godot/thirdparty/opus/silk/float/burg_modified_FLP.c
Rémi Verschelde 46ae64cd60 Revert "Update opus to 1.3.1 and opusfile to 0.11"
This reverts commit e00426c512.

The way we handle platform-specific intrinsics is not good, so the
current state will not compile on armv8. This commit also requires
SSE4.1 support, which is likely not a good idea for portable binaries.

We'll have to redo this with more caution after 3.2 is released, or
we might simply drop opus as we're only using it as dependency for
theora right now.

Fixes #33606.
2019-11-18 09:56:48 +01:00

187 lines
7.7 KiB
C

/***********************************************************************
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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
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#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include "SigProc_FLP.h"
#include "tuning_parameters.h"
#include "define.h"
#define MAX_FRAME_SIZE 384 /* subfr_length * nb_subfr = ( 0.005 * 16000 + 16 ) * 4 = 384*/
/* Compute reflection coefficients from input signal */
silk_float silk_burg_modified_FLP( /* O returns residual energy */
silk_float A[], /* O prediction coefficients (length order) */
const silk_float x[], /* I input signal, length: nb_subfr*(D+L_sub) */
const silk_float minInvGain, /* I minimum inverse prediction gain */
const opus_int subfr_length, /* I input signal subframe length (incl. D preceding samples) */
const opus_int nb_subfr, /* I number of subframes stacked in x */
const opus_int D /* I order */
)
{
opus_int k, n, s, reached_max_gain;
double C0, invGain, num, nrg_f, nrg_b, rc, Atmp, tmp1, tmp2;
const silk_float *x_ptr;
double C_first_row[ SILK_MAX_ORDER_LPC ], C_last_row[ SILK_MAX_ORDER_LPC ];
double CAf[ SILK_MAX_ORDER_LPC + 1 ], CAb[ SILK_MAX_ORDER_LPC + 1 ];
double Af[ SILK_MAX_ORDER_LPC ];
silk_assert( subfr_length * nb_subfr <= MAX_FRAME_SIZE );
/* Compute autocorrelations, added over subframes */
C0 = silk_energy_FLP( x, nb_subfr * subfr_length );
silk_memset( C_first_row, 0, SILK_MAX_ORDER_LPC * sizeof( double ) );
for( s = 0; s < nb_subfr; s++ ) {
x_ptr = x + s * subfr_length;
for( n = 1; n < D + 1; n++ ) {
C_first_row[ n - 1 ] += silk_inner_product_FLP( x_ptr, x_ptr + n, subfr_length - n );
}
}
silk_memcpy( C_last_row, C_first_row, SILK_MAX_ORDER_LPC * sizeof( double ) );
/* Initialize */
CAb[ 0 ] = CAf[ 0 ] = C0 + FIND_LPC_COND_FAC * C0 + 1e-9f;
invGain = 1.0f;
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) */
for( s = 0; s < nb_subfr; s++ ) {
x_ptr = x + s * subfr_length;
tmp1 = x_ptr[ n ];
tmp2 = x_ptr[ subfr_length - n - 1 ];
for( k = 0; k < n; k++ ) {
C_first_row[ k ] -= x_ptr[ n ] * x_ptr[ n - k - 1 ];
C_last_row[ k ] -= x_ptr[ subfr_length - n - 1 ] * x_ptr[ subfr_length - n + k ];
Atmp = Af[ k ];
tmp1 += x_ptr[ n - k - 1 ] * Atmp;
tmp2 += x_ptr[ subfr_length - n + k ] * Atmp;
}
for( k = 0; k <= n; k++ ) {
CAf[ k ] -= tmp1 * x_ptr[ n - k ];
CAb[ k ] -= tmp2 * x_ptr[ subfr_length - n + k - 1 ];
}
}
tmp1 = C_first_row[ n ];
tmp2 = C_last_row[ n ];
for( k = 0; k < n; k++ ) {
Atmp = Af[ k ];
tmp1 += C_last_row[ n - k - 1 ] * Atmp;
tmp2 += C_first_row[ n - k - 1 ] * Atmp;
}
CAf[ n + 1 ] = tmp1;
CAb[ n + 1 ] = tmp2;
/* Calculate nominator and denominator for the next order reflection (parcor) coefficient */
num = CAb[ n + 1 ];
nrg_b = CAb[ 0 ];
nrg_f = CAf[ 0 ];
for( k = 0; k < n; k++ ) {
Atmp = Af[ k ];
num += CAb[ n - k ] * Atmp;
nrg_b += CAb[ k + 1 ] * Atmp;
nrg_f += CAf[ k + 1 ] * Atmp;
}
silk_assert( nrg_f > 0.0 );
silk_assert( nrg_b > 0.0 );
/* Calculate the next order reflection (parcor) coefficient */
rc = -2.0 * num / ( nrg_f + nrg_b );
silk_assert( rc > -1.0 && rc < 1.0 );
/* Update inverse prediction gain */
tmp1 = invGain * ( 1.0 - rc * rc );
if( tmp1 <= minInvGain ) {
/* Max prediction gain exceeded; set reflection coefficient such that max prediction gain is exactly hit */
rc = sqrt( 1.0 - minInvGain / invGain );
if( num > 0 ) {
/* Ensure adjusted reflection coefficients has the original sign */
rc = -rc;
}
invGain = minInvGain;
reached_max_gain = 1;
} else {
invGain = tmp1;
}
/* Update the AR coefficients */
for( k = 0; k < (n + 1) >> 1; k++ ) {
tmp1 = Af[ k ];
tmp2 = Af[ n - k - 1 ];
Af[ k ] = tmp1 + rc * tmp2;
Af[ n - k - 1 ] = tmp2 + rc * tmp1;
}
Af[ n ] = rc;
if( reached_max_gain ) {
/* Reached max prediction gain; set remaining coefficients to zero and exit loop */
for( k = n + 1; k < D; k++ ) {
Af[ k ] = 0.0;
}
break;
}
/* Update C * Af and C * Ab */
for( k = 0; k <= n + 1; k++ ) {
tmp1 = CAf[ k ];
CAf[ k ] += rc * CAb[ n - k + 1 ];
CAb[ n - k + 1 ] += rc * tmp1;
}
}
if( reached_max_gain ) {
/* Convert to silk_float */
for( k = 0; k < D; k++ ) {
A[ k ] = (silk_float)( -Af[ k ] );
}
/* Subtract energy of preceding samples from C0 */
for( s = 0; s < nb_subfr; s++ ) {
C0 -= silk_energy_FLP( x + s * subfr_length, D );
}
/* Approximate residual energy */
nrg_f = C0 * invGain;
} else {
/* Compute residual energy and store coefficients as silk_float */
nrg_f = CAf[ 0 ];
tmp1 = 1.0;
for( k = 0; k < D; k++ ) {
Atmp = Af[ k ];
nrg_f += CAf[ k + 1 ] * Atmp;
tmp1 += Atmp * Atmp;
A[ k ] = (silk_float)(-Atmp);
}
nrg_f -= FIND_LPC_COND_FAC * C0 * tmp1;
}
/* Return residual energy */
return (silk_float)nrg_f;
}