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1.压缩：使用赫夫曼编码进行压缩

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题目

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构建赫夫曼树

package tree.huffmantree;import java.util.*;public class HuffmanCode {public static void main(String[] args) {String content = "i like like like java do you like a java";byte [] contentBytes = content.getBytes();System.out.println(contentBytes.length);List<Node1> nodes = getNodes(contentBytes);//System.out.println(nodes);//测试创建二叉树Node1 huffmanTree = createHuffmanTree(nodes);//前序遍历preOrder(huffmanTree);}//前序遍历public static void preOrder(Node1 root){if (root != null){root.preOrder();}else {System.out.println("赫夫曼树为空");}}private  static List<Node1> getNodes(byte [] bytes){//1.创建ArrayListArrayList<Node1> node1s = new ArrayList<>();//遍历bytes 统计乜咯 byte出现的次数，存储每个byte出现的次数 -> mapMap<Byte,Integer> counts = new HashMap<>();for (byte b : bytes){Integer count = counts.get(b);if (count == null){ //说明map中还没有这个字符counts.put(b,1);}else {counts.put(b,count+1);}}//把每个键值对转成一个Node对象，并加入到nodes集合//遍历mapfor (Map.Entry<Byte,Integer> entry : counts.entrySet()){node1s.add(new Node1(entry.getKey(),entry.getValue()));}return node1s;}//通过List创建赫夫曼树private static Node1 createHuffmanTree(List<Node1> nodes){while (nodes.size() > 1){//排序  从小到大Collections.sort(nodes);//取出第一颗、第二颗最小的二叉树Node1 leftNode = nodes.get(0);Node1 rightNode = nodes.get(1);//创建新的二叉树,新的二叉树没有数据，只有权值Node1 parent = new Node1(null,leftNode.weight + rightNode.weight);parent.left  = leftNode;parent.right = rightNode;//将0,1移除Listnodes.remove(leftNode);nodes.remove(rightNode);//parent加入Listnodes.add(parent);}//nodes最后剩余就是哈弗曼树的根节点return nodes.get(0);}
}
class Node1 implements Comparable<Node1>{Byte data; //存放数据 按照asciiint weight; //权值,表示字符出现的次数Node1 left;Node1 right;//前序遍历public void preOrder(){System.out.println(this);if (this.left != null){this.left.preOrder();}if (this.right != null){this.right.preOrder();}}@Overridepublic int compareTo(Node1 o) {return this.weight - o.weight;}public Node1(Byte data, int weight) {this.data = data;this.weight = weight;}@Overridepublic String toString() {return "Node1{" +"data=" + data +", weight=" + weight +'}';}
}

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//生成赫夫曼树对应的赫夫曼编码//思路：//1.将赫夫曼编码表存放在Map<Byte,String> 形式//32->01  97->100 100->11000等等static Map<Byte,String> huffmanCodes = new HashMap<>();//2.在生成赫夫曼编码表时需要拼接路径，创建Stringbuilder存储某个叶子节点的路径static  StringBuilder stringBuilder = new StringBuilder();/*** 功能：将传入的node节点的所有叶子节点赫夫曼编码得到，并放入到赫夫曼集合中* @param node  传入节点* @param code  路径：左子节点是0，右子节点是1* @param stringBuilder 是用于拼接路径*/private static void getCondes(Node1 node,String code, StringBuilder stringBuilder){StringBuilder stringBuilder2 = new StringBuilder(stringBuilder);//将传入的code加入到Stringbuilder2stringBuilder2.append(code);if (node != null){//判断当前node是叶子节点还是非叶子节点if (node.data == null){ //说明是非叶子节点//递归处理//向左递归getCondes(node.left,"0",stringBuilder2);//向右递归getCondes(node.right,"1",stringBuilder2);}else {//说明是叶子节点//就表示找到了某个叶子节点最后huffmanCodes.put(node.data,stringBuilder2.toString());}}}

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//编写一个方法，将字符串对应的byte[]数组，通过生成的赫夫曼编码表，返回赫夫曼编码压缩后的byte[]/**** @param bytes 原始的字符对应的byte[]* @param huffmanCodes  生成的赫夫曼编码表map* @return  返回赫夫曼编码处理后的byte[]* 举例：String content = "i like like like java do you like a java";* 返回的是字符串"10101000"。。。等等* =>对应byte[] huffmancodeBytes，即8位对应一个byte，放入到huffmanCodeBytes* huffmancodeBytes[0] = 10101000(补码) => byte [推导 10101000 => 10101000 -1 => 10100111(反码) => 11011000(原码)]* huffmancodeBytes[1] = -88*/private static byte[] zip(byte [] bytes, Map<Byte,String> huffmanCodes){//1.利用赫夫曼编码表将传进来的byte数组转成赫夫曼编码字符串StringBuilder stringBuilder = new StringBuilder();//遍历bytes数组for (byte b : bytes){stringBuilder.append(huffmanCodes.get(b));}//按照这个字符串发送肯定是变大了，不行，那么就要将字符串转成byte数组System.out.println(stringBuilder.toString());//统计返回的byte[] huffmanCodeBytes 长度//一句话搞定int len = (stringBuilder.length() + 7) / 8;int len;if (stringBuilder.length() % 8 == 0){len = stringBuilder.length() /8;}else {len = stringBuilder.length() /8 + 1;}//创建存储压缩后的byte数组byte [] huffmanCodeBytes = new byte[len];int index = 0;//记录是第几个bytefor (int i = 0; i < stringBuilder.length(); i += 8){//因为每8位对应一个byteString strByte;if (i+8 <= stringBuilder.length()){strByte = stringBuilder.substring(i,i+8);}else {strByte = stringBuilder.substring(i); //-88}//将StringByte转成byte数组放入到huffmanCodeByteshuffmanCodeBytes[index] = (byte) Integer.parseInt(strByte,2);index++;}return huffmanCodeBytes;}

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完整代码

package tree.huffmantree;import java.util.*;public class HuffmanCode {public static void main(String[] args) {String content = "i like like like java do you like a java";byte [] contentBytes = content.getBytes();byte[] bytes = huffmanZip(contentBytes);System.out.println("压缩后的结果: " + Arrays.toString(bytes));//        System.out.println(contentBytes.length);
//
//        List<Node1> nodes = getNodes(contentBytes);
//        //System.out.println(nodes);
//
//        //测试创建二叉树
//        Node1 huffmanTree = createHuffmanTree(nodes);
//        //前序遍历
//        preOrder(huffmanTree);
//
//        //测试是否生成了对应的哈夫曼编码
//        Map<Byte, String> huffmancondes = getCondes(huffmanTree);
//        System.out.println("生成的赫夫曼编码表" + huffmancondes);
//
//        //测试
//        byte[] huffmanCodeBytes = zip(contentBytes, huffmancondes);
//        System.out.println("huffmanCodeBytes=" + Arrays.toString(huffmanCodeBytes));}//封装前面所写的，便于调用/**** @param bytes 原始字符串对应的字节数组* @return  返回的是经过赫夫曼编码处理后的字节数组（压缩后的数组）*/private static byte[] huffmanZip(byte [] bytes){//第一步：创建节点List<Node1> nodes = getNodes(bytes);//第二步：创建赫夫曼树Node1 huffmanTree = createHuffmanTree(nodes);//第三步：生成对应的赫夫曼编码（根据赫夫曼树）Map<Byte, String> hufumanCodes = getCondes(huffmanTree);//第四步：根据赫夫曼编码压缩，生成赫夫曼字节数组byte[] huffmanBytes = zip(bytes, hufumanCodes);return huffmanBytes;}//编写一个方法，将字符串对应的byte[]数组，通过生成的赫夫曼编码表，返回赫夫曼编码压缩后的byte[]/**** @param bytes 原始的字符对应的byte[]* @param huffmanCodes  生成的赫夫曼编码表map* @return  返回赫夫曼编码处理后的byte[]* 举例：String content = "i like like like java do you like a java";* 返回的是字符串"10101000"。。。等等* =>对应byte[] huffmancodeBytes，即8位对应一个byte，放入到huffmanCodeBytes* huffmancodeBytes[0] = 10101000(补码) => byte [推导 10101000 => 10101000 -1 => 10100111(反码) => 11011000(原码)]* huffmancodeBytes[1] = -88*/private static byte[] zip(byte [] bytes, Map<Byte,String> huffmanCodes){//1.利用赫夫曼编码表将传进来的byte数组转成赫夫曼编码字符串StringBuilder stringBuilder = new StringBuilder();//遍历bytes数组for (byte b : bytes){stringBuilder.append(huffmanCodes.get(b));}//按照这个字符串发送肯定是变大了，不行，那么就要将字符串转成byte数组System.out.println(stringBuilder.toString());//统计返回的byte[] huffmanCodeBytes 长度//一句话搞定int len = (stringBuilder.length() + 7) / 8;int len;if (stringBuilder.length() % 8 == 0){len = stringBuilder.length() /8;}else {len = stringBuilder.length() /8 + 1;}//创建存储压缩后的byte数组byte [] huffmanCodeBytes = new byte[len];int index = 0;//记录是第几个bytefor (int i = 0; i < stringBuilder.length(); i += 8){//因为每8位对应一个byteString strByte;if (i+8 <= stringBuilder.length()){strByte = stringBuilder.substring(i,i+8);}else {strByte = stringBuilder.substring(i); //-88}//将StringByte转成byte数组放入到huffmanCodeByteshuffmanCodeBytes[index] = (byte) Integer.parseInt(strByte,2);index++;}return huffmanCodeBytes;}//生成赫夫曼树对应的赫夫曼编码//思路：//1.将赫夫曼编码表存放在Map<Byte,String> 形式//32->01  97->100 100->11000等等static Map<Byte,String> huffmanCodes = new HashMap<>();//2.在生成赫夫曼编码表时需要拼接路径，创建Stringbuilder存储某个叶子节点的路径static  StringBuilder stringBuilder = new StringBuilder();//为了调用方便重载getCondesprivate static Map<Byte,String> getCondes(Node1 root){if (root == null){return null;}//处理rootgetCondes(root,"",stringBuilder);return huffmanCodes;}/*** 功能：将传入的node节点的所有叶子节点赫夫曼编码得到，并放入到赫夫曼集合中* @param node  传入节点* @param code  路径：左子节点是0，右子节点是1* @param stringBuilder 是用于拼接路径*/private static void getCondes(Node1 node,String code, StringBuilder stringBuilder){StringBuilder stringBuilder2 = new StringBuilder(stringBuilder);//将传入的code加入到Stringbuilder2stringBuilder2.append(code);if (node != null){//判断当前node是叶子节点还是非叶子节点if (node.data == null){ //说明是非叶子节点//递归处理//向左递归getCondes(node.left,"0",stringBuilder2);//向右递归getCondes(node.right,"1",stringBuilder2);}else {//说明是叶子节点//就表示找到了某个叶子节点最后huffmanCodes.put(node.data,stringBuilder2.toString());}}}//前序遍历public static void preOrder(Node1 root){if (root != null){root.preOrder();}else {System.out.println("赫夫曼树为空");}}private  static List<Node1> getNodes(byte [] bytes){//1.创建ArrayListArrayList<Node1> node1s = new ArrayList<>();//遍历bytes 统计乜咯 byte出现的次数，存储每个byte出现的次数 -> mapMap<Byte,Integer> counts = new HashMap<>();for (byte b : bytes){Integer count = counts.get(b);if (count == null){ //说明map中还没有这个字符counts.put(b,1);}else {counts.put(b,count+1);}}//把每个键值对转成一个Node对象，并加入到nodes集合//遍历mapfor (Map.Entry<Byte,Integer> entry : counts.entrySet()){node1s.add(new Node1(entry.getKey(),entry.getValue()));}return node1s;}//通过List创建赫夫曼树private static Node1 createHuffmanTree(List<Node1> nodes){while (nodes.size() > 1){//排序  从小到大Collections.sort(nodes);//取出第一颗、第二颗最小的二叉树Node1 leftNode = nodes.get(0);Node1 rightNode = nodes.get(1);//创建新的二叉树,新的二叉树没有数据，只有权值Node1 parent = new Node1(null,leftNode.weight + rightNode.weight);parent.left  = leftNode;parent.right = rightNode;//将0,1移除Listnodes.remove(leftNode);nodes.remove(rightNode);//parent加入Listnodes.add(parent);}//nodes最后剩余就是哈弗曼树的根节点return nodes.get(0);}
}
class Node1 implements Comparable<Node1>{Byte data; //存放数据 按照asciiint weight; //权值,表示字符出现的次数Node1 left;Node1 right;//前序遍历public void preOrder(){System.out.println(this);if (this.left != null){this.left.preOrder();}if (this.right != null){this.right.preOrder();}}@Overridepublic int compareTo(Node1 o) {return this.weight - o.weight;}public Node1(Byte data, int weight) {this.data = data;this.weight = weight;}@Overridepublic String toString() {return "Node1{" +"data=" + data +", weight=" + weight +'}';}
}

2.解压（解码）

  //完成数据解压//思路//1.将huffmanCodeBytes[-88,-65..]重写先转成赫夫曼编码对应的二进制字符串//2.赫夫曼编码对应的二进制字符串根据赫夫曼编码转成字符//编写一个方法，对压缩数据解码/**** @param huffmanCodes 赫夫曼编码表 map* @param huffmanBytes 需要解码的字节数组* @return 返回原来字符串对应的数组*/private static byte[] decode(Map<Byte,String> huffmanCodes, byte[] huffmanBytes){//1.先得到huffmanBytes对应的二进制的字符串StringBuilder stringBuilder = new StringBuilder();//将byte数组转成二进制字符串for (int i = 0; i < huffmanBytes.length; i++) {//判断是否是最后一个字节boolean flag = (i == huffmanBytes.length - 1);stringBuilder.append(byteToBitString(!flag,huffmanBytes[i]));}System.out.println("赫夫曼 解码后 对应的二进制字符串:" + stringBuilder.toString());//把字符串按照指定的赫夫曼编码进行解码//把赫夫曼编码表的k,v进行调换；因为要反向查询Map<String,Byte> map = new HashMap<>();for (Map.Entry<Byte,String> entry : huffmanCodes.entrySet()){map.put(entry.getValue(),entry.getKey());}//System.out.println(map);//创建一个集合存放byteList<Byte> list = new ArrayList<>();for (int i = 0; i < stringBuilder.length();) {int count = 1; //小的计数器boolean flag = true;Byte b = null;while (flag){//1010100010111。。。。String key = stringBuilder.substring(i, i + count);// i 不动让count移动，直到匹配到字符b = map.get(key);if (b == null){count ++;}else {flag = false;}}list.add(b);i += count; //让 i 移动到count}//for循环结束后list中存放了所以的字符//把list放入到byte[] 并返回byte b [] = new byte[list.size()];for (int i = 0; i < b.length; i++) {b[i] = list.get(i);}return b;}/*** 将一个byte转成二进制字符串* @param b 传入一个byte* @param flag 标志是否需要补高位，true需要补高位，如果是最后一个字节不需要补高位* @return*/private static String byteToBitString(boolean flag, byte b){//使用变量保存bint temp = b;//将b转成intif (flag){temp |= 256; //按位与256 1 0000 0000 | 0000 0001 =》1 0000 0001}String str = Integer.toBinaryString(temp);if (flag){return str.substring(str.length() - 8);}else {return str;}}

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3.对文件进行压缩（加入io，通过对象流把赫夫曼编码传入，解压的时候需要用）

//编写一个方法，进行文件压缩public static void zipFile(String srcFile, String dstFile){//创建输出流FileInputStream is = null;//文件输入流OutputStream os = null;ObjectOutputStream oos = null;try{is = new FileInputStream(srcFile);//创建一个和源文件大小一样的btyte[]byte[] b = new byte[is.available()];//读取文件is.read(b);//直接对源文件压缩byte[] huffmanBytes = huffmanZip(b);//创建文件的输出流，存放压缩文件os = new FileOutputStream(dstFile);//创建一个和文件输出流关联的ObjectOutPutStream对象流oos = new ObjectOutputStream(os);//把赫夫曼编码后的字节数组写入压缩文件oos.writeObject(huffmanBytes);//这里我们以对象流的方式写入 赫夫曼编码，为了恢复原文件时使用//!!!一定要把赫夫曼编码也写入，要不然无法恢复oos.writeObject(huffmanCodes);}catch (Exception e){System.out.println(e.getMessage());}finally {try {is.close();os.close();oos.close();} catch (IOException ex) {System.out.println(ex);}}}

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4.对文件进行解压

    //编写一个方法，进行解压public static void unzipFile(String zipFile,String dstFile){//文件输入流InputStream is = null;//创建输出流OutputStream os = null;//对象输入流ObjectInputStream ois = null;try {//创建文件输入流is = new FileInputStream(zipFile);//场景和is关联的对象输入流ois = new ObjectInputStream(is);//读取byte数组 huffmanBytesbyte [] huffmanBytes = (byte[]) ois.readObject();//读取赫夫曼编码表Map<Byte,String> huffmanCode = (Map<Byte,String>)ois.readObject();//解码byte [] bytes = decode(huffmanCode,huffmanBytes);//将bytes数组写入到目标文件os = new FileOutputStream(dstFile);//写出数据os.write(bytes);} catch (Exception e) {System.out.println(e.getMessage());}finally {try {os.close();ois.close();is.close();} catch (IOException e) {System.out.println(e.getMessage());}}}

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赫夫曼编码可以压缩所有类型的文件，因为是通过字节进行压缩

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完整代码

package tree.huffmantree.ZipFile;import java.io.*;
import java.util.*;public class HuffmanZipFile {public static void main(String[] args) {//测试压缩文件String srcFile = "D:\\薛艳春\\桌面\\新建文件夹 (3)\\薛艳春2.pdf";String dstFile = "D:\\薛艳春\\桌面\\新建文件夹 (3)\\薛艳春2.zip";zipFile(srcFile,dstFile);System.out.println("压缩成功~~");String zipFile = "D:\\薛艳春\\桌面\\新建文件夹 (3)\\dst.zip";String dstFile2 = "D:\\薛艳春\\桌面\\新建文件夹 (3)\\src2.png";//unzipFile(zipFile,dstFile2);}//编写一个方法，进行解压public static void unzipFile(String zipFile,String dstFile){//文件输入流InputStream is = null;//创建输出流OutputStream os = null;//对象输入流ObjectInputStream ois = null;try {//创建文件输入流is = new FileInputStream(zipFile);//场景和is关联的对象输入流ois = new ObjectInputStream(is);//读取byte数组 huffmanBytesbyte [] huffmanBytes = (byte[]) ois.readObject();//读取赫夫曼编码表Map<Byte,String> huffmanCode = (Map<Byte,String>)ois.readObject();//解码byte [] bytes = decode(huffmanCode,huffmanBytes);//将bytes数组写入到目标文件os = new FileOutputStream(dstFile);//写出数据os.write(bytes);} catch (Exception e) {System.out.println(e.getMessage());}finally {try {os.close();ois.close();is.close();} catch (IOException e) {System.out.println(e.getMessage());}}}//编写一个方法，进行文件压缩public static void zipFile(String srcFile, String dstFile){//创建输出流FileInputStream is = null;//文件输入流OutputStream os = null;ObjectOutputStream oos = null;try{is = new FileInputStream(srcFile);//创建一个和源文件大小一样的btyte[]byte[] b = new byte[is.available()];//读取文件is.read(b);//直接对源文件压缩byte[] huffmanBytes = huffmanZip(b);//创建文件的输出流，存放压缩文件os = new FileOutputStream(dstFile);//创建一个和文件输出流关联的ObjectOutPutStream对象流oos = new ObjectOutputStream(os);//把赫夫曼编码后的字节数组写入压缩文件oos.writeObject(huffmanBytes);//这里我们以对象流的方式写入 赫夫曼编码，为了恢复原文件时使用//!!!一定要把赫夫曼编码也写入，要不然无法恢复oos.writeObject(huffmanCodes);}catch (Exception e){System.out.println(e.getMessage());}finally {try {is.close();os.close();oos.close();} catch (IOException ex) {System.out.println(ex);}}}//完成数据解压//思路//1.将huffmanCodeBytes[-88,-65..]重写先转成赫夫曼编码对应的二进制字符串//2.赫夫曼编码对应的二进制字符串根据赫夫曼编码转成字符//编写一个方法，对压缩数据解码/**** @param huffmanCodes 赫夫曼编码表 map* @param huffmanBytes 需要解码的字节数组* @return 返回原来字符串对应的数组*/private static byte[] decode(Map<Byte,String> huffmanCodes, byte[] huffmanBytes){//1.先得到huffmanBytes对应的二进制的字符串StringBuilder stringBuilder = new StringBuilder();//将byte数组转成二进制字符串for (int i = 0; i < huffmanBytes.length; i++) {//判断是否是最后一个字节boolean flag = (i == huffmanBytes.length - 1);stringBuilder.append(byteToBitString(!flag,huffmanBytes[i]));}//System.out.println("赫夫曼 解码后 对应的二进制字符串:" + stringBuilder.toString());//把字符串按照指定的赫夫曼编码进行解码//把赫夫曼编码表的k,v进行调换；因为要反向查询Map<String,Byte> map = new HashMap<>();for (Map.Entry<Byte,String> entry : huffmanCodes.entrySet()){map.put(entry.getValue(),entry.getKey());}//System.out.println(map);//创建一个集合存放byteList<Byte> list = new ArrayList<>();for (int i = 0; i < stringBuilder.length();) {int count = 1; //小的计数器boolean flag = true;Byte b = null;while (flag){//1010100010111。。。。String key = stringBuilder.substring(i, i + count);// i 不动让count移动，直到匹配到字符b = map.get(key);if (b == null){count ++;}else {flag = false;}}list.add(b);i += count; //让 i 移动到count}//for循环结束后list中存放了所以的字符//把list放入到byte[] 并返回byte b [] = new byte[list.size()];for (int i = 0; i < b.length; i++) {b[i] = list.get(i);}return b;}/*** 将一个byte转成二进制字符串* @param b 传入一个byte* @param flag 标志是否需要补高位，true需要补高位，如果是最后一个字节不需要补高位* @return*/private static String byteToBitString(boolean flag, byte b){//使用变量保存bint temp = b;//将b转成intif (flag){temp |= 256; //按位与256 1 0000 0000 | 0000 0001 =》1 0000 0001}String str = Integer.toBinaryString(temp);if (flag){return str.substring(str.length() - 8);}else {return str;}}//封装前面所写的，便于调用/**** @param bytes 原始字符串对应的字节数组* @return  返回的是经过赫夫曼编码处理后的字节数组（压缩后的数组）*/private static byte[] huffmanZip(byte [] bytes){//第一步：创建节点List<Node1> nodes = getNodes(bytes);//第二步：创建赫夫曼树Node1 huffmanTree = createHuffmanTree(nodes);//第三步：生成对应的赫夫曼编码（根据赫夫曼树）Map<Byte, String> hufumanCodes = getCondes(huffmanTree);//第四步：根据赫夫曼编码压缩，生成赫夫曼字节数组byte[] huffmanBytes = zip(bytes, hufumanCodes);return huffmanBytes;}//编写一个方法，将字符串对应的byte[]数组，通过生成的赫夫曼编码表，返回赫夫曼编码压缩后的byte[]/**** @param bytes 原始的字符对应的byte[]* @param huffmanCodes  生成的赫夫曼编码表map* @return  返回赫夫曼编码处理后的byte[]* 举例：String content = "i like like like java do you like a java";* 返回的是字符串"10101000"。。。等等* =>对应byte[] huffmancodeBytes，即8位对应一个byte，放入到huffmanCodeBytes* huffmancodeBytes[0] = 10101000(补码) => byte [推导 10101000 => 10101000 -1 => 10100111(反码) => 11011000(原码)]* huffmancodeBytes[1] = -88*/private static byte[] zip(byte [] bytes, Map<Byte,String> huffmanCodes){//1.利用赫夫曼编码表将传进来的byte数组转成赫夫曼编码字符串StringBuilder stringBuilder = new StringBuilder();//遍历bytes数组for (byte b : bytes){stringBuilder.append(huffmanCodes.get(b));}//按照这个字符串发送肯定是变大了，不行，那么就要将字符串转成byte数组//System.out.println("赫夫曼 编码后 对应的二进制字符串:" + stringBuilder.toString());//统计返回的byte[] huffmanCodeBytes 长度//一句话搞定int len = (stringBuilder.length() + 7) / 8;int len;if (stringBuilder.length() % 8 == 0){len = stringBuilder.length() /8;}else {len = stringBuilder.length() /8 + 1;}//创建存储压缩后的byte数组byte [] huffmanCodeBytes = new byte[len];int index = 0;//记录是第几个bytefor (int i = 0; i < stringBuilder.length(); i += 8){//因为每8位对应一个byteString strByte;if (i+8 <= stringBuilder.length()){strByte = stringBuilder.substring(i,i+8);}else {strByte = stringBuilder.substring(i); //-88}//将StringByte转成byte数组放入到huffmanCodeByteshuffmanCodeBytes[index] = (byte) Integer.parseInt(strByte,2);index++;}return huffmanCodeBytes;}//生成赫夫曼树对应的赫夫曼编码//思路：//1.将赫夫曼编码表存放在Map<Byte,String> 形式//32->01  97->100 100->11000等等static Map<Byte,String> huffmanCodes = new HashMap<>();//2.在生成赫夫曼编码表时需要拼接路径，创建Stringbuilder存储某个叶子节点的路径static  StringBuilder stringBuilder = new StringBuilder();//为了调用方便重载getCondesprivate static Map<Byte,String> getCondes(Node1 root){if (root == null){return null;}//处理rootgetCondes(root,"",stringBuilder);return huffmanCodes;}/*** 功能：将传入的node节点的所有叶子节点赫夫曼编码得到，并放入到赫夫曼集合中* @param node  传入节点* @param code  路径：左子节点是0，右子节点是1* @param stringBuilder 是用于拼接路径*/private static void getCondes(Node1 node,String code, StringBuilder stringBuilder){StringBuilder stringBuilder2 = new StringBuilder(stringBuilder);//将传入的code加入到Stringbuilder2stringBuilder2.append(code);if (node != null){//判断当前node是叶子节点还是非叶子节点if (node.data == null){ //说明是非叶子节点//递归处理//向左递归getCondes(node.left,"0",stringBuilder2);//向右递归getCondes(node.right,"1",stringBuilder2);}else {//说明是叶子节点//就表示找到了某个叶子节点最后huffmanCodes.put(node.data,stringBuilder2.toString());}}}//前序遍历public static void preOrder(Node1 root){if (root != null){root.preOrder();}else {System.out.println("赫夫曼树为空");}}private  static List<Node1> getNodes(byte [] bytes){//1.创建ArrayListArrayList<Node1> node1s = new ArrayList<>();//遍历bytes 统计乜咯 byte出现的次数，存储每个byte出现的次数 -> mapMap<Byte,Integer> counts = new HashMap<>();for (byte b : bytes){Integer count = counts.get(b);if (count == null){ //说明map中还没有这个字符counts.put(b,1);}else {counts.put(b,count+1);}}//把每个键值对转成一个Node对象，并加入到nodes集合//遍历mapfor (Map.Entry<Byte,Integer> entry : counts.entrySet()){node1s.add(new Node1(entry.getKey(),entry.getValue()));}return node1s;}//通过List创建赫夫曼树private static Node1 createHuffmanTree(List<Node1> nodes){while (nodes.size() > 1){//排序  从小到大Collections.sort(nodes);//取出第一颗、第二颗最小的二叉树Node1 leftNode = nodes.get(0);Node1 rightNode = nodes.get(1);//创建新的二叉树,新的二叉树没有数据，只有权值Node1 parent = new Node1(null,leftNode.weight + rightNode.weight);parent.left  = leftNode;parent.right = rightNode;//将0,1移除Listnodes.remove(leftNode);nodes.remove(rightNode);//parent加入Listnodes.add(parent);}//nodes最后剩余就是哈弗曼树的根节点return nodes.get(0);}
}
class Node1 implements Comparable<Node1>{Byte data; //存放数据 按照asciiint weight; //权值,表示字符出现的次数Node1 left;Node1 right;//前序遍历public void preOrder(){System.out.println(this);if (this.left != null){this.left.preOrder();}if (this.right != null){this.right.preOrder();}}@Overridepublic int compareTo(Node1 o) {return this.weight - o.weight;}public Node1(Byte data, int weight) {this.data = data;this.weight = weight;}@Overridepublic String toString() {return "Node1{" +"data=" + data +", weight=" + weight +'}';}
}