Codeforces Gym 100889 B Backward and Forward

本文介绍了一种通过合并相邻元素的方法,使数组成为回文数组所需的最少步骤数。具体包括读取数组、比较首尾元素并调整的过程。

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B. Backward and Forward

time limit per test2 seconds
memory limit per test256 megabytes
inputstandard input
outputstandard output

An array is called a ‘Mirror’ if it reads the same backward and forward. For example, [23, 15, 23] is a ‘Mirror’ but [2, 0, 1] is not.

You are given an array A of size N. Your task is to make a given array a ‘Mirror’. The only allowed operation is that you can merge two adjacent elements in the array and replace them with their sum.

Find minimum number of operations required to make given array a ‘Mirror’ such that it reads the same backward and forward.

Input

First line contains T(1 ≤ T ≤ 20), the number of test cases. Each test case consist of 2 lines. First line contains number N(1 ≤ N ≤ 105), size of the array. Next line contains N space separated integers Ai(0 ≤ Ai ≤ 109) denoting elements in the array A.

Output

For each test case output in one line minimum steps required to make given array a ‘Mirror’.

input

2
3
1 0 1
5
10 20 20 10 40

output

0
3

Sample test case 1:

Given array is already a ‘Mirror’ . So, no need to perform any operation.

Sample test case 2:

One possible sequence of operations.

Step 1 : Merge 2nd and 3rd element to get array [10, 40, 10, 40].

Step 2 : Merge 1st and 2nd element to get array [50, 10, 40].

Step 3 : Merge 2nd and 3rd element to get array [50, 50].


#include<cstdio>
#include<cstring>
#include<algorithm>
using namespace std;

__int64 a[100005];

int main()
{
    int t;
    long long n, i, j;
    scanf("%d", &t);
    while(t--){
        long long op = 0;

        scanf("%lld", &n);

        for(i = 0; i < n; i++){
            scanf("%I64d", &a[i]);
        }

        for(i = 0, j = n-1; i <= j; ){
            if(a[i]==a[j]){
                i++;
                j--;
            }
            else if(a[i] > a[j]){ // 需要从尾部开始合并 
                j--;
                a[j]+=a[j+1];
                op++;
            }
            else{   //从头部开始合并 
                i++;
                a[i]+=a[i-1];
                op++;
            }
        }
        printf("%lld\n", op);
    }
    return 0;
}


Codeforces Gym 101630 是一场编程竞赛,通常包含多个算法挑战问题。这些问题往往涉及数据结构、算法设计、数学建模等多个方面,旨在测试参赛者的编程能力和解决问题的能力。 以下是一些可能出现在 Codeforces Gym 101630 中的题目类型及解决方案概述: ### 题目类型 1. **动态规划(DP)** 动态规划是编程竞赛中常见的题型之一。问题通常要求找到某种最优解,例如最小路径和、最长递增子序列等。解决这类问题的关键在于状态定义和转移方程的设计[^1]。 2. **图论** 图论问题包括最短路径、最小生成树、网络流等。例如,Dijkstra 算法用于求解单源最短路径问题,而 Kruskal 或 Prim 算法则常用于最小生成树问题[^1]。 3. **字符串处理** 字符串问题可能涉及模式匹配、后缀数组、自动机等高级技巧。KMP 算法和 Trie 树是解决此类问题的常用工具[^1]。 4. **数论与组合数学** 这类问题通常需要对质数、模运算、排列组合等有深入的理解。例如,快速幂算法可以用来高效计算大数的模幂运算[^1]。 5. **几何** 几何问题可能涉及点、线、多边形的计算,如判断点是否在多边形内部、计算两个圆的交点等。向量运算和坐标变换是解决几何问题的基础[^1]。 ### 解决方案示例 #### 示例问题:动态规划 - 最长递增子序列 ```python def longest_increasing_subsequence(nums): if not nums: return 0 dp = [1] * len(nums) for i in range(len(nums)): for j in range(i): if nums[i] > nums[j]: dp[i] = max(dp[i], dp[j] + 1) return max(dp) # 示例输入 nums = [10, 9, 2, 5, 3, 7, 101, 18] print(longest_increasing_subsequence(nums)) # 输出: 4 ``` #### 示例问题:图论 - Dijkstra 算法 ```python import heapq def dijkstra(graph, start): distances = {node: float('infinity') for node in graph} distances[start] = 0 priority_queue = [(0, start)] while priority_queue: current_distance, current_node = heapq.heappop(priority_queue) if current_distance > distances[current_node]: continue for neighbor, weight in graph[current_node].items(): distance = current_distance + weight if distance < distances[neighbor]: distances[neighbor] = distance heapq.heappush(priority_queue, (distance, neighbor)) return distances # 示例输入 graph = { 'A': {'B': 1, 'C': 4}, 'B': {'A': 1, 'C': 2, 'D': 5}, 'C': {'A': 4, 'B': 2, 'D': 1}, 'D': {'B': 5, 'C': 1} } start = 'A' print(dijkstra(graph, start)) # 输出: {'A': 0, 'B': 1, 'C': 3, 'D': 4} ``` #### 示例问题:字符串处理 - KMP 算法 ```python def kmp_failure_function(pattern): m = len(pattern) lps = [0] * m length = 0 # length of the previous longest prefix suffix i = 1 while i < m: if pattern[i] == pattern[length]: length += 1 lps[i] = length i += 1 else: if length != 0: length = lps[length - 1] else: lps[i] = 0 i += 1 return lps def kmp_search(text, pattern): n = len(text) m = len(pattern) lps = kmp_failure_function(pattern) i = 0 # index for text j = 0 # index for pattern while i < n: if pattern[j] == text[i]: i += 1 j += 1 if j == m: print("Pattern found at index", i - j) j = lps[j - 1] elif i < n and pattern[j] != text[i]: if j != 0: j = lps[j - 1] else: i += 1 # 示例输入 text = "ABABDABACDABABCABAB" pattern = "ABABCABAB" kmp_search(text, pattern) # 输出: Pattern found at index 10 ``` ###
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