Diff of /pkg/Matrix/src/Csparse.c

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	pkg/src/Csparse.c revision 1657, Wed Nov 1 16:29:53 2006 UTC	pkg/Matrix/src/Csparse.c revision 3069, Thu Mar 26 10:00:49 2015 UTC
#	Line 1	Line 1
1	/* Sparse matrices in compressed column-oriented form */	/* Sparse matrices in compressed column-oriented form */
2
3	#include "Csparse.h"	#include "Csparse.h"
4		#include "Tsparse.h"
5	#include "chm_common.h"	#include "chm_common.h"
6
7	SEXP Csparse_validate(SEXP x)	/** "Cheap" C version of  Csparse_validate() - *not* sorting : */
8		Rboolean isValid_Csparse(SEXP x)
9	{	{
10	/* NB: we do *NOT* check a potential 'x' slot here, at all */	/* NB: we do *NOT* check a potential 'x' slot here, at all */
11	SEXP pslot = GET_SLOT(x, Matrix_pSym),	SEXP pslot = GET_SLOT(x, Matrix_pSym),
12	islot = GET_SLOT(x, Matrix_iSym);	islot = GET_SLOT(x, Matrix_iSym);
13	int j, k, ncol, nrow, sorted,	int *dims = INTEGER(GET_SLOT(x, Matrix_DimSym)), j,
14	*dims = INTEGER(GET_SLOT(x, Matrix_DimSym)),	nrow = dims[0],
15		ncol = dims[1],
16	*xp = INTEGER(pslot),	*xp = INTEGER(pslot),
17	*xi = INTEGER(islot);	*xi = INTEGER(islot);
18
	nrow = dims[0];
	ncol = dims[1];
19	if (length(pslot) != dims[1] + 1)	if (length(pslot) != dims[1] + 1)
20	return mkString(_("slot p must have length = ncol(.) + 1"));	return FALSE;
21	if (xp[0] != 0)	if (xp[0] != 0)
22	return mkString(_("first element of slot p must be zero"));	return FALSE;
23	if (length(islot) != xp[ncol])	if (length(islot) < xp[ncol]) /* allow larger slots from over-allocation!*/
24	return	return FALSE;
25	mkString(_("last element of slot p must match length of slots i and x"));	for (j = 0; j < xp[ncol]; j++) {
	for (j = 0; j < length(islot); j++) {
26	if (xi[j] < 0 || xi[j] >= nrow)	if (xi[j] < 0 || xi[j] >= nrow)
27	return mkString(_("all row indices must be between 0 and nrow-1"));	return FALSE;
28	}	}
	sorted = TRUE;
29	for (j = 0; j < ncol; j++) {	for (j = 0; j < ncol; j++) {
30	if (xp[j] > xp[j+1])	if (xp[j] > xp[j+1])
31		return FALSE;
32		}
33		return TRUE;
34		}
35
36		SEXP Csparse_validate(SEXP x) {
37		return Csparse_validate_(x, FALSE);
38		}
39
40
41		#define _t_Csparse_validate
42		#include "t_Csparse_validate.c"
43
44		#define _t_Csparse_sort
45		#include "t_Csparse_validate.c"
46
47		// R: .validateCsparse(x, sort.if.needed = FALSE) :
48		SEXP Csparse_validate2(SEXP x, SEXP maybe_modify) {
49		return Csparse_validate_(x, asLogical(maybe_modify));
50		}
51
52		// R: Matrix:::.sortCsparse(x) :
53		SEXP Csparse_sort (SEXP x) {
54		int ok = Csparse_sort_2(x, TRUE); // modifying x directly
55		if(!ok) warning(_("Csparse_sort(x): x is not a valid (apart from sorting) CsparseMatrix"));
56		return x;
57		}
58
59		SEXP Rsparse_validate(SEXP x)
60		{
61		/* NB: we do *NOT* check a potential 'x' slot here, at all */
62		SEXP pslot = GET_SLOT(x, Matrix_pSym),
63		jslot = GET_SLOT(x, Matrix_jSym);
64		Rboolean sorted, strictly;
65		int i, k,
66		*dims = INTEGER(GET_SLOT(x, Matrix_DimSym)),
67		nrow = dims[0],
68		ncol = dims[1],
69		*xp = INTEGER(pslot),
70		*xj = INTEGER(jslot);
71
72		if (length(pslot) != dims[0] + 1)
73		return mkString(_("slot p must have length = nrow(.) + 1"));
74		if (xp[0] != 0)
75		return mkString(_("first element of slot p must be zero"));
76		if (length(jslot) < xp[nrow]) /* allow larger slots from over-allocation!*/
77		return
78		mkString(_("last element of slot p must match length of slots j and x"));
79		for (i = 0; i < length(jslot); i++) {
80		if (xj[i] < 0 || xj[i] >= ncol)
81		return mkString(_("all column indices must be between 0 and ncol-1"));
82		}
83		sorted = TRUE; strictly = TRUE;
84		for (i = 0; i < nrow; i++) {
85		if (xp[i] > xp[i+1])
86	return mkString(_("slot p must be non-decreasing"));	return mkString(_("slot p must be non-decreasing"));
87	for (k = xp[j] + 1; k < xp[j + 1]; k++)	if(sorted)
88	if (xi[k] < xi[k - 1]) sorted = FALSE;	for (k = xp[i] + 1; k < xp[i + 1]; k++) {
89		if (xj[k] < xj[k - 1])
90		sorted = FALSE;
91		else if (xj[k] == xj[k - 1])
92		strictly = FALSE;
93	}	}
	if (!sorted) {
	cholmod_sparse *chx = as_cholmod_sparse(x);
	cholmod_sort(chx, &c);
	Free(chx);
94	}	}
95		if (!sorted)
96		/* cannot easily use cholmod_sort(.) ... -> "error out" :*/
97		return mkString(_("slot j is not increasing inside a column"));
98		else if(!strictly) /* sorted, but not strictly */
99		return mkString(_("slot j is not *strictly* increasing inside a column"));
100
101	return ScalarLogical(1);	return ScalarLogical(1);
102	}	}
103
104	SEXP Csparse_to_dense(SEXP x)	/**
105		* From a CsparseMatrix, produce a dense one.
106		* Directly deals with symmetric, triangular and general.
107		* Called from ../R/Csparse.R's  C2dense()
108		*
109		* @param x a CsparseMatrix: currently all 9 of  "[dln][gst]CMatrix"
110		* @param symm_or_tri integer (NA, < 0, > 0, = 0) specifying the knowledge of the caller about x:
111		*      NA  : unknown => will be determined
112		*      = 0 : "generalMatrix" (not symm or tri);
113		*      < 0 : "triangularMatrix"
114		*      > 0 : "symmetricMatrix"
115		*
116		* @return a "denseMatrix"
117		*/
118		SEXP Csparse_to_dense(SEXP x, SEXP symm_or_tri)
119	{	{
120	cholmod_sparse *chxs = as_cholmod_sparse(x);	Rboolean is_sym, is_tri;
121	cholmod_dense *chxd = cholmod_sparse_to_dense(chxs, &c);	int is_sym_or_tri = asInteger(symm_or_tri),
122		ctype = 0; // <- default = "dgC"
123	Free(chxs);	static const char *valid[] = { MATRIX_VALID_Csparse, ""};
124	return chm_dense_to_SEXP(chxd, 1, Real_kind(x));	if(is_sym_or_tri == NA_INTEGER) { // find if  is(x, "symmetricMatrix") :
125		ctype = Matrix_check_class_etc(x, valid);
126		is_sym = (ctype % 3 == 1);
127		is_tri = (ctype % 3 == 2);
128		} else {
129		is_sym = is_sym_or_tri > 0;
130		is_tri = is_sym_or_tri < 0;
131		// => both are FALSE  iff  is_.. == 0
132		if(is_sym || is_tri)
133		ctype = Matrix_check_class_etc(x, valid);
134		}
135		CHM_SP chxs = AS_CHM_SP__(x);// -> chxs->stype = +- 1 <==> symmetric
136		R_CheckStack();
137		if(is_tri && *diag_P(x) == 'U') { // ==>  x := diagU2N(x), directly for chxs
138		CHM_SP eye = cholmod_speye(chxs->nrow, chxs->ncol, chxs->xtype, &c);
139		double one[] = {1, 0};
140		CHM_SP ans = cholmod_add(chxs, eye, one, one,
141		/* values: */ ((ctype / 3) != 2), // TRUE iff not "nMatrix"
142		TRUE, &c);
143		cholmod_free_sparse(&eye, &c);
144		chxs = cholmod_copy_sparse(ans, &c);
145		cholmod_free_sparse(&ans, &c);
146		}
147		/* The following loses the symmetry property, since cholmod_dense has none,
148		* BUT, much worse (FIXME!), it also transforms CHOLMOD_PATTERN ("n") matrices
149		* to numeric (CHOLMOD_REAL) ones {and we "revert" via chm_dense_to_SEXP()}: */
150		CHM_DN chxd = cholmod_sparse_to_dense(chxs, &c);
151		int Rkind = (chxs->xtype == CHOLMOD_PATTERN)? -1 : Real_kind(x);
152
153		SEXP ans = chm_dense_to_SEXP(chxd, 1, Rkind, GET_SLOT(x, Matrix_DimNamesSym),
154		/* transp: */ FALSE);
155		// -> a [dln]geMatrix
156		if(is_sym) { // ==> want  [dln]syMatrix
157		const char cl1 = class_P(ans)[0];
158		PROTECT(ans);
159		SEXP aa = PROTECT(NEW_OBJECT(MAKE_CLASS((cl1 == 'd') ? "dsyMatrix" :
160		((cl1 == 'l') ? "lsyMatrix" : "nsyMatrix"))));
161		// No need to duplicate() as slots of ans are freshly allocated and ans will not be used
162		SET_SLOT(aa, Matrix_xSym,       GET_SLOT(ans, Matrix_xSym));
163		SET_SLOT(aa, Matrix_DimSym,     GET_SLOT(ans, Matrix_DimSym));
164		SET_SLOT(aa, Matrix_DimNamesSym,GET_SLOT(ans, Matrix_DimNamesSym));
165		SET_SLOT(aa, Matrix_uploSym, mkString((chxs->stype > 0) ? "U" : "L"));
166		UNPROTECT(2);
167		return aa;
168		}
169		else if(is_tri) { // ==> want  [dln]trMatrix
170		const char cl1 = class_P(ans)[0];
171		PROTECT(ans);
172		SEXP aa = PROTECT(NEW_OBJECT(MAKE_CLASS((cl1 == 'd') ? "dtrMatrix" :
173		((cl1 == 'l') ? "ltrMatrix" : "ntrMatrix"))));
174		// No need to duplicate() as slots of ans are freshly allocated and ans will not be used
175		SET_SLOT(aa, Matrix_xSym,       GET_SLOT(ans, Matrix_xSym));
176		SET_SLOT(aa, Matrix_DimSym,     GET_SLOT(ans, Matrix_DimSym));
177		SET_SLOT(aa, Matrix_DimNamesSym,GET_SLOT(ans, Matrix_DimNamesSym));
178		slot_dup(aa, x, Matrix_uploSym);
179		/* already by NEW_OBJECT(..) above:
180		SET_SLOT(aa, Matrix_diagSym, mkString("N")); */
181		UNPROTECT(2);
182		return aa;
183		}
184		else
185		return ans;
186	}	}
187
188		// FIXME: do not go via CHM (should not be too hard, to just *drop* the x-slot, right?
189	SEXP Csparse_to_nz_pattern(SEXP x, SEXP tri)	SEXP Csparse_to_nz_pattern(SEXP x, SEXP tri)
190	{	{
191	cholmod_sparse *chxs = as_cholmod_sparse(x);	CHM_SP chxs = AS_CHM_SP__(x);
192	cholmod_sparse	CHM_SP chxcp = cholmod_copy(chxs, chxs->stype, CHOLMOD_PATTERN, &c);
193	*chxcp = cholmod_copy(chxs, chxs->stype, CHOLMOD_PATTERN, &c);	int tr = asLogical(tri);
194	int uploT = 0; char *diag = "";	R_CheckStack();
195
196	Free(chxs);	return chm_sparse_to_SEXP(chxcp, 1/*do_free*/,
197	if (asLogical(tri)) {       /* triangular sparse matrices */	tr ? ((*uplo_P(x) == 'U') ? 1 : -1) : 0,
198	uploT = (strcmp(CHAR(asChar(GET_SLOT(x, Matrix_uploSym))), "U")) ?	/* Rkind: pattern */ 0,
199	-1 : 1;	/* diag = */ tr ? diag_P(x) : "",
	diag = CHAR(asChar(GET_SLOT(x, Matrix_diagSym)));
	}
	return chm_sparse_to_SEXP(chxcp, 1, uploT, 0, diag,
200	GET_SLOT(x, Matrix_DimNamesSym));	GET_SLOT(x, Matrix_DimNamesSym));
201	}	}
202
203	SEXP Csparse_to_matrix(SEXP x)	// n.CMatrix --> [dli].CMatrix  (not going through CHM!)
204		SEXP nz_pattern_to_Csparse(SEXP x, SEXP res_kind)
205	{	{
206	cholmod_sparse *chxs = as_cholmod_sparse(x);	return nz2Csparse(x, asInteger(res_kind));
207	cholmod_dense *chxd = cholmod_sparse_to_dense(chxs, &c);	}
208
209	Free(chxs);	// n.CMatrix --> [dli].CMatrix  (not going through CHM!)
210	return chm_dense_to_matrix(chxd, 1,	// NOTE: use chm_MOD_xtype(() to change type of  'cholmod_sparse' matrix
211	GET_SLOT(x, Matrix_DimNamesSym));	SEXP nz2Csparse(SEXP x, enum x_slot_kind r_kind)
212		{
213		const char *cl_x = class_P(x);
214		if(cl_x[0] != 'n') error(_("not a 'n.CMatrix'"));
215		if(cl_x[2] != 'C') error(_("not a CsparseMatrix"));
216		int nnz = LENGTH(GET_SLOT(x, Matrix_iSym));
217		SEXP ans;
218		char *ncl = alloca(strlen(cl_x) + 1); /* not much memory required */
219		strcpy(ncl, cl_x);
220		double *dx_x; int *ix_x;
221		ncl[0] = (r_kind == x_double ? 'd' :
222		(r_kind == x_logical ? 'l' :
223		/* else (for now):  r_kind == x_integer : */ 'i'));
224		PROTECT(ans = NEW_OBJECT(MAKE_CLASS(ncl)));
225		// create a correct 'x' slot:
226		switch(r_kind) {
227		int i;
228		case x_double: // 'd'
229		dx_x = REAL(ALLOC_SLOT(ans, Matrix_xSym, REALSXP, nnz));
230		for (i=0; i < nnz; i++) dx_x[i] = 1.;
231		break;
232		case x_logical: // 'l'
233		ix_x = LOGICAL(ALLOC_SLOT(ans, Matrix_xSym, LGLSXP, nnz));
234		for (i=0; i < nnz; i++) ix_x[i] = TRUE;
235		break;
236		case x_integer: // 'i'
237		ix_x = INTEGER(ALLOC_SLOT(ans, Matrix_xSym, INTSXP, nnz));
238		for (i=0; i < nnz; i++) ix_x[i] = 1;
239		break;
240
241		default:
242		error(_("nz2Csparse(): invalid/non-implemented r_kind = %d"),
243		r_kind);
244		}
245
246		// now copy all other slots :
247		slot_dup(ans, x, Matrix_iSym);
248		slot_dup(ans, x, Matrix_pSym);
249		slot_dup(ans, x, Matrix_DimSym);
250		slot_dup(ans, x, Matrix_DimNamesSym);
251		if(ncl[1] != 'g') { // symmetric or triangular ...
252		slot_dup_if_has(ans, x, Matrix_uploSym);
253		slot_dup_if_has(ans, x, Matrix_diagSym);
254		}
255		UNPROTECT(1);
256		return ans;
257		}
258
259		SEXP Csparse_to_matrix(SEXP x, SEXP chk, SEXP symm)
260		{
261		int is_sym = asLogical(symm);
262		if(is_sym == NA_LOGICAL) { // find if  is(x, "symmetricMatrix") :
263		static const char *valid[] = { MATRIX_VALID_Csparse, ""};
264		int ctype = Matrix_check_class_etc(x, valid);
265		is_sym = (ctype % 3 == 1);
266		}
267		return chm_dense_to_matrix(
268		cholmod_sparse_to_dense(AS_CHM_SP2(x, asLogical(chk)), &c),
269		1 /*do_free*/,
270		(is_sym
271		? symmetric_DimNames(GET_SLOT(x, Matrix_DimNamesSym))
272		:                    GET_SLOT(x, Matrix_DimNamesSym)));
273		}
274
275		SEXP Csparse_to_vector(SEXP x)
276		{
277		return chm_dense_to_vector(cholmod_sparse_to_dense(AS_CHM_SP__(x), &c), 1);
278	}	}
279
280	SEXP Csparse_to_Tsparse(SEXP x, SEXP tri)	SEXP Csparse_to_Tsparse(SEXP x, SEXP tri)
281	{	{
282	cholmod_sparse *chxs = as_cholmod_sparse(x);	CHM_SP chxs = AS_CHM_SP__(x);
283	cholmod_triplet *chxt = cholmod_sparse_to_triplet(chxs, &c);	CHM_TR chxt = cholmod_sparse_to_triplet(chxs, &c);
284	int uploT = 0;	int tr = asLogical(tri);
285	char *diag = "";	int Rkind = (chxs->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
286	int Rkind = (chxs->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;	R_CheckStack();
287
288		return chm_triplet_to_SEXP(chxt, 1,
289		tr ? ((*uplo_P(x) == 'U') ? 1 : -1) : 0,
290		Rkind, tr ? diag_P(x) : "",
291		GET_SLOT(x, Matrix_DimNamesSym));
292		}
293
294	Free(chxs);	SEXP Csparse_to_tCsparse(SEXP x, SEXP uplo, SEXP diag)
295	if (asLogical(tri)) {       /* triangular sparse matrices */	{
296	uploT = (*uplo_P(x) == 'U') ? -1 : 1;	CHM_SP chxs = AS_CHM_SP__(x);
297	diag = diag_P(x);	int Rkind = (chxs->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
298		R_CheckStack();
299		return chm_sparse_to_SEXP(chxs, /* dofree = */ 0,
300		/* uploT = */ (*CHAR(asChar(uplo)) == 'U')? 1: -1,
301		Rkind, /* diag = */ CHAR(STRING_ELT(diag, 0)),
302		GET_SLOT(x, Matrix_DimNamesSym));
303	}	}
304	return chm_triplet_to_SEXP(chxt, 1, uploT, Rkind, diag,
305		SEXP Csparse_to_tTsparse(SEXP x, SEXP uplo, SEXP diag)
306		{
307		CHM_SP chxs = AS_CHM_SP__(x);
308		CHM_TR chxt = cholmod_sparse_to_triplet(chxs, &c);
309		int Rkind = (chxs->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
310		R_CheckStack();
311		return chm_triplet_to_SEXP(chxt, 1,
312		/* uploT = */ (*CHAR(asChar(uplo)) == 'U')? 1: -1,
313		Rkind, /* diag = */ CHAR(STRING_ELT(diag, 0)),
314	GET_SLOT(x, Matrix_DimNamesSym));	GET_SLOT(x, Matrix_DimNamesSym));
315	}	}
316
317	/* this used to be called  sCMatrix_to_gCMatrix(..)   [in ./dsCMatrix.c ]: */
318	SEXP Csparse_symmetric_to_general(SEXP x)	SEXP Csparse_symmetric_to_general(SEXP x)
319	{	{
320	cholmod_sparse *chx = as_cholmod_sparse(x), *chgx;	CHM_SP chx = AS_CHM_SP__(x), chgx;
321	int Rkind = (chx->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;	int Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
322		R_CheckStack();
323
324	if (!(chx->stype))	if (!(chx->stype))
325	error(_("Nonsymmetric matrix in Csparse_symmetric_to_general"));	error(_("Nonsymmetric matrix in Csparse_symmetric_to_general"));
326	chgx = cholmod_copy(chx, /* stype: */ 0, chx->xtype, &c);	chgx = cholmod_copy(chx, /* stype: */ 0, chx->xtype, &c);
327	/* xtype: pattern, "real", complex or .. */	/* xtype: pattern, "real", complex or .. */
	Free(chx);
328	return chm_sparse_to_SEXP(chgx, 1, 0, Rkind, "",	return chm_sparse_to_SEXP(chgx, 1, 0, Rkind, "",
329	GET_SLOT(x, Matrix_DimNamesSym));	symmetric_DimNames(GET_SLOT(x, Matrix_DimNamesSym)));
330	}	}
331
332	SEXP Csparse_general_to_symmetric(SEXP x, SEXP uplo)	SEXP Csparse_general_to_symmetric(SEXP x, SEXP uplo, SEXP sym_dmns)
333	{	{
334	cholmod_sparse *chx = as_cholmod_sparse(x), *chgx;	int *adims = INTEGER(GET_SLOT(x, Matrix_DimSym)), n = adims[0];
335	int uploT = (*CHAR(asChar(uplo)) == 'U') ? -1 : 1;	if(n != adims[1]) {
336	int Rkind = (chx->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;	error(_("Csparse_general_to_symmetric(): matrix is not square!"));
337		return R_NilValue; /* -Wall */
338		}
339		CHM_SP chx = AS_CHM_SP__(x), chgx;
340		int uploT = (*CHAR(asChar(uplo)) == 'U') ? 1 : -1;
341		int Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
342		R_CheckStack();
343	chgx = cholmod_copy(chx, /* stype: */ uploT, chx->xtype, &c);	chgx = cholmod_copy(chx, /* stype: */ uploT, chx->xtype, &c);
344
345		SEXP dns = GET_SLOT(x, Matrix_DimNamesSym);
346		if(asLogical(sym_dmns))
347		dns = symmetric_DimNames(dns);
348		else if((!isNull(VECTOR_ELT(dns, 0)) &&
349		!isNull(VECTOR_ELT(dns, 1))) ||
350		!isNull(getAttrib(dns, R_NamesSymbol))) {
351		/* symmetrize them if both are not NULL
352		* or names(dimnames(.)) is asymmetric : */
353		dns = PROTECT(duplicate(dns));
354		if(!equal_string_vectors(VECTOR_ELT(dns, 0),
355		VECTOR_ELT(dns, 1))) {
356		if(uploT == 1)
357		SET_VECTOR_ELT(dns, 0, VECTOR_ELT(dns,1));
358		else
359		SET_VECTOR_ELT(dns, 1, VECTOR_ELT(dns,0));
360		}
361		SEXP nms_dns = getAttrib(dns, R_NamesSymbol);
362		if(!isNull(nms_dns) &&  // names(dimnames(.)) :
363		!R_compute_identical(STRING_ELT(nms_dns, 0),
364		STRING_ELT(nms_dns, 1), 16)) {
365		if(uploT == 1)
366		SET_STRING_ELT(nms_dns, 0, STRING_ELT(nms_dns,1));
367		else
368		SET_STRING_ELT(nms_dns, 1, STRING_ELT(nms_dns,0));
369		setAttrib(dns, R_NamesSymbol, nms_dns);
370		}
371		UNPROTECT(1);
372		}
373	/* xtype: pattern, "real", complex or .. */	/* xtype: pattern, "real", complex or .. */
374	Free(chx);	return chm_sparse_to_SEXP(chgx, 1, 0, Rkind, "", dns);
	return chm_sparse_to_SEXP(chgx, 1, 0, Rkind, "",
	GET_SLOT(x, Matrix_DimNamesSym));
375	}	}
376
377	SEXP Csparse_transpose(SEXP x, SEXP tri)	SEXP Csparse_transpose(SEXP x, SEXP tri)
378	{	{
379	cholmod_sparse *chx = as_cholmod_sparse(x);	/* TODO: lgCMatrix & igC* currently go via double prec. cholmod -
380	int Rkind = (chx->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;	*       since cholmod (& cs) lacks sparse 'int' matrices */
381	cholmod_sparse *chxt = cholmod_transpose(chx, (int) chx->xtype, &c);	CHM_SP chx = AS_CHM_SP__(x);
382		int Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
383		CHM_SP chxt = cholmod_transpose(chx, chx->xtype, &c);
384	SEXP dn = PROTECT(duplicate(GET_SLOT(x, Matrix_DimNamesSym))), tmp;	SEXP dn = PROTECT(duplicate(GET_SLOT(x, Matrix_DimNamesSym))), tmp;
385	int uploT = 0; char *diag = "";	int tr = asLogical(tri);
386		R_CheckStack();
387
	Free(chx);
388	tmp = VECTOR_ELT(dn, 0);    /* swap the dimnames */	tmp = VECTOR_ELT(dn, 0);    /* swap the dimnames */
389	SET_VECTOR_ELT(dn, 0, VECTOR_ELT(dn, 1));	SET_VECTOR_ELT(dn, 0, VECTOR_ELT(dn, 1));
390	SET_VECTOR_ELT(dn, 1, tmp);	SET_VECTOR_ELT(dn, 1, tmp);
391		if(!isNull(tmp = getAttrib(dn, R_NamesSymbol))) { // swap names(dimnames(.)):
392		SEXP nms_dns = PROTECT(allocVector(VECSXP, 2));
393		SET_VECTOR_ELT(nms_dns, 1, STRING_ELT(tmp, 0));
394		SET_VECTOR_ELT(nms_dns, 0, STRING_ELT(tmp, 1));
395		setAttrib(dn, R_NamesSymbol, nms_dns);
396	UNPROTECT(1);	UNPROTECT(1);
	if (asLogical(tri)) {       /* triangular sparse matrices */
	uploT = (*uplo_P(x) == 'U') ? -1 : 1;
	diag = diag_P(x);
	}
	return chm_sparse_to_SEXP(chxt, 1, uploT, Rkind, diag, dn);
397	}	}
398		UNPROTECT(1);
399		return chm_sparse_to_SEXP(chxt, 1, /* SWAP 'uplo' for triangular */
400		tr ? ((*uplo_P(x) == 'U') ? -1 : 1) : 0,
401		Rkind, tr ? diag_P(x) : "", dn);
402		}
403
404		/* NOTA BENE:  cholmod_ssmult(A,B, ...) ->  ./CHOLMOD/MatrixOps/cholmod_ssmult.c
405		* ---------  computes a patter*n* matrix __always_ when
406		* *one* of A or B is pattern*n*, because of this (line 73-74):
407		---------------------------------------------------------------------------
408		values = values &&
409		(A->xtype != CHOLMOD_PATTERN) && (B->xtype != CHOLMOD_PATTERN) ;
410		---------------------------------------------------------------------------
411		* ==> Often need to copy the patter*n* to a *l*ogical matrix first !!!
412		*/
413
414	SEXP Csparse_Csparse_prod(SEXP a, SEXP b)	SEXP Csparse_Csparse_prod(SEXP a, SEXP b, SEXP bool_arith)
415	{	{
416	cholmod_sparse *cha = as_cholmod_sparse(a),	CHM_SP
417	*chb = as_cholmod_sparse(b);	cha = AS_CHM_SP(a),
418	cholmod_sparse *chc = cholmod_ssmult(cha, chb, 0, cha->xtype, 1, &c);	chb = AS_CHM_SP(b), chc;
419	SEXP dn = allocVector(VECSXP, 2);	R_CheckStack();
420		// const char *cl_a = class_P(a), *cl_b = class_P(b);
421		static const char *valid_tri[] = { MATRIX_VALID_tri_Csparse, "" };
422		char diag[] = {'\0', '\0'};
423		int uploT = 0, nprot = 1,
424		do_bool = asLogical(bool_arith); // TRUE / NA / FALSE
425		Rboolean
426		a_is_n = (cha->xtype == CHOLMOD_PATTERN),
427		b_is_n = (chb->xtype == CHOLMOD_PATTERN),
428		force_num = (do_bool == FALSE),
429		maybe_bool= (do_bool == NA_LOGICAL);
430
431		#ifdef DEBUG_Matrix_verbose
432		Rprintf("DBG Csparse_C*_prod(%s, %s)\n", class_P(a), class_P(b));
433		#endif
434
435		if(a_is_n && (force_num || (maybe_bool && !b_is_n))) {
436		/* coerce 'a' to  double;
437		* have no CHOLMOD function (pattern -> logical) --> use "our" code */
438		SEXP da = PROTECT(nz2Csparse(a, x_double)); nprot++;
439		cha = AS_CHM_SP(da);
440		R_CheckStack();
441		a_is_n = FALSE;
442		}
443		else if(b_is_n && (force_num || (maybe_bool && !a_is_n))) {
444		// coerce 'b' to  double
445		SEXP db = PROTECT(nz2Csparse(b, x_double)); nprot++;
446		chb = AS_CHM_SP(db);
447		R_CheckStack();
448		b_is_n = FALSE;
449		}
450		chc = cholmod_ssmult(cha, chb, /*out_stype:*/ 0,
451		/* values : */ do_bool != TRUE,
452		/* sorted = TRUE: */ 1, &c);
453
454		/* Preserve triangularity and even unit-triangularity if appropriate.
455		* Note that in that case, the multiplication itself should happen
456		* faster.  But there's no support for that in CHOLMOD */
457
458		if(Matrix_check_class_etc(a, valid_tri) >= 0 &&
459		Matrix_check_class_etc(b, valid_tri) >= 0)
460		if(*uplo_P(a) == *uplo_P(b)) { /* both upper, or both lower tri. */
461		uploT = (*uplo_P(a) == 'U') ? 1 : -1;
462		if(*diag_P(a) == 'U' && *diag_P(b) == 'U') { /* return UNIT-triag. */
463		/* "remove the diagonal entries": */
464		chm_diagN2U(chc, uploT, /* do_realloc */ FALSE);
465		diag[0]= 'U';
466		}
467		else diag[0]= 'N';
468		}
469
470	Free(cha); Free(chb);	SEXP dn = PROTECT(allocVector(VECSXP, 2));
471	SET_VECTOR_ELT(dn, 0,       /* establish dimnames */	SET_VECTOR_ELT(dn, 0,       /* establish dimnames */
472	duplicate(VECTOR_ELT(GET_SLOT(a, Matrix_DimNamesSym), 0)));	duplicate(VECTOR_ELT(GET_SLOT(a, Matrix_DimNamesSym), 0)));
473	SET_VECTOR_ELT(dn, 1,	SET_VECTOR_ELT(dn, 1,
474	duplicate(VECTOR_ELT(GET_SLOT(b, Matrix_DimNamesSym), 1)));	duplicate(VECTOR_ELT(GET_SLOT(b, Matrix_DimNamesSym), 1)));
475	return chm_sparse_to_SEXP(chc, 1, 0, 0, "", dn);	UNPROTECT(nprot);
476		return chm_sparse_to_SEXP(chc, 1, uploT, /*Rkind*/0, diag, dn);
477	}	}
478
479	SEXP Csparse_Csparse_crossprod(SEXP a, SEXP b)	/* trans = FALSE:  crossprod(a,b)
480		* trans = TRUE : tcrossprod(a,b) */
481		SEXP Csparse_Csparse_crossprod(SEXP a, SEXP b, SEXP trans, SEXP bool_arith)
482	{	{
483	cholmod_sparse *cha = as_cholmod_sparse(a),	int tr = asLogical(trans), nprot = 1,
484	*chb = as_cholmod_sparse(b);	do_bool = asLogical(bool_arith); // TRUE / NA / FALSE
485	cholmod_sparse *chta = cholmod_transpose(cha, 1, &c);	CHM_SP
486	cholmod_sparse *chc = cholmod_ssmult(chta, chb, 0, cha->xtype, 1, &c);	cha = AS_CHM_SP(a),
487	SEXP dn = allocVector(VECSXP, 2);	chb = AS_CHM_SP(b),
488		chTr, chc;
489		R_CheckStack();
490		// const char *cl_a = class_P(a), *cl_b = class_P(b);
491		static const char *valid_tri[] = { MATRIX_VALID_tri_Csparse, "" };
492		char diag[] = {'\0', '\0'};
493		int uploT = 0;
494		Rboolean
495		a_is_n = (cha->xtype == CHOLMOD_PATTERN),
496		b_is_n = (chb->xtype == CHOLMOD_PATTERN),
497		force_num = (do_bool == FALSE),
498		maybe_bool= (do_bool == NA_LOGICAL);
499
500		if(a_is_n && (force_num || (maybe_bool && !b_is_n))) {
501		// coerce 'a' to  double
502		SEXP da = PROTECT(nz2Csparse(a, x_double)); nprot++;
503		cha = AS_CHM_SP(da);
504		R_CheckStack();
505		a_is_n = FALSE;
506		}
507		else if(b_is_n && (force_num || (maybe_bool && !a_is_n))) {
508		// coerce 'b' to  double
509		SEXP db = PROTECT(nz2Csparse(b, x_double)); nprot++;
510		chb = AS_CHM_SP(db);
511		R_CheckStack();
512		b_is_n = FALSE;
513		}
514
515		chTr = cholmod_transpose((tr) ? chb : cha, chb->xtype, &c);
516		chc = cholmod_ssmult((tr) ? cha : chTr, (tr) ? chTr : chb,
517		/*out_stype:*/ 0, /* values : */ do_bool != TRUE,
518		/* sorted = TRUE: */ 1, &c);
519		cholmod_free_sparse(&chTr, &c);
520
521		/* Preserve triangularity and unit-triangularity if appropriate;
522		* see Csparse_Csparse_prod() for comments */
523		if(Matrix_check_class_etc(a, valid_tri) >= 0 &&
524		Matrix_check_class_etc(b, valid_tri) >= 0)
525		if(*uplo_P(a) != *uplo_P(b)) { /* one 'U', the other 'L' */
526		uploT = (*uplo_P(b) == 'U') ? 1 : -1;
527		if(*diag_P(a) == 'U' && *diag_P(b) == 'U') { /* return UNIT-triag. */
528		chm_diagN2U(chc, uploT, /* do_realloc */ FALSE);
529		diag[0]= 'U';
530		}
531		else diag[0]= 'N';
532		}
533
534	Free(cha); Free(chb); cholmod_free_sparse(&chta, &c);	SEXP dn = PROTECT(allocVector(VECSXP, 2));
535	SET_VECTOR_ELT(dn, 0,       /* establish dimnames */	SET_VECTOR_ELT(dn, 0,       /* establish dimnames */
536	duplicate(VECTOR_ELT(GET_SLOT(a, Matrix_DimNamesSym), 1)));	duplicate(VECTOR_ELT(GET_SLOT(a, Matrix_DimNamesSym),
537		(tr) ? 0 : 1)));
538	SET_VECTOR_ELT(dn, 1,	SET_VECTOR_ELT(dn, 1,
539	duplicate(VECTOR_ELT(GET_SLOT(b, Matrix_DimNamesSym), 1)));	duplicate(VECTOR_ELT(GET_SLOT(b, Matrix_DimNamesSym),
540	return chm_sparse_to_SEXP(chc, 1, 0, 0, "", dn);	(tr) ? 0 : 1)));
541		UNPROTECT(nprot);
542		return chm_sparse_to_SEXP(chc, 1, uploT, /*Rkind*/0, diag, dn);
543		}
544
545		/**
546		* All (dense * sparse)  Matrix products and cross products
547		*
548		*   f( f(<Csparse>)  %*%  f(<dense>) )   for  f in {t(), identity()}
549		*
550		* @param a CsparseMatrix  (n x m)
551		* @param b numeric vector, matrix, or denseMatrix (m x k) or (k x m)  if `transp` is '2' or 'B'
552		* @param transp character.
553		*        = " " : nothing transposed {apart from a}
554		*        = "2" : "transpose 2nd arg": use  t(b) instead of b (= 2nd argument)
555		*        = "c" : "transpose c":       Return  t(c) instead of c
556		*        = "B" : "transpose both":    use t(b) and return t(c) instead of c
557		* NB: For "2", "c", "B", need to transpose a *dense* matrix, B or C --> chm_transpose_dense()
558		*
559		* @return a dense matrix, the matrix product c = g(a,b) :
560		*
561		*                                                Condition (R)   Condition (C)
562		*   R notation            Math notation          cross  transp   t.a t.b t.ans
563		*   ~~~~~~~~~~~~~~~~~     ~~~~~~~~~~~~~~~~~~     ~~~~~~~~~~~~~   ~~~~~~~~~~~~~
564		*   c <-   a %*%   b      C :=      A B            .       " "    .   .   .
565		*   c <-   a %*% t(b)     C :=      A B'           .       "2"    .   |   .
566		*   c <- t(a %*%   b)     C := (A B)'  = B'A'      .       "c"    .   .   |
567		*   c <- t(a %*% t(b))    C := (A B')' = B A'      .       "B"    .   |   |
568		*
569		*   c <-   t(a) %*%   b   C :=      A'B           TRUE     " "    |   .   .
570		*   c <-   t(a) %*% t(b)  C :=      A'B'          TRUE     "2"    |   |   .
571		*   c <- t(t(a) %*%   b)  C := (A'B)'  = B'A      TRUE     "c"    |   .   |
572		*   c <- t(t(a) %*% t(b)) C := (A'B')' = B A      TRUE     "B"    |   |   |
573		*/
574		SEXP Csp_dense_products(SEXP a, SEXP b,
575		Rboolean transp_a, Rboolean transp_b, Rboolean transp_ans)
576		{
577		CHM_SP cha = AS_CHM_SP(a);
578		int a_nc = transp_a ? cha->nrow : cha->ncol,
579		a_nr = transp_a ? cha->ncol : cha->nrow;
580		Rboolean
581		maybe_transp_b = (a_nc == 1),
582		b_is_vector = FALSE;
583		/* NOTE: trans_b {<--> "use t(b) instead of b" }
584		----  "interferes" with the  case automatic treatment of *vector* b.
585		In that case,  t(b) or b is used "whatever make more sense",
586		according to the general R philosophy of treating vectors in matrix products.
587		*/
588
589		/* repeating a "cheap part" of  mMatrix_as_dgeMatrix2(b, .)  to see if
590		* we have a vector that we might 'transpose_if_vector' : */
591		static const char *valid[] = {"_NOT_A_CLASS_", MATRIX_VALID_ddense, ""};
592		/* int ctype = Matrix_check_class_etc(b, valid);
593		* if (ctype > 0)   /.* a ddenseMatrix object */
594		if (Matrix_check_class_etc(b, valid) < 0) {
595		// not a ddenseM*:  is.matrix() or vector:
596		b_is_vector = !isMatrix(b);
597		}
598
599		if(b_is_vector) {
600		/* determine *if* we want/need to transpose at all:
601		* if (length(b) == ncol(A)) have match: use dim = c(n, 1) (<=> do *not* transp);
602		*  otherwise, try to transpose: ok  if (ncol(A) == 1) [see also above]:  */
603		maybe_transp_b = (LENGTH(b) != a_nc);
604		// Here, we transpose already in mMatrix_as_dge*()  ==> don't do it later:
605		transp_b = FALSE;
606		}
607		SEXP b_M = PROTECT(mMatrix_as_dgeMatrix2(b, maybe_transp_b));
608
609		CHM_DN chb = AS_CHM_DN(b_M), b_t;
610		R_CheckStack();
611		int ncol_b;
612		if(transp_b) { // transpose b:
613		b_t = cholmod_allocate_dense(chb->ncol, chb->nrow, chb->ncol, chb->xtype, &c);
614		chm_transpose_dense(b_t, chb);
615		ncol_b = b_t->ncol;
616		} else
617		ncol_b = chb->ncol;
618		// Result C {with dim() before it may be transposed}:
619		CHM_DN chc = cholmod_allocate_dense(a_nr, ncol_b, a_nr, chb->xtype, &c);
620		double one[] = {1,0}, zero[] = {0,0};
621		int nprot = 2;
622
623		/* Tim Davis, please FIXME:  currently (2010-11) *fails* when  a  is a pattern matrix:*/
624		if(cha->xtype == CHOLMOD_PATTERN) {
625		/* warning(_("Csparse_dense_prod(): cholmod_sdmult() not yet implemented for pattern./ ngCMatrix" */
626		/*        " --> slightly inefficient coercion")); */
627
628		// This *fails* to produce a CHOLMOD_REAL ..
629		// CHM_SP chd = cholmod_l_copy(cha, cha->stype, CHOLMOD_REAL, &c);
630		// --> use our Matrix-classes
631		SEXP da = PROTECT(nz2Csparse(a, x_double)); nprot++;
632		cha = AS_CHM_SP(da);
633		}
634
635		/* cholmod_sdmult(A, transp, alpha, beta, X,  Y,  &c): depending on transp == 0 / != 0:
636		*  Y := alpha*(A*X) + beta*Y or alpha*(A'*X) + beta*Y;  here, alpha = 1, beta = 0:
637		*  Y := A*X  or  A'*X
638		*                       NB: always  <sparse> %*% <dense> !
639		*/
640		cholmod_sdmult(cha, transp_a, one, zero, (transp_b ? b_t : chb), /* -> */ chc, &c);
641
642		SEXP dn = PROTECT(allocVector(VECSXP, 2));  /* establish dimnames */
643		SET_VECTOR_ELT(dn, transp_ans ? 1 : 0,
644		duplicate(VECTOR_ELT(GET_SLOT(a, Matrix_DimNamesSym), transp_a ? 1 : 0)));
645		SET_VECTOR_ELT(dn, transp_ans ? 0 : 1,
646		duplicate(VECTOR_ELT(GET_SLOT(b_M, Matrix_DimNamesSym),
647		transp_b ? 0 : 1)));
648		if(transp_b) cholmod_free_dense(&b_t, &c);
649		UNPROTECT(nprot);
650		return chm_dense_to_SEXP(chc, 1, 0, dn, transp_ans);
651	}	}
652
	SEXP Csparse_dense_prod(SEXP a, SEXP b)
	{
	cholmod_sparse *cha = as_cholmod_sparse(a);
	cholmod_dense *chb = as_cholmod_dense(PROTECT(mMatrix_as_dgeMatrix(b)));
	cholmod_dense *chc =
	cholmod_allocate_dense(cha->nrow, chb->ncol, cha->nrow, chb->xtype, &c);
	double alpha[] = {1,0}, beta[] = {0,0};
653
654	cholmod_sdmult(cha, 0, alpha, beta, chb, chc, &c);	SEXP Csparse_dense_prod(SEXP a, SEXP b, SEXP transp)
655	Free(cha); Free(chb);	{
656	UNPROTECT(1);	return
657	return chm_dense_to_SEXP(chc, 1, 0);	Csp_dense_products(a, b,
658		/* transp_a = */ FALSE,
659		/* transp_b   = */ (*CHAR(asChar(transp)) == '2' || *CHAR(asChar(transp)) == 'B'),
660		/* transp_ans = */ (*CHAR(asChar(transp)) == 'c' || *CHAR(asChar(transp)) == 'B'));
661	}	}
662
663	SEXP Csparse_dense_crossprod(SEXP a, SEXP b)	SEXP Csparse_dense_crossprod(SEXP a, SEXP b, SEXP transp)
664	{	{
665	cholmod_sparse *cha = as_cholmod_sparse(a);	return
666	cholmod_dense *chb = as_cholmod_dense(PROTECT(mMatrix_as_dgeMatrix(b)));	Csp_dense_products(a, b,
667	cholmod_dense *chc =	/* transp_a = */ TRUE,
668	cholmod_allocate_dense(cha->ncol, chb->ncol, cha->ncol, chb->xtype, &c);	/* transp_b   = */ (*CHAR(asChar(transp)) == '2' || *CHAR(asChar(transp)) == 'B'),
669	double alpha[] = {1,0}, beta[] = {0,0};	/* transp_ans = */ (*CHAR(asChar(transp)) == 'c' || *CHAR(asChar(transp)) == 'B'));
	cholmod_sdmult(cha, 1, alpha, beta, chb, chc, &c);
	Free(cha); Free(chb);
	UNPROTECT(1);
	return chm_dense_to_SEXP(chc, 1, 0);
670	}	}
671
672	SEXP Csparse_crossprod(SEXP x, SEXP trans, SEXP triplet)
673		/* Computes   x'x  or  x x' -- *also* for Tsparse (triplet = TRUE)
674		see Csparse_Csparse_crossprod above for  x'y and x y' */
675		SEXP Csparse_crossprod(SEXP x, SEXP trans, SEXP triplet, SEXP bool_arith)
676	{	{
677	int trip = asLogical(triplet),	int tripl = asLogical(triplet),
678	tr   = asLogical(trans); /* gets reversed because _aat is tcrossprod */	tr   = asLogical(trans), /* gets reversed because _aat is tcrossprod */
679	cholmod_triplet	do_bool = asLogical(bool_arith); // TRUE / NA / FALSE
680	*cht = trip ? as_cholmod_triplet(x) : (cholmod_triplet*) NULL;	#ifdef AS_CHM_DIAGU2N_FIXED_FINALLY
681	cholmod_sparse *chcp, *chxt,	CHM_TR cht = tripl ? AS_CHM_TR(x) : (CHM_TR) NULL;  int nprot = 1;
682	*chx = trip ? cholmod_triplet_to_sparse(cht, cht->nnz, &c)	#else /* workaround needed:*/
683	: as_cholmod_sparse(x);	SEXP xx = PROTECT(Tsparse_diagU2N(x));
684		CHM_TR cht = tripl ? AS_CHM_TR__(xx) : (CHM_TR) NULL; int nprot = 2;
685		#endif
686		CHM_SP chcp, chxt,
687		chx = (tripl ?
688		cholmod_triplet_to_sparse(cht, cht->nnz, &c) :
689		AS_CHM_SP(x));
690	SEXP dn = PROTECT(allocVector(VECSXP, 2));	SEXP dn = PROTECT(allocVector(VECSXP, 2));
691		R_CheckStack();
692	if (!tr)	Rboolean
693	chxt = cholmod_transpose(chx, chx->xtype, &c);	x_is_n = (chx->xtype == CHOLMOD_PATTERN),
694	chcp = cholmod_aat((!tr) ? chxt : chx, (int *) NULL, 0, chx->xtype, &c);	force_num = (do_bool == FALSE);
695	if(!chcp)
696		if(x_is_n && force_num) {
697		// coerce 'x' to  double
698		SEXP dx = PROTECT(nz2Csparse(x, x_double)); nprot++;
699		chx = AS_CHM_SP(dx);
700		R_CheckStack();
701		}
702
703		if (!tr) chxt = cholmod_transpose(chx, chx->xtype, &c);
704
705		chcp = cholmod_aat((!tr) ? chxt : chx, (int *) NULL, 0,
706		/* mode: */ chx->xtype, &c);
707		if(!chcp) {
708		UNPROTECT(1);
709	error(_("Csparse_crossprod(): error return from cholmod_aat()"));	error(_("Csparse_crossprod(): error return from cholmod_aat()"));
	cholmod_band_inplace(0, chcp->ncol, chcp->xtype, chcp, &c);
	chcp->stype = 1;
	if (trip) {
	cholmod_free_sparse(&chx, &c);
	Free(cht);
	} else {
	Free(chx);
710	}	}
711		cholmod_band_inplace(0, chcp->ncol, chcp->xtype, chcp, &c);
712		chcp->stype = 1; // symmetric
713		if (tripl) cholmod_free_sparse(&chx, &c);
714	if (!tr) cholmod_free_sparse(&chxt, &c);	if (!tr) cholmod_free_sparse(&chxt, &c);
715	/* create dimnames */	SET_VECTOR_ELT(dn, 0,       /* establish dimnames */
	SET_VECTOR_ELT(dn, 0,
716	duplicate(VECTOR_ELT(GET_SLOT(x, Matrix_DimNamesSym),	duplicate(VECTOR_ELT(GET_SLOT(x, Matrix_DimNamesSym),
717	(tr) ? 1 : 0)));	(tr) ? 0 : 1)));
718	SET_VECTOR_ELT(dn, 1, duplicate(VECTOR_ELT(dn, 0)));	SET_VECTOR_ELT(dn, 1, duplicate(VECTOR_ELT(dn, 0)));
719	UNPROTECT(1);	UNPROTECT(nprot);
720		// FIXME: uploT for symmetric ?
721	return chm_sparse_to_SEXP(chcp, 1, 0, 0, "", dn);	return chm_sparse_to_SEXP(chcp, 1, 0, 0, "", dn);
722	}	}
723
724		/* Csparse_drop(x, tol):  drop entries with absolute value < tol, i.e,
725		*  at least all "explicit" zeros */
726	SEXP Csparse_drop(SEXP x, SEXP tol)	SEXP Csparse_drop(SEXP x, SEXP tol)
727	{	{
728	cholmod_sparse *chx = as_cholmod_sparse(x),	const char *cl = class_P(x);
729	*ans = cholmod_copy(chx, chx->stype, chx->xtype, &c);	/* dtCMatrix, etc; [1] = the second character =?= 't' for triangular */
730		int tr = (cl[1] == 't');
731		CHM_SP chx = AS_CHM_SP__(x);
732		CHM_SP ans = cholmod_copy(chx, chx->stype, chx->xtype, &c);
733	double dtol = asReal(tol);	double dtol = asReal(tol);
734	int Rkind = (chx->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;	int Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
735		R_CheckStack();
736
737	if(!cholmod_drop(dtol, ans, &c))	if(!cholmod_drop(dtol, ans, &c))
738	error(_("cholmod_drop() failed"));	error(_("cholmod_drop() failed"));
739	Free(chx);	return chm_sparse_to_SEXP(ans, 1,
740	/* FIXME: currently drops dimnames */	tr ? ((*uplo_P(x) == 'U') ? 1 : -1) : 0,
741	return chm_sparse_to_SEXP(ans, 1, 0, Rkind, "", R_NilValue);	Rkind, tr ? diag_P(x) : "",
742		GET_SLOT(x, Matrix_DimNamesSym));
743	}	}
744
745	SEXP Csparse_horzcat(SEXP x, SEXP y)	SEXP Csparse_horzcat(SEXP x, SEXP y)
746	{	{
747	cholmod_sparse *chx = as_cholmod_sparse(x),	#define CSPARSE_CAT(_KIND_)                                             \
748	*chy = as_cholmod_sparse(y), *ans;	CHM_SP chx = AS_CHM_SP__(x), chy = AS_CHM_SP__(y);                  \
749	int Rkind = 0; /* only for "d" - FIXME */	R_CheckStack();                                                     \
750		int Rk_x = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : -3,     \
751	ans = cholmod_horzcat(chx, chy, 1, &c);	Rk_y = (chy->xtype != CHOLMOD_PATTERN) ? Real_kind(y) : -3, Rkind; \
752	Free(chx); Free(chy);	if(Rk_x == -3 || Rk_y == -3) { /* at least one of them is patter"n" */ \
753	/* FIXME: currently drops dimnames */	if(Rk_x == -3 && Rk_y == -3) { /* fine */                       \
754	return chm_sparse_to_SEXP(ans, 1, 0, Rkind, "", R_NilValue);	} else { /* only one is a patter"n"                             \
755		* "Bug" in cholmod_horzcat()/vertcat(): returns patter"n" matrix if one of them is */ \
756		Rboolean ok;                                                \
757		if(Rk_x == -3) {                                            \
758		ok = chm_MOD_xtype(CHOLMOD_REAL, chx, &c); Rk_x = 0;    \
759		} else if(Rk_y == -3) {                                     \
760		ok = chm_MOD_xtype(CHOLMOD_REAL, chy, &c); Rk_y = 0;    \
761		} else                                                      \
762		error(_("Impossible Rk_x/Rk_y in Csparse_%s(), please report"), _KIND_); \
763		if(!ok)                                                     \
764		error(_("chm_MOD_xtype() was not successful in Csparse_%s(), please report"), \
765		_KIND_);                                          \
766		}                                                               \
767		}                                                                   \
768		Rkind = /* logical if both x and y are */ (Rk_x == 1 && Rk_y == 1) ? 1 : 0
769
770		CSPARSE_CAT("horzcat");
771		// TODO: currently drops dimnames - and we fix at R level;
772
773		return chm_sparse_to_SEXP(cholmod_horzcat(chx, chy, 1, &c),
774		1, 0, Rkind, "", R_NilValue);
775	}	}
776
777	SEXP Csparse_vertcat(SEXP x, SEXP y)	SEXP Csparse_vertcat(SEXP x, SEXP y)
778	{	{
779	cholmod_sparse *chx = as_cholmod_sparse(x),	CSPARSE_CAT("vertcat");
780	*chy = as_cholmod_sparse(y), *ans;	// TODO: currently drops dimnames - and we fix at R level;
781	int Rkind = 0; /* only for "d" - FIXME */
782		return chm_sparse_to_SEXP(cholmod_vertcat(chx, chy, 1, &c),
783	ans = cholmod_vertcat(chx, chy, 1, &c);	1, 0, Rkind, "", R_NilValue);
	Free(chx); Free(chy);
	/* FIXME: currently drops dimnames */
	return chm_sparse_to_SEXP(ans, 1, 0, Rkind, "", R_NilValue);
784	}	}
785
786	SEXP Csparse_band(SEXP x, SEXP k1, SEXP k2)	SEXP Csparse_band(SEXP x, SEXP k1, SEXP k2)
787	{	{
788	cholmod_sparse *chx = as_cholmod_sparse(x), *ans;	CHM_SP chx = AS_CHM_SP__(x);
789	int Rkind = (chx->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;	int Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
790		CHM_SP ans = cholmod_band(chx, asInteger(k1), asInteger(k2), chx->xtype, &c);
791		R_CheckStack();
792
793	ans = cholmod_band(chx, asInteger(k1), asInteger(k2), chx->xtype, &c);	return chm_sparse_to_SEXP(ans, 1, 0, Rkind, "",
794	Free(chx);	GET_SLOT(x, Matrix_DimNamesSym));
	return chm_sparse_to_SEXP(ans, 1, 0, Rkind, "", R_NilValue);
795	}	}
796
797	SEXP Csparse_diagU2N(SEXP x)	SEXP Csparse_diagU2N(SEXP x)
798	{	{
799	cholmod_sparse *chx = as_cholmod_sparse(x);	const char *cl = class_P(x);
800	cholmod_sparse *eye = cholmod_speye(chx->nrow, chx->ncol, chx->xtype, &c);	/* dtCMatrix, etc; [1] = the second character =?= 't' for triangular */
801		if (cl[1] != 't' || *diag_P(x) != 'U') {
802		/* "trivially fast" when not triangular (<==> no 'diag' slot),
803		or not *unit* triangular */
804		return (x);
805		}
806		else { /* unit triangular (diag='U'): "fill the diagonal" & diag:= "N" */
807		CHM_SP chx = AS_CHM_SP__(x);
808		CHM_SP eye = cholmod_speye(chx->nrow, chx->ncol, chx->xtype, &c);
809	double one[] = {1, 0};	double one[] = {1, 0};
810	cholmod_sparse *ans = cholmod_add(chx, eye, one, one, TRUE, TRUE, &c);	CHM_SP ans = cholmod_add(chx, eye, one, one, TRUE, TRUE, &c);
811	int uploT = (strcmp(CHAR(asChar(GET_SLOT(x, Matrix_uploSym))), "U")) ?	int uploT = (*uplo_P(x) == 'U') ? 1 : -1;
812	-1 : 1;	int Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
	int Rkind = (chx->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;
813
814	Free(chx); cholmod_free_sparse(&eye, &c);	R_CheckStack();
815		cholmod_free_sparse(&eye, &c);
816	return chm_sparse_to_SEXP(ans, 1, uploT, Rkind, "N",	return chm_sparse_to_SEXP(ans, 1, uploT, Rkind, "N",
817	duplicate(GET_SLOT(x, Matrix_DimNamesSym)));	GET_SLOT(x, Matrix_DimNamesSym));
818		}
819	}	}
820
821		SEXP Csparse_diagN2U(SEXP x)
822		{
823		const char *cl = class_P(x);
824		/* dtCMatrix, etc; [1] = the second character =?= 't' for triangular */
825		if (cl[1] != 't' || *diag_P(x) != 'N') {
826		/* "trivially fast" when not triangular (<==> no 'diag' slot),
827		or already *unit* triangular */
828		return (x);
829		}
830		else { /* triangular with diag='N'): now drop the diagonal */
831		/* duplicate, since chx will be modified: */
832		SEXP xx = PROTECT(duplicate(x));
833		CHM_SP chx = AS_CHM_SP__(xx);
834		int uploT = (*uplo_P(x) == 'U') ? 1 : -1,
835		Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
836		R_CheckStack();
837
838		chm_diagN2U(chx, uploT, /* do_realloc */ FALSE);
839
840		SEXP ans = chm_sparse_to_SEXP(chx, /*dofree*/ 0/* or 1 ?? */,
841		uploT, Rkind, "U",
842		GET_SLOT(x, Matrix_DimNamesSym));
843		UNPROTECT(1);// only now !
844		return ans;
845		}
846		}
847
848		/**
849		* "Indexing" aka subsetting : Compute  x[i,j], also for vectors i and j
850		* Working via CHOLMOD_submatrix, see ./CHOLMOD/MatrixOps/cholmod_submatrix.c
851		* @param x CsparseMatrix
852		* @param i row     indices (0-origin), or NULL (R's)
853		* @param j columns indices (0-origin), or NULL
854		*
855		* @return x[i,j]  still CsparseMatrix --- currently, this loses dimnames
856		*/
857	SEXP Csparse_submatrix(SEXP x, SEXP i, SEXP j)	SEXP Csparse_submatrix(SEXP x, SEXP i, SEXP j)
858	{	{
859	cholmod_sparse *chx = as_cholmod_sparse(x);	CHM_SP chx = AS_CHM_SP(x); /* << does diagU2N() when needed */
860	int rsize = (isNull(i)) ? -1 : LENGTH(i),	int rsize = (isNull(i)) ? -1 : LENGTH(i),
861	csize = (isNull(j)) ? -1 : LENGTH(j);	csize = (isNull(j)) ? -1 : LENGTH(j);
862	int Rkind = (chx->xtype == CHOLMOD_REAL) ? Real_kind(x) : 0;	int Rkind = (chx->xtype != CHOLMOD_PATTERN) ? Real_kind(x) : 0;
863		R_CheckStack();
864
865	if (rsize >= 0 && !isInteger(i))	if (rsize >= 0 && !isInteger(i))
866	error(_("Index i must be NULL or integer"));	error(_("Index i must be NULL or integer"));
867	if (csize >= 0 && !isInteger(j))	if (csize >= 0 && !isInteger(j))
868	error(_("Index j must be NULL or integer"));	error(_("Index j must be NULL or integer"));
869	return chm_sparse_to_SEXP(cholmod_submatrix(chx, INTEGER(i), rsize,
870	INTEGER(j), csize,	#define CHM_SUB(_M_, _i_, _j_)                                  \
871	TRUE, TRUE, &c),	cholmod_submatrix(_M_,                                      \
872	1, 0, Rkind, "", R_NilValue);	(rsize < 0) ? NULL : INTEGER(_i_), rsize, \
873		(csize < 0) ? NULL : INTEGER(_j_), csize, \
874		TRUE, TRUE, &c)
875		CHM_SP ans;
876		if (!chx->stype) {/* non-symmetric Matrix */
877		ans = CHM_SUB(chx, i, j);
878		}
879		else {
880		/* for now, cholmod_submatrix() only accepts "generalMatrix" */
881		CHM_SP tmp = cholmod_copy(chx, /* stype: */ 0, chx->xtype, &c);
882		ans = CHM_SUB(tmp, i, j);
883		cholmod_free_sparse(&tmp, &c);
884		}
885
886		// "FIXME": currently dropping dimnames, and adding them afterwards in R :
887		/* // dimnames: */
888		/* SEXP x_dns = GET_SLOT(x, Matrix_DimNamesSym), */
889		/*  dn = PROTECT(allocVector(VECSXP, 2)); */
890		return chm_sparse_to_SEXP(ans, 1, 0, Rkind, "", /* dimnames: */ R_NilValue);
891		}
892
893		#define _d_Csp_
894		#include "t_Csparse_subassign.c"
895
896		#define _l_Csp_
897		#include "t_Csparse_subassign.c"
898
899		#define _i_Csp_
900		#include "t_Csparse_subassign.c"
901
902		#define _n_Csp_
903		#include "t_Csparse_subassign.c"
904
905		#define _z_Csp_
906		#include "t_Csparse_subassign.c"
907
908
909
910		SEXP Csparse_MatrixMarket(SEXP x, SEXP fname)
911		{
912		FILE *f = fopen(CHAR(asChar(fname)), "w");
913
914		if (!f)
915		error(_("failure to open file \"%s\" for writing"),
916		CHAR(asChar(fname)));
917		if (!cholmod_write_sparse(f, AS_CHM_SP(x),
918		(CHM_SP)NULL, (char*) NULL, &c))
919		error(_("cholmod_write_sparse returned error code"));
920		fclose(f);
921		return R_NilValue;
922		}
923
924
925		/**
926		* Extract the diagonal entries from *triangular* Csparse matrix  __or__ a
927		* cholmod_sparse factor (LDL = TRUE).
928		*
929		* @param n  dimension of the matrix.
930		* @param x_p  'p' (column pointer) slot contents
931		* @param x_x  'x' (non-zero entries) slot contents
932		* @param perm 'perm' (= permutation vector) slot contents; only used for "diagBack"
933		* @param resultKind a (SEXP) string indicating which kind of result is desired.
934		*
935		* @return  a SEXP, either a (double) number or a length n-vector of diagonal entries
936		*/
937		SEXP diag_tC_ptr(int n, int *x_p, double *x_x, Rboolean is_U, int *perm,
938		/*                                ^^^^^^ FIXME[Generalize] to int / ... */
939		SEXP resultKind)
940		{
941		const char* res_ch = CHAR(STRING_ELT(resultKind,0));
942		enum diag_kind { diag, diag_backpermuted, trace, prod, sum_log, min, max, range
943		} res_kind = ((!strcmp(res_ch, "trace")) ? trace :
944		((!strcmp(res_ch, "sumLog")) ? sum_log :
945		((!strcmp(res_ch, "prod")) ? prod :
946		((!strcmp(res_ch, "min")) ? min :
947		((!strcmp(res_ch, "max")) ? max :
948		((!strcmp(res_ch, "range")) ? range :
949		((!strcmp(res_ch, "diag")) ? diag :
950		((!strcmp(res_ch, "diagBack")) ? diag_backpermuted :
951		-1))))))));
952		int i, n_x, i_from;
953		SEXP ans = PROTECT(allocVector(REALSXP,
954		/*                                 ^^^^  FIXME[Generalize] */
955		(res_kind == diag ||
956		res_kind == diag_backpermuted) ? n :
957		(res_kind == range ? 2 : 1)));
958		double *v = REAL(ans);
959		/*  ^^^^^^      ^^^^  FIXME[Generalize] */
960
961		i_from = (is_U ? -1 : 0);
962
963		#define for_DIAG(v_ASSIGN)                                      \
964		for(i = 0; i < n; i++) {                                    \
965		/* looking at i-th column */                            \
966		n_x = x_p[i+1] - x_p[i];/* #{entries} in this column */ \
967		if( is_U) i_from += n_x;                                \
968		v_ASSIGN;                                               \
969		if(!is_U) i_from += n_x;                                \
970		}
971
972		/* NOTA BENE: we assume  -- uplo = "L" i.e. lower triangular matrix
973		*            for uplo = "U" (makes sense with a "dtCMatrix" !),
974		*            should use  x_x[i_from + (n_x - 1)] instead of x_x[i_from],
975		*            where n_x = (x_p[i+1] - x_p[i])
976		*/
977
978		switch(res_kind) {
979		case trace: // = sum
980		v[0] = 0.;
981		for_DIAG(v[0] += x_x[i_from]);
982		break;
983
984		case sum_log:
985		v[0] = 0.;
986		for_DIAG(v[0] += log(x_x[i_from]));
987		break;
988
989		case prod:
990		v[0] = 1.;
991		for_DIAG(v[0] *= x_x[i_from]);
992		break;
993
994		case min:
995		v[0] = R_PosInf;
996		for_DIAG(if(v[0] > x_x[i_from]) v[0] = x_x[i_from]);
997		break;
998
999		case max:
1000		v[0] = R_NegInf;
1001		for_DIAG(if(v[0] < x_x[i_from]) v[0] = x_x[i_from]);
1002		break;
1003
1004		case range:
1005		v[0] = R_PosInf;
1006		v[1] = R_NegInf;
1007		for_DIAG(if(v[0] > x_x[i_from]) v[0] = x_x[i_from];
1008		if(v[1] < x_x[i_from]) v[1] = x_x[i_from]);
1009		break;
1010
1011		case diag:
1012		for_DIAG(v[i] = x_x[i_from]);
1013		break;
1014
1015		case diag_backpermuted:
1016		for_DIAG(v[i] = x_x[i_from]);
1017
1018		warning(_("%s = '%s' (back-permuted) is experimental"),
1019		"resultKind", "diagBack");
1020		/* now back_permute : */
1021		for(i = 0; i < n; i++) {
1022		double tmp = v[i]; v[i] = v[perm[i]]; v[perm[i]] = tmp;
1023		/*^^^^ FIXME[Generalize] */
1024		}
1025		break;
1026
1027		default: /* -1 from above */
1028		error(_("diag_tC(): invalid 'resultKind'"));
1029		/* Wall: */ ans = R_NilValue; v = REAL(ans);
1030		}
1031
1032		UNPROTECT(1);
1033		return ans;
1034		}
1035
1036		/**
1037		* Extract the diagonal entries from *triangular* Csparse matrix  __or__ a
1038		* cholmod_sparse factor (LDL = TRUE).
1039		*
1040		* @param obj -- now a cholmod_sparse factor or a dtCMatrix
1041		* @param pslot  'p' (column pointer)   slot of Csparse matrix/factor
1042		* @param xslot  'x' (non-zero entries) slot of Csparse matrix/factor
1043		* @param perm_slot  'perm' (= permutation vector) slot of corresponding CHMfactor;
1044		*                   only used for "diagBack"
1045		* @param resultKind a (SEXP) string indicating which kind of result is desired.
1046		*
1047		* @return  a SEXP, either a (double) number or a length n-vector of diagonal entries
1048		*/
1049		SEXP diag_tC(SEXP obj, SEXP resultKind)
1050		{
1051
1052		SEXP
1053		pslot = GET_SLOT(obj, Matrix_pSym),
1054		xslot = GET_SLOT(obj, Matrix_xSym);
1055		Rboolean is_U = (R_has_slot(obj, Matrix_uploSym) &&
1056		*CHAR(asChar(GET_SLOT(obj, Matrix_uploSym))) == 'U');
1057		int n = length(pslot) - 1, /* n = ncol(.) = nrow(.) */
1058		*x_p  = INTEGER(pslot), pp = -1, *perm;
1059		double *x_x = REAL(xslot);
1060		/*  ^^^^^^        ^^^^ FIXME[Generalize] to INTEGER(.) / LOGICAL(.) / ... xslot !*/
1061
1062		if(R_has_slot(obj, Matrix_permSym))
1063		perm = INTEGER(GET_SLOT(obj, Matrix_permSym));
1064		else perm = &pp;
1065
1066		return diag_tC_ptr(n, x_p, x_x, is_U, perm, resultKind);
1067		}
1068
1069
1070		/**
1071		* Create a Csparse matrix object from indices and/or pointers.
1072		*
1073		* @param cls name of actual class of object to create
1074		* @param i optional integer vector of length nnz of row indices
1075		* @param j optional integer vector of length nnz of column indices
1076		* @param p optional integer vector of length np of row or column pointers
1077		* @param np length of integer vector p.  Must be zero if p == (int*)NULL
1078		* @param x optional vector of values
1079		* @param nnz length of vectors i, j and/or x, whichever is to be used
1080		* @param dims optional integer vector of length 2 to be used as
1081		*     dimensions.  If dims == (int*)NULL then the maximum row and column
1082		*     index are used as the dimensions.
1083		* @param dimnames optional list of length 2 to be used as dimnames
1084		* @param index1 indicator of 1-based indices
1085		*
1086		* @return an SEXP of class cls inheriting from CsparseMatrix.
1087		*/
1088		SEXP create_Csparse(char* cls, int* i, int* j, int* p, int np,
1089		void* x, int nnz, int* dims, SEXP dimnames,
1090		int index1)
1091		{
1092		SEXP ans;
1093		int *ij = (int*)NULL, *tri, *trj,
1094		mi, mj, mp, nrow = -1, ncol = -1;
1095		int xtype = -1;             /* -Wall */
1096		CHM_TR T;
1097		CHM_SP A;
1098
1099		if (np < 0 || nnz < 0)
1100		error(_("negative vector lengths not allowed: np = %d, nnz = %d"),
1101		np, nnz);
1102		if (1 != ((mi = (i == (int*)NULL)) +
1103		(mj = (j == (int*)NULL)) +
1104		(mp = (p == (int*)NULL))))
1105		error(_("exactly 1 of 'i', 'j' or 'p' must be NULL"));
1106		if (mp) {
1107		if (np) error(_("np = %d, must be zero when p is NULL"), np);
1108		} else {
1109		if (np) {               /* Expand p to form i or j */
1110		if (!(p[0])) error(_("p[0] = %d, should be zero"), p[0]);
1111		for (int ii = 0; ii < np; ii++)
1112		if (p[ii] > p[ii + 1])
1113		error(_("p must be non-decreasing"));
1114		if (p[np] != nnz)
1115		error("p[np] = %d != nnz = %d", p[np], nnz);
1116		ij = Calloc(nnz, int);
1117		if (mi) {
1118		i = ij;
1119		nrow = np;
1120		} else {
1121		j = ij;
1122		ncol = np;
1123		}
1124		/* Expand p to 0-based indices */
1125		for (int ii = 0; ii < np; ii++)
1126		for (int jj = p[ii]; jj < p[ii + 1]; jj++) ij[jj] = ii;
1127		} else {
1128		if (nnz)
1129		error(_("Inconsistent dimensions: np = 0 and nnz = %d"),
1130		nnz);
1131		}
1132		}
1133		/* calculate nrow and ncol */
1134		if (nrow < 0) {
1135		for (int ii = 0; ii < nnz; ii++) {
1136		int i1 = i[ii] + (index1 ? 0 : 1); /* 1-based index */
1137		if (i1 < 1) error(_("invalid row index at position %d"), ii);
1138		if (i1 > nrow) nrow = i1;
1139		}
1140		}
1141		if (ncol < 0) {
1142		for (int jj = 0; jj < nnz; jj++) {
1143		int j1 = j[jj] + (index1 ? 0 : 1);
1144		if (j1 < 1) error(_("invalid column index at position %d"), jj);
1145		if (j1 > ncol) ncol = j1;
1146		}
1147		}
1148		if (dims != (int*)NULL) {
1149		if (dims[0] > nrow) nrow = dims[0];
1150		if (dims[1] > ncol) ncol = dims[1];
1151		}
1152		/* check the class name */
1153		if (strlen(cls) != 8)
1154		error(_("strlen of cls argument = %d, should be 8"), strlen(cls));
1155		if (!strcmp(cls + 2, "CMatrix"))
1156		error(_("cls = \"%s\" does not end in \"CMatrix\""), cls);
1157		switch(cls[0]) {
1158		case 'd':
1159		case 'l':
1160		xtype = CHOLMOD_REAL;
1161		break;
1162		case 'n':
1163		xtype = CHOLMOD_PATTERN;
1164		break;
1165		default:
1166		error(_("cls = \"%s\" must begin with 'd', 'l' or 'n'"), cls);
1167		}
1168		if (cls[1] != 'g')
1169		error(_("Only 'g'eneral sparse matrix types allowed"));
1170		/* allocate and populate the triplet */
1171		T = cholmod_allocate_triplet((size_t)nrow, (size_t)ncol, (size_t)nnz, 0,
1172		xtype, &c);
1173		T->x = x;
1174		tri = (int*)T->i;
1175		trj = (int*)T->j;
1176		for (int ii = 0; ii < nnz; ii++) {
1177		tri[ii] = i[ii] - ((!mi && index1) ? 1 : 0);
1178		trj[ii] = j[ii] - ((!mj && index1) ? 1 : 0);
1179		}
1180		/* create the cholmod_sparse structure */
1181		A = cholmod_triplet_to_sparse(T, nnz, &c);
1182		cholmod_free_triplet(&T, &c);
1183		/* copy the information to the SEXP */
1184		ans = PROTECT(NEW_OBJECT(MAKE_CLASS(cls)));
1185		// FIXME: This has been copied from chm_sparse_to_SEXP in  chm_common.c
1186		/* allocate and copy common slots */
1187		nnz = cholmod_nnz(A, &c);
1188		dims = INTEGER(ALLOC_SLOT(ans, Matrix_DimSym, INTSXP, 2));
1189		dims[0] = A->nrow; dims[1] = A->ncol;
1190		Memcpy(INTEGER(ALLOC_SLOT(ans, Matrix_pSym, INTSXP, A->ncol + 1)), (int*)A->p, A->ncol + 1);
1191		Memcpy(INTEGER(ALLOC_SLOT(ans, Matrix_iSym, INTSXP, nnz)), (int*)A->i, nnz);
1192		switch(cls[1]) {
1193		case 'd':
1194		Memcpy(REAL(ALLOC_SLOT(ans, Matrix_xSym, REALSXP, nnz)), (double*)A->x, nnz);
1195		break;
1196		case 'l':
1197		error(_("code not yet written for cls = \"lgCMatrix\""));
1198		}
1199		/* FIXME: dimnames are *NOT* put there yet (if non-NULL) */
1200		cholmod_free_sparse(&A, &c);
1201		UNPROTECT(1);
1202		return ans;
1203	}	}

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