c#代码将[n,m] 2D数组向右旋转90度

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace MatrixProject
{
    // mattrix class

    class Matrix{
        private int rows;
        private int cols;
        private int[,] matrix;

        public Matrix(int n){
            this.rows = n;
            this.cols = n;
            this.matrix = new int[this.rows,this.cols];

        }

        public Matrix(int n,int m){
            this.rows = n;
            this.cols = m;

            this.matrix = new int[this.rows,this.cols];
        }

        public void Show()
        {
            for (var i = 0; i < this.rows; i++)
            {
                for (var j = 0; j < this.cols; j++) {
                    Console.Write("{0,3}", this.matrix[i, j]);
                }
                Console.WriteLine();
            }                
        }

        public void ReadElements()
        {
           for (var i = 0; i < this.rows; i++)
                for (var j = 0; j < this.cols; j++)
                {
                    Console.Write("element[{0},{1}]=",i,j);
                    this.matrix[i, j] = Convert.ToInt32(Console.ReadLine());
                }            
        }


        // rotate [n,m] 2D array by 90 deg right
        public void Rotate90DegRight()
        {

            // create a mirror of current matrix
            int[,] mirror = this.matrix;

            // create a new matrix
            this.matrix = new int[this.cols, this.rows];

            for (int i = 0; i < this.rows; i++)
            {
                for (int j = 0; j < this.cols; j++)
                {
                    this.matrix[j, this.rows - i - 1] = mirror[i, j];
                }
            }

            // replace cols count with rows count
            int tmp = this.rows;
            this.rows = this.cols;
            this.cols = tmp;           
        }
    }

    class Program
    {
        static void Main(string[] args)
        {
            Matrix myMatrix = new Matrix(3,4);
            Console.WriteLine("Enter matrix elements:");
            myMatrix.ReadElements();
            Console.WriteLine("Matrix elements are:");
            myMatrix.Show();
            myMatrix.Rotate90DegRight();
            Console.WriteLine("Matrix rotated at 90 deg are:");
            myMatrix.Show();
            Console.ReadLine();
        }
    }
}

结果:

    Enter matrix elements:
    element[0,0]=1
    element[0,1]=2
    element[0,2]=3
    element[0,3]=4
    element[1,0]=5
    element[1,1]=6
    element[1,2]=7
    element[1,3]=8
    element[2,0]=9
    element[2,1]=10
    element[2,2]=11
    element[2,3]=12
    Matrix elements are:
      1  2  3  4
      5  6  7  8
      9 10 11 12
    Matrix rotated at 90 deg are:
      9  5  1
     10  6  2
     11  7  3
     12  8  4

时间- O(N)，空间- O(1)

public void rotate(int[][] matrix) {
    int n = matrix.length;
    for (int i = 0; i < n / 2; i++) {
        int last = n - 1 - i;
        for (int j = i; j < last; j++) {
            int top = matrix[i][j];
            matrix[i][j] = matrix[last - j][i];
            matrix[last - j][i] = matrix[last][last - j];
            matrix[last][last - j] = matrix[j][last];
            matrix[j][last] = top;
        }
    }
}

已经有很多答案了，我发现两个声称O(1)时间复杂度。真正的O(1)算法是保持数组存储不变，并改变索引其元素的方式。这里的目标是不消耗额外的内存，也不需要额外的时间来迭代数据。

旋转90度，-90度和180度是简单的转换，只要你知道你的2D数组中有多少行和列就可以执行;要将任何向量旋转90度，交换轴并与Y轴相反。对于-90度，交换轴和X轴。对于180度，两个坐标轴都是负的，不交换。

进一步的转换是可能的，例如通过独立地否定轴来水平和/或垂直地镜像。

这可以通过访问器方法来实现。下面的例子是JavaScript函数，但是这些概念同样适用于所有语言。

//按列/行顺序获取数组元素 var getArray2d =函数(a, x, y) { 返回一个[y] [x]; }; / /演示 Var arr = [ [5,4,6]， [1,7,9]， [- 2,11,0]， [8,21， -3]， [3， -1, 2] ]; Var newar = []; arr[0]. foreach (() => newarr。push(新数组(arr.length))); For (var I = 0;I < newar .length;我+ +){ For (var j = 0;J < newarr[0].length;j + +) { newarr[i][j] = getArray2d(arr, i, j); ｝ ｝ console.log (newarr);

// Get an array element rotated 90 degrees clockwise function getArray2dCW(a, x, y) { var t = x; x = y; y = a.length - t - 1; return a[y][x]; } //demo var arr = [ [5, 4, 6], [1, 7, 9], [-2, 11, 0], [8, 21, -3], [3, -1, 2] ]; var newarr = []; arr[0].forEach(() => newarr.push(new Array(arr.length))); for (var i = 0; i < newarr[0].length; i++) { for (var j = 0; j < newarr.length; j++) { newarr[j][i] = getArray2dCW(arr, i, j); } } console.log(newarr);

// Get an array element rotated 90 degrees counter-clockwise function getArray2dCCW(a, x, y) { var t = x; x = a[0].length - y - 1; y = t; return a[y][x]; } //demo var arr = [ [5, 4, 6], [1, 7, 9], [-2, 11, 0], [8, 21, -3], [3, -1, 2] ]; var newarr = []; arr[0].forEach(() => newarr.push(new Array(arr.length))); for (var i = 0; i < newarr[0].length; i++) { for (var j = 0; j < newarr.length; j++) { newarr[j][i] = getArray2dCCW(arr, i, j); } } console.log(newarr);

// Get an array element rotated 180 degrees function getArray2d180(a, x, y) { x = a[0].length - x - 1; y = a.length - y - 1; return a[y][x]; } //demo var arr = [ [5, 4, 6], [1, 7, 9], [-2, 11, 0], [8, 21, -3], [3, -1, 2] ]; var newarr = []; arr.forEach(() => newarr.push(new Array(arr[0].length))); for (var i = 0; i < newarr[0].length; i++) { for (var j = 0; j < newarr.length; j++) { newarr[j][i] = getArray2d180(arr, i, j); } } console.log(newarr);

这段代码假设有一个嵌套数组的数组，其中每个内部数组都是一行。

该方法允许您读取(或写入)元素(甚至是随机顺序)，就像数组已经旋转或转换一样。现在只要选择正确的函数来调用，可能是通过引用，然后就可以了!

这个概念可以扩展为通过访问器方法附加地(非破坏性地)应用转换。包括任意角度旋转和缩放。

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!

在原地顺时针90度旋转使用矢量矢量..

 #include<iostream>
 #include<vector>
 #include<algorithm>
 using namespace std;
 //Rotate a Matrix by 90 degrees
void rotateMatrix(vector<vector<int> > &matrix){
   int n=matrix.size();
   for(int i=0;i<n;i++){
    for(int j=i+1;j<n;j++){
        swap(matrix[i][j],matrix[j][i]);
    }
 }
     for(int i=0;i<n;i++){
        reverse(matrix[i].begin(),matrix[i].end());
       }
   }

    int main(){

   int n;
   cout<<"enter the size of the matrix:"<<endl;
     while (cin >> n) {
    vector< vector<int> > m;
      cout<<"enter the elements"<<endl;
    for (int i = 0; i < n; i++) {
        m.push_back(vector<int>(n));
        for (int j = 0; j < n; j++)
            scanf("%d", &m[i][j]);
    }
      cout<<"the rotated matrix is:"<<endl;
      rotateMatrix(m);
    for (int i = 0; i < n; i++) {
        for (int j = 0; j < n; j++)
            cout << m[i][j] << ' ';
        cout << endl;
    }
   }
   return 0;
 }

矩阵转置和旋转(+/-90，+/-180)的C代码

支持方阵和非方阵，具有原位和复制功能 支持2D数组和带有逻辑行/cols的1D指针 单元测试;有关使用示例，请参阅测试 测试gcc -std=c90 -Wall -pedantic, MSVC17

`

#include <stdlib.h>
#include <memory.h>
#include <assert.h>

/* 
    Matrix transpose & rotate (+/-90, +/-180)
        Supports both 2D arrays and 1D pointers with logical rows/cols
        Supports square and non-square matrices, has in-place and copy features
        See tests for examples of usage
    tested gcc -std=c90 -Wall -pedantic, MSVC17
*/

typedef int matrix_data_t;  /* matrix data type */

void transpose(const matrix_data_t* src, matrix_data_t* dst, int rows, int cols);
void transpose_inplace(matrix_data_t* data, int n );
void rotate(int direction, const matrix_data_t* src, matrix_data_t* dst, int rows, int cols);
void rotate_inplace(int direction, matrix_data_t* data, int n);
void reverse_rows(matrix_data_t* data, int rows, int cols);
void reverse_cols(matrix_data_t* data, int rows, int cols);

/* test/compare fn */
int test_cmp(const matrix_data_t* lhs, const matrix_data_t* rhs, int rows, int cols );

/* TESTS/USAGE */
void transpose_test() {

    matrix_data_t sq3x3[9] = { 0,1,2,3,4,5,6,7,8 };/* 3x3 square, odd length side */
    matrix_data_t sq3x3_cpy[9];
    matrix_data_t sq3x3_2D[3][3] = { { 0,1,2 },{ 3,4,5 },{ 6,7,8 } };/* 2D 3x3 square */
    matrix_data_t sq3x3_2D_copy[3][3];

    /* expected test values */
    const matrix_data_t sq3x3_orig[9] = { 0,1,2,3,4,5,6,7,8 };
    const matrix_data_t sq3x3_transposed[9] = { 0,3,6,1,4,7,2,5,8};

    matrix_data_t sq4x4[16]= { 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 };/* 4x4 square, even length*/
    const matrix_data_t sq4x4_orig[16] = { 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 };
    const matrix_data_t sq4x4_transposed[16] = { 0,4,8,12,1,5,9,13,2,6,10,14,3,7,11,15 };

    /* 2x3 rectangle */
    const matrix_data_t r2x3_orig[6] = { 0,1,2,3,4,5 };
    const matrix_data_t r2x3_transposed[6] = { 0,3,1,4,2,5 };
    matrix_data_t r2x3_copy[6];

    matrix_data_t r2x3_2D[2][3] = { {0,1,2},{3,4,5} };  /* 2x3 2D rectangle */
    matrix_data_t r2x3_2D_t[3][2];

    /* matrix_data_t r3x2[6] = { 0,1,2,3,4,5 }; */
    matrix_data_t r3x2_copy[6];
    /* 3x2 rectangle */
    const matrix_data_t r3x2_orig[6] = { 0,1,2,3,4,5 };
    const matrix_data_t r3x2_transposed[6] = { 0,2,4,1,3,5 };

    matrix_data_t r6x1[6] = { 0,1,2,3,4,5 };    /* 6x1 */
    matrix_data_t r6x1_copy[6];

    matrix_data_t r1x1[1] = { 0 };  /*1x1*/
    matrix_data_t r1x1_copy[1];

    /* 3x3 tests, 2D array tests */
    transpose_inplace(sq3x3, 3);    /* transpose in place */
    assert(!test_cmp(sq3x3, sq3x3_transposed, 3, 3));
    transpose_inplace(sq3x3, 3);    /* transpose again */
    assert(!test_cmp(sq3x3, sq3x3_orig, 3, 3));

    transpose(sq3x3, sq3x3_cpy, 3, 3);  /* transpose copy 3x3*/
    assert(!test_cmp(sq3x3_cpy, sq3x3_transposed, 3, 3));

    transpose((matrix_data_t*)sq3x3_2D, (matrix_data_t*)sq3x3_2D_copy, 3, 3);   /* 2D array transpose/copy */
    assert(!test_cmp((matrix_data_t*)sq3x3_2D_copy, sq3x3_transposed, 3, 3));
    transpose_inplace((matrix_data_t*)sq3x3_2D_copy, 3);    /* 2D array transpose in place */
    assert(!test_cmp((matrix_data_t*)sq3x3_2D_copy, sq3x3_orig, 3, 3));

    /* 4x4 tests */
    transpose_inplace(sq4x4, 4);    /* transpose in place */
    assert(!test_cmp(sq4x4, sq4x4_transposed, 4,4));
    transpose_inplace(sq4x4, 4);    /* transpose again */
    assert(!test_cmp(sq4x4, sq4x4_orig, 3, 3));

    /* 2x3,3x2 tests */
    transpose(r2x3_orig, r2x3_copy, 2, 3);
    assert(!test_cmp(r2x3_copy, r2x3_transposed, 3, 2));

    transpose(r3x2_orig, r3x2_copy, 3, 2);
    assert(!test_cmp(r3x2_copy, r3x2_transposed, 2,3));

    /* 2D array */
    transpose((matrix_data_t*)r2x3_2D, (matrix_data_t*)r2x3_2D_t, 2, 3);
    assert(!test_cmp((matrix_data_t*)r2x3_2D_t, r2x3_transposed, 3,2));

    /* Nx1 test, 1x1 test */
    transpose(r6x1, r6x1_copy, 6, 1);
    assert(!test_cmp(r6x1_copy, r6x1, 1, 6));

    transpose(r1x1, r1x1_copy, 1, 1);
    assert(!test_cmp(r1x1_copy, r1x1, 1, 1));

}

void rotate_test() {

    /* 3x3 square */
    const matrix_data_t sq3x3[9] = { 0,1,2,3,4,5,6,7,8 };
    const matrix_data_t sq3x3_r90[9] = { 6,3,0,7,4,1,8,5,2 };
    const matrix_data_t sq3x3_180[9] = { 8,7,6,5,4,3,2,1,0 };
    const matrix_data_t sq3x3_l90[9] = { 2,5,8,1,4,7,0,3,6 };
    matrix_data_t sq3x3_copy[9];

    /* 3x3 square, 2D */
    matrix_data_t sq3x3_2D[3][3] = { { 0,1,2 },{ 3,4,5 },{ 6,7,8 } };

    /* 4x4, 2D */
    matrix_data_t sq4x4[4][4] = { { 0,1,2,3 },{ 4,5,6,7 },{ 8,9,10,11 },{ 12,13,14,15 } };
    matrix_data_t sq4x4_copy[4][4];
    const matrix_data_t sq4x4_r90[16] = { 12,8,4,0,13,9,5,1,14,10,6,2,15,11,7,3 };
    const matrix_data_t sq4x4_l90[16] = { 3,7,11,15,2,6,10,14,1,5,9,13,0,4,8,12 };
    const matrix_data_t sq4x4_180[16] = { 15,14,13,12,11,10,9,8,7,6,5,4,3,2,1,0 };

    matrix_data_t r6[6] = { 0,1,2,3,4,5 };  /* rectangle with area of 6 (1x6,2x3,3x2, or 6x1) */
    matrix_data_t r6_copy[6];
    const matrix_data_t r1x6_r90[6] = { 0,1,2,3,4,5 };
    const matrix_data_t r1x6_l90[6] = { 5,4,3,2,1,0 };
    const matrix_data_t r1x6_180[6] = { 5,4,3,2,1,0 };

    const matrix_data_t r2x3_r90[6] = { 3,0,4,1,5,2 };
    const matrix_data_t r2x3_l90[6] = { 2,5,1,4,0,3 };
    const matrix_data_t r2x3_180[6] = { 5,4,3,2,1,0 };

    const matrix_data_t r3x2_r90[6] = { 4,2,0,5,3,1 };
    const matrix_data_t r3x2_l90[6] = { 1,3,5,0,2,4 };
    const matrix_data_t r3x2_180[6] = { 5,4,3,2,1,0 };

    const matrix_data_t r6x1_r90[6] = { 5,4,3,2,1,0 };
    const matrix_data_t r6x1_l90[6] = { 0,1,2,3,4,5 };
    const matrix_data_t r6x1_180[6] = { 5,4,3,2,1,0 };

    /* sq3x3 tests */
    rotate(90, sq3x3, sq3x3_copy, 3, 3);    /* +90 */
    assert(!test_cmp(sq3x3_copy, sq3x3_r90, 3, 3));
    rotate(-90, sq3x3, sq3x3_copy, 3, 3);   /* -90 */
    assert(!test_cmp(sq3x3_copy, sq3x3_l90, 3, 3));
    rotate(180, sq3x3, sq3x3_copy, 3, 3);   /* 180 */
    assert(!test_cmp(sq3x3_copy, sq3x3_180, 3, 3));
    /* sq3x3 in-place rotations */
    memcpy( sq3x3_copy, sq3x3, 3 * 3 * sizeof(matrix_data_t));
    rotate_inplace(90, sq3x3_copy, 3);
    assert(!test_cmp(sq3x3_copy, sq3x3_r90, 3, 3));
    rotate_inplace(-90, sq3x3_copy, 3);
    assert(!test_cmp(sq3x3_copy, sq3x3, 3, 3)); /* back to 0 orientation */
    rotate_inplace(180, sq3x3_copy, 3);
    assert(!test_cmp(sq3x3_copy, sq3x3_180, 3, 3));
    rotate_inplace(-180, sq3x3_copy, 3);
    assert(!test_cmp(sq3x3_copy, sq3x3, 3, 3));
    rotate_inplace(180, (matrix_data_t*)sq3x3_2D, 3);/* 2D test */
    assert(!test_cmp((matrix_data_t*)sq3x3_2D, sq3x3_180, 3, 3));

    /* sq4x4 */
    rotate(90, (matrix_data_t*)sq4x4, (matrix_data_t*)sq4x4_copy, 4, 4);
    assert(!test_cmp((matrix_data_t*)sq4x4_copy, sq4x4_r90, 4, 4));
    rotate(-90, (matrix_data_t*)sq4x4, (matrix_data_t*)sq4x4_copy, 4, 4);
    assert(!test_cmp((matrix_data_t*)sq4x4_copy, sq4x4_l90, 4, 4));
    rotate(180, (matrix_data_t*)sq4x4, (matrix_data_t*)sq4x4_copy, 4, 4);
    assert(!test_cmp((matrix_data_t*)sq4x4_copy, sq4x4_180, 4, 4));

    /* r6 as 1x6 */
    rotate(90, r6, r6_copy, 1, 6);
    assert(!test_cmp(r6_copy, r1x6_r90, 1, 6));
    rotate(-90, r6, r6_copy, 1, 6);
    assert(!test_cmp(r6_copy, r1x6_l90, 1, 6));
    rotate(180, r6, r6_copy, 1, 6);
    assert(!test_cmp(r6_copy, r1x6_180, 1, 6));

    /* r6 as 2x3 */
    rotate(90, r6, r6_copy, 2, 3);
    assert(!test_cmp(r6_copy, r2x3_r90, 2, 3));
    rotate(-90, r6, r6_copy, 2, 3);
    assert(!test_cmp(r6_copy, r2x3_l90, 2, 3));
    rotate(180, r6, r6_copy, 2, 3);
    assert(!test_cmp(r6_copy, r2x3_180, 2, 3));

    /* r6 as 3x2 */
    rotate(90, r6, r6_copy, 3, 2);
    assert(!test_cmp(r6_copy, r3x2_r90, 3, 2));
    rotate(-90, r6, r6_copy, 3, 2);
    assert(!test_cmp(r6_copy, r3x2_l90, 3, 2));
    rotate(180, r6, r6_copy, 3, 2);
    assert(!test_cmp(r6_copy, r3x2_180, 3, 2));

    /* r6 as 6x1 */
    rotate(90, r6, r6_copy, 6, 1);
    assert(!test_cmp(r6_copy, r6x1_r90, 6, 1));
    rotate(-90, r6, r6_copy, 6, 1);
    assert(!test_cmp(r6_copy, r6x1_l90, 6, 1));
    rotate(180, r6, r6_copy, 6, 1);
    assert(!test_cmp(r6_copy, r6x1_180, 6, 1));
}

/* test comparison fn, return 0 on match else non zero */
int test_cmp(const matrix_data_t* lhs, const matrix_data_t* rhs, int rows, int cols) {

    int r, c;

    for (r = 0; r < rows; ++r) {
        for (c = 0; c < cols; ++c) {
            if ((lhs + r * cols)[c] != (rhs + r * cols)[c])
                return -1;
        }
    }
    return 0;
}

/*
Reverse values in place of each row in 2D matrix data[rows][cols] or in 1D pointer with logical rows/cols
[A B C] ->  [C B A]
[D E F]     [F E D]
*/
void reverse_rows(matrix_data_t* data, int rows, int cols) {

    int r, c;
    matrix_data_t temp;
    matrix_data_t* pRow = NULL;

    for (r = 0; r < rows; ++r) {
        pRow = (data + r * cols);
        for (c = 0; c < (int)(cols / 2); ++c) { /* explicit truncate */
            temp = pRow[c];
            pRow[c] = pRow[cols - 1 - c];
            pRow[cols - 1 - c] = temp;
        }
    }
}

/*
Reverse values in place of each column in 2D matrix data[rows][cols] or in 1D pointer with logical rows/cols
[A B C] ->  [D E F]
[D E F]     [A B C]
*/
void reverse_cols(matrix_data_t* data, int rows, int cols) {

    int r, c;
    matrix_data_t temp;
    matrix_data_t* pRowA = NULL;
    matrix_data_t* pRowB = NULL;

    for (c = 0; c < cols; ++c) {
        for (r = 0; r < (int)(rows / 2); ++r) { /* explicit truncate */
            pRowA = data + r * cols;
            pRowB = data + cols * (rows - 1 - r);
            temp = pRowA[c];
            pRowA[c] = pRowB[c];
            pRowB[c] = temp;
        }
    }
}

/* Transpose NxM matrix to MxN matrix in O(n) time */
void transpose(const matrix_data_t* src, matrix_data_t* dst, int N, int M) {

    int i;
    for (i = 0; i<N*M; ++i) dst[(i%M)*N + (i / M)] = src[i];    /* one-liner version */

    /*
    expanded version of one-liner:  calculate XY based on array index, then convert that to YX array index
    int i,j,x,y;
    for (i = 0; i < N*M; ++i) {
    x = i % M;
    y = (int)(i / M);
    j = x * N + y;
    dst[j] = src[i];
    }
    */

    /*
    nested for loop version
    using ptr arithmetic to get proper row/column
    this is really just dst[col][row]=src[row][col]

    int r, c;

    for (r = 0; r < rows; ++r) {
        for (c = 0; c < cols; ++c) {
            (dst + c * rows)[r] = (src + r * cols)[c];
        }
    }
    */
}

/*
Transpose NxN matrix in place
*/
void transpose_inplace(matrix_data_t* data, int N ) {

    int r, c;
    matrix_data_t temp;

    for (r = 0; r < N; ++r) {
        for (c = r; c < N; ++c) { /*start at column=row*/
                                    /* using ptr arithmetic to get proper row/column */
                                    /* this is really just
                                    temp=dst[col][row];
                                    dst[col][row]=src[row][col];
                                    src[row][col]=temp;
                                    */
            temp = (data + c * N)[r];
            (data + c * N)[r] = (data + r * N)[c];
            (data + r * N)[c] = temp;
        }
    }
}

/*
Rotate 1D or 2D src matrix to dst matrix in a direction (90,180,-90)
Precondition:  src and dst are 2d matrices with dimensions src[rows][cols] and dst[cols][rows] or 1D pointers with logical rows/cols
*/
void rotate(int direction, const matrix_data_t* src, matrix_data_t* dst, int rows, int cols) {

    switch (direction) {
    case -90:
        transpose(src, dst, rows, cols);
        reverse_cols(dst, cols, rows);
        break;
    case 90:
        transpose(src, dst, rows, cols);
        reverse_rows(dst, cols, rows);
        break;
    case 180:
    case -180:
        /* bit copy to dst, use in-place reversals */
        memcpy(dst, src, rows*cols*sizeof(matrix_data_t));
        reverse_cols(dst, cols, rows);
        reverse_rows(dst, cols, rows);
        break;
    }
}

/*
Rotate array in a direction.
Array must be NxN 2D or 1D array with logical rows/cols
Direction can be (90,180,-90,-180)
*/
void rotate_inplace( int direction, matrix_data_t* data, int n) {

    switch (direction) {
    case -90:
        transpose_inplace(data, n);
        reverse_cols(data, n, n);
        break;
    case 90:
        transpose_inplace(data, n);
        reverse_rows(data, n, n);
        break;
    case 180:
    case -180:
        reverse_cols(data, n, n);
        reverse_rows(data, n, n);
        break;
    }
}

`