python/aubio/gnuplot.py

   1 """Copyright (C) 2004 Paul Brossier <piem@altern.org>
   2 print aubio.__LICENSE__ for the terms of use
   3 """
   4
   5 __LICENSE__ = """\
   6          Copyright (C) 2004 Paul Brossier <piem@altern.org>
   7
   8          This program is free software; you can redistribute it and/or modify
   9          it under the terms of the GNU General Public License as published by
  10          the Free Software Foundation; either version 2 of the License, or
  11          (at your option) any later version.
  12
  13          This program is distributed in the hope that it will be useful,
  14          but WITHOUT ANY WARRANTY; without even the implied warranty of
  15          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  16          GNU General Public License for more details.
  17
  18          You should have received a copy of the GNU General Public License
  19          along with this program; if not, write to the Free Software
  20          Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
  21 """
  22
  23 __notesheight = 0.25
  24
  25 from numarray import *
  26 import Gnuplot, Gnuplot.funcutils
  27
  28 def plotnote(la,title=None) :
  29         if la[0,:].size() == 3:
  30                 d = plotnote_withends(la, plot_title=title)
  31         else:
  32             # scale data if in freq (for REF.txt files)
  33             if max(la[:,1] > 128 ):
  34                 print "scaling frequency data to midi range"
  35                 la[:,1] /= 6.875
  36                 la[:,1] = log(la[:,1])/0.6931
  37                 la[:,1] *= 12
  38                 la[:,1] -= 3
  39             d = plotnote_withoutends(la, plot_title=title)
  40         return d
  41
  42 def plotnote_multi(lalist,title=None,fileout=None) :
  43         d=list()
  44         for i in range(len(lalist)):
  45             d.append(plotnote(lalist[i], title=title))
  46         return d
  47
  48
  49 def plotnote_withends(la,plot_title=None) :
  50         d=[]
  51         x_widths = array(la[:,1]-la[:,0])/2.
  52         d.append(Gnuplot.Data(
  53                 la[:,0]+x_widths,               # x centers
  54                 la[:,2],                        # y centers
  55                 x_widths,                       # x errors
  56                 __notesheight*ones(len(la)),    # y errors
  57                 title=plot_title,with=('boxxyerrorbars fs 3')))
  58         return d
  59
  60
  61 def plotnote_withoutends(la,plot_title=None) :
  62         """ bug: fails drawing last note """
  63         d=[]
  64         x_widths = array(la[1:,0]-la[:-1,0])/2;
  65         d.append(Gnuplot.Data(
  66                 la[:-1,0]+x_widths,             # x centers
  67                 la[:-1,1],                      # y centers
  68                 x_widths,                       # x errors
  69                 __notesheight*ones(len(la)-1),  # y errors
  70                 title=plot_title,with=('boxxyerrorbars fs 3')))
  71         return d
  72
  73 def plotnote_do(d,fileout=None):
  74     g = Gnuplot.Gnuplot(debug=1, persist=1)
  75     g.gnuplot('set style fill solid border 1; \
  76     set size ratio 1/6; \
  77     set boxwidth 0.9 relative; \
  78     set mxtics 2.5; \
  79     set mytics 2.5; \
  80     set xtics 5; \
  81     set ytics 1; \
  82     set grid xtics ytics mxtics mytics')
  83
  84     g.xlabel('Time (s)')
  85     g.ylabel('Midi pitch')
  86     # do the plot
  87     #g.gnuplot('set multiplot')
  88     #for i in d:
  89     g.plot(d[0])
  90     #g.gnuplot('set nomultiplot')
  91     if fileout != None:
  92         g.hardcopy(fileout, enhanced=1, color=0)
  93
  94 def audio_to_array(filename):
  95         import aubio.aubioclass
  96         hopsize  = 2048
  97         filei    = aubio.aubioclass.sndfile(filename)
  98         framestep = 1/(filei.samplerate()+0.)
  99         channels = filei.channels()
 100         myvec    = aubio.aubioclass.fvec(hopsize,channels)
 101         data = []
 102         readsize = hopsize
 103         while (readsize==hopsize):
 104                 readsize = filei.read(hopsize,myvec)
 105                 #for i in range(channels):
 106                 i = 0
 107                 curpos = 0
 108                 while (curpos < readsize):
 109                         data.append(myvec.get(curpos,i))
 110                         curpos+=1
 111         time = arange(len(data))*framestep
 112         return time,data
 113
 114 def plot_audio(filenames, fileout=None, start=0, end=None, noaxis=None):
 115         g = Gnuplot.Gnuplot(debug=1, persist=1)
 116         d = []
 117         todraw = len(filenames)
 118         xorig = 0.
 119         xsize = 1./todraw
 120         g.gnuplot('set multiplot;')
 121         while (len(filenames)):
 122                 d.append(plot_audio_make(filenames.pop(0)))
 123                 if not noaxis and todraw==1:
 124                         g.xlabel('Time (s)')
 125                         g.ylabel('Amplitude')
 126                 g.gnuplot('set size %f,1.;' % (xsize) )
 127                 g.gnuplot('set origin %f,0.;' % (xorig) )
 128                 g.gnuplot('set style data lines; \
 129                         set yrange [-1.:1.]; \
 130                         set xrange [0:%f]' % b[-1])
 131                 g.plot(d.pop(0))
 132                 xorig += 1./todraw
 133         g.gnuplot('unset multiplot;')
 134         if fileout != None:
 135                 g.hardcopy(fileout, enhanced=1, color=0)
 136
 137 def make_audio_plot(time,data,maxpoints=10000):
 138         """ create gnuplot plot from an audio file """
 139         length = len(time)
 140         downsample = length/maxpoints
 141         if downsample == 0: downsample = 1
 142         x = array(time).resize(length)[0:-1:downsample]
 143         y = array(data).resize(length)[0:-1:downsample]
 144         return Gnuplot.Data(x,y,with='lines')
 145
 146
 147 def plot_onsets(filename, onsets, ofunc, samplerate=44100., hopsize=512, outplot=None):
 148         import aubio.txtfile
 149         import os.path
 150         import numarray
 151         from aubio.onsetcompare import onset_roc
 152
 153         if len(onsets) == 0: onsets = [0.];
 154
 155         # onset detection function
 156         downtime = (hopsize/samplerate)*numarray.arange(len(ofunc))
 157         d = Gnuplot.Data(downtime,ofunc,with='lines')
 158
 159         # detected onsets
 160         x1 = (hopsize/samplerate)*numarray.array(onsets)
 161         y1 = max(ofunc)*numarray.ones(len(onsets))
 162         e = Gnuplot.Data(x1,-y1,with='impulses')
 163         e2= Gnuplot.Data(x1,y1,with='impulses')
 164
 165         # check if datafile exists truth
 166         datafile = filename.replace('.wav','.txt')
 167         if not os.path.isfile(datafile):
 168                 title = "truth file not found"
 169                 t = Gnuplot.Data(0,0,with='impulses')
 170         else:
 171                 t_onsets = aubio.txtfile.read_datafile(datafile)
 172                 y2 = max(ofunc)*numarray.ones(len(t_onsets))
 173                 x2 = numarray.array(t_onsets).resize(len(t_onsets))
 174                 t = Gnuplot.Data(x2,y2,with='impulses')
 175
 176                 tol = 0.050
 177
 178                 orig, missed, merged, expc, bad, doubled = \
 179                         onset_roc(x2,x1,tol)
 180                 title = "GD %2.3f%% FP %2.3f%%" % \
 181                         ((100*float(orig-missed-merged)/(orig)),
 182                          (100*float(bad+doubled)/(orig)))
 183                 #print  orig, missed, merged, expc, bad, doubled
 184                 #print "GD %2.8f\t"        % (100*float(orig-missed-merged)/(orig)),
 185                 #print "FP %2.8f\t"        % (100*float(bad+doubled)/(orig))       ,
 186                 #print "GD-merged %2.8f\t" % (100*float(orig-missed)/(orig))       ,
 187                 #print "FP-pruned %2.8f\t" % (100*float(bad)/(orig))
 188
 189         # audio data
 190         time,data = audio_to_array(filename)
 191         f = make_audio_plot(time,data)
 192
 193         # prepare the plot
 194         g = Gnuplot.Gnuplot(debug=1, persist=1)
 195         if outplot:
 196                 extension = outplot.split('.')[-1]
 197                 if extension == 'ps': extension = 'postscript'
 198                 g('set terminal %s' % extension)
 199                 g('set output \'%s\'' % outplot)
 200
 201         g('set title \'%s %s\'' % (filename,title))
 202
 203         g('set multiplot')
 204
 205         # hack to align left axis
 206         g('set lmargin 15')
 207
 208         # plot waveform and onsets
 209         g('set size 1,0.3')
 210         g('set origin 0,0.7')
 211         g('set xrange [0:%f]' % max(time))
 212         g('set yrange [-1:1]')
 213         g.ylabel('amplitude')
 214         g.plot(f,e,t)
 215
 216         g('unset title')
 217
 218         # plot onset detection function
 219         g('set size 1,0.7')
 220         g('set origin 0,0')
 221         g('set xrange [0:%f]' % (hopsize/samplerate*len(ofunc)))
 222         g('set yrange [0:%f]' % (max(ofunc)*1.01))
 223         g.xlabel('time')
 224         g.ylabel('onset detection value')
 225         g.plot(d,e2)
 226
 227         g('unset multiplot')
 228
 229
 230 def plot_pitch(filename, pitch, samplerate=44100., hopsize=512, outplot=None):
 231         import aubio.txtfile
 232         import os.path
 233         import numarray
 234
 235         # onset detection function
 236         downtime = (hopsize/samplerate)*numarray.arange(len(pitch))
 237         d = Gnuplot.Data(downtime,pitch,with='lines')
 238
 239         # check if datafile exists truth
 240         datafile = filename.replace('.wav','.txt')
 241         if not os.path.isfile(datafile):
 242                 title = "truth file not found"
 243                 t = Gnuplot.Data(0,0,with='impulses')
 244         else:
 245                 title = "truth file plotting not implemented yet"
 246                 t = Gnuplot.Data(0,0,with='impulses')
 247                 #times,pitch = aubio.txtfile.read_datafile(datafile)
 248                 #t = Gnuplot.Data(times,pitch,with='lines')
 249
 250                 #orig, missed, merged, expc, bad, doubled = \
 251                 #        onset_roc(x2,x1,tol)
 252                 #title = "GD %2.3f%% FP %2.3f%%" % \
 253                 #        ((100*float(orig-missed-merged)/(orig)),
 254                 #         (100*float(bad+doubled)/(orig)))
 255                 #print  orig, missed, merged, expc, bad, doubled
 256                 #print "GD %2.8f\t"        % (100*float(orig-missed-merged)/(orig)),
 257                 #print "FP %2.8f\t"        % (100*float(bad+doubled)/(orig))       ,
 258                 #print "GD-merged %2.8f\t" % (100*float(orig-missed)/(orig))       ,
 259                 #print "FP-pruned %2.8f\t" % (100*float(bad)/(orig))
 260
 261         # audio data
 262         time,data = audio_to_array(filename)
 263         f = make_audio_plot(time,data)
 264
 265         # prepare the plot
 266         g = Gnuplot.Gnuplot(debug=1, persist=1)
 267         if outplot:
 268                 extension = outplot.split('.')[-1]
 269                 if extension == 'ps': extension = 'postscript'
 270                 g('set terminal %s' % extension)
 271                 g('set output \'%s\'' % outplot)
 272
 273         g('set title \'%s %s\'' % (filename,title))
 274
 275         g('set multiplot')
 276
 277         # hack to align left axis
 278         g('set lmargin 15')
 279
 280         # plot waveform and onsets
 281         g('set size 1,0.3')
 282         g('set origin 0,0.7')
 283         g('set xrange [0:%f]' % max(time))
 284         g('set yrange [-1:1]')
 285         g.ylabel('amplitude')
 286         g.plot(f)
 287
 288         g('unset title')
 289
 290         # plot onset detection function
 291         g('set size 1,0.7')
 292         g('set origin 0,0')
 293         g('set xrange [0:%f]' % (hopsize/samplerate*len(pitch)))
 294         g('set yrange [0:%f]' % (max(pitch)*1.01))
 295         g.xlabel('time')
 296         g.ylabel('frequency (Hz)')
 297         g.plot(d,t)
 298
 299         g('unset multiplot')