4 from aubio import fvec, source, pvoc, specdesc
5 from numpy import hstack
8 hop_s = win_s / 4 # hop size
11 print "Usage: %s <filename> [samplerate]" % sys.argv[0]
14 filename = sys.argv[1]
17 if len( sys.argv ) > 2: samplerate = int(sys.argv[2])
19 s = source(filename, samplerate, hop_s)
20 samplerate = s.samplerate
22 pv = pvoc(win_s, hop_s)
24 methods = ['default', 'energy', 'hfc', 'complex', 'phase', 'specdiff', 'kl',
25 'mkl', 'specflux', 'centroid', 'slope', 'rolloff', 'spread', 'skewness',
26 'kurtosis', 'decrease',]
31 for method in methods:
33 all_descs[method] = fvec(0)
34 o[method] = specdesc(method, win_s)
41 fftgrain = pv(samples)
42 #print "%f" % ( total_frames / float(samplerate) ),
43 for method in methods:
44 specdesc_val = o[method](fftgrain)[0]
45 all_descs[method] = hstack ( [all_descs[method], specdesc_val] )
46 #print "%f" % specdesc_val,
49 if read < hop_s: break
52 print "done computing, now plotting"
53 import matplotlib.pyplot as plt
54 from demo_waveform_plot import get_waveform_plot
55 from demo_waveform_plot import set_xlabels_sample2time
57 plt.rc('lines',linewidth='.8')
58 wave = plt.axes([0.1, 0.75, 0.8, 0.19])
59 get_waveform_plot(filename, samplerate, block_size = hop_s, ax = wave )
60 wave.yaxis.set_visible(False)
61 wave.xaxis.set_visible(False)
63 all_desc_times = [ x * hop_s for x in range(len(all_descs["default"])) ]
64 n_methods = len(methods)
65 for i, method in enumerate(methods):
66 #ax = fig.add_subplot (n_methods, 1, i)
67 #plt2 = plt.axes([0.1, 0.1, 0.8, 0.65], sharex = plt1)
68 ax = plt.axes ( [0.1, 0.75 - ((i+1) * 0.65 / n_methods), 0.8, 0.65 / n_methods], sharex = wave )
69 ax.plot(all_desc_times, all_descs[method], '-', label = method)
70 #ax.set_ylabel(method, rotation = 0)
71 ax.xaxis.set_visible(False)
72 ax.yaxis.set_visible(False)
73 ax.axis(xmax = all_desc_times[-1], xmin = all_desc_times[0])
74 ax.annotate(method, xy=(-10, 0), xycoords='axes points',
75 horizontalalignment='right', verticalalignment='bottom',
77 set_xlabels_sample2time(ax, all_desc_times[-1], samplerate)
78 #plt.ylabel('spectral descriptor value')
79 ax.xaxis.set_visible(True)