java huffman code 解压缩文件

package com.gxmedu.huffman_code;import java.io.*;
import java.util.*;/*** @author 郭学明* @version 1.0*/
public class HuffmanCode {public static void main(String[] args) {HuffmanCode huffmanCode1 = new HuffmanCode();String s1= "i like like like java do you like a java";
//        s1 = "hello,world";
//        List<Node> nodes = huffmanCode1.getNodes(s1.getBytes());
//        Node huffmanTree = huffmanCode1.createHuffmanTree(nodes);
//        huffmanCode1.getHuffmanCode(huffmanTree,"",huffmanCode1.huffmanCodeBuilder);
//       System.out.println(huffmanCode1.huffmanCode);byte[] result = huffmanCode1.zip(s1.getBytes());System.out.println(Arrays.toString(result));byte[] decompression = huffmanCode1.decompression(result,huffmanCode1.huffmanCode);System.out.println(new String(decompression));//        String compressionSrcPath = "D:\\chapter19_case\\WorldWarII.png";
//        String compressionDestPath = "D:\\chapter19_case\\WorldWarII.gxm";
//        String decompressionDestPath = "D:\\chapter19_case\\WorldWarII2.png";
//        huffmanCode1.compressionFile(compressionSrcPath,compressionDestPath);
//        huffmanCode1.decompressionFile(compressionDestPath,decompressionDestPath);}public class Node implements Comparable<Node>{private Byte data;private int weigh;private Node left;private Node right;public Node(Byte data, int weigh) {this.data = data;this.weigh = weigh;}public Byte getData() {return data;}public void setData(byte data) {this.data = data;}public int getWeigh() {return weigh;}public void setWeigh(int weigh) {this.weigh = weigh;}public Node getLeft() {return left;}public void setLeft(Node left) {this.left = left;}public Node getRight() {return right;}public void setRight(Node right) {this.right = right;}@Overridepublic String toString() {return "Node{" +"data=" + data +", weigh=" + weigh +'}';}@Overridepublic int compareTo(Node o) {return this.weigh - o.weigh;}}/***  1.将字节数组的元素进行次数统计，这个次数就是之后huffman tree结点的weigh,*  目标是得到一个ArrayList<Node>,这里我们用hashmap，key不能重复的特性，来统计出现次数。*/public List<Node> getNodes(byte[] bytes){HashMap<Byte, Integer> dataCount = new HashMap<>();Set<Map.Entry<Byte, Integer>> entries = dataCount.entrySet();for (byte b : bytes) {Integer count = dataCount.get(b);if(count == null){dataCount.put(b,1);}else{dataCount.put(b,count + 1);}}ArrayList<Node> nodes = new ArrayList<>();for (Map.Entry<Byte, Integer> entry : entries) {Node node = new Node(entry.getKey(), entry.getValue());nodes.add(node);}return nodes;}/***  2.生成huffman tree*/public Node createHuffmanTree(List<Node> nodes){while(nodes.size() > 1){Collections.sort(nodes);Node left = nodes.get(0);Node right = nodes.get(1);Node parent = new Node(null, left.weigh + right.weigh);parent.setLeft(left);parent.setRight(right);nodes.remove(left);nodes.remove(right);nodes.add(parent);}return nodes.get(0);}/***  3.生成huffman code,这里也用hashmap 存储*/private StringBuilder huffmanCodeBuilder = new StringBuilder();private HashMap<Byte,String> huffmanCode = new HashMap<>();public void getHuffmanCode(Node node,String code,StringBuilder sb){StringBuilder stringBuilder2 = new StringBuilder(sb);stringBuilder2.append(code);
//        HashMap<Byte, String> huffmanCode = new HashMap<>();if(node != null){if(node.data == null){getHuffmanCode(node.left,"0",stringBuilder2);getHuffmanCode(node.right,"1",stringBuilder2);}else{//            stringBuilder2.append(code);huffmanCode.put(node.data,stringBuilder2.toString());}}}/***  4.根据HuffmanCode将传入的字节数组进行压缩转换*/public byte[] huffmanCodeBytes(byte[] bytes,HashMap<Byte,String> huffmanCode){StringBuilder stringBuilder = new StringBuilder();for (byte b :bytes) {String s = huffmanCode.get(b);stringBuilder.append(s);}int length = stringBuilder.length();
//        这里给数组多加最后一位，用来记录最后一个字符串的长度
//        比如说最后一个字符串是"0001"或者"001",但是在byte[]中存的都是1,
//        这样就会导致huffmanCode解码错误。byte[] huffmanCodeBytes = new byte[(length + 7)/8 + 1];
//        String s = stringBuilder.toString();int zipIndex = 0;int lastStringLength = 0;for (int i = 0; i < length ; i += 8) {String s = "";if(i + 7 < length){s = stringBuilder.substring(i, i + 8);}else{s = stringBuilder.substring(i);
//                 lastStringLength = s.length();}lastStringLength = s.length();huffmanCodeBytes[zipIndex++] = (byte)Integer.parseInt(s,2);}huffmanCodeBytes[huffmanCodeBytes.length - 1] = (byte)lastStringLength;return huffmanCodeBytes;}/***  5.对上述方法进行封装*/public byte[] zip(byte[] bytes){List<Node> nodes = getNodes(bytes);Node huffmanTree = createHuffmanTree(nodes);getHuffmanCode(huffmanTree,"",huffmanCodeBuilder);byte[] zip = huffmanCodeBytes(bytes, huffmanCode);return zip;}/***  1.解码 得到二进制的huffmanCode*/public String  getBinaryHuffmanCode(byte[] bytes){int length = bytes.length;StringBuilder sb = new StringBuilder();for (int i = 0; i < length - 1; i++) {int b = bytes[i];// 注意这里要int类型，因为下面要进行按位或操作String s = Integer.toBinaryString(b | 256);//                256 按位或 如果是正数 则倒数八位省略的零都能补上。//                          如果是负数 则倒数八位不会改变if(i != length - 2){String s2 = s.substring(s.length() - 8);sb.append(s2);}else{//                根据bytes[]最后一个记录最后一个字符串的长度来截取转换后的字符串。sb.append(s.substring(s.length() - bytes[length - 1]));}}return sb.toString();}/*** 2.根据huffmanCode还原原文*/public byte[] decode(HashMap<Byte,String> huffmanCode, String huffmanString){HashMap<String, Byte> hm = new HashMap<>();Set<Map.Entry<Byte, String>> entries = huffmanCode.entrySet();Iterator<Map.Entry<Byte, String>> iterator = entries.iterator();while (iterator.hasNext()) {Map.Entry<Byte, String> next =  iterator.next();Byte key = next.getKey();String value = next.getValue();hm.put(value,key);}
//        用来存储转换后的字节ArrayList<Byte> bytes = new ArrayList<>();int length = huffmanString.length();int end = 1;for (int i = 0; i < length; ) {String substring = huffmanString.substring(i, end);
//            if(hm.get(substring) == null){//                count++;
//            }else{//                bytes.add(hm.get(substring));
//                i = count;
//            }if(hm.get(substring) != null){bytes.add(hm.get(substring));i = end;}end++;}byte[] result = new byte[bytes.size()];for (int i = 0; i < result.length; i++) {result[i] = bytes.get(i);}return result;}/*** 3. 对上面两个方法进行封装*/public byte[] decompression(byte[] bytes,HashMap<Byte,String> huffmanCode){String huffmanString = getBinaryHuffmanCode(bytes);byte[] decode = decode(huffmanCode, huffmanString);return decode;}/***  对文件进行压缩*/public void compressionFile(String srcPath,String destPath){FileInputStream fis = null;byte[] bytes;ObjectOutputStream oos = null;FileOutputStream fos = null;try {fis = new FileInputStream(srcPath);int available = fis.available();bytes = new byte[available];
//            int content;fis.read(bytes);
//            for (int i = 0; (content = fis.read()) != -1; i++) {//                bytes[i] = (byte)content;
//            }/***  下面进行huffman编码*/byte[] zip = zip(bytes);fos = new FileOutputStream(destPath);oos = new ObjectOutputStream(fos);oos.writeObject(zip);oos.writeObject(huffmanCode);//            while((content = fis.read()) != -1){//                bytes.[]
//            }} catch (IOException e) {throw new RuntimeException(e);}finally{try {if(oos != null){oos.close();}if(fos != null){fos.close();}if(fis != null){fis.close();}} catch (IOException e) {throw new RuntimeException(e);}}}/***  对文件进行解压*/public void decompressionFile(String srcPath,String destPath){ObjectInputStream ois = null;FileOutputStream fos = null;FileInputStream fis = null;try {fis = new FileInputStream(srcPath);ois = new ObjectInputStream(fis);byte[] bytes = (byte[])ois.readObject();HashMap<Byte,String> hm = (HashMap<Byte,String>)ois.readObject();byte[] decompression = decompression(bytes, hm);fos = new FileOutputStream(destPath);fos.write(decompression);} catch (IOException e) {throw new RuntimeException(e);} catch (ClassNotFoundException e) {throw new RuntimeException(e);} finally{try{if(fos != null){fos.close();}if(ois != null){ois.close();}if(fis != null){fis.close();}}catch(IOException e){throw new RuntimeException(e);}}}
}

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