文章目录
一.二叉树的存储结构
二叉树一般可以使用两种结构存储,一种顺序结构,一种是链式结构
1.顺序存储
顺序结构适用于完全二叉树
2.链式存储
typedef int BTDataType;
//二叉链
struct BinaryTreeNode
{
struct BinaryTreeNode* left;
struct BinaryTreeNode* right;
BTDataType data;
}
//三叉链
struct BinaryTreeNode
{
struct BinaryTreeNode* parent;
struct BinaryTreeNode* left;
struct BinaryTreeNode* right;
BTDataType data;
}
//多叉链,使用指针数组的方式存储
//如果知道树的度
#define N 5
struct TreeNode
{
int data;
//利用指针数组存储子节点的指针
struct TreeNode*subs[N];
};
//不知道树的度
struct TreeNode
{
int data;
//顺序表存孩子的指针
SeqList _s1;
vector<struct TreeNode *> _subs;
}
//孩子兄弟表示法
typedef int DataType;
struct TreeNode
{
struct TreeNode*firstchild;
struct TreeNode* pnextbrother;
DataType data;
}
二、堆的概念和结构
三、堆的实现
堆的头文件
//防止头文件被重复包含
#pragma once
#include<stdio.h>
#include<assert.h>
#include<stdlib.h>
#include<stdbool.h>
typedef int HPDataType;
//顺序结构实现堆
typedef struct Heap
{
HPDataType* a;
//当前存储数
size_t size;
//最大容量
size_t capacity;
}HP;
void swap(HPDataType*a,HPDataType*b);
//初始化堆
void HeapInit(HP*php);
//摧毁堆
void HeapDestroy(HP*php);
//打印堆元素
void HeapPrint(HP*php);
//插入数据
void HeapPush(HP*php, HPDataType x;
//删除栈顶数据
void HeapPop(HP*php);
//判断为空
bool HeapEmpty(HP*php);
size_t HeapSize(HP*php);
//返回堆顶数据
HPDateType HeapTop(HP*php);
void AdjustUp(HPDataType* a, size_t child);
void AdjustDown(HPDataType* a, size_t size, size_t root);
接口实现
void HeapInit(HP* php)
{
assert(php);
php->a = NULL;
php->size = php->capacity = 0;
}
void HeapDestroy(HP* php)
{
assert(php);
free(php->a);
php->a = NULL;
php->size = php->capacity = 0;
}
void Swap(HPDataType* pa, HPDataType* pb)
{
HPDataType tmp = *pa;
*pa = *pb;
*pb = tmp;
}
void HeapPrint(HP* php)
{
assert(php);
for (size_t i = 0; i < (php->size); ++i)
{
printf("%d ", php->a[i]);
}
printf("\n");
}
void AdjustUp(HPDataType* a, size_t child)
{
size_t parent = (child - 1) / 2;
while (child > 0)
{
if (a[child] < a[parent])
//如果要建立大堆
//if (a[child] > a[parent])
{
Swap(&a[child], &a[parent]);
child = parent;
parent = (child - 1) / 2;
}
else
{
break;
}
}
}
void HeapPush(HP* php, HPDataType x)
{
assert(php);
if (php->size == php->capacity)
{
size_t newCapacity = php->capacity == 0 ? 4 : php->capacity * 2;
HPDataType* tmp = realloc(php->a, sizeof(HPDataType) * newCapacity);
if (tmp == NULL)
{
printf("realloc failed\n");
exit(-1);
}
php->a = tmp;
php->capacity = newCapacity;
}
php->a[php->size] = x;
++php->size;
// 向上调整,控制保持是一个小堆
AdjustUp(php->a, php->size - 1);
}
void AdjustDown(HPDataType* a, size_t size, size_t root)
{
size_t parent = root;
size_t child = parent * 2 + 1;
while (child < size)
{
// 1、选出左右孩子中小的那个
if (child + 1 < size && a[child + 1] < a[child])
//建立大堆
//if(child+1<size&&a[child+1]>a[child])
{
++child;
}
// 2、如果孩子小于父亲,则交换,并继续往下调整
if (a[child] < a[parent])
//建立大堆
//if(a[child]>a[parent])
{
Swap(&a[child], &a[parent]);
parent = child;
child = parent * 2 + 1;
}
else
{
break;
}
}
}
// 删除堆顶的数据。(最小/最大)
void HeapPop(HP* php)
{
assert(php);
assert(php->size > 0);
Swap(&php->a[0], &php->a[php->size - 1]);
--php->size;
AdjustDown(php->a, php->size, 0);
}
bool HeapEmpty(HP* php)
{
assert(php);
return php->size == 0;
}
int HeapSize(HP* php)
{
assert(php);
return php->size;
}
HPDataType HeapTop(HP* php)
{
assert(php);
assert(php->size > 0);
return php->a[0];
}
四、测试堆和二叉树
#include"Heap.h"
void TestHeap()
{
HP hp;
HeapInit(&hp);
HeapPush(&hp, 1);
HeapPush(&hp, 5);
HeapPush(&hp, 0);
HeapPush(&hp, 8);
HeapPush(&hp, 3);
HeapPush(&hp, 9);
HeapPrint(&hp);
HeapPop(&hp);
HeapPrint(&hp);
HeapDestroy(&hp);
}
//堆排序
void HeapSort(int*a,int size)
{
//创建一个堆
HP hp;
HeapInit(&hp);
//吧=把数据存放在堆中
for(int i=0;i<size;i++)
{
HeapPush(&hp,a[i]);
}
size_t j=0;
while(!HeapEmpty(&hp))
{
//返回堆顶
a[j]=HeapTop(&hp);
j++;
HeapPop(&hp);
}
HeapStory(&hp);
}
int main()
{
int a[]={4,2,7,8,5,1,0,6};
//进行堆排序
HeapSort(a,sizeof(a)/sizeof(int);i++);
for(int i=0;i<sizeof(a)/sizeof(int);i++)
{
printf("%d ",a[i]);
}
printf("\n");
return 0;
}
堆的实现
int array[] = {27,15,19,18,28,34,65,49,25,37};
堆的创建
int a[]={1,5,3,8,7,6};
//元素数组建堆
//通过向下调整法建立堆
void HeapSort(int *a,int size)
{
assert(a);
assert(size==1);
for(size_t j=1;j<size;j++)
{
AdjustUp(a,j);
}
}
//使用向下调整建堆
//向下调整的前提是左子树和右子树必须是堆
//从最后一个节点的父亲开始调
void HeapSort(int *a,int size)
{
for(int i=(n-1-1)/2;i>=0;i--)
{
AdjustDown(a,n,i);
}
}
建堆的时间复杂度
向上调整法的时间复杂度
向下调整法的时间复杂度
作业
堆的应用
堆排序
-
升序:建立大堆
-
//原数组升序 //建大堆 for(int i=(n-1-1)/2;i>=0;i++) { AdjustDown(a,n,i); } int end=n-1; while(end>0) { swap(&a[end],a[0]); end--; AdjustDown(a,end,0); }
-
降序:建立小堆
TopK问题
void PrintTopK(int* a, int n, int k)
{
// 1. 建堆--用a中前k个元素建堆
int* kmaxheap = (int*)malloc(sizeof(int) * k);
for (int i = 0;i < k;i++)
{
kmaxheap[i] = a[i];
}
//建立堆
for (int i = (k - 1 - 1) / 2;i >= 0;i--)
{
AdjustDown(kmaxheap, k, i);
}
// 2. 将剩余n-k个元素依次与堆顶元素交换,不满则则替换
for (int j = k;j < n;j++)
{
if (a[j] > kmaxheap[0])
{
kmaxheap[0] = a[j];
//向下调整
AdjustDown(kmaxheap, k, 0);
}
}
for (int i = 0;i < k;i++)
{
printf("%d ", kmaxheap[i]);
}
}
void TestTopk()
{
int n = 10000;
int* a = (int*)malloc(sizeof(int) * n);
srand(time(0));
for (int i = 0; i < n; ++i)
{
a[i] = rand() % 1000000;
}
a[5] = 1000000 + 1;
a[1231] = 1000000 + 2;
a[531] = 1000000 + 3;
a[5121] = 1000000 + 4;
a[115] = 1000000 + 5;
a[2335] = 1000000 + 6;
a[9999] = 1000000 + 7;
a[76] = 1000000 + 8;
a[423] = 1000000 + 9;
a[3144] = 1000000 + 10;
PrintTopK(a, n, 10);
}
int main()
{
TestTopk();
return 0;
}