#include <iostream>
#include <memory>
#include <cmath>
#include <complex>
#include <device_launch_parameters.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <cuComplex.h>
 
#include "BaseConstVariable.h"
#include "GPUTool.cuh"

#ifdef __CUDANVCC___

#define CUDAMEMORY Memory1MB*100

#define LAMP_CUDA_PI 3.141592653589793238462643383279



// 定义参数
 __device__  cuComplex cuCexpf(cuComplex x)
{
	float factor = exp(x.x);
	return make_cuComplex(factor * cos(x.y), factor * sin(x.y));
}
 
__global__ void CUDA_DistanceAB(float* Ax, float* Ay, float* Az, float* Bx, float* By, float* Bz,float *R, long len) {
	long  idx = blockIdx.x * blockDim.x + threadIdx.x;
	if (idx < len) {
		R[idx] = sqrtf(powf(Ax[idx]-Bx[idx], 2) + powf(Ay[idx] - By[idx], 2) + powf(Az[idx] - Bz[idx], 2));
	}
}

__global__ void CUDA_B_DistanceA(float* Ax, float* Ay, float* Az, float Bx, float By, float Bz, float* R, long len) {
	long  idx = blockIdx.x * blockDim.x + threadIdx.x;
	if (idx < len) {
		R[idx] = sqrtf(powf(Ax[idx] - Bx, 2) + powf(Ay[idx] - By, 2) + powf(Az[idx] - Bz, 2));
	}
}

__global__ void CUDA_make_VectorA_B(float sX, float sY, float sZ, float* tX, float* tY, float* tZ, float* RstX, float* RstY, float* RstZ, long len) {
	long  idx = blockIdx.x * blockDim.x + threadIdx.x;
	if (idx < len) {
		RstX[idx] = sX - tX[idx];
		RstY[idx] = sY - tY[idx];
		RstZ[idx] = sZ - tZ[idx];
	}
}
 
__global__ void CUDA_Norm_Vector(float* Vx, float* Vy, float* Vz,float *R, long len) {
	long  idx = blockIdx.x * blockDim.x + threadIdx.x;
	if (idx < len) {
		R[idx] = sqrtf(powf(Vx[idx],2)+powf(Vy[idx],2)+powf(Vz[idx], 2));
	}
}

__global__ void CUDA_cosAngle_VA_AB(float* Ax, float* Ay, float* Az, float* Bx, float* By, float* Bz, float* anglecos,long len) {
	long  idx = blockIdx.x * blockDim.x + threadIdx.x;
	if (idx < len) {
		float tAx = Ax[idx];
		float tAy = Ay[idx];
		float tAz = Az[idx];
		float tBx = Bx[idx];
		float tBy = By[idx];
		float tBz = Bz[idx];
		float AR = sqrtf(powf(tAx,2) + powf(tAy,2) + powf(tAz,2));
		float BR = sqrtf(powf(tBx,2) + powf(tBy,2) + powf(tBz,2));
		float dotAB = tAx * tBx + tAy * tBy + tAz * tBz;
		float result =acosf( dotAB / (AR * BR));
		anglecos[idx] = result;
	}
}

__global__ void CUDA_SatelliteAntDirectNormal(float* RstX,float* RstY,float* RstZ,
	float  antXaxisX,float  antXaxisY,float  antXaxisZ,
	float  antYaxisX,float  antYaxisY,float  antYaxisZ,
	float  antZaxisX,float  antZaxisY,float  antZaxisZ,
	float  antDirectX,float  antDirectY,float  antDirectZ,
	float* thetaAnt,float* phiAnt
	, long len) {
	long  idx = blockIdx.x * blockDim.x + threadIdx.x;
	if (idx < len) {
		float Xst = -1*RstX[idx]; // 卫星 -->  地面
		float Yst = -1*RstY[idx];
		float Zst = -1*RstZ[idx];
		float AntXaxisX=antXaxisX ;
		float AntXaxisY=antXaxisY ;
		float AntXaxisZ=antXaxisZ ;
		float AntYaxisX=antYaxisX ;
		float AntYaxisY=antYaxisY ;
		float AntYaxisZ=antYaxisZ ;
		float AntZaxisX=antZaxisX ;
		float AntZaxisY=antZaxisY ;
		float AntZaxisZ=antZaxisZ ;
		// 天线指向在天线坐标系下的值
		float Xant = (Xst * (AntYaxisY * AntZaxisZ - AntYaxisZ * AntZaxisY) + Xst * ( AntXaxisZ *  AntZaxisY -  AntXaxisY *  AntZaxisZ) +  Xst * ( AntXaxisY *  AntYaxisZ -  AntXaxisZ * AntYaxisY)) / ( AntXaxisX * ( AntYaxisY *  AntZaxisZ - AntZaxisY *  AntYaxisZ) -  AntYaxisX * ( AntXaxisY *  AntZaxisZ -  AntXaxisZ *  AntZaxisY) +  AntZaxisX * ( AntXaxisY *  AntYaxisZ -  AntXaxisZ * AntYaxisY));
		float Yant = (Yst * (AntYaxisZ * AntZaxisX - AntYaxisX * AntZaxisZ) + Yst * ( AntXaxisX *  AntZaxisZ -  AntXaxisZ *  AntZaxisX) +  Yst * ( AntYaxisX *  AntXaxisZ -  AntXaxisX * AntYaxisZ)) / ( AntXaxisX * ( AntYaxisY *  AntZaxisZ - AntZaxisY *  AntYaxisZ) -  AntYaxisX * ( AntXaxisY *  AntZaxisZ -  AntXaxisZ *  AntZaxisY) +  AntZaxisX * ( AntXaxisY *  AntYaxisZ -  AntXaxisZ * AntYaxisY));
		float Zant = (Zst * (AntYaxisX * AntZaxisY - AntYaxisY * AntZaxisX) + Zst * ( AntXaxisY *  AntZaxisX -  AntXaxisX *  AntZaxisY) +  Zst * ( AntXaxisX *  AntYaxisY -  AntYaxisX * AntXaxisY)) / ( AntXaxisX * ( AntYaxisY *  AntZaxisZ - AntZaxisY *  AntYaxisZ) -  AntYaxisX * ( AntXaxisY *  AntZaxisZ -  AntXaxisZ *  AntZaxisY) +  AntZaxisX * ( AntXaxisY *  AntYaxisZ -  AntXaxisZ * AntYaxisY));
		// 计算theta 与 phi
		float Norm =  sqrtf(Xant *  Xant +  Yant * Yant +  Zant *  Zant); // 计算 pho
		float ThetaAnt  = acosf(Zant / Norm); // theta 与 Z轴的夹角
		float YsinTheta = Yant / sinf(ThetaAnt);
		float PhiAnt  = (YsinTheta/abs(YsinTheta)) * acosf( Xant / (Norm *  sinf(ThetaAnt)));
		thetaAnt[idx] = ThetaAnt;
		phiAnt[idx] = PhiAnt;
	}
}


__global__ void CUDA_calculationEcho(float* sigma0, float* TransAnt, float* ReciveAnt,
	float* localangle, float* R,float* slopeangle,
	float nearRange, float Fs,float Pt,float lamda,long FreqIDmax,
	cuComplex* echoArr , long* FreqID,
	long len) {
	long  idx = blockIdx.x * blockDim.x + threadIdx.x;
	if (idx < len) {
		float r = R[idx];
		float amp = Pt * TransAnt[idx] * ReciveAnt[idx];
		amp= amp * sigma0[idx]; 
		amp = amp / (powf(4* LAMP_CUDA_PI,2)*powf(r,4)); // 反射强度

		// 处理相位
		float phi = (-4 * LAMP_CUDA_PI / lamda) * r;
		cuComplex echophi =  make_cuComplex(0, phi) ;
		cuComplex echophiexp = cuCexpf(echophi);
		
		float timeR = 2 * (r - nearRange) / LIGHTSPEED * Fs;
		long timeID = floorf(timeR);
		if (timeID < 0 || timeID >= FreqIDmax) {
			timeID = 0;
			amp = 0;
		}
 
		cuComplex echo;  
		echo.x = echophiexp.x * amp;
		echo.y = echophiexp.y * amp;


		echoArr[idx] = echo;
 
	}
}



//错误提示
void checkCudaError(cudaError_t err, const char* msg) {
	if (err != cudaSuccess) {
		std::cerr << "CUDA error: " << msg << " (" << cudaGetErrorString(err) << ")" << std::endl;
		exit(EXIT_FAILURE);
	}

}
 
// 主机参数内存声明
extern "C"  void mallocCUDAHost(void* ptr, long memsize) {
	cudaMallocHost(&ptr, memsize);
}

// 主机参数内存释放
extern "C"  void FreeCUDAHost(void* ptr) {
	cudaFreeHost(ptr);
}

// GPU参数内存声明
extern "C" void mallocCUDADevice(void* ptr, long memsize) {
	cudaMalloc(&ptr, memsize);
}

// GPU参数内存释放
extern "C" void FreeCUDADevice(void* ptr) {
	cudaFree(ptr);
}

// GPU 内存数据转移
extern "C" void HostToDevice(void* hostptr, void* deviceptr, long memsize) {
	cudaMemcpy(deviceptr, hostptr, memsize, cudaMemcpyHostToDevice);
}

extern "C" void DeviceToHost(void* hostptr, void* deviceptr, long memsize) {
	cudaMemcpy(hostptr, deviceptr, memsize, cudaMemcpyDeviceToHost);
}



extern "C" void distanceAB(float* Ax, float* Ay, float* Az, float* Bx, float* By, float* Bz, float* R,long len) {
	// 设置 CUDA 核函数的网格和块的尺寸
	int blockSize = 256; // 每个块的线程数
	int numBlocks = (len + blockSize - 1) / blockSize; // 根据 pixelcount 计算网格大小
	// 调用 CUDA 核函数
	CUDA_DistanceAB << <blockSize, numBlocks >> > ( Ax,  Ay,   Az,  Bx, By,   Bz, R, len);
}

extern "C" void BdistanceAs(float* Ax, float* Ay, float* Az, float Bx, float By, float Bz, float* R, long len) {
	// 设置 CUDA 核函数的网格和块的尺寸
	int blockSize = 256; // 每个块的线程数
	int numBlocks = (len + blockSize - 1) / blockSize; // 根据 pixelcount 计算网格大小
	// 调用 CUDA 核函数
	CUDA_B_DistanceA << <blockSize, numBlocks >> > (Ax, Ay, Az, Bx, By, Bz, R, len);
	cudaDeviceSynchronize();
}

extern "C" void make_VectorA_B(float sX, float sY, float sZ, float* tX, float* tY, float* tZ, float* RstX, float* RstY, float* RstZ, long len) {
	// 设置 CUDA 核函数的网格和块的尺寸
	int blockSize = 256; // 每个块的线程数
	int numBlocks = (len + blockSize - 1) / blockSize; // 根据 pixelcount 计算网格大小
	// 调用 CUDA 核函数
	CUDA_make_VectorA_B << <blockSize, numBlocks >> > (sX,  sY,  sZ,tX, tY,  tZ, RstX,RstY,  RstZ,  len);
	cudaDeviceSynchronize();
}

extern "C" void Norm_Vector(float* Vx, float* Vy, float* Vz, float* R, long len) {
	// 设置 CUDA 核函数的网格和块的尺寸
	int blockSize = 256; // 每个块的线程数
	int numBlocks = (len + blockSize - 1) / blockSize; // 根据 pixelcount 计算网格大小
	// 调用 CUDA 核函数
	CUDA_Norm_Vector << <blockSize, numBlocks >> > (Vx,Vy,Vz,R, len);
	cudaDeviceSynchronize();
}

extern "C" void cosAngle_VA_AB(float* Ax, float* Ay, float* Az, float* Bx, float* By, float* Bz, float* anglecos, long len) {
	int blockSize = 256; // 每个块的线程数
	int numBlocks = (len + blockSize - 1) / blockSize; // 根据 pixelcount 计算网格大小
	// 调用 CUDA 核函数
	CUDA_cosAngle_VA_AB << <blockSize, numBlocks >> > (Ax, Ay, Az, Bx, By, Bz, anglecos, len);
	cudaDeviceSynchronize();
}
 
extern "C" void SatelliteAntDirectNormal(float* RstX, float* RstY, float* RstZ,
	float  antXaxisX, float  antXaxisY, float  antXaxisZ,
	float  antYaxisX, float  antYaxisY, float  antYaxisZ,
	float  antZaxisX, float  antZaxisY, float  antZaxisZ,
	float  antDirectX, float  antDirectY, float  antDirectZ,
	float* thetaAnt, float* phiAnt
	, long len) {

	int blockSize = 256; // 每个块的线程数
	int numBlocks = (len + blockSize - 1) / blockSize; // 根据 pixelcount 计算网格大小
	// 调用 CUDA 核函数
	CUDA_SatelliteAntDirectNormal << <blockSize, numBlocks >> > ( RstX, RstY,  RstZ,
			 antXaxisX,  antXaxisY,  antXaxisZ,
			 antYaxisX,  antYaxisY,  antYaxisZ,
			 antZaxisX,  antZaxisY,  antZaxisZ,
			 antDirectX, antDirectY,   antDirectZ,
			 thetaAnt,  phiAnt
			,  len);
	cudaDeviceSynchronize();

 }



extern "C" void calculationEcho(float* sigma0,float* TransAnt,float* ReciveAnt,
	float* localangle,float* R, float* slopeangle,
	float nearRange,float Fs,  float pt, float lamda, long FreqIDmax,
	cuComplex* echoAmp,long* FreqID,
	long len)
{
	int blockSize = 256; // 每个块的线程数
	int numBlocks = (len + blockSize - 1) / blockSize; // 根据 pixelcount 计算网格大小
	// 调用 CUDA 核函数
	CUDA_calculationEcho << <blockSize, numBlocks >> > (  sigma0, TransAnt,ReciveAnt,
		localangle, R, slopeangle,
		nearRange, Fs, pt, lamda, FreqIDmax,
		echoAmp, FreqID,
		len);
	cudaDeviceSynchronize();
 
}






#endif