Actual source code: ex3.c

petsc-master 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,flg_string;

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);
113:   flg_string = PETSC_FALSE;
114:   PetscOptionsGetBool(NULL,NULL,"-test_string_viewer",&flg_string,NULL);

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

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

123:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
124:      Create vector data structures
125:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

133:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
134:      Set up displays to show graphs of the solution and error
135:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

144:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
145:      Create timestepping solver context
146:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

151:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
152:      Set optional user-defined monitoring routine
153:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

155:   if (!flg_string) {
156:     TSMonitorSet(ts,Monitor,&appctx,NULL);
157:   }

159:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

161:      Create matrix data structure; set matrix evaluation routine.
162:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

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

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

202:     PetscObjectReference((PetscObject)A);
203:     appctx.A = A;
204:     appctx.oshift = PETSC_MIN_REAL;
205:   }
206:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
207:      Set solution vector and initial timestep
208:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

213:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
214:      Customize timestepping solver:
215:        - Set the solution method to be the Backward Euler method.
216:        - Set timestepping duration info
217:      Then set runtime options, which can override these defaults.
218:      For example,
219:           -ts_max_steps <maxsteps> -ts_max_time <maxtime>
220:      to override the defaults set by TSSetMaxSteps()/TSSetMaxTime().
221:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

228:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
229:      Solve the problem
230:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

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

243:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
244:      View timestepping solver info
245:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

247:   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));
248:   if (!flg_string) {
249:     TSView(ts,PETSC_VIEWER_STDOUT_SELF);
250:   } else {
251:     PetscViewer stringviewer;
252:     char        string[512];
253:     const char  *outstring;

255:     PetscViewerStringOpen(PETSC_COMM_WORLD,string,sizeof(string),&stringviewer);
256:     TSView(ts,stringviewer);
257:     PetscViewerStringGetStringRead(stringviewer,&outstring,NULL);
258:     if ((char*)outstring != (char*)string) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_PLIB,"String returned from viewer does not equal original string");
259:     PetscPrintf(PETSC_COMM_WORLD,"Output from string viewer:%s\n",outstring);
260:     PetscViewerDestroy(&stringviewer);
261:   }

263:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
264:      Free work space.  All PETSc objects should be destroyed when they
265:      are no longer needed.
266:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

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

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

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

302:   /*
303:     Get a pointer to vector data.
304:     - For default PETSc vectors, VecGetArray() returns a pointer to
305:       the data array.  Otherwise, the routine is implementation dependent.
306:     - You MUST call VecRestoreArray() when you no longer need access to
307:       the array.
308:     - Note that the Fortran interface to VecGetArray() differs from the
309:       C version.  See the users manual for details.
310:   */
311:   VecGetArray(u,&u_localptr);

313:   /*
314:      We initialize the solution array by simply writing the solution
315:      directly into the array locations.  Alternatively, we could use
316:      VecSetValues() or VecSetValuesLocal().
317:   */
318:   for (i=0; i<appctx->m; i++) u_localptr[i] = PetscSinScalar(PETSC_PI*i*6.*h) + 3.*PetscSinScalar(PETSC_PI*i*2.*h);

320:   /*
321:      Restore vector
322:   */
323:   VecRestoreArray(u,&u_localptr);

325:   /*
326:      Print debugging information if desired
327:   */
328:   if (appctx->debug) {
329:     PetscPrintf(PETSC_COMM_WORLD,"Initial guess vector\n");
330:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
331:   }

333:   return 0;
334: }
335: /* --------------------------------------------------------------------- */
336: /*
337:    ExactSolution - Computes the exact solution at a given time.

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

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

353:   /*
354:      Get a pointer to vector data.
355:   */
356:   VecGetArray(solution,&s_localptr);

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

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

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

381:    Input Parameters:
382:    ts     - the timestep context
383:    step   - the count of the current step (with 0 meaning the
384:              initial condition)
385:    time   - the current time
386:    u      - the solution at this timestep
387:    ctx    - the user-provided context for this monitoring routine.
388:             In this case we use the application context which contains
389:             information about the problem size, workspace and the exact
390:             solution.
391: */
392: PetscErrorCode Monitor(TS ts,PetscInt step,PetscReal time,Vec u,void *ctx)
393: {
394:   AppCtx         *appctx = (AppCtx*) ctx;   /* user-defined application context */
396:   PetscReal      norm_2,norm_max,dt,dttol;

398:   /*
399:      View a graph of the current iterate
400:   */
401:   VecView(u,appctx->viewer2);

403:   /*
404:      Compute the exact solution
405:   */
406:   ExactSolution(time,appctx->solution,appctx);

408:   /*
409:      Print debugging information if desired
410:   */
411:   if (appctx->debug) {
412:     PetscPrintf(PETSC_COMM_SELF,"Computed solution vector\n");
413:     VecView(u,PETSC_VIEWER_STDOUT_SELF);
414:     PetscPrintf(PETSC_COMM_SELF,"Exact solution vector\n");
415:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
416:   }

418:   /*
419:      Compute the 2-norm and max-norm of the error
420:   */
421:   VecAXPY(appctx->solution,-1.0,u);
422:   VecNorm(appctx->solution,NORM_2,&norm_2);
423:   norm_2 = PetscSqrtReal(appctx->h)*norm_2;
424:   VecNorm(appctx->solution,NORM_MAX,&norm_max);
425:   if (norm_2   < 1e-14) norm_2   = 0;
426:   if (norm_max < 1e-14) norm_max = 0;

428:   TSGetTimeStep(ts,&dt);
429:   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);

431:   appctx->norm_2   += norm_2;
432:   appctx->norm_max += norm_max;

434:   dttol = .0001;
435:   PetscOptionsGetReal(NULL,NULL,"-dttol",&dttol,NULL);
436:   if (dt < dttol) {
437:     dt  *= .999;
438:     TSSetTimeStep(ts,dt);
439:   }

441:   /*
442:      View a graph of the error
443:   */
444:   VecView(appctx->solution,appctx->viewer1);

446:   /*
447:      Print debugging information if desired
448:   */
449:   if (appctx->debug) {
450:     PetscPrintf(PETSC_COMM_SELF,"Error vector\n");
451:     VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);
452:   }

454:   return 0;
455: }
456: /* --------------------------------------------------------------------- */
457: /*
458:    RHSMatrixHeat - User-provided routine to compute the right-hand-side
459:    matrix for the heat equation.

461:    Input Parameters:
462:    ts - the TS context
463:    t - current time
464:    global_in - global input vector
465:    dummy - optional user-defined context, as set by TSetRHSJacobian()

467:    Output Parameters:
468:    AA - Jacobian matrix
469:    BB - optionally different preconditioning matrix
470:    str - flag indicating matrix structure

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

486:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
487:      Compute entries for the locally owned part of the matrix
488:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
489:   /*
490:      Set matrix rows corresponding to boundary data
491:   */

493:   mstart = 0;
494:   v[0]   = 1.0;
495:   MatSetValues(A,1,&mstart,1,&mstart,v,INSERT_VALUES);
496:   mstart++;

498:   mend--;
499:   v[0] = 1.0;
500:   MatSetValues(A,1,&mend,1,&mend,v,INSERT_VALUES);

502:   /*
503:      Set matrix rows corresponding to interior data.  We construct the
504:      matrix one row at a time.
505:   */
506:   v[0] = sone; v[1] = stwo; v[2] = sone;
507:   for (i=mstart; i<mend; i++) {
508:     idx[0] = i-1; idx[1] = i; idx[2] = i+1;
509:     MatSetValues(A,1,&i,3,idx,v,INSERT_VALUES);
510:   }

512:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
513:      Complete the matrix assembly process and set some options
514:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
515:   /*
516:      Assemble matrix, using the 2-step process:
517:        MatAssemblyBegin(), MatAssemblyEnd()
518:      Computations can be done while messages are in transition
519:      by placing code between these two statements.
520:   */
521:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
522:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

524:   /*
525:      Set and option to indicate that we will never add a new nonzero location
526:      to the matrix. If we do, it will generate an error.
527:   */
528:   MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);

530:   return 0;
531: }

533: PetscErrorCode IFunctionHeat(TS ts,PetscReal t,Vec X,Vec Xdot,Vec r,void *ctx)
534: {
535:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */

538:   MatMult(appctx->A,X,r);
539:   VecAYPX(r,-1.0,Xdot);
540:   return 0;
541: }

543: PetscErrorCode IJacobianHeat(TS ts,PetscReal t,Vec X,Vec Xdot,PetscReal s,Mat A,Mat B,void *ctx)
544: {
545:   AppCtx         *appctx = (AppCtx*)ctx;     /* user-defined application context */

548:   if (appctx->oshift == s) return 0;
549:   MatCopy(appctx->A,A,SAME_NONZERO_PATTERN);
550:   MatScale(A,-1);
551:   MatShift(A,s);
552:   MatCopy(A,B,SAME_NONZERO_PATTERN);
553:   appctx->oshift = s;
554:   return 0;
555: }

557: /*TEST

559:     test:
560:       args: -nox -ts_type ssp -ts_dt 0.0005

562:     test:
563:       suffix: 2
564:       args: -nox -ts_type ssp -ts_dt 0.0005 -time_dependent_rhs 1

566:     test:
567:       suffix: 3
568:       args:  -nox -ts_type rosw -ts_max_steps 3 -ksp_converged_reason
569:       filter: sed "s/ATOL/RTOL/g"
570:       requires: !single

572:     test:
573:       suffix: 4
574:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason
575:       filter: sed "s/ATOL/RTOL/g"

577:     test:
578:       suffix: 5
579:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason -time_dependent_rhs
580:       filter: sed "s/ATOL/RTOL/g"

582:     test:
583:       requires: !single
584:       suffix: pod_guess
585:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type pod -pc_type none -ksp_converged_reason

587:     test:
588:       requires: !single
589:       suffix: pod_guess_Ainner
590:       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

592:     test:
593:       requires: !single
594:       suffix: fischer_guess
595:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -pc_type none -ksp_converged_reason

597:     test:
598:       requires: !single
599:       suffix: fischer_guess_2
600:       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

602:     test:
603:       requires: !single
604:       suffix: stringview
605:       args: -nox -ts_type rosw -test_string_viewer

607:     test:
608:       requires: !single
609:       suffix: stringview_euler
610:       args: -nox -ts_type euler -test_string_viewer

612: TEST*/