#include "stdafx.h"
#include "TBPImageAlgCls.h"
#include <QDateTime>
#include <QDebug>
#include <QString>
#include <cmath>
#include <QProgressDialog>
#include <QMessageBox>
#include "GPUTool.cuh"
#include "GPUTBPImage.cuh"
#include "ImageOperatorBase.h"

void CreatePixelXYZ(std::shared_ptr<EchoL0Dataset> echoL0ds, QString outPixelXYZPath)
{
	long bandwidth = echoL0ds->getBandwidth();
	double Rnear = echoL0ds->getNearRange();
	double Rfar = echoL0ds->getFarRange();
	double refRange = echoL0ds->getRefPhaseRange();
	double dx = LIGHTSPEED / 2.0 / bandwidth; // c/2b


	// 创建坐标系统
	long prfcount = echoL0ds->getPluseCount();
	long freqcount = echoL0ds->getPlusePoints();
	Eigen::MatrixXd gt = Eigen::MatrixXd::Zero(2, 3);
	gt(0, 0) = 0;
	gt(0, 1) = 1;
	gt(0, 2) = 0;
	gt(1, 0) = 0;
	gt(1, 1) = 0;
	gt(1, 2) = 1;
	gdalImage xyzRaster = CreategdalImage(outPixelXYZPath, prfcount, freqcount, 3, gt, QString(""), false, true,true,GDT_Float64);
	std::shared_ptr<double> antpos = echoL0ds->getAntPos();
	dx = (echoL0ds->getFarRange()-echoL0ds->getNearRange())/(echoL0ds->getPlusePoints()-1);
	Rnear = echoL0ds->getNearRange();
	double Rref = echoL0ds->getRefPhaseRange();
	double centerInc = echoL0ds->getCenterAngle()*d2r;
	long echocol = Memory1GB * 1.0 / 8 / 4 / prfcount * 6;
	qDebug() << "echocol:\t " << echocol ;
	echocol = echocol < 1 ?  1: echocol;


	std::shared_ptr<double>  Pxs((double*)mallocCUDAHost(sizeof(double)*prfcount), FreeCUDAHost);
	std::shared_ptr<double>  Pys((double*)mallocCUDAHost(sizeof(double) * prfcount), FreeCUDAHost);
	std::shared_ptr<double>  Pzs((double*)mallocCUDAHost(sizeof(double) * prfcount), FreeCUDAHost);
	std::shared_ptr<double>  AntDirectX((double*)mallocCUDAHost(sizeof(double) * prfcount), FreeCUDAHost);
	std::shared_ptr<double>  AntDirectY((double*)mallocCUDAHost(sizeof(double) * prfcount), FreeCUDAHost);
	std::shared_ptr<double>  AntDirectZ((double*)mallocCUDAHost(sizeof(double) * prfcount), FreeCUDAHost);

	{
		std::shared_ptr<double> antpos = echoL0ds->getAntPos();
		double time = 0;
		double Px = 0;
		double Py = 0;
		double Pz = 0;
		for (long i = 0; i < prfcount; i++) {
 
			Pxs.get()[i] = antpos.get()[i * 19 + 1]; // 卫星坐标
			Pys.get()[i] = antpos.get()[i * 19 + 2];
			Pzs.get()[i] = antpos.get()[i * 19 + 3];
			AntDirectX.get()[i] = antpos.get()[i * 19 + 13];// zero doppler
			AntDirectY.get()[i] = antpos.get()[i * 19 + 14];
			AntDirectZ.get()[i] = antpos.get()[i * 19 + 15];

			double NormAnt = std::sqrt(AntDirectX.get()[i] * AntDirectX.get()[i] + 
				AntDirectY.get()[i] * AntDirectY.get()[i] + 
				AntDirectZ.get()[i] * AntDirectZ.get()[i]);
			AntDirectX.get()[i] = AntDirectX.get()[i] / NormAnt;
			AntDirectY.get()[i] = AntDirectY.get()[i] / NormAnt;
			AntDirectZ.get()[i] = AntDirectZ.get()[i] / NormAnt;// 归一化
		}
		antpos.reset();
	}

	std::shared_ptr<double>  d_Pxs((double*)mallocCUDADevice(sizeof(double) * prfcount), FreeCUDADevice);
	std::shared_ptr<double>  d_Pys((double*)mallocCUDADevice(sizeof(double) * prfcount), FreeCUDADevice);
	std::shared_ptr<double>  d_Pzs((double*)mallocCUDADevice(sizeof(double) * prfcount), FreeCUDADevice);
	std::shared_ptr<double>  d_AntDirectX((double*)mallocCUDADevice(sizeof(double) * prfcount), FreeCUDADevice);
	std::shared_ptr<double>  d_AntDirectY((double*)mallocCUDADevice(sizeof(double) * prfcount), FreeCUDADevice);
	std::shared_ptr<double>  d_AntDirectZ((double*)mallocCUDADevice(sizeof(double) * prfcount), FreeCUDADevice);

	HostToDevice(Pxs.get(),		 d_Pxs.get(), sizeof(double) * prfcount);
	HostToDevice(Pys.get(),		 d_Pys.get(), sizeof(double) * prfcount);
	HostToDevice(Pzs.get(),		 d_Pzs.get(), sizeof(double) * prfcount);
	HostToDevice(AntDirectX.get(),		 d_AntDirectX.get(), sizeof(double) * prfcount);
	HostToDevice(AntDirectY.get(),		 d_AntDirectY.get(), sizeof(double) * prfcount);
	HostToDevice(AntDirectZ.get(),		 d_AntDirectZ.get(), sizeof(double) * prfcount);


	for (long startcolidx = 0; startcolidx < freqcount; startcolidx = startcolidx + echocol) {

		long tempechocol = echocol;
		if (startcolidx + tempechocol >= freqcount) {
			tempechocol = freqcount - startcolidx;
		}
		qDebug() << "\r[" << QDateTime::currentDateTime().toString("yyyy-MM-dd hh:mm:ss.zzz")  << "]  imgxyz :\t" << startcolidx << "\t-\t" << startcolidx + tempechocol << " / " << freqcount  ;

		std::shared_ptr<double> demx = readDataArr<double>(xyzRaster, 0, startcolidx, prfcount, tempechocol, 1, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
		std::shared_ptr<double> demy = readDataArr<double>(xyzRaster, 0, startcolidx, prfcount, tempechocol, 2, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
		std::shared_ptr<double> demz = readDataArr<double>(xyzRaster, 0, startcolidx, prfcount, tempechocol, 3, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
		
		std::shared_ptr<double> h_demx((double*)mallocCUDAHost(sizeof(double) * prfcount*tempechocol), FreeCUDAHost);
		std::shared_ptr<double> h_demy((double*)mallocCUDAHost(sizeof(double) * prfcount*tempechocol), FreeCUDAHost);
		std::shared_ptr<double> h_demz((double*)mallocCUDAHost(sizeof(double) * prfcount*tempechocol), FreeCUDAHost);

#pragma omp parallel for 
		for (long ii = 0; ii < prfcount; ii++) {
			for (long jj = 0; jj < tempechocol; jj++) {
				h_demx.get()[ii*tempechocol+jj]=demx.get()[ii*tempechocol+jj];
				h_demy.get()[ii*tempechocol+jj]=demy.get()[ii*tempechocol+jj];
				h_demz.get()[ii*tempechocol+jj]=demz.get()[ii*tempechocol+jj];
			}
		}

		std::shared_ptr<double> d_demx((double*)mallocCUDADevice(sizeof(double) * prfcount * tempechocol), FreeCUDADevice);
		std::shared_ptr<double> d_demy((double*)mallocCUDADevice(sizeof(double) * prfcount * tempechocol), FreeCUDADevice);
		std::shared_ptr<double> d_demz((double*)mallocCUDADevice(sizeof(double) * prfcount * tempechocol), FreeCUDADevice);

		HostToDevice(h_demx.get(), d_demx.get(), sizeof(double) * prfcount * tempechocol);
		HostToDevice(h_demy.get(), d_demy.get(), sizeof(double) * prfcount * tempechocol);
		HostToDevice(h_demz.get(), d_demz.get(), sizeof(double) * prfcount * tempechocol);


		TIMEBPCreateImageGrid(
			d_Pxs.get(), d_Pys.get(), d_Pzs.get(),
			d_AntDirectX.get(), d_AntDirectY.get(), d_AntDirectZ.get(),
			d_demx.get(), d_demy.get(), d_demz.get(),
			prfcount, tempechocol, 1000,
			Rnear+dx* startcolidx, dx, refRange // 更新最近修读
		);

		DeviceToHost(h_demx.get(), d_demx.get(), sizeof(double) * prfcount * tempechocol);
		DeviceToHost(h_demy.get(), d_demy.get(), sizeof(double) * prfcount * tempechocol);
		DeviceToHost(h_demz.get(), d_demz.get(), sizeof(double) * prfcount * tempechocol);

#pragma omp parallel for 
		for (long ii = 0; ii < prfcount; ii++) {
			for (long jj = 0; jj < tempechocol; jj++) {
				 demx.get()[ii * tempechocol + jj]=h_demx.get()[ii * tempechocol + jj] ;
				 demy.get()[ii * tempechocol + jj]=h_demy.get()[ii * tempechocol + jj] ;
				 demz.get()[ii * tempechocol + jj]=h_demz.get()[ii * tempechocol + jj] ;
			}
		}

		xyzRaster.saveImage(demx, 0, startcolidx,prfcount,tempechocol, 1);
		xyzRaster.saveImage(demy, 0, startcolidx,prfcount,tempechocol, 2);
		xyzRaster.saveImage(demz, 0, startcolidx,prfcount,tempechocol, 3);
	}
	
}

void TBPImageProcess(QString echofile, QString outImageFolder, QString imagePlanePath,long num_thread)
{
	std::shared_ptr<EchoL0Dataset> echoL0ds(new EchoL0Dataset);
	echoL0ds->Open(echofile);

	std::shared_ptr< SARSimulationImageL1Dataset> imagL1(new SARSimulationImageL1Dataset);
	imagL1->setCenterAngle(echoL0ds->getCenterAngle());
	imagL1->setCenterFreq(echoL0ds->getCenterFreq());
	imagL1->setNearRange(echoL0ds->getNearRange());
	imagL1->setRefRange((echoL0ds->getNearRange() + echoL0ds->getFarRange()) / 2);
	imagL1->setFarRange(echoL0ds->getFarRange());
	imagL1->setFs(echoL0ds->getFs());
	imagL1->setLookSide(echoL0ds->getLookSide());

	imagL1->OpenOrNew(outImageFolder, echoL0ds->getSimulationTaskName(), echoL0ds->getPluseCount(), echoL0ds->getPlusePoints());

	
	TBPImageAlgCls TBPimag;
	TBPimag.setEchoL0(echoL0ds);
	TBPimag.setImageL1(imagL1);
	TBPimag.setImagePlanePath(imagePlanePath);

	TBPimag.Process(num_thread);
}



void TBPImageAlgCls::setImagePlanePath(QString INimagePlanePath)
{
	this->imagePlanePath = INimagePlanePath;
}

QString TBPImageAlgCls::getImagePlanePath()
{
	return this->imagePlanePath;
}

void TBPImageAlgCls::setEchoL0(std::shared_ptr<EchoL0Dataset> inL0ds)
{
	this->L0ds = inL0ds;
}

void TBPImageAlgCls::setImageL1(std::shared_ptr<SARSimulationImageL1Dataset> inL1ds)
{
	this->L1ds = inL1ds;
}

std::shared_ptr<EchoL0Dataset> TBPImageAlgCls::getEchoL1()
{
	return  this->L0ds;
}

std::shared_ptr<SARSimulationImageL1Dataset> TBPImageAlgCls::getImageL0()
{
	return this->L1ds;
}

ErrorCode TBPImageAlgCls::Process(long num_thread)
{

	qDebug() << u8"开始成像";


	qDebug() << u8"创建成像平面的XYZ";
	QString outRasterXYZ = JoinPath(this->L1ds->getoutFolderPath(), this->L0ds->getSimulationTaskName() + "_xyz.bin");
	CreatePixelXYZ(this->L0ds, outRasterXYZ);
	this->outRasterXYZPath = outRasterXYZ;


		qDebug() << u8"频域回波-> 时域回波";
	this->TimeEchoDataPath = JoinPath(this->L1ds->getoutFolderPath(), this->L0ds->getSimulationTaskName() + "_Timeecho.bin");
	this->EchoFreqToTime();

	// 初始化Raster
	qDebug() << u8"初始化影像";
	long imageheight = this->L1ds->getrowCount();
	long imagewidth = this->L1ds->getcolCount();

	 
	long blokline = Memory1GB  / 8 / 4 / imageheight * 32;
	blokline = blokline < 1000 ? 1000 : blokline;

	long startline = 0;
	for (startline = 0; startline < imageheight; startline = startline + blokline) {
		long templine = blokline;
		if (startline + templine >= imageheight) {
			templine = imageheight - startline;
		}
		qDebug() << "\r[" << QDateTime::currentDateTime().toString("yyyy-MM-dd hh:mm:ss.zzz")  << "]  imgxyz :\t" << startline << "\t-\t" << startline + templine << " / " << imageheight  ;

		std::shared_ptr<std::complex<double>> imageRaster = this->L1ds->getImageRaster(startline, templine);

		for (long i = 0; i < templine; i++) {
			for (long j = 0; j < imagewidth; j++) {
				imageRaster.get()[i * imagewidth + j] = std::complex<double>(0,0);
			}
		}
		this->L1ds->saveImageRaster(imageRaster, startline,templine);
	}


	qDebug() << u8"频域回波-> 时域回波 结束";

	if (GPURUN) {
		return this->ProcessGPU();
	}
	else {
		QMessageBox::information(nullptr,u8"提示",u8"目前只支持显卡");
		return	ErrorCode::FAIL;
	}
	return ErrorCode::SUCCESS;
}

ErrorCode TBPImageAlgCls::ProcessGPU()
{
	// 常用参数
	long rowCount = this->L1ds->getrowCount();
	long colCount = this->L1ds->getcolCount();
	long pixelCount = rowCount * colCount;
	long PRFCount = this->L0ds->getPluseCount();
	long PlusePoints = this->L0ds->getPlusePoints();
	long bandwidth = this->L0ds->getBandwidth();

	double Rnear = this->L1ds->getNearRange();
	double Rfar = this->L1ds->getFarRange();
	double refRange = this->L0ds->getRefPhaseRange();
	double dx = LIGHTSPEED / 2.0 / bandwidth; // c/2b
	Rfar = Rnear + dx * (PlusePoints - 1); // 更新斜距距离


	float freq =  this->L1ds->getCenterFreq();
	double factorj = freq * 4 * M_PI / LIGHTSPEED  ;

	qDebug() << "------------------------------------------------";
	qDebug() << "TBP params:";
	qDebug() << "Rnear:\t" << Rnear;
	qDebug() << "Rfar:\t" << Rfar;
	qDebug() << "refRange:\t" << this->getEchoL1()->getRefPhaseRange();
	qDebug() << "dx:\t" << dx;
	qDebug() << "freq:\t" << freq;
	qDebug() << "rowCount:\t" << rowCount;
	qDebug() << "colCount:\t" << colCount;
	qDebug() << "PRFCount:\t" << PRFCount;
	qDebug() << "PlusePoints:\t" << PlusePoints;
	qDebug() << "bandwidth:\t" << bandwidth;
	
	// 反方向计算起始相位
	
	double deltaF = bandwidth / (PlusePoints - 1);
	double startfreq = freq - bandwidth / 2;
	
	double startlamda = LIGHTSPEED / startfreq;
	qDebug() << "deltaF:\t" << deltaF;


	std::shared_ptr<double>  Pxs (new double[this->L0ds->getPluseCount()],delArrPtr);
	std::shared_ptr<double>  Pys (new double[this->L0ds->getPluseCount()],delArrPtr);
	std::shared_ptr<double>  Pzs (new double[this->L0ds->getPluseCount()],delArrPtr);

	{
		std::shared_ptr<double> antpos = this->L0ds->getAntPos();
		double time = 0;
		double Px = 0;
		double Py = 0;
		double Pz = 0;
		for (long i = 0; i < rowCount; i++) {
			time = antpos.get()[i *19 + 0];
			Px = antpos.get()[i *19 + 1];
			Py = antpos.get()[i *19 + 2];
			Pz = antpos.get()[i *19 + 3];
			Pxs.get()[i] = Px;
			Pys.get()[i] = Py;
			Pzs.get()[i] = Pz;
		}
		antpos.reset();
	}




	// 计算成像的基本参数
	// 距离向分辨率
	double dr = sqrt(pow(Pxs.get()[2]- Pxs.get()[1],2)+pow(Pys.get()[2] - Pys.get()[1],2)+pow(Pzs.get()[2] - Pzs.get()[1],2));
	qDebug() << "-------  resolution ----------------------------------";
	qDebug() << "Range Resolution (m):\t" << dx ;
	qDebug() << "Cross Resolution (m):\t" << dr;
	qDebug() << "Range Range (m):\t" << dx*PlusePoints;
	qDebug() << "Cross Range (m):\t" << dr*PRFCount;
	qDebug() << "start Freq (Hz):\t" << startfreq;
	qDebug() << "start lamda (m):\t" << startlamda;
	qDebug() << "rowCount:\t" << rowCount;
	qDebug() << "colCount:\t" << colCount;
	qDebug() << "PRFCount:\t" << PRFCount;
	qDebug() << "PlusePoints:\t" << PlusePoints;
	qDebug() << "Rnear:\t" << Rnear;
	qDebug() << "Rfar:\t" << Rfar;
	qDebug() << "refRange:\t" << refRange;
	// 方位向分辨率

	long echoBlockline = Memory1GB  / 8 / 2 / PlusePoints * 2; //2GB
	echoBlockline = echoBlockline < 1 ? 1 : echoBlockline;

	long imageBlockline = Memory1GB  / 8 / 2 / colCount * 2; //2GB
	imageBlockline = imageBlockline < 1 ? 1 : imageBlockline;

	gdalImage imageXYZ(this->outRasterXYZPath);
	gdalImageComplex imagetimeimg(this->TimeEchoDataPath);

	long startimgrowid = 0;
	for (startimgrowid = 0; startimgrowid < rowCount; startimgrowid = startimgrowid + imageBlockline) {
		long tempimgBlockline = imageBlockline;
		if (startimgrowid + imageBlockline >= rowCount) {
			tempimgBlockline = rowCount - startimgrowid;
		}
		qDebug() << "\r image create Row Range  :\t"<<QString("[%1]").arg(startimgrowid*100.0/ rowCount)<< startimgrowid << "\t-\t" << startimgrowid + tempimgBlockline << "\t/\t" << rowCount;
		// 提取局部pixel x,y,z
		std::shared_ptr<double> img_x = readDataArr<double>(imageXYZ,startimgrowid,0,tempimgBlockline,colCount,1,GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
		std::shared_ptr<double> img_y = readDataArr<double>(imageXYZ,startimgrowid,0,tempimgBlockline,colCount,2,GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
		std::shared_ptr<double> img_z = readDataArr<double>(imageXYZ,startimgrowid,0,tempimgBlockline,colCount,3,GDALREADARRCOPYMETHOD::VARIABLEMETHOD);
		std::shared_ptr<std::complex<double>> imgArr = this->L1ds->getImageRaster(startimgrowid, tempimgBlockline);
		// 获取回波
		long startechoid = 0;
		long iffeechoLen = PlusePoints;
		for (long startechoid = 0; startechoid < PRFCount; startechoid = startechoid + echoBlockline) {
			long tempechoBlockline = echoBlockline;
			if (startechoid + tempechoBlockline >= PRFCount) {
				tempechoBlockline = PRFCount - startechoid;
			}
			std::shared_ptr<std::complex<double>> echoArr = readDataArrComplex < std::complex<double>>(imagetimeimg,startechoid,long(0), tempechoBlockline, iffeechoLen, 1, GDALREADARRCOPYMETHOD::VARIABLEMETHOD);//; this->L0ds->getEchoArr(startechoid, tempechoBlockline);
			std::shared_ptr<double> antpx(new double[tempechoBlockline],delArrPtr);
			std::shared_ptr<double> antpy(new double[tempechoBlockline], delArrPtr);
			std::shared_ptr<double> antpz(new double[tempechoBlockline], delArrPtr);
			
			for (long anti = 0; anti < tempechoBlockline; anti++) { // 天线坐标
				antpx.get()[anti] = Pxs.get()[anti + startechoid];
				antpy.get()[anti] = Pys.get()[anti + startechoid];
				antpz.get()[anti] = Pzs.get()[anti + startechoid];
			}


			TBPImageGPUAlg2(
				antpx, antpy, antpz, // 坐标
				img_x, img_y, img_z, // 图像坐标
				echoArr, // 回波
				imgArr,  // 图像
				startfreq, dx,
				Rnear, Rfar, refRange,
				tempimgBlockline, colCount, 
				tempechoBlockline, PlusePoints
				);
			qDebug() << QString(" image block PRF:[%1] \t").arg((startechoid + tempechoBlockline) * 100.0 / PRFCount)
				<< startechoid << "\t-\t" << startechoid + tempechoBlockline;
		}
		this->L1ds->saveImageRaster(imgArr, startimgrowid, tempimgBlockline);
	}
 
	qDebug() << "\r[" << QDateTime::currentDateTime().toString("yyyy-MM-dd hh:mm:ss.zzz")  << "] image writing:\t" << this->L1ds->getxmlFilePath();
	this->L1ds->saveToXml();
	return ErrorCode::SUCCESS;
}



void TBPImageGPUAlg2(std::shared_ptr<double> antPx, std::shared_ptr<double> antPy, std::shared_ptr<double> antPz,
	std::shared_ptr<double> img_x, std::shared_ptr<double> img_y, std::shared_ptr<double> img_z,
	std::shared_ptr<std::complex<double>> echoArr,
	std::shared_ptr<std::complex<double>> img_arr,
	double freq, double dx, double Rnear, double Rfar, double refRange,
	long rowcount, long colcount,
	long prfcount, long freqcount
)
{

	// 天线
	std::shared_ptr<double> h_antPx ((double*)mallocCUDAHost(sizeof(double) * prfcount),FreeCUDAHost); 
	std::shared_ptr<double> h_antPy ((double*)mallocCUDAHost(sizeof(double) * prfcount),FreeCUDAHost); 
	std::shared_ptr<double> h_antPz ((double*)mallocCUDAHost(sizeof(double) * prfcount),FreeCUDAHost);

	std::shared_ptr<double> d_antPx ((double*)mallocCUDADevice(sizeof(double) * prfcount),FreeCUDADevice);
	std::shared_ptr<double> d_antPy ((double*)mallocCUDADevice(sizeof(double) * prfcount),FreeCUDADevice);
	std::shared_ptr<double> d_antPz ((double*)mallocCUDADevice(sizeof(double) * prfcount),FreeCUDADevice);
	// 网格坐标
	std::shared_ptr<double> h_imgx((double*)mallocCUDAHost(sizeof(double) * rowcount * colcount),FreeCUDAHost);
	std::shared_ptr<double> h_imgy((double*)mallocCUDAHost(sizeof(double) * rowcount * colcount),FreeCUDAHost);
	std::shared_ptr<double> h_imgz((double*)mallocCUDAHost(sizeof(double) * rowcount * colcount),FreeCUDAHost);

	std::shared_ptr<double> d_imgx ((double*)mallocCUDADevice(sizeof(double) * rowcount * colcount),FreeCUDADevice);
	std::shared_ptr<double> d_imgy ((double*)mallocCUDADevice(sizeof(double) * rowcount * colcount),FreeCUDADevice);
	std::shared_ptr<double> d_imgz ((double*)mallocCUDADevice(sizeof(double) * rowcount * colcount),FreeCUDADevice);
 
	// 回波范围
	std::shared_ptr<cuComplex> h_echoArr((cuComplex*)mallocCUDAHost(sizeof(cuComplex) * prfcount * freqcount), FreeCUDAHost);
	std::shared_ptr<cuComplex> d_echoArr((cuComplex*)mallocCUDADevice(sizeof(cuComplex) * prfcount * freqcount), FreeCUDADevice);
	
	// 成像结果
	std::shared_ptr<cuComplex> h_imgArr((cuComplex*)mallocCUDAHost(sizeof(cuComplex) * rowcount * colcount), FreeCUDAHost);
	std::shared_ptr<cuComplex> d_imgArr((cuComplex*)mallocCUDADevice(sizeof(cuComplex) * rowcount * colcount), FreeCUDADevice);

#pragma omp parallel for
	for (long i = 0; i < prfcount; i++) {
		for (long j = 0; j < freqcount; j++) {
			h_echoArr.get()[i * freqcount + j] = make_cuComplex(echoArr.get()[i * freqcount + j].real(),
				echoArr.get()[i * freqcount + j].imag());
		}
	}

	// 天线位置
	for (long i = 0; i < prfcount; i++) {
		h_antPx.get()[i] = antPx.get()[i];
		h_antPy.get()[i] = antPy.get()[i];
		h_antPz.get()[i] = antPz.get()[i];
	}

#pragma omp parallel for
	for (long i = 0; i < rowcount; i++) {
		for (long j = 0; j < colcount; j++) {
			h_imgx.get()[i * colcount + j] = img_x.get()[i * colcount + j];
			h_imgy.get()[i * colcount + j] = img_y.get()[i * colcount + j];
			h_imgz.get()[i * colcount + j] = img_z.get()[i * colcount + j];
		}
	}

#pragma omp parallel for
	for (long i = 0; i < rowcount; i++) {
		for (long j = 0; j < colcount; j++) {
			h_imgArr.get()[i * colcount + j].x = img_arr.get()[i * colcount + j].real();
			h_imgArr.get()[i * colcount + j].y = img_arr.get()[i * colcount + j].imag();
		}
	}
	HostToDevice(h_imgArr.get(), d_imgArr.get(), sizeof(cuComplex) * rowcount * colcount);
	HostToDevice(h_echoArr.get(), d_echoArr.get(), sizeof(cuComplex) * prfcount * freqcount);
	HostToDevice(h_antPx.get(), d_antPx.get(), sizeof(double) * prfcount);
	HostToDevice(h_antPy.get(), d_antPy.get(), sizeof(double) * prfcount);
	HostToDevice(h_antPz.get(), d_antPz.get(), sizeof(double) * prfcount);

	HostToDevice(h_imgx.get(), d_imgx.get(), sizeof(double) * rowcount * colcount);
	HostToDevice(h_imgy.get(), d_imgy.get(), sizeof(double) * rowcount * colcount);
	HostToDevice(h_imgz.get(), d_imgz.get(), sizeof(double) * rowcount * colcount);


	// 直接使用
	double startlamda = LIGHTSPEED / freq;
 
	TimeBPImage(
		d_antPx.get(), d_antPy.get(), d_antPz.get(),
		d_imgx.get(), d_imgy.get(), d_imgz.get(),
		d_echoArr.get(), prfcount, freqcount,
		d_imgArr.get(), rowcount, colcount,
		startlamda, Rnear, dx, refRange,Rfar
	);

	// Device -> Host
	DeviceToHost(h_imgArr.get(), d_imgArr.get(), sizeof(cuComplex)* rowcount* colcount);
 


#pragma omp parallel for
	for (long i = 0; i < rowcount; i++) {
		for (long j = 0; j < colcount; j++) {
			img_arr.get()[i * colcount + j] = std::complex<double>(h_imgArr.get()[i * colcount + j].x, h_imgArr.get()[i * colcount + j].y);
		}
	}

 

}


void TBPImageAlgCls::setGPU(bool flag)
{
	this->GPURUN = flag;
}

bool TBPImageAlgCls::getGPU( )
{
	return this->GPURUN;
}

void TBPImageAlgCls::EchoFreqToTime()
{
	// 读取数据

	long PRFCount = this->L0ds->getPluseCount();
	long inColCount = this->L0ds->getPlusePoints();
	long outColCount = inColCount;// nextpow2(inColCount);
	this->TimeEchoRowCount = PRFCount;
	this->TimeEchoColCount = outColCount;
	qDebug() << "IFFT : " << this->TimeEchoDataPath;
	qDebug() << "PRF Count:\t" << PRFCount;
	qDebug() << "inColCount:\t" << inColCount;
	qDebug() << "outColCount:\t" << outColCount;
	// 创建二进制文件
	gdalImageComplex outTimeEchoImg = CreategdalImageComplexNoProj(this->TimeEchoDataPath, this->TimeEchoRowCount, this->TimeEchoColCount, 1);

	// 分块
	long echoBlockline = Memory1GB / 8 / 2 / outColCount * 3; //1GB
	echoBlockline = echoBlockline < 1 ? 1 : echoBlockline;


	long startechoid = 0;
	for (long startechoid = 0; startechoid < PRFCount; startechoid = startechoid + echoBlockline) {

		long tempechoBlockline = echoBlockline;
		if (startechoid + tempechoBlockline >= PRFCount) {
			tempechoBlockline = PRFCount - startechoid;
		}
		std::shared_ptr<std::complex<double>> echoArr = this->L0ds->getEchoArr(startechoid, tempechoBlockline);
		std::shared_ptr<std::complex<double>> IFFTArr = outTimeEchoImg.getDataComplexSharePtr(startechoid, 0, tempechoBlockline, outColCount, 1);

		std::shared_ptr<cuComplex> host_echoArr((cuComplex*)mallocCUDAHost(sizeof(cuComplex) * tempechoBlockline * outColCount), FreeCUDAHost);
		std::shared_ptr<cuComplex> host_IFFTechoArr((cuComplex*)mallocCUDAHost(sizeof(cuComplex) * tempechoBlockline * outColCount), FreeCUDAHost);

		memset(host_echoArr.get(), 0, sizeof(cuComplex) * tempechoBlockline * outColCount);
#pragma omp parallel for
		for (long ii = 0; ii < tempechoBlockline; ii++) {
			for (long jj = 0; jj < inColCount; jj++) {
				host_echoArr.get()[ii * outColCount + jj] = make_cuComplex(echoArr.get()[ii * inColCount + jj].real(), echoArr.get()[ii * inColCount + jj].imag());
			}
		}
#pragma omp parallel for
		for (long ii = 0; ii < tempechoBlockline * outColCount; ii++) {
			host_IFFTechoArr.get()[ii] = make_cuComplex(0, 0);
		}

		std::shared_ptr<cuComplex> device_echoArr((cuComplex*)mallocCUDADevice(sizeof(cuComplex) * tempechoBlockline * inColCount), FreeCUDADevice);
		std::shared_ptr<cuComplex> device_IFFTechoArr((cuComplex*)mallocCUDADevice(sizeof(cuComplex) * tempechoBlockline * outColCount), FreeCUDADevice);

		HostToDevice(host_echoArr.get(), device_echoArr.get(), sizeof(cuComplex) * tempechoBlockline * inColCount);
		HostToDevice(host_IFFTechoArr.get(), device_IFFTechoArr.get(), sizeof(cuComplex) * tempechoBlockline * outColCount);
		CUDAIFFT(device_echoArr.get(), device_IFFTechoArr.get(), tempechoBlockline, outColCount, outColCount);

		FFTShift1D(device_IFFTechoArr.get(), tempechoBlockline, outColCount);

		DeviceToHost(host_IFFTechoArr.get(), device_IFFTechoArr.get(), sizeof(cuComplex) * tempechoBlockline * outColCount);

#pragma omp parallel for
		for (long ii = 0; ii < tempechoBlockline; ii++) {
			for (long jj = 0; jj < outColCount; jj++) {
				IFFTArr.get()[ii * outColCount + jj] = std::complex<double>(host_IFFTechoArr.get()[ii * outColCount + jj].x, host_IFFTechoArr.get()[ii * outColCount + jj].y);
				//IFFTArr.get()[ii * outColCount + jj] = std::complex<double>(host_echoArr.get()[ii * outColCount + jj].x, host_echoArr.get()[ii * outColCount + jj].y);
			}
		}

		outTimeEchoImg.saveImage(IFFTArr, startechoid, 0, tempechoBlockline, outColCount, 1);

		qDebug() << QString(" image block PRF:[%1] \t").arg((startechoid + tempechoBlockline) * 100.0 / PRFCount)
			<< startechoid << "\t-\t" << startechoid + tempechoBlockline;
	}

	return;


}