import java.util.*; class HuffmanNode implements Comparable<HuffmanNode> { int frequency; char data; HuffmanNode left, right; public HuffmanNode(int frequency, char data) { this.frequency = frequency; this.data = data; } public boolean isLeaf() { return left == null && right == null; } @Override public int compareTo(HuffmanNode node) { return frequency - node.frequency; } } public class HuffmanCoding { public static void main(String[] args) { String text = "Hello, world!"; Map<Character, Integer> frequencyMap = buildFrequencyMap(text); HuffmanNode root = buildHuffmanTree(frequencyMap); Map<Character, String> huffmanCodes = buildHuffmanCodes(root); System.out.println("Original text: " + text); System.out.println("Huffman codes: " + huffmanCodes); System.out.println("Encoded text: " + encode(text, huffmanCodes)); System.out.println("Decoded text: " + decode(encode(text, huffmanCodes), root)); } private static Map<Character, Integer> buildFrequencyMap(String text) { Map<Character, Integer> frequencyMap = new HashMap<>(); for (char c : text.toCharArray()) { frequencyMap.put(c, frequencyMap.getOrDefault(c, 0) + 1); } return frequencyMap; } private static HuffmanNode buildHuffmanTree(Map<Character, Integer> frequencyMap) { PriorityQueue<HuffmanNode> priorityQueue = new PriorityQueue<>(); for (Map.Entry<Character, Integer> entry : frequencyMap.entrySet()) { priorityQueue.offer(new HuffmanNode(entry.getValue(), entry.getKey())); } while (priorityQueue.size() > 1) { HuffmanNode left = priorityQueue.poll(); HuffmanNode right = priorityQueue.poll(); HuffmanNode parent = new HuffmanNode(left.frequency + right.frequency, '-'); parent.left = left; parent.right = right; priorityQueue.offer(parent); } return priorityQueue.poll(); } private static Map<Character, String> buildHuffmanCodes(HuffmanNode root) { Map<Character, String> huffmanCodes = new HashMap<>(); buildHuffmanCodesHelper(root, "", huffmanCodes); return huffmanCodes; } private static void buildHuffmanCodesHelper(HuffmanNode node, String code, Map<Character, String> huffmanCodes) { if (node.isLeaf()) { huffmanCodes.put(node.data, code); return; } buildHuffmanCodesHelper(node.left, code + "0", huffmanCodes); buildHuffmanCodesHelper(node.right, code + "1", huffmanCodes); } private static String encode(String text, Map<Character, String> huffmanCodes) { StringBuilder encodedText = new StringBuilder(); for (char c : text.toCharArray()) { encodedText.append(huffmanCodes.get(c)); } return encodedText.toString(); } private static String decode(String encodedText, HuffmanNode root) { StringBuilder decodedText = new StringBuilder(); HuffmanNode current = root; for (char c : encodedText.toCharArray()) { 后面代码请补充完整

接下来的代码是对编码文本进行解码的部分，请继续阅读：

for (char c : encodedText.toCharArray()) {
    if (c == '0') {
        current = current.left;
    } else if (c == '1') {
        current = current.right;
    }

    if (current.isLeaf()) {
        decodedText.append(current.data);
        current = root;
    }
}

return decodedText.toString();

这段代码使用了当前字符的编码（0或1）来遍历Huffman树。如果遇到叶子节点，就将对应的字符添加到解码文本中，并将当前节点重新设置为根节点，以便继续解码下一个字符。最后返回解码后的文本。

希望这段代码能帮助到您！如果您有任何其他问题，请随时问我。

相关问题

在一个class里用java编写代码

为了实现本周实验的内容，可以使用Java编程语言来构建一个`BinaryTree`类以及一个`HuffmanTree`类。以下是具体的实现方案：

### 基本题 - 二叉树操作

#### BinaryTree 类定义
首先定义一个表示二叉树节点的内部类 `Node` 和主类 `BinaryTree`:

public class BinaryTree {
    static class Node {
        int data;
        Node left, right;

        public Node(int item) {
            data = item;
            left = right = null;
        }
    }

    Node root;

    // 构造函数
    public BinaryTree() {
        this.root = null;
    }

    // 查找最大值的方法
    public int findMax(Node node) {
        if (node == null) return Integer.MIN_VALUE;
        int res = node.data;
        int lres = findMax(node.left);
        int rres = findMax(node.right);

        if (lres > res) res = lres;
        if (rres > res) res = rres;
        return res;
    }

    // 求所有节点数据总和的方法
    public int sumOfNodes(Node node) {
        if (node == null) return 0;
        return node.data + sumOfNodes(node.left) + sumOfNodes(node.right);
    }

    // 获取树高度的方法
    public int getHeight(Node node) {
        if (node == null) return 0;
        return Math.max(getHeight(node.left), getHeight(node.right)) + 1;
    }

    // 统计单分支节点数量的方法
    public int countSingleChildNodes(Node node) {
        if (node == null) return 0;
        if ((node.left != null && node.right == null) || (node.left == null && node.right != null))
            return 1 + countSingleChildNodes(node.left) + countSingleChildNodes(node.right);
        else
            return countSingleChildNodes(node.left) + countSingleChildNodes(node.right);
    }
}

### 拓展题 - 哈夫曼树

#### HuffmanTree 类定义
接下来是创建哈夫曼树并生成编码的过程：

import java.util.*;

public class HuffmanTree {
    static class TreeNode implements Comparable<TreeNode> {
        char ch;
        int freq;
        TreeNode left, right;

        public TreeNode(char ch, int freq, TreeNode left, TreeNode right) {
            this.ch = ch;
            this.freq = freq;
            this.left = left;
            this.right = right;
        }

        @Override
        public int compareTo(TreeNode other) {
            return this.freq - other.freq;
        }
    }

    private Map<Character, String> huffmanCodes = new HashMap<>();

    public void buildHuffmanTree(String input) {
        Map<Character, Integer> frequencyMap = getFrequency(input);
        PriorityQueue<TreeNode> priorityQueue = new PriorityQueue<>();
        
        for (char c : frequencyMap.keySet()) {
            priorityQueue.add(new TreeNode(c, frequencyMap.get(c), null, null));
        }

        while (priorityQueue.size() > 1) {
            TreeNode first = priorityQueue.poll();
            TreeNode second = priorityQueue.poll();

            TreeNode merged = new TreeNode('\0', first.freq + second.freq, first, second);
            priorityQueue.add(merged);
        }

        TreeNode root = priorityQueue.poll();
        generateCodes(root, "");
    }

    private Map<Character, Integer> getFrequency(String s) {
        Map<Character, Integer> map = new HashMap<>();
        for (char c : s.toCharArray()) {
            map.put(c, map.getOrDefault(c, 0) + 1);
        }
        return map;
    }

    private void generateCodes(TreeNode node, String code) {
        if (node == null) return;
        if (node.ch != '\0') {
            huffmanCodes.put(node.ch, code);
        }
        generateCodes(node.left, code + "0");
        generateCodes(node.right, code + "1");
    }

    public String encode(String text) {
        StringBuilder sb = new StringBuilder();
        for (char c : text.toCharArray()) {
            sb.append(huffmanCodes.get(c));
        }
        return sb.toString();
    }

    public String decode(String encodedText) {
        StringBuilder sb = new StringBuilder();
        TreeNode current = root;
        for (char bit : encodedText.toCharArray()) {
            if (bit == '0') {
                current = current.left;
            } else if (bit == '1') {
                current = current.right;
            }

            if (current != null && current.ch != '\0') {
                sb.append(current.ch);
                current = root; // 重置到根节点
            }
        }
        return sb.toString();
    }
}

以上就是完整的Java实现，包括了二叉树的基本操作（查找最大值、求和、计算高度及统计单分支节点）和哈夫曼树的构建与编码解码功能。希望这对你有帮助！如果有任何疑问或需要进一步解释，请随时告诉我。

哈夫曼树java实现

哈夫曼树是一种用于数据压缩的树形结构，它通过将出现频率较高的字符用较短的编码表示，从而实现数据的高效压缩。下面是哈夫曼树的Java实现：

import java.util.PriorityQueue;

class Node implements Comparable<Node> {
    char data;
    int frequency;
    Node left, right;

    public Node(char data, int frequency) {
        this.data = data;
        this.frequency = frequency;
        left = right = null;
    }

    @Override
    public int compareTo(Node node) {
        return this.frequency - node.frequency;
    }
}

public class HuffmanTree {
    public static void main(String[] args) {
        String text = "Hello, World!";
        Node root = buildHuffmanTree(text);
        String encodedText = encode(root, text);
        String decodedText = decode(root, encodedText);

        System.out.println("Original text: " + text);
        System.out.println("Encoded text: " + encodedText);
        System.out.println("Decoded text: " + decodedText);
    }

    public static Node buildHuffmanTree(String text) {
        int[] frequencies = new int[256];
        for (char c : text.toCharArray()) {
            frequencies[c]++;
        }

        PriorityQueue<Node> queue = new PriorityQueue<>();
        for (int i = 0; i < 256; i++) {
            if (frequencies[i] > 0) {
                queue.add(new Node((char) i, frequencies[i]));
            }
        }

        while (queue.size() > 1) {
            Node left = queue.poll();
            Node right = queue.poll();
            Node parent = new Node('\0', left.frequency + right.frequency);
            parent.left = left;
            parent.right = right;
            queue.add(parent);
        }

        return queue.poll();
    }

    public static String encode(Node root, String text) {
        StringBuilder encodedText = new StringBuilder();
        encodeHelper(root, text, encodedText);
        return encodedText.toString();
    }

    private static void encodeHelper(Node node, String text, StringBuilder encodedText) {
        if (node == null) {
            return;
        }

        if (node.left == null && node.right == null) {
            encodedText.append(node.data);
            return;
        }

        encodeHelper(node.left, text, encodedText);
        encodeHelper(node.right, text, encodedText);
    }

    public static String decode(Node root, String encodedText) {
        StringBuilder decodedText = new StringBuilder();
        Node current = root;
        for (char c : encodedText.toCharArray()) {
            if (c == '0') {
                current = current.left;
            } else if (c == '1') {
                current = current.right;
            }

            if (current.left == null && current.right == null) {
                decodedText.append(current.data);
                current = root;
            }
        }
        return decodedText.toString();
    }
}

以上是一个简单的哈夫曼树的Java实现。它包括了构建哈夫曼树、编码和解码的功能。你可以通过调用`buildHuffmanTree`方法来构建哈夫曼树，然后使用`encode`方法对文本进行编码，使用`decode`方法对编码后的文本进行解码。