//============================================================// COOOL           version 1.1           ---     Nov,  1995//   Center for Wave Phenomena, Colorado School of Mines//============================================================////   This code is part of a preliminary release of COOOL (CWP// Object-Oriented Optimization Library) and associated class // libraries. //// The COOOL library is a free software. You can do anything you want// with it including make a fortune.  However, neither the authors,// the Center for Wave Phenomena, nor anyone else you can think of// makes any guarantees about anything in this package or any aspect// of its functionality.//// Since you've got the source code you can also modify the// library to suit your own purposes. We would appreciate it // if the headers that identify the authors are kept in the // source code.////=============================// author:  H. Lydia Deng, 03/14/94// derived class from CGLS, the preconditioned CGLS//=============================#include <PreCGLS.hh>PreconditionedCGLS::PreconditionedCGLS(int n, LinearForward* p,  Vector<double>* data, int it, double eps): LSConjugateGradient(n, p,data,it,eps){    int	size	=	p->dataSize();    weight	=	new DiagMatrix<double>(size);}PreconditionedCGLS::PreconditionedCGLS(int n, LinearForward* p,  Vector<double>* data, int it, double eps, int verb): LSConjugateGradient(n, p,data,it,eps,verb){    int	size	=	p->dataSize();    weight	=	new DiagMatrix<double>(size);}PreconditionedCGLS::~PreconditionedCGLS()	{ delete weight;}		// Preconditioned Least square Conjugate gradient methodModel<double> PreconditionedCGLS::optimizer(Model<double>& model){    dataError[0]	=	((MisFitFcn*)fp)->updateError(model);    Vector<double>  temp(dataError->size());    temp = dataError[0]*weight[0];    LSConjugateGradient::getModelError(temp);    search[0]	=	modelError[0];    double value 	=	fp->performance(model);    if (isVerbose) cerr << "the current residue: "<< value << endl;    QuadraticOptima::appendResidue(value);    while(fp->iterations() < iterMax && residue->last() >tol) {	LSConjugateGradient::upDating();	temp = weight[0]*dataError[0];	LSConjugateGradient::getModelError(temp);	model	=	model.update(1,alpha,search[0]);	LSConjugateGradient::conjugateDirection();	value 	=	fp->performance(model);	if (isVerbose) cerr << "the current residue: "<< value << endl;	Optima::appendResidue(value);    }    return(model);}Model<long> PreconditionedCGLS::optimizer(Model<long>& model){    Model<double> mtemp(model);    mtemp = optimizer(mtemp);    Model<long> optm(mtemp);    return optm;}