Actual source code: ex3.c

petsc-3.11.2 2019-05-18
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  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/examples/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 */
 97:   PetscInt       steps,m;
 98:   PetscMPIInt    size;
 99:   PetscReal      dt;
100:   PetscBool      flg;

102:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
103:      Initialize program and set problem parameters
104:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

106:   PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
107:   MPI_Comm_size(PETSC_COMM_WORLD,&size);
108:   if (size != 1) SETERRQ(PETSC_COMM_SELF,1,"This is a uniprocessor example only!");

110:   m    = 60;
111:   PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);
112:   PetscOptionsHasName(NULL,NULL,"-debug",&appctx.debug);

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

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

121:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
122:      Create vector data structures
123:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

125:   /*
126:      Create vector data structures for approximate and exact solutions
127:   */
128:   VecCreateSeq(PETSC_COMM_SELF,m,&u);
129:   VecDuplicate(u,&appctx.solution);

131:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
132:      Set up displays to show graphs of the solution and error
133:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

142:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
143:      Create timestepping solver context
144:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

149:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
150:      Set optional user-defined monitoring routine
151:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

153:   TSMonitorSet(ts,Monitor,&appctx,NULL);

155:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

157:      Create matrix data structure; set matrix evaluation routine.
158:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

160:   MatCreate(PETSC_COMM_SELF,&A);
161:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,m);
162:   MatSetFromOptions(A);
163:   MatSetUp(A);

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

192:     RHSMatrixHeat(ts,0.0,u,A,A,&appctx);
193:     MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&J);
194:     TSSetIFunction(ts,NULL,IFunctionHeat,&appctx);
195:     TSSetIJacobian(ts,J,J,IJacobianHeat,&appctx);
196:     MatDestroy(&J);

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

206:   dt   = appctx.h*appctx.h/2.0;
207:   TSSetTimeStep(ts,dt);

209:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
210:      Customize timestepping solver:
211:        - Set the solution method to be the Backward Euler method.
212:        - Set timestepping duration info
213:      Then set runtime options, which can override these defaults.
214:      For example,
215:           -ts_max_steps <maxsteps> -ts_max_time <maxtime>
216:      to override the defaults set by TSSetMaxSteps()/TSSetMaxTime().
217:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

219:   TSSetMaxSteps(ts,time_steps_max);
220:   TSSetMaxTime(ts,time_total_max);
221:   TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);
222:   TSSetFromOptions(ts);

224:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
225:      Solve the problem
226:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

228:   /*
229:      Evaluate initial conditions
230:   */
231:   InitialConditions(u,&appctx);

233:   /*
234:      Run the timestepping solver
235:   */
236:   TSSolve(ts,u);
237:   TSGetStepNumber(ts,&steps);

239:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
240:      View timestepping solver info
241:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

243:   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));
244:   TSView(ts,PETSC_VIEWER_STDOUT_SELF);

246:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
247:      Free work space.  All PETSc objects should be destroyed when they
248:      are no longer needed.
249:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

251:   TSDestroy(&ts);
252:   MatDestroy(&A);
253:   VecDestroy(&u);
254:   PetscViewerDestroy(&appctx.viewer1);
255:   PetscViewerDestroy(&appctx.viewer2);
256:   VecDestroy(&appctx.solution);
257:   MatDestroy(&appctx.A);

259:   /*
260:      Always call PetscFinalize() before exiting a program.  This routine
261:        - finalizes the PETSc libraries as well as MPI
262:        - provides summary and diagnostic information if certain runtime
263:          options are chosen (e.g., -log_view).
264:   */
265:   PetscFinalize();
266:   return ierr;
267: }
268: /* --------------------------------------------------------------------- */
269: /*
270:    InitialConditions - Computes the solution at the initial time.

272:    Input Parameter:
273:    u - uninitialized solution vector (global)
274:    appctx - user-defined application context

276:    Output Parameter:
277:    u - vector with solution at initial time (global)
278: */
279: PetscErrorCode InitialConditions(Vec u,AppCtx *appctx)
280: {
281:   PetscScalar    *u_localptr,h = appctx->h;
283:   PetscInt       i;

285:   /*
286:     Get a pointer to vector data.
287:     - For default PETSc vectors, VecGetArray() returns a pointer to
288:       the data array.  Otherwise, the routine is implementation dependent.
289:     - You MUST call VecRestoreArray() when you no longer need access to
290:       the array.
291:     - Note that the Fortran interface to VecGetArray() differs from the
292:       C version.  See the users manual for details.
293:   */
294:   VecGetArray(u,&u_localptr);

296:   /*
297:      We initialize the solution array by simply writing the solution
298:      directly into the array locations.  Alternatively, we could use
299:      VecSetValues() or VecSetValuesLocal().
300:   */
301:   for (i=0; i<appctx->m; i++) u_localptr[i] = PetscSinScalar(PETSC_PI*i*6.*h) + 3.*PetscSinScalar(PETSC_PI*i*2.*h);

303:   /*
304:      Restore vector
305:   */
306:   VecRestoreArray(u,&u_localptr);

308:   /*
309:      Print debugging information if desired
310:   */
311:   if (appctx->debug) {
312:     PetscPrintf(PETSC_COMM_WORLD,"Initial guess vector\n");
313:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
314:   }

316:   return 0;
317: }
318: /* --------------------------------------------------------------------- */
319: /*
320:    ExactSolution - Computes the exact solution at a given time.

322:    Input Parameters:
323:    t - current time
324:    solution - vector in which exact solution will be computed
325:    appctx - user-defined application context

327:    Output Parameter:
328:    solution - vector with the newly computed exact solution
329: */
330: PetscErrorCode ExactSolution(PetscReal t,Vec solution,AppCtx *appctx)
331: {
332:   PetscScalar    *s_localptr,h = appctx->h,ex1,ex2,sc1,sc2,tc = t;
334:   PetscInt       i;

336:   /*
337:      Get a pointer to vector data.
338:   */
339:   VecGetArray(solution,&s_localptr);

341:   /*
342:      Simply write the solution directly into the array locations.
343:      Alternatively, we culd use VecSetValues() or VecSetValuesLocal().
344:   */
345:   ex1 = PetscExpScalar(-36.*PETSC_PI*PETSC_PI*tc);
346:   ex2 = PetscExpScalar(-4.*PETSC_PI*PETSC_PI*tc);
347:   sc1 = PETSC_PI*6.*h;                 sc2 = PETSC_PI*2.*h;
348:   for (i=0; i<appctx->m; i++) s_localptr[i] = PetscSinScalar(sc1*(PetscReal)i)*ex1 + 3.*PetscSinScalar(sc2*(PetscReal)i)*ex2;

350:   /*
351:      Restore vector
352:   */
353:   VecRestoreArray(solution,&s_localptr);
354:   return 0;
355: }
356: /* --------------------------------------------------------------------- */
357: /*
358:    Monitor - User-provided routine to monitor the solution computed at
359:    each timestep.  This example plots the solution and computes the
360:    error in two different norms.

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

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

381:   /*
382:      View a graph of the current iterate
383:   */
384:   VecView(u,appctx->viewer2);

386:   /*
387:      Compute the exact solution
388:   */
389:   ExactSolution(time,appctx->solution,appctx);

391:   /*
392:      Print debugging information if desired
393:   */
394:   if (appctx->debug) {
395:     PetscPrintf(PETSC_COMM_SELF,"Computed solution vector\n");
396:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
397:     PetscPrintf(PETSC_COMM_SELF,"Exact solution vector\n");
398:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
399:   }

401:   /*
402:      Compute the 2-norm and max-norm of the error
403:   */
404:   VecAXPY(appctx->solution,-1.0,u);
405:   VecNorm(appctx->solution,NORM_2,&norm_2);
406:   norm_2 = PetscSqrtReal(appctx->h)*norm_2;
407:   VecNorm(appctx->solution,NORM_MAX,&norm_max);
408:   if (norm_2   < 1e-14) norm_2   = 0;
409:   if (norm_max < 1e-14) norm_max = 0;

411:   TSGetTimeStep(ts,&dt);
412:   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);

414:   appctx->norm_2   += norm_2;
415:   appctx->norm_max += norm_max;

417:   dttol = .0001;
418:   PetscOptionsGetReal(NULL,NULL,"-dttol",&dttol,NULL);
419:   if (dt < dttol) {
420:     dt  *= .999;
421:     TSSetTimeStep(ts,dt);
422:   }

424:   /*
425:      View a graph of the error
426:   */
427:   VecView(appctx->solution,appctx->viewer1);

429:   /*
430:      Print debugging information if desired
431:   */
432:   if (appctx->debug) {
433:     PetscPrintf(PETSC_COMM_SELF,"Error vector\n");
434:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
435:   }

437:   return 0;
438: }
439: /* --------------------------------------------------------------------- */
440: /*
441:    RHSMatrixHeat - User-provided routine to compute the right-hand-side
442:    matrix for the heat equation.

444:    Input Parameters:
445:    ts - the TS context
446:    t - current time
447:    global_in - global input vector
448:    dummy - optional user-defined context, as set by TSetRHSJacobian()

450:    Output Parameters:
451:    AA - Jacobian matrix
452:    BB - optionally different preconditioning matrix
453:    str - flag indicating matrix structure

455:    Notes:
456:    Recall that MatSetValues() uses 0-based row and column numbers
457:    in Fortran as well as in C.
458: */
459: PetscErrorCode RHSMatrixHeat(TS ts,PetscReal t,Vec X,Mat AA,Mat BB,void *ctx)
460: {
461:   Mat            A       = AA;                /* Jacobian matrix */
462:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */
463:   PetscInt       mstart  = 0;
464:   PetscInt       mend    = appctx->m;
466:   PetscInt       i,idx[3];
467:   PetscScalar    v[3],stwo = -2./(appctx->h*appctx->h),sone = -.5*stwo;

469:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
470:      Compute entries for the locally owned part of the matrix
471:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
472:   /*
473:      Set matrix rows corresponding to boundary data
474:   */

476:   mstart = 0;
477:   v[0]   = 1.0;
478:   MatSetValues(A,1,&mstart,1,&mstart,v,INSERT_VALUES);
479:   mstart++;

481:   mend--;
482:   v[0] = 1.0;
483:   MatSetValues(A,1,&mend,1,&mend,v,INSERT_VALUES);

485:   /*
486:      Set matrix rows corresponding to interior data.  We construct the
487:      matrix one row at a time.
488:   */
489:   v[0] = sone; v[1] = stwo; v[2] = sone;
490:   for (i=mstart; i<mend; i++) {
491:     idx[0] = i-1; idx[1] = i; idx[2] = i+1;
492:     MatSetValues(A,1,&i,3,idx,v,INSERT_VALUES);
493:   }

495:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
496:      Complete the matrix assembly process and set some options
497:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
498:   /*
499:      Assemble matrix, using the 2-step process:
500:        MatAssemblyBegin(), MatAssemblyEnd()
501:      Computations can be done while messages are in transition
502:      by placing code between these two statements.
503:   */
504:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
505:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

507:   /*
508:      Set and option to indicate that we will never add a new nonzero location
509:      to the matrix. If we do, it will generate an error.
510:   */
511:   MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);

513:   return 0;
514: }

516: PetscErrorCode IFunctionHeat(TS ts,PetscReal t,Vec X,Vec Xdot,Vec r,void *ctx)
517: {
518:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */

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

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

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

540: /*TEST

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

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

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

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

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

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

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

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

580:     test:
581:       requires: !single
582:       suffix: fischer_guess_2
583:       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
584: TEST*/