SparseMatrixEZ< number > Class Template Reference
[Basic matrices]

Inheritance diagram for SparseMatrixEZ< number >:
Inheritance graph
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List of all members.

Classes

class  const_iterator
struct  Entry
class  ExcEntryAllocationFailure
class  ExcInvalidEntry
class  ExcNoDiagonal
struct  RowInfo

Public Types

typedef number value_type

Public Member Functions

 SparseMatrixEZ ()
 SparseMatrixEZ (const SparseMatrixEZ &)
 SparseMatrixEZ (const unsigned int n_rows, const unsigned int n_columns, const unsigned int default_row_length=0, const unsigned int default_increment=1)
 ~SparseMatrixEZ ()
SparseMatrixEZ< number > & operator= (const SparseMatrixEZ< number > &)
SparseMatrixEZ< number > & operator= (const double d)
void reinit (const unsigned int n_rows, const unsigned int n_columns, unsigned int default_row_length=0, unsigned int default_increment=1, unsigned int reserve=0)
void clear ()
bool empty () const
unsigned int m () const
unsigned int n () const
void set (const unsigned int i, const unsigned int j, const number value)
void add (const unsigned int i, const unsigned int j, const number value)
template<typename number2 >
void add (const std::vector< unsigned int > &indices, const FullMatrix< number2 > &full_matrix, const bool elide_zero_values=true)
template<typename number2 >
void add (const std::vector< unsigned int > &row_indices, const std::vector< unsigned int > &col_indices, const FullMatrix< number2 > &full_matrix, const bool elide_zero_values=true)
template<typename number2 >
void add (const unsigned int row, const std::vector< unsigned int > &col_indices, const std::vector< number2 > &values, const bool elide_zero_values=true)
template<typename number2 >
void add (const unsigned int row, const unsigned int n_cols, const unsigned int *col_indices, const number2 *values, const bool elide_zero_values=true, const bool col_indices_are_sorted=false)
template<class MATRIX >
SparseMatrixEZ< number > & copy_from (const MATRIX &source)
template<class MATRIX >
void add (const number factor, const MATRIX &matrix)
number operator() (const unsigned int i, const unsigned int j) const
number el (const unsigned int i, const unsigned int j) const
template<typename somenumber >
void vmult (Vector< somenumber > &dst, const Vector< somenumber > &src) const
template<typename somenumber >
void Tvmult (Vector< somenumber > &dst, const Vector< somenumber > &src) const
template<typename somenumber >
void vmult_add (Vector< somenumber > &dst, const Vector< somenumber > &src) const
template<typename somenumber >
void Tvmult_add (Vector< somenumber > &dst, const Vector< somenumber > &src) const
number l2_norm () const
template<typename somenumber >
void precondition_Jacobi (Vector< somenumber > &dst, const Vector< somenumber > &src, const number omega=1.) const
template<typename somenumber >
void precondition_SSOR (Vector< somenumber > &dst, const Vector< somenumber > &src, const number om=1., const std::vector< unsigned int > &pos_right_of_diagonal=std::vector< unsigned int >()) const
template<typename somenumber >
void precondition_SOR (Vector< somenumber > &dst, const Vector< somenumber > &src, const number om=1.) const
template<typename somenumber >
void precondition_TSOR (Vector< somenumber > &dst, const Vector< somenumber > &src, const number om=1.) const
template<class MATRIXA , class MATRIXB >
void conjugate_add (const MATRIXA &A, const MATRIXB &B, const bool transpose=false)
const_iterator begin () const
const_iterator end () const
const_iterator begin (const unsigned int r) const
const_iterator end (const unsigned int r) const
void print (std::ostream &out) const
void print_formatted (std::ostream &out, const unsigned int precision=3, const bool scientific=true, const unsigned int width=0, const char *zero_string=" ", const double denominator=1.) const
void block_write (std::ostream &out) const
void block_read (std::istream &in)
unsigned int memory_consumption () const
template<class STREAM >
void print_statistics (STREAM &s, bool full=false)
void compute_statistics (unsigned int &used, unsigned int &allocated, unsigned int &reserved, std::vector< unsigned int > &used_by_line, const bool compute_by_line) const

Private Member Functions

const Entrylocate (const unsigned int row, const unsigned int col) const
Entrylocate (const unsigned int row, const unsigned int col)
Entryallocate (const unsigned int row, const unsigned int col)
template<typename somenumber >
void threaded_vmult (Vector< somenumber > &dst, const Vector< somenumber > &src, const unsigned int begin_row, const unsigned int end_row) const
template<typename somenumber >
void threaded_matrix_norm_square (const Vector< somenumber > &v, const unsigned int begin_row, const unsigned int end_row, somenumber *partial_sum) const
template<typename somenumber >
void threaded_matrix_scalar_product (const Vector< somenumber > &u, const Vector< somenumber > &v, const unsigned int begin_row, const unsigned int end_row, somenumber *partial_sum) const

Private Attributes

unsigned int n_columns
std::vector< RowInforow_info
std::vector< Entrydata
unsigned int increment

Detailed Description

template<typename number>
class SparseMatrixEZ< number >

Sparse matrix without sparsity pattern.

Instead of using a pre-assembled sparsity pattern, this matrix builds the pattern on the fly. Filling the matrix may consume more time as with SparseMatrix, since large memory movements may be involved. To help optimizing things, an expected row-length may be provided to the constructor, as well as an increment size for rows.

The storage structure: like with the usual sparse matrix, it is attempted to store only non-zero elements. these are stored in a single data array data. They are ordered by row and inside each row by column number. Each row is described by its starting point in the data array and its length. These are stored in the row_info array, together with additional useful information.

Due to the structure, gaps may occur between rows. Whenever a new entry must be created, an attempt is made to use the gap in its row. If the gap is full, the row must be extended and all subsequent rows must be shifted backwards. This is a very expensive operation and should be avoided as much as possible.

This is, where the optimization parameters, provided to the constructor or to the function reinit come in. default_row_length is the amount of entries that will be allocated for each row on initialization (the actual length of the rows is still zero). This means, that default_row_length entries can be added to this row without shifting other rows. If less entries are added, the additional memory will be wasted.

If the space for a row is not sufficient, then it is enlarged by default_increment entries. This way, the subsequent rows are not shifted by single entries very often.

Finally, the default_reserve allocates extra space at the end of the data array. This space is used whenever a row must be enlarged. Since std::vector doubles the capacity everytime it must increase it, this value should allow for all the growth needed.

Suggested settings: default_row_length should be the length of a typical row, for instance the size of the stencil in regular parts of the grid. Then, default_increment may be the expected amount of entries added to the row by having one hanging node. This way, a good compromise between memory consumption and speed should be achieved. default_reserve should then be an estimate for the number of hanging nodes times default_increment.

Letting default_increment zero causes an exception whenever a row overflows.

If the rows are expected to be filled more or less from first to last, using a default_row_length of zero may not be such a bad idea.

The name of this matrix is in reverence to a publication of the Internal Revenue Service of the United States of America. I hope some other aliens will appreciate it. By the way, the suffix makes sense by pronouncing it the American way.

Author:
Guido Kanschat, 2002

Member Typedef Documentation

template<typename number>
typedef number SparseMatrixEZ< number >::value_type

Type of matrix entries. In analogy to the STL container classes.


Constructor & Destructor Documentation

template<typename number>
SparseMatrixEZ< number >::SparseMatrixEZ (  ) 

Constructor. Initializes an empty matrix of dimension zero times zero.

template<typename number>
SparseMatrixEZ< number >::SparseMatrixEZ ( const SparseMatrixEZ< number > &   ) 

Dummy copy constructor. This is here for use in containers. It may only be called for empty objects.

If you really want to copy a whole matrix, you can do so by using the copy_from function.

template<typename number>
SparseMatrixEZ< number >::SparseMatrixEZ ( const unsigned int  n_rows,
const unsigned int  n_columns,
const unsigned int  default_row_length = 0,
const unsigned int  default_increment = 1 
) [explicit]

Constructor. Generates a matrix of the given size, ready to be filled. The optional parameters default_row_length and default_increment allow for preallocating memory. Providing these properly is essential for an efficient assembling of the matrix.

template<typename number>
SparseMatrixEZ< number >::~SparseMatrixEZ (  ) 

Destructor. Free all memory, but do not release the memory of the sparsity structure.


Member Function Documentation

template<typename number>
SparseMatrixEZ<number>& SparseMatrixEZ< number >::operator= ( const SparseMatrixEZ< number > &   ) 

Pseudo operator only copying empty objects.

Reimplemented from Subscriptor.

template<typename number>
SparseMatrixEZ<number>& SparseMatrixEZ< number >::operator= ( const double  d  ) 

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 matrix=0, which sets all elements of the matrix to zero, but keep the sparsity pattern previously used.

template<typename number>
void SparseMatrixEZ< number >::reinit ( const unsigned int  n_rows,
const unsigned int  n_columns,
unsigned int  default_row_length = 0,
unsigned int  default_increment = 1,
unsigned int  reserve = 0 
)

Reinitialize the sparse matrix to the dimensions provided. The matrix will have no entries at this point. The optional parameters default_row_length, default_increment and reserve allow for preallocating memory. Providing these properly is essential for an efficient assembling of the matrix.

Referenced by SparseMatrixEZ< number >::copy_from().

template<typename number>
void SparseMatrixEZ< number >::clear (  ) 

Release all memory and return to a state just like after having called the default constructor. It also forgets its sparsity pattern.

template<typename number>
bool SparseMatrixEZ< number >::empty (  )  const

Return whether the object is empty. It is empty if both dimensions are zero.

template<typename number >
unsigned int SparseMatrixEZ< number >::m (  )  const [inline]
template<typename number >
unsigned int SparseMatrixEZ< number >::n (  )  const [inline]

Return the dimension of the range space. To remember: the matrix is of dimension $m \times n$.

References SparseMatrixEZ< number >::n_columns.

Referenced by SparseMatrixEZ< number >::add(), SparseMatrixEZ< number >::allocate(), SparseMatrixEZ< number >::locate(), and SparseMatrixEZ< number >::set().

template<typename number>
void SparseMatrixEZ< number >::set ( const unsigned int  i,
const unsigned int  j,
const number  value 
) [inline]

Set the element (i,j) to value. Allocates the entry, if it does not exist and value is non-zero. If value is not a finite number an exception is thrown.

References SparseMatrixEZ< number >::allocate(), Assert, numbers::is_finite(), SparseMatrixEZ< number >::locate(), SparseMatrixEZ< number >::m(), SparseMatrixEZ< number >::n(), and SparseMatrixEZ< number >::Entry::value.

Referenced by BlockSparseMatrixEZ< Number >::set().

template<typename number>
void SparseMatrixEZ< number >::add ( const unsigned int  i,
const unsigned int  j,
const number  value 
) [inline]

Add value to the element (i,j). Allocates the entry if it does not exist. Filters out zeroes automatically. If value is not a finite number an exception is thrown.

References SparseMatrixEZ< number >::allocate(), Assert, numbers::is_finite(), SparseMatrixEZ< number >::m(), SparseMatrixEZ< number >::n(), and SparseMatrixEZ< number >::Entry::value.

Referenced by SparseMatrixEZ< number >::add(), BlockSparseMatrixEZ< Number >::add(), and SparseMatrixEZ< number >::conjugate_add().

template<typename number >
template<typename number2 >
void SparseMatrixEZ< number >::add ( const std::vector< unsigned int > &  indices,
const FullMatrix< number2 > &  full_matrix,
const bool  elide_zero_values = true 
) [inline]

Add all elements given in a FullMatrix<double> into sparse matrix locations given by indices. In other words, this function adds the elements in full_matrix to the respective entries in calling matrix, using the local-to-global indexing specified by indices for both the rows and the columns of the matrix. This function assumes a quadratic sparse matrix and a quadratic full_matrix, the usual situation in FE calculations.

The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.

References SparseMatrixEZ< number >::add().

template<typename number >
template<typename number2 >
void SparseMatrixEZ< number >::add ( const std::vector< unsigned int > &  row_indices,
const std::vector< unsigned int > &  col_indices,
const FullMatrix< number2 > &  full_matrix,
const bool  elide_zero_values = true 
) [inline]

Same function as before, but now including the possibility to use rectangular full_matrices and different local-to-global indexing on rows and columns, respectively.

References SparseMatrixEZ< number >::add().

template<typename number >
template<typename number2 >
void SparseMatrixEZ< number >::add ( const unsigned int  row,
const std::vector< unsigned int > &  col_indices,
const std::vector< number2 > &  values,
const bool  elide_zero_values = true 
) [inline]

Set several elements in the specified row of the matrix with column indices as given by col_indices to the respective value.

The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.

References SparseMatrixEZ< number >::add().

template<typename number >
template<typename number2 >
void SparseMatrixEZ< number >::add ( const unsigned int  row,
const unsigned int  n_cols,
const unsigned int col_indices,
const number2 *  values,
const bool  elide_zero_values = true,
const bool  col_indices_are_sorted = false 
) [inline]

Add an array of values given by values in the given global matrix row at columns specified by col_indices in the sparse matrix.

The optional parameter elide_zero_values can be used to specify whether zero values should be added anyway or these should be filtered away and only non-zero data is added. The default value is true, i.e., zero values won't be added into the matrix.

References SparseMatrixEZ< number >::add().

template<typename number >
template<class MATRIX >
SparseMatrixEZ< number > & SparseMatrixEZ< number >::copy_from ( const MATRIX &  source  )  [inline]

Copy the given matrix to this one. The operation throws an error if the sparsity patterns of the two involved matrices do not point to the same object, since in this case the copy operation is cheaper. Since this operation is notheless not for free, we do not make it available through operator =, since this may lead to unwanted usage, e.g. in copy arguments to functions, which should really be arguments by reference.

The source matrix may be a matrix of arbitrary type, as long as its data type is convertible to the data type of this matrix.

The function returns a reference to this.

References SparseMatrixEZ< number >::reinit().

template<typename number>
template<class MATRIX >
void SparseMatrixEZ< number >::add ( const number  factor,
const MATRIX &  matrix 
) [inline]

Add matrix scaled by factor to this matrix.

The source matrix may be a matrix of arbitrary type, as long as its data type is convertible to the data type of this matrix and it has the standard const_iterator.

References SparseMatrixEZ< number >::add(), Assert, SparseMatrixEZ< number >::m(), and SparseMatrixEZ< number >::n().

template<typename number >
number SparseMatrixEZ< number >::operator() ( const unsigned int  i,
const unsigned int  j 
) const [inline]

Return the value of the entry (i,j). This may be an expensive operation and you should always take care where to call this function. In order to avoid abuse, this function throws an exception if the required element does not exist in the matrix.

In case you want a function that returns zero instead (for entries that are not in the sparsity pattern of the matrix), use the el function.

References Assert, SparseMatrixEZ< number >::locate(), and SparseMatrixEZ< number >::Entry::value.

template<typename number >
number SparseMatrixEZ< number >::el ( const unsigned int  i,
const unsigned int  j 
) const [inline]

Return the value of the entry (i,j). Returns zero for all non-existing entries.

References SparseMatrixEZ< number >::locate(), and SparseMatrixEZ< number >::Entry::value.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::vmult ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src 
) const [inline]

Matrix-vector multiplication: let $dst = M*src$ with $M$ being this matrix.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::Tvmult ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src 
) const [inline]

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 number>
template<typename somenumber >
void SparseMatrixEZ< number >::vmult_add ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src 
) const [inline]

Adding Matrix-vector multiplication. Add $M*src$ on $dst$ with $M$ being this matrix.

Referenced by BlockSparseMatrixEZ< Number >::vmult(), and BlockSparseMatrixEZ< Number >::vmult_add().

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::Tvmult_add ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src 
) const [inline]

Adding Matrix-vector multiplication. Add $M^T*src$ to $dst$ with $M$ being this matrix. This function does the same as vmult_add but takes the transposed matrix.

Referenced by BlockSparseMatrixEZ< Number >::Tvmult(), and BlockSparseMatrixEZ< Number >::Tvmult_add().

template<typename number>
number SparseMatrixEZ< number >::l2_norm (  )  const

Frobenius-norm of the matrix.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::precondition_Jacobi ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src,
const number  omega = 1. 
) const [inline]

Apply the Jacobi preconditioner, which multiplies every element of the src vector by the inverse of the respective diagonal element and multiplies the result with the damping factor omega.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::precondition_SSOR ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src,
const number  om = 1.,
const std::vector< unsigned int > &  pos_right_of_diagonal = std::vector< unsigned int >() 
) const [inline]

Apply SSOR preconditioning to src.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::precondition_SOR ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src,
const number  om = 1. 
) const [inline]

Apply SOR preconditioning matrix to src. The result of this method is $dst = (om D - L)^{-1} src$.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::precondition_TSOR ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src,
const number  om = 1. 
) const [inline]

Apply transpose SOR preconditioning matrix to src. The result of this method is $dst = (om D - U)^{-1} src$.

template<typename number >
template<class MATRIXA , class MATRIXB >
void SparseMatrixEZ< number >::conjugate_add ( const MATRIXA &  A,
const MATRIXB &  B,
const bool  transpose = false 
) [inline]

Add the matrix A conjugated by B, that is, $B A B^T$ to this object. If the parameter transpose is true, compute $B^T A B$.

This function requires that B has a const_iterator traversing all matrix entries and that A has a function el(i,j) for access to a specific entry.

References SparseMatrixEZ< number >::add().

template<typename number >
SparseMatrixEZ< number >::const_iterator SparseMatrixEZ< number >::begin (  )  const [inline]

STL-like iterator with the first existing entry.

template<typename number >
SparseMatrixEZ< number >::const_iterator SparseMatrixEZ< number >::end (  )  const [inline]
template<typename number >
SparseMatrixEZ< number >::const_iterator SparseMatrixEZ< number >::begin ( const unsigned int  r  )  const [inline]

STL-like iterator with the first entry of row r. If this row is empty, the result is end(r), which does NOT point into row r..

References Assert, and SparseMatrixEZ< number >::m().

template<typename number >
SparseMatrixEZ< number >::const_iterator SparseMatrixEZ< number >::end ( const unsigned int  r  )  const [inline]

Final iterator of row r. The result may be different from end()!

References Assert, and SparseMatrixEZ< number >::m().

template<typename number>
void SparseMatrixEZ< number >::print ( std::ostream &  out  )  const

Print the matrix to the given stream, using the format (line,col) value, i.e. one nonzero entry of the matrix per line.

template<typename number>
void SparseMatrixEZ< number >::print_formatted ( std::ostream &  out,
const unsigned int  precision = 3,
const bool  scientific = true,
const unsigned int  width = 0,
const char *  zero_string = " ",
const double  denominator = 1. 
) const

Print the matrix in the usual format, i.e. as a matrix and not as a list of nonzero elements. For better readability, elements not in the matrix are displayed as empty space, while matrix elements which are explicitly set to zero are displayed as such.

The parameters allow for a flexible setting of the output format: precision and scientific are used to determine the number format, where scientific = false means fixed point notation. A zero entry for width makes the function compute a width, but it may be changed to a positive value, if output is crude.

Additionally, a character for an empty value may be specified.

Finally, the whole matrix can be multiplied with a common denominator to produce more readable output, even integers.

This function may produce large amounts of output if applied to a large matrix!

template<typename number>
void SparseMatrixEZ< number >::block_write ( std::ostream &  out  )  const

Write the data of this object in binary mode to a file.

Note that this binary format is platform dependent.

template<typename number>
void SparseMatrixEZ< number >::block_read ( std::istream &  in  ) 

Read data that has previously been written by block_write.

The object is resized on this operation, and all previous contents are lost.

A primitive form of error checking is performed which will recognize the bluntest attempts to interpret some data as a vector stored bitwise to a file, but not more.

template<typename number>
unsigned int SparseMatrixEZ< number >::memory_consumption (  )  const

Determine an estimate for the memory consumption (in bytes) of this object.

template<typename number >
template<class STREAM >
void SparseMatrixEZ< number >::print_statistics ( STREAM &  s,
bool  full = false 
) [inline]

Print statistics. If full is true, prints a histogram of all existing row lengths and allocated row lengths. Otherwise, just the relation of allocated and used entries is shown.

References SparseMatrixEZ< number >::compute_statistics().

template<typename number>
void SparseMatrixEZ< number >::compute_statistics ( unsigned int used,
unsigned int allocated,
unsigned int reserved,
std::vector< unsigned int > &  used_by_line,
const bool  compute_by_line 
) const

Compute numbers of entries.

In the first three arguments, this function returns the number of entries used, allocated and reserved by this matrix.

If the final argument is true, the number of entries in each line is printed as well.

Referenced by SparseMatrixEZ< number >::print_statistics(), and BlockSparseMatrixEZ< Number >::print_statistics().

template<typename number >
const SparseMatrixEZ< number >::Entry * SparseMatrixEZ< number >::locate ( const unsigned int  row,
const unsigned int  col 
) const [inline, private]

Find an entry and return a const pointer. Return a zero-pointer if the entry does not exist.

References SparseMatrixEZ< number >::locate().

Referenced by SparseMatrixEZ< number >::el(), SparseMatrixEZ< number >::locate(), SparseMatrixEZ< number >::operator()(), and SparseMatrixEZ< number >::set().

template<typename number >
SparseMatrixEZ< number >::Entry * SparseMatrixEZ< number >::locate ( const unsigned int  row,
const unsigned int  col 
) [inline, private]
template<typename number >
SparseMatrixEZ< number >::Entry * SparseMatrixEZ< number >::allocate ( const unsigned int  row,
const unsigned int  col 
) [inline, private]
template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::threaded_vmult ( Vector< somenumber > &  dst,
const Vector< somenumber > &  src,
const unsigned int  begin_row,
const unsigned int  end_row 
) const [inline, private]

Version of vmult which only performs its actions on the region defined by [begin_row,end_row). This function is called by vmult in the case of enabled multithreading.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::threaded_matrix_norm_square ( const Vector< somenumber > &  v,
const unsigned int  begin_row,
const unsigned int  end_row,
somenumber *  partial_sum 
) const [inline, private]

Version of matrix_norm_square which only performs its actions on the region defined by [begin_row,end_row). This function is called by matrix_norm_square in the case of enabled multithreading.

template<typename number>
template<typename somenumber >
void SparseMatrixEZ< number >::threaded_matrix_scalar_product ( const Vector< somenumber > &  u,
const Vector< somenumber > &  v,
const unsigned int  begin_row,
const unsigned int  end_row,
somenumber *  partial_sum 
) const [inline, private]

Version of matrix_scalar_product which only performs its actions on the region defined by [begin_row,end_row). This function is called by matrix_scalar_product in the case of enabled multithreading.


Member Data Documentation

template<typename number>
unsigned int SparseMatrixEZ< number >::n_columns [private]

Number of columns. This is used to check vector dimensions only.

Referenced by SparseMatrixEZ< number >::n().

template<typename number>
std::vector<RowInfo> SparseMatrixEZ< number >::row_info [private]
template<typename number>
std::vector<Entry> SparseMatrixEZ< number >::data [private]
template<typename number>
unsigned int SparseMatrixEZ< number >::increment [private]

Increment when a row grows.

Referenced by SparseMatrixEZ< number >::allocate().


The documentation for this class was generated from the following file:

deal.II documentation generated on Mon Nov 23 22:58:08 2009 by doxygen 1.6.1