当前所有的解决方案都有O(n^2)开销作为临时空间(这不包括那些肮脏的OOP骗子!)这里有一个内存占用为O(1)的解决方案，将矩阵原地右转90度。该死的延展性，这玩意儿跑得很快!

#include <algorithm>
#include <cstddef>

// Rotates an NxN matrix of type T 90 degrees to the right.
template <typename T, size_t N>
void rotate_matrix(T (&matrix)[N][N])
{
    for(size_t i = 0; i < N; ++i)
        for(size_t j = 0; j <= (N-i); ++j)
            std::swap(matrix[i][j], matrix[j][i]);
}

免责声明:我实际上并没有测试这个。让我们玩打虫游戏吧!

这个解决方案不关心正方形或矩形的尺寸，你可以旋转4x5或5x4甚至4x4，它也不关心大小。 注意，这种实现在每次调用rotate90方法时都会创建一个新数组，它根本不会改变原始数组。

public static void main(String[] args) {
    int[][] a = new int[][] { 
                    { 1, 2, 3, 4 }, 
                    { 5, 6, 7, 8 }, 
                    { 9, 0, 1, 2 }, 
                    { 3, 4, 5, 6 }, 
                    { 7, 8, 9, 0 } 
                  };
    int[][] rotate180 = rotate90(rotate90(a));
    print(rotate180);
}

static int[][] rotate90(int[][] a) {
    int[][] ret = new int[a[0].length][a.length];
    for (int i = 0; i < a.length; i++) {
        for (int j = 0; j < a[i].length; j++) {
            ret[j][a.length - i - 1] = a[i][j];
        }
    }
    return ret;
}

static void print(int[][] array) {
    for (int i = 0; i < array.length; i++) {
        System.out.print("[");
        for (int j = 0; j < array[i].length; j++) {
            System.out.print(array[i][j]);
            System.out.print(" ");
        }
        System.out.println("]");
    }
}

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!

这是一个空间旋转方法，由java编写，只适用于正方形。对于非正方形的2d数组，无论如何都必须创建新数组。

private void rotateInSpace(int[][] arr) {
    int z = arr.length;
    for (int i = 0; i < z / 2; i++) {
        for (int j = 0; j < (z / 2 + z % 2); j++) {
            int x = i, y = j;
            int temp = arr[x][y];
            for (int k = 0; k < 4; k++) {
                int temptemp = arr[y][z - x - 1];
                arr[y][z - x - 1] = temp;
                temp = temptemp;

                int tempX = y;
                y = z - x - 1;
                x = tempX;
            }
        }
    }
}

通过创建新数组旋转任何大小的2d数组的代码:

private int[][] rotate(int[][] arr) {
    int width = arr[0].length;
    int depth = arr.length;
    int[][] re = new int[width][depth];
    for (int i = 0; i < depth; i++) {
        for (int j = 0; j < width; j++) {
            re[j][depth - i - 1] = arr[i][j];
        }
    }
    return re;
}

这是Java中的一个更好的版本:我已经为一个具有不同宽度和高度的矩阵制作了它

H是旋转后矩阵的高度 W是旋转后矩阵的宽度

public int[][] rotateMatrixRight(int[][] matrix)
{
    /* W and H are already swapped */
    int w = matrix.length;
    int h = matrix[0].length;
    int[][] ret = new int[h][w];
    for (int i = 0; i < h; ++i) {
        for (int j = 0; j < w; ++j) {
            ret[i][j] = matrix[w - j - 1][i];
        }
    }
    return ret;
}


public int[][] rotateMatrixLeft(int[][] matrix)
{
    /* W and H are already swapped */
    int w = matrix.length;
    int h = matrix[0].length;   
    int[][] ret = new int[h][w];
    for (int i = 0; i < h; ++i) {
        for (int j = 0; j < w; ++j) {
            ret[i][j] = matrix[j][h - i - 1];
        }
    }
    return ret;
}

此代码基于Nick Berardi的帖子。

哦，伙计。我一直认为这是一个“我很无聊，我能思考什么”的谜题。我想出了我的原地换位码，但到了这里发现你的和我的几乎一模一样……啊,好。这里是Ruby版本。

require 'pp'
n = 10
a = []
n.times { a << (1..n).to_a }

pp a

0.upto(n/2-1) do |i|
  i.upto(n-i-2) do |j|
    tmp             = a[i][j]
    a[i][j]         = a[n-j-1][i]
    a[n-j-1][i]     = a[n-i-1][n-j-1]
    a[n-i-1][n-j-1] = a[j][n-i-1]
    a[j][n-i-1]     = tmp
  end
end

pp a