| /* Copyright 2010 Google Inc. All Rights Reserved. |
| |
| Distributed under MIT license. |
| See file LICENSE for detail or copy at https://opensource.org/licenses/MIT |
| */ |
| |
| /* Entropy encoding (Huffman) utilities. */ |
| |
| #include "./entropy_encode.h" |
| |
| #include <string.h> /* memset */ |
| |
| #include "../common/constants.h" |
| #include "../public/types.h" |
| #include "./port.h" |
| |
| #if defined(__cplusplus) || defined(c_plusplus) |
| extern "C" { |
| #endif |
| |
| BROTLI_BOOL BrotliSetDepth( |
| int p0, HuffmanTree* pool, uint8_t* depth, int max_depth) { |
| int stack[16]; |
| int level = 0; |
| int p = p0; |
| assert(max_depth <= 15); |
| stack[0] = -1; |
| while (BROTLI_TRUE) { |
| if (pool[p].index_left_ >= 0) { |
| level++; |
| if (level > max_depth) return BROTLI_FALSE; |
| stack[level] = pool[p].index_right_or_value_; |
| p = pool[p].index_left_; |
| continue; |
| } else { |
| depth[pool[p].index_right_or_value_] = (uint8_t)level; |
| } |
| while (level >= 0 && stack[level] == -1) level--; |
| if (level < 0) return BROTLI_TRUE; |
| p = stack[level]; |
| stack[level] = -1; |
| } |
| } |
| |
| /* Sort the root nodes, least popular first. */ |
| static BROTLI_INLINE BROTLI_BOOL SortHuffmanTree( |
| const HuffmanTree* v0, const HuffmanTree* v1) { |
| if (v0->total_count_ != v1->total_count_) { |
| return TO_BROTLI_BOOL(v0->total_count_ < v1->total_count_); |
| } |
| return TO_BROTLI_BOOL(v0->index_right_or_value_ > v1->index_right_or_value_); |
| } |
| |
| /* This function will create a Huffman tree. |
| |
| The catch here is that the tree cannot be arbitrarily deep. |
| Brotli specifies a maximum depth of 15 bits for "code trees" |
| and 7 bits for "code length code trees." |
| |
| count_limit is the value that is to be faked as the minimum value |
| and this minimum value is raised until the tree matches the |
| maximum length requirement. |
| |
| This algorithm is not of excellent performance for very long data blocks, |
| especially when population counts are longer than 2**tree_limit, but |
| we are not planning to use this with extremely long blocks. |
| |
| See http://en.wikipedia.org/wiki/Huffman_coding */ |
| void BrotliCreateHuffmanTree(const uint32_t *data, |
| const size_t length, |
| const int tree_limit, |
| HuffmanTree* tree, |
| uint8_t *depth) { |
| uint32_t count_limit; |
| HuffmanTree sentinel; |
| InitHuffmanTree(&sentinel, BROTLI_UINT32_MAX, -1, -1); |
| /* For block sizes below 64 kB, we never need to do a second iteration |
| of this loop. Probably all of our block sizes will be smaller than |
| that, so this loop is mostly of academic interest. If we actually |
| would need this, we would be better off with the Katajainen algorithm. */ |
| for (count_limit = 1; ; count_limit *= 2) { |
| size_t n = 0; |
| size_t i; |
| size_t j; |
| size_t k; |
| for (i = length; i != 0;) { |
| --i; |
| if (data[i]) { |
| const uint32_t count = BROTLI_MAX(uint32_t, data[i], count_limit); |
| InitHuffmanTree(&tree[n++], count, -1, (int16_t)i); |
| } |
| } |
| |
| if (n == 1) { |
| depth[tree[0].index_right_or_value_] = 1; /* Only one element. */ |
| break; |
| } |
| |
| SortHuffmanTreeItems(tree, n, SortHuffmanTree); |
| |
| /* The nodes are: |
| [0, n): the sorted leaf nodes that we start with. |
| [n]: we add a sentinel here. |
| [n + 1, 2n): new parent nodes are added here, starting from |
| (n+1). These are naturally in ascending order. |
| [2n]: we add a sentinel at the end as well. |
| There will be (2n+1) elements at the end. */ |
| tree[n] = sentinel; |
| tree[n + 1] = sentinel; |
| |
| i = 0; /* Points to the next leaf node. */ |
| j = n + 1; /* Points to the next non-leaf node. */ |
| for (k = n - 1; k != 0; --k) { |
| size_t left, right; |
| if (tree[i].total_count_ <= tree[j].total_count_) { |
| left = i; |
| ++i; |
| } else { |
| left = j; |
| ++j; |
| } |
| if (tree[i].total_count_ <= tree[j].total_count_) { |
| right = i; |
| ++i; |
| } else { |
| right = j; |
| ++j; |
| } |
| |
| { |
| /* The sentinel node becomes the parent node. */ |
| size_t j_end = 2 * n - k; |
| tree[j_end].total_count_ = |
| tree[left].total_count_ + tree[right].total_count_; |
| tree[j_end].index_left_ = (int16_t)left; |
| tree[j_end].index_right_or_value_ = (int16_t)right; |
| |
| /* Add back the last sentinel node. */ |
| tree[j_end + 1] = sentinel; |
| } |
| } |
| if (BrotliSetDepth((int)(2 * n - 1), &tree[0], depth, tree_limit)) { |
| /* We need to pack the Huffman tree in tree_limit bits. If this was not |
| successful, add fake entities to the lowest values and retry. */ |
| break; |
| } |
| } |
| } |
| |
| static void Reverse(uint8_t* v, size_t start, size_t end) { |
| --end; |
| while (start < end) { |
| uint8_t tmp = v[start]; |
| v[start] = v[end]; |
| v[end] = tmp; |
| ++start; |
| --end; |
| } |
| } |
| |
| static void BrotliWriteHuffmanTreeRepetitions( |
| const uint8_t previous_value, |
| const uint8_t value, |
| size_t repetitions, |
| size_t* tree_size, |
| uint8_t* tree, |
| uint8_t* extra_bits_data) { |
| assert(repetitions > 0); |
| if (previous_value != value) { |
| tree[*tree_size] = value; |
| extra_bits_data[*tree_size] = 0; |
| ++(*tree_size); |
| --repetitions; |
| } |
| if (repetitions == 7) { |
| tree[*tree_size] = value; |
| extra_bits_data[*tree_size] = 0; |
| ++(*tree_size); |
| --repetitions; |
| } |
| if (repetitions < 3) { |
| size_t i; |
| for (i = 0; i < repetitions; ++i) { |
| tree[*tree_size] = value; |
| extra_bits_data[*tree_size] = 0; |
| ++(*tree_size); |
| } |
| } else { |
| size_t start = *tree_size; |
| repetitions -= 3; |
| while (BROTLI_TRUE) { |
| tree[*tree_size] = BROTLI_REPEAT_PREVIOUS_CODE_LENGTH; |
| extra_bits_data[*tree_size] = repetitions & 0x3; |
| ++(*tree_size); |
| repetitions >>= 2; |
| if (repetitions == 0) { |
| break; |
| } |
| --repetitions; |
| } |
| Reverse(tree, start, *tree_size); |
| Reverse(extra_bits_data, start, *tree_size); |
| } |
| } |
| |
| static void BrotliWriteHuffmanTreeRepetitionsZeros( |
| size_t repetitions, |
| size_t* tree_size, |
| uint8_t* tree, |
| uint8_t* extra_bits_data) { |
| if (repetitions == 11) { |
| tree[*tree_size] = 0; |
| extra_bits_data[*tree_size] = 0; |
| ++(*tree_size); |
| --repetitions; |
| } |
| if (repetitions < 3) { |
| size_t i; |
| for (i = 0; i < repetitions; ++i) { |
| tree[*tree_size] = 0; |
| extra_bits_data[*tree_size] = 0; |
| ++(*tree_size); |
| } |
| } else { |
| size_t start = *tree_size; |
| repetitions -= 3; |
| while (BROTLI_TRUE) { |
| tree[*tree_size] = BROTLI_REPEAT_ZERO_CODE_LENGTH; |
| extra_bits_data[*tree_size] = repetitions & 0x7; |
| ++(*tree_size); |
| repetitions >>= 3; |
| if (repetitions == 0) { |
| break; |
| } |
| --repetitions; |
| } |
| Reverse(tree, start, *tree_size); |
| Reverse(extra_bits_data, start, *tree_size); |
| } |
| } |
| |
| void BrotliOptimizeHuffmanCountsForRle(size_t length, uint32_t* counts, |
| uint8_t* good_for_rle) { |
| size_t nonzero_count = 0; |
| size_t stride; |
| size_t limit; |
| size_t sum; |
| const size_t streak_limit = 1240; |
| /* Let's make the Huffman code more compatible with rle encoding. */ |
| size_t i; |
| for (i = 0; i < length; i++) { |
| if (counts[i]) { |
| ++nonzero_count; |
| } |
| } |
| if (nonzero_count < 16) { |
| return; |
| } |
| while (length != 0 && counts[length - 1] == 0) { |
| --length; |
| } |
| if (length == 0) { |
| return; /* All zeros. */ |
| } |
| /* Now counts[0..length - 1] does not have trailing zeros. */ |
| { |
| size_t nonzeros = 0; |
| uint32_t smallest_nonzero = 1 << 30; |
| for (i = 0; i < length; ++i) { |
| if (counts[i] != 0) { |
| ++nonzeros; |
| if (smallest_nonzero > counts[i]) { |
| smallest_nonzero = counts[i]; |
| } |
| } |
| } |
| if (nonzeros < 5) { |
| /* Small histogram will model it well. */ |
| return; |
| } |
| if (smallest_nonzero < 4) { |
| size_t zeros = length - nonzeros; |
| if (zeros < 6) { |
| for (i = 1; i < length - 1; ++i) { |
| if (counts[i - 1] != 0 && counts[i] == 0 && counts[i + 1] != 0) { |
| counts[i] = 1; |
| } |
| } |
| } |
| } |
| if (nonzeros < 28) { |
| return; |
| } |
| } |
| /* 2) Let's mark all population counts that already can be encoded |
| with an rle code. */ |
| memset(good_for_rle, 0, length); |
| { |
| /* Let's not spoil any of the existing good rle codes. |
| Mark any seq of 0's that is longer as 5 as a good_for_rle. |
| Mark any seq of non-0's that is longer as 7 as a good_for_rle. */ |
| uint32_t symbol = counts[0]; |
| size_t step = 0; |
| for (i = 0; i <= length; ++i) { |
| if (i == length || counts[i] != symbol) { |
| if ((symbol == 0 && step >= 5) || |
| (symbol != 0 && step >= 7)) { |
| size_t k; |
| for (k = 0; k < step; ++k) { |
| good_for_rle[i - k - 1] = 1; |
| } |
| } |
| step = 1; |
| if (i != length) { |
| symbol = counts[i]; |
| } |
| } else { |
| ++step; |
| } |
| } |
| } |
| /* 3) Let's replace those population counts that lead to more rle codes. |
| Math here is in 24.8 fixed point representation. */ |
| stride = 0; |
| limit = 256 * (counts[0] + counts[1] + counts[2]) / 3 + 420; |
| sum = 0; |
| for (i = 0; i <= length; ++i) { |
| if (i == length || good_for_rle[i] || |
| (i != 0 && good_for_rle[i - 1]) || |
| (256 * counts[i] - limit + streak_limit) >= 2 * streak_limit) { |
| if (stride >= 4 || (stride >= 3 && sum == 0)) { |
| size_t k; |
| /* The stride must end, collapse what we have, if we have enough (4). */ |
| size_t count = (sum + stride / 2) / stride; |
| if (count == 0) { |
| count = 1; |
| } |
| if (sum == 0) { |
| /* Don't make an all zeros stride to be upgraded to ones. */ |
| count = 0; |
| } |
| for (k = 0; k < stride; ++k) { |
| /* We don't want to change value at counts[i], |
| that is already belonging to the next stride. Thus - 1. */ |
| counts[i - k - 1] = (uint32_t)count; |
| } |
| } |
| stride = 0; |
| sum = 0; |
| if (i < length - 2) { |
| /* All interesting strides have a count of at least 4, */ |
| /* at least when non-zeros. */ |
| limit = 256 * (counts[i] + counts[i + 1] + counts[i + 2]) / 3 + 420; |
| } else if (i < length) { |
| limit = 256 * counts[i]; |
| } else { |
| limit = 0; |
| } |
| } |
| ++stride; |
| if (i != length) { |
| sum += counts[i]; |
| if (stride >= 4) { |
| limit = (256 * sum + stride / 2) / stride; |
| } |
| if (stride == 4) { |
| limit += 120; |
| } |
| } |
| } |
| } |
| |
| static void DecideOverRleUse(const uint8_t* depth, const size_t length, |
| BROTLI_BOOL *use_rle_for_non_zero, |
| BROTLI_BOOL *use_rle_for_zero) { |
| size_t total_reps_zero = 0; |
| size_t total_reps_non_zero = 0; |
| size_t count_reps_zero = 1; |
| size_t count_reps_non_zero = 1; |
| size_t i; |
| for (i = 0; i < length;) { |
| const uint8_t value = depth[i]; |
| size_t reps = 1; |
| size_t k; |
| for (k = i + 1; k < length && depth[k] == value; ++k) { |
| ++reps; |
| } |
| if (reps >= 3 && value == 0) { |
| total_reps_zero += reps; |
| ++count_reps_zero; |
| } |
| if (reps >= 4 && value != 0) { |
| total_reps_non_zero += reps; |
| ++count_reps_non_zero; |
| } |
| i += reps; |
| } |
| *use_rle_for_non_zero = |
| TO_BROTLI_BOOL(total_reps_non_zero > count_reps_non_zero * 2); |
| *use_rle_for_zero = TO_BROTLI_BOOL(total_reps_zero > count_reps_zero * 2); |
| } |
| |
| void BrotliWriteHuffmanTree(const uint8_t* depth, |
| size_t length, |
| size_t* tree_size, |
| uint8_t* tree, |
| uint8_t* extra_bits_data) { |
| uint8_t previous_value = BROTLI_INITIAL_REPEATED_CODE_LENGTH; |
| size_t i; |
| BROTLI_BOOL use_rle_for_non_zero = BROTLI_FALSE; |
| BROTLI_BOOL use_rle_for_zero = BROTLI_FALSE; |
| |
| /* Throw away trailing zeros. */ |
| size_t new_length = length; |
| for (i = 0; i < length; ++i) { |
| if (depth[length - i - 1] == 0) { |
| --new_length; |
| } else { |
| break; |
| } |
| } |
| |
| /* First gather statistics on if it is a good idea to do rle. */ |
| if (length > 50) { |
| /* Find rle coding for longer codes. |
| Shorter codes seem not to benefit from rle. */ |
| DecideOverRleUse(depth, new_length, |
| &use_rle_for_non_zero, &use_rle_for_zero); |
| } |
| |
| /* Actual rle coding. */ |
| for (i = 0; i < new_length;) { |
| const uint8_t value = depth[i]; |
| size_t reps = 1; |
| if ((value != 0 && use_rle_for_non_zero) || |
| (value == 0 && use_rle_for_zero)) { |
| size_t k; |
| for (k = i + 1; k < new_length && depth[k] == value; ++k) { |
| ++reps; |
| } |
| } |
| if (value == 0) { |
| BrotliWriteHuffmanTreeRepetitionsZeros( |
| reps, tree_size, tree, extra_bits_data); |
| } else { |
| BrotliWriteHuffmanTreeRepetitions(previous_value, |
| value, reps, tree_size, |
| tree, extra_bits_data); |
| previous_value = value; |
| } |
| i += reps; |
| } |
| } |
| |
| static uint16_t BrotliReverseBits(size_t num_bits, uint16_t bits) { |
| static const size_t kLut[16] = { /* Pre-reversed 4-bit values. */ |
| 0x0, 0x8, 0x4, 0xc, 0x2, 0xa, 0x6, 0xe, |
| 0x1, 0x9, 0x5, 0xd, 0x3, 0xb, 0x7, 0xf |
| }; |
| size_t retval = kLut[bits & 0xf]; |
| size_t i; |
| for (i = 4; i < num_bits; i += 4) { |
| retval <<= 4; |
| bits = (uint16_t)(bits >> 4); |
| retval |= kLut[bits & 0xf]; |
| } |
| retval >>= ((0 - num_bits) & 0x3); |
| return (uint16_t)retval; |
| } |
| |
| /* 0..15 are values for bits */ |
| #define MAX_HUFFMAN_BITS 16 |
| |
| void BrotliConvertBitDepthsToSymbols(const uint8_t *depth, |
| size_t len, |
| uint16_t *bits) { |
| /* In Brotli, all bit depths are [1..15] |
| 0 bit depth means that the symbol does not exist. */ |
| uint16_t bl_count[MAX_HUFFMAN_BITS] = { 0 }; |
| uint16_t next_code[MAX_HUFFMAN_BITS]; |
| size_t i; |
| int code = 0; |
| for (i = 0; i < len; ++i) { |
| ++bl_count[depth[i]]; |
| } |
| bl_count[0] = 0; |
| next_code[0] = 0; |
| for (i = 1; i < MAX_HUFFMAN_BITS; ++i) { |
| code = (code + bl_count[i - 1]) << 1; |
| next_code[i] = (uint16_t)code; |
| } |
| for (i = 0; i < len; ++i) { |
| if (depth[i]) { |
| bits[i] = BrotliReverseBits(depth[i], next_code[depth[i]]++); |
| } |
| } |
| } |
| |
| #if defined(__cplusplus) || defined(c_plusplus) |
| } /* extern "C" */ |
| #endif |