nrfct.h File Reference

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Macros
#define	SIGN(a, b)   ((b) >= 0.0 ? fabs(a) : -fabs(a))
#define	IMIN(a, b)
#define	DMAX(a, b)
#define	DSQR(a)   ((dsqrarg=(a)) == 0.0 ? 0.0 : dsqrarg*dsqrarg)

Functions
int	ludcmp (double **a, int n, int *indx, double *d)
	LU decomposition of a matrix with index starting at 1. More...
int	ludcmp_0 (double **a, int n, int *indx, double *d)
	LU decomposition of a matrix with index starting at 0. More...
void	lubksb (double **a, int n, int *indx, double b[])
void	lubksb_0 (double **a, int n, int *indx, double b[])
int	choldc (double **a, int n, double p[])
	Compute the Cholesky decomposition of a, i.e. More...
int	choldc_0 (double **a, int n, double *p)
void	cholsl (double **a, int n, double p[], double b[], double x[])
void	cholsl_0 (double **a, int n, double *p, double *b, double *x)
void	svdcmp (double **a, int m, int n, double w[], double **v)
	computes the Singular Value Decomposition a = u.w.v' More...
void	svdcmp_0 (double **a, int m, int n, double w[], double **v)
	computes the Singular Value Decomposition a = u.w.v' More...
void	svbksb (double **u, double w[], double **v, int m, int n, double b[], double x[])
void	svbksb_0 (double **u, double w[], double **v, int m, int n, double b[], double x[])
void	gaussj (double **a, int n, double **b, int m)

Detailed Description

This c header file declares various functions about linear algebra.

Creation date: 2006

Author

Robotran team

(c) Universite catholique de Louvain

Macro Definition Documentation

DMAX

#define DMAX	(		a,
			b
	)

Value:

        (dmaxarg1=(a),dmaxarg2=(b),(dmaxarg1) > (dmaxarg2) ?\
        (dmaxarg1) : (dmaxarg2))

DSQR

#define DSQR

(

a

)

((dsqrarg=(a)) == 0.0 ? 0.0 : dsqrarg*dsqrarg)

IMIN

#define IMIN	(		a,
			b
	)

Value:

        (iminarg1=(a),iminarg2=(b),(iminarg1) < (iminarg2) ?\
        (iminarg1) : (iminarg2))

SIGN

#define SIGN	(		a,
			b
	)		((b) >= 0.0 ? fabs(a) : -fabs(a))

Function Documentation

choldc()

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

Compute the Cholesky decomposition of a, i.e.

the lower triangular matrix L such that a=L*L'

Elements off diagonal are stored directly in a. Diagonal elements are stored in p.

WARNING: a is modified !

choldc_0()

int choldc_0	(	double **	a,
		int	n,
		double *	p
	)

cholsl()

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

cholsl_0()

void cholsl_0	(	double **	a,
		int	n,
		double *	p,
		double *	b,
		double *	x
	)

gaussj()

void gaussj	(	double **	a,
		int	n,
		double **	b,
		int	m
	)

lubksb()

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

lubksb_0()

void lubksb_0	(	double **	a,
		int	n,
		int *	indx,
		double	b[]
	)

ludcmp()

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

LU decomposition of a matrix with index starting at 1.

Parameters

[in,out]	a	Input and output matrix with index starting at 1.
[in]	n	size of the square matrix a : [n x n] .
[out]	indx	Row permutations with index starting at 1.
[out]	d	+1 if the number of row interchange is even, -1 if it is odd.

Returns

Error status, <0 in case of failure (= 0 if no error).

ludcmp_0()

int ludcmp_0	(	double **	a,
		int	n,
		int *	indx,
		double *	d
	)

LU decomposition of a matrix with index starting at 0.

Parameters

[in,out]	a	Input and output matrix with index starting at 0.
[in]	n	size of the square matrix a : [n x n].
[out]	indx	Row permutations with index starting at 0.
[out]	d	+1 if the number of row interchange is even, -1 if it is odd.

Returns

Error status, <0 in case of failure.

svbksb()

void svbksb	(	double **	u,
		double	w[],
		double **	v,
		int	m,
		int	n,
		double	b[],
		double	x[]
	)

svbksb_0()

void svbksb_0	(	double **	u,
		double	w[],
		double **	v,
		int	m,
		int	n,
		double	b[],
		double	x[]
	)

svdcmp()

void svdcmp	(	double **	a,
		int	m,
		int	n,
		double	w[],
		double **	v
	)

computes the Singular Value Decomposition a = u.w.v'

The output matrix u is stored in the input matrix a.

The given arrays size is the minimum size, bigger arrays are acceptable. Indeed, the function will only use the first N elements of a 1D array or the first N rows and M columns of 2D arrays. Giving an oversized array as input (for example one of mbs_aux->... that is initialized at the system maximum possible size) is not an issue.

Parameters

[in,out]	a	the input matrix, with index starting at 1, to be decomposed. The content is modified to be the output matrix u. Its size must at least be m x n (0 element not taken into account).
[in]	m	the number of rows (0 element not taken into account) of the matrix a.
[in]	n	the number of columns (0 element not taken into account) of the matrix a.
[out]	w	the vector, with index starting at 1, to store the singular values.
[out]	v	the matrix v (not the transpose) of size n x n (0 element not taken into account).

svdcmp_0()

void svdcmp_0	(	double **	a,
		int	m,
		int	n,
		double	w[],
		double **	v
	)

computes the Singular Value Decomposition a = u.w.v'

The output matrix u is stored in the input matrix a. The given arrays size are minimum size, bigger arrays are acceptable.

Parameters

[in,out]	a	the input matrix, with index starting at 0, to be decomposed. The content is modified to be the output matrix u. Its size must be m x n.
[in]	m	the number of rows of the matrix a.
[in]	n	the number of columns of the matrix a.
[out]	w	the vector, with index starting at 0, to store the singular values.
[out]	v	the matrix v (not the transpose) of size n x n.