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review.jami.net / jami-client-android / 744f742538c1f3ef21cb5ef77d7156006d5855b3 / . / jni / libopus / silk / VQ_WMat_EC.c
blob: a308cfbf1c50db424152bb978f22329adc37f7be [file] [log] [blame]
Alexandre Lision744f7422013-09-25 11:39:37 -0400[diff] [blame^]1/***********************************************************************
2Copyright (c) 2006-2011, Skype Limited. All rights reserved.
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26***********************************************************************/
27
28#ifdef HAVE_CONFIG_H
29#include "config.h"
30#endif
31
32#include "main.h"
33
34/* Entropy constrained matrix-weighted VQ, hard-coded to 5-element vectors, for a single input data vector */
35void silk_VQ_WMat_EC(
36 opus_int8 *ind, /* O index of best codebook vector */
37 opus_int32 *rate_dist_Q14, /* O best weighted quant error + mu * rate */
38 const opus_int16 *in_Q14, /* I input vector to be quantized */
39 const opus_int32 *W_Q18, /* I weighting matrix */
40 const opus_int8 *cb_Q7, /* I codebook */
41 const opus_uint8 *cl_Q5, /* I code length for each codebook vector */
42 const opus_int mu_Q9, /* I tradeoff betw. weighted error and rate */
43 opus_int L /* I number of vectors in codebook */
44)
45{
46 opus_int k;
47 const opus_int8 *cb_row_Q7;
48 opus_int16 diff_Q14[ 5 ];
49 opus_int32 sum1_Q14, sum2_Q16;
50
51 /* Loop over codebook */
52 *rate_dist_Q14 = silk_int32_MAX;
53 cb_row_Q7 = cb_Q7;
54 for( k = 0; k < L; k++ ) {
55 diff_Q14[ 0 ] = in_Q14[ 0 ] - silk_LSHIFT( cb_row_Q7[ 0 ], 7 );
56 diff_Q14[ 1 ] = in_Q14[ 1 ] - silk_LSHIFT( cb_row_Q7[ 1 ], 7 );
57 diff_Q14[ 2 ] = in_Q14[ 2 ] - silk_LSHIFT( cb_row_Q7[ 2 ], 7 );
58 diff_Q14[ 3 ] = in_Q14[ 3 ] - silk_LSHIFT( cb_row_Q7[ 3 ], 7 );
59 diff_Q14[ 4 ] = in_Q14[ 4 ] - silk_LSHIFT( cb_row_Q7[ 4 ], 7 );
60
61 /* Weighted rate */
62 sum1_Q14 = silk_SMULBB( mu_Q9, cl_Q5[ k ] );
63
64 silk_assert( sum1_Q14 >= 0 );
65
66 /* first row of W_Q18 */
67 sum2_Q16 = silk_SMULWB( W_Q18[ 1 ], diff_Q14[ 1 ] );
68 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 2 ], diff_Q14[ 2 ] );
69 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 3 ], diff_Q14[ 3 ] );
70 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 4 ], diff_Q14[ 4 ] );
71 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
72 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 0 ], diff_Q14[ 0 ] );
73 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 0 ] );
74
75 /* second row of W_Q18 */
76 sum2_Q16 = silk_SMULWB( W_Q18[ 7 ], diff_Q14[ 2 ] );
77 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 8 ], diff_Q14[ 3 ] );
78 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 9 ], diff_Q14[ 4 ] );
79 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
80 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 6 ], diff_Q14[ 1 ] );
81 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 1 ] );
82
83 /* third row of W_Q18 */
84 sum2_Q16 = silk_SMULWB( W_Q18[ 13 ], diff_Q14[ 3 ] );
85 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 14 ], diff_Q14[ 4 ] );
86 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
87 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 12 ], diff_Q14[ 2 ] );
88 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 2 ] );
89
90 /* fourth row of W_Q18 */
91 sum2_Q16 = silk_SMULWB( W_Q18[ 19 ], diff_Q14[ 4 ] );
92 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
93 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 18 ], diff_Q14[ 3 ] );
94 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 3 ] );
95
96 /* last row of W_Q18 */
97 sum2_Q16 = silk_SMULWB( W_Q18[ 24 ], diff_Q14[ 4 ] );
98 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 4 ] );
99
100 silk_assert( sum1_Q14 >= 0 );
101
102 /* find best */
103 if( sum1_Q14 < *rate_dist_Q14 ) {
104 *rate_dist_Q14 = sum1_Q14;
105 *ind = (opus_int8)k;
106 }
107
108 /* Go to next cbk vector */
109 cb_row_Q7 += LTP_ORDER;
110 }
111}