Actual source code: ex3.c


  2: static char help[] ="Solves a simple time-dependent linear PDE (the heat equation).\n\
  3: Input parameters include:\n\
  4:   -m <points>, where <points> = number of grid points\n\
  5:   -time_dependent_rhs : Treat the problem as having a time-dependent right-hand side\n\
  6:   -use_ifunc          : Use IFunction/IJacobian interface\n\
  7:   -debug              : Activate debugging printouts\n\
  8:   -nox                : Deactivate x-window graphics\n\n";

 10: /*
 11:    Concepts: TS^time-dependent linear problems
 12:    Concepts: TS^heat equation
 13:    Concepts: TS^diffusion equation
 14:    Processors: 1
 15: */

 17: /* ------------------------------------------------------------------------

 19:    This program solves the one-dimensional heat equation (also called the
 20:    diffusion equation),
 21:        u_t = u_xx,
 22:    on the domain 0 <= x <= 1, with the boundary conditions
 23:        u(t,0) = 0, u(t,1) = 0,
 24:    and the initial condition
 25:        u(0,x) = sin(6*pi*x) + 3*sin(2*pi*x).
 26:    This is a linear, second-order, parabolic equation.

 28:    We discretize the right-hand side using finite differences with
 29:    uniform grid spacing h:
 30:        u_xx = (u_{i+1} - 2u_{i} + u_{i-1})/(h^2)
 31:    We then demonstrate time evolution using the various TS methods by
 32:    running the program via
 33:        ex3 -ts_type <timestepping solver>

 35:    We compare the approximate solution with the exact solution, given by
 36:        u_exact(x,t) = exp(-36*pi*pi*t) * sin(6*pi*x) +
 37:                       3*exp(-4*pi*pi*t) * sin(2*pi*x)

 39:    Notes:
 40:    This code demonstrates the TS solver interface to two variants of
 41:    linear problems, u_t = f(u,t), namely
 42:      - time-dependent f:   f(u,t) is a function of t
 43:      - time-independent f: f(u,t) is simply f(u)

 45:     The parallel version of this code is ts/tutorials/ex4.c

 47:   ------------------------------------------------------------------------- */

 49: /*
 50:    Include "petscts.h" so that we can use TS solvers.  Note that this file
 51:    automatically includes:
 52:      petscsys.h       - base PETSc routines   petscvec.h  - vectors
 53:      petscmat.h  - matrices
 54:      petscis.h     - index sets            petscksp.h  - Krylov subspace methods
 55:      petscviewer.h - viewers               petscpc.h   - preconditioners
 56:      petscksp.h   - linear solvers        petscsnes.h - nonlinear solvers
 57: */

 59: #include <petscts.h>
 60: #include <petscdraw.h>

 62: /*
 63:    User-defined application context - contains data needed by the
 64:    application-provided call-back routines.
 65: */
 66: typedef struct {
 67:   Vec         solution;          /* global exact solution vector */
 68:   PetscInt    m;                 /* total number of grid points */
 69:   PetscReal   h;                 /* mesh width h = 1/(m-1) */
 70:   PetscBool   debug;             /* flag (1 indicates activation of debugging printouts) */
 71:   PetscViewer viewer1,viewer2;   /* viewers for the solution and error */
 72:   PetscReal   norm_2,norm_max;   /* error norms */
 73:   Mat         A;                 /* RHS mat, used with IFunction interface */
 74:   PetscReal   oshift;            /* old shift applied, prevent to recompute the IJacobian */
 75: } AppCtx;

 77: /*
 78:    User-defined routines
 79: */
 80: extern PetscErrorCode InitialConditions(Vec,AppCtx*);
 81: extern PetscErrorCode RHSMatrixHeat(TS,PetscReal,Vec,Mat,Mat,void*);
 82: extern PetscErrorCode IFunctionHeat(TS,PetscReal,Vec,Vec,Vec,void*);
 83: extern PetscErrorCode IJacobianHeat(TS,PetscReal,Vec,Vec,PetscReal,Mat,Mat,void*);
 84: extern PetscErrorCode Monitor(TS,PetscInt,PetscReal,Vec,void*);
 85: extern PetscErrorCode ExactSolution(PetscReal,Vec,AppCtx*);

 87: int main(int argc,char **argv)
 88: {
 89:   AppCtx         appctx;                 /* user-defined application context */
 90:   TS             ts;                     /* timestepping context */
 91:   Mat            A;                      /* matrix data structure */
 92:   Vec            u;                      /* approximate solution vector */
 93:   PetscReal      time_total_max = 100.0; /* default max total time */
 94:   PetscInt       time_steps_max = 100;   /* default max timesteps */
 95:   PetscDraw      draw;                   /* drawing context */
 96:   PetscInt       steps,m;
 97:   PetscMPIInt    size;
 98:   PetscReal      dt;
 99:   PetscBool      flg,flg_string;

101:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
102:      Initialize program and set problem parameters
103:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

105:   PetscInitialize(&argc,&argv,(char*)0,help);
106:   MPI_Comm_size(PETSC_COMM_WORLD,&size);

109:   m    = 60;
110:   PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);
111:   PetscOptionsHasName(NULL,NULL,"-debug",&appctx.debug);
112:   flg_string = PETSC_FALSE;
113:   PetscOptionsGetBool(NULL,NULL,"-test_string_viewer",&flg_string,NULL);

115:   appctx.m        = m;
116:   appctx.h        = 1.0/(m-1.0);
117:   appctx.norm_2   = 0.0;
118:   appctx.norm_max = 0.0;

120:   PetscPrintf(PETSC_COMM_SELF,"Solving a linear TS problem on 1 processor\n");

122:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
123:      Create vector data structures
124:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

126:   /*
127:      Create vector data structures for approximate and exact solutions
128:   */
129:   VecCreateSeq(PETSC_COMM_SELF,m,&u);
130:   VecDuplicate(u,&appctx.solution);

132:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
133:      Set up displays to show graphs of the solution and error
134:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

136:   PetscViewerDrawOpen(PETSC_COMM_SELF,0,"",80,380,400,160,&appctx.viewer1);
137:   PetscViewerDrawGetDraw(appctx.viewer1,0,&draw);
138:   PetscDrawSetDoubleBuffer(draw);
139:   PetscViewerDrawOpen(PETSC_COMM_SELF,0,"",80,0,400,160,&appctx.viewer2);
140:   PetscViewerDrawGetDraw(appctx.viewer2,0,&draw);
141:   PetscDrawSetDoubleBuffer(draw);

143:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
144:      Create timestepping solver context
145:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

147:   TSCreate(PETSC_COMM_SELF,&ts);
148:   TSSetProblemType(ts,TS_LINEAR);

150:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
151:      Set optional user-defined monitoring routine
152:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

154:   if (!flg_string) {
155:     TSMonitorSet(ts,Monitor,&appctx,NULL);
156:   }

158:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

160:      Create matrix data structure; set matrix evaluation routine.
161:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

163:   MatCreate(PETSC_COMM_SELF,&A);
164:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,m);
165:   MatSetFromOptions(A);
166:   MatSetUp(A);

168:   flg  = PETSC_FALSE;
169:   PetscOptionsGetBool(NULL,NULL,"-use_ifunc",&flg,NULL);
170:   if (!flg) {
171:     appctx.A = NULL;
172:     PetscOptionsGetBool(NULL,NULL,"-time_dependent_rhs",&flg,NULL);
173:     if (flg) {
174:       /*
175:          For linear problems with a time-dependent f(u,t) in the equation
176:          u_t = f(u,t), the user provides the discretized right-hand-side
177:          as a time-dependent matrix.
178:       */
179:       TSSetRHSFunction(ts,NULL,TSComputeRHSFunctionLinear,&appctx);
180:       TSSetRHSJacobian(ts,A,A,RHSMatrixHeat,&appctx);
181:     } else {
182:       /*
183:          For linear problems with a time-independent f(u) in the equation
184:          u_t = f(u), the user provides the discretized right-hand-side
185:          as a matrix only once, and then sets the special Jacobian evaluation
186:          routine TSComputeRHSJacobianConstant() which will NOT recompute the Jacobian.
187:       */
188:       RHSMatrixHeat(ts,0.0,u,A,A,&appctx);
189:       TSSetRHSFunction(ts,NULL,TSComputeRHSFunctionLinear,&appctx);
190:       TSSetRHSJacobian(ts,A,A,TSComputeRHSJacobianConstant,&appctx);
191:     }
192:   } else {
193:     Mat J;

195:     RHSMatrixHeat(ts,0.0,u,A,A,&appctx);
196:     MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&J);
197:     TSSetIFunction(ts,NULL,IFunctionHeat,&appctx);
198:     TSSetIJacobian(ts,J,J,IJacobianHeat,&appctx);
199:     MatDestroy(&J);

201:     PetscObjectReference((PetscObject)A);
202:     appctx.A = A;
203:     appctx.oshift = PETSC_MIN_REAL;
204:   }
205:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
206:      Set solution vector and initial timestep
207:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

209:   dt   = appctx.h*appctx.h/2.0;
210:   TSSetTimeStep(ts,dt);

212:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
213:      Customize timestepping solver:
214:        - Set the solution method to be the Backward Euler method.
215:        - Set timestepping duration info
216:      Then set runtime options, which can override these defaults.
217:      For example,
218:           -ts_max_steps <maxsteps> -ts_max_time <maxtime>
219:      to override the defaults set by TSSetMaxSteps()/TSSetMaxTime().
220:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

222:   TSSetMaxSteps(ts,time_steps_max);
223:   TSSetMaxTime(ts,time_total_max);
224:   TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);
225:   TSSetFromOptions(ts);

227:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
228:      Solve the problem
229:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

231:   /*
232:      Evaluate initial conditions
233:   */
234:   InitialConditions(u,&appctx);

236:   /*
237:      Run the timestepping solver
238:   */
239:   TSSolve(ts,u);
240:   TSGetStepNumber(ts,&steps);

242:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
243:      View timestepping solver info
244:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

246:   PetscPrintf(PETSC_COMM_SELF,"avg. error (2 norm) = %g, avg. error (max norm) = %g\n",(double)(appctx.norm_2/steps),(double)(appctx.norm_max/steps));
247:   if (!flg_string) {
248:     TSView(ts,PETSC_VIEWER_STDOUT_SELF);
249:   } else {
250:     PetscViewer stringviewer;
251:     char        string[512];
252:     const char  *outstring;

254:     PetscViewerStringOpen(PETSC_COMM_WORLD,string,sizeof(string),&stringviewer);
255:     TSView(ts,stringviewer);
256:     PetscViewerStringGetStringRead(stringviewer,&outstring,NULL);
258:     PetscPrintf(PETSC_COMM_WORLD,"Output from string viewer:%s\n",outstring);
259:     PetscViewerDestroy(&stringviewer);
260:   }

262:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
263:      Free work space.  All PETSc objects should be destroyed when they
264:      are no longer needed.
265:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

267:   TSDestroy(&ts);
268:   MatDestroy(&A);
269:   VecDestroy(&u);
270:   PetscViewerDestroy(&appctx.viewer1);
271:   PetscViewerDestroy(&appctx.viewer2);
272:   VecDestroy(&appctx.solution);
273:   MatDestroy(&appctx.A);

275:   /*
276:      Always call PetscFinalize() before exiting a program.  This routine
277:        - finalizes the PETSc libraries as well as MPI
278:        - provides summary and diagnostic information if certain runtime
279:          options are chosen (e.g., -log_view).
280:   */
281:   PetscFinalize();
282:   return 0;
283: }
284: /* --------------------------------------------------------------------- */
285: /*
286:    InitialConditions - Computes the solution at the initial time.

288:    Input Parameter:
289:    u - uninitialized solution vector (global)
290:    appctx - user-defined application context

292:    Output Parameter:
293:    u - vector with solution at initial time (global)
294: */
295: PetscErrorCode InitialConditions(Vec u,AppCtx *appctx)
296: {
297:   PetscScalar    *u_localptr,h = appctx->h;
298:   PetscInt       i;

300:   /*
301:     Get a pointer to vector data.
302:     - For default PETSc vectors, VecGetArray() returns a pointer to
303:       the data array.  Otherwise, the routine is implementation dependent.
304:     - You MUST call VecRestoreArray() when you no longer need access to
305:       the array.
306:     - Note that the Fortran interface to VecGetArray() differs from the
307:       C version.  See the users manual for details.
308:   */
309:   VecGetArrayWrite(u,&u_localptr);

311:   /*
312:      We initialize the solution array by simply writing the solution
313:      directly into the array locations.  Alternatively, we could use
314:      VecSetValues() or VecSetValuesLocal().
315:   */
316:   for (i=0; i<appctx->m; i++) u_localptr[i] = PetscSinScalar(PETSC_PI*i*6.*h) + 3.*PetscSinScalar(PETSC_PI*i*2.*h);

318:   /*
319:      Restore vector
320:   */
321:   VecRestoreArrayWrite(u,&u_localptr);

323:   /*
324:      Print debugging information if desired
325:   */
326:   if (appctx->debug) {
327:     PetscPrintf(PETSC_COMM_WORLD,"Initial guess vector\n");
328:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
329:   }

331:   return 0;
332: }
333: /* --------------------------------------------------------------------- */
334: /*
335:    ExactSolution - Computes the exact solution at a given time.

337:    Input Parameters:
338:    t - current time
339:    solution - vector in which exact solution will be computed
340:    appctx - user-defined application context

342:    Output Parameter:
343:    solution - vector with the newly computed exact solution
344: */
345: PetscErrorCode ExactSolution(PetscReal t,Vec solution,AppCtx *appctx)
346: {
347:   PetscScalar    *s_localptr,h = appctx->h,ex1,ex2,sc1,sc2,tc = t;
348:   PetscInt       i;

350:   /*
351:      Get a pointer to vector data.
352:   */
353:   VecGetArrayWrite(solution,&s_localptr);

355:   /*
356:      Simply write the solution directly into the array locations.
357:      Alternatively, we culd use VecSetValues() or VecSetValuesLocal().
358:   */
359:   ex1 = PetscExpScalar(-36.*PETSC_PI*PETSC_PI*tc);
360:   ex2 = PetscExpScalar(-4.*PETSC_PI*PETSC_PI*tc);
361:   sc1 = PETSC_PI*6.*h;                 sc2 = PETSC_PI*2.*h;
362:   for (i=0; i<appctx->m; i++) s_localptr[i] = PetscSinScalar(sc1*(PetscReal)i)*ex1 + 3.*PetscSinScalar(sc2*(PetscReal)i)*ex2;

364:   /*
365:      Restore vector
366:   */
367:   VecRestoreArrayWrite(solution,&s_localptr);
368:   return 0;
369: }
370: /* --------------------------------------------------------------------- */
371: /*
372:    Monitor - User-provided routine to monitor the solution computed at
373:    each timestep.  This example plots the solution and computes the
374:    error in two different norms.

376:    This example also demonstrates changing the timestep via TSSetTimeStep().

378:    Input Parameters:
379:    ts     - the timestep context
380:    step   - the count of the current step (with 0 meaning the
381:              initial condition)
382:    time   - the current time
383:    u      - the solution at this timestep
384:    ctx    - the user-provided context for this monitoring routine.
385:             In this case we use the application context which contains
386:             information about the problem size, workspace and the exact
387:             solution.
388: */
389: PetscErrorCode Monitor(TS ts,PetscInt step,PetscReal time,Vec u,void *ctx)
390: {
391:   AppCtx         *appctx = (AppCtx*) ctx;   /* user-defined application context */
392:   PetscReal      norm_2,norm_max,dt,dttol;

394:   /*
395:      View a graph of the current iterate
396:   */
397:   VecView(u,appctx->viewer2);

399:   /*
400:      Compute the exact solution
401:   */
402:   ExactSolution(time,appctx->solution,appctx);

404:   /*
405:      Print debugging information if desired
406:   */
407:   if (appctx->debug) {
408:     PetscPrintf(PETSC_COMM_SELF,"Computed solution vector\n");
409:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
410:     PetscPrintf(PETSC_COMM_SELF,"Exact solution vector\n");
411:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
412:   }

414:   /*
415:      Compute the 2-norm and max-norm of the error
416:   */
417:   VecAXPY(appctx->solution,-1.0,u);
418:   VecNorm(appctx->solution,NORM_2,&norm_2);
419:   norm_2 = PetscSqrtReal(appctx->h)*norm_2;
420:   VecNorm(appctx->solution,NORM_MAX,&norm_max);

422:   TSGetTimeStep(ts,&dt);
423:   PetscPrintf(PETSC_COMM_WORLD,"Timestep %3D: step size = %g, time = %g, 2-norm error = %g, max norm error = %g\n",step,(double)dt,(double)time,(double)norm_2,(double)norm_max);

425:   appctx->norm_2   += norm_2;
426:   appctx->norm_max += norm_max;

428:   dttol = .0001;
429:   PetscOptionsGetReal(NULL,NULL,"-dttol",&dttol,NULL);
430:   if (dt < dttol) {
431:     dt  *= .999;
432:     TSSetTimeStep(ts,dt);
433:   }

435:   /*
436:      View a graph of the error
437:   */
438:   VecView(appctx->solution,appctx->viewer1);

440:   /*
441:      Print debugging information if desired
442:   */
443:   if (appctx->debug) {
444:     PetscPrintf(PETSC_COMM_SELF,"Error vector\n");
445:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
446:   }

448:   return 0;
449: }
450: /* --------------------------------------------------------------------- */
451: /*
452:    RHSMatrixHeat - User-provided routine to compute the right-hand-side
453:    matrix for the heat equation.

455:    Input Parameters:
456:    ts - the TS context
457:    t - current time
458:    global_in - global input vector
459:    dummy - optional user-defined context, as set by TSetRHSJacobian()

461:    Output Parameters:
462:    AA - Jacobian matrix
463:    BB - optionally different preconditioning matrix
464:    str - flag indicating matrix structure

466:    Notes:
467:    Recall that MatSetValues() uses 0-based row and column numbers
468:    in Fortran as well as in C.
469: */
470: PetscErrorCode RHSMatrixHeat(TS ts,PetscReal t,Vec X,Mat AA,Mat BB,void *ctx)
471: {
472:   Mat            A       = AA;                /* Jacobian matrix */
473:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */
474:   PetscInt       mstart  = 0;
475:   PetscInt       mend    = appctx->m;
476:   PetscInt       i,idx[3];
477:   PetscScalar    v[3],stwo = -2./(appctx->h*appctx->h),sone = -.5*stwo;

479:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
480:      Compute entries for the locally owned part of the matrix
481:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
482:   /*
483:      Set matrix rows corresponding to boundary data
484:   */

486:   mstart = 0;
487:   v[0]   = 1.0;
488:   MatSetValues(A,1,&mstart,1,&mstart,v,INSERT_VALUES);
489:   mstart++;

491:   mend--;
492:   v[0] = 1.0;
493:   MatSetValues(A,1,&mend,1,&mend,v,INSERT_VALUES);

495:   /*
496:      Set matrix rows corresponding to interior data.  We construct the
497:      matrix one row at a time.
498:   */
499:   v[0] = sone; v[1] = stwo; v[2] = sone;
500:   for (i=mstart; i<mend; i++) {
501:     idx[0] = i-1; idx[1] = i; idx[2] = i+1;
502:     MatSetValues(A,1,&i,3,idx,v,INSERT_VALUES);
503:   }

505:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
506:      Complete the matrix assembly process and set some options
507:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
508:   /*
509:      Assemble matrix, using the 2-step process:
510:        MatAssemblyBegin(), MatAssemblyEnd()
511:      Computations can be done while messages are in transition
512:      by placing code between these two statements.
513:   */
514:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
515:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

517:   /*
518:      Set and option to indicate that we will never add a new nonzero location
519:      to the matrix. If we do, it will generate an error.
520:   */
521:   MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);

523:   return 0;
524: }

526: PetscErrorCode IFunctionHeat(TS ts,PetscReal t,Vec X,Vec Xdot,Vec r,void *ctx)
527: {
528:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */

530:   MatMult(appctx->A,X,r);
531:   VecAYPX(r,-1.0,Xdot);
532:   return 0;
533: }

535: PetscErrorCode IJacobianHeat(TS ts,PetscReal t,Vec X,Vec Xdot,PetscReal s,Mat A,Mat B,void *ctx)
536: {
537:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */

539:   if (appctx->oshift == s) return 0;
540:   MatCopy(appctx->A,A,SAME_NONZERO_PATTERN);
541:   MatScale(A,-1);
542:   MatShift(A,s);
543:   MatCopy(A,B,SAME_NONZERO_PATTERN);
544:   appctx->oshift = s;
545:   return 0;
546: }

548: /*TEST

550:     test:
551:       args: -nox -ts_type ssp -ts_dt 0.0005

553:     test:
554:       suffix: 2
555:       args: -nox -ts_type ssp -ts_dt 0.0005 -time_dependent_rhs 1

557:     test:
558:       suffix: 3
559:       args:  -nox -ts_type rosw -ts_max_steps 3 -ksp_converged_reason
560:       filter: sed "s/ATOL/RTOL/g"
561:       requires: !single

563:     test:
564:       suffix: 4
565:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason
566:       filter: sed "s/ATOL/RTOL/g"

568:     test:
569:       suffix: 5
570:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason -time_dependent_rhs
571:       filter: sed "s/ATOL/RTOL/g"

573:     test:
574:       requires: !single
575:       suffix: pod_guess
576:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type pod -pc_type none -ksp_converged_reason

578:     test:
579:       requires: !single
580:       suffix: pod_guess_Ainner
581:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type pod -ksp_guess_pod_Ainner -pc_type none -ksp_converged_reason

583:     test:
584:       requires: !single
585:       suffix: fischer_guess
586:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -pc_type none -ksp_converged_reason

588:     test:
589:       requires: !single
590:       suffix: fischer_guess_2
591:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -ksp_guess_fischer_model 2,10 -pc_type none -ksp_converged_reason

593:     test:
594:       requires: !single
595:       suffix: fischer_guess_3
596:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -ksp_guess_fischer_model 3,10 -pc_type none -ksp_converged_reason

598:     test:
599:       requires: !single
600:       suffix: stringview
601:       args: -nox -ts_type rosw -test_string_viewer

603:     test:
604:       requires: !single
605:       suffix: stringview_euler
606:       args: -nox -ts_type euler -test_string_viewer

608: TEST*/