godot/thirdparty/opus/silk/float/solve_LS_FLP.c
Rémi Verschelde d9a291f641 ogg/vorbis/opus: Make them modules and unbundle thirdparty libs
Took the opportunity to undo the Godot changed made to the
opus source. The opus module should eventually be built in its
own environment to avoid polluting others with too many include
dirs and defines.

TODO: Fix the platform/ stuff for opus.
2016-10-15 11:50:40 +02:00

208 lines
9.9 KiB
C

/***********************************************************************
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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***********************************************************************/
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include "main_FLP.h"
#include "tuning_parameters.h"
/**********************************************************************
* LDL Factorisation. Finds the upper triangular matrix L and the diagonal
* Matrix D (only the diagonal elements returned in a vector)such that
* the symmetric matric A is given by A = L*D*L'.
**********************************************************************/
static OPUS_INLINE void silk_LDL_FLP(
silk_float *A, /* I/O Pointer to Symetric Square Matrix */
opus_int M, /* I Size of Matrix */
silk_float *L, /* I/O Pointer to Square Upper triangular Matrix */
silk_float *Dinv /* I/O Pointer to vector holding the inverse diagonal elements of D */
);
/**********************************************************************
* Function to solve linear equation Ax = b, when A is a MxM lower
* triangular matrix, with ones on the diagonal.
**********************************************************************/
static OPUS_INLINE void silk_SolveWithLowerTriangularWdiagOnes_FLP(
const silk_float *L, /* I Pointer to Lower Triangular Matrix */
opus_int M, /* I Dim of Matrix equation */
const silk_float *b, /* I b Vector */
silk_float *x /* O x Vector */
);
/**********************************************************************
* Function to solve linear equation (A^T)x = b, when A is a MxM lower
* triangular, with ones on the diagonal. (ie then A^T is upper triangular)
**********************************************************************/
static OPUS_INLINE void silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP(
const silk_float *L, /* I Pointer to Lower Triangular Matrix */
opus_int M, /* I Dim of Matrix equation */
const silk_float *b, /* I b Vector */
silk_float *x /* O x Vector */
);
/**********************************************************************
* Function to solve linear equation Ax = b, when A is a MxM
* symmetric square matrix - using LDL factorisation
**********************************************************************/
void silk_solve_LDL_FLP(
silk_float *A, /* I/O Symmetric square matrix, out: reg. */
const opus_int M, /* I Size of matrix */
const silk_float *b, /* I Pointer to b vector */
silk_float *x /* O Pointer to x solution vector */
)
{
opus_int i;
silk_float L[ MAX_MATRIX_SIZE ][ MAX_MATRIX_SIZE ];
silk_float T[ MAX_MATRIX_SIZE ];
silk_float Dinv[ MAX_MATRIX_SIZE ]; /* inverse diagonal elements of D*/
silk_assert( M <= MAX_MATRIX_SIZE );
/***************************************************
Factorize A by LDL such that A = L*D*(L^T),
where L is lower triangular with ones on diagonal
****************************************************/
silk_LDL_FLP( A, M, &L[ 0 ][ 0 ], Dinv );
/****************************************************
* substitute D*(L^T) = T. ie:
L*D*(L^T)*x = b => L*T = b <=> T = inv(L)*b
******************************************************/
silk_SolveWithLowerTriangularWdiagOnes_FLP( &L[ 0 ][ 0 ], M, b, T );
/****************************************************
D*(L^T)*x = T <=> (L^T)*x = inv(D)*T, because D is
diagonal just multiply with 1/d_i
****************************************************/
for( i = 0; i < M; i++ ) {
T[ i ] = T[ i ] * Dinv[ i ];
}
/****************************************************
x = inv(L') * inv(D) * T
*****************************************************/
silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP( &L[ 0 ][ 0 ], M, T, x );
}
static OPUS_INLINE void silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP(
const silk_float *L, /* I Pointer to Lower Triangular Matrix */
opus_int M, /* I Dim of Matrix equation */
const silk_float *b, /* I b Vector */
silk_float *x /* O x Vector */
)
{
opus_int i, j;
silk_float temp;
const silk_float *ptr1;
for( i = M - 1; i >= 0; i-- ) {
ptr1 = matrix_adr( L, 0, i, M );
temp = 0;
for( j = M - 1; j > i ; j-- ) {
temp += ptr1[ j * M ] * x[ j ];
}
temp = b[ i ] - temp;
x[ i ] = temp;
}
}
static OPUS_INLINE void silk_SolveWithLowerTriangularWdiagOnes_FLP(
const silk_float *L, /* I Pointer to Lower Triangular Matrix */
opus_int M, /* I Dim of Matrix equation */
const silk_float *b, /* I b Vector */
silk_float *x /* O x Vector */
)
{
opus_int i, j;
silk_float temp;
const silk_float *ptr1;
for( i = 0; i < M; i++ ) {
ptr1 = matrix_adr( L, i, 0, M );
temp = 0;
for( j = 0; j < i; j++ ) {
temp += ptr1[ j ] * x[ j ];
}
temp = b[ i ] - temp;
x[ i ] = temp;
}
}
static OPUS_INLINE void silk_LDL_FLP(
silk_float *A, /* I/O Pointer to Symetric Square Matrix */
opus_int M, /* I Size of Matrix */
silk_float *L, /* I/O Pointer to Square Upper triangular Matrix */
silk_float *Dinv /* I/O Pointer to vector holding the inverse diagonal elements of D */
)
{
opus_int i, j, k, loop_count, err = 1;
silk_float *ptr1, *ptr2;
double temp, diag_min_value;
silk_float v[ MAX_MATRIX_SIZE ], D[ MAX_MATRIX_SIZE ]; /* temp arrays*/
silk_assert( M <= MAX_MATRIX_SIZE );
diag_min_value = FIND_LTP_COND_FAC * 0.5f * ( A[ 0 ] + A[ M * M - 1 ] );
for( loop_count = 0; loop_count < M && err == 1; loop_count++ ) {
err = 0;
for( j = 0; j < M; j++ ) {
ptr1 = matrix_adr( L, j, 0, M );
temp = matrix_ptr( A, j, j, M ); /* element in row j column j*/
for( i = 0; i < j; i++ ) {
v[ i ] = ptr1[ i ] * D[ i ];
temp -= ptr1[ i ] * v[ i ];
}
if( temp < diag_min_value ) {
/* Badly conditioned matrix: add white noise and run again */
temp = ( loop_count + 1 ) * diag_min_value - temp;
for( i = 0; i < M; i++ ) {
matrix_ptr( A, i, i, M ) += ( silk_float )temp;
}
err = 1;
break;
}
D[ j ] = ( silk_float )temp;
Dinv[ j ] = ( silk_float )( 1.0f / temp );
matrix_ptr( L, j, j, M ) = 1.0f;
ptr1 = matrix_adr( A, j, 0, M );
ptr2 = matrix_adr( L, j + 1, 0, M);
for( i = j + 1; i < M; i++ ) {
temp = 0.0;
for( k = 0; k < j; k++ ) {
temp += ptr2[ k ] * v[ k ];
}
matrix_ptr( L, i, j, M ) = ( silk_float )( ( ptr1[ i ] - temp ) * Dinv[ j ] );
ptr2 += M; /* go to next column*/
}
}
}
silk_assert( err == 0 );
}