Codeforces 710C-Magic Odd Square

构建奇数阶奇异数字矩阵
本文介绍了一个算法,用于构建一个n×n的矩阵,其中n为奇数,矩阵内数字从1到n²不重复,且每行、每列及两条对角线之和均为奇数。通过特定的填充方式实现这一目标。
C. Magic Odd Square
time limit per test:1 second
memory limit per test:256 megabytes
input:standard input
output:standard output

Find an n × n matrix with different numbers from1 to n2, so the sum in each row, column and both main diagonals are odd.

Input

The only line contains odd integer n (1 ≤ n ≤ 49).

Output

Print n lines with n integers. All the integers should be different and from 1 to n2. The sum in each row, column and both main diagonals should be odd.

Examples
Input
1
Output
1
Input
3
Output
2 1 4
3 5 7
6 9 8


解:魔方矩阵的变形,输入一个奇数n,形成一个n*n的矩阵,使得矩阵的每一行,每一列,两个对角线都是奇数。

因为输入为奇数,所以直接利用魔方矩阵的思路做就可以了。

#include <stdio.h>
#include <stdlib.h>

void CalculateOddMagicSquare(int n)
{
  int matrix[50][50];

  int nsqr = n * n;
  int i=0, j=n/2;    

  for (int k=1; k<=nsqr; ++k) 
  {
    matrix[i][j] = k;

    i--;
    j++;

    if (k%n == 0) 
    { 
      i += 2; 
      --j; 
    }
    else 
    {
      if (j==n) 
        j -= n;
      else if (i<0) 
        i += n;
    }
  }
  for(int i=0;i<n;i++){
  	for(int j=0;j<n-1;j++){
  		printf("%d ",matrix[i][j]);
  	}
  	printf("%d\n",matrix[i][n-1]);
  }
}
int main()
{
	int n;
	while(~scanf("%d",&n)){
		CalculateOddMagicSquare(n);
	}
	return 0;
}


### 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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