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// $Id: compressed_simple_sparsity_pattern.h 30036 2013-07-18 16:55:32Z maier $
//
// Copyright (C) 2001 - 2013 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 __deal2__compressed_simple_sparsity_pattern_h
#define __deal2__compressed_simple_sparsity_pattern_h
#include <deal.II/base/config.h>
#include <deal.II/base/subscriptor.h>
#include <deal.II/base/utilities.h>
#include <deal.II/lac/exceptions.h>
#include <deal.II/base/index_set.h>
#include <vector>
#include <algorithm>
#include <iostream>
DEAL_II_NAMESPACE_OPEN
template <typename number> class SparseMatrix;
/*! @addtogroup Sparsity
*@{
*/
/**
* This class acts as an intermediate form of the
* SparsityPattern class. From the interface it mostly
* represents a SparsityPattern object that is kept compressed
* at all times. However, since the final sparsity pattern is not
* known while constructing it, keeping the pattern compressed at all
* times can only be achieved at the expense of either increased
* memory or run time consumption upon use. The main purpose of this
* class is to avoid some memory bottlenecks, so we chose to implement
* it memory conservative. The chosen data format is too unsuited
* to be used for actual matrices, though. It is therefore necessary to first
* copy the data of this object over to an object of type
* SparsityPattern before using it in actual matrices.
*
* Another viewpoint is that this class does not need up front allocation of a
* certain amount of memory, but grows as necessary. An extensive description
* of sparsity patterns can be found in the documentation of the @ref Sparsity
* module.
*
* This class is an example of the "dynamic" type of @ref Sparsity.
*
* <h3>Interface</h3>
*
* Since this class is intended as an intermediate replacement of the
* SparsityPattern class, it has mostly the same interface, with
* small changes where necessary. In particular, the add()
* function, and the functions inquiring properties of the sparsity
* pattern are the same.
*
*
* <h3>Usage</h3>
*
* Use this class as follows:
* @code
* CompressedSimpleSparsityPattern compressed_pattern (dof_handler.n_dofs());
* DoFTools::make_sparsity_pattern (dof_handler,
* compressed_pattern);
* constraints.condense (compressed_pattern);
*
* SparsityPattern sp;
* sp.copy_from (compressed_pattern);
* @endcode
*
*
* <h3>Notes</h3>
*
* There are several, exchangeable variations of this class, see @ref Sparsity,
* section '"Dynamic" or "compressed" sparsity patterns' for more information.
*
* @author Timo Heister, 2008
*/
class CompressedSimpleSparsityPattern : public Subscriptor
{
public:
/**
* Declare the type for container size.
*/
typedef types::global_dof_index size_type;
/**
* An iterator that can be used to
* iterate over the elements of a single
* row. The result of dereferencing such
* an iterator is a column index.
*/
typedef std::vector<size_type>::const_iterator row_iterator;
/**
* Initialize the matrix empty,
* that is with no memory
* allocated. This is useful if
* you want such objects as
* member variables in other
* classes. You can make the
* structure usable by calling
* the reinit() function.
*/
CompressedSimpleSparsityPattern ();
/**
* Copy constructor. This constructor is
* only allowed to be called if the
* matrix structure to be copied is
* empty. This is so in order to prevent
* involuntary copies of objects for
* temporaries, which can use large
* amounts of computing time. However,
* copy constructors are needed if you
* want to use the STL data types on
* classes like this, e.g. to write such
* statements like <tt>v.push_back
* (CompressedSparsityPattern());</tt>,
* with @p v a vector of @p
* CompressedSparsityPattern objects.
*/
CompressedSimpleSparsityPattern (const CompressedSimpleSparsityPattern &);
/**
* Initialize a rectangular
* matrix with @p m rows and
* @p n columns. The @p rowset
* restricts the storage to
* elements in rows of this set.
* Adding elements outside of
* this set has no effect. The
* default argument keeps all
* entries.
*/
CompressedSimpleSparsityPattern (const size_type m,
const size_type n,
const IndexSet &rowset = IndexSet());
/**
* Create a square SparsityPattern using
* the index set.
*/
CompressedSimpleSparsityPattern (const IndexSet &indexset);
/**
* Initialize a square matrix of
* dimension @p n.
*/
CompressedSimpleSparsityPattern (const size_type n);
/**
* Copy operator. For this the
* same holds as for the copy
* constructor: it is declared,
* defined and fine to be called,
* but the latter only for empty
* objects.
*/
CompressedSimpleSparsityPattern &operator = (const CompressedSimpleSparsityPattern &);
/**
* Reallocate memory and set up
* data structures for a new
* matrix with @p m rows and
* @p n columns, with at most
* max_entries_per_row() nonzero
* entries per row. The @p rowset
* restricts the storage to
* elements in rows of this set.
* Adding elements outside of
* this set has no effect. The
* default argument keeps all
* entries.
*/
void reinit (const size_type m,
const size_type n,
const IndexSet &rowset = IndexSet());
/**
* Since this object is kept
* compressed at all times anway,
* this function does nothing,
* but is declared to make the
* interface of this class as
* much alike as that of the
* SparsityPattern class.
*/
void compress ();
/**
* Return whether the object is
* empty. It is empty if no
* memory is allocated, which is
* the same as that both
* dimensions are zero.
*/
bool empty () const;
/**
* Return the maximum number of
* entries per row. Note that
* this number may change as
* entries are added.
*/
size_type max_entries_per_row () const;
/**
* Add a nonzero entry to the
* matrix. If the entry already
* exists, nothing bad happens.
*/
void add (const size_type i,
const size_type j);
/**
* Add several nonzero entries to the
* specified row of the matrix. If the
* entries already exist, nothing bad
* happens.
*/
template <typename ForwardIterator>
void add_entries (const size_type row,
ForwardIterator begin,
ForwardIterator end,
const bool indices_are_unique_and_sorted = false);
/**
* Check if a value at a certain
* position may be non-zero.
*/
bool exists (const size_type i,
const size_type j) const;
/**
* Make the sparsity pattern
* symmetric by adding the
* sparsity pattern of the
* transpose object.
*
* This function throws an
* exception if the sparsity
* pattern does not represent a
* square matrix.
*/
void symmetrize ();
/**
* Print the sparsity of the
* matrix. The output consists of
* one line per row of the format
* <tt>[i,j1,j2,j3,...]</tt>. <i>i</i>
* is the row number and
* <i>jn</i> are the allocated
* columns in this row.
*/
void print (std::ostream &out) const;
/**
* Print the sparsity of the matrix in a
* format that @p gnuplot understands and
* which can be used to plot the sparsity
* pattern in a graphical way. The format
* consists of pairs <tt>i j</tt> of
* nonzero elements, each representing
* one entry of this matrix, one per line
* of the output file. Indices are
* counted from zero on, as usual. Since
* sparsity patterns are printed in the
* same way as matrices are displayed, we
* print the negative of the column
* index, which means that the
* <tt>(0,0)</tt> element is in the top
* left rather than in the bottom left
* corner.
*
* Print the sparsity pattern in
* gnuplot by setting the data style
* to dots or points and use the
* @p plot command.
*/
void print_gnuplot (std::ostream &out) const;
/**
* Return number of rows of this
* matrix, which equals the dimension
* of the image space.
*/
size_type n_rows () const;
/**
* Return number of columns of this
* matrix, which equals the dimension
* of the range space.
*/
size_type n_cols () const;
/**
* Number of entries in a
* specific row. This function
* can only be called if the
* given row is a member of the
* index set of rows that we want
* to store.
*/
size_type row_length (const size_type row) const;
/**
* Access to column number field.
* Return the column number of
* the @p indexth entry in @p row.
*/
size_type column_number (const size_type row,
const size_type index) const;
/**
* Return an iterator that can loop over
* all entries in the given
* row. Dereferencing the iterator yields
* a column index.
*/
row_iterator row_begin (const size_type row) const;
/**
* Returns the end of the current row.
*/
row_iterator row_end (const size_type row) const;
/**
* Compute the bandwidth of the matrix
* represented by this structure. The
* bandwidth is the maximum of
* $|i-j|$ for which the index pair
* $(i,j)$ represents a nonzero entry
* of the matrix.
*/
size_type bandwidth () const;
/**
* Return the number of nonzero elements
* allocated through this sparsity pattern.
*/
size_type n_nonzero_elements () const;
/**
* Return the IndexSet that sets which
* rows are active on the current
* processor. It corresponds to the
* IndexSet given to this class in the
* constructor or in the reinit function.
*/
const IndexSet &row_index_set () const;
/**
* return whether this object stores only
* those entries that have been added
* explicitly, or if the sparsity pattern
* contains elements that have been added
* through other means (implicitly) while
* building it. For the current class,
* the result is always true.
*
* This function mainly serves the
* purpose of describing the current
* class in cases where several kinds of
* sparsity patterns can be passed as
* template arguments.
*/
static
bool stores_only_added_elements ();
/**
* Determine an estimate for the
* memory consumption (in bytes)
* of this object.
*/
size_type memory_consumption () const;
private:
/**
* Number of rows that this sparsity
* structure shall represent.
*/
size_type rows;
/**
* Number of columns that this sparsity
* structure shall represent.
*/
size_type cols;
/**
* A set that contains the valid rows.
*/
IndexSet rowset;
/**
* Store some data for each row
* describing which entries of this row
* are nonzero. Data is stored sorted in
* the @p entries std::vector.
* The vector per row is dynamically
* growing upon insertion doubling its
* memory each time.
*/
struct Line
{
public:
/**
* Storage for the column indices of
* this row. This array is always
* kept sorted.
*/
std::vector<size_type> entries;
/**
* Constructor.
*/
Line ();
/**
* Add the given column number to
* this line.
*/
void add (const size_type col_num);
/**
* Add the columns specified by the
* iterator range to this line.
*/
template <typename ForwardIterator>
void add_entries (ForwardIterator begin,
ForwardIterator end,
const bool indices_are_sorted);
/**
* estimates memory consumption.
*/
size_type memory_consumption () const;
};
/**
* Actual data: store for each
* row the set of nonzero
* entries.
*/
std::vector<Line> lines;
};
/*@}*/
/*---------------------- Inline functions -----------------------------------*/
inline
void
CompressedSimpleSparsityPattern::Line::add (const size_type j)
{
// first check the last element (or if line
// is still empty)
if ( (entries.size()==0) || ( entries.back() < j) )
{
entries.push_back(j);
return;
}
// do a binary search to find the place
// where to insert:
std::vector<size_type>::iterator
it = Utilities::lower_bound(entries.begin(),
entries.end(),
j);
// If this entry is a duplicate, exit
// immediately
if (*it == j)
return;
// Insert at the right place in the
// vector. Vector grows automatically to
// fit elements. Always doubles its size.
entries.insert(it, j);
}
inline
CompressedSimpleSparsityPattern::size_type
CompressedSimpleSparsityPattern::n_rows () const
{
return rows;
}
inline
types::global_dof_index
CompressedSimpleSparsityPattern::n_cols () const
{
return cols;
}
inline
void
CompressedSimpleSparsityPattern::add (const size_type i,
const size_type j)
{
Assert (i<rows, ExcIndexRangeType<size_type>(i, 0, rows));
Assert (j<cols, ExcIndexRangeType<size_type>(j, 0, cols));
if (rowset.size() > 0 && !rowset.is_element(i))
return;
const size_type rowindex =
rowset.size()==0 ? i : rowset.index_within_set(i);
lines[rowindex].add (j);
}
template <typename ForwardIterator>
inline
void
CompressedSimpleSparsityPattern::add_entries (const size_type row,
ForwardIterator begin,
ForwardIterator end,
const bool indices_are_sorted)
{
Assert (row < rows, ExcIndexRangeType<size_type> (row, 0, rows));
if (rowset.size() > 0 && !rowset.is_element(row))
return;
const size_type rowindex =
rowset.size()==0 ? row : rowset.index_within_set(row);
lines[rowindex].add_entries (begin, end, indices_are_sorted);
}
inline
CompressedSimpleSparsityPattern::Line::Line ()
{}
inline
types::global_dof_index
CompressedSimpleSparsityPattern::row_length (const size_type row) const
{
Assert (row < n_rows(), ExcIndexRangeType<size_type> (row, 0, n_rows()));
if (rowset.size() > 0 && !rowset.is_element(row))
return 0;
const size_type rowindex =
rowset.size()==0 ? row : rowset.index_within_set(row);
return lines[rowindex].entries.size();
}
inline
types::global_dof_index
CompressedSimpleSparsityPattern::column_number (const size_type row,
const size_type index) const
{
Assert (row < n_rows(), ExcIndexRangeType<size_type> (row, 0, n_rows()));
Assert( rowset.size() == 0 || rowset.is_element(row), ExcInternalError());
const size_type local_row = rowset.size() ? rowset.index_within_set(row) : row;
Assert (index < lines[local_row].entries.size(),
ExcIndexRangeType<size_type> (index, 0, lines[local_row].entries.size()));
return lines[local_row].entries[index];
}
inline
CompressedSimpleSparsityPattern::row_iterator
CompressedSimpleSparsityPattern::row_begin (const size_type row) const
{
Assert (row < n_rows(), ExcIndexRangeType<size_type> (row, 0, n_rows()));
const size_type local_row = rowset.size() ? rowset.index_within_set(row) : row;
return lines[local_row].entries.begin();
}
inline
CompressedSimpleSparsityPattern::row_iterator
CompressedSimpleSparsityPattern::row_end (const size_type row) const
{
Assert (row < n_rows(), ExcIndexRangeType<size_type> (row, 0, n_rows()));
const size_type local_row = rowset.size() ? rowset.index_within_set(row) : row;
return lines[local_row].entries.end();
}
inline
const IndexSet &
CompressedSimpleSparsityPattern::row_index_set () const
{
return rowset;
}
inline
bool
CompressedSimpleSparsityPattern::stores_only_added_elements ()
{
return true;
}
DEAL_II_NAMESPACE_CLOSE
#endif
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