4 from aubio import source, pitch
7 print("Usage: %s <filename> [samplerate]" % sys.argv[0])
10 filename = sys.argv[1]
13 samplerate = 44100 // downsample
14 if len( sys.argv ) > 2: samplerate = int(sys.argv[2])
16 win_s = 4096 // downsample # fft size
17 hop_s = 512 // downsample # hop size
19 s = source(filename, samplerate, hop_s)
20 samplerate = s.samplerate
24 pitch_o = pitch("yin", win_s, hop_s, samplerate)
25 pitch_o.set_unit("midi")
26 pitch_o.set_tolerance(tolerance)
31 # total number of frames read
35 pitch = pitch_o(samples)[0]
36 #pitch = int(round(pitch))
37 confidence = pitch_o.get_confidence()
38 #if confidence < 0.8: pitch = 0.
39 print("%f %f %f" % (total_frames / float(samplerate), pitch, confidence))
41 confidences += [confidence]
43 if read < hop_s: break
49 from numpy import array, ma
50 import matplotlib.pyplot as plt
51 from demo_waveform_plot import get_waveform_plot, set_xlabels_sample2time
55 pitches = array(pitches[skip:])
56 confidences = array(confidences[skip:])
57 times = [t * hop_s for t in range(len(pitches))]
61 ax1 = fig.add_subplot(311)
62 ax1 = get_waveform_plot(filename, samplerate = samplerate, block_size = hop_s, ax = ax1)
63 plt.setp(ax1.get_xticklabels(), visible = False)
66 def array_from_text_file(filename, dtype = 'float'):
67 filename = os.path.join(os.path.dirname(__file__), filename)
68 return array([line.split() for line in open(filename).readlines()],
71 ax2 = fig.add_subplot(312, sharex = ax1)
72 ground_truth = os.path.splitext(filename)[0] + '.f0.Corrected'
73 if os.path.isfile(ground_truth):
74 ground_truth = array_from_text_file(ground_truth)
75 true_freqs = ground_truth[:,2]
76 true_freqs = ma.masked_where(true_freqs < 2, true_freqs)
77 true_times = float(samplerate) * ground_truth[:,0]
78 ax2.plot(true_times, true_freqs, 'r')
79 ax2.axis( ymin = 0.9 * true_freqs.min(), ymax = 1.1 * true_freqs.max() )
81 ax2.plot(times, pitches, '.g')
82 # plot cleaned up pitches
83 cleaned_pitches = pitches
84 #cleaned_pitches = ma.masked_where(cleaned_pitches < 0, cleaned_pitches)
85 #cleaned_pitches = ma.masked_where(cleaned_pitches > 120, cleaned_pitches)
86 cleaned_pitches = ma.masked_where(confidences < tolerance, cleaned_pitches)
87 ax2.plot(times, cleaned_pitches, '.-')
88 #ax2.axis( ymin = 0.9 * cleaned_pitches.min(), ymax = 1.1 * cleaned_pitches.max() )
89 #ax2.axis( ymin = 55, ymax = 70 )
90 plt.setp(ax2.get_xticklabels(), visible = False)
91 ax2.set_ylabel('f0 (midi)')
94 ax3 = fig.add_subplot(313, sharex = ax1)
96 ax3.plot(times, confidences)
97 # draw a line at tolerance
98 ax3.plot(times, [tolerance]*len(confidences))
99 ax3.axis( xmin = times[0], xmax = times[-1])
100 ax3.set_ylabel('confidence')
101 set_xlabels_sample2time(ax3, times[-1], samplerate)
103 #plt.savefig(os.path.basename(filename) + '.svg')