vendor.github.com.andybalholm.brotli.cluster_command.go Maven / Gradle / Ivy
The newest version!
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
*/
/* Computes the bit cost reduction by combining out[idx1] and out[idx2] and if
it is below a threshold, stores the pair (idx1, idx2) in the *pairs queue. */
func compareAndPushToQueueCommand(out []histogramCommand, cluster_size []uint32, idx1 uint32, idx2 uint32, max_num_pairs uint, pairs []histogramPair, num_pairs *uint) {
var is_good_pair bool = false
var p histogramPair
p.idx2 = 0
p.idx1 = p.idx2
p.cost_combo = 0
p.cost_diff = p.cost_combo
if idx1 == idx2 {
return
}
if idx2 < idx1 {
var t uint32 = idx2
idx2 = idx1
idx1 = t
}
p.idx1 = idx1
p.idx2 = idx2
p.cost_diff = 0.5 * clusterCostDiff(uint(cluster_size[idx1]), uint(cluster_size[idx2]))
p.cost_diff -= out[idx1].bit_cost_
p.cost_diff -= out[idx2].bit_cost_
if out[idx1].total_count_ == 0 {
p.cost_combo = out[idx2].bit_cost_
is_good_pair = true
} else if out[idx2].total_count_ == 0 {
p.cost_combo = out[idx1].bit_cost_
is_good_pair = true
} else {
var threshold float64
if *num_pairs == 0 {
threshold = 1e99
} else {
threshold = brotli_max_double(0.0, pairs[0].cost_diff)
}
var combo histogramCommand = out[idx1]
var cost_combo float64
histogramAddHistogramCommand(&combo, &out[idx2])
cost_combo = populationCostCommand(&combo)
if cost_combo < threshold-p.cost_diff {
p.cost_combo = cost_combo
is_good_pair = true
}
}
if is_good_pair {
p.cost_diff += p.cost_combo
if *num_pairs > 0 && histogramPairIsLess(&pairs[0], &p) {
/* Replace the top of the queue if needed. */
if *num_pairs < max_num_pairs {
pairs[*num_pairs] = pairs[0]
(*num_pairs)++
}
pairs[0] = p
} else if *num_pairs < max_num_pairs {
pairs[*num_pairs] = p
(*num_pairs)++
}
}
}
func histogramCombineCommand(out []histogramCommand, cluster_size []uint32, symbols []uint32, clusters []uint32, pairs []histogramPair, num_clusters uint, symbols_size uint, max_clusters uint, max_num_pairs uint) uint {
var cost_diff_threshold float64 = 0.0
var min_cluster_size uint = 1
var num_pairs uint = 0
{
/* We maintain a vector of histogram pairs, with the property that the pair
with the maximum bit cost reduction is the first. */
var idx1 uint
for idx1 = 0; idx1 < num_clusters; idx1++ {
var idx2 uint
for idx2 = idx1 + 1; idx2 < num_clusters; idx2++ {
compareAndPushToQueueCommand(out, cluster_size, clusters[idx1], clusters[idx2], max_num_pairs, pairs[0:], &num_pairs)
}
}
}
for num_clusters > min_cluster_size {
var best_idx1 uint32
var best_idx2 uint32
var i uint
if pairs[0].cost_diff >= cost_diff_threshold {
cost_diff_threshold = 1e99
min_cluster_size = max_clusters
continue
}
/* Take the best pair from the top of heap. */
best_idx1 = pairs[0].idx1
best_idx2 = pairs[0].idx2
histogramAddHistogramCommand(&out[best_idx1], &out[best_idx2])
out[best_idx1].bit_cost_ = pairs[0].cost_combo
cluster_size[best_idx1] += cluster_size[best_idx2]
for i = 0; i < symbols_size; i++ {
if symbols[i] == best_idx2 {
symbols[i] = best_idx1
}
}
for i = 0; i < num_clusters; i++ {
if clusters[i] == best_idx2 {
copy(clusters[i:], clusters[i+1:][:num_clusters-i-1])
break
}
}
num_clusters--
{
/* Remove pairs intersecting the just combined best pair. */
var copy_to_idx uint = 0
for i = 0; i < num_pairs; i++ {
var p *histogramPair = &pairs[i]
if p.idx1 == best_idx1 || p.idx2 == best_idx1 || p.idx1 == best_idx2 || p.idx2 == best_idx2 {
/* Remove invalid pair from the queue. */
continue
}
if histogramPairIsLess(&pairs[0], p) {
/* Replace the top of the queue if needed. */
var front histogramPair = pairs[0]
pairs[0] = *p
pairs[copy_to_idx] = front
} else {
pairs[copy_to_idx] = *p
}
copy_to_idx++
}
num_pairs = copy_to_idx
}
/* Push new pairs formed with the combined histogram to the heap. */
for i = 0; i < num_clusters; i++ {
compareAndPushToQueueCommand(out, cluster_size, best_idx1, clusters[i], max_num_pairs, pairs[0:], &num_pairs)
}
}
return num_clusters
}
/* What is the bit cost of moving histogram from cur_symbol to candidate. */
func histogramBitCostDistanceCommand(histogram *histogramCommand, candidate *histogramCommand) float64 {
if histogram.total_count_ == 0 {
return 0.0
} else {
var tmp histogramCommand = *histogram
histogramAddHistogramCommand(&tmp, candidate)
return populationCostCommand(&tmp) - candidate.bit_cost_
}
}