基于社区wiki算法和这个转置数组的SO答案，这里是一个Swift 4版本，可以逆时针旋转一些2D数组90度。这里假设matrix是一个2D数组:

func rotate(matrix: [[Int]]) -> [[Int]] {
    let transposedPoints = transpose(input: matrix)
    let rotatedPoints = transposedPoints.map{ Array($0.reversed()) }
    return rotatedPoints
}


fileprivate func transpose<T>(input: [[T]]) -> [[T]] {
    if input.isEmpty { return [[T]]() }
    let count = input[0].count
    var out = [[T]](repeating: [T](), count: count)
    for outer in input {
        for (index, inner) in outer.enumerated() {
            out[index].append(inner)
        }
    }

    return out
}

为新手程序员，在纯c++。(宝蓝的东西)

#include<iostream.h>
#include<conio.h>

int main()
{
    clrscr();

    int arr[10][10];        // 2d array that holds input elements 
    int result[10][10];     //holds result

    int m,n;                //rows and columns of arr[][]
    int x,y;                //rows and columns of result[][]

    int i,j;                //loop variables
    int t;                  //temporary , holds data while conversion

    cout<<"Enter no. of rows and columns of array: ";
    cin>>m>>n;
    cout<<"\nEnter elements of array: \n\n";
    for(i = 0; i < m; i++)
    {
        for(j = 0; j<n ; j++)
        {
          cin>>arr[i][j];         // input array elements from user
        }
    }


   //rotating matrix by +90 degrees

    x = n ;                      //for non-square matrix
    y = m ;     

    for(i = 0; i < x; i++)
    {  t = m-1;                     // to create required array bounds
       for(j = 0; j < y; j++)
       {
          result[i][j] = arr[t][i];
          t--;
       }
   }

   //print result

   cout<<"\nRotated matrix is: \n\n";
   for(i = 0; i < x; i++)
   {
       for(j = 0; j < y; j++)
       {
             cout<<result[i][j]<<" ";
       }
       cout<<"\n";
   }

   getch();
   return 0;
}

从线性的角度来看，考虑以下矩阵:

    1 2 3        0 0 1
A = 4 5 6    B = 0 1 0
    7 8 9        1 0 0

现在求A

     1 4 7
A' = 2 5 8
     3 6 9

考虑A'对B的作用，或B对A'的作用。 分别为:

      7 4 1          3 6 9
A'B = 8 5 2    BA' = 2 5 8
      9 6 3          1 4 7

这对任何nxn矩阵都是可展开的。 在代码中快速应用这个概念:

void swapInSpace(int** mat, int r1, int c1, int r2, int c2)
{
    mat[r1][c1] ^= mat[r2][c2];
    mat[r2][c2] ^= mat[r1][c1];
    mat[r1][c1] ^= mat[r2][c2];
}

void transpose(int** mat, int size)
{
    for (int i = 0; i < size; i++)
    {
        for (int j = (i + 1); j < size; j++)
        {
            swapInSpace(mat, i, j, j, i);
        }
    }
}

void rotate(int** mat, int size)
{
    //Get transpose
    transpose(mat, size);

    //Swap columns
    for (int i = 0; i < size / 2; i++)
    {
        for (int j = 0; j < size; j++)
        {
            swapInSpace(mat, i, j, size - (i + 1), j);
        }
    }
}

O(1)内存算法:

旋转最外层的数据，然后你可以得到以下结果: [3] [9] [5] [1] [4] [6] [7] [2] [5] [0] [1] [3] [6] [2] [8] [4]

做这个旋转，我们知道

    dest[j][n-1-i] = src[i][j]

观察下图: A (0,0) -> A (0,3) A (0,3) -> A (3,3) A (3,3) -> A (3,0) A (3,0) -> A (0,0)

因此它是一个圆，你可以在一个循环中旋转N个元素。做这个N-1循环，然后你可以旋转最外层的元素。

对于2X2，内部也是一样的问题。

因此，我们可以得出如下结论:

function rotate(array, N)
{
    Rotate outer-most data
    rotate a new array with N-2 or you can do the similar action following step1
}

这是我在C中的就地实现

void rotateRight(int matrix[][SIZE], int length) {

    int layer = 0;

    for (int layer = 0; layer < length / 2; ++layer) {

        int first = layer;
        int last = length - 1 - layer;

        for (int i = first; i < last; ++i) {

            int topline = matrix[first][i];
            int rightcol = matrix[i][last];
            int bottomline = matrix[last][length - layer - 1 - i];
            int leftcol = matrix[length - layer - 1 - i][first];

            matrix[first][i] = leftcol;
            matrix[i][last] = topline;
            matrix[last][length - layer - 1 - i] = rightcol;
            matrix[length - layer - 1 - i][first] = bottomline;
        }
    }
}

试试我图书馆的算盘——常见的:

@Test
public void test_42519() throws Exception {
    final IntMatrix matrix = IntMatrix.range(0, 16).reshape(4);

    N.println("======= original =======================");
    matrix.println();
    // print out:
    //    [0, 1, 2, 3]
    //    [4, 5, 6, 7]
    //    [8, 9, 10, 11]
    //    [12, 13, 14, 15]

    N.println("======= rotate 90 ======================");
    matrix.rotate90().println();
    // print out:
    //    [12, 8, 4, 0]
    //    [13, 9, 5, 1]
    //    [14, 10, 6, 2]
    //    [15, 11, 7, 3]

    N.println("======= rotate 180 =====================");
    matrix.rotate180().println();
    // print out:
    //    [15, 14, 13, 12]
    //    [11, 10, 9, 8]
    //    [7, 6, 5, 4]
    //    [3, 2, 1, 0]

    N.println("======= rotate 270 ======================");
    matrix.rotate270().println();
    // print out:
    //    [3, 7, 11, 15]
    //    [2, 6, 10, 14]
    //    [1, 5, 9, 13]
    //    [0, 4, 8, 12]

    N.println("======= transpose =======================");
    matrix.transpose().println();
    // print out:
    //    [0, 4, 8, 12]
    //    [1, 5, 9, 13]
    //    [2, 6, 10, 14]
    //    [3, 7, 11, 15]

    final IntMatrix bigMatrix = IntMatrix.range(0, 10000_0000).reshape(10000);

    // It take about 2 seconds to rotate 10000 X 10000 matrix.
    Profiler.run(1, 2, 3, "sequential", () -> bigMatrix.rotate90()).printResult();

    // Want faster? Go parallel. 1 second to rotate 10000 X 10000 matrix.
    final int[][] a = bigMatrix.array();
    final int[][] c = new int[a[0].length][a.length];
    final int n = a.length;
    final int threadNum = 4;

    Profiler.run(1, 2, 3, "parallel", () -> {
        IntStream.range(0, n).parallel(threadNum).forEach(i -> {
            for (int j = 0; j < n; j++) {
                c[i][j] = a[n - j - 1][i];
            }
        });
    }).printResult();
}