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

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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.
*/
namespace Concentus.Silk
{
using Concentus.Common;
using Concentus.Common.CPlusPlus;
using Concentus.Silk.Enums;
using Concentus.Silk.Structs;
using System.Diagnostics;
internal static class LPCInversePredGain
{
private const float RC_THRESHOLD = 0.9999f;
private const int QA = 24;
private static readonly int A_LIMIT = ((int)((0.99975f) * ((long)1 << (QA)) + 0.5))/*Inlines.SILK_CONST(0.99975f, QA)*/;
/* Compute inverse of LPC prediction gain, and */
/* test if LPC coefficients are stable (all poles within unit circle) */
internal static int LPC_inverse_pred_gain_QA( /* O Returns inverse prediction gain in energy domain, Q30 */
int[][] A_QA, /* I Prediction coefficients [ 2 ][SILK_MAX_ORDER_LPC] */
int order /* I Prediction order */
)
{
int k, n, mult2Q;
int invGain_Q30, rc_Q31, rc_mult1_Q30, rc_mult2, tmp_QA;
int[] Aold_QA;
int[] Anew_QA;
Anew_QA = A_QA[order & 1];
invGain_Q30 = (int)1 << 30;
for (k = order - 1; k > 0; k--)
{
/* Check for stability */
if ((Anew_QA[k] > A_LIMIT) || (Anew_QA[k] < -A_LIMIT))
{
return 0;
}
/* Set RC equal to negated AR coef */
rc_Q31 = 0 - Inlines.silk_LSHIFT(Anew_QA[k], 31 - QA);
/* rc_mult1_Q30 range: [ 1 : 2^30 ] */
rc_mult1_Q30 = ((int)1 << 30) - Inlines.silk_SMMUL(rc_Q31, rc_Q31);
Inlines.OpusAssert(rc_mult1_Q30 > (1 << 15)); /* reduce A_LIMIT if fails */
Inlines.OpusAssert(rc_mult1_Q30 <= (1 << 30));
/* rc_mult2 range: [ 2^30 : silk_int32_MAX ] */
mult2Q = 32 - Inlines.silk_CLZ32(Inlines.silk_abs(rc_mult1_Q30));
rc_mult2 = Inlines.silk_INVERSE32_varQ(rc_mult1_Q30, mult2Q + 30);
/* Update inverse gain */
/* invGain_Q30 range: [ 0 : 2^30 ] */
invGain_Q30 = Inlines.silk_LSHIFT(Inlines.silk_SMMUL(invGain_Q30, rc_mult1_Q30), 2);
Inlines.OpusAssert(invGain_Q30 >= 0);
Inlines.OpusAssert(invGain_Q30 <= (1 << 30));
/* Swap pointers */
Aold_QA = Anew_QA;
Anew_QA = A_QA[k & 1];
/* Update AR coefficient */
for (n = 0; n < k; n++)
{
tmp_QA = Aold_QA[n] - Inlines.MUL32_FRAC_Q(Aold_QA[k - n - 1], rc_Q31, 31);
Anew_QA[n] = Inlines.MUL32_FRAC_Q(tmp_QA, rc_mult2, mult2Q);
}
}
/* Check for stability */
if ((Anew_QA[0] > A_LIMIT) || (Anew_QA[0] < -A_LIMIT))
{
return 0;
}
/* Set RC equal to negated AR coef */
rc_Q31 = 0 - Inlines.silk_LSHIFT(Anew_QA[0], 31 - QA);
/* Range: [ 1 : 2^30 ] */
rc_mult1_Q30 = ((int)1 << 30) - Inlines.silk_SMMUL(rc_Q31, rc_Q31);
/* Update inverse gain */
/* Range: [ 0 : 2^30 ] */
invGain_Q30 = Inlines.silk_LSHIFT(Inlines.silk_SMMUL(invGain_Q30, rc_mult1_Q30), 2);
Inlines.OpusAssert(invGain_Q30 >= 0);
Inlines.OpusAssert(invGain_Q30 <= 1 << 30);
return invGain_Q30;
}
/* For input in Q12 domain */
internal static int silk_LPC_inverse_pred_gain( /* O Returns inverse prediction gain in energy domain, Q30 */
short[] A_Q12, /* I Prediction coefficients, Q12 [order] */
int order /* I Prediction order */
)
{
int k;
int[][] Atmp_QA = Arrays.InitTwoDimensionalArray<int>(2, SilkConstants.SILK_MAX_ORDER_LPC);
int[] Anew_QA;
int DC_resp = 0;
Anew_QA = Atmp_QA[order & 1];
/* Increase Q domain of the AR coefficients */
for (k = 0; k < order; k++)
{
DC_resp += (int)A_Q12[k];
Anew_QA[k] = Inlines.silk_LSHIFT32((int)A_Q12[k], QA - 12);
}
/* If the DC is unstable, we don't even need to do the full calculations */
if (DC_resp >= 4096)
{
return 0;
}
return LPC_inverse_pred_gain_QA(Atmp_QA, order);
}
internal static int silk_LPC_inverse_pred_gain_Q24( /* O Returns inverse prediction gain in energy domain, Q30 */
int[] A_Q24, /* I Prediction coefficients [order] */
int order /* I Prediction order */
)
{
int k;
int[][] Atmp_QA = Arrays.InitTwoDimensionalArray<int>(2, SilkConstants.SILK_MAX_ORDER_LPC);
int[] Anew_QA;
Anew_QA = Atmp_QA[order & 1];
/* Increase Q domain of the AR coefficients */
for (k = 0; k < order; k++)
{
Anew_QA[k] = Inlines.silk_RSHIFT32(A_Q24[k], 24 - QA);
}
return LPC_inverse_pred_gain_QA(Atmp_QA, order);
}
}
}