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// NOX: An Object-Oriented Nonlinear Solver Package
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#ifndef NOX_EPETRA_LINEARSYSTEM_H
#define NOX_EPETRA_LINEARSYSTEM_H
#include "NOX_Epetra_Vector.H" // class data element
#include "NOX_Utils.H" // class data element
#include "NOX_Common.H" // class data element (std::string)
#include "Teuchos_RCP.hpp" // class data element
// Forward declares
namespace NOX {
namespace Epetra {
class Scaling;
}
namespace Parameter {
class List;
}
}
class Epetra_Vector;
class Epetra_Operator;
namespace NOX {
namespace Epetra {
//! Pure virtual class interface for allowing different linear solvers to be used by the NOX::Epetra::Group.
class LinearSystem {
public:
//! Determines handling of the preconditioner between nonlinear iterations.
enum PreconditionerReusePolicyType {
//! Destroy and recreate the preconditioner between nonlinear iterations.
PRPT_REBUILD,
//! Recompute using already allocated structures for preconditioner.
PRPT_RECOMPUTE,
//! Reuse the preconditioner from previous iteration.
PRPT_REUSE
};
public:
//! Constructor.
LinearSystem(){};
//! Destructor.
virtual ~LinearSystem(){};
/*!
\brief Applies Jacobian to the given input vector and puts the answer in the result.
Computes
\f[ v = J u, \f]
where \f$J\f$ is the Jacobian, \f$u\f$ is the input vector,
and \f$v\f$ is the result vector. Returns true if successful.
*/
virtual bool applyJacobian(const NOX::Epetra::Vector& input,
NOX::Epetra::Vector& result) const = 0;
/*!
\brief Applies Jacobian-Transpose to the given input vector and puts the answer in the result.
Computes
\f[ v = J^T u, \f]
where \f$J\f$ is the Jacobian, \f$u\f$ is the input vector, and \f$v\f$ is the result vector. Returns true if successful.
*/
virtual bool applyJacobianTranspose(const NOX::Epetra::Vector& input,
NOX::Epetra::Vector& result) const = 0;
/*!
\brief Applies the inverse of the Jacobian matrix to the given
input vector and puts the answer in result.
Computes
\f[ v = J^{-1} u, \f]
where \f$J\f$ is the Jacobian, \f$u\f$ is the input vector,
and \f$v\f$ is the result vector.
The parameter list contains the linear solver options.
*/
virtual bool applyJacobianInverse(Teuchos::ParameterList ¶ms,
const NOX::Epetra::Vector &input,
NOX::Epetra::Vector &result) = 0;
/*!
\brief Apply right preconditiong to the given input vector
Let \f$M\f$ be a right preconditioner for the Jacobian \f$J\f$; in
other words, \f$M\f$ is a matrix such that
\f[ JM \approx I. \f]
Compute
\f[ u = M^{-1} v, \f]
where \f$u\f$ is the input vector and \f$v\f$ is the result vector.
If <em>useTranspose</em> is true, then the transpose of the
preconditioner is applied:
\f[ u = {M^{-1}}^T v, \f]
The transpose preconditioner is currently only required for
Tensor methods.
The parameter list contains the linear solver options.
*/
virtual bool applyRightPreconditioning(bool useTranspose,
Teuchos::ParameterList& params,
const NOX::Epetra::Vector& input,
NOX::Epetra::Vector& result) const = 0;
//! Get the scaling object
virtual Teuchos::RCP<NOX::Epetra::Scaling> getScaling() = 0;
/*!
\brief Sets the diagonal scaling vector(s) used in scaling the linear system.
See NOX::Epetra::Scaling for details on how to specify scaling
of the linear system.
*/
virtual void
resetScaling(const Teuchos::RCP<NOX::Epetra::Scaling>& s) = 0;
//! Evaluates the Jacobian based on the solution vector x.
virtual bool computeJacobian(const NOX::Epetra::Vector& x) = 0;
/*!
\brief Explicitly constructs a preconditioner based on the solution vector x and the parameter list p.
The user has the option of recomputing the graph when a new
preconditioner is created. The NOX::Epetra::Group controls the
isValid flag for the preconditioner and will control when to call this.
*/
virtual bool createPreconditioner(const NOX::Epetra::Vector& x,
Teuchos::ParameterList& p,
bool recomputeGraph) const = 0;
/*!
\brief Deletes the preconditioner.
The NOX::Epetra::Group controls the isValid flag for the preconditioner and will control when to call this.
*/
virtual bool destroyPreconditioner() const = 0;
/*! \brief Recalculates the preconditioner using an already allocated graph.
Use this to compute a new preconditioner while using the same
graph for the preconditioner. This avoids deleting and
reallocating the memory required for the preconditioner and
results in a big speed-up for large-scale jobs.
*/
virtual bool recomputePreconditioner(const NOX::Epetra::Vector& x,
Teuchos::ParameterList& linearSolverParams) const = 0;
/*! \brief Evaluates the preconditioner policy at the current state.
NOTE: This can change values between nonlienar iterations. It is
not a static value.
*/
virtual PreconditionerReusePolicyType
getPreconditionerPolicy(bool advanceReuseCounter=true) = 0;
//! Indicates whether a preconditioner has been constructed
virtual bool isPreconditionerConstructed() const = 0;
//! Indicates whether the linear system has a preconditioner
virtual bool hasPreconditioner() const = 0;
//! Return Jacobian operator
virtual Teuchos::RCP<const Epetra_Operator>
getJacobianOperator() const = 0;
//! Return Jacobian operator
virtual Teuchos::RCP<Epetra_Operator> getJacobianOperator() = 0;
//! Return preconditioner operator
/*!
* Note: This should only be called if hasPreconditioner() returns true.
*/
virtual Teuchos::RCP<const Epetra_Operator>
getGeneratedPrecOperator() const = 0;
//! Return preconditioner operator
virtual Teuchos::RCP<Epetra_Operator> getGeneratedPrecOperator() = 0;
//! Set Jacobian operator for solve
virtual void setJacobianOperatorForSolve(const
Teuchos::RCP<const Epetra_Operator>& solveJacOp) = 0;
//! Set preconditioner operator for solve
/*!
* Note: This should only be called if hasPreconditioner() returns true.
*/
virtual void setPrecOperatorForSolve(const
Teuchos::RCP<const Epetra_Operator>& solvePrecOp) = 0;
//! Statistics for number of times the linear solver has been called (def: 0)
virtual int getNumLinearSolves() {return 0;};
//! Statistics for number of iterations taken in last linear solve (def: 0)
virtual int getLinearItersLastSolve() {return 0;};
//! Statistics for cumulative number of iterations in all linear solve (def: 0)
virtual int getLinearItersTotal() {return 0;};
//! Statistics for the achieved tolerance of last linear solve (def: 0.0)
virtual double getAchievedTol() {return 0.0;};
};
} // namespace Epetra
} // namespace NOX
#endif
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