зеркало из https://github.com/mozilla/gecko-dev.git
128 строки
4.0 KiB
C
128 строки
4.0 KiB
C
/* NOLINT(build/header_guard) */
|
|
/* Copyright 2013 Google Inc. All Rights Reserved.
|
|
|
|
Distributed under MIT license.
|
|
See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
|
|
*/
|
|
|
|
/* template parameters: FN */
|
|
|
|
#define HistogramType FN(Histogram)
|
|
|
|
double FN(BrotliPopulationCost)(const HistogramType* histogram) {
|
|
static const double kOneSymbolHistogramCost = 12;
|
|
static const double kTwoSymbolHistogramCost = 20;
|
|
static const double kThreeSymbolHistogramCost = 28;
|
|
static const double kFourSymbolHistogramCost = 37;
|
|
const size_t data_size = FN(HistogramDataSize)();
|
|
int count = 0;
|
|
size_t s[5];
|
|
double bits = 0.0;
|
|
size_t i;
|
|
if (histogram->total_count_ == 0) {
|
|
return kOneSymbolHistogramCost;
|
|
}
|
|
for (i = 0; i < data_size; ++i) {
|
|
if (histogram->data_[i] > 0) {
|
|
s[count] = i;
|
|
++count;
|
|
if (count > 4) break;
|
|
}
|
|
}
|
|
if (count == 1) {
|
|
return kOneSymbolHistogramCost;
|
|
}
|
|
if (count == 2) {
|
|
return (kTwoSymbolHistogramCost + (double)histogram->total_count_);
|
|
}
|
|
if (count == 3) {
|
|
const uint32_t histo0 = histogram->data_[s[0]];
|
|
const uint32_t histo1 = histogram->data_[s[1]];
|
|
const uint32_t histo2 = histogram->data_[s[2]];
|
|
const uint32_t histomax =
|
|
BROTLI_MAX(uint32_t, histo0, BROTLI_MAX(uint32_t, histo1, histo2));
|
|
return (kThreeSymbolHistogramCost +
|
|
2 * (histo0 + histo1 + histo2) - histomax);
|
|
}
|
|
if (count == 4) {
|
|
uint32_t histo[4];
|
|
uint32_t h23;
|
|
uint32_t histomax;
|
|
for (i = 0; i < 4; ++i) {
|
|
histo[i] = histogram->data_[s[i]];
|
|
}
|
|
/* Sort */
|
|
for (i = 0; i < 4; ++i) {
|
|
size_t j;
|
|
for (j = i + 1; j < 4; ++j) {
|
|
if (histo[j] > histo[i]) {
|
|
BROTLI_SWAP(uint32_t, histo, j, i);
|
|
}
|
|
}
|
|
}
|
|
h23 = histo[2] + histo[3];
|
|
histomax = BROTLI_MAX(uint32_t, h23, histo[0]);
|
|
return (kFourSymbolHistogramCost +
|
|
3 * h23 + 2 * (histo[0] + histo[1]) - histomax);
|
|
}
|
|
|
|
{
|
|
/* In this loop we compute the entropy of the histogram and simultaneously
|
|
build a simplified histogram of the code length codes where we use the
|
|
zero repeat code 17, but we don't use the non-zero repeat code 16. */
|
|
size_t max_depth = 1;
|
|
uint32_t depth_histo[BROTLI_CODE_LENGTH_CODES] = { 0 };
|
|
const double log2total = FastLog2(histogram->total_count_);
|
|
for (i = 0; i < data_size;) {
|
|
if (histogram->data_[i] > 0) {
|
|
/* Compute -log2(P(symbol)) = -log2(count(symbol)/total_count) =
|
|
= log2(total_count) - log2(count(symbol)) */
|
|
double log2p = log2total - FastLog2(histogram->data_[i]);
|
|
/* Approximate the bit depth by round(-log2(P(symbol))) */
|
|
size_t depth = (size_t)(log2p + 0.5);
|
|
bits += histogram->data_[i] * log2p;
|
|
if (depth > 15) {
|
|
depth = 15;
|
|
}
|
|
if (depth > max_depth) {
|
|
max_depth = depth;
|
|
}
|
|
++depth_histo[depth];
|
|
++i;
|
|
} else {
|
|
/* Compute the run length of zeros and add the appropriate number of 0
|
|
and 17 code length codes to the code length code histogram. */
|
|
uint32_t reps = 1;
|
|
size_t k;
|
|
for (k = i + 1; k < data_size && histogram->data_[k] == 0; ++k) {
|
|
++reps;
|
|
}
|
|
i += reps;
|
|
if (i == data_size) {
|
|
/* Don't add any cost for the last zero run, since these are encoded
|
|
only implicitly. */
|
|
break;
|
|
}
|
|
if (reps < 3) {
|
|
depth_histo[0] += reps;
|
|
} else {
|
|
reps -= 2;
|
|
while (reps > 0) {
|
|
++depth_histo[BROTLI_REPEAT_ZERO_CODE_LENGTH];
|
|
/* Add the 3 extra bits for the 17 code length code. */
|
|
bits += 3;
|
|
reps >>= 3;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
/* Add the estimated encoding cost of the code length code histogram. */
|
|
bits += (double)(18 + 2 * max_depth);
|
|
/* Add the entropy of the code length code histogram. */
|
|
bits += BitsEntropy(depth_histo, BROTLI_CODE_LENGTH_CODES);
|
|
}
|
|
return bits;
|
|
}
|
|
|
|
#undef HistogramType
|