/usr/include/deal.II/lac/sparse_decomposition.templates.h is in libdeal.ii-dev 8.4.2-2+b1.
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//
// Copyright (C) 2002 - 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__sparse_decomposition_templates_h
#define dealii__sparse_decomposition_templates_h
#include <deal.II/base/memory_consumption.h>
#include <deal.II/base/template_constraints.h>
#include <deal.II/base/utilities.h>
#include <deal.II/lac/sparse_decomposition.h>
#include <algorithm>
#include <cstring>
DEAL_II_NAMESPACE_OPEN
template<typename number>
SparseLUDecomposition<number>::SparseLUDecomposition()
:
SparseMatrix<number>(),
own_sparsity(0)
{}
template<typename number>
SparseLUDecomposition<number>::~SparseLUDecomposition()
{
clear();
}
template<typename number>
void SparseLUDecomposition<number>::clear()
{
std::vector<const size_type *> tmp;
tmp.swap (prebuilt_lower_bound);
SparseMatrix<number>::clear();
if (own_sparsity)
{
delete own_sparsity;
own_sparsity=0;
}
}
template<typename number>
template <typename somenumber>
void SparseLUDecomposition<number>::initialize (
const SparseMatrix<somenumber> &matrix,
const AdditionalData data)
{
const SparsityPattern &matrix_sparsity=matrix.get_sparsity_pattern();
const SparsityPattern *sparsity_pattern_to_use = 0;
if (data.use_this_sparsity)
sparsity_pattern_to_use = data.use_this_sparsity;
else if (data.use_previous_sparsity &&
!this->empty() &&
(this->m()==matrix.m()))
{
// Use the sparsity that was
// previously used. This is
// particularly useful when
// matrix entries change but
// not the sparsity, as for the
// case of several Newton
// iteration steps on an
// unchanged grid.
sparsity_pattern_to_use = &this->get_sparsity_pattern();
}
else if (data.extra_off_diagonals==0)
{
// Use same sparsity as matrix
sparsity_pattern_to_use = &matrix_sparsity;
}
else
{
// Create new sparsity
// for the case that
// own_sparsity wasn't deleted
// before (e.g. by clear()), do
// it here
if (own_sparsity)
{
// release the sparsity
SparseMatrix<number>::clear();
// delete it
delete own_sparsity;
}
// and recreate
own_sparsity = new SparsityPattern(matrix_sparsity,
matrix_sparsity.max_entries_per_row()
+2*data.extra_off_diagonals,
data.extra_off_diagonals);
own_sparsity->compress();
sparsity_pattern_to_use = own_sparsity;
}
// now use this sparsity pattern
Assert (sparsity_pattern_to_use->n_rows()==sparsity_pattern_to_use->n_cols(),
typename SparsityPattern::ExcDiagonalNotOptimized());
{
std::vector<const size_type *> tmp;
tmp.swap (prebuilt_lower_bound);
}
SparseMatrix<number>::reinit (*sparsity_pattern_to_use);
}
template<typename number>
void
SparseLUDecomposition<number>::prebuild_lower_bound()
{
const size_type *const
column_numbers = this->get_sparsity_pattern().colnums;
const std::size_t *const
rowstart_indices = this->get_sparsity_pattern().rowstart;
const size_type N = this->m();
prebuilt_lower_bound.resize (N);
for (size_type row=0; row<N; row++)
{
prebuilt_lower_bound[row]
= Utilities::lower_bound (&column_numbers[rowstart_indices[row]+1],
&column_numbers[rowstart_indices[row+1]],
row);
}
}
template <typename number>
template <typename somenumber>
void
SparseLUDecomposition<number>::copy_from (const SparseMatrix<somenumber> &matrix)
{
// check whether we use the same sparsity
// pattern as the input matrix
if (&this->get_sparsity_pattern() == &matrix.get_sparsity_pattern())
{
const somenumber *input_ptr = matrix.val;
number *this_ptr = this->val;
const number *const end_ptr = this_ptr + this->n_nonzero_elements();
if (types_are_equal<somenumber, number>::value == true)
std::memcpy (this_ptr, input_ptr, this->n_nonzero_elements()*sizeof(number));
else
for ( ; this_ptr != end_ptr; ++input_ptr, ++this_ptr)
*this_ptr = *input_ptr;
return;
}
// preset the elements by zero. this needs to be written in a slightly
// awkward way so that we find the corresponding function in the base class.
SparseMatrix<number>::operator= (number(0));
// both allow more and less entries in the new matrix
for (size_type row=0; row<this->m(); ++row)
{
typename SparseMatrix<number>::iterator index = this->begin(row);
typename SparseMatrix<somenumber>::const_iterator
in_index = matrix.begin(row);
index->value() = in_index->value();
++index, ++in_index;
while (index < this->end(row) && in_index < matrix.end(row))
{
while (index->column() < in_index->column() && index < this->end(row))
++index;
while (in_index->column() < index->column() && in_index < matrix.end(row))
++in_index;
index->value() = in_index->value();
++index, ++in_index;
}
}
}
template <typename number>
void
SparseLUDecomposition<number>::strengthen_diagonal_impl ()
{
for (size_type row=0; row<this->m(); ++row)
{
// get the global index of the first
// non-diagonal element in this row
Assert (this->m() == this->n(), ExcNotImplemented());
typename SparseMatrix<number>::iterator
diagonal_element = this->begin(row);
number rowsum = 0;
for (typename SparseMatrix<number>::iterator
p = diagonal_element + 1;
p != this->end(row); ++p)
rowsum += std::fabs(p->value());
diagonal_element->value() += this->get_strengthen_diagonal (rowsum, row) *
rowsum;
}
}
template <typename number>
std::size_t
SparseLUDecomposition<number>::memory_consumption () const
{
return (SparseMatrix<number>::memory_consumption () +
MemoryConsumption::memory_consumption(prebuilt_lower_bound));
}
DEAL_II_NAMESPACE_CLOSE
#endif // dealii__sparse_decomposition_templates_h
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