PyTrilinos::AztecOO::AztecOO Class Reference

Inheritance diagram for PyTrilinos::AztecOO::AztecOO:

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Collaboration diagram for PyTrilinos::AztecOO::AztecOO:

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List of all members.

Public Member Functions

def __init__
def SetProblem
def SetUserOperator
def SetUserMatrix
def SetLHS
def SetRHS
def SetPrecMatrix
def SetPrecOperator
def SetStatusTest
def SetOutputStream
def SetErrorStream
def SetPreconditioner
def SetScaling
def SetMatrixName
def SetLabel
def GetLabel
def ConstructPreconditioner
def DestroyPreconditioner
def Condest
def CheckInput
def GetProblem
def GetUserOperator
def GetUserMatrix
def GetPrecOperator
def GetPrecMatrix
def GetLHS
def GetRHS
def PrintLinearSystem
def SetParameters
def SetAztecDefaults
def SetAztecOption
def GetAztecOption
def SetAztecParam
def SetAllAztecOptions
def SetAllAztecParams
def Iterate
def recursiveIterate
def SetUseAdaptiveDefaultsTrue
def SetAdaptiveParams
def AdaptiveIterate
def NumIters
def TrueResidual
def ScaledResidual
def RecursiveResidual
def SolveTime
def GetAllAztecOptions
def GetAllAztecParams
def GetAztecStatus
def __init__
def SetProblem
def SetUserOperator
def SetUserMatrix
def SetLHS
def SetRHS
def SetPrecMatrix
def SetPrecOperator
def SetStatusTest
def SetOutputStream
def SetErrorStream
def SetPreconditioner
def SetScaling
def SetMatrixName
def SetLabel
def GetLabel
def ConstructPreconditioner
def DestroyPreconditioner
def Condest
def CheckInput
def GetProblem
def GetUserOperator
def GetUserMatrix
def GetPrecOperator
def GetPrecMatrix
def GetLHS
def GetRHS
def PrintLinearSystem
def SetParameters
def SetAztecDefaults
def SetAztecOption
def GetAztecOption
def SetAztecParam
def SetAllAztecOptions
def SetAllAztecParams
def Iterate
def recursiveIterate
def SetUseAdaptiveDefaultsTrue
def SetAdaptiveParams
def AdaptiveIterate
def NumIters
def TrueResidual
def ScaledResidual
def RecursiveResidual
def SolveTime
def GetAllAztecOptions
def GetAllAztecParams
def GetAztecStatus

Public Attributes

 this


Detailed Description

AztecOO: An object-oriented wrapper for Aztec.

Currently it accepts a Petra matrix, initial guess and RHS as separate
arguments, or alternatively, accepts a Epetra_LinearProblem. If
constructed using a Epetra_LinearProblem, AztecOO will infer some
solver/preconditioner, etc., options and parameters. Users may
override these choices and manually choose from among the full set of
Aztec options using the SetAztecOption() and SetAztecParam()
functions.

AztecOO will solve a linear systems of equations: $ AX=B $, using
Epetra objects and the Aztec solver library, where $A$ is an
Epetra_Operator or Epetra_RowMatrix (note that the Epetra_Operator
class is a base class for Epetra_RowMatrix so that Epetra_RowMatrix
isa Epetra_Operator.) $X$ and $B$ are Epetra_MultiVector objects.

WARNING:   AztecOO does not presently support solution of more than
one simultaneous right-hand-side.

C++ includes: AztecOO.h 

Member Function Documentation

def PyTrilinos::AztecOO::AztecOO::__init__ (   self,
  args 
)

__init__(self, Operator A, Epetra_MultiVector X, Epetra_MultiVector B) -> AztecOO
__init__(self, RowMatrix A, Epetra_MultiVector X, Epetra_MultiVector B) -> AztecOO
__init__(self, LinearProblem LinearProblem) -> AztecOO
__init__(self) -> AztecOO
__init__(self, AztecOO Solver) -> AztecOO

AztecOO::AztecOO(const
AztecOO &Solver)

AztecOO Copy Constructor.

Makes copy of an existing AztecOO instance. 

def PyTrilinos::AztecOO::AztecOO::__init__ (   self,
  args 
)

__init__(self, Operator A, Epetra_MultiVector X, Epetra_MultiVector B) -> AztecOO
__init__(self, RowMatrix A, Epetra_MultiVector X, Epetra_MultiVector B) -> AztecOO
__init__(self, LinearProblem LinearProblem) -> AztecOO
__init__(self) -> AztecOO
__init__(self, AztecOO Solver) -> AztecOO

AztecOO::AztecOO(const
AztecOO &Solver)

AztecOO Copy Constructor.

Makes copy of an existing AztecOO instance. 

def PyTrilinos::AztecOO::AztecOO::AdaptiveIterate (   self,
  args 
)

AdaptiveIterate(self, int MaxIters, int MaxSolveAttempts, double Tolerance) -> int

int
AztecOO::AdaptiveIterate(int MaxIters, int MaxSolveAttempts, double
Tolerance)

Attempts to solve the given linear problem using an adaptive strategy.

def PyTrilinos::AztecOO::AztecOO::AdaptiveIterate (   self,
  args 
)

AdaptiveIterate(self, int MaxIters, int MaxSolveAttempts, double Tolerance) -> int

int
AztecOO::AdaptiveIterate(int MaxIters, int MaxSolveAttempts, double
Tolerance)

Attempts to solve the given linear problem using an adaptive strategy.

def PyTrilinos::AztecOO::AztecOO::CheckInput (   self,
  args 
)

CheckInput(self) -> int

int AztecOO::CheckInput()
const

Prints a summary of solver parameters, performs simple sanity checks.

def PyTrilinos::AztecOO::AztecOO::CheckInput (   self,
  args 
)

CheckInput(self) -> int

int AztecOO::CheckInput()
const

Prints a summary of solver parameters, performs simple sanity checks.

def PyTrilinos::AztecOO::AztecOO::Condest (   self,
  args 
)

Condest(self) -> double

double AztecOO::Condest()
const

Returns the condition number estimate for the current preconditioner,
if one exists, returns -1.0 if no estimate. 

def PyTrilinos::AztecOO::AztecOO::Condest (   self,
  args 
)

Condest(self) -> double

double AztecOO::Condest()
const

Returns the condition number estimate for the current preconditioner,
if one exists, returns -1.0 if no estimate. 

def PyTrilinos::AztecOO::AztecOO::ConstructPreconditioner (   self,
  args 
)

ConstructPreconditioner(self, double condest) -> int

int
AztecOO::ConstructPreconditioner(double &condest)

Forces explicit construction and retention of an AztecOO native
preconditioner.

AztecOO typically constructs the preconditioner on the first call to
the solve function. However, there are situations where we would like
to compute the preconditioner ahead of time. One particular case is
when we want to confirm that the preconditioner well-conditioned. This
method allows us to precompute the preconditioner. It also provides a
estimate of the condition number of the preconditioner. If  condest is
large, e.g., > 1.0e+14, it is likely the preconditioner will fail. In
this case, using threshold values (available in the incomplete
factorizations) can be used to reduce the condition number.

Note: This method does not work for user-defined preconditioners
(defined via calls to SetPrecOperator(). It will return with an error
code of -1 for this case. 

def PyTrilinos::AztecOO::AztecOO::ConstructPreconditioner (   self,
  args 
)

ConstructPreconditioner(self, double condest) -> int

int
AztecOO::ConstructPreconditioner(double &condest)

Forces explicit construction and retention of an AztecOO native
preconditioner.

AztecOO typically constructs the preconditioner on the first call to
the solve function. However, there are situations where we would like
to compute the preconditioner ahead of time. One particular case is
when we want to confirm that the preconditioner well-conditioned. This
method allows us to precompute the preconditioner. It also provides a
estimate of the condition number of the preconditioner. If  condest is
large, e.g., > 1.0e+14, it is likely the preconditioner will fail. In
this case, using threshold values (available in the incomplete
factorizations) can be used to reduce the condition number.

Note: This method does not work for user-defined preconditioners
(defined via calls to SetPrecOperator(). It will return with an error
code of -1 for this case. 

def PyTrilinos::AztecOO::AztecOO::DestroyPreconditioner (   self,
  args 
)

DestroyPreconditioner(self) -> int

int
AztecOO::DestroyPreconditioner()

Destroys a preconditioner computed using ConstructPreconditioner().

The ConstructPreconditioner() method creates a persistent
preconditioner. In other words the preconditioner will be used by all
calls to the Iterate() method. DestroyPreconditioner() deletes the
current preconditioner and restores AztecOO to a state where the
preconditioner will computed on first use of the preconditioner solve.

def PyTrilinos::AztecOO::AztecOO::DestroyPreconditioner (   self,
  args 
)

DestroyPreconditioner(self) -> int

int
AztecOO::DestroyPreconditioner()

Destroys a preconditioner computed using ConstructPreconditioner().

The ConstructPreconditioner() method creates a persistent
preconditioner. In other words the preconditioner will be used by all
calls to the Iterate() method. DestroyPreconditioner() deletes the
current preconditioner and restores AztecOO to a state where the
preconditioner will computed on first use of the preconditioner solve.

def PyTrilinos::AztecOO::AztecOO::GetAllAztecOptions (   self,
  args 
)

GetAllAztecOptions(self) -> PyObject

const int*
AztecOO::GetAllAztecOptions() const

AztecOO option setting function.

Return a pointer to an array (size AZ_OPTIONS_SIZE) of all of the
currently set aztec options. 

def PyTrilinos::AztecOO::AztecOO::GetAllAztecOptions (   self,
  args 
)

GetAllAztecOptions(self) -> PyObject

const int*
AztecOO::GetAllAztecOptions() const

AztecOO option setting function.

Return a pointer to an array (size AZ_OPTIONS_SIZE) of all of the
currently set aztec options. 

def PyTrilinos::AztecOO::AztecOO::GetAllAztecParams (   self,
  args 
)

GetAllAztecParams(self) -> PyObject

const double*
AztecOO::GetAllAztecParams() const

AztecOO param setting function.

Return a pointer to an array (size AZ_PARAMS_SIZE) of all of the
currently set aztec parameters. 

def PyTrilinos::AztecOO::AztecOO::GetAllAztecParams (   self,
  args 
)

GetAllAztecParams(self) -> PyObject

const double*
AztecOO::GetAllAztecParams() const

AztecOO param setting function.

Return a pointer to an array (size AZ_PARAMS_SIZE) of all of the
currently set aztec parameters. 

def PyTrilinos::AztecOO::AztecOO::GetAztecOption (   self,
  args 
)

GetAztecOption(self, int option) -> int

int
AztecOO::GetAztecOption(int option)

AztecOO option getting function.

Get a specific Aztec optioin value. Example:
problem.GetAztecOption(AZ_precond)

See the Aztec 2.1 User Guide for a complete list of these options. 

def PyTrilinos::AztecOO::AztecOO::GetAztecOption (   self,
  args 
)

GetAztecOption(self, int option) -> int

int
AztecOO::GetAztecOption(int option)

AztecOO option getting function.

Get a specific Aztec optioin value. Example:
problem.GetAztecOption(AZ_precond)

See the Aztec 2.1 User Guide for a complete list of these options. 

def PyTrilinos::AztecOO::AztecOO::GetAztecStatus (   self,
  args 
)

GetAztecStatus(self) -> PyObject

const double*
AztecOO::GetAztecStatus() const

Return the Aztec status after iterating.

Returns pointer to the underlying Aztec Status array (of length
AZ_STATUS_SIZE). See the Aztec documenation. 

def PyTrilinos::AztecOO::AztecOO::GetAztecStatus (   self,
  args 
)

GetAztecStatus(self) -> PyObject

const double*
AztecOO::GetAztecStatus() const

Return the Aztec status after iterating.

Returns pointer to the underlying Aztec Status array (of length
AZ_STATUS_SIZE). See the Aztec documenation. 

def PyTrilinos::AztecOO::AztecOO::GetLabel (   self,
  args 
)

GetLabel(self) -> char

const char *
AztecOO::GetLabel() const

Get the label describing this AztecOO object.

Returns the string used to define this object. 

def PyTrilinos::AztecOO::AztecOO::GetLabel (   self,
  args 
)

GetLabel(self) -> char

const char *
AztecOO::GetLabel() const

Get the label describing this AztecOO object.

Returns the string used to define this object. 

def PyTrilinos::AztecOO::AztecOO::GetLHS (   self,
  args 
)

GetLHS(self) -> Epetra_MultiVector

Epetra_MultiVector*
AztecOO::GetLHS() const

Get a pointer to the left-hand-side X. 

def PyTrilinos::AztecOO::AztecOO::GetLHS (   self,
  args 
)

GetLHS(self) -> Epetra_MultiVector

Epetra_MultiVector*
AztecOO::GetLHS() const

Get a pointer to the left-hand-side X. 

def PyTrilinos::AztecOO::AztecOO::GetPrecMatrix (   self,
  args 
)

GetPrecMatrix(self) -> RowMatrix

Epetra_RowMatrix*
AztecOO::GetPrecMatrix() const

Get a pointer to the matrix used to construct the preconditioner. 

def PyTrilinos::AztecOO::AztecOO::GetPrecMatrix (   self,
  args 
)

GetPrecMatrix(self) -> RowMatrix

Epetra_RowMatrix*
AztecOO::GetPrecMatrix() const

Get a pointer to the matrix used to construct the preconditioner. 

def PyTrilinos::AztecOO::AztecOO::GetPrecOperator (   self,
  args 
)

GetPrecOperator(self) -> Operator

Epetra_Operator*
AztecOO::GetPrecOperator() const

Get a pointer to the preconditioner operator. 

def PyTrilinos::AztecOO::AztecOO::GetPrecOperator (   self,
  args 
)

GetPrecOperator(self) -> Operator

Epetra_Operator*
AztecOO::GetPrecOperator() const

Get a pointer to the preconditioner operator. 

def PyTrilinos::AztecOO::AztecOO::GetProblem (   self,
  args 
)

GetProblem(self) -> LinearProblem

Epetra_LinearProblem*
AztecOO::GetProblem() const

Get a pointer to the Linear Problem used to construct this solver;
returns zero if not available. 

def PyTrilinos::AztecOO::AztecOO::GetProblem (   self,
  args 
)

GetProblem(self) -> LinearProblem

Epetra_LinearProblem*
AztecOO::GetProblem() const

Get a pointer to the Linear Problem used to construct this solver;
returns zero if not available. 

def PyTrilinos::AztecOO::AztecOO::GetRHS (   self,
  args 
)

GetRHS(self) -> Epetra_MultiVector

Epetra_MultiVector*
AztecOO::GetRHS() const

Get a pointer to the right-hand-side B. 

def PyTrilinos::AztecOO::AztecOO::GetRHS (   self,
  args 
)

GetRHS(self) -> Epetra_MultiVector

Epetra_MultiVector*
AztecOO::GetRHS() const

Get a pointer to the right-hand-side B. 

def PyTrilinos::AztecOO::AztecOO::GetUserMatrix (   self,
  args 
)

GetUserMatrix(self) -> RowMatrix

Epetra_RowMatrix*
AztecOO::GetUserMatrix() const

Get a pointer to the user matrix A. 

def PyTrilinos::AztecOO::AztecOO::GetUserMatrix (   self,
  args 
)

GetUserMatrix(self) -> RowMatrix

Epetra_RowMatrix*
AztecOO::GetUserMatrix() const

Get a pointer to the user matrix A. 

def PyTrilinos::AztecOO::AztecOO::GetUserOperator (   self,
  args 
)

GetUserOperator(self) -> Operator

Epetra_Operator*
AztecOO::GetUserOperator() const

Get a pointer to the user operator A. 

def PyTrilinos::AztecOO::AztecOO::GetUserOperator (   self,
  args 
)

GetUserOperator(self) -> Operator

Epetra_Operator*
AztecOO::GetUserOperator() const

Get a pointer to the user operator A. 

def PyTrilinos::AztecOO::AztecOO::Iterate (   self,
  args 
)

Iterate(self, int MaxIters, double Tolerance) -> int
Iterate(self, RowMatrix A, Epetra_MultiVector X, Epetra_MultiVector B, 
    int MaxIters, double Tolerance) -> int

int
AztecOO::Iterate(Epetra_RowMatrix *A, Epetra_MultiVector *X,
Epetra_MultiVector *B, int MaxIters, double Tolerance)

AztecOO iteration function.

Iterates on the specified matrix and vectors until MaxIters or
Tolerance is reached.. 

def PyTrilinos::AztecOO::AztecOO::Iterate (   self,
  args 
)

Iterate(self, int MaxIters, double Tolerance) -> int
Iterate(self, RowMatrix A, Epetra_MultiVector X, Epetra_MultiVector B, 
    int MaxIters, double Tolerance) -> int

int
AztecOO::Iterate(Epetra_RowMatrix *A, Epetra_MultiVector *X,
Epetra_MultiVector *B, int MaxIters, double Tolerance)

AztecOO iteration function.

Iterates on the specified matrix and vectors until MaxIters or
Tolerance is reached.. 

def PyTrilinos::AztecOO::AztecOO::NumIters (   self,
  args 
)

NumIters(self) -> int

int AztecOO::NumIters()
const

Returns the total number of iterations performed on this problem. 

def PyTrilinos::AztecOO::AztecOO::NumIters (   self,
  args 
)

NumIters(self) -> int

int AztecOO::NumIters()
const

Returns the total number of iterations performed on this problem. 

def PyTrilinos::AztecOO::AztecOO::PrintLinearSystem (   self,
  args 
)

PrintLinearSystem(self, char name)

void
AztecOO::PrintLinearSystem(const char *name)

Print linear-system to files.

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

name:  Print the matrix to the file A_'name', and print the solution
and rhs vectors to files X_'name' and B_'name', respectively. Will
only produce a matrix file if the run-time-type of the matrix is
either Epetra_CrsMatrix or Epetra_VbrMatrix. 

def PyTrilinos::AztecOO::AztecOO::PrintLinearSystem (   self,
  args 
)

PrintLinearSystem(self, char name)

void
AztecOO::PrintLinearSystem(const char *name)

Print linear-system to files.

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

name:  Print the matrix to the file A_'name', and print the solution
and rhs vectors to files X_'name' and B_'name', respectively. Will
only produce a matrix file if the run-time-type of the matrix is
either Epetra_CrsMatrix or Epetra_VbrMatrix. 

def PyTrilinos::AztecOO::AztecOO::recursiveIterate (   self,
  args 
)

recursiveIterate(self, int MaxIters, double Tolerance) -> int

int
AztecOO::recursiveIterate(int MaxIters, double Tolerance)

AztecOO iteration functions.

Iterates on the current problem until MaxIters or Tolerance is
reached.. This one should be suitable for recursive invocations of
Aztec. 

def PyTrilinos::AztecOO::AztecOO::recursiveIterate (   self,
  args 
)

recursiveIterate(self, int MaxIters, double Tolerance) -> int

int
AztecOO::recursiveIterate(int MaxIters, double Tolerance)

AztecOO iteration functions.

Iterates on the current problem until MaxIters or Tolerance is
reached.. This one should be suitable for recursive invocations of
Aztec. 

def PyTrilinos::AztecOO::AztecOO::RecursiveResidual (   self,
  args 
)

RecursiveResidual(self) -> double

double
AztecOO::RecursiveResidual() const

Returns the recursive residual for this problem. 

def PyTrilinos::AztecOO::AztecOO::RecursiveResidual (   self,
  args 
)

RecursiveResidual(self) -> double

double
AztecOO::RecursiveResidual() const

Returns the recursive residual for this problem. 

def PyTrilinos::AztecOO::AztecOO::ScaledResidual (   self,
  args 
)

ScaledResidual(self) -> double

double
AztecOO::ScaledResidual() const

Returns the true scaled residual for this problem. 

def PyTrilinos::AztecOO::AztecOO::ScaledResidual (   self,
  args 
)

ScaledResidual(self) -> double

double
AztecOO::ScaledResidual() const

Returns the true scaled residual for this problem. 

def PyTrilinos::AztecOO::AztecOO::SetAdaptiveParams (   self,
  args 
)

SetAdaptiveParams(self, int NumTrials, double athresholds, double rthresholds, 
    double condestThreshold, double maxFill, 
    int maxKspace) -> int

int
AztecOO::SetAdaptiveParams(int NumTrials, double *athresholds, double
*rthresholds, double condestThreshold, double maxFill, int maxKspace)

Set the parameter that control the AdaptiveIterate() method.

The AdaptiveIterate() method attempts to solve a given problem using
multiple preconditioner and iterative method tuning parameters. There
are defaults that are coded into AdaptiveIterate() method, but the
defaults can be over-ridden by the use of the SetAdaptiveParams()
method. Details of condition number management follow:

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

NumTrials:  In The number of Athresh and Rthresh pairs that should be
tried when attempting to stabilize the preconditioner.

athresholds:  In The list of absolute threshold values that should be
tried when attempting to stabilize the preconditioner.

rthresholds:  In The list of relative threshold values that should be
tried when attempting to stabilize the preconditioner.

condestThreshold:  In If the condition number estimate of the
preconditioner is above this number, no attempt will be made to try
iterations. Instead a new preconditioner will be computed using the
next threshold pair.

maxFill:  In In addition to managing the condest, the
AdaptiveIterate() method will also try to increase the preconditioner
fill if it is determined that this might help. maxFill specifies the
maximum fill allowed.

maxKspace:  In In addition to managing the condest, the
AdaptiveIterate() method will also try to increase the Krylov subspace
size if GMRES is being used and it is determined that this might help.
maxKspace specifies the maximum Krylov subspace allowed. 

def PyTrilinos::AztecOO::AztecOO::SetAdaptiveParams (   self,
  args 
)

SetAdaptiveParams(self, int NumTrials, double athresholds, double rthresholds, 
    double condestThreshold, double maxFill, 
    int maxKspace) -> int

int
AztecOO::SetAdaptiveParams(int NumTrials, double *athresholds, double
*rthresholds, double condestThreshold, double maxFill, int maxKspace)

Set the parameter that control the AdaptiveIterate() method.

The AdaptiveIterate() method attempts to solve a given problem using
multiple preconditioner and iterative method tuning parameters. There
are defaults that are coded into AdaptiveIterate() method, but the
defaults can be over-ridden by the use of the SetAdaptiveParams()
method. Details of condition number management follow:

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

NumTrials:  In The number of Athresh and Rthresh pairs that should be
tried when attempting to stabilize the preconditioner.

athresholds:  In The list of absolute threshold values that should be
tried when attempting to stabilize the preconditioner.

rthresholds:  In The list of relative threshold values that should be
tried when attempting to stabilize the preconditioner.

condestThreshold:  In If the condition number estimate of the
preconditioner is above this number, no attempt will be made to try
iterations. Instead a new preconditioner will be computed using the
next threshold pair.

maxFill:  In In addition to managing the condest, the
AdaptiveIterate() method will also try to increase the preconditioner
fill if it is determined that this might help. maxFill specifies the
maximum fill allowed.

maxKspace:  In In addition to managing the condest, the
AdaptiveIterate() method will also try to increase the Krylov subspace
size if GMRES is being used and it is determined that this might help.
maxKspace specifies the maximum Krylov subspace allowed. 

def PyTrilinos::AztecOO::AztecOO::SetAllAztecOptions (   self,
  args 
)

SetAllAztecOptions(self, int options) -> int

int
AztecOO::SetAllAztecOptions(const int *options)

AztecOO option setting function.

Set all Aztec option values using an existing Aztec options array. 

def PyTrilinos::AztecOO::AztecOO::SetAllAztecOptions (   self,
  args 
)

SetAllAztecOptions(self, int options) -> int

int
AztecOO::SetAllAztecOptions(const int *options)

AztecOO option setting function.

Set all Aztec option values using an existing Aztec options array. 

def PyTrilinos::AztecOO::AztecOO::SetAllAztecParams (   self,
  args 
)

SetAllAztecParams(self, double params) -> int

int
AztecOO::SetAllAztecParams(const double *params)

AztecOO param setting function.

Set all Aztec parameter values using an existing Aztec params array.

def PyTrilinos::AztecOO::AztecOO::SetAllAztecParams (   self,
  args 
)

SetAllAztecParams(self, double params) -> int

int
AztecOO::SetAllAztecParams(const double *params)

AztecOO param setting function.

Set all Aztec parameter values using an existing Aztec params array.

def PyTrilinos::AztecOO::AztecOO::SetAztecDefaults (   self,
  args 
)

SetAztecDefaults(self) -> int

int
AztecOO::SetAztecDefaults()

AztecOO function to restore default options/parameter settings.

This function is called automatically within AztecOO's constructor,
but if constructed using a Epetra_LinearProblem object, some options
are reset based on the ProblemDifficultyLevel associated with the
Epetra_LinearProblem.

See the Aztec 2.1 User Guide for a complete list of these options.

WARNING:  In AztecOO, the default value of options[AZ_poly_ord] is set
to 1. This is different than Aztec 2.1, but the preferred value since
Jacobi preconditioning is used much more often than polynomial
preconditioning and one step of Jacobi is far more effective than 3
steps. 

def PyTrilinos::AztecOO::AztecOO::SetAztecDefaults (   self,
  args 
)

SetAztecDefaults(self) -> int

int
AztecOO::SetAztecDefaults()

AztecOO function to restore default options/parameter settings.

This function is called automatically within AztecOO's constructor,
but if constructed using a Epetra_LinearProblem object, some options
are reset based on the ProblemDifficultyLevel associated with the
Epetra_LinearProblem.

See the Aztec 2.1 User Guide for a complete list of these options.

WARNING:  In AztecOO, the default value of options[AZ_poly_ord] is set
to 1. This is different than Aztec 2.1, but the preferred value since
Jacobi preconditioning is used much more often than polynomial
preconditioning and one step of Jacobi is far more effective than 3
steps. 

def PyTrilinos::AztecOO::AztecOO::SetAztecOption (   self,
  args 
)

SetAztecOption(self, int option, int value) -> int

int
AztecOO::SetAztecOption(int option, int value)

AztecOO option setting function.

Set a specific Aztec option value. Example:
problem.SetAztecOption(AZ_precond, AZ_Jacobi)

See the Aztec 2.1 User Guide for a complete list of these options. 

def PyTrilinos::AztecOO::AztecOO::SetAztecOption (   self,
  args 
)

SetAztecOption(self, int option, int value) -> int

int
AztecOO::SetAztecOption(int option, int value)

AztecOO option setting function.

Set a specific Aztec option value. Example:
problem.SetAztecOption(AZ_precond, AZ_Jacobi)

See the Aztec 2.1 User Guide for a complete list of these options. 

def PyTrilinos::AztecOO::AztecOO::SetAztecParam (   self,
  args 
)

SetAztecParam(self, int param, double value) -> int

int
AztecOO::SetAztecParam(int param, double value)

AztecOO param setting function.

Set a specific Aztec parameter value. Example:
problem.SetAztecParam(AZ_drop, 1.0E-6)

See the Aztec 2.1 User Guide for a complete list of these parameters.

def PyTrilinos::AztecOO::AztecOO::SetAztecParam (   self,
  args 
)

SetAztecParam(self, int param, double value) -> int

int
AztecOO::SetAztecParam(int param, double value)

AztecOO param setting function.

Set a specific Aztec parameter value. Example:
problem.SetAztecParam(AZ_drop, 1.0E-6)

See the Aztec 2.1 User Guide for a complete list of these parameters.

def PyTrilinos::AztecOO::AztecOO::SetErrorStream (   self,
  args 
)

SetErrorStream(self, std::ostream errstrm)

void
AztecOO::SetErrorStream(std::ostream &errstrm)

Set std::ostream for Aztec's error output.

This sets the destination for output that Aztec would normally send to
stderr. 

def PyTrilinos::AztecOO::AztecOO::SetErrorStream (   self,
  args 
)

SetErrorStream(self, std::ostream errstrm)

void
AztecOO::SetErrorStream(std::ostream &errstrm)

Set std::ostream for Aztec's error output.

This sets the destination for output that Aztec would normally send to
stderr. 

def PyTrilinos::AztecOO::AztecOO::SetLabel (   self,
  args 
)

SetLabel(self, char Label)

void
AztecOO::SetLabel(const char *const Label)

Set Label this AztecOO object.

Defines the label used to describe the this object. 

def PyTrilinos::AztecOO::AztecOO::SetLabel (   self,
  args 
)

SetLabel(self, char Label)

void
AztecOO::SetLabel(const char *const Label)

Set Label this AztecOO object.

Defines the label used to describe the this object. 

def PyTrilinos::AztecOO::AztecOO::SetLHS (   self,
  args 
)

SetLHS(self, Epetra_MultiVector X) -> int

int
AztecOO::SetLHS(Epetra_MultiVector *X)

AztecOO LHS Set.

Associates an already defined Epetra_MultiVector (or Epetra_Vector) as
the initial guess and location where the solution will be return. 

def PyTrilinos::AztecOO::AztecOO::SetLHS (   self,
  args 
)

SetLHS(self, Epetra_MultiVector X) -> int

int
AztecOO::SetLHS(Epetra_MultiVector *X)

AztecOO LHS Set.

Associates an already defined Epetra_MultiVector (or Epetra_Vector) as
the initial guess and location where the solution will be return. 

def PyTrilinos::AztecOO::AztecOO::SetMatrixName (   self,
  args 
)

SetMatrixName(self, int label) -> int

int
AztecOO::SetMatrixName(int label)

AztecOO Label Matrix for Aztec.

This is used to label individual matrices within Aztec. This might be
useful if several Aztec invocations are involved corresponding to
different matrices. 

def PyTrilinos::AztecOO::AztecOO::SetMatrixName (   self,
  args 
)

SetMatrixName(self, int label) -> int

int
AztecOO::SetMatrixName(int label)

AztecOO Label Matrix for Aztec.

This is used to label individual matrices within Aztec. This might be
useful if several Aztec invocations are involved corresponding to
different matrices. 

def PyTrilinos::AztecOO::AztecOO::SetOutputStream (   self,
  args 
)

SetOutputStream(self, std::ostream ostrm)

void
AztecOO::SetOutputStream(std::ostream &ostrm)

Set std::ostream for Aztec's screen output.

This sets the destination for output that Aztec would normally send to
stdout. 

def PyTrilinos::AztecOO::AztecOO::SetOutputStream (   self,
  args 
)

SetOutputStream(self, std::ostream ostrm)

void
AztecOO::SetOutputStream(std::ostream &ostrm)

Set std::ostream for Aztec's screen output.

This sets the destination for output that Aztec would normally send to
stdout. 

def PyTrilinos::AztecOO::AztecOO::SetParameters (   self,
  args 
)

SetParameters(self, ParameterList parameterlist, bool cerr_warning_if_unused = False) -> int

def PyTrilinos::AztecOO::AztecOO::SetParameters (   self,
  args 
)

SetParameters(self, ParameterList parameterlist, bool cerr_warning_if_unused = False) -> int

def PyTrilinos::AztecOO::AztecOO::SetPrecMatrix (   self,
  args 
)

SetPrecMatrix(self, RowMatrix PrecMatrix) -> int

int
AztecOO::SetPrecMatrix(Epetra_RowMatrix *PrecMatrix)

AztecOO Preconditioner Matrix Set.

Associates an already defined Epetra_Matrix as the matrix that will be
used by AztecOO when constructing native AztecOO preconditioners. By
default, if AztecOO native preconditioners are used, the original
operator matrix will be used as the source for deriving the
preconditioner. However, there are instances where a user would like
to have the preconditioner be defined using a different matrix than
the original operator matrix. Another common situation is where the
user may not have the operator in matrix form but has a matrix that
approximates the operator and can be used as the basis for an
incomplete factorization. This set method allows the user to pass any
Epetra_RowMatrix to AztecOO for use in constructing an AztecOO native
preconditioner, as long as the matrix implements the Epetra_RowMatrix
pure virtual class, and has proper domain and range map dimensions.
Epetra_CrsMatrix and Epetra_VbrMatrix objects can be passed in through
this method. 

def PyTrilinos::AztecOO::AztecOO::SetPrecMatrix (   self,
  args 
)

SetPrecMatrix(self, RowMatrix PrecMatrix) -> int

int
AztecOO::SetPrecMatrix(Epetra_RowMatrix *PrecMatrix)

AztecOO Preconditioner Matrix Set.

Associates an already defined Epetra_Matrix as the matrix that will be
used by AztecOO when constructing native AztecOO preconditioners. By
default, if AztecOO native preconditioners are used, the original
operator matrix will be used as the source for deriving the
preconditioner. However, there are instances where a user would like
to have the preconditioner be defined using a different matrix than
the original operator matrix. Another common situation is where the
user may not have the operator in matrix form but has a matrix that
approximates the operator and can be used as the basis for an
incomplete factorization. This set method allows the user to pass any
Epetra_RowMatrix to AztecOO for use in constructing an AztecOO native
preconditioner, as long as the matrix implements the Epetra_RowMatrix
pure virtual class, and has proper domain and range map dimensions.
Epetra_CrsMatrix and Epetra_VbrMatrix objects can be passed in through
this method. 

def PyTrilinos::AztecOO::AztecOO::SetPreconditioner (   self,
  args 
)

SetPreconditioner(self, AZ_PRECOND Prec) -> int
SetPreconditioner(self, AZ_PREC_FUN prec_function, void prec_data) -> int

int
AztecOO::SetPreconditioner(AZ_PREC_FUN prec_function, void *prec_data)

AztecOO External Preconditioner Set (function and data).

Associates an external function and data pointer with preconditioner

def PyTrilinos::AztecOO::AztecOO::SetPreconditioner (   self,
  args 
)

SetPreconditioner(self, AZ_PRECOND Prec) -> int
SetPreconditioner(self, AZ_PREC_FUN prec_function, void prec_data) -> int

int
AztecOO::SetPreconditioner(AZ_PREC_FUN prec_function, void *prec_data)

AztecOO External Preconditioner Set (function and data).

Associates an external function and data pointer with preconditioner

def PyTrilinos::AztecOO::AztecOO::SetPrecOperator (   self,
  args 
)

SetPrecOperator(self, Operator PrecOperator) -> int

int
AztecOO::SetPrecOperator(Epetra_Operator *PrecOperator)

AztecOO External Preconditioner Set.

Associates an already defined Epetra_Operator as the preconditioner
that will be called during iterations. This set method allows the user
to pass any type of preconditioner to AztecOO, as long as the
preconditioner implements the Epetra_Operator pure virtual class, and
has proper domain and range map dimensions. Ifpack preconditioners can
be passed in through this method. 

def PyTrilinos::AztecOO::AztecOO::SetPrecOperator (   self,
  args 
)

SetPrecOperator(self, Operator PrecOperator) -> int

int
AztecOO::SetPrecOperator(Epetra_Operator *PrecOperator)

AztecOO External Preconditioner Set.

Associates an already defined Epetra_Operator as the preconditioner
that will be called during iterations. This set method allows the user
to pass any type of preconditioner to AztecOO, as long as the
preconditioner implements the Epetra_Operator pure virtual class, and
has proper domain and range map dimensions. Ifpack preconditioners can
be passed in through this method. 

def PyTrilinos::AztecOO::AztecOO::SetProblem (   self,
  args 
)

SetProblem(self, LinearProblem prob, bool call_SetPrecMatrix = False) -> int

int
AztecOO::SetProblem(const Epetra_LinearProblem &prob, bool
call_SetPrecMatrix=false)

AztecOO Epetra_LinearProblem Set.

Associates an already defined Epetra_LinearProblem as the problem that
will be solved during iterations. This method allows the user to
change which problem is being solved by an existing AztecOO object.

Internally calls SetUserMatrix() if the Epetra_LinearProblem's
operator can be cast to Epetra_RowMatrix, otherwise calls
SetUserOperator().

IMPORTANT WARNING *** This method calls SetUserMatrix(), which also
sets the *preconditioner* matrix to the matrix passed in, by
internally calling SetPrecMatrix(), but *ONLY* if SetPrecMatrix()
hasn't previously been called. If the user wants to make sure that any
pre-existing preconditioner is replaced, they must set the optional
bool argument 'call_SetPrecMatrix' to true, which will force this
function to call SetPrecMatrix().

WARNING:  If a preconditioner has been pre-built and associated with
this AztecOO object, the Epetra_LinearProblem being passed in to this
method must have compatible domain and range maps. 

def PyTrilinos::AztecOO::AztecOO::SetProblem (   self,
  args 
)

SetProblem(self, LinearProblem prob, bool call_SetPrecMatrix = False) -> int

int
AztecOO::SetProblem(const Epetra_LinearProblem &prob, bool
call_SetPrecMatrix=false)

AztecOO Epetra_LinearProblem Set.

Associates an already defined Epetra_LinearProblem as the problem that
will be solved during iterations. This method allows the user to
change which problem is being solved by an existing AztecOO object.

Internally calls SetUserMatrix() if the Epetra_LinearProblem's
operator can be cast to Epetra_RowMatrix, otherwise calls
SetUserOperator().

IMPORTANT WARNING *** This method calls SetUserMatrix(), which also
sets the *preconditioner* matrix to the matrix passed in, by
internally calling SetPrecMatrix(), but *ONLY* if SetPrecMatrix()
hasn't previously been called. If the user wants to make sure that any
pre-existing preconditioner is replaced, they must set the optional
bool argument 'call_SetPrecMatrix' to true, which will force this
function to call SetPrecMatrix().

WARNING:  If a preconditioner has been pre-built and associated with
this AztecOO object, the Epetra_LinearProblem being passed in to this
method must have compatible domain and range maps. 

def PyTrilinos::AztecOO::AztecOO::SetRHS (   self,
  args 
)

SetRHS(self, Epetra_MultiVector B) -> int

int
AztecOO::SetRHS(Epetra_MultiVector *B)

AztecOO RHS Set.

Associates an already defined Epetra_MultiVector (or Epetra_Vector) as
the right-hand-side of the linear system. 

def PyTrilinos::AztecOO::AztecOO::SetRHS (   self,
  args 
)

SetRHS(self, Epetra_MultiVector B) -> int

int
AztecOO::SetRHS(Epetra_MultiVector *B)

AztecOO RHS Set.

Associates an already defined Epetra_MultiVector (or Epetra_Vector) as
the right-hand-side of the linear system. 

def PyTrilinos::AztecOO::AztecOO::SetScaling (   self,
  args 
)

SetScaling(self, AZ_SCALING Scaling) -> int

int
AztecOO::SetScaling(struct AZ_SCALING *Scaling)

AztecOO External Scaling Set.

Associates an already defined Aztec scaling object with this solve. 

def PyTrilinos::AztecOO::AztecOO::SetScaling (   self,
  args 
)

SetScaling(self, AZ_SCALING Scaling) -> int

int
AztecOO::SetScaling(struct AZ_SCALING *Scaling)

AztecOO External Scaling Set.

Associates an already defined Aztec scaling object with this solve. 

def PyTrilinos::AztecOO::AztecOO::SetStatusTest (   self,
  args 
)

SetStatusTest(self, AztecOO_StatusTest StatusTest) -> int

int
AztecOO::SetStatusTest(AztecOO_StatusTest *StatusTest)

AztecOO External Convergence/Status Test Set.

Assigns an already defined AztecOO_StatusTest object as the class that
will determine when iterations should stop, either because convergence
was reached or the iteration failed. This method allows a large
variety of convergence tests to be used with AztecOO. The
AztecOO_StatusTest class is a pure virtual class, so any class that
implements its interface can be passed in to this set method. A number
of pre-defined AztecOO_StatusTest derived classes are already
available, including AztecOO_StatusTestCombo, a class that allows
logical combinations of other status test objects for sophisticated
convergence testing. 

def PyTrilinos::AztecOO::AztecOO::SetStatusTest (   self,
  args 
)

SetStatusTest(self, AztecOO_StatusTest StatusTest) -> int

int
AztecOO::SetStatusTest(AztecOO_StatusTest *StatusTest)

AztecOO External Convergence/Status Test Set.

Assigns an already defined AztecOO_StatusTest object as the class that
will determine when iterations should stop, either because convergence
was reached or the iteration failed. This method allows a large
variety of convergence tests to be used with AztecOO. The
AztecOO_StatusTest class is a pure virtual class, so any class that
implements its interface can be passed in to this set method. A number
of pre-defined AztecOO_StatusTest derived classes are already
available, including AztecOO_StatusTestCombo, a class that allows
logical combinations of other status test objects for sophisticated
convergence testing. 

def PyTrilinos::AztecOO::AztecOO::SetUseAdaptiveDefaultsTrue (   self,
  args 
)

SetUseAdaptiveDefaultsTrue(self) -> int

int
AztecOO::SetUseAdaptiveDefaultsTrue()

Force the AdaptiveIterate() method to use default adaptive strategy.

def PyTrilinos::AztecOO::AztecOO::SetUseAdaptiveDefaultsTrue (   self,
  args 
)

SetUseAdaptiveDefaultsTrue(self) -> int

int
AztecOO::SetUseAdaptiveDefaultsTrue()

Force the AdaptiveIterate() method to use default adaptive strategy.

def PyTrilinos::AztecOO::AztecOO::SetUserMatrix (   self,
  args 
)

SetUserMatrix(self, RowMatrix UserMatrix, bool call_SetPrecMatrix = False) -> int

int
AztecOO::SetUserMatrix(Epetra_RowMatrix *UserMatrix, bool
call_SetPrecMatrix=false)

AztecOO User Matrix Set.

Associates an already defined Epetra_Matrix as the matrix that will be
used by AztecOO as the linear operator when solving the linear system.
Epetra_CrsMatrix and Epetra_VbrMatrix objects can be passed in through
this method.

IMPORTANT WARNING *** This method sets the preconditioner matrix to
the matrix passed in here, by internally calling SetPrecMatrix(), but
*ONLY* if SetPrecMatrix() hasn't previously been called. If the user
wants to make sure that any pre-existing preconditioner is replaced,
they must set the optional bool argument 'call_SetPrecMatrix' to true,
which will force this function to call SetPrecMatrix(). 

def PyTrilinos::AztecOO::AztecOO::SetUserMatrix (   self,
  args 
)

SetUserMatrix(self, RowMatrix UserMatrix, bool call_SetPrecMatrix = False) -> int

int
AztecOO::SetUserMatrix(Epetra_RowMatrix *UserMatrix, bool
call_SetPrecMatrix=false)

AztecOO User Matrix Set.

Associates an already defined Epetra_Matrix as the matrix that will be
used by AztecOO as the linear operator when solving the linear system.
Epetra_CrsMatrix and Epetra_VbrMatrix objects can be passed in through
this method.

IMPORTANT WARNING *** This method sets the preconditioner matrix to
the matrix passed in here, by internally calling SetPrecMatrix(), but
*ONLY* if SetPrecMatrix() hasn't previously been called. If the user
wants to make sure that any pre-existing preconditioner is replaced,
they must set the optional bool argument 'call_SetPrecMatrix' to true,
which will force this function to call SetPrecMatrix(). 

def PyTrilinos::AztecOO::AztecOO::SetUserOperator (   self,
  args 
)

SetUserOperator(self, Operator UserOperator) -> int

int
AztecOO::SetUserOperator(Epetra_Operator *UserOperator)

AztecOO User Operator Set.

Associates an already defined Epetra_Operator as the linear operator
for the linear system system that will be solved during iterations.
This set method allows the user to pass any type of linear operator to
AztecOO, as long as the operator implements the Epetra_Operator pure
virtual class, and has proper domain and range map dimensions.
Epetra_CrsMatrix and Epetra_VbrMatrix objects can be passed in through
this method. 

def PyTrilinos::AztecOO::AztecOO::SetUserOperator (   self,
  args 
)

SetUserOperator(self, Operator UserOperator) -> int

int
AztecOO::SetUserOperator(Epetra_Operator *UserOperator)

AztecOO User Operator Set.

Associates an already defined Epetra_Operator as the linear operator
for the linear system system that will be solved during iterations.
This set method allows the user to pass any type of linear operator to
AztecOO, as long as the operator implements the Epetra_Operator pure
virtual class, and has proper domain and range map dimensions.
Epetra_CrsMatrix and Epetra_VbrMatrix objects can be passed in through
this method. 

def PyTrilinos::AztecOO::AztecOO::SolveTime (   self,
  args 
)

SolveTime(self) -> double

double
AztecOO::SolveTime() const

Returns the solve time. 

def PyTrilinos::AztecOO::AztecOO::SolveTime (   self,
  args 
)

SolveTime(self) -> double

double
AztecOO::SolveTime() const

Returns the solve time. 

def PyTrilinos::AztecOO::AztecOO::TrueResidual (   self,
  args 
)

TrueResidual(self) -> double

double
AztecOO::TrueResidual() const

Returns the true unscaled residual for this problem. 

def PyTrilinos::AztecOO::AztecOO::TrueResidual (   self,
  args 
)

TrueResidual(self) -> double

double
AztecOO::TrueResidual() const

Returns the true unscaled residual for this problem. 


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

Generated on Thu Dec 17 11:00:20 2009 for PyTrilinos by  doxygen 1.5.9