1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175
|
/* ========================================================================== */
/* === CHOLMOD/MATLAB/ldlsolve mexFunction ================================== */
/* ========================================================================== */
/* -----------------------------------------------------------------------------
* CHOLMOD/MATLAB Module. Copyright (C) 2005-2006, Timothy A. Davis
* http://www.suitesparse.com
* MATLAB(tm) is a Trademark of The MathWorks, Inc.
* -------------------------------------------------------------------------- */
/* Solve LDL'x=b given an LDL' factorization computed by ldlchol.
*
* Usage:
*
* x = ldlsolve (LD,b)
*
* b can be dense or sparse.
*/
#include "cholmod_matlab.h"
void mexFunction
(
int nargout,
mxArray *pargout [ ],
int nargin,
const mxArray *pargin [ ]
)
{
double dummy = 0, rcond ;
Long *Lp, *Lnz, *Lprev, *Lnext ;
cholmod_sparse *Bs, Bspmatrix, *Xs ;
cholmod_dense *B, Bmatrix, *X ;
cholmod_factor *L ;
cholmod_common Common, *cm ;
Long j, k, n, B_is_sparse, head, tail ;
/* ---------------------------------------------------------------------- */
/* start CHOLMOD and set parameters */
/* ---------------------------------------------------------------------- */
cm = &Common ;
cholmod_l_start (cm) ;
sputil_config (SPUMONI, cm) ;
/* ---------------------------------------------------------------------- */
/* check inputs */
/* ---------------------------------------------------------------------- */
if (nargout > 1 || nargin != 2)
{
mexErrMsgTxt ("Usage: x = ldlsolve (LD, b)") ;
}
n = mxGetN (pargin [0]) ;
k = mxGetN (pargin [1]) ;
if (!mxIsSparse (pargin [0]) || n != mxGetM (pargin [0]))
{
mexErrMsgTxt ("ldlsolve: LD must be sparse and square") ;
}
if (n != mxGetM (pargin [1]))
{
mexErrMsgTxt ("ldlsolve: b wrong dimension") ;
}
/* ---------------------------------------------------------------------- */
/* get b */
/* ---------------------------------------------------------------------- */
/* get sparse or dense matrix B */
B = NULL ;
Bs = NULL ;
B_is_sparse = mxIsSparse (pargin [1]) ;
if (B_is_sparse)
{
/* get sparse matrix B (unsymmetric) */
Bs = sputil_get_sparse (pargin [1], &Bspmatrix, &dummy, 0) ;
}
else
{
/* get dense matrix B */
B = sputil_get_dense (pargin [1], &Bmatrix, &dummy) ;
}
/* ---------------------------------------------------------------------- */
/* construct a shallow copy of the input sparse matrix L */
/* ---------------------------------------------------------------------- */
/* the construction of the CHOLMOD takes O(n) time and memory */
/* allocate the CHOLMOD symbolic L */
L = cholmod_l_allocate_factor (n, cm) ;
L->ordering = CHOLMOD_NATURAL ;
/* get the MATLAB L */
L->p = mxGetJc (pargin [0]) ;
L->i = mxGetIr (pargin [0]) ;
L->x = mxGetPr (pargin [0]) ;
L->z = mxGetPi (pargin [0]) ;
/* allocate and initialize the rest of L */
L->nz = cholmod_l_malloc (n, sizeof (Long), cm) ;
Lp = L->p ;
Lnz = L->nz ;
for (j = 0 ; j < n ; j++)
{
Lnz [j] = Lp [j+1] - Lp [j] ;
}
L->prev = cholmod_l_malloc (n+2, sizeof (Long), cm) ;
L->next = cholmod_l_malloc (n+2, sizeof (Long), cm) ;
Lprev = L->prev ;
Lnext = L->next ;
head = n+1 ;
tail = n ;
Lnext [head] = 0 ;
Lprev [head] = -1 ;
Lnext [tail] = -1 ;
Lprev [tail] = n-1 ;
for (j = 0 ; j < n ; j++)
{
Lnext [j] = j+1 ;
Lprev [j] = j-1 ;
}
Lprev [0] = head ;
L->xtype = (mxIsComplex (pargin [0])) ? CHOLMOD_ZOMPLEX : CHOLMOD_REAL ;
L->nzmax = Lp [n] ;
/* ---------------------------------------------------------------------- */
/* solve and return solution to MATLAB */
/* ---------------------------------------------------------------------- */
if (B_is_sparse)
{
/* solve LDL'X=B with sparse X and B; return sparse X to MATLAB */
Xs = cholmod_l_spsolve (CHOLMOD_LDLt, L, Bs, cm) ;
pargout [0] = sputil_put_sparse (&Xs, cm) ;
}
else
{
/* solve AX=B with dense X and B; return dense X to MATLAB */
X = cholmod_l_solve (CHOLMOD_LDLt, L, B, cm) ;
pargout [0] = sputil_put_dense (&X, cm) ;
}
rcond = cholmod_l_rcond (L, cm) ;
if (rcond == 0)
{
mexWarnMsgTxt ("Matrix is indefinite or singular to working precision");
}
else if (rcond < DBL_EPSILON)
{
mexWarnMsgTxt ("Matrix is close to singular or badly scaled.") ;
mexPrintf (" Results may be inaccurate. RCOND = %g.\n", rcond) ;
}
/* ---------------------------------------------------------------------- */
/* free workspace and the CHOLMOD L, except for what is copied to MATLAB */
/* ---------------------------------------------------------------------- */
L->p = NULL ;
L->i = NULL ;
L->x = NULL ;
L->z = NULL ;
cholmod_l_free_factor (&L, cm) ;
cholmod_l_finish (cm) ;
cholmod_l_print_common (" ", cm) ;
/*
if (cm->malloc_count !=
(mxIsComplex (pargout [0]) + (mxIsSparse (pargout[0]) ? 3:1)))
mexErrMsgTxt ("!") ;
*/
}
|