def filter_dart(line):
# append newest sample
for i, sample in enumerate(line):
input_buffers[i].append(sample)
if len(input_buffers[0]) == BUFFER_SIZE:
for i in range(N_MIC):
output_buffers[i] = filtering_utils.process(
input_buffers[i], LOW_FREQ, HIGH_FREQ)
fresh_buffers(input_buffers)
if output_buffers[0]:
output = [buf[len(input_buffers[0]) - (BUFFER_SIZE/4)]
for buf in output_buffers]
pipe_util.join_output("dd", output)
#filtered_graph = fig.add_subplot(grid + 5)
#filteredfft_graph = fig.add_subplot(grid + 6)
harmonic_pattern = [(10 - i) / 10. for i in range(10)]
signal = make_signal(1900, harmonic_pattern)
noisy = add_noise(signal, 0.4)
filtered = violent_multi_band_pass(noisy, prepare_multi_band_filter([(1500, 2500)]))
mask = make_mask_for_signal(noisy, 1000, 2500, 0.05)
multifiltered = violent_multi_band_pass(noisy, mask)
plot(signal, sig_graph, fft_graph)
plot(noisy, noisy_graph, noisyfft_graph)
#plot(filtered, filtered_graph, filteredfft_graph)
plot(multifiltered, multifiltered_graph, multifilteredfft_graph)
plt.show()
def draw_signal(signal):
fig = plt.figure()
grid = 210
sig_graph = fig.add_subplot(grid + 1)
fft_graph = fig.add_subplot(grid + 2)
plot(signal, sig_graph, fft_graph)
plt.show()
if __name__ == '__main__':
for value in sine(DART_FREQ_HERTZ, 10000):
values = [value] * CHANNEL_COUNT
join_output(ZERO_DETECTION_INPUT_FORMAT, values)
mic_positions = mic_positions - origin
for time__mic_dart_distances in time__mic_dart_distances_stream:
time_seconds = time__mic_dart_distances[0]
mic_dart_distances = array(time__mic_dart_distances[1:])
# The algorithm fails on any 0 - m distance degeneracies. Add some
# wiggle if so.
degeneracies = (mic_dart_distances[1:] == mic_dart_distances[0])
mic_dart_distances[1:] += 1.0e-12 * degeneracies
vt = mic_dart_distances - mic_dart_distances[0]
free_vt = vt[2:]
A = 2.0 * mic_positions[2:, 0] / free_vt - 2.0 * mic_positions[1, 0] / vt[1]
B = 2.0 * mic_positions[2:, 1] / free_vt - 2.0 * mic_positions[1, 1] / vt[1]
C = 2.0 * mic_positions[2:, 2] / free_vt - 2.0 * mic_positions[1, 2] / vt[1]
D = free_vt - vt[1] - sum(mic_positions[2:, :] ** 2, axis=1) / free_vt + sum(mic_positions[1] ** 2) / vt[1]
M = concatenate([transpose_1D(A), transpose_1D(B), transpose_1D(C)], axis=1)
try:
yield time_seconds, pinv(M).dot(-transpose_1D(D)).reshape(3) + origin
except LinAlgError:
sys.stderr.write('Could not multilaterate at t = %f\n' % time_seconds)
if __name__ == '__main__':
for time_seconds, coordinates in multilaterate(MIC_COORDS_METERS, split_fileinput(MULTILATERATE_INPUT_FORMAT)):
join_output(DISPLAY_INPUT_FORMAT, [time_seconds] + list(coordinates))
multifiltered_graph = fig.add_subplot(grid + 7)
multifilteredfft_graph = fig.add_subplot(grid + 8)
noisy = add_noise(signal, 0.5)
filtered = violent_multi_band_pass(noisy, prepare_multi_band_filter([(1500, 2500)]))
mask = make_mask_for_signal(noisy, 1500, 3000, 0.05)
multifiltered = violent_multi_band_pass(noisy, mask)
plot(signal, sig_graph, fft_graph)
plot(noisy, noisy_graph, noisyfft_graph)
plot(filtered, filtered_graph, filteredfft_graph)
plot(multifiltered, multifiltered_graph, multifilteredfft_graph)
plt.show()
# f = scipy.fft(noisy)[:BUFFER_SIZE/2]
# plt.plot(noisy)
# plt.show()
# plt.plot(f)
# plt.show()
# max_index, max_value = max(enumerate(f), key=lambda x:x[1]
# if freq_from_index(x[0])>200 else 0)
# print "Freq:", freq_from_index(max_index)
if __name__ == '__main__':
for timestep, value in enumerate(sine(DART_FREQ_HERTZ, 10000)):
join_output([value] * CHANNELS)
WAVELENGTH_SAMPLES = SAMPLE_RATE_HERTZ / DART_FREQ_HERTZ def zero_detection(sample_stream): """Make events for 0-crossings. sample_stream must be a generator of CHANNEL_COUNT-tuples of values that represent the current microphone level. Yields channel ID, time tuples. """ last_samples_sign = None samples_since_zero = array([WAVELENGTH_SAMPLES] * CHANNEL_COUNT) for timestep, samples in enumerate(sample_stream): samples_sign = signbit(samples) if last_samples_sign is not None: sign_changes = logical_and(samples_sign, ~last_samples_sign) sign_changes = logical_and(sign_changes, samples_since_zero > 2 * WAVELENGTH_SAMPLES / 3) for channel in nonzero(sign_changes)[0]: yield channel, timestep / float(SAMPLE_RATE_HERTZ) samples_since_zero[sign_changes] = 0 samples_since_zero[~sign_changes] += 1 last_samples_sign = samples_sign if __name__ == '__main__': for channel, event_time_seconds in zero_detection(split_fileinput(ZERO_DETECTION_INPUT_FORMAT)): join_output(ALIGN_INPUT_FORMAT, (channel, event_time_seconds))
Yields time, 3D coords of dart. """ mic_positions = array(mic_positions) origin = mic_positions[0] mic_positions = mic_positions - origin for time__mic_dart_distances in time__mic_dart_distances_stream: time = time__mic_dart_distances[0] mic_dart_distances = array(time__mic_dart_distances[1:]) # The algorithm fails on any 0 - m distance degeneracies. Add some wiggle if so. while any(mic_dart_distances[1:] == mic_dart_distances[0]): mic_dart_distances[1:] += 1.0e-12 vt = mic_dart_distances - mic_dart_distances[0] free_vt = vt[2:] A = 2.0 * mic_positions[2:, 0] / free_vt - 2.0 * mic_positions[1, 0] / vt[1] B = 2.0 * mic_positions[2:, 1] / free_vt - 2.0 * mic_positions[1, 1] / vt[1] C = 2.0 * mic_positions[2:, 2] / free_vt - 2.0 * mic_positions[1, 2] / vt[1] D = free_vt - vt[1] - sum(mic_positions[2:, :] ** 2, axis=1) / free_vt + sum(mic_positions[1] ** 2) / vt[1] M = concatenate([transpose_1D(A), transpose_1D(B), transpose_1D(C)], axis=1) yield time, pinv(M).dot(-transpose_1D(D)).reshape(3) + origin if __name__ == '__main__': for time, coordinates in multilaterate(MIC_COORDS, split_fileinput([float] + [float] * CHANNELS)): join_output([time] + list(coordinates))
from numpy import signbit from numpy import logical_xor from pipe_util import split_fileinput from pipe_util import join_output from world_params import CHANNELS from world_params import SAMPLE_RATE_HERTZ def generate_events(sample_stream): """Make events for 0-crossings. sample_stream must be a generator of CHANNELS-tuples of values that represent the current microphone level. Yields channel ID, time tuples. """ last_samples_sign = None for timestep, samples in enumerate(sample_stream): samples_sign = signbit(samples) if last_samples_sign is not None: sign_changes = logical_xor(last_samples_sign, samples_sign) for channel, sign_change in enumerate(sign_changes): if sign_change: yield channel, float(timestep) / float(SAMPLE_RATE_HERTZ) last_samples_sign = samples_sign if __name__ == '__main__': for channel_event_t in generate_events(split_fileinput([float] * CHANNELS)): join_output(channel_event_t)
vt = mic_dart_distances - mic_dart_distances[0]
free_vt = vt[2:]
A = 2.0 * mic_positions[2:, 0] / free_vt - 2.0 * mic_positions[
1, 0] / vt[1]
B = 2.0 * mic_positions[2:, 1] / free_vt - 2.0 * mic_positions[
1, 1] / vt[1]
C = 2.0 * mic_positions[2:, 2] / free_vt - 2.0 * mic_positions[
1, 2] / vt[1]
D = free_vt - vt[1] - sum(mic_positions[
2:, :]**2, axis=1) / free_vt + sum(mic_positions[1]**2) / vt[1]
M = concatenate([transpose_1D(A),
transpose_1D(B),
transpose_1D(C)],
axis=1)
try:
yield time_seconds, pinv(M).dot(-transpose_1D(D)).reshape(
3) + origin
except LinAlgError:
sys.stderr.write('Could not multilaterate at t = %f\n' %
time_seconds)
if __name__ == '__main__':
for time_seconds, coordinates in multilaterate(
MIC_COORDS_METERS, split_fileinput(MULTILATERATE_INPUT_FORMAT)):
join_output(DISPLAY_INPUT_FORMAT, [time_seconds] + list(coordinates))
# Check to see if any peaks could be missing at this point. This # should be detectable as an empty channel queue. if (allow_dropped_events and detect_missed_event( event_time_seconds, time_seconds_queues, MAX_MIC_DELAY_SECONDS )): for time_seconds_queue in time_seconds_queues: if len(time_seconds_queue) < 1: time_seconds_queue.append(None) # If we've seen a peak on every channel, if all( len(time_seconds_queue) > 0 for time_seconds_queue in time_seconds_queues ): # yield all those relative times. yield time_seconds_to_time_seconds_distances(tuple( # Out on the left. time_seconds_queue.popleft() for time_seconds_queue in time_seconds_queues )) if __name__ == '__main__': for time_seconds, aligned_distances in align(split_fileinput(ALIGN_INPUT_FORMAT)): join_output(MULTILATERATE_INPUT_FORMAT, [time_seconds] + aligned_distances)
def zero_detection(sample_stream):
"""Make events for 0-crossings.
sample_stream must be a generator of CHANNEL_COUNT-tuples of values that
represent the current microphone level.
Yields channel ID, time tuples.
"""
last_samples_sign = None
samples_since_zero = array([WAVELENGTH_SAMPLES] * CHANNEL_COUNT)
for timestep, samples in enumerate(sample_stream):
samples_sign = signbit(samples)
if last_samples_sign is not None:
sign_changes = logical_and(samples_sign, ~last_samples_sign)
sign_changes = logical_and(
sign_changes, samples_since_zero > 2 * WAVELENGTH_SAMPLES / 3)
for channel in nonzero(sign_changes)[0]:
yield channel, timestep / float(SAMPLE_RATE_HERTZ)
samples_since_zero[sign_changes] = 0
samples_since_zero[~sign_changes] += 1
last_samples_sign = samples_sign
if __name__ == '__main__':
for channel, event_time_seconds in zero_detection(
split_fileinput(ZERO_DETECTION_INPUT_FORMAT)):
join_output(ALIGN_INPUT_FORMAT, (channel, event_time_seconds))