aaarticlea/png;base64,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" alt="" />

题目地址 :  https://www.patest.cn/contests/gplt/L2-011

和之前那题很像,不明白为什么这么少人做。。。

>>>**********************************************************************>>>

#include <stdio.h>
#include <string.h>
#include <iostream>
#include <stdlib.h>
#include <math.h> 
#include <queue>
#define maxn 32
using namespace std; typedef struct{
    
    int l;
    int r;
}node;
int mid[maxn], fora[maxn], n, root, ex;
node ans[maxn]; void level(int rt){
    
     int cnt = , temp;
     queue <int> q; 
     q.push(rt);
     while(!q.empty()){
         temp = q.front();
         q.pop();
         
         cout << fora[temp]; 
         cnt ++;
         if(cnt < n)
         cout << " ";
         else if(cnt == n)
         cout << endl;
         if(ans[temp].l != -)
            q.push(ans[temp].l);
         if(ans[temp].r != -)   
            q.push(ans[temp].r);
         
         
     }
    return;
}
int build(int a, int b, int c, int d){
    
    if(a > b)
    return -;
        
    int rt = c;
    int point = a;
    while(mid[point] != fora[rt])
          point++;
    int dis = point-a ;           ans[rt].l = build(a, point-, c+, c+dis);
    ans[rt].r = build(point+, b, c+dis+, d);
    
    return c;
}
void trans(int rt){
     if(rt <  || rt >= n){
         return ;
     }
     if(ans[rt].l == - && ans[rt].r == -){
         return ;
     }
     ex = ans[rt].l;
     ans[rt].l = ans[rt].r;
     ans[rt].r = ex;
     
     trans(ans[rt].l);
     trans(ans[rt].r);
} int main(){
    //freopen("in.txt", "r", stdin);
    scanf("%d", &n);
    for(int i=; i<n; ++i)
        scanf("%d", &mid[i]);
    for(int i=; i<n; ++i)
        scanf("%d", &fora[i]);
    
    memset(ans, -, sizeof(ans));
    root = build(, n-, , n-);    
    trans(root);
    level(root);
    
    
    return ;
}

>>>好不容易水过31 题来到第一页,明天就要去比赛了.>>>

>>>强行装逼

aaarticlea/png;base64,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" alt="" />

aaarticlea/png;base64,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" alt="" />

>>>

L2-011. 玩转二叉树的更多相关文章

  1. 团体程序设计天梯赛-练习集L2-011. 玩转二叉树

    L2-011. 玩转二叉树 时间限制 400 ms 内存限制 65536 kB 代码长度限制 8000 B 判题程序 Standard 作者 陈越 给定一棵二叉树的中序遍历和前序遍历,请你先将树做个镜 ...

  2. 团体程序设计天梯赛 L2-006. 树的遍历 L2-011. 玩转二叉树

    L2-006. 树的遍历 #include <stdio.h> #include <stdlib.h> #include <string.h> #include & ...

  3. pat 团体天梯赛 L2-011. 玩转二叉树

    L2-011. 玩转二叉树 时间限制 400 ms 内存限制 65536 kB 代码长度限制 8000 B 判题程序 Standard 作者 陈越 给定一棵二叉树的中序遍历和前序遍历,请你先将树做个镜 ...

  4. L2-011. 玩转二叉树(不建树)

    L2-011. 玩转二叉树   给定一棵二叉树的中序遍历和前序遍历,请你先将树做个镜面反转,再输出反转后的层序遍历的序列.所谓镜面反转,是指将所有非叶结点的左右孩子对换.这里假设键值都是互不相等的正整 ...

  5. 【PAT-二叉树】L2-011. 玩转二叉树- 仅仅开100大的数组模拟即可!

    L2-011. 玩转二叉树 给定一棵二叉树的中序遍历和前序遍历,请你先将树做个镜面反转,再输出反转后的层序遍历的序列.所谓镜面反转,是指将所有非叶结点的左右孩子对换.(我的分析:无非就是说把左子树当成 ...

  6. PAT L2-011 玩转二叉树(二叉树层序遍历)

    给定一棵二叉树的中序遍历和前序遍历,请你先将树做个镜面反转,再输出反转后的层序遍历的序列.所谓镜面反转,是指将所有非叶结点的左右孩子对换.这里假设键值都是互不相等的正整数. 输入格式: 输入第一行给出 ...

  7. 天梯赛 L2-011. (二叉树) 玩转二叉树

    题目链接 题目描述 给定一棵二叉树的中序遍历和前序遍历,请你先将树做个镜面反转,再输出反转后的层序遍历的序列.所谓镜面反转,是指将所有非叶结点的左右孩子对换.这里假设键值都是互不相等的正整数. 输入格 ...

  8. ACM题目————玩转二叉树

    给定一棵二叉树的中序遍历和前序遍历,请你先将树做个镜面反转,再输出反转后的层序遍历的序列.所谓镜面反转,是指将所有非叶结点的左右孩子对换.这里假设键值都是互不相等的正整数. 输入格式: 输入第一行给出 ...

  9. L2-011 玩转二叉树 (25 分) (树)

    链接:https://pintia.cn/problem-sets/994805046380707840/problems/994805065406070784 题目: 给定一棵二叉树的中序遍历和前序 ...

  10. PTA 天梯赛练习 7-11 玩转二叉树-二叉树重建

    以前就思考过这个问题,但是没有深入的想过,这是一种叫二叉树重建的典型题目 如果给出中序和前序,求出后序遍历. 这道题则求的是交换儿子节点的层序遍历. 二叉树的重建应该怎么重建,首先我们知道,先根遍历, ...

随机推荐

  1. AngularJS之指令

    紧接上篇博客“初探AngularJS” 一.前言 在AngularJS中指令尤为重要且内容庞多,固单独提炼出来,梳理一番.如有错误,请不吝讲解. 好了,言归正传,让我们一起走进Angular指令的世界 ...

  2. JavaScript中尺寸、坐标

    测试环境是IE8,Chrome38,Firefox40,下面是全局通用脚本打印代码 /** * 打印 */ function write(str) { document.write(str + '&l ...

  3. 使用MATLAB对图像处理的几种方法(上)

    实验一图像的滤波处理 一.实验目的 使用MATLAB处理图像,掌握均值滤波器和加权均值滤波器的使用,对比两种滤波器对图像处理结果及系统自带函数和自定义函数性能的比较,体会不同大小的掩模对图像细节的影响 ...

  4. Oracle 11.2.0.4 RAC安装最新PSU补丁

    环境:两节点RAC(RHEL 6.4 + GI 11.2.0.4 + Oracle 11.2.0.4) 需求:安装最新PSU补丁11.2.0.4.7 1.下载补丁和最新OPatch 2.检查数据库当前 ...

  5. SQL Server 统计信息更新时采样百分比对数据预估准确性的影响

    为什么要写统计信息 最近看到园子里有人写统计信息,楼主也来凑热闹. 话说经常做数据库的,尤其是做开发的或者优化的,统计信息造成的性能问题应该说是司空见惯. 当然解决办法也并非一成不变,“一招鲜吃遍天” ...

  6. Java进击C#——应用开发之WinForm环境

    本章简言 上一章笔者讲到关于IO文件操作类,了解如何处理文件流.从这一章开始笔者将讲解相对比较高级的知识点.而本章笔者就对WinForm开发的知识点进行讲解和引导.现在很多业务都是面向于B/S模式的开 ...

  7. CSS3 值得称赞新特性

    Html5和CSS3相信大家现在都已不陌生了吧,但CSS3哪些新特性值得我们去称赞呢? 首先还是让大家来看几张效果图,相信大家看到这些效果图,肯定会说这些效果只用CSS是如何实现的呢? 1.3D正方形 ...

  8. C#-#define条件编译

    本文导读: C#的预处理器指令从来不会转化为可执行代码的命令,但是会影响编译过程的各个方面,常用的预处理器指令有#define.#undef.#if,#elif,#else和#endif等等,下面介绍 ...

  9. Checkbox 模板和样式

    <Style TargetType="{x:Type CheckBox}"> <Setter Property="FontFamily" Va ...

  10. 有点激动,WPF换肤搞定了!

    一如既往没废话! wpf桌面应用开发都是window内引入很多个UserControl. 如果你有通过不同颜色来换肤的需求,那么下面我就将整个过程! 分2个步骤: 1.主窗体背景色替换: 2.同时界面 ...