Index: python/aubio/gnuplot.py
===================================================================
--- python/aubio/gnuplot.py	(revision 300adc30c0d03d0c96f71358773e6520ba0eb8d7)
+++ python/aubio/gnuplot.py	(revision 1e3089c97d3e6f364e4bcea2f2c09c1963947e6a)
@@ -150,149 +150,4 @@
 	return Gnuplot.Data(x,y,with='lines')
 
-
-def plot_onsets(filename, onsets, ofunc, samplerate=44100., hopsize=512, outplot=None):
-	import Gnuplot, Gnuplot.funcutils
-        import aubio.txtfile
-        import os.path
-        import numarray
-	import re
-        from aubio.onsetcompare import onset_roc
-
-        d,d2 = [],[]
-        maxofunc = 0
-        for i in range(len(onsets)):
-                if len(onsets[i]) == 0: onsets[i] = [0.];
-
-                # onset detection function 
-                downtime = (hopsize/samplerate)*numarray.arange(len(ofunc[i]))
-                d.append(Gnuplot.Data(downtime,ofunc[i],with='lines'))
-                maxofunc = max(max(ofunc[i]), maxofunc)
-
-        for i in range(len(onsets)):
-                # detected onsets
-                x1 = (hopsize/samplerate)*numarray.array(onsets[i])
-                y1 = maxofunc*numarray.ones(len(onsets[i]))
-                d.append(Gnuplot.Data(x1,y1,with='impulses'))
-                d2.append(Gnuplot.Data(x1,-y1,with='impulses'))
-
-        # check if datafile exists truth
-        datafile = filename.replace('.wav','.txt')
-	if datafile == filename: datafile = ""
-        if not os.path.isfile(datafile):
-                title = "truth file not found"
-                t = Gnuplot.Data(0,0,with='impulses') 
-        else:
-                t_onsets = aubio.txtfile.read_datafile(datafile)
-                y2 = maxofunc*numarray.ones(len(t_onsets))
-                x2 = numarray.array(t_onsets).resize(len(t_onsets))
-                d2.append(Gnuplot.Data(x2,y2,with='impulses'))
-                
-                tol = 0.050 
-
-                orig, missed, merged, expc, bad, doubled = \
-                        onset_roc(x2,x1,tol)
-                title = "GD %2.3f%% FP %2.3f%%" % \
-                        ((100*float(orig-missed-merged)/(orig)),
-                         (100*float(bad+doubled)/(orig)))
-
-        # audio data
-        time,data = audio_to_array(filename)
-        d2.append(make_audio_plot(time,data))
-
-        # prepare the plot
-        g = gnuplot_init(outplot)
-
-        g('set title \'%s %s\'' % (re.sub('.*/','',filename),title))
-
-        g('set multiplot')
-
-        # hack to align left axis
-        g('set lmargin 15')
-
-        # plot waveform and onsets
-        g('set size 1,0.3')
-        g('set origin 0,0.7')
-        g('set xrange [0:%f]' % max(time)) 
-        g('set yrange [-1:1]') 
-        g.ylabel('amplitude')
-        g.plot(*d2)
-        
-        g('unset title')
-
-        # plot onset detection function
-        g('set size 1,0.7')
-        g('set origin 0,0')
-        g('set xrange [0:%f]' % (hopsize/samplerate*len(ofunc[0])))
-        g('set yrange [0:%f]' % (maxofunc*1.01))
-        g.xlabel('time')
-        g.ylabel('onset detection value')
-        g.plot(*d)
-
-        g('unset multiplot')
-
-
-def plot_pitch(filename, pitch, samplerate=44100., hopsize=512, outplot=None):
-        import aubio.txtfile
-        import os.path
-        import numarray
-	import Gnuplot
-	import re
-
-        d = []
-        maxpitch = 1000.
-        for i in range(len(pitch)):
-                #if len(pitch[i]) == 0: pitch[i] = [0.];
-
-                downtime = (hopsize/samplerate)*numarray.arange(len(pitch[i]))
-                d.append(Gnuplot.Data(downtime,pitch[i],with='lines',
-                        title=('%d' % i)))
-                maxpitch = max(maxpitch,max(pitch[i][:])*1.1)
-
-        # check if ground truth exists
-        datafile = filename.replace('.wav','.txt')
-	if datafile == filename: datafile = ""
-        if not os.path.isfile(datafile):
-                title = "truth file not found"
-                t = Gnuplot.Data(0,0,with='impulses') 
-        else:
-                title = "truth file plotting not implemented yet"
-                values = aubio.txtfile.read_datafile(datafile)
-		if (len(datafile[0])) > 1:
-                        time, pitch = [], []
-                        for i in range(len(values)):
-                                time.append(values[i][0])
-                                pitch.append(values[i][1])
-                        d.append(Gnuplot.Data(time,pitch,with='lines',
-				title='ground truth'))
-                
-        # audio data
-        time,data = audio_to_array(filename)
-        f = make_audio_plot(time,data)
-
-	g = gnuplot_init(outplot)
-        g('set title \'%s %s\'' % (re.sub('.*/','',filename),title))
-        g('set multiplot')
-        # hack to align left axis
-        g('set lmargin 15')
-        # plot waveform and onsets
-        g('set size 1,0.3')
-        g('set origin 0,0.7')
-        g('set xrange [0:%f]' % max(time)) 
-        g('set yrange [-1:1]') 
-        g.ylabel('amplitude')
-        g.plot(f)
-        g('unset title')
-        # plot onset detection function
-        g('set size 1,0.7')
-        g('set origin 0,0')
-        g('set xrange [0:%f]' % max(time))
-        g('set yrange [40:%f]' % maxpitch) 
-        g('set key right top')
-        g('set noclip one') 
-        g.xlabel('time')
-        g.ylabel('frequency (Hz)')
-        g.plot(*d)
-        g('unset multiplot')
-
 def gnuplot_init(outplot,debug=0,persist=1):
         # prepare the plot
Index: python/aubio/tasks.py
===================================================================
--- python/aubio/tasks.py	(revision 300adc30c0d03d0c96f71358773e6520ba0eb8d7)
+++ python/aubio/tasks.py	(revision 1e3089c97d3e6f364e4bcea2f2c09c1963947e6a)
@@ -71,127 +71,4 @@
                  print "error: unknown pitch detection output selected"
                  sys.exit(1)
-
-
-#def getonsets(filein,threshold=0.2,silence=-70.,bufsize=1024,hopsize=512,
-#                mode='dual',localmin=False,storefunc=False,derivate=False):
-#        frameread = 0
-#        filei     = sndfile(filein)
-#        channels  = filei.channels()
-#        myvec     = fvec(hopsize,channels)
-#        readsize  = filei.read(hopsize,myvec)
-#        opick     = onsetpick(bufsize,hopsize,channels,myvec,threshold,
-#                         mode=mode,derivate=derivate)
-#        mylist    = list()
-#        if localmin:
-#                ovalist   = [0., 0., 0., 0., 0.]
-#        ofunclist = []
-#        while(readsize):
-#                readsize = filei.read(hopsize,myvec)
-#                isonset,val = opick.do(myvec)
-#                if (aubio_silence_detection(myvec(),silence)):
-#                        isonset=0
-#                if localmin:
-#                        if val > 0: ovalist.append(val)
-#                        else: ovalist.append(0)
-#                        ovalist.pop(0)
-#                if storefunc:
-#                        ofunclist.append(val)
-#                if (isonset == 1):
-#                        if localmin:
-#                                i=len(ovalist)-1
-#                                # find local minima before peak 
-#                                while ovalist[i-1] < ovalist[i] and i > 0:
-#                                        i -= 1
-#                                now = (frameread+1-i)
-#                        else:
-#                                now = frameread
-#                        if now > 0 :
-#                                mylist.append(now)
-#                        else:
-#                                now = 0
-#                                mylist.append(now)
-#                frameread += 1
-#        return mylist, ofunclist
-#
-#def cutfile(filein,slicetimes,zerothres=0.008,bufsize=1024,hopsize=512):
-#    frameread = 0
-#    readsize  = hopsize 
-#    filei     = sndfile(filein)
-#    framestep = hopsize/(filei.samplerate()+0.)
-#    channels  = filei.channels()
-#    newname   = "%s%s%09.5f%s%s" % (filein.split(".")[0].split("/")[-1],".",
-#                frameread*framestep,".",filein.split(".")[-1])
-#    fileo     = sndfile(newname,model=filei)
-#    myvec     = fvec(hopsize,channels)
-#    mycopy    = fvec(hopsize,channels)
-#    while(readsize==hopsize):
-#        readsize = filei.read(hopsize,myvec)
-#        # write to current file
-#        if len(slicetimes) and frameread >= slicetimes[0]:
-#            slicetimes.pop(0)
-#            # write up to 1st zero crossing
-#            zerocross = 0
-#            while ( abs( myvec.get(zerocross,0) ) > zerothres ):
-#                zerocross += 1
-#            writesize = fileo.write(zerocross,myvec)
-#            fromcross = 0
-#            while (zerocross < readsize):
-#                for i in range(channels):
-#                    mycopy.set(myvec.get(zerocross,i),fromcross,i)
-#                    fromcross += 1
-#                    zerocross += 1
-#            del fileo
-#            fileo = sndfile("%s%s%09.5f%s%s" % 
-#                (filein.split(".")[0].split("/")[-1],".",
-#                frameread*framestep,".",filein.split(".")[-1]),model=filei)
-#            writesize = fileo.write(fromcross,mycopy)
-#        else:
-#            writesize = fileo.write(readsize,myvec)
-#        frameread += 1
-#    del fileo
-#
-#
-#def getsilences(filein,hopsize=512,silence=-70):
-#    frameread = 0
-#    filei     = sndfile(filein)
-#    srate     = filei.samplerate()
-#    channels  = filei.channels()
-#    myvec     = fvec(hopsize,channels)
-#    readsize  = filei.read(hopsize,myvec)
-#    mylist    = []
-#    wassilence = 0
-#    while(readsize==hopsize):
-#        readsize = filei.read(hopsize,myvec)
-#        if (aubio_silence_detection(myvec(),silence)==1):
-#            if wassilence == 0:
-#                mylist.append(frameread)
-#                wassilence == 1
-#        else: wassilence = 0
-#        frameread += 1
-#    return mylist
-#
-#
-#def getpitch(filein,mode=aubio_pitch_mcomb,bufsize=1024,hopsize=512,omode=aubio_pitchm_freq,
-#        samplerate=44100.,silence=-70):
-#    frameread = 0
-#    filei     = sndfile(filein)
-#    srate     = filei.samplerate()
-#    channels  = filei.channels()
-#    myvec     = fvec(hopsize,channels)
-#    readsize  = filei.read(hopsize,myvec)
-#    pitchdet  = pitchdetection(mode=mode,bufsize=bufsize,hopsize=hopsize,
-#                         channels=channels,samplerate=srate,omode=omode)
-#    mylist    = []
-#    while(readsize==hopsize):
-#        readsize = filei.read(hopsize,myvec)
-#        freq = pitchdet(myvec)
-#        #print "%.3f     %.2f" % (now,freq)
-#        if (aubio_silence_detection(myvec(),silence)!=1):
-#                mylist.append(freq)
-#        else: 
-#                mylist.append(-1.)
-#        frameread += 1
-#    return mylist
-
 
 class taskparams(object):
