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数据压缩中的编码问题实验

#define _CRT_SECURE_NO_WARNINGS#include
   
    #include
    
     #define Minweight -1typedef struct Node* ElementType;struct Node {   	int Weight;	char Key;};typedef struct HfTNode* HuffmanTree;struct HfTNode {   	ElementType Data;	HuffmanTree Left, Right;};typedef struct Heapstruct* MinHeap;struct Heapstruct {   	HuffmanTree* Elements;	int Size;	int Capacity;};typedef struct SNode* PtrToSNode;struct SNode {   	ElementType Data;	PtrToSNode Next; };typedef PtrToSNode Stack;Stack CreateStack(void);//创建一个栈int IsEmpty_Stack(Stack);//判断栈是否为空void Push(Stack, ElementType);//将元素放入栈中ElementType Pop(Stack);//将元素从栈顶拿出ElementType GetStackTop(Stack);//查看栈顶元素MinHeap CreateMinHeap(int MaxSize);int IsEmpty_MinHeap(MinHeap H);int IsFull_MinHeap(MinHeap H);void Insert_MinHeap(MinHeap H, HuffmanTree Item);HuffmanTree Delete_MinHeap(MinHeap H);void MinMaking(MinHeap H, int Root);void BuildMinHeap(MinHeap H);HuffmanTree Huffman(MinHeap H);void PrintPath(HuffmanTree T);int main(void){   	Stack S;	int MaxSize;	MinHeap H;	HuffmanTree T;	S = CreateStack();	do {   		printf("输入关键字个数\n");		scanf("%d", &MaxSize);		getchar();		if (MaxSize <= 1)			printf("不必为%d个关键字编码\n");		else			break;	} while (1);	H = CreateMinHeap(MaxSize);	for (int i = 1; i <= MaxSize; i++) {   		H->Elements[i] = (HuffmanTree)malloc(sizeof(struct HfTNode));		H->Elements[i]->Left = NULL;		H->Elements[i]->Right = NULL;		H->Elements[i]->Data = (ElementType)malloc(sizeof(struct HfTNode));		printf("输入关键字及出现频率\n");		scanf("%c %d", &H->Elements[i]->Data->Key, &H->Elements[i]->Data->Weight);		getchar();	}//建立一个任意顺序存放关键字和权重的数组	T = Huffman(H);//将这个数组转换成哈弗曼树	printf("#######
     
      #######\n");	PrintPath(T);//将哈弗曼树转换成编码!}//将哈弗曼树转换成编码void PrintPath(HuffmanTree T)//所有无用树结点的Key都会被修改为-1{   	HuffmanTree PtoT;	HuffmanTree Root;	char Word[10];	int i = 0;	while (T->Data->Key != -1) {   		PtoT = T;		Root = PtoT;		i = 0;		while (1) {   			if (!PtoT->Left && !PtoT->Right) {   				Word[i++] = PtoT->Data->Key;				Word[i] = '\0';				printf("%s\n", Word);				PtoT->Data->Key = -1;				if ((!Root->Left || Root->Left->Data->Key == -1) && (!Root->Right || Root->Right->Data->Key == -1))					Root->Data->Key = -1;				break;			}			else if (PtoT->Left && PtoT->Left->Data->Key != -1) {   				Word[i++] = '1';				Root = PtoT;				PtoT = PtoT->Left;				continue;			}			else if (PtoT->Right && PtoT->Right->Data->Key != -1) {   				Word[i++] = '0';				Root = PtoT;				PtoT = PtoT->Right;				continue;			}			PtoT->Data->Key = -1;			break;		}	}}//以下为用到的堆函数MinHeap CreateMinHeap(int MaxSize){   	MinHeap H;	H = (MinHeap)malloc(sizeof(struct Heapstruct));	H->Elements = (HuffmanTree*)malloc(sizeof(HuffmanTree) * (MaxSize + 1));	H->Size = MaxSize;	H->Capacity = MaxSize;	H->Elements[0] = (HuffmanTree)malloc(sizeof(struct HfTNode));	H->Elements[0]->Data = (ElementType)malloc(sizeof(struct Node));	H->Elements[0]->Data->Weight = Minwight;	return H;}int IsEmpty_MinHeap(MinHeap H){   	return (H->Size == 0);}int IsFull_MinHeap(MinHeap H){   	return (H->Size == H->Capacity);}void Insert_MinHeap(MinHeap H, HuffmanTree Item){   	int i;	if (IsFull_MinHeap(H)) return;	i = ++H->Size;//i相当于子结点下标，i/2相当于父结点下标 	for (; H->Elements[i / 2]->Data->Weight > Item->Data->Weight; i /= 2)		H->Elements[i] = H->Elements[i / 2];	H->Elements[i] = Item;}HuffmanTree Delete_MinHeap(MinHeap H){   	HuffmanTree Item, MinItem;	int Parent, Child;	if (IsEmpty_MinHeap(H))		return NULL;	MinItem = H->Elements[1];	Item = H->Elements[H->Size--];	for (Parent = 1; Parent * 2 <= H->Size; Parent = Child) {   		Child = Parent * 2;		if (H->Elements[Child]->Data->Weight > H->Elements[Child + 1]->Data->Weight)			Child++;		if (H->Elements[Child]->Data->Weight > Item->Data->Weight)			break;		else			H->Elements[Parent] = H->Elements[Child];	}	H->Elements[Parent] = Item;	return MinItem;}void MinMaking(MinHeap H, int Root){   	int Parent, Child;	HuffmanTree Item;	Item = H->Elements[Root];	for (Parent = Root; Parent * 2 <= H->Size; Parent = Child) {   		Child = Parent * 2;		if (Child + 1 < H->Size && H->Elements[Child]->Data->Weight > H->Elements[Child + 1]->Data->Weight)			Child++;		if (H->Elements[Child]->Data->Weight > Item->Data->Weight)			break;		else			H->Elements[Parent] = H->Elements[Child];	}	H->Elements[Parent] = Item;}void BuildMinHeap(MinHeap H){   	int i;	for (i = H->Size / 2; i >= 1; i--) {   		MinMaking(H, i);	}}HuffmanTree Huffman(MinHeap H){   	HuffmanTree T;	BuildMinHeap(H);	while (H->Size > 1) {   		T = (HuffmanTree)malloc(sizeof(struct HfTNode));		T->Left = Delete_MinHeap(H);		T->Right = Delete_MinHeap(H);		T->Data = (ElementType)malloc(sizeof(struct Node));		T->Data->Weight = T->Left->Data->Weight + T->Right->Data->Weight;		Insert_MinHeap(H, T);//将新T插入最小值 	}	T = Delete_MinHeap(H);	return T;}//以下为所用到的栈函数Stack CreateStack(void){   	Stack S = (Stack)malloc(sizeof(struct SNode));	S->Next = NULL;	return S;}int IsEmpty_Stack(Stack S){   	return (S->Next == NULL);}void Push(Stack S, ElementType Sdata){   	PtrToSNode P;	P = (PtrToSNode)malloc(sizeof(struct SNode));//创建新的栈结点	P->Data = Sdata;	P->Next = S->Next;//将栈顶链接在新栈顶后	S->Next = P;//将新栈顶链接在栈头后}ElementType Pop(Stack S){   	if (IsEmpty_Stack(S)) {   		printf("The Stack is Empty.");		return NULL;	}	else {   		PtrToSNode P;		ElementType Sdata;		P = S->Next;//找到栈顶结点		Sdata = P->Data;//取出数据		S->Next = P->Next;//栈头链接新的栈顶		free(P);//释放原栈顶		return Sdata;	}}ElementType GetStackTop(Stack S){   	if (IsEmpty_Stack(S)) {   		printf("The Stack is empty.");		return NULL;	}	else		return S->Next->Data;}
     
    
   

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