poj 1151(离散化+矩形面积并)

题目链接：http://poj.org/problem?id=1151

关于离散化,这篇博客讲的很好：http://www.cppblog.com/MiYu/archive/2010/10/15/129999.aspx

我线段树还是不会写这个。。

借个图：

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" alt="" />

///离散化
#include <iostream>
#include <stdio.h>
#include <algorithm>
#include <string.h>
#include <cmath>
using namespace std;
const int N = ;
const double eps = 1e-;
struct Rec{
    double x1,y1;
    double x2,y2;
}rec[N];
double x[N],y[N];
int vis[N][N];
int n,k;
int cmp(double a,double b){
    if(a<b) return ;
    return ;
}
void input(){
    k = ;
    for(int i=;i<n;i++){
        scanf("%lf%lf%lf%lf",&rec[i].x1,&rec[i].y1,&rec[i].x2,&rec[i].y2);
        x[k] = rec[i].x1,y[k++] = rec[i].y1;
        x[k] = rec[i].x2,y[k++] = rec[i].y2;
    }
    sort(x,x+k,cmp);
    sort(y,y+k,cmp);
}
int binary1(double value){
    int mid,l=,r=k-;
    while(l<r){
        mid = (l+r)>>;
        if(fabs(x[mid]-value)<eps) return mid;
        if(x[mid]<value) l = mid+;
        else r = mid-;
    }
    return l;
}
int binary2(double value){
    int mid,l=,r=k-;
    while(l<r){
        mid = (l+r)>>;
        if(fabs(y[mid]-value)<eps) return mid;
        if(y[mid]<value) l = mid+;
        else r = mid-;
    }
    return l;
}
double solve(){
    int t1,t2,t3,t4;
    for(int i=;i<n;i++){
        t1 = binary1(rec[i].x1);
        t2 = binary1(rec[i].x2);
        t3 = binary2(rec[i].y1);
        t4 = binary2(rec[i].y2);
        for(int j=t1;j<t2;j++){
            for(int l = t3;l<t4;l++){
                vis[j][l]=;
            }
        }
    }
    double area = ;
    for(int i=;i<k;i++){
        for(int j=;j<k;j++){
            area+=vis[i][j]*(x[i+]-x[i])*(y[j+]-y[j]);
        }
    }
    return area;
}
int main()
{
    int cnt=;
    while(scanf("%d",&n)!=EOF&&n){
        memset(vis,,sizeof(vis));
        input();
        printf("Test case #%d\nTotal explored area: %.2lf\n\n",cnt++,solve());
    }
    return ;
}