PyTrilinos::Epetra::SerialDenseSolver Class Reference
Inheritance diagram for PyTrilinos::Epetra::SerialDenseSolver:
Collaboration diagram for PyTrilinos::Epetra::SerialDenseSolver:
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, | ||
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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, | ||
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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 | ||||
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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, | ||
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| ) |
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:
- build/lib.linux-x86_64-2.5/PyTrilinos/Epetra.py
- PyTrilinos/Epetra.py
