1118. Birds in Forest (25)

本文介绍了一个关于并查集算法的应用实例,通过处理鸟类图片数据来解决科学家们面临的树数量统计及鸟类位置判断的问题。文章提供了完整的代码实现,并对关键步骤进行了详细解释。

Some scientists took pictures of thousands of birds in a forest. Assume that all the birds appear in the same picture belong to the same tree. You are supposed to help the scientists to count the maximum number of trees in the forest, and for any pair of birds, tell if they are on the same tree.

Input Specification:

Each input file contains one test case. For each case, the first line contains a positive number N (<= 104) which is the number of pictures. Then N lines follow, each describes a picture in the format:
K B1 B2 ... BK
where K is the number of birds in this picture, and Bi's are the indices of birds. It is guaranteed that the birds in all the pictures are numbered continuously from 1 to some number that is no more than 104.

After the pictures there is a positive number Q (<= 104) which is the number of queries. Then Q lines follow, each contains the indices of two birds.

Output Specification:

For each test case, first output in a line the maximum possible number of trees and the number of birds. Then for each query, print in a line "Yes" if the two birds belong to the same tree, or "No" if not.

Sample Input:
4
3 10 1 2
2 3 4
4 1 5 7 8
3 9 6 4
2
10 5
3 7
Sample Output:
2 10
Yes
No

问题分析:简单的并查集,只是这里根节点要每次更新,使叶子节点与根节点直接相连,最终计算树的数量的时候只要看有几个根节点就可以了

#include<cstdio>
#include<cstring>
#include<iostream>
using namespace std;

const int maxn = 10100;
int fa[10100];
int isroot[10100];
int bird_num,tree_num;

int root(int x)
{
	int tmp = x;
	
	//找到最终根节点 
	while(x != fa[x])
		x = fa[x];
	
	//所有点连接到根节点 
	while(tmp != fa[tmp])
	{
		int index = tmp;
		
		tmp = fa[tmp];
		fa[index] = x;
	}	
	
	return x;
} 

void Union(int a,int b)
{
	int fA = root(a);
	int fB = root(b);
	
	if (fA != fB)
		fa[fA] = fB;
}

int main()
{
	int n,k,q;
	
	cin >> n;
	for(int i=0; i<=maxn; i++)
	{
		fa[i] = i;
		isroot[i] = -1;
	}
	
	bird_num = -1;
	tree_num = 0;
	for(int i=0; i<n; i++)
	{
		cin >> k;
		int b[11000];
		for(int j=0; j<k; j++)
		{
			cin >> b[j];
			if (bird_num < b[j])
				bird_num = b[j];
			Union(b[j],b[0]);
		}
	}

	//有多少个根节点就有多少棵树 
	for(int i=1; i<=bird_num; i++)
	{
		isroot[root(i)] = 1;
	}
	
	for(int i=1; i<=bird_num; i++)
	{
		if (isroot[i] == 1)
			tree_num++;
	}
	
	printf("%d %d\n",tree_num,bird_num);
	cin >> q;
	
	for(int i=0; i<q; i++)
	{
		int a,b;
		
		cin >> a >> b;
		if (fa[a] == fa[b])
			cout << "Yes" << endl;
		else
			cout << "No" << endl; 
	}
	
	return 0;
}


问题分析:简单的并查集,只是这里根节点要每次更新,使叶子节点与根节点直接相连,最终计算树的数量的时候只要看有几个根节点就可以了

内容概要:本文档介绍了基于3D FDTD(时域有限差分)方法在MATLAB平台上对微带线馈电的矩形天线进行仿真分析的技术方案,重点在于模拟超MATLAB基于3D FDTD的微带线馈矩形天线分析[用于模拟超宽带脉冲通过线馈矩形天线的传播,以计算微带结构的回波损耗参数]宽带脉冲信号通过天线结构的传播过程,并计算微带结构的回波损耗参数(S11),以评估天线的匹配性能和辐射特性。该方法通过建立三维电磁场模型,精确求解麦克斯韦方程组,适用于高频电磁仿真,能够有效分析天线在宽频带内的响应特性。文档还提及该资源属于一个涵盖多个科研方向的综合性MATLAB仿真资源包,涉及通信、信号处理、电力系统、机器学习等多个领域。; 适合人群:具备电磁场与微波技术基础知识,熟悉MATLAB编程及数值仿真的高校研究生、科研人员及通信工程领域技术人员。; 使用场景及目标:① 掌握3D FDTD方法在天线仿真中的具体实现流程;② 分析微带天线的回波损耗特性,优化天线设计参数以提升宽带匹配性能;③ 学习复杂电磁问题的数值建模与仿真技巧,拓展在射频与无线通信领域的研究能力。; 阅读建议:建议读者结合电磁理论基础,仔细理解FDTD算法的离散化过程和边界条件设置,运行并调试提供的MATLAB代码,通过调整天线几何尺寸和材料参数观察回波损耗曲线的变化,从而深入掌握仿真原理与工程应用方法。
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