ref: c54b2c04a5ea796ee3eecb0515469c231c363717
parent: 3f27a98ed43e11b18e94150ae8ffa2f1ab9be946
author: Paul Brossier <piem@piem.org>
date: Mon Dec 2 07:14:33 EST 2013
python/demos/demo_pitch.py: add plotting
--- a/python/demos/demo_pitch.py
+++ b/python/demos/demo_pitch.py
@@ -1,11 +1,8 @@
#! /usr/bin/env python
import sys
-from aubio import source, pitch
+from aubio import source, pitch, freqtomidi
-win_s = 1024 # fft size
-hop_s = win_s # hop size
-
if len(sys.argv) < 2:
print "Usage: %s <filename> [samplerate]" % sys.argv[0]
sys.exit(1)
@@ -12,26 +9,93 @@
filename = sys.argv[1]
-samplerate = 0
+downsample = 1
+samplerate = 44100 / downsample
if len( sys.argv ) > 2: samplerate = int(sys.argv[2])
+win_s = 4096 / downsample # fft size
+hop_s = 512 / downsample # hop size
+
s = source(filename, samplerate, hop_s)
samplerate = s.samplerate
-pitch_o = pitch("default", win_s, hop_s, samplerate)-pitch_o.set_unit("midi")+tolerance = 0.8
+pitch_o = pitch("yin", win_s, hop_s, samplerate)+pitch_o.set_unit("freq")+pitch_o.set_tolerance(tolerance)
+
pitches = []
+confidences = []
-
# total number of frames read
total_frames = 0
while True:
samples, read = s()
pitch = pitch_o(samples)[0]
- print "%f %f" % (total_frames / float(samplerate), pitch)
- #pitches += [pitches]
+ #pitch = int(round(pitch))
+ confidence = pitch_o.get_confidence()
+ #if confidence < 0.8: pitch = 0.
+ print "%f %f %f" % (total_frames / float(samplerate), pitch, confidence)
+ pitches += [pitch]
+ confidences += [confidence]
total_frames += read
if read < hop_s: break
+if 0: sys.exit(0)
+
#print pitches
+from numpy import array, ma
+import matplotlib.pyplot as plt
+from demo_waveform_plot import get_waveform_plot, set_xlabels_sample2time
+
+skip = 1
+
+pitches = array(pitches[skip:])
+confidences = array(confidences[skip:])
+times = [t * hop_s for t in range(len(pitches))]
+
+fig = plt.figure()
+ax1 = fig.add_subplot(311)
+ax1 = get_waveform_plot(filename, samplerate = samplerate, block_size = hop_s, ax = ax1)
+ax1.set_xticklabels([])
+
+def array_from_text_file(filename, dtype = 'float'):
+ import os.path
+ from numpy import array
+ filename = os.path.join(os.path.dirname(__file__), filename)
+ return array([line.split() for line in open(filename).readlines()],
+ dtype = dtype)
+
+ax2 = fig.add_subplot(312, sharex = ax1)
+import sys, os.path
+ground_truth = os.path.splitext(filename)[0] + '.f0.Corrected'
+if os.path.isfile(ground_truth):
+ ground_truth = array_from_text_file(ground_truth)
+ true_freqs = ground_truth[:,2]
+ true_freqs = ma.masked_where(true_freqs < 2, true_freqs)
+ true_times = float(samplerate) * ground_truth[:,0]
+ ax2.plot(true_times, true_freqs, 'r')
+ ax2.axis( ymin = 0.9 * true_freqs.min(), ymax = 1.1 * true_freqs.max() )
+# plot raw pitches
+ax2.plot(times, pitches, '--g')
+# plot cleaned up pitches
+cleaned_pitches = pitches
+#cleaned_pitches = ma.masked_where(cleaned_pitches < 0, cleaned_pitches)
+#cleaned_pitches = ma.masked_where(cleaned_pitches > 120, cleaned_pitches)
+cleaned_pitches = ma.masked_where(confidences < tolerance, cleaned_pitches)
+ax2.plot(times, cleaned_pitches, '.-')
+#ax2.axis( ymin = 0.9 * cleaned_pitches.min(), ymax = 1.1 * cleaned_pitches.max() )
+#ax2.axis( ymin = 55, ymax = 70 )
+ax2.set_xticklabels([])
+
+# plot confidence
+ax3 = fig.add_subplot(313, sharex = ax1)
+# plot the confidence
+ax3.plot(times, confidences)
+# draw a line at tolerance
+ax3.plot(times, [tolerance]*len(confidences))
+ax3.axis( xmin = times[0], xmax = times[-1])
+plt.show()
+set_xlabels_sample2time(ax3, times[-1], samplerate)
+#plt.savefig(os.path.basename(filename) + '.png', dpi=200)