summaryrefslogtreecommitdiffstats
path: root/libvpx/vp9/common/vp9_entropy.c
blob: 32d9e0cf7c87d77c9a5937090362cf2675064abe (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
/*
 *  Copyright (c) 2010 The WebM project authors. All Rights Reserved.
 *
 *  Use of this source code is governed by a BSD-style license
 *  that can be found in the LICENSE file in the root of the source
 *  tree. An additional intellectual property rights grant can be found
 *  in the file PATENTS.  All contributing project authors may
 *  be found in the AUTHORS file in the root of the source tree.
 */

#include "vp9/common/vp9_entropy.h"
#include "vp9/common/vp9_blockd.h"
#include "vp9/common/vp9_onyxc_int.h"
#include "vp9/common/vp9_entropymode.h"
#include "vpx_mem/vpx_mem.h"
#include "vpx/vpx_integer.h"

#define MODEL_NODES (ENTROPY_NODES - UNCONSTRAINED_NODES)

DECLARE_ALIGNED(16, const uint8_t, vp9_norm[256]) = {
  0, 7, 6, 6, 5, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4,
  3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
  2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
  2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
};

DECLARE_ALIGNED(16, const uint8_t,
                vp9_coefband_trans_8x8plus[MAXBAND_INDEX + 1]) = {
  0, 1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4,
  4, 4, 4, 4, 4, 5
};

DECLARE_ALIGNED(16, const uint8_t,
                vp9_coefband_trans_4x4[MAXBAND_INDEX + 1]) = {
  0, 1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 5, 5, 5,
  5, 5, 5, 5, 5, 5
};

DECLARE_ALIGNED(16, const uint8_t, vp9_pt_energy_class[MAX_ENTROPY_TOKENS]) = {
  0, 1, 2, 3, 3, 4, 4, 5, 5, 5, 5, 5
};

DECLARE_ALIGNED(16, const int16_t, vp9_default_scan_4x4[16]) = {
  0,  4,  1,  5,
  8,  2, 12,  9,
  3,  6, 13, 10,
  7, 14, 11, 15,
};

DECLARE_ALIGNED(16, const int16_t, vp9_col_scan_4x4[16]) = {
  0,  4,  8,  1,
  12,  5,  9,  2,
  13,  6, 10,  3,
  7, 14, 11, 15,
};

DECLARE_ALIGNED(16, const int16_t, vp9_row_scan_4x4[16]) = {
  0,  1,  4,  2,
  5,  3,  6,  8,
  9,  7, 12, 10,
  13, 11, 14, 15,
};

DECLARE_ALIGNED(16, const int16_t, vp9_default_scan_8x8[64]) = {
  0,  8,  1, 16,  9,  2, 17, 24,
  10,  3, 18, 25, 32, 11,  4, 26,
  33, 19, 40, 12, 34, 27,  5, 41,
  20, 48, 13, 35, 42, 28, 21,  6,
  49, 56, 36, 43, 29,  7, 14, 50,
  57, 44, 22, 37, 15, 51, 58, 30,
  45, 23, 52, 59, 38, 31, 60, 53,
  46, 39, 61, 54, 47, 62, 55, 63,
};

DECLARE_ALIGNED(16, const int16_t, vp9_col_scan_8x8[64]) = {
  0,  8, 16,  1, 24,  9, 32, 17,
  2, 40, 25, 10, 33, 18, 48,  3,
  26, 41, 11, 56, 19, 34,  4, 49,
  27, 42, 12, 35, 20, 57, 50, 28,
  5, 43, 13, 36, 58, 51, 21, 44,
  6, 29, 59, 37, 14, 52, 22,  7,
  45, 60, 30, 15, 38, 53, 23, 46,
  31, 61, 39, 54, 47, 62, 55, 63,
};

DECLARE_ALIGNED(16, const int16_t, vp9_row_scan_8x8[64]) = {
  0,  1,  2,  8,  9,  3, 16, 10,
  4, 17, 11, 24,  5, 18, 25, 12,
  19, 26, 32,  6, 13, 20, 33, 27,
  7, 34, 40, 21, 28, 41, 14, 35,
  48, 42, 29, 36, 49, 22, 43, 15,
  56, 37, 50, 44, 30, 57, 23, 51,
  58, 45, 38, 52, 31, 59, 53, 46,
  60, 39, 61, 47, 54, 55, 62, 63,
};

DECLARE_ALIGNED(16, const int16_t, vp9_default_scan_16x16[256]) = {
  0,  16,   1,  32,  17,   2,  48,  33,  18,   3,  64,  34,  49,  19,  65,  80,
  50,   4,  35,  66,  20,  81,  96,  51,   5,  36,  82,  97,  67, 112,  21,  52,
  98,  37,  83, 113,   6,  68, 128,  53,  22,  99, 114,  84,   7, 129,  38,  69,
  100, 115, 144, 130,  85,  54,  23,   8, 145,  39,  70, 116, 101, 131, 160, 146,
  55,  86,  24,  71, 132, 117, 161,  40,   9, 102, 147, 176, 162,  87,  56,  25,
  133, 118, 177, 148,  72, 103,  41, 163,  10, 192, 178,  88,  57, 134, 149, 119,
  26, 164,  73, 104, 193,  42, 179, 208,  11, 135,  89, 165, 120, 150,  58, 194,
  180,  27,  74, 209, 105, 151, 136,  43,  90, 224, 166, 195, 181, 121, 210,  59,
  12, 152, 106, 167, 196,  75, 137, 225, 211, 240, 182, 122,  91,  28, 197,  13,
  226, 168, 183, 153,  44, 212, 138, 107, 241,  60,  29, 123, 198, 184, 227, 169,
  242,  76, 213, 154,  45,  92,  14, 199, 139,  61, 228, 214, 170, 185, 243, 108,
  77, 155,  30,  15, 200, 229, 124, 215, 244,  93,  46, 186, 171, 201, 109, 140,
  230,  62, 216, 245,  31, 125,  78, 156, 231,  47, 187, 202, 217,  94, 246, 141,
  63, 232, 172, 110, 247, 157,  79, 218, 203, 126, 233, 188, 248,  95, 173, 142,
  219, 111, 249, 234, 158, 127, 189, 204, 250, 235, 143, 174, 220, 205, 159, 251,
  190, 221, 175, 236, 237, 191, 206, 252, 222, 253, 207, 238, 223, 254, 239, 255,
};

DECLARE_ALIGNED(16, const int16_t, vp9_col_scan_16x16[256]) = {
  0,  16,  32,  48,   1,  64,  17,  80,  33,  96,  49,   2,  65, 112,  18,  81,
  34, 128,  50,  97,   3,  66, 144,  19, 113,  35,  82, 160,  98,  51, 129,   4,
  67, 176,  20, 114, 145,  83,  36,  99, 130,  52, 192,   5, 161,  68, 115,  21,
  146,  84, 208, 177,  37, 131, 100,  53, 162, 224,  69,   6, 116, 193, 147,  85,
  22, 240, 132,  38, 178, 101, 163,  54, 209, 117,  70,   7, 148, 194,  86, 179,
  225,  23, 133,  39, 164,   8, 102, 210, 241,  55, 195, 118, 149,  71, 180,  24,
  87, 226, 134, 165, 211,  40, 103,  56,  72, 150, 196, 242, 119,   9, 181, 227,
  88, 166,  25, 135,  41, 104, 212,  57, 151, 197, 120,  73, 243, 182, 136, 167,
  213,  89,  10, 228, 105, 152, 198,  26,  42, 121, 183, 244, 168,  58, 137, 229,
  74, 214,  90, 153, 199, 184,  11, 106, 245,  27, 122, 230, 169,  43, 215,  59,
  200, 138, 185, 246,  75,  12,  91, 154, 216, 231, 107,  28,  44, 201, 123, 170,
  60, 247, 232,  76, 139,  13,  92, 217, 186, 248, 155, 108,  29, 124,  45, 202,
  233, 171,  61,  14,  77, 140,  15, 249,  93,  30, 187, 156, 218,  46, 109, 125,
  62, 172,  78, 203,  31, 141, 234,  94,  47, 188,  63, 157, 110, 250, 219,  79,
  126, 204, 173, 142,  95, 189, 111, 235, 158, 220, 251, 127, 174, 143, 205, 236,
  159, 190, 221, 252, 175, 206, 237, 191, 253, 222, 238, 207, 254, 223, 239, 255,
};

DECLARE_ALIGNED(16, const int16_t, vp9_row_scan_16x16[256]) = {
  0,   1,   2,  16,   3,  17,   4,  18,  32,   5,  33,  19,   6,  34,  48,  20,
  49,   7,  35,  21,  50,  64,   8,  36,  65,  22,  51,  37,  80,   9,  66,  52,
  23,  38,  81,  67,  10,  53,  24,  82,  68,  96,  39,  11,  54,  83,  97,  69,
  25,  98,  84,  40, 112,  55,  12,  70,  99, 113,  85,  26,  41,  56, 114, 100,
  13,  71, 128,  86,  27, 115, 101, 129,  42,  57,  72, 116,  14,  87, 130, 102,
  144,  73, 131, 117,  28,  58,  15,  88,  43, 145, 103, 132, 146, 118,  74, 160,
  89, 133, 104,  29,  59, 147, 119,  44, 161, 148,  90, 105, 134, 162, 120, 176,
  75, 135, 149,  30,  60, 163, 177,  45, 121,  91, 106, 164, 178, 150, 192, 136,
  165, 179,  31, 151, 193,  76, 122,  61, 137, 194, 107, 152, 180, 208,  46, 166,
  167, 195,  92, 181, 138, 209, 123, 153, 224, 196,  77, 168, 210, 182, 240, 108,
  197,  62, 154, 225, 183, 169, 211,  47, 139,  93, 184, 226, 212, 241, 198, 170,
  124, 155, 199,  78, 213, 185, 109, 227, 200,  63, 228, 242, 140, 214, 171, 186,
  156, 229, 243, 125,  94, 201, 244, 215, 216, 230, 141, 187, 202,  79, 172, 110,
  157, 245, 217, 231,  95, 246, 232, 126, 203, 247, 233, 173, 218, 142, 111, 158,
  188, 248, 127, 234, 219, 249, 189, 204, 143, 174, 159, 250, 235, 205, 220, 175,
  190, 251, 221, 191, 206, 236, 207, 237, 252, 222, 253, 223, 238, 239, 254, 255,
};

DECLARE_ALIGNED(16, const int16_t, vp9_default_scan_32x32[1024]) = {
  0,   32,    1,   64,   33,    2,   96,   65,   34,  128,    3,   97,   66,  160,  129,   35,   98,    4,   67,  130,  161,  192,   36,   99,  224,    5,  162,  193,   68,  131,   37,  100,
  225,  194,  256,  163,   69,  132,    6,  226,  257,  288,  195,  101,  164,   38,  258,    7,  227,  289,  133,  320,   70,  196,  165,  290,  259,  228,   39,  321,  102,  352,    8,  197,
  71,  134,  322,  291,  260,  353,  384,  229,  166,  103,   40,  354,  323,  292,  135,  385,  198,  261,   72,    9,  416,  167,  386,  355,  230,  324,  104,  293,   41,  417,  199,  136,
  262,  387,  448,  325,  356,   10,   73,  418,  231,  168,  449,  294,  388,  105,  419,  263,   42,  200,  357,  450,  137,  480,   74,  326,  232,   11,  389,  169,  295,  420,  106,  451,
  481,  358,  264,  327,  201,   43,  138,  512,  482,  390,  296,  233,  170,  421,   75,  452,  359,   12,  513,  265,  483,  328,  107,  202,  514,  544,  422,  391,  453,  139,   44,  234,
  484,  297,  360,  171,   76,  515,  545,  266,  329,  454,   13,  423,  203,  108,  546,  485,  576,  298,  235,  140,  361,  330,  172,  547,   45,  455,  267,  577,  486,   77,  204,  362,
  608,   14,  299,  578,  109,  236,  487,  609,  331,  141,  579,   46,   15,  173,  610,  363,   78,  205,   16,  110,  237,  611,  142,   47,  174,   79,  206,   17,  111,  238,   48,  143,
  80,  175,  112,  207,   49,   18,  239,   81,  113,   19,   50,   82,  114,   51,   83,  115,  640,  516,  392,  268,  144,   20,  672,  641,  548,  517,  424,  393,  300,  269,  176,  145,
  52,   21,  704,  673,  642,  580,  549,  518,  456,  425,  394,  332,  301,  270,  208,  177,  146,   84,   53,   22,  736,  705,  674,  643,  612,  581,  550,  519,  488,  457,  426,  395,
  364,  333,  302,  271,  240,  209,  178,  147,  116,   85,   54,   23,  737,  706,  675,  613,  582,  551,  489,  458,  427,  365,  334,  303,  241,  210,  179,  117,   86,   55,  738,  707,
  614,  583,  490,  459,  366,  335,  242,  211,  118,   87,  739,  615,  491,  367,  243,  119,  768,  644,  520,  396,  272,  148,   24,  800,  769,  676,  645,  552,  521,  428,  397,  304,
  273,  180,  149,   56,   25,  832,  801,  770,  708,  677,  646,  584,  553,  522,  460,  429,  398,  336,  305,  274,  212,  181,  150,   88,   57,   26,  864,  833,  802,  771,  740,  709,
  678,  647,  616,  585,  554,  523,  492,  461,  430,  399,  368,  337,  306,  275,  244,  213,  182,  151,  120,   89,   58,   27,  865,  834,  803,  741,  710,  679,  617,  586,  555,  493,
  462,  431,  369,  338,  307,  245,  214,  183,  121,   90,   59,  866,  835,  742,  711,  618,  587,  494,  463,  370,  339,  246,  215,  122,   91,  867,  743,  619,  495,  371,  247,  123,
  896,  772,  648,  524,  400,  276,  152,   28,  928,  897,  804,  773,  680,  649,  556,  525,  432,  401,  308,  277,  184,  153,   60,   29,  960,  929,  898,  836,  805,  774,  712,  681,
  650,  588,  557,  526,  464,  433,  402,  340,  309,  278,  216,  185,  154,   92,   61,   30,  992,  961,  930,  899,  868,  837,  806,  775,  744,  713,  682,  651,  620,  589,  558,  527,
  496,  465,  434,  403,  372,  341,  310,  279,  248,  217,  186,  155,  124,   93,   62,   31,  993,  962,  931,  869,  838,  807,  745,  714,  683,  621,  590,  559,  497,  466,  435,  373,
  342,  311,  249,  218,  187,  125,   94,   63,  994,  963,  870,  839,  746,  715,  622,  591,  498,  467,  374,  343,  250,  219,  126,   95,  995,  871,  747,  623,  499,  375,  251,  127,
  900,  776,  652,  528,  404,  280,  156,  932,  901,  808,  777,  684,  653,  560,  529,  436,  405,  312,  281,  188,  157,  964,  933,  902,  840,  809,  778,  716,  685,  654,  592,  561,
  530,  468,  437,  406,  344,  313,  282,  220,  189,  158,  996,  965,  934,  903,  872,  841,  810,  779,  748,  717,  686,  655,  624,  593,  562,  531,  500,  469,  438,  407,  376,  345,
  314,  283,  252,  221,  190,  159,  997,  966,  935,  873,  842,  811,  749,  718,  687,  625,  594,  563,  501,  470,  439,  377,  346,  315,  253,  222,  191,  998,  967,  874,  843,  750,
  719,  626,  595,  502,  471,  378,  347,  254,  223,  999,  875,  751,  627,  503,  379,  255,  904,  780,  656,  532,  408,  284,  936,  905,  812,  781,  688,  657,  564,  533,  440,  409,
  316,  285,  968,  937,  906,  844,  813,  782,  720,  689,  658,  596,  565,  534,  472,  441,  410,  348,  317,  286, 1000,  969,  938,  907,  876,  845,  814,  783,  752,  721,  690,  659,
  628,  597,  566,  535,  504,  473,  442,  411,  380,  349,  318,  287, 1001,  970,  939,  877,  846,  815,  753,  722,  691,  629,  598,  567,  505,  474,  443,  381,  350,  319, 1002,  971,
  878,  847,  754,  723,  630,  599,  506,  475,  382,  351, 1003,  879,  755,  631,  507,  383,  908,  784,  660,  536,  412,  940,  909,  816,  785,  692,  661,  568,  537,  444,  413,  972,
  941,  910,  848,  817,  786,  724,  693,  662,  600,  569,  538,  476,  445,  414, 1004,  973,  942,  911,  880,  849,  818,  787,  756,  725,  694,  663,  632,  601,  570,  539,  508,  477,
  446,  415, 1005,  974,  943,  881,  850,  819,  757,  726,  695,  633,  602,  571,  509,  478,  447, 1006,  975,  882,  851,  758,  727,  634,  603,  510,  479, 1007,  883,  759,  635,  511,
  912,  788,  664,  540,  944,  913,  820,  789,  696,  665,  572,  541,  976,  945,  914,  852,  821,  790,  728,  697,  666,  604,  573,  542, 1008,  977,  946,  915,  884,  853,  822,  791,
  760,  729,  698,  667,  636,  605,  574,  543, 1009,  978,  947,  885,  854,  823,  761,  730,  699,  637,  606,  575, 1010,  979,  886,  855,  762,  731,  638,  607, 1011,  887,  763,  639,
  916,  792,  668,  948,  917,  824,  793,  700,  669,  980,  949,  918,  856,  825,  794,  732,  701,  670, 1012,  981,  950,  919,  888,  857,  826,  795,  764,  733,  702,  671, 1013,  982,
  951,  889,  858,  827,  765,  734,  703, 1014,  983,  890,  859,  766,  735, 1015,  891,  767,  920,  796,  952,  921,  828,  797,  984,  953,  922,  860,  829,  798, 1016,  985,  954,  923,
  892,  861,  830,  799, 1017,  986,  955,  893,  862,  831, 1018,  987,  894,  863, 1019,  895,  924,  956,  925,  988,  957,  926, 1020,  989,  958,  927, 1021,  990,  959, 1022,  991, 1023,
};

/* Array indices are identical to previously-existing CONTEXT_NODE indices */

const vp9_tree_index vp9_coef_tree[ 22] =     /* corresponding _CONTEXT_NODEs */
{
  -DCT_EOB_TOKEN, 2,                          /* 0 = EOB */
  -ZERO_TOKEN, 4,                             /* 1 = ZERO */
  -ONE_TOKEN, 6,                              /* 2 = ONE */
  8, 12,                                      /* 3 = LOW_VAL */
  -TWO_TOKEN, 10,                            /* 4 = TWO */
  -THREE_TOKEN, -FOUR_TOKEN,                /* 5 = THREE */
  14, 16,                                   /* 6 = HIGH_LOW */
  -DCT_VAL_CATEGORY1, -DCT_VAL_CATEGORY2,   /* 7 = CAT_ONE */
  18, 20,                                   /* 8 = CAT_THREEFOUR */
  -DCT_VAL_CATEGORY3, -DCT_VAL_CATEGORY4,   /* 9 = CAT_THREE */
  -DCT_VAL_CATEGORY5, -DCT_VAL_CATEGORY6    /* 10 = CAT_FIVE */
};

struct vp9_token vp9_coef_encodings[MAX_ENTROPY_TOKENS];

/* Trees for extra bits.  Probabilities are constant and
   do not depend on previously encoded bits */

static const vp9_prob Pcat1[] = { 159};
static const vp9_prob Pcat2[] = { 165, 145};
static const vp9_prob Pcat3[] = { 173, 148, 140};
static const vp9_prob Pcat4[] = { 176, 155, 140, 135};
static const vp9_prob Pcat5[] = { 180, 157, 141, 134, 130};
static const vp9_prob Pcat6[] = {
  254, 254, 254, 252, 249, 243, 230, 196, 177, 153, 140, 133, 130, 129
};

const vp9_tree_index vp9_coefmodel_tree[6] = {
  -DCT_EOB_MODEL_TOKEN, 2,                      /* 0 = EOB */
  -ZERO_TOKEN, 4,                               /* 1 = ZERO */
  -ONE_TOKEN, -TWO_TOKEN,
};

// Model obtained from a 2-sided zero-centerd distribuition derived
// from a Pareto distribution. The cdf of the distribution is:
// cdf(x) = 0.5 + 0.5 * sgn(x) * [1 - {alpha/(alpha + |x|)} ^ beta]
//
// For a given beta and a given probablity of the 1-node, the alpha
// is first solved, and then the {alpha, beta} pair is used to generate
// the probabilities for the rest of the nodes.

// beta = 8
static const vp9_prob modelcoefprobs_pareto8[COEFPROB_MODELS][MODEL_NODES] = {
  {  3,  86, 128,   6,  86,  23,  88,  29},
  {  9,  86, 129,  17,  88,  61,  94,  76},
  { 15,  87, 129,  28,  89,  93, 100, 110},
  { 20,  88, 130,  38,  91, 118, 106, 136},
  { 26,  89, 131,  48,  92, 139, 111, 156},
  { 31,  90, 131,  58,  94, 156, 117, 171},
  { 37,  90, 132,  66,  95, 171, 122, 184},
  { 42,  91, 132,  75,  97, 183, 127, 194},
  { 47,  92, 133,  83,  98, 193, 132, 202},
  { 52,  93, 133,  90, 100, 201, 137, 208},
  { 57,  94, 134,  98, 101, 208, 142, 214},
  { 62,  94, 135, 105, 103, 214, 146, 218},
  { 66,  95, 135, 111, 104, 219, 151, 222},
  { 71,  96, 136, 117, 106, 224, 155, 225},
  { 76,  97, 136, 123, 107, 227, 159, 228},
  { 80,  98, 137, 129, 109, 231, 162, 231},
  { 84,  98, 138, 134, 110, 234, 166, 233},
  { 89,  99, 138, 140, 112, 236, 170, 235},
  { 93, 100, 139, 145, 113, 238, 173, 236},
  { 97, 101, 140, 149, 115, 240, 176, 238},
  {101, 102, 140, 154, 116, 242, 179, 239},
  {105, 103, 141, 158, 118, 243, 182, 240},
  {109, 104, 141, 162, 119, 244, 185, 241},
  {113, 104, 142, 166, 120, 245, 187, 242},
  {116, 105, 143, 170, 122, 246, 190, 243},
  {120, 106, 143, 173, 123, 247, 192, 244},
  {123, 107, 144, 177, 125, 248, 195, 244},
  {127, 108, 145, 180, 126, 249, 197, 245},
  {130, 109, 145, 183, 128, 249, 199, 245},
  {134, 110, 146, 186, 129, 250, 201, 246},
  {137, 111, 147, 189, 131, 251, 203, 246},
  {140, 112, 147, 192, 132, 251, 205, 247},
  {143, 113, 148, 194, 133, 251, 207, 247},
  {146, 114, 149, 197, 135, 252, 208, 248},
  {149, 115, 149, 199, 136, 252, 210, 248},
  {152, 115, 150, 201, 138, 252, 211, 248},
  {155, 116, 151, 204, 139, 253, 213, 249},
  {158, 117, 151, 206, 140, 253, 214, 249},
  {161, 118, 152, 208, 142, 253, 216, 249},
  {163, 119, 153, 210, 143, 253, 217, 249},
  {166, 120, 153, 212, 144, 254, 218, 250},
  {168, 121, 154, 213, 146, 254, 220, 250},
  {171, 122, 155, 215, 147, 254, 221, 250},
  {173, 123, 155, 217, 148, 254, 222, 250},
  {176, 124, 156, 218, 150, 254, 223, 250},
  {178, 125, 157, 220, 151, 254, 224, 251},
  {180, 126, 157, 221, 152, 254, 225, 251},
  {183, 127, 158, 222, 153, 254, 226, 251},
  {185, 128, 159, 224, 155, 255, 227, 251},
  {187, 129, 160, 225, 156, 255, 228, 251},
  {189, 131, 160, 226, 157, 255, 228, 251},
  {191, 132, 161, 227, 159, 255, 229, 251},
  {193, 133, 162, 228, 160, 255, 230, 252},
  {195, 134, 163, 230, 161, 255, 231, 252},
  {197, 135, 163, 231, 162, 255, 231, 252},
  {199, 136, 164, 232, 163, 255, 232, 252},
  {201, 137, 165, 233, 165, 255, 233, 252},
  {202, 138, 166, 233, 166, 255, 233, 252},
  {204, 139, 166, 234, 167, 255, 234, 252},
  {206, 140, 167, 235, 168, 255, 235, 252},
  {207, 141, 168, 236, 169, 255, 235, 252},
  {209, 142, 169, 237, 171, 255, 236, 252},
  {210, 144, 169, 237, 172, 255, 236, 252},
  {212, 145, 170, 238, 173, 255, 237, 252},
  {214, 146, 171, 239, 174, 255, 237, 253},
  {215, 147, 172, 240, 175, 255, 238, 253},
  {216, 148, 173, 240, 176, 255, 238, 253},
  {218, 149, 173, 241, 177, 255, 239, 253},
  {219, 150, 174, 241, 179, 255, 239, 253},
  {220, 152, 175, 242, 180, 255, 240, 253},
  {222, 153, 176, 242, 181, 255, 240, 253},
  {223, 154, 177, 243, 182, 255, 240, 253},
  {224, 155, 178, 244, 183, 255, 241, 253},
  {225, 156, 178, 244, 184, 255, 241, 253},
  {226, 158, 179, 244, 185, 255, 242, 253},
  {228, 159, 180, 245, 186, 255, 242, 253},
  {229, 160, 181, 245, 187, 255, 242, 253},
  {230, 161, 182, 246, 188, 255, 243, 253},
  {231, 163, 183, 246, 189, 255, 243, 253},
  {232, 164, 184, 247, 190, 255, 243, 253},
  {233, 165, 185, 247, 191, 255, 244, 253},
  {234, 166, 185, 247, 192, 255, 244, 253},
  {235, 168, 186, 248, 193, 255, 244, 253},
  {236, 169, 187, 248, 194, 255, 244, 253},
  {236, 170, 188, 248, 195, 255, 245, 253},
  {237, 171, 189, 249, 196, 255, 245, 254},
  {238, 173, 190, 249, 197, 255, 245, 254},
  {239, 174, 191, 249, 198, 255, 245, 254},
  {240, 175, 192, 249, 199, 255, 246, 254},
  {240, 177, 193, 250, 200, 255, 246, 254},
  {241, 178, 194, 250, 201, 255, 246, 254},
  {242, 179, 195, 250, 202, 255, 246, 254},
  {242, 181, 196, 250, 203, 255, 247, 254},
  {243, 182, 197, 251, 204, 255, 247, 254},
  {244, 184, 198, 251, 205, 255, 247, 254},
  {244, 185, 199, 251, 206, 255, 247, 254},
  {245, 186, 200, 251, 207, 255, 247, 254},
  {246, 188, 201, 252, 207, 255, 248, 254},
  {246, 189, 202, 252, 208, 255, 248, 254},
  {247, 191, 203, 252, 209, 255, 248, 254},
  {247, 192, 204, 252, 210, 255, 248, 254},
  {248, 194, 205, 252, 211, 255, 248, 254},
  {248, 195, 206, 252, 212, 255, 249, 254},
  {249, 197, 207, 253, 213, 255, 249, 254},
  {249, 198, 208, 253, 214, 255, 249, 254},
  {250, 200, 210, 253, 215, 255, 249, 254},
  {250, 201, 211, 253, 215, 255, 249, 254},
  {250, 203, 212, 253, 216, 255, 249, 254},
  {251, 204, 213, 253, 217, 255, 250, 254},
  {251, 206, 214, 254, 218, 255, 250, 254},
  {252, 207, 216, 254, 219, 255, 250, 254},
  {252, 209, 217, 254, 220, 255, 250, 254},
  {252, 211, 218, 254, 221, 255, 250, 254},
  {253, 213, 219, 254, 222, 255, 250, 254},
  {253, 214, 221, 254, 223, 255, 250, 254},
  {253, 216, 222, 254, 224, 255, 251, 254},
  {253, 218, 224, 254, 225, 255, 251, 254},
  {254, 220, 225, 254, 225, 255, 251, 254},
  {254, 222, 227, 255, 226, 255, 251, 254},
  {254, 224, 228, 255, 227, 255, 251, 254},
  {254, 226, 230, 255, 228, 255, 251, 254},
  {255, 228, 231, 255, 230, 255, 251, 254},
  {255, 230, 233, 255, 231, 255, 252, 254},
  {255, 232, 235, 255, 232, 255, 252, 254},
  {255, 235, 237, 255, 233, 255, 252, 254},
  {255, 238, 240, 255, 235, 255, 252, 255},
  {255, 241, 243, 255, 236, 255, 252, 254},
  {255, 246, 247, 255, 239, 255, 253, 255}
};

static void extend_model_to_full_distribution(vp9_prob p,
                                              vp9_prob *tree_probs) {
  const int l = (p - 1) / 2;
  const vp9_prob (*model)[MODEL_NODES] = modelcoefprobs_pareto8;
  if (p & 1) {
    vpx_memcpy(tree_probs + UNCONSTRAINED_NODES,
               model[l], MODEL_NODES * sizeof(vp9_prob));
  } else {
    // interpolate
    int i;
    for (i = UNCONSTRAINED_NODES; i < ENTROPY_NODES; ++i)
      tree_probs[i] = (model[l][i - UNCONSTRAINED_NODES] +
                       model[l + 1][i - UNCONSTRAINED_NODES]) >> 1;
  }
}

void vp9_model_to_full_probs(const vp9_prob *model, vp9_prob *full) {
  if (full != model)
    vpx_memcpy(full, model, sizeof(vp9_prob) * UNCONSTRAINED_NODES);
  extend_model_to_full_distribution(model[PIVOT_NODE], full);
}

static vp9_tree_index cat1[2], cat2[4], cat3[6], cat4[8], cat5[10], cat6[28];

static void init_bit_tree(vp9_tree_index *p, int n) {
  int i = 0;

  while (++i < n) {
    p[0] = p[1] = i << 1;
    p += 2;
  }

  p[0] = p[1] = 0;
}

static void init_bit_trees() {
  init_bit_tree(cat1, 1);
  init_bit_tree(cat2, 2);
  init_bit_tree(cat3, 3);
  init_bit_tree(cat4, 4);
  init_bit_tree(cat5, 5);
  init_bit_tree(cat6, 14);
}

const vp9_extra_bit vp9_extra_bits[12] = {
  { 0, 0, 0, 0},
  { 0, 0, 0, 1},
  { 0, 0, 0, 2},
  { 0, 0, 0, 3},
  { 0, 0, 0, 4},
  { cat1, Pcat1, 1, 5},
  { cat2, Pcat2, 2, 7},
  { cat3, Pcat3, 3, 11},
  { cat4, Pcat4, 4, 19},
  { cat5, Pcat5, 5, 35},
  { cat6, Pcat6, 14, 67},
  { 0, 0, 0, 0}
};

#include "vp9/common/vp9_default_coef_probs.h"

void vp9_default_coef_probs(VP9_COMMON *cm) {
  vp9_copy(cm->fc.coef_probs[TX_4X4], default_coef_probs_4x4);
  vp9_copy(cm->fc.coef_probs[TX_8X8], default_coef_probs_8x8);
  vp9_copy(cm->fc.coef_probs[TX_16X16], default_coef_probs_16x16);
  vp9_copy(cm->fc.coef_probs[TX_32X32], default_coef_probs_32x32);
}

// Neighborhood 5-tuples for various scans and blocksizes,
// in {top, left, topleft, topright, bottomleft} order
// for each position in raster scan order.
// -1 indicates the neighbor does not exist.
DECLARE_ALIGNED(16, int16_t,
                vp9_default_scan_4x4_neighbors[17 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_col_scan_4x4_neighbors[17 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_row_scan_4x4_neighbors[17 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_col_scan_8x8_neighbors[65 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_row_scan_8x8_neighbors[65 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_default_scan_8x8_neighbors[65 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_col_scan_16x16_neighbors[257 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_row_scan_16x16_neighbors[257 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_default_scan_16x16_neighbors[257 * MAX_NEIGHBORS]);
DECLARE_ALIGNED(16, int16_t,
                vp9_default_scan_32x32_neighbors[1025 * MAX_NEIGHBORS]);

DECLARE_ALIGNED(16, int16_t, vp9_default_iscan_4x4[16]);
DECLARE_ALIGNED(16, int16_t, vp9_col_iscan_4x4[16]);
DECLARE_ALIGNED(16, int16_t, vp9_row_iscan_4x4[16]);
DECLARE_ALIGNED(16, int16_t, vp9_col_iscan_8x8[64]);
DECLARE_ALIGNED(16, int16_t, vp9_row_iscan_8x8[64]);
DECLARE_ALIGNED(16, int16_t, vp9_default_iscan_8x8[64]);
DECLARE_ALIGNED(16, int16_t, vp9_col_iscan_16x16[256]);
DECLARE_ALIGNED(16, int16_t, vp9_row_iscan_16x16[256]);
DECLARE_ALIGNED(16, int16_t, vp9_default_iscan_16x16[256]);
DECLARE_ALIGNED(16, int16_t, vp9_default_iscan_32x32[1024]);

static int find_in_scan(const int16_t *scan, int l, int idx) {
  int n, l2 = l * l;
  for (n = 0; n < l2; n++) {
    int rc = scan[n];
    if (rc == idx)
      return  n;
  }
  assert(0);
  return -1;
}
static void init_scan_neighbors(const int16_t *scan,
                                int16_t *iscan,
                                int l, int16_t *neighbors) {
  int l2 = l * l;
  int n, i, j;

  // dc doesn't use this type of prediction
  neighbors[MAX_NEIGHBORS * 0 + 0] = 0;
  neighbors[MAX_NEIGHBORS * 0 + 1] = 0;
  iscan[0] = find_in_scan(scan, l, 0);
  for (n = 1; n < l2; n++) {
    int rc = scan[n];
    iscan[n] = find_in_scan(scan, l, n);
    i = rc / l;
    j = rc % l;
    if (i > 0 && j > 0) {
      // col/row scan is used for adst/dct, and generally means that
      // energy decreases to zero much faster in the dimension in
      // which ADST is used compared to the direction in which DCT
      // is used. Likewise, we find much higher correlation between
      // coefficients within the direction in which DCT is used.
      // Therefore, if we use ADST/DCT, prefer the DCT neighbor coeff
      // as a context. If ADST or DCT is used in both directions, we
      // use the combination of the two as a context.
      int a = (i - 1) * l + j;
      int b =  i      * l + j - 1;
      if (scan == vp9_col_scan_4x4 || scan == vp9_col_scan_8x8 ||
          scan == vp9_col_scan_16x16) {
        // in the col/row scan cases (as well as left/top edge cases), we set
        // both contexts to the same value, so we can branchlessly do a+b+1>>1
        // which automatically becomes a if a == b
        neighbors[MAX_NEIGHBORS * n + 0] =
        neighbors[MAX_NEIGHBORS * n + 1] = a;
      } else if (scan == vp9_row_scan_4x4 || scan == vp9_row_scan_8x8 ||
                 scan == vp9_row_scan_16x16) {
        neighbors[MAX_NEIGHBORS * n + 0] =
        neighbors[MAX_NEIGHBORS * n + 1] = b;
      } else {
        neighbors[MAX_NEIGHBORS * n + 0] = a;
        neighbors[MAX_NEIGHBORS * n + 1] = b;
      }
    } else if (i > 0) {
      neighbors[MAX_NEIGHBORS * n + 0] =
      neighbors[MAX_NEIGHBORS * n + 1] = (i - 1) * l + j;
    } else {
      assert(j > 0);
      neighbors[MAX_NEIGHBORS * n + 0] =
      neighbors[MAX_NEIGHBORS * n + 1] =  i      * l + j - 1;
    }
    assert(iscan[neighbors[MAX_NEIGHBORS * n + 0]] < n);
  }
  // one padding item so we don't have to add branches in code to handle
  // calls to get_coef_context() for the token after the final dc token
  neighbors[MAX_NEIGHBORS * l2 + 0] = 0;
  neighbors[MAX_NEIGHBORS * l2 + 1] = 0;
}

void vp9_init_neighbors() {
  init_scan_neighbors(vp9_default_scan_4x4, vp9_default_iscan_4x4, 4,
                      vp9_default_scan_4x4_neighbors);
  init_scan_neighbors(vp9_row_scan_4x4, vp9_row_iscan_4x4, 4,
                      vp9_row_scan_4x4_neighbors);
  init_scan_neighbors(vp9_col_scan_4x4, vp9_col_iscan_4x4, 4,
                      vp9_col_scan_4x4_neighbors);
  init_scan_neighbors(vp9_default_scan_8x8, vp9_default_iscan_8x8, 8,
                      vp9_default_scan_8x8_neighbors);
  init_scan_neighbors(vp9_row_scan_8x8, vp9_row_iscan_8x8, 8,
                      vp9_row_scan_8x8_neighbors);
  init_scan_neighbors(vp9_col_scan_8x8, vp9_col_iscan_8x8, 8,
                      vp9_col_scan_8x8_neighbors);
  init_scan_neighbors(vp9_default_scan_16x16, vp9_default_iscan_16x16, 16,
                      vp9_default_scan_16x16_neighbors);
  init_scan_neighbors(vp9_row_scan_16x16, vp9_row_iscan_16x16, 16,
                      vp9_row_scan_16x16_neighbors);
  init_scan_neighbors(vp9_col_scan_16x16, vp9_col_iscan_16x16, 16,
                      vp9_col_scan_16x16_neighbors);
  init_scan_neighbors(vp9_default_scan_32x32, vp9_default_iscan_32x32, 32,
                      vp9_default_scan_32x32_neighbors);
}

const int16_t *vp9_get_coef_neighbors_handle(const int16_t *scan) {
  if (scan == vp9_default_scan_4x4) {
    return vp9_default_scan_4x4_neighbors;
  } else if (scan == vp9_row_scan_4x4) {
    return vp9_row_scan_4x4_neighbors;
  } else if (scan == vp9_col_scan_4x4) {
    return vp9_col_scan_4x4_neighbors;
  } else if (scan == vp9_default_scan_8x8) {
    return vp9_default_scan_8x8_neighbors;
  } else if (scan == vp9_row_scan_8x8) {
    return vp9_row_scan_8x8_neighbors;
  } else if (scan == vp9_col_scan_8x8) {
    return vp9_col_scan_8x8_neighbors;
  } else if (scan == vp9_default_scan_16x16) {
    return vp9_default_scan_16x16_neighbors;
  } else if (scan == vp9_row_scan_16x16) {
    return vp9_row_scan_16x16_neighbors;
  } else if (scan == vp9_col_scan_16x16) {
    return vp9_col_scan_16x16_neighbors;
  } else {
    assert(scan == vp9_default_scan_32x32);
    return vp9_default_scan_32x32_neighbors;
  }
}

void vp9_coef_tree_initialize() {
  vp9_init_neighbors();
  init_bit_trees();
  vp9_tokens_from_tree(vp9_coef_encodings, vp9_coef_tree);
}

// #define COEF_COUNT_TESTING

#define COEF_COUNT_SAT 24
#define COEF_MAX_UPDATE_FACTOR 112
#define COEF_COUNT_SAT_KEY 24
#define COEF_MAX_UPDATE_FACTOR_KEY 112
#define COEF_COUNT_SAT_AFTER_KEY 24
#define COEF_MAX_UPDATE_FACTOR_AFTER_KEY 128

static void adapt_coef_probs(VP9_COMMON *cm, TX_SIZE tx_size,
                             unsigned int count_sat,
                             unsigned int update_factor) {
  FRAME_CONTEXT *pre_fc = &cm->frame_contexts[cm->frame_context_idx];

  vp9_coeff_probs_model *dst_coef_probs = cm->fc.coef_probs[tx_size];
  vp9_coeff_probs_model *pre_coef_probs = pre_fc->coef_probs[tx_size];
  vp9_coeff_count_model *coef_counts = cm->counts.coef[tx_size];
  unsigned int (*eob_branch_count)[REF_TYPES][COEF_BANDS][PREV_COEF_CONTEXTS] =
      cm->counts.eob_branch[tx_size];
  int t, i, j, k, l;
  unsigned int branch_ct[UNCONSTRAINED_NODES][2];
  vp9_prob coef_probs[UNCONSTRAINED_NODES];

  for (i = 0; i < BLOCK_TYPES; ++i)
    for (j = 0; j < REF_TYPES; ++j)
      for (k = 0; k < COEF_BANDS; ++k)
        for (l = 0; l < PREV_COEF_CONTEXTS; ++l) {
          if (l >= 3 && k == 0)
            continue;
          vp9_tree_probs_from_distribution(vp9_coefmodel_tree, coef_probs,
                                           branch_ct, coef_counts[i][j][k][l],
                                           0);
          branch_ct[0][1] = eob_branch_count[i][j][k][l] - branch_ct[0][0];
          coef_probs[0] = get_binary_prob(branch_ct[0][0], branch_ct[0][1]);
          for (t = 0; t < UNCONSTRAINED_NODES; ++t)
            dst_coef_probs[i][j][k][l][t] = merge_probs(
                pre_coef_probs[i][j][k][l][t], coef_probs[t],
                branch_ct[t], count_sat, update_factor);
        }
}

void vp9_adapt_coef_probs(VP9_COMMON *cm) {
  TX_SIZE t;
  unsigned int count_sat, update_factor;

  if (cm->frame_type == KEY_FRAME || cm->intra_only) {
    update_factor = COEF_MAX_UPDATE_FACTOR_KEY;
    count_sat = COEF_COUNT_SAT_KEY;
  } else if (cm->last_frame_type == KEY_FRAME) {
    update_factor = COEF_MAX_UPDATE_FACTOR_AFTER_KEY;  /* adapt quickly */
    count_sat = COEF_COUNT_SAT_AFTER_KEY;
  } else {
    update_factor = COEF_MAX_UPDATE_FACTOR;
    count_sat = COEF_COUNT_SAT;
  }
  for (t = TX_4X4; t <= TX_32X32; t++)
    adapt_coef_probs(cm, t, count_sat, update_factor);
}