Teuchos::RCP<Tpetra::Operator<Scalar,LocalOrdinal,GlobalOrdinal,Node> >
build_precond(Teuchos::ParameterList& test_params,
const Teuchos::RCP<const Tpetra::CrsMatrix<Scalar,LocalOrdinal,GlobalOrdinal,Node,LocalMatOps> >& A)
{
Teuchos::Time timer("precond");
typedef Ifpack2::Preconditioner<Scalar,LocalOrdinal,GlobalOrdinal,Node> Tprec;
Teuchos::RCP<Tprec> prec;
Ifpack2::Factory factory;
std::string prec_name("not specified");
Ifpack2::getParameter(test_params, "Ifpack2::Preconditioner", prec_name);
prec = factory.create(prec_name, A);
Teuchos::ParameterList tif_params;
if (test_params.isSublist("Ifpack2")) {
tif_params = test_params.sublist("Ifpack2");
}
if (A->getRowMap()->getComm()->getRank() == 0) {
std::cout << "Configuring/Initializing/Computing Ifpack2 preconditioner..."
<< std::endl;
}
prec->setParameters(tif_params);
prec->initialize();
timer.start();
prec->compute();
timer.stop();
if (A->getRowMap()->getComm()->getRank() == 0) {
std::cout << "... Finished Computing Ifpack2 preconditioner (time: "<<timer.totalElapsedTime() << "s)"
<< std::endl;
}
typedef typename Teuchos::ScalarTraits<Scalar>::magnitudeType magnitudeType;
magnitudeType condest = prec->computeCondEst(Ifpack2::Cheap);
if (A->getRowMap()->getComm()->getRank() == 0) {
std::cout << "Condition estimate(cheap) for preconditioner on proc 0: "
<< condest << std::endl;
}
return prec;
}
void PeridigmNS::HorizonManager::loadHorizonInformationFromBlockParameters(Teuchos::ParameterList& blockParams) {
// Find the horizon value for each block and record the default horizon value (if any)
for(Teuchos::ParameterList::ConstIterator it = blockParams.begin() ; it != blockParams.end() ; it++){
Teuchos::ParameterList& params = blockParams.sublist(it->first);
bool hasConstantHorizon = params.isType<double>("Horizon");
bool hasVariableHorizon = params.isType<string>("Horizon");
TEUCHOS_TEST_FOR_EXCEPT_MSG(hasConstantHorizon && hasVariableHorizon, "\n**** Error parsing horizon information! Multiple horizon definitions found!\n");
TEUCHOS_TEST_FOR_EXCEPT_MSG(!hasConstantHorizon && !hasVariableHorizon, "\n**** Error parsing horizon information! No horizon definition found!\n");
// Record the horizon as a string regardless of whether or not it is constant
string horizonString;
if(hasConstantHorizon){
double constantHorizon = params.get<double>("Horizon");
stringstream horizonStringStream;
horizonStringStream.precision(16);
horizonStringStream << constantHorizon;
horizonString = horizonStringStream.str();
}
else{
horizonString = params.get<string>("Horizon");
}
// Parse space-delimited list of block names
string blockNamesString = params.get<string>("Block Names");
istringstream iss(blockNamesString);
vector<string> blockNames;
copy(istream_iterator<string>(iss),
istream_iterator<string>(),
back_inserter<vector<string> >(blockNames));
for(vector<string>::const_iterator it = blockNames.begin() ; it != blockNames.end() ; ++it){
if( *it == "Default" || *it == "default" || *it == "DEFAULT" ){
horizonIsConstant["default"] = hasConstantHorizon;
horizonStrings["default"] = horizonString;
}
else{
horizonIsConstant[*it] = hasConstantHorizon;
horizonStrings[*it] = horizonString;
}
}
}
}
inline Teuchos::RCP<RiskMeasure<Real> > RiskMeasureFactory(Teuchos::ParameterList &parlist) {
std::string dist = parlist.sublist("SOL").sublist("Risk Measure").get("Name","CVaR");
ERiskMeasure ed = StringToERiskMeasure(dist);
switch(ed) {
case RISKMEASURE_CVAR:
return Teuchos::rcp(new CVaR<Real>(parlist));
case RISKMEASURE_EXPUTILITY:
return Teuchos::rcp(new ExpUtility<Real>(parlist));
case RISKMEASURE_HMCR:
return Teuchos::rcp(new HMCR<Real>(parlist));
case RISKMEASURE_MEANDEVIATIONFROMTARGET:
return Teuchos::rcp(new MeanDeviationFromTarget<Real>(parlist));
case RISKMEASURE_MEANDEVIATION:
return Teuchos::rcp(new MeanDeviation<Real>(parlist));
case RISKMEASURE_MEANVARIANCEFROMTARGET:
return Teuchos::rcp(new MeanVarianceFromTarget<Real>(parlist));
case RISKMEASURE_MEANVARIANCE:
return Teuchos::rcp(new MeanVariance<Real>(parlist));
case RISKMEASURE_MOREAUYOSIDACVAR:
return Teuchos::rcp(new MoreauYosidaCVaR<Real>(parlist));
case RISKMEASURE_LOGEXPONENTIALQUADRANGLE:
return Teuchos::rcp(new LogExponentialQuadrangle<Real>(parlist));
case RISKMEASURE_LOGQUANTILEQUADRANGLE:
return Teuchos::rcp(new LogQuantileQuadrangle<Real>(parlist));
case RISKMEASURE_MIXEDQUANTILEQUADRANGLE:
return Teuchos::rcp(new MixedQuantileQuadrangle<Real>(parlist));
case RISKMEASURE_QUANTILEQUADRANGLE:
return Teuchos::rcp(new QuantileQuadrangle<Real>(parlist));
case RISKMEASURE_QUANTILERADIUSQUADRANGLE:
return Teuchos::rcp(new QuantileRadiusQuadrangle<Real>(parlist));
case RISKMEASURE_SMOOTHEDWORSTCASEQUADRANGLE:
return Teuchos::rcp(new SmoothedWorstCaseQuadrangle<Real>(parlist));
case RISKMEASURE_TRUNCATEDMEANQUADRANGLE:
return Teuchos::rcp(new TruncatedMeanQuadrangle<Real>(parlist));
case RISKMEASURE_CHI2DIVERGENCE:
return Teuchos::rcp(new Chi2Divergence<Real>(parlist));
case RISKMEASURE_KLDIVERGENCE:
return Teuchos::rcp(new KLDivergence<Real>(parlist));
default:
TEUCHOS_TEST_FOR_EXCEPTION(true,std::logic_error,
"Invalid risk measure type" << dist);
}
}
bool NOX::Epetra::LinearSystemMPBD::
applyJacobianInverse(Teuchos::ParameterList ¶ms,
const NOX::Epetra::Vector &input,
NOX::Epetra::Vector &result)
{
TEUCHOS_FUNC_TIME_MONITOR("Total deterministic solve Time");
// Extract blocks
EpetraExt::BlockVector input_block(View, *base_map,
input.getEpetraVector());
EpetraExt::BlockVector result_block(View, *base_map,
result.getEpetraVector());
result_block.PutScalar(0.0);
Teuchos::ParameterList& block_solver_params =
params.sublist("Deterministic Solver Parameters");
// Solve block linear systems
bool final_status = true;
bool status;
for (int i=0; i<num_mp_blocks; i++) {
NOX::Epetra::Vector nox_input(input_block.GetBlock(i),
NOX::Epetra::Vector::CreateView);
NOX::Epetra::Vector nox_result(result_block.GetBlock(i),
NOX::Epetra::Vector::CreateView);
block_solver->setJacobianOperatorForSolve(block_ops->getCoeffPtr(i));
if (precStrategy == STANDARD)
block_solver->setPrecOperatorForSolve(precs[i]);
else if (precStrategy == ON_THE_FLY) {
block_solver->createPreconditioner(*(prec_x->GetBlock(i)),
block_solver_params, false);
}
status = block_solver->applyJacobianInverse(block_solver_params, nox_input,
nox_result);
final_status = final_status && status;
}
return final_status;
}
int main(int argc, char *argv[]) {
bool success = false;
bool verbose = false;
try {
// Set up the printing utilities
Teuchos::ParameterList noxParams;
Teuchos::ParameterList& printParams = noxParams.sublist("Printing");
printParams.set("Output Precision", 5);
if (argc > 1) {
if (argv[1][0]=='-' && argv[1][1]=='v')
printParams.set("Output Information",
NOX::Utils::OuterIteration +
NOX::Utils::OuterIterationStatusTest +
NOX::Utils::InnerIteration +
NOX::Utils::Parameters +
NOX::Utils::Details +
NOX::Utils::Warning +
NOX::Utils::TestDetails);
else
printParams.set("Output Information", NOX::Utils::Error);
}
NOX::Utils printing(printParams);
// Identify the test
if (printing.isPrintType(NOX::Utils::TestDetails)) {
std::cout << "Starting lapack/NOX_NewTest/NOX_NewTest.exe" << std::endl;
}
// *** Insert your testing here! ***
success = true;
if (success)
std::cout << "Test passed!" << std::endl;
else
std::cout << "Test failed!" << std::endl;
}
TEUCHOS_STANDARD_CATCH_STATEMENTS(verbose, std::cerr, success);
return ( success ? EXIT_SUCCESS : EXIT_FAILURE );
}
Teuchos::RCP<Belos::SolverManager<Scalar,MV,OP> >
build_solver(const Teuchos::RCP<const Teuchos::Comm<int> > &comm,
Teuchos::ParameterList& test_params,
Teuchos::RCP<Belos::LinearProblem<Scalar,MV,OP> > problem)
{
typedef Belos::LinearProblem<Scalar,MV,OP> BLinProb;
Teuchos::RCP<Belos::SolverManager<Scalar,MV,OP> > solver;
Teuchos::ParameterList bparams;
if (test_params.isSublist("Belos")) {
bparams = test_params.sublist("Belos");
}
Teuchos::RCP<Teuchos::ParameterList> rcpparams = Teuchos::rcpFromRef(bparams);
std::string solver_type("not specified");
Ifpack2::getParameter(test_params, "solver_type", solver_type);
if (solver_type == "BlockGmres") {
// if (comm->getRank() == 0) std::cout << *rcpparams << std::endl;
solver = Teuchos::rcp(new Belos::BlockGmresSolMgr<Scalar,MV,OP>(problem,rcpparams));
}
// else if (solver_type == "PseudoBlockGmres") {
// solver = Teuchos::rcp(new Belos::PseudoBlockGmresSolMgr<Scalar,MV,OP>(problem,rcpparams));
// }
// else if (solver_type == "PseudoBlockCG") {
// solver = Teuchos::rcp(new Belos::PseudoBlockCGSolMgr<Scalar,MV,OP>(problem,rcpparams));
// }
// else if (solver_type == "TFQMR") {
// solver = Teuchos::rcp(new Belos::TFQMRSolMgr<Scalar,MV,OP>(problem,rcpparams));
// }
else if (solver_type == "not specified") {
throw std::runtime_error("Error in build_solver: solver_type not specified.");
}
else {
std::ostringstream os;
os << "Error in build_solver: solver_type ("<<solver_type<<") not recognized.";
os << "\nIfpack2's test-driver recognizes these solvers: PseudoBlockCG, PesudoBlockGmres, BlockGmres, TFQMR.";
std::string str = os.str();
throw std::runtime_error(str);
}
return solver;
}
int main(int argc, char *argv[]) {
// Set up the printing utilities
Teuchos::ParameterList noxParams;
Teuchos::ParameterList& printParams = noxParams.sublist("Printing");
printParams.set("Output Precision", 5);
if (argc > 1) {
if (argv[1][0]=='-' && argv[1][1]=='v')
printParams.set("Output Information",
NOX::Utils::OuterIteration +
NOX::Utils::OuterIterationStatusTest +
NOX::Utils::InnerIteration +
NOX::Utils::Parameters +
NOX::Utils::Details +
NOX::Utils::Warning +
NOX::Utils::TestDetails);
else
printParams.set("Output Information", NOX::Utils::Error);
}
NOX::Utils printing(printParams);
// Identify the test
if (printing.isPrintType(NOX::Utils::TestDetails)) {
cout << "Starting lapack/NOX_NewTest/NOX_NewTest.exe" << endl;
}
// Final return value (0 = succefull, non-zero = failure)
int status = 0;
// *** Insert your testing here! ***
if (status == 0)
cout << "Test passed!" << endl;
else
cout << "Test failed!" << endl;
// Final return value (0 = succefull, non-zero = failure)
return status;
}
bool
BroydenOperator::initialize( Teuchos::ParameterList & nlParams, const Epetra_Vector & vec )
{
stepVec = Teuchos::rcp( new NOX::Epetra::Vector(vec) );
yieldVec = Teuchos::rcp( new NOX::Epetra::Vector(vec) );
workVec = Teuchos::rcp( new NOX::Epetra::Vector(vec) );
oldX = Teuchos::rcp( new NOX::Epetra::Vector(vec) );
oldF = Teuchos::rcp( new NOX::Epetra::Vector(vec) );
// Set ourself as the Pre/Post Operator so we can update our data during
// runPostIterate. Note: we need to make provision for storing and calling
// any existing Pre/Post Operator.
// RPP 9/20/2005: This is a very bad idea! It breaks the rcp and
// user's expectations. For now we will have to create rcp without
// ownership. What happens if a user write their own PPO?
Teuchos::RCP<NOX::Abstract::PrePostOperator> me = Teuchos::rcp(this, false);
nlParams.sublist("Solver Options").set("User Defined Pre/Post Operator", me);
return true;
}
void xmlToModelPList(const Teuchos::XMLObject &xml, Teuchos::ParameterList & plist)
{
// This method composes a plist for the problem
Teuchos::XMLParameterListReader reader;
plist = reader.toParameterList(xml);
// Get list of valid Zoltan2 Parameters
// Zoltan 2 parameters appear in the input file
// Right now we have default values stored in
// the parameter list, we would like to apply
// the options specified by the user in their
// input file
Teuchos::ParameterList zoltan2Parameters;
Zoltan2::createAllParameters(zoltan2Parameters);
if (plist.isSublist("Zoltan2Parameters")) {
// Apply user specified zoltan2Parameters
ParameterList &sub = plist.sublist("Zoltan2Parameters");
zoltan2Parameters.setParameters(sub);
}
}
TEUCHOS_UNIT_TEST(bc, dirichlet_complete_param_list)
{
Teuchos::ParameterList p;
p.set("Type", "Dirichlet");
p.set("Sideset ID", "4");
p.set("Element Block ID", "fluid");
p.set("Equation Set Name", "UX");
p.set("Strategy", "Constant");
p.sublist("Data").set("Value",1.0);
panzer::BC bc(0,p);
TEST_EQUALITY(bc.bcID(), 0);
TEST_EQUALITY(bc.bcType(), BCT_Dirichlet);
TEST_EQUALITY(bc.sidesetID(), "4");
TEST_EQUALITY(bc.elementBlockID(), "fluid");
TEST_EQUALITY(bc.equationSetName(), "UX");
std::stringstream s;
s << bc << std::endl;
}
bool NOX::Epetra::LinearSystemMPBD::
recomputePreconditioner(const NOX::Epetra::Vector& x,
Teuchos::ParameterList& p) const
{
EpetraExt::BlockVector mp_x_block(View, *base_map, x.getEpetraVector());
Teuchos::ParameterList& solverParams =
p.sublist("Deterministic Solver Parameters");
bool total_success = true;
if (precStrategy == STANDARD) {
for (int i=0; i<num_mp_blocks; i++) {
block_solver->setJacobianOperatorForSolve(block_ops->getCoeffPtr(i));
if (precs[i] != Teuchos::null)
block_solver->setPrecOperatorForSolve(precs[i]);
bool success =
block_solver->recomputePreconditioner(*(mp_x_block.GetBlock(i)),
solverParams);
precs[i] = block_solver->getGeneratedPrecOperator();
total_success = total_success && success;
}
}
else if (precStrategy == MEAN) {
block_solver->setJacobianOperatorForSolve(block_ops->getCoeffPtr(0));
bool success =
block_solver->recomputePreconditioner(*(mp_x_block.GetBlock(0)),
solverParams);
total_success = total_success && success;
}
else if (precStrategy == ON_THE_FLY) {
if (prec_x == Teuchos::null)
prec_x = Teuchos::rcp(new EpetraExt::BlockVector(mp_x_block));
else
*prec_x = mp_x_block;
}
return total_success;
}
/** \brief Constructor.
Constructor to build a NewtonKrylovStep object with user-defined
secant and Krylov objects. Algorithmic specifications are passed in through
a Teuchos::ParameterList.
@param[in] parlist is a parameter list containing algorithmic specifications
@param[in] krylov is a user-defined Krylov object
@param[in] secant is a user-defined secant object
*/
NewtonKrylovStep(Teuchos::ParameterList &parlist,
const Teuchos::RCP<Krylov<Real> > &krylov,
const Teuchos::RCP<Secant<Real> > &secant,
const bool computeObj = true)
: Step<Real>(), secant_(secant), krylov_(krylov),
ekv_(KRYLOV_USERDEFINED), esec_(SECANT_USERDEFINED),
gp_(Teuchos::null), iterKrylov_(0), flagKrylov_(0),
verbosity_(0), computeObj_(computeObj), useSecantPrecond_(false) {
// Parse ParameterList
Teuchos::ParameterList& Glist = parlist.sublist("General");
useSecantPrecond_ = Glist.sublist("Secant").get("Use as Preconditioner", false);
verbosity_ = Glist.get("Print Verbosity",0);
// Initialize secant object
if ( useSecantPrecond_ && secant_ == Teuchos::null ) {
esec_ = StringToESecant(Glist.sublist("Secant").get("Type","Limited-Memory BFGS"));
secant_ = SecantFactory<Real>(parlist);
}
// Initialize Krylov object
if ( krylov_ == Teuchos::null ) {
ekv_ = StringToEKrylov(Glist.sublist("Krylov").get("Type","Conjugate Gradients"));
krylov_ = KrylovFactory<Real>(parlist);
}
}
// ************************************************************************
// ************************************************************************
Teuchos::RCP<LOCA::StatusTest::Abstract> LOCA::StatusTest::Factory::
buildComboTest(Teuchos::ParameterList& p,
const Teuchos::RCP<const LOCA::GlobalData> & globalData,
std::map<std::string, Teuchos::RCP<LOCA::StatusTest::Abstract> >*
tagged_tests) const
{
int number_of_tests = get<int>(p, "Number of Tests");
std::string combo_type_string = get<std::string>(p, "Combo Type");
LOCA::StatusTest::Combo::ComboType combo_type;
if (combo_type_string == "AND")
combo_type = LOCA::StatusTest::Combo::AND;
else if (combo_type_string == "OR")
combo_type = LOCA::StatusTest::Combo::OR;
else{
std::string msg =
"Error - The \"Combo Type\" must be \"AND\" or \"OR\"!";
TEST_FOR_EXCEPTION(true, std::logic_error, msg);
}
RCP<LOCA::StatusTest::Combo> combo_test =
rcp(new LOCA::StatusTest::Combo(combo_type, globalData));
for (int i=0; i < number_of_tests; ++i) {
ostringstream subtest_name;
subtest_name << "Test " << i;
ParameterList& subtest_list = p.sublist(subtest_name.str(), true);
RCP<LOCA::StatusTest::Abstract> subtest =
this->buildStatusTests(subtest_list, globalData, tagged_tests);
combo_test->addStatusTest(subtest);
}
return combo_test;
}
int Amesos_Scalapack::SetParameters( Teuchos::ParameterList &ParameterList ) {
if( debug_ == 1 ) std::cout << "Entering `SetParameters()'" << std::endl;
// retrive general parameters
SetStatusParameters( ParameterList );
SetControlParameters( ParameterList );
//
// We have to set these to their defaults here because user codes
// are not guaranteed to have a "Scalapack" parameter list.
//
TwoD_distribution_ = true;
grid_nb_ = 32;
// Some compilers reject the following cast:
// if( &ParameterList == 0 ) return 0;
// ========================================= //
// retrive ScaLAPACK's parameters from list. //
// ========================================= //
// retrive general parameters
// check to see if they exist before trying to retrieve them
if (ParameterList.isSublist("Scalapack") ) {
const Teuchos::ParameterList ScalapackParams = ParameterList.sublist("Scalapack") ;
// Fix Bug #3251
if ( ScalapackParams.isParameter("2D distribution") )
TwoD_distribution_ = ScalapackParams.get<bool>("2D distribution");
if ( ScalapackParams.isParameter("grid_nb") )
grid_nb_ = ScalapackParams.get<int>("grid_nb");
}
return 0;
}
// ************************************************************************
// ************************************************************************
Teuchos::RCP<NOX::StatusTest::Generic> NOX::StatusTest::Factory::
buildComboTest(Teuchos::ParameterList& p, const NOX::Utils& u,
std::map<std::string, Teuchos::RCP<NOX::StatusTest::Generic> >*
tagged_tests) const
{
int number_of_tests = get<int>(p, "Number of Tests");
std::string combo_type_string = get<std::string>(p, "Combo Type");
NOX::StatusTest::Combo::ComboType combo_type;
if (combo_type_string == "AND")
combo_type = NOX::StatusTest::Combo::AND;
else if (combo_type_string == "OR")
combo_type = NOX::StatusTest::Combo::OR;
else{
std::string msg =
"Error - The \"Combo Type\" must be \"AND\" or \"OR\"!";
TEUCHOS_TEST_FOR_EXCEPTION(true, std::logic_error, msg);
}
RCP<NOX::StatusTest::Combo> combo_test =
rcp(new NOX::StatusTest::Combo(combo_type, &u));
for (int i=0; i < number_of_tests; ++i) {
std::ostringstream subtest_name;
subtest_name << "Test " << i;
ParameterList& subtest_list = p.sublist(subtest_name.str(), true);
RCP<NOX::StatusTest::Generic> subtest =
this->buildStatusTests(subtest_list, u, tagged_tests);
combo_test->addStatusTest(subtest);
}
return combo_test;
}
GMRES( Teuchos::ParameterList &parlist ) : isInitialized_(false) {
using Teuchos::RCP;
using Teuchos::rcp;
using std::vector;
Teuchos::ParameterList &gList = parlist.sublist("General");
Teuchos::ParameterList &kList = gList.sublist("Krylov");
useInexact_ = gList.get("Inexact Hessian-Times-A-Vector",false);
maxit_ = kList.get("Iteration Limit",50);
absTol_ = kList.get("Absolute Tolerance", 1.e-4);
relTol_ = kList.get("Relative Tolerance", 1.e-2);
useInitialGuess_ = kList.get("Use Initial Guess",false);
H_ = rcp( new SDMatrix( maxit_+1, maxit_ ) );
cs_ = rcp( new SDVector( maxit_ ) );
sn_ = rcp( new SDVector( maxit_ ) );
s_ = rcp( new SDVector( maxit_+1 ) );
y_ = rcp( new SDVector( maxit_+1 ) );
cnorm_ = rcp( new SDVector( maxit_ ) );
res_ = rcp( new std::vector<Real>(maxit_+1,0.0) );
}
inline Teuchos::RCP<Distribution<Real> > DistributionFactory(Teuchos::ParameterList &parlist) {
std::string dist = parlist.sublist("Distribution").get("Name","Dirac");
EDistribution ed = StringToEDistribution(dist);
switch(ed) {
case DISTRIBUTION_ARCSINE: return Teuchos::rcp(new Arcsine<Real>(parlist));
case DISTRIBUTION_BETA: return Teuchos::rcp(new Beta<Real>(parlist));
case DISTRIBUTION_CAUCHY: return Teuchos::rcp(new Cauchy<Real>(parlist));
case DISTRIBUTION_DIRAC: return Teuchos::rcp(new Dirac<Real>(parlist));
case DISTRIBUTION_EXPONENTIAL: return Teuchos::rcp(new Exponential<Real>(parlist));
case DISTRIBUTION_GAMMA: return Teuchos::rcp(new Gamma<Real>(parlist));
case DISTRIBUTION_GAUSSIAN: return Teuchos::rcp(new Gaussian<Real>(parlist));
case DISTRIBUTION_KUMARASWAMY: return Teuchos::rcp(new Kumaraswamy<Real>(parlist));
case DISTRIBUTION_LAPLACE: return Teuchos::rcp(new Laplace<Real>(parlist));
case DISTRIBUTION_LOGISTIC: return Teuchos::rcp(new Logistic<Real>(parlist));
case DISTRIBUTION_PARABOLIC: return Teuchos::rcp(new Parabolic<Real>(parlist));
case DISTRIBUTION_RAISEDCOSINE: return Teuchos::rcp(new RaisedCosine<Real>(parlist));
case DISTRIBUTION_SMALE: return Teuchos::rcp(new Smale<Real>(parlist));
case DISTRIBUTION_TRIANGLE: return Teuchos::rcp(new Triangle<Real>(parlist));
case DISTRIBUTION_TRUNCATEDEXPONENTIAL: return Teuchos::rcp(new TruncatedExponential<Real>(parlist));
case DISTRIBUTION_TRUNCATEDGAUSSIAN: return Teuchos::rcp(new TruncatedGaussian<Real>(parlist));
case DISTRIBUTION_UNIFORM: return Teuchos::rcp(new Uniform<Real>(parlist));
default: return Teuchos::null;
}
}
int main(int argc, char *argv[]) {
// Set up the printing utilities
Teuchos::ParameterList noxParams;
Teuchos::ParameterList& printParams = noxParams.sublist("Printing");
printParams.set("Output Precision", 5);
if (argc > 1) {
if (argv[1][0]=='-' && argv[1][1]=='v')
printParams.set("Output Information",
NOX::Utils::OuterIteration +
NOX::Utils::OuterIterationStatusTest +
NOX::Utils::InnerIteration +
NOX::Utils::Parameters +
NOX::Utils::Details +
NOX::Utils::Warning +
NOX::Utils::TestDetails);
else
printParams.set("Output Information", NOX::Utils::Error);
}
NOX::Utils printing(printParams);
if (printing.isPrintType(NOX::Utils::TestDetails)) {
cout << "Starting lapack/NOX_Group/NOX_Group.exe" << endl;
}
int status = 0;
// Begin real testing here!
if (status == 0)
cout << "Test passed!" << endl;
else
cout << "Test failed!" << endl;
// 0 is success
return status;
}
void tLSCIntegrationTest::solveList(Teuchos::ParameterList & paramList,int vcycles)
{
paramList.set("Linear Solver Type","AztecOO");
paramList.sublist("Linear Solver Types")
.sublist("AztecOO").sublist("Forward Solve").set("Max Iterations",500);
paramList.sublist("Linear Solver Types")
.sublist("AztecOO").sublist("Forward Solve").set("Tolerance",1e-12);
paramList.sublist("Linear Solver Types")
.sublist("AztecOO").sublist("Forward Solve").sublist("AztecOO Settings").set("Aztec Solver","GMRES");
paramList.sublist("Linear Solver Types")
.sublist("AztecOO").sublist("Forward Solve").sublist("AztecOO Settings").set("Size of Krylov Subspace",500);
paramList.sublist("Linear Solver Types")
.sublist("AztecOO").sublist("Forward Solve").sublist("AztecOO Settings").set("Output Frequency",0);
paramList.set("Preconditioner Type","ML");
Teuchos::ParameterList & MLList = paramList.sublist("Preconditioner Types").sublist("ML").sublist("ML Settings");
// set default values for smoothed aggregation in MLList
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("max levels",6);
MLList.set("cycle applications",vcycles);
MLList.set("coarse: type","Amesos-KLU");
}
int main(int argc, char** argv) {
int fail = 0, dim=0;
#ifdef HAVE_MPI
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &localProc);
MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
const Epetra_MpiComm Comm(MPI_COMM_WORLD);
#else
const Epetra_SerialComm Comm;
#endif
// =============================================================
// get command line options
// =============================================================
Teuchos::CommandLineProcessor clp(false,true);
std::string *inputFile = new std::string("simple.coords");
bool verbose = false;
clp.setOption( "f", inputFile, "Name of coordinate input file");
clp.setOption( "v", "q", &verbose,
"Display coordinates and weights before and after partitioning.");
Teuchos::CommandLineProcessor::EParseCommandLineReturn parse_return =
clp.parse(argc,argv);
if( parse_return == Teuchos::CommandLineProcessor::PARSE_HELP_PRINTED){
#ifdef HAVE_MPI
MPI_Finalize();
#endif
return 0;
}
if( parse_return != Teuchos::CommandLineProcessor::PARSE_SUCCESSFUL ) {
#ifdef HAVE_MPI
MPI_Finalize();
#endif
return 1;
}
// =============================================================
// Open file of coordinates and distribute them across processes
// so they are unbalanced.
// =============================================================
Epetra_MultiVector *mv = ispatest::file2multivector(Comm, *inputFile);
if (!mv || ((dim = mv->NumVectors()) < 1)){
if (localProc == 0)
std::cerr << "Invalid input file " << *inputFile << std::endl;
exit(1);
}
if (localProc == 0){
std::cerr << "Found input file " << *inputFile << ", " ;
std::cerr << dim << " dimensional coordinates" << std::endl;
}
delete inputFile;
int base = mv->Map().IndexBase();
int globalSize = mv->GlobalLength();
int myShare = 0;
int n = numProcs - 1;
if (n){
if (localProc < n){
int oneShare = globalSize / n;
int leftOver = globalSize - (n * oneShare);
myShare = oneShare + ((localProc < leftOver) ? 1 : 0);
}
}
else{
myShare = globalSize;
}
Epetra_BlockMap unbalancedMap(globalSize, myShare, 1, base, mv->Map().Comm());
Epetra_Import importer(unbalancedMap, mv->Map());
Epetra_MultiVector umv(unbalancedMap, dim);
umv.Import(*mv, importer, Insert);
delete mv;
Teuchos::RCP<const Epetra_MultiVector> coords =
Teuchos::rcp(new const Epetra_MultiVector(umv));
// =============================================================
// Create some different coordinate weight vectors
// =============================================================
Epetra_MultiVector *unitWgts = ispatest::makeWeights(coords->Map(), &ispatest::unitWeights);
Epetra_MultiVector *veeWgts = ispatest::makeWeights(coords->Map(), &ispatest::veeWeights);
Epetra_MultiVector *altWgts = ispatest::makeWeights(coords->Map(), &ispatest::alternateWeights);
Teuchos::RCP<const Epetra_MultiVector> unit_weights_rcp = Teuchos::rcp(unitWgts);
Teuchos::RCP<const Epetra_MultiVector> vee_weights_rcp = Teuchos::rcp(veeWgts);
Teuchos::RCP<const Epetra_MultiVector> alt_weights_rcp = Teuchos::rcp(altWgts);
if (localProc == 0){
std::cerr << "Unit weights: Each object has weight 1.0" << std::endl;
std::cerr << "V weights: Low and high GIDs have high weights, center GIDs have low weights" << std::endl;
std::cerr << "Alternate weights: Objects on even rank processes have one weight, on odd another weight" << std::endl;
std::cerr << std::endl;
}
// ======================================================================
// Create a parameter list for Zoltan, and one for internal partitioning
// ======================================================================
Teuchos::ParameterList internalParams;
internalParams.set("PARTITIONING_METHOD", "SIMPLE_LINEAR");
Teuchos::ParameterList zoltanParams;
Teuchos::ParameterList sublist = zoltanParams.sublist("ZOLTAN");
//sublist.set("DEBUG_LEVEL", "1"); // Zoltan will print out parameters
//sublist.set("DEBUG_LEVEL", "5"); // proc 0 will trace Zoltan calls
//sublist.set("DEBUG_MEMORY", "2"); // Zoltan will trace alloc & free
// =============================================================
// Run some tests
// =============================================================
zoltanParams.set("PARTITIONING METHOD", "RCB");
if (localProc == 0){
std::cerr << "RCB - unit weights" << std::endl;
}
fail = run_test(coords, unit_weights_rcp, zoltanParams);
if (fail) goto failure;
if (localProc == 0){
std::cerr << "PASS" << std::endl << std::endl;
}
// *************************************************************
if (localProc == 0){
std::cerr << "HSFC - V weights" << std::endl;
}
zoltanParams.set("PARTITIONING METHOD", "HSFC");
fail = run_test(coords, vee_weights_rcp, zoltanParams);
if (fail) goto failure;
if (localProc == 0){
std::cerr << "PASS" << std::endl << std::endl;
}
// *************************************************************
if (localProc == 0){
std::cerr << "RIB - alternate weights" << std::endl;
}
zoltanParams.set("PARTITIONING METHOD", "RIB");
fail = run_test(coords, alt_weights_rcp, zoltanParams);
if (fail) goto failure;
if (localProc == 0){
std::cerr << "PASS" << std::endl << std::endl;
}
// *************************************************************
if (localProc == 0){
std::cerr << "RIB - no weights supplied" << std::endl;
}
zoltanParams.set("PARTITIONING METHOD", "RIB");
fail = run_test(coords, zoltanParams);
if (fail) goto failure;
if (localProc == 0){
std::cerr << "PASS" << std::endl << std::endl;
}
// *************************************************************
goto done;
failure:
if (localProc == 0){
std::cerr << "FAIL: test failed" << std::endl;
}
done:
#ifdef HAVE_MPI
MPI_Finalize();
#endif
return fail;
}
/** \brief This function builds the internals of the state from a parameter list.
*
* This function builds the internals of the LU 2x2 state
* from a parameter list. Furthermore, it allows a
* developer to easily add a factory to the build system.
*
* \param[in] settings Parameter list to use as the internal settings
* \param[in] invLib Inverse library to use for building inverse factory objects
*
* \note The default implementation does nothing.
*/
void PCDStrategy::initializeFromParameterList(const Teuchos::ParameterList & pl,
const InverseLibrary & invLib)
{
Teko_DEBUG_SCOPE("PCDStrategy::initializeFromParameterList",10);
std::string invStr="Amesos", invFStr="", invSStr="";
massInverseType_ = Diagonal;
// "parse" the parameter list
if(pl.isParameter("Inverse Type"))
invStr = pl.get<std::string>("Inverse Type");
if(pl.isParameter("Inverse F Type"))
invFStr = pl.get<std::string>("Inverse F Type");
if(pl.isParameter("Inverse Laplace Type"))
invSStr = pl.get<std::string>("Inverse Laplace Type");
if(pl.isParameter("Inverse Mass Type")) {
std::string massInverseStr = pl.get<std::string>("Inverse Mass Type");
// build inverse types
massInverseType_ = getDiagonalType(massInverseStr);
}
if(pl.isParameter("Flip Schur Complement Ordering"))
schurCompOrdering_ = pl.get<bool>("Flip Schur Complement Ordering");
// set defaults as needed
if(invFStr=="") invFStr = invStr;
if(invSStr=="") invSStr = invStr;
// read pressure laplace parameters
if(pl.isSublist("Pressure Laplace Parameters"))
lapParams_ = Teuchos::rcp(new Teuchos::ParameterList(pl.sublist("Pressure Laplace Parameters")));
else
lapParams_ = Teuchos::rcp(new Teuchos::ParameterList);
// read pcd operator parameters
if(pl.isSublist("Pressure Convection Diffusion Parameters"))
pcdParams_ = Teuchos::rcp(new Teuchos::ParameterList(pl.sublist("Pressure Convection Diffusion Parameters")));
else
pcdParams_ = Teuchos::rcp(new Teuchos::ParameterList);
// The user should not have already added this parameters
TEUCHOS_TEST_FOR_EXCEPTION(lapParams_->isParameter("Name"),std::logic_error,
"Teko: Parameter \"Name\" is not allowed in the sublist \""+lapParams_->name()+"\"");
TEUCHOS_TEST_FOR_EXCEPTION(lapParams_->isParameter("Tag"),std::logic_error,
"Teko: Parameter \"Tag\" is not allowed in the sublist \""+lapParams_->name()+"\"");
TEUCHOS_TEST_FOR_EXCEPTION(pcdParams_->isParameter("Name"),std::logic_error,
"Teko: Parameter \"Name\" is not allowed in the sublist \""+pcdParams_->name()+"\"");
TEUCHOS_TEST_FOR_EXCEPTION(pcdParams_->isParameter("Tag"),std::logic_error,
"Teko: Parameter \"Tag\" is not allowed in the sublist \""+pcdParams_->name()+"\"");
Teko_DEBUG_MSG_BEGIN(5)
DEBUG_STREAM << "PCD Strategy Parameters: " << std::endl;
DEBUG_STREAM << " inv type = \"" << invStr << "\"" << std::endl;
DEBUG_STREAM << " inv F type = \"" << invFStr << "\"" << std::endl;
DEBUG_STREAM << " inv Laplace type = \"" << invSStr << "\"" << std::endl;
DEBUG_STREAM << " inv Mass type = \"" << Teko::getDiagonalName(massInverseType_) << "\"" << std::endl;
DEBUG_STREAM << "PCD Strategy Parameter list: " << std::endl;
pl.print(DEBUG_STREAM);
Teko_DEBUG_MSG_END()
// build velocity inverse factory
invFactoryF_ = invLib.getInverseFactory(invFStr);
if(invFStr==invSStr)
invFactoryS_ = invFactoryF_;
else
invFactoryS_ = invLib.getInverseFactory(invSStr);
lapParams_->set("Name",getPressureLaplaceString());
pcdParams_->set("Name",getPCDString());
// setup a request for required operators
getRequestHandler()->preRequest<Teko::LinearOp>(getPressureMassString());
// getRequestHandler()->preRequest<Teko::LinearOp>(getPCDString());
// getRequestHandler()->preRequest<Teko::LinearOp>(getPressureLaplaceString());
getRequestHandler()->preRequest<Teko::LinearOp>(Teko::RequestMesg(lapParams_));
getRequestHandler()->preRequest<Teko::LinearOp>(Teko::RequestMesg(pcdParams_));
}
int main_(Teuchos::CommandLineProcessor &clp, int argc, char *argv[]) {
#include <MueLu_UseShortNames.hpp>
using Teuchos::RCP;
using Teuchos::rcp;
using Teuchos::TimeMonitor;
// =========================================================================
// MPI initialization using Teuchos
// =========================================================================
Teuchos::GlobalMPISession mpiSession(&argc, &argv, NULL);
RCP< const Teuchos::Comm<int> > comm = Teuchos::DefaultComm<int>::getComm();
int numProc = comm->getSize();
int myRank = comm->getRank();
// =========================================================================
// Parameters initialization
// =========================================================================
::Xpetra::Parameters xpetraParameters(clp);
bool runHeavyTests = false;
clp.setOption("heavytests", "noheavytests", &runHeavyTests, "whether to exercise tests that take a long time to run");
clp.recogniseAllOptions(true);
switch (clp.parse(argc,argv)) {
case Teuchos::CommandLineProcessor::PARSE_HELP_PRINTED: return EXIT_SUCCESS;
case Teuchos::CommandLineProcessor::PARSE_ERROR:
case Teuchos::CommandLineProcessor::PARSE_UNRECOGNIZED_OPTION: return EXIT_FAILURE;
case Teuchos::CommandLineProcessor::PARSE_SUCCESSFUL: break;
}
Xpetra::UnderlyingLib lib = xpetraParameters.GetLib();
// =========================================================================
// Problem construction
// =========================================================================
ParameterList matrixParameters;
matrixParameters.set("nx", Teuchos::as<GO>(9999));
matrixParameters.set("matrixType", "Laplace1D");
RCP<Matrix> A = MueLuTests::TestHelpers::TestFactory<SC, LO, GO, NO>::Build1DPoisson(matrixParameters.get<GO>("nx"), lib);
RCP<MultiVector> coordinates = Galeri::Xpetra::Utils::CreateCartesianCoordinates<SC,LO,GO,Map,MultiVector>("1D", A->getRowMap(), matrixParameters);
std::string outDir = "Output/";
std::vector<std::string> dirList;
if (runHeavyTests) {
dirList.push_back("EasyParameterListInterpreter-heavy/");
dirList.push_back("FactoryParameterListInterpreter-heavy/");
} else {
dirList.push_back("EasyParameterListInterpreter/");
dirList.push_back("FactoryParameterListInterpreter/");
}
#if defined(HAVE_MPI) && defined(HAVE_MUELU_ISORROPIA) && defined(HAVE_AMESOS2_KLU2)
// The ML interpreter have internal ifdef, which means that the resulting
// output would depend on configuration (reguarl interpreter does not have
// that). Therefore, we need to stabilize the configuration here.
// In addition, we run ML parameter list tests only if KLU is available
dirList.push_back("MLParameterListInterpreter/");
dirList.push_back("MLParameterListInterpreter2/");
#endif
int numLists = dirList.size();
bool failed = false;
Teuchos::Time timer("Interpreter timer");
//double lastTime = timer.wallTime();
for (int k = 0; k < numLists; k++) {
Teuchos::ArrayRCP<std::string> fileList = MueLuTests::TestHelpers::GetFileList(dirList[k],
(numProc == 1 ? std::string(".xml") : std::string("_np" + Teuchos::toString(numProc) + ".xml")));
for (int i = 0; i < fileList.size(); i++) {
// Set seed
std::srand(12345);
// Reset (potentially) cached value of the estimate
A->SetMaxEigenvalueEstimate(-Teuchos::ScalarTraits<SC>::one());
std::string xmlFile = dirList[k] + fileList[i];
std::string outFile = outDir + fileList[i];
std::string baseFile = outFile.substr(0, outFile.find_last_of('.'));
std::size_t found = baseFile.find("_np");
if (numProc == 1 && found != std::string::npos) {
#ifdef HAVE_MPI
baseFile = baseFile.substr(0, found);
#else
std::cout << "Skipping \"" << xmlFile << "\" as MPI is not enabled" << std::endl;
continue;
#endif
}
baseFile = baseFile + (lib == Xpetra::UseEpetra ? "_epetra" : "_tpetra");
std::string goldFile = baseFile + ".gold";
std::ifstream f(goldFile.c_str());
if (!f.good()) {
if (myRank == 0)
std::cout << "Warning: comparison file " << goldFile << " not found. Skipping test" << std::endl;
continue;
}
std::filebuf buffer;
std::streambuf* oldbuffer = NULL;
if (myRank == 0) {
// Redirect output
buffer.open((baseFile + ".out").c_str(), std::ios::out);
oldbuffer = std::cout.rdbuf(&buffer);
}
// NOTE: we cannot use ParameterListInterpreter(xmlFile, comm), because we want to update the ParameterList
// first to include "test" verbosity
Teuchos::ParameterList paramList;
Teuchos::updateParametersFromXmlFileAndBroadcast(xmlFile, Teuchos::Ptr<Teuchos::ParameterList>(¶mList), *comm);
if (dirList[k] == "EasyParameterListInterpreter/" || dirList[k] == "EasyParameterListInterpreter-heavy/")
paramList.set("verbosity", "test");
else if (dirList[k] == "FactoryParameterListInterpreter/" || dirList[k] == "FactoryParameterListInterpreter-heavy/")
paramList.sublist("Hierarchy").set("verbosity", "Test");
else if (dirList[k] == "MLParameterListInterpreter/")
paramList.set("ML output", 42);
else if (dirList[k] == "MLParameterListInterpreter2/")
paramList.set("ML output", 10);
try {
timer.start();
Teuchos::RCP<HierarchyManager> mueluFactory;
// create parameter list interpreter
// here we have to distinguish between the general MueLu parameter list interpreter
// and the ML parameter list interpreter. Note that the ML paramter interpreter also
// works with Tpetra matrices.
if (dirList[k] == "EasyParameterListInterpreter/" ||
dirList[k] == "EasyParameterListInterpreter-heavy/" ||
dirList[k] == "FactoryParameterListInterpreter/" ||
dirList[k] == "FactoryParameterListInterpreter-heavy/") {
mueluFactory = Teuchos::rcp(new ParameterListInterpreter(paramList));
} else if (dirList[k] == "MLParameterListInterpreter/") {
mueluFactory = Teuchos::rcp(new MLParameterListInterpreter(paramList));
} else if (dirList[k] == "MLParameterListInterpreter2/") {
//std::cout << "ML ParameterList: " << std::endl;
//std::cout << paramList << std::endl;
RCP<ParameterList> mueluParamList = Teuchos::getParametersFromXmlString(MueLu::ML2MueLuParameterTranslator::translate(paramList,"SA"));
//std::cout << "MueLu ParameterList: " << std::endl;
//std::cout << *mueluParamList << std::endl;
mueluFactory = Teuchos::rcp(new ParameterListInterpreter(*mueluParamList));
}
RCP<Hierarchy> H = mueluFactory->CreateHierarchy();
H->GetLevel(0)->template Set<RCP<Matrix> >("A", A);
if (dirList[k] == "MLParameterListInterpreter/") {
// MLParameterInterpreter needs the nullspace information if rebalancing is active!
// add default constant null space vector
RCP<MultiVector> nullspace = MultiVectorFactory::Build(A->getRowMap(), 1);
nullspace->putScalar(1.0);
H->GetLevel(0)->Set("Nullspace", nullspace);
}
H->GetLevel(0)->Set("Coordinates", coordinates);
mueluFactory->SetupHierarchy(*H);
if (strncmp(fileList[i].c_str(), "reuse", 5) == 0) {
// Build the Hierarchy the second time
// Should be faster if we actually do the reuse
A->SetMaxEigenvalueEstimate(-Teuchos::ScalarTraits<SC>::one());
mueluFactory->SetupHierarchy(*H);
}
timer.stop();
} catch (Teuchos::ExceptionBase& e) {
std::string msg = e.what();
msg = msg.substr(msg.find_last_of('\n')+1);
if (myRank == 0) {
std::cout << "Caught exception: " << msg << std::endl;
// Redirect output back
std::cout.rdbuf(oldbuffer);
buffer.close();
}
if (msg == "Zoltan interface is not available" ||
msg == "Zoltan2 interface is not available" ||
msg == "MueLu::FactoryFactory:BuildFactory(): Cannot create a Zoltan2Interface object: Zoltan2 is disabled: HAVE_MUELU_ZOLTAN2 && HAVE_MPI == false.") {
if (myRank == 0)
std::cout << xmlFile << ": skipped (missing library)" << std::endl;
continue;
}
}
std::string cmd;
if (myRank == 0) {
// Redirect output back
std::cout.rdbuf(oldbuffer);
buffer.close();
// Create a copy of outputs
cmd = "cp -f ";
system((cmd + baseFile + ".gold " + baseFile + ".gold_filtered").c_str());
system((cmd + baseFile + ".out " + baseFile + ".out_filtered").c_str());
// Tpetra produces different eigenvalues in Chebyshev due to using
// std::rand() for generating random vectors, which may be initialized
// using different seed, and may have different algorithm from one
// gcc version to another, or to anogther compiler (like clang)
// This leads to us always failing this test.
// NOTE1 : Epetra, on the other hand, rolls out its out random number
// generator, which always produces same results
// Ignore the value of "lambdaMax"
run_sed("'s/lambdaMax: [0-9]*.[0-9]*/lambdaMax = <ignored>/'", baseFile);
// Ignore the value of "lambdaMin"
run_sed("'s/lambdaMin: [0-9]*.[0-9]*/lambdaMin = <ignored>/'", baseFile);
// Ignore the value of "chebyshev: max eigenvalue"
// NOTE: we skip lines with default value ([default])
run_sed("'/[default]/! s/chebyshev: max eigenvalue = [0-9]*.[0-9]*/chebyshev: max eigenvalue = <ignored>/'", baseFile);
// Ignore the exact type of direct solver (it is selected semi-automatically
// depending on how Trilinos was configured
run_sed("'s/Amesos\\([2]*\\)Smoother{type = .*}/Amesos\\1Smoother{type = <ignored>}/'", baseFile);
run_sed("'s/SuperLU solver interface, direct solve/<Direct> solver interface/'", baseFile);
run_sed("'s/KLU2 solver interface/<Direct> solver interface/'", baseFile);
run_sed("'s/Basker solver interface/<Direct> solver interface/'", baseFile);
// Strip template args for some classes
std::vector<std::string> classes;
classes.push_back("Xpetra::Matrix");
classes.push_back("MueLu::Constraint");
classes.push_back("MueLu::SmootherPrototype");
for (size_t q = 0; q < classes.size(); q++)
run_sed("'s/" + classes[q] + "<.*>/" + classes[q] + "<ignored> >/'", baseFile);
#ifdef __APPLE__
// Some Macs print outs ptrs as 0x0 instead of 0, fix that
run_sed("'/RCP/ s/=0x0/=0/g'", baseFile);
#endif
// Run comparison (ignoring whitespaces)
cmd = "diff -u -w -I\"^\\s*$\" " + baseFile + ".gold_filtered " + baseFile + ".out_filtered";
int ret = system(cmd.c_str());
if (ret)
failed = true;
//std::ios_base::fmtflags ff(std::cout.flags());
//std::cout.precision(2);
//std::cout << xmlFile << " (" << std::setiosflags(std::ios::fixed)
// << timer.wallTime() - lastTime << " sec.) : " << (ret ? "failed" : "passed") << std::endl;
//lastTime = timer.wallTime();
//std::cout.flags(ff); // reset flags to whatever they were prior to printing time
std::cout << xmlFile << " : " << (ret ? "failed" : "passed") << std::endl;
}
}
}
if (myRank == 0)
std::cout << std::endl << "End Result: TEST " << (failed ? "FAILED" : "PASSED") << std::endl;
return (failed ? EXIT_FAILURE : EXIT_SUCCESS);
}
void ParameterListInterpreter<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::UpdateFactoryManager(Teuchos::ParameterList& paramList,
const Teuchos::ParameterList& defaultList, FactoryManager& manager) const {
// NOTE: Factory::SetParameterList must be called prior to Factory::SetFactory, as
// SetParameterList sets default values for non mentioned parameters, including factories
// === Smoothing ===
bool isCustomSmoother =
paramList.isParameter("smoother: pre or post") ||
paramList.isParameter("smoother: type") || paramList.isParameter("smoother: pre type") || paramList.isParameter("smoother: post type") ||
paramList.isSublist ("smoother: params") || paramList.isSublist ("smoother: pre params") || paramList.isSublist ("smoother: post params") ||
paramList.isParameter("smoother: sweeps") || paramList.isParameter("smoother: pre sweeps") || paramList.isParameter("smoother: post sweeps") ||
paramList.isParameter("smoother: overlap") || paramList.isParameter("smoother: pre overlap") || paramList.isParameter("smoother: post overlap");;
MUELU_READ_2LIST_PARAM(paramList, defaultList, "smoother: pre or post", std::string, "both", PreOrPost);
if (PreOrPost == "none") {
manager.SetFactory("Smoother", Teuchos::null);
} else if (isCustomSmoother) {
// FIXME: get default values from the factory
// NOTE: none of the smoothers at the moment use parameter validation framework, so we
// cannot get the default values from it.
#define TEST_MUTUALLY_EXCLUSIVE(arg1,arg2) \
TEUCHOS_TEST_FOR_EXCEPTION(paramList.isParameter(#arg1) && paramList.isParameter(#arg2), \
Exceptions::InvalidArgument, "You cannot specify both \""#arg1"\" and \""#arg2"\"");
#define TEST_MUTUALLY_EXCLUSIVE_S(arg1,arg2) \
TEUCHOS_TEST_FOR_EXCEPTION(paramList.isSublist(#arg1) && paramList.isSublist(#arg2), \
Exceptions::InvalidArgument, "You cannot specify both \""#arg1"\" and \""#arg2"\"");
TEST_MUTUALLY_EXCLUSIVE ("smoother: type", "smoother: pre type");
TEST_MUTUALLY_EXCLUSIVE ("smoother: type", "smoother: post type");
TEST_MUTUALLY_EXCLUSIVE ("smoother: sweeps", "smoother: pre sweeps");
TEST_MUTUALLY_EXCLUSIVE ("smoother: sweeps", "smoother: post sweeps");
TEST_MUTUALLY_EXCLUSIVE ("smoother: overlap", "smoother: pre overlap");
TEST_MUTUALLY_EXCLUSIVE ("smoother: overlap", "smoother: post overlap");
TEST_MUTUALLY_EXCLUSIVE_S("smoother: params", "smoother: pre params");
TEST_MUTUALLY_EXCLUSIVE_S("smoother: params", "smoother: post params");
TEUCHOS_TEST_FOR_EXCEPTION(PreOrPost == "both" && (paramList.isParameter("smoother: pre type") != paramList.isParameter("smoother: post type")),
Exceptions::InvalidArgument, "You must specify both \"smoother: pre type\" and \"smoother: post type\"");
// Default values
int overlap = 0;
ParameterList defaultSmootherParams;
defaultSmootherParams.set("relaxation: type", "Symmetric Gauss-Seidel");
defaultSmootherParams.set("relaxation: sweeps", Teuchos::OrdinalTraits<LO>::one());
defaultSmootherParams.set("relaxation: damping factor", Teuchos::ScalarTraits<Scalar>::one());
RCP<SmootherPrototype> preSmoother = Teuchos::null, postSmoother = Teuchos::null;
std::string preSmootherType, postSmootherType;
ParameterList preSmootherParams, postSmootherParams;
if (paramList.isParameter("smoother: overlap"))
overlap = paramList.get<int>("smoother: overlap");
if (PreOrPost == "pre" || PreOrPost == "both") {
if (paramList.isParameter("smoother: pre type")) {
preSmootherType = paramList.get<std::string>("smoother: pre type");
} else {
MUELU_READ_2LIST_PARAM(paramList, defaultList, "smoother: type", std::string, "RELAXATION", preSmootherTypeTmp);
preSmootherType = preSmootherTypeTmp;
}
if (paramList.isParameter("smoother: pre overlap"))
overlap = paramList.get<int>("smoother: pre overlap");
if (paramList.isSublist("smoother: pre params"))
preSmootherParams = paramList.sublist("smoother: pre params");
else if (paramList.isSublist("smoother: params"))
preSmootherParams = paramList.sublist("smoother: params");
else if (defaultList.isSublist("smoother: params"))
preSmootherParams = defaultList.sublist("smoother: params");
else if (preSmootherType == "RELAXATION")
preSmootherParams = defaultSmootherParams;
preSmoother = rcp(new TrilinosSmoother(preSmootherType, preSmootherParams, overlap));
}
if (PreOrPost == "post" || PreOrPost == "both") {
if (paramList.isParameter("smoother: post type"))
postSmootherType = paramList.get<std::string>("smoother: post type");
else {
MUELU_READ_2LIST_PARAM(paramList, defaultList, "smoother: type", std::string, "RELAXATION", postSmootherTypeTmp);
postSmootherType = postSmootherTypeTmp;
}
if (paramList.isSublist("smoother: post params"))
postSmootherParams = paramList.sublist("smoother: post params");
else if (paramList.isSublist("smoother: params"))
postSmootherParams = paramList.sublist("smoother: params");
else if (defaultList.isSublist("smoother: params"))
postSmootherParams = defaultList.sublist("smoother: params");
else if (postSmootherType == "RELAXATION")
postSmootherParams = defaultSmootherParams;
if (paramList.isParameter("smoother: post overlap"))
overlap = paramList.get<int>("smoother: post overlap");
if (postSmootherType == preSmootherType && areSame(preSmootherParams, postSmootherParams))
postSmoother = preSmoother;
else
postSmoother = rcp(new TrilinosSmoother(postSmootherType, postSmootherParams, overlap));
}
manager.SetFactory("Smoother", rcp(new SmootherFactory(preSmoother, postSmoother)));
}
// === Coarse solver ===
bool isCustomCoarseSolver =
paramList.isParameter("coarse: type") ||
paramList.isParameter("coarse: params");
if (paramList.isParameter("coarse: type") && paramList.get<std::string>("coarse: type") == "none") {
manager.SetFactory("CoarseSolver", Teuchos::null);
} else if (isCustomCoarseSolver) {
// FIXME: get default values from the factory
// NOTE: none of the smoothers at the moment use parameter validation framework, so we
// cannot get the default values from it.
MUELU_READ_2LIST_PARAM(paramList, defaultList, "coarse: type", std::string, "", coarseType);
ParameterList coarseParams;
if (paramList.isSublist("coarse: params"))
coarseParams = paramList.sublist("coarse: params");
else if (defaultList.isSublist("coarse: params"))
coarseParams = defaultList.sublist("coarse: params");
RCP<SmootherPrototype> coarseSmoother;
// TODO: this is not a proper place to check. If we consider direct solver to be a special
// case of smoother, we would like to unify Amesos and Ifpack2 smoothers in src/Smoothers, and
// have a single factory responsible for those. Then, this check would belong there.
if (coarseType == "RELAXATION" || coarseType == "CHEBYSHEV" ||
coarseType == "ILUT" || coarseType == "ILU" || coarseType == "RILUK" || coarseType == "SCHWARZ")
coarseSmoother = rcp(new TrilinosSmoother(coarseType, coarseParams));
else
coarseSmoother = rcp(new DirectSolver(coarseType, coarseParams));
manager.SetFactory("CoarseSolver", rcp(new SmootherFactory(coarseSmoother)));
}
// === Aggregation ===
// Aggregation graph
RCP<CoalesceDropFactory> dropFactory = rcp(new CoalesceDropFactory());
ParameterList dropParams;
dropParams.set("lightweight wrap", true);
MUELU_TEST_AND_SET_PARAM(dropParams, "algorithm", paramList, defaultList, "aggregation: drop scheme", std::string);
// Rename classical to original
if (dropParams.isParameter("algorithm") && dropParams.get<std::string>("algorithm") == "classical")
dropParams.set("algorithm", "original");
MUELU_TEST_AND_SET_PARAM(dropParams, "aggregation threshold", paramList, defaultList, "aggregation: drop tol", double);
MUELU_TEST_AND_SET_PARAM(dropParams, "Dirichlet detection threshold", paramList, defaultList, "aggregation: Dirichlet threshold", double);
dropFactory->SetParameterList(dropParams);
manager.SetFactory("Graph", dropFactory);
// Aggregation sheme
MUELU_READ_2LIST_PARAM(paramList, defaultList, "aggregation: type", std::string, "uncoupled", aggType);
RCP<Factory> aggFactory;
if (aggType == "uncoupled") {
aggFactory = rcp(new UncoupledAggregationFactory());
ParameterList aggParams;
MUELU_TEST_AND_SET_PARAM(aggParams, "mode", paramList, defaultList, "aggregation: mode", std::string);
MUELU_TEST_AND_SET_PARAM(aggParams, "MinNodesPerAggregate", paramList, defaultList, "aggregation: min agg size", int);
MUELU_TEST_AND_SET_PARAM(aggParams, "MaxNodesPerAggregate", paramList, defaultList, "aggregation: max agg size", int);
MUELU_TEST_AND_SET_PARAM(aggParams, "aggregation: preserve Dirichlet points", paramList, defaultList, "aggregation: preserve Dirichlet points", bool);
aggFactory->SetParameterList(aggParams);
} else if (aggType == "coupled") {
std::string ML2MueLuParameterTranslator::SetParameterList(const Teuchos::ParameterList & paramList_in, const std::string& defaultVals) {
Teuchos::ParameterList paramList = paramList_in;
RCP<Teuchos::FancyOStream> out = Teuchos::fancyOStream(Teuchos::rcpFromRef(std::cout)); // TODO: use internal out (GetOStream())
#if defined(HAVE_MUELU_ML) && defined(HAVE_MUELU_EPETRA)
// TODO alternative with standard parameterlist from ML user guide?
if (defaultVals != "") {
TEUCHOS_TEST_FOR_EXCEPTION(defaultVals!="SA" && defaultVals!="NSSA", Exceptions::RuntimeError,
"MueLu::MLParameterListInterpreter: only \"SA\" and \"NSSA\" allowed as options for ML default parameters.");
Teuchos::ParameterList ML_defaultlist;
ML_Epetra::SetDefaults(defaultVals,ML_defaultlist);
// merge user parameters with default parameters
MueLu::MergeParameterList(paramList_in, ML_defaultlist, true);
paramList = ML_defaultlist;
}
#else
if (defaultVals != "") {
// If no validator available: issue a warning and set parameter value to false in the output list
*out << "Warning: MueLu_ENABLE_ML=OFF. No ML default values available." << std::endl;
}
#endif // HAVE_MUELU_ML
//
// Move smoothers/aggregation/coarse parameters to sublists
//
// ML allows to have level-specific smoothers/aggregation/coarse parameters at the top level of the list or/and defined in sublists:
// See also: ML Guide section 6.4.1, MueLu::CreateSublists, ML_CreateSublists
ParameterList paramListWithSubList;
MueLu::CreateSublists(paramList, paramListWithSubList);
paramList = paramListWithSubList; // swap
Teuchos::ParameterList adaptingParamList = paramList; // copy of paramList which is used to removed already interpreted parameters
//
// Validate parameter list
//
{
bool validate = paramList.get("ML validate parameter list", true); /* true = default in ML */
if (validate) {
#if defined(HAVE_MUELU_ML) && defined(HAVE_MUELU_EPETRA)
// Validate parameter list using ML validator
int depth = paramList.get("ML validate depth", 5); /* 5 = default in ML */
TEUCHOS_TEST_FOR_EXCEPTION(! ML_Epetra::ValidateMLPParameters(paramList, depth), Exceptions::RuntimeError,
"ERROR: ML's Teuchos::ParameterList contains incorrect parameter!");
#else
// If no validator available: issue a warning and set parameter value to false in the output list
*out << "Warning: MueLu_ENABLE_ML=OFF. The parameter list cannot be validated." << std::endl;
paramList.set("ML validate parameter list", false);
#endif // HAVE_MUELU_ML
} // if(validate)
} // scope
// stringstream for concatenating xml parameter strings.
std::stringstream mueluss;
// create surrounding MueLu parameter list
mueluss << "<ParameterList name=\"MueLu\">" << std::endl;
// loop over all ML parameters in provided parameter list
for (ParameterList::ConstIterator param = paramListWithSubList.begin(); param != paramListWithSubList.end(); ++param) {
// extract ML parameter name
const std::string & pname=paramListWithSubList.name(param);
// extract corresponding (ML) value
// remove ParameterList specific information from result string
std::stringstream valuess;
valuess << paramList.entry(param);
std::string valuestr = valuess.str();
replaceAll(valuestr, "[unused]", "");
replaceAll(valuestr, "[default]", "");
valuestr = trim(valuestr);
// transform ML parameter to corresponding MueLu parameter and generate XML string
std::string valueInterpreterStr = "\"" + valuestr + "\"";
std::string ret = MasterList::interpretParameterName(MasterList::ML2MueLu(pname),valueInterpreterStr);
// add XML string
if (ret != "") {
mueluss << ret << std::endl;
// remove parameter from ML parameter list
adaptingParamList.remove(pname,false);
}
// special handling for energy minimization
// TAW: this is not optimal for symmetric problems but at least works.
// for symmetric problems the "energy minimization" parameter should not exist anyway...
if (pname == "energy minimization: enable") {
mueluss << "<Parameter name=\"problem: symmetric\" type=\"bool\" value=\"false\"/>" << std::endl;
mueluss << "<Parameter name=\"transpose: use implicit\" type=\"bool\" value=\"false\"/>" << std::endl;
}
// special handling for smoothers
if (pname == "smoother: type") {
mueluss << GetSmootherFactory(paramList, adaptingParamList, pname, valuestr);
}
// special handling for level-specific smoothers
if (pname.find("smoother: list (level",0) == 0) {
// Scan pname (ex: pname="smoother: type (level 2)")
std::string type, option;
int levelID=-1;
{
typedef Teuchos::ArrayRCP<char>::size_type size_type;
Teuchos::Array<char> ctype (size_type(pname.size()+1));
Teuchos::Array<char> coption(size_type(pname.size()+1));
int matched = sscanf(pname.c_str(),"%s %[^(](level %d)", ctype.getRawPtr(), coption.getRawPtr(), &levelID); // use [^(] instead of %s to allow for strings with white-spaces (ex: "ifpack list")
type = std::string(ctype.getRawPtr());
option = std::string(coption.getRawPtr()); option.resize(option.size () - 1); // remove final white-space
if (matched != 3 || (type != "smoother:")) {
TEUCHOS_TEST_FOR_EXCEPTION(true, MueLu::Exceptions::RuntimeError, "MueLu::CreateSublist(), Line " << __LINE__ << ". "
<< "Error in creating level-specific sublists" << std::endl
<< "Offending parameter: " << pname << std::endl);
}
mueluss << "<ParameterList name=\"level " << levelID << "\">" << std::endl;
mueluss << GetSmootherFactory(paramList.sublist(pname),adaptingParamList.sublist(pname), "smoother: type", paramList.sublist(pname).get<std::string>("smoother: type"));
mueluss << "</ParameterList>" << std::endl;
}
}
// special handling for coarse level
TEUCHOS_TEST_FOR_EXCEPTION(paramList.isParameter("coarse: type"), Exceptions::RuntimeError, "MueLu::MLParameterListInterpreter::Setup(): The parameter \"coarse: type\" should not exist but being stored in \"coarse: list\" instead.");
if ( pname == "coarse: list" ) {
// interpret smoother/coarse solver data.
// Note, that we inspect the "coarse: list" sublist to define the "coarse" smoother/solver
// Be aware, that MueLu::CreateSublists renames the prefix of the parameters in the "coarse: list" from "coarse" to "smoother".
// Therefore, we have to check the values of the "smoother" parameters
TEUCHOS_TEST_FOR_EXCEPTION(!paramList.sublist("coarse: list").isParameter("smoother: type"), Exceptions::RuntimeError, "MueLu::MLParameterListInterpreter::Setup(): no coarse grid solver defined.");
mueluss << GetSmootherFactory(paramList.sublist("coarse: list"), adaptingParamList.sublist("coarse: list"), "coarse: type", paramList.sublist("coarse: list").get<std::string>("smoother: type"));
}
} // for
mueluss << "</ParameterList>" << std::endl;
return mueluss.str();
}
int main(int argc, char *argv[])
{
#ifdef HAVE_MPI
Teuchos::GlobalMPISession mpiSession(&argc, &argv, 0);
Epetra_MpiComm Comm(MPI_COMM_WORLD);
#else
Epetra_SerialComm Comm;
#endif
int nProcs, myPID ;
Teuchos::ParameterList pLUList ; // ParaLU parameters
Teuchos::ParameterList isoList ; // Isorropia parameters
Teuchos::ParameterList shyLUList ; // shyLU parameters
Teuchos::ParameterList ifpackList ; // shyLU parameters
string ipFileName = "ShyLU.xml"; // TODO : Accept as i/p
nProcs = mpiSession.getNProc();
myPID = Comm.MyPID();
if (myPID == 0)
{
cout <<"Parallel execution: nProcs="<< nProcs << endl;
}
// =================== Read input xml file =============================
Teuchos::updateParametersFromXmlFile(ipFileName, &pLUList);
isoList = pLUList.sublist("Isorropia Input");
shyLUList = pLUList.sublist("ShyLU Input");
shyLUList.set("Outer Solver Library", "AztecOO");
// Get matrix market file name
string MMFileName = Teuchos::getParameter<string>(pLUList, "mm_file");
string prec_type = Teuchos::getParameter<string>(pLUList, "preconditioner");
int maxiters = Teuchos::getParameter<int>(pLUList, "Outer Solver MaxIters");
double tol = Teuchos::getParameter<double>(pLUList, "Outer Solver Tolerance");
string rhsFileName = pLUList.get<string>("rhs_file", "");
if (myPID == 0)
{
cout << "Input :" << endl;
cout << "ParaLU params " << endl;
pLUList.print(std::cout, 2, true, true);
cout << "Matrix market file name: " << MMFileName << endl;
}
// ==================== Read input Matrix ==============================
Epetra_CrsMatrix *A;
Epetra_MultiVector *b1;
int err = EpetraExt::MatrixMarketFileToCrsMatrix(MMFileName.c_str(), Comm,
A);
//EpetraExt::MatlabFileToCrsMatrix(MMFileName.c_str(), Comm, A);
//assert(err != 0);
//cout <<"Done reading the matrix"<< endl;
int n = A->NumGlobalRows();
//cout <<"n="<< n << endl;
// Create input vectors
Epetra_Map vecMap(n, 0, Comm);
if (rhsFileName != "")
{
err = EpetraExt::MatrixMarketFileToMultiVector(rhsFileName.c_str(),
vecMap, b1);
}
else
{
b1 = new Epetra_MultiVector(vecMap, 1, false);
b1->PutScalar(1.0);
}
Epetra_MultiVector x(vecMap, 1);
//cout << "Created the vectors" << endl;
// Partition the matrix with hypergraph partitioning and redisstribute
Isorropia::Epetra::Partitioner *partitioner = new
Isorropia::Epetra::Partitioner(A, isoList, false);
partitioner->partition();
Isorropia::Epetra::Redistributor rd(partitioner);
Epetra_CrsMatrix *newA;
Epetra_MultiVector *newX, *newB;
rd.redistribute(*A, newA);
delete A;
A = newA;
rd.redistribute(x, newX);
rd.redistribute(*b1, newB);
Epetra_LinearProblem problem(A, newX, newB);
AztecOO solver(problem);
ifpackList ;
Ifpack_Preconditioner *prec;
ML_Epetra::MultiLevelPreconditioner *MLprec;
if (prec_type.compare("ShyLU") == 0)
{
prec = new Ifpack_ShyLU(A);
prec->SetParameters(shyLUList);
prec->Initialize();
prec->Compute();
//(dynamic_cast<Ifpack_ShyLU *>(prec))->JustTryIt();
//cout << " Going to set it in solver" << endl ;
solver.SetPrecOperator(prec);
//cout << " Done setting the solver" << endl ;
}
else if (prec_type.compare("ILU") == 0)
{
ifpackList.set( "fact: level-of-fill", 1 );
prec = new Ifpack_ILU(A);
prec->SetParameters(ifpackList);
prec->Initialize();
prec->Compute();
solver.SetPrecOperator(prec);
}
else if (prec_type.compare("ILUT") == 0)
{
ifpackList.set( "fact: ilut level-of-fill", 2 );
ifpackList.set( "fact: drop tolerance", 1e-8);
prec = new Ifpack_ILUT(A);
prec->SetParameters(ifpackList);
prec->Initialize();
prec->Compute();
solver.SetPrecOperator(prec);
}
else if (prec_type.compare("ML") == 0)
{
Teuchos::ParameterList mlList; // TODO : Take it from i/p
MLprec = new ML_Epetra::MultiLevelPreconditioner(*A, mlList, true);
solver.SetPrecOperator(MLprec);
}
solver.SetAztecOption(AZ_solver, AZ_gmres);
solver.SetMatrixName(333);
//solver.SetAztecOption(AZ_output, 1);
//solver.SetAztecOption(AZ_conv, AZ_Anorm);
//cout << "Going to iterate for the global problem" << endl;
solver.Iterate(maxiters, tol);
// compute ||Ax - b||
double Norm;
Epetra_MultiVector Ax(vecMap, 1);
Epetra_MultiVector *newAx;
rd.redistribute(Ax, newAx);
A->Multiply(false, *newX, *newAx);
newAx->Update(1.0, *newB, -1.0);
newAx->Norm2(&Norm);
double ANorm = A->NormOne();
cout << "|Ax-b |/|A| = " << Norm/ANorm << endl;
delete newAx;
if (prec_type.compare("ML") == 0)
{
delete MLprec;
}
else
{
delete prec;
}
delete b1;
delete newX;
delete newB;
delete A;
delete partitioner;
}
int main(int argc, char *argv[]) {
#ifdef HAVE_MPI
MPI_Init(&argc, &argv);
Epetra_MpiComm Comm(MPI_COMM_WORLD);
#else
Epetra_SerialComm Comm;
#endif
// initialize the random number generator
int ml_one = 1;
ML_srandom1(&ml_one);
// ===================== //
// create linear problem //
// ===================== //
ParameterList GaleriList;
GaleriList.set("nx", 10);
GaleriList.set("ny", 10);
GaleriList.set("nz", 10 * Comm.NumProc());
GaleriList.set("mx", 1);
GaleriList.set("my", 1);
GaleriList.set("mz", Comm.NumProc());
Epetra_Map* Map = CreateMap("Cartesian3D", Comm, GaleriList);
Epetra_CrsMatrix* Matrix = CreateCrsMatrix("Laplace3D", Map, GaleriList);
Epetra_MultiVector* Coords = CreateCartesianCoordinates("3D",Map,GaleriList);
Epetra_Vector LHS(*Map);
Epetra_Vector RHS(*Map);
Epetra_LinearProblem Problem(Matrix, &LHS, &RHS);
Teuchos::ParameterList MLList;
double TotalErrorResidual = 0.0, TotalErrorExactSol = 0.0;
// ====================== //
// default options for SA //
// ====================== //
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("smoother: type", "Gauss-Seidel");
char mystring[80];
strcpy(mystring,"SA");
TestMultiLevelPreconditioner(mystring, MLList, Problem,
TotalErrorResidual, TotalErrorExactSol);
// ============================================== //
// default options for SA, efficient symmetric GS //
// ============================================== //
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("smoother: type", "Gauss-Seidel");
MLList.set("smoother: Gauss-Seidel efficient symmetric",true);
TestMultiLevelPreconditioner(mystring, MLList, Problem,
TotalErrorResidual, TotalErrorExactSol,true);
// ============================== //
// default options for SA, Jacobi //
// ============================== //
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("smoother: type", "Jacobi");
TestMultiLevelPreconditioner(mystring, MLList, Problem, TotalErrorResidual,
TotalErrorExactSol,true);
// =========================== //
// default options for SA, Cheby //
// =========================== //
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("smoother: type", "Chebyshev");
TestMultiLevelPreconditioner(mystring, MLList, Problem,
TotalErrorResidual, TotalErrorExactSol);
// =========================== //
// Specifying Ifpack coarse lists correctly
// =========================== //
#ifdef HAVE_ML_IFPACK
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
if(!Comm.MyPID()) {
MLList.set("ML print initial list",1);
MLList.set("ML print final list",1);
}
MLList.set("smoother: type","ILU");
MLList.set("coarse: type","ILUT");
ParameterList &fList = MLList.sublist("smoother: ifpack list");
fList.set("fact: level-of-fill",1);
ParameterList &cList = MLList.sublist("coarse: ifpack list");
cList.set("fact: ilut level-of-fill",1e-2);
TestMultiLevelPreconditioner(mystring, MLList, Problem,
TotalErrorResidual, TotalErrorExactSol);
#endif
// =========================== //
// Specifying level sublists
// =========================== //
if (Comm.MyPID() == 0) PrintLine();
ParameterList LevelList;
ML_Epetra::SetDefaults("SA",LevelList);
ParameterList &smList = LevelList.sublist("smoother: list (level 0)");
smList.set("smoother: type","Jacobi");
smList.set("smoother: sweeps",5);
ParameterList &smList2 = LevelList.sublist("smoother: list (level 1)");
smList2.set("smoother: type","symmetric Gauss-Seidel");
smList2.set("smoother: sweeps",3);
ParameterList &coarseList = LevelList.sublist("coarse: list");
coarseList.set("smoother: type","symmetric Gauss-Seidel");
TestMultiLevelPreconditioner(mystring, LevelList, Problem,
TotalErrorResidual, TotalErrorExactSol);
// =========================== //
// Ifpack G-S w/ L1
// =========================== //
#ifdef HAVE_ML_IFPACK
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("smoother: use l1 Gauss-Seidel",true);
MLList.set("smoother: type", "Gauss-Seidel");
TestMultiLevelPreconditioner(mystring, MLList, Problem,
TotalErrorResidual, TotalErrorExactSol);
#endif
// =========================== //
// Ifpack SGS w/ L1
// =========================== //
#ifdef HAVE_ML_IFPACK
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("smoother: use l1 Gauss-Seidel",true);
MLList.set("smoother: type", "symmetric Gauss-Seidel");
TestMultiLevelPreconditioner(mystring, MLList, Problem,
TotalErrorResidual, TotalErrorExactSol);
#endif
// =========================== //
// Autodetected Line SGS (trivial lines)
// =========================== //
if (Comm.MyPID() == 0) PrintLine();
ML_Epetra::SetDefaults("SA",MLList);
MLList.set("smoother: type", "line Gauss-Seidel");
MLList.set("smoother: line detection threshold",0.1);
MLList.set("x-coordinates",(*Coords)[0]);
MLList.set("y-coordinates",(*Coords)[1]);
MLList.set("z-coordinates",(*Coords)[2]);
TestMultiLevelPreconditioner(mystring, MLList, Problem,
TotalErrorResidual, TotalErrorExactSol);
// ===================== //
// print out total error //
// ===================== //
if (Comm.MyPID() == 0) {
cout << endl;
cout << "......Total error for residual = " << TotalErrorResidual << endl;
cout << "......Total error for exact solution = " << TotalErrorExactSol << endl;
cout << endl;
}
delete Matrix;
delete Coords;
delete Map;
if (TotalErrorResidual > 1e-8) {
cerr << "Error: `MultiLevelPrecoditioner_Sym.exe' failed!" << endl;
exit(EXIT_FAILURE);
}
#ifdef HAVE_MPI
MPI_Finalize();
#endif
if (Comm.MyPID() == 0)
cerr << "`MultiLevelPrecoditioner_Sym.exe' passed!" << endl;
return (EXIT_SUCCESS);
}
bool SolverTrilinosML::Solve(INMOST::Sparse::Vector &RHS, INMOST::Sparse::Vector &SOL) {
std::string name = Epetra_problem->first;
Epetra_LinearProblem *Epetra_linear_problem = &Epetra_problem->second;
Epetra_Vector VectorRHS(View, matrix->Map(), &*RHS.Begin());
Epetra_Vector VectorSOL(View, matrix->Map(), &*SOL.Begin());
Epetra_linear_problem->SetRHS(&VectorRHS);
Epetra_linear_problem->SetLHS(&VectorSOL);
bool have_params = parameters_file != "";
const Teuchos::RCP<Teuchos::ParameterList> top_level_params = Teuchos::createParameterList();
Teuchos::ParameterList local_list;
if (have_params) {
Teuchos::updateParametersFromXmlFileAndBroadcast(parameters_file, top_level_params.ptr(),
Teuchos::MpiComm<int>(Teuchos::opaqueWrapper(
RHS.GetCommunicator())));
if (!top_level_params->isSublist(name))
have_params = false;
else {
local_list = top_level_params->sublist(name);
}
}
AztecOO AztecSolver(*Epetra_linear_problem);
if (have_params && local_list.isSublist("AztecOO")) {
Teuchos::ParameterList AztecOOParams = local_list.sublist("AztecOO");
if (AztecOOParams.isParameter("Max Iterations")) {
maximum_iterations = AztecOOParams.get<int>("Max Iterations");
}
if (AztecOOParams.isParameter("Tolerance")) {
rtol = AztecOOParams.get<double>("Tolerance");
}
if (AztecOOParams.isSublist("AztecOO Settings")) {
AztecSolver.SetParameters(AztecOOParams.sublist("AztecOO Settings"));
}
} else {
AztecSolver.SetAztecOption(AZ_diagnostics, AZ_none);
AztecSolver.SetAztecOption(AZ_output, AZ_none);
AztecSolver.SetAztecOption(AZ_solver, AZ_bicgstab);
AztecSolver.SetAztecOption(AZ_overlap, schwartz_overlap);
}
Teuchos::ParameterList List;
if (have_params && local_list.isSublist("ML") && local_list.sublist("ML").isSublist("ML Settings")) {
List = local_list.sublist("ML").sublist("ML Settings");
} else {
ML_Epetra::SetDefaults("SA", List);
List.set("max levels", 6);
List.set("increasing or decreasing", "decreasing");
}
ML_Epetra::MultiLevelPreconditioner *Prec = new ML_Epetra::MultiLevelPreconditioner(*matrix, List, true);
AztecSolver.SetPrecOperator(Prec);
AztecSolver.Iterate(maximum_iterations, rtol);
const double *stats = AztecSolver.GetAztecStatus();
bool success = true;
std::string reason = "";
TrilinosCheckStatus(static_cast<int>(stats[AZ_why]), success, reason);
lastIterations = static_cast<INMOST_DATA_ENUM_TYPE>(AztecSolver.NumIters());
lastResidual = AztecSolver.TrueResidual();
returnReason = reason;
delete Prec;
return success;
}
Teuchos::RCP< std::vector<std::string> > RBGen::genFileList( const Teuchos::ParameterList& params )
{
Teuchos::RCP< std::vector< std::string > > filenames = Teuchos::rcp( new std::vector< std::string >() );
// See if the "File I/O" sublist exists
TEUCHOS_TEST_FOR_EXCEPTION(!params.isSublist( "File IO" ), std::invalid_argument, "File I/O sublist does not exist!");
// Get the "File I/O" sublist.
Teuchos::ParameterList& fileio_params = const_cast<Teuchos::ParameterList&>(params.sublist( "File IO" ) );
// See if the "Data Filename Format" sublist exists
TEUCHOS_TEST_FOR_EXCEPTION(!fileio_params.isSublist( "Data Filename Format" ), std::invalid_argument, "Data Filename Format sublist does not exist!");
// Get the "Data Filename Format" sublist.
Teuchos::ParameterList& fileformat_params = fileio_params.sublist( "Data Filename Format" );
// Get the string prepended to the numeric characters.
std::string prepend = "";
if ( fileformat_params.isParameter( "Prepend" ) ) {
prepend = Teuchos::getParameter<std::string>( fileformat_params, "Prepend" );
}
// Get the string postpended to the numeric characters.
std::string postpend = "";
if ( fileformat_params.isParameter( "Postpend" ) ) {
postpend = Teuchos::getParameter<std::string>( fileformat_params, "Postpend" );
}
// Get the string prepended to the numeric characters.
std::string extension = "";
if ( fileformat_params.isParameter( "Extension" ) ) {
extension = Teuchos::getParameter<std::string>( fileformat_params, "Extension" );
}
// Get the base for the numeric count
int base_num = 0;
if ( fileformat_params.isParameter( "File Number Base" ) ) {
base_num = Teuchos::getParameter<int>( fileformat_params, "File Number Base" );
}
std::string format_type = Teuchos::getParameter<std::string>( fileformat_params, "Type" );
if ( format_type == "Single file" ) {
// Get the file to process
filenames->push_back( Teuchos::getParameter<std::string>( fileformat_params, "Data File" ) );
} else
if ( format_type == "Fixed length numeric" ) {
// Get the number of files to process
int num_files = Teuchos::getParameter<int>( fileformat_params, "Number of Files" );
int max_num = base_num + num_files;
int num_places = (int)::ceil( ::log10( (double)(max_num) ) );
for (int i=base_num; i<max_num; i++) {
// Generate the current filename
std::string curr_filename = prepend;
// Get the number of places needed for the current file number
int curr_places = (int)::ceil( ::log10( (double)(i+1) ) );
// Add zeros to pad the file number
for (int j=curr_places; j<num_places; j++) {
curr_filename += "0";
}
// Now add on the current file number, postpend string and extension
filenames->push_back( curr_filename + Teuchos::Utils::toString( i ) + postpend + extension );
}
} else
if ( format_type == "Variable length numeric" ) {
// Get the number of files to process
int num_files = Teuchos::getParameter<int>( fileformat_params, "Number of Files" );
int max_num = base_num + num_files;
for (int i=base_num; i<max_num; i++) {
filenames->push_back( prepend + Teuchos::Utils::toString( i ) + postpend + extension );
}
}
else {
std::string err_str = "File format type, 'Type = " + format_type + "', is not recognized!";
TEUCHOS_TEST_FOR_EXCEPTION(true, std::invalid_argument, err_str);
}
return filenames;
}
int main(int argc, char *argv[]) {
typedef std::vector<RealT> vector;
typedef ROL::Vector<RealT> V;
typedef ROL::StdVector<RealT> SV;
typedef ROL::Objective<RealT> OBJ;
typedef ROL::EqualityConstraint<RealT> EC;
typedef typename vector::size_type uint;
using Teuchos::RCP; using Teuchos::rcp;
Teuchos::GlobalMPISession mpiSession(&argc, &argv);
// This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
int iprint = argc - 1;
Teuchos::RCP<std::ostream> outStream;
Teuchos::oblackholestream bhs; // outputs nothing
if (iprint > 0)
outStream = Teuchos::rcp(&std::cout, false);
else
outStream = Teuchos::rcp(&bhs, false);
int errorFlag = 0;
// *** Example body.
try {
uint xdim = 4;
uint cdim = 1;
RCP<vector> x_exact_rcp = rcp( new vector(xdim), 0.0 );
(*x_exact_rcp)[0] = 1.0;
(*x_exact_rcp)[1] = 1.0;
RCP<V> x = rcp( new SV( rcp( new vector(xdim, 0.0) ) ) );
RCP<V> d = rcp( new SV( rcp( new vector(xdim, 0.0) ) ) );
RCP<V> xtest = rcp( new SV( rcp( new vector(xdim, 0.0) ) ) );
RCP<V> c1 = rcp( new SV( rcp( new vector(cdim, 1.0) ) ) );
RCP<V> c2 = rcp( new SV( rcp( new vector(cdim, 1.0) ) ) );
RCP<V> l1 = rcp( new SV( rcp( new vector(cdim, 1.0) ) ) );
RCP<V> l2 = rcp( new SV( rcp( new vector(cdim, 1.0) ) ) );
RCP<V> c = ROL::CreatePartitionedVector( c1, c2 );
RCP<V> l = ROL::CreatePartitionedVector( l1, l2 );
SV x_exact( x_exact_rcp );
// Initial guess from H&S 39
x->applyUnary(ROL::Elementwise::Fill<RealT>(2.0));
ROL::RandomizeVector(*d, -1.0, 1.0 );
ROL::RandomizeVector(*xtest, -1.0, 1.0 );
RCP<OBJ> obj = rcp( new ROL::ZOO::Objective_HS39<RealT>() );
RCP<EC> con1 = rcp( new ROL::ZOO::EqualityConstraint_HS39a<RealT>() );
RCP<EC> con2 = rcp( new ROL::ZOO::EqualityConstraint_HS39b<RealT>() );
RCP<EC> con = CreateEqualityConstraintPartitioned(con1, con2);
*outStream << "Checking objective" << std::endl;
obj->checkGradient(*x,*d,true,*outStream);
*outStream << "\nChecking first equality constraint" << std::endl;
con1->checkApplyJacobian( *xtest, *d, *c1 , true, *outStream );
con1->checkApplyAdjointJacobian( *xtest, *l1, *c1, *d, true, *outStream );
con1->checkApplyAdjointHessian( *xtest, *l1, *d, *xtest, true, *outStream );
*outStream << "\nChecking second equality constraint" << std::endl;
con2->checkApplyJacobian( *xtest, *d, *c2, true, *outStream );
con2->checkApplyAdjointJacobian( *xtest, *l2, *c2, *d, true, *outStream );
con2->checkApplyAdjointHessian( *xtest, *l2, *d, *xtest, true, *outStream );
*outStream << "\nChecking partitioned equality constraint" << std::endl;
con->checkApplyJacobian( *xtest, *d, *c, true, *outStream );
con->checkApplyAdjointJacobian( *xtest, *l, *c, *d, true, *outStream );
con->checkApplyAdjointHessian( *xtest, *l, *d, *xtest, true, *outStream );
// Define algorithm.
Teuchos::ParameterList parlist;
std::string stepname = "Composite Step";
parlist.sublist("Step").sublist(stepname).sublist("Optimality System Solver").set("Nominal Relative Tolerance",1.e-4);
parlist.sublist("Step").sublist(stepname).sublist("Optimality System Solver").set("Fix Tolerance",true);
parlist.sublist("Step").sublist(stepname).sublist("Tangential Subproblem Solver").set("Iteration Limit",20);
parlist.sublist("Step").sublist(stepname).sublist("Tangential Subproblem Solver").set("Relative Tolerance",1e-2);
parlist.sublist("Step").sublist(stepname).set("Output Level",0);
parlist.sublist("Status Test").set("Gradient Tolerance",1.e-12);
parlist.sublist("Status Test").set("Constraint Tolerance",1.e-12);
parlist.sublist("Status Test").set("Step Tolerance",1.e-18);
parlist.sublist("Status Test").set("Iteration Limit",100);
ROL::Algorithm<RealT> algo(stepname, parlist);
algo.run(*x,x->dual(),*l,*c,*obj,*con,true,*outStream);
x->axpy(-1.0,x_exact);
if( x->norm() > 1e-6 ) {
++errorFlag;
}
}
catch (std::logic_error err) {
*outStream << err.what() << "\n";
errorFlag = -1000;
}; // end try
if (errorFlag != 0)
std::cout << "End Result: TEST FAILED\n";
else
std::cout << "End Result: TEST PASSED\n";
return 0;
}
int main(int argc, char* argv[]) {
Teuchos::GlobalMPISession mpiSession(&argc, &argv);
Teuchos::RCP<const Teuchos::Comm<int> > comm
= Teuchos::DefaultComm<int>::getComm();
// This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
int iprint = argc - 1;
Teuchos::RCP<std::ostream> outStream;
Teuchos::oblackholestream bhs; // outputs nothing
if (iprint > 0 && Teuchos::rank<int>(*comm)==0)
outStream = Teuchos::rcp(&std::cout, false);
else
outStream = Teuchos::rcp(&bhs, false);
int errorFlag = 0;
try {
/**********************************************************************************************/
/************************* CONSTRUCT ROL ALGORITHM ********************************************/
/**********************************************************************************************/
// Get ROL parameterlist
std::string filename = "input.xml";
Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp( new Teuchos::ParameterList() );
Teuchos::updateParametersFromXmlFile( filename, parlist.ptr() );
// Build ROL algorithm
parlist->sublist("Status Test").set("Gradient Tolerance",1.e-7);
parlist->sublist("Status Test").set("Step Tolerance",1.e-14);
parlist->sublist("Status Test").set("Iteration Limit",100);
/**********************************************************************************************/
/************************* CONSTRUCT VECTORS **************************************************/
/**********************************************************************************************/
// Build control vectors
int nx = 256;
// Construct storage for optimal solution
Teuchos::RCP<std::vector<RealT> > z_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0));
Teuchos::RCP<ROL::Vector<RealT> > zp = Teuchos::rcp(new ROL::StdVector<RealT>(z_rcp));
Teuchos::RCP<std::vector<RealT> > x1_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0));
Teuchos::RCP<ROL::Vector<RealT> > x1p = Teuchos::rcp(new ROL::StdVector<RealT>(x1_rcp));
Teuchos::RCP<std::vector<RealT> > x2_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0));
Teuchos::RCP<ROL::Vector<RealT> > x2p = Teuchos::rcp(new ROL::StdVector<RealT>(x2_rcp));
Teuchos::RCP<std::vector<RealT> > x3_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0));
Teuchos::RCP<ROL::Vector<RealT> > x3p = Teuchos::rcp(new ROL::StdVector<RealT>(x3_rcp));
std::vector<Teuchos::RCP<ROL::Vector<RealT> > > xvec = {x1p, x2p, x3p};
// Create vectors for derivative check
Teuchos::RCP<std::vector<RealT> > xr_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0));
ROL::StdVector<RealT> xr(xr_rcp);
Teuchos::RCP<std::vector<RealT> > d_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0));
ROL::StdVector<RealT> d(d_rcp);
for ( int i = 0; i < nx+2; i++ ) {
(*xr_rcp)[i] = random<RealT>(comm);
(*d_rcp)[i] = random<RealT>(comm);
}
// Build state and adjoint vectors
Teuchos::RCP<std::vector<RealT> > u_rcp = Teuchos::rcp(new std::vector<RealT>(nx,1));
Teuchos::RCP<ROL::Vector<RealT> > up = Teuchos::rcp(new ROL::StdVector<RealT>(u_rcp));
Teuchos::RCP<std::vector<RealT> > p_rcp = Teuchos::rcp(new std::vector<RealT>(nx,0));
Teuchos::RCP<ROL::Vector<RealT> > pp = Teuchos::rcp(new ROL::StdVector<RealT>(p_rcp));
/**********************************************************************************************/
/************************* CONSTRUCT SOL COMPONENTS *******************************************/
/**********************************************************************************************/
// Build samplers
int dim = 4, nSamp = 100;
std::vector<RealT> tmp = {-1, 1};
std::vector<std::vector<RealT> > bounds(dim,tmp);
Teuchos::RCP<ROL::BatchManager<RealT> > bman
= Teuchos::rcp(new ROL::StdTeuchosBatchManager<RealT,int>(comm));
Teuchos::RCP<ROL::SampleGenerator<RealT> > sampler
= Teuchos::rcp(new ROL::MonteCarloGenerator<RealT>(nSamp,bounds,bman,false,false,100));
/**********************************************************************************************/
/************************* CONSTRUCT OBJECTIVE FUNCTION ***************************************/
/**********************************************************************************************/
// Build risk-averse objective function
RealT alpha = 1.e-3;
Teuchos::RCP<ROL::ParametrizedObjective_SimOpt<RealT> > pobjSimOpt
= Teuchos::rcp(new Objective_BurgersControl<RealT>(alpha,nx));
Teuchos::RCP<ROL::ParametrizedEqualityConstraint_SimOpt<RealT> > pconSimOpt
= Teuchos::rcp(new EqualityConstraint_BurgersControl<RealT>(nx));
pconSimOpt->setSolveParameters(*parlist);
Teuchos::RCP<ROL::ParametrizedObjective<RealT> > pObj
= Teuchos::rcp(new ROL::Reduced_ParametrizedObjective_SimOpt<RealT>(pobjSimOpt,pconSimOpt,up,pp));
// Test parametrized objective functions
*outStream << "Check Derivatives of Parametrized Objective Function\n";
xvec[0]->set(xr);
pObj->setParameter(sampler->getMyPoint(0));
pObj->checkGradient(*xvec[0],d,true,*outStream);
pObj->checkHessVec(*xvec[0],d,true,*outStream);
/**********************************************************************************************/
/************************* SMOOTHED CVAR 1.e-2, 1.e-4, 1.e-6 **********************************/
/**********************************************************************************************/
const RealT cl(0.9), cc(1), lb(-0.5), ub(0.5);
const std::string ra = "Risk Averse", rm = "CVaR", dist = "Parabolic";
const bool storage = true;
RealT eps(1.e-2);
std::vector<RealT> stat(3,0);
Teuchos::RCP<ROL::Algorithm<RealT> > algo;
Teuchos::RCP<ROL::StochasticProblem<RealT> > optProb;
for (int i = 0; i < 3; ++i) {
*outStream << "\nSOLVE SMOOTHED CONDITIONAL VALUE AT RISK WITH TRUST REGION\n";
// Build CVaR risk measure
Teuchos::ParameterList list;
list.sublist("SOL").set("Stochastic Optimization Type",ra);
list.sublist("SOL").set("Store Sampled Value and Gradient",storage);
list.sublist("SOL").sublist("Risk Measure").set("Name",rm);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).set("Confidence Level",cl);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).set("Convex Combination Parameter",cc);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).set("Smoothing Parameter",eps);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).sublist("Distribution").set("Name",dist);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).sublist("Distribution").sublist(dist).set("Lower Bound",lb);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).sublist("Distribution").sublist(dist).set("Upper Bound",ub);
// Build stochastic problem
if ( i==0 ) { xvec[i]->zero(); }
else { xvec[i]->set(*xvec[i-1]); }
optProb = Teuchos::rcp(new ROL::StochasticProblem<RealT>(list,pObj,sampler,xvec[i]));
if ( i==0 ) { optProb->setSolutionStatistic(1); }
else { optProb->setSolutionStatistic(stat[i-1]); }
optProb->checkObjectiveGradient(d,true,*outStream);
optProb->checkObjectiveHessVec(d,true,*outStream);
// Run ROL algorithm
algo = Teuchos::rcp(new ROL::Algorithm<RealT>("Trust Region",*parlist,false));
clock_t start = clock();
algo->run(*optProb,true,*outStream);
*outStream << "Optimization time: " << (RealT)(clock()-start)/(RealT)CLOCKS_PER_SEC << " seconds.\n";
// Get solution statistic
stat[i] = optProb->getSolutionStatistic();
// Update smoothing parameter
eps *= static_cast<RealT>(1.e-2);
}
/**********************************************************************************************/
/************************* NONSMOOTH PROBLEM **************************************************/
/**********************************************************************************************/
*outStream << "\nSOLVE NONSMOOTH CVAR PROBLEM WITH BUNDLE TRUST REGION\n";
Teuchos::ParameterList list;
list.sublist("SOL").set("Stochastic Optimization Type",ra);
list.sublist("SOL").set("Store Sampled Value and Gradient",storage);
list.sublist("SOL").sublist("Risk Measure").set("Name",rm);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).set("Confidence Level",cl);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).set("Convex Combination Parameter",cc);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).set("Smoothing Parameter",0.);
list.sublist("SOL").sublist("Risk Measure").sublist(rm).sublist("Distribution").set("Name","Dirac");
list.sublist("SOL").sublist("Risk Measure").sublist(rm).sublist("Distribution").sublist("Dirac").set("Location",0.);
// Build stochastic problem
zp->set(*xvec[2]);
optProb = Teuchos::rcp(new ROL::StochasticProblem<RealT>(list,pObj,sampler,zp));
optProb->setSolutionStatistic(stat[2]);
optProb->checkObjectiveGradient(d,true,*outStream);
optProb->checkObjectiveHessVec(d,true,*outStream);
// Run ROL algorithm
parlist->sublist("Status Test").set("Iteration Limit",1000);
parlist->sublist("Step").sublist("Bundle").set("Epsilon Solution Tolerance",1.e-7);
algo = Teuchos::rcp(new ROL::Algorithm<RealT>("Bundle",*parlist,false));
clock_t start = clock();
algo->run(*optProb,true,*outStream);
*outStream << "Optimization time: " << (RealT)(clock()-start)/(RealT)CLOCKS_PER_SEC << " seconds.\n";
/**********************************************************************************************/
/************************* COMPUTE ERROR ******************************************************/
/**********************************************************************************************/
Teuchos::RCP<ROL::Vector<RealT> > cErr = zp->clone();
RealT zstat = optProb->getSolutionStatistic();
*outStream << "\nSUMMARY:\n";
*outStream << " ---------------------------------------------\n";
*outStream << " True Value-At-Risk = " << zstat << "\n";
*outStream << " ---------------------------------------------\n";
RealT VARerror = std::abs(zstat-stat[0]);
cErr->set(*xvec[0]); cErr->axpy(-1.0,*zp);
RealT CTRLerror = cErr->norm();
RealT TOTerror1 = std::sqrt(std::pow(VARerror,2)+std::pow(CTRLerror,2));
*outStream << " Value-At-Risk (1.e-2) = " << stat[0] << "\n";
*outStream << " Value-At-Risk Error = " << VARerror << "\n";
*outStream << " Control Error = " << CTRLerror << "\n";
*outStream << " Total Error = " << TOTerror1 << "\n";
*outStream << " ---------------------------------------------\n";
VARerror = std::abs(zstat-stat[1]);
cErr->set(*xvec[1]); cErr->axpy(-1.0,*zp);
CTRLerror = cErr->norm();
RealT TOTerror2 = std::sqrt(std::pow(VARerror,2)+std::pow(CTRLerror,2));
*outStream << " Value-At-Risk (1.e-4) = " << stat[1] << "\n";
*outStream << " Value-At-Risk Error = " << VARerror << "\n";
*outStream << " Control Error = " << CTRLerror << "\n";
*outStream << " Total Error = " << TOTerror2 << "\n";
*outStream << " ---------------------------------------------\n";
VARerror = std::abs(zstat-stat[2]);
cErr->set(*xvec[2]); cErr->axpy(-1.0,*zp);
CTRLerror = cErr->norm();
RealT TOTerror3 = std::sqrt(std::pow(VARerror,2)+std::pow(CTRLerror,2));
*outStream << " Value-At-Risk (1.e-6) = " << stat[2] << "\n";
*outStream << " Value-At-Risk Error = " << VARerror << "\n";
*outStream << " Control Error = " << CTRLerror << "\n";
*outStream << " Total Error = " << TOTerror3 << "\n";
*outStream << " ---------------------------------------------\n\n";
// Comparison
errorFlag += ((TOTerror1 < 90.*TOTerror2) && (TOTerror2 < 90.*TOTerror3)) ? 1 : 0;
// Output controls
std::ofstream control;
control.open("example04_control.txt");
for (int n = 0; n < nx+2; n++) {
control << std::scientific << std::setprecision(15)
<< std::setw(25) << static_cast<RealT>(n)/static_cast<RealT>(nx+1)
<< std::setw(25) << (*z_rcp)[n]
<< std::endl;
}
control.close();
}
catch (std::logic_error err) {
*outStream << err.what() << "\n";
errorFlag = -1000;
}; // end try
if (errorFlag != 0)
std::cout << "End Result: TEST FAILED\n";
else
std::cout << "End Result: TEST PASSED\n";
return 0;
}