Codeforces 1042 D Petya and Array

本文探讨了计算数组中区间和大于特定阈值K的子区间个数的问题。采用二分法与排序技巧,通过构造后缀和与前缀和并排序,利用单调性忽略部分状态,有效降低计算复杂度。

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1.题意

给出一个数组,元素有正有负有0,问其区间和大于K的子区间的个数。

2.解法

若直接求所有区间和,有n^2个状态,显然是要直接略过一些状态。
对这类问题,解决方法一般是排序——利用单调性,在处理到某个状态时不和要求,则其后的状态也不合要求,continue。

对于本题,有个技巧:我们运用二分。对于[l,r]之间的子区间,我们只考虑跨越区间中点mid的子区间。
首先,我们要从mid开始向左构造后缀和suf,向右构造前缀和pre,进而通过任意的suf+pre产生一个区间和。
然后,我们把suf和pre们按照升序排序。
道理是很清晰的,既然任一suf+任一pre都能产生一个经过mid的子区间的区间和,我们必然希望让suf和pre都尽可能小,直到suf+pre达到阈值K——那余下的suf+pre也必然大于K,便不做考虑。

核心思路就是利用单调性忽略部分状态。

3.代码

注意有数字超过INT_MAX,要用longlong。

### 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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