// ======================================================================
void Eig(const Operator& Op, MultiVector& ER, MultiVector& EI)
{
int ierr;
if (Op.GetDomainSpace() != Op.GetRangeSpace())
ML_THROW("Matrix is not square", -1);
ER.Reshape(Op.GetDomainSpace());
EI.Reshape(Op.GetDomainSpace());
Epetra_LinearProblem Problem;
Problem.SetOperator(const_cast<Epetra_RowMatrix*>(Op.GetRowMatrix()));
Amesos_Lapack Lapack(Problem);
Epetra_Vector ER_Epetra(Op.GetRowMatrix()->RowMatrixRowMap());
Epetra_Vector EI_Epetra(Op.GetRowMatrix()->RowMatrixRowMap());
ierr = Lapack.GEEV(ER_Epetra, EI_Epetra);
if (ierr)
ML_THROW("GEEV returned error code = " + GetString(ierr), -1);
for (int i = 0 ; i < ER.GetMyLength() ; ++i) {
ER(i) = ER_Epetra[i];
EI(i) = EI_Epetra[i];
}
}
//---------------------------------------------------------------------------
const std::vector<int> ManyDigitIndexTable::FindInternal(
const std::vector<int>& indices,
const MultiVector<int>& v,
const int value)
{
//Check indices
{
const auto begin = v.PeekIndices().begin();
const auto end = v.PeekIndices().end();
const auto x = std::find(begin,end,value);
if (x!=end)
{
const int index_found = std::distance(begin,x);
assert(index_found >= 0);
assert(index_found < boost::numeric_cast<int>(v.PeekIndices().size()));
std::vector<int> result = indices;
result.push_back(index_found);
return result;
}
}
//Check MultiVector
const auto& mvs = v.PeekMultiVectors();
const int size = mvs.size();
for (int i=0; i!=size; ++i)
{
std::vector<int> indices_deeper = indices;
indices_deeper.push_back(i);
const auto result
= FindInternal(
indices_deeper,mvs[i],value);
if (!result.empty()) return result;
}
return std::vector<int>();
}
/*----------------------------------------------------------------------*
| apply multigrid linear preconditioner (private) m.gee 03/06|
*----------------------------------------------------------------------*/
int MOERTEL::Mortar_ML_Preconditioner::MultiLevelSA(
const MultiVector& b1_f,
const MultiVector& b2_f,
MultiVector& x1_f,
MultiVector& x2_f,
int level) const
{
MultiVector r1_f(b1_f.GetVectorSpace(),1,false);
MultiVector z1_f(b1_f.GetVectorSpace(),1,false);
// presmoothing
x1_f = 0;
G_.Apply(b1_f,x1_f);
x2_f = mlapiMT_ * x1_f;
x2_f.Scale(-1.0);
// compute residual
r1_f = b1_f - mlapiAhat11_ * x1_f;
// postsmoothing
z1_f = 0;
G_.Apply(r1_f,z1_f);
x1_f = x1_f + z1_f;
x2_f = mlapiMT_ * x1_f;
x2_f.Scale(-1.0);
return 0;
}
void IfpackSmoother::Apply(MultiVector& X, const MultiVector& B, bool InitialGuessIsZero) const {
TEUCHOS_TEST_FOR_EXCEPTION(SmootherPrototype::IsSetup() == false, Exceptions::RuntimeError, "MueLu::IfpackSmoother::Apply(): Setup() has not been called");
// Forward the InitialGuessIsZero option to Ifpack
Teuchos::ParameterList paramList;
if (type_ == "Chebyshev")
paramList.set("chebyshev: zero starting solution", InitialGuessIsZero);
else if (type_ == "point relaxation stand-alone")
paramList.set("relaxation: zero starting solution", InitialGuessIsZero);
SetPrecParameters(paramList);
// Apply
if (InitialGuessIsZero) {
Epetra_MultiVector& epX = Utils::MV2NonConstEpetraMV(X);
const Epetra_MultiVector& epB = Utils::MV2EpetraMV(B);
prec_->ApplyInverse(epB, epX);
} else {
RCP<MultiVector> Residual = Utils::Residual(*A_,X,B);
RCP<MultiVector> Correction = MultiVectorFactory::Build(A_->getDomainMap(), X.getNumVectors());
Epetra_MultiVector& epX = Utils::MV2NonConstEpetraMV(*Correction);
const Epetra_MultiVector& epB = Utils::MV2EpetraMV(*Residual);
prec_->ApplyInverse(epB, epX);
X.update(1.0, *Correction, 1.0);
}
}
void ZoltanInterface<LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::
GetProblemGeometry(void *data, int numGIDEntries, int numLIDEntries, int numObjectIDs,
ZOLTAN_ID_PTR gids, ZOLTAN_ID_PTR lids, int dim, double *coordinates, int *ierr)
{
if (data == NULL) {
*ierr = ZOLTAN_FATAL;
return;
}
MultiVector *Coords = (MultiVector*) data;
if (dim != Teuchos::as<int>(Coords->getNumVectors())) {
//FIXME I'm assuming dim should be 1, 2, or 3 coming in?!
*ierr = ZOLTAN_FATAL;
return;
}
TEUCHOS_TEST_FOR_EXCEPTION(numObjectIDs != Teuchos::as<int>(Coords->getLocalLength()), Exceptions::Incompatible, "Length of coordinates must be the same as the number of objects");
ArrayRCP<ArrayRCP<const SC> > CoordsData(dim);
for (int j = 0; j < dim; ++j)
CoordsData[j] = Coords->getData(j);
size_t numElements = Coords->getLocalLength();
for (size_t i = 0; i < numElements; ++i)
for (int j = 0; j < dim; ++j)
coordinates[i*dim+j] = (double) CoordsData[j][i];
*ierr = ZOLTAN_OK;
} //GetProblemGeometry
void test_rotate()
{
QVector<Vector> axis(MultiVector::count()), vec(MultiVector::count());
QVector<double> angle(MultiVector::count());
QVector<Vector> result(MultiVector::count());
for (int i=0; i<MultiVector::count(); ++i)
{
axis[i] = rangen.vectorOnSphere(1);
vec[i] = rangen.vectorOnSphere(5);
angle[i] = rangen.rand(-2.0*SireMaths::pi, 2.0*SireMaths::pi);
result[i] = Quaternion(Angle(angle[i]),axis[i]).rotate(vec[i]);
}
MultiVector maxis(axis);
MultiVector mvec(vec);
MultiDouble mangle(angle);
MultiVector mresult = MultiQuaternion(mangle, maxis).rotate(mvec);
for (int i=0; i<MultiVector::count(); ++i)
{
for (int j=0; j<3; ++j)
{
assert_nearly_equal( mresult.at(i)[j], result[i][j], 1e-5 );
}
}
}
// ======================================================================
// FIXME: Add List
void Eigs(const Operator& A, int NumEigenvalues,
MultiVector& ER, MultiVector& EI)
{
if (A.GetDomainSpace() != A.GetRangeSpace())
ML_THROW("Input Operator is not square", -1);
double time;
time = GetClock();
int length = NumEigenvalues;
double tol = 1e-3;
int restarts = 1;
int output = 10;
bool PrintStatus = true;
// 1.- set parameters for Anasazi
Teuchos::ParameterList AnasaziList;
// MatVec should be either "A" or "ML^{-1}A"
AnasaziList.set("eigen-analysis: matrix operation", "A");
AnasaziList.set("eigen-analysis: use diagonal scaling", false);
AnasaziList.set("eigen-analysis: symmetric problem", false);
AnasaziList.set("eigen-analysis: length", length);
AnasaziList.set("eigen-analysis: block-size",1);
AnasaziList.set("eigen-analysis: tolerance", tol);
AnasaziList.set("eigen-analysis: restart", restarts);
AnasaziList.set("eigen-analysis: output", output);
AnasaziList.get("eigen-analysis: print current status",PrintStatus);
// data to hold real and imag for eigenvalues and eigenvectors
Space ESpace(-1, NumEigenvalues);
ER.Reshape(ESpace);
EI.Reshape(ESpace);
// this is the starting value -- random
Epetra_MultiVector EigenVectors(A.GetRowMatrix()->OperatorDomainMap(),
NumEigenvalues);
EigenVectors.Random();
#ifdef HAVE_ML_ANASAxI
//int NumRealEigenvectors, NumImagEigenvectors;
#endif
AnasaziList.set("eigen-analysis: action", "LM");
#ifdef HAVE_ML_ANASAxI
ML_THROW("fixme...", -1);
/* FIXME
ML_Anasazi::Interface(A.GetRowMatrix(),EigenVectors,ER.GetValues(),
EI.GetValues(), AnasaziList, 0, 0,
&NumRealEigenvectors, &NumImagEigenvectors, 0);
*/
#else
ML_THROW("Anasazi is no longer supported", -1);
#endif
return;
}
void IndefBlockedDiagonalSmoother<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Apply(MultiVector& X, const MultiVector& B, bool InitialGuessIsZero) const
{
TEUCHOS_TEST_FOR_EXCEPTION(SmootherPrototype::IsSetup() == false, Exceptions::RuntimeError, "MueLu::IndefBlockedDiagonalSmoother::Apply(): Setup() has not been called");
Teuchos::RCP<Teuchos::FancyOStream> fos = Teuchos::getFancyOStream(Teuchos::rcpFromRef(std::cout));
SC zero = Teuchos::ScalarTraits<SC>::zero(), one = Teuchos::ScalarTraits<SC>::one();
// extract parameters from internal parameter list
const ParameterList & pL = Factory::GetParameterList();
LocalOrdinal nSweeps = pL.get<LocalOrdinal>("Sweeps");
Scalar omega = pL.get<Scalar>("Damping factor");
// wrap current solution vector in RCP
RCP<MultiVector> rcpX = Teuchos::rcpFromRef(X);
// create residual vector
// contains current residual of current solution X with rhs B
RCP<MultiVector> residual = MultiVectorFactory::Build(B.getMap(), B.getNumVectors());
// incrementally improve solution vector X
for (LocalOrdinal run = 0; run < nSweeps; ++run) {
// 1) calculate current residual
residual->update(one,B,zero); // residual = B
A_->apply(*rcpX, *residual, Teuchos::NO_TRANS, -one, one);
// split residual vector
Teuchos::RCP<MultiVector> r1 = rangeMapExtractor_->ExtractVector(residual, 0);
Teuchos::RCP<MultiVector> r2 = rangeMapExtractor_->ExtractVector(residual, 1);
// 2) solve F * \Delta \tilde{x}_1 = r_1
// start with zero guess \Delta \tilde{x}_1
RCP<MultiVector> xtilde1 = MultiVectorFactory::Build(F_->getRowMap(),1);
xtilde1->putScalar(zero);
velPredictSmoo_->Apply(*xtilde1,*r1);
// 3) solve SchurComp equation
// start with zero guess \Delta \tilde{x}_2
RCP<MultiVector> xtilde2 = MultiVectorFactory::Build(Z_->getRowMap(),1);
xtilde2->putScalar(zero);
schurCompSmoo_->Apply(*xtilde2,*r2);
// 4) extract parts of solution vector X
Teuchos::RCP<MultiVector> x1 = domainMapExtractor_->ExtractVector(rcpX, 0);
Teuchos::RCP<MultiVector> x2 = domainMapExtractor_->ExtractVector(rcpX, 1);
// 5) update solution vector with increments xhat1 and xhat2
// rescale increment for x2 with omega_
x1->update(omega,*xtilde1,one); // x1 = x1_old + omega xtilde1
x2->update(omega,*xtilde2,one); // x2 = x2_old + omega xtilde2
// write back solution in global vector X
domainMapExtractor_->InsertVector(x1, 0, rcpX);
domainMapExtractor_->InsertVector(x2, 1, rcpX);
}
}
// ======================================================================
MultiVector Extract(const MultiVector& y, const int v)
{
if ((v < 0) || v >= y.GetNumVectors())
ML_THROW("Wrong input parameter v (" +
GetString(v) + ")", -1);
MultiVector x(y.GetVectorSpace(), y.GetRCPValues(v));
return(x);
}
/** Use this quaternion to rotate 'p' */
MultiVector MultiQuaternion::rotate(const MultiVector &p) const
{
const MultiDouble sx2 = sc[0]*sc[0];
const MultiDouble sy2 = sc[1]*sc[1];
const MultiDouble sz2 = sc[2]*sc[2];
const MultiDouble sxy = sc[0]*sc[1];
const MultiDouble sxz = sc[0]*sc[2];
const MultiDouble syz = sc[1]*sc[2];
const MultiDouble swx = sc[0]*sc[3];
const MultiDouble swy = sc[1]*sc[3];
const MultiDouble swz = sc[2]*sc[3];
const MultiDouble two(2.0);
const MultiDouble half(0.5);
return MultiVector( two*( ( half - sy2 - sz2 )*p.x()
+ ( sxy - swz ) *p.y()
+ ( sxz + swy ) *p.z()),
two*( ( sxy + swz ) *p.x()
+ ( half - sx2 - sz2 ) *p.y()
+ ( syz - swx ) *p.z()),
two*( ( sxz - swy ) *p.x()
+ ( syz + swx ) *p.y()
+ ( half - sx2 - sy2 ) *p.z()) );
}
// ======================================================================
MultiVector Duplicate(const MultiVector& y, const int v)
{
if ((v < 0) || v >= y.GetNumVectors())
ML_THROW("Wrong input parameter v (" +
GetString(v) + ")", -1);
// FIXME: use Extract
MultiVector x(y.GetVectorSpace(), 1);
for (int i = 0 ; i < x.GetMyLength() ; ++i)
x(i) = y(i,v);
return(x);
}
void LinearCheckNodeUpdater::updateNode(
unsigned int nodeInd,
MultiVector<float>& messages)
{
uint32_t begin = messages.begin(nodeInd);
uint32_t end = messages.end(nodeInd);
uint32_t N = end - begin;
if(N == 1) {
messages[begin] = m_checkNodesPriorLogPmQ[nodeInd].getFloat();
return;
}
// Convert all message values into log(p-q) values
for (unsigned int j = begin; j < end; j++) {
m_messagesPmQ.push_back(LogPmQ(messages[j]));
}
// calculate the multiplication from the right of p-q values:
// rightSum[j] = encodedSoftBit[i] * messages[-1].p-q * messages[-2].p-q * ... * messages[-j].p-q
LogPmQ curSum = m_checkNodesPriorLogPmQ[nodeInd]; // get log(p-q)
m_rightSum.push_back(curSum);
// go over all messages except the first one (which will never be
// needed anyway)
for(unsigned int rightInd = N - 1; rightInd > 0; rightInd--) {
curSum += m_messagesPmQ[rightInd];
m_rightSum.push_back(curSum);
}
// special case for j = 0
messages[begin] = m_rightSum[N - 1].getFloat();
// now we use curSum as the cumulative multiplication from the
// left rather than right
curSum = m_messagesPmQ[0];
for (unsigned int j = 1; j < N; j++) {
messages[begin + j] = (curSum + m_rightSum[N - j - 1]).getFloat();
//assert(isfinite(messages[begin + j]));
curSum += m_messagesPmQ[j];
}
m_rightSum.clear();
m_messagesPmQ.clear();
}
void
apply (const MultiVector<S,LO,GO,Node> &X,
MultiVector<S,LO,GO,Node> &Y,
Teuchos::ETransp mode = Teuchos::NO_TRANS,
S alpha = Teuchos::ScalarTraits<S>::one (),
S beta = Teuchos::ScalarTraits<S>::zero ()) const
{
const size_t numVectors = X.getNumVectors ();
RCP<MultiVector<S,LO,GO,Node> > mvec_inout;
RCP<const MultiVector<S,LO,GO,Node> > mvec_in2;
if (_importer != null) {
if (_importMV != null && _importMV->getNumVectors () != numVectors) {
_importMV = null;
}
if (_importMV == null) {
_importMV = createMultiVector<S> (_importer->getTargetMap (), numVectors);
}
_importMV->doImport (X, *_importer, INSERT);
mvec_in2 = _importMV;
}
else {
mvec_in2 = rcpFromRef(X);
}
if (_exporter != null) {
if (_exportMV != null && _exportMV->getNumVectors () != numVectors) {
_exportMV = null;
}
if (_exportMV == null) {
_exportMV = createMultiVector<S> (_exporter->getSourceMap (), numVectors);
}
mvec_inout = _exportMV;
}
else {
mvec_inout = rcpFromRef (Y);
}
_kernel.setAlphaBeta (alpha, beta);
//
for (size_t j=0; j < numVectors; ++j) {
RCP< Vector<S,LO,GO,Node> > vec_inout = mvec_inout->getVectorNonConst(j);
RCP< const Vector<S,LO,GO,Node> > vec_in2 = mvec_in2->getVector(j);
Tpetra::RTI::detail::binary_transform( *vec_inout, *vec_in2, _kernel );
}
// export
if (_exporter != null) {
Y.doExport (*_exportMV, *_exporter, ADD);
}
}
/** \brief Copy the contents of a multivector to a destination vector.
*
* Copy the contents of a multivector to a new vector. If the destination
* vector is null, a deep copy of the source multivector is made to a newly allocated
* vector. Also, if the destination and the source do not match, a new destination
* object is allocated and returned to the user.
*
* \param[in] src Source multivector to be copied.
* \param[in] dst Destination multivector. If null a new multivector will be allocated.
*
* \returns A copy of the source multivector. If dst is not null a pointer to this object
* is returned. Otherwise a new multivector is returned.
*/
inline MultiVector datacopy(const MultiVector & src,MultiVector & dst)
{
if(dst==Teuchos::null)
return deepcopy(src);
bool rangeCompat = src->range()->isCompatible(*dst->range());
bool domainCompat = src->domain()->isCompatible(*dst->domain());
if(not (rangeCompat && domainCompat))
return deepcopy(src);
// perform data copy
Thyra::assign<double>(dst.ptr(),*src);
return dst;
}
// ======================================================================
Operator GetPtent1D(const MultiVector& D, const int offset = 0)
{
if (D.GetNumVectors() != 1)
ML_THROW("D.GetNumVectors() != 1", -1);
int size = D.GetMyLength();
if (size == 0)
ML_THROW("empty diagonal vector in input", -1);
double* diag = new double[size];
for (int i = 0 ; i < size ; ++i)
diag[i] = D(i);
// creates the ML operator and store the diag pointer,
// as well as the function pointers
ML_Operator* MLDiag = ML_Operator_Create(GetML_Comm());
int invec_leng = size / 3 + size % 3;
int outvec_leng = size;
MLDiag->invec_leng = invec_leng;
MLDiag->outvec_leng = outvec_leng;
MLDiag->data = (void*)diag;
MLDiag->data_destroy = Ptent1D_destroy;
MLDiag->matvec->func_ptr = Ptent1D_matvec;
MLDiag->matvec->ML_id = ML_NONEMPTY;
MLDiag->matvec->Nrows = outvec_leng;
MLDiag->from_an_ml_operator = 0;
MLDiag->getrow->func_ptr = Ptent1D_getrows;
MLDiag->getrow->ML_id = ML_NONEMPTY;
MLDiag->getrow->Nrows = outvec_leng;
// creates the domain space
vector<int> MyGlobalElements(invec_leng);
for (int i = 0 ; i < invec_leng ; ++i)
MyGlobalElements[i] = D.GetVectorSpace()(i * 3) / 3;
Space DomainSpace(invec_leng, -1, &MyGlobalElements[0]);
Space RangeSpace = D.GetVectorSpace();
// creates the MLAPI wrapper
Operator Diag(DomainSpace,RangeSpace,MLDiag,true);
return(Diag);
}
void Amesos2Smoother<Scalar, LocalOrdinal, GlobalOrdinal, Node>::Apply(MultiVector& X, const MultiVector& B, bool InitialGuessIsZero) const {
TEUCHOS_TEST_FOR_EXCEPTION(SmootherPrototype::IsSetup() == false, Exceptions::RuntimeError, "MueLu::Amesos2Smoother::Apply(): Setup() has not been called");
RCP<Tpetra_MultiVector> tX, tB;
if (!useTransformation_) {
tX = Utilities::MV2NonConstTpetraMV2(X);
tB = Utilities::MV2NonConstTpetraMV2(const_cast<MultiVector&>(B));
} else {
// Copy data of the original vectors into the transformed ones
size_t numVectors = X.getNumVectors();
size_t length = X.getLocalLength();
TEUCHOS_TEST_FOR_EXCEPTION(numVectors > 1, Exceptions::RuntimeError,
"MueLu::Amesos2Smoother::Apply: Fixing coarse matrix for Amesos2 for multivectors has not been implemented yet.");
ArrayRCP<const SC> Xdata = X. getData(0), Bdata = B. getData(0);
ArrayRCP<SC> X_data = X_->getDataNonConst(0), B_data = B_->getDataNonConst(0);
for (size_t i = 0; i < length; i++) {
X_data[i] = Xdata[i];
B_data[i] = Bdata[i];
}
tX = Utilities::MV2NonConstTpetraMV2(*X_);
tB = Utilities::MV2NonConstTpetraMV2(*B_);
}
prec_->setX(tX);
prec_->setB(tB);
prec_->solve();
prec_->setX(Teuchos::null);
prec_->setB(Teuchos::null);
if (useTransformation_) {
// Copy data from the transformed vectors into the original ones
size_t length = X.getLocalLength();
ArrayRCP<SC> Xdata = X. getDataNonConst(0);
ArrayRCP<const SC> X_data = X_->getData(0);
for (size_t i = 0; i < length; i++)
Xdata[i] = X_data[i];
}
}
// ======================================================================
void Krylov(const Operator& A, const MultiVector& LHS,
const MultiVector& RHS, const BaseOperator& Prec,
Teuchos::ParameterList& List)
{
#ifndef HAVE_ML_AZTECOO
std::cerr << "Please configure ML with --enable-aztecoo to use" << std::endl;
std::cerr << "MLAPI Krylov solvers" << std::endl;
exit(EXIT_FAILURE);
#else
if (LHS.GetNumVectors() != 1)
ML_THROW("FIXME: only one vector is currently supported", -1);
Epetra_LinearProblem Problem;
const Epetra_RowMatrix& A_Epetra = *(A.GetRowMatrix());
Epetra_Vector LHS_Epetra(View,A_Epetra.OperatorDomainMap(),
(double*)&(LHS(0)));
Epetra_Vector RHS_Epetra(View,A_Epetra.OperatorRangeMap(),
(double*)&(RHS(0)));
// FIXME: this works only for Epetra-based operators
Problem.SetOperator((const_cast<Epetra_RowMatrix*>(&A_Epetra)));
Problem.SetLHS(&LHS_Epetra);
Problem.SetRHS(&RHS_Epetra);
AztecOO solver(Problem);
EpetraBaseOperator Prec_Epetra(A_Epetra.OperatorDomainMap(),Prec);
solver.SetPrecOperator(&Prec_Epetra);
// get options from List
int NumIters = List.get("krylov: max iterations", 1550);
double Tol = List.get("krylov: tolerance", 1e-9);
std::string type = List.get("krylov: type", "gmres");
int output = List.get("krylov: output level", GetPrintLevel());
// set options in `solver'
if (type == "cg")
solver.SetAztecOption(AZ_solver, AZ_cg);
else if (type == "cg_condnum")
solver.SetAztecOption(AZ_solver, AZ_cg_condnum);
else if (type == "gmres")
solver.SetAztecOption(AZ_solver, AZ_gmres);
else if (type == "gmres_condnum")
solver.SetAztecOption(AZ_solver, AZ_gmres_condnum);
else if (type == "fixed point")
solver.SetAztecOption(AZ_solver, AZ_fixed_pt);
else
ML_THROW("krylov: type has incorrect value (" +
type + ")", -1);
solver.SetAztecOption(AZ_output, output);
solver.Iterate(NumIters, Tol);
#endif
}
int
InverseOperator::Apply(const MultiVector& x, MultiVector& y) const
{
ResetTimer();
StackPush();
if (GetDomainSpace() != x.GetVectorSpace())
ML_THROW("DomainSpace and x.GetVectorSpace() differ", -1);
if (GetRangeSpace() != y.GetVectorSpace())
ML_THROW("RangeSpace and y.GetVectorSpace() differ", -1);
int x_nv = x.GetNumVectors();
int y_nv = y.GetNumVectors();
double FL = 0.0;
if (RCPData_ != Teuchos::null)
FL = RCPData_->ComputeFlops();
if (x_nv != y_nv)
ML_THROW("Number of vectors of x and y differ (" +
GetString(x_nv) + " vs. " + GetString(x_nv), -1);
for (int v = 0 ; v < x_nv ; ++v) {
Epetra_Vector x_Epetra(View,RowMatrix()->OperatorDomainMap(),
(double*)&(x(0,v)));
Epetra_Vector y_Epetra(View,RowMatrix()->OperatorRangeMap(),
(double*)&(y(0,v)));
if (RCPData_ != Teuchos::null)
RCPData_->ApplyInverse(x_Epetra,y_Epetra);
else if (RCPMLPrec_ != Teuchos::null)
RCPMLPrec_->ApplyInverse(x_Epetra,y_Epetra);
else
ML_THROW("Neither Ifpack nor ML smoother is properly set up", -1);
}
StackPop();
if (RCPData_ != Teuchos::null)
UpdateFlops(RCPData_->ComputeFlops() - FL);
UpdateTime();
return(0);
}
// SmootherBase test
ST::magnitudeType testApply(const Matrix& A, const SmootherBase & smoother, MultiVector & X, const MultiVector & RHS, Teuchos::FancyOStream & out, bool & success) {
Array<ST::magnitudeType> norms(1);
RHS.norm2(norms);
out << "||RHS|| = " << std::setiosflags(std::ios::fixed) << std::setprecision(10) << norms[0] << std::endl;
Teuchos::Array<ST::magnitudeType> initialNorms(1); X.norm2(initialNorms);
out << "||X_initial|| = " << std::setiosflags(std::ios::fixed) << std::setprecision(10) << initialNorms[0] << std::endl;
smoother.Apply(X, RHS); // TODO: bool const &InitialGuessIsZero=false
Teuchos::Array<ST::magnitudeType> finalNorms(1); X.norm2(finalNorms);
out << "||X_final|| = " << std::setiosflags(std::ios::fixed) << std::setprecision(25) << norms[0] << std::endl;
Teuchos::Array<ST::magnitudeType> residualNorms = Utils::ResidualNorm(A, X, RHS);
out << "||Residual|| = " << std::setiosflags(std::ios::fixed) << std::setprecision(20) << residualNorms[0] << std::endl;
return residualNorms[0];
}
void PermutingSmoother<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Apply(MultiVector &X, MultiVector const &B, bool const &InitialGuessIsZero) const
{
TEUCHOS_TEST_FOR_EXCEPTION(SmootherPrototype::IsSetup() == false, Exceptions::RuntimeError, "MueLu::PermutingSmoother::Apply(): Setup() has not been called");
TEUCHOS_TEST_FOR_EXCEPTION(s_ == Teuchos::null, Exceptions::RuntimeError, "IsSetup() == true but s_ == Teuchos::null. This does not make sense");
Teuchos::RCP<MultiVector> Xtemp = MultiVectorFactory::Build(X.getMap(),1,true);
Xtemp->update(1.0,X,0.0);
// TODO: unify scaling and left permutation operator
Teuchos::RCP<MultiVector> Btemp = MultiVectorFactory::Build(B.getMap(),1,true);
Teuchos::RCP<MultiVector> Btemp2 = MultiVectorFactory::Build(B.getMap(),1,true);
permP_->apply(B, *Btemp, Teuchos::NO_TRANS); // apply permutation operator to rhs
diagScalingOp_->apply(*Btemp,*Btemp2, Teuchos::NO_TRANS); // apply scaling operator to rhs
// apply smoother to permuted linear system
s_->Apply(*Xtemp, *Btemp2, InitialGuessIsZero);
// retransform smooth solution
permQT_->apply(*Xtemp, X, Teuchos::NO_TRANS);
}
void PermutingSmoother<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Apply(MultiVector& X, const MultiVector& B, bool InitialGuessIsZero) const {
TEUCHOS_TEST_FOR_EXCEPTION(SmootherPrototype::IsSetup() == false, Exceptions::RuntimeError, "MueLu::PermutingSmoother::Apply(): Setup() has not been called");
typedef Teuchos::ScalarTraits<Scalar> STS;
Teuchos::RCP<MultiVector> Xtemp = MultiVectorFactory::Build(X.getMap(), 1, true);
Xtemp->update(STS::one(), X, STS::zero());
// TODO: unify scaling and left permutation operator
Teuchos::RCP<MultiVector> Btemp = MultiVectorFactory::Build(B.getMap(), 1, true);
Teuchos::RCP<MultiVector> Btemp2 = MultiVectorFactory::Build(B.getMap(), 1, true);
permP_->apply(B, *Btemp, Teuchos::NO_TRANS); // apply permutation operator to rhs
diagScalingOp_->apply(*Btemp, *Btemp2, Teuchos::NO_TRANS); // apply scaling operator to rhs
// apply smoother to permuted linear system
s_->Apply(*Xtemp, *Btemp2, InitialGuessIsZero);
// retransform smooth solution
permQT_->apply(*Xtemp, X, Teuchos::NO_TRANS);
}
void test_getset()
{
QVector<Vector> v(MultiVector::count());
for (int i=0; i<MultiVector::count(); ++i)
{
v[i] = Vector( rangen.rand(-10,10), rangen.rand(-10,10),
rangen.rand(-10,10) );
}
MultiVector mv;
for (int i=0; i<MultiVector::count(); ++i)
{
mv.set(i, v[i]);
assert_equal( mv.getitem(i), v[i] );
}
assert_equal( MultiVector(v), mv );
}
MultiQuaternion SIREMATHS_EXPORT SireMaths::operator*(const MultiQuaternion &q,
const MultiVector &p)
{
//quaternion multiplication - p is [0, p]
MultiDouble nw = -p.sc[0]*q.sc[0] - p.sc[1]*q.sc[1] - p.sc[2]*q.sc[2];
//do the cross product
MultiDouble cx = (q.sc[1]*p.z())-(q.sc[2]*p.y());
MultiDouble cy = (q.sc[2]*p.x())-(q.sc[0]*p.z());
MultiDouble cz = (q.sc[0]*p.y())-(q.sc[1]*p.x());
MultiDouble nx = q.sc[3]*p.x() + cx;
MultiDouble ny = q.sc[3]*p.y() + cy;
MultiDouble nz = q.sc[3]*p.z() + cz;
return MultiQuaternion(nx,ny,nz,nw);
}
void LinearCheckNodeUpdater::update(MultiVector<float> & messages)
{
uint32_t N_nodes = messages.size();
assert(N_nodes == m_checkNodesPriorLogPmQ.size());
// for each check node
for (uint32_t node_ind = 0; node_ind < N_nodes; node_ind++) {
updateNode(node_ind, messages);
}
}
void test_cross()
{
QVector<Vector> v0(MultiVector::count()), v1(MultiVector::count());
QVector<Vector> cross(MultiVector::count());
for (int i=0; i<MultiVector::count(); ++i)
{
v0[i] = rangen.vectorOnSphere(5);
v1[i] = rangen.vectorOnSphere(5);
cross[i] = Vector::cross(v0[i], v1[i]);
}
MultiVector mv0(v0);
MultiVector mv1(v1);
MultiVector mcross = MultiVector::cross(mv0, mv1);
for (int i=0; i<MultiVector::count(); ++i)
{
assert_equal( mcross.at(i), cross.at(i) );
}
}
void
CrsMatrixSolveOp<OpScalar,MatScalar,LocalOrdinal,GlobalOrdinal,Node,LocalMatOps>::apply(
const MultiVector<OpScalar,LocalOrdinal,GlobalOrdinal,Node> & X,
MultiVector<OpScalar,LocalOrdinal,GlobalOrdinal,Node> & Y,
Teuchos::ETransp mode, OpScalar alpha, OpScalar beta) const
{
TEUCHOS_TEST_FOR_EXCEPTION(!matrix_->isFillComplete(), std::runtime_error,
Teuchos::typeName(*this) << "::apply(): underlying matrix is not fill-complete.");
TEUCHOS_TEST_FOR_EXCEPTION(X.getNumVectors() != Y.getNumVectors(), std::runtime_error,
Teuchos::typeName(*this) << "::apply(X,Y): X and Y must have the same number of vectors.");
TEUCHOS_TEST_FOR_EXCEPTION(matrix_->isLowerTriangular() == false && matrix_->isUpperTriangular() == false, std::runtime_error,
Teuchos::typeName(*this) << "::apply() requires either upper or lower triangular structure in underlying matrix.");
TEUCHOS_TEST_FOR_EXCEPTION( alpha != Teuchos::ScalarTraits<OpScalar>::one() || beta != Teuchos::ScalarTraits<OpScalar>::zero(), std::runtime_error,
Teuchos::typeName(*this) << "::apply(): non-trivial alpha,beta not supported at this time.");
if (mode == Teuchos::NO_TRANS) {
applyNonTranspose(X,Y);
}
else {
applyTranspose(X,Y);
}
}
MultiVector LoadBalanceInverseOperator::operator()(const MultiVector& LHS)
{
StackPush();
MultiVector RHS(LHS.GetVectorSpace());
RHS = 0.0;
Apply(LHS,RHS);
StackPop();
return(RHS);
}
/// \brief Compute \f$Y = \beta Y + \alpha B X\f$, where \f$B X\f$
/// represents the result of the local triangular solve.
void
apply (const MultiVector<Scalar,LocalOrdinal,GlobalOrdinal,Node> & X,
MultiVector<Scalar,LocalOrdinal,GlobalOrdinal,Node> &Y,
Teuchos::ETransp mode = Teuchos::NO_TRANS,
Scalar alpha = Teuchos::ScalarTraits<Scalar>::one (),
Scalar beta = Teuchos::ScalarTraits<Scalar>::zero ()) const
{
typedef Teuchos::ScalarTraits<Scalar> STOS;
const char prefix[] = "Tpetra::CrsMatrixSolveOp::apply: ";
TEUCHOS_TEST_FOR_EXCEPTION
(! matrix_->isFillComplete (), std::runtime_error,
prefix << "Underlying matrix is not fill complete.");
TEUCHOS_TEST_FOR_EXCEPTION
(! matrix_->isLowerTriangular () && ! matrix_->isUpperTriangular (),
std::runtime_error, prefix << "The matrix is neither lower nor upper "
"triangular. Remember that in Tpetra, triangular-ness is a local "
"(per MPI process) property.");
TEUCHOS_TEST_FOR_EXCEPTION
(X.getNumVectors () != Y.getNumVectors (), std::invalid_argument,
prefix << "X and Y must have the same number of columns (vectors). "
"X.getNumVectors() = " << X.getNumVectors ()
<< " != Y.getNumVectors() = " << Y.getNumVectors () << ".");
TEUCHOS_TEST_FOR_EXCEPTION
(alpha != STOS::one () || beta != STOS::zero (), std::logic_error,
prefix << "The case alpha != 1 or beta != 0 has not yet been "
"implemented. Please speak with the Tpetra developers.");
if (mode == Teuchos::NO_TRANS) {
applyNonTranspose (X,Y);
} else if (mode == Teuchos::TRANS || mode == Teuchos::CONJ_TRANS) {
applyTranspose (X, Y, mode);
} else {
TEUCHOS_TEST_FOR_EXCEPTION
(true, std::invalid_argument, prefix << "The 'mode' argument has an "
"invalid value " << mode << ". Valid values are Teuchos::NO_TRANS="
<< Teuchos::NO_TRANS << ", Teuchos::TRANS=" << Teuchos::TRANS << ", "
"and Teuchos::CONJ_TRANS=" << Teuchos::CONJ_TRANS << ".");
}
}
// ======================================================================
MultiVector Redistribute(const MultiVector& y, const int NumEquations)
{
StackPush();
if (y.GetMyLength() % NumEquations)
ML_THROW("NumEquations does not divide MyLength()", -1);
if (y.GetNumVectors() != 1)
ML_THROW("Redistribute() works with single vectors only", -1);
Space NewSpace(y.GetMyLength() / NumEquations);
MultiVector y2(NewSpace, NumEquations);
for (int i = 0 ; i < y2.GetMyLength() ; ++i)
for (int j = 0 ; j < NumEquations ; ++j)
y2(i, j) = y(j + NumEquations * i);
StackPop();
return(y2);
}
/** Construct a quaternion which represents a rotation of 'angle' around 'axis' */
MultiQuaternion::MultiQuaternion(const MultiDouble &angle, const MultiVector &axis)
{
//the unit quaternion can be represented by;
// Q = cos(theta) + u*sin(theta)
// which represents a rotation of 2*theta around the
// vector u
MultiFloat sintheta;
{
MultiFloat half_angle(angle);
half_angle *= 0.5;
MultiFloat costheta;
sincos(half_angle, sintheta, costheta);
sc[3] = costheta;
}
//the vector must be normalised
MultiVector norm = axis.normalise();
sc[0] = sintheta * axis.x();
sc[1] = sintheta * axis.y();
sc[2] = sintheta * axis.z();
}
