precgls.cc

COOOL：CWP面向对象最优化库（CWP Object Oriented Optimization Library） COOOL是C++类的一个集合

//============================================================
// 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 method
Model<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;
}