Actual source code: sbaij.c

  1: #define PETSCMAT_DLL

  3: /*
  4:     Defines the basic matrix operations for the SBAIJ (compressed row)
  5:   matrix storage format.
  6: */
 7:  #include ../src/mat/impls/baij/seq/baij.h
 8:  #include ../src/inline/spops.h
 9:  #include ../src/mat/impls/sbaij/seq/sbaij.h

 12: #define CHUNKSIZE  10

 14: /*
 15:      Checks for missing diagonals
 16: */
 19: PetscErrorCode MatMissingDiagonal_SeqSBAIJ(Mat A,PetscTruth *missing,PetscInt *dd)
 20: {
 21:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
 23:   PetscInt       *diag,*jj = a->j,i;

 26:   MatMarkDiagonal_SeqSBAIJ(A);
 27:   diag = a->diag;
 28:   *missing = PETSC_FALSE;
 29:   for (i=0; i<a->mbs; i++) {
 30:     if (jj[diag[i]] != i) {
 31:       *missing    = PETSC_TRUE;
 32:       if (dd) *dd = i;
 33:       break;
 34:     }
 35:   }
 36:   return(0);
 37: }

 41: PetscErrorCode MatMarkDiagonal_SeqSBAIJ(Mat A)
 42: {
 43:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
 45:   PetscInt       i;

 48:   if (!a->diag) {
 49:     PetscMalloc(a->mbs*sizeof(PetscInt),&a->diag);
 50:   }
 51:   for (i=0; i<a->mbs; i++) a->diag[i] = a->i[i];
 52:   return(0);
 53: }

 57: static PetscErrorCode MatGetRowIJ_SeqSBAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth blockcompressed,PetscInt *nn,PetscInt *ia[],PetscInt *ja[],PetscTruth *done)
 58: {
 59:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
 60:   PetscInt     i,j,n = a->mbs,nz = a->i[n],bs = A->rmap->bs;

 64:   *nn = n;
 65:   if (!ia) return(0);
 66:   if (!blockcompressed) {
 67:     /* malloc & create the natural set of indices */
 68:     PetscMalloc2((n+1)*bs,PetscInt,ia,nz*bs,PetscInt,ja);
 69:     for (i=0; i<n+1; i++) {
 70:       for (j=0; j<bs; j++) {
 71:         *ia[i*bs+j] = a->i[i]*bs+j+oshift;
 72:       }
 73:     }
 74:     for (i=0; i<nz; i++) {
 75:       for (j=0; j<bs; j++) {
 76:         *ja[i*bs+j] = a->j[i]*bs+j+oshift;
 77:       }
 78:     }
 79:   } else { /* blockcompressed */
 80:     if (oshift == 1) {
 81:       /* temporarily add 1 to i and j indices */
 82:       for (i=0; i<nz; i++) a->j[i]++;
 83:       for (i=0; i<n+1; i++) a->i[i]++;
 84:     }
 85:     *ia = a->i; *ja = a->j;
 86:   }

 88:   return(0);
 89: }

 93: static PetscErrorCode MatRestoreRowIJ_SeqSBAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth blockcompressed,PetscInt *nn,PetscInt *ia[],PetscInt *ja[],PetscTruth *done)
 94: {
 95:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
 96:   PetscInt     i,n = a->mbs,nz = a->i[n];

100:   if (!ia) return(0);

102:   if (!blockcompressed) {
103:     PetscFree2(*ia,*ja);
104:   } else if (oshift == 1) { /* blockcompressed */
105:     for (i=0; i<nz; i++) a->j[i]--;
106:     for (i=0; i<n+1; i++) a->i[i]--;
107:   }

109:   return(0);
110: }

114: PetscErrorCode MatDestroy_SeqSBAIJ(Mat A)
115: {
116:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;

120: #if defined(PETSC_USE_LOG)
121:   PetscLogObjectState((PetscObject)A,"Rows=%D, NZ=%D",A->rmap->N,a->nz);
122: #endif
123:   MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);
124:   if (a->row) {ISDestroy(a->row);}
125:   if (a->col){ISDestroy(a->col);}
126:   if (a->icol) {ISDestroy(a->icol);}
127:   PetscFree(a->diag);
128:   PetscFree2(a->imax,a->ilen);
129:   PetscFree(a->solve_work);
130:   PetscFree(a->relax_work);
131:   PetscFree(a->solves_work);
132:   PetscFree(a->mult_work);
133:   PetscFree(a->saved_values);
134:   PetscFree(a->xtoy);

136:   PetscFree(a->inew);
137:   PetscFree(a);

139:   PetscObjectChangeTypeName((PetscObject)A,0);
140:   PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C","",PETSC_NULL);
141:   PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C","",PETSC_NULL);
142:   PetscObjectComposeFunction((PetscObject)A,"MatSeqSBAIJSetColumnIndices_C","",PETSC_NULL);
143:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqsbaij_seqaij_C","",PETSC_NULL);
144:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqsbaij_seqbaij_C","",PETSC_NULL);
145:   PetscObjectComposeFunction((PetscObject)A,"MatSeqSBAIJSetPreallocation_C","",PETSC_NULL);
146:   return(0);
147: }

151: PetscErrorCode MatSetOption_SeqSBAIJ(Mat A,MatOption op,PetscTruth flg)
152: {
153:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;

157:   switch (op) {
158:   case MAT_ROW_ORIENTED:
159:     a->roworiented = flg;
160:     break;
161:   case MAT_KEEP_ZEROED_ROWS:
162:     a->keepzeroedrows = flg;
163:     break;
164:   case MAT_NEW_NONZERO_LOCATIONS:
165:     a->nonew = (flg ? 0 : 1);
166:     break;
167:   case MAT_NEW_NONZERO_LOCATION_ERR:
168:     a->nonew = (flg ? -1 : 0);
169:     break;
170:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
171:     a->nonew = (flg ? -2 : 0);
172:     break;
173:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
174:     a->nounused = (flg ? -1 : 0);
175:     break;
176:   case MAT_NEW_DIAGONALS:
177:   case MAT_IGNORE_OFF_PROC_ENTRIES:
178:   case MAT_USE_HASH_TABLE:
179:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
180:     break;
181:   case MAT_HERMITIAN:
182:     if (flg) SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric");
183:   case MAT_SYMMETRIC:
184:   case MAT_STRUCTURALLY_SYMMETRIC:
185:   case MAT_SYMMETRY_ETERNAL:
186:     if (!flg) SETERRQ(PETSC_ERR_SUP,"Matrix must be symmetric");
187:     PetscInfo1(A,"Option %s not relevent\n",MatOptions[op]);
188:     break;
189:   case MAT_IGNORE_LOWER_TRIANGULAR:
190:     a->ignore_ltriangular = flg;
191:     break;
192:   case MAT_ERROR_LOWER_TRIANGULAR:
193:     a->ignore_ltriangular = flg;
194:     break;
195:   case MAT_GETROW_UPPERTRIANGULAR:
196:     a->getrow_utriangular = flg;
197:     break;
198:   default:
199:     SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op);
200:   }
201:   return(0);
202: }

206: PetscErrorCode MatGetRow_SeqSBAIJ(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **v)
207: {
208:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
210:   PetscInt       itmp,i,j,k,M,*ai,*aj,bs,bn,bp,*cols_i,bs2;
211:   MatScalar      *aa,*aa_i;
212:   PetscScalar    *v_i;

215:   if (A && !a->getrow_utriangular) SETERRQ(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()");
216:   /* Get the upper triangular part of the row */
217:   bs  = A->rmap->bs;
218:   ai  = a->i;
219:   aj  = a->j;
220:   aa  = a->a;
221:   bs2 = a->bs2;
222: 
223:   if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE, "Row %D out of range", row);
224: 
225:   bn  = row/bs;   /* Block number */
226:   bp  = row % bs; /* Block position */
227:   M   = ai[bn+1] - ai[bn];
228:   *ncols = bs*M;
229: 
230:   if (v) {
231:     *v = 0;
232:     if (*ncols) {
233:       PetscMalloc((*ncols+row)*sizeof(PetscScalar),v);
234:       for (i=0; i<M; i++) { /* for each block in the block row */
235:         v_i  = *v + i*bs;
236:         aa_i = aa + bs2*(ai[bn] + i);
237:         for (j=bp,k=0; j<bs2; j+=bs,k++) {v_i[k] = aa_i[j];}
238:       }
239:     }
240:   }
241: 
242:   if (cols) {
243:     *cols = 0;
244:     if (*ncols) {
245:       PetscMalloc((*ncols+row)*sizeof(PetscInt),cols);
246:       for (i=0; i<M; i++) { /* for each block in the block row */
247:         cols_i = *cols + i*bs;
248:         itmp  = bs*aj[ai[bn] + i];
249:         for (j=0; j<bs; j++) {cols_i[j] = itmp++;}
250:       }
251:     }
252:   }
253: 
254:   /*search column A(0:row-1,row) (=A(row,0:row-1)). Could be expensive! */
255:   /* this segment is currently removed, so only entries in the upper triangle are obtained */
256: #ifdef column_search
257:   v_i    = *v    + M*bs;
258:   cols_i = *cols + M*bs;
259:   for (i=0; i<bn; i++){ /* for each block row */
260:     M = ai[i+1] - ai[i];
261:     for (j=0; j<M; j++){
262:       itmp = aj[ai[i] + j];    /* block column value */
263:       if (itmp == bn){
264:         aa_i   = aa    + bs2*(ai[i] + j) + bs*bp;
265:         for (k=0; k<bs; k++) {
266:           *cols_i++ = i*bs+k;
267:           *v_i++    = aa_i[k];
268:         }
269:         *ncols += bs;
270:         break;
271:       }
272:     }
273:   }
274: #endif
275:   return(0);
276: }

280: PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
281: {
283: 
285:   if (idx) {PetscFree(*idx);}
286:   if (v)   {PetscFree(*v);}
287:   return(0);
288: }

292: PetscErrorCode MatGetRowUpperTriangular_SeqSBAIJ(Mat A)
293: {
294:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;

297:   a->getrow_utriangular = PETSC_TRUE;
298:   return(0);
299: }
302: PetscErrorCode MatRestoreRowUpperTriangular_SeqSBAIJ(Mat A)
303: {
304:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;

307:   a->getrow_utriangular = PETSC_FALSE;
308:   return(0);
309: }

313: PetscErrorCode MatTranspose_SeqSBAIJ(Mat A,MatReuse reuse,Mat *B)
314: {
317:   if (reuse == MAT_INITIAL_MATRIX || *B != A) {
318:     MatDuplicate(A,MAT_COPY_VALUES,B);
319:   }
320:   return(0);
321: }

325: static PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat A,PetscViewer viewer)
326: {
327:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
328:   PetscErrorCode    ierr;
329:   PetscInt          i,j,bs = A->rmap->bs,k,l,bs2=a->bs2;
330:   const char        *name;
331:   PetscViewerFormat format;
332: 
334:   PetscObjectGetName((PetscObject)A,&name);
335:   PetscViewerGetFormat(viewer,&format);
336:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
337:     PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
338:   } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
339:     Mat aij;

341:     if (A->factor && bs>1){
342:       PetscPrintf(PETSC_COMM_SELF,"Warning: matrix is factored with bs>1. MatView() with PETSC_VIEWER_ASCII_MATLAB is not supported and ignored!\n");
343:       return(0);
344:     }
345:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);
346:     MatView(aij,viewer);
347:     MatDestroy(aij);
348:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
349:     PetscViewerASCIIUseTabs(viewer,PETSC_NO);
350:     for (i=0; i<a->mbs; i++) {
351:       for (j=0; j<bs; j++) {
352:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
353:         for (k=a->i[i]; k<a->i[i+1]; k++) {
354:           for (l=0; l<bs; l++) {
355: #if defined(PETSC_USE_COMPLEX)
356:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
357:               PetscViewerASCIIPrintf(viewer," (%D, %G + %G i) ",bs*a->j[k]+l,
358:                                             PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
359:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
360:               PetscViewerASCIIPrintf(viewer," (%D, %G - %G i) ",bs*a->j[k]+l,
361:                                             PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
362:             } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
363:               PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));
364:             }
365: #else
366:             if (a->a[bs2*k + l*bs + j] != 0.0) {
367:               PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);
368:             }
369: #endif
370:           }
371:         }
372:         PetscViewerASCIIPrintf(viewer,"\n");
373:       }
374:     }
375:     PetscViewerASCIIUseTabs(viewer,PETSC_YES);
376:   } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
377:      return(0);
378:   } else {
379:     if (A->factor && bs>1){
380:       PetscPrintf(PETSC_COMM_SELF,"Warning: matrix is factored. MatView_SeqSBAIJ_ASCII() may not display complete or logically correct entries!\n");
381:     }
382:     PetscViewerASCIIUseTabs(viewer,PETSC_NO);
383:     for (i=0; i<a->mbs; i++) {
384:       for (j=0; j<bs; j++) {
385:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
386:         for (k=a->i[i]; k<a->i[i+1]; k++) {
387:           for (l=0; l<bs; l++) {
388: #if defined(PETSC_USE_COMPLEX)
389:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) {
390:               PetscViewerASCIIPrintf(viewer," (%D, %G + %G i) ",bs*a->j[k]+l,
391:                                             PetscRealPart(a->a[bs2*k + l*bs + j]),PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
392:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) {
393:               PetscViewerASCIIPrintf(viewer," (%D, %G - %G i) ",bs*a->j[k]+l,
394:                                             PetscRealPart(a->a[bs2*k + l*bs + j]),-PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
395:             } else {
396:               PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,PetscRealPart(a->a[bs2*k + l*bs + j]));
397:             }
398: #else
399:             PetscViewerASCIIPrintf(viewer," (%D, %G) ",bs*a->j[k]+l,a->a[bs2*k + l*bs + j]);
400: #endif
401:           }
402:         }
403:         PetscViewerASCIIPrintf(viewer,"\n");
404:       }
405:     }
406:     PetscViewerASCIIUseTabs(viewer,PETSC_YES);
407:   }
408:   PetscViewerFlush(viewer);
409:   return(0);
410: }

414: static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw,void *Aa)
415: {
416:   Mat            A = (Mat) Aa;
417:   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data;
419:   PetscInt       row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2;
420:   PetscMPIInt    rank;
421:   PetscReal      xl,yl,xr,yr,x_l,x_r,y_l,y_r;
422:   MatScalar      *aa;
423:   MPI_Comm       comm;
424:   PetscViewer    viewer;
425: 
427:   /*
428:     This is nasty. If this is called from an originally parallel matrix
429:     then all processes call this,but only the first has the matrix so the
430:     rest should return immediately.
431:   */
432:   PetscObjectGetComm((PetscObject)draw,&comm);
433:   MPI_Comm_rank(comm,&rank);
434:   if (rank) return(0);
435: 
436:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
437: 
438:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);
439:   PetscDrawString(draw, .3*(xl+xr), .3*(yl+yr), PETSC_DRAW_BLACK, "symmetric");
440: 
441:   /* loop over matrix elements drawing boxes */
442:   color = PETSC_DRAW_BLUE;
443:   for (i=0,row=0; i<mbs; i++,row+=bs) {
444:     for (j=a->i[i]; j<a->i[i+1]; j++) {
445:       y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
446:       x_l = a->j[j]*bs; x_r = x_l + 1.0;
447:       aa = a->a + j*bs2;
448:       for (k=0; k<bs; k++) {
449:         for (l=0; l<bs; l++) {
450:           if (PetscRealPart(*aa++) >=  0.) continue;
451:           PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
452:         }
453:       }
454:     }
455:   }
456:   color = PETSC_DRAW_CYAN;
457:   for (i=0,row=0; i<mbs; i++,row+=bs) {
458:     for (j=a->i[i]; j<a->i[i+1]; j++) {
459:       y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
460:       x_l = a->j[j]*bs; x_r = x_l + 1.0;
461:       aa = a->a + j*bs2;
462:       for (k=0; k<bs; k++) {
463:         for (l=0; l<bs; l++) {
464:           if (PetscRealPart(*aa++) != 0.) continue;
465:           PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
466:         }
467:       }
468:     }
469:   }
470: 
471:   color = PETSC_DRAW_RED;
472:   for (i=0,row=0; i<mbs; i++,row+=bs) {
473:     for (j=a->i[i]; j<a->i[i+1]; j++) {
474:       y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
475:       x_l = a->j[j]*bs; x_r = x_l + 1.0;
476:       aa = a->a + j*bs2;
477:       for (k=0; k<bs; k++) {
478:         for (l=0; l<bs; l++) {
479:           if (PetscRealPart(*aa++) <= 0.) continue;
480:           PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
481:         }
482:       }
483:     }
484:   }
485:   return(0);
486: }

490: static PetscErrorCode MatView_SeqSBAIJ_Draw(Mat A,PetscViewer viewer)
491: {
493:   PetscReal      xl,yl,xr,yr,w,h;
494:   PetscDraw      draw;
495:   PetscTruth     isnull;
496: 
498:   PetscViewerDrawGetDraw(viewer,0,&draw);
499:   PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
500: 
501:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
502:   xr  = A->rmap->N; yr = A->rmap->N; h = yr/10.0; w = xr/10.0;
503:   xr += w;    yr += h;  xl = -w;     yl = -h;
504:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
505:   PetscDrawZoom(draw,MatView_SeqSBAIJ_Draw_Zoom,A);
506:   PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);
507:   return(0);
508: }

512: PetscErrorCode MatView_SeqSBAIJ(Mat A,PetscViewer viewer)
513: {
515:   PetscTruth     iascii,isdraw;
516: 
518:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
519:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
520:   if (iascii){
521:     MatView_SeqSBAIJ_ASCII(A,viewer);
522:   } else if (isdraw) {
523:     MatView_SeqSBAIJ_Draw(A,viewer);
524:   } else {
525:     Mat B;
526:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);
527:     MatView(B,viewer);
528:     MatDestroy(B);
529:   }
530:   return(0);
531: }


536: PetscErrorCode MatGetValues_SeqSBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
537: {
538:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
539:   PetscInt     *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j;
540:   PetscInt     *ai = a->i,*ailen = a->ilen;
541:   PetscInt     brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2;
542:   MatScalar    *ap,*aa = a->a;
543: 
545:   for (k=0; k<m; k++) { /* loop over rows */
546:     row  = im[k]; brow = row/bs;
547:     if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */
548:     if (row >= A->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1);
549:     rp   = aj + ai[brow] ; ap = aa + bs2*ai[brow] ;
550:     nrow = ailen[brow];
551:     for (l=0; l<n; l++) { /* loop over columns */
552:       if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */
553:       if (in[l] >= A->cmap->n) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1);
554:       col  = in[l] ;
555:       bcol = col/bs;
556:       cidx = col%bs;
557:       ridx = row%bs;
558:       high = nrow;
559:       low  = 0; /* assume unsorted */
560:       while (high-low > 5) {
561:         t = (low+high)/2;
562:         if (rp[t] > bcol) high = t;
563:         else             low  = t;
564:       }
565:       for (i=low; i<high; i++) {
566:         if (rp[i] > bcol) break;
567:         if (rp[i] == bcol) {
568:           *v++ = ap[bs2*i+bs*cidx+ridx];
569:           goto finished;
570:         }
571:       }
572:       *v++ = 0.0;
573:       finished:;
574:     }
575:   }
576:   return(0);
577: }


582: PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
583: {
584:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
585:   PetscErrorCode    ierr;
586:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1;
587:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
588:   PetscInt          *aj=a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval;
589:   PetscTruth        roworiented=a->roworiented;
590:   const PetscScalar *value = v;
591:   MatScalar         *ap,*aa = a->a,*bap;
592: 
594:   if (roworiented) {
595:     stepval = (n-1)*bs;
596:   } else {
597:     stepval = (m-1)*bs;
598:   }
599:   for (k=0; k<m; k++) { /* loop over added rows */
600:     row  = im[k];
601:     if (row < 0) continue;
602: #if defined(PETSC_USE_DEBUG)  
603:     if (row >= a->mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,a->mbs-1);
604: #endif
605:     rp   = aj + ai[row];
606:     ap   = aa + bs2*ai[row];
607:     rmax = imax[row];
608:     nrow = ailen[row];
609:     low  = 0;
610:     high = nrow;
611:     for (l=0; l<n; l++) { /* loop over added columns */
612:       if (in[l] < 0) continue;
613:       col = in[l];
614: #if defined(PETSC_USE_DEBUG)  
615:       if (col >= a->nbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",col,a->nbs-1);
616: #endif
617:       if (col < row) continue; /* ignore lower triangular block */
618:       if (roworiented) {
619:         value = v + k*(stepval+bs)*bs + l*bs;
620:       } else {
621:         value = v + l*(stepval+bs)*bs + k*bs;
622:       }
623:       if (col <= lastcol) low = 0; else high = nrow;
624:       lastcol = col;
625:       while (high-low > 7) {
626:         t = (low+high)/2;
627:         if (rp[t] > col) high = t;
628:         else             low  = t;
629:       }
630:       for (i=low; i<high; i++) {
631:         if (rp[i] > col) break;
632:         if (rp[i] == col) {
633:           bap  = ap +  bs2*i;
634:           if (roworiented) {
635:             if (is == ADD_VALUES) {
636:               for (ii=0; ii<bs; ii++,value+=stepval) {
637:                 for (jj=ii; jj<bs2; jj+=bs) {
638:                   bap[jj] += *value++;
639:                 }
640:               }
641:             } else {
642:               for (ii=0; ii<bs; ii++,value+=stepval) {
643:                 for (jj=ii; jj<bs2; jj+=bs) {
644:                   bap[jj] = *value++;
645:                 }
646:                }
647:             }
648:           } else {
649:             if (is == ADD_VALUES) {
650:               for (ii=0; ii<bs; ii++,value+=stepval) {
651:                 for (jj=0; jj<bs; jj++) {
652:                   *bap++ += *value++;
653:                 }
654:               }
655:             } else {
656:               for (ii=0; ii<bs; ii++,value+=stepval) {
657:                 for (jj=0; jj<bs; jj++) {
658:                   *bap++  = *value++;
659:                 }
660:               }
661:             }
662:           }
663:           goto noinsert2;
664:         }
665:       }
666:       if (nonew == 1) goto noinsert2;
667:       if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
668:       MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
669:       N = nrow++ - 1; high++;
670:       /* shift up all the later entries in this row */
671:       for (ii=N; ii>=i; ii--) {
672:         rp[ii+1] = rp[ii];
673:         PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
674:       }
675:       if (N >= i) {
676:         PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
677:       }
678:       rp[i] = col;
679:       bap   = ap +  bs2*i;
680:       if (roworiented) {
681:         for (ii=0; ii<bs; ii++,value+=stepval) {
682:           for (jj=ii; jj<bs2; jj+=bs) {
683:             bap[jj] = *value++;
684:           }
685:         }
686:       } else {
687:         for (ii=0; ii<bs; ii++,value+=stepval) {
688:           for (jj=0; jj<bs; jj++) {
689:             *bap++  = *value++;
690:           }
691:         }
692:        }
693:     noinsert2:;
694:       low = i;
695:     }
696:     ailen[row] = nrow;
697:   }
698:    return(0);
699: }

703: PetscErrorCode MatAssemblyEnd_SeqSBAIJ(Mat A,MatAssemblyType mode)
704: {
705:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
707:   PetscInt       fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax;
708:   PetscInt       m = A->rmap->N,*ip,N,*ailen = a->ilen;
709:   PetscInt       mbs = a->mbs,bs2 = a->bs2,rmax = 0;
710:   MatScalar      *aa = a->a,*ap;
711: 
713:   if (mode == MAT_FLUSH_ASSEMBLY) return(0);
714: 
715:   if (m) rmax = ailen[0];
716:   for (i=1; i<mbs; i++) {
717:     /* move each row back by the amount of empty slots (fshift) before it*/
718:     fshift += imax[i-1] - ailen[i-1];
719:      rmax   = PetscMax(rmax,ailen[i]);
720:      if (fshift) {
721:        ip = aj + ai[i]; ap = aa + bs2*ai[i];
722:        N = ailen[i];
723:        for (j=0; j<N; j++) {
724:          ip[j-fshift] = ip[j];
725:          PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));
726:        }
727:      }
728:      ai[i] = ai[i-1] + ailen[i-1];
729:   }
730:   if (mbs) {
731:     fshift += imax[mbs-1] - ailen[mbs-1];
732:      ai[mbs] = ai[mbs-1] + ailen[mbs-1];
733:   }
734:   /* reset ilen and imax for each row */
735:   for (i=0; i<mbs; i++) {
736:     ailen[i] = imax[i] = ai[i+1] - ai[i];
737:   }
738:   a->nz = ai[mbs];
739: 
740:   /* diagonals may have moved, reset it */
741:   if (a->diag) {
742:     PetscMemcpy(a->diag,ai,(mbs+1)*sizeof(PetscInt));
743:   }
744:   if (fshift && a->nounused == -1) {
745:     SETERRQ4(PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D block size %D, %D unneeded", m, A->cmap->n, A->rmap->bs, fshift*bs2);
746:   }
747:   PetscInfo5(A,"Matrix size: %D X %D, block size %D; storage space: %D unneeded, %D used\n",m,A->rmap->N,A->rmap->bs,fshift*bs2,a->nz*bs2);
748:   PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);
749:   PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);
750:   a->reallocs          = 0;
751:   A->info.nz_unneeded  = (PetscReal)fshift*bs2;
752:   return(0);
753: }

755: /* 
756:    This function returns an array of flags which indicate the locations of contiguous
757:    blocks that should be zeroed. for eg: if bs = 3  and is = [0,1,2,3,5,6,7,8,9]
758:    then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)]
759:    Assume: sizes should be long enough to hold all the values.
760: */
763: PetscErrorCode MatZeroRows_SeqSBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max)
764: {
765:   PetscInt   i,j,k,row;
766:   PetscTruth flg;
767: 
769:    for (i=0,j=0; i<n; j++) {
770:      row = idx[i];
771:      if (row%bs!=0) { /* Not the begining of a block */
772:        sizes[j] = 1;
773:        i++;
774:      } else if (i+bs > n) { /* Beginning of a block, but complete block doesn't exist (at idx end) */
775:        sizes[j] = 1;         /* Also makes sure atleast 'bs' values exist for next else */
776:        i++;
777:      } else { /* Begining of the block, so check if the complete block exists */
778:        flg = PETSC_TRUE;
779:        for (k=1; k<bs; k++) {
780:          if (row+k != idx[i+k]) { /* break in the block */
781:            flg = PETSC_FALSE;
782:            break;
783:          }
784:        }
785:        if (flg) { /* No break in the bs */
786:          sizes[j] = bs;
787:          i+= bs;
788:        } else {
789:          sizes[j] = 1;
790:          i++;
791:        }
792:      }
793:    }
794:    *bs_max = j;
795:    return(0);
796: }


799: /* Only add/insert a(i,j) with i<=j (blocks). 
800:    Any a(i,j) with i>j input by user is ingored. 
801: */

805: PetscErrorCode MatSetValues_SeqSBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
806: {
807:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
809:   PetscInt       *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
810:   PetscInt       *imax=a->imax,*ai=a->i,*ailen=a->ilen,roworiented=a->roworiented;
811:   PetscInt       *aj=a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
812:   PetscInt       ridx,cidx,bs2=a->bs2;
813:   MatScalar      *ap,value,*aa=a->a,*bap;
814: 
816:   for (k=0; k<m; k++) { /* loop over added rows */
817:     row  = im[k];       /* row number */
818:     brow = row/bs;      /* block row number */
819:     if (row < 0) continue;
820: #if defined(PETSC_USE_DEBUG)  
821:     if (row >= A->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1);
822: #endif
823:     rp   = aj + ai[brow]; /*ptr to beginning of column value of the row block*/
824:     ap   = aa + bs2*ai[brow]; /*ptr to beginning of element value of the row block*/
825:     rmax = imax[brow];  /* maximum space allocated for this row */
826:     nrow = ailen[brow]; /* actual length of this row */
827:     low  = 0;
828: 
829:     for (l=0; l<n; l++) { /* loop over added columns */
830:       if (in[l] < 0) continue;
831: #if defined(PETSC_USE_DEBUG)  
832:       if (in[l] >= A->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->rmap->N-1);
833: #endif
834:       col = in[l];
835:       bcol = col/bs;              /* block col number */
836: 
837:       if (brow > bcol) {
838:         if (a->ignore_ltriangular){
839:           continue; /* ignore lower triangular values */
840:         } else {
841:           SETERRQ(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)");
842:         }
843:       }
844: 
845:       ridx = row % bs; cidx = col % bs; /*row and col index inside the block */
846:       if ((brow==bcol && ridx<=cidx) || (brow<bcol)){
847:         /* element value a(k,l) */
848:         if (roworiented) {
849:           value = v[l + k*n];
850:         } else {
851:           value = v[k + l*m];
852:         }
853: 
854:         /* move pointer bap to a(k,l) quickly and add/insert value */
855:         if (col <= lastcol) low = 0; high = nrow;
856:         lastcol = col;
857:         while (high-low > 7) {
858:           t = (low+high)/2;
859:           if (rp[t] > bcol) high = t;
860:           else              low  = t;
861:         }
862:         for (i=low; i<high; i++) {
863:           if (rp[i] > bcol) break;
864:           if (rp[i] == bcol) {
865:             bap  = ap +  bs2*i + bs*cidx + ridx;
866:             if (is == ADD_VALUES) *bap += value;
867:             else                  *bap  = value;
868:             /* for diag block, add/insert its symmetric element a(cidx,ridx) */
869:             if (brow == bcol && ridx < cidx){
870:               bap  = ap +  bs2*i + bs*ridx + cidx;
871:               if (is == ADD_VALUES) *bap += value;
872:               else                  *bap  = value;
873:             }
874:             goto noinsert1;
875:           }
876:         }
877: 
878:         if (nonew == 1) goto noinsert1;
879:         if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
880:         MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
881: 
882:         N = nrow++ - 1; high++;
883:         /* shift up all the later entries in this row */
884:         for (ii=N; ii>=i; ii--) {
885:           rp[ii+1] = rp[ii];
886:           PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
887:         }
888:         if (N>=i) {
889:           PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
890:         }
891:         rp[i]                      = bcol;
892:         ap[bs2*i + bs*cidx + ridx] = value;
893:       noinsert1:;
894:         low = i;
895:       }
896:     }   /* end of loop over added columns */
897:     ailen[brow] = nrow;
898:   }   /* end of loop over added rows */
899:   return(0);
900: }

904: PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA,IS row,const MatFactorInfo *info)
905: {
906:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inA->data;
907:   Mat            outA;
909:   PetscTruth     row_identity;
910: 
912:   if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels=0 is supported for in-place icc");
913:   ISIdentity(row,&row_identity);
914:   if (!row_identity) SETERRQ(PETSC_ERR_SUP,"Matrix reordering is not supported");
915:   if (inA->rmap->bs != 1) SETERRQ1(PETSC_ERR_SUP,"Matrix block size %D is not supported",inA->rmap->bs); /* Need to replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR()! */

917:   outA        = inA;
918:   inA->factor = MAT_FACTOR_ICC;
919: 
920:   MatMarkDiagonal_SeqSBAIJ(inA);
921:   MatSeqSBAIJSetNumericFactorization(inA,row_identity);

923:   PetscObjectReference((PetscObject)row);
924:   if (a->row) { ISDestroy(a->row); }
925:   a->row = row;
926:   PetscObjectReference((PetscObject)row);
927:   if (a->col) { ISDestroy(a->col); }
928:   a->col = row;
929: 
930:   /* Create the invert permutation so that it can be used in MatCholeskyFactorNumeric() */
931:   if (a->icol) {ISInvertPermutation(row,PETSC_DECIDE, &a->icol);}
932:   PetscLogObjectParent(inA,a->icol);
933: 
934:   if (!a->solve_work) {
935:     PetscMalloc((inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar),&a->solve_work);
936:     PetscLogObjectMemory(inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));
937:   }
938: 
939:   MatCholeskyFactorNumeric(outA,inA,info);
940:   return(0);
941: }

946: PetscErrorCode  MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat,PetscInt *indices)
947: {
948:   Mat_SeqSBAIJ *baij = (Mat_SeqSBAIJ *)mat->data;
949:   PetscInt     i,nz,n;
950: 
952:   nz = baij->maxnz;
953:   n  = mat->cmap->n;
954:   for (i=0; i<nz; i++) {
955:     baij->j[i] = indices[i];
956:   }
957:    baij->nz = nz;
958:    for (i=0; i<n; i++) {
959:      baij->ilen[i] = baij->imax[i];
960:    }
961:    return(0);
962: }

967: /*@
968:   MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows
969:   in the matrix.
970:   
971:   Input Parameters:
972:   +  mat     - the SeqSBAIJ matrix
973:   -  indices - the column indices
974:   
975:   Level: advanced
976:   
977:   Notes:
978:   This can be called if you have precomputed the nonzero structure of the 
979:   matrix and want to provide it to the matrix object to improve the performance
980:   of the MatSetValues() operation.
981:   
982:   You MUST have set the correct numbers of nonzeros per row in the call to 
983:   MatCreateSeqSBAIJ(), and the columns indices MUST be sorted.
984:   
985:   MUST be called before any calls to MatSetValues()
986:   
987:   .seealso: MatCreateSeqSBAIJ
988: @*/
989: PetscErrorCode  MatSeqSBAIJSetColumnIndices(Mat mat,PetscInt *indices)
990: {
991:   PetscErrorCode ierr,(*f)(Mat,PetscInt *);
992: 
996:   PetscObjectQueryFunction((PetscObject)mat,"MatSeqSBAIJSetColumnIndices_C",(void (**)(void))&f);
997:   if (f) {
998:     (*f)(mat,indices);
999:   } else {
1000:     SETERRQ(PETSC_ERR_SUP,"Wrong type of matrix to set column indices");
1001:   }
1002:   return(0);
1003: }

1007: PetscErrorCode MatCopy_SeqSBAIJ(Mat A,Mat B,MatStructure str)
1008: {

1012:   /* If the two matrices have the same copy implementation, use fast copy. */
1013:   if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) {
1014:     Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
1015:     Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ*)B->data;

1017:     if (a->i[A->rmap->N] != b->i[B->rmap->N]) {
1018:       SETERRQ(PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different");
1019:     }
1020:     PetscMemcpy(b->a,a->a,(a->i[A->rmap->N])*sizeof(PetscScalar));
1021:   } else {
1022:     MatGetRowUpperTriangular(A);
1023:     MatCopy_Basic(A,B,str);
1024:     MatRestoreRowUpperTriangular(A);
1025:   }
1026:   return(0);
1027: }

1031: PetscErrorCode MatSetUpPreallocation_SeqSBAIJ(Mat A)
1032: {
1034: 
1036:    MatSeqSBAIJSetPreallocation_SeqSBAIJ(A,-PetscMax(A->rmap->bs,1),PETSC_DEFAULT,0);
1037:   return(0);
1038: }

1042: PetscErrorCode MatGetArray_SeqSBAIJ(Mat A,PetscScalar *array[])
1043: {
1044:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
1046:   *array = a->a;
1047:   return(0);
1048: }

1052: PetscErrorCode MatRestoreArray_SeqSBAIJ(Mat A,PetscScalar *array[])
1053: {
1055:   return(0);
1056:  }

1058:  #include petscblaslapack.h
1061: PetscErrorCode MatAXPY_SeqSBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1062: {
1063:   Mat_SeqSBAIJ   *x=(Mat_SeqSBAIJ *)X->data, *y=(Mat_SeqSBAIJ *)Y->data;
1065:   PetscInt       i,bs=Y->rmap->bs,bs2,j;
1066:   PetscBLASInt   one = 1,bnz = PetscBLASIntCast(x->nz);
1067: 
1069:   if (str == SAME_NONZERO_PATTERN) {
1070:     PetscScalar alpha = a;
1071:     BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one);
1072:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1073:     if (y->xtoy && y->XtoY != X) {
1074:       PetscFree(y->xtoy);
1075:       MatDestroy(y->XtoY);
1076:     }
1077:     if (!y->xtoy) { /* get xtoy */
1078:       MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);
1079:       y->XtoY = X;
1080:     }
1081:     bs2 = bs*bs;
1082:     for (i=0; i<x->nz; i++) {
1083:       j = 0;
1084:       while (j < bs2){
1085:         y->a[bs2*y->xtoy[i]+j] += a*(x->a[bs2*i+j]);
1086:         j++;
1087:       }
1088:     }
1089:     PetscInfo3(Y,"ratio of nnz_s(X)/nnz_s(Y): %D/%D = %G\n",bs2*x->nz,bs2*y->nz,(PetscReal)(bs2*x->nz)/(bs2*y->nz));
1090:   } else {
1091:     MatGetRowUpperTriangular(X);
1092:     MatAXPY_Basic(Y,a,X,str);
1093:     MatRestoreRowUpperTriangular(X);
1094:   }
1095:   return(0);
1096: }

1100: PetscErrorCode MatIsSymmetric_SeqSBAIJ(Mat A,PetscReal tol,PetscTruth *flg)
1101: {
1103:   *flg = PETSC_TRUE;
1104:   return(0);
1105: }

1109: PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A,PetscTruth *flg)
1110: {
1112:    *flg = PETSC_TRUE;
1113:    return(0);
1114: }

1118: PetscErrorCode MatIsHermitian_SeqSBAIJ(Mat A,PetscReal tol,PetscTruth *flg)
1119:  {
1121:    *flg = PETSC_FALSE;
1122:    return(0);
1123:  }

1127: PetscErrorCode MatRealPart_SeqSBAIJ(Mat A)
1128: {
1129:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
1130:   PetscInt       i,nz = a->bs2*a->i[a->mbs];
1131:   MatScalar      *aa = a->a;

1134:   for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
1135:   return(0);
1136: }

1140: PetscErrorCode MatImaginaryPart_SeqSBAIJ(Mat A)
1141: {
1142:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
1143:   PetscInt       i,nz = a->bs2*a->i[a->mbs];
1144:   MatScalar      *aa = a->a;

1147:   for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
1148:   return(0);
1149: }

1151: /* -------------------------------------------------------------------*/
1152: static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ,
1153:        MatGetRow_SeqSBAIJ,
1154:        MatRestoreRow_SeqSBAIJ,
1155:        MatMult_SeqSBAIJ_N,
1156: /* 4*/ MatMultAdd_SeqSBAIJ_N,
1157:        MatMult_SeqSBAIJ_N,       /* transpose versions are same as non-transpose versions */
1158:        MatMultAdd_SeqSBAIJ_N,
1159:        0,
1160:        0,
1161:        0,
1162: /*10*/ 0,
1163:        0,
1164:        MatCholeskyFactor_SeqSBAIJ,
1165:        MatRelax_SeqSBAIJ,
1166:        MatTranspose_SeqSBAIJ,
1167: /*15*/ MatGetInfo_SeqSBAIJ,
1168:        MatEqual_SeqSBAIJ,
1169:        MatGetDiagonal_SeqSBAIJ,
1170:        MatDiagonalScale_SeqSBAIJ,
1171:        MatNorm_SeqSBAIJ,
1172: /*20*/ 0,
1173:        MatAssemblyEnd_SeqSBAIJ,
1174:        0,
1175:        MatSetOption_SeqSBAIJ,
1176:        MatZeroEntries_SeqSBAIJ,
1177: /*25*/ 0,
1178:        0,
1179:        0,
1180:        0,
1181:        0,
1182: /*30*/ MatSetUpPreallocation_SeqSBAIJ,
1183:        0,
1184:        0,
1185:        MatGetArray_SeqSBAIJ,
1186:        MatRestoreArray_SeqSBAIJ,
1187: /*35*/ MatDuplicate_SeqSBAIJ,
1188:        0,
1189:        0,
1190:        0,
1191:        MatICCFactor_SeqSBAIJ,
1192: /*40*/ MatAXPY_SeqSBAIJ,
1193:        MatGetSubMatrices_SeqSBAIJ,
1194:        MatIncreaseOverlap_SeqSBAIJ,
1195:        MatGetValues_SeqSBAIJ,
1196:        MatCopy_SeqSBAIJ,
1197: /*45*/ 0,
1198:        MatScale_SeqSBAIJ,
1199:        0,
1200:        0,
1201:        0,
1202: /*50*/ 0,
1203:        MatGetRowIJ_SeqSBAIJ,
1204:        MatRestoreRowIJ_SeqSBAIJ,
1205:        0,
1206:        0,
1207: /*55*/ 0,
1208:        0,
1209:        0,
1210:        0,
1211:        MatSetValuesBlocked_SeqSBAIJ,
1212: /*60*/ MatGetSubMatrix_SeqSBAIJ,
1213:        0,
1214:        0,
1215:        0,
1216:        0,
1217: /*65*/ 0,
1218:        0,
1219:        0,
1220:        0,
1221:        0,
1222: /*70*/ MatGetRowMaxAbs_SeqSBAIJ,
1223:        0,
1224:        0,
1225:        0,
1226:        0,
1227: /*75*/ 0,
1228:        0,
1229:        0,
1230:        0,
1231:        0,
1232: /*80*/ 0,
1233:        0,
1234:        0,
1235: #if !defined(PETSC_USE_COMPLEX)
1236:        MatGetInertia_SeqSBAIJ,
1237: #else
1238:        0,
1239: #endif
1240:        MatLoad_SeqSBAIJ,
1241: /*85*/ MatIsSymmetric_SeqSBAIJ,
1242:        MatIsHermitian_SeqSBAIJ,
1243:        MatIsStructurallySymmetric_SeqSBAIJ,
1244:        0,
1245:        0,
1246: /*90*/ 0,
1247:        0,
1248:        0,
1249:        0,
1250:        0,
1251: /*95*/ 0,
1252:        0,
1253:        0,
1254:        0,
1255:        0,
1256: /*100*/0,
1257:        0,
1258:        0,
1259:        0,
1260:        0,
1261: /*105*/0,
1262:        MatRealPart_SeqSBAIJ,
1263:        MatImaginaryPart_SeqSBAIJ,
1264:        MatGetRowUpperTriangular_SeqSBAIJ,
1265:        MatRestoreRowUpperTriangular_SeqSBAIJ,
1266: /*110*/0,
1267:        0,
1268:        0,
1269:        0,
1270:        MatMissingDiagonal_SeqSBAIJ
1271: };

1276: PetscErrorCode  MatStoreValues_SeqSBAIJ(Mat mat)
1277: {
1278:   Mat_SeqSBAIJ   *aij = (Mat_SeqSBAIJ *)mat->data;
1279:   PetscInt       nz = aij->i[mat->rmap->N]*mat->rmap->bs*aij->bs2;
1281: 
1283:   if (aij->nonew != 1) {
1284:     SETERRQ(PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1285:   }
1286: 
1287:   /* allocate space for values if not already there */
1288:   if (!aij->saved_values) {
1289:     PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);
1290:   }
1291: 
1292:   /* copy values over */
1293:   PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));
1294:   return(0);
1295: }

1301: PetscErrorCode  MatRetrieveValues_SeqSBAIJ(Mat mat)
1302: {
1303:   Mat_SeqSBAIJ   *aij = (Mat_SeqSBAIJ *)mat->data;
1305:   PetscInt       nz = aij->i[mat->rmap->N]*mat->rmap->bs*aij->bs2;
1306: 
1308:   if (aij->nonew != 1) {
1309:     SETERRQ(PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
1310:   }
1311:   if (!aij->saved_values) {
1312:     SETERRQ(PETSC_ERR_ORDER,"Must call MatStoreValues(A);first");
1313:   }
1314: 
1315:   /* copy values over */
1316:   PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));
1317:   return(0);
1318: }

1324: PetscErrorCode  MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz)
1325: {
1326:   Mat_SeqSBAIJ   *b = (Mat_SeqSBAIJ*)B->data;
1328:   PetscInt       i,mbs,bs2, newbs = PetscAbs(bs);
1329:   PetscTruth     skipallocation = PETSC_FALSE,flg;
1330: 
1332:   B->preallocated = PETSC_TRUE;
1333:   if (bs < 0) {
1334:     PetscOptionsBegin(((PetscObject)B)->comm,((PetscObject)B)->prefix,"Options for MPISBAIJ matrix","Mat");
1335:       PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatSeqSBAIJSetPreallocation",newbs,&newbs,PETSC_NULL);
1336:     PetscOptionsEnd();
1337:     bs   = PetscAbs(bs);
1338:   }
1339:   if (nnz && newbs != bs) {
1340:     SETERRQ(PETSC_ERR_ARG_WRONG,"Cannot change blocksize from command line if setting nnz");
1341:   }
1342:   bs = newbs;

1344:   PetscMapSetBlockSize(B->rmap,bs);
1345:   PetscMapSetBlockSize(B->cmap,bs);
1346:   PetscMapSetUp(B->rmap);
1347:   PetscMapSetUp(B->cmap);

1349:   mbs  = B->rmap->N/bs;
1350:   bs2  = bs*bs;
1351: 
1352:   if (mbs*bs != B->rmap->N) {
1353:     SETERRQ(PETSC_ERR_ARG_SIZ,"Number rows, cols must be divisible by blocksize");
1354:   }
1355: 
1356:   if (nz == MAT_SKIP_ALLOCATION) {
1357:     skipallocation = PETSC_TRUE;
1358:     nz             = 0;
1359:   }

1361:   if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3;
1362:   if (nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz);
1363:   if (nnz) {
1364:     for (i=0; i<mbs; i++) {
1365:       if (nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]);
1366:       if (nnz[i] > mbs) SETERRQ3(PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %D value %D rowlength %D",i,nnz[i],mbs);
1367:     }
1368:   }
1369: 
1370:   B->ops->mult             = MatMult_SeqSBAIJ_N;
1371:   B->ops->multadd          = MatMultAdd_SeqSBAIJ_N;
1372:   B->ops->multtranspose    = MatMult_SeqSBAIJ_N;
1373:   B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_N;
1374:   PetscOptionsHasName(((PetscObject)B)->prefix,"-mat_no_unroll",&flg);
1375:   if (!flg) {
1376:     switch (bs) {
1377:     case 1:
1378:       B->ops->mult             = MatMult_SeqSBAIJ_1;
1379:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_1;
1380:       B->ops->multtranspose    = MatMult_SeqSBAIJ_1;
1381:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_1;
1382:       break;
1383:     case 2:
1384:       B->ops->mult             = MatMult_SeqSBAIJ_2;
1385:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_2;
1386:       B->ops->multtranspose    = MatMult_SeqSBAIJ_2;
1387:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_2;
1388:       break;
1389:     case 3:
1390:       B->ops->mult             = MatMult_SeqSBAIJ_3;
1391:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_3;
1392:       B->ops->multtranspose    = MatMult_SeqSBAIJ_3;
1393:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_3;
1394:       break;
1395:     case 4:
1396:       B->ops->mult             = MatMult_SeqSBAIJ_4;
1397:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_4;
1398:       B->ops->multtranspose    = MatMult_SeqSBAIJ_4;
1399:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_4;
1400:       break;
1401:     case 5:
1402:       B->ops->mult             = MatMult_SeqSBAIJ_5;
1403:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_5;
1404:       B->ops->multtranspose    = MatMult_SeqSBAIJ_5;
1405:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_5;
1406:       break;
1407:     case 6:
1408:       B->ops->mult             = MatMult_SeqSBAIJ_6;
1409:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_6;
1410:       B->ops->multtranspose    = MatMult_SeqSBAIJ_6;
1411:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_6;
1412:       break;
1413:     case 7:
1414:       B->ops->mult             = MatMult_SeqSBAIJ_7;
1415:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_7;
1416:       B->ops->multtranspose    = MatMult_SeqSBAIJ_7;
1417:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_7;
1418:       break;
1419:     }
1420:   }
1421: 
1422:   b->mbs = mbs;
1423:   b->nbs = mbs;
1424:   if (!skipallocation) {
1425:     if (!b->imax) {
1426:       PetscMalloc2(mbs,PetscInt,&b->imax,mbs,PetscInt,&b->ilen);
1427:       PetscLogObjectMemory(B,2*mbs*sizeof(PetscInt));
1428:     }
1429:     if (!nnz) {
1430:       if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
1431:       else if (nz <= 0)        nz = 1;
1432:       for (i=0; i<mbs; i++) {
1433:         b->imax[i] = nz;
1434:       }
1435:       nz = nz*mbs; /* total nz */
1436:     } else {
1437:       nz = 0;
1438:       for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];}
1439:     }
1440:     /* b->ilen will count nonzeros in each block row so far. */
1441:     for (i=0; i<mbs; i++) { b->ilen[i] = 0;}
1442:     /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */
1443: 
1444:     /* allocate the matrix space */
1445:     MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);
1446:     PetscMalloc3(bs2*nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->N+1,PetscInt,&b->i);
1447:     PetscLogObjectMemory(B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));
1448:     PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));
1449:     PetscMemzero(b->j,nz*sizeof(PetscInt));
1450:     b->singlemalloc = PETSC_TRUE;
1451: 
1452:     /* pointer to beginning of each row */
1453:     b->i[0] = 0;
1454:     for (i=1; i<mbs+1; i++) {
1455:       b->i[i] = b->i[i-1] + b->imax[i-1];
1456:     }
1457:     b->free_a     = PETSC_TRUE;
1458:     b->free_ij    = PETSC_TRUE;
1459:   } else {
1460:     b->free_a     = PETSC_FALSE;
1461:     b->free_ij    = PETSC_FALSE;
1462:   }
1463: 
1464:   B->rmap->bs               = bs;
1465:   b->bs2              = bs2;
1466:   b->nz             = 0;
1467:   b->maxnz          = nz*bs2;
1468: 
1469:   b->inew             = 0;
1470:   b->jnew             = 0;
1471:   b->anew             = 0;
1472:   b->a2anew           = 0;
1473:   b->permute          = PETSC_FALSE;
1474:   return(0);
1475: }

1480: /*
1481:    This is used to set the numeric factorization for both Cholesky and ICC symbolic factorization
1482: */
1483: PetscErrorCode MatSeqSBAIJSetNumericFactorization(Mat B,PetscTruth natural)
1484: {
1486:   PetscTruth     flg;
1487:   PetscInt       bs = B->rmap->bs;

1490:   PetscOptionsHasName(((PetscObject)B)->prefix,"-mat_no_unroll",&flg);
1491:   if (flg) bs = 8;

1493:   if (!natural) {
1494:     switch (bs) {
1495:     case 1:
1496:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1;
1497:       break;
1498:     case 2:
1499:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2;
1500:       break;
1501:     case 3:
1502:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3;
1503:       break;
1504:     case 4:
1505:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4;
1506:       break;
1507:     case 5:
1508:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5;
1509:       break;
1510:     case 6:
1511:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6;
1512:       break;
1513:     case 7:
1514:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7;
1515:       break;
1516:     default:
1517:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N;
1518:       break;
1519:     }
1520:   } else {
1521:     switch (bs) {
1522:     case 1:
1523:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering;
1524:       break;
1525:     case 2:
1526:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
1527:       break;
1528:     case 3:
1529:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
1530:       break;
1531:     case 4:
1532:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
1533:       break;
1534:     case 5:
1535:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
1536:       break;
1537:     case 6:
1538:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
1539:       break;
1540:     case 7:
1541:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
1542:       break;
1543:     default:
1544:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
1545:       break;
1546:     }
1547:   }
1548:   return(0);
1549: }

1552: EXTERN PetscErrorCode  MatConvert_SeqSBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*);
1553: EXTERN PetscErrorCode  MatConvert_SeqSBAIJ_SeqBAIJ(Mat, MatType,MatReuse,Mat*);

1556: 
1560: PetscErrorCode MatGetFactor_seqsbaij_petsc(Mat A,MatFactorType ftype,Mat *B)
1561: {
1562:   PetscInt           n = A->rmap->n;
1563:   PetscErrorCode     ierr;

1566:   MatCreate(((PetscObject)A)->comm,B);
1567:   MatSetSizes(*B,n,n,n,n);
1568:   if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
1569:     MatSetType(*B,MATSEQSBAIJ);
1570:     MatSeqSBAIJSetPreallocation(*B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);
1571:     (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ;
1572:     (*B)->ops->iccfactorsymbolic      = MatICCFactorSymbolic_SeqSBAIJ;
1573:   } else SETERRQ(PETSC_ERR_SUP,"Factor type not supported");
1574:   (*B)->factor = ftype;
1575:   return(0);
1576: }

1582: PetscErrorCode MatGetFactorAvailable_seqsbaij_petsc(Mat A,MatFactorType ftype,PetscTruth *flg)
1583: {
1585:   if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
1586:     *flg = PETSC_TRUE;
1587:   } else {
1588:     *flg = PETSC_FALSE;
1589:   }
1590:   return(0);
1591: }

1595: #if defined(PETSC_HAVE_MUMPS)
1597: #endif
1598: #if defined(PETSC_HAVE_SPOOLES)
1600: #endif
1601: #if defined(PETSC_HAVE_PASTIX)
1603: #endif

1606: /*MC
1607:   MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices, 
1608:   based on block compressed sparse row format.  Only the upper triangular portion of the matrix is stored.
1609:   
1610:   Options Database Keys:
1611:   . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to MatSetFromOptions()
1612:   
1613:   Level: beginner
1614:   
1615:   .seealso: MatCreateSeqSBAIJ
1616: M*/

1621: PetscErrorCode  MatCreate_SeqSBAIJ(Mat B)
1622: {
1623:   Mat_SeqSBAIJ   *b;
1625:   PetscMPIInt    size;
1626:   PetscTruth     flg;
1627: 
1629:   MPI_Comm_size(((PetscObject)B)->comm,&size);
1630:   if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"Comm must be of size 1");
1631: 
1632:   PetscNewLog(B,Mat_SeqSBAIJ,&b);
1633:   B->data = (void*)b;
1634:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
1635:   B->ops->destroy     = MatDestroy_SeqSBAIJ;
1636:   B->ops->view        = MatView_SeqSBAIJ;
1637:   B->mapping          = 0;
1638:   b->row              = 0;
1639:   b->icol             = 0;
1640:   b->reallocs         = 0;
1641:   b->saved_values     = 0;
1642: 
1643: 
1644:   b->roworiented      = PETSC_TRUE;
1645:   b->nonew            = 0;
1646:   b->diag             = 0;
1647:   b->solve_work       = 0;
1648:   b->mult_work        = 0;
1649:   B->spptr            = 0;
1650:   b->keepzeroedrows   = PETSC_FALSE;
1651:   b->xtoy             = 0;
1652:   b->XtoY             = 0;
1653: 
1654:   b->inew             = 0;
1655:   b->jnew             = 0;
1656:   b->anew             = 0;
1657:   b->a2anew           = 0;
1658:   b->permute          = PETSC_FALSE;

1660:   b->ignore_ltriangular = PETSC_FALSE;
1661:   PetscOptionsHasName(((PetscObject)B)->prefix,"-mat_ignore_lower_triangular",&flg);
1662:   if (flg) b->ignore_ltriangular = PETSC_TRUE;

1664:   b->getrow_utriangular = PETSC_FALSE;
1665:   PetscOptionsHasName(((PetscObject)B)->prefix,"-mat_getrow_uppertriangular",&flg);
1666:   if (flg) b->getrow_utriangular = PETSC_TRUE;

1668: #if defined(PETSC_HAVE_PASTIX)
1669:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_seqsbaij_pastix_C",
1670:                                            "MatGetFactor_seqsbaij_pastix",
1671:                                            MatGetFactor_seqsbaij_pastix);
1672: #endif
1673: #if defined(PETSC_HAVE_SPOOLES)
1674:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_seqsbaij_spooles_C",
1675:                                      "MatGetFactor_seqsbaij_spooles",
1676:                                      MatGetFactor_seqsbaij_spooles);
1677: #endif
1678: #if defined(PETSC_HAVE_MUMPS)
1679:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_seqsbaij_mumps_C",
1680:                                      "MatGetFactor_seqsbaij_mumps",
1681:                                      MatGetFactor_seqsbaij_mumps);
1682: #endif
1683:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactorAvailable_seqsbaij_petsc_C",
1684:                                      "MatGetFactorAvailable_seqsbaij_petsc",
1685:                                      MatGetFactorAvailable_seqsbaij_petsc);
1686:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_seqsbaij_petsc_C",
1687:                                      "MatGetFactor_seqsbaij_petsc",
1688:                                      MatGetFactor_seqsbaij_petsc);
1689:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C",
1690:                                      "MatStoreValues_SeqSBAIJ",
1691:                                      MatStoreValues_SeqSBAIJ);
1692:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C",
1693:                                      "MatRetrieveValues_SeqSBAIJ",
1694:                                      (void*)MatRetrieveValues_SeqSBAIJ);
1695:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqSBAIJSetColumnIndices_C",
1696:                                      "MatSeqSBAIJSetColumnIndices_SeqSBAIJ",
1697:                                      MatSeqSBAIJSetColumnIndices_SeqSBAIJ);
1698:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqsbaij_seqaij_C",
1699:                                      "MatConvert_SeqSBAIJ_SeqAIJ",
1700:                                       MatConvert_SeqSBAIJ_SeqAIJ);
1701:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqsbaij_seqbaij_C",
1702:                                      "MatConvert_SeqSBAIJ_SeqBAIJ",
1703:                                       MatConvert_SeqSBAIJ_SeqBAIJ);
1704:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqSBAIJSetPreallocation_C",
1705:                                      "MatSeqSBAIJSetPreallocation_SeqSBAIJ",
1706:                                      MatSeqSBAIJSetPreallocation_SeqSBAIJ);

1708:   B->symmetric                  = PETSC_TRUE;
1709:   B->structurally_symmetric     = PETSC_TRUE;
1710:   B->symmetric_set              = PETSC_TRUE;
1711:   B->structurally_symmetric_set = PETSC_TRUE;
1712:   PetscObjectChangeTypeName((PetscObject)B,MATSEQSBAIJ);
1713:   return(0);
1714: }

1719: /*@C
1720:    MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block
1721:    compressed row) format.  For good matrix assembly performance the
1722:    user should preallocate the matrix storage by setting the parameter nz
1723:    (or the array nnz).  By setting these parameters accurately, performance
1724:    during matrix assembly can be increased by more than a factor of 50.

1726:    Collective on Mat

1728:    Input Parameters:
1729: +  A - the symmetric matrix 
1730: .  bs - size of block
1731: .  nz - number of block nonzeros per block row (same for all rows)
1732: -  nnz - array containing the number of block nonzeros in the upper triangular plus
1733:          diagonal portion of each block (possibly different for each block row) or PETSC_NULL

1735:    Options Database Keys:
1736: .   -mat_no_unroll - uses code that does not unroll the loops in the 
1737:                      block calculations (much slower)
1738: .    -mat_block_size - size of the blocks to use (only works if a negative bs is passed in

1740:    Level: intermediate

1742:    Notes:
1743:    Specify the preallocated storage with either nz or nnz (not both).
1744:    Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 
1745:    allocation.  For additional details, see the users manual chapter on
1746:    matrices.

1748:    You can call MatGetInfo() to get information on how effective the preallocation was;
1749:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1750:    You can also run with the option -info and look for messages with the string 
1751:    malloc in them to see if additional memory allocation was needed.

1753:    If the nnz parameter is given then the nz parameter is ignored


1756: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPISBAIJ()
1757: @*/
1758: PetscErrorCode  MatSeqSBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
1759: {
1760:   PetscErrorCode ierr,(*f)(Mat,PetscInt,PetscInt,const PetscInt[]);

1763:   PetscObjectQueryFunction((PetscObject)B,"MatSeqSBAIJSetPreallocation_C",(void (**)(void))&f);
1764:   if (f) {
1765:     (*f)(B,bs,nz,nnz);
1766:   }
1767:   return(0);
1768: }

1772: /*@C
1773:    MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in block AIJ (block
1774:    compressed row) format.  For good matrix assembly performance the
1775:    user should preallocate the matrix storage by setting the parameter nz
1776:    (or the array nnz).  By setting these parameters accurately, performance
1777:    during matrix assembly can be increased by more than a factor of 50.

1779:    Collective on MPI_Comm

1781:    Input Parameters:
1782: +  comm - MPI communicator, set to PETSC_COMM_SELF
1783: .  bs - size of block
1784: .  m - number of rows, or number of columns
1785: .  nz - number of block nonzeros per block row (same for all rows)
1786: -  nnz - array containing the number of block nonzeros in the upper triangular plus
1787:          diagonal portion of each block (possibly different for each block row) or PETSC_NULL

1789:    Output Parameter:
1790: .  A - the symmetric matrix 

1792:    Options Database Keys:
1793: .   -mat_no_unroll - uses code that does not unroll the loops in the 
1794:                      block calculations (much slower)
1795: .    -mat_block_size - size of the blocks to use

1797:    Level: intermediate

1799:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
1800:    MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely
1801:    true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles.
1802:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

1804:    Notes:
1805:    The number of rows and columns must be divisible by blocksize.
1806:    This matrix type does not support complex Hermitian operation.

1808:    Specify the preallocated storage with either nz or nnz (not both).
1809:    Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 
1810:    allocation.  For additional details, see the users manual chapter on
1811:    matrices.

1813:    If the nnz parameter is given then the nz parameter is ignored

1815: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPISBAIJ()
1816: @*/
1817: PetscErrorCode  MatCreateSeqSBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A)
1818: {
1820: 
1822:   MatCreate(comm,A);
1823:   MatSetSizes(*A,m,n,m,n);
1824:   MatSetType(*A,MATSEQSBAIJ);
1825:   MatSeqSBAIJSetPreallocation_SeqSBAIJ(*A,bs,nz,(PetscInt*)nnz);
1826:   return(0);
1827: }

1831: PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B)
1832: {
1833:   Mat            C;
1834:   Mat_SeqSBAIJ   *c,*a = (Mat_SeqSBAIJ*)A->data;
1836:   PetscInt       i,mbs = a->mbs,nz = a->nz,bs2 =a->bs2;

1839:   if (a->i[mbs] != nz) SETERRQ(PETSC_ERR_PLIB,"Corrupt matrix");

1841:   *B = 0;
1842:   MatCreate(((PetscObject)A)->comm,&C);
1843:   MatSetSizes(C,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);
1844:   MatSetType(C,((PetscObject)A)->type_name);
1845:   PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));
1846:   c    = (Mat_SeqSBAIJ*)C->data;

1848:   C->preallocated   = PETSC_TRUE;
1849:   C->factor         = A->factor;
1850:   c->row            = 0;
1851:   c->icol           = 0;
1852:   c->saved_values   = 0;
1853:   c->keepzeroedrows = a->keepzeroedrows;
1854:   C->assembled      = PETSC_TRUE;

1856:   PetscMapCopy(((PetscObject)A)->comm,A->rmap,C->rmap);
1857:   PetscMapCopy(((PetscObject)A)->comm,A->cmap,C->cmap);
1858:   c->bs2  = a->bs2;
1859:   c->mbs  = a->mbs;
1860:   c->nbs  = a->nbs;

1862:   PetscMalloc2((mbs+1),PetscInt,&c->imax,(mbs+1),PetscInt,&c->ilen);
1863:   for (i=0; i<mbs; i++) {
1864:     c->imax[i] = a->imax[i];
1865:     c->ilen[i] = a->ilen[i];
1866:   }

1868:   /* allocate the matrix space */
1869:   PetscMalloc3(bs2*nz,MatScalar,&c->a,nz,PetscInt,&c->j,mbs+1,PetscInt,&c->i);
1870:   c->singlemalloc = PETSC_TRUE;
1871:   PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));
1872:   PetscLogObjectMemory(C,(mbs+1)*sizeof(PetscInt) + nz*(bs2*sizeof(MatScalar) + sizeof(PetscInt)));
1873:   if (mbs > 0) {
1874:     PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));
1875:     if (cpvalues == MAT_COPY_VALUES) {
1876:       PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));
1877:     } else {
1878:       PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));
1879:     }
1880:   }

1882:   c->roworiented = a->roworiented;
1883:   c->nonew       = a->nonew;

1885:   if (a->diag) {
1886:     PetscMalloc((mbs+1)*sizeof(PetscInt),&c->diag);
1887:     PetscLogObjectMemory(C,(mbs+1)*sizeof(PetscInt));
1888:     for (i=0; i<mbs; i++) {
1889:       c->diag[i] = a->diag[i];
1890:     }
1891:   } else c->diag  = 0;
1892:   c->nz           = a->nz;
1893:   c->maxnz        = a->maxnz;
1894:   c->solve_work   = 0;
1895:   c->mult_work    = 0;
1896:   c->free_a       = PETSC_TRUE;
1897:   c->free_ij      = PETSC_TRUE;
1898:   *B = C;
1899:   PetscFListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
1900:   return(0);
1901: }

1905: PetscErrorCode MatLoad_SeqSBAIJ(PetscViewer viewer, const MatType type,Mat *A)
1906: {
1907:   Mat_SeqSBAIJ   *a;
1908:   Mat            B;
1910:   int            fd;
1911:   PetscMPIInt    size;
1912:   PetscInt       i,nz,header[4],*rowlengths=0,M,N,bs=1;
1913:   PetscInt       *mask,mbs,*jj,j,rowcount,nzcount,k,*s_browlengths,maskcount;
1914:   PetscInt       kmax,jcount,block,idx,point,nzcountb,extra_rows;
1915:   PetscInt       *masked,nmask,tmp,bs2,ishift;
1916:   PetscScalar    *aa;
1917:   MPI_Comm       comm = ((PetscObject)viewer)->comm;

1920:   PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);
1921:   bs2  = bs*bs;

1923:   MPI_Comm_size(comm,&size);
1924:   if (size > 1) SETERRQ(PETSC_ERR_ARG_WRONG,"view must have one processor");
1925:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1926:   PetscBinaryRead(fd,header,4,PETSC_INT);
1927:   if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not Mat object");
1928:   M = header[1]; N = header[2]; nz = header[3];

1930:   if (header[3] < 0) {
1931:     SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqSBAIJ");
1932:   }

1934:   if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices");

1936:   /* 
1937:      This code adds extra rows to make sure the number of rows is 
1938:     divisible by the blocksize
1939:   */
1940:   mbs        = M/bs;
1941:   extra_rows = bs - M + bs*(mbs);
1942:   if (extra_rows == bs) extra_rows = 0;
1943:   else                  mbs++;
1944:   if (extra_rows) {
1945:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
1946:   }

1948:   /* read in row lengths */
1949:   PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);
1950:   PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
1951:   for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;

1953:   /* read in column indices */
1954:   PetscMalloc((nz+extra_rows)*sizeof(PetscInt),&jj);
1955:   PetscBinaryRead(fd,jj,nz,PETSC_INT);
1956:   for (i=0; i<extra_rows; i++) jj[nz+i] = M+i;

1958:   /* loop over row lengths determining block row lengths */
1959:   PetscMalloc(mbs*sizeof(PetscInt),&s_browlengths);
1960:   PetscMemzero(s_browlengths,mbs*sizeof(PetscInt));
1961:   PetscMalloc(2*mbs*sizeof(PetscInt),&mask);
1962:   PetscMemzero(mask,mbs*sizeof(PetscInt));
1963:   masked   = mask + mbs;
1964:   rowcount = 0; nzcount = 0;
1965:   for (i=0; i<mbs; i++) {
1966:     nmask = 0;
1967:     for (j=0; j<bs; j++) {
1968:       kmax = rowlengths[rowcount];
1969:       for (k=0; k<kmax; k++) {
1970:         tmp = jj[nzcount++]/bs;   /* block col. index */
1971:         if (!mask[tmp] && tmp >= i) {masked[nmask++] = tmp; mask[tmp] = 1;}
1972:       }
1973:       rowcount++;
1974:     }
1975:     s_browlengths[i] += nmask;
1976: 
1977:     /* zero out the mask elements we set */
1978:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
1979:   }

1981:   /* create our matrix */
1982:   MatCreate(comm,&B);
1983:   MatSetSizes(B,M+extra_rows,N+extra_rows,M+extra_rows,N+extra_rows);
1984:   MatSetType(B,type);
1985:   MatSeqSBAIJSetPreallocation_SeqSBAIJ(B,bs,0,s_browlengths);
1986:   a = (Mat_SeqSBAIJ*)B->data;

1988:   /* set matrix "i" values */
1989:   a->i[0] = 0;
1990:   for (i=1; i<= mbs; i++) {
1991:     a->i[i]      = a->i[i-1] + s_browlengths[i-1];
1992:     a->ilen[i-1] = s_browlengths[i-1];
1993:   }
1994:   a->nz = a->i[mbs];

1996:   /* read in nonzero values */
1997:   PetscMalloc((nz+extra_rows)*sizeof(PetscScalar),&aa);
1998:   PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);
1999:   for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0;

2001:   /* set "a" and "j" values into matrix */
2002:   nzcount = 0; jcount = 0;
2003:   for (i=0; i<mbs; i++) {
2004:     nzcountb = nzcount;
2005:     nmask    = 0;
2006:     for (j=0; j<bs; j++) {
2007:       kmax = rowlengths[i*bs+j];
2008:       for (k=0; k<kmax; k++) {
2009:         tmp = jj[nzcount++]/bs; /* block col. index */
2010:         if (!mask[tmp] && tmp >= i) { masked[nmask++] = tmp; mask[tmp] = 1;}
2011:       }
2012:     }
2013:     /* sort the masked values */
2014:     PetscSortInt(nmask,masked);

2016:     /* set "j" values into matrix */
2017:     maskcount = 1;
2018:     for (j=0; j<nmask; j++) {
2019:       a->j[jcount++]  = masked[j];
2020:       mask[masked[j]] = maskcount++;
2021:     }

2023:     /* set "a" values into matrix */
2024:     ishift = bs2*a->i[i];
2025:     for (j=0; j<bs; j++) {
2026:       kmax = rowlengths[i*bs+j];
2027:       for (k=0; k<kmax; k++) {
2028:         tmp       = jj[nzcountb]/bs ; /* block col. index */
2029:         if (tmp >= i){
2030:           block     = mask[tmp] - 1;
2031:           point     = jj[nzcountb] - bs*tmp;
2032:           idx       = ishift + bs2*block + j + bs*point;
2033:           a->a[idx] = aa[nzcountb];
2034:         }
2035:         nzcountb++;
2036:       }
2037:     }
2038:     /* zero out the mask elements we set */
2039:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
2040:   }
2041:   if (jcount != a->nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix");

2043:   PetscFree(rowlengths);
2044:   PetscFree(s_browlengths);
2045:   PetscFree(aa);
2046:   PetscFree(jj);
2047:   PetscFree(mask);

2049:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2050:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2051:   MatView_Private(B);
2052:   *A = B;
2053:   return(0);
2054: }

2058: PetscErrorCode MatRelax_SeqSBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2059: {
2060:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
2061:   MatScalar      *aa=a->a,*v,*v1;
2062:   PetscScalar    *x,*b,*t,sum,d;
2064:   PetscInt       m=a->mbs,bs=A->rmap->bs,*ai=a->i,*aj=a->j;
2065:   PetscInt       nz,nz1,*vj,*vj1,i;

2068:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_ERR_SUP,"No support yet for Eisenstat");

2070:   its = its*lits;
2071:   if (its <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);

2073:   if (bs > 1)
2074:     SETERRQ(PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

2076:   VecGetArray(xx,&x);
2077:   if (xx != bb) {
2078:     VecGetArray(bb,&b);
2079:   } else {
2080:     b = x;
2081:   }

2083:   if (!a->relax_work) {
2084:     PetscMalloc(m*sizeof(PetscScalar),&a->relax_work);
2085:   }
2086:   t = a->relax_work;
2087: 
2088:   if (flag & SOR_ZERO_INITIAL_GUESS) {
2089:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
2090:       PetscMemcpy(t,b,m*sizeof(PetscScalar));

2092:       for (i=0; i<m; i++){
2093:         d  = *(aa + ai[i]);  /* diag[i] */
2094:         v  = aa + ai[i] + 1;
2095:         vj = aj + ai[i] + 1;
2096:         nz = ai[i+1] - ai[i] - 1;
2097:         PetscLogFlops(2*nz-1);
2098:         x[i] = omega*t[i]/d;
2099:         while (nz--) t[*vj++] -= x[i]*(*v++); /* update rhs */
2100:       }
2101:     }

2103:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
2104:       if (!(flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP)){
2105:         t = b;
2106:       }
2107: 
2108:       for (i=m-1; i>=0; i--){
2109:         d  = *(aa + ai[i]);
2110:         v  = aa + ai[i] + 1;
2111:         vj = aj + ai[i] + 1;
2112:         nz = ai[i+1] - ai[i] - 1;
2113:         PetscLogFlops(2*nz-1);
2114:         sum = t[i];
2115:         while (nz--) sum -= x[*vj++]*(*v++);
2116:         x[i] =   (1-omega)*x[i] + omega*sum/d;
2117:       }
2118:       t = a->relax_work;
2119:     }
2120:     its--;
2121:   }

2123:   while (its--) {
2124:     /* 
2125:        forward sweep:
2126:        for i=0,...,m-1:
2127:          sum[i] = (b[i] - U(i,:)x )/d[i];
2128:          x[i]   = (1-omega)x[i] + omega*sum[i];
2129:          b      = b - x[i]*U^T(i,:);
2130:          
2131:     */
2132:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){
2133:       PetscMemcpy(t,b,m*sizeof(PetscScalar));

2135:       for (i=0; i<m; i++){
2136:         d  = *(aa + ai[i]);  /* diag[i] */
2137:         v  = aa + ai[i] + 1; v1=v;
2138:         vj = aj + ai[i] + 1; vj1=vj;
2139:         nz = ai[i+1] - ai[i] - 1; nz1=nz;
2140:         sum = t[i];
2141:         PetscLogFlops(4*nz-2);
2142:         while (nz1--) sum -= (*v1++)*x[*vj1++];
2143:         x[i] = (1-omega)*x[i] + omega*sum/d;
2144:         while (nz--) t[*vj++] -= x[i]*(*v++);
2145:       }
2146:     }
2147: 
2148:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){
2149:       /* 
2150:        backward sweep:
2151:        b = b - x[i]*U^T(i,:), i=0,...,n-2
2152:        for i=m-1,...,0:
2153:          sum[i] = (b[i] - U(i,:)x )/d[i];
2154:          x[i]   = (1-omega)x[i] + omega*sum[i];
2155:       */
2156:       /* if there was a forward sweep done above then I thing the next two for loops are not needed */
2157:       PetscMemcpy(t,b,m*sizeof(PetscScalar));
2158: 
2159:       for (i=0; i<m-1; i++){  /* update rhs */
2160:         v  = aa + ai[i] + 1;
2161:         vj = aj + ai[i] + 1;
2162:         nz = ai[i+1] - ai[i] - 1;
2163:         PetscLogFlops(2*nz-1);
2164:         while (nz--) t[*vj++] -= x[i]*(*v++);
2165:       }
2166:       for (i=m-1; i>=0; i--){
2167:         d  = *(aa + ai[i]);
2168:         v  = aa + ai[i] + 1;
2169:         vj = aj + ai[i] + 1;
2170:         nz = ai[i+1] - ai[i] - 1;
2171:         PetscLogFlops(2*nz-1);
2172:         sum = t[i];
2173:         while (nz--) sum -= x[*vj++]*(*v++);
2174:         x[i] =   (1-omega)*x[i] + omega*sum/d;
2175:       }
2176:     }
2177:   }

2179:   VecRestoreArray(xx,&x);
2180:   if (bb != xx) {
2181:     VecRestoreArray(bb,&b);
2182:   }
2183:   return(0);
2184: }

2188: /*@
2189:      MatCreateSeqSBAIJWithArrays - Creates an sequential SBAIJ matrix using matrix elements 
2190:               (upper triangular entries in CSR format) provided by the user.

2192:      Collective on MPI_Comm

2194:    Input Parameters:
2195: +  comm - must be an MPI communicator of size 1
2196: .  bs - size of block
2197: .  m - number of rows
2198: .  n - number of columns
2199: .  i - row indices
2200: .  j - column indices
2201: -  a - matrix values

2203:    Output Parameter:
2204: .  mat - the matrix

2206:    Level: intermediate

2208:    Notes:
2209:        The i, j, and a arrays are not copied by this routine, the user must free these arrays
2210:     once the matrix is destroyed

2212:        You cannot set new nonzero locations into this matrix, that will generate an error.

2214:        The i and j indices are 0 based

2216: .seealso: MatCreate(), MatCreateMPISBAIJ(), MatCreateSeqSBAIJ()

2218: @*/
2219: PetscErrorCode  MatCreateSeqSBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt* i,PetscInt*j,PetscScalar *a,Mat *mat)
2220: {
2222:   PetscInt       ii;
2223:   Mat_SeqSBAIJ   *sbaij;

2226:   if (bs != 1) SETERRQ1(PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs);
2227:   if (i[0]) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
2228: 
2229:   MatCreate(comm,mat);
2230:   MatSetSizes(*mat,m,n,m,n);
2231:   MatSetType(*mat,MATSEQSBAIJ);
2232:   MatSeqSBAIJSetPreallocation_SeqSBAIJ(*mat,bs,MAT_SKIP_ALLOCATION,0);
2233:   sbaij = (Mat_SeqSBAIJ*)(*mat)->data;
2234:   PetscMalloc2(m,PetscInt,&sbaij->imax,m,PetscInt,&sbaij->ilen);

2236:   sbaij->i = i;
2237:   sbaij->j = j;
2238:   sbaij->a = a;
2239:   sbaij->singlemalloc = PETSC_FALSE;
2240:   sbaij->nonew        = -1;             /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
2241:   sbaij->free_a       = PETSC_FALSE;
2242:   sbaij->free_ij      = PETSC_FALSE;

2244:   for (ii=0; ii<m; ii++) {
2245:     sbaij->ilen[ii] = sbaij->imax[ii] = i[ii+1] - i[ii];
2246: #if defined(PETSC_USE_DEBUG)
2247:     if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %d length = %d",ii,i[ii+1] - i[ii]);
2248: #endif    
2249:   }
2250: #if defined(PETSC_USE_DEBUG)
2251:   for (ii=0; ii<sbaij->i[m]; ii++) {
2252:     if (j[ii] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]);
2253:     if (j[ii] > n - 1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %d index = %d",ii,j[ii]);
2254:   }
2255: #endif    

2257:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
2258:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
2259:   return(0);
2260: }