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LuaCsForBarotraumaEP/Libraries/Concentus/CSharp/Concentus/Silk/BurgModified.cs

326 lines
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C#

/* Copyright (c) 2006-2011 Skype Limited. All Rights Reserved
Ported to C# by Logan Stromberg
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
- Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
- Neither the name of Internet Society, IETF or IETF Trust, nor the
names of specific contributors, may be used to endorse or promote
products derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER
OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#if !UNSAFE
namespace Concentus.Silk
{
using Concentus.Celt;
using Concentus.Common;
using Concentus.Common.CPlusPlus;
using Concentus.Silk.Enums;
using Concentus.Silk.Structs;
using System;
using System.Diagnostics;
internal static class BurgModified
{
/* subfr_length * nb_subfr = ( 0.005 * 16000 + 16 ) * 4 = 384 */
private const int MAX_FRAME_SIZE = 384;
private const int QA = 25;
private const int N_BITS_HEAD_ROOM = 2;
private const int MIN_RSHIFTS = -16;
private const int MAX_RSHIFTS = (32 - QA);
/* Compute reflection coefficients from input signal */
internal static void silk_burg_modified(
BoxedValueInt res_nrg, /* O Residual energy */
BoxedValueInt res_nrg_Q, /* O Residual energy Q value */
int[] A_Q16, /* O Prediction coefficients (length order) */
short[] x, /* I Input signal, length: nb_subfr * ( D + subfr_length ) */
int x_ptr,
int minInvGain_Q30, /* I Inverse of max prediction gain */
int subfr_length, /* I Input signal subframe length (incl. D preceding samples) */
int nb_subfr, /* I Number of subframes stacked in x */
int D /* I Order */
)
{
int k, n, s, lz, rshifts, reached_max_gain;
int C0, num, nrg, rc_Q31, invGain_Q30, Atmp_QA, Atmp1, tmp1, tmp2, x1, x2;
int x_offset;
int[] C_first_row = new int[SilkConstants.SILK_MAX_ORDER_LPC];
int[] C_last_row = new int[SilkConstants.SILK_MAX_ORDER_LPC];
int[] Af_QA = new int[SilkConstants.SILK_MAX_ORDER_LPC];
int[] CAf = new int[SilkConstants.SILK_MAX_ORDER_LPC + 1];
int[] CAb = new int[SilkConstants.SILK_MAX_ORDER_LPC + 1];
int[] xcorr = new int[SilkConstants.SILK_MAX_ORDER_LPC];
long C0_64;
Inlines.OpusAssert(subfr_length * nb_subfr <= MAX_FRAME_SIZE);
/* Compute autocorrelations, added over subframes */
C0_64 = Inlines.silk_inner_prod16_aligned_64(x, x_ptr, x, x_ptr, subfr_length * nb_subfr);
lz = Inlines.silk_CLZ64(C0_64);
rshifts = 32 + 1 + N_BITS_HEAD_ROOM - lz;
if (rshifts > MAX_RSHIFTS) rshifts = MAX_RSHIFTS;
if (rshifts < MIN_RSHIFTS) rshifts = MIN_RSHIFTS;
if (rshifts > 0)
{
C0 = (int)Inlines.silk_RSHIFT64(C0_64, rshifts);
}
else {
C0 = Inlines.silk_LSHIFT32((int)C0_64, -rshifts);
}
CAb[0] = CAf[0] = C0 + Inlines.silk_SMMUL(((int)((TuningParameters.FIND_LPC_COND_FAC) * ((long)1 << (32)) + 0.5))/*Inlines.SILK_CONST(TuningParameters.FIND_LPC_COND_FAC, 32)*/, C0) + 1; /* Q(-rshifts) */
Arrays.MemSetInt(C_first_row, 0, SilkConstants.SILK_MAX_ORDER_LPC);
if (rshifts > 0)
{
for (s = 0; s < nb_subfr; s++)
{
x_offset = x_ptr + s * subfr_length;
for (n = 1; n < D + 1; n++)
{
C_first_row[n - 1] += (int)Inlines.silk_RSHIFT64(
Inlines.silk_inner_prod16_aligned_64(x, x_offset, x, x_offset + n, subfr_length - n), rshifts);
}
}
}
else {
for (s = 0; s < nb_subfr; s++)
{
int i;
int d;
x_offset = x_ptr + s * subfr_length;
CeltPitchXCorr.pitch_xcorr(x, x_offset, x, x_offset + 1, xcorr, subfr_length - D, D);
for (n = 1; n < D + 1; n++)
{
for (i = n + subfr_length - D, d = 0; i < subfr_length; i++)
d = Inlines.MAC16_16(d, x[x_offset + i], x[x_offset + i - n]);
xcorr[n - 1] += d;
}
for (n = 1; n < D + 1; n++)
{
C_first_row[n - 1] += Inlines.silk_LSHIFT32(xcorr[n - 1], -rshifts);
}
}
}
Array.Copy(C_first_row, C_last_row, SilkConstants.SILK_MAX_ORDER_LPC);
/* Initialize */
CAb[0] = CAf[0] = C0 + Inlines.silk_SMMUL(((int)((TuningParameters.FIND_LPC_COND_FAC) * ((long)1 << (32)) + 0.5))/*Inlines.SILK_CONST(TuningParameters.FIND_LPC_COND_FAC, 32)*/, C0) + 1; /* Q(-rshifts) */
invGain_Q30 = (int)1 << 30;
reached_max_gain = 0;
for (n = 0; n < D; n++)
{
/* Update first row of correlation matrix (without first element) */
/* Update last row of correlation matrix (without last element, stored in reversed order) */
/* Update C * Af */
/* Update C * flipud(Af) (stored in reversed order) */
if (rshifts > -2)
{
for (s = 0; s < nb_subfr; s++)
{
x_offset = x_ptr + s * subfr_length;
x1 = -Inlines.silk_LSHIFT32((int)x[x_offset + n], 16 - rshifts); /* Q(16-rshifts) */
x2 = -Inlines.silk_LSHIFT32((int)x[x_offset + subfr_length - n - 1], 16 - rshifts); /* Q(16-rshifts) */
tmp1 = Inlines.silk_LSHIFT32((int)x[x_offset + n], QA - 16); /* Q(QA-16) */
tmp2 = Inlines.silk_LSHIFT32((int)x[x_offset + subfr_length - n - 1], QA - 16); /* Q(QA-16) */
for (k = 0; k < n; k++)
{
C_first_row[k] = Inlines.silk_SMLAWB(C_first_row[k], x1, x[x_offset + n - k - 1]); /* Q( -rshifts ) */
C_last_row[k] = Inlines.silk_SMLAWB(C_last_row[k], x2, x[x_offset + subfr_length - n + k]); /* Q( -rshifts ) */
Atmp_QA = Af_QA[k];
tmp1 = Inlines.silk_SMLAWB(tmp1, Atmp_QA, x[x_offset + n - k - 1]); /* Q(QA-16) */
tmp2 = Inlines.silk_SMLAWB(tmp2, Atmp_QA, x[x_offset + subfr_length - n + k]); /* Q(QA-16) */
}
tmp1 = Inlines.silk_LSHIFT32(-tmp1, 32 - QA - rshifts); /* Q(16-rshifts) */
tmp2 = Inlines.silk_LSHIFT32(-tmp2, 32 - QA - rshifts); /* Q(16-rshifts) */
for (k = 0; k <= n; k++)
{
CAf[k] = Inlines.silk_SMLAWB(CAf[k], tmp1, x[x_offset + n - k]); /* Q( -rshift ) */
CAb[k] = Inlines.silk_SMLAWB(CAb[k], tmp2, x[x_offset + subfr_length - n + k - 1]); /* Q( -rshift ) */
}
}
}
else {
for (s = 0; s < nb_subfr; s++)
{
x_offset = x_ptr + s * subfr_length;
x1 = -Inlines.silk_LSHIFT32((int)x[x_offset + n], -rshifts); /* Q( -rshifts ) */
x2 = -Inlines.silk_LSHIFT32((int)x[x_offset + subfr_length - n - 1], -rshifts); /* Q( -rshifts ) */
tmp1 = Inlines.silk_LSHIFT32((int)x[x_offset + n], 17); /* Q17 */
tmp2 = Inlines.silk_LSHIFT32((int)x[x_offset + subfr_length - n - 1], 17); /* Q17 */
for (k = 0; k < n; k++)
{
C_first_row[k] = Inlines.silk_MLA(C_first_row[k], x1, x[x_offset + n - k - 1]); /* Q( -rshifts ) */
C_last_row[k] = Inlines.silk_MLA(C_last_row[k], x2, x[x_offset + subfr_length - n + k]); /* Q( -rshifts ) */
Atmp1 = Inlines.silk_RSHIFT_ROUND(Af_QA[k], QA - 17); /* Q17 */
tmp1 = Inlines.silk_MLA(tmp1, x[x_offset + n - k - 1], Atmp1); /* Q17 */
tmp2 = Inlines.silk_MLA(tmp2, x[x_offset + subfr_length - n + k], Atmp1); /* Q17 */
}
tmp1 = -tmp1; /* Q17 */
tmp2 = -tmp2; /* Q17 */
for (k = 0; k <= n; k++)
{
CAf[k] = Inlines.silk_SMLAWW(CAf[k], tmp1,
Inlines.silk_LSHIFT32((int)x[x_offset + n - k], -rshifts - 1)); /* Q( -rshift ) */
CAb[k] = Inlines.silk_SMLAWW(CAb[k], tmp2,
Inlines.silk_LSHIFT32((int)x[x_offset + subfr_length - n + k - 1], -rshifts - 1)); /* Q( -rshift ) */
}
}
}
/* Calculate nominator and denominator for the next order reflection (parcor) coefficient */
tmp1 = C_first_row[n]; /* Q( -rshifts ) */
tmp2 = C_last_row[n]; /* Q( -rshifts ) */
num = 0; /* Q( -rshifts ) */
nrg = Inlines.silk_ADD32(CAb[0], CAf[0]); /* Q( 1-rshifts ) */
for (k = 0; k < n; k++)
{
Atmp_QA = Af_QA[k];
lz = Inlines.silk_CLZ32(Inlines.silk_abs(Atmp_QA)) - 1;
lz = Inlines.silk_min(32 - QA, lz);
Atmp1 = Inlines.silk_LSHIFT32(Atmp_QA, lz); /* Q( QA + lz ) */
tmp1 = Inlines.silk_ADD_LSHIFT32(tmp1, Inlines.silk_SMMUL(C_last_row[n - k - 1], Atmp1), 32 - QA - lz); /* Q( -rshifts ) */
tmp2 = Inlines.silk_ADD_LSHIFT32(tmp2, Inlines.silk_SMMUL(C_first_row[n - k - 1], Atmp1), 32 - QA - lz); /* Q( -rshifts ) */
num = Inlines.silk_ADD_LSHIFT32(num, Inlines.silk_SMMUL(CAb[n - k], Atmp1), 32 - QA - lz); /* Q( -rshifts ) */
nrg = Inlines.silk_ADD_LSHIFT32(nrg, Inlines.silk_SMMUL(Inlines.silk_ADD32(CAb[k + 1], CAf[k + 1]),
Atmp1), 32 - QA - lz); /* Q( 1-rshifts ) */
}
CAf[n + 1] = tmp1; /* Q( -rshifts ) */
CAb[n + 1] = tmp2; /* Q( -rshifts ) */
num = Inlines.silk_ADD32(num, tmp2); /* Q( -rshifts ) */
num = Inlines.silk_LSHIFT32(-num, 1); /* Q( 1-rshifts ) */
/* Calculate the next order reflection (parcor) coefficient */
if (Inlines.silk_abs(num) < nrg)
{
rc_Q31 = Inlines.silk_DIV32_varQ(num, nrg, 31);
}
else {
rc_Q31 = (num > 0) ? int.MaxValue : int.MinValue;
}
/* Update inverse prediction gain */
tmp1 = ((int)1 << 30) - Inlines.silk_SMMUL(rc_Q31, rc_Q31);
tmp1 = Inlines.silk_LSHIFT(Inlines.silk_SMMUL(invGain_Q30, tmp1), 2);
if (tmp1 <= minInvGain_Q30)
{
/* Max prediction gain exceeded; set reflection coefficient such that max prediction gain is exactly hit */
tmp2 = ((int)1 << 30) - Inlines.silk_DIV32_varQ(minInvGain_Q30, invGain_Q30, 30); /* Q30 */
rc_Q31 = Inlines.silk_SQRT_APPROX(tmp2); /* Q15 */
/* Newton-Raphson iteration */
rc_Q31 = Inlines.silk_RSHIFT32(rc_Q31 + Inlines.silk_DIV32(tmp2, rc_Q31), 1); /* Q15 */
rc_Q31 = Inlines.silk_LSHIFT32(rc_Q31, 16); /* Q31 */
if (num < 0)
{
/* Ensure adjusted reflection coefficients has the original sign */
rc_Q31 = -rc_Q31;
}
invGain_Q30 = minInvGain_Q30;
reached_max_gain = 1;
}
else {
invGain_Q30 = tmp1;
}
/* Update the AR coefficients */
for (k = 0; k < (n + 1) >> 1; k++)
{
tmp1 = Af_QA[k]; /* QA */
tmp2 = Af_QA[n - k - 1]; /* QA */
Af_QA[k] = Inlines.silk_ADD_LSHIFT32(tmp1, Inlines.silk_SMMUL(tmp2, rc_Q31), 1); /* QA */
Af_QA[n - k - 1] = Inlines.silk_ADD_LSHIFT32(tmp2, Inlines.silk_SMMUL(tmp1, rc_Q31), 1); /* QA */
}
Af_QA[n] = Inlines.silk_RSHIFT32(rc_Q31, 31 - QA); /* QA */
if (reached_max_gain != 0)
{
/* Reached max prediction gain; set remaining coefficients to zero and exit loop */
for (k = n + 1; k < D; k++)
{
Af_QA[k] = 0;
}
break;
}
/* Update C * Af and C * Ab */
for (k = 0; k <= n + 1; k++)
{
tmp1 = CAf[k]; /* Q( -rshifts ) */
tmp2 = CAb[n - k + 1]; /* Q( -rshifts ) */
CAf[k] = Inlines.silk_ADD_LSHIFT32(tmp1, Inlines.silk_SMMUL(tmp2, rc_Q31), 1); /* Q( -rshifts ) */
CAb[n - k + 1] = Inlines.silk_ADD_LSHIFT32(tmp2, Inlines.silk_SMMUL(tmp1, rc_Q31), 1); /* Q( -rshifts ) */
}
}
if (reached_max_gain != 0)
{
for (k = 0; k < D; k++)
{
/* Scale coefficients */
A_Q16[k] = -Inlines.silk_RSHIFT_ROUND(Af_QA[k], QA - 16);
}
/* Subtract energy of preceding samples from C0 */
if (rshifts > 0)
{
for (s = 0; s < nb_subfr; s++)
{
x_offset = x_ptr + s * subfr_length;
C0 -= (int)Inlines.silk_RSHIFT64(Inlines.silk_inner_prod16_aligned_64(x, x_offset, x, x_offset, D), rshifts);
}
}
else {
for (s = 0; s < nb_subfr; s++)
{
x_offset = x_ptr + s * subfr_length;
C0 -= Inlines.silk_LSHIFT32(Inlines.silk_inner_prod_self(x, x_offset, D), -rshifts);
}
}
/* Approximate residual energy */
res_nrg.Val = Inlines.silk_LSHIFT(Inlines.silk_SMMUL(invGain_Q30, C0), 2);
res_nrg_Q.Val = 0 - rshifts;
}
else {
/* Return residual energy */
nrg = CAf[0]; /* Q( -rshifts ) */
tmp1 = (int)1 << 16; /* Q16 */
for (k = 0; k < D; k++)
{
Atmp1 = Inlines.silk_RSHIFT_ROUND(Af_QA[k], QA - 16); /* Q16 */
nrg = Inlines.silk_SMLAWW(nrg, CAf[k + 1], Atmp1); /* Q( -rshifts ) */
tmp1 = Inlines.silk_SMLAWW(tmp1, Atmp1, Atmp1); /* Q16 */
A_Q16[k] = -Atmp1;
}
res_nrg.Val = Inlines.silk_SMLAWW(nrg, Inlines.silk_SMMUL(((int)((TuningParameters.FIND_LPC_COND_FAC) * ((long)1 << (32)) + 0.5))/*Inlines.SILK_CONST(TuningParameters.FIND_LPC_COND_FAC, 32)*/, C0), -tmp1);/* Q( -rshifts ) */
res_nrg_Q.Val = -rshifts;
}
}
}
}
#endif