double AztecOO_StatusTestResNorm::ComputeNorm(const Epetra_Vector & vec, NormType typeofnorm) {
double result = 0.0;
if (typeofnorm==TwoNorm) vec.Norm2(&result);
else if (typeofnorm==OneNorm) vec.Norm1(&result);
else vec.NormInf(&result);
return(result);
}
//
// Calculate and print the 1-norm of the solution vector x along with the parameter value.
// Used to generate the solution graph
//
void HeqProblem::printSolution(const Epetra_Vector &x, const double conParam)
{
double n1; // temporary variable to hold the value of the norm
x.Norm1(&n1); // calculate the 1-norm of x
if (outputFilePtr) { // print out the values of c and ||x||_1
if (Comm->MyPID()==0) {
(*outputFilePtr) << conParam << " " << n1 << endl;
}
}
else
cout << "No output file!" << endl;
}
/******************************************************************
Compute weight balance
******************************************************************/
int compute_balance(const Epetra_Vector &wgts, double myGoalWeight,
double &min, double &max, double &avg)
{
if ((myGoalWeight < 0) || (myGoalWeight > 1.0)){
std::cerr << "compute_balance: Goal weight should be in the range [0, 1]" << std::endl;
return -1;
}
double weightTotal;
wgts.Norm1(&weightTotal);
double weightLocal = 0.0;
for (int i=0; i < wgts.MyLength(); i++){
weightLocal += wgts[i];
}
/* My degree of imbalance.
* If myGoalWeight is zero, I'm in perfect balance since I got what I wanted.
*/
double goalWeight = myGoalWeight * weightTotal;
double imbalance = 1.0;
if (myGoalWeight > 0.0){
if (weightLocal >= goalWeight)
imbalance += (weightLocal - goalWeight) / goalWeight;
else
imbalance += (goalWeight - weightLocal) / goalWeight;
}
const Epetra_Comm &comm = wgts.Comm();
comm.MaxAll(&imbalance, &max, 1);
comm.MinAll(&imbalance, &min, 1);
comm.SumAll(&imbalance, &avg, 1);
avg /= comm.NumProc();
return 0;
}
int TestOneMatrix( std::string HBname, std::string MMname, std::string TRIname, Epetra_Comm &Comm, bool verbose ) {
if ( Comm.MyPID() != 0 ) verbose = false ;
Epetra_Map * readMap = 0;
Epetra_CrsMatrix * HbA = 0;
Epetra_Vector * Hbx = 0;
Epetra_Vector * Hbb = 0;
Epetra_Vector * Hbxexact = 0;
Epetra_CrsMatrix * TriplesA = 0;
Epetra_Vector * Triplesx = 0;
Epetra_Vector * Triplesb = 0;
Epetra_Vector * Triplesxexact = 0;
Epetra_CrsMatrix * MatrixMarketA = 0;
Epetra_Vector * MatrixMarketx = 0;
Epetra_Vector * MatrixMarketb = 0;
Epetra_Vector * MatrixMarketxexact = 0;
int TRI_Size = TRIname.size() ;
std::string LastFiveBytes = TRIname.substr( EPETRA_MAX(0,TRI_Size-5), TRI_Size );
if ( LastFiveBytes == ".TimD" ) {
// Call routine to read in a file with a Tim Davis header and zero-based indexing
EPETRA_CHK_ERR( Trilinos_Util_ReadTriples2Epetra64( &TRIname[0], false, Comm,
readMap, TriplesA, Triplesx,
Triplesb, Triplesxexact, false, true, true ) );
delete readMap;
} else {
if ( LastFiveBytes == ".triU" ) {
// Call routine to read in unsymmetric Triplet matrix
EPETRA_CHK_ERR( Trilinos_Util_ReadTriples2Epetra64( &TRIname[0], false, Comm,
readMap, TriplesA, Triplesx,
Triplesb, Triplesxexact, false, false ) );
delete readMap;
} else {
if ( LastFiveBytes == ".triS" ) {
// Call routine to read in symmetric Triplet matrix
EPETRA_CHK_ERR( Trilinos_Util_ReadTriples2Epetra64( &TRIname[0], true, Comm,
readMap, TriplesA, Triplesx,
Triplesb, Triplesxexact, false, false ) );
delete readMap;
} else {
assert( false ) ;
}
}
}
EPETRA_CHK_ERR( Trilinos_Util_ReadMatrixMarket2Epetra64( &MMname[0], Comm, readMap,
MatrixMarketA, MatrixMarketx,
MatrixMarketb, MatrixMarketxexact) );
delete readMap;
// Call routine to read in HB problem
Trilinos_Util_ReadHb2Epetra64( &HBname[0], Comm, readMap, HbA, Hbx,
Hbb, Hbxexact) ;
#if 0
std::cout << " HbA " ;
HbA->Print( std::cout ) ;
std::cout << std::endl ;
std::cout << " MatrixMarketA " ;
MatrixMarketA->Print( std::cout ) ;
std::cout << std::endl ;
std::cout << " TriplesA " ;
TriplesA->Print( std::cout ) ;
std::cout << std::endl ;
#endif
int TripleErr = 0 ;
int MMerr = 0 ;
for ( int i = 0 ; i < 10 ; i++ )
{
double resid_Hb_Triples;
double resid_Hb_Matrix_Market;
double norm_A ;
Hbx->Random();
//
// Set the output vectors to different values:
//
Triplesb->PutScalar(1.1);
Hbb->PutScalar(1.2);
MatrixMarketb->PutScalar(1.3);
HbA->Multiply( false, *Hbx, *Hbb );
norm_A = HbA->NormOne( ) ;
TriplesA->Multiply( false, *Hbx, *Triplesb );
Triplesb->Update( 1.0, *Hbb, -1.0 ) ;
MatrixMarketA->Multiply( false, *Hbx, *MatrixMarketb );
MatrixMarketb->Update( 1.0, *Hbb, -1.0 ) ;
Triplesb->Norm1( &resid_Hb_Triples ) ;
MatrixMarketb->Norm1( &resid_Hb_Matrix_Market ) ;
TripleErr += ( resid_Hb_Triples > 1e-11 * norm_A ) ;
MMerr += ( resid_Hb_Matrix_Market > 1e-11 * norm_A ) ;
if ( verbose && resid_Hb_Triples > 1e-11 * norm_A )
std::cout << " resid_Hb_Triples = " << resid_Hb_Triples
<< " norm_A = " << norm_A << std::endl ;
if ( verbose && resid_Hb_Matrix_Market > 1e-11 * norm_A )
std::cout << " resid_Hb_Matrix_Market = " << resid_Hb_Matrix_Market
<< " norm_A = " << norm_A << std::endl ;
}
if ( verbose ) {
if ( TripleErr ) std::cout << " Error in reading " << HBname << " or " << TRIname << std::endl ;
if ( MMerr ) std::cout << " Error in reading " << HBname << " or " << MMname << std::endl ;
}
delete HbA;
delete Hbx;
delete Hbb;
delete Hbxexact;
delete TriplesA;
delete Triplesx;
delete Triplesb;
delete Triplesxexact;
delete MatrixMarketA;
delete MatrixMarketx;
delete MatrixMarketb;
delete MatrixMarketxexact;
delete readMap;
return TripleErr+MMerr ;
}
/*----------------------------------------------------------------------*
| Constructor (public) m.gee 01/05|
| IMPORTANT: |
| No matter on which level we are here, the vector xfine is ALWAYS |
| a fine grid vector here! |
| this is the constructor for the ismatrixfree==true case
*----------------------------------------------------------------------*/
ML_NOX::ML_Nox_NonlinearLevel::ML_Nox_NonlinearLevel(
int level, int nlevel, int printlevel, ML* ml,
ML_Aggregate* ag,Epetra_CrsMatrix** P,
ML_NOX::Ml_Nox_Fineinterface& interface,
const Epetra_Comm& comm, const Epetra_Vector& xfine,
bool ismatrixfree, bool isnlnCG, int nitersCG, bool broyden,
string fsmoothertype, string smoothertype, string coarsesolvetype,
int nsmooth_fine, int nsmooth, int nsmooth_coarse,
double conv_normF,
double conv_nupdate, int conv_maxiter,
int numPDE, int nullspdim, Epetra_CrsMatrix* Mat,
ML_NOX::Nox_CoarseProblem_Interface* coarseinterface)
: fineinterface_(interface),
comm_(comm)
{
level_ = level; // this level
nlevel_ = nlevel; // number of total levels
ml_printlevel_ = printlevel; // printlevel
ml_ = ml; // the global ML object
ag_ = ag; // the global ML_Aggregate object
thislevel_prec_ = 0; // this level's linear preconditioner
thislevel_ml_ = 0; // this level's local ML object
thislevel_ag_ = 0; // this level's local ML_Aggregate object
coarseinterface_ = coarseinterface; // this level's coarse interface
coarseprepost_ = 0;
xthis_ = 0; // this level's current solution matching this level's map!!!!
thislevel_A_ = 0; // this level's NOX Matrixfree operator
SmootherA_ = 0; // this level's Epetra_CrsMatrix for thislevel_prec_
ismatrixfree_ = ismatrixfree; // matrixfree flag
conv_normF_ = conv_normF; // NOX convergence test stuff
conv_nupdate_ = conv_nupdate;
conv_maxiter_ = conv_maxiter;
absresid_ = 0;
nupdate_ = 0;
fv_ = 0;
maxiters_ = 0;
combo1_ = 0;
combo2_ = 0;
thislevel_linSys_ = 0; // this level's NOX linear system
nlParams_ = 0; // NOX parameters
initialGuess_ = 0; // NOX initial guess
group_ = 0; // NOX group
solver_ = 0; // NOX solver
SmootherA_ = Mat;
isnlnCG_ = isnlnCG;
azlinSys_ = 0;
clone_ = 0;
nitersCG_ = nitersCG;
broyden_ = broyden;
Broyd_ = 0;
#if 0
if (isnlnCG_==false &&
(fsmoothertype == "Jacobi" ||
smoothertype == "Jacobi" ||
coarsesolvetype == "Jacobi" ))
{
cout << "**ERR**: ML_NOX::ML_Nox_NonlinearLevel::ML_Nox_NonlinearLevel:\n"
<< "**ERR**: Modified Newton's method not supported for \n"
<< "**ERR**: ismatrixfree_==true && smoothertype == Jacobi-Smoother\n"
<< "**ERR**: because no full Jacobian exists!\n"
<< "**ERR**: file/line: " << __FILE__ << "/" << __LINE__ << "\n"; throw -1;
}
#endif
if (ismatrixfree_==false)
{
cout << "**ERR**: ML_NOX::ML_Nox_NonlinearLevel::ML_Nox_NonlinearLevel:\n"
<< "**ERR**: ismatrixfree_==false on level " << level_ << "\n"
<< "**ERR**: in constructor for ismatrixfree_==true - case\n"
<< "**ERR**: file/line: " << __FILE__ << "/" << __LINE__ << "\n"; throw -1;
}
if (!coarseinterface_)
{
cout << "**ERR**: ML_NOX::ML_Nox_NonlinearLevel::ML_Nox_NonlinearLevel:\n"
<< "**ERR**: ptr to coarseinterface=NULL on level " << level_ << "\n"
<< "**ERR**: file/line: " << __FILE__ << "/" << __LINE__ << "\n"; throw -1;
}
if (!Mat)
{
cout << "**ERR**: ML_NOX::ML_Nox_NonlinearLevel::ML_Nox_NonlinearLevel:\n"
<< "**ERR**: ptr to Matrix Mat=NULL on level " << level_ << "\n"
<< "**ERR**: file/line: " << __FILE__ << "/" << __LINE__ << "\n"; throw -1;
}
// ------------------------------------------------------------------------
Mat->OptimizeStorage();
// ------------------------------------------------------------------------
// get the current solution to this level
xthis_ = coarseinterface_->restrict_fine_to_this(xfine);
// ------------------------------------------------------------------------
// create this level's preconditioner
// We use a 1-level ML-hierarchy for that
ML_Aggregate_Create(&thislevel_ag_);
ML_Create(&thislevel_ml_,1);
// ------------------------------------------------------------------------
// set the Jacobian on level 0 of the local ml
EpetraMatrix2MLMatrix(thislevel_ml_,0,
(dynamic_cast<Epetra_RowMatrix*>(Mat)));
// ------------------------------------------------------------------------
// construct a 1-level ML-hierarchy on this level as a smoother
// ------------------------------------------------------------------------
ML_Set_PrintLevel(ml_printlevel_);
ML_Aggregate_Set_CoarsenScheme_Uncoupled(thislevel_ag_);
ML_Aggregate_Set_DampingFactor(thislevel_ag_, 0.0);
ML_Aggregate_Set_Threshold(thislevel_ag_, 0.0);
ML_Aggregate_Set_MaxCoarseSize(thislevel_ag_,1);
ML_Aggregate_Set_NullSpace(thislevel_ag_,numPDE,nullspdim,NULL,Mat->NumMyRows());
int thislevel_nlevel = ML_Gen_MGHierarchy_UsingAggregation(thislevel_ml_,0,
ML_INCREASING,thislevel_ag_);
if (thislevel_nlevel != 1)
{
cout << "**ERR**: ML_NOX::ML_Nox_NonlinearLevel::ML_Nox_NonlinearLevel:\n"
<< "**ERR**: ML generated a local hierarchy of " << thislevel_nlevel << " on level " << level_ << "\n"
<< "**ERR**: this is supposed to be 1 Level only!\n"
<< "**ERR**: file/line: " << __FILE__ << "/" << __LINE__ << "\n"; throw -1;
}
// set the smoother
if (level_==0)
Set_Smoother(ml,ag,level_,nlevel,thislevel_ml_,thislevel_ag_,fsmoothertype,nsmooth_fine);
else if (level_ != nlevel_-1) // set the smoother from the input
Set_Smoother(ml,ag,level_,nlevel,thislevel_ml_,thislevel_ag_,smoothertype,nsmooth);
else // set the coarse solver from the input
Set_Smoother(ml,ag,level_,nlevel,thislevel_ml_,thislevel_ag_,coarsesolvetype,nsmooth_coarse);
// create this level's preconditioner class
ML_Epetra::MultiLevelOperator* ml_tmp = new ML_Epetra::MultiLevelOperator(
thislevel_ml_,comm_,
Mat->OperatorDomainMap(),
Mat->OperatorRangeMap());
thislevel_prec_ = new ML_NOX::ML_Nox_ConstrainedMultiLevelOperator(ml_tmp,*coarseinterface_);
if (!thislevel_prec_)
{
cout << "**ERR**: ML_NOX::ML_Nox_NonlinearLevel::ML_Nox_NonlinearLevel:\n"
<< "**ERR**: thislevel_prec_==NULL on level " << level_ << "\n"
<< "**ERR**: file/line: " << __FILE__ << "/" << __LINE__ << "\n"; throw -1;
}
// intensive test of this level's ML-smoother
#if 0
{
cout << "Test of smoother on level " << level_ << endl;
Epetra_Vector *out = new Epetra_Vector(Copy,*xthis_,0);
out->PutScalar(0.0);
cout << "Input\n";
xthis_->PutScalar(1.0);
Mat->Multiply(false,*xthis_,*out);
xthis_->PutScalar(3.0);
cout << "rhs\n";
cout << *out;
double norm = 0.0;
out->Norm1(&norm);
cout << "Norm of rhs = " << norm << endl;
thislevel_prec_->ApplyInverse(*out,*xthis_);
cout << "result after smoother\n";
cout << *xthis_;
delete out; out = 0;
}
if (level_==2) exit(0);
#endif
// ------------------------------------------------------------------------
// generate this level's coarse prepostoperator
if (level_==0)
coarseprepost_ = new ML_NOX::Ml_Nox_CoarsePrePostOperator(*coarseinterface_,
fineinterface_);
// ------------------------------------------------------------------------
// set up NOX on this level
// ------------------------------------------------------------------------
nlParams_ = new Teuchos::ParameterList();
Teuchos::ParameterList& printParams = nlParams_->sublist("Printing");
printParams.setParameter("MyPID", comm_.MyPID());
printParams.setParameter("Output Precision", 9);
printParams.setParameter("Output Processor", 0);
if (ml_printlevel_>9)
printParams.setParameter("Output Information",
NOX::Utils::OuterIteration +
//NOX::Utils::OuterIterationStatusTest +
//NOX::Utils::InnerIteration +
//NOX::Utils::Parameters +
//NOX::Utils::Details +
NOX::Utils::Warning);
else if (ml_printlevel_>8)
printParams.setParameter("Output Information",
NOX::Utils::Warning);
else
printParams.setParameter("Output Information",0);
if (level_==0)
nlParams_->sublist("Solver Options").setParameter("User Defined Pre/Post Operator", *coarseprepost_);
nlParams_->setParameter("Nonlinear Solver", "Line Search Based");
Teuchos::ParameterList& searchParams = nlParams_->sublist("Line Search");
Teuchos::ParameterList* lsParamsptr = 0;
if (isnlnCG_)
{
searchParams.setParameter("Method", "NonlinearCG");
Teuchos::ParameterList& dirParams = nlParams_->sublist("Direction");
dirParams.setParameter("Method", "NonlinearCG");
Teuchos::ParameterList& nlcgParams = dirParams.sublist("Nonlinear CG");
nlcgParams.setParameter("Restart Frequency", 10);
nlcgParams.setParameter("Precondition", "On");
nlcgParams.setParameter("Orthogonalize", "Polak-Ribiere");
//nlcgParams.setParameter("Orthogonalize", "Fletcher-Reeves");
Teuchos::ParameterList& lsParams = nlcgParams.sublist("Linear Solver");
lsParams.setParameter("Aztec Solver", "CG");
lsParams.setParameter("Max Iterations", 1);
lsParams.setParameter("Tolerance", 1e-11);
lsParams.setParameter("Output Frequency", 0);
lsParams.setParameter("Preconditioning", "User Supplied Preconditioner");
lsParams.setParameter("Preconditioner","User Defined");
}
else // Newton's method using ML-preconditioned Aztec as linear solver
{
searchParams.setParameter("Method", "Full Step");
// Sublist for direction
Teuchos::ParameterList& dirParams = nlParams_->sublist("Direction");
dirParams.setParameter("Method", "Newton");
Teuchos::ParameterList& newtonParams = dirParams.sublist("Newton");
newtonParams.setParameter("Forcing Term Method", "Constant");
//newtonParams.setParameter("Forcing Term Method", "Type 1");
//newtonParams.setParameter("Forcing Term Method", "Type 2");
newtonParams.setParameter("Forcing Term Minimum Tolerance", 1.0e-6);
newtonParams.setParameter("Forcing Term Maximum Tolerance", 0.1);
Teuchos::ParameterList& lsParams = newtonParams.sublist("Linear Solver");
lsParamsptr = &lsParams;
lsParams.setParameter("Aztec Solver", "CG");
lsParams.setParameter("Max Iterations", nitersCG_);
lsParams.setParameter("Tolerance", conv_normF_); // FIXME? is this correct?
if (ml_printlevel_>8)
lsParams.setParameter("Output Frequency", 50);
else
lsParams.setParameter("Output Frequency", 0);
lsParams.setParameter("Preconditioning", "User Supplied Preconditioner");
lsParams.setParameter("Preconditioner","User Defined");
}
// create the initial guess
initialGuess_ = new NOX::Epetra::Vector(*xthis_, NOX::DeepCopy, true);
// NOTE: do not delete xthis_, it's used and destroyed by initialGuess_
// create the necessary interfaces
NOX::EpetraNew::Interface::Preconditioner* iPrec = 0;
NOX::EpetraNew::Interface::Required* iReq = 0;
NOX::EpetraNew::Interface::Jacobian* iJac = 0;
if (isnlnCG_)
{
// create the matrixfree operator used in the nlnCG
thislevel_A_ = new NOX::EpetraNew::MatrixFree(*coarseinterface_,*xthis_,false);
// create the necessary interfaces
iPrec = 0;
iReq = coarseinterface_;
iJac = thislevel_A_;
// create the linear system
thislevel_linSys_ = new ML_NOX::Ml_Nox_LinearSystem(
*iJac,*thislevel_A_,*iPrec,
coarseinterface_,*thislevel_prec_,
*xthis_,ismatrixfree_,level_,ml_printlevel_);
// create the group
group_ = new NOX::EpetraNew::Group(printParams,*iReq,*initialGuess_,*thislevel_linSys_);
}
else // Modified Newton's method
{
if (!broyden_)
{
// create the necessary interfaces
iPrec = this;
iReq = coarseinterface_;
iJac = this;
// create the initial guess vector
clone_ = new Epetra_Vector(*xthis_);
// create the linear system
azlinSys_ = new NOX::EpetraNew::LinearSystemAztecOO(
printParams,*lsParamsptr,
*iJac,*SmootherA_,*iPrec,
*thislevel_prec_,*clone_);
}
else
{
// create the initial guess vector
clone_ = new Epetra_Vector(*xthis_);
// create the necessary interfaces
iPrec = this;
iReq = coarseinterface_;
Broyd_ = new NOX::EpetraNew::BroydenOperator(*nlParams_,*clone_,
*SmootherA_,false);
// create the linear system
azlinSys_ = new NOX::EpetraNew::LinearSystemAztecOO(
printParams,*lsParamsptr,
*Broyd_,*SmootherA_,*iPrec,
*thislevel_prec_,*clone_);
}
// create the group
group_ = new NOX::EpetraNew::Group(printParams,*iReq,*initialGuess_,*azlinSys_);
}
// create convergence test
create_Nox_Convergencetest(conv_normF_,conv_nupdate_,conv_maxiter_);
// create the solver
solver_ = new NOX::Solver::Manager(*group_,*combo2_,*nlParams_);
return;
}