#include <cuda_runtime.h>
#include <cufft.h>
#include <cuComplex.h>
#include "fft_correlate.h"

// Helper function for checking CUDA errors
#define CUDA_CHECK(call) \
do { \
    cudaError_t result = call; \
    if (result != cudaSuccess) { \
        fprintf(stderr, "CUDA error at %s:%d code=%d(%s) \"%s\" \n", \
        __FILE__, __LINE__, result, cudaGetErrorString(result), #call); \
        exit(EXIT_FAILURE); \
    } \
} while(0)

// CUDA kernel to fill the padded 3D array for ligand grid for FFT
__global__ void fill_padded_array_cuda(
    float *arr_l, float *padded_arr_l,
    int x, int y, int z,
    int pad_x, int pad_y, int pad_z
) {
    int i = blockIdx.x * blockDim.x + threadIdx.x;
    int j = blockIdx.y * blockDim.y + threadIdx.y;
    if (i < x && j < y) {
        float *padded_arr_l_ij = padded_arr_l + (pad_y * pad_z * i) + (pad_z * j);
        float *arr_l_ij = arr_l + (y * z * i) + z * j;
        for (int k = 0; k < z; ++k) {
            padded_arr_l_ij[k] = arr_l_ij[k];
        }
    }
}

// CUDA kernel to perform element-wise complex conjugate multiplication and scale
__global__ void complex_conj_mult_scale(
    cufftComplex *fft_r, cufftComplex *fft_l, int N_fft_points, float scale
) {
    int idx = blockIdx.x * blockDim.x + threadIdx.x;
    if (idx < N_fft_points) {
        cufftComplex a = fft_r[idx];
        cufftComplex b = fft_l[idx];
        // Perform complex conjugate multiplication and scale
        cufftComplex c;
        c.x = (a.x * b.x + a.y * b.y) * scale;
        c.y = (a.x * b.y - a.y * b.x) * scale;
        fft_l[idx] = c;
    }
}
// Main function to convert
// This is a pseudo-structure to guide the conversion process.
// It assumes the existence of CUDA kernels and proper memory allocation,
// data transfer, and cuFFT plan creation.
void fft_correlate_cuda(
    float *recep_arr, float *lig_arr,
    int nx, int ny, int nz,
    int nx_lig, int ny_lig, int nz_lig,
    int N_orientations,
    float *correlation_results
) {
    // Number of grid points
    size_t N_grid_points = nx * ny * nz;
    size_t N_lig_grid_points = nx_lig * ny_lig * nz_lig;

    // Number FFT coefficients (only half of the array is needed due to symmetry)
    size_t N_fft_points = nx * ny * (nz / 2 + 1); 
    // Allocate memory for FFTW plans and data
    cufftComplex *fft_r, *fft_l;
    // Assume all device memory allocations, cuFFT plans, and data transfers are done here

    // Launch kernel to fill padded array
    dim3 dimBlocks(32, 32);
    dim3 dimGrid(
        (N_lig_grid_points + dimBlocks.x - 1) / dimBlocks.x
    );
    fill_padded_array_cuda<<<dimBlocks, threadsPerBlock>>>(/* arguments */);

    // Execute forward FFTs using cuFFT
    cufftHandle* plan_fwd, plan_inv;

    // Launch kernel for complex conjugate multiplication and scaling
    int threads = 256; // Example thread count
    int blocks = (N_fft_points + threads - 1) / threads;
    complex_conj_mult_scale<<<blocks, threads>>>(/* arguments */);

    // Execute inverse FFTs and sum up results


    // Cleanup: deallocate device memory, destroy cuFFT plans
}