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//
// Copyright (C) 2008 - 2015 by the deal.II authors
//
// This file is part of the deal.II library.
//
// The deal.II library is free software; you can use it, redistribute
// it, and/or modify it under the terms of the GNU Lesser General
// Public License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
// The full text of the license can be found in the file LICENSE at
// the top level of the deal.II distribution.
//
// ---------------------------------------------------------------------
#ifndef dealii__trilinos_block_sparse_matrix_h
#define dealii__trilinos_block_sparse_matrix_h
#include <deal.II/base/config.h>
#ifdef DEAL_II_WITH_TRILINOS
# include <deal.II/base/table.h>
# include <deal.II/base/template_constraints.h>
# include <deal.II/lac/block_matrix_base.h>
# include <deal.II/lac/trilinos_sparse_matrix.h>
# include <deal.II/lac/trilinos_block_vector.h>
# include <deal.II/lac/full_matrix.h>
# include <deal.II/lac/exceptions.h>
# include <cmath>
# define TrilinosScalar double
DEAL_II_NAMESPACE_OPEN
// forward declarations
class BlockSparsityPattern;
template <typename number> class BlockSparseMatrix;
namespace TrilinosWrappers
{
/*! @addtogroup TrilinosWrappers
*@{
*/
/**
* Blocked sparse matrix based on the TrilinosWrappers::SparseMatrix class.
* This class implements the functions that are specific to the Trilinos
* SparseMatrix base objects for a blocked sparse matrix, and leaves the
* actual work relaying most of the calls to the individual blocks to the
* functions implemented in the base class. See there also for a description
* of when this class is useful.
*
* In contrast to the deal.II-type SparseMatrix class, the Trilinos matrices
* do not have external objects for the sparsity patterns. Thus, one does
* not determine the size of the individual blocks of a block matrix of this
* type by attaching a block sparsity pattern, but by calling reinit() to
* set the number of blocks and then by setting the size of each block
* separately. In order to fix the data structures of the block matrix, it
* is then necessary to let it know that we have changed the sizes of the
* underlying matrices. For this, one has to call the collect_sizes()
* function, for much the same reason as is documented with the
* BlockSparsityPattern class.
*
* @ingroup Matrix1 @see
* @ref GlossBlockLA "Block (linear algebra)"
* @author Martin Kronbichler, Wolfgang Bangerth, 2008
*/
class BlockSparseMatrix : public BlockMatrixBase<SparseMatrix>
{
public:
/**
* Typedef the base class for simpler access to its own typedefs.
*/
typedef BlockMatrixBase<SparseMatrix> BaseClass;
/**
* Typedef the type of the underlying matrix.
*/
typedef BaseClass::BlockType BlockType;
/**
* Import the typedefs from the base class.
*/
typedef BaseClass::value_type value_type;
typedef BaseClass::pointer pointer;
typedef BaseClass::const_pointer const_pointer;
typedef BaseClass::reference reference;
typedef BaseClass::const_reference const_reference;
typedef BaseClass::size_type size_type;
typedef BaseClass::iterator iterator;
typedef BaseClass::const_iterator const_iterator;
/**
* Constructor; initializes the matrix to be empty, without any structure,
* i.e. the matrix is not usable at all. This constructor is therefore
* only useful for matrices which are members of a class. All other
* matrices should be created at a point in the data flow where all
* necessary information is available.
*
* You have to initialize the matrix before usage with
* reinit(BlockSparsityPattern). The number of blocks per row and column
* are then determined by that function.
*/
BlockSparseMatrix ();
/**
* Destructor.
*/
~BlockSparseMatrix ();
/**
* Pseudo copy operator only copying empty objects. The sizes of the block
* matrices need to be the same.
*/
BlockSparseMatrix &
operator = (const BlockSparseMatrix &);
/**
* This operator assigns a scalar to a matrix. Since this does usually not
* make much sense (should we set all matrix entries to this value? Only
* the nonzero entries of the sparsity pattern?), this operation is only
* allowed if the actual value to be assigned is zero. This operator only
* exists to allow for the obvious notation <tt>matrix=0</tt>, which sets
* all elements of the matrix to zero, but keep the sparsity pattern
* previously used.
*/
BlockSparseMatrix &
operator = (const double d);
/**
* Resize the matrix, by setting the number of block rows and columns.
* This deletes all blocks and replaces them with uninitialized ones, i.e.
* ones for which also the sizes are not yet set. You have to do that by
* calling the @p reinit functions of the blocks themselves. Do not forget
* to call collect_sizes() after that on this object.
*
* The reason that you have to set sizes of the blocks yourself is that
* the sizes may be varying, the maximum number of elements per row may be
* varying, etc. It is simpler not to reproduce the interface of the @p
* SparsityPattern class here but rather let the user call whatever
* function she desires.
*/
void reinit (const size_type n_block_rows,
const size_type n_block_columns);
/**
* Resize the matrix, by using an array of Epetra maps to determine the
* %parallel distribution of the individual matrices. This function
* assumes that a quadratic block matrix is generated.
*/
template <typename BlockSparsityPatternType>
void reinit (const std::vector<Epetra_Map> &input_maps,
const BlockSparsityPatternType &block_sparsity_pattern,
const bool exchange_data = false);
/**
* Resize the matrix, by using an array of index sets to determine the
* %parallel distribution of the individual matrices. This function
* assumes that a quadratic block matrix is generated.
*/
template <typename BlockSparsityPatternType>
void reinit (const std::vector<IndexSet> &input_maps,
const BlockSparsityPatternType &block_sparsity_pattern,
const MPI_Comm &communicator = MPI_COMM_WORLD,
const bool exchange_data = false);
/**
* Resize the matrix and initialize it by the given sparsity pattern.
* Since no distribution map is given, the result is a block matrix for
* which all elements are stored locally.
*/
template <typename BlockSparsityPatternType>
void reinit (const BlockSparsityPatternType &block_sparsity_pattern);
/**
* This function initializes the Trilinos matrix using the deal.II sparse
* matrix and the entries stored therein. It uses a threshold to copy only
* elements whose modulus is larger than the threshold (so zeros in the
* deal.II matrix can be filtered away).
*
* @deprecated Use the respective method with IndexSet arguments instead.
*/
void reinit (const std::vector<Epetra_Map> &input_maps,
const ::dealii::BlockSparseMatrix<double> &deal_ii_sparse_matrix,
const double drop_tolerance=1e-13) DEAL_II_DEPRECATED;
/**
* This function initializes the Trilinos matrix using the deal.II sparse
* matrix and the entries stored therein. It uses a threshold to copy only
* elements whose modulus is larger than the threshold (so zeros in the
* deal.II matrix can be filtered away). Since no Epetra_Map is given, all
* the elements will be locally stored.
*/
void reinit (const ::dealii::BlockSparseMatrix<double> &deal_ii_sparse_matrix,
const double drop_tolerance=1e-13);
/**
* Returns the state of the matrix, i.e., whether compress() needs to be
* called after an operation requiring data exchange. Does only return
* non-true values when used in <tt>debug</tt> mode, since it is quite
* expensive to keep track of all operations that lead to the need for
* compress().
*/
bool is_compressed () const;
/**
* This function collects the sizes of the sub-objects and stores them in
* internal arrays, in order to be able to relay global indices into the
* matrix to indices into the subobjects. You *must* call this function
* each time after you have changed the size of the sub-objects. Note that
* this is a collective operation, i.e., it needs to be called on all MPI
* processes. This command internally calls the method
* <tt>compress()</tt>, so you don't need to call that function in case
* you use <tt>collect_sizes()</tt>.
*/
void collect_sizes ();
/**
* Return the number of nonzero elements of this matrix.
*/
size_type n_nonzero_elements () const;
/**
* Return a vector of the underlying Trilinos Epetra_Map that sets the
* partitioning of the domain space of this block matrix, i.e., the
* partitioning of the individual block vectors this matrix has to be
* multiplied with.
*
* @deprecated Use the methods of the individual matrices based on
* IndexSet arguments.
*/
std::vector<Epetra_Map> domain_partitioner () const DEAL_II_DEPRECATED;
/**
* Return a vector of the underlying Trilinos Epetra_Map that sets the
* partitioning of the range space of this block matrix, i.e., the
* partitioning of the individual block vectors that are the result from
* matrix-vector products.
*
* @deprecated Use the methods of the individual matrices based on
* IndexSet arguments.
*/
std::vector<Epetra_Map> range_partitioner () const DEAL_II_DEPRECATED;
/**
* Matrix-vector multiplication: let $dst = M*src$ with $M$ being this
* matrix. The vector types can be block vectors or non-block vectors
* (only if the matrix has only one row or column, respectively), and need
* to define TrilinosWrappers::SparseMatrix::vmult.
*/
template <typename VectorType1, typename VectorType2>
void vmult (VectorType1 &dst,
const VectorType2 &src) const;
/**
* Matrix-vector multiplication: let $dst = M^T*src$ with $M$ being this
* matrix. This function does the same as vmult() but takes the transposed
* matrix.
*/
template <typename VectorType1, typename VectorType2>
void Tvmult (VectorType1 &dst,
const VectorType2 &src) const;
/**
* Compute the residual of an equation <i>Mx=b</i>, where the residual is
* defined to be <i>r=b-Mx</i>. Write the residual into @p dst. The
* <i>l<sub>2</sub></i> norm of the residual vector is returned.
*
* Source <i>x</i> and destination <i>dst</i> must not be the same vector.
*
* Note that both vectors have to be distributed vectors generated using
* the same Map as was used for the matrix in case you work on a
* distributed memory architecture, using the interface in the
* TrilinosWrappers::MPI::BlockVector class.
*/
TrilinosScalar residual (MPI::BlockVector &dst,
const MPI::BlockVector &x,
const MPI::BlockVector &b) const;
/**
* Compute the residual of an equation <i>Mx=b</i>, where the residual is
* defined to be <i>r=b-Mx</i>. Write the residual into @p dst. The
* <i>l<sub>2</sub></i> norm of the residual vector is returned.
*
* Source <i>x</i> and destination <i>dst</i> must not be the same vector.
*
* Note that both vectors have to be distributed vectors generated using
* the same Map as was used for the matrix in case you work on a
* distributed memory architecture, using the interface in the
* TrilinosWrappers::BlockVector class. Since the block matrix is in
* general distributed among processes, this function only works when
* running the program on one processor.
*/
TrilinosScalar residual (BlockVector &dst,
const BlockVector &x,
const BlockVector &b) const;
/**
* Compute the residual of an equation <i>Mx=b</i>, where the residual is
* defined to be <i>r=b-Mx</i>. Write the residual into @p dst. The
* <i>l<sub>2</sub></i> norm of the residual vector is returned. Just like
* the previous function, but only applicable if the matrix only has one
* block row.
*/
TrilinosScalar residual (MPI::BlockVector &dst,
const MPI::Vector &x,
const MPI::BlockVector &b) const;
/**
* Compute the residual of an equation <i>Mx=b</i>, where the residual is
* defined to be <i>r=b-Mx</i>. Write the residual into @p dst. The
* <i>l<sub>2</sub></i> norm of the residual vector is returned. Just like
* the previous function, but only applicable if the matrix only has one
* block row.
*/
TrilinosScalar residual (BlockVector &dst,
const Vector &x,
const BlockVector &b) const;
/**
* Compute the residual of an equation <i>Mx=b</i>, where the residual is
* defined to be <i>r=b-Mx</i>. Write the residual into @p dst. The
* <i>l<sub>2</sub></i> norm of the residual vector is returned. Just like
* the previous function, but only applicable if the matrix only has one
* block column.
*/
TrilinosScalar residual (MPI::Vector &dst,
const MPI::BlockVector &x,
const MPI::Vector &b) const;
/**
* Compute the residual of an equation <i>Mx=b</i>, where the residual is
* defined to be <i>r=b-Mx</i>. Write the residual into @p dst. The
* <i>l<sub>2</sub></i> norm of the residual vector is returned. Just like
* the previous function, but only applicable if the matrix only has one
* block column.
*/
TrilinosScalar residual (Vector &dst,
const BlockVector &x,
const Vector &b) const;
/**
* Compute the residual of an equation <i>Mx=b</i>, where the residual is
* defined to be <i>r=b-Mx</i>. Write the residual into @p dst. The
* <i>l<sub>2</sub></i> norm of the residual vector is returned. Just like
* the previous function, but only applicable if the matrix only has one
* block.
*/
TrilinosScalar residual (VectorBase &dst,
const VectorBase &x,
const VectorBase &b) const;
/**
* Make the clear() function in the base class visible, though it is
* protected.
*/
using BlockMatrixBase<SparseMatrix>::clear;
/**
* @addtogroup Exceptions
* @{
*/
/**
* Exception
*/
DeclException4 (ExcIncompatibleRowNumbers,
int, int, int, int,
<< "The blocks [" << arg1 << ',' << arg2 << "] and ["
<< arg3 << ',' << arg4 << "] have differing row numbers.");
/**
* Exception
*/
DeclException4 (ExcIncompatibleColNumbers,
int, int, int, int,
<< "The blocks [" << arg1 << ',' << arg2 << "] and ["
<< arg3 << ',' << arg4 << "] have differing column numbers.");
///@}
private:
/**
* Internal version of (T)vmult with two block vectors
*/
template <typename VectorType1, typename VectorType2>
void vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
const dealii::internal::bool2type<true>,
const dealii::internal::bool2type<true>) const;
/**
* Internal version of (T)vmult where the source vector is a block vector
* but the destination vector is a non-block vector
*/
template <typename VectorType1, typename VectorType2>
void vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
const dealii::internal::bool2type<false>,
const dealii::internal::bool2type<true>) const;
/**
* Internal version of (T)vmult where the source vector is a non-block
* vector but the destination vector is a block vector
*/
template <typename VectorType1, typename VectorType2>
void vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
const dealii::internal::bool2type<true>,
const dealii::internal::bool2type<false>) const;
/**
* Internal version of (T)vmult where both source vector and the
* destination vector are non-block vectors (only defined if the matrix
* consists of only one block)
*/
template <typename VectorType1, typename VectorType2>
void vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
const dealii::internal::bool2type<false>,
const dealii::internal::bool2type<false>) const;
};
/*@}*/
// ------------- inline and template functions -----------------
inline
BlockSparseMatrix &
BlockSparseMatrix::operator = (const double d)
{
Assert (d==0, ExcScalarAssignmentOnlyForZeroValue());
for (size_type r=0; r<this->n_block_rows(); ++r)
for (size_type c=0; c<this->n_block_cols(); ++c)
this->block(r,c) = d;
return *this;
}
inline
bool
BlockSparseMatrix::is_compressed () const
{
bool compressed = true;
for (size_type row=0; row<n_block_rows(); ++row)
for (size_type col=0; col<n_block_cols(); ++col)
if (block(row, col).is_compressed() == false)
{
compressed = false;
break;
}
return compressed;
}
template <typename VectorType1, typename VectorType2>
inline
void
BlockSparseMatrix::vmult (VectorType1 &dst,
const VectorType2 &src) const
{
vmult(dst, src, false,
dealii::internal::bool2type<IsBlockVector<VectorType1>::value>(),
dealii::internal::bool2type<IsBlockVector<VectorType2>::value>());
}
template <typename VectorType1, typename VectorType2>
inline
void
BlockSparseMatrix::Tvmult (VectorType1 &dst,
const VectorType2 &src) const
{
vmult(dst, src, true,
dealii::internal::bool2type<IsBlockVector<VectorType1>::value>(),
dealii::internal::bool2type<IsBlockVector<VectorType2>::value>());
}
template <typename VectorType1, typename VectorType2>
inline
void
BlockSparseMatrix::vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
dealii::internal::bool2type<true>,
dealii::internal::bool2type<true>) const
{
if (transpose == true)
BaseClass::Tvmult_block_block (dst, src);
else
BaseClass::vmult_block_block (dst, src);
}
template <typename VectorType1, typename VectorType2>
inline
void
BlockSparseMatrix::vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
dealii::internal::bool2type<false>,
dealii::internal::bool2type<true>) const
{
if (transpose == true)
BaseClass::Tvmult_nonblock_block (dst, src);
else
BaseClass::vmult_nonblock_block (dst, src);
}
template <typename VectorType1, typename VectorType2>
inline
void
BlockSparseMatrix::vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
dealii::internal::bool2type<true>,
dealii::internal::bool2type<false>) const
{
if (transpose == true)
BaseClass::Tvmult_block_nonblock (dst, src);
else
BaseClass::vmult_block_nonblock (dst, src);
}
template <typename VectorType1, typename VectorType2>
inline
void
BlockSparseMatrix::vmult (VectorType1 &dst,
const VectorType2 &src,
const bool transpose,
dealii::internal::bool2type<false>,
dealii::internal::bool2type<false>) const
{
if (transpose == true)
BaseClass::Tvmult_nonblock_nonblock (dst, src);
else
BaseClass::vmult_nonblock_nonblock (dst, src);
}
}
DEAL_II_NAMESPACE_CLOSE
#endif // DEAL_II_WITH_TRILINOS
#endif // dealii__trilinos_block_sparse_matrix_h
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