#
# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import numpy as np
import lc3
import tables as T, appendix_c as C
import bwdet as m_bwdet
import ltpf as m_ltpf
import sns as m_sns
import tns as m_tns
### ------------------------------------------------------------------------ ###
class SpectrumQuantization:
def __init__(self, dt, sr):
self.dt = dt
self.sr = sr
def get_gain_offset(self, nbytes):
sr_ind = self.sr if self.sr < T.SRATE_48K_HR \
else 4 + (self.sr - T.SRATE_48K_HR)
g_off = (nbytes * 8) // (10 * (1 + sr_ind))
g_off = -min(115, g_off) - (105 + 5*(1 + sr_ind))
if self.sr >= T.SRATE_48K_HR:
g_off = max(g_off, -181)
return g_off
def get_noise_indices(self, bw, xq, lastnz):
nf_start = [ 6, 12, 18, 24 ][self.dt]
nf_width = [ 1, 1, 2, 3 ][self.dt]
bw_stop = T.I[self.dt][min(bw, T.SRATE_48K)][-1]
xq = np.append(xq[:lastnz], np.zeros(len(xq) - lastnz))
xq[:nf_start-nf_width] = 1
return [ np.all(xq[max(k-nf_width, 0):min(k+nf_width+1, bw_stop)] == 0)
for k in range(bw_stop) ]
class SpectrumAnalysis(SpectrumQuantization):
def __init__(self, dt, sr):
super().__init__(dt, sr)
self.reset_off = 0
self.nbits_off = 0
self.nbits_spec = 0
self.nbits_est = 0
(self.g_idx, self.noise_factor, self.xq, self.lastnz,
self.nbits_residual_max, self.xg) = \
(None, None, None, None, None, None)
def estimate_gain(self, x, nbytes, nbits_spec, nbits_off, g_off):
nbits = int(nbits_spec + nbits_off + 0.5)
### Energy (dB) by 4 MDCT coefficients
hr = (self.sr >= T.SRATE_48K_HR)
nf = 0
if hr:
dt = self.dt
sr = self.sr
dt_ms = T.DT_MS[dt]
bitrate = (8 * nbytes / (dt_ms * 1e-3)).astype(int)
C = [ [ -6, 0, None, 2 ], [ -6, 0, None, 5 ] ]
reg_bits = np.clip(
bitrate // 12500 + C[sr - T.SRATE_48K_HR][dt], 6, 23)
M0 = np.sum(np.abs(x)) + 1e-5
M1 = np.sum(np.arange(len(x)) * np.abs(x)) + 1e-5
low_bits = (4 / dt_ms) * (2*dt_ms - min(M0/M1, 2*dt_ms))
nf = np.max(np.abs(x)) * np.exp2(-reg_bits - low_bits)
e = [ np.sum(x[4*k:4*(k+1)] ** 2) for k in range(len(x) // 4) ]
e = 10 * np.log10(2**-31 + np.array(e) + nf)
### Compute gain index
g_idx = 255
for i in range(8):
factor = 1 << (7 - i)
g_idx -= factor
tmp = 0
iszero = 1
for ei in e[-1::-1]:
if ei * 28/20 < g_idx + g_off:
if iszero == 0:
tmp += 2.7*28/20
else:
if g_idx + g_off < (ei - 43) * 28/20:
tmp += 2*ei*28/20 - 2*(g_idx + g_off) - 36*28/20
else:
tmp += ei*28/20 - (g_idx + g_off) + 7*28/20
iszero = 0
if tmp > nbits * 1.4 * 28/20 and iszero == 0:
g_idx += factor
### Limit gain index
x_max = np.amax(np.abs(x))
if x_max > 0:
x_lim = [ 2**15 - 0.375, 2**23 ][hr]
g_min = 28 * np.log10(x_max / x_lim)
g_min = np.ceil(g_min).astype(int) - g_off
reset_off = g_idx < g_min
else:
g_min = 0
reset_off = True
if reset_off:
g_idx = g_min
return (g_min, g_idx + g_off, reset_off)
def quantize(self, g_int, x):
xg = x / 10 ** (g_int / 28)
hr = (self.sr >= T.SRATE_48K_HR)
offset = [ 0.375, 0.5 ][hr]
xq_min = [ -(2**15) , -(2**23) ][hr]
xq_max = [ (2**15)-1, (2**23)-1 ][hr]
xq = np.where(xg < 0, np.ceil(xg - offset), np.floor(xg + offset))
xq = xq.astype(np.int32)
xq = np.fmin(np.fmax(xq, xq_min), xq_max)
nz_pairs = np.any([ xq[::2] != 0, xq[1::2] != 0 ], axis=0)
lastnz = len(xq) - 2 * np.argmax(nz_pairs[-1::-1])
if not np.any(nz_pairs):
lastnz = 0
return (xg, xq, lastnz)
def compute_nbits(self, nbytes, x, lastnz, nbits_spec):
mode = [ 0, 1 ][int(self.sr < T.SRATE_96K_HR and \
nbytes >= 20 * (3 + min(self.sr, T.SRATE_48K)))]
rate = [ 0, 512 ][int(self.sr < T.SRATE_96K_HR and \
nbytes > 20 * (1 + min(self.sr, T.SRATE_48K)))]
nbits_est = 0
nbits_trunc = 0
nbits_lsb = 0
lastnz_trunc = 2
c = 0
for n in range(0, lastnz, 2):
t = c + rate
if n > len(x) // 2:
t += 256
a = abs(x[n ])
b = abs(x[n+1])
lev = 0
while max(a, b) >= 4:
nbits_est += \
T.AC_SPEC_BITS[T.AC_SPEC_LOOKUP[t + lev*1024]][16]
if lev == 0 and mode == 1:
nbits_lsb += 2
else:
nbits_est += 2 * 2048
a >>= 1
b >>= 1
lev = min(lev + 1, 3)
nbits_est += \
T.AC_SPEC_BITS[T.AC_SPEC_LOOKUP[t + lev*1024]][a + 4*b]
a_lsb = abs(x[n ])
b_lsb = abs(x[n+1])
nbits_est += (min(a_lsb, 1) + min(b_lsb, 1)) * 2048
if lev > 0 and mode == 1:
a_lsb >>= 1
b_lsb >>= 1
nbits_lsb += int(a_lsb == 0 and x[n ] != 0)
nbits_lsb += int(b_lsb == 0 and x[n+1] != 0)
if (x[n] != 0 or x[n+1] != 0) and \
(nbits_est <= nbits_spec * 2048):
lastnz_trunc = n + 2
nbits_trunc = nbits_est
t = 1 + (a + b) * (lev + 1) if lev <= 1 else 12 + lev
c = (c & 15) * 16 + t
nbits_est = (nbits_est + 2047) // 2048 + nbits_lsb
nbits_trunc = (nbits_trunc + 2047) // 2048
self.rate = rate
self.lsb_mode = mode == 1 and nbits_est > nbits_spec
return (nbits_est, nbits_trunc, lastnz_trunc, self.lsb_mode)
def adjust_gain(self, g_idx, nbits, nbits_spec):
T1 = [ 80, 230, 380, 530, 680, 680, 830 ]
T2 = [ 500, 1025, 1550, 2075, 2600, 2600, 3125 ]
T3 = [ 850, 1700, 2550, 3400, 4250, 4250, 5100 ]
dt = self.dt
sr = self.sr
if nbits < T1[sr]:
delta = (nbits + 48) / 16
elif nbits < T2[sr]:
a = T1[sr] / 16 + 3
b = T2[sr] / 48
delta = a + (nbits - T1[sr]) * (b - a) / (T2[sr] - T1[sr])
elif nbits < T3[sr]:
delta = nbits / 48
else:
delta = T3[sr] / 48
delta = np.fix(delta + 0.5).astype(int)
if self.sr >= T.SRATE_48K_HR and \
(g_idx < 255 and nbits > nbits_spec):
factor = [ 3 + (nbits >= 520), 2, 0, 1 ][dt]
g_incr = int(factor * (1 + (nbits - nbits_spec) / delta))
return min(g_idx + g_incr, 255) - g_idx
elif self.sr < T.SRATE_48K_HR and \
( (g_idx < 255 and nbits > nbits_spec) or \
(g_idx > 0 and nbits < nbits_spec - (delta + 2)) ):
if nbits < nbits_spec - (delta + 2):
return -1
if g_idx == 254 or nbits < nbits_spec + delta:
return 1
else:
return 2
return 0
def estimate_noise(self, bw, xq, lastnz, x):
i_nf = self.get_noise_indices(bw, xq, lastnz)
l_nf = sum(abs(x[:len(i_nf)] * i_nf)) / sum(i_nf) \
if sum(i_nf) > 0 else 0
return min(max(np.rint(8 - 16 * l_nf).astype(int), 0), 7)
def run(self, bw, nbytes, nbits_bw, nbits_ltpf, nbits_sns, nbits_tns, x):
sr = self.sr
### Bit budget
hr = self.sr >= T.SRATE_48K_HR
nbits_gain = 8
nbits_nf = 3
nbits_ari = np.ceil(np.log2(len(x) / 2)).astype(int)
nbits_ari += 3 + int(hr) + min((8*nbytes - 1) // 1280, 2)
nbits_spec = 8*nbytes - \
nbits_bw - nbits_ltpf - nbits_sns - nbits_tns - \
nbits_gain - nbits_nf - nbits_ari
### Global gain estimation
nbits_off = self.nbits_off + self.nbits_spec - self.nbits_est
nbits_off = min(40, max(-40, nbits_off))
nbits_off = 0 if self.reset_off else \
0.8 * self.nbits_off + 0.2 * nbits_off
g_off = self.get_gain_offset(nbytes)
(g_min, g_int, self.reset_off) = \
self.estimate_gain(x, nbytes, nbits_spec, nbits_off, g_off)
self.nbits_off = nbits_off
self.nbits_spec = nbits_spec
### Quantization
(xg, xq, lastnz) = self.quantize(g_int, x)
(nbits_est, nbits_trunc, lastnz_trunc, _) = \
self.compute_nbits(nbytes, xq, lastnz, nbits_spec)
self.nbits_est = nbits_est
### Adjust gain and requantize
g_adj = self.adjust_gain(g_int - g_off, nbits_est, nbits_spec)
g_adj = max(g_int + g_adj, g_min + g_off) - g_int
(xg, xq, lastnz) = self.quantize(g_adj, xg)
(nbits_est, nbits_trunc, lastnz_trunc, lsb_mode) = \
self.compute_nbits(nbytes, xq, lastnz, nbits_spec)
self.g_idx = g_int + g_adj - g_off
self.xq = xq
self.lastnz = lastnz_trunc
self.nbits_residual_max = nbits_spec - nbits_trunc + 4
self.xg = xg
### Noise factor
self.noise_factor = self.estimate_noise(bw, xq, lastnz, x)
return (self.xq, self.lastnz, self.xg)
def store(self, b):
ne = T.I[self.dt][self.sr][-1]
nbits_lastnz = np.ceil(np.log2(ne/2)).astype(int)
b.write_uint((self.lastnz >> 1) - 1, nbits_lastnz)
b.write_uint(self.lsb_mode, 1)
b.write_uint(self.g_idx, 8)
def encode(self, bits):
### Noise factor
bits.write_uint(self.noise_factor, 3)
### Quantized data
lsbs = []
x = self.xq
c = 0
for n in range(0, self.lastnz, 2):
t = c + self.rate
if n > len(x) // 2:
t += 256
a = abs(x[n ])
b = abs(x[n+1])
lev = 0
while max(a, b) >= 4:
bits.ac_encode(
T.AC_SPEC_CUMFREQ[T.AC_SPEC_LOOKUP[t + lev*1024]][16],
T.AC_SPEC_FREQ[T.AC_SPEC_LOOKUP[t + lev*1024]][16])
if lev == 0 and self.lsb_mode:
lsb_0 = a & 1
lsb_1 = b & 1
else:
bits.write_bit(a & 1)
bits.write_bit(b & 1)
a >>= 1
b >>= 1
lev = min(lev + 1, 3)
bits.ac_encode(
T.AC_SPEC_CUMFREQ[T.AC_SPEC_LOOKUP[t + lev*1024]][a + 4*b],
T.AC_SPEC_FREQ[T.AC_SPEC_LOOKUP[t + lev*1024]][a + 4*b])
a_lsb = abs(x[n ])
b_lsb = abs(x[n+1])
if lev > 0 and self.lsb_mode:
a_lsb >>= 1
b_lsb >>= 1
lsbs.append(lsb_0)
if a_lsb == 0 and x[n+0] != 0:
lsbs.append(int(x[n+0] < 0))
lsbs.append(lsb_1)
if b_lsb == 0 and x[n+1] != 0:
lsbs.append(int(x[n+1] < 0))
if a_lsb > 0:
bits.write_bit(int(x[n+0] < 0))
if b_lsb > 0:
bits.write_bit(int(x[n+1] < 0))
t = 1 + (a + b) * (lev + 1) if lev <= 1 else 12 + lev
c = (c & 15) * 16 + t
### Residual data
if self.lsb_mode == 0:
nbits_residual = min(bits.get_bits_left(), self.nbits_residual_max)
for i in range(len(self.xg)):
if self.xq[i] == 0:
continue
bits.write_bit(self.xg[i] >= self.xq[i])
nbits_residual -= 1
if nbits_residual <= 0:
break
else:
nbits_residual = min(bits.get_bits_left(), len(lsbs))
for lsb in lsbs[:nbits_residual]:
bits.write_bit(lsb)
class SpectrumSynthesis(SpectrumQuantization):
def __init__(self, dt, sr):
super().__init__(dt, sr)
(self.lastnz, self.lsb_mode, self.g_idx) = \
(None, None, None)
def fill_noise(self, bw, x, lastnz, f_nf, nf_seed):
i_nf = self.get_noise_indices(bw, x, lastnz)
k_nf = np.argwhere(i_nf)
l_nf = (8 - f_nf)/16
for k in k_nf:
nf_seed = (13849 + nf_seed * 31821) & 0xffff
x[k] = [ -l_nf, l_nf ][nf_seed < 0x8000]
return x
def load(self, b):
ne = T.I[self.dt][self.sr][-1]
nbits_lastnz = np.ceil(np.log2(ne/2)).astype(int)
self.lastnz = (b.read_uint(nbits_lastnz) + 1) << 1
self.lsb_mode = b.read_uint(1)
self.g_idx = b.read_uint(8)
if self.lastnz > ne:
raise ValueError('Invalid count of coded samples')
def decode(self, bits, bw, nbytes):
### Noise factor
f_nf = bits.read_uint(3)
### Quantized data
ne = T.I[self.dt][self.sr][-1]
x = np.zeros(ne)
rate = [ 0, 512 ][int(self.sr < T.SRATE_96K_HR and \
nbytes > 20 * (1 + min(self.sr, T.SRATE_48K)))]
levs = np.zeros(len(x), dtype=np.intc)
c = 0
for n in range(0, self.lastnz, 2):
t = c + rate
if n > len(x) // 2:
t += 256
for lev in range(14):
s = t + min(lev, 3) * 1024
sym = bits.ac_decode(
T.AC_SPEC_CUMFREQ[T.AC_SPEC_LOOKUP[s]],
T.AC_SPEC_FREQ[T.AC_SPEC_LOOKUP[s]])
if sym < 16:
break
if self.lsb_mode == 0 or lev > 0:
x[n ] += bits.read_bit() << lev
x[n+1] += bits.read_bit() << lev
if lev >= 14:
raise ValueError('Out of range value')
a = sym % 4
b = sym // 4
levs[n ] = lev
levs[n+1] = lev
x[n ] += a << lev
x[n+1] += b << lev
if x[n] and bits.read_bit():
x[n] = -x[n]
if x[n+1] and bits.read_bit():
x[n+1] = -x[n+1]
lev = min(lev, 3)
t = 1 + (a + b) * (lev + 1) if lev <= 1 else 12 + lev
c = (c & 15) * 16 + t
### Residual data
nbits_residual = bits.get_bits_left()
if nbits_residual < 0:
raise ValueError('Out of bitstream')
if self.lsb_mode == 0:
xr = np.zeros(len(x), dtype=np.bool)
for i in range(len(x)):
if nbits_residual <= 0:
xr.resize(i)
break
if x[i] == 0:
continue
xr[i] = bits.read_bit()
nbits_residual -= 1
else:
for i in range(len(levs)):
if nbits_residual <= 0:
break
if levs[i] <= 0:
continue
lsb = bits.read_bit()
nbits_residual -= 1
if not lsb:
continue
sign = int(x[i] < 0)
if x[i] == 0:
if nbits_residual <= 0:
break
sign = bits.read_bit()
nbits_residual -= 1
x[i] += [ 1, -1 ][sign]
### Set residual and noise
nf_seed = sum(abs(x.astype(np.intc)) * range(len(x)))
zero_frame = (self.lastnz <= 2 and x[0] == 0 and x[1] == 0
and self.g_idx <= 0 and f_nf >= 7)
if self.lsb_mode == 0:
for i in range(len(xr)):
if x[i] and xr[i] == 0:
x[i] += [ -0.1875, -0.3125 ][x[i] < 0]
elif x[i]:
x[i] += [ 0.1875, 0.3125 ][x[i] > 0]
if not zero_frame:
x = self.fill_noise(bw, x, self.lastnz, f_nf, nf_seed)
### Rescale coefficients
g_int = self.get_gain_offset(nbytes) + self.g_idx
x *= 10 ** (g_int / 28)
return x
def initial_state():
return { 'nbits_off' : 0.0, 'nbits_spare' : 0 }
### ------------------------------------------------------------------------ ###
def check_estimate_gain(rng, dt, sr):
ok = True
analysis = SpectrumAnalysis(dt, sr)
mismatch_count = 0
for i in range(10):
ne = T.I[dt][sr][-1]
x = rng.random(ne) * i * 1e2
nbytes = 20 + int(rng.random() * 100)
nbits_budget = 8 * nbytes - int(rng.random() * 100)
nbits_off = rng.random() * 10
g_off = 10 - int(rng.random() * 20)
(_, g_int, reset_off) = \
analysis.estimate_gain(x, nbytes, nbits_budget, nbits_off, g_off)
(g_int_c, reset_off_c, _) = lc3.spec_estimate_gain(
dt, sr, x, nbytes, nbits_budget, nbits_off, -g_off)
if g_int_c != g_int:
mismatch_count += 1
ok = ok and (g_int_c == g_int or mismatch_count <= 1)
ok = ok and (reset_off_c == reset_off or mismatch_count <= 1)
return ok
def check_quantization(rng, dt, sr):
ok = True
analysis = SpectrumAnalysis(dt, sr)
for g_int in range(-128, 128):
ne = T.I[dt][sr][-1]
x = rng.random(ne) * 1e2
nbytes = 20 + int(rng.random() * 30)
(xg, xq, nq) = analysis.quantize(g_int, x)
(xg_c, nq_c) = lc3.spec_quantize(dt, sr, g_int, x)
ok = ok and np.amax(np.abs(1 - xg_c/xg)) < 1e-6
ok = ok and nq_c == nq
return ok
def check_compute_nbits(rng, dt, sr):
ok = True
analysis = SpectrumAnalysis(dt, sr)
for nbytes in range(20, 150):
nbits_budget = nbytes * 8 - int(rng.random() * 100)
ne = T.I[dt][sr][-1]
xq = (rng.random(ne) * 8).astype(int)
nq = ne // 2 + int(rng.random() * ne // 2)
nq = nq - nq % 2
if xq[nq-2] == 0 and xq[nq-1] == 0:
xq[nq-2] = 1
(nbits, nbits_trunc, nq_trunc, lsb_mode) = \
analysis.compute_nbits(nbytes, xq, nq, nbits_budget)
(nbits_c, nq_c, _) = \
lc3.spec_compute_nbits(dt, sr, nbytes, xq, nq, 0)
(nbits_trunc_c, nq_trunc_c, lsb_mode_c) = \
lc3.spec_compute_nbits(dt, sr, nbytes, xq, nq, nbits_budget)
ok = ok and nbits_c == nbits
ok = ok and nbits_trunc_c == nbits_trunc
ok = ok and nq_trunc_c == nq_trunc
ok = ok and lsb_mode_c == lsb_mode
return ok
def check_adjust_gain(rng, dt, sr):
ok = True
analysis = SpectrumAnalysis(dt, sr)
for g_idx in (0, 128, 254, 255):
for nbits in range(50, 5000, 5):
nbits_budget = int(nbits * (0.95 + (rng.random() * 0.1)))
g_adj = analysis.adjust_gain(g_idx, nbits, nbits_budget)
g_adj_c = lc3.spec_adjust_gain(
dt, sr, g_idx, nbits, nbits_budget, 0)
ok = ok and g_adj_c == g_adj
return ok
def check_unit(rng, dt, sr):
ok = True
state_c = initial_state()
bwdet = m_bwdet.BandwidthDetector(dt, sr)
ltpf = m_ltpf.LtpfAnalysis(dt, sr)
tns = m_tns.TnsAnalysis(dt)
sns = m_sns.SnsAnalysis(dt, sr)
analysis = SpectrumAnalysis(dt, sr)
nbytes = 100
for i in range(10):
ns = T.NS[dt][sr]
ne = T.I[dt][sr][-1]
x = rng.random(ns) * 1e4
e = rng.random(min(len(x), 64)) * 1e10
if sr < T.SRATE_48K_HR:
bwdet.run(e)
pitch_present = ltpf.run(x)
tns.run(x[:ne], sr, False, nbytes)
sns.run(e, False, 0, x)
(xq, nq, xg) = analysis.run(sr, nbytes,
0 if sr >= T.SRATE_48K_HR else bwdet.get_nbits(),
ltpf.get_nbits(), sns.get_nbits(), tns.get_nbits(), x[:ne])
(xg_c, side_c) = lc3.spec_analyze(dt, sr,
nbytes, pitch_present, tns.get_data(), state_c, x[:ne])
ok = ok and side_c['g_idx'] == analysis.g_idx
ok = ok and side_c['nq'] == nq
ok = ok and np.amax(np.abs(1 - xg_c/xg)) < 1e-6
return ok
def check_noise(rng, dt, bw, hrmode = False):
ok = True
analysis = SpectrumAnalysis(dt, bw)
xq_off = [ 0.375, 0.5 ][hrmode]
for i in range(10):
ne = T.I[dt][bw][-1]
xq = ((rng.random(ne) - 0.5) * 10 ** (0.5)).astype(int)
nq = ne - int(rng.random() * 5)
x = xq - np.select([xq < 0, xq > 0], np.array([ xq_off, -xq_off ]))
nf = analysis.estimate_noise(bw, xq, nq, x)
nf_c = lc3.spec_estimate_noise(dt, bw, hrmode, x, nq)
ok = ok and nf_c == nf
return ok
def check_appendix_c(dt):
i0 = dt - T.DT_7M5
sr = T.SRATE_16K
ok = True
state_c = initial_state()
for i in range(len(C.X_F[i0])):
ne = T.I[dt][sr][-1]
g_int = lc3.spec_estimate_gain(dt, sr, C.X_F[i0][i],
0, C.NBITS_SPEC[i0][i], C.NBITS_OFFSET[i0][i], -C.GG_OFF[i0][i])[0]
ok = ok and g_int == C.GG_IND[i0][i] + C.GG_OFF[i0][i]
(x, nq) = lc3.spec_quantize(dt, sr,
C.GG_IND[i0][i] + C.GG_OFF[i0][i], C.X_F[i0][i])
x += np.select([x < 0, x > 0], np.array([ 0.375, -0.375 ]))
ok = ok and np.any((np.trunc(x) - C.X_Q[i0][i]) == 0)
ok = ok and nq == C.LASTNZ[i0][i]
nbits = lc3.spec_compute_nbits(dt, sr,
C.NBYTES[i0], C.X_Q[i0][i], C.LASTNZ[i0][i], 0)[0]
ok = ok and nbits == C.NBITS_EST[i0][i]
g_adj = lc3.spec_adjust_gain(dt, sr,
C.GG_IND[i0][i], C.NBITS_EST[i0][i], C.NBITS_SPEC[i0][i], 0)
ok = ok and g_adj == C.GG_IND_ADJ[i0][i] - C.GG_IND[i0][i]
if C.GG_IND_ADJ[i0][i] != C.GG_IND[i0][i]:
(x, nq) = lc3.spec_quantize(dt, sr,
C.GG_IND_ADJ[i0][i] + C.GG_OFF[i0][i], C.X_F[i0][i])
lastnz = C.LASTNZ_REQ[i0][i]
x += np.select([x < 0, x > 0], np.array([ 0.375, -0.375 ]))
ok = ok and np.any(((np.trunc(x) - C.X_Q_REQ[i0][i])[:lastnz]) == 0)
tns_data = {
'nfilters' : C.NUM_TNS_FILTERS[i0][i],
'lpc_weighting' : [ True, True ],
'rc_order' : [ C.RC_ORDER[i0][i][0], 0 ],
'rc' : [ C.RC_I_1[i0][i] - 8, np.zeros(8, dtype = np.intc) ]
}
(x, side) = lc3.spec_analyze(dt, sr, C.NBYTES[i0],
C.PITCH_PRESENT[i0][i], tns_data, state_c, C.X_F[i0][i])
xq = x + np.select([x < 0, x > 0], np.array([ 0.375, -0.375 ]))
xq = np.trunc(xq)
ok = ok and np.abs(state_c['nbits_off'] - C.NBITS_OFFSET[i0][i]) < 1e-5
if C.GG_IND_ADJ[i0][i] != C.GG_IND[i0][i]:
xq = C.X_Q_REQ[i0][i]
nq = C.LASTNZ_REQ[i0][i]
ok = ok and side['g_idx'] == C.GG_IND_ADJ[i0][i]
ok = ok and side['nq'] == nq
ok = ok and np.any(((xq[:nq] - xq[:nq])) == 0)
else:
xq = C.X_Q[i0][i]
nq = C.LASTNZ[i0][i]
ok = ok and side['g_idx'] == C.GG_IND[i0][i]
ok = ok and side['nq'] == nq
ok = ok and np.any((xq[:nq] - C.X_Q[i0][i][:nq]) == 0)
ok = ok and side['lsb_mode'] == C.LSB_MODE[i0][i]
gg = C.GG[i0][i] if C.GG_IND_ADJ[i0][i] == C.GG_IND[i0][i] \
else C.GG_ADJ[i0][i]
nf = lc3.spec_estimate_noise(
dt, C.P_BW[i0][i], False, C.X_F[i0][i] / gg, nq)
ok = ok and nf == C.F_NF[i0][i]
return ok
def check():
rng = np.random.default_rng(1234)
ok = True
for dt in range(T.NUM_DT):
for sr in range(T.SRATE_8K, T.SRATE_48K + 1):
ok = ok and check_estimate_gain(rng, dt, sr)
ok = ok and check_quantization(rng, dt, sr)
ok = ok and check_compute_nbits(rng, dt, sr)
ok = ok and check_adjust_gain(rng, dt, sr)
ok = ok and check_unit(rng, dt, sr)
ok = ok and check_noise(rng, dt, sr)
for dt in ( T.DT_2M5, T.DT_5M, T.DT_10M ):
for sr in ( T.SRATE_48K_HR, T.SRATE_96K_HR ):
ok = ok and check_estimate_gain(rng, dt, sr)
ok = ok and check_quantization(rng, dt, sr)
ok = ok and check_compute_nbits(rng, dt, sr)
ok = ok and check_adjust_gain(rng, dt, sr)
ok = ok and check_unit(rng, dt, sr)
ok = ok and check_noise(rng, dt, sr, True)
for dt in ( T.DT_7M5, T.DT_10M ):
ok = ok and check_appendix_c(dt)
return ok
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