author Paul Brossier Thu, 2 Feb 2017 01:39:05 +0000 (02:39 +0100) committer Paul Brossier Thu, 2 Feb 2017 01:39:05 +0000 (02:39 +0100)
 python/demos/demo_bench_yin.py [new file with mode: 0755] patch | blob

diff --git a/python/demos/demo_bench_yin.py b/python/demos/demo_bench_yin.py
new file mode 100755 (executable)
index 0000000..0d03c05
--- /dev/null
@@ -0,0 +1,50 @@
+#! /usr/bin/env python
+
+import numpy as np
+from aubio import pitch
+import pylab as plt
+
+buf_size = 2048 * 1
+hop_size = buf_size // 4
+
+samplerate = 44100
+minfreq = 40
+maxfreq = 6000
+
+def sinewave(freq, duration, samplerate = samplerate):
+    """ generate a sinewave """
+    length = hop_size
+    while length < duration * samplerate:
+        length += hop_size
+    return np.sin( 2. * np.pi * np.arange(length) * freq / samplerate ).astype("float32")
+
+def get_stats_for_pitch_method(method, freqs, samplerate = samplerate):
+    """ for a given pitch method and a list of frequency, generate a sinewave
+    and get mean deviation """
+    means = np.zeros(len(freqs))
+    medians = np.zeros(len(freqs))
+    for freq, fn in zip(freqs, range(len(freqs))):
+        s = sinewave(freq, .50).reshape(-1, hop_size)
+        #s = (sinewave(freq, .50) + .0*sinewave(freq/2., .50)).reshape(-1, hop_size)
+        p = pitch(method, buf_size, hop_size, samplerate = samplerate)
+        candidates = np.zeros(len(s))
+        #samples = np.zeros(buf_size)
+        for frame, i in zip(s, range(len(s))):
+            candidates[i] = p(frame)
+        # skip first few candidates
+        candidates = candidates[4:]
+        means[fn] = np.mean(candidates[candidates != 0] - freq)
+        medians[fn] = np.median(candidates[candidates != 0] - freq)
+        print (freq, means[fn], medians[fn])
+    return means, medians
+
+if __name__ == '__main__':
+    freqs = np.arange(minfreq, maxfreq, 1.)
+    modes = ["yin", "yinfft"]
+    for mode in modes:
+        means, medians = get_stats_for_pitch_method(mode, freqs)
+        plt.figure()
+        plt.plot(freqs, means, 'g-')
+        plt.plot(freqs, medians, 'r--')
+        #plt.savefig(mode + '_deviations_test.png', dpi=300)
+        plt.show()