AuroraMiddleware/brotli
1
0
Fork 0
mirror of https://github.com/google/brotli.git synced 2024-11-22 11:40:06 +00:00
Code Issues Packages Projects Releases Wiki Activity

Make the histogram clustering function more generic.

Browse Source 
Change the template parameter to be the histogram class
instead of the alphabet size of the histogram.
This commit is contained in:
Zoltan Szabadka 2014-10-28 13:36:21 +01:00
parent c6c08e492e
commit f321ba1964
1 changed files with 19 additions and 18 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

37
enc/cluster.h
View File

@ -20,6 +20,7 @@
#include <math.h> #include <math.h>
#include <stdint.h> #include <stdint.h>
#include <stdio.h> #include <stdio.h>
#include <algorithm>
#include <complex> #include <complex>
#include <map> #include <map>
#include <set> #include <set>
@ -59,8 +60,8 @@ inline double ClusterCostDiff(int size_a, int size_b) {
// Computes the bit cost reduction by combining out[idx1] and out[idx2] and if // 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 heap. // it is below a threshold, stores the pair (idx1, idx2) in the *pairs heap.
template<int kSize> template<typename HistogramType>
void CompareAndPushToHeap(const Histogram<kSize>* out, void CompareAndPushToHeap(const HistogramType* out,
const int* cluster_size, const int* cluster_size,
int idx1, int idx2, int idx1, int idx2,
std::vector<HistogramPair>* pairs) { std::vector<HistogramPair>* pairs) {
@ -90,7 +91,7 @@ void CompareAndPushToHeap(const Histogram<kSize>* out,
} else { } else {
double threshold = pairs->empty() ? 1e99 : double threshold = pairs->empty() ? 1e99 :
std::max(0.0, (*pairs)[0].cost_diff); std::max(0.0, (*pairs)[0].cost_diff);
Histogram<kSize> combo = out[idx1]; HistogramType combo = out[idx1];
combo.AddHistogram(out[idx2]); combo.AddHistogram(out[idx2]);
double cost_combo = PopulationCost(combo); double cost_combo = PopulationCost(combo);
if (cost_combo < threshold - p.cost_diff) { if (cost_combo < threshold - p.cost_diff) {
@ -105,8 +106,8 @@ void CompareAndPushToHeap(const Histogram<kSize>* out,
} }
} }
template<int kSize> template<typename HistogramType>
void HistogramCombine(Histogram<kSize>* out, void HistogramCombine(HistogramType* out,
int* cluster_size, int* cluster_size,
int* symbols, int* symbols,
int symbols_size, int symbols_size,
@ -178,22 +179,22 @@ void HistogramCombine(Histogram<kSize>* out,
// Histogram refinement // Histogram refinement
// What is the bit cost of moving histogram from cur_symbol to candidate. // What is the bit cost of moving histogram from cur_symbol to candidate.
template<int kSize> template<typename HistogramType>
double HistogramBitCostDistance(const Histogram<kSize>& histogram, double HistogramBitCostDistance(const HistogramType& histogram,
const Histogram<kSize>& candidate) { const HistogramType& candidate) {
if (histogram.total_count_ == 0) { if (histogram.total_count_ == 0) {
return 0.0; return 0.0;
} }
Histogram<kSize> tmp = histogram; HistogramType tmp = histogram;
tmp.AddHistogram(candidate); tmp.AddHistogram(candidate);
return PopulationCost(tmp) - candidate.bit_cost_; return PopulationCost(tmp) - candidate.bit_cost_;
} }
// Find the best 'out' histogram for each of the 'in' histograms. // Find the best 'out' histogram for each of the 'in' histograms.
// Note: we assume that out[]->bit_cost_ is already up-to-date. // Note: we assume that out[]->bit_cost_ is already up-to-date.
template<int kSize> template<typename HistogramType>
void HistogramRemap(const Histogram<kSize>* in, int in_size, void HistogramRemap(const HistogramType* in, int in_size,
Histogram<kSize>* out, int* symbols) { HistogramType* out, int* symbols) {
std::set<int> all_symbols; std::set<int> all_symbols;
for (int i = 0; i < in_size; ++i) { for (int i = 0; i < in_size; ++i) {
all_symbols.insert(symbols[i]); all_symbols.insert(symbols[i]);
@ -224,10 +225,10 @@ void HistogramRemap(const Histogram<kSize>* in, int in_size,
// Reorder histograms in *out so that the new symbols in *symbols come in // Reorder histograms in *out so that the new symbols in *symbols come in
// increasing order. // increasing order.
template<int kSize> template<typename HistogramType>
void HistogramReindex(std::vector<Histogram<kSize> >* out, void HistogramReindex(std::vector<HistogramType>* out,
std::vector<int>* symbols) { std::vector<int>* symbols) {
std::vector<Histogram<kSize> > tmp(*out); std::vector<HistogramType> tmp(*out);
std::map<int, int> new_index; std::map<int, int> new_index;
int next_index = 0; int next_index = 0;
for (int i = 0; i < symbols->size(); ++i) { for (int i = 0; i < symbols->size(); ++i) {
@ -246,11 +247,11 @@ void HistogramReindex(std::vector<Histogram<kSize> >* out,
// Clusters similar histograms in 'in' together, the selected histograms are // Clusters similar histograms in 'in' together, the selected histograms are
// placed in 'out', and for each index in 'in', *histogram_symbols will // placed in 'out', and for each index in 'in', *histogram_symbols will
// indicate which of the 'out' histograms is the best approximation. // indicate which of the 'out' histograms is the best approximation.
template<int kSize> template<typename HistogramType>
void ClusterHistograms(const std::vector<Histogram<kSize> >& in, void ClusterHistograms(const std::vector<HistogramType>& in,
int num_contexts, int num_blocks, int num_contexts, int num_blocks,
int max_histograms, int max_histograms,
std::vector<Histogram<kSize> >* out, std::vector<HistogramType>* out,
std::vector<int>* histogram_symbols) { std::vector<int>* histogram_symbols) {
const int in_size = num_contexts * num_blocks; const int in_size = num_contexts * num_blocks;
std::vector<int> cluster_size(in_size, 1); std::vector<int> cluster_size(in_size, 1);