int main( int argc, char **argv )
{
// check for parallel computation
#ifdef HAVE_MPI
MPI_Init(&argc, &argv);
Epetra_MpiComm Comm(MPI_COMM_WORLD);
#else
Epetra_SerialComm Comm;
#endif
// define main parameters
double c = 0.25; // continuation parameter
int N = 50; // number of grid points
int maxNewtonIters = 20; // max number of Newton iterations
int maxSteps = 75; // max number of continuation steps taken
// Set flag for whether the computations will be Matrix-free (true) or will use a computed
// Jacobian (false)
bool doMatFree = false;
// Create output file to save solutions
ofstream outFile("Heq4.dat");
outFile.setf(ios::scientific, ios::floatfield);
outFile.precision(10);
// Define the problem class
HeqProblem Problem(N,&Comm,outFile);
// Create the initial guess vector and set it to all ones
Epetra_Vector InitialGuess(Problem.GetMap());
InitialGuess.PutScalar(1.0);
// Create the top level parameter list
Teuchos::RCP<Teuchos::ParameterList> ParamList = Teuchos::rcp(new Teuchos::ParameterList);
// Create LOCA sublist
Teuchos::ParameterList& locaParamsList = ParamList->sublist("LOCA");
// Create the sublist for continuation and set the stepper parameters
Teuchos::ParameterList& stepperList = locaParamsList.sublist("Stepper");
stepperList.set("Continuation Method", "Arc Length");// Default
// stepperList.set("Continuation Method", "Natural");
stepperList.set("Continuation Parameter", "c"); // Must set
stepperList.set("Initial Value", c); // Must set
stepperList.set("Max Value", 100.0); // Must set
stepperList.set("Min Value", 0.0); // Must set
stepperList.set("Max Steps", maxSteps); // Should set
stepperList.set("Max Nonlinear Iterations", maxNewtonIters); // Should set
// Set up parameters to compute Eigenvalues
#ifdef HAVE_LOCA_ANASAZI
// Create Anasazi Eigensolver sublist (needs --with-loca-anasazi)
stepperList.set("Compute Eigenvalues",true);
Teuchos::ParameterList& aList = stepperList.sublist("Eigensolver");
aList.set("Method", "Anasazi");
aList.set("Block Size", 1); // Size of blocks
aList.set("Num Blocks", 20); // Size of Arnoldi factorization
aList.set("Num Eigenvalues", 5); // Number of eigenvalues
// aList.set("Sorting Order", "SR");
aList.set("Convergence Tolerance", 2.0e-7); // Tolerance
aList.set("Step Size", 1); // How often to check convergence
aList.set("Maximum Restarts",2); // Maximum number of restarts
aList.set("Verbosity",
Anasazi::Errors +
Anasazi::Warnings +
Anasazi::FinalSummary); // Verbosity
#else
stepperList.set("Compute Eigenvalues",false);
#endif
stepperList.set("Bordered Solver Method", "Householder");
// stepperList.set("Bordered Solver Method", "Bordering");
// Teuchos::ParameterList& nestedList =
// stepperList.sublist("Nested Bordered Solver");
// nestedList.set("Bordered Solver Method", "Householder");
// nestedList.set("Include UV In Preconditioner", true);
// //nestedList.set("Use P For Preconditioner", true);
// nestedList.set("Preconditioner Method", "SMW");
// Create bifurcation sublist -- use if not doing turning point
Teuchos::ParameterList& bifurcationList = locaParamsList.sublist("Bifurcation");
bifurcationList.set("Type", "None"); // Default
// Create predictor sublist
Teuchos::ParameterList& predictorList = locaParamsList.sublist("Predictor");
predictorList.set("Method", "Secant"); // Default
// predictorList.set("Method", "Constant"); // Other options
// predictorList.set("Method", "Tangent"); // Other options
// Create step size sublist
Teuchos::ParameterList& stepSizeList = locaParamsList.sublist("Step Size");
stepSizeList.set("Method", "Adaptive"); // Default
stepSizeList.set("Initial Step Size", 0.1); // Should set
stepSizeList.set("Min Step Size", 1.0e-4); // Should set
stepSizeList.set("Max Step Size", 1.0); // Should set
stepSizeList.set("Aggressiveness", 0.1);
// Set up NOX info
Teuchos::ParameterList& nlParams = ParamList->sublist("NOX");
// Set the nonlinear solver method
nlParams.set("Nonlinear Solver", "Line Search Based");
// Set the printing parameters in the "Printing" sublist
Teuchos::ParameterList& printParams = nlParams.sublist("Printing");
printParams.set("MyPID", Comm.MyPID());
printParams.set("Output Precision", 5);
printParams.set("Output Processor", 0);
printParams.set("Output Information",
NOX::Utils::OuterIteration +
NOX::Utils::OuterIterationStatusTest +
NOX::Utils::InnerIteration +
NOX::Utils::LinearSolverDetails +
NOX::Utils::Parameters +
NOX::Utils::Details +
NOX::Utils::Warning +
NOX::Utils::StepperIteration +
NOX::Utils::StepperDetails +
NOX::Utils::StepperParameters);
// NOX parameters - Sublist for line search
Teuchos::ParameterList& searchParams = nlParams.sublist("Line Search");
searchParams.set("Method", "Full Step");
// searchParams.set("Method", "Backtrack");
// Sublist for direction
Teuchos::ParameterList& dirParams = nlParams.sublist("Direction");
dirParams.set("Method", "Newton");
Teuchos::ParameterList& newtonParams = dirParams.sublist("Newton");
newtonParams.set("Forcing Term Method", "Constant");
// Sublist for linear solver for the Newton method
Teuchos::ParameterList& lsParams = newtonParams.sublist("Linear Solver");
lsParams.set("Aztec Solver", "GMRES");
lsParams.set("Max Iterations", 800);
lsParams.set("Tolerance", 1e-8);
lsParams.set("Output Frequency", 1);
lsParams.set("Preconditioner", "None");
// lsParams.set("Preconditioner", "AztecOO");
// lsParams.set("Aztec Preconditioner", "ilu");
// lsParams.set("Preconditioner", "Ifpack");
// lsParams.set("Ifpack Preconditioner", "ILU");
// lsParams.set("Preconditioner", "New Ifpack");
// Teuchos::ParameterList& ifpackParams = lsParams.sublist("Ifpack");
// ifpackParams.set("fact: level-of-fill", 1);
// set up the continuation parameter vector
LOCA::ParameterVector p;
p.addParameter("c",c);
// Set up the problem interface
Teuchos::RCP<SimpleProblemInterface> interface =
Teuchos::rcp(new SimpleProblemInterface(&Problem,c) );
Teuchos::RCP<LOCA::Epetra::Interface::Required> iReq = interface;
// Create the operator to hold either the Jacobian matrix or the Matrix-free operator
Teuchos::RCP<Epetra_Operator> A;
Teuchos::RCP<NOX::Epetra::Interface::Jacobian> iJac;
// Need a NOX::Epetra::Vector for constructor
// This becomes the initial guess vector that is used for the nonlinear solves
NOX::Epetra::Vector noxInitGuess(InitialGuess, NOX::DeepCopy);
if (doMatFree) {
// Matrix Free application (Epetra Operator):
Teuchos::RCP<NOX::Epetra::MatrixFree> MF =
Teuchos::rcp(new NOX::Epetra::MatrixFree(printParams, interface, noxInitGuess));
A = MF;
iJac = MF;
}
else { // Computed Jacobian application
A = Teuchos::rcp( Problem.GetMatrix(), false );
iJac = interface;
}
// Build the linear system solver
Teuchos::RCP<NOX::Epetra::LinearSystemAztecOO> linSys =
Teuchos::rcp(new NOX::Epetra::LinearSystemAztecOO(printParams, lsParams,
iReq,
iJac, A,
noxInitGuess));
// Create the Loca (continuation) vector
NOX::Epetra::Vector locaSoln(noxInitGuess);
// Create Epetra Factory
Teuchos::RCP<LOCA::Abstract::Factory> epetraFactory = Teuchos::rcp(new LOCA::Epetra::Factory);
// Create global data object
Teuchos::RCP<LOCA::GlobalData> globalData = LOCA::createGlobalData(ParamList, epetraFactory);
// Create the Group - must be LOCA group
Teuchos::RCP<LOCA::Epetra::Group> grpPtr =
Teuchos::rcp(new LOCA::Epetra::Group(globalData, printParams,
iReq, locaSoln,
linSys, p));
// Calculate the first F(x0) as a starting point. This is only needed for
// certain status tests, to ensure that an initial residual (|r0|) is calculated
grpPtr->computeF();
// Set up the status tests to check for convergence
// Determines the error tolerance for the Newton solves
Teuchos::RCP<NOX::StatusTest::NormF> testNormF =
Teuchos::rcp(new NOX::StatusTest::NormF(1.0e-4));
// Sets the max number of nonlinear (Newton) iterations that will be taken. If this is not
// already set, it will default to the '20' given
Teuchos::RCP<NOX::StatusTest::MaxIters> testMaxIters =
Teuchos::rcp(new NOX::StatusTest::MaxIters(stepperList.get("Max Nonlinear Iterations", 20)));
// This combination of tests will be used by NOX to determine whether the step converged
Teuchos::RCP<NOX::StatusTest::Combo> combo =
Teuchos::rcp(new NOX::StatusTest::Combo(NOX::StatusTest::Combo::OR,
testNormF, testMaxIters));
// This is sample code to write and read parameters to/from a file. Currently not activated!
// To use, change the 'XXXHAVE_TEUCHOS_EXTENDED' TO 'HAVE_TEUCHOS_EXTENDED'
#ifdef XXXHAVE_TEUCHOS_EXTENDED
// Write the parameter list to a file
cout << "Writing parameter list to \"input.xml\"" << endl;
Teuchos::writeParameterListToXmlFile(*ParamList, "input.xml");
// Read in the parameter list from a file
cout << "Reading parameter list from \"input.xml\"" << endl;
Teuchos::RCP<Teuchos::ParameterList> paramList2 =
Teuchos::rcp(new Teuchos::ParameterList);
Teuchos::updateParametersFromXmlFile("input.xml", paramList2.get());
ParamList = paramList2;
#endif
// Create the stepper
LOCA::Stepper stepper(globalData, grpPtr, combo, ParamList);
LOCA::Abstract::Iterator::IteratorStatus status = stepper.run();
// Check if the stepper completed
if (status == LOCA::Abstract::Iterator::Finished)
globalData->locaUtils->out() << "\nAll tests passed!" << endl;
else
if (globalData->locaUtils->isPrintType(NOX::Utils::Error))
globalData->locaUtils->out() << "\nStepper failed to converge!" << endl;
// Output the stepper parameter list info
if (globalData->locaUtils->isPrintType(NOX::Utils::StepperParameters)) {
globalData->locaUtils->out() << endl << "Final Parameters" << endl
<< "*******************" << endl;
stepper.getList()->print(globalData->locaUtils->out());
globalData->locaUtils->out() << endl;
}
// Make sure all processors are done and close the output file
Comm.Barrier();
outFile.close();
// Deallocate memory
LOCA::destroyGlobalData(globalData);
#ifdef HAVE_MPI
MPI_Finalize();
#endif
return(EXIT_SUCCESS);
} // DONE!!
int main(int argc, char *argv[])
{
// Initialize MPI
#ifdef HAVE_MPI
MPI_Init(&argc,&argv);
#endif
// Create a communicator for Epetra objects
#ifdef HAVE_MPI
Epetra_MpiComm Comm( MPI_COMM_WORLD );
#else
Epetra_SerialComm Comm;
#endif
bool verbose = false;
if (argc > 1)
if (argv[1][0]=='-' && argv[1][1]=='v')
verbose = true;
// Get the process ID and the total number of processors
int MyPID = Comm.MyPID();
#ifdef HAVE_MPI
int NumProc = Comm.NumProc();
#endif
// define the parameters of the nonlinear PDE problem
int nx = 5;
int ny = 6;
double lambda = 1.0;
PDEProblem Problem(nx,ny,lambda,&Comm);
// starting solution, here a zero vector
Epetra_Vector InitialGuess(Problem.GetMatrix()->Map());
InitialGuess.PutScalar(0.0);
// random vector upon which to apply each operator being tested
Epetra_Vector directionVec(Problem.GetMatrix()->Map());
directionVec.Random();
// Set up the problem interface
Teuchos::RCP<SimpleProblemInterface> interface =
Teuchos::rcp(new SimpleProblemInterface(&Problem) );
// Set up theolver options parameter list
Teuchos::RCP<Teuchos::ParameterList> noxParamsPtr = Teuchos::rcp(new Teuchos::ParameterList);
Teuchos::ParameterList & noxParams = *(noxParamsPtr.get());
// Set the nonlinear solver method
noxParams.set("Nonlinear Solver", "Line Search Based");
// Set up the printing utilities
// Only print output if the "-v" flag is set on the command line
Teuchos::ParameterList& printParams = noxParams.sublist("Printing");
printParams.set("MyPID", MyPID);
printParams.set("Output Precision", 5);
printParams.set("Output Processor", 0);
if( verbose )
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::TestDetails);
NOX::Utils printing(printParams);
// Identify the test problem
if (printing.isPrintType(NOX::Utils::TestDetails))
printing.out() << "Starting epetra/NOX_Operators/NOX_Operators.exe" << std::endl;
// Identify processor information
#ifdef HAVE_MPI
if (printing.isPrintType(NOX::Utils::TestDetails)) {
printing.out() << "Parallel Run" << std::endl;
printing.out() << "Number of processors = " << NumProc << std::endl;
printing.out() << "Print Process = " << MyPID << std::endl;
}
Comm.Barrier();
if (printing.isPrintType(NOX::Utils::TestDetails))
printing.out() << "Process " << MyPID << " is alive!" << std::endl;
Comm.Barrier();
#else
if (printing.isPrintType(NOX::Utils::TestDetails))
printing.out() << "Serial Run" << std::endl;
#endif
int status = 0;
Teuchos::RCP<NOX::Epetra::Interface::Required> iReq = interface;
// Need a NOX::Epetra::Vector for constructor
NOX::Epetra::Vector noxInitGuess(InitialGuess, NOX::DeepCopy);
// Analytic matrix
Teuchos::RCP<Epetra_CrsMatrix> A = Teuchos::rcp( Problem.GetMatrix(), false );
Epetra_Vector A_resultVec(Problem.GetMatrix()->Map());
interface->computeJacobian( InitialGuess, *A );
A->Apply( directionVec, A_resultVec );
// FD operator
Teuchos::RCP<Epetra_CrsGraph> graph = Teuchos::rcp( const_cast<Epetra_CrsGraph*>(&A->Graph()), false );
Teuchos::RCP<NOX::Epetra::FiniteDifference> FD = Teuchos::rcp(
new NOX::Epetra::FiniteDifference(printParams, iReq, noxInitGuess, graph) );
Epetra_Vector FD_resultVec(Problem.GetMatrix()->Map());
FD->computeJacobian(InitialGuess, *FD);
FD->Apply( directionVec, FD_resultVec );
// Matrix-Free operator
Teuchos::RCP<NOX::Epetra::MatrixFree> MF = Teuchos::rcp(
new NOX::Epetra::MatrixFree(printParams, iReq, noxInitGuess) );
Epetra_Vector MF_resultVec(Problem.GetMatrix()->Map());
MF->computeJacobian(InitialGuess, *MF);
MF->Apply( directionVec, MF_resultVec );
// Need NOX::Epetra::Vectors for tests
NOX::Epetra::Vector noxAvec ( A_resultVec , NOX::DeepCopy );
NOX::Epetra::Vector noxFDvec( FD_resultVec, NOX::DeepCopy );
NOX::Epetra::Vector noxMFvec( MF_resultVec, NOX::DeepCopy );
// Create a TestCompare class
NOX::Epetra::TestCompare tester( printing.out(), printing);
double abstol = 1.e-4;
double reltol = 1.e-4 ;
//NOX::TestCompare::CompareType aComp = NOX::TestCompare::Absolute;
status += tester.testVector( noxFDvec, noxAvec, reltol, abstol,
"Finite-Difference Operator Apply Test" );
status += tester.testVector( noxMFvec, noxAvec, reltol, abstol,
"Matrix-Free Operator Apply Test" );
// Summarize test results
if( status == 0 )
printing.out() << "Test passed!" << std::endl;
else
printing.out() << "Test failed!" << std::endl;
#ifdef HAVE_MPI
MPI_Finalize();
#endif
// Final return value (0 = successfull, non-zero = failure)
return status;
}
int main( int argc, char **argv )
{
// check for parallel computation
#ifdef HAVE_MPI
MPI_Init(&argc, &argv);
Epetra_MpiComm Comm(MPI_COMM_WORLD);
#else
Epetra_SerialComm Comm;
#endif
// define main parameters
double c = 0.9999; // continuation parameter
int N = 50; // number of grid points
int maxNewtonIters = 20; // max number of Newton iterations
int maxSteps = 50; // max number of continuation steps taken
int ilocal, iglobal; // counter variables used for loops:
// ilocal = counter for local elements on this processor;
// iglobal = counter to signify global position across all procs
int Myele; // holds the number of elements on the processor
// Set flag for whether the computations will be Matrix-free (true) or will use a computed
// Jacobian (false)
bool doMatFree = false;
// Create output file to save solutions
ofstream outFile("Heq5.dat");
outFile.setf(ios::scientific, ios::floatfield);
outFile.precision(10);
// Define the problem class
HeqProblem Problem(N,&Comm,outFile);
// Build initial guess. The initial guess should be a solution vector x close to the
// bifurcation point.
// Create the initial guess vector
Epetra_Vector InitialGuess(Problem.GetMap());
// Get the number of elements on this processor
Myele = Problem.GetMap().NumMyElements();
// Compute the initial guess. For this example, it is a line from (0,1) to (1,8/3)
for (ilocal=0; ilocal<Myele; ilocal++) {
iglobal=Problem.GetMap().GID(ilocal);
InitialGuess[ilocal]= 1.0 + (5.0*iglobal)/(3.0*(N-1));
}
// Create the null vector for the Jacobian (ie, J*v=0, used to solve the system of equations
// f(x,p)=0; J*v=0; v0*v=1. The solution of the system is [x*,v*,p*]. )
Teuchos::RCP<NOX::Abstract::Vector> nullVec =
Teuchos::rcp(new NOX::Epetra::Vector(InitialGuess));
// Initialize to all ones
nullVec->init(1.0);
// NOTE: init is a function within the NOX::Abstract:Vector class which initializes every
// value of the vector to the value within the parentheses (must be in 'double' format)
// Create the top level parameter list
Teuchos::RCP<Teuchos::ParameterList> ParamList = Teuchos::rcp(new Teuchos::ParameterList);
// Create LOCA sublist
Teuchos::ParameterList& locaParamsList = ParamList->sublist("LOCA");
// Create the sublist for continuation and set the stepper parameters
Teuchos::ParameterList& stepperList = locaParamsList.sublist("Stepper");
//stepperList.set("Continuation Method", "Arc Length");// Default
stepperList.set("Continuation Method", "Natural");
stepperList.set("Continuation Parameter", "dummy"); // Must set
stepperList.set("Initial Value", 999.0); // Must set
stepperList.set("Max Value", 50.0e4); // Must set
stepperList.set("Min Value", 0.0); // Must set
stepperList.set("Max Steps", maxSteps); // Should set
stepperList.set("Max Nonlinear Iterations", maxNewtonIters); // Should set
stepperList.set("Bordered Solver Method", "Bordering");
// Teuchos::ParameterList& nestedList =
// stepperList.sublist("Nested Bordered Solver");
// nestedList.set("Bordered Solver Method", "Householder");
// nestedList.set("Include UV In Preconditioner", true);
// //nestedList.set("Use P For Preconditioner", true);
// nestedList.set("Preconditioner Method", "SMW");
// Set up parameters to compute Eigenvalues
#ifdef HAVE_LOCA_ANASAZI
// Create Anasazi Eigensolver sublist (needs --with-loca-anasazi)
stepperList.set("Compute Eigenvalues",true);
Teuchos::ParameterList& aList = stepperList.sublist("Eigensolver");
aList.set("Method", "Anasazi");
aList.set("Block Size", 1); // Size of blocks
aList.set("Num Blocks", 20); // Size of Arnoldi factorization
aList.set("Num Eigenvalues", 5); // Number of eigenvalues
// aList.set("Sorting Order", "SR");
aList.set("Convergence Tolerance", 2.0e-7); // Tolerance
aList.set("Step Size", 1); // How often to check convergence
aList.set("Maximum Restarts",2); // Maximum number of restarts
aList.set("Verbosity",
Anasazi::Errors +
Anasazi::Warnings +
Anasazi::FinalSummary); // Verbosity
#else
stepperList.set("Compute Eigenvalues",false);
#endif
// Create bifurcation sublist. Note that for turning point continuation, the "type"
// is set to "Turning Point". If not doing TP, type should be "None".
Teuchos::ParameterList& bifurcationList = locaParamsList.sublist("Bifurcation");
bifurcationList.set("Type", "Turning Point");
bifurcationList.set("Bifurcation Parameter", "c");
// bifurcationList.set("Formulation", "Minimally Augmented");
bifurcationList.set("Symmetric Jacobian", false);
bifurcationList.set("Update Null Vectors Every Continuation Step", true);
bifurcationList.set("Update Null Vectors Every Nonlinear Iteration", false);
bifurcationList.set("Transpose Solver Method","Explicit Transpose");
// bifurcationList.set("Transpose Solver Method","Transpose Preconditioner");
// bifurcationList.set("Transpose Solver Method","Left Preconditioning");
bifurcationList.set("Initial Null Vector Computation", "Solve df/dp");
// bifurcationList.set("Initial A Vector", nullVec); // minimally augmented
// bifurcationList.set("Initial B Vector", nullVec); //minimally augmented
// bifurcationList.set("Bordered Solver Method", "Householder");
// bifurcationList.set("Include UV In Preconditioner", true);
// //bifurcationList.set("Use P For Preconditioner", true);
// bifurcationList.set("Preconditioner Method", "SMW");
bifurcationList.set("Formulation", "Moore-Spence");
bifurcationList.set("Solver Method", "Phipps Bordering"); // better for nearly singular matrices
// bifurcationList.set("Solver Method", "Salinger Bordering");
bifurcationList.set("Initial Null Vector", nullVec);
bifurcationList.set("Length Normalization Vector", nullVec);
// Create the sublist for the predictor
Teuchos::ParameterList& predictorList = locaParamsList.sublist("Predictor");
predictorList.set("Method", "Secant"); // Default
// predictorList.set("Method", "Constant"); // Other options
// predictorList.set("Method", "Tangent"); // Other options
// Create step size sublist
Teuchos::ParameterList& stepSizeList = locaParamsList.sublist("Step Size");
stepSizeList.set("Method", "Adaptive"); // Default
stepSizeList.set("Initial Step Size", 0.1); // Should set
stepSizeList.set("Min Step Size", 1.0e-6); // Should set
stepSizeList.set("Max Step Size", 1.0); // Should set
stepSizeList.set("Aggressiveness", 0.1);
// Set up NOX info
Teuchos::ParameterList& nlParams = ParamList->sublist("NOX");
// Set the nonlinear solver method
nlParams.set("Nonlinear Solver", "Line Search Based");
// Set the printing parameters in the "Printing" sublist. This list determines how much
// of the NOX information is output
Teuchos::ParameterList& printParams = nlParams.sublist("Printing");
printParams.set("MyPID", Comm.MyPID());
printParams.set("Output Precision", 5);
printParams.set("Output Processor", 0);
printParams.set("Output Information",
NOX::Utils::OuterIteration +
NOX::Utils::OuterIterationStatusTest +
NOX::Utils::InnerIteration +
NOX::Utils::LinearSolverDetails +
NOX::Utils::Parameters +
NOX::Utils::Details +
NOX::Utils::Warning +
NOX::Utils::StepperIteration +
NOX::Utils::StepperDetails +
NOX::Utils::StepperParameters);
// NOX parameters - Sublist for line search
Teuchos::ParameterList& searchParams = nlParams.sublist("Line Search");
searchParams.set("Method", "Backtrack");
// searchParams.set("Method", "Full Step");
// Sublist for direction
Teuchos::ParameterList& dirParams = nlParams.sublist("Direction");
dirParams.set("Method", "Newton");
Teuchos::ParameterList& newtonParams = dirParams.sublist("Newton");
newtonParams.set("Forcing Term Method", "Constant");
// Sublist for linear solver for the Newton method
Teuchos::ParameterList& lsParams = newtonParams.sublist("Linear Solver");
lsParams.set("Aztec Solver", "GMRES");
lsParams.set("Max Iterations", 800);
lsParams.set("Tolerance", 1e-8);
lsParams.set("Output Frequency", 1);
lsParams.set("Preconditioner", "None");
// lsParams.set("Preconditioner", "AztecOO");
// lsParams.set("Aztec Preconditioner", "ilu");
// lsParams.set("Scaling", "None");
// lsParams.set("Scaling", "Row Sum");
lsParams.set("Compute Scaling Manually", false);
// lsParams.set("Preconditioner", "Ifpack");
// lsParams.set("Ifpack Preconditioner", "ILU");
// lsParams.set("Preconditioner", "New Ifpack");
// Teuchos::ParameterList& ifpackParams = lsParams.sublist("Ifpack");
// ifpackParams.set("fact: level-of-fill", 1);
// Set up the continuation parameter vector
LOCA::ParameterVector p;
p.addParameter("c",c);
p.addParameter("dummy",999.0);
// Create the problem interface
Teuchos::RCP<SimpleProblemInterface> interface =
Teuchos::rcp(new SimpleProblemInterface(&Problem,c) );
Teuchos::RCP<LOCA::Epetra::Interface::Required> iReq = interface;
// Create the operator to hold either the Jacobian matrix or the Matrix-free operator
Teuchos::RCP<Epetra_Operator> A;
// Teuchos::RCP<Epetra_RowMatrix> A;
Teuchos::RCP<NOX::Epetra::Interface::Jacobian> iJac;
// Need a NOX::Epetra::Vector for constructor
// This becomes the initial guess vector that is used for the nonlinear solves
NOX::Epetra::Vector noxInitGuess(InitialGuess, NOX::DeepCopy);
if (doMatFree) {
// Matrix Free application (Epetra Operator):
Teuchos::RCP<NOX::Epetra::MatrixFree> MF =
Teuchos::rcp(new NOX::Epetra::MatrixFree(printParams, interface, noxInitGuess));
A = MF;
iJac = MF;
}
else { // Computed Jacobian application
A = Teuchos::rcp( Problem.GetMatrix(), false );
iJac = interface;
}
// Create scaling object
Teuchos::RCP<NOX::Epetra::Scaling> scaling = Teuchos::null;
// scaling = Teuchos::rcp(new NOX::Epetra::Scaling);
// Teuchos::RCP<Epetra_Vector> scalingVector =
// Teuchos::rcp(new Epetra_Vector(soln.Map()));
// //scaling->addRowSumScaling(NOX::Epetra::Scaling::Left, scalingVector);
// scaling->addColSumScaling(NOX::Epetra::Scaling::Right, scalingVector);
// Create transpose scaling object
Teuchos::RCP<NOX::Epetra::Scaling> trans_scaling = Teuchos::null;
// trans_scaling = Teuchos::rcp(new NOX::Epetra::Scaling);
// Teuchos::RCP<Epetra_Vector> transScalingVector =
// Teuchos::rcp(new Epetra_Vector(soln.Map()));
// trans_scaling->addRowSumScaling(NOX::Epetra::Scaling::Right,
// transScalingVector);
// trans_scaling->addColSumScaling(NOX::Epetra::Scaling::Left,
// transScalingVector);
//bifurcationList.set("Transpose Scaling", trans_scaling);
// Build the linear system solver
Teuchos::RCP<NOX::Epetra::LinearSystemAztecOO> linSys =
Teuchos::rcp(new NOX::Epetra::LinearSystemAztecOO(printParams, lsParams,
iReq,
iJac, A,
noxInitGuess, scaling)); // use if scaling
// noxInitGuess)); // use if no scaling
// Create the Loca (continuation) vector
NOX::Epetra::Vector locaSoln(noxInitGuess);
// Create Epetra Factory
Teuchos::RCP<LOCA::Abstract::Factory> epetraFactory = Teuchos::rcp(new LOCA::Epetra::Factory);
// Create global data object
Teuchos::RCP<LOCA::GlobalData> globalData = LOCA::createGlobalData(ParamList, epetraFactory);
// Create the Group - must be LOCA group
Teuchos::RCP<LOCA::Epetra::Group> grpPtr =
Teuchos::rcp(new LOCA::Epetra::Group(globalData, printParams,
iReq, locaSoln,
linSys, p));
// Calculate the first F(x0) as a starting point. This is only needed for
// certain status tests, to ensure that an initial residual (|r0|) is calculated
grpPtr->computeF();
// Set up the status tests to check for convergence
// Determines the error tolerance for the Newton solves
Teuchos::RCP<NOX::StatusTest::NormF> testNormF =
Teuchos::rcp(new NOX::StatusTest::NormF(1.0e-4));
// Sets the max number of nonlinear (Newton) iterations that will be taken. If this is not
// already set, it will default to the '20' given
Teuchos::RCP<NOX::StatusTest::MaxIters> testMaxIters =
Teuchos::rcp(new NOX::StatusTest::MaxIters(stepperList.get("Max Nonlinear Iterations", 20)));
// This combination of tests will be used by NOX to determine whether the step converged
Teuchos::RCP<NOX::StatusTest::Combo> combo =
Teuchos::rcp(new NOX::StatusTest::Combo(NOX::StatusTest::Combo::OR,
testNormF, testMaxIters));
// This is sample code to write and read parameters to/from a file. Currently not activated!
// To use, change the 'XXXHAVE_TEUCHOS_EXTENDED' TO 'HAVE_TEUCHOS_EXTENDED'
#ifdef XXXHAVE_TEUCHOS_EXTENDED
// Write the parameter list to a file
cout << "Writing parameter list to \"input.xml\"" << endl;
Teuchos::writeParameterListToXmlFile(*ParamList, "input.xml");
// Read in the parameter list from a file
cout << "Reading parameter list from \"input.xml\"" << endl;
Teuchos::RCP<Teuchos::ParameterList> paramList2 =
Teuchos::rcp(new Teuchos::ParameterList);
Teuchos::updateParametersFromXmlFile("input.xml", paramList2.get());
ParamList = paramList2;
#endif
// Create the stepper
LOCA::Stepper stepper(globalData, grpPtr, combo, ParamList);
LOCA::Abstract::Iterator::IteratorStatus status = stepper.run();
// Check if the stepper completed
if (status == LOCA::Abstract::Iterator::Finished)
globalData->locaUtils->out() << "\nAll tests passed!" << endl;
else
if (globalData->locaUtils->isPrintType(NOX::Utils::Error))
globalData->locaUtils->out() << "\nStepper failed to converge!" << endl;
// Output the stepper parameter list info
if (globalData->locaUtils->isPrintType(NOX::Utils::StepperParameters)) {
globalData->locaUtils->out() << endl << "Final Parameters" << endl
<< "*******************" << endl;
stepper.getList()->print(globalData->locaUtils->out());
globalData->locaUtils->out() << endl;
}
// Make sure all processors are done and close the output file
Comm.Barrier();
outFile.close();
// Deallocate memory
LOCA::destroyGlobalData(globalData);
#ifdef HAVE_MPI
MPI_Finalize();
#endif
return(EXIT_SUCCESS);
} // DONE!!
std::pair<int, typename SolverNonLinearTrilinos<T>::real_type>
SolverNonLinearTrilinos<T>::solve ( sparse_matrix_ptrtype& jac_in, // System Jacobian Matrix
vector_ptrtype& x_in, // Solution vector
vector_ptrtype& r_in, // Residual vector
const double, // Stopping tolerance
const unsigned int )
{
//printf("Entering solve...\n");
MatrixEpetra* jac = dynamic_cast<MatrixEpetra *>( jac_in.get() );
VectorEpetra<T>* x = dynamic_cast<VectorEpetra<T>*>( x_in.get() );
// We cast to pointers so we can be sure that they succeeded
// by comparing the result against NULL.
// assert(jac != NULL); assert(jac->mat() != NULL);
// assert(x != NULL); assert(x->vec() != NULL);
// assert(r != NULL); assert(r->vec() != NULL);
// Create the top level parameter list
Teuchos::RCP<Teuchos::ParameterList> nlParamsPtr =
Teuchos::rcp( new Teuchos::ParameterList );
Teuchos::ParameterList& nlParams = *( nlParamsPtr.get() );
// Set the nonlinear solver method
nlParams.set( "Nonlinear Solver", "Line Search Based" );
// Set the printing parameters in the "Printing" sublist
Teuchos::ParameterList& printParams = nlParams.sublist( "Printing" );
printParams.set( "Output Precision", 10 );
printParams.set( "Output Processor", 0 );
printParams.set( "Output Information",
NOX::Utils::OuterIteration +
NOX::Utils::OuterIterationStatusTest +
NOX::Utils::InnerIteration +
NOX::Utils::Parameters +
NOX::Utils::Details +
NOX::Utils::Warning );
// start definition of nonlinear solver parameters
// Sublist for line search
Teuchos::ParameterList& searchParams = nlParams.sublist( "Line Search" );
searchParams.set( "Method", "Polynomial" );
// Sublist for direction
Teuchos::ParameterList& dirParams = nlParams.sublist( "Direction" );
dirParams.set( "Method", "Newton" );
Teuchos::ParameterList& newtonParams = dirParams.sublist( "Newton" );
newtonParams.set( "Forcing Term Method", "Constant" );
// Sublist for linear solver for the Newton method
Teuchos::ParameterList& lsParams = newtonParams.sublist( "Linear Solver" );
lsParams.set( "Aztec Solver", "GMRES" );
lsParams.set( "Max Iterations", 800 );
lsParams.set( "Tolerance", 1e-7 );
lsParams.set( "Output Frequency", 50 );
lsParams.set( "Aztec Preconditioner", "ilu" );
// -> A : Jacobian for the first iteration
// -> InitialGuess : first value x0
//printf("convert vectors...\n");
boost::shared_ptr<Epetra_Vector> InitialGuess = x->epetraVector();
// has_ownership=false in order to let the matrix jac be destroyed by boost
// and not by Teuchos::RCP
Teuchos::RCP<Epetra_CrsMatrix> A =
Teuchos::rcp( ( ( boost::shared_ptr<Epetra_CrsMatrix> )( jac->matrix() ) ).get(),false );
//std::cout << "A.has_ownership()=" << A.has_ownership() << std::endl;
Teuchos::RCP<NOX::Epetra::Interface::Required> iReq =
Teuchos::rcp( new SolverNonLinearTrilinosInterface( this ) );
Teuchos::RCP<NOX::Epetra::Interface::Jacobian> iJac =
Teuchos::rcp( new SolverNonLinearTrilinosInterface( this ) );
Teuchos::RCP<NOX::Epetra::LinearSystemAztecOO> linSys =
Teuchos::rcp( new NOX::Epetra::LinearSystemAztecOO( printParams,
lsParams,
iReq,
iJac,
A,
*InitialGuess ) );
// Need a NOX::Epetra::Vector for constructor
NOX::Epetra::Vector noxInitGuess( *InitialGuess, NOX::DeepCopy );
Teuchos::RCP<NOX::Epetra::Group> grpPtr =
Teuchos::rcp( new NOX::Epetra::Group( printParams,
iReq,
noxInitGuess,
linSys ) );
// Set up the status tests
Teuchos::RCP<NOX::StatusTest::NormF> testNormF =
Teuchos::rcp( new NOX::StatusTest::NormF( 1.0e-7 ) );
Teuchos::RCP<NOX::StatusTest::MaxIters> testMaxIters =
Teuchos::rcp( new NOX::StatusTest::MaxIters( 20 ) );
// this will be the convergence test to be used
Teuchos::RCP<NOX::StatusTest::Combo> combo =
Teuchos::rcp( new NOX::StatusTest::Combo( NOX::StatusTest::Combo::OR,
testNormF, testMaxIters ) );
// Create the solver
Teuchos::RCP<NOX::Solver::Generic> solver =
NOX::Solver::buildSolver( grpPtr, combo, nlParamsPtr );
// Solve the nonlinesar system
NOX::StatusTest::StatusType status = solver->solve();
if ( NOX::StatusTest::Converged != status )
std::cout << "\n" << "-- NOX solver did not converged --" << "\n";
else
std::cout << "\n" << "-- NOX solver converged --" << "\n";
// Print the answer
std::cout << "\n" << "-- Parameter List From Solver --" << "\n";
solver->getList().print( cout );
// Get the Epetra_Vector with the final solution from the solver
const NOX::Epetra::Group & finalGroup =
dynamic_cast<const NOX::Epetra::Group&>( solver->getSolutionGroup() );
const Epetra_Vector & finalSolution =
( dynamic_cast<const NOX::Epetra::Vector&>( finalGroup.getX() ) ).getEpetraVector();
//cout << "Computed solution : " << endl;
//cout << finalSolution;
x_in = boost::shared_ptr<VectorEpetra<T> > ( new VectorEpetra<T>( &finalSolution ) );
//std::cout << "InitialGuess.use_count()=" << InitialGuess.use_count() << std::endl;
//std::cout << "jac.use_count()=" << jac->matrix().use_count() << std::endl;
//std::cout << "x_in.use_count()=" << x_in.use_count() << std::endl;
return std::make_pair( 1,finalGroup.getNormF() );
}
