gsStaticBase.h

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#include <typeinfo>
 
#include <gsCore/gsLinearAlgebra.h>
#ifdef gsSpectra_ENABLED
#include <gsSpectra/gsSpectra.h>
#endif
#include <gsIO/gsOptionList.h>
#include <gsStructuralAnalysis/src/gsStructuralAnalysisTools/gsStructuralAnalysisTypes.h>
 
#pragma once
 
 
namespace gismo
{
 
template <class T>
class gsStaticBase
{
protected:
    
    typedef typename gsStructuralAnalysisOps<T>::Residual_t      Residual_t;
    typedef typename gsStructuralAnalysisOps<T>::ALResidual_t    ALResidual_t;
    typedef typename gsStructuralAnalysisOps<T>::Jacobian_t      Jacobian_t;
    typedef typename gsStructuralAnalysisOps<T>::dJacobian_t     dJacobian_t;
 
public:
 
    virtual ~gsStaticBase() {};
 
    virtual gsStatus solve() = 0;
 
    virtual void initialize()
    {
        this->reset();
        this->getOptions();
    }
 
    virtual void initOutput() {};
    virtual void stepOutput(index_t /*k*/) {};
 
    virtual void defaultOptions()
    {
        m_options.addReal("tol","Relative Tolerance",1e-6);
        m_options.addReal("tolF","Residual relative tolerance",-1);
        m_options.addReal("tolU","Solution step relative tolerance",-1);
        m_options.addInt("maxIt","Maximum number of iterations",25);
        m_options.addInt("verbose","Verbose output",0);
        m_options.addInt ("BifurcationMethod","Bifurcation Identification based on: 0: Determinant;  1: Eigenvalue",stabmethod::Eigenvalue);
        m_options.addString("Solver","Sparse linear solver", "SimplicialLDLT");
    }
 
    virtual void getOptions()
    {
        m_tolF = m_options.getReal("tolF")!=-1 ? m_options.getReal("tolF") : m_options.getReal("tol");
        m_tolU = m_options.getReal("tolU")!=-1 ? m_options.getReal("tolU") : m_options.getReal("tol");
        m_maxIterations = m_options.getInt("maxIt");
        m_verbose = m_options.getInt("verbose");
        m_stabilityMethod     = m_options.getInt ("BifurcationMethod");
        m_solver = gsSparseSolver<T>::get( m_options.askString("Solver","SimplicialLDLT") );
    }
 
    virtual void setOptions(gsOptionList & options) {m_options.update(options,gsOptionList::addIfUnknown); }
 
    virtual gsOptionList options() const {return m_options;}
 
    virtual gsVector<T> solution() const {return m_U;}
 
    virtual gsVector<T> update() const {return m_DeltaU;}
 
    virtual void setDisplacement(const gsVector<T> & displacement)
    {
        m_start = true;
        m_U = displacement;
    }
 
    virtual void setLoad(const T L) { m_L = L;}
 
    virtual void setSolution(const gsVector<T> & displacement, const T L)
    {
        this->setDisplacement(displacement);
        this->setLoad(L);
    }
    virtual void setUpdate(const gsVector<T> & update)
    {
        m_headstart = true;
        m_DeltaU = update;
    }
 
    virtual index_t iterations() const { return m_numIterations; }
 
    virtual bool converged() const { return m_status==gsStatus::Success; }
 
    virtual gsStatus status() const { return m_status; }
 
    virtual index_t numDofs() { return m_dofs; }
 
    virtual void reset()
    {
        m_U.setZero(m_dofs);
        m_DeltaU.setZero(m_dofs);
        m_deltaU.setZero(m_dofs);
        m_R.setZero(m_dofs);
        m_L = m_DeltaL = m_deltaL = 0.0;
        m_headstart = false;
    }
 
    virtual T indicator(const gsSparseMatrix<T> & jacMat, T shift = -1e-2)
    {
       _computeStability(jacMat, shift);
       return m_indicator;
    }
 
    virtual gsVector<T> stabilityVec(const gsSparseMatrix<T> & jacMat, T shift = -1e-2)
    {
       _computeStability(jacMat, shift);
       return m_stabilityVec;
    }
 
protected:
    virtual bool _computeStabilityDet(const gsSparseMatrix<T> & jacMat)
    {
        m_solver->compute(jacMat);
        // If 1: matrix is not SPD
        if (m_solver->info()!=gsEigen::ComputationInfo::Success)
        {
            gsInfo<<"Solver error with code "<<m_solver->info()<<". See Eigen documentation on ComputationInfo \n"
                     <<gsEigen::ComputationInfo::Success<<": Success"<<"\n"
                     <<gsEigen::ComputationInfo::NumericalIssue<<": NumericalIssue"<<"\n"
                     <<gsEigen::ComputationInfo::NoConvergence<<": NoConvergence"<<"\n"
                     <<gsEigen::ComputationInfo::InvalidInput<<": InvalidInput"<<"\n";
            return false;
        }
 
        if ( auto * s = dynamic_cast<typename gsSparseSolver<T>::SimplicialLDLT*>(m_solver.get()) )
            m_stabilityVec = s->vectorD();
        return true;
    }
 
    virtual bool _computeStabilityEig(const gsSparseMatrix<T> & jacMat, T shift)
    {
#ifdef gsSpectra_ENABLED
        index_t number = std::min(static_cast<index_t>(std::floor(jacMat.cols()/5.)),10);
        /*
        // Without shift!
        // This one can sometimes not converge, because spectra is better at finding large values.
          gsSpectraSymSolver<gsSparseMatrix<T>> es(jacMat,number,5*number);
          es.init();
          es.compute(Spectra::SortRule::SmallestAlge,1000,1e-6,Spectra::SortRule::SmallestAlge);
          GISMO_ASSERT(es.info()==Spectra::CompInfo::Successful,"Spectra did not converge!"); // Reason for not converging can be due to the value of ncv (last input in the class member), which is too low.
        */
 
        // With shift!
        // This one converges easier. However, a shift must be provided!
        gsSpectraSymShiftSolver<gsSparseMatrix<T>> es(jacMat,number,5*number,shift);
        es.init();
        es.compute(Spectra::SortRule::LargestAlge,1000,1e-6,Spectra::SortRule::SmallestAlge);
        if (es.info()!=Spectra::CompInfo::Successful)
        {
            gsWarn<<"Spectra did not converge!\n";
            return false;   
        }
 
        // if (es.info()==Spectra::CompInfo::NotComputed)
        // if (es.info()==Spectra::CompInfo::NotConverging)
        // if (es.info()==Spectra::CompInfo::NumericalIssue)
        // gsEigen::SelfAdjointEigenSolver< gsMatrix<T> > es(jacMat);
        m_stabilityVec = es.eigenvalues();
#else
        GISMO_UNUSED(shift);
        gsEigen::SelfAdjointEigenSolver<gsMatrix<T>> es2(jacMat);
        m_stabilityVec = es2.eigenvalues();
#endif
 
        m_indicator = m_stabilityVec.colwise().minCoeff()[0]; // This is required since D does not necessarily have one column.
        return true;
    }
 
    virtual bool _computeStability   (const gsSparseMatrix<T> & jacMat, T shift)
    {
        bool success = false;
        if (m_stabilityMethod == stabmethod::Determinant)
            success = _computeStabilityDet(jacMat);
        else if (m_stabilityMethod == stabmethod::Eigenvalue)
            success = _computeStabilityEig(jacMat, shift);
        else
          gsInfo<<"bifurcation method unknown!";
 
        if (success)
            m_indicator = m_stabilityVec.colwise().minCoeff()[0]; // This is required since D does not necessarily have one column
        return success;
    }
 
protected:
    mutable gsOptionList m_options;
 
    T           m_L, m_DeltaL, m_deltaL;
    gsVector<T> m_U, m_DeltaU, m_deltaU;
    gsVector<T> m_R;
    T           m_residual, m_residualIni, m_residualOld;
 
    index_t m_numIterations;
    index_t m_maxIterations;
    bool m_start;
    index_t m_headstart;
 
    index_t m_verbose;
 
    index_t m_dofs;
 
    T m_tolF,m_tolU;
 
    T m_indicator;
 
    gsVector<T> m_stabilityVec;
 
    mutable typename gsSparseSolver<T>::uPtr  m_solver;   // Cholesky by default
 
    index_t m_stabilityMethod;
 
    struct stabmethod
    {
        enum type
        {
            Determinant = 0,
            Eigenvalue  = 1,
        };
    };
 
    gsStatus m_status;
 
};
 
 
} // namespace gismo
 
 
#ifndef GISMO_BUILD_LIB
#include GISMO_HPP_HEADER(gsStaticBase.hpp)
#endif