class AudioLocalizerTest(unittest.TestCase):
def setUp(self):
self.sampling_rate = 44100
self.dirloc = DirectionLocalizer(mic_layout=None,
sample_rate=44100)
self.dft_len = 8
self.stft = StftManager(dft_length=self.dft_len,
window_length=self.dft_len,
hop_length=self.dft_len,
use_window_fcn=False)
mic_positions = np.array([[1, 1, 0],
[-1, 1, 0],
[-1, -1, 0],
[1, -1, 0],
[0, 0, 1]])
self._n_mics = mic_positions.shape[0]
self._n_theta = 4
self._n_phi = 4
self.distrloc = DistributionLocalizer(mic_positions=mic_positions,
dft_len=self.dft_len,
sample_rate=44100,
n_theta=self._n_theta,
n_phi=self._n_phi)
pass
def testGetPeaks(self):
g = np.array([[1, 2, 2, 1, 1, 2, 3, 4],
[2, 3, 4, 1, 2, 2, 1, 1],
[1, 1, 2, 3, 4, 1, 2, 2],
[1, 2, 2, 1, 1, 2, 3, 4]])
G = fftp.ifft(g)
shift_max = 4
shift_n = 2 * shift_max + 1
loc = DirectionLocalizer(mic_layout=None, shift_n=shift_n, shift_max=shift_max)
peaks = loc.get_peaks(G)
print peaks
max_ind = np.argmax(peaks, 1)
shifts = peaks[0, max_ind]
self.assertListFloatEqual(np.array([4, 3, -3, 0]), shifts)
def testGetPeaksSame(self):
sample_rate = 44100
loc = DirectionLocalizer(mic_layout=None, sample_rate=sample_rate, shift_n=20, shift_max=2)
data = np.array([1, -2, 3, 4, 0, 0, 1, 2], dtype=np.float32)
fft = fftp.fft(data)
ffts = np.array([fft, fft])
peaks = loc.get_peaks(ffts)
inds = np.argmax(peaks, 1)
delays = peaks[0, inds[1:]]
delays *= pa_tools.SPEED_OF_SOUND / sample_rate
self.assertListFloatEqual([0.0], delays)
def testGetDirectionOrthogonal(self):
sample_rate = 44100
mics = np.array([[-.025], [.025]], dtype=np.float32)
source_loc = np.array([10])
dist_1 = np.linalg.norm(source_loc - mics[0, :], 2)
dist_2 = np.linalg.norm(source_loc - mics[1, :], 2)
loc = DirectionLocalizer(mic_layout=mics, sample_rate=sample_rate, shift_n=20, shift_max=2)
data = np.array([1, -2, 3, 4, 0, 0, 1, 2], dtype=np.float32)
fft = fftp.fft(data)
ffts = np.array([fft, fft])
direction = loc.get_direction_np(ffts)
self.assertListFloatEqual([0.0], direction)
def testGetDirection3Mic(self):
sample_rate = 16000
sample_delay = 3
# Get side_length of mic triangle so that the sample
# delay will be an integer if source comes from direction
# perpendicular to some side of the triangle
side_length = 2 * sample_delay * pa_tools.SPEED_OF_SOUND / (np.sqrt(3) * sample_rate)
mics = np.array([[0, side_length / np.sqrt(3)],
[side_length / 2, -side_length / (2 * np.sqrt(3))],
[-side_length / 2, -side_length / (2 * np.sqrt(3))]])
# Sides are orthogonal to directions (sqrt(3)/2, 1/2), (-sqrt(3)/2, 1/2), (0, 1)
data_len = 100
data1 = np.random.rand(1, data_len)
if sample_delay > 0:
data2 = np.concatenate((np.random.rand(1, sample_delay),
[data1[0, :-sample_delay]]), axis=1)
else:
data2 = data1
# Get dfts
fft1 = fftp.fft(data1[0])
fft2 = fftp.fft(data2[0])
loc = DirectionLocalizer(mic_layout=mics, sample_rate=sample_rate, shift_max=data_len / 2, shift_n=100)
ffts = np.array([fft1, fft1, fft2])
# Get peaks and direction
peaks = loc.get_peaks(ffts)
print "Sample delay from mic 1: " + str(peaks[0, (np.argmax(peaks, 1))[1:]])
direction = loc.get_direction_np(ffts)
print "Direction to source: " + str(direction)
direction /= np.linalg.norm(direction, 2) # Normalize
direction *= 10 # Scale for plotting
print mics
# Plot
plt.figure()
plt.plot(mics[:, 0], mics[:, 1], 'bo')
plt.quiver(0, 0, direction[0], direction[1], scale=20)
plt.show()
#self.assertEquals(0, 1)
def testAngularMethod(self):
sample_rate = 16000
sample_delay = 5
angle = math.pi / 6
if abs(math.cos(angle)) > 1e-10:
dist = sample_delay * pa_tools.SPEED_OF_SOUND / (sample_rate * math.cos(angle))
else:
dist = 1
sample_delay = 0
print "distance: " + str(dist)
mics = np.array([[0., 0.], [dist, 0.]], dtype=np.float32)
data_len = 100
data1 = np.random.rand(1, data_len)
if sample_delay > 0:
data2 = np.concatenate((np.random.rand(1, sample_delay),
[data1[0, :-sample_delay]]), axis=1)
else:
data2 = data1
# Get dfts
fft1 = fftp.fft(data1[0])
fft2 = fftp.fft(data2[0])
ffts = np.array([fft1, fft2])
loc = DirectionLocalizer(mics, sample_rate=sample_rate)
direction = loc.get_direction_np(ffts)
print "direction: " + str(direction)
# Plot
plt.figure()
plt.plot(mics[:, 0], mics[:, 1], 'bo')
plt.quiver(0, 0, direction[0], direction[1], scale=20)
plt.show()
#self.assertEquals(0, 1)
def testifftMatrix(self):
ffts = np.array([[1, 0, 0, 0],
[2, 0, 0, 0],
[3, 0, 0, 0],
[4, 0, 0, 0]], dtype=np.float32)
ifft = fftp.ifft(ffts)
print ifft
#self.assertEquals(0, 1)
def testGetDistribution3D(self):
R = 0.0375
H = 0.07
x = np.array([[0, 0, H],
[R, 0, 0],
[R*math.cos(math.pi/3), R*math.sin(math.pi/3), 0],
[-R*math.cos(math.pi/3), R*math.sin(math.pi/3), 0],
[-R, 0, 0],
[-R*math.cos(math.pi/3), -R*math.sin(math.pi/3), 0],
[R*math.cos(math.pi/3), -R*math.sin(math.pi/3), 0]])
nmics = 7
# Setup plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plt.show(block=False)
# Peform simulation
N_trials = 10
for n in range(N_trials):
# Get random direction
source = np.array([-100, -100, 0]) + 200 * np.random.rand(3)
#source =np.array([70, 20, 100])
# Compute distances and delays
d = np.sqrt(np.sum((x - source) ** 2, axis=1))
#d1 = d[0] - d
delays = d / pa_tools.SPEED_OF_SOUND
print "delays: " + str(delays)
# Create audio sample
Fs = 44100
T = 1. / Fs
nsecs = .25
N = Fs * nsecs
fund_freq = 50
low_freq = 1 / (2 * nsecs)
n = (np.tile(np.arange(N) * T, (nmics, 1)).T - delays).T
s = np.sin(n * math.pi * low_freq)
# Add different harmonics to signal
for k in range(50):
if k % 3 == 1:
s += 5 * np.sin(n * 2 * math.pi * fund_freq * k)
# Add random noise to each signal
#s += .35 * np.random.rand(nmics, s.shape[1])
# Setup localizer
window_len = 512
N_THETA = 20
N_PHI = N_THETA / 2
loc = DistributionLocalizer(x, sample_rate=Fs, n_theta=N_THETA, dft_len=window_len, n_phi=N_PHI)
# Get section of signal
ind = round(random.random() * (N - 512 - 1))
#ind = 200;
g = s[:, ind:ind + window_len]
#print g
#f = plt.figure()
#a = f.add_subplot(111)
#a.plot(np.arange(g.shape[1]), g.T)
#plt.show()
G = np.fft.fft(g, n=window_len, axis=1)
G_real = np.fft.rfft(g, n=window_len, axis=1)
direcs = loc.get_directions()
d_real = loc.get_distribution_real(G_real)
d = loc.get_distribution_mat(G)
#self.assertListFloatEqual(d, d_real)
d = d_real
print "max: " + str(np.max(d))
print "min: " + str(np.min(d))
maxind = np.argmax(d)
u = 1.5 * direcs[:, maxind]
v = 1.5 * source / np.linalg.norm(source, 2)
#self.assertLessEqual(np.sqrt(np.sum((u / 1.5 - v / 1.5) ** 2)), .2)
plt.cla()
ax.scatter(direcs[0, :], direcs[1, :], direcs[2, :], s=30, c=d)
ax.plot([0, v[0]], [0, v[1]], [0, v[2]])
ax.plot([0, u[0]], [0, u[1]], [0, u[2]], c='r')
#ax.view_init(azim=-90, elev=90)
plt.draw()
time.sleep(.5)
#self.assertEquals(0, 1)
def testGetAlignMats(self):
a_mats = self.distrloc.get_align_mat()
self.assertTupleEqual(a_mats.shape, (self._n_mics, self.dft_len, self._n_theta * self._n_phi))
def testGetPosAlignMats(self):
a_mats = self.distrloc.get_pos_align_mat()
self.assertTupleEqual(a_mats.shape, (self._n_mics, self.dft_len / 2 + 1, self._n_theta * self._n_phi))
def assertListFloatEqual(self, list1, list2):
if not len(list1) == len(list2):
raise AssertionError("Lists differ in lenght. Cannot be equal")
for i in range(len(list1)):
try:
self.assertLessEqual(abs(list1[i] - list2[i]), 1e-4)
except AssertionError:
err_str = "Lists differ on element " + str(i) + ": " + \
str(list1[i]) + " vs. " + str(list2[i])
raise AssertionError(err_str)
def tearDown(self):
pass
class AudioLocalizerTest(unittest.TestCase):
def setUp(self):
self.sampling_rate = 44100
self.dirloc = DirectionLocalizer(mic_layout=None, sample_rate=44100)
self.dft_len = 8
self.stft = StftManager(dft_length=self.dft_len,
window_length=self.dft_len,
hop_length=self.dft_len,
use_window_fcn=False)
mic_positions = np.array([[1, 1, 0], [-1, 1, 0], [-1, -1, 0],
[1, -1, 0], [0, 0, 1]])
self._n_mics = mic_positions.shape[0]
self._n_theta = 4
self._n_phi = 4
self.distrloc = DistributionLocalizer(mic_positions=mic_positions,
dft_len=self.dft_len,
sample_rate=44100,
n_theta=self._n_theta,
n_phi=self._n_phi)
pass
def testGetPeaks(self):
g = np.array([[1, 2, 2, 1, 1, 2, 3, 4], [2, 3, 4, 1, 2, 2, 1, 1],
[1, 1, 2, 3, 4, 1, 2, 2], [1, 2, 2, 1, 1, 2, 3, 4]])
G = fftp.ifft(g)
shift_max = 4
shift_n = 2 * shift_max + 1
loc = DirectionLocalizer(mic_layout=None,
shift_n=shift_n,
shift_max=shift_max)
peaks = loc.get_peaks(G)
print peaks
max_ind = np.argmax(peaks, 1)
shifts = peaks[0, max_ind]
self.assertListFloatEqual(np.array([4, 3, -3, 0]), shifts)
def testGetPeaksSame(self):
sample_rate = 44100
loc = DirectionLocalizer(mic_layout=None,
sample_rate=sample_rate,
shift_n=20,
shift_max=2)
data = np.array([1, -2, 3, 4, 0, 0, 1, 2], dtype=np.float32)
fft = fftp.fft(data)
ffts = np.array([fft, fft])
peaks = loc.get_peaks(ffts)
inds = np.argmax(peaks, 1)
delays = peaks[0, inds[1:]]
delays *= pa_tools.SPEED_OF_SOUND / sample_rate
self.assertListFloatEqual([0.0], delays)
def testGetDirectionOrthogonal(self):
sample_rate = 44100
mics = np.array([[-.025], [.025]], dtype=np.float32)
source_loc = np.array([10])
dist_1 = np.linalg.norm(source_loc - mics[0, :], 2)
dist_2 = np.linalg.norm(source_loc - mics[1, :], 2)
loc = DirectionLocalizer(mic_layout=mics,
sample_rate=sample_rate,
shift_n=20,
shift_max=2)
data = np.array([1, -2, 3, 4, 0, 0, 1, 2], dtype=np.float32)
fft = fftp.fft(data)
ffts = np.array([fft, fft])
direction = loc.get_direction_np(ffts)
self.assertListFloatEqual([0.0], direction)
def testGetDirection3Mic(self):
sample_rate = 16000
sample_delay = 3
# Get side_length of mic triangle so that the sample
# delay will be an integer if source comes from direction
# perpendicular to some side of the triangle
side_length = 2 * sample_delay * pa_tools.SPEED_OF_SOUND / (
np.sqrt(3) * sample_rate)
mics = np.array([[0, side_length / np.sqrt(3)],
[side_length / 2, -side_length / (2 * np.sqrt(3))],
[-side_length / 2, -side_length / (2 * np.sqrt(3))]])
# Sides are orthogonal to directions (sqrt(3)/2, 1/2), (-sqrt(3)/2, 1/2), (0, 1)
data_len = 100
data1 = np.random.rand(1, data_len)
if sample_delay > 0:
data2 = np.concatenate(
(np.random.rand(1, sample_delay), [data1[0, :-sample_delay]]),
axis=1)
else:
data2 = data1
# Get dfts
fft1 = fftp.fft(data1[0])
fft2 = fftp.fft(data2[0])
loc = DirectionLocalizer(mic_layout=mics,
sample_rate=sample_rate,
shift_max=data_len / 2,
shift_n=100)
ffts = np.array([fft1, fft1, fft2])
# Get peaks and direction
peaks = loc.get_peaks(ffts)
print "Sample delay from mic 1: " + str(
peaks[0, (np.argmax(peaks, 1))[1:]])
direction = loc.get_direction_np(ffts)
print "Direction to source: " + str(direction)
direction /= np.linalg.norm(direction, 2) # Normalize
direction *= 10 # Scale for plotting
print mics
# Plot
plt.figure()
plt.plot(mics[:, 0], mics[:, 1], 'bo')
plt.quiver(0, 0, direction[0], direction[1], scale=20)
plt.show()
#self.assertEquals(0, 1)
def testAngularMethod(self):
sample_rate = 16000
sample_delay = 5
angle = math.pi / 6
if abs(math.cos(angle)) > 1e-10:
dist = sample_delay * pa_tools.SPEED_OF_SOUND / (sample_rate *
math.cos(angle))
else:
dist = 1
sample_delay = 0
print "distance: " + str(dist)
mics = np.array([[0., 0.], [dist, 0.]], dtype=np.float32)
data_len = 100
data1 = np.random.rand(1, data_len)
if sample_delay > 0:
data2 = np.concatenate(
(np.random.rand(1, sample_delay), [data1[0, :-sample_delay]]),
axis=1)
else:
data2 = data1
# Get dfts
fft1 = fftp.fft(data1[0])
fft2 = fftp.fft(data2[0])
ffts = np.array([fft1, fft2])
loc = DirectionLocalizer(mics, sample_rate=sample_rate)
direction = loc.get_direction_np(ffts)
print "direction: " + str(direction)
# Plot
plt.figure()
plt.plot(mics[:, 0], mics[:, 1], 'bo')
plt.quiver(0, 0, direction[0], direction[1], scale=20)
plt.show()
#self.assertEquals(0, 1)
def testifftMatrix(self):
ffts = np.array(
[[1, 0, 0, 0], [2, 0, 0, 0], [3, 0, 0, 0], [4, 0, 0, 0]],
dtype=np.float32)
ifft = fftp.ifft(ffts)
print ifft
#self.assertEquals(0, 1)
def testGetDistribution3D(self):
R = 0.0375
H = 0.07
x = np.array(
[[0, 0, H], [R, 0, 0],
[R * math.cos(math.pi / 3), R * math.sin(math.pi / 3), 0],
[-R * math.cos(math.pi / 3), R * math.sin(math.pi / 3), 0],
[-R, 0, 0],
[-R * math.cos(math.pi / 3), -R * math.sin(math.pi / 3), 0],
[R * math.cos(math.pi / 3), -R * math.sin(math.pi / 3), 0]])
nmics = 7
# Setup plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plt.show(block=False)
# Peform simulation
N_trials = 10
for n in range(N_trials):
# Get random direction
source = np.array([-100, -100, 0]) + 200 * np.random.rand(3)
#source =np.array([70, 20, 100])
# Compute distances and delays
d = np.sqrt(np.sum((x - source)**2, axis=1))
#d1 = d[0] - d
delays = d / pa_tools.SPEED_OF_SOUND
print "delays: " + str(delays)
# Create audio sample
Fs = 44100
T = 1. / Fs
nsecs = .25
N = Fs * nsecs
fund_freq = 50
low_freq = 1 / (2 * nsecs)
n = (np.tile(np.arange(N) * T, (nmics, 1)).T - delays).T
s = np.sin(n * math.pi * low_freq)
# Add different harmonics to signal
for k in range(50):
if k % 3 == 1:
s += 5 * np.sin(n * 2 * math.pi * fund_freq * k)
# Add random noise to each signal
#s += .35 * np.random.rand(nmics, s.shape[1])
# Setup localizer
window_len = 512
N_THETA = 20
N_PHI = N_THETA / 2
loc = DistributionLocalizer(x,
sample_rate=Fs,
n_theta=N_THETA,
dft_len=window_len,
n_phi=N_PHI)
# Get section of signal
ind = round(random.random() * (N - 512 - 1))
#ind = 200;
g = s[:, ind:ind + window_len]
#print g
#f = plt.figure()
#a = f.add_subplot(111)
#a.plot(np.arange(g.shape[1]), g.T)
#plt.show()
G = np.fft.fft(g, n=window_len, axis=1)
G_real = np.fft.rfft(g, n=window_len, axis=1)
direcs = loc.get_directions()
d_real = loc.get_distribution_real(G_real)
d = loc.get_distribution_mat(G)
#self.assertListFloatEqual(d, d_real)
d = d_real
print "max: " + str(np.max(d))
print "min: " + str(np.min(d))
maxind = np.argmax(d)
u = 1.5 * direcs[:, maxind]
v = 1.5 * source / np.linalg.norm(source, 2)
#self.assertLessEqual(np.sqrt(np.sum((u / 1.5 - v / 1.5) ** 2)), .2)
plt.cla()
ax.scatter(direcs[0, :], direcs[1, :], direcs[2, :], s=30, c=d)
ax.plot([0, v[0]], [0, v[1]], [0, v[2]])
ax.plot([0, u[0]], [0, u[1]], [0, u[2]], c='r')
#ax.view_init(azim=-90, elev=90)
plt.draw()
time.sleep(.5)
#self.assertEquals(0, 1)
def testGetAlignMats(self):
a_mats = self.distrloc.get_align_mat()
self.assertTupleEqual(
a_mats.shape,
(self._n_mics, self.dft_len, self._n_theta * self._n_phi))
def testGetPosAlignMats(self):
a_mats = self.distrloc.get_pos_align_mat()
self.assertTupleEqual(
a_mats.shape,
(self._n_mics, self.dft_len / 2 + 1, self._n_theta * self._n_phi))
def assertListFloatEqual(self, list1, list2):
if not len(list1) == len(list2):
raise AssertionError("Lists differ in lenght. Cannot be equal")
for i in range(len(list1)):
try:
self.assertLessEqual(abs(list1[i] - list2[i]), 1e-4)
except AssertionError:
err_str = "Lists differ on element " + str(i) + ": " + \
str(list1[i]) + " vs. " + str(list2[i])
raise AssertionError(err_str)
def tearDown(self):
pass
