from aubio.task import task from aubio.task.utils import * from aubio.aubioclass import * class tasknotes(task): def __init__(self,input,output=None,params=None): task.__init__(self,input,params=params) self.opick = onsetpick(self.params.bufsize, self.params.hopsize, self.channels, self.myvec, self.params.threshold, mode=get_onset_mode(self.params.onsetmode), dcthreshold=self.params.dcthreshold, derivate=self.params.derivate) self.pitchdet = pitchdetection(mode=get_pitch_mode(self.params.pitchmode), bufsize=self.params.pbufsize, hopsize=self.params.phopsize, channels=self.channels, samplerate=self.srate, omode=self.params.omode) self.olist = [] self.ofunc = [] self.maxofunc = 0 self.last = -1000 self.oldifreq = 0 if self.params.localmin: self.ovalist = [0., 0., 0., 0., 0.] def __call__(self): from aubio.median import short_find task.__call__(self) isonset,val = self.opick.do(self.myvec) if (aubio_silence_detection(self.myvec(),self.params.silence)): isonset=0 freq = -1. else: freq = self.pitchdet(self.myvec) minpitch = self.params.pitchmin maxpitch = self.params.pitchmax if maxpitch and freq > maxpitch : freq = -1. elif minpitch and freq < minpitch : freq = -1. freq = aubio_freqtomidi(freq) if self.params.pitchsmooth: self.shortlist.append(freq) self.shortlist.pop(0) smoothfreq = short_find(self.shortlist, len(self.shortlist)/2) freq = smoothfreq now = self.frameread ifreq = int(round(freq)) if self.oldifreq == ifreq: self.oldifreq = ifreq else: self.oldifreq = ifreq ifreq = 0 # take back delay if self.params.delay != 0.: now -= self.params.delay if now < 0 : now = 0 if (isonset == 1): if self.params.mintol: # prune doubled if (now - self.last) > self.params.mintol: self.last = now return now, 1, freq, ifreq else: return now, 0, freq, ifreq else: return now, 1, freq, ifreq else: return now, 0, freq, ifreq def fprint(self,foo): print self.params.step*foo[0], foo[1], foo[2], foo[3] def compute_all(self): """ Compute data """ now, onset, freq, ifreq = [], [], [], [] while(self.readsize==self.params.hopsize): n, o, f, i = self() now.append(n*self.params.step) onset.append(o) freq.append(f) ifreq.append(i) if self.params.verbose: self.fprint((n,o,f,i)) return now, onset, freq, ifreq def plot(self,now,onset,freq,ifreq,oplots): import Gnuplot oplots.append(Gnuplot.Data(now,freq,with_='lines', title=self.params.pitchmode)) oplots.append(Gnuplot.Data(now,ifreq,with_='lines', title=self.params.pitchmode)) temponsets = [] for i in onset: temponsets.append(i*1000) oplots.append(Gnuplot.Data(now,temponsets,with_='impulses', title=self.params.pitchmode)) def plotplot(self,wplot,oplots,outplot=None,multiplot = 0): from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot import re import Gnuplot # audio data time,data = audio_to_array(self.input) f = make_audio_plot(time,data) # check if ground truth exists #timet,pitcht = self.gettruth() #if timet and pitcht: # oplots = [Gnuplot.Data(timet,pitcht,with_='lines', # title='ground truth')] + oplots t = Gnuplot.Data(0,0,with_='impulses') g = gnuplot_init(outplot) g('set title \'%s\'' % (re.sub('.*/','',self.input))) 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 [20:100]') g('set key right top') g('set noclip one') #g('set format x ""') #g('set log y') #g.xlabel('time (s)') g.ylabel('f0 (Hz)') if multiplot: for i in range(len(oplots)): # plot onset detection functions g('set size 1,%f' % (0.7/(len(oplots)))) g('set origin 0,%f' % (float(i)*0.7/(len(oplots)))) g('set xrange [0:%f]' % max(time)) g.plot(oplots[i]) else: g.plot(*oplots) #g('unset multiplot')