PAT甲级1064

1064. Complete Binary Search Tree (30)

时间限制
100 ms
内存限制
65536 kB
代码长度限制
16000 B
判题程序
Standard
作者
CHEN, Yue

A Binary Search Tree (BST) is recursively defined as a binary tree which has the following properties:

  • The left subtree of a node contains only nodes with keys less than the node's key.
  • The right subtree of a node contains only nodes with keys greater than or equal to the node's key.
  • Both the left and right subtrees must also be binary search trees.

A Complete Binary Tree (CBT) is a tree that is completely filled, with the possible exception of the bottom level, which is filled from left to right.

Now given a sequence of distinct non-negative integer keys, a unique BST can be constructed if it is required that the tree must also be a CBT. You are supposed to output the level order traversal sequence of this BST.

Input Specification:

Each input file contains one test case. For each case, the first line contains a positive integer N (<=1000). Then N distinct non-negative integer keys are given in the next line. All the numbers in a line are separated by a space and are no greater than 2000.

Output Specification:

For each test case, print in one line the level order traversal sequence of the corresponding complete binary search tree. All the numbers in a line must be separated by a space, and there must be no extra space at the end of the line.

Sample Input:
10
1 2 3 4 5 6 7 8 9 0
Sample Output:
6 3 8 1 5 7 9 0 2 4

#include<cstdio>
#include<algorithm>
#include<vector>
#include<queue>
using namespace std;
struct node
{
	int data;
	node*l, *r;
	node():l(NULL),r(NULL){}
};
void createCBT(node*&root,int N)
{
	queue<node*> Q;
	if (!root)
	{
		root = new node;
		N--;
		if (!N)
			return;
		Q.push(root);
	}
	while (!Q.empty())
	{
		node* t = Q.front();
		Q.pop();
		if (!t->l)
		{
			t->l = new node;
			Q.push(t->l);
			N--;
			if (!N)
				return;
		}
		if (!t->r)
		{
			t->r = new node;
			Q.push(t->r);
			N--;
			if (!N)
				return;
		}
	}
}
vector<int> v; int index = 0;
void inorder(node* &root)
{
	if (!root)
		return;
	inorder(root->l);
	root->data = v[index++];
	inorder(root->r);
}
void levelorder(node*root)
{
	queue<node*> Q;
	if (root)
	{
		printf("%d", root->data);
		Q.push(root);
	}
	while (!Q.empty())
	{
		node*f = Q.front();
		Q.pop();
		if (f->l)
		{
			printf(" %d", f->l->data);
			Q.push(f->l);
		}
		if (f->r)
		{
			printf(" %d", f->r->data);
			Q.push(f->r);
		}
	}
}
int main()
{
	int N;
	scanf("%d", &N);
	node*root = NULL;
	int t;
	for (int i = 0; i <N; i++)
	{
		scanf("%d", &t);
		v.push_back(t);
	}
	createCBT(root, N);//先造出未装填数据的完全二叉树
	sort(v.begin(), v.end());//利用BST的中序遍历是递增序列
	inorder(root);//对完全二叉树进行中序遍历并往其中填数据
	levelorder(root);
	return 0;
}

### 关于 PAT 甲级 1024 题目 PAT (Programming Ability Test) 是一项编程能力测试,其中甲级考试面向有一定编程基础的学生。对于 PAT 甲级 1024 题目,虽然具体题目描述未直接给出,但从相似类型的题目分析来看,这类题目通常涉及较为复杂的算法设计。 #### 数据结构的选择与实现 针对此类问题,常用的数据结构包括但不限于二叉树节点定义: ```cpp struct Node { int val; Node* lchild, *rchild; }; ``` 此数据结构用于表示二叉树中的节点[^1]。通过这种方式构建的二叉树能够支持多种遍历操作,如前序、中序和后序遍历等。 #### 算法思路 当处理涉及到图论的问题时,深度优先搜索(DFS)是一种常见的解题策略。特别是当需要寻找最优路径或访问尽可能多的节点时,结合贪心算法可以在某些情况下提供有效的解决方案[^2]。 #### 输入输出格式说明 根据以往的经验,在解决 PAT 类型的问题时,输入部分往往遵循特定模式。例如,给定 N 行输入来描述每个节点的信息,每行按照如下格式:“Address Data Next”,这有助于理解如何解析输入并建立相应的数据模型[^4]。 #### 数学运算示例 有时也会遇到基本算术表达式的求值问题,比如分数之间的加减乘除运算。下面是一些简单的例子展示不同情况下的计算结果: - \( \frac{2}{3} + (-2) = -\frac{7}{3}\) -2) = -\frac{4}{3}\) - \( \frac{2}{3} ÷ (-2) = -\frac{1}{3}\) 这些运算是基于样例提供的信息得出的结果[^3]。
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