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 (A->hash_active) {
179:     PetscInt bs;
180:     PetscCall(PetscMemcpy(&A->ops, &a->cops, sizeof(*(A->ops))));
181:     PetscCall(PetscHMapIJVDestroy(&a->ht));
182:     PetscCall(MatGetBlockSize(A, &bs));
183:     if (bs > 1) PetscCall(PetscHSetIJDestroy(&a->bht));
184:     PetscCall(PetscFree(a->dnz));
185:     PetscCall(PetscFree(a->bdnz));
186:     A->hash_active = PETSC_FALSE;
187:   }
188: #if defined(PETSC_USE_LOG)
189:   PetscCall(PetscLogObjectState((PetscObject)A, "Rows=%" PetscInt_FMT ", NZ=%" PetscInt_FMT, A->rmap->N, a->nz));
190: #endif
191:   PetscCall(MatSeqXAIJFreeAIJ(A, &a->a, &a->j, &a->i));
192:   if (a->free_diag) PetscCall(PetscFree(a->diag));
193:   PetscCall(ISDestroy(&a->row));
194:   PetscCall(ISDestroy(&a->col));
195:   PetscCall(ISDestroy(&a->icol));
196:   PetscCall(PetscFree(a->idiag));
197:   PetscCall(PetscFree(a->inode.size));
198:   if (a->free_imax_ilen) PetscCall(PetscFree2(a->imax, a->ilen));
199:   PetscCall(PetscFree(a->solve_work));
200:   PetscCall(PetscFree(a->sor_work));
201:   PetscCall(PetscFree(a->solves_work));
202:   PetscCall(PetscFree(a->mult_work));
203:   PetscCall(PetscFree(a->saved_values));
204:   if (a->free_jshort) PetscCall(PetscFree(a->jshort));
205:   PetscCall(PetscFree(a->inew));
206:   PetscCall(MatDestroy(&a->parent));
207:   PetscCall(PetscFree(A->data));

209:   PetscCall(PetscObjectChangeTypeName((PetscObject)A, NULL));
210:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJGetArray_C", NULL));
211:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJRestoreArray_C", NULL));
212:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatStoreValues_C", NULL));
213:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatRetrieveValues_C", NULL));
214:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetColumnIndices_C", NULL));
215:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqaij_C", NULL));
216:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_seqbaij_C", NULL));
217:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocation_C", NULL));
218:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSeqSBAIJSetPreallocationCSR_C", NULL));
219: #if defined(PETSC_HAVE_ELEMENTAL)
220:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_elemental_C", NULL));
221: #endif
222: #if defined(PETSC_HAVE_SCALAPACK)
223:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatConvert_seqsbaij_scalapack_C", NULL));
224: #endif
225:   PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL));
226:   PetscFunctionReturn(PETSC_SUCCESS);
227: }

229: PetscErrorCode MatSetOption_SeqSBAIJ(Mat A, MatOption op, PetscBool flg)
230: {
231:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
232: #if defined(PETSC_USE_COMPLEX)
233:   PetscInt bs;
234: #endif

236:   PetscFunctionBegin;
237: #if defined(PETSC_USE_COMPLEX)
238:   PetscCall(MatGetBlockSize(A, &bs));
239: #endif
240:   switch (op) {
241:   case MAT_ROW_ORIENTED:
242:     a->roworiented = flg;
243:     break;
244:   case MAT_KEEP_NONZERO_PATTERN:
245:     a->keepnonzeropattern = flg;
246:     break;
247:   case MAT_NEW_NONZERO_LOCATIONS:
248:     a->nonew = (flg ? 0 : 1);
249:     break;
250:   case MAT_NEW_NONZERO_LOCATION_ERR:
251:     a->nonew = (flg ? -1 : 0);
252:     break;
253:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
254:     a->nonew = (flg ? -2 : 0);
255:     break;
256:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
257:     a->nounused = (flg ? -1 : 0);
258:     break;
259:   case MAT_FORCE_DIAGONAL_ENTRIES:
260:   case MAT_IGNORE_OFF_PROC_ENTRIES:
261:   case MAT_USE_HASH_TABLE:
262:   case MAT_SORTED_FULL:
263:     PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op]));
264:     break;
265:   case MAT_HERMITIAN:
266: #if defined(PETSC_USE_COMPLEX)
267:     if (flg) { /* disable transpose ops */
268:       PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for Hermitian with block size greater than 1");
269:       A->ops->multtranspose    = NULL;
270:       A->ops->multtransposeadd = NULL;
271:       A->symmetric             = PETSC_BOOL3_FALSE;
272:     }
273: #endif
274:     break;
275:   case MAT_SYMMETRIC:
276:   case MAT_SPD:
277: #if defined(PETSC_USE_COMPLEX)
278:     if (flg) { /* An hermitian and symmetric matrix has zero imaginary part (restore back transpose ops) */
279:       A->ops->multtranspose    = A->ops->mult;
280:       A->ops->multtransposeadd = A->ops->multadd;
281:     }
282: #endif
283:     break;
284:     /* These options are handled directly by MatSetOption() */
285:   case MAT_STRUCTURALLY_SYMMETRIC:
286:   case MAT_SYMMETRY_ETERNAL:
287:   case MAT_STRUCTURAL_SYMMETRY_ETERNAL:
288:   case MAT_STRUCTURE_ONLY:
289:   case MAT_SPD_ETERNAL:
290:     /* These options are handled directly by MatSetOption() */
291:     break;
292:   case MAT_IGNORE_LOWER_TRIANGULAR:
293:     a->ignore_ltriangular = flg;
294:     break;
295:   case MAT_ERROR_LOWER_TRIANGULAR:
296:     a->ignore_ltriangular = flg;
297:     break;
298:   case MAT_GETROW_UPPERTRIANGULAR:
299:     a->getrow_utriangular = flg;
300:     break;
301:   case MAT_SUBMAT_SINGLEIS:
302:     break;
303:   default:
304:     SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "unknown option %d", op);
305:   }
306:   PetscFunctionReturn(PETSC_SUCCESS);
307: }

309: PetscErrorCode MatGetRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
310: {
311:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;

313:   PetscFunctionBegin;
314:   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()");

316:   /* Get the upper triangular part of the row */
317:   PetscCall(MatGetRow_SeqBAIJ_private(A, row, nz, idx, v, a->i, a->j, a->a));
318:   PetscFunctionReturn(PETSC_SUCCESS);
319: }

321: PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat A, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
322: {
323:   PetscFunctionBegin;
324:   if (nz) *nz = 0;
325:   if (idx) PetscCall(PetscFree(*idx));
326:   if (v) PetscCall(PetscFree(*v));
327:   PetscFunctionReturn(PETSC_SUCCESS);
328: }

330: PetscErrorCode MatGetRowUpperTriangular_SeqSBAIJ(Mat A)
331: {
332:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;

334:   PetscFunctionBegin;
335:   a->getrow_utriangular = PETSC_TRUE;
336:   PetscFunctionReturn(PETSC_SUCCESS);
337: }

339: PetscErrorCode MatRestoreRowUpperTriangular_SeqSBAIJ(Mat A)
340: {
341:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;

343:   PetscFunctionBegin;
344:   a->getrow_utriangular = PETSC_FALSE;
345:   PetscFunctionReturn(PETSC_SUCCESS);
346: }

348: PetscErrorCode MatTranspose_SeqSBAIJ(Mat A, MatReuse reuse, Mat *B)
349: {
350:   PetscFunctionBegin;
351:   if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *B));
352:   if (reuse == MAT_INITIAL_MATRIX) {
353:     PetscCall(MatDuplicate(A, MAT_COPY_VALUES, B));
354:   } else if (reuse == MAT_REUSE_MATRIX) {
355:     PetscCall(MatCopy(A, *B, SAME_NONZERO_PATTERN));
356:   }
357:   PetscFunctionReturn(PETSC_SUCCESS);
358: }

360: PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat A, PetscViewer viewer)
361: {
362:   Mat_SeqSBAIJ     *a = (Mat_SeqSBAIJ *)A->data;
363:   PetscInt          i, j, bs = A->rmap->bs, k, l, bs2 = a->bs2;
364:   PetscViewerFormat format;
365:   PetscInt         *diag;
366:   const char       *matname;

368:   PetscFunctionBegin;
369:   PetscCall(PetscViewerGetFormat(viewer, &format));
370:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
371:     PetscCall(PetscViewerASCIIPrintf(viewer, "  block size is %" PetscInt_FMT "\n", bs));
372:   } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
373:     Mat aij;

375:     if (A->factortype && bs > 1) {
376:       PetscCall(PetscPrintf(PETSC_COMM_SELF, "Warning: matrix is factored with bs>1. MatView() with PETSC_VIEWER_ASCII_MATLAB is not supported and ignored!\n"));
377:       PetscFunctionReturn(PETSC_SUCCESS);
378:     }
379:     PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &aij));
380:     if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
381:     if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)aij, matname));
382:     PetscCall(MatView_SeqAIJ(aij, viewer));
383:     PetscCall(MatDestroy(&aij));
384:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
385:     Mat B;

387:     PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
388:     if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
389:     if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
390:     PetscCall(MatView_SeqAIJ(B, viewer));
391:     PetscCall(MatDestroy(&B));
392:   } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
393:     PetscFunctionReturn(PETSC_SUCCESS);
394:   } else {
395:     PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_FALSE));
396:     if (A->factortype) { /* for factored matrix */
397:       PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "matrix is factored with bs>1. Not implemented yet");

399:       diag = a->diag;
400:       for (i = 0; i < a->mbs; i++) { /* for row block i */
401:         PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i));
402:         /* diagonal entry */
403: #if defined(PETSC_USE_COMPLEX)
404:         if (PetscImaginaryPart(a->a[diag[i]]) > 0.0) {
405:           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]])));
406:         } else if (PetscImaginaryPart(a->a[diag[i]]) < 0.0) {
407:           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]])));
408:         } else {
409:           PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)PetscRealPart(1.0 / a->a[diag[i]])));
410:         }
411: #else
412:         PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[diag[i]], (double)(1.0 / a->a[diag[i]])));
413: #endif
414:         /* off-diagonal entries */
415:         for (k = a->i[i]; k < a->i[i + 1] - 1; k++) {
416: #if defined(PETSC_USE_COMPLEX)
417:           if (PetscImaginaryPart(a->a[k]) > 0.0) {
418:             PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g + %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), (double)PetscImaginaryPart(a->a[k])));
419:           } else if (PetscImaginaryPart(a->a[k]) < 0.0) {
420:             PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g - %g i) ", bs * a->j[k], (double)PetscRealPart(a->a[k]), -(double)PetscImaginaryPart(a->a[k])));
421:           } else {
422:             PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k], (double)PetscRealPart(a->a[k])));
423:           }
424: #else
425:           PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", a->j[k], (double)a->a[k]));
426: #endif
427:         }
428:         PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
429:       }

431:     } else {                         /* for non-factored matrix */
432:       for (i = 0; i < a->mbs; i++) { /* for row block i */
433:         for (j = 0; j < bs; j++) {   /* for row bs*i + j */
434:           PetscCall(PetscViewerASCIIPrintf(viewer, "row %" PetscInt_FMT ":", i * bs + j));
435:           for (k = a->i[i]; k < a->i[i + 1]; k++) { /* for column block */
436:             for (l = 0; l < bs; l++) {              /* for column */
437: #if defined(PETSC_USE_COMPLEX)
438:               if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) > 0.0) {
439:                 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])));
440:               } else if (PetscImaginaryPart(a->a[bs2 * k + l * bs + j]) < 0.0) {
441:                 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])));
442:               } else {
443:                 PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)PetscRealPart(a->a[bs2 * k + l * bs + j])));
444:               }
445: #else
446:               PetscCall(PetscViewerASCIIPrintf(viewer, " (%" PetscInt_FMT ", %g) ", bs * a->j[k] + l, (double)a->a[bs2 * k + l * bs + j]));
447: #endif
448:             }
449:           }
450:           PetscCall(PetscViewerASCIIPrintf(viewer, "\n"));
451:         }
452:       }
453:     }
454:     PetscCall(PetscViewerASCIIUseTabs(viewer, PETSC_TRUE));
455:   }
456:   PetscCall(PetscViewerFlush(viewer));
457:   PetscFunctionReturn(PETSC_SUCCESS);
458: }

460: #include <petscdraw.h>
461: static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw, void *Aa)
462: {
463:   Mat           A = (Mat)Aa;
464:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
465:   PetscInt      row, i, j, k, l, mbs = a->mbs, color, bs = A->rmap->bs, bs2 = a->bs2;
466:   PetscReal     xl, yl, xr, yr, x_l, x_r, y_l, y_r;
467:   MatScalar    *aa;
468:   PetscViewer   viewer;

470:   PetscFunctionBegin;
471:   PetscCall(PetscObjectQuery((PetscObject)A, "Zoomviewer", (PetscObject *)&viewer));
472:   PetscCall(PetscDrawGetCoordinates(draw, &xl, &yl, &xr, &yr));

474:   /* loop over matrix elements drawing boxes */

476:   PetscDrawCollectiveBegin(draw);
477:   PetscCall(PetscDrawString(draw, .3 * (xl + xr), .3 * (yl + yr), PETSC_DRAW_BLACK, "symmetric"));
478:   /* Blue for negative, Cyan for zero and  Red for positive */
479:   color = PETSC_DRAW_BLUE;
480:   for (i = 0, row = 0; i < mbs; i++, row += bs) {
481:     for (j = a->i[i]; j < a->i[i + 1]; j++) {
482:       y_l = A->rmap->N - row - 1.0;
483:       y_r = y_l + 1.0;
484:       x_l = a->j[j] * bs;
485:       x_r = x_l + 1.0;
486:       aa  = a->a + j * bs2;
487:       for (k = 0; k < bs; k++) {
488:         for (l = 0; l < bs; l++) {
489:           if (PetscRealPart(*aa++) >= 0.) continue;
490:           PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
491:         }
492:       }
493:     }
494:   }
495:   color = PETSC_DRAW_CYAN;
496:   for (i = 0, row = 0; i < mbs; i++, row += bs) {
497:     for (j = a->i[i]; j < a->i[i + 1]; j++) {
498:       y_l = A->rmap->N - row - 1.0;
499:       y_r = y_l + 1.0;
500:       x_l = a->j[j] * bs;
501:       x_r = x_l + 1.0;
502:       aa  = a->a + j * bs2;
503:       for (k = 0; k < bs; k++) {
504:         for (l = 0; l < bs; l++) {
505:           if (PetscRealPart(*aa++) != 0.) continue;
506:           PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
507:         }
508:       }
509:     }
510:   }
511:   color = PETSC_DRAW_RED;
512:   for (i = 0, row = 0; i < mbs; i++, row += bs) {
513:     for (j = a->i[i]; j < a->i[i + 1]; j++) {
514:       y_l = A->rmap->N - row - 1.0;
515:       y_r = y_l + 1.0;
516:       x_l = a->j[j] * bs;
517:       x_r = x_l + 1.0;
518:       aa  = a->a + j * bs2;
519:       for (k = 0; k < bs; k++) {
520:         for (l = 0; l < bs; l++) {
521:           if (PetscRealPart(*aa++) <= 0.) continue;
522:           PetscCall(PetscDrawRectangle(draw, x_l + k, y_l - l, x_r + k, y_r - l, color, color, color, color));
523:         }
524:       }
525:     }
526:   }
527:   PetscDrawCollectiveEnd(draw);
528:   PetscFunctionReturn(PETSC_SUCCESS);
529: }

531: static PetscErrorCode MatView_SeqSBAIJ_Draw(Mat A, PetscViewer viewer)
532: {
533:   PetscReal xl, yl, xr, yr, w, h;
534:   PetscDraw draw;
535:   PetscBool isnull;

537:   PetscFunctionBegin;
538:   PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
539:   PetscCall(PetscDrawIsNull(draw, &isnull));
540:   if (isnull) PetscFunctionReturn(PETSC_SUCCESS);

542:   xr = A->rmap->N;
543:   yr = A->rmap->N;
544:   h  = yr / 10.0;
545:   w  = xr / 10.0;
546:   xr += w;
547:   yr += h;
548:   xl = -w;
549:   yl = -h;
550:   PetscCall(PetscDrawSetCoordinates(draw, xl, yl, xr, yr));
551:   PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", (PetscObject)viewer));
552:   PetscCall(PetscDrawZoom(draw, MatView_SeqSBAIJ_Draw_Zoom, A));
553:   PetscCall(PetscObjectCompose((PetscObject)A, "Zoomviewer", NULL));
554:   PetscCall(PetscDrawSave(draw));
555:   PetscFunctionReturn(PETSC_SUCCESS);
556: }

558: /* Used for both MPIBAIJ and MPISBAIJ matrices */
559: #define MatView_SeqSBAIJ_Binary MatView_SeqBAIJ_Binary

561: PetscErrorCode MatView_SeqSBAIJ(Mat A, PetscViewer viewer)
562: {
563:   PetscBool iascii, isbinary, isdraw;

565:   PetscFunctionBegin;
566:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
567:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
568:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
569:   if (iascii) {
570:     PetscCall(MatView_SeqSBAIJ_ASCII(A, viewer));
571:   } else if (isbinary) {
572:     PetscCall(MatView_SeqSBAIJ_Binary(A, viewer));
573:   } else if (isdraw) {
574:     PetscCall(MatView_SeqSBAIJ_Draw(A, viewer));
575:   } else {
576:     Mat         B;
577:     const char *matname;
578:     PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &B));
579:     if (((PetscObject)A)->name) PetscCall(PetscObjectGetName((PetscObject)A, &matname));
580:     if (((PetscObject)A)->name) PetscCall(PetscObjectSetName((PetscObject)B, matname));
581:     PetscCall(MatView(B, viewer));
582:     PetscCall(MatDestroy(&B));
583:   }
584:   PetscFunctionReturn(PETSC_SUCCESS);
585: }

587: PetscErrorCode MatGetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], PetscScalar v[])
588: {
589:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
590:   PetscInt     *rp, k, low, high, t, row, nrow, i, col, l, *aj = a->j;
591:   PetscInt     *ai = a->i, *ailen = a->ilen;
592:   PetscInt      brow, bcol, ridx, cidx, bs = A->rmap->bs, bs2 = a->bs2;
593:   MatScalar    *ap, *aa = a->a;

595:   PetscFunctionBegin;
596:   for (k = 0; k < m; k++) { /* loop over rows */
597:     row  = im[k];
598:     brow = row / bs;
599:     if (row < 0) {
600:       v += n;
601:       continue;
602:     } /* negative row */
603:     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);
604:     rp   = aj + ai[brow];
605:     ap   = aa + bs2 * ai[brow];
606:     nrow = ailen[brow];
607:     for (l = 0; l < n; l++) { /* loop over columns */
608:       if (in[l] < 0) {
609:         v++;
610:         continue;
611:       } /* negative column */
612:       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);
613:       col  = in[l];
614:       bcol = col / bs;
615:       cidx = col % bs;
616:       ridx = row % bs;
617:       high = nrow;
618:       low  = 0; /* assume unsorted */
619:       while (high - low > 5) {
620:         t = (low + high) / 2;
621:         if (rp[t] > bcol) high = t;
622:         else low = t;
623:       }
624:       for (i = low; i < high; i++) {
625:         if (rp[i] > bcol) break;
626:         if (rp[i] == bcol) {
627:           *v++ = ap[bs2 * i + bs * cidx + ridx];
628:           goto finished;
629:         }
630:       }
631:       *v++ = 0.0;
632:     finished:;
633:     }
634:   }
635:   PetscFunctionReturn(PETSC_SUCCESS);
636: }

638: PetscErrorCode MatPermute_SeqSBAIJ(Mat A, IS rowp, IS colp, Mat *B)
639: {
640:   Mat C;

642:   PetscFunctionBegin;
643:   PetscCall(MatConvert(A, MATSEQBAIJ, MAT_INITIAL_MATRIX, &C));
644:   PetscCall(MatPermute(C, rowp, colp, B));
645:   PetscCall(MatDestroy(&C));
646:   if (rowp == colp) PetscCall(MatConvert(*B, MATSEQSBAIJ, MAT_INPLACE_MATRIX, B));
647:   PetscFunctionReturn(PETSC_SUCCESS);
648: }

650: PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
651: {
652:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ *)A->data;
653:   PetscInt          *rp, k, low, high, t, ii, jj, row, nrow, i, col, l, rmax, N, lastcol = -1;
654:   PetscInt          *imax = a->imax, *ai = a->i, *ailen = a->ilen;
655:   PetscInt          *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs, stepval;
656:   PetscBool          roworiented = a->roworiented;
657:   const PetscScalar *value       = v;
658:   MatScalar         *ap, *aa = a->a, *bap;

660:   PetscFunctionBegin;
661:   if (roworiented) stepval = (n - 1) * bs;
662:   else stepval = (m - 1) * bs;

664:   for (k = 0; k < m; k++) { /* loop over added rows */
665:     row = im[k];
666:     if (row < 0) continue;
667:     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);
668:     rp   = aj + ai[row];
669:     ap   = aa + bs2 * ai[row];
670:     rmax = imax[row];
671:     nrow = ailen[row];
672:     low  = 0;
673:     high = nrow;
674:     for (l = 0; l < n; l++) { /* loop over added columns */
675:       if (in[l] < 0) continue;
676:       col = in[l];
677:       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);
678:       if (col < row) {
679:         if (a->ignore_ltriangular) continue; /* ignore lower triangular block */
680:         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)");
681:       }
682:       if (roworiented) value = v + k * (stepval + bs) * bs + l * bs;
683:       else value = v + l * (stepval + bs) * bs + k * bs;

685:       if (col <= lastcol) low = 0;
686:       else high = nrow;

688:       lastcol = col;
689:       while (high - low > 7) {
690:         t = (low + high) / 2;
691:         if (rp[t] > col) high = t;
692:         else low = t;
693:       }
694:       for (i = low; i < high; i++) {
695:         if (rp[i] > col) break;
696:         if (rp[i] == col) {
697:           bap = ap + bs2 * i;
698:           if (roworiented) {
699:             if (is == ADD_VALUES) {
700:               for (ii = 0; ii < bs; ii++, value += stepval) {
701:                 for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
702:               }
703:             } else {
704:               for (ii = 0; ii < bs; ii++, value += stepval) {
705:                 for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
706:               }
707:             }
708:           } else {
709:             if (is == ADD_VALUES) {
710:               for (ii = 0; ii < bs; ii++, value += stepval) {
711:                 for (jj = 0; jj < bs; jj++) *bap++ += *value++;
712:               }
713:             } else {
714:               for (ii = 0; ii < bs; ii++, value += stepval) {
715:                 for (jj = 0; jj < bs; jj++) *bap++ = *value++;
716:               }
717:             }
718:           }
719:           goto noinsert2;
720:         }
721:       }
722:       if (nonew == 1) goto noinsert2;
723:       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);
724:       MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
725:       N = nrow++ - 1;
726:       high++;
727:       /* shift up all the later entries in this row */
728:       PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
729:       PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
730:       PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
731:       rp[i] = col;
732:       bap   = ap + bs2 * i;
733:       if (roworiented) {
734:         for (ii = 0; ii < bs; ii++, value += stepval) {
735:           for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
736:         }
737:       } else {
738:         for (ii = 0; ii < bs; ii++, value += stepval) {
739:           for (jj = 0; jj < bs; jj++) *bap++ = *value++;
740:         }
741:       }
742:     noinsert2:;
743:       low = i;
744:     }
745:     ailen[row] = nrow;
746:   }
747:   PetscFunctionReturn(PETSC_SUCCESS);
748: }

750: /*
751:     This is not yet used
752: */
753: PetscErrorCode MatAssemblyEnd_SeqSBAIJ_SeqAIJ_Inode(Mat A)
754: {
755:   Mat_SeqSBAIJ   *a  = (Mat_SeqSBAIJ *)A->data;
756:   const PetscInt *ai = a->i, *aj = a->j, *cols;
757:   PetscInt        i = 0, j, blk_size, m = A->rmap->n, node_count = 0, nzx, nzy, *ns, row, nz, cnt, cnt2, *counts;
758:   PetscBool       flag;

760:   PetscFunctionBegin;
761:   PetscCall(PetscMalloc1(m, &ns));
762:   while (i < m) {
763:     nzx = ai[i + 1] - ai[i]; /* Number of nonzeros */
764:     /* Limits the number of elements in a node to 'a->inode.limit' */
765:     for (j = i + 1, blk_size = 1; j < m && blk_size < a->inode.limit; ++j, ++blk_size) {
766:       nzy = ai[j + 1] - ai[j];
767:       if (nzy != (nzx - j + i)) break;
768:       PetscCall(PetscArraycmp(aj + ai[i] + j - i, aj + ai[j], nzy, &flag));
769:       if (!flag) break;
770:     }
771:     ns[node_count++] = blk_size;

773:     i = j;
774:   }
775:   if (!a->inode.size && m && node_count > .9 * m) {
776:     PetscCall(PetscFree(ns));
777:     PetscCall(PetscInfo(A, "Found %" PetscInt_FMT " nodes out of %" PetscInt_FMT " rows. Not using Inode routines\n", node_count, m));
778:   } else {
779:     a->inode.node_count = node_count;

781:     PetscCall(PetscMalloc1(node_count, &a->inode.size));
782:     PetscCall(PetscArraycpy(a->inode.size, ns, node_count));
783:     PetscCall(PetscFree(ns));
784:     PetscCall(PetscInfo(A, "Found %" PetscInt_FMT " nodes of %" PetscInt_FMT ". Limit used: %" PetscInt_FMT ". Using Inode routines\n", node_count, m, a->inode.limit));

786:     /* count collections of adjacent columns in each inode */
787:     row = 0;
788:     cnt = 0;
789:     for (i = 0; i < node_count; i++) {
790:       cols = aj + ai[row] + a->inode.size[i];
791:       nz   = ai[row + 1] - ai[row] - a->inode.size[i];
792:       for (j = 1; j < nz; j++) {
793:         if (cols[j] != cols[j - 1] + 1) cnt++;
794:       }
795:       cnt++;
796:       row += a->inode.size[i];
797:     }
798:     PetscCall(PetscMalloc1(2 * cnt, &counts));
799:     cnt = 0;
800:     row = 0;
801:     for (i = 0; i < node_count; i++) {
802:       cols            = aj + ai[row] + a->inode.size[i];
803:       counts[2 * cnt] = cols[0];
804:       nz              = ai[row + 1] - ai[row] - a->inode.size[i];
805:       cnt2            = 1;
806:       for (j = 1; j < nz; j++) {
807:         if (cols[j] != cols[j - 1] + 1) {
808:           counts[2 * (cnt++) + 1] = cnt2;
809:           counts[2 * cnt]         = cols[j];
810:           cnt2                    = 1;
811:         } else cnt2++;
812:       }
813:       counts[2 * (cnt++) + 1] = cnt2;
814:       row += a->inode.size[i];
815:     }
816:     PetscCall(PetscIntView(2 * cnt, counts, NULL));
817:   }
818:   PetscFunctionReturn(PETSC_SUCCESS);
819: }

821: PetscErrorCode MatAssemblyEnd_SeqSBAIJ(Mat A, MatAssemblyType mode)
822: {
823:   Mat_SeqSBAIJ *a      = (Mat_SeqSBAIJ *)A->data;
824:   PetscInt      fshift = 0, i, *ai = a->i, *aj = a->j, *imax = a->imax;
825:   PetscInt      m = A->rmap->N, *ip, N, *ailen = a->ilen;
826:   PetscInt      mbs = a->mbs, bs2 = a->bs2, rmax = 0;
827:   MatScalar    *aa = a->a, *ap;

829:   PetscFunctionBegin;
830:   if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(PETSC_SUCCESS);

832:   if (m) rmax = ailen[0];
833:   for (i = 1; i < mbs; i++) {
834:     /* move each row back by the amount of empty slots (fshift) before it*/
835:     fshift += imax[i - 1] - ailen[i - 1];
836:     rmax = PetscMax(rmax, ailen[i]);
837:     if (fshift) {
838:       ip = aj + ai[i];
839:       ap = aa + bs2 * ai[i];
840:       N  = ailen[i];
841:       PetscCall(PetscArraymove(ip - fshift, ip, N));
842:       PetscCall(PetscArraymove(ap - bs2 * fshift, ap, bs2 * N));
843:     }
844:     ai[i] = ai[i - 1] + ailen[i - 1];
845:   }
846:   if (mbs) {
847:     fshift += imax[mbs - 1] - ailen[mbs - 1];
848:     ai[mbs] = ai[mbs - 1] + ailen[mbs - 1];
849:   }
850:   /* reset ilen and imax for each row */
851:   for (i = 0; i < mbs; i++) ailen[i] = imax[i] = ai[i + 1] - ai[i];
852:   a->nz = ai[mbs];

854:   /* diagonals may have moved, reset it */
855:   if (a->diag) PetscCall(PetscArraycpy(a->diag, ai, mbs));
856:   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);

858:   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));
859:   PetscCall(PetscInfo(A, "Number of mallocs during MatSetValues is %" PetscInt_FMT "\n", a->reallocs));
860:   PetscCall(PetscInfo(A, "Most nonzeros blocks in any row is %" PetscInt_FMT "\n", rmax));

862:   A->info.mallocs += a->reallocs;
863:   a->reallocs         = 0;
864:   A->info.nz_unneeded = (PetscReal)fshift * bs2;
865:   a->idiagvalid       = PETSC_FALSE;
866:   a->rmax             = rmax;

868:   if (A->cmap->n < 65536 && A->cmap->bs == 1) {
869:     if (a->jshort && a->free_jshort) {
870:       /* when matrix data structure is changed, previous jshort must be replaced */
871:       PetscCall(PetscFree(a->jshort));
872:     }
873:     PetscCall(PetscMalloc1(a->i[A->rmap->n], &a->jshort));
874:     for (i = 0; i < a->i[A->rmap->n]; i++) a->jshort[i] = a->j[i];
875:     A->ops->mult   = MatMult_SeqSBAIJ_1_ushort;
876:     A->ops->sor    = MatSOR_SeqSBAIJ_ushort;
877:     a->free_jshort = PETSC_TRUE;
878:   }
879:   PetscFunctionReturn(PETSC_SUCCESS);
880: }

882: /*
883:    This function returns an array of flags which indicate the locations of contiguous
884:    blocks that should be zeroed. for eg: if bs = 3  and is = [0,1,2,3,5,6,7,8,9]
885:    then the resulting sizes = [3,1,1,3,1] corresponding to sets [(0,1,2),(3),(5),(6,7,8),(9)]
886:    Assume: sizes should be long enough to hold all the values.
887: */
888: PetscErrorCode MatZeroRows_SeqSBAIJ_Check_Blocks(PetscInt idx[], PetscInt n, PetscInt bs, PetscInt sizes[], PetscInt *bs_max)
889: {
890:   PetscInt  i, j, k, row;
891:   PetscBool flg;

893:   PetscFunctionBegin;
894:   for (i = 0, j = 0; i < n; j++) {
895:     row = idx[i];
896:     if (row % bs != 0) { /* Not the beginning of a block */
897:       sizes[j] = 1;
898:       i++;
899:     } else if (i + bs > n) { /* Beginning of a block, but complete block doesn't exist (at idx end) */
900:       sizes[j] = 1;          /* Also makes sure at least 'bs' values exist for next else */
901:       i++;
902:     } else { /* Beginning of the block, so check if the complete block exists */
903:       flg = PETSC_TRUE;
904:       for (k = 1; k < bs; k++) {
905:         if (row + k != idx[i + k]) { /* break in the block */
906:           flg = PETSC_FALSE;
907:           break;
908:         }
909:       }
910:       if (flg) { /* No break in the bs */
911:         sizes[j] = bs;
912:         i += bs;
913:       } else {
914:         sizes[j] = 1;
915:         i++;
916:       }
917:     }
918:   }
919:   *bs_max = j;
920:   PetscFunctionReturn(PETSC_SUCCESS);
921: }

923: /* Only add/insert a(i,j) with i<=j (blocks).
924:    Any a(i,j) with i>j input by user is ignored.
925: */

927: PetscErrorCode MatSetValues_SeqSBAIJ(Mat A, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode is)
928: {
929:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
930:   PetscInt     *rp, k, low, high, t, ii, row, nrow, i, col, l, rmax, N, lastcol = -1;
931:   PetscInt     *imax = a->imax, *ai = a->i, *ailen = a->ilen, roworiented = a->roworiented;
932:   PetscInt     *aj = a->j, nonew = a->nonew, bs = A->rmap->bs, brow, bcol;
933:   PetscInt      ridx, cidx, bs2                 = a->bs2;
934:   MatScalar    *ap, value, *aa                  = a->a, *bap;

936:   PetscFunctionBegin;
937:   for (k = 0; k < m; k++) { /* loop over added rows */
938:     row  = im[k];           /* row number */
939:     brow = row / bs;        /* block row number */
940:     if (row < 0) continue;
941:     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);
942:     rp   = aj + ai[brow];       /*ptr to beginning of column value of the row block*/
943:     ap   = aa + bs2 * ai[brow]; /*ptr to beginning of element value of the row block*/
944:     rmax = imax[brow];          /* maximum space allocated for this row */
945:     nrow = ailen[brow];         /* actual length of this row */
946:     low  = 0;
947:     high = nrow;
948:     for (l = 0; l < n; l++) { /* loop over added columns */
949:       if (in[l] < 0) continue;
950:       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);
951:       col  = in[l];
952:       bcol = col / bs; /* block col number */

954:       if (brow > bcol) {
955:         if (a->ignore_ltriangular) continue; /* ignore lower triangular values */
956:         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)");
957:       }

959:       ridx = row % bs;
960:       cidx = col % bs; /*row and col index inside the block */
961:       if ((brow == bcol && ridx <= cidx) || (brow < bcol)) {
962:         /* element value a(k,l) */
963:         if (roworiented) value = v[l + k * n];
964:         else value = v[k + l * m];

966:         /* move pointer bap to a(k,l) quickly and add/insert value */
967:         if (col <= lastcol) low = 0;
968:         else high = nrow;

970:         lastcol = col;
971:         while (high - low > 7) {
972:           t = (low + high) / 2;
973:           if (rp[t] > bcol) high = t;
974:           else low = t;
975:         }
976:         for (i = low; i < high; i++) {
977:           if (rp[i] > bcol) break;
978:           if (rp[i] == bcol) {
979:             bap = ap + bs2 * i + bs * cidx + ridx;
980:             if (is == ADD_VALUES) *bap += value;
981:             else *bap = value;
982:             /* for diag block, add/insert its symmetric element a(cidx,ridx) */
983:             if (brow == bcol && ridx < cidx) {
984:               bap = ap + bs2 * i + bs * ridx + cidx;
985:               if (is == ADD_VALUES) *bap += value;
986:               else *bap = value;
987:             }
988:             goto noinsert1;
989:           }
990:         }

992:         if (nonew == 1) goto noinsert1;
993:         PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", row, col);
994:         MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);

996:         N = nrow++ - 1;
997:         high++;
998:         /* shift up all the later entries in this row */
999:         PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
1000:         PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
1001:         PetscCall(PetscArrayzero(ap + bs2 * i, bs2));
1002:         rp[i]                          = bcol;
1003:         ap[bs2 * i + bs * cidx + ridx] = value;
1004:         /* for diag block, add/insert its symmetric element a(cidx,ridx) */
1005:         if (brow == bcol && ridx < cidx) ap[bs2 * i + bs * ridx + cidx] = value;
1006:         A->nonzerostate++;
1007:       noinsert1:;
1008:         low = i;
1009:       }
1010:     } /* end of loop over added columns */
1011:     ailen[brow] = nrow;
1012:   } /* end of loop over added rows */
1013:   PetscFunctionReturn(PETSC_SUCCESS);
1014: }

1016: PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA, IS row, const MatFactorInfo *info)
1017: {
1018:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)inA->data;
1019:   Mat           outA;
1020:   PetscBool     row_identity;

1022:   PetscFunctionBegin;
1023:   PetscCheck(info->levels == 0, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only levels=0 is supported for in-place icc");
1024:   PetscCall(ISIdentity(row, &row_identity));
1025:   PetscCheck(row_identity, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix reordering is not supported");
1026:   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()! */

1028:   outA            = inA;
1029:   inA->factortype = MAT_FACTOR_ICC;
1030:   PetscCall(PetscFree(inA->solvertype));
1031:   PetscCall(PetscStrallocpy(MATSOLVERPETSC, &inA->solvertype));

1033:   PetscCall(MatMarkDiagonal_SeqSBAIJ(inA));
1034:   PetscCall(MatSeqSBAIJSetNumericFactorization_inplace(inA, row_identity));

1036:   PetscCall(PetscObjectReference((PetscObject)row));
1037:   PetscCall(ISDestroy(&a->row));
1038:   a->row = row;
1039:   PetscCall(PetscObjectReference((PetscObject)row));
1040:   PetscCall(ISDestroy(&a->col));
1041:   a->col = row;

1043:   /* Create the invert permutation so that it can be used in MatCholeskyFactorNumeric() */
1044:   if (a->icol) PetscCall(ISInvertPermutation(row, PETSC_DECIDE, &a->icol));

1046:   if (!a->solve_work) PetscCall(PetscMalloc1(inA->rmap->N + inA->rmap->bs, &a->solve_work));

1048:   PetscCall(MatCholeskyFactorNumeric(outA, inA, info));
1049:   PetscFunctionReturn(PETSC_SUCCESS);
1050: }

1052: PetscErrorCode MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat, PetscInt *indices)
1053: {
1054:   Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data;
1055:   PetscInt      i, nz, n;

1057:   PetscFunctionBegin;
1058:   nz = baij->maxnz;
1059:   n  = mat->cmap->n;
1060:   for (i = 0; i < nz; i++) baij->j[i] = indices[i];

1062:   baij->nz = nz;
1063:   for (i = 0; i < n; i++) baij->ilen[i] = baij->imax[i];

1065:   PetscCall(MatSetOption(mat, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
1066:   PetscFunctionReturn(PETSC_SUCCESS);
1067: }

1069: /*@
1070:   MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows
1071:   in a `MATSEQSBAIJ` matrix.

1073:   Input Parameters:
1074: +  mat     - the `MATSEQSBAIJ` matrix
1075: -  indices - the column indices

1077:   Level: advanced

1079:   Notes:
1080:   This can be called if you have precomputed the nonzero structure of the
1081:   matrix and want to provide it to the matrix object to improve the performance
1082:   of the `MatSetValues()` operation.

1084:   You MUST have set the correct numbers of nonzeros per row in the call to
1085:   `MatCreateSeqSBAIJ()`, and the columns indices MUST be sorted.

1087:   MUST be called before any calls to `MatSetValues()`

1089: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ`
1090: @*/
1091: PetscErrorCode MatSeqSBAIJSetColumnIndices(Mat mat, PetscInt *indices)
1092: {
1093:   PetscFunctionBegin;
1096:   PetscUseMethod(mat, "MatSeqSBAIJSetColumnIndices_C", (Mat, PetscInt *), (mat, indices));
1097:   PetscFunctionReturn(PETSC_SUCCESS);
1098: }

1100: PetscErrorCode MatCopy_SeqSBAIJ(Mat A, Mat B, MatStructure str)
1101: {
1102:   PetscBool isbaij;

1104:   PetscFunctionBegin;
1105:   PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isbaij, MATSEQSBAIJ, MATMPISBAIJ, ""));
1106:   PetscCheck(isbaij, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for matrix type %s", ((PetscObject)B)->type_name);
1107:   /* If the two matrices have the same copy implementation and nonzero pattern, use fast copy. */
1108:   if (str == SAME_NONZERO_PATTERN && A->ops->copy == B->ops->copy) {
1109:     Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1110:     Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;

1112:     PetscCheck(a->i[a->mbs] == b->i[b->mbs], PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of nonzeros in two matrices are different");
1113:     PetscCheck(a->mbs == b->mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of rows in two matrices are different");
1114:     PetscCheck(a->bs2 == b->bs2, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Different block size");
1115:     PetscCall(PetscArraycpy(b->a, a->a, a->bs2 * a->i[a->mbs]));
1116:     PetscCall(PetscObjectStateIncrease((PetscObject)B));
1117:   } else {
1118:     PetscCall(MatGetRowUpperTriangular(A));
1119:     PetscCall(MatCopy_Basic(A, B, str));
1120:     PetscCall(MatRestoreRowUpperTriangular(A));
1121:   }
1122:   PetscFunctionReturn(PETSC_SUCCESS);
1123: }

1125: static PetscErrorCode MatSeqSBAIJGetArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1126: {
1127:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;

1129:   PetscFunctionBegin;
1130:   *array = a->a;
1131:   PetscFunctionReturn(PETSC_SUCCESS);
1132: }

1134: static PetscErrorCode MatSeqSBAIJRestoreArray_SeqSBAIJ(Mat A, PetscScalar *array[])
1135: {
1136:   PetscFunctionBegin;
1137:   *array = NULL;
1138:   PetscFunctionReturn(PETSC_SUCCESS);
1139: }

1141: PetscErrorCode MatAXPYGetPreallocation_SeqSBAIJ(Mat Y, Mat X, PetscInt *nnz)
1142: {
1143:   PetscInt      bs = Y->rmap->bs, mbs = Y->rmap->N / bs;
1144:   Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data;
1145:   Mat_SeqSBAIJ *y = (Mat_SeqSBAIJ *)Y->data;

1147:   PetscFunctionBegin;
1148:   /* Set the number of nonzeros in the new matrix */
1149:   PetscCall(MatAXPYGetPreallocation_SeqX_private(mbs, x->i, x->j, y->i, y->j, nnz));
1150:   PetscFunctionReturn(PETSC_SUCCESS);
1151: }

1153: PetscErrorCode MatAXPY_SeqSBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str)
1154: {
1155:   Mat_SeqSBAIJ *x = (Mat_SeqSBAIJ *)X->data, *y = (Mat_SeqSBAIJ *)Y->data;
1156:   PetscInt      bs = Y->rmap->bs, bs2 = bs * bs;
1157:   PetscBLASInt  one = 1;

1159:   PetscFunctionBegin;
1160:   if (str == UNKNOWN_NONZERO_PATTERN || (PetscDefined(USE_DEBUG) && str == SAME_NONZERO_PATTERN)) {
1161:     PetscBool e = x->nz == y->nz && x->mbs == y->mbs ? PETSC_TRUE : PETSC_FALSE;
1162:     if (e) {
1163:       PetscCall(PetscArraycmp(x->i, y->i, x->mbs + 1, &e));
1164:       if (e) {
1165:         PetscCall(PetscArraycmp(x->j, y->j, x->i[x->mbs], &e));
1166:         if (e) str = SAME_NONZERO_PATTERN;
1167:       }
1168:     }
1169:     if (!e) PetscCheck(str != SAME_NONZERO_PATTERN, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "MatStructure is not SAME_NONZERO_PATTERN");
1170:   }
1171:   if (str == SAME_NONZERO_PATTERN) {
1172:     PetscScalar  alpha = a;
1173:     PetscBLASInt bnz;
1174:     PetscCall(PetscBLASIntCast(x->nz * bs2, &bnz));
1175:     PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one));
1176:     PetscCall(PetscObjectStateIncrease((PetscObject)Y));
1177:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1178:     PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE));
1179:     PetscCall(MatAXPY_Basic(Y, a, X, str));
1180:     PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE));
1181:   } else {
1182:     Mat       B;
1183:     PetscInt *nnz;
1184:     PetscCheck(bs == X->rmap->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Matrices must have same block size");
1185:     PetscCall(MatGetRowUpperTriangular(X));
1186:     PetscCall(MatGetRowUpperTriangular(Y));
1187:     PetscCall(PetscMalloc1(Y->rmap->N, &nnz));
1188:     PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B));
1189:     PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name));
1190:     PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N));
1191:     PetscCall(MatSetBlockSizesFromMats(B, Y, Y));
1192:     PetscCall(MatSetType(B, ((PetscObject)Y)->type_name));
1193:     PetscCall(MatAXPYGetPreallocation_SeqSBAIJ(Y, X, nnz));
1194:     PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));

1196:     PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str));

1198:     PetscCall(MatHeaderMerge(Y, &B));
1199:     PetscCall(PetscFree(nnz));
1200:     PetscCall(MatRestoreRowUpperTriangular(X));
1201:     PetscCall(MatRestoreRowUpperTriangular(Y));
1202:   }
1203:   PetscFunctionReturn(PETSC_SUCCESS);
1204: }

1206: PetscErrorCode MatIsSymmetric_SeqSBAIJ(Mat A, PetscReal tol, PetscBool *flg)
1207: {
1208:   PetscFunctionBegin;
1209:   *flg = PETSC_TRUE;
1210:   PetscFunctionReturn(PETSC_SUCCESS);
1211: }

1213: PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A, PetscBool *flg)
1214: {
1215:   PetscFunctionBegin;
1216:   *flg = PETSC_TRUE;
1217:   PetscFunctionReturn(PETSC_SUCCESS);
1218: }

1220: PetscErrorCode MatIsHermitian_SeqSBAIJ(Mat A, PetscReal tol, PetscBool *flg)
1221: {
1222:   PetscFunctionBegin;
1223:   *flg = PETSC_FALSE;
1224:   PetscFunctionReturn(PETSC_SUCCESS);
1225: }

1227: PetscErrorCode MatConjugate_SeqSBAIJ(Mat A)
1228: {
1229: #if defined(PETSC_USE_COMPLEX)
1230:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1231:   PetscInt      i, nz = a->bs2 * a->i[a->mbs];
1232:   MatScalar    *aa = a->a;

1234:   PetscFunctionBegin;
1235:   for (i = 0; i < nz; i++) aa[i] = PetscConj(aa[i]);
1236: #else
1237:   PetscFunctionBegin;
1238: #endif
1239:   PetscFunctionReturn(PETSC_SUCCESS);
1240: }

1242: PetscErrorCode MatRealPart_SeqSBAIJ(Mat A)
1243: {
1244:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1245:   PetscInt      i, nz = a->bs2 * a->i[a->mbs];
1246:   MatScalar    *aa = a->a;

1248:   PetscFunctionBegin;
1249:   for (i = 0; i < nz; i++) aa[i] = PetscRealPart(aa[i]);
1250:   PetscFunctionReturn(PETSC_SUCCESS);
1251: }

1253: PetscErrorCode MatImaginaryPart_SeqSBAIJ(Mat A)
1254: {
1255:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
1256:   PetscInt      i, nz = a->bs2 * a->i[a->mbs];
1257:   MatScalar    *aa = a->a;

1259:   PetscFunctionBegin;
1260:   for (i = 0; i < nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
1261:   PetscFunctionReturn(PETSC_SUCCESS);
1262: }

1264: PetscErrorCode MatZeroRowsColumns_SeqSBAIJ(Mat A, PetscInt is_n, const PetscInt is_idx[], PetscScalar diag, Vec x, Vec b)
1265: {
1266:   Mat_SeqSBAIJ      *baij = (Mat_SeqSBAIJ *)A->data;
1267:   PetscInt           i, j, k, count;
1268:   PetscInt           bs = A->rmap->bs, bs2 = baij->bs2, row, col;
1269:   PetscScalar        zero = 0.0;
1270:   MatScalar         *aa;
1271:   const PetscScalar *xx;
1272:   PetscScalar       *bb;
1273:   PetscBool         *zeroed, vecs = PETSC_FALSE;

1275:   PetscFunctionBegin;
1276:   /* fix right hand side if needed */
1277:   if (x && b) {
1278:     PetscCall(VecGetArrayRead(x, &xx));
1279:     PetscCall(VecGetArray(b, &bb));
1280:     vecs = PETSC_TRUE;
1281:   }

1283:   /* zero the columns */
1284:   PetscCall(PetscCalloc1(A->rmap->n, &zeroed));
1285:   for (i = 0; i < is_n; i++) {
1286:     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]);
1287:     zeroed[is_idx[i]] = PETSC_TRUE;
1288:   }
1289:   if (vecs) {
1290:     for (i = 0; i < A->rmap->N; i++) {
1291:       row = i / bs;
1292:       for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1293:         for (k = 0; k < bs; k++) {
1294:           col = bs * baij->j[j] + k;
1295:           if (col <= i) continue;
1296:           aa = ((MatScalar *)(baij->a)) + j * bs2 + (i % bs) + bs * k;
1297:           if (!zeroed[i] && zeroed[col]) bb[i] -= aa[0] * xx[col];
1298:           if (zeroed[i] && !zeroed[col]) bb[col] -= aa[0] * xx[i];
1299:         }
1300:       }
1301:     }
1302:     for (i = 0; i < is_n; i++) bb[is_idx[i]] = diag * xx[is_idx[i]];
1303:   }

1305:   for (i = 0; i < A->rmap->N; i++) {
1306:     if (!zeroed[i]) {
1307:       row = i / bs;
1308:       for (j = baij->i[row]; j < baij->i[row + 1]; j++) {
1309:         for (k = 0; k < bs; k++) {
1310:           col = bs * baij->j[j] + k;
1311:           if (zeroed[col]) {
1312:             aa    = ((MatScalar *)(baij->a)) + j * bs2 + (i % bs) + bs * k;
1313:             aa[0] = 0.0;
1314:           }
1315:         }
1316:       }
1317:     }
1318:   }
1319:   PetscCall(PetscFree(zeroed));
1320:   if (vecs) {
1321:     PetscCall(VecRestoreArrayRead(x, &xx));
1322:     PetscCall(VecRestoreArray(b, &bb));
1323:   }

1325:   /* zero the rows */
1326:   for (i = 0; i < is_n; i++) {
1327:     row   = is_idx[i];
1328:     count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs;
1329:     aa    = ((MatScalar *)(baij->a)) + baij->i[row / bs] * bs2 + (row % bs);
1330:     for (k = 0; k < count; k++) {
1331:       aa[0] = zero;
1332:       aa += bs;
1333:     }
1334:     if (diag != 0.0) PetscUseTypeMethod(A, setvalues, 1, &row, 1, &row, &diag, INSERT_VALUES);
1335:   }
1336:   PetscCall(MatAssemblyEnd_SeqSBAIJ(A, MAT_FINAL_ASSEMBLY));
1337:   PetscFunctionReturn(PETSC_SUCCESS);
1338: }

1340: PetscErrorCode MatShift_SeqSBAIJ(Mat Y, PetscScalar a)
1341: {
1342:   Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)Y->data;

1344:   PetscFunctionBegin;
1345:   if (!Y->preallocated || !aij->nz) PetscCall(MatSeqSBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL));
1346:   PetscCall(MatShift_Basic(Y, a));
1347:   PetscFunctionReturn(PETSC_SUCCESS);
1348: }

1350: static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ,
1351:                                        MatGetRow_SeqSBAIJ,
1352:                                        MatRestoreRow_SeqSBAIJ,
1353:                                        MatMult_SeqSBAIJ_N,
1354:                                        /*  4*/ MatMultAdd_SeqSBAIJ_N,
1355:                                        MatMult_SeqSBAIJ_N, /* transpose versions are same as non-transpose versions */
1356:                                        MatMultAdd_SeqSBAIJ_N,
1357:                                        NULL,
1358:                                        NULL,
1359:                                        NULL,
1360:                                        /* 10*/ NULL,
1361:                                        NULL,
1362:                                        MatCholeskyFactor_SeqSBAIJ,
1363:                                        MatSOR_SeqSBAIJ,
1364:                                        MatTranspose_SeqSBAIJ,
1365:                                        /* 15*/ MatGetInfo_SeqSBAIJ,
1366:                                        MatEqual_SeqSBAIJ,
1367:                                        MatGetDiagonal_SeqSBAIJ,
1368:                                        MatDiagonalScale_SeqSBAIJ,
1369:                                        MatNorm_SeqSBAIJ,
1370:                                        /* 20*/ NULL,
1371:                                        MatAssemblyEnd_SeqSBAIJ,
1372:                                        MatSetOption_SeqSBAIJ,
1373:                                        MatZeroEntries_SeqSBAIJ,
1374:                                        /* 24*/ NULL,
1375:                                        NULL,
1376:                                        NULL,
1377:                                        NULL,
1378:                                        NULL,
1379:                                        /* 29*/ MatSetUp_Seq_Hash,
1380:                                        NULL,
1381:                                        NULL,
1382:                                        NULL,
1383:                                        NULL,
1384:                                        /* 34*/ MatDuplicate_SeqSBAIJ,
1385:                                        NULL,
1386:                                        NULL,
1387:                                        NULL,
1388:                                        MatICCFactor_SeqSBAIJ,
1389:                                        /* 39*/ MatAXPY_SeqSBAIJ,
1390:                                        MatCreateSubMatrices_SeqSBAIJ,
1391:                                        MatIncreaseOverlap_SeqSBAIJ,
1392:                                        MatGetValues_SeqSBAIJ,
1393:                                        MatCopy_SeqSBAIJ,
1394:                                        /* 44*/ NULL,
1395:                                        MatScale_SeqSBAIJ,
1396:                                        MatShift_SeqSBAIJ,
1397:                                        NULL,
1398:                                        MatZeroRowsColumns_SeqSBAIJ,
1399:                                        /* 49*/ NULL,
1400:                                        MatGetRowIJ_SeqSBAIJ,
1401:                                        MatRestoreRowIJ_SeqSBAIJ,
1402:                                        NULL,
1403:                                        NULL,
1404:                                        /* 54*/ NULL,
1405:                                        NULL,
1406:                                        NULL,
1407:                                        MatPermute_SeqSBAIJ,
1408:                                        MatSetValuesBlocked_SeqSBAIJ,
1409:                                        /* 59*/ MatCreateSubMatrix_SeqSBAIJ,
1410:                                        NULL,
1411:                                        NULL,
1412:                                        NULL,
1413:                                        NULL,
1414:                                        /* 64*/ NULL,
1415:                                        NULL,
1416:                                        NULL,
1417:                                        NULL,
1418:                                        NULL,
1419:                                        /* 69*/ MatGetRowMaxAbs_SeqSBAIJ,
1420:                                        NULL,
1421:                                        MatConvert_MPISBAIJ_Basic,
1422:                                        NULL,
1423:                                        NULL,
1424:                                        /* 74*/ NULL,
1425:                                        NULL,
1426:                                        NULL,
1427:                                        NULL,
1428:                                        NULL,
1429:                                        /* 79*/ NULL,
1430:                                        NULL,
1431:                                        NULL,
1432:                                        MatGetInertia_SeqSBAIJ,
1433:                                        MatLoad_SeqSBAIJ,
1434:                                        /* 84*/ MatIsSymmetric_SeqSBAIJ,
1435:                                        MatIsHermitian_SeqSBAIJ,
1436:                                        MatIsStructurallySymmetric_SeqSBAIJ,
1437:                                        NULL,
1438:                                        NULL,
1439:                                        /* 89*/ NULL,
1440:                                        NULL,
1441:                                        NULL,
1442:                                        NULL,
1443:                                        NULL,
1444:                                        /* 94*/ NULL,
1445:                                        NULL,
1446:                                        NULL,
1447:                                        NULL,
1448:                                        NULL,
1449:                                        /* 99*/ NULL,
1450:                                        NULL,
1451:                                        NULL,
1452:                                        MatConjugate_SeqSBAIJ,
1453:                                        NULL,
1454:                                        /*104*/ NULL,
1455:                                        MatRealPart_SeqSBAIJ,
1456:                                        MatImaginaryPart_SeqSBAIJ,
1457:                                        MatGetRowUpperTriangular_SeqSBAIJ,
1458:                                        MatRestoreRowUpperTriangular_SeqSBAIJ,
1459:                                        /*109*/ NULL,
1460:                                        NULL,
1461:                                        NULL,
1462:                                        NULL,
1463:                                        MatMissingDiagonal_SeqSBAIJ,
1464:                                        /*114*/ NULL,
1465:                                        NULL,
1466:                                        NULL,
1467:                                        NULL,
1468:                                        NULL,
1469:                                        /*119*/ NULL,
1470:                                        NULL,
1471:                                        NULL,
1472:                                        NULL,
1473:                                        NULL,
1474:                                        /*124*/ NULL,
1475:                                        NULL,
1476:                                        NULL,
1477:                                        NULL,
1478:                                        NULL,
1479:                                        /*129*/ NULL,
1480:                                        NULL,
1481:                                        NULL,
1482:                                        NULL,
1483:                                        NULL,
1484:                                        /*134*/ NULL,
1485:                                        NULL,
1486:                                        NULL,
1487:                                        NULL,
1488:                                        NULL,
1489:                                        /*139*/ MatSetBlockSizes_Default,
1490:                                        NULL,
1491:                                        NULL,
1492:                                        NULL,
1493:                                        NULL,
1494:                                        /*144*/ MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ,
1495:                                        NULL,
1496:                                        NULL,
1497:                                        NULL,
1498:                                        NULL,
1499:                                        NULL,
1500:                                        /*150*/ NULL,
1501:                                        NULL};

1503: PetscErrorCode MatStoreValues_SeqSBAIJ(Mat mat)
1504: {
1505:   Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1506:   PetscInt      nz  = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;

1508:   PetscFunctionBegin;
1509:   PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");

1511:   /* allocate space for values if not already there */
1512:   if (!aij->saved_values) PetscCall(PetscMalloc1(nz + 1, &aij->saved_values));

1514:   /* copy values over */
1515:   PetscCall(PetscArraycpy(aij->saved_values, aij->a, nz));
1516:   PetscFunctionReturn(PETSC_SUCCESS);
1517: }

1519: PetscErrorCode MatRetrieveValues_SeqSBAIJ(Mat mat)
1520: {
1521:   Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)mat->data;
1522:   PetscInt      nz  = aij->i[mat->rmap->N] * mat->rmap->bs * aij->bs2;

1524:   PetscFunctionBegin;
1525:   PetscCheck(aij->nonew == 1, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1526:   PetscCheck(aij->saved_values, PETSC_COMM_SELF, PETSC_ERR_ORDER, "Must call MatStoreValues(A);first");

1528:   /* copy values over */
1529:   PetscCall(PetscArraycpy(aij->a, aij->saved_values, nz));
1530:   PetscFunctionReturn(PETSC_SUCCESS);
1531: }

1533: static PetscErrorCode MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B, PetscInt bs, PetscInt nz, PetscInt *nnz)
1534: {
1535:   Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ *)B->data;
1536:   PetscInt      i, mbs, nbs, bs2;
1537:   PetscBool     skipallocation = PETSC_FALSE, flg = PETSC_FALSE, realalloc = PETSC_FALSE;

1539:   PetscFunctionBegin;
1540:   if (B->hash_active) {
1541:     PetscInt bs;
1542:     PetscCall(PetscMemcpy(&B->ops, &b->cops, sizeof(*(B->ops))));
1543:     PetscCall(PetscHMapIJVDestroy(&b->ht));
1544:     PetscCall(MatGetBlockSize(B, &bs));
1545:     if (bs > 1) PetscCall(PetscHSetIJDestroy(&b->bht));
1546:     PetscCall(PetscFree(b->dnz));
1547:     PetscCall(PetscFree(b->bdnz));
1548:     B->hash_active = PETSC_FALSE;
1549:   }
1550:   if (nz >= 0 || nnz) realalloc = PETSC_TRUE;

1552:   PetscCall(MatSetBlockSize(B, PetscAbs(bs)));
1553:   PetscCall(PetscLayoutSetUp(B->rmap));
1554:   PetscCall(PetscLayoutSetUp(B->cmap));
1555:   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);
1556:   PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));

1558:   B->preallocated = PETSC_TRUE;

1560:   mbs = B->rmap->N / bs;
1561:   nbs = B->cmap->n / bs;
1562:   bs2 = bs * bs;

1564:   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");

1566:   if (nz == MAT_SKIP_ALLOCATION) {
1567:     skipallocation = PETSC_TRUE;
1568:     nz             = 0;
1569:   }

1571:   if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3;
1572:   PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nz cannot be less than 0: value %" PetscInt_FMT, nz);
1573:   if (nnz) {
1574:     for (i = 0; i < mbs; i++) {
1575:       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]);
1576:       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);
1577:     }
1578:   }

1580:   B->ops->mult             = MatMult_SeqSBAIJ_N;
1581:   B->ops->multadd          = MatMultAdd_SeqSBAIJ_N;
1582:   B->ops->multtranspose    = MatMult_SeqSBAIJ_N;
1583:   B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_N;

1585:   PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1586:   if (!flg) {
1587:     switch (bs) {
1588:     case 1:
1589:       B->ops->mult             = MatMult_SeqSBAIJ_1;
1590:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_1;
1591:       B->ops->multtranspose    = MatMult_SeqSBAIJ_1;
1592:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_1;
1593:       break;
1594:     case 2:
1595:       B->ops->mult             = MatMult_SeqSBAIJ_2;
1596:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_2;
1597:       B->ops->multtranspose    = MatMult_SeqSBAIJ_2;
1598:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_2;
1599:       break;
1600:     case 3:
1601:       B->ops->mult             = MatMult_SeqSBAIJ_3;
1602:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_3;
1603:       B->ops->multtranspose    = MatMult_SeqSBAIJ_3;
1604:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_3;
1605:       break;
1606:     case 4:
1607:       B->ops->mult             = MatMult_SeqSBAIJ_4;
1608:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_4;
1609:       B->ops->multtranspose    = MatMult_SeqSBAIJ_4;
1610:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_4;
1611:       break;
1612:     case 5:
1613:       B->ops->mult             = MatMult_SeqSBAIJ_5;
1614:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_5;
1615:       B->ops->multtranspose    = MatMult_SeqSBAIJ_5;
1616:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_5;
1617:       break;
1618:     case 6:
1619:       B->ops->mult             = MatMult_SeqSBAIJ_6;
1620:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_6;
1621:       B->ops->multtranspose    = MatMult_SeqSBAIJ_6;
1622:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_6;
1623:       break;
1624:     case 7:
1625:       B->ops->mult             = MatMult_SeqSBAIJ_7;
1626:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_7;
1627:       B->ops->multtranspose    = MatMult_SeqSBAIJ_7;
1628:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_7;
1629:       break;
1630:     }
1631:   }

1633:   b->mbs = mbs;
1634:   b->nbs = nbs;
1635:   if (!skipallocation) {
1636:     if (!b->imax) {
1637:       PetscCall(PetscMalloc2(mbs, &b->imax, mbs, &b->ilen));

1639:       b->free_imax_ilen = PETSC_TRUE;
1640:     }
1641:     if (!nnz) {
1642:       if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
1643:       else if (nz <= 0) nz = 1;
1644:       nz = PetscMin(nbs, nz);
1645:       for (i = 0; i < mbs; i++) b->imax[i] = nz;
1646:       PetscCall(PetscIntMultError(nz, mbs, &nz));
1647:     } else {
1648:       PetscInt64 nz64 = 0;
1649:       for (i = 0; i < mbs; i++) {
1650:         b->imax[i] = nnz[i];
1651:         nz64 += nnz[i];
1652:       }
1653:       PetscCall(PetscIntCast(nz64, &nz));
1654:     }
1655:     /* b->ilen will count nonzeros in each block row so far. */
1656:     for (i = 0; i < mbs; i++) b->ilen[i] = 0;
1657:     /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */

1659:     /* allocate the matrix space */
1660:     PetscCall(MatSeqXAIJFreeAIJ(B, &b->a, &b->j, &b->i));
1661:     PetscCall(PetscMalloc3(bs2 * nz, &b->a, nz, &b->j, B->rmap->N + 1, &b->i));
1662:     PetscCall(PetscArrayzero(b->a, nz * bs2));
1663:     PetscCall(PetscArrayzero(b->j, nz));

1665:     b->singlemalloc = PETSC_TRUE;

1667:     /* pointer to beginning of each row */
1668:     b->i[0] = 0;
1669:     for (i = 1; i < mbs + 1; i++) b->i[i] = b->i[i - 1] + b->imax[i - 1];

1671:     b->free_a  = PETSC_TRUE;
1672:     b->free_ij = PETSC_TRUE;
1673:   } else {
1674:     b->free_a  = PETSC_FALSE;
1675:     b->free_ij = PETSC_FALSE;
1676:   }

1678:   b->bs2     = bs2;
1679:   b->nz      = 0;
1680:   b->maxnz   = nz;
1681:   b->inew    = NULL;
1682:   b->jnew    = NULL;
1683:   b->anew    = NULL;
1684:   b->a2anew  = NULL;
1685:   b->permute = PETSC_FALSE;

1687:   B->was_assembled = PETSC_FALSE;
1688:   B->assembled     = PETSC_FALSE;
1689:   if (realalloc) PetscCall(MatSetOption(B, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE));
1690:   PetscFunctionReturn(PETSC_SUCCESS);
1691: }

1693: PetscErrorCode MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[])
1694: {
1695:   PetscInt     i, j, m, nz, anz, nz_max = 0, *nnz;
1696:   PetscScalar *values      = NULL;
1697:   PetscBool    roworiented = ((Mat_SeqSBAIJ *)B->data)->roworiented;

1699:   PetscFunctionBegin;
1700:   PetscCheck(bs >= 1, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_OUTOFRANGE, "Invalid block size specified, must be positive but it is %" PetscInt_FMT, bs);
1701:   PetscCall(PetscLayoutSetBlockSize(B->rmap, bs));
1702:   PetscCall(PetscLayoutSetBlockSize(B->cmap, bs));
1703:   PetscCall(PetscLayoutSetUp(B->rmap));
1704:   PetscCall(PetscLayoutSetUp(B->cmap));
1705:   PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1706:   m = B->rmap->n / bs;

1708:   PetscCheck(!ii[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]);
1709:   PetscCall(PetscMalloc1(m + 1, &nnz));
1710:   for (i = 0; i < m; i++) {
1711:     nz = ii[i + 1] - ii[i];
1712:     PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz);
1713:     anz = 0;
1714:     for (j = 0; j < nz; j++) {
1715:       /* count only values on the diagonal or above */
1716:       if (jj[ii[i] + j] >= i) {
1717:         anz = nz - j;
1718:         break;
1719:       }
1720:     }
1721:     nz_max = PetscMax(nz_max, anz);
1722:     nnz[i] = anz;
1723:   }
1724:   PetscCall(MatSeqSBAIJSetPreallocation(B, bs, 0, nnz));
1725:   PetscCall(PetscFree(nnz));

1727:   values = (PetscScalar *)V;
1728:   if (!values) PetscCall(PetscCalloc1(bs * bs * nz_max, &values));
1729:   for (i = 0; i < m; i++) {
1730:     PetscInt        ncols = ii[i + 1] - ii[i];
1731:     const PetscInt *icols = jj + ii[i];
1732:     if (!roworiented || bs == 1) {
1733:       const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0);
1734:       PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, ncols, icols, svals, INSERT_VALUES));
1735:     } else {
1736:       for (j = 0; j < ncols; j++) {
1737:         const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0);
1738:         PetscCall(MatSetValuesBlocked_SeqSBAIJ(B, 1, &i, 1, &icols[j], svals, INSERT_VALUES));
1739:       }
1740:     }
1741:   }
1742:   if (!V) PetscCall(PetscFree(values));
1743:   PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
1744:   PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
1745:   PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
1746:   PetscFunctionReturn(PETSC_SUCCESS);
1747: }

1749: /*
1750:    This is used to set the numeric factorization for both Cholesky and ICC symbolic factorization
1751: */
1752: PetscErrorCode MatSeqSBAIJSetNumericFactorization_inplace(Mat B, PetscBool natural)
1753: {
1754:   PetscBool flg = PETSC_FALSE;
1755:   PetscInt  bs  = B->rmap->bs;

1757:   PetscFunctionBegin;
1758:   PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_no_unroll", &flg, NULL));
1759:   if (flg) bs = 8;

1761:   if (!natural) {
1762:     switch (bs) {
1763:     case 1:
1764:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace;
1765:       break;
1766:     case 2:
1767:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2;
1768:       break;
1769:     case 3:
1770:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3;
1771:       break;
1772:     case 4:
1773:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4;
1774:       break;
1775:     case 5:
1776:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5;
1777:       break;
1778:     case 6:
1779:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6;
1780:       break;
1781:     case 7:
1782:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7;
1783:       break;
1784:     default:
1785:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N;
1786:       break;
1787:     }
1788:   } else {
1789:     switch (bs) {
1790:     case 1:
1791:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace;
1792:       break;
1793:     case 2:
1794:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
1795:       break;
1796:     case 3:
1797:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
1798:       break;
1799:     case 4:
1800:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
1801:       break;
1802:     case 5:
1803:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
1804:       break;
1805:     case 6:
1806:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
1807:       break;
1808:     case 7:
1809:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
1810:       break;
1811:     default:
1812:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
1813:       break;
1814:     }
1815:   }
1816:   PetscFunctionReturn(PETSC_SUCCESS);
1817: }

1819: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqAIJ(Mat, MatType, MatReuse, Mat *);
1820: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *);
1821: static PetscErrorCode       MatFactorGetSolverType_petsc(Mat A, MatSolverType *type)
1822: {
1823:   PetscFunctionBegin;
1824:   *type = MATSOLVERPETSC;
1825:   PetscFunctionReturn(PETSC_SUCCESS);
1826: }

1828: PETSC_INTERN PetscErrorCode MatGetFactor_seqsbaij_petsc(Mat A, MatFactorType ftype, Mat *B)
1829: {
1830:   PetscInt n = A->rmap->n;

1832:   PetscFunctionBegin;
1833: #if defined(PETSC_USE_COMPLEX)
1834:   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");
1835: #endif

1837:   PetscCall(MatCreate(PetscObjectComm((PetscObject)A), B));
1838:   PetscCall(MatSetSizes(*B, n, n, n, n));
1839:   if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
1840:     PetscCall(MatSetType(*B, MATSEQSBAIJ));
1841:     PetscCall(MatSeqSBAIJSetPreallocation(*B, A->rmap->bs, MAT_SKIP_ALLOCATION, NULL));

1843:     (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ;
1844:     (*B)->ops->iccfactorsymbolic      = MatICCFactorSymbolic_SeqSBAIJ;
1845:     PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_CHOLESKY]));
1846:     PetscCall(PetscStrallocpy(MATORDERINGNATURAL, (char **)&(*B)->preferredordering[MAT_FACTOR_ICC]));
1847:   } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");

1849:   (*B)->factortype     = ftype;
1850:   (*B)->canuseordering = PETSC_TRUE;
1851:   PetscCall(PetscFree((*B)->solvertype));
1852:   PetscCall(PetscStrallocpy(MATSOLVERPETSC, &(*B)->solvertype));
1853:   PetscCall(PetscObjectComposeFunction((PetscObject)*B, "MatFactorGetSolverType_C", MatFactorGetSolverType_petsc));
1854:   PetscFunctionReturn(PETSC_SUCCESS);
1855: }

1857: /*@C
1858:    MatSeqSBAIJGetArray - gives access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored

1860:    Not Collective

1862:    Input Parameter:
1863: .  mat - a `MATSEQSBAIJ` matrix

1865:    Output Parameter:
1866: .   array - pointer to the data

1868:    Level: intermediate

1870: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJRestoreArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1871: @*/
1872: PetscErrorCode MatSeqSBAIJGetArray(Mat A, PetscScalar **array)
1873: {
1874:   PetscFunctionBegin;
1875:   PetscUseMethod(A, "MatSeqSBAIJGetArray_C", (Mat, PetscScalar **), (A, array));
1876:   PetscFunctionReturn(PETSC_SUCCESS);
1877: }

1879: /*@C
1880:    MatSeqSBAIJRestoreArray - returns access to the array where the numerical data for a `MATSEQSBAIJ` matrix is stored obtained by `MatSeqSBAIJGetArray()`

1882:    Not Collective

1884:    Input Parameters:
1885: +  mat - a `MATSEQSBAIJ` matrix
1886: -  array - pointer to the data

1888:    Level: intermediate

1890: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatSeqSBAIJGetArray()`, `MatSeqAIJGetArray()`, `MatSeqAIJRestoreArray()`
1891: @*/
1892: PetscErrorCode MatSeqSBAIJRestoreArray(Mat A, PetscScalar **array)
1893: {
1894:   PetscFunctionBegin;
1895:   PetscUseMethod(A, "MatSeqSBAIJRestoreArray_C", (Mat, PetscScalar **), (A, array));
1896:   PetscFunctionReturn(PETSC_SUCCESS);
1897: }

1899: /*MC
1900:   MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices,
1901:   based on block compressed sparse row format.  Only the upper triangular portion of the matrix is stored.

1903:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
1904:   can call `MatSetOption`(`Mat`, `MAT_HERMITIAN`).

1906:   Options Database Key:
1907:   . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to `MatSetFromOptions()`

1909:   Level: beginner

1911:   Notes:
1912:     By default if you insert values into the lower triangular part of the matrix they are simply ignored (since they are not
1913:      stored and it is assumed they symmetric to the upper triangular). If you call `MatSetOption`(`Mat`,`MAT_IGNORE_LOWER_TRIANGULAR`,`PETSC_FALSE`) or use
1914:      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.

1916:     The number of rows in the matrix must be less than or equal to the number of columns

1918: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreateSeqSBAIJ()`, `MatType`, `MATMPISBAIJ`
1919: M*/
1920: PETSC_EXTERN PetscErrorCode MatCreate_SeqSBAIJ(Mat B)
1921: {
1922:   Mat_SeqSBAIJ *b;
1923:   PetscMPIInt   size;
1924:   PetscBool     no_unroll = PETSC_FALSE, no_inode = PETSC_FALSE;

1926:   PetscFunctionBegin;
1927:   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size));
1928:   PetscCheck(size <= 1, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Comm must be of size 1");

1930:   PetscCall(PetscNew(&b));
1931:   B->data = (void *)b;
1932:   PetscCall(PetscMemcpy(B->ops, &MatOps_Values, sizeof(struct _MatOps)));

1934:   B->ops->destroy    = MatDestroy_SeqSBAIJ;
1935:   B->ops->view       = MatView_SeqSBAIJ;
1936:   b->row             = NULL;
1937:   b->icol            = NULL;
1938:   b->reallocs        = 0;
1939:   b->saved_values    = NULL;
1940:   b->inode.limit     = 5;
1941:   b->inode.max_limit = 5;

1943:   b->roworiented        = PETSC_TRUE;
1944:   b->nonew              = 0;
1945:   b->diag               = NULL;
1946:   b->solve_work         = NULL;
1947:   b->mult_work          = NULL;
1948:   B->spptr              = NULL;
1949:   B->info.nz_unneeded   = (PetscReal)b->maxnz * b->bs2;
1950:   b->keepnonzeropattern = PETSC_FALSE;

1952:   b->inew    = NULL;
1953:   b->jnew    = NULL;
1954:   b->anew    = NULL;
1955:   b->a2anew  = NULL;
1956:   b->permute = PETSC_FALSE;

1958:   b->ignore_ltriangular = PETSC_TRUE;

1960:   PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_ignore_lower_triangular", &b->ignore_ltriangular, NULL));

1962:   b->getrow_utriangular = PETSC_FALSE;

1964:   PetscCall(PetscOptionsGetBool(((PetscObject)B)->options, ((PetscObject)B)->prefix, "-mat_getrow_uppertriangular", &b->getrow_utriangular, NULL));

1966:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJGetArray_C", MatSeqSBAIJGetArray_SeqSBAIJ));
1967:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJRestoreArray_C", MatSeqSBAIJRestoreArray_SeqSBAIJ));
1968:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_SeqSBAIJ));
1969:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_SeqSBAIJ));
1970:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetColumnIndices_C", MatSeqSBAIJSetColumnIndices_SeqSBAIJ));
1971:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqaij_C", MatConvert_SeqSBAIJ_SeqAIJ));
1972:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_seqbaij_C", MatConvert_SeqSBAIJ_SeqBAIJ));
1973:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocation_C", MatSeqSBAIJSetPreallocation_SeqSBAIJ));
1974:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSeqSBAIJSetPreallocationCSR_C", MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ));
1975: #if defined(PETSC_HAVE_ELEMENTAL)
1976:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_elemental_C", MatConvert_SeqSBAIJ_Elemental));
1977: #endif
1978: #if defined(PETSC_HAVE_SCALAPACK)
1979:   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_seqsbaij_scalapack_C", MatConvert_SBAIJ_ScaLAPACK));
1980: #endif

1982:   B->symmetry_eternal            = PETSC_TRUE;
1983:   B->structural_symmetry_eternal = PETSC_TRUE;
1984:   B->symmetric                   = PETSC_BOOL3_TRUE;
1985:   B->structurally_symmetric      = PETSC_BOOL3_TRUE;
1986: #if defined(PETSC_USE_COMPLEX)
1987:   B->hermitian = PETSC_BOOL3_FALSE;
1988: #else
1989:   B->hermitian = PETSC_BOOL3_TRUE;
1990: #endif

1992:   PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATSEQSBAIJ));

1994:   PetscOptionsBegin(PetscObjectComm((PetscObject)B), ((PetscObject)B)->prefix, "Options for SEQSBAIJ matrix", "Mat");
1995:   PetscCall(PetscOptionsBool("-mat_no_unroll", "Do not optimize for inodes (slower)", NULL, no_unroll, &no_unroll, NULL));
1996:   if (no_unroll) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_unroll\n"));
1997:   PetscCall(PetscOptionsBool("-mat_no_inode", "Do not optimize for inodes (slower)", NULL, no_inode, &no_inode, NULL));
1998:   if (no_inode) PetscCall(PetscInfo(B, "Not using Inode routines due to -mat_no_inode\n"));
1999:   PetscCall(PetscOptionsInt("-mat_inode_limit", "Do not use inodes larger then this value", NULL, b->inode.limit, &b->inode.limit, NULL));
2000:   PetscOptionsEnd();
2001:   b->inode.use = (PetscBool)(!(no_unroll || no_inode));
2002:   if (b->inode.limit > b->inode.max_limit) b->inode.limit = b->inode.max_limit;
2003:   PetscFunctionReturn(PETSC_SUCCESS);
2004: }

2006: /*@C
2007:    MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block
2008:    compressed row) `MATSEQSBAIJ` format.  For good matrix assembly performance the
2009:    user should preallocate the matrix storage by setting the parameter `nz`
2010:    (or the array `nnz`).

2012:    Collective

2014:    Input Parameters:
2015: +  B - the symmetric matrix
2016: .  bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2017:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
2018: .  nz - number of block nonzeros per block row (same for all rows)
2019: -  nnz - array containing the number of block nonzeros in the upper triangular plus
2020:          diagonal portion of each block (possibly different for each block row) or `NULL`

2022:    Options Database Keys:
2023: +   -mat_no_unroll - uses code that does not unroll the loops in the
2024:                      block calculations (much slower)
2025: -   -mat_block_size - size of the blocks to use (only works if a negative bs is passed in

2027:    Level: intermediate

2029:    Notes:
2030:    Specify the preallocated storage with either `nz` or `nnz` (not both).
2031:    Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
2032:    allocation.  See [Sparse Matrices](sec_matsparse) for details.

2034:    You can call `MatGetInfo()` to get information on how effective the preallocation was;
2035:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2036:    You can also run with the option `-info` and look for messages with the string
2037:    malloc in them to see if additional memory allocation was needed.

2039:    If the `nnz` parameter is given then the `nz` parameter is ignored

2041: .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
2042: @*/
2043: PetscErrorCode MatSeqSBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt nz, const PetscInt nnz[])
2044: {
2045:   PetscFunctionBegin;
2049:   PetscTryMethod(B, "MatSeqSBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[]), (B, bs, nz, nnz));
2050:   PetscFunctionReturn(PETSC_SUCCESS);
2051: }

2053: /*@C
2054:    MatSeqSBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATSEQSBAIJ` format using the given nonzero structure and (optional) numerical values

2056:    Input Parameters:
2057: +  B - the matrix
2058: .  bs - size of block, the blocks are ALWAYS square.
2059: .  i - the indices into j for the start of each local row (starts with zero)
2060: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2061: -  v - optional values in the matrix

2063:    Level: advanced

2065:    Notes:
2066:    The order of the entries in values is specified by the `MatOption` `MAT_ROW_ORIENTED`.  For example, C programs
2067:    may want to use the default `MAT_ROW_ORIENTED` = `PETSC_TRUE` and use an array v[nnz][bs][bs] where the second index is
2068:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
2069:    `MAT_ROW_ORIENTED` = `PETSC_FALSE` and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
2070:    block column and the second index is over columns within a block.

2072:    Any entries below the diagonal are ignored

2074:    Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2075:    and usually the numerical values as well

2077: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValuesBlocked()`, `MatSeqSBAIJSetPreallocation()`, `MATSEQSBAIJ`
2078: @*/
2079: PetscErrorCode MatSeqSBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[])
2080: {
2081:   PetscFunctionBegin;
2085:   PetscTryMethod(B, "MatSeqSBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v));
2086:   PetscFunctionReturn(PETSC_SUCCESS);
2087: }

2089: /*@C
2090:    MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in (block
2091:    compressed row) `MATSEQSBAIJ` format.  For good matrix assembly performance the
2092:    user should preallocate the matrix storage by setting the parameter `nz`
2093:    (or the array `nnz`).

2095:    Collective

2097:    Input Parameters:
2098: +  comm - MPI communicator, set to `PETSC_COMM_SELF`
2099: .  bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2100:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2101: .  m - number of rows
2102: .  n - number of columns
2103: .  nz - number of block nonzeros per block row (same for all rows)
2104: -  nnz - array containing the number of block nonzeros in the upper triangular plus
2105:          diagonal portion of each block (possibly different for each block row) or `NULL`

2107:    Output Parameter:
2108: .  A - the symmetric matrix

2110:    Options Database Keys:
2111: +   -mat_no_unroll - uses code that does not unroll the loops in the
2112:                      block calculations (much slower)
2113: -   -mat_block_size - size of the blocks to use

2115:    Level: intermediate

2117:    Notes:
2118:    It is recommended that one use the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`,
2119:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
2120:    [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`]

2122:    The number of rows and columns must be divisible by blocksize.
2123:    This matrix type does not support complex Hermitian operation.

2125:    Specify the preallocated storage with either `nz` or `nnz` (not both).
2126:    Set `nz` = `PETSC_DEFAULT` and `nnz` = `NULL` for PETSc to control dynamic memory
2127:    allocation.  See [Sparse Matrices](sec_matsparse) for details.

2129:    If the `nnz` parameter is given then the `nz` parameter is ignored

2131: .seealso: [](ch_matrices), `Mat`, [Sparse Matrices](sec_matsparse), `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatCreateSBAIJ()`
2132: @*/
2133: PetscErrorCode MatCreateSeqSBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt nz, const PetscInt nnz[], Mat *A)
2134: {
2135:   PetscFunctionBegin;
2136:   PetscCall(MatCreate(comm, A));
2137:   PetscCall(MatSetSizes(*A, m, n, m, n));
2138:   PetscCall(MatSetType(*A, MATSEQSBAIJ));
2139:   PetscCall(MatSeqSBAIJSetPreallocation(*A, bs, nz, (PetscInt *)nnz));
2140:   PetscFunctionReturn(PETSC_SUCCESS);
2141: }

2143: PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A, MatDuplicateOption cpvalues, Mat *B)
2144: {
2145:   Mat           C;
2146:   Mat_SeqSBAIJ *c, *a  = (Mat_SeqSBAIJ *)A->data;
2147:   PetscInt      i, mbs = a->mbs, nz = a->nz, bs2 = a->bs2;

2149:   PetscFunctionBegin;
2150:   PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Cannot duplicate unassembled matrix");
2151:   PetscCheck(a->i[mbs] == nz, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Corrupt matrix");

2153:   *B = NULL;
2154:   PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &C));
2155:   PetscCall(MatSetSizes(C, A->rmap->N, A->cmap->n, A->rmap->N, A->cmap->n));
2156:   PetscCall(MatSetBlockSizesFromMats(C, A, A));
2157:   PetscCall(MatSetType(C, MATSEQSBAIJ));
2158:   c = (Mat_SeqSBAIJ *)C->data;

2160:   C->preallocated       = PETSC_TRUE;
2161:   C->factortype         = A->factortype;
2162:   c->row                = NULL;
2163:   c->icol               = NULL;
2164:   c->saved_values       = NULL;
2165:   c->keepnonzeropattern = a->keepnonzeropattern;
2166:   C->assembled          = PETSC_TRUE;

2168:   PetscCall(PetscLayoutReference(A->rmap, &C->rmap));
2169:   PetscCall(PetscLayoutReference(A->cmap, &C->cmap));
2170:   c->bs2 = a->bs2;
2171:   c->mbs = a->mbs;
2172:   c->nbs = a->nbs;

2174:   if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2175:     c->imax           = a->imax;
2176:     c->ilen           = a->ilen;
2177:     c->free_imax_ilen = PETSC_FALSE;
2178:   } else {
2179:     PetscCall(PetscMalloc2((mbs + 1), &c->imax, (mbs + 1), &c->ilen));
2180:     for (i = 0; i < mbs; i++) {
2181:       c->imax[i] = a->imax[i];
2182:       c->ilen[i] = a->ilen[i];
2183:     }
2184:     c->free_imax_ilen = PETSC_TRUE;
2185:   }

2187:   /* allocate the matrix space */
2188:   if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2189:     PetscCall(PetscMalloc1(bs2 * nz, &c->a));
2190:     c->i            = a->i;
2191:     c->j            = a->j;
2192:     c->singlemalloc = PETSC_FALSE;
2193:     c->free_a       = PETSC_TRUE;
2194:     c->free_ij      = PETSC_FALSE;
2195:     c->parent       = A;
2196:     PetscCall(PetscObjectReference((PetscObject)A));
2197:     PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2198:     PetscCall(MatSetOption(C, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2199:   } else {
2200:     PetscCall(PetscMalloc3(bs2 * nz, &c->a, nz, &c->j, mbs + 1, &c->i));
2201:     PetscCall(PetscArraycpy(c->i, a->i, mbs + 1));
2202:     c->singlemalloc = PETSC_TRUE;
2203:     c->free_a       = PETSC_TRUE;
2204:     c->free_ij      = PETSC_TRUE;
2205:   }
2206:   if (mbs > 0) {
2207:     if (cpvalues != MAT_SHARE_NONZERO_PATTERN) PetscCall(PetscArraycpy(c->j, a->j, nz));
2208:     if (cpvalues == MAT_COPY_VALUES) {
2209:       PetscCall(PetscArraycpy(c->a, a->a, bs2 * nz));
2210:     } else {
2211:       PetscCall(PetscArrayzero(c->a, bs2 * nz));
2212:     }
2213:     if (a->jshort) {
2214:       /* cannot share jshort, it is reallocated in MatAssemblyEnd_SeqSBAIJ() */
2215:       /* if the parent matrix is reassembled, this child matrix will never notice */
2216:       PetscCall(PetscMalloc1(nz, &c->jshort));
2217:       PetscCall(PetscArraycpy(c->jshort, a->jshort, nz));

2219:       c->free_jshort = PETSC_TRUE;
2220:     }
2221:   }

2223:   c->roworiented = a->roworiented;
2224:   c->nonew       = a->nonew;

2226:   if (a->diag) {
2227:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
2228:       c->diag      = a->diag;
2229:       c->free_diag = PETSC_FALSE;
2230:     } else {
2231:       PetscCall(PetscMalloc1(mbs, &c->diag));
2232:       for (i = 0; i < mbs; i++) c->diag[i] = a->diag[i];
2233:       c->free_diag = PETSC_TRUE;
2234:     }
2235:   }
2236:   c->nz         = a->nz;
2237:   c->maxnz      = a->nz; /* Since we allocate exactly the right amount */
2238:   c->solve_work = NULL;
2239:   c->mult_work  = NULL;

2241:   *B = C;
2242:   PetscCall(PetscFunctionListDuplicate(((PetscObject)A)->qlist, &((PetscObject)C)->qlist));
2243:   PetscFunctionReturn(PETSC_SUCCESS);
2244: }

2246: /* Used for both SeqBAIJ and SeqSBAIJ matrices */
2247: #define MatLoad_SeqSBAIJ_Binary MatLoad_SeqBAIJ_Binary

2249: PetscErrorCode MatLoad_SeqSBAIJ(Mat mat, PetscViewer viewer)
2250: {
2251:   PetscBool isbinary;

2253:   PetscFunctionBegin;
2254:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
2255:   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);
2256:   PetscCall(MatLoad_SeqSBAIJ_Binary(mat, viewer));
2257:   PetscFunctionReturn(PETSC_SUCCESS);
2258: }

2260: /*@
2261:      MatCreateSeqSBAIJWithArrays - Creates an sequential `MATSEQSBAIJ` matrix using matrix elements
2262:               (upper triangular entries in CSR format) provided by the user.

2264:      Collective

2266:    Input Parameters:
2267: +  comm - must be an MPI communicator of size 1
2268: .  bs - size of block
2269: .  m - number of rows
2270: .  n - number of columns
2271: .  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
2272: .  j - column indices
2273: -  a - matrix values

2275:    Output Parameter:
2276: .  mat - the matrix

2278:    Level: advanced

2280:    Notes:
2281:        The `i`, `j`, and `a` arrays are not copied by this routine, the user must free these arrays
2282:     once the matrix is destroyed

2284:        You cannot set new nonzero locations into this matrix, that will generate an error.

2286:        The `i` and `j` indices are 0 based

2288:        When block size is greater than 1 the matrix values must be stored using the `MATSBAIJ` storage format. For block size of 1
2289:        it is the regular CSR format excluding the lower triangular elements.

2291: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MatCreate()`, `MatCreateSBAIJ()`, `MatCreateSeqSBAIJ()`
2292: @*/
2293: PetscErrorCode MatCreateSeqSBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt i[], PetscInt j[], PetscScalar a[], Mat *mat)
2294: {
2295:   PetscInt      ii;
2296:   Mat_SeqSBAIJ *sbaij;

2298:   PetscFunctionBegin;
2299:   PetscCheck(bs == 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "block size %" PetscInt_FMT " > 1 is not supported yet", bs);
2300:   PetscCheck(m == 0 || i[0] == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0");

2302:   PetscCall(MatCreate(comm, mat));
2303:   PetscCall(MatSetSizes(*mat, m, n, m, n));
2304:   PetscCall(MatSetType(*mat, MATSEQSBAIJ));
2305:   PetscCall(MatSeqSBAIJSetPreallocation(*mat, bs, MAT_SKIP_ALLOCATION, NULL));
2306:   sbaij = (Mat_SeqSBAIJ *)(*mat)->data;
2307:   PetscCall(PetscMalloc2(m, &sbaij->imax, m, &sbaij->ilen));

2309:   sbaij->i = i;
2310:   sbaij->j = j;
2311:   sbaij->a = a;

2313:   sbaij->singlemalloc   = PETSC_FALSE;
2314:   sbaij->nonew          = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
2315:   sbaij->free_a         = PETSC_FALSE;
2316:   sbaij->free_ij        = PETSC_FALSE;
2317:   sbaij->free_imax_ilen = PETSC_TRUE;

2319:   for (ii = 0; ii < m; ii++) {
2320:     sbaij->ilen[ii] = sbaij->imax[ii] = i[ii + 1] - i[ii];
2321:     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]);
2322:   }
2323:   if (PetscDefined(USE_DEBUG)) {
2324:     for (ii = 0; ii < sbaij->i[m]; ii++) {
2325:       PetscCheck(j[ii] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative column index at location = %" PetscInt_FMT " index = %" PetscInt_FMT, ii, j[ii]);
2326:       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]);
2327:     }
2328:   }

2330:   PetscCall(MatAssemblyBegin(*mat, MAT_FINAL_ASSEMBLY));
2331:   PetscCall(MatAssemblyEnd(*mat, MAT_FINAL_ASSEMBLY));
2332:   PetscFunctionReturn(PETSC_SUCCESS);
2333: }

2335: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
2336: {
2337:   PetscFunctionBegin;
2338:   PetscCall(MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(comm, inmat, n, scall, outmat));
2339:   PetscFunctionReturn(PETSC_SUCCESS);
2340: }