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// ************************************************************************
//
// Belos: Block Linear Solvers Package
// Copyright 2004 Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
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// modification, are permitted provided that the following conditions are
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//
// 1. Redistributions of source code must retain the above copyright
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//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
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// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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// Questions? Contact Michael A. Heroux (maherou@sandia.gov)
//
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//@HEADER
#ifndef BELOS_MULTI_VEC_HPP
#define BELOS_MULTI_VEC_HPP
/// \file BelosMultiVec.hpp
/// \brief Interface for multivectors used by Belos' linear solvers.
///
/// We provide two options for letting Belos' linear solvers use
/// arbitrary multivector types. One is via compile-time
/// polymorphism, by specializing Belos::MultiVecTraits. The other is
/// via run-time polymorphism, by implementing Belos::MultiVec (the
/// interface defined in this header file). Belos ultimately only
/// uses Belos::MultiVecTraits (it uses Belos::MultiVec via a
/// specialization of Belos::MultiVecTraits for Belos::MultiVec), so
/// the preferred way to tell Belos how to use your multivector class
/// is via a Belos::MultiVecTraits specialization. However, some
/// users find a run-time polymorphic interface useful, so we provide
/// it as a service to them.
#include "BelosMultiVecTraits.hpp"
#include "BelosTypes.hpp"
#include "BelosConfigDefs.hpp"
namespace Belos {
/// \class MultiVec
/// \brief Interface for multivectors used by Belos' linear solvers.
/// \author Michael Heroux, Rich Lehoucq, and Heidi Thornquist
///
/// \tparam ScalarType The type of entries of the multivector.
///
/// Belos accesses multivectors through a traits interface called
/// MultiVecTraits. If you want to use Belos with your own
/// multivector class MV, you may either specialize MultiVecTraits for
/// MV, or you may wrap MV in your own class that implements MultiVec.
/// Specializing MultiVecTraits works via compile-time polymorphism,
/// whereas implementing the MultiVec interface works via run-time
/// polymorphism. You may pick whichever option you like. However,
/// specializing MultiVecTraits is the preferred method. This is
/// because Belos' linear solvers always use a specialization of
/// MultiVecTraits to access multivector operations. They only use
/// MultiVec through a specialization of the MultiVecTraits traits
/// class, which is implemented below in this header file.
///
/// If you want your multivector class (or a wrapper thereof) to
/// implement the MultiVec interface, you should inherit from
/// MultiVec<ScalarType>, where ScalarType is the type of entries in
/// the multivector. For example, a multivector with entries of type
/// double would inherit from MultiVec<double>.
template <class ScalarType>
class MultiVec {
public:
//! @name Constructor/Destructor
//@{
//! Default constructor.
MultiVec() {};
//! Destructor (virtual for memory safety of derived classes).
virtual ~MultiVec () {};
//@}
//! @name Creation methods for new multivectors
//@{
/// \brief Create a new MultiVec with \c numvecs columns.
/// \return Pointer to the new multivector with uninitialized values.
virtual MultiVec<ScalarType> * Clone ( const int numvecs ) const = 0;
/// \brief Create a new MultiVec and copy contents of \c *this into it (deep copy).
/// \return Pointer to the new multivector
virtual MultiVec<ScalarType> * CloneCopy () const = 0;
/*! \brief Creates a new %Belos::MultiVec and copies the selected contents of \c *this
into the new multivector (deep copy). The copied
vectors from \c *this are indicated by the \c index.size() indices in \c index.
\return Pointer to the new multivector
*/
virtual MultiVec<ScalarType> * CloneCopy ( const std::vector<int>& index ) const = 0;
/*! \brief Creates a new %Belos::MultiVec that shares the selected contents of \c *this.
The index of the \c numvecs vectors copied from \c *this are indicated by the
indices given in \c index.
\return Pointer to the new multivector
*/
virtual MultiVec<ScalarType> * CloneViewNonConst ( const std::vector<int>& index ) = 0;
/*! \brief Creates a new %Belos::MultiVec that shares the selected contents of \c *this.
The index of the \c numvecs vectors copied from \c *this are indicated by the
indices given in \c index.
\return Pointer to the new multivector
*/
virtual const MultiVec<ScalarType> * CloneView ( const std::vector<int>& index ) const = 0;
//@}
//! @name Dimension information methods
//@{
//! The number of rows in the multivector.
virtual ptrdiff_t GetGlobalLength () const = 0;
//! The number of vectors (i.e., columns) in the multivector.
virtual int GetNumberVecs () const = 0;
//@}
//! @name Update methods
//@{
//! Update \c *this with \c alpha * \c A * \c B + \c beta * (\c *this).
virtual void
MvTimesMatAddMv (const ScalarType alpha,
const MultiVec<ScalarType>& A,
const Teuchos::SerialDenseMatrix<int,ScalarType>& B, const ScalarType beta) = 0;
//! Replace \c *this with \c alpha * \c A + \c beta * \c B.
virtual void MvAddMv ( const ScalarType alpha, const MultiVec<ScalarType>& A, const ScalarType beta, const MultiVec<ScalarType>& B ) = 0;
//! Scale each element of the vectors in \c *this with \c alpha.
virtual void MvScale ( const ScalarType alpha ) = 0;
//! Scale each element of the <tt>i</tt>-th vector in \c *this with <tt>alpha[i]</tt>.
virtual void MvScale ( const std::vector<ScalarType>& alpha ) = 0;
/*! \brief Compute a dense matrix \c B through the matrix-matrix multiply
\c alpha * \c A^T * (\c *this).
*/
virtual void MvTransMv ( const ScalarType alpha, const MultiVec<ScalarType>& A, Teuchos::SerialDenseMatrix<int,ScalarType>& B) const = 0;
/// \brief Compute the dot product of each column of *this with the corresponding column of A.
///
/// Compute a vector \c b whose entries are the individual
/// dot-products. That is, <tt>b[i] = A[i]^H * (*this)[i]</tt>
/// where <tt>A[i]</tt> is the i-th column of A.
virtual void MvDot ( const MultiVec<ScalarType>& A, std::vector<ScalarType>& b ) const = 0;
//@}
//! @name Norm method
//@{
/// \brief Compute the norm of each vector in \c *this.
///
/// \param normvec [out] On output, normvec[i] holds the norm of the
/// \c i-th vector of \c *this.
/// \param type [in] The type of norm to compute. The 2-norm is the default.
virtual void MvNorm ( std::vector<typename Teuchos::ScalarTraits<ScalarType>::magnitudeType>& normvec, NormType type = TwoNorm ) const = 0;
//@}
//! @name Initialization methods
//@{
/// \brief Copy the vectors in \c A to a set of vectors in \c *this.
///
/// The \c numvecs vectors in \c A are copied to a subset of vectors
/// in \c *this indicated by the indices given in \c index.
virtual void SetBlock ( const MultiVec<ScalarType>& A, const std::vector<int>& index ) = 0;
//! Fill all the vectors in \c *this with random numbers.
virtual void MvRandom () = 0;
//! Replace each element of the vectors in \c *this with \c alpha.
virtual void MvInit ( const ScalarType alpha ) = 0;
//@}
//! @name Print method
//@{
//! Print \c *this multivector to the \c os output stream.
virtual void MvPrint ( std::ostream& os ) const = 0;
//@}
#ifdef HAVE_BELOS_TSQR
//! @name TSQR-related methods
//@{
/// \brief Compute the QR factorization *this = QR, using TSQR.
///
/// The *this multivector on input is the multivector A to factor.
/// It is overwritten with garbage on output.
///
/// \param Q [out] On input: a multivector with the same number of
/// rows and columns as A (the *this multivector). Its contents
/// are overwritten on output with the (explicitly stored) Q
/// factor in the QR factorization of A.
///
/// \param R [out] On output: the R factor in the QR factorization
/// of the (input) multivector A.
///
/// \param forceNonnegativeDiagonal [in] If true, then (if
/// necessary) do extra work (modifying both the Q and R
/// factors) in order to force the R factor to have a
/// nonnegative diagonal.
///
/// For syntax's sake, we provide a default implementation of this
/// method that throws std::logic_error. You should implement this
/// method if you intend to use TsqrOrthoManager or
/// TsqrMatOrthoManager with your subclass of MultiVec.
virtual void
factorExplicit (MultiVec<ScalarType>& Q,
Teuchos::SerialDenseMatrix<int, ScalarType>& R,
const bool forceNonnegativeDiagonal=false)
{
TEUCHOS_TEST_FOR_EXCEPTION(true, std::logic_error, "The Belos::MultiVec<"
<< Teuchos::TypeNameTraits<ScalarType>::name() << "> subclass which you "
"are using does not implement the TSQR-related method factorExplicit().");
}
/// \brief Use result of factorExplicit() to compute rank-revealing decomposition.
///
/// When calling this method, the *this multivector should be the Q
/// factor output of factorExplicit(). Using that Q factor and the
/// R factor from factorExplicit(), compute the singular value
/// decomposition (SVD) of R (\f$R = U \Sigma V^*\f$). If R is full
/// rank (with respect to the given relative tolerance tol), don't
/// change Q (= *this) or R. Otherwise, compute \f$Q := Q \cdot
/// U\f$ and \f$R := \Sigma V^*\f$ in place (the latter may be no
/// longer upper triangular).
///
/// The *this multivector on input must be the explicit Q factor
/// output of a previous call to factorExplicit(). On output: On
/// output: If R is of full numerical rank with respect to the
/// tolerance tol, Q is unmodified. Otherwise, Q is updated so that
/// the first rank columns of Q are a basis for the column space of
/// A (the original matrix whose QR factorization was computed by
/// factorExplicit()). The remaining columns of Q are a basis for
/// the null space of A.
///
/// \param R [in/out] On input: N by N upper triangular matrix with
/// leading dimension LDR >= N. On output: if input is full rank,
/// R is unchanged on output. Otherwise, if \f$R = U \Sigma
/// V^*\f$ is the SVD of R, on output R is overwritten with
/// \f$\Sigma \cdot V^*\f$. This is also an N by N matrix, but
/// may not necessarily be upper triangular.
///
/// \param tol [in] Relative tolerance for computing the numerical
/// rank of the matrix R.
///
/// For syntax's sake, we provide a default implementation of this
/// method that throws std::logic_error. You should implement this
/// method if you intend to use TsqrOrthoManager or
/// TsqrMatOrthoManager with your subclass of MultiVec.
virtual int
revealRank (Teuchos::SerialDenseMatrix<int, ScalarType>& R,
const typename Teuchos::ScalarTraits<ScalarType>::magnitudeType& tol)
{
TEUCHOS_TEST_FOR_EXCEPTION(true, std::logic_error, "The Belos::MultiVec<"
<< Teuchos::TypeNameTraits<ScalarType>::name() << "> subclass which you "
"are using does not implement the TSQR-related method revealRank().");
}
//@}
#endif // HAVE_BELOS_TSQR
};
namespace details {
/// \class MultiVecTsqrAdapter
/// \brief TSQR adapter for MultiVec.
///
/// TSQR (Tall Skinny QR factorization) is an orthogonalization
/// kernel that is as accurate as Householder QR, yet requires only
/// \f$2 \log P\f$ messages between $P$ MPI processes, independently
/// of the number of columns in the multivector.
///
/// TSQR works independently of the particular multivector
/// implementation, and interfaces to the latter via an adapter
/// class. Each multivector type MV needs its own adapter class.
/// The specialization of MultiVecTraits for MV refers to its
/// corresponding adapter class as its \c tsqr_adaptor_type [sic;
/// sorry about the lack of standard spelling of "adapter"] typedef.
///
/// This class is the TSQR adapter for MultiVec. It merely calls
/// MultiVec's corresponding methods for TSQR functionality.
template<class ScalarType>
class MultiVecTsqrAdapter {
public:
typedef MultiVec<ScalarType> MV;
typedef ScalarType scalar_type;
typedef int ordinal_type; // This doesn't matter either
typedef int node_type; // Nor does this
typedef Teuchos::SerialDenseMatrix<ordinal_type, scalar_type> dense_matrix_type;
typedef typename Teuchos::ScalarTraits<scalar_type>::magnitudeType magnitude_type;
//! Compute QR factorization A = QR, using TSQR.
void
factorExplicit (MV& A,
MV& Q,
dense_matrix_type& R,
const bool forceNonnegativeDiagonal=false)
{
A.factorExplicit (Q, R, forceNonnegativeDiagonal);
}
//! Compute rank-revealing decomposition using results of factorExplicit().
int
revealRank (MV& Q,
dense_matrix_type& R,
const magnitude_type& tol)
{
return Q.revealRank (R, tol);
}
void setParameterList (const Teuchos::RCP<Teuchos::ParameterList>& params) {
(void) params;
}
Teuchos::RCP<const Teuchos::ParameterList> getValidParameters () const {
return Teuchos::parameterList ();
}
};
} // namespace details
/// \brief Specialization of MultiVecTraits for Belos::MultiVec.
///
/// Belos interfaces to every multivector implementation through a
/// specialization of MultiVecTraits. Thus, we provide a
/// specialization of MultiVecTraits for the MultiVec run-time
/// polymorphic interface above.
///
/// \tparam ScalarType The type of entries in the multivector; the
/// template parameter of MultiVec.
template<class ScalarType>
class MultiVecTraits<ScalarType,MultiVec<ScalarType> > {
public:
//! @name Creation methods
//@{
/// \brief Create a new empty \c MultiVec containing \c numvecs columns.
/// \return Reference-counted pointer to the new \c MultiVec.
static Teuchos::RCP<MultiVec<ScalarType> >
Clone (const MultiVec<ScalarType>& mv, const int numvecs) {
return Teuchos::rcp (const_cast<MultiVec<ScalarType>&> (mv).Clone (numvecs));
}
///
static Teuchos::RCP<MultiVec<ScalarType> > CloneCopy( const MultiVec<ScalarType>& mv )
{ return Teuchos::rcp( const_cast<MultiVec<ScalarType>&>(mv).CloneCopy() ); }
///
static Teuchos::RCP<MultiVec<ScalarType> > CloneCopy( const MultiVec<ScalarType>& mv, const std::vector<int>& index )
{ return Teuchos::rcp( const_cast<MultiVec<ScalarType>&>(mv).CloneCopy(index) ); }
///
static Teuchos::RCP<MultiVec<ScalarType> >
CloneViewNonConst (MultiVec<ScalarType>& mv, const std::vector<int>& index)
{
return Teuchos::rcp( mv.CloneViewNonConst(index) );
}
static Teuchos::RCP<MultiVec<ScalarType> >
CloneViewNonConst (MultiVec<ScalarType>& mv, const Teuchos::Range1D& index)
{
// mfh 02 Mar 2013: For now, we'll just use the above index
// vector version of CloneViewNonConst to implement this, since
// that doesn't require adding to the MultiVec interface.
std::vector<int> indVec (index.size ());
for (int k = 0; k < index.size (); ++k) {
indVec[k] = k;
}
return CloneViewNonConst (mv, indVec);
}
///
static Teuchos::RCP<const MultiVec<ScalarType> >
CloneView (const MultiVec<ScalarType>& mv, const std::vector<int>& index) {
return Teuchos::rcp( const_cast<MultiVec<ScalarType>&>(mv).CloneView(index) );
}
static Teuchos::RCP<const MultiVec<ScalarType> >
CloneView (const MultiVec<ScalarType>& mv, const Teuchos::Range1D& index)
{
// mfh 02 Mar 2013: For now, we'll just use the above index
// vector version of CloneView to implement this, since that
// doesn't require adding to the MultiVec interface.
std::vector<int> indVec (index.size ());
for (int k = 0; k < index.size (); ++k) {
indVec[k] = k;
}
return CloneView (mv, indVec);
}
///
static ptrdiff_t GetGlobalLength( const MultiVec<ScalarType>& mv )
{ return mv.GetGlobalLength(); }
///
static int GetNumberVecs( const MultiVec<ScalarType>& mv )
{ return mv.GetNumberVecs(); }
///
static void MvTimesMatAddMv( ScalarType alpha, const MultiVec<ScalarType>& A,
const Teuchos::SerialDenseMatrix<int,ScalarType>& B,
ScalarType beta, MultiVec<ScalarType>& mv )
{ mv.MvTimesMatAddMv(alpha, A, B, beta); }
///
static void MvAddMv( ScalarType alpha, const MultiVec<ScalarType>& A, ScalarType beta, const MultiVec<ScalarType>& B, MultiVec<ScalarType>& mv )
{ mv.MvAddMv(alpha, A, beta, B); }
///
static void MvScale ( MultiVec<ScalarType>& mv, const ScalarType alpha )
{ mv.MvScale( alpha ); }
static void MvScale ( MultiVec<ScalarType>& mv, const std::vector<ScalarType>& alpha )
{ mv.MvScale(alpha); }
///
static void MvTransMv( const ScalarType alpha, const MultiVec<ScalarType>& A, const MultiVec<ScalarType>& mv, Teuchos::SerialDenseMatrix<int,ScalarType>& B )
{ mv.MvTransMv(alpha, A, B); }
///
static void MvDot( const MultiVec<ScalarType>& mv, const MultiVec<ScalarType>& A, std::vector<ScalarType>& b )
{ mv.MvDot( A, b ); }
///
static void MvNorm( const MultiVec<ScalarType>& mv, std::vector<typename Teuchos::ScalarTraits<ScalarType>::magnitudeType>& normvec, NormType type = TwoNorm )
{ mv.MvNorm(normvec,type); }
///
static void SetBlock( const MultiVec<ScalarType>& A, const std::vector<int>& index, MultiVec<ScalarType>& mv )
{ mv.SetBlock(A, index); }
static void
Assign (const MultiVec<ScalarType>& A,
MultiVec<ScalarType>& mv)
{
// mfh 02 Mar 2013: For now, we'll just use SetBlock to implement this,
// since that doesn't require adding to the MultiVec interface.
const int numVecsRhs = GetNumberVecs (A);
const int numVecsLhs = GetNumberVecs (mv);
TEUCHOS_TEST_FOR_EXCEPTION(
numVecsLhs != numVecsRhs, std::invalid_argument,
"Belos::MultiVecTraits::Assign: Input multivector A has " << numVecsRhs
<< " columns, which differs from the number of columns " << numVecsLhs
<< " in the output multivector mv.");
// mfh 02 Mar 2013: It's pretty silly to build this each time.
// However, at least that makes the code correct.
std::vector<int> index (numVecsRhs);
for (int k = 0; k < numVecsRhs; ++k) {
index[k] = k;
}
SetBlock (A, index, mv);
}
///
static void MvRandom( MultiVec<ScalarType>& mv )
{ mv.MvRandom(); }
///
static void MvInit( MultiVec<ScalarType>& mv, ScalarType alpha = Teuchos::ScalarTraits<ScalarType>::zero() )
{ mv.MvInit(alpha); }
///
static void MvPrint( const MultiVec<ScalarType>& mv, std::ostream& os )
{ mv.MvPrint(os); }
#ifdef HAVE_BELOS_TSQR
/// \typedef tsqr_adaptor_type
/// \brief TSQR adapter for MultiVec.
///
/// Our TSQR adapter for MultiVec calls MultiVec's virtual
/// methods. If you want to use TSQR with your MultiVec subclass,
/// you must implement these methods yourself, as the default
/// implementations throw std::logic_error.
typedef details::MultiVecTsqrAdapter<ScalarType> tsqr_adaptor_type;
#endif // HAVE_BELOS_TSQR
};
} // namespace Belos
#endif
// end of file BelosMultiVec.hpp
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