brotli/enc/entropy_encode.cc - platform/external/chromium_org/third_party/brotli/src - Git at Google

 // Copyright 2010 Google Inc. All Rights Reserved.
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
 // You may obtain a copy of the License at
 //
 // http://www.apache.org/licenses/LICENSE-2.0
 //
 // Unless required by applicable law or agreed to in writing, software
 // distributed under the License is distributed on an "AS IS" BASIS,
 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 // See the License for the specific language governing permissions and
 // limitations under the License.
 //
 // Entropy encoding (Huffman) utilities.

 #include "./entropy_encode.h"

 #include <stdint.h>
 #include <algorithm>
 #include <limits>
 #include <vector>
 #include <cstdlib>

 #include "./histogram.h"

 namespace brotli {

 namespace {

 struct HuffmanTree {
   HuffmanTree();
   HuffmanTree(int count, int16_t left, int16_t right)
       : total_count_(count),
         index_left_(left),
         index_right_or_value_(right) {
   }
   int total_count_;
   int16_t index_left_;
   int16_t index_right_or_value_;
 };

 HuffmanTree::HuffmanTree() {}

 // Sort the root nodes, least popular first.
 bool SortHuffmanTree(const HuffmanTree &v0, const HuffmanTree &v1) {
   if (v0.total_count_ == v1.total_count_) {
     return v0.index_right_or_value_ > v1.index_right_or_value_;
   }
   return v0.total_count_ < v1.total_count_;
 }

 void SetDepth(const HuffmanTree &p,
               HuffmanTree *pool,
               uint8_t *depth,
               int level) {
   if (p.index_left_ >= 0) {
     ++level;
     SetDepth(pool[p.index_left_], pool, depth, level);
     SetDepth(pool[p.index_right_or_value_], pool, depth, level);
   } else {
     depth[p.index_right_or_value_] = level;
   }
 }

 }  // namespace

 // This function will create a Huffman tree.
 //
 // The catch here is that the tree cannot be arbitrarily deep.
 // Brotli specifies a maximum depth of 15 bits for "code trees"
 // and 7 bits for "code length code trees."
 //
 // count_limit is the value that is to be faked as the minimum value
 // and this minimum value is raised until the tree matches the
 // maximum length requirement.
 //
 // This algorithm is not of excellent performance for very long data blocks,
 // especially when population counts are longer than 2**tree_limit, but
 // we are not planning to use this with extremely long blocks.
 //
 // See http://en.wikipedia.org/wiki/Huffman_coding
 void CreateHuffmanTree(const int *data,
                        const int length,
                        const int tree_limit,
                        uint8_t *depth) {
   // For block sizes below 64 kB, we never need to do a second iteration
   // of this loop. Probably all of our block sizes will be smaller than
   // that, so this loop is mostly of academic interest. If we actually
   // would need this, we would be better off with the Katajainen algorithm.
   for (int count_limit = 1; ; count_limit *= 2) {
     std::vector<HuffmanTree> tree;
     tree.reserve(2 * length + 1);

     for (int i = 0; i < length; ++i) {
       if (data[i]) {
         const int count = std::max(data[i], count_limit);
         tree.push_back(HuffmanTree(count, -1, i));
       }
     }

     const int n = tree.size();
     if (n == 1) {
       depth[tree[0].index_right_or_value_] = 1;      // Only one element.
       break;
     }

     std::sort(tree.begin(), tree.end(), SortHuffmanTree);

     // The nodes are:
     // [0, n): the sorted leaf nodes that we start with.
     // [n]: we add a sentinel here.
     // [n + 1, 2n): new parent nodes are added here, starting from
     //              (n+1). These are naturally in ascending order.
     // [2n]: we add a sentinel at the end as well.
     // There will be (2n+1) elements at the end.
     const HuffmanTree sentinel(std::numeric_limits<int>::max(), -1, -1);
     tree.push_back(sentinel);
     tree.push_back(sentinel);

     int i = 0;      // Points to the next leaf node.
     int j = n + 1;  // Points to the next non-leaf node.
     for (int k = n - 1; k > 0; --k) {
       int left, right;
       if (tree[i].total_count_ <= tree[j].total_count_) {
         left = i;
         ++i;
       } else {
         left = j;
         ++j;
       }
       if (tree[i].total_count_ <= tree[j].total_count_) {
         right = i;
         ++i;
       } else {
         right = j;
         ++j;
       }

       // The sentinel node becomes the parent node.
       int j_end = tree.size() - 1;
       tree[j_end].total_count_ =
           tree[left].total_count_ + tree[right].total_count_;
       tree[j_end].index_left_ = left;
       tree[j_end].index_right_or_value_ = right;

       // Add back the last sentinel node.
       tree.push_back(sentinel);
     }
     SetDepth(tree[2 * n - 1], &tree[0], depth, 0);

     // We need to pack the Huffman tree in tree_limit bits.
     // If this was not successful, add fake entities to the lowest values
     // and retry.
     if (*std::max_element(&depth[0], &depth[length]) <= tree_limit) {
       break;
     }
   }
 }

 void Reverse(uint8_t* v, int start, int end) {
   --end;
   while (start < end) {
     int tmp = v[start];
     v[start] = v[end];
     v[end] = tmp;
     ++start;
     --end;
   }
 }

 void WriteHuffmanTreeRepetitions(
     const int previous_value,
     const int value,
     int repetitions,
     uint8_t* tree,
     uint8_t* extra_bits,
     int* tree_size) {
   if (previous_value != value) {
     tree[*tree_size] = value;
     extra_bits[*tree_size] = 0;
     ++(*tree_size);
     --repetitions;
   }
   if (repetitions == 7) {
     tree[*tree_size] = value;
     extra_bits[*tree_size] = 0;
     ++(*tree_size);
     --repetitions;
   }
   if (repetitions < 3) {
     for (int i = 0; i < repetitions; ++i) {
       tree[*tree_size] = value;
       extra_bits[*tree_size] = 0;
       ++(*tree_size);
     }
   } else {
     repetitions -= 3;
     int start = *tree_size;
     while (repetitions >= 0) {
       tree[*tree_size] = 16;
       extra_bits[*tree_size] = repetitions & 0x3;
       ++(*tree_size);
       repetitions >>= 2;
       --repetitions;
     }
     Reverse(tree, start, *tree_size);
     Reverse(extra_bits, start, *tree_size);
   }
 }

 void WriteHuffmanTreeRepetitionsZeros(
     int repetitions,
     uint8_t* tree,
     uint8_t* extra_bits,
     int* tree_size) {
   if (repetitions == 11) {
     tree[*tree_size] = 0;
     extra_bits[*tree_size] = 0;
     ++(*tree_size);
     --repetitions;
   }
   if (repetitions < 3) {
     for (int i = 0; i < repetitions; ++i) {
       tree[*tree_size] = 0;
       extra_bits[*tree_size] = 0;
       ++(*tree_size);
     }
   } else {
     repetitions -= 3;
     int start = *tree_size;
     while (repetitions >= 0) {
       tree[*tree_size] = 17;
       extra_bits[*tree_size] = repetitions & 0x7;
       ++(*tree_size);
       repetitions >>= 3;
       --repetitions;
     }
     Reverse(tree, start, *tree_size);
     Reverse(extra_bits, start, *tree_size);
   }
 }


 int OptimizeHuffmanCountsForRle(int length, int* counts) {
   int stride;
   int limit;
   int sum;
   uint8_t* good_for_rle;
   // Let's make the Huffman code more compatible with rle encoding.
   int i;
   for (; length >= 0; --length) {
     if (length == 0) {
       return 1;  // All zeros.
     }
     if (counts[length - 1] != 0) {
       // Now counts[0..length - 1] does not have trailing zeros.
       break;
     }
   }
   {
     int nonzeros = 0;
     int smallest_nonzero = 1 << 30;
     for (i = 0; i < length; ++i) {
       if (counts[i] != 0) {
         ++nonzeros;
         if (smallest_nonzero > counts[i]) {
           smallest_nonzero = counts[i];
         }
       }
     }
     if (nonzeros < 5) {
       // Small histogram will model it well.
       return 1;
     }
     int zeros = length - nonzeros;
     if (smallest_nonzero < 4) {
       if (zeros < 6) {
         for (i = 1; i < length - 1; ++i) {
           if (counts[i - 1] != 0 && counts[i] == 0 && counts[i + 1] != 0) {
             counts[i] = 1;
           }
         }
       }
     }
     if (nonzeros < 28) {
       return 1;
     }
   }
   // 2) Let's mark all population counts that already can be encoded
   // with an rle code.
   good_for_rle = (uint8_t*)calloc(length, 1);
   if (good_for_rle == NULL) {
     return 0;
   }
   {
     // Let's not spoil any of the existing good rle codes.
     // Mark any seq of 0's that is longer as 5 as a good_for_rle.
     // Mark any seq of non-0's that is longer as 7 as a good_for_rle.
     int symbol = counts[0];
     int stride = 0;
     for (i = 0; i < length + 1; ++i) {
       if (i == length || counts[i] != symbol) {
         if ((symbol == 0 && stride >= 5) ||
             (symbol != 0 && stride >= 7)) {
           int k;
           for (k = 0; k < stride; ++k) {
             good_for_rle[i - k - 1] = 1;
           }
         }
         stride = 1;
         if (i != length) {
           symbol = counts[i];
         }
       } else {
         ++stride;
       }
     }
   }
   // 3) Let's replace those population counts that lead to more rle codes.
   // Math here is in 24.8 fixed point representation.
   const int streak_limit = 1240;
   stride = 0;
   limit = 256 * (counts[0] + counts[1] + counts[2]) / 3 + 420;
   sum = 0;
   for (i = 0; i < length + 1; ++i) {
     if (i == length || good_for_rle[i] ||
         (i != 0 && good_for_rle[i - 1]) ||
         abs(256 * counts[i] - limit) >= streak_limit) {
       if (stride >= 4 || (stride >= 3 && sum == 0)) {
         int k;
         // The stride must end, collapse what we have, if we have enough (4).
         int count = (sum + stride / 2) / stride;
         if (count < 1) {
           count = 1;
         }
         if (sum == 0) {
           // Don't make an all zeros stride to be upgraded to ones.
           count = 0;
         }
         for (k = 0; k < stride; ++k) {
           // We don't want to change value at counts[i],
           // that is already belonging to the next stride. Thus - 1.
           counts[i - k - 1] = count;
         }
       }
       stride = 0;
       sum = 0;
       if (i < length - 2) {
         // All interesting strides have a count of at least 4,
         // at least when non-zeros.
         limit = 256 * (counts[i] + counts[i + 1] + counts[i + 2]) / 3 + 420;
       } else if (i < length) {
         limit = 256 * counts[i];
       } else {
         limit = 0;
       }
     }
     ++stride;
     if (i != length) {
       sum += counts[i];
       if (stride >= 4) {
         limit = (256 * sum + stride / 2) / stride;
       }
       if (stride == 4) {
         limit += 120;
       }
     }
   }
   free(good_for_rle);
   return 1;
 }


 static void DecideOverRleUse(const uint8_t* depth, const int length,
                              bool *use_rle_for_non_zero,
                              bool *use_rle_for_zero) {
   int total_reps_zero = 0;
   int total_reps_non_zero = 0;
   int count_reps_zero = 0;
   int count_reps_non_zero = 0;
   int new_length = length;
   for (int i = 0; i < length; ++i) {
     if (depth[length - i - 1] == 0) {
       --new_length;
     } else {
       break;
     }
   }
   for (uint32_t i = 0; i < new_length;) {
     const int value = depth[i];
     int reps = 1;
     // Find rle coding for longer codes.
     // Shorter codes seem not to benefit from rle.
     for (uint32_t k = i + 1; k < new_length && depth[k] == value; ++k) {
       ++reps;
     }
     if (reps >= 3 && value == 0) {
       total_reps_zero += reps;
       ++count_reps_zero;
     }
     if (reps >= 4 && value != 0) {
       total_reps_non_zero += reps;
       ++count_reps_non_zero;
     }
     i += reps;
   }
   total_reps_non_zero -= count_reps_non_zero * 2;
   total_reps_zero -= count_reps_zero * 2;
   *use_rle_for_non_zero = total_reps_non_zero > 2;
   *use_rle_for_zero = total_reps_zero > 2;
 }


 void WriteHuffmanTree(const uint8_t* depth, const int length,
                       uint8_t* tree,
                       uint8_t* extra_bits_data,
                       int* huffman_tree_size) {
   int previous_value = 8;

   // First gather statistics on if it is a good idea to do rle.
   bool use_rle_for_non_zero;
   bool use_rle_for_zero;
   DecideOverRleUse(depth, length, &use_rle_for_non_zero, &use_rle_for_zero);

   // Actual rle coding.
   for (uint32_t i = 0; i < length;) {
     const int value = depth[i];
     int reps = 1;
     if (length > 50) {
       // Find rle coding for longer codes.
       // Shorter codes seem not to benefit from rle.
       if ((value != 0 && use_rle_for_non_zero) ||
           (value == 0 && use_rle_for_zero)) {
         for (uint32_t k = i + 1; k < length && depth[k] == value; ++k) {
           ++reps;
         }
       }
     }
     if (value == 0) {
       WriteHuffmanTreeRepetitionsZeros(reps, tree, extra_bits_data,
                                        huffman_tree_size);
     } else {
       WriteHuffmanTreeRepetitions(previous_value, value, reps, tree,
                                   extra_bits_data, huffman_tree_size);
       previous_value = value;
     }
     i += reps;
   }
   // Throw away trailing zeros.
   for (; *huffman_tree_size > 0; --(*huffman_tree_size)) {
     if (tree[*huffman_tree_size - 1] > 0 && tree[*huffman_tree_size - 1] < 17) {
       break;
     }
   }
 }

 namespace {

 uint16_t ReverseBits(int num_bits, uint16_t bits) {
   static const size_t kLut[16] = {  // Pre-reversed 4-bit values.
     0x0, 0x8, 0x4, 0xc, 0x2, 0xa, 0x6, 0xe,
     0x1, 0x9, 0x5, 0xd, 0x3, 0xb, 0x7, 0xf
   };
   size_t retval = kLut[bits & 0xf];
   for (int i = 4; i < num_bits; i += 4) {
     retval <<= 4;
     bits >>= 4;
     retval |= kLut[bits & 0xf];
   }
   retval >>= (-num_bits & 0x3);
   return retval;
 }

 }  // namespace

 void ConvertBitDepthsToSymbols(const uint8_t *depth, int len, uint16_t *bits) {
   // In Brotli, all bit depths are [1..15]
   // 0 bit depth means that the symbol does not exist.
   const int kMaxBits = 16;  // 0..15 are values for bits
   uint16_t bl_count[kMaxBits] = { 0 };
   {
     for (int i = 0; i < len; ++i) {
       ++bl_count[depth[i]];
     }
     bl_count[0] = 0;
   }
   uint16_t next_code[kMaxBits];
   next_code[0] = 0;
   {
     int code = 0;
     for (int bits = 1; bits < kMaxBits; ++bits) {
       code = (code + bl_count[bits - 1]) << 1;
       next_code[bits] = code;
     }
   }
   for (int i = 0; i < len; ++i) {
     if (depth[i]) {
       bits[i] = ReverseBits(depth[i], next_code[depth[i]]++);
     }
   }
 }

 }  // namespace brotli
	// Copyright 2010 Google Inc. All Rights Reserved.
	//
	// Licensed under the Apache License, Version 2.0 (the "License");
	// you may not use this file except in compliance with the License.
	// You may obtain a copy of the License at
	//
	// http://www.apache.org/licenses/LICENSE-2.0
	//
	// Unless required by applicable law or agreed to in writing, software
	// distributed under the License is distributed on an "AS IS" BASIS,
	// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	// See the License for the specific language governing permissions and
	// limitations under the License.
	//
	// Entropy encoding (Huffman) utilities.

	#include "./entropy_encode.h"

	#include <stdint.h>
	#include <algorithm>
	#include <limits>
	#include <vector>
	#include <cstdlib>

	#include "./histogram.h"

	namespace brotli {

	namespace {

	struct HuffmanTree {
	HuffmanTree();
	HuffmanTree(int count, int16_t left, int16_t right)
	: total_count_(count),
	index_left_(left),
	index_right_or_value_(right) {
	}
	int total_count_;
	int16_t index_left_;
	int16_t index_right_or_value_;
	};

	HuffmanTree::HuffmanTree() {}

	// Sort the root nodes, least popular first.
	bool SortHuffmanTree(const HuffmanTree &v0, const HuffmanTree &v1) {
	if (v0.total_count_ == v1.total_count_) {
	return v0.index_right_or_value_ > v1.index_right_or_value_;
	}
	return v0.total_count_ < v1.total_count_;
	}

	void SetDepth(const HuffmanTree &p,
	HuffmanTree *pool,
	uint8_t *depth,
	int level) {
	if (p.index_left_ >= 0) {
	++level;
	SetDepth(pool[p.index_left_], pool, depth, level);
	SetDepth(pool[p.index_right_or_value_], pool, depth, level);
	} else {
	depth[p.index_right_or_value_] = level;
	}
	}

	} // namespace

	// This function will create a Huffman tree.
	//
	// The catch here is that the tree cannot be arbitrarily deep.
	// Brotli specifies a maximum depth of 15 bits for "code trees"
	// and 7 bits for "code length code trees."
	//
	// count_limit is the value that is to be faked as the minimum value
	// and this minimum value is raised until the tree matches the
	// maximum length requirement.
	//
	// This algorithm is not of excellent performance for very long data blocks,
	// especially when population counts are longer than 2**tree_limit, but
	// we are not planning to use this with extremely long blocks.
	//
	// See http://en.wikipedia.org/wiki/Huffman_coding
	void CreateHuffmanTree(const int *data,
	const int length,
	const int tree_limit,
	uint8_t *depth) {
	// For block sizes below 64 kB, we never need to do a second iteration
	// of this loop. Probably all of our block sizes will be smaller than
	// that, so this loop is mostly of academic interest. If we actually
	// would need this, we would be better off with the Katajainen algorithm.
	for (int count_limit = 1; ; count_limit *= 2) {
	std::vector<HuffmanTree> tree;
	tree.reserve(2 * length + 1);

	for (int i = 0; i < length; ++i) {
	if (data[i]) {
	const int count = std::max(data[i], count_limit);
	tree.push_back(HuffmanTree(count, -1, i));
	}
	}

	const int n = tree.size();
	if (n == 1) {
	depth[tree[0].index_right_or_value_] = 1; // Only one element.
	break;
	}

	std::sort(tree.begin(), tree.end(), SortHuffmanTree);

	// The nodes are:
	// [0, n): the sorted leaf nodes that we start with.
	// [n]: we add a sentinel here.
	// [n + 1, 2n): new parent nodes are added here, starting from
	// (n+1). These are naturally in ascending order.
	// [2n]: we add a sentinel at the end as well.
	// There will be (2n+1) elements at the end.
	const HuffmanTree sentinel(std::numeric_limits<int>::max(), -1, -1);
	tree.push_back(sentinel);
	tree.push_back(sentinel);

	int i = 0; // Points to the next leaf node.
	int j = n + 1; // Points to the next non-leaf node.
	for (int k = n - 1; k > 0; --k) {
	int left, right;
	if (tree[i].total_count_ <= tree[j].total_count_) {
	left = i;
	++i;
	} else {
	left = j;
	++j;
	}
	if (tree[i].total_count_ <= tree[j].total_count_) {
	right = i;
	++i;
	} else {
	right = j;
	++j;
	}

	// The sentinel node becomes the parent node.
	int j_end = tree.size() - 1;
	tree[j_end].total_count_ =
	tree[left].total_count_ + tree[right].total_count_;
	tree[j_end].index_left_ = left;
	tree[j_end].index_right_or_value_ = right;

	// Add back the last sentinel node.
	tree.push_back(sentinel);
	}
	SetDepth(tree[2 * n - 1], &tree[0], depth, 0);

	// We need to pack the Huffman tree in tree_limit bits.
	// If this was not successful, add fake entities to the lowest values
	// and retry.
	if (*std::max_element(&depth[0], &depth[length]) <= tree_limit) {
	break;
	}
	}
	}

	void Reverse(uint8_t* v, int start, int end) {
	--end;
	while (start < end) {
	int tmp = v[start];
	v[start] = v[end];
	v[end] = tmp;
	++start;
	--end;
	}
	}

	void WriteHuffmanTreeRepetitions(
	const int previous_value,
	const int value,
	int repetitions,
	uint8_t* tree,
	uint8_t* extra_bits,
	int* tree_size) {
	if (previous_value != value) {
	tree[*tree_size] = value;
	extra_bits[*tree_size] = 0;
	++(*tree_size);
	--repetitions;
	}
	if (repetitions == 7) {
	tree[*tree_size] = value;
	extra_bits[*tree_size] = 0;
	++(*tree_size);
	--repetitions;
	}
	if (repetitions < 3) {
	for (int i = 0; i < repetitions; ++i) {
	tree[*tree_size] = value;
	extra_bits[*tree_size] = 0;
	++(*tree_size);
	}
	} else {
	repetitions -= 3;
	int start = *tree_size;
	while (repetitions >= 0) {
	tree[*tree_size] = 16;
	extra_bits[*tree_size] = repetitions & 0x3;
	++(*tree_size);
	repetitions >>= 2;
	--repetitions;
	}
	Reverse(tree, start, *tree_size);
	Reverse(extra_bits, start, *tree_size);
	}
	}

	void WriteHuffmanTreeRepetitionsZeros(
	int repetitions,
	uint8_t* tree,
	uint8_t* extra_bits,
	int* tree_size) {
	if (repetitions == 11) {
	tree[*tree_size] = 0;
	extra_bits[*tree_size] = 0;
	++(*tree_size);
	--repetitions;
	}
	if (repetitions < 3) {
	for (int i = 0; i < repetitions; ++i) {
	tree[*tree_size] = 0;
	extra_bits[*tree_size] = 0;
	++(*tree_size);
	}
	} else {
	repetitions -= 3;
	int start = *tree_size;
	while (repetitions >= 0) {
	tree[*tree_size] = 17;
	extra_bits[*tree_size] = repetitions & 0x7;
	++(*tree_size);
	repetitions >>= 3;
	--repetitions;
	}
	Reverse(tree, start, *tree_size);
	Reverse(extra_bits, start, *tree_size);
	}
	}


	int OptimizeHuffmanCountsForRle(int length, int* counts) {
	int stride;
	int limit;
	int sum;
	uint8_t* good_for_rle;
	// Let's make the Huffman code more compatible with rle encoding.
	int i;
	for (; length >= 0; --length) {
	if (length == 0) {
	return 1; // All zeros.
	}
	if (counts[length - 1] != 0) {
	// Now counts[0..length - 1] does not have trailing zeros.
	break;
	}
	}
	{
	int nonzeros = 0;
	int smallest_nonzero = 1 << 30;
	for (i = 0; i < length; ++i) {
	if (counts[i] != 0) {
	++nonzeros;
	if (smallest_nonzero > counts[i]) {
	smallest_nonzero = counts[i];
	}
	}
	}
	if (nonzeros < 5) {
	// Small histogram will model it well.
	return 1;
	}
	int zeros = length - nonzeros;
	if (smallest_nonzero < 4) {
	if (zeros < 6) {
	for (i = 1; i < length - 1; ++i) {
	if (counts[i - 1] != 0 && counts[i] == 0 && counts[i + 1] != 0) {
	counts[i] = 1;
	}
	}
	}
	}
	if (nonzeros < 28) {
	return 1;
	}
	}
	// 2) Let's mark all population counts that already can be encoded
	// with an rle code.
	good_for_rle = (uint8_t*)calloc(length, 1);
	if (good_for_rle == NULL) {
	return 0;
	}
	{
	// Let's not spoil any of the existing good rle codes.
	// Mark any seq of 0's that is longer as 5 as a good_for_rle.
	// Mark any seq of non-0's that is longer as 7 as a good_for_rle.
	int symbol = counts[0];
	int stride = 0;
	for (i = 0; i < length + 1; ++i) {
	if (i == length \|\| counts[i] != symbol) {
	if ((symbol == 0 && stride >= 5) \|\|
	(symbol != 0 && stride >= 7)) {
	int k;
	for (k = 0; k < stride; ++k) {
	good_for_rle[i - k - 1] = 1;
	}
	}
	stride = 1;
	if (i != length) {
	symbol = counts[i];
	}
	} else {
	++stride;
	}
	}
	}
	// 3) Let's replace those population counts that lead to more rle codes.
	// Math here is in 24.8 fixed point representation.
	const int streak_limit = 1240;
	stride = 0;
	limit = 256 * (counts[0] + counts[1] + counts[2]) / 3 + 420;
	sum = 0;
	for (i = 0; i < length + 1; ++i) {
	if (i == length \|\| good_for_rle[i] \|\|
	(i != 0 && good_for_rle[i - 1]) \|\|
	abs(256 * counts[i] - limit) >= streak_limit) {
	if (stride >= 4 \|\| (stride >= 3 && sum == 0)) {
	int k;
	// The stride must end, collapse what we have, if we have enough (4).
	int count = (sum + stride / 2) / stride;
	if (count < 1) {
	count = 1;
	}
	if (sum == 0) {
	// Don't make an all zeros stride to be upgraded to ones.
	count = 0;
	}
	for (k = 0; k < stride; ++k) {
	// We don't want to change value at counts[i],
	// that is already belonging to the next stride. Thus - 1.
	counts[i - k - 1] = count;
	}
	}
	stride = 0;
	sum = 0;
	if (i < length - 2) {
	// All interesting strides have a count of at least 4,
	// at least when non-zeros.
	limit = 256 * (counts[i] + counts[i + 1] + counts[i + 2]) / 3 + 420;
	} else if (i < length) {
	limit = 256 * counts[i];
	} else {
	limit = 0;
	}
	}
	++stride;
	if (i != length) {
	sum += counts[i];
	if (stride >= 4) {
	limit = (256 * sum + stride / 2) / stride;
	}
	if (stride == 4) {
	limit += 120;
	}
	}
	}
	free(good_for_rle);
	return 1;
	}


	static void DecideOverRleUse(const uint8_t* depth, const int length,
	bool *use_rle_for_non_zero,
	bool *use_rle_for_zero) {
	int total_reps_zero = 0;
	int total_reps_non_zero = 0;
	int count_reps_zero = 0;
	int count_reps_non_zero = 0;
	int new_length = length;
	for (int i = 0; i < length; ++i) {
	if (depth[length - i - 1] == 0) {
	--new_length;
	} else {
	break;
	}
	}
	for (uint32_t i = 0; i < new_length;) {
	const int value = depth[i];
	int reps = 1;
	// Find rle coding for longer codes.
	// Shorter codes seem not to benefit from rle.
	for (uint32_t k = i + 1; k < new_length && depth[k] == value; ++k) {
	++reps;
	}
	if (reps >= 3 && value == 0) {
	total_reps_zero += reps;
	++count_reps_zero;
	}
	if (reps >= 4 && value != 0) {
	total_reps_non_zero += reps;
	++count_reps_non_zero;
	}
	i += reps;
	}
	total_reps_non_zero -= count_reps_non_zero * 2;
	total_reps_zero -= count_reps_zero * 2;
	*use_rle_for_non_zero = total_reps_non_zero > 2;
	*use_rle_for_zero = total_reps_zero > 2;
	}


	void WriteHuffmanTree(const uint8_t* depth, const int length,
	uint8_t* tree,
	uint8_t* extra_bits_data,
	int* huffman_tree_size) {
	int previous_value = 8;

	// First gather statistics on if it is a good idea to do rle.
	bool use_rle_for_non_zero;
	bool use_rle_for_zero;
	DecideOverRleUse(depth, length, &use_rle_for_non_zero, &use_rle_for_zero);

	// Actual rle coding.
	for (uint32_t i = 0; i < length;) {
	const int value = depth[i];
	int reps = 1;
	if (length > 50) {
	// Find rle coding for longer codes.
	// Shorter codes seem not to benefit from rle.
	if ((value != 0 && use_rle_for_non_zero) \|\|
	(value == 0 && use_rle_for_zero)) {
	for (uint32_t k = i + 1; k < length && depth[k] == value; ++k) {
	++reps;
	}
	}
	}
	if (value == 0) {
	WriteHuffmanTreeRepetitionsZeros(reps, tree, extra_bits_data,
	huffman_tree_size);
	} else {
	WriteHuffmanTreeRepetitions(previous_value, value, reps, tree,
	extra_bits_data, huffman_tree_size);
	previous_value = value;
	}
	i += reps;
	}
	// Throw away trailing zeros.
	for (; huffman_tree_size > 0; --(huffman_tree_size)) {
	if (tree[huffman_tree_size - 1] > 0 && tree[huffman_tree_size - 1] < 17) {
	break;
	}
	}
	}

	namespace {

	uint16_t ReverseBits(int num_bits, uint16_t bits) {
	static const size_t kLut[16] = { // Pre-reversed 4-bit values.
	0x0, 0x8, 0x4, 0xc, 0x2, 0xa, 0x6, 0xe,
	0x1, 0x9, 0x5, 0xd, 0x3, 0xb, 0x7, 0xf
	};
	size_t retval = kLut[bits & 0xf];
	for (int i = 4; i < num_bits; i += 4) {
	retval <<= 4;
	bits >>= 4;
	retval \|= kLut[bits & 0xf];
	}
	retval >>= (-num_bits & 0x3);
	return retval;
	}

	} // namespace

	void ConvertBitDepthsToSymbols(const uint8_t depth, int len, uint16_t bits) {
	// In Brotli, all bit depths are [1..15]
	// 0 bit depth means that the symbol does not exist.
	const int kMaxBits = 16; // 0..15 are values for bits
	uint16_t bl_count[kMaxBits] = { 0 };
	{
	for (int i = 0; i < len; ++i) {
	++bl_count[depth[i]];
	}
	bl_count[0] = 0;
	}
	uint16_t next_code[kMaxBits];
	next_code[0] = 0;
	{
	int code = 0;
	for (int bits = 1; bits < kMaxBits; ++bits) {
	code = (code + bl_count[bits - 1]) << 1;
	next_code[bits] = code;
	}
	}
	for (int i = 0; i < len; ++i) {
	if (depth[i]) {
	bits[i] = ReverseBits(depth[i], next_code[depth[i]]++);
	}
	}
	}

	} // namespace brotli