HDU - 1542 Atlantis

本文介绍了一种使用线段树算法来计算多个矩形地图重叠总面积的方法。通过将地图的横线按照y轴高度排序并扫描,利用线段树记录和更新横轴区间的覆盖情况,最终计算出所有地图覆盖的总探索面积。

Problem Description

There are several ancient Greek texts that contain descriptions of the fabled island Atlantis. Some of these texts even include maps of parts of the island. But unfortunately, these maps describe different regions of Atlantis. Your friend Bill has to know the total area for which maps exist. You (unwisely) volunteered to write a program that calculates this quantity.

Input

The input file consists of several test cases. Each test case starts with a line containing a single integer n (1<=n<=100) of available maps. The n following lines describe one map each. Each of these lines contains four numbers x1;y1;x2;y2 (0<=x1<x2<=100000;0<=y1<y2<=100000), not necessarily integers. The values (x1; y1) and (x2;y2) are the coordinates of the top-left resp. bottom-right corner of the mapped area.

The input file is terminated by a line containing a single 0. Don’t process it.

Output

For each test case, your program should output one section. The first line of each section must be “Test case #k”, where k is the number of the test case (starting with 1). The second one must be “Total explored area: a”, where a is the total explored area (i.e. the area of the union of all rectangles in this test case), printed exact to two digits to the right of the decimal point.

Output a blank line after each test case.

 

Sample Input

2 10 10 20 20 15 15 25 25.5 0

Sample Output

Test case #1

Total explored area: 180.00

思路:
将所有的区域的竖线延长后,它们分隔出的横轴区间可用线段树的叶子节点表示。

对于每个长方形区域的横线按照y轴高度排序,从下向上扫描每一条横线。对于一个区域的下面那条横线标记flag为1,上面那条横线标记flag为-1。

1:当线段树的一个叶子节点的flag原本为0,如果新扫描到的横线的flag为1,这时更新这个线段的底的y坐标。

2:当线段树的一个叶子节点的flag原本为1,如果新扫描到的横线的flag为-1,则计算新区域。

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

typedef long long ll;
const int MAXN = 205;

double area = 0;
double x[MAXN];

struct Line
{
	double l, r;
	double y;
	int flag;
}line[MAXN];

struct Node
{
	double l, r;
	double y;
	int flag;
	bool end;
}node[MAXN << 2];

bool cmp(const Line &a, const Line &b)
{
	return a.y < b.y;
}

void build(int rt, int l, int r)
{
	node[rt].l = x[l];
	node[rt].r = x[r];
	node[rt].y = 0;
	node[rt].flag = 0;

	if (l + 1 == r)
	{
		node[rt].end = true;
		return;
	}

	node[rt].end = false;
	int mid = l + (r - l) / 2;
	build(rt << 1, l, mid);
	build(rt << 1 | 1, mid, r);
}

void update(int rt, double l, double r, int flag, double y)
{
	if (l >= node[rt].r || r <= node[rt].l)
	{
		return;
	}

	if (node[rt].end)
	{
		if ((node[rt].flag == 1) && (flag == -1))
		{
			area += (node[rt].r - node[rt].l) * (y - node[rt].y);
		}
		else if ((node[rt].flag == 0) && (flag == 1))
		{
			node[rt].y = y;
		}

		node[rt].flag += flag;
	}
	else
	{
		update(rt << 1, l, r, flag, y);
		update(rt << 1 | 1, l, r, flag, y);
	}
}

int main() 
{
	int n;
	double x1, y1, x2, y2;
	int Case = 0;

	while (~scanf("%d", &n) && n)
	{
		Case++;
		area = 0;
		int count = -1;
		for (int i = 0; i < n; i++)
		{
			scanf("%lf%lf%lf%lf", &x1, &y1, &x2, &y2);
			count++;
			x[count] = x1;
			line[count].l = x1;
			line[count].r = x2;
			line[count].y = y1;
			line[count].flag = 1;

			count++;
			x[count] = x2;
			line[count].l = x1;
			line[count].r = x2;
			line[count].y = y2;
			line[count].flag = -1;
		}
		sort(x, x + count + 1);
		sort(line, line + count + 1, cmp);

		build(1, 0, count);

		for (int i = 0; i <= count; i++)
		{
			update(1, line[i].l, line[i].r, line[i].flag, line[i].y);
		}

		printf("Test case #%d\n", Case);
		printf("Total explored area: %.2lf\n\n", area);
	}

    return 0;
}

 

### 关于HDU - 6609 的题目解析 由于当前未提供具体关于 HDU - 6609 题目的详细描述,以下是基于一般算法竞赛题型可能涉及的内容进行推测和解答。 #### 可能的题目背景 假设该题目属于动态规划类问题(类似于多重背包问题),其核心在于优化资源分配或路径选择。此类问题通常会给出一组物品及其属性(如重量、价值等)以及约束条件(如容量限制)。目标是最优地选取某些物品使得满足特定的目标函数[^2]。 #### 动态转移方程设计 如果此题确实是一个变种的背包问题,则可以采用如下状态定义方法: 设 `dp[i][j]` 表示前 i 种物品,在某种条件下达到 j 值时的最大收益或者最小代价。对于每一种新加入考虑范围内的物体 k ,更新规则可能是这样的形式: ```python for i in range(n): for s in range(V, w[k]-1, -1): dp[s] = max(dp[s], dp[s-w[k]] + v[k]) ``` 这里需要注意边界情况处理以及初始化设置合理值来保证计算准确性。 另外还有一种可能性就是它涉及到组合数学方面知识或者是图论最短路等相关知识点。如果是后者的话那么就需要构建相应的邻接表表示图形结构并通过Dijkstra/Bellman-Ford/Floyd-Warshall等经典算法求解两点间距离等问题了[^4]。 最后按照输出格式要求打印结果字符串"Case #X: Y"[^3]。 #### 示例代码片段 下面展示了一个简单的伪代码框架用于解决上述提到类型的DP问题: ```python def solve(): t=int(input()) res=[] cas=1 while(t>0): n,k=list(map(int,input().split())) # Initialize your data structures here ans=find_min_unhappiness() # Implement function find_min_unhappiness() res.append(f'Case #{cas}: {round(ans)}') cas+=1 t-=1 print("\n".join(res)) solve() ```
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