c_cpp 哈夫曼编码是广泛地用于数据文件压缩的​​十分有效的编码方法。其压缩率通常在20％〜90％之间。哈夫曼编码算法用字符在文件中出现的频率表来建立一个用0,1串表示各字符的最优表示方式。一个包含

Posted 2021-05-14

//4d4 贪心算法 哈夫曼算法
#include "stdafx.h"
#include "BinaryTree.h"
#include "MinHeap.h"
#include <iostream> 
using namespace std; 
 
const int N = 6;
 
template<class Type> class Huffman;
 
template<class Type> 
BinaryTree<int> HuffmanTree(Type f[],int n);
 
template<class Type> 
class Huffman
{
	friend BinaryTree<int> HuffmanTree(Type[],int);
	public:
		operator Type() const 
		{
			return weight;
		}
	//private:
		BinaryTree<int> tree;
		Type weight;
};
 
int main()
{
	char c[] = {'0','a','b','c','d','e','f'};
	int f[] = {0,45,13,12,16,9,5};//下标从1开始
	BinaryTree<int> t = HuffmanTree(f,N);
 
	cout<<"各字符出现的对应频率分别为："<<endl;
	for(int i=1; i<=N; i++)
	{
		cout<<c[i]<<":"<<f[i]<<" ";
	}
	cout<<endl;
 
	cout<<"生成二叉树的前序遍历结果为："<<endl;
	t.Pre_Order();
	cout<<endl;
 
	cout<<"生成二叉树的中序遍历结果为："<<endl;
	t.In_Order();
	cout<<endl;
 
	t.DestroyTree();
	return 0;
}
 
template<class Type>
BinaryTree<int> HuffmanTree(Type f[],int n)
{
	//生成单节点树
	Huffman<Type> *w = new Huffman<Type>[n+1];
	BinaryTree<int> z,zero;
 
	for(int i=1; i<=n; i++)
	{
		z.MakeTree(i,zero,zero);
		w[i].weight = f[i];
		w[i].tree = z;
	}
 
	//建优先队列
	MinHeap<Huffman<Type>> Q(n);
	for(int i=1; i<=n; i++) Q.Insert(w[i]);
 
	//反复合并最小频率树
	Huffman<Type> x,y;
	for(int i=1; i<n; i++)
	{
		x = Q.RemoveMin();
		y = Q.RemoveMin();
		z.MakeTree(0,x.tree,y.tree);
		x.weight += y.weight;
		x.tree = z;
		Q.Insert(x);
	}
 
	x = Q.RemoveMin();
 
	delete[] w;
 
	return x.tree;
}