def __init__(self, min_hunt, max_hunt, min_range, low_per_mil, high_per_mil, start_window, start_count, stop_window, stop_count):
assert high_per_mil > low_per_mil
assert min_range > 0
assert start_window > start_count
assert stop_window > stop_count
self.tracker = RangeTracker(min_hunt, max_hunt)
self.data = low_per_mil / 1000, high_per_mil / 1000, min_range, start_window, start_count, stop_window, stop_count
dprint('UtteranceTagger', '__init__:', min_hunt, max_hunt, *self.data)
count = 0
self.state = BAC, count, deque()
def __init__(self, min_hunt, max_hunt, min_range, low_per_mil,
high_per_mil, start_window, start_count, stop_window,
stop_count):
assert high_per_mil > low_per_mil
assert min_range > 0
assert start_window > start_count
assert stop_window > stop_count
self.tracker = RangeTracker(min_hunt, max_hunt)
self.data = low_per_mil / 1000, high_per_mil / 1000, min_range, start_window, start_count, stop_window, stop_count
dprint('UtteranceTagger', '__init__:', min_hunt, max_hunt, *self.data)
count = 0
self.state = BAC, count, deque()
def __call__(self, data):
# empirically, (and interestingly): this (near 16-bit) shift factor lets
# the exposed ref property be 1 while giving occasional 0 dB output on a
# Mac with "Use ambient noise reduction" set to on and "Input volume"
# slider set to the minimum (settings which give about the lowest level
# signal data you can get on the mac)
ref_factor = N.float32(1 / (1 << 18))
# this should be an adequate range of dBs
clip_lo, clip_hi = 0, 140
assert data.shape[-1] == self.data_length
band = data[self.select]
assert len(band) >= 1
ref = N.float32(self.ref * len(band) * ref_factor)
band *= band
bandsum = band.sum()
# XXX not ndarrays....
sum = float(bandsum)
if False:
# slight smoothing; bizarre: causes Python ncurses to bog down!
sum = (self.prev + sum) / 2
self.prev = sum
# space is 10 * log10 (energy)
dB = (10 * math.log10(sum / ref)) if sum > ref else 0
dB = max(clip_lo, dB)
dB = min(clip_hi, dB)
dcheck(vumeterlog) and dprint(vumeterlog, 'dB', N.float32(dB), 'channels', len(band), 'ref', self.ref, 'scaled_ref', ref, 'energy', bandsum)
# we return the dB in decibel scaling
return dB
def ddt_accum(value):
event0, event1 = value
assert event0[0] == event1[0]
data0 = event0[1]
data1 = event1[1]
assert len(data0) == len(data1) == 2
line_len = 255
line = [' '] * line_len
offset = line_len // 4
label = event0[0]
label_stats[0] += 1
if label == True:
label_stats[1] += 1
else:
assert label == False
if data0[0][1] == label:
accuracy_stats[0] += 1
if data1[0][1] == label:
accuracy_stats[1] += 1
global last_label
if label != last_label:
dprint('ddt_accum', label)
dprint('ddt_accum', ' ', label_stats, accuracy_stats)
last_label = label
if data0[0][1] == True:
c0True = data0[0][0]
c0False = data0[1][0]
else:
assert data0[0][1] == False
c0True = data0[1][0]
c0False = data0[0][0]
if data1[0][1] == True:
c1True = data1[0][0]
c1False = data1[1][0]
else:
assert data1[0][1] == False
c1True = data1[1][0]
c1False = data1[0][0]
llrTrue = math.log(c0True / c1True)
llrFalse = math.log(c0False / c1False)
if llrTrue > 0:
ddt_sums[0] += 1
elif llrTrue < 0:
ddt_sums[0] -= 1
else:
pass
if llrFalse > 0:
ddt_sums[1] += 1
elif llrFalse < 0:
ddt_sums[1] -= 1
else:
pass
def clip(val, scale):
val = int(val * scale) + offset
val = max(0, val)
val = min(line_len-1, val)
return val
indexTrue = clip(llrTrue, ddt_scale)
indexFalse = clip(llrFalse, ddt_scale)
line[indexTrue] = '*'
line[indexFalse] = '|'
indexTrue = clip(ddt_sums[0], ddt_accum_scale)
indexFalse = clip(ddt_sums[1], ddt_accum_scale)
line[indexTrue] = '0'
line[indexFalse] = 'X'
line.append('\n')
displaystream2.write(''.join(line))