def test_vocoder():
"""Test noise and tone vocoding
"""
data = np.random.randn(10000)
env = np.random.randn(10000)
b, a = butter(4, 0.001, 'lowpass')
data *= lfilter(b, a, env)
# bad limits
assert_raises(ValueError, vocode_ci, data, 44100, freq_lims=(200, 30000))
# bad mode
assert_raises(ValueError, vocode_ci, data, 44100, mode='foo')
voc1 = vocode_ci(data, 20000, mode='noise', order=2)
voc2 = vocode_ci(data, 20000, mode='tone', order=4, rand_seed=0)
# XXX This is about the best we can do for now...
assert_array_equal(voc1.shape, data.shape)
assert_array_equal(voc2.shape, data.shape)
========================
This shows how to make simple vocoded stimuli.
@author: larsoner
"""
import numpy as np
from expyfun.stimuli import vocode_ci, play_sound, window_edges, read_wav
from expyfun import fetch_data_file
data, fs = read_wav(fetch_data_file('audio/dream.wav'))
data = window_edges(data[0], fs)
t = np.arange(data.size) / float(fs)
data_ci = vocode_ci(data, fs, mode='noise', order=4, verbose=True)
# Uncomment this to play the original, too:
#snd = play_sound(data, fs, norm=False, wait=False)
snd = play_sound(data_ci, fs, norm=False, wait=False)
import matplotlib.pyplot as mpl
mpl.ion()
ax1 = mpl.subplot(2, 1, 1)
ax1.plot(t, data)
ax1.set_title('Original')
ax2 = mpl.subplot(2, 1, 2, sharex=ax1, sharey=ax1)
ax2.plot(t, data_ci)
ax2.set_title('Vocoded')
ax2.set_xlabel('Time (sec)')
