An implementation of the Anasazi::GenOrthoManager that performs orthogonalization using iterated classical Gram-Schmidt. More...

#include <AnasaziICGSOrthoManager.hpp>

Inheritance diagram for Anasazi::ICGSOrthoManager< ScalarType, MV, OP >:

Public Member Functions
Constructor/Destructor
	ICGSOrthoManager (Teuchos::RCP< const OP > Op=Teuchos::null, int numIters=2, typename Teuchos::ScalarTraits< ScalarType >::magnitudeType eps=0.0, typename Teuchos::ScalarTraits< ScalarType >::magnitudeType tol=0.20)
	Constructor specifying the operator defining the inner product as well as the number of orthogonalization iterations. More...

	~ICGSOrthoManager ()
	Destructor. More...

Methods implementing Anasazi::GenOrthoManager
void	projectGen (MV &S, Teuchos::Array< Teuchos::RCP< const MV > > X, Teuchos::Array< Teuchos::RCP< const MV > > Y, bool isBiOrtho, Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > > C=Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >(Teuchos::null)), Teuchos::RCP< MV > MS=Teuchos::null, Teuchos::Array< Teuchos::RCP< const MV > > MX=Teuchos::tuple(Teuchos::RCP< const MV >(Teuchos::null)), Teuchos::Array< Teuchos::RCP< const MV > > MY=Teuchos::tuple(Teuchos::RCP< const MV >(Teuchos::null))) const
	Applies a series of generic projectors. More...

int	projectAndNormalizeGen (MV &S, Teuchos::Array< Teuchos::RCP< const MV > > X, Teuchos::Array< Teuchos::RCP< const MV > > Y, bool isBiOrtho, Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > > C=Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >(Teuchos::null)), Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > B=Teuchos::null, Teuchos::RCP< MV > MS=Teuchos::null, Teuchos::Array< Teuchos::RCP< const MV > > MX=Teuchos::tuple(Teuchos::RCP< const MV >(Teuchos::null)), Teuchos::Array< Teuchos::RCP< const MV > > MY=Teuchos::tuple(Teuchos::RCP< const MV >(Teuchos::null))) const
	Applies a series of generic projectors and returns an orthonormal basis for the residual data. More...

Methods implementing Anasazi::MatOrthoManager
void	projectMat (MV &X, Teuchos::Array< Teuchos::RCP< const MV > > Q, Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > > C=Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >(Teuchos::null)), Teuchos::RCP< MV > MX=Teuchos::null, Teuchos::Array< Teuchos::RCP< const MV > > MQ=Teuchos::tuple(Teuchos::RCP< const MV >(Teuchos::null))) const
	Given a list of mutually orthogonal and internally orthonormal bases `Q`, this method projects a multivector `X` onto the space orthogonal to the individual `Q[i]`, optionally returning the coefficients of `X` for the individual `Q[i]`. All of this is done with respect to the inner product innerProd(). More...

int	normalizeMat (MV &X, Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > B=Teuchos::null, Teuchos::RCP< MV > MX=Teuchos::null) const
	This method takes a multivector `X` and attempts to compute an orthonormal basis for , with respect to innerProd(). More...

int	projectAndNormalizeMat (MV &X, Teuchos::Array< Teuchos::RCP< const MV > > Q, Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > > C=Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >(Teuchos::null)), Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > B=Teuchos::null, Teuchos::RCP< MV > MX=Teuchos::null, Teuchos::Array< Teuchos::RCP< const MV > > MQ=Teuchos::tuple(Teuchos::RCP< const MV >(Teuchos::null))) const
	Given a set of bases `Q[i]` and a multivector `X`, this method computes an orthonormal basis for $colspan(X) - \sum_i colspan(Q[i])$ . More...

Error methods
Teuchos::ScalarTraits < ScalarType >::magnitudeType	orthonormErrorMat (const MV &X, Teuchos::RCP< const MV > MX=Teuchos::null) const
	This method computes the error in orthonormality of a multivector, measured as the Frobenius norm of the difference `innerProd(X,Y) - I`. The method has the option of exploiting a caller-provided `MX`. More...

Teuchos::ScalarTraits < ScalarType >::magnitudeType	orthogErrorMat (const MV &X1, const MV &X2, Teuchos::RCP< const MV > MX1, Teuchos::RCP< const MV > MX2) const
	This method computes the error in orthogonality of two multivectors, measured as the Frobenius norm of `innerProd(X,Y)`. The method has the option of exploiting a caller-provided `MX`. More...

Accessor routines
void	setNumIters (int numIters)
	Set parameter for re-orthogonalization threshold. More...

int	getNumIters () const
	Return parameter for re-orthogonalization threshold. More...

Public Member Functions inherited from Anasazi::GenOrthoManager< ScalarType, MV, OP >
	GenOrthoManager (Teuchos::RCP< const OP > Op=Teuchos::null)
	Default constructor. More...

virtual	~GenOrthoManager ()
	Destructor. More...

Public Member Functions inherited from Anasazi::MatOrthoManager< ScalarType, MV, OP >
	MatOrthoManager (Teuchos::RCP< const OP > Op=Teuchos::null)
	Default constructor. More...

virtual	~MatOrthoManager ()
	Destructor. More...

virtual void	setOp (Teuchos::RCP< const OP > Op)
	Set operator used for inner product. More...

virtual Teuchos::RCP< const OP >	getOp () const
	Get operator used for inner product. More...

int	getOpCounter () const
	Retrieve operator counter. More...

void	resetOpCounter ()
	Reset the operator counter to zero. More...

void	innerProdMat (const MV &X, const MV &Y, Teuchos::SerialDenseMatrix< int, ScalarType > &Z, Teuchos::RCP< const MV > MX=Teuchos::null, Teuchos::RCP< const MV > MY=Teuchos::null) const
	Provides a matrix-based inner product. More...

void	normMat (const MV &X, std::vector< typename Teuchos::ScalarTraits< ScalarType >::magnitudeType > &normvec, Teuchos::RCP< const MV > MX=Teuchos::null) const
	Provides the norm induced by the matrix-based inner product. More...

void	innerProd (const MV &X, const MV &Y, Teuchos::SerialDenseMatrix< int, ScalarType > &Z) const
	Implements the interface OrthoManager::innerProd(). More...

void	norm (const MV &X, std::vector< typename Teuchos::ScalarTraits< ScalarType >::magnitudeType > &normvec) const
	Implements the interface OrthoManager::norm(). More...

void	project (MV &X, Teuchos::Array< Teuchos::RCP< const MV > > Q, Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > > C=Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >(Teuchos::null))) const
	Implements the interface OrthoManager::project(). More...

int	normalize (MV &X, Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > B=Teuchos::null) const
	Implements the interface OrthoManager::normalize(). More...

int	projectAndNormalize (MV &X, Teuchos::Array< Teuchos::RCP< const MV > > Q, Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > > C=Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >(Teuchos::null)), Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > B=Teuchos::null) const
	Implements the interface OrthoManager::projectAndNormalize(). More...

Teuchos::ScalarTraits < ScalarType >::magnitudeType	orthonormError (const MV &X) const
	Implements the interface OrthoManager::orthonormError(). More...

Teuchos::ScalarTraits < ScalarType >::magnitudeType	orthogError (const MV &X1, const MV &X2) const
	Implements the interface OrthoManager::orthogError(). More...

Public Member Functions inherited from Anasazi::OrthoManager< ScalarType, MV >
	OrthoManager ()
	Default constructor. More...

virtual	~OrthoManager ()
	Destructor. More...

Detailed Description

template<class ScalarType, class MV, class OP>
class Anasazi::ICGSOrthoManager< ScalarType, MV, OP >

An implementation of the Anasazi::GenOrthoManager that performs orthogonalization using iterated classical Gram-Schmidt.

Author: Chris Baker, Ulrich Hetmaniuk, Rich Lehoucq, and Heidi Thornquist

Definition at line 39 of file AnasaziICGSOrthoManager.hpp.

Constructor & Destructor Documentation

template<class ScalarType , class MV , class OP >

Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::ICGSOrthoManager	(	Teuchos::RCP< const OP >	Op = `Teuchos::null`,
		int	numIters = `2`,
		typename Teuchos::ScalarTraits< ScalarType >::magnitudeType	eps = `0.0`,
		typename Teuchos::ScalarTraits< ScalarType >::magnitudeType	tol = `0.20`
	)

Constructor specifying the operator defining the inner product as well as the number of orthogonalization iterations.

Definition at line 379 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::~ICGSOrthoManager ( )

inline

Destructor.

Definition at line 58 of file AnasaziICGSOrthoManager.hpp.

Member Function Documentation

template<class ScalarType , class MV , class OP >

void Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::projectGen	(	MV &	S,
		Teuchos::Array< Teuchos::RCP< const MV > >	X,
		Teuchos::Array< Teuchos::RCP< const MV > >	Y,
		bool	isBiOrtho,
		Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > >	C = `Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix<int,ScalarType> >(Teuchos::null))`,
		Teuchos::RCP< MV >	MS = `Teuchos::null`,
		Teuchos::Array< Teuchos::RCP< const MV > >	MX = `Teuchos::tuple(Teuchos::RCP<const MV>(Teuchos::null))`,
		Teuchos::Array< Teuchos::RCP< const MV > >	MY = `Teuchos::tuple(Teuchos::RCP<const MV>(Teuchos::null))`
	)		const

virtual

Applies a series of generic projectors.

Given a list of bases X[i] and Y[i] (a projection pair), this method takes a multivector S and applies the projectors

$P_{X[i],Y[i]} S = S - X[i] \langle Y[i], X[i] \rangle^{-1} \langle Y[i], S \rangle\ .$

This operation projects S onto the space orthogonal to the Y[i], along the range of the X[i]. The inner product specified by $\langle \cdot, \cdot \rangle$ is given by innerProd().

Note: The call
projectGen(S, tuple(X1,X2), tuple(Y1,Y2))

is equivalent to the call
projectGen(S, tuple(X2,X1), tuple(Y2,Y1))

The method also returns the coefficients C[i] associated with each projection pair, so that

$S_{in} = S_{out} + \sum_i X[i] C[i]$

and therefore

$C[i] = \langle Y[i], X[i] \rangle^{-1} \langle Y[i], S \rangle\ .$

Lastly, for reasons of efficiency, the user must specify whether the projection pairs are bi-orthonormal with respect to innerProd(), i.e., whether $\langle Y[i], X[i] \rangle = I$ . In the case that the bases are specified to be biorthogonal, the inverse $\langle Y, X \rangle^{-1}$ will not be computed. Furthermore, the user may optionally specifiy the image of S and the projection pairs under the inner product operator getOp().

projectGen() is implemented to apply the projectors via an iterated Classical Gram-Schmidt, where the iteration is performed getNumIters() number of times.

Parameters

S	[in/out] The multivector to be modified. On output, the columns of `S` will be orthogonal to each `Y[i]`, satisfying $\langle Y[i], S_{out} \rangle = 0$ Also, $S_{in} = S_{out} + \sum_i X[i] C[i]$
X	[in] Multivectors for bases under which $S_{in}$ is modified.
Y	[in] Multivectors for bases to which $S_{out}$ should be orthogonal.
isBiortho	[in] A flag specifying whether the bases `X[i]` and `Y[i]` are biorthonormal, i.e,. whether $\langle Y[i], X[i]\rangle == I$ .
C	[out] Coefficients for reconstructing $S_{in}$ via the bases `X[i]`. If `C[i]` is a non-null pointer and `C[i]` matches the dimensions of `S` and `X[i]`, then the coefficients computed during the orthogonalization routine will be stored in the matrix `C[i]`. If `C[i]` points to a Teuchos::SerialDenseMatrix with size inconsistent with `S` and `X[i]`, then a std::invalid_argument exception will be thrown. Otherwise, if `C.size() < i` or `C[i]` is a null pointer, the caller will not have access to the computed coefficients `C[i]`.
MS	[in/out] If specified by the user, on input `MS` is required to be the image of `S` under the operator getOp(). On output, `MS` will be updated to reflect the changes in `S`.
MX	[in] If specified by the user, on `MX[i]` is required to be the image of `X[i]` under the operator getOp().
MY	[in] If specified by the user, on `MY[i]` is required to be the image of `Y[i]` under the operator getOp().

Precondition

If X[i] != Teuchos::null or Y[i] != Teuchos::null, then X[i] and Y[i] are required to have the same number of columns, and each should have the same number of rows as S.
For any i != j, $\langle Y[i], X[j] \rangle == 0$ .
If biOrtho == true, $\langle Y[i], X[i]\rangle == I$
Otherwise, if biOrtho == false, then $\langle Y[i], X[i]\rangle$ should be Hermitian positive-definite.
If X[i] and Y[i] have columns and S has columns, then C[i] if specified must be $xc_i \times sc$ .

Implements Anasazi::GenOrthoManager< ScalarType, MV, OP >.

Definition at line 515 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

int Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::projectAndNormalizeGen	(	MV &	S,
		Teuchos::Array< Teuchos::RCP< const MV > >	X,
		Teuchos::Array< Teuchos::RCP< const MV > >	Y,
		bool	isBiOrtho,
		Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > >	C = `Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix<int,ScalarType> >(Teuchos::null))`,
		Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >	B = `Teuchos::null`,
		Teuchos::RCP< MV >	MS = `Teuchos::null`,
		Teuchos::Array< Teuchos::RCP< const MV > >	MX = `Teuchos::tuple(Teuchos::RCP<const MV>(Teuchos::null))`,
		Teuchos::Array< Teuchos::RCP< const MV > >	MY = `Teuchos::tuple(Teuchos::RCP<const MV>(Teuchos::null))`
	)		const

virtual

Applies a series of generic projectors and returns an orthonormal basis for the residual data.

Given a list of bases X[i] and Y[i] (a projection pair), this method takes a multivector S and applies the projectors

$P_{X[i],Y[i]} S = S - X[i] \langle Y[i], X[i] \rangle^{-1} \langle Y[i], S \rangle\ .$

These operation project S onto the space orthogonal to the range of the Y[i], along the range of X[i]. The inner product specified by $\langle \cdot, \cdot \rangle$ is given by innerProd().

The method returns in S an orthonormal basis for the residual

$\left( \prod_{i} P_{X[i],Y[i]} \right) S_{in} = S_{out} B\ ,$

where B contains the (not necessarily triangular) coefficients of the residual with respect to the new basis.

The method also returns the coefficients C[i] and B associated with each projection pair, so that

$S_{in} = S_{out} B + \sum_i X[i] C[i]$

and

$C[i] = \langle Y[i], X[i] \rangle^{-1} \langle Y[i], S \rangle\ .$

Lastly, for reasons of efficiency, the user must specify whether the projection pairs are bi-orthonormal with respect to innerProd(), i.e., whether $\langle Y[i], X[i] \rangle = I$ . Furthermore, the user may optionally specifiy the image of S and the projection pairs under the inner product operator getOp().

Parameters

S	[in/out] The multivector to be modified. On output, the columns of `S` will be orthogonal to each `Y[i]`, satisfying $\langle Y[i], S_{out} \rangle = 0$ Also, $S_{in}(1:m,1:n) = S_{out}(1:m,1:rank) B(1:rank,1:n) + \sum_i X[i] C[i]\ ,$ where `m` is the number of rows in `S`, `n` is the number of columns in `S`, and `rank` is the value returned from the method.
X	[in] Multivectors for bases under which $S_{in}$ is modified.
Y	[in] Multivectors for bases to which $S_{out}$ should be orthogonal.
isBiortho	[in] A flag specifying whether the bases `X[i]` and `Y[i]` are biorthonormal, i.e,. whether $\langle Y[i], X[i]\rangle == I$ .
C	[out] Coefficients for reconstructing $S_{in}$ via the bases `X[i]`. If `C[i]` is a non-null pointer and `C[i]` matches the dimensions of `X` and `Q[i]`, then the coefficients computed during the orthogonalization routine will be stored in the matrix `C[i]`. If `C[i]` points to a Teuchos::SerialDenseMatrix with size inconsistent with `S` and `X[i]`, then a std::invalid_argument exception will be thrown. Otherwise, if `C.size() < i` or `C[i]` is a null pointer, the caller will not have access to the computed coefficients `C[i]`.
B	[out] The coefficients of the original `S` with respect to the computed basis. If `B` is a non-null pointer and `B` matches the dimensions of `B`, then the coefficients computed during the orthogonalization routine will be stored in `B`, similar to calling innerProd( Sout, Sin, B ); If `B` points to a Teuchos::SerialDenseMatrix with size inconsistent with `S`, then a std::invalid_argument exception will be thrown. Otherwise, if `B` is null, the caller will not have access to the computed coefficients. The normalization uses classical Gram-Schmidt iteration, so that `B` is an upper triangular matrix with positive diagonal elements.
MS	[in/out] If specified by the user, on input `MS` is required to be the image of `S` under the operator getOp(). On output, `MS` will be updated to reflect the changes in `S`.
MX	[in] If specified by the user, on `MX[i]` is required to be the image of `X[i]` under the operator getOp().
MY	[in] If specified by the user, on `MY[i]` is required to be the image of `Y[i]` under the operator getOp().

Precondition

If X[i] != Teuchos::null or Y[i] != Teuchos::null, then X[i] and Y[i] are required to have the same number of columns, and each should have the same number of rows as S.
For any i != j, $\langle Y[i], X[j] \rangle == 0$ .
If biOrtho == true, $\langle Y[i], X[i]\rangle == I$
Otherwise, if biOrtho == false, then $\langle Y[i], X[i]\rangle$ should be Hermitian positive-definite.
If X[i] and Y[i] have columns and S has columns, then C[i] if specified must be $xc_i \times sc$ .
If S has columns, then B if specified must be $sc \times sc$ .

Returns: Rank of the basis computed by this method.

Implements Anasazi::GenOrthoManager< ScalarType, MV, OP >.

Definition at line 860 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

void Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::projectMat	(	MV &	X,
		Teuchos::Array< Teuchos::RCP< const MV > >	Q,
		Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > >	C = `Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix<int,ScalarType> >(Teuchos::null))`,
		Teuchos::RCP< MV >	MX = `Teuchos::null`,
		Teuchos::Array< Teuchos::RCP< const MV > >	MQ = `Teuchos::tuple(Teuchos::RCP<const MV>(Teuchos::null))`
	)		const

virtual

Given a list of mutually orthogonal and internally orthonormal bases Q, this method projects a multivector X onto the space orthogonal to the individual Q[i], optionally returning the coefficients of X for the individual Q[i]. All of this is done with respect to the inner product innerProd().

This method calls projectGen() as follows:

projectGen(X,Q,Q,true,C,MX,MQ,MQ);

See projectGen() for argument requirements.

Implements Anasazi::MatOrthoManager< ScalarType, MV, OP >.

Definition at line 434 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

int Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::normalizeMat	(	MV &	X,
		Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >	B = `Teuchos::null`,
		Teuchos::RCP< MV >	MX = `Teuchos::null`
	)		const

virtual

This method takes a multivector X and attempts to compute an orthonormal basis for $colspan(X)$ , with respect to innerProd().

This method calls projectAndNormalizeGen() as follows:

projectAndNormalizeGen(X,empty,empty,true,empty,B,MX);

See projectAndNormalizeGen() for argument requirements.

Implements Anasazi::MatOrthoManager< ScalarType, MV, OP >.

Definition at line 450 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

int Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::projectAndNormalizeMat	(	MV &	X,
		Teuchos::Array< Teuchos::RCP< const MV > >	Q,
		Teuchos::Array< Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > > >	C = `Teuchos::tuple(Teuchos::RCP< Teuchos::SerialDenseMatrix<int,ScalarType> >(Teuchos::null))`,
		Teuchos::RCP< Teuchos::SerialDenseMatrix< int, ScalarType > >	B = `Teuchos::null`,
		Teuchos::RCP< MV >	MX = `Teuchos::null`,
		Teuchos::Array< Teuchos::RCP< const MV > >	MQ = `Teuchos::tuple(Teuchos::RCP<const MV>(Teuchos::null))`
	)		const

virtual

Given a set of bases Q[i] and a multivector X, this method computes an orthonormal basis for $colspan(X) - \sum_i colspan(Q[i])$ .

This method calls projectAndNormalizeGen() as follows:

projectAndNormalizeGen(X,Q,Q,true,C,B,MX,MQ,MQ);

See projectAndNormalizeGen() for argument requirements.

Implements Anasazi::MatOrthoManager< ScalarType, MV, OP >.

Definition at line 499 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

Teuchos::ScalarTraits< ScalarType >::magnitudeType Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::orthonormErrorMat	(	const MV &	X,
		Teuchos::RCP< const MV >	MX = `Teuchos::null`
	)		const

virtual

This method computes the error in orthonormality of a multivector, measured as the Frobenius norm of the difference innerProd(X,Y) - I. The method has the option of exploiting a caller-provided MX.

Implements Anasazi::MatOrthoManager< ScalarType, MV, OP >.

Definition at line 405 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

Teuchos::ScalarTraits< ScalarType >::magnitudeType Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::orthogErrorMat	(	const MV &	X1,
		const MV &	X2,
		Teuchos::RCP< const MV >	MX1,
		Teuchos::RCP< const MV >	MX2
	)		const

virtual

This method computes the error in orthogonality of two multivectors, measured as the Frobenius norm of innerProd(X,Y). The method has the option of exploiting a caller-provided MX.

Implements Anasazi::MatOrthoManager< ScalarType, MV, OP >.

Definition at line 422 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

void Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::setNumIters ( int numIters )

inline

Set parameter for re-orthogonalization threshold.

Definition at line 350 of file AnasaziICGSOrthoManager.hpp.

template<class ScalarType , class MV , class OP >

int Anasazi::ICGSOrthoManager< ScalarType, MV, OP >::getNumIters ( ) const

inline

Return parameter for re-orthogonalization threshold.

Definition at line 357 of file AnasaziICGSOrthoManager.hpp.