codeforces 1338A - Powered Addition (二进制表示)

探讨一种算法,通过最少次数的操作使数列单调递增。每次操作可向数列元素添加2的幂,目标是最小化操作次数。算法遍历数列,对比相邻元素,若后续元素小于前驱,则计算最小操作数使其相等,以此实现数列的单调递增。

题目大意:

现在有一个数列an,每次,我们可以进行无数次操作,每次可以选择任意的数字往其中加2^x,其中x为第x次操作。问我们,为了使得最终数列满足单调递增,我们最少需要做多少次的操作。

n<=1e5

解题思路:

首先,我们从左往右看数列,假如一个数比前面的数字要大,那么很明显地,我们不应该对这个数字再增加(否则给后面的数字带来负担),当比前面的数字ai-1要小的时候,我们需要思考这一个数字需要加多少。那么,我们发现当前数字最好是加到和ai-1一样大,为什么呢?因为这个差值的二进制表示的位数等同于需要我们用到操作数,那么我们肯定想这个差值要尽可能地小从而所占的位数不多,毕竟我假如只用0b'100来表示差值(3次操作)就足够了没必要用0b'1000(4次操作)来表示!最后答案就是我们操作数的最大值。

#include <bits/stdc++.h>
#define int long long 
using namespace std;
int32_t main(){
    int cas;cin>>cas;
    while(cas--){
        int n;cin>>n;
        vector<int> arrmv(n+1);
        for(int i=1;i<=n;i++)cin>>arrmv[i];
        
        int ans = 0;
        for(int i=2;i<=n;i++){
            if(arrmv[i]>arrmv[i-1])continue;
            int no = arrmv[i-1]-arrmv[i] ;
            int cnt = 0;
            while(no){
                cnt++;
                no>>=1;
            }
            arrmv[i] = arrmv[i-1];
            ans = max(ans, cnt);
        }
        cout<<ans<<endl;
    }
	return 0;
}

 

### Codeforces Problem 976C Solution in Python For solving problem 976C on Codeforces using Python, efficiency becomes a critical factor due to strict time limits aimed at distinguishing between efficient and less efficient solutions[^1]. Given these constraints, it is advisable to focus on optimizing algorithms and choosing appropriate data structures. The provided code snippet offers insight into handling string manipulation problems efficiently by customizing comparison logic for sorting elements based on specific criteria[^2]. However, for addressing problem 976C specifically, which involves determining the winner ('A' or 'B') based on frequency counts within given inputs, one can adapt similar principles of optimization but tailored towards counting occurrences directly as shown below: ```python from collections import Counter def determine_winner(): for _ in range(int(input())): count_map = Counter(input().strip()) result = "A" if count_map['A'] > count_map['B'] else "B" print(result) determine_winner() ``` This approach leverages `Counter` from Python’s built-in `collections` module to quickly tally up instances of 'A' versus 'B'. By iterating over multiple test cases through a loop defined by user input, this method ensures that comparisons are made accurately while maintaining performance standards required under tight computational resources[^3]. To further enhance execution speed when working with Python, consider submitting codes via platforms like PyPy instead of traditional interpreters whenever possible since they offer better runtime efficiencies especially important during competitive programming contests where milliseconds matter significantly.
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