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289 lines
9.5 KiB
C++
289 lines
9.5 KiB
C++
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/**
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* consteval_huffman.hpp - Provides compile-time text compression.
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* Written by Clyne Sullivan.
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* https://github.com/tcsullivan/consteval-huffman
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*/
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#ifndef TCSULLIVAN_CONSTEVAL_HUFFMAN_HPP_
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#define TCSULLIVAN_CONSTEVAL_HUFFMAN_HPP_
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#include <algorithm>
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#include <span>
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/**
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* Compresses the given character string using Huffman coding, providing a
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* minimal run-time interface for decompressing the data.
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* @tparam data The string of data to be compressed.
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* @tparam data_length The size in bytes of the data, defaults to using strlen().
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*/
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template<const char *data, std::size_t data_length = std::char_traits<char>::length(data)>
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class huffman_compress
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{
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using size_t = unsigned long int;
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// Jump to the bottom of this header for the public-facing features of this
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// class.
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// The internals needed to be defined before they were used.
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private:
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// Node structure used to build a tree for calculating Huffman codes.
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struct node {
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int value = 0;
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size_t freq = 0;
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// Below values are indices into the node list
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int parent = -1;
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int left = -1;
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int right = -1;
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};
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/**
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* Builds a list of nodes for every character that appears in the given data.
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* This list is sorted by increasing frequency.
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* @return Compile-time allocated array of nodes
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*/
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consteval static auto build_node_list() {
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// Build a list for counting every occuring value
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auto list = std::span(new node[256] {}, 256);
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for (int i = 0; i < 256; i++)
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list[i].value = i;
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for (size_t i = 0; i < data_length; i++)
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list[data[i]].freq++;
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std::sort(list.begin(), list.end(),
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[](const auto& a, const auto& b) { return a.freq < b.freq; });
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// Filter out the non-occuring values, and build a compact list to return
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auto first_valid_node = std::find_if(list.begin(), list.end(),
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[](const auto& n) { return n.freq != 0; });
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auto fit_size = std::distance(first_valid_node, list.end());
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auto fit_list = std::span(new node[fit_size] {}, fit_size);
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std::copy(first_valid_node, list.end(), fit_list.begin());
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delete[] list.data();
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return fit_list;
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}
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/**
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* Returns the count of how many nodes are in the node tree.
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*/
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consteval static auto tree_count() {
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auto list = build_node_list();
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auto count = list.size() * 2 - 1;
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delete[] list.data();
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return count;
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}
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/**
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* Builds a tree out of the node list, allowing for the calculation of
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* Huffman codes.
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* @return Compile-time allocated tree of nodes, root node at index zero.
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*/
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consteval static auto build_node_tree() {
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auto list = build_node_list();
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auto tree = std::span(new node[tree_count()] {}, tree_count());
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auto list_end = list.end(); // Track end of list as it shrinks
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auto tree_begin = tree.end(); // Build tree from bottom
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int next_parent_node_value = 0x100; // Give parent nodes unique ids
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while (1) {
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// Create parent node for two least-occuring values
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node new_node {
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next_parent_node_value++,
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list[0].freq + list[1].freq,
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-1,
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list[0].value,
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list[1].value
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};
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// Move the two nodes into the tree and remove them from the list
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*--tree_begin = list[0];
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*--tree_begin = list[1];
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std::copy(list.begin() + 2, list_end--, list.begin());
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if (std::distance(list.begin(), list_end) == 1) {
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list.front() = new_node;
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break;
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}
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// Insert the parent node back into the list
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auto insertion_point = std::find_if(list.begin(), list_end - 1,
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[&new_node](const auto& n) { return n.freq >= new_node.freq; });
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if (insertion_point != list_end - 1) {
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*(list_end - 1) = node();
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std::copy_backward(insertion_point, list_end - 1, list_end);
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}
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*insertion_point = new_node;
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}
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// Connect child nodes to their parents
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tree[0] = list[0];
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for (auto iter = tree.begin(); ++iter != tree.end();) {
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if (iter->parent == -1) {
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auto parent = std::find_if(tree.begin(), iter,
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[&iter](const auto& n) { return n.left == iter->value || n.right == iter->value; });
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if (parent != iter)
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iter->parent = std::distance(tree.begin(), parent);
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}
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}
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delete[] list.data();
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return tree;
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}
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/**
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* Determines the size of the compressed data.
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* @return A pair of total bytes used, and bits used in last byte.
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*/
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consteval static auto compressed_size_info() {
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auto tree = build_node_tree();
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size_t bytes = 1, bits = 0;
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for (size_t i = 0; i < data_length; i++) {
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auto leaf = std::find_if(tree.begin(), tree.end(),
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[c = data[i]](const auto& n) { return n.value == c; });
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while (leaf->parent != -1) {
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if (++bits == 8)
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bits = 0, bytes++;
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leaf = tree.begin() + leaf->parent;
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}
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}
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delete[] tree.data();
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return std::make_pair(bytes, bits);
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}
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/**
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* Compresses the input data, storing the result in the object instance.
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*/
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consteval void compress()
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{
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auto tree = build_node_tree();
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// Set up byte and bit count (note, we're compressing the data backwards)
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auto [bytes, bits] = compressed_size_info();
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if (bits > 0)
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bits = 8 - bits;
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else
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bits = 0, bytes--;
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// Compress data backwards, because we obtain the Huffman codes backwards
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// as we traverse towards the parent node.
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for (auto i = data_length; i > 0; i--) {
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auto leaf = std::find_if(tree.begin(), tree.end(),
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[c = data[i - 1]](auto& n) { return n.value == c; });
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while (leaf->parent != -1) {
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auto parent = tree.begin() + leaf->parent;
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if (parent->right == leaf->value)
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compressed_data[bytes - 1] |= (1 << bits);
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if (++bits == 8)
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bits = 0, --bytes;
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leaf = parent;
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}
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}
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delete[] tree.data();
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}
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/**
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* Builds the decode tree, used to decompress the data.
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* Format: three bytes per node.
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* 1. Node value, 2. Distance to left child, 3. Distance to right child.
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*/
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consteval void build_decode_tree() {
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auto tree = build_node_tree();
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for (size_t i = 0; i < tree_count(); i++) {
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// Only store node value if it represents a data value
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decode_tree[i * 3] = tree[i].value <= 0xFF ? tree[i].value : 0;
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size_t j;
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// Find the left child of this node
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for (j = i + 1; j < tree_count(); j++) {
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if (tree[i].left == tree[j].value)
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break;
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}
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decode_tree[i * 3 + 1] = j < tree_count() ? j - i : 0;
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// Find the right child of this node
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for (j = i + 1; j < tree_count(); j++) {
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if (tree[i].right == tree[j].value)
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break;
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}
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decode_tree[i * 3 + 2] = j < tree_count() ? j - i : 0;
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}
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delete[] tree.data();
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}
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// Contains the compressed data.
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unsigned char compressed_data[compressed_size_info().first] = {};
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// Contains a 'tree' that can be used to decompress the data.
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unsigned char decode_tree[3 * tree_count()] = {};
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public:
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// Utility for decoding compressed data.
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class decode_info {
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public:
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decode_info(const huffman_compress<data, data_length>& comp_data) :
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m_data(comp_data) { get_next(); }
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// Checks if another byte is available
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operator bool() const {
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const auto [size_bytes, last_bits] = m_data.compressed_size_info();
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return m_pos < (size_bytes - 1) || m_bit > (8 - last_bits);
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}
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// Gets the current byte
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int operator*() const { return m_current; }
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// Moves to the next byte
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int operator++() {
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get_next();
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return m_current;
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}
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private:
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// Internal: moves to next byte
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void get_next() {
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auto *node = m_data.decode_tree;
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do {
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bool bit = m_data.compressed_data[m_pos] & (1 << (m_bit - 1));
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if (--m_bit == 0)
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m_bit = 8, m_pos++;
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node += 3 * node[bit ? 2 : 1];
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} while (node[1] != 0);
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m_current = *node;
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}
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const huffman_compress<data>& m_data;
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size_t m_pos = 0;
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unsigned char m_bit = 8;
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int m_current = -1;
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friend class huffman_compress;
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};
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consteval huffman_compress() {
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build_decode_tree();
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compress();
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}
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consteval static auto compressed_size() {
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return sizeof(compressed_data) + sizeof(decode_tree);
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}
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consteval static auto uncompressed_size() {
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return data_length;
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}
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consteval static auto bytes_saved() {
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return uncompressed_size() - compressed_size();
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}
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// Creates a decoder object for iteratively decompressing the data.
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auto get_decoder() const {
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return decode_info(*this);
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}
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};
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#endif // TCSULLIVAN_CONSTEVAL_HUFFMAN_HPP_
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