Codeforces446C - DZY Loves Fibonacci Numbers

本文详细解析了CF446C题目的解法,使用线段树维护斐波那契数列加法和区间求和操作,通过数学推导优化算法至O(mlogn)的时间复杂度。

Portal

Description

给出一个\(n(n\leq3\times10^5)\)个数的序列,进行\(m(m\leq3\times10^5)\)次操作,操作有两种:

  • 给区间\([L,R]\)加上一个斐波那契数列,即\(\{a_L,a_{L+1},...,a_R\} \rightarrow \{a_L+F_1,a_{L+1}+F_2,...,a_R+F_{R-L+1}\}\)
  • 询问区间\([L,R]\)的和,对\(10^9+9\)取模。
    斐波那契数列:\(F_1=1,F_2=2\)且满足\(F_{n+2}=F_n+F_{n+1}\)

Solution

容易知道,满足\(a_{n+2}=a_n+a_{n+1}\)的数列具有以下性质:

  • \(c_n=a_n+b_n\),则\(c_1=a_1+b_1,c_2=a_2+b_2,c_{n+2}=c_n+c_{n+1}\)
  • 有通项公式\(a_n=F_{n-2}a_1+F_{n-1}a_2\)
  • 有前缀和公式\(\sum_{i=1}^n a_i=a_{n+2}-a_2\)

下面依次进行证明。
证明1
\(c_{n+2}=a_{n+2}+b_{n+2}=(a_n+a_{n+1})+(b_n+b_{n+1})=(a_n+b_n)+(a_{n+1}+b_{n+1})=c_n+c_{n+1}\)
证明2
若当\(n\leq k\)时,\(a_n=F_{n-2}a_1+F_{n-1}a_2\),则
\(a_{k+1}=a_{k-1}+a_k=(F_{k-3}a_1+F_{k-2}a_2)+(F_{k-2}a_1+F_{k-1}a_2)=F_{k-1}a_1+F_ka_2\)
因为\(a_1=F_{-1}a_1+F_0\)(可以认为\(F_0=F_2-F_1=0,F_{-1}=F_1-F_0=1\)),\(a_2=F_0a_1+F_1a_2\)
所以\(\forall n\in\mathbb{Z},a_n=F_{n-2}a_1+F_{n-1}a_2\)
证明3
\(\begin{align} 2\Sigma_{i=1}^n a_i &= (a_1+a_2+...+a_n)+(a_1+a_2+...+a_n) \\ &=a_1+(a_1+a_2)+(a_2+a_3)+...+(a_{n-1}+a_n)+a_n \\ &=a_1+a_n+(a_3+a_4...+a_{n+1}) \\ &=(a_1+a_2+...+a_n)-a_2+a_n+a_{n+1} \\ &=\Sigma_{i=1}^n a_i+a_{n+2}-a_2 \\ \Sigma_{i=1}^n a_i &=a_{n+2}-a_2 \end{align}\)
我们现在就可以用线段树维护这个序列了。线段树中的每个节点记录三个值\(f_1,f_2,sum\),表示该区间被加上了一个以\(f_1,f_2\)开头的数列,区间和为\(sum\)
通过性质1,我们知道\(f_1,f_2\)可以叠加;
通过性质2,我们可以\(O(1)\)地将\(f_1,f_2\)下放;
通过性质3,我们可以\(O(1)\)地更新\(sum\)

时间复杂度\(O(mlogn)\)

Code

//DZY Loves Fibonacci Numbers
#include <cstdio>
inline char gc()
{
    static char now[1<<16],*S,*T;
    if(S==T) {T=(S=now)+fread(now,1,1<<16,stdin); if(S==T) return EOF;}
    return *S++;
}
inline int read()
{
    int x=0,f=1; char ch=gc();
    while(ch<'0'||'9'<ch) {if(ch=='-') f=-1; ch=gc();}
    while('0'<=ch&&ch<='9') x=x*10+ch-'0',ch=gc();
    return x*f;
}
typedef long long lint;
int const N=3e5+10;
lint const P=1e9+9;
int n,m; lint F[N],a[N];
#define s sg[s0]
struct seg{lint f1,f2,sum;} sg[N*20];
void update(int s0,int len)
{
    s.f1%=P,s.f2%=P;
    s.sum=sg[s0<<1].sum+sg[s0<<1|1].sum+(s.f1*F[len]+s.f2*F[len+1]-s.f2),s.sum%=P;
}
void pushdown(int s0,int L0,int R0)
{
    if(s.f1==0&&s.f2==0) return;
    int mid=L0+R0>>1,Ls0=s0<<1,Rs0=Ls0|1;
    sg[Ls0].f1+=s.f1; sg[Rs0].f1+=s.f1*F[mid-L0]+s.f2*F[mid-L0+1];
    sg[Ls0].f2+=s.f2; sg[Rs0].f2+=s.f1*F[mid-L0+1]+s.f2*F[mid-L0+2];
    s.f1=s.f2=0;
    update(Ls0,mid-L0+1); update(Rs0,R0-mid); 
}
void ins(int s0,int L0,int R0,int L,int R)
{
    if(L<=L0&&R0<=R) {s.f1+=F[L0-L+1],s.f2+=F[L0-L+2],update(s0,R0-L0+1); return;}
    pushdown(s0,L0,R0);
    int mid=L0+R0>>1;
    if(L<=mid) ins(s0<<1,L0,mid,L,R);
    if(mid<R) ins(s0<<1|1,mid+1,R0,L,R);
    update(s0,R0-L0+1);
}
lint query(int s0,int L0,int R0,int L,int R)
{
    if(L<=L0&&R0<=R) return s.sum;
    pushdown(s0,L0,R0);
    lint res=0; int mid=L0+R0>>1;
    if(L<=mid) res+=query(s0<<1,L0,mid,L,R);
    if(mid<R) res+=query(s0<<1|1,mid+1,R0,L,R);
    return res%P;
}
lint sumA[N];
int main()
{
    n=read(),m=read();
    F[1]=F[2]=1; for(int i=3;i<=n+1;i++) F[i]=(F[i-2]+F[i-1])%P;
    for(int i=1;i<=n;i++) a[i]=read(),sumA[i]=sumA[i-1]+a[i];
    int rt=1;
    for(int i=1;i<=m;i++)
    {
        int opt=read(),L=read(),R=read();
        if(opt==1) ins(rt,1,n,L,R);
        else printf("%lld\n",(query(rt,1,n,L,R)+sumA[R]-sumA[L-1])%P);
    }
    return 0;
}

P.S.

CF怎么是个题就要开long long!?
不知道为什么要求对\(10^9+9\)取模,而不是\(10^9+7\)

转载于:https://www.cnblogs.com/VisJiao/p/Cf446C.html

### 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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