CodeForces 195D(脑洞)

本文介绍了一个编程任务:计算多个特殊形式的一次函数相加后得到的折线图中,不等于180度的角度数量。具体而言,需要找出所有不同交点,这些交点对应着折线图的拐点。

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问题描述:

As Valeric and Valerko were watching one of the last Euro Championship games in a sports bar, they broke a mug. Of course, the guys paid for it but the barman said that he will let them watch football in his bar only if they help his son complete a programming task. The task goes like that.

Let's consider a set of functions of the following form:

Let's define a sum of n functions y1(x), ..., yn(x) of the given type as functions(x) = y1(x) + ... + yn(x) for any x. It's easy to show that in this case the graph s(x)is a polyline. You are given n functions of the given type, your task is to find the number of angles that do not equal 180 degrees, in the graph s(x), that is the sum of the given functions.

Valeric and Valerko really want to watch the next Euro Championship game, so they asked you to help them.

Input

The first line contains integer n (1 ≤ n ≤ 105) — the number of functions. Each of the following n lines contains two space-separated integer numbers ki, bi ( - 109 ≤ ki, bi ≤ 109) that determine the i-th function.

Output

Print a single number — the number of angles that do not equal 180 degrees in the graph of the polyline that equals the sum of the given functions.

Input
1
1 0
Output
1
Input
3
1 0
0 2
-1 1
Output
2
Input
3
-2 -4
1 7
-5 1
Output
3
题目题意:问我们s(x)函数上有多少个不是180°的倾角。

题目分析:我们假象y(x)不是那样定义的,它就是简单的一次函数,那么n个一次函数相加肯定是一次函数,都是180°的倾角(直的),那么问题就出现在y(x)<0时,y(x)=0,也就是它本身应该加上一个小于0的数结果加上0了,所以就会有弯曲。

也就是记录与x轴有多少不同的交点

代码如下:

#include<iostream>
#include<cstdio>
#include<cstring>
#include<cmath>
#include<set>
#define ll long long
using namespace std;

set<long double> M;
int main()
{
    M.clear();
    int n;
    scanf("%d",&n);
    for (int i=1;i<=n;i++) {
        ll k,b;
        scanf("%lld%lld",&k,&b);
        if (k==0) continue;
        else {
            long double ans=-(long double)b/k;
            if (M.count(ans)==0) M.insert(ans);
        }
    }
    printf("%d\n",M.size());
    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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