def decodeInitialization(chunk, rate=96000.0):
settings = {}
diffs = at.findTdiffs(chunk, rate=rate)
params = np.load("initialization_settings.npz")
# Decode channel
# Calculate square error of received time distances with reference
ch_times = diffs[0:2]
dists = np.power(params['channels'] - ch_times, 2).sum(1)
# TODO: Probably error message if minimum distance is too large
# Assume the group with smallest error
settings['channel'] = dists.argmin() + 1
# Read intermediate, though not used here at the moment
inter_dist = np.power(params['intermediate'] - diffs[2:5], 2).sum()
# TODO: Probably error message if distance is too large
# Read group settings
settings['group'] = np.array([])
pos = 5
length = diffs.shape[0]
while pos < (length - 1):
if length - pos == 2:
# Last presence pulse
# Calculate distance, though not used here at the moment
dist = np.power(params['grp_present'][0:2] - diffs[pos:pos + 2],
2).sum()
settings['group'] = np.append(settings['group'], True)
pos += 2
else:
# There is more than one group remaining
dist_present = np.power(params['grp_present'] - diffs[pos:pos + 3],
2).sum()
dist_absent = np.power(params['grp_absent'] - diffs[pos], 2)
if dist_present < dist_absent:
settings['group'] = np.append(settings['group'], True)
pos += 3
else:
settings['group'] = np.append(settings['group'], False)
pos += 1
return settings
def decodeInitialization(chunk, rate=96000.0):
settings = {}
diffs = at.findTdiffs(chunk, rate=rate)
params = np.load("initialization_settings.npz")
# Decode channel
# Calculate square error of received time distances with reference
ch_times = diffs[0:2]
dists = np.power(params['channels'] - ch_times, 2).sum(1)
# TODO: Probably error message if minimum distance is too large
# Assume the group with smallest error
settings['channel'] = dists.argmin() + 1
# Read intermediate, though not used here at the moment
inter_dist = np.power(params['intermediate'] - diffs[2:5], 2).sum()
# TODO: Probably error message if distance is too large
# Read group settings
settings['group'] = np.array([])
pos = 5
length = diffs.shape[0]
while pos < (length - 1):
if length - pos == 2:
# Last presence pulse
# Calculate distance, though not used here at the moment
dist = np.power(params['grp_present'][0:2] - diffs[pos:pos+2], 2).sum()
settings['group'] = np.append(settings['group'], True)
pos += 2
else:
# There is more than one group remaining
dist_present = np.power(params['grp_present'] - diffs[pos:pos+3], 2).sum()
dist_absent = np.power(params['grp_absent'] - diffs[pos], 2)
if dist_present < dist_absent:
settings['group'] = np.append(settings['group'], True)
pos += 3
else:
settings['group'] = np.append(settings['group'], False)
pos += 1
return settings
wavs.append(al.wavread("Samples/Ch1_G2_M128_NoMaster_NoFlashPresent_sb900.wav")[0][:,0])
wavs.append(al.wavread("Samples/Ch1_G3_M128_NoMaster_NoFlashPresent_sb900.wav")[0][:,0])
wavs.append(al.wavread("Samples/Ch1_G1_M128_G2_M128_NoMaster_NoFlashPresent_sb900.wav")[0][:,0])
wavs.append(al.wavread("Samples/Ch1_G1_M128_G3_M128_NoMaster_NoFlashPresent_sb900.wav")[0][:,0])
wavs.append(al.wavread("Samples/Ch1_G2_M128_G3_M128_NoMaster_NoFlashPresent_sb900.wav")[0][:,0])
wavs.append(al.wavread("Samples/Ch1_G1_M128_G2_M128_G3_M128_NoMaster_NoFlashPresent_sb900.wav")[0][:,0])
N = len(wavs)
chunks = [];
bl1 = [];
td1 = [];
for wav in wavs:
nc = tools.findChunks(wav, 1000.0, 0.1)
chunks.append(nc)
bl1.append(wav[nc[0].start:nc[0].end]);
td1.append(tools.findTdiffs(bl1[-1]));
# Calculate average tdiffs for the next three blocks
tdb1 = 0.0
tdb2 = 0.0
tdb3 = 0.0
for td in td1:
tdb1 = tdb1 + td[2]
tdb2 = tdb2 + td[3]
tdb3 = tdb3 + td[4]
tdb1 = (tdb1 / N);
tdb2 = (tdb2 / N);
tdb3 = (tdb3 / N);
# Calculate average tdiffs for Group Present pulse information
#wavs.append(al.wavread("Samples/Ch1_G1_TTL+3.0_NoMaster_NoFlashPresent_d7000.wav")[0][:,0])
#wavs.append(al.wavread("Samples/Ch1_G1_AA-3.0_NoMaster_NoFlashPresent_d7000.wav")[0][:,0])
#wavs.append(al.wavread("Samples/Ch1_G1_AA_0_NoMaster_NoFlashPresent_d7000.wav")[0][:,0])
wavs.append(tools.normalize(al.wavread("Samples/Ch1_G1_AA+3.0_NoMaster_NoFlashPresent_d7000.wav")[0][:,0]))
wavs.append(tools.normalize(al.wavread("Samples/Ch1_G1_TTL_0_G2_TTL_0_NoMaster_NoFlashPresent_d7000.wav")[0][:,0]))
wavs.append(tools.normalize(al.wavread("Samples/Ch1_G1_TTL_0_G2_TTL_0_G3_TTL_0_NoMaster_NoFlashPresent_d7000.wav")[0][:,0]))
wavs.append(tools.normalize(al.wavread("Samples/Ch1_G1_M32_G2_TTL_0_G3_TTL_0_NoMaster_NoFlashPresent_sb900.wav")[0][:,0]))
wavs.append(tools.normalize(al.wavread("Samples/Ch1_G1_M32_G2_M32_G3_TTL_0_NoMaster_NoFlashPresent_sb900.wav")[0][:,0]))
wavs.append(tools.normalize(al.wavread("Samples/Ch1_G1_M32_G2_TTL_0_G3_M32_NoMaster_NoFlashPresent_sb900.wav")[0][:,0]))
wavs.append(tools.normalize(al.wavread("Samples/Ch1_G1_TTL_0_G2_M32_G3_M32_NoMaster_NoFlashPresent_sb900.wav")[0][:,0]))
N = len(wavs);
# Extract the second chunk of every data block
chunks = [tools.findChunks(wav, 2500.0, 0.1) for wav in wavs]
bl2 = [wav[c[1].start:c[1].end] for (wav, c) in zip(wavs, chunks)]
td2 = [tools.findTdiffs(bl) for bl in bl2]
pl2 = [tools.findPulses(bl) for bl in bl2]
plnorm = [p - p[0] for p in pl2]
pl.plot(wavs[-1])
pl.show()
# Group pulses
corr = tools.groupPulses(plnorm)
# Plot result
pl.figure()
pl.hold(True)
for i in range(N):
pl.plot(corr[i], i * np.ones(len(corr[i])), 'bx')
