/usr/include/trilinos/AnasaziTpetraAdapter.hpp is in libtrilinos-anasazi-dev 12.12.1-5.
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// ***********************************************************************
//
// Anasazi: Block Eigensolvers Package
// Copyright 2004 Sandia Corporation
//
// Under terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
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//
// 1. Redistributions of source code must retain the above copyright
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// 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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// @HEADER
#ifndef ANASAZI_TPETRA_ADAPTER_HPP
#define ANASAZI_TPETRA_ADAPTER_HPP
/// \file AnasaziTpetraAdapter.hpp
/// \brief Partial specialization of Anasazi::MultiVecTraits and
/// Anasazi::OperatorTraits for Tpetra objects.
///
/// \section Anasazi_TpetraAdapter_sum Summary
///
/// If you want to use Anasazi solvers with Tpetra objects, include this
/// header file, along with the header file(s) for the solver(s) you
/// want to use. "Tpetra objects" means the following:
/// - Tpetra::MultiVector for the multivector type (MV)
/// - Tpetra::Operator for the operator type (OP)
///
/// You may use any subclass of Tpetra::Operator here, as long as its
/// template parameters match those of the Tpetra::MultiVector type.
/// Many different Trilinos packages implement Tpetra::Operator
/// subclasses. For example, when solving a linear system Ax=b, you
/// could use a Tpetra::CrsMatrix or Tpetra::RowMatrix for the matrix
/// A, and a preconditioner from Ifpack2, Amesos2, or MueLu.
///
/// \section Anasazi_TpetraAdapter_dev Note to Anasazi developers
///
/// This partial specialization assumes that the first (Scalar)
/// template parameter of Anasazi::MultiVecTraits and
/// Anasazi::OperatorTraits matches the first template parameters of
/// Tpetra::MultiVector and Tpetra::Operator. In terms of Anasazi
/// solvers, this means that the specialization assumes that the
/// result of an inner product has the same type as any entry of the
/// multivector or matrix. This is true for most Scalar types of
/// interest, but may not necessarily be true for certain Scalar types
/// implemented in the Stokhos package, or when implementing
/// mixed-precision solvers in certain ways. If you don't know what
/// this means, don't worry about it. If you <i>do</i> know what this
/// means, you might need to write your own partial specialization of
/// Anasazi::MultiVecTraits and Anasazi::OperatorTraits, for a Scalar
/// type different than that of the Tpetra::MultiVector or
/// Tpetra::Operator.
#include <Tpetra_MultiVector.hpp>
#include <Tpetra_Operator.hpp>
#include <Teuchos_Array.hpp>
#include <Teuchos_Assert.hpp>
#include <Teuchos_DefaultSerialComm.hpp>
#include <Teuchos_ScalarTraits.hpp>
#include <AnasaziConfigDefs.hpp>
#include <AnasaziTypes.hpp>
#include <AnasaziMultiVecTraits.hpp>
#include <AnasaziOperatorTraits.hpp>
#ifdef HAVE_ANASAZI_TSQR
# include <Tpetra_TsqrAdaptor.hpp>
#endif // HAVE_ANASAZI_TSQR
namespace Anasazi {
/// \brief Specialization of MultiVecTraits for MV = Tpetra::MultiVector.
///
/// This interface lets Anasazi' solvers work directly with
/// Tpetra::MultiVector objects as the MultiVector type. That type
/// corresponds to the MV template parameter, which is the second
/// template parameter (after Scalar) of most Anasazi classes.
///
/// The four template parameters of this partial specialization
/// correspond exactly to the four template parameters of
/// Tpetra::MultiVector. See the Tpetra::MultiVector documentation
/// for more information.
template<class Scalar, class LO, class GO, class Node>
class MultiVecTraits<Scalar, Tpetra::MultiVector<Scalar,LO,GO,Node> > {
typedef Tpetra::MultiVector<Scalar, LO, GO, Node> MV;
public:
/// \brief Create a new MultiVector with \c numVecs columns.
///
/// The returned Tpetra::MultiVector has the same Tpetra::Map
/// (distribution over one or more parallel processes) as \c X.
/// Its entries are not initialized and have undefined values.
static Teuchos::RCP<MV> Clone (const MV& X, const int numVecs) {
Teuchos::RCP<MV> Y (new MV (X.getMap (), numVecs, false));
Y->setCopyOrView (Teuchos::View);
return Y;
}
//! Create and return a deep copy of X.
static Teuchos::RCP<MV> CloneCopy (const MV& X)
{
// Make a deep copy of X. The one-argument copy constructor
// does a shallow copy by default; the second argument tells it
// to do a deep copy.
Teuchos::RCP<MV> X_copy (new MV (X, Teuchos::Copy));
// Make Tpetra::MultiVector use the new view semantics. This is
// a no-op for the Kokkos refactor version of Tpetra; it only
// does something for the "classic" version of Tpetra. This
// shouldn't matter because Belos only handles MV through RCP
// and through this interface anyway, but it doesn't hurt to set
// it and make sure that it works.
X_copy->setCopyOrView (Teuchos::View);
return X_copy;
}
/// \brief Create and return a deep copy of the given columns of mv.
///
/// \pre \code mv.getNumVectors() != 0 || index.size() == 0 \endcode
/// \pre For all k such that <tt>0 <= k < index.size()</tt>,
/// \code
/// 0 <= index[k] < mv.getNumVectors();
/// \endcode
/// \post If this method returns Y:
/// \code
/// Y->isConstantStride() && Y->getNumVectors() == index.size();
/// \endcode
static Teuchos::RCP<MV>
CloneCopy (const MV& mv, const std::vector<int>& index)
{
#ifdef HAVE_TPETRA_DEBUG
const char fnName[] = "Anasazi::MultiVecTraits::CloneCopy(mv,index)";
const size_t inNumVecs = mv.getNumVectors ();
TEUCHOS_TEST_FOR_EXCEPTION(
index.size () > 0 && *std::min_element (index.begin (), index.end ()) < 0,
std::runtime_error, fnName << ": All indices must be nonnegative.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.size () > 0 &&
static_cast<size_t> (*std::max_element (index.begin (), index.end ())) >= inNumVecs,
std::runtime_error,
fnName << ": All indices must be strictly less than the number of "
"columns " << inNumVecs << " of the input multivector mv.");
#endif // HAVE_TPETRA_DEBUG
// Tpetra wants an array of size_t, not of int.
Teuchos::Array<size_t> columns (index.size ());
for (std::vector<int>::size_type j = 0; j < index.size (); ++j) {
columns[j] = index[j];
}
// mfh 14 Aug 2014: Tpetra already detects and optimizes for a
// continuous column index range in MultiVector::subCopy, so we
// don't have to check here.
Teuchos::RCP<MV> X_copy = mv.subCopy (columns ());
X_copy->setCopyOrView (Teuchos::View);
return X_copy;
}
/// \brief Create and return a deep copy of the given columns of mv.
///
/// \post If this method returns Y:
/// \code
/// Y->isConstantStride() && Y->getNumVectors() == index.size();
/// \endcode
static Teuchos::RCP<MV>
CloneCopy (const MV& mv, const Teuchos::Range1D& index)
{
const bool validRange = index.size() > 0 &&
index.lbound() >= 0 &&
index.ubound() < GetNumberVecs(mv);
if (! validRange) { // invalid range; generate error message
std::ostringstream os;
os << "Anasazi::MultiVecTraits::CloneCopy(mv,index=["
<< index.lbound() << "," << index.ubound() << "]): ";
TEUCHOS_TEST_FOR_EXCEPTION(
index.size() == 0, std::invalid_argument,
os.str() << "Empty index range is not allowed.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.lbound() < 0, std::invalid_argument,
os.str() << "Index range includes negative index/ices, which is not "
"allowed.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.ubound() >= GetNumberVecs(mv), std::invalid_argument,
os.str() << "Index range exceeds number of vectors "
<< mv.getNumVectors() << " in the input multivector.");
TEUCHOS_TEST_FOR_EXCEPTION(true, std::logic_error,
os.str() << "Should never get here!");
}
Teuchos::RCP<MV> X_copy = mv.subCopy (index);
X_copy->setCopyOrView (Teuchos::View);
return X_copy;
}
static Teuchos::RCP<MV>
CloneViewNonConst (MV& mv, const std::vector<int>& index)
{
#ifdef HAVE_TPETRA_DEBUG
const char fnName[] = "Anasazi::MultiVecTraits::CloneViewNonConst(mv,index)";
const size_t numVecs = mv.getNumVectors ();
TEUCHOS_TEST_FOR_EXCEPTION(
index.size () > 0 && *std::min_element (index.begin (), index.end ()) < 0,
std::invalid_argument,
fnName << ": All indices must be nonnegative.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.size () > 0 &&
static_cast<size_t> (*std::max_element (index.begin (), index.end ())) >= numVecs,
std::invalid_argument,
fnName << ": All indices must be strictly less than the number of "
"columns " << numVecs << " in the input MultiVector mv.");
#endif // HAVE_TPETRA_DEBUG
// Tpetra wants an array of size_t, not of int.
Teuchos::Array<size_t> columns (index.size ());
for (std::vector<int>::size_type j = 0; j < index.size (); ++j) {
columns[j] = index[j];
}
// mfh 14 Aug 2014: Tpetra already detects and optimizes for a
// continuous column index range in
// MultiVector::subViewNonConst, so we don't have to check here.
Teuchos::RCP<MV> X_view = mv.subViewNonConst (columns ());
X_view->setCopyOrView (Teuchos::View);
return X_view;
}
static Teuchos::RCP<MV>
CloneViewNonConst (MV& mv, const Teuchos::Range1D& index)
{
// NOTE (mfh 11 Jan 2011) We really should check for possible
// overflow of int here. However, the number of columns in a
// multivector typically fits in an int.
const int numCols = static_cast<int> (mv.getNumVectors());
const bool validRange = index.size() > 0 &&
index.lbound() >= 0 && index.ubound() < numCols;
if (! validRange) {
std::ostringstream os;
os << "Belos::MultiVecTraits::CloneViewNonConst(mv,index=["
<< index.lbound() << ", " << index.ubound() << "]): ";
TEUCHOS_TEST_FOR_EXCEPTION(
index.size() == 0, std::invalid_argument,
os.str() << "Empty index range is not allowed.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.lbound() < 0, std::invalid_argument,
os.str() << "Index range includes negative inde{x,ices}, which is "
"not allowed.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.ubound() >= numCols, std::invalid_argument,
os.str() << "Index range exceeds number of vectors " << numCols
<< " in the input multivector.");
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error,
os.str() << "Should never get here!");
}
Teuchos::RCP<MV> X_view = mv.subViewNonConst (index);
X_view->setCopyOrView (Teuchos::View);
return X_view;
}
static Teuchos::RCP<const MV>
CloneView (const MV& mv, const std::vector<int>& index)
{
#ifdef HAVE_TPETRA_DEBUG
const char fnName[] = "Belos::MultiVecTraits<Scalar, "
"Tpetra::MultiVector<...> >::CloneView(mv,index)";
const size_t numVecs = mv.getNumVectors ();
TEUCHOS_TEST_FOR_EXCEPTION(
*std::min_element (index.begin (), index.end ()) < 0,
std::invalid_argument,
fnName << ": All indices must be nonnegative.");
TEUCHOS_TEST_FOR_EXCEPTION(
static_cast<size_t> (*std::max_element (index.begin (), index.end ())) >= numVecs,
std::invalid_argument,
fnName << ": All indices must be strictly less than the number of "
"columns " << numVecs << " in the input MultiVector mv.");
#endif // HAVE_TPETRA_DEBUG
// Tpetra wants an array of size_t, not of int.
Teuchos::Array<size_t> columns (index.size ());
for (std::vector<int>::size_type j = 0; j < index.size (); ++j) {
columns[j] = index[j];
}
// mfh 14 Aug 2014: Tpetra already detects and optimizes for a
// continuous column index range in MultiVector::subView, so we
// don't have to check here.
Teuchos::RCP<const MV> X_view = mv.subView (columns);
Teuchos::rcp_const_cast<MV> (X_view)->setCopyOrView (Teuchos::View);
return X_view;
}
static Teuchos::RCP<const MV>
CloneView (const MV& mv, const Teuchos::Range1D& index)
{
// NOTE (mfh 11 Jan 2011) We really should check for possible
// overflow of int here. However, the number of columns in a
// multivector typically fits in an int.
const int numCols = static_cast<int> (mv.getNumVectors());
const bool validRange = index.size() > 0 &&
index.lbound() >= 0 && index.ubound() < numCols;
if (! validRange) {
std::ostringstream os;
os << "Anasazi::MultiVecTraits::CloneView(mv, index=["
<< index.lbound () << ", " << index.ubound() << "]): ";
TEUCHOS_TEST_FOR_EXCEPTION(index.size() == 0, std::invalid_argument,
os.str() << "Empty index range is not allowed.");
TEUCHOS_TEST_FOR_EXCEPTION(index.lbound() < 0, std::invalid_argument,
os.str() << "Index range includes negative index/ices, which is not "
"allowed.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.ubound() >= numCols, std::invalid_argument,
os.str() << "Index range exceeds number of vectors " << numCols
<< " in the input multivector.");
TEUCHOS_TEST_FOR_EXCEPTION(true, std::logic_error,
os.str() << "Should never get here!");
}
Teuchos::RCP<const MV> X_view = mv.subView (index);
Teuchos::rcp_const_cast<MV> (X_view)->setCopyOrView (Teuchos::View);
return X_view;
}
static ptrdiff_t GetGlobalLength( const MV& mv ) {
return static_cast<ptrdiff_t> (mv.getGlobalLength ());
}
static int GetNumberVecs (const MV& mv) {
return static_cast<int> (mv.getNumVectors ());
}
static void
MvTimesMatAddMv (Scalar alpha,
const MV& A,
const Teuchos::SerialDenseMatrix<int, Scalar>& B,
Scalar beta,
MV& mv)
{
using Teuchos::ArrayView;
using Teuchos::Comm;
using Teuchos::rcpFromRef;
typedef Tpetra::Map<LO, GO, Node> map_type;
#ifdef HAVE_ANASAZI_TPETRA_TIMERS
const std::string timerName ("Anasazi::MVT::MvTimesMatAddMv");
Teuchos::RCP<Teuchos::Time> timer =
Teuchos::TimeMonitor::lookupCounter (timerName);
if (timer.is_null ()) {
timer = Teuchos::TimeMonitor::getNewCounter (timerName);
}
TEUCHOS_TEST_FOR_EXCEPTION(
timer.is_null (), std::logic_error,
"Anasazi::MultiVecTraits::MvTimesMatAddMv: "
"Failed to look up timer \"" << timerName << "\". "
"Please report this bug to the Belos developers.");
// This starts the timer. It will be stopped on scope exit.
Teuchos::TimeMonitor timeMon (*timer);
#endif
// Check if B is 1-by-1, in which case we can just call update()
if (B.numRows () == 1 && B.numCols () == 1) {
mv.update (alpha*B(0,0), A, beta);
return;
}
// Create local map
Teuchos::SerialComm<int> serialComm;
map_type LocalMap (B.numRows (), A.getMap ()->getIndexBase (),
rcpFromRef<const Comm<int> > (serialComm),
Tpetra::LocallyReplicated, A.getMap ()->getNode ());
// encapsulate Teuchos::SerialDenseMatrix data in ArrayView
ArrayView<const Scalar> Bvalues (B.values (), B.stride () * B.numCols ());
// create locally replicated MultiVector with a copy of this data
MV B_mv (rcpFromRef (LocalMap), Bvalues, B.stride (), B.numCols ());
mv.multiply (Teuchos::NO_TRANS, Teuchos::NO_TRANS, alpha, A, B_mv, beta);
}
/// \brief <tt>mv := alpha*A + beta*B</tt>
///
/// The Tpetra specialization of this method ignores and
/// completely overwrites any NaN or Inf entries in A. Thus, it
/// does <i>not</i> mean the same thing as <tt>mv := 0*mv +
/// alpha*A + beta*B</tt> in IEEE 754 floating-point arithmetic.
/// (Remember that NaN*0 = NaN.)
static void
MvAddMv (Scalar alpha,
const MV& A,
Scalar beta,
const MV& B,
MV& mv)
{
mv.update (alpha, A, beta, B, Teuchos::ScalarTraits<Scalar>::zero ());
}
static void MvScale (MV& mv, Scalar alpha) {
mv.scale (alpha);
}
static void MvScale (MV& mv, const std::vector<Scalar>& alphas) {
mv.scale (alphas);
}
static void
MvTransMv (const Scalar alpha,
const MV& A,
const MV& B,
Teuchos::SerialDenseMatrix<int,Scalar>& C)
{
using Tpetra::LocallyReplicated;
using Teuchos::Comm;
using Teuchos::RCP;
using Teuchos::rcp;
using Teuchos::TimeMonitor;
typedef Tpetra::Map<LO,GO,Node> map_type;
#ifdef HAVE_ANASAZI_TPETRA_TIMERS
const std::string timerName ("Anasazi::MVT::MvTransMv");
RCP<Teuchos::Time> timer = TimeMonitor::lookupCounter (timerName);
if (timer.is_null ()) {
timer = TimeMonitor::getNewCounter (timerName);
}
TEUCHOS_TEST_FOR_EXCEPTION(
timer.is_null (), std::logic_error, "Anasazi::MvTransMv: "
"Failed to look up timer \"" << timerName << "\". "
"Please report this bug to the Belos developers.");
// This starts the timer. It will be stopped on scope exit.
TimeMonitor timeMon (*timer);
#endif // HAVE_ANASAZI_TPETRA_TIMERS
// Form alpha * A^H * B, then copy into the SerialDenseMatrix.
// We will create a multivector C_mv from a a local map. This
// map has a serial comm, the purpose being to short-circuit the
// MultiVector::reduce() call at the end of
// MultiVector::multiply(). Otherwise, the reduced multivector
// data would be copied back to the GPU, only to turn around and
// have to get it back here. This saves us a round trip for
// this data.
const int numRowsC = C.numRows ();
const int numColsC = C.numCols ();
const int strideC = C.stride ();
// Check if numRowsC == numColsC == 1, in which case we can call dot()
if (numRowsC == 1 && numColsC == 1) {
if (alpha == Teuchos::ScalarTraits<Scalar>::zero ()) {
// Short-circuit, as required by BLAS semantics.
C(0,0) = alpha;
return;
}
A.dot (B, Teuchos::ArrayView<Scalar> (C.values (), 1));
if (alpha != Teuchos::ScalarTraits<Scalar>::one ()) {
C(0,0) *= alpha;
}
return;
}
// get comm
RCP<const Comm<int> > pcomm = A.getMap ()->getComm ();
// create local map with comm
RCP<const map_type> LocalMap =
rcp (new map_type (numRowsC, 0, pcomm, LocallyReplicated,
A.getMap ()->getNode ()));
// create local multivector to hold the result
const bool INIT_TO_ZERO = true;
MV C_mv (LocalMap, numColsC, INIT_TO_ZERO);
// multiply result into local multivector
C_mv.multiply (Teuchos::CONJ_TRANS, Teuchos::NO_TRANS, alpha, A, B,
Teuchos::ScalarTraits<Scalar>::zero ());
// create arrayview encapsulating the Teuchos::SerialDenseMatrix
Teuchos::ArrayView<Scalar> C_view (C.values (), strideC * numColsC);
// No accumulation to do; simply extract the multivector data
// into C. Extract a copy of the result into the array view
// (and therefore, the SerialDenseMatrix).
C_mv.get1dCopy (C_view, strideC);
}
//! For all columns j of A, set <tt>dots[j] := A[j]^T * B[j]</tt>.
static void
MvDot (const MV& A, const MV& B, std::vector<Scalar> &dots)
{
const size_t numVecs = A.getNumVectors ();
TEUCHOS_TEST_FOR_EXCEPTION(
numVecs != B.getNumVectors (), std::invalid_argument,
"Anasazi::MultiVecTraits::MvDot(A,B,dots): "
"A and B must have the same number of columns. "
"A has " << numVecs << " column(s), "
"but B has " << B.getNumVectors () << " column(s).");
#ifdef HAVE_TPETRA_DEBUG
TEUCHOS_TEST_FOR_EXCEPTION(
dots.size() < numVecs, std::invalid_argument,
"Anasazi::MultiVecTraits::MvDot(A,B,dots): "
"The output array 'dots' must have room for all dot products. "
"A and B each have " << numVecs << " column(s), "
"but 'dots' only has " << dots.size() << " entry(/ies).");
#endif // HAVE_TPETRA_DEBUG
Teuchos::ArrayView<Scalar> av (dots);
A.dot (B, av (0, numVecs));
}
//! For all columns j of mv, set <tt>normvec[j] = norm(mv[j])</tt>.
static void
MvNorm (const MV& mv,
std::vector<typename Teuchos::ScalarTraits<Scalar>::magnitudeType> &normvec)
{
typedef typename Teuchos::ScalarTraits<Scalar>::magnitudeType magnitude_type;
#ifdef HAVE_TPETRA_DEBUG
TEUCHOS_TEST_FOR_EXCEPTION(
normvec.size () < static_cast<std::vector<int>::size_type> (mv.getNumVectors ()),
std::invalid_argument,
"Anasazi::MultiVecTraits::MvNorm(mv,normvec): The normvec output "
"argument must have at least as many entries as the number of vectors "
"(columns) in the MultiVector mv. normvec.size() = " << normvec.size ()
<< " < mv.getNumVectors() = " << mv.getNumVectors () << ".");
#endif // HAVE_TPETRA_DEBUG
Teuchos::ArrayView<magnitude_type> av (normvec);
mv.norm2 (av (0, mv.getNumVectors ()));
}
static void
SetBlock (const MV& A, const std::vector<int>& index, MV& mv)
{
using Teuchos::Range1D;
using Teuchos::RCP;
const size_t inNumVecs = A.getNumVectors ();
#ifdef HAVE_TPETRA_DEBUG
TEUCHOS_TEST_FOR_EXCEPTION(
inNumVecs < static_cast<size_t> (index.size ()), std::invalid_argument,
"Anasazi::MultiVecTraits::SetBlock(A,index,mv): 'index' argument must "
"have no more entries as the number of columns in the input MultiVector"
" A. A.getNumVectors() = " << inNumVecs << " < index.size () = "
<< index.size () << ".");
#endif // HAVE_TPETRA_DEBUG
RCP<MV> mvsub = CloneViewNonConst (mv, index);
if (inNumVecs > static_cast<size_t> (index.size ())) {
RCP<const MV> Asub = A.subView (Range1D (0, index.size () - 1));
Tpetra::deep_copy (*mvsub, *Asub);
} else {
Tpetra::deep_copy (*mvsub, A);
}
}
static void
SetBlock (const MV& A, const Teuchos::Range1D& index, MV& mv)
{
// Range1D bounds are signed; size_t is unsigned.
// Assignment of Tpetra::MultiVector is a deep copy.
// Tpetra::MultiVector::getNumVectors() returns size_t. It's
// fair to assume that the number of vectors won't overflow int,
// since the typical use case of multivectors involves few
// columns, but it's friendly to check just in case.
const size_t maxInt =
static_cast<size_t> (Teuchos::OrdinalTraits<int>::max ());
const bool overflow =
maxInt < A.getNumVectors () && maxInt < mv.getNumVectors ();
if (overflow) {
std::ostringstream os;
os << "Anasazi::MultiVecTraits::SetBlock(A, index=[" << index.lbound ()
<< ", " << index.ubound () << "], mv): ";
TEUCHOS_TEST_FOR_EXCEPTION(
maxInt < A.getNumVectors (), std::range_error, os.str () << "Number "
"of columns (size_t) in the input MultiVector 'A' overflows int.");
TEUCHOS_TEST_FOR_EXCEPTION(
maxInt < mv.getNumVectors (), std::range_error, os.str () << "Number "
"of columns (size_t) in the output MultiVector 'mv' overflows int.");
}
// We've already validated the static casts above.
const int numColsA = static_cast<int> (A.getNumVectors ());
const int numColsMv = static_cast<int> (mv.getNumVectors ());
// 'index' indexes into mv; it's the index set of the target.
const bool validIndex =
index.lbound () >= 0 && index.ubound () < numColsMv;
// We can't take more columns out of A than A has.
const bool validSource = index.size () <= numColsA;
if (! validIndex || ! validSource) {
std::ostringstream os;
os << "Anasazi::MultiVecTraits::SetBlock(A, index=[" << index.lbound ()
<< ", " << index.ubound () << "], mv): ";
TEUCHOS_TEST_FOR_EXCEPTION(
index.lbound() < 0, std::invalid_argument,
os.str() << "Range lower bound must be nonnegative.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.ubound() >= numColsMv, std::invalid_argument,
os.str() << "Range upper bound must be less than the number of "
"columns " << numColsA << " in the 'mv' output argument.");
TEUCHOS_TEST_FOR_EXCEPTION(
index.size() > numColsA, std::invalid_argument,
os.str() << "Range must have no more elements than the number of "
"columns " << numColsA << " in the 'A' input argument.");
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error, "Should never get here!");
}
// View of the relevant column(s) of the target multivector mv.
// We avoid view creation overhead by only creating a view if
// the index range is different than [0, (# columns in mv) - 1].
Teuchos::RCP<MV> mv_view;
if (index.lbound () == 0 && index.ubound () + 1 == numColsMv) {
mv_view = Teuchos::rcpFromRef (mv); // Non-const, non-owning RCP
} else {
mv_view = CloneViewNonConst (mv, index);
}
// View of the relevant column(s) of the source multivector A.
// If A has fewer columns than mv_view, then create a view of
// the first index.size() columns of A.
Teuchos::RCP<const MV> A_view;
if (index.size () == numColsA) {
A_view = Teuchos::rcpFromRef (A); // Const, non-owning RCP
} else {
A_view = CloneView (A, Teuchos::Range1D (0, index.size () - 1));
}
Tpetra::deep_copy (*mv_view, *A_view);
}
static void Assign (const MV& A, MV& mv)
{
const char errPrefix[] = "Anasazi::MultiVecTraits::Assign(A, mv): ";
// Range1D bounds are signed; size_t is unsigned.
// Assignment of Tpetra::MultiVector is a deep copy.
// Tpetra::MultiVector::getNumVectors() returns size_t. It's
// fair to assume that the number of vectors won't overflow int,
// since the typical use case of multivectors involves few
// columns, but it's friendly to check just in case.
const size_t maxInt =
static_cast<size_t> (Teuchos::OrdinalTraits<int>::max ());
const bool overflow =
maxInt < A.getNumVectors () && maxInt < mv.getNumVectors ();
if (overflow) {
TEUCHOS_TEST_FOR_EXCEPTION(
maxInt < A.getNumVectors(), std::range_error,
errPrefix << "Number of columns in the input multivector 'A' "
"(a size_t) overflows int.");
TEUCHOS_TEST_FOR_EXCEPTION(
maxInt < mv.getNumVectors(), std::range_error,
errPrefix << "Number of columns in the output multivector 'mv' "
"(a size_t) overflows int.");
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error, "Should never get here!");
}
// We've already validated the static casts above.
const int numColsA = static_cast<int> (A.getNumVectors ());
const int numColsMv = static_cast<int> (mv.getNumVectors ());
if (numColsA > numColsMv) {
TEUCHOS_TEST_FOR_EXCEPTION(
numColsA > numColsMv, std::invalid_argument,
errPrefix << "Input multivector 'A' has " << numColsA << " columns, "
"but output multivector 'mv' has only " << numColsMv << " columns.");
TEUCHOS_TEST_FOR_EXCEPTION(true, std::logic_error, "Should never get here!");
}
if (numColsA == numColsMv) {
Tpetra::deep_copy (mv, A);
} else {
Teuchos::RCP<MV> mv_view =
CloneViewNonConst (mv, Teuchos::Range1D (0, numColsA - 1));
Tpetra::deep_copy (*mv_view, A);
}
}
static void MvRandom (MV& mv) {
mv.randomize ();
}
static void
MvInit (MV& mv, const Scalar alpha = Teuchos::ScalarTraits<Scalar>::zero ())
{
mv.putScalar (alpha);
}
static void MvPrint (const MV& mv, std::ostream& os) {
mv.print (os);
}
#ifdef HAVE_ANASAZI_TSQR
/// \typedef tsqr_adaptor_type
/// \brief TsqrAdaptor specialization for Tpetra::MultiVector
typedef Tpetra::TsqrAdaptor<Tpetra::MultiVector<Scalar, LO, GO, Node> > tsqr_adaptor_type;
#endif // HAVE_ANASAZI_TSQR
};
//! Partial specialization of OperatorTraits for Tpetra objects.
template <class Scalar, class LO, class GO, class Node>
class OperatorTraits<Scalar,
Tpetra::MultiVector<Scalar,LO,GO,Node>,
Tpetra::Operator<Scalar,LO,GO,Node> >
{
public:
static void
Apply (const Tpetra::Operator<Scalar,LO,GO,Node>& Op,
const Tpetra::MultiVector<Scalar,LO,GO,Node>& X,
Tpetra::MultiVector<Scalar,LO,GO,Node>& Y)
{
Op.apply (X, Y, Teuchos::NO_TRANS);
}
};
} // end of Anasazi namespace
#endif
// end of file ANASAZI_TPETRA_ADAPTER_HPP
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