c++实现霍夫曼编码：实现任意Q符号的N重序列信源的最优R进制编码

以下是C++实现任意Q符号的N重序列信源的最优R进制编码的代码示例：

#include <iostream>
#include <vector>
#include <unordered_map>
#include <queue>
#include <cmath>

using namespace std;

// 定义哈夫曼树的节点
struct Node {
  string str;
  int freq;
  Node* left;
  Node* right;

  Node(string s, int f) : str(s), freq(f), left(NULL), right(NULL) {}

  ~Node() {
    delete left;
    delete right;
  }
};

// 定义哈夫曼树节点的比较器
struct NodeComparator {
  bool operator()(Node* a, Node* b) { return a->freq > b->freq; }
};

// 哈夫曼编码函数
unordered_map<string, string> huffmanEncoding(vector<string>& seq, int n, int r) {
  // 统计序列出现的频率
  unordered_map<string, int> freqMap;
  for (int i = 0; i < seq.size(); i += n) {
    string str = seq.substr(i, n);
    freqMap[str]++;
  }

  // 将序列频率信息转换为节点信息
  priority_queue<Node*, vector<Node*>, NodeComparator> minHeap;
  for (auto pair : freqMap) {
    minHeap.push(new Node(pair.first, pair.second));
  }

  // 构建哈夫曼树
  while (minHeap.size() > 1) {
    Node* left = minHeap.top();
    minHeap.pop();
    Node* right = minHeap.top();
    minHeap.pop();
    Node* parent = new Node(left->str + right->str, left->freq + right->freq);
    parent->left = left;
    parent->right = right;
    minHeap.push(parent);
  }

  // 构建哈夫曼编码表
  unordered_map<string, string> encodingMap;
  function<void(Node*, string)> dfs = [&](Node* node, string code) {
    if (!node) {
      return;
    }
    if (node->str.length() == n) {
      encodingMap[node->str] = code;
    }
    dfs(node->left, code + "0");
    dfs(node->right, code + "1");
  };
  dfs(minHeap.top(), "");

  // 将编码表转换为R进制编码表
  unordered_map<string, string> rEncodingMap;
  for (auto pair : encodingMap) {
    string str = pair.second;
    int num = 0;
    for (int i = 0; i < str.length(); i++) {
      num += (str[i] - '0') * pow(2, i);
    }
    string rEncoding = "";
    while (num > 0) {
      rEncoding = to_string(num % r) + rEncoding;
      num /= r;
    }
    rEncodingMap[pair.first] = rEncoding;
  }

  return rEncodingMap;
}

int main() {
  string seq = "ABCDEABCDEABCDEABCDE";
  int n = 3;
  int r = 5;
  vector<string> subSeqs;
  for (int i = 0; i < seq.length(); i += n) {
    subSeqs.push_back(seq.substr(i, n));
  }
  unordered_map<string, string> encodingMap = huffmanEncoding(subSeqs, n, r);
  for (auto pair : encodingMap) {
    cout << pair.first << ": " << pair.second << endl;
  }
  return 0;
}

上述代码中，首先使用 `unordered_map` 统计序列中各个子序列的出现频率，然后将频率信息转换为节点信息，并使用最小堆构建哈夫曼树。接着使用深度优先搜索构建哈夫曼编码表，并返回编码表。最后，将编码表转换为R进制编码表，并输出各个子序列对应的编码。