PLearn::RowMapSparseMatrix< T > Class Template Reference

#include <RowMapSparseMatrix.h>

Inheritance diagram for PLearn::RowMapSparseMatrix< T >:

[legend]Collaboration diagram for PLearn::RowMapSparseMatrix< T >:

[legend]List of all members.


Public Member Functions
	RowMapSparseMatrix (int n_rows=0, int n_columns=0)
	RowMapSparseMatrix (string filename)
	RowMapSparseMatrix (const Mat &m, bool fill_all=true)
	RowMapSparseMatrix (const SparseMatrix &sm, int n_rows, int n_cols)
	Accepts a FORTRAN formatted sparse matrix as an initializer.
void	resize (int n_rows, int n_columns)
	THIS ALSO CLEARS THE MATRIX.
void	clear ()
	this is equivalent to setting all values to "0" (the default value of T)
void	clearRow (int i)
T &	operator() (int i, int j)
const T &	operator() (int i, int j) const
map< int, T > &	operator() (int i)
int	size () const
	NOTE THIS IS A BIT EXPENSIVE!
int	length () const
int	width () const
void	save (string filename) const
void	saveAscii (string filename)
void	load (string filename)
	determines automatically whether file is binary or ascii
void	read (istream &in)
void	write (ostream &out) const
	mode used to write depends on save_binary flag
void	saveNonZeroElements (string filename) const
void	product (const Vec &x, Vec &y)
	multiply a sparse matrix by a full vector and set resulting vector y = matrix * x
Mat	toMat ()
bool	isSymmetric (real tolerance=0)
bool	fillSymmetricPart (real tolerance=0)
void	diag (Vec &d)
	set d[i] = A[i,i]
void	diagonalOfSquare (Vec &d)
	d = diagonal(A*A'), i.e.
real	dotRow (int i, Vec v)
	return dot product of i-th row with vector v
real	dotColumn (int j, Vec v)
	return dot product of j-th column with vector v
void	transposeProduct (RowMapSparseMatrix &m, bool verbose=false)
	M = A' * A.
void	add2Rows (Vec row, bool only_on_non_zeros=true)
	add vector to each row; by default do it only on the non-zero elements
void	add2Columns (Vec col, bool only_on_non_zeros=true)
	add vector to each column; by default do it only on the non-zero elements
void	add (real scalar, bool only_on_non_zeros=true)
	add a scalar everywhere; by default do it only on the non-zero elements
void	averageAcrossRowsAndColumns (Vec avg_across_rows, Vec avg_across_columns, bool only_on_non_zeros=true)
real	sumRow (int i)
void	operator *= (real scalar)
	multiply each (non-zero) element
void	exportToMatlabReadableFormat (string filename)
real	density ()
	Compute the matrix density, that is : number_of_nonzero_elements / (length*width).
Static Public Member Functions
void	transpose (RowMapSparseMatrix< T > &src, RowMapSparseMatrix< T > &dest)
	D = S'.
real	multiplyVecs (map< int, T > &map1, map< int, T > &map2)
	Sparse vectors mutliplication.
real	euclidianDistance (map< int, real > &map1, map< int, real > &map2)
void	substractVecs (map< int, real > &map1, map< int, real > &map2, Vec &dest)
	Vec dest[i] = map1[i] - map2[i].
int	getMaxColumnIndex (map< int, T > &map1, map< int, T > &map2)
	Return the last non-zero position of a sparse vector (used for sparse operations that need to know the "end" of a vector).
Public Attributes
vector< map< int, T > >	rows
bool	save_binary
Protected Attributes
int	_width

Detailed Description

template<class T>
class PLearn::RowMapSparseMatrix< T >

Sparse matrices implemented with STL maps.

We assume that there are elements in each ROW.

We associate an STL map to each row: column index --> value

Space used is about O( size_of_elements * number_of_non_zero_elements )

Random access time is O(log(number_of_elements_per_row))

Row-wise iterations can be done in constant time per access.

Binary or ascii load/save streaming are available. Recommended filename extensions are .armsm and .brmsm respectively for Ascii Row Map Sparse Matrix or Binary Row Map Sparse Matrix.

Definition at line 69 of file RowMapSparseMatrix.h.

Constructor & Destructor Documentation

template<class T>

PLearn::RowMapSparseMatrix< T >::RowMapSparseMatrix ( int n_rows = 0,

int n_columns = 0

) [inline]

Definition at line 78 of file RowMapSparseMatrix.h.

template<class T>

PLearn::RowMapSparseMatrix< T >::RowMapSparseMatrix ( string filename ) [inline]

Definition at line 81 of file RowMapSparseMatrix.h.

template<class T>

PLearn::RowMapSparseMatrix< T >::RowMapSparseMatrix ( const Mat & m,

bool fill_all = true

) [inline]

Definition at line 83 of file RowMapSparseMatrix.h.

template<class T>

PLearn::RowMapSparseMatrix< T >::RowMapSparseMatrix ( const SparseMatrix & sm,

int n_rows,

int n_cols

) [inline]

Accepts a FORTRAN formatted sparse matrix as an initializer.

Definition at line 106 of file RowMapSparseMatrix.h.

Member Function Documentation

template<class T>

void PLearn::RowMapSparseMatrix< T >::add ( real scalar,

bool only_on_non_zeros = true

) [inline]

add a scalar everywhere; by default do it only on the non-zero elements

Definition at line 507 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::add2Columns ( Vec col,

bool only_on_non_zeros = true

) [inline]

add vector to each column; by default do it only on the non-zero elements

Definition at line 491 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::add2Rows ( Vec row,

bool only_on_non_zeros = true

) [inline]

add vector to each row; by default do it only on the non-zero elements

Definition at line 475 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::averageAcrossRowsAndColumns ( Vec avg_across_rows,

Vec avg_across_columns,

bool only_on_non_zeros = true

) [inline]

average across rows on one hand, and in parallel average across columns (thus getting two averages). The boolean argument specifies whether the average is across the explicit elements (the non-zeros) or across everything (currently unsupported).
Reimplemented in PLearn::RowMapSparseValueMatrix< T >.
Definition at line 526 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::clear ( ) [inline]

this is equivalent to setting all values to "0" (the default value of T)

Definition at line 127 of file RowMapSparseMatrix.h.
Referenced by PLearn::RowMapSparseMatrix< real >::resize(), and PLearn::RowMapSparseMatrix< real >::transpose().

template<class T>

void PLearn::RowMapSparseMatrix< T >::clearRow ( int i ) [inline]

Definition at line 133 of file RowMapSparseMatrix.h.

template<class T>

real PLearn::RowMapSparseMatrix< T >::density ( ) [inline]

Compute the matrix density, that is : number_of_nonzero_elements / (length*width).

Definition at line 793 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::diag ( Vec & d ) [inline]

set d[i] = A[i,i]

Definition at line 383 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::diagonalOfSquare ( Vec & d ) [inline]

d = diagonal(A*A'), i.e.
d[i] = |A[i]|^2 where A[i] is i-th row
Definition at line 392 of file RowMapSparseMatrix.h.

template<class T>

real PLearn::RowMapSparseMatrix< T >::dotColumn ( int j,

Vec v

) [inline]

return dot product of j-th column with vector v

Definition at line 426 of file RowMapSparseMatrix.h.

template<class T>

real PLearn::RowMapSparseMatrix< T >::dotRow ( int i,

Vec v

) [inline]

return dot product of i-th row with vector v

Definition at line 408 of file RowMapSparseMatrix.h.

template<class T>

real PLearn::RowMapSparseMatrix< T >::euclidianDistance ( map< int, real > & map1,

map< int, real > & map2

) [inline, static]

This is not a "true" euclidian distance
Reimplemented in PLearn::RowMapSparseValueMatrix< T >.
Definition at line 651 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::exportToMatlabReadableFormat ( string filename ) [inline]

Export as matlab readable [i, j , v] format to file <out> Matlab : (1) load <out> (2) A = spconvert(out) (note: the file extension must be '.dat')
Add the bottom right corner, to make sure that the sparse matrix has the right dimensions
Definition at line 763 of file RowMapSparseMatrix.h.
Referenced by PLearn::MatlabInterface::eigs_r11(), and PLearn::matlabR11eigs().

template<class T>

bool PLearn::RowMapSparseMatrix< T >::fillSymmetricPart ( real tolerance = 0 ) [inline]

if A(i,j) is specified and not A(j,i) then set A(j,i)=A(i,j). if both were specified but different, up to the tolerance (in abs. value difference), then abort the operation and return false (there is a problem!). Otherwise return true.
see if entry i exists in row j
not found, then set A(j,i) to A(i,j)
check if they are equal
Definition at line 354 of file RowMapSparseMatrix.h.

template<class T>

int PLearn::RowMapSparseMatrix< T >::getMaxColumnIndex ( map< int, T > & map1,

map< int, T > & map2

) [inline, static]

Return the last non-zero position of a sparse vector (used for sparse operations that need to know the "end" of a vector).

Definition at line 750 of file RowMapSparseMatrix.h.

template<class T>

bool PLearn::RowMapSparseMatrix< T >::isSymmetric ( real tolerance = 0 ) [inline]

Definition at line 329 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::load ( string filename ) [inline]

determines automatically whether file is binary or ascii

Definition at line 193 of file RowMapSparseMatrix.h.

template<class T>

real PLearn::RowMapSparseMatrix< T >::multiplyVecs ( map< int, T > & map1,

map< int, T > & map2

) [inline, static]

Sparse vectors mutliplication.

Definition at line 608 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::operator *= ( real scalar ) [inline]

multiply each (non-zero) element

Definition at line 576 of file RowMapSparseMatrix.h.

template<class T>

map<int,T>& PLearn::RowMapSparseMatrix< T >::operator() ( int i ) [inline]

Get i-th row. Exemple to iterate on i-th row:
map<int,T>& row_i = A(i); < note very important: row_i is a reference (&) map<int,T>::const_iterator it = row_i.begin(); map<int,T>::const_iterator end = row_i.end(); for (;it!=end;++it) { int j = it->first; T Aij = it->second; ... }
Reimplemented in PLearn::RowMapSparseValueMatrix< T >.
Definition at line 172 of file RowMapSparseMatrix.h.

template<class T>

const T& PLearn::RowMapSparseMatrix< T >::operator() ( int i,

int j

) const [inline]

Reimplemented in PLearn::RowMapSparseValueMatrix< T >.
Definition at line 147 of file RowMapSparseMatrix.h.

template<class T>

T& PLearn::RowMapSparseMatrix< T >::operator() ( int i,

int j

) [inline]

Reimplemented in PLearn::RowMapSparseValueMatrix< T >.
Definition at line 138 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::product ( const Vec & x,

Vec & y

) [inline]

multiply a sparse matrix by a full vector and set resulting vector y = matrix * x

Definition at line 293 of file RowMapSparseMatrix.h.
Referenced by PLearn::product().

template<class T>

void PLearn::RowMapSparseMatrix< T >::read ( istream & in ) [inline]

Definition at line 194 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::resize ( int n_rows,

int n_columns

) [inline]

THIS ALSO CLEARS THE MATRIX.

Definition at line 120 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::save ( string filename ) const [inline]

Definition at line 184 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::saveAscii ( string filename ) [inline]

Definition at line 187 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::saveNonZeroElements ( string filename ) const [inline]

saves the non-zero elements in an ascii file with the following simple format: first line: <length> <width> <numbernonzero> subsequent lines: <row> <column> <value>
Definition at line 277 of file RowMapSparseMatrix.h.

template<class T>

int PLearn::RowMapSparseMatrix< T >::size ( ) const [inline]

NOTE THIS IS A BIT EXPENSIVE!

Definition at line 175 of file RowMapSparseMatrix.h.
Referenced by PLearn::RowMapSparseMatrix< real >::density(), and PLearn::RowMapSparseMatrix< real >::saveNonZeroElements().

template<class T>

void PLearn::RowMapSparseMatrix< T >::substractVecs ( map< int, real > & map1,

map< int, real > & map2,

Vec & dest

) [inline, static]

Vec dest[i] = map1[i] - map2[i].

Definition at line 704 of file RowMapSparseMatrix.h.

template<class T>

real PLearn::RowMapSparseMatrix< T >::sumRow ( int i ) [inline]

average across rows on one hand, and in parallel average across columns (thus getting two averages). The boolean argument specifies whether the average is across the explicit elements (the non-zeros) or across everything (currently unsupported).
Definition at line 563 of file RowMapSparseMatrix.h.

template<class T>

Mat PLearn::RowMapSparseMatrix< T >::toMat ( ) [inline]

Reimplemented in PLearn::RowMapSparseValueMatrix< T >.
Definition at line 314 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::transpose ( RowMapSparseMatrix< T > & src,

RowMapSparseMatrix< T > & dest

) [inline, static]

D = S'.

Definition at line 589 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::transposeProduct ( RowMapSparseMatrix< T > & m,

bool verbose = false

) [inline]

M = A' * A.

Definition at line 442 of file RowMapSparseMatrix.h.

template<class T>

void PLearn::RowMapSparseMatrix< T >::write ( ostream & out ) const [inline]

mode used to write depends on save_binary flag

Definition at line 237 of file RowMapSparseMatrix.h.