Actual source code: sbaij.c
2: /*
3: Defines the basic matrix operations for the SBAIJ (compressed row)
4: matrix storage format.
5: */
6: #include <../src/mat/impls/baij/seq/baij.h>
7: #include <../src/mat/impls/sbaij/seq/sbaij.h>
8: #include <petscblaslapack.h>
10: #include <../src/mat/impls/sbaij/seq/relax.h>
11: #define USESHORT
12: #include <../src/mat/impls/sbaij/seq/relax.h>
14: /* defines MatSetValues_Seq_Hash(), MatAssemblyEnd_Seq_Hash(), MatSetUp_Seq_Hash() */
15: #define TYPE SBAIJ
16: #define TYPE_SBAIJ
17: #define TYPE_BS
18: #include "../src/mat/impls/aij/seq/seqhashmatsetvalues.h"
19: #undef TYPE_BS
20: #define TYPE_BS _BS
21: #define TYPE_BS_ON
22: #include "../src/mat/impls/aij/seq/seqhashmatsetvalues.h"
23: #undef TYPE_BS
24: #undef TYPE_SBAIJ
25: #include "../src/mat/impls/aij/seq/seqhashmat.h"
26: #undef TYPE
27: #undef TYPE_BS_ON
29: #if defined(PETSC_HAVE_ELEMENTAL)
30: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_Elemental(Mat, MatType, MatReuse, Mat *);
31: #endif
32: #if defined(PETSC_HAVE_SCALAPACK)
33: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
34: #endif
35: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat, MatType, MatReuse, Mat *);
37: /*
38: Checks for missing diagonals
39: */
40: PetscErrorCode MatMissingDiagonal_SeqSBAIJ(Mat A, PetscBool *missing, PetscInt *dd)
41: {
42: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
43: PetscInt *diag, *ii = a->i, i;
45: PetscFunctionBegin;
46: PetscCall(MatMarkDiagonal_SeqSBAIJ(A));
47: *missing = PETSC_FALSE;
48: if (A->rmap->n > 0 && !ii) {
49: *missing = PETSC_TRUE;
50: if (dd) *dd = 0;
51: PetscCall(PetscInfo(A, "Matrix has no entries therefore is missing diagonal\n"));
52: } else {
53: diag = a->diag;
54: for (i = 0; i < a->mbs; i++) {
55: if (diag[i] >= ii[i + 1]) {
56: *missing = PETSC_TRUE;
57: if (dd) *dd = i;
58: break;
59: }
60: }
61: }
62: PetscFunctionReturn(PETSC_SUCCESS);
63: }
65: PetscErrorCode MatMarkDiagonal_SeqSBAIJ(Mat A)
66: {
67: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
68: PetscInt i, j;
70: PetscFunctionBegin;
71: if (!a->diag) {
72: PetscCall(PetscMalloc1(a->mbs, &a->diag));
73: a->free_diag = PETSC_TRUE;
74: }
75: for (i = 0; i < a->mbs; i++) {
76: a->diag[i] = a->i[i + 1];
77: for (j = a->i[i]; j < a->i[i + 1]; j++) {
78: if (a->j[j] == i) {
79: a->diag[i] = j;
80: break;
81: }
82: }
83: }
84: PetscFunctionReturn(PETSC_SUCCESS);
85: }
87: static PetscErrorCode MatGetRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *inia[], const PetscInt *inja[], PetscBool *done)
88: {
89: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
90: PetscInt i, j, n = a->mbs, nz = a->i[n], *tia, *tja, bs = A->rmap->bs, k, l, cnt;
91: PetscInt **ia = (PetscInt **)inia, **ja = (PetscInt **)inja;
93: PetscFunctionBegin;
94: *nn = n;
95: if (!ia) PetscFunctionReturn(PETSC_SUCCESS);
96: if (symmetric) {
97: PetscCall(MatToSymmetricIJ_SeqAIJ(n, a->i, a->j, PETSC_FALSE, 0, 0, &tia, &tja));
98: nz = tia[n];
99: } else {
100: tia = a->i;
101: tja = a->j;
102: }
104: if (!blockcompressed && bs > 1) {
105: (*nn) *= bs;
106: /* malloc & create the natural set of indices */
107: PetscCall(PetscMalloc1((n + 1) * bs, ia));
108: if (n) {
109: (*ia)[0] = oshift;
110: for (j = 1; j < bs; j++) (*ia)[j] = (tia[1] - tia[0]) * bs + (*ia)[j - 1];
111: }
113: for (i = 1; i < n; i++) {
114: (*ia)[i * bs] = (tia[i] - tia[i - 1]) * bs + (*ia)[i * bs - 1];
115: for (j = 1; j < bs; j++) (*ia)[i * bs + j] = (tia[i + 1] - tia[i]) * bs + (*ia)[i * bs + j - 1];
116: }
117: if (n) (*ia)[n * bs] = (tia[n] - tia[n - 1]) * bs + (*ia)[n * bs - 1];
119: if (inja) {
120: PetscCall(PetscMalloc1(nz * bs * bs, ja));
121: cnt = 0;
122: for (i = 0; i < n; i++) {
123: for (j = 0; j < bs; j++) {
124: for (k = tia[i]; k < tia[i + 1]; k++) {
125: for (l = 0; l < bs; l++) (*ja)[cnt++] = bs * tja[k] + l;
126: }
127: }
128: }
129: }
131: if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
132: PetscCall(PetscFree(tia));
133: PetscCall(PetscFree(tja));
134: }
135: } else if (oshift == 1) {
136: if (symmetric) {
137: nz = tia[A->rmap->n / bs];
138: /* add 1 to i and j indices */
139: for (i = 0; i < A->rmap->n / bs + 1; i++) tia[i] = tia[i] + 1;
140: *ia = tia;
141: if (ja) {
142: for (i = 0; i < nz; i++) tja[i] = tja[i] + 1;
143: *ja = tja;
144: }
145: } else {
146: nz = a->i[A->rmap->n / bs];
147: /* malloc space and add 1 to i and j indices */
148: PetscCall(PetscMalloc1(A->rmap->n / bs + 1, ia));
149: for (i = 0; i < A->rmap->n / bs + 1; i++) (*ia)[i] = a->i[i] + 1;
150: if (ja) {
151: PetscCall(PetscMalloc1(nz, ja));
152: for (i = 0; i < nz; i++) (*ja)[i] = a->j[i] + 1;
153: }
154: }
155: } else {
156: *ia = tia;
157: if (ja) *ja = tja;
158: }
159: PetscFunctionReturn(PETSC_SUCCESS);
160: }
162: static PetscErrorCode MatRestoreRowIJ_SeqSBAIJ(Mat A, PetscInt oshift, PetscBool symmetric, PetscBool blockcompressed, PetscInt *nn, const PetscInt *ia[], const PetscInt *ja[], PetscBool *done)
163: {
164: PetscFunctionBegin;
165: if (!ia) PetscFunctionReturn(PETSC_SUCCESS);
166: if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
167: PetscCall(PetscFree(*ia));
168: if (ja) PetscCall(PetscFree(*ja));
169: }
170: PetscFunctionReturn(PETSC_SUCCESS);
171: }
173: PetscErrorCode MatDestroy_SeqSBAIJ(Mat A)
174: {
175: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
177: PetscFunctionBegin;
178: #if defined(PETSC_USE_LOG)
179: PetscCall(PetscLogObjectState((PetscObject)A, "Rows=%" PetscInt_FMT ", NZ=%" PetscInt_FMT, A->rmap->N, a->nz));
180: #endif
181: PetscCall(MatSeqXAIJFreeAIJ(A, &a->a, &a->j, &a->i));
182: if (a->free_diag) PetscCall(PetscFree(a->diag));
183: PetscCall(ISDestroy(&a->row));
184: PetscCall(ISDestroy(&a->col));
185: PetscCall(ISDestroy(&a->icol));
186: PetscCall(PetscFree(a->idiag));
187: PetscCall(PetscFree(a->inode.size));
188: if (a->free_imax_ilen) PetscCall(PetscFree2(a->imax, a->ilen));
189: PetscCall(PetscFree(a->solve_work));
190: PetscCall(PetscFree(a->sor_work));
191: PetscCall(PetscFree(a->solves_work));
192: PetscCall(PetscFree(a->mult_work));
193: PetscCall(PetscFree(a->saved_values));
194: if (a->free_jshort) PetscCall(PetscFree(a->jshort));
195: PetscCall(PetscFree(a->inew));
196: PetscCall(MatDestroy(&a->parent));
197: PetscCall(PetscFree(A->data));
199: PetscCall(PetscObjectChangeTypeName((PetscObject)A, NULL));
200: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJGetArray_C", NULL));
201: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJRestoreArray_C", NULL));
202: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatStoreValues_C", NULL));
203: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatRetrieveValues_C", NULL));
204: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetColumnIndices_C", NULL));
205: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqaij_C", NULL));
206: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqbaij_C", NULL));
207: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocation_C", NULL));
208: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocationCSR_C", NULL));
209: #if defined(PETSC_HAVE_ELEMENTAL)
210: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_elemental_C", NULL));
211: #endif
212: #if defined(PETSC_HAVE_SCALAPACK)
213: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_scalapack_C", NULL));
214: #endif
215: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL));
216: PetscFunctionReturn(PETSC_SUCCESS);
217: }
219: PetscErrorCode MatSetOption_SeqSBAIJ(Mat A, MatOption op, PetscBool flg)
220: {
221: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
222: #if defined(PETSC_USE_COMPLEX)
223: PetscInt bs;
224: #endif
226: PetscFunctionBegin;
227: #if defined(PETSC_USE_COMPLEX)
228: PetscCall(MatGetBlockSize(A, &bs));
229: #endif
230: switch (op) {
231: case MAT_ROW_ORIENTED:
232: a->roworiented = flg;
233: break;
234: case MAT_KEEP_NONZERO_PATTERN:
235: a->keepnonzeropattern = flg;
236: break;
237: case MAT_NEW_NONZERO_LOCATIONS:
238: a->nonew = (flg ? 0 : 1);
239: break;
240: case MAT_NEW_NONZERO_LOCATION_ERR:
241: a->nonew = (flg ? -1 : 0);
242: break;
243: case MAT_NEW_NONZERO_ALLOCATION_ERR:
244: a->nonew = (flg ? -2 : 0);
245: break;
246: case MAT_UNUSED_NONZERO_LOCATION_ERR:
247: a->nounused = (flg ? -1 : 0);
248: break;
249: case MAT_FORCE_DIAGONAL_ENTRIES:
250: case MAT_IGNORE_OFF_PROC_ENTRIES:
251: case MAT_USE_HASH_TABLE:
252: case MAT_SORTED_FULL:
253: PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op]));
254: break;
255: case MAT_HERMITIAN:
256: #if defined(PETSC_USE_COMPLEX)
257: if (flg) { /* disable transpose ops */
258: PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for Hermitian with block size greater than 1");
259: A->ops->multtranspose = NULL;
260: A->ops->multtransposeadd = NULL;
261: A->symmetric = PETSC_BOOL3_FALSE;
262: }
263: #endif
264: break;
265: case MAT_SYMMETRIC:
266: case MAT_SPD:
267: #if defined(PETSC_USE_COMPLEX)
268: if (flg) { /* An hermitian and symmetric matrix has zero imaginary part (restore back transpose ops) */
269: A->ops->multtranspose = A->ops->mult;
270: A->ops->multtransposeadd = A->ops->multadd;
271: }
272: #endif
273: break;
274: /* These options are handled directly by MatSetOption() */
275: case MAT_STRUCTURALLY_SYMMETRIC:
276: case MAT_SYMMETRY_ETERNAL:
277: case MAT_STRUCTURAL_SYMMETRY_ETERNAL:
278: case MAT_STRUCTURE_ONLY:
279: case MAT_SPD_ETERNAL:
280: /* These options are handled directly by MatSetOption() */
281: break;
282: case MAT_IGNORE_LOWER_TRIANGULAR:
283: a->ignore_ltriangular = flg;
284: break;
285: case MAT_ERROR_LOWER_TRIANGULAR:
286: a->ignore_ltriangular = flg;
287: break;
288: case MAT_GETROW_UPPERTRIANGULAR:
289: a->getrow_utriangular = flg;
290: break;
291: case MAT_SUBMAT_SINGLEIS:
292: break;
293: default:
294: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "unknown option %d", op);
295: }
296: PetscFunctionReturn(PETSC_SUCCESS);
297: }
299: PetscErrorCode MatGetRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
300: {
301: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
303: PetscFunctionBegin;
304: PetscCheck(!A || a->getrow_utriangular, PETSC_COMM_SELF, PETSC_ERR_SUP, "MatGetRow is not supported for SBAIJ matrix format. Getting the upper triangular part of row, run with -mat_getrow_uppertriangular, call MatSetOption(mat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE) or MatGetRowUpperTriangular()");
306: /* Get the upper triangular part of the row */
307: PetscCall(MatGetRow_SeqBAIJ_private(A, row, nz, idx, v, a->i, a->j, a->a));
308: PetscFunctionReturn(PETSC_SUCCESS);
309: }
311: PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
312: {
313: PetscFunctionBegin;
314: if (nz) *nz = 0;
315: if (idx) PetscCall(PetscFree(*idx));
316: if (v) PetscCall(PetscFree(*v));
317: PetscFunctionReturn(PETSC_SUCCESS);
318: }
320: PetscErrorCode MatGetRowUpperTriangular_SeqSBAIJ(Mat A)
321: {
322: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
324: PetscFunctionBegin;
325: a->getrow_utriangular = PETSC_TRUE;
326: PetscFunctionReturn(PETSC_SUCCESS);
327: }
329: PetscErrorCode MatRestoreRowUpperTriangular_SeqSBAIJ(Mat A)
330: {
331: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
333: PetscFunctionBegin;
334: a->getrow_utriangular = PETSC_FALSE;
335: PetscFunctionReturn(PETSC_SUCCESS);
336: }
338: PetscErrorCode MatTranspose_SeqSBAIJ(Mat A, MatReuse reuse, Mat *B)
339: {
340: PetscFunctionBegin;
341: if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *B));
342: if (reuse == MAT_INITIAL_MATRIX) {
343: PetscCall(MatDuplicate(A, MAT_COPY_VALUES, B));
344: } else if (reuse == MAT_REUSE_MATRIX) {
345: PetscCall(MatCopy(A, *B, SAME_NONZERO_PATTERN));
346: }
347: PetscFunctionReturn(PETSC_SUCCESS);
348: }
350: PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat A, PetscViewer viewer)
351: {
352: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
353: PetscInt i, j, bs = A->rmap->bs, k, l, bs2 = a->bs2;
354: PetscViewerFormat format;
355: PetscInt *diag;
356: const char *matname;
358: PetscFunctionBegin;
359: PetscCall(PetscViewerGetFormat(viewer, &format));
360: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
361: PetscCall(PetscViewerASCIIPrintf(viewer, " block size is %" PetscInt_FMT "\n", bs));
362: } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
363: Mat aij;
365: if (A->factortype && bs > 1) {
366: PetscCall(PetscPrintf(PETSC_COMM_SELF, "Warning: matrix is factored with bs>1. MatView() with PETSC_VIEWER_ASCII_MATLAB is not supported and ignored!\n"));
367: PetscFunctionReturn(PETSC_SUCCESS);
368: }
369: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &aij));
370: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
371: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)aij, matname));
372: PetscCall(MatView_SeqAIJ(aij, viewer));
373: PetscCall(MatDestroy(&aij));
374: } else if (format == PETSC_VIEWER_ASCII_COMMON) {
375: Mat B;
377: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
378: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
379: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
380: PetscCall(MatView_SeqAIJ(B, viewer));
381: PetscCall(MatDestroy(&B));
382: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
383: PetscFunctionReturn(PETSC_SUCCESS);
384: } else {
385: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE));
386: if (A->factortype) { /* for factored matrix */
387: PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "matrix is factored with bs>1. Not implemented yet");
389: diag = a->diag;
390: for (i = 0; i < a->mbs; i++) { /* for row block i */
391: PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i));
392: /* diagonal entry */
393: #if defined(PETSC_USE_COMPLEX)
394: if (PetscImaginaryPart(a->a[diag[i]]) > 0.0) {
395: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]]), (double)PetscImaginaryPart(1.0 / a->a[diag[i]])));
396: } else if (PetscImaginaryPart(a->a[diag[i]]) < 0.0) {
397: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]]), -(double)PetscImaginaryPart(1.0 / a->a[diag[i]])));
398: } else {
399: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]])));
400: }
401: #else
402: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)(1.0 / a->a[diag[i]])));
403: #endif
404: /* off-diagonal entries */
405: for (k = a->i[i]; k < a->i[i + 1] - 1; k++) {
406: #if defined(PETSC_USE_COMPLEX)
407: if (PetscImaginaryPart(a->a[k]) > 0.0) {
408: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), (double)PetscImaginaryPart(a->a[k])));
409: } else if (PetscImaginaryPart(a->a[k]) < 0.0) {
410: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), -(double)PetscImaginaryPart(a->a[k])));
411: } else {
412: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k], (double)PetscRealPart(a->a[k])));
413: }
414: #else
415: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[k], (double)a->a[k]));
416: #endif
417: }
418: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
419: }
421: } else { /* for non-factored matrix */
422: for (i = 0; i < a->mbs; i++) { /* for row block i */
423: for (j = 0; j < bs; j++) { /* for row bs*i + j */
424: PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j));
425: for (k = a->i[i]; k < a->i[i + 1]; k++) { /* for column block */
426: for (l = 0; l < bs; l++) { /* for column */
427: #if defined(PETSC_USE_COMPLEX)
428: if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0) {
429: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), (double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j])));
430: } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0) {
431: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j]), -(double)PetscImaginaryPart(a->a[bs2 * k + l * bs + j])));
432: } else {
433: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j])));
434: }
435: #else
436: PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j]));
437: #endif
438: }
439: }
440: PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
441: }
442: }
443: }
444: PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE));
445: }
446: PetscCall(PetscViewerFlush(viewer));
447: PetscFunctionReturn(PETSC_SUCCESS);
448: }
450: #include <petscdraw.h>
451: static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw, void *Aa)
452: {
453: Mat A = (Mat)Aa;
454: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
455: PetscInt row, i, j, k, l, mbs = a->mbs, color, bs = A->rmap->bs, bs2 = a->bs2;
456: PetscReal xl, yl, xr, yr, x_l, x_r, y_l, y_r;
457: MatScalar *aa;
458: PetscViewer viewer;
460: PetscFunctionBegin;
461: PetscCall(PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer));
462: PetscCall(PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr));
464: /* loop over matrix elements drawing boxes */
466: PetscDrawCollectiveBegin(draw);
467: PetscCall(PetscDrawString(draw, .3 * (xl + xr), .3 * (yl + yr), PETSC_DRAW_BLACK, "symmetric"));
468: /* Blue for negative, Cyan for zero and Red for positive */
469: color = PETSC_DRAW_BLUE;
470: for (i = 0, row = 0; i < mbs; i++, row += bs) {
471: for (j = a->i[i]; j < a->i[i + 1]; j++) {
472: y_l = A->rmap->N - row - 1.0;
473: y_r = y_l + 1.0;
474: x_l = a->j[j] * bs;
475: x_r = x_l + 1.0;
476: aa = a->a + j * bs2;
477: for (k = 0; k < bs; k++) {
478: for (l = 0; l < bs; l++) {
479: if (PetscRealPart(*aa++) >= 0.) continue;
480: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
481: }
482: }
483: }
484: }
485: color = PETSC_DRAW_CYAN;
486: for (i = 0, row = 0; i < mbs; i++, row += bs) {
487: for (j = a->i[i]; j < a->i[i + 1]; j++) {
488: y_l = A->rmap->N - row - 1.0;
489: y_r = y_l + 1.0;
490: x_l = a->j[j] * bs;
491: x_r = x_l + 1.0;
492: aa = a->a + j * bs2;
493: for (k = 0; k < bs; k++) {
494: for (l = 0; l < bs; l++) {
495: if (PetscRealPart(*aa++) != 0.) continue;
496: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
497: }
498: }
499: }
500: }
501: color = PETSC_DRAW_RED;
502: for (i = 0, row = 0; i < mbs; i++, row += bs) {
503: for (j = a->i[i]; j < a->i[i + 1]; j++) {
504: y_l = A->rmap->N - row - 1.0;
505: y_r = y_l + 1.0;
506: x_l = a->j[j] * bs;
507: x_r = x_l + 1.0;
508: aa = a->a + j * bs2;
509: for (k = 0; k < bs; k++) {
510: for (l = 0; l < bs; l++) {
511: if (PetscRealPart(*aa++) <= 0.) continue;
512: PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
513: }
514: }
515: }
516: }
517: PetscDrawCollectiveEnd(draw);
518: PetscFunctionReturn(PETSC_SUCCESS);
519: }
521: static PetscErrorCode MatView_SeqSBAIJ_Draw(Mat A, PetscViewer viewer)
522: {
523: PetscReal xl, yl, xr, yr, w, h;
524: PetscDraw draw;
525: PetscBool isnull;
527: PetscFunctionBegin;
528: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
529: PetscCall(PetscDrawIsNull(draw, &isnull));
530: if (isnull) PetscFunctionReturn(PETSC_SUCCESS);
532: xr = A->rmap->N;
533: yr = A->rmap->N;
534: h = yr / 10.0;
535: w = xr / 10.0;
536: xr += w;
537: yr += h;
538: xl = -w;
539: yl = -h;
540: PetscCall(PetscDrawSetCoordinates(draw, xl, yl, xr, yr));
541: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer));
542: PetscCall(PetscDrawZoom(draw, MatView_SeqSBAIJ_Draw_Zoom, A));
543: PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL));
544: PetscCall(PetscDrawSave(draw));
545: PetscFunctionReturn(PETSC_SUCCESS);
546: }
548: /* Used for both MPIBAIJ and MPISBAIJ matrices */
549: #define MatView_SeqSBAIJ_Binary MatView_SeqBAIJ_Binary
551: PetscErrorCode MatView_SeqSBAIJ(Mat A, PetscViewer viewer)
552: {
553: PetscBool iascii, isbinary, isdraw;
555: PetscFunctionBegin;
556: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
557: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
558: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
559: if (iascii) {
560: PetscCall(MatView_SeqSBAIJ_ASCII(A, viewer));
561: } else if (isbinary) {
562: PetscCall(MatView_SeqSBAIJ_Binary(A, viewer));
563: } else if (isdraw) {
564: PetscCall(MatView_SeqSBAIJ_Draw(A, viewer));
565: } else {
566: Mat B;
567: const char *matname;
568: PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
569: if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
570: if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
571: PetscCall(MatView(B, viewer));
572: PetscCall(MatDestroy(&B));
573: }
574: PetscFunctionReturn(PETSC_SUCCESS);
575: }
577: PetscErrorCode MatGetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], PetscScalar v[])
578: {
579: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
580: PetscInt *rp, k, low, high, t, row, nrow, i, col, l, *aj = a->j;
581: PetscInt *ai = a->i, *ailen = a->ilen;
582: PetscInt brow, bcol, ridx, cidx, bs = A->rmap->bs, bs2 = a->bs2;
583: MatScalar *ap, *aa = a->a;
585: PetscFunctionBegin;
586: for (k = 0; k < m; k++) { /* loop over rows */
587: row = im[k];
588: brow = row / bs;
589: if (row < 0) {
590: v += n;
591: continue;
592: } /* negative row */
593: PetscCheck(row < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, row, A->rmap->N - 1);
594: rp = aj + ai[brow];
595: ap = aa + bs2 * ai[brow];
596: nrow = ailen[brow];
597: for (l = 0; l < n; l++) { /* loop over columns */
598: if (in[l] < 0) {
599: v++;
600: continue;
601: } /* negative column */
602: PetscCheck(in[l] < A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[l], A->cmap->n - 1);
603: col = in[l];
604: bcol = col / bs;
605: cidx = col % bs;
606: ridx = row % bs;
607: high = nrow;
608: low = 0; /* assume unsorted */
609: while (high - low > 5) {
610: t = (low + high) / 2;
611: if (rp[t] > bcol) high = t;
612: else low = t;
613: }
614: for (i = low; i < high; i++) {
615: if (rp[i] > bcol) break;
616: if (rp[i] == bcol) {
617: *v++ = ap[bs2 * i + bs * cidx + ridx];
618: goto finished;
619: }
620: }
621: *v++ = 0.0;
622: finished:;
623: }
624: }
625: PetscFunctionReturn(PETSC_SUCCESS);
626: }
628: PetscErrorCode MatPermute_SeqSBAIJ(Mat A, IS rowp, IS colp, Mat *B)
629: {
630: Mat C;
632: PetscFunctionBegin;
633: PetscCall(MatConvert(A, MATSEQBAIJ, MAT_INITIAL_MATRIX, &C));
634: PetscCall(MatPermute(C, rowp, colp, B));
635: PetscCall(MatDestroy(&C));
636: if (rowp == colp) PetscCall(MatConvert(*B, MATSEQSBAIJ, MAT_INPLACE_MATRIX, B));
637: PetscFunctionReturn(PETSC_SUCCESS);
638: }
640: PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
641: {
642: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
643: PetscInt *rp, k, low, high, t, ii, jj, row, nrow, i, col, l, rmax, N, lastcol = -1;
644: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen;
645: PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs, stepval;
646: PetscBool roworiented = a->roworiented;
647: const PetscScalar *value = v;
648: MatScalar *ap, *aa = a->a, *bap;
650: PetscFunctionBegin;
651: if (roworiented) stepval = (n - 1) * bs;
652: else stepval = (m - 1) * bs;
654: for (k = 0; k < m; k++) { /* loop over added rows */
655: row = im[k];
656: if (row < 0) continue;
657: PetscCheck(row < a->mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block index row too large %" PetscInt_FMT " max %" PetscInt_FMT, row, a->mbs - 1);
658: rp = aj + ai[row];
659: ap = aa + bs2 * ai[row];
660: rmax = imax[row];
661: nrow = ailen[row];
662: low = 0;
663: high = nrow;
664: for (l = 0; l < n; l++) { /* loop over added columns */
665: if (in[l] < 0) continue;
666: col = in[l];
667: PetscCheck(col < a->nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block index column too large %" PetscInt_FMT " max %" PetscInt_FMT, col, a->nbs - 1);
668: if (col < row) {
669: if (a->ignore_ltriangular) continue; /* ignore lower triangular block */
670: else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
671: }
672: if (roworiented) value = v + k * (stepval + bs) * bs + l * bs;
673: else value = v + l * (stepval + bs) * bs + k * bs;
675: if (col <= lastcol) low = 0;
676: else high = nrow;
678: lastcol = col;
679: while (high - low > 7) {
680: t = (low + high) / 2;
681: if (rp[t] > col) high = t;
682: else low = t;
683: }
684: for (i = low; i < high; i++) {
685: if (rp[i] > col) break;
686: if (rp[i] == col) {
687: bap = ap + bs2 * i;
688: if (roworiented) {
689: if (is == ADD_VALUES) {
690: for (ii = 0; ii < bs; ii++, value += stepval) {
691: for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
692: }
693: } else {
694: for (ii = 0; ii < bs; ii++, value += stepval) {
695: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
696: }
697: }
698: } else {
699: if (is == ADD_VALUES) {
700: for (ii = 0; ii < bs; ii++, value += stepval) {
701: for (jj = 0; jj < bs; jj++) *bap++ += *value++;
702: }
703: } else {
704: for (ii = 0; ii < bs; ii++, value += stepval) {
705: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
706: }
707: }
708: }
709: goto noinsert2;
710: }
711: }
712: if (nonew == 1) goto noinsert2;
713: PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new block index nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col);
714: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
715: N = nrow++ - 1;
716: high++;
717: /* shift up all the later entries in this row */
718: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
719: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
720: PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
721: rp[i] = col;
722: bap = ap + bs2 * i;
723: if (roworiented) {
724: for (ii = 0; ii < bs; ii++, value += stepval) {
725: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
726: }
727: } else {
728: for (ii = 0; ii < bs; ii++, value += stepval) {
729: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
730: }
731: }
732: noinsert2:;
733: low = i;
734: }
735: ailen[row] = nrow;
736: }
737: PetscFunctionReturn(PETSC_SUCCESS);
738: }
740: /*
741: This is not yet used
742: */
743: PetscErrorCode MatAssemblyEnd_SeqSBAIJ_SeqAIJ_Inode(Mat A)
744: {
745: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
746: const PetscInt *ai = a->i, *aj = a->j, *cols;
747: PetscInt i = 0, j, blk_size, m = A->rmap->n, node_count = 0, nzx, nzy, *ns, row, nz, cnt, cnt2, *counts;
748: PetscBool flag;
750: PetscFunctionBegin;
751: PetscCall(PetscMalloc1(m, &ns));
752: while (i < m) {
753: nzx = ai[i + 1] - ai[i]; /* Number of nonzeros */
754: /* Limits the number of elements in a node to 'a->inode.limit' */
755: for (j = i + 1, blk_size = 1; j < m && blk_size < a->inode.limit; ++j, ++blk_size) {
756: nzy = ai[j + 1] - ai[j];
757: if (nzy != (nzx - j + i)) break;
758: PetscCall(PetscArraycmp(aj + ai[i] + j - i, aj + ai[j], nzy, &flag));
759: if (!flag) break;
760: }
761: ns[node_count++] = blk_size;
763: i = j;
764: }
765: if (!a->inode.size && m && node_count > .9 * m) {
766: PetscCall(PetscFree(ns));
767: PetscCall(PetscInfo(A, "Found %" PetscInt_FMT " nodes out of %" PetscInt_FMT " rows. Not using Inode routines\n", node_count, m));
768: } else {
769: a->inode.node_count = node_count;
771: PetscCall(PetscMalloc1(node_count, &a->inode.size));
772: PetscCall(PetscArraycpy(a->inode.size, ns, node_count));
773: PetscCall(PetscFree(ns));
774: PetscCall(PetscInfo(A, "Found %" PetscInt_FMT " nodes of %" PetscInt_FMT ". Limit used: %" PetscInt_FMT ". Using Inode routines\n", node_count, m, a->inode.limit));
776: /* count collections of adjacent columns in each inode */
777: row = 0;
778: cnt = 0;
779: for (i = 0; i < node_count; i++) {
780: cols = aj + ai[row] + a->inode.size[i];
781: nz = ai[row + 1] - ai[row] - a->inode.size[i];
782: for (j = 1; j < nz; j++) {
783: if (cols[j] != cols[j - 1] + 1) cnt++;
784: }
785: cnt++;
786: row += a->inode.size[i];
787: }
788: PetscCall(PetscMalloc1(2 * cnt, &counts));
789: cnt = 0;
790: row = 0;
791: for (i = 0; i < node_count; i++) {
792: cols = aj + ai[row] + a->inode.size[i];
793: counts[2 * cnt] = cols[0];
794: nz = ai[row + 1] - ai[row] - a->inode.size[i];
795: cnt2 = 1;
796: for (j = 1; j < nz; j++) {
797: if (cols[j] != cols[j - 1] + 1) {
798: counts[2 * (cnt++) + 1] = cnt2;
799: counts[2 * cnt] = cols[j];
800: cnt2 = 1;
801: } else cnt2++;
802: }
803: counts[2 * (cnt++) + 1] = cnt2;
804: row += a->inode.size[i];
805: }
806: PetscCall(PetscIntView(2 * cnt, counts, NULL));
807: }
808: PetscFunctionReturn(PETSC_SUCCESS);
809: }
811: PetscErrorCode MatAssemblyEnd_SeqSBAIJ(Mat A, MatAssemblyType mode)
812: {
813: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
814: PetscInt fshift = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax;
815: PetscInt m = A->rmap->N, *ip, N, *ailen = a->ilen;
816: PetscInt mbs = a->mbs, bs2 = a->bs2, rmax = 0;
817: MatScalar *aa = a->a, *ap;
819: PetscFunctionBegin;
820: if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(PETSC_SUCCESS);
822: if (m) rmax = ailen[0];
823: for (i = 1; i < mbs; i++) {
824: /* move each row back by the amount of empty slots (fshift) before it*/
825: fshift += imax[i - 1] - ailen[i - 1];
826: rmax = PetscMax(rmax, ailen[i]);
827: if (fshift) {
828: ip = aj + ai[i];
829: ap = aa + bs2 * ai[i];
830: N = ailen[i];
831: PetscCall(PetscArraymove(ip - fshift, ip, N));
832: PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2 * N));
833: }
834: ai[i] = ai[i - 1] + ailen[i - 1];
835: }
836: if (mbs) {
837: fshift += imax[mbs - 1] - ailen[mbs - 1];
838: ai[mbs] = ai[mbs - 1] + ailen[mbs - 1];
839: }
840: /* reset ilen and imax for each row */
841: for (i = 0; i < mbs; i++) ailen[i] = imax[i] = ai[i + 1] - ai[i];
842: a->nz = ai[mbs];
844: /* diagonals may have moved, reset it */
845: if (a->diag) PetscCall(PetscArraycpy(a->diag, ai, mbs));
846: PetscCheck(!fshift || a->nounused != -1, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Unused space detected in matrix: %" PetscInt_FMT " X %" PetscInt_FMT " block size %" PetscInt_FMT ", %" PetscInt_FMT " unneeded", m, A->cmap->n, A->rmap->bs, fshift * bs2);
848: PetscCall(PetscInfo(A, "Matrix size: %" PetscInt_FMT " X %" PetscInt_FMT ", block size %" PetscInt_FMT "; storage space: %" PetscInt_FMT " unneeded, %" PetscInt_FMT " used\n", m, A->rmap->N, A->rmap->bs, fshift * bs2, a->nz * bs2));
849: PetscCall(PetscInfo(A, "Number of mallocs during MatSetValues is %" PetscInt_FMT "\n", a->reallocs));
850: PetscCall(PetscInfo(A, "Most nonzeros blocks in any row is %" PetscInt_FMT "\n", rmax));
852: A->info.mallocs += a->reallocs;
853: a->reallocs = 0;
854: A->info.nz_unneeded = (PetscReal)fshift * bs2;
855: a->idiagvalid = PETSC_FALSE;
856: a->rmax = rmax;
858: if (A->cmap->n < 65536 && A->cmap->bs == 1) {
859: if (a->jshort && a->free_jshort) {
860: /* when matrix data structure is changed, previous jshort must be replaced */
861: PetscCall(PetscFree(a->jshort));
862: }
863: PetscCall(PetscMalloc1(a->i[A->rmap->n], &a->jshort));
864: for (i = 0; i < a->i[A->rmap->n]; i++) a->jshort[i] = a->j[i];
865: A->ops->mult = MatMult_SeqSBAIJ_1_ushort;
866: A->ops->sor = MatSOR_SeqSBAIJ_ushort;
867: a->free_jshort = PETSC_TRUE;
868: }
869: PetscFunctionReturn(PETSC_SUCCESS);
870: }
872: /*
873: This function returns an array of flags which indicate the locations of contiguous
874: blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9]
875: then the resulting sizes = [3,1,1,3,1] corresponding to sets [(0,1,2),(3),(5),(6,7,8),(9)]
876: Assume: sizes should be long enough to hold all the values.
877: */
878: PetscErrorCode MatZeroRows_SeqSBAIJ_Check_Blocks(PetscInt idx[], PetscInt n, PetscInt bs, PetscInt sizes[], PetscInt *bs_max)
879: {
880: PetscInt i, j, k, row;
881: PetscBool flg;
883: PetscFunctionBegin;
884: for (i = 0, j = 0; i < n; j++) {
885: row = idx[i];
886: if (row % bs != 0) { /* Not the beginning of a block */
887: sizes[j] = 1;
888: i++;
889: } else if (i + bs > n) { /* Beginning of a block, but complete block doesn't exist (at idx end) */
890: sizes[j] = 1; /* Also makes sure at least 'bs' values exist for next else */
891: i++;
892: } else { /* Beginning of the block, so check if the complete block exists */
893: flg = PETSC_TRUE;
894: for (k = 1; k < bs; k++) {
895: if (row + k != idx[i + k]) { /* break in the block */
896: flg = PETSC_FALSE;
897: break;
898: }
899: }
900: if (flg) { /* No break in the bs */
901: sizes[j] = bs;
902: i += bs;
903: } else {
904: sizes[j] = 1;
905: i++;
906: }
907: }
908: }
909: *bs_max = j;
910: PetscFunctionReturn(PETSC_SUCCESS);
911: }
913: /* Only add/insert a(i,j) with i<=j (blocks).
914: Any a(i,j) with i>j input by user is ignored.
915: */
917: PetscErrorCode MatSetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
918: {
919: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
920: PetscInt *rp, k, low, high, t, ii, row, nrow, i, col, l, rmax, N, lastcol = -1;
921: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen, roworiented = a->roworiented;
922: PetscInt *aj = a->j, nonew = a->nonew, bs = A->rmap->bs, brow, bcol;
923: PetscInt ridx, cidx, bs2 = a->bs2;
924: MatScalar *ap, value, *aa = a->a, *bap;
926: PetscFunctionBegin;
927: for (k = 0; k < m; k++) { /* loop over added rows */
928: row = im[k]; /* row number */
929: brow = row / bs; /* block row number */
930: if (row < 0) continue;
931: PetscCheck(row < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, row, A->rmap->N - 1);
932: rp = aj + ai[brow]; /*ptr to beginning of column value of the row block*/
933: ap = aa + bs2 * ai[brow]; /*ptr to beginning of element value of the row block*/
934: rmax = imax[brow]; /* maximum space allocated for this row */
935: nrow = ailen[brow]; /* actual length of this row */
936: low = 0;
937: high = nrow;
938: for (l = 0; l < n; l++) { /* loop over added columns */
939: if (in[l] < 0) continue;
940: PetscCheck(in[l] < A->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[l], A->cmap->N - 1);
941: col = in[l];
942: bcol = col / bs; /* block col number */
944: if (brow > bcol) {
945: if (a->ignore_ltriangular) continue; /* ignore lower triangular values */
946: else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
947: }
949: ridx = row % bs;
950: cidx = col % bs; /*row and col index inside the block */
951: if ((brow == bcol && ridx <= cidx) || (brow < bcol)) {
952: /* element value a(k,l) */
953: if (roworiented) value = v[l + k * n];
954: else value = v[k + l * m];
956: /* move pointer bap to a(k,l) quickly and add/insert value */
957: if (col <= lastcol) low = 0;
958: else high = nrow;
960: lastcol = col;
961: while (high - low > 7) {
962: t = (low + high) / 2;
963: if (rp[t] > bcol) high = t;
964: else low = t;
965: }
966: for (i = low; i < high; i++) {
967: if (rp[i] > bcol) break;
968: if (rp[i] == bcol) {
969: bap = ap + bs2 * i + bs * cidx + ridx;
970: if (is == ADD_VALUES) *bap += value;
971: else *bap = value;
972: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
973: if (brow == bcol && ridx < cidx) {
974: bap = ap + bs2 * i + bs * ridx + cidx;
975: if (is == ADD_VALUES) *bap += value;
976: else *bap = value;
977: }
978: goto noinsert1;
979: }
980: }
982: if (nonew == 1) goto noinsert1;
983: PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col);
984: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
986: N = nrow++ - 1;
987: high++;
988: /* shift up all the later entries in this row */
989: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
990: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
991: PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
992: rp[i] = bcol;
993: ap[bs2 * i + bs * cidx + ridx] = value;
994: /* for diag block, add/insert its symmetric element a(cidx,ridx) */
995: if (brow == bcol && ridx < cidx) ap[bs2 * i + bs * ridx + cidx] = value;
996: A->nonzerostate++;
997: noinsert1:;
998: low = i;
999: }
1000: } /* end of loop over added columns */
1001: ailen[brow] = nrow;
1002: } /* end of loop over added rows */
1003: PetscFunctionReturn(PETSC_SUCCESS);
1004: }
1006: PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA, IS row, const MatFactorInfo *info)
1007: {
1008: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)inA->data;
1009: Mat outA;
1010: PetscBool row_identity;
1012: PetscFunctionBegin;
1013: PetscCheck(info->levels == 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only levels=0 is supported for in-place icc");
1014: PetscCall(ISIdentity(row, &row_identity));
1015: PetscCheck(row_identity, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix reordering is not supported");
1016: PetscCheck(inA->rmap->bs == 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix block size %" PetscInt_FMT " is not supported", inA->rmap->bs); /* Need to replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR()! */
1018: outA = inA;
1019: inA->factortype = MAT_FACTOR_ICC;
1020: PetscCall(PetscFree(inA->solvertype));
1021: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &inA->solvertype));
1023: PetscCall(MatMarkDiagonal_SeqSBAIJ(inA));
1024: PetscCall(MatSeqSBAIJSetNumericFactorization_inplace(inA, row_identity));
1026: PetscCall(PetscObjectReference((PetscObject)row));
1027: PetscCall(ISDestroy(&a->row));
1028: a->row = row;
1029: PetscCall(PetscObjectReference((PetscObject)row));
1030: PetscCall(ISDestroy(&a->col));
1031: a->col = row;
1033: /* Create the invert permutation so that it can be used in MatCholeskyFactorNumeric() */
1034: if (a->icol) PetscCall(ISInvertPermutation(row, PETSC_DECIDE, &a->icol));
1036: if (!a->solve_work) PetscCall(PetscMalloc1(inA->rmap->N + inA->rmap->bs, &a->solve_work));
1038: PetscCall(MatCholeskyFactorNumeric(outA, inA, info));
1039: PetscFunctionReturn(PETSC_SUCCESS);
1040: }
1042: PetscErrorCode MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat, PetscInt *indices)
1043: {
1044: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data;
1045: PetscInt i, nz, n;
1047: PetscFunctionBegin;
1048: nz = baij->maxnz;
1049: n = mat->cmap->n;
1050: for (i = 0; i < nz; i++) baij->j[i] = indices[i];
1052: baij->nz = nz;
1053: for (i = 0; i < n; i++) baij->ilen[i] = baij->imax[i];
1055: PetscCall(MatSetOption(mat, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
1056: PetscFunctionReturn(PETSC_SUCCESS);
1057: }
1059: /*@
1060: MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows
1061: in a `MATSEQSBAIJ` matrix.
1063: Input Parameters:
1064: + mat - the `MATSEQSBAIJ` matrix
1065: - indices - the column indices
1067: Level: advanced
1069: Notes:
1070: This can be called if you have precomputed the nonzero structure of the
1071: matrix and want to provide it to the matrix object to improve the performance
1072: of the `MatSetValues()` operation.
1074: You MUST have set the correct numbers of nonzeros per row in the call to
1075: `MatCreateSeqSBAIJ()`, and the columns indices MUST be sorted.
1077: MUST be called before any calls to `MatSetValues()`
1079: .seealso: [](chapter_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ`
1080: @*/
1081: PetscErrorCode MatSeqSBAIJSetColumnIndices(Mat mat, PetscInt *indices)
1082: {
1083: PetscFunctionBegin;
1086: PetscUseMethod(mat, "MatSeqSBAIJSetColumnIndices_C", (Mat, PetscInt *), (mat, indices));
1087: PetscFunctionReturn(PETSC_SUCCESS);
1088: }
1090: PetscErrorCode MatCopy_SeqSBAIJ(Mat A, Mat B, MatStructure str)
1091: {
1092: PetscBool isbaij;
1094: PetscFunctionBegin;
1095: PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isbaij, MATSEQSBAIJ, MATMPISBAIJ, ""));
1096: PetscCheck(isbaij, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for matrix type %s", ((PetscObject)B)->type_name);
1097: /* If the two matrices have the same copy implementation and nonzero pattern, use fast copy. */
1098: if (str == SAME_NONZERO_PATTERN && A->ops->copy == B->ops->copy) {
1099: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1100: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1102: PetscCheck(a->i[a->mbs] == b->i[b->mbs], PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of nonzeros in two matrices are different");
1103: PetscCheck(a->mbs == b->mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of rows in two matrices are different");
1104: PetscCheck(a->bs2 == b->bs2, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Different block size");
1105: PetscCall(PetscArraycpy(b->a, a->a, a->bs2 * a->i[a->mbs]));
1106: PetscCall(PetscObjectStateIncrease((PetscObject)B));
1107: } else {
1108: PetscCall(MatGetRowUpperTriangular(A));
1109: PetscCall(MatCopy_Basic(A, B, str));
1110: PetscCall(MatRestoreRowUpperTriangular(A));
1111: }
1112: PetscFunctionReturn(PETSC_SUCCESS);
1113: }
1115: static PetscErrorCode MatSeqSBAIJGetArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1116: {
1117: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1119: PetscFunctionBegin;
1120: *array = a->a;
1121: PetscFunctionReturn(PETSC_SUCCESS);
1122: }
1124: static PetscErrorCode MatSeqSBAIJRestoreArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1125: {
1126: PetscFunctionBegin;
1127: *array = NULL;
1128: PetscFunctionReturn(PETSC_SUCCESS);
1129: }
1131: PetscErrorCode MatAXPYGetPreallocation_SeqSBAIJ(Mat Y, Mat X, PetscInt *nnz)
1132: {
1133: PetscInt bs = Y->rmap->bs, mbs = Y->rmap->N / bs;
1134: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data;
1135: Mat_SeqSBAIJ *y = (Mat_SeqSBAIJ *)Y->data;
1137: PetscFunctionBegin;
1138: /* Set the number of nonzeros in the new matrix */
1139: PetscCall(MatAXPYGetPreallocation_SeqX_private(mbs, x->i, x->j, y->i, y->j, nnz));
1140: PetscFunctionReturn(PETSC_SUCCESS);
1141: }
1143: PetscErrorCode MatAXPY_SeqSBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str)
1144: {
1145: Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data, *y = (Mat_SeqSBAIJ *)Y->data;
1146: PetscInt bs = Y->rmap->bs, bs2 = bs * bs;
1147: PetscBLASInt one = 1;
1149: PetscFunctionBegin;
1150: if (str == UNKNOWN_NONZERO_PATTERN || (PetscDefined(USE_DEBUG) && str == SAME_NONZERO_PATTERN)) {
1151: PetscBool e = x->nz == y->nz && x->mbs == y->mbs ? PETSC_TRUE : PETSC_FALSE;
1152: if (e) {
1153: PetscCall(PetscArraycmp(x->i, y->i, x->mbs + 1, &e));
1154: if (e) {
1155: PetscCall(PetscArraycmp(x->j, y->j, x->i[x->mbs], &e));
1156: if (e) str = SAME_NONZERO_PATTERN;
1157: }
1158: }
1159: if (!e) PetscCheck(str != SAME_NONZERO_PATTERN, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "MatStructure is not SAME_NONZERO_PATTERN");
1160: }
1161: if (str == SAME_NONZERO_PATTERN) {
1162: PetscScalar alpha = a;
1163: PetscBLASInt bnz;
1164: PetscCall(PetscBLASIntCast(x->nz * bs2, &bnz));
1165: PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one));
1166: PetscCall(PetscObjectStateIncrease((PetscObject)Y));
1167: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1168: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE));
1169: PetscCall(MatAXPY_Basic(Y, a, X, str));
1170: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE));
1171: } else {
1172: Mat B;
1173: PetscInt *nnz;
1174: PetscCheck(bs == X->rmap->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Matrices must have same block size");
1175: PetscCall(MatGetRowUpperTriangular(X));
1176: PetscCall(MatGetRowUpperTriangular(Y));
1177: PetscCall(PetscMalloc1(Y->rmap->N, &nnz));
1178: PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B));
1179: PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name));
1180: PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N));
1181: PetscCall(MatSetBlockSizesFromMats(B, Y, Y));
1182: PetscCall(MatSetType(B, ((PetscObject)Y)->type_name));
1183: PetscCall(MatAXPYGetPreallocation_SeqSBAIJ(Y, X, nnz));
1184: PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));
1186: PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str));
1188: PetscCall(MatHeaderMerge(Y, &B));
1189: PetscCall(PetscFree(nnz));
1190: PetscCall(MatRestoreRowUpperTriangular(X));
1191: PetscCall(MatRestoreRowUpperTriangular(Y));
1192: }
1193: PetscFunctionReturn(PETSC_SUCCESS);
1194: }
1196: PetscErrorCode MatIsSymmetric_SeqSBAIJ(Mat A, PetscReal tol, PetscBool *flg)
1197: {
1198: PetscFunctionBegin;
1199: *flg = PETSC_TRUE;
1200: PetscFunctionReturn(PETSC_SUCCESS);
1201: }
1203: PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A, PetscBool *flg)
1204: {
1205: PetscFunctionBegin;
1206: *flg = PETSC_TRUE;
1207: PetscFunctionReturn(PETSC_SUCCESS);
1208: }
1210: PetscErrorCode MatIsHermitian_SeqSBAIJ(Mat A, PetscReal tol, PetscBool *flg)
1211: {
1212: PetscFunctionBegin;
1213: *flg = PETSC_FALSE;
1214: PetscFunctionReturn(PETSC_SUCCESS);
1215: }
1217: PetscErrorCode MatConjugate_SeqSBAIJ(Mat A)
1218: {
1219: #if defined(PETSC_USE_COMPLEX)
1220: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1221: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1222: MatScalar *aa = a->a;
1224: PetscFunctionBegin;
1225: for (i = 0; i < nz; i++) aa[i] = PetscConj(aa[i]);
1226: #else
1227: PetscFunctionBegin;
1228: #endif
1229: PetscFunctionReturn(PETSC_SUCCESS);
1230: }
1232: PetscErrorCode MatRealPart_SeqSBAIJ(Mat A)
1233: {
1234: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1235: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1236: MatScalar *aa = a->a;
1238: PetscFunctionBegin;
1239: for (i = 0; i < nz; i++) aa[i] = PetscRealPart(aa[i]);
1240: PetscFunctionReturn(PETSC_SUCCESS);
1241: }
1243: PetscErrorCode MatImaginaryPart_SeqSBAIJ(Mat A)
1244: {
1245: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1246: PetscInt i, nz = a->bs2 * a->i[a->mbs];
1247: MatScalar *aa = a->a;
1249: PetscFunctionBegin;
1250: for (i = 0; i < nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
1251: PetscFunctionReturn(PETSC_SUCCESS);
1252: }
1254: PetscErrorCode MatZeroRowsColumns_SeqSBAIJ(Mat A, PetscInt is_n, const PetscInt is_idx[], PetscScalar diag, Vec x, Vec b)
1255: {
1256: Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)A->data;
1257: PetscInt i, j, k, count;
1258: PetscInt bs = A->rmap->bs, bs2 = baij->bs2, row, col;
1259: PetscScalar zero = 0.0;
1260: MatScalar *aa;
1261: const PetscScalar *xx;
1262: PetscScalar *bb;
1263: PetscBool *zeroed, vecs = PETSC_FALSE;
1265: PetscFunctionBegin;
1266: /* fix right hand side if needed */
1267: if (x && b) {
1268: PetscCall(VecGetArrayRead(x, &xx));
1269: PetscCall(VecGetArray(b, &bb));
1270: vecs = PETSC_TRUE;
1271: }
1273: /* zero the columns */
1274: PetscCall(PetscCalloc1(A->rmap->n, &zeroed));
1275: for (i = 0; i < is_n; i++) {
1276: PetscCheck(is_idx[i] >= 0 && is_idx[i] < A->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "row %" PetscInt_FMT " out of range", is_idx[i]);
1277: zeroed[is_idx[i]] = PETSC_TRUE;
1278: }
1279: if (vecs) {
1280: for (i = 0; i < A->rmap->N; i++) {
1281: row = i / bs;
1282: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1283: for (k = 0; k < bs; k++) {
1284: col = bs * baij->j[j] + k;
1285: if (col <= i) continue;
1286: aa = ((MatScalar *)(baij->a)) + j * bs2 + (i % bs) + bs * k;
1287: if (!zeroed[i] && zeroed[col]) bb[i] -= aa[0] * xx[col];
1288: if (zeroed[i] && !zeroed[col]) bb[col] -= aa[0] * xx[i];
1289: }
1290: }
1291: }
1292: for (i = 0; i < is_n; i++) bb[is_idx[i]] = diag * xx[is_idx[i]];
1293: }
1295: for (i = 0; i < A->rmap->N; i++) {
1296: if (!zeroed[i]) {
1297: row = i / bs;
1298: for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1299: for (k = 0; k < bs; k++) {
1300: col = bs * baij->j[j] + k;
1301: if (zeroed[col]) {
1302: aa = ((MatScalar *)(baij->a)) + j * bs2 + (i % bs) + bs * k;
1303: aa[0] = 0.0;
1304: }
1305: }
1306: }
1307: }
1308: }
1309: PetscCall(PetscFree(zeroed));
1310: if (vecs) {
1311: PetscCall(VecRestoreArrayRead(x, &xx));
1312: PetscCall(VecRestoreArray(b, &bb));
1313: }
1315: /* zero the rows */
1316: for (i = 0; i < is_n; i++) {
1317: row = is_idx[i];
1318: count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs;
1319: aa = ((MatScalar *)(baij->a)) + baij->i[row / bs] * bs2 + (row % bs);
1320: for (k = 0; k < count; k++) {
1321: aa[0] = zero;
1322: aa += bs;
1323: }
1324: if (diag != 0.0) PetscUseTypeMethod(A, setvalues, 1, &row, 1, &row, &diag, INSERT_VALUES);
1325: }
1326: PetscCall(MatAssemblyEnd_SeqSBAIJ(A, MAT_FINAL_ASSEMBLY));
1327: PetscFunctionReturn(PETSC_SUCCESS);
1328: }
1330: PetscErrorCode MatShift_SeqSBAIJ(Mat Y, PetscScalar a)
1331: {
1332: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)Y->data;
1334: PetscFunctionBegin;
1335: if (!Y->preallocated || !aij->nz) PetscCall(MatSeqSBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL));
1336: PetscCall(MatShift_Basic(Y, a));
1337: PetscFunctionReturn(PETSC_SUCCESS);
1338: }
1340: static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ,
1341: MatGetRow_SeqSBAIJ,
1342: MatRestoreRow_SeqSBAIJ,
1343: MatMult_SeqSBAIJ_N,
1344: /* 4*/ MatMultAdd_SeqSBAIJ_N,
1345: MatMult_SeqSBAIJ_N, /* transpose versions are same as non-transpose versions */
1346: MatMultAdd_SeqSBAIJ_N,
1347: NULL,
1348: NULL,
1349: NULL,
1350: /* 10*/ NULL,
1351: NULL,
1352: MatCholeskyFactor_SeqSBAIJ,
1353: MatSOR_SeqSBAIJ,
1354: MatTranspose_SeqSBAIJ,
1355: /* 15*/ MatGetInfo_SeqSBAIJ,
1356: MatEqual_SeqSBAIJ,
1357: MatGetDiagonal_SeqSBAIJ,
1358: MatDiagonalScale_SeqSBAIJ,
1359: MatNorm_SeqSBAIJ,
1360: /* 20*/ NULL,
1361: MatAssemblyEnd_SeqSBAIJ,
1362: MatSetOption_SeqSBAIJ,
1363: MatZeroEntries_SeqSBAIJ,
1364: /* 24*/ NULL,
1365: NULL,
1366: NULL,
1367: NULL,
1368: NULL,
1369: /* 29*/ MatSetUp_Seq_Hash,
1370: NULL,
1371: NULL,
1372: NULL,
1373: NULL,
1374: /* 34*/ MatDuplicate_SeqSBAIJ,
1375: NULL,
1376: NULL,
1377: NULL,
1378: MatICCFactor_SeqSBAIJ,
1379: /* 39*/ MatAXPY_SeqSBAIJ,
1380: MatCreateSubMatrices_SeqSBAIJ,
1381: MatIncreaseOverlap_SeqSBAIJ,
1382: MatGetValues_SeqSBAIJ,
1383: MatCopy_SeqSBAIJ,
1384: /* 44*/ NULL,
1385: MatScale_SeqSBAIJ,
1386: MatShift_SeqSBAIJ,
1387: NULL,
1388: MatZeroRowsColumns_SeqSBAIJ,
1389: /* 49*/ NULL,
1390: MatGetRowIJ_SeqSBAIJ,
1391: MatRestoreRowIJ_SeqSBAIJ,
1392: NULL,
1393: NULL,
1394: /* 54*/ NULL,
1395: NULL,
1396: NULL,
1397: MatPermute_SeqSBAIJ,
1398: MatSetValuesBlocked_SeqSBAIJ,
1399: /* 59*/ MatCreateSubMatrix_SeqSBAIJ,
1400: NULL,
1401: NULL,
1402: NULL,
1403: NULL,
1404: /* 64*/ NULL,
1405: NULL,
1406: NULL,
1407: NULL,
1408: NULL,
1409: /* 69*/ MatGetRowMaxAbs_SeqSBAIJ,
1410: NULL,
1411: MatConvert_MPISBAIJ_Basic,
1412: NULL,
1413: NULL,
1414: /* 74*/ NULL,
1415: NULL,
1416: NULL,
1417: NULL,
1418: NULL,
1419: /* 79*/ NULL,
1420: NULL,
1421: NULL,
1422: MatGetInertia_SeqSBAIJ,
1423: MatLoad_SeqSBAIJ,
1424: /* 84*/ MatIsSymmetric_SeqSBAIJ,
1425: MatIsHermitian_SeqSBAIJ,
1426: MatIsStructurallySymmetric_SeqSBAIJ,
1427: NULL,
1428: NULL,
1429: /* 89*/ NULL,
1430: NULL,
1431: NULL,
1432: NULL,
1433: NULL,
1434: /* 94*/ NULL,
1435: NULL,
1436: NULL,
1437: NULL,
1438: NULL,
1439: /* 99*/ NULL,
1440: NULL,
1441: NULL,
1442: MatConjugate_SeqSBAIJ,
1443: NULL,
1444: /*104*/ NULL,
1445: MatRealPart_SeqSBAIJ,
1446: MatImaginaryPart_SeqSBAIJ,
1447: MatGetRowUpperTriangular_SeqSBAIJ,
1448: MatRestoreRowUpperTriangular_SeqSBAIJ,
1449: /*109*/ NULL,
1450: NULL,
1451: NULL,
1452: NULL,
1453: MatMissingDiagonal_SeqSBAIJ,
1454: /*114*/ NULL,
1455: NULL,
1456: NULL,
1457: NULL,
1458: NULL,
1459: /*119*/ NULL,
1460: NULL,
1461: NULL,
1462: NULL,
1463: NULL,
1464: /*124*/ NULL,
1465: NULL,
1466: NULL,
1467: NULL,
1468: NULL,
1469: /*129*/ NULL,
1470: NULL,
1471: NULL,
1472: NULL,
1473: NULL,
1474: /*134*/ NULL,
1475: NULL,
1476: NULL,
1477: NULL,
1478: NULL,
1479: /*139*/ MatSetBlockSizes_Default,
1480: NULL,
1481: NULL,
1482: NULL,
1483: NULL,
1484: /*144*/ MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ,
1485: NULL,
1486: NULL,
1487: NULL,
1488: NULL,
1489: NULL,
1490: /*150*/ NULL,
1491: NULL};
1493: PetscErrorCode MatStoreValues_SeqSBAIJ(Mat mat)
1494: {
1495: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1496: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1498: PetscFunctionBegin;
1499: PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1501: /* allocate space for values if not already there */
1502: if (!aij->saved_values) PetscCall(PetscMalloc1(nz + 1, &aij->saved_values));
1504: /* copy values over */
1505: PetscCall(PetscArraycpy(aij->saved_values, aij->a, nz));
1506: PetscFunctionReturn(PETSC_SUCCESS);
1507: }
1509: PetscErrorCode MatRetrieveValues_SeqSBAIJ(Mat mat)
1510: {
1511: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1512: PetscInt nz = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;
1514: PetscFunctionBegin;
1515: PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1516: PetscCheck(aij->saved_values, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatStoreValues(A);first");
1518: /* copy values over */
1519: PetscCall(PetscArraycpy(aij->a, aij->saved_values, nz));
1520: PetscFunctionReturn(PETSC_SUCCESS);
1521: }
1523: static PetscErrorCode MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B, PetscInt bs, PetscInt nz, PetscInt *nnz)
1524: {
1525: Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1526: PetscInt i, mbs, nbs, bs2;
1527: PetscBool skipallocation = PETSC_FALSE, flg = PETSC_FALSE, realalloc = PETSC_FALSE;
1529: if (B->hash_active) {
1530: PetscInt bs;
1531: PetscCall(PetscMemcpy(&B->ops, &b->cops, sizeof(*(B->ops))));
1532: PetscCall(PetscHMapIJVDestroy(&b->ht));
1533: PetscCall(MatGetBlockSize(B, &bs));
1534: if (bs > 1) PetscCall(PetscHSetIJDestroy(&b->bht));
1535: PetscCall(PetscFree(b->dnz));
1536: PetscCall(PetscFree(b->bdnz));
1537: B->hash_active = PETSC_FALSE;
1538: }
1539: PetscFunctionBegin;
1540: if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
1542: PetscCall(MatSetBlockSize(B, PetscAbs(bs)));
1543: PetscCall(PetscLayoutSetUp(B->rmap));
1544: PetscCall(PetscLayoutSetUp(B->cmap));
1545: PetscCheck(B->rmap->N <= B->cmap->N, PETSC_COMM_SELF, PETSC_ERR_SUP, "SEQSBAIJ matrix cannot have more rows %" PetscInt_FMT " than columns %" PetscInt_FMT, B->rmap->N, B->cmap->N);
1546: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1548: B->preallocated = PETSC_TRUE;
1550: mbs = B->rmap->N / bs;
1551: nbs = B->cmap->n / bs;
1552: bs2 = bs * bs;
1554: PetscCheck(mbs * bs == B->rmap->N && nbs * bs == B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Number rows, cols must be divisible by blocksize");
1556: if (nz == MAT_SKIP_ALLOCATION) {
1557: skipallocation = PETSC_TRUE;
1558: nz = 0;
1559: }
1561: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3;
1562: PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nz cannot be less than 0: value %" PetscInt_FMT, nz);
1563: if (nnz) {
1564: for (i = 0; i < mbs; i++) {
1565: PetscCheck(nnz[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nnz cannot be less than 0: local row %" PetscInt_FMT " value %" PetscInt_FMT, i, nnz[i]);
1566: PetscCheck(nnz[i] <= nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nnz cannot be greater than block row length: local row %" PetscInt_FMT " value %" PetscInt_FMT " block rowlength %" PetscInt_FMT, i, nnz[i], nbs);
1567: }
1568: }
1570: B->ops->mult = MatMult_SeqSBAIJ_N;
1571: B->ops->multadd = MatMultAdd_SeqSBAIJ_N;
1572: B->ops->multtranspose = MatMult_SeqSBAIJ_N;
1573: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_N;
1575: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1576: if (!flg) {
1577: switch (bs) {
1578: case 1:
1579: B->ops->mult = MatMult_SeqSBAIJ_1;
1580: B->ops->multadd = MatMultAdd_SeqSBAIJ_1;
1581: B->ops->multtranspose = MatMult_SeqSBAIJ_1;
1582: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_1;
1583: break;
1584: case 2:
1585: B->ops->mult = MatMult_SeqSBAIJ_2;
1586: B->ops->multadd = MatMultAdd_SeqSBAIJ_2;
1587: B->ops->multtranspose = MatMult_SeqSBAIJ_2;
1588: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_2;
1589: break;
1590: case 3:
1591: B->ops->mult = MatMult_SeqSBAIJ_3;
1592: B->ops->multadd = MatMultAdd_SeqSBAIJ_3;
1593: B->ops->multtranspose = MatMult_SeqSBAIJ_3;
1594: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_3;
1595: break;
1596: case 4:
1597: B->ops->mult = MatMult_SeqSBAIJ_4;
1598: B->ops->multadd = MatMultAdd_SeqSBAIJ_4;
1599: B->ops->multtranspose = MatMult_SeqSBAIJ_4;
1600: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_4;
1601: break;
1602: case 5:
1603: B->ops->mult = MatMult_SeqSBAIJ_5;
1604: B->ops->multadd = MatMultAdd_SeqSBAIJ_5;
1605: B->ops->multtranspose = MatMult_SeqSBAIJ_5;
1606: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_5;
1607: break;
1608: case 6:
1609: B->ops->mult = MatMult_SeqSBAIJ_6;
1610: B->ops->multadd = MatMultAdd_SeqSBAIJ_6;
1611: B->ops->multtranspose = MatMult_SeqSBAIJ_6;
1612: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_6;
1613: break;
1614: case 7:
1615: B->ops->mult = MatMult_SeqSBAIJ_7;
1616: B->ops->multadd = MatMultAdd_SeqSBAIJ_7;
1617: B->ops->multtranspose = MatMult_SeqSBAIJ_7;
1618: B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_7;
1619: break;
1620: }
1621: }
1623: b->mbs = mbs;
1624: b->nbs = nbs;
1625: if (!skipallocation) {
1626: if (!b->imax) {
1627: PetscCall(PetscMalloc2(mbs, &b->imax, mbs, &b->ilen));
1629: b->free_imax_ilen = PETSC_TRUE;
1630: }
1631: if (!nnz) {
1632: if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
1633: else if (nz <= 0) nz = 1;
1634: nz = PetscMin(nbs, nz);
1635: for (i = 0; i < mbs; i++) b->imax[i] = nz;
1636: PetscCall(PetscIntMultError(nz, mbs, &nz));
1637: } else {
1638: PetscInt64 nz64 = 0;
1639: for (i = 0; i < mbs; i++) {
1640: b->imax[i] = nnz[i];
1641: nz64 += nnz[i];
1642: }
1643: PetscCall(PetscIntCast(nz64, &nz));
1644: }
1645: /* b->ilen will count nonzeros in each block row so far. */
1646: for (i = 0; i < mbs; i++) b->ilen[i] = 0;
1647: /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */
1649: /* allocate the matrix space */
1650: PetscCall(MatSeqXAIJFreeAIJ(B, &b->a, &b->j, &b->i));
1651: PetscCall(PetscMalloc3(bs2 * nz, &b->a, nz, &b->j, B->rmap->N + 1, &b->i));
1652: PetscCall(PetscArrayzero(b->a, nz * bs2));
1653: PetscCall(PetscArrayzero(b->j, nz));
1655: b->singlemalloc = PETSC_TRUE;
1657: /* pointer to beginning of each row */
1658: b->i[0] = 0;
1659: for (i = 1; i < mbs + 1; i++) b->i[i] = b->i[i - 1] + b->imax[i - 1];
1661: b->free_a = PETSC_TRUE;
1662: b->free_ij = PETSC_TRUE;
1663: } else {
1664: b->free_a = PETSC_FALSE;
1665: b->free_ij = PETSC_FALSE;
1666: }
1668: b->bs2 = bs2;
1669: b->nz = 0;
1670: b->maxnz = nz;
1671: b->inew = NULL;
1672: b->jnew = NULL;
1673: b->anew = NULL;
1674: b->a2anew = NULL;
1675: b->permute = PETSC_FALSE;
1677: B->was_assembled = PETSC_FALSE;
1678: B->assembled = PETSC_FALSE;
1679: if (realalloc) PetscCall(MatSetOption(B, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE));
1680: PetscFunctionReturn(PETSC_SUCCESS);
1681: }
1683: PetscErrorCode MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[])
1684: {
1685: PetscInt i, j, m, nz, anz, nz_max = 0, *nnz;
1686: PetscScalar *values = NULL;
1687: PetscBool roworiented = ((Mat_SeqSBAIJ *)B->data)->roworiented;
1689: PetscFunctionBegin;
1690: PetscCheck(bs >= 1, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_OUTOFRANGE, "Invalid block size specified, must be positive but it is %" PetscInt_FMT, bs);
1691: PetscCall(PetscLayoutSetBlockSize(B->rmap, bs));
1692: PetscCall(PetscLayoutSetBlockSize(B->cmap, bs));
1693: PetscCall(PetscLayoutSetUp(B->rmap));
1694: PetscCall(PetscLayoutSetUp(B->cmap));
1695: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1696: m = B->rmap->n / bs;
1698: PetscCheck(!ii[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]);
1699: PetscCall(PetscMalloc1(m + 1, &nnz));
1700: for (i = 0; i < m; i++) {
1701: nz = ii[i + 1] - ii[i];
1702: PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz);
1703: anz = 0;
1704: for (j = 0; j < nz; j++) {
1705: /* count only values on the diagonal or above */
1706: if (jj[ii[i] + j] >= i) {
1707: anz = nz - j;
1708: break;
1709: }
1710: }
1711: nz_max = PetscMax(nz_max, anz);
1712: nnz[i] = anz;
1713: }
1714: PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));
1715: PetscCall(PetscFree(nnz));
1717: values = (PetscScalar *)V;
1718: if (!values) PetscCall(PetscCalloc1(bs * bs * nz_max, &values));
1719: for (i = 0; i < m; i++) {
1720: PetscInt ncols = ii[i + 1] - ii[i];
1721: const PetscInt *icols = jj + ii[i];
1722: if (!roworiented || bs == 1) {
1723: const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0);
1724: PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, ncols, icols, svals, INSERT_VALUES));
1725: } else {
1726: for (j = 0; j < ncols; j++) {
1727: const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0);
1728: PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, 1, &icols[j], svals, INSERT_VALUES));
1729: }
1730: }
1731: }
1732: if (!V) PetscCall(PetscFree(values));
1733: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
1734: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
1735: PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
1736: PetscFunctionReturn(PETSC_SUCCESS);
1737: }
1739: /*
1740: This is used to set the numeric factorization for both Cholesky and ICC symbolic factorization
1741: */
1742: PetscErrorCode MatSeqSBAIJSetNumericFactorization_inplace(Mat B, PetscBool natural)
1743: {
1744: PetscBool flg = PETSC_FALSE;
1745: PetscInt bs = B->rmap->bs;
1747: PetscFunctionBegin;
1748: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1749: if (flg) bs = 8;
1751: if (!natural) {
1752: switch (bs) {
1753: case 1:
1754: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace;
1755: break;
1756: case 2:
1757: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2;
1758: break;
1759: case 3:
1760: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3;
1761: break;
1762: case 4:
1763: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4;
1764: break;
1765: case 5:
1766: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5;
1767: break;
1768: case 6:
1769: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6;
1770: break;
1771: case 7:
1772: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7;
1773: break;
1774: default:
1775: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N;
1776: break;
1777: }
1778: } else {
1779: switch (bs) {
1780: case 1:
1781: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace;
1782: break;
1783: case 2:
1784: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
1785: break;
1786: case 3:
1787: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
1788: break;
1789: case 4:
1790: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
1791: break;
1792: case 5:
1793: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
1794: break;
1795: case 6:
1796: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
1797: break;
1798: case 7:
1799: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
1800: break;
1801: default:
1802: B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
1803: break;
1804: }
1805: }
1806: PetscFunctionReturn(PETSC_SUCCESS);
1807: }
1809: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqAIJ(Mat, MatType, MatReuse, Mat *);
1810: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *);
1811: static PetscErrorCode MatFactorGetSolverType_petsc(Mat A, MatSolverType *type)
1812: {
1813: PetscFunctionBegin;
1814: *type = MATSOLVERPETSC;
1815: PetscFunctionReturn(PETSC_SUCCESS);
1816: }
1818: PETSC_INTERN PetscErrorCode MatGetFactor_seqsbaij_petsc(Mat A, MatFactorType ftype, Mat *B)
1819: {
1820: PetscInt n = A->rmap->n;
1822: PetscFunctionBegin;
1823: #if defined(PETSC_USE_COMPLEX)
1824: PetscCheck(A->hermitian != PETSC_BOOL3_TRUE || A->symmetric == PETSC_BOOL3_TRUE || (ftype != MAT_FACTOR_CHOLESKY && ftype != MAT_FACTOR_ICC), PETSC_COMM_SELF, PETSC_ERR_SUP, "Hermitian CHOLESKY or ICC Factor is not supported");
1825: #endif
1827: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), B));
1828: PetscCall(MatSetSizes(*B, n, n, n, n));
1829: if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
1830: PetscCall(MatSetType(*B, MATSEQSBAIJ));
1831: PetscCall(MatSeqSBAIJSetPreallocation(*B, A->rmap->bs, MAT_SKIP_ALLOCATION, NULL));
1833: (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ;
1834: (*B)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ;
1835: PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_CHOLESKY]));
1836: PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_ICC]));
1837: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
1839: (*B)->factortype = ftype;
1840: (*B)->canuseordering = PETSC_TRUE;
1841: PetscCall(PetscFree((*B)->solvertype));
1842: PetscCall(PetscStrallocpy(MATSOLVERPETSC, &(*B)->solvertype));
1843: PetscCall(PetscObjectComposeFunction((PetscObject)*B, "MatFactorGetSolverType_C", MatFactorGetSolverType_petsc));
1844: PetscFunctionReturn(PETSC_SUCCESS);
1845: }
1847: /*@C
1848: MatSeqSBAIJGetArray - gives access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored
1850: Not Collective
1852: Input Parameter:
1853: . mat - a `MATSEQSBAIJ` matrix
1855: Output Parameter:
1856: . array - pointer to the data
1858: Level: intermediate
1860: .seealso: [](chapter_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJRestoreArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1861: @*/
1862: PetscErrorCode MatSeqSBAIJGetArray(Mat A, PetscScalar **array)
1863: {
1864: PetscFunctionBegin;
1865: PetscUseMethod(A, "MatSeqSBAIJGetArray_C", (Mat, PetscScalar **), (A, array));
1866: PetscFunctionReturn(PETSC_SUCCESS);
1867: }
1869: /*@C
1870: MatSeqSBAIJRestoreArray - returns access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored obtained by `MatSeqSBAIJGetArray()`
1872: Not Collective
1874: Input Parameters:
1875: + mat - a `MATSEQSBAIJ` matrix
1876: - array - pointer to the data
1878: Level: intermediate
1880: .seealso: [](chapter_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJGetArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1881: @*/
1882: PetscErrorCode MatSeqSBAIJRestoreArray(Mat A, PetscScalar **array)
1883: {
1884: PetscFunctionBegin;
1885: PetscUseMethod(A, "MatSeqSBAIJRestoreArray_C", (Mat, PetscScalar **), (A, array));
1886: PetscFunctionReturn(PETSC_SUCCESS);
1887: }
1889: /*MC
1890: MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices,
1891: based on block compressed sparse row format. Only the upper triangular portion of the matrix is stored.
1893: For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
1894: can call `MatSetOption`(`Mat`, `MAT_HERMITIAN`).
1896: Options Database Key:
1897: . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to `MatSetFromOptions()`
1899: Level: beginner
1901: Notes:
1902: By default if you insert values into the lower triangular part of the matrix they are simply ignored (since they are not
1903: stored and it is assumed they symmetric to the upper triangular). If you call `MatSetOption`(`Mat`,`MAT_IGNORE_LOWER_TRIANGULAR`,`PETSC_FALSE`) or use
1904: the options database `-mat_ignore_lower_triangular` false it will generate an error if you try to set a value in the lower triangular portion.
1906: The number of rows in the matrix must be less than or equal to the number of columns
1908: .seealso: [](chapter_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ()`, `MatType`, `MATMPISBAIJ`
1909: M*/
1910: PETSC_EXTERN PetscErrorCode MatCreate_SeqSBAIJ(Mat B)
1911: {
1912: Mat_SeqSBAIJ *b;
1913: PetscMPIInt size;
1914: PetscBool no_unroll = PETSC_FALSE, no_inode = PETSC_FALSE;
1916: PetscFunctionBegin;
1917: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size));
1918: PetscCheck(size <= 1, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Comm must be of size 1");
1920: PetscCall(PetscNew(&b));
1921: B->data = (void *)b;
1922: PetscCall(PetscMemcpy(B->ops, &MatOps_Values, sizeof(struct _MatOps)));
1924: B->ops->destroy = MatDestroy_SeqSBAIJ;
1925: B->ops->view = MatView_SeqSBAIJ;
1926: b->row = NULL;
1927: b->icol = NULL;
1928: b->reallocs = 0;
1929: b->saved_values = NULL;
1930: b->inode.limit = 5;
1931: b->inode.max_limit = 5;
1933: b->roworiented = PETSC_TRUE;
1934: b->nonew = 0;
1935: b->diag = NULL;
1936: b->solve_work = NULL;
1937: b->mult_work = NULL;
1938: B->spptr = NULL;
1939: B->info.nz_unneeded = (PetscReal)b->maxnz * b->bs2;
1940: b->keepnonzeropattern = PETSC_FALSE;
1942: b->inew = NULL;
1943: b->jnew = NULL;
1944: b->anew = NULL;
1945: b->a2anew = NULL;
1946: b->permute = PETSC_FALSE;
1948: b->ignore_ltriangular = PETSC_TRUE;
1950: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_ignore_lower_triangular", &b->ignore_ltriangular, NULL));
1952: b->getrow_utriangular = PETSC_FALSE;
1954: PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_getrow_uppertriangular", &b->getrow_utriangular, NULL));
1956: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJGetArray_C", MatSeqSBAIJGetArray_SeqSBAIJ));
1957: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJRestoreArray_C", MatSeqSBAIJRestoreArray_SeqSBAIJ));
1958: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_SeqSBAIJ));
1959: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_SeqSBAIJ));
1960: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetColumnIndices_C", MatSeqSBAIJSetColumnIndices_SeqSBAIJ));
1961: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqaij_C", MatConvert_SeqSBAIJ_SeqAIJ));
1962: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqbaij_C", MatConvert_SeqSBAIJ_SeqBAIJ));
1963: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocation_C", MatSeqSBAIJSetPreallocation_SeqSBAIJ));
1964: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocationCSR_C", MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ));
1965: #if defined(PETSC_HAVE_ELEMENTAL)
1966: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_elemental_C", MatConvert_SeqSBAIJ_Elemental));
1967: #endif
1968: #if defined(PETSC_HAVE_SCALAPACK)
1969: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_scalapack_C", MatConvert_SBAIJ_ScaLAPACK));
1970: #endif
1972: B->symmetry_eternal = PETSC_TRUE;
1973: B->structural_symmetry_eternal = PETSC_TRUE;
1974: B->symmetric = PETSC_BOOL3_TRUE;
1975: B->structurally_symmetric = PETSC_BOOL3_TRUE;
1976: #if defined(PETSC_USE_COMPLEX)
1977: B->hermitian = PETSC_BOOL3_FALSE;
1978: #else
1979: B->hermitian = PETSC_BOOL3_TRUE;
1980: #endif
1982: PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATSEQSBAIJ));
1984: PetscOptionsBegin(PetscObjectComm((PetscObject)B), ((PetscObject)B)->prefix, "Options for SEQSBAIJ matrix", "Mat");
1985: PetscCall(PetscOptionsBool("-mat_no_unroll", "Do not optimize for inodes (slower)", NULL, no_unroll, &no_unroll, NULL));
1986: if (no_unroll) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_unroll\n"));
1987: PetscCall(PetscOptionsBool("-mat_no_inode", "Do not optimize for inodes (slower)", NULL, no_inode, &no_inode, NULL));
1988: if (no_inode) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_inode\n"));
1989: PetscCall(PetscOptionsInt("-mat_inode_limit", "Do not use inodes larger then this value", NULL, b->inode.limit, &b->inode.limit, NULL));
1990: PetscOptionsEnd();
1991: b->inode.use = (PetscBool)(!(no_unroll || no_inode));
1992: if (b->inode.limit > b->inode.max_limit) b->inode.limit = b->inode.max_limit;
1993: PetscFunctionReturn(PETSC_SUCCESS);
1994: }
1996: /*@C
1997: MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block
1998: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
1999: user should preallocate the matrix storage by setting the parameter `nz`
2000: (or the array `nnz`).
2002: Collective
2004: Input Parameters:
2005: + B - the symmetric matrix
2006: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2007: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
2008: . nz - number of block nonzeros per block row (same for all rows)
2009: - nnz - array containing the number of block nonzeros in the upper triangular plus
2010: diagonal portion of each block (possibly different for each block row) or `NULL`
2012: Options Database Keys:
2013: + -mat_no_unroll - uses code that does not unroll the loops in the
2014: block calculations (much slower)
2015: - -mat_block_size - size of the blocks to use (only works if a negative bs is passed in
2017: Level: intermediate
2019: Notes:
2020: Specify the preallocated storage with either `nz` or `nnz` (not both).
2021: Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
2022: allocation. See [Sparse Matrices](sec_matsparse) for details.
2024: You can call `MatGetInfo()` to get information on how effective the preallocation was;
2025: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2026: You can also run with the option `-info` and look for messages with the string
2027: malloc in them to see if additional memory allocation was needed.
2029: If the `nnz` parameter is given then the `nz` parameter is ignored
2031: .seealso: [](chapter_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
2032: @*/
2033: PetscErrorCode MatSeqSBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[])
2034: {
2035: PetscFunctionBegin;
2039: PetscTryMethod(B, "MatSeqSBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[]), (B, bs, nz, nnz));
2040: PetscFunctionReturn(PETSC_SUCCESS);
2041: }
2043: /*@C
2044: MatSeqSBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATSEQSBAIJ` format using the given nonzero structure and (optional) numerical values
2046: Input Parameters:
2047: + B - the matrix
2048: . bs - size of block, the blocks are ALWAYS square.
2049: . i - the indices into j for the start of each local row (starts with zero)
2050: . j - the column indices for each local row (starts with zero) these must be sorted for each row
2051: - v - optional values in the matrix
2053: Level: advanced
2055: Notes:
2056: The order of the entries in values is specified by the `MatOption` `MAT_ROW_ORIENTED`. For example, C programs
2057: may want to use the default `MAT_ROW_ORIENTED` = `PETSC_TRUE` and use an array v[nnz][bs][bs] where the second index is
2058: over rows within a block and the last index is over columns within a block row. Fortran programs will likely set
2059: `MAT_ROW_ORIENTED` = `PETSC_FALSE` and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
2060: block column and the second index is over columns within a block.
2062: Any entries below the diagonal are ignored
2064: Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2065: and usually the numerical values as well
2067: .seealso: [](chapter_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValuesBlocked()`, `MatSeqSBAIJSetPreallocation()`, `MATSEQSBAIJ`
2068: @*/
2069: PetscErrorCode MatSeqSBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[])
2070: {
2071: PetscFunctionBegin;
2075: PetscTryMethod(B, "MatSeqSBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v));
2076: PetscFunctionReturn(PETSC_SUCCESS);
2077: }
2079: /*@C
2080: MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in (block
2081: compressed row) `MATSEQSBAIJ` format. For good matrix assembly performance the
2082: user should preallocate the matrix storage by setting the parameter `nz`
2083: (or the array `nnz`).
2085: Collective
2087: Input Parameters:
2088: + comm - MPI communicator, set to `PETSC_COMM_SELF`
2089: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2090: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2091: . m - number of rows
2092: . n - number of columns
2093: . nz - number of block nonzeros per block row (same for all rows)
2094: - nnz - array containing the number of block nonzeros in the upper triangular plus
2095: diagonal portion of each block (possibly different for each block row) or `NULL`
2097: Output Parameter:
2098: . A - the symmetric matrix
2100: Options Database Keys:
2101: + -mat_no_unroll - uses code that does not unroll the loops in the
2102: block calculations (much slower)
2103: - -mat_block_size - size of the blocks to use
2105: Level: intermediate
2107: Notes:
2108: It is recommended that one use the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`,
2109: MatXXXXSetPreallocation() paradigm instead of this routine directly.
2110: [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`]
2112: The number of rows and columns must be divisible by blocksize.
2113: This matrix type does not support complex Hermitian operation.
2115: Specify the preallocated storage with either `nz` or `nnz` (not both).
2116: Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
2117: allocation. See [Sparse Matrices](sec_matsparse) for details.
2119: If the `nnz` parameter is given then the `nz` parameter is ignored
2121: .seealso: [](chapter_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
2122: @*/
2123: PetscErrorCode MatCreateSeqSBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], Mat *A)
2124: {
2125: PetscFunctionBegin;
2126: PetscCall(MatCreate(comm, A));
2127: PetscCall(MatSetSizes(*A, m, n, m, n));
2128: PetscCall(MatSetType(*A, MATSEQSBAIJ));
2129: PetscCall(MatSeqSBAIJSetPreallocation(*A, bs, nz, (PetscInt *)nnz));
2130: PetscFunctionReturn(PETSC_SUCCESS);
2131: }
2133: PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A, MatDuplicateOption cpvalues, Mat *B)
2134: {
2135: Mat C;
2136: Mat_SeqSBAIJ *c, *a = (Mat_SeqSBAIJ *)A->data;
2137: PetscInt i, mbs = a->mbs, nz = a->nz, bs2 = a->bs2;
2139: PetscFunctionBegin;
2140: PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Cannot duplicate unassembled matrix");
2141: PetscCheck(a->i[mbs] == nz, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Corrupt matrix");
2143: *B = NULL;
2144: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &C));
2145: PetscCall(MatSetSizes(C, A->rmap->N, A->cmap->n, A->rmap->N, A->cmap->n));
2146: PetscCall(MatSetBlockSizesFromMats(C, A, A));
2147: PetscCall(MatSetType(C, MATSEQSBAIJ));
2148: c = (Mat_SeqSBAIJ *)C->data;
2150: C->preallocated = PETSC_TRUE;
2151: C->factortype = A->factortype;
2152: c->row = NULL;
2153: c->icol = NULL;
2154: c->saved_values = NULL;
2155: c->keepnonzeropattern = a->keepnonzeropattern;
2156: C->assembled = PETSC_TRUE;
2158: PetscCall(PetscLayoutReference(A->rmap, &C->rmap));
2159: PetscCall(PetscLayoutReference(A->cmap, &C->cmap));
2160: c->bs2 = a->bs2;
2161: c->mbs = a->mbs;
2162: c->nbs = a->nbs;
2164: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2165: c->imax = a->imax;
2166: c->ilen = a->ilen;
2167: c->free_imax_ilen = PETSC_FALSE;
2168: } else {
2169: PetscCall(PetscMalloc2((mbs + 1), &c->imax, (mbs + 1), &c->ilen));
2170: for (i = 0; i < mbs; i++) {
2171: c->imax[i] = a->imax[i];
2172: c->ilen[i] = a->ilen[i];
2173: }
2174: c->free_imax_ilen = PETSC_TRUE;
2175: }
2177: /* allocate the matrix space */
2178: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2179: PetscCall(PetscMalloc1(bs2 * nz, &c->a));
2180: c->i = a->i;
2181: c->j = a->j;
2182: c->singlemalloc = PETSC_FALSE;
2183: c->free_a = PETSC_TRUE;
2184: c->free_ij = PETSC_FALSE;
2185: c->parent = A;
2186: PetscCall(PetscObjectReference((PetscObject)A));
2187: PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2188: PetscCall(MatSetOption(C, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2189: } else {
2190: PetscCall(PetscMalloc3(bs2 * nz, &c->a, nz, &c->j, mbs + 1, &c->i));
2191: PetscCall(PetscArraycpy(c->i, a->i, mbs + 1));
2192: c->singlemalloc = PETSC_TRUE;
2193: c->free_a = PETSC_TRUE;
2194: c->free_ij = PETSC_TRUE;
2195: }
2196: if (mbs > 0) {
2197: if (cpvalues != MAT_SHARE_NONZERO_PATTERN) PetscCall(PetscArraycpy(c->j, a->j, nz));
2198: if (cpvalues == MAT_COPY_VALUES) {
2199: PetscCall(PetscArraycpy(c->a, a->a, bs2 * nz));
2200: } else {
2201: PetscCall(PetscArrayzero(c->a, bs2 * nz));
2202: }
2203: if (a->jshort) {
2204: /* cannot share jshort, it is reallocated in MatAssemblyEnd_SeqSBAIJ() */
2205: /* if the parent matrix is reassembled, this child matrix will never notice */
2206: PetscCall(PetscMalloc1(nz, &c->jshort));
2207: PetscCall(PetscArraycpy(c->jshort, a->jshort, nz));
2209: c->free_jshort = PETSC_TRUE;
2210: }
2211: }
2213: c->roworiented = a->roworiented;
2214: c->nonew = a->nonew;
2216: if (a->diag) {
2217: if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2218: c->diag = a->diag;
2219: c->free_diag = PETSC_FALSE;
2220: } else {
2221: PetscCall(PetscMalloc1(mbs, &c->diag));
2222: for (i = 0; i < mbs; i++) c->diag[i] = a->diag[i];
2223: c->free_diag = PETSC_TRUE;
2224: }
2225: }
2226: c->nz = a->nz;
2227: c->maxnz = a->nz; /* Since we allocate exactly the right amount */
2228: c->solve_work = NULL;
2229: c->mult_work = NULL;
2231: *B = C;
2232: PetscCall(PetscFunctionListDuplicate(((PetscObject)A)->qlist, &((PetscObject)C)->qlist));
2233: PetscFunctionReturn(PETSC_SUCCESS);
2234: }
2236: /* Used for both SeqBAIJ and SeqSBAIJ matrices */
2237: #define MatLoad_SeqSBAIJ_Binary MatLoad_SeqBAIJ_Binary
2239: PetscErrorCode MatLoad_SeqSBAIJ(Mat mat, PetscViewer viewer)
2240: {
2241: PetscBool isbinary;
2243: PetscFunctionBegin;
2244: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
2245: PetscCheck(isbinary, PetscObjectComm((PetscObject)viewer), PETSC_ERR_SUP, "Viewer type %s not yet supported for reading %s matrices", ((PetscObject)viewer)->type_name, ((PetscObject)mat)->type_name);
2246: PetscCall(MatLoad_SeqSBAIJ_Binary(mat, viewer));
2247: PetscFunctionReturn(PETSC_SUCCESS);
2248: }
2250: /*@
2251: MatCreateSeqSBAIJWithArrays - Creates an sequential `MATSEQSBAIJ` matrix using matrix elements
2252: (upper triangular entries in CSR format) provided by the user.
2254: Collective
2256: Input Parameters:
2257: + comm - must be an MPI communicator of size 1
2258: . bs - size of block
2259: . m - number of rows
2260: . n - number of columns
2261: . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix
2262: . j - column indices
2263: - a - matrix values
2265: Output Parameter:
2266: . mat - the matrix
2268: Level: advanced
2270: Notes:
2271: The `i`, `j`, and `a` arrays are not copied by this routine, the user must free these arrays
2272: once the matrix is destroyed
2274: You cannot set new nonzero locations into this matrix, that will generate an error.
2276: The `i` and `j` indices are 0 based
2278: When block size is greater than 1 the matrix values must be stored using the `MATSBAIJ` storage format. For block size of 1
2279: it is the regular CSR format excluding the lower triangular elements.
2281: .seealso: [](chapter_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSBAIJ()`, `MatCreateSeqSBAIJ()`
2282: @*/
2283: PetscErrorCode MatCreateSeqSBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt i[], PetscInt j[], PetscScalar a[], Mat *mat)
2284: {
2285: PetscInt ii;
2286: Mat_SeqSBAIJ *sbaij;
2288: PetscFunctionBegin;
2289: PetscCheck(bs == 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "block size %" PetscInt_FMT " > 1 is not supported yet", bs);
2290: PetscCheck(m == 0 || i[0] == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0");
2292: PetscCall(MatCreate(comm, mat));
2293: PetscCall(MatSetSizes(*mat, m, n, m, n));
2294: PetscCall(MatSetType(*mat, MATSEQSBAIJ));
2295: PetscCall(MatSeqSBAIJSetPreallocation(*mat, bs, MAT_SKIP_ALLOCATION, NULL));
2296: sbaij = (Mat_SeqSBAIJ *)(*mat)->data;
2297: PetscCall(PetscMalloc2(m, &sbaij->imax, m, &sbaij->ilen));
2299: sbaij->i = i;
2300: sbaij->j = j;
2301: sbaij->a = a;
2303: sbaij->singlemalloc = PETSC_FALSE;
2304: sbaij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
2305: sbaij->free_a = PETSC_FALSE;
2306: sbaij->free_ij = PETSC_FALSE;
2307: sbaij->free_imax_ilen = PETSC_TRUE;
2309: for (ii = 0; ii < m; ii++) {
2310: sbaij->ilen[ii] = sbaij->imax[ii] = i[ii + 1] - i[ii];
2311: PetscCheck(i[ii + 1] >= i[ii], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative row length in i (row indices) row = %" PetscInt_FMT " length = %" PetscInt_FMT, ii, i[ii + 1] - i[ii]);
2312: }
2313: if (PetscDefined(USE_DEBUG)) {
2314: for (ii = 0; ii < sbaij->i[m]; ii++) {
2315: PetscCheck(j[ii] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative column index at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]);
2316: PetscCheck(j[ii] < n, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column index too large at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]);
2317: }
2318: }
2320: PetscCall(MatAssemblyBegin(*mat, MAT_FINAL_ASSEMBLY));
2321: PetscCall(MatAssemblyEnd(*mat, MAT_FINAL_ASSEMBLY));
2322: PetscFunctionReturn(PETSC_SUCCESS);
2323: }
2325: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
2326: {
2327: PetscFunctionBegin;
2328: PetscCall(MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(comm, inmat, n, scall, outmat));
2329: PetscFunctionReturn(PETSC_SUCCESS);
2330: }