Actual source code: dense.c

petsc-3.4.4 2014-03-13
  2: /*
  3:      Defines the basic matrix operations for sequential dense.
  4: */

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

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

 13: PETSC_EXTERN PetscErrorCode MatConvert_SeqDense_SeqAIJ(Mat A, MatType newtype,MatReuse reuse,Mat *newmat)
 14: {
 15:   Mat            B;
 16:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
 18:   PetscInt       i;
 19:   PetscInt       *rows;
 20:   MatScalar      *aa = a->v;

 23:   MatCreate(PetscObjectComm((PetscObject)A),&B);
 24:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
 25:   MatSetType(B,MATSEQAIJ);
 26:   MatSeqAIJSetPreallocation(B,A->cmap->n,NULL);

 28:   PetscMalloc(A->rmap->n*sizeof(PetscInt),&rows);
 29:   for (i=0; i<A->rmap->n; i++) rows[i] = i;

 31:   for (i=0; i<A->cmap->n; i++) {
 32:     MatSetValues(B,A->rmap->n,rows,1,&i,aa,INSERT_VALUES);
 33:     aa  += a->lda;
 34:   }
 35:   PetscFree(rows);
 36:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
 37:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

 39:   if (reuse == MAT_REUSE_MATRIX) {
 40:     MatHeaderReplace(A,B);
 41:   } else {
 42:     *newmat = B;
 43:   }
 44:   return(0);
 45: }

 49: PetscErrorCode MatAXPY_SeqDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str)
 50: {
 51:   Mat_SeqDense   *x     = (Mat_SeqDense*)X->data,*y = (Mat_SeqDense*)Y->data;
 52:   PetscScalar    oalpha = alpha;
 53:   PetscInt       j;
 54:   PetscBLASInt   N,m,ldax,lday,one = 1;

 58:   PetscBLASIntCast(X->rmap->n*X->cmap->n,&N);
 59:   PetscBLASIntCast(X->rmap->n,&m);
 60:   PetscBLASIntCast(x->lda,&ldax);
 61:   PetscBLASIntCast(y->lda,&lday);
 62:   if (ldax>m || lday>m) {
 63:     for (j=0; j<X->cmap->n; j++) {
 64:       PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&m,&oalpha,x->v+j*ldax,&one,y->v+j*lday,&one));
 65:     }
 66:   } else {
 67:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&N,&oalpha,x->v,&one,y->v,&one));
 68:   }
 69:   PetscLogFlops(PetscMax(2*N-1,0));
 70:   return(0);
 71: }

 75: PetscErrorCode MatGetInfo_SeqDense(Mat A,MatInfoType flag,MatInfo *info)
 76: {
 77:   PetscInt N = A->rmap->n*A->cmap->n;

 80:   info->block_size        = 1.0;
 81:   info->nz_allocated      = (double)N;
 82:   info->nz_used           = (double)N;
 83:   info->nz_unneeded       = (double)0;
 84:   info->assemblies        = (double)A->num_ass;
 85:   info->mallocs           = 0;
 86:   info->memory            = ((PetscObject)A)->mem;
 87:   info->fill_ratio_given  = 0;
 88:   info->fill_ratio_needed = 0;
 89:   info->factor_mallocs    = 0;
 90:   return(0);
 91: }

 95: PetscErrorCode MatScale_SeqDense(Mat A,PetscScalar alpha)
 96: {
 97:   Mat_SeqDense   *a     = (Mat_SeqDense*)A->data;
 98:   PetscScalar    oalpha = alpha;
100:   PetscBLASInt   one = 1,j,nz,lda;

103:   PetscBLASIntCast(a->lda,&lda);
104:   if (lda>A->rmap->n) {
105:     PetscBLASIntCast(A->rmap->n,&nz);
106:     for (j=0; j<A->cmap->n; j++) {
107:       PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v+j*lda,&one));
108:     }
109:   } else {
110:     PetscBLASIntCast(A->rmap->n*A->cmap->n,&nz);
111:     PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v,&one));
112:   }
113:   PetscLogFlops(nz);
114:   return(0);
115: }

119: PetscErrorCode MatIsHermitian_SeqDense(Mat A,PetscReal rtol,PetscBool  *fl)
120: {
121:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
122:   PetscInt     i,j,m = A->rmap->n,N;
123:   PetscScalar  *v = a->v;

126:   *fl = PETSC_FALSE;
127:   if (A->rmap->n != A->cmap->n) return(0);
128:   N = a->lda;

130:   for (i=0; i<m; i++) {
131:     for (j=i+1; j<m; j++) {
132:       if (PetscAbsScalar(v[i+j*N] - PetscConj(v[j+i*N])) > rtol) return(0);
133:     }
134:   }
135:   *fl = PETSC_TRUE;
136:   return(0);
137: }

141: PetscErrorCode MatDuplicateNoCreate_SeqDense(Mat newi,Mat A,MatDuplicateOption cpvalues)
142: {
143:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data,*l;
145:   PetscInt       lda = (PetscInt)mat->lda,j,m;

148:   PetscLayoutReference(A->rmap,&newi->rmap);
149:   PetscLayoutReference(A->cmap,&newi->cmap);
150:   MatSeqDenseSetPreallocation(newi,NULL);
151:   if (cpvalues == MAT_COPY_VALUES) {
152:     l = (Mat_SeqDense*)newi->data;
153:     if (lda>A->rmap->n) {
154:       m = A->rmap->n;
155:       for (j=0; j<A->cmap->n; j++) {
156:         PetscMemcpy(l->v+j*m,mat->v+j*lda,m*sizeof(PetscScalar));
157:       }
158:     } else {
159:       PetscMemcpy(l->v,mat->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));
160:     }
161:   }
162:   newi->assembled = PETSC_TRUE;
163:   return(0);
164: }

168: PetscErrorCode MatDuplicate_SeqDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat)
169: {

173:   MatCreate(PetscObjectComm((PetscObject)A),newmat);
174:   MatSetSizes(*newmat,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);
175:   MatSetType(*newmat,((PetscObject)A)->type_name);
176:   MatDuplicateNoCreate_SeqDense(*newmat,A,cpvalues);
177:   return(0);
178: }


181: extern PetscErrorCode MatLUFactor_SeqDense(Mat,IS,IS,const MatFactorInfo*);

185: PetscErrorCode MatLUFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy)
186: {
187:   MatFactorInfo  info;

191:   MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);
192:   MatLUFactor_SeqDense(fact,0,0,&info);
193:   return(0);
194: }

198: PetscErrorCode MatSolve_SeqDense(Mat A,Vec xx,Vec yy)
199: {
200:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
202:   PetscScalar    *x,*y;
203:   PetscBLASInt   one = 1,info,m;

206:   PetscBLASIntCast(A->rmap->n,&m);
207:   VecGetArray(xx,&x);
208:   VecGetArray(yy,&y);
209:   PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));
210:   if (A->factortype == MAT_FACTOR_LU) {
211: #if defined(PETSC_MISSING_LAPACK_GETRS)
212:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
213: #else
214:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
215:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve");
216: #endif
217:   } else if (A->factortype == MAT_FACTOR_CHOLESKY) {
218: #if defined(PETSC_MISSING_LAPACK_POTRS)
219:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
220: #else
221:     PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info));
222:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve");
223: #endif
224:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve");
225:   VecRestoreArray(xx,&x);
226:   VecRestoreArray(yy,&y);
227:   PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);
228:   return(0);
229: }

233: PetscErrorCode MatMatSolve_SeqDense(Mat A,Mat B,Mat X)
234: {
235:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
237:   PetscScalar    *b,*x;
238:   PetscInt       n;
239:   PetscBLASInt   nrhs,info,m;
240:   PetscBool      flg;

243:   PetscBLASIntCast(A->rmap->n,&m);
244:   PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
245:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix");
246:   PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
247:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix");

249:   MatGetSize(B,NULL,&n);
250:   PetscBLASIntCast(n,&nrhs);
251:   MatDenseGetArray(B,&b);
252:   MatDenseGetArray(X,&x);

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

256:   if (A->factortype == MAT_FACTOR_LU) {
257: #if defined(PETSC_MISSING_LAPACK_GETRS)
258:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
259: #else
260:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info));
261:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve");
262: #endif
263:   } else if (A->factortype == MAT_FACTOR_CHOLESKY) {
264: #if defined(PETSC_MISSING_LAPACK_POTRS)
265:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
266: #else
267:     PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&nrhs,mat->v,&mat->lda,x,&m,&info));
268:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve");
269: #endif
270:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve");

272:   MatDenseRestoreArray(B,&b);
273:   MatDenseRestoreArray(X,&x);
274:   PetscLogFlops(nrhs*(2.0*m*m - m));
275:   return(0);
276: }

280: PetscErrorCode MatSolveTranspose_SeqDense(Mat A,Vec xx,Vec yy)
281: {
282:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
284:   PetscScalar    *x,*y;
285:   PetscBLASInt   one = 1,info,m;

288:   PetscBLASIntCast(A->rmap->n,&m);
289:   VecGetArray(xx,&x);
290:   VecGetArray(yy,&y);
291:   PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));
292:   /* assume if pivots exist then use LU; else Cholesky */
293:   if (mat->pivots) {
294: #if defined(PETSC_MISSING_LAPACK_GETRS)
295:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
296: #else
297:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("T",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
298:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS - Bad solve");
299: #endif
300:   } else {
301: #if defined(PETSC_MISSING_LAPACK_POTRS)
302:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
303: #else
304:     PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info));
305:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS - Bad solve");
306: #endif
307:   }
308:   VecRestoreArray(xx,&x);
309:   VecRestoreArray(yy,&y);
310:   PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);
311:   return(0);
312: }

316: PetscErrorCode MatSolveAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
317: {
318:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
320:   PetscScalar    *x,*y,sone = 1.0;
321:   Vec            tmp = 0;
322:   PetscBLASInt   one = 1,info,m;

325:   PetscBLASIntCast(A->rmap->n,&m);
326:   VecGetArray(xx,&x);
327:   VecGetArray(yy,&y);
328:   if (!A->rmap->n || !A->cmap->n) return(0);
329:   if (yy == zz) {
330:     VecDuplicate(yy,&tmp);
331:     PetscLogObjectParent(A,tmp);
332:     VecCopy(yy,tmp);
333:   }
334:   PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));
335:   /* assume if pivots exist then use LU; else Cholesky */
336:   if (mat->pivots) {
337: #if defined(PETSC_MISSING_LAPACK_GETRS)
338:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
339: #else
340:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
341:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve");
342: #endif
343:   } else {
344: #if defined(PETSC_MISSING_LAPACK_POTRS)
345:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
346: #else
347:     PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info));
348:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve");
349: #endif
350:   }
351:   if (tmp) {
352:     VecAXPY(yy,sone,tmp);
353:     VecDestroy(&tmp);
354:   } else {
355:     VecAXPY(yy,sone,zz);
356:   }
357:   VecRestoreArray(xx,&x);
358:   VecRestoreArray(yy,&y);
359:   PetscLogFlops(2.0*A->cmap->n*A->cmap->n);
360:   return(0);
361: }

365: PetscErrorCode MatSolveTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
366: {
367:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
369:   PetscScalar    *x,*y,sone = 1.0;
370:   Vec            tmp;
371:   PetscBLASInt   one = 1,info,m;

374:   PetscBLASIntCast(A->rmap->n,&m);
375:   if (!A->rmap->n || !A->cmap->n) return(0);
376:   VecGetArray(xx,&x);
377:   VecGetArray(yy,&y);
378:   if (yy == zz) {
379:     VecDuplicate(yy,&tmp);
380:     PetscLogObjectParent(A,tmp);
381:     VecCopy(yy,tmp);
382:   }
383:   PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));
384:   /* assume if pivots exist then use LU; else Cholesky */
385:   if (mat->pivots) {
386: #if defined(PETSC_MISSING_LAPACK_GETRS)
387:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable.");
388: #else
389:     PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("T",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info));
390:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve");
391: #endif
392:   } else {
393: #if defined(PETSC_MISSING_LAPACK_POTRS)
394:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable.");
395: #else
396:     PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info));
397:     if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve");
398: #endif
399:   }
400:   if (tmp) {
401:     VecAXPY(yy,sone,tmp);
402:     VecDestroy(&tmp);
403:   } else {
404:     VecAXPY(yy,sone,zz);
405:   }
406:   VecRestoreArray(xx,&x);
407:   VecRestoreArray(yy,&y);
408:   PetscLogFlops(2.0*A->cmap->n*A->cmap->n);
409:   return(0);
410: }

412: /* ---------------------------------------------------------------*/
413: /* COMMENT: I have chosen to hide row permutation in the pivots,
414:    rather than put it in the Mat->row slot.*/
417: PetscErrorCode MatLUFactor_SeqDense(Mat A,IS row,IS col,const MatFactorInfo *minfo)
418: {
419: #if defined(PETSC_MISSING_LAPACK_GETRF)
421:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRF - Lapack routine is unavailable.");
422: #else
423:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
425:   PetscBLASInt   n,m,info;

428:   PetscBLASIntCast(A->cmap->n,&n);
429:   PetscBLASIntCast(A->rmap->n,&m);
430:   if (!mat->pivots) {
431:     PetscMalloc((A->rmap->n+1)*sizeof(PetscBLASInt),&mat->pivots);
432:     PetscLogObjectMemory(A,A->rmap->n*sizeof(PetscBLASInt));
433:   }
434:   if (!A->rmap->n || !A->cmap->n) return(0);
435:   PetscFPTrapPush(PETSC_FP_TRAP_OFF);
436:   PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&m,&n,mat->v,&mat->lda,mat->pivots,&info));
437:   PetscFPTrapPop();

439:   if (info<0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad argument to LU factorization");
440:   if (info>0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Bad LU factorization");
441:   A->ops->solve             = MatSolve_SeqDense;
442:   A->ops->solvetranspose    = MatSolveTranspose_SeqDense;
443:   A->ops->solveadd          = MatSolveAdd_SeqDense;
444:   A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense;
445:   A->factortype             = MAT_FACTOR_LU;

447:   PetscLogFlops((2.0*A->cmap->n*A->cmap->n*A->cmap->n)/3);
448: #endif
449:   return(0);
450: }

454: PetscErrorCode MatCholeskyFactor_SeqDense(Mat A,IS perm,const MatFactorInfo *factinfo)
455: {
456: #if defined(PETSC_MISSING_LAPACK_POTRF)
458:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable.");
459: #else
460:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
462:   PetscBLASInt   info,n;

465:   PetscBLASIntCast(A->cmap->n,&n);
466:   PetscFree(mat->pivots);

468:   if (!A->rmap->n || !A->cmap->n) return(0);
469:   PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&n,mat->v,&mat->lda,&info));
470:   if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad factorization: zero pivot in row %D",(PetscInt)info-1);
471:   A->ops->solve             = MatSolve_SeqDense;
472:   A->ops->solvetranspose    = MatSolveTranspose_SeqDense;
473:   A->ops->solveadd          = MatSolveAdd_SeqDense;
474:   A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense;
475:   A->factortype             = MAT_FACTOR_CHOLESKY;

477:   PetscLogFlops((A->cmap->n*A->cmap->n*A->cmap->n)/3.0);
478: #endif
479:   return(0);
480: }


485: PetscErrorCode MatCholeskyFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy)
486: {
488:   MatFactorInfo  info;

491:   info.fill = 1.0;

493:   MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);
494:   MatCholeskyFactor_SeqDense(fact,0,&info);
495:   return(0);
496: }

500: PetscErrorCode MatCholeskyFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,const MatFactorInfo *info)
501: {
503:   fact->assembled                  = PETSC_TRUE;
504:   fact->preallocated               = PETSC_TRUE;
505:   fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqDense;
506:   return(0);
507: }

511: PetscErrorCode MatLUFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,IS col,const MatFactorInfo *info)
512: {
514:   fact->preallocated         = PETSC_TRUE;
515:   fact->assembled            = PETSC_TRUE;
516:   fact->ops->lufactornumeric = MatLUFactorNumeric_SeqDense;
517:   return(0);
518: }

522: PETSC_EXTERN PetscErrorCode MatGetFactor_seqdense_petsc(Mat A,MatFactorType ftype,Mat *fact)
523: {

527:   MatCreate(PetscObjectComm((PetscObject)A),fact);
528:   MatSetSizes(*fact,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);
529:   MatSetType(*fact,((PetscObject)A)->type_name);
530:   if (ftype == MAT_FACTOR_LU) {
531:     (*fact)->ops->lufactorsymbolic = MatLUFactorSymbolic_SeqDense;
532:   } else {
533:     (*fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqDense;
534:   }
535:   (*fact)->factortype = ftype;
536:   return(0);
537: }

539: /* ------------------------------------------------------------------*/
542: PetscErrorCode MatSOR_SeqDense(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal shift,PetscInt its,PetscInt lits,Vec xx)
543: {
544:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
545:   PetscScalar    *x,*b,*v = mat->v,zero = 0.0,xt;
547:   PetscInt       m = A->rmap->n,i;
548:   PetscBLASInt   o = 1,bm;

551:   PetscBLASIntCast(m,&bm);
552:   if (flag & SOR_ZERO_INITIAL_GUESS) {
553:     /* this is a hack fix, should have another version without the second BLASdot */
554:     VecSet(xx,zero);
555:   }
556:   VecGetArray(xx,&x);
557:   VecGetArray(bb,&b);
558:   its  = its*lits;
559:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
560:   while (its--) {
561:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
562:       for (i=0; i<m; i++) {
563:         PetscStackCallBLAS("BLASdot",xt   = b[i] - BLASdot_(&bm,v+i,&bm,x,&o));
564:         x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift);
565:       }
566:     }
567:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
568:       for (i=m-1; i>=0; i--) {
569:         PetscStackCallBLAS("BLASdot",xt   = b[i] - BLASdot_(&bm,v+i,&bm,x,&o));
570:         x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift);
571:       }
572:     }
573:   }
574:   VecRestoreArray(bb,&b);
575:   VecRestoreArray(xx,&x);
576:   return(0);
577: }

579: /* -----------------------------------------------------------------*/
582: PetscErrorCode MatMultTranspose_SeqDense(Mat A,Vec xx,Vec yy)
583: {
584:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
585:   PetscScalar    *v   = mat->v,*x,*y;
587:   PetscBLASInt   m, n,_One=1;
588:   PetscScalar    _DOne=1.0,_DZero=0.0;

591:   PetscBLASIntCast(A->rmap->n,&m);
592:   PetscBLASIntCast(A->cmap->n,&n);
593:   if (!A->rmap->n || !A->cmap->n) return(0);
594:   VecGetArray(xx,&x);
595:   VecGetArray(yy,&y);
596:   PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&mat->lda,x,&_One,&_DZero,y,&_One));
597:   VecRestoreArray(xx,&x);
598:   VecRestoreArray(yy,&y);
599:   PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->cmap->n);
600:   return(0);
601: }

605: PetscErrorCode MatMult_SeqDense(Mat A,Vec xx,Vec yy)
606: {
607:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
608:   PetscScalar    *v   = mat->v,*x,*y,_DOne=1.0,_DZero=0.0;
610:   PetscBLASInt   m, n, _One=1;

613:   PetscBLASIntCast(A->rmap->n,&m);
614:   PetscBLASIntCast(A->cmap->n,&n);
615:   if (!A->rmap->n || !A->cmap->n) return(0);
616:   VecGetArray(xx,&x);
617:   VecGetArray(yy,&y);
618:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DZero,y,&_One));
619:   VecRestoreArray(xx,&x);
620:   VecRestoreArray(yy,&y);
621:   PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->rmap->n);
622:   return(0);
623: }

627: PetscErrorCode MatMultAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
628: {
629:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
630:   PetscScalar    *v   = mat->v,*x,*y,_DOne=1.0;
632:   PetscBLASInt   m, n, _One=1;

635:   PetscBLASIntCast(A->rmap->n,&m);
636:   PetscBLASIntCast(A->cmap->n,&n);
637:   if (!A->rmap->n || !A->cmap->n) return(0);
638:   if (zz != yy) {VecCopy(zz,yy);}
639:   VecGetArray(xx,&x);
640:   VecGetArray(yy,&y);
641:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One));
642:   VecRestoreArray(xx,&x);
643:   VecRestoreArray(yy,&y);
644:   PetscLogFlops(2.0*A->rmap->n*A->cmap->n);
645:   return(0);
646: }

650: PetscErrorCode MatMultTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy)
651: {
652:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
653:   PetscScalar    *v   = mat->v,*x,*y;
655:   PetscBLASInt   m, n, _One=1;
656:   PetscScalar    _DOne=1.0;

659:   PetscBLASIntCast(A->rmap->n,&m);
660:   PetscBLASIntCast(A->cmap->n,&n);
661:   if (!A->rmap->n || !A->cmap->n) return(0);
662:   if (zz != yy) {VecCopy(zz,yy);}
663:   VecGetArray(xx,&x);
664:   VecGetArray(yy,&y);
665:   PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One));
666:   VecRestoreArray(xx,&x);
667:   VecRestoreArray(yy,&y);
668:   PetscLogFlops(2.0*A->rmap->n*A->cmap->n);
669:   return(0);
670: }

672: /* -----------------------------------------------------------------*/
675: PetscErrorCode MatGetRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals)
676: {
677:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
678:   PetscScalar    *v;
680:   PetscInt       i;

683:   *ncols = A->cmap->n;
684:   if (cols) {
685:     PetscMalloc((A->cmap->n+1)*sizeof(PetscInt),cols);
686:     for (i=0; i<A->cmap->n; i++) (*cols)[i] = i;
687:   }
688:   if (vals) {
689:     PetscMalloc((A->cmap->n+1)*sizeof(PetscScalar),vals);
690:     v    = mat->v + row;
691:     for (i=0; i<A->cmap->n; i++) {(*vals)[i] = *v; v += mat->lda;}
692:   }
693:   return(0);
694: }

698: PetscErrorCode MatRestoreRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals)
699: {

703:   if (cols) {PetscFree(*cols);}
704:   if (vals) {PetscFree(*vals); }
705:   return(0);
706: }
707: /* ----------------------------------------------------------------*/
710: PetscErrorCode MatSetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],const PetscScalar v[],InsertMode addv)
711: {
712:   Mat_SeqDense *mat = (Mat_SeqDense*)A->data;
713:   PetscInt     i,j,idx=0;

717:   if (!mat->roworiented) {
718:     if (addv == INSERT_VALUES) {
719:       for (j=0; j<n; j++) {
720:         if (indexn[j] < 0) {idx += m; continue;}
721: #if defined(PETSC_USE_DEBUG)
722:         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);
723: #endif
724:         for (i=0; i<m; i++) {
725:           if (indexm[i] < 0) {idx++; continue;}
726: #if defined(PETSC_USE_DEBUG)
727:           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);
728: #endif
729:           mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++];
730:         }
731:       }
732:     } else {
733:       for (j=0; j<n; j++) {
734:         if (indexn[j] < 0) {idx += m; continue;}
735: #if defined(PETSC_USE_DEBUG)
736:         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);
737: #endif
738:         for (i=0; i<m; i++) {
739:           if (indexm[i] < 0) {idx++; continue;}
740: #if defined(PETSC_USE_DEBUG)
741:           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);
742: #endif
743:           mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++];
744:         }
745:       }
746:     }
747:   } else {
748:     if (addv == INSERT_VALUES) {
749:       for (i=0; i<m; i++) {
750:         if (indexm[i] < 0) { idx += n; continue;}
751: #if defined(PETSC_USE_DEBUG)
752:         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);
753: #endif
754:         for (j=0; j<n; j++) {
755:           if (indexn[j] < 0) { idx++; continue;}
756: #if defined(PETSC_USE_DEBUG)
757:           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);
758: #endif
759:           mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++];
760:         }
761:       }
762:     } else {
763:       for (i=0; i<m; i++) {
764:         if (indexm[i] < 0) { idx += n; continue;}
765: #if defined(PETSC_USE_DEBUG)
766:         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);
767: #endif
768:         for (j=0; j<n; j++) {
769:           if (indexn[j] < 0) { idx++; continue;}
770: #if defined(PETSC_USE_DEBUG)
771:           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);
772: #endif
773:           mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++];
774:         }
775:       }
776:     }
777:   }
778:   return(0);
779: }

783: PetscErrorCode MatGetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],PetscScalar v[])
784: {
785:   Mat_SeqDense *mat = (Mat_SeqDense*)A->data;
786:   PetscInt     i,j;

789:   /* row-oriented output */
790:   for (i=0; i<m; i++) {
791:     if (indexm[i] < 0) {v += n;continue;}
792:     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);
793:     for (j=0; j<n; j++) {
794:       if (indexn[j] < 0) {v++; continue;}
795:       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);
796:       *v++ = mat->v[indexn[j]*mat->lda + indexm[i]];
797:     }
798:   }
799:   return(0);
800: }

802: /* -----------------------------------------------------------------*/

806: PetscErrorCode MatLoad_SeqDense(Mat newmat,PetscViewer viewer)
807: {
808:   Mat_SeqDense   *a;
810:   PetscInt       *scols,i,j,nz,header[4];
811:   int            fd;
812:   PetscMPIInt    size;
813:   PetscInt       *rowlengths = 0,M,N,*cols,grows,gcols;
814:   PetscScalar    *vals,*svals,*v,*w;
815:   MPI_Comm       comm;

818:   PetscObjectGetComm((PetscObject)viewer,&comm);
819:   MPI_Comm_size(comm,&size);
820:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor");
821:   PetscViewerBinaryGetDescriptor(viewer,&fd);
822:   PetscBinaryRead(fd,header,4,PETSC_INT);
823:   if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not matrix object");
824:   M = header[1]; N = header[2]; nz = header[3];

826:   /* set global size if not set already*/
827:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) {
828:     MatSetSizes(newmat,M,N,M,N);
829:   } else {
830:     /* if sizes and type are already set, check if the vector global sizes are correct */
831:     MatGetSize(newmat,&grows,&gcols);
832:     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);
833:   }
834:   MatSeqDenseSetPreallocation(newmat,NULL);

836:   if (nz == MATRIX_BINARY_FORMAT_DENSE) { /* matrix in file is dense */
837:     a = (Mat_SeqDense*)newmat->data;
838:     v = a->v;
839:     /* Allocate some temp space to read in the values and then flip them
840:        from row major to column major */
841:     PetscMalloc((M*N > 0 ? M*N : 1)*sizeof(PetscScalar),&w);
842:     /* read in nonzero values */
843:     PetscBinaryRead(fd,w,M*N,PETSC_SCALAR);
844:     /* now flip the values and store them in the matrix*/
845:     for (j=0; j<N; j++) {
846:       for (i=0; i<M; i++) {
847:         *v++ =w[i*N+j];
848:       }
849:     }
850:     PetscFree(w);
851:   } else {
852:     /* read row lengths */
853:     PetscMalloc((M+1)*sizeof(PetscInt),&rowlengths);
854:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);

856:     a = (Mat_SeqDense*)newmat->data;
857:     v = a->v;

859:     /* read column indices and nonzeros */
860:     PetscMalloc((nz+1)*sizeof(PetscInt),&scols);
861:     cols = scols;
862:     PetscBinaryRead(fd,cols,nz,PETSC_INT);
863:     PetscMalloc((nz+1)*sizeof(PetscScalar),&svals);
864:     vals = svals;
865:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

867:     /* insert into matrix */
868:     for (i=0; i<M; i++) {
869:       for (j=0; j<rowlengths[i]; j++) v[i+M*scols[j]] = svals[j];
870:       svals += rowlengths[i]; scols += rowlengths[i];
871:     }
872:     PetscFree(vals);
873:     PetscFree(cols);
874:     PetscFree(rowlengths);
875:   }
876:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
877:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
878:   return(0);
879: }

883: static PetscErrorCode MatView_SeqDense_ASCII(Mat A,PetscViewer viewer)
884: {
885:   Mat_SeqDense      *a = (Mat_SeqDense*)A->data;
886:   PetscErrorCode    ierr;
887:   PetscInt          i,j;
888:   const char        *name;
889:   PetscScalar       *v;
890:   PetscViewerFormat format;
891: #if defined(PETSC_USE_COMPLEX)
892:   PetscBool allreal = PETSC_TRUE;
893: #endif

896:   PetscViewerGetFormat(viewer,&format);
897:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
898:     return(0);  /* do nothing for now */
899:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
900:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
901:     PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer,"Matrix Object");
902:     for (i=0; i<A->rmap->n; i++) {
903:       v    = a->v + i;
904:       PetscViewerASCIIPrintf(viewer,"row %D:",i);
905:       for (j=0; j<A->cmap->n; j++) {
906: #if defined(PETSC_USE_COMPLEX)
907:         if (PetscRealPart(*v) != 0.0 && PetscImaginaryPart(*v) != 0.0) {
908:           PetscViewerASCIIPrintf(viewer," (%D, %G + %G i) ",j,PetscRealPart(*v),PetscImaginaryPart(*v));
909:         } else if (PetscRealPart(*v)) {
910:           PetscViewerASCIIPrintf(viewer," (%D, %G) ",j,PetscRealPart(*v));
911:         }
912: #else
913:         if (*v) {
914:           PetscViewerASCIIPrintf(viewer," (%D, %G) ",j,*v);
915:         }
916: #endif
917:         v += a->lda;
918:       }
919:       PetscViewerASCIIPrintf(viewer,"\n");
920:     }
921:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
922:   } else {
923:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
924: #if defined(PETSC_USE_COMPLEX)
925:     /* determine if matrix has all real values */
926:     v = a->v;
927:     for (i=0; i<A->rmap->n*A->cmap->n; i++) {
928:       if (PetscImaginaryPart(v[i])) { allreal = PETSC_FALSE; break;}
929:     }
930: #endif
931:     if (format == PETSC_VIEWER_ASCII_MATLAB) {
932:       PetscObjectGetName((PetscObject)A,&name);
933:       PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",A->rmap->n,A->cmap->n);
934:       PetscViewerASCIIPrintf(viewer,"%s = zeros(%D,%D);\n",name,A->rmap->n,A->cmap->n);
935:       PetscViewerASCIIPrintf(viewer,"%s = [\n",name);
936:     } else {
937:       PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer,"Matrix Object");
938:     }

940:     for (i=0; i<A->rmap->n; i++) {
941:       v = a->v + i;
942:       for (j=0; j<A->cmap->n; j++) {
943: #if defined(PETSC_USE_COMPLEX)
944:         if (allreal) {
945:           PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)PetscRealPart(*v));
946:         } else {
947:           PetscViewerASCIIPrintf(viewer,"%18.16e + %18.16ei ",(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));
948:         }
949: #else
950:         PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*v);
951: #endif
952:         v += a->lda;
953:       }
954:       PetscViewerASCIIPrintf(viewer,"\n");
955:     }
956:     if (format == PETSC_VIEWER_ASCII_MATLAB) {
957:       PetscViewerASCIIPrintf(viewer,"];\n");
958:     }
959:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
960:   }
961:   PetscViewerFlush(viewer);
962:   return(0);
963: }

967: static PetscErrorCode MatView_SeqDense_Binary(Mat A,PetscViewer viewer)
968: {
969:   Mat_SeqDense      *a = (Mat_SeqDense*)A->data;
970:   PetscErrorCode    ierr;
971:   int               fd;
972:   PetscInt          ict,j,n = A->cmap->n,m = A->rmap->n,i,*col_lens,nz = m*n;
973:   PetscScalar       *v,*anonz,*vals;
974:   PetscViewerFormat format;

977:   PetscViewerBinaryGetDescriptor(viewer,&fd);

979:   PetscViewerGetFormat(viewer,&format);
980:   if (format == PETSC_VIEWER_NATIVE) {
981:     /* store the matrix as a dense matrix */
982:     PetscMalloc(4*sizeof(PetscInt),&col_lens);

984:     col_lens[0] = MAT_FILE_CLASSID;
985:     col_lens[1] = m;
986:     col_lens[2] = n;
987:     col_lens[3] = MATRIX_BINARY_FORMAT_DENSE;

989:     PetscBinaryWrite(fd,col_lens,4,PETSC_INT,PETSC_TRUE);
990:     PetscFree(col_lens);

992:     /* write out matrix, by rows */
993:     PetscMalloc((m*n+1)*sizeof(PetscScalar),&vals);
994:     v    = a->v;
995:     for (j=0; j<n; j++) {
996:       for (i=0; i<m; i++) {
997:         vals[j + i*n] = *v++;
998:       }
999:     }
1000:     PetscBinaryWrite(fd,vals,n*m,PETSC_SCALAR,PETSC_FALSE);
1001:     PetscFree(vals);
1002:   } else {
1003:     PetscMalloc((4+nz)*sizeof(PetscInt),&col_lens);

1005:     col_lens[0] = MAT_FILE_CLASSID;
1006:     col_lens[1] = m;
1007:     col_lens[2] = n;
1008:     col_lens[3] = nz;

1010:     /* store lengths of each row and write (including header) to file */
1011:     for (i=0; i<m; i++) col_lens[4+i] = n;
1012:     PetscBinaryWrite(fd,col_lens,4+m,PETSC_INT,PETSC_TRUE);

1014:     /* Possibly should write in smaller increments, not whole matrix at once? */
1015:     /* store column indices (zero start index) */
1016:     ict = 0;
1017:     for (i=0; i<m; i++) {
1018:       for (j=0; j<n; j++) col_lens[ict++] = j;
1019:     }
1020:     PetscBinaryWrite(fd,col_lens,nz,PETSC_INT,PETSC_FALSE);
1021:     PetscFree(col_lens);

1023:     /* store nonzero values */
1024:     PetscMalloc((nz+1)*sizeof(PetscScalar),&anonz);
1025:     ict  = 0;
1026:     for (i=0; i<m; i++) {
1027:       v = a->v + i;
1028:       for (j=0; j<n; j++) {
1029:         anonz[ict++] = *v; v += a->lda;
1030:       }
1031:     }
1032:     PetscBinaryWrite(fd,anonz,nz,PETSC_SCALAR,PETSC_FALSE);
1033:     PetscFree(anonz);
1034:   }
1035:   return(0);
1036: }

1038: #include <petscdraw.h>
1041: PetscErrorCode MatView_SeqDense_Draw_Zoom(PetscDraw draw,void *Aa)
1042: {
1043:   Mat               A  = (Mat) Aa;
1044:   Mat_SeqDense      *a = (Mat_SeqDense*)A->data;
1045:   PetscErrorCode    ierr;
1046:   PetscInt          m  = A->rmap->n,n = A->cmap->n,color,i,j;
1047:   PetscScalar       *v = a->v;
1048:   PetscViewer       viewer;
1049:   PetscDraw         popup;
1050:   PetscReal         xl,yl,xr,yr,x_l,x_r,y_l,y_r,scale,maxv = 0.0;
1051:   PetscViewerFormat format;

1054:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
1055:   PetscViewerGetFormat(viewer,&format);
1056:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);

1058:   /* Loop over matrix elements drawing boxes */
1059:   if (format != PETSC_VIEWER_DRAW_CONTOUR) {
1060:     /* Blue for negative and Red for positive */
1061:     color = PETSC_DRAW_BLUE;
1062:     for (j = 0; j < n; j++) {
1063:       x_l = j;
1064:       x_r = x_l + 1.0;
1065:       for (i = 0; i < m; i++) {
1066:         y_l = m - i - 1.0;
1067:         y_r = y_l + 1.0;
1068:         if (PetscRealPart(v[j*m+i]) >  0.) {
1069:           color = PETSC_DRAW_RED;
1070:         } else if (PetscRealPart(v[j*m+i]) <  0.) {
1071:           color = PETSC_DRAW_BLUE;
1072:         } else {
1073:           continue;
1074:         }
1075:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1076:       }
1077:     }
1078:   } else {
1079:     /* use contour shading to indicate magnitude of values */
1080:     /* first determine max of all nonzero values */
1081:     for (i = 0; i < m*n; i++) {
1082:       if (PetscAbsScalar(v[i]) > maxv) maxv = PetscAbsScalar(v[i]);
1083:     }
1084:     scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv;
1085:     PetscDrawGetPopup(draw,&popup);
1086:     if (popup) {PetscDrawScalePopup(popup,0.0,maxv);}
1087:     for (j = 0; j < n; j++) {
1088:       x_l = j;
1089:       x_r = x_l + 1.0;
1090:       for (i = 0; i < m; i++) {
1091:         y_l   = m - i - 1.0;
1092:         y_r   = y_l + 1.0;
1093:         color = PETSC_DRAW_BASIC_COLORS + (int)(scale*PetscAbsScalar(v[j*m+i]));
1094:         PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);
1095:       }
1096:     }
1097:   }
1098:   return(0);
1099: }

1103: PetscErrorCode MatView_SeqDense_Draw(Mat A,PetscViewer viewer)
1104: {
1105:   PetscDraw      draw;
1106:   PetscBool      isnull;
1107:   PetscReal      xr,yr,xl,yl,h,w;

1111:   PetscViewerDrawGetDraw(viewer,0,&draw);
1112:   PetscDrawIsNull(draw,&isnull);
1113:   if (isnull) return(0);

1115:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
1116:   xr   = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0;
1117:   xr  += w;    yr += h;  xl = -w;     yl = -h;
1118:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
1119:   PetscDrawZoom(draw,MatView_SeqDense_Draw_Zoom,A);
1120:   PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
1121:   return(0);
1122: }

1126: PetscErrorCode MatView_SeqDense(Mat A,PetscViewer viewer)
1127: {
1129:   PetscBool      iascii,isbinary,isdraw;

1132:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1133:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1134:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);

1136:   if (iascii) {
1137:     MatView_SeqDense_ASCII(A,viewer);
1138:   } else if (isbinary) {
1139:     MatView_SeqDense_Binary(A,viewer);
1140:   } else if (isdraw) {
1141:     MatView_SeqDense_Draw(A,viewer);
1142:   }
1143:   return(0);
1144: }

1148: PetscErrorCode MatDestroy_SeqDense(Mat mat)
1149: {
1150:   Mat_SeqDense   *l = (Mat_SeqDense*)mat->data;

1154: #if defined(PETSC_USE_LOG)
1155:   PetscLogObjectState((PetscObject)mat,"Rows %D Cols %D",mat->rmap->n,mat->cmap->n);
1156: #endif
1157:   PetscFree(l->pivots);
1158:   if (!l->user_alloc) {PetscFree(l->v);}
1159:   PetscFree(mat->data);

1161:   PetscObjectChangeTypeName((PetscObject)mat,0);
1162:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);
1163:   PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);
1164:   PetscObjectComposeFunction((PetscObject)mat,"MatSeqDenseSetPreallocation_C",NULL);
1165:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_seqaij_seqdense_C",NULL);
1166:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_seqaij_seqdense_C",NULL);
1167:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_seqaij_seqdense_C",NULL);
1168:   return(0);
1169: }

1173: PetscErrorCode MatTranspose_SeqDense(Mat A,MatReuse reuse,Mat *matout)
1174: {
1175:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1177:   PetscInt       k,j,m,n,M;
1178:   PetscScalar    *v,tmp;

1181:   v = mat->v; m = A->rmap->n; M = mat->lda; n = A->cmap->n;
1182:   if (reuse == MAT_REUSE_MATRIX && *matout == A) { /* in place transpose */
1183:     if (m != n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can not transpose non-square matrix in place");
1184:     else {
1185:       for (j=0; j<m; j++) {
1186:         for (k=0; k<j; k++) {
1187:           tmp        = v[j + k*M];
1188:           v[j + k*M] = v[k + j*M];
1189:           v[k + j*M] = tmp;
1190:         }
1191:       }
1192:     }
1193:   } else { /* out-of-place transpose */
1194:     Mat          tmat;
1195:     Mat_SeqDense *tmatd;
1196:     PetscScalar  *v2;

1198:     if (reuse == MAT_INITIAL_MATRIX) {
1199:       MatCreate(PetscObjectComm((PetscObject)A),&tmat);
1200:       MatSetSizes(tmat,A->cmap->n,A->rmap->n,A->cmap->n,A->rmap->n);
1201:       MatSetType(tmat,((PetscObject)A)->type_name);
1202:       MatSeqDenseSetPreallocation(tmat,NULL);
1203:     } else {
1204:       tmat = *matout;
1205:     }
1206:     tmatd = (Mat_SeqDense*)tmat->data;
1207:     v = mat->v; v2 = tmatd->v;
1208:     for (j=0; j<n; j++) {
1209:       for (k=0; k<m; k++) v2[j + k*n] = v[k + j*M];
1210:     }
1211:     MatAssemblyBegin(tmat,MAT_FINAL_ASSEMBLY);
1212:     MatAssemblyEnd(tmat,MAT_FINAL_ASSEMBLY);
1213:     *matout = tmat;
1214:   }
1215:   return(0);
1216: }

1220: PetscErrorCode MatEqual_SeqDense(Mat A1,Mat A2,PetscBool  *flg)
1221: {
1222:   Mat_SeqDense *mat1 = (Mat_SeqDense*)A1->data;
1223:   Mat_SeqDense *mat2 = (Mat_SeqDense*)A2->data;
1224:   PetscInt     i,j;
1225:   PetscScalar  *v1,*v2;

1228:   if (A1->rmap->n != A2->rmap->n) {*flg = PETSC_FALSE; return(0);}
1229:   if (A1->cmap->n != A2->cmap->n) {*flg = PETSC_FALSE; return(0);}
1230:   for (i=0; i<A1->rmap->n; i++) {
1231:     v1 = mat1->v+i; v2 = mat2->v+i;
1232:     for (j=0; j<A1->cmap->n; j++) {
1233:       if (*v1 != *v2) {*flg = PETSC_FALSE; return(0);}
1234:       v1 += mat1->lda; v2 += mat2->lda;
1235:     }
1236:   }
1237:   *flg = PETSC_TRUE;
1238:   return(0);
1239: }

1243: PetscErrorCode MatGetDiagonal_SeqDense(Mat A,Vec v)
1244: {
1245:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1247:   PetscInt       i,n,len;
1248:   PetscScalar    *x,zero = 0.0;

1251:   VecSet(v,zero);
1252:   VecGetSize(v,&n);
1253:   VecGetArray(v,&x);
1254:   len  = PetscMin(A->rmap->n,A->cmap->n);
1255:   if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec");
1256:   for (i=0; i<len; i++) {
1257:     x[i] = mat->v[i*mat->lda + i];
1258:   }
1259:   VecRestoreArray(v,&x);
1260:   return(0);
1261: }

1265: PetscErrorCode MatDiagonalScale_SeqDense(Mat A,Vec ll,Vec rr)
1266: {
1267:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1268:   PetscScalar    *l,*r,x,*v;
1270:   PetscInt       i,j,m = A->rmap->n,n = A->cmap->n;

1273:   if (ll) {
1274:     VecGetSize(ll,&m);
1275:     VecGetArray(ll,&l);
1276:     if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vec wrong size");
1277:     for (i=0; i<m; i++) {
1278:       x = l[i];
1279:       v = mat->v + i;
1280:       for (j=0; j<n; j++) { (*v) *= x; v+= m;}
1281:     }
1282:     VecRestoreArray(ll,&l);
1283:     PetscLogFlops(n*m);
1284:   }
1285:   if (rr) {
1286:     VecGetSize(rr,&n);
1287:     VecGetArray(rr,&r);
1288:     if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec wrong size");
1289:     for (i=0; i<n; i++) {
1290:       x = r[i];
1291:       v = mat->v + i*m;
1292:       for (j=0; j<m; j++) (*v++) *= x;
1293:     }
1294:     VecRestoreArray(rr,&r);
1295:     PetscLogFlops(n*m);
1296:   }
1297:   return(0);
1298: }

1302: PetscErrorCode MatNorm_SeqDense(Mat A,NormType type,PetscReal *nrm)
1303: {
1304:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1305:   PetscScalar    *v   = mat->v;
1306:   PetscReal      sum  = 0.0;
1307:   PetscInt       lda  =mat->lda,m=A->rmap->n,i,j;

1311:   if (type == NORM_FROBENIUS) {
1312:     if (lda>m) {
1313:       for (j=0; j<A->cmap->n; j++) {
1314:         v = mat->v+j*lda;
1315:         for (i=0; i<m; i++) {
1316:           sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1317:         }
1318:       }
1319:     } else {
1320:       for (i=0; i<A->cmap->n*A->rmap->n; i++) {
1321:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1322:       }
1323:     }
1324:     *nrm = PetscSqrtReal(sum);
1325:     PetscLogFlops(2.0*A->cmap->n*A->rmap->n);
1326:   } else if (type == NORM_1) {
1327:     *nrm = 0.0;
1328:     for (j=0; j<A->cmap->n; j++) {
1329:       v   = mat->v + j*mat->lda;
1330:       sum = 0.0;
1331:       for (i=0; i<A->rmap->n; i++) {
1332:         sum += PetscAbsScalar(*v);  v++;
1333:       }
1334:       if (sum > *nrm) *nrm = sum;
1335:     }
1336:     PetscLogFlops(A->cmap->n*A->rmap->n);
1337:   } else if (type == NORM_INFINITY) {
1338:     *nrm = 0.0;
1339:     for (j=0; j<A->rmap->n; j++) {
1340:       v   = mat->v + j;
1341:       sum = 0.0;
1342:       for (i=0; i<A->cmap->n; i++) {
1343:         sum += PetscAbsScalar(*v); v += mat->lda;
1344:       }
1345:       if (sum > *nrm) *nrm = sum;
1346:     }
1347:     PetscLogFlops(A->cmap->n*A->rmap->n);
1348:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No two norm");
1349:   return(0);
1350: }

1354: PetscErrorCode MatSetOption_SeqDense(Mat A,MatOption op,PetscBool flg)
1355: {
1356:   Mat_SeqDense   *aij = (Mat_SeqDense*)A->data;

1360:   switch (op) {
1361:   case MAT_ROW_ORIENTED:
1362:     aij->roworiented = flg;
1363:     break;
1364:   case MAT_NEW_NONZERO_LOCATIONS:
1365:   case MAT_NEW_NONZERO_LOCATION_ERR:
1366:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1367:   case MAT_NEW_DIAGONALS:
1368:   case MAT_KEEP_NONZERO_PATTERN:
1369:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1370:   case MAT_USE_HASH_TABLE:
1371:   case MAT_IGNORE_LOWER_TRIANGULAR:
1372:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1373:     break;
1374:   case MAT_SPD:
1375:   case MAT_SYMMETRIC:
1376:   case MAT_STRUCTURALLY_SYMMETRIC:
1377:   case MAT_HERMITIAN:
1378:   case MAT_SYMMETRY_ETERNAL:
1379:     /* These options are handled directly by MatSetOption() */
1380:     break;
1381:   default:
1382:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]);
1383:   }
1384:   return(0);
1385: }

1389: PetscErrorCode MatZeroEntries_SeqDense(Mat A)
1390: {
1391:   Mat_SeqDense   *l = (Mat_SeqDense*)A->data;
1393:   PetscInt       lda=l->lda,m=A->rmap->n,j;

1396:   if (lda>m) {
1397:     for (j=0; j<A->cmap->n; j++) {
1398:       PetscMemzero(l->v+j*lda,m*sizeof(PetscScalar));
1399:     }
1400:   } else {
1401:     PetscMemzero(l->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));
1402:   }
1403:   return(0);
1404: }

1408: PetscErrorCode MatZeroRows_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1409: {
1410:   PetscErrorCode    ierr;
1411:   Mat_SeqDense      *l = (Mat_SeqDense*)A->data;
1412:   PetscInt          m  = l->lda, n = A->cmap->n, i,j;
1413:   PetscScalar       *slot,*bb;
1414:   const PetscScalar *xx;

1417: #if defined(PETSC_USE_DEBUG)
1418:   for (i=0; i<N; i++) {
1419:     if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed");
1420:     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);
1421:   }
1422: #endif

1424:   /* fix right hand side if needed */
1425:   if (x && b) {
1426:     VecGetArrayRead(x,&xx);
1427:     VecGetArray(b,&bb);
1428:     for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]];
1429:     VecRestoreArrayRead(x,&xx);
1430:     VecRestoreArray(b,&bb);
1431:   }

1433:   for (i=0; i<N; i++) {
1434:     slot = l->v + rows[i];
1435:     for (j=0; j<n; j++) { *slot = 0.0; slot += m;}
1436:   }
1437:   if (diag != 0.0) {
1438:     if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices");
1439:     for (i=0; i<N; i++) {
1440:       slot  = l->v + (m+1)*rows[i];
1441:       *slot = diag;
1442:     }
1443:   }
1444:   return(0);
1445: }

1449: PetscErrorCode MatDenseGetArray_SeqDense(Mat A,PetscScalar *array[])
1450: {
1451:   Mat_SeqDense *mat = (Mat_SeqDense*)A->data;

1454:   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");
1455:   *array = mat->v;
1456:   return(0);
1457: }

1461: PetscErrorCode MatDenseRestoreArray_SeqDense(Mat A,PetscScalar *array[])
1462: {
1464:   *array = 0; /* user cannot accidently use the array later */
1465:   return(0);
1466: }

1470: /*@C
1471:    MatDenseGetArray - gives access to the array where the data for a SeqDense matrix is stored

1473:    Not Collective

1475:    Input Parameter:
1476: .  mat - a MATSEQDENSE matrix

1478:    Output Parameter:
1479: .   array - pointer to the data

1481:    Level: intermediate

1483: .seealso: MatDenseRestoreArray()
1484: @*/
1485: PetscErrorCode  MatDenseGetArray(Mat A,PetscScalar **array)
1486: {

1490:   PetscUseMethod(A,"MatDenseGetArray_C",(Mat,PetscScalar**),(A,array));
1491:   return(0);
1492: }

1496: /*@C
1497:    MatDenseRestoreArray - returns access to the array where the data for a SeqDense matrix is stored obtained by MatDenseGetArray()

1499:    Not Collective

1501:    Input Parameters:
1502: .  mat - a MATSEQDENSE matrix
1503: .  array - pointer to the data

1505:    Level: intermediate

1507: .seealso: MatDenseGetArray()
1508: @*/
1509: PetscErrorCode  MatDenseRestoreArray(Mat A,PetscScalar **array)
1510: {

1514:   PetscUseMethod(A,"MatDenseRestoreArray_C",(Mat,PetscScalar**),(A,array));
1515:   return(0);
1516: }

1520: static PetscErrorCode MatGetSubMatrix_SeqDense(Mat A,IS isrow,IS iscol,PetscInt cs,MatReuse scall,Mat *B)
1521: {
1522:   Mat_SeqDense   *mat = (Mat_SeqDense*)A->data;
1524:   PetscInt       i,j,nrows,ncols;
1525:   const PetscInt *irow,*icol;
1526:   PetscScalar    *av,*bv,*v = mat->v;
1527:   Mat            newmat;

1530:   ISGetIndices(isrow,&irow);
1531:   ISGetIndices(iscol,&icol);
1532:   ISGetLocalSize(isrow,&nrows);
1533:   ISGetLocalSize(iscol,&ncols);

1535:   /* Check submatrixcall */
1536:   if (scall == MAT_REUSE_MATRIX) {
1537:     PetscInt n_cols,n_rows;
1538:     MatGetSize(*B,&n_rows,&n_cols);
1539:     if (n_rows != nrows || n_cols != ncols) {
1540:       /* resize the result matrix to match number of requested rows/columns */
1541:       MatSetSizes(*B,nrows,ncols,nrows,ncols);
1542:     }
1543:     newmat = *B;
1544:   } else {
1545:     /* Create and fill new matrix */
1546:     MatCreate(PetscObjectComm((PetscObject)A),&newmat);
1547:     MatSetSizes(newmat,nrows,ncols,nrows,ncols);
1548:     MatSetType(newmat,((PetscObject)A)->type_name);
1549:     MatSeqDenseSetPreallocation(newmat,NULL);
1550:   }

1552:   /* Now extract the data pointers and do the copy,column at a time */
1553:   bv = ((Mat_SeqDense*)newmat->data)->v;

1555:   for (i=0; i<ncols; i++) {
1556:     av = v + mat->lda*icol[i];
1557:     for (j=0; j<nrows; j++) *bv++ = av[irow[j]];
1558:   }

1560:   /* Assemble the matrices so that the correct flags are set */
1561:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
1562:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);

1564:   /* Free work space */
1565:   ISRestoreIndices(isrow,&irow);
1566:   ISRestoreIndices(iscol,&icol);
1567:   *B   = newmat;
1568:   return(0);
1569: }

1573: PetscErrorCode MatGetSubMatrices_SeqDense(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1574: {
1576:   PetscInt       i;

1579:   if (scall == MAT_INITIAL_MATRIX) {
1580:     PetscMalloc((n+1)*sizeof(Mat),B);
1581:   }

1583:   for (i=0; i<n; i++) {
1584:     MatGetSubMatrix_SeqDense(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);
1585:   }
1586:   return(0);
1587: }

1591: PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat,MatAssemblyType mode)
1592: {
1594:   return(0);
1595: }

1599: PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat,MatAssemblyType mode)
1600: {
1602:   return(0);
1603: }

1607: PetscErrorCode MatCopy_SeqDense(Mat A,Mat B,MatStructure str)
1608: {
1609:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data,*b = (Mat_SeqDense*)B->data;
1611:   PetscInt       lda1=a->lda,lda2=b->lda, m=A->rmap->n,n=A->cmap->n, j;

1614:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1615:   if (A->ops->copy != B->ops->copy) {
1616:     MatCopy_Basic(A,B,str);
1617:     return(0);
1618:   }
1619:   if (m != B->rmap->n || n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"size(B) != size(A)");
1620:   if (lda1>m || lda2>m) {
1621:     for (j=0; j<n; j++) {
1622:       PetscMemcpy(b->v+j*lda2,a->v+j*lda1,m*sizeof(PetscScalar));
1623:     }
1624:   } else {
1625:     PetscMemcpy(b->v,a->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));
1626:   }
1627:   return(0);
1628: }

1632: PetscErrorCode MatSetUp_SeqDense(Mat A)
1633: {

1637:    MatSeqDenseSetPreallocation(A,0);
1638:   return(0);
1639: }

1643: static PetscErrorCode MatConjugate_SeqDense(Mat A)
1644: {
1645:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
1646:   PetscInt     i,nz = A->rmap->n*A->cmap->n;
1647:   PetscScalar  *aa = a->v;

1650:   for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]);
1651:   return(0);
1652: }

1656: static PetscErrorCode MatRealPart_SeqDense(Mat A)
1657: {
1658:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
1659:   PetscInt     i,nz = A->rmap->n*A->cmap->n;
1660:   PetscScalar  *aa = a->v;

1663:   for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
1664:   return(0);
1665: }

1669: static PetscErrorCode MatImaginaryPart_SeqDense(Mat A)
1670: {
1671:   Mat_SeqDense *a = (Mat_SeqDense*)A->data;
1672:   PetscInt     i,nz = A->rmap->n*A->cmap->n;
1673:   PetscScalar  *aa = a->v;

1676:   for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
1677:   return(0);
1678: }

1680: /* ----------------------------------------------------------------*/
1683: PetscErrorCode MatMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
1684: {

1688:   if (scall == MAT_INITIAL_MATRIX) {
1689:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
1690:     MatMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);
1691:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
1692:   }
1693:   PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
1694:   MatMatMultNumeric_SeqDense_SeqDense(A,B,*C);
1695:   PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
1696:   return(0);
1697: }

1701: PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
1702: {
1704:   PetscInt       m=A->rmap->n,n=B->cmap->n;
1705:   Mat            Cmat;

1708:   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);
1709:   MatCreate(PETSC_COMM_SELF,&Cmat);
1710:   MatSetSizes(Cmat,m,n,m,n);
1711:   MatSetType(Cmat,MATSEQDENSE);
1712:   MatSeqDenseSetPreallocation(Cmat,NULL);

1714:   *C = Cmat;
1715:   return(0);
1716: }

1720: PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C)
1721: {
1722:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
1723:   Mat_SeqDense   *b = (Mat_SeqDense*)B->data;
1724:   Mat_SeqDense   *c = (Mat_SeqDense*)C->data;
1725:   PetscBLASInt   m,n,k;
1726:   PetscScalar    _DOne=1.0,_DZero=0.0;

1730:   PetscBLASIntCast(A->rmap->n,&m);
1731:   PetscBLASIntCast(B->cmap->n,&n);
1732:   PetscBLASIntCast(A->cmap->n,&k);
1733:   PetscStackCallBLAS("BLASgemv",BLASgemm_("N","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda));
1734:   return(0);
1735: }

1739: PetscErrorCode MatTransposeMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
1740: {

1744:   if (scall == MAT_INITIAL_MATRIX) {
1745:     PetscLogEventBegin(MAT_TransposeMatMultSymbolic,A,B,0,0);
1746:     MatTransposeMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);
1747:     PetscLogEventEnd(MAT_TransposeMatMultSymbolic,A,B,0,0);
1748:   }
1749:   PetscLogEventBegin(MAT_TransposeMatMultNumeric,A,B,0,0);
1750:   MatTransposeMatMultNumeric_SeqDense_SeqDense(A,B,*C);
1751:   PetscLogEventEnd(MAT_TransposeMatMultNumeric,A,B,0,0);
1752:   return(0);
1753: }

1757: PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
1758: {
1760:   PetscInt       m=A->cmap->n,n=B->cmap->n;
1761:   Mat            Cmat;

1764:   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);
1765:   MatCreate(PETSC_COMM_SELF,&Cmat);
1766:   MatSetSizes(Cmat,m,n,m,n);
1767:   MatSetType(Cmat,MATSEQDENSE);
1768:   MatSeqDenseSetPreallocation(Cmat,NULL);

1770:   Cmat->assembled = PETSC_TRUE;

1772:   *C = Cmat;
1773:   return(0);
1774: }

1778: PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C)
1779: {
1780:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
1781:   Mat_SeqDense   *b = (Mat_SeqDense*)B->data;
1782:   Mat_SeqDense   *c = (Mat_SeqDense*)C->data;
1783:   PetscBLASInt   m,n,k;
1784:   PetscScalar    _DOne=1.0,_DZero=0.0;

1788:   PetscBLASIntCast(A->cmap->n,&m);
1789:   PetscBLASIntCast(B->cmap->n,&n);
1790:   PetscBLASIntCast(A->rmap->n,&k);
1791:   /*
1792:      Note the m and n arguments below are the number rows and columns of A', not A!
1793:   */
1794:   PetscStackCallBLAS("BLASgemv",BLASgemm_("T","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda));
1795:   return(0);
1796: }

1800: PetscErrorCode MatGetRowMax_SeqDense(Mat A,Vec v,PetscInt idx[])
1801: {
1802:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
1804:   PetscInt       i,j,m = A->rmap->n,n = A->cmap->n,p;
1805:   PetscScalar    *x;
1806:   MatScalar      *aa = a->v;

1809:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

1811:   VecSet(v,0.0);
1812:   VecGetArray(v,&x);
1813:   VecGetLocalSize(v,&p);
1814:   if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
1815:   for (i=0; i<m; i++) {
1816:     x[i] = aa[i]; if (idx) idx[i] = 0;
1817:     for (j=1; j<n; j++) {
1818:       if (PetscRealPart(x[i]) < PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;}
1819:     }
1820:   }
1821:   VecRestoreArray(v,&x);
1822:   return(0);
1823: }

1827: PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A,Vec v,PetscInt idx[])
1828: {
1829:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
1831:   PetscInt       i,j,m = A->rmap->n,n = A->cmap->n,p;
1832:   PetscScalar    *x;
1833:   PetscReal      atmp;
1834:   MatScalar      *aa = a->v;

1837:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

1839:   VecSet(v,0.0);
1840:   VecGetArray(v,&x);
1841:   VecGetLocalSize(v,&p);
1842:   if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
1843:   for (i=0; i<m; i++) {
1844:     x[i] = PetscAbsScalar(aa[i]);
1845:     for (j=1; j<n; j++) {
1846:       atmp = PetscAbsScalar(aa[i+m*j]);
1847:       if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = j;}
1848:     }
1849:   }
1850:   VecRestoreArray(v,&x);
1851:   return(0);
1852: }

1856: PetscErrorCode MatGetRowMin_SeqDense(Mat A,Vec v,PetscInt idx[])
1857: {
1858:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
1860:   PetscInt       i,j,m = A->rmap->n,n = A->cmap->n,p;
1861:   PetscScalar    *x;
1862:   MatScalar      *aa = a->v;

1865:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

1867:   VecSet(v,0.0);
1868:   VecGetArray(v,&x);
1869:   VecGetLocalSize(v,&p);
1870:   if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
1871:   for (i=0; i<m; i++) {
1872:     x[i] = aa[i]; if (idx) idx[i] = 0;
1873:     for (j=1; j<n; j++) {
1874:       if (PetscRealPart(x[i]) > PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;}
1875:     }
1876:   }
1877:   VecRestoreArray(v,&x);
1878:   return(0);
1879: }

1883: PetscErrorCode MatGetColumnVector_SeqDense(Mat A,Vec v,PetscInt col)
1884: {
1885:   Mat_SeqDense   *a = (Mat_SeqDense*)A->data;
1887:   PetscScalar    *x;

1890:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");

1892:   VecGetArray(v,&x);
1893:   PetscMemcpy(x,a->v+col*a->lda,A->rmap->n*sizeof(PetscScalar));
1894:   VecRestoreArray(v,&x);
1895:   return(0);
1896: }


1901: PetscErrorCode MatGetColumnNorms_SeqDense(Mat A,NormType type,PetscReal *norms)
1902: {
1904:   PetscInt       i,j,m,n;
1905:   PetscScalar    *a;

1908:   MatGetSize(A,&m,&n);
1909:   PetscMemzero(norms,n*sizeof(PetscReal));
1910:   MatDenseGetArray(A,&a);
1911:   if (type == NORM_2) {
1912:     for (i=0; i<n; i++) {
1913:       for (j=0; j<m; j++) {
1914:         norms[i] += PetscAbsScalar(a[j]*a[j]);
1915:       }
1916:       a += m;
1917:     }
1918:   } else if (type == NORM_1) {
1919:     for (i=0; i<n; i++) {
1920:       for (j=0; j<m; j++) {
1921:         norms[i] += PetscAbsScalar(a[j]);
1922:       }
1923:       a += m;
1924:     }
1925:   } else if (type == NORM_INFINITY) {
1926:     for (i=0; i<n; i++) {
1927:       for (j=0; j<m; j++) {
1928:         norms[i] = PetscMax(PetscAbsScalar(a[j]),norms[i]);
1929:       }
1930:       a += m;
1931:     }
1932:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
1933:   MatDenseRestoreArray(A,&a);
1934:   if (type == NORM_2) {
1935:     for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
1936:   }
1937:   return(0);
1938: }

1942: static PetscErrorCode  MatSetRandom_SeqDense(Mat x,PetscRandom rctx)
1943: {
1945:   PetscScalar    *a;
1946:   PetscInt       m,n,i;

1949:   MatGetSize(x,&m,&n);
1950:   MatDenseGetArray(x,&a);
1951:   for (i=0; i<m*n; i++) {
1952:     PetscRandomGetValue(rctx,a+i);
1953:   }
1954:   MatDenseRestoreArray(x,&a);
1955:   return(0);
1956: }


1959: /* -------------------------------------------------------------------*/
1960: static struct _MatOps MatOps_Values = { MatSetValues_SeqDense,
1961:                                         MatGetRow_SeqDense,
1962:                                         MatRestoreRow_SeqDense,
1963:                                         MatMult_SeqDense,
1964:                                 /*  4*/ MatMultAdd_SeqDense,
1965:                                         MatMultTranspose_SeqDense,
1966:                                         MatMultTransposeAdd_SeqDense,
1967:                                         0,
1968:                                         0,
1969:                                         0,
1970:                                 /* 10*/ 0,
1971:                                         MatLUFactor_SeqDense,
1972:                                         MatCholeskyFactor_SeqDense,
1973:                                         MatSOR_SeqDense,
1974:                                         MatTranspose_SeqDense,
1975:                                 /* 15*/ MatGetInfo_SeqDense,
1976:                                         MatEqual_SeqDense,
1977:                                         MatGetDiagonal_SeqDense,
1978:                                         MatDiagonalScale_SeqDense,
1979:                                         MatNorm_SeqDense,
1980:                                 /* 20*/ MatAssemblyBegin_SeqDense,
1981:                                         MatAssemblyEnd_SeqDense,
1982:                                         MatSetOption_SeqDense,
1983:                                         MatZeroEntries_SeqDense,
1984:                                 /* 24*/ MatZeroRows_SeqDense,
1985:                                         0,
1986:                                         0,
1987:                                         0,
1988:                                         0,
1989:                                 /* 29*/ MatSetUp_SeqDense,
1990:                                         0,
1991:                                         0,
1992:                                         0,
1993:                                         0,
1994:                                 /* 34*/ MatDuplicate_SeqDense,
1995:                                         0,
1996:                                         0,
1997:                                         0,
1998:                                         0,
1999:                                 /* 39*/ MatAXPY_SeqDense,
2000:                                         MatGetSubMatrices_SeqDense,
2001:                                         0,
2002:                                         MatGetValues_SeqDense,
2003:                                         MatCopy_SeqDense,
2004:                                 /* 44*/ MatGetRowMax_SeqDense,
2005:                                         MatScale_SeqDense,
2006:                                         0,
2007:                                         0,
2008:                                         0,
2009:                                 /* 49*/ MatSetRandom_SeqDense,
2010:                                         0,
2011:                                         0,
2012:                                         0,
2013:                                         0,
2014:                                 /* 54*/ 0,
2015:                                         0,
2016:                                         0,
2017:                                         0,
2018:                                         0,
2019:                                 /* 59*/ 0,
2020:                                         MatDestroy_SeqDense,
2021:                                         MatView_SeqDense,
2022:                                         0,
2023:                                         0,
2024:                                 /* 64*/ 0,
2025:                                         0,
2026:                                         0,
2027:                                         0,
2028:                                         0,
2029:                                 /* 69*/ MatGetRowMaxAbs_SeqDense,
2030:                                         0,
2031:                                         0,
2032:                                         0,
2033:                                         0,
2034:                                 /* 74*/ 0,
2035:                                         0,
2036:                                         0,
2037:                                         0,
2038:                                         0,
2039:                                 /* 79*/ 0,
2040:                                         0,
2041:                                         0,
2042:                                         0,
2043:                                 /* 83*/ MatLoad_SeqDense,
2044:                                         0,
2045:                                         MatIsHermitian_SeqDense,
2046:                                         0,
2047:                                         0,
2048:                                         0,
2049:                                 /* 89*/ MatMatMult_SeqDense_SeqDense,
2050:                                         MatMatMultSymbolic_SeqDense_SeqDense,
2051:                                         MatMatMultNumeric_SeqDense_SeqDense,
2052:                                         0,
2053:                                         0,
2054:                                 /* 94*/ 0,
2055:                                         0,
2056:                                         0,
2057:                                         0,
2058:                                         0,
2059:                                 /* 99*/ 0,
2060:                                         0,
2061:                                         0,
2062:                                         MatConjugate_SeqDense,
2063:                                         0,
2064:                                 /*104*/ 0,
2065:                                         MatRealPart_SeqDense,
2066:                                         MatImaginaryPart_SeqDense,
2067:                                         0,
2068:                                         0,
2069:                                 /*109*/ MatMatSolve_SeqDense,
2070:                                         0,
2071:                                         MatGetRowMin_SeqDense,
2072:                                         MatGetColumnVector_SeqDense,
2073:                                         0,
2074:                                 /*114*/ 0,
2075:                                         0,
2076:                                         0,
2077:                                         0,
2078:                                         0,
2079:                                 /*119*/ 0,
2080:                                         0,
2081:                                         0,
2082:                                         0,
2083:                                         0,
2084:                                 /*124*/ 0,
2085:                                         MatGetColumnNorms_SeqDense,
2086:                                         0,
2087:                                         0,
2088:                                         0,
2089:                                 /*129*/ 0,
2090:                                         MatTransposeMatMult_SeqDense_SeqDense,
2091:                                         MatTransposeMatMultSymbolic_SeqDense_SeqDense,
2092:                                         MatTransposeMatMultNumeric_SeqDense_SeqDense,
2093:                                         0,
2094:                                 /*134*/ 0,
2095:                                         0,
2096:                                         0,
2097:                                         0,
2098:                                         0,
2099:                                 /*139*/ 0,
2100:                                         0
2101: };

2105: /*@C
2106:    MatCreateSeqDense - Creates a sequential dense matrix that
2107:    is stored in column major order (the usual Fortran 77 manner). Many
2108:    of the matrix operations use the BLAS and LAPACK routines.

2110:    Collective on MPI_Comm

2112:    Input Parameters:
2113: +  comm - MPI communicator, set to PETSC_COMM_SELF
2114: .  m - number of rows
2115: .  n - number of columns
2116: -  data - optional location of matrix data in column major order.  Set data=NULL for PETSc
2117:    to control all matrix memory allocation.

2119:    Output Parameter:
2120: .  A - the matrix

2122:    Notes:
2123:    The data input variable is intended primarily for Fortran programmers
2124:    who wish to allocate their own matrix memory space.  Most users should
2125:    set data=NULL.

2127:    Level: intermediate

2129: .keywords: dense, matrix, LAPACK, BLAS

2131: .seealso: MatCreate(), MatCreateDense(), MatSetValues()
2132: @*/
2133: PetscErrorCode  MatCreateSeqDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscScalar *data,Mat *A)
2134: {

2138:   MatCreate(comm,A);
2139:   MatSetSizes(*A,m,n,m,n);
2140:   MatSetType(*A,MATSEQDENSE);
2141:   MatSeqDenseSetPreallocation(*A,data);
2142:   return(0);
2143: }

2147: /*@C
2148:    MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements

2150:    Collective on MPI_Comm

2152:    Input Parameters:
2153: +  A - the matrix
2154: -  data - the array (or NULL)

2156:    Notes:
2157:    The data input variable is intended primarily for Fortran programmers
2158:    who wish to allocate their own matrix memory space.  Most users should
2159:    need not call this routine.

2161:    Level: intermediate

2163: .keywords: dense, matrix, LAPACK, BLAS

2165: .seealso: MatCreate(), MatCreateDense(), MatSetValues(), MatSeqDenseSetLDA()

2167: @*/
2168: PetscErrorCode  MatSeqDenseSetPreallocation(Mat B,PetscScalar data[])
2169: {

2173:   PetscTryMethod(B,"MatSeqDenseSetPreallocation_C",(Mat,PetscScalar[]),(B,data));
2174:   return(0);
2175: }

2179: PetscErrorCode  MatSeqDenseSetPreallocation_SeqDense(Mat B,PetscScalar *data)
2180: {
2181:   Mat_SeqDense   *b;

2185:   B->preallocated = PETSC_TRUE;

2187:   PetscLayoutSetUp(B->rmap);
2188:   PetscLayoutSetUp(B->cmap);

2190:   b       = (Mat_SeqDense*)B->data;
2191:   b->Mmax = B->rmap->n;
2192:   b->Nmax = B->cmap->n;
2193:   if (b->lda <= 0 || b->changelda) b->lda = B->rmap->n;

2195:   if (!data) { /* petsc-allocated storage */
2196:     if (!b->user_alloc) { PetscFree(b->v); }
2197:     PetscMalloc((size_t)b->lda*b->Nmax*sizeof(PetscScalar),&b->v);
2198:     PetscMemzero(b->v,b->lda*b->Nmax*sizeof(PetscScalar));
2199:     PetscLogObjectMemory(B,b->lda*b->Nmax*sizeof(PetscScalar));

2201:     b->user_alloc = PETSC_FALSE;
2202:   } else { /* user-allocated storage */
2203:     if (!b->user_alloc) { PetscFree(b->v); }
2204:     b->v          = data;
2205:     b->user_alloc = PETSC_TRUE;
2206:   }
2207:   B->assembled = PETSC_TRUE;
2208:   return(0);
2209: }

2213: /*@C
2214:   MatSeqDenseSetLDA - Declare the leading dimension of the user-provided array

2216:   Input parameter:
2217: + A - the matrix
2218: - lda - the leading dimension

2220:   Notes:
2221:   This routine is to be used in conjunction with MatSeqDenseSetPreallocation();
2222:   it asserts that the preallocation has a leading dimension (the LDA parameter
2223:   of Blas and Lapack fame) larger than M, the first dimension of the matrix.

2225:   Level: intermediate

2227: .keywords: dense, matrix, LAPACK, BLAS

2229: .seealso: MatCreate(), MatCreateSeqDense(), MatSeqDenseSetPreallocation(), MatSetMaximumSize()

2231: @*/
2232: PetscErrorCode  MatSeqDenseSetLDA(Mat B,PetscInt lda)
2233: {
2234:   Mat_SeqDense *b = (Mat_SeqDense*)B->data;

2237:   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);
2238:   b->lda       = lda;
2239:   b->changelda = PETSC_FALSE;
2240:   b->Mmax      = PetscMax(b->Mmax,lda);
2241:   return(0);
2242: }

2244: /*MC
2245:    MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices.

2247:    Options Database Keys:
2248: . -mat_type seqdense - sets the matrix type to "seqdense" during a call to MatSetFromOptions()

2250:   Level: beginner

2252: .seealso: MatCreateSeqDense()

2254: M*/

2258: PETSC_EXTERN PetscErrorCode MatCreate_SeqDense(Mat B)
2259: {
2260:   Mat_SeqDense   *b;
2262:   PetscMPIInt    size;

2265:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2266:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1");

2268:   PetscNewLog(B,Mat_SeqDense,&b);
2269:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
2270:   B->data = (void*)b;

2272:   b->pivots      = 0;
2273:   b->roworiented = PETSC_TRUE;
2274:   b->v           = 0;
2275:   b->changelda   = PETSC_FALSE;

2277:   PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArray_C",MatDenseGetArray_SeqDense);
2278:   PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArray_C",MatDenseRestoreArray_SeqDense);

2280:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_seqaij_C",MatConvert_SeqDense_SeqAIJ);
2281:   PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqdense_petsc);
2282:   PetscObjectComposeFunction((PetscObject)B,"MatSeqDenseSetPreallocation_C",MatSeqDenseSetPreallocation_SeqDense);
2283:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaij_seqdense_C",MatMatMult_SeqAIJ_SeqDense);
2284:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaij_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);
2285:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaij_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);
2286:   PetscObjectChangeTypeName((PetscObject)B,MATSEQDENSE);
2287:   return(0);
2288: }