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//
// Copyright (C) 2010 - 2016 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__block_linear_operator_h
#define dealii__block_linear_operator_h
#include <deal.II/base/config.h>
#include <deal.II/base/exceptions.h>
#include <deal.II/lac/linear_operator.h>
#ifdef DEAL_II_WITH_CXX11
DEAL_II_NAMESPACE_OPEN
// Forward declarations:
template <typename Number> class BlockVector;
template <typename Range = BlockVector<double>,
typename Domain = Range>
class BlockLinearOperator;
template <typename Range = BlockVector<double>,
typename Domain = Range,
typename BlockMatrixType>
BlockLinearOperator<Range, Domain>
block_operator(const BlockMatrixType &matrix);
template <size_t m, size_t n,
typename Range = BlockVector<double>,
typename Domain = Range>
BlockLinearOperator<Range, Domain>
block_operator(const std::array<std::array<LinearOperator<typename Range::BlockType, typename Domain::BlockType>, n>, m> &);
template <size_t m,
typename Range = BlockVector<double>,
typename Domain = Range>
BlockLinearOperator<Range, Domain>
block_diagonal_operator(const std::array<LinearOperator<typename Range::BlockType, typename Domain::BlockType>, m> &);
template <size_t m,
typename Range = BlockVector<double>,
typename Domain = Range>
BlockLinearOperator<Range, Domain>
block_diagonal_operator(const LinearOperator<typename Range::BlockType, typename Domain::BlockType> &op);
// This is a workaround for a bug in <=gcc-4.7 that does not like partial
// template default values in combination with local lambda expressions [1]
//
// [1] https://gcc.gnu.org/bugzilla/show_bug.cgi?id=53624
//
// Forward declare functions with partial template defaults:
template <typename Range = BlockVector<double>,
typename Domain = Range,
typename BlockMatrixType>
BlockLinearOperator<Range, Domain>
block_diagonal_operator(const BlockMatrixType &block_matrix);
template <typename Range = BlockVector<double>,
typename Domain = Range>
LinearOperator<Domain, Range>
block_forward_substitution(const BlockLinearOperator<Range, Domain> &,
const BlockLinearOperator<Domain, Range> &);
template <typename Range = BlockVector<double>,
typename Domain = Range>
LinearOperator<Domain, Range>
block_back_substitution(const BlockLinearOperator<Range, Domain> &,
const BlockLinearOperator<Domain, Range> &);
// end of workaround
/**
* A class to store the concept of a block linear operator.
*
* This class increases the interface of LinearOperator (which encapsulates
* the @p Matrix interface) by three additional functions:
* @code
* std::function<unsigned int()> n_block_rows;
* std::function<unsigned int()> n_block_cols;
* std::function<BlockType(unsigned int, unsigned int)> block;
* @endcode
* that describe the underlying block structure (of an otherwise opaque)
* linear operator.
*
* Objects of type BlockLinearOperator can be created similarly to
* LinearOperator with a wrapper function:
* @code
* dealii::BlockSparseMatrix<double> A;
* const auto block_op_a = block_operator(A);
* @endcode
*
* A BlockLinearOperator can be sliced to a LinearOperator at any time. This
* removes all information about the underlying block structure (beacuse above
* <code>std::function</code> objects are no longer available) - the linear
* operator interface, however, remains intact.
*
* @note This class makes heavy use of <code>std::function</code> objects and
* lambda functions. This flexibiliy comes with a run-time penalty. Only use
* this object to encapsulate object with medium to large individual block
* sizes, and small block structure (as a rule of thumb, matrix blocks greater
* than $1000\times1000$).
*
* @note This class is only available if deal.II was configured with C++11
* support, i.e., if <code>DEAL_II_WITH_CXX11</code> is enabled during cmake
* configure.
*
* @author Matthias Maier, 2015
*
* @ingroup LAOperators
*/
template <typename Range, typename Domain>
class BlockLinearOperator : public LinearOperator<Range, Domain>
{
public:
typedef LinearOperator<typename Range::BlockType, typename Domain::BlockType> BlockType;
/**
* Create an empty BlockLinearOperator object.
*
* All<code>std::function</code> member objects of this class and its base
* class LinearOperator are initialized with default variants that throw an
* exception upon invocation.
*/
BlockLinearOperator()
: LinearOperator<Range, Domain>()
{
n_block_rows = []() -> unsigned int
{
Assert(false, ExcMessage("Uninitialized BlockLinearOperator<Range, Domain>::n_block_rows called"));
return 0;
};
n_block_cols = []() -> unsigned int
{
Assert(false, ExcMessage("Uninitialized BlockLinearOperator<Range, Domain>::n_block_cols called"));
return 0;
};
block = [](unsigned int, unsigned int) -> BlockType
{
Assert(false, ExcMessage("Uninitialized BlockLinearOperator<Range, Domain>::block called"));
return BlockType();
};
}
/**
* Default copy constructor.
*/
BlockLinearOperator(const BlockLinearOperator<Range, Domain> &) =
default;
/**
* Templated copy constructor that creates a BlockLinearOperator object from
* an object @p op for which the conversion function
* <code>block_operator</code> is defined.
*/
template<typename Op>
BlockLinearOperator(const Op &op)
{
*this = block_operator<Range, Domain, Op>(op);
}
/**
* Create a BlockLinearOperator from a two-dimensional array @p ops of
* LinearOperator. This constructor calls the corresponding block_operator()
* specialization.
*/
template<size_t m, size_t n>
BlockLinearOperator(const std::array<std::array<BlockType, n>, m> &ops)
{
*this = block_operator<m, n, Range, Domain>(ops);
}
/**
* Create a block-diagonal BlockLinearOperator from a one-dimensional array
* @p ops of LinearOperator. This constructor calls the corresponding
* block_operator() specialization.
*/
template<size_t m>
BlockLinearOperator(const std::array<BlockType, m> &ops)
{
*this = block_diagonal_operator<m, Range, Domain>(ops);
}
/**
* Default copy assignment operator.
*/
BlockLinearOperator<Range, Domain> &
operator=(const BlockLinearOperator<Range, Domain> &) = default;
/**
* Templated copy assignment operator for an object @p op for which the
* conversion function <code>block_operator</code> is defined.
*/
template <typename Op>
BlockLinearOperator<Range, Domain> &operator=(const Op &op)
{
*this = block_operator<Range, Domain, Op>(op);
return *this;
}
/**
* Copy assignment from a two-dimensional array @p ops of LinearOperator.
* This assignment operator calls the corresponding block_operator()
* specialization.
*/
template <size_t m, size_t n>
BlockLinearOperator<Range, Domain> &
operator=(const std::array<std::array<BlockType, n>, m> &ops)
{
*this = block_operator<m, n, Range, Domain>(ops);
return *this;
}
/**
* Copy assignment from a one-dimensional array @p ops of LinearOperator
* that creates a block-diagonal BlockLinearOperator. This assignment
* operator calls the corresponding block_operator() specialization.
*/
template <size_t m>
BlockLinearOperator<Range, Domain> &
operator=(const std::array<BlockType, m> &ops)
{
*this = block_diagonal_operator<m, Range, Domain>(ops);
return *this;
}
/**
* Return the number of blocks in a column (i.e, the number of "block rows",
* or the number $m$, if interpreted as a $m\times n$ block system).
*/
std::function<unsigned int()> n_block_rows;
/**
* Return the number of blocks in a row (i.e, the number of "block columns",
* or the number $n$, if interpreted as a $m\times n$ block system).
*/
std::function<unsigned int()> n_block_cols;
/**
* Access the block with the given coordinates. This
* <code>std::function</code> object returns a LinearOperator representing
* the $(i,j)$-th block of the BlockLinearOperator.
*/
std::function<BlockType(unsigned int, unsigned int)> block;
};
namespace internal
{
namespace BlockLinearOperator
{
// Populate the LinearOperator interfaces with the help of the
// BlockLinearOperator functions
template <typename Range, typename Domain>
inline void
populate_linear_operator_functions(
dealii::BlockLinearOperator<Range, Domain> &op)
{
op.reinit_range_vector = [=](Range &v, bool omit_zeroing_entries)
{
const unsigned int m = op.n_block_rows();
// Reinitialize the block vector to m blocks:
v.reinit(m);
// And reinitialize every individual block with reinit_range_vectors:
for (unsigned int i = 0; i < m; ++i)
op.block(i, 0).reinit_range_vector(v.block(i), omit_zeroing_entries);
v.collect_sizes();
};
op.reinit_domain_vector = [=](Domain &v, bool omit_zeroing_entries)
{
const unsigned int n = op.n_block_cols();
// Reinitialize the block vector to n blocks:
v.reinit(n);
// And reinitialize every individual block with reinit_domain_vectors:
for (unsigned int i = 0; i < n; ++i)
op.block(0, i).reinit_domain_vector(v.block(i), omit_zeroing_entries);
v.collect_sizes();
};
op.vmult = [=](Range &v, const Domain &u)
{
const unsigned int m = op.n_block_rows();
const unsigned int n = op.n_block_cols();
Assert(v.n_blocks() == m, ExcDimensionMismatch(v.n_blocks(), m));
Assert(u.n_blocks() == n, ExcDimensionMismatch(u.n_blocks(), n));
for (unsigned int i = 0; i < m; ++i)
{
op.block(i, 0).vmult(v.block(i), u.block(0));
for (unsigned int j = 1; j < n; ++j)
op.block(i, j).vmult_add(v.block(i), u.block(j));
}
};
op.vmult_add = [=](Range &v, const Domain &u)
{
const unsigned int m = op.n_block_rows();
const unsigned int n = op.n_block_cols();
Assert(v.n_blocks() == m, ExcDimensionMismatch(v.n_blocks(), m));
Assert(u.n_blocks() == n, ExcDimensionMismatch(u.n_blocks(), n));
for (unsigned int i = 0; i < m; ++i)
for (unsigned int j = 0; j < n; ++j)
op.block(i, j).vmult_add(v.block(i), u.block(j));
};
op.Tvmult = [=](Domain &v, const Range &u)
{
const unsigned int n = op.n_block_cols();
const unsigned int m = op.n_block_rows();
Assert(v.n_blocks() == n, ExcDimensionMismatch(v.n_blocks(), n));
Assert(u.n_blocks() == m, ExcDimensionMismatch(u.n_blocks(), m));
for (unsigned int i = 0; i < n; ++i)
{
op.block(0, i).Tvmult(v.block(i), u.block(0));
for (unsigned int j = 1; j < m; ++j)
op.block(j, i).Tvmult_add(v.block(i), u.block(j));
}
};
op.Tvmult_add = [=](Domain &v, const Range &u)
{
const unsigned int n = op.n_block_cols();
const unsigned int m = op.n_block_rows();
Assert(v.n_blocks() == n, ExcDimensionMismatch(v.n_blocks(), n));
Assert(u.n_blocks() == m, ExcDimensionMismatch(u.n_blocks(), m));
for (unsigned int i = 0; i < n; ++i)
for (unsigned int j = 0; j < m; ++j)
op.block(j, i).Tvmult_add(v.block(i), u.block(j));
};
}
} /*namespace BlockLinearOperator*/
} /*namespace internal*/
/**
* @name Creation of a BlockLinearOperator
*/
//@{
/**
* @relates BlockLinearOperator
*
* A function that encapsulates a @p block_matrix into a BlockLinearOperator.
*
* All changes made on the block structure and individual blocks of @p
* block_matrix after the creation of the BlockLinearOperator object are
* reflected by the operator object.
*
* @ingroup LAOperators
*/
template <typename Range,
typename Domain,
typename BlockMatrixType>
BlockLinearOperator<Range, Domain>
block_operator(const BlockMatrixType &block_matrix)
{
typedef typename BlockLinearOperator<Range, Domain>::BlockType BlockType;
BlockLinearOperator<Range, Domain> return_op;
return_op.n_block_rows = [&block_matrix]() -> unsigned int
{
return block_matrix.n_block_rows();
};
return_op.n_block_cols = [&block_matrix]() -> unsigned int
{
return block_matrix.n_block_cols();
};
return_op.block = [&block_matrix](unsigned int i, unsigned int j) -> BlockType
{
#ifdef DEBUG
const unsigned int m = block_matrix.n_block_rows();
const unsigned int n = block_matrix.n_block_cols();
Assert(i < m, ExcIndexRange (i, 0, m));
Assert(j < n, ExcIndexRange (j, 0, n));
#endif
return BlockType(block_matrix.block(i, j));
};
internal::BlockLinearOperator::populate_linear_operator_functions(return_op);
return return_op;
}
/**
* @relates BlockLinearOperator
*
* A variant of above function that encapsulates a given collection @p ops of
* LinearOperators into a block structure. Here, it is assumed that Range and
* Domain are blockvectors, i.e., derived from
* @ref BlockVectorBase.
* The individual linear operators in @p ops must act on the underlying vector
* type of the block vectors, i.e., on Domain::BlockType yielding a result in
* Range::BlockType.
*
* The list @p ops is best passed as an initializer list. Consider for example
* a linear operator block (acting on Vector<double>)
* @code
* op_a00 | op_a01
* |
* ---------------
* |
* op_a10 | op_a11
* @endcode
* The corresponding block_operator invocation takes the form
* @code
* block_operator<2, 2, BlockVector<double>>({op_a00, op_a01, op_a10, op_a11});
* @endcode
*
* @ingroup LAOperators
*/
template <size_t m, size_t n, typename Range, typename Domain>
BlockLinearOperator<Range, Domain>
block_operator(const std::array<std::array<LinearOperator<typename Range::BlockType, typename Domain::BlockType>, n>, m> &ops)
{
static_assert(m > 0 && n > 0,
"a blocked LinearOperator must consist of at least one block");
typedef typename BlockLinearOperator<Range, Domain>::BlockType BlockType;
BlockLinearOperator<Range, Domain> return_op;
return_op.n_block_rows = []() -> unsigned int
{
return m;
};
return_op.n_block_cols = []() -> unsigned int
{
return n;
};
return_op.block = [ops](unsigned int i, unsigned int j) -> BlockType
{
Assert(i < m, ExcIndexRange (i, 0, m));
Assert(j < n, ExcIndexRange (j, 0, n));
return ops[i][j];
};
internal::BlockLinearOperator::populate_linear_operator_functions(return_op);
return return_op;
}
/**
* @relates BlockLinearOperator
*
* This function extracts the diagonal blocks of @p block_matrix (either a
* block matrix type or a BlockLinearOperator) and creates a
* BlockLinearOperator with the diagonal. Off-diagonal elements are
* initialized as null_operator (with correct reinit_range_vector and
* reinit_domain_vector methods).
*
* All changes made on the individual diagonal blocks of @p block_matrix after
* the creation of the BlockLinearOperator object are reflected by the
* operator object.
*
* @ingroup LAOperators
*/
template <typename Range,
typename Domain,
typename BlockMatrixType>
BlockLinearOperator<Range, Domain>
block_diagonal_operator(const BlockMatrixType &block_matrix)
{
typedef typename BlockLinearOperator<Range, Domain>::BlockType BlockType;
BlockLinearOperator<Range, Domain> return_op;
return_op.n_block_rows = [&block_matrix]() -> unsigned int
{
return block_matrix.n_block_rows();
};
return_op.n_block_cols = [&block_matrix]() -> unsigned int
{
return block_matrix.n_block_cols();
};
return_op.block = [&block_matrix](unsigned int i, unsigned int j) -> BlockType
{
#ifdef DEBUG
const unsigned int m = block_matrix.n_block_rows();
const unsigned int n = block_matrix.n_block_cols();
Assert(m == n, ExcDimensionMismatch(m, n));
Assert(i < m, ExcIndexRange (i, 0, m));
Assert(j < n, ExcIndexRange (j, 0, n));
#endif
if (i == j)
return BlockType(block_matrix.block(i, j));
else
return null_operator(BlockType(block_matrix.block(i, j)));
};
internal::BlockLinearOperator::populate_linear_operator_functions(return_op);
return return_op;
}
/**
* @relates BlockLinearOperator
*
* A variant of above function that builds up a block diagonal linear operator
* from an array @p ops of diagonal elements (off-diagonal blocks are assumed
* to be 0).
*
* The list @p ops is best passed as an initializer list. Consider for example
* a linear operator block (acting on Vector<double>) <code>diag(op_a0, op_a1,
* ..., op_am)</code>. The corresponding block_operator invocation takes the
* form
* @code
* block_diagonal_operator<m, BlockVector<double>>({op_00, op_a1, ..., op_am});
* @endcode
*
* @ingroup LAOperators
*/
template <size_t m, typename Range, typename Domain>
BlockLinearOperator<Range, Domain>
block_diagonal_operator(const std::array<LinearOperator<typename Range::BlockType, typename Domain::BlockType>, m> &ops)
{
static_assert(m > 0,
"a blockdiagonal LinearOperator must consist of at least one block");
typedef typename BlockLinearOperator<Range, Domain>::BlockType BlockType;
std::array<std::array<BlockType, m>, m> new_ops;
// This is a bit tricky. We have to make sure that the off-diagonal
// elements of return_op.ops are populated correctly. They must be
// null_operators, but with correct reinit_domain_vector and
// reinit_range_vector functions.
for (unsigned int i = 0; i < m; ++i)
for (unsigned int j = 0; j < m; ++j)
if (i == j)
{
// diagonal elements are easy:
new_ops[i][j] = ops[i];
}
else
{
// create a null-operator...
new_ops[i][j] = null_operator(ops[i]);
// ... and fix up reinit_domain_vector:
new_ops[i][j].reinit_domain_vector = ops[j].reinit_domain_vector;
}
return block_operator<m,m,Range,Domain>(new_ops);
}
/**
* @relates BlockLinearOperator
*
* A variant of above function that only takes a single LinearOperator
* argument @p op and creates a blockdiagonal linear operator with @p m copies
* of it.
*
* @ingroup LAOperators
*/
template <size_t m, typename Range, typename Domain>
BlockLinearOperator<Range, Domain>
block_diagonal_operator(const LinearOperator<typename Range::BlockType, typename Domain::BlockType> &op)
{
static_assert(m > 0,
"a blockdiagonal LinearOperator must consist of at least "
"one block");
typedef typename BlockLinearOperator<Range, Domain>::BlockType BlockType;
std::array<BlockType, m> new_ops;
new_ops.fill(op);
return block_diagonal_operator(new_ops);
}
//@}
/**
* @name Manipulation of a BlockLinearOperator
*/
//@{
/**
* @relates LinearOperator
* @relates BlockLinearOperator
*
* This function implements forward substitution to invert a lower block
* triangular matrix. As arguments, it takes a BlockLinearOperator @p
* block_operator representing a block lower triangular matrix, as well as a
* BlockLinearOperator @p diagonal_inverse representing inverses of diagonal
* blocks of @p block_operator.
*
* Let us assume we have a linear system with the following block structure:
*
* @code
* A00 x0 + ... = y0
* A01 x0 + A11 x1 + ... = y1
* ... ...
* A0n x0 + A1n x1 + ... + Ann xn = yn
* @endcode
*
* First of all, <code>x0 = A00^-1 y0</code>. Then, we can use x0 to recover
* x1:
* @code
* x1 = A11^-1 ( y1 - A01 x0 )
* @endcode
* and therefore:
* @code
* xn = Ann^-1 ( yn - A0n x0 - ... - A(n-1)n x(n-1) )
* @endcode
*
* @note We are not using all blocks of the BlockLinearOperator arguments:
* Just the lower triangular block matrix of @p block_operator is used as well
* as the diagonal of @p diagonal_inverse.
*
* @ingroup LAOperators
*/
template <typename Range, typename Domain>
LinearOperator<Domain, Range>
block_forward_substitution(const BlockLinearOperator<Range, Domain> &block_operator,
const BlockLinearOperator<Domain, Range> &diagonal_inverse)
{
LinearOperator<Range, Range> return_op;
return_op.reinit_range_vector = diagonal_inverse.reinit_range_vector;
return_op.reinit_domain_vector = diagonal_inverse.reinit_domain_vector;
return_op.vmult = [block_operator, diagonal_inverse](Range &v, const Range &u)
{
const unsigned int m = block_operator.n_block_rows();
Assert(block_operator.n_block_cols() == m,
ExcDimensionMismatch(block_operator.n_block_cols(), m));
Assert(diagonal_inverse.n_block_rows() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_rows(), m));
Assert(diagonal_inverse.n_block_cols() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_cols(), m));
Assert(v.n_blocks() == m, ExcDimensionMismatch(v.n_blocks(), m));
Assert(u.n_blocks() == m, ExcDimensionMismatch(u.n_blocks(), m));
if (m == 0)
return;
diagonal_inverse.block(0, 0).vmult(v.block(0), u.block(0));
for (unsigned int i = 1; i < m; ++i)
{
auto &dst = v.block(i);
dst = u.block(i);
dst *= -1.;
for (unsigned int j = 0; j < i; ++j)
block_operator.block(i, j).vmult_add(dst, v.block(j));
dst *= -1.;
diagonal_inverse.block(i, i).vmult(dst, dst); // uses intermediate storage
}
};
return_op.vmult_add = [block_operator, diagonal_inverse](Range &v, const Range &u)
{
const unsigned int m = block_operator.n_block_rows();
Assert(block_operator.n_block_cols() == m,
ExcDimensionMismatch(block_operator.n_block_cols(), m));
Assert(diagonal_inverse.n_block_rows() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_rows(), m));
Assert(diagonal_inverse.n_block_cols() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_cols(), m));
Assert(v.n_blocks() == m, ExcDimensionMismatch(v.n_blocks(), m));
Assert(u.n_blocks() == m, ExcDimensionMismatch(u.n_blocks(), m));
if (m == 0)
return;
static GrowingVectorMemory<typename Range::BlockType> vector_memory;
typename Range::BlockType *tmp = vector_memory.alloc();
diagonal_inverse.block(0, 0).vmult_add(v.block(0), u.block(0));
for (unsigned int i = 1; i < m; ++i)
{
diagonal_inverse.block(i, i).reinit_range_vector(*tmp, /*bool omit_zeroing_entries=*/ true);
*tmp = u.block(i);
*tmp *= -1.;
for (unsigned int j = 0; j < i; ++j)
block_operator.block(i, j).vmult_add(*tmp, v.block(j));
*tmp *= -1.;
diagonal_inverse.block(i, i).vmult_add(v.block(i),*tmp);
}
vector_memory.free(tmp);
};
return return_op;
}
/**
* @relates LinearOperator
* @relates BlockLinearOperator
*
* This function implements back substitution to invert an upper block
* triangular matrix. As arguments, it takes a BlockLinearOperator @p
* block_operator representing an upper block triangular matrix, as well as a
* BlockLinearOperator @p diagonal_inverse representing inverses of diagonal
* blocks of @p block_operator.
*
* Let us assume we have a linear system with the following block structure:
*
* @code
* A00 x0 + A01 x1 + ... + A0n xn = yn
* A11 x1 + ... = y1
* ... ..
* Ann xn = yn
* @endcode
*
* First of all, <code>xn = Ann^-1 yn</code>. Then, we can use xn to recover
* x(n-1):
* @code
* x(n-1) = A(n-1)(n-1)^-1 ( y(n-1) - A(n-1)n x(n-1) )
* @endcode
* and therefore:
* @code
* x0 = A00^-1 ( y0 - A0n xn - ... - A01 x1 )
* @endcode
*
* @note We are not using all blocks of the BlockLinearOperator arguments:
* Just the upper triangular block matrix of @p block_operator is used as well
* as the diagonal of @p diagonal_inverse.
*
* @ingroup LAOperators
*/
template <typename Range, typename Domain>
LinearOperator<Domain, Range>
block_back_substitution(const BlockLinearOperator<Range, Domain> &block_operator,
const BlockLinearOperator<Domain, Range> &diagonal_inverse)
{
LinearOperator<Range, Range> return_op;
return_op.reinit_range_vector = diagonal_inverse.reinit_range_vector;
return_op.reinit_domain_vector = diagonal_inverse.reinit_domain_vector;
return_op.vmult = [block_operator, diagonal_inverse](Range &v, const Range &u)
{
const unsigned int m = block_operator.n_block_rows();
Assert(block_operator.n_block_cols() == m,
ExcDimensionMismatch(block_operator.n_block_cols(), m));
Assert(diagonal_inverse.n_block_rows() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_rows(), m));
Assert(diagonal_inverse.n_block_cols() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_cols(), m));
Assert(v.n_blocks() == m, ExcDimensionMismatch(v.n_blocks(), m));
Assert(u.n_blocks() == m, ExcDimensionMismatch(u.n_blocks(), m));
if (m == 0)
return;
diagonal_inverse.block(m-1, m-1).vmult(v.block(m-1),u.block(m-1));
for (int i = m - 2; i >= 0; --i)
{
auto &dst = v.block(i);
dst = u.block(i);
dst *= -1.;
for (unsigned int j = i + 1; j < m; ++j)
block_operator.block(i, j).vmult_add(dst, v.block(j));
dst *= -1.;
diagonal_inverse.block(i, i).vmult(dst, dst); // uses intermediate storage
}
};
return_op.vmult_add = [block_operator, diagonal_inverse](Range &v, const Range &u)
{
const unsigned int m = block_operator.n_block_rows();
Assert(block_operator.n_block_cols() == m,
ExcDimensionMismatch(block_operator.n_block_cols(), m));
Assert(diagonal_inverse.n_block_rows() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_rows(), m));
Assert(diagonal_inverse.n_block_cols() == m,
ExcDimensionMismatch(diagonal_inverse.n_block_cols(), m));
Assert(v.n_blocks() == m, ExcDimensionMismatch(v.n_blocks(), m));
Assert(u.n_blocks() == m, ExcDimensionMismatch(u.n_blocks(), m));
static GrowingVectorMemory<typename Range::BlockType> vector_memory;
typename Range::BlockType *tmp = vector_memory.alloc();
if (m == 0)
return;
diagonal_inverse.block(m-1, m-1).vmult_add(v.block(m-1),u.block(m-1));
for (int i = m - 2; i >= 0; --i)
{
diagonal_inverse.block(i, i).reinit_range_vector(*tmp, /*bool omit_zeroing_entries=*/ true);
*tmp = u.block(i);
*tmp *= -1.;
for (unsigned int j = i + 1; j < m; ++j)
block_operator.block(i, j).vmult_add(*tmp,v.block(j));
*tmp *= -1.;
diagonal_inverse.block(i, i).vmult_add(v.block(i),*tmp);
}
vector_memory.free(tmp);
};
return return_op;
}
//@}
DEAL_II_NAMESPACE_CLOSE
#endif // DEAL_II_WITH_CXX11
#endif
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