哈夫曼编码 即最优二叉树 一般用于压缩数据
哈夫曼案例
成绩⽐比重: 在70~89分之间占⽤用了了70% 但是都是需要经过3次判断才能得到正 确的结果. 那么如果数量量集⾮非常⼤大时,这样的⽐比较就会出现效率问题.
这颗树最后:WPL = 1 * 5 + 2 * 15 + 3 *40 +4 * 30 + 4 * 10 = 315
如果用哈夫曼树最后:
这颗树最后WPL = 5 * 3 + 15 * 3 + 40 * 2 + 30 * 2 +10 * 2 = 220
相比哈弗曼树就比第一个颗树要快的多
哈夫曼树构建
- 初始化哈夫曼⼆二叉树
- 循环不不断找到结点中,最⼩小的2个结点值. 加⼊入到哈夫曼树中.
typedef struct HaffNode{
int weight;
int flag;
int parent;
int leftChild;
int rightChild;
}HaffNode;
typedef struct Code//存放哈夫曼编码的数据元素结构
{
int bit[MaxBit];//数组
int start; //编码的起始下标
int weight;//字符的权值
}Code;
初始化哈夫曼树
//1.
//根据权重值,构建哈夫曼树;
//{2,4,5,7}
//n = 4;
void Haffman(int weight[],int n,HaffNode *haffTree){
int j,m1,m2,x1,x2;
//1.哈夫曼树初始化
//n个叶子结点. 2n-1
for(int i = 0; i < 2*n-1;i++){
if(i<n)
haffTree[i].weight = weight[i];
else
haffTree[i].weight = 0;
haffTree[i].parent = 0;
haffTree[i].flag = 0;
haffTree[i].leftChild = -1;
haffTree[i].rightChild = -1;
}
//2.构造哈夫曼树haffTree的n-1个非叶结点
for (int i = 0; i< n - 1; i++){
m1 = m2 = MaxValue;
x1 = x2 = 0;
//2,4,5,7
for (j = 0; j< n + i; j++)//循环找出所有权重中,最小的二个值--morgan
{
if (haffTree[j].weight < m1 && haffTree[j].flag == 0)
{
m2 = m1;
x2 = x1;
m1 = haffTree[j].weight;
x1 = j;
} else if(haffTree[j].weight<m2 && haffTree[j].flag == 0)
{
m2 = haffTree[j].weight;
x2 = j;
}
}
//3.将找出的两棵权值最小的子树合并为一棵子树
haffTree[x1].parent = n + i;
haffTree[x2].parent = n + i;
//将2个结点的flag 标记为1,表示已经加入到哈夫曼树中
haffTree[x1].flag = 1;
haffTree[x2].flag = 1;
//修改n+i结点的权值
haffTree[n + i].weight = haffTree[x1].weight + haffTree[x2].weight;
//修改n+i的左右孩子的值
haffTree[n + i].leftChild = x1;
haffTree[n + i].rightChild = x2;
}
}
哈夫曼编码
/*
9.2 哈夫曼编码
由n个结点的哈夫曼树haffTree构造哈夫曼编码haffCode
//{2,4,5,7}
*/
void HaffmanCode(HaffNode haffTree[], int n, Code haffCode[])
{
//1.创建一个结点cd
Code *cd = (Code * )malloc(sizeof(Code));
int child, parent;
//2.求n个叶结点的哈夫曼编码
for (int i = 0; i<n; i++)
{
//从0开始计数
cd->start = 0;
//取得编码对应权值的字符
cd->weight = haffTree[i].weight;
//当叶子结点i 为孩子结点.
child = i;
//找到child 的双亲结点;
parent = haffTree[child].parent;
//由叶结点向上直到根结点
while (parent != 0)
{
if (haffTree[parent].leftChild == child)
cd->bit[cd->start] = 0;//左孩子结点编码0
else
cd->bit[cd->start] = 1;//右孩子结点编码1
//编码自增
cd->start++;
//当前双亲结点成为孩子结点
child = parent;
//找到双亲结点
parent = haffTree[child].parent;
}
int temp = 0;
for (int j = cd->start - 1; j >= 0; j--){
temp = cd->start-j-1;
haffCode[i].bit[temp] = cd->bit[j];
}
//把cd中的数据赋值到haffCode[i]中.
//保存好haffCode 的起始位以及权值;
haffCode[i].start = cd->start;
//保存编码对应的权值
haffCode[i].weight = cd->weight;
}
}
结果
int main(int argc, const char * argv[]) {
// insert code here...
printf("Hello, 哈夫曼编码!\n");
int i, j, n = 4, m = 0;
//权值
int weight[] = {2,4,5,7};
//初始化哈夫曼树, 哈夫曼编码
HaffNode *myHaffTree = malloc(sizeof(HaffNode)*2*n-1);
Code *myHaffCode = malloc(sizeof(Code)*n);
//当前n > MaxN,表示超界. 无法处理.
if (n>MaxN)
{
printf("定义的n越界,修改MaxN!");
exit(0);
}
//1. 构建哈夫曼树
Haffman(weight, n, myHaffTree);
//2.根据哈夫曼树得到哈夫曼编码
HaffmanCode(myHaffTree, n, myHaffCode);
//3.
for (i = 0; i<n; i++)
{
printf("Weight = %d\n",myHaffCode[i].weight);
for (j = 0; j<myHaffCode[i].start; j++)
printf("%d",myHaffCode[i].bit[j]);
m = m + myHaffCode[i].weight*myHaffCode[i].start;
printf("\n");
}
printf("Huffman's WPS is:%d\n",m);
/*
Hello, 哈夫曼编码!
Weight = 2
110
Weight = 4
111
Weight = 5
10
Weight = 7
0
Huffman's WPS is:35
Program ended with exit code: 0
*/
return 0;
}