gsGradientMethod.h

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#pragma once
 
#include <gsSolver/gsIterativeSolver.h>
 
namespace gismo
{
 
template<class T = real_t>
class gsGradientMethod : public gsIterativeSolver<T>
{
public:
    typedef gsIterativeSolver<T> Base;
 
    typedef gsMatrix<T>  VectorType;
 
    typedef typename Base::LinOpPtr LinOpPtr;
 
    typedef memory::shared_ptr<gsGradientMethod> Ptr;
    typedef memory::unique_ptr<gsGradientMethod> uPtr;
 
    template< typename OperatorType >
    explicit gsGradientMethod( const OperatorType& mat,
                               const LinOpPtr& precond = LinOpPtr())
    : Base(mat, precond), m_adapt_step_size(true), m_step_size(0) {}
 
    template< typename OperatorType >
    explicit gsGradientMethod( const OperatorType& mat,
                               const LinOpPtr& precond,
                               T step_size )
    : Base(mat, precond), m_adapt_step_size(false), m_step_size(step_size) {}
 
    template< typename OperatorType >
    static uPtr make( const OperatorType& mat,
                      const LinOpPtr& precond = LinOpPtr())
    { return uPtr( new gsGradientMethod(mat, precond) ); }
 
    template< typename OperatorType >
    static uPtr make( const OperatorType& mat,
                      const LinOpPtr& precond,
                      T step_size )
    { return uPtr( new gsGradientMethod(mat, precond, step_size) ); }
 
    bool adaptiveStepSize() const { return m_adapt_step_size;                           }
 
    T stepSize() const            { return m_step_size;                                 }
 
    void setAdaptiveStepSize()    { m_adapt_step_size = true;  m_step_size = 0;         }
 
    void setStepSize(T step_size) { m_adapt_step_size = false; m_step_size = (gsOptionList::Real)step_size; }
 
    static gsOptionList defaultOptions()
    {
        gsOptionList opt = Base::defaultOptions();
        opt.addSwitch("AdaptiveStepSize", "Adaptive step sizes (to minimize residual)", true );
        opt.addReal  ("StepSize", "Step size (requires AdaptiveStepSize to be false)" , 0    );
        return opt;
    }
 
    gsGradientMethod& setOptions(const gsOptionList & opt)
    {
        Base::setOptions(opt);
        m_adapt_step_size = opt.askSwitch("AdaptiveStepSize", m_adapt_step_size);
        m_step_size       = opt.askReal  ("StepSize",         m_step_size      );
        if (m_adapt_step_size) m_step_size = 0; // for consistency of output, see above
        return *this;
    }
 
    bool initIteration( const VectorType& rhs, VectorType& x );
    bool step( VectorType& x );
 
    std::ostream &print(std::ostream &os) const
    {
        os << "gsGradientMethod\n";
        return os;
    }
 
private:
    using Base::m_mat;
    using Base::m_precond;
    using Base::m_max_iters;
    using Base::m_tol;
    using Base::m_num_iter;
    using Base::m_rhs_norm;
    using Base::m_error;
 
    VectorType m_res;
    VectorType m_tmp;
    VectorType m_update;
    bool m_adapt_step_size;
    gsOptionList::Real m_step_size;
 
};
 
} // namespace gismo
 
#ifndef GISMO_BUILD_LIB
#include GISMO_HPP_HEADER(gsGradientMethod.hpp)
#endif