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: }