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 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 localize():
# Setup pyaudio instances
pa = pyaudio.PyAudio()
helper = AudioHelper(pa)
localizer = DistributionLocalizer(mic_positions=mic_layout,
dft_len=FFT_LENGTH,
sample_rate=SAMPLE_RATE,
n_theta=N_THETA,
n_phi=N_PHI)
# Setup STFT object
stft = StftManager(dft_length=FFT_LENGTH,
window_length=WINDOW_LENGTH,
hop_length=HOP_LENGTH,
use_window_fcn=True,
n_channels=NUM_CHANNELS_IN,
dtype=DATA_TYPE)
# Setup devices
in_device = helper.get_input_device_from_user()
if PLAY_AUDIO:
out_device = helper.get_output_device_from_user()
else:
out_device = helper.get_default_output_device_info()
# Setup streams
in_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_IN,
format=SAMPLE_TYPE,
frames_per_buffer=FRAMES_PER_BUF,
input=True,
input_device_index=int(in_device['index']),
stream_callback=read_in_data)
out_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_OUT,
format=SAMPLE_TYPE,
output=True,
frames_per_buffer=FRAMES_PER_BUF,
output_device_index=int(out_device['index']),
stream_callback=write_out_data)
# Start recording/playing back
in_stream.start_stream()
out_stream.start_stream()
# Start thread to check for user quit
quit_thread = threading.Thread(target=check_for_quit)
quit_thread.start()
# Plotting setup
if PLOT_CARTES:
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plt.show(block=False)
scat = []
if PLOT_POLAR:
fig = plt.figure()
ax = fig.add_axes([.1, .1, .8, .8], projection='polar')
ax.set_rlim(0, 1)
plt.show(block=False)
# Setup space for plotting in new coordinates
spher_coords = localizer.get_spher_directions()
pol = localizer.to_spher_grid(spher_coords[2, :])
weight = 1. - .3 * np.sin(2 * pol) # Used to pull visualization off edges
r = np.sin(pol) * weight
theta = localizer.to_spher_grid(spher_coords[1, :])
if EXTERNAL_PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.show(block=False)
count = 0
direcs = localizer.get_directions()
try:
global done
while in_stream.is_active() or out_stream.is_active():
data_available = in_buf.wait_for_read(WINDOW_LENGTH, TIMEOUT)
if data_available:
# Get data from the circular buffer
data = in_buf.read_samples(WINDOW_LENGTH)
# Perform an stft
stft.performStft(data)
# Process dfts from windowed segments of input
dfts = stft.getDFTs()
d = localizer.get_3d_real_distribution(dfts)
ind = np.argmax(d)
u = 1.5 * direcs[:, ind] # Direction of arrival
# Take car of plotting
if count % 1 == 0:
if PLOT_CARTES:
plt.cla()
ax.scatter(direcs[0, :], direcs[1, :], direcs[2, :], s=30, c=d[3, :])
ax.plot([0, u[0]], [0, u[1]], [0, u[2]], c='blue')
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.set_zlim(0, 1)
plt.draw()
if PLOT_POLAR:
plt.cla()
d = localizer.to_spher_grid(d)
con = ax.contourf(theta, r, d, vmin=0, vmax=40)
con.set_cmap('gist_heat')
fig.canvas.draw()
count += 1
# Get the istft of the processed data
if PLAY_AUDIO:
new_data = stft.performIStft()
new_data = out_buf.reduce_channels(new_data, NUM_CHANNELS_IN, NUM_CHANNELS_OUT)
# Write out the new, altered data
if out_buf.get_available_write() >= WINDOW_LENGTH:
out_buf.write_samples(new_data)
#time.sleep(.05)
except KeyboardInterrupt:
print "Program interrupted"
done = True
print "Cleaning up"
in_stream.stop_stream()
in_stream.close()
out_stream.stop_stream()
out_stream.close()
pa.terminate()
print "Done"
def localize():
# Setup search space
# x vector points to front of class, -z vector points to floor
teacher_plane = SourcePlane(TEACHER_NORMAL, TEACHER_OFFSET)
student_plane = SourcePlane(STUDENT_NORMAL, STUDENT_OFFSET)
space = SearchSpace(MIC_LOC, CAMERA_LOC, [teacher_plane, student_plane])
# Setup camera
forward = np.array([1, 0, 0])
above = np.array([0, 0, 1])
camera = SonyCamera(URL, forward, above)
# Setup pyaudio instances
pa = pyaudio.PyAudio()
helper = AudioHelper(pa)
localizer = DistributionLocalizer(mic_positions=mic_layout,
dft_len=FFT_LENGTH,
sample_rate=SAMPLE_RATE,
n_theta=N_THETA,
n_phi=N_PHI)
# Setup STFT object
stft = StftManager(dft_length=FFT_LENGTH,
window_length=WINDOW_LENGTH,
hop_length=HOP_LENGTH,
use_window_fcn=True,
n_channels=NUM_CHANNELS_IN,
dtype=DATA_TYPE)
# Setup devices
in_device = helper.get_input_device_from_user()
if PLAY_AUDIO:
out_device = helper.get_output_device_from_user()
else:
out_device = helper.get_default_output_device_info()
# Setup streams
in_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_IN,
format=SAMPLE_TYPE,
frames_per_buffer=FRAMES_PER_BUF,
input=True,
input_device_index=int(in_device['index']),
stream_callback=read_in_data)
out_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_OUT,
format=SAMPLE_TYPE,
output=True,
frames_per_buffer=FRAMES_PER_BUF,
output_device_index=int(out_device['index']),
stream_callback=write_out_data)
# Start recording/playing back
in_stream.start_stream()
out_stream.start_stream()
# Start thread to check for user quit
quit_thread = threading.Thread(target=check_for_quit)
quit_thread.start()
# Plotting setup
if PLOT_CARTES:
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plt.show(block=False)
scat = []
if PLOT_SPACE:
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# Setup bounds
xlo, xhi = (-5, DISTANCE_TO_TEACHER + 5)
ylo, yhi = (-15, 15)
zlo, zhi = (-15, 5)
# Setup grid
nx, ny = (200, 100)
x = np.linspace(xlo, xhi, nx)
y = np.linspace(ylo, yhi, ny)
X, Y = np.meshgrid(x, y)
n, m = (STUDENT_NORMAL, STUDENT_OFFSET)
TP = (n.dot(m) - n[0] * X - n[1] * Y) / n[2] - 2
# Plot markers for mic
m = MIC_LOC
ax.plot([MIC_LOC[0]], [MIC_LOC[1]], [MIC_LOC[2]], 'r.', markersize=10.)
# Plot marker for camera
c = CAMERA_LOC
ax.plot([CAMERA_LOC[0]], [CAMERA_LOC[1]], [CAMERA_LOC[2]], 'b.', markersize=10.)
# Draw lines from camera and mic to source
source_loc = np.array([10, 0, 0])
source_point, = ax.plot([source_loc[0]], [source_loc[1]], [source_loc[2]], 'black', marker='.', markersize=10.)
s = source_loc
camera_dir, = ax.plot([c[0], m[0]], [c[1], m[1]], [c[2], m[2]], 'blue')
mic_dir, = ax.plot([m[0], m[0]], [m[1], m[1]], [m[2], m[2]], 'red')
#ax.plot_surface(X, Y, TP)
ax.set_xlim(xlo, xhi)
ax.set_ylim(ylo, yhi)
ax.set_zlim(zlo, zhi)
ax.view_init(elev=25, azim=-120)
plt.show(block=False)
if EXTERNAL_PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.show(block=False)
count = 0
prev_direc = np.array([0, 0, 0])
direcs = localizer.get_directions()
try:
global done
while in_stream.is_active() or out_stream.is_active():
data_available = in_buf.wait_for_read(WINDOW_LENGTH, TIMEOUT)
if data_available:
# Get data from the circular buffer
data = in_buf.read_samples(WINDOW_LENGTH)
# Perform an stft
stft.performStft(data)
# Process dfts from windowed segments of input
dfts = stft.getDFTs()
d = localizer.get_3d_real_distribution(dfts)
ind = np.argmax(d)
u = 1.5 * direcs[:, ind] # Direction of arrival
if DO_TRACK and count % TRACKING_FREQ == 0:
#v = np.array([1, 0, 1])
v = u
direc = space.get_camera_dir(v)
if not direc.any():
direc = prev_direc
else:
prev_direc = direc
# Send camera new direction
camera.face_direction(direc)
if PLOT_SPACE:
if direc.any():
src = space.get_source_loc(u)
source_point.set_xdata([src[0]])
source_point.set_ydata([src[1]])
source_point.set_3d_properties(zs=[src[2]])
cam_src = CAMERA_LOC + 30 * direc
mic_src = MIC_LOC + 30 * u
# Update camera line
camera_dir.set_xdata([CAMERA_LOC[0], cam_src[0]])
camera_dir.set_ydata([CAMERA_LOC[1], cam_src[1]])
camera_dir.set_3d_properties(zs=[CAMERA_LOC[2], cam_src[2]])
# Update mic line
mic_dir.set_xdata([MIC_LOC[0], mic_src[0]])
mic_dir.set_ydata([MIC_LOC[1], mic_src[1]])
mic_dir.set_3d_properties(zs=[MIC_LOC[2], mic_src[2]])
plt.draw()
# Take care of plotting
if count % 1 == 0:
if PLOT_CARTES:
plt.cla()
ax.scatter(direcs[0, :], direcs[1, :], direcs[2, :], s=30, c=d[:])
ax.plot([0, u[0]], [0, u[1]], [0, u[2]], c='blue')
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.set_zlim(0, 1)
plt.draw()
count += 1
# Get the istft of the processed data
if PLAY_AUDIO:
new_data = stft.performIStft()
new_data = out_buf.reduce_channels(new_data, NUM_CHANNELS_IN, NUM_CHANNELS_OUT)
# Write out the new, altered data
if out_buf.get_available_write() >= WINDOW_LENGTH:
out_buf.write_samples(new_data)
#time.sleep(.05)
except KeyboardInterrupt:
print "Program interrupted"
done = True
print "Cleaning up"
in_stream.stop_stream()
in_stream.close()
out_stream.stop_stream()
out_stream.close()
pa.terminate()
print "Done"
def localize():
# Setup pyaudio instances
pa = pyaudio.PyAudio()
helper = AudioHelper(pa)
localizer = DistributionLocalizer(mic_positions=mic_layout,
dft_len=FFT_LENGTH,
sample_rate=SAMPLE_RATE,
n_theta=N_THETA,
n_phi=N_PHI)
# Setup STFT object
stft = StftManager(dft_length=FFT_LENGTH,
window_length=WINDOW_LENGTH,
hop_length=HOP_LENGTH,
use_window_fcn=True,
n_channels=NUM_CHANNELS_IN,
dtype=DATA_TYPE)
# Setup devices
in_device = helper.get_input_device_from_user()
if PLAY_AUDIO:
out_device = helper.get_output_device_from_user()
else:
out_device = helper.get_default_output_device_info()
# Setup streams
in_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_IN,
format=SAMPLE_TYPE,
frames_per_buffer=FRAMES_PER_BUF,
input=True,
input_device_index=int(in_device['index']),
stream_callback=read_in_data)
out_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_OUT,
format=SAMPLE_TYPE,
output=True,
frames_per_buffer=FRAMES_PER_BUF,
output_device_index=int(out_device['index']),
stream_callback=write_out_data)
# Start recording/playing back
in_stream.start_stream()
out_stream.start_stream()
# Start thread to check for user quit
quit_thread = threading.Thread(target=check_for_quit)
quit_thread.start()
# Plotting setup
if PLOT_POLAR:
fig = plt.figure()
ax = fig.add_subplot(111, projection='polar')
ax.set_rlim(0, 1)
plt.show(block=False)
# Setup space for plotting in new coordinates
spher_coords = localizer.get_spher_directions()
theta = spher_coords[1, :]
pol_plot, = plt.plot(theta, np.ones(theta.shape))
ax.set_ylim(0, 1)
if EXTERNAL_PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.show(block=False)
count = 0
direcs = localizer.get_directions()
try:
global done
while in_stream.is_active() or out_stream.is_active():
data_available = in_buf.wait_for_read(WINDOW_LENGTH, TIMEOUT)
if data_available:
# Get data from the circular buffer
data = in_buf.read_samples(WINDOW_LENGTH)
# Perform an stft
stft.performStft(data)
# Process dfts from windowed segments of input
dfts = stft.getDFTs()
d = localizer.get_3d_real_distribution(dfts)
ind = np.argmax(d)
u = 1.5 * direcs[:, ind] # Direction of arrival
# Take car of plotting
if count % 1 == 0:
if PLOT_POLAR:
d = localizer.to_spher_grid(d)
d /= np.max(d)
pol_plot.set_ydata(d[0, :])
plt.draw()
count += 1
# Get the istft of the processed data
if PLAY_AUDIO:
new_data = stft.performIStft()
new_data = out_buf.reduce_channels(new_data,
NUM_CHANNELS_IN,
NUM_CHANNELS_OUT)
# Write out the new, altered data
if out_buf.get_available_write() >= WINDOW_LENGTH:
out_buf.write_samples(new_data)
#time.sleep(.05)
except KeyboardInterrupt:
print "Program interrupted"
done = True
print "Cleaning up"
in_stream.stop_stream()
in_stream.close()
out_stream.stop_stream()
out_stream.close()
pa.terminate()
print "Done"
def localize():
global switch_beamforming
global DO_BEAMFORM
# Setup pyaudio instances
pa = pyaudio.PyAudio()
helper = AudioHelper(pa)
localizer = DistributionLocalizer(mic_positions=mic_layout,
dft_len=FFT_LENGTH,
sample_rate=SAMPLE_RATE,
n_theta=N_THETA,
n_phi=N_PHI)
beamformer = BeamFormer(mic_layout, SAMPLE_RATE)
# Setup STFT object
stft = StftManager(dft_length=FFT_LENGTH,
window_length=WINDOW_LENGTH,
hop_length=HOP_LENGTH,
use_window_fcn=True,
n_channels=NUM_CHANNELS_IN,
dtype=DATA_TYPE)
# Setup devices
in_device = helper.get_input_device_from_user()
if PLAY_AUDIO:
out_device = helper.get_output_device_from_user()
else:
out_device = helper.get_default_output_device_info()
# Setup streams
in_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_IN,
format=SAMPLE_TYPE,
frames_per_buffer=FRAMES_PER_BUF,
input=True,
input_device_index=int(in_device['index']),
stream_callback=read_in_data)
out_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_OUT,
format=SAMPLE_TYPE,
output=True,
frames_per_buffer=FRAMES_PER_BUF,
output_device_index=int(out_device['index']),
stream_callback=write_out_data)
# Start recording/playing back
in_stream.start_stream()
out_stream.start_stream()
# Start thread to check for user quit
quit_thread = threading.Thread(target=check_for_quit)
quit_thread.start()
# Setup directions and alignment matrices
direcs = localizer.get_directions()
align_mats = localizer.get_pos_align_mat()
# Plotting setup
if PLOT_CARTES:
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plt.show(block=False)
x = localizer.to_spher_grid(direcs[0, :])
y = localizer.to_spher_grid(direcs[1, :])
z = localizer.to_spher_grid(direcs[2, :])
#scat = ax.scatter(x, y, z, s=100)
if PLOT_POLAR:
fig = plt.figure()
ax = fig.add_axes([.1, .1, .8, .8], projection='polar')
ax.set_rlim(0, 1)
plt.show(block=False)
# Setup space for plotting in new coordinates
spher_coords = localizer.get_spher_directions()
pol = localizer.to_spher_grid(spher_coords[2, :])
weight = 1. - .3 * np.sin(
2 * pol) # Used to pull visualization off edges
r = np.sin(pol) * weight
theta = localizer.to_spher_grid(spher_coords[1, :])
if EXTERNAL_PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.show(block=False)
count = 0
try:
global done
while in_stream.is_active() or out_stream.is_active():
data_available = in_buf.wait_for_read(WINDOW_LENGTH, TIMEOUT)
if data_available:
if switch_beamforming:
DO_BEAMFORM = not DO_BEAMFORM
switch_beamforming = False
# Get data from the circular buffer
data = in_buf.read_samples(WINDOW_LENGTH)
# Perform an stft
stft.performStft(data)
# Process dfts from windowed segments of input
dfts = stft.getDFTs()
rffts = mat.to_all_real_matlab_format(dfts)
d, energy = localizer.get_distribution_real(rffts[:, :, 0])
ind = np.argmax(d)
u = 1.5 * direcs[:, ind] # Direction of arrival
# Do beam forming
if DO_BEAMFORM:
align_mat = align_mats[:, :, ind]
filtered = beamformer.filter_real(rffts, align_mat)
mat.set_dfts_real(dfts, filtered, n_channels=2)
# Get beam plot
freq = 1500. # Hz
response = beamformer.get_beam(align_mat, align_mats,
rffts, freq)
response = localizer.to_spher_grid(response)
# Take car of plotting
if count % 1 == 0:
if PLOT_CARTES:
ax.cla()
ax.grid(False)
d = localizer.to_spher_grid(d /
(np.max(d) + consts.EPS))
ax.scatter(x, y, z, c=d, s=40)
#ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolor=plt.cm.gist_heat(d))
ax.plot([0, u[0]], [0, u[1]], [0, u[2]],
c='black',
linewidth=3)
if DO_BEAMFORM:
if np.max(np.abs(response)) > 1:
response /= np.max(np.abs(response))
X = response * x
Y = response * y
Z = response * z
ax.plot_surface(X,
Y,
Z,
rstride=1,
cstride=1,
color='white')
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.set_zlim(0, 1)
#ax.view_init(90, -90)
fig.canvas.draw()
if PLOT_POLAR:
plt.cla()
d = localizer.to_spher_grid(d)
con = ax.contourf(theta, r, d, vmin=0, vmax=40)
con.set_cmap('gist_heat')
if DO_BEAMFORM:
response = response[
-1, :] # Pick which polar angle sample to use
ax.plot(theta[0, :], response, 'cyan', linewidth=4)
ax.set_rlim(0, 1)
fig.canvas.draw()
count += 1
# Get the istft of the processed data
if PLAY_AUDIO or RECORD_AUDIO:
new_data = stft.performIStft()
new_data = out_buf.reduce_channels(new_data,
NUM_CHANNELS_IN,
NUM_CHANNELS_OUT)
# Write out the new, altered data
if PLAY_AUDIO:
if out_buf.get_available_write() >= WINDOW_LENGTH:
out_buf.write_samples(new_data)
if RECORD_AUDIO:
if record_buf.get_available_write() >= WINDOW_LENGTH:
record_buf.write_samples(new_data)
except KeyboardInterrupt:
print "Program interrupted"
done = True
print "Cleaning up"
in_stream.stop_stream()
in_stream.close()
out_stream.stop_stream()
out_stream.close()
pa.terminate()
# Take care of output file
if RECORD_AUDIO:
print "Writing output file"
make_wav()
print "Done"
def localize():
global switch_beamforming
global DO_BEAMFORM
# Setup pyaudio instances
pa = pyaudio.PyAudio()
helper = AudioHelper(pa)
localizer = DistributionLocalizer(mic_positions=mic_layout,
dft_len=FFT_LENGTH,
sample_rate=SAMPLE_RATE,
n_theta=N_THETA,
n_phi=N_PHI)
beamformer = BeamFormer(mic_layout, SAMPLE_RATE)
# Setup STFT object
stft = StftManager(dft_length=FFT_LENGTH,
window_length=WINDOW_LENGTH,
hop_length=HOP_LENGTH,
use_window_fcn=True,
n_channels=NUM_CHANNELS_IN,
dtype=DATA_TYPE)
# Setup devices
in_device = helper.get_input_device_from_user()
if PLAY_AUDIO:
out_device = helper.get_output_device_from_user()
else:
out_device = helper.get_default_output_device_info()
# Setup streams
in_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_IN,
format=SAMPLE_TYPE,
frames_per_buffer=FRAMES_PER_BUF,
input=True,
input_device_index=int(in_device['index']),
stream_callback=read_in_data)
out_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_OUT,
format=SAMPLE_TYPE,
output=True,
frames_per_buffer=FRAMES_PER_BUF,
output_device_index=int(out_device['index']),
stream_callback=write_out_data)
# Start recording/playing back
in_stream.start_stream()
out_stream.start_stream()
# Start thread to check for user quit
quit_thread = threading.Thread(target=check_for_quit)
quit_thread.start()
# Setup directions and alignment matrices
direcs = localizer.get_directions()
align_mats = localizer.get_pos_align_mat()
# Plotting setup
if PLOT_CARTES:
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plt.show(block=False)
x = localizer.to_spher_grid(direcs[0, :])
y = localizer.to_spher_grid(direcs[1, :])
z = localizer.to_spher_grid(direcs[2, :])
#scat = ax.scatter(x, y, z, s=100)
if PLOT_POLAR:
fig = plt.figure()
ax = fig.add_axes([.1, .1, .8, .8], projection='polar')
ax.set_rlim(0, 1)
plt.show(block=False)
# Setup space for plotting in new coordinates
spher_coords = localizer.get_spher_directions()
pol = localizer.to_spher_grid(spher_coords[2, :])
weight = 1. - .3 * np.sin(2 * pol) # Used to pull visualization off edges
r = np.sin(pol) * weight
theta = localizer.to_spher_grid(spher_coords[1, :])
if EXTERNAL_PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.show(block=False)
count = 0
try:
global done
while in_stream.is_active() or out_stream.is_active():
data_available = in_buf.wait_for_read(WINDOW_LENGTH, TIMEOUT)
if data_available:
if switch_beamforming:
DO_BEAMFORM = not DO_BEAMFORM
switch_beamforming = False
# Get data from the circular buffer
data = in_buf.read_samples(WINDOW_LENGTH)
# Perform an stft
stft.performStft(data)
# Process dfts from windowed segments of input
dfts = stft.getDFTs()
rffts = mat.to_all_real_matlab_format(dfts)
d, energy = localizer.get_distribution_real(rffts[:, :, 0])
ind = np.argmax(d)
u = 1.5 * direcs[:, ind] # Direction of arrival
# Do beam forming
if DO_BEAMFORM:
align_mat = align_mats[:, :, ind]
filtered = beamformer.filter_real(rffts, align_mat)
mat.set_dfts_real(dfts, filtered, n_channels=2)
# Get beam plot
freq = 1500. # Hz
response = beamformer.get_beam(align_mat, align_mats, rffts, freq)
response = localizer.to_spher_grid(response)
# Take car of plotting
if count % 1 == 0:
if PLOT_CARTES:
ax.cla()
ax.grid(False)
d = localizer.to_spher_grid(d / (np.max(d) + consts.EPS))
ax.scatter(x, y, z, c=d, s=40)
#ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolor=plt.cm.gist_heat(d))
ax.plot([0, u[0]], [0, u[1]], [0, u[2]], c='black', linewidth=3)
if DO_BEAMFORM:
if np.max(np.abs(response)) > 1:
response /= np.max(np.abs(response))
X = response * x
Y = response * y
Z = response * z
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, color='white')
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.set_zlim(0, 1)
#ax.view_init(90, -90)
fig.canvas.draw()
if PLOT_POLAR:
plt.cla()
d = localizer.to_spher_grid(d)
con = ax.contourf(theta, r, d, vmin=0, vmax=40)
con.set_cmap('gist_heat')
if DO_BEAMFORM:
response = response[-1, :] # Pick which polar angle sample to use
ax.plot(theta[0, :], response, 'cyan', linewidth=4)
ax.set_rlim(0, 1)
fig.canvas.draw()
count += 1
# Get the istft of the processed data
if PLAY_AUDIO or RECORD_AUDIO:
new_data = stft.performIStft()
new_data = out_buf.reduce_channels(new_data, NUM_CHANNELS_IN, NUM_CHANNELS_OUT)
# Write out the new, altered data
if PLAY_AUDIO:
if out_buf.get_available_write() >= WINDOW_LENGTH:
out_buf.write_samples(new_data)
if RECORD_AUDIO:
if record_buf.get_available_write() >= WINDOW_LENGTH:
record_buf.write_samples(new_data)
except KeyboardInterrupt:
print "Program interrupted"
done = True
print "Cleaning up"
in_stream.stop_stream()
in_stream.close()
out_stream.stop_stream()
out_stream.close()
pa.terminate()
# Take care of output file
if RECORD_AUDIO:
print "Writing output file"
make_wav()
print "Done"
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
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)
def localize():
global switch_beamforming
global DO_BEAMFORM
# Setup pyaudio instances
pa = pyaudio.PyAudio()
helper = AudioHelper(pa)
localizer = DistributionLocalizer(mic_positions=mic_layout,
dft_len=FFT_LENGTH,
sample_rate=SAMPLE_RATE,
n_theta=N_THETA,
n_phi=N_PHI)
beamformer = BeamFormer(mic_layout, SAMPLE_RATE)
# Setup STFT object
stft = StftManager(dft_length=FFT_LENGTH,
window_length=WINDOW_LENGTH,
hop_length=HOP_LENGTH,
use_window_fcn=True,
n_channels=NUM_CHANNELS_IN,
dtype=DATA_TYPE)
# Setup devices
in_device = helper.get_input_device_from_user()
if PLAY_AUDIO:
out_device = helper.get_output_device_from_user()
else:
out_device = helper.get_default_output_device_info()
# Setup streams
in_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_IN,
format=SAMPLE_TYPE,
frames_per_buffer=FRAMES_PER_BUF,
input=True,
input_device_index=int(in_device['index']),
stream_callback=read_in_data)
out_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_OUT,
format=SAMPLE_TYPE,
output=True,
frames_per_buffer=FRAMES_PER_BUF,
output_device_index=int(out_device['index']),
stream_callback=write_out_data)
# Start recording/playing back
in_stream.start_stream()
out_stream.start_stream()
# Start thread to check for user quit
quit_thread = threading.Thread(target=check_for_quit)
quit_thread.start()
# Setup directions and alignment matrices
direcs = localizer.get_directions()
align_mats = localizer.get_pos_align_mat()
# Plotting setup
if PLOT_POLAR:
fig = plt.figure()
ax = fig.add_subplot(111, projection='polar')
ax.set_rlim(0, 1)
plt.show(block=False)
# Setup space for plotting in new coordinates
spher_coords = localizer.get_spher_directions()
theta = spher_coords[1, :]
pol_plot, = plt.plot(theta, np.ones(theta.shape))
ax.set_ylim(0, 1)
if DO_BEAMFORM:
pol_beam_plot, = plt.plot(theta, np.ones(theta.shape), 'red')
if EXTERNAL_PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.show(block=False)
count = 0
try:
global done
while in_stream.is_active() or out_stream.is_active():
data_available = in_buf.wait_for_read(WINDOW_LENGTH, TIMEOUT)
if data_available:
if switch_beamforming:
DO_BEAMFORM = not DO_BEAMFORM
switch_beamforming = False
# Get data from the circular buffer
data = in_buf.read_samples(WINDOW_LENGTH)
# Perform an stft
stft.performStft(data)
# Process dfts from windowed segments of input
dfts = stft.getDFTs()
rffts = mat.to_all_real_matlab_format(dfts)
d, energy = localizer.get_distribution_real(rffts[:, :, 0], 'gcc') # Use first hop
print d
print "SIZE: " + str(d.shape)
ind = np.argmax(d)
u = 1.5 * direcs[:, ind] # Direction of arrival
# Do beam forming
if DO_BEAMFORM:
align_mat = align_mats[:, :, ind]
filtered = beamformer.filter_real(rffts, align_mat)
mat.set_dfts_real(dfts, filtered, n_channels=2)
# Take care of plotting
if count % 1 == 0:
if PLOT_POLAR:
#d -= np.min(d)
d = localizer.to_spher_grid(d)
#d /= np.max(d)
if np.max(d) > 1:
d /= np.max(d)
pol_plot.set_ydata(d[0, :])
if DO_BEAMFORM:
# Get beam plot
freq = 1000. # Hz
response = beamformer.get_beam(align_mat, align_mats, rffts, freq)
response = localizer.to_spher_grid(response)
if np.max(response) > 1:
response /= np.max(response)
pol_beam_plot.set_ydata(response[-1, :])
plt.draw()
count += 1
# Get the istft of the processed data
if PLAY_AUDIO or RECORD_AUDIO:
new_data = stft.performIStft()
new_data = out_buf.reduce_channels(new_data, NUM_CHANNELS_IN, NUM_CHANNELS_OUT)
# Write out the new, altered data
if PLAY_AUDIO:
if out_buf.get_available_write() >= WINDOW_LENGTH:
out_buf.write_samples(new_data)
if RECORD_AUDIO:
if record_buf.get_available_write() >= WINDOW_LENGTH:
record_buf.write_samples(new_data)
except KeyboardInterrupt:
print "Program interrupted"
done = True
print "Cleaning up"
in_stream.stop_stream()
in_stream.close()
out_stream.stop_stream()
out_stream.close()
pa.terminate()
# Take care of output file
if RECORD_AUDIO:
print "Writing output file"
make_wav()
print "Done"
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
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)
def localize():
global switch_beamforming
global DO_BEAMFORM
# Setup pyaudio instances
pa = pyaudio.PyAudio()
helper = AudioHelper(pa)
localizer = DistributionLocalizer(mic_positions=mic_layout,
dft_len=FFT_LENGTH,
sample_rate=SAMPLE_RATE,
n_theta=N_THETA,
n_phi=N_PHI)
beamformer = BeamFormer(mic_layout, SAMPLE_RATE)
# Setup STFT object
stft = StftManager(dft_length=FFT_LENGTH,
window_length=WINDOW_LENGTH,
hop_length=HOP_LENGTH,
use_window_fcn=True,
n_channels=NUM_CHANNELS_IN,
dtype=DATA_TYPE)
# Setup devices
in_device = helper.get_input_device_from_user()
if PLAY_AUDIO:
out_device = helper.get_output_device_from_user()
else:
out_device = helper.get_default_output_device_info()
# Setup streams
in_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_IN,
format=SAMPLE_TYPE,
frames_per_buffer=FRAMES_PER_BUF,
input=True,
input_device_index=int(in_device['index']),
stream_callback=read_in_data)
out_stream = pa.open(rate=SAMPLE_RATE,
channels=NUM_CHANNELS_OUT,
format=SAMPLE_TYPE,
output=True,
frames_per_buffer=FRAMES_PER_BUF,
output_device_index=int(out_device['index']),
stream_callback=write_out_data)
# Start recording/playing back
in_stream.start_stream()
out_stream.start_stream()
# Start thread to check for user quit
quit_thread = threading.Thread(target=check_for_quit)
quit_thread.start()
# Setup directions and alignment matrices
direcs = localizer.get_directions()
align_mats = localizer.get_pos_align_mat()
# Plotting setup
if PLOT_POLAR:
fig = plt.figure()
ax = fig.add_subplot(111, projection='polar')
ax.set_rlim(0, 1)
plt.show(block=False)
# Setup space for plotting in new coordinates
spher_coords = localizer.get_spher_directions()
theta = spher_coords[1, :]
pol_plot, = plt.plot(theta, np.ones(theta.shape))
ax.set_ylim(0, 1)
if DO_BEAMFORM:
pol_beam_plot, = plt.plot(theta, np.ones(theta.shape), 'red')
if EXTERNAL_PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.show(block=False)
count = 0
try:
global done
while in_stream.is_active() or out_stream.is_active():
data_available = in_buf.wait_for_read(WINDOW_LENGTH, TIMEOUT)
if data_available:
if switch_beamforming:
DO_BEAMFORM = not DO_BEAMFORM
switch_beamforming = False
# Get data from the circular buffer
data = in_buf.read_samples(WINDOW_LENGTH)
# Perform an stft
stft.performStft(data)
# Process dfts from windowed segments of input
dfts = stft.getDFTs()
rffts = mat.to_all_real_matlab_format(dfts)
d, energy = localizer.get_distribution_real(
rffts[:, :, 0], 'gcc') # Use first hop
print d
print "SIZE: " + str(d.shape)
ind = np.argmax(d)
u = 1.5 * direcs[:, ind] # Direction of arrival
# Do beam forming
if DO_BEAMFORM:
align_mat = align_mats[:, :, ind]
filtered = beamformer.filter_real(rffts, align_mat)
mat.set_dfts_real(dfts, filtered, n_channels=2)
# Take care of plotting
if count % 1 == 0:
if PLOT_POLAR:
#d -= np.min(d)
d = localizer.to_spher_grid(d)
#d /= np.max(d)
if np.max(d) > 1:
d /= np.max(d)
pol_plot.set_ydata(d[0, :])
if DO_BEAMFORM:
# Get beam plot
freq = 1000. # Hz
response = beamformer.get_beam(
align_mat, align_mats, rffts, freq)
response = localizer.to_spher_grid(response)
if np.max(response) > 1:
response /= np.max(response)
pol_beam_plot.set_ydata(response[-1, :])
plt.draw()
count += 1
# Get the istft of the processed data
if PLAY_AUDIO or RECORD_AUDIO:
new_data = stft.performIStft()
new_data = out_buf.reduce_channels(new_data,
NUM_CHANNELS_IN,
NUM_CHANNELS_OUT)
# Write out the new, altered data
if PLAY_AUDIO:
if out_buf.get_available_write() >= WINDOW_LENGTH:
out_buf.write_samples(new_data)
if RECORD_AUDIO:
if record_buf.get_available_write() >= WINDOW_LENGTH:
record_buf.write_samples(new_data)
except KeyboardInterrupt:
print "Program interrupted"
done = True
print "Cleaning up"
in_stream.stop_stream()
in_stream.close()
out_stream.stop_stream()
out_stream.close()
pa.terminate()
# Take care of output file
if RECORD_AUDIO:
print "Writing output file"
make_wav()
print "Done"