#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include "math_constants.h"

#include "ImageIO.h"

#include <iostream>
#include <ctime>

using namespace std;

#define N           512
#define BLOCKDIM    16

__global__ void rippleKernel(unsigned char* result, int w, int h, float waveLength);

int main(int argc, char** argv)
{
    unsigned char* result = new unsigned char[N*N*4];
    unsigned char* dev_result;

    cudaMalloc((void**)&dev_result, N*N*4 * sizeof(unsigned char));

    dim3 blockDim = dim3(BLOCKDIM, BLOCKDIM, 1);
    dim3 gridDim = dim3((N + BLOCKDIM - 1) / BLOCKDIM, (N + BLOCKDIM - 1) / BLOCKDIM, 1);

    rippleKernel << <gridDim, blockDim >> > (dev_result, N, N, 50);

    cudaMemcpy(result, dev_result, N*N*4 * sizeof(unsigned char), cudaMemcpyDeviceToHost);

    writeRGBImageToFile("image.png", result, N, N);

    return 0;
}

__global__ void rippleKernel(unsigned char* result, int w, int h, float waveLength)
{
    int x = blockDim.x *blockIdx.x + threadIdx.x;
    int y = blockDim.y *blockIdx.y + threadIdx.y;

    int tid = y*w + x;

    float dist = sqrtf((x - w / 2.0f)*(x - w / 2.0f) + (y-h/2.0f)*(y - h / 2.0f));
    float value = (cosf(dist / waveLength * CUDART_PI_F * 2)+1)*127;

    if (x < w && y < h)
    {
        result[tid * 4] = value;
        result[tid * 4 + 1] = value;
        result[tid * 4 + 2] = value;
		result[tid * 4 + 3] = 255;
	}

    return;
}