How do you flatten image coordinates into a 1D arr

Question

My source code is from Heterogeneous Computing with OpenCL Chapter 4 Basic OpenCL Examples > Image Rotation. The book leaves out several critical details.

My major problem is that I don't know how to initialize the array that I supply to their kernel (they don't tell you how). What I have is:

int W = inImage.width();
int H = inImage.height();
float *myImage = new float[W*H];
    for(int row = 0; row < H; row++)
        for(int col = 0; col < W; col++)
            myImage[row*W+col] = col;

which I supply to this kernel:

    __kernel void img_rotate(__global float* dest_data, __global float* src_data, int W, int H, float sinTheta, float cosTheta) 
{
    const int ix = get_global_id(0);
    const int iy = get_global_id(1);
    float x0 = W/2.0f;
    float y0 = H/2.0f;
    float xoff = ix-x0;
    float yoff = iy-y0;
    int xpos = (int)(xoff*cosTheta + yoff*sinTheta + x0);
    int ypos = (int)(yoff*cosTheta - xoff*sinTheta + y0);
    if(((int)xpos>=0) && ((int)xpos < W) && ((int)ypos>=0) && ((int)ypos<H))
    {
        dest_data[iy*W+ix] = src_data[ypos*W+xpos];
        //dest_data[iy*W+ix] = src_data[iy*W+ix];
    }
}

I'm having trouble finding the right value for theta too. An integer would be an appropriate value for theta, right?

float theta = 45; // 45 degrees, right?
float cos_theta = cos(theta);
float sin_theta = sin(theta);

Answer 1

When writing my OpenCL code, I always treat each kernel as reading a 3D set of data, regardless if the data is 1D, 2D, or 3D:

 __kernel void TestKernel(__global float *Data){
      k = get_global_id(0); //also z
      j = get_global_id(1); //also y
      i = get_global_id(2); //also x

      //Convert 3D to 1D
      int linear_coord = i + get_global_size(0)*j + get_global_size(0)*get_global_size(1)*k;

      //do stuff
 }

When doing the clEnqueueNDKernelRange(...), just set the dimension to be:

 int X = 500;
 int Y = 300;
 int Z = 1;

 size_t GlobalDim = {Z, Y, X};

This let's all of my kernels work easily in all dimensions.