package brotli /* Copyright 2013 Google Inc. All Rights Reserved. Distributed under MIT license. See file LICENSE for detail or copy at https://opensource.org/licenses/MIT */ /* Function to find backward reference copies. */ func computeDistanceCode(distance uint, max_distance uint, dist_cache []int) uint { if distance <= max_distance { var distance_plus_3 uint = distance + 3 var offset0 uint = distance_plus_3 - uint(dist_cache[0]) var offset1 uint = distance_plus_3 - uint(dist_cache[1]) if distance == uint(dist_cache[0]) { return 0 } else if distance == uint(dist_cache[1]) { return 1 } else if offset0 < 7 { return (0x9750468 >> (4 * offset0)) & 0xF } else if offset1 < 7 { return (0xFDB1ACE >> (4 * offset1)) & 0xF } else if distance == uint(dist_cache[2]) { return 2 } else if distance == uint(dist_cache[3]) { return 3 } } return distance + numDistanceShortCodes - 1 } func createBackwardReferences(num_bytes uint, position uint, ringbuffer []byte, ringbuffer_mask uint, params *encoderParams, hasher hasherHandle, dist_cache []int, last_insert_len *uint, commands *[]command, num_literals *uint) { var max_backward_limit uint = maxBackwardLimit(params.lgwin) var insert_length uint = *last_insert_len var pos_end uint = position + num_bytes var store_end uint if num_bytes >= hasher.StoreLookahead() { store_end = position + num_bytes - hasher.StoreLookahead() + 1 } else { store_end = position } var random_heuristics_window_size uint = literalSpreeLengthForSparseSearch(params) var apply_random_heuristics uint = position + random_heuristics_window_size var gap uint = 0 /* Set maximum distance, see section 9.1. of the spec. */ const kMinScore uint = scoreBase + 100 /* For speed up heuristics for random data. */ /* Minimum score to accept a backward reference. */ hasher.PrepareDistanceCache(dist_cache) var sr2 hasherSearchResult var sr hasherSearchResult for position+hasher.HashTypeLength() < pos_end { var max_length uint = pos_end - position var max_distance uint = brotli_min_size_t(position, max_backward_limit) sr.len = 0 sr.len_code_delta = 0 sr.distance = 0 sr.score = kMinScore hasher.FindLongestMatch(¶ms.dictionary, ringbuffer, ringbuffer_mask, dist_cache, position, max_length, max_distance, gap, params.dist.max_distance, &sr) if sr.score > kMinScore { /* Found a match. Let's look for something even better ahead. */ var delayed_backward_references_in_row int = 0 max_length-- for ; ; max_length-- { var cost_diff_lazy uint = 175 if params.quality < minQualityForExtensiveReferenceSearch { sr2.len = brotli_min_size_t(sr.len-1, max_length) } else { sr2.len = 0 } sr2.len_code_delta = 0 sr2.distance = 0 sr2.score = kMinScore max_distance = brotli_min_size_t(position+1, max_backward_limit) hasher.FindLongestMatch(¶ms.dictionary, ringbuffer, ringbuffer_mask, dist_cache, position+1, max_length, max_distance, gap, params.dist.max_distance, &sr2) if sr2.score >= sr.score+cost_diff_lazy { /* Ok, let's just write one byte for now and start a match from the next byte. */ position++ insert_length++ sr = sr2 delayed_backward_references_in_row++ if delayed_backward_references_in_row < 4 && position+hasher.HashTypeLength() < pos_end { continue } } break } apply_random_heuristics = position + 2*sr.len + random_heuristics_window_size max_distance = brotli_min_size_t(position, max_backward_limit) { /* The first 16 codes are special short-codes, and the minimum offset is 1. */ var distance_code uint = computeDistanceCode(sr.distance, max_distance+gap, dist_cache) if (sr.distance <= (max_distance + gap)) && distance_code > 0 { dist_cache[3] = dist_cache[2] dist_cache[2] = dist_cache[1] dist_cache[1] = dist_cache[0] dist_cache[0] = int(sr.distance) hasher.PrepareDistanceCache(dist_cache) } *commands = append(*commands, makeCommand(¶ms.dist, insert_length, sr.len, sr.len_code_delta, distance_code)) } *num_literals += insert_length insert_length = 0 /* Put the hash keys into the table, if there are enough bytes left. Depending on the hasher implementation, it can push all positions in the given range or only a subset of them. Avoid hash poisoning with RLE data. */ { var range_start uint = position + 2 var range_end uint = brotli_min_size_t(position+sr.len, store_end) if sr.distance < sr.len>>2 { range_start = brotli_min_size_t(range_end, brotli_max_size_t(range_start, position+sr.len-(sr.distance<<2))) } hasher.StoreRange(ringbuffer, ringbuffer_mask, range_start, range_end) } position += sr.len } else { insert_length++ position++ /* If we have not seen matches for a long time, we can skip some match lookups. Unsuccessful match lookups are very very expensive and this kind of a heuristic speeds up compression quite a lot. */ if position > apply_random_heuristics { /* Going through uncompressible data, jump. */ if position > apply_random_heuristics+4*random_heuristics_window_size { var kMargin uint = brotli_max_size_t(hasher.StoreLookahead()-1, 4) /* It is quite a long time since we saw a copy, so we assume that this data is not compressible, and store hashes less often. Hashes of non compressible data are less likely to turn out to be useful in the future, too, so we store less of them to not to flood out the hash table of good compressible data. */ var pos_jump uint = brotli_min_size_t(position+16, pos_end-kMargin) for ; position < pos_jump; position += 4 { hasher.Store(ringbuffer, ringbuffer_mask, position) insert_length += 4 } } else { var kMargin uint = brotli_max_size_t(hasher.StoreLookahead()-1, 2) var pos_jump uint = brotli_min_size_t(position+8, pos_end-kMargin) for ; position < pos_jump; position += 2 { hasher.Store(ringbuffer, ringbuffer_mask, position) insert_length += 2 } } } } } insert_length += pos_end - position *last_insert_len = insert_length }