Index: webrtc/modules/audio_coding/codecs/opus/opus/src/silk/float/solve_LS_FLP.c |
diff --git a/webrtc/modules/audio_coding/codecs/opus/opus/src/silk/float/solve_LS_FLP.c b/webrtc/modules/audio_coding/codecs/opus/opus/src/silk/float/solve_LS_FLP.c |
new file mode 100644 |
index 0000000000000000000000000000000000000000..7c90d665a0f0d18b573b632a9328560511bf2a81 |
--- /dev/null |
+++ b/webrtc/modules/audio_coding/codecs/opus/opus/src/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 ); |
+} |
+ |