Actual source code: ex2.c

petsc-master 2015-07-06
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  2: static char help[] ="Solves a time-dependent nonlinear PDE. Uses implicit\n\
  3: timestepping.  Runtime options include:\n\
  4:   -M <xg>, where <xg> = number of grid points\n\
  5:   -debug : Activate debugging printouts\n\
  6:   -nox   : Deactivate x-window graphics\n\n";

  8: /*
  9:    Concepts: TS^time-dependent nonlinear problems
 10:    Processors: n
 11: */

 13: /* ------------------------------------------------------------------------

 15:    This program solves the PDE

 17:                u * u_xx
 18:          u_t = ---------
 19:                2*(t+1)^2

 21:     on the domain 0 <= x <= 1, with boundary conditions
 22:          u(t,0) = t + 1,  u(t,1) = 2*t + 2,
 23:     and initial condition
 24:          u(0,x) = 1 + x*x.

 26:     The exact solution is:
 27:          u(t,x) = (1 + x*x) * (1 + t)

 29:     Note that since the solution is linear in time and quadratic in x,
 30:     the finite difference scheme actually computes the "exact" solution.

 32:     We use by default the backward Euler method.

 34:   ------------------------------------------------------------------------- */

 36: /*
 37:    Include "petscts.h" to use the PETSc timestepping routines. Note that
 38:    this file automatically includes "petscsys.h" and other lower-level
 39:    PETSc include files.

 41:    Include the "petscdmda.h" to allow us to use the distributed array data
 42:    structures to manage the parallel grid.
 43: */
 44: #include <petscts.h>
 45: #include <petscdm.h>
 46: #include <petscdmda.h>
 47: #include <petscdraw.h>

 49: /*
 50:    User-defined application context - contains data needed by the
 51:    application-provided callback routines.
 52: */
 53: typedef struct {
 54:   MPI_Comm  comm;           /* communicator */
 55:   DM        da;             /* distributed array data structure */
 56:   Vec       localwork;      /* local ghosted work vector */
 57:   Vec       u_local;        /* local ghosted approximate solution vector */
 58:   Vec       solution;       /* global exact solution vector */
 59:   PetscInt  m;              /* total number of grid points */
 60:   PetscReal h;              /* mesh width: h = 1/(m-1) */
 61:   PetscBool debug;          /* flag (1 indicates activation of debugging printouts) */
 62: } AppCtx;

 64: /*
 65:    User-defined routines, provided below.
 66: */
 67: extern PetscErrorCode InitialConditions(Vec,AppCtx*);
 68: extern PetscErrorCode RHSFunction(TS,PetscReal,Vec,Vec,void*);
 69: extern PetscErrorCode RHSJacobian(TS,PetscReal,Vec,Mat,Mat,void*);
 70: extern PetscErrorCode Monitor(TS,PetscInt,PetscReal,Vec,void*);
 71: extern PetscErrorCode ExactSolution(PetscReal,Vec,AppCtx*);

 75: int main(int argc,char **argv)
 76: {
 77:   AppCtx         appctx;                 /* user-defined application context */
 78:   TS             ts;                     /* timestepping context */
 79:   Mat            A;                      /* Jacobian matrix data structure */
 80:   Vec            u;                      /* approximate solution vector */
 81:   PetscInt       time_steps_max = 100;  /* default max timesteps */
 83:   PetscReal      dt;
 84:   PetscReal      time_total_max = 100.0; /* default max total time */
 85:   PetscBool      mymonitor      = PETSC_FALSE;
 86:   PetscReal      bounds[]       = {1.0, 3.3};

 88:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 89:      Initialize program and set problem parameters
 90:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 92:   PetscInitialize(&argc,&argv,(char*)0,help);
 93:   PetscViewerDrawSetBounds(PETSC_VIEWER_DRAW_(PETSC_COMM_WORLD),1,bounds);

 95:   appctx.comm = PETSC_COMM_WORLD;
 96:   appctx.m    = 60;

 98:   PetscOptionsGetInt(NULL,"-M",&appctx.m,NULL);
 99:   PetscOptionsHasName(NULL,"-debug",&appctx.debug);
100:   PetscOptionsHasName(NULL,"-mymonitor",&mymonitor);

102:   appctx.h    = 1.0/(appctx.m-1.0);

104:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
105:      Create vector data structures
106:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

108:   /*
109:      Create distributed array (DMDA) to manage parallel grid and vectors
110:      and to set up the ghost point communication pattern.  There are M
111:      total grid values spread equally among all the processors.
112:   */
113:   DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,appctx.m,1,1,NULL,&appctx.da);

115:   /*
116:      Extract global and local vectors from DMDA; we use these to store the
117:      approximate solution.  Then duplicate these for remaining vectors that
118:      have the same types.
119:   */
120:   DMCreateGlobalVector(appctx.da,&u);
121:   DMCreateLocalVector(appctx.da,&appctx.u_local);

123:   /*
124:      Create local work vector for use in evaluating right-hand-side function;
125:      create global work vector for storing exact solution.
126:   */
127:   VecDuplicate(appctx.u_local,&appctx.localwork);
128:   VecDuplicate(u,&appctx.solution);

130:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
131:      Create timestepping solver context; set callback routine for
132:      right-hand-side function evaluation.
133:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

135:   TSCreate(PETSC_COMM_WORLD,&ts);
136:   TSSetProblemType(ts,TS_NONLINEAR);
137:   TSSetRHSFunction(ts,NULL,RHSFunction,&appctx);

139:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
140:      Set optional user-defined monitoring routine
141:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

143:   if (mymonitor) {
144:     TSMonitorSet(ts,Monitor,&appctx,NULL);
145:   }

147:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
148:      For nonlinear problems, the user can provide a Jacobian evaluation
149:      routine (or use a finite differencing approximation).

151:      Create matrix data structure; set Jacobian evaluation routine.
152:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

154:   MatCreate(PETSC_COMM_WORLD,&A);
155:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,appctx.m,appctx.m);
156:   MatSetFromOptions(A);
157:   MatSetUp(A);
158:   TSSetRHSJacobian(ts,A,A,RHSJacobian,&appctx);

160:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
161:      Set solution vector and initial timestep
162:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

164:   dt   = appctx.h/2.0;
165:   TSSetInitialTimeStep(ts,0.0,dt);

167:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
168:      Customize timestepping solver:
169:        - Set the solution method to be the Backward Euler method.
170:        - Set timestepping duration info
171:      Then set runtime options, which can override these defaults.
172:      For example,
173:           -ts_max_steps <maxsteps> -ts_final_time <maxtime>
174:      to override the defaults set by TSSetDuration().
175:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

177:   TSSetType(ts,TSBEULER);
178:   TSSetDuration(ts,time_steps_max,time_total_max);
179:   TSSetFromOptions(ts);

181:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
182:      Solve the problem
183:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

185:   /*
186:      Evaluate initial conditions
187:   */
188:   InitialConditions(u,&appctx);

190:   /*
191:      Run the timestepping solver
192:   */
193:   TSSolve(ts,u);

195:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
196:      Free work space.  All PETSc objects should be destroyed when they
197:      are no longer needed.
198:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

200:   TSDestroy(&ts);
201:   VecDestroy(&u);
202:   MatDestroy(&A);
203:   DMDestroy(&appctx.da);
204:   VecDestroy(&appctx.localwork);
205:   VecDestroy(&appctx.solution);
206:   VecDestroy(&appctx.u_local);

208:   /*
209:      Always call PetscFinalize() before exiting a program.  This routine
210:        - finalizes the PETSc libraries as well as MPI
211:        - provides summary and diagnostic information if certain runtime
212:          options are chosen (e.g., -log_summary).
213:   */
214:   PetscFinalize();
215:   return 0;
216: }
217: /* --------------------------------------------------------------------- */
220: /*
221:    InitialConditions - Computes the solution at the initial time.

223:    Input Parameters:
224:    u - uninitialized solution vector (global)
225:    appctx - user-defined application context

227:    Output Parameter:
228:    u - vector with solution at initial time (global)
229: */
230: PetscErrorCode InitialConditions(Vec u,AppCtx *appctx)
231: {
232:   PetscScalar    *u_localptr,h = appctx->h,x;
233:   PetscInt       i,mybase,myend;

236:   /*
237:      Determine starting point of each processor's range of
238:      grid values.
239:   */
240:   VecGetOwnershipRange(u,&mybase,&myend);

242:   /*
243:     Get a pointer to vector data.
244:     - For default PETSc vectors, VecGetArray() returns a pointer to
245:       the data array.  Otherwise, the routine is implementation dependent.
246:     - You MUST call VecRestoreArray() when you no longer need access to
247:       the array.
248:     - Note that the Fortran interface to VecGetArray() differs from the
249:       C version.  See the users manual for details.
250:   */
251:   VecGetArray(u,&u_localptr);

253:   /*
254:      We initialize the solution array by simply writing the solution
255:      directly into the array locations.  Alternatively, we could use
256:      VecSetValues() or VecSetValuesLocal().
257:   */
258:   for (i=mybase; i<myend; i++) {
259:     x = h*(PetscReal)i; /* current location in global grid */
260:     u_localptr[i-mybase] = 1.0 + x*x;
261:   }

263:   /*
264:      Restore vector
265:   */
266:   VecRestoreArray(u,&u_localptr);

268:   /*
269:      Print debugging information if desired
270:   */
271:   if (appctx->debug) {
272:     PetscPrintf(appctx->comm,"initial guess vector\n");
273:     VecView(u,PETSC_VIEWER_STDOUT_WORLD);
274:   }

276:   return 0;
277: }
278: /* --------------------------------------------------------------------- */
281: /*
282:    ExactSolution - Computes the exact solution at a given time.

284:    Input Parameters:
285:    t - current time
286:    solution - vector in which exact solution will be computed
287:    appctx - user-defined application context

289:    Output Parameter:
290:    solution - vector with the newly computed exact solution
291: */
292: PetscErrorCode ExactSolution(PetscReal t,Vec solution,AppCtx *appctx)
293: {
294:   PetscScalar    *s_localptr,h = appctx->h,x;
295:   PetscInt       i,mybase,myend;

298:   /*
299:      Determine starting and ending points of each processor's
300:      range of grid values
301:   */
302:   VecGetOwnershipRange(solution,&mybase,&myend);

304:   /*
305:      Get a pointer to vector data.
306:   */
307:   VecGetArray(solution,&s_localptr);

309:   /*
310:      Simply write the solution directly into the array locations.
311:      Alternatively, we could use VecSetValues() or VecSetValuesLocal().
312:   */
313:   for (i=mybase; i<myend; i++) {
314:     x = h*(PetscReal)i;
315:     s_localptr[i-mybase] = (t + 1.0)*(1.0 + x*x);
316:   }

318:   /*
319:      Restore vector
320:   */
321:   VecRestoreArray(solution,&s_localptr);
322:   return 0;
323: }
324: /* --------------------------------------------------------------------- */
327: /*
328:    Monitor - User-provided routine to monitor the solution computed at
329:    each timestep.  This example plots the solution and computes the
330:    error in two different norms.

332:    Input Parameters:
333:    ts     - the timestep context
334:    step   - the count of the current step (with 0 meaning the
335:             initial condition)
336:    time   - the current time
337:    u      - the solution at this timestep
338:    ctx    - the user-provided context for this monitoring routine.
339:             In this case we use the application context which contains
340:             information about the problem size, workspace and the exact
341:             solution.
342: */
343: PetscErrorCode Monitor(TS ts,PetscInt step,PetscReal time,Vec u,void *ctx)
344: {
345:   AppCtx         *appctx = (AppCtx*) ctx;   /* user-defined application context */
347:   PetscReal      en2,en2s,enmax;
348:   PetscDraw      draw;

350:   /*
351:      We use the default X windows viewer
352:              PETSC_VIEWER_DRAW_(appctx->comm)
353:      that is associated with the current communicator. This saves
354:      the effort of calling PetscViewerDrawOpen() to create the window.
355:      Note that if we wished to plot several items in separate windows we
356:      would create each viewer with PetscViewerDrawOpen() and store them in
357:      the application context, appctx.

359:      PetscReal buffering makes graphics look better.
360:   */
361:   PetscViewerDrawGetDraw(PETSC_VIEWER_DRAW_(appctx->comm),0,&draw);
362:   PetscDrawSetDoubleBuffer(draw);
363:   VecView(u,PETSC_VIEWER_DRAW_(appctx->comm));

365:   /*
366:      Compute the exact solution at this timestep
367:   */
368:   ExactSolution(time,appctx->solution,appctx);

370:   /*
371:      Print debugging information if desired
372:   */
373:   if (appctx->debug) {
374:     PetscPrintf(appctx->comm,"Computed solution vector\n");
375:     VecView(u,PETSC_VIEWER_STDOUT_WORLD);
376:     PetscPrintf(appctx->comm,"Exact solution vector\n");
377:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_WORLD);
378:   }

380:   /*
381:      Compute the 2-norm and max-norm of the error
382:   */
383:   VecAXPY(appctx->solution,-1.0,u);
384:   VecNorm(appctx->solution,NORM_2,&en2);
385:   en2s = PetscSqrtReal(appctx->h)*en2;  /* scale the 2-norm by the grid spacing */
386:   VecNorm(appctx->solution,NORM_MAX,&enmax);

388:   /*
389:      PetscPrintf() causes only the first processor in this
390:      communicator to print the timestep information.
391:   */
392:   PetscPrintf(appctx->comm,"Timestep %D: time = %g 2-norm error = %g  max norm error = %g\n",step,(double)time,(double)en2s,(double)enmax);

394:   /*
395:      Print debugging information if desired
396:   */
397:   if (appctx->debug) {
398:     PetscPrintf(appctx->comm,"Error vector\n");
399:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_WORLD);
400:   }
401:   return 0;
402: }
403: /* --------------------------------------------------------------------- */
406: /*
407:    RHSFunction - User-provided routine that evalues the right-hand-side
408:    function of the ODE.  This routine is set in the main program by
409:    calling TSSetRHSFunction().  We compute:
410:           global_out = F(global_in)

412:    Input Parameters:
413:    ts         - timesteping context
414:    t          - current time
415:    global_in  - vector containing the current iterate
416:    ctx        - (optional) user-provided context for function evaluation.
417:                 In this case we use the appctx defined above.

419:    Output Parameter:
420:    global_out - vector containing the newly evaluated function
421: */
422: PetscErrorCode RHSFunction(TS ts,PetscReal t,Vec global_in,Vec global_out,void *ctx)
423: {
424:   AppCtx            *appctx   = (AppCtx*) ctx;     /* user-defined application context */
425:   DM                da        = appctx->da;        /* distributed array */
426:   Vec               local_in  = appctx->u_local;   /* local ghosted input vector */
427:   Vec               localwork = appctx->localwork; /* local ghosted work vector */
428:   PetscErrorCode    ierr;
429:   PetscInt          i,localsize;
430:   PetscMPIInt       rank,size;
431:   PetscScalar       *copyptr,sc;
432:   const PetscScalar *localptr;

434:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
435:      Get ready for local function computations
436:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
437:   /*
438:      Scatter ghost points to local vector, using the 2-step process
439:         DMGlobalToLocalBegin(), DMGlobalToLocalEnd().
440:      By placing code between these two statements, computations can be
441:      done while messages are in transition.
442:   */
443:   DMGlobalToLocalBegin(da,global_in,INSERT_VALUES,local_in);
444:   DMGlobalToLocalEnd(da,global_in,INSERT_VALUES,local_in);

446:   /*
447:       Access directly the values in our local INPUT work array
448:   */
449:   VecGetArrayRead(local_in,&localptr);

451:   /*
452:       Access directly the values in our local OUTPUT work array
453:   */
454:   VecGetArray(localwork,&copyptr);

456:   sc = 1.0/(appctx->h*appctx->h*2.0*(1.0+t)*(1.0+t));

458:   /*
459:       Evaluate our function on the nodes owned by this processor
460:   */
461:   VecGetLocalSize(local_in,&localsize);

463:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
464:      Compute entries for the locally owned part
465:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

467:   /*
468:      Handle boundary conditions: This is done by using the boundary condition
469:         u(t,boundary) = g(t,boundary)
470:      for some function g. Now take the derivative with respect to t to obtain
471:         u_{t}(t,boundary) = g_{t}(t,boundary)

473:      In our case, u(t,0) = t + 1, so that u_{t}(t,0) = 1
474:              and  u(t,1) = 2t+ 2, so that u_{t}(t,1) = 2
475:   */
476:   MPI_Comm_rank(appctx->comm,&rank);
477:   MPI_Comm_size(appctx->comm,&size);
478:   if (!rank)          copyptr[0]           = 1.0;
479:   if (rank == size-1) copyptr[localsize-1] = 2.0;

481:   /*
482:      Handle the interior nodes where the PDE is replace by finite
483:      difference operators.
484:   */
485:   for (i=1; i<localsize-1; i++) copyptr[i] =  localptr[i] * sc * (localptr[i+1] + localptr[i-1] - 2.0*localptr[i]);

487:   /*
488:      Restore vectors
489:   */
490:   VecRestoreArrayRead(local_in,&localptr);
491:   VecRestoreArray(localwork,&copyptr);

493:   /*
494:      Insert values from the local OUTPUT vector into the global
495:      output vector
496:   */
497:   DMLocalToGlobalBegin(da,localwork,INSERT_VALUES,global_out);
498:   DMLocalToGlobalEnd(da,localwork,INSERT_VALUES,global_out);

500:   /* Print debugging information if desired */
501:   if (appctx->debug) {
502:     PetscPrintf(appctx->comm,"RHS function vector\n");
503:     VecView(global_out,PETSC_VIEWER_STDOUT_WORLD);
504:   }

506:   return 0;
507: }
508: /* --------------------------------------------------------------------- */
511: /*
512:    RHSJacobian - User-provided routine to compute the Jacobian of
513:    the nonlinear right-hand-side function of the ODE.

515:    Input Parameters:
516:    ts - the TS context
517:    t - current time
518:    global_in - global input vector
519:    dummy - optional user-defined context, as set by TSetRHSJacobian()

521:    Output Parameters:
522:    AA - Jacobian matrix
523:    BB - optionally different preconditioning matrix
524:    str - flag indicating matrix structure

526:   Notes:
527:   RHSJacobian computes entries for the locally owned part of the Jacobian.
528:    - Currently, all PETSc parallel matrix formats are partitioned by
529:      contiguous chunks of rows across the processors.
530:    - Each processor needs to insert only elements that it owns
531:      locally (but any non-local elements will be sent to the
532:      appropriate processor during matrix assembly).
533:    - Always specify global row and columns of matrix entries when
534:      using MatSetValues().
535:    - Here, we set all entries for a particular row at once.
536:    - Note that MatSetValues() uses 0-based row and column numbers
537:      in Fortran as well as in C.
538: */
539: PetscErrorCode RHSJacobian(TS ts,PetscReal t,Vec global_in,Mat AA,Mat BB,void *ctx)
540: {
541:   AppCtx            *appctx  = (AppCtx*)ctx;    /* user-defined application context */
542:   Vec               local_in = appctx->u_local;   /* local ghosted input vector */
543:   DM                da       = appctx->da;        /* distributed array */
544:   PetscScalar       v[3],sc;
545:   const PetscScalar *localptr;
546:   PetscErrorCode    ierr;
547:   PetscInt          i,mstart,mend,mstarts,mends,idx[3],is;

549:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
550:      Get ready for local Jacobian computations
551:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
552:   /*
553:      Scatter ghost points to local vector, using the 2-step process
554:         DMGlobalToLocalBegin(), DMGlobalToLocalEnd().
555:      By placing code between these two statements, computations can be
556:      done while messages are in transition.
557:   */
558:   DMGlobalToLocalBegin(da,global_in,INSERT_VALUES,local_in);
559:   DMGlobalToLocalEnd(da,global_in,INSERT_VALUES,local_in);

561:   /*
562:      Get pointer to vector data
563:   */
564:   VecGetArrayRead(local_in,&localptr);

566:   /*
567:      Get starting and ending locally owned rows of the matrix
568:   */
569:   MatGetOwnershipRange(BB,&mstarts,&mends);
570:   mstart = mstarts; mend = mends;

572:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
573:      Compute entries for the locally owned part of the Jacobian.
574:       - Currently, all PETSc parallel matrix formats are partitioned by
575:         contiguous chunks of rows across the processors.
576:       - Each processor needs to insert only elements that it owns
577:         locally (but any non-local elements will be sent to the
578:         appropriate processor during matrix assembly).
579:       - Here, we set all entries for a particular row at once.
580:       - We can set matrix entries either using either
581:         MatSetValuesLocal() or MatSetValues().
582:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

584:   /*
585:      Set matrix rows corresponding to boundary data
586:   */
587:   if (mstart == 0) {
588:     v[0] = 0.0;
589:     MatSetValues(BB,1,&mstart,1,&mstart,v,INSERT_VALUES);
590:     mstart++;
591:   }
592:   if (mend == appctx->m) {
593:     mend--;
594:     v[0] = 0.0;
595:     MatSetValues(BB,1,&mend,1,&mend,v,INSERT_VALUES);
596:   }

598:   /*
599:      Set matrix rows corresponding to interior data.  We construct the
600:      matrix one row at a time.
601:   */
602:   sc = 1.0/(appctx->h*appctx->h*2.0*(1.0+t)*(1.0+t));
603:   for (i=mstart; i<mend; i++) {
604:     idx[0] = i-1; idx[1] = i; idx[2] = i+1;
605:     is     = i - mstart + 1;
606:     v[0]   = sc*localptr[is];
607:     v[1]   = sc*(localptr[is+1] + localptr[is-1] - 4.0*localptr[is]);
608:     v[2]   = sc*localptr[is];
609:     MatSetValues(BB,1,&i,3,idx,v,INSERT_VALUES);
610:   }

612:   /*
613:      Restore vector
614:   */
615:   VecRestoreArrayRead(local_in,&localptr);

617:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
618:      Complete the matrix assembly process and set some options
619:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
620:   /*
621:      Assemble matrix, using the 2-step process:
622:        MatAssemblyBegin(), MatAssemblyEnd()
623:      Computations can be done while messages are in transition
624:      by placing code between these two statements.
625:   */
626:   MatAssemblyBegin(BB,MAT_FINAL_ASSEMBLY);
627:   MatAssemblyEnd(BB,MAT_FINAL_ASSEMBLY);
628:   if (BB != AA) {
629:     MatAssemblyBegin(AA,MAT_FINAL_ASSEMBLY);
630:     MatAssemblyEnd(AA,MAT_FINAL_ASSEMBLY);
631:   }

633:   /*
634:      Set and option to indicate that we will never add a new nonzero location
635:      to the matrix. If we do, it will generate an error.
636:   */
637:   MatSetOption(BB,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);

639:   return 0;
640: }