Inheritance diagram for PyTrilinos.Amesos.BaseSolver:

Collaboration diagram for PyTrilinos.Amesos.BaseSolver:

Public Member Functions
def	__init__
def	getParameterList
def	SymbolicFactorization
def	NumericFactorization
def	Solve
def	SetUseTranspose
def	UseTranspose
def	SetParameters
def	GetProblem
def	MatrixShapeOK
def	Comm
def	NumSymbolicFact
def	NumNumericFact
def	NumSolve
def	PrintStatus
def	PrintTiming
def	setParameterList
def	getNonconstParameterList
def	unsetParameterList
def	GetTiming

Detailed Description

Amesos_BaseSolver: A pure virtual class for direct solution of real-
valued double- precision operators.

Pure virtual class for all Amesos concrete implementions.

The Amesos_BaseSolver class is a pure virtual class (that is, it
specifies interface only) that enables the use of real-valued double-
precision direct sparse solvers. Every Amesos class named Amesos_
SolverName derives from Amesos_BaseSolver.

Usage Examples

Basic calling sequence

The basic calling sequence solves A x = b or AT x = b without
specifying how A has changed between each call to Solve().

Re-using the symbolic factorization

The following calling sequence performs multiple solves of A x = b or
AT x = b in cases where the non-zero structure of A remains unchanged
between each call to Solve().

Re-using the numeric factorization

The following calling sequence performs multiple solves of A x = b or
AT x = b provided that A remains unchanged between each call to
Solve().

Constructor requirements

Every Amesos_SolverName class should accept an Epetra_LinearProblem

Mathematical methods

Four mathematical methods are defined in the base class
Amesos_BaseSolver: SymbolicFactorization(), NumericFactorization(),
and Solve().

Switching concrete classes

Different concrete classes, each based on a different third party
solver, will have different performance characteristics and will
accept different parameters.

Changing the values of the underlying matrix operator.

Any changes to the values of a matrix must be accompanied by a call to
NumericFactorization() before the next call to Solve() or the behavior
of Solve() is undefined. Any changes to the numerical structure of the
matrix must be followed by a call to SymbolicFactorization() and
NumericalFactorization() before the next call to Solve().

Once SymbolicFactorization() has been called, classes implementing
this interface may assume that any change made to the non-zero
structure of the underlying matrix will be accompanied by a call to
SymbolicFactorization() prior to a subsequent call to
NumericFactorization or Solve().

Named Parameters

Parameters can be changed or added at any time by calling
SetParameters(ParamList) with the new parameters specified in
ParamList.

It is left to the user to be sure that changes made to the parameters
are appropriate for the concrete class that they are using.

Examples of appropriate changes in parameters include:  Changing
iterative refinement rules between calls to Solve()

Changing drop tolerance rules between calls to NumericFactorization()

Examples of inappropriate changes in parameters include:  Changing
drop tolerance rules between solve steps.
Solver.NumericFactorization();
Solver.getList()->set("DropTolerance",.001); Solver.Solve();
Results of making inappropriate changes in parameters is unpredictable
and could include an error return, a bogus result or ignoring the
parameter change.

Transpose solve

Any class implementing Amesos_BaseSolver should handle calls to
SetUseTranspose() at any point. However, the result of a call to
SetUseTranspose() which is not followed by a call to
SymbolicFactorization() and NumericFactorization() is implementation
dependent. Some third party libraries are able to solve AT x = b and
Ax = b using the same factorization. Others will require a new
factorization anytime that a call to SetUseTranspose() changes the
intended solve from AT x = b to Ax = b or vice-versa.

Performance expectations

The following is a list of performance guidelines that classes which
implement the Amesos_BaseSolver class are expected to maintain.

Memory usage:

For serial codes, no more than one extra copy of the original matrix
should be required. Except that some codes require matrix transpostion
which requires additional copies of the input matrix.

For distributed memory codes, no serial copies of the original matrix
should be required.

Robustness requirements

Failures should be caught by AMESOS_CHK_ERR(). The following error
codes should be used: 1: Singular matrix

2: Non-symmetric matrix

3: Matrix is not positive definite

4: Insufficient memory

Because we do not check to see if a matrix has changed between the
call to SymbolicFactorization() and the call to
NumericFactorization(), it is possible that a change to the matrix
will cause a potentially catastrophic error.

C++ includes: Amesos_BaseSolver.h

Member Function Documentation

def PyTrilinos.Amesos.BaseSolver.Comm	(	self,
		args
	)

Comm(BaseSolver self) -> Comm

virtual const
Epetra_Comm& Amesos_BaseSolver::Comm() const =0

Returns a pointer to the Epetra_Comm communicator associated with this
operator.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.getNonconstParameterList	(	self,
		args
	)

getNonconstParameterList(BaseSolver self) -> Teuchos::RCP< Teuchos::ParameterList >

virtual Teuchos::RCP<Teuchos::ParameterList>
Amesos_BaseSolver::getNonconstParameterList()

This is an empty stub.

Reimplemented from PyTrilinos.Teuchos.ParameterListAcceptor.

def PyTrilinos.Amesos.BaseSolver.getParameterList	(	self,
		args
	)

getParameterList(BaseSolver self) -> Teuchos::RCP< Teuchos::ParameterList const >

Teuchos::RCP< const
Teuchos::ParameterList >
Teuchos::ParameterListAcceptor::getParameterList() const

Get const version of the parameter list that was set using
setParameterList().

The default implementation returns:

Reimplemented from PyTrilinos.Teuchos.ParameterListAcceptor.

def PyTrilinos.Amesos.BaseSolver.GetProblem	(	self,
		args
	)

GetProblem(BaseSolver self) -> LinearProblem

virtual const
Epetra_LinearProblem* Amesos_BaseSolver::GetProblem() const =0

Returns the Epetra_LinearProblem.

Warning! Do not call return->SetOperator(...) to attempt to change the
Epetra_Operator object (even if the new matrix has the same
structure). This new operator matrix will be ignored!

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.GetTiming	(	self,
		args
	)

GetTiming(BaseSolver self, ParameterList TimingParameterList)

virtual void
Amesos_BaseSolver::GetTiming(Teuchos::ParameterList
&TimingParameterList) const

Extracts timing information from the current solver and places it in
the parameter list.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.MatrixShapeOK	(	self,
		args
	)

MatrixShapeOK(BaseSolver self) -> bool

virtual bool
Amesos_BaseSolver::MatrixShapeOK() const =0

Returns true if the solver can handle this matrix shape.

Returns true if the matrix shape is one that the underlying sparse
direct solver can handle. Classes that work only on square matrices
should return false for rectangular matrices. Classes that work only
on symmetric matrices whould return false for non-symmetric matrices.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.NumericFactorization	(	self,
		args
	)

NumericFactorization(BaseSolver self) -> int

virtual int Amesos_BaseSolver::NumericFactorization()=0

Performs NumericFactorization on the matrix A.

In addition to performing numeric factorization on the matrix A, the
call to NumericFactorization() implies that no change will be made to
the underlying matrix without a subsequent call to
NumericFactorization().

<br >Preconditions:  GetProblem().GetOperator() != 0 (return -1)

MatrixShapeOk( GetProblem().GetOperator()) == true (return -6)

The non-zero structure of the matrix should not have changed since the
last call to SymbolicFactorization(). (return -2 if the number of non-
zeros changes) Other changes can have arbitrary consequences.

The distribution of the matrix should not have changed since the last
call to SymbolicFactorization()

The matrix should be indexed from 0 to n-1, unless the parameter
"Reindex" was set to "true" prior to the call to
SymbolicFactorization(). (return -3 - if caught)

The paremeter "Reindex" should not be set to "true" except on
CrsMatrices. (return -4)

The paremeter "Reindex" should not be set to "true" unless Amesos
was built with EpetraExt, i.e. with --enable-epetraext on the
configure line. (return -4)

Internal errors retur -5.

<br >Postconditions: Numeric Factorization will be performed (or
marked to be performed) allowing Solve() to be performed correctly
despite a potential change in in the matrix values (though not in the
non-zero structure).

Integer error code, set to 0 if successful.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.NumNumericFact	(	self,
		args
	)

NumNumericFact(BaseSolver self) -> int

virtual int
Amesos_BaseSolver::NumNumericFact() const =0

Returns the number of numeric factorizations performed by this object.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.NumSolve	(	self,
		args
	)

NumSolve(BaseSolver self) -> int

virtual int
Amesos_BaseSolver::NumSolve() const =0

Returns the number of solves performed by this object.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.NumSymbolicFact	(	self,
		args
	)

NumSymbolicFact(BaseSolver self) -> int

virtual
int Amesos_BaseSolver::NumSymbolicFact() const =0

Returns the number of symbolic factorizations performed by this
object.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.PrintStatus	(	self,
		args
	)

PrintStatus(BaseSolver self)

virtual void
Amesos_BaseSolver::PrintStatus() const =0

Prints status information about the current solver.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.PrintTiming	(	self,
		args
	)

PrintTiming(BaseSolver self)

virtual void
Amesos_BaseSolver::PrintTiming() const =0

Prints timing information about the current solver.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.setParameterList	(	self,
		args
	)

setParameterList(BaseSolver self, Teuchos::RCP< Teuchos::ParameterList > const & paramList)

virtual
void Amesos_BaseSolver::setParameterList(Teuchos::RCP<
Teuchos::ParameterList > const &paramList)

Redefined from Teuchos::ParameterListAcceptor.

Reimplemented from PyTrilinos.Teuchos.ParameterListAcceptor.

Reimplemented in PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.SetParameters	(	self,
		args
	)

SetParameters(BaseSolver self, ParameterList ParameterList) -> int

virtual int
Amesos_BaseSolver::SetParameters(Teuchos::ParameterList
&ParameterList)=0

Updates internal variables.

<br >Preconditions: None.

<br >Postconditions: Internal variables controlling the factorization
and solve will be updated and take effect on all subseuent calls to
NumericFactorization() and Solve().

All parameters whose value are to differ from the default values must
be included in ParameterList. Parameters not specified in
ParameterList revert to their default values.

Integer error code, set to 0 if successful.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.SetUseTranspose	(	self,
		args
	)

SetUseTranspose(BaseSolver self, bool UseTranspose) -> int

virtual
int Amesos_BaseSolver::SetUseTranspose(bool UseTranspose)=0

If set true, X will be set to the solution of AT X = B (not A X = B)

If the implementation of this interface does not support transpose
use, this method should return a value of -1.

<br >Preconditions:  SetUseTranspose() should be called prior to the
call to SymbolicFactorization() If NumericFactorization() or Solve()
is called after SetUseTranspose() without an intervening call to
SymbolicFactorization() the result is implementation dependent.

<br >Postconditions: The next factorization and solve will be
performed with the new value of UseTranspose.

Parameters:
-----------

UseTranspose:  -- (In) If true, solve AT X = B, otherwise solve A X =
B.

Integer error code, set to 0 if successful. Set to -1 if this
implementation does not support transpose.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.Solve	(	self,
		args
	)

Solve(BaseSolver self) -> int

virtual int
Amesos_BaseSolver::Solve()=0

Solves A X = B (or AT x = B)

<br >Preconditions:  GetProblem().GetOperator() != 0 (return -1)

MatrixShapeOk( GetProblem().GetOperator()) == true (return -6)

GetProblem()->CheckInput (see Epetra_LinearProblem::CheckInput() for
return values)

The non-zero structure of the matrix should not have changed since the
last call to SymbolicFactorization().

The distribution of the matrix should not have changed since the last
call to SymbolicFactorization()

The matrix should not have changed since the last call to
NumericFactorization().

<br >Postconditions: X will be set such that A X = B (or AT X = B),
within the limits of the accuracy of the underlying solver.

Integer error code, set to 0 if successful.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.SymbolicFactorization	(	self,
		args
	)

SymbolicFactorization(BaseSolver self) -> int

virtual int Amesos_BaseSolver::SymbolicFactorization()=0

Performs SymbolicFactorization on the matrix A.

In addition to performing symbolic factorization on the matrix A, the
call to SymbolicFactorization() implies that no change will be made to
the non-zero structure of the underlying matrix without a subsequent
call to SymbolicFactorization().

<br >Preconditions:  GetProblem().GetOperator() != 0 (return -1)

MatrixShapeOk( GetProblem().GetOperator()) == true (return -6)

<br >Postconditions: Symbolic Factorization will be performed (or
marked to be performed) allowing NumericFactorization() and Solve() to
be called.

Integer error code, set to 0 if successful.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.unsetParameterList	(	self,
		args
	)

unsetParameterList(BaseSolver self) -> Teuchos::RCP< Teuchos::ParameterList >

virtual
Teuchos::RCP<Teuchos::ParameterList>
Amesos_BaseSolver::unsetParameterList()

This is an empty stub.

Reimplemented from PyTrilinos.Teuchos.ParameterListAcceptor.

Reimplemented in PyTrilinos.Amesos.Lapack.

def PyTrilinos.Amesos.BaseSolver.UseTranspose	(	self,
		args
	)

UseTranspose(BaseSolver self) -> bool

virtual bool
Amesos_BaseSolver::UseTranspose() const =0

Returns the current UseTranspose setting.

Reimplemented in PyTrilinos.Amesos.Klu, and PyTrilinos.Amesos.Lapack.

The documentation for this class was generated from the following file:

Amesos.py

Public Member Functions

Detailed Description

Member Function Documentation