C# を使用してハフマン符号化アルゴリズムを作成する方法

// 步骤1：统计字符频率
Dictionary frequencies = new Dictionary();
string data = "Hello, World!";
foreach (char c in data)
{
    if (frequencies.ContainsKey(c))
    {
        frequencies[c]++;
    }
    else
    {
        frequencies[c] = 1;
    }
}

// 步骤2：构建霍夫曼树
var pq = new PriorityQueue();
foreach (var entry in frequencies)
{
    pq.Enqueue(new HuffmanNode(entry.Key, entry.Value), entry.Value);
}

while (pq.Count > 1)
{
    var left = pq.Dequeue();
    var right = pq.Dequeue();
    pq.Enqueue(new HuffmanNode(left, right), left.Frequency + right.Frequency);
}

HuffmanNode root = pq.Dequeue();

// 步骤3：生成霍夫曼编码
var codes = new Dictionary();
GenerateCodes(root, "", codes);

void GenerateCodes(HuffmanNode node, string code, Dictionary codes)
{
    if (node.IsLeaf())
    {
        codes[node.Character] = code;
    }
    else
    {
        GenerateCodes(node.Left, code + '0', codes);
        GenerateCodes(node.Right, code + '1', codes);
    }
}

// 步骤4：压缩和解压缩
string compressedData = Compress(data, codes);
string decompressedData = Decompress(compressedData, root);

string Compress(string data, Dictionary codes)
{
    StringBuilder compressed = new StringBuilder();
    foreach (char c in data)
    {
        compressed.Append(codes[c]);
    }
    return compressed.ToString();
}

string Decompress(string compressedData, HuffmanNode root)
{
    StringBuilder decompressed = new StringBuilder();
    HuffmanNode current = root;
    foreach (char c in compressedData)
    {
        if (c == '0')
        {
            current = current.Left;
        }
        else if (c == '1')
        {
            current = current.Right;
        }

        if (current.IsLeaf())
        {
            decompressed.Append(current.Character);
            current = root;
        }
    }
    return decompressed.ToString();
}