mirror of https://github.com/acidanthera/audk.git
123 lines
4.1 KiB
C
123 lines
4.1 KiB
C
/* Copyright 2010 Google Inc. All Rights Reserved.
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Distributed under MIT license.
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See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
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*/
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/* Entropy encoding (Huffman) utilities. */
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#ifndef BROTLI_ENC_ENTROPY_ENCODE_H_
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#define BROTLI_ENC_ENTROPY_ENCODE_H_
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#include "../common/types.h"
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#include "./port.h"
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#if defined(__cplusplus) || defined(c_plusplus)
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extern "C" {
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#endif
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/* A node of a Huffman tree. */
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typedef struct HuffmanTree {
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uint32_t total_count_;
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int16_t index_left_;
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int16_t index_right_or_value_;
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} HuffmanTree;
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static BROTLI_INLINE void InitHuffmanTree(HuffmanTree* self, uint32_t count,
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int16_t left, int16_t right) {
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self->total_count_ = count;
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self->index_left_ = left;
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self->index_right_or_value_ = right;
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}
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/* Returns 1 is assignment of depths succeded, otherwise 0. */
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BROTLI_INTERNAL BROTLI_BOOL BrotliSetDepth(
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int p, HuffmanTree* pool, uint8_t* depth, int max_depth);
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/* This function will create a Huffman tree.
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The (data,length) contains the population counts.
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The tree_limit is the maximum bit depth of the Huffman codes.
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The depth contains the tree, i.e., how many bits are used for
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the symbol.
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The actual Huffman tree is constructed in the tree[] array, which has to
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be at least 2 * length + 1 long.
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See http://en.wikipedia.org/wiki/Huffman_coding */
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BROTLI_INTERNAL void BrotliCreateHuffmanTree(const uint32_t *data,
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const size_t length,
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const int tree_limit,
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HuffmanTree* tree,
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uint8_t *depth);
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/* Change the population counts in a way that the consequent
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Huffman tree compression, especially its rle-part will be more
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likely to compress this data more efficiently.
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length contains the size of the histogram.
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counts contains the population counts.
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good_for_rle is a buffer of at least length size */
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BROTLI_INTERNAL void BrotliOptimizeHuffmanCountsForRle(
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size_t length, uint32_t* counts, uint8_t* good_for_rle);
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/* Write a Huffman tree from bit depths into the bitstream representation
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of a Huffman tree. The generated Huffman tree is to be compressed once
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more using a Huffman tree */
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BROTLI_INTERNAL void BrotliWriteHuffmanTree(const uint8_t* depth,
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size_t num,
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size_t* tree_size,
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uint8_t* tree,
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uint8_t* extra_bits_data);
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/* Get the actual bit values for a tree of bit depths. */
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BROTLI_INTERNAL void BrotliConvertBitDepthsToSymbols(const uint8_t *depth,
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size_t len,
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uint16_t *bits);
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/* Input size optimized Shell sort. */
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typedef BROTLI_BOOL (*HuffmanTreeComparator)(
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const HuffmanTree*, const HuffmanTree*);
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static BROTLI_INLINE void SortHuffmanTreeItems(HuffmanTree* items,
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const size_t n, HuffmanTreeComparator comparator) {
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static const size_t gaps[] = {132, 57, 23, 10, 4, 1};
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if (n < 13) {
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/* Insertion sort. */
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size_t i;
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for (i = 1; i < n; ++i) {
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HuffmanTree tmp = items[i];
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size_t k = i;
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size_t j = i - 1;
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while (comparator(&tmp, &items[j])) {
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items[k] = items[j];
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k = j;
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if (!j--) break;
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}
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items[k] = tmp;
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}
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return;
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} else {
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/* Shell sort. */
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int g = n < 57 ? 2 : 0;
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for (; g < 6; ++g) {
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size_t gap = gaps[g];
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size_t i;
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for (i = gap; i < n; ++i) {
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size_t j = i;
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HuffmanTree tmp = items[i];
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for (; j >= gap && comparator(&tmp, &items[j - gap]); j -= gap) {
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items[j] = items[j - gap];
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}
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items[j] = tmp;
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}
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}
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}
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}
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#if defined(__cplusplus) || defined(c_plusplus)
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} /* extern "C" */
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#endif
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#endif /* BROTLI_ENC_ENTROPY_ENCODE_H_ */
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