数据结构实验报告欧阳光明(2021.03.07)实验名称:实验三树——哈夫曼编/解码器学生姓名:班级:班内序号:学号:日期: 2014年12月11日1.实验要求利用二叉树结构实现赫夫曼编/解码器。
基本要求:1、初始化(Init):能够对输入的任意长度的字符串s进行统计,统计每个字符的频度,并建立赫夫曼树2、建立编码表(CreateTable):利用已经建好的赫夫曼树进行编码,并将每个字符的编码输出。
3、编码(Encoding):根据编码表对输入的字符串进行编码,并将编码后的字符串输出。
4、译码(Decoding):利用已经建好的赫夫曼树对编码后的字符串进行译码,并输出译码结果。
5、打印(Print):以直观的方式打印赫夫曼树(选作)6、计算输入的字符串编码前和编码后的长度,并进行分析,讨论赫夫曼编码的压缩效果。
测试数据:I love data Structure, I love Computer。
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2、根据输入的字符串中每个字符出现的次数统计频度,对没有出现的字符一律不用编码。
2. 程序分析2.1 存储结构Huffman树给定一组具有确定权值的叶子结点,可以构造出不同的二叉树,其中带权路径长度最小的二叉树称为Huffman树,也叫做最优二叉树。
weight lchild rchildparent 2-1-1-15-1-1-1 6-1-1-1 7-1-1-1 9-1-1-1weight lchild rchild parent2-1-155-1-156-1-167-1-169-1-17701713238165482967-12.2关键算法分析(1)计算出现字符的权值利用ASCII码统计出现字符的次数,再将未出现的字符进行筛选,将出现的字符及頻数存储在数组a[]中。
void Huffman::Init(){int nNum[256]= {0}; //记录每一个字符出现的次数int ch = cin.get();int i=0;while((ch!='\r') && (ch!='\n')){nNum[ch]++; //统计字符出现的次数str[i++] = ch; //记录原始字符串ch = cin.get(); //读取下一个字符}str[i]='\0';n = 0;for ( i=0;i<256;i++){if (nNum[i]>0) //若nNum[i]==0,字符未出现{l[n] = (char)i;a[n] = nNum[i];n++;}}}时间复杂度为O(1);(2)创建哈夫曼树:算法过程:Huffman树采用顺序存储---数组;数组的前n个结点存储叶子结点,然后是分支结点,最后是根结点;首先初始化叶子结点元素—循环实现;以循环结构,实现分支结点的合成,合成规则按照huffman 树构成规则进行。
关键点:选择最小和次小结点合成。
void Huffman::CreateHTree(){HTree = new HNode [2*n-1]; //根据权重数组a[0..n-1] 初始化Huffman树for (int j = 0; j < n; j++){HTree[j].weight = a[j];HTree[j].LChild = HTree[j].RChild = HTree[j].parent = -1;}int x,y;for (int i = n; i < 2*n-1; i++) //开始建Huffman树{SelectMin( HTree, i, x, y); //从1~i中选出两个权值最小的结点HTree[x].parent = HTree[y].parent = i;HTree[i].weight = HTree[x].weight+ HTree[y].weight;HTree[i].LChild = x;HTree[i].RChild = y;HTree[i].parent = -1;}}时间复杂度为O(n2)void Huffman::SelectMin( HNode *hTree,int n, int &i1, int &i2 ) {int i;//找一个比较值的起始值for(i=0; i<n; i++) //找i1{ if(hTree[i].parent==-1 ){ i1=i; break; }}i++;for( ; i<n; i++) //找i2{ if(hTree[i].parent==-1 ){ i2=i; break; }}if(hTree[i1].weight>hTree[i2].weight) //i1指向最小的{ int j=i2; i2=i1; i1 = j; }//开始找最小的两个i++;for( ; i<n; i++){ if(hTree[i].parent==-1&& hTree[i].weight < hTree[i1].weight ){ i2=i1; i1 = i; }else if( hTree[i].parent==-1&& hTree[i].weight < hTree[i2].weight){ i2=i; }}}时间复杂度为O(n)(3)创建编码表算法过程:从叶子到根---自底向上首先定义码表存储空间;循环对n个叶子结点自底向上回溯到根,记下途径的左右关系,形成编码的逆序串;将各个叶子结点对应的逆序串反序即可。
void Huffman::CreateCodeTable(){HCodeTable = new HCode[n]; //生成编码表for (int i=0;i<n;i++){HCodeTable[i].data = l[i];int child = i; //孩子结点编号int parent = HTree[i].parent; //当前结点的父结点编号int k=0;while(parent!=-1){if (child==HTree[parent].LChild) //左孩子标‘0’HCodeTable[i].code[k] = '0';elseHCodeTable[i].code[k] = '1' ; //右孩子标‘1’k++;child = parent; //迭代parent = HTree[child].parent;}HCodeTable[i].code[k] = '\0';Reverse(HCodeTable[i].code); //将编码字符逆置}}时间复杂度为O(n)(4)生成编码串将输入的字符串的每一个字符与编码表比较void Huffman::Encode(char *d)//编码,d为编码后的字符串{char *s = str;while(*s!='\0'){for (int i=0;i<n;i++)if (*s == HCodeTable[i].data ){strcat(d, HCodeTable[i].code);break;}s++;}}时间复杂度为O(n)(5)解码:算法过程:从根到叶子---自顶向下基于huffman树存储数组,从根结点开始,依据输入待解码串s中码字0或1,分别向左或右跟踪至叶子结点,叶子结点对应的字符(见码表),即为解码得到的字符;只要s串为结束,重复上述过程void Huffman::Decode(char* s, char *d) //解码,s为编码串,d为解码后的字符串{while(*s!='\0'){int parent = 2*n-2; //根结点在HTree中的下标while (HTree[parent].LChild!=-1) //如果不是叶子结点{if (*s=='0')parent = HTree[parent].LChild;elseparent = HTree[parent].RChild;s++;}*d = HCodeTable[parent].data;d++;}}时间复杂度为O(n)2.3其他(1)哈夫曼树的输出是以凹入表示法来实现的,具体算法如下:void Huffman::Print(int i, int m){if (HTree[i].LChild == -1)cout<<setfill(' ')<<setw(m+1)<<l[i]<<setfill('-')<<setw(10-m)<<'\n';else{cout<<setfill(' ')<<setw(m+1)<<HTree[i].weight<<setfill('-')<<setw(10-m)<<'\n';Print(HTree[i].LChild,m+1);Print(HTree[i].RChild,m+1);} } (2)统计字符頻数时,利用字符的ASCII 码进行计数统计,调用了cin.get()函数3. 程序运行程序框图:程序源代码: #include <iostream>#include <iomanip>using namespace std;struct HNode{int weight; //结点权值int parent; //双亲指针int LChild; //左孩子指针 int RChild ; //右孩子指针};开始 输入要编码的字符串 统计字符頻数 生成哈夫曼树 创建编码表 生成编码串 解码结束struct HCode{char data;char code[100];};class Huffman{private:HNode* HTree; //Huffman树HCode* HCodeTable; //Huffman编码表char str[1024]; //输入的原始字符串char l[256]; //叶子节点对应的字符int a[256]; //记录每个出现的字符的个数public:int n; //叶子节点数void Init(); //初始化void CreateHTree(); //创建huffman树void CreateCodeTable(); //创建编码表void PrintTable();void Encode(char *d); //编码void Decode(char *s, char *d); //解码void Print(int i,int m); //打印Huffman树void SelectMin( HNode *hTree,int n, int &i1, int &i2);//找出最小的两个权值void Reverse(char* s); //逆序void Compare(char*d); //比较压缩大小~ Huffman(); //析构};void Huffman::Init(){int nNum[256]= {0}; //记录每一个字符出现的次数int ch = cin.get();int i=0;while((ch!='\r') && (ch!='\n')){nNum[ch]++; //统计字符出现的次数str[i++] = ch; //记录原始字符串ch = cin.get(); //读取下一个字符}str[i]='\0';n = 0;for ( i=0;i<256;i++){if (nNum[i]>0) //若nNum[i]==0,字符未出现{l[n] = (char)i;a[n] = nNum[i];n++;}}}void Huffman::CreateHTree(){HTree = new HNode [2*n-1]; //根据权重数组a[0..n-1] 初始化Huffman树for (int j = 0; j < n; j++){HTree[j].weight = a[j];HTree[j].LChild = HTree[j].RChild = HTree[j].parent = -1;}int x,y;for (int i = n; i < 2*n-1; i++) //开始建Huffman树{SelectMin( HTree, i, x, y); //从1~i中选出两个权值最小的结点HTree[x].parent = HTree[y].parent = i;HTree[i].weight = HTree[x].weight+ HTree[y].weight;HTree[i].LChild = x;HTree[i].RChild = y;HTree[i].parent = -1;}}void Huffman::SelectMin( HNode *hTree,int n, int &i1, int &i2 ){int i;//找一个比较值的起始值for(i=0; i<n; i++) //找i1{ if(hTree[i].parent==-1 ){ i1=i; break; }}i++;for( ; i<n; i++) //找i2{ if(hTree[i].parent==-1 ){ i2=i; break; }}if(hTree[i1].weight>hTree[i2].weight) //i1指向最小的 { int j=i2; i2=i1; i1 = j; }//开始找最小的两个i++;for( ; i<n; i++){ if(hTree[i].parent==-1&& hTree[i].weight < hTree[i1].weight ){ i2=i1; i1 = i; }else if( hTree[i].parent==-1&& hTree[i].weight < hTree[i2].weight){ i2=i; }}}void Huffman::Print(int i, int m){if (HTree[i].LChild == -1)cout<<setfill(' ')<<setw(m+1)<<l[i]<<setfill('-')<<setw(10-m)<<'\n';else{cout<<setfill('')<<setw(m+1)<<HTree[i].weight<<setfill('-')<<setw(10-m)<<'\n';Print(HTree[i].LChild,m+1);Print(HTree[i].RChild,m+1);}}void Huffman::CreateCodeTable(){HCodeTable = new HCode[n]; //生成编码表for (int i=0;i<n;i++){HCodeTable[i].data = l[i];i nt child = i; //孩子结点编号i nt parent = HTree[i].parent; //当前结点的父结点编号i nt k=0;w hile(parent!=-1){if (child==HTree[parent].LChild) //左孩子标‘0’HCodeTable[i].code[k] = '0';elseHCodeTable[i].code[k] = '1' ; //右孩子标‘1’k++;child = parent; //迭代parent = HTree[child].parent;}HCodeTable[i].code[k] = '\0';Reverse(HCodeTable[i].code); //将编码字符逆置}}void Huffman::PrintTable(){for (int i=0;i<n;i++)cout<<HCodeTable[i].data<<'\t'<<HCodeTable[i].cod e<<endl;}void Huffman::Encode(char *d)//编码,d为编码后的字符串{char *s = str;while(*s!='\0'){for (int i=0;i<n;i++)if (*s == HCodeTable[i].data ){strcat(d,HCodeTable[i].code);break;}s++;}}void Huffman::Decode(char* s, char *d) //解码,s为编码串,d为解码后的字符串{while(*s!='\0'){int parent = 2*n-2; //根结点在HTree中的下标while (HTree[parent].LChild!=-1) //如果不是叶子结点{if (*s=='0')parent = HTree[parent].LChild;elseparent = HTree[parent].RChild;s++;}*d = HCodeTable[parent].data;d++;}}void Huffman::Reverse(char* s)//换序{char ch;int len = strlen(s);for (int i=0;i<len/2;i++){ch = s[i];s[i] = s[len-i-1];s[len-i-1] = ch;}}void Huffman::Compare(char*d)//比较压缩大小{cout<<"编码前:"<<strlen(str)*8<<"bit"<<endl;cout<<"编码后:"<<strlen(d)<<"bit"<<endl;}Huffman::~ Huffman()//析构函数{delete []HTree;delete []HCodeTable;}void main(){Huffman HFCode;char d[1024]={0};char s[1024]={0};cout<<"请输入要编码的字符串:";HFCode.Init();HFCode.CreateHTree();HFCode.CreateCodeTable();HFCode.Encode(d);HFCode.Decode(d,s);int m;cout<<"欢迎使用\n"<<"1.打印哈夫曼树\n"<<"2.打印哈夫曼编码表\n"<<"3.打印编码\n"<<"4.打印解码\n"<<"5.压缩比"<<endl;while(1){cin>>m;switch(m){case 1:{HFCode.Print(2*HFCode.n-2,1);break;}case 2:{HFCode.PrintTable( );break;}case 3:{cout<<"编码结果:"<<d<<endl;break;}case 4:{cout<<"解码结果:"<<s<<endl;break;}case 5:{pare(d);}}}}运行结果:4. 总结在编程时,最开始在字符统计时出现了空格无法统计的问题,后来用cin.get()函数进行统计。