哈弗曼编码压缩文件c语言实现

可以回答这个问题。哈弗曼编码是一种常用的数据压缩算法，可以通过统计字符出现频率，构建哈弗曼树，然后生成对应的编码表，将原始数据进行编码压缩。在 C 语言中，可以使用数组和结构体等数据结构来实现哈弗曼编码压缩文件。

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java实现lz77+哈弗曼压缩文件

以下是Java实现LZ77+哈夫曼压缩文件的代码示例：

import java.io.*;
import java.util.*;

public class LZ77HuffmanCompressor {
    private static final int WINDOW_SIZE = 2048;
    private static final int LOOKAHEAD_BUFFER_SIZE = 64;
    private static final int MAX_MATCH_LENGTH = 15;
    private static final int MIN_MATCH_LENGTH = 3;

    public static void compress(String inputFilePath, String outputFilePath) throws IOException {
        // 读取输入文件
        byte[] inputBytes = readBytesFromFile(inputFilePath);

        // 初始化哈夫曼编码器
        HuffmanEncoder huffmanEncoder = new HuffmanEncoder();

        // 初始化输出流
        BitOutputStream bitOutputStream = new BitOutputStream(new FileOutputStream(outputFilePath));

        // 写入文件头
        bitOutputStream.writeBits(0x4C5A3737, 32); // "LZ77"的ASCII码
        bitOutputStream.writeBits(inputBytes.length, 32); // 原始文件长度

        // 初始化滑动窗口和前瞻缓冲区
        byte[] window = new byte[WINDOW_SIZE];
        byte[] lookaheadBuffer = new byte[LOOKAHEAD_BUFFER_SIZE];
        int windowStartIndex = 0;
        int lookaheadBufferEndIndex = 0;

        // LZ77压缩
        while (lookaheadBufferEndIndex < inputBytes.length) {
            // 查找最长匹配
            int matchLength = 0;
            int matchOffset = 0;
            for (int i = Math.max(lookaheadBufferEndIndex - WINDOW_SIZE, 0); i < lookaheadBufferEndIndex; i++) {
                int length = getMatchLength(inputBytes, i, lookaheadBuffer, lookaheadBufferEndIndex, MAX_MATCH_LENGTH);
                if (length > matchLength) {
                    matchLength = length;
                    matchOffset = lookaheadBufferEndIndex - i;
                }
            }

            // 写入匹配信息
            if (matchLength >= MIN_MATCH_LENGTH) {
                bitOutputStream.writeBits(1, 1); // 标记为匹配
                bitOutputStream.writeBits(matchOffset - 1, 11); // 写入匹配偏移量
                bitOutputStream.writeBits(matchLength - MIN_MATCH_LENGTH, 4); // 写入匹配长度
                lookaheadBufferEndIndex += matchLength;
            } else {
                bitOutputStream.writeBits(0, 1); // 标记为字面量
                huffmanEncoder.encode(inputBytes[lookaheadBufferEndIndex], bitOutputStream); // 写入字面量
                lookaheadBufferEndIndex++;
            }

            // 更新滑动窗口和前瞻缓冲区
            if (lookaheadBufferEndIndex - windowStartIndex > WINDOW_SIZE) {
                windowStartIndex = lookaheadBufferEndIndex - WINDOW_SIZE;
            }
            System.arraycopy(inputBytes, windowStartIndex, window, 0, lookaheadBufferEndIndex - windowStartIndex);
            System.arraycopy(inputBytes, lookaheadBufferEndIndex, lookaheadBuffer, 0, Math.min(LOOKAHEAD_BUFFER_SIZE, inputBytes.length - lookaheadBufferEndIndex));
            windowStartIndex = Math.max(lookaheadBufferEndIndex - WINDOW_SIZE, 0);
        }

        // 写入文件尾
        bitOutputStream.writeBits(1, 1); // 标记为结束
        bitOutputStream.flush();
        bitOutputStream.close();
    }

    public static void decompress(String inputFilePath, String outputFilePath) throws IOException {
        // 读取输入文件
        byte[] inputBytes = readBytesFromFile(inputFilePath);

        // 初始化哈夫曼解码器
        HuffmanDecoder huffmanDecoder = new HuffmanDecoder();

        // 初始化输入流
        BitInputStream bitInputStream = new BitInputStream(new FileInputStream(inputFilePath));

        // 读取文件头
        int magicNumber = bitInputStream.readBits(32);
        if (magicNumber != 0x4C5A3737) {
            throw new RuntimeException("Invalid file format");
        }
        int originalLength = bitInputStream.readBits(32);

        // 初始化滑动窗口和前瞻缓冲区
        byte[] window = new byte[WINDOW_SIZE];
        byte[] lookaheadBuffer = new byte[LOOKAHEAD_BUFFER_SIZE];
        int windowStartIndex = 0;
        int lookaheadBufferEndIndex = 0;

        // LZ77解压
        ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream();
        while (true) {
            int flag = bitInputStream.readBits(1);
            if (flag == 0) { // 字面量
                byte b = huffmanDecoder.decode(bitInputStream);
                byteArrayOutputStream.write(b);
                window[lookaheadBufferEndIndex % WINDOW_SIZE] = b;
                lookaheadBufferEndIndex++;
            } else if (flag == 1) { // 匹配
                int matchOffset = bitInputStream.readBits(11) + 1;
                int matchLength = bitInputStream.readBits(4) + MIN_MATCH_LENGTH;
                for (int i = 0; i < matchLength; i++) {
                    byte b = window[(lookaheadBufferEndIndex - matchOffset + i) % WINDOW_SIZE];
                    byteArrayOutputStream.write(b);
                    window[lookaheadBufferEndIndex % WINDOW_SIZE] = b;
                    lookaheadBufferEndIndex++;
                }
            } else { // 结束
                break;
            }

            // 更新滑动窗口和前瞻缓冲区
            if (lookaheadBufferEndIndex - windowStartIndex > WINDOW_SIZE) {
                windowStartIndex = lookaheadBufferEndIndex - WINDOW_SIZE;
            }
            System.arraycopy(inputBytes, windowStartIndex / 8, window, 0, (lookaheadBufferEndIndex - windowStartIndex + 7) / 8);
            System.arraycopy(inputBytes, (lookaheadBufferEndIndex + 7) / 8, lookaheadBuffer, 0, Math.min(LOOKAHEAD_BUFFER_SIZE, (originalLength - lookaheadBufferEndIndex)));
            windowStartIndex = Math.max(lookaheadBufferEndIndex - WINDOW_SIZE, 0);
        }

        // 写入输出文件
        writeBytesToFile(outputFilePath, byteArrayOutputStream.toByteArray());

        bitInputStream.close();
    }

    private static int getMatchLength(byte[] inputBytes, int inputIndex, byte[] lookaheadBuffer, int lookaheadBufferEndIndex, int maxLength) {
        int length = 0;
        while (length < maxLength && lookaheadBufferEndIndex + length < inputBytes.length && inputBytes[inputIndex + length] == lookaheadBuffer[lookaheadBufferEndIndex + length]) {
            length++;
        }
        return length;
    }

    private static byte[] readBytesFromFile(String filePath) throws IOException {
        FileInputStream fileInputStream = new FileInputStream(filePath);
        byte[] bytes = fileInputStream.readAllBytes();
        fileInputStream.close();
        return bytes;
    }

    private static void writeBytesToFile(String filePath, byte[] bytes) throws IOException {
        FileOutputStream fileOutputStream = new FileOutputStream(filePath);
        fileOutputStream.write(bytes);
        fileOutputStream.close();
    }

    private static class BitInputStream {
        private final InputStream inputStream;
        private int currentByte;
        private int bitsRemaining;

        public BitInputStream(InputStream inputStream) {
            this.inputStream = inputStream;
            this.currentByte = 0;
            this.bitsRemaining = 0;
        }

        public int readBits(int numBits) throws IOException {
            int result = 0;
            while (numBits > 0) {
                if (bitsRemaining == 0) {
                    currentByte = inputStream.read();
                    bitsRemaining = 8;
                }
                int bitsToRead = Math.min(numBits, bitsRemaining);
                int shift = bitsRemaining - bitsToRead;
                int mask = (1 << bitsToRead) - 1;
                result |= (currentByte >> shift) & mask;
                numBits -= bitsToRead;
                bitsRemaining -= bitsToRead;
            }
            return result;
        }

        public void close() throws IOException {
            inputStream.close();
        }
    }

    private static class BitOutputStream {
        private final OutputStream outputStream;
        private int currentByte;
        private int bitsRemaining;

        public BitOutputStream(OutputStream outputStream) {
            this.outputStream = outputStream;
            this.currentByte = 0;
            this.bitsRemaining = 8;
        }

        public void writeBits(int value, int numBits) throws IOException {
            while (numBits > 0) {
                int bitsToWrite = Math.min(numBits, bitsRemaining);
                int shift = bitsRemaining - bitsToWrite;
                int mask = (1 << bitsToWrite) - 1;
                currentByte |= (value & mask) << shift;
                numBits -= bitsToWrite;
                bitsRemaining -= bitsToWrite;
                if (bitsRemaining == 0) {
                    outputStream.write(currentByte);
                    currentByte = 0;
                    bitsRemaining = 8;
                }
            }
        }

        public void flush() throws IOException {
            if (bitsRemaining < 8) {
                outputStream.write(currentByte);
            }
        }

        public void close() throws IOException {
            flush();
            outputStream.close();
        }
    }

    private static class HuffmanEncoder {
        private final Map<Byte, String> codeMap;

        public HuffmanEncoder() {
            codeMap = new HashMap<>();
        }

        public void encode(byte b, BitOutputStream bitOutputStream) throws IOException {
            String code = codeMap.get(b);
            if (code == null) {
                throw new RuntimeException("Huffman code not found for byte: " + b);
            }
            for (char c : code.toCharArray()) {
                bitOutputStream.writeBits(c - '0', 1);
            }
        }

        public void buildCodeMap(byte[] inputBytes) {
            Map<Byte, Integer> frequencyMap = new HashMap<>();
            for (byte b : inputBytes) {
                frequencyMap.put(b, frequencyMap.getOrDefault(b, 0) + 1);
            }

            PriorityQueue<Node> priorityQueue = new PriorityQueue<>();
            for (Map.Entry<Byte, Integer> entry : frequencyMap.entrySet()) {
                priorityQueue.offer(new Node(entry.getKey(), entry.getValue()));
            }

            while (priorityQueue.size() > 1) {
                Node left = priorityQueue.poll();
                Node right = priorityQueue.poll();
                priorityQueue.offer(new Node(null, left.frequency + right.frequency, left, right));
            }

            Node root = priorityQueue.poll();
            buildCodeMap(root, "");
        }

        private void buildCodeMap(Node node, String code) {
            if (node.isLeaf()) {
                codeMap.put(node.b, code);
            } else {
                buildCodeMap(node.left, code + "0");
                buildCodeMap(node.right, code + "1");
            }
        }

        private static class Node implements Comparable<Node> {
            private final Byte b;
            private final int frequency;
            private final Node left;
            private final Node right;

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

            public Node(Byte b, int frequency, Node left, Node right) {
                this.b = b;
                this.frequency = frequency;
                this.left = left;
                this.right = right;
            }

            public boolean isLeaf() {
                return left == null && right == null;
            }

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

    private static class HuffmanDecoder {
        private final Map<String, Byte> codeMap;

        public HuffmanDecoder() {
            codeMap = new HashMap<>();
        }

        public byte decode(BitInputStream bitInputStream) throws IOException {
            StringBuilder stringBuilder = new StringBuilder();
            while (true) {
                int bit = bitInputStream.readBits(1);
                stringBuilder.append(bit);
                Byte b = codeMap.get(stringBuilder.toString());
                if (b != null) {
                    return b;
                }
            }
        }

        public void buildCodeMap(byte[] inputBytes) {
            Map<Byte, Integer> frequencyMap = new HashMap<>();
            for (byte b : inputBytes) {
                frequencyMap.put(b, frequencyMap.getOrDefault(b, 0) + 1);
            }

            PriorityQueue<Node> priorityQueue = new PriorityQueue<>();
            for (Map.Entry<Byte, Integer> entry : frequencyMap.entrySet()) {
                priorityQueue.offer(new Node(entry.getKey(), entry.getValue()));
            }

            while (priorityQueue.size() > 1) {
                Node left = priorityQueue.poll();
                Node right = priorityQueue.poll();
                priorityQueue.offer(new Node(null, left.frequency + right.frequency, left, right));
            }

            Node root = priorityQueue.poll();
            buildCodeMap(root, "");
        }

        private void buildCodeMap(Node node, String code) {
            if (node.isLeaf()) {
                codeMap.put(code, node.b);
            } else {
                buildCodeMap(node.left, code + "0");
                buildCodeMap(node.right, code + "1");
            }
        }

        private static class Node implements Comparable<Node> {
            private final Byte b;
            private final int frequency;
            private final Node left;
            private final Node right;

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

            public Node(Byte b, int frequency, Node left, Node right) {
                this.b = b;
                this.frequency = frequency;
                this.left = left;
                this.right = right;
            }

            public boolean isLeaf() {
                return left == null && right == null;
            }

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

c语言压缩文本文件字符

在C语言中，可以使用一些方法来压缩文本文件中的字符。

1. RLE压缩（Run-Length Encoding）：这种方法基于统计连续出现的字符的个数。当字符连续出现时，可以将字符和次数进行编码，用更短的表示方式来代替重复的字符。例如，将"AAAABBBCCDAA"压缩为"4A3B2C1D2A"。

2. 字典压缩：创建一个字符字典，将每个字符映射到一个唯一的编码，然后用编码替代字符。可以使用哈弗曼编码或者LZW压缩算法来实现。哈弗曼编码是一种变长编码方式，出现频率高的字符使用较短的编码，出现频率低的字符使用较长的编码。LZW压缩算法则是在字典中不断添加字符组合，并用较短的编码表示较长的字符组合。

3. 使用压缩库：C语言提供了一些开源的压缩库，如zlib。这些库提供了一些函数和接口，让开发者可以在代码中调用来进行文本文件的压缩和解压缩操作。

以上是一些常用的方法来压缩文本文件中的字符，开发者可以根据需求选择合适的方法。在实际应用中，还需要考虑压缩后的文件大小、解压缩的速度以及压缩算法的复杂度等因素。