SEXP dsCMatrix_chol(SEXP x, SEXP pivot)
{
int pivP = asLogical(pivot);
CHM_FR L = internal_chm_factor(x, pivP, 0, 0, 0.);
CHM_SP R, Rt;
SEXP ans;
Rt = cholmod_l_factor_to_sparse(L, &c);
R = cholmod_l_transpose(Rt, /*values*/ 1, &c);
cholmod_l_free_sparse(&Rt, &c);
ans = PROTECT(chm_sparse_to_SEXP(R, 1/*do_free*/, 1/*uploT*/, 0/*Rkind*/,
"N"/*diag*/, GET_SLOT(x, Matrix_DimNamesSym)));
if (pivP) {
SEXP piv = PROTECT(allocVector(INTSXP, L->n));
int *dest = INTEGER(piv), *src = (int*)L->Perm;
for (int i = 0; i < L->n; i++) dest[i] = src[i] + 1;
setAttrib(ans, install("pivot"), piv);
setAttrib(ans, install("rank"), ScalarInteger((size_t) L->minor));
UNPROTECT(1);
}
cholmod_l_free_factor(&L, &c);
UNPROTECT(1);
return ans;
}
void mexFunction
(
int nargout,
mxArray *pargout [ ],
int nargin,
const mxArray *pargin [ ]
)
{
double dummy = 0, *px ;
cholmod_sparse Amatrix, *A, *Lsparse, *R ;
cholmod_factor *L ;
cholmod_common Common, *cm ;
Long n, minor ;
/* ---------------------------------------------------------------------- */
/* start CHOLMOD and set parameters */
/* ---------------------------------------------------------------------- */
cm = &Common ;
cholmod_l_start (cm) ;
sputil_config (SPUMONI, cm) ;
/* convert to packed LL' when done */
cm->final_asis = FALSE ;
cm->final_super = FALSE ;
cm->final_ll = TRUE ;
cm->final_pack = TRUE ;
cm->final_monotonic = TRUE ;
/* no need to prune entries due to relaxed supernodal amalgamation, since
* zeros are dropped with sputil_drop_zeros instead */
cm->final_resymbol = FALSE ;
cm->quick_return_if_not_posdef = (nargout < 2) ;
/* ---------------------------------------------------------------------- */
/* get inputs */
/* ---------------------------------------------------------------------- */
if (nargin != 1 || nargout > 3)
{
mexErrMsgTxt ("usage: [R,p,q] = chol2 (A)") ;
}
n = mxGetN (pargin [0]) ;
if (!mxIsSparse (pargin [0]) || n != mxGetM (pargin [0]))
{
mexErrMsgTxt ("A must be square and sparse") ;
}
/* get input sparse matrix A. Use triu(A) only */
A = sputil_get_sparse (pargin [0], &Amatrix, &dummy, 1) ;
/* use natural ordering if no q output parameter */
if (nargout < 3)
{
cm->nmethods = 1 ;
cm->method [0].ordering = CHOLMOD_NATURAL ;
cm->postorder = FALSE ;
}
/* ---------------------------------------------------------------------- */
/* analyze and factorize */
/* ---------------------------------------------------------------------- */
L = cholmod_l_analyze (A, cm) ;
cholmod_l_factorize (A, L, cm) ;
if (nargout < 2 && cm->status != CHOLMOD_OK)
{
mexErrMsgTxt ("matrix is not positive definite") ;
}
/* ---------------------------------------------------------------------- */
/* convert L to a sparse matrix */
/* ---------------------------------------------------------------------- */
/* the conversion sets L->minor back to n, so get a copy of it first */
minor = L->minor ;
Lsparse = cholmod_l_factor_to_sparse (L, cm) ;
if (Lsparse->xtype == CHOLMOD_COMPLEX)
{
/* convert Lsparse from complex to zomplex */
cholmod_l_sparse_xtype (CHOLMOD_ZOMPLEX, Lsparse, cm) ;
}
if (minor < n)
{
/* remove columns minor to n-1 from Lsparse */
sputil_trim (Lsparse, minor, cm) ;
}
/* drop zeros from Lsparse */
sputil_drop_zeros (Lsparse) ;
/* Lsparse is lower triangular; conjugate transpose to get R */
R = cholmod_l_transpose (Lsparse, 2, cm) ;
cholmod_l_free_sparse (&Lsparse, cm) ;
/* ---------------------------------------------------------------------- */
/* return results to MATLAB */
/* ---------------------------------------------------------------------- */
/* return R */
pargout [0] = sputil_put_sparse (&R, cm) ;
/* return minor (translate to MATLAB convention) */
if (nargout > 1)
{
pargout [1] = mxCreateDoubleMatrix (1, 1, mxREAL) ;
px = mxGetPr (pargout [1]) ;
px [0] = ((minor == n) ? 0 : (minor+1)) ;
}
/* return permutation */
if (nargout > 2)
{
pargout [2] = sputil_put_int (L->Perm, n, 1) ;
}
/* ---------------------------------------------------------------------- */
/* free workspace and the CHOLMOD L, except for what is copied to MATLAB */
/* ---------------------------------------------------------------------- */
cholmod_l_free_factor (&L, cm) ;
cholmod_l_finish (cm) ;
cholmod_l_print_common (" ", cm) ;
/*
if (cm->malloc_count != (3 + mxIsComplex (pargout[0]))) mexErrMsgTxt ("!") ;
*/
}
void mexFunction
(
int nargout,
mxArray *pargout [ ],
int nargin,
const mxArray *pargin [ ]
)
{
double dummy = 0, beta [2], *px ;
cholmod_sparse Amatrix, *A, *Lsparse ;
cholmod_factor *L ;
cholmod_common Common, *cm ;
Long n, minor ;
/* ---------------------------------------------------------------------- */
/* start CHOLMOD and set parameters */
/* ---------------------------------------------------------------------- */
cm = &Common ;
cholmod_l_start (cm) ;
sputil_config (SPUMONI, cm) ;
/* convert to packed LDL' when done */
cm->final_asis = FALSE ;
cm->final_super = FALSE ;
cm->final_ll = FALSE ;
cm->final_pack = TRUE ;
cm->final_monotonic = TRUE ;
/* since numerically zero entries are NOT dropped from the symbolic
* pattern, we DO need to drop entries that result from supernodal
* amalgamation. */
cm->final_resymbol = TRUE ;
cm->quick_return_if_not_posdef = (nargout < 2) ;
/* This will disable the supernodal LL', which will be slow. */
/* cm->supernodal = CHOLMOD_SIMPLICIAL ; */
/* ---------------------------------------------------------------------- */
/* get inputs */
/* ---------------------------------------------------------------------- */
if (nargin < 1 || nargin > 2 || nargout > 3)
{
mexErrMsgTxt ("usage: [L,p,q] = ldlchol (A,beta)") ;
}
n = mxGetM (pargin [0]) ;
if (!mxIsSparse (pargin [0]))
{
mexErrMsgTxt ("A must be sparse") ;
}
if (nargin == 1 && n != mxGetN (pargin [0]))
{
mexErrMsgTxt ("A must be square") ;
}
/* get sparse matrix A, use tril(A) */
A = sputil_get_sparse (pargin [0], &Amatrix, &dummy, -1) ;
if (nargin == 1)
{
A->stype = -1 ; /* use lower part of A */
beta [0] = 0 ;
beta [1] = 0 ;
}
else
{
A->stype = 0 ; /* use all of A, factorizing A*A' */
beta [0] = mxGetScalar (pargin [1]) ;
beta [1] = 0 ;
}
/* use natural ordering if no q output parameter */
if (nargout < 3)
{
cm->nmethods = 1 ;
cm->method [0].ordering = CHOLMOD_NATURAL ;
cm->postorder = FALSE ;
}
/* ---------------------------------------------------------------------- */
/* analyze and factorize */
/* ---------------------------------------------------------------------- */
L = cholmod_l_analyze (A, cm) ;
cholmod_l_factorize_p (A, beta, NULL, 0, L, cm) ;
if (nargout < 2 && cm->status != CHOLMOD_OK)
{
mexErrMsgTxt ("matrix is not positive definite") ;
}
/* ---------------------------------------------------------------------- */
/* convert L to a sparse matrix */
/* ---------------------------------------------------------------------- */
/* the conversion sets L->minor back to n, so get a copy of it first */
minor = L->minor ;
Lsparse = cholmod_l_factor_to_sparse (L, cm) ;
if (Lsparse->xtype == CHOLMOD_COMPLEX)
{
/* convert Lsparse from complex to zomplex */
cholmod_l_sparse_xtype (CHOLMOD_ZOMPLEX, Lsparse, cm) ;
}
/* ---------------------------------------------------------------------- */
/* return results to MATLAB */
/* ---------------------------------------------------------------------- */
/* return L as a sparse matrix (it may contain numerically zero entries) */
pargout [0] = sputil_put_sparse (&Lsparse, cm) ;
/* return minor (translate to MATLAB convention) */
if (nargout > 1)
{
pargout [1] = mxCreateDoubleMatrix (1, 1, mxREAL) ;
px = mxGetPr (pargout [1]) ;
px [0] = ((minor == n) ? 0 : (minor+1)) ;
}
/* return permutation */
if (nargout > 2)
{
pargout [2] = sputil_put_int (L->Perm, n, 1) ;
}
/* ---------------------------------------------------------------------- */
/* free workspace and the CHOLMOD L, except for what is copied to MATLAB */
/* ---------------------------------------------------------------------- */
cholmod_l_free_factor (&L, cm) ;
cholmod_l_finish (cm) ;
cholmod_l_print_common (" ", cm) ;
/*
if (cm->malloc_count != 3 + mxIsComplex (pargout[0])) mexErrMsgTxt ("!") ;
*/
}
void mexFunction
(
int nargout,
mxArray *pargout [ ],
int nargin,
const mxArray *pargin [ ]
)
{
int ki;
double dummy = 0 ;
double *Lx, *Lx2 ;
Int *Li, *Lp, *Li2, *Lp2, *Lnz2, *ColCount ;
cholmod_sparse Cmatrix, *R, *Lsparse ;
cholmod_factor *L ;
cholmod_common Common, *cm ;
Int j, k, s, update, n, lnz ;
char buf [LEN] ;
/* ---------------------------------------------------------------------- */
/* start CHOLMOD and set parameters */
/* ---------------------------------------------------------------------- */
cm = &Common ;
cholmod_l_start (cm) ;
sputil_config (SPUMONI, cm) ;
/* ---------------------------------------------------------------------- */
/* check inputs */
/* ---------------------------------------------------------------------- */
if (nargout > 1 || nargin < 3 || nargin > 4)
{
mexErrMsgTxt ("Usage: L = ldlrowupdate (k, L, R, '+')") ;
}
n = mxGetN (pargin [1]) ;
k = mxGetN (pargin [2]) ;
if (!mxIsSparse (pargin [1]) || !mxIsSparse (pargin [2])
|| n != mxGetM (pargin [1]) || n != mxGetM (pargin [2])
|| mxIsComplex (pargin [1]) || mxIsComplex (pargin [2]))
{
k = mxGetM (pargin [2]);
j = mxGetM (pargin [1]);
printf("n=%d L=%d R=%d \n", n, j, k);
mexErrMsgTxt ("ldlrowupdate: R and/or L not sparse, complex, or wrong"
" dimensions") ;
}
/* ---------------------------------------------------------------------- */
/* determine if we're doing an update or downdate */
/* ---------------------------------------------------------------------- */
update = TRUE ;
if (nargin > 3 && mxIsChar (pargin [3]))
{
mxGetString (pargin [3], buf, LEN) ;
if (buf [0] == '-')
{
update = FALSE ;
}
else if (buf [0] != '+')
{
mexErrMsgTxt ("ldlrowupdate: update string must be '+' or '-'") ;
}
}
/* ---------------------------------------------------------------------- */
/* get ki: column integer of update */
/* ---------------------------------------------------------------------- */
ki = (int) *mxGetPr(pargin[0]);
ki = ki-1;
/* ---------------------------------------------------------------------- */
/* get R: sparse matrix of incoming/outgoing columns */
/* ---------------------------------------------------------------------- */
R = sputil_get_sparse (pargin [2], &Cmatrix, &dummy, 0) ;
/* ---------------------------------------------------------------------- */
/* construct a copy of the input sparse matrix L */
/* ---------------------------------------------------------------------- */
/* get the MATLAB L */
Lp = (Int *) mxGetJc (pargin [1]) ;
Li = (Int *) mxGetIr (pargin [1]) ;
Lx = mxGetPr (pargin [1]) ;
/* allocate the CHOLMOD symbolic L */
L = cholmod_l_allocate_factor (n, cm) ;
L->ordering = CHOLMOD_NATURAL ;
ColCount = L->ColCount ;
for (j = 0 ; j < n ; j++)
{
ColCount [j] = Lp [j+1] - Lp [j] ;
}
/* allocate space for a CHOLMOD LDL' packed factor */
cholmod_l_change_factor (CHOLMOD_REAL, FALSE, FALSE, TRUE, TRUE, L, cm) ;
/* copy MATLAB L into CHOLMOD L */
Lp2 = L->p ;
Li2 = L->i ;
Lx2 = L->x ;
Lnz2 = L->nz ;
lnz = L->nzmax ;
for (j = 0 ; j <= n ; j++)
{
Lp2 [j] = Lp [j] ;
}
for (j = 0 ; j < n ; j++)
{
Lnz2 [j] = Lp [j+1] - Lp [j] ;
}
for (s = 0 ; s < lnz ; s++)
{
Li2 [s] = Li [s] ;
}
for (s = 0 ; s < lnz ; s++)
{
Lx2 [s] = Lx [s] ;
}
/* ---------------------------------------------------------------------- */
/* update/downdate the LDL' factorization */
/* ---------------------------------------------------------------------- */
/* add row */
if (update){
if (!cholmod_l_rowadd (ki, R, L, cm))
{
mexErrMsgTxt ("rowadd failed\n") ;
}
}
/* delete row */
else {
if (!cholmod_l_rowdel (ki, NULL, L, cm))
{
mexErrMsgTxt ("rowdel failed\n") ;
}
}
/* ---------------------------------------------------------------------- */
/* copy the results back to MATLAB */
/* ---------------------------------------------------------------------- */
/* change L back to packed LDL' (it may have become unpacked if the
* sparsity pattern changed). This change takes O(n) time if the pattern
* of L wasn't updated. */
Lsparse = cholmod_l_factor_to_sparse (L, cm) ;
/* return L as a sparse matrix */
pargout [0] = sputil_put_sparse (&Lsparse, cm) ;
/* ---------------------------------------------------------------------- */
/* free workspace and the CHOLMOD L, except for what is copied to MATLAB */
/* ---------------------------------------------------------------------- */
cholmod_l_free_factor (&L, cm) ;
cholmod_l_finish (cm) ;
cholmod_l_print_common (" ", cm) ;
/*
if (cm->malloc_count != 3 + mxIsComplex (pargout[0])) mexErrMsgTxt ("!") ;
*/
}
void mexFunction
(
int nargout,
mxArray *pargout [ ],
int nargin,
const mxArray *pargin [ ]
)
{
double dummy = 0, beta [2], *px, *C, *Ct, *C2, *fil, *Zt, *zt, done=1.0, *zz, dzero=0.0;
cholmod_sparse Amatrix, *A, *Lsparse ;
cholmod_factor *L ;
cholmod_common Common, *cm ;
Int minor, *It2, *Jt2 ;
mwIndex l, k2, h, k, i, j, ik, *I, *J, *Jt, *It, *I2, *J2, lfi, *w, *w2, *r;
mwSize nnz, nnzlow, m, n;
int nz = 0;
mwSignedIndex one=1, lfi_si;
mxArray *Am, *Bm;
char *uplo="L", *trans="N";
/* ---------------------------------------------------------------------- */
/* Only one input. We have to find first the Cholesky factorization. */
/* start CHOLMOD and set parameters */
/* ---------------------------------------------------------------------- */
if (nargin == 1) {
cm = &Common ;
cholmod_l_start (cm) ;
sputil_config (SPUMONI, cm) ;
/* convert to packed LDL' when done */
cm->final_asis = FALSE ;
cm->final_super = FALSE ;
cm->final_ll = FALSE ;
cm->final_pack = TRUE ;
cm->final_monotonic = TRUE ;
/* since numerically zero entries are NOT dropped from the symbolic
* pattern, we DO need to drop entries that result from supernodal
* amalgamation. */
cm->final_resymbol = TRUE ;
cm->quick_return_if_not_posdef = (nargout < 2) ;
}
/* This will disable the supernodal LL', which will be slow. */
/* cm->supernodal = CHOLMOD_SIMPLICIAL ; */
/* ---------------------------------------------------------------------- */
/* get inputs */
/* ---------------------------------------------------------------------- */
if (nargin > 3)
{
mexErrMsgTxt ("usage: Z = sinv(A), or Z = sinv(LD, 1)") ;
}
n = mxGetM (pargin [0]) ;
m = mxGetM (pargin [0]) ;
if (!mxIsSparse (pargin [0]))
{
mexErrMsgTxt ("A must be sparse") ;
}
if (n != mxGetN (pargin [0]))
{
mexErrMsgTxt ("A must be square") ;
}
/* Only one input. We have to find first the Cholesky factorization. */
if (nargin == 1) {
/* get sparse matrix A, use tril(A) */
A = sputil_get_sparse (pargin [0], &Amatrix, &dummy, -1) ;
A->stype = -1 ; /* use lower part of A */
beta [0] = 0 ;
beta [1] = 0 ;
/* ---------------------------------------------------------------------- */
/* analyze and factorize */
/* ---------------------------------------------------------------------- */
L = cholmod_l_analyze (A, cm) ;
cholmod_l_factorize_p (A, beta, NULL, 0, L, cm) ;
if (cm->status != CHOLMOD_OK)
{
mexErrMsgTxt ("matrix is not positive definite") ;
}
/* ---------------------------------------------------------------------- */
/* convert L to a sparse matrix */
/* ---------------------------------------------------------------------- */
Lsparse = cholmod_l_factor_to_sparse (L, cm) ;
if (Lsparse->xtype == CHOLMOD_COMPLEX)
{
mexErrMsgTxt ("matrix is complex") ;
}
/* ---------------------------------------------------------------------- */
/* Set the sparse Cholesky factorization in Matlab format */
/* ---------------------------------------------------------------------- */
/*Am = sputil_put_sparse (&Lsparse, cm) ;
I = mxGetIr(Am);
J = mxGetJc(Am);
C = mxGetPr(Am);
nnz = mxGetNzmax(Am); */
It2 = Lsparse->i;
Jt2 = Lsparse->p;
Ct = Lsparse->x;
nnz = (mwSize) Lsparse->nzmax;
Am = mxCreateSparse(m, m, nnz, mxREAL) ;
I = mxGetIr(Am);
J = mxGetJc(Am);
C = mxGetPr(Am);
for (j = 0 ; j < n+1 ; j++) J[j] = (mwIndex) Jt2[j];
for ( i = 0 ; i < nnz ; i++) {
I[i] = (mwIndex) It2[i];
C[i] = Ct[i];
}
cholmod_l_free_sparse (&Lsparse, cm) ;
/*FILE *out1 = fopen( "output1.txt", "w" );
if( out1 != NULL )
fprintf( out1, "Hello %d\n", nnz );
fclose (out1);*/
} else {
/* The cholesky factorization is given as an input. */
/* We have to copy it into workspace */
It = mxGetIr(pargin [0]);
Jt = mxGetJc(pargin [0]);
Ct = mxGetPr(pargin [0]);
nnz = mxGetNzmax(pargin [0]);
Am = mxCreateSparse(m, m, nnz, mxREAL) ;
I = mxGetIr(Am);
J = mxGetJc(Am);
C = mxGetPr(Am);
for (j = 0 ; j < n+1 ; j++) J[j] = Jt[j];
for ( i = 0 ; i < nnz ; i++) {
I[i] = It[i];
C[i] = Ct[i];
}
}
/* Evaluate the sparse inverse */
C[nnz-1] = 1.0/C[J[m-1]]; /* set the last element of sparse inverse */
fil = mxCalloc((mwSize)1,sizeof(double));
zt = mxCalloc((mwSize)1,sizeof(double));
Zt = mxCalloc((mwSize)1,sizeof(double));
zz = mxCalloc((mwSize)1,sizeof(double));
for (j=m-2;j!=-1;j--){
lfi = J[j+1]-(J[j]+1);
/* if (lfi > 0) */
if ( J[j+1] > (J[j]+1) )
{
/* printf("lfi = %u \n ", lfi);
printf("lfi*double = %u \n", (mwSize)lfi*sizeof(double));
printf("lfi*lfi*double = %u \n", (mwSize)lfi*(mwSize)lfi*sizeof(double));
printf("\n \n");
*/
fil = mxRealloc(fil,(mwSize)lfi*sizeof(double));
for (i=0;i<lfi;i++) fil[i] = C[J[j]+i+1]; /* take the j'th lower triangular column of the Cholesky */
zt = mxRealloc(zt,(mwSize)lfi*sizeof(double)); /* memory for the sparse inverse elements to be evaluated */
Zt = mxRealloc(Zt,(mwSize)lfi*(mwSize)lfi*sizeof(double)); /* memory for the needed sparse inverse elements */
/* Set the lower triangular for Zt */
k2 = 0;
for (k=J[j]+1;k<J[j+1];k++){
ik = I[k];
h = k2;
for (l=J[ik];l<=J[ik+1];l++){
if (I[l] == I[ J[j]+h+1 ]){
Zt[h+lfi*k2] = C[l];
h++;
}
}
k2++;
}
/* evaluate zt = fil*Zt */
lfi_si = (mwSignedIndex) lfi;
dsymv(uplo, &lfi_si, &done, Zt, &lfi_si, fil, &one, &dzero, zt, &one);
/* Set the evaluated sparse inverse elements, zt, into C */
k=lfi-1;
for (i = J[j+1]-1; i!=J[j] ; i--){
C[i] = -zt[k];
k--;
}
/* evaluate the j'th diagonal of sparse inverse */
dgemv(trans, &one, &lfi_si, &done, fil, &one, zt, &one, &dzero, zz, &one);
C[J[j]] = 1.0/C[J[j]] + zz[0];
}
else
{
/* evaluate the j'th diagonal of sparse inverse */
C[J[j]] = 1.0/C[J[j]];
}
}
/* Free the temporary variables */
mxFree(fil);
mxFree(zt);
mxFree(Zt);
mxFree(zz);
/* ---------------------------------------------------------------------- */
/* Permute the elements according to r(q) = 1:n */
/* Done only if the Cholesky was evaluated here */
/* ---------------------------------------------------------------------- */
if (nargin == 1) {
Bm = mxCreateSparse(m, m, nnz, mxREAL) ;
It = mxGetIr(Bm);
Jt = mxGetJc(Bm);
Ct = mxGetPr(Bm); /* Ct = C(r,r) */
r = (mwIndex *) L->Perm; /* fill reducing ordering */
w = mxCalloc(m,sizeof(mwIndex)); /* column counts of Am */
/* count entries in each column of Bm */
for (j=0; j<m; j++){
k = r ? r[j] : j ; /* column j of Bm is column k of Am */
for (l=J[j] ; l<J[j+1] ; l++){
i = I[l];
ik = r ? r[i] : i ; /* row i of Bm is row ik of Am */
w[ max(ik,k) ]++;
}
}
cumsum2(Jt, w, m);
for (j=0; j<m; j++){
k = r ? r[j] : j ; /* column j of Bm is column k of Am */
for (l=J[j] ; l<J[j+1] ; l++){
i= I[l];
ik = r ? r[i] : i ; /* row i of Bm is row ik of Am */
It [k2 = w[max(ik,k)]++ ] = min(ik,k);
Ct[k2] = C[l];
}
}
mxFree(w);
/* ---------------------------------------------------------------------- */
/* Transpose the permuted (upper triangular) matrix Bm into Am */
/* (this way we get sorted columns) */
/* ---------------------------------------------------------------------- */
w = mxCalloc(m,sizeof(mwIndex));
for (i=0 ; i<Jt[m] ; i++) w[It[i]]++; /* row counts of Bm */
cumsum2(J, w, m); /* row pointers */
for (j=0 ; j<m ; j++){
for (i=Jt[j] ; i<Jt[j+1] ; i++){
I[ l=w[ It[i] ]++ ] = j;
C[l] = Ct[i];
}
}
mxFree(w);
mxDestroyArray(Bm);
}
/* ---------------------------------------------------------------------- */
/* Fill the upper triangle of the sparse inverse */
/* ---------------------------------------------------------------------- */
w = mxCalloc(m,sizeof(mwIndex)); /* workspace */
w2 = mxCalloc(m,sizeof(mwIndex)); /* workspace */
for (k=0;k<J[m];k++) w[I[k]]++; /* row counts of the lower triangular */
for (k=0;k<m;k++) w2[k] = w[k] + J[k+1] - J[k] - 1; /* column counts of the sparse inverse */
nnz = (mwSize)2*nnz - m; /* The number of nonzeros in Z */
pargout[0] = mxCreateSparse(m,m,nnz,mxREAL); /* The sparse matrix */
It = mxGetIr(pargout[0]);
Jt = mxGetJc(pargout[0]);
Ct = mxGetPr(pargout[0]);
cumsum2(Jt, w2, m); /* column starting points */
for (j = 0 ; j < m ; j++){ /* fill the upper triangular */
for (k = J[j] ; k < J[j+1] ; k++){
It[l = w2[ I[k]]++] = j ; /* place C(i,j) as entry Ct(j,i) */
if (Ct) Ct[l] = C[k] ;
}
}
for (j = 0 ; j < m ; j++){ /* fill the lower triangular */
for (k = J[j]+1 ; k < J[j+1] ; k++){
It[l = w2[j]++] = I[k] ; /* place C(j,i) as entry Ct(j,i) */
if (Ct) Ct[l] = C[k] ;
}
}
mxFree(w2);
mxFree(w);
/* ---------------------------------------------------------------------- */
/* return to MATLAB */
/* ---------------------------------------------------------------------- */
/* ---------------------------------------------------------------------- */
/* free workspace and the CHOLMOD L, except for what is copied to MATLAB */
/* ---------------------------------------------------------------------- */
if (nargin == 1) {
cholmod_l_free_factor (&L, cm) ;
cholmod_l_finish (cm) ;
cholmod_l_print_common (" ", cm) ;
}
mxDestroyArray(Am);
}
void mexFunction
(
int nargout,
mxArray *pargout [ ],
int nargin,
const mxArray *pargin [ ]
)
{
double dummy = 0 ;
double *Lx, *Lx2, *Lz, *Lz2 ;
Long *Li, *Lp, *Lnz2, *Li2, *Lp2, *ColCount ;
cholmod_sparse *A, Amatrix, *Lsparse, *S ;
cholmod_factor *L ;
cholmod_common Common, *cm ;
Long j, s, n, lnz, is_complex ;
/* ---------------------------------------------------------------------- */
/* start CHOLMOD and set parameters */
/* ---------------------------------------------------------------------- */
cm = &Common ;
cholmod_l_start (cm) ;
sputil_config (SPUMONI, cm) ;
/* ---------------------------------------------------------------------- */
/* check inputs */
/* ---------------------------------------------------------------------- */
if (nargout > 1 || nargin != 2)
{
mexErrMsgTxt ("usage: L = resymbol (L, A)\n") ;
}
n = mxGetN (pargin [0]) ;
if (!mxIsSparse (pargin [0]) || n != mxGetM (pargin [0]))
{
mexErrMsgTxt ("resymbol: L must be sparse and square") ;
}
if (n != mxGetM (pargin [1]) || n != mxGetN (pargin [1]))
{
mexErrMsgTxt ("resymbol: A and L must have same dimensions") ;
}
/* ---------------------------------------------------------------------- */
/* get the sparse matrix A */
/* ---------------------------------------------------------------------- */
A = sputil_get_sparse_pattern (pargin [1], &Amatrix, &dummy, cm) ;
S = (A == &Amatrix) ? NULL : A ;
A->stype = -1 ;
/* A = sputil_get_sparse (pargin [1], &Amatrix, &dummy, -1) ; */
/* ---------------------------------------------------------------------- */
/* construct a copy of the input sparse matrix L */
/* ---------------------------------------------------------------------- */
/* get the MATLAB L */
Lp = (Long *) mxGetJc (pargin [0]) ;
Li = (Long *) mxGetIr (pargin [0]) ;
Lx = mxGetPr (pargin [0]) ;
Lz = mxGetPi (pargin [0]) ;
is_complex = mxIsComplex (pargin [0]) ;
/* allocate the CHOLMOD symbolic L */
L = cholmod_l_allocate_factor (n, cm) ;
L->ordering = CHOLMOD_NATURAL ;
ColCount = L->ColCount ;
for (j = 0 ; j < n ; j++)
{
ColCount [j] = Lp [j+1] - Lp [j] ;
}
/* allocate space for a CHOLMOD LDL' packed factor */
/* (LL' and LDL' are treated identically) */
cholmod_l_change_factor (is_complex ? CHOLMOD_ZOMPLEX : CHOLMOD_REAL,
FALSE, FALSE, TRUE, TRUE, L, cm) ;
/* copy MATLAB L into CHOLMOD L */
Lp2 = L->p ;
Li2 = L->i ;
Lx2 = L->x ;
Lz2 = L->z ;
Lnz2 = L->nz ;
lnz = L->nzmax ;
for (j = 0 ; j <= n ; j++)
{
Lp2 [j] = Lp [j] ;
}
for (j = 0 ; j < n ; j++)
{
Lnz2 [j] = Lp [j+1] - Lp [j] ;
}
for (s = 0 ; s < lnz ; s++)
{
Li2 [s] = Li [s] ;
}
for (s = 0 ; s < lnz ; s++)
{
Lx2 [s] = Lx [s] ;
}
if (is_complex)
{
for (s = 0 ; s < lnz ; s++)
{
Lz2 [s] = Lz [s] ;
}
}
/* ---------------------------------------------------------------------- */
/* resymbolic factorization */
/* ---------------------------------------------------------------------- */
cholmod_l_resymbol (A, NULL, 0, TRUE, L, cm) ;
/* ---------------------------------------------------------------------- */
/* copy the results back to MATLAB */
/* ---------------------------------------------------------------------- */
Lsparse = cholmod_l_factor_to_sparse (L, cm) ;
/* return L as a sparse matrix */
pargout [0] = sputil_put_sparse (&Lsparse, cm) ;
/* ---------------------------------------------------------------------- */
/* free workspace and the CHOLMOD L, except for what is copied to MATLAB */
/* ---------------------------------------------------------------------- */
cholmod_l_free_factor (&L, cm) ;
cholmod_l_free_sparse (&S, cm) ;
cholmod_l_finish (cm) ;
cholmod_l_print_common (" ", cm) ;
/*
if (cm->malloc_count != 3 + mxIsComplex (pargout[0])) mexErrMsgTxt ("!") ;
*/
}
void mexFunction
(
int nargout,
mxArray *pargout [ ],
int nargin,
const mxArray *pargin [ ]
)
{
double dummy = 0 ;
double *Lx, *Lx2 ;
Long *Li, *Lp, *Li2, *Lp2, *Lnz2, *ColCount ;
cholmod_sparse Cmatrix, *C, *Lsparse ;
cholmod_factor *L ;
cholmod_common Common, *cm ;
Long j, k, s, rowadd, n, lnz, ok ;
/* ---------------------------------------------------------------------- */
/* start CHOLMOD and set parameters */
/* ---------------------------------------------------------------------- */
cm = &Common ;
cholmod_l_start (cm) ;
sputil_config (SPUMONI, cm) ;
/* ---------------------------------------------------------------------- */
/* check inputs */
/* ---------------------------------------------------------------------- */
if (nargout > 1 || nargin < 2 || nargin > 3)
{
mexErrMsgTxt ("Usage: LD = ldlrowmod (LD,k,C) or ldlrowmod (LD,k)") ;
}
n = mxGetN (pargin [0]) ;
k = (Long) mxGetScalar (pargin [1]) ;
k = k - 1 ; /* change from 1-based to 0-based */
if (!mxIsSparse (pargin [0])
|| n != mxGetM (pargin [0])
|| mxIsComplex (pargin [0]))
{
mexErrMsgTxt ("ldlrowmod: L must be real, square, and sparse") ;
}
/* ---------------------------------------------------------------------- */
/* determine if we're doing an rowadd or rowdel */
/* ---------------------------------------------------------------------- */
rowadd = (nargin > 2) ;
if (rowadd)
{
if (!mxIsSparse (pargin [2])
|| n != mxGetM (pargin [2])
|| 1 != mxGetN (pargin [2])
|| mxIsComplex (pargin [2]))
{
mexErrMsgTxt ("ldlrowmod: C must be a real sparse vector, "
"with the same number of rows as LD") ;
}
}
/* ---------------------------------------------------------------------- */
/* get C: sparse vector of incoming/outgoing column */
/* ---------------------------------------------------------------------- */
C = (rowadd) ? sputil_get_sparse (pargin [2], &Cmatrix, &dummy, 0) : NULL ;
/* ---------------------------------------------------------------------- */
/* construct a copy of the input sparse matrix L */
/* ---------------------------------------------------------------------- */
/* get the MATLAB L */
Lp = (Long *) mxGetJc (pargin [0]) ;
Li = (Long *) mxGetIr (pargin [0]) ;
Lx = mxGetPr (pargin [0]) ;
/* allocate the CHOLMOD symbolic L */
L = cholmod_l_allocate_factor (n, cm) ;
L->ordering = CHOLMOD_NATURAL ;
ColCount = L->ColCount ;
for (j = 0 ; j < n ; j++)
{
ColCount [j] = Lp [j+1] - Lp [j] ;
}
/* allocate space for a CHOLMOD LDL' packed factor */
cholmod_l_change_factor (CHOLMOD_REAL, FALSE, FALSE, TRUE, TRUE, L, cm) ;
/* copy MATLAB L into CHOLMOD L */
Lp2 = L->p ;
Li2 = L->i ;
Lx2 = L->x ;
Lnz2 = L->nz ;
lnz = L->nzmax ;
for (j = 0 ; j <= n ; j++)
{
Lp2 [j] = Lp [j] ;
}
for (j = 0 ; j < n ; j++)
{
Lnz2 [j] = Lp [j+1] - Lp [j] ;
}
for (s = 0 ; s < lnz ; s++)
{
Li2 [s] = Li [s] ;
}
for (s = 0 ; s < lnz ; s++)
{
Lx2 [s] = Lx [s] ;
}
/* ---------------------------------------------------------------------- */
/* rowadd/rowdel the LDL' factorization */
/* ---------------------------------------------------------------------- */
if (rowadd)
{
ok = cholmod_l_rowadd (k, C, L, cm) ;
}
else
{
ok = cholmod_l_rowdel (k, NULL, L, cm) ;
}
if (!ok) mexErrMsgTxt ("ldlrowmod failed\n") ;
/* ---------------------------------------------------------------------- */
/* copy the results back to MATLAB */
/* ---------------------------------------------------------------------- */
/* change L back to packed LDL' (it may have become unpacked if the
* sparsity pattern changed). This change takes O(n) time if the pattern
* of L wasn't updated. */
Lsparse = cholmod_l_factor_to_sparse (L, cm) ;
/* return L as a sparse matrix */
pargout [0] = sputil_put_sparse (&Lsparse, cm) ;
/* ---------------------------------------------------------------------- */
/* free workspace and the CHOLMOD L, except for what is copied to MATLAB */
/* ---------------------------------------------------------------------- */
cholmod_l_free_factor (&L, cm) ;
cholmod_l_finish (cm) ;
cholmod_l_print_common (" ", cm) ;
/*
if (cm->malloc_count != 3 + mxIsComplex (pargout[0])) mexErrMsgTxt ("!") ;
*/
}
