Add m-esr52 at 52.6.0

1 files changed, 207 insertions, 0 deletions

diff --git a/media/libopus/silk/float/solve_LS_FLP.c b/media/libopus/silk/float/solve_LS_FLP.c
new file mode 100644
index 000000000..7c90d665a
--- /dev/null
+++ b/media/libopus/silk/float/solve_LS_FLP.c
@@ -0,0 +1,207 @@
+/***********************************************************************
+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 );
+}
+