nnls.c File Reference

#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include "include/nnls.h"
#include "include/lss_lib.h"

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Functions
int	nnls (double **a, int m, int n, double *b, double *x, double *rnorm, double *wp, double *zzp, int *indexp)
int	nnlsWght (int N, int M, double **A, double *b, double *weight)
int	nnlsWghtSquared (int N, int M, double **A, double *b, double *sweight)

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Function Documentation

int nnls	(	double **	a,
		int	m,
		int	n,
		double *	b,
		double *	x,
		double *	rnorm,
		double *	wp,
		double *	zzp,
		int *	indexp
	)

Algorithm NNLS (Non-negative least-squares)

Given an m by n matrix A, and an m-vector B, computes an n-vector X, that solves the least squares problem A * X = B , subject to X>=0

Instead of pointers for working space, NULL can be given to let this function to allocate and free the required memory.

Returns:

Function returns 0 if succesful, 1, if iteration count exceeded 3*N, or 2 in case of invalid problem dimensions or memory allocation error.

Parameters:

a	On entry, a[ 0... N ][ 0 ... M ] contains the M by N matrix A. On exit, a[][] contains the product matrix Q*A, where Q is an m by n orthogonal matrix generated implicitly by this function.
m	Matrix dimension m
n	Matrix dimension n
b	On entry, b[] must contain the m-vector B. On exit, b[] contains Q*B
x	On exit, x[] will contain the solution vector
rnorm	On exit, rnorm contains the Euclidean norm of the residual vector. If NULL is given, no rnorm is calculated
wp	An n-array of working space, wp[]. On exit, wp[] will contain the dual solution vector. wp[i]=0.0 for all i in set p and wp[i]<=0.0 for all i in set z. Can be NULL, which causes this algorithm to allocate memory for it.
zzp	An m-array of working space, zz[]. Can be NULL, which causes this algorithm to allocate memory for it.
indexp	An n-array of working space, index[]. Can be NULL, which causes this algorithm to allocate memory for it.

Definition at line 63 of file nnls.c.

References _lss_g1(), _lss_h12(), _lss_print_matrix(), and NNLS_TEST.

Referenced by do_nnls(), and ldp().

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int nnlsWght	(	int	N,
		int	M,
		double **	A,
		double *	b,
		double *	weight
	)

Algorithm for weighting the problem that is given to nnls-algorithm. Square roots of weights are used because in nnls the difference w*A-w*b is squared.

Returns:

Algorithm returns zero if successful, 1 if arguments are inappropriate.

Parameters:

N	NNLS dimension N (nr of parameters)
M	NNLS dimension M (nr of samples)
A	NNLS matrix A
b	NNLS vector B
weight	Weights for each sample (array of length M)

Definition at line 307 of file nnls.c.

References M.

int nnlsWghtSquared	(	int	N,
		int	M,
		double **	A,
		double *	b,
		double *	sweight
	)

Algorithm for weighting the problem that is given to nnls-algorithm. Square roots of weights are used because in nnls the difference w*A-w*b is squared. Here user must give squared weights; this makes calculation faster, when this function needs to be called many times.

Returns:

Algorithm returns zero if successful, 1 if arguments are inappropriate.

Parameters:

N	NNLS dimension N (nr of parameters)
M	NNLS dimension M (nr of samples)
A	NNLS matrix A
b	NNLS vector B
sweight	Squared weights for each sample (array of length M)

Definition at line 355 of file nnls.c.

References M.