Actual source code: dense.c

petsc-3.11.1 2019-04-17
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  2: /*
  3:      Defines the basic matrix operations for sequential dense.
  4: */

  6:  #include <../src/mat/impls/dense/seq/dense.h>
  7:  #include <petscblaslapack.h>

  9:  #include <../src/mat/impls/aij/seq/aij.h>

 11: static PetscErrorCode MatSeqDenseSymmetrize_Private(Mat A, PetscBool hermitian)
 12: {
 13:   Mat_SeqDense *mat = (Mat_SeqDense*)A->data;
 14:   PetscInt      j, k, n = A->rmap->n;

 17:   if (A->rmap->n != A->cmap->n) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Cannot symmetrize a rectangular matrix");
 18:   if (!hermitian) {
 19:     for (k=0;k<n;k++) {
 20:       for (j=k;j<n;j++) {
 21:         mat->v[j*mat->lda + k] = mat->v[k*mat->lda + j];
 22:       }
 23:     }
 24:   } else {
 25:     for (k=0;k<n;k++) {
 26:       for (j=k;j<n;j++) {
 27:         mat->v[j*mat->lda + k] = PetscConj(mat->v[k*mat->lda + j]);
 28:       }
 29:     }
 30:   }
 31:   return(0);
 32: }

 34: PETSC_EXTERN PetscErrorCode MatSeqDenseInvertFactors_Private(Mat A)
 35: {
 36: #if defined(PETSC_MISSING_LAPACK_POTRF)
 38:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable.");
 39: #else
 40:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
 42:   PetscBLASInt   info,n;

 45:   if (!A->rmap->n || !A->cmap->n) return(0);
 46:   PetscBLASIntCast(A->cmap->n,&n);
 47:   if (A->factortype == MAT_FACTOR_LU) {
 48:     if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present");
 49:     if (!mat->fwork) {
 50:       mat->lfwork = n;
 51:       PetscMalloc1(mat->lfwork,&mat->fwork);
 52:       PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));
 53:     }
 54:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
 55:     PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info));
 56:     PetscFPTrapPop();
 57:     PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0); /* TODO CHECK FLOPS */
 58:   } else if (A->factortype == MAT_FACTOR_CHOLESKY) {
 59:     if (A->spd) {
 60:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
 61:       PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&n,mat->v,&mat->lda,&info));
 62:       PetscFPTrapPop();
 63:       MatSeqDenseSymmetrize_Private(A,PETSC_TRUE);
 64: #if defined(PETSC_USE_COMPLEX)
 65:     } else if (A->hermitian) {
 66:       if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present");
 67:       if (!mat->fwork) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Fwork not present");
 68:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
 69:       PetscStackCallBLAS("LAPACKhetri",LAPACKhetri_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&info));
 70:       PetscFPTrapPop();
 71:       MatSeqDenseSymmetrize_Private(A,PETSC_TRUE);
 72: #endif
 73:     } else { /* symmetric case */
 74:       if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present");
 75:       if (!mat->fwork) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Fwork not present");
 76:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
 77:       PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&info));
 78:       PetscFPTrapPop();
 79:       MatSeqDenseSymmetrize_Private(A,PETSC_FALSE);
 80:     }
 81:     if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad Inversion: zero pivot in row %D",(PetscInt)info-1);
 82:     PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0); /* TODO CHECK FLOPS */
 83:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve");
 84: #endif

 86:   A->ops->solve             = NULL;
 87:   A->ops->matsolve          = NULL;
 88:   A->ops->solvetranspose    = NULL;
 89:   A->ops->matsolvetranspose = NULL;
 90:   A->ops->solveadd          = NULL;
 91:   A->ops->solvetransposeadd = NULL;
 92:   A->factortype             = MAT_FACTOR_NONE;
 93:   PetscFree(A->solvertype);
 94:   return(0);
 95: }

 97: PetscErrorCode MatZeroRowsColumns_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
 98: {
 99:   PetscErrorCode    ierr;
100:   Mat_SeqDense      *l = (Mat_SeqDense*)A->data;
101:   PetscInt          m  = l->lda, n = A->cmap->n,r = A->rmap->n, i,j;
102:   PetscScalar       *slot,*bb;
103:   const PetscScalar *xx;

106: #if defined(PETSC_USE_DEBUG)
107:   for (i=0; i<N; i++) {
108:     if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed");
109:     if (rows[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested to be zeroed greater than or equal number of rows %D",rows[i],A->rmap->n);
110:     if (rows[i] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Col %D requested to be zeroed greater than or equal number of cols %D",rows[i],A->cmap->n);
111:   }
112: #endif

114:   /* fix right hand side if needed */
115:   if (x && b) {
116:     Vec xt;

118:     if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices");
119:     VecDuplicate(x,&xt);
120:     VecCopy(x,xt);
121:     VecScale(xt,-1.0);
122:     MatMultAdd(A,xt,b,b);
123:     VecDestroy(&xt);
124:     VecGetArrayRead(x,&xx);
125:     VecGetArray(b,&bb);
126:     for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]];
127:     VecRestoreArrayRead(x,&xx);
128:     VecRestoreArray(b,&bb);
129:   }

131:   for (i=0; i<N; i++) {
132:     slot = l->v + rows[i]*m;
133:     PetscMemzero(slot,r*sizeof(PetscScalar));
134:   }
135:   for (i=0; i<N; i++) {
136:     slot = l->v + rows[i];
137:     for (j=0; j<n; j++) { *slot = 0.0; slot += m;}
138:   }
139:   if (diag != 0.0) {
140:     if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices");
141:     for (i=0; i<N; i++) {
142:       slot  = l->v + (m+1)*rows[i];
143:       *slot = diag;
144:     }
145:   }
146:   return(0);
147: }

149: PetscErrorCode MatPtAPNumeric_SeqDense_SeqDense(Mat A,Mat P,Mat C)
150: {
151:   Mat_SeqDense   *c = (Mat_SeqDense*)(C->data);

155:   MatMatMultNumeric_SeqDense_SeqDense(A,P,c->ptapwork);
156:   MatTransposeMatMultNumeric_SeqDense_SeqDense(P,c->ptapwork,C);
157:   return(0);
158: }

160: PetscErrorCode MatPtAPSymbolic_SeqDense_SeqDense(Mat A,Mat P,PetscReal fill,Mat *C)
161: {
162:   Mat_SeqDense   *c;

166:   MatCreateSeqDense(PetscObjectComm((PetscObject)A),P->cmap->N,P->cmap->N,NULL,C);
167:   c = (Mat_SeqDense*)((*C)->data);
168:   MatCreateSeqDense(PetscObjectComm((PetscObject)A),A->rmap->N,P->cmap->N,NULL,&c->ptapwork);
169:   return(0);
170: }

172: PETSC_INTERN PetscErrorCode MatPtAP_SeqDense_SeqDense(Mat A,Mat P,MatReuse reuse,PetscReal fill,Mat *C)
173: {

177:   if (reuse == MAT_INITIAL_MATRIX) {
178:     MatPtAPSymbolic_SeqDense_SeqDense(A,P,fill,C);
179:   }
180:   PetscLogEventBegin(MAT_PtAPNumeric,A,P,0,0);
181:   (*(*C)->ops->ptapnumeric)(A,P,*C);
182:   PetscLogEventEnd(MAT_PtAPNumeric,A,P,0,0);
183:   return(0);
184: }

186: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
187: {
188:   Mat            B = NULL;
189:   Mat_SeqAIJ     *a = (Mat_SeqAIJ*)A->data;
190:   Mat_SeqDense   *b;
192:   PetscInt       *ai=a->i,*aj=a->j,m=A->rmap->N,n=A->cmap->N,i;
193:   MatScalar      *av=a->a;
194:   PetscBool      isseqdense;

197:   if (reuse == MAT_REUSE_MATRIX) {
198:     PetscObjectTypeCompare((PetscObject)*newmat,MATSEQDENSE,&isseqdense);
199:     if (!isseqdense) SETERRQ1(PetscObjectComm((PetscObject)*newmat),PETSC_ERR_USER,"Cannot reuse matrix of type %s",((PetscObject)(*newmat))->type);
200:   }
201:   if (reuse != MAT_REUSE_MATRIX) {
202:     MatCreate(PetscObjectComm((PetscObject)A),&B);
203:     MatSetSizes(B,m,n,m,n);
204:     MatSetType(B,MATSEQDENSE);
205:     MatSeqDenseSetPreallocation(B,NULL);
206:     b    = (Mat_SeqDense*)(B->data);
207:   } else {
208:     b    = (Mat_SeqDense*)((*newmat)->data);
209:     PetscMemzero(b->v,m*n*sizeof(PetscScalar));
210:   }
211:   for (i=0; i<m; i++) {
212:     PetscInt j;
213:     for (j=0;j<ai[1]-ai[0];j++) {
214:       b->v[*aj*m+i] = *av;
215:       aj++;
216:       av++;
217:     }
218:     ai++;
219:   }

221:   if (reuse == MAT_INPLACE_MATRIX) {
222:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
223:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
224:     MatHeaderReplace(A,&B);
225:   } else {
226:     if (B) *newmat = B;
227:     MatAssemblyBegin(*newmat,MAT_FINAL_ASSEMBLY);
228:     MatAssemblyEnd(*newmat,MAT_FINAL_ASSEMBLY);
229:   }
230:   return(0);
231: }

233: PETSC_INTERN PetscErrorCode MatConvert_SeqDense_SeqAIJ(Mat A, MatType newtype,MatReuse reuse,Mat *newmat)
234: {
235:   Mat            B;
236:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
238:   PetscInt       i, j;
239:   PetscInt       *rows, *nnz;
240:   MatScalar      *aa = a->v, *vals;

243:   MatCreate(PetscObjectComm((PetscObject)A),&B);
244:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
245:   MatSetType(B,MATSEQAIJ);
246:   PetscCalloc3(A->rmap->n,&rows,A->rmap->n,&nnz,A->rmap->n,&vals);
247:   for (j=0; j<A->cmap->n; j++) {
248:     for (i=0; i<A->rmap->n; i++) if (aa[i] != 0.0 || i == j) ++nnz[i];
249:     aa += a->lda;
250:   }
251:   MatSeqAIJSetPreallocation(B,PETSC_DETERMINE,nnz);
252:   aa = a->v;
253:   for (j=0; j<A->cmap->n; j++) {
254:     PetscInt numRows = 0;
255:     for (i=0; i<A->rmap->n; i++) if (aa[i] != 0.0 || i == j) {rows[numRows] = i; vals[numRows++] = aa[i];}
256:     MatSetValues(B,numRows,rows,1,&j,vals,INSERT_VALUES);
257:     aa  += a->lda;
258:   }
259:   PetscFree3(rows,nnz,vals);
260:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
261:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

263:   if (reuse == MAT_INPLACE_MATRIX) {
264:     MatHeaderReplace(A,&B);
265:   } else {
266:     *newmat = B;
267:   }
268:   return(0);
269: }

271: static PetscErrorCode MatAXPY_SeqDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str)
272: {
273:   Mat_SeqDense   *x     = (Mat_SeqDense*)X->data,*y = (Mat_SeqDense*)Y->data;
274:   PetscScalar    oalpha = alpha;
275:   PetscInt       j;
276:   PetscBLASInt   N,m,ldax,lday,one = 1;

280:   PetscBLASIntCast(X->rmap->n*X->cmap->n,&N);
281:   PetscBLASIntCast(X->rmap->n,&m);
282:   PetscBLASIntCast(x->lda,&ldax);
283:   PetscBLASIntCast(y->lda,&lday);
284:   if (ldax>m || lday>m) {
285:     for (j=0; j<X->cmap->n; j++) {
286:       PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&m,&oalpha,x->v+j*ldax,&one,y->v+j*lday,&one));
287:     }
288:   } else {
289:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&N,&oalpha,x->v,&one,y->v,&one));
290:   }
291:   PetscObjectStateIncrease((PetscObject)Y);
292:   PetscLogFlops(PetscMax(2*N-1,0));
293:   return(0);
294: }

296: static PetscErrorCode MatGetInfo_SeqDense(Mat A,MatInfoType flag,MatInfo *info)
297: {
298:   PetscInt N = A->rmap->n*A->cmap->n;

301:   info->block_size        = 1.0;
302:   info->nz_allocated      = (double)N;
303:   info->nz_used           = (double)N;
304:   info->nz_unneeded       = (double)0;
305:   info->assemblies        = (double)A->num_ass;
306:   info->mallocs           = 0;
307:   info->memory            = ((PetscObject)A)->mem;
308:   info->fill_ratio_given  = 0;
309:   info->fill_ratio_needed = 0;
310:   info->factor_mallocs    = 0;
311:   return(0);
312: }

314: static PetscErrorCode MatScale_SeqDense(Mat A,PetscScalar alpha)
315: {
316:   Mat_SeqDense   *a     = (Mat_SeqDense*)A->data;
317:   PetscScalar    oalpha = alpha;
319:   PetscBLASInt   one = 1,j,nz,lda;

322:   PetscBLASIntCast(a->lda,&lda);
323:   if (lda>A->rmap->n) {
324:     PetscBLASIntCast(A->rmap->n,&nz);
325:     for (j=0; j<A->cmap->n; j++) {
326:       PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v+j*lda,&one));
327:     }
328:   } else {
329:     PetscBLASIntCast(A->rmap->n*A->cmap->n,&nz);
330:     PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v,&one));
331:   }
332:   PetscLogFlops(nz);
333:   return(0);
334: }

336: static PetscErrorCode MatIsHermitian_SeqDense(Mat A,PetscReal rtol,PetscBool  *fl)
337: {
338:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
339:   PetscInt     i,j,m = A->rmap->n,N;
340:   PetscScalar  *v = a->v;

343:   *fl = PETSC_FALSE;
344:   if (A->rmap->n != A->cmap->n) return(0);
345:   N = a->lda;

347:   for (i=0; i<m; i++) {
348:     for (j=i+1; j<m; j++) {
349:       if (PetscAbsScalar(v[i+j*N] - PetscConj(v[j+i*N])) > rtol) return(0);
350:     }
351:   }
352:   *fl = PETSC_TRUE;
353:   return(0);
354: }

356: static PetscErrorCode MatDuplicateNoCreate_SeqDense(Mat newi,Mat A,MatDuplicateOption cpvalues)
357: {
358:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data,*l;
360:   PetscInt       lda = (PetscInt)mat->lda,j,m;

363:   PetscLayoutReference(A->rmap,&newi->rmap);
364:   PetscLayoutReference(A->cmap,&newi->cmap);
365:   MatSeqDenseSetPreallocation(newi,NULL);
366:   if (cpvalues == MAT_COPY_VALUES) {
367:     l = (Mat_SeqDense*)newi->data;
368:     if (lda>A->rmap->n) {
369:       m = A->rmap->n;
370:       for (j=0; j<A->cmap->n; j++) {
371:         PetscMemcpy(l->v+j*m,mat->v+j*lda,m*sizeof(PetscScalar));
372:       }
373:     } else {
374:       PetscMemcpy(l->v,mat->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));
375:     }
376:   }
377:   newi->assembled = PETSC_TRUE;
378:   return(0);
379: }

381: static PetscErrorCode MatDuplicate_SeqDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat)
382: {

386:   MatCreate(PetscObjectComm((PetscObject)A),newmat);
387:   MatSetSizes(*newmat,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);
388:   MatSetType(*newmat,((PetscObject)A)->type_name);
389:   MatDuplicateNoCreate_SeqDense(*newmat,A,cpvalues);
390:   return(0);
391: }


394: static PetscErrorCode MatLUFactor_SeqDense(Mat,IS,IS,const MatFactorInfo*);

396: static PetscErrorCode MatLUFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy)
397: {
398:   MatFactorInfo  info;

402:   MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);
403:   MatLUFactor_SeqDense(fact,0,0,&info);
404:   return(0);
405: }

407: static PetscErrorCode MatSolve_SeqDense(Mat A,Vec xx,Vec yy)
408: {
409:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
410:   PetscErrorCode    ierr;
411:   const PetscScalar *x;
412:   PetscScalar       *y;
413:   PetscBLASInt      one = 1,info,m;

416:   PetscBLASIntCast(A->rmap->n,&m);
417:   VecGetArrayRead(xx,&x);
418:   VecGetArray(yy,&y);
419:   PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));
420:   if (A->factortype == MAT_FACTOR_LU) {
421: #if defined(PETSC_MISSING_LAPACK_GETRS)
422:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
423: #else
424:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
425:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
426:     PetscFPTrapPop();
427:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve");
428: #endif
429:   } else if (A->factortype == MAT_FACTOR_CHOLESKY) {
430: #if defined(PETSC_MISSING_LAPACK_POTRS)
431:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
432: #else
433:     if (A->spd) {
434:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
435:       PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info));
436:       PetscFPTrapPop();
437:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve");
438: #if defined(PETSC_USE_COMPLEX)
439:     } else if (A->hermitian) {
440:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
441:       PetscStackCallBLAS("LAPACKhetrs",LAPACKhetrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
442:       PetscFPTrapPop();
443:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"HETRS Bad solve");
444: #endif
445:     } else { /* symmetric case */
446:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
447:       PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
448:       PetscFPTrapPop();
449:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve");
450:     }
451: #endif
452:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve");
453:   VecRestoreArrayRead(xx,&x);
454:   VecRestoreArray(yy,&y);
455:   PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);
456:   return(0);
457: }

459: static PetscErrorCode MatMatSolve_SeqDense(Mat A,Mat B,Mat X)
460: {
461:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
463:   PetscScalar    *b,*x;
464:   PetscInt       n;
465:   PetscBLASInt   nrhs,info,m;
466:   PetscBool      flg;

469:   PetscBLASIntCast(A->rmap->n,&m);
470:   PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
471:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix");
472:   PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
473:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix");

475:   MatGetSize(B,NULL,&n);
476:   PetscBLASIntCast(n,&nrhs);
477:   MatDenseGetArray(B,&b);
478:   MatDenseGetArray(X,&x);

480:   PetscMemcpy(x,b,m*nrhs*sizeof(PetscScalar));

482:   if (A->factortype == MAT_FACTOR_LU) {
483: #if defined(PETSC_MISSING_LAPACK_GETRS)
484:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
485: #else
486:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
487:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info));
488:     PetscFPTrapPop();
489:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve");
490: #endif
491:   } else if (A->factortype == MAT_FACTOR_CHOLESKY) {
492: #if defined(PETSC_MISSING_LAPACK_POTRS)
493:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
494: #else
495:     if (A->spd) {
496:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
497:       PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&nrhs,mat->v,&mat->lda,x,&m,&info));
498:       PetscFPTrapPop();
499:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve");
500: #if defined(PETSC_USE_COMPLEX)
501:     } else if (A->hermitian) {
502:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
503:       PetscStackCallBLAS("LAPACKhetrs",LAPACKhetrs_("L",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info));
504:       PetscFPTrapPop();
505:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"HETRS Bad solve");
506: #endif
507:     } else { /* symmetric case */
508:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
509:       PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info));
510:       PetscFPTrapPop();
511:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve");
512:     }
513: #endif
514:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve");

516:   MatDenseRestoreArray(B,&b);
517:   MatDenseRestoreArray(X,&x);
518:   PetscLogFlops(nrhs*(2.0*m*m - m));
519:   return(0);
520: }

522: static PetscErrorCode MatConjugate_SeqDense(Mat);

524: static PetscErrorCode MatSolveTranspose_SeqDense(Mat A,Vec xx,Vec yy)
525: {
526:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
527:   PetscErrorCode    ierr;
528:   const PetscScalar *x;
529:   PetscScalar       *y;
530:   PetscBLASInt      one = 1,info,m;

533:   PetscBLASIntCast(A->rmap->n,&m);
534:   VecGetArrayRead(xx,&x);
535:   VecGetArray(yy,&y);
536:   PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));
537:   if (A->factortype == MAT_FACTOR_LU) {
538: #if defined(PETSC_MISSING_LAPACK_GETRS)
539:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
540: #else
541:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
542:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("T",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
543:     PetscFPTrapPop();
544:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS - Bad solve");
545: #endif
546:   } else if (A->factortype == MAT_FACTOR_CHOLESKY) {
547: #if defined(PETSC_MISSING_LAPACK_POTRS)
548:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
549: #else
550:     if (A->spd) {
551: #if defined(PETSC_USE_COMPLEX)
552:       MatConjugate_SeqDense(A);
553: #endif
554:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
555:       PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info));
556:       PetscFPTrapPop();
557: #if defined(PETSC_USE_COMPLEX)
558:       MatConjugate_SeqDense(A);
559: #endif
560:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve");
561: #if defined(PETSC_USE_COMPLEX)
562:     } else if (A->hermitian) {
563:       MatConjugate_SeqDense(A);
564:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
565:       PetscStackCallBLAS("LAPACKhetrs",LAPACKhetrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
566:       PetscFPTrapPop();
567:       MatConjugate_SeqDense(A);
568: #endif
569:     } else { /* symmetric case */
570:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
571:       PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
572:       PetscFPTrapPop();
573:       if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve");
574:     }
575: #endif
576:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve");
577:   VecRestoreArrayRead(xx,&x);
578:   VecRestoreArray(yy,&y);
579:   PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);
580:   return(0);
581: }

583: static PetscErrorCode MatSolveAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
584: {
585:   PetscErrorCode    ierr;
586:   const PetscScalar *x;
587:   PetscScalar       *y,sone = 1.0;
588:   Vec               tmp = 0;

591:   VecGetArrayRead(xx,&x);
592:   VecGetArray(yy,&y);
593:   if (!A->rmap->n || !A->cmap->n) return(0);
594:   if (yy == zz) {
595:     VecDuplicate(yy,&tmp);
596:     PetscLogObjectParent((PetscObject)A,(PetscObject)tmp);
597:     VecCopy(yy,tmp);
598:   }
599:   MatSolve_SeqDense(A,xx,yy);
600:   if (tmp) {
601:     VecAXPY(yy,sone,tmp);
602:     VecDestroy(&tmp);
603:   } else {
604:     VecAXPY(yy,sone,zz);
605:   }
606:   VecRestoreArrayRead(xx,&x);
607:   VecRestoreArray(yy,&y);
608:   PetscLogFlops(A->cmap->n);
609:   return(0);
610: }

612: static PetscErrorCode MatSolveTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
613: {
614:   PetscErrorCode    ierr;
615:   const PetscScalar *x;
616:   PetscScalar       *y,sone = 1.0;
617:   Vec               tmp = NULL;

620:   if (!A->rmap->n || !A->cmap->n) return(0);
621:   VecGetArrayRead(xx,&x);
622:   VecGetArray(yy,&y);
623:   if (yy == zz) {
624:     VecDuplicate(yy,&tmp);
625:     PetscLogObjectParent((PetscObject)A,(PetscObject)tmp);
626:     VecCopy(yy,tmp);
627:   }
628:   MatSolveTranspose_SeqDense(A,xx,yy);
629:   if (tmp) {
630:     VecAXPY(yy,sone,tmp);
631:     VecDestroy(&tmp);
632:   } else {
633:     VecAXPY(yy,sone,zz);
634:   }
635:   VecRestoreArrayRead(xx,&x);
636:   VecRestoreArray(yy,&y);
637:   PetscLogFlops(A->cmap->n);
638:   return(0);
639: }

641: /* ---------------------------------------------------------------*/
642: /* COMMENT: I have chosen to hide row permutation in the pivots,
643:    rather than put it in the Mat->row slot.*/
644: static PetscErrorCode MatLUFactor_SeqDense(Mat A,IS row,IS col,const MatFactorInfo *minfo)
645: {
646: #if defined(PETSC_MISSING_LAPACK_GETRF)
648:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRF - Lapack routine is unavailable.");
649: #else
650:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
652:   PetscBLASInt   n,m,info;

655:   PetscBLASIntCast(A->cmap->n,&n);
656:   PetscBLASIntCast(A->rmap->n,&m);
657:   if (!mat->pivots) {
658:     PetscMalloc1(A->rmap->n,&mat->pivots);
659:     PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));
660:   }
661:   if (!A->rmap->n || !A->cmap->n) return(0);
662:   PetscFPTrapPush(PETSC_FP_TRAP_OFF);
663:   PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&m,&n,mat->v,&mat->lda,mat->pivots,&info));
664:   PetscFPTrapPop();

666:   if (info<0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad argument to LU factorization");
667:   if (info>0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Bad LU factorization");

669:   A->ops->solve             = MatSolve_SeqDense;
670:   A->ops->matsolve          = MatMatSolve_SeqDense;
671:   A->ops->solvetranspose    = MatSolveTranspose_SeqDense;
672:   A->ops->solveadd          = MatSolveAdd_SeqDense;
673:   A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense;
674:   A->factortype             = MAT_FACTOR_LU;

676:   PetscFree(A->solvertype);
677:   PetscStrallocpy(MATSOLVERPETSC,&A->solvertype);

679:   PetscLogFlops((2.0*A->cmap->n*A->cmap->n*A->cmap->n)/3);
680: #endif
681:   return(0);
682: }

684: /* Cholesky as L*L^T or L*D*L^T and the symmetric/hermitian complex variants */
685: static PetscErrorCode MatCholeskyFactor_SeqDense(Mat A,IS perm,const MatFactorInfo *factinfo)
686: {
687: #if defined(PETSC_MISSING_LAPACK_POTRF)
689:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable.");
690: #else
691:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
693:   PetscBLASInt   info,n;

696:   PetscBLASIntCast(A->cmap->n,&n);
697:   if (!A->rmap->n || !A->cmap->n) return(0);
698:   if (A->spd) {
699:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
700:     PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&n,mat->v,&mat->lda,&info));
701:     PetscFPTrapPop();
702: #if defined(PETSC_USE_COMPLEX)
703:   } else if (A->hermitian) {
704:     if (!mat->pivots) {
705:       PetscMalloc1(A->rmap->n,&mat->pivots);
706:       PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));
707:     }
708:     if (!mat->fwork) {
709:       PetscScalar dummy;

711:       mat->lfwork = -1;
712:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
713:       PetscStackCallBLAS("LAPACKhetrf",LAPACKhetrf_("L",&n,mat->v,&mat->lda,mat->pivots,&dummy,&mat->lfwork,&info));
714:       PetscFPTrapPop();
715:       mat->lfwork = (PetscInt)PetscRealPart(dummy);
716:       PetscMalloc1(mat->lfwork,&mat->fwork);
717:       PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));
718:     }
719:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
720:     PetscStackCallBLAS("LAPACKhetrf",LAPACKhetrf_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info));
721:     PetscFPTrapPop();
722: #endif
723:   } else { /* symmetric case */
724:     if (!mat->pivots) {
725:       PetscMalloc1(A->rmap->n,&mat->pivots);
726:       PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));
727:     }
728:     if (!mat->fwork) {
729:       PetscScalar dummy;

731:       mat->lfwork = -1;
732:       PetscFPTrapPush(PETSC_FP_TRAP_OFF);
733:       PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&n,mat->v,&mat->lda,mat->pivots,&dummy,&mat->lfwork,&info));
734:       PetscFPTrapPop();
735:       mat->lfwork = (PetscInt)PetscRealPart(dummy);
736:       PetscMalloc1(mat->lfwork,&mat->fwork);
737:       PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));
738:     }
739:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
740:     PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info));
741:     PetscFPTrapPop();
742:   }
743:   if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad factorization: zero pivot in row %D",(PetscInt)info-1);

745:   A->ops->solve             = MatSolve_SeqDense;
746:   A->ops->matsolve          = MatMatSolve_SeqDense;
747:   A->ops->solvetranspose    = MatSolveTranspose_SeqDense;
748:   A->ops->solveadd          = MatSolveAdd_SeqDense;
749:   A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense;
750:   A->factortype             = MAT_FACTOR_CHOLESKY;

752:   PetscFree(A->solvertype);
753:   PetscStrallocpy(MATSOLVERPETSC,&A->solvertype);

755:   PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0);
756: #endif
757:   return(0);
758: }


761: PetscErrorCode MatCholeskyFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy)
762: {
764:   MatFactorInfo  info;

767:   info.fill = 1.0;

769:   MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);
770:   MatCholeskyFactor_SeqDense(fact,0,&info);
771:   return(0);
772: }

774: static PetscErrorCode MatCholeskyFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,const MatFactorInfo *info)
775: {
777:   fact->assembled                  = PETSC_TRUE;
778:   fact->preallocated               = PETSC_TRUE;
779:   fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqDense;
780:   fact->ops->solve                 = MatSolve_SeqDense;
781:   fact->ops->matsolve              = MatMatSolve_SeqDense;
782:   fact->ops->solvetranspose        = MatSolveTranspose_SeqDense;
783:   fact->ops->solveadd              = MatSolveAdd_SeqDense;
784:   fact->ops->solvetransposeadd     = MatSolveTransposeAdd_SeqDense;
785:   return(0);
786: }

788: static PetscErrorCode MatLUFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,IS col,const MatFactorInfo *info)
789: {
791:   fact->preallocated           = PETSC_TRUE;
792:   fact->assembled              = PETSC_TRUE;
793:   fact->ops->lufactornumeric   = MatLUFactorNumeric_SeqDense;
794:   fact->ops->solve             = MatSolve_SeqDense;
795:   fact->ops->matsolve          = MatMatSolve_SeqDense;
796:   fact->ops->solvetranspose    = MatSolveTranspose_SeqDense;
797:   fact->ops->solveadd          = MatSolveAdd_SeqDense;
798:   fact->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense;
799:   return(0);
800: }

802: PETSC_INTERN PetscErrorCode MatGetFactor_seqdense_petsc(Mat A,MatFactorType ftype,Mat *fact)
803: {

807:   MatCreate(PetscObjectComm((PetscObject)A),fact);
808:   MatSetSizes(*fact,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);
809:   MatSetType(*fact,((PetscObject)A)->type_name);
810:   if (ftype == MAT_FACTOR_LU) {
811:     (*fact)->ops->lufactorsymbolic = MatLUFactorSymbolic_SeqDense;
812:   } else {
813:     (*fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqDense;
814:   }
815:   (*fact)->factortype = ftype;

817:   PetscFree((*fact)->solvertype);
818:   PetscStrallocpy(MATSOLVERPETSC,&(*fact)->solvertype);
819:   return(0);
820: }

822: /* ------------------------------------------------------------------*/
823: static PetscErrorCode MatSOR_SeqDense(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal shift,PetscInt its,PetscInt lits,Vec xx)
824: {
825:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
826:   PetscScalar       *x,*v = mat->v,zero = 0.0,xt;
827:   const PetscScalar *b;
828:   PetscErrorCode    ierr;
829:   PetscInt          m = A->rmap->n,i;
830:   PetscBLASInt      o = 1,bm;

833:   if (shift == -1) shift = 0.0; /* negative shift indicates do not error on zero diagonal; this code never zeros on zero diagonal */
834:   PetscBLASIntCast(m,&bm);
835:   if (flag & SOR_ZERO_INITIAL_GUESS) {
836:     /* this is a hack fix, should have another version without the second BLASdotu */
837:     VecSet(xx,zero);
838:   }
839:   VecGetArray(xx,&x);
840:   VecGetArrayRead(bb,&b);
841:   its  = its*lits;
842:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
843:   while (its--) {
844:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
845:       for (i=0; i<m; i++) {
846:         PetscStackCallBLAS("BLASdotu",xt   = b[i] - BLASdotu_(&bm,v+i,&bm,x,&o));
847:         x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift);
848:       }
849:     }
850:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
851:       for (i=m-1; i>=0; i--) {
852:         PetscStackCallBLAS("BLASdotu",xt   = b[i] - BLASdotu_(&bm,v+i,&bm,x,&o));
853:         x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift);
854:       }
855:     }
856:   }
857:   VecRestoreArrayRead(bb,&b);
858:   VecRestoreArray(xx,&x);
859:   return(0);
860: }

862: /* -----------------------------------------------------------------*/
863: PETSC_INTERN PetscErrorCode MatMultTranspose_SeqDense(Mat A,Vec xx,Vec yy)
864: {
865:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
866:   const PetscScalar *v   = mat->v,*x;
867:   PetscScalar       *y;
868:   PetscErrorCode    ierr;
869:   PetscBLASInt      m, n,_One=1;
870:   PetscScalar       _DOne=1.0,_DZero=0.0;

873:   PetscBLASIntCast(A->rmap->n,&m);
874:   PetscBLASIntCast(A->cmap->n,&n);
875:   VecGetArrayRead(xx,&x);
876:   VecGetArray(yy,&y);
877:   if (!A->rmap->n || !A->cmap->n) {
878:     PetscBLASInt i;
879:     for (i=0; i<n; i++) y[i] = 0.0;
880:   } else {
881:     PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&mat->lda,x,&_One,&_DZero,y,&_One));
882:     PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->cmap->n);
883:   }
884:   VecRestoreArrayRead(xx,&x);
885:   VecRestoreArray(yy,&y);
886:   return(0);
887: }

889: PETSC_INTERN PetscErrorCode MatMult_SeqDense(Mat A,Vec xx,Vec yy)
890: {
891:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
892:   PetscScalar       *y,_DOne=1.0,_DZero=0.0;
893:   PetscErrorCode    ierr;
894:   PetscBLASInt      m, n, _One=1;
895:   const PetscScalar *v = mat->v,*x;

898:   PetscBLASIntCast(A->rmap->n,&m);
899:   PetscBLASIntCast(A->cmap->n,&n);
900:   VecGetArrayRead(xx,&x);
901:   VecGetArray(yy,&y);
902:   if (!A->rmap->n || !A->cmap->n) {
903:     PetscBLASInt i;
904:     for (i=0; i<m; i++) y[i] = 0.0;
905:   } else {
906:     PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DZero,y,&_One));
907:     PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->rmap->n);
908:   }
909:   VecRestoreArrayRead(xx,&x);
910:   VecRestoreArray(yy,&y);
911:   return(0);
912: }

914: PETSC_INTERN PetscErrorCode MatMultAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
915: {
916:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
917:   const PetscScalar *v = mat->v,*x;
918:   PetscScalar       *y,_DOne=1.0;
919:   PetscErrorCode    ierr;
920:   PetscBLASInt      m, n, _One=1;

923:   PetscBLASIntCast(A->rmap->n,&m);
924:   PetscBLASIntCast(A->cmap->n,&n);
925:   if (!A->rmap->n || !A->cmap->n) return(0);
926:   if (zz != yy) {VecCopy(zz,yy);}
927:   VecGetArrayRead(xx,&x);
928:   VecGetArray(yy,&y);
929:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One));
930:   VecRestoreArrayRead(xx,&x);
931:   VecRestoreArray(yy,&y);
932:   PetscLogFlops(2.0*A->rmap->n*A->cmap->n);
933:   return(0);
934: }

936: static PetscErrorCode MatMultTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
937: {
938:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
939:   const PetscScalar *v = mat->v,*x;
940:   PetscScalar       *y;
941:   PetscErrorCode    ierr;
942:   PetscBLASInt      m, n, _One=1;
943:   PetscScalar       _DOne=1.0;

946:   PetscBLASIntCast(A->rmap->n,&m);
947:   PetscBLASIntCast(A->cmap->n,&n);
948:   if (!A->rmap->n || !A->cmap->n) return(0);
949:   if (zz != yy) {VecCopy(zz,yy);}
950:   VecGetArrayRead(xx,&x);
951:   VecGetArray(yy,&y);
952:   PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One));
953:   VecRestoreArrayRead(xx,&x);
954:   VecRestoreArray(yy,&y);
955:   PetscLogFlops(2.0*A->rmap->n*A->cmap->n);
956:   return(0);
957: }

959: /* -----------------------------------------------------------------*/
960: static PetscErrorCode MatGetRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals)
961: {
962:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
963:   PetscScalar    *v;
965:   PetscInt       i;

968:   *ncols = A->cmap->n;
969:   if (cols) {
970:     PetscMalloc1(A->cmap->n+1,cols);
971:     for (i=0; i<A->cmap->n; i++) (*cols)[i] = i;
972:   }
973:   if (vals) {
974:     PetscMalloc1(A->cmap->n+1,vals);
975:     v    = mat->v + row;
976:     for (i=0; i<A->cmap->n; i++) {(*vals)[i] = *v; v += mat->lda;}
977:   }
978:   return(0);
979: }

981: static PetscErrorCode MatRestoreRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals)
982: {

986:   if (cols) {PetscFree(*cols);}
987:   if (vals) {PetscFree(*vals); }
988:   return(0);
989: }
990: /* ----------------------------------------------------------------*/
991: static PetscErrorCode MatSetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],const PetscScalar v[],InsertMode addv)
992: {
993:   Mat_SeqDense *mat = (Mat_SeqDense*)A->data;
994:   PetscInt     i,j,idx=0;

997:   if (!mat->roworiented) {
998:     if (addv == INSERT_VALUES) {
999:       for (j=0; j<n; j++) {
1000:         if (indexn[j] < 0) {idx += m; continue;}
1001: #if defined(PETSC_USE_DEBUG)
1002:         if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1);
1003: #endif
1004:         for (i=0; i<m; i++) {
1005:           if (indexm[i] < 0) {idx++; continue;}
1006: #if defined(PETSC_USE_DEBUG)
1007:           if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1);
1008: #endif
1009:           mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++];
1010:         }
1011:       }
1012:     } else {
1013:       for (j=0; j<n; j++) {
1014:         if (indexn[j] < 0) {idx += m; continue;}
1015: #if defined(PETSC_USE_DEBUG)
1016:         if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1);
1017: #endif
1018:         for (i=0; i<m; i++) {
1019:           if (indexm[i] < 0) {idx++; continue;}
1020: #if defined(PETSC_USE_DEBUG)
1021:           if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1);
1022: #endif
1023:           mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++];
1024:         }
1025:       }
1026:     }
1027:   } else {
1028:     if (addv == INSERT_VALUES) {
1029:       for (i=0; i<m; i++) {
1030:         if (indexm[i] < 0) { idx += n; continue;}
1031: #if defined(PETSC_USE_DEBUG)
1032:         if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1);
1033: #endif
1034:         for (j=0; j<n; j++) {
1035:           if (indexn[j] < 0) { idx++; continue;}
1036: #if defined(PETSC_USE_DEBUG)
1037:           if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1);
1038: #endif
1039:           mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++];
1040:         }
1041:       }
1042:     } else {
1043:       for (i=0; i<m; i++) {
1044:         if (indexm[i] < 0) { idx += n; continue;}
1045: #if defined(PETSC_USE_DEBUG)
1046:         if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1);
1047: #endif
1048:         for (j=0; j<n; j++) {
1049:           if (indexn[j] < 0) { idx++; continue;}
1050: #if defined(PETSC_USE_DEBUG)
1051:           if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1);
1052: #endif
1053:           mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++];
1054:         }
1055:       }
1056:     }
1057:   }
1058:   return(0);
1059: }

1061: static PetscErrorCode MatGetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],PetscScalar v[])
1062: {
1063:   Mat_SeqDense *mat = (Mat_SeqDense*)A->data;
1064:   PetscInt     i,j;

1067:   /* row-oriented output */
1068:   for (i=0; i<m; i++) {
1069:     if (indexm[i] < 0) {v += n;continue;}
1070:     if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested larger than number rows %D",indexm[i],A->rmap->n);
1071:     for (j=0; j<n; j++) {
1072:       if (indexn[j] < 0) {v++; continue;}
1073:       if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D requested larger than number columns %D",indexn[j],A->cmap->n);
1074:       *v++ = mat->v[indexn[j]*mat->lda + indexm[i]];
1075:     }
1076:   }
1077:   return(0);
1078: }

1080: /* -----------------------------------------------------------------*/

1082: static PetscErrorCode MatLoad_SeqDense(Mat newmat,PetscViewer viewer)
1083: {
1084:   Mat_SeqDense   *a;
1086:   PetscInt       *scols,i,j,nz,header[4];
1087:   int            fd;
1088:   PetscMPIInt    size;
1089:   PetscInt       *rowlengths = 0,M,N,*cols,grows,gcols;
1090:   PetscScalar    *vals,*svals,*v,*w;
1091:   MPI_Comm       comm;
1092:   PetscBool      isbinary;

1095:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1096:   if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)newmat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newmat)->type_name);

1098:   /* force binary viewer to load .info file if it has not yet done so */
1099:   PetscViewerSetUp(viewer);
1100:   PetscObjectGetComm((PetscObject)viewer,&comm);
1101:   MPI_Comm_size(comm,&size);
1102:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor");
1103:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1104:   PetscBinaryRead(fd,header,4,PETSC_INT);
1105:   if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not matrix object");
1106:   M = header[1]; N = header[2]; nz = header[3];

1108:   /* set global size if not set already*/
1109:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) {
1110:     MatSetSizes(newmat,M,N,M,N);
1111:   } else {
1112:     /* if sizes and type are already set, check if the vector global sizes are correct */
1113:     MatGetSize(newmat,&grows,&gcols);
1114:     if (M != grows ||  N != gcols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,grows,gcols);
1115:   }
1116:   a = (Mat_SeqDense*)newmat->data;
1117:   if (!a->user_alloc) {
1118:     MatSeqDenseSetPreallocation(newmat,NULL);
1119:   }

1121:   if (nz == MATRIX_BINARY_FORMAT_DENSE) { /* matrix in file is dense */
1122:     a = (Mat_SeqDense*)newmat->data;
1123:     v = a->v;
1124:     /* Allocate some temp space to read in the values and then flip them
1125:        from row major to column major */
1126:     PetscMalloc1(M*N > 0 ? M*N : 1,&w);
1127:     /* read in nonzero values */
1128:     PetscBinaryRead(fd,w,M*N,PETSC_SCALAR);
1129:     /* now flip the values and store them in the matrix*/
1130:     for (j=0; j<N; j++) {
1131:       for (i=0; i<M; i++) {
1132:         *v++ =w[i*N+j];
1133:       }
1134:     }
1135:     PetscFree(w);
1136:   } else {
1137:     /* read row lengths */
1138:     PetscMalloc1(M+1,&rowlengths);
1139:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);

1141:     a = (Mat_SeqDense*)newmat->data;
1142:     v = a->v;

1144:     /* read column indices and nonzeros */
1145:     PetscMalloc1(nz+1,&scols);
1146:     cols = scols;
1147:     PetscBinaryRead(fd,cols,nz,PETSC_INT);
1148:     PetscMalloc1(nz+1,&svals);
1149:     vals = svals;
1150:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

1152:     /* insert into matrix */
1153:     for (i=0; i<M; i++) {
1154:       for (j=0; j<rowlengths[i]; j++) v[i+M*scols[j]] = svals[j];
1155:       svals += rowlengths[i]; scols += rowlengths[i];
1156:     }
1157:     PetscFree(vals);
1158:     PetscFree(cols);
1159:     PetscFree(rowlengths);
1160:   }
1161:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
1162:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
1163:   return(0);
1164: }

1166: static PetscErrorCode MatView_SeqDense_ASCII(Mat A,PetscViewer viewer)
1167: {
1168:   Mat_SeqDense      *a = (Mat_SeqDense*)A->data;
1169:   PetscErrorCode    ierr;
1170:   PetscInt          i,j;
1171:   const char        *name;
1172:   PetscScalar       *v;
1173:   PetscViewerFormat format;
1174: #if defined(PETSC_USE_COMPLEX)
1175:   PetscBool         allreal = PETSC_TRUE;
1176: #endif

1179:   PetscViewerGetFormat(viewer,&format);
1180:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1181:     return(0);  /* do nothing for now */
1182:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
1183:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1184:     for (i=0; i<A->rmap->n; i++) {
1185:       v    = a->v + i;
1186:       PetscViewerASCIIPrintf(viewer,"row %D:",i);
1187:       for (j=0; j<A->cmap->n; j++) {
1188: #if defined(PETSC_USE_COMPLEX)
1189:         if (PetscRealPart(*v) != 0.0 && PetscImaginaryPart(*v) != 0.0) {
1190:           PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",j,(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));
1191:         } else if (PetscRealPart(*v)) {
1192:           PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)PetscRealPart(*v));
1193:         }
1194: #else
1195:         if (*v) {
1196:           PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)*v);
1197:         }
1198: #endif
1199:         v += a->lda;
1200:       }
1201:       PetscViewerASCIIPrintf(viewer,"\n");
1202:     }
1203:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1204:   } else {
1205:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1206: #if defined(PETSC_USE_COMPLEX)
1207:     /* determine if matrix has all real values */
1208:     v = a->v;
1209:     for (i=0; i<A->rmap->n*A->cmap->n; i++) {
1210:       if (PetscImaginaryPart(v[i])) { allreal = PETSC_FALSE; break;}
1211:     }
1212: #endif
1213:     if (format == PETSC_VIEWER_ASCII_MATLAB) {
1214:       PetscObjectGetName((PetscObject)A,&name);
1215:       PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",A->rmap->n,A->cmap->n);
1216:       PetscViewerASCIIPrintf(viewer,"%s = zeros(%D,%D);\n",name,A->rmap->n,A->cmap->n);
1217:       PetscViewerASCIIPrintf(viewer,"%s = [\n",name);
1218:     }

1220:     for (i=0; i<A->rmap->n; i++) {
1221:       v = a->v + i;
1222:       for (j=0; j<A->cmap->n; j++) {
1223: #if defined(PETSC_USE_COMPLEX)
1224:         if (allreal) {
1225:           PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)PetscRealPart(*v));
1226:         } else {
1227:           PetscViewerASCIIPrintf(viewer,"%18.16e + %18.16ei ",(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));
1228:         }
1229: #else
1230:         PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*v);
1231: #endif
1232:         v += a->lda;
1233:       }
1234:       PetscViewerASCIIPrintf(viewer,"\n");
1235:     }
1236:     if (format == PETSC_VIEWER_ASCII_MATLAB) {
1237:       PetscViewerASCIIPrintf(viewer,"];\n");
1238:     }
1239:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1240:   }
1241:   PetscViewerFlush(viewer);
1242:   return(0);
1243: }

1245: static PetscErrorCode MatView_SeqDense_Binary(Mat A,PetscViewer viewer)
1246: {
1247:   Mat_SeqDense      *a = (Mat_SeqDense*)A->data;
1248:   PetscErrorCode    ierr;
1249:   int               fd;
1250:   PetscInt          ict,j,n = A->cmap->n,m = A->rmap->n,i,*col_lens,nz = m*n;
1251:   PetscScalar       *v,*anonz,*vals;
1252:   PetscViewerFormat format;

1255:   PetscViewerBinaryGetDescriptor(viewer,&fd);

1257:   PetscViewerGetFormat(viewer,&format);
1258:   if (format == PETSC_VIEWER_NATIVE) {
1259:     /* store the matrix as a dense matrix */
1260:     PetscMalloc1(4,&col_lens);

1262:     col_lens[0] = MAT_FILE_CLASSID;
1263:     col_lens[1] = m;
1264:     col_lens[2] = n;
1265:     col_lens[3] = MATRIX_BINARY_FORMAT_DENSE;

1267:     PetscBinaryWrite(fd,col_lens,4,PETSC_INT,PETSC_TRUE);
1268:     PetscFree(col_lens);

1270:     /* write out matrix, by rows */
1271:     PetscMalloc1(m*n+1,&vals);
1272:     v    = a->v;
1273:     for (j=0; j<n; j++) {
1274:       for (i=0; i<m; i++) {
1275:         vals[j + i*n] = *v++;
1276:       }
1277:     }
1278:     PetscBinaryWrite(fd,vals,n*m,PETSC_SCALAR,PETSC_FALSE);
1279:     PetscFree(vals);
1280:   } else {
1281:     PetscMalloc1(4+nz,&col_lens);

1283:     col_lens[0] = MAT_FILE_CLASSID;
1284:     col_lens[1] = m;
1285:     col_lens[2] = n;
1286:     col_lens[3] = nz;

1288:     /* store lengths of each row and write (including header) to file */
1289:     for (i=0; i<m; i++) col_lens[4+i] = n;
1290:     PetscBinaryWrite(fd,col_lens,4+m,PETSC_INT,PETSC_TRUE);

1292:     /* Possibly should write in smaller increments, not whole matrix at once? */
1293:     /* store column indices (zero start index) */
1294:     ict = 0;
1295:     for (i=0; i<m; i++) {
1296:       for (j=0; j<n; j++) col_lens[ict++] = j;
1297:     }
1298:     PetscBinaryWrite(fd,col_lens,nz,PETSC_INT,PETSC_FALSE);
1299:     PetscFree(col_lens);

1301:     /* store nonzero values */
1302:     PetscMalloc1(nz+1,&anonz);
1303:     ict  = 0;
1304:     for (i=0; i<m; i++) {
1305:       v = a->v + i;
1306:       for (j=0; j<n; j++) {
1307:         anonz[ict++] = *v; v += a->lda;
1308:       }
1309:     }
1310:     PetscBinaryWrite(fd,anonz,nz,PETSC_SCALAR,PETSC_FALSE);
1311:     PetscFree(anonz);
1312:   }
1313:   return(0);
1314: }

1316:  #include <petscdraw.h>
1317: static PetscErrorCode MatView_SeqDense_Draw_Zoom(PetscDraw draw,void *Aa)
1318: {
1319:   Mat               A  = (Mat) Aa;
1320:   Mat_SeqDense      *a = (Mat_SeqDense*)A->data;
1321:   PetscErrorCode    ierr;
1322:   PetscInt          m  = A->rmap->n,n = A->cmap->n,i,j;
1323:   int               color = PETSC_DRAW_WHITE;
1324:   PetscScalar       *v = a->v;
1325:   PetscViewer       viewer;
1326:   PetscReal         xl,yl,xr,yr,x_l,x_r,y_l,y_r;
1327:   PetscViewerFormat format;

1330:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
1331:   PetscViewerGetFormat(viewer,&format);
1332:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);

1334:   /* Loop over matrix elements drawing boxes */

1336:   if (format != PETSC_VIEWER_DRAW_CONTOUR) {
1337:     PetscDrawCollectiveBegin(draw);
1338:     /* Blue for negative and Red for positive */
1339:     for (j = 0; j < n; j++) {
1340:       x_l = j; x_r = x_l + 1.0;
1341:       for (i = 0; i < m; i++) {
1342:         y_l = m - i - 1.0;
1343:         y_r = y_l + 1.0;
1344:         if (PetscRealPart(v[j*m+i]) >  0.) {
1345:           color = PETSC_DRAW_RED;
1346:         } else if (PetscRealPart(v[j*m+i]) <  0.) {
1347:           color = PETSC_DRAW_BLUE;
1348:         } else {
1349:           continue;
1350:         }
1351:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1352:       }
1353:     }
1354:     PetscDrawCollectiveEnd(draw);
1355:   } else {
1356:     /* use contour shading to indicate magnitude of values */
1357:     /* first determine max of all nonzero values */
1358:     PetscReal minv = 0.0, maxv = 0.0;
1359:     PetscDraw popup;

1361:     for (i=0; i < m*n; i++) {
1362:       if (PetscAbsScalar(v[i]) > maxv) maxv = PetscAbsScalar(v[i]);
1363:     }
1364:     if (minv >= maxv) maxv = minv + PETSC_SMALL;
1365:     PetscDrawGetPopup(draw,&popup);
1366:     PetscDrawScalePopup(popup,minv,maxv);

1368:     PetscDrawCollectiveBegin(draw);
1369:     for (j=0; j<n; j++) {
1370:       x_l = j;
1371:       x_r = x_l + 1.0;
1372:       for (i=0; i<m; i++) {
1373:         y_l = m - i - 1.0;
1374:         y_r = y_l + 1.0;
1375:         color = PetscDrawRealToColor(PetscAbsScalar(v[j*m+i]),minv,maxv);
1376:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1377:       }
1378:     }
1379:     PetscDrawCollectiveEnd(draw);
1380:   }
1381:   return(0);
1382: }

1384: static PetscErrorCode MatView_SeqDense_Draw(Mat A,PetscViewer viewer)
1385: {
1386:   PetscDraw      draw;
1387:   PetscBool      isnull;
1388:   PetscReal      xr,yr,xl,yl,h,w;

1392:   PetscViewerDrawGetDraw(viewer,0,&draw);
1393:   PetscDrawIsNull(draw,&isnull);
1394:   if (isnull) return(0);

1396:   xr   = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0;
1397:   xr  += w;          yr += h;        xl = -w;     yl = -h;
1398:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
1399:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
1400:   PetscDrawZoom(draw,MatView_SeqDense_Draw_Zoom,A);
1401:   PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
1402:   PetscDrawSave(draw);
1403:   return(0);
1404: }

1406: PetscErrorCode MatView_SeqDense(Mat A,PetscViewer viewer)
1407: {
1409:   PetscBool      iascii,isbinary,isdraw;

1412:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1413:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1414:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);

1416:   if (iascii) {
1417:     MatView_SeqDense_ASCII(A,viewer);
1418:   } else if (isbinary) {
1419:     MatView_SeqDense_Binary(A,viewer);
1420:   } else if (isdraw) {
1421:     MatView_SeqDense_Draw(A,viewer);
1422:   }
1423:   return(0);
1424: }

1426: static PetscErrorCode MatDensePlaceArray_SeqDense(Mat A,const PetscScalar array[])
1427: {
1428:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;

1431:   a->unplacedarray       = a->v;
1432:   a->unplaced_user_alloc = a->user_alloc;
1433:   a->v                   = (PetscScalar*) array;
1434:   return(0);
1435: }

1437: static PetscErrorCode MatDenseResetArray_SeqDense(Mat A)
1438: {
1439:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;

1442:   a->v             = a->unplacedarray;
1443:   a->user_alloc    = a->unplaced_user_alloc;
1444:   a->unplacedarray = NULL;
1445:   return(0);
1446: }

1448: static PetscErrorCode MatDestroy_SeqDense(Mat mat)
1449: {
1450:   Mat_SeqDense   *l = (Mat_SeqDense*)mat->data;

1454: #if defined(PETSC_USE_LOG)
1455:   PetscLogObjectState((PetscObject)mat,"Rows %D Cols %D",mat->rmap->n,mat->cmap->n);
1456: #endif
1457:   PetscFree(l->pivots);
1458:   PetscFree(l->fwork);
1459:   MatDestroy(&l->ptapwork);
1460:   if (!l->user_alloc) {PetscFree(l->v);}
1461:   PetscFree(mat->data);

1463:   PetscObjectChangeTypeName((PetscObject)mat,0);
1464:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);
1465:   PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",NULL);
1466:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",NULL);
1467:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);
1468:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_seqaij_C",NULL);
1469: #if defined(PETSC_HAVE_ELEMENTAL)
1470:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_elemental_C",NULL);
1471: #endif
1472:   PetscObjectComposeFunction((PetscObject)mat,"MatSeqDenseSetPreallocation_C",NULL);
1473:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_seqaij_seqdense_C",NULL);
1474:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_seqaij_seqdense_C",NULL);
1475:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_seqaij_seqdense_C",NULL);
1476:   PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_seqaij_seqdense_C",NULL);
1477:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_seqaij_seqdense_C",NULL);
1478:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",NULL);
1479:   PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_seqaij_seqdense_C",NULL);
1480:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetColumn_C",NULL);
1481:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreColumn_C",NULL);
1482:   return(0);
1483: }

1485: static PetscErrorCode MatTranspose_SeqDense(Mat A,MatReuse reuse,Mat *matout)
1486: {
1487:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1489:   PetscInt       k,j,m,n,M;
1490:   PetscScalar    *v,tmp;

1493:   v = mat->v; m = A->rmap->n; M = mat->lda; n = A->cmap->n;
1494:   if (reuse == MAT_INPLACE_MATRIX && m == n) { /* in place transpose */
1495:     for (j=0; j<m; j++) {
1496:       for (k=0; k<j; k++) {
1497:         tmp        = v[j + k*M];
1498:         v[j + k*M] = v[k + j*M];
1499:         v[k + j*M] = tmp;
1500:       }
1501:     }
1502:   } else { /* out-of-place transpose */
1503:     Mat          tmat;
1504:     Mat_SeqDense *tmatd;
1505:     PetscScalar  *v2;
1506:     PetscInt     M2;

1508:     if (reuse != MAT_REUSE_MATRIX) {
1509:       MatCreate(PetscObjectComm((PetscObject)A),&tmat);
1510:       MatSetSizes(tmat,A->cmap->n,A->rmap->n,A->cmap->n,A->rmap->n);
1511:       MatSetType(tmat,((PetscObject)A)->type_name);
1512:       MatSeqDenseSetPreallocation(tmat,NULL);
1513:     } else {
1514:       tmat = *matout;
1515:     }
1516:     tmatd = (Mat_SeqDense*)tmat->data;
1517:     v = mat->v; v2 = tmatd->v; M2 = tmatd->lda;
1518:     for (j=0; j<n; j++) {
1519:       for (k=0; k<m; k++) v2[j + k*M2] = v[k + j*M];
1520:     }
1521:     MatAssemblyBegin(tmat,MAT_FINAL_ASSEMBLY);
1522:     MatAssemblyEnd(tmat,MAT_FINAL_ASSEMBLY);
1523:     if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) *matout = tmat;
1524:     else {
1525:       MatHeaderMerge(A,&tmat);
1526:     }
1527:   }
1528:   return(0);
1529: }

1531: static PetscErrorCode MatEqual_SeqDense(Mat A1,Mat A2,PetscBool  *flg)
1532: {
1533:   Mat_SeqDense *mat1 = (Mat_SeqDense*)A1->data;
1534:   Mat_SeqDense *mat2 = (Mat_SeqDense*)A2->data;
1535:   PetscInt     i,j;
1536:   PetscScalar  *v1,*v2;

1539:   if (A1->rmap->n != A2->rmap->n) {*flg = PETSC_FALSE; return(0);}
1540:   if (A1->cmap->n != A2->cmap->n) {*flg = PETSC_FALSE; return(0);}
1541:   for (i=0; i<A1->rmap->n; i++) {
1542:     v1 = mat1->v+i; v2 = mat2->v+i;
1543:     for (j=0; j<A1->cmap->n; j++) {
1544:       if (*v1 != *v2) {*flg = PETSC_FALSE; return(0);}
1545:       v1 += mat1->lda; v2 += mat2->lda;
1546:     }
1547:   }
1548:   *flg = PETSC_TRUE;
1549:   return(0);
1550: }

1552: static PetscErrorCode MatGetDiagonal_SeqDense(Mat A,Vec v)
1553: {
1554:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1556:   PetscInt       i,n,len;
1557:   PetscScalar    *x,zero = 0.0;

1560:   VecSet(v,zero);
1561:   VecGetSize(v,&n);
1562:   VecGetArray(v,&x);
1563:   len  = PetscMin(A->rmap->n,A->cmap->n);
1564:   if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec");
1565:   for (i=0; i<len; i++) {
1566:     x[i] = mat->v[i*mat->lda + i];
1567:   }
1568:   VecRestoreArray(v,&x);
1569:   return(0);
1570: }

1572: static PetscErrorCode MatDiagonalScale_SeqDense(Mat A,Vec ll,Vec rr)
1573: {
1574:   Mat_SeqDense      *mat = (Mat_SeqDense*)A->data;
1575:   const PetscScalar *l,*r;
1576:   PetscScalar       x,*v;
1577:   PetscErrorCode    ierr;
1578:   PetscInt          i,j,m = A->rmap->n,n = A->cmap->n;

1581:   if (ll) {
1582:     VecGetSize(ll,&m);
1583:     VecGetArrayRead(ll,&l);
1584:     if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vec wrong size");
1585:     for (i=0; i<m; i++) {
1586:       x = l[i];
1587:       v = mat->v + i;
1588:       for (j=0; j<n; j++) { (*v) *= x; v+= mat->lda;}
1589:     }
1590:     VecRestoreArrayRead(ll,&l);
1591:     PetscLogFlops(1.0*n*m);
1592:   }
1593:   if (rr) {
1594:     VecGetSize(rr,&n);
1595:     VecGetArrayRead(rr,&r);
1596:     if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec wrong size");
1597:     for (i=0; i<n; i++) {
1598:       x = r[i];
1599:       v = mat->v + i*mat->lda;
1600:       for (j=0; j<m; j++) (*v++) *= x;
1601:     }
1602:     VecRestoreArrayRead(rr,&r);
1603:     PetscLogFlops(1.0*n*m);
1604:   }
1605:   return(0);
1606: }

1608: static PetscErrorCode MatNorm_SeqDense(Mat A,NormType type,PetscReal *nrm)
1609: {
1610:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1611:   PetscScalar    *v   = mat->v;
1612:   PetscReal      sum  = 0.0;
1613:   PetscInt       lda  =mat->lda,m=A->rmap->n,i,j;

1617:   if (type == NORM_FROBENIUS) {
1618:     if (lda>m) {
1619:       for (j=0; j<A->cmap->n; j++) {
1620:         v = mat->v+j*lda;
1621:         for (i=0; i<m; i++) {
1622:           sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1623:         }
1624:       }
1625:     } else {
1626: #if defined(PETSC_USE_REAL___FP16)
1627:       PetscBLASInt one = 1,cnt = A->cmap->n*A->rmap->n;
1628:       *nrm = BLASnrm2_(&cnt,v,&one);
1629:     }
1630: #else
1631:       for (i=0; i<A->cmap->n*A->rmap->n; i++) {
1632:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1633:       }
1634:     }
1635:     *nrm = PetscSqrtReal(sum);
1636: #endif
1637:     PetscLogFlops(2.0*A->cmap->n*A->rmap->n);
1638:   } else if (type == NORM_1) {
1639:     *nrm = 0.0;
1640:     for (j=0; j<A->cmap->n; j++) {
1641:       v   = mat->v + j*mat->lda;
1642:       sum = 0.0;
1643:       for (i=0; i<A->rmap->n; i++) {
1644:         sum += PetscAbsScalar(*v);  v++;
1645:       }
1646:       if (sum > *nrm) *nrm = sum;
1647:     }
1648:     PetscLogFlops(1.0*A->cmap->n*A->rmap->n);
1649:   } else if (type == NORM_INFINITY) {
1650:     *nrm = 0.0;
1651:     for (j=0; j<A->rmap->n; j++) {
1652:       v   = mat->v + j;
1653:       sum = 0.0;
1654:       for (i=0; i<A->cmap->n; i++) {
1655:         sum += PetscAbsScalar(*v); v += mat->lda;
1656:       }
1657:       if (sum > *nrm) *nrm = sum;
1658:     }
1659:     PetscLogFlops(1.0*A->cmap->n*A->rmap->n);
1660:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No two norm");
1661:   return(0);
1662: }

1664: static PetscErrorCode MatSetOption_SeqDense(Mat A,MatOption op,PetscBool flg)
1665: {
1666:   Mat_SeqDense   *aij = (Mat_SeqDense*)A->data;

1670:   switch (op) {
1671:   case MAT_ROW_ORIENTED:
1672:     aij->roworiented = flg;
1673:     break;
1674:   case MAT_NEW_NONZERO_LOCATIONS:
1675:   case MAT_NEW_NONZERO_LOCATION_ERR:
1676:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1677:   case MAT_NEW_DIAGONALS:
1678:   case MAT_KEEP_NONZERO_PATTERN:
1679:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1680:   case MAT_USE_HASH_TABLE:
1681:   case MAT_IGNORE_ZERO_ENTRIES:
1682:   case MAT_IGNORE_LOWER_TRIANGULAR:
1683:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1684:     break;
1685:   case MAT_SPD:
1686:   case MAT_SYMMETRIC:
1687:   case MAT_STRUCTURALLY_SYMMETRIC:
1688:   case MAT_HERMITIAN:
1689:   case MAT_SYMMETRY_ETERNAL:
1690:     /* These options are handled directly by MatSetOption() */
1691:     break;
1692:   default:
1693:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]);
1694:   }
1695:   return(0);
1696: }

1698: static PetscErrorCode MatZeroEntries_SeqDense(Mat A)
1699: {
1700:   Mat_SeqDense   *l = (Mat_SeqDense*)A->data;
1702:   PetscInt       lda=l->lda,m=A->rmap->n,j;

1705:   if (lda>m) {
1706:     for (j=0; j<A->cmap->n; j++) {
1707:       PetscMemzero(l->v+j*lda,m*sizeof(PetscScalar));
1708:     }
1709:   } else {
1710:     PetscMemzero(l->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));
1711:   }
1712:   return(0);
1713: }

1715: static PetscErrorCode MatZeroRows_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1716: {
1717:   PetscErrorCode    ierr;
1718:   Mat_SeqDense      *l = (Mat_SeqDense*)A->data;
1719:   PetscInt          m  = l->lda, n = A->cmap->n, i,j;
1720:   PetscScalar       *slot,*bb;
1721:   const PetscScalar *xx;

1724: #if defined(PETSC_USE_DEBUG)
1725:   for (i=0; i<N; i++) {
1726:     if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed");
1727:     if (rows[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested to be zeroed greater than or equal number of rows %D",rows[i],A->rmap->n);
1728:   }
1729: #endif

1731:   /* fix right hand side if needed */
1732:   if (x && b) {
1733:     VecGetArrayRead(x,&xx);
1734:     VecGetArray(b,&bb);
1735:     for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]];
1736:     VecRestoreArrayRead(x,&xx);
1737:     VecRestoreArray(b,&bb);
1738:   }

1740:   for (i=0; i<N; i++) {
1741:     slot = l->v + rows[i];
1742:     for (j=0; j<n; j++) { *slot = 0.0; slot += m;}
1743:   }
1744:   if (diag != 0.0) {
1745:     if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices");
1746:     for (i=0; i<N; i++) {
1747:       slot  = l->v + (m+1)*rows[i];
1748:       *slot = diag;
1749:     }
1750:   }
1751:   return(0);
1752: }

1754: static PetscErrorCode MatDenseGetArray_SeqDense(Mat A,PetscScalar *array[])
1755: {
1756:   Mat_SeqDense *mat = (Mat_SeqDense*)A->data;

1759:   if (mat->lda != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot get array for Dense matrices with LDA different from number of rows");
1760:   *array = mat->v;
1761:   return(0);
1762: }

1764: static PetscErrorCode MatDenseRestoreArray_SeqDense(Mat A,PetscScalar *array[])
1765: {
1767:   return(0);
1768: }

1770: /*@C
1771:    MatDenseGetArray - gives access to the array where the data for a SeqDense matrix is stored

1773:    Logically Collective on Mat

1775:    Input Parameter:
1776: .  mat - a MATSEQDENSE or MATMPIDENSE matrix

1778:    Output Parameter:
1779: .   array - pointer to the data

1781:    Level: intermediate

1783: .seealso: MatDenseRestoreArray(), MatDenseGetArrayRead(), MatDenseRestoreArrayRead()
1784: @*/
1785: PetscErrorCode  MatDenseGetArray(Mat A,PetscScalar **array)
1786: {

1790:   PetscUseMethod(A,"MatDenseGetArray_C",(Mat,PetscScalar**),(A,array));
1791:   return(0);
1792: }

1794: /*@C
1795:    MatDenseRestoreArray - returns access to the array where the data for a dense matrix is stored obtained by MatDenseGetArray()

1797:    Logically Collective on Mat

1799:    Input Parameters:
1800: .  mat - a MATSEQDENSE or MATMPIDENSE matrix
1801: .  array - pointer to the data

1803:    Level: intermediate

1805: .seealso: MatDenseGetArray(), MatDenseGetArrayRead(), MatDenseRestoreArrayRead()
1806: @*/
1807: PetscErrorCode  MatDenseRestoreArray(Mat A,PetscScalar **array)
1808: {

1812:   PetscUseMethod(A,"MatDenseRestoreArray_C",(Mat,PetscScalar**),(A,array));
1813:   if (array) *array = NULL;
1814:   PetscObjectStateIncrease((PetscObject)A);
1815:   return(0);
1816: }

1818: /*@C
1819:    MatDenseGetArrayRead - gives access to the array where the data for a SeqDense matrix is stored

1821:    Not Collective

1823:    Input Parameter:
1824: .  mat - a MATSEQDENSE or MATMPIDENSE matrix

1826:    Output Parameter:
1827: .   array - pointer to the data

1829:    Level: intermediate

1831: .seealso: MatDenseRestoreArray(), MatDenseGetArray(), MatDenseRestoreArrayRead()
1832: @*/
1833: PetscErrorCode  MatDenseGetArrayRead(Mat A,const PetscScalar **array)
1834: {

1838:   PetscUseMethod(A,"MatDenseGetArrayRead_C",(Mat,const PetscScalar**),(A,array));
1839:   return(0);
1840: }

1842: /*@C
1843:    MatDenseRestoreArrayRead - returns access to the array where the data for a dense matrix is stored obtained by MatDenseGetArray()

1845:    Not Collective

1847:    Input Parameters:
1848: .  mat - a MATSEQDENSE or MATMPIDENSE matrix
1849: .  array - pointer to the data

1851:    Level: intermediate

1853: .seealso: MatDenseGetArray(), MatDenseGetArrayRead(), MatDenseRestoreArray()
1854: @*/
1855: PetscErrorCode  MatDenseRestoreArrayRead(Mat A,const PetscScalar **array)
1856: {

1860:   PetscUseMethod(A,"MatDenseRestoreArrayRead_C",(Mat,const PetscScalar**),(A,array));
1861:   if (array) *array = NULL;
1862:   return(0);
1863: }

1865: static PetscErrorCode MatCreateSubMatrix_SeqDense(Mat A,IS isrow,IS iscol,PetscInt cs,MatReuse scall,Mat *B)
1866: {
1867:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1869:   PetscInt       i,j,nrows,ncols;
1870:   const PetscInt *irow,*icol;
1871:   PetscScalar    *av,*bv,*v = mat->v;
1872:   Mat            newmat;

1875:   ISGetIndices(isrow,&irow);
1876:   ISGetIndices(iscol,&icol);
1877:   ISGetLocalSize(isrow,&nrows);
1878:   ISGetLocalSize(iscol,&ncols);

1880:   /* Check submatrixcall */
1881:   if (scall == MAT_REUSE_MATRIX) {
1882:     PetscInt n_cols,n_rows;
1883:     MatGetSize(*B,&n_rows,&n_cols);
1884:     if (n_rows != nrows || n_cols != ncols) {
1885:       /* resize the result matrix to match number of requested rows/columns */
1886:       MatSetSizes(*B,nrows,ncols,nrows,ncols);
1887:     }
1888:     newmat = *B;
1889:   } else {
1890:     /* Create and fill new matrix */
1891:     MatCreate(PetscObjectComm((PetscObject)A),&newmat);
1892:     MatSetSizes(newmat,nrows,ncols,nrows,ncols);
1893:     MatSetType(newmat,((PetscObject)A)->type_name);
1894:     MatSeqDenseSetPreallocation(newmat,NULL);
1895:   }

1897:   /* Now extract the data pointers and do the copy,column at a time */
1898:   bv = ((Mat_SeqDense*)newmat->data)->v;

1900:   for (i=0; i<ncols; i++) {
1901:     av = v + mat->lda*icol[i];
1902:     for (j=0; j<nrows; j++) *bv++ = av[irow[j]];
1903:   }

1905:   /* Assemble the matrices so that the correct flags are set */
1906:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
1907:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);

1909:   /* Free work space */
1910:   ISRestoreIndices(isrow,&irow);
1911:   ISRestoreIndices(iscol,&icol);
1912:   *B   = newmat;
1913:   return(0);
1914: }

1916: static PetscErrorCode MatCreateSubMatrices_SeqDense(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1917: {
1919:   PetscInt       i;

1922:   if (scall == MAT_INITIAL_MATRIX) {
1923:     PetscCalloc1(n+1,B);
1924:   }

1926:   for (i=0; i<n; i++) {
1927:     MatCreateSubMatrix_SeqDense(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);
1928:   }
1929:   return(0);
1930: }

1932: static PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat,MatAssemblyType mode)
1933: {
1935:   return(0);
1936: }

1938: static PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat,MatAssemblyType mode)
1939: {
1941:   return(0);
1942: }

1944: static PetscErrorCode MatCopy_SeqDense(Mat A,Mat B,MatStructure str)
1945: {
1946:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data,*b = (Mat_SeqDense*)B->data;
1948:   PetscInt       lda1=a->lda,lda2=b->lda, m=A->rmap->n,n=A->cmap->n, j;

1951:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1952:   if (A->ops->copy != B->ops->copy) {
1953:     MatCopy_Basic(A,B,str);
1954:     return(0);
1955:   }
1956:   if (m != B->rmap->n || n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"size(B) != size(A)");
1957:   if (lda1>m || lda2>m) {
1958:     for (j=0; j<n; j++) {
1959:       PetscMemcpy(b->v+j*lda2,a->v+j*lda1,m*sizeof(PetscScalar));
1960:     }
1961:   } else {
1962:     PetscMemcpy(b->v,a->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));
1963:   }
1964:   PetscObjectStateIncrease((PetscObject)B);
1965:   return(0);
1966: }

1968: static PetscErrorCode MatSetUp_SeqDense(Mat A)
1969: {

1973:    MatSeqDenseSetPreallocation(A,0);
1974:   return(0);
1975: }

1977: static PetscErrorCode MatConjugate_SeqDense(Mat A)
1978: {
1979:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
1980:   PetscInt     i,nz = A->rmap->n*A->cmap->n;
1981:   PetscScalar  *aa = a->v;

1984:   for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]);
1985:   return(0);
1986: }

1988: static PetscErrorCode MatRealPart_SeqDense(Mat A)
1989: {
1990:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
1991:   PetscInt     i,nz = A->rmap->n*A->cmap->n;
1992:   PetscScalar  *aa = a->v;

1995:   for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
1996:   return(0);
1997: }

1999: static PetscErrorCode MatImaginaryPart_SeqDense(Mat A)
2000: {
2001:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
2002:   PetscInt     i,nz = A->rmap->n*A->cmap->n;
2003:   PetscScalar  *aa = a->v;

2006:   for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
2007:   return(0);
2008: }

2010: /* ----------------------------------------------------------------*/
2011: PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
2012: {

2016:   if (scall == MAT_INITIAL_MATRIX) {
2017:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
2018:     MatMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);
2019:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
2020:   }
2021:   PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
2022:   MatMatMultNumeric_SeqDense_SeqDense(A,B,*C);
2023:   PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
2024:   return(0);
2025: }

2027: PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
2028: {
2030:   PetscInt       m=A->rmap->n,n=B->cmap->n;
2031:   Mat            Cmat;

2034:   if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n);
2035:   MatCreate(PETSC_COMM_SELF,&Cmat);
2036:   MatSetSizes(Cmat,m,n,m,n);
2037:   MatSetType(Cmat,MATSEQDENSE);
2038:   MatSeqDenseSetPreallocation(Cmat,NULL);

2040:   *C = Cmat;
2041:   return(0);
2042: }

2044: PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C)
2045: {
2046:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
2047:   Mat_SeqDense   *b = (Mat_SeqDense*)B->data;
2048:   Mat_SeqDense   *c = (Mat_SeqDense*)C->data;
2049:   PetscBLASInt   m,n,k;
2050:   PetscScalar    _DOne=1.0,_DZero=0.0;
2052:   PetscBool      flg;

2055:   PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);
2056:   if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Second matrix must be dense");

2058:   /* Handle case where where user provided the final C matrix rather than calling MatMatMult() with MAT_INITIAL_MATRIX*/
2059:   PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&flg);
2060:   if (flg) {
2061:     C->ops->matmultnumeric = MatMatMultNumeric_SeqAIJ_SeqDense;
2062:     (*C->ops->matmultnumeric)(A,B,C);
2063:     return(0);
2064:   }

2066:   PetscObjectTypeCompare((PetscObject)A,MATSEQDENSE,&flg);
2067:   if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"First matrix must be dense");
2068:   PetscBLASIntCast(C->rmap->n,&m);
2069:   PetscBLASIntCast(C->cmap->n,&n);
2070:   PetscBLASIntCast(A->cmap->n,&k);
2071:   if (!m || !n || !k) return(0);
2072:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda));
2073:   return(0);
2074: }

2076: PetscErrorCode MatMatTransposeMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
2077: {

2081:   if (scall == MAT_INITIAL_MATRIX) {
2082:     PetscLogEventBegin(MAT_MatTransposeMultSymbolic,A,B,0,0);
2083:     MatMatTransposeMultSymbolic_SeqDense_SeqDense(A,B,fill,C);
2084:     PetscLogEventEnd(MAT_MatTransposeMultSymbolic,A,B,0,0);
2085:   }
2086:   PetscLogEventBegin(MAT_MatTransposeMultNumeric,A,B,0,0);
2087:   MatMatTransposeMultNumeric_SeqDense_SeqDense(A,B,*C);
2088:   PetscLogEventEnd(MAT_MatTransposeMultNumeric,A,B,0,0);
2089:   return(0);
2090: }

2092: PetscErrorCode MatMatTransposeMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
2093: {
2095:   PetscInt       m=A->rmap->n,n=B->rmap->n;
2096:   Mat            Cmat;

2099:   if (A->cmap->n != B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->cmap->n %d\n",A->cmap->n,B->cmap->n);
2100:   MatCreate(PETSC_COMM_SELF,&Cmat);
2101:   MatSetSizes(Cmat,m,n,m,n);
2102:   MatSetType(Cmat,MATSEQDENSE);
2103:   MatSeqDenseSetPreallocation(Cmat,NULL);

2105:   Cmat->assembled = PETSC_TRUE;

2107:   *C = Cmat;
2108:   return(0);
2109: }

2111: PetscErrorCode MatMatTransposeMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C)
2112: {
2113:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
2114:   Mat_SeqDense   *b = (Mat_SeqDense*)B->data;
2115:   Mat_SeqDense   *c = (Mat_SeqDense*)C->data;
2116:   PetscBLASInt   m,n,k;
2117:   PetscScalar    _DOne=1.0,_DZero=0.0;

2121:   PetscBLASIntCast(C->rmap->n,&m);
2122:   PetscBLASIntCast(C->cmap->n,&n);
2123:   PetscBLASIntCast(A->cmap->n,&k);
2124:   if (!m || !n || !k) return(0);
2125:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda));
2126:   return(0);
2127: }

2129: PetscErrorCode MatTransposeMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
2130: {

2134:   if (scall == MAT_INITIAL_MATRIX) {
2135:     PetscLogEventBegin(MAT_TransposeMatMultSymbolic,A,B,0,0);
2136:     MatTransposeMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);
2137:     PetscLogEventEnd(MAT_TransposeMatMultSymbolic,A,B,0,0);
2138:   }
2139:   PetscLogEventBegin(MAT_TransposeMatMultNumeric,A,B,0,0);
2140:   MatTransposeMatMultNumeric_SeqDense_SeqDense(A,B,*C);
2141:   PetscLogEventEnd(MAT_TransposeMatMultNumeric,A,B,0,0);
2142:   return(0);
2143: }

2145: PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
2146: {
2148:   PetscInt       m=A->cmap->n,n=B->cmap->n;
2149:   Mat            Cmat;

2152:   if (A->rmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->rmap->n %d != B->rmap->n %d\n",A->rmap->n,B->rmap->n);
2153:   MatCreate(PETSC_COMM_SELF,&Cmat);
2154:   MatSetSizes(Cmat,m,n,m,n);
2155:   MatSetType(Cmat,MATSEQDENSE);
2156:   MatSeqDenseSetPreallocation(Cmat,NULL);

2158:   Cmat->assembled = PETSC_TRUE;

2160:   *C = Cmat;
2161:   return(0);
2162: }

2164: PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C)
2165: {
2166:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
2167:   Mat_SeqDense   *b = (Mat_SeqDense*)B->data;
2168:   Mat_SeqDense   *c = (Mat_SeqDense*)C->data;
2169:   PetscBLASInt   m,n,k;
2170:   PetscScalar    _DOne=1.0,_DZero=0.0;

2174:   PetscBLASIntCast(C->rmap->n,&m);
2175:   PetscBLASIntCast(C->cmap->n,&n);
2176:   PetscBLASIntCast(A->rmap->n,&k);
2177:   if (!m || !n || !k) return(0);
2178:   PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda));
2179:   return(0);
2180: }

2182: static PetscErrorCode MatGetRowMax_SeqDense(Mat A,Vec v,PetscInt idx[])
2183: {
2184:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
2186:   PetscInt       i,j,m = A->rmap->n,n = A->cmap->n,p;
2187:   PetscScalar    *x;
2188:   MatScalar      *aa = a->v;

2191:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

2193:   VecSet(v,0.0);
2194:   VecGetArray(v,&x);
2195:   VecGetLocalSize(v,&p);
2196:   if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
2197:   for (i=0; i<m; i++) {
2198:     x[i] = aa[i]; if (idx) idx[i] = 0;
2199:     for (j=1; j<n; j++) {
2200:       if (PetscRealPart(x[i]) < PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;}
2201:     }
2202:   }
2203:   VecRestoreArray(v,&x);
2204:   return(0);
2205: }

2207: static PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A,Vec v,PetscInt idx[])
2208: {
2209:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
2211:   PetscInt       i,j,m = A->rmap->n,n = A->cmap->n,p;
2212:   PetscScalar    *x;
2213:   PetscReal      atmp;
2214:   MatScalar      *aa = a->v;

2217:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

2219:   VecSet(v,0.0);
2220:   VecGetArray(v,&x);
2221:   VecGetLocalSize(v,&p);
2222:   if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
2223:   for (i=0; i<m; i++) {
2224:     x[i] = PetscAbsScalar(aa[i]);
2225:     for (j=1; j<n; j++) {
2226:       atmp = PetscAbsScalar(aa[i+m*j]);
2227:       if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = j;}
2228:     }
2229:   }
2230:   VecRestoreArray(v,&x);
2231:   return(0);
2232: }

2234: static PetscErrorCode MatGetRowMin_SeqDense(Mat A,Vec v,PetscInt idx[])
2235: {
2236:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
2238:   PetscInt       i,j,m = A->rmap->n,n = A->cmap->n,p;
2239:   PetscScalar    *x;
2240:   MatScalar      *aa = a->v;

2243:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

2245:   VecSet(v,0.0);
2246:   VecGetArray(v,&x);
2247:   VecGetLocalSize(v,&p);
2248:   if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
2249:   for (i=0; i<m; i++) {
2250:     x[i] = aa[i]; if (idx) idx[i] = 0;
2251:     for (j=1; j<n; j++) {
2252:       if (PetscRealPart(x[i]) > PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;}
2253:     }
2254:   }
2255:   VecRestoreArray(v,&x);
2256:   return(0);
2257: }

2259: static PetscErrorCode MatGetColumnVector_SeqDense(Mat A,Vec v,PetscInt col)
2260: {
2261:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
2263:   PetscScalar    *x;

2266:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

2268:   VecGetArray(v,&x);
2269:   PetscMemcpy(x,a->v+col*a->lda,A->rmap->n*sizeof(PetscScalar));
2270:   VecRestoreArray(v,&x);
2271:   return(0);
2272: }

2274: PetscErrorCode MatGetColumnNorms_SeqDense(Mat A,NormType type,PetscReal *norms)
2275: {
2277:   PetscInt       i,j,m,n;
2278:   PetscScalar    *a;

2281:   MatGetSize(A,&m,&n);
2282:   PetscMemzero(norms,n*sizeof(PetscReal));
2283:   MatDenseGetArray(A,&a);
2284:   if (type == NORM_2) {
2285:     for (i=0; i<n; i++) {
2286:       for (j=0; j<m; j++) {
2287:         norms[i] += PetscAbsScalar(a[j]*a[j]);
2288:       }
2289:       a += m;
2290:     }
2291:   } else if (type == NORM_1) {
2292:     for (i=0; i<n; i++) {
2293:       for (j=0; j<m; j++) {
2294:         norms[i] += PetscAbsScalar(a[j]);
2295:       }
2296:       a += m;
2297:     }
2298:   } else if (type == NORM_INFINITY) {
2299:     for (i=0; i<n; i++) {
2300:       for (j=0; j<m; j++) {
2301:         norms[i] = PetscMax(PetscAbsScalar(a[j]),norms[i]);
2302:       }
2303:       a += m;
2304:     }
2305:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
2306:   MatDenseRestoreArray(A,&a);
2307:   if (type == NORM_2) {
2308:     for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
2309:   }
2310:   return(0);
2311: }

2313: static PetscErrorCode  MatSetRandom_SeqDense(Mat x,PetscRandom rctx)
2314: {
2316:   PetscScalar    *a;
2317:   PetscInt       m,n,i;

2320:   MatGetSize(x,&m,&n);
2321:   MatDenseGetArray(x,&a);
2322:   for (i=0; i<m*n; i++) {
2323:     PetscRandomGetValue(rctx,a+i);
2324:   }
2325:   MatDenseRestoreArray(x,&a);
2326:   return(0);
2327: }

2329: static PetscErrorCode MatMissingDiagonal_SeqDense(Mat A,PetscBool  *missing,PetscInt *d)
2330: {
2332:   *missing = PETSC_FALSE;
2333:   return(0);
2334: }

2336: static PetscErrorCode MatDenseGetColumn_SeqDense(Mat A,PetscInt col,PetscScalar **vals)
2337: {
2338:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;

2341:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
2342:   *vals = a->v+col*a->lda;
2343:   return(0);
2344: }

2346: static PetscErrorCode MatDenseRestoreColumn_SeqDense(Mat A,PetscScalar **vals)
2347: {
2349:   *vals = 0; /* user cannot accidently use the array later */
2350:   return(0);
2351: }

2353: /* -------------------------------------------------------------------*/
2354: static struct _MatOps MatOps_Values = { MatSetValues_SeqDense,
2355:                                         MatGetRow_SeqDense,
2356:                                         MatRestoreRow_SeqDense,
2357:                                         MatMult_SeqDense,
2358:                                 /*  4*/ MatMultAdd_SeqDense,
2359:                                         MatMultTranspose_SeqDense,
2360:                                         MatMultTransposeAdd_SeqDense,
2361:                                         0,
2362:                                         0,
2363:                                         0,
2364:                                 /* 10*/ 0,
2365:                                         MatLUFactor_SeqDense,
2366:                                         MatCholeskyFactor_SeqDense,
2367:                                         MatSOR_SeqDense,
2368:                                         MatTranspose_SeqDense,
2369:                                 /* 15*/ MatGetInfo_SeqDense,
2370:                                         MatEqual_SeqDense,
2371:                                         MatGetDiagonal_SeqDense,
2372:                                         MatDiagonalScale_SeqDense,
2373:                                         MatNorm_SeqDense,
2374:                                 /* 20*/ MatAssemblyBegin_SeqDense,
2375:                                         MatAssemblyEnd_SeqDense,
2376:                                         MatSetOption_SeqDense,
2377:                                         MatZeroEntries_SeqDense,
2378:                                 /* 24*/ MatZeroRows_SeqDense,
2379:                                         0,
2380:                                         0,
2381:                                         0,
2382:                                         0,
2383:                                 /* 29*/ MatSetUp_SeqDense,
2384:                                         0,
2385:                                         0,
2386:                                         0,
2387:                                         0,
2388:                                 /* 34*/ MatDuplicate_SeqDense,
2389:                                         0,
2390:                                         0,
2391:                                         0,
2392:                                         0,
2393:                                 /* 39*/ MatAXPY_SeqDense,
2394:                                         MatCreateSubMatrices_SeqDense,
2395:                                         0,
2396:                                         MatGetValues_SeqDense,
2397:                                         MatCopy_SeqDense,
2398:                                 /* 44*/ MatGetRowMax_SeqDense,
2399:                                         MatScale_SeqDense,
2400:                                         MatShift_Basic,
2401:                                         0,
2402:                                         MatZeroRowsColumns_SeqDense,
2403:                                 /* 49*/ MatSetRandom_SeqDense,
2404:                                         0,
2405:                                         0,
2406:                                         0,
2407:                                         0,
2408:                                 /* 54*/ 0,
2409:                                         0,
2410:                                         0,
2411:                                         0,
2412:                                         0,
2413:                                 /* 59*/ 0,
2414:                                         MatDestroy_SeqDense,
2415:                                         MatView_SeqDense,
2416:                                         0,
2417:                                         0,
2418:                                 /* 64*/ 0,
2419:                                         0,
2420:                                         0,
2421:                                         0,
2422:                                         0,
2423:                                 /* 69*/ MatGetRowMaxAbs_SeqDense,
2424:                                         0,
2425:                                         0,
2426:                                         0,
2427:                                         0,
2428:                                 /* 74*/ 0,
2429:                                         0,
2430:                                         0,
2431:                                         0,
2432:                                         0,
2433:                                 /* 79*/ 0,
2434:                                         0,
2435:                                         0,
2436:                                         0,
2437:                                 /* 83*/ MatLoad_SeqDense,
2438:                                         0,
2439:                                         MatIsHermitian_SeqDense,
2440:                                         0,
2441:                                         0,
2442:                                         0,
2443:                                 /* 89*/ MatMatMult_SeqDense_SeqDense,
2444:                                         MatMatMultSymbolic_SeqDense_SeqDense,
2445:                                         MatMatMultNumeric_SeqDense_SeqDense,
2446:                                         MatPtAP_SeqDense_SeqDense,
2447:                                         MatPtAPSymbolic_SeqDense_SeqDense,
2448:                                 /* 94*/ MatPtAPNumeric_SeqDense_SeqDense,
2449:                                         MatMatTransposeMult_SeqDense_SeqDense,
2450:                                         MatMatTransposeMultSymbolic_SeqDense_SeqDense,
2451:                                         MatMatTransposeMultNumeric_SeqDense_SeqDense,
2452:                                         0,
2453:                                 /* 99*/ 0,
2454:                                         0,
2455:                                         0,
2456:                                         MatConjugate_SeqDense,
2457:                                         0,
2458:                                 /*104*/ 0,
2459:                                         MatRealPart_SeqDense,
2460:                                         MatImaginaryPart_SeqDense,
2461:                                         0,
2462:                                         0,
2463:                                 /*109*/ 0,
2464:                                         0,
2465:                                         MatGetRowMin_SeqDense,
2466:                                         MatGetColumnVector_SeqDense,
2467:                                         MatMissingDiagonal_SeqDense,
2468:                                 /*114*/ 0,
2469:                                         0,
2470:                                         0,
2471:                                         0,
2472:                                         0,
2473:                                 /*119*/ 0,
2474:                                         0,
2475:                                         0,
2476:                                         0,
2477:                                         0,
2478:                                 /*124*/ 0,
2479:                                         MatGetColumnNorms_SeqDense,
2480:                                         0,
2481:                                         0,
2482:                                         0,
2483:                                 /*129*/ 0,
2484:                                         MatTransposeMatMult_SeqDense_SeqDense,
2485:                                         MatTransposeMatMultSymbolic_SeqDense_SeqDense,
2486:                                         MatTransposeMatMultNumeric_SeqDense_SeqDense,
2487:                                         0,
2488:                                 /*134*/ 0,
2489:                                         0,
2490:                                         0,
2491:                                         0,
2492:                                         0,
2493:                                 /*139*/ 0,
2494:                                         0,
2495:                                         0,
2496:                                         0,
2497:                                         0,
2498:                                 /*144*/ MatCreateMPIMatConcatenateSeqMat_SeqDense
2499: };

2501: /*@C
2502:    MatCreateSeqDense - Creates a sequential dense matrix that
2503:    is stored in column major order (the usual Fortran 77 manner). Many
2504:    of the matrix operations use the BLAS and LAPACK routines.

2506:    Collective on MPI_Comm

2508:    Input Parameters:
2509: +  comm - MPI communicator, set to PETSC_COMM_SELF
2510: .  m - number of rows
2511: .  n - number of columns
2512: -  data - optional location of matrix data in column major order.  Set data=NULL for PETSc
2513:    to control all matrix memory allocation.

2515:    Output Parameter:
2516: .  A - the matrix

2518:    Notes:
2519:    The data input variable is intended primarily for Fortran programmers
2520:    who wish to allocate their own matrix memory space.  Most users should
2521:    set data=NULL.

2523:    Level: intermediate

2525: .keywords: dense, matrix, LAPACK, BLAS

2527: .seealso: MatCreate(), MatCreateDense(), MatSetValues()
2528: @*/
2529: PetscErrorCode  MatCreateSeqDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscScalar *data,Mat *A)
2530: {

2534:   MatCreate(comm,A);
2535:   MatSetSizes(*A,m,n,m,n);
2536:   MatSetType(*A,MATSEQDENSE);
2537:   MatSeqDenseSetPreallocation(*A,data);
2538:   return(0);
2539: }

2541: /*@C
2542:    MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements

2544:    Collective on MPI_Comm

2546:    Input Parameters:
2547: +  B - the matrix
2548: -  data - the array (or NULL)

2550:    Notes:
2551:    The data input variable is intended primarily for Fortran programmers
2552:    who wish to allocate their own matrix memory space.  Most users should
2553:    need not call this routine.

2555:    Level: intermediate

2557: .keywords: dense, matrix, LAPACK, BLAS

2559: .seealso: MatCreate(), MatCreateDense(), MatSetValues(), MatSeqDenseSetLDA()

2561: @*/
2562: PetscErrorCode  MatSeqDenseSetPreallocation(Mat B,PetscScalar data[])
2563: {

2567:   PetscTryMethod(B,"MatSeqDenseSetPreallocation_C",(Mat,PetscScalar[]),(B,data));
2568:   return(0);
2569: }

2571: PetscErrorCode  MatSeqDenseSetPreallocation_SeqDense(Mat B,PetscScalar *data)
2572: {
2573:   Mat_SeqDense   *b;

2577:   B->preallocated = PETSC_TRUE;

2579:   PetscLayoutSetUp(B->rmap);
2580:   PetscLayoutSetUp(B->cmap);

2582:   b       = (Mat_SeqDense*)B->data;
2583:   b->Mmax = B->rmap->n;
2584:   b->Nmax = B->cmap->n;
2585:   if (b->lda <= 0 || b->changelda) b->lda = B->rmap->n;

2587:   PetscIntMultError(b->lda,b->Nmax,NULL);
2588:   if (!data) { /* petsc-allocated storage */
2589:     if (!b->user_alloc) { PetscFree(b->v); }
2590:     PetscCalloc1((size_t)b->lda*b->Nmax,&b->v);
2591:     PetscLogObjectMemory((PetscObject)B,b->lda*b->Nmax*sizeof(PetscScalar));

2593:     b->user_alloc = PETSC_FALSE;
2594:   } else { /* user-allocated storage */
2595:     if (!b->user_alloc) { PetscFree(b->v); }
2596:     b->v          = data;
2597:     b->user_alloc = PETSC_TRUE;
2598:   }
2599:   B->assembled = PETSC_TRUE;
2600:   return(0);
2601: }

2603: #if defined(PETSC_HAVE_ELEMENTAL)
2604: PETSC_INTERN PetscErrorCode MatConvert_SeqDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat)
2605: {
2606:   Mat            mat_elemental;
2608:   PetscScalar    *array,*v_colwise;
2609:   PetscInt       M=A->rmap->N,N=A->cmap->N,i,j,k,*rows,*cols;

2612:   PetscMalloc3(M*N,&v_colwise,M,&rows,N,&cols);
2613:   MatDenseGetArray(A,&array);
2614:   /* convert column-wise array into row-wise v_colwise, see MatSetValues_Elemental() */
2615:   k = 0;
2616:   for (j=0; j<N; j++) {
2617:     cols[j] = j;
2618:     for (i=0; i<M; i++) {
2619:       v_colwise[j*M+i] = array[k++];
2620:     }
2621:   }
2622:   for (i=0; i<M; i++) {
2623:     rows[i] = i;
2624:   }
2625:   MatDenseRestoreArray(A,&array);

2627:   MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);
2628:   MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,M,N);
2629:   MatSetType(mat_elemental,MATELEMENTAL);
2630:   MatSetUp(mat_elemental);

2632:   /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */
2633:   MatSetValues(mat_elemental,M,rows,N,cols,v_colwise,ADD_VALUES);
2634:   MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);
2635:   MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);
2636:   PetscFree3(v_colwise,rows,cols);

2638:   if (reuse == MAT_INPLACE_MATRIX) {
2639:     MatHeaderReplace(A,&mat_elemental);
2640:   } else {
2641:     *newmat = mat_elemental;
2642:   }
2643:   return(0);
2644: }
2645: #endif

2647: /*@C
2648:   MatSeqDenseSetLDA - Declare the leading dimension of the user-provided array

2650:   Input parameter:
2651: + A - the matrix
2652: - lda - the leading dimension

2654:   Notes:
2655:   This routine is to be used in conjunction with MatSeqDenseSetPreallocation();
2656:   it asserts that the preallocation has a leading dimension (the LDA parameter
2657:   of Blas and Lapack fame) larger than M, the first dimension of the matrix.

2659:   Level: intermediate

2661: .keywords: dense, matrix, LAPACK, BLAS

2663: .seealso: MatCreate(), MatCreateSeqDense(), MatSeqDenseSetPreallocation(), MatSetMaximumSize()

2665: @*/
2666: PetscErrorCode  MatSeqDenseSetLDA(Mat B,PetscInt lda)
2667: {
2668:   Mat_SeqDense *b = (Mat_SeqDense*)B->data;

2671:   if (lda < B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"LDA %D must be at least matrix dimension %D",lda,B->rmap->n);
2672:   b->lda       = lda;
2673:   b->changelda = PETSC_FALSE;
2674:   b->Mmax      = PetscMax(b->Mmax,lda);
2675:   return(0);
2676: }

2678: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqDense(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
2679: {
2681:   PetscMPIInt    size;

2684:   MPI_Comm_size(comm,&size);
2685:   if (size == 1) {
2686:     if (scall == MAT_INITIAL_MATRIX) {
2687:       MatDuplicate(inmat,MAT_COPY_VALUES,outmat);
2688:     } else {
2689:       MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);
2690:     }
2691:   } else {
2692:     MatCreateMPIMatConcatenateSeqMat_MPIDense(comm,inmat,n,scall,outmat);
2693:   }
2694:   return(0);
2695: }

2697: /*MC
2698:    MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices.

2700:    Options Database Keys:
2701: . -mat_type seqdense - sets the matrix type to "seqdense" during a call to MatSetFromOptions()

2703:   Level: beginner

2705: .seealso: MatCreateSeqDense()

2707: M*/

2709: PETSC_EXTERN PetscErrorCode MatCreate_SeqDense(Mat B)
2710: {
2711:   Mat_SeqDense   *b;
2713:   PetscMPIInt    size;

2716:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2717:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1");

2719:   PetscNewLog(B,&b);
2720:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
2721:   B->data = (void*)b;

2723:   b->roworiented = PETSC_TRUE;

2725:   PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArray_C",MatDenseGetArray_SeqDense);
2726:   PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArray_C",MatDenseRestoreArray_SeqDense);
2727:   PetscObjectComposeFunction((PetscObject)B,"MatDensePlaceArray_C",MatDensePlaceArray_SeqDense);
2728:   PetscObjectComposeFunction((PetscObject)B,"MatDenseResetArray_C",MatDenseResetArray_SeqDense);
2729:   PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArrayRead_C",MatDenseGetArray_SeqDense);
2730:   PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArrayRead_C",MatDenseRestoreArray_SeqDense);
2731:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_seqaij_C",MatConvert_SeqDense_SeqAIJ);
2732: #if defined(PETSC_HAVE_ELEMENTAL)
2733:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_elemental_C",MatConvert_SeqDense_Elemental);
2734: #endif
2735:   PetscObjectComposeFunction((PetscObject)B,"MatSeqDenseSetPreallocation_C",MatSeqDenseSetPreallocation_SeqDense);
2736:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaij_seqdense_C",MatMatMult_SeqAIJ_SeqDense);
2737:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaij_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);
2738:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaij_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);
2739:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaij_seqdense_C",MatPtAP_SeqDense_SeqDense);
2740:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijperm_seqdense_C",MatMatMult_SeqAIJ_SeqDense);
2741:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijperm_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);
2742:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijperm_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);
2743:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijperm_seqdense_C",MatPtAP_SeqDense_SeqDense);
2744:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijsell_seqdense_C",MatMatMult_SeqAIJ_SeqDense);
2745:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijsell_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);
2746:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijsell_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);
2747:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijsell_seqdense_C",MatPtAP_SeqDense_SeqDense);
2748:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijmkl_seqdense_C",MatMatMult_SeqAIJ_SeqDense);
2749:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijmkl_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);
2750:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijmkl_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);
2751:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijmkl_seqdense_C",MatPtAP_SeqDense_SeqDense);

2753:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaij_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);
2754:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);
2755:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaij_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);
2756:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijperm_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);
2757:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijperm_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);
2758:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijperm_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);
2759:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijsell_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);
2760:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijsell_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);
2761:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijsell_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);

2763:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijmkl_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);
2764:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijmkl_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);
2765:   PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijmkl_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);
2766:   PetscObjectComposeFunction((PetscObject)B,"MatDenseGetColumn_C",MatDenseGetColumn_SeqDense);
2767:   PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreColumn_C",MatDenseRestoreColumn_SeqDense);
2768:   PetscObjectChangeTypeName((PetscObject)B,MATSEQDENSE);
2769:   return(0);
2770: }

2772: /*@C
2773:    MatDenseGetColumn - gives access to a column of a dense matrix. This is only the local part of the column. You MUST call MatDenseRestoreColumn() to avoid memory bleeding.

2775:    Not Collective

2777:    Input Parameter:
2778: +  mat - a MATSEQDENSE or MATMPIDENSE matrix
2779: -  col - column index

2781:    Output Parameter:
2782: .  vals - pointer to the data

2784:    Level: intermediate

2786: .seealso: MatDenseRestoreColumn()
2787: @*/
2788: PetscErrorCode MatDenseGetColumn(Mat A,PetscInt col,PetscScalar **vals)
2789: {

2793:   PetscUseMethod(A,"MatDenseGetColumn_C",(Mat,PetscInt,PetscScalar**),(A,col,vals));
2794:   return(0);
2795: }

2797: /*@C
2798:    MatDenseRestoreColumn - returns access to a column of a dense matrix which is returned by MatDenseGetColumn().

2800:    Not Collective

2802:    Input Parameter:
2803: .  mat - a MATSEQDENSE or MATMPIDENSE matrix

2805:    Output Parameter:
2806: .  vals - pointer to the data

2808:    Level: intermediate

2810: .seealso: MatDenseGetColumn()
2811: @*/
2812: PetscErrorCode MatDenseRestoreColumn(Mat A,PetscScalar **vals)
2813: {

2817:   PetscUseMethod(A,"MatDenseRestoreColumn_C",(Mat,PetscScalar**),(A,vals));
2818:   return(0);
2819: }