matrix.h File Reference

#include "common.h"
#include <common/error.h>

Go to the source code of this file.

Classes
class	Matrix
class	SparseMatrix
struct	SparseMatrix::Page
class	Vector
Enumerations
enum	EMatrixDumpFormat { DF_MATLAB_SPARSE, DF_PLAIN_ASCII, DF_HERMES_BIN, DF_NATIVE }
Functions
template<typename T >
T **	new_matrix (int m, int n=0)
	Creates a new (full) matrix with m rows and n columns with entries of the type T. The entries can be accessed by matrix[i][j]. To delete the matrix, just do "delete matrix".
template<typename T >
void	transpose (T **matrix, int m, int n)
	Transposes an m by n matrix. If m != n, the array matrix in fact has to be a square matrix of the size max(m, n) in order for the transpose to fit inside it.
template<typename T >
void	chsgn (T **matrix, int m, int n)
	Changes the sign of a matrix.
void	ludcmp (double **a, int n, int *indx, double *d)
	Given a matrix a[n][n], this routine replaces it by the LU decomposition of a rowwise permutation of itself. a and n are input. a is output, arranged as in equation (2.3.14) above; indx[n] is an output vector that records the row permutation effected by the partial pivoting; d is output as +-1 depending on whether the number of row interchanges was even or odd, respectively. This routine is used in combination with lubksb to solve linear equations or invert a matrix.
template<typename T >
void	lubksb (double **a, int n, int *indx, T *b)
	Solves the set of n linear equations AX = B. Here a[n][n] is input, not as the matrix A but rather as its LU decomposition, determined by the routine ludcmp. indx[n] is input as the permutation vector returned by ludcmp. b[n] is input as the right-hand side vector B, and returns with the solution vector X. a, n, and indx are not modified by this routine and can be left in place for successive calls with different right-hand sides b. This routine takes into account the possibility that b will begin with many zero elements, so it is efficient for use in matrix inversion.
void	choldc (double **a, int n, double p[])
	Given a positive-definite symmetric matrix a[n][n], this routine constructs its Cholesky decomposition, A = L*L^T . On input, only the upper triangle of a need be given; it is not modified. The Cholesky factor L is returned in the lower triangle of a, except for its diagonal elements which are returned in p[n].
template<typename T >
void	cholsl (double **a, int n, double p[], T b[], T x[])
	Solves the set of n linear equations A*x = b, where a is a positive-definite symmetric matrix. a[n][n] and p[n] are input as the output of the routine choldc. Only the lower subdiagonal portion of a is accessed. b[n] is input as the right-hand side vector. The solution vector is returned in x[n]. a, n, and p are not modified and can be left in place for successive calls with different right-hand sides b. b is not modified unless you identify b and x in the calling sequence, which is allowed. The right-hand side b can be complex, in which case the solution x is also complex.

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Enumeration Type Documentation

enum EMatrixDumpFormat

Enumerator:

DF_MATLAB_SPARSE
DF_PLAIN_ASCII
DF_HERMES_BIN
DF_NATIVE

---

Function Documentation

void choldc	(	double **	a,
		int	n,
		double	p[]
	)

Given a positive-definite symmetric matrix a[n][n], this routine constructs its Cholesky decomposition, A = L*L^T . On input, only the upper triangle of a need be given; it is not modified. The Cholesky factor L is returned in the lower triangle of a, except for its diagonal elements which are returned in p[n].

template<typename T >

void cholsl	(	double **	a,
		int	n,
		double	p[],
		T	b[],
		T	x[]
	)			[inline]

Solves the set of n linear equations A*x = b, where a is a positive-definite symmetric matrix. a[n][n] and p[n] are input as the output of the routine choldc. Only the lower subdiagonal portion of a is accessed. b[n] is input as the right-hand side vector. The solution vector is returned in x[n]. a, n, and p are not modified and can be left in place for successive calls with different right-hand sides b. b is not modified unless you identify b and x in the calling sequence, which is allowed. The right-hand side b can be complex, in which case the solution x is also complex.

template<typename T >

void chsgn	(	T **	matrix,
		int	m,
		int	n
	)			[inline]

Changes the sign of a matrix.

template<typename T >

void lubksb	(	double **	a,
		int	n,
		int *	indx,
		T *	b
	)			[inline]

Solves the set of n linear equations AX = B. Here a[n][n] is input, not as the matrix A but rather as its LU decomposition, determined by the routine ludcmp. indx[n] is input as the permutation vector returned by ludcmp. b[n] is input as the right-hand side vector B, and returns with the solution vector X. a, n, and indx are not modified by this routine and can be left in place for successive calls with different right-hand sides b. This routine takes into account the possibility that b will begin with many zero elements, so it is efficient for use in matrix inversion.

void ludcmp	(	double **	a,
		int	n,
		int *	indx,
		double *	d
	)

Given a matrix a[n][n], this routine replaces it by the LU decomposition of a rowwise permutation of itself. a and n are input. a is output, arranged as in equation (2.3.14) above; indx[n] is an output vector that records the row permutation effected by the partial pivoting; d is output as +-1 depending on whether the number of row interchanges was even or odd, respectively. This routine is used in combination with lubksb to solve linear equations or invert a matrix.

template<typename T >

T** new_matrix	(	int	m,
		int	n = 0
	)			[inline]

Creates a new (full) matrix with m rows and n columns with entries of the type T. The entries can be accessed by matrix[i][j]. To delete the matrix, just do "delete matrix".

template<typename T >

void transpose	(	T **	matrix,
		int	m,
		int	n
	)			[inline]

Transposes an m by n matrix. If m != n, the array matrix in fact has to be a square matrix of the size max(m, n) in order for the transpose to fit inside it.