CodeForces 341D

本文介绍了一种使用四个二维树状数组来处理矩形区域的异或查询与更新操作的方法。通过将问题分解为一维情况,利用奇偶性区分不同树状数组,实现了高效的查询与更新。

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题目大意:

   两种操作:

       Query(x0,y0,x1,y1) 将以(x0,y0)与(x1,y1)为顶点的矩形区域^val

       Update(x0,y0,x1,y1)将以(x0,y0)与(x1,y1)为顶点的矩形区域求^和

解决方法:

   先考虑一维的情况,如果现在不是在二维的情况,现在是在一维的情况,我们应该怎么做呢?

   建立一个二维树状数组,对于修改操作[x,y]我们执行两种操作,第一种add(x,v),第二种add(y+1,v) 但是现在是^,而不是相加,所以呢,我们就建立两个树状数组,如果x是奇数这修改第一个树状数组,否则修改第二个树状数组。因为如果处于x与y之间是,判断与x的奇偶性如果相同就为1,否者就为0,而查询的时候我们也正是这样,如果x是奇数,修改第一个,查询奇数项也是查询第一个,当询问大于y的时候,如果x与y+1奇偶性相同,一共修改偶数项,修改在同一个树状数组中,对后面没有影响。

    现在扩展到二维,也是一样的只不过现在是建立4个树状数组而已。

我的代码:

#include <iostream>
#include <cstring>
#include <cstdio>
using namespace std;
long long tree[2][2][1200][1200];
int n,m;
int add(int x,int y,int v){
  for (int i=x;i<=n;i+=i&(-i))
    for (int j=y;j<=n;j+=j&(-j))
      tree[x&1][y&1][i][j]^=v;
  return 0;
}
long long sum(int x,int y){
  long long ans=0;
  for (int i=x;i>0;i-=i&(-i))
    for (int j=y;j>0;j-=j&(-j))
      ans^=tree[x&1][y&1][i][j];
  return ans;
}
int main(){
  //freopen("test.in","r",stdin);
  while (~scanf("%d%d",&n,&m)){
    for (int i=1;i<=m;i++){
        int op;scanf("%d",&op);
        int x1,y1,x2,y2;scanf("%d%d%d%d",&x1,&y1,&x2,&y2);
        if (op==2){
            long long val;cin>>val;
            add(x2+1,y2+1,val);
            add(x1,y2+1,val);
            add(x2+1,y1,val);
            add(x1,y1,val);
        }
        else {
            long long ans=0;
            ans^=sum(x2,y2);
            if (x1>1) ans^=sum(x1-1,y2);
            if (y1>1) ans^=sum(x2,y1-1);
            if (x1>1&&y1>1) ans^=sum(x1-1,y1-1);
            cout<<ans<<endl;
        }
    }
  }
  return 0;
}


### Codeforces 1487D Problem Solution The problem described involves determining the maximum amount of a product that can be created from given quantities of ingredients under an idealized production process. For this specific case on Codeforces with problem number 1487D, while direct details about this exact question are not provided here, similar problems often involve resource allocation or limiting reagent type calculations. For instance, when faced with such constraints-based questions where multiple resources contribute to producing one unit of output but at different ratios, finding the bottleneck becomes crucial. In another context related to crafting items using various materials, it was determined that the formula `min(a[0],a[1],a[2]/2,a[3]/7,a[4]/4)` could represent how these limits interact[^1]. However, applying this directly without knowing specifics like what each array element represents in relation to the actual requirements for creating "philosophical stones" as mentioned would require adjustments based upon the precise conditions outlined within 1487D itself. To solve or discuss solutions effectively regarding Codeforces' challenge numbered 1487D: - Carefully read through all aspects presented by the contest organizers. - Identify which ingredient or component acts as the primary constraint towards achieving full capacity utilization. - Implement logic reflecting those relationships accurately; typically involving loops, conditionals, and possibly dynamic programming depending on complexity level required beyond simple minimum value determination across adjusted inputs. ```cpp #include <iostream> #include <vector> using namespace std; int main() { int n; cin >> n; vector<long long> a(n); for(int i=0;i<n;++i){ cin>>a[i]; } // Assuming indices correspond appropriately per problem statement's ratio requirement cout << min({a[0], a[1], a[2]/2LL, a[3]/7LL, a[4]/4LL}) << endl; } ``` --related questions-- 1. How does identifying bottlenecks help optimize algorithms solving constrained optimization problems? 2. What strategies should contestants adopt when translating mathematical formulas into code during competitive coding events? 3. Can you explain why understanding input-output relations is critical before implementing any algorithmic approach? 4. In what ways do prefix-suffix-middle frameworks enhance model training efficiency outside of just tokenization improvements? 5. Why might adjusting sample proportions specifically benefit models designed for tasks requiring both strong linguistic comprehension alongside logical reasoning skills?
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