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Unified Diff: third_party/brotli/enc/bit_cost.h

Issue 2537133002: Update brotli to v1.0.0-snapshot. (Closed)
Patch Set: Fixed typo Created 4 years ago
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Index: third_party/brotli/enc/bit_cost.h
diff --git a/third_party/brotli/enc/bit_cost.h b/third_party/brotli/enc/bit_cost.h
index 4652006864c581c6589b92e50932251fca5a9124..e69ee04a1876ea69ebb082795ec0b6ff19b7b6d9 100644
--- a/third_party/brotli/enc/bit_cost.h
+++ b/third_party/brotli/enc/bit_cost.h
@@ -4,19 +4,22 @@
See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
*/
-// Functions to estimate the bit cost of Huffman trees.
+/* Functions to estimate the bit cost of Huffman trees. */
#ifndef BROTLI_ENC_BIT_COST_H_
#define BROTLI_ENC_BIT_COST_H_
-#include "./entropy_encode.h"
+#include <brotli/types.h>
#include "./fast_log.h"
-#include "./types.h"
+#include "./histogram.h"
+#include "./port.h"
-namespace brotli {
+#if defined(__cplusplus) || defined(c_plusplus)
+extern "C" {
+#endif
-static inline double ShannonEntropy(const uint32_t *population, size_t size,
- size_t *total) {
+static BROTLI_INLINE double ShannonEntropy(const uint32_t *population,
+ size_t size, size_t *total) {
size_t sum = 0;
double retval = 0;
const uint32_t *population_end = population + size;
@@ -27,135 +30,34 @@ static inline double ShannonEntropy(const uint32_t *population, size_t size,
while (population < population_end) {
p = *population++;
sum += p;
- retval -= static_cast<double>(p) * FastLog2(p);
+ retval -= (double)p * FastLog2(p);
odd_number_of_elements_left:
p = *population++;
sum += p;
- retval -= static_cast<double>(p) * FastLog2(p);
+ retval -= (double)p * FastLog2(p);
}
- if (sum) retval += static_cast<double>(sum) * FastLog2(sum);
+ if (sum) retval += (double)sum * FastLog2(sum);
*total = sum;
return retval;
}
-static inline double BitsEntropy(const uint32_t *population, size_t size) {
+static BROTLI_INLINE double BitsEntropy(
+ const uint32_t *population, size_t size) {
size_t sum;
double retval = ShannonEntropy(population, size, &sum);
if (retval < sum) {
- // At least one bit per literal is needed.
- retval = static_cast<double>(sum);
+ /* At least one bit per literal is needed. */
+ retval = (double)sum;
}
return retval;
}
-template<int kSize>
-double PopulationCost(const Histogram<kSize>& histogram) {
- static const double kOneSymbolHistogramCost = 12;
- static const double kTwoSymbolHistogramCost = 20;
- static const double kThreeSymbolHistogramCost = 28;
- static const double kFourSymbolHistogramCost = 37;
- if (histogram.total_count_ == 0) {
- return kOneSymbolHistogramCost;
- }
- int count = 0;
- int s[5];
- for (int i = 0; i < kSize; ++i) {
- if (histogram.data_[i] > 0) {
- s[count] = i;
- ++count;
- if (count > 4) break;
- }
- }
- if (count == 1) {
- return kOneSymbolHistogramCost;
- }
- if (count == 2) {
- return (kTwoSymbolHistogramCost +
- static_cast<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 = std::max(histo0, std::max(histo1, histo2));
- return (kThreeSymbolHistogramCost +
- 2 * (histo0 + histo1 + histo2) - histomax);
- }
- if (count == 4) {
- uint32_t histo[4];
- for (int i = 0; i < 4; ++i) {
- histo[i] = histogram.data_[s[i]];
- }
- // Sort
- for (int i = 0; i < 4; ++i) {
- for (int j = i + 1; j < 4; ++j) {
- if (histo[j] > histo[i]) {
- std::swap(histo[j], histo[i]);
- }
- }
- }
- const uint32_t h23 = histo[2] + histo[3];
- const uint32_t histomax = std::max(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.
- double bits = 0;
- size_t max_depth = 1;
- uint32_t depth_histo[kCodeLengthCodes] = { 0 };
- const double log2total = FastLog2(histogram.total_count_);
- for (size_t i = 0; i < kSize;) {
- 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 = static_cast<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;
- for (size_t k = i + 1; k < kSize && histogram.data_[k] == 0; ++k) {
- ++reps;
- }
- i += reps;
- if (i == kSize) {
- // 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[17];
- // 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 += static_cast<double>(18 + 2 * max_depth);
- // Add the entropy of the code length code histogram.
- bits += BitsEntropy(depth_histo, kCodeLengthCodes);
- return bits;
-}
+BROTLI_INTERNAL double BrotliPopulationCostLiteral(const HistogramLiteral*);
+BROTLI_INTERNAL double BrotliPopulationCostCommand(const HistogramCommand*);
+BROTLI_INTERNAL double BrotliPopulationCostDistance(const HistogramDistance*);
-} // namespace brotli
+#if defined(__cplusplus) || defined(c_plusplus)
+} /* extern "C" */
+#endif
-#endif // BROTLI_ENC_BIT_COST_H_
+#endif /* BROTLI_ENC_BIT_COST_H_ */
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