PyTrilinos::Epetra::SerialDenseSolver Class Reference

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List of all members.

Public Member Functions

def __init__
def SetMatrix
def SetVectors
def FactorWithEquilibration
def SolveWithTranspose
def SolveToRefinedSolution
def EstimateSolutionErrors
def Factor
def Solve
def Invert
def ComputeEquilibrateScaling
def EquilibrateMatrix
def EquilibrateRHS
def ApplyRefinement
def UnequilibrateLHS
def Transpose
def Factored
def A_Equilibrated
def B_Equilibrated
def ShouldEquilibrate
def SolutionErrorsEstimated
def Inverted
def ReciprocalConditionEstimated
def Solved
def SolutionRefined
def Matrix
def FactoredMatrix
def LHS
def RHS
def M
def N
def LDA
def LDB
def NRHS
def LDX
def LDAF
def ANORM
def RCOND
def ROWCND
def COLCND
def AMAX
def IPIV
def A
def B
def X
def AF
def FERR
def BERR
def R
def C
def ReciprocalConditionEstimate
def __init__
def SetMatrix
def SetVectors
def FactorWithEquilibration
def SolveWithTranspose
def SolveToRefinedSolution
def EstimateSolutionErrors
def Factor
def Solve
def Invert
def ComputeEquilibrateScaling
def EquilibrateMatrix
def EquilibrateRHS
def ApplyRefinement
def UnequilibrateLHS
def Transpose
def Factored
def A_Equilibrated
def B_Equilibrated
def ShouldEquilibrate
def SolutionErrorsEstimated
def Inverted
def ReciprocalConditionEstimated
def Solved
def SolutionRefined
def Matrix
def FactoredMatrix
def LHS
def RHS
def M
def N
def LDA
def LDB
def NRHS
def LDX
def LDAF
def ANORM
def RCOND
def ROWCND
def COLCND
def AMAX
def IPIV
def A
def B
def X
def AF
def FERR
def BERR
def R
def C
def ReciprocalConditionEstimate

Public Attributes

 this


Detailed Description

Epetra_SerialDenseSolver: A class for solving dense linear problems.

The Epetra_SerialDenseSolver class enables the definition, in terms of
Epetra_SerialDenseMatrix and Epetra_SerialDenseVector objects, of a
dense linear problem, followed by the solution of that problem via the
most sophisticated techniques available in LAPACK.

The Epetra_SerialDenseSolver class is intended to provide full-
featured support for solving linear problems for general dense
rectangular (or square) matrices. It is written on top of BLAS and
LAPACK and thus has excellent performance and numerical capabilities.
Using this class, one can either perform simple factorizations and
solves or apply all the tricks available in LAPACK to get the best
possible solution for very ill-conditioned problems.

Epetra_SerialDenseSolver vs. Epetra_LAPACK

The Epetra_LAPACK class provides access to most of the same
functionality as Epetra_SerialDenseSolver. The primary difference is
that Epetra_LAPACK is a "thin" layer on top of LAPACK and
Epetra_SerialDenseSolver attempts to provide easy access to the more
sophisticated aspects of solving dense linear and eigensystems. When
you should use Epetra_LAPACK: If you are simply looking for a
convenient wrapper around the Fortran LAPACK routines and you have a
well-conditioned problem, you should probably use Epetra_LAPACK
directly.

When you should use Epetra_SerialDenseSolver: If you want to (or
potentially want to) solve ill-conditioned problems or want to work
with a more object-oriented interface, you should probably use
Epetra_SerialDenseSolver.

Constructing Epetra_SerialDenseSolver Objects

There is a single Epetra_SerialDenseSolver constructor. However, the
matrix, right hand side and solution vectors must be set prior to
executing most methods in this class.

Setting vectors used for linear solves

The matrix A, the left hand side X and the right hand side B (when
solving AX = B, for X), can be set by appropriate set methods. Each of
these three objects must be an Epetra_SerialDenseMatrix or and
Epetra_SerialDenseVector object. The set methods are as follows:
SetMatrix() - Sets the matrix.

SetVectors() - Sets the left and right hand side vector(s).

Vector and Utility Functions

Once a Epetra_SerialDenseSolver is constructed, several mathematical
functions can be applied to the object. Specifically: Factorizations.

Solves.

Condition estimates.

Equilibration.

Norms.

Counting floating point operations The Epetra_SerialDenseSolver class
has Epetra_CompObject as a base class. Thus, floating point operations
are counted and accumulated in the Epetra_Flop object (if any) that
was set using the SetFlopCounter() method in the Epetra_CompObject
base class.

Strategies for Solving Linear Systems In many cases, linear systems
can be accurately solved by simply computing the LU factorization of
the matrix and then performing a forward back solve with a given set
of right hand side vectors. However, in some instances, the
factorization may be very poorly conditioned and this simple approach
may not work. In these situations, equilibration and iterative
refinement may improve the accuracy, or prevent a breakdown in the
factorization.

Epetra_SerialDenseSolver will use equilibration with the factorization
if, once the object is constructed and before it is factored, you call
the function FactorWithEquilibration(true) to force equilibration to
be used. If you are uncertain if equilibration should be used, you may
call the function ShouldEquilibrate() which will return true if
equilibration could possibly help. ShouldEquilibrate() uses guidelines
specified in the LAPACK User Guide, namely if SCOND < 0.1 and AMAX <
Underflow or AMAX > Overflow, to determine if equilibration might be
useful.

Epetra_SerialDenseSolver will use iterative refinement after a
forward/back solve if you call SolveToRefinedSolution(true). It will
also compute forward and backward error estimates if you call
EstimateSolutionErrors(true). Access to the forward (back) error
estimates is available via FERR() ( BERR()).

Examples using Epetra_SerialDenseSolver can be found in the Epetra
test directories.

C++ includes: Epetra_SerialDenseSolver.h 

Member Function Documentation

def PyTrilinos::Epetra::SerialDenseSolver::__init__ (   self  ) 

__init__(self) -> SerialDenseSolver

Epetra_SerialDenseSolver::Epetra_SerialDenseSolver()

Default constructor; matrix should be set using SetMatrix(), LHS and
RHS set with SetVectors(). 

def PyTrilinos::Epetra::SerialDenseSolver::__init__ (   self  ) 

__init__(self) -> SerialDenseSolver

Epetra_SerialDenseSolver::Epetra_SerialDenseSolver()

Default constructor; matrix should be set using SetMatrix(), LHS and
RHS set with SetVectors(). 

def PyTrilinos::Epetra::SerialDenseSolver::A (   self  ) 

A(self) -> PyObject

double*
Epetra_SerialDenseSolver::A() const

Returns pointer to the this matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::A (   self  ) 

A(self) -> PyObject

double*
Epetra_SerialDenseSolver::A() const

Returns pointer to the this matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::A_Equilibrated (   self  ) 

A_Equilibrated(self) -> bool

bool
Epetra_SerialDenseSolver::A_Equilibrated()

Returns true if factor is equilibrated (factor available via AF() and
LDAF()). 

def PyTrilinos::Epetra::SerialDenseSolver::A_Equilibrated (   self  ) 

A_Equilibrated(self) -> bool

bool
Epetra_SerialDenseSolver::A_Equilibrated()

Returns true if factor is equilibrated (factor available via AF() and
LDAF()). 

def PyTrilinos::Epetra::SerialDenseSolver::AF (   self  ) 

AF(self) -> PyObject

double*
Epetra_SerialDenseSolver::AF() const

Returns pointer to the factored matrix (may be the same as A() if
factorization done in place). 

def PyTrilinos::Epetra::SerialDenseSolver::AF (   self  ) 

AF(self) -> PyObject

double*
Epetra_SerialDenseSolver::AF() const

Returns pointer to the factored matrix (may be the same as A() if
factorization done in place). 

def PyTrilinos::Epetra::SerialDenseSolver::AMAX (   self  ) 

AMAX(self) -> double

double
Epetra_SerialDenseSolver::AMAX() const

Returns the absolute value of the largest entry of the this matrix
(returns -1 if not yet computed). 

def PyTrilinos::Epetra::SerialDenseSolver::AMAX (   self  ) 

AMAX(self) -> double

double
Epetra_SerialDenseSolver::AMAX() const

Returns the absolute value of the largest entry of the this matrix
(returns -1 if not yet computed). 

def PyTrilinos::Epetra::SerialDenseSolver::ANORM (   self  ) 

ANORM(self) -> double

double
Epetra_SerialDenseSolver::ANORM() const

Returns the 1-Norm of the this matrix (returns -1 if not yet
computed). 

def PyTrilinos::Epetra::SerialDenseSolver::ANORM (   self  ) 

ANORM(self) -> double

double
Epetra_SerialDenseSolver::ANORM() const

Returns the 1-Norm of the this matrix (returns -1 if not yet
computed). 

def PyTrilinos::Epetra::SerialDenseSolver::ApplyRefinement (   self  ) 

ApplyRefinement(self) -> int

int
Epetra_SerialDenseSolver::ApplyRefinement(void)

Apply Iterative Refinement.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::ApplyRefinement (   self  ) 

ApplyRefinement(self) -> int

int
Epetra_SerialDenseSolver::ApplyRefinement(void)

Apply Iterative Refinement.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::B (   self  ) 

B(self) -> PyObject

double*
Epetra_SerialDenseSolver::B() const

Returns pointer to current RHS. 

def PyTrilinos::Epetra::SerialDenseSolver::B (   self  ) 

B(self) -> PyObject

double*
Epetra_SerialDenseSolver::B() const

Returns pointer to current RHS. 

def PyTrilinos::Epetra::SerialDenseSolver::B_Equilibrated (   self  ) 

B_Equilibrated(self) -> bool

bool
Epetra_SerialDenseSolver::B_Equilibrated()

Returns true if RHS is equilibrated (RHS available via B() and LDB()).

def PyTrilinos::Epetra::SerialDenseSolver::B_Equilibrated (   self  ) 

B_Equilibrated(self) -> bool

bool
Epetra_SerialDenseSolver::B_Equilibrated()

Returns true if RHS is equilibrated (RHS available via B() and LDB()).

def PyTrilinos::Epetra::SerialDenseSolver::BERR (   self  ) 

BERR(self) -> PyObject

double*
Epetra_SerialDenseSolver::BERR() const

Returns a pointer to the backward error estimates computed by LAPACK.

def PyTrilinos::Epetra::SerialDenseSolver::BERR (   self  ) 

BERR(self) -> PyObject

double*
Epetra_SerialDenseSolver::BERR() const

Returns a pointer to the backward error estimates computed by LAPACK.

def PyTrilinos::Epetra::SerialDenseSolver::C (   self  ) 

C(self) -> PyObject

double*
Epetra_SerialDenseSolver::C() const

Returns a pointer to the column scale vector used for equilibration.

def PyTrilinos::Epetra::SerialDenseSolver::C (   self  ) 

C(self) -> PyObject

double*
Epetra_SerialDenseSolver::C() const

Returns a pointer to the column scale vector used for equilibration.

def PyTrilinos::Epetra::SerialDenseSolver::COLCND (   self  ) 

COLCND(self) -> double

double
Epetra_SerialDenseSolver::COLCND() const

Ratio of smallest to largest column scale factors for the this matrix
(returns -1 if not yet computed).

If COLCND() is >= 0.1 then equilibration is not needed. 

def PyTrilinos::Epetra::SerialDenseSolver::COLCND (   self  ) 

COLCND(self) -> double

double
Epetra_SerialDenseSolver::COLCND() const

Ratio of smallest to largest column scale factors for the this matrix
(returns -1 if not yet computed).

If COLCND() is >= 0.1 then equilibration is not needed. 

def PyTrilinos::Epetra::SerialDenseSolver::ComputeEquilibrateScaling (   self  ) 

ComputeEquilibrateScaling(self) -> int

int
Epetra_SerialDenseSolver::ComputeEquilibrateScaling(void)

Computes the scaling vector S(i) = 1/sqrt(A(i,i)) of the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::ComputeEquilibrateScaling (   self  ) 

ComputeEquilibrateScaling(self) -> int

int
Epetra_SerialDenseSolver::ComputeEquilibrateScaling(void)

Computes the scaling vector S(i) = 1/sqrt(A(i,i)) of the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::EquilibrateMatrix (   self  ) 

EquilibrateMatrix(self) -> int

int Epetra_SerialDenseSolver::EquilibrateMatrix(void)

Equilibrates the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::EquilibrateMatrix (   self  ) 

EquilibrateMatrix(self) -> int

int Epetra_SerialDenseSolver::EquilibrateMatrix(void)

Equilibrates the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::EquilibrateRHS (   self  ) 

EquilibrateRHS(self) -> int

int
Epetra_SerialDenseSolver::EquilibrateRHS(void)

Equilibrates the current RHS.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::EquilibrateRHS (   self  ) 

EquilibrateRHS(self) -> int

int
Epetra_SerialDenseSolver::EquilibrateRHS(void)

Equilibrates the current RHS.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::EstimateSolutionErrors (   self,
  args 
)

EstimateSolutionErrors(self, bool Flag)

void
Epetra_SerialDenseSolver::EstimateSolutionErrors(bool Flag)

Causes all solves to estimate the forward and backward solution error.

Error estimates will be in the arrays FERR and BERR, resp, after the
solve step is complete. These arrays are accessible via the FERR() and
BERR() access functions. 

def PyTrilinos::Epetra::SerialDenseSolver::EstimateSolutionErrors (   self,
  args 
)

EstimateSolutionErrors(self, bool Flag)

void
Epetra_SerialDenseSolver::EstimateSolutionErrors(bool Flag)

Causes all solves to estimate the forward and backward solution error.

Error estimates will be in the arrays FERR and BERR, resp, after the
solve step is complete. These arrays are accessible via the FERR() and
BERR() access functions. 

def PyTrilinos::Epetra::SerialDenseSolver::Factor (   self  ) 

Factor(self) -> int

int
Epetra_SerialDenseSolver::Factor(void)

Computes the in-place LU factorization of the matrix using the LAPACK
routine DGETRF.

Integer error code, set to 0 if successful. 

def PyTrilinos::Epetra::SerialDenseSolver::Factor (   self  ) 

Factor(self) -> int

int
Epetra_SerialDenseSolver::Factor(void)

Computes the in-place LU factorization of the matrix using the LAPACK
routine DGETRF.

Integer error code, set to 0 if successful. 

def PyTrilinos::Epetra::SerialDenseSolver::Factored (   self  ) 

Factored(self) -> bool

bool
Epetra_SerialDenseSolver::Factored()

Returns true if matrix is factored (factor available via AF() and
LDAF()). 

def PyTrilinos::Epetra::SerialDenseSolver::Factored (   self  ) 

Factored(self) -> bool

bool
Epetra_SerialDenseSolver::Factored()

Returns true if matrix is factored (factor available via AF() and
LDAF()). 

def PyTrilinos::Epetra::SerialDenseSolver::FactoredMatrix (   self  ) 

FactoredMatrix(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::FactoredMatrix()
const

Returns pointer to factored matrix (assuming factorization has been
performed). 

def PyTrilinos::Epetra::SerialDenseSolver::FactoredMatrix (   self  ) 

FactoredMatrix(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::FactoredMatrix()
const

Returns pointer to factored matrix (assuming factorization has been
performed). 

def PyTrilinos::Epetra::SerialDenseSolver::FactorWithEquilibration (   self,
  args 
)

FactorWithEquilibration(self, bool Flag)

void
Epetra_SerialDenseSolver::FactorWithEquilibration(bool Flag)

Causes equilibration to be called just before the matrix factorization
as part of the call to Factor.

This function must be called before the factorization is performed. 

def PyTrilinos::Epetra::SerialDenseSolver::FactorWithEquilibration (   self,
  args 
)

FactorWithEquilibration(self, bool Flag)

void
Epetra_SerialDenseSolver::FactorWithEquilibration(bool Flag)

Causes equilibration to be called just before the matrix factorization
as part of the call to Factor.

This function must be called before the factorization is performed. 

def PyTrilinos::Epetra::SerialDenseSolver::FERR (   self  ) 

FERR(self) -> PyObject

double*
Epetra_SerialDenseSolver::FERR() const

Returns a pointer to the forward error estimates computed by LAPACK.

def PyTrilinos::Epetra::SerialDenseSolver::FERR (   self  ) 

FERR(self) -> PyObject

double*
Epetra_SerialDenseSolver::FERR() const

Returns a pointer to the forward error estimates computed by LAPACK.

def PyTrilinos::Epetra::SerialDenseSolver::Invert (   self  ) 

Invert(self) -> int

int
Epetra_SerialDenseSolver::Invert(void)

Inverts the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::Invert (   self  ) 

Invert(self) -> int

int
Epetra_SerialDenseSolver::Invert(void)

Inverts the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::Inverted (   self  ) 

Inverted(self) -> bool

bool
Epetra_SerialDenseSolver::Inverted()

Returns true if matrix inverse has been computed (inverse available
via AF() and LDAF()). 

def PyTrilinos::Epetra::SerialDenseSolver::Inverted (   self  ) 

Inverted(self) -> bool

bool
Epetra_SerialDenseSolver::Inverted()

Returns true if matrix inverse has been computed (inverse available
via AF() and LDAF()). 

def PyTrilinos::Epetra::SerialDenseSolver::IPIV (   self  ) 

IPIV(self) -> PyObject

int*
Epetra_SerialDenseSolver::IPIV() const

Returns pointer to pivot vector (if factorization has been computed),
zero otherwise. 

def PyTrilinos::Epetra::SerialDenseSolver::IPIV (   self  ) 

IPIV(self) -> PyObject

int*
Epetra_SerialDenseSolver::IPIV() const

Returns pointer to pivot vector (if factorization has been computed),
zero otherwise. 

def PyTrilinos::Epetra::SerialDenseSolver::LDA (   self  ) 

LDA(self) -> int

int
Epetra_SerialDenseSolver::LDA() const

Returns the leading dimension of the this matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::LDA (   self  ) 

LDA(self) -> int

int
Epetra_SerialDenseSolver::LDA() const

Returns the leading dimension of the this matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::LDAF (   self  ) 

LDAF(self) -> int

int
Epetra_SerialDenseSolver::LDAF() const

Returns the leading dimension of the factored matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::LDAF (   self  ) 

LDAF(self) -> int

int
Epetra_SerialDenseSolver::LDAF() const

Returns the leading dimension of the factored matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::LDB (   self  ) 

LDB(self) -> int

int
Epetra_SerialDenseSolver::LDB() const

Returns the leading dimension of the RHS. 

def PyTrilinos::Epetra::SerialDenseSolver::LDB (   self  ) 

LDB(self) -> int

int
Epetra_SerialDenseSolver::LDB() const

Returns the leading dimension of the RHS. 

def PyTrilinos::Epetra::SerialDenseSolver::LDX (   self  ) 

LDX(self) -> int

int
Epetra_SerialDenseSolver::LDX() const

Returns the leading dimension of the solution. 

def PyTrilinos::Epetra::SerialDenseSolver::LDX (   self  ) 

LDX(self) -> int

int
Epetra_SerialDenseSolver::LDX() const

Returns the leading dimension of the solution. 

def PyTrilinos::Epetra::SerialDenseSolver::LHS (   self  ) 

LHS(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::LHS() const

Returns pointer to current LHS. 

def PyTrilinos::Epetra::SerialDenseSolver::LHS (   self  ) 

LHS(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::LHS() const

Returns pointer to current LHS. 

def PyTrilinos::Epetra::SerialDenseSolver::M (   self  ) 

M(self) -> int

int
Epetra_SerialDenseSolver::M() const

Returns row dimension of system. 

def PyTrilinos::Epetra::SerialDenseSolver::M (   self  ) 

M(self) -> int

int
Epetra_SerialDenseSolver::M() const

Returns row dimension of system. 

def PyTrilinos::Epetra::SerialDenseSolver::Matrix (   self  ) 

Matrix(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::Matrix() const

Returns pointer to current matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::Matrix (   self  ) 

Matrix(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::Matrix() const

Returns pointer to current matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::N (   self  ) 

N(self) -> int

int
Epetra_SerialDenseSolver::N() const

Returns column dimension of system. 

def PyTrilinos::Epetra::SerialDenseSolver::N (   self  ) 

N(self) -> int

int
Epetra_SerialDenseSolver::N() const

Returns column dimension of system. 

def PyTrilinos::Epetra::SerialDenseSolver::NRHS (   self  ) 

NRHS(self) -> int

int
Epetra_SerialDenseSolver::NRHS() const

Returns the number of current right hand sides and solution vectors.

def PyTrilinos::Epetra::SerialDenseSolver::NRHS (   self  ) 

NRHS(self) -> int

int
Epetra_SerialDenseSolver::NRHS() const

Returns the number of current right hand sides and solution vectors.

def PyTrilinos::Epetra::SerialDenseSolver::R (   self  ) 

R(self) -> PyObject

double*
Epetra_SerialDenseSolver::R() const

Returns a pointer to the row scaling vector used for equilibration. 

def PyTrilinos::Epetra::SerialDenseSolver::R (   self  ) 

R(self) -> PyObject

double*
Epetra_SerialDenseSolver::R() const

Returns a pointer to the row scaling vector used for equilibration. 

def PyTrilinos::Epetra::SerialDenseSolver::RCOND (   self  ) 

RCOND(self) -> double

double
Epetra_SerialDenseSolver::RCOND() const

Returns the reciprocal of the condition number of the this matrix
(returns -1 if not yet computed). 

def PyTrilinos::Epetra::SerialDenseSolver::RCOND (   self  ) 

RCOND(self) -> double

double
Epetra_SerialDenseSolver::RCOND() const

Returns the reciprocal of the condition number of the this matrix
(returns -1 if not yet computed). 

def PyTrilinos::Epetra::SerialDenseSolver::ReciprocalConditionEstimate (   self  ) 

ReciprocalConditionEstimate(self) -> double

int
Epetra_SerialDenseSolver::ReciprocalConditionEstimate(double &Value)

Returns the reciprocal of the 1-norm condition number of the this
matrix.

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

Value:  Out On return contains the reciprocal of the 1-norm condition
number of the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::ReciprocalConditionEstimate (   self  ) 

ReciprocalConditionEstimate(self) -> double

int
Epetra_SerialDenseSolver::ReciprocalConditionEstimate(double &Value)

Returns the reciprocal of the 1-norm condition number of the this
matrix.

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

Value:  Out On return contains the reciprocal of the 1-norm condition
number of the this matrix.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::ReciprocalConditionEstimated (   self  ) 

ReciprocalConditionEstimated(self) -> bool

bool
Epetra_SerialDenseSolver::ReciprocalConditionEstimated()

Returns true if the condition number of the this matrix has been
computed (value available via ReciprocalConditionEstimate()). 

def PyTrilinos::Epetra::SerialDenseSolver::ReciprocalConditionEstimated (   self  ) 

ReciprocalConditionEstimated(self) -> bool

bool
Epetra_SerialDenseSolver::ReciprocalConditionEstimated()

Returns true if the condition number of the this matrix has been
computed (value available via ReciprocalConditionEstimate()). 

def PyTrilinos::Epetra::SerialDenseSolver::RHS (   self  ) 

RHS(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::RHS() const

Returns pointer to current RHS. 

def PyTrilinos::Epetra::SerialDenseSolver::RHS (   self  ) 

RHS(self) -> Epetra_SerialDenseMatrix

Epetra_SerialDenseMatrix* Epetra_SerialDenseSolver::RHS() const

Returns pointer to current RHS. 

def PyTrilinos::Epetra::SerialDenseSolver::ROWCND (   self  ) 

ROWCND(self) -> double

double
Epetra_SerialDenseSolver::ROWCND() const

Ratio of smallest to largest row scale factors for the this matrix
(returns -1 if not yet computed).

If ROWCND() is >= 0.1 and AMAX() is not close to overflow or
underflow, then equilibration is not needed. 

def PyTrilinos::Epetra::SerialDenseSolver::ROWCND (   self  ) 

ROWCND(self) -> double

double
Epetra_SerialDenseSolver::ROWCND() const

Ratio of smallest to largest row scale factors for the this matrix
(returns -1 if not yet computed).

If ROWCND() is >= 0.1 and AMAX() is not close to overflow or
underflow, then equilibration is not needed. 

def PyTrilinos::Epetra::SerialDenseSolver::SetMatrix (   self,
  args 
)

SetMatrix(self, Epetra_SerialDenseMatrix A) -> int

int
Epetra_SerialDenseSolver::SetMatrix(Epetra_SerialDenseMatrix &A)

Sets the pointers for coefficient matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::SetMatrix (   self,
  args 
)

SetMatrix(self, Epetra_SerialDenseMatrix A) -> int

int
Epetra_SerialDenseSolver::SetMatrix(Epetra_SerialDenseMatrix &A)

Sets the pointers for coefficient matrix. 

def PyTrilinos::Epetra::SerialDenseSolver::SetVectors (   self,
  args 
)

SetVectors(self, Epetra_SerialDenseMatrix X, Epetra_SerialDenseMatrix B) -> int

int
Epetra_SerialDenseSolver::SetVectors(Epetra_SerialDenseMatrix &X,
Epetra_SerialDenseMatrix &B)

Sets the pointers for left and right hand side vector(s).

Row dimension of X must match column dimension of matrix A, row
dimension of B must match row dimension of A. X and B must have the
same dimensions. 

def PyTrilinos::Epetra::SerialDenseSolver::SetVectors (   self,
  args 
)

SetVectors(self, Epetra_SerialDenseMatrix X, Epetra_SerialDenseMatrix B) -> int

int
Epetra_SerialDenseSolver::SetVectors(Epetra_SerialDenseMatrix &X,
Epetra_SerialDenseMatrix &B)

Sets the pointers for left and right hand side vector(s).

Row dimension of X must match column dimension of matrix A, row
dimension of B must match row dimension of A. X and B must have the
same dimensions. 

def PyTrilinos::Epetra::SerialDenseSolver::ShouldEquilibrate (   self  ) 

ShouldEquilibrate(self) -> bool

virtual bool Epetra_SerialDenseSolver::ShouldEquilibrate()

Returns true if the LAPACK general rules for equilibration suggest you
should equilibrate the system. 

def PyTrilinos::Epetra::SerialDenseSolver::ShouldEquilibrate (   self  ) 

ShouldEquilibrate(self) -> bool

virtual bool Epetra_SerialDenseSolver::ShouldEquilibrate()

Returns true if the LAPACK general rules for equilibration suggest you
should equilibrate the system. 

def PyTrilinos::Epetra::SerialDenseSolver::SolutionErrorsEstimated (   self  ) 

SolutionErrorsEstimated(self) -> bool

bool
Epetra_SerialDenseSolver::SolutionErrorsEstimated()

Returns true if forward and backward error estimated have been
computed (available via FERR() and BERR()). 

def PyTrilinos::Epetra::SerialDenseSolver::SolutionErrorsEstimated (   self  ) 

SolutionErrorsEstimated(self) -> bool

bool
Epetra_SerialDenseSolver::SolutionErrorsEstimated()

Returns true if forward and backward error estimated have been
computed (available via FERR() and BERR()). 

def PyTrilinos::Epetra::SerialDenseSolver::SolutionRefined (   self  ) 

SolutionRefined(self) -> bool

bool Epetra_SerialDenseSolver::SolutionRefined()

Returns true if the current set of vectors has been refined. 

def PyTrilinos::Epetra::SerialDenseSolver::SolutionRefined (   self  ) 

SolutionRefined(self) -> bool

bool Epetra_SerialDenseSolver::SolutionRefined()

Returns true if the current set of vectors has been refined. 

def PyTrilinos::Epetra::SerialDenseSolver::Solve (   self  ) 

Solve(self) -> int

int
Epetra_SerialDenseSolver::Solve(void)

Computes the solution X to AX = B for the this matrix and the B
provided to SetVectors()..

Integer error code, set to 0 if successful. 

def PyTrilinos::Epetra::SerialDenseSolver::Solve (   self  ) 

Solve(self) -> int

int
Epetra_SerialDenseSolver::Solve(void)

Computes the solution X to AX = B for the this matrix and the B
provided to SetVectors()..

Integer error code, set to 0 if successful. 

def PyTrilinos::Epetra::SerialDenseSolver::Solved (   self  ) 

Solved(self) -> bool

bool
Epetra_SerialDenseSolver::Solved()

Returns true if the current set of vectors has been solved. 

def PyTrilinos::Epetra::SerialDenseSolver::Solved (   self  ) 

Solved(self) -> bool

bool
Epetra_SerialDenseSolver::Solved()

Returns true if the current set of vectors has been solved. 

def PyTrilinos::Epetra::SerialDenseSolver::SolveToRefinedSolution (   self,
  args 
)

SolveToRefinedSolution(self, bool Flag)

void
Epetra_SerialDenseSolver::SolveToRefinedSolution(bool Flag)

Causes all solves to compute solution to best ability using iterative
refinement. 

def PyTrilinos::Epetra::SerialDenseSolver::SolveToRefinedSolution (   self,
  args 
)

SolveToRefinedSolution(self, bool Flag)

void
Epetra_SerialDenseSolver::SolveToRefinedSolution(bool Flag)

Causes all solves to compute solution to best ability using iterative
refinement. 

def PyTrilinos::Epetra::SerialDenseSolver::SolveWithTranspose (   self,
  args 
)

SolveWithTranspose(self, bool Flag)

void Epetra_SerialDenseSolver::SolveWithTranspose(bool Flag)

If Flag is true, causes all subsequent function calls to work with the
transpose of this matrix, otherwise not. 

def PyTrilinos::Epetra::SerialDenseSolver::SolveWithTranspose (   self,
  args 
)

SolveWithTranspose(self, bool Flag)

void Epetra_SerialDenseSolver::SolveWithTranspose(bool Flag)

If Flag is true, causes all subsequent function calls to work with the
transpose of this matrix, otherwise not. 

def PyTrilinos::Epetra::SerialDenseSolver::Transpose (   self  ) 

Transpose(self) -> bool

bool
Epetra_SerialDenseSolver::Transpose()

Returns true if transpose of this matrix has and will be used. 

def PyTrilinos::Epetra::SerialDenseSolver::Transpose (   self  ) 

Transpose(self) -> bool

bool
Epetra_SerialDenseSolver::Transpose()

Returns true if transpose of this matrix has and will be used. 

def PyTrilinos::Epetra::SerialDenseSolver::UnequilibrateLHS (   self  ) 

UnequilibrateLHS(self) -> int

int Epetra_SerialDenseSolver::UnequilibrateLHS(void)

Unscales the solution vectors if equilibration was used to solve the
system.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::UnequilibrateLHS (   self  ) 

UnequilibrateLHS(self) -> int

int Epetra_SerialDenseSolver::UnequilibrateLHS(void)

Unscales the solution vectors if equilibration was used to solve the
system.

Integer error code, set to 0 if successful. Otherwise returns the
LAPACK error code INFO. 

def PyTrilinos::Epetra::SerialDenseSolver::X (   self  ) 

X(self) -> PyObject

double*
Epetra_SerialDenseSolver::X() const

Returns pointer to current solution. 

def PyTrilinos::Epetra::SerialDenseSolver::X (   self  ) 

X(self) -> PyObject

double*
Epetra_SerialDenseSolver::X() const

Returns pointer to current solution. 


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