DriverModifiedArnoldi.cpp

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///////////////////////////////////////////////////////////////////////////////
//
// File DriverModifiedArnoldi.cpp
//
// For more information, please see: http://www.nektar.info
//
// The MIT License
//
// Copyright (c) 2006 Division of Applied Mathematics, Brown University (USA),
// Department of Aeronautics, Imperial College London (UK), and Scientific
// Computing and Imaging Institute, University of Utah (USA).
//
// License for the specific language governing rights and limitations under
// Permission is hereby granted, free of charge, to any person obtaining a
// copy of this software and associated documentation files (the "Software"),
// to deal in the Software without restriction, including without limitation
// the rights to use, copy, modify, merge, publish, distribute, sublicense,
// and/or sell copies of the Software, and to permit persons to whom the
// Software is furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included
// in all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
// OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
// THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
// DEALINGS IN THE SOFTWARE.
//
// Description: Driver for eigenvalue analysis using the modified Arnoldi
//              method.
//
///////////////////////////////////////////////////////////////////////////////

#include <iomanip>

#include <SolverUtils/DriverModifiedArnoldi.h>

namespace Nektar
{
    namespace SolverUtils
    {
    
    string DriverModifiedArnoldi::className =
    GetDriverFactory().RegisterCreatorFunction("ModifiedArnoldi",
                           DriverModifiedArnoldi::create);
    string DriverModifiedArnoldi::driverLookupId =
    LibUtilities::SessionReader::RegisterEnumValue("Driver",
                               "ModifiedArnoldi",0);
    
    /**
     * 
     */
    DriverModifiedArnoldi::DriverModifiedArnoldi(
        const LibUtilities::SessionReaderSharedPtr pSession)
    : DriverArnoldi(pSession)
    {
    }
    
    
    /**
     * 
     */
    DriverModifiedArnoldi::~DriverModifiedArnoldi()
    {
    }
    
    
    /**
     * 
     */
    void DriverModifiedArnoldi::v_InitObject(ostream &out)
    {
        DriverArnoldi::v_InitObject(out);
        
        m_equ[0]->PrintSummary(out);
        
        // Print session parameters
        if (m_comm->GetRank() == 0)
        {
        out << "\tArnoldi solver type    : Modified Arnoldi" << endl;
        }
        
        DriverArnoldi::ArnoldiSummary(out);
        
        m_equ[m_nequ - 1]->DoInitialise();
        
        //FwdTrans Initial conditions to be in Coefficient Space
        m_equ[m_nequ-1] ->TransPhysToCoeff();
        
    }
    
    
    /**
     * 
     */
    void DriverModifiedArnoldi::v_Execute(ostream &out)
    {
        int i               = 0;
        int j               = 0;
        int nq              = m_equ[0]->UpdateFields()[0]->GetNcoeffs();
        int ntot            = m_nfields*nq;
        int converged       = 0;
        NekDouble resnorm   = 0.0;
        ofstream evlout;
        std::string evlFile = m_session->GetSessionName() + ".evl";
        
        if (m_comm->GetRank() == 0)
        {
        evlout.open(evlFile.c_str());
        }
        
        // Allocate memory
        Array<OneD, NekDouble> alpha = Array<OneD, NekDouble> (m_kdim+1,      0.0);
        Array<OneD, NekDouble> wr    = Array<OneD, NekDouble> (m_kdim,        0.0);
        Array<OneD, NekDouble> wi    = Array<OneD, NekDouble> (m_kdim,        0.0);
        Array<OneD, NekDouble> zvec  = Array<OneD, NekDouble> (m_kdim*m_kdim, 0.0);
        
        Array<OneD, Array<OneD, NekDouble> > Kseq
        = Array<OneD, Array<OneD, NekDouble> > (m_kdim + 1);
        Array<OneD, Array<OneD, NekDouble> > Tseq
        = Array<OneD, Array<OneD, NekDouble> > (m_kdim + 1);
        for (i = 0; i < m_kdim + 1; ++i)
        {
        Kseq[i] = Array<OneD, NekDouble>(ntot, 0.0);
        Tseq[i] = Array<OneD, NekDouble>(ntot, 0.0);
        }
        
        // Copy starting vector into second sequence element (temporary).
        if(m_session->DefinesFunction("InitialConditions"))
        {
        if (m_comm->GetRank() == 0)
        {
            out << "\tInital vector       : specified in input file " << endl;
        }
        m_equ[0]->SetInitialConditions(0.0,false);
        
        CopyFieldToArnoldiArray(Kseq[1]);
        }
        else
        {
        if (m_comm->GetRank() == 0)
        {
            out << "\tInital vector       : random  " << endl;
        }
        
        NekDouble eps=1;
        Vmath::FillWhiteNoise(ntot, eps , &Kseq[1][0], 1);
        }
        
        // Perform one iteration to enforce boundary conditions.
        // Set this as the initial value in the sequence.
        EV_update(Kseq[1], Kseq[0]);
        if (m_comm->GetRank() == 0)
        {
        out << "Iteration: " << 0 <<  endl;
        }
        
        // Normalise first vector in sequence
        alpha[0] = Blas::Ddot(ntot, &Kseq[0][0], 1, &Kseq[0][0], 1);
        m_comm->AllReduce(alpha[0], Nektar::LibUtilities::ReduceSum);
        alpha[0] = std::sqrt(alpha[0]);
        Vmath::Smul(ntot, 1.0/alpha[0], Kseq[0], 1, Kseq[0], 1);
        
        // Fill initial krylov sequence
        NekDouble resid0;
        for (i = 1; !converged && i <= m_kdim; ++i)
        {
        // Compute next vector
        EV_update(Kseq[i-1], Kseq[i]);
        
        // Normalise
        alpha[i] = Blas::Ddot(ntot, &Kseq[i][0], 1, &Kseq[i][0], 1);
        m_comm->AllReduce(alpha[i], Nektar::LibUtilities::ReduceSum);
        alpha[i] = std::sqrt(alpha[i]);
        
        //alpha[i] = std::sqrt(alpha[i]);
        Vmath::Smul(ntot, 1.0/alpha[i], Kseq[i], 1, Kseq[i], 1);
        
        // Copy Krylov sequence into temporary storage
        for (int k = 0; k < i + 1; ++k)
        {
            Vmath::Vcopy(ntot, Kseq[k], 1, Tseq[k], 1);
        }
        
        // Generate Hessenberg matrix and compute eigenvalues of it.
        EV_small(Tseq, ntot, alpha, i, zvec, wr, wi, resnorm);
        
        // Test for convergence.
        converged = EV_test(i, i, zvec, wr, wi, resnorm,
                    std::min(i, m_nvec), evlout, resid0);
        converged = max (converged, 0);
        
        if (m_comm->GetRank() == 0)
        {
            out << "Iteration: " <<  i << " (residual : " << resid0
            << ")" <<endl;
        }
        }
        
        // Continue with full sequence
        if (!converged)
        {
        for (i = m_kdim + 1; !converged && i <= m_nits; ++i)
        {
            // Shift all the vectors in the sequence.
            // First vector is removed.
            for (int j = 1; j <= m_kdim; ++j)
            {
            alpha[j-1] = alpha[j];
            Vmath::Vcopy(ntot, Kseq[j], 1, Kseq[j-1], 1);
            }
            
            // Compute next vector
            EV_update(Kseq[m_kdim - 1], Kseq[m_kdim]);
            
            // Compute new scale factor
            alpha[m_kdim] = Blas::Ddot(ntot, &Kseq[m_kdim][0], 1,
                           &Kseq[m_kdim][0], 1);
            m_comm->AllReduce(alpha[m_kdim],
                      Nektar::LibUtilities::ReduceSum);
            alpha[m_kdim] = std::sqrt(alpha[m_kdim]);
            Vmath::Smul(ntot, 1.0/alpha[m_kdim], Kseq[m_kdim], 1,
                Kseq[m_kdim], 1);
            
            // Copy Krylov sequence into temporary storage
            for (int k = 0; k < m_kdim + 1; ++k)
            {
            Vmath::Vcopy(ntot, Kseq[k], 1, Tseq[k], 1);
            }
            
            // Generate Hessenberg matrix and compute eigenvalues of it
            EV_small(Tseq, ntot, alpha, m_kdim, zvec, wr, wi, resnorm);
            
            // Test for convergence.
            converged = EV_test(i, m_kdim, zvec, wr, wi, resnorm,
                    m_nvec, evlout, resid0);
            
            if (m_comm->GetRank() == 0)
            {
            out << "Iteration: " <<  i << " (residual : "
            << resid0 << ")" <<endl;
            }
        }
        }
        
        m_equ[0]->Output();
        
        // Evaluate and output computation time and solution accuracy.
        // The specific format of the error output is essential for the
        // regression tests to work.
        // Evaluate L2 Error
        for(j = 0; j < m_equ[0]->GetNvariables(); ++j)
        {
        NekDouble vL2Error = m_equ[0]->L2Error(j,false);
        NekDouble vLinfError = m_equ[0]->LinfError(j);
        if (m_comm->GetRank() == 0)
        {
            out << "L 2 error (variable " << m_equ[0]->GetVariable(j)
            << ") : " << vL2Error << endl;
            out << "L inf error (variable " << m_equ[0]->GetVariable(j)
            << ") : " << vLinfError << endl;
        }
        }
        
        // Process eigenvectors and write out.
        EV_post(Tseq, Kseq, ntot, min(--i, m_kdim), m_nvec, zvec, wr, wi,
            converged);
        
        // store eigenvalues so they can be access from driver class
        m_real_evl = wr;
        m_imag_evl = wi;
        
        // Close the runtime info file.
        if (m_comm->GetRank() == 0)
        {
        evlout.close();
        }
    }
    
    
    /**
     * 
     */
    void DriverModifiedArnoldi::EV_update(
        Array<OneD, NekDouble> &src,
        Array<OneD, NekDouble> &tgt)
    {
        // Copy starting vector into first sequence element.
        CopyArnoldiArrayToField(src);
        m_equ[0]->TransCoeffToPhys();
        
        m_equ[0]->DoSolve();
        
        if(m_EvolutionOperator == eTransientGrowth)
        {
        Array<OneD, MultiRegions::ExpListSharedPtr> fields;
        fields = m_equ[0]->UpdateFields();
        
        //start Adjoint with latest fields of direct
        CopyFwdToAdj();
        m_equ[1]->TransCoeffToPhys();
        
        m_equ[1]->DoSolve();
        }
        
        // Copy starting vector into first sequence element.
        CopyFieldToArnoldiArray(tgt);
    }
    
    
    /**
     * 
     */
    void DriverModifiedArnoldi::EV_small(
        Array<OneD, Array<OneD, NekDouble> > &Kseq,
        const int                             ntot,
        const Array<OneD, NekDouble>         &alpha,
        const int                             kdim,
        Array<OneD, NekDouble>               &zvec,
        Array<OneD, NekDouble>               &wr,
        Array<OneD, NekDouble>               &wi,
        NekDouble                            &resnorm)
    {
        int kdimp = kdim + 1;
        int lwork = 10*kdim;
        int ier;
        Array<OneD, NekDouble> R(kdimp * kdimp, 0.0);
        Array<OneD, NekDouble> H(kdimp * kdim, 0.0);
        Array<OneD, NekDouble> rwork(lwork, 0.0);
        
        // Modified G-S orthonormalisation
        for (int i = 0; i < kdimp; ++i)
        {
        NekDouble gsc = Blas::Ddot(ntot, &Kseq[i][0], 1, &Kseq[i][0], 1);
        m_comm->AllReduce(gsc, Nektar::LibUtilities::ReduceSum);
        gsc = std::sqrt(gsc);
        ASSERTL0(gsc != 0.0, "Vectors are linearly independent.");
        
        R[i*kdimp+i] = gsc;
        Vmath::Smul(ntot, 1.0/gsc, Kseq[i], 1, Kseq[i], 1);
        
        for (int j = i + 1; j < kdimp; ++j)
        {
            gsc = Blas::Ddot(ntot, &Kseq[i][0], 1, &Kseq[j][0], 1);
            m_comm->AllReduce(gsc, Nektar::LibUtilities::ReduceSum);
            Vmath::Svtvp(ntot, -gsc, Kseq[i], 1, Kseq[j], 1, Kseq[j], 1);
            R[j*kdimp+i] = gsc;
        }
        }
        
        // Compute H matrix
        for (int i = 0; i < kdim; ++i)
        {
        for (int j = 0; j < kdim; ++j)
        {
            H[j*kdim+i] = alpha[j+1] * R[(j+1)*kdimp+i]
            - Vmath::Dot(j, &H[0] + i, kdim, &R[0] + j*kdimp, 1);
            H[j*kdim+i] /= R[j*kdimp+j];
        }
        }
        
        H[(kdim-1)*kdim+kdim] = alpha[kdim]
        * std::fabs(R[kdim*kdimp+kdim] / R[(kdim-1)*kdimp + kdim-1]);
        
        Lapack::dgeev_('N', 'V', kdim, &H[0], kdim, &wr[0], &wi[0], 0, 1,
               &zvec[0], kdim, &rwork[0], lwork, ier);
        
        ASSERTL0(!ier, "Error with dgeev");
        
        resnorm = H[(kdim-1)*kdim + kdim];
    }
    
    
    /**
     * 
     */
    int DriverModifiedArnoldi::EV_test(
        const int               itrn,
        const int               kdim,
        Array<OneD, NekDouble> &zvec,
        Array<OneD, NekDouble> &wr,
        Array<OneD, NekDouble> &wi,
        const NekDouble         resnorm,
        const int               nvec,
        ofstream               &evlout,
        NekDouble              &resid0)
    {
        int idone = 0;
        // NekDouble period = 0.1;
        
        Array<OneD, NekDouble> resid(kdim);
        for (int i = 0; i < kdim; ++i)
        {
        NekDouble tmp = std::sqrt(Vmath::Dot(kdim, &zvec[0] + i*kdim, 1,
                             &zvec[0] + i*kdim, 1));
        resid[i] = resnorm * std::fabs(zvec[kdim - 1 + i*kdim]) / tmp;
        if (wi[i] < 0.0)
        {
            resid[i-1] = resid[i] = hypot(resid[i-1], resid[i]);
        }
        }
        
        EV_sort(zvec, wr, wi, resid, kdim);
        
        if (resid[nvec-1] < m_evtol)
        {
        idone = nvec;
        }
        
        if (m_comm->GetRank() == 0)
        {
        evlout << "-- Iteration = " << itrn << ", H(k+1, k) = "
        << resnorm << endl;
        evlout.precision(4);
        evlout.setf(ios::scientific, ios::floatfield);
        if(m_timeSteppingAlgorithm)
        {
            evlout << "EV  Magnitude   Angle       Growth      "
            << "Frequency   Residual" << endl;
        }
        else
        {
            evlout << "EV  Real        Imaginary   inverse real  "
            << "inverse imag  Residual" << endl;
        }
        
        for (int i = 0; i < kdim; i++)
        {
            WriteEvs(evlout,i,wr[i],wi[i],resid[i]);
        }
        }
        
        resid0 = resid[nvec-1];
        return idone;
    }
    
    
    /**
     * 
     */
    void DriverModifiedArnoldi::EV_sort(
        Array<OneD, NekDouble> &evec,
        Array<OneD, NekDouble> &wr,
        Array<OneD, NekDouble> &wi,
        Array<OneD, NekDouble> &test,
        const int               dim)
    {
        Array<OneD, NekDouble> z_tmp(dim,0.0);
        NekDouble wr_tmp, wi_tmp, te_tmp;
        for (int j = 1; j < dim; ++j)
        {
        wr_tmp = wr[j];
        wi_tmp = wi[j];
        te_tmp = test[j];
        Vmath::Vcopy(dim, &evec[0] + j*dim, 1, &z_tmp[0], 1);
        int i = j - 1;
        while (i >= 0 && test[i] > te_tmp)
        {
            wr[i+1] = wr[i];
            wi[i+1] = wi[i];
            test[i+1] = test[i];
            Vmath::Vcopy(dim, &evec[0] + i*dim, 1, &evec[0] + (i+1)*dim, 1);
            i--;
        }
        wr[i+1] = wr_tmp;
        wi[i+1] = wi_tmp;
        test[i+1] = te_tmp;
        Vmath::Vcopy(dim, &z_tmp[0], 1, &evec[0] + (i+1)*dim, 1);
        }
    }
    
    
    /**
     * 
     */
    void DriverModifiedArnoldi::EV_post(
        Array<OneD, Array<OneD, NekDouble> > &Tseq,
        Array<OneD, Array<OneD, NekDouble> > &Kseq,
        const int                             ntot,
        const int                             kdim,
        const int                             nvec,
        Array<OneD, NekDouble>               &zvec,
        Array<OneD, NekDouble>               &wr,
        Array<OneD, NekDouble>               &wi,
        const int                             icon)
    {
        if (icon == 0)
        {
        // Not converged, write final Krylov vector
        ASSERTL0(false, "Convergence was not achieved within the "
        "prescribed number of iterations.");
        }
        else if (icon < 0)
        {
        // Minimum residual reached
        ASSERTL0(false, "Minimum residual reached.");
        }
        else if (icon == nvec)
        {
        // Converged, write out eigenvectors
        EV_big(Tseq, Kseq, ntot, kdim, icon, zvec, wr, wi);
        Array<OneD, MultiRegions::ExpListSharedPtr> fields
        = m_equ[0]->UpdateFields();
        
        for (int j = 0; j < icon; ++j)
        {
            std::string file = m_session->GetSessionName() + "_eig_"
            + boost::lexical_cast<std::string>(j);
            
            WriteFld(file,Kseq[j]);
        }
        }
        else
        {
        // Not recognised
        ASSERTL0(false, "Unrecognised value.");
        }
    }
    
    
    /**
     * 
     */
    void DriverModifiedArnoldi::EV_big(
        Array<OneD, Array<OneD, NekDouble> > &bvecs,
        Array<OneD, Array<OneD, NekDouble> > &evecs,
        const int                             ntot,
        const int                             kdim,
        const int                             nvec,
        Array<OneD, NekDouble>               &zvec,
        Array<OneD, NekDouble>               &wr,
        Array<OneD, NekDouble>               &wi)
    {
        NekDouble wgt, norm;
        
        // Generate big eigenvectors
        for (int j = 0; j < nvec; ++j)
        {
        Vmath::Zero(ntot, evecs[j], 1);
        for (int i = 0; i < kdim; ++i)
        {
            wgt = zvec[i + j*kdim];
            Vmath::Svtvp(ntot, wgt, bvecs[i], 1, evecs[j], 1, evecs[j], 1);
        }
        }
        
        // Normalise the big eigenvectors
        for (int i = 0; i < nvec; ++i)
        {
        if (wi[i] == 0.0)   // Real mode
        {
            norm = Blas::Ddot(ntot, &evecs[i][0], 1, &evecs[i][0], 1);
            m_comm->AllReduce(norm, Nektar::LibUtilities::ReduceSum);
            norm = std::sqrt(norm);
            Vmath::Smul(ntot, 1.0/norm, evecs[i], 1, evecs[i], 1);
        }
        else
        {
            norm  = Blas::Ddot(ntot, &evecs[i][0],   1, &evecs[i][0],   1);
            norm += Blas::Ddot(ntot, &evecs[i+1][0], 1, &evecs[i+1][0], 1);
            m_comm->AllReduce(norm, Nektar::LibUtilities::ReduceSum);
            norm = std::sqrt(norm);
            
            Vmath::Smul(ntot, 1.0/norm, evecs[i],   1, evecs[i],   1);
            Vmath::Smul(ntot, 1.0/norm, evecs[i+1], 1, evecs[i+1], 1);
            
            i++;
        }
        }
    }
    
    }
}