由于今天太颓了,所以没有解释
t1:
Description
码零鼠是一只很喜欢mx数学的神犇,上面那个不是ta本人的样子。这天,ta在研究一个神奇的数列,这个数列是这样的:
a0 = 1
an = ai + aj (n>=1, i,j均在[0,n-1]内均匀随机)
Ta想知道对于给定的n,an的期望值是多少,你能告诉ta吗?
出于ta对整数的热爱,你只需要输出答案向下取整后的值
Input
一个整数T,表示数据组数
每组数据一行,包括一个整数n
一道快乐题。
#include<iostream>
#include<cstdio>
#include<cstring>
#include<algorithm>
using namespace std;
int t;
long long a;
int main()
{
scanf("%d",&t);
while(t--)
{
scanf("%lld",&a);
printf("%lld\n",a+);
}
return ;
}
t2:
Description
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Input
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Output
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" alt=" " width="509" height="33" />
dp+kmp
#include<iostream>
#include<cstdio>
#include<cstring>
#include<algorithm>
using namespace std;
char b[];
int nxt[],f[];
int p,len,sum;
long long ans;
int main()
{
scanf("%s",&b);
int lenb=strlen(b);
int j=;
for(int i=;i<lenb;i++)
{
while(j!=&&b[i]!=b[j])
j=nxt[j];
if(b[i]==b[j])
nxt[i+]=++j;
else
nxt[i+]=;
}
for(int i=;i<=lenb; i++)
{
if(i%==) f[i]++;
f[i]+=f[nxt[i]];
ans+=f[i];
}
cout<<ans;
return ;
}
t3:
Description
悠悠岁月,不知不觉,距那传说中的pppfish晋级泡泡帝已是过 去数十年。数十年 中,这颗泡泡树上,也是再度变得精彩,各种泡泡 天才辈出,惊艳世人,然而,似乎 不论后人如何的出彩,在他们的头 顶之上,依然是有着一道身影而立。 泡泡帝,pppfish。 现在,pppfish即将带着被自己收服的无数个泡泡怪前往下一个 空间,而在前往下 一个空间的道路上,有N个中转站,和M条空间虫洞连接中转站(双向通道,可有重 边,可有环),然而,通过虫洞 是要一定的条件的,pppfish将手下所有泡泡怪编号为 1,2 … +∞,对于每个空间虫洞,有两个值L和R,表示此虫洞只允许编号从L到 R的泡 泡怪通过,pppfish现在在1号中转站,他想带尽可能多的泡 泡怪到达N号中转站,于是 pppfish找到了机智的你,希望你告诉 他最多可以带多少个泡泡怪,同时他还想知道所 有泡泡怪的编号(若 有多组解取字典序最小的一组 )
Input
第一行两个用空格隔开的整数N,M(2<=N<=1000,0<=M<=3000) 接下来M行,每行四个用空格隔开的整数a,b,l,r 表示在a,b中转站间有一个空间虫洞允许编号l~r的泡泡怪通过。(1<=a, b<=N,1<=l<=r<=1e6
Output
第一行一个整数ans,表示最多能携带的泡泡怪数量 接下来一行ans个用空格隔开的正整数,表示泡泡怪的编号,从小到大依次输出,如 果没有泡泡怪能通过只要输出“0”就可以了
#include<iostream>
#include<cstdio>
#include<cstring>
#include<algorithm>
#include<queue>
using namespace std;
int n,m,head[],cnt,disr[],ml,mr,flg,vis[];
struct Edge
{
int v,nxt,l,r;
}e[];
void add(int u,int v,int l,int r)
{
e[++cnt].nxt=head[u];
e[cnt].v=v;
e[cnt].l=l;
e[cnt].r=r;
head[u]=cnt;
}
void spfa(int x)
{
queue<int>q;
memset(disr,,sizeof(disr));
disr[]=0x3f3f3f3f;
vis[]=;
q.push();
while(!q.empty())
{
int u=q.front();
q.pop();
vis[u]=;
for(int i=head[u];i;i=e[i].nxt)
{
int v=e[i].v;
if(e[i].l>x||e[i].r<x)
continue;
int mindisr=min(disr[u],e[i].r);
if(disr[v]<mindisr)
{
disr[v]=mindisr;
if(!vis[v])
{
q.push(v);
vis[v]=;
}
}
}
}
if((disr[n]-x>mr-ml)||(ml==))
{
mr=disr[n];
ml=x;
flg=;
}
if(x<=ml)
{
if(disr[n]-x==mr-ml)
{
mr=disr[n];
ml=x;
flg=;
}
}
return;
}
int main()
{
scanf("%d%d",&n,&m);
for(int i=;i<=m;i++)
{
int a,b,ll,rr;
scanf("%d%d%d%d",&a,&b,&ll,&rr);
add(a,b,ll,rr);
add(b,a,ll,rr);
}
for(int i=;i<=cnt;i+=)
{
spfa(e[i].l);
}
if(!flg)
cout<<""<<endl;
else
{
printf("%d\n",mr-ml+);
while(ml<=mr)
{
printf("%d ",ml);
ml++;
}
}
return ;
}
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