Function(HDU5875)

大连网络赛。当时挺混乱的,其实根本都没看这道题。后来看了题解觉得用的方法很巧妙。

值得学习。

同时回忆起一道以前的题目。

用的都是类似的思想。

#include<bits/stdc++.h>
using namespace std;
#define inf 0x3f3f3f3f
int t,n,q,l,r,ans,modpos;
int a[100005];
int rightpos[100005];
int main()
{
    scanf("%d",&t);
    while(t--)
    {
        cin>>n;
        for(int i=1; i<=n; i++)
            scanf("%d",&a[i]);
        memset(rightpos,inf,sizeof(rightpos));
        for(int i=n-1; i>=1; i--)
        {
            int k=i+1;
            while(1)
            {
                if(a[i]>a[k]) //找到右边的数比自己小,对答案有影响,存下这个位置
                {
                    rightpos[i]=k;
                    break;
                }
                if(rightpos[k]==inf)//找到最后
                    break;
                k=rightpos[k];
            }
        }
        scanf("%d",&q);
        while(q--)
        {
            scanf("%d%d",&l,&r);
            ans=a[l];
            modpos=rightpos[l];
            while(modpos<=r)
            {
                ans%=a[modpos];
                if(ans==0)
                    break;
                modpos=rightpos[modpos];
            }
            printf("%d\n",ans);
        }

    }
    return 0;
}
思路很简单,就是一直找右边的第一个比这个数小的数。然后不断的存起来,从左往右更新是n^2,从右往左更新最差是n。思路很巧妙,不断的递归往右侧找第一个出现的,小于当前位置的这个数的位置。

当时第一次启蒙我的题目是

the nearest taller cow

题目是在牛的左侧或者右侧找到最近的一个比自己高的牛的位置。然后求平均值。

也是用的类似的方法,从前往后更新出每个点往左边的第一个比他大的值。

在从右往左更新出在右边的第一个比这个数大的值。

最后求和求平均值

#include<bits/stdc++.h>
using namespace std;
#define inf 0x3f3f3f3f
#define eps 1e-7
int n,pos;
int a[1000005];
int rightpos[1000005],leftpos[1000005];
double  ans;
int main()
{
    while(~scanf("%d",&n))
    {
        ans=0;
        for(int i=1; i<=n; i++)
            scanf("%d",&a[i]);
        a[0]=inf;
        a[n+1]=inf;
        memset(rightpos,inf,sizeof(rightpos));
        memset(leftpos,inf,sizeof(leftpos));
        for(int i=1; i<=n; i++)
        {
            pos=i-1;
            while(a[pos]<=a[i])
                pos=leftpos[pos];
            leftpos[i]=pos;
        }
        for(int i=n; i>=1; i--)
        {
            pos=i+1;
            while(a[pos]<=a[i])
                pos=rightpos[pos];
            rightpos[i]=pos;
        }
        for(int i=1; i<=n; i++)
        {
            //cout<<leftpos[i]<<" "<<rightpos[i]<<endl;
            if(leftpos[i]==0)
                leftpos[i]=-inf;
            if(rightpos[i]==n+1)
                rightpos[i]=inf;
            ans+=min(min(i-leftpos[i],rightpos[i]-i),n);
        }
        //cout<<ans<<endl;
        printf("%.2f\n",ans/n+eps);
    }

    return 0;
}





### HDU 1466 Problem Description and Solution The problem **HDU 1466** involves calculating the expected number of steps to reach a certain state under specific conditions. The key elements include: #### Problem Statement Given an interactive scenario where operations are performed on numbers modulo \(998244353\), one must determine the expected number of steps required to achieve a particular outcome. For this type of problem, dynamic programming (DP) is often employed as it allows breaking down complex problems into simpler subproblems that can be solved iteratively or recursively with memoization techniques[^1]. In more detail, consider the constraints provided by similar problems such as those found in references like HDU 6327 which deals with random sequences using DP within given bounds \((1 \leq T \leq 10, 4 \leq n \leq 100)\)[^2]. These types of constraints suggest iterative approaches over small ranges might work efficiently here too. Additionally, when dealing with large inputs up to \(2 \times 10^7\) as seen in reference materials related to counting algorithms [^4], efficient data structures and optimization strategies become crucial for performance reasons. However, directly applying these methods requires understanding how they fit specifically into solving the expectation value calculation involved in HDU 1466. For instance, if each step has multiple outcomes weighted differently based on probabilities, then summing products of probability times cost across all possible states until convergence gives us our answer. To implement this approach effectively: ```python MOD = 998244353 def solve_expectation(n): dp = [0] * (n + 1) # Base case initialization depending upon problem specifics for i in range(1, n + 1): total_prob = 0 # Calculate transition probabilities from previous states for j in transitions_from(i): # Placeholder function representing valid moves prob = calculate_probability(j) next_state_cost = get_next_state_cost(j) dp[i] += prob * (next_state_cost + dp[j]) % MOD total_prob += prob dp[i] %= MOD # Normalize current state's expectation due to accumulated probability mass if total_prob != 0: dp[i] *= pow(total_prob, MOD - 2, MOD) dp[i] %= MOD return dp[n] # Example usage would depend heavily on exact rules governing transitions between states. ``` This code snippet outlines a generic framework tailored towards computing expectations via dynamic programming while adhering strictly to modular arithmetic requirements specified by the contest question format.
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