python-pytrilinos 10.4.0.dfsg-1ubuntu2 / usr / share / pyshared / PyTrilinos / Amesos.py

# This file was automatically generated by SWIG (http://www.swig.org).
# Version 2.0.4
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.


"""

PyTrilinos.Amesos is the python interface to the Trilinos direct
linear solver package Amesos:

    http://trilinos.sandia.gov/packages/amesos

The purpose of Amesos is to provide a common interface to a variety of
third-party direct solvers, made compatible with PyTrilinos.Epetra.
Note that the C++ version of Amesos uses the prefix 'Amesos_', which
has been stripped from the python implementation.

The most important classes of the Amesos module are:

    * Factory      - Factory class
    * Lapack       - LAPACK interface
    * Klu          - KLU interface
    * Umfpack      - UMFPACK interface
    * Scalapack    - SCALAPACK interface
    * Superlu      - SuperLU interface
    * Superludist  - SuperLU_DIST interface
    * Dscpack      - DSCPACK interface
    * Mumps        - MUMPS interface

Use dir(Amesos) to see what specific interfaces have been enabled on
your platform.  For examples of usage, please consult the examples
subdirectory of the PyTrilinos package, scripts exAmesos_Simple.py and
exAmesos_Factory.py.

"""


from sys import version_info
if version_info >= (2,6,0):
    def swig_import_helper():
        from os.path import dirname
        import imp
        fp = None
        try:
            fp, pathname, description = imp.find_module('_Amesos', [dirname(__file__)])
        except ImportError:
            import _Amesos
            return _Amesos
        if fp is not None:
            try:
                _mod = imp.load_module('_Amesos', fp, pathname, description)
            finally:
                fp.close()
            return _mod
    _Amesos = swig_import_helper()
    del swig_import_helper
else:
    import _Amesos
del version_info
try:
    _swig_property = property
except NameError:
    pass # Python < 2.2 doesn't have 'property'.
def _swig_setattr_nondynamic(self,class_type,name,value,static=1):
    if (name == "thisown"): return self.this.own(value)
    if (name == "this"):
        if type(value).__name__ == 'SwigPyObject':
            self.__dict__[name] = value
            return
    method = class_type.__swig_setmethods__.get(name,None)
    if method: return method(self,value)
    if (not static):
        self.__dict__[name] = value
    else:
        raise AttributeError("You cannot add attributes to %s" % self)

def _swig_setattr(self,class_type,name,value):
    return _swig_setattr_nondynamic(self,class_type,name,value,0)

def _swig_getattr(self,class_type,name):
    if (name == "thisown"): return self.this.own()
    method = class_type.__swig_getmethods__.get(name,None)
    if method: return method(self)
    raise AttributeError(name)

def _swig_repr(self):
    try: strthis = "proxy of " + self.this.__repr__()
    except: strthis = ""
    return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)

try:
    _object = object
    _newclass = 1
except AttributeError:
    class _object : pass
    _newclass = 0


try:
    import weakref
    weakref_proxy = weakref.proxy
except:
    weakref_proxy = lambda x: x


class SwigPyIterator(_object):
    """Proxy of C++ swig::SwigPyIterator class"""
    __swig_setmethods__ = {}
    __setattr__ = lambda self, name, value: _swig_setattr(self, SwigPyIterator, name, value)
    __swig_getmethods__ = {}
    __getattr__ = lambda self, name: _swig_getattr(self, SwigPyIterator, name)
    def __init__(self, *args, **kwargs): raise AttributeError("No constructor defined - class is abstract")
    __repr__ = _swig_repr
    __swig_destroy__ = _Amesos.delete_SwigPyIterator
    __del__ = lambda self : None;
    def value(self):
        """value(self) -> PyObject"""
        return _Amesos.SwigPyIterator_value(self)

    def incr(self, n = 1):
        """
        incr(self, size_t n = 1) -> SwigPyIterator
        incr(self) -> SwigPyIterator
        """
        return _Amesos.SwigPyIterator_incr(self, n)

    def decr(self, n = 1):
        """
        decr(self, size_t n = 1) -> SwigPyIterator
        decr(self) -> SwigPyIterator
        """
        return _Amesos.SwigPyIterator_decr(self, n)

    def distance(self, *args):
        """distance(self, SwigPyIterator x) -> ptrdiff_t"""
        return _Amesos.SwigPyIterator_distance(self, *args)

    def equal(self, *args):
        """equal(self, SwigPyIterator x) -> bool"""
        return _Amesos.SwigPyIterator_equal(self, *args)

    def copy(self):
        """copy(self) -> SwigPyIterator"""
        return _Amesos.SwigPyIterator_copy(self)

    def next(self):
        """next(self) -> PyObject"""
        return _Amesos.SwigPyIterator_next(self)

    def __next__(self):
        """__next__(self) -> PyObject"""
        return _Amesos.SwigPyIterator___next__(self)

    def previous(self):
        """previous(self) -> PyObject"""
        return _Amesos.SwigPyIterator_previous(self)

    def advance(self, *args):
        """advance(self, ptrdiff_t n) -> SwigPyIterator"""
        return _Amesos.SwigPyIterator_advance(self, *args)

    def __eq__(self, *args):
        """__eq__(self, SwigPyIterator x) -> bool"""
        return _Amesos.SwigPyIterator___eq__(self, *args)

    def __ne__(self, *args):
        """__ne__(self, SwigPyIterator x) -> bool"""
        return _Amesos.SwigPyIterator___ne__(self, *args)

    def __iadd__(self, *args):
        """__iadd__(self, ptrdiff_t n) -> SwigPyIterator"""
        return _Amesos.SwigPyIterator___iadd__(self, *args)

    def __isub__(self, *args):
        """__isub__(self, ptrdiff_t n) -> SwigPyIterator"""
        return _Amesos.SwigPyIterator___isub__(self, *args)

    def __add__(self, *args):
        """__add__(self, ptrdiff_t n) -> SwigPyIterator"""
        return _Amesos.SwigPyIterator___add__(self, *args)

    def __sub__(self, *args):
        """
        __sub__(self, ptrdiff_t n) -> SwigPyIterator
        __sub__(self, SwigPyIterator x) -> ptrdiff_t
        """
        return _Amesos.SwigPyIterator___sub__(self, *args)

    def __iter__(self): return self
SwigPyIterator_swigregister = _Amesos.SwigPyIterator_swigregister
SwigPyIterator_swigregister(SwigPyIterator)

import Teuchos
import Epetra
class Factory(_object):
    """Proxy of C++ Amesos class"""
    __swig_setmethods__ = {}
    __setattr__ = lambda self, name, value: _swig_setattr(self, Factory, name, value)
    __swig_getmethods__ = {}
    __getattr__ = lambda self, name: _swig_getattr(self, Factory, name)
    __repr__ = _swig_repr
    def Create(self, *args):
        """
        Create(self, char ClassType, LinearProblem LinearProblem) -> BaseSolver
        Create(self, string CT, LinearProblem LinearProblem) -> BaseSolver
        """
        return _Amesos.Factory_Create(self, *args)

    def Query(self, *args):
        """
        Query(self, char ClassType) -> bool
        Query(self, string CT) -> bool
        """
        return _Amesos.Factory_Query(self, *args)

    def GetValidParameters(*args):
        """GetValidParameters() -> ParameterList"""
        return _Amesos.Factory_GetValidParameters(*args)

    if _newclass:GetValidParameters = staticmethod(GetValidParameters)
    __swig_getmethods__["GetValidParameters"] = lambda x: GetValidParameters
    def __init__(self, *args): 
        """__init__(self) -> Factory"""
        this = _Amesos.new_Factory(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _Amesos.delete_Factory
    __del__ = lambda self : None;
Factory_swigregister = _Amesos.Factory_swigregister
Factory_swigregister(Factory)

def Factory_GetValidParameters(*args):
  """Factory_GetValidParameters() -> ParameterList"""
  return _Amesos.Factory_GetValidParameters(*args)

class BaseSolver(Teuchos.ParameterListAcceptor):
    """
    Amesos_BaseSolver: A pure virtual class for direct solution of real-
    valued double- precision operators.

    Pure virtual class for all Amesos concrete implementions.

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

    Usage Examples

    Basic calling sequence

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

    Re-using the symbolic factorization

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

    Re-using the numeric factorization

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

    Constructor requirements

    Every Amesos_SolverName class should accept an Epetra_LinearProblem

    Mathematical methods

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

    Switching concrete classes

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

    Changing the values of the underlying matrix operator.

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

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

    Named Parameters

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

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

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

    Changing drop tolerance rules between calls to NumericFactorization()

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

    Transpose solve

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

    Performance expectations

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

    Memory usage:

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

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

    Robustness requirements

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

    2: Non-symmetric matrix

    3: Matrix is not positive definite

    4: Insufficient memory

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

    C++ includes: Amesos_BaseSolver.h 
    """
    __swig_setmethods__ = {}
    for _s in [Teuchos.ParameterListAcceptor]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, BaseSolver, name, value)
    __swig_getmethods__ = {}
    for _s in [Teuchos.ParameterListAcceptor]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, BaseSolver, name)
    def __init__(self, *args, **kwargs): raise AttributeError("No constructor defined - class is abstract")
    __repr__ = _swig_repr
    __swig_destroy__ = _Amesos.delete_BaseSolver
    __del__ = lambda self : None;
    def SymbolicFactorization(self, *args):
        """
        SymbolicFactorization(self) -> int

        virtual int Amesos_BaseSolver::SymbolicFactorization()=0

        Performs SymbolicFactorization on the matrix A.

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

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

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

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

        Integer error code, set to 0 if successful. 
        """
        return _Amesos.BaseSolver_SymbolicFactorization(self, *args)

    def NumericFactorization(self, *args):
        """
        NumericFactorization(self) -> int

        virtual int Amesos_BaseSolver::NumericFactorization()=0

        Performs NumericFactorization on the matrix A.

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

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

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

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

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

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

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

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

        Internal errors retur -5.

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

        Integer error code, set to 0 if successful. 
        """
        return _Amesos.BaseSolver_NumericFactorization(self, *args)

    def Solve(self, *args):
        """
        Solve(self) -> int

        virtual int
        Amesos_BaseSolver::Solve()=0

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

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

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

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

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

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

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

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

        Integer error code, set to 0 if successful. 
        """
        return _Amesos.BaseSolver_Solve(self, *args)

    def SetUseTranspose(self, *args):
        """
        SetUseTranspose(self, bool UseTranspose) -> int

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

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

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

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

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

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

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

        Integer error code, set to 0 if successful. Set to -1 if this
        implementation does not support transpose. 
        """
        return _Amesos.BaseSolver_SetUseTranspose(self, *args)

    def UseTranspose(self, *args):
        """
        UseTranspose(self) -> bool

        virtual bool
        Amesos_BaseSolver::UseTranspose() const =0

        Returns the current UseTranspose setting. 
        """
        return _Amesos.BaseSolver_UseTranspose(self, *args)

    def SetParameters(self, *args):
        """
        SetParameters(self, ParameterList ParameterList) -> int

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

        Updates internal variables.

        <br >Preconditions: None.

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

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

        Integer error code, set to 0 if successful. 
        """
        return _Amesos.BaseSolver_SetParameters(self, *args)

    def GetProblem(self, *args):
        """
        GetProblem(self) -> LinearProblem

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

        Returns the Epetra_LinearProblem.

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

    def MatrixShapeOK(self, *args):
        """
        MatrixShapeOK(self) -> bool

        virtual bool
        Amesos_BaseSolver::MatrixShapeOK() const =0

        Returns true if the solver can handle this matrix shape.

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

        """
        return _Amesos.BaseSolver_MatrixShapeOK(self, *args)

    def Comm(self, *args):
        """
        Comm(self) -> Comm

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

        Returns a pointer to the Epetra_Comm communicator associated with this
        operator. 
        """
        return _Amesos.BaseSolver_Comm(self, *args)

    def NumSymbolicFact(self, *args):
        """
        NumSymbolicFact(self) -> int

        virtual
        int Amesos_BaseSolver::NumSymbolicFact() const =0

        Returns the number of symbolic factorizations performed by this
        object. 
        """
        return _Amesos.BaseSolver_NumSymbolicFact(self, *args)

    def NumNumericFact(self, *args):
        """
        NumNumericFact(self) -> int

        virtual int
        Amesos_BaseSolver::NumNumericFact() const =0

        Returns the number of numeric factorizations performed by this object.

        """
        return _Amesos.BaseSolver_NumNumericFact(self, *args)

    def NumSolve(self, *args):
        """
        NumSolve(self) -> int

        virtual int
        Amesos_BaseSolver::NumSolve() const =0

        Returns the number of solves performed by this object. 
        """
        return _Amesos.BaseSolver_NumSolve(self, *args)

    def PrintStatus(self, *args):
        """
        PrintStatus(self)

        virtual void
        Amesos_BaseSolver::PrintStatus() const =0

        Prints status information about the current solver. 
        """
        return _Amesos.BaseSolver_PrintStatus(self, *args)

    def PrintTiming(self, *args):
        """
        PrintTiming(self)

        virtual void
        Amesos_BaseSolver::PrintTiming() const =0

        Prints timing information about the current solver. 
        """
        return _Amesos.BaseSolver_PrintTiming(self, *args)

    def setParameterList(self, *args):
        """
        setParameterList(self, Teuchos::RCP<(Teuchos::ParameterList)> paramList)

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

        Redefined from Teuchos::ParameterListAcceptor. 
        """
        return _Amesos.BaseSolver_setParameterList(self, *args)

    def getNonconstParameterList(self, *args):
        """
        getNonconstParameterList(self) -> Teuchos::RCP<(Teuchos::ParameterList)>

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

        This is an empty stub. 
        """
        return _Amesos.BaseSolver_getNonconstParameterList(self, *args)

    def GetTiming(self, *args):
        """
        GetTiming(self, ParameterList TimingParameterList)

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

        Extracts timing information from the current solver and places it in
        the parameter list. 
        """
        return _Amesos.BaseSolver_GetTiming(self, *args)

    def __str__(self, *args):
        """__str__(self) -> string"""
        return _Amesos.BaseSolver___str__(self, *args)

    def __del__(self, *args):
        """__del__(self)"""
        return _Amesos.BaseSolver___del__(self, *args)

BaseSolver_swigregister = _Amesos.BaseSolver_swigregister
BaseSolver_swigregister(BaseSolver)
cvar = _Amesos.cvar
StructurallySingularMatrixError = cvar.StructurallySingularMatrixError
NumericallySingularMatrixError = cvar.NumericallySingularMatrixError

class Lapack(BaseSolver):
    """
    Amesos_Lapack: an interface to LAPACK.

    Class Amesos_Lapack enables the solution of the distributed linear
    system, defined by an Epetra_LinearProblem, using LAPACK.

    Amesos_Lapack stores the lineaar system matrix as an
    Epetra_SerialDensMatrix. The linear problem is an
    Epetra_SerialDenseProblem. Amesos_Lapack factorizes the matrix using
    DGETRF().

    Marzio Sala, 9214.

    C++ includes: Amesos_Lapack.h 
    """
    __swig_setmethods__ = {}
    for _s in [BaseSolver]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Lapack, name, value)
    __swig_getmethods__ = {}
    for _s in [BaseSolver]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Lapack, name)
    __repr__ = _swig_repr
    def __init__(self, *args): 
        """
        __init__(self, LinearProblem LinearProblem) -> Lapack

        Amesos_Lapack::Amesos_Lapack(const Epetra_LinearProblem
        &LinearProblem)

        Amesos_Lapack Constructor.

        Creates an Amesos_Lapack instance, using an Epetra_LinearProblem,
        passing in an already- defined Epetra_LinearProblem object.

        Note: The operator in LinearProblem must be an Epetra_RowMatrix. 
        """
        this = _Amesos.new_Lapack(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _Amesos.delete_Lapack
    __del__ = lambda self : None;
    def SymbolicFactorization(self, *args):
        """
        SymbolicFactorization(self) -> int

        int
        Amesos_Lapack::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. 
        """
        return _Amesos.Lapack_SymbolicFactorization(self, *args)

    def NumericFactorization(self, *args):
        """
        NumericFactorization(self) -> int

        int
        Amesos_Lapack::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. 
        """
        return _Amesos.Lapack_NumericFactorization(self, *args)

    def Solve(self, *args):
        """
        Solve(self) -> int

        int
        Amesos_Lapack::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. 
        """
        return _Amesos.Lapack_Solve(self, *args)

    def GetProblem(self, *args):
        """
        GetProblem(self) -> LinearProblem

        const
        Epetra_LinearProblem* Amesos_Lapack::GetProblem() const

        Returns the Epetra_LinearProblem.

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

    def MatrixShapeOK(self, *args):
        """
        MatrixShapeOK(self) -> bool

        bool
        Amesos_Lapack::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.

        """
        return _Amesos.Lapack_MatrixShapeOK(self, *args)

    def SetUseTranspose(self, *args):
        """
        SetUseTranspose(self, bool UseTranspose_in) -> int

        int
        Amesos_Lapack::SetUseTranspose(bool UseTranspose_in)

        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. 
        """
        return _Amesos.Lapack_SetUseTranspose(self, *args)

    def UseTranspose(self, *args):
        """
        UseTranspose(self) -> bool

        bool
        Amesos_Lapack::UseTranspose() const

        Returns the current UseTranspose setting. 
        """
        return _Amesos.Lapack_UseTranspose(self, *args)

    def Comm(self, *args):
        """
        Comm(self) -> Comm

        const Epetra_Comm&
        Amesos_Lapack::Comm() const

        Returns a pointer to the Epetra_Comm communicator associated with this
        operator. 
        """
        return _Amesos.Lapack_Comm(self, *args)

    def setParameterList(self, *args):
        """
        setParameterList(self, Teuchos::RCP<(Teuchos::ParameterList)> paramList)

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

        Use this parameter list to read values from.

        Redefined from Teuchos::ParameterListAcceptor 
        """
        return _Amesos.Lapack_setParameterList(self, *args)

    def SetParameters(self, *args):
        """
        SetParameters(self, ParameterList ParameterList) -> int

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

        Deprecated - Sets parameters. 
        """
        return _Amesos.Lapack_SetParameters(self, *args)

    def GEEV(self, *args):
        """
        GEEV(self, Epetra_Vector Er, Epetra_Vector Ei) -> int

        int
        Amesos_Lapack::GEEV(Epetra_Vector &Er, Epetra_Vector &Ei)

        Computes the eigenvalues of the linear system matrix using DGEEV.

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

        Er:  - (Out) On processor zero only, it will contain the real
        component of the eigenvalues.

        Ei:  - (Out) On processor zero only, it will contain the imaginary
        component of the eigenvalues.

        Er and Ei must have been allocated so that the local length on
        processor 0 equals the global size of the matrix. 
        """
        return _Amesos.Lapack_GEEV(self, *args)

    def NumSymbolicFact(self, *args):
        """
        NumSymbolicFact(self) -> int

        int
        Amesos_Lapack::NumSymbolicFact() const

        Returns the number of symbolic factorizations performed by this
        object. 
        """
        return _Amesos.Lapack_NumSymbolicFact(self, *args)

    def NumNumericFact(self, *args):
        """
        NumNumericFact(self) -> int

        int
        Amesos_Lapack::NumNumericFact() const

        Returns the number of numeric factorizations performed by this object.

        """
        return _Amesos.Lapack_NumNumericFact(self, *args)

    def NumSolve(self, *args):
        """
        NumSolve(self) -> int

        int
        Amesos_Lapack::NumSolve() const

        Returns the number of solves performed by this object. 
        """
        return _Amesos.Lapack_NumSolve(self, *args)

    def PrintTiming(self, *args):
        """
        PrintTiming(self)

        void
        Amesos_Lapack::PrintTiming() const

        Print timing information. 
        """
        return _Amesos.Lapack_PrintTiming(self, *args)

    def PrintStatus(self, *args):
        """
        PrintStatus(self)

        void
        Amesos_Lapack::PrintStatus() const

        Print information about the factorization and solution phases. 
        """
        return _Amesos.Lapack_PrintStatus(self, *args)

    def GetTiming(self, *args):
        """
        GetTiming(self, ParameterList TimingParameterList)

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

        Extracts timing information from the current solver and places it in
        the parameter list. 
        """
        return _Amesos.Lapack_GetTiming(self, *args)

Lapack_swigregister = _Amesos.Lapack_swigregister
Lapack_swigregister(Lapack)

class Klu(BaseSolver):
    """
    Interface to KLU internal solver.

    Interface to UMFPACK.

    C++ includes: Amesos_Umfpack.h 
    """
    __swig_setmethods__ = {}
    for _s in [BaseSolver]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
    __setattr__ = lambda self, name, value: _swig_setattr(self, Klu, name, value)
    __swig_getmethods__ = {}
    for _s in [BaseSolver]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
    __getattr__ = lambda self, name: _swig_getattr(self, Klu, name)
    __repr__ = _swig_repr
    def __init__(self, *args): 
        """
        __init__(self, LinearProblem LinearProblem) -> Klu

        Amesos_Klu::Amesos_Klu(const Epetra_LinearProblem &LinearProblem)

        Amesos_Klu Constructor.

        Creates an Amesos_Klu instance, using an Epetra_LinearProblem, passing
        in an already- defined Epetra_LinearProblem object.

        Note: The operator in LinearProblem must be an Epetra_RowMatrix. 
        """
        this = _Amesos.new_Klu(*args)
        try: self.this.append(this)
        except: self.this = this
    __swig_destroy__ = _Amesos.delete_Klu
    __del__ = lambda self : None;
    def SymbolicFactorization(self, *args):
        """
        SymbolicFactorization(self) -> int

        int
        Amesos_Klu::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. 
        """
        return _Amesos.Klu_SymbolicFactorization(self, *args)

    def NumericFactorization(self, *args):
        """
        NumericFactorization(self) -> int

        int
        Amesos_Klu::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. 
        """
        return _Amesos.Klu_NumericFactorization(self, *args)

    def Solve(self, *args):
        """
        Solve(self) -> int

        int Amesos_Klu::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. 
        """
        return _Amesos.Klu_Solve(self, *args)

    def GetProblem(self, *args):
        """
        GetProblem(self) -> LinearProblem

        const
        Epetra_LinearProblem* Amesos_Klu::GetProblem() const

        Get a pointer to the Problem. 
        """
        return _Amesos.Klu_GetProblem(self, *args)

    def MatrixShapeOK(self, *args):
        """
        MatrixShapeOK(self) -> bool

        bool
        Amesos_Klu::MatrixShapeOK() const

        Returns true if KLU can handle this matrix shape.

        Returns true if the matrix shape is one that KLU can handle. KLU only
        works with square matrices. 
        """
        return _Amesos.Klu_MatrixShapeOK(self, *args)

    def SetUseTranspose(self, *args):
        """
        SetUseTranspose(self, bool UseTranspose_in) -> int

        int
        Amesos_Klu::SetUseTranspose(bool UseTranspose_in)

        SetUseTranpose(true) is more efficient in Amesos_Klu.

        If SetUseTranspose() is set to true, $A^T X = B$ is computed. 
        """
        return _Amesos.Klu_SetUseTranspose(self, *args)

    def UseTranspose(self, *args):
        """
        UseTranspose(self) -> bool

        bool
        Amesos_Klu::UseTranspose() const

        Returns the current UseTranspose setting. 
        """
        return _Amesos.Klu_UseTranspose(self, *args)

    def Comm(self, *args):
        """
        Comm(self) -> Comm

        const Epetra_Comm&
        Amesos_Klu::Comm() const

        Returns a pointer to the Epetra_Comm communicator associated with this
        operator. 
        """
        return _Amesos.Klu_Comm(self, *args)

    def SetParameters(self, *args):
        """
        SetParameters(self, ParameterList ParameterList) -> int

        int
        Amesos_Klu::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. 
        """
        return _Amesos.Klu_SetParameters(self, *args)

    def NumSymbolicFact(self, *args):
        """
        NumSymbolicFact(self) -> int

        int
        Amesos_Klu::NumSymbolicFact() const

        Returns the number of symbolic factorizations performed by this
        object. 
        """
        return _Amesos.Klu_NumSymbolicFact(self, *args)

    def NumNumericFact(self, *args):
        """
        NumNumericFact(self) -> int

        int
        Amesos_Klu::NumNumericFact() const

        Returns the number of numeric factorizations performed by this object.

        """
        return _Amesos.Klu_NumNumericFact(self, *args)

    def NumSolve(self, *args):
        """
        NumSolve(self) -> int

        int
        Amesos_Klu::NumSolve() const

        Returns the number of solves performed by this object. 
        """
        return _Amesos.Klu_NumSolve(self, *args)

    def PrintTiming(self, *args):
        """
        PrintTiming(self)

        void
        Amesos_Klu::PrintTiming() const

        Prints timing information. 
        """
        return _Amesos.Klu_PrintTiming(self, *args)

    def PrintStatus(self, *args):
        """
        PrintStatus(self)

        void
        Amesos_Klu::PrintStatus() const

        Prints information about the factorization and solution phases. 
        """
        return _Amesos.Klu_PrintStatus(self, *args)

    def GetTiming(self, *args):
        """
        GetTiming(self, ParameterList TimingParameterList)

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

        Extracts timing information and places in parameter list. 
        """
        return _Amesos.Klu_GetTiming(self, *args)

Klu_swigregister = _Amesos.Klu_swigregister
Klu_swigregister(Klu)

# This file is compatible with both classic and new-style classes.