--- /dev/null
+#! /usr/bin/python
+
+""" this file was written by Paul Brossier
+ it is released under the GNU/GPL license.
+"""
+
+import sys,time
+from aubio.task import taskbeat,taskparams
+from aubio.aubioclass import fvec, aubio_autocorr
+from aubio.gnuplot import gnuplot_create, gnuplot_addargs
+from aubio.aubiowrapper import *
+from math import exp,log
+
+usage = "usage: %s [options] -i soundfile" % sys.argv[0]
+
+def parse_args():
+ from optparse import OptionParser
+ parser = OptionParser(usage=usage)
+ parser.add_option("-i","--input",
+ action="store", dest="filename",
+ help="input sound file")
+ parser.add_option("-n","--printframe",
+ action="store", dest="printframe", default=-1,
+ help="make a plot of the n_th frame")
+ gnuplot_addargs(parser)
+ (options, args) = parser.parse_args()
+ if not options.filename:
+ print "no file name given\n", usage
+ sys.exit(1)
+ return options, args
+
+def plotdata(x,y,plottitle="",**keyw):
+ import Gnuplot
+ return Gnuplot.Data(x, y, title="%s" % plottitle,**keyw)
+
+options, args = parse_args()
+filename = options.filename
+xsize = float(options.xsize)
+ysize = float(options.ysize)
+
+printframe = int(options.printframe)
+
+if options.outplot and printframe > 0:
+ extension = options.outplot.split('.')[-1]
+ outplot = '.'.join(options.outplot.split('.')[:-1])
+else:
+ extension = ''
+ outplot = None
+f = gnuplot_create(outplot=outplot,extension=extension,options=options)
+
+params = taskparams()
+params.onsetmode = 'specdiff'
+task = taskbeat(filename,params=params)
+
+hopsize = params.hopsize
+bufsize = params.bufsize
+btstep = task.btstep
+winlen = task.btwinlen
+laglen = winlen/4
+step = winlen/4
+
+timesig = 0
+maxnumelem = 4
+gp = 0
+counter = 0
+flagconst = 0
+constthresh = 3.901
+g_var = 3.901
+rp = 0
+rp1 = 0
+rp2 = 0
+g_mu = 0
+
+rayparam = 48/512.*winlen
+
+#t = [i for i in range(hopsize)]
+#tlong = [i for i in range(hopsize*(btstep-1))]
+#tall = [i for i in range(hopsize*btstep)]
+#a = [0 for i in range(hopsize*btstep)]
+dfx = [i for i in range(winlen)]
+dfframe = [0 for i in range(winlen)]
+dfrev = [0 for i in range(winlen)]
+acframe = [0 for i in range(winlen)]
+
+localacf = [0 for i in range(winlen)]
+inds = [0 for i in range(maxnumelem)]
+
+acx = [i for i in range(laglen)]
+acfout = [0 for i in range(laglen)]
+
+phwv = [0 for i in range(2*laglen)]
+phwvx = [i for i in range(2*laglen)]
+
+dfwvnorm = exp(log(2.0)*(winlen+2.)/rayparam);
+dfwv = [exp(log(2.)*(i+1.)/rayparam)/dfwvnorm for i in range(winlen)]
+
+gwv = [exp(-.5*(j+1.-g_mu)**2/g_var**2) for j in range(laglen)]
+rwv = [(i+1.)/rayparam**2 * exp(-(i+1.)**2 / (2.*rayparam)**2)
+ for i in range(0,laglen)]
+acf = fvec(winlen,1)
+
+nrframe = 0
+while (task.readsize == params.hopsize):
+ task()
+ #print task.pos2
+ #a[:-hopsize] = [i for i in a[-(btstep-1)*hopsize:]]
+ #a[-hopsize:] = [task.myvec.get(i,0) for i in t]
+
+ #g('set xrange [%f:%f]' % (t[0],t[-1]))
+ #time.sleep(.2)
+ if task.pos2==btstep-1:
+ nrframe += 1
+ dfframe = [task.dfframe.get(i,0) for i in range(winlen)]
+ if printframe == nrframe or printframe == -1:
+ d = [[plotdata(range(-winlen,0),dfframe,plottitle="onset detection", with='lines')]]
+ # start beattracking_do
+ for i in range(winlen):
+ dfrev[winlen-1-i] = 0.
+ dfrev[winlen-1-i] = dfframe[i]*dfwv[i]
+ aubio_autocorr(task.dfframe(),acf());
+ acframe = [acf.get(i,0) for i in range(winlen)]
+ if not timesig:
+ numelem = 4
+ else:
+ numelem = timesig
+
+ old = 0
+ acfout = [0 for i in range(winlen/4)]
+ for i in range(1,laglen-1):
+ for a in range(1,numelem+1):
+ for b in range (1-a,a):
+ acfout[i] += acframe[a*(i+1)+b-1] * 1./(2.*a-1.)*rwv[i]
+ if old < acfout[i]:
+ old = acfout[i]
+ maxi = i
+ rp = max(maxi,1);
+
+ if printframe == nrframe or printframe == -1:
+ rwvs = [rwv[i]*max(acframe) for i in range(len(rwv))]
+ d += [[plotdata(acx,acfout,plottitle="comb filterbank", with='lines', axes='x1y1'),
+ plotdata([rp,rp],[1.2*old,min(acfout)],plottitle="period", with='impulses', axes='x1y1'),
+ plotdata(acx,rwvs,plottitle="L_w", with='lines', axes='x1y1')]]
+
+ # getperiod
+ inds = [0 for i in range(maxnumelem)]
+ localacf = [0 for i in range(winlen)]
+ period = 0
+ for a in range(1,4+1):
+ for b in range(1-a,a):
+ localacf[a*rp+b-1] = acframe[a*rp+b-1]
+ for i in range(numelem):
+ maxindex = 0
+ maxval = 0.0
+ for j in range(rp*(i+1)+i):
+ if localacf[j] > maxval:
+ maxval = localacf[j]
+ maxind = j
+ localacf[j] = 0
+ inds[i] = maxind
+ for i in range(numelem):
+ period += inds[i]/(i+1.)
+ period = period/numelem
+ #print "period", period
+
+ # checkstate
+ if gp:
+ # context dependant model
+ acfout = [0 for i in range(winlen/4)]
+ old = 0
+ for i in range(laglen-1):
+ for a in range(timesig):
+ for b in range(1-a,a):
+ acfout[i] += acframe[a*(i+1)+b-1] * gwv[i]
+ if old < acfout[i]:
+ old = acfout[i]
+ maxi = i
+ gp = maxi
+ else:
+ # general model
+ gp = 0
+ #print "gp", gp
+ if printframe == nrframe or printframe == -1:
+ gwvs = [gwv[i]*max(acfout) for i in range(len(gwv))]
+ d += [[plotdata(acx,acfout,plottitle="comb filterbank", with='lines', axes='x1y1'),
+ plotdata(gp,old,plottitle="period", with='impulses', axes='x1y1'),
+ plotdata(acx,gwvs,plottitle="L_{gw}", with='lines', axes='x1y1')]]
+
+ if counter == 0:
+ # initial step
+ if abs(gp-rp) > 2.*constthresh:
+ flagstep = 1
+ counter = 3
+ else:
+ flagstep = 0
+ #print "flagstep", flagstep
+ #print "rp2,rp1,rp", rp2,rp1,rp
+ acfw = [dfframe[i]*dfwv[i] for i in range(winlen)]
+
+ if counter == 1 and flagstep == 1:
+ # "3rd frame after flagstep set"
+ if abs(2.*rp-rp1- rp2) < constthresh:
+ flagconst = 1
+ counter = 0
+ else:
+ flagconst = 0
+ counter = 2
+ elif counter > 0:
+ counter -= 1
+
+ rp2 = rp1; rp1 = rp
+
+ if flagconst:
+ # "first run of new hypothesis"
+ gp = rp
+ g_mu = gp
+ timesig = 4 #FIXME
+ gwv = [exp(-.5*(j+1.-g_mu)**2/g_var**2) for j in range(laglen)]
+ flagconst = 0
+ bp = gp
+ phwv = [1 for i in range(2*laglen)]
+ elif timesig:
+ # "contex dependant"
+ bp = gp
+ if step > lastbeat:
+ phwv = [exp(-.5*(1.+j-step+lastbeat)**2/(bp/8.)) for j in range(2*laglen)]
+ else:
+ print "NOT using phase weighting"
+ phwv = [1 for i in range(2*laglen)]
+ else:
+ # "initial state"
+ bp = rp
+ phwv = [1 for i in range(2*laglen)]
+
+ while bp < 25:
+ print "WARNING, doubling the beat period"
+ bp *= 2
+
+ #
+ phout = [0. for i in range(winlen)]
+
+ kmax = int(winlen/float(bp));
+
+ old = 0
+ for i in range(bp):
+ phout[i] = 0.
+ for k in range(kmax):
+ phout[i] += dfrev[i+bp*k] * phwv[i]
+ if phout[i] > old:
+ old = phout[i]
+ maxi = i
+ maxindex = maxi
+ if (maxindex == winlen - 1): maxindex = 0
+ phase = 1 + maxindex
+ i = 1
+ beat = bp - phase
+ beats= []
+ if beat >= 0: beats.append(beat)
+ while beat+bp < step:
+ beat += bp
+ beats.append(beat)
+ lastbeat = beat
+ #print beats,
+ #print "the lastbeat is", lastbeat
+
+ # plot all this
+ if printframe == nrframe or printframe == -1:
+ phwvs = [phwv[i]*max(phout) for i in range(len(phwv))]
+ d += [[plotdata(range(-laglen,0),phwvs[laglen:0:-1],plottitle="A_{gw}", with='lines',axes='x1y1'),
+ plotdata(range(-laglen,0),phout[laglen:0:-1],plottitle="df", with='lines'),
+ plotdata(-phase,old,plottitle="phase", with='impulses', axes='x1y1'),
+ plotdata([i for i in beats],[old for i in beats],plottitle="predicted", with='impulses')
+ ]]
+ #d += [[plotdata(dfx,dfwv,plottitle="phase weighting", with='lines', axes='x1y2'),
+ # plotdata(dfx,dfrev,plottitle="df reverse", with='lines', axes='x1y1')]]
+ #d += [[plotdata(dfx,phout,plottitle="phase", with='lines', axes='x1y2')]]
+ #d += [[plotdata(dfx,dfwv,plottitle="phase weighting", with='lines', axes='x1y2'),
+ # plotdata(dfx,dfrev,plottitle="df reverse", with='lines', axes='x1y1')]]
+ #d += [[plotdata(dfx,phout,plottitle="phase", with='lines', axes='x1y2')]]
+
+ f('set lmargin 4')
+ f('set rmargin 4')
+ f('set size %f,%f' % (1.0*xsize,1.0*ysize) )
+ f('set key spacing 1.3')
+ f('set multiplot')
+
+ f('set size %f,%f' % (1.0*xsize,0.33*ysize) )
+ f('set orig %f,%f' % (0.0*xsize,0.66*ysize) )
+ f('set xrange [%f:%f]' % (-winlen,0) )
+ f.title('Onset detection function')
+ f.xlabel('time (df samples)')
+ f.plot(*d[0])
+ f('set size %f,%f' % (0.5*xsize,0.33*ysize) )
+ f('set orig %f,%f' % (0.0*xsize,0.33*ysize) )
+ f('set xrange [%f:%f]' % (0,laglen) )
+ f.title('Period detection: Rayleygh weighting')
+ f.xlabel('lag (df samples)')
+ f.plot(*d[1])
+ f('set size %f,%f' % (0.5*xsize,0.33*ysize) )
+ f('set orig %f,%f' % (0.5*xsize,0.33*ysize) )
+ f('set xrange [%f:%f]' % (0,laglen) )
+ f.title('Period detection: Gaussian weighting')
+ f.xlabel('lag (df samples)')
+ f.plot(*d[2])
+ f('set size %f,%f' % (1.0*xsize,0.33*ysize) )
+ f('set orig %f,%f' % (0.0*xsize,0.00*ysize) )
+ f('set xrange [%f:%f]' % (-laglen,laglen) )
+ f.title('Phase detection and predicted beats')
+ f.xlabel('time (df samples)')
+ f.plot(*d[3])
+ f('set nomultiplot')
+ if printframe == -1: a = sys.stdin.read()
+ elif 0 < printframe and printframe < nrframe:
+ break
projects / aubio.git / blobdiff