//! Solve least square problem using numerix solver
public Vector perform(ref LeastSquareProblem lsProblem)
{
double eps = accuracy_;
// wrap the least square problem in an optimization function
LeastSquareFunction lsf = new LeastSquareFunction(lsProblem);
// define optimization problem
Problem P = new Problem(lsf, c_, initialValue_);
// minimize
EndCriteria ec = new EndCriteria(maxIterations_, Math.Min(maxIterations_ / 2, 100), eps, eps, eps);
exitFlag_ = (int)om_.minimize(P, ec);
results_ = P.currentValue();
resnorm_ = P.functionValue();
bestAccuracy_ = P.functionValue();
return(results_);
}
//! Default constructor
public LeastSquareFunction(LeastSquareProblem lsp)
{
lsp_ = lsp;
}
//! Default constructor
public LeastSquareFunction(LeastSquareProblem lsp)
{
lsp_ = lsp;
}
//! Solve least square problem using numerix solver
public Vector perform(ref LeastSquareProblem lsProblem)
{
double eps = accuracy_;
// wrap the least square problem in an optimization function
LeastSquareFunction lsf = new LeastSquareFunction(lsProblem);
// define optimization problem
Problem P = new Problem(lsf, c_, initialValue_);
// minimize
EndCriteria ec = new EndCriteria(maxIterations_, Math.Min((int)(maxIterations_ / 2), (int)(100)), eps, eps, eps);
exitFlag_ = (int)om_.minimize(P, ec);
// summarize results of minimization
// nbIterations_ = om_->iterationNumber();
results_ = P.currentValue();
resnorm_ = P.functionValue();
bestAccuracy_ = P.functionValue();
return results_;
}