PyTrilinos::Amesos::Mumps Class Reference

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List of all members.

Public Member Functions

def __init__
def SymbolicFactorization
def NumericFactorization
def Solve
def Destroy
def SetUseTranspose
def UseTranspose
def SetParameters
def NumSymbolicFact
def NumNumericFact
def NumSolve
def PrintTiming
def PrintStatus
def GetTiming
def SetPrecscaling
def SetRowScaling
def SetColScaling
def SetOrdering
def GetRINFO
def GetINFO
def GetRINFOG
def GetINFOG
def SetICNTL
def SetCNTL
def MatrixShapeOK
def Comm
def GetProblem
def __init__
def SymbolicFactorization
def NumericFactorization
def Solve
def Destroy
def SetUseTranspose
def UseTranspose
def SetParameters
def NumSymbolicFact
def NumNumericFact
def NumSolve
def PrintTiming
def PrintStatus
def GetTiming
def SetPrecscaling
def SetRowScaling
def SetColScaling
def SetOrdering
def GetRINFO
def GetINFO
def GetRINFOG
def GetINFOG
def SetICNTL
def SetCNTL
def MatrixShapeOK
def Comm
def GetProblem

Public Attributes

 this


Detailed Description

Amesos_Mumps: An object-oriented wrapper for the double precision
version of MUMPS.

Amesos_Mumps is an interface to the the double precision version of
the sparse parallel direct solver MUMPS. Given an Epetra_RowMatrix A,
and two Epetra_MultiVectors X and B, the solution with Amesos_Mumps
reads as follows:

Epetra_LinearProblem Problem; Amesos_BaseSolver * Solver; Amesos
Amesos_Factory;

Solver = Amesos_Factory.Create("Amesos_Mumps", Problem);

if( Solver == 0 ) cerr << "library not available" << endl;

Problem.SetMatrix(&A);

Solver-> SymbolicFactorization();

Solver-> NumericFactorization();

Problem.SetLHS(&X);

Problem.SetLHS(&B);

Solver-> Solve();

A number of parameters is available to tune the performances of MUMPS.
We refer to the Amesos Reference Guide for a detailed overview of
these parameters. Here, we just recall that it is possible to solve
the linear system on a subset of the processes contained in the Comm
object of the Epetra_LinearProblem.

Amesos_Mumps accepts any Epetra_RowMatrix derived class. However,
special functions are available for Epetra_CrsMatrix and
Epetra_VbrMatrix objects.

As Amesos is based on Epetra, and Epetra is only double-precision, we
still require an Epetra_LinearProblem composed by a double-precision
matrix, and two double-precision vectors. The solution vector is
casted to double after solution. Single precision may be of interest
if Amesos is used with ML, to solve the coarse problem (for which
single-precision can be enough in term of numerical error, and usually
save memory and CPU time).

Amesos_Mumps is based on Amesos_EpetraBaseSolver, that is derived from
Amesos_BaseSolver. The main redistribution utilities, as well as a
getrow function, is obtained by EpetraBaseSolver.

WARNING:  This interface is compatible with MUMPS 4.5.4.

Marzio Sala, ETHZ.

C++ includes: Amesos_Mumps.h 

Member Function Documentation

def PyTrilinos::Amesos::Mumps::__init__ (   self,
  args 
)

__init__(self, LinearProblem LinearProblem) -> Mumps

Amesos_Mumps::Amesos_Mumps(const Epetra_LinearProblem &LinearProblem)

Amesos_Mumps Constructor.

Creates an Amesos_Mumps instance, using an Epetra_LinearProblem, 

def PyTrilinos::Amesos::Mumps::__init__ (   self,
  args 
)

__init__(self, LinearProblem LinearProblem) -> Mumps

Amesos_Mumps::Amesos_Mumps(const Epetra_LinearProblem &LinearProblem)

Amesos_Mumps Constructor.

Creates an Amesos_Mumps instance, using an Epetra_LinearProblem, 

def PyTrilinos::Amesos::Mumps::Comm (   self,
  args 
)

Comm(self) -> Comm

const Epetra_Comm&
Amesos_Mumps::Comm() const

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

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::Comm (   self,
  args 
)

Comm(self) -> Comm

const Epetra_Comm&
Amesos_Mumps::Comm() const

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

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::Destroy (   self,
  args 
)

Destroy(self)

void
Amesos_Mumps::Destroy()

Destroys all data associated with  this object. 

def PyTrilinos::Amesos::Mumps::Destroy (   self,
  args 
)

Destroy(self)

void
Amesos_Mumps::Destroy()

Destroys all data associated with  this object. 

def PyTrilinos::Amesos::Mumps::GetINFO (   self,
  args 
)

GetINFO(self) -> int

int *
Amesos_Mumps::GetINFO()

Gets the pointer to the INFO array (defined on all processes).

Gets the pointer to the internally stored INFO array, of type int. 

def PyTrilinos::Amesos::Mumps::GetINFO (   self,
  args 
)

GetINFO(self) -> int

int *
Amesos_Mumps::GetINFO()

Gets the pointer to the INFO array (defined on all processes).

Gets the pointer to the internally stored INFO array, of type int. 

def PyTrilinos::Amesos::Mumps::GetINFOG (   self,
  args 
)

GetINFOG(self) -> int

int *
Amesos_Mumps::GetINFOG()

Get the pointer to the INFOG array (defined on host only).

Gets the pointer to the internally stored INFOG (defined on the host
process only) array, of type int. 

def PyTrilinos::Amesos::Mumps::GetINFOG (   self,
  args 
)

GetINFOG(self) -> int

int *
Amesos_Mumps::GetINFOG()

Get the pointer to the INFOG array (defined on host only).

Gets the pointer to the internally stored INFOG (defined on the host
process only) array, of type int. 

def PyTrilinos::Amesos::Mumps::GetProblem (   self,
  args 
)

GetProblem(self) -> LinearProblem

const
Epetra_LinearProblem* Amesos_Mumps::GetProblem() const

Gets a pointer to the Epetra_LinearProblem. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::GetProblem (   self,
  args 
)

GetProblem(self) -> LinearProblem

const
Epetra_LinearProblem* Amesos_Mumps::GetProblem() const

Gets a pointer to the Epetra_LinearProblem. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::GetRINFO (   self,
  args 
)

GetRINFO(self) -> double

double *
Amesos_Mumps::GetRINFO()

Gets the pointer to the RINFO array (defined on all processes).

Gets the pointer to the internally stored RINFO array, of type float
if option --enable-amesos-smumps is enabled, double otherwise. 

def PyTrilinos::Amesos::Mumps::GetRINFO (   self,
  args 
)

GetRINFO(self) -> double

double *
Amesos_Mumps::GetRINFO()

Gets the pointer to the RINFO array (defined on all processes).

Gets the pointer to the internally stored RINFO array, of type float
if option --enable-amesos-smumps is enabled, double otherwise. 

def PyTrilinos::Amesos::Mumps::GetRINFOG (   self,
  args 
)

GetRINFOG(self) -> double

double *
Amesos_Mumps::GetRINFOG()

Gets the pointer to the RINFOG array (defined on host only).

Gets the pointer to the internally stored RINFOG array (defined on the
host process only), of type float if option --enable-amesos-smumps is
enabled, double otherwise. 

def PyTrilinos::Amesos::Mumps::GetRINFOG (   self,
  args 
)

GetRINFOG(self) -> double

double *
Amesos_Mumps::GetRINFOG()

Gets the pointer to the RINFOG array (defined on host only).

Gets the pointer to the internally stored RINFOG array (defined on the
host process only), of type float if option --enable-amesos-smumps is
enabled, double otherwise. 

def PyTrilinos::Amesos::Mumps::GetTiming (   self,
  args 
)

GetTiming(self, ParameterList TimingParameterList)

void
Amesos_Mumps::GetTiming(Teuchos::ParameterList &TimingParameterList)
const

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

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::GetTiming (   self,
  args 
)

GetTiming(self, ParameterList TimingParameterList)

void
Amesos_Mumps::GetTiming(Teuchos::ParameterList &TimingParameterList)
const

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

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::MatrixShapeOK (   self,
  args 
)

MatrixShapeOK(self) -> bool

bool
Amesos_Mumps::MatrixShapeOK() const

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::MatrixShapeOK (   self,
  args 
)

MatrixShapeOK(self) -> bool

bool
Amesos_Mumps::MatrixShapeOK() const

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumericFactorization (   self,
  args 
)

NumericFactorization(self) -> int

int
Amesos_Mumps::NumericFactorization()

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumericFactorization (   self,
  args 
)

NumericFactorization(self) -> int

int
Amesos_Mumps::NumericFactorization()

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumNumericFact (   self,
  args 
)

NumNumericFact(self) -> int

int
Amesos_Mumps::NumNumericFact() const

Returns the number of numeric factorizations performed by this object.

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumNumericFact (   self,
  args 
)

NumNumericFact(self) -> int

int
Amesos_Mumps::NumNumericFact() const

Returns the number of numeric factorizations performed by this object.

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumSolve (   self,
  args 
)

NumSolve(self) -> int

int
Amesos_Mumps::NumSolve() const

Returns the number of solves performed by this object. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumSolve (   self,
  args 
)

NumSolve(self) -> int

int
Amesos_Mumps::NumSolve() const

Returns the number of solves performed by this object. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumSymbolicFact (   self,
  args 
)

NumSymbolicFact(self) -> int

int
Amesos_Mumps::NumSymbolicFact() const

Returns the number of symbolic factorizations performed by this
object. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::NumSymbolicFact (   self,
  args 
)

NumSymbolicFact(self) -> int

int
Amesos_Mumps::NumSymbolicFact() const

Returns the number of symbolic factorizations performed by this
object. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::PrintStatus (   self,
  args 
)

PrintStatus(self)

void
Amesos_Mumps::PrintStatus() const

Prints information about the factorization and solution phases.

In the destruction phase, prints out some information furnished by
MUMPS, like the amount of required memory, the MFLOPS. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::PrintStatus (   self,
  args 
)

PrintStatus(self)

void
Amesos_Mumps::PrintStatus() const

Prints information about the factorization and solution phases.

In the destruction phase, prints out some information furnished by
MUMPS, like the amount of required memory, the MFLOPS. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::PrintTiming (   self,
  args 
)

PrintTiming(self)

void
Amesos_Mumps::PrintTiming() const

Prints timing information.

In the destruction phase, prints out detailed information about the
various phases: symbolic and numeric factorization, solution,
gather/scatter for vectors and matrices. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::PrintTiming (   self,
  args 
)

PrintTiming(self)

void
Amesos_Mumps::PrintTiming() const

Prints timing information.

In the destruction phase, prints out detailed information about the
various phases: symbolic and numeric factorization, solution,
gather/scatter for vectors and matrices. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::SetCNTL (   self,
  args 
)

SetCNTL(self, int pos, double value)

void
Amesos_Mumps::SetCNTL(int pos, double value)

Set CNTL[pos] to value. pos is expressed in FORTRAN style (starting
from 1). 

def PyTrilinos::Amesos::Mumps::SetCNTL (   self,
  args 
)

SetCNTL(self, int pos, double value)

void
Amesos_Mumps::SetCNTL(int pos, double value)

Set CNTL[pos] to value. pos is expressed in FORTRAN style (starting
from 1). 

def PyTrilinos::Amesos::Mumps::SetColScaling (   self,
  args 
)

SetColScaling(self, double ColSca) -> int

int
Amesos_Mumps::SetColScaling(double *ColSca)

Set column scaling.

Use double precision vectors of size N (global dimension of the
matrix) for column scaling.

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

ColSca:  (In) - float pointer with --enable-amesos-smumps, double
pointer otherwise. 

def PyTrilinos::Amesos::Mumps::SetColScaling (   self,
  args 
)

SetColScaling(self, double ColSca) -> int

int
Amesos_Mumps::SetColScaling(double *ColSca)

Set column scaling.

Use double precision vectors of size N (global dimension of the
matrix) for column scaling.

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

ColSca:  (In) - float pointer with --enable-amesos-smumps, double
pointer otherwise. 

def PyTrilinos::Amesos::Mumps::SetICNTL (   self,
  args 
)

SetICNTL(self, int pos, int value)

void
Amesos_Mumps::SetICNTL(int pos, int value)

Set ICNTL[pos] to value. pos is expressed in FORTRAN style (starting
from 1). 

def PyTrilinos::Amesos::Mumps::SetICNTL (   self,
  args 
)

SetICNTL(self, int pos, int value)

void
Amesos_Mumps::SetICNTL(int pos, int value)

Set ICNTL[pos] to value. pos is expressed in FORTRAN style (starting
from 1). 

def PyTrilinos::Amesos::Mumps::SetOrdering (   self,
  args 
)

SetOrdering(self, int PermIn) -> int

int
Amesos_Mumps::SetOrdering(int *PermIn)

Sets ordering.

Use integer vectors of size N (global dimension of the matrix) as
given ordering. PermIn must be defined on the host only, and allocated
by the user, if the user sets ICNTL(7) = 1. 

def PyTrilinos::Amesos::Mumps::SetOrdering (   self,
  args 
)

SetOrdering(self, int PermIn) -> int

int
Amesos_Mumps::SetOrdering(int *PermIn)

Sets ordering.

Use integer vectors of size N (global dimension of the matrix) as
given ordering. PermIn must be defined on the host only, and allocated
by the user, if the user sets ICNTL(7) = 1. 

def PyTrilinos::Amesos::Mumps::SetParameters (   self,
  args 
)

SetParameters(self, ParameterList ParameterList) -> int

int
Amesos_Mumps::SetParameters(Teuchos::ParameterList &ParameterList)

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::SetParameters (   self,
  args 
)

SetParameters(self, ParameterList ParameterList) -> int

int
Amesos_Mumps::SetParameters(Teuchos::ParameterList &ParameterList)

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::SetPrecscaling (   self,
  args 
)

SetPrecscaling(self, double ColSca, double RowSca) -> int

int
Amesos_Mumps::SetPrecscaling(double *ColSca, double *RowSca)

Set prescaling.

Use double precision vectors of size N (global dimension of the
matrix) as scaling for columns and rows. ColSca and RowSca must be
defined on the host only, and allocated by the user, if the user sets
ICNTL(8) = -1.

Both input vectors are float with --enable-amesos-smumps, double
otherwise. 

def PyTrilinos::Amesos::Mumps::SetPrecscaling (   self,
  args 
)

SetPrecscaling(self, double ColSca, double RowSca) -> int

int
Amesos_Mumps::SetPrecscaling(double *ColSca, double *RowSca)

Set prescaling.

Use double precision vectors of size N (global dimension of the
matrix) as scaling for columns and rows. ColSca and RowSca must be
defined on the host only, and allocated by the user, if the user sets
ICNTL(8) = -1.

Both input vectors are float with --enable-amesos-smumps, double
otherwise. 

def PyTrilinos::Amesos::Mumps::SetRowScaling (   self,
  args 
)

SetRowScaling(self, double RowSca) -> int

int
Amesos_Mumps::SetRowScaling(double *RowSca)

Set row scaling.

Use double precision vectors of size N (global dimension of the
matrix) for row scaling.

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

RowSca:  (In) - float pointer with --enable-amesos-smumps, double
pointer otherwise. 

def PyTrilinos::Amesos::Mumps::SetRowScaling (   self,
  args 
)

SetRowScaling(self, double RowSca) -> int

int
Amesos_Mumps::SetRowScaling(double *RowSca)

Set row scaling.

Use double precision vectors of size N (global dimension of the
matrix) for row scaling.

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

RowSca:  (In) - float pointer with --enable-amesos-smumps, double
pointer otherwise. 

def PyTrilinos::Amesos::Mumps::SetUseTranspose (   self,
  args 
)

SetUseTranspose(self, bool UseTranspose) -> int

int
Amesos_Mumps::SetUseTranspose(bool UseTranspose)

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::SetUseTranspose (   self,
  args 
)

SetUseTranspose(self, bool UseTranspose) -> int

int
Amesos_Mumps::SetUseTranspose(bool UseTranspose)

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::Solve (   self,
  args 
)

Solve(self) -> int

int Amesos_Mumps::Solve()

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::Solve (   self,
  args 
)

Solve(self) -> int

int Amesos_Mumps::Solve()

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::SymbolicFactorization (   self,
  args 
)

SymbolicFactorization(self) -> int

int
Amesos_Mumps::SymbolicFactorization()

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::SymbolicFactorization (   self,
  args 
)

SymbolicFactorization(self) -> int

int
Amesos_Mumps::SymbolicFactorization()

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 from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::UseTranspose (   self,
  args 
)

UseTranspose(self) -> bool

bool
Amesos_Mumps::UseTranspose() const

Returns the current UseTranspose setting. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.

def PyTrilinos::Amesos::Mumps::UseTranspose (   self,
  args 
)

UseTranspose(self) -> bool

bool
Amesos_Mumps::UseTranspose() const

Returns the current UseTranspose setting. 

Reimplemented from PyTrilinos::Amesos::BaseSolver.


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

Generated on Thu Dec 17 11:00:19 2009 for PyTrilinos by  doxygen 1.5.9