codeforces 1019D Large Triangle

博客围绕从n个点中选3个点组成面积为s的三角形问题展开。先提及原题bzoj 3707求3点组成最小面积的两种解法,即分块+暴力、枚举线段+O(1)找最小值。还介绍了相关数组维护及序列调整方法,最后指出CF题可利用序列性质用二分查找求解。

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题意:
给出n个点和一个面积s,问能否从n个点中选3个点组成s的三角形的面积为s。

题解:

这题我思考了很久,因为确实方法不是很好懂。

首先,原题是bzoj 3707,这道题是给出n个点,求3个点组成的最小面积。

我们先从这题入手。

解法一:分块+暴力

            将坐标系多次旋转一个随机角度,将点排序后,由于是求最小值,所以在相邻的点最有可能,可以分块,在块内部暴力求解。

解法二:枚举线段+O(1)找最小值

            先将点以x轴坐标为关键字排序,再枚举所有的线段,将线段以斜率为关键字排序。

两个数组:

            rk[i]表示第i个点的序号。

            pos[i]表示序号为i的点是第几个点。

当我们枚举第一条线段时,他的斜率一定是最小的,而且它的两个端点的序号一定是紧挨着的。

那么,与这条线段形成的面积最小的三角形的点一定满足下列性质:

将线段当做y轴旋转坐标系后,横坐标距离线段最近的点就是面积最小的点。

而rk数组和pos数组,维护的就是一个序列,这个序列满足,序号从小到大,到当前的斜率的直线的距离满足距离递减,可以想象x轴的无穷远处有1条斜率已知的直线。

那么一开始,这个序列就是1-n,因为我们先按x坐标排序了,符合条件。

当判断完第一条线段,要判断第二条线段时,显然这个序列不再满足条件,需要做一些调整。

设第一条线段的两个点为u、v,当判断第二条线段时,画图可以发现,只有u、v两点不满足条件,而且调整方法就是交换u、v两点的序号。

这样,我们知道线段的端点u、v的序号rk[u]、rk[v](rk[u]<rk[v]),那么,序号为rk[u]-1或者rk[v]+1的点与线段形成的面积最小。

这时,pos数组就派上用场,因为刚刚说了需要一个序号到点的映射,可见,pos和rk是互逆的。

回到CF这道题来,根据序列的性质,序号的单调与面积的单调是一致的,所以我们可以用二分查找。

代码:

#include<bits/stdc++.h>
#define N 2001
#define INF 0x3f3f3f3f
#define eps 1e-10
#define pi 3.141592653589793
#define LL long long
#define pb push_back
#define cl clear
#define si size
#define lb lowwer_bound
#define mem(x) memset(x,0,sizeof x)
#define sc(x) scanf("%d",&x)
#define scc(x,y) scanf("%d%d",&x,&y)
#define sccc(x,y,z) scanf("%d%d%d",&x,&y,&z)
using namespace std;

struct Point
{
    LL x,y;
    Point(LL x=0,LL y=0):x(x),y(y){}
    bool operator < (const Point z) const
    {
        return x<z.x || (x==z.x && y<z.y);
    }
    Point operator - (const Point z) const
    {
        return Point(x-z.x,y-z.y);
    }
}a[N];
LL Cross(Point z,Point zz)
{
    return z.x*zz.y-z.y*zz.x;
}
struct Seg
{
    int u,v;
    Point p;
}seg[N*N/2];

bool cmp (Seg z,Seg zz)
{
    return Cross(z.p,zz.p)>0;
}

int rk[N],pos[N];

int main()
{
    int n;LL s;
    sc(n); scanf("%lld",&s); s<<=1;
    for (int i=1;i<=n;i++) scanf("%lld%lld",&a[i].x,&a[i].y);
    sort(a+1,a+n+1);
    int cnt=0;
    for (int i=1;i<=n;i++)
        for (int j=i+1;j<=n;j++) seg[++cnt]=Seg{i,j,a[j]-a[i]};
    sort(seg+1,seg+cnt+1,cmp);
    for (int i=1;i<=n;i++) rk[i]=pos[i]=i;
    for (int i=1;i<=cnt;i++)
    {
        Point p=seg[i].p;
        int u=seg[i].u,v=seg[i].v,l,r;
        if (rk[u]>rk[v]) swap(u,v);
        l=1;    r=rk[u]-1;
        while(l<=r)
        {
            int t=(l+r)>>1;
            LL tm=abs(Cross(p,a[pos[t]]-a[pos[rk[u]]]));
            if (tm==s)
            {
                cout<<"Yes\n"<<a[u].x<<' '<<a[u].y<<"\n"<<a[v].x<<' '<<a[v].y<<"\n"<<a[pos[t]].x<<' '<<a[pos[t]].y;
                return 0;
            }else tm>s?l=t+1:r=t-1;
        }
        swap(rk[u],rk[v]);
        swap(pos[rk[u]],pos[rk[v]]);
    }
    cout<<"No";
    return 0;
}

 

### Codeforces 1487D Problem Solution The problem described involves determining the maximum amount of a product that can be created from given quantities of ingredients under an idealized production process. For this specific case on Codeforces with problem number 1487D, while direct details about this exact question are not provided here, similar problems often involve resource allocation or limiting reagent type calculations. For instance, when faced with such constraints-based questions where multiple resources contribute to producing one unit of output but at different ratios, finding the bottleneck becomes crucial. In another context related to crafting items using various materials, it was determined that the formula `min(a[0],a[1],a[2]/2,a[3]/7,a[4]/4)` could represent how these limits interact[^1]. However, applying this directly without knowing specifics like what each array element represents in relation to the actual requirements for creating "philosophical stones" as mentioned would require adjustments based upon the precise conditions outlined within 1487D itself. To solve or discuss solutions effectively regarding Codeforces' challenge numbered 1487D: - Carefully read through all aspects presented by the contest organizers. - Identify which ingredient or component acts as the primary constraint towards achieving full capacity utilization. - Implement logic reflecting those relationships accurately; typically involving loops, conditionals, and possibly dynamic programming depending on complexity level required beyond simple minimum value determination across adjusted inputs. ```cpp #include <iostream> #include <vector> using namespace std; int main() { int n; cin >> n; vector<long long> a(n); for(int i=0;i<n;++i){ cin>>a[i]; } // Assuming indices correspond appropriately per problem statement's ratio requirement cout << min({a[0], a[1], a[2]/2LL, a[3]/7LL, a[4]/4LL}) << endl; } ``` --related questions-- 1. How does identifying bottlenecks help optimize algorithms solving constrained optimization problems? 2. What strategies should contestants adopt when translating mathematical formulas into code during competitive coding events? 3. Can you explain why understanding input-output relations is critical before implementing any algorithmic approach? 4. In what ways do prefix-suffix-middle frameworks enhance model training efficiency outside of just tokenization improvements? 5. Why might adjusting sample proportions specifically benefit models designed for tasks requiring both strong linguistic comprehension alongside logical reasoning skills?
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