Date: 2022-08-02T03:13:52+00:00

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: #if defined(PETSC_HAVE_ELEMENTAL)
     15: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
     16: #endif
     17: #if defined(PETSC_HAVE_SCALAPACK)
     18: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
     19: #endif
     20: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat,MatType,MatReuse,Mat*);

     22: /*
     23:      Checks for missing diagonals
     24: */
     25: PetscErrorCode MatMissingDiagonal_SeqSBAIJ(Mat A,PetscBool  *missing,PetscInt *dd)
     26: {
     27:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
     28:   PetscInt       *diag,*ii = a->i,i;

     30:   MatMarkDiagonal_SeqSBAIJ(A);
     31:   *missing = PETSC_FALSE;
     32:   if (A->rmap->n > 0 && !ii) {
     33:     *missing = PETSC_TRUE;
     34:     if (dd) *dd = 0;
     35:     PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");
     36:   } else {
     37:     diag = a->diag;
     38:     for (i=0; i<a->mbs; i++) {
     39:       if (diag[i] >= ii[i+1]) {
     40:         *missing = PETSC_TRUE;
     41:         if (dd) *dd = i;
     42:         break;
     43:       }
     44:     }
     45:   }
     46:   return 0;
     47: }

     49: PetscErrorCode MatMarkDiagonal_SeqSBAIJ(Mat A)
     50: {
     51:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
     52:   PetscInt       i,j;

     54:   if (!a->diag) {
     55:     PetscMalloc1(a->mbs,&a->diag);
     56:     PetscLogObjectMemory((PetscObject)A,a->mbs*sizeof(PetscInt));
     57:     a->free_diag = PETSC_TRUE;
     58:   }
     59:   for (i=0; i<a->mbs; i++) {
     60:     a->diag[i] = a->i[i+1];
     61:     for (j=a->i[i]; j<a->i[i+1]; j++) {
     62:       if (a->j[j] == i) {
     63:         a->diag[i] = j;
     64:         break;
     65:       }
     66:     }
     67:   }
     68:   return 0;
     69: }

     71: static PetscErrorCode MatGetRowIJ_SeqSBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool  *done)
     72: {
     73:   Mat_SeqSBAIJ    *a = (Mat_SeqSBAIJ*)A->data;
     74:   PetscInt       i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt;
     75:   PetscInt       **ia = (PetscInt**)inia,**ja = (PetscInt**)inja;

     77:   *nn = n;
     78:   if (!ia) return 0;
     79:   if (symmetric) {
     80:     MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,PETSC_FALSE,0,0,&tia,&tja);
     81:     nz   = tia[n];
     82:   } else {
     83:     tia = a->i; tja = a->j;
     84:   }

     86:   if (!blockcompressed && bs > 1) {
     87:     (*nn) *= bs;
     88:     /* malloc & create the natural set of indices */
     89:     PetscMalloc1((n+1)*bs,ia);
     90:     if (n) {
     91:       (*ia)[0] = oshift;
     92:       for (j=1; j<bs; j++) {
     93:         (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1];
     94:       }
     95:     }

     97:     for (i=1; i<n; i++) {
     98:       (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1];
     99:       for (j=1; j<bs; j++) {
    100:         (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1];
    101:       }
    102:     }
    103:     if (n) {
    104:       (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1];
    105:     }

    107:     if (inja) {
    108:       PetscMalloc1(nz*bs*bs,ja);
    109:       cnt = 0;
    110:       for (i=0; i<n; i++) {
    111:         for (j=0; j<bs; j++) {
    112:           for (k=tia[i]; k<tia[i+1]; k++) {
    113:             for (l=0; l<bs; l++) {
    114:               (*ja)[cnt++] = bs*tja[k] + l;
    115:             }
    116:           }
    117:         }
    118:       }
    119:     }

    121:     if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
    122:       PetscFree(tia);
    123:       PetscFree(tja);
    124:     }
    125:   } else if (oshift == 1) {
    126:     if (symmetric) {
    127:       nz = tia[A->rmap->n/bs];
    128:       /*  add 1 to i and j indices */
    129:       for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1;
    130:       *ia = tia;
    131:       if (ja) {
    132:         for (i=0; i<nz; i++) tja[i] = tja[i] + 1;
    133:         *ja = tja;
    134:       }
    135:     } else {
    136:       nz = a->i[A->rmap->n/bs];
    137:       /* malloc space and  add 1 to i and j indices */
    138:       PetscMalloc1(A->rmap->n/bs+1,ia);
    139:       for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1;
    140:       if (ja) {
    141:         PetscMalloc1(nz,ja);
    142:         for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1;
    143:       }
    144:     }
    145:   } else {
    146:     *ia = tia;
    147:     if (ja) *ja = tja;
    148:   }
    149:   return 0;
    150: }

    152: static PetscErrorCode MatRestoreRowIJ_SeqSBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
    153: {
    154:   if (!ia) return 0;
    155:   if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
    156:     PetscFree(*ia);
    157:     if (ja) PetscFree(*ja);
    158:   }
    159:   return 0;
    160: }

    162: PetscErrorCode MatDestroy_SeqSBAIJ(Mat A)
    163: {
    164:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;

    166: #if defined(PETSC_USE_LOG)
    167:   PetscLogObjectState((PetscObject)A,"Rows=%" PetscInt_FMT ", NZ=%" PetscInt_FMT,A->rmap->N,a->nz);
    168: #endif
    169:   MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);
    170:   if (a->free_diag) PetscFree(a->diag);
    171:   ISDestroy(&a->row);
    172:   ISDestroy(&a->col);
    173:   ISDestroy(&a->icol);
    174:   PetscFree(a->idiag);
    175:   PetscFree(a->inode.size);
    176:   if (a->free_imax_ilen) PetscFree2(a->imax,a->ilen);
    177:   PetscFree(a->solve_work);
    178:   PetscFree(a->sor_work);
    179:   PetscFree(a->solves_work);
    180:   PetscFree(a->mult_work);
    181:   PetscFree(a->saved_values);
    182:   if (a->free_jshort) PetscFree(a->jshort);
    183:   PetscFree(a->inew);
    184:   MatDestroy(&a->parent);
    185:   PetscFree(A->data);

    187:   PetscObjectChangeTypeName((PetscObject)A,NULL);
    188:   PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);
    189:   PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);
    190:   PetscObjectComposeFunction((PetscObject)A,"MatSeqSBAIJSetColumnIndices_C",NULL);
    191:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqsbaij_seqaij_C",NULL);
    192:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqsbaij_seqbaij_C",NULL);
    193:   PetscObjectComposeFunction((PetscObject)A,"MatSeqSBAIJSetPreallocation_C",NULL);
    194:   PetscObjectComposeFunction((PetscObject)A,"MatSeqSBAIJSetPreallocationCSR_C",NULL);
    195: #if defined(PETSC_HAVE_ELEMENTAL)
    196:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqsbaij_elemental_C",NULL);
    197: #endif
    198: #if defined(PETSC_HAVE_SCALAPACK)
    199:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqsbaij_scalapack_C",NULL);
    200: #endif
    201:   return 0;
    202: }

    204: PetscErrorCode MatSetOption_SeqSBAIJ(Mat A,MatOption op,PetscBool flg)
    205: {
    206:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
    207: #if defined(PETSC_USE_COMPLEX)
    208:   PetscInt       bs;
    209: #endif

    211: #if defined(PETSC_USE_COMPLEX)
    212:   MatGetBlockSize(A,&bs);
    213: #endif
    214:   switch (op) {
    215:   case MAT_ROW_ORIENTED:
    216:     a->roworiented = flg;
    217:     break;
    218:   case MAT_KEEP_NONZERO_PATTERN:
    219:     a->keepnonzeropattern = flg;
    220:     break;
    221:   case MAT_NEW_NONZERO_LOCATIONS:
    222:     a->nonew = (flg ? 0 : 1);
    223:     break;
    224:   case MAT_NEW_NONZERO_LOCATION_ERR:
    225:     a->nonew = (flg ? -1 : 0);
    226:     break;
    227:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    228:     a->nonew = (flg ? -2 : 0);
    229:     break;
    230:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    231:     a->nounused = (flg ? -1 : 0);
    232:     break;
    233:   case MAT_FORCE_DIAGONAL_ENTRIES:
    234:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    235:   case MAT_USE_HASH_TABLE:
    236:   case MAT_SORTED_FULL:
    237:     PetscInfo(A,"Option %s ignored\n",MatOptions[op]);
    238:     break;
    239:   case MAT_HERMITIAN:
    240: #if defined(PETSC_USE_COMPLEX)
    241:     if (flg) { /* disable transpose ops */
    243:       A->ops->multtranspose    = NULL;
    244:       A->ops->multtransposeadd = NULL;
    245:       A->symmetric             = PETSC_FALSE;
    246:     }
    247: #endif
    248:     break;
    249:   case MAT_SYMMETRIC:
    250:   case MAT_SPD:
    251: #if defined(PETSC_USE_COMPLEX)
    252:     if (flg) { /* An hermitian and symmetric matrix has zero imaginary part (restore back transpose ops) */
    253:       A->ops->multtranspose    = A->ops->mult;
    254:       A->ops->multtransposeadd = A->ops->multadd;
    255:     }
    256: #endif
    257:     break;
    258:     /* These options are handled directly by MatSetOption() */
    259:   case MAT_STRUCTURALLY_SYMMETRIC:
    260:   case MAT_SYMMETRY_ETERNAL:
    261:   case MAT_STRUCTURE_ONLY:
    262:     /* These options are handled directly by MatSetOption() */
    263:     break;
    264:   case MAT_IGNORE_LOWER_TRIANGULAR:
    265:     a->ignore_ltriangular = flg;
    266:     break;
    267:   case MAT_ERROR_LOWER_TRIANGULAR:
    268:     a->ignore_ltriangular = flg;
    269:     break;
    270:   case MAT_GETROW_UPPERTRIANGULAR:
    271:     a->getrow_utriangular = flg;
    272:     break;
    273:   case MAT_SUBMAT_SINGLEIS:
    274:     break;
    275:   default:
    276:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
    277:   }
    278:   return 0;
    279: }

    281: PetscErrorCode MatGetRow_SeqSBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    282: {
    283:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;

    287:   /* Get the upper triangular part of the row */
    288:   MatGetRow_SeqBAIJ_private(A,row,nz,idx,v,a->i,a->j,a->a);
    289:   return 0;
    290: }

    292: PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    293: {
    294:   if (nz)  *nz = 0;
    295:   if (idx) PetscFree(*idx);
    296:   if (v)   PetscFree(*v);
    297:   return 0;
    298: }

    300: PetscErrorCode MatGetRowUpperTriangular_SeqSBAIJ(Mat A)
    301: {
    302:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;

    304:   a->getrow_utriangular = PETSC_TRUE;
    305:   return 0;
    306: }

    308: PetscErrorCode MatRestoreRowUpperTriangular_SeqSBAIJ(Mat A)
    309: {
    310:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;

    312:   a->getrow_utriangular = PETSC_FALSE;
    313:   return 0;
    314: }

    316: PetscErrorCode MatTranspose_SeqSBAIJ(Mat A,MatReuse reuse,Mat *B)
    317: {
    318:   if (reuse == MAT_INITIAL_MATRIX) {
    319:     MatDuplicate(A,MAT_COPY_VALUES,B);
    320:   } else if (reuse == MAT_REUSE_MATRIX) {
    321:     MatCopy(A,*B,SAME_NONZERO_PATTERN);
    322:   }
    323:   return 0;
    324: }

    326: PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat A,PetscViewer viewer)
    327: {
    328:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
    329:   PetscInt          i,j,bs = A->rmap->bs,k,l,bs2=a->bs2;
    330:   PetscViewerFormat format;
    331:   PetscInt          *diag;

    333:   PetscViewerGetFormat(viewer,&format);
    334:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    335:     PetscViewerASCIIPrintf(viewer,"  block size is %" PetscInt_FMT "\n",bs);
    336:   } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
    337:     Mat        aij;
    338:     const char *matname;

    340:     if (A->factortype && bs>1) {
    341:       PetscPrintf(PETSC_COMM_SELF,"Warning: matrix is factored with bs>1. MatView() with PETSC_VIEWER_ASCII_MATLAB is not supported and ignored!\n");
    342:       return 0;
    343:     }
    344:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);
    345:     PetscObjectGetName((PetscObject)A,&matname);
    346:     PetscObjectSetName((PetscObject)aij,matname);
    347:     MatView(aij,viewer);
    348:     MatDestroy(&aij);
    349:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
    350:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    351:     for (i=0; i<a->mbs; i++) {
    352:       for (j=0; j<bs; j++) {
    353:         PetscViewerASCIIPrintf(viewer,"row %" PetscInt_FMT ":",i*bs+j);
    354:         for (k=a->i[i]; k<a->i[i+1]; k++) {
    355:           for (l=0; l<bs; l++) {
    356: #if defined(PETSC_USE_COMPLEX)
    357:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    358:               PetscCall(PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g + %g i) ",bs*a->j[k]+l,
    359:                                              (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j])));
    360:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    361:               PetscCall(PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g - %g i) ",bs*a->j[k]+l,
    362:                                              (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j])));
    363:             } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
    364:               PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
    365:             }
    366: #else
    367:             if (a->a[bs2*k + l*bs + j] != 0.0) {
    368:               PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
    369:             }
    370: #endif
    371:           }
    372:         }
    373:         PetscViewerASCIIPrintf(viewer,"\n");
    374:       }
    375:     }
    376:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    377:   } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    378:     return 0;
    379:   } else {
    380:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    381:     if (A->factortype) { /* for factored matrix */

    384:       diag=a->diag;
    385:       for (i=0; i<a->mbs; i++) { /* for row block i */
    386:         PetscViewerASCIIPrintf(viewer,"row %" PetscInt_FMT ":",i);
    387:         /* diagonal entry */
    388: #if defined(PETSC_USE_COMPLEX)
    389:         if (PetscImaginaryPart(a->a[diag[i]]) > 0.0) {
    390:           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]]));
    391:         } else if (PetscImaginaryPart(a->a[diag[i]]) < 0.0) {
    392:           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]]));
    393:         } else {
    394:           PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",a->j[diag[i]],(double)PetscRealPart(1.0/a->a[diag[i]]));
    395:         }
    396: #else
    397:         PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",a->j[diag[i]],(double)(1.0/a->a[diag[i]]));
    398: #endif
    399:         /* off-diagonal entries */
    400:         for (k=a->i[i]; k<a->i[i+1]-1; k++) {
    401: #if defined(PETSC_USE_COMPLEX)
    402:           if (PetscImaginaryPart(a->a[k]) > 0.0) {
    403:             PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g + %g i) ",bs*a->j[k],(double)PetscRealPart(a->a[k]),(double)PetscImaginaryPart(a->a[k]));
    404:           } else if (PetscImaginaryPart(a->a[k]) < 0.0) {
    405:             PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g - %g i) ",bs*a->j[k],(double)PetscRealPart(a->a[k]),-(double)PetscImaginaryPart(a->a[k]));
    406:           } else {
    407:             PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",bs*a->j[k],(double)PetscRealPart(a->a[k]));
    408:           }
    409: #else
    410:           PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",a->j[k],(double)a->a[k]);
    411: #endif
    412:         }
    413:         PetscViewerASCIIPrintf(viewer,"\n");
    414:       }

    416:     } else { /* for non-factored matrix */
    417:       for (i=0; i<a->mbs; i++) { /* for row block i */
    418:         for (j=0; j<bs; j++) {   /* for row bs*i + j */
    419:           PetscViewerASCIIPrintf(viewer,"row %" PetscInt_FMT ":",i*bs+j);
    420:           for (k=a->i[i]; k<a->i[i+1]; k++) { /* for column block */
    421:             for (l=0; l<bs; l++) {            /* for column */
    422: #if defined(PETSC_USE_COMPLEX)
    423:               if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) {
    424:                 PetscCall(PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g + %g i) ",bs*a->j[k]+l,
    425:                                                (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j])));
    426:               } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) {
    427:                 PetscCall(PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g - %g i) ",bs*a->j[k]+l,
    428:                                                (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j])));
    429:               } else {
    430:                 PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
    431:               }
    432: #else
    433:               PetscViewerASCIIPrintf(viewer," (%" PetscInt_FMT ", %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
    434: #endif
    435:             }
    436:           }
    437:           PetscViewerASCIIPrintf(viewer,"\n");
    438:         }
    439:       }
    440:     }
    441:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    442:   }
    443:   PetscViewerFlush(viewer);
    444:   return 0;
    445: }

    447: #include <petscdraw.h>
    448: static PetscErrorCode MatView_SeqSBAIJ_Draw_Zoom(PetscDraw draw,void *Aa)
    449: {
    450:   Mat            A = (Mat) Aa;
    451:   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data;
    452:   PetscInt       row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2;
    453:   PetscReal      xl,yl,xr,yr,x_l,x_r,y_l,y_r;
    454:   MatScalar      *aa;
    455:   PetscViewer    viewer;

    458:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
    459:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);

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

    463:   PetscDrawCollectiveBegin(draw);
    464:   PetscDrawString(draw, .3*(xl+xr), .3*(yl+yr), PETSC_DRAW_BLACK, "symmetric");
    465:   /* Blue for negative, Cyan for zero and  Red for positive */
    466:   color = PETSC_DRAW_BLUE;
    467:   for (i=0,row=0; i<mbs; i++,row+=bs) {
    468:     for (j=a->i[i]; j<a->i[i+1]; j++) {
    469:       y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    470:       x_l = a->j[j]*bs; x_r = x_l + 1.0;
    471:       aa  = a->a + j*bs2;
    472:       for (k=0; k<bs; k++) {
    473:         for (l=0; l<bs; l++) {
    474:           if (PetscRealPart(*aa++) >=  0.) continue;
    475:           PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    476:         }
    477:       }
    478:     }
    479:   }
    480:   color = PETSC_DRAW_CYAN;
    481:   for (i=0,row=0; i<mbs; i++,row+=bs) {
    482:     for (j=a->i[i]; j<a->i[i+1]; j++) {
    483:       y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    484:       x_l = a->j[j]*bs; x_r = x_l + 1.0;
    485:       aa = a->a + j*bs2;
    486:       for (k=0; k<bs; k++) {
    487:         for (l=0; l<bs; l++) {
    488:           if (PetscRealPart(*aa++) != 0.) continue;
    489:           PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    490:         }
    491:       }
    492:     }
    493:   }
    494:   color = PETSC_DRAW_RED;
    495:   for (i=0,row=0; i<mbs; i++,row+=bs) {
    496:     for (j=a->i[i]; j<a->i[i+1]; j++) {
    497:       y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
    498:       x_l = a->j[j]*bs; x_r = x_l + 1.0;
    499:       aa = a->a + j*bs2;
    500:       for (k=0; k<bs; k++) {
    501:         for (l=0; l<bs; l++) {
    502:           if (PetscRealPart(*aa++) <= 0.) continue;
    503:           PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
    504:         }
    505:       }
    506:     }
    507:   }
    508:   PetscDrawCollectiveEnd(draw);
    509:   return 0;
    510: }

    512: static PetscErrorCode MatView_SeqSBAIJ_Draw(Mat A,PetscViewer viewer)
    513: {
    514:   PetscReal      xl,yl,xr,yr,w,h;
    515:   PetscDraw      draw;
    516:   PetscBool      isnull;

    518:   PetscViewerDrawGetDraw(viewer,0,&draw);
    519:   PetscDrawIsNull(draw,&isnull);
    520:   if (isnull) return 0;

    522:   xr   = A->rmap->N; yr = A->rmap->N; h = yr/10.0; w = xr/10.0;
    523:   xr  += w;          yr += h;        xl = -w;     yl = -h;
    524:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
    525:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
    526:   PetscDrawZoom(draw,MatView_SeqSBAIJ_Draw_Zoom,A);
    527:   PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
    528:   PetscDrawSave(draw);
    529:   return 0;
    530: }

    532: /* Used for both MPIBAIJ and MPISBAIJ matrices */
    533: #define MatView_SeqSBAIJ_Binary MatView_SeqBAIJ_Binary

    535: PetscErrorCode MatView_SeqSBAIJ(Mat A,PetscViewer viewer)
    536: {
    537:   PetscBool      iascii,isbinary,isdraw;

    539:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    540:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    541:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    542:   if (iascii) {
    543:     MatView_SeqSBAIJ_ASCII(A,viewer);
    544:   } else if (isbinary) {
    545:     MatView_SeqSBAIJ_Binary(A,viewer);
    546:   } else if (isdraw) {
    547:     MatView_SeqSBAIJ_Draw(A,viewer);
    548:   } else {
    549:     Mat        B;
    550:     const char *matname;
    551:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);
    552:     PetscObjectGetName((PetscObject)A,&matname);
    553:     PetscObjectSetName((PetscObject)B,matname);
    554:     MatView(B,viewer);
    555:     MatDestroy(&B);
    556:   }
    557:   return 0;
    558: }

    560: PetscErrorCode MatGetValues_SeqSBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
    561: {
    562:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
    563:   PetscInt     *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j;
    564:   PetscInt     *ai = a->i,*ailen = a->ilen;
    565:   PetscInt     brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2;
    566:   MatScalar    *ap,*aa = a->a;

    568:   for (k=0; k<m; k++) { /* loop over rows */
    569:     row = im[k]; brow = row/bs;
    570:     if (row < 0) {v += n; continue;} /* negative row */
    572:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow];
    573:     nrow = ailen[brow];
    574:     for (l=0; l<n; l++) { /* loop over columns */
    575:       if (in[l] < 0) {v++; continue;} /* negative column */
    577:       col  = in[l];
    578:       bcol = col/bs;
    579:       cidx = col%bs;
    580:       ridx = row%bs;
    581:       high = nrow;
    582:       low  = 0; /* assume unsorted */
    583:       while (high-low > 5) {
    584:         t = (low+high)/2;
    585:         if (rp[t] > bcol) high = t;
    586:         else              low  = t;
    587:       }
    588:       for (i=low; i<high; i++) {
    589:         if (rp[i] > bcol) break;
    590:         if (rp[i] == bcol) {
    591:           *v++ = ap[bs2*i+bs*cidx+ridx];
    592:           goto finished;
    593:         }
    594:       }
    595:       *v++ = 0.0;
    596: finished:;
    597:     }
    598:   }
    599:   return 0;
    600: }

    602: PetscErrorCode MatPermute_SeqSBAIJ(Mat A,IS rowp,IS colp,Mat *B)
    603: {
    604:   Mat            C;

    606:   MatConvert(A,MATSEQBAIJ,MAT_INITIAL_MATRIX,&C);
    607:   MatPermute(C,rowp,colp,B);
    608:   MatDestroy(&C);
    609:   if (rowp == colp) {
    610:     MatConvert(*B,MATSEQSBAIJ,MAT_INPLACE_MATRIX,B);
    611:   }
    612:   return 0;
    613: }

    615: PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
    616: {
    617:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
    618:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1;
    619:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
    620:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval;
    621:   PetscBool         roworiented=a->roworiented;
    622:   const PetscScalar *value     = v;
    623:   MatScalar         *ap,*aa = a->a,*bap;

    625:   if (roworiented) stepval = (n-1)*bs;
    626:   else stepval = (m-1)*bs;

    628:   for (k=0; k<m; k++) { /* loop over added rows */
    629:     row = im[k];
    630:     if (row < 0) continue;
    632:     rp   = aj + ai[row];
    633:     ap   = aa + bs2*ai[row];
    634:     rmax = imax[row];
    635:     nrow = ailen[row];
    636:     low  = 0;
    637:     high = nrow;
    638:     for (l=0; l<n; l++) { /* loop over added columns */
    639:       if (in[l] < 0) continue;
    640:       col = in[l];
    642:       if (col < row) {
    643:         if (a->ignore_ltriangular) continue; /* ignore lower triangular block */
    644:         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)");
    645:       }
    646:       if (roworiented) value = v + k*(stepval+bs)*bs + l*bs;
    647:       else value = v + l*(stepval+bs)*bs + k*bs;

    649:       if (col <= lastcol) low = 0;
    650:       else high = nrow;

    652:       lastcol = col;
    653:       while (high-low > 7) {
    654:         t = (low+high)/2;
    655:         if (rp[t] > col) high = t;
    656:         else             low  = t;
    657:       }
    658:       for (i=low; i<high; i++) {
    659:         if (rp[i] > col) break;
    660:         if (rp[i] == col) {
    661:           bap = ap +  bs2*i;
    662:           if (roworiented) {
    663:             if (is == ADD_VALUES) {
    664:               for (ii=0; ii<bs; ii++,value+=stepval) {
    665:                 for (jj=ii; jj<bs2; jj+=bs) {
    666:                   bap[jj] += *value++;
    667:                 }
    668:               }
    669:             } else {
    670:               for (ii=0; ii<bs; ii++,value+=stepval) {
    671:                 for (jj=ii; jj<bs2; jj+=bs) {
    672:                   bap[jj] = *value++;
    673:                 }
    674:                }
    675:             }
    676:           } else {
    677:             if (is == ADD_VALUES) {
    678:               for (ii=0; ii<bs; ii++,value+=stepval) {
    679:                 for (jj=0; jj<bs; jj++) {
    680:                   *bap++ += *value++;
    681:                 }
    682:               }
    683:             } else {
    684:               for (ii=0; ii<bs; ii++,value+=stepval) {
    685:                 for (jj=0; jj<bs; jj++) {
    686:                   *bap++  = *value++;
    687:                 }
    688:               }
    689:             }
    690:           }
    691:           goto noinsert2;
    692:         }
    693:       }
    694:       if (nonew == 1) goto noinsert2;
    696:       MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    697:       N = nrow++ - 1; high++;
    698:       /* shift up all the later entries in this row */
    699:       PetscArraymove(rp+i+1,rp+i,N-i+1);
    700:       PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
    701:       PetscArrayzero(ap+bs2*i,bs2);
    702:       rp[i] = col;
    703:       bap   = ap +  bs2*i;
    704:       if (roworiented) {
    705:         for (ii=0; ii<bs; ii++,value+=stepval) {
    706:           for (jj=ii; jj<bs2; jj+=bs) {
    707:             bap[jj] = *value++;
    708:           }
    709:         }
    710:       } else {
    711:         for (ii=0; ii<bs; ii++,value+=stepval) {
    712:           for (jj=0; jj<bs; jj++) {
    713:             *bap++ = *value++;
    714:           }
    715:         }
    716:        }
    717:     noinsert2:;
    718:       low = i;
    719:     }
    720:     ailen[row] = nrow;
    721:   }
    722:   return 0;
    723: }

    725: /*
    726:     This is not yet used
    727: */
    728: PetscErrorCode MatAssemblyEnd_SeqSBAIJ_SeqAIJ_Inode(Mat A)
    729: {
    730:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
    731:   const PetscInt *ai = a->i, *aj = a->j,*cols;
    732:   PetscInt       i   = 0,j,blk_size,m = A->rmap->n,node_count = 0,nzx,nzy,*ns,row,nz,cnt,cnt2,*counts;
    733:   PetscBool      flag;

    735:   PetscMalloc1(m,&ns);
    736:   while (i < m) {
    737:     nzx = ai[i+1] - ai[i];       /* Number of nonzeros */
    738:     /* Limits the number of elements in a node to 'a->inode.limit' */
    739:     for (j=i+1,blk_size=1; j<m && blk_size <a->inode.limit; ++j,++blk_size) {
    740:       nzy = ai[j+1] - ai[j];
    741:       if (nzy != (nzx - j + i)) break;
    742:       PetscArraycmp(aj + ai[i] + j - i,aj + ai[j],nzy,&flag);
    743:       if (!flag) break;
    744:     }
    745:     ns[node_count++] = blk_size;

    747:     i = j;
    748:   }
    749:   if (!a->inode.size && m && node_count > .9*m) {
    750:     PetscFree(ns);
    751:     PetscInfo(A,"Found %" PetscInt_FMT " nodes out of %" PetscInt_FMT " rows. Not using Inode routines\n",node_count,m);
    752:   } else {
    753:     a->inode.node_count = node_count;

    755:     PetscMalloc1(node_count,&a->inode.size);
    756:     PetscLogObjectMemory((PetscObject)A,node_count*sizeof(PetscInt));
    757:     PetscArraycpy(a->inode.size,ns,node_count);
    758:     PetscFree(ns);
    759:     PetscInfo(A,"Found %" PetscInt_FMT " nodes of %" PetscInt_FMT ". Limit used: %" PetscInt_FMT ". Using Inode routines\n",node_count,m,a->inode.limit);

    761:     /* count collections of adjacent columns in each inode */
    762:     row = 0;
    763:     cnt = 0;
    764:     for (i=0; i<node_count; i++) {
    765:       cols = aj + ai[row] + a->inode.size[i];
    766:       nz   = ai[row+1] - ai[row] - a->inode.size[i];
    767:       for (j=1; j<nz; j++) {
    768:         if (cols[j] != cols[j-1]+1) cnt++;
    769:       }
    770:       cnt++;
    771:       row += a->inode.size[i];
    772:     }
    773:     PetscMalloc1(2*cnt,&counts);
    774:     cnt  = 0;
    775:     row  = 0;
    776:     for (i=0; i<node_count; i++) {
    777:       cols = aj + ai[row] + a->inode.size[i];
    778:       counts[2*cnt] = cols[0];
    779:       nz   = ai[row+1] - ai[row] - a->inode.size[i];
    780:       cnt2 = 1;
    781:       for (j=1; j<nz; j++) {
    782:         if (cols[j] != cols[j-1]+1) {
    783:           counts[2*(cnt++)+1] = cnt2;
    784:           counts[2*cnt]       = cols[j];
    785:           cnt2 = 1;
    786:         } else cnt2++;
    787:       }
    788:       counts[2*(cnt++)+1] = cnt2;
    789:       row += a->inode.size[i];
    790:     }
    791:     PetscIntView(2*cnt,counts,NULL);
    792:   }
    793:   return 0;
    794: }

    796: PetscErrorCode MatAssemblyEnd_SeqSBAIJ(Mat A,MatAssemblyType mode)
    797: {
    798:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
    799:   PetscInt       fshift = 0,i,*ai = a->i,*aj = a->j,*imax = a->imax;
    800:   PetscInt       m      = A->rmap->N,*ip,N,*ailen = a->ilen;
    801:   PetscInt       mbs    = a->mbs,bs2 = a->bs2,rmax = 0;
    802:   MatScalar      *aa    = a->a,*ap;

    804:   if (mode == MAT_FLUSH_ASSEMBLY) return 0;

    806:   if (m) rmax = ailen[0];
    807:   for (i=1; i<mbs; i++) {
    808:     /* move each row back by the amount of empty slots (fshift) before it*/
    809:     fshift += imax[i-1] - ailen[i-1];
    810:     rmax    = PetscMax(rmax,ailen[i]);
    811:     if (fshift) {
    812:       ip = aj + ai[i];
    813:       ap = aa + bs2*ai[i];
    814:       N  = ailen[i];
    815:       PetscArraymove(ip-fshift,ip,N);
    816:       PetscArraymove(ap-bs2*fshift,ap,bs2*N);
    817:     }
    818:     ai[i] = ai[i-1] + ailen[i-1];
    819:   }
    820:   if (mbs) {
    821:     fshift += imax[mbs-1] - ailen[mbs-1];
    822:     ai[mbs] = ai[mbs-1] + ailen[mbs-1];
    823:   }
    824:   /* reset ilen and imax for each row */
    825:   for (i=0; i<mbs; i++) {
    826:     ailen[i] = imax[i] = ai[i+1] - ai[i];
    827:   }
    828:   a->nz = ai[mbs];

    830:   /* diagonals may have moved, reset it */
    831:   if (a->diag) {
    832:     PetscArraycpy(a->diag,ai,mbs);
    833:   }

    836:   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);
    837:   PetscInfo(A,"Number of mallocs during MatSetValues is %" PetscInt_FMT "\n",a->reallocs);
    838:   PetscInfo(A,"Most nonzeros blocks in any row is %" PetscInt_FMT "\n",rmax);

    840:   A->info.mallocs    += a->reallocs;
    841:   a->reallocs         = 0;
    842:   A->info.nz_unneeded = (PetscReal)fshift*bs2;
    843:   a->idiagvalid       = PETSC_FALSE;
    844:   a->rmax             = rmax;

    846:   if (A->cmap->n < 65536 && A->cmap->bs == 1) {
    847:     if (a->jshort && a->free_jshort) {
    848:       /* when matrix data structure is changed, previous jshort must be replaced */
    849:       PetscFree(a->jshort);
    850:     }
    851:     PetscMalloc1(a->i[A->rmap->n],&a->jshort);
    852:     PetscLogObjectMemory((PetscObject)A,a->i[A->rmap->n]*sizeof(unsigned short));
    853:     for (i=0; i<a->i[A->rmap->n]; i++) a->jshort[i] = a->j[i];
    854:     A->ops->mult   = MatMult_SeqSBAIJ_1_ushort;
    855:     A->ops->sor    = MatSOR_SeqSBAIJ_ushort;
    856:     a->free_jshort = PETSC_TRUE;
    857:   }
    858:   return 0;
    859: }

    861: /*
    862:    This function returns an array of flags which indicate the locations of contiguous
    863:    blocks that should be zeroed. for eg: if bs = 3  and is = [0,1,2,3,5,6,7,8,9]
    864:    then the resulting sizes = [3,1,1,3,1] corresponding to sets [(0,1,2),(3),(5),(6,7,8),(9)]
    865:    Assume: sizes should be long enough to hold all the values.
    866: */
    867: PetscErrorCode MatZeroRows_SeqSBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max)
    868: {
    869:   PetscInt  i,j,k,row;
    870:   PetscBool flg;

    872:   for (i=0,j=0; i<n; j++) {
    873:     row = idx[i];
    874:     if (row%bs!=0) { /* Not the beginning of a block */
    875:       sizes[j] = 1;
    876:       i++;
    877:     } else if (i+bs > n) { /* Beginning of a block, but complete block doesn't exist (at idx end) */
    878:       sizes[j] = 1;         /* Also makes sure at least 'bs' values exist for next else */
    879:       i++;
    880:     } else { /* Beginning of the block, so check if the complete block exists */
    881:       flg = PETSC_TRUE;
    882:       for (k=1; k<bs; k++) {
    883:         if (row+k != idx[i+k]) { /* break in the block */
    884:           flg = PETSC_FALSE;
    885:           break;
    886:         }
    887:       }
    888:       if (flg) { /* No break in the bs */
    889:         sizes[j] = bs;
    890:         i       += bs;
    891:       } else {
    892:         sizes[j] = 1;
    893:         i++;
    894:       }
    895:     }
    896:   }
    897:   *bs_max = j;
    898:   return 0;
    899: }

    901: /* Only add/insert a(i,j) with i<=j (blocks).
    902:    Any a(i,j) with i>j input by user is ingored.
    903: */

    905: PetscErrorCode MatSetValues_SeqSBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
    906: {
    907:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data;
    908:   PetscInt       *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
    909:   PetscInt       *imax=a->imax,*ai=a->i,*ailen=a->ilen,roworiented=a->roworiented;
    910:   PetscInt       *aj  =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
    911:   PetscInt       ridx,cidx,bs2=a->bs2;
    912:   MatScalar      *ap,value,*aa=a->a,*bap;

    914:   for (k=0; k<m; k++) { /* loop over added rows */
    915:     row  = im[k];       /* row number */
    916:     brow = row/bs;      /* block row number */
    917:     if (row < 0) continue;
    919:     rp   = aj + ai[brow]; /*ptr to beginning of column value of the row block*/
    920:     ap   = aa + bs2*ai[brow]; /*ptr to beginning of element value of the row block*/
    921:     rmax = imax[brow];  /* maximum space allocated for this row */
    922:     nrow = ailen[brow]; /* actual length of this row */
    923:     low  = 0;
    924:     high = nrow;
    925:     for (l=0; l<n; l++) { /* loop over added columns */
    926:       if (in[l] < 0) continue;
    928:       col  = in[l];
    929:       bcol = col/bs;              /* block col number */

    931:       if (brow > bcol) {
    932:         if (a->ignore_ltriangular) continue; /* ignore lower triangular values */
    933:         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)");
    934:       }

    936:       ridx = row % bs; cidx = col % bs; /*row and col index inside the block */
    937:       if ((brow==bcol && ridx<=cidx) || (brow<bcol)) {
    938:         /* element value a(k,l) */
    939:         if (roworiented) value = v[l + k*n];
    940:         else value = v[k + l*m];

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

    946:         lastcol = col;
    947:         while (high-low > 7) {
    948:           t = (low+high)/2;
    949:           if (rp[t] > bcol) high = t;
    950:           else              low  = t;
    951:         }
    952:         for (i=low; i<high; i++) {
    953:           if (rp[i] > bcol) break;
    954:           if (rp[i] == bcol) {
    955:             bap = ap +  bs2*i + bs*cidx + ridx;
    956:             if (is == ADD_VALUES) *bap += value;
    957:             else                  *bap  = value;
    958:             /* for diag block, add/insert its symmetric element a(cidx,ridx) */
    959:             if (brow == bcol && ridx < cidx) {
    960:               bap = ap +  bs2*i + bs*ridx + cidx;
    961:               if (is == ADD_VALUES) *bap += value;
    962:               else                  *bap  = value;
    963:             }
    964:             goto noinsert1;
    965:           }
    966:         }

    968:         if (nonew == 1) goto noinsert1;
    970:         MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);

    972:         N = nrow++ - 1; high++;
    973:         /* shift up all the later entries in this row */
    974:         PetscArraymove(rp+i+1,rp+i,N-i+1);
    975:         PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
    976:         PetscArrayzero(ap+bs2*i,bs2);
    977:         rp[i]                      = bcol;
    978:         ap[bs2*i + bs*cidx + ridx] = value;
    979:         /* for diag block, add/insert its symmetric element a(cidx,ridx) */
    980:         if (brow == bcol && ridx < cidx) {
    981:           ap[bs2*i + bs*ridx + cidx] = value;
    982:         }
    983:         A->nonzerostate++;
    984: noinsert1:;
    985:         low = i;
    986:       }
    987:     }   /* end of loop over added columns */
    988:     ailen[brow] = nrow;
    989:   }   /* end of loop over added rows */
    990:   return 0;
    991: }

    993: PetscErrorCode MatICCFactor_SeqSBAIJ(Mat inA,IS row,const MatFactorInfo *info)
    994: {
    995:   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inA->data;
    996:   Mat            outA;
    997:   PetscBool      row_identity;

    1000:   ISIdentity(row,&row_identity);

    1004:   outA            = inA;
    1005:   inA->factortype = MAT_FACTOR_ICC;
    1006:   PetscFree(inA->solvertype);
    1007:   PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);

    1009:   MatMarkDiagonal_SeqSBAIJ(inA);
    1010:   MatSeqSBAIJSetNumericFactorization_inplace(inA,row_identity);

    1012:   PetscObjectReference((PetscObject)row);
    1013:   ISDestroy(&a->row);
    1014:   a->row = row;
    1015:   PetscObjectReference((PetscObject)row);
    1016:   ISDestroy(&a->col);
    1017:   a->col = row;

    1019:   /* Create the invert permutation so that it can be used in MatCholeskyFactorNumeric() */
    1020:   if (a->icol) ISInvertPermutation(row,PETSC_DECIDE, &a->icol);
    1021:   PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);

    1023:   if (!a->solve_work) {
    1024:     PetscMalloc1(inA->rmap->N+inA->rmap->bs,&a->solve_work);
    1025:     PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));
    1026:   }

    1028:   MatCholeskyFactorNumeric(outA,inA,info);
    1029:   return 0;
    1030: }

    1032: PetscErrorCode  MatSeqSBAIJSetColumnIndices_SeqSBAIJ(Mat mat,PetscInt *indices)
    1033: {
    1034:   Mat_SeqSBAIJ   *baij = (Mat_SeqSBAIJ*)mat->data;
    1035:   PetscInt       i,nz,n;

    1037:   nz = baij->maxnz;
    1038:   n  = mat->cmap->n;
    1039:   for (i=0; i<nz; i++) baij->j[i] = indices[i];

    1041:   baij->nz = nz;
    1042:   for (i=0; i<n; i++) baij->ilen[i] = baij->imax[i];

    1044:   MatSetOption(mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    1045:   return 0;
    1046: }

    1048: /*@
    1049:   MatSeqSBAIJSetColumnIndices - Set the column indices for all the rows
    1050:   in the matrix.

    1052:   Input Parameters:
    1053:   +  mat     - the SeqSBAIJ matrix
    1054:   -  indices - the column indices

    1056:   Level: advanced

    1058:   Notes:
    1059:   This can be called if you have precomputed the nonzero structure of the
    1060:   matrix and want to provide it to the matrix object to improve the performance
    1061:   of the MatSetValues() operation.

    1063:   You MUST have set the correct numbers of nonzeros per row in the call to
    1064:   MatCreateSeqSBAIJ(), and the columns indices MUST be sorted.

    1066:   MUST be called before any calls to MatSetValues()

    1068:   .seealso: MatCreateSeqSBAIJ
    1069: @*/
    1070: PetscErrorCode  MatSeqSBAIJSetColumnIndices(Mat mat,PetscInt *indices)
    1071: {
    1074:   PetscUseMethod(mat,"MatSeqSBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));
    1075:   return 0;
    1076: }

    1078: PetscErrorCode MatCopy_SeqSBAIJ(Mat A,Mat B,MatStructure str)
    1079: {
    1080:   PetscBool      isbaij;

    1082:   PetscObjectTypeCompareAny((PetscObject)B,&isbaij,MATSEQSBAIJ,MATMPISBAIJ,"");
    1084:   /* If the two matrices have the same copy implementation and nonzero pattern, use fast copy. */
    1085:   if (str == SAME_NONZERO_PATTERN && A->ops->copy == B->ops->copy) {
    1086:     Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
    1087:     Mat_SeqSBAIJ *b = (Mat_SeqSBAIJ*)B->data;

    1092:     PetscArraycpy(b->a,a->a,a->bs2*a->i[a->mbs]);
    1093:     PetscObjectStateIncrease((PetscObject)B);
    1094:   } else {
    1095:     MatGetRowUpperTriangular(A);
    1096:     MatCopy_Basic(A,B,str);
    1097:     MatRestoreRowUpperTriangular(A);
    1098:   }
    1099:   return 0;
    1100: }

    1102: PetscErrorCode MatSetUp_SeqSBAIJ(Mat A)
    1103: {
    1104:   MatSeqSBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,NULL);
    1105:   return 0;
    1106: }

    1108: static PetscErrorCode MatSeqSBAIJGetArray_SeqSBAIJ(Mat A,PetscScalar *array[])
    1109: {
    1110:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;

    1112:   *array = a->a;
    1113:   return 0;
    1114: }

    1116: static PetscErrorCode MatSeqSBAIJRestoreArray_SeqSBAIJ(Mat A,PetscScalar *array[])
    1117: {
    1118:   *array = NULL;
    1119:   return 0;
    1120: }

    1122: PetscErrorCode MatAXPYGetPreallocation_SeqSBAIJ(Mat Y,Mat X,PetscInt *nnz)
    1123: {
    1124:   PetscInt       bs = Y->rmap->bs,mbs = Y->rmap->N/bs;
    1125:   Mat_SeqSBAIJ   *x = (Mat_SeqSBAIJ*)X->data;
    1126:   Mat_SeqSBAIJ   *y = (Mat_SeqSBAIJ*)Y->data;

    1128:   /* Set the number of nonzeros in the new matrix */
    1129:   MatAXPYGetPreallocation_SeqX_private(mbs,x->i,x->j,y->i,y->j,nnz);
    1130:   return 0;
    1131: }

    1133: PetscErrorCode MatAXPY_SeqSBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    1134: {
    1135:   Mat_SeqSBAIJ   *x=(Mat_SeqSBAIJ*)X->data, *y=(Mat_SeqSBAIJ*)Y->data;
    1136:   PetscInt       bs=Y->rmap->bs,bs2=bs*bs;
    1137:   PetscBLASInt   one = 1;

    1139:   if (str == UNKNOWN_NONZERO_PATTERN || (PetscDefined(USE_DEBUG) && str == SAME_NONZERO_PATTERN)) {
    1140:     PetscBool e = x->nz == y->nz && x->mbs == y->mbs ? PETSC_TRUE : PETSC_FALSE;
    1141:     if (e) {
    1142:       PetscArraycmp(x->i,y->i,x->mbs+1,&e);
    1143:       if (e) {
    1144:         PetscArraycmp(x->j,y->j,x->i[x->mbs],&e);
    1145:         if (e) str = SAME_NONZERO_PATTERN;
    1146:       }
    1147:     }
    1149:   }
    1150:   if (str == SAME_NONZERO_PATTERN) {
    1151:     PetscScalar  alpha = a;
    1152:     PetscBLASInt bnz;
    1153:     PetscBLASIntCast(x->nz*bs2,&bnz);
    1154:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
    1155:     PetscObjectStateIncrease((PetscObject)Y);
    1156:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
    1157:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
    1158:     MatAXPY_Basic(Y,a,X,str);
    1159:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
    1160:   } else {
    1161:     Mat      B;
    1162:     PetscInt *nnz;
    1164:     MatGetRowUpperTriangular(X);
    1165:     MatGetRowUpperTriangular(Y);
    1166:     PetscMalloc1(Y->rmap->N,&nnz);
    1167:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
    1168:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
    1169:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
    1170:     MatSetBlockSizesFromMats(B,Y,Y);
    1171:     MatSetType(B,((PetscObject)Y)->type_name);
    1172:     MatAXPYGetPreallocation_SeqSBAIJ(Y,X,nnz);
    1173:     MatSeqSBAIJSetPreallocation(B,bs,0,nnz);

    1175:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);

    1177:     MatHeaderMerge(Y,&B);
    1178:     PetscFree(nnz);
    1179:     MatRestoreRowUpperTriangular(X);
    1180:     MatRestoreRowUpperTriangular(Y);
    1181:   }
    1182:   return 0;
    1183: }

    1185: PetscErrorCode MatIsSymmetric_SeqSBAIJ(Mat A,PetscReal tol,PetscBool  *flg)
    1186: {
    1187:   *flg = PETSC_TRUE;
    1188:   return 0;
    1189: }

    1191: PetscErrorCode MatIsStructurallySymmetric_SeqSBAIJ(Mat A,PetscBool  *flg)
    1192: {
    1193:   *flg = PETSC_TRUE;
    1194:   return 0;
    1195: }

    1197: PetscErrorCode MatIsHermitian_SeqSBAIJ(Mat A,PetscReal tol,PetscBool  *flg)
    1198: {
    1199:   *flg = PETSC_FALSE;
    1200:   return 0;
    1201: }

    1203: PetscErrorCode MatConjugate_SeqSBAIJ(Mat A)
    1204: {
    1205: #if defined(PETSC_USE_COMPLEX)
    1206:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
    1207:   PetscInt     i,nz = a->bs2*a->i[a->mbs];
    1208:   MatScalar    *aa = a->a;

    1210:   for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]);
    1211: #else
    1212: #endif
    1213:   return 0;
    1214: }

    1216: PetscErrorCode MatRealPart_SeqSBAIJ(Mat A)
    1217: {
    1218:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
    1219:   PetscInt     i,nz = a->bs2*a->i[a->mbs];
    1220:   MatScalar    *aa = a->a;

    1222:   for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
    1223:   return 0;
    1224: }

    1226: PetscErrorCode MatImaginaryPart_SeqSBAIJ(Mat A)
    1227: {
    1228:   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
    1229:   PetscInt     i,nz = a->bs2*a->i[a->mbs];
    1230:   MatScalar    *aa = a->a;

    1232:   for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
    1233:   return 0;
    1234: }

    1236: PetscErrorCode MatZeroRowsColumns_SeqSBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
    1237: {
    1238:   Mat_SeqSBAIJ      *baij=(Mat_SeqSBAIJ*)A->data;
    1239:   PetscInt          i,j,k,count;
    1240:   PetscInt          bs   =A->rmap->bs,bs2=baij->bs2,row,col;
    1241:   PetscScalar       zero = 0.0;
    1242:   MatScalar         *aa;
    1243:   const PetscScalar *xx;
    1244:   PetscScalar       *bb;
    1245:   PetscBool         *zeroed,vecs = PETSC_FALSE;

    1247:   /* fix right hand side if needed */
    1248:   if (x && b) {
    1249:     VecGetArrayRead(x,&xx);
    1250:     VecGetArray(b,&bb);
    1251:     vecs = PETSC_TRUE;
    1252:   }

    1254:   /* zero the columns */
    1255:   PetscCalloc1(A->rmap->n,&zeroed);
    1256:   for (i=0; i<is_n; i++) {
    1258:     zeroed[is_idx[i]] = PETSC_TRUE;
    1259:   }
    1260:   if (vecs) {
    1261:     for (i=0; i<A->rmap->N; i++) {
    1262:       row = i/bs;
    1263:       for (j=baij->i[row]; j<baij->i[row+1]; j++) {
    1264:         for (k=0; k<bs; k++) {
    1265:           col = bs*baij->j[j] + k;
    1266:           if (col <= i) continue;
    1267:           aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
    1268:           if (!zeroed[i] && zeroed[col]) bb[i]   -= aa[0]*xx[col];
    1269:           if (zeroed[i] && !zeroed[col]) bb[col] -= aa[0]*xx[i];
    1270:         }
    1271:       }
    1272:     }
    1273:     for (i=0; i<is_n; i++) bb[is_idx[i]] = diag*xx[is_idx[i]];
    1274:   }

    1276:   for (i=0; i<A->rmap->N; i++) {
    1277:     if (!zeroed[i]) {
    1278:       row = i/bs;
    1279:       for (j=baij->i[row]; j<baij->i[row+1]; j++) {
    1280:         for (k=0; k<bs; k++) {
    1281:           col = bs*baij->j[j] + k;
    1282:           if (zeroed[col]) {
    1283:             aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
    1284:             aa[0] = 0.0;
    1285:           }
    1286:         }
    1287:       }
    1288:     }
    1289:   }
    1290:   PetscFree(zeroed);
    1291:   if (vecs) {
    1292:     VecRestoreArrayRead(x,&xx);
    1293:     VecRestoreArray(b,&bb);
    1294:   }

    1296:   /* zero the rows */
    1297:   for (i=0; i<is_n; i++) {
    1298:     row   = is_idx[i];
    1299:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
    1300:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
    1301:     for (k=0; k<count; k++) {
    1302:       aa[0] =  zero;
    1303:       aa   += bs;
    1304:     }
    1305:     if (diag != 0.0) {
    1306:       (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);
    1307:     }
    1308:   }
    1309:   MatAssemblyEnd_SeqSBAIJ(A,MAT_FINAL_ASSEMBLY);
    1310:   return 0;
    1311: }

    1313: PetscErrorCode MatShift_SeqSBAIJ(Mat Y,PetscScalar a)
    1314: {
    1315:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)Y->data;

    1317:   if (!Y->preallocated || !aij->nz) {
    1318:     MatSeqSBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL);
    1319:   }
    1320:   MatShift_Basic(Y,a);
    1321:   return 0;
    1322: }

    1324: /* -------------------------------------------------------------------*/
    1325: static struct _MatOps MatOps_Values = {MatSetValues_SeqSBAIJ,
    1326:                                        MatGetRow_SeqSBAIJ,
    1327:                                        MatRestoreRow_SeqSBAIJ,
    1328:                                        MatMult_SeqSBAIJ_N,
    1329:                                /*  4*/ MatMultAdd_SeqSBAIJ_N,
    1330:                                        MatMult_SeqSBAIJ_N,       /* transpose versions are same as non-transpose versions */
    1331:                                        MatMultAdd_SeqSBAIJ_N,
    1332:                                        NULL,
    1333:                                        NULL,
    1334:                                        NULL,
    1335:                                /* 10*/ NULL,
    1336:                                        NULL,
    1337:                                        MatCholeskyFactor_SeqSBAIJ,
    1338:                                        MatSOR_SeqSBAIJ,
    1339:                                        MatTranspose_SeqSBAIJ,
    1340:                                /* 15*/ MatGetInfo_SeqSBAIJ,
    1341:                                        MatEqual_SeqSBAIJ,
    1342:                                        MatGetDiagonal_SeqSBAIJ,
    1343:                                        MatDiagonalScale_SeqSBAIJ,
    1344:                                        MatNorm_SeqSBAIJ,
    1345:                                /* 20*/ NULL,
    1346:                                        MatAssemblyEnd_SeqSBAIJ,
    1347:                                        MatSetOption_SeqSBAIJ,
    1348:                                        MatZeroEntries_SeqSBAIJ,
    1349:                                /* 24*/ NULL,
    1350:                                        NULL,
    1351:                                        NULL,
    1352:                                        NULL,
    1353:                                        NULL,
    1354:                                /* 29*/ MatSetUp_SeqSBAIJ,
    1355:                                        NULL,
    1356:                                        NULL,
    1357:                                        NULL,
    1358:                                        NULL,
    1359:                                /* 34*/ MatDuplicate_SeqSBAIJ,
    1360:                                        NULL,
    1361:                                        NULL,
    1362:                                        NULL,
    1363:                                        MatICCFactor_SeqSBAIJ,
    1364:                                /* 39*/ MatAXPY_SeqSBAIJ,
    1365:                                        MatCreateSubMatrices_SeqSBAIJ,
    1366:                                        MatIncreaseOverlap_SeqSBAIJ,
    1367:                                        MatGetValues_SeqSBAIJ,
    1368:                                        MatCopy_SeqSBAIJ,
    1369:                                /* 44*/ NULL,
    1370:                                        MatScale_SeqSBAIJ,
    1371:                                        MatShift_SeqSBAIJ,
    1372:                                        NULL,
    1373:                                        MatZeroRowsColumns_SeqSBAIJ,
    1374:                                /* 49*/ NULL,
    1375:                                        MatGetRowIJ_SeqSBAIJ,
    1376:                                        MatRestoreRowIJ_SeqSBAIJ,
    1377:                                        NULL,
    1378:                                        NULL,
    1379:                                /* 54*/ NULL,
    1380:                                        NULL,
    1381:                                        NULL,
    1382:                                        MatPermute_SeqSBAIJ,
    1383:                                        MatSetValuesBlocked_SeqSBAIJ,
    1384:                                /* 59*/ MatCreateSubMatrix_SeqSBAIJ,
    1385:                                        NULL,
    1386:                                        NULL,
    1387:                                        NULL,
    1388:                                        NULL,
    1389:                                /* 64*/ NULL,
    1390:                                        NULL,
    1391:                                        NULL,
    1392:                                        NULL,
    1393:                                        NULL,
    1394:                                /* 69*/ MatGetRowMaxAbs_SeqSBAIJ,
    1395:                                        NULL,
    1396:                                        MatConvert_MPISBAIJ_Basic,
    1397:                                        NULL,
    1398:                                        NULL,
    1399:                                /* 74*/ NULL,
    1400:                                        NULL,
    1401:                                        NULL,
    1402:                                        NULL,
    1403:                                        NULL,
    1404:                                /* 79*/ NULL,
    1405:                                        NULL,
    1406:                                        NULL,
    1407:                                        MatGetInertia_SeqSBAIJ,
    1408:                                        MatLoad_SeqSBAIJ,
    1409:                                /* 84*/ MatIsSymmetric_SeqSBAIJ,
    1410:                                        MatIsHermitian_SeqSBAIJ,
    1411:                                        MatIsStructurallySymmetric_SeqSBAIJ,
    1412:                                        NULL,
    1413:                                        NULL,
    1414:                                /* 89*/ NULL,
    1415:                                        NULL,
    1416:                                        NULL,
    1417:                                        NULL,
    1418:                                        NULL,
    1419:                                /* 94*/ NULL,
    1420:                                        NULL,
    1421:                                        NULL,
    1422:                                        NULL,
    1423:                                        NULL,
    1424:                                /* 99*/ NULL,
    1425:                                        NULL,
    1426:                                        NULL,
    1427:                                        MatConjugate_SeqSBAIJ,
    1428:                                        NULL,
    1429:                                /*104*/ NULL,
    1430:                                        MatRealPart_SeqSBAIJ,
    1431:                                        MatImaginaryPart_SeqSBAIJ,
    1432:                                        MatGetRowUpperTriangular_SeqSBAIJ,
    1433:                                        MatRestoreRowUpperTriangular_SeqSBAIJ,
    1434:                                /*109*/ NULL,
    1435:                                        NULL,
    1436:                                        NULL,
    1437:                                        NULL,
    1438:                                        MatMissingDiagonal_SeqSBAIJ,
    1439:                                /*114*/ NULL,
    1440:                                        NULL,
    1441:                                        NULL,
    1442:                                        NULL,
    1443:                                        NULL,
    1444:                                /*119*/ NULL,
    1445:                                        NULL,
    1446:                                        NULL,
    1447:                                        NULL,
    1448:                                        NULL,
    1449:                                /*124*/ NULL,
    1450:                                        NULL,
    1451:                                        NULL,
    1452:                                        NULL,
    1453:                                        NULL,
    1454:                                /*129*/ NULL,
    1455:                                        NULL,
    1456:                                        NULL,
    1457:                                        NULL,
    1458:                                        NULL,
    1459:                                /*134*/ NULL,
    1460:                                        NULL,
    1461:                                        NULL,
    1462:                                        NULL,
    1463:                                        NULL,
    1464:                                /*139*/ MatSetBlockSizes_Default,
    1465:                                        NULL,
    1466:                                        NULL,
    1467:                                        NULL,
    1468:                                        NULL,
    1469:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ,
    1470:                                        NULL,
    1471:                                        NULL,
    1472:                                        NULL
    1473: };

    1475: PetscErrorCode  MatStoreValues_SeqSBAIJ(Mat mat)
    1476: {
    1477:   Mat_SeqSBAIJ   *aij = (Mat_SeqSBAIJ*)mat->data;
    1478:   PetscInt       nz   = aij->i[mat->rmap->N]*mat->rmap->bs*aij->bs2;

    1482:   /* allocate space for values if not already there */
    1483:   if (!aij->saved_values) {
    1484:     PetscMalloc1(nz+1,&aij->saved_values);
    1485:   }

    1487:   /* copy values over */
    1488:   PetscArraycpy(aij->saved_values,aij->a,nz);
    1489:   return 0;
    1490: }

    1492: PetscErrorCode  MatRetrieveValues_SeqSBAIJ(Mat mat)
    1493: {
    1494:   Mat_SeqSBAIJ   *aij = (Mat_SeqSBAIJ*)mat->data;
    1495:   PetscInt       nz = aij->i[mat->rmap->N]*mat->rmap->bs*aij->bs2;

    1500:   /* copy values over */
    1501:   PetscArraycpy(aij->a,aij->saved_values,nz);
    1502:   return 0;
    1503: }

    1505: static PetscErrorCode  MatSeqSBAIJSetPreallocation_SeqSBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz)
    1506: {
    1507:   Mat_SeqSBAIJ   *b = (Mat_SeqSBAIJ*)B->data;
    1508:   PetscInt       i,mbs,nbs,bs2;
    1509:   PetscBool      skipallocation = PETSC_FALSE,flg = PETSC_FALSE,realalloc = PETSC_FALSE;

    1511:   if (nz >= 0 || nnz) realalloc = PETSC_TRUE;

    1513:   MatSetBlockSize(B,PetscAbs(bs));
    1514:   PetscLayoutSetUp(B->rmap);
    1515:   PetscLayoutSetUp(B->cmap);
    1517:   PetscLayoutGetBlockSize(B->rmap,&bs);

    1519:   B->preallocated = PETSC_TRUE;

    1521:   mbs = B->rmap->N/bs;
    1522:   nbs = B->cmap->n/bs;
    1523:   bs2 = bs*bs;

    1527:   if (nz == MAT_SKIP_ALLOCATION) {
    1528:     skipallocation = PETSC_TRUE;
    1529:     nz             = 0;
    1530:   }

    1532:   if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 3;
    1534:   if (nnz) {
    1535:     for (i=0; i<mbs; i++) {
    1538:     }
    1539:   }

    1541:   B->ops->mult             = MatMult_SeqSBAIJ_N;
    1542:   B->ops->multadd          = MatMultAdd_SeqSBAIJ_N;
    1543:   B->ops->multtranspose    = MatMult_SeqSBAIJ_N;
    1544:   B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_N;

    1546:   PetscOptionsGetBool(((PetscObject)B)->options,((PetscObject)B)->prefix,"-mat_no_unroll",&flg,NULL);
    1547:   if (!flg) {
    1548:     switch (bs) {
    1549:     case 1:
    1550:       B->ops->mult             = MatMult_SeqSBAIJ_1;
    1551:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_1;
    1552:       B->ops->multtranspose    = MatMult_SeqSBAIJ_1;
    1553:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_1;
    1554:       break;
    1555:     case 2:
    1556:       B->ops->mult             = MatMult_SeqSBAIJ_2;
    1557:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_2;
    1558:       B->ops->multtranspose    = MatMult_SeqSBAIJ_2;
    1559:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_2;
    1560:       break;
    1561:     case 3:
    1562:       B->ops->mult             = MatMult_SeqSBAIJ_3;
    1563:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_3;
    1564:       B->ops->multtranspose    = MatMult_SeqSBAIJ_3;
    1565:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_3;
    1566:       break;
    1567:     case 4:
    1568:       B->ops->mult             = MatMult_SeqSBAIJ_4;
    1569:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_4;
    1570:       B->ops->multtranspose    = MatMult_SeqSBAIJ_4;
    1571:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_4;
    1572:       break;
    1573:     case 5:
    1574:       B->ops->mult             = MatMult_SeqSBAIJ_5;
    1575:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_5;
    1576:       B->ops->multtranspose    = MatMult_SeqSBAIJ_5;
    1577:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_5;
    1578:       break;
    1579:     case 6:
    1580:       B->ops->mult             = MatMult_SeqSBAIJ_6;
    1581:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_6;
    1582:       B->ops->multtranspose    = MatMult_SeqSBAIJ_6;
    1583:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_6;
    1584:       break;
    1585:     case 7:
    1586:       B->ops->mult             = MatMult_SeqSBAIJ_7;
    1587:       B->ops->multadd          = MatMultAdd_SeqSBAIJ_7;
    1588:       B->ops->multtranspose    = MatMult_SeqSBAIJ_7;
    1589:       B->ops->multtransposeadd = MatMultAdd_SeqSBAIJ_7;
    1590:       break;
    1591:     }
    1592:   }

    1594:   b->mbs = mbs;
    1595:   b->nbs = nbs;
    1596:   if (!skipallocation) {
    1597:     if (!b->imax) {
    1598:       PetscMalloc2(mbs,&b->imax,mbs,&b->ilen);

    1600:       b->free_imax_ilen = PETSC_TRUE;

    1602:       PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));
    1603:     }
    1604:     if (!nnz) {
    1605:       if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
    1606:       else if (nz <= 0) nz = 1;
    1607:       nz = PetscMin(nbs,nz);
    1608:       for (i=0; i<mbs; i++) b->imax[i] = nz;
    1609:       PetscIntMultError(nz,mbs,&nz);
    1610:     } else {
    1611:       PetscInt64 nz64 = 0;
    1612:       for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz64 += nnz[i];}
    1613:       PetscIntCast(nz64,&nz);
    1614:     }
    1615:     /* b->ilen will count nonzeros in each block row so far. */
    1616:     for (i=0; i<mbs; i++) b->ilen[i] = 0;
    1617:     /* nz=(nz+mbs)/2; */ /* total diagonal and superdiagonal nonzero blocks */

    1619:     /* allocate the matrix space */
    1620:     MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);
    1621:     PetscMalloc3(bs2*nz,&b->a,nz,&b->j,B->rmap->N+1,&b->i);
    1622:     PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));
    1623:     PetscArrayzero(b->a,nz*bs2);
    1624:     PetscArrayzero(b->j,nz);

    1626:     b->singlemalloc = PETSC_TRUE;

    1628:     /* pointer to beginning of each row */
    1629:     b->i[0] = 0;
    1630:     for (i=1; i<mbs+1; i++) b->i[i] = b->i[i-1] + b->imax[i-1];

    1632:     b->free_a  = PETSC_TRUE;
    1633:     b->free_ij = PETSC_TRUE;
    1634:   } else {
    1635:     b->free_a  = PETSC_FALSE;
    1636:     b->free_ij = PETSC_FALSE;
    1637:   }

    1639:   b->bs2     = bs2;
    1640:   b->nz      = 0;
    1641:   b->maxnz   = nz;
    1642:   b->inew    = NULL;
    1643:   b->jnew    = NULL;
    1644:   b->anew    = NULL;
    1645:   b->a2anew  = NULL;
    1646:   b->permute = PETSC_FALSE;

    1648:   B->was_assembled = PETSC_FALSE;
    1649:   B->assembled     = PETSC_FALSE;
    1650:   if (realalloc) MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
    1651:   return 0;
    1652: }

    1654: PetscErrorCode MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[], const PetscScalar V[])
    1655: {
    1656:   PetscInt       i,j,m,nz,anz, nz_max=0,*nnz;
    1657:   PetscScalar    *values=NULL;
    1658:   PetscBool      roworiented = ((Mat_SeqSBAIJ*)B->data)->roworiented;

    1661:   PetscLayoutSetBlockSize(B->rmap,bs);
    1662:   PetscLayoutSetBlockSize(B->cmap,bs);
    1663:   PetscLayoutSetUp(B->rmap);
    1664:   PetscLayoutSetUp(B->cmap);
    1665:   PetscLayoutGetBlockSize(B->rmap,&bs);
    1666:   m      = B->rmap->n/bs;

    1669:   PetscMalloc1(m+1,&nnz);
    1670:   for (i=0; i<m; i++) {
    1671:     nz = ii[i+1] - ii[i];
    1673:     anz = 0;
    1674:     for (j=0; j<nz; j++) {
    1675:       /* count only values on the diagonal or above */
    1676:       if (jj[ii[i] + j] >= i) {
    1677:         anz = nz - j;
    1678:         break;
    1679:       }
    1680:     }
    1681:     nz_max = PetscMax(nz_max,anz);
    1682:     nnz[i] = anz;
    1683:   }
    1684:   MatSeqSBAIJSetPreallocation(B,bs,0,nnz);
    1685:   PetscFree(nnz);

    1687:   values = (PetscScalar*)V;
    1688:   if (!values) {
    1689:     PetscCalloc1(bs*bs*nz_max,&values);
    1690:   }
    1691:   for (i=0; i<m; i++) {
    1692:     PetscInt          ncols  = ii[i+1] - ii[i];
    1693:     const PetscInt    *icols = jj + ii[i];
    1694:     if (!roworiented || bs == 1) {
    1695:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    1696:       MatSetValuesBlocked_SeqSBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);
    1697:     } else {
    1698:       for (j=0; j<ncols; j++) {
    1699:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
    1700:         MatSetValuesBlocked_SeqSBAIJ(B,1,&i,1,&icols[j],svals,INSERT_VALUES);
    1701:       }
    1702:     }
    1703:   }
    1704:   if (!V) PetscFree(values);
    1705:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    1706:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    1707:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    1708:   return 0;
    1709: }

    1711: /*
    1712:    This is used to set the numeric factorization for both Cholesky and ICC symbolic factorization
    1713: */
    1714: PetscErrorCode MatSeqSBAIJSetNumericFactorization_inplace(Mat B,PetscBool natural)
    1715: {
    1716:   PetscBool      flg = PETSC_FALSE;
    1717:   PetscInt       bs  = B->rmap->bs;

    1719:   PetscOptionsGetBool(((PetscObject)B)->options,((PetscObject)B)->prefix,"-mat_no_unroll",&flg,NULL);
    1720:   if (flg) bs = 8;

    1722:   if (!natural) {
    1723:     switch (bs) {
    1724:     case 1:
    1725:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace;
    1726:       break;
    1727:     case 2:
    1728:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2;
    1729:       break;
    1730:     case 3:
    1731:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3;
    1732:       break;
    1733:     case 4:
    1734:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4;
    1735:       break;
    1736:     case 5:
    1737:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5;
    1738:       break;
    1739:     case 6:
    1740:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6;
    1741:       break;
    1742:     case 7:
    1743:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7;
    1744:       break;
    1745:     default:
    1746:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N;
    1747:       break;
    1748:     }
    1749:   } else {
    1750:     switch (bs) {
    1751:     case 1:
    1752:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace;
    1753:       break;
    1754:     case 2:
    1755:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
    1756:       break;
    1757:     case 3:
    1758:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
    1759:       break;
    1760:     case 4:
    1761:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
    1762:       break;
    1763:     case 5:
    1764:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
    1765:       break;
    1766:     case 6:
    1767:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
    1768:       break;
    1769:     case 7:
    1770:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
    1771:       break;
    1772:     default:
    1773:       B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
    1774:       break;
    1775:     }
    1776:   }
    1777:   return 0;
    1778: }

    1780: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);
    1781: PETSC_INTERN PetscErrorCode MatConvert_SeqSBAIJ_SeqBAIJ(Mat,MatType,MatReuse,Mat*);
    1782: static PetscErrorCode MatFactorGetSolverType_petsc(Mat A,MatSolverType *type)
    1783: {
    1784:   *type = MATSOLVERPETSC;
    1785:   return 0;
    1786: }

    1788: PETSC_INTERN PetscErrorCode MatGetFactor_seqsbaij_petsc(Mat A,MatFactorType ftype,Mat *B)
    1789: {
    1790:   PetscInt       n = A->rmap->n;

    1792: #if defined(PETSC_USE_COMPLEX)
    1794: #endif

    1796:   MatCreate(PetscObjectComm((PetscObject)A),B);
    1797:   MatSetSizes(*B,n,n,n,n);
    1798:   if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
    1799:     MatSetType(*B,MATSEQSBAIJ);
    1800:     MatSeqSBAIJSetPreallocation(*B,A->rmap->bs,MAT_SKIP_ALLOCATION,NULL);

    1802:     (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ;
    1803:     (*B)->ops->iccfactorsymbolic      = MatICCFactorSymbolic_SeqSBAIJ;
    1804:     PetscStrallocpy(MATORDERINGNATURAL,(char**)&(*B)->preferredordering[MAT_FACTOR_CHOLESKY]);
    1805:     PetscStrallocpy(MATORDERINGNATURAL,(char**)&(*B)->preferredordering[MAT_FACTOR_ICC]);
    1806:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");

    1808:   (*B)->factortype = ftype;
    1809:   (*B)->canuseordering = PETSC_TRUE;
    1810:   PetscFree((*B)->solvertype);
    1811:   PetscStrallocpy(MATSOLVERPETSC,&(*B)->solvertype);
    1812:   PetscObjectComposeFunction((PetscObject)*B,"MatFactorGetSolverType_C",MatFactorGetSolverType_petsc);
    1813:   return 0;
    1814: }

    1816: /*@C
    1817:    MatSeqSBAIJGetArray - gives access to the array where the data for a MATSEQSBAIJ matrix is stored

    1819:    Not Collective

    1821:    Input Parameter:
    1822: .  mat - a MATSEQSBAIJ matrix

    1824:    Output Parameter:
    1825: .   array - pointer to the data

    1827:    Level: intermediate

    1829: .seealso: MatSeqSBAIJRestoreArray(), MatSeqAIJGetArray(), MatSeqAIJRestoreArray()
    1830: @*/
    1831: PetscErrorCode  MatSeqSBAIJGetArray(Mat A,PetscScalar **array)
    1832: {
    1833:   PetscUseMethod(A,"MatSeqSBAIJGetArray_C",(Mat,PetscScalar**),(A,array));
    1834:   return 0;
    1835: }

    1837: /*@C
    1838:    MatSeqSBAIJRestoreArray - returns access to the array where the data for a MATSEQSBAIJ matrix is stored obtained by MatSeqSBAIJGetArray()

    1840:    Not Collective

    1842:    Input Parameters:
    1843: +  mat - a MATSEQSBAIJ matrix
    1844: -  array - pointer to the data

    1846:    Level: intermediate

    1848: .seealso: MatSeqSBAIJGetArray(), MatSeqAIJGetArray(), MatSeqAIJRestoreArray()
    1849: @*/
    1850: PetscErrorCode  MatSeqSBAIJRestoreArray(Mat A,PetscScalar **array)
    1851: {
    1852:   PetscUseMethod(A,"MatSeqSBAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));
    1853:   return 0;
    1854: }

    1856: /*MC
    1857:   MATSEQSBAIJ - MATSEQSBAIJ = "seqsbaij" - A matrix type to be used for sequential symmetric block sparse matrices,
    1858:   based on block compressed sparse row format.  Only the upper triangular portion of the matrix is stored.

    1860:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
    1861:   can call MatSetOption(Mat, MAT_HERMITIAN).

    1863:   Options Database Keys:
    1864:   . -mat_type seqsbaij - sets the matrix type to "seqsbaij" during a call to MatSetFromOptions()

    1866:   Notes:
    1867:     By default if you insert values into the lower triangular part of the matrix they are simply ignored (since they are not
    1868:      stored and it is assumed they symmetric to the upper triangular). If you call MatSetOption(Mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_FALSE) or use
    1869:      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.

    1871:     The number of rows in the matrix must be less than or equal to the number of columns

    1873:   Level: beginner

    1875:   .seealso: MatCreateSeqSBAIJ(), MatType, MATMPISBAIJ
    1876: M*/
    1877: PETSC_EXTERN PetscErrorCode MatCreate_SeqSBAIJ(Mat B)
    1878: {
    1879:   Mat_SeqSBAIJ   *b;
    1881:   PetscMPIInt    size;
    1882:   PetscBool      no_unroll = PETSC_FALSE,no_inode = PETSC_FALSE;

    1884:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);

    1887:   PetscNewLog(B,&b);
    1888:   B->data = (void*)b;
    1889:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

    1891:   B->ops->destroy    = MatDestroy_SeqSBAIJ;
    1892:   B->ops->view       = MatView_SeqSBAIJ;
    1893:   b->row             = NULL;
    1894:   b->icol            = NULL;
    1895:   b->reallocs        = 0;
    1896:   b->saved_values    = NULL;
    1897:   b->inode.limit     = 5;
    1898:   b->inode.max_limit = 5;

    1900:   b->roworiented        = PETSC_TRUE;
    1901:   b->nonew              = 0;
    1902:   b->diag               = NULL;
    1903:   b->solve_work         = NULL;
    1904:   b->mult_work          = NULL;
    1905:   B->spptr              = NULL;
    1906:   B->info.nz_unneeded   = (PetscReal)b->maxnz*b->bs2;
    1907:   b->keepnonzeropattern = PETSC_FALSE;

    1909:   b->inew    = NULL;
    1910:   b->jnew    = NULL;
    1911:   b->anew    = NULL;
    1912:   b->a2anew  = NULL;
    1913:   b->permute = PETSC_FALSE;

    1915:   b->ignore_ltriangular = PETSC_TRUE;

    1917:   PetscOptionsGetBool(((PetscObject)B)->options,((PetscObject)B)->prefix,"-mat_ignore_lower_triangular",&b->ignore_ltriangular,NULL);

    1919:   b->getrow_utriangular = PETSC_FALSE;

    1921:   PetscOptionsGetBool(((PetscObject)B)->options,((PetscObject)B)->prefix,"-mat_getrow_uppertriangular",&b->getrow_utriangular,NULL);

    1923:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSBAIJGetArray_C",MatSeqSBAIJGetArray_SeqSBAIJ);
    1924:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSBAIJRestoreArray_C",MatSeqSBAIJRestoreArray_SeqSBAIJ);
    1925:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqSBAIJ);
    1926:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqSBAIJ);
    1927:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSBAIJSetColumnIndices_C",MatSeqSBAIJSetColumnIndices_SeqSBAIJ);
    1928:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqsbaij_seqaij_C",MatConvert_SeqSBAIJ_SeqAIJ);
    1929:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqsbaij_seqbaij_C",MatConvert_SeqSBAIJ_SeqBAIJ);
    1930:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSBAIJSetPreallocation_C",MatSeqSBAIJSetPreallocation_SeqSBAIJ);
    1931:   PetscObjectComposeFunction((PetscObject)B,"MatSeqSBAIJSetPreallocationCSR_C",MatSeqSBAIJSetPreallocationCSR_SeqSBAIJ);
    1932: #if defined(PETSC_HAVE_ELEMENTAL)
    1933:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqsbaij_elemental_C",MatConvert_SeqSBAIJ_Elemental);
    1934: #endif
    1935: #if defined(PETSC_HAVE_SCALAPACK)
    1936:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqsbaij_scalapack_C",MatConvert_SBAIJ_ScaLAPACK);
    1937: #endif

    1939:   B->symmetric                  = PETSC_TRUE;
    1940:   B->structurally_symmetric     = PETSC_TRUE;
    1941:   B->symmetric_set              = PETSC_TRUE;
    1942:   B->structurally_symmetric_set = PETSC_TRUE;
    1943:   B->symmetric_eternal          = PETSC_TRUE;
    1944: #if defined(PETSC_USE_COMPLEX)
    1945:   B->hermitian                  = PETSC_FALSE;
    1946:   B->hermitian_set              = PETSC_FALSE;
    1947: #else
    1948:   B->hermitian                  = PETSC_TRUE;
    1949:   B->hermitian_set              = PETSC_TRUE;
    1950: #endif

    1952:   PetscObjectChangeTypeName((PetscObject)B,MATSEQSBAIJ);

    1954:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),((PetscObject)B)->prefix,"Options for SEQSBAIJ matrix","Mat");
    1955:   PetscOptionsBool("-mat_no_unroll","Do not optimize for inodes (slower)",NULL,no_unroll,&no_unroll,NULL);
    1956:   if (no_unroll) {
    1957:     PetscInfo(B,"Not using Inode routines due to -mat_no_unroll\n");
    1958:   }
    1959:   PetscOptionsBool("-mat_no_inode","Do not optimize for inodes (slower)",NULL,no_inode,&no_inode,NULL);
    1960:   if (no_inode) PetscInfo(B,"Not using Inode routines due to -mat_no_inode\n");
    1961:   PetscOptionsInt("-mat_inode_limit","Do not use inodes larger then this value",NULL,b->inode.limit,&b->inode.limit,NULL);
    1962:   PetscOptionsEnd();
    1963:   b->inode.use = (PetscBool)(!(no_unroll || no_inode));
    1964:   if (b->inode.limit > b->inode.max_limit) b->inode.limit = b->inode.max_limit;
    1965:   return 0;
    1966: }

    1968: /*@C
    1969:    MatSeqSBAIJSetPreallocation - Creates a sparse symmetric matrix in block AIJ (block
    1970:    compressed row) format.  For good matrix assembly performance the
    1971:    user should preallocate the matrix storage by setting the parameter nz
    1972:    (or the array nnz).  By setting these parameters accurately, performance
    1973:    during matrix assembly can be increased by more than a factor of 50.

    1975:    Collective on Mat

    1977:    Input Parameters:
    1978: +  B - the symmetric matrix
    1979: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    1980:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    1981: .  nz - number of block nonzeros per block row (same for all rows)
    1982: -  nnz - array containing the number of block nonzeros in the upper triangular plus
    1983:          diagonal portion of each block (possibly different for each block row) or NULL

    1985:    Options Database Keys:
    1986: +   -mat_no_unroll - uses code that does not unroll the loops in the
    1987:                      block calculations (much slower)
    1988: -   -mat_block_size - size of the blocks to use (only works if a negative bs is passed in

    1990:    Level: intermediate

    1992:    Notes:
    1993:    Specify the preallocated storage with either nz or nnz (not both).
    1994:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
    1995:    allocation.  See Users-Manual: ch_mat for details.

    1997:    You can call MatGetInfo() to get information on how effective the preallocation was;
    1998:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    1999:    You can also run with the option -info and look for messages with the string
    2000:    malloc in them to see if additional memory allocation was needed.

    2002:    If the nnz parameter is given then the nz parameter is ignored

    2004: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateSBAIJ()
    2005: @*/
    2006: PetscErrorCode  MatSeqSBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
    2007: {
    2011:   PetscTryMethod(B,"MatSeqSBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));
    2012:   return 0;
    2013: }

    2015: /*@C
    2016:    MatSeqSBAIJSetPreallocationCSR - Creates a sparse parallel matrix in SBAIJ format using the given nonzero structure and (optional) numerical values

    2018:    Input Parameters:
    2019: +  B - the matrix
    2020: .  bs - size of block, the blocks are ALWAYS square.
    2021: .  i - the indices into j for the start of each local row (starts with zero)
    2022: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    2023: -  v - optional values in the matrix

    2025:    Level: advanced

    2027:    Notes:
    2028:    The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
    2029:    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
    2030:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
    2031:    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
    2032:    block column and the second index is over columns within a block.

    2034:    Any entries below the diagonal are ignored

    2036:    Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
    2037:    and usually the numerical values as well

    2039: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValuesBlocked(), MatSeqSBAIJSetPreallocation(), MATSEQSBAIJ
    2040: @*/
    2041: PetscErrorCode MatSeqSBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    2042: {
    2046:   PetscTryMethod(B,"MatSeqSBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    2047:   return 0;
    2048: }

    2050: /*@C
    2051:    MatCreateSeqSBAIJ - Creates a sparse symmetric matrix in block AIJ (block
    2052:    compressed row) format.  For good matrix assembly performance the
    2053:    user should preallocate the matrix storage by setting the parameter nz
    2054:    (or the array nnz).  By setting these parameters accurately, performance
    2055:    during matrix assembly can be increased by more than a factor of 50.

    2057:    Collective

    2059:    Input Parameters:
    2060: +  comm - MPI communicator, set to PETSC_COMM_SELF
    2061: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    2062:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    2063: .  m - number of rows, or number of columns
    2064: .  nz - number of block nonzeros per block row (same for all rows)
    2065: -  nnz - array containing the number of block nonzeros in the upper triangular plus
    2066:          diagonal portion of each block (possibly different for each block row) or NULL

    2068:    Output Parameter:
    2069: .  A - the symmetric matrix

    2071:    Options Database Keys:
    2072: +   -mat_no_unroll - uses code that does not unroll the loops in the
    2073:                      block calculations (much slower)
    2074: -   -mat_block_size - size of the blocks to use

    2076:    Level: intermediate

    2078:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    2079:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
    2080:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    2082:    Notes:
    2083:    The number of rows and columns must be divisible by blocksize.
    2084:    This matrix type does not support complex Hermitian operation.

    2086:    Specify the preallocated storage with either nz or nnz (not both).
    2087:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
    2088:    allocation.  See Users-Manual: ch_mat for details.

    2090:    If the nnz parameter is given then the nz parameter is ignored

    2092: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateSBAIJ()
    2093: @*/
    2094: PetscErrorCode  MatCreateSeqSBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A)
    2095: {
    2096:   MatCreate(comm,A);
    2097:   MatSetSizes(*A,m,n,m,n);
    2098:   MatSetType(*A,MATSEQSBAIJ);
    2099:   MatSeqSBAIJSetPreallocation(*A,bs,nz,(PetscInt*)nnz);
    2100:   return 0;
    2101: }

    2103: PetscErrorCode MatDuplicate_SeqSBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B)
    2104: {
    2105:   Mat            C;
    2106:   Mat_SeqSBAIJ   *c,*a = (Mat_SeqSBAIJ*)A->data;
    2107:   PetscInt       i,mbs = a->mbs,nz = a->nz,bs2 =a->bs2;

    2111:   *B   = NULL;
    2112:   MatCreate(PetscObjectComm((PetscObject)A),&C);
    2113:   MatSetSizes(C,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);
    2114:   MatSetBlockSizesFromMats(C,A,A);
    2115:   MatSetType(C,MATSEQSBAIJ);
    2116:   c    = (Mat_SeqSBAIJ*)C->data;

    2118:   C->preallocated       = PETSC_TRUE;
    2119:   C->factortype         = A->factortype;
    2120:   c->row                = NULL;
    2121:   c->icol               = NULL;
    2122:   c->saved_values       = NULL;
    2123:   c->keepnonzeropattern = a->keepnonzeropattern;
    2124:   C->assembled          = PETSC_TRUE;

    2126:   PetscLayoutReference(A->rmap,&C->rmap);
    2127:   PetscLayoutReference(A->cmap,&C->cmap);
    2128:   c->bs2 = a->bs2;
    2129:   c->mbs = a->mbs;
    2130:   c->nbs = a->nbs;

    2132:   if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    2133:     c->imax           = a->imax;
    2134:     c->ilen           = a->ilen;
    2135:     c->free_imax_ilen = PETSC_FALSE;
    2136:   } else {
    2137:     PetscMalloc2((mbs+1),&c->imax,(mbs+1),&c->ilen);
    2138:     PetscLogObjectMemory((PetscObject)C,2*(mbs+1)*sizeof(PetscInt));
    2139:     for (i=0; i<mbs; i++) {
    2140:       c->imax[i] = a->imax[i];
    2141:       c->ilen[i] = a->ilen[i];
    2142:     }
    2143:     c->free_imax_ilen = PETSC_TRUE;
    2144:   }

    2146:   /* allocate the matrix space */
    2147:   if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    2148:     PetscMalloc1(bs2*nz,&c->a);
    2149:     PetscLogObjectMemory((PetscObject)C,nz*bs2*sizeof(MatScalar));
    2150:     c->i            = a->i;
    2151:     c->j            = a->j;
    2152:     c->singlemalloc = PETSC_FALSE;
    2153:     c->free_a       = PETSC_TRUE;
    2154:     c->free_ij      = PETSC_FALSE;
    2155:     c->parent       = A;
    2156:     PetscObjectReference((PetscObject)A);
    2157:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    2158:     MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    2159:   } else {
    2160:     PetscMalloc3(bs2*nz,&c->a,nz,&c->j,mbs+1,&c->i);
    2161:     PetscArraycpy(c->i,a->i,mbs+1);
    2162:     PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt) + nz*(bs2*sizeof(MatScalar) + sizeof(PetscInt)));
    2163:     c->singlemalloc = PETSC_TRUE;
    2164:     c->free_a       = PETSC_TRUE;
    2165:     c->free_ij      = PETSC_TRUE;
    2166:   }
    2167:   if (mbs > 0) {
    2168:     if (cpvalues != MAT_SHARE_NONZERO_PATTERN) {
    2169:       PetscArraycpy(c->j,a->j,nz);
    2170:     }
    2171:     if (cpvalues == MAT_COPY_VALUES) {
    2172:       PetscArraycpy(c->a,a->a,bs2*nz);
    2173:     } else {
    2174:       PetscArrayzero(c->a,bs2*nz);
    2175:     }
    2176:     if (a->jshort) {
    2177:       /* cannot share jshort, it is reallocated in MatAssemblyEnd_SeqSBAIJ() */
    2178:       /* if the parent matrix is reassembled, this child matrix will never notice */
    2179:       PetscMalloc1(nz,&c->jshort);
    2180:       PetscLogObjectMemory((PetscObject)C,nz*sizeof(unsigned short));
    2181:       PetscArraycpy(c->jshort,a->jshort,nz);

    2183:       c->free_jshort = PETSC_TRUE;
    2184:     }
    2185:   }

    2187:   c->roworiented = a->roworiented;
    2188:   c->nonew       = a->nonew;

    2190:   if (a->diag) {
    2191:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
    2192:       c->diag      = a->diag;
    2193:       c->free_diag = PETSC_FALSE;
    2194:     } else {
    2195:       PetscMalloc1(mbs,&c->diag);
    2196:       PetscLogObjectMemory((PetscObject)C,mbs*sizeof(PetscInt));
    2197:       for (i=0; i<mbs; i++) c->diag[i] = a->diag[i];
    2198:       c->free_diag = PETSC_TRUE;
    2199:     }
    2200:   }
    2201:   c->nz         = a->nz;
    2202:   c->maxnz      = a->nz; /* Since we allocate exactly the right amount */
    2203:   c->solve_work = NULL;
    2204:   c->mult_work  = NULL;

    2206:   *B   = C;
    2207:   PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
    2208:   return 0;
    2209: }

    2211: /* Used for both SeqBAIJ and SeqSBAIJ matrices */
    2212: #define MatLoad_SeqSBAIJ_Binary MatLoad_SeqBAIJ_Binary

    2214: PetscErrorCode MatLoad_SeqSBAIJ(Mat mat,PetscViewer viewer)
    2215: {
    2216:   PetscBool      isbinary;

    2218:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    2220:   MatLoad_SeqSBAIJ_Binary(mat,viewer);
    2221:   return 0;
    2222: }

    2224: /*@
    2225:      MatCreateSeqSBAIJWithArrays - Creates an sequential SBAIJ matrix using matrix elements
    2226:               (upper triangular entries in CSR format) provided by the user.

    2228:      Collective

    2230:    Input Parameters:
    2231: +  comm - must be an MPI communicator of size 1
    2232: .  bs - size of block
    2233: .  m - number of rows
    2234: .  n - number of columns
    2235: .  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
    2236: .  j - column indices
    2237: -  a - matrix values

    2239:    Output Parameter:
    2240: .  mat - the matrix

    2242:    Level: advanced

    2244:    Notes:
    2245:        The i, j, and a arrays are not copied by this routine, the user must free these arrays
    2246:     once the matrix is destroyed

    2248:        You cannot set new nonzero locations into this matrix, that will generate an error.

    2250:        The i and j indices are 0 based

    2252:        When block size is greater than 1 the matrix values must be stored using the SBAIJ storage format (see the SBAIJ code to determine this). For block size of 1
    2253:        it is the regular CSR format excluding the lower triangular elements.

    2255: .seealso: MatCreate(), MatCreateSBAIJ(), MatCreateSeqSBAIJ()

    2257: @*/
    2258: PetscErrorCode  MatCreateSeqSBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat)
    2259: {
    2260:   PetscInt       ii;
    2261:   Mat_SeqSBAIJ   *sbaij;

    2266:   MatCreate(comm,mat);
    2267:   MatSetSizes(*mat,m,n,m,n);
    2268:   MatSetType(*mat,MATSEQSBAIJ);
    2269:   MatSeqSBAIJSetPreallocation(*mat,bs,MAT_SKIP_ALLOCATION,NULL);
    2270:   sbaij = (Mat_SeqSBAIJ*)(*mat)->data;
    2271:   PetscMalloc2(m,&sbaij->imax,m,&sbaij->ilen);
    2272:   PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));

    2274:   sbaij->i = i;
    2275:   sbaij->j = j;
    2276:   sbaij->a = a;

    2278:   sbaij->singlemalloc   = PETSC_FALSE;
    2279:   sbaij->nonew          = -1;             /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
    2280:   sbaij->free_a         = PETSC_FALSE;
    2281:   sbaij->free_ij        = PETSC_FALSE;
    2282:   sbaij->free_imax_ilen = PETSC_TRUE;

    2284:   for (ii=0; ii<m; ii++) {
    2285:     sbaij->ilen[ii] = sbaij->imax[ii] = i[ii+1] - i[ii];
    2287:   }
    2288:   if (PetscDefined(USE_DEBUG)) {
    2289:     for (ii=0; ii<sbaij->i[m]; ii++) {
    2292:     }
    2293:   }

    2295:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
    2296:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
    2297:   return 0;
    2298: }

    2300: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqSBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    2301: {
    2302:   PetscMPIInt    size;

    2304:   MPI_Comm_size(comm,&size);
    2305:   if (size == 1 && scall == MAT_REUSE_MATRIX) {
    2306:     MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);
    2307:   } else {
    2308:     MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(comm,inmat,n,scall,outmat);
    2309:   }
    2310:   return 0;
    2311: }