32	+ self.params.delay = 0.
	33	+ self.dir_exec()
	34	+ self.dir_eval()
	35	+ self.pretty_print()
	36	+ self.plotdiffs(d,plottitle="Local min")
	37	+
	38	+ self.params.localmin = False
	39	+ self.params.delay = 6.
	40	+ self.dir_exec()
	41	+ self.dir_eval()
	42	+ self.pretty_print()
	43	+ self.plotdiffs(d,plottitle="Fixed delay")
	44	+
	45	+ self.plotplotdiffs(d)
	46	+ self.plotplotdiffs(d,outplot=outplot,extension="png")
	47	+ self.plotplotdiffs(d,outplot=outplot,extension="ps")
	48	+ self.plotplotdiffs(d,outplot=outplot,extension="svg")
	49	+
	50	+
	51	+if __name__ == "__main__":
	52	+ import sys
	53	+ if len(sys.argv) > 1: datapath = sys.argv[1]
	54	+ else: print "ERR: a path is required"; sys.exit(1)
	55	+ modes = ['complex', 'energy', 'phase', 'specdiff', 'kl', 'mkl', 'dual']
	56	+ #modes = [ 'complex' ]
	57	+ thresholds = [ 0.5]
	58	+ #thresholds = [1.5]
	59	+
	60	+ #datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
	61	+ respath = '/var/tmp/DB-testings'
	62	+
	63	+ benchonset = mybenchonset(datapath,respath,checkres=True,checkanno=True)
	64	+ benchonset.params = taskparams()
	65	+ benchonset.task = taskonset
	66	+ benchonset.valuesdict = {}
	67	+
	68	+ try:
	69	+ #benchonset.auto_learn2(modes=modes)
	70	+ benchonset.run_bench(modes=modes,thresholds=thresholds)
	71	+ except KeyboardInterrupt:
	72	+ sys.exit(1)

python/test/bench/onset/bench-onset+28−72

@@ -1,80 +1,18 @@
1	1	#! /usr/bin/python
2	2
3		−from aubio.bench.node import *
4	3	from aubio.tasks import *
5	4
	5	+from benchonset import mmean, stdev, benchonset
6	6
7		−
8		−
9		−def mmean(l):
10		− return sum(l)/float(len(l))
11		−
12		−def stdev(l):
13		− smean = 0
14		− lmean = mmean(l)
15		− for i in l:
16		− smean += (i-lmean)**2
17		− smean *= 1. / len(l)
18		− return smean**.5
19		−
20		−class benchonset(bench):
21		−
22		− """ list of values to store per file """
23		− valuenames = ['orig','missed','Tm','expc','bad','Td']
24		− """ list of lists to store per file """
25		− valuelists = ['l','labs']
26		− """ list of values to print per dir """
27		− printnames = [ 'mode', 'thres', 'dist', 'prec', 'recl',
28		− 'Ttrue', 'Tfp', 'Tfn', 'Tm', 'Td',
29		− 'aTtrue', 'aTfp', 'aTfn', 'aTm', 'aTd',
30		− 'mean', 'smean', 'amean', 'samean']
31		−
32		− """ per dir """
33		− formats = {'mode': "%12s" , 'thres': "%5.4s",
34		− 'dist': "%5.4s", 'prec': "%5.4s", 'recl': "%5.4s",
35		− 'Ttrue': "%5.4s", 'Tfp': "%5.4s", 'Tfn': "%5.4s",
36		− 'Tm': "%5.4s", 'Td': "%5.4s",
37		− 'aTtrue':"%5.4s", 'aTfp': "%5.4s", 'aTfn': "%5.4s",
38		− 'aTm': "%5.4s", 'aTd': "%5.4s",
39		− 'mean': "%5.40s", 'smean': "%5.40s",
40		− 'amean': "%5.40s", 'samean': "%5.40s"}
41		−
42		− def dir_eval(self):
43		− """ evaluate statistical data over the directory """
44		− totaltrue = sum(self.v['expc'])-sum(self.v['bad'])-sum(self.v['Td'])
45		− totalfp = sum(self.v['bad'])+sum(self.v['Td'])
46		− totalfn = sum(self.v['missed'])+sum(self.v['Tm'])
47		− self.P = 100*float(totaltrue)/max(totaltrue + totalfp,1)
48		− self.R = 100*float(totaltrue)/max(totaltrue + totalfn,1)
49		− if self.R < 0: self.R = 0
50		− self.F = 2.* self.P*self.R / max(float(self.P+self.R),1)
51		− N = float(len(self.reslist))
52		− self.v['mode'] = self.params.onsetmode
53		− self.v['thres'] = self.params.threshold
54		− self.v['thres'] = "%2.3f" % self.params.threshold
55		− self.v['dist'] = "%2.3f" % self.F
56		− self.v['prec'] = "%2.3f" % self.P
57		− self.v['recl'] = "%2.3f" % self.R
58		− self.v['Ttrue'] = totaltrue
59		− self.v['Tfp'] = totalfp
60		− self.v['Tfn'] = totalfn
61		− self.v['aTtrue'] = totaltrue/N
62		− self.v['aTfp'] = totalfp/N
63		− self.v['aTfn'] = totalfn/N
64		− self.v['aTm'] = sum(self.v['Tm'])/N
65		− self.v['aTd'] = sum(self.v['Td'])/N
66		− self.v['Tm'] = sum(self.v['Tm'])
67		− self.v['Td'] = sum(self.v['Td'])
68		− self.v['mean'] = mmean(self.v['l'])
69		− self.v['smean'] = stdev(self.v['l'])
70		− self.v['amean'] = mmean(self.v['labs'])
71		− self.v['samean'] = stdev(self.v['labs'])
	7	+class mybenchonset(benchonset):
72	8
73	9	def run_bench(self,modes=['dual'],thresholds=[0.5]):
74		− self.modes = modes
	10	+ from os.path import dirname,basename
75	11	self.thresholds = thresholds
76	12	self.pretty_titles()
77		− for mode in self.modes:
	13	+ d,e,f = [],[],[]
	14	+ for mode in modes:
	15	+ self.vlist = []
78	16	self.params.onsetmode = mode
79	17	for threshold in self.thresholds:
80	18	self.params.threshold = threshold
@@ -82,6 +20,20 @@ class benchonset(bench): · 1 unmodified line
82	20	self.dir_eval()
83	21	self.pretty_print()
84	22	#print self.v
	23	+ self.vlist.append(self.v)
	24	+ self.plotroc(d)
	25	+ self.plotfmeas(e)
	26	+ self.plotpr(f)
	27	+ #print vlist
	28	+ #self.plotplotroc(d)
	29	+ #self.plotplotfmeas(e)
	30	+ #self.plotplotpr(f)
	31	+ outplot = basename(self.datadir)
	32	+ for ext in ("png","svg","ps"):
	33	+ self.plotplotroc(d,outplot=outplot,extension=ext)
	34	+ self.plotplotfmeas(e,outplot=outplot,extension=ext)
	35	+ self.plotplotpr(f,outplot=outplot,extension=ext)
	36	+
85	37
86	38	def auto_learn(self,modes=['dual'],thresholds=[0.1,1.5]):
87	39	""" simple dichotomia like algorithm to optimise threshold """
@@ -106,6 +58,10 @@ class benchonset(bench): · 18 unmodified lines
106	58	lessF = self.F
107	59
108	60	for i in range(steps):
	61	+ self.params.localmin = True
	62	+ self.params.delay = 1.
	63	+ self.dir_exec()
	64	+ self.dir_eval()
109	65	self.params.threshold = ( lesst + topt ) * .5
110	66	self.dir_exec()
111	67	self.dir_eval()
@@ -169,15 +125,15 @@ if __name__ == "__main__": · 57 unmodified lines
169	125	import sys
170	126	if len(sys.argv) > 1: datapath = sys.argv[1]
171	127	else: print "ERR: a path is required"; sys.exit(1)
172		− modes = ['complex', 'energy', 'phase', 'specdiff', 'kl', 'mkl', 'dual']
173		− #modes = [ 'mkl' ]
	128	+ modes = ['complex', 'energy', 'phase', 'hfc', 'specdiff', 'kl', 'mkl', 'dual']
174	129	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]
175		− #thresholds = [1.5]
	130	+ #modes = [ 'hfc' ]
	131	+ #thresholds = [0.1, 1.5]
176	132
177	133	#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
178	134	respath = '/var/tmp/DB-testings'
179	135
180		− benchonset = benchonset(datapath,respath,checkres=True,checkanno=True)
	136	+ benchonset = mybenchonset(datapath,respath,checkres=True,checkanno=True)
181	137	benchonset.params = taskparams()
182	138	benchonset.task = taskonset
183	139	benchonset.valuesdict = {}

python/test/bench/onset/bench-window+63−0

@@ -0,0 +1,63 @@
	1	+#! /usr/bin/python
	2	+
	3	+from aubio.tasks import *
	4	+
	5	+from benchonset import mmean, stdev, plotdiffs, plotplotdiffs, benchonset
	6	+
	7	+class mybenchonset(benchonset):
	8	+
	9	+ def run_bench(self,modes=['dual'],thresholds=[0.5]):
	10	+ from os.path import dirname,basename
	11	+ self.thresholds = thresholds
	12	+ self.pretty_titles()
	13	+ for mode in modes:
	14	+
	15	+ self.params.onsetmode = mode
	16	+ self.params.threshold = thresholds[0]
	17	+ self.params.localmin = False
	18	+
	19	+ for delay in (0., 4.):
	20	+ d = []
	21	+ outplot = "_-_".join(("window",mode,"delay-%s" % delay,
	22	+ basename(self.datadir) ))
	23	+ self.params.delay = delay
	24	+
	25	+ for buf in (2048, 1024, 512):
	26	+ for hop in (buf/2, buf/4):
	27	+ self.params.bufsize = buf
	28	+ self.params.hopsize = hop
	29	+ self.params.step = float(self.params.hopsize)/float(self.params.samplerate)
	30	+
	31	+ self.dir_exec()
	32	+ self.dir_eval()
	33	+ self.pretty_print()
	34	+ plotdiffs(self.v,d,plottitle="%s %s" % (buf,hop))
	35	+
	36	+ plotplotdiffs(d)
	37	+ plotplotdiffs(d,outplot=outplot,extension="png")
	38	+ plotplotdiffs(d,outplot=outplot,extension="ps")
	39	+ plotplotdiffs(d,outplot=outplot,extension="svg")
	40	+
	41	+
	42	+if __name__ == "__main__":
	43	+ import sys
	44	+ if len(sys.argv) > 1: datapath = sys.argv[1]
	45	+ else: print "ERR: a path is required"; sys.exit(1)
	46	+ modes = ['complex', 'energy', 'phase', 'specdiff', 'kl', 'mkl', 'dual']
	47	+ #modes = [ 'complex' ]
	48	+ thresholds = [ 0.5]
	49	+ #thresholds = [1.5]
	50	+
	51	+ #datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
	52	+ respath = '/var/tmp/DB-testings'
	53	+
	54	+ benchonset = mybenchonset(datapath,respath,checkres=True,checkanno=True)
	55	+ benchonset.params = taskparams()
	56	+ benchonset.task = taskonset
	57	+ benchonset.valuesdict = {}
	58	+
	59	+ try:
	60	+ #benchonset.auto_learn2(modes=modes)
	61	+ benchonset.run_bench(modes=modes,thresholds=thresholds)
	62	+ except KeyboardInterrupt:
	63	+ sys.exit(1)

python/test/bench/onset/benchonset.py+235−0

@@ -0,0 +1,235 @@
	1	+#! /usr/bin/python
	2	+
	3	+from aubio.bench.node import *
	4	+from os.path import dirname,basename
	5	+
	6	+def mmean(l):
	7	+ return sum(l)/max(float(len(l)),1)
	8	+
	9	+def stdev(l):
	10	+ smean = 0
	11	+ if not len(l): return smean
	12	+ lmean = mmean(l)
	13	+ for i in l:
	14	+ smean += (i-lmean)**2
	15	+ smean *= 1. / len(l)
	16	+ return smean**.5
	17	+
	18	+class benchonset(bench):
	19	+
	20	+ """ list of values to store per file """
	21	+ valuenames = ['orig','missed','Tm','expc','bad','Td']
	22	+ """ list of lists to store per file """
	23	+ valuelists = ['l','labs']
	24	+ """ list of values to print per dir """
	25	+ printnames = [ 'mode', 'thres', 'dist', 'prec', 'recl',
	26	+ 'GD', 'FP',
	27	+ 'Torig', 'Ttrue', 'Tfp', 'Tfn', 'TTm', 'TTd',
	28	+ 'aTtrue', 'aTfp', 'aTfn', 'aTm', 'aTd',
	29	+ 'mean', 'smean', 'amean', 'samean']
	30	+
	31	+ """ per dir """
	32	+ formats = {'mode': "%12s" , 'thres': "%5.4s",
	33	+ 'dist': "%5.4s", 'prec': "%5.4s", 'recl': "%5.4s",
	34	+ 'Torig': "%5.4s", 'Ttrue': "%5.4s", 'Tfp': "%5.4s", 'Tfn': "%5.4s",
	35	+ 'TTm': "%5.4s", 'TTd': "%5.4s",
	36	+ 'aTtrue':"%5.4s", 'aTfp': "%5.4s", 'aTfn': "%5.4s",
	37	+ 'aTm': "%5.4s", 'aTd': "%5.4s",
	38	+ 'mean': "%5.40s", 'smean': "%5.40s",
	39	+ 'amean': "%5.40s", 'samean': "%5.40s",
	40	+ "GD": "%5.4s", "FP": "%5.4s",
	41	+ "GDm": "%5.4s", "FPd": "%5.4s"}
	42	+
	43	+ def dir_eval(self):
	44	+ """ evaluate statistical data over the directory """
	45	+ v = self.v
	46	+
	47	+ v['mode'] = self.params.onsetmode
	48	+ v['thres'] = self.params.threshold
	49	+
	50	+ v['Torig'] = sum(v['orig'])
	51	+ v['TTm'] = sum(v['Tm'])
	52	+ v['TTd'] = sum(v['Td'])
	53	+ v['Texpc'] = sum(v['expc'])
	54	+ v['Tbad'] = sum(v['bad'])
	55	+ v['Tmissed'] = sum(v['missed'])
	56	+ v['aTm'] = mmean(v['Tm'])
	57	+ v['aTd'] = mmean(v['Td'])
	58	+
	59	+ v['mean'] = mmean(v['l'])
	60	+ v['smean'] = stdev(v['l'])
	61	+
	62	+ v['amean'] = mmean(v['labs'])
	63	+ v['samean'] = stdev(v['labs'])
	64	+
	65	+ # old type calculations
	66	+ # good detection rate
	67	+ v['GD'] = 100.*(v['Torig']-v['Tmissed']-v['TTm'])/v['Torig']
	68	+ # false positive rate
	69	+ v['FP'] = 100.*(v['Tbad']+v['TTd'])/v['Torig']
	70	+ # good detection counting merged detections as good
	71	+ v['GDm'] = 100.*(v['Torig']-v['Tmissed'])/v['Torig']
	72	+ # false positives counting doubled as good
	73	+ v['FPd'] = 100.*v['Tbad']/v['Torig']
	74	+
	75	+ # mirex type annotations
	76	+ totaltrue = v['Texpc']-v['Tbad']-v['TTd']
	77	+ totalfp = v['Tbad']+v['TTd']
	78	+ totalfn = v['Tmissed']+v['TTm']
	79	+ self.v['Ttrue'] = totaltrue
	80	+ self.v['Tfp'] = totalfp
	81	+ self.v['Tfn'] = totalfn
	82	+ # average over the number of annotation files
	83	+ N = float(len(self.reslist))
	84	+ self.v['aTtrue'] = totaltrue/N
	85	+ self.v['aTfp'] = totalfp/N
	86	+ self.v['aTfn'] = totalfn/N
	87	+
	88	+ # F-measure
	89	+ self.P = 100.*float(totaltrue)/max(totaltrue + totalfp,1)
	90	+ self.R = 100.*float(totaltrue)/max(totaltrue + totalfn,1)
	91	+ #if self.R < 0: self.R = 0
	92	+ self.F = 2.* self.P*self.R / max(float(self.P+self.R),1)
	93	+ self.v['dist'] = self.F
	94	+ self.v['prec'] = self.P
	95	+ self.v['recl'] = self.R
	96	+
	97	+ def plotroc(self,d,plottitle=""):
	98	+ import Gnuplot, Gnuplot.funcutils
	99	+ gd = []
	100	+ fp = []
	101	+ for i in self.vlist:
	102	+ gd.append(i['GD'])
	103	+ fp.append(i['FP'])
	104	+ d.append(Gnuplot.Data(fp, gd, with='linespoints',
	105	+ title="%s %s" % (plottitle,i['mode']) ))
	106	+
	107	+ def plotplotroc(self,d,outplot=0,extension='ps'):
	108	+ import Gnuplot, Gnuplot.funcutils
	109	+ from sys import exit
	110	+ g = Gnuplot.Gnuplot(debug=0, persist=1)
	111	+ if outplot:
	112	+ if extension == 'ps': ext, extension = '.ps' , 'postscript'
	113	+ elif extension == 'png': ext, extension = '.png', 'png'
	114	+ elif extension == 'svg': ext, extension = '.svg', 'svg'
	115	+ else: exit("ERR: unknown plot extension")
	116	+ g('set terminal %s' % extension)
	117	+ g('set output \'roc-%s%s\'' % (outplot,ext))
	118	+ xmax = 30 #max(fp)
	119	+ ymin = 50
	120	+ g('set xrange [0:%f]' % xmax)
	121	+ g('set yrange [%f:100]' % ymin)
	122	+ # grid set
	123	+ g('set grid')
	124	+ g('set xtics 0,5,%f' % xmax)
	125	+ g('set ytics %f,5,100' % ymin)
	126	+ g('set key 27,65')
	127	+ #g('set format \"%g\"')
	128	+ g.title(basename(self.datadir))
	129	+ g.xlabel('false positives (%)')
	130	+ g.ylabel('correct detections (%)')
	131	+ g.plot(*d)
	132	+
	133	+ def plotpr(self,d,plottitle=""):
	134	+ import Gnuplot, Gnuplot.funcutils
	135	+ x = []
	136	+ y = []
	137	+ for i in self.vlist:
	138	+ x.append(i['prec'])
	139	+ y.append(i['recl'])
	140	+ d.append(Gnuplot.Data(x, y, with='linespoints',
	141	+ title="%s %s" % (plottitle,i['mode']) ))
	142	+
	143	+ def plotplotpr(self,d,outplot=0,extension='ps'):
	144	+ import Gnuplot, Gnuplot.funcutils
	145	+ from sys import exit
	146	+ g = Gnuplot.Gnuplot(debug=0, persist=1)
	147	+ if outplot:
	148	+ if extension == 'ps': ext, extension = '.ps' , 'postscript'
	149	+ elif extension == 'png': ext, extension = '.png', 'png'
	150	+ elif extension == 'svg': ext, extension = '.svg', 'svg'
	151	+ else: exit("ERR: unknown plot extension")
	152	+ g('set terminal %s' % extension)
	153	+ g('set output \'pr-%s%s\'' % (outplot,ext))
	154	+ g.title(basename(self.datadir))
	155	+ g.xlabel('Recall (%)')
	156	+ g.ylabel('Precision (%)')
	157	+ g.plot(*d)
	158	+
	159	+ def plotfmeas(self,d,plottitle=""):
	160	+ import Gnuplot, Gnuplot.funcutils
	161	+ x,y = [],[]
	162	+ for i in self.vlist:
	163	+ x.append(i['thres'])
	164	+ y.append(i['dist'])
	165	+ d.append(Gnuplot.Data(x, y, with='linespoints',
	166	+ title="%s %s" % (plottitle,i['mode']) ))
	167	+
	168	+ def plotplotfmeas(self,d,outplot="",extension='ps', title="F-measure"):
	169	+ import Gnuplot, Gnuplot.funcutils
	170	+ from sys import exit
	171	+ g = Gnuplot.Gnuplot(debug=0, persist=1)
	172	+ if outplot:
	173	+ if extension == 'ps': terminal = 'postscript'
	174	+ elif extension == 'png': terminal = 'png'
	175	+ elif extension == 'svg': terminal = 'svg'
	176	+ else: exit("ERR: unknown plot extension")
	177	+ g('set terminal %s' % terminal)
	178	+ g('set output \'fmeas-%s.%s\'' % (outplot,extension))
	179	+ g.xlabel('threshold \\delta')
	180	+ g.ylabel('F-measure (%)')
	181	+ g('set xrange [0:1.2]')
	182	+ g('set yrange [0:100]')
	183	+ g.title(basename(self.datadir))
	184	+ # grid set
	185	+ #g('set grid')
	186	+ #g('set xtics 0,5,%f' % xmax)
	187	+ #g('set ytics %f,5,100' % ymin)
	188	+ #g('set key 27,65')
	189	+ #g('set format \"%g\"')
	190	+ g.plot(*d)
	191	+
	192	+ def plotdiffs(self,d,plottitle=""):
	193	+ import Gnuplot, Gnuplot.funcutils
	194	+ v = self.v
	195	+ l = v['l']
	196	+ mean = v['mean']
	197	+ smean = v['smean']
	198	+ amean = v['amean']
	199	+ samean = v['samean']
	200	+ val = []
	201	+ per = [0] * 100
	202	+ for i in range(0,100):
	203	+ val.append(i*.001-.05)
	204	+ for j in l:
	205	+ if abs(j-val[i]) <= 0.001:
	206	+ per[i] += 1
	207	+ total = v['Torig']
	208	+ for i in range(len(per)): per[i] /= total/100.
	209	+
	210	+ d.append(Gnuplot.Data(val, per, with='fsteps',
	211	+ title="%s %s" % (plottitle,v['mode']) ))
	212	+ #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (mean,smean))
	213	+ #d.append('mean=%f,sigma=%f,eps(x) title \"\"'% (amean,samean))
	214	+
	215	+
	216	+ def plotplotdiffs(self,d,outplot=0,extension='ps'):
	217	+ import Gnuplot, Gnuplot.funcutils
	218	+ from sys import exit
	219	+ g = Gnuplot.Gnuplot(debug=0, persist=1)
	220	+ if outplot:
	221	+ if extension == 'ps': ext, extension = '.ps' , 'postscript'
	222	+ elif extension == 'png': ext, extension = '.png', 'png'
	223	+ elif extension == 'svg': ext, extension = '.svg', 'svg'
	224	+ else: exit("ERR: unknown plot extension")
	225	+ g('set terminal %s' % extension)
	226	+ g('set output \'diffhist-%s%s\'' % (outplot,ext))
	227	+ g('eps(x) = 1./(sigma(2.3.14159)*.5) exp ( - ( x - mean ) ** 2. / ( 2. * sigma ** 2. ))')
	228	+ g.title(basename(self.datadir))
	229	+ g.xlabel('delay to hand-labelled onset (s)')
	230	+ g.ylabel('% number of correct detections / ms ')
	231	+ g('set xrange [-0.05:0.05]')
	232	+ g('set yrange [0:50]')
	233	+ g.plot(*d)
	234	+
	235	+

added bench-window, bench-delay, benchonset added bench-window, bench-delay, benchonset

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