/* 90-degree clockwise:
   temp_array         = left_col
   left_col           = bottom_row
   bottom_row         = reverse(right_col)
   reverse(right_col) = reverse(top_row)
   reverse(top_row)   = temp_array
*/
void RotateClockwise90(int ** arr, int lo, int hi) {

  if (lo >= hi) 
    return;

  for (int i=lo; i<hi; i++) {
    int j = lo+hi-i;
    int temp   = arr[i][lo];
    arr[i][lo] = arr[hi][i];
    arr[hi][i] = arr[j][hi];
    arr[j][hi] = arr[lo][j];
    arr[lo][j] = temp;
  }

  RotateClockwise90(arr, lo+1, hi-1);
}

#转置是Ruby的Array类的标准方法，因此:

% irb
irb(main):001:0> m = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 0, 1, 2], [3, 4, 5, 6]]
=> [[1, 2, 3, 4], [5, 6, 7, 8], [9, 0, 1, 2], [3, 4, 5, 6]] 
irb(main):002:0> m.reverse.transpose
=> [[3, 9, 5, 1], [4, 0, 6, 2], [5, 1, 7, 3], [6, 2, 8, 4]]

实现是一个用c写的n^2转置函数，你可以在这里看到: http://www.ruby-doc.org/core-1.9.3/Array.html#method-i-transpose 通过选择“点击切换源”旁边的“转置”。

我记得比O(n^2)的解更好，但只适用于特殊构造的矩阵(如稀疏矩阵)

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
}

    public static void rotateMatrix(int[,] matrix)
    {
        //C#, to rotate an N*N matrix in place
        int n = matrix.GetLength(0);
        int layers =  n / 2;
        int temp, temp2;

        for (int i = 0; i < layers; i++) // for a 5 * 5 matrix, layers will be 2, since at layer three there would be only one element, (2,2), and we do not need to rotate it with itself 
        {
            int offset = 0;
            while (offset < n - 2 * i - 1)
            {
                // top right <- top left 
                temp = matrix[i + offset, n - i - 1]; //top right value when offset is zero
                matrix[i + offset, n - i - 1] = matrix[i, i + offset];   

                //bottom right <- top right 
                temp2 = matrix[n - i - 1, n - i - 1 - offset]; //bottom right value when offset is zero
                matrix[n - i - 1, n - i - 1 - offset] = temp;  

                //bottom left <- bottom right 
                temp = matrix[n - i - 1 - offset, i];
                matrix[n - i - 1 - offset, i] = temp2;  

                //top left <- bottom left 
                matrix[i, i + offset] = temp; 

                offset++;
            }
        }
    }

C代码的矩阵旋转90度顺时针在任何M*N矩阵的地方

void rotateInPlace(int * arr[size][size], int row, int column){
    int i, j;
    int temp = row>column?row:column;
    int flipTill = row < column ? row : column;
    for(i=0;i<flipTill;i++){
        for(j=0;j<i;j++){
            swapArrayElements(arr, i, j);
        }
    }

    temp = j+1;

    for(i = row>column?i:0; i<row; i++){
            for(j=row<column?temp:0; j<column; j++){
                swapArrayElements(arr, i, j);
            }
    }

    for(i=0;i<column;i++){
        for(j=0;j<row/2;j++){
            temp = arr[i][j];
            arr[i][j] = arr[i][row-j-1];
            arr[i][row-j-1] = temp;
        }
    }
}

虽然旋转数据可能是必要的(也许是为了更新物理存储的表示)，但在数组访问上添加一层间接层(也许是一个接口)会变得更简单，可能更性能:

interface IReadableMatrix
{
    int GetValue(int x, int y);
}

如果你的矩阵已经实现了这个接口，那么它可以通过这样一个装饰器类来旋转:

class RotatedMatrix : IReadableMatrix
{
    private readonly IReadableMatrix _baseMatrix;

    public RotatedMatrix(IReadableMatrix baseMatrix)
    {
        _baseMatrix = baseMatrix;
    }

    int GetValue(int x, int y)
    {
        // transpose x and y dimensions
        return _baseMatrix(y, x);
    }
}

旋转+90/-90/180度，水平/垂直翻转和缩放都可以以这种方式实现。

Performance would need to be measured in your specific scenario. However the O(n^2) operation has now been replaced with an O(1) call. It's a virtual method call which is slower than direct array access, so it depends upon how frequently the rotated array is used after rotation. If it's used once, then this approach would definitely win. If it's rotated then used in a long-running system for days, then in-place rotation might perform better. It also depends whether you can accept the up-front cost.

与所有性能问题一样，测量，测量，测量!