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

 12:    This program solves the one-dimensional heat equation (also called the
 13:    diffusion equation),
 14:        u_t = u_xx,
 15:    on the domain 0 <= x <= 1, with the boundary conditions
 16:        u(t,0) = 0, u(t,1) = 0,
 17:    and the initial condition
 18:        u(0,x) = sin(6*pi*x) + 3*sin(2*pi*x).
 19:    This is a linear, second-order, parabolic equation.

 21:    We discretize the right-hand side using finite differences with
 22:    uniform grid spacing h:
 23:        u_xx = (u_{i+1} - 2u_{i} + u_{i-1})/(h^2)
 24:    We then demonstrate time evolution using the various TS methods by
 25:    running the program via
 26:        ex3 -ts_type <timestepping solver>

 28:    We compare the approximate solution with the exact solution, given by
 29:        u_exact(x,t) = exp(-36*pi*pi*t) * sin(6*pi*x) +
 30:                       3*exp(-4*pi*pi*t) * sin(2*pi*x)

 32:    Notes:
 33:    This code demonstrates the TS solver interface to two variants of
 34:    linear problems, u_t = f(u,t), namely
 35:      - time-dependent f:   f(u,t) is a function of t
 36:      - time-independent f: f(u,t) is simply f(u)

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

 40:   ------------------------------------------------------------------------- */

 42: /*
 43:    Include "petscts.h" so that we can use TS solvers.  Note that this file
 44:    automatically includes:
 45:      petscsys.h       - base PETSc routines   petscvec.h  - vectors
 46:      petscmat.h  - matrices
 47:      petscis.h     - index sets            petscksp.h  - Krylov subspace methods
 48:      petscviewer.h - viewers               petscpc.h   - preconditioners
 49:      petscksp.h   - linear solvers        petscsnes.h - nonlinear solvers
 50: */

 52: #include <petscts.h>
 53: #include <petscdraw.h>

 55: /*
 56:    User-defined application context - contains data needed by the
 57:    application-provided call-back routines.
 58: */
 59: typedef struct {
 60:   Vec         solution;          /* global exact solution vector */
 61:   PetscInt    m;                 /* total number of grid points */
 62:   PetscReal   h;                 /* mesh width h = 1/(m-1) */
 63:   PetscBool   debug;             /* flag (1 indicates activation of debugging printouts) */
 64:   PetscViewer viewer1,viewer2;   /* viewers for the solution and error */
 65:   PetscReal   norm_2,norm_max;   /* error norms */
 66:   Mat         A;                 /* RHS mat, used with IFunction interface */
 67:   PetscReal   oshift;            /* old shift applied, prevent to recompute the IJacobian */
 68: } AppCtx;

 70: /*
 71:    User-defined routines
 72: */
 73: extern PetscErrorCode InitialConditions(Vec,AppCtx*);
 74: extern PetscErrorCode RHSMatrixHeat(TS,PetscReal,Vec,Mat,Mat,void*);
 75: extern PetscErrorCode IFunctionHeat(TS,PetscReal,Vec,Vec,Vec,void*);
 76: extern PetscErrorCode IJacobianHeat(TS,PetscReal,Vec,Vec,PetscReal,Mat,Mat,void*);
 77: extern PetscErrorCode Monitor(TS,PetscInt,PetscReal,Vec,void*);
 78: extern PetscErrorCode ExactSolution(PetscReal,Vec,AppCtx*);

 80: int main(int argc,char **argv)
 81: {
 82:   AppCtx         appctx;                 /* user-defined application context */
 83:   TS             ts;                     /* timestepping context */
 84:   Mat            A;                      /* matrix data structure */
 85:   Vec            u;                      /* approximate solution vector */
 86:   PetscReal      time_total_max = 100.0; /* default max total time */
 87:   PetscInt       time_steps_max = 100;   /* default max timesteps */
 88:   PetscDraw      draw;                   /* drawing context */
 89:   PetscInt       steps,m;
 90:   PetscMPIInt    size;
 91:   PetscReal      dt;
 92:   PetscBool      flg,flg_string;

 94:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 95:      Initialize program and set problem parameters
 96:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

102:   m    = 60;
103:   PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);
104:   PetscOptionsHasName(NULL,NULL,"-debug",&appctx.debug);
105:   flg_string = PETSC_FALSE;
106:   PetscOptionsGetBool(NULL,NULL,"-test_string_viewer",&flg_string,NULL);

108:   appctx.m        = m;
109:   appctx.h        = 1.0/(m-1.0);
110:   appctx.norm_2   = 0.0;
111:   appctx.norm_max = 0.0;

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

115:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
116:      Create vector data structures
117:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

119:   /*
120:      Create vector data structures for approximate and exact solutions
121:   */
122:   VecCreateSeq(PETSC_COMM_SELF,m,&u);
123:   VecDuplicate(u,&appctx.solution);

125:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
126:      Set up displays to show graphs of the solution and error
127:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

129:   PetscViewerDrawOpen(PETSC_COMM_SELF,0,"",80,380,400,160,&appctx.viewer1);
130:   PetscViewerDrawGetDraw(appctx.viewer1,0,&draw);
131:   PetscDrawSetDoubleBuffer(draw);
132:   PetscViewerDrawOpen(PETSC_COMM_SELF,0,"",80,0,400,160,&appctx.viewer2);
133:   PetscViewerDrawGetDraw(appctx.viewer2,0,&draw);
134:   PetscDrawSetDoubleBuffer(draw);

136:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
137:      Create timestepping solver context
138:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

140:   TSCreate(PETSC_COMM_SELF,&ts);
141:   TSSetProblemType(ts,TS_LINEAR);

143:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
144:      Set optional user-defined monitoring routine
145:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

147:   if (!flg_string) {
148:     TSMonitorSet(ts,Monitor,&appctx,NULL);
149:   }

151:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

153:      Create matrix data structure; set matrix evaluation routine.
154:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

156:   MatCreate(PETSC_COMM_SELF,&A);
157:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,m);
158:   MatSetFromOptions(A);
159:   MatSetUp(A);

161:   flg  = PETSC_FALSE;
162:   PetscOptionsGetBool(NULL,NULL,"-use_ifunc",&flg,NULL);
163:   if (!flg) {
164:     appctx.A = NULL;
165:     PetscOptionsGetBool(NULL,NULL,"-time_dependent_rhs",&flg,NULL);
166:     if (flg) {
167:       /*
168:          For linear problems with a time-dependent f(u,t) in the equation
169:          u_t = f(u,t), the user provides the discretized right-hand-side
170:          as a time-dependent matrix.
171:       */
172:       TSSetRHSFunction(ts,NULL,TSComputeRHSFunctionLinear,&appctx);
173:       TSSetRHSJacobian(ts,A,A,RHSMatrixHeat,&appctx);
174:     } else {
175:       /*
176:          For linear problems with a time-independent f(u) in the equation
177:          u_t = f(u), the user provides the discretized right-hand-side
178:          as a matrix only once, and then sets the special Jacobian evaluation
179:          routine TSComputeRHSJacobianConstant() which will NOT recompute the Jacobian.
180:       */
181:       RHSMatrixHeat(ts,0.0,u,A,A,&appctx);
182:       TSSetRHSFunction(ts,NULL,TSComputeRHSFunctionLinear,&appctx);
183:       TSSetRHSJacobian(ts,A,A,TSComputeRHSJacobianConstant,&appctx);
184:     }
185:   } else {
186:     Mat J;

188:     RHSMatrixHeat(ts,0.0,u,A,A,&appctx);
189:     MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&J);
190:     TSSetIFunction(ts,NULL,IFunctionHeat,&appctx);
191:     TSSetIJacobian(ts,J,J,IJacobianHeat,&appctx);
192:     MatDestroy(&J);

194:     PetscObjectReference((PetscObject)A);
195:     appctx.A = A;
196:     appctx.oshift = PETSC_MIN_REAL;
197:   }
198:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
199:      Set solution vector and initial timestep
200:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

202:   dt   = appctx.h*appctx.h/2.0;
203:   TSSetTimeStep(ts,dt);

205:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
206:      Customize timestepping solver:
207:        - Set the solution method to be the Backward Euler method.
208:        - Set timestepping duration info
209:      Then set runtime options, which can override these defaults.
210:      For example,
211:           -ts_max_steps <maxsteps> -ts_max_time <maxtime>
212:      to override the defaults set by TSSetMaxSteps()/TSSetMaxTime().
213:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

215:   TSSetMaxSteps(ts,time_steps_max);
216:   TSSetMaxTime(ts,time_total_max);
217:   TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);
218:   TSSetFromOptions(ts);

220:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
221:      Solve the problem
222:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

224:   /*
225:      Evaluate initial conditions
226:   */
227:   InitialConditions(u,&appctx);

229:   /*
230:      Run the timestepping solver
231:   */
232:   TSSolve(ts,u);
233:   TSGetStepNumber(ts,&steps);

235:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
236:      View timestepping solver info
237:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

239:   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));
240:   if (!flg_string) {
241:     TSView(ts,PETSC_VIEWER_STDOUT_SELF);
242:   } else {
243:     PetscViewer stringviewer;
244:     char        string[512];
245:     const char  *outstring;

247:     PetscViewerStringOpen(PETSC_COMM_WORLD,string,sizeof(string),&stringviewer);
248:     TSView(ts,stringviewer);
249:     PetscViewerStringGetStringRead(stringviewer,&outstring,NULL);
251:     PetscPrintf(PETSC_COMM_WORLD,"Output from string viewer:%s\n",outstring);
252:     PetscViewerDestroy(&stringviewer);
253:   }

255:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
256:      Free work space.  All PETSc objects should be destroyed when they
257:      are no longer needed.
258:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

260:   TSDestroy(&ts);
261:   MatDestroy(&A);
262:   VecDestroy(&u);
263:   PetscViewerDestroy(&appctx.viewer1);
264:   PetscViewerDestroy(&appctx.viewer2);
265:   VecDestroy(&appctx.solution);
266:   MatDestroy(&appctx.A);

268:   /*
269:      Always call PetscFinalize() before exiting a program.  This routine
270:        - finalizes the PETSc libraries as well as MPI
271:        - provides summary and diagnostic information if certain runtime
272:          options are chosen (e.g., -log_view).
273:   */
274:   PetscFinalize();
275:   return 0;
276: }
277: /* --------------------------------------------------------------------- */
278: /*
279:    InitialConditions - Computes the solution at the initial time.

281:    Input Parameter:
282:    u - uninitialized solution vector (global)
283:    appctx - user-defined application context

285:    Output Parameter:
286:    u - vector with solution at initial time (global)
287: */
288: PetscErrorCode InitialConditions(Vec u,AppCtx *appctx)
289: {
290:   PetscScalar    *u_localptr,h = appctx->h;
291:   PetscInt       i;

293:   /*
294:     Get a pointer to vector data.
295:     - For default PETSc vectors, VecGetArray() returns a pointer to
296:       the data array.  Otherwise, the routine is implementation dependent.
297:     - You MUST call VecRestoreArray() when you no longer need access to
298:       the array.
299:     - Note that the Fortran interface to VecGetArray() differs from the
300:       C version.  See the users manual for details.
301:   */
302:   VecGetArrayWrite(u,&u_localptr);

304:   /*
305:      We initialize the solution array by simply writing the solution
306:      directly into the array locations.  Alternatively, we could use
307:      VecSetValues() or VecSetValuesLocal().
308:   */
309:   for (i=0; i<appctx->m; i++) u_localptr[i] = PetscSinScalar(PETSC_PI*i*6.*h) + 3.*PetscSinScalar(PETSC_PI*i*2.*h);

311:   /*
312:      Restore vector
313:   */
314:   VecRestoreArrayWrite(u,&u_localptr);

316:   /*
317:      Print debugging information if desired
318:   */
319:   if (appctx->debug) {
320:     PetscPrintf(PETSC_COMM_WORLD,"Initial guess vector\n");
321:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
322:   }

324:   return 0;
325: }
326: /* --------------------------------------------------------------------- */
327: /*
328:    ExactSolution - Computes the exact solution at a given time.

330:    Input Parameters:
331:    t - current time
332:    solution - vector in which exact solution will be computed
333:    appctx - user-defined application context

335:    Output Parameter:
336:    solution - vector with the newly computed exact solution
337: */
338: PetscErrorCode ExactSolution(PetscReal t,Vec solution,AppCtx *appctx)
339: {
340:   PetscScalar    *s_localptr,h = appctx->h,ex1,ex2,sc1,sc2,tc = t;
341:   PetscInt       i;

343:   /*
344:      Get a pointer to vector data.
345:   */
346:   VecGetArrayWrite(solution,&s_localptr);

348:   /*
349:      Simply write the solution directly into the array locations.
350:      Alternatively, we culd use VecSetValues() or VecSetValuesLocal().
351:   */
352:   ex1 = PetscExpScalar(-36.*PETSC_PI*PETSC_PI*tc);
353:   ex2 = PetscExpScalar(-4.*PETSC_PI*PETSC_PI*tc);
354:   sc1 = PETSC_PI*6.*h;                 sc2 = PETSC_PI*2.*h;
355:   for (i=0; i<appctx->m; i++) s_localptr[i] = PetscSinScalar(sc1*(PetscReal)i)*ex1 + 3.*PetscSinScalar(sc2*(PetscReal)i)*ex2;

357:   /*
358:      Restore vector
359:   */
360:   VecRestoreArrayWrite(solution,&s_localptr);
361:   return 0;
362: }
363: /* --------------------------------------------------------------------- */
364: /*
365:    Monitor - User-provided routine to monitor the solution computed at
366:    each timestep.  This example plots the solution and computes the
367:    error in two different norms.

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

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

387:   /*
388:      View a graph of the current iterate
389:   */
390:   VecView(u,appctx->viewer2);

392:   /*
393:      Compute the exact solution
394:   */
395:   ExactSolution(time,appctx->solution,appctx);

397:   /*
398:      Print debugging information if desired
399:   */
400:   if (appctx->debug) {
401:     PetscPrintf(PETSC_COMM_SELF,"Computed solution vector\n");
402:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
403:     PetscPrintf(PETSC_COMM_SELF,"Exact solution vector\n");
404:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
405:   }

407:   /*
408:      Compute the 2-norm and max-norm of the error
409:   */
410:   VecAXPY(appctx->solution,-1.0,u);
411:   VecNorm(appctx->solution,NORM_2,&norm_2);
412:   norm_2 = PetscSqrtReal(appctx->h)*norm_2;
413:   VecNorm(appctx->solution,NORM_MAX,&norm_max);

415:   TSGetTimeStep(ts,&dt);
416:   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);

418:   appctx->norm_2   += norm_2;
419:   appctx->norm_max += norm_max;

421:   dttol = .0001;
422:   PetscOptionsGetReal(NULL,NULL,"-dttol",&dttol,NULL);
423:   if (dt < dttol) {
424:     dt  *= .999;
425:     TSSetTimeStep(ts,dt);
426:   }

428:   /*
429:      View a graph of the error
430:   */
431:   VecView(appctx->solution,appctx->viewer1);

433:   /*
434:      Print debugging information if desired
435:   */
436:   if (appctx->debug) {
437:     PetscPrintf(PETSC_COMM_SELF,"Error vector\n");
438:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
439:   }

441:   return 0;
442: }
443: /* --------------------------------------------------------------------- */
444: /*
445:    RHSMatrixHeat - User-provided routine to compute the right-hand-side
446:    matrix for the heat equation.

448:    Input Parameters:
449:    ts - the TS context
450:    t - current time
451:    global_in - global input vector
452:    dummy - optional user-defined context, as set by TSetRHSJacobian()

454:    Output Parameters:
455:    AA - Jacobian matrix
456:    BB - optionally different preconditioning matrix
457:    str - flag indicating matrix structure

459:    Notes:
460:    Recall that MatSetValues() uses 0-based row and column numbers
461:    in Fortran as well as in C.
462: */
463: PetscErrorCode RHSMatrixHeat(TS ts,PetscReal t,Vec X,Mat AA,Mat BB,void *ctx)
464: {
465:   Mat            A       = AA;                /* Jacobian matrix */
466:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */
467:   PetscInt       mstart  = 0;
468:   PetscInt       mend    = appctx->m;
469:   PetscInt       i,idx[3];
470:   PetscScalar    v[3],stwo = -2./(appctx->h*appctx->h),sone = -.5*stwo;

472:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
473:      Compute entries for the locally owned part of the matrix
474:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
475:   /*
476:      Set matrix rows corresponding to boundary data
477:   */

479:   mstart = 0;
480:   v[0]   = 1.0;
481:   MatSetValues(A,1,&mstart,1,&mstart,v,INSERT_VALUES);
482:   mstart++;

484:   mend--;
485:   v[0] = 1.0;
486:   MatSetValues(A,1,&mend,1,&mend,v,INSERT_VALUES);

488:   /*
489:      Set matrix rows corresponding to interior data.  We construct the
490:      matrix one row at a time.
491:   */
492:   v[0] = sone; v[1] = stwo; v[2] = sone;
493:   for (i=mstart; i<mend; i++) {
494:     idx[0] = i-1; idx[1] = i; idx[2] = i+1;
495:     MatSetValues(A,1,&i,3,idx,v,INSERT_VALUES);
496:   }

498:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
499:      Complete the matrix assembly process and set some options
500:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
501:   /*
502:      Assemble matrix, using the 2-step process:
503:        MatAssemblyBegin(), MatAssemblyEnd()
504:      Computations can be done while messages are in transition
505:      by placing code between these two statements.
506:   */
507:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
508:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

510:   /*
511:      Set and option to indicate that we will never add a new nonzero location
512:      to the matrix. If we do, it will generate an error.
513:   */
514:   MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);

516:   return 0;
517: }

519: PetscErrorCode IFunctionHeat(TS ts,PetscReal t,Vec X,Vec Xdot,Vec r,void *ctx)
520: {
521:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */

523:   MatMult(appctx->A,X,r);
524:   VecAYPX(r,-1.0,Xdot);
525:   return 0;
526: }

528: PetscErrorCode IJacobianHeat(TS ts,PetscReal t,Vec X,Vec Xdot,PetscReal s,Mat A,Mat B,void *ctx)
529: {
530:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */

532:   if (appctx->oshift == s) return 0;
533:   MatCopy(appctx->A,A,SAME_NONZERO_PATTERN);
534:   MatScale(A,-1);
535:   MatShift(A,s);
536:   MatCopy(A,B,SAME_NONZERO_PATTERN);
537:   appctx->oshift = s;
538:   return 0;
539: }

541: /*TEST

543:     test:
544:       args: -nox -ts_type ssp -ts_dt 0.0005

546:     test:
547:       suffix: 2
548:       args: -nox -ts_type ssp -ts_dt 0.0005 -time_dependent_rhs 1

550:     test:
551:       suffix: 3
552:       args:  -nox -ts_type rosw -ts_max_steps 3 -ksp_converged_reason
553:       filter: sed "s/ATOL/RTOL/g"
554:       requires: !single

556:     test:
557:       suffix: 4
558:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason
559:       filter: sed "s/ATOL/RTOL/g"

561:     test:
562:       suffix: 5
563:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason -time_dependent_rhs
564:       filter: sed "s/ATOL/RTOL/g"

566:     test:
567:       requires: !single
568:       suffix: pod_guess
569:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type pod -pc_type none -ksp_converged_reason

571:     test:
572:       requires: !single
573:       suffix: pod_guess_Ainner
574:       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

576:     test:
577:       requires: !single
578:       suffix: fischer_guess
579:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -pc_type none -ksp_converged_reason

581:     test:
582:       requires: !single
583:       suffix: fischer_guess_2
584:       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

586:     test:
587:       requires: !single
588:       suffix: fischer_guess_3
589:       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

591:     test:
592:       requires: !single
593:       suffix: stringview
594:       args: -nox -ts_type rosw -test_string_viewer

596:     test:
597:       requires: !single
598:       suffix: stringview_euler
599:       args: -nox -ts_type euler -test_string_viewer

601: TEST*/