[Opus] Update to v1.2.1

third_party/opus/src/silk/float/solve_LS_FLP.c

Index: third_party/opus/src/silk/float/solve_LS_FLP.c
diff --git a/third_party/opus/src/silk/float/solve_LS_FLP.c b/third_party/opus/src/silk/float/solve_LS_FLP.c
deleted file mode 100644
index 7c90d665a0f0d18b573b632a9328560511bf2a81..0000000000000000000000000000000000000000
--- a/third_party/opus/src/silk/float/solve_LS_FLP.c
+++ /dev/null
@@ -1,207 +0,0 @@
-/***********************************************************************
-Copyright (c) 2006-2011, Skype Limited. All rights reserved.
-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.
-***********************************************************************/
-
-#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 );
-}
-