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_ */ |