Actual source code: blockmat.c
petsc-3.10.5 2019-03-28
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      2: /*
      3:    This provides a matrix that consists of Mats
      4: */

      6:  #include <petsc/private/matimpl.h>
      7: #include <../src/mat/impls/baij/seq/baij.h>    /* use the common AIJ data-structure */

      9: typedef struct {
     10:   SEQAIJHEADER(Mat);
     11:   SEQBAIJHEADER;
     12:   Mat *diags;

     14:   Vec left,right,middle,workb;                 /* dummy vectors to perform local parts of product */
     15: } Mat_BlockMat;

     17: extern PetscErrorCode  MatBlockMatSetPreallocation(Mat,PetscInt,PetscInt,const PetscInt*);

     19: static PetscErrorCode MatSOR_BlockMat_Symmetric(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
     20: {
     21:   Mat_BlockMat      *a = (Mat_BlockMat*)A->data;
     22:   PetscScalar       *x;
     23:   const Mat         *v;
     24:   const PetscScalar *b;
     25:   PetscErrorCode    ierr;
     26:   PetscInt          n = A->cmap->n,i,mbs = n/A->rmap->bs,j,bs = A->rmap->bs;
     27:   const PetscInt    *idx;
     28:   IS                row,col;
     29:   MatFactorInfo     info;
     30:   Vec               left = a->left,right = a->right, middle = a->middle;
     31:   Mat               *diag;

     34:   its = its*lits;
     35:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
     36:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");
     37:   if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for omega not equal to 1.0");
     38:   if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for fshift");
     39:   if ((flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) && !(flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP)) {
     40:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot do backward sweep without forward sweep");
     41:   }

     43:   if (!a->diags) {
     44:     PetscMalloc1(mbs,&a->diags);
     45:     MatFactorInfoInitialize(&info);
     46:     for (i=0; i<mbs; i++) {
     47:       MatGetOrdering(a->a[a->diag[i]], MATORDERINGND,&row,&col);
     48:       MatCholeskyFactorSymbolic(a->diags[i],a->a[a->diag[i]],row,&info);
     49:       MatCholeskyFactorNumeric(a->diags[i],a->a[a->diag[i]],&info);
     50:       ISDestroy(&row);
     51:       ISDestroy(&col);
     52:     }
     53:     VecDuplicate(bb,&a->workb);
     54:   }
     55:   diag = a->diags;

     57:   VecSet(xx,0.0);
     58:   VecGetArray(xx,&x);
     59:   /* copy right hand side because it must be modified during iteration */
     60:   VecCopy(bb,a->workb);
     61:   VecGetArrayRead(a->workb,&b);

     63:   /* need to add code for when initial guess is zero, see MatSOR_SeqAIJ */
     64:   while (its--) {
     65:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {

     67:       for (i=0; i<mbs; i++) {
     68:         n   = a->i[i+1] - a->i[i] - 1;
     69:         idx = a->j + a->i[i] + 1;
     70:         v   = a->a + a->i[i] + 1;

     72:         VecSet(left,0.0);
     73:         for (j=0; j<n; j++) {
     74:           VecPlaceArray(right,x + idx[j]*bs);
     75:           MatMultAdd(v[j],right,left,left);
     76:           VecResetArray(right);
     77:         }
     78:         VecPlaceArray(right,b + i*bs);
     79:         VecAYPX(left,-1.0,right);
     80:         VecResetArray(right);

     82:         VecPlaceArray(right,x + i*bs);
     83:         MatSolve(diag[i],left,right);

     85:         /* now adjust right hand side, see MatSOR_SeqSBAIJ */
     86:         for (j=0; j<n; j++) {
     87:           MatMultTranspose(v[j],right,left);
     88:           VecPlaceArray(middle,b + idx[j]*bs);
     89:           VecAXPY(middle,-1.0,left);
     90:           VecResetArray(middle);
     91:         }
     92:         VecResetArray(right);

     94:       }
     95:     }
     96:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {

     98:       for (i=mbs-1; i>=0; i--) {
     99:         n   = a->i[i+1] - a->i[i] - 1;
    100:         idx = a->j + a->i[i] + 1;
    101:         v   = a->a + a->i[i] + 1;

    103:         VecSet(left,0.0);
    104:         for (j=0; j<n; j++) {
    105:           VecPlaceArray(right,x + idx[j]*bs);
    106:           MatMultAdd(v[j],right,left,left);
    107:           VecResetArray(right);
    108:         }
    109:         VecPlaceArray(right,b + i*bs);
    110:         VecAYPX(left,-1.0,right);
    111:         VecResetArray(right);

    113:         VecPlaceArray(right,x + i*bs);
    114:         MatSolve(diag[i],left,right);
    115:         VecResetArray(right);

    117:       }
    118:     }
    119:   }
    120:   VecRestoreArray(xx,&x);
    121:   VecRestoreArrayRead(a->workb,&b);
    122:   return(0);
    123: }

    125: static PetscErrorCode MatSOR_BlockMat(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    126: {
    127:   Mat_BlockMat      *a = (Mat_BlockMat*)A->data;
    128:   PetscScalar       *x;
    129:   const Mat         *v;
    130:   const PetscScalar *b;
    131:   PetscErrorCode    ierr;
    132:   PetscInt          n = A->cmap->n,i,mbs = n/A->rmap->bs,j,bs = A->rmap->bs;
    133:   const PetscInt    *idx;
    134:   IS                row,col;
    135:   MatFactorInfo     info;
    136:   Vec               left = a->left,right = a->right;
    137:   Mat               *diag;

    140:   its = its*lits;
    141:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
    142:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");
    143:   if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for omega not equal to 1.0");
    144:   if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for fshift");

    146:   if (!a->diags) {
    147:     PetscMalloc1(mbs,&a->diags);
    148:     MatFactorInfoInitialize(&info);
    149:     for (i=0; i<mbs; i++) {
    150:       MatGetOrdering(a->a[a->diag[i]], MATORDERINGND,&row,&col);
    151:       MatLUFactorSymbolic(a->diags[i],a->a[a->diag[i]],row,col,&info);
    152:       MatLUFactorNumeric(a->diags[i],a->a[a->diag[i]],&info);
    153:       ISDestroy(&row);
    154:       ISDestroy(&col);
    155:     }
    156:   }
    157:   diag = a->diags;

    159:   VecSet(xx,0.0);
    160:   VecGetArray(xx,&x);
    161:   VecGetArrayRead(bb,&b);

    163:   /* need to add code for when initial guess is zero, see MatSOR_SeqAIJ */
    164:   while (its--) {
    165:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {

    167:       for (i=0; i<mbs; i++) {
    168:         n   = a->i[i+1] - a->i[i];
    169:         idx = a->j + a->i[i];
    170:         v   = a->a + a->i[i];

    172:         VecSet(left,0.0);
    173:         for (j=0; j<n; j++) {
    174:           if (idx[j] != i) {
    175:             VecPlaceArray(right,x + idx[j]*bs);
    176:             MatMultAdd(v[j],right,left,left);
    177:             VecResetArray(right);
    178:           }
    179:         }
    180:         VecPlaceArray(right,b + i*bs);
    181:         VecAYPX(left,-1.0,right);
    182:         VecResetArray(right);

    184:         VecPlaceArray(right,x + i*bs);
    185:         MatSolve(diag[i],left,right);
    186:         VecResetArray(right);
    187:       }
    188:     }
    189:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {

    191:       for (i=mbs-1; i>=0; i--) {
    192:         n   = a->i[i+1] - a->i[i];
    193:         idx = a->j + a->i[i];
    194:         v   = a->a + a->i[i];

    196:         VecSet(left,0.0);
    197:         for (j=0; j<n; j++) {
    198:           if (idx[j] != i) {
    199:             VecPlaceArray(right,x + idx[j]*bs);
    200:             MatMultAdd(v[j],right,left,left);
    201:             VecResetArray(right);
    202:           }
    203:         }
    204:         VecPlaceArray(right,b + i*bs);
    205:         VecAYPX(left,-1.0,right);
    206:         VecResetArray(right);

    208:         VecPlaceArray(right,x + i*bs);
    209:         MatSolve(diag[i],left,right);
    210:         VecResetArray(right);

    212:       }
    213:     }
    214:   }
    215:   VecRestoreArray(xx,&x);
    216:   VecRestoreArrayRead(bb,&b);
    217:   return(0);
    218: }

    220: static PetscErrorCode MatSetValues_BlockMat(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
    221: {
    222:   Mat_BlockMat   *a = (Mat_BlockMat*)A->data;
    223:   PetscInt       *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
    224:   PetscInt       *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    225:   PetscInt       *aj  =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
    227:   PetscInt       ridx,cidx;
    228:   PetscBool      roworiented=a->roworiented;
    229:   MatScalar      value;
    230:   Mat            *ap,*aa = a->a;

    233:   for (k=0; k<m; k++) { /* loop over added rows */
    234:     row  = im[k];
    235:     brow = row/bs;
    236:     if (row < 0) continue;
    237: #if defined(PETSC_USE_DEBUG)
    238:     if (row >= A->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1);
    239: #endif
    240:     rp   = aj + ai[brow];
    241:     ap   = aa + ai[brow];
    242:     rmax = imax[brow];
    243:     nrow = ailen[brow];
    244:     low  = 0;
    245:     high = nrow;
    246:     for (l=0; l<n; l++) { /* loop over added columns */
    247:       if (in[l] < 0) continue;
    248: #if defined(PETSC_USE_DEBUG)
    249:       if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1);
    250: #endif
    251:       col = in[l]; bcol = col/bs;
    252:       if (A->symmetric && brow > bcol) continue;
    253:       ridx = row % bs; cidx = col % bs;
    254:       if (roworiented) value = v[l + k*n];
    255:       else value = v[k + l*m];

    257:       if (col <= lastcol) low = 0;
    258:       else high = nrow;
    259:       lastcol = col;
    260:       while (high-low > 7) {
    261:         t = (low+high)/2;
    262:         if (rp[t] > bcol) high = t;
    263:         else              low  = t;
    264:       }
    265:       for (i=low; i<high; i++) {
    266:         if (rp[i] > bcol) break;
    267:         if (rp[i] == bcol) goto noinsert1;
    268:       }
    269:       if (nonew == 1) goto noinsert1;
    270:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
    271:       MatSeqXAIJReallocateAIJ(A,a->mbs,1,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,Mat);
    272:       N = nrow++ - 1; high++;
    273:       /* shift up all the later entries in this row */
    274:       for (ii=N; ii>=i; ii--) {
    275:         rp[ii+1] = rp[ii];
    276:         ap[ii+1] = ap[ii];
    277:       }
    278:       if (N>=i) ap[i] = 0;
    279:       rp[i] = bcol;
    280:       a->nz++;
    281:       A->nonzerostate++;
    282: noinsert1:;
    283:       if (!*(ap+i)) {
    284:         MatCreateSeqAIJ(PETSC_COMM_SELF,bs,bs,0,0,ap+i);
    285:       }
    286:       MatSetValues(ap[i],1,&ridx,1,&cidx,&value,is);
    287:       low  = i;
    288:     }
    289:     ailen[brow] = nrow;
    290:   }
    291:   return(0);
    292: }

    294: static PetscErrorCode MatLoad_BlockMat(Mat newmat, PetscViewer viewer)
    295: {
    296:   PetscErrorCode    ierr;
    297:   Mat               tmpA;
    298:   PetscInt          i,j,m,n,bs = 1,ncols,*lens,currentcol,mbs,**ii,*ilens,nextcol,*llens,cnt = 0;
    299:   const PetscInt    *cols;
    300:   const PetscScalar *values;
    301:   PetscBool         flg = PETSC_FALSE,notdone;
    302:   Mat_SeqAIJ        *a;
    303:   Mat_BlockMat      *amat;

    306:   /* force binary viewer to load .info file if it has not yet done so */
    307:   PetscViewerSetUp(viewer);
    308:   MatCreate(PETSC_COMM_SELF,&tmpA);
    309:   MatSetType(tmpA,MATSEQAIJ);
    310:   MatLoad_SeqAIJ(tmpA,viewer);

    312:   MatGetLocalSize(tmpA,&m,&n);
    313:   PetscOptionsBegin(PETSC_COMM_SELF,NULL,"Options for loading BlockMat matrix 1","Mat");
    314:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    315:   PetscOptionsBool("-matload_symmetric","Store the matrix as symmetric","MatLoad",flg,&flg,NULL);
    316:   PetscOptionsEnd();

    318:   /* Determine number of nonzero blocks for each block row */
    319:   a    = (Mat_SeqAIJ*) tmpA->data;
    320:   mbs  = m/bs;
    321:   PetscMalloc3(mbs,&lens,bs,&ii,bs,&ilens);
    322:   PetscMemzero(lens,mbs*sizeof(PetscInt));

    324:   for (i=0; i<mbs; i++) {
    325:     for (j=0; j<bs; j++) {
    326:       ii[j]    = a->j + a->i[i*bs + j];
    327:       ilens[j] = a->i[i*bs + j + 1] - a->i[i*bs + j];
    328:     }

    330:     currentcol = -1;
    331:     while (PETSC_TRUE) {
    332:       notdone = PETSC_FALSE;
    333:       nextcol = 1000000000;
    334:       for (j=0; j<bs; j++) {
    335:         while ((ilens[j] > 0 && ii[j][0]/bs <= currentcol)) {
    336:           ii[j]++;
    337:           ilens[j]--;
    338:         }
    339:         if (ilens[j] > 0) {
    340:           notdone = PETSC_TRUE;
    341:           nextcol = PetscMin(nextcol,ii[j][0]/bs);
    342:         }
    343:       }
    344:       if (!notdone) break;
    345:       if (!flg || (nextcol >= i)) lens[i]++;
    346:       currentcol = nextcol;
    347:     }
    348:   }

    350:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) {
    351:     MatSetSizes(newmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
    352:   }
    353:   MatBlockMatSetPreallocation(newmat,bs,0,lens);
    354:   if (flg) {
    355:     MatSetOption(newmat,MAT_SYMMETRIC,PETSC_TRUE);
    356:   }
    357:   amat = (Mat_BlockMat*)(newmat)->data;

    359:   /* preallocate the submatrices */
    360:   PetscMalloc1(bs,&llens);
    361:   for (i=0; i<mbs; i++) { /* loops for block rows */
    362:     for (j=0; j<bs; j++) {
    363:       ii[j]    = a->j + a->i[i*bs + j];
    364:       ilens[j] = a->i[i*bs + j + 1] - a->i[i*bs + j];
    365:     }

    367:     currentcol = 1000000000;
    368:     for (j=0; j<bs; j++) { /* loop over rows in block finding first nonzero block */
    369:       if (ilens[j] > 0) {
    370:         currentcol = PetscMin(currentcol,ii[j][0]/bs);
    371:       }
    372:     }

    374:     while (PETSC_TRUE) {  /* loops over blocks in block row */
    375:       notdone = PETSC_FALSE;
    376:       nextcol = 1000000000;
    377:       PetscMemzero(llens,bs*sizeof(PetscInt));
    378:       for (j=0; j<bs; j++) { /* loop over rows in block */
    379:         while ((ilens[j] > 0 && ii[j][0]/bs <= currentcol)) { /* loop over columns in row */
    380:           ii[j]++;
    381:           ilens[j]--;
    382:           llens[j]++;
    383:         }
    384:         if (ilens[j] > 0) {
    385:           notdone = PETSC_TRUE;
    386:           nextcol = PetscMin(nextcol,ii[j][0]/bs);
    387:         }
    388:       }
    389:       if (cnt >= amat->maxnz) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Number of blocks found greater than expected %D",cnt);
    390:       if (!flg || currentcol >= i) {
    391:         amat->j[cnt] = currentcol;
    392:         MatCreateSeqAIJ(PETSC_COMM_SELF,bs,bs,0,llens,amat->a+cnt++);
    393:       }

    395:       if (!notdone) break;
    396:       currentcol = nextcol;
    397:     }
    398:     amat->ilen[i] = lens[i];
    399:   }

    401:   PetscFree3(lens,ii,ilens);
    402:   PetscFree(llens);

    404:   /* copy over the matrix, one row at a time */
    405:   for (i=0; i<m; i++) {
    406:     MatGetRow(tmpA,i,&ncols,&cols,&values);
    407:     MatSetValues(newmat,1,&i,ncols,cols,values,INSERT_VALUES);
    408:     MatRestoreRow(tmpA,i,&ncols,&cols,&values);
    409:   }
    410:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
    411:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
    412:   return(0);
    413: }

    415: static PetscErrorCode MatView_BlockMat(Mat A,PetscViewer viewer)
    416: {
    417:   Mat_BlockMat      *a = (Mat_BlockMat*)A->data;
    418:   PetscErrorCode    ierr;
    419:   const char        *name;
    420:   PetscViewerFormat format;

    423:   PetscObjectGetName((PetscObject)A,&name);
    424:   PetscViewerGetFormat(viewer,&format);
    425:   if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) {
    426:     PetscViewerASCIIPrintf(viewer,"Nonzero block matrices = %D \n",a->nz);
    427:     if (A->symmetric) {
    428:       PetscViewerASCIIPrintf(viewer,"Only upper triangular part of symmetric matrix is stored\n");
    429:     }
    430:   }
    431:   return(0);
    432: }

    434: static PetscErrorCode MatDestroy_BlockMat(Mat mat)
    435: {
    437:   Mat_BlockMat   *bmat = (Mat_BlockMat*)mat->data;
    438:   PetscInt       i;

    441:   VecDestroy(&bmat->right);
    442:   VecDestroy(&bmat->left);
    443:   VecDestroy(&bmat->middle);
    444:   VecDestroy(&bmat->workb);
    445:   if (bmat->diags) {
    446:     for (i=0; i<mat->rmap->n/mat->rmap->bs; i++) {
    447:       MatDestroy(&bmat->diags[i]);
    448:     }
    449:   }
    450:   if (bmat->a) {
    451:     for (i=0; i<bmat->nz; i++) {
    452:       MatDestroy(&bmat->a[i]);
    453:     }
    454:   }
    455:   MatSeqXAIJFreeAIJ(mat,(PetscScalar**)&bmat->a,&bmat->j,&bmat->i);
    456:   PetscFree(mat->data);
    457:   return(0);
    458: }

    460: static PetscErrorCode MatMult_BlockMat(Mat A,Vec x,Vec y)
    461: {
    462:   Mat_BlockMat   *bmat = (Mat_BlockMat*)A->data;
    464:   PetscScalar    *xx,*yy;
    465:   PetscInt       *aj,i,*ii,jrow,m = A->rmap->n/A->rmap->bs,bs = A->rmap->bs,n,j;
    466:   Mat            *aa;

    469:   /*
    470:      Standard CSR multiply except each entry is a Mat
    471:   */
    472:   VecGetArray(x,&xx);

    474:   VecSet(y,0.0);
    475:   VecGetArray(y,&yy);
    476:   aj   = bmat->j;
    477:   aa   = bmat->a;
    478:   ii   = bmat->i;
    479:   for (i=0; i<m; i++) {
    480:     jrow = ii[i];
    481:     VecPlaceArray(bmat->left,yy + bs*i);
    482:     n    = ii[i+1] - jrow;
    483:     for (j=0; j<n; j++) {
    484:       VecPlaceArray(bmat->right,xx + bs*aj[jrow]);
    485:       MatMultAdd(aa[jrow],bmat->right,bmat->left,bmat->left);
    486:       VecResetArray(bmat->right);
    487:       jrow++;
    488:     }
    489:     VecResetArray(bmat->left);
    490:   }
    491:   VecRestoreArray(x,&xx);
    492:   VecRestoreArray(y,&yy);
    493:   return(0);
    494: }

    496: PetscErrorCode MatMult_BlockMat_Symmetric(Mat A,Vec x,Vec y)
    497: {
    498:   Mat_BlockMat   *bmat = (Mat_BlockMat*)A->data;
    500:   PetscScalar    *xx,*yy;
    501:   PetscInt       *aj,i,*ii,jrow,m = A->rmap->n/A->rmap->bs,bs = A->rmap->bs,n,j;
    502:   Mat            *aa;

    505:   /*
    506:      Standard CSR multiply except each entry is a Mat
    507:   */
    508:   VecGetArray(x,&xx);

    510:   VecSet(y,0.0);
    511:   VecGetArray(y,&yy);
    512:   aj   = bmat->j;
    513:   aa   = bmat->a;
    514:   ii   = bmat->i;
    515:   for (i=0; i<m; i++) {
    516:     jrow = ii[i];
    517:     n    = ii[i+1] - jrow;
    518:     VecPlaceArray(bmat->left,yy + bs*i);
    519:     VecPlaceArray(bmat->middle,xx + bs*i);
    520:     /* if we ALWAYS required a diagonal entry then could remove this if test */
    521:     if (aj[jrow] == i) {
    522:       VecPlaceArray(bmat->right,xx + bs*aj[jrow]);
    523:       MatMultAdd(aa[jrow],bmat->right,bmat->left,bmat->left);
    524:       VecResetArray(bmat->right);
    525:       jrow++;
    526:       n--;
    527:     }
    528:     for (j=0; j<n; j++) {
    529:       VecPlaceArray(bmat->right,xx + bs*aj[jrow]);            /* upper triangular part */
    530:       MatMultAdd(aa[jrow],bmat->right,bmat->left,bmat->left);
    531:       VecResetArray(bmat->right);

    533:       VecPlaceArray(bmat->right,yy + bs*aj[jrow]);            /* lower triangular part */
    534:       MatMultTransposeAdd(aa[jrow],bmat->middle,bmat->right,bmat->right);
    535:       VecResetArray(bmat->right);
    536:       jrow++;
    537:     }
    538:     VecResetArray(bmat->left);
    539:     VecResetArray(bmat->middle);
    540:   }
    541:   VecRestoreArray(x,&xx);
    542:   VecRestoreArray(y,&yy);
    543:   return(0);
    544: }

    546: static PetscErrorCode MatMultAdd_BlockMat(Mat A,Vec x,Vec y,Vec z)
    547: {
    549:   return(0);
    550: }

    552: static PetscErrorCode MatMultTranspose_BlockMat(Mat A,Vec x,Vec y)
    553: {
    555:   return(0);
    556: }

    558: static PetscErrorCode MatMultTransposeAdd_BlockMat(Mat A,Vec x,Vec y,Vec z)
    559: {
    561:   return(0);
    562: }

    564: /*
    565:      Adds diagonal pointers to sparse matrix structure.
    566: */
    567: static PetscErrorCode MatMarkDiagonal_BlockMat(Mat A)
    568: {
    569:   Mat_BlockMat   *a = (Mat_BlockMat*)A->data;
    571:   PetscInt       i,j,mbs = A->rmap->n/A->rmap->bs;

    574:   if (!a->diag) {
    575:     PetscMalloc1(mbs,&a->diag);
    576:   }
    577:   for (i=0; i<mbs; i++) {
    578:     a->diag[i] = a->i[i+1];
    579:     for (j=a->i[i]; j<a->i[i+1]; j++) {
    580:       if (a->j[j] == i) {
    581:         a->diag[i] = j;
    582:         break;
    583:       }
    584:     }
    585:   }
    586:   return(0);
    587: }

    589: static PetscErrorCode MatCreateSubMatrix_BlockMat(Mat A,IS isrow,IS iscol,MatReuse scall,Mat *B)
    590: {
    591:   Mat_BlockMat   *a = (Mat_BlockMat*)A->data;
    592:   Mat_SeqAIJ     *c;
    594:   PetscInt       i,k,first,step,lensi,nrows,ncols;
    595:   PetscInt       *j_new,*i_new,*aj = a->j,*ailen = a->ilen;
    596:   PetscScalar    *a_new;
    597:   Mat            C,*aa = a->a;
    598:   PetscBool      stride,equal;

    601:   ISEqual(isrow,iscol,&equal);
    602:   if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only for idential column and row indices");
    603:   PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);
    604:   if (!stride) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only for stride indices");
    605:   ISStrideGetInfo(iscol,&first,&step);
    606:   if (step != A->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only select one entry from each block");

    608:   ISGetLocalSize(isrow,&nrows);
    609:   ncols = nrows;

    611:   /* create submatrix */
    612:   if (scall == MAT_REUSE_MATRIX) {
    613:     PetscInt n_cols,n_rows;
    614:     C    = *B;
    615:     MatGetSize(C,&n_rows,&n_cols);
    616:     if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size");
    617:     MatZeroEntries(C);
    618:   } else {
    619:     MatCreate(PetscObjectComm((PetscObject)A),&C);
    620:     MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);
    621:     if (A->symmetric) {
    622:       MatSetType(C,MATSEQSBAIJ);
    623:     } else {
    624:       MatSetType(C,MATSEQAIJ);
    625:     }
    626:     MatSeqAIJSetPreallocation(C,0,ailen);
    627:     MatSeqSBAIJSetPreallocation(C,1,0,ailen);
    628:   }
    629:   c = (Mat_SeqAIJ*)C->data;

    631:   /* loop over rows inserting into submatrix */
    632:   a_new = c->a;
    633:   j_new = c->j;
    634:   i_new = c->i;

    636:   for (i=0; i<nrows; i++) {
    637:     lensi = ailen[i];
    638:     for (k=0; k<lensi; k++) {
    639:       *j_new++ = *aj++;
    640:       MatGetValue(*aa++,first,first,a_new++);
    641:     }
    642:     i_new[i+1] = i_new[i] + lensi;
    643:     c->ilen[i] = lensi;
    644:   }

    646:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
    647:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
    648:   *B   = C;
    649:   return(0);
    650: }

    652: static PetscErrorCode MatAssemblyEnd_BlockMat(Mat A,MatAssemblyType mode)
    653: {
    654:   Mat_BlockMat   *a = (Mat_BlockMat*)A->data;
    656:   PetscInt       fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax;
    657:   PetscInt       m      = a->mbs,*ip,N,*ailen = a->ilen,rmax = 0;
    658:   Mat            *aa    = a->a,*ap;

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

    663:   if (m) rmax = ailen[0]; /* determine row with most nonzeros */
    664:   for (i=1; i<m; i++) {
    665:     /* move each row back by the amount of empty slots (fshift) before it*/
    666:     fshift += imax[i-1] - ailen[i-1];
    667:     rmax    = PetscMax(rmax,ailen[i]);
    668:     if (fshift) {
    669:       ip = aj + ai[i];
    670:       ap = aa + ai[i];
    671:       N  = ailen[i];
    672:       for (j=0; j<N; j++) {
    673:         ip[j-fshift] = ip[j];
    674:         ap[j-fshift] = ap[j];
    675:       }
    676:     }
    677:     ai[i] = ai[i-1] + ailen[i-1];
    678:   }
    679:   if (m) {
    680:     fshift += imax[m-1] - ailen[m-1];
    681:     ai[m]   = ai[m-1] + ailen[m-1];
    682:   }
    683:   /* reset ilen and imax for each row */
    684:   for (i=0; i<m; i++) {
    685:     ailen[i] = imax[i] = ai[i+1] - ai[i];
    686:   }
    687:   a->nz = ai[m];
    688:   for (i=0; i<a->nz; i++) {
    689: #if defined(PETSC_USE_DEBUG)
    690:     if (!aa[i]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Null matrix at location %D column %D nz %D",i,aj[i],a->nz);
    691: #endif
    692:     MatAssemblyBegin(aa[i],MAT_FINAL_ASSEMBLY);
    693:     MatAssemblyEnd(aa[i],MAT_FINAL_ASSEMBLY);
    694:   }
    695:   PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n/A->cmap->bs,fshift,a->nz);
    696:   PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);
    697:   PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);

    699:   A->info.mallocs    += a->reallocs;
    700:   a->reallocs         = 0;
    701:   A->info.nz_unneeded = (double)fshift;
    702:   a->rmax             = rmax;
    703:   MatMarkDiagonal_BlockMat(A);
    704:   return(0);
    705: }

    707: static PetscErrorCode MatSetOption_BlockMat(Mat A,MatOption opt,PetscBool flg)
    708: {
    711:   if (opt == MAT_SYMMETRIC && flg) {
    712:     A->ops->sor  = MatSOR_BlockMat_Symmetric;
    713:     A->ops->mult = MatMult_BlockMat_Symmetric;
    714:   } else {
    715:     PetscInfo1(A,"Unused matrix option %s\n",MatOptions[opt]);
    716:   }
    717:   return(0);
    718: }

    721: static struct _MatOps MatOps_Values = {MatSetValues_BlockMat,
    722:                                        0,
    723:                                        0,
    724:                                        MatMult_BlockMat,
    725:                                /*  4*/ MatMultAdd_BlockMat,
    726:                                        MatMultTranspose_BlockMat,
    727:                                        MatMultTransposeAdd_BlockMat,
    728:                                        0,
    729:                                        0,
    730:                                        0,
    731:                                /* 10*/ 0,
    732:                                        0,
    733:                                        0,
    734:                                        MatSOR_BlockMat,
    735:                                        0,
    736:                                /* 15*/ 0,
    737:                                        0,
    738:                                        0,
    739:                                        0,
    740:                                        0,
    741:                                /* 20*/ 0,
    742:                                        MatAssemblyEnd_BlockMat,
    743:                                        MatSetOption_BlockMat,
    744:                                        0,
    745:                                /* 24*/ 0,
    746:                                        0,
    747:                                        0,
    748:                                        0,
    749:                                        0,
    750:                                /* 29*/ 0,
    751:                                        0,
    752:                                        0,
    753:                                        0,
    754:                                        0,
    755:                                /* 34*/ 0,
    756:                                        0,
    757:                                        0,
    758:                                        0,
    759:                                        0,
    760:                                /* 39*/ 0,
    761:                                        0,
    762:                                        0,
    763:                                        0,
    764:                                        0,
    765:                                /* 44*/ 0,
    766:                                        0,
    767:                                        MatShift_Basic,
    768:                                        0,
    769:                                        0,
    770:                                /* 49*/ 0,
    771:                                        0,
    772:                                        0,
    773:                                        0,
    774:                                        0,
    775:                                /* 54*/ 0,
    776:                                        0,
    777:                                        0,
    778:                                        0,
    779:                                        0,
    780:                                /* 59*/ MatCreateSubMatrix_BlockMat,
    781:                                        MatDestroy_BlockMat,
    782:                                        MatView_BlockMat,
    783:                                        0,
    784:                                        0,
    785:                                /* 64*/ 0,
    786:                                        0,
    787:                                        0,
    788:                                        0,
    789:                                        0,
    790:                                /* 69*/ 0,
    791:                                        0,
    792:                                        0,
    793:                                        0,
    794:                                        0,
    795:                                /* 74*/ 0,
    796:                                        0,
    797:                                        0,
    798:                                        0,
    799:                                        0,
    800:                                /* 79*/ 0,
    801:                                        0,
    802:                                        0,
    803:                                        0,
    804:                                        MatLoad_BlockMat,
    805:                                /* 84*/ 0,
    806:                                        0,
    807:                                        0,
    808:                                        0,
    809:                                        0,
    810:                                /* 89*/ 0,
    811:                                        0,
    812:                                        0,
    813:                                        0,
    814:                                        0,
    815:                                /* 94*/ 0,
    816:                                        0,
    817:                                        0,
    818:                                        0,
    819:                                        0,
    820:                                /* 99*/ 0,
    821:                                        0,
    822:                                        0,
    823:                                        0,
    824:                                        0,
    825:                                /*104*/ 0,
    826:                                        0,
    827:                                        0,
    828:                                        0,
    829:                                        0,
    830:                                /*109*/ 0,
    831:                                        0,
    832:                                        0,
    833:                                        0,
    834:                                        0,
    835:                                /*114*/ 0,
    836:                                        0,
    837:                                        0,
    838:                                        0,
    839:                                        0,
    840:                                /*119*/ 0,
    841:                                        0,
    842:                                        0,
    843:                                        0,
    844:                                        0,
    845:                                /*124*/ 0,
    846:                                        0,
    847:                                        0,
    848:                                        0,
    849:                                        0,
    850:                                /*129*/ 0,
    851:                                        0,
    852:                                        0,
    853:                                        0,
    854:                                        0,
    855:                                /*134*/ 0,
    856:                                        0,
    857:                                        0,
    858:                                        0,
    859:                                        0,
    860:                                /*139*/ 0,
    861:                                        0,
    862:                                        0
    863: };

    865: /*@C
    866:    MatBlockMatSetPreallocation - For good matrix assembly performance
    867:    the user should preallocate the matrix storage by setting the parameter nz
    868:    (or the array nnz).  By setting these parameters accurately, performance
    869:    during matrix assembly can be increased by more than a factor of 50.

    871:    Collective on MPI_Comm

    873:    Input Parameters:
    874: +  B - The matrix
    875: .  bs - size of each block in matrix
    876: .  nz - number of nonzeros per block row (same for all rows)
    877: -  nnz - array containing the number of nonzeros in the various block rows
    878:          (possibly different for each row) or NULL

    880:    Notes:
    881:      If nnz is given then nz is ignored

    883:    Specify the preallocated storage with either nz or nnz (not both).
    884:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
    885:    allocation.  For large problems you MUST preallocate memory or you
    886:    will get TERRIBLE performance, see the users' manual chapter on matrices.

    888:    Level: intermediate

    890: .seealso: MatCreate(), MatCreateBlockMat(), MatSetValues()

    892: @*/
    893: PetscErrorCode  MatBlockMatSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
    894: {

    898:   PetscTryMethod(B,"MatBlockMatSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));
    899:   return(0);
    900: }

    902: static PetscErrorCode  MatBlockMatSetPreallocation_BlockMat(Mat A,PetscInt bs,PetscInt nz,PetscInt *nnz)
    903: {
    904:   Mat_BlockMat   *bmat = (Mat_BlockMat*)A->data;
    906:   PetscInt       i;

    909:   PetscLayoutSetBlockSize(A->rmap,bs);
    910:   PetscLayoutSetBlockSize(A->cmap,bs);
    911:   PetscLayoutSetUp(A->rmap);
    912:   PetscLayoutSetUp(A->cmap);
    913:   PetscLayoutGetBlockSize(A->rmap,&bs);

    915:   if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
    916:   if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz);
    917:   if (nnz) {
    918:     for (i=0; i<A->rmap->n/bs; i++) {
    919:       if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %d value %d",i,nnz[i]);
    920:       if (nnz[i] > A->cmap->n/bs) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than row length: local row %d value %d rowlength %d",i,nnz[i],A->cmap->n/bs);
    921:     }
    922:   }
    923:   bmat->mbs = A->rmap->n/bs;

    925:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs,NULL,&bmat->right);
    926:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs,NULL,&bmat->middle);
    927:   VecCreateSeq(PETSC_COMM_SELF,bs,&bmat->left);

    929:   if (!bmat->imax) {
    930:     PetscMalloc2(A->rmap->n,&bmat->imax,A->rmap->n,&bmat->ilen);
    931:     PetscLogObjectMemory((PetscObject)A,2*A->rmap->n*sizeof(PetscInt));
    932:   }
    933:   if (nnz) {
    934:     nz = 0;
    935:     for (i=0; i<A->rmap->n/A->rmap->bs; i++) {
    936:       bmat->imax[i] = nnz[i];
    937:       nz           += nnz[i];
    938:     }
    939:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Currently requires block row by row preallocation");

    941:   /* bmat->ilen will count nonzeros in each row so far. */
    942:   for (i=0; i<bmat->mbs; i++) bmat->ilen[i] = 0;

    944:   /* allocate the matrix space */
    945:   MatSeqXAIJFreeAIJ(A,(PetscScalar**)&bmat->a,&bmat->j,&bmat->i);
    946:   PetscMalloc3(nz,&bmat->a,nz,&bmat->j,A->rmap->n+1,&bmat->i);
    947:   PetscLogObjectMemory((PetscObject)A,(A->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));
    948:   bmat->i[0] = 0;
    949:   for (i=1; i<bmat->mbs+1; i++) {
    950:     bmat->i[i] = bmat->i[i-1] + bmat->imax[i-1];
    951:   }
    952:   bmat->singlemalloc = PETSC_TRUE;
    953:   bmat->free_a       = PETSC_TRUE;
    954:   bmat->free_ij      = PETSC_TRUE;

    956:   bmat->nz            = 0;
    957:   bmat->maxnz         = nz;
    958:   A->info.nz_unneeded = (double)bmat->maxnz;
    959:   MatSetOption(A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
    960:   return(0);
    961: }

    963: /*MC
    964:    MATBLOCKMAT - A matrix that is defined by a set of Mat's that represents a sparse block matrix
    965:                  consisting of (usually) sparse blocks.

    967:   Level: advanced

    969: .seealso: MatCreateBlockMat()

    971: M*/

    973: PETSC_EXTERN PetscErrorCode MatCreate_BlockMat(Mat A)
    974: {
    975:   Mat_BlockMat   *b;

    979:   PetscNewLog(A,&b);
    980:   A->data = (void*)b;
    981:   PetscMemcpy(A->ops,&MatOps_Values,sizeof(struct _MatOps));

    983:   A->assembled    = PETSC_TRUE;
    984:   A->preallocated = PETSC_FALSE;
    985:   PetscObjectChangeTypeName((PetscObject)A,MATBLOCKMAT);

    987:   PetscObjectComposeFunction((PetscObject)A,"MatBlockMatSetPreallocation_C",MatBlockMatSetPreallocation_BlockMat);
    988:   return(0);
    989: }

    991: /*@C
    992:    MatCreateBlockMat - Creates a new matrix in which each block contains a uniform-size sequential Mat object

    994:   Collective on MPI_Comm

    996:    Input Parameters:
    997: +  comm - MPI communicator
    998: .  m - number of rows
    999: .  n  - number of columns
    1000: .  bs - size of each submatrix
    1001: .  nz  - expected maximum number of nonzero blocks in row (use PETSC_DEFAULT if not known)
    1002: -  nnz - expected number of nonzers per block row if known (use NULL otherwise)

    1005:    Output Parameter:
    1006: .  A - the matrix

    1008:    Level: intermediate

    1010:    Notes:
    1011:     Matrices of this type are nominally-sparse matrices in which each "entry" is a Mat object.  Each Mat must
    1012:    have the same size and be sequential.  The local and global sizes must be compatible with this decomposition.

    1014:    For matrices containing parallel submatrices and variable block sizes, see MATNEST.

    1016: .keywords: matrix, bmat, create

    1018: .seealso: MATBLOCKMAT, MatCreateNest()
    1019: @*/
    1020: PetscErrorCode  MatCreateBlockMat(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt bs,PetscInt nz,PetscInt *nnz, Mat *A)
    1021: {

    1025:   MatCreate(comm,A);
    1026:   MatSetSizes(*A,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
    1027:   MatSetType(*A,MATBLOCKMAT);
    1028:   MatBlockMatSetPreallocation(*A,bs,nz,nnz);
    1029:   return(0);
    1030: }