java 对排序输入进行高效霍夫曼编码 | 贪婪算法（Efficient Huffman Coding for Sorted Input

2. 如果第一个队列为空，则从第二个队列出队。
3. 否则，比较两个队列的前面，并使最小的节点出队。
4.创建一个新的内部节点，其频率等于两个节点频率之和。将第一个出队节点设为其左子节点，将第二个出队节点设为右子节点。将此节点入队到第二个队列。
5.重复步骤 3 和 4，直到队列中有多个节点。剩下的节点就是根节点，树就完成了。

示例代码：

//// java Program for Efficient Huffman Coding for Sorted input //

import java.util.PriorityQueue;
import java.util.HashMap;

// Node structure for creating a binary tree //
class Node {
char ch;
int freq;
Node left;
Node right;

Node(char c, int f) {
ch = c;
freq = f;
left = null;
right = null;
}
}

public class Main {
// Function to print the generated Huffman codes
static void printHuffmanCodes(Node root, String str) {
if (root == null)
return;
if (root.ch != '$') {
System.out.println(root.ch + ": " + str);
return;
}

printHuffmanCodes(root.left, str + "0");
printHuffmanCodes(root.right, str + "1");
}

// Function to generate Huffman codes
static void generateHuffmanCode(HashMap<Character, Integer> charFreq) {
if (charFreq.isEmpty())
return;

PriorityQueue<Node> pq = new PriorityQueue<>((a, b) -> a.freq - b.freq);

for (char c : charFreq.keySet()) {
pq.add(new Node(c, charFreq.get(c)));
}

while (pq.size() > 1) {
Node left = pq.poll();
Node right = pq.poll();
Node node = new Node('$', left.freq + right.freq);
node.left = left;
node.right = right;
pq.add(node);
}

printHuffmanCodes(pq.poll(), "");
}

public static void main(String[] args) {
HashMap<Character, Integer> charFreq = new HashMap<>();
charFreq.put('a', 5);
charFreq.put('b', 9);
charFreq.put('c', 12);
charFreq.put('d', 13);
charFreq.put('e', 16);
charFreq.put('f', 45);

generateHuffmanCode(charFreq);
}
}