codeforces 1030E

本文探讨了一种算法,用于计算数组中满足特定条件的区间数量。这些区间必须包含偶数个数字1,并且最大的数字1不能超过所有1一半的数量。通过预处理和巧妙的数据结构,算法能高效地解决问题。

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根据题意,反正就是随便安排每个数字1的位置了,那么一段区间是good,首先要是1的个数是偶数,因为1个1消掉另一个1,然后就是要一个数的1要用另外一个1去消掉,所以最多的1不能比所有1的一半大,那么这个区间是good的。

又考虑到b[i](每个数字1的个数)是1到63的,所以以每个i为左端点,只要for循环遍历j<=i+63,sum[j]-sum[i-1]%==0,2*mx<=sum[j]-sum[i]就行了,因为大于j的所有sum[j]-sum[i]都一定比2*mx要大,那么只要满足sum[j]-sum[i-1]%2==0就行了,这个预处理一蛤。

#include<bits/stdc++.h>
#define maxl 300010

using namespace std;

int n;
long long ans;
long long a[maxl],b[maxl],sum[maxl];
int f[maxl][2];

int main()
{
	scanf("%d",&n);
	for(int i=1;i<=n;i++)
		scanf("%lld",&a[i]),b[i]=__builtin_popcountll(a[i]);
	for(int i=1;i<=n;i++)
	{
		sum[i]=sum[i-1]+b[i];
		if(sum[i]&1)
			f[i][1]=f[i-1][1]+1,f[i][0]=f[i-1][0];
		else
			f[i][0]=f[i-1][0]+1,f[i][1]=f[i-1][1];
	}
	ans=0;
	long long mx,tmp;
	for(int i=1;i<=n;i++)
	{
		mx=0;
		for(int j=i;j<=i+63 && j<=n;j++)
		{
			mx=b[j]>mx?b[j]:mx;
			if((sum[j]-sum[i-1])%2==0 && sum[j]-sum[i-1]>=mx*2)
				ans++;
		}
		if(i+63<n)
		{
			if(sum[i-1]&1)
				ans+=f[n][1]-f[i+63][1];
			else
				ans+=f[n][0]-f[i+63][0];
		}
	}
	printf("%lld\n",ans);
}

 

### Codeforces 887E Problem Solution and Discussion The problem **887E - The Great Game** on Codeforces involves a strategic game between two players who take turns to perform operations under specific rules. To tackle this challenge effectively, understanding both dynamic programming (DP) techniques and bitwise manipulation is crucial. #### Dynamic Programming Approach One effective method to approach this problem utilizes DP with memoization. By defining `dp[i][j]` as the optimal result when starting from state `(i,j)` where `i` represents current position and `j` indicates some status flag related to previous moves: ```cpp #include <bits/stdc++.h> using namespace std; const int MAXN = ...; // Define based on constraints int dp[MAXN][2]; // Function to calculate minimum steps using top-down DP int minSteps(int pos, bool prevMoveType) { if (pos >= N) return 0; if (dp[pos][prevMoveType] != -1) return dp[pos][prevMoveType]; int res = INT_MAX; // Try all possible next positions and update 'res' for (...) { /* Logic here */ } dp[pos][prevMoveType] = res; return res; } ``` This code snippet outlines how one might structure a solution involving recursive calls combined with caching results through an array named `dp`. #### Bitwise Operations Insight Another critical aspect lies within efficiently handling large integers via bitwise operators instead of arithmetic ones whenever applicable. This optimization can significantly reduce computation time especially given tight limits often found in competitive coding challenges like those hosted by platforms such as Codeforces[^1]. For detailed discussions about similar problems or more insights into solving strategies specifically tailored towards contest preparation, visiting forums dedicated to algorithmic contests would be beneficial. Websites associated directly with Codeforces offer rich resources including editorials written after each round which provide comprehensive explanations alongside alternative approaches taken by successful contestants during live events. --related questions-- 1. What are common pitfalls encountered while implementing dynamic programming solutions? 2. How does bit manipulation improve performance in algorithms dealing with integer values? 3. Can you recommend any online communities focused on discussing competitive programming tactics? 4. Are there particular patterns that frequently appear across different levels of difficulty within Codeforces contests?
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